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Abstract Near-infrared (NIR)-II fluorescence imaging-guided photodynamic therapy (PDT) has shown great potential for precise diagnosis and treatment of tumors in deep tissues; however, its performance is severely limited by the undesired aggregation of photosensitizers and the competitive relationship between fluorescence emission and reactive oxygen species (ROS) generation. Herein, we report an example of an anionic pentamethine cyanine (C5T) photosensitizer for high-performance NIR-II fluorescence imaging-guided PDT. Through the counterion engineering approach, a triphenylphosphine cation (Pco) modified with oligoethylene glycol chain is synthesized and adopted as the counterion of C5T, which can effectively suppress the excessive and disordered aggregation of the resulting C5T-Pco by optimizing the dye amphipathicity and enhancing the cyanine-counterion interactions. Dynamic tuning of fluorescence characteristics and ROS generation is achieved at the aggregate level, resulting in an impressive type I ROS generation under 760 nm light irradiation, accompanied by efficient NIR-II fluorescence emission excited at 808 nm. As a result, excitation wavelength selective NIR-II fluorescence imaging-guided PDT has been successfully demonstrated for tumor diagnosis and therapeutics of female mice.

Abstract The growth in carbon emissions poses a severe challenge to global sustainable development, making it imperative to explore the impacts of economic restructuring and technological progress on Carbon Emission Performance (CEP). However, existing studies often lack an integrated analysis of economic restructuring and technological progress, while giving limited attention to the indirect role of Environmental Regulation (ER). This study constructs a multidimensional theoretical framework, breaking down economic restructuring into four dimensions—industrial structure, factor input, ownership, and new-type urbanization (NTU), and refining technological progress into technological innovation and energy efficiency. It uncovers the complex interplay among CEP, economic restructuring, technological progress, and ER. The findings reveal critical insights: (1) industrial structure suppresses CEP, whereas adjustments in factor input and ownership structure significantly enhance it; (2) the relationship between NTU and CEP exhibits a non-linear pattern; (3) compared to the technological innovation, energy efficiency provide a more substantial boost to CEP; and (4) ER positively moderates the impacts of factor input, ownership structure, and NTU. Finally, the study proposes recommendations for holistic economic restructuring and diversified ERs.

Abstract Temporal lobe epilepsy (TLE) is the most common form of medically-intractable epilepsy. Subicular hyperexcitability is frequently observed with TLE, presumably caused by impaired inhibition of local excitatory neurons. Here, we evaluated the effectiveness of silencing subicular pyramidal neurons to treat a rodent model of TLE. First, we generated a chronic TLE mouse model via initial intrahippocampal kainic acid (IHKA) injection. In the chronic state after first IHKA injection, behavioral seizures and histological abnormalities were reliably observed. We then injected an adeno-associated viral (AAV) vector carrying an inhibitory chemogenetic element, hM4Di, directly into the subiculum. Eight weeks after the first IHKA injection, acute seizures were induced by giving a second dose of kainic acid (KA), which mimicked generalized tonic–clonic seizures. Herein, precise control over generalized tonic–clonic seizure onset was achieved via this two-step process. We found that chemogenetic suppression of subicular pyramidal neurons had a robust anti-epileptogenesis effect in this acute-chronic model of TLE. These data confirm a crucial role of the subiculum in the propagation of hippocampal seizures and highlight the potential for using subicular chemogenetic manipulation to treat generalized tonic–clonic seizures.

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 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 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.

Summary: Background: Idiopathic pulmonary fibrosis (IPF) is a fibrosing interstitial pneumonia with restrictive ventilation. Recently, the structural and functional defects of small airways have received attention in the early pathogenesis of IPF. This study aimed to elucidate the characteristics of small airway epithelial dysfunction in patients with IPF and explore novel therapeutic interventions to impede IPF progression by targeting the dysfunctional small airways. Methods: Airway trees spanning the proximal–distal axis were harvested from control lungs and explanted lungs with end-stage IPF undergoing transplant. Qualified basal cells (BCs, p63/Krt5/ITGA6/NGFR) were expanded, and their cellular functions, feasibility, safety and efficacy for transplantation therapy in IPF were validated with experiments in vitro and mouse model. Single-cell RNA-sequencing was employed to elucidate the underlying mechanisms governing the BCs based therapy. Based upon these evidences, three patients with advanced IPF and small airway dysfunction received autologous-BCs transplantation. Post-transplantation assessments included lung function, exercise capacity and high resolution computed tomography (HRCT) scans were analyzed to quantify the clinical benefits conferred by the BCs transplantation. Findings: An overall landscape of senescent phenotype in airway epithelial cells and airway stem/progenitor cells along the proximal–distal axis of the airway tree in IPF were outlined. In contrast to the cells situated in distal airways, BCs located in small bronchi in IPF displayed a non-senescent phenotype, with comparable proliferative, differentiative capabilities, and similar transcriptomic profiles to normal controls. In a mouse model of pulmonary fibrosis, BCs exhibited promising protective efficacy and safety for transplantation therapy. Autologous BCs transplantation in three advanced IPF patients with small airway dysfunction yielded significant clinical improvements in pulmonary function, particularly evidence in lung volume and small airway function. Interpretation: Epithelia of small bronchi in IPF contain functional and expandable basal stem cells, which exert therapeutic benefits via bronchoscopic implantation. Our findings offer a potential for IPF treatment by targeting small airways. Funding: National Natural Science Foundation of China (82430001, 81930001, and 81900059), Shanghai Shenkang Hospital Development Center (SHDC2020CR3063B), Department of Science and Technology of Shandong Province (2024HWYQ-058).

ABSTRACT Objective This study was conducted to further understand the clinical characteristics of COVID‐19 associated pulmonary aspergillosis (CAPA). Methods In this study, we conducted a multicenter retrospective survey, which included patients with COVID‐19 from five hospitals in Zhejiang, China. A total of 197 patients with COVID‐19 were included in the study. The detailed clinical data of seven patients with CAPA from COVID‐19 onset to 28 days after CAPA were collected and analyzed. Results In the total of 197 patients, 36 were admitted to the intensive care unit (ICU), 13 received mechanical ventilation; among them, nine received extracorporeal membrane oxygenation (ECMO). All seven cases acquired CAPA in the ICU, six cases during MV, of which five cases received ECMO treatment at the same time, and one case had been off ventilation. The average duration from onset of COVID‐19 to CAPA was 25.4 days, from ICU admission to CAPA was 23.4 days, and from MV to CAPA was 22.1 days. All seven patients were diagnosed with CAPA without neutropenia, four with lymphopenia, seven with decreased CD4+ T lymphocyte, and five with decreased CD8+ T lymphocyte. All cases received glucocorticoids before CAPA, with an average duration of 15 days and an average cumulative dose of 762.5 mg prednisolone. In addition, all patients suffered bacterial infections and received antibacterial agents before CAPA, with an average duration of 22.6 days. CAPA was diagnosed according to a positive culture of Aspergillus fumigatus in sputum or bronchoalveolar lavage fluid (BALF) and positive serum 1,3‐β‐d‐glucan in all seven patients; serum galactomannan was positive in three cases. Rhizopus was cultured from BALF of one case during treatment of CAPA. All patients received antifungal therapy, and the 28‐day survival rate was 100%. Conclusion The incidence of CAPA in patients with COVID‐19 admitted to the ICU was 19.44%, all patients with CAPA had a history of chronic underlying diseases, and all had a history of high dose glucocorticoid. Patients with CAPA had no specific clinical symptoms and lung imaging manifestations, and diagnosis depended on Aspergillus culture and galactomannan detection. For patients with COVID‐19 with these high‐risk factors, Aspergillus culture and GM testing should be performed actively to avoid delaying the diagnosis of CAPA.

The development of an effective treatment for myelodysplastic syndrome (MDS) is needed due to the insufficient efficacy of current therapies. Gambogenic acid (GNA) is a xanthone constituent of gamboge, a resin secreted by Garcinia hanburyi Hook. f. GNA exhibits antitumor and apoptosis-inducing activities against some cancer cells, but the mechanism is unknown. This study aimed to validate the anti-proliferative and apoptosis-inducing effects of GNA on MDS cells and to elucidate the mechanisms underlying those activities. Apoptosis, proliferation and cell cycle of MDS-L cells were assessed by the caspase 3/7 assay, cell counting and flow cytometry, respectively. The levels of apoptotic, tubulin, NF-κB pathways, and Fas proteins were determined by Western blotting. CRISPR/Cas9 knockout (KO) plasmids were used to generate KO cells of p65 and Fas. MDS cell growth in a xenograft model was evaluated by the AkaBLI system. GNA induced MDS cell apoptosis, accompanied by a reduction in the anti-apoptotic protein MCL-1 expression, and inhibited their growth in vitro and in vivo. GNA combined with the MCL-1 inhibitor MIK665 potently suppressed the proliferation of MDS cells. GNA interfered with tubulin polymerization, resulting in G2/M arrest. GNA induced NF-κB activation and upregulation of Fas, the latter of which was inhibited by p65 KO. GNA-induced apoptosis was attenuated in either p65 KO or Fas KO cells. These results demonstrate that GNA inhibited tubulin polymerization and induced apoptosis of MDS cells through upregulation of Fas expression mediated by the NF-κB signaling pathway, suggesting a chemotherapeutic strategy for MDS by microtubule dynamics disruption.

PurposeChronic ankle instability (CAI) causes maladaptive neuroplastic changes in the central nervous system, which may lead to high injury potential under dual-task conditions. This study aims to explore the effects of dual-task paradigm on the injury potential during landing among individuals with CAI.MethodsTwenty participants with CAI (4 female and 16 male, 12 were affected with their right limbs and 8 were affected with their left limbs, 20.4 ± 1.7 years, 176.9 ± 5.0 cm, and 72.0 ± 11.1 kg) and eighteen without CAI (6 female and 12 male, 20.2 ± 1.5 years, 173.5 ± 7.0 cm, and 70.3 ± 10.8 kg) were recruited. They drop-landed on a trap-door device, with their affected or matched limbs on a flippable platform, under single- (drop-landing only) and dual-task (drop-landing while subtracting of serial threes) conditions. A twelve-camera motion capture system was used to capture the kinematic data. Two-way ANOVA with mixed design (CAI vs non-CAI groups by single-vs dual-task conditions) was used to analyze the data.ResultsSignificant group-by-condition interactions were detected in the ankle inversion angle (P = 0.040, η2p = 0.012) and ankle inversion angular velocity (P = 0.038, η2p = 0.114). Both indicators decreased among individuals without CAI from single-to dual-task conditions, while remained unchanged among those with CAI; and they were higher among individuals with CAI under both single- and dual-task conditions, compared to those without CAI.ConclusionIndividuals with CAI have a reduced ability to limit ankle inversion compared to those without CAI. Under dual-task conditions, individuals without CAI limited their ankle inversion, while those with CAI did not. Drop-landing, especially under dual-task conditions, poses a high risk of excessive ankle inversion for individuals with CAI.

ABSTRACT Marine biofilms were newly revealed as a giant microbial diversity pool for global oceans. However, the cyanobacterial diversity in marine biofilms within the upper seawater column and its ecological and evolutionary implications remains undetermined. Here, we reconstructed a full picture of modern marine cyanobacteria habitats by re-analyzing 9.3 terabyte metagenomic data sets and 2,648 metagenome-assembled genomes (MAGs). The abundances of cyanobacteria lineages exclusively detected in marine biofilms were up to ninefold higher than those in seawater at similar sample size. Analyses revealed that cyanobacteria in marine biofilms are specialists with strong geographical and environmental constraints on their genome and functional adaption, which is in stark contrast to the generalistic features of seawater-derived cyanobacteria. Molecular dating suggests that the important diversifications in biofilm-forming cyanobacteria appear to coincide with the Great Oxidation Event (GOE), “boring billion” middle Proterozoic, and the Neoproterozoic Oxidation Event (NOE). These new insights suggest that marine biofilms are large and important cyanobacterial factories for the global oceans.IMPORTANCECyanobacteria, highly diverse microbial organisms, play a crucial role in Earth’s oxygenation and biogeochemical cycling. However, their connection to these processes remains unclear, partly due to incomplete surveys of oceanic niches. Our study uncovered significant cyanobacterial diversity in marine biofilms, showing distinct niche differentiation compared to seawater counterparts. These patterns reflect three key stages of marine cyanobacterial diversification, coinciding with major geological events in the Earth's history.

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 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.

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 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 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.

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 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 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.

RNA nanoparticles, derived from the packaging RNA three-way junction motif (pRNA-3WJ) of the bacteriophage phi29 DNA packaging motor, have been demonstrated to be thermodynamically and chemically stable, with promise as a nanodelivery system. Background/Objectives: A previous study showed that RNA nanoparticles with antiangiogenic aptamers (anti-vascular endothelial growth factor (VEGF) and anti-angiopoietin-2 (Ang2) aptamers) inhibited cell proliferation via WST-1 assay. To further investigate the antiangiogenic potential of these RNA nanoparticles, a modified three-dimensional (3D) spheroid sprouting assay model of human umbilical vein endothelial cells was utilized in the present study. Methods: Three groups of RNA nanoparticles were evaluated, namely, pRNA-3WJ series, RNA square series (polygon-type RNA nanoparticles), and 8WJ series (multiple-way junction RNA nanoparticles), which were conjugated with a single anti-VEGF, the combination of one anti-VEGF and one anti-Ang2, or multiple anti-VEGF aptamers. The core scaffold RNA nanoparticles (without aptamers) were used as the references, and bevacizumab was used as the positive control. Results: The results demonstrated the inhibition effects of the RNA nanoparticles on endothelial cell tube formation at 67 nM in a 3D spheroid sprouting model. The results in the 3D spheroid sprouting assay are consistent with those of the WST-1 proliferation assays. Conclusions: Among the RNA nanoparticles evaluated, 3WJ-3VEGF and SQR-VEGF-Ang2 had inhibition effects equivalent to bevacizumab and were promising for anti-angiogenesis treatment.

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.

Abstract Background LATS1/2 are frequently mutated and down-regulated in endometrial cancer (EC), but the contributions of LATS1/2 in EC progression remains unclear. Impaired antigen presentation due to mutations or downregulation of the major histocompatibility complex class I (MHC-I) has been implicated in tumor immune evasion. Herein, we elucidate the oncogenic role that dysregulation of LATS1/2 in EC leads to immune evasion through the down-regulation of MHC-I. Methods The mutation and expression as well as the clinical significance of LATS1/2 in EC was assessed in the TCGA cohort and our sample cohort. CRISPR-Cas9 was used to construct knockout cell lines of LATS1/2 in EC. Differentially expressed genes were analyzed by RNA-seq. The interaction between LATS1/2 and STAT1 was verified using co-immunoprecipitation and GST pull-down assays. Mass spectrometry, in vitro kinase assays, ChIP-qPCR, flow cytometry, immunohistochemistry, immunofluorescence and confocal microscopy were performed to investigate the regulation of LATS1/2 on MHC-I through interaction with and phosphorylate STAT1. The killing effect of activated PBMCs on EC cells were used to monitor anti-tumor activity. Results Here, we demonstrate that LATS1/2 are frequently mutated and down-regulated in EC. Moreover, LATS1/2 loss was found to be associated with a significant down-regulation of MHC-I, independently of the Hippo-YAP pathway. Instead, LATS1/2 were found to directly interact with and phosphorylate STAT1 at Ser727, a crucial transcription factor for MHC-I upregulation in response to interferon-gamma (IFN-γ) signaling, to promote STAT1 accumulating and moving into the nucleus to enhance the transcriptional activation of IRF1/NLRC5 on MHC-I. Additionally, the loss of LATS1/2 was observed to confer increased resistance of EC cells to immune cell-mediated killing and this resistance could be reversed by over-expression of MHC-I. Conclusion Our findings indicate that dysregulation of LATS1/2 in EC leads to immune evasion through the down-regulation of MHC-I, leading to the suppression of infiltrating activated CD8 + T cells and highlight the importance of LATS1/2 in IFN-γ signaling-mediated tumor immune response, suggesting that LATS1/2 is a promising target for immune checkpoint blockade therapy in EC.

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

Abstract Background Driver genes play a vital role in the development of cancer. Identifying driver genes is critical for diagnosing and understanding cancer. However, challenges remain in identifying personalized driver genes due to tumor heterogeneity of cancer. Although many computational methods have been developed to solve this problem, few efforts have been undertaken to explore gene-patient associations to identify personalized driver genes. Results Here we propose a method called LPDriver to identify personalized cancer driver genes by employing linear neighborhood propagation model on individual genetic data. LPDriver builds personalized gene network based on the genetic data of individual patients, extracts the gene-patient associations from the bipartite graph of the personalized gene network and utilizes a linear neighborhood propagation model to mine gene-patient associations to detect personalized driver genes. The experimental results demonstrate that as compared to the existing methods, our method shows competitive performance and can predict cancer driver genes in a more accurate way. Furthermore, these results also show that besides revealing novel driver genes that have been reported to be related with cancer, LPDriver is also able to identify personalized cancer driver genes for individual patients by their network characteristics even if the mutation data of genes are hidden. Conclusions LPDriver can provide an effective approach to predict personalized cancer driver genes, which could promote the diagnosis and treatment of cancer. The source code and data are freely available at https://github.com/hyr0771/LPDriver .

Abstract Anoikis resistance, a notable factor in osteosarcoma, plays a significant role in tumor invasion and metastasis. This study seeks to identify a distinct gene signature that is specifically associated with the anoikis subcluster in osteosarcoma. Clinical, single-cell, and transcriptional data from TARGET and GEO datasets were used to develop a gene signature for osteosarcoma based on the anoikis subcluster. Univariate Cox and LASSO regression analyses were employed. The signature's predictive value was evaluated using time-dependent ROC and Kaplan–Meier analyses. Functional enrichment analyses and drug sensitivity analyses were conducted. Validation of three modular genes was performed using RT-qPCR and Western blotting. Signature (ZNF583, CGNL1, CXCL13) was developed to predict overall survival in osteosarcoma patients, targeting the anoikis subcluster. The signature demonstrated good performance in external validation. Stratification based on the signature revealed significantly different prognoses. The signature was an independent prognostic factor. The low-risk group showed enhanced immune cell infiltration and improved immune function. Drug sensitivity analysis indicated efficacy of chemotherapy agents. Prognostic nomograms incorporating the signature provided greater predictive accuracy and clinical utility. Signatures related to the anoikis subcluster play a significant role in osteosarcoma progression. Incorporating these findings into clinical decision-making can improve osteosarcoma treatment and patient outcomes.

Abstract Silicon suboxide (SiOx, x ≈ 1) is promising in serving as an anode material for lithium‐ion batteries with high capacity, but it has a low initial Coulombic efficiency (ICE) due to the irreversible formation of lithium silicates during the first cycle. In this work, we modify SiOx by solid‐phase Mg doping reaction using low‐cost Mg powder as a reducing agent. We show that Mg reduces SiO2 in SiOx to Si and forms MgSiO3 or Mg2SiO4. The MgSiO3 or Mg2SiO4 are mainly distributed on the surface of SiOx, which suppresses the irreversible lithium‐ion loss and enhances the ICE of SiOx. However, the formation of MgSiO3 or Mg2SiO4 also sacrifices the capacity of SiOx. Therefore, by controlling the reaction process between Mg and SiOx, we can tune the phase composition, proportion, and morphology of the Mg‐doped SiOx and manipulate the performance. We obtain samples with a capacity of 1226 mAh g–1 and an ICE of 84.12%, which show significant improvement over carbon‐coated SiOx without Mg doping. By the synergistical modification of both Mg doping and prelithiation, the capacity of SiOx is further increased to 1477 mAh g–1 with a minimal compromise in the ICE (83.77%).

The pore architecture of porous scaffolds is a critical factor in osteogenesis, but it is a challenge to precisely configure strut-based scaffolds because of the inevitable filament corner and pore geometry deformation. This study provides a pore architecture tailoring strategy in which a series of Mg-doped wollastonite scaffolds with fully interconnected pore networks and curved pore architectures called triply periodic minimal surfaces (TPMS), which are similar to cancellous bone, are fabricated by a digital light processing technique. The sheet-TPMS pore geometries (s-Diamond, s-Gyroid) contribute to a 3‒4-fold higher initial compressive strength and 20%–40% faster Mg-ion-release rate compared to the other-TPMS scaffolds, including Diamond, Gyroid, and the Schoen's I-graph-Wrapped Package (IWP) in vitro. However, we found that Gyroid and Diamond pore scaffolds can significantly induce osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). Analyses of rabbit experiments in vivo show that the regeneration of bone tissue in the sheet-TPMS pore geometry is delayed; on the other hand, Diamond and Gyroid pore scaffolds show notable neo-bone tissue in the center pore regions during the early stages (3–5 weeks) and the bone tissue uniformly fills the whole porous network after 7 weeks. Collectively, the design methods in this study provide an important perspective for optimizing the pore architecture design of bioceramic scaffolds to accelerate the rate of osteogenesis and promote the clinical translation of bioceramic scaffolds in the repair of bone defects.

Nanocellulose has various outstanding properties and great potential for replacing petrochemical products. The utilization of lignocellulose to produce nanocellulose is of great significance to the sustainable development of the economy and society. However, the direct extraction of nanocellulose from lignocellulose by chemical method is challenged by toxic chemicals utilization, energy and time consumption, and waste water generation. Therefore, this paper addressed the conversion of lignocellulosic biomass into bacterial nanocellulose (BNC) by the biological method. Moreover, this article highlights the recent advances in potentials and challenges of lignocellulosic biomass for BNC production through the bioconversion process, including biomass pretreatment, enzymatic hydrolysis, glucose and xylose fermentation, GA accumulation, and inhibitor tolerant. The development in metabolic and evolutionary engineering to enhance the production capacity of BNC-producing strain is also discussed. It is expected to provide guidance on the effective bioproduction of nanocellulose from lignocellulosic biomass.

Background: Idiopathic pulmonary fibrosis (IPF) is a type of interstitial lung disease characterized by unknown causes and a poor prognosis. Recent research indicates that age-related mechanisms, such as cellular senescence, may play a role in the development of this condition. However, the relationship between cellular senescence and clinical outcomes in IPF remains uncertain. Methods: Data from the GSE70867 database were meticulously analyzed in this study. The research employed differential expression analysis, as well as univariate and multivariate Cox regression analysis, to pinpoint senescence-related genes (SRGs) linked to prognosis and construct a prognostic risk model. The model’s clinical relevance and its connection to potential biological processes were systematically assessed in training and testing datasets. Additionally, the expression location of prognosis-related SRGs was identified through immunohistochemical staining, and the correlation between SRGs and immune cell infiltration was deduced using the GSE28221 dataset. Result: The prognostic risk model was constructed based on five SRGs (cellular communication network factor 1, CYR61, stratifin, SFN, megakaryocyte-associated tyrosine kinase, MATK, C-X-C motif chemokine ligand 1, CXCL1, LIM domain, and actin binding 1, LIMA1). Both Kaplan-Meier (KM) curves (p = 0.005) and time-dependent receiver operating characteristic (ROC) analysis affirmed the predictive accuracy of this model in testing datasets, with respective areas under the ROC curve at 1-, 2-, and 3-years being 0.721, 0.802, and 0.739. Furthermore, qRT-RCR analysis and immunohistochemical staining verify the differential expression of SRGs in IPF samples and controls. Moreover, patients in the high-risk group contained higher infiltration levels of neutrophils, eosinophils, and M1 macrophages in BALF, which appeared to be independent indicators of poor prognosis in IPF patients. Conclusion: Our research reveals the effectiveness of the 5 SRGs model in BALF for risk stratification and prognosis prediction in IPF patients, providing new insights into the immune infiltration of IPF progression.

Online demand prediction plays an important role in transport network services from operations, controls to management, and information provision. However, the online prediction models are impacted by streaming data quality issues with noise measurements and missing data. To address these, we develop a robust prediction method for online network-level demand prediction in public transport. It consists of a PCA method to extract eigen demand images and an optimization-based pattern recognition model to predict the weights of eigen demand images by making use of the partially observed real-time data up to the prediction time in a day. The prediction model is robust to data quality issues given that the eigen demand images are stable and the predicted weights of them are optimized using the network level data (less impacted by local data quality issues). In the case study, we validate the accuracy and transferability of the model by comparing it with benchmark models and evaluate the robustness in tolerating data quality issues of the proposed model. The experimental results demonstrate that the proposed Pattern Recognition Prediction based on PCA (PRP-PCA) consistently outperforms other benchmark models in accuracy and transferability. Moreover, the model shows high robustness in accommodating data quality issues. For example, the PRP-PCA model is robust to missing data up to 50% regardless of the noise level. We also discuss the hidden patterns behind the network level demand. The visualization analysis shows that eigen demand images are significantly connected to the network structure and station activity variabilities. Though the demand changes dramatically before and after the pandemic, the eigen demand images are consistent over time in Stockholm.

[Introduction] To achieve the "carbon peak and neutrality" goals, the ways for enterprise energy conservation and emission reduction need to fully explored, and the green and low-carbon policy tools should be fully exploited. Green hydrogen, as a clean energy, has become the key to social low-carbon transition thanks to its full link zero carbon emission. Carbon emission rights trading market is a key policy tool to control and reduce carbon emissions by making use of the market-oriented mechanism. Building a carbon trading center hydrogen energy industry trading mechanism to achieve the coupling of carbon trading and hydrogen energy will greatly promote the achieving of the "carbon peak and neutrality" goals. [Method] Based on this, a coupling mechanism of "green hydrogen market - national carbon trading market - electricity market" was built in this paper. The "green hydrogen market - national carbon trading market - electricity market" was modeled and simulated by further utilizing the system dynamics method, and the interaction of multiple markets was studied. [Result] The results show that: Firstly, the coupling among the green hydrogen market, carbon trading market and electricity market can be realized through green hydrogen certification and carbon quota trading, and it is found that the coupling model is feasible through simulation. Secondly, it is found through the simulation of the basic scenario that the coupling of multiple markets can stimulate the increase of carbon price and control the increase of thermal power generation and green hydrogen production. Finally, increasing the proportion of green hydrogen certification and improving the obsolete unit elimination mechanism and carbon quota auction mechanism will help form a carbon pricing mechanism. [Conclusion] On the one hand, this study diversifies the green hydrogen trading models, promotes the participation of green hydrogen in carbon trading to obtain certain benefits, and reduces the hydrogen energy cost. On the other hand, it makes use of the multi-market linkage mechanism to bring into play the forced effect of carbon price and promote the reduction of the proportion of traditional fossil hydrogen production and thermal power generation.

Establishing the relationship between thermal cycling and the induced evolution of microstructures and cladding layer properties is crucial to achieving microstructural and performance control, given the complexity involved in high-speed laser cladding process. We hereby report our new findings from laser cladding of Inconel 625 on Q245R steel substrate using a high-speed laser cladding technique. The microstructure evolution and microhardness variations in the first cladding track with different thermal cycles were examined by XRD, SEM, EBSD, TEM, and microhardness tests in detail. Numerical simulation was also conducted to characteristically illustrate the complex thermal cycles during the laser cladding process. Our work revealed that the first six thermal cycles resulted in significant variations of microstructure in the laser cladding layers. The dislocation density and low angle grain boundaries (LAGBs) of the first cladding track decreased after two thermal cycles due to the high peak temperature (above 1000 °C) of thermal cycles and subsequently increased when subjected to further thermal cycles with low peak temperature (below 500 °C). The microhardness value increased from 220 HV0.2 to 320 HV0.2, mainly caused by the formation of precipitated phase during the first four thermal cycles, and through by the enhancement of dislocations after six thermal cycles.

Ultra-high-speed laser cladding (UHSLC) is an effective way to deposit Inconel 625 coatings on 27SiMn steel to prolong its service life. However, elemental segregation in the Inconel 625 coatings is serious and high-speed laser remelting (HSLR) was investigated in order to tackle the issue. The HSLR treatment was also found to reduce the surface roughness of UHSLC Inconel 625 laser cladding significantly, while enhancing their wear resistance. Furthermore, finite element simulation suggests that a higher remelting power may result in a better melt pool fluidity and a more uniform composition distribution.

Given the complexity of biological samples and the trace nature of target materials in forensic trace analysis, a simple and effective method is needed to obtain sufficient target materials from complex substrates. Magnetic nanoparticles （MNPs） have shown a wide range of application value in many research fields, such as biomedicine, drug delivery and separation, due to their unique superparamagnetic properties, stable physical and chemical properties, biocompatibility, small size, high specific surface area and other characteristics. To apply MNPs in the pretreatment of forensic materials, maximize the extraction rate of the target materials, and minimize interference factors to meet the requirements of trace analysis of the target materials, this paper reviews the application of MNPs in the fields of forensic toxicological analysis, environmental forensic science, trace evidence analysis and criminal investigation in recent years, and provides research ideas for the application of MNPs in forensic trace analysis.

Abstract Background Many deep-sea invertebrates largely depend on chemoautotrophic symbionts for energy and nutrition, and some of them have reduced functional digestive tracts. By contrast, deep-sea mussels have a complete digestive system although symbionts in their gills play vital roles in nutrient supply. This digestive system remains functional and can utilise available resources, but the roles and associations among gut microbiomes in these mussels remain unknown. Specifically, how the gut microbiome reacts to environmental change is unclear. Results The meta-pathway analysis showed the nutritional and metabolic roles of the deep-sea mussel gut microbiome. Comparative analyses of the gut microbiomes of original and transplanted mussels subjected to environmental change revealed shifts in bacterial communities. Gammaproteobacteria were enriched, whereas Bacteroidetes were slightly depleted. The functional response for the shifted communities was attributed to the acquisition of carbon sources and adjusting the utilisation of ammonia and sulphide. Self-protection was observed after transplantation. Conclusion This study provides the first metagenomic insights into the community structure and function of the gut microbiome in deep-sea chemosymbiotic mussels and their critical mechanisms for adapting to changing environments and meeting of essential nutrient demand.

Abstract Background Genomic structural variant detection is a significant and challenging issue in genome analysis. The existing long-read based structural variant detection methods still have space for improvement in detecting multi-type structural variants. Results In this paper, we propose a method called cnnLSV to obtain detection results with higher quality by eliminating false positives in the detection results merged from the callsets of existing methods. We design an encoding strategy for four types of structural variants to represent long-read alignment information around structural variants into images, input the images into a constructed convolutional neural network to train a filter model, and load the trained model to remove the false positives to improve the detection performance. We also eliminate mislabeled training samples in the training model phase by using principal component analysis algorithm and unsupervised clustering algorithm k-means. Experimental results on both simulated and real datasets show that our proposed method outperforms existing methods overall in detecting insertions, deletions, inversions, and duplications. The program of cnnLSV is available at https://github.com/mhuidong/cnnLSV . Conclusions The proposed cnnLSV can detect structural variants by using long-read alignment information and convolutional neural network to achieve overall higher performance, and effectively eliminate incorrectly labeled samples by using the principal component analysis and k-means algorithms in training model stage.

In the Sichuan Basin, geologic conditions are complex in deep layers. Burial depth of shale reservoirs is high. Gas well productivity is widespread low, and hydraulic fracturing confronts with extremely large challenges. In order to search for "engineering sweet spots" of deep shale gas layers, Yongchuan and Dingshan areas were taken as the examples. In-depth discussion was conducted on affecting factors of hydraulic fracturing results in deep shale reservoirs by drilling, core, imaging logging and seismic data, based on measured rock mechanical parameters, development degree of natural fractures, natural fracture effectiveness, horizontal stress difference and included angle between horizontal well track and the minimum main horizontal stress. Study results demonstrated that No.31 sublayer of the first member of Longmaxi Formation in Yongchuan and Dingshan areas, southern Sichuan had the best brittleness as the first-choice target horizon for hydraulic fracturing. Shorter distance from the faults, higher pump pressure and operational pressure, and smaller reconstructed volume. Good extension and turning capacity of the fractures could beguaranteed when included angle between hydraulic and natural fractures was roughly 55°. In silicon-rich shale and faulting zones, lower minimum main horizontal stress, easier-diffused hydraulic fractures. Higher included angle between horizontal well track and maximum main horizontal stress azimuth, better fracturing results. Finally, evaluation index system of "engineering sweet spots" for marine shale gas in complex structural areas of Yongchuan and Dingshan was constructed. Class Ⅰ geologic and engineering "sweet spots" were optimized in Yongchuan and Dingshan areas.

To solve the problem that existing algorithms were difficult to effectively identify sensitive sequences in genomic data for long-read with high error rate, a recognition algorithm using hybrid CPU and GPU parallel computing, called CGPU-F3SR, was proposed.Firstly, the long-read in genomic data were partitioned into multiple short-read, and the Bloom filtering mechanism was used to avoid repeated calculation of the short-read.Secondly, the k-mer coding strategy was used to extract in parallel the error information of all short-read, the recognition accuracy was promoted by improving the sequence similarity calculation model.Finally, CPU and GPU were used to coordinate and parallel to accelerate the calculation of short-read similarity to improve recognition efficiency.As a result, both two types of sensitive sequences including short tandem repeats and disease related sequences could be identified efficiently and accurately from genome data for long-read with high error rate.The experimental results of recognizing sensitive sequences from genomic data for long-read with length 100～400 kbp each show that, compared with existing parallel algorithm, the average recognition accuracy and precision rate of proposed CPU/GPU parallel algorithm CGPU-F3SR are increased by 7.77% and 43.07% respectively, its average false positive rate is reduced by 7.41%, and its average recognition throughput is increased by 2.44 times.

IntroductionAnti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a common autoimmune encephalitis, and it is associated with psychosis, dyskinesia, and seizures. Anti-NMDAR encephalitis (NMDARE) in juveniles and adults presents different clinical charactreistics. However, the pathogenesis of juvenile anti-NMDAR encephalitis remains unclear, partly because of a lack of suitable animal models.MethodsWe developed a model of juvenile anti-NMDAR encephalitis using active immunization with an amino terminal domain peptide from the GluN1 subunit (GluN1356 − 385) against NMDARs in 3-week-old female C57BL/6J mice.ResultsImmunofluorescence staining suggested that autoantibody levels in the hippocampus increased, and HEK-293T cells staining identified the target of the autoantibodies as GluN1, suggesting that GluN1-specific immunoglobulin G was successfully induced. Behavior assessment showed that the mice suffered significant cognition impairment and sociability reduction, which is similar to what is observed in patients affected by anti-NMDAR encephalitis. The mice also exhibited impaired long-term potentiation in hippocampal CA1. Pilocarpine-induced epilepsy was more severe and had a longer duration, while no spontaneous seizures were observed.ConclusionThe juvenile mouse model for anti-NMDAR encephalitis is of great importance to investigate the pathological mechanism and therapeutic strategies for the disease, and could accelerate the study of autoimmune encephalitis.

The exploration of catalysts for the oxygen evolution reaction (OER) with high activity and acceptable price is essential for water splitting to hydrogen generation. High-entropy materials (HEMs) have aroused increasing interest in the field of electrocatalysis due to their unusual physicochemical properties. In this work, we reported a novel FeCoNiMoZn-OH high entropy hydroxide (HEH)/nickel foam (NF) synthesized by a facile pulsed electrochemical deposition method at room temperature. The FeCoNiMoZn-OH HEH displays a 3D porous nanosheet morphology and polycrystalline structure, which exhibits extraordinary OER activity in alkaline media, including much lower overpotential (248 mV at 10 mA cm−2) and Tafel slope (30 mV dec−1). Furthermore, FeCoNiMoZn-OH HEH demonstrates excellent OER catalytic stability. The enhanced catalytic performance of the FeCoNiMoZn-OH HEH primarily contributed to the porous morphology and the positive synergistic effect between Mo and Zn. This work provides a novel insight into the design of HEMs in catalytic application.

Background: As a dedifferentiated tumor, small cell endometrial neuroendocrine tumors (NETs) are rare and frequently diagnosed at an advanced stage with a poor prognosis. Current treatment recommendations are often extrapolated from histologically similar tumors in other sites or based on retrospective studies. The exploration for diagnostic and therapeutic markers in small cell NETs is of great significance. Methods: In this study, we conducted single-cell RNA sequencing on a specimen obtained from a patient diagnosed with small cell endometrial neuroendocrine carcinoma (SCNEC) based on pathology. We revealed the cell map and intratumoral heterogeneity of the cancer cells through data analysis. Further, we validated the function of ISL LIM Homeobox 1 (ISL1) in vitro in an established neuroendocrine cell line. Finally, we examined the association between ISL1 and tumor staging in small cell lung cancer (SCLC) patient samples. Results: We observed the significant upregulation of ISL1 expression in tumor cells that showed high expression of the neuroepithelial markers. Additionally, in vitro cell function experiments demonstrated that the high ISL1 expression group exhibited markedly higher cell proliferation and migration abilities compared to the low expression group. Finally, we showed that the expression level of ISL1 was correlated with SCLC stages. Conclusions: ISL1 protein in NETs shows promise as a potential biomarker for diagnosis and treatment.

Virtual synchronous generator control (VSG) is an attractive method for the grid-tied inverter to provide inertia and frequency support. However, it brings some troubles on DC-link voltage control when it is applied to two-stage photovoltaic (PV) power generation. This study proposes a DC-Side synchronous active power Control for two-stage photovoltaic (PV) power generation without energy storage. Synchronous active power Control is applied to DC–DC converters, while the grid-tied inverter still maintains the DC-link voltage constant. The DC–DC converters flexibly regulate active power to provide the simultaneous inertial and primary frequency response like a synchronous generator. A simple sensorless iterative maximum power estimation method is introduced and integrated into the DC-side VSG strategy. It can estimate a rough MAP based on one sample point and converge to an accurate value along with the VSG control. The effectiveness and advantages of the control strategy are validated through case studies on an islanded microgrid that included PV generations with a DC-bus collection system. The results show that the proposed strategy significantly improves the frequency nadir and the steady frequency and maintains DC-link voltage stability during irradiance change conditions.

Abstract A metal electrode is a significant component of a zinc–air battery (ZAB), but the metal material is usually not elastic, which severely restricts the application of flexible and stretchable ZABs in the field of wearable electronic devices. Herein, we report a flexible and stretchable metal‐coated textile prepared by a dynamic stretching–electroplating based on a wavy spandex textile substrate. Benefiting from the unique woven and wavy structure, the metal‐coated textile shows a high stretchability of 100% and stable conductivity. In situ scanning electron microscope observation during stretching showed that the tensile strain of the metal‐coated textile is mainly attributed to the deformation of the microfiber network at the bottom position of the wave structure. In addition, a sodium carboxymethyl cellulose–polyacrylic acid–potassium hydroxide composite hydrogel has been used as the electrolyte. This hydrogel shows excellent ionic conductivity, mechanical properties, and water retention properties, which makes it suitable for the semi‐open system of ZAB. Furthermore, a flexible and stretchable sandwich‐structure ZAB, assembled using the above‐mentioned electrodes and electrolyte, operates stably even under rapid stretching/releasing cycle deformation. Because of its facile preparation and low cost, this flexible and stretchable ZAB is suitable for fabrication of large‐area batteries to obtain higher output current and power to drive wearable electronic devices.

BackgroundImmunoglobulin A nephropathy (IgAN) is one of the most common kidney diseases leading to renal injury. Of pediatric cases, 25%–30% progress into end-stage kidney disease (ESKD) in 20–25 years. Therefore, predicting and intervening in IgAN at an early stage is crucial. The purpose of this study was to validate the availability of an international predictive tool for childhood IgAN in a cohort of children with IgAN treated at a regional medical centre.MethodsAn external validation cohort of children with IgAN from medical centers in Southwest China was formed to validate the predictive performance of the two full models with and without race differences by comparing four measures: area under the curve (AUC), the regression coefficient of linear prediction (PI), survival analysis curves for different risk groups, and R2D.ResultsA total of 210 Chinese children, including 129 males, with an overall mean age of 9.43 ± 2.71 years, were incorporated from this regional medical center. In total, 11.43% (24/210) of patients achieved an outcome with a GFR decrease of more than 30% or reached ESKD. The AUC of the full model with race was 0.685 (95% CI: 0.570–0.800) and the AUC of the full model without race was 0.640 (95% CI: 0.517–0.764). The PI of the full model with race and without race was 0.816 (SE = 0.006, P

The pore morphology design of bioceramic scaffolds plays a substantial role in the induction of bone regeneration. Specifically, the effects of different scaffold pore geometry designs on angiogenesis and new bone regeneration remain unclear. Therefore, we fabricated Mg/Sr co-doped wollastonite bioceramic (MS-CSi) scaffolds with three different pore geometries (gyroid, cylindrical, and cubic) and compared their effects on osteogenesis and angiogenesis in vitro and in vivo. The MS-CSi scaffolds were fabricated by digital light processing (DLP) printing technology. The pore structure, mechanical properties, and degradation rate of the scaffolds were investigated. Cell proliferation on the scaffolds was evaluated using CCK-8 assays while angiogenesis was assessed using Transwell migration assays, tube formation assays, and immunofluorescence staining. The underlying mechanism was explored by western blotting. Osteogenic ability of scaffolds was evaluated by alkaline phosphatase (ALP) staining, western blotting, and qRT-PCR. Subsequently, a rabbit femoral defect model was prepared to compare differences in the scaffolds in osteogenesis and angiogenesis in vivo. Cell culture experiments showed that the gyroid pore scaffold downregulated YAP/TAZ phosphorylation and enhanced YAP/TAZ nuclear translocation, thereby promoting proliferation, migration, tube formation, and high expression of CD31 in human umbilical vein endothelial cells (HUVECs) while strut-based (cubic and cylindrical pore) scaffolds promoted osteogenic differentiation in bone marrow mesenchymal stem cells and upregulation of osteogenesis-related genes. The gyroid pore scaffolds were observed to facilitate early angiogenesis in the femoral-defect model rabbits while the strut-based scaffolds promoted the formation of new bone tissue. Our study indicated that the pore geometries and pore curvature characteristics of bioceramic scaffolds can be precisely tuned for enhancing both osteogenesis and angiogenesis. These results may provide new ideas for the design of bioceramic scaffolds for bone regeneration.