Quantum gravity theories rely on a minimal measurable length for their formulations, which clashes with the classical formulation of the uncertainty principle and with Lorentz invariance from general relativity. These incompatibilities led to the development of the generalized uncertainty principle (GUP) from string theories and its various modifications. GUP and covariant formulations of the uncertainty principle are discussed, together with implications for space-time quantization.

Streptococcus agalactiae is a highly contagious Gram- positive bacterium that causes mastitis, has a high infectivity for mammary epithelial cells, and is challenging to treat. However, the molecular interactions between it and mammary epithelial cells remains poorly understood. This study analyzed differential gene expression in mammary epithelial cells with varying levels of S. agalactiae infection using UID- Dual Seq and bioinformatics tools. This study identified 211 differentially expressed mRNAs (DEmRNAs) and 452 differentially expressed lncRNAs (DElncRNAs) in host cells, primarily enriched in anti-inflammatory responses, immune responses, and cancer-related processes. Additionally, 854 pathogen differentially expressed mRNAs (pDEmRNAs) were identified, mainly enriched in protein metabolism, gene expression, and biosynthesis processes. Mammary epithelial cells activate pathways, such as the ERK1/2 pathway to produce, to produce reactive oxygen species (ROS) to eliminate bacteria. However, the bacteria disrupt the host's innate immune mechanisms by interfering with the alternative splicing processes of mammary epithelial cells. Specifically, the bacterial genes of tsf, prfB, and infC can interfere with lncRNAs targeting RUNX1 and BCL2L11 in mammary epithelial cells, affecting the alternative splicing of target genes and altering normal molecular regulation.

Black barley seeds are a health-beneficial diet resource because of their special chemical composition and antioxidant properties. The black lemma and pericarp (BLP) locus was mapped in a genetic interval of 0.807 Mb on chromosome 1H, but its genetic basis remains unknown. In this study, targeted metabolomics and conjunctive analyses of BSA-seq and BSR-seq were used to identify candidate genes of BLP and the precursors of black pigments. The results revealed that five differentially expressed genes identified on the 1H chromosome were candidate genes of the BLP locus, and 17 differential metabolites, including the precursor and repeating unit of allomelanin, were accumulated in the grain-filling stage of black barley. Phenol nitrogen-free precursors such as catechol (protocatechuic aldehyde) or catecholic acids (caffeic, protocatechuic, and gallic acids) may promote black pigmentation. BLP can manipulate the accumulation of benzoic acid derivatives (salicylic acid, 2,4-dihydroxybenzoic acid, gallic acid, gentisic acid, protocatechuic acid, syringic acid, vanillic acid, protocatechuic aldehyde, and syringaldehyde) through the shikimate/chorismite pathway other than the phenylalanine pathway and alter the metabolism of the phenylpropanoid-monolignol branch. Collectively, it is reasonable to infer that black pigmentation in barley is due to allomelanin biosynthesis in lemma and pericarp, and BLP regulates melanogenesis by manipulating the biosynthesis of its precursors.

The number of physical devices connected to the Internet such as vehicles, household appliances and other "things" has been steadily increasing in recent years, thus forming the basis for the Internet of Things (IoT). IoT ecosystem extends beyond country borders and application domains, combining thousands of versatile devices that differ in terms of their structures, capabilities, and available resources. It is therefore not surprising that the landscape of wireless communication technologies and the degree of IoT devices available today is excessively broad and diverse. Interference between networks leads to frame collisions and consequent packet loss. Frame collisions occur when two or more packets overlap in time and frequency and use the same Long Range (LoRa) parameters, i.e. the same Spreading Factor (SF), Bandwidth (BW) and Carrier Frequency (CF). When most devices use the same configuration, collision probability is higher. The probability of frame collisions is also affected by traffic characteristics, particularly the periodicity of the transmission and the payload size. Larger payload sizes and more frequent transmissions accumulate with higher Time on Air (ToA) and channel occupancy [1]. Transmission powers and the location of the gateways also influences this situation. The aim of this experimental work is to verify the effects of collisions and interference in Long Range Wide Area Network (LoRaWAN), regarding the periodicity of transmissions and the payload sizes in a context of an inter-SF interference scenario. And to validate measuring tools like Received Signal Strength Indicator (RSSI), ToA and Packet Delivery Ratio (PDR) in the reliability of a network. We validate our conclusions by analyzing ToA according with RSSI and different data sizes, the RSSI for different SFs and different data sizes and finally the packet loss through the PDR for a better understanding of the reliability of packet transmission in our link. In the end we conclude that in an environment with inter-SF interference, the choice of SFs and packet lengths impacts ToA. When dealing with multiple devices near gateways, different SFs and varying packet lengths can lead to increased latency and longer ToA. Consequently, the risk of packet loss becomes more significant, especially if the signal-to-interference ratio (SIR) is low. This limitation will therefore affect scalability, particularly in Non-Line-Of-Sight (NLOS) scenarios.

Abstract: (1) Background: Cancer immune escape is associated with the metabolic reprogramming of TME, and combining metabolic targets with immunotherapy has great potential to improve clinical outcomes. Among all metabolic processes, lipid metabolism, especially fatty acid (FA) metabolism, has a huge role in cancer cell survival, migration, and proliferation, but its mechanism and role in the tumor immune microenvironment remain to be investigated. (2) Methods: We comprehensively analyzed 309 fatty acid-related genes, screened 121 different genes, and used one-way COX regression to select 15 genes with prognostic impact. Systematically evaluated the correlation between FMGs modification patterns and Tumor Microenvironment Infiltration, prognosis, and Immunotherapy. The FMGs-Score was constructed to quantify the FMGs modification patterns using principal component analysis. (3) Results: Three clusters based on FMGs-related genes were demonstrated in breast cancer, with three patterns of distinct immune cell infiltration and biological behavior. An FMGsScore signature was constructed to reveal that patients with a low FMGsScore had higher immune checkpoint expression, higher immune checkpoint inhibitor (ICI) scores, increased immune microenvironment infiltration, better survival advantage, and were more sensitive to immunotherapy than those with a high FMGsScore. Finally, the expression and function of the signature key gene NDUFAB1 were examined by in vitro experiments. (4) Conclusions: This study significantly demonstrates the non-negligible role of FMGs in the immune microenvironment of breast cancer, and that FMGsScores can be used to guide the prediction of immunotherapy in breast cancer patients. In in vitro experiments, knockdown of the NDUFAB1 gene resulted in reduced proliferation and migration of MCF-7 cell lines.

Gene regulation is vital for cellular function and homeostasis, involving diverse mechanisms controlling specific gene products and contributing to tissue-specific gene expression. Dysregulation leads to diseases, emphasizing the need for understanding these mechanisms. Non-coding regions, notably enhancers and super-enhancers (SEs), act as crucial gene regulators, orchestrating transcriptional activity via transcription factors (TFs). SEs, with high activity, are pivotal in cell identity and disease progression. Current computational approaches focus on individual regulators like TFs and miRNAs, neglecting SE interactions. We emphasize incorporating SEs into models to enhance understanding. Experimental studies have recently linked miRNAs and TFs to SEs. Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) provides valuable SE information. In this review, we categorize computational methods leveraging TF and miRNA data into three areas and explore challenges integrating enhancers/SEs. These include unraveling indirect regulatory networks, identifying network motifs, and enriching pathway identification by dissecting gene regulators, including SEs. We hypothesize that addressing these challenges will enhance our understanding of gene regulation, aiding in identifying therapeutic targets and disease biomarkers. We believe that understanding the role of ChIP-Seq data in predicting the effect of miRNA on gene regulation is crucial to construct statistical/computational model that would tackle these challenges.

Photoplethysmography is a widely used technique to noninvasively assess heart rate, blood pressure, and oxygen saturation. This technique has a large potential for further applications, for example in the field of physiological and mental health monitoring. However, advanced applications of photoplethysmography have been hampered by the lack of accurate and reliable methods to analyze the characteristics of the complex nonlinear dynamics of the photoplethysmogram. Methods of nonlinear time series analysis may be used to estimate the dynamical characteristics of the photoplethysmogram but they are highly influenced by the length of the time series, which is often limited in practical photoplethysmography applications. The aim of this study was to evaluate the error in the estimation of the dynamical characteristics of the photoplethysmogram associated to the limited length of the time series. The dynamical properties were evaluated using recurrence quantification analysis, and the estimation error was computed as a function of the length of the time series. Results demonstrated that properties such as de-terminism and entropy can be estimated with an error lower than 1% even for short photople-thysmogram recordings. Additionally, the lower limit for the time series length to estimate the average prediction time was computed.

Solanesol is a noncyclic terpene alcohol composed of nine isoprene units and it mainly accumulates in solanaceous plants, especially tobacco (Nicotiana tabacum L.). Here, RNA-seq analyses of tobacco leaves, stems, and roots were used to identify solanesol biosynthesis genes. Six 1-deoxy-d-xylulose 5-phosphate synthase, two 1-deoxy-d-xylulose 5-phosphate reductoisomerase, two 2-C-methyl-d-erythritol 4-phosphate cytidylyltransferase, four 4-diphosphocytidyl-2-C-methyl-d-erythritol kinase, two 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase, four 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase, two 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase, six isopentenyl diphosphate isomerase, and two solanesyl diphosphate synthase (SPS) genes were identified to be involved in solanesol biosynthesis. Furthermore, the two N. tabacum SPS (NtSPS1 and NtSPS2), which had two conserved aspartate-rich DDxxD domains, were highly homologous with SPS enzymes from other solanaceous plant species. In addition, the solanesol contents of three organs, and leaves from four growing stages, corresponded with the distribution of chlorophyll. Our findings provide a comprehensive evaluation of the correlation between the expression of different biosynthetic genes and the accumulation of solanesol in tobacco.

In the realm of physical activity and sports science, motion tracking emerges as an important tool for specialists aiming to analyze movement data, whether for daily life activities or enhancing athletic performance. This study introduces an innovative approach to motion tracking through the development of a fully embedded smart shoe sensor system, which employs an inertial measurement unit (IMU) affixed to the shoe sole, coupled with six pressure sensors, to provide real-time calculation of individual stride lengths along with other vital movement statistics. Traditional motion tracking methods, which typically rely on various body-attached sensors, often necessitate substantial post-processing, delaying the feedback loop. In contrast, our system is designed to overcome these limitations by offering high-accuracy, real-time feedback with a minimal error rate of 1.88% from our experiments. Such prompt data acquisition facilitates immediate interventions by sports performance coaches or healthcare professionals, significantly contributing to injury prevention and performance enhancement. The experimental outcomes of this study underscore the system’s capability to deliver precise stride length measurements instantaneously, marking a significant advancement in motion tracking technology and its application in sports science and healthcare.

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole. Letrozole inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. Letrozole resistance is increasingly being observed, which poses a unique problem for patients. We reanalyzed transcriptomic data comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two genes that significantly differed between these patients; with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 as the top transcriptional biomarkers for ER+ treatment resistance. Many of the other significant gene products play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified do not have a characterized role in ER+ breast cancer. Our analysis identified a set of genes that warrant further research to elucidate the molecular mechanism of Letrozole resistance in this patient population, as well as novel high-performing biomarkers. We anticipate that these findings could contribute to improved therapeutic outcomes in human patients.

Flying-fox populations are increasingly threatened by heat events, starvation events and other stressors due to habitat clearing and human/flying-fox conflict.These factors are unlikely to resolve, meaning that a well-coordinated and timely approach to flying-fox disasters is imperative for the mitigation of further flying-fox population impacts.

RNA-seq faces persistent challenges due to the ongoing expanding array of data processing workflows, none of which have yet achieved standardization to date. It is imperative to determine which method most effectively preserves biological facts. Shannon entropy serves as a tool for depicting the biological status of a system. Thus, we assessed the measurement of Shannon entropy by several RNA-seq workflow approaches, employing RPKM and median normalization on paired samples of 475 TCGA RNA-seq datasets spanning eight different cancer types with 5-year overall survival rates ranging from 30% to 98%. Our analysis revealed that the RPKM normalization coupled with a threshold of log2 fold change ≥1 for indentifying differentially expressed genes, yielded the best results with a correlation coefficient of 0.91. We propose that Shannon entropy can serve as an objective metric for refining the optimization of RNA-seq workflows.

Bigeye grunt Brachydeuterus auritus is an important economic species in the waters off Sierra Leone in West Africa, with great ecological value. Based on the survey data of bottom trawl nets from 6 voyages from 2019 to 2021, the body weight-length relationship (WLR), as well as their relative fatness, were studied in depth using the method of body length and its corresponding mean body weight. This study fitted the WLR of bigeye grunt by gender, calculated its fullness, and analyzed the influence of environmental factors. The results showed that month and gender had a significant impact on body length and weight distribution (P<0.01). There was a highly significant negative correlation (P<0.01) between the condition factor (a) and the allometric factor (b) in the WLR, and salinity significantly affects b (P<0.05). The (lga)/b ratio was less affected by environmental factors which may be related to the body size and density of the fish. The difference in b between male and female populations was extremely significant (P<0.01). The relative fatness had significant seasonal variation characteristics, with highly significant effects of sex and body length (P<0.01). With increasing body length, the relative fatness showed two types of changes, continuously increasing and first increasing then decreasing, with salinity and b significantly affecting the type of change (P<0.05) and depth having a highly significant effect (P<0.01). The bigeye grunt off the coast Sierra Leone exhibited significant seasonal growth characteristics, with significant differences in growth characteristics between male and female individuals. This study suggested that salinity may be the main factor affecting its growth and development. In addition, this study hypothesised that the peak breeding season may occur during the dry season, beginning in December and ending before April of the following year. The study provides updated and more comprehensive insights into the biology and ecology of the bigeye grunt offshore Sierra Leone, West Africa, which can provide scientific basis for its resource assessment, development and utilization, and resource management.

COVID-19 was an inflammatory pneumonia caused by a respiratory infection with a coronavirus named SARS-CoV-2. Severely ill COVID-19 patients could die of acute pulmonary and systemic inflammation. Thus, there was a theory that long COVID-19 shared many similarities with systemic autoimmune diseases. There was also a theory that the SARS-CoV-2 virus could infect many cell- and tissue-types distributed throughout multiple organ systems of the body. I aim to review the above theories using unbiased high-throughput datasets cataloguing gene expression. Studies reviewed used the technology of next generation sequencing, either as bulk tissue RNA sequencing, or as single-cell RNAs sequencing; ingenious methods for signal deconvolution were then used to identify individual cell types. Datasets reviewed suggested that severe COVID-19 induced expression of genes associated with pro-inflammatory signaling, tissue development or remodeling, scarring, or cell death. The datasets also provided evidence for several inflammatory syndromes associated with COVID-19, such as neuronal COVID, acute respiratory disease syndrome, vascular inflammation, or multisystem inflammatory syndrome. Indeed, inflammatory signal during severe COVID-19 was reported in many cell types, for example in structural cells, in infiltrating immune cells, in the vascular system, or in circulating cells in the blood. There was also frequently a change in proportions of immune cell-types in the blood, epithelial cells in the lungs, or among infiltrating immune cells.

Disease classification based on biological data is an important area in bioinformatics and biomedical research. It helps the doctors and medical practitioners for the early detection of disease and support them as a computer-aided diagnostic tool for accurate diagnosis, prognosis, and treatment of disease. Earlier Microarray gene expression data have wide application for the classification of disease, but now Next-generation sequencing (NGS) has replaced the Microarray technology. From the last few years, RNA sequence (RNA-Seq) data are widely used for the transcriptomic analysis. Hence, RNA-Seq based classification of disease is in its infancy. In this article, we present a general framework for the classification of disease constructed on RNA-Seq data. This framework will guide the researchers to process RNA-Seq, extract relevant features and apply the appropriate classifier to classify any kind of disease.

Post-traumatic stress disorder (PTSD), a mental disorder caused by exposure to traumatic stress, affects 5-10% of the world’s population. PTSD is associated with several medical and neurological comorbidities. It has been suggested that these are due to accelerated aging, and that changes in telomere length (TL) and telomerase enzyme activity may serve as biomarkers of this process. Early research in this field suggested that TL was significantly reduced in PTSD. The current review was conducted to provide a critical analysis of recent clinical and translational research on telomere length and telomerase in PTSD. The results of 26 clinical studies suggest that TL in PTSD is highly variable, and may be influenced by methodological, demographic, trauma-related and psychosocial factors. There is no evidence for altered telomerase activity in PTSD, though this was hypothesized by earlier workers in the field. Translational research suggests that exposure to traumatic stress does lead to TL shortening. Overall, it is likely that TL in PTSD depends on several variables that are specific to individuals and groups. Other markers of cellular aging, such as epigenetic changes, may be more specific indices of accelerated aging in patients with PTSD.

Gastrointestinal (GI) cancers, such as colorectal and gastric cancers, pose significant global health challenges due to their high rates of incidence and mortality. Even with advancements in treatment and early detection, many patients still face poor outcomes, highlighting the critical need for new biomarkers and therapeutic targets. Telomere length (TL) and telomerase activity (TA) have gained attention in this context. Telomeres, protective nucleotide sequences at chromo-some ends, shorten with each cell division, leading to cellular aging. Telomerase, a ribonucleoprotein enzyme, counteracts this shortening by adding telomeric repeats, a process tightly regulated in normal cells but often dysregulated in cancer. This review critically evaluates the role of TL and TA in the pathogenesis of GI cancers, examining their potential as diagnostic, prognostic, and predictive biomarkers. It explores how alterations in telomere biology contribute to the initiation and progression of GI tumors and assesses the therapeutic implications of targeting telomerase. By integrating findings from diverse studies, this review aims to elucidate the intricate relationship between telomere dynamics and gastrointestinal carcinogenesis, offering in-sights into how TL and TA could be leveraged to enhance the early detection, treatment, and prognosis of GI cancers.

Аnalysis of small RNA sequencing data across a range of biofluids is a significant research area, given the diversity of RNA types that holds potential diagnostic, prognostic, and predictive value. The intricate task of segregating the complex mixture of small RNAs from both human and other species, including bacteria, fungi, and viruses, poses one of the most formidable challenges in the analysis of small RNA sequencing data, currently lacking satisfactory solutions. This study introduces sRNAflow, a user-friendly bioinformatic tool with a web interface designed for the analysis of small RNAs obtained from biological fluids. Tailored to the unique requirements of such samples, the proposed pipeline addresses various challenges, including filtering potential RNAs from reagents and environment, classifying small RNA types, managing small RNA annotation overlap, conducting differential expression assays, analysing isomiRs, and presenting an approach to identify the sources of small RNAs within samples. sRNAflow also encompasses an alternative alignment-free analysis of RNA-seq data, featuring clustering and initial RNA source identification using BLAST. This comprehensive approach facilitates meaningful comparisons of results between different analytical methods. The source code can be accessed at https://github.com/zajakin/sRNAflow under the GPL3 licence.

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = \(Read\ length - 40\% Adapter\ length\); (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; and (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

Background Telomere shortening is related to aging and unfavourable health outcomes. Obesity and metabolic diseases are important factors for accelerating aging. This study aimed to find out the association between obesity, metabolic disease, and telomere length in metabolically healthy adults. Methods 237 adults were enrolled with written consents at a health promotion centre of a tertiary hospital from February 2014 to March 2015. After excluding 99 subjects who met the exclusion criterion, a total of 130 metabolically healthy subjects were selected for final analysis. The subjects were divided into quartile groups according to the telomere lengths of their oral mucosal cells. Results The subjects consisted of 66 (50.8%) males with a mean age of 58.59 years. The body mass index (BMI, kg/m2) increased significantly along with the quartile groups (Q1, 23.00; Q2, 23.96; Q3, 23.70; Q4, 25.20; P-for trend=0.008). Waist circumference (WC, P-for trend=0.022), waist-to-hip ratio (WHR, P-for trend=0.005), and waist-to-height ratio (WHtR, P=0.001) also increased along with the quartile groups. Obesity prevalence (BMI ≥25 kg/m2), abdominal obesity (WC ≥90 cm for men, ≥85 cm for women), WHR 〉1.0 for men or 〉0.85 for women, and WHtR ≥0.5 increased significantly as the telomere length increased (P-for trend <0.05). After adjusting for covariates, the ORs for each obesity markers increased as the telomere length increased (P-for trend <0.05); and the ORs of WHtR were especially meaningful (Q1, 1.00; Q2, 2.53; Q3, 2.97; Q4, 7.81; P-for trend = 0.001). There were no significant trends for metabolic syndrome and its components along with the prevalence of fatty liver disease. Conclusion Obesity markers and telomere length had significant positive correlation despite the established theory. The obesity paradox may exist in metabolically healthy adults with regard to telomere length, However, further studies with larger sample sizes for the association between obesity and telomere length are needed.

The ends of linear chromosomes of most eukaryotes consist of protein-bound DNA arrays called telomeres, which play essential roles in protecting genome integrity. Despite general evolutionary conservation in function, telomeric DNA is known to drastically vary in length and sequence between different eukaryotic lineages. Bryophytes are a group of early diverging land plants that include mosses, liverworts, and hornworts. This group of ancient land plants recently emerged as a new model for important discoveries in genomics and evolutionary biology, as well as for understanding plant adaptations to a terrestrial lifestyle. We measured telomere length in different ecotypes of model Bryophyte species, including Physcomitrium patens, Marchantia polymorpha, Ceratodon purpureus, and in Sphagnum isolates. Our data indicate that all analyzed moss and liverwort genotypes have relatively short telomeres. Furthermore, all analyzed ecotypes and isolates of model mosses and liverworts display evidence of substantial natural variation in telomere length. Interestingly, telomere length also differs between male and female strains of the dioecious liverwort M. polymorpha and dioecious moss C. purpureus. Given that Bryophytes are extraordinarily well-adapted to different ecological niches from polar to tropical environments, our data will contribute to understanding the impact of natural telomere length variation on evolutionary adaptations in this ancient land plant lineage.

When generalized noncommutative Heisenberg algebra accommodating impacts of finite gravitational fields as specified by loop quantum gravity, doubly–special relativity, and string theory, for instance, is thoughtfully applied to the eight-dimensional manifold (M8), the generalization of the Riemannian manifold becomes imminent. By constructing the deformed affine connections on a four-dimensional Riemannian manifold, we have determined the minimal length deformation of Riemann curvature tensor and its contractions, the Ricci curvature tensor, and Ricci scalar. Consequently, we have been able to construct the deformed Einstein tensor. As in Einstein’s classical theory of general relativity, we have proved that the covariant derivative of the deformed Einstein tensor vanishes, as well. We conclude that the minimal length correction suggests a correction to the spacetime curvature which is manifest in the additional curvature terms of the corrected Riemann tensor and its contractions. Accordingly, the spacetime curvature endows additional curvature and geometrical structure.

The Cobb angle is critical in assessing adolescent idiopathic scoliosis (AIS) patients. This study aimed to evaluate the error in selecting the cranial and caudal limit vertebrae on AIS digital X-rays of experienced and novice observers and its correlation with the error in measuring the Cobb angle and determining the length of the scoliotic curves. Using the TraumaMeter v.873 software, eight raters (four experienced and four novices) independently evaluated 68 scoliotic curves on 42 AIS X-rays across three sessions one month apart according to Hopkins’ criteria of absolute reliability. Two spine specialist experts using the Cobb method established the gold standard measurements. The percentage of error in the selection of the cranial vertebrae (the most-tilted vertebra above the apex) is higher than in the caudal vertebrae (the most-tilted vertebrae below the apex) (44.7%, CI95% 41.05-48.3 compared to 35%, CI95% 29.7-40.4). The error in the choice of the most tilted vertebrae, in number of vertebrae per scoliotic curve, was MBE (mean bias error) =0.45, CI95% 0.38-0.52 in the cranial and MBE=0.35, CI% 0.69-0.91 in the caudal. The percentage of errors in the choice of boundary vertebrae is lower for the experienced than for the novices, both in cranial and caudal. The experienced chose at least one boundary vertebrae incorrectly in 52% of the meas-urements and the novices in 65.1%. The error in the Cobb angle did not depend on the number of boundary vertebrae chosen incorrectly (r=0.198, p=0.111). Of the 50% of Cobb angle measurements closest to the actual value, 55.4% (454) were obtained by incorrectly selecting at least one boundary vertebra. There was a positive correlation (r=0.673, p=0.000) between the error in selecting the boundary vertebrae and the error in determining the length of the scoliotic curves. The error in quantifying the length of scoliotic curves was MBE=0.43, CI95% 0.35-0.51 vertebrae per curve. We can conclude that errors in selecting boundary vertebrae are common among experienced and novice observers, with a greater frequency of error in the cranial vertebrae. There is no correlation between the error in selecting the boundary vertebrae and the error in measuring the Cobb angle. Contrary to the consensus, the accuracy of determining the length of the scoliotic curve is limited by the Cobb method’s reliance on the correct selection of boundary vertebrae. Inappropriate choice of boundary vertebrae leads to an estimated error in determining the length of the scoliotic curves of 0.805 vertebrae for each boundary vertebra chosen incorrectly.

Single-cell RNA sequencing data facilitates investigation of cell heterogeneity and subpopulations as well as differentially abundant states however modern single-cell RNA sequencing datasets are growing in size and complexity requiring advances in the bioinformatic methods that analyze them. Many methods exist for each step of analysis including read alignment, normalization, quality control, batch effect correction, imputation and dimensionality reduction. With so many options to choose from at each step of the analysis, benchmarking and a synthesis of the literature on the methods available is necessary to inform biological researchers on the most optimal workflow for their data. Here, recent key methods of analysis are highlighted with a focus on methods that facilitate identification of cell subpopulations and differentially abundant cell states. With a constantly expanding toolset for each step in single-cell RNA sequencing dataset analysis, biological researchers should stay informed to utilize the most applicable methods for their own analyses.

Sugarcane is an important sugar-source crop. As any other plant, it can be exposed to several abiotic stress conditions. Though some metals contribute to critical physiological processes in plants, the presence of aluminum ions (Al3+) can be very toxic. In order to develop plants that flourish in acidic soils, it is critical to gain insights into the molecular mechanisms of sugarcane response to aluminum stress. To determine the genes involved in sugarcane response to aluminum stress we generated 372 million paired-end RNA sequencing reads, from roots of CTC-2 and RB855453 two contrasting cultivars. Data normalization resulted in 162,161 contigs and 97,335 trinity genes. After the read cutoff, the differentially expressed genes were 4,858 in CTC-2 and 1,307 in the RB855453, Treatment Vs Control, respectively. The differentially expressed genes were annotated into 34 functional categories. The majority of the genes were upregulated in the CTC-2 (tolerant cultivar) and down regulated in RB855453 (sensitive cultivar). Here, we present the first root-transcriptome of sugarcane under aluminum stress. The results and conclusions of this study provide a valuable resource for future genetic and genomic studies in sugarcane. This transcriptome analysis points out that sugarcane tolerance to aluminum may be explained by an efficient detoxification mechanism combined with the lateral root formation and activation of redox enzymes. Following our results, we present here, a hypothetical model for the aluminum tolerance in CTC-2 cultivar.

This study presents a comparative analysis of length deformation in Classical and Relativistic Mechanics, specifically investigating 10-gram objects accelerating to 1% of the speed of light. By employing Hooke's Law in Classical Mechanics and the Relativistic Lorentz Factor, the research explores the implications of acceleration dynamics and the limitations inherent in Relativistic Mechanics. The results reveal significant differences in predicted length changes between the two frameworks, emphasizing the necessity of considering relativistic effects beyond velocity alone. This study underscores the critical importance of addressing the incomplete treatment of acceleration dynamics in Relativistic Mechanics to achieve a more accurate depiction of length deformation in high-speed scenarios.

We investigate the power of time series analysis based on a variety of information-theoretic approaches from statistics (AIC, BIC) and machine learning (Minimum Message Length) - and we then compare their efficacy with traditional time series model and with hybrids involving deep learning. More specifically, we develop AIC, BIC and Minimum Message Length (MML) ARMA (autoregressive moving average) time series models - with this Bayesian information-theoretic MML ARMA modelling already being new work. We then study deep learning based algorithms in time series forecasting, using Long Short Term Memory (LSTM), and we then combine this with the ARMA modelling to produce a hybrid ARMA-LSTM prediction. Part of the purpose of the use of LSTM is to seek capture any hidden information in the residuals left from the traditional ARMA model. We show that MML not only outperforms earlier statistical approaches to ARMA modelling, but we further show that the hybrid MML ARMA-LSTM models outperform both ARMA models and LSTM models.

The current paper provides a cutting-edge information data length- theoretic approach to the transient M/M/Infinity queueing system. This is a first time ever investigation that unifies information data length and queueing theories. The significant impact of both time and the number of states for the transient M/M/ Infinity queue on both the upper and lower bounds of the obtained information data length is observed and noted. The paper concludes with some challenging open problems, combined with concluding remarks and future research pathways.

Enhancement in chemisorption is one of the active research areas in carbon materials. To remedy the thermally degraded chemisorption at high temperatures, we report a comprehensive study of kink structures in free-standing monoatomic carbon nanowires upon heating. Our Monte Carlo simulation considers multi-monoatomic carbon chains laterally interacted by the Van der Waals force. Our study reveals that the carbon nanowires maintain their linearity regardless of chain length at low temperatures, but this is not the case at high temperatures. Disordered kink structure is observed in the short carbon chains, especially above the Peierls transition temperature. The severe kink structure might increase the possibility of attaching negatively charged atoms, thereby contributing to the development of next-generation materials for chemisorption at high temperatures. We have also provided an important inspection that any physical property of the finite-length carbon chain predicted by ab-initio calculation should reconsider the atomic rearrangement due to the thermal instability at high temperatures.

Background. During the COVID-19 pandemic, there was an increased number of the hospitalized COVID-19 positive patients suffering from type 2 diabetes mellitus (T2DM). The objective of this research was to explore factors associated with the length of hospitalization of patients with T2DM and mild form of COVID-19. Material and Methods. This retrospective cohort study involved all patients who tested positive for COVID-19 and were treated in the dedicated COVID department of the University Clinical Center (UCC) in Nis between September 10, 2021, and December 31, 2021. Upon admission, patients underwent blood tests for biochemical analysis, including blood count, kidney and liver function parameters (C-reactive protein-CRP, creatinine kinase, D-dimer), as well as glycemia and HbA1c assessments. Additionally, all patients underwent lung radiography. Univariate and multivariate regression analyses were employed to assess the impact of specific factors on the length of hospitalization among patients with T2DM. Results. Out of the total 549 COVID-19 positive patients treated, 124 (21.0%) had T2DM, while 470 (79.0%) did not have diabetes. Among patients with T2DM, men were significantly younger than women (60.6±16.8 vs. 64.2±15.3, p

To guide analysts to select the right tool and parameters in differential gene expression analysis of single-cell RNA sequencing (scRNA-seq) data, we developed a novel simulator that recapitulates the data characteristics of real scRNA-seq datasets while accounting for all the relevant sources of variation in a multi-subject, multi-condition scRNA-seq experiment: the cell-to-cell variation within a subject, the variation across subjects, the variability across cell types, the mean/variance relationship of gene expression across genes, library size effects, group effects, and covariate effects. By applying it to benchmark 12 differential gene expression analysis methods (including cell-level and pseudo-bulk methods) on simulated multi-condition, multi-subject data of the 10x Genomics platform, we demonstrated that methods originating from the negative binomial mixed model such as glmmTMB and NEBULA-HL outperformed other methods. Utilizing NEBULA-HL in a statistical analysis pipeline (https://github.com/interactivereport/scRNAseq_DE) for single cell analysis will enable scientists to better understand cell-type specific transcriptomic response to disease or treatment effects and to discover new drug targets. Further, application to two real datasets showed the outperformance of our differential expression (DE) pipeline, with unified findings of differentially expressed genes (DEG) and a pseudo-time trajectory transcriptomic result. In the end, we made recommendations of filtering strategies of cells and genes based on simulation results to achieve optimal experimental goals.

Circular RNAs are a special type of RNAs which recently attracted a lot of research interest in studying its formation and function. RNA binding proteins (RBPs) that bind circRNAs are important in these processes but are relatively less studied. CLIP-Seq technology has been invented and applied to profile RBP-RNA interactions on the genome-wide scale. While mRNAs are usually the focus of CLIP-Seq experiments, RBP-circRNA interactions could also be identified through specialized analysis of CLIP-Seq datasets. However, many technical difficulties are involved in this process, such as the usually short read length of CLIP-Seq reads. In this study, we created a pipeline called Clirc specialized for profiling circRNAs in CLIP-Seq data and analyzing the characteristics of RBP- circRNAs interactions. In conclusion, this is one of the first few studies to investigate circRNAs and their binding partners through repurposing CLIP-Seq datasets to our knowledge, and we hope our work will become a valuable resource for future studies into the biogenesis and function of circRNAs. Clirc software is available at https://github.com/Minzhe/Clirc

In this paper, the results of a high-precision control survey carried out in the underground mining of the Oyu Tolgoi project using terrestrial laser scanning technology are presented. The purpose of the measurements was to ensure that the direction, total length and volume of the penetration and excavation works were being implemented in accordance with the planned and designed dimensions. The coordinates of the geodetic traverse checkpoints were also assessed. In addition, we checked a traverse network of 18 checkpoints in the tunnel of the selected underground level. These checkpoints were repeatedly measured four times by two using readings of the Trimble S7 1” total station and were processed using the Compass/Bowditch method with Trimble Business Center software. All points except for one were within the tolerance limits. Based on these points, the excavation length and volumes were determined using the terrestrial laser scanners (TLSs) Trimble X7 and Trimble SX12 [25]. The difference between the planned work quantity provided by the Oyu Tolgoi project and the actual values measured using laser scanner was calculated with the comparative method. The TLS partial control measurements in the excavations made through the ore bodies revealed a length of 20285.72m and a volume of 441128.80m3 for the seven underground mine levels, while their project values were 16158.26m length and 422837.50m3 volume.

Nickelate superconductors, R1-xAxNiO2 (where R is a rare earth metal and A = Sr, Ca), experimentally discovered in 2019 exhibit many unexplained mysteries as the existence of a superconducting state with Tc (up to 18 K) in thin films and its absence in bulk materials. Another unexplained mystery of nickelates is their temperature-dependent upper critical field, Bc2T, which can be nicely fitted to two-dimensional (2D) models; however the deduced film thickness, dsc,GL, exceeds the physical film thickness, dsc, by a manifold. To address the latter, it should be noted that 2D models assume that dsc is less than the in-plane and out-of-plane ground state coherence lengths, dsc&lt;ξab0 and dsc&lt;ξc0, respectively, and, in addition, that the inequality ξc0&lt;ξab0 satisfies. Analysis of the reported experimental Bc2T data showed that at least one of these conditions does not satisfy for R1-xAxNiO2 films. This implies that nickelate films are not 2D superconductors, even despite though that the superconducting state is observed only in thin films. Based on this, here we proposed analytical three dimensional (3D) model for global data fit of in-plane and out-of-plane Bc2T in nickelates. The model is based on a heuristic expression for temperature dependent coherence length anisotropy: γξT=γξ01-1a×TTc, where a&gt;1 is a unitless free-fitting parameter. The proposed expression for γξT, perhaps, has a much broader application because it has been successfully applied to bulk pnictide and chalcogenide superconductors.

The current paper provides a cutting-edge information data length- theoretic approach to human emotions. This is a revolutionary breakthrough that unifies information data length and the dynamics of emotions. The significant impact of both time and its mean value associate on both the upper and lower bounds of the obtained information data length is observed and noted. The paper concludes with some challenging open problems, combined with concluding remarks and future research pathways.

When the minimal length approach emerging from noncommutative Heisenberg algebra, generalized uncertainty principle (GUP), and thereby integrating gravitational fields to this fundamental theory of quantum mechanics (QM) is thoughtfully extended to Einstein field equations, the possible deformation of the metric tensor could be suggested. This is a complementary term combining the effects of QM and general relativity (GR) and comprising noncommutative algebra together with maximal spacelike four–acceleration. This deformation compiles with GR as curvature in relativistic eight–dimensional spacetime tangent bundle, generalization of Riemannian spacetime, is the recipe applied to derive the deformed metric tensor. This dictates how the affine connection on Riemannian manifold is straightforwardly deformed. We have discussed the symmetric property of deformed metric tensor and affine connection. Also, we have evaluated the dependence of a parallel transported tangent vector on the spacelike four–acceleration given in units of L, where L = rℏcG3 is a universal constant, c is speed of light, and ℏ is Planck constant, and G is Newton’s gravitational constant.

The pinning force density FpJc,B=Jc×B (where Jc is the critical current density and B is the applied magnetic field) is one of the main parameters that characterize the resilience of a superconductor to carry a dissipative-free transport current in an applied magnetic field. Kramer (1973 J. Appl. Phys. 44 1360), and Dew-Hughes (1974 Phil. Mag. 30 293) proposed a widely used scaling law for the pinning force density amplitude: FpB=Fp,max×p+qp+qppqq×BBc2p×1-BBc2q, where Fp,max, Bc2, p, and q are free-fitting parameters. Since the late 1970-s till now, several research groups have reported experimental data on the dependence of Fp,max on the average grain size, d, in Nb3Sn-based conductors. Godeke (2006 Supercond. Sci. Techn. 19 R68) proposed that the dependence obeys the law Fp,maxd=A×ln1d+B. However, this scaling law has several problems, for instance, the logarithm is taken from a non-dimensionless variable, and Fp,maxd&lt;0 for large grain sizes, and Fp,maxd→∞ for d→0. Here, we reanalysed the full inventory of publicly available Fp,maxd data for Nb3Sn conductors and found that the dependence can be described by Fp,maxd=Fp,max0×exp-dδ law, where the characteristic length, δ, varies within a remarkably narrow range, that is, δ=175±13 nm, for samples fabricated by different technologies. The interpretation of the result is based on the idea that the in-field supercurrent flows within a thin surface layer (thickness of δ) near the grain boundary surfaces (similar to London’s law, where the self-field supercurrent flows within a thin surface layer with a thickness of the London penetration depth, λ, and the surface is a superconductor-vacuum surface). An alternative interpretation is that δ represents the characteristic length of the exponential decay flux pinning potential from the dominant defects in Nb3Sn superconductors, which are grain boundaries.

RNA sequencing (RNA-Seq) is a complicated protocol, both in the laboratory in generation of data and at the computer in analysis of results. Several decisions during RNA-Seq library construction have important implications for analysis, most notably strandedness during complementary DNA (cDNA) library construction. Here we clarify bioinformatic decisions related to strandedness in both alignment of DNA sequencing reads to reference genomes and subsequent determination of transcript abundance.

The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential therapeutic and biotechnological applications. Identifying such DVGs in high-throughput sequencing data has become an interesting computational problem. Up to nowadays, several algorithms have been proposed, though all incur in false positives, a problem of practical interest if such DVGs have to be synthetized and tested in the laboratory. Here we develop a novel software, DVGfinder, that wraps the two most commonly used algorithms into a pipeline that predicts DVGs. Using a gradient boosting classifier machine learning algorithm, we evaluate the performance of DVGfinder compared to previous algorithms and found that it outcompetes their precision and sensitivity in simulated datasets. DVGfinder generates user-friendly output files in HTML format that can assist users to identify DVGs based on their associated probability of being true positives.

Recently the increased cost-effectiveness of high-throughput technologies has made available a large number of RNA sequencing datasets to identify circular RNAs (circRNAs). However, despite many computational tools were developed to predict circRNAs, a limited number of workflows exists to predict and to characterize circRNAs. Moreover, to the best of our knowledge, these available workflows do not ensure computational reproducibility and require advanced bash scripting skills to be correctly installed and used. To cope with these critical aspects we present Docker4Circ, a new computational framework designed for a comprehensive analysis of circRNAs composed of: circRNAs prediction, classification and annotation using public databases, the back-splicing sequence reconstruction; the internal alternative splicing of circularizing exons; the alignment-free circRNAs quantification from RNA-Seq reads, and, finally, their differential expression analysis. Docker4Circ was specifically designed for making easier and more accessible circRNAs analysis thanks to the following features: (i) its R interface; (ii) the encapsulation of its computational tasks into a docker image; (iii) an available user-friendly Java GUI Interface. Furthermore, Docker4Circ ensures a reproducible analysis because all its tasks were embedded into a docker image following the guidelines provided by Reproducible Bioinformatics Project (RBP, http://reproducible-bioinformatics.org/). The effectiveness of Docker4Circ was demonstrated on a real case study whose goal is to characterize the circRNAs predicted in colorectal cancer cell lines and quantified in public RNA-Seq experiments performed on primary tumor tissues. In conclusion, we propose Docker4Circ as a framework for reproducible and comprehensive analyses of circRNAs to efficiently exploit their biological role.

This study, serving as Part-2 of the research titled "Comparative Analysis of Length Deformation in Classical and Relativistic Mechanics," investigates the behaviour of matter within gravitationally bound systems. Through meticulous examination of projected length alterations, the research highlights differences between classical and relativistic mechanics frameworks, emphasizing the necessity of considering relativistic effects beyond velocity alone. Additionally, the study underscores the crucial role of gravitational effects on the effective mass of moving objects, which emerges as a critical factor in predicting length deformation across scientific disciplines. The incomplete treatment of relativistic effects within Relativistic Mechanics, including acceleration and material stiffness, emphasizes the importance of comprehensively understanding gravitational influences on effective mass. This is evident in gravitational equations, where the gravitational force depends not only on the object's mass but also on its effective mass, influenced by kinetic energy. Thus, incorporating the gravitational effect on effective mass enhances the understanding of length deformation phenomena within gravitationally bound systems, enriching scientific discourse.

The conventional theory of neutron beams interacting with many-body systems treats the beam as a classical system, i.e. with its dynamical variables appearing in the quantum dynamics of the scattering process not as operators but only as c-numbers. Moreover, neutrons are described with plane waves, i.e. the concept of neutron's (finite) coherence length is here irrelevant. The same holds for electron, atom or X-ray scattering. This simplification results in the full decoupling of the probe particle's dynamics from the quantum dynamics of the scatterer---a well-known fact also reflected in the standard formalism of time-correlation functions (see textbooks). Making contact with modern quantum theoretical approaches (e.g., quantum entanglement, 'which-path detection' versus interference, von Neumann measurement, Week Values, etc.) new observable effects may be exposed and/or predicted, for instance, a momentum-transfer deficit and an intensity deficit in neutron scattering from protons of hydrogen-containing samples. 7

Preterm birth (PTB), a multi-causal syndrome, is one of the global epidemics. Maternal nutrition, but also neonatal and placental telomere length (TL), are among the factors affecting PTB risk. However, the exact relationship between these factors and the PTB outcome, remains obscure. The aim of this review, was to investigate the association between PTB, maternal nutrition and placental-infant TL. Observational studies were sought, with the keywords: maternal nutrition, placenta TL, newborn, TL, and PTB. No study was found that included all keywords simultaneously, and thus, the keywords, were searched in dyads, to reach assumptive conclusions. The findings show that maternal nutrition affects PTB risk, through its influence on maternal TL. On the other hand, maternal TL independently affects PTB risk, and at the same time PTB is a major determinant of offspring TL regulation. The strength of the associations and the extent of the influence from covariates, remains to be elucidated in future research. Furthermore, the question of whether maternal TL, is simply a biomarker of maternal nutritional status and PTB risk, or a causative factor of PTB, to date, remains to be answered.

In the 21st century, the effects of HIV-associated neurocognitive disorders (HAND) have been significantly reduced in individuals due to the development of antiretroviral therapies (ARTs). However, the growing epidemic of polysubstance use (PSU) has led to concern for the effects of PSU on HIV-seropositive individuals. To effectively treat individuals affected by HAND, it is critical to understand the biological mechanisms affected by PSU including identification of novel markers. To fill this important knowledge gap, we used an in vivo HIV-Transgenic (HIV-Tg) animal model, to investigate the effects of the combined use of chronic methamphetamine (METH) and oxycodone (oxy). RNA-Seq analysis on the striatum - a brain region that is primarily targeted by both HIV and drugs of abuse - identified key differentially expressed markers post-METH and oxy exposure. Furthermore, ClueGO analysis and Ingenuity Pathway Analysis (IPA) revealed crucial molecular and biological functions associated with ATP-activated adenosine receptor, neuropeptide hormone activity, and the oxytocin signaling pathway to be altered between the different treatment groups. The current study further reveals the harmful effects of chronic PSU and HIV infection that can subsequently impact neurological outcomes in polysubstance users with HAND.

Telomeres are crucial structures that preserve genome stability. Their progressive erosion over rounds of DNA duplication determines senescence of cells and organisms. Telomere length homeostasis is critical for cancer development then telomere maintenance mechanisms are established targets in cancer treatment. Besides telomere elongation, telomere’s dysfunction impinges on intracellular signalling pathways, in particular DNA damage signalling and repair affecting cancer cell survival and proliferation. This review summarizes and discusses about the recent findings in anti-cancer drug development targeting different “telosome” components.

With a reduction in the mortality rate of burn patients, patient length of stay (LOS) is increasingly adopted as an outcome measure. Some studies have attempted to identify factors that explain a burn patient's expected LOS. However, few have investigated the association between LOS and a patient's mental and socioeconomic status. There is anecdotal evidence for links between these factors and uncovering these will aid in better addressing the specific physical and emotional needs of burn patients, and facilitate the planning of scarce hospital resources. Here, we employ machine learning (clustering) and statistical models (regression) to investigate whether a segmentation by socioeconomic/mental status can improve the performance and interpretability of an upstream predictive model, relative to a unitary model derived for the full adult population of patients. Although we found no significant difference in the performance of the unitary model and segment-specific models, the interpretation of the segment-specific models reveals a reduced impact of burn severity in LOS prediction with increasing adverse socioeconomic and mental status. Furthermore, the models for the socioeconomic segments highlight an increased influence of living circumstances and source of injury on LOS. These findings suggest that, in addition to ensuring that the physical needs of patients are met, management of their mental status is crucial for delivering an effective care plan.

A naked human eye can perceive objects down to a millimeter length. While lenses and microscopes have overcome this limit, the human mind still lacks perspective when navigating conventional scales (1), especially in the range that are less palpable to naked human eye (2,3). This problem is particularly acute in the context of science communication, where the conventional scale bar units facilitate little comprehension regarding the perception for factorial size differences (3). Here we aim to bridge the gap of scale factors and perspectives using a universal toolkit of objects, which can help comprehend the relative change in length dimensions up to 13 orders of magnitude difference. We further have demonstrated the use of such a universal object toolkit as a length perceptive scale by illustrating and narrating biological phenomena. The meter to picometer ‘length perceptive scale’ proposed here has the potential to cover majority of length scales present in the biological realm, and is analogous to the time compression methods widely used in explaining cosmos timeline (4). Our toolkit can also be calibrated according to the users need in their scientific communication and illustrations, which will aid the readers’ benefit in understanding the length scale perception of illustrated phenomenon.

The A. japonicus industry has expanded significantly, but no research has focused on how to de-termine the age of A. japonicus during farming. Correctly estimating the age of A. japonicus can provide a decision-making basis for the breeding process, and data for the protection of A. japonicus aquatic germplasm resources. DNA methylation levels in the body wall of Apostichopus japonicus at 4 months, 1 year, 2 years, and 3 years old were determined by MethylRAD-Seq, and differentially methylated genes related to age were screened. The results of the study found that 441 and 966 differentially methylated genes were detected at CCGG and CCWGG sites, respectively. As-partate aminotransferase, succinate semialdehyde dehydrogenase, isocitrate dehydrogenase, the histone H2AX, heat shock protein Hsp90, aminopeptidase N, cell division cycle CDC6, Ras GTPase activating protein (RasGAP), slit guidance ligand slit 1, integrin linked kinase ILK, mechanistic target of rapamycin kinase Mtor, protein kinase A Pka, and autophagy-related 3 atg3 these genes may play key roles in the growth and aging process of A. japonicus. This study provided data for identifying the age of A. japonicus.

Objective: To determine if higher weight-to-length z-scores after 32 weeks of gestation are associated with higher Pulmonary Scores (PS) in preterm infants requiring respiratory support using a prospective observational study. Methods: Infants born <30 weeks, with a post-menstrual age (PMA) of 30-33 weeks were enrolled. Weight, infant’s length, and head circumference were measured weekly. Data on calories/kg/d, protein g/kg/d, weight for length percentiles, z-scores, and BMI at 33 through 40 weeks PMA were collected. PS was calculated. Results: We analyzed 91 infants. The mean gestational age was 26.9 ± 1.7 weeks. There was a significant association between PS and W/L z scores(p<0.0001). For every one-unit increase in W/L z-scores, PS increased by 0.063. There was a significant association between PS and W/L percentiles (p = 0.0017) as well as BMI (p = <0.0001). For every unit increase in W/L percentiles, PS increased by 0.002, and for a unit increase in BMI, PS increased by 0.04. The association remained significant after postnatal steroids, sex, corrected, and birth gestational ages were included in the regression analysis. Nutrition did not affect anthropometric measurements. Conclusion: Our study is the first to demonstrate that higher BMI and W/L may adversely affect respiratory severity in infants.

Hospital readmission and length of stay prediction provide info to manage hospitals’ bed capacity and the number of required staff, especially during pandemics. We present a hybrid deep model called Genetic Algorithm-Optimized Convolutional Neural Network (GAOCNN) with a unique preprocessing method to predict hospital readmission and the length of stay in patients having various conditions. GAOCNN uses one-dimensional convolutional layers to predict hospital readmission and length of stay. The parameters of the layers are optimized using a genetic algorithm. To show the performance of the proposed model in patients with various conditions, we evaluate the model under three healthcare datasets; the Diabetes 130-US hospitals dataset, the COVID-19 dataset, and the MIMIC-III dataset. The diabetes 130-US hospitals dataset has information on both readmission and the length of stay, while COVID-19 and MIMIC-III datasets just include information on the length of stay. Experimental results show that the proposed model’s accuracy for hospital readmission is 97.2% for diabetic patients. Also, the accuracy of the length of stay prediction is 89%, 99.4%, and 94.1% for diabetic, COVID-19, and ICU patients, respectively. These results confirm the superiority of the proposed model compared to existing methods. Our findings offer a platform for managing healthcare funds and resources for patients with various diseases.

Smoking is a pervasive global health concern associated with a myriad of diseases, but its impact on cellular aging, particularly in relation to telomeres, is increasingly recognized. Telomeres, protective caps at the ends of chromosomes, play a crucial role in maintaining genomic integrity. This review critically examines the existing evidence on the association between smoking and telomere atrophy, exploring the molecular mechanisms involved and the implications for accelerated aging and heightened disease risk. The comprehensive analysis encompasses both cross-sectional and longitudinal studies, elucidating potential gender and age disparities. Insights into the molecular pathways linking smoking to telomere shortening are discussed, along with the broader implications for public health. The review concludes by outlining potential interventions and suggesting future research directions in this critical area.

The Golden ratio is an irrational number that has a tendency to appear in many different scientific and artistic fields. It may be found in natural phenomena across a vast range of length scales; from galactic to atomic. In this review, the mathematical properties of the Golden ratio are discussed before exploring where in nature it has been found; beginning at astronomical scales and progressing to smaller lengths, until reaching those of atomic and quantum physics. In making such a tour across length scales, it is illustrated just how prevalent this single number is within the natural universe.

Plastid gene expression involves many post-transcriptional maturation steps resulting in a complex transcriptome composed of multiple isoforms. Although short read RNA-seq has considerably improved our understanding of the molecular mechanisms controlling these processes, it is unable to sequence full-length transcripts. This information is however crucial when it comes to understand the interplay between the various steps of plastid gene expression. Here, the study of the Arabidopsis leaf plastid transcriptome using Nanopore sequencing showed that many splicing and editing events were not independent but co-occurring. For a given transcript, maturation events also appeared to be chronologically ordered with splicing happening after most sites are edited.

Amine containing polymers are extensively studied as special carriers for short-chain RNA (13–25 nucleotides) which are applied as gene silencing agent in gene therapy of various diseases including cancer. Elaboration of the oligonucleotide carriers requires knowledge about peculiarities of oligonucleotide - polymeric amine interaction. Critical length of the interacting chains is the important parameter which allows to design sophisticated constructions containing oligonucleotide binding segments, solubilizing, protective and aiming parts. We studied interaction of (TCAG)n, n=1-6 DNA oligonucleotides with polyethylenimine and poly(N-(3-((3-(dimethyl­amino)propyl)(methyl)amino)propyl)-N-methylacrylamide). Critical length for oligonucleotides in interaction with polymeric amines is 8-12 units and complexation at these length can be accompanied by "all-or-nothing" effects. New dimethylacrylamide based polymers with grafted polyamine chains were obtained and studied in complexation with DNA and RNA oligonucleotides. The most effective interaction and transfection activity into A549 cancer cells was found for a sample with average number of nitrogens in polyamine chain equal to 27, i.e. for a sample in which all grafted chains are longer the critical length for polymeric amine - oligonucleotide complexation.

Breast cancer (BC) is the second leading cause of death in the United States in women. 1 in 8 women in their lifetime has a risk of developing breast cancer. With advances in omics technology, more data is available for diagnosis, treatment, and prognosis. The help of Machine Learning algorithms, a subdomain of Artificial Intelligence, would allow for a better clinical support tool. Machine Learning could be the key to answering a complex problem in BC. The methodology of this research question involves collecting and finding data such as RNA-Seq datasets, selecting and training appropriate machine learning algorithms, and evaluating the performance of the algorithms in predicting BC prognosis. Also, the study explores and tries to identify the most relevant genes and pathways through feature selection extraction and dimensionality reduction techniques. After applying feature extraction, the top 10 genes were extracted using the Univariate Feature Selection (UFS) method, precisely the SelectKBest technique. After employing different machine learning algorithms, such as Networks, Random Forest, Linear SVM, Logistic Regression, and Quadratic Discriminant Analysis (QDA), we found QDA was the best model in classifying the RNA-seq dataset with a 96% accuracy rate and 94% ROC AUC. This study suggests that AK2 and CD68 have a positive correlation with each other, and it could potentially be a biomarker and therapeutic target for BC.

Trichomes are a common morphological defense against pests, in particular, type IV glandular trichomes have been associated with resistance against different invertebrates. Cultivated tomatoes usually lack or have a very low density of type IV trichomes. Thus, specific breeding programs to incorporate these natural defences, that are common within the Solanum genus, might improve a more sustainable management. We have identified a S. pimpinellifolium accession with very high density of this type of trichomes. Two F2 mapping populations using two different parents have been developed, characterized and genotyped using a new genotype methodology, K-seq. We have been able to build an ultra-dense genetic map with 147,326 markers with an average distance between markers of 0.2 cM that has allowed us to perform a detailed mapping. We have used two different families and two different approaches, QTL mapping and QTL-seq, to identify several QTLs implicated in the control of trichome type IV developed in this accession on the chromosomes 5, 6, 9 and 11. The QTL located on chromosome 9 is a major QTL that has not been previously reported in S. pimpinellifolium that increases by a factor of 9 the density of trichomes.

Corynebacterium pseudotuberculosis is a Gram-positive bacterium that causes caseous lymphadenitis, a disease that predominantly affects sheep, goat, cattle, buffalo, and horses, but has also been recognized in other animals. This bacterium generates a severe economic impact on countries producing meat. Gene expression studies using RNA-seq is one of the most commonly used techniques to perform transcriptional experiments. Computational analysis on such data through reverse-engineering algorithms leads to a better understanding of the genome-wide complexity of gene interactomes, enabling the identification of genes having the most significant functions inferred by the activated stress response pathways. In this study, we identified the influential or causal genes from four RNA-seq data-sets from different stress conditions (high iron, low iron, acid, osmosis, and PH) in C. pseudotuberculosis, using a consensus-based network inference algorithm called miRsig and identified the causal genes in the network using the miRinfluence tool, which is based on the influence diffusion model. We found that over 50\% of the genes identified as influential have some essential cellular functions in the genomes. In the strains analyzed, most of the causal genes have crucial roles or participate in processes associated with response to extracellular stresses, pathogenicity, membrane components, and essential genes. This research brings new insight into the understanding of virulence and infection by C. pseudotuberculosis.

Natural killer cells are associated with the pathogenesis of ulcerative colitis (UC), but their precise contributions remain unclear. The present study sought to investigate the diagnostic value of activated NK-associated genes (ANAGs) in UC. Bulk RNA-seq and scRNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) and Single Cell Portal (SCP) databases. In the bulk RNA-seq, 92 differentially expressed genes (DEGs) were screened out by the “Batch correction” and “Robust rank aggregation” (RRA) methods. The immune infiltration landscape was estimated by single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT, which revealed a higher abundance of activated NK cells in noninflamed UC tissues. 54 DEGs correlated with activated NK cells were identified as ANAGs. Protein-protein interaction (PPI) analysis and least absolute shrinkage and selection operator (LASSO) regression were utilized to screen out 4 key ANAGs (SELP, TIMP1, MMP7, and ABCG2) and establish an activated NK-associated gene score (ANAG score). The ANAG score demonstrated excellent diagnostic value and was validated in three external datasets. The expression of the 4 key ANAGs was validated in UC patients and healthy controls (HC) samples. Through scRNA-seq data analysis, higher expression levels of SELP, TIMP1, MMP7, and ABCG2 were observed in post-capillary venules, inflammatory fibroblasts, enterocytes, and immature enterocytes. The cell scores based on the ANAGs showed enrichment in endothelial cells and fibroblasts. In conclusion, we established and validated an ANAG score with the ability to precisely diagnose UC. The 4 key ANAGs have the potential to serve as therapeutic targets in UC.

Emerging evidence suggests that patients suffering from COVID-19 may experience neurocognitive symptoms. Besides, other studies indicate a probable association between leukocyte telomere length (LTL) and neurocognitive changes in subjects with post-COVID-19 condition. Our study was designed to determine the correlation between telomere length and cognitive changes in subjects post-COVID-19. The study included 256 subjects, categorized based on SARS-CoV-2 infection from 2020 to 2023. On the other hand, those subjects who have a psychiatric diagnosis are considered. Besides, the MoCA and MMSE scales were applied. Telomere length was determined using a Polymerase Chain Reaction, and statistical analysis was employed ANOVA and X2 tests. We identified a decrease in LTL in individuals with post-COVID-19 conditions compared to those without SARS-CoV-2 infection (p≤0.05). However, no association was found between LTL and cognitive impairment in subjects post-COVID-19. The findings suggest that LTL is affected by SARS-CoV-2 infection. Nonetheless, this important finding requires further research by monitoring neurological changes in subjects with post-COVID condition.

Nuclear magnetic resonance (NMR) techniques are widely used to identify pure substances and probe protein dynamics. Edible oil is a complex mixture composed of hydrocarbons, which have a wide range of molecular size distribution. In this research, low field NMR (LF-NMR) relaxation characteristic data of various sample oils were analyzed. We also suggest a new method for prediction size of edible oil molecules using LF-NMR relaxation time distributions. According to the relative molecular mass, carbon chain length, transverse relaxation time of different sample oils, combined with oil viscosity and other factors, the relationship between carbon chain length and transverse relaxation time rate was analyzed. Various oils and fats in the mixed fluid are displayed, reflecting the composition information of different oils. To study the correlation between the rotation correlation time and molecular information of oil molecules. The molecular composition of the resulting fluid determines its properties, such as viscosity and phase behavior. The results show that low-field NMR can obtain information on the composition, macromolecular aggregation, and molecular dynamics of complex fluids. Measurements of grease in the free fluid state show that the relaxation time can reflect the intrinsic properties of the fluid. It is shown that the composition characteristics and states of complex fluids can be measured by low-field nuclear magnetic resonance.

Prostate cancer (Pca) is a highly heterogeneous disease and the second more common tumor in males. Molecular and genetic profiles have been used to identify subtypes and guide therapeutic intervention. However, roughly 26% of primary Pca are driven by unknown molecular lesions. We use Principal Component Analysis (PCA) and custom RNAseq-data normalization to identify a gene expression signature which segregates primary PRAD from normal tissues. This Core-Expression Signature (PRAD-CES) includes 33 genes and accounts for 39% of data complexity along the PC1-cancer axis. The PRAD-CES is populated by protein-coding (AMACR, TP63, HPN) and RNA-genes (PCA3, ARLN1) sparsely found in previous studies, validated/predicted biomarkers (HOXC6, TDRD1, DLX1), and/or cancer drivers (PCA3, ARLN1, PCAT-14). Of note, the PRAD-CES also comprises six over-expressed LncRNAs without previous Pca association, four of them potentially modulating driver’s genes TMPRSS2, PRUNE2 and AMACR. Overall, our PCA capture 57% of data complexity within PC1-3. GO enrichment and correlation analysis involving major clinical features (i.e., Gleason Score, AR Score, TMPRSS2-ERG fusion and Tumor Cellularity) suggest that PC2 and PC3 gene signatures might describe more aggressive and inflammation-prone transitional forms of PRAD. Of note, surfaced genes may entail novel prognostic biomarkers and molecular alterations to intervene. Particularly, our work uncovered RNA genes with appealing implications on Pca biology and progression.

This study examines the association between dietary saturated fatty acid (SFA) intake and leukocyte telomere length (LTL) using data from the National Health and Nutrition Examination Survey (NHANES) 1999-2002. Telomeres, protective repeats of DNA at the ends of chromosomes, play a crucial role in cellular aging. Their length is shortened over time and is influenced by various factors, one of which is diet. The present study's objective was to evaluate whether increased SFA consumption is associated with shorter LTL. The analysis, conducted on a large, nationally representative sample of 6646 adults, revealed an inverse association between dietary SFAs and LTL. When examined further, this association was found to be significant in women, but not in men. Serum C-reactive protein (CRP) levels were tested as a potential mediator in this relationship, but no such mediation was found. These findings support the role of dietary factors in modulating cellular aging. However, further research is warranted to elucidate the underlying mechanisms driving the overall association, as well as the gender-specific effects observed.

A custom-designed series of unsymmetrical spiroalkanedithiols having tailgroups comprised of a terminally fluorinated chain and a hydrocarbon chain of varying lengths were synthesized and used to prepare self-assembled monolayers (SAMs) on gold substrates. The specific structure of the adsorbates was of the form [CH₃(CH₂)_n][CF₃(CF₂)₇(CH₂)₈]C[CH₂SH]₂, where n = 7, 9, and 12 (designated as F8H10-C10, F8H10-C12, and F8H10-C18, respectively). The influence of the length of the hydrocarbon chain in the bidentate dithiol on the structure and interfacial properties of the monolayer was explored. A structurally analogous partially fluorinated monodentate alkanethiol and the corresponding normal alkanethiols were used to generate appropriate SAMs as reference systems. Ellipsometric thickness measurements showed an unexpectedly low film thickness for the SAMs derived from the bidentate adsorbates, possibly due to disruptions in interchain packing caused by the fluorocarbon chains (i.e., phase-incompatible fluorocarbon-hydrocarbon interactions), ultimately giving rise to loosely packed and disordered films. Analysis by X-ray photoelectron spectroscopy (XPS) were also consistent with a model in which the films were loosely packed; additionally, the XPS spectra confirmed the attachment of the sulfur headgroups of the bidentate adsorbates onto the gold substrates. Studies of the SAMs by polarization modulation-infrared reflection-adsorption spectroscopy (PM-IRRAS) suggested that as the length of the hydrocarbon chain in the adsorbates was extended, a more ordered surface was achieved by reducing the tilt of the fluorocarbon segment. The wettability data indicated that the adsorbates with longer alkyl chains were less wettable than those with shorter alkyl chains, likely due to an increase in interchain van der Waals forces in the former.

Submergence stress challenges direct seeding in rice cultivation. In this study, we identified a heat shock protein, NAL11, with a DnaJ domain, which can regulate the length of rice coleoptiles under flooded conditions. Through bioinformatics analyses, we identified cis-regulatory elements in its promoter, making it responsive to abiotic stresses, such as hypoxia or anoxia. Expression of NAL11 was higher in the basal regions of shoots and coleoptiles during flooding. NAL11 knockout triggered the rapid accumulation of abscisic acid (ABA) and reduction of Gibberellin (GA), stimulating rice coleoptile elongation and contributes to flooding stress management. In addition, NAL11 mutants were found to be more sensitive to ABA treatments. Such knockout lines exhibited enhanced cell elongation for coleoptile extension. Quantitative RT-PCR analysis revealed that NAL11 mediated the gluconeogenic pathway, essential for the energy needed in cell expansion. Furthermore, NAL11 mutants reduced the accumulation of reactive oxygen species (ROS) and malondialdehyde under submerged stress, attributed to an improved antioxidant enzyme system compared to the wild-type. In conclusion, our findings underscore the pivotal role of NAL11 knockout in enhancing the tolerance of rice to submergence stress by elucidating its mechanisms. This insight offers a new strategy for improving resilience against flooding in rice cultivation.

The turbulent Poiseuille flow between two parallel plates is one of the simplest possible physical situations, and it has been studied intensively. In this paper, we propose a modified Prandtl-van Driest mixing length that satisfies both boundary conditions and wall damping effects. With our new formulations, we numerically solve the problem and, moreover, propose an approximate analytical solution of mean velocity. As applications of our solution, an approximate analytical friction coefficient of turbulent Poiseuille flow is proposed.

The present study provides an observation and documentation on the effect of static magnetic field on the growth of Triticum aestivum. The seeds are allowed to germinate and the seedlings are grown in an environment of the controlled static magnetic field while other physical factors such as temperature, light exposure, soil pH, etc. are held constant. Also, a comparison of influence on the average height between both the poles of the magnet is estimated and north pole oriented magnet is found to imply a significant difference. Finally some of the potential applications of the study in non-invasive protein silencing, GMO production, Vertical farming and Terraforming are briefly discussed.

Background: Constipation is one of the chronic gastrointestinal functional diseases that affects the quality of life. While Qi Lang Formula (QLF) has demonstrated effectiveness in alleviating constipation symptoms, its precise mechanism remains elusive. Methods: QLF was analyzed using UPLC-MS/MS. Targets for QLF were collected from SwissADME, Herb, ITCM databases, and FC-related targets from scRNA-seq and Genecards databases. Overlapping targets suggested potential QLF therapy targets for FC. Enrichment analysis used the KOBAS database. A "drug-ingredient-target" network was constructed with Cytoscape, and AutoDock verified active component binding. H&E staining assessed colonic mucosa changes, TEM examined ICC structural changes. ELISA measured neurotransmitter levels, and western blot verified QLF's effect on target proteins. ICC proliferation was observed through immunofluorescence. Results: We identified 89 targets of QLF associated with ICC-related FC, with c-Kit emerging as the pivotal target. Molecular docking studies revealed that Atractylenolide Ⅲ, Apigenin, Formononetin, Isorhamnetin, Naringenin, and Ononin exhibited strong binding affinities for the c-Kit structural domain. QLF significantly enhanced first stool passage time, fecal frequency, fecal moisture content, and intestinal propulsion rate. Further analysis unveiled that QLF not only restored neurotransmitter levels but also mitigated colon muscular fiber ruptures. ICC ultrastructure exhibited partial recovery, while RT-qPCR and western blot confirmed upregulated c-Kit expression and downstream targets. Immunofluorescence results indicated ICC proliferation post QLF treatment in rat colon. Conclusion: Our findings suggest that QLF may promote ICC proliferation by targeting SCF/c-Kit and its downstream signaling pathway, thereby regulating intestinal motility.

Legume-rhizobial symbiosis leads to to the formation of root nodules, where rhizobia reside and develop into bacteroids to reduce nitrogen into ammonium for plant growth, which leaves an opening question as how plant immunity is attenuated in nodules in the presence of large number of foreign bacteria. In Medicago truncatula, mutation in NAD1 (Nodules with Activated Defense 1) only produces necrotic nodules with overactivated immunity, indicating NAD1 is an indispensable component required for suppressing immunity in nodules. In this study, a dual RNA-seq transcriptomic technology was performed to extensively analyze gene expressions in nad1-1 mutant nodules. We indenifited 89 DEGs in symbiotic nitrogen fixation and 89 DEGs in immunity in Medicago truncatula at 10 dpi. Simultaneously, we indenifited 27 DEGs in fix and nif genes in Sinorhizobium meliloti. Then we identified 56 DEGs related to stress, including ROS, NO, and NCR, most of which were upregulated in Sinorhizobium meliloti. Our analyses of nitrogen fixation-defective plant nad1-1 mutants with overactivated defense indicate that host use plant immunity to control massive bacterial colonization during early and late symbiotic stages. Our findings provide insight into the function of NAD1 in improvement or inhibition of plant immune response to maintain symbiosis during rhizobial endosymbiosis.

This paper presents additional results of the generalized bathtub model for urban networks, including a simpler derivation and exact solutions for uniformly distributed trip lengths. It is shown that in steady state this trip-based model is equivalent to the more parsimonious accumulation-based model, and that the trip-length distribution has merely a transient effect on traffic dynamics, which converge to the same point in the macroscopic fundamental diagram (MFD). To understand the statistical properties of the system, a queueing approximation method is proposed to compute the network accumulation variance. It is found that (i) the accumulation variance is much larger than predicted by traditional queueing models, due to the nonlinear dynamics imposed by the MFD, (ii) the trip-length distribution has no effect on the accumulation variance, indicating that the proposed formula for the variance might be universal, (iii) the system exhibits critical behavior near the capacity state where the variance diverges to infinity. This indicates that the tools from critical phenomena and phase transitions might be useful to understand congestion in cities.

Focused electron beam induced deposition is a versatile tool for the direct fabrication of complex-shaped nanostructures with unprecedented shape fidelity and resolution. While the technique is well-established for various materials, the direct electron beam writing of silver is still in its infancy. Here, five different silver carboxylates, three fluorinated: [Ag2(µ-O2CCF3)2], [Ag2(µ-O2CC2F5)2], [Ag2(µ-O2CC3F7)2] and two containing hydrogen: [Ag2(µ-O2CCMe2Et)2] and [Ag2(µ-O2CtBu)2] were examined and compared as potential precursors for focused electron beam induced deposition. All of the compounds show high sensitivity to electron dissociation and efficient dissociation of Ag-O bonds. The as-deposited materials showed high silver content from 42 at.% to above 70at.% and silver nano-crystal formation with impurities of carbon and fluorine incorporated between metal grains. A correlation of the number of carbon atoms in the precursor ligands and silver content of the deposited structures was found. The highest silver contents were achieved for compounds with the shortest CF chains. The deposited silver content depends on the balance of electron induced ligand co-deposition and thermal ligand desorption. Low electron flux is advantageous for high silver content. Our findings demonstrate that silver carboxylates constitute a promising group of precursors for focused electron beam nanoprinting of high silver content materials.

Liver cancers give rise to a heavy burden of health care worldwide. Understanding the tumour microenvironment (TME) underpins the development of precision therapy. Single-cell RNA sequencing (scRNA-seq) technology has generated high-quality cell atlases of the TME, but its wider application faces enormous costs for various clinical circumstances. Fortunately, a variety of deconvolution algorithms can instead repurpose bulk RNA-seq data, alleviating the need for generating scRNA-seq datasets. In this study, we reviewed major public omics databases for relevance in this study and utilized 8 RNA-seq and 1 microarray datasets from clinical studies. To decipher the TME of liver cancer, we estimated the fractions of liver cell components by deconvoluting the samples with Cibersortx using three reference scRNA-seq atlases. We also confirmed that Cibersortx can accurately deconvolute cell types/subtypes of interest. Compared with non-tumorous liver, liver cancers showed multiple decreased cell types forming normal liver microarchitecture, as well as elevated cell types involved in fibrogenesis, abnormal angiogenesis and disturbed immune responses. Survival analysis shows that the fractions of five cell types/subtypes significantly correlated with patient outcomes, indicating potential therapeutic targets. Therefore, deconvolution of bulk RNA-seq data with scRNA-seq atlas references can be a useful tool to help understand the TME.

Recently, research on ultra-high-performance concrete (UHPC) with the characteristics of ultra-high strength, high toughness, and high durability has been actively conducted from materials to actual structural applications. However, research on experimental methods that reflect the unique characteristics of UHPC, which are different from those of normal concrete, is insufficient. To solve the difficulties in applying the compressive creep test method for normal concrete to UHPC and to verify the validity of the recently proposed ASTM C 1856 standard test method, this study performed compressive creep tests on UHPC with variables of specimen size, sustained load intensity, fiber length, and strain measuring method. Two types of cylindrical specimens of ϕ100 × 200 mm and ϕ75 × 150 mm were used for a specimen size variable. The sustained load intensities of 10% to 40% based on the specified compressive strength of 150 MPa were applied. Two types of steel fiber lengths of 13 mm and 19.5 mm in the UHPC mix were used as a variable, and three strain measuring methods of the embedded strain gauge method, the attached strain gauge method, and the strain meter with stud measured the change in length of the UHPC specimens. The experimental results showed that the strain meter method using the standard rod had limitations due to the error in the verification process using the standard rod and the observation error of the measurer, and the sustained load intensity is preferable to 15% to 40% of the actual compressive strength. It was found that it is possible to perform a compressive creep test for UHPC using a specimen with a size of ϕ75 mm or more, and the fiber length did not affect the creep behavior of UHPC up to 19.5 mm. As a result of comparing the UHPC creep test results with the creep prediction model, the B3 model was found to most accurately predict the UHPC creep behavior. The creep coefficient pattern of the B3 model was very similar to the measured results, and well reflected the effects of the mixing ratio and compressive strength of UHPC.

This review covers the last 25 years literature on analogs of suberoylanilide hydroxamic acid (SAHA, known also as Vorinostat) acting as HDAC inhibitor. In particular, the topic has been focused on the synthesis and biological activity of compounds where the phenyl group (the surface recognition moiety, CAP) of SAHA has been replaced by an azaheterocycle through a direct bond with amide nitrogen atom, and the methylene chain in the linker region is of variable length. Most of the compounds reported displayed good to excellent inhibitory activity against HDACs and in many cases showed anti-proliferative activity against human cancer cell lines.

Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson's Disease (PD) heterogeneity among individuals is a proof that disease subtypes exist, and assigning individuals to subgroups is necessary for a better understanding of disease mechanisms and designing precise treatment approaches. The purpose of this study was to identify PD subtypes using RNA-Seq data in a combined pipeline including unsupervised machine learning, bioinformatics, and network analysis. 210 post mortem brain RNA-Seq samples from PD (n = 115) and Normal Controls (NC, n = 95) were obtained with a systematic data retrieval following PRISMA statements and a fully data-driven clustering pipeline was performed to identify PD subtypes. Bioinformatics and Network analyses were performed to characterize the disease mechanisms of the identified PD subtypes and to identify target genes for drug repurposing. Two PD clusters were identified and 42 DEGs were found (p.adjusted ≤ 0.01). PD clusters had significantly different gene network structures (p &lt; 0.0001) and phenotype-specific disease mechanisms, highlighting the differential involvement of the Wnt/β-catenin pathway regulating adult neurogenesis. NEUROD1 was identified as a key regulator of gene networks and ISX9 and PD98059 were identified as NEUROD1-interacting compounds with disease-modifying potential, reducing the effects of dopaminergic neurodegeneration. This hybrid data analysis approach could enable precision medicine applications by providing insights for the identification and characterization of pathological subtypes. This workflow has proven useful on PD brain RNA-Seq, but its application to other neurodegenerative diseases is encouraged.

The aim of the research was to determine the most productive tree cutting methods and the factors influencing them in flat and sloping terrain in tree plantations in Brazil. The study utilized drone-captured video material from eucalyptus and pine plantations harvesting operations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge of the harvesting front or inside. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned methods. In slope terrain, the machines were also equipped with a winch assistance system. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m3, cutting productivity was 45 m3/E0h in pine cuttings and 55 m3/E0h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m3/E0h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work in sloping terrain. The research results suggest that it would be the most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident if we want to precisely identify the harvesting conditions and work phases in the tree cutting cycle affecting the differences in the productivity of the harvesting chain in tree plantations.

Keywords: underground engineering; numerical simulation; excavation length effect, major principal stress; displacement; damage initiation; CPU time

The ageing global population and changing labor force participation are having a profound impact on state pension programs worldwide, including Malaysia. However, the effects of an ageing workforce and declining fertility rates are having a significant impact on future trends in labor force participation and the duration of retirement. This paper presents an innovative examination of labor force participation rate (LFPR) forecasting within the context of an aging workforce, utilizing the Lee-Carter and Cairns-Blake Dowd stochastic models, traditionally applied to mortality data. By adapting these models to LFPR data, the study offers a novel perspective on predicting workforce participation trends and understanding the dynamics of retirement planning from year 2001 to 2047. Additionally, by incorporating the mortality forecasts from the United Nations, the research navigates through the complexities of applying actuarial methods to labor economics, revealing differentiated pathways for male and female participation in the labor market and the anticipated length of retirement. This study offers a unique comparison between the Lee-Carter and the Cairns-Blake-Dowd (CBD) LFPR models. It focuses on fitting and forecasting the LFPR of senior employees aged 50 to 64. The results highlighted discrepancies among models that demonstrated evidence of model risk for extended retirement duration.

The world population is aging, which along with recent shifts in the labor force participation (LFP), is having a significant longevity influence on state pension programs across the board, including Canada, Finland, Japan, and Germany. Except Japan, these countries have set their statutory re-tirement age at 65, but the impact of aging workforce and declined fertility rates create wonders on the estimate future trends in the LFP, as well as the length of retirement. In this study, we fit the LFP rates of these countries, representing continents from Asia, Europe and North America among the OECD countries, using the Lee-Carter and Cairns-Blake-Dowd (CBD) stochastic models. The es-timates are then used for the projection of future LFP rates (1989-2066), and by combining the mortality forecasts from the United Nations, we project the expected length of retirement (1989-2066). This study provided a novel comparison between the Lee-Carter and the CBD LFP models by fitting and forecasting the LFP rates of senior employees between 50- to 74-year-olds. The results revealed disparities between models that provided proof of the presence of model risk for longer retirement durations. The study findings emphasized the importance for decision-makers in pension industry to have awareness of potential risks and limits associated with the LFP models. The Lee-Carter model outperformed the CBD model even though the CBD model is known for its ac-curate prediction in higher ages. Population aging should be considered in any analysis of the long-term viability of pensions, together with the participation rate trends for a sustainable labor market future.

Safe sample transport is of great importance for infectious diseases diagnostics. Various treatments and buffers are used to inactivate pathogens in diagnostic samples. At the same time, adequate sample preservation, particularly of nucleic acids, is essential to allow an accurate laboratory diagnosis. For viruses with single-stranded RNA genomes of positive polarity, such as foot-and-mouth disease virus (FMDV), however, naked full-length viral RNA can itself be infectious. In order to assess the risk of infection from inactivated FMDV samples, two animal experiments were performed. In the first trial, six cattle were injected with FMDV RNA (isolate A22/IRQ/24/64) into the tongue epithelium. All animals developed clinical disease within two days and FMDV was reisolated from serum and saliva samples. In the second trial, another group of six cattle was exposed to FMDV RNA by instilling it on the tongue and spraying it into the nose. The animals were observed for 10 days after exposure. All animals remained clinically unremarkable and virus isolation as well as FMDV genome detection in serum and saliva were negative. No transfection reagent was used for any of the animal inoculations. In conclusion, cattle can be infected by injection with naked FMDV RNA, but not by non-invasive exposure to the RNA. Inactivated FMDV samples that contain full-length viral RNA carry only a negligible risk of infecting animals.

Facing with errors of a product after machining was a big title in this field. That will affect to product’s quality with unpredictable situation when products is in use for some particular application such as in medical facilities. Improving the precision of machine tools by exploring temperature on multiple points and measuring differential locations of the spindle is going to be executed in this study. A temperature measurement tool and a software running on Windows platform have been developed and combining with Non-bar system in order to support analyzing the temperature rising with the changes of length of the spindle to find the compensation solution based on eccentricity and length distortion. In this study, the whole tests have done on UX300 five – axis CNC machine tools for this investigation and the errors after applying compensation function have reduced 70% at least, with respect to the errors after machining without using compensation function.

Running on a non-motorized, curved-deck treadmill is thought to improve gait mechanics. It is not known, though, if the change in gait carries over to running on a motorized treadmill or level ground. To determine the effect of running on a curved non-motorized treadmill (CNT) on gait characteristics measured during a subsequent bout of running on a traditional motorized treadmill (TMT). Sixteen healthy college-aged participants, age (mean±SD) 20.4±1.6 years volunteered to have their gait analyzed while running on a TMT and CNT. After familiarization and warm-up on both treadmills, each subject completed five, 4-minute bouts of running alternating between traditional motorized and curved non-motorized treadmills: TMT-1, CNT-1, TMT-2, CNT-2, and TMT-3. Variables of interest included step length (m), stride length (m), imbalance score (%), and step angle (°) and were measured using Optogait gait analysis equipment. Differences in gait char acteristics among TMT-1, TMT-2, and TMT-3 can be attributed to running on the CNT. The results show that running on a CNT resulted in significant changes in gait characteristics. These findings suggest that running on a CNT can significantly alter gait characteristics may result in improvements in running gait that persist to subsequent running on a TMT.

Mutations that provide environment dependent selective advantages drive adaptive divergence among species. Many phenotypic differences among related species are more likely to result from gene expression divergence rather than from non-synonymous mutations. In this regard, cis-regulatory mutations play an important part in generating functionally significant variation. Some proposed mechanisms that explore the role of cis-regulatory mutations in gene expression divergence involve microsatellites. Microsatellites exhibit high mutation rates and are abundant in both coding and non-coding regions and could influence gene function and products. Here we tested the hypothesis that microsatellites contribute to gene expression divergence among species with 50 individuals from nine closely related Helianthus species using an RNA-seq approach. Differential expression analyses of the transcriptomes revealed that genes containing microsatellites in non-coding regions (UTRs and introns) are more likely to be differentially expressed among species when compared to genes with microsatellites in the coding regions and transcripts lacking microsatellites. We detected a greater proportion of shared microsatellites in 5’UTRs and coding regions compared to 3’UTRs and non-coding transcripts among Helianthus spp. Further, allele frequency differences measured by pairwise FST at single nucleotide polymorphisms (SNPs), indicate greater genetic divergence in transcripts containing microsatellites compared to those lacking microsatellites. A gene ontology (GO) analysis revealed that microsatellite-containing differentially expressed genes are significantly enriched for GO terms associated with regulation of transcription and transcription factor activity. Collectively, our study provides compelling evidence to support the role of microsatellites in gene expression divergence.

Background: Transcription factors (TFs) are main regulators of eukaryotic gene expression. The cooperative binding to genomic DNA of at least two TFs is the widespread mechanism of transcription regulation. Cooperating TFs can be revealed through the analysis of co-occurrence of their motifs. Methods: We applied Motifs Co-Occurrence Tool (MCOT) that predicted pairs of spaced or overlapped motifs (composite elements, CEs) for a single ChIP-seq dataset. We improved MCOT capability for prediction of asymmetric CEs with one of participating motifs possessing higher conservation than another does. Results: Analysis of 119 ChIP-seq datasets for 45 human TFs revealed that almost for all families of TFs the co-occurrence with an overlap between motifs of target TFs and more conserved partner motifs was significantly higher than that for less conserved partner motifs. The asymmetry toward partner TFs was the most clear for partner motifs of TFs from ETS family. Conclusion: Co-occurrence with an overlap of less conserved motif of a target TF and more conserved motifs of partner TFs explained a substantial portion of ChIP-seq data lacking conserved motifs of target TFs. Among other TF families, conservative motifs of TFs from ETS family were the most prone to mediate interaction of target TFs with its weak motifs in ChIP-seq.

This study explores the impact of carbon fiber length and content on the rheological properties and performance of coatings used in lost foam casting. The investigation encompassed fiber lengths of 1 mm, 3 mm, and 6 mm, and fiber contents of 0.2%, 0.5%, and 0.8%. The effects on coating viscosity, shear stress, coating weight, and surface morphology were meticulously evaluated. The results demonstrate that incorporating carbon fibers significantly enhances coating viscosity and shear stress compared to fiber-free coatings, with more pronounced effects observed at higher fiber contents and longer fiber lengths. Nevertheless, excessive fiber content and length can lead to agglomeration, negatively impacting coating uniformity. Optimal fiber length and content were identified, striking a balance between improved rheological properties and coating performance. These findings provide critical insights for the development and industrial application of high-performance coatings in lost foam casting.

Background: Telomere length (TL) shortening process is associated with several known environment and individual determinants. DNA methylation is the most studied epigenetic process and may be associated with TL. We investigated the associations between DNA methylation and TL in peripheral blood. Methods: Methylation wide association study was conducted in 47 women (37.1±8.8 years) with different nutritional status. Association between TL and DNA methylation levels were explored by univariate and multiple linear regression models, corrected by age and Body Mass Index. Corrections for multiple comparisons by Benjamini‐Hochberg test was also performed. WEBGestalt was used to identify pathways that are responsible for regulating TL. Results: We found negative correlations between TL and BMI (r = -0.641; p = 0.001), abdominal circumference (r = -0.622; p = 0.001) and fat mass (r = -0.656; p = 0.001). 44 CpGs sites were associated with TL, independent of age and BMI. The most of these sites were negatively correlated with TL. For the 7 remained sites, DNA hypomethylation were associated with shorter TL. These CpGs were related to nine different pathways, including thermogenesis, cancer, glutamatergic and serotonergic synapse. Conclusion: There is an epigenetic contribution in TL, independent of nutritional status and age. Genes related to TL are involved in important metabolic pathways.

Some evidence supports the influence of the implant macro-design and primary stability. Additionally, tactile perception can be used to assess implant stability when placing the implant. This research aimed to quantify the primary and secondary stability of three implant systems with two different macro geometries (cylindrical and conical) determined through the insertion torque and the implant stability quotient (ISQ) at the moment of implant placement as a function of implant-related factors (length, width, dental arch, and implant location in the arch), intraoperative factors (bone density determined subjectively by the clinician's tactile perception), and patient-related factors (age, gender and bone density determined objectively in the cone beam computed tomography (CBCT). Methods: 102 implants of three implant systems with two different macro geometries (conical and cylindrical) were placed in 53 patients. The insertion torque, the ISQ at the implant placement (ISQ0), and bone quality according to the clinician's tactile sensation were recorded on the day of the surgery. After a three-month healing period, the ISQ was re-evaluated (ISQ3). Results: Cylindrical implants exhibited significantly higher insertion torque and ISQ at the moment of the surgery and after three months than conical implants. Cylindrical implants also showed significantly lower indices of tactile evaluation of bone quality during the implant placement surgery. However, no differences were demonstrated in the bone density measured objectively in the CBCT. (4) Conclusions: The cylindrical implants achieved the highest values for primary stability (Ncm and ISQ) and secondary stability (ISQ after three months). Insertion torque was the variable that most influenced ISQ on the day of the surgery. Implant location (incisors-canines, bicuspids-molars) and the implant macro geometry were the variables that most influenced the secondary stability (ISQ at three months).

When undertaking wind assessment around buildings using large eddy simulation (LES), the implementation of the integral length scale at the inlet for inflow generation is controversial, as real atmospheric length scales require huge computational domains. While length scales significantly influence inflow generation in the domain, their effect on the downstream flow field has not yet, been investigated. In this paper, we validate the effectiveness and accuracy of implementing a reduced turbulence integral length scale for inflow generation in LES results at the rooftop of low-rise buildings and develop a technique to estimate the real local length scales using simulation results. We measure the wind locally and calculate the turbulence length scales from the energy spectrum of the wind data and simulation data. According to these results, there is an excellent agreement between the length scale from simulation and measurement when they are scaled with their corresponding freestream/inlet value. These results indicate that a reduced integral length scale can be safely used for LES to provide a reliable prediction of the energy spectrum as well as the length scales around complex geometries. The simulation results were confidently employed to obtain the best location for a wind turbine installation on low-rise buildings.

Quartz Crystal Microbalance (QCM) is a well-known method to measure the mass of ligands bound to receptor-covered surfaces in various fields, ranging from materials science to biology. Actin molecule is essential in various cellular processes through its function of monomer-to-filament polymerization, forming a double-stranded filament with a 75 nm pitch. In this study, QCM was applied to measure the physical properties of actin, finding that the frequency shifted negatively when monomeric actin bound to the QCM surface, whereas the frequency shifted positively when filaments bound. Using fluorescence light microscopic observations, we have examined whether negative and positive frequency shifts originated from their length. In order to control this process, a severing protein, fragmin was used to change the length of actin filament. When the average length of filaments shortened, the magnitude of positive shift decreased in a concentration-dependent manner. However, shorter filaments showed a negative frequency shift depending on their concentration, showing that the weight derived from the loaded concentration and the function derived from actin polymerization dynamics are detectable. Interestingly, the transition from positive to negative occurred when the average length of actin was ~33 nm, or approximately equal to the half-pitch of filaments. Thus, actin filaments can serve as an excellent standard to measure the mechanical properties of biopolymers. Our results show that the QCM sensor could be both a "weight" and a "function" sensor of biomolecules in vitro.

The exact similarity solutions of two dimensional laminar boundary layer were obtained by Blasius in 1908, however, for two dimensional turbulent boundary layers, no similarity solutions (special exact solutions) have ever been found. In the light of Blasius' pioneer works, we extend Blasius similarity transformation to the two dimensional turbulent boundary layers, and successfully transform the two dimensional turbulent boundary layers partial differential equations into a single ordinary differential equation. By author's Maple code, we numerically solve the ordinary differential equation and produce some useful quantities.

The variable-length arbitrary Lagrange-Euler (ALE)-ANCF finite element, which employ nonrational interpolating polynomials, cannot exactly describe the rational cubic Bezier curves such as conic and circular curves. The rational absolute nodal coordinate formulation (RANCF) finite element, whose reference length (undeformed length) is constant, can exactly represent the rational cubic Bezier curves. A new variable-length finite element called the ALE-RANCF finite element, which is capable of accurately describe the rational cubic Bezier curves, is proposed by combining the desirable features of the ALE-ANCF and RANCF finite element. In order to control the reference length of ALE-RANCF element within a suitable range, element segmentation and merging schemes are proposed. It is demonstrated that exact geometry and mechanic is maintained after the ALE-RANCF element is divided into two shorter ones, and compared with the ALE-ANCF elements, there are smaller deviations and oscillations after two ALE-RANCF elements are merged into a longer one. Numerical examples are presented and the feasibility and advantages of the ALE-RANCF finite element are demonstrated.

Quantum turbulence is characterized by many degrees of freedom interacting non-linearly to produce disordered states, both in space and time. The advances in trapping, cooling, and tuning the interparticle interactions in atomic Bose-Einstein condensates (BECs) make them excellent candidates for studying quantum turbulence. In this work, we investigate the decaying regime of quantum turbulence in a trapped BEC. Although much progress has been made in understanding quantum turbulence, other strategies are needed to overcome some intrinsic difficulties. We present an alternative way of investigating this phenomenon by defining and computing a characteristic length scale, which possesses relevant characteristics to study the establishment of the quantum turbulent regime. One intrinsic difficulty related to these systems is that absorption images of BECs are projected to a plane, thus eliminating some of the information present in the original momentum distribution. We overcome this difficulty by exploring the symmetry of the cloud, which allows us to reconstruct the three-dimensional momentum distributions with the inverse Abel transform. We present our analysis with both the two- and three-dimensional momentum distributions, discussing their similarities and differences. We argue that the characteristic length allows us to visualize the time evolution of the turbulent state intuitively.

With improved measurement and modelling technology, variability has emerged as an essential feature in non-equilibrium processes. While traditionally, mean values and variance have been heavily used, they are not appropriate in describing extreme events where a significant deviation from mean values often occurs. Furthermore, stationary Probability Density Functions (PDFs) miss crucial information about the dynamics associated with variability. It is thus critical to go beyond a traditional approach and deal with time-dependent PDFs. Here, we consider atmospheric data from the Whole Atmosphere Community Climate Model (WACCM) and calculate time-dependent PDFs and the information length from these PDFs, which is the total number of statistically different states that a system passes through in time. Time-dependent PDFs are shown to be non-Gaussian in general, and the information length calculated from these PDFs shed us a new perspective of understanding variabilities, correlation among different variables and regions. Specifically, we calculate time-dependent PDFs and information length and show that the information length tends to increase with the altitude albeit in a complex form. This tendency is more robust for flows/shears than temperature. Also, much similarity among flows and shears in the information length is found in comparison with the temperature. This means a stronger correlation among flows/shears because of a strong coupling through gravity waves in this particular WACCM model. We also find the increase of the information length with the latitude and interesting hemispheric asymmetry for flows/shears/temperature, a stronger anti-correlation (correlation) between flows/shears and temperature at a higher (low) latitude. These results also suggest the importance of high latitude/altitude in the information budge in the Earth's atmosphere, the spatial gradient of the information as a useful proxy for the transport of physical quantities.

Proper regulation of microtubules (MTs) is critical for the execution of diverse cellular processes, including mitotic spindle assembly and chromosome segregation. There are a multitude of cellular factors that regulate the dynamicity of MTs and play critical roles in mitosis. Members of the Kinesin-8 family of motor proteins act as MT-destabilizing factors to control MT length in a spatially and temporally regulated manner. In this review, we focus on recent advances in our understanding of the structure and function of the Kinesin-8 motor domain, and the emerging contributions of the C-terminal tail of Kinesin-8 proteins to regulate motor activity and localization.

The SI unit of length, the Metre, is presently defined by taking the fixed numerical value of the fundamental constant `c', the invariant speed of light in vacuum. This definition has the same physical basis as the previous definition, as the length of the path travelled by light in vacuum during a time interval of 1/299 792 458 of a second. With the atomic standard second defined in terms of the ground state hyperfine transition in Caesium-133, this definition is supposed to provide a universally reproducible standard of length. However, this relies on Einstein's singular postulate that the relative velocity of light in vacuum is an invariant constant that is independent of any inertial motion of the reference laboratory. I argue that the basis of the definition of the standard metre should be changed to the specific form, "the length of the path equal to the two-way propagation of light in vacuum during a time interval of 1/299 792 458 of a second", to be compatible and consistent with the fact that it is only the two-way relative velocity that is consistent with being an invariant. The null result in the Michelson-Morley two-way experiment, and in all such experiments to date, is consistent with a Galilean one-way propagation of light (relative velocity $c'=c\pm v$) as well as an invariant relative velocity of light. All practical methods and protocols related to the implementation of length standard involve also a two-way propagation, not conforming to the present definition. Besides, this redefinition is absolutely necessary because the relative velocity of light in one-way propagation is indeed Galilean, and not an invariant, as proved here in multiple ways including a direct experiment.

Interstitial lung diseases (ILDs) constitute a group of more than 200 disorders, being idiopathic pulmonary fibrosis (IPF) one of the most frequent. Telomere length (TL) shortening causes loss of function of the lung parenchyma. However, little is known about its role as prognostic factor in ILD patients. With the aim of investigating the role of TL and telomerase activity in the prognosis of patients affected by ILDs, we analysed lung tissue samples from 61 patients. We measured relative TL and telomerase activity by conventional procedures. Both clinical and molecular parameters were associated with overall survival by the Kaplan-Meier method. Patients with IPF had poorer prognosis than patients with other ILDs (p = 0.034). When patients were classified according to TL, those with shortened telomeres reported lower overall survival (p = 0.085); differences reached statistical significance after excluding ILD patients who developed cancer (p = 0.021). In a Cox regression analysis, TL behaved as a risk-modifying variable for death associated with rheumatological disorders (RD) co-occurrence (p = 0.029). Also, in patients without cancer, ferritin was significantly increased in cases with RD and IPF co-occurrence (p = 0.032). In relation to telomerase activity, no significant differences were detected. In conclusion, TL in lung tissue emerges as a prognostic factor in ILD patients, Specifically, in cases with RD and IPF co-occurrence, TL can be considered as a risk-modifying variable for death.

Healthcare professionals and resource planners can use healthcare delivery process mining to ensure the optimal utilisation of scarce healthcare resources when developing policies. Within hospitals, patients' Length of Stay (LOS) and volume of admitted patients, in terms of number and characteristics (age, gender, and social deter-minants), are significant factors determining daily resource requirements. In this study, we used Coxian phase-type Distribution (C-PHD) based Phase-Type Survival (PTS) trees for analysing how covariates such as admission date, gender, age, district, and admissions source influence the admission rate and LOS distribution. PTS trees. This study used a two-year data set (2011-2012) of patients admitted to the Emergency Department at Mater Dei Hospital to generate models and an independent one-year data set (2013) of patients admitted to the Emergency Department at Mater Dei Hospital to evaluate. The PTS tree effectively clusters patients based on their LOS, considering the prognostic significance of different covariates related to patients' characteristics. Charac-terising these covariates provided meaningful results about LOS. Similarly, the PTS tree was used to effectively cluster patients based on the admission rate, considering the prognostic significance of these covariates.

Tanzania like any other developing countries is depending on uncertain rainfall for their subsistence and commercial agriculture. In this paper the start and end of rains for Mbeya Meteorological Station in Tanzania Mainland was analyzed and critically examined. Data were kindly given by Tanzania Meteorological Agency (TMA) during face to face Statistics in Applied Climatology (fSIAC) workshop which was held at Sokoine University of Agriculture (SUA) the year 2013 prior to online Course on Statistics in Applied climatology (eSIAC). In this study data were analyzed using Instat (for windows version 3.3.7) package developed by the Statistical Services Centre of the University of Reading. The analysis showed that much of rains start early December all the way to May. There is also 50 percent chance of having below and above the mean for both total annual rainfall and number of rains, in other word one in two years the total rains are below means likewise the number of rain days.

The construction of reinforced concrete (RC) structures inevitably consumes an excessive number of rebars, leading to significant cutting waste and carbon emissions. Extensive research has been conducted to minimize this issue and its consequences; however, these methods consistently consume a substantial number of rebars. This includes a previous study that utilizes the lap splice position optimization and special-length rebar concept without considering the lapping zone regulation. Moreover, conventional lap splices pose inherent drawbacks that could jeopardize the structural integrity of RC members. In contrast, mechanical couplers eliminate the need for rebar lapping, effectively reducing rebar consumption. This research aims to evaluate the impact of an integrated mechanical coupler and special-length-priority minimization algorithm on the reduction in rebar consumption and cutting waste in RC columns, achieving near-zero cutting waste. To validate the effectiveness of the proposed algorithm, it was applied to the column rebars of an RC building. The results revealed a significant reduction in ordered rebar consumption by 18.25%, accompanied by substantial reductions in cutting waste (8.93%), carbon emissions (12.99%), and total costs (10.81%) compared with a previous study. The outcomes provide the industry with insights into further reducing rebar consumption and its related consequences. Applying the proposed algorithm to various construction projects will further amplify the corresponding benefits.

The aim of this study was to create a novel machine learning (ML) algorithm for predicting the post-pubertal mandibular length and Y-axis in females. Cephalometric data from 176 females with Angle Class I occlusion were used to train and test 7 ML algorithms. For all ML methods tested, the mean absolute errors (MAEs) for the 2-year prediction ranged from 2.78-5.40 mm and 0.88-1.48 degrees, respectively. For the 4-year prediction, MAEs of mandibular length and Y-axis ranged from 3.21-4.00 mm and 1.19-5.12 degrees, respectively. The most predictive factors for post-pubertal mandibular length were mandibular length at previous timepoints, age, sagittal positions of the maxillary and mandibular skeletal bases, mandibular plane angle, and anterior and posterior face heights. The most predictive factors for post-pubertal Y-axis were Y-axis at previous timepoints, mandibular plane angle, and sagittal positions of the maxillary and mandibular skeletal bases. ML methods were identified as capable of predicting mandibular length within 3 mm, and Y-axis within 1 degree. Compared to each other, all of the ML algorithms were similarly accurate, with the exception of MLP regressor.

In China, the demand for rabbit meat is also increasing, and the production for rabbit meat is important. However, the underlying mechanisms of regulate skeletal muscle growth and development in rabbits remain unclear. The purpose of this study was to identify candidate genes related to skeletal muscle growth in rabbits and explore their potential regulatory mechanisms. RNA-seq technique was used to compare the differences of skeletal muscle transcriptome in Fujian white rabbits at different developmental stages (day 20 and 26 of embryos and birth 1, 30 and 60-day-olds) with a total of 25 individual selected. A total of 9737 DEGs that were acquired from the five groups were annotated into three ontologies of the GO database: biological process (BP), cell component (CC), and molecular function (MF). For KEGG analysis, there are 8249 genes were enriched in 1148 pathways, of which 67 pathways were significantly enriched, mainly in Hypertrophic cardiomyopathy (HCM), the PPAR signaling pathway, MAPK signaling pathway. Among all comparison groups, SE was the most abundant AS event. Real-time PCR verified that the expression patterns of differential genes were consistent with the transcriptome sequencing results. These results will provide a molecular regulation mechanism of muscle growth and development in Fujian white rabbits, and should serve an important theoretical basis for improving meat performance and growth rate of Chinese local meat rabbit breeds.