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Abstract Potassium-ion batteries (KIBs) are emerging as a promising alternative technology to lithium-ion batteries (LIBs) due to their significantly reduced dependency on critical minerals. KIBs may also present an opportunity for superior fast-charging compared to LIBs, with significantly faster K-ion electrolyte transport properties already demonstrated. In the absence of a viable K-ion electrolyte, a full-cell KIB rate model in commercial cell formats is required to determine the fast-charging potential for KIBs. However, a thorough and accurate characterisation of the critical electrode material properties determining rate performance—the solid state diffusivity and exchange current density—has not yet been conducted for the leading KIB electrode materials. Here, we accurately characterise the effective solid state diffusivities and exchange current densities of the graphite negative electrode and potassium manganese hexacyanoferrate $${{{{\rm{K}}}}}_{2}{{{\rm{Mn}}}}[{{{\rm{Fe}}}}{({{{\rm{CN}}}})}_{6}]$$ K 2 Mn [ Fe ( CN ) 6 ] (KMF) positive electrode, through a combination of optimised material design and state-of-the-art analysis. Finally, we present a Doyle-Fuller-Newman model of a KIB full cell with realistic geometry and loadings, identifying the critical materials properties that limit their rate capability.

Abstract Methanogenic hydrocarbon degradation can be carried out by archaea that couple alkane oxidation directly to methanogenesis, or by syntrophic associations of bacteria with methanogenic archaea. However, metagenomic analyses of methanogenic environments have revealed other archaea with potential for alkane degradation but apparent inability to form methane, suggesting the existence of other modes of syntrophic hydrocarbon degradation. Here, we provide experimental evidence supporting the existence of a third mode of methanogenic degradation of hydrocarbons, mediated by syntrophic cooperation between archaeal partners. We collected sediment samples from a hot spring sediment in Tengchong, China, and enriched Hadarchaeota under methanogenic conditions at 60 °C, using hexadecane as substrate. We named the enriched archaeon Candidatus Melinoarchaeum fermentans DL9YTT1. We used 13C-substrate incubations, metagenomic, metatranscriptomic and metabolomic analyses to show that Ca. Melinoarchaeum uses alkyl-coenzyme M reductases (ACRs) to activate hexadecane via alkyl-CoM formation. Ca. Melinoarchaeum likely degrades alkanes to carbon dioxide, hydrogen and acetate, which can be used as substrates by hydrogenotrophic and acetoclastic methanogens such as Methanothermobacter and Methanothrix.

This paper addresses the problem of high-resolution imaging of shadowed multiple-targets with limited labeled data, by proposing a transfer-learning-based method for through-the-wall radar imaging. First, a generative adversarial sub-network is developed to facilitate the migration of labeled simulation data to measured data, overcoming the difficulty of generating labeled data. This method incorporates an attention mechanism, adaptive residual blocks, and a multi-scale discriminator to improve the quality of image migration. It also incorporates a structural consistency loss function to minimize perceptual differences between images. Finally, the labeled data are used to train the through-the-wall radar target-imaging sub-network, achieving high-resolution imaging of multiple targets through walls. Experimental results show that the proposed method effectively reduces discrepancies between simulated and obtained images, and generates pseudo-measured images with labels. It systematically addresses issues such as side/grating ghost interference, target image defocusing, and multi-target mutual interference, significantly improving the multi-target imaging quality of the through-the-wall radar. The imaging accuracy achieved is 98.24%, 90.97% and 55.17% for single, double, and triple-target scenarios, respectively. Compared with CycleGAN, the imaging accuracy for the corresponding scenarios is improved by 2.29%, 40.28% and 15.51%, respectively.

Abstract Background The endothelial-to-hematopoietic transition (EHT) process during definitive hematopoiesis is highly conserved in vertebrates. Stage-specific expression of transposable elements (TEs) has been detected during zebrafish EHT and may promote hematopoietic stem cell (HSC) formation by activating inflammatory signaling. However, little is known about how TEs contribute to the EHT process in human and mouse. Results We reconstructed the single-cell EHT trajectories of human and mouse and resolved the dynamic expression patterns of TEs during EHT. Most TEs presented a transient co-upregulation pattern along the conserved EHT trajectories, coinciding with the temporal relaxation of epigenetic silencing systems. TE products can be sensed by multiple pattern recognition receptors, triggering inflammatory signaling to facilitate HSC emergence. Interestingly, we observed that hypoxia-related signals were enriched in cells with higher TE expression. Furthermore, we constructed the hematopoietic cis-regulatory network of accessible TEs and identified potential TE-derived enhancers that may boost the expression of specific EHT marker genes. Conclusions Our study provides a systematic vision of how TEs are dynamically controlled to promote the hematopoietic fate decisions through transcriptional and cis-regulatory networks, and pre-train the immunity of nascent HSCs.

Abstract A key strategy for minimizing our reliance on precious metals is to increase the fraction of surface atoms and improve the metal-support interface. In this work, we employ a solvent/ligand/counterion-free method to deposit copper in the atomic form directly onto a nanotextured surface of graphitized carbon nanofibers (GNFs). Our results demonstrate that under these conditions, copper atoms coalesce into nanoparticles securely anchored to the graphitic step edges, limiting their growth to 2–5 nm. The resultant hybrid Cu/GNF material displays high selectivity in the CO2 reduction reaction (CO2RR) for formate production with a faradaic efficiency of ~94% at -0.38 V vs RHE and a high turnover frequency of 2.78 × 106 h-1. The Cu nanoparticles adhered to the graphitic step edges significantly enhance electron transfer to CO2. Long-term CO2RR tests coupled with atomic-scale elucidation of changes in Cu/GNF reveal nanoparticles coarsening, and a simultaneous increase in the fraction of single Cu atoms. These changes in the catalyst structure make the onset of the CO2 reduction potential more negative, leading to less formate production at -0.38 V vs RHE, correlating with a less efficient competition of CO2 with H2O for adsorption on single Cu atoms on the graphitic surfaces, revealed by density functional theory calculations.

Abstract Background & aims Pyogenic liver abscess (PLA) is a common hepatobiliary infection that has been shown to have an increasing incidence, with biliary surgery being identified as a trigger. Our aim was to investigate the clinical characteristics and treatments of PLA patients with and without a history of biliary surgery (BS). Methods The study included a total of 353 patients with PLA who received treatment at our hospital between January 2014 and February 2023. These patients were categorized into two groups: the BS group (n = 91) and the non-BS group (n = 262). In the BS group, according to the anastomosis method, they were further divided into bilioenteric anastomoses group (BEA, n = 22) and non-bilioenteric anastomoses group (non-BEA, n = 69). Clinical characteristics were recorded and analyzed. Results The percentage of PLA patients with BS history was 25.78%. The BS group exhibited elevated levels of TBIL and activated APTT abnormalities (P = 0.009 and P = 0.041, respectively). Within the BS group, the BEA subgroup had a higher prevalence of diabetes mellitus (P

Abstract Background Our previous study found that crude polysaccharide extracted from Sargassum fusiforme (PSF) exhibited excellent anti-photoaging activity, but the composition responsible for this activity remained unknown. Results In this study, three fractions (P1, P2 and P3) obtained by hot water extraction and column chromatographic separation from PSF were structurally characterized. The anti-photoaging activities of these isolated polysaccharides were evaluated using HaCaT cells. The results showed that P1, P2 and P3 were acidic polysaccharides with 42.94%, 40.75% and 2.21% uronic acid. In addition, the contents of sulfate groups were 3.01%, 10.05% and 7.44%, respectively. Moreover, their content of reducing sugar was low, and none of the fractions had a triple-stranded helical structure. P1 had the largest average molecular weight of 208.89 kDa, while P2 and P3 had a relatively lower molecular weight of 154.09 and 151.71 kDa, respectively. Treatment with P2 effectively safeguarded the viability of HaCaT cells exposed to UVB irradiation. Additionally, it inhibited the secretion of MMP-1 and MMP-3 while elevating the content of hydroxyproline (HYP) in the cell supernatant. Methylation and NMR analysis suggested the main structure of P2 might be → [4)-β-ManA-(1]23 → 4)-β-ManA-(1 → 3)-β-d-Glcp-(1 → 4)-β-d-Glcp-(1 → 4)-β-d-Glcp-(1 → . The two terminal groups of β-ManA-(1 → and β-d-Glcp-(1 → were connected via the glycosidic bonds of → 3, 4)-O-3 in β-ManA-(1 → and O-6 in → 4, 6)-β-d-Glcp-(1 → , respectively. Conclusions These findings will open new avenues for exploring the potential use of Sargassum fusiforme polysaccharide, particularly P2, as a functional ingredient with anti-photoaging activity. Graphical Abstract

Abstract Ultralight dark photons constitute a well-motivated candidate for dark matter. A coherent electromagnetic wave is expected to be induced by dark photons when coupled with Standard-Model photons through kinetic mixing mechanism, and should be spatially correlated within the de Broglie wavelength of dark photons. Here we report the first search for correlated dark-photon signals using a long-baseline network of 15 atomic magnetometers, which are situated in two separated meter-scale shield rooms with a distance of about 1700 km. Both the network’s multiple sensors and the shields large size significantly enhance the expected dark-photon electromagnetic signals, and long-baseline measurements confidently reduce many local noise sources. Using this network, we constrain the kinetic mixing coefficient of dark photon dark matter over the mass range 4.1 feV-2.1 peV, which represents the most stringent constraints derived from any terrestrial experiments operating over the aforementioned mass range. Our prospect indicates that future data releases may go beyond the astrophysical constraints from the cosmic microwave background and the plasma heating.

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China. Presently, most remote sensing process models use the “biomass×harvest index (HI)” method to simulate regional-scale winter wheat yield. However, spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale. Time-series dry matter partition coefficients (Fr) can dynamically reflect the dry matter partition of winter wheat. In this study, Fr equations were fitted for each organ of winter wheat using site-scale data. These equations were then coupled into a process-based and remote sensing-driven crop yield model for wheat (PRYM-Wheat) to improve the regional simulation of winter wheat yield over the North China Plain (NCP). The improved PRYM-Wheat model integrated with the fitted Fr equations (PRYM-Wheat-Fr) was validated using data obtained from provincial yearbooks. A 3-year (2000–2002) averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination (R²=0.55) and lower root mean square error (RMSE=0.94 t ha–1) than PRYM-Wheat with a stable HI (abbreviated as PRYM-Wheat-HI), which had R² and RMSE values of 0.30 and 1.62 t ha–1, respectively. The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years (2013–2015). In conclusion, the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model, making it a useful tool for the simulation of regional winter wheat yield.

ABSTRACT: This experiment was conducted to investigate the effects of mulberry leaf extract (MLE) on alleviating fatty liver hemorrhagic syndrome (FLHS) in laying hens. The 576 Jing Fen laying hens of 56 weeks of age with good health and similar weights (1.76 ± 0.17 kg) were randomly divided into 6 groups, with 8 replicates in each group and 12 chickens in each replicate. The experiment lasted 56 d. The control group was fed a corn-soybean meal diet. The FLHS group was fed a high energy-low protein (HELP) diet, and the other four experimental groups were fed HELP diets supplemented with 0.04, 0.40, 0.80, and 1.20% MLE, respectively. The results showed that HELP treatment significantly induced liver injury, which indicated that the FLHS model was successfully established. MLE supplementation could alleviate the FLHS by reducing the liver index, abdominal fat percentage, total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL) in the serum (P < 0.05), and subsequently increase the egg production rate (P < 0.05). The laying hens fed 0.8% MLE exhibited the greatest production performance (P < 0.05) and could improve serum lipid levels. In addition, the genes associated with fatty acid synthesis (ACC, HMGR and SREBP-1C) were downregulated (P < 0.05), and genes related to fatty acid oxidation (CPT1A, AMPK, and ATGL) were found to be upregulated (P < 0.05). Supplementation with 1.2% MLE significantly reduced the relative abundance of Firmicutes and Desulfurized Bacillus (P < 0.05) and significantly increased the relative abundance of Fecal Bacillus (P < 0.05). In conclusion, MLE may regulate the mRNA expression of lipid metabolism-related genes through the AMPK signaling pathway and improve cecal microbiota balance and serum lipid levels to alleviate FLHS in laying hens and subsequently improve egg production performance.

Heterosigma akashiwo is a harmful algal bloom species that causes significant detrimental effects on marine ecosystems worldwide. The algicidal bacterium Pseudalteromonas sp. LD-B1 has demonstrated potential effectiveness in mitigating these blooms. However, the molecular mechanisms underlying LD-B1’s inhibitory effects on H. akashiwo remain poorly understood. In this study, we employed the comprehensive methodology, including morphological observation, assessment of photosynthetic efficiency (Fv/Fm), and transcriptomic analysis, to investigate the response of H. akashiwo to LD-B1. Exposure to LD-B1 resulted in a rapid decline of H. akashiwo's Fv/Fm ratio, with cells transitioning to a rounded shape within 2 hours, subsequently undergoing structural collapse and cytoplasmic leakage. Transcriptomic data revealed sustained downregulation of photosynthetic genes, indicating impaired functionality of the photosynthetic system. Additionally, genes related to the respiratory electron transfer chain and antioxidant defenses were consistently downregulated, suggesting prolonged oxidative stress beyond the cellular antioxidative capacity. Notably, upregulation of autophagy-related genes was observed, indicating autophagic responses in the algal cells. This study elucidates the molecular basis of LD-B1's algicidal effects on H. akashiwo, advancing our understanding of algicidal mechanisms and contributing to the development of effective strategies for controlling harmful algal blooms.

Objective The mechanisms of intervertebral disc degeneration (IVDD) in low back pain (LBP) patients are multiples. In this study, we attempt to investigate whether melatonergic system plays a potential role in IVDD patients with LBP by analyzing their clinical specimens. The fucus will be given to the correlation between the melatonin receptor expression and intervertebral disc tissue apoptosis. Methods In this clinical study, 107 lumbar intervertebral disc nucleus pulposus (NP) specimens from patients with LBP were collected with patients’ consents. The disc height (DH) discrepancy ratio, range of motion and sagittal parameters of the pathological plane were measured and Pfirrmann grade was used to classified the grades of IVDD level. Discs at grades 1–3 were served as normal control and grades 4–5 were considered as IVDD. The expression levels of melatonin receptor 1A (MT1) and 1B (MT2) were measured by immunohistochemistry. The apoptosis of NP was assessed using TUNEL staining. Their potential associations among MT1/2, DH, apoptosis, sagittal parameters with IVDD and LBP were evaluated with statistical analysis. Results The incidence of IVDD was positively associated with age and negatively related to VAS scores for LBP (p

BackgroundThe protective role of gut microbiota and its metabolites against intestinal damage in sepsis patients remain unclear.MethodsFecal samples were acquired from patients categorized into sepsis and non-sepsis groups for analysis of microbial composition via 16S rRNA sequencing and untargeted metabolomics analysis. We assessed the impact of gut microbiota from sepsis patients on intestinal barriers in antibiotic-treated mice. Furthermore, We conducted spearman’s correlation analysis to examine the relationship between metabolites and the severity of sepsis. Additionally, we performed animal experiments to validate the functionality of identified metabolites.ResultsThe diversity of intestinal flora is decreased in patients with sepsis compared to the control group. Through fecal microbiota transplantation experiments, it was discovered that the gut microbiota derived from sepsis patients could induce intestinal damage in antibiotic-treated mice. Metabolomics analysis of the microbiota revealed a significant enrichment of the Valine, leucine, and isoleucine biosynthesis pathway. Further analysis showed a significant decrease in the abundance of L-valine in sepsis patients, which was negatively correlated with APACHE-II and SOFA scores. In sepsis mouse experiments, it was found that L-valine could alleviate sepsis-induced intestinal damage.ConclusionAlterations in microbial and metabolic features in the gut can affect the severity of sepsis. Furthermore, L-valine can protect against sepsis-induced intestinal injury.

Diabetic cardiomyopathy (DCM) is a major complication of diabetes and is characterized by left ventricular dysfunction. Currently, there is a lack of effective treatments for DCM. Ubiquitin-specific protease 7 (USP7) plays a key role in various diseases. However, whether USP7 is involved in DCM has not been established. In this study, we demonstrated that USP7 was upregulated in diabetic mouse hearts and NMCMs co-treated with HG+PA or H9c2 cells treated with PA. Abnormalities in diabetic heart morphology and function were reversed by USP7 silencing through conditional gene knockout or chemical inhibition. Proteomic analysis coupled with biochemical validation confirmed that PCG1β was one of the direct protein substrates of USP7 and aggravated myocardial damage through coactivation of the PPARα signaling pathway. USP7 silencing restored the expression of fatty acid metabolism-related proteins and restored mitochondrial homeostasis by inhibiting mitochondrial fission and promoting fusion events. Similar effects were also observed in vitro. Our data demonstrated that USP7 promoted cardiometabolic metabolism disorders and mitochondrial homeostasis dysfunction via stabilizing PCG1β and suggested that silencing USP7 may be a therapeutic strategy for DCM.

Abstract An understanding of the mechanisms regulating embryonic hematopoietic stem cell (HSC) development would facilitate their regeneration. The aorta-gonad-mesonephros region is the site for HSC production from hemogenic endothelial cells (HEC). While several distinct regulators are involved in this process, it is not yet known whether macroautophagy (autophagy) plays a role in hematopoiesis in the pre-liver stage. Here, we show that different states of autophagy exist in hematopoietic precursors and correlate with hematopoietic potential based on the LC3-RFP-EGFP mouse model. Deficiency of autophagy-related gene 5 (Atg5) specifically in endothelial cells disrupts endothelial to hematopoietic transition (EHT), by blocking the autophagic process. Using combined approaches, including single-cell RNA-sequencing (scRNA-seq), we have confirmed that Atg5 deletion interrupts developmental temporal order of EHT to further affect the pre-HSC I maturation, and that autophagy influences hemogenic potential of HEC and the formation of pre-HSC I likely via the nucleolin pathway. These findings demonstrate a role for autophagy in the formation/maturation of hematopoietic precursors.

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

Abstract Ageing exhibits common and distinct features in various tissues, making it critical to decipher the tissue-specific ageing mechanisms. MiRNAs are essential regulators in ageing and are recently highlighted as a class of intercellular messengers. However, little is known about the tissue-specific transcriptomic changes of miRNAs during ageing. C. elegans is a well-established model organism in ageing research. Here, we profile the age-dependent miRNAomic changes in five isolated worm tissues. Besides the diverse ageing-regulated miRNA expression across tissues, we discover numerous miRNAs in the tissues without their transcription. We further profile miRNAs in the extracellular vesicles and find that worm miRNAs undergo inter-tissue trafficking via these vesicles in an age-dependent manner. Using these datasets, we uncover the interaction between body wall muscle-derived mir-1 and DAF-16/FOXO in the intestine, suggesting mir-1 as a messenger in inter-tissue signalling. Taken together, we systematically investigate worm miRNAs in the somatic tissues and extracellular vesicles during ageing, providing a valuable resource to study tissue-autonomous and nonautonomous functions of miRNAs in ageing.

Abstract Background Oils are important sources of energy in pig diets. The combination of oils with different degree of saturation contributes to improve the utilization efficiency of the mixed oils and may reduce the cost of oil supplemented. An experiment was conducted to evaluate the effects of oils with different degree of saturation on the fat digestibility and corresponding additivity and bacterial community in growing pigs. Methods Eighteen crossbred (Duroc × Landrace × Yorkshire) barrows (initial body weight: 29.3 ± 2.8 kg) were surgically fitted with a T-cannula in the distal ileum. The experimental diets included a fat-free basal diet and 5 oil-added diets. The 5 oil-added diets were formulated by adding 6% oil with different ratio of unsaturated to saturated fatty acids (U:S) to the basal diet. The 5 oils were palm oil (U:S = 1.2), canola oil (U:S = 12.0), and palm oil and canola oil were mixed in different proportions to prepare a combination of U:S of 2.5, 3.5 and 4.5, respectively. Results The apparent and standardized ileal digestibility (AID and SID) of fat and fatty acids increased linearly (P

Subgroup 4 (Sg4) members of the R2R3-MYB are generally known as negative regulators of the phenylpropanoid pathway in plants. Our previous research showed that a R2R3-MYB Sg4 member from Camellia sinensis (CsMYB4a) inhibits expression of some genes in the phenylpropanoid pathway, but its physiological function in the tea plant remained unknown. Here, CsMYB4a was found to be highly expressed in anther and filaments, and participated in regulating filament growth. Transcriptome analysis and exogenous auxin treatment showed that the target of CsMYB4a might be the auxin signal pathway. Auxin/indole-3-acetic acid 4 (AUX/IAA4), a repressor in auxin signal transduction, was detected from a yeast two-hybrid screen using CsMYB4a as bait. Gene silencing assays showed that both CsIAA4 and CsMYB4a regulate filament growth. Tobacco plants overexpressing CsIAA4 were insensitive to exogenous α-NAA, consistent with overexpression of CsMYB4a. Protein-protein interaction experiments revealed that CsMYB4a interacts with N-terminal of CsIAA4 to prevent CsIAA4 degradation. Knock out of the endogenous NtIAA4 gene, a CsIAA4 homolog, in tobacco alleviated filament growth inhibition and α-NAA insensitivity in plants overexpressing CsMYB4a. All results strongly suggest that CsMYB4a works synergistically with CsIAA4 and participates in regulation of the auxin pathway in stamen.

Abstract The devastating impact of youth mental health concerns is increasingly evident on a global scale. This crisis calls for innovative solutions that are sufficiently accessible, scalable, and cost-effective to support diverse communities around the world. One such solution involves engagement in the arts: incorporating and building upon existing local resources and cultural practices to bolster youth mental health. In this article, we describe the global youth mental health crisis and note major gaps in the knowledge and resources needed to address it. We then discuss the potential for arts- and culture-based strategies to help meet this challenge, review the mounting evidence regarding art’s ability to support mental health, and call for action to undertake critical research and its translation into accessible community practices. Four steps are suggested: (1) elevate and prioritize youth voice, (2) develop core outcome measures, (3) identify and analyze successful models around the globe, and (4) generate clear funding pathways for research and translational efforts. Worldwide implementation of arts- and culture-based strategies to address youth mental health will provide critical resources to support the health, wellbeing and flourishing of countless youth across the globe.

Dihedral is a common structure in polarimetric SAR images and can be found on many man-made targets. Many researchers have proposed different dihedral models, but the accuracy of these models is limited. In this case, the feature extraction methods based on these models are also not effective enough, which affects the subsequent applications such as target detection. Therefore, it is necessary to propose a new and accurate scattering model, which can be applied to dihedral with different orientation angles for feature extraction and target detection. In this article, a general scattering model called modified oriented dihedral scattering model (MODM) is proposed based on physical optics and geometric optics of high-frequency approximation techniques. By analyzing the propagation and reflection of electromagnetic wave, MODM can accurately describe the scattering characteristic of dihedral for all observation conditions. In order to apply the model to real polarimetric synthetic aperture radar images, MODM is introduced into a new feature extraction method, which is called five-scattering component polarimetric decomposition method (MODM-5SD). Feature extraction and target detection experiments of buildings with various oriented dihedral structures are performed using different datasets, which show that dihedral scattering components from oriented dihedral structures can be more effectively extracted by MODM-5SD. In addition, more buildings with oriented dihedral structures can be detected with the features from MODM-5SD. The experimental results show that MODM can more accurately describe the scattering characteristic of dihedral, which can be further applied for scattering characterization and feature extraction of targets with typical dihedral structures.

Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient. In this study, a one-tube dual recombinase polymerase amplification (RPA) reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay, named ''Dual-RPA-LFD'', to visualize the dual detection of genetically modified (GM) crops. In which, the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits. Gradient diluted plasmids, transgenic standards, and actual samples were used as templates to conduct sensitivity, specificity, and practicality assays, respectively. The constructed method achieved the visual detection of plasmid at levels as low as 100 copies, demonstrating its high sensitivity. In addition, good applicability to transgenic samples was observed, with no cross-interference between two test lines and no influence from other genes. In conclusion, this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37 ℃ in a rapid, equipment-free field manner, providing a new alternative for rapid screening for transgenic assays in the field.

The value of Baijiu is affected by its flavor, age, and adulteration. Therefore, a simple and rapid identification method is crucial for the market. In this study, we present a rapid, non-intrusive identification technique for Baijiu utilizing the Tyndall effect combined with chemometrics analysis. Our experiment begins illuminating Baijiu with a 405 nm wavelength laser and recording the resulting bright light path due to the Tyndall effect. To further analyze the color and brightness information, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Hierarchical Cluster Analysis (HCA), and Multilayer Perceptron (MLP) were employed. This study establishes correlations between the brightness of the Tyndall light path and seven trace flavor compounds in Baijiu. The findings demonstrate that this method effectively identifies the flavor, age cellar, and adulteration of Baijiu and also quantitatively detects the concentrations of flavor compounds. Additionally, an analysis platform was developed to enable the rapid identification of Baijiu.

BackgroundThe increasing prevalence of fungal infections necessitates broader use of antifungal medications. However, the prevalence of adverse drug events (ADEs) restricts their clinical application. This study aimed to develop a reliable ADEs trigger for antifungals to enable proactive ADEs monitoring, serving as a reference for ADEs prevention and control.MethodsThis investigation comprises two phases. Initially, the trigger was established via a literature review, extraction of relevant items, and refinement through Delphi expert consultation. Subsequently, the validity of the trigger was assessed by analyzing hospital records of antifungal drug users from 1 January 2019 to 31 December 2020. The correlation between each trigger signal and ADEs occurrence was examined, and the sensitivity and specificity of the trigger were evaluated through the spontaneous reporting system (SRS) and Global Trigger Tool (GTT). Additionally, risk factors contributing to adverse drug events (ADEs) resulting from antifungal use were analyzed. Results: Twenty-one preliminary triggers were refined into 21 final triggers after one expert round. In the retrospective analysis, the positive trigger rate was 65.83%, with a positive predictive value (PPV) of 28.75%. The incidence of ADEs in inpatients was 28.75%, equating to 44.58 ADEs per 100 admissions and 33.04 ADEs per 1,000 patient days. Predominant ADEs categories included metabolic disturbances, gastrointestinal damage, and skin rashes. ADEs severity was classified into 36 cases at grade 1, 160 at grade 2, and 18 at grade 3. The likelihood of ADEs increased with longer stays, more positive triggers, and greater comorbidity counts.ConclusionThis study underscores the effectiveness of the GTT in enhancing ADEs detection during antifungal medication use, thereby confirming its value as a monitoring tool.

IntroductionMorchella esculenta is a popular edible fungus with high economic and nutritional value. However, the rot disease caused by Lecanicillium aphanocladii, pose a serious threat to the quality and yield of M. esculenta. Biological control is one of the effective ways to control fungal diseases.Methods and resultsIn this study, an effective endophytic B. subtilis A9 for the control of M. esculenta rot disease was screened, and its biocontrol mechanism was studied by transcriptome analysis. In total, 122 strains of endophytic bacteria from M. esculenta, of which the antagonistic effect of Bacillus subtilis A9 on L. aphanocladii G1 reached 72.2% in vitro tests. Biological characteristics and genomic features of B. subtilis A9 were analyzed, and key antibiotic gene clusters were detected. Scanning electron microscope (SEM) observation showed that B. subtilis A9 affected the mycelium and spores of L. aphanocladii G1. In field experiments, the biological control effect of B. subtilis A9 reached to 62.5%. Furthermore, the transcritome profiling provides evidence of B. subtilis A9 bicontrol at the molecular level. A total of 1,246 differentially expressed genes (DEGs) were identified between the treatment and control group. Gene Ontology (GO) enrichment analysis showed that a large number of DEGs were related to antioxidant activity related. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the main pathways were Nitrogen metabolism, Pentose Phosphate Pathway (PPP) and Mitogen-Activated Protein Kinases (MAPK) signal pathway. Among them, some important genes such as carbonic anhydrase CA (H6S33_007248), catalase CAT (H6S33_001409), tRNA dihydrouridine synthase DusB (H6S33_001297) and NAD(P)-binding protein NAD(P) BP (H6S33_000823) were found. Furthermore, B. subtilis A9 considerably enhanced the M. esculenta activity of Polyphenol oxidase (POD), Superoxide dismutase (SOD), Phenylal anineammonia lyase (PAL) and Catalase (CAT).ConclusionThis study presents the innovative utilization of B. subtilis A9, for effectively controlling M. esculenta rot disease. This will lay a foundation for biological control in Morchella, which may lead to the improvement of new biocontrol agents for production.

BackgroundChat Generative Pre-trained Transformer (ChatGPT) is a new machine learning tool that allows patients to access health information online, specifically compared to Google, the most commonly used search engine in the United States. Patients can use ChatGPT to better understand medical issues. This study compared the two search engines based on: (i) frequently asked questions (FAQs) about Femoroacetabular Impingement Syndrome (FAI), (ii) the corresponding answers to these FAQs, and (iii) the most FAQs yielding a numerical response.PurposeTo assess the suitability of ChatGPT as an online health information resource for patients by replicating their internet searches.Study designCross-sectional study.MethodsThe same keywords were used to search the 10 most common questions about FAI on both Google and ChatGPT. The responses from both search engines were recorded and analyzed.ResultsOf the 20 questions, 8 (40%) were similar. Among the 10 questions searched on Google, 7 were provided by a medical practice. For numerical questions, there was a notable difference in answers between Google and ChatGPT for 3 out of the top 5 most common questions (60%). Expert evaluation indicated that 67.5% of experts were satisfied or highly satisfied with the accuracy of ChatGPT’s descriptions of both conservative and surgical treatment options for FAI. Additionally, 62.5% of experts were satisfied or highly satisfied with the safety of the information provided. Regarding the etiology of FAI, including cam and pincer impingements, 52.5% of experts expressed satisfaction or high satisfaction with ChatGPT’s explanations. Overall, 62.5% of experts affirmed that ChatGPT could serve effectively as a reliable medical resource for initial information retrieval.ConclusionThis study confirms that ChatGPT, despite being a new tool, shows significant potential as a supplementary resource for health information on FAI. Expert evaluations commend its capacity to provide accurate and comprehensive responses, valued by medical professionals for relevance and safety. Nonetheless, continuous improvements in its medical content’s depth and precision are recommended for ongoing reliability. While ChatGPT offers a promising alternative to traditional search engines, meticulous validation is imperative before it can be fully embraced as a trusted medical resource.

ABSTRACT: This study aimed to systematically determined the effect of 28 h ahemeral light cycle on production performance, egg quality, blood parameters, uterine morphological characteristics, and gene expression of hens during the late laying period. At 74 wk, 260 Hy-Line Brown layers were randomly divided into 2 groups of 130 birds each and in duplicates. Both a regular (16L:8D) and an ahemeral light cycle (16L:12D) were provided to the hens. The oviposition pattern in an ahemeral cycle shifted into darkness, with oviposition mostly occurring 3 to 5 h after light out. Production performance was unaffected by light cycle (P > 0.05). Nonetheless, compared to the normal group, the ahemeral group exhibited increased egg weight, eggshell weight, eggshell percentage, yolk percentage, eggshell thickness, and eggshell strength (P < 0.05). There were rhythmic changes in the uterine morphological structure in both cycles, however, the ahemeral group maintained a longer duration and had more uterine folds than the normal group. In the ahemeral cycle, the phases of the CLOCK and PER2 genes were phase-advanced for 3.96 h and 4.54 h compared to the normal cycle. The PHLPP1 gene, which controls clock resetting, exhibited a substantial oscillated rhythm in the ahemeral group (P < 0.05), while the expression of genes presenting biological rhythm, such as CRY2 and FBXL3, was rhythmically oscillated in normal cycle (P < 0.05). The ITPR2 gene, which regulates intracellular Ca2+ transport, displayed a significant oscillated rhythm in ahemeral alone (P < 0.05), while the CA2 gene, which presents biomineralization, rhythmically oscillated in both cycles (P < 0.05). The ahemeral cycle caused 2.5 h phase delays in the CA2 gene compared to the normal cycle. In conclusion, the 28 h ahemeral light cycle preserved the high condition of the uterine folds and changed the uterine rhythms of CLOCK, PER2, ITPR2, and CA2 gene expression to improve ion transport and uterine biomineralization.

Non-alcoholic fatty liver disease (NAFLD), a complex liver disorder that can result in non-alcoholic steatohepatitis, cirrhosis, and liver cancer, is the accumulation of fat in the liver seen in people due to metabolic dysfunction. The pathophysiology of NAFLD is influenced by several variables, such as metabolic dysregulation, oxidative stress, inflammation, and genetic susceptibility. This illness seriously threatens global health because of its link to obesity, insulin resistance, type 2 diabetes, and other metabolic disorders. In recent years, lipid–NAFLD crosstalk has drawn a lot of interest. Through numerous methods, lipids have been connected to the onset and advancement of the illness. The connection between lipids and NAFLD is the main topic of the current review, along with the various therapeutic targets and currently available drugs. The importance of hepatic lipid metabolism in the progression of NAFLD is summarized with the latest results in the field.

The prediction of long non-coding RNA (lncRNA) subcellular localization is essential to the understanding of its function and involvement in cellular regulation. Traditional biological experimental methods are costly and time-consuming, making computational methods the preferred approach for predicting lncRNA subcellular localization (LSL). However, existing computational methods have limitations due to the structural characteristics of lncRNAs and the uneven distribution of data across subcellular compartments. We propose a discrete wavelet transform (DWT)-based model for predicting LSL, called DlncRNALoc. We construct a physicochemical property matrix of a 2-tuple bases based on lncRNA sequences, and we introduce a DWT lncRNA feature extraction method. We use the Synthetic Minority Over-sampling Technique (SMOTE) for oversampling and the local fisher discriminant analysis (LFDA) algorithm to optimize feature information. The optimized feature vectors are fed into support vector machine (SVM) to construct a predictive model. DlncRNALoc has been applied for a five-fold cross-validation on the three sets of benchmark datasets. Extensive experiments have demonstrated the superiority and effectiveness of the DlncRNALoc model in predicting LSL.

Abstract The accuracy and reliability of hydrodynamic models are sensitive to both hydraulic state variables and model parameters, particularly the bed roughness, while their simultaneous real-time corrections and corresponding effects still need to be well-established and understood. This paper presents a real-time data assimilation model that corrects channel-bed roughness and water level in a river network hydrodynamic model, ensuring its accuracy and reliability. Experiments and parameter analysis evaluated the effect of initial roughness and observation noise level on model performance. Correcting both roughness and water level improved filtering time and forecasting accuracy by up to 63% and 80%, respectively, compared to methods only correcting water level. The filtering time was reduced by 44–63%, and the water level forecasting RMSE decreased by up to 80%. Both models experienced increased filtering time and forecasting error as observation noise increased, but the proposed model had a lower increase. With accurate hydraulic state measurement (e.g., 0.005 m error), the model achieved negligible water level forecasting error after 7 h of data assimilation. The model's accuracy depended on the initial channel-bed roughness, and the algorithm enables real-time roughness correction, making it useful for flood forecasting.

The benzofuran core inhibitors HCV-796, BMS-929075, MK-8876, compound 2, and compound 9B exhibit good pan-genotypic activity against various genotypes of NS5B polymerase. To elucidate their mechanism of action, multiple molecular simulation methods were used to investigate the complex systems of these inhibitors binding to GT1a, 1b, 2a, and 2b NS5B polymerases. The calculation results indicated that these five inhibitors can not only interact with the residues in the palm II subdomain of NS5B polymerase, but also with the residues in the palm I subdomain or the palm I/III overlap region. Interestingly, the binding of inhibitors with longer substituents at the C5 position (BMS-929075, MK-8876, compound 2, and compound 9B) to the GT1a and 2b NS5B polymerases exhibits different binding patterns compared to the binding to the GT1b and 2a NS5B polymerases. The interactions between the para-fluorophenyl groups at the C2 positions of the inhibitors and the residues at the binding pockets, together with the interactions between the substituents at the C5 positions and the residues at the reverse β-fold (residues 441–456), play a key role in recognition and the induction of the binding. The relevant studies could provide valuable information for further research and development of novel anti-HCV benzofuran core pan-genotypic inhibitors.

Vehicle re-identification employs computer vision to determine the presence of specific vehicles in images or video sequences, often using vehicle appearance for identification due to the challenge of capturing complete license plate information. Addressing the performance issues caused by fog, such as image blur and loss of key positional information, this paper introduces a multi-task learning framework incorporating a multi-scale fusion defogging method (MsF). This method effectively mitigates image blur to produce clearer images, which are then processed by the re-identification branch. Additionally, a phase attention mechanism is introduced to adaptively preserve crucial details. Utilizing advanced artificial intelligence techniques and deep learning algorithms, the framework is evaluated on both synthetic and real datasets, showing significant improvements in mean average precision (mAP)—an increase of 2.5% to 87.8% on the synthetic dataset and 1.4% to 84.1% on the real dataset. These enhancements demonstrate the method’s superior performance over the semi-supervised joint defogging learning (SJDL) model, particularly under challenging foggy conditions, thus enhancing vehicle re-identification accuracy and deepening the understanding of applying multi-task learning frameworks in adverse visual environments.

PurposeThe objective of this study was to investigate the accumulation of 18F-fluorodeoxyglucose (18F-FDG) in the whole brain between Alzheimer’s disease (AD) with depressive (ADD) symptoms compared with AD without depressive (ADND) symptoms using positron emission tomography/magnetic resonance imaging (PET/MRI). Additionally, this study aimed to explore the associations among the accumulation of 18F-FDG in the brain, depressive symptoms, and cognitive function in ADD patients.MethodsIn this study, 25 AD patients and 22 healthy controls were enrolled. The AD patients were stratified into two groups, namely ADD and ADND, based on their scores of the Hamilton Depression Scale (HAMD). Both AD patients and healthy controls underwent an 18F-FDG PET/MRI scan. A standardized uptake value ratio (SUVR) was calculated to examine the accumulation of 18F-FDG in the brain. A simple mediation model was employed to examine the mediation effect between SUVR, depressive symptoms and cognitive function in ADD patients.ResultsThe ADD group exhibited significant cognitive impairment compared to the ADND group (p

The variation of temperature modifies the magnetic behavior of ferromagnetic cores which may affect the performance of electrical equipment. Therefore, it is imperative to develop a temperature-dependent hysteresis model to precisely calculate electromagnetic characteristics of electrical equipment. In this paper, a Temporal Convolutional Network (TCN) in combination with the Play operator is developed. The proposed model incorporates the temperature-dependent spontaneous magnetization intensity as the model input to introduce the temperature effect. To enhance the accuracy of model training outcomes, the Bayesian optimization approach for automatically selecting network model parameters is provided. The results show that the proposed model can accurately predict the hysteresis characteristics of materials under varying temperature and frequency conditions.

Background Bipolar disorder is identified as a cause of severe damage to the physical, psychological and social functioning of adolescents and young adults.Aims The aim of this study is to ascertain the trends in the burden of bipolar disorder among individuals aged 10–24 years at global, regional and national levels from 1990 to 2019.Methods The data analysed in this study were from the Global Burden of Diseases 2019. The numbers, rates per 100 000 population, average annual percentage changes (AAPCs) of incidence, prevalence and years lived with disability (YLDs) of bipolar disorder are reported at the global, regional and national levels among individuals aged 10–24 years. Global trends by age, sex and Social Development Index (SDI) were further analysed.Results Globally, the incidence of bipolar disorder among adolescents and young adults increased from 79.21 per 100 000 population (95% uncertainty interval (UI): 58.13 to 105.15) in 1990 to 84.97 per 100 000 population (95% UI: 61.73 to 113.46) in 2019, AAPC 0.24 (95% confidence interval (CI): 0.22 to 0.26). In the past three decades, there has been an increase in incidence, prevalence and YLDs in both males and females. The largest increase in incidence between 1990 and 2019 was observed in those aged 20–24 years old (from 51.76 per 100 000 population (95% UI: 26.81 to 87.20) in 1990 to 58.37 per 100 000 population (95% UI: 30.39 to 98.55) in 2019; AAPC 0.42 (95% CI: 0.38 to 0.47)). By the SDI quintile, the largest increase in incidence was observed in the middle SDI; however, the high SDI countries had the highest incidence. Regionally, the largest increase in incidence was observed in southern Latin America. At the national level, the most pronounced increase in the incidence was in Greenland.Conclusions The global increase in incidence among adolescents and young adults between 1990 and 2019 indicates that strategies to improve their mental health still need to be emphasised.

Accurately extracting the Region of Interest (ROI) of a palm print was crucial for subsequent palm print recognition. However, under unconstrained environmental conditions, the user's palm posture and angle, as well as the background and lighting of the environment, were not controlled, making the extraction of the ROI of palm print a major challenge. In existing research methods, traditional ROI extraction methods relied on image segmentation and were difficult to apply to multiple datasets simultaneously under the aforementioned interference. However, deep learning-based methods typically did not consider the computational cost of the model and were difficult to apply to embedded devices. This article proposed a palm print ROI extraction method based on lightweight networks. Firstly, the YOLOv5-lite network was used to detect and preliminarily locate the palm, in order to eliminate most of the interference from complex backgrounds. Then, an improved UNet was used for keypoints detection. This network model reduced the number of parameters compared to the original UNet model, improved network performance, and accelerated network convergence. The output of this model combined Gaussian heatmap regression and direct regression and proposed a joint loss function based on JS loss and L2 loss for supervision. During the experiment, a mixed database consisting of 5 databases was used to meet the needs of practical applications. The results showed that the proposed method achieved an accuracy of 98.3% on the database, with an average detection time of only 28ms on the GPU, which was superior to other mainstream lightweight networks, and the model size was only 831k. In the open-set test, with a success rate of 93.4%, an average detection time of 5.95ms on the GPU, it was far ahead of the latest palm print ROI extraction algorithm and could be applied in practice.

In actual storage processes of rice, environment temperatures fluctuate rather than remain constant. Accumulated temperature is the sum of temperature during the storage period. In this research, six different temperature-varied conditions with two accumulated temperatures (low intensity: 7200°C⸱d; high intensity: 9000°C⸱d) were designed to store rice for 12 months and the stored rice samples were compared in quality. Three low-accumulated temperature conditions were set as follows: No. 4–15°C for 6 months followed by 25°C; No. 5–25°C for 6 months followed by 15°C; No. 8-alternating between 15°C and 25°C every 2 months. Similarly, three high-intensity conditions, No. 6, No. 7, and No. 9, were set with a temperature change from 25°C to 35°C. Three constant temperature conditions, No. 1, No. 2, and No. 3, with storage temperature of 15, 25, and 35°C, respectively, were used as controls. Under temperature-varied conditions, rice demonstrated a decline in germination rate (GR), catalase (CAT) and peroxidase (POD) activities, and an increase in fatty acid value (FAV) as storage time increased. After storage, rice exhibited higher water absorption rate (WAR) and volume expansion rate (VER), but reduced stickiness and sensory scores for appearance, taste and overall quality. Generally, three batches at high-accumulated temperature conditions had lower GR and sensory scores, and higher FAV, WAR, and VER compared to those under low-intensity conditions. Furthermore, variations in the sequence of temperature also affected quality parameters, even at the same accumulated temperature. These findings indicate that under temperature-varied conditions, increased accumulated temperature exacerbates rice deterioration, and different temperature sequences can influence quality at a given accumulated temperature.

Qingqiao Kangdu granule (QQKDG), a traditional Chinese medicine (TCM), has been used clinically to treat various viral diseases, including flu, mumps, and viral hepatitis, owing to its abundant bioactivities. Nevertheless, the chemical components of QQKDG have not been sufficiently elucidated; consequently, the development of standards for quality evaluation and complete understanding of the pharmacological mechanisms of action are hindered. Therefore, a systematic approach must be developed to efficiently discover novel compounds and advance pharmacological research. In this regard, this study proposed an integrated strategy for the comprehensive characterization of the chemical components in QQKDG by UHPLC-Q-Exactive-MS coupled with feature-based molecular networking (FBMN) to improve annotation accuracy and achieve visualization. First, the chromatographic and mass spectrum conditions were optimized to obtain good separation and abundant signal response. Subsequently, an in-house library was established by searching for relevant literature to improve annotation confidence. Finally, the raw data acquired under optimized conditions were uploaded to the FBMN to achieve component visualization by connecting precursor ions of the same color, in which compounds have similar structural features. Thus, a total of 231 compounds, including 89 flavonoids, 36 phenolic acids, 26 phenylethanoid glycosides, 23 coumarins, 17 chlorogenic acid derivatives, 14 terpenoids, 10 alkaloids, 10 lignans and 6 other compounds, were characterized, and numerous novel compounds with new structures were explored. Thus, this study provides a strategy for comprehensive characterization, which can also be applied to other TCMs.

Objective: To assess the relationship between optic disc microvasculature and renal function in subjects with diabetes mellitus without diabetic retinopathy (DR). Design: Prospective, cross-sectional study. Participants: A total 1629 patients with type 2 diabetes mellitus without DR were recruited from the community of Guangzhou, China. Methods: All subjects underwent 6 mm × 6 mm OCT angiography (OCTA) centered on the optic nerve head. Four state-of-the-art microcirculation parameters, including peripapillary vessel density (PVD) in the radial peripapillary capillaries (RPC), superficial capillary plexus, deep capillary plexus (DCP), and a choriocapillaris flow void density percentage (CC FVD%) were assessed via swept-source OCTA. Primary Outcomes: Renal function was assessed by levels of microalbuminuria (MAU) and estimated glomerular filtration rate (eGFR). Results: Compared with non-chronic kidney disease (CKD) participants, PVD was significantly lower in subjects in the CKD group and worsened as eGFR declined. After adjustment for covariates, higher eGFR was significantly associated with higher PVD in the RPC (β = 0.01; 95% confidence interval [CI], 0.01–0.02; P < 0.001), in the superficial capillary plexus (β = 0.010; 95% CI, 0.002–0.019; P = 0.020), in the DCP (β = 0.02; 95% CI, 0.01–0.03; P < 0.001), and lower CC FVD% (β = −0.01; 95% CI, −0.03 to −0.001; P = 0.040) in the entire images. After they were fully adjusted, the parameters in the inner ring of the RPC, DCP, and CC FVD% were significantly associated with MAU (P < 0.05). Conclusion: Decrease in retinal and choroidal microcirculation in the optic nerve head was independently associated with renal dysfunction. Further longitudinal studies are needed to clarify the peripapillary vessel changes during CKD progression. Financial Disclosure(s): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Abstract Background Uncut Roux-en-Y (URY) effectively alleviates the prevalent complexities connected with RY, such as Roux-en-Y stasis syndrome (RSS). Nevertheless, for gastric cancer (GC) patients, it is still controversial whether URY has an impact on long-term prognosis and whether it has fewer afferent loop recanalization. Therefore, compare whether URY and RY have differences in prognosis and long-term complications of GC patients undergoing totally laparoscopic gastrectomy (TLG). Methods We analyzed the data of patients who underwent TLG combined with digestive tract reconstruction from dual-center between 2016 and 2022. Only patients undergoing URY and RY were selected for analysis. Relapse-free survival (RFS) and overall survival (OS) were estimated. Bias between the groups was reduced by propensity score matching (PSM). The Cox proportional hazard regression model was used to further analyze the influence of URY on prognosis. Results Two hundred forty two GC patients were enrolled. The URY had significantly shorter operation time, liquid food intake time, and in-hospital stays than the RY (P

Abstract Gallstone disease is a prevalent biliary disease worldwide, and bacteria play vital roles in the disease development and progression, as well as the prognosis after endoscopic surgery. However, there have been limited studies to explore the key taxa involved. In this study, bile samples from healthy controls (HCs, liver donors without hepatobiliary disease) and three diseased groups, namely patients with gallbladder stones (GBS), patients with common bile duct stones (CBDS), and patients with stricture in the common bile duct (SCBD), were collected and analyzed. Bacterial community characterization based on 16S rRNA amplicon sequencing showed that bacterial diversities did not change significantly alongside gallstone disease development and progression. The predominant phyla in each group were Proteobacteria, Firmicutes, Bacteroidota, and Fusobacteriota, representing over 80% in abundance of the biliary bacteria community. Specifically, the abundance of Proteobacteria decreased greatly while that of Firmicutes and Bacteroidota increased greatly in the diseased groups when compared to that in HCs. Moreover, linear discriminant analysis identified several genera highly represented in the diseased groups. Among them, Klebsiella, Prevotella, Pseudomonas and Veillonella are persistent in both the HCs group and the diseased groups, indicating an enrichment of local bile bacteria in the diseased bile; while Lachnoanerobaculum, Atopobium, Oribacterium, and Stomatobaculum, those aligned to oral cavity taxa, are persistent in the diseased groups but are transient in the HCs group, and their abundances sequentially increased with the disease development and progression (HCs→GBS→CBDS→SCBD), implying a translocation and colonization of the oral cavity bacteria in the diseased bile. Moreover, co-occurrence network analysis revealed that bacterial infection (e.g., Photobacterium and Plesiomonas) from the intestine was developed during endoscopic surgery with reduced bile bacteria diversity. The results of this study revealed that the bile bacterial community is relatively stable and dominated by a few persistent taxa. Moreover, we hypothesized that translocation and colonization of specific bacteria from the oral cavity happens alongside gallstone disease development and progression, and bacterial infection from the intestinal tract results in poor outcomes after endoscopic surgery.

Abstract Metabolism vulnerability of cisplatin resistance in BCa cells remains to be discovered, which we applied integrated multi-omics analysis to elucidate the metabolism related regulation mechanism in bladder cancer (BCa) microenvironment. Integrated multi-omics analysis of metabolomics and proteomics revealed that MAT2A regulated methionine metabolism contributes to cisplatin resistance in BCa cells. We further validated MAT2A and cancer stem cell markers were up-regulated and circARHGAP10 was down-regulated through the regulation of MAT2A protein stability in cisplatin resistant BCa cells. circARHGAP10 formed a complex with MAT2A and TRIM25 to accelerate the degradation of MAT2A through ubiquitin-proteasome pathway. Knockdown of MAT2A through overexpression of circARHGAP10 and restriction of methionine up-take was sufficient to overcome cisplatin resistance in vivo in immuno-deficiency model but not in immuno-competent model. Tumor-infiltrating CD8+ T cells characterized an exhausted phenotype in tumors with low methionine. High expression of SLC7A6 in BCa negatively correlated with expression of CD8. Synergistic inhibition of MAT2A and SLC7A6 could overcome cisplatin resistance in immuno-competent model in vivo. Cisplatin resistant BCa cells rely on methionine for survival and stem cell renewal. circARHGAP10/TRIM25/MAT2A regulation pathway plays an important role in cisplatin resistant BCa cells while circARHGAP10 and SLC7A6 should be evaluated as one of the therapeutic target of cisplatin resistant BCa.

Ultra-high-temperature ceramics (UHTCs) are materials capable of withstanding temperatures above 2000 °C while maintaining exceptional properties, making them ideal for aerospace, automotive, and energy applications. However, they face challenges such as brittleness and limited oxidation resistance. This review highlights the potential benefits of modifying UHTCs with graphene, a material known for its excellent mechanical, thermal, and electrical properties. Incorporating graphene into UHTCs can enhance their mechanical properties, improve the oxidation resistance, increase the thermal conductivity, and tailor the electrical properties, while also improving the processability. By addressing the inherent limitations of UHTCs and enhancing their properties, graphene-modified UHTCs show promise for a wide range of high-temperature applications. The review covers recent research achievements in graphene/UHTCs composites, focusing on the synthesis methods, microstructures, macroscopic mechanical properties, oxidation resistance, thermal shock resistance, and the underlying mechanisms.

In situ electroporation, a non-invasive technique for enhancing the permeability of cell membranes, has emerged as a powerful tool for intracellular delivery and manipulation. This method allows for the precise introduction of therapeutic agents, such as nucleic acids, drugs, and proteins, directly into target cells within their native tissue environment. Herein, we introduce an innovative electroporation strategy that employs a Janus particle (JP)-based microelectrode to generate a localized and controllable electric field within a microfluidic chip. The microfluidic device is engineered with an indium tin oxide (ITO)-sandwiched microchannel, where the electric field is applied, and suspended JP microelectrodes that induce a stronger localized electric field. The corresponding simulation model is developed to better understand the dynamic electroporation process. Numerical simulations for both single-cell and chain-assembled cell electroporation have been successfully conducted. The effects of various parameters, including pulse voltage, duration medium conductivity, and radius of Janus microelectrode, on cell membrane permeabilization are systematically investigated. Our findings indicate that the enhanced electric intensity near the poles of the JP microelectrode significantly contributes to the electroporation process. In addition, the distribution for both transmembrane voltage and the resultant nanopores can be altered by conveniently adjusting the relative position of the JP microelectrode, demonstrating a selective and in situ electroporation technique for spatial control over the delivery area. Moreover, the obtained differences in the distribution of electroporation between chain cells can offer insightful directives for the electroporation of tissues or cell populations, enabling the precise and targeted modulation of specific cell populations. As a proof of concept, this work can provide a robust alternative technique for the study of complex and personalized cellular processes.

The development of digital villages plays a critical role in advancing green agriculture steadily and with high quality. This study measures the efficiency of agricultural water resource allocation using provincial-level rural data from 2011 to 2022 and a super Slacks-Based Measure model accounting for non-desirable outputs. Using the ArcGIS tool, this study illustrates the spatiotemporal patterns and provincial clustering of the green allocation of agricultural water resources. A spatial Durbin model further examines interactions between digital villages and water resource efficiency. Findings indicate the following: (1) The green water resource efficiency in China’s 30 provinces showed a gradual, steady increase, albeit with notable regional differences, particularly a “northwestern depression” in spatial distribution. (2) Moran’s I index indicates a strong positive spatial correlation between digital villages and green water resource efficiency, manifested as either “high–high” or “low–low” clustering. (3) The spatial Durbin model results demonstrate that digital villages enhance the green water resource efficiency of neighboring areas, a phenomenon referred to as the “Matthew effect”. (4) Different aspects of digital village construction, operation, and lifestyle positively influence green water resource efficiency, while digital loops have a negative impact. Aligning resource allocation efficiency with the establishment of digital village infrastructure is paramount. This symbiotic relationship bolsters the structural foundation of agricultural production, optimizing resource utilization and fostering technological advancements in rural settings.

To develop a simplified and highly accurate ship motion model, this study thoroughly investigated the relationship between the dimensionless cross-flow coefficient and the four hydrodynamic derivatives of the Norrbin model. Eight different types of ships were simulated to explore the impact of dimensionless cross-flow coefficients and individual hydrodynamic derivatives on the ship’s turning circle. A set of precise formulas is proposed to depict the interplay between these variables. The simulation outcomes indicate that the average deviation in the agreement between the turning circles produced by adjusting the dimensionless cross-flow coefficient and those predicted by modifying the four hydrodynamic derivatives was only 2.70%. Furthermore, the similarities between the two circles and the sea trail were significantly higher at 91.45% and 92.87% compared with the original Norrbin model’s accuracy of 78.12%. Adjusting the dimensionless cross-flow coefficients enabled the rapid identification of a curve that closely mirrored the sea trail. This research aimed to improve the accuracy of the Norrbin model and resolve issues related to determining the magnification of the hydrodynamic derivatives, laying a robust foundation for subsequent studies and applications in relevant domains.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements’ polarization in the vertical plane of the breast, while the second array has half of the elements’ polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications.

ZnO-CeO2 hollow nanospheres have been successfully synthesized via the hard templating method, in which CeO2 is used as the support skeleton to avoid ZnO agglomeration. The synthesized ZnO-CeO2 hollow nanospheres possess a large electrochemically active area and high electron transfer owing to the high specific surface area and synergistic effect of ZnO and CeO2. Due to the above advantages, the resulting ZnO-CeO2 hollow spheres display high sensitivities of 1122.86 μA mM−1 cm−2 and 908.53 μA mM−1 cm−2 under a neutral environment for the selective detection of dopamine and uric acid. The constructed electrochemical sensor shows excellent selectivity, stability and recovery for the selective analysis of dopamine and uric acid in actual samples. This study provides a valuable strategy for the synthesis of ZnO-CeO2 hollow nanospheres via the hard templating method as electrocatalysts for the selective detection of dopamine and uric acid.

IntroductionDue to the inefficiency and high cost of the current healthcare supply chain mode, in order to adapt to the great changes in the global economy and public health, it is urgent to choose an effective mode for sustainable development of healthcare supply chain. The aim of this paper is to use artificial intelligence systems to make intelligent decisions for healthcare supply chain mode selection.MethodsFirstly, according to the economic benefits, social benefits and environmental benefits of healthcare supply chain, this paper identifies different healthcare supply chain modes in combination with artificial intelligence technology. Secondly, this paper presents the intelligent choice optimization method of healthcare supply chain mode based on deep reinforcement learning algorithm. Finally, the effect of artificial intelligence in healthcare supply chain mode selection is verified by simulation experiment.Results and DiscussionThe experimental results show that healthcare supply chain mode selected by artificial intelligence is basically consistent with the target mode, while healthcare supply chain mode selected by the basic selection method, BP neural network method and big data method is different from the target mode, which indicates that AI has more advantages in the selection of medical supply chain mode. Therefore, we recommend the application of artificial intelligence to healthcare supply chain management. This study not only makes up for the ineffective problems of existing methods, but also makes up for the gaps in the application of AI technology in the field of healthcare supply chain. The scientific value of this paper is that the proposed framework and the artificial intelligence algorithm enrich the relevant theories of healthcare supply chain research and provide methodological guidance for intelligent decision-making of healthcare supply chain. At the same time, for medical enterprises, this research provides a new practical guideline for the application of artificial intelligence in the sustainable development and modern management of healthcare supply chain.

Pulmonary fibrosis is highly lethal with limited treatments. Butaselen (BS) is an inhibitor of thioredoxin reductase (TrxR)/thioredoxin (Trx) with anti-tumor activity. However, its impact on pulmonary fibrosis and the involved mechanisms remain unclear. Here, we demonstrate that BS is a potential drug for the treatment of pulmonary fibrosis. Specifically, BS can inhibit pulmonary fibrosis both in vitro and in vivo, with comparable efficacy and enhanced safety when compared with pirfenidone. BS and dexamethasone display a synergistic effect in inhibiting pulmonary fibrosis both in vitro and in vivo. Mechanistic studies reveal that BS can inhibit the TrxR activity during pulmonary fibrosis. RNA-sequencing analysis identifies that genes of ECM-related signaling pathways are notably affected by BS. BS can not only inhibit the activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and reduce pulmonary fibrosis-related inflammation, but also reduce NF-κB-activated transcriptional expression of transforming growth factor-β1 (TGF-β1), which leads to the inactivation of Smad2/Smad3 and decrease of collagen formation and fibrosis. Moreover, the knockdown of Trx1 with siRNA can also inhibit NF-κB/TGF-β1/Smads signaling. In conclusion, the TrxR/Trx inhibitor butaselen can suppress pulmonary fibrosis by inhibiting NF-κB/TGF-β1/Smads signaling.