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Small-animal single-photon emission computed tomography-X-ray computed tomography (SPECT-CT) is an advanced imaging tool for preclinical research of single-photon radiopharmaceuticals. Its detection performance is the foundation of image quality and the reliability of experimental data. This study aims to evaluate the performance of Albira SI SPECT-CT in terms of advisable test range，linearity，stability，deviation of measurement results，related to the radioactive isotope 99mTc，and to explore the authenticity and reliability of the scan results.The Albira SI SPECT-CT was subjected to quarterly quality control using the clinically commonly used single-photon radionuclide 99mTc. The linearity，stability，and deviation of the measurement results were tested，and preliminary attempts were made at small-animal bone metabolism scanning. The device demonstrated a strong linear correlation between radioactivity and measurement results，exhibited high stability，and showed minimal variation when compared to commonly used radioactivity measurement devices.The Albira SI small animal SPECT-CT accurately reflects the distribution of the radioactive activity of the single photon isotope 99mTc，showing excellent imaging of mouse bone metabolism，suitable for preclinical radiopharmaceutical research. The method for evaluating SPECT-CT performance established in this study is expected to provide a reference for the operation of similar equipment.

To enhance the drying efficiency and quality of Foshou leaf powder, this investigation assessed the effects of intermittent drying modes, microwave power, and load amount on its drying attributes and sensory qualities, utilizing dry basis moisture content, rate of dehydration, and sensory evaluations as benchmarks. The objective was to identify the most favorable drying conditions while also compare the variances in microstructure, color, chlorophyll concentration, hygroscopicity, solubility, and tea polyphenol between Foshou leaf powders dried using hot air and microwave techniques. The findings demonstrated that the intermittent drying modes of 20 and 30 seconds yielded the highest quality Foshou leaf powder, establishing these conditions as optimal. Notably, microwave power and the quantity of material loaded were determinants of drying speed, with an increase in microwave power notably shortening the drying duration, especially during the constant-rate phase of drying. Conversely, the effect of the load amount on drying speed was less pronounced during the falling-rate phase. Optimal sensory quality, scoring 16.5, was observed at a microwave setting of 385 W with a 20 g load amount. Through the comparison of three mathematical models to simulate drying kinetics, a nonlinear relationship between the moisture ratio of Foshou leaves and the drying time was observed. The Page and Wang-Singh models were particularly effective, with the Wang-Singh model providing superior predictive accuracy. The most accurate fitting function determined was MR=(0.0011+0.0058X1+0.0037X2)t2−(0.086+0.1544X1+0.086X2)t+1. In comparison to hot air drying, the Foshou leaf powder produced under optimal microwave drying conditions showed a looser and finer particle structure, a vibrant green hue, and enhanced sensory properties (16.9), alongside improved wettability, solubility, and a higher preservation of tea polyphenols and chlorophyll. These insights offer valuable scientific direction for the advanced processing of Foshou leaves, highlighting the potential of microwave drying in augmenting the quality of leaf powders.

Profiles and driving mechanisms of antibiotic resistome in the polar region are important for exploring the natural evolution of antibiotic resistance genes (ARGs). Here, we evaluated the profiles of antibiotic resistome in multiple media on Inexpressible Island, Terra Nova Bay, Antarctica. Average concentrations of ARGs in intracellular DNA (iARGs) among water (3.98 × 106 copies/L), soil (3.41 × 107 copies/kg), and penguin guano (7.04 × 107 copies/kg) were higher than those of ARGs in extracellular DNA (eARGs) among water (1.99 × 104 copies/L), soil (1.75 × 106 copies/kg), and penguin guano (8.02 × 106 copies/kg). It was indicated that the transmission of ARGs across different media occurs with around 77.8% of iARGs from soil and 86.7% of iARGs from penguins observed in water, and 80.7% of iARGs and 56.7% of eARGs from penguins found in soil. Annual inputs of ARGs from Adélie penguins on Inexpressible Island have increased since 1983. Bacitracin, multidrug, and aminoglycoside resistance genes were the main ARGs among water, soil, and penguin guano. Primary medium-risk ARGs associated with human pathogenic bacteria were multidrug resistance genes, and main low-risk ARGs associated with mobile genetic elements (MGEs) were aminoglycoside resistance genes. Antibiotic-resistant bacteria (ARB) from soil and penguins were more phylogenetically related to aquatic antibiotic-resistant mesophiles than aquatic antibiotic-resistant psychrophiles. MGEs, ARB, bacterial diversities, antibiotics, and metals could explain total ARGs between water and soil. Intracellular MGEs were the most significant in-situ driver of iARGs in water, reflecting that horizontal gene transfer could facilitate the spread of ARGs in water. Penguins were important ex-situ drivers of environmental antibiotic resistome, which was linked with risky ARGs between water and soil. These findings highlight the major roles of natural drivers (e.g., MGEs and penguins) in shaping environmental antibiotic resistome in polar areas, improving our understanding of the evolution of environmental microbiome.

A growing body of evidence suggests that emotion regulation (ER) plays a crucial role in the decision-making (DM) process of suicide attempters (SA). Cognitive reappraisal (CR), an emotion regulation strategy that reinterprets emotional situations to alter physiological and emotional responses, has been studied widely. Whereas, its effect on SA is yet to be explored. The present study attempted to use CR to modulate ER in SA to improve their DM performance, and explore the physiological mechanisms underlying this process. Scale scores under natural responses and after using the CR strategy, as well as behavioral and electroencephalographic (EEG) data from subjects were recorded during the classical DM task - ultimatum game (UG) paradigm. 52 patients with psychiatric disorders (including 26 SA and 26 non-suicide attempters) and 22 healthy controls (HC) performed in UG. Scale results showed that negative emotional experience scores decreased in all three groups after CR, but SA showed less improvement compared to HC. The behavioral results showed that acceptance of SA significantly increased after CR in both fair and unfair alternatives in the UG task, suggesting that CR can improve DM performance of SA. Besides, we extracted the late-positive potential (LPP) and theta-gamma coupling (TGC) of EEG for analysis. The LPP of SA was significantly higher when facing unfair alternatives than in fair ones, reflecting the fact that SA showed stronger negative emotions in the face of unfair situations. In addition, SA exhibited TGC diminished in frontotemporal regions when facing unfair allocation schemes, which demonstrated the existence of cognitive impairment in SA. This study verified the feasibility of CR for the moderation of DM ability in SA and provided new ideas for early intervention of suicidal behavior.

Abstract Purpose Pancreatic ductal adenocarcinoma (PDAC) is considered a “cold” tumor because the tumor immune microenvironment (TIME) exhibits poor intratumoral T-cell infiltration. This study aimed to identify the marker genes associated with induction of cold TIME in PDAC cells. Methods We orthotopically transplanted 10 primary cultures of PDAC derived from KrasG12D/+; Trp53R172H/+; Pdx-1-Cre (KPC) mice into immunocompetent mice and evaluated TIME by immunohistochemistry (IHC) staining of CD8. We divided primary cultures into two groups: cold TIME group with low CD8+ T-cell infiltration and a hot TIME group with high infiltration. RNA sequencing was performed to identify specific genes in the cold TIME group, and single-cell RNA sequencing (scRNA-seq) data was used for validation. IHC was performed to evaluate expressions in human PDAC samples. Results We identified six genes specific in PDAC cells to the cold TIME group by RNA sequencing; these were defined as “cold tumor induction–related genes”. Human PDAC scRNA-seq data revealed that cold tumor induction–related genes were significantly and negatively correlated with the number of CD8+ T-cells (p = 0.0341). These genes included protocadherin 7 (PCDH7). High expression of PCDH7 significantly and negatively correlated with the number of CD8+ T-cells in scRNA-seq (p = 0.0474) and IHC (p = 0.0110) data using human PDAC samples. PCDH7 was an independent factor for poor prognosis in PDAC (overall survival: hazard ratio = 2.07, p = 0.0367). Conclusion PCDH7 is a prognostic marker associated with CD8+ T-cell infiltration for PDAC patients.

Abstract The coastline reflects coastal environmental processes and dynamic changes, serving as a fundamental parameter for coast. Although several global coastline datasets have been developed, they mainly focus on coastal morphology, the typology of coastlines are still lacking. We produced a Global CoastLine Dataset (GCL_FCS30) with a detailed classification system. The coastline extraction employed a combined algorithm incorporating the Modified Normalized Difference Water Index and an adaptive threshold segmentation method. The coastline classification was performed a hybrid transect classifier that integrates a random forest algorithm with stable training samples derived from multi-source geophysical data. The GCL_FCS30 offers significant advantages in capturing artificial coastlines, reflecting strong alignment with location validation data. The GCL_FCS30 classification was found to achieve an overall accuracy and Kappa coefficient over 85% and 0.75. Each coastline category accurately covered the majority of the area represented in third-party data and exhibited a high degree of spatial relevance. Therefore, the GCL_FCS30 is the first global coastline category dataset covering the high latitudes in a continuous and smooth line vector format.

Abstract Background An accurate diagnosis of septic versus reactive or autoimmune arthritis remains clinically challenging. A multi-omics strategy comprising metagenomic and proteomic technologies were undertaken for children diagnosed with presumed septic arthritis to advance clinical diagnoses and care for affected individuals. Methods Twelve children with suspected septic arthritis were prospectively enrolled to compare standard of care tests with a rapid multi-omics approach. The multi-omics combined bacterial 16S rRNA metagenomics, single cell transcriptomics, and proteomics on knee joint fluid specimens. The diagnostic value of the multi-omics was ascertained relative to standard of care culture and PCR-negative results. Results Ten children with suspected primary septic arthritis and two with acute hematogenous osteomyelitis (AHO) diagnoses were assessed. Joint fluid bacterial cultures were positive for 6/12 (50%) patients, consistent with elevated inflammatory markers (IL-4, IL-6, IL-17A, TNF-a, etc.). Metagenomic bacterial sequencing results were 100% concordant with the culture results. Six patients were culture- and PCR-negative. Multiomics analyses of the 6 culture negative patients established that 2/6 culture-negative children had inflammatory arthritis with potential Juvenile idiopathic arthritis (JIA) and 1 had post-Streptococcal Reactive Arthritis. The children without any bacteremia had autoantibodies (IgGs) in the joint-fluid targeting several nuclear antigens (i.e., dsDNA, histones, Jo-1, scl-70, Ro/SS-A, SmDs, CENP-A along with non-nuclear antigens i.e. Albumin, Collagens, Myosin, Laminin, etc. Single cell transcriptomics confirmed an abundance of CD4+ follicular helper T (Tfh), CD8 + T cells and B cells in the autoantibody positive subjects. The combination of 16S DNA sequencing (p = 0.006), cytokine assays (p = 0.009) and autoantibody profiling (p = 0.02) were significantly distinct between those children with and without infections. This improved the diagnostic confidence for 9 of 12 (75%) children, key for treatment decisions. Conclusions The multiomics approach rapidly identified children with bacterial or autoimmune inflammatory conditions, improving diagnostic and treatment strategies for those with presumptive septic arthritis.

Abstract Objective In today's fast-paced society, stress has become a widespread phenomenon, garnering increasing attention for its impact on cancer. This study aims to investigate the current status and research hotspots of chronic stress in cancer research from 2014 to 2024, with the goal of providing valuable insights for future studies. Methods We retrieved 618 articles published between 2014 and 2024 from the Web of Science database and analyzed them using R software, VOSviewer, and CiteSpace. Results There is an overall upward trend in chronic stress-related cancer research, with China leading in publications, followed by the United States, India, Australia, and Italy. The journal most cited is Brain Behavior and Immunity. Key themes identified include 'inflammation', 'breast cancer', 'anxiety', 'psychological stress', and 'oxidative stress'. The primary focus of the research is the impact of chronic stress on various cancer types, the underlying molecular mechanisms, and the implications of chronic stress-related treatments on cancer outcomes. Conclusion Chronic stress is increasingly recognized as a Carcinogenic factors. This study provides a comprehensive analysis of chronic stress-related cancer research from 2014 to 2024, offering valuable guidance for future research in this field.

Abstract Objectives To establish and validate a dual-modal radiomics nomogram from grayscale ultrasound and color doppler flow imaging (CDFI) of cervical lymph nodes (LNs), aiming to improve the diagnostic accuracy of metastatic LNs in differentiated thyroid carcinoma (DTC). Methods DTC patients with suspected cervical LNs in two medical centers were retrospectively enrolled. Pathological results were set as gold standard. We extracted radiomic characteristics from grayscale ultrasound and CDFI images, then applied lasso (least absolute shrinkage and selection operator) regression analysis to analyze radiomics features and calculate the rad-score. A nomogram based on rad-score, clinical data, and ultrasound signs was developed. The performance of the model was evaluated using AUC and calibration curve. We also assessed the model’s diagnostic ability in European Thyroid Association (ETA) indeterminate LNs. Results 377 DTC patients and 726 LNs were enrolled. 37 radiomics features were determined and calculated as rad-score. The dual-modal radiomics model showed good calibration capabilities. The radiomics model displayed higher diagnostic ability than the traditional ultrasound model in the training set [0.871 (95% CI: 0.839–0.904) vs. 0.848 (95% CI: 0.812–0.884), p

Temperature could change the migration characteristics of coastal groundwater. However, research on groundwater discharge processes under the influences of cut-off walls has been limited to isothermal conditions. This study built a two-dimensional numerical model coupling groundwater flow and salt transport in non-isothermal conditions at the site scale to investigate the impact of cut-off walls on groundwater discharge processes, considering the thermal effect. We focused on the dynamic characteristics of submarine groundwater discharge in non-isothermal conditions which are common in reality. This research quantitatively assessed the influence of seawater temperature on groundwater discharge flux (Q) and relative discharge flux (Q'). The results indicate that, under high-temperature seawater conditions, the timescale for Q' to reach equilibrium is significantly reduced. Specifically, higher freshwater temperatures and lower seawater temperatures could result in a greater Q'. However, when the seawater temperature exceeded the groundwater temperature by 15°C, reverse circulation is more likely to develop in the saltwater zone, which accelerates groundwater circulation and increases the total groundwater discharge into the sea, resulting in a corresponding rise in the Q' value. This study is significant for cut-off wall structure optimization and coastal groundwater sustainable utilization.

Abstract Neutralizing antibody titer has been a surrogate endpoint for guiding COVID-19 vaccine approval and use, although the pandemic’s evolution and the introduction of variant-adapted vaccine boosters raise questions as to this surrogate’s contemporary performance. For 985 recipients of an mRNA second bivalent or monovalent booster containing various Spike inserts [Prototype (Ancestral), Beta, Delta, and/or Omicron BA.1 or BA.4/5] in the COVAIL trial (NCT05289037), titers against 5 strains were assessed as correlates of risk of symptomatic COVID-19 (“COVID-19”) and as correlates of relative (Pfizer-BioNTech Omicron vs. Prototype) booster protection against COVID-19 over 6 months of follow-up during the BA.2-BA.5 Omicron-dominant period. Consistently across the Moderna and Pfizer-BioNTech vaccine platforms and across all variant Spike inserts assessed, both peak and exposure-proximal (“predicted-at-exposure”) titers correlated with lower Omicron COVID-19 risk in individuals previously infected with SARS-CoV-2, albeit significantly less so in naïve individuals [e.g., exposure-proximal hazard ratio per 10-fold increase in BA.1 titer 0.74 (95% CI 0.59, 0.94) for naïve vs. 0.41 (95% CI 0.23, 0.64) for non-naïve; interaction p = 0.013]. Neutralizing antibody titer was a strong inverse correlate of Omicron COVID-19 in non-naïve individuals and a weaker correlate in naïve individuals, posing questions about how prior infection alters the neutralization correlate.

Abstract Colorectal cancer (CRC) is the third most prevalent malignancy and the second leading cause of cancer-related mortality worldwide, with an increasing shift towards younger age of onset. In recent years, there has been increasing recognition of the significance of tRNA-derived small RNAs (tsRNAs), encompassing tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs). Their involvement in regulating translation, gene expression, reverse transcription, and epigenetics has gradually come to light. Emerging research has revealed dysregulation of tsRNAs in CRC, implicating their role in CRC initiation and progression, and highlighting their potential in early diagnosis, prognosis, and therapeutic strategies. Although the clinical application of tsRNAs is still in its early stages, recent findings highlight a close relationship between the biogenesis and function of tsRNAs, tRNA chemical modifications, and the tumor immune microenvironment (TIME). Additionally, similar to other small RNAs, tsRNAs can be effectively delivered via nanoparticles (NPs). Consequently, future research should focus on elucidating the clinical significance of tsRNAs concerning base modifications, TIME regulation, cancer immunotherapy, and NPs delivery systems to facilitate their clinical translation.

Abstract Background The prevalence of type 2 diabetes (T2D) and asthma is rising, yet evidence regarding the relationship between T2D and asthma, particularly in the context of genetic predispositions, remains limited. Methods This study utilized data from the UK Biobank longitudinal cohort, involving 388,775 participants. A polygenic risk score (PRS) for asthma was derived from genome-wide association studies summary. Cox regression models were used to assess the association between T2D and asthma, incorporating the asthma PRS. Results Over a median follow-up of 13.62 years, 10,211 asthma cases were documented. After adjusting for age, sex, current smoking status, and other confounding variables, T2D was significantly associated with an increased risk of developing asthma (Hazard Ratios [HR] 1.16, 95% confidence interval [CI] 1.06–1.26). This association remained significant after further adjustments for genetic susceptibility to asthma. Furthermore, T2D increased the risk of developing asthma across both high and low genetic risk groups. Conclusions T2D is associated with an increased risk of developing asthma, irrespective of genetic susceptibility. These findings underscore the importance of incorporating glucose regulation strategies into asthma prevention efforts.

Medium carbon boron steel is a cost-effective, high-strength steel used for bolts. This paper aims to provide a theoretical foundation and data support for optimizing heat treatment and improving performance in wind turbine bolts by systematically analyzing the synergistic effects of boron segregation, dislocation density, high-angle grain boundaries (HAGBs) and other factors during tempering on the low-temperature impact toughness of 35MnB steel. The form and distribution of boron in the steel were characterized by time-of-flight secondary ion mass spectrometry (TOF-SIMS) combined with transmission electron microscopy (TEM). The relationship between crystallographic orientation and low-temperature impact toughness was analyzed using electron backscatter diffraction (EBSD). The results show that when the tempering temperature is between 350 °C and 410 °C, numerous large M3(C, B) at the prior austenite grain boundaries (PAGBs) lead to intergranular fracture in the radial zone of the impact fracture. However, the adverse effects on low-temperature impact toughness are mitigated by the decrease in dislocation density, effective grain size, and the increase in HAGBs. As a result, the low-temperature impact energy increases slowly from 19.5 J to 24.2 J. When the tempering temperature is between 410 °C and 470 °C, the size and quantity of boron phases at the PAGBs decrease, leading to a rapid increase in impact energy from 24.2 J to 86 J. The rolling texture gradually weakens and eventually disappears after tempering, resulting in anisotropy. Therefore, boron segregation is the primary factor affecting the low-temperature impact toughness.

Abstract Aerial images can cover a wide area and capture rich scene information. These images are often taken from a high altitude and contain many small objects. It is difficult to detect small objects accurately because their features are not obvious and are susceptible to background interference. The CPDD-YOLOv8 is proposed to improve the performance of small object detection. Firstly, we propose the C2fGAM structure, which integrates the Global Attention Mechanism (GAM) into the C2f structure of the backbone so that the model can better understand the overall semantics of the images. Secondly, a detection layer named P2 is added to extract the shallow features. Thirdly, a new DSC2f structure is proposed, which uses Dynamic Snake Convolution (DSConv) to take the place of the first standard Conv of Bottleneck in the C2f structure, so that the model can adapt to different inputs more effectively. Finally, the Dynamic Head (DyHead), which integrates multiple attention mechanisms, is used in the head to assign different weights to different feature layers. To prove the effectiveness of the CPDD-YOLOv8, we carry out ablation and comparison experiments on the VisDrone2019 dataset. Ablation experiments show that all the improved and added modules in CPDD-YOLOv8 are effective. Comparative experiments suggest that the mAP of CPDD-YOLOv8 is higher than the other seven comparison models. The mAP@0.5 of this model reaches 41%, which is 6.9% higher than that of YOLOv8. The CPDD-YOLOv8’s small object detection rate is improved by 13.1%. The generalizability of the CPDD-YOLOv8 model is verified on the WiderPerson, VOC_MASK and SHWD datasets.

Abstract A distinctive feature of both type 1 and type 2 diabetes is the waning of insulin-secreting beta cells in the pancreas. New methods for direct and specific targeting of the beta cells could provide platforms for delivery of pharmaceutical reagents. Imaging techniques such as Positron Emission Tomography (PET) rely on the efficient and specific delivery of imaging reagents, and could greatly improve our understanding of diabetes etiology as well as providing biomarkers for viable beta-cell mass in tissue, in both pancreas and in islet grafts. The DiGeorge Syndrome Critical Region Gene 2 (DGCR2) protein has been suggested as a beta-cell specific protein in the pancreas, but so far there has been a lack of available high-affinity binders suitable for targeted drug delivery or molecular imaging. Affibody molecules belong to a class of small affinity proteins with excellent properties for molecular imaging. Here, we further validate the presence of DGCR2 in pancreatic and stem cell (SC)-derived beta cells, and then describe the generation and selection of several Affibody molecules candidates that target human DGCR2. Using an in-house developed directed evolution method, new DGCR2-binding Affibody molecules were generated and evaluated for thermal stability and affinity. The Affibody molecules variants were further developed as targeting agents for delivering imaging reagents to beta cell. The Affibody molecule ZDGCR2:AM106 displayed nanomolar affinity, suitable stability and biodistribution, with negligible toxicity to islets, qualifying it as a suitable lead candidate for further development as a tool for specific delivery of drugs and imaging reagents to beta cells.

Abstract Although immune checkpoint inhibitors have changed the treatment paradigm for non-small cell lung cancer (NSCLC), not all patients benefit from them. Therefore, there is an urgent need to explore novel immune checkpoint inhibitors. Neuropilin-1 (Nrp-1) is a unique immune checkpoint capable of exerting antitumor effects through CD8+ T cells. It is also a T-cell memory checkpoint that regulates long-term antitumor immunity. However, its role in NSCLC remains unclear. The aim of this study was to develop a fully human anti-Nrp-1 antibody with therapeutic effects against NSCLC in vitro and in vivo. We screened and constructed of a high-affinity anti-Nrp-1 IgG antibody from a constructed high-capacity fully human single-chain fragment variable (scFv) phage library. This novel anti-Nrp-1 IgG antibody partially restored the killing function of exhausted CD8+ T cells in malignant pleural fluid in vitro. Co-culture of peripheral blood mononuclear cells (PBMC) with A549 and the addition of anti-Nrp1-IgG enhanced the killing of A549 target cells, leading to an increase in late-stage apoptosis of target cells. Importantly, anti-Nrp1-IgG treatment significantly reduced tumor volume in a mouse model of lung cancer with humanized immune system. These findings suggest that 53-IgG has a promising application as a potent Nrp-1-targeting agent in NSCLC immunotherapy.

Lycium barbarum var. implicatum (2010), is a new variety of L. barbarum in Solanaceae. Here, we sequenced, assembled, and annotated the complete chloroplast (cp) genome of L. barbarum var. implicatum. Results showed that the complete cp genome of L. barbarum var. implicatum was 154,888 bp in length, containing a large single copy (LSC) region of 85,894 bp, a pair of inverted repeats (IR) region of 25,393 bp, and a small single copy (SSC) region of 18,208 bp. Maximum-likelihood (ML) phylogenetic tree elucidated that L. barbarum var. implicatum was sister to L. ruthenicum. Our results provide useful information for future phylogenetic studies in the family of Solanaceae.

Abstract Background Fruit acidity and color are important quality attributes in peaches. Although there are some exceptions, blood-fleshed peaches typically have a sour taste. However, little is known about the genetic variations linking organic acid and color regulation in peaches. Results Here, we report a peach graph-based pangenome constructed from sixteen individual genome assemblies, capturing abundant structural variations and 82.3 Mb of sequences absent in the reference genome. Pangenome analysis reveals a long terminal repeat retrotransposon insertion in the promoter of the NAC transcription factor (TF) PpBL in blood-fleshed peaches, which enhances PpBL expression. Genome-wide association study identifies a significant association between PpBL and malate content. Silencing PpBL in peach fruit and ectopic overexpression of PpBL in tomatoes confirm that PpBL is a positive regulator of malate accumulation. Furthermore, we demonstrate that PpBL works synergistically with another NAC TF, PpNAC1, to activate the transcription of the aluminum-activated malate transporter PpALMT4, leading to increased malate content. Conclusions These findings, along with previous research showing that PpBL and PpNAC1 also regulate anthocyanin accumulation, explain the red coloration and sour taste in blood-fleshed peach fruits.

Abstract Background Metabolic health is closely related to testosterone levels, and the cardiometabolic index (CMI) is a novel metabolic evaluation metric that encompasses obesity and lipid metabolism. However, there is currently a lack of research on the relationship between CMI and testosterone, which is the objective of this study. Methods This study utilized data from the National Health and Nutrition Examination Survey (NHANES) cycles from 2011 to 2016. Only adult males who completed physical measurements, lipid metabolism assessments, and testosterone measurements were included in the final analysis. The exposure variable CMI was analyzed both as a continuous variable and a categorical variable divided into quartiles. Testosterone was measured using the isotope dilution liquid chromatography-tandem mass spectrometry technique. Linear and logistic regression analyses were used to explore the relationship between CMI and total testosterone (TT) levels, as well as the risk of testosterone deficiency (TD). Smooth curve fittings were employed to visualize their linear relationships. Subgroup analyses were conducted to evaluate the stability of our results across different participant characteristics. Finally, ROC analysis was used to assess the performance of CMI in predicting TD. Results A total of 2,747 participants were included in the analysis, including 552 with TD (20.10%). The average CMI of the sample was 1.59 ± 0.03, with TD participants having a higher CMI of 2.18 ± 0.08 compared to non-TD participants at 1.46 ± 0.03. Corresponding testosterone levels were 223.79 ± 3.69 ng/dL and 508.36 ± 5.73 ng/dL, respectively. After adjusting for all covariates, participants with higher CMI showed lower TT (β = -23.84, 95% CI: -33.94, -13.74, p

Abstract Background In clinical practice, creative arts therapy is frequently utilized for the treatment of traumatized adults, with reports of favorable outcomes. However, the effectiveness of this intervention in post-traumatic stress disorder (PTSD) treatment has not yet been definitively established through meta-analysis. In this meta-analysis, we aim to assess the effectiveness of creative arts therapy in the management of PTSD. Methods We conducted systematic literature searches through electronic databases from the extended inception of each database to November 2023. We utilized the Cochrane risk of bias tool to evaluate the quality of evidence. Standardized mean differences (SMDs) were calculated as the effects of creative art therapy on the improvement of PTSD. Results Seven controlled, comparative studies investigated the use of creative arts therapy in treating adults with PTSD. Meta-analysis demonstrated a significant decrease in PTSD symptoms following creative arts therapy (SMD = -1.98, 95% Confidence Interval (CI): -3.8 to -0.16, p

The development of biodegradable bone scaffolds that align with the growth cycle of new bone has become a prominent focus in the field of bone defect repair. The sintered porous hydroxyapatite scaffolds exhibit a high degree of crystallization and demonstrate a slow degradation rate following implantation. The apatite phase with low crystallinity can be obtained following the hydration reaction of the non-sintered calcium phosphate bone cement (CPC) scaffolds. However, this leads to the formation of a weak alkaline environment during degradation, ultimately resulting in unsustainable degradation. The present study focuses on the fabrication of porous pectin/CPC composite scaffolds through two approaches during the preparation process of non-sintered porous CPC scaffolds: uniform composite and surface modification. The degradation performance of porous composite scaffolds exhibited an increase with the rise in pectin content. At a pectin content of 70 mg/mL, the scaffolds demonstrated a degradation rate of 13.79% within a span of 30 days. The mechanical properties of the porous scaffolds were enhanced with an increase in pectin concentration through surface coating. When the pectin concentration was 5 wt%, the scaffold exhibited a compressive strength of 8.72 MPa, an elastic modulus of 0.82 GPa, and experienced a degradation rate of 12.57% after a period of 30 days. The local acidic environment not only facilitates the dissolution of bone-like apatite but also enhances cell proliferation and adhesion. Pectin/apatite porous scaffolds exhibit excellent biocompatibility, offering a novel approach for the development of biodegradable bone replacement scaffolds.

With the rapid development of IoT technology, real-time human pose estimation has become increasingly important in sports training feedback systems. However, current methods often fall short in balancing high accuracy with low computational resource requirements, especially in resource-constrained environments. Deep learning has shown significant potential in enhancing computer vision tasks, including human pose estimation. In this study, we propose DESNet, an improved EfficientHRNet model that integrates IoT technology. DESNet combines Dynamic Multi-Scale Context (DMC) modules and Squeeze-and-Excitation (SE) modules, and utilizes IoT for real-time data collection, transmission, and processing. Experimental results show that DESNet achieves an average precision (AP) of 74.8% on the COCO dataset and a PCKh (Percentage of Correct Keypoints with head-normalized) of 90.9% on the MPII dataset, outperforming existing lightweight models. The integration of deep learning and IoT technology not only improves the accuracy and efficiency of human pose estimation but also significantly enhances the timeliness and robustness of feedback in sports training applications. Our findings demonstrate that DESNet is a powerful tool for real-time human pose analysis, offering promising solutions for intelligent sports training and rehabilitation systems.

Abstract Background Abdominal fluid collection (AFC) is one of the most common complications after pancreatic surgery, yet there are few recommendations on how to manage it. Most cases of AFC only require observation, while others may require more invasive techniques. Unfortunately, there are no drugs that effectively promote the absorption of AFCs. The aim of this study was to evaluate the potential efficacy of Glauber’s salt solution for promoting the absorption of AFCs after pancreatectomy. Methods This study included 196 patients who underwent pancreatomy and had AFCs on at least 2 cross-sectional follow-up CT images between 2020 and 2022. AFCs were defined as effusion with a diameter ≥ 3 cm and located around the pancreatic resection margin. We retrospectively investigated the relationship between Glauber’s salt concentration and clinical variables. Results The rate of clinically significant pancreatic fistula (grades B + C) was significantly higher in the control group (62.8% vs. 40.7%, P = 0.014). The median maximum diameter of the AFC was smaller, and the median time for the AFC to decrease to 30 mm in diameter was shorter in the Glauber’s salt group than in the control group (41.9 mm vs. 53.5 mm, P = 0.008; 35.5 d vs. 100 d, P

Abstract There is a phenomenon that better teachers cannot teach out better students in knowledge distillation due to the capacity mismatch. Especially in pixel-level object segmentation, there are some challenging pixels that are difficult for the student model to learn. Even if the student model learns from the teacher model for each pixel, the student’s performance still struggles to show significant improvement. Mimicking the learning process of human beings from easy to difficult, a dynamic dropout self-distillation method for object segmentation is proposed, which solves this problem by discarding the knowledge that the student struggles to learn. Firstly, the pixels where there is a significant difference between the teacher and student models are found according to the predicted probabilities. And these pixels are defined as difficult-to-learn pixel for the student model. Secondly, a dynamic dropout strategy is proposed to match the capability variation of the student model, which is used to discard the pixels with hard knowledge for the student model. Finally, to validate the effectiveness of the proposed method, a simple student model for object segmentation and a virtual teacher model with perfect segmentation accuracy are constructed. Experiment results on four public datasets demonstrate that, when there is a large performance gap between the teacher and student models, the proposed self-distillation method is more effective in improving the performance of the student model compared to other methods.

Nanofine zero−valent iron (nZVI) is a new, eco−friendly material with strong reducing and adsorbent properties that can be used to clean up heavy metal−affected soils. Herein, nZVI encapsulated with carboxymethyl cellulose (CMC−nZVI) is synthesized via an aqueous−phase reduction technique and subsequently deployed to evaluate its effectiveness in Cr(VI) soil remediation. The characterization analysis used SEM−EDS, XRD, XPS, and LSV to determine the relevant properties of the material. The results show that at an initial Cr(VI) concentration of 169.5 mg·kg−1, 93.2% of Cr(VI) was removed from the soil after 10 h of treatment with CMC−nZVI at pH 3.3. The kinetic analysis showed that CMC−nZVI had the maximum equilibrium adsorption capacity for removing Cr(VI) from soil at 105.3 mg·g−1. This followed a pseudo−second−order kinetic model. The study shows that CMC−nZVI converts Cr(VI) to Cr(III), which forms complexes with Fe(III) ions in the presence of hydroxide ions (OH−) to form a highly stable compound that eventually adsorbs into the nanomaterial’s surface for efficient removal.

Abstract Background Abnormal body temperature (fever or hypothermia) is a critical symptom in sepsis and is strongly associated with clinical prognosis and disease progression. Given the duality and variability of body temperature fluctuations throughout the disease course, further research is essential to refine clinical strategies for temperature management in sepsis patients. Methods We extracted clinical data of sepsis patients from the MIMIC-IV database. A restricted cubic spline (RCS) curve was employed to describe the non-linear relationship between body temperature and clinical outcomes. Based on peak temperature within the first 24 h after admission, patients were categorized into three groups: 38 °C. We subsequently matched patients one-to-one into three cohorts using a pairwise propensity score matching (PSM) approach. Alongside clinical data, we conducted log-rank and McNemar tests, and established multiple models, including multiple Cox regression, overlap-weighted (OW) adjusted Cox regression, multiple logistic regression, and OW-adjusted multiple logistic regression, to investigate the impact of temperature on clinical outcomes. Results A total of 35,499 sepsis patients were included in my study: 311 with a temperature below 36 °C, 27,538 with a temperature between 36 and 38 °C, and 7650 with a temperature above 38 °C. The RCS analysis revealed a non-linear, U-shaped relationship between body temperature and 28-day, ICU, and in-hospital mortality. Patients with hypothermia had significantly higher 28-day mortality (54.34% vs. 19.28%), ICU mortality (44.37% vs. 12.89%), and in-hospital mortality (49.20% vs. 17.46%) compared to those with hyperthermia. Among patients younger than 65 years, hyperthermia was a protective factor against 28-day mortality relative to normal body temperature, while the opposite was observed in patients aged 65 and older. This trend was consistent in the analysis of ICU and in-hospital mortality. Conclusions Among sepsis patients admitted to the ICU, a peak temperature below 36 °C within the first 24 h of admission was associated with higher 28-day mortality. However, no significant difference in clinical prognosis was observed between normothermic and hyperthermic patients.

Abstract Since agriculture is a major source of greenhouse gas emissions, accurately calculating these emissions is essential for simultaneously addressing climate change and food security challenges. This paper explores the critical role of trade in transferring agricultural greenhouse gas (AGHG) emissions throughout global agricultural supply chains. We develop a detailed AGHG emission inventory with comprehensive coverage across a wide range of countries and emission sources at first. Utilizing this inventory, the multi-regional input-output analysis is integrated with the complex network analysis to specifically reveal the characteristics of global AGHG flow networks. Finally, scenario analyses reflecting current trends and policy changes in global agriculture are conducted to investigate the emission reduction potential of different networks. The results show that the community division and characteristics of different AGHG networks vary, with more communities in the rice-CH4 and livestock-CH4, N2O networks, and fewer in the cropland-N2O network. Production-side technology improvements (reducing direct carbon emission intensities) and consumption-side livestock products substitution can contribute to the reduction of global AGHG emissions. At the same time, these impacts may propagate to other countries through AGHG networks. In contrast, localization substitution has minimal impact on AGHG emissions and may even result in slight negative effects. It is suggested that enhancing cooperation between countries from a network perspective, such as strengthening the transfer of advanced production technologies within communities, could help reconceptualize global agricultural decarbonization.

Abstract Background The Hezuo (HZ) pig, a famous indigenous breed in China, is characterized by precocious puberty compared with foreign-introduced pig breeds. Sexual maturation is a complex physiological process, and in recent years, circular RNAs (circRNAs), a new class of noncoding RNAs with endogenous regulatory functions, have been shown to play important roles in regulating sexual maturation. However, the dynamic expression and regulatory mechanism of circRNAs during sexual maturation in HZ pigs remain unclear. In this study, we performed RNA sequencing and bioinformatics analysis to reveal circRNA expression patterns in the testes of HZ boars at 30 days (sexual immaturity; Ha) and 120 days (sexual maturity; Hb), with Landrace (LC) boars of the same age (La and Lb) as controls. Subsequently, an abundant circ_005678 (circPAN3) transcribed from the PAN3 gene, was functionally investigated by RT-qPCR, Western Blot, CCK-8, and flow cytometry. Results We identified 31,134 circRNAs in 12 samples, and 2,562, 2,401, 749, and 831 differentially expressed (DE) circRNAs were identified in the Ha-vs-Hb, La-vs-Lb, Ha-vs-La, and Hb-vs-Lb groups, respectively. The results of functional enrichment analyses indicated that these source genes of the DE circRNAs were involved mainly in testicular development and spermatogenesis. Furthermore, we constructed a circRNA-miRNA-mRNA interaction network and functionally analyzed the target genes. GO functional annotation of the target genes suggested that they were mainly involved in biological processes such as gland development, cell proliferation, and reproduction. KEGG pathway analysis further revealed that these genes were enriched mainly in signaling pathways involved in testicular development and spermatogenesis, including the PI3K-Akt and MAPK signaling pathways. Cellular assays revealed that circPAN3 promoted proliferation and inhibited apoptosis in immature Sertoli cells, whereas opposite changes were observed by circPAN3 knockdown. Conclusions This study revealed the dynamic expression profiles and regulatory mechanisms of circRNAs during sexual maturation in HZ pigs. Further functional studies demonstrated that circPAN3 promoted the proliferation and inhibited the apoptosis of immature Sertoli cells, suggesting that circPAN3 may be closely related to the characteristics of precocious puberty in HZ boars. These findings provide a new perspective for exploring the regulatory mechanism of circRNAs in precocious puberty in HZ pigs.

Abstract Phosphogypsum is the main industrial solid waste from wet process phosphoric acid production, which has significant potential for environmental sustainability and engineering applications when modified. In order to explore the mechanical properties of modified phosphogypsum (MG) in different loading environments, uniaxial compression tests were conducted at four loading rates: 0.03, 0.06, 0.12, and 0.6 mm/min. The test results show that MG undergoes creeping at the loading rate of 0.03 mm/min, quasi-static loading at 0.12 to 0.6 mm/min, and transition between the two states at 0.06 mm/min. As the loading rate increases, the crack initiation stress $${\sigma _{{\text{ci}}}}$$ , damage stress $${\sigma _{{\text{cd}}}}$$ , and peak strength $${\sigma _f}$$ gradually increase, but the increasing amplitude gradually decreases. Under quasi-static loading at 0.12 to 0.6 mm/min, $${\sigma _{{\text{ci}}}}{\text{/}}{\sigma _f}$$ and $${\sigma _{{\text{cd}}}}{\text{/}}{\sigma _f}$$ show no significant changes and remain at 0.52 and 0.81, respectively, close to the values of rock materials. As the loading rate increases from creep loading to quasi-static loading, the elastic strain energy increases slowly and steadily, while the total strain energy and dissipative strain energy decrease first and then increase slowly. With the axial stress increasing from 0 to 0.81 $${\sigma _f}$$ , the principal strain field changes from relatively uniform to a concentration band, which has a very steep angle with the horizontal direction. The research results provide an important theoretical basis for the engineering application of MG as building materials.

Abstract. Objective:. Eosinophils (EOS) are inflammatory innate immune cells that play an important role in arterial thrombogenesis. There is a paucity of data on whether EOS levels have an impact on long-term outcomes following ST-segment elevation myocardial infarction (STEMI). This study aimed to investigate the impact of EOS count on the clinical outcomes of STEMI patients who underwent emergency percutaneous coronary intervention (PCI). Methods:. This is a retrospective multicenter cohort study. A total of 754 patients with STEMI who required emergency PCI at 5 centers were screened between October 2015 and November 2016. Patients were divided into 2 groups based on EOS count: EOS count

Objective: The protective effect of Poria cocos polysaccharides (PCPs) on the learning and memory function of scopolamine-induced dementia mice and its mechanism were explored, which was expected to provide a new idea for the prevention and treatment of dementia. Methods: Mice were divided into control group, model group, low-dose PCPs group (50 mg/kg), high-dose PCPs group (100 mg/kg), and donepezil group (1 mg/kg). The mice were administered by gavage once daily, continuously for 28 d, in which mice except those in the control group were intraperitoneally injected with scopolamine (1 mg/kg) from the 24th d, successively for 5 d. The learning and memory function of mice were observed by water maze test, the pathological changes in the hippocampal tissue were examined by hematoxylin and eosin (HE) staining, the apoptosis of hippocampal cells was observed by TUNEL staining, the expression of hippocampal apoptosis-related genes was detected by real-time quantitative PCR, the hippocampal central cholinergic system indicators and oxidative stress indicators were detected by enzyme-linked immunosorbent assay (ELISA), and the expression of Kelch-like ECH-associated protein 1 (Keap1), nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) in the hippocampal tissue was detected by Western blot. Results: Compared with that in the model group, the escape latency of mice in low-dose and high-dose PCPs groups was shortened (P

Abstract Background Despite the increasing use of metagenomic next-generation sequencing (mNGS) in sepsis, identifying clinically relevant pathogens remains challenging. This study was aimed to evaluate the clinical utility of simultaneous plasma and bronchoalveolar lavage fluid (BALF) detection using mNGS. Methods This retrospective study enrolled 95 patients with pneumonia-derived sepsis (PDS) admitted to the intensive care unit (ICU) between October 2021 and January 2023. Patients were divided into two groups: mNGS group (n = 60) and the non-mNGS group (n = 35), based on whether simultaneous plasma and BALF mNGS were conducted. All patients underwent conventional microbiological tests (CMT), including bacterial/fungal culture of peripheral blood and BALF, as well as sputum culture, detection of 1, 3-beta-D- glucan in BALF and RT-PCR testing. The clinical data of the enrolled patients were collected, and the detection performance and prognosis of plasma mNGS, BALF mNGS and CMT were compared. Results The mNGS group exhibited a lower mortality rate than the non-mNGS group (35.0% vs. 57.1%, P = 0.034). Simultaneous detection in dual-sample resulted in a higher proportion of microorganisms identified as definite causes of sepsis alert compared to detection in either plasma or BALF alone (55.6% vs. 20.8% vs. 18.8%, P

Abstract Urban greening plays a crucial role in maintaining environmental sustainability and enhancing people’s well-being. However, limited by the shortcomings of traditional methods, studying the heterogeneity and nonlinearity between environmental factors and green view index (GVI) still faces many challenges. To address the concerns of nonlinearity, spatial heterogeneity, and interpretability, an interpretable spatial machine learning framework incorporating the Geographically Weighted Random Forest (GWRF) model and the SHapley Additive exPlanation (Shap) model is proposed in this paper. In this paper, we combine multi-source big data, such as Baidu Street View data and remote sensing images, and utilize semantic segmentation models and geographic data processing techniques to study the global and local interpretation of the Beijing region with GVI as the key indicator. Our research results show that: (1) Within the Sixth Ring Road of Beijing, GVI shows significant spatial clustering phenomenon and positive correlation linkage, and at the same time exhibits significant spatial differences; (2) Among many environmental variables, the increase of green coverage rate has the most significant positive effect on GVI, while the increase of building density shows a strong negative correlation with GVI; (3) The performance of the GWRF model in predicting GVI is excellent and far exceeds that of comparison models.; (4) Whether it is the green coverage rate, urban built environment or socioeconomic factors, their influence on GVI shows non-linear characteristics and a certain threshold effect. With the help of these non-linear influences and explicit threshold effects, quantitative analyses of greening are provided, which can help to assist urban planners in making more scientific and rational decisions when allocating greening resources.

The outbreak of algal blooms caused by cyanobacteria has led to a significant concern regarding water safety due to the release of microcystins. This study aimed to investigate the release and removal of microcystins (RR, LR) using coagulant polyaluminum chloride (PAC) with the assistance of nano-Fe3O4 particles. The findings indicate that the addition of PAC alone resulted in the rupture of Microcystis aeruginosa cells, leading to the release of microcystins into the water. PAC alone faced challenges in coagulating and removing the extracellular microcystins, especially at low dosages, but increasing the dosage of PAC could promote the release of intracellular microcystins. When combined with nano-Fe3O4, even a low concentration of PAC exhibited effective removal of microcystins in water. The presence of nano-Fe3O4 facilitated the hydrolysis of PAC, resulting in the production of Alc, which enhanced the coagulation performance of PAC. Furthermore, the addition of nano-Fe3O4 significantly improved the removal rate of microcystins by coagulant PAC under different pH conditions. Notably, at pH 5, the residual amount of microcystins was only about 7% compared to PAC alone. This study holds great significance in terms of achieving safer and more economical removal of microcystins from water.

Background: Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication. Method: We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network. Results: We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes. Conclusion: Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

In object segmentation, the existence of hard-classified-pixels limits the segmentation performance. Focusing on these hard pixels through assigning different weights to pixel loss can guide the learning of segmentation model effectively. Existing loss weight assignment methods perceive pixels hardness by current predicted information, pay less attention to past predicted information. While current studies show that samples with less improvement in predicted probability compared to the past are difficult to learn. To define hard pixels more accurately, a hardness-aware loss for object segmentation is proposed. Firstly, the metric of pixel hardness degree is defined, and a mapping function is proposed to quantitatively evaluate the hardness degree which is defined on the difference between current and past predicted probabilities. Then a new compound metric, hardness value, is defined based on hardness degree and the uncertainty. Based on the compound metric, a new loss function is proposed. Experiment results on four datasets using convolutional neural network and Transformer as the backbone models demonstrate that the proposed method effectively improves the accuracy of object segmentation. Especially, in the segmentation model based on ResNet-50, the proposed method improves mean Intersection over Union (mIoU) by almost 4.3 % compared to cross entropy on DUT-O dataset.

Low tumor immunogenicity, immunosuppressive tumor microenvironment, and bacterial infections have emerged as significant challenges in postsurgical immunotherapy and skin regeneration for preventing melanoma recurrence. Herein, an immunotherapeutic hydrogel booster (GelMA-CJCNPs) was developed to prevent postoperative tumor recurrence and promote wound healing by incorporating ternary carrier-free nanoparticles (CJCNPs) containing chlorine e6 (Ce6), a BRD4 inhibitor (JQ1), and a glutaminase inhibitor (C968) into methacrylic anhydride-modified gelatin (GelMA) dressings. GelMA-CJCNPs reduced glutathione production by inhibiting glutamine metabolism, thereby preventing the destruction of reactive oxygen species generated by photodynamic therapy, which could amplify oxidative stress to induce severe cell death and enhance immunogenic cell death. In addition, GelMA-CJCNPs reduced M2-type tumor-associated macrophage polarization by blocking glutamine metabolism to reverse the immunosuppressive tumor microenvironment, recruiting more tumor-infiltrating T lymphocytes. GelMA-CJCNPs also downregulated IFN-γ-induced expression of programmed cell death ligand 1 to mitigate acquired immune resistance. Benefiting from the amplified systemic antitumor immunity, GelMA-CJCNPs markedly inhibited the growth of both primary and distant tumors. Moreover, GelMA-CJCNPs demonstrated satisfactory photodynamic antibacterial effects against Staphylococcus aureus infections, thereby promoting postsurgical wound healing. Hence, this immunotherapeutic hydrogel booster, as a facile and effective postoperative adjuvant, possesses a promising potential for inhibiting tumor recurrence and accelerating skin regeneration.

Objective: The presence of complex components in Chinese herbal medicine (CHM) hinders identification of the primary active substances and understanding of pharmacological principles. This study was aimed at developing a big-data-based, knowledge-driven in silico algorithm for predicting central components in complex CHM formulas. Methods: Network pharmacology (TCMSP) and clinical (GEO) databases were searched to retrieve gene targets corresponding to the formula ingredients, herbal components, and specific disease being treated. Intersections were determined to obtain disease-specific core targets, which underwent further GO and KEGG enrichment analyses to generate non-redundant biological processes and molecular targets for the formula and each component. The ratios of the numbers of biological and molecular events associated with a component were calculated with a formula, and entropy weighting was performed to obtain a fitting score to facilitate ranking and improve identification of the key components. The established method was tested on the traditional CHM formula Danggui Sini Decoction (DSD) for gastric cancer. Finally, the effects of the predicted critical component were experimentally validated in gastric cancer cells. Results: An algorithm called Chinese Herb Medicine-Formula vs. Ingredients Efficacy Fitting & Prediction (CHM-FIEFP) was developed. Ferulic acid was identified as having the highest fitting score among all tested DSD components. The pharmacological effects of ferulic acid alone were similar to those of DSD. Conclusions: CHM-FIEFP is a promising in silico method for identifying pharmacological components of CHM formulas with activity against specific diseases. This approach may also be practical for solving other similarly complex problems. The algorithm is available at http://chm-fiefp.net/.

Abstract As a critical component of the tumour immune microenvironment (TIME), the resident microbiota promotes tumorigenesis across a variety of cancer types. Here, we integrated multiple types of omics data, including microbiome, transcriptome, and metabolome data, to investigate the functional role of intratumoral bacteria in gastric cancer (GC). The microbiome was used to categorize GC samples into six subtypes, and patients with a high abundance of Streptococcus or Pseudomonas had a markedly worse prognosis. Further assays revealed that Streptococcus anginosus (SA) promoted tumour cell proliferation and metastasis while suppressing the differentiation and infiltration of CD8+ T cells. However, antibiotic treatment significantly suppressed tumorigenesis in SA+ mice in vivo. We further demonstrated that the SA arginine pathway increased the abundance of ornithine, which may be a major contributor to reshaping of the TIME. Our findings demonstrated that SA, a novel risk factor, plays significant roles in the initiation and progression of GC, suggesting that SA might be a promising target for the diagnosis and treatment of GC.

Abstract Background Flower morphology is believed to be primarily shaped by the most important pollinators when more than one pollinating species visits the flowers. However, floral adaptation to the selection mediated by multiple pollinators has received little attention. The plant Stellera chamaejasme has evolved a pollination syndrome matching both lepidopteran and thrips. In this study, to test the relative importance of different pollinators to the plant’s reproductive success and clarify how phenotypic selection on floral traits relates to different functional groups of pollinators, we determined the relative contributions of different pollinating insects to plant reproductive fitness through pollinator manipulation experiments and investigated the associated phenotypic selection on floral traits. Results Lepidopterans and thrips had comparable contributions to the reproductive fitness of S. chamaejasme. Among lepidopterans, the fitness contribution was distinctly higher for moths than for butterflies. Corolla opening size (i.e., corolla entrance) was subject to positive directional selection mediated mainly by lepidopterans, with thrips exerting opposing directional selection for this trait. The significant correlational selection between tube length and corolla opening size suggested that thrips and lepidopteran pollinators favored either the broad-entranced short flowers or the narrow-entranced long flowers. Conclusions Most likely, a functionally integrated adaptation to accommodate a variety of pollinators led to the floral design of S. chamaejasme, which in turn contributed to the diversity of flowers. Clinical trial number Not applicable.

Abstract Ultrasonic detection has emerged as a rapid method for acquiring rock mass sound velocity and converting it into an elastic modulus parameter, a pivotal technique for investigating the in-situ mechanical properties of rock masses. Despite its significance, accurately deducing rock mass strength from elastic modulus remains a formidable challenge and a pressing issue in the realm of protorock parameter research. This study introduces an innovative artificial intelligence-driven methodology for transforming elastic modulus and strength parameters specific to coal measures through rigorous data analysis and experimental validation. By integrating two illustrative engineering cases, we explore the complexities of water inrush and floor heave issues encountered in tunnels traversing fault zones. The novel strength parameter calculation approach is benchmarked against previous studies, highlighting its superior advantages in terms of effectiveness and applicability. In essence, this research offers a comprehensive framework and practical workflow for translating in-situ acoustic parameter-derived elastic modulus into rock mass strength, serving as a valuable resource for future endeavors in mine water control research.

Abstract Conventional methods for identifying voltage sag sources are difficult to categorize accurately due to the complexity of transmission lines and the influence of noise. In order to solve the problem of difficulty in recognizing voltage sag sources of transmission lines under different locations, this paper proposes a new method for transmission line fault diagnosis based on modified wavelet denoising and multi‐location information convolution transformer. The improved wavelet denoising method proposed in this paper solves the problems of discontinuity and bias of the traditional wavelet denoising method, and is able to better reconstruct the original voltage signal in a strong noise environment. In addition, multi‐location information convolution transformer adopts a new model combining multi‐location information convolution and multi‐scale convolution transformer, which realizes the combination of global information and local context information capturing ability under multi‐location faults. This paper validates the method through simulation experiments and practical situations, and the results show that the method can well classify and identify the type and location of voltage sag sources in transmission lines.

Abstract Background Maladaptive illness perception and coping strategies have been linked to illness-related quality of life in patients with chronic diseases. However, the impact of illness perception and coping strategies on vision-related quality of life (VRQOL) in patients with diabetic retinopathy (DR), a significant microvascular complication of diabetes mellitus, remains unclear. This study aims to evaluate the associations among illness perception, coping styles, and VRQOL in Chinese patients with DR, and to explore the mediating role of coping styles in the relationship between illness perception and VRQOL. Methods This cross-sectional study included 303 adult Chinese with DR recruited from a general Grade-A tertiary hospital in Hunan, China. All participants completed clinical and demographic questionnaires. The Brief Illness Perception Questionnaire (BIPQ), the National Eye Institute 25-Item Visual Function Questionnaire (NEI-VFQ-25), and the Medical Coping Modes Questionnaire were respectively adopted to assess the illness perception, VRQOL and coping styles. The BIPQ total scores were converted to logit scores using Rasch analysis. The NEI-VFQ-25 composite scores were converted to estimated person measures based on Rasch analysis and the method of successive dichotomizations. The relationships among these variables were assessed through independent-sample t-test, one-way analysis of variance, correlation analyses and multiple linear regression analysis, while SPSS Process model and the bootstrap analysis were utilized to evaluate the mediating effect. Results Illness perception was positively correlated with resignation coping style (r = 0.33, P

Abstract Background This study explored the influence of type 2 diabetes and impaired glucose tolerance (IGT) on the risk of the multimorbidity cluster of cardiovascular disease (CVD) and cancer. Methods A total of 1629 participants in the Da Qing Diabetes Prevention Outcome Study were recruited in the present analysis, including normal glucose tolerance (NGT, N = 492), IGT (N = 540), and newly diagnosed type 2 diabetes (N = 597) groups. Cox proportional hazards analyses were performed to assess the relationship between NGT, IGT, and newly diagnosed type 2 diabetes and the risk of the multimorbidity cluster of CVD and cancer. Results The incidence rates for multimorbidity cluster CVD and cancer were 1.25, 3.17, and 3.23 per 1000 person-years in people with NGT, IGT, and the newly diagnosed type 2 diabetes groups, respectively, over 34-year follow-up. Cox analysis revealed that diabetes status (as time-dependent variable) was significantly associated with the subsequent increased risk of multimorbidity cluster of CVD and cancer compared with non-diabetes (hazard ratios [HR] = 2.55, 95% confidence interval [CI] 1.51–4.31) after adjustment of potential confounders. Similar analysis showed that this risk was significantly higher in the IGT and newly diagnosed type 2 diabetes groups compared with NGT, with HR of 3.28 (95% CI 1.83–5.87) and HR of 3.90 (95% CI 2.14–7.09), respectively. Whereas compared diabetes with IGT group, this risk was not significantly different. Conclusions Similar to newly diagnosed type 2 diabetes, IGT is significantly associated with an increased risk of the multimorbidity cluster of CVD and cancer compared with NGT. This finding highlights the urgent need for an active detection of IGT and effective prevention and management of diabetes.

Abstract This study investigated the corrosion and oxidation mechanism of the Cr-free Fe-40Ni-15Co superalloy with exposure to a tropical marine atmosphere for one year and a subsequent high temperature of 650 °C for 300 h. The degradation behavior of the samples was evaluated based on surface characterization and analysis. In the tropical marine atmospheres, the corrosion process of the Fe-40Ni-15Co superalloy presented an initial localized type after one month of exposure and gradually developed into uniform. The corrosion products were mainly comprised of Fe2O3 and NiO, suppressing the pitting process. During the high-temperature oxidation process, all samples presented super-parabolic oxidation kinetics. Except for the initial active oxidation due to salt deposits, the corrosion products after atmospheric exposure could significantly enhance the oxidation resistance at 650 °C. An explanation for the degradation mechanism of the Fe-40Ni-15Co superalloy was developed based on the synergistic effects of atmospheric corrosion and high-temperature oxidation.

Introduction: Investigation on virus-host interaction may provide new clues for antitumor immunotherapy. Case Presentation: In this case report, we describe an unusual case of B-cell non-Hodgkin lymphoma in an aged woman who recovered following SARS-COV-2 infection. We discuss the case and suggest that virus induced cross-reactivity against tumor account for the remission. Conclusion: Mapping epitope characteristics on B cell non-Hodgkin lymphoma antigen and on SARS-COV-2 antigen may provide much needed information for antigen based antitumor immune therapy in the future.

Abstract Assessing street walkability is a critical agenda in urban planning and multidisciplinary research, as it facilitates public health, community cohesion, and urban sustainability. Existing evaluation systems primarily focus on objective measurements, often neglecting subjective assessments and the diverse walking needs influenced by different urban spatial elements. This study addresses these gaps by constructing a comprehensive evaluation framework that integrates both subjective and objective dimensions, combining three neighbourhood indicators: Macro-Scale Index, Micro-Scale Index, and Street Walking Preferences Index. A normalization weighting method synthesizes these indicators into a comprehensive index. We applied this framework to assess the street environment within Beijing’s Fifth Ring Road. The empirical results demonstrate that: (1) The framework reliably reflects the distribution of walkability. (2) The three indicators show both similarities and differences, underscoring the need to consider the distinct roles of community and street-level elements and the interaction between subjective and objective dimensions. (3) In high-density cities with ring-road development patterns, the Macro-Scale Index closely aligns with the Comprehensive Index, demonstrating its accuracy in reflecting walkability. The proposed framework and findings offer new insights for street walkability research and theoretical support for developing more inclusive, sustainable and walkable cities.