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BackgroundCOVID-19 has overwhelmed health systems worldwide. It is important to identify severe cases as early as possible, such that resources can be mobilized and treatment can be escalated. ObjectiveThis study aims to develop a machine learning approach for automated severity assessment of COVID-19 based on clinical and imaging data. MethodsClinical data—including demographics, signs, symptoms, comorbidities, and blood test results—and chest computed tomography scans of 346 patients from 2 hospitals in the Hubei Province, China, were used to develop machine learning models for automated severity assessment in diagnosed COVID-19 cases. We compared the predictive power of the clinical and imaging data from multiple machine learning models and further explored the use of four oversampling methods to address the imbalanced classification issue. Features with the highest predictive power were identified using the Shapley Additive Explanations framework. ResultsImaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with those reported previously. Although oversampling yielded mixed results, it achieved the best model performance in our study. Logistic regression models differentiating between mild and severe cases achieved the best performance for clinical features (area under the curve [AUC] 0.848; sensitivity 0.455; specificity 0.906), imaging features (AUC 0.926; sensitivity 0.818; specificity 0.901), and a combination of clinical and imaging features (AUC 0.950; sensitivity 0.764; specificity 0.919). The synthetic minority oversampling method further improved the performance of the model using combined features (AUC 0.960; sensitivity 0.845; specificity 0.929). ConclusionsClinical and imaging features can be used for automated severity assessment of COVID-19 and can potentially help triage patients with COVID-19 and prioritize care delivery to those at a higher risk of severe disease.

Abstract To analyze the clinical features, epidemiological characteristics, risk factors, and complication characteristics of pulmonary tuberculosis (PTB) combined with extrapulmonary tuberculosis (EPTB) in elderly patients (aged > 60 years). Clinical data were collected from pathogen positive elderly patients with PTB hospitalized in a teaching hospital in Zhejiang from 2017 to 2023. We retrospectively analyzed the risk factors for complications of EPTB in elderly patients with PTB by univariate and multivariate logistic regression models. We also described the characteristics of complications in PTB with EPTB. A total of 781 PTB elderly patients were enrolled, of whom 86 (11.01%) had complicated EPTB. The most commonly invasive sites for EPTB were thoracic spine (17.53%), cervical lymph nodes (13.40%), and meninges (12.37%). 60

Abstract Background Ammonia-oxidizing archaea (AOA) of the phylum Thaumarchaeota mediate the rate-limiting step of nitrification and remove the ammonia that inhibits the aerobic metabolism of methanotrophs. However, the AOA that inhabit deep-sea methane-seep surface sediments (DMS) are rarely studied. Here, we used global DMS metagenomics and metagenome-assembled genomes (MAGs) to investigate the metabolic activity, evolutionary history, and ecological contributions of AOA. Expression of AOA-specific ammonia-oxidizing gene (amoA) was examined in the sediments collected from the South China Sea (SCS) to identify their active ammonia metabolism in the DMS. Results Our analysis indicated that AOA contribute > 75% to the composition of ammonia-utilization genes within the surface layers (above 30 cm) of global DMS. The AOA-specific ammonia-oxidizing gene was actively expressed in the DMS collected from the SCS. Phylogenomic analysis of medium-/high-quality MAGs from 18 DMS-AOA indicated that they evolved from ancestors in the barren deep-sea sediment and then expanded from the DMS to shallow water forming an amoA-NP-gamma clade-affiliated lineage. Molecular dating suggests that the DMS-AOA origination coincided with the Neoproterozoic oxidation event (NOE), which occurred ~ 800 million years ago (mya), and their expansion to shallow water coincided with the Sturtian glaciation (~ 713 mya). Comparative genomic analysis suggests that DMS-AOA exhibit higher requirement of carbon source for protein synthesis with enhanced genomic capability for osmotic regulation, motility, chemotaxis, and utilization of exogenous organic compounds, suggesting it could be more heterotrophic compared with other lineages. Conclusion Our findings provide new insights into the evolutionary history of AOA within the Thaumarchaeota, highlighting their critical roles in nitrogen cycling in the global DMS ecosystems. Video Abstract

Abstract Background The formation of stem cell clones enables close contact of stem cells inside. The gap junctions in such clone spheres establish a microenvironment that allows frequent intercellular communication to maintain self-renewal and functions of stem cells. Nevertheless, the essential gap junction protein for molecular signaling in clones is poorly known. Methods Primary human airway basal cells (hBCs) were isolated from brushing samples through bronchoscopy and then cultured. A tightly focused femtosecond laser was used to excite the local Ca2+ in an individual cell to initiate an internal Ca2+ wave in a clone to screen gap junction proteins. Immunoflourescence staining and clonogenicity assay were used to evaluate self-renewal and functions. RNA and protein levels were assessed by PCR and Western blot. Air–liquid interface assay was conducted to evaluate the differentiation potential. A Naphthalene injury mouse model was used to assess the regeneration potential. Results Herein, we identify Connexin 25 (Cx25) dominates intercellular Ca2+ communications in clones of hBCs in vitro to maintain the self-renewal and pluripotency of them. The self-renewal and in vitro differentiation functions and in vivo regeneration potential of hBCs in an airway damage model are both regulated by Cx25. The abnormal expression of Cx25 is validated in several diseases including IPF, Covid-19 and bronchiectasis. Conclusion Cx25 is essential for hBC clones in maintaining self-renewal and functions of hBCs via gap junctions.

The progression of precancerous lesions to malignancy is often accompanied by increasing complexity of chromosomal alterations but how these alterations arise is poorly understood. Here we perform haplotype-specific analysis of chromosomal copy-number evolution in the progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) on multiregional whole-genome sequencing data of BE with dysplasia and microscopic EAC foci. We identify distinct patterns of copy-number evolution indicating multigenerational chromosomal instability that is initiated by cell division errors but propagated only after p53 loss. While abnormal mitosis, including whole-genome duplication, underlies chromosomal copy-number changes, segmental alterations display signatures of successive breakage-fusion-bridge cycles and chromothripsis of unstable dicentric chromosomes. Our analysis elucidates how multigenerational chromosomal instability generates copy-number variation in BE cells, precipitates complex alterations including DNA amplifications, and promotes their independent clonal expansion and transformation. In particular, we suggest sloping copy-number variation as a signature of ongoing chromosomal instability that precedes copy-number complexity. These findings suggest copy-number heterogeneity in advanced cancers originates from chromosomal instability in precancerous cells and such instability may be identified from the presence of sloping copy-number variation in bulk sequencing data.

In the field of electrocatalysis, most of the electrodes have the problem of poor mechanical properties, which leads to the electrode can not be used on a large scale. At present, most bulk electrodes are used to study their mechanical properties due to their unique phase composition distribution and facile fabricate methods. But their novel properties in the field of electrocatalysts have not been fully developed. Multi-element bulk electrodes not only diversified the electronic states, but also build complex surface morphology by different dissolution rate between multi-phase distribution. In this paper, we synthesized the FeNiMo bulk electrode for oxygen evolution reaction (OER) with two-phase coexistence of Mo-doped face center cubic phase (FCC) and Mo-rich intermetallic compound (IMC) phase. During cyclic voltammetry activation, the surface reconstruction of Mo-rich IMC phases generated by ion leaching leaves Fe–Ni pore structures with more active area, which enhances OER performance. Meanwhile, the electron states get more diverse on the surface of remaining FCC phases due to Mo doping, which provides more suitable sites for four-step OER process. The FeNiMo electrode shows an ultra-low overpotential of 212 mV and 293.4 mV at a current density of 10 mA cm−2 and 100 mA cm−2, respectively. Moreover, it can maintain stability at 100 mA cm−2 for up to 72 h. This work provides a strategy for studying the relationship between phase composition and electrochemical performance of alloy bulk electrodes.

Abstract Objective To investigate whether intrauterine chilled saline can reduce endometrial impairment during US-guided percutaneous microwave ablation (PMWA) of adenomyosis. Methods An open-label, randomized trial was conducted with sixty symptomatic adenomyosis patients who were randomly assigned (1:1) to receive PMWA treatment assisted by intrauterine saline instillation (study group) or traditional PMWA treatment alone (control group). The primary endpoint was endometrial perfusion impairment grade on post-ablation contrast-enhanced MRI. The secondary endpoints were endometrial dehydration grade, ablation rate, and intra-ablation discomfort. Results The baseline characteristics of the two groups were similar. The incidence rates of endometrial perfusion impairment on MRI in the study and control groups were 6.7% (2/30) and 46.7% (14/30), respectively (p

Abstract Interfacial electron transfer between electroactive microorganisms (EAMs) and electrodes underlies a wide range of bio‐electrochemical systems with diverse applications. However, the electron transfer rate at the biotic‐electrode interface remains low due to high transmembrane and cell‐electrode interfacial electron transfer resistance. Herein, a modular engineering strategy is adopted to construct a Shewanella oneidensis‐carbon felt biohybrid electrode decorated with bacterial cellulose aerogel‐electropolymerized anthraquinone to boost cell‐electrode interfacial electron transfer. First, a heterologous riboflavin synthesis and secretion pathway is constructed to increase flavin‐mediated transmembrane electron transfer. Second, outer membrane c‐Cyts OmcF is screened and optimized via protein engineering strategy to accelerate contacted‐based transmembrane electron transfer. Third, a S. oneidensis‐carbon felt biohybrid electrode decorated with bacterial cellulose aerogel and electropolymerized anthraquinone is constructed to boost the interfacial electron transfer. As a result, the internal resistance decreased to 42 Ω, 480.8‐fold lower than that of the wild‐type (WT) S. oneidensis MR‐1. The maximum power density reached 4286.6 ± 202.1 mW m−2, 72.8‐fold higher than that of WT. Lastly, the engineered biohybrid electrode exhibited superior abilities for bioelectricity harvest, Cr6+ reduction, and CO2 reduction. This study showed that enhancing transmembrane and cell‐electrode interfacial electron transfer is a promising way to increase the extracellular electron transfer of EAMs.

Pathogenic missense mutation of the FGF12 gene is responsible for a variable disease phenotypic spectrum. Disease-specific therapies require precise dissection of the relationship between different mutations and phenotypes. The lack of a proper animal model hinders the investigation of related diseases, such as early-onset epileptic encephalopathy. Here, an FGF12AV52H mouse model was generated using CRISPR/Cas9 technology, which altered the A isoform without affecting the B isoform. The FGF12AV52H mice exhibited seizure susceptibility, while no spontaneous seizures were observed. The increased excitability in dorsal hippocampal CA3 neurons was confirmed by patch-clamp recordings. Furthermore, immunostaining showed that the balance of excitatory/inhibitory neurons in the hippocampus of the FGF12AV52H mice was perturbed. The increases in inhibitory SOM+ neurons and excitatory CaMKII+ neurons were heterogeneous. Moreover, the locomotion, anxiety levels, risk assessment behavior, social behavior, and cognition of the FGF12AV52H mice were investigated by elevated plus maze, open field, three-chamber sociability, and novel object tests, respectively. Cognition deficit, impaired risk assessment, and social behavior with normal social indexes were observed, implying complex consequences of V52H FGF12A in mice. Together, these data suggest that the function of FGF12A in neurons can be immediate or long-term and involves modulation of ion channels and the differentiation and maturation of neurons. The FGF12AV52H mouse model increases the understanding of the function of FGF12A, and it is of great importance for revealing the complex network of the FGF12 gene in physiological and pathological processes.

Abstract Micrometer‐sized silicon monoxide (SiO) is regarded as a high‐capacity anode material with great potential for lithium ion batteries (LIBs). However, the problems of low initial Coulombic efficiency (ICE), poor electrical conductivity, and large volume change of SiO inevitably impede further application. Herein, the vacuum thermal reduced SiOx with amorphous AlPO4 and carbon double‐coating layers is used as the ideal anode material in LIBs. The vacuum thermal reduction at low temperature forms fine silicon grains in the internal particles and maintains the external integrity of SiOx particles, contributing to mitigation of the stress intensification and the subsequent design of multifunctional coating. Meanwhile, the innovative introduction of the multifunctional amorphous AlPO4 layer not only improves the ion/electron conduction properties to ensure the fast reversible reaction but also provides a robust protective layer with stable physicochemical characteristics and inhibits the volume expansion effect. The sample of SiOx anode shows an ICE up to 87.6% and a stable cycling of 200 cycles at 1 A g−1 with an initial specific capacity of 1775.8 mAh g−1. In addition, the assembled pouch battery of 1.8 Ah can also ensure a cycling life of over 150 cycles, demonstrating a promising prospect of this optimized micrometer‐sized SiOx anode material for industrial applications.

ABSTRACT Nitrogen (N)-fixing organisms, also known as diazotrophs, play a crucial role in N-limited ecosystems by controlling the production of bioavailable N. The carbon-dominated cold-seep ecosystems are inherently N-limited, making them hotspots of N fixation. However, the knowledge of diazotrophs in cold-seep ecosystems is limited compared to other marine ecosystems. In this study, we used multi-omics to investigate the diversity and catabolism of diazotrophs in deep-sea cold-seep bottom waters. Our findings showed that the relative abundance of diazotrophs in the bacterial community reached its highest level in the cold-seep bottom waters compared to the cold-seep upper waters and non-seep bottom waters. Remarkably, more than 98% of metatranscriptomic reads aligned on diazotrophs in cold-seep bottom waters belonged to the genus Sagittula, an alphaproteobacterium. Its metagenome-assembled genome, named Seep-BW-D1, contained catalytic genes (nifHDK) for nitrogen fixation, and the nifH gene was actively transcribed in situ. Seep-BW-D1 also exhibited chemosynthetic capability to oxidize C1 compounds (methanol, formaldehyde, and formate) and thiosulfate (S2O32−). In addition, we observed abundant transcripts mapped to genes involved in the transport systems for acetate, spermidine/putrescine, and pectin oligomers, suggesting that Seep-BW-D1 can utilize organics from the intermediates synthesized by methane-oxidizing microorganisms, decaying tissues from cold-seep benthic animals, and refractory pectin derived from upper photosynthetic ecosystems. Overall, our study corroborates that carbon-dominated cold-seep bottom waters select for diazotrophs and reveals the catabolism of a novel chemosynthetic alphaproteobacterial diazotroph in cold-seep bottom waters.IMPORTANCEBioavailable nitrogen (N) is a crucial element for cellular growth and division, and its production is controlled by diazotrophs. Marine diazotrophs contribute to nearly half of the global fixed N and perform N fixation in various marine ecosystems. While previous studies mainly focused on diazotrophs in the sunlit ocean and oxygen minimum zones, recent research has recognized cold-seep ecosystems as overlooked N-fixing hotspots because the seeping fluids in cold-seep ecosystems introduce abundant bioavailable carbon but little bioavailable N, making most cold seeps inherently N-limited. With thousands of cold-seep ecosystems detected at continental margins worldwide in the past decades, the significant role of cold seeps in marine N biogeochemical cycling is emphasized. However, the diazotrophs in cold-seep bottom waters remain poorly understood. Through multi-omics, this study identified a novel alphaproteobacterial chemoheterotroph belonging to Sagittula as one of the most active diazotrophs residing in cold-seep bottom waters and revealed its catabolism.

Abstract Background Formolase (FLS) is a computationally designed enzyme that catalyzes the carboligation of two or three C1 formaldehyde molecules into C2 glycolaldehyde or C3 dihydroxyacetone (DHA). FLS lays the foundation for several artificial carbon fixation and valorization pathways, such as the artificial starch anabolic pathway. However, the application of FLS is limited by its low catalytic activity and product promiscuity. Findings FLS, designed and engineered based on benzoylformate decarboxylase from Pseudomonas putida, was selected as a candidate for modification. To evaluate its catalytic activity, 25 residues located within an 8 Å distance from the active center were screened using single-point saturation mutagenesis. A screening approach based on the color reaction of the DHA product was applied to identify the desired FLS variants. After screening approximately 5,000 variants (approximately 200 transformants per site), several amino acid sites that were not identified by directed evolution were found to improve DHA formation. The serine-to-phenylalanine substitution at position 236 improved the activity towards DHA formation by 7.6-fold. Molecular dynamics simulations suggested that the mutation increased local hydrophobicity at the active site, predisposing the cofactor-C2 intermediate to nucleophilic attack by the third formaldehyde molecule for subsequent DHA generation. Conclusions This study provides improved FLS variants and valuable information into the influence of residues adjacent to the active center affecting catalytic efficiency, which can guide the rational engineering or directed evolution of FLS to optimize its performance in artificial carbon fixation and valorization.

Abstract In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk RNA-Seq data, we identify three genes referred to as HMR, FAM83A, and KRT6A these genes are related to necroptotic anoikis-related gene expression. Initial validation, conducted on the GSE50081 dataset, demonstrated the model's ability to categorize LUAD patients into high-risk and low-risk groups with significant survival differences. This model was further applied to predict responses to PD-1/PD-L1 blockade therapies, utilizing the IMvigor210 and GSE78220 cohorts, and showed strong correlation with patient outcomes, highlighting its potential in personalized immunotherapy. Further, LUAD cell lines were analyzed using quantitative PCR (qPCR) and Western blot analysis to confirm their expression levels, further corroborating the model's relevance in LUAD pathophysiology. The mutation landscape of these genes was also explored, revealing their broad implication in various cancer types through a pan-cancer analysis. The study also delved into molecular subclustering, revealing distinct expression profiles and associations with different survival outcomes, emphasizing the model’s utility in precision oncology. Moreover, the diversity of immune cell infiltration, analyzed in relation to the necroptotic anoikis signature, suggested significant implications for immune evasion mechanisms in LUAD. While the findings present a promising stride towards personalized LUAD treatment, especially in immunotherapy, limitations such as the retrospective nature of the datasets and the need for larger sample sizes are acknowledged. Prospective clinical trials and further experimental research are essential to validate these findings and enhance the clinical applicability of our prognostic model.

Abstract Background Fibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated. Methods In this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan–Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored. Results The study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan–Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells. Conclusion Despite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.

Flame retardant ceramic silicone rubber was prepared by dehydrogenation condensation using α,ω-hydroxy-terminated polysiloxane as matrix, and composite ceramic powder and fumed silica as fillers. The effects of the amount of composite ceramic powder, type of raw rubber side groups and ablation temperatures on the properties of the flame retardant ceramic silicone rubber were investigated. The results showed that the physical and mechanical properties of 107 silicone rubber containing side methyl group were almost the best when the amount of composite ceramic powder was 120 phr (mass), the tensile strength was 4.69 MPa, elongation at break was 686%, Shore A hardness was 48 and flexural strength was 12.29 MPa. Compared with 107 silicone rubber and 108 silicone rubber containing pendant phenyl group, the ceramic silicone rubber prepared from 109 silicone rubber containing pendant methyl vinyl group had better thermal stability, and the residual carbon mass fraction of composite up to 86% at 1 000 ℃. The ceramic silicone rubber from 109 silicone rubber had better flame retardancy, the limiting oxygen index was 49.5%, and the vertical combustion grade was V-0. In addition, it had a lower ceramization temperature and a good ceramization effect at 600 ℃.

Abstract Background Classifying breast cancer subtypes is crucial for clinical diagnosis and treatment. However, the early symptoms of breast cancer may not be apparent. Rapid advances in high-throughput sequencing technology have led to generating large number of multi-omics biological data. Leveraging and integrating the available multi-omics data can effectively enhance the accuracy of identifying breast cancer subtypes. However, few efforts focus on identifying the associations of different omics data to predict the breast cancer subtypes. Results In this paper, we propose a differential sparse canonical correlation analysis network (DSCCN) for classifying the breast cancer subtypes. DSCCN performs differential analysis on multi-omics expression data to identify differentially expressed (DE) genes and adopts sparse canonical correlation analysis (SCCA) to mine highly correlated features between multi-omics DE-genes. Meanwhile, DSCCN uses multi-task deep learning neural network separately to train the correlated DE-genes to predict breast cancer subtypes, which spontaneously tackle the data heterogeneity problem in integrating multi-omics data. Conclusions The experimental results show that by mining the associations among multi-omics data, DSCCN is more capable of accurately classifying breast cancer subtypes than the existing methods.

AbstractDianella ensifolia (L.) Redouté 1802 is a plant known for its significant medicinal values. In this study, we presented its chloroplast genome. The length of the chloroplast genome was found to be 156,571 bp, with a GC content of 37.86%. It consisted of a large single-copy (LSC) of 85,318 bp and a small single-copy (SSC) of 18,307 bp, a pair of inverted repeats (IRs) of 26,473 bp each that separated the LSC and SSC regions. The chloroplast genome of D. ensifolia consisted of 114 unique genes, including 80 protein-coding genes, four rRNA genes, and 30 tRNA genes. Through phylogenetic analysis, we identified a close relationship between D. ensifolia and D. nigra. This newly sequenced chloroplast genome not only enhances our understanding of the genome of Dianella, but also provides valuable insights for the evolutionary study of the family Asphodelaceae.

Abstract Unmanned aerial vehicles (UAVs) offer a new approach to wireless communication, leveraging their high mobility, flexibility, and visual communication capabilities. Ambient backscatter communication enables Internet of Things devices to transmit data by reflecting and modulating ambient radio waves, eliminating the need for additional wireless channels, and reducing energy consumption and cost for sensors. However, passive ambient backscatter communication has limitations such as limited range and poor communication quality. By utilizing UAVs as communication nodes, these limitations can be overcome, expanding the communication range and improving the quality of communication. Although some research has been conducted on combining UAVs and ambient backscatter, several challenges remain. One key challenge is the strong direct link interference in ambient backscatter under UAV conditions, which significantly affects communication quality. In this paper, we propose an intelligent backward and forward straight link interference cancellation algorithm based on NOMA decoding technique to enhance ambient backscatter communication quality under UAV conditions and extract more ambient energy for UAV energy supply. The paper includes theoretical derivation, algorithm description, and simulation analysis to validate the error bit rate of labeled information bits. The results demonstrate that the forward algorithm reduces the error bit rate by approximately 20% under low signal-to-noise ratio (SNR) conditions, while the backward algorithm reduces the error bit rate under high SNR conditions. The combination of the forward and backward algorithms reduces the error bit rate under both high and low SNR conditions. The proposed method contributes to improving the quality of ambient backscatter communication in UAV settings.

Abstract All-small-molecule organic solar cells with good batch-to-batch reproducibility combined with non-halogen solvent processing show great potential for commercialization. However, non-halogen solvent processing of all-small-molecule organic solar cells are rarely reported and its power conversion efficiencies are very difficult to improve. Herein, we designed and synthesized a small molecule donor BM-ClEH that can take advantage of strong aggregation property induced by intramolecular chlorine-sulfur non-covalent interaction to improve molecular pre-aggregation in tetrahydrofuran and corresponding micromorphology after film formation. Tetrahydrofuran-fabricated all-small-molecule organic solar cells based on BM-ClEH:BO-4Cl achieved high power conversion efficiencies of 15.0% in binary device and 16.1% in ternary device under thermal annealing treatment. In contrast, weakly aggregated BM-HEH without chlorine-sulfur non-covalent bond is almost inefficient under same processing conditions due to poor pre-aggregation induced disordered π-π stacking, indistinct phase separation and exciton dissociation. This work promotes the development of non-halogen solvent processing of all-small-molecule organic solar cells and provides further guidance.

ABSTRACT: Objectives: Aquatic ecosystems serve as a dissemination pathway and a reservoir of both antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). This study aimed to determine the prevalence of colistin-resistant mcr-like genes in Enterobacteriales in aquatic products, which may be contribute to the transfer of ARGs in water environments. Methods: The mcr-1-positive Escherichia coli were recovered from 123 freshwater fish and 34 cultured crocodile cecum samples from 10 farmers’ markets in Guangdong, China. Minimum inhibitory concentration (MIC) was determined using the agar dilution method. Genotyping was performed using pulsed-field gel electrophoresis (PFGE) and multi-locus sequence typing (MLST). Conjugation assay was carried out to investigate the transferability of mcr-1. Genomic information was obtained by whole genome sequencing (WGS) and bioinformatic analysis. Results: Forty-four mcr-1 positive isolates showed co-resistance to tetracycline, trimethoprim/sulfamethoxazole, and gentamicin, while they were all sensitive to tigecycline, meropenem, and amikacin. They were typed into sixteen PFGE clusters. ST10 and ST117 were the most popular sequence types, followed by ST1114. S1-PFGE verified the presence of the mcr-1 gene on plasmids in sizes of ∼60 kb (n = 1) and ∼240 kb (n = 3). Whole genome sequencing-based analysis identified mcr-1 integrated in IncHI2 plasmid (n = 3), IncI2 plasmid (n = 2), and bacterial chromosome in two copies (n = 1). In addition to mcr-1, they carried several other antibiotic resistance genes, such as blaCTX-M-14, fosA3, and aac(6’)-Ib-cr. Conclusion: These data suggest that aquatic products are an important antibiotic resistance reservoir and highlight possible risks regarding food safety.

Microgrids comprising photovoltaic (PV), energy-storage systems and electric vehicles have received increasing attention. However, the increase in renewable energy sources, such as PVs, will introduce uncertainty factors to the frequency response, resulting in frequency fluctuations that can reduce power quality. Hence, we propose an outstanding learning-based control approach that combines a model of physical principles with a Gaussian Process (GP) learning approach. The learning model corrects the physical principles model and estimates its uncertainty. Simulations are performed by comparing the proposed controller with conventional model-predictive controllers. The results indicate that the learning-based controller proposed can adjust the frequency with less overshooting and a lower root mean square error compared to the conventional MPC control method.

Abstract Organic scintillators have recently gained considerable attentions in X‐ray detection for their potential applications in biomedical radiograph and security inspection. However, the weak X‐ray absorption and/or inefficient exciton utilization have limited the development and commercialization of organic scintillators. Currently, high‐performance X‐ray organic scintillators are scarce and organic scintillators with dual triplet‐harvesting channels have not been explored before. Here, we develop several proof‐of‐concept sulfone‐based organic molecules, C1–C7, using different alkoxy chains to manipulate molecular packing mode. These materials exhibit dual triplet‐harvesting channels of thermally activated delayed fluorescence (TADF) and room‐temperature phosphorescence (RTP) in aggregated state. Inspiringly, these molecules display distinct radioluminescence under the X‐ray stimulation. Among them, C6 behaves the highest light yield of 16,558 photons MeV−1. Moreover, clear X‐ray images are demonstrated in both aggregated state and single‐molecule level. High spatial resolutions of 15.0 and 10.6 line pairs per millimeter (lp mm−1) are achieved for rigid and flexible scintillator screens, exceeding most reported organic and conventional inorganic scintillators. These results highlight the great potential of organic molecules with TADF and RTP nature for efficient X‐ray scintillation and imaging.

BackgroundBariatric surgery has emerged as an important tool in the management of obesity. Some patients undergoing bariatric surgery are prone to develop emotional abnormalities and have abnormally elevated concentrations of inflammatory factors level in peripheral blood， whereas current domestic research focusing on the impact of preoperative emotional states and peripheral blood inflammatory factors level on weight loss effect remains limited.ObjectiveTo explore the correlation of preoperative emotional abnormalities with the effectiveness of bariatric surgery in obese patients， and to provide theoretical basis for improving the clinical efficacy of bariatric surgery.MethodsEighty-one obese patients scheduled for bariatric surgery at gastrointestinal surgery Department of West China Hospital， Sichuan University from December 30， 2022 to June 30， 2023 were enrolled and assessed using Hamilton Depression Scale-17 item （HAMD-17） and Hamilton Anxiety Scale （HAMA）. Patients who scored 7 or above on HAMD-17 or HAMA or had a history of previous depression or anxiety diagnoses were classified into emotional abnormality group （n=34）， and samples who scored less than 7 on HAMD-17 and HAMA and were free of history of previous depression and anxiety diagnoses were set as non-emotional abnormality group （n=47）. The data were collected by the self made questionnaire. Patients were subjected to complete the assessment of Beck Scale for Suicide Ideation-Chinese Version （BSI-CV）， Eating Disorder Inventory （EDI） and Pittsburgh Sleep Quality Index （PSQI）. Laboratory tests including peripheral blood C-reactive protein （CRP） and interleukin-6 （IL-6）. Body weight and height assessed in the early morning after an overnight fasting period were recorded in all participants at 1- and 6-month after surgery through outpatient clinic visits or telephone follow-up. Pearson correlation coefficient was used to examine relationship among body mass index （BMI）， preoperative emotional states and peripheral blood inflammation mediators.ResultsAmong 81 obese patients， 62 completed the study， including 27 cases in emotional abnormality group and 35 cases in non-emotional abnormality group. Emotional abnormality group scored higher on BSI-CV （current）， BSI-CV （worst）， EDI and PSQI， and detected higher levels of CRP and IL-6 compared with non-emotional abnormality group （Z=2.677， 2.975， t=3.573， 4.035， 1.990， 2.799， P0.05）， but a significant time effect （F=227.740， P