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Abstract Energy deprivation and metabolic rewiring of cardiomyocytes are widely recognized hallmarks of heart failure. Here, we report that HEY2 (a Hairy/Enhancer-of-split-related transcriptional repressor) is upregulated in hearts of patients with dilated cardiomyopathy. Induced Hey2 expression in zebrafish hearts or mammalian cardiomyocytes impairs mitochondrial respiration, accompanied by elevated ROS, resulting in cardiomyocyte apoptosis and heart failure. Conversely, Hey2 depletion in adult mouse hearts and zebrafish enhances the expression of mitochondrial oxidation genes and cardiac function. Multifaceted genome-wide analyses reveal that HEY2 enriches at the promoters of genes known to regulate metabolism (including Ppargc1, Esrra and Cpt1) and colocalizes with HDAC1 to effectuate histone deacetylation and transcriptional repression. Consequently, restoration of PPARGC1A/ESRRA in Hey2- overexpressing zebrafish hearts or human cardiomyocyte-like cells rescues deficits in mitochondrial bioenergetics. Knockdown of Hey2 in adult mouse hearts protects against doxorubicin-induced cardiac dysfunction. These studies reveal an evolutionarily conserved HEY2/HDAC1-Ppargc1/Cpt transcriptional module that controls energy metabolism to preserve cardiac function.

Abstract Background Limited epidemiological evidence exists regarding the role of healthy eating patterns in reducing the risk of Crohn’s disease (CD) and ulcerative colitis (UC). This study aimed to investigate the association between adherence to four established healthy eating patterns and subsequent CD or UC risk, and further examined whether these associations are linked to anti-inflammatory mechanisms. Methods We conducted a prospective cohort study of 197,391 participants from the UK Biobank who completed at least one dietary questionnaire and were free from inflammatory bowel disease or cancer at baseline. Four dietary patterns were assessed, including Alternate Mediterranean Diet (AMED), Healthy Eating Index 2015 (HEI-2015), Healthful Plant-based Diet Index (HPDI), and EAT-Lancet. Cox proportional models with restricted cubic splines were applied to explore the associations. The potential role of low-grade inflammation in these associations was examined through mediation analysis. Results During 2,193,436 person-years follow-up, 260 CD and 601 UC cases were identified. Higher AMED and HEI-2015 scores were associated with a reduced risk of CD but no UC, with no evidence against nonlinearity. These associations remained consistent across multiple sensitive and subgroup analyses. For dietary components, the fruits and monounsaturated fatty acids: saturated fatty acids ratio in AMED, and total fruits, total protein foods and fatty acid in HEI-2015 were linked to a decreased CD risk. Both diets were also associated with lower plasma inflammation biomarkers. Mediation analysis indicated that 7.66% and 13.40% of the reductions in CD risk attributed to AMED and HEI-2015 diets, respectively, were mediated by low-grade inflammation scores. Conclusions Higher adherence to AMED and HEI-2015 might significantly reduce CD risk, partly due to their anti-inflammatory properties.

Abstract Recently, RNA velocity has driven a paradigmatic change in single-cell RNA sequencing (scRNA-seq) studies, allowing the reconstruction and prediction of directed trajectories in cell differentiation and state transitions. Most existing methods of dynamic modeling use ordinary differential equations (ODE) for individual genes without applying multivariate approaches. However, this modeling strategy inadequately captures the intrinsically stochastic nature of transcriptional dynamics governed by a cell-specific latent time across multiple genes, potentially leading to erroneous results. Here, we present SDEvelo, a generative approach to inferring RNA velocity by modeling the dynamics of unspliced and spliced RNAs via multivariate stochastic differential equations (SDE). Uniquely, SDEvelo explicitly models inherent uncertainty in transcriptional dynamics while estimating a cell-specific latent time across genes. Using both simulated and four scRNA-seq and spatial transcriptomics datasets, we show that SDEvelo can model the random dynamic patterns of mature-state cells while accurately detecting carcinogenesis. Additionally, the estimated gene-shared latent time can facilitate many downstream analyses for biological discovery. We demonstrate that SDEvelo is computationally scalable and applicable to both scRNA-seq and sequencing-based spatial transcriptomics data.

Abstract This study was to determine the involvement of long non‐coding RNA C7orf13 in nasopharyngeal carcinoma (NPC) and its underlying mechanism. Real‐time quantitative PCR results indicated that C7orf13 was overexpressed in NPC and associated with malignant features. C7orf13 knockdown significantly suppressed the proliferation, migration and invasion of NPC cells. Furthermore, we found that C7orf13 sequestered miR‐449c and miR‐28‐5p in NPC cells by dual‐luciferase reporter assays and RNA immunoprecipitation analysis. Sequent experiments showed that C7orf13 has a positive relationship with formin‐like 2 (FMNL2) in NPC tissues. Moreover, C7orf13 knockdown weakened FMNL2‐mediated cell invasion and migration. Finally, functional experiments revealed that the positive effect of C7orf13 on cell migration and invasion was mediated by the miR‐449c/miR‐28‐5p‐FMNL2 axis. Generally, our study identifies the biological role of long non‐coding RNA C7orf13 in the malignant process of NPC, which may pave a new way for the diagnosis and treatment of NPC.

Loss of plant functional group diversity has significant repercussions for ecosystem productivity globally. However, our understanding of how this loss of specific functional groups, particularly those providing non-food resources, influences herbivores and, consequently, ecosystem productivity remains limited. To elucidate these, we conducted a series of experiments consisting of (1) a two-factor field experiment, where we manipulated the forb abundance and caterpillar presence to assess their interactive effects on plant productivity and caterpillar performance, (2) a field complementary shelter addition experiment, designed to isolate and evaluate the effects of microclimatic changes resulting from forb removal, and (3) a confirmatory microcosm experiment to validate the field findings under controlled by monitoring the herbivory patterns. Our results show that forb removal significantly decreased the aboveground plant biomass (APB) by 41.3%, but did not affect the APB of sedges. The presence of caterpillars significantly decreased total APB by 16.7% and APB of sedges by 34.8%, but these effects disappeared with forbs removed. Specifically, forb removal significantly increased caterpillar mortality rates by 319% and decreased caterpillar body size by 27.2%, which in turn diminished the herbivory pressure on sedges. Changes in caterpillar performance were correlated with maximum and average soil surface temperatures influenced by forb removal and the addition of shelters. Further investigation by the confirmatory microcosm experiment indicated that the absence of forbs decreased the feeding time of caterpillars and deprived caterpillars of refuge from the midday heat and intense sunlight, ultimately resulting in lower body size and higher larval mortality. Our findings suggest that forb removal disrupts trophic interactions, with potential cascading effects on herbivore populations, plant community structure, and ecosystem productivity. These results underscore the importance of plant functional diversity in maintaining ecosystem stability, especially under changing environmental conditions.

Abstract With the increasing complexity of the distribution network, the proportion of abnormal data in the monitoring data of the distribution network and its daily work is extremely low. Traditional clustering analysis methods are difficult to effectively solve the imbalance problem. Therefore, this paper introduces the influence parameters that can adaptively adjust the cluster center of local samples in the boundary area, and improves the cluster center update formula, and proposes a method of distribution network operation state evaluation based on the local blur measurement of the boundary region. The research results found that the five evaluation indicators of the proposed algorithm were 112, 0, 2, 26, and 5, respectively, all of which were superior to the comparison algorithms. The research results showed that the cluster center update optimization method based on local fuzzy measure in boundary region could effectively reduce the negative impact of the edge region occupied by most clusters on its clustering effect, so that the cluster center was always in an ideal position. At the same time, the example results showed that the research method had a risk prediction of 0.91 for power outage networks, which was close to the real situation and had high accuracy. It can provide reference for the operation and maintenance work of power grid personnel, eliminate hidden dangers in advance, and ensure the safe operation of the power grid.

Abstract There are mixed findings on the impact of women directors on board (WOB) on corporate financial performance (CFP). To reconcile these mixed findings, we propose that WOB could influence CFP in the following two ways. On the one hand, WOB could enhance CFP by leading more CSR activities. On the other hand, WOB may weaken the CSR-CFP relationship due to expectations on their role-playing. These two effects go in opposite directions, and their relative strength determines the WOB-CFP relationship. Using Chinese listed firms from 2011 to 2020 as samples, the results lend strong support to these two effects. And WOB will have a positive effect on CFP only if its moderating effect on the CSR-CFP relationship has been controlled for. Additional tests show that neither critical mass nor qualification of women directors matters in explaining variations of CFP in Chinese firms. The contributions and limitations are discussed at the end of this study.

This study examined the silverside, striploin, rump, high rib, shoulder, and shank of yak meat. Specifically, the differences in nutritional quality, muscle fiber characteristics, and physicochemical properties before shabu-shabu processing, as well as physicochemical properties and edible quality indices after shabu-shabu processing were analyzed. Through correlation analysis, principal component analysis (PCA), and cluster analysis, key quality indicators for shabu-shabu yak meat processing were identified. Rsults showed that, the raw yak meat redness (a*), fat content, water loss rate under pressure, gel hardness, shabu-shabu yak meat yellowness (b*), and chewiness were the key quality indicators for shabu-shabu yak meat processing. A comprehensive quality evaluation equation for shabu-shabu yak meat was established: Y=0.1644X1+0.0561X2+0.3630X3+0.1102X4+0.1609X5+0.1453X6. This equation was employed to calculate scores for different shabu-shabu yak meat cuts. K-means cluster analysis was used to assess the suitability of various cuts for shabu-shabu processing, indicating that high rib and silverside cuts with Y values greater than or equal to 0.61 were suitable, striploin and rump with Y values between 0.50 and 0.61 were relatively suitable, and shank and shoulder with Y values less than or equal to 0.50 were unsuitable. The regression equation, y=5.0914x−2.2958 (R²=0.8232), correlating comprehensive quality scores as the independent variable with overall acceptability scores of consumer sensory evaluations as the dependent variable, validates the accuracy of the quality assessment model in determining the suitability of different yak meat cuts for shabu-shabu. This study provides distinct evidence validating the suitability of different yak meat cuts for shabu-shabu, as well as a basis for the rationalization and standardization of yak meat processing.

Abstract Purpose Systemic immunity is essential for driving therapeutically induced antitumor immune responses, and the spleen may reflect alterations in systemic immunity. This study aimed to evaluate the predictive value of contrast-enhanced CT-based spleen radiomics for progression-free survival (PFS) in patients with locally advanced cervical cancer (LACC) who underwent definitive chemoradiotherapy (dCRT). Additionally, we investigated the role of spleen radiomics features and changes in spleen volume in assessing systemic immunity. Methods This retrospective study included 257 patients with LACC who underwent dCRT. The patients were randomly divided into training and validation groups in a 7:3 ratio. Radiomic features were extracted from CT images obtained before and after dCRT. Radiomic scores (Radscore) were calculated using features selected through least absolute shrinkage and selection operator (LASSO) Cox regression. The percentage change in spleen volume was determined from measurements taken before and after treatment. Independent prognostic factors for PFS were identified through multivariate Cox regression analyses. Model performance was evaluated with the receiver operating characteristic (ROC) curve and the C-index. The Radscore cut-off value, determined from the ROC curve, was used to stratify patients into high- and low-risk survival groups. The Wilcoxon test was used to analyze differences in hematological parameters between different survival risk groups and between different spleen volume change groups. Spearman correlation analysis was used to explore the relationship between spleen volume change and hematological parameters. Results Independent prognostic factors included FIGO stage, pre-treatment neutrophil-to-lymphocyte ratio (pre-NLR), spleen volume change, and Radscore. The radiomics-combined model demonstrated the best predictive performance for PFS in both the training group (AUC: 0.923, C-index: 0.884) and the validation group (AUC: 0.895, C-index: 0.834). Compared to the low-risk group, the high-risk group had higher pre-NLR (p = 0.0054) and post-NLR (p = 0.038). Additionally, compared to the decreased spleen volume group, the increased spleen volume group had lower post-NLR (p = 0.0059) and post-treatment platelet-to-lymphocyte ratio (p

Flavor significantly influences the quality of meat and meat products. The dynamic equilibrium between the release and retention of volatile flavor compounds, influenced by the interaction of muscle proteins and flavor compounds, is crucial in determining meat's sensory quality and consumer acceptability. Elucidating the interaction mechanisms between proteins and flavor substances lays the foundation for accurately predicting and controlling the binding behavior of these substances. This article reviews the recent advancements on flavor retention and release in muscle protein solutions. It includes the calculation of binding parameters (such as binding sites and constants) using mathematical modeling and fluorescence spectroscopy, the analysis of protein conformation and binding modes employing multispectral and molecular docking techniques, as well as factors influencing protein-flavor interaction. These studies are crucial for both qualitative and quantitative prediction of flavor binding behavior. Future research should further investigate the influence of complex protein systems and other food matrices on flavor binding behavior.

ABSTRACTPreviously, we reported a cohort of Japanese encephalitis (JE) patients with Guillain–Barré syndrome. However, the evidence linking Japanese encephalitis virus (JEV) infection and peripheral nerve injury (PNI) remains limited, especially the epidemiology, clinical presentation, diagnosis, treatment, and outcome significantly differ from traditional JE. We performed a retrospective and multicenter study of 1626 patients with JE recorded in the surveillance system of the Chinese Center for Disease Control and Prevention, spanning the years 2016–2020. Cases were classified into type 1 and type 2 JE based on whether the JE was combined with PNI or not. A comparative analysis was conducted on demographic characteristics, clinical manifestations, imaging findings, electromyography data, laboratory results, and treatment outcomes. Among 1626 laboratory confirmed JE patients, 230 (14%) were type 2 mainly located along the Yellow River in northwest China. In addition to fever, headache, and disturbance of consciousness, type 2 patients experienced acute flaccid paralysis of the limbs, as well as severe respiratory muscle paralysis. These patients presented a greater mean length of stay in hospital (children, 22 years [range, 1–34]; adults, 25 years [range, 0–183]) and intensive care unit (children, 16 years [range, 1–30]; adults, 17 years [range, 0–102]). The mortality rate was higher in type 2 patients (36/230 [16%]) compared to type 1 (67/1396 [5%]). The clinical classification of the diagnosis of JE may play a crucial role in developing a rational treatment strategy, thereby mitigating the severity of the disease and potentially reducing disability and mortality rates among patients.

Objective Gut microbiota was closely involved in the pathogenesis of depression, but the underlying molecular mechanisms in depression remained unclear. This study was conducted to investigate the relationship between neurotransmitters/inflammatory factors and gut microbiota in depressed mice.Materials and methods A chronic social defeat stress (CSDS) depression model was established. Gut microbial composition was detected in faeces, neurotransmitters were detected in faeces, colon, blood and hippocampus, and inflammatory factors were detected in hippocampus. After a key neurotransmitter was identified, intervention experiment was conducted to explore whether it could improve depressive-like behaviours.Results Six differential genera in faeces, 14 differential neurotransmitters in gut-brain axis, and two differential inflammatory factors (interleukin-1 beta (IL-1β) and interleukin-6 (IL-6)) in hippocampus were identified in depressed mice. There were significant correlations among differential genera, differential neurotransmitters and IL-1β/IL-6. Among these differential neurotransmitters, 3-O-Methyldopa (3-OMDP) was found to be consistently decreased in faeces, colon, blood and hippocampus, and 3-OMDP was significantly correlated to Limosilactobacillus and IL-1β. After receiving 3-OMDP, the depressive-like behaviours in depressed mice were improved and the increased IL-1β/IL-6 levels were reversed.Conclusions These results indicated that gut microbiota might affect host’s inflammation levels in brain through regulating neurotransmitters, eventually leading to the onset of depression. ‘Limosilactobacillus-3-OMDP-IL-1β/IL-6’ might be a potential pathway in the crosstalk of gut and brain, and 3-OMDP held the promise as a therapeutic target for depression.

Background Oral lichen planus (OLP) is a chronic oral mucosal inflammatory disease with a risk of becoming malignant. Emerging evidence suggests that microbial imbalance plays an important role in the development of OLP. However, the association between the oral microbiota and the metabolic features in OLP is still unclear.Methods We conducted 16S rRNA sequencing and metabolomics profiling on 95 OLP patients and 105 healthy controls (HC).To study oral microbes and metabolic changes in OLP, we applied differential analysis, Spearman correlation analysis and four machine learning algoeithmsResults The alpha and beta diversity both differed between OLP and HC. After adjustment for gender and age, we found an increase in the relative abundance of Pseudomonas, Aggregatibacter, Campylobacter, and Lautropia in OLP, while 18 genera decreased in OLP. A total of 153 saliva metabolites distinguishing OLP from HC were identified. Notably, correlations were found between Oribacterium, specific lipid and amino acid metabolites, and OLP’s clinical phenotype. Additionally, the combination of Pseudomonas, Rhodococcus and (±)10-HDoHE effectively distinguished OLP from HC.Conclusions Based on multi-omics data, this study provides comprehensive evidence of a novel interplay between oral microbiome and metabolome in OLP pathogenesis using the oral microbiota and metabolites of OLP patients.

Abstract Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Abstract Background The administration of tranexamic acid (TXA) during spinal surgery has been shown to reduce blood loss. However, the efficacy and safety of intravenous TXA (ivTXA) and topical TXA (tTXA) are poorly documented. The present meta-analysis aimed to compare the efficacy and safety of ivTXA and tTXA administration in spinal surgery. Methods Potentially relevant academic articles were identified from PubMed, Ovid, Cochrane Library, CNKI database, and Wanfang Data from the date of inception until March 1, 2024. Randomized controlled trials (RCTs) and nonrandomized controlled trials (non-RCTs) were included in our meta-analysis if they compared the efficacy and safety of ivTXA versus tTXA administration during spinal surgery. Secondary sources were identified from the references of the included literature. The meta-analysis was performed in accordance with the guidelines of the Cochrane Reviewer’s Handbook and the PRISMA statement. Data were summarized using RevMan 5.3 software from Denmark. Results Four RCTs and one non-RCT met our inclusion criteria. The pooled outcomes demonstrated that ivTXA groups compared with tTXA groups had significantly less amount of total blood loss [weighted mean difference (WMD)=-159.55, 95% CI (-181.91,-137.19), P

Abstract Background Weight gain and metabolic disorders are commonly induced by antipsychotics. Orlistat is a lipase inhibitor used for weight control. The effect of orlistat on weight gain and metabolic disturbances in people (especially women) treated with antipsychotics has not been sufficiently studied. This study aimed to investigate the efficacy of orlistat in mitigating antipsychotic-induced weight gain and abnormal glycolipid metabolism. Methods Patients with schizophrenia or bipolar disorder with a weight gain ≥ 7% after taking antipsychotics were recruited. Participants were randomly allocated to two groups: one received eight weeks of orlistat (360 mg/day) and the other received a placebo. Anthropometric and fasting serum biochemical parameters were measured at baseline, week 4 and week 8. Results Sixty individuals (orlistat:placebo = 32:28) participated in the study. After controlling for the study center, the eight-week changes in body mass index (BMI), cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-CH) and low-density lipoprotein cholesterol (LDL-CH) were significantly different between the groups. According to the mixed linear models, CHOL and LDL-CH were significantly lower in the orlistat group than in the control group at week 8. The week 0-to-8 slopes of BMI, CHOL and LDL-CH were also significantly lower in the orlistat group. Conclusions These findings suggested that orlistat is an effective intervention for attenuating weight gain and serum lipid disturbances in antipsychotic-treated patients. Trial registration ClinicalTrials.gov NCT03451734.

BackgroundSepsis is the body’s extreme response to an infection leading to organ dysfunction. Sepsis-related acquired weakness (SAW), a critical illness closely related to metabolic disorders, is characterized by generalized sepsis-induced skeletal muscle weakness, mainly manifesting as symmetrical atrophy of respiratory and limb muscles. Muscle accounts for 40% of the body’s total mass and is one of the major sites of glucose and energy absorption. Diet affects skeletal muscle metabolism, which further impacts physiology and signaling pathways. The ketogenic diet (KD) is a high-fat, low-carbohydrate diet that has shown benefits in patients with a variety of neuromuscular disorders. Patients with SAW are in a hypermetabolic state and can consume approximately 1% of total body muscle mass in a day. Due to the decreased total body energy expenditure secondary to starvation, skeletal muscles enter a low metabolic state, with reduced gluconeogenesis and protein consumption and elevated levels of ketone bodies. The latest research suggests that KD may be a new strategy for SAW prevention and treatment, but its mechanism is still unclear.ObjectiveOur article aims to explore the effect and mechanism of KD on SAW. And we hope that our review will inspire further research on the KD and foster the exploration of novel strategies for combating SAW.MethodsSearch medical databases and related academic websites, using keywords such as “Sepsis-related acquired weakness,” “ketogenic diet,” and “skeletal muscle,” and select representative literature. Using the method of induction and summary, analyze the effect and mechanism of KD on SAW.ResultsCompared with early nutrition, KD has a more protective effect on SAW, but its mechanism is complex. Firstly, KD can alter energy metabolism substrates to affect SAW’s energy metabolism; Secondly, KD can directly act as a signaling molecule to improve mitochondrial function in skeletal muscle and stimulate skeletal muscle regeneration signaling molecules; Thirdly, KD can affect the gut microbiota to exert anti-inflammatory effects, enhance immunity, and thus protect SAW.ConclusionKD has a protective effect on SAW, which includes improving energy metabolism, stimulating muscle regeneration signals, optimizing gut microbiota composition, and reducing inflammation and oxidative stress.

ObjectivesThe aim of this study is to develop an ultrasound-based fusion model of clinical, radiomics and deep learning (CRDL) for accurate diagnosis of benign and malignant soft tissue tumors (STTs)MethodsIn this retrospective study, ultrasound images and clinical data of patients with STTs from two hospitals were collected between January 2021 and December 2023. Radiomics features and deep learning features were extracted from the ultrasound images, and the optimal features were selected to construct fusion models using support vector machines. The predictive performance of the model was evaluated based on three aspects: discrimination, calibration and clinical usefulness. The DeLong test was used to compare whether there was a significant difference in AUC between the models. Finally, two radiologists who were unaware of the clinical information performed an independent diagnosis and a model-assisted diagnosis of the tumor to compare the performance of the two diagnoses.ResultsA training cohort of 516 patients from Hospital-1 and an external validation cohort of 78 patients from Hospital-2 were included in the study. The Pre-FM CRDL showed the best performance in predicting STTs, with area under the curve (AUC) of 0.911 (95%CI: 0.894-0.928) and 0.948 (95%CI: 0.906-0.990) for training cohort and external validation cohort, respectively. The DeLong test showed that the Pre-FM CRDL significantly outperformed the clinical models (P< 0.05). In addition, the Pre-FM CRDL can improve the diagnostic accuracy of radiologists.ConclusionThis study demonstrates the high clinical applicability of the fusion model in the differential diagnosis of STTs.

BackgroundAnimal models focusing on neuromuscular outcomes are crucial for understanding the mechanisms of intensive care unit-acquired weakness (ICU-AW) and exploring potential innovative prevention and treatment strategies.AimTo analyse and evaluate preclinical ICU-AW models.MethodsWe manually searched five English and four Chinese databases from 1 January 2002, to 1 February 2024, and reviewed related study references. Full-text publications describing animal models of muscle weakness and atrophy in critical illness were included. Detailed information about model types, animal species, sex, age, induction methods, outcome measures, drawbacks and strengths was extracted from each included study.ResultsA total of 3,451 citations were initially retrieved, with 84 studies included in the final analysis. The most frequently studied animal model included rodents (86.9%), 64.3% of which were male animals. ICU-AW animal models were mostly induced by comprehensive intensive care unit (ICU) interventions (38.1%) and sepsis (51.2%). Most studies focused on limb muscles (66.7%), diaphragm muscles (21.4%) or both (9.5%). Reported outcomes primarily included muscular pathological changes (83.3%), electrophysiological examinations of muscles (57.1%) and animal grip strength (16.6%). However, details such as animal age, mortality data, experimental design, randomisation, blinding, sample size and interventions for the experimental group and/or control group were inadequately reported.ConclusionMany preclinical models are used to study ICU-AW, but the reporting of methodological details is often incomplete. Although current ICU animal models can mimic the characteristics of human ICU-AW, there is no standard model. Future preclinical studies should develop a standard ICU-AW animal model to enhance reproducibility and improve scientific rigor in exploring the mechanisms and potential treatment of ICU-AW.

BackgroundSchizophrenia is one of the most severe mental disorders, frequently associated with aggression and violence, particularly in male patients. The underlying mechanisms of violent behavior in these patients remain unclear, limiting effective treatment options and highlighting the need for further research into interventions for impulsive behaviors. This study aims to evaluate the clinical efficacy of neurofeedback treatment in hospitalized male schizophrenia patients exhibiting impulsive behaviors.MethodsThe study was designed as a single-center, randomized, single-blind, sham-controlled parallel trial. Eighty patients were randomly assigned to either a study group or a control group. The control group received risperidone and sham neurofeedback, while the study group received risperidone and active neurofeedback therapy. Both groups underwent training five times per week, with each session lasting 20 minutes, over a six-week period. Clinical symptoms were assessed at baseline, three weeks and six weeks using the Positive and Negative Syndrome Scale (PANSS), the Modified Overt Aggression Scale (MOAS), and the Rating Scale for Extrapyramidal Side Effects (RSESE). Statistical analyses were conducted to compare the therapeutic effects between the two groups at the study’s conclusion.ResultsInitial comparisons showed no significant differences in baseline data, except for the number of prior hospitalizations (P

In order to improve the recognition rate of the tone classification of doctors in online medical services scenarios, we propose a model that integrates a one-dimensional convolutional neural network (1DCNN) with a bidirectional long short-term memory network (BiLSTM). Firstly, significant tone types within online medical services scenarios were identified through a survey questionnaire. Secondly, 68 features in both the time and frequency domains of doctors’ tone were extracted using Librosa, serving as the initial input for the model. We utilize the 1DCNN branch to extract local features in the time and frequency domains, while the BiLSTM branch captures the global sequential features of the audio, and a feature-level fusion is performed to enhance tone classification effectiveness. When applied in online medical services scenarios, experimental results show that the model achieved an average recognition rate of 84.4% and an F1 score of 84.4%, significantly outperforming other models and effectively improving the efficiency of doctor-patient communication. Additionally, a series of ablation experiments were conducted to validate the effectiveness of the 1DCNN and BiLSTM modules and the parameter settings.

Given the rapid development of the distributed energy resources (DER), involving DERs into the wholesale market under the market and renewable uncertainties to achieve economic benefits is necessary but challenging. In this work, an arbitraging strategy is proposed for DER aggregators that bridge DERs with the wholesale market through energy trading. Besides, a novel self-adaptive minimax regret (MMR)-based optimal offering model is proposed for the DER aggregator to handle the uncertainties in both renewable generations and market prices. Additionally, an exact and communication-free solution methodology is proposed to resolve the formulated optimization problem with high computational efficiency. In the numerical results, the proposed methods can achieve near-to-optimal profits. Moreover, the performance of the proposed approach remains satisfactory even if the environment becomes very volatile.

Introduction: Neuroinflammation and autophagy are implicated in stress-related major depressive disorder (MDD), but the underlying molecular mechanisms remain largely unknown. Objectives: Here, we identified that MDD regulated by HMGB1/STAT3/p65 axis mediated microglial activation and autophagy for the first time. Further investigations were performed to uncover the effects of this axis on MDD in vivo and in vitro. Methods: Bioinformatics analyses were used to re-analysis the transcriptome data from the dorsolateral prefrontal cortex (dlPFC) of post-mortem male MDD patients. The expression level of HMGB1 and its correlation with depression symptoms were explored in MDD clinical patients and chronic social defeat stress (CSDS)-induced depression model mice. Specific adeno-associated virus and recombinant (r)HMGB1 injection into the medial PFC (mPFC) of mice, and pharmacological inhibitors with rHMGB1 in two microglial cell lines exposed to lipopolysaccharide were used to analyze the effects of HMGB1/STAT3/p65 axis on MDD. Results: The differential expression of genes from MDD patients implicated in microglial activation and autophagy regulated by HMGB1/STAT3/p65 axis. Serum HMGB1 level was elevated in MDD patients and positively correlated with symptom severity. CSDS not only induced depression-like states in mice, but also enhanced microglial reactivity, autophagy as well as activation of the HMGB1/STAT3/p65 axis in mPFC. The expression level of HMGB1 was mainly increased in the microglial cells of CSDS-susceptible mice, which also correlated with depressive-like behaviors. Specific HMGB1 knockdown produced a depression-resilient phenotype and suppressed the associated microglial activation and autophagy effects of CSDS-induced. The effects induced by CSDS were mimicked by exogenous administration of rHMGB1 or specific overexpression of HMGB1, while blocked by STAT3 inhibitor or p65 knockdown. In vitro, inhibition of HMGB1/STAT3/p65 axis prevented lipopolysaccharide-induced microglial activation and autophagy, while rHMGB1 reversed these changes. Conclusion: Our study established the role of microglial HMGB1/STAT3/p65 axis in mPFC in mediating microglial activation and autophagy in MDD.

Abstract The pathogenesis of major depressive disorder (MDD) involves lipid metabolism. Our earlier research also revealed that MDD patients had much lower total cholesterol (TC) concentrations than healthy controls (HCs). However, it is still unclear why TC decreased in MDD. Here, based on the Ingenuity Knowledge Base’s ingenuity pathway analysis, we found that sodium voltage-gated channel alpha subunit 11A (SCN11A) might serve as a link between low lipid levels and MDD. We analyzed the TC levels and used ELISA kits to measure the levels of SCN11A in the serum from 139 MDD patients, and 65 HCs to confirm this theory and explore the potential involvement of SCN11A in MDD. The findings revealed that TC levels were considerably lower and SCN11A levels were remarkably increased in MDD patients than those in HCs, while they were significantly reversed in drug-treatment MDD patients than in drug-naïve MDD patients. There was no significant difference in SCN11A levels among MDD patients who used single or multiple antidepressants, and selective serotonin reuptake inhibitors or other antidepressants. Pearson correlation analysis showed that the levels of TC and SCN11A were linked with the Hamilton Depression Rating Scales score. A substantial association was also found between TC and SCN11A. Moreover, a discriminative model made up of SCN11A was discovered, which produced an area under a curve of 0.9571 in the training set and 0.9357 in the testing set. Taken together, our findings indicated that SCN11A may serve as a link between low lipid levels and MDD, and showed promise as a candidate biomarker for MDD.

Abstract Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Satellite remote sensing technology has been widely applied in various fields due to its efficient data acquisition speed, short period and significant benefit ratio. This article summarizes and analyzes the application of satellite remote sensing technology in the field of health at home and abroad by searching the relevant literature in recent years. From epidemiology, environmental health, medical and health management to public health emergency response, satellite remote sensing technology has shown strong application potential in the field of health. It is recommended to draw on international experience and further expand the application scope of satellite remote sensing technology in China's health field, including expanding the scope of epidemic monitoring, establishing the relationship between environmental factors and health outcomes, and promoting cross-application research in various fields. This will provide more comprehensive and accurate data support for the high-quality development of China's health and wellness initiatives.

Abstract Calendula officinalis L.is a versatile medicinal plant with numerous applications in various fields. However, its chloroplast genome structure, features, phylogeny, and patterns of evolution and mutation remain largely unexplored. This study examines the chloroplast genome, phylogeny, codon usage bias, and divergence time of C. officinalis, enhancing our understanding of its evolution and adaptation. The chloroplast genome of C. officinalis is a 150,465 bp circular molecule with a G + C content of 37.75% and comprises 131 genes. Phylogenetic analysis revealed a close relationship between C. officinalis, C. arvensis, and Osteospermum ecklonis. A key finding is the similarity in codon usage bias among these species, which, coupled with the divergence time analysis, supports their close phylogenetic proximity. This similarity in codon preference and divergence times underscores a parallel evolutionary adaptation journey for these species, highlighting the intricate interplay between genetic evolution and environmental adaptation in the Asteraceae family. Moreover unique evolutionary features in C. officinalis, possibly associated with certain genes were identified, laying a foundation for future research into the genetic diversity and medicinal value of C. officinalis.

In this paper, the formation process, morphology, and electrochemical performance of PEO coatings on AM50 magnesium alloy prepared in low concentration phosphate, aluminate, and phosphate-aluminate electrolytes were systematically studied. The results show that the coatings prepared from the phosphate electrolytes have a higher thickness and better corrosion resistance properties compared to the other electrolytes. The coatings prepared from low concentration phosphate-aluminate mixed electrolytes have slightly thinner thickness, a similar coating structure and an order of magnitude lower value of electrochemical impedance compared with phosphate electrolyte coatings. The Coatings prepared from low concentration aluminate electrolytes have the lowest thickness and the worst corrosion resistance properties which gets close to corrosion behavior of the bare AM50 under the same test conditions. Considering application, coatings prepared from single low concentration phosphate electrolytes and low concentration phosphate-aluminate electrolytes have greater potential than single low concentration aluminate coatings. However, reducing the electrolyte concentrations of coating forming ions too much has negative influence on the coating growth rate.

Abstract Major depressive disorder (MDD) is a serious mental illness, characterized by disturbances of gut microbiome, it is required to further explore how the carbohydrate-active enzymes (CAZymes) were changed in MDD. Here, using the metagenomic data from patients with MDD (n = 118) and heath controls (HC, n = 118), we found that the whole CAZymes signatures of MDD were significantly discriminated from that in HC. α-diversity indexes of the two groups were also significantly different. The patients with MDD were characterized by enriched Glycoside Hydrolases (GHs) and Polysaccharide Lyases (PLs) relative to HC. A panel of makers composed of 9 CAZymes mainly belonging to GHs enabled to discriminate the patients with MDD and HC with AUC of 0.824. In addition, this marker panel could classify blinded test samples from the two groups with an AUC of 0.736. Moreover, we found that baseline 4 CAZymes levels also could predict the antidepressant efficacy after adjusted confounding factors and times of depressive episode. Our findings showed that MDD was associated with disturbances of gut CAZymes, which may help to develop diagnostic and predictive tools for depression.

In orchard environments, negative obstacles such as ditches and potholes pose significant safety risks to robots working within them. This paper proposes a negative obstacle detection method based on LiDAR tilt mounting. With the LiDAR tilted at 40°, the blind spot is reduced from 3 m to 0.21 m, and the ground point cloud density is increased by an order of magnitude. Based on geometric features of laser point clouds (such as rear wall height and density, and spacing jump between points), a method for detecting negative obstacles is presented. This method establishes a mathematical model by analyzing changes in point cloud height, density, and point spacing, integrating features captured from multiple frames to enhance detection accuracy. Experiments demonstrate that this approach effectively detects negative obstacles in orchard environments, achieving a success rate of 92.7% in obstacle detection. The maximum detection distance reaches approximately 8.0 m, significantly mitigating threats posed to robots by negative obstacles in orchards. This research contributes valuable technological advancements for future orchard automation.

IntroductionWorkplace violence against healthcare workers has become a serious global public health problem. The incidence of workplace violence towards Psychiatric nurses is higher than in all other medical institutions, up to 84.2% per year. It not only negatively affects many aspects of healthcare workers’ lives, but also destroys the harmony of the nurse–patient relationship and reduces the quality of nursing care. The number of psychiatric nurses in China was approximately 96,000, far lower than most other countries and unable to meet the growing demand for mental health. However, the increase in workplace violence has future exacerbates the current shortage of nurses. Therefore, it is necessary to develop effective strategies to prevent psychiatric nurses from suffering from workplace violence, thereby to reduce nurse turnover and improve the quality of nursing care. A comprehensive understanding of psychiatric nurses’ preferences and priorities for preventing workplace violence is an important prerequisite before formulating strategies and taking measures. Unfortunately, to date, no research has investigated the psychiatric nurses’ preferences. Therefore, a discrete choice experiment (DCE) is conducting to explore the psychiatric nurses’ preferences for workplace violence prevention. This article reports on methodological details of the DCE.Methods and analysisSix attributes were developed through a literature review, one-on-one interviews and focus group discussions. D-efficient design in NGENE was used to generate choice sets. SPSS 24.0 will be used for descriptive analysis of social Demography, and Stata 16.0 will be used for analysis of DCE data. A multinomial logit model will be used to preliminarily explore trade-offs between workplace violence prevention characteristics included in the choice tasks. Then, in a mixed logit model, we plan to choose some arbitrarily defined base violence prevention program and will use the nlcom command to evaluate the probability of an alternative violence prevention program.Ethics and disseminationThe study was approved by the relevant ethics committees. Our findings will emphasize priority intervention areas based on the preferences of psychiatric nurses and provide references for hospitals to develop and improve workplace violence prevention strategies. The results will be shared through seminars, policy briefs, peer-reviewed journal articles and online blogs.

Microalgal-indigenous bacterial wastewater treatment (MBWT) emerges as a promising approach for the concurrent removal of nitrogen (N) and phosphorus (P). Despite its potential, the prevalent use of MBWT in batch systems limits its broader application. Furthermore, the success of MBWT critically depends on the stable self-adaptation and synergistic interactions between microalgae and indigenous bacteria, yet the underlying biological mechanisms are not fully understood. Here we explore the viability and microbial dynamics of a continuous flow microalgae-indigenous bacteria advanced wastewater treatment system (CFMBAWTS) in processing actual secondary effluent, with a focus on varying hydraulic retention times (HRTs). The research highlights a stable, mutually beneficial relationship between indigenous bacteria and microalgae. Microalgae and indigenous bacteria can create an optimal environment for each other by providing essential cofactors (like iron, vitamins, and indole-3-acetic acid), oxygen, dissolved organic matter, and tryptophan. This collaboration leads to effective microbial growth, enhanced N and P removal, and energy generation. The study also uncovers crucial metabolic pathways, functional genes, and patterns of microbial succession. Significantly, the effluent NH4+-N and P levels complied with the Chinese national Class-II, Class-V, Class-IA, and Class-IB wastewater discharge standards when the HRT was reduced from 15 to 6 h. Optimal results, including the highest rates of CO2 fixation (1.23 g L−1), total energy yield (32.35 kJ L−1), and the maximal lipid (33.91%) and carbohydrate (41.91%) content, were observed at an HRT of 15 h. Overall, this study not only confirms the feasibility of CFMBAWTS but also lays a crucial foundation for enhancing our understanding of this technology and propelling its practical application in wastewater treatment plants.

Studies have shown that the microbiota-gut-brain axis is highly correlated with the pathogenesis of depression in humans. However, whether independent oral microbiome that do not depend on gut microbes could affect the progression of depression in human beings remains unclear, neither does the presence and underlying mechanisms of the microbiota-oral-brain axis in the development of the condition. Hence this study that encompasses clinical and animal experiments aims at investigating the correlation between oral microbiota and the onset of depression via mediating the microbiota-oral-brain axis. We compared the oral microbial compositions and metabolomes of 87 patients with depressive symptoms versus 70 healthy controls. We found that the oral microbial and metabolic signatures were significantly different between the two groups. Significantly, germ-free (GF) mice transplanted with saliva from mice exposing to chronic restraint stress (CRS) displayed depression-like behavior and oral microbial dysbiosis. This was characterized by a significant differential abundance of bacterial species, including the enrichment of Pseudomonas, Pasteurellaceae, and Muribacter, as well as the depletion of Streptococcus. Metabolomic analysis showed the alternation of metabolites in the plasma of CRS-exposed GF mice, especially Eicosapentaenoic Acid. Furthermore, oral and gut barrier dysfunction caused by CRS-induced oral microbiota dysbiosis may be associated with increased blood-brain barrier permeability. Pseudomonas aeruginosa supplementation exacerbated depression-like behavior, while Eicosapentaenoic Acid treatment conferred protection against depression-like states in mice. These results suggest that oral microbiome and metabolic function dysbiosis may be relevant to the pathogenesis and pathophysiology of depression. The proposed microbiota-oral-brain axis provides a new way and targets for us to study the pathogenesis of depression.

Abstract Objective To assess the prevalence and factors associated with early cognitive impairment in intracerebral hemorrhage (ICH) patients and to describe short‐term recovery trajectories among ICH patients with early cognitive impairment. Methods We prospectively enrolled ICH patients without baseline dementia in our institutions. Cognitive function was assessed using mini‐mental state examination (MMSE), and functional outcome was evaluated at discharge, 3, and 6 months after symptoms onset using the modified Rankin Scale (mRS). We used multinomial logistic regression models to investigate potential risk factors and generalized linear models to analyze the functional outcome data. Results Out of 181 patients with ICH, 167 were included in the final analysis. Early cognitive impairment occurred in 60.48% of patients with ICH. Age (odds ratio [OR] per 1‐year increase, 1.037; 95% confidence interval [CI], 1.003–1.071; p = 0.034), National Institutes of Health Stroke Scale (NIHSS) score (OR per 1‐point increase, 1.146; 95% CI, 1.065–1.233; p

Abstract Background Secondary immunodeficiency can arise from various clinical conditions that include HIV infection, chronic diseases, malignancy and long-term use of immunosuppressives, which makes the suffering patients susceptible to all types of pathogenic infections. Other than HIV infection, the possible pathogen profiles in other aetiology-induced secondary immunodeficiency are largely unknown. Methods Medical records of the patients with secondary immunodeficiency caused by various aetiologies were collected from the First Affiliated Hospital of Nanchang University, China. Based on these records, models were developed with the machine learning method to predict the potential infectious pathogens that may inflict the patients with secondary immunodeficiency caused by various disease conditions other than HIV infection. Results Several metrics were used to evaluate the models’ performance. A consistent conclusion can be drawn from all the metrics that Gradient Boosting Machine had the best performance with the highest accuracy at 91.01%, exceeding other models by 13.48, 7.14, and 4.49% respectively. Conclusions The models developed in our study enable the prediction of potential infectious pathogens that may affect the patients with secondary immunodeficiency caused by various aetiologies except for HIV infection, which will help clinicians make a timely decision on antibiotic use before microorganism culture results return.

Abstract The brain neurotramsmitter dopamine may play an important role in modulating systemic glucose homeostasis. In seven hundred and four drug- naïve patients with first-episode schizophrenia, we provide robust evidence of positive associations between negative symptoms of schizophrenia and high fasting blood glucose. We then show that glucose metabolism and negative symptoms are improved when intermittent theta burst stimulation (iTBS) on prefrontal cortex (PFC) is performed in patients with predominantly negative symptoms of schizophrenia. These findings led us to hypothesize that the prefrontal cortical dopamine deficit, which is known to be associated with negative symptoms, may be responsible for abnormal glucose metabolism in schizophrenia. To explore this, we optogenetically and chemogenetically inhibited the ventral tegmental area (VTA)-medial prefrontal cortex (mPFC) dopamine projection in mice and found both procedures caused glucose intolerance. Moreover, microinjection of dopamine two receptor (D2R) neuron antagonists into mPFC in mice significantly impaired glucose tolerance. Finally, a transgenic mouse model of psychosis named Disc1tr exhibited depressive-like symptoms, impaired glucose homeostasis, and compared to wild type littermates reduced D2R expression in prefrontal cortex.

Abstract Our previous work has shown that d-ribose (RIB)-induced depressive-like behaviors in mice. However, the relationship between variations in RIB levels and depression as well as potential RIB participation in depressive disorder is yet unknown. Here, a reanalysis of metabonomics data from depressed patients and depression model rats is performed to clarify whether the increased RIB level is positively correlated with the severity of depression. Moreover, we characterize intestinal epithelial barrier damage, gut microbial composition and function, and microbiota-gut-brain metabolic signatures in RIB-fed mice using colonic histomorphology, 16 S rRNA gene sequencing, and untargeted metabolomics analysis. The results show that RIB caused intestinal epithelial barrier impairment and microbiota-gut-brain axis dysbiosis. These microbial and metabolic modules are consistently enriched in peripheral (fecal, colon wall, and serum) and central (hippocampus) glycerophospholipid metabolism. In addition, three differential genera (Lachnospiraceae_UCG-006, Turicibacter, and Akkermansia) and two types of glycerophospholipids (phosphatidylcholine and phosphatidylethanolamine) have greater contributions to the overall correlations between differential genera and glycerophospholipids. These findings suggest that the disturbances of gut microbiota by RIB may contribute to the onset of depressive-like behaviors via regulating glycerophospholipid metabolism, and providing new insight for understanding the function of microbiota-gut-brain axis in depression.

Abstract Background Fibrinogen plays pivotal roles in multiple biological processes. Genetic mutation of the fibrinogen coding genes can result in congenital fibrinogen disorders (CFDs). We identified a novel heterozygous missense mutation, FGG c.1168G > T (NCBI NM_000509.6), and conducted expression studies and functional analyses to explore the influence on fibrinogen synthesis, secretion, and polymerization. Methods Coagulation tests were performed on the patients to detect the fibrinogen concentration. Whole-exome sequencing (WES) and Sanger sequencing were employed to detect the novel mutation. Recombinant fibrinogen-producing Chinese hamster ovary (CHO) cell lines were built to examine the recombinant fibrinogen synthesis and secretion by western blotting and enzyme-linked immunosorbent assay (ELISA). The functional analysis of fibrinogen was performed by thrombin-catalyzed fibrin polymerization assay. In silico molecular analyses were carried out to elucidate the potential molecular mechanisms. Results The clinical manifestations, medical history, and laboratory tests indicated the diagnosis of hypodysfibrinogenemia with bleeding phenotype in two patients. The WES and Sanger sequencing revealed that they shared the same heterozygous missense mutation, FGG c.1168G > T. In the expression studies and functional analysis, the missense mutation impaired the recombinant fibrinogen's synthesis, secretion, and polymerization. Furthermore, the in silico analyses indicated novel mutation led to the hydrogen bond substitution. Conclusion The study highlighted that the novel heterozygous missense mutation, FGG c.1168G > T, would change the protein secondary structure, impair the “A: a” interaction, and consequently deteriorate the fibrinogen synthesis, secretion, and polymerization.

Abstract Objective The association between Metabolic Syndrome (MetS), its components, and the risk of osteoarthritis (OA) has been a topic of conflicting evidence in different studies. The aim of this present study is to investigate the association between MetS, its components, and the risk of OA using data from the UK Biobank. Methods A prospective cohort study was conducted in the UK Biobank to assess the risk of osteoarthritis (OA) related to MetS. MetS was defined according to the criteria set by the International Diabetes Federation (IDF). Additionally, lifestyle factors, medications, and the inflammatory marker C-reactive protein (CRP) were included in the model. Cox proportional hazards regression was used to calculate hazard ratios (HR) and 95% confidence intervals (CI). The cumulative risk of OA was analyzed using Kaplan–Meier curves and log-rank tests. To explore potential nonlinear associations between MetS components and OA risk, a restricted cubic splines (RCS) model was employed. In addition, the polygenic risk score (PRS) of OA was calculated to characterize individual genetic risk. Results A total of 45,581 cases of OA were identified among 370,311 participants, with a median follow-up time of 12.48 years. The study found that individuals with MetS had a 15% higher risk of developing OA (HR = 1.15, 95%CI:1.12–1.19). Additionally, central obesity was associated with a 58% increased risk of OA (HR = 1.58, 95%CI:1.5–1.66), while hyperglycemia was linked to a 13% higher risk (HR = 1.13, 95%CI:1.1–1.15). Dyslipidemia, specifically in triglycerides (HR = 1.07, 95%CI:1.05–1.09) and high-density lipoprotein (HR = 1.05, 95%CI:1.02–1.07), was also found to be slightly associated with OA risk. When stratified by PRS, those in the high PRS group had a significantly higher risk of OA compared to those with a low PRS, whereas no interaction was found between MetS and PRS on OA risks. Furthermore, the presence of MetS significantly increased the risk of OA by up to 35% in individuals with elevated CRP levels (HR = 1.35, 95% CI:1.3–1.4). Conclusion MetS and its components have been found to be associated with an increased risk of OA, particularly in individuals with elevated levels of CRP. These findings highlight the significance of managing MetS as a preventive and intervention measure for OA.

Inductive Wireless Power Transfer (IWPT) using magnetic induction has seen remarkable progress over the past few decades. Despite their growing popularity, IWPT systems suffer from output power instability due to variations in system parameters. This paper provides a comprehensive review of the strategies for maintaining stable output power under system parameters that deviate from the original design specifications. First, the root cause of power instability and the state-of-the-art techniques for avoiding the output power decrease are carefully examined. In addition, by comparing these methods, this paper clarifies their respective application scenarios and offers insights into their practical benefits. Furthermore, this paper outlines potential future advancements in improving the robustness and reliability of IWPT systems. As presented, the output power instability is induced by frequency mismatch and coupling coefficient variation. Resonant frequency regulation, operation frequency regulation, and coupling optimization are targeted techniques for the issues. Based on the comparison, respective application scenarios are clarified. Moreover, the trade-offs should be carefully weighed in terms of their impact, complexity, and cost. Future research directions on variable devices, closed-loop control, and new mechanisms for power stability enhancement are highlighted, thereby facilitating the pervasive application of IWPT systems.

Abstract Background Artichoke (Cynara scolymus L.) is a typical element of a traditional Mediterranean diet and has potential health advantages for insulin resistance (IR) and type 2 diabetes mellitus (T2DM). This study aims to evaluate the effect and underlying mechanism of artichoke water extract (AWE) on palmitate (PA)-induced IR in human hepatocellular carcinoma (HepG2) cells. Methods The effect of AWE on cell viability was determined using CCK8 assay. Cellular glucose uptake, glucose consumption, glucose production, and glycogen content were assessed after AWE treatment. The gene expression and protein levels were examined by real-time polymerase chain reaction (qRT-PCR) and western blotting. Results The results showed that AWE dose-dependently increased cell viability in IR HepG2 cells (P

Mode-locked microcombs with flat spectral profiles provide the high signal-to-noise ratio and are in high demand for wavelength division multiplexing (WDM)-based applications, particularly in future high-capacity communication and parallel optical computing. Here, we present two solutions to generate local relatively flat spectral profiles. One microcavity with ultra-flat integrated dispersion is pumped to generate one relatively flat single soliton source spanning over 150 nm. Besides, one extraordinary soliton crystal with single vacancy demonstrates the local relatively flat microcomb lines when the inner soliton spacings are slightly irregular. Our work paves a new way for soliton-based applications owing to the relatively flat spectral characteristics.

The positional accuracy of satellite imagery is essential for remote sensing cameras. However, vibrations and temperature changes during launch and operation can alter the exterior orientation parameters of remote sensing cameras, significantly reducing image positional accuracy. To address this issue, this article proposes an exterior orientation parameter variation real-time monitoring system (EOPV-RTMS). This system employs lasers to establish a full-link active optical monitoring path, which is free from time and space constraints. By simultaneously receiving star and laser signals with the star tracker, the system monitors changes in the exterior orientation parameters of the remote sensing camera in real time. Based on the in-orbit calibration geometric model, a new theoretical model and process for the calibration of exterior orientation parameters are proposed, and the accuracy and effectiveness of the system design are verified by ground experiments. The results indicate that, under the condition of a centroid extraction error of 0.1 pixel for the star tracker, the EOPV-RTMS achieves a measurement accuracy of up to 0.6″(3σ) for a single image. Displacement variation experiments validate that the measurement error of the system deviates by at most 0.05″ from the theoretical calculation results. The proposed EOPV-RTMS provides a new design solution for improving in-orbit calibration technology and image positional accuracy.

Abstract Background Genetic and lifestyle factors both contribute to the pathogenesis of bladder cancer, but the extent to which the increased genetic risk can be mitigated by adhering to a healthy lifestyle remains unclear. We aimed to investigate the association of combined lifestyle factors with bladder cancer risk within genetic risk groups. Methods We conducted a prospective study of 375 998 unrelated participants of European ancestry with genotype and lifestyle data and free of cancer from the UK biobank. We generated a polygenic risk score (PRS) using 16 single nucleotide polymorphisms and a healthy lifestyle score based on body weight, smoking status, physical activity, and diet. Cox models were fitted to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of genetic and lifestyle factors on bladder cancer. Results During a median follow-up of 11.8 years, 880 participants developed bladder cancer. Compared with those with low PRS, participants with intermediate and high PRS had a higher risk of bladder cancer (HR 1.29, 95% CI 1.07–1.56; HR 1.63, 95% CI 1.32–2.02, respectively). An optimal lifestyle was associated with an approximately 50% lower risk of bladder cancer than a poor lifestyle across all genetic strata. Participants with a high genetic risk and a poor lifestyle had 3.6-fold elevated risk of bladder cancer compared with those with a low genetic risk and an optimal lifestyle (HR 3.63, 95% CI 2.23 –5.91). Conclusions Adhering to a healthy lifestyle could substantially reduce the bladder cancer risk across all genetic strata, even for high-genetic risk individuals. For all populations, adopting an intermediate lifestyle is more beneficial than a poor one, and adhering to an optimal lifestyle is the ideal effective strategy for bladder cancer prevention.

Abstract Background Triple-negative breast cancer (TNBC) is a subtype of breast cancer with limited treatment options and poor prognosis. This study aimed to identify potential therapeutic targets based on the expression profiles of differentially expressed genes (DEGs) in TNBC. Methods The Limma package was used to identify DEGs in TCGA and GEO datasets. Immunohistochemical (IHC) analysis and western blotting were used to determine the expression of ZDHHC9 in TNBC tissues. Flow cytometry assay and tissue immunofluorescence analysis were used to detect infiltration of multiple immune cells in tumor tissue at different levels of ZDHHC9 expression. Results ZDHHC9 was identified as a key factor associated with resistance to ICB therapy through weighted gene co-expression network analysis (WGCNA) and single-cell RNA sequencing (scRNA-seq). Subsequently, immunohistochemical (IHC) analysis and western blotting verified that ZDHHC9 expression was elevated in TNBC cancer tissues and that elevated expression of ZDHHC9 was associated with the poor survival of patients with TNBC. Analysis of data from several public datasets revealed that patients with high ZDHHC9 expression had an increased proportion of Ki-67 + breast cancer cells and tended to be basal-like breast cancer. In addition, in vitro and in vivo experiments demonstrated that high expression of ZDHHC9 significantly predicted the efficacy and responsiveness of immunotherapy in TNBC. Conclusion These findings suggest that ZDHHC9 is a valuable marker for guiding the classification, diagnosis and prognosis of TNBC and developing specific targeted therapies.

In recent years, karst construction projects in the built-up area of Wuhan (capital of Hubei Province, China) are increasing, and the karst geological disasters have aroused social concerns. The actual engineering projects usually use shallow geophysical exploration methods to explore karst. This paper uses Spatial Auto-Correlation Method (SPAC) and electromagnetic Computerized Tomography (CT) to detect karst in urban built-up areas. Depending on the different physical properties of rock and soil, the SPAC method can better reveal the interface between soil and rock strata and the interface between soil layers. The electromagnetic CT method can identify strata according to the apparent absorption coefficient, which can better reveal the interface between soil and rock, the interface between the more intact and weathered rock. The SPAC method is mainly qualitative to measure the low-speed area, namely, the wrong geological body i.e., karst cave, but also can detect the fracture zone or filling mode of karst cave, and at the same time, cannot use exploration holes or logging observation. The electromagnetic CT method can accurately detect the location and scale of the karst caves and has a higher accuracy detecting karst bands. In addition, exploration holes or well logging observations are also expected to be conducted, and their detection effect is greatly affected by lithology.

Abstract High‐entropy alloys (HEAs) materials, as promising nanomaterials, have garnered significant attention from researchers due to their excellent performance in the field of hydrogen evolution reaction (HER). The four core effects of HEAs, including the high‐entropy effect, severe lattice distortion effect, sluggish diffusion effect, and cocktail effect, are pivotal in underpinning their remarkable mechanical and thermodynamic properties. Nevertheless, the intricate geometric and electronic structures of HEAs make their catalytic mechanisms exceptionally complex and challenging to decipher. In particular, a thorough analysis of the underlying factors responsible for the outstanding catalytic activity, selectivity, and the ability to maintain stable hydrogen production, even at high current densities, in HEAs is lacking. To provide a systematic exploration of the design and application of HEAs in HER systems, this review commences with an examination of the physicochemical properties of HEAs. It covers a wide range of topics, including the synthesis methods of HEAs, and the major reaction mechanisms of HERs, and presents innovative methods and approaches for designing HEAs specifically in the context of HERs.

Background: Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. Methods: We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. Results: Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. Conclusions: The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Abstract Sepsis‐associated encephalopathy (SAE) describes diffuse or multifocal cerebral dysfunction caused by the systemic inflammatory response to sepsis. SAE is a common neurological complication in patients in the middle and late stages of sepsis in the intensive care unit. Microglia, resident macrophages of the central nervous system, phagocytose small numbers of neuronal cells and apoptotic cells, among other cells, to maintain the dynamic balance of the brain's internal environment. The neuroinflammatory response induced by activated microglia plays a central role in the pathogenesis of various central nervous system diseases. In this paper, we systematically describe the functions and phenotypes of microglia, summarize how microglia mediate neuroinflammation and contribute to the occurrence and development of SAE, and discuss recent progress in autophagy‐ and microRNA‐mediated regulation of microglial activation to provide a theoretical basis for the prevention and treatment of SAE and identify related therapeutic targets.

Background: Exosomes play a role in intercellular communication and participate in the interaction between pancreatic ductal adenocarcinoma (PDAC) cells and immune cells. Macrophages can receive tumor cell–derived exosomes to polarize into M2-type macrophages, which can enhance the invasion and metastasis of pancreatic cancer, leading to poor prognosis. However, the mechanism by which pancreatic cancer cell–derived exosomes promote M2-type macrophages is still unclear. Methods: M2 macrophage–associated exosome-derived key module genes were identified by differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) analysis using exoRbase 2.0, The Cancer Genome Atlas (TCGA), and The International Cancer Genome Consortium (ICGC) databases. Multivariate Cox regression analysis was used to identify key prognostic genes and obtain regression coefficients to establish prognostic signature. Immune infiltration, tumor mutations, and GSEA among different risk groups were compared. exoRbase 2.0, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), HPA, and TISCH2 databases were used to further analyze the expression pattern of S100A9 in pancreatic cancer. In vitro experiments, cell-derived exosome isolation, quantitative polymerase chain reaction (qPCR), western blot, flow cytometry analysis, cell transfection, transwell assay, and CCK-8 assay were applied to investigate the roles of S100A9 in macrophage M2 polarization and tumor progression. Results: The key genes of PDAC-derived exosomes promoting M2-type macrophage polarization were identified, and a risk score model was established. The risk score is related to the expression of common immune checkpoints, immune score, and stromal score, and the tumor mutational burden and biological function of high- and low-risk groups were also different. S100A9 was positively correlated with M2-type macrophage marker. In addition, scRNA-seq data from the TISCH2 database revealed that S100A9 is predominantly expressed in pancreatic cancer cells and mono/macrophage cells, suggesting that S100A9 in pancreatic cancer cells could be received by macrophages, thereby inducing macrophage polarization. In vitro , we used exosomes from BxPC-3 cell lines to coculture macrophages and found that macrophages were mainly polarized toward M2 type, which further promoted the proliferation and metastasis of PDAC. Conclusions: Our study established a reliable risk score model for PDAC-derived exosomes and M2 macrophages, identified the important role of S100A9 in macrophage M2 polarization, which provides a new strategy for the diagnosis and treatment of PDAC, and strengthened the understanding of the mechanism of tumor development and metastasis.