Background: Three drug-combinations, ipilimumab-nivolumab (Ipi-Nivo), pembrolizumab-axitinib (Pembro-Axi) and avelumab-axitinib (Ave-Axi), have received regulatory approvals in USA and Europe for the treatment of metastatic renal cell carcinoma with clear cell component (mRCC). However, no head-to-head comparison data are available to identify the best option. Therefore, we aimed to compare these new treatments in the first-line setting. Methods: We conducted a systematic search in Pubmed, the Cochrane library and clinicaltri-al.gov website from January 2015 to October 2019, for any randomized controlled trials of treatment-naïve patients with mRCC. The process was performed according to PRISMA guide-lines. We performed a Bayesian network meta-analysis with two different approaches. The out-comes for analysis were overall survival, progression-free survival, and objective response rate. Results: Our search identified 3 published phase 3 randomized clinical trials (2835 patients). In the contrast-based model, Ave-Axi (SUCRA: 83%) and Pembro-Axi (SUCRA: 80%) exhibited the best ranking probabilities for PFS. For OS, Pembro-Axi (SUCRA: 96%) was the most pref-erable option against Ave-Axi and Ipi-Nivo. Objective response rate analysis showed Ave-Axi as the best (SUCRA= 94%) and Pembro-Axi as second best option. In the parametric models, risk of progression was comparable for Ave-Axi and Ipi-Nivo, whereas Pembro-Axi exhibited a lower risk during the first 6 months of treatment and a higher risk afterward. Furthermore, Pembro-Axi exhibited a net advantage in terms of OS over the two other regimens, while Ave-Axi was the least preferable option. Conclusions: Overall evidences suggested pembrolizumab plus axitinib may be the best option.

Pathogenic adenovirus (Ad) infections are widespread but typically mild and transient, except in the immunocompromised. As vectors for gene therapy, vaccine and oncology applications, Ad based platforms offer advantages including ease of genetic manipulation, scale of production and well established safety profiles, making them attractive tools for therapeutic development. However, the immune system often poses a significant challenge that may need to be overcome for adenovirus based therapies to be truly efficacious. Both pre-existing anti-Ad immunity in the population as well as the rapid development of an immune response against engineered adenoviral vectors can have detrimental effects upon the downstream impact of an adenovirus-based therapeutic. This review focusses on the different challenges posed, including pre-existing natural immunity and anti-vector immunity induced by a therapeutic, both in context of the innate and adaptive immune responses. We summarize different approaches developed with the aim of tackling these problems, as well as their outcomes and potential future applications.

Ulcerative colitis (UC) is a chronic autoimmune disorder affecting the colonic mucosa. UC is a subtype of inflammatory bowel disease along with Crohn’s disease and presents with varying extraintestinal manifestations. No single etiology for UC has been found, but a combination of genetic and environmental factors is suspected. Research has focused on the role of intestinal dysbiosis in the pathogenesis of UC, including the effects of dysbiosis on the integrity of the colonic mucosal barrier, priming and regulation of the host immune system, chronic inflammation, and progression to tumorigenesis. Characterization of key microbial taxa and their implications in the pathogenesis of UC and colitis-associated cancer (CAC) may present opportunities for modulating intestinal inflammation through microbial-targeted therapies. In this review, we will discuss the microbiota-immune crosstalk in UC and CAC, as well as the evolution of microbiota-based therapies.

Dendritic cell (DC) cancer vaccines are a promising therapeutic approach, leveraging the immune system to fight tumors. These vaccines utilize DCs' ability to present tumor-associated antigens to T cells, triggering a robust immune response. DC vaccine development has progressed through three generations. The first generation involved priming DCs with tumor-associated antigens or messenger RNA outside the body, showing limited clinical success. The second generation improved efficacy by using cytokine mixtures and specialized DC subsets to enhance immunogenicity. The third generation uses blood-derived DCs to elicit a stronger immune response. Clinical trials indicate that cancer vaccines have lower toxicity than traditional cytotoxic treatments. However, achieving significant clinical responses with DC immunotherapy remains challenging. Combining DC vaccines with immune checkpoint inhibitors (ICIs) such as anti-cytotoxic T-lymphocyte Antigen 4 and anti-programmed Death-1 antibodies has shown promise by enhancing T cell responses and improving clinical outcomes. These combinations can transform non-inflamed tumors into inflamed ones, boosting ICIs' efficacy. Current research is exploring new checkpoint targets like LAG-3, TIM-3, and TIGIT, considering their potential with DC vaccines. Additionally, engineering T cells with chimeric antigen receptors or T cell receptors could further augment the anti-tumor response. This comprehensive strategy aims to enhance cancer immunotherapy, focusing on increased efficacy and improved patient survival rates.

Triple-negative breast cancer (TNBC), lacking specific receptors found in other breast cancer subtypes, poses significant treatment challenges due to limited therapeutic options. Therefore, it is necessary to develop novel treatment approaches for TNBC. In the last few decades, many attempts have been reported for alternative tools for TNBC treatment: immunotherapy, radiotherapy, targeted therapy, combination therapy, and nanotechnology-based therapy. Among them, combination therapy and nanotechnology-based therapy show the most promise for TNBC treatment. This review outlines recent advancements in these areas, highlighting the efficacy of combination therapy (immunotherapy paired with chemotherapy, targeted therapy, or radiotherapy) in both preclinical and clinical stages and nanotechnology-based therapies utilizing various nanoparticles loaded with anticancer agents, nucleic acids, immunotherapeutics, or CRISPRs in preclinical stages for TNBC treatment.

Osteoimmunology was coined about twenty years ago to identify a strict cross talk between bone niche and immune system both in physiological and pathological activities, including cancer. Several molecules are involved in the complex interaction between bone niche, immune and cancer cells. The Receptor Activator ok NF-kB (RANK)/RANK Ligand (RANKL/Osteoprotegerin (OPG) pathway plays a crucial role in bone cells/cancer interactions with subsequently immune system control failure, bone destruction, inhibition of effect and metastasis outcome. The bidirectional cross talk between bone and immune system could became a potential target for anticancer drugs. Several studies evidenced a direct anticancer role with improved survival of bone-targeted therapies such as bisphosphonates and RANKL antagonist Denosumab. Conversely, initial data evidenced a possible anti-bone resorption effect of systemic anticancer drugs through and immunomodulation activity, i.e. new generation antiandrogens (Abiraterone) in prostate cancer. All data could open a future rationale of combined bone, immunologic and targeted therapies in cancer treatment.

Asymmetric lithium salts, such as Lithium (difluoromethanesulfonyl)(trifluoromethanesulfonyl)imide (LiDFTFSI), have been demonstrated to surpass traditional symmetric lithium salts with improved Li+ conductivity and the capacity to generate stable solid electrolyte interphase (SEI) while maintaining compatibility with aluminum (Al0) current collector. However, the intrinsic reductive mechanism through which LiDFTFSI influences battery performance remains unclear and under debate. Herein, the detailed SEI reactions of LiDFTFSI-based electrolytes were investigated by combining density functional theory and molecular dynamics, aiming to clarify the formation process and atomic structure of SEI. Our results show that asymmetric DFTFSI– weakens the interaction between carbonate solvents and Li+, and substantially alter the solvation structure, exhibiting a well-balanced coordination capacity to bis(trifluoromethanesulfonyl)imide (TFSI–). Nanoseconds hybrid molecular dynamics simulation further reveals that the preferential decomposition of LiDFTFSI produces sufficient LiF and Li2O to facilitate a robust SEI. Moreover, the abundant F– generated from LiDFTFSI decomposition accumulates on the Al surface and subsequently combines with Al3+ from the current collector to form AlF3, potentially inhibiting corrosion of the current collector. Overall, these findings elucidate how LiDFTFSI regulates the solvation sheath and SEI structure, advancing the development of high-performance electrolytes compatible with current collector.

This investigation explores the potential of enhancing aqueous zinc-ion batteries (AZIBs) through the introduction of a novel cathode material, NH4V4O10 (NVO), combined with reduced graphene oxide (rGO). Utilizing Density Functional Theory (DFT), it was hypothesized that the incorpora-tion of rGO would increase the interlayer spacing of NVO and diminish the charge transfer in-teractions, thus promoting enhanced diffusion of Zn2+ ions. These theoretical predictions were substantiated by experimental data acquired from hydrothermal synthesis, which indicated a marked increase in interlayer spacing. Significantly, the NVO-rGO composite exhibits remarkable cyclic durability, maintaining 95% of its initial specific capacity of 507 mAh g−1 after 600 cycles at a current density of 5 A g−1. The electrochemical performance of NVO-rGO not only surpasses that of pristine NVO but also outperforms the majority of existing vanadium oxide cathode materials reported in the literature. This study underscores the effective integration of theoretical insights and experimental validation, contributing to the advancement of high-performance energy storage technologies.

This study explores the enhancement of aqueous zinc-ion batteries (AZIBs) using ammonium-enhanced vanadium oxide cathodes. Density Functional Theory (DFT) calculations reveal that NH₄⁺ incorporation into V₆O₁₆ lattices significantly facilitates Zn²⁺ ion diffusion by reducing electrostatic interactions, acting as a structural lubricant. Subsequent experimental validation using (NH₄)₂V₆O₁₆ cathodes synthesized via a hydrothermal method corroborates the DFT findings, demonstrating remarkable electrochemical stability with a capacity retention of 90% after 2000 cycles at 5 A g⁻¹. These results underscore the potential of NH₄⁺ in improving the performance and longevity of AZIBs, providing a pathway for sustainable energy storage solutions.

This study presents the synthesis and electrochemical evaluation of nitrogen-doped vanadium oxide (N-V2O3/C) as a cathode material for aqueous zinc-ion batteries (AZIBs), using a hydrothermal method. Compared to undoped V2O3/C, N-V2O3/C exhibits enhanced electrical conductivity, capacity, and electrochemical kinetics, attributed to the incorporation of pyridinic and pyrrolic nitrogen. Initial charge-discharge cycles indicate phase transitions to amorphous vanadium oxides, enhancing conductivity. N-V2O3/C shows a high specific capacity of 168.4 mAh g−1 at 10 A g−1 and remarkable reversibility, highlighted by the transient existence of intermediate species during cycling. Optimal electrochemical performance is achieved with a vanadium to nitrogen molar ratio of 2:3, indicating the significant impact of nitrogen doping concentration on the material’s efficiency. This work underscores the potential of N-V2O3/C as a superior cathode material for AZIBs.

Using density functional theory (DFT), the density of states of NH4V3O8 (NVO) was analyzed pre and post-oxygen defects (Od) formation. The findings revealed a reduced bandgap in NVO after Od introduction, emphasizing the role of Od in enhancing conductivity of the material, thus improving its electrochemical attributes. Through the water bath method, both NVO and its oxygen-deficient counterpart, (NH4)2V10O25⸱8H2O (NVOd), were synthesized as potential cathode materials for aqueous zinc-ion batteries (AZIBs). Experimental outcomes resonated with DFT predictions, highlighting the beneficial role of oxygen defects in boosting electrical conductivity. Notably, the refined material displayed a remarkable capacity of 479.3 mAh g-1 at 0.1 A g-1, underscoring its promise for advanced energy storage solutions.

Perturbation in the microbial population/colony index has harmful consequences on human health. Both biological and social factors influence the composition of the gut microbiota and promote gastric diseases. Changes in the gut microbiota manifest in disease progression owing to epigenetic modification in host which influences differentiation and function of immune cells adversely. Uncontrolled use of antibiotics; chemotherapeutic drugs and change in the diet pattern usually contribute to the changes in the colony index of sensitive strains known to release microbial content in the tissue micromillieu. Ligands released from dying microbes induce TLR mimicry on interaction with TLR abnormally which skew hypoxia and sterile inflammation contributing to severity of disease like IBD autoimmunity and cancer. Various modalities/interventions practiced across the globe and future strategies for microbiota based therapeutic approaches with special emphasis on tumor and inflammatory diseases are reviewed here. Therefore the major aim and scope of this manuscript is to both discuss various modalities/interventions across the globe and to design future microbiota based therapeutic approaches for mitigating the burden with special emphasis on tumor and Inflammatory diseases.

This study reports on the development of bio-based hydrophobic coatings for packaging papers through deposition of polyhydroxybutyrate (PHB) particles in combination with nanofibrillated cellulose (NFC) and plant wax. In a first approach, PHB particles in micrometer range (PHB-MP) were prepared through a phase-separation technique providing internally nanosized structures. The particles were transferred as a coating by dip-coating filter papers in the particle suspension, followed by sizing with a carnauba wax solution. This approach allowed partial to almost full surface coverage of PHB-MP over the paper surface resulting in static water contact angles of 105° to 122° and 129° to 144° after additional wax coating. In a second approach, PHB particles with submicron sizes (PHB-SP) were synthesized by an oil-in-emulsion (o/w) solvent evaporation method, and mixed in aqueous suspensions with 0 to 7 wt% NFC. After dip-coating filter papers in PHB-SP/NFC suspensions and sizing with a carnauba wax solution, static water contact angles of 112° to 152° were obtained. The intrinsic properties of the particles were analyzed by scanning electron microscopy, thermal analysis and infrared spectroscopy, indicating higher crystallinity for PHB-SP than PHB-MP. The chemical interactions between the more amorphous PHB-MP particles and paper fibers were identified as an esterification reaction, while the morphology of the NFC fibrillar network was playing a key role as binding agent in the retention of more crystalline PHB-SP at the paper surface, hence contributing to higher hydrophobicity.

This work presents a novel approach for the study of the movement of droplets on inclined surfaces under the influence of gravity and chemical heterogeneities. The developed numerical methodology uses data-driven modeling to extend the applicability limits of an analytically derived reduced-order model for the contact line velocity. More specifically, while the reduced-order model is able to capture the effects of the chemical heterogeneities to a satisfactory degree, it does not account for gravity. To alleviate this shortcoming, datasets generated from direct numerical simulations are used to train a data-driven model for the contact line velocity, which is based on the Fourier neural operator and corrects the reduced-order model predictions to match the reference solutions. This hybrid surrogate model, which comprises of both analytical and data-driven components, is then integrated in time to simulate the droplet movement, offering a speedup of five orders of magnitude compared to direct numerical simulations. The performance of this hybrid model is quantified and assessed in different wetting scenarios, by considering various inclination angles and values for the Bond number, demonstrating the accuracy of the predictions as long as the adopted parameters lie within the ranges considered in the training dataset.

As a member of smart materials, electrorheological elastomers (EREs) formed by pre-treating active electrorheological particles are attracting more and more attention. In this work, four Mg-doped strontium titanate particles with spherical, dendritic, flake-like and pinecone-like morphorlogies were obtained by hydrothermal and low-temperature co-precipitation. XRD, SEM, Raman and FT-IR were used to characterize the obtained products. The results showed that the sizes of Mg-doped strontium titanates are about 1.5‒2.0 μm, and the phase structure are dominated by cubic crystal. These Mg-doped strontium titanates were dispersed in a hydrogel composite elastic medium. Then, Mg-doped strontium titanate/glycerol/gelatin electrorheological composite hydrophilic elastomers were obtained with or without electric field. The electric field response properties of Mg-doped strontium titanate composite elastomers were investigated. It concluded that dendritic Mg-doped strontium titanate composite elastomers is high-performance EREs. And the maximum value of energy storage modulus of Mg-doped strontium titanate composite elastomers has achieved 8.70 MPa. This high electrorheological performance of the products is helpful for their applications in vibration control, force transducers, smart structures, dampers, and other fields.

Accumulating evidences demonstrate that the host genome's epigenetic modificationsare essential for living organisms to adapt extreme conditions.DNA methylation, covalent modifications of histone, andinter-association of non-coding RNAs facilitate the cellular manifestation ofepigenetic changes in the genome. Out of various factors involved in the epigenetic programming of the host, miRNA (microRNA) and LncRNA (Long non-coding RNA) are new generationnon-coding molecules that influence a variety of cellular processes like immunity, cellular differentiation, and tumor development. During tumor development, temporal changes in miRNA/LncRNA rheostat influence sterile inflammatory responses accompanied by the changes in the carcinogenic signalling in the host. At the cellular level, this is manifested by the up-regulation of Inflammasome and inflammatory pathways, which promotes cancer-related inflammation. In view of this, we discuss the potential of lncRNA and miRNA directed interventions in regulating inflammation and tumor development in the host.

This paper numerically investigates a 3D mesh independency study of a straight blade horizontal axis tidal turbine modelled using Computational Fluid Dynamics (CFD). The solution was produced by employing two turbulence models, the standard k-ε model and Shear Stress Transport (SST) in ANSYS CFX. Three parameters were investigated: mesh resolution, turbulence model, and power coefficient in the initial CFD, analysis. It was found that the mesh resolution and the turbulence model affect the power coefficient results. The power coefficients obtained from the standard k-ε model are 15% to 20% lower than the accuracy of the SST model. It can also be demonstrated that the torque coefficient increases with the increasing Tip Speed Ratio (TSR), but drops drastically after TSR = 5 and k-ε model failing to capture the non-linearity in the torque coefficient with the increasing TSR.

In this paper, carbon nanotubes modified screen-printed electrode (CNTs/SPE) was prepared and the CNTs/SPE was employed for the electrochemical determination of antioxidant substance Chlorogenic acids (CGAs). A pair of well-defined redox peak of CGA was observed at the CNTs/SPE in 0.10 mol∙L^-1 acetic acid-sodium acetate buffer (pH 6.2) and electrode process is adsorption-controlled. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) method for the determination of CGA were proposed based on the CNTs/SPE. Under the optimal conditions, the proposed method exhibited linear ranges from 4.73×10^-7 to 4.45×10^-5 mol∙L^-1, the linear regression equation was Ipa(µA) = 4.1993 C (mol∙L^-1)+1.1039 (r = 0.9976) and the detection limit for CGA could reach 3.25×10^-6 mol∙L^-1. The recovery of matrine was 94.74~106.65% (RSD = 2.92%) in coffe beans. The proposed method is quick, sensitive, reliable, and can be used for the determination of CGA.

Intrahepatic cholangiocarcinoma (ICCA) is a malignant epithelial neoplasm characterized by biliary differentiation within the liver. ICCA is molecularly heterogeneous and exhibits a broad spectrum of histopathological features. It is a highly aggressive carcinoma with high mortality and poor survival rates. ICCAs are classified into two main subtypes: small duct type and large duct types. These two tumor types have different cell origins and clinicopathological features. ICCAs are characterized by numerous molecular alterations, including mutations in KRAS, TP53, IDH1/2, ARID1A, BAP1, BRAF, SAMD4, and EGFR, and FGFR2 fusion. Two main molecular subtypes–inflammation and proliferation–have been proposed. Recent advances in high-throughput assays using next-generation sequencing have improved our understanding of ICCA pathogenesis and molecular genetics. The diagnosis of ICCA poses a significant challenge for pathologists because of its varied morphologies and phenotypes. Accurate diagnosis of ICCA is essential for effective patient management and prognostic determination. This article provides an updated overview of ICCA pathology, focusing particularly on molecular features, histological subtypes, and diagnostic approaches.

Drug-induced liver disease represents one of the main problems in the therapeutic field. As with most pathologies, also in this case various risk factors can be recognised, such as age, sex, but also the gut microbiota. Therefore all drugs on the market can, in fact, cause hepatotoxicity of varying degrees. Drugs used in the treatment of IBD can also cause these adverse effects and even lead to DILI. In this review, the various classes of drugs used in the treatment of IBD were taken into consideration and the various adverse effects on the liver were illustrated. In particular, a major role has emerged regarding hepatotoxicity of immunosuppressants. Biological drugs, however, seem to be responsible for these complications to a much lesser extent.

Omicron SARS-CoV-2 variants have dominated the strains of COVID-19 circulating worldwide for the last two years. Although the mortality rate of the COVID-19 Omicron variants is only approximately half that of previous variants, vaccines effective against Omicron are needed. Demonstrating that a SARS-CoV-2 vaccine can protect against Omicron in an in vivo infection model, particularly in that of Syrian hamsters, is important for the preclinical characterization of SARS-CoV-2 vaccines. Here, we report on the evaluation of W-PreS-O for its ability to protect Syrian hamsters against infection by Omicron. W-PreS-O is a chimeric vaccine based on a single fusion protein (W-PreS-O), combining RBDs from Wuhan hu-1 wild-type and Omicron adsorbed to aluminum hydroxide. The Syrian hamsters were immunized three times at three-week intervals with W-PreS-O or with aluminum hydroxide (placebo), and then they were infected with Omicron BA.1. Non-infected and non-vaccinated animals served as controls. Neutralizing antibody (nAB) titers, weight, lung symptoms (i.e., edema and pneumonia index), and viral loads, as measured using RT-PCR in the upper and lower respiratory tracts, were determined. In addition, infectious virus titers from the lungs were measured using a plaque-forming assay. W-PreS-O-vaccinated hamsters developed robust nABs against Omicron, showed almost no development of pneumonia, and had significantly reduced infectious virus titers in the lungs. Importantly, the viral loads in the nasal cavities of W-PreS-O-vaccinated hamsters were close to or above the PCR cycle threshold considered to be non-infectious. Our data provide compelling evidence demonstrating that the W-PreS-O vaccine has protective effect against Omicron in a Syrian hamster in vivo infection model. W-PreS-O is therefore a highly promising candidate vaccine for Omicron infections, and it should be further evaluated in clinical studies.

Alkaloid-based urea derivatives were produced with high yield through the reaction of anabasine and cytisine with isoxazolylphenylcarbamates in boiling benzene. Their antitumor ac-tivity in combination with the commonly used six anticancer drugs namely cyclophosphane, fluorouracil, etoposide, cysplatine, ribomustine with different mechanisms of action was investi-gated. Based on the quantum chemical calculations data and molecular docking, hypotheses have been put forward to explain their mutual influence when affecting on the С6 rat glioma model cells.

Hereditary Hemorrhagic Telangiectasia (HHT), also known as Osler-Weber-Rendu syndrome, is a rare and inherited vascular disorder, characterized by the development of arteriovenous malformations (AVMs) in various organs and telangiectasia (small AVM) in the mucocutaneous. The majority of HHT patients have haploinsufficiency of genes involved in the transforming growth factor-beta (TGFβ) signaling pathway, including endoglin (ENG), activin receptor-like kinase 1 (ALK1, also known as ACVRL1), or SMAD4. Active angiogenesis is also required for telangiectasia and AVM development. Anti-angiogenic strategies have been tested in patients and animal models extensively. However, the exact mechanisms for telangiectasia and AVM development remain unclear. In this review, we discuss recent advances in identifying disease mechanisms, and potential therapeutic targets.

Radiotherapy for cancer has been known to affect the responses of immune cells, especially those of CD8+ T cells that play a pivotal role in anti-tumor immunity. Clinical success of immune checkpoint inhibitors led to an increasing interest into the ability of radiation to modulate CD8+ T cell responses. Recent studies that carefully analyzed the CD8+ T cell responses following radiotherapy suggest the beneficial roles of radiotherapy on anti-tumor immunity. In addition, numerous clinical trials that evaluate the efficacy of combining radiotherapy with immune checkpoint inhibitors are undergoing. In this review, we summarize the current status of knowledge regarding the changes of CD8+ T cells following radiotherapy from various preclinical and clinical studies. Furthermore, key biologic mechanisms that underlie such modulation, including both direct and indirect effects, are described. Lastly, we discuss the current evidence and essential considerations for harnessing radiotherapy as a combination partner for immune checkpoint inhibitors.

Regenerative Medicine and Tissue Engineering are interdisciplinary fields that combine cell biology, material science, and bioengineering to develop therapies for tissue repair and regeneration. This field has made significant advances in recent years, particularly in the use of stem cells and biomaterials. Advancements in cell-based therapies have involved the use of cells to repair or replace damaged tissues and organs. Tissue engineering involves using scaffolds and growth factors to promote tissue regeneration. However, a major challenge in this field is the formation of adhesions, which can cause complications, such as intestinal obstruction and chronic pain. Adhesion barriers are used to prevent adhesion of tissues and organs during recovery, thereby reducing the risk of complications. Anti-adhesion materials, such as polysaccharides, proteins, and synthetic polymers, are used to create a physical barrier between tissues and prevent adhesion. These materials can be used alone or in combination, but their effectiveness varies.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

The targeting-Her-2/neu therapy by passive application with trastuzumab is associated with acquired resistance and subsequent metastasis development, attributed to upregulation of tumoral PD-L1 expression and downregulation of Her-2/neu. We aimed to investigate this association, following active immunization with our recently constructed B cell–peptide based Her-2/neu vaccines in both preclinical and clinical settings. Immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and combined positive score (CPS), were applied to evaluate Her-2/neu and PD-L1 expression using a murine syngeneic tumor model for Her-2/neu lung metastases, and tumor biopsies from a gastric cancer patient with disease progression. A significant and concomitant reduction of Her-2/neu and upregulation of PD-L1 expression was observed in the vaccinated mice, after 7 but not after 4 weeks of metastases development. A significant increase of tumor-infiltrating B lymphocytes was observed at both time points. Downregulation of Her-2/neu and upregulation of PD-L1 were observed in a patient’s primary tumor at the disease progression time point but not prior to vaccination (Her-2/neu IHC: 3 to 0, FISH: 4.98 to 1.63; PD-L1 CPS: 0% to 5%). Our results further underline the need for combination therapy by targeting PD-L1 to prevent metastasis formation and immune evasion of Her-2/neu positive and PD-L1 negative tumor cells.

Background: Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy. We determined the validity of a rare-cell detection platform and demonstrated the usefulness of a certain rare cell subset as a novel approach to characterize the breast cancer system. Methods: Linearity of the Rarmax® platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 non-cancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts and inflammation-associated cells, was performed using a phenotype and morphology-based classification system. Results: The platform performed linearly over a range of 5-950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 50% and 85.7%, respectively and the specificity was 100% and 96.6%, respectively. Conclusion: The present study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances and the therapeutic effects of metabolic ketogenic therapy remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

Within phototherapy, a grand challenge in clinical cancer treatments is to develop a simple, cost-effective, and biocompatible approach to treat this disease using ultra-low doses of light. Carbon-based materials (CBM), such as graphene oxide (GO), reduced GO (r-GO), graphene quantum dots (GQDs), and carbon dots (C-DOTs), are rapidly emerging as a new class of thera-peutic materials against cancer. This mini-review summarizes the progress in lasts years re-garding the applications of CBM in photodynamic (PDT) and photothermal (PTT) therapies for tumor destruction. The current understanding of the performance of modified CBM, hybrids and composites, is also addressed. This approach seeks to achieve an enhanced healing action by im-proving and modulating the properties of CBM to treat various types of cancer. Metal oxides, organic molecules, biopolymers, therapeutic drugs, among others, have been combined with CBM to treat cancer by PDT, PTT, or synergistic therapies.

Currently, urban renewal activities in China are booming. And promoting the renovation of public buildings is the key due to its large scale, high cost and significant impact to the nature and social environment. To reduce the ambiguity and uncertainty in evaluating the potential for renewal of existing public buildings, a renewal potential evaluation model combining game theory combination weighting method and cloud model theory is proposed. The paper constructs a comprehensive evaluation index system based on relevant standards and literature. Game theory is used to optimize the weights obtained by AHP and entropy weight methods to obtain a combined weight. MATLAB programming is used to calculate the comprehensive cloud parameters of the evaluation index for the potential renewal of existing public buildings and therefore generate cloud Graphs. Through case study in Nanjing of China, it has been demonstrated that the combination empowerment cloud model can objectively reflect the relationship between the fuzziness and randomness of evaluation indicators for public building renewal potential. The expression of cloud Graphs can intuitively reflect the magnitude of renewal and renovation potential and the degree of uncertainty in evaluation results. The research result provides useful references for the sustainable utilization of building resources in the era of building.

Enclosed public spaces are the hotspots for airborne disease transmission. To measure and maintain indoor air quality in terms of airborne transmission, an open source, low cost and distributed array of Particulate Matter Sensors has been developed and named as Dynamic Aerosol Transport for Indoor Ventilation or DATIV system. This system can use multiple Particulate Matter Sensors (PMS) simultaneously and can be remotely controlled using a Raspberry Pie based operating system. The data acquisition system can be easily operated using the GUI within any common browser installed on a remote device such as a PC or Smartphone with corresponding IP address. The software architecture and validation measurements are presented together with possible future developments.

Androgenetic alopecia, the most common cause of hair loss affecting both men and women, is typically treated using pharmaceutical options such as minoxidil and finasteride. While these medications work for many individuals, they are not suitable options for all. To date, the only non-pharmaceutical option that the United States Food and Drug Administration has cleared as a treatment for androgenetic alopecia is low-level laser therapy (LLLT). Various clinical trials utilizing LLLT devices of various types are available. However, a myriad of other physical treatments for this form of hair loss are reported in the literature. This review evaluated the effectiveness of microneedling, pulsed-electromagnetic field (PEMF) therapy, low-level laser therapy (LLLT), fractional laser therapy, and non-ablative laser therapy for the treatment of androgenetic alopecia (AGA). It also explores the potential of multimodal treatments combining these physical therapies. LLLT has the majority of evidence in the literature as a physical therapy for androgenetic alopecia. However, other physical treatments, such as non-ablative laser treatments, and multimodal approaches, such as PEMF-LLLT, seem to have the potential to be equally or more promising and merit further exploration.

The impact of financial risks extends beyond the normal operation and survival of industrial and commercial enterprises and financial institutions. They also have the potential to impede the stable development of a country's and even the world's financial economy. This is clearly demonstrated by the severe consequences of the frequent financial crises that have occurred in recent years. It thus follows that the prevention of financial risks has become one of the core tasks of the operation and management of industrial and commercial enterprises and financial institutions. Portfolio optimization techniques are employed in the construction of a variety of asset allocation models, with reinforcement learning algorithms used to dynamically adjust investment strategies with the objective of maximizing returns and minimizing risks. The preliminary construction of an asset allocation model is achieved through the utilization of a genetic algorithm. Genetic algorithms emulate the processes of natural selection and genetic variation to identify the optimal portfolio of assets that will yield the greatest returns at a pre-established level of risk. Subsequently, the Deep Q-Learning algorithm is introduced to facilitate dynamic adjustments and optimization of the asset allocation, based on the initial construction. Deep Q-learning employs deep neural networks to forecast the prospective returns of disparate investment strategies, thereby optimizing the decision-making process through continuous learning and updating. The combination of genetic algorithms and deep Q-learning enables the system to identify the optimal investment strategy under a diverse range of initial conditions and to adapt it in real-time to respond to market fluctuations and uncertainties. The experimental analysis demonstrates that the proposed method exhibits an exemplary capacity for risk control and a robust ability to generate stable income growth across diverse market environments. In simulation experiments, portfolios constructed using this method demonstrate lower volatility and higher average returns than those generated through traditional methods.

As new treatment modalities are being explored in neuro-oncology, viruses are emerging as a promising class of therapeutics. Virotherapy consists of introduction of either wild-type or engineered viruses to the site of disease, where they exert anti-tumor effect. These viruses can either be non-lytic, in which case they are used to deliver gene therapy, or lytic, which induce tumor cell lysis and subsequent host immunologic response. Replication-competent viruses can then go on to further infect and lyse neighboring glioma cells. This treatment paradigm is being explored extensively in both preclinical and clinical studies for a variety of indications. Virus-based therapies are advantageous due to the natural susceptibility of glioma cells to viral infection, which improves therapeutic selectivity. Furthermore, lytic viruses expose glioma antigens to the host immune system and subsequently stimulate an immune response that specifically targets tumor cells. This review surveys the current landscape of oncolytic virotherapy clinical trials in high-grade glioma, summarizes preclinical experiences, identifies challenges associated with this modality across multiple trials, and highlights potential to integrate this therapeutic strategy into promising combinatory approaches.

In this paper, inspired by Jleli and Samet [journal of inequalities and applications 38 (2014) 2 1–8] we introduce two new classes of auxiliary functions and utilize the same to define (q, y)R-weak 3 contractions. Utilizing (q, y)R-weak contractions, we prove some fixed point theorems in the setting 4 of relational metric spaces. We employ some examples to substantiate the utility of our newly proved 5 results. Finally, we apply one of our newly proved results to ensure the existence and uniqueness of 6 solution of a Volterra-type integral equation.

The recent outbreak and spread of the COVID-19 virus infection across the world has seen a massive global system-wide shutdown of human social and economic activity. Both developed and developing nations have been forced to contain and isolate their citizens as much as possible. However, the continuous rising cases in both categories of nations, especially those with poor or nonexistent testing facilities and healthcare systems pose a hidden danger. The seemingly lack of and access to a truly global concerted research effort in both temporary but effective symptom mitigation may lead to more deaths in infected cases. We propose that a fusion of both technological and home-grown solutions can be utilized effectively to manage symptoms. This would add to the preventive methods of social distancing, isolation, quarantine and frequent handwashing to halt the impact of the disease. We also hope to spur further research in such drug/non-drug combination therapy-based methods with emphasis on effectiveness based on quality of nutrient sources.

The task of determining the distance from one object to another is one of the important tasks solved in robotics systems. Conventional algorithms rely on an iterative process of predicting distance estimates, which results in an increased computational burden. Algorithms used in robotic systems should require minimal time costs, as well as be resistant to the presence of noise. To solve these problems, the paper proposes an algorithm for Kalman combination filtering with a Goldschmidt divisor and a median filter. Software simulation showed an increase in the accuracy of predicting the estimate of the developed algorithm in comparison with the traditional filtering algorithm, as well as an increase in the speed of the algorithm. The results obtained can be effectively applied in various computer vision systems.

The oncologic disease is a big global health issue that causes thousands of deaths annually, and it has a significant impact in the life quality of patients. Prostate cancer (PCa) is the second most diagnosed cancer and the fourth leading cause of cancer-related death in men in the western world. Delineation of pathogenetic pathways and key driver molecular alterations involved in PCa development has provided a roadmap for the evaluation of biomarkers in predicting disease outcome and to identify potential therapeutic targets. Chemotherapeutic agents introduced from the 1990s include the taxanes (paclitaxel, docetaxel and cabazitaxel), which are the most anticancer drugs used for PCa treatment. This review presents the current knowledge about the onset and development of PCa, state-of-art on the use of taxane-based therapy, and their combination with targeting different transmembrane oncoproteins in PCa. The silencing of some transmembrane proteins can improve taxane sensitivity, and therefore, may be a mechanism to improve the ef-fectiveness of these drugs in PCa treatment. This combined therapy needs to be explored as po-tential therapeutic agent for reducing cell proliferation, migration, and invasiveness in PCa.

Immune checkpoint inhibitors (ICI) are a promising form of immunotherapy that has significantly changed the therapeutic landscape for many advanced cancers. They have shown unique clinical benefit against a broad range of tumour types and a strong overall impact on survival in studied patient populations. However, there are still many limitations holding back this immunotherapy from reaching its full potential as a possible curative option for advanced cancer patients. A great deal of research is being undertaken in the hope of driving advancements in this area, building a better understanding of the mechanisms behind immune checkpoint inhibition and ultimately developing more effective, safer, and wider-reaching agents. Taking into account the current literature on this topic, this review aims to explore in depth the basis of the use of ICIs in the treatment of advanced cancers, evaluate its efficacy and safety, consider its current limitations, and finally reflect on what the future holds for this very promising form of cancer immunotherapy.

Long COVID is the collective term used to describe the persistence of symptoms in individuals who have recovered from SARS-CoV-2 infection. Some people who have healed from COVID-19 continue to experience new or persistent symptoms that last for weeks or months. While Long COVID is becoming more widely recognized, its fundamental causes and effective therapies remain largely unclear. This study aims to explore the potential of phytochemical medications as a cutting-edge therapeutic strategy for treating Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC).G protein-coupled receptors (GPCRs), which play a critical role in cell signaling, were the focus of this study. GPCRs are known to be involved in immunological and inflammatory responses and are considered potential targets for Long COVID therapy. The GPCRs examined included chemokine receptors, serotonin receptors, adrenergic receptors, and histamine receptors. The docking results demonstrated high binding affinity between phytochemical drug structures and these receptors for most drug-receptor combinations.The study consists of three main parts. First, data on receptors and drugs were retrieved from the Protein Data Bank (PDB) and PubChem, respectively. The receptors selected are those predicted to be linked to Long COVID. The structure of the drugs was converted from SDF to PDB format using OpenBabel from ChemInfo. Docking studies were performed to assess the binding affinity between the drugs (ligands) and their respective receptors (binding sites) using iGemDock v2.1.In conclusion, the findings of this study could have significant implications for the development of alternative therapies for Long COVID.

Background: Bladder cancer (BC) development is highly related to immune cell infiltration and inflammation. This study aimed to construct a new classification of bladder cancer (BC) molecular subtypes based on immune cells-associated CpG sites. Methods: The genes of 28 types of immune cells were obtained from previous studies. Then methylation sites corresponding to immune cells-associated genes were acquired. Differentially methylation sites (DMSs) were identified between normal samples and bladder cancer samples. Unsupervised clustering analysis of differentially methylation sites was performed to divide into several subtypes. Then the potential mechanism of different subtypes was exploded. Result: Bladder cancer patients were divided into three groups. Cluster 3 (methylation-L) subtype had the best prognosis. Cluster 1 (methylation-M) had the worst prognosis. The distribution of immune cells, level expression of checkpoints, stromal score, immune score, ESTIMATEScore, tumor purity, APC_co_inhibition, APC_co_stimulation, HLA, MHC_class_I, Type_I_IFN_Reponse, and Type_II_IFN_Reponse were significant difference among three subgroups. The distribution of genomic alterations was different among them. Conclusion: The classification was accurate and stable. BC patients could be divided into three subtypes based on the immune cells-associated CpG sites. Specific biological signaling pathways, immune mechanisms, and genomic alterations were various among three subgroups. High level immune infiltration was a correlation with high level methylation. The lower RNAss score was associated with higher immune infiltration and higher level expression of CD274.

Background: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder with a rapidly increasing prevalence. Current therapeutic options primarily manage symptoms, not modifying the disease. Secretome-based therapies have emerged as a promising avenue for AD treatment in targeting multiple pathways and promoting neuroprotection and regeneration. This systematic review evaluated the preclinical and clinical evidences for secretome-based therapies in AD.Methods: A systematic search was conducted across Scopus, PubMed, ScienceDirect, and Cochrane Library. The SYRCLE risk of bias (RoB) tool was used for preclinical studies and Cochrane RoB 2.0 for clinical studies. We performed qualitative analysis of study results.Results: Included 21 in vivo studies and 2 clinical trials revealed promising outcomes of treatments involving secretomes, exosomes, and extracellular vesicles from different cell sources. The therapies could reduce amyloid plaque load, reactive gliosis, and enhance neuronal density. These findings suggested the treatments reveal mechanism of action in neuroprotection, neuroregeneration, and inflammation modulation, which are critical in AD pathology. Ongoing trials also supported the safety and efficacy of the treatment strategies. However, translational medical study faces several challenges regarding large-scale production, optimization of protocols, and understanding biomarkers. The heterogeneity in secretome-based therapies administration have complicated the comparison of study outcomes and the translation of preclinical findings into clinical settings. Deeper understanding of the secretome's mechanisms of action, optimal dosing, and delivery methods are needed to maximize therapeutic outcomes.Conclusion: Despite secretome-based therapies hold significant promise for AD treatment, addressing the identified gaps and limitations is crucial for advancing these therapies from preclinical research to clinical practice.

Cancer remains one of the main causes of death in the world due to its increasing incidence and treatment difficulties. Although several progresses have been done in this field, innovative approaches are needed to reduce tumor incidence, progression and spreading. In particular, the development of cancer vaccines is currently ongoing like both preventive and therapeutic strategy. This concept is not new, but few vaccines have been approved in oncology. Antigen-based vaccination emerges as a promising strategy, leveraging specific tumor antigens to activate the immune system response. However, challenges persist in finding suitable delivery systems and antigen preparation methods. Exosomes (EXs) are highly heterogeneous bilayered vesicles which carry several molecule types in the extracellular space. The peculiarity is that they may be released from different cells and may be able to induce a direct or indirect stimulation of immune system. In particular, EX-based vaccines may cause anti-tumor immune attack or produce memory cells recognizing cancer antigens and inhibit disease appearance. This review delves into EXs composition, biogenesis, and immune-modulating properties exploring their role as tool for prevention and therapy in solid tumors. Finally, here we describe future research directions to optimize vaccine efficacy and realize the full potential of EX-based cancer immunotherapy.

Hydrogen is the lightest atom and composes roughly half of the atomic content in macromolecules, yet their location can only be inferred or predicted in most macromolecular structures. This is because hydrogen can rarely be directly observed by the most common structure determination techniques (such as X-ray crystallography and electron cryo-microscopy). However, knowledge of hydrogen atom positions, especially for enzymes, can reveal protonation states of titratable active site residues, hydrogen bonding patterns, and the orientation of water molecules. Though we know they are present, this vital layer of information, which can inform a myriad of biological processes, is frustratingly invisible to us. The good news is that, even at modest resolution, neutron crystallography (NC) can reveal this layer and has emerged this century as a powerful tool for elucidating enzyme catalytic mechanisms. Due to its strong and coherent scattering of neutrons, incorporation of deuterium into the protein crystal amplifies the power of NC. This is especially true when solvation and the specific participation of key water molecules are crucial for catalysis. Neutron data allow the modeling of all three atoms in water molecules and have even revealed previously unobserved and unique species such as hydronium (D3O+) and deuteroxide (OD-) ions as well as lone deuterons (D+). Herein, we briefly review why neutrons are ideal probes for identifying catalytically important water molecules and these unique water-like species, limitations in interpretation, and four vignettes of enzyme success stories from disparate research groups. One of these groups was that of Dr. Chris G. Dealwis, who died unexpectedly in 2022. As a memorial appreciation of his scientific career, we will also highlight his interest and contributions to the neutron crystallography field. As both the authors were mentored by Chris, we feel we have a unique perspective on his love of molecular structure and admiration for neutrons as a tool to query those structures.

Background: Liver failure profoundly affects the immune system, leading to dysregulation of innate and adaptive immune responses. Body: This review explores the intricate relationship between liver function and immune homeostasis. The role of the liver as a central hub in immune response initiation is elucidated, emphasizing its involvement in hepatic inflammation induction and subsequent systemic inflammation. Cytokines, chemokines, growth factors, and lipid mediators orchestrate these immune processes, serving as both prognostic biomarkers and potential therapeutic targets in liver failure-associated immune dysregulation. Furthermore, the review delves into the mechanisms underlying immunosuppression in liver failure, encompassing alterations in innate immune cell functions such as neutrophils, macrophages, and natural killer cells (NK cells), as well as perturbations in adaptive immune responses mediated by B and T cells. Conclusion: Understanding the immunological consequences of liver failure is crucial for developing targeted therapeutic interventions and improving patient outcomes in liver disease management.

The antimicrobial resistance to clinically approved antibiotics is rapidly increasing worldwide. Staphylococcus aureus is a critical contributor to deaths associated with antibiotic resistance. In this regard, the search for natural compounds is quite active, that alone or in combination with other agents can be effective as new antibacterial agents. The antibacterial activity of essential oils has presented an increasing interest during the last years and was effective even on multidrug-resistant strains. The present study aims to investigate the interaction effects of oregano essential oil (OEO) with some conventional antibiotics against Staphylococcus aureus tested by agar methods. For this purpose, we selected S. aureus ATCC 29213 and five clinical isolates representative of the species. The essential oil was analyzed using gas chromatography coupled with mass spectrometry (GC-MS). The analysis of the Oregano essential oil revealed the main component to be carvacrol (81,20%). Concentration 2.5% (v/v) OEO was combined with drugs proposed by EUCAST, 2024, specifically penicillin, cefoxitin, erythromycin, gentamycin and tetracycline. The research results showed that the combination of OEO with penicillin, cefoxitin, erythromycin, and tetracycline enhanced the antimicrobial activity of the antibiotics against S. aureus in almost all cases. The area of suppression remained identical (but not smaller) in the unaffected cases. When comparing the effects of the GEN-OEO combination and GEN against most S. aureus strains, a decrease in antimicrobial activity was reported by the diffusion agar method.

Molten salt electrolysis stands as an indispensable technique for the production of rare earth metals, where the judicious distribution of the electric field within the electrolytic cell is paramount for ensuring the seamless operation of the electrolysis process. This study introduces a pioneering approach by integrating the Nernst-Planck equation with the Butler-Volmer equation, thereby devising a holographic electric field model tailored for the electrolysis of the NdF3-LiF molten salt system. The paper presents pioneering experimental measurements concerning the potential distribution and voltage drop characteristics within a 6kA rare earth electrolytic cell, elucidating the interplay between decomposition voltage and current density, which substantiates the model's precision. Our findings unveil that, under operational conditions of 4010 amperes, the 6kA electrolytic cell incurs a total voltage drop of 6.3 volts, delineating a melt voltage drop of 4.43 volts, an ohmic voltage drop of 0.248 volts, and an interfacial voltage drop of 1.622 volts at the electrode-electrolyte junction. The discrepancy in error is confined to within 0.3% of the actual measured voltage of 6.28 volts.The simulation outcomes from the holographic electric field model have been confirmed to precisely and comprehensively reflect the characteristics of the electric field distribution during the rare earth molten salt electrolysis process, offering valuable theoretical insights for practical manufacturing applications.

Primary biliary cholangitis (PBC) is a cholestatic liver disease characterized by immune-mediated injury to small bile ducts. Although PBC is an autoimmune disease, the results of traditional immunosuppressive therapy are disappointing. Nearly 40% of PBC patients do not respond to the first-line drug UDCA. Without appropriate intervention, PBC patients would eventually progress to liver cirrhosis and even death. There is an urgent need to develop new therapies. The gut-liver axis emphasizes the interconnection between the gut and the liver, and there is increasing evidence that gut microbiota and bile acids play an important role in cholestatic diseases. Dysbiosis of gut microbiota, imbalance of bile acids, and immune-mediated bile duct injury constitute the triad of pathophysiology in PBC. Understanding the gut microbiota-bile acid network and corresponding immune functions in PBC provides a new perspective for its treatment strategies. Therefore, we summarize the latest advancements in research of gut microbiota and bile acids in PBC and, for the first time, explore the potential of immune factors related to them as novel immunotherapy targets. This article discusses potential therapeutic approaches focusing on regulating gut microbiota, maintaining bile acid homeostasis, their interactions, and related immune factors.

Retweet prediction is an important task related to different problems such as information spreading analysis, the automatic detection of fake news, social media monitoring, etc. In this study we explore the possibilities of retweet prediction based on heterogeneous data sources. In order to classify the tweet according to the amount of retweets, we combine features extracted from the multilayer network and the text. More specifically, we introduce a multilayer framework that proposes the multilayer network representation of Twitter. This formalism captures different users' actions and complex relationships as well as other key properties of communication on Twitter. We select a set of local network measures from each layer and construct a set of multilayer network features. In addition, we adopt a BERT-based language model, namely Cro-CoV-cseBERT to capture high-level semantics and structure of tweets as a set of text features. Then, we train six machine learning (ML) algorithms: random forest, multilayer perceptron, light gradient boosting machine, category embedding model, neural oblivious decision ensembles and attentive interpretable tabular learning model in the task of retweet prediction. We compare the performance of all six algorithms in three different setups (i) using only text features, (ii) using only multilayer network features and (iii) using both sets of features. We evaluate all setups in terms of standard evaluation measures i.e. precision, recall, F1-score and accuracy. For this task, we first prepare and use an empirical dataset of 199,431 tweets in the Croatian language posted during the period between January 1, 2020 and May 31, 2021. Our results indicate that by integrating multilayer network features with text features the prediction model would perform better than using just one set of features.

Present study on land use land cover analysis and taluka wise combination of cropped area, carried out in Beed district of Maharashtra state in India and studied 11 talukas of the district. Secondary data on land use land cover and area in various crops has been collected, compiled and analyzed from various secondary sources. Simple descriptive statistics used to examine the agricultural land use land cover and J.C. Weaver’s crop combination technique was used for taluka wise analysis of crop combinations and on the basis of highest to smallest area engaged in particular crop, crops have been ranked. The study showed that, in the district as a whole, percentage of uncultivated land other than fallow was about 46 percent as compare to net sown area is only 35 percent in total geographical area (1063855ha) of Beed district. The study further revealed that about 42 percent area engaged in food crops and about 58 percent area occupied by nonfood crops, which includes cereals (25%), cotton (19%), pulses (13%), oilseed (12%), sugarcane (5%) and fruits and vegetables (3%). Results of Weaver’s crop combination technique showed that the Wadwani taluka demarcated as most diversified taluka by means of maximum number (sixteen) of crops combinations with the lowest variance value (14) found in the present investigation. Further, the study revealed that the high crop diversity found in Dharur taluka with eighteen crop combinations and the taluka has given first rank amongst others. To derive the crop diversity ranking, taluka wise maximum to minimum number of crop combinations derived in different talukas and given ranks accordingly. The study concluded that, agricultural land use analysis is essential for solving and optimizing the land use problem, maintaining socio-ecological balance, best utilization of scarce resources. The authors enlightened that the rational use of agricultural land has important for food security and biodiversity which increase the productivity and profitability of the agriculture sector and it indicates the decision making ability of farmers in study area.

Exosomes have shown promising potential as a therapeutic approach for wound healing. Nevertheless, the translation from experimental studies to commercially available treatments is still lacking. To assess the current state of research in this field, a systematic review was performed to examine the methodological heterogeneity among studies conducted over the past five years. Additionally, the review analyzed the suitability of animal models used and their relevance to human medicine. A PubMed search was performed for english-language, full-text available papers published from 2018 to June 2023, focusing on exosomes derived from mammalian sources and their application in wound healing, particularly those involving in vivo assays. Out of 531 results, 148 papers were selected for analysis. The findings revealed significant variability in terms of cell sources and types, biomaterials, and administration routes under investigation, indicating the need for further research in this field. Additionally, a comparative examination encompassing diverse cellular origins, types, administration pathways, or biomaterials is imperative. Furthermore, the predominance of rodent-based animal models raises concerns, as there have been limited advancements towards more complex in vivo models and scale-up assays. These constraints underscore the substantial efforts that remain necessary before attaining commercially viable and extensively applicable therapeutic approaches using exosomes.

This manuscript explores significant advancements and emerging challenges in CAR T cell therapies, focusing on the production methodologies and regulatory complexities. The discussion highlights ongoing challenges like the lack of in vivo persistence, lengthy production times, and elevated costs associated with current CAR T cell therapies. It analyzes innovative solutions such as genetic engineering techniques aimed at enhancing cellular efficacy and endurance, alongside cutting-edge manufacturing processes, including closed systems and development of allogeneic products. These advancements hold promise for reducing costs and improving production efficiency, potentially increasing patient access to these transformative therapies globally. Furthermore, the manuscript underscores the necessity for expanding ongoing research and enhancing regulatory frameworks to fully realize and implement these innovations in CAR T cell manufacturing and bring these innovations to fruition.

Pulmonary hypertension (PH) is a severe and chronic disease characterized by increased pulmonary vascular resistance and remodeling often precipitating right-sided heart dysfunction and death. Although the condition is progressive and incurable, current therapies for the disease focus on multiple different drugs and general supportive therapies to manage symptoms and prolong survival, ranging from medications more specific to pulmonary arterial hypertension (PAH) to exercise training. Moreover, there are multiple studies exploring novel experimental drugs and therapies including unique neurostimulation, to help better manage the disease. Here we provide a narrative review focusing on current PH treatments that target multiple underlying biochemical mechanisms, including but not limited to imbalances in vasoconstrictor-vasodilator and autonomic nervous system function, inflammation, and bone morphogenic protein (BMP) signaling. We also focus on the potential of novel therapies for managing PH, focusing on multiple types of neu-rostimulation including acupuncture. Lastly, we also touch upon the disease’s different subgroups, clinical presentations and prognosis, diagnostics, demographics, and cost.

Cardiac amyloidosis is caused by amyloid fibrils that deposit in the myocardial interstitium, causing restrictive cardiomyopathy and eventually death. The electromechanical, inflammatory, and autonomic changes due to amyloid deposition result in arrhythmias. Atrial fibrillation is by far the most common arrhythmia. Rate control strategy is generally poorly tolerated due to restrictive filling physiology and heart rate dependance, favoring adoption of rhythm control strategy. Anticoagulation for stroke prophylaxis is warranted irrespective of CHA2DS2Vasc score in patients with favorable bleeding profile; data on left appendage closure devices is still insufficient. Ventricular arrhythmias are also not uncommon and the role of implantable cardioverter-defibrillator in cardiac amyloidosis is controversial. There is no evidence of improvement in outcomes when used for primary prevention in these patients. Bradyarrhythmia is most commonly associated with sudden cardiac death in cardiac amyloidosis. Pacemaker implantation can help provide symptomatic relief but does not confer mortality benefit.

New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with emergence of resistance resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies, that are clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers and phages. Clinical diagnostics optimizes the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious disease include detection, monitoring of response and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives into the use of alternate therapeutics with a particular focus on companion diagnostic applications in infectious diseases.

GM2 gangliosidoses are a group of pathologies characterized by GM2 ganglioside accumulation into the lysosome due to mutations on the genes encoding for the β-hexosaminidases subunits or the GM2 activator protein. Three GM2 gangliosidoses have been described: Tay-Sachs disease, Sandhoff disease, and the AB variant. Central nervous system dysfunction is the main characteristic of GM2 gangliosidoses patients that include neurodevelopment alterations, neuroinflammation, and neuronal apoptosis. Currently, there is not approved therapy for GM2 gangliosidoses, but different therapeutic strategies have been studied including hematopoietic stem cell transplantation, enzyme replacement therapy, substrate reduction therapy, pharmacological chaperones, and gene therapy. The blood-brain barrier represents a challenge for the development of therapeutic agents for these disorders. In this sense, alternative routes of administration (e.g. intrathecal or intracerebroventricular) have been evaluated, as well as the design of fusion peptides that allow the protein transport from the brain capillaries to the central nervous system. In this review, we outline the current knowledge about clinical and physiopathological findings of GM2 gangliosidoses, as well as the ongoing proposals to overcome some limitations of the traditional alternatives by using novel strategies such as molecular Trojan horses or advanced tools of genome editing.

Immunosuppressed individuals, such as people living with HIV (PLWH), remain vulnerable to severe COVID-19. We analyzed the persistence of specific SARS-CoV-2 humoral and cellular immune responses in a retrospective, cross-sectional study in PLWH on antiretroviral therapy. Among 104 participants, 70.2% had anti-S IgG antibodies and 55.8% had significant neutralizing activity against the Omicron variant in a surrogate virus neutralization test. Only 38.5% were vaccinated (8.76 ± 4.1 months prior), all displaying anti-S IgG, 75% with neutralizing antibodies and anti-S IgA. 29.8% had no SARS-CoV-2 serologic markers and displayed significantly lower CD4 counts and HIV viral load. Severe immunosuppression (present in 12.5% of participants) was linked to lower levels of detectable anti-S IgG (0.0003), anti-S IgA (p < 0.0001) and lack of neutralizing activity against Omicron variant (p < 0.0001). T-cell responses were present in 86.7% of tested participants, even in those lacking serological markers. In PLWH without severe immunosuppression, neutralizing antibodies and T-cell responses persisted for up to 9 months post-infection or vaccination. Advanced immunosuppression led to diminished humoral immunity, but retained cellular immune.

The rapid development of digital multimedia has resulted in a massive storm of large-scale data. The data compression method reduces data size and lowers transmission costs. As a result, data-hiding research in the compression domain poses significant challenges to researchers. This paper proposes a highly imperceptible data-hiding scheme for a compressed image of Absolute Moment Block Truncation Coding (AMBTC). The combination theory is implemented to ensure the high imperceptibility of the modified compressed images. By only modifying one pixel in a block to embed secret bits, the experimental results show that the proposed method achieved high imperceptibility and high hiding capacity.

Hypoxia is a hallmark of solid tumors, including hepatocellular carcinoma (HCC). Hypoxia has proved to be involved in multiple tumor biological processes and associated with malignant progression and resistance to therapy. Transarterial chemoembolization (TACE) is a well-established locoregional therapy for patients with unresectable HCC. However, TACE-induced hypoxia regulates tumor angiogenesis, energy metabolism, epithelial-mesenchymal transition (EMT), and immune processes through hypoxia-inducible factor 1 (HIF-1), which may have adverse effects on the therapeutic efficacy of TACE. Hypoxia has emerged as a promising target for combination with TACE in treatment of HCC. This review summarizes impact of hypoxia on HCC tumor biology, adverse effects of TACE-induced hypoxia on its therapeutic efficacy, highlighting the therapeutic potential of hypoxia-targeted therapy in combination with TACE for HCC.

The emergence of drug-resistant mycobacteria has rendered many clinical drugs and regimens ineffective, imposing significant economic and healthcare burden on individuals and society. Repurposing drugs intended for treating other diseases is a time-saving, cost-effective, and efficient approach for identifying excellent anti-mycobacterial candidates or lead compounds. This study is the first to demonstrate that rupatadine (RTD), a drug used to treat allergic rhinitis, possesses excellent activity against mycobacteria without detectable resistance, particularly Mycobacterium tuberculosis and Mycobacterium marinum, with a minimal inhibitory concentration as low as 3.13 µg/mL. Furthermore, RTD exhibited moderate activity against nonreplicating M. tuberculosis with the minimal inhibitory concentrations lower than drugs targeting the cell wall, suggesting that RTD has the great potential to be modified and used for the treatment of nonreplicating M. tuberculosis. Additionally, RTD exhibits partial synergistic effects when combined with clofazimine, pretomanid, and TB47 against M. tuberculosis, providing the theoretical foundation for the development of treatment regimens. Transcriptomic profiling leads us to speculate that eight essential genes may be the targets of RTD or may be closely associated with the mycobacterial resistance to RTD. In summary, RTD may be a promising hit for further anti-mycobacterial drug or regimen optimization, especially in case of nonreplicating mycobacteria.

Lumpy skin disease (LSD), caused by a virus within the Poxviridae family and Capripoxvirus genus, induces nodular skin lesions in cattle, spreading through direct contact and insect vectors, significantly affecting global cattle farming. Despite available vaccines, their effectiveness is limited by poor bioavailability and adverse effects. Our study aimed to identify potential inhibitors targeting LSD-associated DNA polymerase protein, selecting LSDV039 for further investigation through comprehensive analysis and computational methods. Virtual screening revealed rhein and taxifolin as potent binders among 380 phytocompounds, with respective affinities of -8.965 and -7.195 kcal/mol. Canagliflozin and tepotinib exhibited strong affinities (-9.858 and -8.856 kcal/mol) among 718 FDA-approved antiviral drugs. Molecular dynamics simulations of canagliflozin, tepotinib, rhein, and taxifolin highlighted taxifolin's superior stability and binding energy. Rhein displayed compactness in RMSD and RMSF but fluctuations in Rg and SASA, while canagliflozin demonstrated stability compared to tepotinib. The study highlights the promising potential of repurposed drugs and phytocompounds as LSD therapeutics. However, extensive validation through in-vitro, in-vivo, and clinical trials is crucial for their practical application.

Chronic obstructive pulmonary disease (COPD) is a condition that significantly impacts both patients and healthcare systems. The management of COPD involves various pharmacological intervention strategies, and addressing the issue of low adherence to these strategies has become a subject of significant interest. In response to this concern, there has been a shift towards utilizing telemedicine and mobile applications. The primary objective of this scoping review is to delineate the usage of mobile applications to enhance pharmacological therapeutic adherence in adult patients with COPD. The study involved a search of databases such as Medline, Google Scholar, Cochrane, and ClinicalTrial.gov, focusing on literature published in English and Spanish over the last decade. The selected studies assessed interventions involving mobile applications (mobile apps) designed to improve pharmacological adherence. Four digital aids were identified, available on online platforms, mobile apps, or both: m-PAC, myCOPD, Wellinks mHealth, and Propeller Health. Pro-peller Health, in particular, is an app that directly measures pharmacological adherence through electronic medication monitors attached to participants' inhalers. Opening the app was associated with higher odds of using control medications compared to participants who did not open the app. The findings suggest that these digital interventions serve as valuable tools to enhance patient adherence to treatment. Future research should focus on evaluating the effectiveness of different digital devices, such as digital inhalers and mobile applications, that directly measure pharmacological adherence.

It is estimated that pancreatic cancer will be the 2^nd leading cause of cancer-related deaths globally by 2030, highlighting the ongoing lack of effective treatment options in this devastating condition. There is a lack of reliable prognostic or predictive markers in pancreatic cancer to guide management decisions, whether for systemic chemotherapy, molecularly targeted therapies, or immunotherapies. To date, the results for targeted agents and immunotherapies in unselected populations of chemo-refractory pancreatic cancer have not met expectations. The reasons for this lack of efficacy of immunotherapy in pancreatic cancer are incompletely understood. The challenges in pancreatic cancer include the physical barrier created by the dense desmoplastic stroma surrounding the tumor, chemokine-mediated exclusion of T cells, poor antigenicity, paucity of infiltrating T cells within the tumor, ultimately leading to an immunosuppressive microenvironment. A better understanding of the role of inflammation in pancreatic cancer, its tumor microenvironment and individualized patient-related features, be they molecular, clinical or histopathological would enable a more effective tailored approach to the management of pancreatic cancer. In this review, the role of inflammation, the immune tumor microenvironment and potential immune biomarkers in pancreatic cancer are explored.

Mining activities could produce a large volume of spoils, waste rocks, and tailings, which are usually deposited at the surface and become sources of metal pollution. Phytostabilization of the mine spoils could limit the spread of these heavy metals. Phytostabilization can be enhanced by using soil amendments like manure-based biochar capable of immobilizing metal(loid)s when combined with plant species that are tolerant of high levels of contaminants while simultaneously improving properties of mine soils. However, the use of manure-based biochar and other organic amendments for mine spoil remediation are still unclear. In this greenhouse study, we evaluated the interactive effect of biochar application and compost on shoots biomass yield (SBY), roots biomass yield (RBY), uptake, and bioconcentration factor (BCF) of Zn and Cd in corn (Zea mays L.) grown in mine soil. Biochar sources (BS) consisted of beef cattle manure (BCM); poultry litter (PL); and lodge pole pine (LPP) were applied at 0, 2.5, and 5.0% (w/w) in combination with different rates (0, 2.5, and 5.0%, w/w) of cattle manure compost (CMC), respectively. Shoots and roots uptake of Cd and Zn were significantly affected by BS, CMC, and the interaction of BS and CMC. Corn plants that received 2.5% PL and 2.5% BCM had the greatest Cd and Zn shoot uptake, respectively. Corn plants with 5% BCM had the greatest Cd and Zn root uptake. When averaged across BS, the greatest BCF for Cd in the shoot of 92.3 was from the application BCM and the least BCF was from the application of PL (72.8). Our results suggest that incorporation of biochar enhanced phytostabilization of Cd and Zn with concentrations of water-soluble Cd and Zn lowest in soils amended with both manure-based biochars while improving biomass productivity of corn. Overall, phytostabilization technique and biochar application have the potential to be combined in the remediation of heavy metals polluted soils.

Cholestasis is a condition defined as an abnormal decrease of bile flow due to progressive pathological states or cholestatic liver diseases that affect the biliary tree at intrahepatic and extrahepatic level. It induces complications such as cirrhosis, liver failure, malignancies, pruritus, fatigue, bone disease and nutritional deficiencies that merit close follow-up and specific interventions to improve quality of life. Furthermore, cholestasis can progress to end-stage liver disease and represents an entity with high morbidity and mortality; and economic burden, Therefore, it is important that clinicians understand the treatment options for cholestatic liver diseases. This review addresses the pathophysiology of cholangiopathies, a general view of current treatments and their molecular targets, and a specific review of those groups of drugs. The objective is to provide clinicians with an overview of the current treatment of cholangiopathies based on evidence on its efficacy and safety.

Arterial wall remodeling underlies increased pulmonary vascular resistance and right heart failure in pulmonary arterial hypertension (PAH). None of the established vasodilator drug therapies for PAH prevents or reverses established arterial wall thickening, stiffening and hypercontractility. Therefore, new approaches are needed to achieve long-acting prevention and reversal of occlusive pulmonary vascular remodeling. Several promising new drug classes are emerging from better understanding of pulmonary vascular gene expression programs. In this review potential epigenetic targets for small molecules and oligonucleotides will be described. Most are in preclinical studies aimed at modifying growth of vascular wall cells in vitro or normalizing vascular remodeling in PAH animal models. Initial success with lung-directed delivery of oligonucleotides targeting microRNAs suggests other epigenetic mechanisms might also be suitable drug targets. Those targets include DNA methylation, proteins of the chromatin remodeling machinery and long noncoding RNAs, all of which act as epigenetic regulators of vascular wall structure and function. Progress in testing small molecules and oligonucleotide-based drugs in PAH models is summarized.

This review explores the transformative role of induced pluripotent stem cells (iPSCs) and organoids in advancing neuropathology research. Focused on Alzheimer's disease, epilepsy, Parkinson's disease, and spinal cord injury, iPSCs offer patient-specific disease modeling with regenerative therapy potential. The versatility of iPSCs, their ability to differentiate into the main neuronal cell types, and their integration into three-dimensional organoid models enable the recreation of complex tissues in vitro. Improvement of organoid and iPSCs generation protocols and the selection of appropriate donor cell types are highlighted as crucial steps toward the application of these new technologies to overcome tumorigenic potential and other challenges. iPSCs demonstrate promise in regenerative therapies, as evidenced by successful applications in animal models.

High-precision dynamic positioning of highway vehicles is the foundation and prerequisite for achieving intelligent connected transportation. For the shortcomings of GNSS/INS combination and GNSS/INS/OD combination in tunnel vehicle positioning, this paper proposes a tunnel vehi-cle positioning method of GNSS/INS/OD combination based on lateral distance measurement and lane constraint. Firstly, lateral distance measurement of vehicles inside the tunnel is conducted based on laser radar point cloud data. Secondly, map matching positioning is performed based on lateral distance measurement, odometer, and lane markings. Experimental results demonstrate that for a 4.6 km tunnel, the average absolute error of lateral positioning is 0.294 meters, and the longitudinal positioning error is no more than 0.6 meters, which can effectively meet practical operational requirements.

In the age of social media, images come from unreliable sources that may change their content to fit a narrative. Automated detection of forged images is a complex task, especially considering recent technological advances in image manipulation software. However, in the existing literature, it is possible to identify two general approaches adopted by detection methods, active and passive. Active techniques preemptively act on an image by inserting structures before any manipulation is made that can verify its authenticity. In contrast, passive methods analyze the content of an image in search of traces of manipulation. In this way, this research proposes a novel approach to image manipulation detection, combining two passive methods through neural networks, creating a generalist approach capable of detecting with greater accuracy than the methods that compose it. Furthermore, this work used a combination of four datasets available in the literature for training and evaluation. After training, the merged approach obtained an accuracy of 89.59% in the set of validation images, significantly higher than the model trained with only unaltered images, which obtained 78.64%, and the two other models trained using images with a feature selection method applied to enhance inconsistencies that obtained 68.02% for Error-Level Analysis images and 50.70% for the method using Discrete Wavelet Transform. In addition to the performance improvement, the proposed approach’s accuracy variation was lower than the other models.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

The study of the area model of Pinus tabulaeformis forest provides an important reference for improving the management of Pinus tabulaeformis and revealing the growth law of Pinus tabulaeformis. According to the classification method proposed by Munro, stand growth and harvest prediction models are divided into three categories: full stand model, single wood model and diameter distribution model. Based on the fixed sample data of Shangluo Pinus tabulaeformis, the spatial instead of time method is used to process the data, and the weight coefficient of each model in the combined prediction model is calculated by using the optimal weighting method. The single wood model, the whole forest model and the diameter distribution model are combined by the combined prediction method to integrate the fault area prediction of Pinus tabulaeformis forest. The results show that the combined prediction method is more accurate than the single model (single wood model, whole forest model and diameter distribution model). At the same time, the method can improve the compatibility of the forest break area prediction model, ensure the consistency of the forest break area prediction, and provide a new direction for the research of forest resource monitoring and investigation.

Infections caused by KPC-producing K. pneumoniae continue to pose a significant clinical challenge due to emerging resistance to new antimicrobials. We investigated the association between two drugs whose roles have been repurposed against multidrug-resistant bacteria: fosfomycin and temocillin. Temocillin exhibits unusual stability against KPC enzymes, while fosfomycin acts as a potent “synergizer”. We conducted in vitro antimicrobial activity studies on 100 clinical isolates of KPC-producing K. pneumoniae using a combination of fosfomycin and temocillin. The results demonstrated synergistic activity in 91% of the isolates. Subsequently, we assessed the effect on Galleria mellonella larvae using 5 different KPC-Kp isolates. The addition of fosfomycin to temocillin increased larvae survival from 73 to 97% (+Δ 32%; isolate 1), from 93 to 100% (+Δ 7%; isolate 2), from 63 to 86% (+Δ 36%; isolate 3), from 63 to 90% (+Δ 42%; isolate 4), and from 93 to 97% (+Δ 4%; isolate 10), respectively. Among the temocillin-resistant KPC-producing K. pneumoniae isolates (24 isolates), the addition of fosfomycin reduced temocillin MIC values below the resistance breakpoint in all isolated except one. Temocillin combined with fosfomycin emerges as a promising combination against KPC-producing K. pneumoniae, warranting further clinical evaluation.

Hypertension is a frequent risk factor for cardiovascular diseases and the prevalence rate is continuously rising. Multiple pathophysiological mechanisms are responsible for hypertension, necessitating a combination of drugs from different classes for best management. Combination therapy is five times more effective in decreasing blood pressure compared to escalating the dose of a single agent. As per the ACCOMPLISH trial analysis, coupling a renin-angiotensin system inhibitor with a calcium channel blocker is more effective than the combination of a renin-angiotensin system inhibitor with diuretics in reducing major cardiovascular events, cardiovascular-related mortality, and the progression of chronic kidney disease. The renin-angiotensin system can be suppressed by inhibiting the angiotensin-converting enzyme or angiotensin type 1 receptor (AT1R), resulting, in decreased vascular smooth muscle contraction, heart performance, and reduced aldosterone synthesis. Calcium channel blockers work by inhibiting L-type calcium channels, reducing heart performance via negative inotropic, chronotropic, and bathmotropic effects, along with reducing vascular smooth muscle contraction. Diuretics exert their antihypertensive impact by changing body fluid volume and electrolytes. Initially, hypertension treatment commences with a single medication but often, different classes of two or more antihypertensive medications are necessary for achieving the target blood pressure goal. Sometimes, for Resistant hypertension four different classes of antihypertensive medications are necessary to reach the target blood pressure goal.

LCK, a member of the Scr kinase family, is a non-receptor tyrosine kinase involved in immune cell activation, antigen recognition, tumor growth, and cytotoxic response. The enzyme has usually been linked to T lymphocyte activation upon antigen recognition. Lck activation is central to CD4, CD8, and NK activation. However, recently, it has become clearer that activating the enzyme in CD8 cells can be independent of antigen presentation and enhance cytotoxic response. The role of Lck in NK cytotoxic function has been controversial in a similar fashion as the role of the enzyme in CAR T cells. Inhibition of Lck has been mainly to treat hematologic malignancies with a high rate of success. They may be useful in treating other tumor types, and they may be useful to prevent cell exhaustion. New, more selective inhibitors have been documented, and they have shown inter-esting activities not only in tumor growth but in the treatment of autoimmune diseases, asthma, and graft vs host disease. Drug repurposing and bioinformatics can aid in solving several unsolved is-sues on the role of Lck in cancer. In summary, the role of Lck in immune response and tumor growth is not a simple event and requires more research.

Background In this study we investigated in detail the role of cannabidiol (CBD), Beta-caryophyllene (BC), or their combinations in diabetic peripheral neuropathy (DN). The key factors that contribute to DN include mitochondrial dysfunction, inflammation, and oxidative stress. Methods Briefly, Streptozotocin (STZ) (55 mg/kg) was injected intraperitoneally to induce DN in Sprague Dawley rats and performed procedures including Randall Sellito Calipers, Von Frey Aesthesiometer, hot plate, and cold plate methods to determine mechanical and thermal hyperalgesia in vivo. The blood flow to the nerves was assessed by using the Laser Doppler device. Schwann cells were exposed to high glucose (HG) at a dose of 30 mM to induce hyperglycemia and DCFDA, JC1 & Mitosox staining were done to determine mitochondrial membrane potential, reactive oxygen species and mitochondrial superoxides in-vitro. The rats were administered i.p with BC (30mg/kg), CBD (15mg/kg), or combination while Schwann cells were treated with 3.65 µM CBD, 75 µM BC, or combination to assess their role in DN amelioration. Results Our results revealed that exposure to BC and CBD diminished HG-induced hyperglycemia in Schwann cells, in part, through reducing mitochondrial membrane potential, reactive oxygen species and mitochondrial superoxides. Further, BC and CBD combination treatment in-vivo could prevent the deterioration of mitochondrial quality control system by promoting autophagy and mitochondrial biogenesis while improving blood flow. CBD and BC treatments also reduced pain hypersensitivity to hyperalgesia and allodynia with increased antioxidant and anti-inflammatory action in diabetic rats. These in vivo effects were attributed to significant upregulation of AMPK, SIRT3, Nrf2, PINK1, PARKIN, LC3B, Beclin1 and TFAM functions while downregulation of NLRP3 inflammasome, NFκB, COX2 and p62 activity was noted as determined by western blotting. Conclusion the present studies demonstrated that STZ & HG induced oxidative and nitrosative stress play a crucial role in the pathogenesis of diabetic neuropathy. We find, for the first time, that CBD and BC combination ameliorate DN via modulating the mitochondrial quality control system.

Lung cancer is the most common cause of cancer deaths worldwide, and lung adenocarcinoma (LUAD) is the most common histological subtype. However, the prognostic and predictive outcomes differ because of the heterogeneity of programmed cell death. The purpose of this work is to investigate and develop a cuproptosis-associated lncRNA-based LUAD prediction marker. We firstly performed bioinformatic analysis of the Cuprotosis database and The Cancer Genome Atlas (TCGA) database to obtain 19 cuprotosis-related gene datasets and transcriptional data for LUAD. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were utilized to construct cuproptosis-associated lncRNA modes. LUAD patients were thus classified into high-risk and low-risk categories based on prognostic risk values, with a median of It acted as a boundary. Risk models were evaluated and validated using Kaplan-Meier analysis, principal component analysis (PCA), gene set enrichment analysis (GSEA) and nomograms. Utilizing the TCGA-LUAD dataset, we identified seven predicted cuproptosis-associated lncRNAs in tumor microenvironment to create the risk model. 95.54% (214/224) of high-risk category tumor samples included cuproptosis-associated gene alterations, compared to 85.65% (203/237) of low-risk category tumor samples, with TP53 accounting for the bulk of occurrences. According to these findings, risk value was superior to other clinical variables and tumor mutation burden as a predictor of 1-, 3-, and 5-year overall survival (OS). The predictive validity of the cuproptosis-associated lncRNA-based risk model for LUAD is high, and this may have implications for how lung cancer patients are treated individually.

Gestational Diabetes Mellitus (GDM) is related with adverse outcomes for both the mother and the offspring. Immune and senescence play a crucial role in GDM progression. This study aims to explore the diagnostic significance of immune-related senescence (IRS) genes in GDM. We used weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) to compute the immune score and aging score in control and GDM samples. Machine learning identified core IRS genes. Then we performed unsupervised cluster analysis in GDM patients to explore immune infiltration. Finally, we validated the core genes in clinical samples. We used the intersection of MEblack module from WGCNA and differentially expressed genes (DEGs) to obtain the potential genes. Next, a univariate logistic regression model including 23 potential genes were constructed, and these genes were filtered by least absolute shrinkage and selection operator (LASSO) algorithm. There were 5 potential genes (COX17, RRAS2, RRAGC, CECR1, and TACC2), which defined as biomarkers, remained eventually, and the efficacy of these biomarkers was evaluated by nomogram. Finally, the results from both qRT-PCR and western blot analyses demonstrated CECR1 was down-regulated, while TACC2 was up-regulated in GDM placental tissue. Our study identified CECR1 and TACC2 as diagnostic biomarkers for GDM associating with immune and senescence, providing a new perspective on GDM progression.

(1) Background: Globally, about 600 million people are afflicted with diabetes, and one of its most prevalent complications is neuropathy, a debilitating condition. At present, the exploration of novel therapies for alleviating diabetic neuropathy-associated pain is genuinely captivating, considering that current therapeutic options are characterized by poor efficacy and significant risk of side effects. In the current research, we evaluated the antihyperalgesic effect of sildenafil (phosphodiesterase-5 inhibitor) – metformin (antihyperglycemic agent) combination and its impact on biochemical markers in alloxan-induced diabetic neuropathy in rats; (2) Methods: The study comprised a cohort of 70 diabetic rats and 10 non-diabetic rats which were submitted to hot, cold, and tactile stimulus tests. Morover, we investigated the influence of this combination on TNF-α, IL-6 nitrites and thiols levels in brain and liver tissues; (3) Results: The results demonstrated that all sildenafil-metformin combinations decreased the pain sensitivity in von Frey test, Hot-plate test and Cold-plate test. Furthermore, alterations in nitrites and thiols concentrations and pro-inflammatory cytokines (specifically TNF-α and IL-6) were noted following a 15-day regimen of various sildenafil-metformin combinations. (4) Conclusions: The combination of sildenafil and metformin has a synergistic effect in alleviating pain in alloxan-induced diabetic neuropathy rats. Additionally, the combination effectively decreased inflammation, inhibited the rise in NOS activity, and provided protection against glutathione depletion.

Duchenne muscular dystrophy (DMD) is caused by genetic mutations in the cytoskeletal-sarcolemmal anchor protein dystrophin. Repeated cycles of sarcolemmal tearing and repair lead to a variety of secondary cellular and physiological stressors that are thought to contribute to weakness, atrophy, and fibrosis. Collectively, these stressors can contribute to a pro-inflammatory milieu in locomotor, cardiac, and respiratory muscles. Given the many unwanted side effects that accompany current anti-inflammatory steroid-based approaches for treating DMD (e.g., glucocorticoids), there is a need to develop new therapies that address inflammation and other cellular dysfunctions. Adiponectin receptor (AdipoR) agonists, which stimulate AdipoR1 and R2 isoforms on various cell types, have emerged as therapeutic candidates for DMD due to their anti-inflammatory, anti-fibrotic, and pro-myogenic properties in pre-clinical human and rodent DMD models. Although these molecules represent a new direction for therapeutic intervention, the mechanisms through which they elicit their beneficial effects are not yet fully understood, and DMD-specific data is limited. The overarching goal of this review is to investigate how adiponectin signaling may ameliorate pathology associated with dystrophin deficiency through inflammatory-dependent and -independent mechanisms, and to determine if current data supports their future progression to clinical trials.

Six bacterial strains with differing abilities to produce varying concentrations of Indole Acetic Acid were tested individually and in consortia for plant growth promoting and fitness related traits of Cicer arietinum. In all experiments the presence of the nitrogen fixer Mesorhizobium ciceri resulted in increased biomass production. In the absence of this strain, IAA Psedomonas putida and Bacillus megaterium hinder plant growth and fitness related traits. The application of mixes of the three strains always resulted in better plant performance when M. ciceri was present. Whereas P. putida has a noticeable plant growth-promoting effect B. megaterium resulted less effective. The low levels of IAA produced by the selected strains had a significantly greater positive effect on plant biomass accumulation, flower, pods and seed production as well as on total plant nitrogen and nitrogen concentration in seed than high IAA producer strains.

Bosentan, an endothelin-receptor antagonist (ERA), has potential anti-atherosclerotic properties. We investigated the complementary effects of bosentan and atorvastatin on the progression and composition of the atherosclerotic lesions in diabetic mice. Forty-eight male apoE-/- mice were fed high-fat diet (HFD) for 14 weeks. At week 8, diabetes was induced with streptozotocin and mice were randomized into 4 groups: 1) Control/COG: no intervention. 2) ΒΟG: bosentan 100 mg/kg/day per os. 3) ATG: atorvastatin 20mg/kg/day per os). 4) BO+ATG: Combined administration of bosentan and atorvastatin. The intra-plaque contents of collagen, elastin, monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-a (TNF-a), matrix-metalloproteinases (MMP-2,-3,-9), and TIMP-1 concentrations were determined. The percentage of lumen stenosis significantly decreased across all treated groups: BOG: 19.5±2.2%, ATG: 12.8±4.8%, BO+ATG: 9.1±2.7% compared to controls (24.6±4.8%, p<0.001). Both atorvastatin and bosentan significantly increased collagen content and fibrous cap thickness versus COG (p<0.01). All intervention groups reduced the relative intra-plaque concentrations of MCP-1, MMP-3,-9, and increased TIMP-1 compared to COG (p<0.001). Importantly, bosentan showed modest but additive to atorvastatin effects on the latter parameters compared COG (p<0.05). Bosentan treatment in diabetic, atherosclerotic apoE-/- mice delayed the atherosclerosis progression and enhanced plaques’ stability, showing modest but complementary effects with atorvastatin, which are promising in atherosclerotic cardiovascular diseases.

The proliferation of SARS-COV-2 through enhanced viral replication and its subsequent triggering of cytokine storm, are some of the hallmark phenotypes in severe COVID-19 patient cases. Cyclosporine, an immunosuppressant drug and Selinexor, an inhibitor of nuclear transporter protein, both have been successfully demonstrated to be effective against SARS-COV-2 infection by targeting those functions individually. However, the highly multifactorial pathology of SARS-COV-2 infection hinders any mono-therapeutic strategy to become an optimal option. In this study, we assess the potential efficacy of the Cyclosporine-Selinexor combination on an integrated interactome by adopting a network-medicine-based repositioning technique, where disease proximity, functional proximity and their topological separation are evaluated, followed by a robust statistical significance test. Results have shown that both drug target modules are highly proximal to the SARS-COV-2 disease modules in terms of network topology and functional associations, in a statistically significant manner, individually. Functional enrichment of both drug modules and SARS-COV-2 infected modules has shown that two drugs target the functions related to viral replication and cytokine storm during infection. Moreover, a high degree of network separation been those two drug target modules has been observed, revealing ``complementary exposure`` patterns, rendering this drug combination as an effective one against SARS-COV-2 infection. We hope that our results will encourage researchers to further investigate the potency of Cyclosporine and Selinexor combination in vivo or in vitro, and ultimately lead that up to clinical trials to treat SARS-COV-2 patients.

Background: At present, the treatments for patients with advanced lung cancer focus on chemotherapy, targeted therapy, immunotherapy, or a combination of multiple treatments. Purpose: The main purpose of this study is to compare the various chemotherapy-based combination therapies and find the best one for patients with advanced lung cancer. Methods: Based on database (PubMed, EMBASE and Medline) for randomized controlled trials of advanced lung cancer with combination therapy from 2008 to 2020, we searched literatures with overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and adverse as outcome indicators and established a Bayesian mesh meta-analysis for multiple treatment strategies. Then, we combined the results of four outcome indicators to find out the best chemotherapy-based combination therapy strategy for patients with advanced lung cancer, further, we tried to screen out the best drugs of which were commonly used now. Results: It contained a total of 51 studies, including five combination therapies: Chemotherapy/Chemotherapy plus placebo (CT), chemotherapy plus one targeted therapy drug (CT+T), chemotherapy plus two targeted therapy drugs (CT+T+T), chemotherapy combined with immunotherapy (CT+I) or chemotherapy combined with biotherapy (CT+B). In terms of four outcome indicators, CT+I showed the best therapeutic benefits. In the comparison of immunotherapy drugs, pembrolizumab showed the best effect. Conclusion: Our results showed that, among the multiple chemotherapy-based combination therapy strategies, chemotherapy combined with immunotherapy is the best choice for patients with advanced lung cancer, and pembrolizumab combined with chemotherapy has the best effect.

Targeted cancer therapy has grown exponentially in the last decade, representing the largest frontier in the modern concept of precision medicine. This renaissance is largely due to our rapidly evolving ability to biochemically harness our immune systems to target cancer-specific antigens. Combined with an increasing armamentarium of surgical and non-invasive techniques for cancer mitigation we have upgraded cancer therapy from a non-specific assault on cell-division to a multi-modal, targeted approach. This renaissance has resulted in an increase in the perioperative footprint of patients with advanced cancer. The scope of the perioperative clinician has evolved from one of passive/reactive management of complications to a proactive approach that starts in the preoperative optimization phase and continues into the postoperative period. The perioperative world should not exist in a silo, and thus involvement of the oncology team is paramount. To provide safe oncologic care, it is essential to be up to date in newer cancer therapies, lest we act on erroneous and/or outdated information. Oncologists should weigh in on immune status, recent chemotherapeutic exposures, and potentially evolving toxicities. These might involve critical changes to perioperative infectious prophylaxis, steroid administration, and coagulopathy management. First, patients living beyond the typical life-expectancy for their cancer will carry a high burden of cancer-related downstream effects. General metabolic issues will include malnutrition, cachexia, and gastric outlet obstruction. Severe protein-calorie malnutrition, as well as hepatic and renal dysfunction can impact the metabolism and clearance of drugs. The cardiovascular, endocrinologic, pulmonary, and central nervous system implications of new cancer therapies will be discussed extensively below. Second, we have to enhance our ability to manage a cancer population who may be experiencing increasing novel chemotherapeutic toxicities. Newer agents differ from historical agents, which were blunt-force tools aimed at nonspecific destruction of cell-division. These drugs are efficacious but physiologically costly. Newer immunogenic therapies have a slightly improved acute safety profile, and a more complex chronic toxicity profile that may be overt or insidious. Chronic toxicities can present overtly or as a smoldering undertone to other active medical conditions such as sepsis, pneumonia, failure to thrive, or renal failure. The new therapies discussed in this review occur in the context of an overall increasingly multi-faceted cancer care machine. An example is screening for esophageal cancer in patients with Barrett's esophagus, or periodic chest CTs for patients with a strong history of tobacco use. These interventions are more likely to detect disease while it is still resectable, and resections will commonly accompany neo-adjuvant therapy. These approaches commonly involve new immunotherapies whose efficacy is higher-yield with a lower disease burden. In a recent example, the immune-checkpoint inhibitors (ICIs) ipilimumab plus nivolumab have significantly increased survival rate for squamous cell esophageal cancer when combined with standard chemotherapy. Surgical resection has evolved to one that often accompanies neoadjuvant chemo and radiation. The increasing efficacy of this approach may de-necessitate many major resections, and increase the number of sub-anatomic resections and minimally invasive procedures. Improved techniques - notably for hepatectomy, whipple procedure, prostatectomy, nephrectomy - have increased the safety profile and decreased the perioperative physiologic burden. This has enabled a broader subset of patients (due to cancer burden or due to medical comorbidities) to qualify for the operation, and increased the involvement of anesthesia and their perioperative services. With an increase in surgical candidacy comes an increase in post-surgical complications, and post-surgical maintenance such as drains, embolizations, imaging studies, etc. In the non-OR anesthesia realm, there have been considerable advancements in cancer “micro-treatments” such as hepatic metastasis embolization, tumor ablation, and peri-tumor vascular embolization. There are an ever-increasing number of IR-guided embolizations for bleeding tumors, aspiration of malignant effusions, and drainage of abscesses. This review serves to provide insight into new categories of chemotherapy and their perioperative implications.

Chronic kidney disease (CKD) is actually considered a public health priority according to the increasing number of patients affected by this condition: this casuistry is not only related to specific glomerular, tubular or autoimmune diseases or a consequence of acute kidney injury (AKI) episodes leading to organ failure, but it is tied to the progression of life expectancy and the impact of comorbidities such as cardiovascular disease, diabetes and cancer. CKD and its comorbidities promote low grade inflammatory status with an impact on patients’ clinical conditions, reducing their possibility for kidney transplantation or graft survival and their survival when receiving renal replacement therapies such as hemodialysis (HD) or peritoneal dialysis (PD). CKD is often referred to as an ageing accelerator: innate immune system dysregulation, in the uraemic proinflammatory milieu, is involved in this accelerated senescence phenomena and pentraxins, particularly Pentraxin-3 (PTX-3), are of particular interest in the development of kidney disease. A complete understanding of the mechanism of CKD progression, innate immune system involvement and a proper definition of PTX-3 role in kidney disease, could redefine the approach for diagnosis and a more centered patients’ management to slow down CKD progression over time and reduce its clinical and social impact.

Viral diseases represent a major public health concern and an ever-present risk for developing into a future pandemic. Antiviral antibody therapeutics, either alone or in combination with other therapies, have emerged as valuable preventative and treatment options, including during a global emergency. Here we will discuss polyclonal and monoclonal antiviral antibody therapies, focusing on the unique biochemical and physiological properties that make them well suited as therapeutic agents. We will describe the methods of antibody characterization and potency assessment throughout development, highlighting similarities and differences between polyclonal and monoclonal products as appropriate. In addition, we will consider the benefits and challenges of antiviral antibodies when used in combination with other antibodies or other types of antiviral therapeutics. Lastly, we will discuss novel approaches to the characterization and development of antiviral antibodies and identify areas that would benefit from additional research.

The construction safety risks (such as landslides or slumps) of the high-fill subgrade are characterized by uncertainty and variability. In order to ensure the construction safety of the high-fill subgrade of the expressway, a comprehensive risk assessment model of high-fill subgrade construction according to the combination weighting method based on game theory was established. Firstly, settlement rate, lateral differential settlement, horizontal displacement at the foot of the slope, deep horizontal displacement, and excess pore pressure were selected as evaluation indicators, and an evaluation index system of high-fill subgrade was constructed. Secondly, the subjective and objective weights were obtained via the analytic hierarchy process and entropy method. Furthermore, the optimized weights were obtained by introducing game theory, and the construction risk of the high-fill subgrade was evaluated and analyzed using the fuzzy comprehensive evaluation method. Finally, based on the high-fill section of the Zhijiang-Tongren Expressway in Hunan Province (China), the evaluation model was validated through field measurement data. The results show that the safety scores obtained using the three methods of analytic hierarchy process, entropy method, and combination weighting method based on game theory are similar. The combination weighting evaluation model can correct the evaluation result error caused by a single weight and avoid information delay caused by the manual processing and analysis of monitoring data. The high-fill subgrade safety evaluation grade based on the combination weighting method and game theory is consistent with the engineering situation, and its fault tolerance range is within 20%. The evaluation model proposed in this study can scientifically and effectively evaluate the safety risks of high-fill subgrade construction, significantly improving the safety and reliability during the construction process.

Modern power system integrates more and more new energy and use a large number of power electronic equipment. This makes it face more challenges in online optimization and real-time control. Deep reinforcement learning(DRL) has the ability of processing big data and high-dimensional features, as well as the ability of independently learning and optimizing decision-making in complex environments. In this paper, we explore DRL based online combination optimization method of grid section for large complex power system. In our method, to improve the convergence speed of the model, we propose to discretize the output action of the unit and simplify the action space. We also design a reinforcement learning loss function with strong constraints to further improve the convergence speed of the model and facilitate the algorithm to obtain the stable solution. Moreover, to avoid the local optimal solution problem caused by the discretization of the output action, we propose to use the annealing optimization algorithm to make the granularity of the unit output finer. We verify our method on IEEE 118-bus system. The experimental results show that our model has fast convergence speed and better performance, and can obtain stable solutions.

Immune checkpoint inhibitors (ICI’s) are in the forefront of advanced Non Small Cell Lung Cancer (NSCLC) treatment. Still, only 27- 46% of patients respond to initial therapy with ICI’s and of those, up to 65% develop resistance within four years. After disease progression (PD), treatment options are limited, with 10% Objective Response Rate (ORR) to second or third-line chemotherapy. In this context, ICI rechallenge is an appealing option for NSCLC. Most data on the efficacy of ICI rechallenge are based on retrospective real-world studies of small, heavily pretreated, and heterogeneous patient groups. Despite these limitations, these studies suggest that ICI monotherapy rechallenge in unselected NSCLC patient populations who discontinued initial ICI due to PD is generally ineffective, with a median Progression-Free Survival (PFS) of 1.6-3.1 months and a Disease Control Rate (DCR) of 21.4%-41.6%. However, there is a subpopulation that benefits from this strategy, and further characterization of this subgroup is essential. Furthermore, immunotherapy rechallenge in patients who discontinued initial immunotherapy following treatment protocol completion and progressed after an immunotherapy-free interval showed promising efficacy, with a DCR of 75-81%, according to post-hoc analyses of several clinical trials. Future research of ICI rechallenge for NSCLC should focus on better patient stratification, to reflect the underlying biology of immunotherapy resistance more accurately.

Lung cancer remains a formidable global health challenge that necessitates inventive strategies to improve therapeutic outcomes. Conventional treatments, including surgery, chemotherapy, and radiation, have demonstrated limitations in achieving sustained responses. Therefore, the explora-tion of novel approaches encompasses a range of interventions that show promise in enhancing outcomes for patients with lung cancer, particularly those facing advanced or refractory cases. These groundbreaking interventions hold the potential to overcome cancer resistance and offer personalized solutions. Despite the rapid evolution of emerging lung cancer therapies, persistent challenges such as resistance, toxicity, and patient selection underscore the need for continued development. Consequently, the landscape of lung cancer therapy is transforming with the in-troduction of precision medicine, immunotherapy, and innovative therapeutic modalities. Addi-tionally, a multifaceted approach involving combination therapies through the integration of tar-geted agents, immunotherapies, or traditional cytotoxic treatments addresses the heterogeneity of lung cancer while minimizing adverse effects. This review provides a brief overview of the latest emerging therapies that are reshaping the landscape of lung cancer treatment. As these novel treatments progress through clinical trials and integrate into standard care, the potential for more effective, targeted, and personalized lung cancer therapies comes into focus, instilling renewed hope for patients facing challenging diagnoses.

Mycobacterium abscessus is a non-tuberculous mycobacteria notoriously known for causing severe, chronic infections. Treatment of these infections is challenging due to either intrinsic or acquired resistance of M. abscessus to multiple antibiotics. Despite prolonged poly-antimicrobial therapy, treatment of M. abscessus infections often fails, leading to progressive morbidity and eventual mortality. Great research efforts are invested in finding new therapeutic options for M. abscessus. Clofazimine and rifabutin are known anti-mycobacterial antibiotics, repurposed for use against M. abscessus. Novel antimicrobials active against M. abscessus include delamanid, pretomanid and PIPD1 and the recently approved beta-lactamase inhibitors avibactam, relebactam and vaborbactam. Previously unused antimicrobial combinations e.g. vancomycin-clarithromycin and dual beta-lactam therapy have been shown to have synergistic effect against M. abscessus in experimental models, suggesting their possible use in multiple-drug regimens. Finally, engineered phage therapy has been reported to be clinically successful in a severe case of disseminated M. abscessus infection. While many of these experimental therapeutics have shown activity against M. abscessus in vitro, as well as intracellular and/or animal models, most have little if any evidence of effect in humans infections. Clinical studies of M. abscesssus treatments are needed in order to reliably determine the value of their incorporation in therapeutic regimens.

The application of three-dimensional (3D) printing/bioprinting technologies and cell therapies has garnered significant attention due to their potential in the field of regenerative medicine. This paper aims to provide a comprehensive overview of 3D printing/bioprinting technology and cell therapies, highlighting their results in diverse medical applications, while also discussing the capabilities and limitations of their combined use. The synergistic combination of 3D printing and cellular therapies has been recognised as a promising and innovative approach, and it is expected that these technologies will progressively assume a crucial role in the treatment of various diseases and conditions in the foreseeable future. This review concludes with a forward-looking perspective on the future impact of these technologies, highlighting their potential to revolutionize regenerative medicine through enhanced tissue repair and organ replacement strategies.

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths. Classically, liver transplantation (LT) can be curable for HCC tumors within the Milan criteria. Bridging strategies to reduce the dropouts from LT waiting lists or/and to downstage patients who are beyond Milan criteria are widely utilized. We conducted a literature-based review to evaluate the role of systemic therapies as a bridging treatment to liver transplantation (LT) in HCC patients. Tyrosine Kinase Inhibitors (TKIs) can be used as a bridging systemic therapy to LT in patients with contraindication to locoregional liver-directed therapies. Immune Checkpoint Inhibitors (ICIs) treatment can be utilized either as a monotherapy or as a combination therapy with Bevacizumab or TKIs prior to LT. Acute rejection post liver transplantation is a concern in the context of ICIs treatment. Thus, a safe ICI washout period before LT and cautious post-LT immunosuppression strategies are required to reduce post-LT rejections and to optimize clinical outcomes. Nevertheless, prospective clinical trials are needed to establish definitive conclusions about the utility of systemic therapy as a bridging modality prior to LT in HCC patients.

(1)Background: Among new anti-angiogenetic agents being developed and everchanging guidelines indications, the question of benefits/safety ratio remains unclear. (2)Methods: we have conducted a systematic review and meta-analysis of 25 randomized controlled trials (15487 patients), evaluating overall survival – OS, progression free survival– PFS and toxicity (grade ≥3 adverse effects, type and number of all adverse effects. (3)Results: analysis showed improvement of pooled-PFS (HR 0.72, 95%CI 0.66–0.78, I2 = 77%, P<0.00001) regardless of treatment settings (first-line - HR 0.83, 95%CI 0.77-0.90, P<0.00001, recurrent cancer – HR 0.61, 95%CI 0.54-0.68, P<0.00001 or maintenance – HR 0.82, 95%CI 0.67-1.00, P=0.04) and type of anti-angiogenetic drug used (VEGF inhibitors, VEGF-R inhibitors or angiopoietin inhibitors). Improved OS was also observed (HR 0.95, 95%CI 0.91–0.99, P=0.02). OS benefits were only observed in recurrent platinum-sensitive or platinum-resistant cancers. Grade≥3 adverse effects were increased across all trials. Anti-angiogenetic therapy increased the risk of hypertension, infection, thromboembolic/ hemorrhagic events, gastro-intestinal perforations but not the risk of wound related issues, anemia or posterior leukoencephalopathy syndrome. (4)Conclusions: Although angiogenesis inhibitors improve PFS, there is little to no OS benefits. Given the high risk of severe adverse reactions a careful selection of patients is required for obtaining the best results possible.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

The objective of this study was to investigate the transcriptomic profiling of differentially ex-pressed genes between a commercial layer breed and an indigenous Indian breed. RNA was ex-tracted from NDV-infected and uninfected embryo lung tissue samples of Aseel, Kadaknath, and White Leghorn chickens. RNA-Seq was performed, and reads were aligned to the chicken refer-ence genome (Galgal7). A total of 594 genes were significantly differentially expressed, with 264 upregulated and 330 downregulated in infected embryos. Highly overexpressed genes in infect-ed conditions included C8A, FGG, PIT54, FETUB, APOC3, FGA, SPIA1, AvBD13, APOH, AMBP, TTR, PLA2G12B. Additionally, 29 novel transcripts and 20 lncRNAs were upregulated. White Leghorn embryos showed distinct expression patterns for CAV1 and GATA3, while Kadaknath healthy embryos had higher levels of CYTB, HBBA, ND4, ND4L, and ND5, indicating breed uniqueness. The analysis revealed significant gene involvement through Gene Ontology and KEGG pathways, highlighting alterations in gene expression related to immune function, me-tabolism, cell cycle, nucleic acid processes, and mitochondrial activity due to NDV infection. ALDOB, PRPS2, XDH, DCK2, and TK1 genes, which were involved in several metabolic path-ways, clearly displayed an altered expression pattern in the infected embryo. Additionally, ALB, TLR4, TLR2, TLR21, IL1R2, IL22RA2, HSP90AA, HSPB9(p60), and HSPB8 were significantly up-regulated in infected lung samples, while CXCR4, CXCL14, GATA3, IL17REL, and IL22RA1 were downregulated. Notably, higher expression of HSPs in Kadaknath suggests heat tolerance. This research provides insights into the genetic differences between commercial and local breeds and reveals the impact of NDV infection on metabolic processes, potentially identifying candidate genes for breed improvement.

The development of multidrug resistance by pathogenic bacteria and yeast is a significant medical problem that needs to be addressed. One possible answer could be the combined use of antibiotics and silver nanoparticles, which have different mechanisms of antimicrobial action. Nanoparticles can be combined with antifungal agents in the same way. Biogenic silver nanoparticles synthesized using environmentally friendly technology using extracts of biologically active plants are an effective nanomaterial that needs to be comprehensively investigated for implementation into medical practice. In this study, the synergistic effects arising from their combined use with antibiotics and fungicides against various bacteria and yeasts, included in the ESKAPE list, were studied. Effective concentrations of substances were established, recommendations for the studied pathogenic species were presented and the effect of destruction of the bacterial membrane was illustrated. The most significant synergistic effect was manifested in pathogenic candida and brewer's yeast.

Glioblastoma (GBL) is one of the more malignant primary brain tumors, currently treated by a multimodality strategy including surgery, radio- and chemotherapy, mainly consisting of Temozolomide(TMZ)-based chemotherapy. Tumor relapse often occurs due to the establishment of TMZ resistance, with a patient median survival <2 years. The identification of natural molecules having strong anti-tumor activity, led to combine these compounds with conventional chemotherapeutic agents, developing protocols of integrated anticancer therapies. Curcumin (CUR), Resveratrol (RES), and its glucoside Polydatin (PLD) are widely employed in the pharmaceutical and nutraceutical fields, and several studies demonstrated that the combination of these natural products was more cytotoxic than the single compound alone in different cancers. Some of us recently demonstrated the synergistic efficacy of the sublingual administration of a new nutraceutical formulation of CUR+PLD in reducing tumor size and improving GBL patient survival. To deepen some mechanistic aspects of these results, we investigated if the pretreatment with a combination of CUR+PLD, can improve TMZ cytotoxicity on GBL cells, by analyzing the effects on cell cycle, viability and morphology, on proteins related to cell proliferation, differentiation, apoptosis or autophagy, and on actin network. Cell viability was assessed by MTT or by the cell counter CytoSmart. CalcuSyn software was used to study the CUR+PLD synergism. Morphology was evaluated by optical and scanning electron microscopy, and protein expression was analyzed by Western Blot. Flow cytometry was used for cell cycle, autophagic flux, and apoptosis analyses. The results obtained provide evidence that CUR and PLD, acting in synergy with each other, strongly improve the efficacy of alkylating antitumor agents such as TMZ, also in drug-resistant GBL cells, through their abilities to affect survival, differentiation, and tumor invasiveness.

Dysmenorrhea symptoms are frequent and often self-treated using non-prescription medicines. To further characterize women with dysmenorrhea using a combination of hyoscine butylbromide and paracetamol (PLUS) for self-management of their complaints, we performed a secondary analysis of a published pharmacy-based patient survey. 314 women (mean age 32.3 years) with dysmenorrhea reported a pain and cramps intensity of 7.45 ± 2.13 on a 0-10 Likert scale, which was reduced to 2.86 ± 1.81 upon treatment. Associated impairments of work/daily chores, leisure activities, and sleep were improved by 64.6%, 62.2% and 70.4%, respectively. The onset of symptom relief was within 60 min in 84.7%. Tolerability was rated as very good or good by 97.2%. These findings confirm the efficacy and tolerability data on PLUS from randomized controlled trials in a larger group of women conducting self-management of their dysmenorrhea.