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Cymbidium (Orchidaceae: Epidendroideae), with around 60 species, is widely-distributed across Southeast Asia, providing a nice system for studying the processes that underlie patterns of biodiversity in the region. However, phylogenetic relationships of Cymbidium have not been well resolved, hampering investigations of species diversification and the biogeographical history of this genus. In this study, we construct a plastome phylogeny of 56 Cymbidium species, with four well-resolved major clades, which provides a framework for biogeographical and diversification rate analyses. Molecular dating and biogeographical analyses show that Cymbidium likely originated in the region spanning northern Indo-Burma to the eastern Himalayas during the early Miocene (∼21.10 Ma). It then rapidly diversified into four major clades in East Asia within approximately a million years during the middle Miocene. Cymbidium spp. migration to the adjacent regions (Borneo, Philippines, and Sulawesi) primarily occurred during the Pliocene-Pleistocene period. Our analyses indicate that the net diversification rate of Cymbidium has decreased since its origin, and is positively associated with changes in temperature and monsoon intensity. Favorable hydrothermal conditions brought by monsoon intensification in the early Miocene possibly contributed to the initial rapid diversification, after which the net diversification rate was reduced with the cooling climate after the middle Miocene. The transition from epiphytic to terrestrial habits may have enabled adaptation to cooler environments and colonization of northern niches, yet without a significant effect on diversification rates. This study provides new insights into how monsoon activity and temperature changes affected the diversification dynamics of plants in Southeast Asia.

Abstract Adipose tissue plays critical roles in an individual’s aging process. In this research, we use single-nucleus RNA sequencing to create highly detailed transcriptional maps of subcutaneous adipose tissue and visceral adipose tissue in young and aged mice. We comprehensively identify the various cell types within the white adipose tissue of mice, our study has elucidated seven distinct cell types within this tissue. Further analyses focus on adipocytes, fibro-adipogenic progenitors, and immune cells, revealing age-related declines in the synthetic metabolic activity of adipocytes, diminished immune regulation, and reduced maturation or proliferation of fibroblasts in undifferentiated adipocytes. We confirm the presence of distinct subpopulations of adipocytes, highlighting decreases in adipogenesis subgroups due to aging. Additionally, we uncover a reduction in immune cell subpopulations, driven by age-associated immune system dysregulation. Furthermore, pseudo-time analyses indicate that Adipocyte1 represents the 'nascent' phase of adipocyte development, while Adipocyte2 represents the 'mature' phase. We use cell–cell interaction to explore the age-dependent complexities of the interactions between FAPs and adipocytes, and observed increased expression of the inflammation-related Retn-Tlr4 interaction in older mice, while the anti-inflammatory Angpt1-Tek interaction was only detected in young mice. These transcriptional profiles serve as a valuable resource for understanding the functional genomics underlying metabolic disorders associated with aging in human adipose tissue.

Abstract Software Defect Detection (SDD) has always been critical to the development life cycle. A stable defect detection system can not only alleviate the workload of software testers but also enhance the overall efficiency of software development. Researchers have recently proposed various artificial intelligence-based SDD methods and achieved significant advancements. However, these methods still exhibit limitations in terms of reliability and usability. Therefore, we introduce MSDD-(IA)3, a novel framework leveraging the pre-trained CodeT5+ and (IA)3 for parameter-efficient multi-classification SDD. This framework constructs a detection model based on pre-trained CodeT5+ to generate code representations while capturing defect-prone features. Considering the high overhead of pre-trained LLMs, we injects (IA)3 vectors into specific layers, where only these injected parameters are updated to reduce the training cost. Furthermore, leveraging the properties of the pre-trained CodeT5+, we design a novel feature sequence that enriches the input data through the combination of source code with Natural Language (NL)-based expert metrics. Our experimental results on 64K real-world Python snippets show that MSDD-(IA)3 demonstrates superior performance compared to state-of-the-art SDD methods, including PM2-CNN, in terms of F1-weighted, Recall-weighted, Precision-weighted, and Matthews Correlation Coefficient. Notably, the training parameters of MSDD-(IA)3 are only 0.04% of those of the original CodeT5+. Our experimental data and code can be available at ( https://gitee.com/wxyzjp123/msdd-ia3/ ).

Abstract The Omicron subvariants BQ.1.1, XBB.1.5, and XBB.1.16 of SARS-CoV-2 are known for their adeptness at evading immune responses. Here, we isolate a neutralizing antibody, 7F3, with the capacity to neutralize all tested SARS-CoV-2 variants, including BQ.1.1, XBB.1.5, and XBB.1.16. 7F3 targets the receptor-binding motif (RBM) region and exhibits broad binding to a panel of 37 RBD mutant proteins. We develop the IgG-like bispecific antibody G7-Fc using 7F3 and the cross-neutralizing antibody GW01. G7-Fc demonstrates robust neutralizing activity against all 28 tested SARS-CoV-2 variants and sarbecoviruses, providing potent prophylaxis and therapeutic efficacy against XBB.1 infection in both K18-ACE and BALB/c female mice. Cryo-EM structure analysis of the G7-Fc in complex with the Omicron XBB spike (S) trimer reveals a trimer-dimer conformation, with G7-Fc synergistically targeting two distinct RBD epitopes and blocking ACE2 binding. Comparative analysis of 7F3 and LY-CoV1404 epitopes highlights a distinct and highly conserved epitope in the RBM region bound by 7F3, facilitating neutralization of the immune-evasive Omicron variant XBB.1.16. G7-Fc holds promise as a potential prophylactic countermeasure against SARS-CoV-2, particularly against circulating and emerging variants.

Abstract Background The influence of native secondary succession associated with anthropogenic disturbance on the biodiversity of the forests in subtropical China remains uncertain. In particular, the evolutionary response of small understory shrubs, particularly pioneer species inhabiting continuously disturbed habitats, to topographic heterogeneity and climate change is poorly understood. This study aimed to address this knowledge gap by focusing on the Gaultheria crenulata group, a clade of small pioneer shrubs in subtropical China. Results We examined the genetic structure and demographic history of all five species of the G. crenulata group with two maternally inherited chloroplast DNA (cpDNA) fragments and two biparentally inherited low-copy nuclear genes (LCG) over 89 natural populations. We found that the genetic differentiation of this group was influenced by the geomorphological boundary between different regions of China in association with Quaternary climatic events. Despite low overall genetic diversity, we observed an isolation-by-distance (IBD) pattern at a regional scale, rather than isolation-by-environment (IBE), which was attributed to ongoing human disturbance in the region. Conclusion Our findings suggest that the genetic structure of the G. crenulata group reflects the interplay of geological topography, historical climates, and anthropogenic disturbance during the Pliocene–Pleistocene-Holocene periods in subtropical China. The observed IBD pattern, particularly prominent in western China, highlights the role of limited dispersal and gene flow, possibly influenced by physical barriers or decreased connectivity over geographic distance. Furthermore, the east-to-west trend of gene flow, potentially facilitated by the East Asian monsoon system, underscores the complex interplay of biotic and abiotic factors shaping the genetic dynamics of pioneer species in subtropical China’s secondary forests. These findings can be used to assess the impact of environmental changes on the adaptation and persistence of biodiversity in subtropical forest ecosystems.

Abstract Background Myocardial infarction (MI) poses a global public health challenge, often associated with elevated mortality rates and a grim prognosis. A crucial aspect of the inflammatory injury and healing process post-MI involves the dynamic differentiation of macrophages. A promising strategy to alleviate myocardial damage after MI is by modulating the inflammatory response and orchestrating the shift from pro-inflammatory (M1) to anti-inflammatory (M2) macrophages, aiming to achieve a reduced M1/M2 ratio. Nuanxinkang (NXK), a simplified herbal decoction, has demonstrated noteworthy cardioprotective, inflammation-regulating, and myocardial energy metabolism-regulating properties. Methods In this study, we constructed an MI model by ligating coronary arteries to investigate the efficacy of NXK in improving ventricular remodeling and cardiac function. Mice were administered NXK (1.65 g/kg/d) or an equivalent volume of regular saline via gavage for 28 consecutive days, commencing the day after surgery. Then, we conducted echocardiography to assess the cardiac function, Masson staining to illustrate the extent of myocardial fibrosis, TUNEL staining to reveal myocardial apoptosis, and flow cytometry to analyze the polarization of M1 and M2 macrophages in the hearts. Besides, a lipopolysaccharide (LPS)-induced pro-inflammatory macrophage (M1) polarization model was implemented in RAW264.7 cells to elucidate the underlying mechanism of NXK in regulating macrophage polarization. RAW264.7 cells were pre-treated with or without NXK-containing serum. Oxidative stress was detected by MitoSox staining, followed by Seahorse energy metabolism assay to evaluate alterations in mitochondrial metabolic patterns and ATP production. Both In vivo and in vitro, HIF-1α and PDK1 were detected by fluorescent quantitative PCR and Western blotting. Results In vivo, MI mice exhibited a decline in cardiac function, adverse ventricular remodeling, and an increase in glycolysis, coupled with M1-dominant polarization mediated by the HIF-1α/PDK1 axis. Notably, robust responses were evident with high-dose NXK treatment (1.65 g/kg/day), leading to a significant enhancement in cardiac function, inhibition of cardiac remodeling, and partial suppression of macrophage glycolysis and the inflammatory phenotype in MI mice. This effect was achieved through the modulation of the HIF-1α/PDK1 axis. In vitro, elevated levels of mitochondrial ROS production and glycolysis were observed in LPS-induced macrophages. Conversely, treatment with NXK notably reduced the oxidative stress damage induced by LPS and enhanced oxidative phosphorylation (OXPHOS). Furthermore, NXK demonstrated the ability to modify the energy metabolism and inflammatory characteristics of macrophages by modulating the HIF-1α/PDK1 axis. The influence of NXK on this axis was partially counteracted by the HIF-1α agonist DMOG. And NXK downregulated PDK1 expression, curtailed glycolysis, and reversed LPS-induced M1 polarization in macrophages, similar to the PDK1 inhibitor DCA. Conclusion In conclusion, NXK protects against MI-induced cardiac remodeling by inducing metabolic reprogramming and phenotypic differentiation of macrophages, achieved through the modulation of the HIF-1α/PDK1 axis. This provides a novel and promising strategy for the treatment of MI.

Abstract Terrestrial geothermal springs are physicochemically diverse and host abundant populations of Archaea. However, the diversity, functionality, and geological influences of these Archaea are not well understood. Here we explore the genomic diversity of Archaea in 152 metagenomes from 48 geothermal springs in Tengchong, China, collected from 2016 to 2021. Our dataset is comprised of 2949 archaeal metagenome-assembled genomes spanning 12 phyla and 392 newly identified species, which increases the known species diversity of Archaea by ~48.6%. The structures and potential functions of the archaeal communities are strongly influenced by temperature and pH, with high-temperature acidic and alkaline springs favoring archaeal abundance over Bacteria. Genome-resolved metagenomics and metatranscriptomics provide insights into the potential ecological niches of these Archaea and their potential roles in carbon, sulfur, nitrogen, and hydrogen metabolism. Furthermore, our findings illustrate the interplay of competition and cooperation among Archaea in biogeochemical cycles, possibly arising from overlapping functional niches and metabolic handoffs. Taken together, our study expands the genomic diversity of Archaea inhabiting geothermal springs and provides a foundation for more incisive study of biogeochemical processes mediated by Archaea in geothermal ecosystems.

Abstract Background Post-anesthetic emergence agitation is common after general anesthesia and may cause adverse consequences, such as injury as well as respiratory and circulatory complications. Emergence agitation after general anesthesia occurs more frequently in nasal surgery than in other surgical procedures. This study aimed to assess the occurrence of emergence agitation in patients undergoing nasal surgery who were extubated under deep anesthesia or when fully awake. Methods A total of 202 patients (18–60 years, American Society of Anesthesiologists classification: I–II) undergoing nasal surgery under general anesthesia were randomized 1:1 into two groups: a deep extubation group (group D) and an awake extubation group (group A). The primary outcome was the incidence of emergence agitation. The secondary outcomes included number of emergence agitations, sedation score, vital signs, and incidence of adverse events. Results The incidence of emergence agitation was lower in group D than in group A (34.7% vs. 72.8%; p

Abstract Nasopharyngeal carcinoma (NPC) is a distinct malignancy primarily prevalent in Southern China and Southeast Asia. Circular RNAs (circRNAs), a class of non-coding RNAs, are evolutionarily conserved and exhibit remarkable stability. Their dysregulation has been observed in various cancers, including NPC. In this review, we investigate the pivotal role of circRNAs in NPC, focusing specifically on their involvement in tumor proliferation, apoptosis, metastasis, angiogenesis, stemness, metabolism, and the tumor microenvironment. We highlight the diagnostic and prognostic potential of circRNAs in NPC, emphasizing their utility as biomarkers for early detection, disease monitoring, and prediction of treatment outcomes. Additionally, we explore the therapeutic implications of circRNAs in NPC, highlighting their potential for targeted therapies.

Abstract Nanjing Yunjin, a traditional Chinese silk weaving craft, is celebrated globally for its unique local characteristics and exquisite workmanship, forming an integral part of the world's intangible cultural heritage. However, with the advancement of information technology, the experiential knowledge of the Nanjing Yunjin production process is predominantly stored in text format. As a highly specialized and vertical domain, this information is not readily convert into usable data. Previous studies on a knowledge graph-based Nanjing Yunjin Question-Answering System have partially addressed this issue. However, knowledge graphs need to be constantly updated and rely on predefined entities and relationship types. Faced with ambiguous or complex natural language problems, knowledge graph information retrieval faces some challenges. Therefore, this study proposes a Nanjing Yunjin Question-Answering System that integrates Knowledge Graphs and Retrieval Augmented Generation techniques. In this system, the ROBERTA model is first utilized to vectorize Nanjing Yunjin textual information, delving deep into textual semantics to unveil its profound cultural connotations. Additionally, the FAISS vector database is employed for efficient storage and retrieval of Nanjing Yunjin information, achieving a deep semantic match between questions and answers. Ultimately, related retrieval results are fed into the Large Language Model for enhanced generation, aiming for more accurate text generation outcomes and improving the interpretability and logic of the Question-Answering System. This research merges technologies like text embedding, vectorized retrieval, and natural language generation, aiming to overcome the limitations of knowledge graphs-based Question-Answering System in terms of graph updating, dependency on predefined types, and semantic understanding. System implementation and testing have shown that the Nanjing Yunjin Intelligent Question-Answering System, constructed on the basis of Knowledge Graphs and Retrieval Augmented Generation, possesses a broader knowledge base that considers context, resolving issues of polysemy, vague language, and sentence ambiguity, and efficiently and accurately generates answers to natural language queries. This significantly facilitates the retrieval and utilization of Yunjin knowledge, providing a paradigm for constructing Question-Answering System for other intangible cultural heritages, and holds substantial theoretical and practical significance for the deep exploration and discovery of the knowledge structure of human intangible heritage, promoting cultural inheritance and protection.

Abstract Previous findings showed that anthocyanins from Lycium ruthenicum Murray (ACN) reduced HFD‐induced hypercholesterolemia by regulating gut microbiota, but the mechanism has not been fully understood. The objective of this research was to know whether the cholesterol‐lowering impact of ACN in HFD‐induced ApoE−/− mice is related to the gut microbiota‐bile acid (BA) metabolism. Twenty‐four male ApoE−/− mice were divided into three groups: the Control group, the HFD group, and the HFD + ACN group. Here, we showed that ACN intervention reduced HFD‐induced body weight serum concentrations of TC and LDL‐C and ameliorated lipid accumulation in the liver and adipose tissues. Besides, ACN altered gut microbiota composition in HFD‐fed ApoE−/− mice. Moreover, UHPLC–MS/MS analysis revealed that ACN intervention significantly increased the ratio of conjugated to unconjugated BAs in feces induced by HFD, attributed to the increase in conjugated BAs and decrease in unconjugated BAs. Finally, the correlation analysis indicated that the above changes in fecal BA profile were linked with an increase in Bifidobacterium, Allobaculum and a decrease in Ileibacterium, Helicobacter, Rikenellaceae_RC9_gut_group, Blautia, Odoribacter, and Colidextribacter. In summary, ACN could alleviate HFD‐induced hypercholesterolemia in ApoE−/− mice, which was associated with the improvement of gut microbiota and modulation of fecal BA profile.

Abstract Many patients who underwent hepatic percutaneous microwave ablation (MWA) reported experiencing pain during the procedure. This study utilized a well-designed multicentral, randomized, and placebo-controlled format to investigate the effects of Butorphanol. Patients who underwent MWA were randomly assigned to either Butorphanol or normal saline group. The primary outcomes of the study were assessed by measuring the patients' intraoperative pain levels using a 10-point visual analog scale (VAS). Secondary outcomes included measuring postoperative pain levels at the 6-h mark (VAS) and evaluating comprehensive pain assessment outcomes. A total of 300 patients were divided between the control group (n = 100) and the experimental group (n = 200). Butorphanol showed statistically significant reductions in intraoperative pain levels compared to the placebo during surgery (5.00 ± 1.46 vs. 3.54 ± 1.67, P

Abstract Respiratory disease caused by coronavirus infection remains a global health crisis. Although several SARS-CoV-2-specific vaccines and direct-acting antivirals are available, their efficacy on emerging coronaviruses in the future, including SARS-CoV-2 variants, might be compromised. Host-targeting antivirals provide preventive and therapeutic strategies to overcome resistance and manage future outbreak of emerging coronaviruses. Cathepsin L (CTSL) and calpain-1 (CAPN1) are host cysteine proteases which play crucial roles in coronaviral entrance into cells and infection-related immune response. Here, two peptidomimetic α-ketoamide compounds, 14a and 14b, were identified as potent dual target inhibitors against CTSL and CAPN1. The X-ray crystal structures of human CTSL and CAPN1 in complex with 14a and 14b revealed the covalent binding of α-ketoamide groups of 14a and 14b to C25 of CTSL and C115 of CAPN1. Both showed potent and broad-spectrum anticoronaviral activities in vitro, and it is worth noting that they exhibited low nanomolar potency against SARS-CoV-2 and its variants of concern (VOCs) with EC50 values ranging from 0.80 to 161.7 nM in various cells. Preliminary mechanistic exploration indicated that they exhibited anticoronaviral activity through blocking viral entrance. Moreover, 14a and 14b exhibited good oral pharmacokinetic properties in mice, rats and dogs, and favorable safety in mice. In addition, both 14a and 14b treatments demonstrated potent antiviral potency against SARS-CoV-2 XBB 1.16 variant infection in a K18-hACE2 transgenic mouse model. And 14b also showed effective antiviral activity against HCoV-OC43 infection in a mouse model with a final survival rate of 60%. Further evaluation showed that 14a and 14b exhibited excellent anti-inflammatory effects in Raw 264.7 mouse macrophages and in mice with acute pneumonia. Taken together, these results suggested that 14a and 14b are promising drug candidates, providing novel insight into developing pan-coronavirus inhibitors with antiviral and anti-inflammatory properties.

Abstract Background Hepatocellular carcinoma (HCC) is closely associatedwith chronic liver diseases, particularly liver cirrhosis, which has an altered extracellular matrix (ECM) composition. The influence and its mechanism of the cirrhotic-ECM on the response of HCC to immune checkpoint inhibitor (ICI) remains less clarified. Methods In silico, proteomic and pathological assessment of alteration of cirrhotic-ECM were applied in clinical cohort. Multiple pre-clinical models with ECM manipulation were used to evaluate cirrhotic-ECM’s effect on ICI treatment. In silico, flow cytometry and IHC were applied to explore how cirrhotic-ECM affect HCC microenvironment. In vitro and in vivo experiments were carried out to identify the mechanism of how cirrhotic-ECM undermined ICI treatment. Results We defined “a pro-tumor cirrhotic-ECM” which was featured as the up-regulation of collagen type 1 (Col1). Cirrhotic-ECM/Col1 was closely related to impaired T cell function and limited anti PD-1 (aPD-1) response of HCC patients from the TCGA pan cancer cohort and the authors’ institution, as well as in multiple pre-clinical models. Mechanically, cirrhotic-ECM/Col1 orchestrated an immunosuppressive microenvironment (TME) by triggering Col1-DDR1-NFκB-CXCL8 axis, which initiated neutrophil extracellular traps (NETs) formation to shield HCC cells from attacking T cells and impede approaching T cells. Nilotinib, an inhibitor of DDR1, reversed the neutrophils/NETs dominant TME and efficiently enhanced the response of HCC to aPD-1. Conclusions Cirrhotic-ECM modulated a NETs enriched TME in HCC, produced an immune suppressive TME and weakened ICI efficiency. Col1 receptor DDR1 could be a potential target synergically used with ICI to overcome ECM mediated ICI resistance. These provide a mechanical insight and novel strategy to overcome the ICI resistance of HCC.

Wastewater treatment is an important source of greenhouse gases (GHGs). Yet large uncertainties remain in the quantification of GHG emissions from municipal wastewater treatment plants (MWWTPs) in China. A high-resolution and technology-specific emission inventory is still lacking to support mitigation strategies of MWWTPs. Here we develop a plant-level and technology-based MWWTP emission inventory for China covering 8703 plants and 19 treatment technology categories by compiling and harmonizing the most up-to-date facility-level databases. China's methane (CH4) and nitrous oxide (N2O) emissions from MWWTPs in 2020 are estimated to be 150.6 Gg and 22.0 Gg, respectively, with the uncertainty range of −30% to 37% and −30% to 26% at 95% confidence interval. We find an emission inequality across cities, with the richest cities emitting two times more CH4 and N2O per capita from municipal wastewater treatment than the poorest cities. The emitted CH4 and N2O are dominated by Anaerobic/Anoxic/Oxic-, Sequencing Batch Reactor-, Oxidation Ditch-, and Anoxic/Oxic-based MWWTPs of less than 20 years old. Considering the relatively young age structure of China's MWWTPs, the committed emissions highlight the importance of reducing on-site GHG emissions by optimization of operating conditions and innovation management. The emission differences among our estimates, previous studies, and the Intergovernmental Panel on Climate Change guidelines are largely attributed to the uncertainties in emission factors, implying the urgent need for more plant-integrated measurements to improve the accuracy of emission accounting.

Abstract BackgroundLarge language models (LLMs) have achieved great progress in natural language processing tasks and demonstrated the potential for use in clinical applications. Despite their capabilities, LLMs in the medical domain are prone to generating hallucinations (not fully reliable responses). Hallucinations in LLMs’ responses create substantial risks, potentially threatening patients’ physical safety. Thus, to perceive and prevent this safety risk, it is essential to evaluate LLMs in the medical domain and build a systematic evaluation. ObjectiveWe developed a comprehensive evaluation system, MedGPTEval, composed of criteria, medical data sets in Chinese, and publicly available benchmarks. MethodsFirst, a set of evaluation criteria was designed based on a comprehensive literature review. Second, existing candidate criteria were optimized by using a Delphi method with 5 experts in medicine and engineering. Third, 3 clinical experts designed medical data sets to interact with LLMs. Finally, benchmarking experiments were conducted on the data sets. The responses generated by chatbots based on LLMs were recorded for blind evaluations by 5 licensed medical experts. The evaluation criteria that were obtained covered medical professional capabilities, social comprehensive capabilities, contextual capabilities, and computational robustness, with 16 detailed indicators. The medical data sets include 27 medical dialogues and 7 case reports in Chinese. Three chatbots were evaluated: ChatGPT by OpenAI; ERNIE Bot by Baidu, Inc; and Doctor PuJiang (Dr PJ) by Shanghai Artificial Intelligence Laboratory. ResultsDr PJ outperformed ChatGPT and ERNIE Bot in the multiple-turn medical dialogues and case report scenarios. Dr PJ also outperformed ChatGPT in the semantic consistency rate and complete error rate category, indicating better robustness. However, Dr PJ had slightly lower scores in medical professional capabilities compared with ChatGPT in the multiple-turn dialogue scenario. ConclusionsMedGPTEval provides comprehensive criteria to evaluate chatbots by LLMs in the medical domain, open-source data sets, and benchmarks assessing 3 LLMs. Experimental results demonstrate that Dr PJ outperforms ChatGPT and ERNIE Bot in social and professional contexts. Therefore, such an assessment system can be easily adopted by researchers in this community to augment an open-source data set.

Commensal microbial–host interaction is crucial for host metabolism, growth, development, and immunity. However, research on microbial–host immunity in large animal models has been limited. This study was conducted to investigate the effects of the commensal microbiota on immune function in two model groups: germ-free (GF) and specific-pathogen-free (SPF) piglets. The weight and organ index of the spleen of the GF piglet were larger than those in the SPF piglet (P < 0.05). The histological structure of the red pulp area and mean area of germinal centers were larger in the SPF piglet than in the GF piglet (P < 0.05), whereas the areas of staining of B cells and T cells in the spleen and mesenteric lymph nodes (MLNs) were lower in the GF piglet (P < 0.05). We identified immune-related genes in the spleen and MLNs using RNA sequencing, and used real-time quantitative PCR to analyze the expression of core genes identified in gene set enrichment analysis. The expression levels of genes in the transforming growth factor-β/SMAD3 signaling pathway, Toll-like receptor 2/MyD88/nuclear factor-κB signaling pathway, and pro-inflammatory factor genes IL-6 and TNF-α in the spleen and MLNs were higher in the SPF piglet and in splenic lymphocytes compared with those in the GF and control group, respectively, under treatment with acetic acid, propionic acid, butyric acid, lipopolysaccharide (LPS), or concanavalin A (ConA). The abundances of plasma cells, CD8++ T cells, follicular helper T cells, and resting natural killer cells in the spleen and MLNs were significantly greater in the SPF piglet than in the GF piglet (P < 0.05). In conclusion, the commensal microbiota influenced the immune tissue structure, abundances of immune cells, and expression of immune-related pathways, indicating the importance of the commensal microbiota for spleen and MLNs development and function. In our study, GF piglet was used as the research model, eliminating the interference of microbiota in the experiment, and providing a suitable and efficient large animal research model for exploring the mechanism of “microbial-host” interactions.

Background: collagen type I is a fundamental composition of extracellular matrix. Typically it exists in the form of a heterotrimer, consisting of two α1 chains encoded by COL1A1 and one α2 chain encoded by COL1A2. However, in cancer a homotrimeric form of collagen type I comprises three α1 chains encoded by COL1A1 was founded. There is still a lack of transcriptional and histologic methods for detecting homotrimeric collagen type I. Furthermore, a comprehensive analysis of the pan-cancer distribution pattern and clinical relevance of homotrimeric collagen type I is conspicuously absent. Method: Using transcriptional and immunoflourance method, we established homocol signature, which is able to transcriptionally and histologically detect homotrimeric collagen type I. We investigated the diagnostic and prognostic potential of homocol as a novel cancer biomarker in a pan-cancer cohort. Furthermore, we assessed its association with clinical manifestations in a liver cancer cohort undergoing treatment at our institute. Result: Homotrimer Collagen Type I is predominantly expressed by cancer cells and is linked to several critical cancer hallmarks, particularly inflammatory response and proliferation. Survival analyses have indicated that a high Homocol expression is correlated with poor outcomes in most types of cancer studied. In terms of cancer detection, Homocol demonstrated strong performance in Receiver Operating Characteristic (ROC) analysis, with an Area Under Curve (AUC) of 0.83 for pan-cancer detection and between 0.72 and 0.99 for individual cancers.In cohorts undergoing PD1 treatment, we noted a higher presence of Homocol in the response group. In a Hepatocellular Carcinoma (HCC) clinical set, high Homocol expression was associated with an increased formation of intra-tumor tertiary lymphoid structures (TLS), larger tumor sizes, more advanced Barcelona Clinic Liver Cancer (BCLC) stages, higher microvascular invasion (MVI) grades, absence of a capsule, and an enriched para-tumor collagen presence. Conclusion: our research has led to the development of a novel gene signature that facilitates the detection of Homotrimer Collagen Type I. This may greatly assist efforts in cancer detection, prognosis, treatment response prediction, and further research into Homotrimer Collagen Type I.

Summary: Synergetic management of waste activated sludge, heavy metals (HMs) and CO2 for their valorization and cyclic utilization is rarely reported. Herein, we employed sludge-derived extracellular polymeric substances (EPS) and HMs in wastewater to fabricate a gas diffusion electrode (GDE) for electrochemical CO2 reduction. This approach atomically dispersed Ni at each nanofiber of the GDE. Abundant N element in the EPS proved to play a key role in the formation of Nx-Ni (mixture of N3-Ni and N4-Ni) sites for highly efficient CO2 to CO conversion. The atomical Ni3+ shows high catalytic activity. Direct gaseous CO2 reduction in a membrane electrode assembly generated a current density up to 50 mA·cm−2 with CO:H2 ratio of ∼100 and ∼75% FECO under 2.69 cell voltage. This strategy takes advantage of all waste streams generated on site and consolidates traditionally separated treatment processes to save costs, produces value-added products and generates carbon benefits during wastewater treatment.

ObjectivesThe objective of this study was to develop a predictive nomogram for intermediate-risk differentiated thyroid cancer (DTC) patients after fixed 3.7GBq (100mCi) radioiodine remnant ablation (RRA).MethodsData from 265 patients who underwent total thyroidectomy with central lymph node dissection (CND) and received RRA treatment at a single institution between January 2018 and March 2023 were analyzed. Patients with certain exclusion criteria were excluded. Univariate and multivariate logistic regression analyses were performed to identify risk factors for a non-excellent response (non-ER) to RRA. A nomogram was developed based on the risk factors, and its performance was validated using the Bootstrap method with 1,000 resamplings. A web-based dynamic calculator was developed for convenient application of the nomogram.ResultsThe study included 265 patients with intermediate-risk DTC. Significant differences were found between the ER group and the non-ER group in terms of CLNM>5, Hashimoto’s thyroiditis, sTg level, TgAb level (P < 0.05). CLNM>5 and sTg level were identified as independent risk factors for non-ER in multivariate analysis. The nomogram showed high accuracy, with an area under the curve (AUC) of 0.833 (95% CI = 0.770–0.895). The nomogram’s predicted probabilities aligned closely with actual clinical outcomes.ConclusionsThis study developed a predictive nomogram for intermediate-risk DTC patients after fixed 3.7GBq (100mCi) RRA. The nomogram incorporates CLNM>5 and sTg levels as risk factors for a non-ER response to RRA. The nomogram and web-based calculator can assist in treatment decision-making and improve the precision of prognosis information. Further research and validation are needed.

Aim: To investigate whether SJF functions in similar manner as the key substance in the inflammatory process, soluble epoxide hydrolase (sEH) inhibitor, to inhibit the arachidonic acid metabolic pathway and nuclear factor kappa-B(NF-κB) signal path in the hippocampi of postpartum depression rats. Methods: The rats were subcutaneous injected estradiol benzoate and progesterone to build PPD rat model. SJF, paroxetine hydrochloride and sEH inhibitor (AUDA) were used to treat PPD rats for 3 weeks. Then the morphological changes of hippocampi and various proteins were observed after that behavioral test were conducted in all 36 SD rats in six group: SJF, paroxetine, AUDA, PPD, sham and normal group. Results: Weight, results of sucrose preference, upright times, total and center squares crossing decreased significantly (P

Pigs are widely used as animal models in various studies related to humans. The interaction between the gut microbiota and the host has significant effects on the host’s health and disease status. However, although there have been many studies investigating the pig gut microbiota, the findings have been inconsistent due to variations in rearing conditions. Interactions between the gut microbiota and host have not been fully explored in pigs. Specific pathogen-free (SPF) pigs are ideal non-primate large animals to study the interactions between the gut microbiota and the host. In this study, we performed high-throughput sequencing analysis of the gut microbiota and the gut tissue transcriptome of six SPF pigs to provide a systematic understanding of the composition, function, and spatial distribution of gut microbiota in SPF pigs. We identified significant differences in microbial diversity and functionality among different gastrointestinal tract sites. Metagenomics data analysis revealed significant differences in alpha diversity and beta diversity of microbiota in different gastrointestinal sites of SPF pigs. Additionally, transcriptomic data indicated significant differences in gene expression as well as KEGG and GO functional enrichment between the small intestine and large intestine. Furthermore, by combining microbial metagenomics and host transcriptomics analyses, specific correlations were found between gut microbiota and host genes. These included a negative correlation between the TCN1 gene and Prevotella dentalis, possibly related to bacterial metabolic pathways involving vitamin B12, and a positive correlation between the BDH1 gene and Roseburia hominis, possibly because both are involved in fatty acid metabolism. These findings lay the groundwork for further exploration of the co-evolution between the microbiota and the host, specifically in relation to nutrition, metabolism, and immunity. In conclusion, we have elucidated the diversity of the gut microbiota in SPF pigs and conducted a detailed investigation into the interactions between the gut microbiota and host gene expression. These results contribute to our understanding of the intricate dynamics between the gut microbiota and the host, offering important references for advancements in life science research, bioproduct production, and sustainable development in animal husbandry.

ABSTRACTOutbreaks of acute respiratory viral diseases, such as influenza and COVID-19 caused by influenza A virus (IAV) and SARS-CoV-2, pose a serious threat to global public health, economic security, and social stability. This calls for the development of broad-spectrum antivirals to prevent or treat infection or co-infection of IAV and SARS-CoV-2. Hemagglutinin (HA) on IAV and spike (S) protein on SARS-CoV-2, which contain various types of glycans, play crucial roles in mediating viral entry into host cells. Therefore, they are key targets for the development of carbohydrate-binding protein-based antivirals. This study demonstrated that griffithsin (GRFT) and the GRFT-based bivalent entry inhibitor GL25E (GRFT-L25-EK1) showed broad-spectrum antiviral effects against IAV infection in vitro by binding to HA in a carbohydrate-dependent manner and effectively protected mice from lethal IAV infection. Although both GRFT and GL25E could inhibit infection of SARS-CoV-2 Omicron variants, GL25E proved to be significantly more effective than GRFT and EK1 alone. Furthermore, GL25E effectively inhibited in vitro co-infection of IAV and SARS-CoV-2 and demonstrated good druggability, including favorable safety and stability profiles. These findings suggest that GL25E is a promising candidate for further development as a broad-spectrum antiviral drug for the prevention and treatment of infection or co-infection from IAV and SARS-CoV-2.IMPORTANCEInfluenza and COVID-19 are highly contagious respiratory illnesses caused by the influenza A virus (IAV) and SARS-CoV-2, respectively. IAV and SARS-CoV-2 co-infection exacerbates damage to lung tissue and leads to more severe clinical symptoms, thus calling for the development of broad-spectrum antivirals for combating IAV and SARS-CoV-2 infection or co-infection. Here we found that griffithsin (GRFT), a carbohydrate-binding protein, and GL25E, a recombinant protein consisting of GRFT, a 25 amino acid linker, and EK1, a broad-spectrum coronavirus inhibitor, could effectively inhibit IAV and SARS-CoV-2 infection and co-infection by targeting glycans on HA of IAV and spike (S) protein of SARS-CoV-2. GL25E is more effective than GRFT because GL25E can also interact with the HR1 domain in SARS-CoV-2 S protein. Furthermore, GL25E possesses favorable safety and stability profiles, suggesting that it is a promising candidate for development as a drug to prevent and treat IAV and SARS-CoV-2 infection or co-infection.

Purpose: This investigation was conceived to engineer and appraise a pioneering clinical nomogram, crafted to bridge the extant chasm in literature regarding the postoperative risk stratification for deep vein thrombosis (DVT) in the aftermath of lower extremity orthopedic procedures. This novel tool offers a sophisticated and discerning algorithm for risk prediction, heretofore unmet by existing methodologies. Methods: In this retrospective observational study, clinical records of hospitalized patients who underwent lower extremity orthopedic surgery were collected at the Wuxi TCM Hospital Affiliated to the Nanjing University of Chinese Medicine between Jan 2017 and Oct 2019. The univariate and multivariate analysis with the backward stepwise method was applied to select features for the predictive nomogram. The performance of the nomogram was evaluated with respect to its discriminant capability, calibration ability, and clinical utility. Result: A total of 5773 in-hospital patients were eligible for the study, with the incidence of deep vein thrombosis being approximately 1 % in this population. Among 31 variables included, 5 of them were identified to be the predictive features in the nomogram, including age, mean corpuscular hemoglobin concentration (MCHC), D-dimer, platelet distribution width (PDW), and thrombin time (TT). The area under the receiver operating characteristic (ROC) curve in the training and validation cohort was 85.9 % (95%CI: 79.96 %–90.04 %) and 85.7 % (95%CI: 78.96 %–90.69 %), respectively. Both the calibration curves and decision curve analysis demonstrated the overall satisfactory performance of the model. Conclusion: Our groundbreaking nomogram is distinguished by its unparalleled accuracy in discriminative and calibrating functions, complemented by its tangible clinical applicability. This innovative instrument is set to empower clinicians with a robust framework for the accurate forecasting of postoperative DVT, thus facilitating the crafting of bespoke and prompt therapeutic strategies, aligning with the rigorous standards upheld by the most esteemed biomedical journals.

Background: Mindfulness-based cognitive therapy (MBCT) has been documented to be effective in treating obsessive-compulsive disorder (OCD). However, the neurobiological basis of MBCT remains largely elusive, which makes it clinically challenging to predict which patients are more likely to respond poorly. Hence, identifying biomarkers for predicting treatment outcomes holds both scientific and clinical values. This prognostic study aims to investigate whether pre-treatment brain morphological metrics can predict the effectiveness of MBCT, compared with psycho-education (PE) as an active placebo, among patients with OCD. Methods: A total of 32 patients with OCD were included in this prognostic study. They received magnetic resonance imaging (MRI) brain scans before treatment. Subsequently, 16 patients received 10 weeks of MBCT, while the other 16 patients underwent a 10-week PE program. The effectiveness of the treatments was primarily assessed by the reduction rate of the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) total score before and after the treatment. We investigated whether several predefined OCD-associated brain morphological metrics, selected based on prior published studies by the ENIGMA Consortium, could predict the treatment effectiveness. Results: Both the MBCT and PE groups exhibited substantial reductions in Y-BOCS scores over 10 weeks of treatment, with the MBCT group showing a larger reduction. Notably, the pallidum total volume was associated with treatment effectiveness, irrespective of the intervention group. Specifically, a linear regression model utilizing the pre-treatment pallidum volume to predict the treatment effectiveness suggested that a one-cubic-centimeter increase in pallidum volume corresponded to a 22.3% decrease in the Y-BOCS total score reduction rate. Conclusions: Pallidum volume may serve as a promising predictor for the effectiveness of MBCT and PE, and perhaps, other treatments with the shared mechanisms by MBCT and PE, among patients with OCD.

Abstract Background The excretory/secretory (ES) antigen of Trichinella spiralis muscle larvae (ML) is currently the most widely used diagnostic antigen to detect T. spiralis infection. However, this antigen has certain drawbacks, such as a complicated ES antigen preparation process and lower sensitivity during the early phase of infection. The aim of this study was to investigate the features of a novel T. spiralis trypsin (TsTryp) and evaluate its potential diagnostic value for trichinellosis. Methods The TsTryp gene was cloned and recombinant TsTryp (rTsTryp) expressed. Western blotting and an enzyme-linked immunosorbent assay (ELISA) were performed to confirm the antigenicity of rTsTryp. The expression pattern and distribution signature of TsTryp at various life-cycle stages of T. spiralis were analyzed by quantitative PCR, western blotting and the immunofluorescence test. An ELISA with rTsTryp and ML ES antigens was used to detect immunoglobulins G and M (IgG, IgM) in serum samples of infected mice, swine and humans. The seropositive results were further confirmed by western blot with rTsTryp and ML ES antigens. Results TsTryp expression was observed in diverse T. spiralis life-cycle phases, with particularly high expression in the early developmental phase (intestinal infectious larvae and adults), with distribution observed mainly at the nematode outer cuticle and stichosome. rTsTryp was identified by T. spiralis-infected mouse sera and anti-rTsTryp sera. Natural TsTryp protease was detected in somatic soluble and ES antigens of the nematode. In mice infected with 200 T. spiralis ML, serum-specific IgG was first detected by rTsTryp-ELISA at 8 days post-infection (dpi), reaching 100% positivity at 12 dpi, and first detected by ES-ELISA at 10 dpi, reaching 100% positivity at 14 dpi. Specific IgG was detected by rTsTryp 2 days earlier than by ES antigens. When specific IgG was determined in serum samples from trichinellosis patients, the sensitivity of rTsTryp-ELISA and ES antigens-ELISA was 98.1% (51/52 samples) and 94.2% (49/52 samples), respectively (P = 0.308), but the specificity of rTsTryp was significantly higher than that of ES antigens (98.7% vs. 95.4%; P = 0.030). Additionally, rTsTryp conferred a lower cross-reaction, with only three serum samples in total testing positive from 11 clonorchiasis, 20 cysticercosis and 24 echinococcosis patients (1 sample from each patient group). Conclusions TsTryp was shown to be an early and highly expressed antigen at intestinal T. spiralis stages, indicating that rTsTryp represents a valuable diagnostic antigen for the serodiagnosis of early Trichinella infection. Graphical Abstract

The precise expression of transcription factors (TFs) is crucial for plant growth and development, especially during somatic embryogenesis. However, conventional overexpression approaches, commonly used for functional genetics, can lead to deleterious effects. Therefore, it is imperative to ensure that TFs are expressed in a controlled and timely manner when aiming to enhance the efficiency of somatic embryogenesis. In this study, a dexamethasone/glucocorticoid receptor (DEX/GR) inducible expression system was employed to modulate the protein expression levels of target TFs within the nucleus during somatic embryogenesis in Liriodendron hybrids. We selected the WUSCHEL (WUS) gene, a well-established functional TF known for its vital role in somatic embryogenesis, as a model to assess the effectiveness of this system. Through DEX treatment, we induced the translocation of LhWUS-GR/LhWUS-GFP-GR fusion proteins from the cytoplasm to the nucleus, consequently leading to WUS-driven somatic embryogenesis. As the DEX concentration increased, there was a corresponding increase in the migration of the LhWUS-GFP-GR fusion protein into the nucleus. Additionally, we observed a higher proliferation ratio of callus expressing LhWUS-GR when exposed to varying DEX concentrations. Notably, the efficiency of somatic embryogenesis exhibited significant improvement under optimal DEX concentration. In conclusion, our study successfully utilizes the DEX/GR inducible system in Liriodendron hybrids, offering a valuable tool for the precise control and utilization of TFs at the desired levels. This innovative approach holds promise for advancing our understanding of TF function and enhancing plant development through the regulated manipulation of TF expression.

Abstract First-line chemoimmunotherapy (with or without bevacizumab) has improved outcomes in advanced non-small cell lung cancer (NSCLC). Here, this open-label, multi-cohort phase II study (NCT05329025) was done to investigate the safety and efficacy of QL1706 (a single bifunctional MabPair product against PD-1 and CTLA-4) and chemotherapy with or without bevacizumab in this population. Patients were enrolled into five different cohorts based on genotype (cohorts 1-4, epidermal growth factor receptor [EGFR] wild-type; cohort 5, EGFR-mutant and progressed on EGFR-tyrosine kinase inhibitors [TKIs]). Between June 11, 2021 and December 29, 2021, 91 patients were enrolled. Most frequent treatment-related adverse events (TRAEs) included decreased appetite (60 [65.9%]), anemia (60 [65.9%]), infusion-related reactions (48 [52.7%]), and pruritus (44 [48.4%]). Grade ≥ 3 TRAEs occurred in 30 (33.0%) patients. Twenty-seven (45%) patients with wild-type EGFR achieved partial response (PR) (objective response rate [ORR] = 45%) and had a median progression-free survival (mPFS) of 6.8 months (95% CI: 5.2-9.7). For 31 patients harboring mutated EGFR, 17 (54.8%) achieved PR (ORR = 54.8%), with an mPFS of 8.5 months (95% CI: 5.72-not evaluable). Overall, QL1706 plus chemotherapy, regardless of having bevacizumab, was generally tolerable and had promising antitumor activity for EGFR wild-type advanced NSCLC in first-line setting. Moreover, QL1706 plus chemotherapy and bevacizumab showed favorable antitumor activity for patients who had EGFR mutated NSCLC but failed in TKI therapy, demonstrating a potential for treating this population.

Visible light communications (VLC) utilizing LEDs for transmissions have been widely considered a revolutionary solution for next-generation networks such as 6G. Frequency response (FR) is of great importance for LEDs, but the inherent internal quantum efficiency (IQE) of LEDs is often disregarded, resulting in imprecise FR models. Although it is widely known that IQE varies with the injected direct current (DC), the impact of IQE on the frequency response has not been thoroughly analyzed. To address this issue, we have developed a precise electro-optical (E-O) FR model by incorporating the ABC model of IQE, named IQE-FR. To validate the accuracy of IQE-FR, we conducted the experiments using commercial off-the-shelf (COTS) LEDs including a tri-color LED and three monochromatic LEDs. The IQE-FR model aligns well with the experimental findings in terms of the maximum FR value, while state-of-the-art FR models that ignore the IQE effects do not yield consistent results. Specifically, we discovered that the red LEDs exhibit a stable DC gain when the biasing current rises to 300 mA, but the highest DC gain for green and blue LEDs can only be achieved under 100 mA. For green and blue LEDs, the biasing currents are much lower than their typical working currents (350 mA and 500 mA). To address the trade-off between luminance and DC gain, we propose cascading multiple LEDs operating at a low current corresponding to the maximum response. Experimental results demonstrate that four cascaded monochromatic LEDs exhibit similar bandwidth and response gain larger than 11 dB compared to a single LED at the same biasing current while delivering four times the emission power, which is very close to the theoretical value of 12 dB. Furthermore, we find that the DC gain improvement by cascading multiple LEDs is nonlinear and bounded by an upper limit as the number of LEDs increases, and as a cost-effective solution, a few tens of LEDs is recommended. To the best of our knowledge, this is the first attempt to apply the IQE model to study the LEDs’ precise FR performances for VLC. We believe that the precise IQE-FR model opens new avenues for optimizing VLC system performance by considering the effects of IQE.

With the rapid development of digital operation and maintenance of transformers, the interference of abnormal data caused by the low reliability of online monitoring sensors has become increasingly evident, directly affecting the accuracy of transformer fault diagnosis and impacting the development of digital operation and maintenance of transformers. Therefore, detecting abnormal data and distinguishing whether abnormal data are caused by equipment faults is an important prerequisite for the accurate diagnosis of transformers. When the difference between normal and abnormal data from online monitoring is insignificant, the existing methods are not ideal for detecting abnormal transformer data and cannot determine invalid data caused by sensor failure. To accurately identify valid data and remove invalid data, this study proposes a combined association rule and improved density clustering method to detect abnormalities in the online monitoring data of transformers. First, association rules mimic the association relationships between transformer data sequences. Then, the association rules are combined with an improved density clustering method based on the number of categories–neighborhood radius threshold curve–to detect anomalies in the sequences. Finally, the accurate identification of abnormal data is achieved, and invalid data caused by sensor reasons are effectively screened, thereby screening valuable data generated by transformer faults. The test results indicate that the proposed method can effectively improve the accuracy and stability of abnormal data detection in online monitoring of transformers.

Visible light communications (VLC) has experienced rapid development in recent years as a strong competitor for next-generation wireless applications due to its wider bandwidth, higher security, and better electromagnetic immunity compared with conventional radio frequency (RF) microwaves. Although state-of- the-art VLC systems can achieve Gbps data rates by employing equalization schemes, designing a general low-complexity VLC transmitter with hundreds of MHz 3-dB bandwidth is still challenging due to the narrow modulation bandwidth nature of light emitting diodes (LEDs). In this paper, we first present a second-order equivalent circuit model for the LED, based on which we propose a general second-order equalizer (GSE) with low complexities, consisting of less than 5 passive capacitors, inductors, and resistors. We show that the GSE can enlarge the LED transmitter's bandwidth to a few hundred MHz. To validate our GSE, we build a broadband VLC transmitter using commercial-off-the-shelf (COTS) red, green and blue (RGB) LEDs, whose bandwidth is 14 MHz, by summing up three colours. Experimental results show that our proposed GSE can extend the transmitter's 3-dB bandwidth from 14 MHz to 1.5 GHz. Furthermore, we demonstrate that a VLC system utilizing the proposed GSE transmitter can achieve 1.15 Gbps data rates at a distance of 250 cm with a bit error ratios (BERs) below the forward error correction (FEC) limit $3.8 \times 10^{-3}$.

Abstract Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by incorporating physical principles into the model. Most PiDL approaches regularize training by embedding governing equations into the loss function, yet this depends heavily on extensive hyperparameter tuning to weigh each loss term. To this end, we propose to leverage physics prior knowledge by “baking” the discretized governing equations into the neural network architecture via the connection between the partial differential equations (PDE) operators and network structures, resulting in a PDE-preserved neural network (PPNN). This method, embedding discretized PDEs through convolutional residual networks in a multi-resolution setting, largely improves the generalizability and long-term prediction accuracy, outperforming conventional black-box models. The effectiveness and merit of the proposed methods have been demonstrated across various spatiotemporal dynamical systems governed by spatiotemporal PDEs, including reaction-diffusion, Burgers’, and Navier-Stokes equations.

Objective In the present study, we aimed to investigate the effects of enzymolysis fermentation of Chinese herbal medicines (CHMs) on egg production performance, egg quality, lipid metabolism, serum reproductive hormone levels, and the mRNA expression of the ovarian hormone receptor of laying hens in the late-laying stage. Methods A total of 360 Hy-Line Brown laying hens (age, 390 days) were randomly categorized into four groups. Hens in the control (C) group were fed a basic diet devoid of CHMs, the crushed CHM (CT), fermented CHM (FC), and enzymatically fermented CHM (EFT) groups received diets containing 2% crushed CHM, 2% fermented CHM, and 2% enzymatically fermented CHM, respectively. Results Compared with crushed CHM, the acid detergent fiber, total flavonoids, and total saponins contents of fermented CHM showed improvement (p

Western diet (rich in highly refined sugar and fat) can induce a range of metabolic dysfunctions in animals and humans, including neuroinflammation and cognitive function decline. Neuroinflammation and cognitive impairment, two critical pathological characteristics of Alzheimer’s disease, have been closely associated with microbial alteration via the gut-brain axis. Thus, the present study aimed to investigate the influence of 2-O-β-D-glucopyranosyl-L-ascorbic acid (AA-2βG) isolated from the fruits of Lycium barbarum on preventing the high-fructose diet (HFrD) induced neuroinflammation in mice. It was found that AA-2βG prevented HFrD-induced cognitive deficits. AA-2βG also predominantly enhanced the gut barrier integrity, decreased lipopolysaccharide entry into the circulation, which subsequently countered the activation of glial cells and neuroinflammatory response. These beneficial effects were transmissible by horizontal fecal microbiome transplantation, transferring from AA-2βG fed mice to HFrD fed mice. Additionally, AA-2βG exerted neuroprotective effects involving the enrichment of Lactobacillus and Akkermansia, potentially beneficial intestinal bacteria. The present study provided the evidence that AA-2βG could improve indices of cognition and neuroinflammmation via modulating gut dybiosis and preventing leaky gut. As a potential functional food ingredient, AA-2βG may be applied to attenuate neuroinflammation associated with Western-style diets.

The final step in the production of the human Sd(a) antigen is catalyzed by beta-1,4-N-acetyl-galactosamine transferase 2 (B4GALNT2). This is done by adding a N-acetylgalactosamine residue via a beta-1,4 linkage to a subterminal galactose residue that has been substituted with an alpha-2,3-linked sialic acid. The final stage of the production of the Cad antigen is also catalyzed by B4GALNT2. Knocking out pig B4GALNT2 gene decreased human serum antibodies binding to pig cells, which greatly reduces the immunological rejection in clinical xenotransplantation trials. Interestingly, gene region LOC110255214 (hereafter named B4GALNT2-like) showed high similarity with the B4GALNT2 gene in the pig genome in our previous work, but whether B4GALNT2-like shares similar biological properties like B4GALNT2 remains to be elucidated, whether B4GALNT2-like is a potential immune gene in xenotransplantation remains to be determined.

The process of identifying substation protection plates faces challenges due to the complex lighting factors that are often inadequately considered. Furthermore， connected domain adhesion during image segmentation tends to be overlooked. Consequently， a recognition method for substation protection plate that leverages HIS （hue， saturation， intensity） color characteristics and employs image processing techniques is introduced. Firstly， the images of the captured protection plate are preprocessed to correct the distortions； then， these images are segmented using HIS color characteristics. Secondly， morphological feature analysis is carried out on the connected domains； the boundary information within these domains is used to eliminate the signboards， and the limit corrosion algorithm is employed to separate the adhesive connected domains. Finally， the state of the protection plate is identified through the fusion of two key features： the boundary feature of the simple minimum bounding rectangle and the deflection angle feature of minimum area bounding rectangle. In a comparative test against the traditional RGB （red， green， blue） color segmentation method and a recognition method based on single aspect ratio， the results demonstrate a substantial improvement in the recognition rate. This method exhibits practical value for engineering applications.

Abstract Goji berry (wolfberry, Lycium), is a genus of Solanaceae, in which the roots, stems, leaves, and fruits are for both food and medicinal uses. In recent years, the demand for health food and research purposes has led to increasing attention being paid to the application of goji berry nutrients and resources. There are three general strategies to process and utilize the goji berry plant. First, the primary processing of goji berry products, such as dried goji berry pulp, and fruit wine with its by‐products. Second, deep processing of sugar–peptides, carotenoids, and the extraction of other efficacy components with their by‐products. Third, the utilization of plant‐based by‐products (roots, stems, leaves, flowers, and fruit residuals). However, the comprehensive use of goji berry is hampered by the non‐standardized production technology of resource utilization and the absence of a multi‐level co‐production and processing technology systems. On the basis of this, we review some novel techniques that are made to more effectively use the resources found in goji berry or its by‐products in order to serve as a guide for the thorough use of these resources and the high‐quality growth of the goji berry processing industry.

Abstract Purpose This study aimed to assess the biodistribution, detection rate, and uptake of the [18F]FAPI-42 at two distinct time intervals. Methods This prospective study enrolled 60 consecutive patients (median age 59; range 35–74) referred to [18F]FAPI-42 PET/CT. [18F]FAPI-42 PET/CT was performed early and late timepoint after tracer injection for staging or restaging. Positive lesions specified for anatomic locations (primary or recurrent tumor, LN metastasis and other metastasis) by visual analysis at both timepoints. Semiquantitative analysis of the tracer activity in lesions as well as normal tissues at both time points were measured and compared. In a subgroup analysis, eleven patients underwent 2-[18F]FDG PET/CT within 1 week, the detection rate and uptake of lesion were compared between early [18F]FAPI-42 and 2-[18F]FDG. Results Uptake of [18F]FAPI-42 in the late timepoint was significantly lower than the early timepoint in most organs (all p

Abstract Background Endostar is a strong angiogenesis inhibitor that is effective in treating non-small cell lung cancer (NSCLC), but the effect of Endostar in the treatment of patients with EGFR-TKI-resistant NSCLC remains unclear. We evaluated the clinical efficacy and safety of Endostar in EGFR-mutant NSCLC patients resistant to EGFR inhibition treatment. Methods From January 1, 2016 to June 30, 2018, 68 patients were selected from the 4 institutions for the study. Patients with NSCLC received Endostar plus chemotherapy every 21-day cycle. Chemotherapy types included platinum-containing dual drugs and platinum-free single drugs. Endostar was administered by intermittent intravenous infusion or continuous microinfusion pump infusion. The overall response rate (ORR), disease control rate (DCR) and adverse events were analyzed. Survival of patients was also evaluated. Results For all patients, the median progression-free survival (PFS) was 2.8 months, and the median overall survival (OS) was 14.2 months. PFS and OS in the Endostar pump continuous group were better than those in the Endostar intravenous infusion group. The disease control rate (DCR) was 79.4%. A total of 28 (41.2%) patients experienced varying grades of adverse events during treatment. No treatment-associated deaths were observed. The grade 3 treatment-emergent adverse events (TEAEs) were myelosuppression, weakness, and nausea/vomiting. Conclusions Endostar was effective and well tolerated in advanced NSCLC patients. Endostar treatment showed promising survival results in EGFR-mutant NSCLC patients.

Abstract Previous studies showed that Trichinella spiralis galectin (Tsgal) facilitates larval invasion of intestinal epithelium cells (IECs). However, IEC proteins binding with Tsgal were not identified, and the mechanism by which Tsgal promotes larval invasion is not clear. Toll-like receptors (TLRs) are protein receptors responsible for recognition of pathogens. The aim of this study was to investigate whether recombinant Tsgal (rTsgal) binds to TLR-4, activates inflammatory pathway in gut epithelium and mediates T. spiralis invasion. Indirect immunofluorescence (IIF), GST pull-down and co-immunoprecipitation (Co-IP) assays confirmed specific binding between rTsgal and TLR-4 in Caco-2 cells. qPCR and Western blotting showed that binding of rTsgal with TLR-4 up-regulated the TLR-4 transcription and expression in Caco-2 cells, and activated p-NF-κB p65 and p-ERK1/2. Activation of inflammatory pathway TLR-4/MAPK-NF-κB by rTsgal up-regulated pro-inflammatory cytokines (IL-1β and IL-6) and down-regulated anti-inflammatory cytokine TGF-β in Caco-2 cells, and induced intestinal inflammation. TAK-242 (TLR-4 inhibitor) and PDTC (NF-κB inhibitor) significantly inhibited the activation of TLR-4 and MAPK-NF-κB pathway. Moreover, the two inhibitors also inhibited IL-1β and IL-6 expression, and increased TGF-β expression in Caco-2 cells. In T. spiralis infected mice, the two inhibitors also inhibited the activation of TLR-4/MAPK-NF-κB pathway, ameliorated intestinal inflammation, impeded larval invasion of gut mucosa and reduced intestinal adult burdens. The results showed that rTsgal binding to TLR-4 in gut epithelium activated MAPK-NF-κB signaling pathway, induced the expression of TLR-4 and pro-inflammatory cytokines, and mediated larval invasion. Tsgal might be regarded as a candidate molecular target of vaccine against T. spiralis enteral invasive stage.

Abstract It is well known that DNA damage can cause apoptosis. However, whether apoptosis and its metabolites contribute to DNA repair is largely unknown. In this study, we found that apoptosis‐deficient Fasmut and Bim−/− mice show significantly elevated DNA damage and premature cellular senescence, along with a significantly reduced number of 16,000 g apoptotic vesicles (apoVs). Intravenous infusion of mesenchymal stromal cell (MSC)‐derived 16,000 g apoVs rescued the DNA damage and premature senescence in Fasmut and Bim−/− mice. Moreover, a sublethal dose of radiation exposure caused more severe DNA damage, reduced survival rate, and loss of body weight in Fasmut mice than in wild‐type mice, which can be recovered by the infusion of MSC‐apoVs. Mechanistically, we showed that apoptosis can assemble multiple nuclear DNA repair enzymes, such as the full‐length PARP1, into 16,000 g apoVs. These DNA repair components are directly transferred by 16,000 g apoVs to recipient cells, leading to the rescue of DNA damage and elimination of senescent cells. Finally, we showed that embryonic stem cell‐derived 16,000 g apoVs have superior DNA repair capacity due to containing a high level of nuclear DNA repair enzymes to rescue lethal dose‐irradiated mice. This study uncovers a previously unknown role of 16,000 g apoVs in safeguarding tissues from DNA damage and demonstrates a strategy for using stem cell‐derived apoVs to ameliorate irradiation‐induced DNA damage.

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor.Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs.Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML.Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

Research on artificial intelligence for brain injury is currently a prominent area of scientific research. A significant amount of related literature has been accumulated in this field. This study aims to identify hotspots and clarify research resources by conducting literature metrology visualization analysis, providing valuable ideas and references for related fields. The research object of this paper consists of 3000 articles cited in the core database of Web of Science from 1998 to 2023. These articles are visualized and analyzed using VOSviewer and CiteSpace. The bibliometric analysis reveals a continuous increase in the number of articles published on this topic, particularly since 2016, indicating significant growth. The United States stands out as the leading country in artificial intelligence for brain injury, followed by China, which tends to catch up. The core research institutions are primarily universities in developed countries, but there is a lack of cooperation and communication between research groups. With the development of computer technology, the research in this field has shown strong wave characteristics, experiencing the early stage of applied research based on expert systems, the middle stage of prediction research based on machine learning, and the current phase of diversified research focused on deep learning. Artificial intelligence has innovative development prospects in brain injury, providing a new orientation for the treatment and auxiliary diagnosis in this field.

Abstract Neuro‐COVID, a condition marked by persistent symptoms post‐COVID‐19 infection, notably affects various organs, with a particular focus on the central nervous system (CNS). Despite scant evidence of SARS‐CoV‐2 invasion in the CNS, the increasing incidence of Neuro‐COVID cases indicates the onset of acute neurological symptoms early in infection. The Omicron variant, distinguished by heightened neurotropism, penetrates the CNS via the olfactory bulb. This direct invasion induces inflammation and neuronal damage, emphasizing the need for vigilance regarding potential neurological complications. Our multicenter study represents a groundbreaking revelation, documenting the definite presence of SARS‐CoV‐2 in the cerebrospinal fluid (CSF) of a significant proportion of Neuro‐COVID patients. Furthermore, notable differences emerged between RNA‐CSF‐positive and negative patients, encompassing aspects such as blood–brain barrier integrity, extent of neuronal damage, and the activation status of inflammation. Despite inherent limitations, this research provides pivotal insights into the intricate interplay between SARS‐CoV‐2 and the CNS, underscoring the necessity for ongoing research to fully comprehend the virus's enduring effects on the CNS. The findings underscore the urgency of continuous investigation Neuro‐COVID to unravel the complexities of this relationship, and pivotal in addressing the long‐term consequences of COVID‐19 on neurological health.

Background: Plant essential oils have long been regarded as repositories of antimicrobial agents. In recent years, they have emerged as potential alternatives or supplements to antimicrobial drugs. Although literature reviews and previous studies have indicated that cinnamon essential oil (CIEO) and its major component, cinnamaldehyde (CID), possess potent antibacterial activities, their antibacterial mechanisms, especially the in vivo antibacterial mechanisms, remain elusive.Methods: In this study, we utilized the in vivo assessment system of Caenorhabditis elegans (C. elegans) to investigate the effects and mechanisms of high dose (100 mg/L) and low dose (10 mg/L) CIEO and CID in inhibiting Pseudomonas aeruginosa (P. aeruginosa). In addition, we also examined the in vitro antibacterial abilities of CIEO and CID against other common pathogens including P. aeruginosa and 4 other strains.Results: Our research revealed that both high (100 mg/L) and low doses (10 mg/L) of CIEO and CID treatment significantly alleviated the reduction in locomotion behavior, lifespan, and accumulation of P. aeruginosa in C. elegans infected with the bacteria. During P. aeruginosa infection, the transcriptional expression of antimicrobial peptide-related genes (lys-1 and lys-8) in C. elegans was upregulated with low-dose CIEO and CID treatment, while this trend was suppressed at high doses. Further investigation suggested that the PMK-1 mediated p38 signaling pathway may be involved in the regulation of CIEO and CID during nematode defense against P. aeruginosa infection. Furthermore, in vitro experimental results also revealed that CIEO and CID exhibit good antibacterial effects, which may be associated with their antioxidant properties.Conclusion: Our results indicated that low-dose CIEO and CID treatment could activate the p38 signaling pathway in C. elegans, thereby regulating antimicrobial peptides, and achieving antimicrobial effects. Meanwhile, high doses of CIEO and CID might directly participate in the internal antimicrobial processes of C. elegans. Our study provides research basis for the antibacterial properties of CIEO and CID both in vivo and in vitro.

Nanoplastics (NPs) continue to accumulate in global aquatic and terrestrial systems, posing a potential threat to human health through the food chain and/or other pathways. Both in vivo and in vitro studies have confirmed that the liver is one of the main organs targeted for the accumulation of NPs in living organisms. However, whether exposure to NPs induces size-dependent disorders of liver lipid metabolism remains controversial, and the reversibility of NPs-induced hepatotoxicity is largely unknown. In this study, the effects of long-term exposure to environmentally relevant doses of polystyrene nanoplastics (PS-NPs) on lipid accumulation were investigated in terms of autophagy and lysosomal mechanisms. The findings indicated that hepatic lipid accumulation was more pronounced in mice exposed to 100 nm PS-NPs compared to 500 nm PS-NPs. This effect was effectively alleviated after 50 days of self-recovery for 100 nm and 500 nm PS-NPs exposure. Mechanistically, although PS-NPs exposure activated autophagosome formation through ERK (mitogen-activated protein kinase 1)/mTOR (mechanistic target of rapamycin kinase) signaling pathway, the inhibition of Rab7 (RAB7, member RAS oncogene family), CTSB (cathepsin B), and CTSD (cathepsin D) expression impaired lysosomal function, thereby blocking autophagic flux and contributing to hepatic lipid accumulation. After termination of PS-NPs exposure, lysosomal exocytosis was responsible for the clearance of PS-NPs accumulated in lysosomes. Furthermore, impaired lysosomal function and autophagic flux inhibition were effectively alleviated. This might be the main reason for the alleviation of PS-NPs-induced lipid accumulation after recovery. Collectively, we demonstrate for the first time that lysosomes play a dual role in the persistence and reversibility of hepatotoxicity induced by environmental relevant doses of NPs, which provide novel evidence for the prevention and intervention of liver injury associated with nanoplastics exposure.

IntroductionMyocardial injury in elderly Omicron variant patients is a leading cause of severe disease and death. This study focuses on elucidating the clinical characteristics and potential risk factors associated with myocardial injury in elderly patients infected with the Omicron variant.MethodsMyocardial injury was defined based on elevated cardiac troponin concentrations exceeding the 99th percentile upper reference limit. Among 772 elderly Omicron-infected patients, categorized into myocardial injury (n = 263) and non-myocardial injury (n = 509) groups. The stratified log-rank statistic was used to compare the probability of patients developing intensive care. Receiver operating characteristic curves were used to determine the best cut-off values of clinical and laboratory data for predicting myocardial injury. Univariate and multivariate logistic regression was adopted to analyze the risk factors for myocardial injury.ResultsThe occurrence of myocardial injury in Omicron variant-infected geriatric patients was up to 34.07% and these patients may have a higher rate of requiring intensive care (P 22.69 pg/ml, procalcitonin > 0.0435 ng/ml, D-dimer > 0.615 mg/L, and sCr > 81.30 μmol/L.ConclusionThis study revealed the clinical characteristics and potential risk factors associated with myocardial injury that enable early diagnosis of myocardial injury in Omicron variant-infected elderly patients, providing important reference indicators for early diagnosis and timely clinical intervention.