Enveloped viruses represent a significant category of pathogens that cause serious diseases in animals. These viruses express envelope glycoproteins that are singularly important during infection of host cells by mediating fusion between the viral envelope and host cell membranes. Despite low homology at protein levels, three classes of viral fusion proteins have, as of yet, been identified based on structural similarities. Their incorporation into viral particles is dependent upon their proper sub-cellular localization after being expressed and folded properly in the endoplasmic reticulum (ER). However, viral protein expression can cause stress in the ER, and host cells respond to alleviate the ER stress in the form of the unfolded protein response (UPR); the effects of which have been observed potentiating or inhibiting viral infection. One important arm of UPR is to elevate the capacity of the ER-associated protein degradation (ERAD) pathway, which is comprised of host quality control machinery that ensures proper protein folding. In this review, we provide relevant details regarding viral envelope glycoproteins, UPR, ERAD, and their interactions in host cells.

Background: Leishmaniasis is a significant global public health issue that is caused by parasites from Leishmania genus. With limited treatment options and rising drug resistance, there is a pressing need for new therapeutic approaches. Molecular chaperones, particularly Hsp90, play a crucial role in parasite biology and are emerging as promising targets for drug development. Objective: This study evaluates the efficacy of 17-DMAG in treating BALB/c mice from cutane-ous leishmaniasis through in vitro and in vivo approaches. Materials and Methods: We assessed 17-DMAG cytotoxic effect on bone marrow-derived mac-rophages (BMMΦ) and its effects against L. braziliensis promastigotes and intracellular amastigotes. Additionally, we tested the compound's efficacy in BALB/c mice infected with L. braziliensis via intraperitoneal administration to evaluate the reduction of lesion size and de-crease of parasite load in the ears and lymph nodes of infected animals. Results: 17-DMAG showed selective toxicity [selective index=432) towards Leishmania amastigotes, causing minimal damage to host cells. The treatment significantly reduced lesion sizes in mice and results in parasite clearance from ears and lymph nodes. It also diminished in-flammatory responses and reduced the release of pro-inflammatory cytokines (IL-6, IFN-g, TNF) and the regulatory cytokine, IL-10, underscoring its dual leishmanicidal and anti-inflammatory properties. Conclusion: Our findings confirm the potential of 17-DMAG as a viable treatment for cutaneous leishmaniasis and support further research into its mechanisms and potential applications against other infectious diseases.

Ocean exploration is crucial for utilizing its extensive resources. Images captured by underwater robots suffer from issues such as color distortion and reduced contrast. To address the issue, we propose an innovative enhancement algorithm that integrates Transformer and Convolutional Neural Network (CNN) in a parallel fusion manner. Firstly, a novel transformer model is intro-duced to capture local features, employing peak-signal-to-noise ratio (PSNR) attention and linear operations. Subsequently, to extract global features, both temporal and frequency domain features are incorporated to construct convolutional neural network. Finally, the Fourier’s high and low-frequency information of the original image are utilized to fuse different features. To demon-strate the algorithm's effectiveness, underwater images with various levels of color distortion are selected for both qualitative and quantitative analyses. The experimental results demonstrate that our approach surpasses other mainstream methods, achieving superior PSNR and structural sim-ilarity index measure (SSIM) metrics and leading to a detection performance improvement of over ten percent.

Combating viral disease outbreaks has doubtlessly been one of the major public health challenges for the 21^st century. Here, the host entry machinery required for COVID-19 (SARS-CoV-2) infection was examined for the gene expression profiles and polymorphism. The four human population groups of Europeans, Africans, Asians, and Americans had specific and also a shared pool of variants for the X-linked locus of ACE2 receptor. Several specific and common ACE2 variants were of the utmost importance to the viral entry and infection. In the absence of gender bias for the gene expression profiles, the hemizygous rare variants of ACE2 describe the observed higher mortality rate in males. Finally, a personalized medicine strategy is conceived for isolating high-risk individuals in epidemic circumstances.

Using numerical simulation method, combined with the pre-branch material characteristics of the measurement results, based on the LS-DYNA software to simulate the branch crushing process, the analysis found that not only the existence of the cutter cutting in the branch destruction process, there is also the cutting of the opposing surface of the bending fracture, with the increase in the speed of the knife rollers, the cutter cutting resistance increases, the cutting resistance reaches 2690 N when the cutter at 2500 r/min, the cutter cutting resistance is the smallest in the cutting simulation at the blade angle of 55°, the blade angle is more suitable for the cutting of the branch. In the cutting simulation under different cutting edge angles, the cutting resistance of the tool is the smallest when the edge angle is 55°, which is 1860 N. This edge angle is more suitable for branch crushing and cutting. Using Fluent software to analyse the airflow characteristics of the crushing device, it was found that with the increase of the knife roller speed, the inlet flow and negative pressure of the crushing chamber are increasing, the speed of 2500 r/min, the inlet flow and negative pressure were 1.92 kg/s and 37.16 Pa, which will be conducive to the feeding of branches, but the speed is too high and it will also lead to the enhancement of the vortex of part of the area in the crushing device, which will affect the feeding of branches and the throwing of the crushed material. affect the feeding of branches and the throwing out of crushed materials, and finally determined the speed range of the crushing knife roller is 1800 ~ 2220 r/min. Based on ANSYS/Model module modal analysis of the crushing knife roller, the knife roller of the first six orders of the intrinsic frequency and vibration pattern, crushing knife roller of the lowest order of the modal intrinsic frequency of 137.42 Hz, much larger than the crushing knife roller operating frequency of 37 Hz, the machine will not resonate during operation.

Clostridioides difficile is a Gram-positive pathogen known for its toxin production and spore formation. It is primarily responsible for most cases of antibiotic-associated diarrhea. Bacterial persisters are a small subset of the population that exhibits transient tolerance to bactericidal substances, and they are of significant medical concern due to their association with the emergence of antibiotic resistance and difficult-to-treat chronic or recurrent infections. Vancomycin, the predominant antibiotic utilized in the management of C. difficile infection, is extensively applied in the realm of clinical practice. Previous studies have demonstrated a persister-like phenotype with treatments involving this antibiotic. However, the mechanism in C. difficile remains largely unknown, primarily due to the challenge of isolating this small population at any given time. To better characterize C. difficile persister cells, we present a study that enables the enrichment and characterization of persister cells from bacterial cultures in both exponential and stationary phases. Moreover, we could differentiate between triggered (induced by antibiotics, such as vancomycin) and spontaneous (stochastic) persister cells. Additionally, we observed the involvement of toxin-antitoxin systems and Clp proteases in persister cell formation.

Worldwide, different strategies are elaborated in order to ensure optimum conditions for the development and growth of the economic competitiveness, but also for increasing the quality of life and environment protection. All these strategies are closely linked with the development and modernization of the systems for producing energy from clean and renewable sources. In this context, the present paper presents the results of the researches regarding the evaluation of the sustainability of the briquettes production, using the biomass resulted from vine winter pruning as raw material. An analysis of the scientific references indicates that nearly 8 Mt of biomass result from over 7.4 million hectares of vine plantations existent worldwide, biomass that could be valorized through densification in order to produce solid biofuels with a lower calorific value of more than 17 MJ·kg-1. When designing the scientific endeavor, the following aspects were considered: defining the aim and objectives of the research; design of the research algorithm; collection, preparation and conditioning of the biomass; chemical analysis of the briquettes; evaluation of the technological characteristics of the briquettes; evaluation of the energy consumption and energy efficiency for producing the briquettes, taking into account two drying methods (natural and artificial drying). In the meantime, some specific laboratory equipment was design and built for the artificial drying of biomass, evaluation of the mechanical durability, measurement of the energy consumption etc. The analysis of the experimental data has led to the conclusion that the agricultural waste from vine pruning can constitute an important and sustainable source of energy in the form of bri-quettes, which fulfill most of the requirements imposed by the international standards.

There is an urgent need to identify effective therapies for COVID-19 given that a broadly available and effective vaccine is likely at least one year away. Here, we identify compounds that transcriptionally inhibit host proteins required for SARS-CoV-2 entry and should be evaluated for efficacy in SARS-CoV-2 viral infection assays. Recognizing the need for immediately available treatment options, we focused particular attention on FDA-approved drugs that could be immediately repurposed to treat COVID-19 patients. By mining publicly available gene expression data, we identify several compounds that down-regulate TMPRSS2, a protein required for SARS-CoV-2 entry that has emerged as a promising therapeutic target. Among these, we find twenty independent studies that implicate estrogen-related and androgen-related compounds as transcriptional modulators of TMPRSS2 expression, suggesting that these drugs and others acting on the pathway may be promising therapeutic candidates for COVID-19 for further testing. It is also noteworthy that TMPRSS2 has highly variable and skewed expression in humans, spanning two orders of magnitude with a small minority of individuals having extremely high expression. Combined with literature showing that TMPRSS2 loss-of-function in mouse is protective against SARS while anti-estrogen treatment predicted to increase TMPRSS2 expression exacerbates SARS, this observation raises the hypothesis that TMPRSS2 expression may positively correlate with severity in COVID-19.

Cystatin F (CstF) is a protease inhibitor of cysteine cathepsins, including those involved in acti-vating the perforin/granzyme cytotoxic pathways. It is targeted to the endolysosomal pathway but can also be secreted to the extracellular milieu or endocytosed by bystander cells. CtsF was shown to be significantly increased in tuberculous pleurisy, and during HIV coinfection, pleural fluids display high viral loads. In human macrophages, we revealed a strong upregulation of CstF during infection with Mycobacterium tuberculosis (Mtb). CstF manipulation using RNA si-lencing led to increased proteolytic activity of lysosomal cathepsins, improving Mtb intracellular killing. Here, we investigate the impact of CstF depletion during coinfection of Mtb-infected mac-rophages with lymphocytes infected with HIV. Our results indicate that decreasing CstF released by phagocytes impacts the major pro-granzyme convertase cathepsin C of cytotoxic immune cells. Consequently, an observed increase of the granzyme B apoptotic effects leads to a significant re-duction in viral replication in HIV-infected lymphocytes. Overall, our results indicate a mecha-nism of Mtb/HIV evasion of the cytotoxic mediated pathogen killing driven by the ax-is CstF/ catC/granzymes contributing to this syndemic interaction. Ultimately, this knowledge can be crucial for developing new therapeutic approaches to control both pathogens based on manipulating CstF.

Since the spread of the deadly virus SARS-CoV2 in late 2019, researchers have restlessly been seeking for unraveling how the virus factually enters the host cells. Some proteins on each side of the interaction between the virus and the host cells are involved as the major contributors to this process: 1- the nano-machine Spike protein on behalf of the virus, 2- angiotensin converting enzyme II, the mono-carboxypeptidase and the key component of renin angiotensin system on behalf of the host cell, 3- some host proteases and proteins exploited by SARS-CoV2, In this review, the complex process of SARS-CoV2 entrance into the host cells with the contribution of the involved host proteins as well as the sequential conformational changes in the Spike protein tending to increase the probability of complexification of the latter with angiotensin converting enzyme II, the receptor of the virus on the host cells, are discussed. Besides, the release of the catalytic ectodomain of angiotensin converting enzyme II as its soluble form in the extracellular space and its positive or negative impact on the infectivity of the virus are considered.

A novel composite consisting of fluorine-doped carbon and graphene double-coated LiMn0.6Fe0.4PO4 (LMFP) nanorods, synthesized via a facile low temperature solvothermal method that employs a hybrid glucose and polyvinylidene fluoride as carbon and fluorine sources. As revealed by physicochemical characterization, F-doped carbon coating and graphene form a ‘point-to-surface’ conductive network, facilitating rapid electron transport and mitigating electrochemical polarization. Furthermore, the uniform thickness of the F-doped carbon coating alters the growth of nanoparticles and prevents direct contact between the material and the electrolyte, thereby enhancing structural stability. Strong electronegative F− is beneficial to inhibit the structural changes of LMFP caused by Li-insertion/extraction during charge/discharge, which effectively reduces the Jahn-Teller effect, and inhibits Mn dissolution. The distinctive architecture of LMFP/C-F/G cathode material exhibits excellent electrochemical properties, exhibiting an initial discharge capacity of 163.1 mAh g−1 at 0.1 C and a constant Coulombic efficiency of 99.7% over 100 cycles. Notably, LMFP/C-F/G cathode material achieves an impressive energy density of 607.6 Wh kg−1 , surpassing that of commercial counterparts. Moreover, it delivers a reversible capacity of 90.3 mAh g−1 at a high current rate of 5 C. The high-capacity capability and energy density of the prepared materials give them great potential for use in next-generation lithium-ion batteries.

Aiming at the problems of high cost of manual pulling, low reliability of existing pulling devices, high breaking rate and high leakage rate in the process of cotton stalk reuse after leaving the field in Xinjiang cotton area, a loosening soil and root-cutting cotton stalk pulling the setting machine has been researched and designed, established the root-cutting force model, calculated and optimized the key parameters of the V-shaped root-cutting knife, and determined the range of slide cutting angle, cutting edge angle and soil entry angle. The shoveling process simulation of V-shaped root-cutting knife and root-soil complex was constructed, and the working mechanism of V-shaped root-cutting knife was clarified. In order to verify the reliability and operation performance of the V-shaped root-cutting knife, the slide cutting angle, cutting edge angle and soil entry angle were used as the test factors, the response surface test of three-factors and three-levels was carried out with root-breaking force and mean value of the cutting resistance as the test index. The test results were analyzed by variance analysis, the significant of influencing factors on the root-breaking force are in a descending order as: slide cutting angle, cutting edge angle, soil entry angle; the degree of influence on the mean value of the cutting resistance are as follows: slide cutting angle, soil entry angle, cutting edge angle. In order to make the V-shaped root-cutting knife achieve the optimal working state, the parameters of the test index were optimized, and the optimal design parameters of the V-shaped root-cutting knife were set as follows: the slide cutting angle was 48.3°, cutting edge angle was 43.4°, and soil entry angle was 26.2°. The field uprooting test showed that the average pass rate of root breakage was 94.8% and the average pull-out rate of the cotton stalk was 93.2%. This study provides theoretical guidance for the development of root breaking mechanism of cotton straw harvester.

With the increasing concern of environment, the energy-efficiency scheduling of manufacturing industry is becoming urgent and popular. In turning processes, both spindle speed and processing time can affect the final energy consumption and thus the spindle speed and scheduling scheme need to be optimized simultaneously. Since the turning workshop can be regarded as the flexible flow shop, this paper formulates a mixed integer linear programming model for energy-efficient scheduling of flexible flow shop. Accordingly, a new decoding method is developed by considering of the optimization of spindle speed and scheduling scheme simultaneously, and an estimation of distribution algorithm adopting the new decoding method is proposed to solve large-size problems. The parameters of this algorithm are determined by statistical technique with a simplified practical case. In order to validate the proposed method, a case from practical factories is studied, in which the makespan can be shortened by 25.22%, and the consumed energy can be saved by 5.48%. These results demonstrate the effectiveness of the proposed mathematical model and algorithm.

The hump feature is one of the major instabilities in pump-turbines. When pump-turbines operate in the hump region, strong noise and serious fluctuations can be observed, which are harmful to their safe and stable operation and can even destroy the whole unit as well as water conveyance system. In this paper, a low specific speed (n_q = 36.1 min⁻¹) pump-turbine model was experimentally investigated. Firstly, the hump characteristic was obtained under 19 mm guide vane opening conditions. More interestingly, when the hump characteristic was measured in two directions (increasing and decreasing the discharge), characteristic hysteresis was found in the hump region. The analysis of performance characteristics reveals that the hump instability is the result of Euler momentum and hydraulic losses, and different Euler momentum and hydraulic losses in the two development processes lead to the hysteresis phenomenon. Then, 12 pressure sensors were mounted in the different parts of the pump-turbine model to obtain the time and frequency characteristics. The analysis of the corresponding fast Fourier transform confirms that the hump characteristic is related to low-frequency (0.04–0.15 times rotational frequency) vortices. The occurrence and cessation of vortices depend on the operating condition and measurement direction, which contribute to the hysteresis feature. Finally, the type of the low-frequency vortices was analyzed through the cross power spectrum.

The paper provides and comments on the results of studies of the effect of sandstone-based abrasives and quartz sand alone on the wear of martensitic surfaces of wear-resistant steels. The wear process was examined on a ring-on-ring test rig seeking to determine the mass decrement parameter which characterised wear. The tests were conducted for three sandstone varieties: Carboniferous, Permian, and Cretaceous, and they made it possible to determine that the most intense process of deterioration of wear-resistant steels took place in the presence of quartz sand grain, while less intense wear was observed in the case of sandstone-based abrasives. The mass decrement values established in the presence of the sandstones in question did not differ significantly between individual sandstone varieties. Based on a surface damage analysis, the basic damage mechanism was found to be micro-scratching, however, with regard to the sandstones examined, it was also determined that individual grains could be pressed into surface irregularities, as well as that films of soft hematite cement developed in the Permian sandstone and that inclusions of carbonaceous matter were formed in the Carboniferous sandstone. With reference to the wear process observations, a wear model was described for the surface of the steels examined in the presence of sandstone-based abrasives.

As marine traffic is contributing to pollution and mostly have predictable route with repetitive load profiles, to reduce their impact on environment, hybrid system with proton exchange membrane fuel cells (PEMFC-s) and battery pack, is promising replacement. For this purpose, the numerical model of repowered existing vessel that have two diesel engines with 300 kWe is developed. The goal of this paper is to develop numerical model which analyzes and determine equivalent hybrid ship propulsion system for known traveling route. The developed numerical model consists of an interconnected system with PEMFC stack and battery pack as power sources. Numerical model is developed and optimized to meet minimal required power demand for successful route demand, which has variable loads and daily sails six-time same voyage- in total 54 nautical miles. The results have shown that equivalent hybrid power system consists of 300 kWe PEMFC stack and battery pack with 424 kWh battery and state of charge varying between 20 and 87%. To power this new hybrid power system, hydrogen tank of 7200 l holding 284.7 kg at pressure of 700 bar is needed, compared to previous system that spend 1524 kg of diesel and generate 4886 kg of CO2.

Both bacteria product flagellin and macrophages are implicated in HIV infection/disease progression. However, the impact of their interaction on HIV infection and the associated mechanisms remain to be determined. We thus examined the effect of the flagellins on HIV infection of primary human macrophages. We observed that the pretreatment of macrophages with the flagellins from the different bacteria significantly inhibited HIV infection. The mechanistic investigation showed that the flagellin treatment of macrophages downregulated the major HIV entry receptors (CD4 and CCR5) and upregulated the CC chemokines (MIP-1α, MIP-1β, and RANTES), the ligands of CCR5. These effects of the flagellin could be compromised by a toll like receptor 5 (TLR5) antagonist. Given the important role of flagellin as a vaccine adjuvant in TLR5 activation-mediated immune regulation and in HIV infection of macrophages, future investigations are necessary to determine the in vivo impact of flagellin-TLR5 interaction on macrophage-mediated innate immunity against HIV infection and the effectiveness of flagellin adjuvant-based vaccines studies.

The optimal functionality and dependability of mechanical systems are important for the sustained productivity and operational reliability of industrial machinery which has direct impact on it’s longevity and profitability. Therefore, failure of a mechanical system or any of it component would be detrimental to production continuity and availability. Consequently,this study proposes a robust diagnostic framework for analyzing the blade conditions of shot blast industrial machinery. The framework involves analyzing the spectral characteristics of the vibration signals generated by Industrial Shot Blast. Additionally, a peak detection algorithms is introduced to identify and extract the unique features present in the peak magnitudes of each signal spectrum. A feature importance algorithm is then deployed as the feature selection tool, and these selected features are fed into 10 machine learning classifier, with Extreme gradient boosting (XGB) as the core classifier. Results show that the XGB classifier achieved the best accuracy of 98.05%, with a cost-efficient computational cost of 0.83 seconds. Other global assessment metrics were also implemented in the study to further validate the model.

In this paper we compare using computational fluid dynamics the aerothermal performance of two candidate casing manifolds for supplying an impingement-actuated active tip clearance control system for an aero-engine high-pressure turbine. The two geometries are (a) single-entry: an annular manifold fed at one circumferential location; (b) multiple-entry: a casing manifold split into four annular sectors, each sector supplied separately from an annular ring main. Both the single-entry and multiple-entry systems analysed in this paper are idealised version of active clearance control systems in current production engines. Aerothermal performance is quantitatively assessed on the basis of the heat transfer coefficient distribution, driving temperature difference for heat transfer between the jet and casing wall, and total pressure loss within the high-pressure turbine active clearance control system. We predict that the mean heat transfer coefficient (defined with respect to the inlet temperature and local wall temperature) of the single-entry active clearance control system is 77% greater than the multiple-entry system; primarily because the coolant in the multiple-entry case picks up approximately 40 K of temperature from the ring main walls, and secondarily because the average jet Reynolds number of impingement holes in the single entry system is 1.2 times greater than in the multiple entry system. The multiple-entry system exhibits many local hot and cold spots, depending on the position of the transfer boxes, while the single-entry case has a more predictable aerothermal field across the system. The multiple-entry feed system uses an average of 20% of the total available pressure drop, while the feed system for the single-entry geometry uses only 2% of the total available pressure drop. From the aerothermal results of this computational study, and in consideration of holistic aero-engine design factors, we conclude that a single-entry system is closer to an optimal solution than a multiple-entry system.

Machine safety is not only a prerequisite for successful production, but also the foundation for sustainability and growth of any manufacturing organisation. The latest approaches in this rapidly developing field are the integration of effective risk management tools and strategies into occupational health and safety (OHS) systems. In this article, using a specific example from practice, we will show how using multi-criteria decision making (AHP) support Machinery Safety Decision Making (MSDM) from the point of reducing losses. Using Classification and Regression Tree Analysis (CART), we estimated the efficiency, cost-effectiveness and thus the sustainability level of the relevant safety measures. These were proposed risk reduction measures that typically raised uncertainty among managers regarding the estimation of cost-effectiveness. The advantage of application decision trees approach is possibility to identify and establish relatively homogeneous groups of undesirable events and their impact on the organisation's objectives. A comprehensive model has been developed to support management decision making in manufacturing organizations in implementing and improving safety measures in line with manufacturing sustainability goals.

In this paper, the ratio of gross agricultural production (GAP) and agricultural carbon emission is defined as agricultural carbon emission efficiency (ACEE). Considering rural labor transfer (RLT) increases the agricultural machinery intensity (AMI), the two are substitutes for each other and may interact with agricultural carbon emission efficiency (ACEE), we constructed a Simultaneous Equations Model (SEM) of ACEE, RLT and AMI, and analyzed the interaction mechanism of these three variables by using the Three-Stage Least Squares (3SLS) method to solve the endogeneity of the model. The following conclusions are drawn. First, RLT and AMI significantly promote the improvement of ACEE, while the improvement of ACEE and AMI further promotes RLT. Secondly, the causal relationship and influence mechanism of ACEE, RLT and AMI are interactive and multi-directional. An increase in AMI promotes ACEE, but an increase in ACEE inhibits an increase in AMI, suggesting that the marginal rate of substitution of machinery for labor is decreasing. Finally, China has significant regional heterogeneity. Labor transfer and machinery are only direct factors in increasing ACEE, while factors such as economic base, technology level and farmers' attitudes provide environmental support for the effective improvement of ACEE.

Calculating a minimum-time trajectory requires the solving of a boundary value problem resulting from invocation of necessary conditions of optimality to set up a set of ordinary differential equations to solve the trajectory between the initial position and desired ending position with set constraints on the path between the two. This manuscript expresses the minimum time optimum trajectory between a satellite in a geosynchronous orbit and a target set on earth’s surface utilizing a non-rotating earth centric coordinate system. Expressing motion in coordinates of rotating reference frames necessitates transformation between reference frames, and one such transformation is embodied in the Direction Cosine Matrices (DCM) formed by a sequence of three successive frame rotations. Rotation about the local wing of an aerospace vehicle is almost never the pitch angle, yet modern application of kinematics often assumes such (with accompanying angular error). The same assertion is usually true about the nature of roll and yaw angles. This manuscript evaluates which sequence is the most advantageous for an object starting in space and then travels through the atmosphere to a target on the Earth’s surface. Simulation precision (validated by the quaternion normalization condition) reveals the so-called 132 rotation is the most accurate with an average error of 0.14° and a computational time of 0.013 seconds: resulting in a 97.95% increase in accuracy over the ubiquitous 321 “aerospace” rotation sequence and a 99.84% increase over the so-called 313 “orbital” rotation sequence. Utilizing the proposed optimal trajectory candidate yields a total flight time of 2 hours, 34 minutes and 46 seconds, or an average velocity of 3.85 kilometers per second, while impacting the target with a velocity of 11.54 kilometers per second.

During the conceptual and preliminary design stage of a ship, designers need to ensure that the selected principal dimensions and parameters are good enough to deliver a stable ship (statically and dynamically) besides deadweight and speed. To support this, the initial intact stability of the proposed ship is required to be calculated, and in doing so, the lightship weight and its detailed breakdown are necessary to be known. After hull steel weight, machinery weight, mainly, marine propulsion and power generation machinery, play a vital role in the lightship weight estimate of a ship due to its robustness. The correct estimation of respective weights improves the accuracy of calculating a ship's initial stability typically to be designed and built. Hence, it would be advantageous for the designer to convince the ship owner. A total of 3006 marine propulsion (main marine diesel) engines and 348 power generation (auxiliary marine diesel) engines/generators of various power output (generators output for auxiliary engines), engine RPM and cylinder number of different engine makers are collected. These are analyzed and presented in both tabular and graphical forms to demonstrate the possible relationship between marine propulsion engine weight and power generation engine weight, and their respective power output, RPM, cylinder number, power-RPM ratio and power-RPM ratio per cylinder.In this article, the authors have attempted to investigate the behavior of marine propulsion engine weight and power generation engine/generator weight regarding engine power output, generator power output, engine RPM and cylinder number (independent variables). Further attempts have been made to identify those independent variables that influence the weight of the marine propulsion engine and power generation engine/generator (dependent variables), and their interrelationships. A mathematical model has thus been developed and proposed, as a guiding tool, for the designer to estimate the weight of main and auxiliary engines more accurately during the conceptual and preliminary design stage.

The past few years have brought substantial progress toward understanding how human cytomegalovirus (HCMV) enters the remarkably wide spectrum of cell types and tissues that the virus infects. Neuropilin-2 and platelet-derived growth factor receptor alpha (PDGFRa) were identified as receptors, respectively, for the trimeric and pentameric glycoprotein H/glycoprotein L (gH/gL) complexes that in large part govern HCMV cell tropism, while CD90 and CD147 were also found to play roles during entry. X-ray crystal structures for the proximal viral fusogen, glycoprotein B (gB), and for the pentameric gH/gL complex (pentamer) have been solved. A novel virion gH complex consisting of gH bound to UL116 instead of gL was described, and findings supporting the existence of a stable complex between gH/gL and gB were reported. Additional work indicates that the pentamer promotes a mode of cell-associated spread that resists antibody neutralization, as opposed to the trimeric gH/gL complex (trimer), which appears to be broadly required for the infectivity of cell-free virions. Finally, viral factors such as UL148 and US16 were identified that can influence the incorporation of the alternative gH/gL complexes into virions. We will review these advances and their implications for understanding HCMV entry and cell tropism.

In this paper, the concept of absolute airspace is further elaborated, and the time transform effect, the frequency transform relation of clock timing, and the principle of Doppler effect of special relativistic light are analyzed and demonstrated. Based on the concept of absolute airspace, a new and accurate Doppler effect relation of light (electromagnetic wave) is proposed. It is proved that there is a synchronous relationship between the time shift effect and the frequency change of the timing inside the clock. When the light (electromagnetic wave) source is in motion, the Doppler effect includes two physical mechanisms: the frequency change caused by time transformation effect and the frequency change caused by relative motion. When the light source is in motion, the Doppler effect of the light there are some differences in different directions due to the rotation of the earth. The relation of Doppler effect of special relativistic light is only a highly approximate relation, and its theoretical basis, special relativity, is flawed in principle.

We analyze a time-delayed SIQR model that considers the transportation-related infections and entry-exit screening. This model aims to determine the measures for preventing and controlling major emergent infectious diseases and the associated costs. We calculate the basic reproduction number (R0), apply the linearization method, and construct an appropriate Lyapunov function to determine the stability of the disease-free equilibrium in the local and global. We collect COVID-19 infection data from two regions in the United States in 2020 for data fitting, obtain a set of optimal parameter values, and show that the model is suitable for simulating the outbreak and spread of emerging infectious diseases. We find that transportation-related infections increase the basic reproduction number, enhancing the impact on disease spread. Entry-exit screening effectively suppress the spread of disease by reducing the basic reproduction number. Furthermore, we investigate the influence of the incubation period on disease and find that a shorter incubation period results in a shorter duration but a larger scale of infection, and the peaks are reduced. We conduct a sensitivity analysis of the R0 and propose three measures to prevent the spread of new infectious diseases based on the most sensitive parameters: wearing masks, implementing urban closures, and administering medication to sick but not yet hospitalized patients promptly. In the case of COVID-19, we use Pontryagin’s minimum principle to get time-varying control measures to control the spread of the outbreak. Optimal control effectively controls the development and deterioration of the disease. Finally, several control measures are compared through cost-effectiveness analysis, and the results show that wearing masks is the most cost-effective measure. Our study provides some practical guidance for controlling the spread of major emerging infectious diseases.

Redundancy in ship systems is provided to ensure operational resilience through equipment backups which ensures system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems, hence is provided with good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired black outs are common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensure a more robust maintenance and support platform for efficient ship operations. In this regard hybrid reliability and fault detection analysis were conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of 4 marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate overall low system reliability of less than 70 per cent within the first 24 months of the 78 operational months. Component criticality using reliability importance measures was used to identify all components with more than 40 per cent contribution to sub systems failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Networks classification. The ANN has identified failure patten threshold at about 200kva which can be attributed to overheating, hence establishing link between component failure and generator performance.

Natural host defensins, also sometimes termed antimicrobial peptides, are evolutionarily conserved. They have been studied as antimicrobials, but some pharmaceutical properties, undesirable for clinical use, led to the development of synthetic molecules with constructed peptide arrangements and/or peptides not found in nature. The leading development currently is synthetic small molecule nonpeptide mimetics, whose physical properties capture the characteristics of the natural molecules, and share their biological attributes. We studied brilacidin, an arylamide of this type, for its activity in vitro against fungi (40 clinical isolates, 20 species) that the World Health Organization has highlighted as problem human pathogens. We find antifungal activity at low concentrations for many pathogens, which indicates further screening for activity, particularly in vivo, is justified to evaluate this compound, and other mimetics, as attractive leads for development of effective antifungal agents.

The shift towards autonomous excavators in construction and mining is a significant leap towards enhancing operational efficiency and ensuring worker safety. However, it presents challenges such as the need for sophisticated decision-making and environmental perception due to complex terrains and diverse conditions. Our study introduces the E-GTN framework, a novel approach tailored for autonomous excavation that leverages advanced multisensor fusion and a custom-designed convolutional neural network to address these challenges. Results demonstrate that GridNet effectively processes grid data, enabling the reinforcement learning algorithm to make informed decisions, thereby ensuring efficient and intelligent autonomous excavator performance. The study concludes that the E-GTN framework offers a robust solution for the challenges in unmanned excavator operations, providing a valuable platform for future advancements in the field.

Ebola Virus Disease (EVD) is one of the most lethal transmissible infections characterized by a high fatality rate, and caused by members of the Filoviridae family. The recent large outbreak of EVD in West Africa (2013-2016), highlighted the worldwide danger of this disease and its impact on global public health and economy. The development of highly needed anti-Filoviridae antivirals has been so far hampered by the shortage of tools to study their life cycle in vitro, and therefore screen for potential active compounds outside a biosafety level-4 (BSL-4) containment. Importantly, the development of surrogate models to in vitro study of Filoviridae entry in a BSL-2 setting, such as viral pseudotypes and Ebola virus like particles, tremendously boosted both our knowledge on viral life cycle and the identification of promising anti-Filoviridae compounds interfering with viral entry. In this context, the combination of such surrogate systems with large-scale small molecule compounds and haploid genetic screenings, as well as rational drug design and drug repurposing approaches will prove priceless in our quest for the development of a treatment for EVD.

Exposure of phosphatidylserine (PS) in the outer leaflet of the plasma membrane is induced by infection with several members of the Alphaherpesvirinae subfamily. There is evidence that PS is used by the equine herpesvirus type 1 (EHV-1) during entry, but the exact role of PS and other phospholipids in the entry process remains unknown. Here, we investigated the interaction of differently charged phospholipids with virus particles and determined their influence on infection. Our data show that liposomes containing negatively charged PS or positively charged DOTAP [N-[1-(2,3-Dioleoyloxy)propyl]-N,N,N-trimethylammonium)] inhibited EHV-1 infection, while neutral phosphatidylcholine (PC) had no effect. Inhibition of infection with PS was transient, decreased with time, and was dose dependent. Our findings indicate that both cationic and anionic phospholipids can interact with the virus and reduce infectivity, while acting through different mechanisms. Charged phospholipids were found to have antiviral effects and can may be used to inhibit EHV-1 infection.

In Korea’s air pollutant inventory, construction machinery is a major emission source in the non-road sector. Since 2004, the Korean government has introduced and reinforced emission regulations to reduce the air pollutants emitted from their diesel engines. Since the engine dynamometer test method used in emission regulations has limitations in reflecting emission characteristics under the diverse working conditions of construction machinery, it is necessary to examine the effectiveness of emission regulations and the validity of the emission factors applied as inputs to the air pollutants inventory. This could be done by evaluating engine operation and emission characteristics under real-world working conditions. In this study, 14 units were selected among the excavators, wheel loaders, and forklifts that represent approximately 90% of the registered construction machines in Korea. They were equipped with a portable emission measurement system (PEMS) to measure gaseous emissions and collect engine data under various real-world working conditions. With the reinforcement of emission regulations for the construction machinery from K-tier3 to K-tier4 in Korea, exhaust after-treatment technologies, such as selective catalytic reduction and diesel oxidation catalyst, were applied. Real world NOx were reduced by approximately 83%, and THC 77% and CO by 73%, respectively. Real world NOx + THC of the K-tier3 machines exceeded the laboratory emission limit, but the K-tier4 machines considerably improved despite some differences. The emission factors applied to the air pollutant inventory have been developed using the engine dynamometer test method, but they were considerably underestimated compared with emissions under real-world working conditions. The difference was even larger for the K-tier4 machines. In this study, the possibility of developing emission factor equations that use the engine load factor as a parameter was confirmed by using the engine work 1 g/kW·h segment moving averaging window (MAW) method.

Corrugated boards are used for packaging because of their high strength-to-weight ratio, recyclability, and biodegradability. They have an orthotropic sandwich structure with unique characteristics for each direction owing to their flute shape. In this study, the bending behavior was qualitatively analyzed for various variables through an FE-based simulation, and the possibility of an alternative test method for the four-point bending test on a corrugated board was examined through a similarity analysis with the experimental results. The cross-machine direction (CD) bending stiffness through finite element analysis (FEA) simulation was closely related to the thickness of the corrugated board. In AB-flute-double-wall (AB/F-DW), the difference in CD bending stiffness based on the bending direction was approximately 17.2% in the FEA simulation and approximately 10.5% in the experiment. However, the differences in the bending behavior (bending force vs. deflection plot) and bending stiffness based on the phase shift between the two flutes constituting BB-flute-double-wall (BB/F-DW) were insignificant. Overall, the CD bending behavior of the corrugated board was simulated relatively well through FEA simulation. However, it was impossible to simulate the machine-direction (MD) bending behavior through FE-based simulation because of a decrease in convergence and a large error caused by the variability of the contact condition of the modeled test specimen with a non-uniform MD cross-section.

The entry and exit method is a simple and practical method to determine the critical slip surface of slope. However, it has the drawback of sacrificing computational efficiency to improve search accuracy. To solve this problem, this paper proposes an improved entry and exit method to search for the critical slip surface. Based on the random fields generated by using Karhunen–Loève expansion method, the simplified Bishop’s method combined with the improved entry and exit method is used to determine the critical slip surface and its corresponding minimum factor of safety. Then, the failure probability is calculated by conducting Monte Carlo simulation. Two examples are reanalyzed to verify the accuracy and efficiency of the proposed method. Meaningful comparisons are made to demonstrate the calculating accuracy and calculating efficiency of the improved entry and exit method in searching for the minimum safety factor of slope, based on which the effect of the reduced searching range on slope reliability was explored. The results indicate that the proposed method provides a practical tool for evaluating the reliability of slopes in spatially variable soils. It can greatly improve the computational efficiency in relatively high-computational accuracy of slope reliability analysis.

Organic electrophoretic coatings have gained significant attention due to their ability to provide a uniform and controlled coating thickness, high coating adhesion, and excellent corrosion protection properties. In this work, to investigate the aging behaviors of an organic electrophoretic coating for magnesium alloys, water absorption kinetics curves of the coatings after immersion in 3.5 wt.% NaCl at 20℃ and 40℃ were measured, and parameters such as the saturated water absorption and saturation time of the free film coatings were fitted to determine the densification evolution of the organic coatings. A tensile test was used to test the tensile strength of the organic coating during service to determine the evolution of the strength and toughness of the organic coating. The evolution of wet adhesion of organic coatings with service time was tested by ASTM D4541-02. The impedance spectra of the organic coatings under the above conditions were detected by EIS, and finally, the failure behavior of the organic coatings under immersion was analyzed.

Cryptococcus neoformans is a facultative intracellular fungal pathogen. Ten-generation-old (10GEN) C. neoformans cells are more resistant to phagocytosis and killing by macrophages than younger daughter cells. However, mechanisms that mediate this resistance and intracellular parasitism are poorly understood. Here, we identified factors important for the intracellular survival of 10GEN C. neoformans, such as urease activity, capsule synthesis, and DNA content using flow cytometry and fluorescent microscopy techniques. Real-time visualization of time-lapse imaging was applied to determine the phagosomal acidity, membrane permeability, and vomocytosis (non-lytic exocytosis) rate in J774 macrophages that phagocytosed C. neoformans of different generational ages. Our results showed that old C. neoformans exhibited higher urease activity, and enhanced capsule formation, which was supported by an increased Golgi complex. In addition, old C. neoformans were more likely to be arrested in the G2 phase, resulting in the occasional formation of aberrant trimera-like cells. To finish, the advanced generational age of the yeast cells slightly reduced vomocytosis events within host cells, which might be associated with increased phagolysosomal pH and membrane permeability. Altogether our results contribute to a better understanding of the strategies used by old C. neoformans to resist phagosomal killing and suggest that old generation C. neoformans intracellular behavior may be driving cryptococcosis pathogenesis.

Even though the rules for free movement of machinery within the European Union market have existed for more than 30 years, accidents related to their activities have constantly been achieving significant value. When designing the machine, a designer must stem from risk assessment, whereas all stages of its life cycle and ways of its use must be taken into consideration. In industrial operations, there is old machinery, which, although fulfilling its function reliably, the safety level is not in accordance with the developing requirements for their safe operation. The proposed methodology of assessment of the machinery safety condition comes out from the presupposition of the right application of steps of risk assessment and their reduction mainly by means of implementation of both effective and efficient preventive measures. The aim of the research applied in 3 operations, was to verify the method of machinery safety management. The created methodology based on 19 requirements for safety evaluates the level of the actual measures by means of the so-called criterion of current status and total efficiency of measures. Its output is the assessment of the efficiency level of implemented safety of each machine as well as of the whole operation.

Fall armyworm, Spodoptera frugiperda, is one of the major migratory polyphagous insect pests of various crops. The essential nutrient and mineral profile of host plants determines the feeding fitness of herbivorous insects. As a result, growth and development of insects is affected. To determine the effect of nutrient and mineral profile of different host plants (maize, castor bean, cotton, cabbage, okra and sugarcane) on the growth and development of S. frugiperda, biological parameters like larval weight, pupal weight (male/female), feeding and growth indices were calculated. The proximate compositions and mineral contents of the tested host plants showed a significant difference (p<0.5). Better nutrients were observed in castor bean and maize host plants. The growth indices on these host plants also showed the statistical difference (p<0.05) except efficiency of ingested food (p>0.05). The maximum relative growth rate (RGR), relative consumption rate (RCR) and consumption index (CI) were recorded in S. frugiperda larvae that fed on maize and castor bean leaves. Larval, male and female pupal weights were the maximum in the larvae feeding on castor bean host plant. In case of fitness indices, the highest larval growth, pupal growth, standard growth and fitness indices were observed in S. frugiperda larvae that fed on maize. The findings of the present study highlight the dynamic growth and development of S. frugiperda larvae on maize plants and provide novel information based on nutritional ecology to develop sustainable integrated pest management strategies using selective crop rotation and limiting alternative host plants.

All kinds of vessels consist of dozens of complex machineries with rotating parts and electric motors that operate continuously in a harsh environment with excess temperature and humidity, vibration, fatigue and load. A breakdown or malfunction in one of these machineries can significantly impact the vessel’s operation and safety and consequently, the safety of the crew and the environment. To maintain operational efficiency and seaworthiness, the shipping industry invests substantial resources in preventive maintenance and repairs. This research presents the economic and technical benefits of predictive maintenance over to traditional preventive maintenance, and repair by replacement approaches in the maritime domain. By leveraging modern technology and Artificial Intelligence, we can analyze real-time operating conditions of machinery, enabling early detection of potential damages and allowing for effective planning of future maintenance and repair activities. In this paper, we propose and develop a Convolutional Neural Network that is fed with raw vibration measurements acquired in a laboratory environment from the ball bearings of a motor. Then, we investigate whether the proposed network can accurately detect the functional state of ball bearings and categorize any possible failures present, contributing to improved maintenance practices in the shipping industry.

Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Interrogating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found African-derived tumors to present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63) including several putative therapeutic targets (CHD7, DPF3, POLR1B, SETD1B, UBTF and VPS72). Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified top genes in African and European-derived tumors that represent a multifunctional “generic machinery”, alteration to which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis but African-derived tumors appear to achieve this with greater diversity amongst such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.

In the recent years, intelligent data-driven faultdiagnosis methods on gearboxes have been successfully developedand popularly applied in the industries. Currently, most ofthe machine learning techniques require that the training andtesting data are from the same distribution. However, thisassumption is difficult to be met in the real industries, sincethe gearbox operating conditions usually change in practice,which results in significant data distribution gap and diagnosticperformance deteriorations in applying the learned knowledgeon the new conditions. This paper proposes a deep learning-based domain adaptation method to address this issue. Theraw current signals are directly used as the model inputs fordiagnostics, which are easy to collect in the real industries andfacilitate practical applications. The maximum mean discrepancymetric is introduced to the deep neural network, the optimizationof which guarantees the extraction of generalized machineryhealth condition features across different operating conditions.The experiments on a real-world gearbox condition monitoringdataset validate the effectiveness of the proposed method, whichoffers a promising tool for cross-domain diagnosis in the realindustries.

The success of any tsetse control programs depends on the knowledge of their behaviour. This study assessed the host choice and feeding behaviours of Glossina morsitans’ siblings whose parents were bloodfed on Rabbits, Guinea pigs, Rodents and Squirrels. Individual host was placed in a screen cage which allowed flies to enter through openings on each side. The groups of flies (20 per replicate) colour-marked differently basing on their parents’ bloodmeal hosts, were released from the centre of large semi-field cage. Released flies were aspirated after 24 hours, then, sorted basing on the location, feeding status and parents’ bloodmeal. A total of 213 flies (72.95% of the recovered) were attracted to the hosts. The number of flies attracted to different hosts varied significantly (χ²4= 33.685, p= 0.0001); Rodent (n=80, p=0.006), Rabbit (n=59, p=0.331), Guinea pig (n=49, p=0.057) and squirrel (n=25, p=0.005). The number of flies attracted to their parent’s blood meal source varied significantly (χ²12 = 56.476, p<0.001); rabbits (n= 35, 59.32%, p<0.001), rodent (n=25, 31.25%, p=0.043) and guinea pig (n= 19, 38.78%, p=0.45). But, only 39 flies (18.31% of total attracted) bloodfed on the hosts; Guinea pigs (n=10, 25.64%), Rodents (n=23, 58.97%), Rabbits (n=6, 15.38%) and Squirrels (n=0,0.0%). There was significant variation in number of flies that fed successively across hosts (χ²4=49.478, p<0.001). The findings from this study confirms the presence of the hosts’ differential attractiveness to flies but failed to explain observed behaviours with reference to genetic inheritance. Therefore, the study attracts the need for detailed investigation on the influence of bloodmeal sources on tsetsefly siblings’ behaviours across filial generations using small mammals.

Special machinery engineering is of great importance to the manufacturing industry and makes a comparatively large contribution to many economies. Digital transformation is already well advanced in many producing industries, and modern ICT technologies such as agents, service orientation, digital twins and artificial intelligence are being used with increasing success. In addition to improving specific product characteristics such as reliability or flexibility, the adoption of modern ICT technologies to ensure sustainability is being intensively discussed. So far, however, there has been little uptake of these technologies in the special machinery industry; sustainability receives little attention. This article examines in detail the reasons for and impediments to the adoption of modern ICT technologies based on a study among special machinery manufacturers. Observations of existing challenges were gathered during daily work, described in detail, and used to derive conclusions about causal barriers. From this, detailed requirements are derived to promote the adoption of modern ICT technologies in the special machinery engineering sector and, ultimately, to bring sustainability more into focus.

This study focuses on the aerodynamic optimization of the re-entry capsule (REC) Orion Crew Exploration Vehicle (CEV) module, evaluating its performance using computational fluid dynamics (CFD). Three different models, namely Baseline, 2-Duct, and 4-Duct, are investigated under a wide range of flow speeds, from supersonic (Ma=1.6) to hypersonic (Ma=6) regimes. Thermofluids aspects, drag coefficient, surface heat flux, and the effectiveness of the modified geometry are assessed using aerodynamic and temperature-based models. The results show that the introduction of ducts in the 2-Duct and 4-Duct models leads to an average decrease in the drag coefficient of approximately 2.1% and 2.9%, respectively, compared to the baseline model, across all Mach numbers. The maximum reduction in drag coefficient is 3.55%, observed at Ma=1.4 using the 4-Duct capsule. However, it is found that the addition of extra ducts to the model increases the maximum heat transfer rate. Specifically, the heat flux is increased by up to 69% for the 4-Duct model at Ma=6, compared to the baseline model. On average, the heat flux is increased by approximately 28.6% for all conditions. The findings indicate that the introduction of ducts in the REC model improves its aerothermodynamic performance by reducing drag but also increases the heat transfer rate on the surface.

Molecular therapies exploiting mRNA vectors embody enormous potential, as evidenced by the utility of this technology for the context of the COVID-19 pandemic. None-the-less, broad implementation of these promising strategies has been restricted by the limited repertoires of delivery vehicles capable of mRNA transport. On this basis, we explored a strategy based on exploiting the well characterized entry biology of adenovirus. To this end, we studied an adenovirus-polylysine (AdpL) that embodied “piggyback” transport of the mRNA on the capsid exterior of adenovirus. We hypothesized that the efficient steps of Ad binding, receptor-mediated entry, and capsid-mediated endosome escape could provide an effective pathway for transport of mRNA to the cellular cytosol for transgene expression. Our studies confirmed that AdpL could mediate effective gene transfer of mRNA vectors in vitro and in vivo. Facets of this method may offer key utilities to feasibilize the promise of mRNA-based therapeutics.

Begomoviruses, which belong to the Geminiviridae family, are intracellular parasites transmitted by whiteflies to dicotyledonous plants, significantly damaging agronomically relevant crops. These nucleus-replicating DNA viruses need to move intracellularly from the nucleus to the cytoplasm and then, like other plant viruses, spread systemically throughout the plant to cause dis-ease. The transport proteins of begomoviruses play a crucial role in recruiting host components for the movement of viral DNA within and between cells while exhibiting functions that suppress the host's immune defense. Pioneering studies on species of the Begomovirus genus have identified specific viral transport proteins involved in intracellular transport, cell-to-cell movement, and systemic spread. Recent research has primarily focused on viral movement proteins and their interaction with the cellular host transport machinery, significantly expanding our understanding of viral infection pathways. This review focuses on three main aspects: (i) the role of viral transport proteins, specifically movement proteins (MPs) and nuclear shuttle proteins (NSPs), (ii) their ability to recruit host factors for intra- and intercellular viral movement, and (iii) suppress antiviral immunity, with a particular emphasis on bipartite begomoviral movement proteins.

Unmanned construction machinery vehicles mostly carry work in bridges, tunnels, and outdoor open spaces. Obtaining accurate pose estimation of the entire vehicle and establishing a map of the surrounding environment is of great significance for path planning and control in the later stage. Traditional simultaneous localization and mapping (SLAM) schemes, which mostly use a single sensor, but there are problems with localization drift and mapping failure in scenarios where there are few geometric features and the environment is prone to degradation. Currently, the multi-sensor fusion strategy has been proven to be an effective solution and widely used in the field of unmanned vehicle localization and mapping. This paper proposes a SLAM framework that tightly couples a LiDAR, IMU and camera to achieve accurate and reliable pose estimation. The framework is based on LiDAR-inertial system(LIS) and factor graph optimization theory. Texture information provided by vision is integrated into the LiDAR-inertial odometry to generate a new visual-inertial subsystem(VIS).The two subsystems, VIS and LIS, can assist each other and work jointly. Through real vehicle tests, the system can perform incremental, real-time state estimation, reconstruct dense 3D point cloud maps,and effectively solve the problems of localization drift and mapping failure in the lack of geometric features or challenging construction environments. Meanwhile, the system has a safety redundancy mechanism. When any subsystem fails, the system can also operate normally, to ensure the reliability and robustness of vehicle positioning.

Anomaly occurrences in hydraulic machinery may lead to massive systems shut down, jeopardizing the safety of the machinery and its surrounding human operator(s) and environment, and the severe economic implications succeeding the faults and their associated damage. Hydraulics are mostly placed in ruthless environments, where they are consistently vulnerable to many faults. Hence, not only the machines and their components are prone to anomalies, but also the sensors attached to them, which monitor and report their health and behavioral changes. In this work, a comprehensive applicational analysis of anomalies in hydraulic systems extracted from a hydraulic test rig is thoroughly achieved. Firstly, we provided a combination of a new architecture of LSTM autoencoders and supervised machine and deep learning methodologies to perform two separate stages of fault detection and diagnosis. The two phases are condensed by: the detection phase using the LSTM autoencoder. Followed by the fault diagnosis phase represented by the classification schema. The previously mentioned framework is applied to both component and sensor faults in hydraulic systems, deployed in the form of two in-depth applicational experiments. Moreover, a thorough literature review of the past decade related work for the two stages separately is successfully conducted in this paper.

In the intricate dance between viruses and host cells, RNA-binding proteins (RBPs) serve as crucial orchestrators of gene expression and cellular processes. We will delve into the riveting realm of viral hijacking, where viruses deftly exploit host RBPs to manipulate cellular machinery for their replication and pathogenesis. Through a masterstroke of molecular subterfuge, viruses co-opt RBPs involved in various facets of RNA metabolism - from transcription to degradation - to promote viral gene expression and evade host immune defenses. This manipulation leads to global alterations in cellular RNA metabolism, impacting essential host genes vital for immune responses and homeostasis.Unveiling this clandestine alliance between viruses and RBPs is not just a scientific pursuit, but a critical imperative for devising innovative antiviral strategies to disrupt these interactions. By unraveling the intricate interplay between viral proteins and host RBPs throughout the viral life cycle - from entry to assembly - researchers aim to identify vulnerabilities that can be targeted for therapeutic intervention. Strategies such as disrupting viral protein-RBP interactions hold promise for inhibiting viral replication and curbing pathogenesis, offering a beacon of hope in the battle against viral infections.Our manuscript elucidates the indispensable roles played by RBPs in viral replication, translation, and pathogenesis, shedding light on the molecular mechanisms driving viral success. Delving deeper, it explores how viruses intricately entwine with host RBPs, manipulating cellular signaling pathways to create a hospitable environment for viral spread. By dissecting these manipulative tactics, researchers uncover new targets for antiviral therapy, envisioning a future where tailored interventions disrupt viral-host RBP interactions with precision and efficacy.As the narrative unfolds, the therapeutic implications of targeting RBPs or their interactions with viral proteins emerge as a promising frontier in the fight against viral infections. From small molecule inhibitors to RNA-based therapeutics, innovative approaches are on the horizon, offering new avenues for combatting viral diseases. We set the stage for future research, beckoning researchers to delve deeper into the molecular intricacies of viral hijacking of RBPs and charting a course towards novel therapeutic interventions that promise to reshape the landscape of antiviral therapy.\Ultimately, it beckons the scientific community to embark on a voyage of discovery, unraveling the secrets of viral hijacking of RBPs and paving the way for transformative advances in antiviral therapeutics. The stage is set for a new chapter in the battle against viral infections, where knowledge becomes the sword and innovation the shield against the pernicious machinations of viral pathogens.

The high transmissibility, rapid evolution, and immune escape of SARS-CoV-2 variants can influence the course of infection and, in turn, morbidity and mortality in COVID-19, posing a challenge in controlling transmission rates and contributing to the emergence and spread of new variants. The factors that shape viral genetic variation are consequently essential for understanding the evolution and transmission of SARS-CoV-2, especially in vaccinated individuals where immune response plays a role in the progression and spread of this disease. This study assessed. In this context, we evaluated the impact of immunity induced by the CoronaVac vaccine (Butantan/Sinovac) on intra-host genetic diversity, analyzing 118 whole-genome sequences of SARS-CoV-2 from unvaccinated and vaccinated patients infected with the Gamma variant. Vaccination with CoronaVac favors negative selection at the intra-host level in different genomic regions and prevent greater genetic diversity of SARS-CoV-2, which may help reduce the emergence of new mutations, reinforcing the importance of vaccination in reducing virus transmission.

Human influenza A viruses (IAVs) cause global pandemics and epidemics. These viruses evolve rapidly, making current treatment options ineffective. To identify novel modulators of IAV-host interactions, we re-analyzed our recent transcriptomics, metabolomics, proteomics, phosphoproteomics, and genomics/virtual ligand screening data. We identified 713 potential modulators targeting 200 cellular and two viral proteins. Anti-influenza activity for 48 of them has been reported previously, whereas the antiviral efficacy of the remaining 665 is unknown. Studying anti-influenza efficacy, immuno-modulating properties and potential resistance of these compounds or their combinations may lead to the discovery of novel modulators of IAV-host interactions, which might be more effective than the currently available anti-influenza therapeutics.

When the zoonotic parasite of rodents that can cause human neuroangiostrongyliasis, i.e., Angiostrongylus cantonensis, is found in its natural definitive hosts, it is usually reported in isolation, as if the rat lungworm were the only component of the within-rat parasite community. In this study we report the coinfections found in rats naturally infected by A. cantonensis in urban populations of Rattus norvegicus and Rattus rattus in Valencia, Spain. In addition to the rat lungworms, which were found in 14 of the 125 rats studied (a prevalence of 11.20%), 18 other parasite infrapopulations (intestinal and tissular protists, microsporidia, and helminths) were found; some of them with high burdens. Fourteen of these 19 species found are potential zoonotic parasites, namely Blastocystis, Giardia duodenalis, Cryptosporidium spp., Enterocytozoon bieneusi, Encephalitozoon hellem, Toxoplasma gondii, Brachylaima spp., Hydatigera taeniaeformis larvae, Hymenolepis nana, Hymenolepis diminuta, Angiostrongylus cantonensis, Calodium hepaticum, Gongylonema neoplasticum and Moniliformis moniliformis. Despite the limited number of rats studied, the total predominance of coinfected rats as well as their high parasite loads seem to indicate a clear trend towards parasite tolerance.

Leasing and recycling are important issues to achieve low-carbon sustainable development of construction machinery industry, however there are some dilemmas bothering which is caused by excessive restriction of product service life. Focusing on the problem of pricing and coordination, a two-stage model of leasing closed-loop supply chain based on the Industrial Internet platform practical application was proposed. Under the centralized and decentralized decision-making scenarios, the price of leasing and selling, maintenance effort and recovery rate are calculated respectively. By using the Shapley value method to optimize the selling price, and the two-part pricing contract to calculate the compensation fee, the global profit is reasonably distributed, while the supply chain achieving Pareto optimality. The performance of different contracts on the improvement of supply chain profit was investigated. And the correlation among parameters was also explored through sensitivity analysis and numerical simulation. The findings showed that maintenance and recycling of construction machinery can be improved with the advantage of the Industrial Internet platform, while achieving the supply chain coordination by contracts. The enhancement of maintenance effort can decrease the remanufacturing cost which is positively correlated to the selling price and leasing price of product, furthermore promoting the recovery rate of used products. In the future, reasonable control of platform cost can help improve the recycling of construction machinery.

Pneumonia cases of unknown etiology in Wuhan, China, were reported to the WHO on 31st of December 2019. Later the pathogen was reported to be a novel coronavirus designated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that causes Coronavirus Disease 2019 (COVID-19). SARS-CoV-2 is a novel pathogenic beta coronavirus that infects humans causing severe respiratory illness. However, multifarious factors can contribute to the susceptibility to COVID-19 related morbidity and mortality such as age, gender and underlying comorbidities. Importantly, SARS-CoV and SARS-CoV-2 entry into the host cells is mediated via ACE2 receptor. However, ACE2 receptor binding affinity to SARS-CoV-2 is 4 folds higher than that to SARS-CoV. Identification of different aspects such as binding affinity, differential antigenic profiles of spike glycoproteins, and ACE2 polymorphisms might influence the investigation of potential therapeutic strategies targeting SARS-CoV-2/ACE2 binding interface. Here we aim to elaborate on SARS-CoV-2 S1/ACE2 ligand that facilitates viral internalization as well as to highlight the differences between SARS-CoVs binding affinity to ACE2. We also discuss the possible immunogenic sequences of spike glycoprotein and the effect of ACE2 polymorphism on viral binding/infectivity and host susceptibility to disease. Furthermore, targeting of ACE2 will be discussed to understand its role in therapeutics.

Acute and chronic graft versus host disease (a/cGVHD) are major complications of allogeneic stem cell transplantation and a frequent cause of non relapse-mortality. The treatment of a/cGVHD consists of steroid administration at full dose. In the case of aGVHD, around 60 % of patients with grade III/IV fails to respond (steroid-resistant, SR), requiring a second line therapy. Extracorporeal photopheresis (ECP) represents a good option for second line treatment, leading to multiorgan response in several patients. Here, we have evaluated the performances of a cytofluorimetric quality control of the first ECP procedure in 29 patients with severe SR aGVHD who underwent ECP. The quality control represents a check control of in vitro cell apoptosis/death induction in collected and irradiated CD3+ cells by ECP. Our analysis shows that in more than 70 % quality controls a relevant apoptotosis/death of CD3+ cells was observed after cell irradiation, as compared to non-irradiated controls. Albeit observed in a small patients’ series, the occurrence of relevant in vitro effect after ECP relates to less procedures and/or to a better survival on ECP. Age, disease, gender, aGVHD grade and time from transplant to the first ECP had not impact on ECP efficacy in this patients’ series.

A relevant aspect in the epidemiology of Tegumentary Leishmaniasis (TL) is the Leishmania parasites carrying a viral endosymbiont Leishmania RNA Virus 1 (LRV1), a dsRNA virus. Leishmania parasites carrying LRV1 are prone to causing more severe TL symptoms, increasing the likelihood of unfavorable clinical outcomes. LRV1 has been observed in cultured strains of five L. (Viannia) species, and host specificity was suggested when studying LRV1 from L. braziliensis and L. guyanensis strains. The coevolution hypothesis of LRV1 and Leishmania was based on phylogenetic analyses, implying an association between LRV1 genotypes, Leishmania species, and their geographic origins. This study aimed to investigate LRV1 specificity to Leishmania (Viannia) species hosts by analyzing LRV1 from L. (Viannia) species. To this end, LRV1 was screened in L. (Viannia) species other than L. braziliensis or L. guyanensis, and it was detected in 11 out of 15 L. naiffi and in 2 out of 4 L. shawi. Phylogenetic analyses based on partial LRV1 genomic sequencing supported the hypothesis of host specificity, as LRV1 clustered according to their respective Leishmania species hosts. These findings underscore the importance of investigating Leishmania and LRV1 coevolution and its impact on Leishmania (Viannia) species dispersion and pathogenesis in the American Continent.

Condition monitoring is a crucial process for ensuring industrial assets' reliability and operational efficiency. In the age of the digital industry, AI-based data-driven condition monitoring is proving extremely effective in detecting potential issues before they escalate into major problems, thereby reducing downtime, minimizing maintenance costs, and extending the lifespan of the equipment. The availability of tools that can enable the operationalization of these data-driven solutions is, therefore, critical. In this direction, this work proposes a comprehensive, modular, and scalable pipeline covering all the steps from the data acquisition to the AI model training and inference phases. The tool integrates the data acquisition and processing steps with a configurable feature extraction phase. Moreover, the system also integrates deep learning algorithms for diagnosis and prognosis, including a domain adaptation stage to permit transfer learning and increase generalizability. In addition, it features a communication system using MQTT, which allows for an online data stream to enable real-time monitoring and maintenance. The overall infrastructure was deployed in actual industrial settings and tested in a real-time experiment, demonstrating the proposed approach's validity.

Machinery degradation assessment can offer meaningful prognosis and health management in-formation. Although numerous machine prediction models based on artificial intelligence have emerged in recent years, they still face a series of challenges: (1) Many models continue to rely on manual feature extraction. (2) Deep learning models still struggle with long sequence prediction tasks. (3) Health indicators are inefficient for remaining useful life (RUL) prediction with cross-operational environments when dealing with high-dimensional datasets as inputs. This research proposes a health indicator construction methodology based on a transformer self-attention transfer network (TSTN). This methodology can directly deal with the high-dimensional raw dataset and keep all the information without missing when the signals are taken as the input of the diagnosis and prognosis model. First, we design an encoder with a long-term and short-term self-attention mechanism to capture crucial time-varying information from a high-dimensional dataset. Second, we propose an estimator that can map the embedding from the encoder output to the estimated degradation trends. Then, we present a domain dis-criminator to extract invariant features from different machine operating conditions. The case studies with the FEMTO-ST bearing dataset and the Monte Carlo method for RUL prediction during the degradation process are conducted. The experiment results fully exhibited the signif-icant advantages of the proposed method compared to other state-of-the-art techniques.

COVID19 is a current pandemic disease due to the novel coronavirus SARS-CoV-2. The scientific community mounted a strong response by accelerating research and innovation, and rapidly setting the basis to the understanding of molecular determinants of the disease for the development of targeted therapeutic interventions. The replication of the viral genome within the infected cells is a key step of SARS-CoV2 life cycle. It is a complex process involving the action of several viral and host proteins in order to perform RNA polymerization, proofreading and final capping. This review provides an update of structural and functional data on key actors of the replicatory machinery of SARS-CoV-2, filling the gaps in the current availability of structural data using homology modelling. Moreover, learning from similar viruses, we collect literature data to reconstruct the pattern of interactions among protein actors of the SARS-CoV-2 RNA polymerase machinery. In this pattern, an important role is played by co-factors, like Nsp8 and Nsp10, not only as allosteric activators but also as molecular connectors holding the entire machinery together to enhance the efficiency of RNA replication.

The Suter curves for Wh and Wm characteristics of collected and the first time presented Four-quadrant (4Q) diagrams of 11 radial pump-turbine models with different specific speeds (nq=24.34, nq=24.8, nq=27, nq=28.6, nq=38, nq=41.6, nq=41.9, nq=43.83, nq=50, nq=56, and nq=64.04) are given in the paper, as well as the Suter curves for 2 pump models (nq=25, and nq=41.8) which were already published in the literature. These 11+2 curves were analyzed to establish a certain universal law of behavior in dependence on the specific speed. For the determination of existing laws in behavior, the fitting procedure using the Regression and Spline methods was used. The paper presents a research plan and structures that include: data collection of four-quadrant diagrams for models of pump-turbines and pumps with different specific speeds (nq), the procedure of recalculation of Four-quadrant diagrams of the models into Suter curves for Wh and Wm characteristics, the definition of the optimal point for the pump and turbine operating mode in pump-turbine models for different specific speeds, and developing numerical models in the MATLAB program to obtain the Universal Equation for the Wh and Wm characteristics. The scientific contribution of this paper is the firstly published original mathematical curve named Universal Equation for the Wh and Wm characteristics for radial pumps and pump-turbines. Application of the equation has been demonstrated at the pumping station where two radial pumps are installed. The calculation of transient processes was performed using the numerical model developed by the authors in the mathematical program MATLAB. Comparison of the transition process results has been made for the two cases - when input data in the numerical model have been firstly used with the values of Suter curves for Wh and Wm characteristics obtained by recalculation from the Four-quadrant operating characteristics (Q11, n11, M11) of model’s specific speed, and then secondly with the values of the Suter curves for Wh and Wm characteristics obtained from the Universal Equation.

Digitalization technologies have been identified as enablers for the adoption of Circular Economy practices. The machinery value chain, addressed in this study, is affected by the introduction of digital technologies that enable real-time monitoring data on product condition and control optimization deploying predictive analytics techniques, as well as the offerings of circular-based services. Machinery lifetime extension can be digitally enabled on both old and new machines. The research objectives were to investigate how digital technologies enable the adoption of circular economy-based business models in manufacturing companies and provide an answer about i) what Life Cycle Extension Strategy is suitable for digital circular business model adoption and ii) how digitalization of machines enables manufacturing companies to innovate their business model. The correlation matrix is the tool developed from the proposed approach; it aims at supporting manufacturers in the very first contact with circular business models. In the context of the European RECLAIM project, two manufacturers apply the approach, proving its validity and wide applicability. The next steps are expected to introduce quantitative indicators to define thresholds for the steps toward circularity, without replacing the qualitative approach, as it guarantees the wide applicability of the approach in context that never considered circularity yet.

Feline panleukopenia (FPL), a highly contagious and frequently fatal disease of cats, is caused by Feline parvovirus (FPV) and Canine parvovirus (CPV). We characterized the diversity of these Carnivore protoparvovirus 1 variants in 18 faecal samples collected from domestic cats with FPL during an outbreak, using targeted parvoviral DNA metagenomics to a mean depth of >10,000 X coverage per site. All samples comprised FPV alone. Compared to the reference FPV genome, isolated in 1967, 44 mutations were detected. Ten of these were non-synonymous, including 9 in non-structural genes and one in VP1/VP2 (Val232Ile), which was the only one to exhibit inter-host diversity, being present in five sequences. There were five other polymorphic nucleotide positions, all with synonymous mutations. Intra-host diversity at all polymorphic positions was low with sub-consensus variant frequencies (SVF) of >1% except for two positions (2108 and 3208) in two samples with SVF of 1.1 – 1.3%. Intra-host nucleotide diversity was measured across the whole genome (0.7 - 1.5%) and for each gene, and was highest in the NS2 gene of four samples (1.2 – 1.9%). Overall, intra-host viral genetic diversity was limited and most mutations observed were synonymous, indicative of a low background mutation rate and strong selective constraints.

The main purpose of this work was to tests of form and size of fatigue wear of the top layer of oil gear pump wheel (3PW-BPF-24). The object of tests was operated during a determined number of hours at strictly controlled operational and environmental parameters. A microscope of focal differentiation by Alicona InfiniteFocus G4 (with Focus-Variation optical measuring technology) was used for an identification, measurement and description of noticed superficial defects, which resulted from the fatigue process of the top layer and an earlier thermochemical treatment. The work was finished with an analysis of obtained results (based on the analysis of 3D scans) and conclusions concerning about optimization of the thermal treatment. Taking into consideration the presented results (suggestions) in the technology of improving strength properties of gear wheels (of this type oil pumps) may render it possible to obtain an appropriate fatigue endurance of the top layer, i.e. a minimization of observed superficial defects.

To address the expression pattern of the SARS-CoV-2 receptor ACE2 and the viral priming protease, TMPRSS2, in the respiratory tract, this study investigated RNA sequencing transcriptome profiling of samples of airway and oral mucosa. As shown, ACE2 has medium levels of expression in both small airway epithelium and masticatory mucosa, and high levels of expression in nasal epithelium. The expression of ACE2 is low in mucosal associated invariant T (MAIT) cells, and can’t be detected in alveolar macrophages. TMPRSS2 is highly expressed in small airway epithelium and nasal epithelium, and has lower expression in masticatory mucosa. Our results provide the molecular basis that the nasal mucosa is the most susceptible locus in the respiratory tract for SARS-CoV-2 infection and consequently for subsequent droplet transmission and should be the focus for protection against SARS-CoV-2 infection.

With the increasing societal expectation that animals are afforded greater protection in emergencies, the legal process from entering a property to rescue a companion animal, through to how to dispose of such animals if they remain unclaimed has not been well examined in New Zealand. It is hypothesised that the legal framework for such response is flawed. In this study, each phase of animal disaster rescue is evaluated against four key statues that may apply in each phase, in that does any statute provide clear end to end provisions with clear legal authority to do so. The study found that all statutes evaluated contained flaws and that the current legal provisions are insufficient to provide clear authority for the sequential process of undertaking rescue of animals during emergencies. A major flaw was discovered in the Civil Defence Emergency Management Act 2002 a key statute, that provided for the seizure of property and animals but omitted a procedure for the disposal of such seized things leaving them all in legal limbo. It is recommended that animal disaster laws are updated to be more animal inclusive. The method also may be applicable to assist evaluating animal disaster management legal frameworks in other countries.

Disease transmission in wildlife is linked to ecosystem and human health, and host community structure can mediate pathogen spread. Here, we decompose the well-known susceptible-infected (SI) compartmental models of disease transmission for multi-host communities to explore the disease-biodiversity relationship. We examine the parameters involved in interspecific transmission and link them to the multi-host outbreak potential, R0. We partition R0 into its separate elements that can be associated with either the recipient or donating host, and show how this allows us to identify maintenance versus spillover hosts, allowing us to quantify separate stages of spillover into a novel, recipient host. We further suggest that the evolutionary relatedness between donating and recipient host may play a role in the probability a pathogen establishes in a novel species, as illustrated by the observed phylogenetic signal in the host-breadth of multi-host pathogens. We discuss how anthropogenic changes to the environment and wildlife communities, such as the reduction and fragmentation of wildlife habitat, might alter the mode and dynamics of disease transmission. This discussion contributes to the ongoing debate on the relationship between disease incidence and biodiversity. Through a synthesis of classic ecological theory, we illustrate how pathogens can affect host populations through phenomena such as in/direct symbioses, that can save a pathogen from extinction or suppress competing host species, but we highlight how host diversity can simultaneosuly influence the survival and success of the pathogen, suggesting a complex feedback between hosts and parasites in multi-host communities. Our review provides a guide to common derivations of interspecific transmission, and underscores the critical connections between community and disease-ecology.

Rotavirus (RV) replicates within viroplasms, membrane-less electron-dense globular cytosolic inclusions with liquid-liquid phase properties. In these structures occur the virus transcription, replication, and packaging of the virus genome in newly assembled double-layered particles. The viroplasms are composed of virus proteins (NSP2, NSP5, NSP4, VP1, VP2, VP3, and VP6), single and double-stranded virus RNAs, and host components such as microtubules, perilipin-1 and chaperonins. The formation, coalescence, maintenance, and perinuclear localization of viroplasms rely on their association with the cytoskeleton. A stabilized microtubule network involving microtubules and kinesin Eg5 and dynein molecular motors is associated with NSP5, NSP2, and VP2, facilitating dynamic processes such as viroplasm coalescence and perinuclear localization. Key post-translation modifications, particularly phosphorylation events of RV proteins NSP5 and NSP2, play pivotal roles in orchestrating these interactions. Actin filaments also contribute, triggering the formation of the viroplasms through the association of soluble cytosolic VP4 with actin and the molecular motor myosin. This review explores the evolving understanding of RV replication, emphasizing the host requirements essential for viroplasm formation and highlighting their dynamic interplay within the host cell.

The spread of viral pathogens both between and within hosts is inherently a spatial process. While the spatial aspects of viral spread at the epidemiological level have been increasingly well characterized, the spatial aspects of viral spread within infected hosts are still understudied. Recent experimental studies, however, have started to shed more light on the mechanisms and spatial dynamics of viral spread within hosts. Here, we review these experimental studies as well as the limited number of computational modeling efforts that have begun to integrate spatial considerations for understanding within-host viral spread. We limit our review to influenza virus to highlight key mechanisms affecting spatial aspects of viral spread for pathogens of the respiratory tract. There is considerable empirical evidence for highly spatial within-host spread of influenza virus, yet few computational modeling studies that shed light on possible factors that structure the dynamics of this spatial spread. In existing modeling studies, there is also a striking absence of theoretical expectations of how spatial dynamics may impact the dynamics of viral populations. To mitigate this, we turn to the extensive ecological and evolutionary literature to provide informed theoretical expectations for what viral and host factors may impact the spatial patterns of within-host viral dynamics and for how spatial spread will affect the genetic composition of within-host viral populations. We end by discussing current knowledge gaps related to the spatial component of within-host influenza virus spread and the potential for within-host spatial considerations to inform the development of disease control strategies.

The human body contains 60-70% of water, depending on age. As a body fluid, it is not only a medium in which physical and chemical processes take place, but it is also one of the active mediators. Water is the richest substance with non-covalent hydrogen bonds. Water molecules, by themselves (in vacuum), are diamagnetic, but when organized into clusters, become diamagnetic or paramagnetic. Also, biomolecules (DNA, collagen, clathrin, and other proteins) have non-covalent hydrogen bonds in their structure. The interaction, as well as signal transmission, between water and biomolecules is achieved through the vibrations of covalent and non-covalent hydrogen bonds, which determine the state and dynamics of conformational changes of biomolecules. Disruptive conformational changes of biomolecules, cells, and tissues lead to their dysfunctionality, so they are a frequent cause of many disorders and diseases. For example, the rearrangement of hydrogen bonding due to mitochondrial disease mutation in cytochrome bc1 disturbs heme bH redox potential and spin state. In order to prevent and repair the dysfunctional conformational changes, a liquid substance was developed based on the second derivative of the C₆₀ molecule (SD-C₆₀), which has classical and quantum properties. Characterization of SD-C₆₀ by UV-VIS-NIR, FTIR, TEM, and AFM/MFM was done and it is shown that SD-C₆₀ water layers generate vibrations with near-zero phase dispersion which are transmitted through the Fibonacci’s water chains to biomolecules. In comparison to previously published SD-C₆₀ derivate (3HFWC, size until 10 nm, and 1-5 water layers), improved formulation (3HFWC-W, size 10-25 nm, and 6-9 water layers) showed multiplied cytotoxic activity against melanoma cell lines of different aggressiveness. Apart from this, the mode of action was preserved and based on induction of senescence rather than cell death. Importantly, high selectivity toward malignant phenotype was detected. Observed effects can be ascribed to a machinery of hydrogen bonds, which are generated in SD-C₆₀ and transmitted through water to biomolecules. This approach may open a new field in science and healthcare - a “water-based nanomedicine”.

Elastic bodies entering the water might experience Fluid-Structure Interaction phenomena introduced by the mutual interaction between the structural deformation and the fluid motion. Cavity formation, often misleadingly named cavitation, is one of these. This work presents the results of an experimental investigation on the water entry of deformable wedges impacting a quiescent water surface with pure vertical velocity in free fall. The experimental campaign is conducted on flexible wedges parametrically varying the flexural stiffness, deadrise angle, and drop height. It is found that under given experimental conditions cavity pockets forms beneath the wedge. Their generation mechanism is found to be ruled by a differential between structural and fluid velocities, which is introduced by the structural vibrations. Results show that the impact force during water entry of stiff bodies is always opposing gravity, while in case of flexible bodies might temporarily reverse its direction, with the body that is being sucked into the water within the time frame between the cavity formation and its collapse. Severe impacts might also generate a series of cavity generation and collapses.

Timely mitosis is critically important for the early embryo development. It is regulated by the activity of the ubiquitously conserved CDK1 kinase. The dynamics of CDK1 activation must be precisely controlled to assure physiologic and timely entry into mitosis. Recently, a known S-phase regulator CDC6 emerged as a key player in the mitotic CDK1 activation cascade in early embryonic divisions, operating together with Xic1 as a CDK1 inhibitor upstream of the Aurora A- and PLK1 kinases, both CDK1 activators. Herein we review the molecular mechanisms that underlie the control of the mitotic timing, with special emphasis on how CDC6/Xic1 function impacts CDK1 regulatory network. We focus on the presence of two independent mechanisms inhibiting the dynamics of CDK1 activation: Wee1/Myt1- and CDC6/Xic1-dependent, and how they cooperate with CDK1 activating mechanisms. As a result we propose a comprehensive model integrating CDC6/Xic1-dependent inhibition into the CDK1-activation cascade. The physiological dynamics of CDK1 activation appear to be tuned by the system of multiple inhibitors and activators and their integrated modulation ensures concomitantly both the robustness and certain flexibility of the control of this process. Identification of multiplied activators and inhibitors of CDK1 activation upon M-phase entry allows a better understanding of why cells divide at a specific time, and how the pathways involved in the timely regulation of the cell division are all integrated to precisely tune the control of mitotic events.

With cancer often classified as a disease that has an important epigenetic component, natural compounds that have the ability to regulate the epigenome become ideal candidates for study. Humans have a complex diet, which illustrates the need to elucidate the mechanisms of interaction between these bioactive compounds in combination. The natural compounds withaferin A (WA), from the Indian winter cherry, and sulforaphane (SFN), from cruciferous vegetables, have numerous anti-cancer effects and some report their ability to regulate epigenetic processes. Our study is the first to investigate the combinatorial effects of low physiologically achievable concentrations of WA and SFN on breast cancer cell proliferation, histone deacetylase1 (HDAC1) and DNA methyltransferases (DNMTs). No adverse effects were observed on control cells at optimal concentrations. There was synergistic inhibition of cellular viability in MCF-7 cells and a greater induction of apoptosis with the combinatorial approach than with either compound administered alone in both MDA-MB-231 and MCF-7 cells. HDAC expression was down-regulated at multiple levels. Lastly, we determined the combined effects of these bioactive compounds on the pro-apoptotic BAX and anti-apoptotic BCL-2 and found decreases in BCL-2 and increases in BAX. Taken together, our findings demonstrate the ability of low concentrations of combinatorial WA and SFN to promote cancer cell death and regulate key epigenetic modifiers in human breast cancer cells.

The information about the BCoV receptors, co/receptors that might be involved in the BCoV entry to the host cells is inconceivable. In addition to that, the roles of other host cell proteases, such as Furin and TMPRSS2, have not yet been well studied during BCoV replication. The current study’s main objectives are to identify some novel BCoV receptors and host cell proteases that might fine-tune the BCoV replication, tissue tropism, and molecular pathogenesis. We used a combination of some in silico prediction, molecular docking, and gene expression profile tools to predict some new BCoV receptors out of some known other coronavirus receptors and some host cell enzymes that are potentially involved in BCoV replication. To achieve these goals, we applied the in-silico prediction tools to check the potential interactions between eh BCoV/S glycoprotein and some known coronaviruses receptors (ACE2, APN1, NPR1, CECAM-1, AXL, and DPP4). We also established some potential models for the interaction between the BCoV/S and some common host cell proteases proved to play important roles in other coronavirus replication cycle (Furin, TMPRRS2, and Cathepsin-L). To confirm our prediction models, we assessed the gene expression profiles of these potential receptors and proteases in some bovine cell lines infected with BCoV using the next generation sequencing and the qRT-PCR assay. Our results show that the NPR1, AXL1 and the ACE2 have the strongest and firm binding affinities to the BCoV-S protein. Our prediction models and gene expression profiles show the potential bindings of the Furin and TMPRSS2 to the BCoV-S polybasic cleavage site (RRSRR|A). Notably, high expression of the host cell Furin was observed in response to both BCoV/Ent and BCoV/Resp infection, whereas TMPRSS2 expression was upregulated in the case of the BCoV/Ent infection, positioning Furin as a common receptor for different BCoV isolates. Further research is needed to study the roles of these top-ranked receptors and host cell proteases in molecular pathogenesis, and tissue tropism.

Oncomelania Hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of its habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB), and the ecological stability. Therefore, it is crucial to analyse the influence of climate change on the distribution of O. Hupensis in order to achieve accurate control over its population. This study utilised the MaxENT model to forecast possible snail habitats by utilising snail distribution data obtained from historical literature. The subsequent outcomes were achieved: The primary ecological factors influencing the distribution of O. Hupensis are elevation, minimum temperature of coldest month, and precipitation of wettest month; Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution centre for O. hupensis; Specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest; These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, resulting in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

With this article, impact of effluent mixed water with the quality of the Mansagar Lake has been established by evaluating the physico-chemical parameters and the heavy-metal contents experimentally. The process of calculating water quality and the metal pollution quality indices is also explained in brief with respect to selected sample locations and varied environmental conditions (Pre- and Post-Monsoon season). Distribution trends of Pearson‘s correlation factor have also been discussed to establish their relation among the physico-chemical parameters and the heavy-metal contents for varied environmental conditions. In the end, detailed discussion on observations made during this study and useful recommendations are also elaborated in details. With this article, we intend to present a document for better understanding of the water quality of this lake in view of futuristic management strategies to be adopted to maintain it heritage values.

Hepatitis B Virus (HBV) is a challenge for global health services, affecting millions and leading hundreds to end-stage liver disease each year. This comprehensive review explores the interactions between HBV and the host, examining their impact on clinical outcomes. HBV infection encompasses a spectrum of severity, ranging from acute hepatitis B to chronic hepatitis B, which can potentially progress to cirrhosis and hepatocellular carcinoma (HCC). Occult hepatitis B infection (OBI), characterized by low HBV DNA levels in hepatitis B surface antigen-negative individuals, can reactivate and cause acute hepatitis B. The identification of diverse HBV genotypes reveals distinct geographical distributions and associations with clinical outcomes. Moreover, single nucleotide polymorphisms (SNPs) within the host genome have been linked to several clinical outcomes, including cirrhosis, HCC, OBI, hepatitis B reactivation, and spontaneous clearance. The immune response plays a key role in controlling HBV infection by eliminating infected cells and neutralizing HBV in the bloodstream. Furthermore, HBV can modulate host metabolic pathways involved in glucose and lipid metabolism and bile acid absorption, further influencing disease progression. HBV clinical outcomes correlate with three levels of viral adaptation. In conclusion, the clinical outcomes of HBV infection could result from complex immune and metabolic interactions between the host and HBV. These outcomes can vary among populations and are influenced by HBV genotypes, host genetics, environmental factors, and lifestyle. Understanding the degrees of HBV adaptation is essential for developing region-specific control and prevention measures.

Pancreatic cancer (PC) is one of the most lethal forms of cancers with 5-year mean survival rate of less than 10%. Most of the PC associated deaths are due to metastasis to secondary sites. Calcium (Ca²⁺) signaling plays a critical role in regulating hallmarks of cancer progression including cell proliferation, migration and apoptotic resistance. Store operated Ca²⁺ entry (SOCE) mediated by Orai1/2/3 channels is a highly regulated and ubiquitous pathway responsible for Ca²⁺ influx into non-excitable cells. In this study, we performed extensive bioinformatic analysis of publicly available datasets and observed that Orai3 expression is inversely associated with the mean survival time of PC patients. Orai3 expression analysis in a battery of PC cell lines corroborated its differential expression profile. We then carried out thorough Ca²⁺ imaging experiments in 6 PC cell lines and found that Orai3 forms a functional SOCE in PC cells. Our in vitro functional assays show that Orai3 regulates PC cell cycle progression, apoptosis and migration. Most importantly, our in vivo xenograft studies demonstrate a critical role of Orai3 in PC tumor growth and secondary metastasis. Mechanistically, Orai3 controls G₁ phase progression, matrix metalloproteinase expression and epithelial-mesenchymal transition in PC cells. Taken together, this study for the first time reports that Orai3 drives aggressive phenotypes of PC cells i.e. migration in vitro and metastasis in vivo. Considering that Orai3 expression is inversely associated with the PC patients survival time, it appears to be a highly attractive therapeutic target.

The coronavirus disease 2019 (COVID-19) was officially declared a pandemic on the 11^th March 2020. It is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), impacting the lower respiratory tract. International travel to Australia during the early stages of the pandemic prior to border closure provided avenues for this virus to spread into Australia. There is little understanding of the clonality of SARS-CoV-2 isolates in Australia, and where they originated. This study aimed to investigate the clonality and ancestral sources of SARS-CoV-2 isolates in Australia using in silico methods. We retrieved 1,346 complete genomes from Australia along with 153 genomes from other countries from the NCBI nucleotide database and Global Initiative On Sharing All Influenza Data (GISAID). We then constructed a representative population of 270 sequences for downstream phylogenetic analysis and ancestral area reconstruction. Overall, two major clusters, one stemming from Europe and another from Asia, especially East Asia, were observed, implying at least two major transmission events with subsequent clades confirming the multiclonality of Australian isolates. We also identified three potential dissemination routes of SARS-CoV-2 into Australia. This study supports the hypothesis of multiple clonality and dispersals of SARS-CoV-2 isolates into Australia.

Little phylogeographic structure is presumed for highly mobile species in pelagic zones. Lake Tanganyika is a unique ecosystem with a speciose and largely endemic fauna famous for its remarkable evolutionary history. In bathybatine cichlid fishes, the pattern of lake-wide population differentiation differs among species. We tested the magnifying glass hypothesis for their parasitic flatworm Cichlidogyrus casuarinus. Lake-wide population structure of C. casuarinus ex Hemibates stenosoma was assessed based on a portion of the mtCOI gene combined with morphological characterisation. Additionally, intraspecific mitogenomic variation among 80 individuals within one spatially constrained parasite metapopulation sample was assessed using shotgun NGS. While no clear geographic genetic structure was detected in parasites, both geographic and host-related phenotypic variation was apparent. The incongruence with the genetic north-south gradient observed in the host may be explained by the broad host range of this flatworm as some of its other host species previously showed no lake-wide restriction of gene flow. Our results are consistent with host driven morphological variation without genetic differentiation of the parasite, and highlight the importance of integratively approaching parasites` potential as “tags” for their hosts. We present the first parasite mitogenome from Lake Tanganyika and propose a methodological framework for studying intraspecific mitogenomic variation of dactylogyrid monogeneans.

The Fusarium fujikuroi species complex (FFSC) includes socioeconomically important pathogens that cause disease and/or mycotoxin contamination on numerous crops. Here, we used comparative genomics to elucidate processes underlying the ability of pine-associated and grass-associated FFSC species to colonize tissues of their respective plant hosts. We characterized the identity, possible functions, evolutionary origins, and chromosomal positions of the host-range-associated genes encoded by the two groups of fungi. The 72 and 47 genes identified as unique to the respective genome groups were potentially involved in diverse processes, ranging from transcription, regulation, and substrate transport, through to virulence/pathogenicity. Most emerged early during the evolution of Fusarium/FFSC and were subsequently retained only in some lineages, while some had origins outside Fusarium. Although differences in the densities of these genes were especially noticeable on the conditionally dispensable chromosome of F. temperatum (representing the grass-associates) and F. circinatum (representing the pine-associates), the host-range-associated genes tended to be located towards the subtelomeric regions of chromosomes. Taken together, these results demonstrate that multiple mechanisms drive the emergence of genes in grass- and pine-associated FFSC taxa examined and highlighted the diversity of molecular processes potentially underlying niche-specificity in these and other Fusarium species.

Recently, two pig-to-human kidney transplants and a pig-to-human heart transplant were completed. The kidney trials involved a patient who was deceased and a patient who was brain dead. They seemed to indicate that pig kidneys can be at least somewhat functional in humans. However, patients still have to be under severe immunosuppression - and the first patient to receive a porcine heart passed away after two months. It is difficult to know exactly which proteins we need to overexpress or underexpress/knockout in a porcine organ to negate the human recipient’s immunological response to it. And testing different porcine organ genetic modifications in baboons can cost around $500,000 per transplant. But there might be a way to decrease immunogenicity where we don’t have to worry so much about modifying the animal’s organs genetically. First, however, we would have to prevent complement factor-mediated lysis of the porcine vascular endothelial cells, which we have made much progress on with triple knockout animals. Then, we could modify the porcine organ so that the cells of said organ secrete a small molecule or peptide that acts as a chemorepellent for the host immune cells. The host immune cells can be modified via bone marrow transplant or vector delivery to express the chemorepulsion receptor.

Bacteria participate in a wide diversity of symbiotic associations with eukaryotic hosts that require precise interactions for bacterial recognition and persistence. Most commonly, host-associated bacteria interfere with host gene expression to modulate the immune response to the infection. However, many of these bacteria also interfere with host cellular differentiation pathways to create a hospitable niche, resulting in the formation of novel cell types, tissues, and organs. In both of these situations, bacterial symbionts must interact with eukaryotic regulatory pathways. Here, we detail what is known about how bacterial symbionts, from pathogens to mutualists, control host cellular differentiation across the central dogma, from epigenetic chromatin modifications, to transcription and mRNA processing, to translation and protein modifications. We identify four main trends from this survey. First, mechanisms for controlling host gene expression appear to evolve from symbionts co-opting cross-talk between host signalling pathways. Second, symbiont regulatory capacity is constrained by the processes that drive reductive genome evolution in host-associated bacteria. Third, the regulatory mechanisms symbionts exhibit correlate with the cost/benefit nature of the association. And, fourth symbiont mechanisms for interacting with host genetic regulatory elements are not bound by native bacterial capabilities. Using this knowledge, we explore how the ubiquitous intracellular Wolbachia symbiont of arthropods and nematodes may modulate host cellular differentiation to manipulate host reproduction. Our survey of the literature on how infection alters gene expression in Wolbachia and its hosts revealed that, despite their intermediate-sized genomes, different strains appear capable of a wide diversity of regulatory manipulations. Given this and Wolbachia’s diversity of phenotypes and eukaryotic-like proteins, we expect that many symbiont-induced host differentiation mechanisms will be discovered in this system.

The hard bottom layer of paddy field has a great influence on the driving stability and operation quality and efficiency of intelligent farm machinery, and the continuous improvement of unmanned precision operation accuracy and operation efficiency of paddy field operation machin-ery is the support to realize unmanned rice farm. In this paper, in view of the complicated hard bottom layer situation of unmanned operation farm machinery driving is difficult to realize to quantify the local characteristics of hard bottom layer of paddy field, the unmanned rice direct seeding machine chassis is used to operate the operation field and collect the hard bottom layer information simultaneously, and the data processing method of automatic calibration of sensor installation error, abnormal value rejection and 3D sample curve denoising of contour trajectory is designed; a hard bottom layer surface profile evaluation method based on the local sliding surface roughness is proposed. The local characteristics of the hard bottom layer were quantified, and the quantified results of the local characteristics of the hard bottom layer in the test plots showed that the mean value of the local roughness was 0.0065, 68.27% was distributed in the variation range of 0.0042~0.0087, and 99.73% was distributed in the variation range of 0~0.0133. Based on the test field data, the surface roughness features are verified to describe the variability of representative working conditions such as transport, downfield, operation and trapping of unmanned operation of intelligent farm machinery. The method of quantifying the hard-bottom local features of farm machinery driving can provide feedback on the local environmental features of intelligent farm machinery driving at the current position, and provide a reference basis for the design optimization of unmanned system for improving the quality of intelligent farm machinery operation.

Insect herbivores have a wide range of life cycles and feeding habits, making them extremely diverse. With their host plants, they form close relationships and suppress their defense mecha-nisms. Molecular elicitors are the key bio-elements in detection and recognition of attacking enemies in tissue consumption. Insect oral secretion, frass, and fluid of egg deposition contain bio-logical active molecules called herbivore-associated elicitors (HAEs) are recognized by pattern recognition receptors (PRRs). However, in insect herbivores, little is known about the molecular basis of signal transduction and regulation of plant resistance. Many plants distinguish insect feeding from wounding by HAEs presenting in their oral secretions (OS) and induce local and systemic responses against arthropod feeding. PRRs perceive HAEs in the oral secretion of cater-pillars in a species-specific manner to elicit exclusive defense responses. HAEs-PRRs interactions induce plant resistance by reprogramming plant metabolism and transcriptional machinery. Quantitative, timely, and coordinated plant response initiate early signalling events including Ca+2, reactive oxygen species (ROS) and mitogen-activated protein kinases (MAPKs). We have discussed how early signalling cascades converge into the accumulation of phytohormones that regulate down-stream special metabolites against herbivores. In this review, we have drawn a hypothetical model of PPRs-HAEs mediated induced responses in plants and discussed how PRRs-HAEs interactions based on molecular mechanism that elicit short- and long-term induced defenses in plants. The identification of plant target insect herbivore PRRs-HAEs interactions will help to explore the fundamental molecular mechanisms of host manipulation and may generate prospects to develop novel pest resistance strategies.

The global pandemic of COVID-19 accounts for more than 14,000 deaths worldwide. However, little is known about the host genetics interaction with infection and COVID-19 progression. To better understand the role of host genetics, we review the current literature, aggregate readily available genetic resources, and provide some updated analysis relevant to COVID-19 and associated phenotypes. Using the unrelated individuals in UK Biobank (total n = 337,579 across 5 populations), we aggregate human leukocyte antigen and ABO blood type frequencies. We find significant and consistent risk reduction of blood group O reported in Zhao et al. and encourage broad sharing of ABO blood type frequencies that are readily accessible across COVID-19 with mild, moderate, and severe/critical symptoms for robust inferences at https://tinyurl.com/abo-covid19. In addition, we generate polygenic risk scores (PRSs) weights for 29 blood measurements, including clinically relevant haematological measurements for COVID-19, such as lymphocyte count and percentage. Focusing on the 8 most COVID-19 clinically relevant blood measurements, we performed PRS-PheWAS analysis across 44 disease antigen measurements (n = 6,643 unrelated individuals in White British group), infectious diseases and acute respiratory infections (n = 20,928 cases and 349,000 controls across 3 population groups) and deaths (n = 1,846 cases and 368,082 controls), recorded in hospital inpatient record and death registry data, respectively, in UK Biobank, and find host genetic PRS associations with disease risk. Taken together, we anticipate these resources (https://github.com/rivas-lab/covid19) will aid in improving our understanding of host genetic risk factors playing a role in SARS-CoV-2 infection and COVID-19 disease severity.

Recently, it was confirmed that ACE2 is the receptor of 2019-nCoV, the pathogen causing the recent outbreak of severe pneumonia in China. It is confused that ACE2 is widely expressed across a variety of organs and is expressed moderately but not highly in lung, which, however, is the major infected organ. It remains unclear why it is the lung but not other tissues among which ACE2 highly expressed is mainly infected. We hypothesized that there could be some other genes playing key roles in the entry of 2019-nCoV into human cells. Here we found that AGTR2 (angiotensin II receptor type 2), a G-protein coupled receptor, has interaction with ACE2 and is highly expressed in lung with a high tissue specificity. More importantly, simulation of 3D structure based protein-protein interaction reveals that AGTR2 shows a higher binding affinity with the Spike protein of 2019-nCov than ACE2 (energy score: -15.7 vs. -6.9 [kcal/mol]). Given these observations, we suggest that AGTR2 could be a putative novel gene for the the entry of 2019-nCoV into human cells but need further confirmation by biological experiments. Finally, a number of compounds, biologics and traditional Chinese medicine that could decrease the expression level of AGTR2 were predicted.

Host immunological pathways have been proposed including TH1, TH2, TH3, TH9, TH17, TH22, TH1-like, and THαβ immune reactions. Besides TH2 and TH9 immune responses which are against multicellular parasites, host immunological pathways against viruses, intracellular micro-organisms (bacteria, protozoa, and fungi), and extracellular micro-organisms can use programmed cell death pathways to trigger immune reactions or to execute effective strategies to eliminate these pathogens. These programmed cell deaths include apoptosis, autophagic death, pyroptosis, ferroptosis, necroptosis, and NETosis. Apoptosis is related to host anti-virus eradicable THαβ immunity. Autophagic death is related to host anti-virus tolerable TH3 immunity. Pyroptosis is related to host anti-intracellular micro-organism eradicable TH1 immunity. Ferroptosis is related to host anti-intracellular micro-organism tolerable TH1-like immunity. Necroptosis is related to host anti-extracellular micro-organism eradicable TH22 immunity. NETosis is related to host anti-extracellular micro-organism tolerable TH17 immunity.

Begomovirus infection in plant causes a great economic loss in many countries every year. Increasing rate of the infectivity of this single stranded DNA virus forces to study of its transmission in detail for the necessary researches regarding the control of this disease. This pathogenic virus is whitefly vector borne and transferred from one plant to another plant during the suckling of phloem sap by that vector. Viral transmissibility through this insect vector may depend on the genetic variations within the cryptic species groups. Two distinct categories of begomoviruses viz., bipartite and monopartite types consist of different genome organization. Virion particles modify the intracellular environment of the host according to their need of replication and survival. Viral replication takes place through RCR as well as RDR methods. Interplay among host, vector and pathogen is crucial for the establishment of infection. Several endosymbiotic organisms living within the insect vector also have vital role here. Being infected with this virus, host plant responds with defensive activities like TGS, PTGS, autophagy, hormonal regulation, metabolic alteration etc. However, virus also counteracts those through the manipulation of several pathways of cellular events. It is necessary to study in different directions and utilize advanced molecular biological techniques to develop begomovirus resistance within plants.

In addition to CD4+ T lymphocytes, myeloid cells, and, particularly, differentiated macrophages, are targets of the human immunodeficiency virus type-1 (HIV-1) infection via interaction of gp120Env with CD4 and CCR5 or CXCR4. Both T cells and macrophages support virus replication although with substantial differences. In contrast to activated CD4+ T lymphocytes, HIV-1 replication in macrophages occurs in nondividing cells and it is characterized by virtual absence of cytopathicity both in vitro and in vivo. These general features should be considered in evaluating the role of cell-associated restriction factors aiming at preventing of curtailing virus replication in macrophages and T cells particularly in the context of designing strategies to tackle the viral reservoir in infected individuals receiving combination antiretroviral therapy. In this regard, we will here also discuss a model of reversible HIV-1 latency in primary human macrophages and the role of host factor determining restriction or reactivation of virus replication in myeloid cells.

Nicotiana benthamiana plants infected with a potato virus Y isolate (PVYO) under ambient conditions of 25 °C and ~405 parts-per-million (ppm) ambient CO2 display symptoms of chlorosis, leaf curling, and stunting. However, under elevated temperature and CO2 levels (30 °C, 970 ppm), systemic viral titers decrease several-fold, and plants appear asymptomatic. Under the latter conditions we have studied how infection, drought, or both combined affect infection, drought-driven loss of leaf turgor, plant water content, stomatal conductance, metabolome, and hormone (ABA, SA, and JA) levels. We found that drought did not affect viral titers. As expected, drought decreased plant water content and stomatal conductance. Under drought conditions, infection did not alter significantly final water content or loss of leaf turgor progression, but it increased the levels of some sugars and other osmo-protectants. Infection and drought altered the levels of many components of the metabolome. Some components altered by infection were not altered by drought, but most of those altered by drought were also altered by infection. Drought increased the levels of ABA, infection increased the levels of ABA, SA, and JA, and altered their relative balance. The effects of drought and of infection on hormone levels were cumulative when combined. Thus, under ambient conditions that turn a severe infection into an asymptomatic one both, plant physiology parameters and the interplay with drought are affected.

Chondroitin is a glycosaminoglycan that has gained widespread use in nutraceuticals and pharmaceuticals, mainly for treating osteoarthritis. Traditionally, it has been extracted from animal cartilage but recently, biotechnological processes have emerged as a commercial alternative to avoid the risk of viral or prion contamination and offer a vegan-friendly source. Typically, these methods involve producing the chondroitin backbone using pathogenic bacteria and then modifying it enzymatically through the action of sulfotransferases. Despite the challenges of expressing active sulfotransferases in bacteria, the use of eukaryotic microorganisms is still limited to a few works using Pichia pastoris. To create a safer and efficient biotechnological platform, we have constructed a biosynthetic pathway for chondroitin production in S. cerevisiae as a proof-of-concept. Up to 125 mg/L and 200 mg/L of intracellular and extracellular chondroitin were produced, respectively. Furthermore, as genome-scale models are valuable tools for identifying novel targets for metabolic engineering, a stoichiometric model of chondroitin-producing S. cerevisiae has been developed and used in optimization algorithms. Our research has yielded several novel targets, such as uridine diphosphate(UDP)-N-acetylglucosamine pyrophosphorylase (QRI1), glucosamine-6-phosphate acetyltransferase (GNA1) or N-acetylglucosamine-phosphate mutase (PCM1) overexpression that might enhance chondroitin production, which will guide future experimental research to develop more efficient host organisms for the biotechnological production process.

The recent Zika virus (ZIKV) outbreak in Americas surprised all of us because of its rapid spread and association with neurologic disorders including fetal microcephaly, brain and ocular anomalies and Guillain-Barré syndrome. In responding to this global health outcry, unprecedented and world-wide efforts are taking place to study the ZIKV etiology. Much have been learned about this virus in the areas of epidemiology, clinical manifestation, viral sequences and protein structures, as well as effects of ZIKV infection on fetal brain development and microcephaly. However, the molecular mechanism underlying ZIKV-mediated neurologic disorders remains elusive. Some critical questions include: 1) what type of virologic changes has taken place that increased the viral virulence? 2) which ZIKV protein(s) is responsible for the enhanced viral pathogenicity? And 3) how the newly adapted and pathogenic ZIKV strains alter their interactions with host cells leading to neurologic disorders? The goal of this review is to explore the molecular insights into the ZIKV-host interactions with special focuses on host cell receptor usage for viral entry, host cellular and immune antiviral responses, ZIKV counteraction and ZIKV-induced cytopathic effects. Our hope with this literature review is to inspire additional studies focusing on molecular studies of ZIKV-host Interactions.

Proteases are integral enzymes of the plant immune system. Multiple aspects of defence are regulated by proteases, including the hypersensitive response, pathogen recognition, priming and peptide hormone release. These processes are regulated by unrelated proteases residing at different subcellular locations. In this review we discuss ten prominent plant proteases contributing to the plant immune system, highlighting the diversity of roles they perform in plant defence.

Patients from regions without stem cell transplant (SCT) facilities often seek treatment abroad and return home for post-transplant care. While extensive data exists on GVHD and its risk factors, the prevalence of GVHD in international SCT patients returning to countries without transplant facilities, where multiple factors compromise post-transplant care, is not well documented. We screened 149 transplant recipients and analyzed data from 91 who received transplants abroad and were followed at our center from January 2019 to December 2022. This observational study used data from electronic medical records (EMR) and employed descriptive statistics, inferential tests, and relative risk calculations with forest plots to analyze GVHD prevalence and key risk factors. Of the recipients, 31.8% were residents from nine countries living in the UAE, and 67.2% were UAE citizens. Adults comprised 48.3% of the recipients, and 51.7% were pediatric. Hematological malignancies were the most common indication (49%), primarily in adults. Siblings were the majority of donors (52.6%), followed by related donors (23.09%), and unrelated donors (8.9%). Most (69.2%) received HLA-identical transplants followed by 21.9% who received haploidentical. Among adults, 62.2% developed GVHD, compared to 26% of pediatric patients. Recipients with related HLA-identical donors had a 50% GVHD prevalence, while those with unrelated identical donors had 71%. The overall GVHD prevalence was 50% among the 87.9% who received allogeneic SCTs. Despite favorable factors, GVHD prevalence remains high. Larger multicenter studies are needed to identify and assess the impact of contributing factors.

The computational model that is able to estimate the temperature distribution inside a solid specimen during the film boiling phase of immersion quenching (water entry) process has been presented in paper, and it is based on the prescribed initial temperatures of the solid specimen and the liquid quenchant. In addition, the turbulence effects have to be considered using the assumed turbulence kinetic energy value, i.e., the “frozen turbulence” approach, that remains constant thorough the simulation. The studied material is nickel alloy, Inconel 600, for which the extensive experimental data is available. The work has been carried out using ANSYS Fluent computational fluid dynamics software and the methods for solution of Stefan problem by Eulerian two fluid VOF model.. A satisfactory agreement between the experimental and the calculated data has been achieved, yielding thereby the computationally obtained data that fits to a great extent to the prescribed error band of ± 10 % during the estimated film boiling phase of the immersion quenching process itself.

In silico analysis is a promising approach for understanding biological events in complex diseases. Herein, we report an in silico analysis of the entire genome of virus ZikaSPH2015 strain, which was performed in order to identify the occurrence of specific motifs on genomic sequence of Zika Virus that is able to bind and therefore, sequester host’s Transcription Factors (TFs) as well as subsequently predict a possible interactions within host genome. Accordingly to obtained results of this original computational work-flow it is possible to hypothesize that these TFs Binding Motifs might be able to explain the complex and heterogeneous phenotype presentation in Zika Virus affected fe-tus/newborns, as well as the less severe condition in adults. Moreover, the proposed in silico protocol identified thirty three different TFs same as the distribution of TFBSs (Transcription Factor Binding Sites) on ZikaSPH2015 strain, potentially able to influence genes and pathways with biological functions confirming that this approach could find potential answers on disease pathogenesis.

Recently scientific research began to shift their focus on looking at both the gut and the skin microbiota as having a reciprocal and integral relationship with one another, rather than assessing them as separate and unrelated fields. In the past five years, the field of microbial endocrinology emerged, which examines how our gut microbiota influences and modulates hormones. We’ve known for decades that hormones greatly affect the condition of the skin, and many skin conditions are often treated with oral hormonal therapy as means to internally treat skin conditions visible on the dermis. Now, a growing body research and discourse examining this triad of biological spheres – gut microbiota, skin microbiota, and the endocrine system – as interconnected rather than binary and unrelated. While there is ample research established and being conducted examining the gut-skin axis, the gut-brain axis, and the gut-hormone axis, through this paper I will review and synthesize some of the significant advancements in this emerging and inclusive field of science to suggest that the fields need to expand the axis and their modality for researching these fields as a connected whole in order to better understand the role of the microbiota in disease prevention as a whole.

The dietary pattern that characterizes the Western diet is strongly associated with obesity and related metabolic diseases, but biological mechanisms supporting these associations remain largely unknown. We argue that the Western diet promotes inflammation that arises from both structural and behavioral changes in the resident microbiome. The environment created in the gut by ultra-processed foods, a hallmark of the Western diet, is an evolutionarily unique selection ground for microbes that can promote diverse forms of inflammatory disease. Recognizing the importance of the microbiome in the development of diet-related disease has implications for future research, public dietary advice as well as food production practices. Research into food patterns suggests that whole foods are a common denominator of diets associated with a low level of diet-related disease. Hence, by studying how ultra-processing changes the properties of whole foods and how these foods affect the gut microbiome, more useful dietary guidelines can be made. Innovations in food production should be focusing on enabling health in the super-organism of man and microbe, and stronger regulation of potentially hazardous components of food products is warranted.

Background: The implementation of tyrosine kinase inhibitors (TKIs) in the treatment of chronic myeloid leukemia (CML) has brought a significant improvement in the prognosis for CML patients and a decrease in the number of patients requiring allogeneic hematopoietic stem cell transplantation (allo-HCT). Nevertheless, the impact of TKIs on allo-HCT outcomes have not been thoroughly explored. Objectives: The main endpoint of our research was to assess the impact of prior TKI treatment on acute graft-versus-host disease (aGvHD) and chronic graft-versus-host disease (cGvHD). Methods: In our retrospective analysis we included 240 patients treated between 1993 and 2013, and divided them into 3 groups according to the therapy administered prior to matched related or matched unrelated donor allo-HCT (imatinib group n=41, dasatinib/nilotinib group n=28, TKI naïve group n=171). Results: Both the cumulative incidence of aGvHD (p=0.044) and cGvHD (p<0.001) in individuals receiving second generation TKIs (2G-TKIs) prior to allo-HCT compared to patients receiving no TKIs or imatinib (IMA) (40.7% vs 61.4% vs 70.7%, p=0.044; 25.0% vs 76.4% vs 51.2%, p<0.001, respectively). In case of the 2G-TKI cohort, the number of low-grade aGvHD and cGvHD was significantly lower compared to the IMA and TKI-naïve groups (p=0.018, p=0.004; p<0.001 versus TKI-naïve, respectively). In terms of 3-year overall survival (OS) there were no important variations between TKI-naïve, IMA and 2G-TKI (55% vs 49.9% vs 69.6%, p=0.740). Conclusions: The results of our study suggest that TKI treatment prior to allo-HCT may have protective impact on immune-mediated outcomes.

The recurrent coronavirus outbreaks in China (SARS-CoV and its relative, SARS-CoV-2) have raised speculations that perhaps Asians are somehow more susceptible to these coronaviruses. Here, we test this possibility based on an analysis of the lung-specific expression of ACE2, which encodes the known cell-entry receptor of both SARS-CoV and SARS-CoV-2. We show that ACE2 expression is not affected during tumorigenesis, supporting that the abundant transcriptomes in cancer genomic studies can be informatively used to study ACE2 expression among diverse individuals without cancer. We find that ACE2 expression in the lung increases with age, but is not associated with sex. Further, Asians do not differ from other populations for ACE2 expression and do not harbor unique genetic polymorphisms in the ACE2 locus. Thus, beyond illustrating an innovative method for assessing the potential impacts of demographic factors for non-cancer diseases from large-scale cancer sample datasets, our statistically robust findings emphasize that individuals of all races require the same level of personal protection against SARS-CoV-2.