Effects of Dietary Ursolic Acid on Growth Performance and Intestinal Health of Largemouth Bass (Micropterus salmoides).

This study aimed to investigate the effects of ursolic acid (UA) on the growth performance and intestinal health of largemouth bass (Micropterus salmoides). Four diets were formulated with UA supplementation at 0, 250, 500, and 1000 mg/kg, defined as the control (CON), UA250, UA500, and UA1000, respectively. After an 8-week feeding experiment, the results showed that, in the UA500 group, the final body weight (FBW), weight gain rate (WGR), and specific growth rate (SGR) increased, and the feed conversion ratio (FCR) and hepatosomatic index decreased. Total superoxide dismutase (T-SOD) activity exhibited a significant increase, and malondialdehyde (MDA) content decreased. An intestinal histological analysis revealed an improvement in the intestinal structural integrity of the UA500 group. The mRNA relative expression levels of physical barrier-related genes [occludin, claudin-1, and zonula occluden-1 (zo-1)] were upregulated. The mRNA relative expression of interlenkin 10 (il-10) increased, and the mRNA relative expression of interlenkin 1ß (il-1ß) and tumor necrosis factor-α (tnf-α) significantly decreased. The abundance of Firmicutes and Proteobacteria decreased, and the abundance of Tenericutes increased. The abundance of Mycoplasma, Cyanobium, and Staphylococcus decreased, while the abundance of Clostridium increased. In conclusion, dietary supplementation of UA significantly enhanced the growth performance and antioxidant capacity of largemouth bass while improving intestinal barrier function through its influence on the abundance of intestinal flora, such as Tenericutes, Firmicutes, and Mycoplasma. Optimal dietary UA levels for largemouth bass were determined to be between 498 and 520 mg/kg based on quadratic regression analyses of WGR, SGR, and FCR or T-SOD and MDA content.

A Bibliometric Analysis of Metabolic Reprogramming in the Tumor Microenvironment From 2003 to 2022.

BACKGROUND: Despite considerable progress in cancer immunotherapy, it is not available for many patients. Resistance to immune checkpoint blockers arises from the intricate interactions between cancer and its microenvironment. Metabolic reprogramming in tumor and immune cells in the tumor microenvironment (TME) influences anti-tumor immune responses by remodeling the immune microenvironment. Metabolic reprogramming has emerged as an important hallmark of tumorigenesis. However, few studies have focused on the TME and metabolic reprogramming. Therefore, we aimed to explore the current research status and popular topics in TME-related metabolic reprogramming over a 20 years using a bibliometric approach. METHODS: Studies focusing on metabolic reprogramming and TME were searched using the Web of Science Core Collection database. Bibliometric and visual analyses of the articles and reviews were performed using Bibliometrix, VOSviewer, and CiteSpace. RESULTS: In total, 4726 articles published between 2003 and 2022 were selected. The number of publications and citations has increased annually. Cooperation network analysis indicated that the United States holds the foremost position in metabolic reprogramming and TME research with the highest volume of publications and citations, thus exerting the greatest influence. Among these institutions, Fudan University displayed the highest level of productivity. Frontiers in Immunology showed the highest degree of productivity in this field. Ho Ping-Chih made the most article contributions, and Pearce Edward J. was the most co-cited author. Four clusters were obtained after a cluster analysis of the authors' keywords: TME, metabolic reprogramming, immunometabolism, and immunity. Immunometabolism, glycolysis, immune cells, and tumor-associated macrophages are relatively recent keywords that have attracted increasing attention. CONCLUSIONS: A comprehensive landscape of advancements in metabolic reprogramming and the TME was evaluated, which provided crucial information for scholars to further advance this promising field. Further research should explore new topics related to immunometabolism in the TME using a transdisciplinary approach.

Endoplasmic Reticulum Stress Promotes Telomerase Reverse Transcriptase Expression Contributes to Development of Allergic Rhinitis.

BACKGROUND: The Th2 cell polarization is a crucial factor in the pathogenesis of allergic diseases. The underlying mechanism requires further investigation. Telomerase has an immune-regulating ability. The aim of this study is to elucidate the association between telomerase and Th2 cell polarization in patients with allergic rhinitis (AR). METHODS: CD4+ T cells were isolated from blood samples collected from AR patients and healthy control subjects. RNA sequencing was employed to analyze RNA samples extracted from CD4+ T cells. An AR mouse model was established using the ovalbumin-alum protocol. RESULTS: High telomerase gene activity and high endoplasmic reticulum (ER) stress status were observed in CD4+ T-cells in patients with AR. Positive correlation between the telomerase reverse transcriptase (TERT) gene expression in CD4+ T cells and AR response in patients with AR. TERT facilitated the degradation of Foxp3 proteins in CD4+ T cells, resulting in the polarization of Th2 cells. Sensitization with the ovalbumin-alum protocol enhanced the Tert expression in CD4+ T cells by exacerbating ER stress. Conditional inhibition of the Tert or eukaryotic translation initiation factor 2-α (Eif2a) expression in CD4+ T cells effectively attenuated experimental AR in mice. CONCLUSIONS: Elevated amounts of telomerase in CD4+ T cells were found in CD4+ T cells of subjects with AR. Telomerase promoted Th2 cell polarization by inducing Foxp3 protein degradation and promotes GATA3 activation. Inhibition of TERT or eIF2a alleviated experimental AR.

Pathogenicity of Duck Adenovirus Type 3 in Chickens.

Duck adenovirus Type 3 (DAdV-3) severely affects the health of ducks; however, its pathogenicity in chickens remains unknown. The objectives of this study were to evaluate the pathogenicity and major pathological changes caused by DAdV-3 in chickens. Viral DNA was extracted from the liver of the Muscovy duck, and the fiber-2 and hexon fragments of DAdV-3 were amplified through polymerase chain reaction (PCR). The evolutionary tree revealed that the isolated virus belonged to DAdV-3, and it was named HE-AN-2022. The mortality rate of chicks that received inoculation with DAdV-3 subcutaneously via the neck was 100%, while the mortality rate for eye-nose drop inoculation was correlated with the numbers of infection, with 26.7% of chicks dying as a result of exposure to multiple infections. The main symptoms exhibited prior to death were hepatitis-hydropericardium syndrome (HHS), ulceration of the glandular stomach, and a swollen bursa with petechial hemorrhages. A histopathological examination revealed swelling, necrosis, lymphocyte infiltration, and basophilic inclusion bodies in multiple organs. Meanwhile, the results of quantitative real-time PCR (qPCR) demonstrated that DAdV-3 could affect most of the organs in chickens, with the gizzard, glandular stomach, bursa, spleen, and liver being the most susceptible to infection. The surviving chicks had extremely high antibody levels. After the chickens were infected with DAdV-3 derived from Muscovy ducks, no amino acid mutation was observed in the major mutation regions of the virus, which were ORF19B, ORF66, and ORF67. On the basis of our findings, we concluded that DAdV-3 infection is possible in chickens, and that it causes classic HHS with ulceration of the glandular stomach and a swollen bursa with petechial hemorrhages, leading to high mortality in chickens. The major variation domains did not change in Muscovy ducks or in chickens after infection. This is the first study to report DAdV-3 in chickens, providing a new basis for preventing and controlling this virus.

A Sheep Identification Method Based on Three-Dimensional Sheep Face Reconstruction and Feature Point Matching.

As the sheep industry rapidly moves towards modernization, digitization, and intelligence, there is a need to build breeding farms integrated with big data. By collecting individual information on sheep, precision breeding can be conducted to improve breeding efficiency, reduce costs, and promote healthy breeding practices. In this context, the accurate identification of individual sheep is essential for establishing digitized sheep farms and precision animal husbandry. Currently, scholars utilize deep learning technology to construct recognition models, learning the biological features of sheep faces to achieve accurate identification. However, existing research methods are limited to pattern recognition at the image level, leading to a lack of diversity in recognition methods. Therefore, this study focuses on the small-tailed Han sheep and develops a sheep face recognition method based on three-dimensional reconstruction technology and feature point matching, aiming to enrich the theoretical research of sheep face recognition technology. The specific recognition approach is as follows: full-angle sheep face images of experimental sheep are collected, and corresponding three-dimensional sheep face models are generated using three-dimensional reconstruction technology, further obtaining three-dimensional sheep face images from three different perspectives. Additionally, this study developed a sheep face orientation recognition algorithm called the sheep face orientation recognition algorithm (SFORA). The SFORA incorporates the ECA mechanism to further enhance recognition performance. Ultimately, the SFORA has a model size of only 5.3 MB, with accuracy and F1 score reaching 99.6% and 99.5%, respectively. During the recognition task, the SFORA is first used for sheep face orientation recognition, followed by matching the recognition image with the corresponding three-dimensional sheep face image based on the established SuperGlue feature-matching algorithm, ultimately outputting the recognition result. Experimental results indicate that when the confidence threshold is set to 0.4, SuperGlue achieves the best matching performance, with matching accuracies for the front, left, and right faces reaching 96.0%, 94.2%, and 96.3%, respectively. This study enriches the theoretical research on sheep face recognition technology and provides technical support.

Nuclear quantum memory for hard x-ray photon wave packets.

Optical quantum memories are key elements in modern quantum technologies to reliably store and retrieve quantum information. At present, they are conceptually limited to the optical wavelength regime. Recent advancements in x-ray quantum optics render an extension of optical quantum memory protocols to ultrashort wavelengths possible, thereby establishing quantum photonics at x-ray energies. Here, we introduce an x-ray quantum memory protocol that utilizes mechanically driven nuclear resonant 57Fe absorbers to form a comb structure in the nuclear absorption spectrum by using the Doppler effect. This room-temperature nuclear frequency comb enables us to control the waveform of x-ray photon wave packets to a high level of accuracy and fidelity using solely mechanical motions. This tunable, robust, and highly flexible system offers a versatile platform for a compact solid-state quantum memory at room temperature for hard x-rays.

Nemo mRNA vaccination improves airway barrier function in mice with airway allergy.

Epithelial barrier dysfunction plays an important role in the pathogenesis of Th2 bias. The mechanism requires further clarification. NEMO is associated with regulating apoptotic activities in the cell. The purpose of this study is to investigate the role of insufficient Nemo signals in developing Th2 bias in the respiratory tract. Nemof/fEpcam-Cre mice (A mouse strain carrying NEMO-deficient epithelial cells. NemoKO mice, in short) was generated. An airway Th2 bias mouse model was established with the ovalbumin/alum protocol. The NemoKO mice exhibited spontaneous airway Th2 bias. Respiratory tract epithelial barrier integrity was compromised in NemoKO mice. Apoptosis was found in approximately 10% of the epithelial cells of the respiratory tract in NemoKO mice. The reconstruction of the Nemo expression restored homeostasis within the epithelial barrier of the airways. Restoration of Nemo gene expression in epithelial cells by Nemo mRNA vaccination alleviated Th2 bias in mice with airway allergy. To sum up, NEMO plays an important role in maintaining the integrity of the epithelial barrier in the respiratory tract. Administration of NEMO mRNA vaccines can restore epithelial barrier functions and alleviate Th2 bias in the airways.

A fluid-structure interaction simulation on the impact of transcatheter micro ventricular assist devices on aortic valves.

BACKGROUND AND OBJECTIVE: The implantation of ventricular assist devices (VADs) has become an important treatment option for patients with heart failure. Aortic valve insufficiency is a common complication caused by VADs implantation. Currently, there is very little quantitative research on the effects of transcatheter micro VADs or the intervention pumps on the aortic valves. METHODS: In this study, the multi-component arbitrary Lagrange-Eulerian method is used to perform fluid-structure interaction simulations of the aortic valve model with and without intervention pumps. The effects of intervention pumps implantation on the opening area of the aortic valves, the stress distribution, and the flow characteristics are quantitatively analyzed. Statistical results are consistent with clinical guidelines and experiments. RESULTS: The implantation of intervention pumps leads to the valve insufficiency and causes weak valve regurgitation. In the short-term treatment, the valve regurgitation is within a controllable range. The distribution and variation of stress on the leaflets are also affected by intervention pumps. The whirling flow in the flow direction affects the closing speed of the aortic valves and optimizes the stress distribution of the valves. In the models with whirling flow, the effects of intervention pumps implantation on valve motion and stress distribution differ from those without whirling flow. However, the valve insufficiency and valve regurgitation caused by intervention pumps still exist in the models with whirling flow. Conventional artificial bioprosthetic valves have limited effectiveness in treating the valve diseases caused by intervention pumps implantation. CONCLUSIONS: This study quantitatively investigates the impact of intervention pumps on the aortic valves, and investigates the effect of blood rotation on the valve behavior, which is a gap in previous research. We suggest that in the short-term treatment, the implantation of intervention pumps has limited impact on aortic valves, caution should be exercised against valve regurgitation issues caused by intervention pumps.

Endothelial cell-derived extracellular vesicles modulate the therapeutic efficacy of mesenchymal stem cells through IDH2/TET pathway in ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe and fatal disease. Although mesenchymal stem cell (MSC)-based therapy has shown remarkable efficacy in treating ARDS in animal experiments, clinical outcomes have been unsatisfactory, which may be attributed to the influence of the lung microenvironment during MSC administration. Extracellular vesicles (EVs) derived from endothelial cells (EC-EVs) are important components of the lung microenvironment and play a crucial role in ARDS. However, the effect of EC-EVs on MSC therapy is still unclear. In this study, we established lipopolysaccharide (LPS) - induced acute lung injury model to evaluate the impact of EC-EVs on the reparative effects of bone marrow-derived MSC (BM-MSC) transplantation on lung injury and to unravel the underlying mechanisms. METHODS: EVs were isolated from bronchoalveolar lavage fluid of mice with LPS - induced acute lung injury and patients with ARDS using ultracentrifugation. and the changes of EC-EVs were analysed using nanoflow cytometry analysis. In vitro assays were performed to establish the impact of EC-EVs on MSC functions, including cell viability and migration, while in vivo studies were performed to validate the therapeutic effect of EC-EVs on MSCs. RNA-Seq analysis, small interfering RNA (siRNA), and a recombinant lentivirus were used to investigate the underlying mechanisms. RESULTS: Compared with that in non-ARDS patients, the quantity of EC-EVs in the lung microenvironment was significantly greater in patients with ARDS. EVs derived from lipopolysaccharide-stimulated endothelial cells (LPS-EVs) significantly decreased the viability and migration of BM-MSCs. Furthermore, engrafting BM-MSCs pretreated with LPS-EVs promoted the release of inflammatory cytokines and increased pulmonary microvascular permeability, aggravating lung injury. Mechanistically, LPS-EVs reduced the expression level of isocitrate dehydrogenase 2 (IDH2), which catalyses the formation of α-ketoglutarate (α-KG), an intermediate product of the tricarboxylic acid (TCA) cycle, in BM-MSCs. α-KG is a cofactor for ten-eleven translocation (TET) enzymes, which catalyse DNA hydroxymethylation in BM-MSCs. CONCLUSIONS: This study revealed that EC-EVs in the lung microenvironment during ARDS can affect the therapeutic efficacy of BM-MSCs through the IDH2/TET pathway, providing potential strategies for improving the therapeutic efficacy of MSC-based therapy in the clinic.

Treatment with immunosuppressants did not increase the risk of COVID-19 in pemphigus patients: A single-center survey-based study.

BACKGROUND: The prevalence and outcomes of coronavirus 2019 (COVID-19) among patients using glucocorticoids and immunosuppressants remain controversial. AIM: The study aims to investigate the impact of immunosuppressants especially glucocorticoids on patients in the Autoimmune Bullous Diseases Cohort of West China Hospital (AIBDWCH) during COVID-19. METHODS: We conducted a cross-sectional survey from December 7, 2022, to February 8, 2023, using questionnaires administered either face-to-face or by phone. COVID-19 cases were classified as confirmed, probable, or suspected according to World Health Organization criteria. Patients were divided into Group A (confirmed and probable cases) and Group B (suspected and other cases). The impact of glucocorticoids and immunosuppressive agents on COVID-19 disease and progression was evaluated with logistic regression models. RESULTS: This study included 111 patients with pemphigus. Overweight patients had a reduced risk of confirmed COVID-19 (odds ratio [OR] 0.35 [95 % CI 0.13-0.97], p = 0.045). Patients treated with a medium dose of prednisone during the pandemic had a lower incidence of COVID-19 compared to those on low doses, though the difference was not statistically significant. No independent effects of age, sex, comorbidities, and therapies were observed. No significant differences were found in COVID-19 symptoms among different therapy groups. CONCLUSIONS: Treatment with immunosuppressants, particularly glucocorticoids at low-to-medium doses, did not elevate COVID-19 risk in pemphigus patients. Consistent outcomes across treatments confirm the safety of these therapies during the pandemic.

Fabrication of an Antifouling Surface Plasmon Resonance Sensor with Stratified Zwitterionic Peptides for Highly Efficient Detection of Peanut Allergens in Biscuits.

Peanut allergen monitoring is currently an effective strategy to avoid allergic diseases, while food matrix interference is a critical challenge during detection. Here, we developed an antifouling surface plasmon resonance sensor (SPR) with stratified zwitterionic peptides, which provides both excellent antifouling and sensing properties. The antifouling performance was measured by the SPR, which showed that stratified peptide coatings showed much better protein resistance, reaching ultralow adsorption levels (<5 ng/cm2). Atomic force microscopy was used to further analyze the antifouling mechanism from a mechanical perspective, which demonstrated lower adsorption forces on hybrid peptide coatings, confirming the better antifouling performance of stratified surfaces. Moreover, the recognition of peanut allergens in biscuits was performed using an SPR with high efficiency and appropriate recovery results (98.2-112%), which verified the feasibility of this assay. Therefore, the fabrication of antifouling sensors with stratified zwitterionic peptides provides an efficient strategy for food safety inspection.

Cu-BTC Derived Mesoporous CuS Nanomaterial as Nanozyme for Colorimetric Detection of Glutathione.

In this paper, Cu-BTC derived mesoporous CuS nanomaterial (m-CuS) was synthesized via a two-step process involving carbonization and sulfidation of Cu-BTC for colorimetric glutathione detection. The Cu-BTC was constructed by 1,3,5-benzenetri-carboxylic acid (H3BTC) and Cu2+ ions. The obtained m-CuS showed a large specific surface area (55.751 m2/g), pore volume (0.153 cm3/g), and pore diameter (15.380 nm). In addition, the synthesized m-CuS exhibited high peroxidase-like activity and could catalyze oxidation of the colorless substrate 3,3',5,5'-tetramethylbenzidine to a blue product. Peroxidase-like activity mechanism studies using terephthalic acid as a fluorescent probe proved that m-CuS assists H2O2 decomposition to reactive oxygen species, which are responsible for TMB oxidation. However, the catalytic activity of m-CuS for the oxidation of TMB by H2O2 could be potently inhibited in the presence of glutathione. Based on this phenomenon, the colorimetric detection of glutathione was demonstrated with good selectivity and high sensitivity. The linear range was 1-20 µM and 20-300 µM with a detection limit of 0.1 µM. The m-CuS showing good stability and robust peroxidase catalytic activity was applied for the detection of glutathione in human urine samples.

Does settlement land expansion necessarily induce the decrease of cultivated land? Differences in national scale and local counties of China.

With the extensive industrialization and urbanization taking place in China during the recent decades, land use throughout the country has experienced profound changes influenced not only by the demand for population growth and living standard improvement but also by the constraints of series of land use policies. However, whether the conflict between the expansion of settlement land (SL) and the loss of cultivated land (CL) have been resolved at the national scale or transferred between the local regions remains unclear. Based on yearly ESA CCI land use and land cover products from 1992 to 2020, the long-term trends of quantity and spatial pattern of SL expansion and CL change in China from national and local views were investigated using trend statistic methods, and finally a comprehensive zoning framework was proposed to recognize the trade-off and synergies relationships between SL expansion and CL change. There are a continuous expansion of SL with global linear trends showing three breakpoints in 2000, 2005, and 2012, and a fluctuation decline of CL presented with four breakpoints in 1997, 2002, 2006, and 2013. Aggregation and dispersion tendencies with linear characteristics of SL expansion and CL change were found with breakpoints in 2001, 2008, 2012, and 2016 and breakpoints in 2001 and 2010, respectively. A spotty spatial pattern of SL was shown spatially coincident with urban agglomerations in China while the planar continuous characteristic was found for CL. Local counties were classified into five tradeoff and synergies zones (TSZs), where general synergies (G-S) and decoupling (D) of SL expansion and CL change were rare cases and the different change in quantity and trend of SL expansion and CL change in local counties was concealed by the national trend. A few scattered counties were belonging to G-S and D TSZs, while most of the counties in the central-east and western China were in General-Tradeoff (G-T) and Superior-Tradeoff (S-T) TSZs. Counties in south and north China with higher percentages of CL were more prevalent in Superior-Synergy (S-S) TSZ. Our findings explicated the complex relationships between SL expansion and CL change of China at the national scale and in local counties, which pointed out the differences of unified land use management activities across scales and could provide insights for future policy-making and management measures of land use to both ensure the national food security and promote regional sustainable development more synchronously.

Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index.

Drylands contribute roughly 40 % of the global net primary productivity and are essential for achieving sustainable development. Investigating the effects on vegetation from urban expansion in drylands within the context of rapid urbanization could help enhance the sustainability of dryland cities. With the use of the drylands of northern China (DNC) as an example, we applied the vegetation disturbance index to investigate the negative and positive effects on vegetation from urban expansion in drylands. The results revealed that the DNC experienced massive and rapid urban expansion from 2000 to 2020. Urban land in the entire DNC increased by 19,646 km2 from 8141 to 27,787 km2, with an annual growth rate of 6.3 %. Urban expansion in the DNC imposed both negative and positive effects on regional vegetation. The area with negative effects reached 7736 km2 and was mainly concentrated in the dry subhumid zones. The area with positive effects amounted to 5011 km2 and was comparable among the dry subhumid, semiarid, and arid zones. Land use/cover change induced by population growth significantly contributed to these negative effects, while the positive effects were largely caused by economic growth. Therefore, it is recommended to strike a balance between urban growth and vegetation conservation to mitigate the adverse effects on vegetation from urban expansion in drylands. Simultaneously, it is imperative to expand urban green spaces and build sustainable and livable ecological cities to facilitate sustainable urban development.

Astragaloside IV attenuates renal tubule injury in DKD rats via suppression of CD36-mediated NLRP3 inflammasome activation.

Background: In recent years, diabetic kidney disease (DKD) has emerged as a prominent factor contributing to end-stage renal disease. Tubulointerstitial inflammation and lipid accumulation have been identified as key factors in the development of DKD. Earlier research indicated that Astragaloside IV (AS-IV) reduces inflammation and oxidative stress, controls lipid accumulation, and provides protection to the kidneys. Nevertheless, the mechanisms responsible for its protective effects against DKD have not yet been completely elucidated. Purpose: The primary objective of this research was to examine the protective properties of AS-IV against DKD and investigate the underlying mechanism, which involves CD36, reactive oxygen species (ROS), NLR family pyrin domain containing 3 (NLRP3), and interleukin-1ß (IL-1ß). Methods: The DKD rat model was created by administering streptozotocin along with a high-fat diet. Subsequently, the DKD rats and palmitic acid (PA)-induced HK-2 cells were treated with AS-IV. Atorvastatin was used as the positive control. To assess the therapeutic effects of AS-IV on DKD, various tests including blood sugar levels, the lipid profile, renal function, and histopathological examinations were conducted. The levels of CD36, ROS, NLRP3, Caspase-1, and IL-1ß were detected using western blot analysis, PCR, and flow cytometry. Furthermore, adenovirus-mediated CD36 overexpression was applied to explore the underlying mechanisms through in vitro experiments. Results: In vivo experiments demonstrated that AS-IV significantly reduced hyperglycemia, dyslipidemia, urinary albumin excretion, and serum creatinine levels in DKD rats. Additionally, it improved renal structural abnormalities and suppressed the expression of CD36, NLRP3, IL-1ß, TNF-α, and MCP-1. In vitro experiments showed that AS-IV decreased CD36 expression, lipid accumulation, and lipid ROS production while inhibiting NLRP3 activation and IL-1ß secretion in PA-induced HK-2 cells. Conclusion: AS-IV alleviated renal tubule interstitial inflammation and tubule epithelial cell apoptosis in DKD rats by inhibiting CD36-mediated lipid accumulation and NLRP3 inflammasome activation.

A causal association between amyotrophic lateral sclerosis and atrial fibrillation: a two-sample Mendelian randomization study.

Objectives: To look into the connection between amyotrophic lateral sclerosis (ALS) and atrial fibrillation (AF) using Mendelian randomization (MR). Methods: Two-sample MR was performed using genetic information from genome-wide association studies (GWAS). Genetic variants robustly associated with ALS and AF were used as instrumental variables. GWAS genetic data for ALS (n = 138,086, ncase = 27,205) and AF (n = 1,030,836, ncase = 60,620), publicly available from IEU Open. The specific MR protocols were Inverse variance-weighted (IVW), Simple mode, MR Egger, Weighted mode, and Weight median estimator (WME). Subsequently, the MR-Egger intercept and Cochran Q examine were used to evaluate instrumental variables (IVs)' heterogeneity and multiplicative effects (IVs). In addition, MR-PRESSO analysis was conducted to exclude any potential pleiotropy. Results: The IVW method demonstrated that ALS positively affected AF [OR: 1.062, 95% CI (1.004-1.122); P = 0.035]. Indeed, other MR methods were in accordance with the tendency of the IVW method (all OR > 1), and sensitivity testing verified the reliability of this MR result. Conclusions: This MR study proves a positive causal connection between ALS and atrial fibrillation. Further studies are warranted to elucidate the mechanisms linking ALS and AF.

(+)-Catechin ameliorates diabetic nephropathy injury by inhibiting endoplasmic reticulum stress-related NLRP3-mediated inflammation.

Endoplasmic reticulum (ER) stress and chronic sterile inflammation are associated with the pathogenesis of diabetic nephropathy (DN). Catechins are natural polyphenolic compounds found in green tea that possess some health benefits. However, whether (+)-catechin can reduce tubular injury in DN by regulating ER stress and NLRP3-associated inflammation remains uncertain. This study examined the effects of (+)-catechin on streptozotocin (STZ)-induced diabetic mice and on palmitic acid (PA)-treated HK-2 cells. In vivo, a DN mouse model was generated by injecting STZ. The biochemical indicators of serum and urine, as well as renal histopathology and ultrastructure were analysed. To predict the mechanisms associated with (+)-catechin, network pharmacology and molecular docking were used. Finally, quantitative real-time PCR (qPCR), western blot analysis and immunofluorescence analysis were performed to measure the mRNA and protein expressions of specific targets in the renal tissue of DN mice and PA-treated HK-2 cells to validate the predicted results. (+)-Catechin significantly ameliorated renal function and pathological changes associated with tubular injury by inhibiting ER stress by downregulating of GRP78, PEAK, CHOP, ATF6 and XBP1. In addition, (+)-catechin inhibited renal inflammation by suppressing NLRP3 associated inflammation, which was characterized by the downregulation of NLRP3, ASC, AIM2, Caspase1, IL-1ß and IL-18 in DN mice and PA-treated HK-2 cells. Collectively, these findings suggested that (+)-catechin exerted a renoprotective effect against DN by inhibiting ER stress and NLRP3-related inflammation to ameliorate tubular injury, suggesting the therapeutic potential of (+)-catechin.

Lightweight model-based sheep face recognition via face image recording channel.

The accurate identification of individual sheep is a crucial prerequisite for establishing digital sheep farms and precision livestock farming. Currently, deep learning technology provides an efficient and non-contact method for sheep identity recognition. In particular, convolutional neural networks can be used to learn features of sheep faces to determine their corresponding identities. However, the existing sheep face recognition models face problems such as large model size, and high computational costs, making it difficult to meet the requirements of practical applications. In response to these issues, we introduce a lightweight sheep face recognition model called YOLOv7-Sheep Face Recognition (YOLOv7-SFR). Considering the labor-intensive nature associated with manually capturing sheep face images, we developed a face image recording channel to streamline the process and improve efficiency. This study collected facial images of 50 Small-tailed Han sheep through a recording channel. The experimental sheep ranged in age from 1 to 3 yr, with an average weight of 63.1 kg. Employing data augmentation methods further enhanced the original images, resulting in a total of 22,000 sheep face images. Ultimately, a sheep face dataset was established. To achieve lightweight improvement and improve the performance of the recognition model, a variety of improvement strategies were adopted. Specifically, we introduced the shuffle attention module into the backbone and fused the Dyhead module with the model's detection head. By combining multiple attention mechanisms, we improved the model's ability to learn target features. Additionally, the traditional convolutions in the backbone and neck were replaced with depthwise separable convolutions. Finally, leveraging knowledge distillation, we enhanced its performance further by employing You Only Look Once version 7 (YOLOv7) as the teacher model and YOLOv7-SFR as the student model. The training results indicate that our proposed approach achieved the best performance on the sheep face dataset, with a mean average precision@0.5 of 96.9%. The model size and average recognition time were 11.3 MB and 3.6 ms, respectively. Compared to YOLOv7-tiny, YOLOv7-SFR showed a 2.1% improvement in mean average precision@0.5, along with a 5.8% reduction in model size and a 42.9% reduction in average recognition time. The research results are expected to drive the practical applications of sheep face recognition technology.

Accurate identification of individual sheep is a crucial prerequisite for establishing digital sheep farms and precision livestock farming. In this study, we developed a lightweight sheep face recognition model, YOLOv7-SFR. Utilizing a face image recording channel, we efficiently collected facial images from 50 experimental sheep, resulting in a comprehensive sheep face dataset. Training results demonstrated that YOLOv7-SFR surpassed state-of-the-art lightweight sheep face recognition models, achieving a mean average precision@0.5 of 96.9%. Notably, the model size and average recognition time of YOLOv7-SFR were merely 11.3 MB and 3.6 ms, respectively. In summary, YOLOv7-SFR strikes an optimal balance between performance, model size, and recognition speed, offering promising practical applications for sheep face recognition technology. This study employs deep learning for sheep face recognition tasks, ensuring the welfare of sheep in the realm of digital agriculture and automation practices.

scSemiGCN: boosting cell-type annotation from noise-resistant graph neural networks with extremely limited supervision.

MOTIVATION: Cell-type annotation is fundamental in revealing cell heterogeneity for single-cell data analysis. Although a host of works have been developed, the low signal-to-noise-ratio single-cell RNA-sequencing data that suffers from batch effects and dropout still poses obstacles in discovering grouped patterns for cell types by unsupervised learning and its alternative-semi-supervised learning that utilizes a few labeled cells as guidance for cell-type annotation. RESULTS: We propose a robust cell-type annotation method scSemiGCN based on graph convolutional networks. Built upon a denoised network structure that characterizes reliable cell-to-cell connections, scSemiGCN generates pseudo labels for unannotated cells. Then supervised contrastive learning follows to refine the noisy single-cell data. Finally, message passing with the refined features over the denoised network structure is conducted for semi-supervised cell-type annotation. Comparison over several datasets with six methods under extremely limited supervision validates the effectiveness and efficiency of scSemiGCN for cell-type annotation. AVAILABILITY AND IMPLEMENTATION: Implementation of scSemiGCN is available at https://github.com/Jane9898/scSemiGCN.