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Abstract Terahertz (THz) emission spectroscopy (TES) has emerged as a highly effective and versatile technique for investigating the photoelectric properties of diverse materials and nonlinear physical processes in the past few decades. Concurrently, research on two-dimensional (2D) materials has experienced substantial growth due to their atomically thin structures, exceptional mechanical and optoelectronic properties, and the potential for applications in flexible electronics, sensing, and nanoelectronics. Specifically, these materials offer advantages such as tunable bandgap, high carrier mobility, wideband optical absorption, and relatively short carrier lifetime. By applying TES to investigate the 2D materials, their interfaces and heterostructures, rich information about the interplay among photons, charges, phonons and spins can be unfolded, which provides fundamental understanding for future applications. Thus it is timely to review the nonlinear processes underlying THz emission in 2D materials including optical rectification, photon-drag, high-order harmonic generation and spin-to-charge conversion, showcasing the rich diversity of the TES employed to unravel the complex nature of these materials. Typical applications based on THz emissions, such as THz lasers, ultrafast imaging and biosensors, are also discussed. Step further, we analyzed the unique advantages of spintronic terahertz emitters and the future technological advancements in the development of new THz generation mechanisms leading to advanced THz sources characterized by wide bandwidth, high power and integration, suitable for industrial and commercial applications. The continuous advancement and integration of TES with the study of 2D materials and heterostructures promise to revolutionize research in different areas, including basic materials physics, novel optoelectronic devices, and chips for post-Moore’s era.

Objective: To validate deep learning models’ ability to predict post-transplantation major adverse cardiovascular events (MACE) in patients undergoing liver transplantation (LT). Patients and Methods: We used data from Optum’s de-identified Clinformatics Data Mart Database to identify liver transplant recipients between January 2007 and March 2020. To predict post-transplantation MACE risk, we considered patients’ demographics characteristics, diagnoses, medications, and procedural data recorded back to 3 years before the LT procedure date (index date). MACE is predicted using the bidirectional gated recurrent units (BiGRU) deep learning model in different prediction interval lengths up to 5 years after the index date. In total, 18,304 liver transplant recipients (mean age, 57.4 years [SD, 12.76]; 7158 [39.1%] women) were used to develop and test the deep learning model’s performance against other baseline machine learning models. Models were optimized using 5-fold cross-validation on 80% of the cohort, and model performance was evaluated on the remaining 20% using the area under the receiver operating characteristic curve (AUC-ROC) and the area under the precision-recall curve (AUC-PR). Results: Using different prediction intervals after the index date, the top-performing model was the deep learning model, BiGRU, and achieved an AUC-ROC of 0.841 (95% CI, 0.822-0.862) and AUC-PR of 0.578 (95% CI, 0.537-0.621) for a 30-day prediction interval after LT. Conclusion: Using longitudinal claims data, deep learning models can efficiently predict MACE after LT, assisting clinicians in identifying high-risk candidates for further risk stratification or other management strategies to improve transplant outcomes based on important features identified by the model.

Summary: Background: Findings regarding the protective effect of Angiotensin II receptor blockers (ARBs) against Alzheimer’s disease and related dementias (AD/ADRD) and cognitive decline have been inconclusive. Methods: Individuals with hypertension who do not have any prior ADRD diagnosis were included in this retrospective cohort study from Optum’s de-identified Clinformatics® Data Mart. We identified antihypertensive medication (AHM) drug classes and subclassified ARBs by blood–brain barrier (BBB) permeability. We compared baseline characteristics and used the Kaplan–Meier (KM) survival curve and adjusted Cox proportional hazards (PH) model for survival analyses. Findings: From 6,390,826 individuals with hypertension, there were 1,839,176 ARB users, 3,366,841 non-ARB AHM users, and 1,184,809 AHM non-users. The unadjusted KM curve showed that ARB users had lower cumulative hazard than other AHM users or AHM non-users (P

Abstract Sustainable functionalization of bacterial cellulose for cost‐effective bionanocomposites with desired properties has received growing attention in recent years. This article presents the results of work aimed at obtaining bionanocomposite materials based on bacterial cellulose, a natural and eco‐friendly material. Bacterial cellulose obtained from the Kombucha symbiotic culture of bacteria and yeast (SCOBY) fermentation process is functionalized by embedding with diatom frustules, silver nanoparticles (AgNPs), and poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). The effects of functionalization on mechanical, optical, plasmonic, electrical, chemiluminescent, and antimicrobial properties are evaluated. Morphological characteristics of the nanocomposites are studied using electron microscopy. Addition of diatom frustules introduced into the SCOBY culture media results in bionanocomposite materials with enhanced tensile strength and increased ultraviolet (UV) blockage properties. In situ functionalization of bacterial cellulose with AgNPs tunes plasmonic and chemiluminescent properties, revealing the biosensing potential of the material. Modified bacterial cellulose shows antimicrobial activity in experiments with gram‐positive and gram‐negative bacteria. Dual functionalization of bacterial cellulose with PEDOT:PSS and AgNPs results in improved electrical conductivity of the bionanocomposite. Overall, bottom‐up physical functionalization approaches and the resulting bionanocomposite materials will open up new opportunities for the low‐cost production of green materials and contribute to the development of a sustainable economy.

BackgroundPatient-targeted Googling (PTG) is an unavoidable aspect of the internet era, offering both opportunities and risks. However, no PTG studies have been conducted in Asian contexts to date. Additionally, existing research has provided limited exploration of factors influencing PTG practices, particularly regarding the professional differences between psychiatrists and psychologists. This study seeks to address these research gaps.MethodA total of 943 licensed psychiatrists and psychologists working in China completed an online survey. The survey included their attitudes towards PTG (including general attitude, application situations, reasons for/against PTG) and their actual practice of PTG.Results250(26.5%) respondents reported using PTG. Among them, 151(60.4%) respondents sought consent from clients before use, and 142(56.8%) respondents discussed search results with clients after use. Chinese psychiatrists and psychologists have contradictory attitudes, with concerns but also recognition of its possible positive effects, and expressing a need for more guidance. Compared to psychiatrists or those working in public institutions, psychologists and those working in private institutions report greater concerns about PTG but engage in it more frequently.ConclusionsAlthough the sample is limited, the study reveals notable differences in attitudes and practice of PTG among Chinese psychiatrists and psychologists, which may be related to their distinct professional roles and workplace environments. These findings suggest the need for further research to better understand the underlying factors contributing to these differences. Moreover, the results highlight the importance of developing tailored ethical guidelines and targeted training programs to address PTG practices for psychiatrists and psychologists in China.

Abstract Background The pattern recognition receptor Dectin-1 was initially discovered to play a pivotal role in mediating pulmonary antifungal immunity and promoting neutrophil-driven inflammation. Recent studies have revealed that Dectin-1 is overexpressed in asthma, but the specific mechanism remains elusive. Additionally, Dectin-1 has been implicated in promoting pyroptosis, a hallmark of severe asthma airway inflammation. Nevertheless, the involvement of the non-classical pyroptosis signal caspase-11/4 and its upstream regulatory mechanisms in asthma has not been completely explored. Methods House dust mite (HDM)-induced mice was treated with Dectin-1 agonist Curdlan, Dectin-1 inhibitor Laminarin, and caspase-11 inhibitor wedelolactone separately. Subsequently, inflammatory cells in bronchoalveolar lavage fluid (BALF) were analyzed. Western blotting was performed to measure the protein expression of caspase-11 and gasdermin D (GSDMD). Cell pyroptosis and the expression of chemokine were detected in vitro. The correlation between Dectin-1 expression, pyroptosis factors and neutrophils in the induced sputum of asthma patients was analyzed. Results Curdlan appeared to exacerbate neutrophil airway inflammation in asthmatic mice, whereas wedelolactone effectively alleviated airway inflammation aggravated by Curdlan. Moreover, Curdlan enhanced the release of caspase-11 activation fragments and N-terminal fragments of gasdermin D (GSDMD-N) stimulated by HDM both in vivo or in vitro. In mouse alveolar macrophages (MH-S cells), Curdlan/HDM stimulation resulted in vacuolar degeneration and elevated lactate dehydrogenase (LDH) release. In addition, there was an upregulation of neutrophil chemokines CXCL1, CXCL3, CXCL5 and their receptor CXCR2, which was suppressed by wedelolactone. In asthma patients, a positive correlation was observed between the expression of Dectin-1 on macrophages and caspase-4 (the human homology of caspase-11), and the proportion of neutrophils in induced sputum. Conclusion Dectin-1 activation in asthma induced caspase-11/4 mediated macrophage pyroptosis, which subsequently stimulated the secretion of chemokines, leading to the exacerbation of airway neutrophil inflammation. Graphical Abstract

Aging increases the risks of various diseases and the vulnerability to death. Cellular senescence is a hallmark of aging that contributes greatly to aging and aging-related diseases. This study demonstrates that extracellular vesicles from human urine-derived stem cells (USC-EVs) efficiently inhibit cellular senescence in vitro and in vivo. The intravenous injection of USC-EVs improves cognitive function, increases physical fitness and bone quality, and alleviates aging-related structural changes in different organs of senescence-accelerated mice and natural aging mice. The anti-aging effects of USC-EVs are not obviously affected by the USC donors’ ages, genders, or health status. Proteomic analysis reveals that USC-EVs are enriched with plasminogen activator urokinase (PLAU) and tissue inhibitor of metalloproteinases 1 (TIMP1). These two proteins contribute importantly to the anti-senescent effects of USC-EVs associated with the inhibition of matrix metalloproteinases, cyclin-dependent kinase inhibitor 2A (P16INK4a), and cyclin-dependent kinase inhibitor 1A (P21cip1). These findings suggest a great potential of autologous USC-EVs as a promising anti-aging agent by transferring PLAU and TIMP1 proteins.

Objective Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets.Methods Network data from two cohorts of younger sexual minority men (SMM) from two U.S. cities (Chicago, IL, and Houston, TX) were collected between 2014 and 2016. Feature importance from graph attention network (GAT) models were determined using GNNExplainer. Domain adaptation was performed to examine model transferability from one city dataset to the other dataset, training with 100% of the source dataset with 30% of the target dataset and prediction on the remaining 70% from the target dataset.Results Domain adaptation showed the ability of GAT to improve prediction over training with single city datasets. Feature importance analysis with GAT models in single city training indicated similar features across different cities, reinforcing potential application of GAT models in predicting HIV infections through domain adaptation.Conclusion GAT models can be used to address the data sparsity issue in HIV study populations. They are powerful tools for predicting individual risk of HIV that can be further explored for better understanding of HIV transmission.

Smoking is by far one of the greatest public health threats and is recognized as an important predisposing factor for osteoporosis. Exposure to cigarette smoke (CS) has been reported to be associated with inflammation-associated diseases through the induction of pyroptosis. Nevertheless, the correlation between pyroptosis and bone loss induced by CS remains uninvestigated. Here, a mouse model of mainstream smoke exposure-induced osteoporosis was established. μCT, biomechanical testing, and immunohistochemical staining of bone tissue were used to assess the deleterious effects of CS on bone metabolism. In vitro, the effects of cigarette smoke extracts (CSE) on mouse primary bone marrow-derived mesenchymal stem cells (BMSCs) were tested by cell viability assays, gene and protein expression assays, and alizarin red staining. The utilization of the pyroptosis inhibitor MCC950 served to confirm the critical role of BMSCs pyroptosis in CS-induced osteoporosis. Our results indicated that exposure to mainstream smoke led to a notable decrease in the quantity of osteoblasts and hindered the process of osteogenic differentiation in mice. Additionally, there was a significant increase in the expression of pyroptosis-related proteins in the bone marrow. The inhibitory effects of CSE on cell viability and osteogenic differentiation of BMSCs were found to be dose-dependent in vitro. However, the presence of the pyroptosis inhibitor MCC950 significantly improved the impaired osteogenic differentiation and bone mineralization caused by CSE. These results highlight the crucial involvement of BMSCs pyroptosis in the development of bone loss induced by CS. In summary, the findings of this study provide novel evidence that CS exerts a detrimental effect on the process of osteogenesis in BMSCs through the induction of pyroptosis, ultimately leading to bone loss. Inhibition of pyroptosis effectively attenuated the toxicological effects of CS on BMSCs, providing a new target for preventing inflammatory osteoporosis.

BackgroundAlzheimer disease and related dementias (ADRD) rank as the sixth leading cause of death in the United States, underlining the importance of accurate ADRD risk prediction. While recent advancements in ADRD risk prediction have primarily relied on imaging analysis, not all patients undergo medical imaging before an ADRD diagnosis. Merging machine learning with claims data can reveal additional risk factors and uncover interconnections among diverse medical codes. ObjectiveThe study aims to use graph neural networks (GNNs) with claim data for ADRD risk prediction. Addressing the lack of human-interpretable reasons behind these predictions, we introduce an innovative, self-explainable method to evaluate relationship importance and its influence on ADRD risk prediction. MethodsWe used a variationally regularized encoder-decoder GNN (variational GNN [VGNN]) integrated with our proposed relation importance method for estimating ADRD likelihood. This self-explainable method can provide a feature-important explanation in the context of ADRD risk prediction, leveraging relational information within a graph. Three scenarios with 1-year, 2-year, and 3-year prediction windows were created to assess the model’s efficiency, respectively. Random forest (RF) and light gradient boost machine (LGBM) were used as baselines. By using this method, we further clarify the key relationships for ADRD risk prediction. ResultsIn scenario 1, the VGNN model showed area under the receiver operating characteristic (AUROC) scores of 0.7272 and 0.7480 for the small subset and the matched cohort data set. It outperforms RF and LGBM by 10.6% and 9.1%, respectively, on average. In scenario 2, it achieved AUROC scores of 0.7125 and 0.7281, surpassing the other models by 10.5% and 8.9%, respectively. Similarly, in scenario 3, AUROC scores of 0.7001 and 0.7187 were obtained, exceeding 10.1% and 8.5% than the baseline models, respectively. These results clearly demonstrate the significant superiority of the graph-based approach over the tree-based models (RF and LGBM) in predicting ADRD. Furthermore, the integration of the VGNN model and our relation importance interpretation could provide valuable insight into paired factors that may contribute to or delay ADRD progression. ConclusionsUsing our innovative self-explainable method with claims data enhances ADRD risk prediction and provides insights into the impact of interconnected medical code relationships. This methodology not only enables ADRD risk modeling but also shows potential for other image analysis predictions using claims data.

MoS2 has excellent vacuum lubricating performance. However, it is prone to be oxidized in a high-temperature atmospheric environment, leading to the deterioration of its lubricating performance and even serious space accidents. The high-temperature lubricating performance of MoS2-based solid lubricating materials can be improved to some extent by the co-compounding of appropriate oxides and Ag. The tribological properties of several common nano-oxides (ZnO, TiO2, Al2O3, and ZrO2) composited with metal Ag of MoS2-based composites were compared at 450 °C. The results showed that the comprehensive tribological performance of MoS2-TiO2-Ag was the best, an the average friction coefficient of about 0.26, and a wear rate of about 1.2 × 10−5 mm3/Nm, which was 18% and 43% lower than that of MoS2-Ag, respectively. The excellent tribological properties of MoS2-TiO2-Ag composites were attributed to three aspects: Firstly, with the help of the oxidation resistance of TiO2 to MoS2 to some extent and its high ionic potential, its oxidation resistance was improved and its shear strength was reduced to provide low friction. Secondly, relying on the low shear strength and good film-forming tendency of soft metal Ag on the sliding surface, a low shear tribo-film was easily formed on the friction interface, which was helpful for the synergistic lubrication of Ag, MoS2, and TiO2.Thirdly, through the matching of hard TiO2 and soft Ag, the wear resistance and bearing capacity of the composites were improved to some extent. The research results can provide some reference for the selection and design of MoS2-based high-temperature lubricating materials and the enhancement of their tribological properties.

Optical biosensors have emerged as a powerful tool in analytical biochemistry, offering high sensitivity and specificity in the detection of various biomolecules. This article explores the advancements in the integration of optical biosensors with microfluidic technologies, creating lab-on-a-chip (LOC) platforms that enable rapid, efficient, and miniaturized analysis at the point of need. These LOC platforms leverage optical phenomena such as chemiluminescence and electrochemiluminescence to achieve real-time detection and quantification of analytes, making them ideal for applications in medical diagnostics, environmental monitoring, and food safety. Various optical detectors used for detecting chemiluminescence are reviewed, including single-point detectors such as photomultiplier tubes (PMT) and avalanche photodiodes (APD), and pixelated detectors such as charge-coupled devices (CCD) and complementary metal–oxide–semiconductor (CMOS) sensors. A significant advancement discussed in this review is the integration of optical biosensors with pixelated image sensors, particularly CMOS image sensors. These sensors provide numerous advantages over traditional single-point detectors, including high-resolution imaging, spatially resolved measurements, and the ability to simultaneously detect multiple analytes. Their compact size, low power consumption, and cost-effectiveness further enhance their suitability for portable and point-of-care diagnostic devices. In the future, the integration of machine learning algorithms with these technologies promises to enhance data analysis and interpretation, driving the development of more sophisticated, efficient, and accessible diagnostic tools for diverse applications.

Cardiolipin (CL), a critical phospholipid situated within the mitochondrial membrane, plays a significant role in modulating intramitochondrial processes, especially in the context of certain cardiac pathologies; however, the exact effects of alterations in cardiolipin on septic cardiomyopathy (SCM) are still debated and the underlying mechanisms remain incompletely understood. This study highlights a notable increase in the expressions of ALCAT1 and PLSCR3 during the advanced stage of lipopolysaccharide (LPS)-induced SCM. This up-regulation potential contribution to mitochondrial dysfunction and cellular apoptosis—as indicated by the augmented oxidative stress and cytochrome c (Cytc) release—coupled with reduced mitophagy, decreased levels of the antiapoptotic protein B-cell lymphoma-2 (Bcl-2) and lowered cell viability. Additionally, the timing of LPS-induced apoptosis coincides with the decline in both autophagy and mitophagy at the late stages, implying that these processes may serve as protective factors against LPS-induced SCM in HL-1 cells. Together, these findings reveal the mechanism of LPS-induced CL changes in the center of SCM, with a particular emphasis on the importance of pathological remodeling and translocation of CL to mitochondrial function and apoptosis. Additionally, it highlights the protective effect of mitophagy in the early stage of SCM. This study complements previous research on the mechanism of CL changes in mediating SCM. These findings enhance our understanding of the role of CL in cardiac pathology and provide a new direction for future research.

An integrated microfluidic planar reactor is essential for achieving efficient and enhanced photocatalytic water treatment. Optimization of catalysts is an area of intense study owing to the need to enhance the performances of microreactors. A high-efficiency photocatalytic microreactor is presented here by combining a planar microreactor with a high-efficiency photocatalyst. TiO2 nanoparticles doped with Y and Yb were prepared to improve the photocatalytic reaction efficiency. First, better performance is achieved with the Y, Yb/TiO2 and TiO2 microreactors than conventional bulk reactors because of good photodegradation and a high reaction rate. Then, the Y, Yb/TiO2 film microreactor exhibits not only efficient catalytic activity with UV light but also higher photocatalytic activity under visible light irradiation than that achieved by a TiO2 film microreactor. The reaction rate constant of the Y, Yb/TiO2 film microreactor is approximately 0.530 s–1, which is twice that of the TiO2 film microreactor. Moreover, the performances under continuous and intermittent reactions are compared to evaluate the stability of the microreactor, thereby building the foundation for practical application of continuous water treatment in the microreactor.The planar microreactor provides a convenient platform for studying photodegradation under various conditions, such as different temperatures, flow rates, light irradiation (UV and Vis), and reaction modes (continuous and intermittent).

ABSTRACT: Artificial insemination (AI) technology has greatly promoted the development of the chicken industry. Recently, AI technology has also begun to be used in the duck industry, but there are some problems. Numerous researchers have shown that microbes colonizing in semen can degrade semen quality, and AI can increase the harmful microbial load in hen's reproductive tract. Different from the degraded external genitalia of roosters, drakes have well-developed external genitalia, which may cause drake semen to be more susceptible to microbial contamination. However, information on the compositions, sources, and effects of semen microbes on semen quality remains unknown in drakes. In the current study, high-throughput sequencing technology was used to detect microbial communities in drake semen, environmental swabs, cloacal swabs, and the spermaduct after quantifying the semen quality of drakes to investigate the effects of microbes in the environment, cloaca, and spermaduct on semen microbiota and the relationships between semen microbes and semen quality. Taxonomic analysis showed that the microbes in the semen, environment, cloaca, and spermaduct samples were all classified into 4 phyla and 25 genera. Firmicutes and Proteobacteria were the dominant phyla. Phyllobacterium only existed in the environment, while Marinococcus did not exist in the cloaca. Of the 24 genera present in semen: Brachybacterium, Brochothrix, Chryseobacterium, Kocuria, Marinococcus, Micrococcus, Rothia, Salinicoccus, and Staphylococcus originated from the environment; Achromobacter, Aerococcus, Corynebacterium, Desemzia, Enterococcus, Jeotgalicoccus, Pseudomonas, Psychrobacter, and Turicibacter originated from the cloaca; and Agrobacterium, Carnobacterium, Chelativorans, Devosia, Halomonas, and Oceanicaulis originated from the spermaduct. In addition, K-means clustering analysis showed that semen samples could be divided into 2 clusters based on microbial compositions, and compared with cluster 1, the counts of Chelativorans (P < 0.05), Devosia (P < 0.01), Halomonas (P < 0.05), and Oceanicaulis (P < 0.05) were higher in cluster 2, while the sperm viability (P < 0.05), total sperm number (P < 0.01), and semen quality factor (SQF) (P < 0.01) were lower in cluster 2. Furthermore, functional prediction analysis of microbes showed that the activities of starch and sucrose metabolism, phosphotransferase system, ABC transporters, microbial metabolism in diverse environments, and quorum sensing pathways between cluster 1 and cluster 2 were significantly different (P < 0.05). Overall, environmental/cloacal microbes resulted in semen contamination, and microbes from the Chelativorans, Devosia, Halomonas, and Oceanicaulis genera may have negative effects on semen quality in drakes by affecting the activities of starch and sucrose metabolism, phosphotransferase system, ABC transporters, and quorum sensing pathways that are associated with carbohydrate metabolism. These data will provide a basis for developing strategies to prevent microbial contamination of drake semen.

Microbubbles with a negligible shell are of utmost importance in the study of harmonic ultrasound contrast agents. The purpose of this study was to collect and quantify experimental pulsation footage of gas microbubbles released from tablet matrix under sonication. Radii were measured as a function of time of 50 microbubbles that had been released from tablet matrix and were subjected to 3-cycle pulses of 1-MHz ultrasound with a 0.3-MPa peak-negative pressure. The size distribution was measured, as well as pre- and postsonication radii. The experimental footage showed proof of asymmetric buckling, but also of excursion-only behaviour. The former phenomenon has been attributed to a surplus of material accumulated on the microbubble-liquid interfaces, whilst the latter phenomenon has been associated with the presence of incompressible material inside the microbubbles. The postsonication resting radii of 41 microbubbles had become less compared to the corresponding pre-sonication radii. The opposite effect was observed with eight microbubbles in the same size range. This feasibility study confirmed that the gas microbubbles released from tablet matrix may pulsate asymmetrically. Thus, they might be suitable tracers for harmonic imaging.

Habenaria and Liparis are well-known orchid genera that grow in terrestrial habitats in the tropics, subtropics or temperate zones. Three species have been found in subtropical regions of China, inhabiting terrestrial to epiphytic habitats. This study focuses on three species, H. dentata (distributed in Asia), H. yachangensis, and L. gigantea. For H. yachangensis and L. gigantea, there is no information about the mycorrhizal community in these species. This study aims to conduct the fungal community screening of Chinese ground orchids from subtropical regions. We performed a comparative analysis of the fungal community among H. dentata, H. yachangensis, and L. gigantea, determining their ITS regions using NGS paired-end sequences. The results clarified the diversity and the predominance of fungal genera. Ascomycota was abundant compared to Basidiomycota or other fungi groups in all communities, with a high dominance in all populations, especially for L. gigantea. At different root spatial locations, the fungal community diversity and richness were higher in the soil than in the rhizosphere or inner root. However, the results suggest that L. gigantea has a different fungal community compared to Habenaria species. In this order, the subtropical terrestrial orchids have a different fungal network compared to the northern terrestrial orchids. Also, there is a high probability of co-existence and co-evolution of endophytic fungi in these terrestrial orchids, indicating the potential role of host plants in selecting an endophytic fungal community. Furthermore, our results highlight the need to elucidate the microbe interactions of these unique orchids for long-term purposes, such as isolating indigenous fungi for suitable inoculants for further orchid propagation, restoration, and conservation.

Abstract In recent years, it has been seen that artificial intelligence (AI) starts to bring revolutionary changes to chemical synthesis. However, the lack of suitable ways of representing chemical reactions and the scarceness of reaction data has limited the wider application of AI to reaction prediction. Here, we introduce a novel reaction representation, GraphRXN, for reaction prediction. It utilizes a universal graph-based neural network framework to encode chemical reactions by directly taking two-dimension reaction structures as inputs. The GraphRXN model was evaluated by three publically available chemical reaction datasets and gave on-par or superior results compared with other baseline models. To further evaluate the effectiveness of GraphRXN, wet-lab experiments were carried out for the purpose of generating reaction data. GraphRXN model was then built on high-throughput experimentation data and a decent accuracy (R2 of 0.712) was obtained on our in-house data. This highlights that the GraphRXN model can be deployed in an integrated workflow which combines robotics and AI technologies for forward reaction prediction.

Background The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug‐eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. Methods and Results We developed and validated a new AI‐based pipeline using retrospective data of drug‐eluting stent‐treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de‐identified Clinformatics Data Mart Database (n=9978). The 36 months following drug‐eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI‐DAPT model. The AI‐DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%–92%] for ischemia and 84% [95% CI, 82%–87%] for bleeding predictions. Conclusions Our AI‐DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients' clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability.

Background. The activation of complement is involved in monocyte recruitment in tuberculous pleural effusion (TPE), while the role of the cleavage product of complement C3 in this process needs further research. Methods. The expression of complement components in pleural biopsy specimens of TPE patients was measured. The concentration of cleavage products of complement was tested in TPE by ELISA. Moreover, the colocalizations of C3b and CR1, C3d and CR3, and CXCL12 and CXCR4 in monocytes and pleural mesothelial cells (PMCs) isolated from TPE were determined by an immunofluorescent assay. Monocyte chemotaxis assay was analyzed via transwell chambers. Results. Three pathways of the complement system were activated in tuberculous pleurisy. In patients with TPE, C3 lysis was more active than peripheral blood in pleural cavity. Tuberculous protein Mpt64 and anaphylatoxin C3a could significantly promote CXCL12 production in human PMCs isolated from TPE. C3b-CR1, C3d-CR3, and CXCL12-CXCR4 were colocalized in PMCs and monocytes from TPE. The recruitment of monocytes into TPE mediated by PMCs could be inhibited by anti-CR1, anti-CR3, and anti-CXCL12 monoclonal antibodies (mAbs). Conclusions. Complement activates strongly in TPE, and PMCs induced monocytes to the pleural cavity through C3a, C3b, and C3d.

Purpose: To investigate perioperative risk factors that affect the recovery of postoperative gastrointestinal function in patients undergoing gynecological surgery and to establish a preoperative risk prediction scoring system. Methods: In this retrospective cohort study, characteristics and perioperative factors of patients who underwent elective gynecological surgery at Union Hospital from January 2021 to March 2022 were extracted from electronic medical records. Patients were grouped according to the Intake, Feeling nauseated, Emesis, physical Exam, and Duration of symptoms (I-FEED) scoring system to compare collected data. Results: In total, clinical data from 208 gynecological patients were extracted. The incidence of poor postoperative gastrointestinal recovery was 7.21 %. The number of previous abdominal surgeries (0.73 ± 0.06 vs 1.20 ± 0.24, p = 0.044), the incidence of malignant disease (20.2 % vs 53.3 %, p = 0.003), postoperative maximum WBC count (9.15 vs 12.44, p = 0.005) and postoperative minimum potassium (3.97 ± 0.36 vs 3.76 ± 0.37, p = 0.036) were not only associated with poor postoperative gastrointestinal recovery, but also malignant disease (p = 0.000), postoperative maximum WBC count (p = 0.027) and postoperative minimum potassium (p = 0.024) were significantly associated with the severity of postoperative gastrointestinal function. An increased number of previous abdominal surgeries and malignant primary disease could increase the risk of an I-FEED score >2 as independent risk factors. Conclusion: Patients with poor postoperative GI function had poorer postoperative recovery outcomes. A preoperative score prediction system was established, in which patients with ≥2 points had a 19.4 % risk of poor postoperative gastrointestinal recovery. Higher-quality prospective studies should be performed to achieve more precise risk stratification and to construct a more accurate prediction system.

Technology mining (or tech mining, TM) is an emerging research field in science, technology, and innovation studies. However, due to the rapid increase and widespread application of TM research, accurately capturing research topics and emerging developments in TM has become a challenge for scholars. Therefore, this bibliometric literature review combines quantitative methods and content analysis to explore the research foundation and development frontiers of TM and distinguish emerging research topics from relatively mature ones, aiming to deepen the understanding. More specifically, it utilizes co-citation analysis and bibliographic coupling techniques to analyze the TM publication dataset. The results indicate that TM research is mainly based on four foundational areas, and there are five current frontier clusters. Emerging topic detection further shows that technology topic analysis, technology opportunity analysis, and technology management and decision support are currently emerging TM research topics.

Abstract Background and Aims Clear cell renal cell carcinoma (ccRCC) is a common and aggressive form of cancer with a high incidence globally. This study aimed to investigate the role of P2RY13 in the progression of ccRCC and elucidate its mechanism of action. Methods Gene Expression Omnibus and The Cancer Genome Atlas databases were used to extract gene expression profiles of ccRCC. These profiles were annotated and visualized by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses, as well as Gene Set Enrichment Analysis (GSEA). The STRING database was used to establish a protein–protein interaction network and to analyze the functional similarity. The GEPIA2 database was used to predict survival associated with hub genes. Meanwhile, the TIMER2.0 database was used to assess immune cell infiltration and its link with the hub genes. Immunohistochemistry (IHC) was used to determine the difference between ccRCC and adjacent normal tissue. Results We identified 272 differentially expressed genes (DEGs). GO and KEGG analyses suggested that DEGs were primarily involved in lymphocyte activation, inflammatory response, immunological effector mechanism pathways. By cytohubba, the 20 highest‐scoring hub genes were screened to identify critical genes in the protein–protein interaction network linked with ccRCC. Resting dendritic cells, CD8 T cells, and activated mast cells all showed a significant positive correlation with these hub genes. Moreover, a higher immune score was associated with increased prognostic risk scores, which in turn correlated with a poorer prognosis. IHC revealed that P2RY13 was expressed at higher levels in ccRCC compared to para‐cancer tissues. Conclusion Identifying the DEGs will aid in the understanding of the causes and molecular mechanisms involved in ccRCC. P2RY13 may play a pivotal role in the progression and prognosis of ccRCC, potentially driving carcinogenesis though immune system mechanisms.

ABSTRACTEpithelial ovarian cancer (EOC) is the most lethal gynecological cancer, which remains a threat to female health at all ages. Hypotheses for EOC development include the continuous presence of inflammation, in which microbiota and inflammatory cytokines participate in cancer-related signaling pathway activation. Hedgehog (Hh) signaling is prominent for EOC progression, and interacts with inflammation response related to gut microbiota (GM). However, the precise roles of GM during this process are unknown. Here, we showed that the GM from patients with EOC differed from that of healthy women and had GM dysbiosis. We found that EOC modeling may lead to GM changes in mice, and it restored after the administration of GM from healthy controls, while GM from patients with EOC further exacerbated GM dysbiosis. Furthermore, we found that GM from EOC markedly promoted tumor progression and activated Hh signaling; meanwhile, it increased the extent of inflammation and activated NF-κB signaling, but GM from healthy controls improved them. Our results demonstrate how GM dysbiosis promoted EOC progression by activating Hh signaling mediated by TLR4/NF-κB signaling. We anticipate our assay to be a new thought for exploring the role of GM in EOC development. Furthermore, improving GM dysbiosis is a novel therapeutic approach for delaying EOC development.

Abstract Background Although mesenchymal stem cells (MSCs) have been effective in tendinopathy, the mechanisms by which MSCs promote tendon healing have not been fully elucidated. In this study, we tested the hypothesis that MSCs transfer mitochondria to injured tenocytes in vitro and in vivo to protect against Achilles tendinopathy (AT). Methods Bone marrow MSCs and H2O2-injured tenocytes were co-cultured, and mitochondrial transfer was visualized by MitoTracker dye staining. Mitochondrial function, including mitochondrial membrane potential, oxygen consumption rate, and adenosine triphosphate content, was quantified in sorted tenocytes. Tenocyte proliferation, apoptosis, oxidative stress, and inflammation were analyzed. Furthermore, a collagenase type I-induced rat AT model was used to detect mitochondrial transfer in tissues and evaluate Achilles tendon healing. Results MSCs successfully donated healthy mitochondria to in vitro and in vivo damaged tenocytes. Interestingly, mitochondrial transfer was almost completely blocked by co-treatment with cytochalasin B. Transfer of MSC-derived mitochondria decreased apoptosis, promoted proliferation, and restored mitochondrial function in H2O2-induced tenocytes. A decrease in reactive oxygen species and pro-inflammatory cytokine levels (interleukin-6 and -1β) was observed. In vivo, mitochondrial transfer from MSCs improved the expression of tendon-specific markers (scleraxis, tenascin C, and tenomodulin) and decreased the infiltration of inflammatory cells into the tendon. In addition, the fibers of the tendon tissue were neatly arranged and the structure of the tendon was remodeled. Inhibition of mitochondrial transfer by cytochalasin B abrogated the therapeutic efficacy of MSCs in tenocytes and tendon tissues. Conclusions MSCs rescued distressed tenocytes from apoptosis by transferring mitochondria. This provides evidence that mitochondrial transfer is one mechanism by which MSCs exert their therapeutic effects on damaged tenocytes.

Inhalation represents a significant route of cadmium (Cd) exposure, which is associated with an elevated risk of lung diseases. This research study aims to evaluate the impact of repeated low-dose cadmium inhalation on exacerbating airway inflammation induced by ovalbumin (OVA) in asthma-afflicted mice. Mice were grouped into four categories: control (Ctrl), OVA, cadmium chloride (CdCl2), and OVA + cadmium chloride (OVA + CdCl2). Mice in the OVA group displayed increased airway mucus secretion and peribronchial and airway inflammation characterized by eosinophil cell infiltration, along with elevated levels of Th2 cytokines (IL-4, IL-5, IL-13) in bronchoalveolar lavage fluids (BALFs). These parameters were further exacerbated in the OVA + CdCl2 group. Additionally, the OVA + CdCl2 group exhibited higher levels of the oxidative stress marker malondialdehyde (MDA), greater activity of glutathione peroxidase (GSH-Px), and higher phosphorylation of extracellular regulated kinase (ERK) in lung tissue. Treatment with U0126 (an ERK inhibitor) and α-tocopherol (an antioxidant) in the OVA + CdCl2 group resulted in reduced peribronchial and airway inflammation as well as decreased airway mucus secretion. These findings indicate that CdCl2 exacerbates airway inflammation in OVA-induced allergic asthma mice following airway exposure. ERK and oxidative stress are integral to this process, and the inhibition of these pathways significantly alleviates the adverse effects of CdCl2 on asthma exacerbation.

Abstract Background Microbiome analysis generally requires PCR-based or metagenomic shotgun sequencing, sophisticated programs, and large volumes of data. Alternative approaches based on widely available RNA-seq data are constrained because of sequence similarities between the transcriptomes of microbes/viruses and those of the host, compounded by the extreme abundance of host sequences in such libraries. Current approaches are also limited to specific microbial groups. There is a need for alternative methods of microbiome analysis that encompass the entire tree of life. Results We report a method to specifically retrieve non-human sequences in human tissue RNA-seq data. For cellular microbes we used a bioinformatic 'net', based on filtered 64-mer sequences designed from small subunit ribosomal RNA (rRNA) sequences across the Tree of Life (the 'electronic tree of life', eToL), to comprehensively (98%) entrap all non-human rRNA sequences present in the target tissue. Using brain as a model, retrieval of matching reads, re-exclusion of human-related sequences, followed by contig building and species identification, is followed by confirmation of the abundance and identity of the corresponding species groups. We provide methods to automate this analysis. The method reduces the computation time versus metagenomics by a factor of >1000. A variant approach is necessary for viruses. Again, because of significant matches between viral and human sequences, a 'stripping' approach is essential. Contamination during workup is a potential problem, and we discuss strategies to circumvent this issue. To illustrate the versatility of the method we report the use of the eToL methodology to unambiguously identify exogenous microbial and viral sequences in human tissue RNA-seq data across the entire tree of life including Archaea, Bacteria, Chloroplastida, basal Eukaryota, Fungi, and Holozoa/Metazoa, and discuss the technical and bioinformatic challenges involved. Conclusions This generic methodology is likely to find wide application in microbiome analysis including diagnostics.

Resting-state fMRI analysis of patients with obsessive-compulsive disorder (OCD) compared to controls suggests a specific role of amygdala subregions in neurocircuitry models of OCD.

Abstract Background To date, there are no effective treatments for most neurodegenerative diseases. Knowledge graphs can provide comprehensive and semantic representation for heterogeneous data, and have been successfully leveraged in many biomedical applications including drug repurposing. Our objective is to construct a knowledge graph from literature to study the relations between Alzheimer’s disease (AD) and chemicals, drugs and dietary supplements in order to identify opportunities to prevent or delay neurodegenerative progression. We collected biomedical annotations and extracted their relations using SemRep via SemMedDB. We used both a BERT-based classifier and rule-based methods during data preprocessing to exclude noise while preserving most AD-related semantic triples. The 1,672,110 filtered triples were used to train with knowledge graph completion algorithms (i.e., TransE, DistMult, and ComplEx) to predict candidates that might be helpful for AD treatment or prevention. Results Among three knowledge graph completion models, TransE outperformed the other two (MR = 10.53, Hits@1 = 0.28). We leveraged the time-slicing technique to further evaluate the prediction results. We found supporting evidence for most highly ranked candidates predicted by our model which indicates that our approach can inform reliable new knowledge. Conclusion This paper shows that our graph mining model can predict reliable new relationships between AD and other entities (i.e., dietary supplements, chemicals, and drugs). The knowledge graph constructed can facilitate data-driven knowledge discoveries and the generation of novel hypotheses.

The [Fe, Al]-FER zeolites, which are prepared from the interzeolite conversion method (from MWW to FER topology) with high Al and Fe content (Si/Al of 8–18 and Si/Fe of 11–13), exhibit excellent catalytic performances and hydrothermal tolerance for NH3-SCR reaction. The interzeolite conversion process can be tuned by optimizing the zeolite synthesis conditions such as synthesis gel composition, crystallization time, crystallization temperature, and adding MWW seeds. The work can provide a new strategy to synthesize high Al and Fe content zeolite with high hydrothermal stability for NOx removal.

This study examined the impact of cognitive style congruence between leaders and followers on followers' organizational citizenship behaviors (OCBs) by integrating the similarity-attraction and signaling theories. We collected dyadic data from 80 leaders and 223 followers in ten manufacturing companies in China. Using polynomial regression analysis and response surface modeling, the study supported the positive influence of cognitive style congruence on followers' OCBs. Specifically, we found that dyads with more intuitive than analytical leader-follower cognitive styles had higher levels of OCBs. However, there were no significant differences in followers' OCBs between dyads consisting of an intuitive leader and an analytic follower versus those consisting of an analytic leader and an intuitive follower under conditions of cognitive style incongruence. Additionally, the study found that interpersonal trust mediated the relationship between leader-follower cognitive style congruence and followers' OCBs, offering valuable insights for promoting OCBs in the workplace.

The glutens obtained from ten different wheat cultivars were employed as materials, and the hydration properties (water and oil holding capacity), and surface properties (foaming ability and foaming stability, emulsifying capacity) of gluten were investigated. Subsequently, available sulfhydryl group, disulfide bond, and secondary structure of gluten were analyzed. The results indicated that the functional properties of gluten were different among cultivars. Both of the water-holding capacity and oil-holding capacity of gluten from high-strength wheat flour were significantly higher than those from low and medium-strength wheat flour (P

BackgroundInsomnia is a commonly seen symptom in adolescents with major depressive disorder (MDD). The suprachiasmatic nucleus (SCN), which is the circadian rhythm regulation center, plays a crucial role in the regulation of sleep-wake circulation. Nevertheless, how SCN function contributes to the exact neural mechanisms underlying the associations between insomnia and depressive symptoms has not been explored in adolescents. In the current study, we aimed to explore the relationship between SCN functional connectivity (FC) and insomnia symptoms in adolescents with MDD using a seed-based FC method.MethodsIn the current study, we recruited sixty-eight first-episode drug-naïve adolescents with MDD and classified them into high insomnia (MDD-HI) and low insomnia (MDD-LI) groups according to the sleep disturbance subscale of the Hamilton Depression Rating Scale (HAMD-S). Forty-three age/gender-matched healthy controls (HCs) were also recruited. SCN FC maps were generally for all subjects and compared among three groups using one-way ANOVA with age, gender and adjusted HAMD score as covariates. We used partial correlations to explore associations between altered FC and clinical symptoms, including sleep quality scores.ResultsAdolescents with MDD showed worse sleep quality, which positively correlated with the severity of depression. Compared to MDD-LI and HCs, MDD-HI adolescents demonstrated significantly decreased FC between the right SCN and bilateral precuneus, and there was no significant difference between the MDD-LI and HC groups. The HAMD-S scores were negatively correlated with bilateral SCN-precuneus connectivity, and the retardation factor score of HAMD was negatively correlated with right SCN-precuneus connectivity.ConclusionThe altered FC between the SCN and precuneus may underline the neural mechanism of sleep-related symptoms in depressive adolescents and provide potential targets for personalized treatment strategies.

ABSTRACT: Libido can affect the semen quality of male, and the sperm motility in semen quality parameters is a reliable index to evaluate the fertility of male. In drakes, the sperm motility is gradually acquired in testis, epididymis, and spermaduct. However, the relationship between libido and sperm motility in drakes has not been reported and the mechanisms of testis, epididymis, and spermaduct regulating the sperm motility of drakes are unclear. Therefore, the purpose of the present study was to compare the semen quality of drakes with libido level 4 (LL4) and libido level 5 (LL5), and tried to identify the mechanisms regulating the sperm motility in drakes by performing RNA-seq in testis, epididymis, and spermaduct. Phenotypically, the sperm motility of drakes (P < 0.01), weight of testis (P < 0.05), and organ index of epididymis (P < 0.05) in the LL5 group were significantly better than those in LL4 group. Moreover, compared with the LL4 group, the ductal square of seminiferous tubule (ST) in testis was significantly bigger in the LL5 group (P < 0.05), and the seminiferous epithelial thickness (P < 0.01) of ST in testis and lumenal diameter (P < 0.05) of ductuli conjugentes/dutus epididymidis in epididymis were significantly longer in the LL5 group. In transcriptional regulation, in addition to KEGG pathways related to metabolism and oxidative phosphorylation, lots of KEGG pathways associated with immunity, proliferation, and signaling were also significantly enriched in testis, epididymis, and spermaduct, respectively. Furthermore, through the integrated analysis of coexpression network and protein–protein interaction network, 3 genes (including COL11A1, COL14A1, and C3AR1) involved in protein digestion and absorption pathway and Staphylococcus aureus infection pathway were identified in testis, 2 genes (including BUB1B and ESPL1) involved in cell cycle pathway were identified in epididymis, and 13 genes (including DNAH1, DNAH3, DNAH7, DNAH10, DNAH12, DNAI1, DNAI2, DNALI1, NTF3, ITGA1, TLR2, RELN, and PAK1) involved in Huntington disease pathway and PI3K-Akt signaling pathway were identified in spermaduct. These genes could play crucial roles in the sperm motility of drakes with different libido, and all data the present study obtained will provide new insights into the molecular mechanisms regulating sperm motility of drakes.

Flours obtained from 12 different wheat cultivars were employed as materials, the characteristics of protein, the farinographic and tensile properties of wheat flour were measured. Simultaneously, the quality of crusts from deep-fried and battered pork slices (CDBPS) containing wheat flour was explored. Subsequently, the correlations between properties of different wheat flour and quality of CDBPS were analyzed. Result indicated that, the contents of protein and its main fraction in wheat flour were significantly different among different test cultivars. The coefficient of variation of total protein and wet gluten content was 15.14% and 16.56%, respectively, while that of globulin reached 62.81%. The variation coefficients of formation time, dough stability time, weakening degree and farinogram quality number were much larger, and those of each index of extensograph properties was more than 20%. Significantly negative correlations were observed between oil content of CDBPS and total content of protein, gluten index, content of gliadin, water absorption, tensile curve area, tensile resistance, and extensibility (r=−0.739, −0.833, −0.833, −0.797, −0.736, −0.709 and −0.722, respectively, P

Abstract Background Monocytes are involved in tumor growth and metastasis, but the distribution of monocyte phenotypes and their role in the development of malignant pleural effusion (MPE) remains unknown. Methods A total of 94 MPE patients (76 diagnosed with adenocarcinoma lung cancer and 18 with squamous cell lung cancer) and 102 volunteers for health examination in Xiangya Hospital from December 2016 to December 2019 were included in the study. Results The distribution of monocyte subtypes identified by the expression of CD14 and CD16 were analyzed by flow cytometry. The proportion of CD14++CD16+ intermediate monocytes were significantly increased in pleural effusion of MPE patients. The complement system components were assayed by immunohistochemistry and ELISA, and higher expression of the classical and alternative pathways were detected in malignant pleural tissue. Transwell assay further revealed that C5a enhanced the infiltration of intermediate monocytes into the pleural cavity by promoting CCL2 production in pleural mesothelial cells (PMCs). In addition, C5a promoted the secretion of IL‐1β by intermediate monocytes. Furthermore, C5a activated in intermediate monocytes and IL‐1β released after C5a stimulation by monocytes promoted the proliferation, migration, adhesion, and epithelial‐to‐mesenchymal transition (EMT) of tumor cells, and attenuated tumor cell apoptosis. Conclusions C5a, activated by the classical and alternative pathways of the complement system, not only mediated the infiltration of intermediate monocytes by enhancing CCL2 production in PMCs but also induced IL‐1β release from the recruited monocytes in MPE. The consequence of C5a activation and the subsequent IL‐1β overexpression in intermediate monocytes contributed to MPE progression.

This experiment was conducted to investigate whether low-dose zinc-loaded montmorillonite (Zn-MMT) could be used as a potential alternative for high-dose conventional ZnO in preventing diarrhea in weaned piglets. In total, 180 piglets were randomly divided to receive either of the three treatments, with six replicates per treatment and 10 piglets per replicate. The treatments were the control group (CT), the Zn-MMT group (ZM), and the ZnO group (ZO). Compared with the CT group, the ZM and ZO groups exhibited increased ADG at 14–28 days and during the whole period (p < 0.05), and a significantly decreased diarrhea rate during the whole period (p < 0.01). The activities of T-AOC and SOD were significantly increased (p < 0.05), whereas the MDA level decreased (p < 0.05) in the serum and colonic mucosa of Zn-MMT- and ZnO-fed piglets. Dietary supplementation with Zn-MMT and ZnO decreased the contents of IFN-γ, TNF-α, IL-1β, IL-6, DAO, and LPS in the serum and colonic mucosa (p < 0.01), and increased the IL-10 level (p < 0.01). The relative mRNA expressions of TLR-4, claudin 2, Pbd1, and MUC2 were elevated in the colonic mucosa of the Zn-MMT and ZnO groups (p < 0.05). 16S rRNA gene sequencing analysis revealed that the abundances of Proteobacteria and Actinobacteria in the ileum and the populations of Ruminnococcus and Faecalibacterium in the cecum were higher in the CT group than in the other two groups. Collectively, dietary addition of Zn from Zn-MMT was comparable to Zn from ZnO for increasing growth performance, alleviating diarrhea, as well as improving mucosal barrier integrity, and regulating the gut microbiota of weaned piglets.

The gut microbiota plays a crucial role in the human microenvironment. Dysbiosis of the gut microbiota is a common pathophysiological phenomenon in critically ill patients. Therefore, utilizing intestinal microbiota to prevent complications and improve the prognosis of critically ill patients is a possible therapeutic direction. The gut microbiome-based therapeutics approach focuses on improving intestinal microbiota homeostasis by modulating its diversity, or treating critical illness by altering the metabolites of intestinal microbiota. There is growing evidence that fecal microbiota transplantation (FMT), selective digestive decontamination (SDD), and microbiota-derived therapies are all effective treatments for critical illness. However, different treatments are appropriate for different conditions, and more evidence is needed to support the selection of optimal gut microbiota-related treatments for different diseases. This narrative review summarizes the curative effects and limitations of microbiome-based therapeutics in different critically ill adult patients, aiming to provide possible directions for gut microbiome-based therapeutics for critically ill patients such as ventilator-associated pneumonia, sepsis, acute respiratory distress syndrome, and COVID-19, etc.

Background and aimsComplement activation is essential for tuberculosis pleural effusion. However, little is known about the value of complement regulatory protein (CD46, CD55, and CD59) in the differential diagnosis of tuberculosis.Materials and methodsNinety-nine patients with exudative pleural effusion admitted to Xiangya Hospital of Central South University from June 1, 2021to November 14, 2022 were enrolled. The expression levels of soluble CD46 (sCD46), soluble CD55 (sCD55), and soluble CD59 (sCD59) in pleural effusion were quantified by enzyme-linked immunosorbent assay, and the receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic and co-diagnostic values.ResultsThe ADA level is higher in TPE patients than non-TPE patients. It is well-found that TPE patients had lower levels of sCD46, sCD55, and sCD59 compared with non-TPE patients. Moreover, the expression of sCD46, sCD55, and sCD59 in pleural effusion was negatively correlated with ADA. In addition, the diagnostic efficacy of sCD46, sCD55 and sCD59 was comparable to that of ADA, with 0.896, 0.857, 0.858 and 0.893, respectively. Furthermore, combine detection of sCD46, sCD55, sCD59 and ADA could improve the diagnostic accuracy.ConclusionsComplement regulatory factors (CD46, CD55, and CD59) were validated by this project to be promising candidate biomarkers for the diagnosis of TPE with high accuracy. The combination of the CD46, CD55, and CD59 and ADA assay exist a better diagnostic value in TPE.

ABSTRACT: Evidences have found important effects of breeds/strains on the content of amino acids (AAs) which is an important substrate for protein synthesis and contributes greatly to meat quality. Therefore, the objective of the present study was to compare the AAs content and protein synthesis-related genes expression levels in breast muscle of native breed (Jianchang duck (J)), hybrid strains (BH1, BH2, and MC♂ × (BGF2♂ × GF2♀)♀ (MC)), and commercial breed (Cherry Verry duck). Results showed that a total of 17 AAs (TAAs) was detected from breast muscle among 5 duck breeds/strains including 11 essential AAs (EAAs). Among these AAs, the contents of Proline, Threonine, Glutamine, Serine, Methionine, Phenylalanine, Histidine, and Cysteine were significant difference among 5 duck breeds/strains. The contents of EAAs, TAAs, and flavor AAs were higher in breast muscle of J and BH2 than those in other duck breeds/strains, and the ratio of EAAs/TAAs was higher in breast muscle of BH2. Furthermore, the expression levels of eukaryotic translation initiation factor 4E-binding protein 1, mammalian target of rapamycin, and proton-coupled amino acid transporter 1 were the highest in breast muscle of BH2, and that of solute carrier family 38 member 2 was the highest in breast muscle of J. Meanwhile, principal component analysis results showed that principal component 1 of BH1, principal component 3 of BH2, and principal component 2 of MC were positively corelated with EAAs/TAAs, and principal component 1 was positively correlated with flavor AAs and EAAs. In conclusion, compared to BH1, MC, and Cherry Verry duck, AA content was higher in breast muscle of BH2 and J, which might be associated with the higher expression levels of mammalian target of rapamycin, eukaryotic translation initiation factor 4E-binding protein 1, and proton-coupled amino acid transporter 1 in breast muscle of BH2 and solute carrier family 38 member 2 in breast muscle of J. The comparative analysis of AA content in breast muscle among different duck breeds/strains could provide an important basis for improving the nutritional value of duck meat in the breeding process.

There is an increasing contradiction between humanity’s growing demand for natural resources and relatively limited supplements. Thus, ecological security has received widespread attention, making it a research hotspot in the global environment and an important topic in construction of ecological civilization. Ebinur Lake Wetland is a typical arid wetland area considered as a fragile and sensitive ecosystem. Quantitative monitoring of the ecological security and landscape patterns of the Ebinur Lake wetland ecosystem is of great significance for environmental protection. To clarify the relationship between ecological landscape indices and land use/cover, this study used Landsat TM/OLI data from 1990, 1998, 2011 and 2021, aimed to analyze the correlated spatio-temporal changes of Ebinur Lake Wetland Reserve, China over past 32 years, in addition to quantitatively evaluating changes in ecological security. The results showed that(1) During 1990–1998, forest and paddy areas increased, while the transformation between paddy fields and wetlands was frequent, and from 1998 to 2011, land use/land cover (LULC) changes gradually stabilized, vegetation recovery was halted, and the water area obviously decreased. Since 2012, Ebinur Lake area decreased by −3.88 % per year, while 44.8 km2 of the subsoils became extremely severe salinized. (2) The variability of ecological landscape in spatial structure and time dynamics is enhanced, landscape scalability declined, resulting in the intensification of fragmentation. CONTAG (Contagion index) decreased annually with the decline in Gobi area; whereas landscape diversity of wetlands increased with growing light and heavy saline-alkali areas. (3) Overall ecological security gradually increased from 0.56 to 0.65, and the unsafe areas first decreased, before increasing slightly. The total saline-alkaline land area continued to increase, indicating that desertification cannot be curbed. Ecological security had the highest sensitivity to landscape separation, and the value range and its safety levels of ecological security (ES) were accurately delimited based on uncertainty calculation and frequency statistics. The results can provide reasonable and practical suggestions for the government and local communities on how to strengthen the ecological environment construction of Ebinur Lake Wetland Reserve. The government should several water-saving measures, in addition to an inter-basin water transfer project can be implemented to help diminish the consequences of insufficient water resources, and planting salt-absorbing vegetation to slow the salinization process.

Semen quality is the most important indicator in evaluating drake fecundity. At present, the low semen quality has become a major factor restricting the development of artificial insemination (AI) technology in ducks. Numerous studies have indicated that seminal plasma proteins play a crucial role in semen quality, but the mechanism of seminal plasma proteins regulating semen quality of drakes remains unclear. Thus, the objective of this study was to identify seminal plasma proteins associated with semen quality by comparing the seminal plasma proteomic profile of drakes with high-quality semen (HQS) and low-quality semen (LQS). Using a label-free MS-based method, a total of 745 seminal plasma proteins were identified. Of these, 55 differentially expressed proteins (DEPs) were identified (40 up-regulated and 15 down-regulated). Gene Ontology (GO) analysis showed that the DEPs were mainly enriched in transmembrane transport, extracellular matrix structural constituent, transferase activity, transferring acyl groups other than amino-acyl groups, transmembrane transporter activity, and integral component of membrane (P < 0.05). Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis indicated that the DEPs were significantly enriched in apoptosis, tyrosine metabolism, glycerophospholipid metabolism, and sulfur metabolism pathways (P < 0.05). Moreover, through protein-protein interaction (PPI) network analysis, eight potential candidate proteins were identified, including P19140 (Alpha-enolase), R0KUV7 (Calreticulin), R0K3X3 (Solute carrier family 2, facilitated glucose transporter member 5), R0L6V0 (Proteasome subunit beta), R0JKW0 (Cytochrome c), R0JMC5 (Tubulin alpha chain), R0LCK1 (Cathepsin C), and R0JUP6 (Cathepsin D), which could play crucial roles in semen quality. Notably, further analysis demonstrated that key protein P19140 (Alpha-enolase) might can control the semen quality of drakes by regulating the expression of proteins related to apoptosis pathway. This study is the first systematically comparing the seminal plasma proteome of drakes exhibiting high and low semen quality. These results provide novel insights into the mechanisms regulating semen quality of drakes.

BackgroundMethamphetamine (METH) use induces neurotoxic effects in brain structures and affective symptoms that persist during abstinence. However, the brain morphometry of individuals with METH use disorder (MUD) remains unclear, as well as their associations with affective symptoms during abstinence.MethodsForty-eight abstinent males with MUD and 66 age-, sex-, and education-matched healthy controls (HCs) underwent high-resolution T1-weighted magnetic resonance imaging. Cortical thickness, surface area, volume, local gyrification index (LGI), and subcortical volume were obtained with FreeSurfer software. Brain morphometry differences between groups and their associations with affective symptoms and drug abuse history within the males with MUD were examined, with intracranial volume, age, and years of education as covariates.ResultsCompared with the HCs, the individuals with MUD showed a significantly higher LGI in the right cuneus gyrus, left lingual gyrus, bilateral supramarginal gyrus, right inferior parietal gyrus (IPG), and right dorsal anterior cingulate cortex (clusterwise p < 0.05, Monte Carlo-corrected), as well as a smaller volume of the left nucleus accumbens (NAcc) (p < 0.05, FDR-corrected). However, there were no significant group differences in cortical thickness, area or volume. In addition, the LGI in the right IPG was positively associatedwith the severity of depression and anxiety symptoms in MUDs (p < 0.05, FDR-corrected).ConclusionBrain morphometric abnormalities in abstinent males with MUD were characterized by hypergyrification across multiple mid-posterior brain regions anda smaller volume of the left NAcc.Gyrification of the right IPG may be a potential neural substrate underlying the affective symptoms experienced by MUDs during abstinence.

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.

Background: Osteoarthritis (OA) has placed a heavy burden to the economy and humanistics. To explore the biological functions and markers of chondrocytes contributes significantly to the accurate diagnosis and targeted treatment of OA.Methods: We systematically analyzed the immunogenicity and biological function of varied chondrocytes at single cell resolution, and identified the chondrocyte subtypes and biomarkers involved in the development of OA, which are verified in the bulk sequencing cohort.Results: Based on previous study, we defined eight subtypes of chondrocytes with different biological functions, finding out that effector chondrocytes (ECs) and fibrocartilage chondrocytes (FCs) may promote the development of OA. Compared with other chondrocytes, ECs and FCs show stronger immunogenicity. FCs mainly affects the degeneration of cartilage caused by fibrous degeneration, while ECs mainly exerts immune function and causes tissues inflammation. In addition, the canonical gene markers of EC and FC assist with the prediction of OA, which has been verified in Bulk RNA sequencing data from two GEO datasets.Conclusion: In summary, this study provides a new perspective for the exploration of cellular heterogeneity and pathophysiology in OA and will make contribution to the accurate diagnosis and targeted treatment of OA.

For a quadrotor unmanned aerial vehicle (UAV), this paper proposes an adaptive sliding mode control (SMC) strategy enhanced with a disturbance observer to attain precise trajectory and attitude tracking performance while compensating for the detrimental impacts of actuator faults and disturbances. First, an adaptive SMC strategy that utilizes an integral sliding surface is presented to enhance the fault-tolerance capabilities of the studied quadrotor UAV against actuator faults. In addition, a disturbance observer is further created to compensate for the disturbances. By integrating the proposed adaptive SMC strategy with the designed disturbance observer, both actuator faults and disturbances can be effectively accommodated. It was theoretically demonstrated that the system is stable while using the proposed adaptive fault-tolerant control strategy. The effectiveness and benefits of the proposed strategy is verified with comparative simulation results under different faulty scenarios.

Wastewater collection systems (WCSs) not only play an indispensable role in urban life but also significantly contribute to greenhouse gas (GHG) emissions. Based on extensive literature research, this study (1) summarizes current research on the production mechanisms, influencing factors, control techniques, and quantitative estimates of GHGs emitted from WCSs and (2) presents initial estimates of total GHG emissions from WCSs in China. A variety of factors affect GHG production, but standard methods are still lacking to quantify GHG emissions from WCSs. China’s WCSs emit approximately 3.86–15.35 Mt of CO2eq annually (equivalent to 5.1–20.2% of the GHG emissions from wastewater treatment). Thus, GHG emissions from WCSs are significant and deserve attention. Control of GHGs in WCSs can be achieved through the application of chemical agents, while the construction of a green stormwater infrastructure can further facilitate GHG reductions. This review provides valuable insights for policymakers to consider in future policy planning related to GHG reduction and the improved operation of WCSs. Future research should focus on quantifying the impacts of various factors and accumulating field data on GHGs in various regions to facilitate the development of standardized calculation methods.

Abstract Background Effector memory T cells are pivotal effectors of adaptive immunity with enhanced migration characteristics and are involved in the pathogenesis of ANCA-associated vasculitis (AAV). The diversity of effector memory T cells in chemokine receptor expression has been well studied in proteinase 3 (PR3)-AAV. However, few studies have been conducted in myeloperoxidase (MPO)-AAV. Here, we characterized chemokine receptor expression on effector memory T cells from patients with active MPO-AAV. Methods Clinical data from newly diagnosed MPO-AAV patients and healthy subjects were collected and analyzed. Human peripheral blood mononuclear cells (PBMCs) isolated from patients with active MPO-AAV were analyzed by flow cytometry. The production of effector memory T cell-related chemokines in serum was assessed by ELISA. Results We observed decreased percentages of CD4+ and CD8+ T cells in the peripheral blood, accompanied by a significant decrease in CCR6-expressing T cells but an increase in CXCR3+ T cells, in active MPO-AAV. Furthermore, the decrease in CCR6 and increase in CXCR3 expression were mainly limited to effector memory T cells. Consistent with this finding, the serum level of CCL20 was increased. In addition, a decreasing trend in the TEM17 cell frequency, with concomitant increases in the frequencies of CD4+ TEM1 and CD4+ TEM17.1 cells, was observed when T cell functional subsets were defined by chemokine receptor expression. Moreover, the proportions of peripheral CD8+ T cells and CD4+ TEM subsets were correlated with renal prognosis and inflammatory markers. Conclusions Our data indicate that dysregulated chemokine receptor expression on CD4+ and CD8+ effector memory T cells and aberrant distribution of functional CD4+ T cell subsets in patients with active MPO-AAV have critical roles related to kidney survival.