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Abstract The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare. Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli. However, realistic mimesis, both in the skin’s three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities, remains a challenging yet vital need for simplifying the design of flexible logic circuits. Herein, we construct an artificial epidermal device by in situ growing Cu3(HHTP)2 particles onto the hollow spherical Ti3C2T x surface, aiming to concurrently emulate the spinous and granular layers of the skin’s epidermis. The bionic Ti3C2T x @Cu3(HHTP)2 exhibits independent NO2 and pressure response, as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication. Ultimately, a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits. This system can assess risk factors related with asthmatic, such as stimulation of external NO2 gas, abnormal expiratory behavior and exertion degrees of fingers, achieving a recognition accuracy of 97.6% as assisted by a machine learning algorithm. Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis.

Abstract Emerging research has shown that lactic acid bacteria in the intestines of newborns play a beneficial role in the growth, immune function, and metabolism of infants after birth. In this study, four strains of Lactobacillus were isolated from fecal samples of newborns, and a safe Lactiplantibacillus plantarum ZFM518 (ZFM518) strain was obtained after the screening, which showed excellent antibacterial activity and adhesion potential. The strain exhibited excellent ability to survive in acidic environments, simulated gastric juice, and simulated intestinal environments, respectively. ZFM518 had a bacteriostatic zone of 31.12 ± 0.33 mm against Staphylococcus aureus, a hydrophobic rate of 76.97% ± 3.35%, and a survival activity of 96.54% ± 0.14% under a simulated intestinal fluid environment. Moreover, ZFM518 can produce up to 161.11 ± 9.67 ng/mL of folate. A genome‐wide investigation of ZFM518 revealed that the majority of its genes were involved in the metabolism of amino acids, carbohydrates, adhesion, immunological defense, and antibacterial activity. In addition, only one antibiotic resistance gene of the antimicrobial peptide was annotated. These results indicate that ZFM518 is a new strain with a strong comprehensive ability and probiotic potential. This study can provide practical support for screening potential probiotics from infant feces and provide a theoretical basis for developing probiotic resources.

Abstract The use of monoclonal antibodies for the control of drug resistant nosocomial bacteria may alleviate a reliance on broad spectrum antimicrobials for treatment of infection. We identify monoclonal antibodies that may prevent infection caused by carbapenem resistant Acinetobacter baumannii. We use human immune repertoire mice (Kymouse platform mice) as a surrogate for human B cell interrogation to establish an unbiased strategy to probe the antibody-accessible target landscape of clinically relevant A. baumannii. After immunisation of the Kymouse platform mice with A. baumannii derived outer membrane vesicles (OMV) we identify 297 antibodies and analyse 26 of these for functional potential. These antibodies target lipooligosaccharide (OCL1), the Oxa-23 protein, and the KL49 capsular polysaccharide. We identify a single monoclonal antibody (mAb1416) recognising KL49 capsular polysaccharide to demonstrate prophylactic in vivo protection against a carbapenem resistant A. baumannii lineage associated with neonatal sepsis mortality in Asia. Our end-to-end approach identifies functional monoclonal antibodies with prophylactic potential against major lineages of drug resistant bacteria accounting for phylogenetic diversity and clinical relevance without existing knowledge of a specific target antigen. Such an approach might be scaled for a additional clinically important bacterial pathogens in the post-antimicrobial era.

Introduction: Ischemia-reperfusion injury (IRI) is detrimental to kidney transplants and may contribute to poor long-term outcomes of transplantation. Programmed cell death (PCD), a regulated cell death form triggered by IRI, is often indicative of an unfavorable prognosis following transplantation. However, given the intricate pathophysiology of IRI and the considerable variability in clinical conditions during kidney transplantation, the specific patterns of cell death within renal tissues remain ambiguous. Consequently, accurately predicting the outcomes for transplanted kidneys continues to be a formidable challenge. Methods: Eight Gene Expression Omnibus datasets of biopsied transplanted kidney samples post-IRI and 1,548 PCD-related genes derived from 18 PCD patterns were collected in our study. Consensus clustering was performed to identify distinct IRI subtypes based on PCD features (IRI PCD subtypes). Differential enrichment analysis of cell death, metabolic signatures, and immune infiltration across these subtypes was evaluated. Three machine learning algorithms were used to identify PCD patterns related to prognosis. Genes associated with graft loss were screened for each PCD type. A predictive model for graft loss was constructed using 101 combinations of 10 machine learning algorithms. Results: Four IRI subtypes were identified: PCD-A, PCD-B, PCD-C, and PCD-D. PCD-A, characterized by high enrichment of multiple cell death patterns, significant metabolic paralysis, and immune infiltration, showed the poorest prognosis among the four subtypes. While PCD-D involved the least kind of cell death patterns with the features of extensive activation of metabolic pathways and the lowest immune infiltration, correlating with the best prognosis in the four subtypes. Using various machine learning algorithms, 10 cell death patterns and 42 PCD-related genes were identified as positively correlated with graft loss. The predictive model demonstrated high sensitivity and specificity, with area under the curve values for 0.5-, 1-, 2-, 3-, and 4-year graft survival at 0.888, 0.91, 0.926, 0.923, and 0.923, respectively. Conclusion: Our study explored the comprehensive features of PCD patterns in transplanted kidney samples post-IRI. The prediction model shows great promise in forecasting graft loss and could aid in risk stratification in patients following kidney transplantation.

Background Acute kidney injury (AKI) is a severe postoperative complication in patients undergoing major surgery. Proton pump inhibitors (PPIs) are used preoperatively as prophylaxis for postoperative gastrointestinal bleeding. Whether preoperative PPI use is associated with an increased risk of postoperative AKI remains uncertain.Methods This retrospective cohort study used electronic medical records from the clinical data warehouse of Peking University First Hospital to screen all adult hospitalizations undergoing major surgery between 1 January 2018 and 31 December 2020. Exposure was preoperative PPI use, defined as PPI use within 7 days before major surgery. The primary outcome was postoperative AKI, defined as AKI occurring within 7 days after major surgery; secondary outcomes included in-hospital AKI and in-hospital mortality.Results A total of 21,533 patients were included in the study (mean [SD] age, 57.8 [15.0] years; 51.2% male), of which 944 (4.4%) were prescribed PPI within 7 days before major surgery (PPI users). Overall, 72 PPI users (7.6%) and 356 non-users (1.7%) developed postoperative AKI. After adjustment, preoperative PPI use was associated with an increased risk of postoperative AKI (adjusted OR, 1.47; 95% CI, 1.04–2.07) and in-hospital AKI (adjusted OR, 1.41; 95% CI, 1.03–1.94). Moreover, subgroup analyses showed that the risk of PPI on postoperative AKI was amplified by the concomitant use of non-steroidal anti-inflammatory drugs or diuretics. No significant difference was observed between preoperative PPI use and in-hospital mortality in the fully adjusted model (adjusted OR 1.63; 95% CI, 0.55–4.85).Conclusions Preoperative PPI use was associated with an increased risk of AKI in patients undergoing major surgery. This risk may be enhanced by the concomitant use of other nephrotoxic drugs. Clinicians should weigh the pros and cons before initiating PPI prophylaxis.

Background & Aims: Dysregulation of one-carbon metabolism is considered an early hallmark of mitochondrial dysfunction and cancer metabolism. ALDH1L2 belongs to the aldehyde dehydrogenase family and plays an important role in tumor progression. However, little is known about the precise role and underlying mechanisms of ALDH1L2 in hepatocellular carcinoma (HCC). Methods: Immunohistochemistry, western blotting, and immunofluorescence staining were used to evaluate ALDH1L2 expression in HCC samples (n = 90) and cell lines (n = 9). A series of in vitro and in vivo assays were performed to explore the role and molecular mechanism of ALDH1L2 in HCC progression. Results: ALDH1L2 upregulation is associated with poor prognosis in HCC (hazard ratio 1.923; 95% confidence interval 1.03–3.59; p = 0.04). ALDH1L2 promotes tumor cell proliferation and metastasis by activating NRF2/IL-6/STAT3 signaling. ALDH1L2 promotes mitochondrial respiration, increases ATP production and protects HCC cells from reactive oxygen species-induced cellular damage via NRF2 stabilization. NRF2 also directly binds to the ALDH1L2 promoter and increases ALDH1L2 transcription, thereby establishing a positive feedback loop to maintain the function of ALDH1L2. The interaction between tumor-associated macrophages and ALDH1L2-overexpressing HCC cells further promotes HCC progression. In addition, ALDH1L2 knockdown enhances the anti-HCC activity of the tyrosine kinase inhibitor sorafenib. Conclusions: These findings provide the first evidence indicating that ALDH1L2 is directly involved in tumor progression by interacting with tumor-associated macrophages through the Jak2/STAT3 signaling pathway and that ALDH1L2 may be a target molecule for HCC therapy. Impact and implications:: This research highlights that ALDH1L2 could serve as a predictive and prognostic marker in HCC. We found that a positive feedback loop between ALDH1L2 and NRF2 promotes HCC progression by activating the IL-6/Jak2/STAT3 signaling axis and tumor-associated macrophage polarization. In addition, we found that ALDH1L2 knockdown enhances the anti-HCC effect of sorafenib.

IntroductionMetabolic dysfunction-associated steatohepatitis (MASH) is increasingly becoming a prevalent cause of hepatocellular carcinoma (HCC). Our study examines the burden of MASH-related HCC globally, regionally, and nationally, along with associated risk factors from 1990 to 2019, considering variables such as age, sex, and socioeconomic status.ObjectiveWe aimed to report the global, regional, and national burden of liver cancer due to MASH and its attributable risk factors between 1990 and 2019, by age, sex, and sociodemographic index (SDI).MethodsUtilizing the Global Burden of Disease 2019 project, we analyzed data on prevalence, mortality, and disability-adjusted life years (DALYs) for liver cancer attributable to MASH across 204 countries. We provided counts and rates per 100,000 population, including 95% uncertainty intervals.ResultsIn 2019, there were 46.8 thousand cases of MASH-related HCC, leading to 34.7 thousand deaths, and 795.8 thousand DALYs globally. While the prevalence increased by 19.8% since 1990, the death and DALY rates decreased by 5.3% and 15.1%, respectively. The highest prevalence was in High-income Asia Pacific, with the greatest increases observed in Australasia, Central Asia, and High-income North America. Southern Sub-Saharan Africa reported the highest death rate, while the lowest rates were in parts of Latin America, Central Sub-Saharan Africa, and Eastern Europe. DALY rates were the highest in Southern Sub-Saharan Africa and the lowest in Tropical Latin America.DiscussionThe burden of MASH-related HCC is expected to rise slightly over the next decade. This disease, which is not associated with the SDI, remains a major public health problem. In addition, the escalating rates of obesity, demographic shifts, and an aging population could position MASH as a leading factor in liver cancer cases, surpassing viral hepatitis. It is imperative, therefore, that the forthcoming years see the implementation of strategic interventions aimed at the early detection and prevention of liver cancer associated with MASH.

In order to give full play to the energy supply potential of distributed energy resources, this paper studies the scheduling optimization of CHP-VPP. First, the CHP unit and various distributed energy sources are aggregated into VPP. Carbon recycling and utilizing are realized through carbon capture and power-to-gas devices. At the same time, carbon storage and hydrogen storage devices are added to decouple carbon capture and P2G procedures. Then, the risk of VPP real-time scheduling is quantified through uncertainty scenario generation and CVaR. Finally, with the goals of operating cost, carbon emission, and operation risk, a multi-objective stochastic scheduling optimization model of VPP is constructed, and the subjective and objective ensemble weighting method is used to solve the problem. The example results show that the proposed method can boost the wastage of wind and photovoltaic power, and also lower the carbon emissions of VPPs.

Abstract Background Gliomas are recognized as the most frequent type of malignancies in the central nervous system, and efficacious prognostic indicators are essential to treat patients with gliomas and improve their clinical outcomes. The chemokine (C‐C motif) ligand 2 (CCL2) is a promising predictor for glioma malignancy and progression. However, at present, the methods to evaluate CCL2 expression level are invasive and operator‐dependent. Objective It was expected to noninvasively predict CCL2 expression levels in malignant glioma tissues by magnetic resonance imaging (MRI)‐based radiomics and assess the association between the developed radiomics model and prognostic indicators and related genes. Methods MRI‐based radiomics was used to predict CCL2 expression level using data obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) databases. A support vector machine (SVM)‐based radiomics model and a logistic regression (LR)‐based radiomics model were used to predict the radiomics score, and its correlation with CCL2 expression level was analyzed. Results The results revealed that there was an association between CCL2 expression level and the overall survival of cases with gliomas, and bioinformatics correlation analysis showed that CCL2 expression level was highly correlated with disease‐related pathways, such as mTOR signaling pathway, cGMP‐PKG signaling pathway, and MAPK signaling pathway. Both SVM‐ and LR‐based radiomics data robustly predicted CCL2 expression level, and radiomics scores could also be used to predict the overall survival of patients. Moreover, the high/low radiomics scores were highly correlated with the known glioma‐related genes, including CD70, CD27, and PDCD1. Conclusion An MRI‐based radiomics model was successfully developed, and its clinical benefits were confirmed, including the prediction of CCL2 expression level and patients' prognosis.

Abstract Chinese patent medicine (CPM) is a typical type of traditional Chinese medicine (TCM) preparation that uses Chinese herbs as raw materials and is an important means of treating diseases in TCM. Chinese patent medicine instructions (CPMI) serve as a guide for patients to use drugs safely and effectively. In this study, we apply a pre-trained language model to the domain of CPM. We have meticulously assembled, processed, and released the first CPMI dataset and fine-tuned the ChatGLM-6B base model, resulting in the development of CPMI-ChatGLM. We employed consumer-grade graphics cards for parameter-efficient fine-tuning and investigated the impact of LoRA and P-Tuning v2, as well as different data scales and instruction data settings on model performance. We evaluated CPMI-ChatGLM using BLEU, ROUGE, and BARTScore metrics. Our model achieved scores of 0.7641, 0.8188, 0.7738, 0.8107, and − 2.4786 on the BLEU-4, ROUGE-1, ROUGE-2, ROUGE-L and BARTScore metrics, respectively. In comparison experiments and human evaluation with four large language models of similar parameter scales, CPMI-ChatGLM demonstrated state-of-the-art performance. CPMI-ChatGLM demonstrates commendable proficiency in CPM recommendations, making it a promising tool for auxiliary diagnosis and treatment. Furthermore, the various attributes in the CPMI dataset can be used for data mining and analysis, providing practical application value and research significance.

Ginseng (Panax ginseng C. A. Meyer) is a valuable plant resource which has been used for centuries as both food and traditional Chinese medicine. It is popular in health research and markets globally. Fresh ginseng has a high moisture content and is prone to mold and rot, reducing its nutritional value without proper preservation. Drying treatments are effective for maintaining the beneficial properties of ginseng post-harvest. In this study, we investigated the effects of natural air drying (ND), hot-air drying (HAD), vacuum drying (VD), microwave vacuum drying (MVD), and vacuum freeze drying (VFD) on volatile organic compounds (VOCs) in ginseng. The results showed that the MVD time was the shortest, followed by the VFD, VD, and HAD times, whereas the ND time was the longest, but the VFD is the most beneficial to the appearance and color retention of ginseng. A total of 72 VOCs were obtained and 68 VOCs were identified using the five drying methods based on gas chromatography–ion mobility spectrometry (GC-IMS) technology, including 23 aldehydes, 19 alkenes, 10 alcohols, 10 ketones, 4 esters, 1 furan, and 1 pyrazine, and the ND method was the best for retaining VOCs. GC-IMS fingerprints, principal component analysis (PCA), Euclidean distance analysis, partial least squares discriminant analysis (PLS-DA), and cluster analysis (CA) can distinguish ginseng from different drying methods. A total of 29 VOCs can be used as the main characteristic markers of different drying methods in ginseng. Overall, our findings provide scientific theoretical guidance for optimizing ginseng’s drying methods, aromatic health effects, and flavor quality research.

IntroductionMany probiotics have the ability to produce extracellular polysaccharides (EPS). EPS derived from these probiotics has been confirmed to regulate the host intestinal microecological balance and alleviate the symptoms of diseases caused by gastrointestinal microecological imbalance.ResultsLactic acid bacteria (LAB) strain with good exopolysaccharide (EPS) producing ability, namely, Lacticaseibacillus paracasei ZFM54 (L. paracasei ZFM54) was screened. The fermentation conditions of L. paracasei ZFM54 for EPS production were optimized. The EPS54 was characterized by chemical component and monosaccharide composition determination, UV, FT-IR and NMR spectra analysis. Cango red, SEM, AFM and XRD analysis were conducted to characterize the structure of EPS54. The EPS54 effectively reduced the colonization of Helicobacter pylori to AGS cells and recovered the cell morphology. EPS54 could also effectively alleviate the gastritis in the H. pylori-infected mice by down-regulating the mRNA expression levels of pro-inflammatory cytokines IL-6, IL-8, IL-1β and TNF-α and up-regulating the mRNA expression of inflammatory cytokine IL-10 in gastric cells. EPS54 was also found to be able to positively regulate the structure of gastric microbiota.ConclusionThe EPS 54 from L. paracasei ZFM54 can alleviate gastritis in H. pylori-infected mice by modulating the gastric microbiota.

A study on infertility in China found that while 543 health care institutions are approved for assisted reproductive technology (ART), only 10.1% offer all ART services, with a significant skew toward the eastern regions, highlighting the accessibility challenges faced by rural and remote populations; this study recommends government measures including travel subsidies and education initiatives to improve ART access for economically disadvantaged individuals.

IntroductionLarge Language Models (LLMs) play a crucial role in clinical information processing, showcasing robust generalization across diverse language tasks. However, existing LLMs, despite their significance, lack optimization for clinical applications, presenting challenges in terms of illusions and interpretability. The Retrieval-Augmented Generation (RAG) model addresses these issues by providing sources for answer generation, thereby reducing errors. This study explores the application of RAG technology in clinical gastroenterology to enhance knowledge generation on gastrointestinal diseases.MethodsWe fine-tuned the embedding model using a corpus consisting of 25 guidelines on gastrointestinal diseases. The fine-tuned model exhibited an 18% improvement in hit rate compared to its base model, gte-base-zh. Moreover, it outperformed OpenAI’s Embedding model by 20%. Employing the RAG framework with the llama-index, we developed a Chinese gastroenterology chatbot named “GastroBot,” which significantly improves answer accuracy and contextual relevance, minimizing errors and the risk of disseminating misleading information.ResultsWhen evaluating GastroBot using the RAGAS framework, we observed a context recall rate of 95%. The faithfulness to the source, stands at 93.73%. The relevance of answers exhibits a strong correlation, reaching 92.28%. These findings highlight the effectiveness of GastroBot in providing accurate and contextually relevant information about gastrointestinal diseases. During manual assessment of GastroBot, in comparison with other models, our GastroBot model delivers a substantial amount of valuable knowledge while ensuring the completeness and consistency of the results.DiscussionResearch findings suggest that incorporating the RAG method into clinical gastroenterology can enhance the accuracy and reliability of large language models. Serving as a practical implementation of this method, GastroBot has demonstrated significant enhancements in contextual comprehension and response quality. Continued exploration and refinement of the model are poised to drive forward clinical information processing and decision support in the gastroenterology field.

Abstract Background Peripheral blood carries a reservoir of mRNAs that regulate cardiac structure and function potential. Although it is well recognized that the typical symptoms of Myxomatous Mitral Valve Disease (MMVD) stage B2 are long-standing hemodynamic disorder and cardiac structure remodeling caused by mitral regurgitation, the transcriptomic alterations in blood from such dogs are not understood. Results In the present study, comparative high-throughput transcriptomic profiling of blood was performed from normal control (NC) and naturally-occurring MMVD stage B2 (MMVD) dogs. Using Weighted Gene Co-expression Network Analyses (WGCNA), Gene Ontology (GO), and Kyoto Encyclopedia of Gene and Genomes (KEGG), we identified that the turquoise module was the most highly correlated with echocardiographic features and found 64 differentially expressed genes (DEGs) that were significantly enriched in platelet activation related pathways. Therefore, from the turquoise module, we selected five DEGs (MDM2, ROCK1, RIPK1, SNAP23, and ARHGAP35) that, according to real-time qPCR, exhibited significant enrichment in platelet activation related pathways for validation. The results showed that the blood transcriptional abundance of MDM2, ROCK1, RIPK1, and SNAP23 differed significantly (P

ABSTRACT: The pathogenesis of inflammatory bowel disease may be related to local inflammatory damage and disturbances in intestinal microecology. Probiotic therapy is a safe and effective therapeutic approach. Considering that fermented milk is accepted and enjoyed by many people as a daily dietary intervention strategy, its potential to alleviate dextran sulfate sodium (DSS)–induced chronic colitis in mice needs to be explored. In this study, we evaluated the therapeutic effects of Lactiplantibacillus plantarum ZJ316–fermented milk by establishing a mouse model of DSS-induced chronic colitis. The results showed that the disease severity and colonic lesions of inflammatory bowel disease were effectively alleviated by ingestion of fermented milk. At the same time, the expression of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) effectively decreased, and the expression of antiinflammatory cytokines (IL-10) increased. Results based on 16S rRNA gene sequencing indicated that the structure and diversity of intestinal microorganisms changed markedly by intake of L. plantarum ZJ316–fermented milk, and fermented milk reduced the abundance of harmful bacteria (Helicobacter) while promoting the growth of beneficial bacteria (Faecalibacterium, Lactiplantibacillus, and Bifidobacterium). Additionally, the levels of short-chain fatty acids (acetic acid, propionic acid, butyric acid, pentanoic acid, and isobutyric acid) were also increased. In conclusion, the intake of L. plantarum ZJ316–fermented milk can alleviate chronic colitis by suppressing the inflammatory response and regulating intestinal microbiota.

With the increasing of renewable energy penetration rate in power source structure, the impact of its uncertainty on the stability of the power system is becoming increasingly apparent. The power system faces dual pressures of ensuring power supply and renewable energy accommodation. The way in which to accurately plan the power structure under situations with a high renewable energy penetration rate has become an urgent issue for future power infrastructure upgrading. In this paper, a rational power structure model was proposed for a provincial power grid by iteratively optimizing variables. The synergistic relationship between renewable energy, traditional power sources, and the energy storage system was considered comprehensively and calculated through the time-series production simulation method. The as-proposed model was studied using a scenario of a provincial grid plan in the year 2035. The power balance, electricity consumption, and renewable energy utilization were systematically analyzed, providing an important theoretical basis for the optimization and upgrading of provincial power systems under the rapid growth of renewable energy.

Aristolochic acid nephropathy (AAN) is a rapidly progressive renal interstitial fibrosis caused by medical or environmental exposure to aristolochic acid (AA). Since the outbreak of AAN in Belgium was reported nearly 30 years ago, the safety of herbal remedies has drawn considerable attention, and AAN has become a global public health problem. Breakthroughs have been made to better understand the disease, including the toxicity of AAs, the possible mechanisms of AAN, the disease patterns, and the pathological features; however, some critical problems remain unresolved. Because of the insidious onset of the disease, the incidence of AAN and the prevalence of exposure to AAs are unknown and might be largely underestimated. During the past decades, AA-containing herbs have been strictly administrated in many regions and the occurrence of AAN has declined sharply, yet cases of AAN are still sporadically reported. Despite the progress in the understanding of the disease’s pathogenesis, there is no effective treatment for delaying or reversing the renal deterioration caused by AAN. Therefore, the risk of exposure to AAs should be taken seriously by public health workers and clinicians. In this review, we updated the latest data on AAN, summarized the advances throughout these years, and put forward some challenges for future research.

The aim of this study was to purify angiotensin I-converting enzyme (ACE) inhibitory glycopeptide from quinoa fermented by Mucor wutungkiao and Rhizopus oryzae. The fermentation process conditions were optimized by a single factor experiment and a response surface experiment. The fermentation liquid was separated and purified by vacuum concentration, alcohol precipitation, Sephadex G-15 and reverse-phase high performance liquid chromatography. Fourier infrared spectroscopy was used to determine the composition of functional groups and β-elimination method to determine the glycopeptide bonding type. The effects of temperature, pH, metal ions, and in vitro simulated digestion on the activity were analyzed. The results showed that the optimal fermentation parameters were as follows: 8.7 d of fermentation time, 2.8% (φ) of total inoculum size containing Mucor wutungkiao to Rhizopus oryzae in a volume ratio of 1:1, and 1:18 g/mL of a solid-liquid ratio. The ACE inhibition rate was 64.22%±4.57%. A novel glycopeptides F3b, was isolated and purified by ethanol precipitation, Sephadex G-15, and reverse-phase high performance liquid chromatography. Fourier-transform infrared spectroscopy proved the presence of polypeptides and polysaccharides in F3b, and β-elimination reaction further demonstrated that the glycoprotein was an O-linked type. In vitro stability results indicate that the ACE inhibitory activity of glycopeptides was hardly changed under heating conditions from 25 to 55 ℃, and was 86.23%±3.47% of the original activity at 100 °C. Conversely, pH (from 2 to 12) had no significant effect (P>0.05) on the ACE inhibitory activity of glycopeptides. 4 mmol/L of Zn2+ and Fe3+ increased the ACE inhibitory activity of F3b to 109.91%±8.12% and 117.43%±6.78% of the control, respectively. While same concentration of K+ and Ca2+ reduced the ACE inhibitory activity to 78.94%±2.18% and 85.31%±4.99% of the control, respectively. After simulated gastrointestinal digestion, the ACE inhibitory activity of F3b decreased to 70.00%±3.30% of the control. In summary, this study could enrich the variety of ACE inhibitory peptides and provide technical reference for high-value utilization of quinoa.

Abstract B cell receptor associated protein 31 (BAP31) is closely associated with tumor progression, while the role and mechanism of BAP31 in gastric cancer (GC) remains unknown. This study explored that BAP31 was upregulated in GC tissues and high expression indicated poor survival of GC patients. BAP31 knockdown inhibited cell growth and induced G1/S arrest. Moreover, BAP31 attenuation increased the lipid peroxidation level of the membrane and facilitated cellular ferroptosis. Mechanistically, BAP31 regulated cell proliferation and ferroptosis by directly binding to VDAC1 and affected VDAC1 oligomerization and polyubiquitination. HNF4A was bound to BAP31 at the promoter and increased its transcription. Furthermore, knockdown of BAP31 inclined to make GC cells vulnerable to 5-FU and ferroptosis inducer, erastin, in vivo and in vitro. Our work suggests that BAP31 may serve as prognostic factor for gastric cancer and act as potential therapeutic strategy for gastric cancer.

Purpose – This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon emission trading. Design/methodology/approach – In view of the strong uncertainty of wind power and photovoltaic power generation in GVPP, the information gap decision theory (IGDT) is used to measure the uncertainty tolerance threshold under different expected target deviations of the decision-makers. To verify the feasibility and effectiveness of the proposed model, nine-node energy hub was selected as the simulation system. Findings – GVPP can coordinate and optimize the output of electricity-to-gas and gas turbines according to the difference in gas and electricity prices in the electricity market and the natural gas market at different times. The IGDT method can be used to describe the impact of wind and solar uncertainty in GVPP. Carbon emission rights trading can increase the operating space of power to gas (P2G) and reduce the operating cost of GVPP. Research limitations/implications – This study considers the electrical conversion and spatio-temporal calming characteristics of P2G, integrates it with VPP into GVPP and uses the IGDT method to describe the impact of wind and solar uncertainty and then proposes a GVPP near-zero carbon random scheduling optimization model based on IGDT. Originality/value – This study designed a novel structure of the GVPP integrating P2G, gas storage device into the VPP and proposed a basic near-zero carbon scheduling optimization model for GVPP under the optimization goal of minimizing operating costs. At last, this study constructed a stochastic scheduling optimization model for GVPP.

Introduction: The increasing incidence of diabetic kidney disease (DKD) and the challenges in its management highlight the necessity for a deeper understanding of its pathogenesis. While recent studies have underscored the substantial impact of circulating immunity on the development of diabetic microvascular complications such as retinopathy and neuropathy, research on circulating immunity in DKD remains limited. Methods: This study utilized Mendelian randomization analysis to explore the potential independent causal relationships between circulating immune cells and DKD pathogenesis. Additionally, a combination of single-cell disease relevance score (scDRS) and immune cell infiltration analysis was employed to map the circulating immunity landscape in DKD patients. Results: Ten immune traits, including 5 of B cells, 2 of T cells, 2 of granulocytes, and one of monocytes, were defined to be associated with the pathogenesis of DKD. Notably, IgD-CD27-B cell Absolute Count (IVW: OR, 1.102 [1.023–1.189], p = 0.011) and IgD-CD24-B cell Absolute Count (IVW: OR, 1.106 [1.030–1.188], p = 0.005) were associated with promoting DKD pathogenesis, while CD24+CD27+B cell %B cell (IVW: OR, 0.943 [0.898–0.989], p = 0.016) demonstrated a protective effect against DKD onset. The presence of B cell-activating factor receptor (BAFF-R) on CD20−CD38−B cell (IVW: OR, 0.946 [0.904–0.989], p = 0.015) and BAFF-R on IgD-CD38+B cell (IVW: OR, 0.902 [0.834–0.975], p = 0.009) also indicated a potential role in preventing DKD. scDRS analysis revealed that two main subsets of B cells, naïve B and memory B cells, had a higher proportion of DKD-related cells or a higher scDRS score of DKD phenotype, indicating their strong association with DKD. Furthermore, immune infiltrate deconvolution analysis showed a notable decrease in the circulating memory B cells and class-switched memory B cells in DKD patients compared to those of DM patients without DKD. Conclusion: Our study revealed the causal relations between circulating immunity and DKD susceptibility, particularly highlighted the potential roles of B cell subtypes in DKD development. Further studies addressing the related mechanisms would broaden the current understanding of DKD pathogenesis.

Based on the intermittent output and inverse peak regulation characteristics of wind power, a multisource peak regulation transaction optimization model that considers the feasibility of combining thermal power, energy storage, and demand response for both power generation and consumption is proposed in this paper. First, a multisource peak regulation transaction cost model is established by considering flexible load participation in peak regulation and price- and incentive-based demand responses. Subsequently, with the objective of minimizing both the peak regulation cost and wind curtailment rate, a reduced half gradient membership function is selected to transform the multiobjective model. Finally, by analyzing the roles of the different subjects in multisource peak regulation transactions, a compensation mechanism based on the Shapley method is designed, and a local power grid in northeast China is chosen as the simulation object. The results show the following: (1) When the thermal power generators (TPGs) transit from regular peak regulation to deep peak regulation, the wind curtailment rate decreases by 5.10%, and the peak regulation cost increases by $ 0.793 × 106. This indicates that the peak regulation cost of the TPGs and the income of the on-grid wind power need to be balanced. (2) When the energy storage and the demand response are combined for peak regulation, both the peak load regulation cost and wind curtailment rate reach the optimal values, decreasing by $ 0.642 × 106 and 5.72%, respectively, showing cooperative optimization. However, the TPGs require a higher regulation cost, whereas the other subjects achieve incremental benefits. (3) The compensation mechanism assists each subject in obtaining incremental benefits depending on the contribution rate. With the strengthening of the peak regulation of the TPGs, more energy storage and demand response output are introduced to meet the urgent peak regulation requirement, which leads to increased regulation revenue and optimal dispatching. In summary, the proposed transaction and compensation mechanism of multisource peak regulation can be used to balance the peak regulation ability and contributions of different subjects and establish the optimal peak regulation scheme.

To resolve a large number of discrete distributed energy resources clusters in rural areas, the electricity retailer (ER) is set as the agent of the distributed energy resources clusters by the way of virtual power plant (VPP), namely the electricity retailer (ER) integrated with virtual power plant (VPP-ER). Then, the electricity–carbon collaborative transaction mode is discussed, and a bi-level purchase–sale transaction optimal model. The upper-level model applies the conditional value-at-risk method (CVaR) to establish an electricity–carbon coordinated transaction model for rural VPP-ER. The lower-level model applies the robust optimization theory to measure the uncertainty risk of the power output of WPP, PV to establishes an optimal dispatching model for VPP. Thirdly, the model is converted into the Karush–Kuhn–Tucker (KKT) optimality conditions to solve the bi-level purchase–sale transaction model. Finally, the Henan Lankao industrial cluster is taken as an example, the results show (1) the proposed bi-level model can establish an optimal electricity–carbon coordinated trading scheme. (2) when the confidence level β belongs to [0.8, 0.9], the decision-maker is willing to bear risk to achieve excess trading returns. At this time, the equivalent carbon emissions of the total transaction electricity should be 1 ± 5% as the initial carbon emission quota and the risk weight λ should be 0.5. (3) When Γ belongs to [0.80, 0.90], the decision-makers are willing to measure the relationship between risks and returns and formulate a dispatching plan that conforms to their risk attitude. When the forecast error ρ fluctuates between (0.05, 0.15), the amplification effect of the forecast error on the uncertainty risk can be minimized. Overall, the findings of this study could provide an effective decision-making tool for rural VPP-ER in China’s electricity market.

Bacteriocins from lactic acid bacteria (LAB) have attracted widespread attention as a new type of biological preservative due to their safety, high efficiency, and non-toxic characteristics. In this study, we focused on Sakacin ZFM225, a novel bacteriocin produced by Lactobacillus sakei ZFM225, which was isolated from raw milk. It was purified by a strategy including precipitation with 70% ammonium sulfate, cation exchange chromatography and reverse-phase high performance liquid chromatography (RP-HPLC). The predicted molecular weight of Sakacin ZFM225 was 14950.92 Da. Sakacin ZFM225 exhibited resistance to high temperatures, strong activity under acidic conditions, and sensitivity to trypsin and pepsin. Bacteriocins from Lactobacillus sakei mainly inhibited the growth of Listeria monocytogenes. The bacteriocin possessed a broad-spectrum inhibition which could kill many foodborne pathogens such as Pseudomonas aeruginosa, Micrococcus luteus, and Staphylococcus aureus. We further demonstrated that the mode of action of Sakacin ZFM225 was related to the formation of cell membrane porosity, and excluded Lipid Ⅱ as its target. These results suggest that this new bacteriocin has great potential in food industry as a biological preservative and even medical field.

Abstract Intelligent wearable devices are essential for telemedicine healthcare as they enable real‐time monitoring of physiological information. Elaborately constructing synapse‐inspired materials provides a crucial guidance for designing high‐performance sensors toward multiplex stimuli response. However, a realistic mimesis both in the “structure and sense” of biological synapses to obtain advanced multi‐functions is still challenging but essential for simplifying subsequent circuit and logic programs. Herein, an ionic artificial synapse integrated with Ti3CNTx nanosheets in situ grown with zeolitic imidazolate framework flowers (ZIF‐L@Ti3CNTx composite) is constructed to concurrently mimic the structure and working mechanism of the synapse. The flexible sensor of the bio‐inspired ZIF‐L@Ti3CNTx composite exhibits excellent dual‐mode dimethylamine (DMA) and strain‐sensitive response with non‐overlapping resistance variations. The specific ions conduction working principle triggered by DMA gas or strain with the assistance of humidity is confirmed by the density functional theory simulation. Last, an intelligent wearable system is self‐developed by integrating the dual‐mode sensor into flexible printed circuits. This device is successfully applied in pluralistic monitoring of abnormal physiological signals of Parkinson's sufferers, including real‐time and accurate assessment of simulated DMA expiration and kinematic tremor signals. This work provides a feasible routine to develop intelligent multifunctional devices for upsurging telemedicine diagnosis.

To optimize the utilization of rural biomass waste resources (e.g., straw and solid waste), biomass waste energy conversion (BWEC) and carbon cycle utilization (CCU) are integrated into a traditional virtual power plant, i.e., a rural BWEC-CCU-based virtual power plant. Furthermore, a fuzzy robust two-stage dispatching optimal model for the BWEC-CCU-based virtual power plant is established considering the non-determinacy from a wind power plant (WPP) and photovoltaic (PV) power. The scheduling model includes the day-ahead deterministic dispatching model and real-time uncertainty dispatching model. Among them, in the day-ahead dispatching phase, the dispatching plan is formulated with minimum operating cost and carbon emission targets. In the real-time dispatching phase, the optimal dispatching strategy is formulated aiming at minimum deviation adjustment cost by applying the Latin hypercube sampling method. The robust stochastic theory is used to describe the uncertainty. Third, in order to achieve optimal distribution of multi-agent cooperation benefits, a benefit distribution strategy based on Nash negotiation is designed considering the three-dimensional interfering factor of the marginal benefit contribution, carbon emission contribution, and deviation risk. Finally, a rural distribution network in Jiangsu province, China, is selected for case analysis, and the results show that 1) the synergistic optimal effect of BWEC and CCU is obvious, and the operation cost and deviation adjustment cost could decrease by 26.21% and 39.78%, respectively. While the capacity ratio of WPP + PV, BWEC, and CCU is 5:3:2, the dispatching scheme is optimum. 2) This scheduling model can be used to formulate the optimal scheduling scheme. Compared with the robust coefficient Γ = 0, when Γ = 1, the WPP and PV output decreased by 15.72% and 15.12%, and the output of BWEC and CCU increased by 30.7% and 188.19%, respectively. When Γ∈ (0.3, 0.9), the growth of Γ has the most direct impact on the dispatching scheme. 3) The proposed benefit equilibrium allocation strategy can formulate the most reasonable benefit allocation plan. Compared with the traditional benefit allocation strategy, when the proposed method is used, the benefit share of the WPP and PV reduces by 5.2%, and the benefit share of a small hydropower station, BWEC, and CCU increases by 1.7%, 9.7%, and 3.8%, respectively. Overall, the proposed optimal dispatching and benefit allocation strategy could improve the aggregated utilization of rural biomass waste resources and distributed energy resources while balancing the benefit appeal of different agents.

With the rapid development of Internet technologies, the public can participate in the information communication of emergency events more conveniently and quickly. Once an emergency occurs, the public will immediately express and disseminate massive information about the causes, processes and results of the emergency. In the process of information communication, the public often adopts diversified communication modes, and then shows differential communication preferences. The detection of the public's communication preferences can more accurately understand the information demands of the public in events, and then contribute to the rational allocation of resources and improve the processing efficiency. Therefore, this paper conducted finer-grained mining on the public's online expressions in multiple events, so as to detect the public's communication preferences. Specifically, we collected the public's expressions related to emergency events from the social media and then we analyzed the expressions from multiple dimensions to obtain the corresponding communication features. Finally, based on the comparative analysis of diversified communication features, static and dynamic communication preferences were obtained. The experimental results indicate that the public's communication preferences do exist, which is universal and consistent. Meanwhile, constructing a better social environment and improving people's livelihood are the fundamental strategies to guide public opinion.

Background: Previous studies have shown a potential beneficial effect of endovascular therapy (EVT) in patients with acute basilar artery occlusion (BAO). It was unclear that whether atrial fibrillation (AF) can affect the clinical outcomes for BAO patients treated with EVT. Objectives: To investigate the association between AF and clinical outcomes, and whether AF can modify the efficacy and safety of EVT in patients with BAO. Design: We conducted a multicenter, nationwide, retrospective analysis to investigate how the presence of AF affects treatment allocation for BAO patients. Methods: The endovascular treatment for acute basilar artery occlusion (ATTENTION) registry was a multicenter, prospective study in China that included acute BAO patients who underwent EVT or received best medical management (BMM) between 2017 and 2021. The outcomes include the distribution of 3-month modified Rankin scale (mRS) score, functional independence (defined as mRS 0–3), symptomatic intracerebral hemorrhage, and mortality. Results: 2134 patients were included in the study, of which 619 had AF and 1515 did not have AF. The median age was 65 (interquartile range [IQR]: 56–73) years, and 689 (32.3%) patients were female. Multivariate regression analysis indicated no significant association existed between AF and the distribution of mRS (adjusted common odds ratio, 1.05 [95% CI: 0.88, 1.25]; p = 0.564) at 90 days. Similarly, AF was not found to have a significant association with and other measured outcomes, or with the effects of EVT in AF subgroups for at 90 days as measured by ordinal mRS ( p for heterogeneity = 0.247). Finally, no significant differences were found for symptomatic intracerebral hemorrhage and mortality within 90 days between the EVT and BMM groups across AF subgroups. Conclusions: Our results illustrated that the effect of EVT did not differ statistically in acute ischemic stroke patients with and without AF. Moreover, no significant association between AF and functional or safety outcomes could be detected at 90 days.

Under soybean–corn intercropping in China, quizalofop-p-ethyl is recommended as a herbicide for stem and leaf treatment after soybean seedling. Nonetheless, herbicide drift during spraying may lead to environmental contamination and damage to the corn plants. In order to clearly show the threshold of the drift deposition amount of quizalofop-p-ethyl that causes herbicide damage to corn, we used a bioassay spray tower to spray quizalofop-p-ethyl herbicide on corn in the laboratory and a boom sprayer to spray quizalofop-p-ethyl herbicide, which drifts to corn in the field, to study and evaluate the damage quizalofop-p-ethyl herbicide causes to corn under different spray volumes and drift deposition rates. The results showed that under a drift deposition rate of 1% of three spray volumes, the corn showed no symptoms of herbicide damage and their plant height was not inhibited 14 days after spray; under a spray volume of 150 L/ha and a drift deposition rate of 5%, the corn showed symptoms of mild herbicide damage but their plant height was not inhibited 14 days after spray, while the corn showed symptoms of moderate herbicide damage and their plant height was slightly and moderately inhibited, respectively, under the spray volumes of 300 L/ha and 450 L/ha; under drift deposition rates of 10% and 30% of three spray volumes, half or more of the corn in each treatment withered and their plant height was severely inhibited or completely inhibited. Under the same spray volume, the symptoms of herbicide damage and the inhibition rate of plant height increased with the increase in the drift deposition rate; under the same drift deposition amount, the symptoms of herbicide damage and the inhibition rate of plant height increased with a decrease in the spray volume. The effect of the drift deposition rate on the symptoms of herbicide damage and plant height was extremely significant, but the spray volume was not significant. The drift deposition rates for 10% inhibition and no inhibition of corn plant height were 5.70% (R10) and 5.05% (R0) under spray volume of 150 L/ha, 4.56% (R10) and 1.23% (R0) under 300 L/ha, and 3.31% (R10) and 1.86% (R0) under 450 L/ha, respectively. When the herbicide was sprayed in the field using a soybean–corn-dedicated plant protection machine under the spray volume of 450 L/ha, the drift deposition rate ranged from 1.22% to 1.69%, and the corn did not produce symptoms of herbicide damage and plant height was not inhibited 14 days after the spray. In actual weeding operations, it is better to ensure that the drift deposition rate of quizalofop-p-ethyl is below R0 by setting reasonable operational parameters, using anti-drift nozzles or additives, and so on, and, at most, not more than R10. This study clarified the drift hazard of quizalofop-p-ethyl herbicide on corn and the safety value of the herbicide drift deposition amount, which provided data support for the standardized use of quizalofop-p-ethyl herbicide under soybean–corn intercropping and guidance for the safe production of field corn.

Pesticide application is an essential means of controlling plant diseases and pests in citrus orchards. In recent years, fixed spraying systems have gradually been used as alternatives to traditional sprayers and manual sprayers in some hilly citrus orchards. In this paper, influences of fixed system spraying parameters, such as droplet size and spraying height, on spraying quality were elucidated and analyzed. The performances of two nozzle types, pressure-swirl nozzles and fixed spray plate sprinklers, were assessed and compared by effective droplet coverage ratio (DCR), droplet distribution uniformity coefficient of variation (CV), and droplet penetration ratio (DPR). The results showed that appropriately increasing droplet size and spraying height could improve the DCR and distribution uniformity of pressure-swirl nozzles. The DCR and distribution uniformity of fixed spray plate sprinklers had a positive correlation with droplet size, while spraying height had no significant effect on these variables. Additionally, with the increase in droplet size, DPR initially increased and then gradually decreased. The optimized results showed that the optimal parameters for pressure-swirl nozzles were a droplet size of 240 μm and spraying height of 100 cm, while for fixed spray plate sprinklers, the results were a droplet size of 240 μm and spraying height of 50 cm. Comparison results showed that the spraying quality of fixed spray plate sprinklers was better overall, with values of DCR, CV, and DPR being 37.15%, 24.20%, and 71.67%, respectively, while the corresponding values for pressure-swirl nozzles were 39.65%, 35.41%, and 56.02%. Based on the above results and the occurrence rule of citrus pests and disease, the optimal spraying parameters of fixed spraying systems were selected to control the Asian citrus psyllid Diaphorina citri. Furthermore, the effect of fixed spraying systems on controlling Diaphorina citri reached the maximum at 3 days after spraying, which was 97.83%, and the effect declined at 14 days after spraying, which was 85.47%. This study provides valuable scientific references for guiding the application of fixed spraying systems in hilly citrus orchards.

Adjuvants are frequently incorporated into crop protection operations to modulate the droplet characteristics by diminishing the surface tension (ST) and contact angle (CA), thereby positively influencing the wetting and spreading behavior of the droplets. However, there are no quantitative conclusions on the extent to which the amount of adjuvant added affects droplet properties. Therefore, the decision to add spraying adjuvants in actual pesticide spraying operations relies on the operator’s experience. In this study, we investigated the effect of a surfactant additive (KAO A-200) on the droplet properties and deposition of prochloraz emulsion in water (PEW) solution for crop protection in unmanned aerial vehicle (UAV) aerial spraying. Three KAO A-200 additive concentrations of 0.42%, 0.83% and 1.67% and four solution concentrations of 2.5%, 3.33%, 4.17% and 5% of PEW were set to evaluate the droplet properties of PEW solution with ST and CA as assessment indicators. The results show that the average STs of adjuvant solution droplets tended to decrease as the concentration of KAO A-200 increased. According to the optimal concentration, the KAO A-200 addition concentration of 0.83% was therefore determined to be the most appropriate dosage. With the appropriate KAO A-200 dosage condition, the results show that the average STs increased as PEW solution concentration increased, while the average CAs of PEW solution droplets showed a first decreasing and then increasing trend. The “4.17% concentration PEW (22.5 g a.i./1.2 L) + 0.83% concentration KAO A-200” condition was selected as the optimized combination for crop protection UAV field aerial spraying tests. The test showed that the coverage rate of PEW solution droplets on the upper and lower layers of oilseed rape canopy increased by 71.47% and 41.55%, the deposition density increased by 71.91% and 98.45%, and the coefficient of variation in droplet deposition decreased by 44.41% and 48.13%, respectively. These results are significantly better than those obtained without the adjuvant addition.

Aberrant expression of SNX5 can contribute to tumorigenesis, invasion, and metastasis of several human cancers. However, the clinicopathological and biological significance of SNX5 in clear cell renal cell carcinoma (ccRCC) remain unclear. In this study, we found that SNX5 expression was downregulated and negatively correlated with tumor size, American Joint Committee on Cancer stage, tumor thrombus of inferior vena cava, and poor prognosis in human ccRCC. Ectopic expression of SNX5 inhibited ccRCC cell proliferation and metastasis, whereas knockdown of SNX5 increased these activities both in vitro and in vivo. Mechanistically, overexpression of SNX5 blocked internalization and intracellular trafficking of CD44 in ccRCC cells. Knockdown of SNX5 was associated with epithelial-to-mesenchymal transition (EMT) in ccRCC cells. Overexpression of SNX5 inhibited TGF-β-induced migration, invasion, and EMT in ccRCC cells. KLF9 directly bound to the SNX5 promoter and increased SNX5 transcription. Moreover, we found that the combination of SNX5 and CD44 or E-cadherin or KLF9 was a more powerful predictor of poor prognosis than either parameter alone. Collectively, our data reveal a mechanism that KLF9-mediated SNX5 expression was associated with poor prognosis via trafficking of CD44 and promoting EMT in ccRCC. SNX5 may be a potential prognostic biomarker and therapeutic target for patients with ccRCC.

The relationship between chronic psychological stress and tumorigenesis has been well defined in epidemiological studies; however, the underlying mechanism remains underexplored. In this study, we discovered that impaired macrophage phagocytosis contributed to the psychological stress-evoked tumor susceptibility, and the stress hormone glucocorticoid (GC) was identified as a principal detrimental factor. Mechanistically, GC disturbed the balance of the “eat me” signal receptor (low-density lipoprotein receptor-related protein-1, LRP1) and the “don't eat me” signal receptor (signal regulatory protein alpha, SIRPα). Further analysis revealed that GC led to a direct, glucocorticoid receptor (GR)-dependent trans-repression of LRP1 expression, and the repressed LRP1, in turn, resulted in the elevated gene level of SIRPα by down-regulating miRNA-4695-3p. These data collectively demonstrate that stress induces the imbalance of the LRP1/SIRPα axis and entails the disturbance of tumor cell clearance by macrophages. Our findings provide the mechanistic insight into psychological stress-evoked tumor susceptibility and indicate that the balance of LRP1/SIRPα axis may serve as a potential therapeutic strategy for tumor treatment.

BackgroundThe associations between preoperative transfer to hemodialysis (HD) and postoperative outcomes in patients on chronic peritoneal dialysis (PD) remain unknown. We conducted this retrospective cohort study to investigate whether preoperative HD could influence surgical outcomes in PD patients undergoing major surgeries.MethodsAll chronic PD patients who underwent major surgeries from January 1, 2007, to December 31, 2020, at Peking University First Hospital were screened. Major surgery was defined as surgical procedures under general, lumbar or epidural anesthesia, with more than an overnight hospital stay. Patients under the age of 18, with a dialysis duration of less than 3 months, and those who underwent renal implantation surgeries and procedures exclusively aimed at placing or removing PD catheters were excluded. Patients involved were divided into either HD or PD group based on their preoperative dialysis status for further analysis.ResultsOf 105 PD patients enrolled, 65 continued PD, and 40 switched to HD preoperatively. Patients with preoperative HD were significantly more likely to develop postoperative hyperkalemia. The total complication rates were numerically higher in patients undergoing preoperative HD. After adjustment, the incidence of postoperative hyperkalemia or any other postoperative complication rates were similar between groups. There were no differences in long-term survival between the two groups.ConclusionsIt does not seem indispensable for PD patients to switch to temporary HD before major surgeries.

Background: Clinical diagnosis and treatment of tumors are greatly complicated by their heterogeneity, and the subtype classification of cancer frequently plays a significant role in the subsequent treatment of tumors. Presently, the majority of studies rely far too heavily on gene expression data, omitting the enormous power of multi-omics fusion data and the potential for patient similarities.Method: In this study, we created a gastric cancer subtype classification model called RRGCN based on residual graph convolutional network (GCN) using multi-omics fusion data and patient similarity network. Given the multi-omics data’s high dimensionality, we built an artificial neural network Autoencoder (AE) to reduce the dimensionality of the data and extract hidden layer features. The model is then built using the feature data. In addition, we computed the correlation between patients using the Pearson correlation coefficient, and this relationship between patients forms the edge of the graph structure. Four graph convolutional network layers and two residual networks with skip connections make up RRGCN, which reduces the amount of information lost during transmission between layers and prevents model degradation.Results: The results show that RRGCN significantly outperforms other classification methods with an accuracy as high as 0.87 when compared to four other traditional machine learning methods and deep learning models.Conclusion: In terms of subtype classification, RRGCN excels in all areas and has the potential to offer fresh perspectives on disease mechanisms and disease progression. It has the potential to be used for a broader range of disorders and to aid in clinical diagnosis.

Abstract China's Green Space System Planning (GSSP) research has gradually expanded from central urban areas to municipal and provincial scales in recent years. Besides, the research on the role of green space in the water environment has also attracted much attention. However, the study of green corridors usually ignored hydrological data, which widespread absence especially in the large area scale. And the scale of green corridor construction mainly focused on central urban areas. This paper took China's Fujian province as an example. Based on the DEM elevation data, the article identified blue corridors without hydrological data. In addition, the green corridors were determined based on the land use data. According to the green corridors and blue corridors protection, we identified the ecological networks and nodes by the network analysis method. The results showed that the blue corridors identified by DEM data were consistent with the hydrological status quo. The regional status of the identified ecological networks and nodes were basically in line with their characteristics, proving the value of the planning methods. Finally, based on the identification results, suggestions for Fujian's ecological networks and nodes are put forward.

Abstract To identify differential metabolites and metabolic pathways and provide guidance for the novel biomarkers for diagnosis and prognosis of amyotrophic lateral sclerosis (ALS). ALS patients and people without nervous diseases were recruited. Metabolomic analysis was performed using gas chromatography-mass spectrometry (GC/MS). The orthogonal projections to latent structures discriminant analysis (OPLS-DA) were used to identify differential metabolites. Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst were used to identify metabolic pathways. 75 metabolites were detected and aligned. The OPLS-DA showed the metabolomic profile of ALS patients and those in the fast-progression and slow-progression ALS groups differed from that of CTRL (p

Abstract Generally, in order to guarantee a good throughput and decrease the complexity of reassembling, the majority of current commodity routers take elaborate closed‐loop flow control schemes such as back pressure to prevent cell loss in the switch fabrics. As commodity router's port number grows larger and link rate becomes faster, the huge I/O pins and memory consumption makes these closed‐loop flow controls very difficult to implement engineeringly. This paper approaches the problem of building ultra‐large‐capacity router from a different angle. Crosspoint‐queued‐based Parallel Packet Switch (CQPPS), a highly scalable switch architecture with no need of any closed‐loop flow control schemes, is proposed. And the authors propose the Padded Frame plus Round‐Robin scheduling scheme for CQPPS architecture. By allowing potential cell loss in the switch fabrics and slightly higher light‐load delay, CQPPS achieves loss rate orders of magnitudes lower than back pressure schemes, and high‐load delay 10 times less than back pressure schemes. It also greatly reduces the complexity of engineering implementation.

Saltmarshes in coastal wetlands provide important ecosystem services. Satellite remote sensing has been widely used for mapping and classification of saltmarsh vegetation, however, medium-spatial-resolution satellite datasets such as Landsat-series imagery may induce mixed pixel problems over saltmarsh landscapes which are spatially heterogeneous. Sub-pixel fractional cover estimation of saltmarsh vegetation at species level are required to better understand the distribution and canopy structure of saltmarsh vegetation. In this study, we presented an approach framework for estimating and mapping the fractional cover of major saltmarsh species in the Yellow River Delta, China based on time series Landsat 8 Operational Land Imager data. To solve the problem that the coastal area is frequently covered by clouds, we adopted the recently developed virtual image-based cloud removal (VICR) algorithm to reconstruct missing image values under the cloud/cloud shadows over the time series Landsat imagery. Then, we developed an ensemble learning model (ELM), which incorporates Random Forest Regression (RFR), K-Nearest Neighbor Regression (KNNR) and Gradient Boosted Regression Tree (GBRT) based on temporal-spectral features derived from the time-series cloudless images to estimate the fractional cover of major vegetation types, i.e., Phragmites australis, Suaeda salsa and the invasive species, Spartina alterniflora. High spatial resolution imagery acquired by the Unmanned Aerial Vehicle and Gaofen-6 satellites were used for reference sample collections. The results showed that our approach successfully estimated the fractional cover of each saltmarsh species (average of R-square:0.891, RMSE: 7.48%). Through four scenarios of experiments, we found that the ELM is advantageous over each individual model. When the images during key months were absent, cloud removal for the Landsat images considerably improved the estimation accuracies. In the study area, Spartina alterniflora covers the largest area (5753.97 ha), followed by Phragmites australis with spatial extent area of 4208.4 ha and Suaeda salsa of 1984.41 ha. The average fractional cover of S. alterniflora was 58.45%, that of P. australis was 51.64% and that of S.salsa was 51.64%.

The recent surge in demand for natural preservatives has ushered in a new era of research into novel bacteriocins capable of effectively combating food-borne infections. In this study, the bacteriocin from Lacticaseibacillus rhamnosus ZFM216, which has a molecular mass of 11851.9 Da, was purified using macroporous resin, gel chromatography, and reversed-phase high performance liquid chromatography. This bacteriocin could inhibit both Gram-positive and Gram-negative bacteria. It had a strong inhibitory effect on Staphylococcus aureus D48 with minimum inhibitory concentration values of 1.75 μM. Bacteriocin ZFM216 was heat stable and showed pH stability under weakly acidic conditions. It was sensitive to pepsin, proteinase K and trypsin. Electron microscopy results showed that when treated with bacteriocin ZFM216, S. aureus D48 was severely deformed, the cell structure was obviously changed, and the intracellular electrolyte leaked to the outside of the cell. Bacteriocin ZFM216 caused the ATP level of the indicator to decrease, the conductivity to sharply increase, and the transmembrane potential difference (ΔΨ) to instantaneously decrease. This research formed the basis for further development and utilization of bacteriocin ZFM216 which has potential in the food industry.

Ferroptosis is a novel regulatory cell death, which is characterized by iron dependency and mainly caused by accumulation of intracellular lipid peroxides and reactive oxygen species. Ferroptosis plays an important role in the occurrence and development of a variety of malignant tumors, especially in anti-tumor treatment. As an emerging treatment method, the immunotherapy has been widely applied in the clinical practice, and the role of ferroptosis in tumor immunotherapy has been gradually explored. This study aims to illustrate the features of ferroptosis, and its role in anti-tumor immunotherapy and potential clinical application.

BackgroundAcute kidney injury (AKI) is a severe clinical syndrome that places a massive burden on medical systems worldwide, yet the seasonality of AKI remains unexplored in China. The aim of this study was to describe the seasonal variation in the detection rate and all-cause in-hospital mortality of AKI in China based on a nationwide cohort study.MethodsThis was a retrospective cohort recruiting a national sample of 7,291 adult patients treated in hospitals in 22 provinces of mainland China during January or July 2013. AKI was defined according to the 2012 Kidney Disease Improving Global Outcomes AKI creatinine criteria or expanded criteria of increase or decrease in serum creatinine level of 50% during the hospital stay. The seasonal group was determined according to the corresponding admission date for each patient. The detection rate of AKI refers to the ratio of identified AKI cases to the total number of adult admissions from the same regional or seasonal group.ResultsBoth the detection rate (2.31 vs. 2.08%, p = 0.001) and in-hospital mortality rate (13.3 vs. 10.7%, p = 0.001) of AKI were higher in winter than in summer. The patients with AKI detected in winter had higher proportions of prehistory diseases, cardiac or vascular kidney injury factors, and severe comorbidities than those in summer (all p < 0.05). In the multivariable analysis, winter was an independent risk factor for in-hospital mortality of patients with AKI [odds ratio (OR) = 1.22, 95% confidence interval (CI), 1.03–1.44, p = 0.02] after adjusting for demographic factors, medical history, comorbidity, and climatic confounders. Higher ambient temperature (OR = 0.91, 95% CI, 0.86–0.97, p = 0.002, per 10°C increase), higher relative humidity level (OR = 1.14, 95% CI, 1.04–1.25, p = 0.005, per 10% increase), and living in temperate continental region (OR = 2.18, 95% CI, 1.63–2.91, p < 0.001) were each independently associated with in-hospital mortality.ConclusionThe detection rate and all-cause in-hospital mortality of AKI showed a winter predominance in patients with AKI in China. Winter appeared to be an independent risk factor for all-cause in-hospital mortality in patients with AKI. Environmental factors, including lower ambient temperature, higher relative humidity level, and living in temperate continental climatic regions, were each independently associated with increased risks of in-hospital mortality in patients with AKI.

Plant protection unmanned aircraft vehicles (UAVs) were developed rapidly in China. The operation performances of different models of UAVs were different. This paper systematically studied droplet deposition distribution; pesticide-mixture utilization rate; operational efficiency; wheat-disease control efficacy; and a comprehensive score of three types of UAVs, a boom sprayer, and a knapsack sprayer. The results showed the descending order of the droplet penetration rate of the pesticide application equipment (PAE) was boom sprayer; UAVs; and knapsack sprayer. The pesticide-mixture utilization rates of the UAVs and boom sprayer were more than 50% while that of the knapsack electric sprayer was only 27.8%. The UAVs’ average labor productivity was 5.75 ha per man-hour, which was slightly less than that of the boom sprayer and 21.3 times that of the knapsack sprayer. The control efficacy of each machine on wheat Fusarium head blight was more than 90%. The average performance comprehensive score of the UAVs was 0.812, which was slightly lower than the score of 0.929 for the 3WPZ-700 self-propelled boom sprayer but much higher than the score of 0.399 for the 3WBD-18 knapsack electric sprayer. The results clearly showed the potential of UAVs for improving the pesticide-mixture utilization rate and operational efficiency, as well as the wheat Fusarium head blight control efficacy.

Helicobacter pylori is the most prevalent pathogen causing chronic gastritis, gastroduodenal ulcers, and gastric tumors and is asymptomatically present in 50% of the world's population. This research is focused on investigating the effect of Lactobacillus paracasei ZFM 54 (CCTCC NO:2016667) on attenuating H. pylori-induced gastritis. H. pylori ZJC03 isolated from a patient with gastritis harbored the virulence genes of vacA and cagA and was highly resistant to metronidazole (MIC > 256 μg/mL). In vitro analysis revealed that the potential anti-H. pylori characteristics of L. paracasei ZFM54 in terms of 65.57 ± 1.87% survival rate in simulated gastric juices at a pH of 2.0, 69.00 ± 2.73% auto-aggregation, 30.28 ± 2.24% co-aggregation, 70.27 ± 2.23% urease inhibition, and 57.89 ± 1.27% radical scavenging. In H. pylori infectious mice, L. paracasei ZFM54 pre- and post-treatment reduced the levels of malondialdehyde in liver tissues to 0.71 ± 0.04 nmol/mgprot (p < 0.05) and 0.70 ± 0.06 nmol/mgprot (p < 0.05), respectively. Glutathione levels were increased to 1.78 ± 0.02 μmol/gprot (p < 0.05) and 1.76 ± 0.52 μmol/gprot (p < 0.05), respectively. L. paracasei ZFM54 significantly inhibited H. pylori-mediated inflammation observed in gastric mucosal repair and downregulated the mRNA expression of pro-inflammatory cytokines IFN-γ, IL-1β, and IL-6 (p < 0.01). Importantly, L. paracasei ZFM54 increased Firmicutes and Actinobacteriota and decreased the relative abundance of bacterial taxa belonging to Campilobacterota and Proteobacteria. With the preventive and therapeutic administration of L. paracasei ZFM54, significant reductions in the average relative abundance of genera Helicobacter, Muribaculum, Staphylococcus, Lachnospiraceae_NK4A136_group, Prevotellaceae_UCG-001, Alloprevotella, and Oscillibacter were observed compared to infected mice. These findings suggest that L. paracasei ZFM 54 has the potential to protect against H. pylori infection by ameliorating inflammation and restoring the gastric microbiota.

This study aimed to evaluate the possible anti-obesity effects of orlistat and ezetimibe and determine the mechanism by which they alter the composition of gut microbiota and short-chain fatty acids (SCFAs) in mice with a high-fat diet (HFD)-induced obesity. Eighty male, specific pathogen-free C57BL/6J mice aged 3 weeks were divided into four groups (n = 20). The NCD group was fed with a normal diet, and the HFD, HFD+ORL, and HFD+EZE groups were fed with HFD for 20 weeks. From the 13th week onward, the HFD+ORL and HFD+EZE groups were administered with orlistat and ezetimibe, respectively. The glucose and lipid metabolism of the tested mice were evaluated by analyzing blood biochemical indicators during the intervention. Furthermore, the changes in the structure of the fecal microbiota and the fecal SCFA content were analyzed by 16S rRNA sequencing and gas chromatography-mass spectrometry, respectively. HFD induced the obesity phenotype in mice. Compared to the HFD group, the body weight, visceral fat-to-body weight ratio, serum total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), and oral glucose tolerance test (OGTT) of the HFD+ORL group significantly decreased, whereas fecal butyric acid levels significantly increased. Ezetimibe intervention significantly reduced the OGTT, serum TC, and HDL-C levels only. The α-diversity of the gut microbiota significantly decreased after intervention with orlistat and ezetimibe. Orlistat altered the relative abundance of some bacteria in the fecal microbiota. The populations of Firmicutes, Alistipes, and Desulfovibrio decreased, whereas those of Verrucomicrobia and Akkermansia significantly increased. Ezetimibe caused changes only in some low-abundance bacteria, as manifested by a decrease in Proteobacteria and Desulfovibrio, and an increase in Bacteroides. The administration of orlistat and ezetimibe can characteristically influence the body weight and serum lipid metabolism, and glucolipid levels in diet-induced obese mice and is accompanied by significant changes in the gut microbiota and SCFAs. These results suggest that the two drugs might exert their own specific anti-obesity effects by modulating the gut microbiota in a different manner. The enhanced health-promoting effect of orlistat might result from its stronger ability to alter the gut microbiota and SCFAs, at least partly.

BackgroundAcute myocardial infarction (AMI) is one of the major causes of mortality and disability worldwide, and ischemic stroke (IS) is a serious complication after AMI. In particular, patients with ST-segment–elevation myocardial infarction (STEMI) are more susceptible to IS. However, the interrelationship between the two disease mechanisms is not clear. Using bioinformatics tools, we investigated genes commonly expressed in patients with STEMI and IS to explore the relationship between these diseases, with the aim of uncovering the underlying biomarkers and therapeutic targets for STEMI-associated IS.MethodsDifferentially expressed genes (DEGs) related to STEMI and IS were identified through bioinformatics analysis of the Gene Expression Omnibus (GEO) datasets GSE60993 and GSE16561, respectively. Thereafter, we assessed protein-protein interaction networks, gene ontology term annotations, and pathway enrichment for DEGs using various prediction and network analysis methods. The predicted miRNAs targeting the co-expressed STEMI- and IS-related DEGs were also evaluated.ResultsWe identified 210 and 29 DEGs in GSE60993 and GSE16561, respectively. CD8A, TLR2, TLR4, S100A12, and TREM1 were associated with STEMI, while the hubgenes, IL7R, CCR7, FCGR3B, CD79A, and ITK were implicated in IS. In addition, binding of the transcripts of the co-expressed DEGs MMP9, ARG1, CA4, CRISPLD2, S100A12, and GZMK to their corresponding predicted miRNAs, especially miR-654-5p, may be associated with STEMI-related IS.ConclusionsSTEMI and IS are related and MMP9, ARG1, CA4, CRISPLD2, S100A12, and GZMK genes may be underlying biomarkers involved in STEMI-related IS.

Methods for selective modification of the N-terminus of proteins are of high interest, but mostly require specific amino acid residues. Here, the authors report a selective and fast method for N-terminal modification of proteins based on quinone-mediated oxidation of the alpha-amine to aldehyde or ketone, and apply it to diverse proteins.

Abstract. Crohn disease and ulcerative colitis are the two main manifestations of inflammatory bowel disease (IBD), and both are highly morbid. However, the precise etiology of IBD is still unknown and effective therapeutics are yet to be discovered. It is becoming increasingly clear that a combination of factors, including genetic background, host immune response, and microbial reduced diversity status are related to IBD. The cardinal symptom of IBD patients is the imbalance of the intestinal microflora. According to previous studies, both probiotics and symbiotic microbiota can play a protective role through intestinal micro-ecosystem regulation, epithelial barrier integrity enhancement, and inflammation reduction. Therefore, probiotics can provide an alternative or auxiliary method to traditional IBD treatment. Here, we reviewed the possible pathogenesis of IBD, summarized the possible mechanisms of probiotics modulation of IBD, and emphasized the prevention and treatment targets of probiotics-mediated IBD, with the aim to provide theoretical support for the treatment of IBD patients by probiotics in clinical trials.

The potential of Lactiplantibacillus plantarum ZJ316 (ZJ316) as a starter culture for quality improvement and microbial community regulation in pickled mustard fermentation was elucidated in this study. Our results show that ZJ316 can deter the occurrence of nitrite peaks and maintain the nitrite content of pickled mustard at a low level (0.34 mg/kg). The headspace solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry results indicate that ZJ316 gives a good flavor to pickled mustard. According to the 16S rDNA results, Firmicutes were the predominant microbiota after inoculation with ZJ316, and the abundances of Citrobacter, Enterobacter, and Proteus decreased simultaneously. In addition, antibacterial activity analysis showed that the supernatant of pickled mustard inoculated with ZJ316 had a significant inhibitory effect on Staphylococcus aureus D48, Escherichia coli DH5α, and Listeria monocytogenes LM1. In conclusion, L. plantarum ZJ316 has potential for use as an ideal starter in the process of vegetable fermentation.