Search

The context of rapid global environmental change underscores the pressing necessity to investigate the environmental factors and high-risk areas that contribute to the occurrence of brucellosis. In this study, a maximum entropy (MaxEnt) model was employed to analyze the factors influencing brucellosis in the Aksu Prefecture from 2014 to 2023. A distributed lag nonlinear model (DLNM) was employed to investigate the lagged effect of meteorological factors on the occurrence of brucellosis. A total of 17 environmental factors were identified as affecting the distribution of brucellosis to varying degrees. The largest contributing was the normalized difference vegetation index (NDVI), followed by gross domestic product (GDP), and then meteorological factors such as average temperature, average relative humidity, and average wind speed. The receiver operating characteristic (ROC) curve demonstrated that the MaxEnt model exhibited a high degree of predictive efficacy, with an area under the curve (AUC) value of 0.921. The impact of high temperature (25℃ with a 2-month lag, RR = 3.130, 95% CI 1.642 ~ 5.965), low relative humidity (28% with a 2.5-month lag, RR = 1.795, 95% CI 1.298 ~ 2.483), and low wind speed (1.9 m/s with a 0-month lag, RR = 2.408, 95% CI 1.360 ~ 4.264) are the most significant meteorological factors associated with the incidence of brucellosis. The trends in the impact of extreme meteorological conditions on the spread of brucellosis were found to be generally consistent. Stratified analyses indicated that males were more affected by meteorological factors than females. The prevalence of brucellosis is influenced by a range of socio-economic and meteorological factors, and a multifaceted approach is necessary to prevent and control brucellosis., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Consent for publication: All authors have approved the final manuscript and have given consent for publication., (© 2025. The Author(s).)

Pulmonary fibrosis (PF) is a chronic, progressive and irreversible interstitial lung disease characterized by unremitting pulmonary myofibroblasts activation, extracellular matrix (ECM) deposition and inflammatory recruitment. PF has no curable medication yet. In this study we investigated the molecular pathogenesis and potential therapeutic targets of PF and discovered drug lead compounds for PF therapy. A murine PF model was established in mice by intratracheal instillation of bleomycin (BLM, 5 mg/kg). We showed that the protein level of pulmonary protein phosphatase magnesium-dependent 1A (PPM1A, also known as PP2Cα) was significantly downregulated in PF patients and BLM-induced PF mice. We demonstrated that TRIM47 promoted ubiquitination and decreased PPM1A protein in PF progression. By screening the lab in-house compound library, we discovered otilonium bromide (OB, clinically used for treating irritable bowel syndrome) as a PPM1A enzymatic activator with an EC 50 value of 4.23 μM. Treatment with OB (2.5, 5 mg·kg -1 ·d -1 , i.p., for 20 days) significantly ameliorated PF-like pathology in mice. We constructed PF mice with PPM1A-specific knockdown in the lung tissues, and determined that by targeting PPM1A, OB treatment suppressed ECM deposition through TGF-β/SMAD3 pathway in fibroblasts, repressed inflammatory responses through NF-κB/NLRP3 pathway in alveolar epithelial cells, and blunted the crosstalk between inflammation in alveolar epithelial cells and ECM deposition in fibroblasts. Together, our results demonstrate that pulmonary PPM1A activation is a promising therapeutic strategy for PF and highlighted the potential of OB in the treatment of the disease., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Shanghai Institute of Materia Medica, Chinese Academy of Sciences and Chinese Pharmacological Society.)

This paper presents a deep learning model based on an active learning strategy. The model achieves accurate identification of vegetation types in the study area by utilizing multispectral data obtained from preprocessing of unmanned aerial vehicle (UAV) remote sensing equipment. This approach offers advantages such as high data accuracy, mobility, and easy data collection. In active learning, the minimum confidence scoring method and a sampling technique based on a data pool are employed to reduce labeling costs. The deep learning model incorporates a semantic segmentation gated full fusion module that integrates a dual attention mechanism. This module enhances the capture of detailed texture information, optimally allocates spectral weights, and improves the model's ability to distinguish between similar categories. At a labeling cost of 20%, the average accuracy of the model is 93.2%. Compared with other models, the proposed model achieved the highest classification accuracy in the case of limited training samples. At full annotation cost, the average accuracy is 95.32%, with only a difference of about 2%, but saving 80% of annotation cost. Therefore, active learning strategies can filter out high-value samples that are beneficial for model training, greatly reducing the annotation cost of samples Finally, the recognition results of surface vegetation cover types in the study area are presented, and the model's accuracy is verified through field investigation., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Differences in prognostic outcomes are prevalent in patients with colorectal cancer liver metastases. Comparative analysis of tissue samples, particularly applying single-cell transcriptome sequencing technology, can provide a deeper understanding of potential impacting factors. However, long-term monitoring for prognosis determination necessitates extended preservation of tissue samples using formalin-fixed and paraffin-embedded (FFPE) treatments, which can cause substantial RNA degradation, presenting challenges to single-cell or single-nucleus sequencing. In this study, employing snRandom-seq, a single-nucleus RNA sequencing (snRNA-seq) technology specifically for FFPE samples, we tested multiple lesion samples from 18 distinctive colorectal cancer liver metastasis cases with diverse prognostic outcomes that have been preserved for at least three years (mostly over five years). The process yielded expression data from 82,285 cells. The high-quality snRNA-seq data demonstrate the feasibility of single-nucleus sequencing in long-term preserved FFPE samples, offering potential insights into the heterogeneity between different prognoses of colorectal cancer liver metastases, and the relationship between the heterogeneity within different lesions of the same patient and prognosis., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The intricate tumor microenvironment presents formidable obstacles to the efficacy of adoptive T cell therapy in the management of solid tumors by limiting the infiltration and inducing exhaustion of the transferred T cells. Here, we developed a bacterial-based adjuvant approach that augments the efficacy of adoptive T-cell therapy for solid tumor treatment. Our study reveals that intratumor injection of E. coli MG1655 normalizes tumor vasculatures and reprograms tumor-associated macrophages into M1 phenotype that produce abundant CCL5, together facilitating tumor infiltration of adoptively transferred T cells. The depletion of tumor-associated macrophages or CCL5 neutralization in vivo leads to the significantly decreased solid tumor infiltration of adoptive T cells in the presence of bacteriotherapy. This combinatorial therapy, consisting of E. coli adjuvant and adoptive T-cell therapy, effectively eradicates early-stage melanoma and inhibits the progression of pancreatic tumors. Notably, this dual strategy also strengthened the distal tumor control capabilities of adoptive T-cell therapy through the induction of in situ tumor vaccination. This dual therapeutic approach involving bacterial therapy targeting the interior of solid tumors and adoptive T-cell therapy attacking the tumor periphery exhibits potent therapeutic efficacy in achieving the eradication of advanced-stage tumors, including melanoma and hepatocellular carcinoma, by converging attacks from both inside and outside the tumor tissues., Competing Interests: Competing interests: Z.G. is the co-founder of Zenomics Inc., ZCapsule Inc., and µZen Pharma Co., Ltd. The other authors declare no competing interests., (© 2024. The Author(s).)

Glioblastoma (GBM) is an aggressive brain tumor with a poor prognosis, largely due to the presence of glioblastoma stem cells (GSCs). These cells drive tumor progression, recurrence, and chemoresistance, making them critical targets for therapy. This study aims to identify novel GSC markers for improved diagnosis and targeted treatment. We utilized single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data to identify PDLIM1 as a novel GSC marker. PDLIM1 was specifically expressed in GSCs and was associated with poor prognosis and advanced tumor stages. Functional assays demonstrated that PDLIM1 overexpression enhanced GBM cell proliferation, reduced apoptosis, increased GSC proportions, and promoted chemoresistance and tumorigenesis. Conversely, PDLIM1 knockdown inhibited these processes. Mechanistically, PDLIM1 was found to exert its effects likely by promoting the PI3K-AKT pathway. In conclusion, PDLIM1 may serve as a potential marker of GSCs associated with poor prognosis, tumorigenesis, and chemoresistance in GBM, representing a potential therapeutic target for improving GBM patient outcomes., Competing Interests: Competing interests The authors declare no competing interests. Ethics approval and consent to participate The Ethics Committee of Anhui Normal University approved the study (NO. AHNU-ET2022032). Informed consents were obtained from patients involved in the study. We confirmed that all methods were performed in accordance with relevant guidelines and regulations., (© 2024. The Author(s).)

Current tools for predicting survival outcomes in colon cancer patients predominantly rely on clinical and pathologic characteristics. However, accumulating evidence demonstrates a significant correlation between nutritional status and patient outcomes. This study aimed to establish a new dynamic nomogram for individualized prediction of postoperative overall survival (OS). The clinicopathological and nutritional data of colon cancer patients undergoing radical resection were retrospectively collected and randomly divided into the primary and validation cohorts. Risk factors on OS rates were investigated by Cox analyses and, the nomogram was constructed using significant predictors. Among 1,024 patients, 341 deaths were observed after median follow-up of 54 months. Five independent prognostic factors, including nutritional status assessments, were incorporated into the nomogram. The C-index regarding 1-, 3-, and 5-year OS were 0.830, 0.859, and 0.757 in the primary cohort and 0.843, 0.870, and 0.773 in the validation cohort, respectively. Calibration curves for the probability of OS exhibited an optimal agreement. Decision curve analyses revealed the greater application value of the nomogram than the TNM staging system. Based on the nomogram, patients could be stratified into three scenarios with significant prognostic classification (P < 0.0001). In conclusion, we developed and validated an easy-to-use dynamic nomogram for predicting postoperative OS in colon cancer patients., Competing Interests: Competing interests The authors declare no competing interests or personal relationships that can influence the work reported in this paper., (© 2024. The Author(s).)

This study investigated the effect of household air pollution on pregnant women with GDM, and assessed the modifying effect of a healthy lifestyle on this relationship. Household solid fuel exposure was defined as using solid fuels (coal, crop residue, and wood) for cooking and heating. Four individually modifiable lifestyle factors were assessed in early pregnancy: body mass index, diet, sleep, and vitamin D supplementation. Multifactorial logistic regression modeling was used to assess the relationship between household air pollution and GDM. A stratified analysis and additive interaction tested the effects of healthy lifestyle scores. After adjusting for potential confounders, we found that using solid fuels for heating was significantly associated with an increased risk of GDM (adjusted OR = 1.60, 95% CI 1.18-2.18). GDM risk showed a decreasing trend in the medium versus the high score group when compared to the low score group, with a consistent trend regardless of household fuel type used (adjusted OR = 0.39, 95% CI 0.27-0.57) (adjusted OR = 0.12, 95% CI 0.05-0.28), respectively. Importantly, when the healthy lifestyle score increased, exposure to household air pollution was no longer associated with a higher GDM risk. There was a negative additive interaction between exposure to household solid fuels exposure and a healthy lifestyle (FERI: -5.10 [-16.48, -2.04]; AP: -1.29 [-2.80, -0.39]; SI: -0.37 [-0.20, -0.67]). We determined that exposure to household air pollution may be an important GDM risk factor. In addition, A healthy lifestyle may have a protective effect on women with GDM exposed to indoor fuel air pollution., (© 2024. The Author(s).)

Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency 1-3 . Classical molecular dynamics simulation is fast but lacks chemical accuracy 4,5 . Quantum chemistry methods such as density functional theory can reach chemical accuracy but cannot scale to support large biomolecules 6 . Here we introduce an artificial intelligence-based ab initio biomolecular dynamics system (AI 2 BMD) that can efficiently simulate full-atom large biomolecules with ab initio accuracy. AI 2 BMD uses a protein fragmentation scheme and a machine learning force field 7 to achieve generalizable ab initio accuracy for energy and force calculations for various proteins comprising more than 10,000 atoms. Compared to density functional theory, it reduces the computational time by several orders of magnitude. With several hundred nanoseconds of dynamics simulations, AI 2 BMD demonstrated its ability to efficiently explore the conformational space of peptides and proteins, deriving accurate 3 J couplings that match nuclear magnetic resonance experiments, and showing protein folding and unfolding processes. Furthermore, AI 2 BMD enables precise free-energy calculations for protein folding, and the estimated thermodynamic properties are well aligned with experiments. AI 2 BMD could potentially complement wet-lab experiments, detect the dynamic processes of bioactivities and enable biomedical research that is impossible to conduct at present., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Malnutrition and insulin resistance are linked to complications like delirium, yet their impact on elderly heart failure patients remains underexplored. This study investigates how nutritional status and the triglyceride-glucose (TyG) index influence delirium in this population. We conducted a retrospective study involving patients aged 75 and older with decompensated heart failure. Delirium was assessed using the Confusion Assessment Method (CAM), and nutritional status was evaluated with the Mini Nutritional Assessment Scale-Short Form (MNA-SF). The TyG index was calculated as: TyG index = ln [triglycerides (mg/dL) × fasting glucose (mg/dL) / 2]. The study included 412 patients (mean age 84.30 ± 5.16 years; 56.31% male), with 24.03% experiencing delirium during hospitalization. After adjusting for confounders, a higher TyG index was significantly associated with increased delirium risk (OR = 1.549, 95% CI: 1.102-2.178, P = 0.012), while a higher MNA-SF score correlated with reduced risk (OR = 0.793, 95% CI: 0.662-0.949, P = 0.011). Kaplan-Meier analysis showed significant differences in cumulative survival based on nutritional status and TyG index (Log-Rank test: χ²= 65.604, P < 0.001). Mediation analysis indicated that nutritional status partially mediated the relationship between the TyG index and delirium, and vice versa. Malnutrition and elevated TyG index levels increase delirium risk in elderly heart failure patients, underscoring the need for effective nutritional management and metabolic regulation., (© 2024. The Author(s).)

Paclitaxel (PTX) serves as a primary chemotherapy agent against diverse solid tumors including breast cancer, lung cancer, head and neck cancer and ovarian cancer, having severe adverse effects including PTX-induced peripheral neuropathy (PIPN) and hypersensitivity reactions (HSR). A recommended anti-allergic agent diphenhydramine (DIP) has been used to alleviate PTX-induced HSR. Desloratadine (DLT) is a third generation of histamine H 1 receptor antagonist, but also acted as a selective antagonist of 5HTR 2A . In this study we investigated whether DLT ameliorated PIPN-like symptoms in mice and the underlying mechanisms. PIPN was induced in male mice by injection of PTX (4 mg/kg, i.p.) every other day for 4 times. The mice exhibited 50% reduction in mechanical threshold, paw thermal response latency and paw cold response latency compared with control mice. PIPN mice were treated with DLT (10, 20 mg/kg, i.p.) 30 min before each PTX administration in the phase of establishing PIPN mice model and then administered daily for 4 weeks after the model was established. We showed that DLT administration dose-dependently elevated the mechanical, thermal and cold pain thresholds in PIPN mice, whereas administration of DIP (10 mg/kg, i.p.) had no ameliorative effects on PIPN-like symptoms. We found that the expression of 5HTR 2A was selectively elevated in the activated spinal astrocytes of PIPN mice. Spinal cord-specific 5HTR 2A knockdown by intrathecal injection of AAV9-5Htr2a-shRNA significantly alleviated the mechanical hyperalgesia, thermal and cold hypersensitivity in PIPN mice, while administration of DLT (20 mg/kg) did not further ameliorate PIPN-like symptoms. We demonstrated that DLT administration alleviated dorsal root ganglion neuronal damage and suppressed sciatic nerve destruction, spinal neuron apoptosis and neuroinflammation in the spinal cord of PIPN mice. Furthermore, we revealed that DLT administration suppressed astrocytic neuroinflammation via the 5HTR 2A /c-Fos/NLRP3 pathway and blocked astrocyte-neuron crosstalk by targeting 5HTR 2A . We conclude that spinal 5HTR 2A inhibition holds promise as a therapeutic approach for PIPN and we emphasize the potential of DLT as a dual-functional agent in ameliorating PTX-induced both PIPN and HSR in chemotherapy. In summary, we determined that spinal 5HTR 2A was selectively activated in PIPN mice and DLT could ameliorate the PTX-induced both PIPN- and HSR-like pathologies in mice. DLT alleviated the damages of DRG neurons and sciatic nerves, while restrained spinal neuronal apoptosis and CGRP release in PIPN mice. The underlying mechanisms were intensively investigated by assay against the PIPN mice with 5HTR 2A -specific knockdown in the spinal cord by injection of adeno-associated virus 9 (AAV9)-5Htr2a-shRNA. DLT inhibited astrocytic NLRP3 inflammasome activation-mediated spinal neuronal damage through 5HTR 2A /c-FOS pathway. Our findings have supported that spinal 5HTR 2A inhibition shows promise as a therapeutic strategy for PIPN and highlighted the potential advantage of DLT as a dual-functional agent in preventing against PTX-induced both PIPN and HSR effects in anticancer chemotherapy., (© 2024. The Author(s), under exclusive licence to Shanghai Institute of Materia Medica, Chinese Academy of Sciences and Chinese Pharmacological Society.)

The Ruddlesden-Popper (R-P) bilayer nickelate, La 3 Ni 2 O 7 , was recently found to show signatures of high-temperature superconductivity (HTSC) at pressures above 14 GPa (ref.  1 ). Subsequent investigations achieved zero resistance in single-crystalline and polycrystalline samples under hydrostatic pressure conditions 2-4 . Yet, obvious diamagnetic signals, the other hallmark of superconductors, are still lacking owing to the filamentary nature with low superconducting volume fraction 2,4,5 . The presence of a new 1313 polymorph and competing R-P phases obscured proper identification of the phase for HTSC 6-9 . Thus, achieving bulk HTSC and identifying the phase at play are the most prominent tasks. Here we address these issues in the praseodymium (Pr)-doped La 2 PrNi 2 O 7 polycrystalline samples. We find that substitutions of Pr for La effectively inhibit the intergrowth of different R-P phases, resulting in a nearly pure bilayer structure. For La 2 PrNi 2 O 7 , pressure-induced orthorhombic to tetragonal structural transition takes place at P c  ≈ 11 GPa, above which HTSC emerges gradually on further compression. The superconducting transition temperatures at 18-20 GPa reach T c onset = 82.5 K and T c zero = 60 K , which are the highest values, to our knowledge, among known nickelate superconductors. Importantly, bulk HTSC was testified by detecting clear diamagnetic signals below about 75 K with appreciable superconducting shielding volume fractions at a pressure of above 15 GPa. Our results not only resolve the existing controversies but also provide directions for exploring bulk HTSC in the bilayer nickelates., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Chronic obstructive pulmonary disease (COPD), a progressive inflammatory condition of the airways, emerges from the complex interplay between genetic predisposition and environmental factors. Notably, its incidence is on the rise, particularly among the elderly demographic. Current research increasingly highlights cellular senescence as a key driver in chronic lung pathologies. Despite this, the detailed mechanisms linking COPD with senescent genomic alterations remain elusive. To address this gap, there is a pressing need for comprehensive bioinformatics methodologies that can elucidate the molecular intricacies of this link. This approach is crucial for advancing our understanding of COPD and its association with cellular aging processes. Utilizing a spectrum of advanced bioinformatics techniques, this research delved into the potential mechanisms linking COPD with aging-related genes, identifying four key genes (EP300, MTOR, NFE2L1, TXN) through machine learning and weighted gene co-expression network analysis (WGCNA) analyses. Subsequently, a precise diagnostic model leveraging an artificial neural network was developed. The study further employed single-cell analysis and molecular docking to investigate senescence-related cell types in COPD tissues, particularly focusing on the interactions between COPD and NFE2L1, thereby enhancing the understanding of COPD's molecular underpinnings. Leveraging artificial neural networks, we developed a robust classification model centered on four genes-EP300, MTOR, NFE2L1, TXN-exhibiting significant predictive capability for COPD and offering novel avenues for its early diagnosis. Furthermore, employing various single-cell analysis techniques, the study intricately unraveled the characteristics of senescence-related cell types in COPD tissues, enriching our understanding of the disease's cellular landscape. This research anticipates offering novel biomarkers and therapeutic targets for early COPD intervention, potentially alleviating the disease's impact on individuals and healthcare systems, and contributing to a reduction in global COPD-related mortality. These findings carry significant clinical and public health ramifications, bolstering the foundation for future research and clinical strategies in managing and understanding COPD., (© 2024. The Author(s).)

Sinonasal squamous cell carcinoma (SNSCC) is an aggressive cancer affecting the nasal and sinus regions, with its progression factors, particularly genetic ones, not yet fully understood. Here, we first conducted a retrospective study with 219 SNSCC patients to identify clinical factors affecting SNSCC prognosis. Additionally, we mined a vast literature dataset to uncover genetic factors associated with SNSCC progression. Based on this data, we constructed SNSCC prognosis pathways and performed a gene set enrichment analysis (GSEA). Clear operative margins were linked to a 73.5-86.3% improvement in overall survival and a 73.5-88.9% lower risk of recurrence. Nasal cavity-originated cases exhibited a 67.6-97.4% decrease in mortality and an 80.7-96.7% lower recurrence rate. Patients at T1-2 staging had a 65.0-80.6% reduced risk of death and recurrence compared to those at T3 stage. Additionally, we identified 53 genes associated with SNSCC, with 14 also implicated in primary tumor site, T stage, and operative margin. These genes, including EGFR, PIK3CA, ERBB2, PTEN, BCL2, BRAF, KRAS, and PRL, form a complex SNSCC-prognosis pathway and were significantly enriched in 42 KEGG pathways and Gene Ontology (GO) terms (FDR-corrected p-value < 0.001), influencing cell growth, apoptosis, and oncogenic signaling pathways. Our study suggests that three clinical parameters (operative margin type, primary tumor site, and T-stage) and 14 genetic factors may influence SNSCC prognosis post-surgery. These findings deepen our understanding of SNSCC and offer potential avenues to enhance its treatment and outcomes., (© 2024. The Author(s).)

Liposomal irinotecan has shown promising antitumor activity in patients with advanced or metastatic pancreatic ductal adenocarcinoma (PDAC) who have undergone prior gemcitabine-based therapies. This randomized, double-blind, parallel-controlled, multicenter phase 3 study (NCT05074589) assessed the efficacy and safety of liposomal irinotecan HR070803 combined with 5-fluorouracil (5-FU) and leucovorin (LV) in this patient population. Patients with unresectable, locally advanced, or metastatic PDAC who had previously received gemcitabine-based therapies were randomized 1:1 to receive either HR070803 (60 mg/m 2 anhydrous irinotecan hydrochloride, equal to 56.5 mg/m 2 free base) or placebo, both in combination with 5-FU (2000 mg/m 2 ) and LV (200 mg/m 2 ), all given intravenously every two weeks. The primary endpoint of the study was overall survival (OS). A total of 298 patients were enrolled and received HR070803 plus 5-FU/LV (HR070803 group, n = 149) or placebo plus 5-FU/LV (placebo group, n = 149). Median OS was significantly improved in the HR070803 group compared to the placebo group (7.4 months [95% CI 6.1-8.4] versus 5.0 months [95% CI 4.3-6.0]; HR 0.63 [95% CI 0.48-0.84]; two-sided p = 0.0019). The most common grade ≥ 3 adverse events in the HR070803 group were increased gamma-glutamyltransferase (19.0% versus 11.6% in placebo group) and decreased neutrophil count (12.9% versus 0 in placebo group). No treatment-related deaths occurred in the HR070803 group, while the placebo group reported one treatment-related death (abdominal infection). HR070803 in combination with 5-FU/LV has shown promising efficacy and manageable safety in advanced or metastatic PDAC in the second-line setting, representing a potential option in this patient population., (© 2024. The Author(s).)

The aim of this study was to evaluate the prognostic value of peripheral blood inflammation indexes in patients with metastatic Colorectal Cancer (CRC) and to establish a predictive scoring system. A total of 324 CRC patients diagnosed through pathological examination from January 2017 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were included. The prognosis of patients with metastatic CRC was examined, and the correlation between IL-10 expression in pathological tissues and IL-10 expression in serum was analyzed. The results showed that the prognosis of CRC was poorer when metastasis occurred (P < 0.001). Additionally, IL-10 was highly expressed in the metastatic CRC group (P = 0.018), and the expression of IL-10 in pathological tissues of patients with metastatic CRC was positively correlated with the expression of IL-10 in serum (P = 0.037). The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-white blood cell ratio (LWR), aggregate index of systemic inflammation (AISI), monocyte-to-lymphocyte ratio (MLR), systemic inflammatory response index (SIRI), prognostic nutritional index (PNI), advanced lung cancer inflammation index (ALI), and interleukin-10 (IL-10) were calculated and determined by ROC curve. The critical values were 2.135, 3.735, 353.745, 0.265, 1.025, 52.975, 353.635, and 11.25, respectively. Inflammatory indexes with an AUC of more than 0.6 were selected, and each colorectal cancer patient with any of these risk factors was assigned a score of one. The 324 patients were then divided into two groups: 0-4 for the low-risk group and 4-8 for the high-risk group. The occurrence of distant metastases in the two groups was statistically analyzed. The results showed that the OS and PFS of the low-risk group were significantly superior to those of the high-risk group (P < 0.05). These findings indicate that NLR, LWR, AISI, MLR, SIRI, PNI, ALI, and IL-10 are risk factors for distant metastasis in CRC patients. Therefore, the prediction scores of these indexes can be used to effectively evaluate the prognosis of patients with metastatic CRC., (© 2024. The Author(s).)

The past two decades has witnessed a remarkable increase in the number of microbial genomes retrieved from marine systems 1,2 . However, it has remained challenging to translate this marine genomic diversity into biotechnological and biomedical applications 3,4 . Here we recovered 43,191 bacterial and archaeal genomes from publicly available marine metagenomes, encompassing a wide range of diversity with 138 distinct phyla, redefining the upper limit of marine bacterial genome size and revealing complex trade-offs between the occurrence of CRISPR-Cas systems and antibiotic resistance genes. In silico bioprospecting of these marine genomes led to the discovery of a novel CRISPR-Cas9 system, ten antimicrobial peptides, and three enzymes that degrade polyethylene terephthalate. In vitro experiments confirmed their effectiveness and efficacy. This work provides evidence that global-scale sequencing initiatives advance our understanding of how microbial diversity has evolved in the oceans and is maintained, and demonstrates how such initiatives can be sustainably exploited to advance biotechnology and biomedicine., (© 2024. The Author(s).)

Most previous studies on the association between vegetarian diet and inflammation have used only one inflammatory biomarker e.g., C-reactive protein (CRP) and the findings were generally inconsistent. Therefore, we conducted a cross-sectional study to investigate the correlation between diet and inflammation in Chinese vegetarians using dietary indices and multiple inflammatory biomarkers. 279 vegetarians and omnivores of the same sex and age recruited in Shanghai, 2016. 24-h dietary review questionnaire was collected and used to calculate Dietary inflammatory index (DII) and Energy-adjusted inflammatory index (E-DII) of both groups. In addition, energy intake matched vegetarian and omnivore recipes were designed by registed dietitions and used to calculate a theoretical DII. Five serum inflammatory biomarkers CRP, interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were measured. We found that vegetarians had significantly lower E-DII and theoretical DII than omnivores (P < 0.001). In contrast, the raw DII of vegetarians was almost the same with that of omnivores, probably due to lower energy intake in vegetarians than in omnivores (1367.97 ± 479.75 vs. 1724.78 ± 568.13, P < 0.001). Levels of TNF-α, IL-6, NLR and PLR were significantly higher in vegetarians than in omnivores while no statistical differences were found in CRP. In conclusion, a theoretical vegetarian diet with adequate energy intake as well as a balanced dietary intake showed good anti-inflammatory effects, though this was not fully reflected in vegetarian population in the real world, probably due to insufficient energy intake in the vegetarian population., (© 2024. The Author(s).)

This study aimed to develop and validate a predictive model of all-cause mortality risk in American adults aged ≥ 18 years with diabetes. 7918 participants with diabetes were enrolled from the National Health and Nutrition Examination Survey (NHANES) 1999-2016 and followed for a median of 96 months. The primary study endpoint was the all-cause mortality. Predictors of all-cause mortality included age, Monocytes, Erythrocyte, creatinine, Nutrition Risk Index (NRI), neutrophils/lymphocytes (NLR), smoking habits, alcohol consumption, cardiovascular disease (CVD), urinary albumin excretion rate (UAE), and insulin use. The c-index was 0.790 (95% CI 0.779-0.801, P < 0.001) and 0.792 (95% CI: 0.776-0.808, P < 0.001) for the training and validation sets, respectively. The area under the ROC curve was 0.815, 0.814, 0.827 and 0.812, 0.818 and 0.829 for the training and validation sets at 3, 5, and 10 years of follow-up, respectively. Both calibration plots and DCA curves performed well. The model provides accurate predictions of the risk of death for American persons with diabetes and its scores can effectively determine the risk of death in outpatients, providing guidance for clinical decision-making and predicting prognosis for patients., (© 2024. The Author(s).)

With advancements in sustainable urban development, research on urban functional areas has garnered significant attention. In recent years, Point-of-Interest, with their large volume of information and ease of acquisition, have been widely applied in research on urban functional domains. However, scholars currently focus on the identification of urban functional areas, usually relying on data from a single period, whereas research on the prediction of functional areas has not yet been well validated. Therefore, in this study, we propose a new method based on several years of POI data to predict urban functional areas. Taking Nanjing City, Jiangsu Province, as an example, we first identified the functional area distribution of the old city of Nanjing over several years using POI data and then designed multiple sets of experiments to explore the CA-Markov model's ability to predict functional areas from various aspects, including model overall accuracy, robustness, and comparison analysis between predictions and actual situations. The results show that (1) for mixed or single functional areas, the model's predictions over several years tend to be stable, and the accuracy of the predictions over many years indicates the robustness of the model in predicting urban functional areas. (2) For mixed functional areas in cities, model predictions largely rely on the distribution of the base years used for prediction, leading to inaccurate results; thus, it is still not applicable for simulating and predicting mixed functional areas. (3) For single functional areas in cities or primary functions within an area, the model's predicted degree of change was close to the actual degree of change, making the results referable., (© 2024. The Author(s).)

Genetic and fragmented palaeoanthropological data suggest that Denisovans were once widely distributed across eastern Eurasia 1-3 . Despite limited archaeological evidence, this indicates that Denisovans were capable of adapting to a highly diverse range of environments. Here we integrate zooarchaeological and proteomic analyses of the late Middle to Late Pleistocene faunal assemblage from Baishiya Karst Cave on the Tibetan Plateau, where a Denisovan mandible and Denisovan sedimentary mitochondrial DNA were found 3,4 . Using zooarchaeology by mass spectrometry, we identify a new hominin rib specimen that dates to approximately 48-32 thousand years ago (layer 3). Shotgun proteomic analysis taxonomically assigns this specimen to the Denisovan lineage, extending their presence at Baishiya Karst Cave well into the Late Pleistocene. Throughout the stratigraphic sequence, the faunal assemblage is dominated by Caprinae, together with megaherbivores, carnivores, small mammals and birds. The high proportion of anthropogenic modifications on the bone surfaces suggests that Denisovans were the primary agent of faunal accumulation. The chaîne opératoire of carcass processing indicates that animal taxa were exploited for their meat, marrow and hides, while bone was also used as raw material for the production of tools. Our results shed light on the behaviour of Denisovans and their adaptations to the diverse and fluctuating environments of the late Middle and Late Pleistocene of eastern Eurasia., (© 2024. The Author(s).)

Non-alcoholic fatty liver disease (NAFLD) has become the first major chronic liver disease in developed countries. 10-20% of NAFLD patients will progress to non-alcoholic steatohepatitis (NASH), and up to 25% of NASH patients may develop cirrhosis within 10 years. Therefore, it is critical to find key targets that may treat this disease. Here, we identified C5aR1 as a highly-expressed gene in NASH mouse model through analyzing Gene Expression Omnibus (GEO) database and confirmed its higher expression in livers of NASH patients than that of NAFL patients. Meanwhile, we verified its positive correlation with patients' serum alanine transaminase (ALT) and aspartate transaminase (AST) levels. In vivo and in vitro experiments revealed that knocking down C5aR1 in liver significantly reduced liver weight ratio and serum ALT and AST levels and attenuated inflammatory cell infiltration and cell apoptosis in the liver of NASH mice as well as enhanced the efferocytotic ability of liver macrophages, suggesting that C5aR1 may play a crucial role in the efferocytosis of liver macrophages. Furthermore, we also found that the expression levels of nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing protein 3 (NLRP3), caspase-1, IL-1β and other inflammation-related factors in the liver were significantly reduced. Our work demonstrates a potential mechanism of how C5aR1 deficiency protects against diet-induced NASH by coordinating the regulation of inflammatory factors and affecting hepatic macrophage efferocytosis., (© 2024. The Author(s).)

The dual activation of glucagon-like peptide-1 receptor (GLP-1R) and glucose-dependent insulinotropic polypeptide receptor (GIPR) has emerged as a promising therapeutic strategy for managing type 2 diabetes and obesity. Tirzepatide, a dual agonist peptide, has exhibited superior clinical efficacy in glycemic and weight control compared to selective GLP-1R agonists. Nevertheless, the structural basis of Tirzepatide's extended half-life, attributed to an acylation side chain on the parent peptide, raises questions regarding its partial agonistic activity. Employing molecular dynamics simulations, we explored the dynamic processes of peptide-receptor interactions. We uncovered a crucial salt bridge between parent peptide and GLP-1R/GIPR at K20, a feature not discernible in cryo-electron microscopy structures. Building upon these insights, we developed an optimization strategy based on the parent peptide which involved repositioning the acylation side chain. The results of both in vitro and in vivo experiments demonstrated that the optimized peptide has twofold to threefold increase in agonistic activity compared to Tirzepatide while maintaining its extended half-life in plasma. This led to the design of BGM0504, which proved to be more effective than its predecessor, Tirzepatide, in both laboratory and animal studies., (© 2024. The Author(s).)

Aphidoletes aphidimyza is widely recognized as an effective predator of aphids in agricultural systems. However, there is limited understanding of its predation mechanisms. In this study, we generated a high-quality chromosome level of the A. aphidimyza genome by combining PacBio, Illumina, and Hi-C data. The genome has a size of 192.08 Mb, with a scaffold N50 size of 46.85 Mb, and 99.08% (190.35 Mb) of the assembly is located on four chromosomes. The BUSCO analysis of our assembly indicates a completeness of 97.8% (n = 1,367), including 1,307 (95.6%) single-copy BUSCOs and 30 (2.2%) duplicated BUSCOs. Additionally, we annotated a total of 13,073 protein-coding genes, 18.43% (35.40 Mb) repetitive elements, and 376 non-coding RNAs. Our study is the first time to report the chromosome-scale genome for the species of A. aphidimyza. It provides a valuable genomic resource for the molecular study of A. aphidimyza., (© 2024. The Author(s).)

Previous research has primarily employed deep learning models such as Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) for decoding imagined character signals. These approaches have treated the temporal and spatial features of the signals in a sequential, parallel, or single-feature manner. However, there has been limited research on the cross-relationships between temporal and spatial features, despite the inherent association between channels and sampling points in Brain-Computer Interface (BCI) signal acquisition, which holds significant information about brain activity. To address the limited research on the relationships between temporal and spatial features, we proposed a Temporal-Spatial Cross-Attention Network model, named TSCA-Net. The TSCA-Net is comprised of four modules: the Temporal Feature (TF), the Spatial Feature (SF), the Temporal-Spatial Cross (TSCross), and the Classifier. The TF combines LSTM and Transformer to extract temporal features from BCI signals, while the SF captures spatial features. The TSCross is introduced to learn the correlations between the temporal and spatial features. The Classifier predicts the label of BCI data based on its characteristics. We validated the TSCA-Net model using publicly available datasets of handwritten characters, which recorded the spiking activity from two micro-electrode arrays (MEAs). The results showed that our proposed TSCA-Net outperformed other comparison models (EEG-Net, EEG-TCNet, S3T, GRU, LSTM, R-Transformer, and ViT) in terms of accuracy, precision, recall, and F1 score, achieving 92.66 % , 92.77 % , 92.70 % , and 92.58 % , respectively. The TSCA-Net model demonstrated a 3.65 % to 7.49 % improvement in accuracy over the comparison models., (© 2024. The Author(s).)

Genome-wide association study (GWAS) is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of dual-phenotype analysis to uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, a common allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locus is co-selected with flowering-time-related genes. The discovered pleiotropic genotype-phenotype map provides new insights into understanding the genetic correlation of complex traits., (© 2024. The Author(s), under exclusive licence to The Genetics Society.)

Synaptic vesicles are organelles with a precisely defined protein and lipid composition 1,2 , yet the molecular mechanisms for the biogenesis of synaptic vesicles are mainly unknown. Here we discovered a well-defined interface between the synaptic vesicle V-ATPase and synaptophysin by in situ cryo-electron tomography and single-particle cryo-electron microscopy of functional synaptic vesicles isolated from mouse brains 3 . The synaptic vesicle V-ATPase is an ATP-dependent proton pump that establishes the proton gradient across the synaptic vesicle, which in turn drives the uptake of neurotransmitters 4,5 . Synaptophysin 6 and its paralogues synaptoporin 7 and synaptogyrin 8 belong to a family of abundant synaptic vesicle proteins whose function is still unclear. We performed structural and functional studies of synaptophysin-knockout mice, confirming the identity of synaptophysin as an interaction partner with the V-ATPase. Although there is little change in the conformation of the V-ATPase upon interaction with synaptophysin, the presence of synaptophysin in synaptic vesicles profoundly affects the copy number of V-ATPases. This effect on the topography of synaptic vesicles suggests that synaptophysin assists in their biogenesis. In support of this model, we observed that synaptophysin-knockout mice exhibit severe seizure susceptibility, suggesting an imbalance of neurotransmitter release as a physiological consequence of the absence of synaptophysin., (© 2024. The Author(s).)

Direct laser acceleration (DLA) of electrons in plasmas of near-critical density (NCD) is a very advancing platform for high-energy PW-class lasers of moderate relativistic intensity supporting Inertial Confinement Fusion research. Experiments conducted at the PHELIX sub-PW Nd:glass laser demonstrated application-promising characteristics of DLA-based radiation and particle sources, such as ultra-high number, high directionality and high conversion efficiency. In this context, the bright synchrotron-like (betatron) radiation of DLA electrons, which arises from the interaction of a sub-ps PHELIX laser pulse with an intensity of 10 19 W/cm 2 with pre-ionized low-density polymer foam, was studied. The experimental results show that the betatron radiation produced by DLA electrons in NCD plasma is well directed with a half-angle of 100-200 mrad, yielding (3.4 ± 0.4)·10 10 photons/keV/sr at 10 keV photon energy. The experimental photon fluence and the brilliance agree well with the particle-in-cell simulations. These results pave the way for innovative applications of the DLA regime using low-density pre-ionized foams in high energy density research., (© 2024. The Author(s).)

The extensive adoption of digital audio recording has revolutionized its application in digital forensics, particularly in civil litigation and criminal prosecution. Electric network frequency (ENF) has emerged as a reliable technique in the field of audio forensics. However, the absence of comprehensive ENF reference datasets limits current ENF-based methods. To address this, this study introduces ATD, a blind audio forensics framework based on a one-dimensional convolutional neural network (1D-CNN) model. ATD can identify phase mutations and waveform discontinuities within the tampered ENF signal, without relying on an ENF reference database. To enhance feature extraction, the framework incorporates characteristics of the fundamental harmonics of ENF signals. In addition, a denoising method termed ENF noise reduction (ENR) based on the variational mode decomposition (VMD) and robust filtering algorithm (RFA) is proposed to reduce the impact of external noise on embedded electric network frequency signals. This study investigates three distinct types of audio tampering-deletion, insertion, and replacement-culminating in the design of binary-class tampering detection scenarios and four-class tampering detection scenarios tailored to these tampering types. ATD achieves a tampering detection accuracy of over 93% in the four-class scenario and exceeds 96% in the binary-class scenario. The effectiveness, efficiency, adaptability, and robustness of ATD in the two and four classification scenarios have been confirmed by extensive experiments., (© 2024. The Author(s).)

The aim of this study is to assess the relationship between dietary intake of fatty acids and the age-related macular degeneration (AMD) in the United States population. Adult participants of the 2005-2008 National Health and Nutrition Examination Survey (NHANES) were included in this nationwide cross-sectional study. Dietary fatty acid intake was obtained from two 24-h dietary recall interviews. The intake of dietary fatty acids was analyzed as a continuous and categorical variable. AMD status was assessed using nonmydriatic fundus photographs. Univariate and multivariate logistic regression analyses were used to assess the association between dietary fatty acid intake and AMD. The unweighted population included 4702 individuals of whom 374 had AMD. After adjusting for relevant variables, each 1 unit increase (1 mg/1000 kcal) intake of EPA (OR: 0.996, 95% CI: 0.993-0.996, P = 0.018), DPA (OR: 0.976, 95% CI: 0.962-0.990, P = 0.002), and DHA (OR: 0.996, 95% CI: 0.994-0.999, P = 0.003) were significantly decreased odds of any AMD. The highest versus lowest quartile of EPA (OR: 0.476, P for trend < 0.001), DPA (OR: 0.467, P for trend = 0.005) and DHA (OR: 0.586, P for trend = 0.008) were negatively associated with the odds of any AMD. Subgroup analysis showed that higher quartiles of EPA (OR: 0.461, P for trend < 0.002), DPA (OR: 0.467, P for trend = 0.006) and DHA (OR: 0.578, P for trend = 0.007) exhibited a negative association with early AMD. The study found no significant association between the intake of dietary fatty acids, including n-3 PUFA, and the odds of late AMD. In the 2005-2008 NHANES population, higher dietary DHA, DPA and EPA intake associated with decreased odds of early AMD. However, no clear association was found between specific types of FAs and late AMD., (© 2024. The Author(s).)

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with progressive loss of motor neurons in the spinal cord, cerebral cortex and brain stem. ALS is characterized by gradual muscle atrophy and dyskinesia. The limited knowledge on the pathology of ALS has impeded the development of therapeutics for the disease. Previous studies have shown that autophagy and astrocyte-mediated neuroinflammation are involved in the pathogenesis of ALS, while 5HTR 2A participates in the early stage of astrocyte activation, and 5HTR 2A antagonism may suppress astrocyte activation. In this study, we evaluated the therapeutic effects of desloratadine (DLT), a selective 5HTR 2A antagonist, in human SOD1 G93A (hSOD1 G93A ) ALS model mice, and elucidated the underlying mechanisms. HSOD1 G93A mice were administered DLT (20 mg·kg -1 ·d -1 , i.g.) from the age of 8 weeks for 10 weeks or until death. ALS onset time and lifespan were determined using rotarod and righting reflex tests, respectively. We found that astrocyte activation accompanying with serotonin receptor 2 A (5HTR 2A ) upregulation in the spinal cord was tightly associated with ALS-like pathology, which was effectively attenuated by DLT administration. We showed that DLT administration significantly delayed ALS symptom onset time, prolonged lifespan and ameliorated movement disorders, gastrocnemius injury and spinal motor neuronal loss in hSOD1 G93A mice. Spinal cord-specific knockdown of 5HTR 2A by intrathecal injection of adeno-associated virus9 (AAV9)-si-5Htr2a also ameliorated ALS pathology in hSOD1 G93A mice, and occluded the therapeutic effects of DLT administration. Furthermore, we demonstrated that DLT administration promoted autophagy to reduce mutant hSOD1 levels through 5HTR 2A /cAMP/AMPK pathway, suppressed oxidative stress through 5HTR 2A /cAMP/AMPK/Nrf2-HO-1/NQO-1 pathway, and inhibited astrocyte neuroinflammation through 5HTR 2A /cAMP/AMPK/NF-κB/NLRP3 pathway in the spinal cord of hSOD1 G93A mice. In summary, 5HTR 2A antagonism shows promise as a therapeutic strategy for ALS, highlighting the potential of DLT in the treatment of the disease. DLT as a 5HTR 2A antagonist effectively promoted autophagy to reduce mutant hSOD1 level through 5HTR 2A /cAMP/AMPK pathway, suppressed oxidative stress through 5HTR 2A /cAMP/AMPK/Nrf2-HO-1/NQO-1 pathway, and inhibited astrocytic neuroinflammation through 5HTR 2A /cAMP/AMPK/NF-κB/NLRP3 pathway in the spinal cord of hSOD1 G93A mice., (© 2024. The Author(s), under exclusive licence to Shanghai Institute of Materia Medica, Chinese Academy of Sciences and Chinese Pharmacological Society.)

Mountain tunnels portal often have to pass through slope terrain unavoidably, thus forming a shallow buried bias tunnel. During the construction of shallow buried bias tunnel, disasters such as slope sliding and tunnel collapse frequently occur. The failure mode of surrounding rock obtained by current research is based on the limit equilibrium theory, which cannot reflect the progressive failure characteristics of the surrounding rock of shallow buried bias tunnel. In order to reveal the failure mechanism of the gradual instability of surrounding rock of shallow buried bias tunnel, the problem of gradual failure of the surrounding rock is reduced to an elastic-plastic analysis problem for surrounding rock considering the strain-softening characteristics. Based on the elastic-plastic analysis of the failure process of shallow buried bias tunnel, MATLAB was used to compile a program to read the finite-difference calculation result file, extract the effective information such as shear strain and tensile strain at the center point of each unit, and establish the analysis method of the progressive failure mode of shallow buried bias tunnel. The reliability of the method proposed was verified by comparing the failure process of the model test with the development process of shear strain increment. Under the condition of no support, the formation mechanism of failure plane of surrounding rock on both sides of shallow buried bias tunnel is different. The shallow buried side is the shear failure plane formed by the collapse of surrounding rock, while the deep buried side of the tunnel is the shear failure plane formed by the collapse of surrounding rock and slope sliding. Under the conditions of excavation and support, the failure plane of the shallow buried bias tunnel can be divided into three parts according to the formation sequence and reasons. The part I is the failure plane, which is formed by active shear under the influence of tunnel excavation. The part II is the failure plane formed by tensile crack of slope top. The part III is the failure plane formed by passive shear under the push of the soil in the upper part of the slope., (© 2024. The Author(s).)

Ran GTPase activating protein 1 (RanGAP1) has been implicated in various diseases, but its role in colorectal cancer (CRC) progression remains unclear. Using tumor tissues and public databases, we found that RanGAP1 was significantly upregulated in CRC tissues and was associated with poor prognosis of patients. N6-methyladenosine (m6A) was found to play an important role in higher expression of RanGAP1. MeRIP-seq, RIP-qPCR, Luciferase reporter assays and other related experiment elucidated the molecular mechanism underlying m6A modification of RanGAP1. Besides, cell function experiments and xenograft tumor models corroborated the function of RanGAP1 in CRC progression. By RNA-seq and related analysis, RanGAP1 was verified to influent CRC progression via the Mitogen-Activated Protein Kinase (MAPK) signaling pathway. Therefore, N6-methyladenosine modification of RanGAP1 by METTL3/YTHDF1 plays a role in CRC progression through the MAPK pathway and could be a potential biomarker and therapeutic target for CRC. Schematic diagram showed that N6-methyladenosine modification of RanGAP1 promotes CRC progression via the MAPK signaling pathway., (© 2024. The Author(s).)

Background: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood. Little is known about how infancy growth trajectories affect adiposity in early childhood in LGA., Methods: In the Shanghai Birth Cohort, we followed up 259 LGA (birth weight >90th percentile) and 1673 appropriate-for-gestational age (AGA, 10th-90th percentiles) children on body composition (by InBody 770) at age 4 years. Adiposity outcomes include body fat mass (BFM), percent body fat (PBF), body mass index (BMI), overweight/obesity, and high adiposity (PBF >85th percentile)., Results: Three weight growth trajectories (low, mid, and high) during infancy (0-2 years) were identified in AGA and LGA subjects separately. BFM, PBF and BMI were progressively higher from low- to mid-to high-growth trajectories in both AGA and LGA children. Compared to the mid-growth trajectory, the high-growth trajectory was associated with greater increases in BFM and the odds of overweight/obesity or high adiposity in LGA than in AGA children (tests for interactions, all P < 0.05)., Conclusions: Weight trajectories during infancy affect adiposity in early childhood regardless of LGA or not. The study is the first to demonstrate that high-growth weight trajectory during infancy has a greater impact on adiposity in early childhood in LGA than in AGA subjects., Impact: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood, but little is known about how weight trajectories during infancy affect adiposity during early childhood in LGA subjects. The study is the first to demonstrate a greater impact of high-growth weight trajectory during infancy (0-2 years) on adiposity in early childhood (at age 4 years) in subjects with fetal overgrowth (LGA) than in those with normal birth size (appropriate-for-gestational age). Weight trajectory monitoring may be a valuable tool in identifying high-risk LGA children for close follow-ups and interventions to decrease the risk of obesity., (© 2024. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Alteration of gut microbiota can affect chronic lung diseases, such as asthma and chronic obstructive pulmonary disease, through abnormal immune and inflammatory responses. Previous studies have shown a feasible connection between gut microbiota and bronchopulmonary dysplasia (BPD) in preterm infants. However, whether BPD can be ameliorated by restoring the gut microbiota remains unclear. In preterm infants with BPD, we found variance in the diversity and structure of gut microbiota. Similarly, BPD rats showed gut dysbiosis, characterized by a deficiency of Lactobacillus, which was abundant in normal rats. We therefore explored the effect and potential mechanism of action of a probiotic strain, Lactobacillus plantarum L168, in improving BPD. The BPD rats were treated with L. plantarum L168 by gavage for 2 weeks, and the effect was evaluated by lung histopathology, lung function, and serum inflammatory markers. Subsequently, we observed reduced lung injury and improved lung development in BPD rats exposed to L. plantarum L168. Further evaluation revealed that L. plantarum L168 improved intestinal permeability in BPD rats. Serum metabolomics showed altered inflammation-associated metabolites following L. plantarum L168 intervention, notably a marked increase in anti-inflammatory metabolites. In agreement with the metabolites analysis, RNA-seq analysis of the intestine and lung showed that inflammation and immune-related genes were down-regulated. Based on the information from RNA-seq, we validated that L. plantarum L168 might improve BPD relating to down-regulation of TLR4 /NF-κB /CCL4 pathway. Together, our findings suggest the potential of L. plantarum L168 to provide probiotic-based therapeutic strategies for BPD., (© 2024. The Author(s).)

This study intended to evaluate the diagnostic accuracy of the prostate imaging reporting and data system (PI-RADS) and prostate-specific antigen density (PSAD) for clinically significant prostate cancer (csPCa) with PSA levels of 4-10 ng/ml. Between July 2018 and June 2022, a total of 453 patients with PSA levels of 4-10 ng/ml were retrospectively included, which were randomly assigned to the training group (323 patients) and validation group (130 patients). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with their 95% CI were calculated. The overall diagnostic performance was determined with area under the receiver operating characteristic curve (AUC), and an integrated nomogram combining PI-RADS score and PSAD was constructed and tested in a validation cohort. In the training group, the AUC for PI-RADS 2.1 and PSAD alone were 0.875 (95% CI 0.834-0.916) and 0.712 (95% CI 0.648-0.775). At the cutoff PI-RADS score ≥ 4, the sensitivity and specificity were 86.2% (95% CI 77.4-1.9%) and 84.7% (95% CI 79.6-88.8%), respectively. For PSAD, the sensitivity and specificity were 73.3% (95% CI 63.0-82.4%) and 62.1% (95% CI 55.8-68.5%) at the cutoff 0.162 ng/ml/ml. While combining PI-RADS with PSAD, the diagnostic performance was improved significantly, with AUC of 0.893 (95% CI 0.853-0.933). In the validation group, the nomogram yielded a AUC of 0.871 (95% CI 0.807-0.934), which is significantly higher than PI-RADS alone (0.829, 95% CI 0.759-0.899, P = 0.02). For patients with PSA levels of 4-10 ng/ml, PSAD demonstrated moderate diagnostic accuracy whereas PI-RADS showed high performance. By combination of PSAD and PI-RADS together, the diagnostic performance could be improved significantly., (© 2024. The Author(s).)

Brominated flame retardants (BFRs) are a group of chemicals widely used in various applications to prevent or slow down the spread of fire. However, they have adverse effects on human health. There is a relative scarcity of population-based studies regarding BFRs, particularly their impact on the respiratory system. This study aimed to investigate the influence of BFRs on pulmonary function using data from the National Health and Nutrition Examination Survey. The study found that elevated serum concentrations of certain BFRs were associated with pulmonary ventilatory dysfunction. Adjusted analyses revealed positive correlations between PBDE47, PBDE183, and PBDE209 concentrations and ventilatory dysfunction. The analysis of mixed BFRs showed a positive relationship with pulmonary ventilation dysfunction, with PBDE47 making the most significant contribution. Our study demonstrates that both individual and combined BFRs exposure can lead to impaired pulmonary ventilation function. These findings provide evidence of the adverse effects of BFRs on lung function, emphasizing the importance of further investigating the potential health consequences of these compounds. Further large-scale longitudinal studies are needed to investigate this relationship in the future., (© 2024. The Author(s).)

Chronic obstructive pulmonary disease (COPD) combined with malnutrition results in decreased exercise capacity and a worse quality of life. We aimed to develop an observational case-control study to explore the effective and convenient method to identify potential individuals is lacking. This study included data from 251 patients with COPD and 85 participants in the control group. Parameters and body composition were compared between groups, and among patients with varied severity. The LASSO approach was employed to select the features for fitting a logistic model to predict the risk of malnutrition in patients with stable COPD. Patients with COPD exhibited significantly lower 6-min walk distance (6MWD), handgrip strength, fat-free mass index (FFMI), skeletal muscle mass (SMM) and protein. The significant predictors identified following LASSO selection included 6MWD, waist-to-hip ratio (WHR), GOLD grades, the COPD Assessment Test (CAT) score, and the prevalence of acute exacerbations. The risk score model yielded good accuracy (C-index, 0.866 [95% CI 0.824-0.909]) and calibration (Brier score = 0.150). After internal validation, the adjusted C-index and Brier score were 0.849, and 0.165, respectively. This model may provide primary physicians with a simple scoring system to identify malnourished patients with COPD and develop appropriate rehabilitation interventions., (© 2024. The Author(s).)

High heterogeneity and complex interactions of malignant cells in breast cancer has been recognized as a driver of cancer progression and therapeutic failure. However, complete understanding of common cancer cell states and their underlying driver factors remain scarce and challenging. Here, we revealed seven consensus cancer cell states recurring cross patients by integrative analysis of single-cell RNA sequencing data of breast cancer. The distinct biological functions, the subtype-specific distribution, the potential cells of origin and the interrelation of consensus cancer cell states were systematically elucidated and validated in multiple independent datasets. We further uncovered the internal regulons and external cell components in tumor microenvironments, which contribute to the consensus cancer cell states. Using the state-specific signature, we also inferred the abundance of cells with each consensus cancer cell state by deconvolution of large breast cancer RNA-seq cohorts, revealing the association of immune-related state with better survival. Our study provides new insights for the cancer cell state composition and potential therapeutic strategies of breast cancer., (© 2024. The Author(s).)

There has been an upward trend in the incidence of glioma, with high recurrence and high mortality. The beta subunits of the 20S proteasome are encoded by the proteasome beta (PSMB) genes and may affect the proteasome's function in glioma, assembly and inhibitor binding. This study attempted to reveal the function of the proliferation and invasion of glioma cells, which is affected by proteasome 20S subunit beta 2 (PSMB2). We subjected the data downloaded from the TCGA database to ROC, survival, and enrichment analyses. After establishing the stable PSMB2 knockdown glioma cell line. We detect the changes in the proliferation, invasion and migration of glioma cells by plate colony formation assay, transwell assay, wound healing assay and flow cytometry and PSMB2 expression was verified by quantitative PCR and Western blotting to identify the mRNA and protein levels. PSMB2 expression was higher in glioma tissues, and its expression positively correlated with poor prognosis and high tumor grade and after PSMB2 knockdown, the proliferation, invasion and migration of glioma cells were weakened., (© 2024. The Author(s).)

NF-κB signaling has been discovered for nearly 40 years. Initially, NF-κB signaling was identified as a pivotal pathway in mediating inflammatory responses. However, with extensive and in-depth investigations, researchers have discovered that its role can be expanded to a variety of signaling mechanisms, biological processes, human diseases, and treatment options. In this review, we first scrutinize the research process of NF-κB signaling, and summarize the composition, activation, and regulatory mechanism of NF-κB signaling. We investigate the interaction of NF-κB signaling with other important pathways, including PI3K/AKT, MAPK, JAK-STAT, TGF-β, Wnt, Notch, Hedgehog, and TLR signaling. The physiological and pathological states of NF-κB signaling, as well as its intricate involvement in inflammation, immune regulation, and tumor microenvironment, are also explicated. Additionally, we illustrate how NF-κB signaling is involved in a variety of human diseases, including cancers, inflammatory and autoimmune diseases, cardiovascular diseases, metabolic diseases, neurological diseases, and COVID-19. Further, we discuss the therapeutic approaches targeting NF-κB signaling, including IKK inhibitors, monoclonal antibodies, proteasome inhibitors, nuclear translocation inhibitors, DNA binding inhibitors, TKIs, non-coding RNAs, immunotherapy, and CAR-T. Finally, we provide an outlook for research in the field of NF-κB signaling. We hope to present a stereoscopic, comprehensive NF-κB signaling that will inform future research and clinical practice., (© 2024. The Author(s).)

Red flesh apple (Malus pumila var. medzwetzkyana Dieck), purple leaf plum (Prunus cerasifera Ehrhar f), and purple leaf peach (Prunus persica 'Atropurpurea') are significant ornamental plants within the Rosaceae family. The coloration of their fruits and leaves is crucial in their appearance and nutritional quality. However, qualitative and quantitative studies on flavonoids in the succulent fruits and leaves of multicolored Rosaceae plants are lacking. To unveil the diversity and variety-specificity of flavonoids in these three varieties, we conducted a comparative analysis of flavonoid metabolic components using ultra-high-performance liquid phase mass spectrometry (UPLC-MS/MS). The results revealed the detection of 311 metabolites, including 47 flavonoids, 105 flavonols, 16 chalcones, 37 dihydroflavonoids, 8 dihydroflavonols, 30 anthocyanins, 14 flavonoid carbon glycosides, 23 flavanols, 8 isoflavones, 11 tannins, and 12 proanthocyanidins. Notably, although the purple plum and peach leaves exhibited distinct anthocyanin compounds, paeoniflorin and corythrin glycosides were common but displayed varying glycosylation levels. While the green purple leaf peach fruit (PEF) and red flesh apple leaf (AL) possessed the lowest anthocyanin content, they exhibited the highest total flavonoid content. Conversely, the red flesh apple fruit (AF) displayed the highest anthocyanin content and a diverse range of anthocyanin glycosylation modifications, indicating that anthocyanins predominantly influenced the fruit's color. Purple PLF, PLL, and PEL showcased varying concentrations of anthocyanins, suggesting that their colors result from the co-color interaction between specific types of anthocyanins and secondary metabolites, such as flavonols, flavonoids, and dihydroflavonoids. This study provides novel insights into the variations in tissue metabolites among Rosaceae plants with distinct fruit and leaf colors., (© 2024. The Author(s).)

Acute carbon monoxide (CO) poisoning is a prevalent type of poisoning that causes significant harm globally. Delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) is a severe complication that occurs after acute CO poisoning; however, the exact underlying pathological cause of DEACMP remains unclear. Accumulating evidence indicates that abnormal inflammation and immune-mediated brain damage, cellular apoptosis and autophagy, and direct neuronal toxicity are involved in the development of delayed neurologic sequelae. Sodium butyrate, a histone deacetylase inhibitor, has gained increasing attention for its numerous beneficial effects on various diseases, such as obesity, diabetes, inflammatory diseases, and cerebral damage. In this study, an acute carbon monoxide poisoning (ACOP) model is established in rats to investigate the mechanism of CO poisoning and the therapeutic potential of sodium butyrate. The results suggested that the ACOP rats had impaired spatial memory, and cell apoptosis was observed in the hippocampi with activated autophagy. Sodium butyrate treatment further increased the activation of autophagy in the hippocampi of CO-exposed rats, inhibited apoptosis, and consolidated spatial memory. These findings indicated that sodium butyrate may improve memory and cognitive function in ACMP rats by promoting autophagy and inhibiting apoptosis., (© 2024. The Author(s).)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes multi-organ damage, which includes hepatic dysfunction, as observed in over 50% of COVID-19 patients. Angiotensin I converting enzyme (peptidyl-dipeptidase A) 2 (ACE2) is the primary receptor for SARS-CoV-2 entry into host cells, and studies have shown the presence of intracellular virus particles in human hepatocytes that express ACE2, but at extremely low levels. Consequently, we asked if hepatocytes might express receptors other than ACE2 capable of promoting the entry of SARS-CoV-2 into cells. To address this question, we performed a genome-wide CRISPR-Cas9 activation library screening and found that Asialoglycoprotein receptor 1 (ASGR1) promoted SARS-CoV-2 pseudovirus infection of HeLa cells. In Huh-7 cells, simultaneous knockout of ACE2 and ASGR1 prevented SARS-CoV-2 pseudovirus infection. In the immortalized THLE-2 hepatocyte cell line and primary hepatic parenchymal cells, both of which barely expressed ACE2, SARS-CoV-2 pseudovirus could successfully establish an infection. However, after treatment with ASGR1 antibody or siRNA targeting ASGR1, the infection rate significantly dropped, suggesting that SARS-CoV-2 pseudovirus infects hepatic parenchymal cells mainly through an ASGR1-dependent mechanism. We confirmed that ASGR1 could interact with Spike protein, which depends on receptor binding domain (RBD) and N-terminal domain (NTD). Finally, we also used Immunohistochemistry and electron microscopy to verify that SARS-CoV-2 could infect primary hepatic parenchymal cells. After inhibiting ASGR1 in primary hepatic parenchymal cells by siRNA, the infection efficiency of the live virus decreased significantly. Collectively, these findings indicate that ASGR1 is a candidate receptor for SARS-CoV-2 that promotes infection of hepatic parenchymal cells., (© 2024. The Author(s).)

Over the past decade, CdS QDs have become versatile semiconductors. Surface modification of CdS QDs has become an interesting case study, as it can eliminate surface defects and improve their photochemical properties. In this study, we report a new strategy of using carbon quantum dots containing a large number of thiol groups (CQDs-SH) as a passivating agent for the stabilization of CdS quantum dots (QDs). Various characterization techniques have clearly revealed that the CdS QDs have been successfully passivated by CQDs-SH. The photocatalytic performance of CQDs-SH/CdS QDs was investigated for the degradation of the insecticide imidacloprid from an aqueous solution. Parameters affecting the photodegradation process, including the light source, photocatalyst amount, initial concentration of the pollutant, radiation time, pH, oxidizing agent, and temperature, were investigated. Furthermore, the HPLC technique was applied to quantitatively analyze imidacloprid and its degradation products. The results of the HPLC analysis revealed that under simulated visible light at pH 9, imidacloprid scarcely existed after 90 min of irradiation (90.13% degradation). The LC-MS method was also used to detect the degradation products and investigate the mechanism of photodegradation of the pesticide. The results showed that the CQDs-SH/CdS QDs composite was a promising photocatalyst for the degradation of imidacloprid in wastewater., (© 2024. The Author(s).)

ZFP36L1, which is a negative regulator of gene transcripts, has been proven to regulate the progression of several carcinomas. However, its role in sarcoma remains unknown. Here, by using data analyses and in vivo experiments, we found that ZFP36L1 inhibited the lung metastasis of osteosarcoma (OS). Knockdown of ZFP36L1 promoted OS cell migration by activating TGF-β signaling and increasing SDC4 expression. Intriguingly, we observed a positive feedback loop between SDC4 and TGF-β signaling. SDC4 protected TGFBR3 from matrix metalloproteinase (MMP)-mediated cleavage and therefore relieved the inhibition of TGF-β signaling by soluble TGFBR3, while TGF-β signaling positively regulated SDC4 transcription. We also proved that ZFP36L1 regulated SDC4 mRNA decay through adenylate-uridylate (AU)-rich elements (AREs) in its 3'UTR. Furthermore, treatment with SB431542 (a TGF-β receptor kinase inhibitor) and MK2 inhibitor III (a MAPKAPK2 inhibitor that increases the ability of ZFP36L1 to degrade mRNA) dramatically inhibited OS lung metastasis, suggesting a promising therapeutic approach for the treatment of OS lung metastasis., (© 2023. The Author(s).)

In the actual decision-making process, there will be situations where decision-makers with hesitant attitudes have difficulties in evaluating alternatives numerically, and hesitant fuzzy linguistic term sets can provide decision-makers with an effective way to describe hesitancy in linguistic terms. In multi-attribute group decision-making, each decision maker typically holds different preferences. If the variation in decision makers' assessment weights across evaluations of each attribute for every alternative is not adequately accounted for, it can result in a problem of coarse-grained calculations, leading to information loss. Additionally, the three-way decision model faces significant challenges in information fusion within the context of the hesitant fuzzy linguistic environment. Therefore, we propose a new three-way decision-making model under the hesitant fuzzy linguistic environment. The model obtains the confidence of different decision makers in attribute evaluations through the fusion of D-S evidence theory, and can perform more fine-grained fusion calculations on the evaluation information of different decision makers. In addition, the model considers the cost function of each alternative in different decision-making actions under hesitant fuzzy linguistic environment, calculates the two thresholds of each alternative in the three-way decision model, and derives the decision rules. The effectiveness of the model is verified through a numerical example and two comparative experiments, therefore, the model can be applied in intelligent classification or recommendation systems of hesitant fuzzy linguistic information systems., (© 2023. The Author(s).)