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BackgroundExisting studies investigating the impact of serum calcium (Ca), phosphate (P), 25 hydroxyvitamin D (25[OH]D), and parathyroid hormone (PTH) levels on kidney function have produced inconsistent results. Further research is needed to establish the direct causal relationship between these factors and kidney function.MethodsThe study used genome-wide association study datasets for exposure and outcome, mainly derived from the UK Biobank and CKDGen Consortium, with sample sizes ranging from 3,310 to 480,699 individuals of European ancestry. Heritability and genetic correlations among these phenotypes were assessed using linkage disequilibrium score regression (LDSC) and phenotypes with a heritability z-score

Multi-site PM2.5 prediction has emerged as a crucial approach, given that the accuracy of prediction models based solely on data from a single monitoring station may be constrained. However, existing multi-site PM2.5 prediction methods predominantly rely on recurrent networks for extracting temporal dependencies and overlook the domain knowledge related to air quality pollutant dispersion. This study aims to explore whether a superior prediction architecture exists that not only approximates the prediction performance of recurrent networks through feedforward networks but also integrates domain knowledge of PM2.5. Consequently, we propose a novel spatio-temporal attention causal convolutional neural network (Causal-STAN) architecture for predicting PM2.5 concentrations at multiple sites in the Yangtze River Delta region of China. Causal-STAN comprises two components: a multi-site spatio-temporal feature integration module, which identifies temporal local correlation trends and spatial correlations in the spatio-temporal data, and extracts inter-site PM2.5 concentrations from the directional residual block to delineate directional features of PM2.5 concentration dispersion between sites; and a temporal causal attention convolutional network that captures the internal correlation information and long-term dependencies in the time series. Causal-STAN was evaluated using one-year data from 247 sites in mainland China. Compared to six state-of-the-art baseline models, Causal-STAN achieves optimal performance in 6-hour future predictions, surpassing the recurrent network model and reducing the prediction error by 8%–10%.

The aurora arc is a separate auroral structure from the aurora oval, whose location and morphology are related to various solar-terrestrial circumstances. However, because of the low occurring frequency of aurora arc and the lack of the automatic identification technique, it can only be manually distinguished from a huge number of observed images, which is very inefficient. In order to improve the identification efficiency, we propose an identification algorithm based on YOLOX network and Convolutional Block Attention Module attention mechanism. Using the aurora images observed by Special Sensor Ultraviolet Spectrographic Imager carried by the Defense Meteorological Satellite Program F16-F19 satellites from 2013 to 2019, the automatic detection models for global and local areas were trained separately. The identification outputs will be integrated by calculating the intersection. According to the test results, the event identification precision is 86% and the position identification precision is 79%, both of which are greater than the results before integration. Therefore, the proposed method is not only able to identify whether the image contains the aurora arcs, but also accurately locate them, making it a highly effective tool for the advancement of future study.

PurposeAimed to assess the impact of wearable device-based aerobic exercise on the physical and mental well-being of women with breast cancer (BC) undergoing chemotherapy.MethodsForty adult women with BC who underwent anthracycline-based chemotherapy were randomly allocated to the exercise group (n = 21) or the control group (n = 19). Both groups received standard health education and oncology care. In addition, the exercise group wore wearable devices to engage in moderate to high-intensity (50–90% HRmax) aerobic exercise during chemotherapy, while the control group did not carry out exercise intervention. Health-related physical fitness level, physical activity energy expenditure (PAEE), anxiety and depression scores, sleep quality, cancer-related fatigue, and overall quality of life (QoL), were assessed both before (prior to the first chemotherapy session) and after (prior to the fifth chemotherapy session) the exercise intervention. Exercise-related adverse events, exercise compliance, number and severity of gastrointestinal reactions and myelosuppression occurred were recorded during the exercise intervention.ResultsAfter the intervention, compared to the control group, the exercise group (1) had significantly higher relative VO2peak (p = 0.003) and handgrip strength (p

ObjectiveNumerous studies emphasize the pivotal role of inflammation in metabolic dysfunction-associated steatotic liver disease (MASLD) development. Some link specific systemic immune biomarkers (e.g., systemic immuno-inflammatory index [SII], neutrophil-to-albumin ratio [NPAR] and neutrophil-to-lymphocyte ratio [NLR]) to hepatic steatosis risk. However, the relevance of other markers like systemic immune-inflammation index [SIRI], platelet-to-lymphocyte ratio [PLR] and lymphocyte/monocyte ratio [LMR] in MASLD remains unclear. Limited literature covers all six markers together. This study aims to investigate the association between SII, SIRI, LMR, NLR, PLR, and NPAR and MASLD, assessing their predictive value.MethodsIn this cross-sectional analysis of adults from NHANES (2007–2018), we investigated the relationship between six systemic immune biomarkers, stratified by quartiles: quartile1 (Q1), quartile2 (Q2), quartile3 (Q3) and quartile4 (Q4), and the outcome of MASLD assessed by Fatty Liver Index (FLI) and United States Fatty Liver Index (USFLI). Logistic regression and restricted cubic splines (RCS) were employed to assess the association between systemic immune biomarkers and MASLD risks. Propensity score matching controlled for potential confounders, and receiver operating characteristic (ROC) curve analysis evaluated the biomarkers’ predictive performances for MASLD. Subgroup and interaction analysis were conducted to explore the effects of systemic immune biomarkers on MASLD risks. Multicollinearity was quantified using the variance inflation factor.ResultsIn total, 14,413 participants were included and 6,518 had MASLD. Compared with non-MASLD, participants with MASLD had higher SII, SIRI, NLR, PLR, and NPAR (p 0.05). The prevalence of MASLD increased with the Q4 of SII [OR = 1.47, 95%CI (1.24, 1.74)], SIRI [OR = 1.30, 95%CI (1.09, 1.54)], NLR [OR = 1.25, 95%CI (1.04, 1.49)], PLR [OR = 1.29, 95%CI (1.09, 1.53)] and NPAR [OR = 1.29, 95%CI (1.09, 1.54)] compared to the Q1 after adjusting for the bias caused by potential confounders. However, the propensity score matching analysis only supported an association between the highest SII, SIRI, NLR NPAR and the risk of MASLD. The results of the subgroup analysis showed considerable robustness in the relationship.ConclusionHigher SII, SIRI, NLR and NPAR were positively associated with a heightened risk of MASLD. NPAR showed the superior predictive value, followed by SII, SIRI and NLR. This needs to be validated in additional longitudinal studies and clinical trials.

Deep learning models have made great accomplishments in space weather forecasting. The critical frequency of the ionospheric F2 layer (foF2) is a key ionospheric parameter, which can be understood and predicted by some advanced new deep learning technologies. In this paper, we utilized an Informer architecture model to predict foF2 for several hours up to 48 h and analyzed its variations during periods of quiet, moderate, and intense geomagnetic conditions. The Informer method forecasts the temporal variations of foF2 by processing and training the past and present foF2 data from the Haikou station, China, during 2006–2014. It is evident that the Informer–foF2 model achieves better prediction performance than the widely used long short-term memory model. The Informer–foF2 model captures the correlation features within the foF2 time series and better predicts the variations ranging for hours up to days during different geomagnetic activities.

BackgroundColorectal cancer (CRC) is an aggressive primary intestinal malignancy with the third-highest incidence and second-highest mortality among all cancer types worldwide. Transcription factors (TFs) regulate cell development and differentiation owing to their ability to recognize specific DNA sequences upstream of genes. Numerous studies have demonstrated a strong correlation between TFs, the etiology of tumors, and therapeutic approaches. Here, we aimed to explore prognosis-related TFs and comprehend their carcinogenic mechanisms, thereby offering novel insights into the diagnosis and management of CRC.Materials and MethodsDifferentially expressed TFs between CRC and normal tissues were identified leveraging The Cancer Genome Atlas database, Weighted correlation network analysis and Cox regression analysis were performed to identify prognosis-related TFs. The cellular functions of hub TF zinc finger E-box binding homeobox 1 (ZEB1) were determined using by 5-ethynyl-2′-deoxyuridine and cell invasion assays in CRC cells. RNA-sequencing, Kyoto Encyclopedia of Genes and Genomes enrichment, and gene set enrichment analyses were used to identify the cellular processes in which ZEB1 participates. Immunoaffinity purification, silver staining mass spectrometry, and a chromatin immunoprecipitation assay were conducted to search for proteins that might interact with ZEB1 and the target genes they jointly regulate.ResultsThirteen central TFs related to prognosis were identified through bioinformatics analysis techniques. Among these TFs, ZEB1 emerged as the TF most closely associated with CRC, as determined through a combination of regulatory network diagrams, survival curves, and phenotype analyses. ZEB1 promotes CRC cell growth by recruiting the NuRD(MTA1) complex, and the ZEB1/NuRD(MTA1) complex transcriptionally represses glycolysis-associated tumor suppressor genes.ConclusionOur study not only identified a hub biomarker related to CRC prognosis but also revealed the specific molecular mechanisms through which ZEB1 affects cancer progression. These insights provide crucial evidence for the diagnosis of CRC and potential treatment opportunities.

BackgroundCancers arise from genetic and epigenetic abnormalities that affect oncogenes and tumor suppressor genes, compounded by gene mutations. The N6-methyladenosine (m6A) RNA modification, regulated by methylation regulators, has been implicated in tumor proliferation, differentiation, tumorigenesis, invasion, and metastasis. However, the role of m6A modification patterns in the tumor microenvironment of gastric cancer (GC) remains poorly understood.Materials and methodsIn this study, we analyzed m6A modification patterns in 267 GC samples utilizing 31 m6A regulators. Using consensus clustering, we identified two unique subgroups of GC. Patients with GC were segregated into high- and low-infiltration cohorts to evaluate the infiltration proportions of the five prognostically significant immune cell types. Leveraging the differential genes in GC, we identified a “green” module via Weighted Gene Co-expression Network Analysis. A risk prediction model was established using the LASSO regression method.ResultsThe “green” module was connected to both the m6A RNA methylation cluster and immune infiltration patterns. Based on “Module Membership” and “Gene Significance”, 37 hub genes were identified, and a risk prediction model incorporating nine hub genes was established. Furthermore, methylated RNA immunoprecipitation and RNA Immunoprecipitation assays revealed that YTHDF1 elevated the expression of DNMT3B, which synergistically promoted the initiation and development of GC. We elucidated the molecular mechanism underlying the regulation of DNMT3B by YTHDF1 and explored the crosstalk between m6A and 5mC modification.Conclusionm6A RNA methylation regulators are instrumental in malignant progression and the dynamics of tumor microenvironment infiltration of GC. Assessing m6A modification patterns and tumor microenvironment infiltration characteristics in patients with GC holds promise as a valuable prognostic biomarker.

The Yongle blue hole (YBH), situated in the South China Sea, represents a compelling subject of study in marine microbiology due to its unique redox-layered microbial ecosystems. However, the diversity and ecology of microbial eukaryotes within the YBH remains underexplored. This study endeavors to bridge this gap through the application of the in situ microbial filtration and fixation (ISMIFF) device to collect 0.22–30 μm microbial samples from 21 water layers of YBH. Subsequent extraction of 18S rRNA metagenomic reads of 21 metagenomes and 10 metatranscriptomes facilitated a comprehensive analysis of community structures. Findings revealed a pronounced superiority in the diversity and richness of eukaryotic microorganisms in the oxic zone compared to its suboxic and anoxic counterparts. Notably, Dinophyceae and Maxillopoda emerged as the predominant taxa based on the analysis of the 18S rRNA reads for the V4 and V9 regions, which showed stratification In their relative abundance and suggested their potential role in the thermo-halocline boundaries and oxic-anoxic interface. Specifically, In these eukaryotic microbial communities, Dinophyceae exhibited significant abundance at 20 m (20.01%) and 105 m (26.13%) water depths, while Maxillopoda was prevalent at 40 m (22.84%), 80 m (23.19%), and 100 m (15.42%) depths. A part of these organisms, identified as larvae and protists, were likely attracted by swarming chemosynthetic bacterial prey prevailing at the thermo-halocline boundaries and oxic-anoxic interface. Furthermore, the phylogenetic relationships of the major 18S operational taxonomic units (OTUs) showed a close adjacency to known species, except for three Dinophyceae OTUs. In conclusion, this study provides critical insights into the vertical distribution and transcriptional activity of

Existing transient stability analysis of grid-following (GFL) converters mainly focuses on the dynamics of the phase-locked loop (PLL), while current loop dynamics are usually neglected due to their faster response than PLL. However, this article reveals that active current may not be able to track its reference quickly during severe grid faults even with high current loop bandwidth, which leads to a non-negligible impact on the transient stability of GFL converters. Furthermore, this article discusses the intrinsic mechanism of why active current cannot track its reference quickly during severe grid faults and establishes a refined third-order transient synchronization model that offers a more accurate assessment of transient stability during severe grid faults than the conventional second-order model.

In the contemporary epoch, cancer stands as the predominant cause of premature global mortality, necessitating a focused exploration of molecular markers and advanced therapeutic strategies. N6-methyladenosine (m6A), the most prevalent mRNA modification, undergoes dynamic regulation by enzymes referred to as methyltransferases (writers), demethylases (erasers), and effective proteins (readers). Despite lacking methylation activity, RNA-binding motif protein 15 (RBM15), a member of the m6A writer family, assumes a crucial role in recruiting the methyltransferase complex (MTC) and binding to mRNA. Although the impact of m6A modifications on cancer has garnered widespread attention, RBM15 has been relatively overlooked. This review briefly outlines the structure and operational mechanism, and delineates the unique role of RBM15 in various cancers, shedding light on its molecular basis and providing a groundwork for potential tumor-targeted therapies.

The cathode in lithium-selenium (Li-Se) batteries has garnered extensive attention owing to its superior specific capacity and enhanced conductivity compared to sulfur. Nonetheless, the adoption and advancement of Li-Se batteries face significant challenges due to selenium’s low reactivity, substantial volume fluctuations, and the shuttle effect associated with polyselenides. Single-atom catalysts (SACs) are under the spotlight for their outstanding catalytic efficiency and optimal atomic utilization. To address the challenges of selenium’s low chemical activity and volume expansion in Li-Se batteries, through electrospun, we have developed a lotus root-inspired carbon nanofiber (CNF) material, featured internal multi-channels and anchored with molybdenum (Mo) single atoms (Mo@CNFs). Mo single atoms significantly enhance the conversion kinetics of selenium (Se), facilitating rapid formation of Li2Se. The internally structured multi-channel CNF serves as an effective host matrix for Se, mitigating its volume expansion during the electrochemical process. The resulting cathode, Se/Mo@CNF composite, exhibits a high discharge specific capacity, superior rate performance, and impressive cycle stability in Li-Se batteries. After 500 cycles at a current density of 1 C, it maintains a capacity retention rate of 82% and nearly 100% coulombic efficiency (CE). This research offers a new avenue for the application of single-atom materials in enhancing advanced Li-Se battery performance.

BackgroundMany studies demonstrated the safety and efficacy of SBRT in the treatment of elderly patients with early-stage non-small cell lung cancer (NSCLC). However, those studies focused on patients with peripheral lung cancer. This study aimed to evaluate the clinical efficacy and toxicity of SBRT in elderly patients with stage I-II central NSCLC in single institution.MethodsFrom April 2009 to January 2020, a retrospective study was conducted on patients ≥ 65 years old with stage I-II NSCLC that was centrally localized and treated with SBRT at a single institution. Absolute C-reactive protein (CRP)/albumin ratio (CAR) and body mass index (BMI) recorded at pretreatment were analyzed. Endpoints included overall survival (OS), progression-free survival (PFS), cancer-specific death, noncancer-specific death, local progression (LP) and distant progression (DP).ResultsStereotactic body radiation treatment (SBRT) was administered to a total of 44 patients. The most common dose fractionation schedule was 60 Gy given in 5 fractions. The median PFS of the cohort was 31 months (95% CI, 19.47–42.53 months). The median OS of all patients was 69 months (95% CI, 33.8–104.2 months). The median time to noncancer-specific death was 54.5 months. The median time to cancer-specific death was 36 months. The cumulative incidences of cancer-specific death at 1 year, 5 years, and 10 years were 11.63% (95%CI, 4.2–23.23%), 42.99% (95%CI, 27.56–57.53%), and 65.94% (95%CI, 45.76–80.1%), respectively. pre-SBRT BMI of ≤ 22.77 (HR 4.60, 95% CI 1.84–11.51, P=0.001) and pre-SBRT CAR of ≤0.91 (HR 5.19, 95% CI 2.15–12.52, P

BackgroundThis study aimed to investigate whether quantitative radiomics features extracted from conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) of primary breast lesions can help noninvasively predict axillary lymph nodes metastasis (ALNM) in breast cancer patients.MethodA total of 111 breast cancer patients with 111 breast lesions were prospectively enrolled. All the included patients received presurgical CUS screening and CEUS examination and were randomly assigned to the training and validation sets at a ratio of 7:3 (n = 78 versus 33). Radiomics features were respectively extracted based on CUS and CEUS using the PyRadiomics package. The max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) analyses were used for feature selection and radiomics score calculation in the training set. The variance inflation factor (VIF) was performed to check the multicollinearity among selected predictors. The best performing model was selected to develop a nomogram using binary logistic regression analysis. The calibration and clinical utility of the nomogram were assessed.ResultsThe model combining CUS reported ALN status, CUS radiomics score (CUS-radscore) and CEUS radiomics score (CEUS-radscore) exhibited the best performance. The areas under the curves (AUC) of our proposed nomogram in the training and external validation sets were 0.845 [95% confidence interval (CI), 0.739-0.950] and 0.901 (95% CI, 0.758-1). The calibration curves and decision curve analysis (DCA) demonstrated the nomogram’s robust consistency and clinical utility.ConclusionsThe established nomogram is a promising prediction tool for noninvasive prediction of ALN status. The radiomics features based on CUS and CEUS can help improve the predictive performance.

Introduction:The diagnostic accuracy of traditional imaging examination in predicting ypT stage of rectal cancer after neoadjuvant therapy is significantly reduced, which would affect patients’ subsequent treatment choices. This study aimed to investigate the use of endorectal shear wave elastography (SWE) for diagnosing ypT0 stage of rectal cancer after neoadjuvant chemoradiotherapy (nCRT).Methods:Sixty patients with rectal cancer were prospectively recruited in this study. Data on endorectal ultrasound (ERUS) and SWE parameters were collected before nCRT and 6–8 weeks after nCRT. Postoperative pathological results were the gold standard for evaluating the diagnostic accuracy of SWE and ERUS in predicting the ypT0 stage of rectal cancer after nCRT. Receiver operating characteristic (ROC) curve analysis was used to determine the cut-off values of the SWE parameters that best corresponded to the ypT0 stage and analyze the sensitivity, specificity, and accuracy.Results:The diagnostic accuracies of using ERUS to predict the ypT and ypT0 stages of rectal cancer after nCRT were 58.1% (18/31) and 64.3% (9/14), respectively. The ROC curve was constructed with the lesion’s Emean, Emean corrected (EC), Emean difference (ED), Emean corrected differencede (ECD), Emean descendding rate (EDR) and Emean corrected descendding rate (ECDR) values after nCRT, the cut-off values of diagnosing the ypT0 stage were 64.40 kPa, 55.45 kPa, 72.55 kPa, 73.75 kPa, 50.15%, and 55.93%, respectively; the area under the curve (AUC) for diagnosing the ypT0 stage was 0.924, 0.933, 0.748, 0.729, 0.857 and 0.861, respectively. The EC value showed the best diagnostic performance.Conclusion:SWE could improve the accuracy of conventional ERUS in diagnosing the ypT0 stage of rectal cancer after nCRT. It is expected to become a new method to help predict pathological complete responses in clinical practice and provide new evidence for the watch-and-wait approach.

Background and aimsCuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusion injury (HIRI).MethodsThe datasets related to HIRI were sourced from the Gene Expression Omnibus database. The comparative analysis of differential gene expression involving CRGs was performed between HIRI and normal liver samples. Correlation analysis, function enrichment analyses, and protein-protein interactions were employed to understand the interactions and roles of these genes. Machine learning techniques were used to identify hub genes. Additionally, differences in immune cell infiltration between HIRI patients and controls were analyzed. Quantitative real-time PCR and western blotting were used to verify the expression of the hub genes.ResultsSeventy-five HIRI and 80 control samples from three databases were included in the bioinformatics analysis. Three hub CRGs (NLRP3, ATP7B and NFE2L2) were identified using three machine learning models. Diagnostic accuracy was assessed using a receiver operating characteristic (ROC) curve for the hub genes, which yielded an area under the ROC curve (AUC) of 0.832. Remarkably, in the validation datasets GSE15480 and GSE228782, the three hub genes had AUC reached 0.904. Additional analyses, including nomograms, decision curves, and calibration curves, supported their predictive power for diagnosis. Enrichment analyses indicated the involvement of these genes in multiple pathways associated with HIRI progression. Comparative assessments using CIBERSORT and gene set enrichment analysis suggested elevated expression of these hub genes in activated dendritic cells, neutrophils, activated CD4 memory T cells, and activated mast cells in HIRI samples versus controls. A ceRNA network underscored a complex regulatory interplay among genes. The genes mRNA and protein levels were also verified in HIRI-affected mouse liver tissues.ConclusionOur findings have provided a comprehensive understanding of the association between cuproptosis and HIRI, establishing a promising diagnostic pattern and identifying latent therapeutic targets for HIRI treatment. Additionally, our study offers novel insights to delve deeper into the underlying mechanisms of HIRI.

When detecting tomato leaf diseases in natural environments, factors such as changes in lighting, occlusion, and the small size of leaf lesions pose challenges to detection accuracy. Therefore, this study proposes a tomato leaf disease detection method based on attention mechanisms and multi-scale feature fusion. Firstly, the Convolutional Block Attention Module (CBAM) is introduced into the backbone feature extraction network to enhance the ability to extract lesion features and suppress the effects of environmental interference. Secondly, shallow feature maps are introduced into the re-parameterized generalized feature pyramid network (RepGFPN), constructing a new multi-scale re-parameterized generalized feature fusion module (BiRepGFPN) to enhance feature fusion expression and improve the localization ability for small lesion features. Finally, the BiRepGFPN replaces the Path Aggregation Feature Pyramid Network (PAFPN) in the YOLOv6 model to achieve effective fusion of deep semantic and shallow spatial information. Experimental results indicate that, when evaluated on the publicly available PlantDoc dataset, the model’s mean average precision (mAP) showed improvements of 7.7%, 11.8%, 3.4%, 5.7%, 4.3%, and 2.6% compared to YOLOX, YOLOv5, YOLOv6, YOLOv6-s, YOLOv7, and YOLOv8, respectively. When evaluated on the tomato leaf disease dataset, the model demonstrated a precision of 92.9%, a recall rate of 95.2%, an F1 score of 94.0%, and a mean average precision (mAP) of 93.8%, showing improvements of 2.3%, 4.0%, 3.1%, and 2.7% respectively compared to the baseline model. These results indicate that the proposed detection method possesses significant detection performance and generalization capabilities.

Durability is a desired characteristic for all battery packs in Electric Vehicles. In this study, the service life of the EV battery pack under real-world operating conditions is projected using an Arrhenius mathematical simulation model. The model comprises a 39.2 kWh EV Lithium-Ion battery pack integrated with a three-phase inverter to convert the battery pack’s Direct Current output to Alternating Current. In addition, the Alternating Current output is coupled to a 100 kW permanent magnet synchronous motor, which is regarded as the load. A field-oriented controller provides pulse width-modulated output signals that are supplied back to the inverter to generate the correct driving current. Variable conditions of charge rate (C-rate: 1.25C − 4C), discharge rate (C-rate: 0.5C − 4C), temperature (25°C–60°C), and depth of discharge (30%–90%) are evaluated to determine the battery pack’s service life. Under a 4C charge rate/0.5C discharge rate and 50% depth of discharge, the modeling results indicate the battery pack has a service life of approximately 6,000 h at low temperatures (25°C) and roughly 3,000 h at high temperatures (60°C). The model has been validated by comparing the results with experimental data from the literature.

BackgroundsThe value of circulating microRNA (miR)-155 for breast cancer (BC) diagnosis may differ in different studies. Therefore, we conducted this systematic review and meta-analysis to evaluate the potential application of circulating miR-155 in the diagnosis of BC.MethodsArticles published before December 2023 and in English were searched in these databases: PubMed, Web of Science, Medline, EMBASE and Google Scholar. A summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR) were calculated from the true positive (TP), true negative (TN), false positive (FP) and false negative (FN) of each study. Additionally, the summary receive-operating characteristics (SROC) curve was constructed to summarize the TP and FP rates.ResultsThe pooled parameters calculated were as follows: sensitivity, 0.93 (95% CI: 0.83-0.97); specificity, 0.85 (95% CI: 0.74-0.92); PLR, 6.4 (95% CI: 3.4-11.9); NLR, 0.09 (95% CI: 0.04-0.20); and DOR, 74 (95% CI: 22-247). The analysis showed a significant heterogeneity (sensitivity, I2 = 95.19%, p < 0.001; specificity, I2 = 95.29%, p < 0.001; DOR, I2 = 92.9%, p < 0.001). The SROC curve was with an area under curve (AUC) of 0.95 (95% CI: 0.93-0.97).ConclusionCirculating miR-155 has a potential in the diagnosis of BC.

ObjectiveAcute myocardial infarction (AMI) is a severe cardiovascular disease that threatens human life and health globally. N6-methyladenosine (m6A) governs the fate of RNAs via m6A regulators. Nevertheless, how m6A regulators affect AMI remains to be deciphered. To solve this issue, an integrative analysis of m6A regulators in AMI was conducted.MethodsWe acquired transcriptome profiles (GSE59867, GSE48060) of peripheral blood samples from AMI patients and healthy controls. Key m6A regulators were used for LASSO, and consensus clustering was conducted. Next, the m6A score was also computed. Immune cell infiltration, ferroptosis, and oxidative stress were evaluated. In-vitro and in-vivo experiments were conducted to verify the role of the m6A regulator ALKBH5 in AMI.ResultsMost m6A regulators presented notable expression alterations in circulating cells of AMI patients versus those of controls. Based on key m6A regulators, we established a gene signature and a nomogram for AMI diagnosis and risk prediction. AMI patients were classified into three m6A clusters or gene clusters, respectively, and each cluster possessed the unique properties of m6A modification, immune cell infiltration, ferroptosis, and oxidative stress. Finally, the m6A score was utilized to quantify m6A modification patterns. Therapeutic targeting of ALKBH5 greatly alleviated apoptosis and intracellular ROS in H/R-induced H9C2 cells and NRCMs.ConclusionAltogether, our findings highlight the clinical significance of m6A regulators in the diagnosis and risk prediction of AMI and indicate the critical roles of m6A modification in the regulation of immune cell infiltration, ferroptosis, and oxidative stress.

Both overall survival (OS) and disease-specific survival (DSS) are significant when determining a patient’s prognosis for breast cancer (BC). The effect of DSS-related microRNAs on BC susrvival, however, is not well understood. Here, we spotted differentially expressed miRNAs (DEMs) in the TCGA database of BC DSS, identified eight DSS-related miRNAs, and constructed a risk model. AUC values at 1, 3, and 5 years were 0.852, 0.861, and 0.868, respectively, indicating a risk model’s excellent prognostic prediction ability. Then, we validated miRNA roles in BC OS and finally defined miR-551b as an independently prognostic miRNA in BC. According to function analysis, miR-551b is strongly linked with the emergence and spread of cancer, including protein ubiquitination, intracellular protein transport, metabolic pathways, and cancer pathways. Moreover, we confirmed the low expression of miR-551b in BC tissue and cells. After miR-551b inhibition or overexpression, cell function was either dramatically increased or diminished, respectively, indicating that miR-551b could regulate BC proliferation, invasion, and migration. In conclusion, we thoroughly clarified BC-related miRNAs on DSS and OS and verified miR-551b as a crucial regulator in the development and prognosis of cancer. These results can offer fresh ideas for BC therapy.

BackgroundEnhanced recovery after surgery (ERAS) has been widely used in adult surgery. However, few studies have reported the efficacy of ERAS in paediatric patients with Meckel's diverticulum (MD), the aim of the study was to prospectively evaluate the safety and efficacy of ERAS in treating MD.MethodsA prospective randomised controlled study of children with MD admitted to our hospital from Jan 1, 2021 to Dec 31, 2023 were conducted, we developed and implemented an ERAS program for this patients. All cases were strictly selected according to the inclusion and exclusion criteria. Among these patients, they were randomly assigned to the ERAS group or the traditional (TRAD) group with random number table row randomization. The main observational indicators were operation time, intraoperative hemorrhage, FLACC pain scale results on 2 h, 6 h, 12 h, 24 h after surgery, length of postoperative stay (LOPS), time to first defecation, time to first eating after surgery, time to discontinuation of intravenous infusion, total treatment cost, incidence of postoperative complications, 30-day readmission rate and parental satisfaction rate.ResultsA total of 50 patients underwent Meckel's diverticulectomy during this period, 7 patients were excluded, 23 patients were assigned to the ERAS group and 20 patients were assigned to the TRAD group. There were no significant differences in demographic data and operation time, intraoperative hemorrhage. The FLACC pain scale results on 2 h, 6 h, 12 h, 24 h after surgery were significantly lower in the ERAS group. The LOPS was 6.17 ± 0.89 days in the ERAS group and 8.30 ± 1.26 days in the TRAD group, resulting in a significantly shorter LOPS in ERAS group. ERAS could also reduce the first postoperative defecation time, the time to first eating after surgery and the time to discontinuation of intravenous infusion. The treatment cost was decreased in the ERAS group. The rate of complications and 30-day readmission were not significantly different between the two groups.ConclusionsIn this single-center study, the ERAS protocol for patients with MD requiring surgery was safe and effective.

ObjectiveRecently, 10 plasmid-mediated mobile colistin resistance genes, mcr-1 to mcr-10, and their variants have been identified, posing a new threat to the treatment of clinical infections caused by Gram-negative bacteria. Our objective was to develop a rapid, sensitive, and accurate molecular assay for detecting mcr genes in clinical isolates.MethodsThe primers and corresponding TaqMan-MGB probes were designed based on the sequence characteristics of all reported MCR family genes, multiplex Taqman-MGB probe-based qPCR assays were developed and optimized, and the sensitivity, specificity and reproducibility of the method were evaluated. The assay contained 8 sets of primers and probes in 4 reaction tubes, each containing 2 sets of primers and probes.ResultsThe standard curves for both the single and multiplex systems showed good linearity (R2 > 0.99) between the starting template amount and the Ct value, with a lower limit of detection of 102 copies/μL. The specificity test showed positive amplification results only for strains containing the mcr genes, whereas the other strains were negative. The results of intra-and inter-group repeatability experiments demonstrated the stability and reliability of the newly developed method. It was used to detect mcr genes in 467 clinically-obtained Gram-negative isolates, which were multidrug-resistant. Twelve strains containing the mcr genes were detected (seven isolates carrying mcr-1, four isolates carrying mcr-10, and one isolate carrying mcr-9). The products amplified by the full-length PCR primer were identified by sequencing, and the results were consistent with those of the multiplex qPCR method.ConclusionThe assay developed in this study has the advantages of high specificity, sensitivity, and reproducibility. It can be used to specifically detect drug-resistant clinical isolates carrying the mcr genes (mcr-1 to mcr-10), thus providing a better basis for clinical drug treatment and drug resistance research.

In the context of developing a new era, the pharmaceutical supply chain market has gradually transformed from a seller’s market to a buyer’s market. The closer the consumers are, the greater the market pricing power, so the pharmaceutical market power of manufacturers and retailers has also changed. This study considers the effect of service on the pricing strategy of the pharmaceutical platform supply chain. The study aimed to coordinate optimization, and the coordination strategy of the pharmaceutical platform supply chain of complementary products is discussed mainly by researching the price and service factors. Various situations are studied by hypothesis and model solving. This study uses Stackelberg game decision-making. Manufacturers are at the forefront of platform supply chain decisions. The research found that the price was lower under centralized decision-making than under decentralized decision-making. Coordination between price and service levels needs attention in the pharmaceutical platform supply chain of complementary products, and the service level should be controlled within a certain range. Only by improving the service level can enterprises maximize profits, providing a theoretical basis for pharmaceutical supply chain pricing strategy research. Supply chain members must strive to improve service levels to improve medical supply consumers’ (patients) psychological satisfaction level. Service levels do not fully mitigate channel conflict. Therefore, pharmaceutical complements have become a way to alleviate the conflicts in the pharmaceutical platform supply chain.

BackgroundIncreased arterial stiffness and low handgrip strength (HGS) are associated with poor health outcomes and are a severe health risk for older adults. However, there is limited evidence and mixed results on whether there is an association between them. Therefore, this study focused on the association between arterial stiffness and HGS in relatively healthy older adults in Beijing, China.MethodsIn 2016, 2,217 adult volunteers were recruited in Beijing. Brachial-ankle pulse wave velocity (baPWV) and the ankle-brachial index were measured using an automatic vascular profiling system. Carotid artery intima-media thickness and common carotid artery-internal diameter (CCAID) were evaluated using Doppler ultrasound, and HGS was measured with a dynamometer. Low HGS was determined using the Asian Sarcopenia Working Group 2019 criteria. Multivariate linear and logistic regressions evaluated the relationship between arterial stiffness and HGS.ResultsUltimately, 776 relatively healthy older adults (mean age 69.05 ± 6.46 years) were included. Based on the AWGS2019 criteria, 137 participants were defined as having low HGS. Compared to the normal HGS group, the low HGS group was older and had higher baPWV (p

IntroductionThere are no standardized assessment criteria for selecting nutritional risk screening tools or indicators to assess reduced muscle mass (RMM) in the Global Leadership Initiative on Malnutrition (GLIM) criteria. We aimed to compare the consistency of different GLIM criteria with Subjective Global Assessment (SGA) and protein-energy wasting (PEW).MethodsIn this study, nutritional risk screening 2002 first four questions (NRS-2002-4Q), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Mini-Nutritional Assessment Short-Form (MNA-SF) tools were used as the first step of nutritional risk screening for the GLIM. The RMM is expressed using different metrics. The SGA and PEW were used to diagnose patients and classify them as malnourished and non-malnourished. Kappa (κ) tests were used to compare the concordance between the SGA, PEW, and GLIM of each combination of screening tools.ResultsA total of 157 patients were included. Patients with Chronic kidney disease (CKD) stage 1–3 accounted for a large proportion (79.0%). The prevalence rates of malnutrition diagnosed using the SGA and PEW were 18.5% and 19.7%, respectively. The prevalence of GLIM-diagnosed malnutrition ranges from 5.1% to 37.6%, depending on the different screening methods for nutritional risk and the different indicators denoting RMM. The SGA was moderately consistent with the PEW (κ = 0.423, p

Low temperature is a critical environmental stress factor that restricts crop growth and geographical distribution, significantly impacting crop quality and yield. When plants are exposed to low temperatures, a series of changes occur in their external morphology and internal physiological and biochemical metabolism. This article comprehensively reviews the alterations and regulatory mechanisms of physiological and biochemical indices, such as membrane system stability, redox system, fatty acid content, photosynthesis, and osmoregulatory substances, in response to low-temperature stress in plants. Furthermore, we summarize recent research on signal transduction and regulatory pathways, phytohormones, epigenetic modifications, and other molecular mechanisms mediating the response to low temperatures in higher plants. In addition, we outline cultivation practices to improve plant cold resistance and highlight the cold-related genes used in molecular breeding. Last, we discuss future research directions, potential application prospects of plant cold resistance breeding, and recent significant breakthroughs in the research and application of cold resistance mechanisms.

The use of human aging markers, which are physiological, biochemical and molecular indicators of structural or functional degeneration associated with aging, is the fundamental basis of individualized aging assessments. Identifying methods for selecting markers has become a primary and vital aspect of aging research. However, there is no clear consensus or uniform principle on the criteria for screening aging markers. Therefore, we combine previous research from our center and summarize the criteria for screening aging markers in previous population studies, which are discussed in three aspects: functional perspective, operational implementation perspective and methodological perspective. Finally, an evaluation framework has been established, and the criteria are categorized into three levels based on their importance, which can help assess the extent to which a candidate biomarker may be feasible, valid, and useful for a specific use context.

BackgroundRecently, the triglyceride glucose (TyG) index has emerged as a reliable predictive indicator for adverse outcomes of cardiovascular disease. However, the roles of the TyG index in patients with acute myocardial infarction (AMI) and low-density lipoprotein cholesterol (LDL-C)≤1.8 mmol/L after percutaneous coronary intervention (PCI) remain unclear.MethodsA total of 599 patients diagnosed with AMI and LDL-C ≤ 1.8 mmol/L at the 1-month follow-up after PCI were consecutively enrolled between January 2017 and January 2020. The patients were subsequently divided into three groups based on tertiles of the TyG index. The parameters, including the TyG index, were compared to explore the risk factors associated with major adverse cardiovascular and cerebrovascular events (MACCEs) during the 1-year follow-up.ResultsSixty-nine patients (11.5%) with 90 MACCEs were recorded during the 1-year follow up, including 13 patients (8.6%) in the Tertile 1 group, 36 (12.0%) in the Tertile 2 group, and 20 (13.4%) in the Tertile 3 group. Patients with a higher TyG index had a significantly increased incidence of MACCEs compared to those with a lower TyG index (22.1% vs. 14.0% vs. 9.9%, p=0.010). Kaplan–Meier analysis demonstrated that patients with a higher TyG index had a significantly lower probability of survival without MACCEs. Furthermore, a binary logistic regression model indicated that the TyG index was the only independent predictor for MACCEs in these patients.ConclusionA higher TyG index was associated with a higher incidence of MACCEs in patients with AMI and well-controlled LDL-C levels after PCI. This suggests that the TyG index can serve as a predictive indicator for adverse cardiovascular outcomes in these patients.

A highly efficient composite sealing material was prepared using drilling cuttings as the base material and a binder, a coagulant, and other additives as auxiliaries. A four-factor, three-level orthogonal test was designed based on the response surface method (RSM), and a response surface regression model was constructed using compressive strength, fluidity, expansion rate, and setting time as performance indexes to analyze the effects of each factor on material performance and optimize the material proportion. The samples were prepared by simulating the grouting process, the permeability of the samples was measured, and the sealability of the material was verified by analyzing the material microscopic morphology. Results showed that the regression model had a high level of confidence and accuracy and could predict the test results accurately within the range of the test. The effects of the interaction between factors on material performance were also examined. The low permeability of the sealing material samples verified the material’s feasibility. Gradual optimization of material performance revealed that the optimal proportion was 52.6% drill cuttings, 44.3% binder, 0.6% coagulant promoter, and 2.5% expansive agent. Under these conditions, the error between the predicted and test values of each material property was less than 5%, and the comprehensive performance was superior. These findings verify the accuracy of RSM and its applicability to the optimization of material performance. This work provides reasonable theoretical guidance for the preparation of drilling cuttings composite (DC) materials in practical engineering.

BackgroundLiver cancer due to hepatitis C (LCDHC) is one of the leading causes of cancer-related deaths worldwide, and the burden of LCDHC is increasing. We aimed to report the burden of LCDHC at the global, regional, and national levels in 204 countries from 1990 to 2019, stratified by etiology, sex, age, and Sociodemographic Index.MethodsData on LCDHC were available from the Global Burden of Disease, Injuries, and Risk Factors (GBD) study 2019. Numbers and age-standardized mortality, incidence, and disability-adjusted life year (DALY) rates per 100,000 population were estimated through a systematic analysis of modeled data from the GBD 2019 study. The trends in the LCDHC burden were assessed using the annual percentage change.ResultsGlobally, in 2019, there were 152,225 new cases, 141,810 deaths, and 2,878,024 DALYs due to LCDHC. From 1990 to 2019, the number of incidences, mortality, and DALY cases increased by 80.68%, 67.50%, and 37.20%, respectively. However, the age-standardized incidence, mortality, and DALY rate had a decreasing trend during this period. In 2019, the highest age-standardized incidence rates (ASIRs) of LCDHC were found in high-income Asia Pacific, North Africa and the Middle East, and Central Asia. At the regional level, Mongolia, Egypt, and Japan had the three highest ASIRs in 2019. The incidence rates of LCDHC were higher in men and increased with age, with a peak incidence in the 95+ age group for women and the 85–89 age group for men in 2019. A nonlinear association was found between the age-standardized rates of LCDHC and sociodemographic index values at the regional and national levels.ConclusionsAlthough the age-standardized rates of LCDHC have decreased, the absolute numbers of incident cases, deaths, and DALYs have increased, indicating that LCDHC remains a significant global burden. In addition, the burden of LCDHC varies geographically. Male and older adult/s individuals have a higher burden of LCDHC. Our findings provide insight into the global burden trend of LCDHC. Policymakers should establish appropriate methods to achieve the HCV elimination target by 2030 and reducing the burden of LCDHC.

ATP-induced cell death has emerged as a captivating realm of inquiry with profound ramifications in the context of osteoporosis. This study unveils a paradigm-shifting hypothesis that illuminates the prospective involvement of ATP-induced cellular demise in the etiology of osteoporosis. Initially, we explicate the morphological attributes of ATP-induced cell death and delve into the intricacies of the molecular machinery and regulatory networks governing ATP homeostasis and ATP-induced cell death. Subsequently, our focus pivots towards the multifaceted interplay between ATP-induced cellular demise and pivotal cellular protagonists, such as bone marrow-derived mesenchymal stem cells, osteoblasts, and osteoclasts, accentuating their potential contributions to secondary osteoporosis phenotypes, encompassing diabetic osteoporosis, glucocorticoid-induced osteoporosis, and postmenopausal osteoporosis. Furthermore, we probe the captivating interplay between ATP-induced cellular demise and alternative modalities of cellular demise, encompassing apoptosis, autophagy, and necroptosis. Through an all-encompassing inquiry into the intricate nexus connecting ATP-induced cellular demise and osteoporosis, our primary goal is to deepen our comprehension of the underlying mechanisms propelling this malady and establish a theoretical bedrock to underpin the development of pioneering therapeutic strategies.

It is widely accepted that the weight distribution of plant fruits conforms to a standard normal distribution. However, some overlooked evidence suggests that some fruits, including strawberries, exhibit positive skewness in fruit weight distribution. This intriguing observation has received limited attention thus far. To shed light on this phenomenon, we conducted a comprehensive simulation study utilizing greenhouse-grown strawberries as our research subject. We modeled the entire process from bee pollination to pollen fertilization on the stigma and fruit growth. The experimental results demonstrated the reliability of the proposed simulation model and revealed that the positive skewness of the fruit weight distribution was the result of the multiplication of several complex intermediate variable distributions, which led to an approximately lognormal distribution. The simulation model and the derived conclusions presented in this paper offer a plausible explanation for the weight distribution patterns observed in strawberry production systems. Furthermore, research results have the potential to be applied to other berry plants that undergo similar bee pollination processes, thereby expanding our understanding of fruit weight distributions across different species.

Osteoarthritis (OA) stands as a prevalent degenerative joint ailment, demanding immediate attention towards the development of efficacious therapeutic interventions. Presently, a definitive cure for OA remains elusive, and when conservative treatment modalities prove ineffective, resorting to a joint prosthesis becomes imperative. Temporary distraction emerges as a pivotal joint-preserving intervention in human OA patients, conferring both clinical amelioration and structural enhancements. Although extant clinical investigations exist, they are characterized by relatively modest sample sizes. Nonetheless, these studies furnish compelling evidence affirming that joint distraction engenders sustained clinical amelioration and structural refinement. Despite substantial strides in the last decade, a bibliometric analysis of joint distraction within the realm of osteoarthritis treatment research has been conspicuously absent. In this context, we have undertaken a comparative investigation utilizing bibliometric methodologies to scrutinize the landscape of joint distraction within osteoarthritis treatment. Our comprehensive analysis encompassed 469 scholarly articles. Our findings evince a consistent escalation in global research interest and publication output pertaining to this subject. The United States emerged as the frontrunner in international collaboration, publication count, and citation frequency, underscoring its preeminence in this domain. The journal “Osteoarthritis and Cartilage” emerged as the principal platform for disseminating research output on this subject. Notably, Mastbergen SC emerged as the most prolific contributor in terms of authorship. The identified keywords predominantly revolved around non-surgical interventions and joint arthroscopy procedures. This bibliometric analysis, augmented by visual representations, furnishes invaluable insights into the evolutionary trajectory of joint distraction as an osteoarthritis treatment modality spanning from 2003 to 2023. These insights will serve as a compass for the scientific community, facilitating further exploration in this promising domain.

Background & aimsThis multicenter retrospective study evaluated the efficacy and safety of transarterial chemoembolization (TACE) combined with donafenib and a programmed death-1 (PD-1) inhibitor (TACE+DP) and TACE combined with donafenib (TACE+D) for unresectable hepatocellular carcinoma (uHCC).MethodsThe clinical data of 388 patients with uHCC who received TACE+DP or TACE+D as first-line treatment at six Chinese academic centers from July 2021 to July 2022 were collected and analyzed retrospectively. Patients in the TACE+DP group received an intravenous administration of a PD-1 inhibitor every three weeks and oral donafenib (0.2 g) twice daily until intolerable toxicity or disease progression. Patients in the TACE+D group received the same dose of donafenib for 3–5 days after TACE. Overall survival (OS) and progression-free survival (PFS)were analyzed by Kaplan-Meier method and log-rank test. The tumor response was compared between the two groups according to modified RECIST criteria. Adverse events were also analyzed between the two groupsResultsThe TACE+D group included 157 patients and the TACE+DP group included 166 patients. Patients in the TACE+DP group had a longer median OS (18.1 vs. 13.2 months, P

ObjectiveWe investigated the association between bronchopulmonary dysplasia (BPD) and 3 years death or neurodevelopmental impairment (NDI) in very preterm infants without severe brain injury.MethodOur prospective cohort study recruited preterm infants who were born prior to 32 weeks of gestational age and survived in the neonatal intensive care unit until 36 weeks of corrected age. Upon reaching 3 years of age, each infant was assessed for death or NDI such as cerebral palsy, cognitive deficit, hearing loss, and blindness. Correlations between BPD and death or NDI were determined using multiple logistic regression analyses adjusted for confounding factors.ResultA total of 1,417 infants without severe brain injury who survived until 36 weeks of corrected age were initially enrolled in the study. Over the study period, 201 infants were lost to follow-up and 5 infants were excluded. Our final dataset, therefore, included 1,211 infants, of which 17 died after 36 weeks of corrected age and 1,194 were followed up to 3 years of age. Among these infants, 337 (27.8%) developed BPD. Interestingly, by 3 years of age, BPD was demonstrated to be independently associated with death or NDI, with an adjusted odds ratio of 1.935 (95% confidence interval: 1.292–2.899, p = 0.001), in preterm infants without severe neonatal brain injury.ConclusionOur findings indicate that BPD is strongly associated with death or NDI in preterm infants without severe neonatal brain injury at 3 years of age. Further research is needed to understand the mechanisms linking the development of BPD with death or NDI and whether appropriate treatment of BPD may ameliorate or prevent the development of neurological complications.

The fabrication of silver joints was done using the pressureless sintering technology to suit the demand of high-reliability schottky barrier diodes (SBD). Porosity of 10.6% and shear strength of 39.6 MPa were reached under the optimized parameters of 290°C sintering temperature and 40 min residence time. The sintered joint demonstrated good mechanical/thermal/electrical performance in the ultimate reliability assessment testing, including the temperature cycling test, second sintering test, steady-state lifetime test, and intermittent lifetime test. This study demonstrated the viability of pressureless sintering of silver joints with good high-temperature reliability, which has significant application potential for aeronautical high-reliability power electronics.

BackgroundNumerous studies have revealed associations between gut microbiota and adipose tissue. However, the specific functional bacterial taxa and their causal relationships with adipose tissue production in different regions of the body remain unclear.MethodsWe conducted a bidirectional two-sample Mendelian Randomization (MR) study using aggregated data from genome-wide association studies (GWAS) for gut microbiota and adipose tissue. We employed methods such as inverse variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode to assess the causal relationships between gut microbiota and subcutaneous adipose tissue (SAT) as well as visceral adipose tissue (VAT). Cochran’s Q test, MR-Egger regression intercept analysis, and MR-PRESSO were used to test for heterogeneity, pleiotropy, and outliers of the instrumental variables, respectively. Reverse MR was employed to evaluate the reverse causal relationships between SAT, VAT, and gut microbiota with significant associations.ResultsIVW results demonstrated that Betaproteobacteria were protective factors for SAT production (OR = 0.88, 95% CI: 0.80–0.96, p = 0.005) and VAT production (OR = 0.91, 95% CI: 0.83–0.99, p = 0.030). Various bacterial taxa including Ruminococcaceae UCG002 (OR = 0.94, 95% CI: 0.89–0.99, p = 0.017), Methanobacteria class (OR = 0.96, 95% CI: 0.92–1.00, p = 0.029), and Burkholderiales (OR = 0.90, 95% CI: 0.83–0.98, p = 0.012) were associated only with decreased SAT production. Rikenellaceae RC9 gut group (OR = 1.05, 95% CI: 1.02–1.10, p = 0.005), Eubacterium hallii group (OR = 1.08, 95% CI: 1.01–1.15, p = 0.028), Peptococcaceae (OR = 1.08, 95% CI: 1.01–1.17, p = 0.034), and Peptococcus (OR = 1.05, 95% CI: 1.00–1.10, p = 0.047) were risk factors for SAT production. Meanwhile, Eubacterium fissicatena group (OR = 0.95, 95% CI: 0.91–0.99, p = 0.019), Turicibacter (OR = 0.93, 95% CI: 0.88–0.99, p = 0.022), and Defluviitaleaceae UCG011 (OR = 0.94, 95% CI: 0.89–0.99, p = 0.024) were protective factors for VAT production. Furthermore, Bacteroidetes (OR = 1.09, 95% CI: 1.01–1.17, p = 0.018), Eubacterium eligens group (OR = 1.09, 95% CI: 1.01–1.19, p = 0.037), Alloprevotella (OR = 1.05, 95% CI: 1.00–1.10, p = 0.038), and Phascolarctobacterium (OR = 1.07, 95% CI: 1.00–1.15, p = 0.042) were associated with VAT accumulation. Additionally, reverse MR revealed significant associations between SAT, VAT, and Rikenellaceae RC9 gut group (IVW: OR = 1.57, 95% CI: 1.18–2.09, p = 0.002) as well as Betaproteobacteria (IVW: OR = 1.14, 95% CI: 1.01–1.29, p = 0.029), both acting as risk factors. Sensitivity analyzes during bidirectional MR did not identify heterogeneity or pleiotropy.ConclusionThis study unveils complex causal relationships between gut microbiota and SAT/VAT, providing novel insights into the diagnostic and therapeutic potential of gut microbiota in obesity and related metabolic disorders.

Sugarcane (Saccharum spp. hybrids) is a worldwide acclaimed important agricultural crop used primarily for sugar production and biofuel. Sugarcane’s genetic complexity, aneuploidy, and extreme heterozygosity make it a challenging crop in developing improved varieties. The molecular breeding programs promise to develop nutritionally improved varieties for both direct consumption and commercial application. Therefore, to address these challenges, the development of simple sequence repeats (SSRs) has been proven to be a powerful molecular tool in sugarcane. This study involved the collection of 285216 expressed sequence tags (ESTs) from sugarcane, resulting in 23666 unigenes, including 4547 contigs. Our analysis identified 4120 unigenes containing a total of 4960 SSRs, with the most abundant repeat types being monomeric (44.33%), dimeric (13.10%), and trimeric (39.68%). We further chose 173 primers to analyze the banding pattern in 10 sugarcane accessions by PAGE analysis. Additionally, functional annotation analysis showed that 71.07%, 53.6%, and 10.3% unigenes were annotated by Uniport, GO, and KEGG, respectively. GO annotations and KEGG pathways were distributed across three functional categories: molecular (46.46%), cellular (33.94%), and biological pathways (19.6%). The cluster analysis indicated the formation of four distinct clusters among selected sugarcane accessions, with maximum genetic distance observed among the varieties. We believe that these EST-SSR markers will serve as valuable references for future genetic characterization, species identification, and breeding efforts in sugarcane.

IntroductionWith the internationalization of traditional Chinese medicine, the demand for medicinal and edible Codonopsis Radix (CR) has increased, and its medicinal resources have attracted attention. CR is a well-known traditional Chinese medicine with a long pharmaceutical and edible history. The Guizhou province in China has abundant CR resources, but in the absence of systematic studies on species identification and chemical compositions, the capacity of the capacity of the province to CR resource has not been fully utilized.MethodologyWe used plant morphology and DNA barcoding techniques to identify Luodang (LD) and Weidang (WD) species. To investigate the differences in metabolites between LD and WD, as well as three Chinese Pharmacopeia CRs, and to predict pharmacological mechanisms of action for the dominant differential metabolites, we utilized widely targeted metabolomics and network pharmacology. The results also revealed the material basis for the excellent food properties of both LD and WD.ResultsThe plant traits and DNA barcoding molecular identification results indicated that Luodang and Weidang from Guizhou were Codonopsis tangshen and Codonopsis pilosula, respectively. Widely targeted metabolomics analysis revealed that a total of 1,116 metabolites from 14 categories, including phenolic acids, lipids, flavonoids, were found in five CRs and shared 1,054 (94.4%) metabolites. LD and WD each contained 3 and 10 dominant differential metabolites, respectively, which were primarily flavonoids and amino acids. Amino acids, phenolic acids, and organic acids play important roles in their excellent food attributes. In CR, eight dominant differential metabolites were discovered for the first time, including isoorientin-7-O-(6″-feruloyl) glucoside, N-formyl-L-methionine, and cyclo (Phe-Glu), among others. Network pharmacology analyses showed that, in LD, dominant differential metabolites were closely related to anti-tumor, cardiovascular disease improvement, nervous system protection, and metabolic disease treatment, whereas in WD, they were closely related to nervous system protection and cardiovascular disease improvement.ConclusionThe species of LD and WD were included in the Chinese Pharmacopeia, and their metabolite profiles were remarkably similar to CR from traditional producing areas. Therefore, LD and WD can be used and promoted medicinally as CR, and they have potential value for new drug development. This study enriched the database of CR compounds and provided a reference for quality control, resource development, and new drug development of CR.

Vegetation cover is a crucial indicator of biodiversity and ecological processes, but there are still uncertainties about the factors driving changes in vegetation. In this study, we conducted a comprehensive analysis of vegetation cover changes in Sichuan Province from 2000 to 2020 using Formation Vegetation Cover (FVC) derived from MODIS13Q1 data. Our results revealed a consistent increase in vegetation FVC, rising from 0.506 to 0.624 over the 21-year period, with an annual growth rate of 0.0028. The turning point in this growth occurred in 2006. Of significance, the expansion of vegetation covered a substantial portion, accounting for 84.76%, while the decrease constituted 13%. Elevation proved to be an effective explanatory factor, with a coefficient of 0.417, indicating its role in explaining vegetation cover changes. It is important to note that FVC trends and averages exhibited distinct patterns concerning elevation, land use, population density, topography, and soil type, while their correlation with meteorological factors was relatively weak. Concurrently, the increase in construction and urban development had a negative impact on vegetation cover.

IntroductionThe variation of organic carbon content in spoil heaps is closely related to improving soil structure, maintaining soil fertility, and regulating soil carbon cycling balance. Analyzing the soil organic carbon content and related driving factors during the natural vegetation restoration process of spoil heaps is of great significance for promoting the accumulation of soil organic carbon in the spoil heaps.Methodswe selected spoil heaps with the same number of years of restoration to research the variations in soil organic carbon components under different vegetation types (grassland: GL, shrubland: SL, secondary forest: SF) and compared the results with those on bare land (BL).ResultsOur results showed that vegetation type and soil depth significantly affect the content of soil organic carbon components. There was no difference in soil organic carbon components between SF and SL, but both were considerably superior to GL and BL (p

The ion upflow associated with the subauroral ion drift (SAID) is a crucial component in the exchange of particles between the ionosphere and the ring currents. The ion upflow associated with the double-peak subauroral ion drift (DSAID), which is a subclass of the SAID, is more complex compared to SAID. In this study, we conducted a statistical analysis of the ion upflow associated with DSAID using Defense Meteorological Satellite Program (DMSP) F16–F18 data spanning 11 years (2010–2020) in the Northern Hemisphere. Our findings revealed that ion upflow associated with DSAID can exhibit either a double-peak or a one-peak upflow. The statistical characteristics of these two types of events displayed significant differences. In DSAID with a double-peak upflow event, the velocity of DSAID around the high-latitude peak was greater than that around the low-latitude peak. However, in DSAID with a one-peak upflow event, the DSAID velocities around the two peaks were very similar. Based on the formation mechanism of DSAID and the process of frictional heating in the ionosphere, we proposed that the formation of DSAID with a double-peak upflow and DSAID with a one-peak upflow are likely related to the formation process of DSAID.

Climate and land-use changes and their interactions have a profound effect on biodiversity, especially in biodiverse areas such as Southeast Asia (SEA) where aggregations of endemic species are widespread. To increase the effectiveness of biodiversity protection, it is crucial to understand the effect of climate and land-use changes on biodiversity. In the present study, we predicted future land-use changes based on a Cellular automaton Markov chain model (CA-MARKOV), and took Galliformes species as an example to assess the impact of climate and land-use changes on the effectiveness of protected areas in SEA. In addition, we used an ensemble of species distribution models (SDMs) to assess the potential habitats and their dynamics of 62 Galliformes species currently and in the 2070s. Our results showed that climate and land-use changes would reduce the suitable habitats of these Galliformes species. Among them, 22 or 31 species would migrate upward because of a decrease in habitat suitability at lower elevations caused by climate and land-use changes, while other 40 or 30 species were predicted to migrate downward because of land use changes under two dispersal scenarios. These changes would expand the area with low and high diversity, but there would be a mismatch between the current protected areas (PAs) and future suitable habitats with high diversity. In order to effectively ensure biodiversity protection and conserve 30% of the planet by 2030, our findings suggest that we should establish new PAs or adjust the range of PAs based on the impact of climate and land-use changes.

IntroductionChanges in the gut microbiota of patients with partial small intestinal obstruction (PSIO) have not been widely clarified. We aimed to explore bacterial diversity in a PSIO mouse model.MethodsA PSIO mouse model was established using male C57BL/6 mice, and feces samples from the distal ileum and ileum epithelium tissues were collected. MiSeq sequencing of the 16S rRNA gene was conducted to characterize microbiota diversity and composition. RNA sequencing for differences in transcriptomic programming of the ileum tissue was performed between the PSIO and (Control) Ctrl groups.ResultsBacterial diversity in the PSIO group was significantly lower than that in the controls. Pseudomonadota was predominant in the feces of the PSIO group. Unclassified_Muribaculaceae (p = 0.008) and Akkermansia (p = 0.007) were more abundant in the Ctrl group than those in the PSIO group. Furthermore, Escherichia_Shigella (p = 0.008) was more predominant in the feces of the PSIO group. The Kyoto Encyclopedia of Genes and Genomes pathways related to metabolism were depleted in the PSIO group. Pathways associated with intestinal fibrosis, including extracellular matrix-receptor interaction, focal adhesion, phosphoinositide 3-kinase (PI3K)-Akt signaling pathway and transforming growth factor (TGF)-beta signaling pathway, which were enriched in ileum epithelial tissue in the PSIO group.ConclusionPSIO can lead to changes in the predominant intestinal bacterial groups. Depleted functional profiles of the gut microbiota were identified in the PSIO group. Functional pathways associated with intestinal fibrosis were activated by PSIO. The potential regulation by the microbiota needs to be explored in the future.

Background and aimsCuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).MethodThe gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein–protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes.ResultsFour datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples.ConclusionOur study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.