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Abstract Alkylamine structures represent one of the most functional and widely used in organic synthesis and drug design. However, the general methods for the functionalization of the shielded and deshielded alkyl radicals remain elusive. Here, we report a general deoxygenative amination protocol using alcohol-derived carbazates and nitrobenzene under electrochemical conditions. A range of primary, secondary, and tertiary alkylamines are obtained. This practical procedure can be scaled up through electrochemical continuous flow technique.

Abstract Recently, environmental temperature has been shown to regulate bone homeostasis. However, the mechanisms by which cold exposure affects bone mass remain unclear. In our present study, we observed that exposure to cold temperature (CT) decreased bone mass and quality in mice. Furthermore, a transplant of exosomes derived from the plasma of mice exposed to cold temperature (CT-EXO) can also impair the osteogenic differentiation of BMSCs and decrease bone mass by inhibiting autophagic activity. Rapamycin, a potent inducer of autophagy, can reverse cold exposure or CT-EXO-induced bone loss. Microarray sequencing revealed that cold exposure increases the miR-25-3p level in CT-EXO. Mechanistic studies showed that miR-25-3p can inhibit the osteogenic differentiation and autophagic activity of BMSCs. It is shown that inhibition of exosomes release or downregulation of miR-25-3p level can suppress CT-induced bone loss. This study identifies that CT-EXO mediates CT-induced osteoporotic effects through miR-25-3p by inhibiting autophagy via targeting SATB2, presenting a novel mechanism underlying the effect of cold temperature on bone mass.

This study explores the potential of Artificial Intelligence (AI) in early screening and prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners. Despite the promising opportunities, challenges such as diverse diagnostic evidence, complex etiology, and interdisciplinary knowledge integration impede the interpretability, reliability, and applicability of AI-based DED detection methods. The research conducts a comprehensive review of datasets, diagnostic evidence, and standards, as well as advanced algorithms in AI-based DED detection over the past five years. The DED diagnostic methods are categorized into three groups based on their relationship with AI techniques: (1) those with ground truth and/or comparable standards, (2) potential AI-based methods with significant advantages, and (3) supplementary methods for AI-based DED detection. The study proposes suggested DED detection standards, the combination of multiple diagnostic evidence, and future research directions to guide further investigations. Ultimately, the research contributes to the advancement of ophthalmic disease detection by providing insights into knowledge foundations, advanced methods, challenges, and potential future perspectives, emphasizing the significant role of AI in both academic and practical aspects of ophthalmology.

Abstract Necroptosis is a lytic form of regulated cell death reported to contribute to inflammatory diseases of the gut, skin and lung, as well as ischemic-reperfusion injuries of the kidney, heart and brain. However, precise identification of the cells and tissues that undergo necroptotic cell death in vivo has proven challenging in the absence of robust protocols for immunohistochemical detection. Here, we provide automated immunohistochemistry protocols to detect core necroptosis regulators – Caspase-8, RIPK1, RIPK3 and MLKL – in formalin-fixed mouse and human tissues. We observed surprising heterogeneity in protein expression within tissues, whereby short-lived immune barrier cells were replete with necroptotic effectors, whereas long-lived cells lacked RIPK3 or MLKL expression. Local changes in the expression of necroptotic effectors occurred in response to insults such as inflammation, dysbiosis or immune challenge, consistent with necroptosis being dysregulated in disease contexts. These methods will facilitate the precise localisation and evaluation of necroptotic signaling in vivo.

Glucagon-like peptide-1 (GLP-1) is a 30-amino acid peptide hormone that is mainly expressed in the intestine and hypothalamus. In recent years, basic and clinical studies have shown that GLP-1 is closely related to lipid metabolism, and it can participate in lipid metabolism by inhibiting fat synthesis, promoting fat differentiation, enhancing cholesterol metabolism, and promoting adipose browning. GLP-1 plays a key role in the occurrence and development of metabolic diseases such as obesity, nonalcoholic fatty liver disease, and atherosclerosis by regulating lipid metabolism. It is expected to become a new target for the treatment of metabolic disorders. The effects of GLP-1 and dual agonists on lipid metabolism also provide a more complete treatment plan for metabolic diseases. This article reviews the recent research progress of GLP-1 in lipid metabolism.

Abstract Background To establish a method to induce Campylobacter jejuni colonization in the intestines of C57BL/6 mice through antibiotic-induced microbiome depletion. Results Fifty-four female C57BL/6 mice were divided into the normal, control, and experimental groups. The experimental group was administered intragastric cefoperazone sodium and sulbactam sodium (50 mg/mL) for 2 days; then, the experimental and control mice were intragastrically administered 200 µL C. jejuni, which was repeated once more after 2 days. Animal feces were collected, and the HipO gene of C. jejuni was detected using TaqMan qPCR from day 1 to day 14 after modeling completion. Immunofluorescence was used to detect intestinal C. jejuni colonization on day 14, and pathological changes were observed using hematoxylin and eosin staining. Additionally, 16S rDNA analyses of the intestinal contents were conducted on day 14. In the experimental group, C. jejuni was detected in the feces from days 1 to 14 on TaqMan qPCR, and immunofluorescence-labeled C. jejuni were visibly discernable in the intestinal lumen. The intestinal mucosa was generally intact and showed no significant inflammatory-cell infiltration. Diversity analysis of the colonic microbiota showed significant inter-group differences. In the experimental group, the composition of the colonic microbiota differed from that in the other 2 groups at the phylum level, and was characterized by a higher proportion of Bacteroidetes and a lower proportion of Firmicutes. Conclusions Microbiome depletion induced by cefoperazone sodium and sulbactam sodium could promote long-term colonization of C. jejuni in the intestines of mice.

Abstract Macroautophagy is a process that cells engulf cytosolic materials by autophagosomes and deliver them to lysosomes for degradation. The biogenesis of autophagosomes requires ATG2 as a lipid transfer protein to transport lipids from existing membranes to phagophores. It is generally believed that endoplasmic reticulum is the main source for lipid supply of the forming autophagosomes; whether ATG2 can transfer lipids from other organelles to phagophores remains elusive. In this study, we identified a new ATG2A-binding protein, ANKFY1. Depletion of this endosome-localized protein led to the impaired autophagosome growth and the reduced autophagy flux, which largely phenocopied ATG2A/B depletion. A pool of ANKFY1 co-localized with ATG2A between endosomes and phagophores and depletion of UVRAG, ANKFY1 or ATG2A/B led to reduction of PI3P distribution on phagophores. Purified recombinant ANKFY1 bound to PI3P on membrane through its FYVE domain and enhanced ATG2A-mediated lipid transfer between PI3P-containing liposomes. Therefore, we propose that ANKFY1 recruits ATG2A to PI3P-enriched endosomes and promotes ATG2A-mediated lipid transfer from endosomes to phagophores. This finding implicates a new lipid source for ATG2A-mediated phagophore expansion, where endosomes donate PI3P and other lipids to phagophores via lipid transfer.

Objective: This study utilized network meta-analysis (NMA) to compare the efficacy of five commonly used traditional Chinese medicine monomers in reducing intimal hyperproliferation in arterial balloon injury models. Methods: Relevant literature up to January 2024 was systematically retrieved from seven major databases. The intima-to-media (I/M) ratio was chosen as the primary outcome measure. The risk of bias in animal studies was assessed using the SYstematic Review Centre for Laboratory Animal Experimentation (SYRCLE) tool. Statistical analysis was conducted using Stata 17 software. Results: A total of 43 studies were included in this meta-analysis. NMA results showed that in the rat model, compared to the control group, GS (SMD: 0.99, 95%CI: 1.25 to −0.73), ASIV (SMD: 1.16, 95%CI: 1.65 to −0.67), TMP (SMD: 0.68, 95%CI: 1.31 to −0.05), and TPNS (SMD: 1.36, 95%CI: 1.91 to −0.80) exhibited inhibitory effects on postoperative intimal hyperproliferation, reducing the I/M ratio. In the rabbit model, compared to the control group, TPNS (SMD: 1.23, 95%CI: 1.97 to −0.49) inhibited postoperative intimal hyperproliferation and reduced the I/M ratio. Superiority ranking analysis suggested that total Panax notoginseng saponin (TPNS) might be the most effective traditional Chinese medicine monomer in reducing intimal hyperproliferation in arterial balloon injury models, lowering the I/M ratio. Conclusion: NMA indicates that traditional Chinese medicine monomers can effectively reduce postoperative intimal hyperproliferation in arterial balloon injury models, lowering the I/M ratio, with TPNS showing optimal efficacy. However, the research on TIIA is insufficient, and the limited sample size may affect the robustness of the results. Furthermore, the majority of research on traditional Chinese medicine monomers is currently limited to the experimental stage, lacking further clinical validation. Conducting standardized animal experiments and reporting their findings can enhance the quality of evidence from animal studies, laying the foundation for future clinical trials.

Summary: Leptomeningeal metastases (LMs) remain a devastating complication of non-small cell lung cancer (NSCLC), particularly following osimertinib resistance. We conducted single-cell RNA sequencing on cerebrospinal fluid (CSF) from EGFR-mutant NSCLC with central nervous system metastases. We found that macrophages of LMs displayed functional and phenotypic heterogeneity and enhanced immunosuppressive properties. A population of lipid-associated macrophages, namely RNASE1_M, were linked to osimertinib resistance and LM development, which was regulated by Midkine (MDK) from malignant epithelial cells. MDK exhibited significant elevation in both CSF and plasma among patients with LMs, with higher MDK levels correlating to poorer outcomes in an independent cohort. Moreover, MDK could promote macrophage M2 polarization with lipid metabolism and phagocytic function. Furthermore, malignant epithelial cells in CSF, particularly after resistance to osimertinib, potentially achieved immune evasion through CD47-SIRPA interactions with RNASE1_M. In conclusion, we revealed a specific subtype of macrophages linked to osimertinib resistance and LM development, providing a potential target to overcome LMs.

Abstract Ir(III) carbene complexes have been explored as one of the best blue phosphors for their high performance. Herein, the authors designed and synthesized a series of blue‐emitting Ir(III) phosphors (f‐ct9a–c), featuring fac‐coordinated cyano‐imidazo[4,5‐b]pyridin‐2‐ylidene cyclometalates. These Ir(III) complexes exhibit true‐blue emission with a peak maximum spanning 448–467 nm, with high photoluminescence quantum yields of 81–88% recorded in degassed toluene. Moreover, OLED devices bearing phosphors f‐ct9a and f‐ct9b deliver maximum external quantum efficiencies (EQEmax) of 25.9% and 30.3%, together with Commission Internationale de L'Eclairage (CIEx,y) coordinates of (0.157, 0.225) and (0.142, 0.169), respectively. Remarkably, the f‐ct9b‐based device displays an incredible EQE of 29.0% at 5000 cd·m−2. The hyper‐OLED device based on f‐ct9b and ν‐DABNA exhibits an EQEmax of 34.7% and CIEx,y coordinates of (0.122, 0.131), affirming high potentials in achieving efficient blue electroluminescence.

The 2H‐MoTe2 is a well‐known layered 2D semiconductor that is considered as a promising material for next‐generation microelectronic and optoelectronic devices. Te‐deficiency‐induced defective structures, like Te vacancy and mirror twin boundary (MTB), would be generated at elevated temperatures. However, the temperature‐dependent evolution of such defects and their influence on the macroscopic electrical transport property of 2H‐MoTe2 is unclear. Herein, the semiconductor–metal transition phenomenon in 2H‐MoTe2−x mediated by the evolving disordered MTB network with increasing Te deficiency is reported on. The samples are grown by molecular beam epitaxy, while the Te deficiency is tuned by post‐growth flash annealing in ultra‐high vacuum. Low‐temperature scanning tunneling microscope investigation discloses the medium‐range disorder evolution of the MTB network incorporated in the 2H‐MoTe2, which eventually transforms to an ordered metallic Mo5Te8 metastable phase. The scanning tunneling spectroscopy shows rich in‐gap states localized at the MTBs, which provide a conducting channel in the semiconductor. The ultra‐high vacuum in situ transport measurement shows a gradual decrease of resistance of the sample upon flash annealing from 50 to 480 °C, confirming the influence of Te deficiency on the transport property, which would play an essential role in the device performance and durability.

In this paper, an experimental and theoretical study on the uniaxial tensile behavior of a fiber-reinforced polymer (FRP) grid-engineered cementitious composite (ECC) composite layer is described. Based on the test parameters, including the ECC material properties, the ECC cross-sectional area and the FRP grid cross-sectional area, three groups of ECC specimens and six groups of composite layer specimens were tested to reveal their joint action mechanism and tensile behavior. The experimental results showed two failure modes: fibers were pulled off or pulled out in the ECC specimens, and in the composite layer specimens, part of the fiber bars in the FRP grid was pulled off. The stress–strain curves show three stages: the elastic stage, softening stage and hardening stage. Due to the reinforcement of the FRP grid, the ultimate stress of the composite layer increased significantly compared with that of the ECC specimens. The composite layer softening strain was primarily related to the ECC softening strain, and the ultimate strain was primarily related to the FRP grid fracture strain. Moreover, a three-stage model was proposed to predict the stressstrain relationship, exhibiting a higher prediction accuracy and smaller dispersion compared with the three existing models.

Generating novel molecules to satisfy specific properties is a challenging task in modern drug discovery, which requires the optimization of a specific objective based on satisfying chemical rules. Herein, we aim to optimize the properties of a specific molecule to satisfy the specific properties of the generated molecule. The Matched Molecular Pairs (MMPs), which contain the source and target molecules, are used herein, and logD and solubility are selected as the optimization properties. The main innovative work lies in the calculation related to a specific transformer from the perspective of a matrix dimension. Threshold intervals and state changes are then used to encode logD and solubility for subsequent tests. During the experiments, we screen the data based on the proportion of heavy atoms to all atoms in the groups and select 12365, 1503, and 1570 MMPs as the training, validation, and test sets, respectively. Transformer models are compared with the baseline models with respect to their abilities to generate molecules with specific properties. Results show that the transformer model can accurately optimize the source molecules to satisfy specific properties.

Abstract Background Cell-free DNA (cfDNA) contains a large amount of molecular information that can be used for multi-cancer early detection (MCED), including changes in epigenetic status of cfDNA, such as cfDNA fragmentation profile. The fragmentation of cfDNA is non-random and may be related to cfDNA methylation. This study provides clinical evidence for the feasibility of inferring cfDNA methylation levels based on cfDNA fragmentation patterns. We performed whole-genome bisulfite sequencing and whole-genome sequencing (WGS) on both healthy individuals and cancer patients. Using the information of whole-genome methylation levels, we investigated cytosine–phosphate–guanine (CpG) cleavage profile and validated the method of predicting the methylation level of individual CpG sites using WGS data. Results We conducted CpG cleavage profile biomarker analysis on data from both healthy individuals and cancer patients. We obtained unique or shared potential biomarkers for each group and built models accordingly. The modeling results proved the feasibility to predict the methylation status of single CpG sites in cfDNA using cleavage profile model from WGS data. Conclusion By combining cfDNA cleavage profile of CpG sites with machine learning algorithms, we have identified specific CpG cleavage profile as biomarkers to predict the methylation status of individual CpG sites. Therefore, methylation profile, a widely used epigenetic biomarker, can be obtained from a single WGS assay for MCED.

Abstract In vascular networks, the transport across different vessel walls regulates chemical compositions in blood over space and time. Replicating such trans-wall transport with spatial heterogeneity can empower synthetic fluidic systems to program fluid compositions spatiotemporally. However, it remains challenging as existing synthetic channel walls are typically impermeable or composed of homogeneous materials without functional heterogeneity. This work presents a vascular network-inspired fluidic system (VasFluidics), which is functionalizable for spatially different trans-wall transport. Facilitated by embedded three-dimensional (3D) printing, elastic, ultrathin, and semipermeable walls self-assemble electrostatically. Physicochemical reactions between fluids and walls are localized to vary the trans-wall molecules among separate regions, for instance, by confining solutions or locally immobilizing enzymes on the outside of channels. Therefore, fluid compositions can be regulated spatiotemporally, for example, to mimic blood changes during glucose absorption and metabolism. Our VasFluidics expands opportunities to replicate biofluid processing in nature, providing an alternative to traditional fluidics.

The principle and application of oil shale in-situ mining technology are reviewed. Oil shale is rich in resources and is an important supplement to petroleum and natural gas as a source of energy. Currently, ground retorting technology is the primary way to produce shale oil because of its elaborated processing method and equipment. However, this technology has several disadvantages such as low thermal efficiency, high environmental pollution and inability to exploit deeply buried oil shale. A novel method called oil shale in-situ mining technology is efficient and environmentally friendly. This technology can exploit deep oil shale while reducing pollution and greenhouse effect. Based on the data collected, this paper summarizes the development of global underground in-situ oil shale mining technology, introduces four heating transfer principles and mathematical models of conduction heating, convection heating, radiation heating and combustion heating, clarifies the process flow, as well as presents advantages and disadvantages of different technologies. It provides a reference for the research of oil shale in-situ mining technology, and also looks into the technologyâs prospects for industrialization, integrating with greenization, information and intelligence.

Abstract Background Despite major advancements, effective treatment for patients with SMARCB1-deficient cancers has remained elusive. Here, we report the first case of a SMARCB1-deficient undifferentiated carcinoma in the rectum expressing high PD-L1 and responding to a PD-1 inhibitor, as well as with low tumor mutation burden (TMB), proficient mismatch repair (MMR) and BRAF V600E mutation. Case presentation A 35-year-old man visited our hospital complaining of increased defecation frequency, bloody stools and weight loss of 3 kg for one month. Colonoscopy revealed an ulcerated and irregular mass approximately 8–12 cm from the anus. Surgical resection was performed. Histopathological findings revealed that the tumor cells had poor connectivity with each other; each cell had eosinophilic cytoplasm and a polymorphic nucleus. Brisk mitotic activity and necrosis were frequently observed in the tumor cells. Immunohistochemical examination showed that the tumor cells were negative for SMARCB1. The tumor proportion score (TPS) of PD-L1 (22C3) expression was 95%, and the combined positive score (CPS) was 100; the tumor was mismatch repair (MMR) proficient. Next-generation sequencing showed a low tumor mutation burden (TMB), as well as the BRAF V600E mutation. The final diagnosis was SMARCB1-deficient undifferentiated carcinoma. Chemotherapy was useless in this case. His tumor recurred during chemotherapy, and he then received targeted therapy with tirelizumab, an inhibitor of PD-1. At present, his general condition is good. A recent computed tomography (CT) scan showed that the tumor had disappeared, indicating that the immunotherapy was effective. Astonishingly, his most recent follow-up was in August, and his condition continued to improve with the tumor has disappeared. Conclusion SMARCB1‑deficient undifferentiated carcinoma in the rectum is extremely rare, and it has aggressive histological malignancy and poor progression. The observed response to PD-1 inhibitors suggests a role for prospective use of SMARCB1 alterations as a predictive marker for immune checkpoint blockade.

The increasing demand for immune cell applications, both in clinical settings and in research laboratories, has highlighted the critical need for cryopreservation (banking) methods for T cells. While conventional techniques such as freezing with liquid nitrogen remain prevalent, they pose significant challenges including high equipment costs, safety considerations, and logistical hurdles in transportation. Our cryopreservation medium, C80EZ®, represents a novel approach, leveraging biocompatible polysaccharides as cryoprotectants to enable safe storage at −80°C. This paper presents a comprehensive series of tests assessing the effectiveness of C80EZ® in shielding T cells from the detrimental effects of cryopreservation. Importantly, our findings demonstrate that C80EZ® not only ensures the survival of T cells, with a particular emphasis on preserving the CD8+ subsets, but also maintains their critical function in targeting and eliminating cancer cells.

Pseudouridine (Ψ), the most prevalent modified base in cellular RNAs, has been mapped to numerous sites not only in rRNAs, tRNAs, and snRNAs but also mRNAs. Although there have been multiple techniques to identify Ψs, due to the recent development of sequencing technologies some reagents are not compatible with the current sequencer. Here, we show the updated Pseudo-seq, a technique enabling the genome-wide identification of pseudouridylation sites with single-nucleotide precision. We provide a comprehensive description of Pseudo-seq, covering protocols for RNA isolation from human cells, library preparation, and detailed data analysis procedures. The methodology presented is easily adaptable to any cell or tissue type with high-quality mRNA isolation. It can be used for discovering novel pseudouridylation sites, thus constituting a crucial initial step toward understanding the regulation and function of this modification.

African swine fever (ASF) is a highly contagious and lethal viral disease that causes severe hemorrhagic fever in pigs. It keeps spreading around the world, posing a severe socioeconomic risk and endangering biodiversity and domestic food security. ASF first outbroke in China in 2018, and has spread to most provinces nationwide. Genotypes I and II ASF virus (ASFV) as the etiological pathogens have been found in China. In this study, three pairs of specific primers and probes targeting the ASFV B646L gene, F1055L gene, and E183L gene were designed to detect universal, genotype I, and genotype II strains, respectively. A triplex crystal digital PCR (cdPCR) was established on the basis of optimizing various reaction conditions. The assay demonstrated remarkably sensitive with low limits of detection (LODs) of 5.120, 4.218, 4.588 copies/reaction for B646L, F1055L, and E183L gene, respectively; excellent repeatability with 1.24–2.01% intra-assay coefficients of variation (CVs) and 1.32–2.53% inter-assay CVs; good specificity for only detection of genotypes I and II ASFV, without cross-reactivity with PCV2, PRV, SIV, PRRSV, PEDV, FMDV, and CSFV. The triplex cdPCR was used to test 1,275 clinical samples from Guangxi province of China, and the positivity rates were 5.05, 3.22, and 1.02% for genotype I, genotype II, and co-infection of genotypes I and II, respectively. These 1,275 clinical samples were also detected using a reported reference triplex real-time quantitative PCR (qPCR), and the agreements of detection results between these two methods were more than 98.98%. In conclusion, the developed triplex cdPCR could be used as a rapid, sensitive, and accurate method to detect and differentiate genotypes I and II strains of ASFV.

Abstract The multi-subunit homotypic fusion and vacuole protein sorting (HOPS) membrane-tethering complex is required for autophagosome-lysosome fusion in mammals, yet reconstituting the mammalian HOPS complex remains a challenge. Here we propose a “hook-up” model for mammalian HOPS complex assembly, which requires two HOPS sub-complexes docking on membranes via membrane-associated Rabs. We identify Rab39A as a key small GTPase that recruits HOPS onto autophagic vesicles. Proper pairing with Rab2 and Rab39A enables HOPS complex assembly between proteoliposomes for its tethering function, facilitating efficient membrane fusion. GTP loading of Rab39A is important for the recruitment of HOPS to autophagic membranes. Activation of Rab39A is catalyzed by C9orf72, a guanine exchange factor associated with amyotrophic lateral sclerosis and familial frontotemporal dementia. Constitutive activation of Rab39A can rescue autophagy defects caused by C9orf72 depletion. These results therefore reveal a crucial role for the C9orf72-Rab39A-HOPS axis in autophagosome-lysosome fusion.

The oxidation of benzylic alcohols is an important transformation in modern organic synthesis. A plethora of photoredox protocols have been developed to achieve the aerobic oxidation of alcohols into carbonyls. Recently, several groups described that ultraviolet (UV) or purple light can initiate the aerobic oxidation of benzylic alcohols in the absence of an external catalyst, and depicted different mechanisms involving the photoinduction of •O2− as a critical reactive oxygen species (ROS). However, based on comprehensive mechanistic investigations, including control experiments, radical quenching experiments, EPR studies, UV–vis spectroscopy, kinetics studies, and density functional theory calculations (DFT), we elucidate here that HOO•, which is released via the H2O2 elimination of α-hydroxyl peroxyl radicals [ArCR(OH)OO•], serves as the real chain carrier for the autocatalytic photooxidation of benzylic alcohols. The mechanistic ambiguities depicted in the precedent literature are clarified, in terms of the crucial ROS and its evolution, the rate-limiting step, and the primary radical cascade. This work highlights the necessity of stricter mechanistic analyses on UV-driven oxidative reactions that involve aldehydes’ (or ketones) generation.

The variant porcine epidemic diarrhea virus (PEDV) has caused considerable economic losses to the global pig industry since 2010. In this study, a total of 5859 diarrhea samples were collected from different pig farms in China’s Guangxi province during January 2020 and March 2024 and tested for PEDV using RT-qPCR. The positivity rate of PEDV was 11.90% (697/5859). Ninety-two PEDV-positive samples were selected based on sampling time, and the sampling region for amplification, sequencing, and analysis of the S1, M, and N genes. Phylogenetic analysis of the S1 gene revealed that all strains from Guangxi province were distributed in three subgroups, i.e., 81.5% (75/92) in the G2a subgroup, 4.3% (4/92) in the G2b subgroup, and 14.1% (13/92) in the G2c subgroup. The sequence analysis revealed that the S1 gene sequences from Guangxi province had higher homology with the variant strains than with the classical strains, showing as high as 99.2% with the variant strain AJ1102 and only 94.3% with the classical strain CV777. Recombination analysis revealed that the GX-BS08-2023 strain (G2c) from Guangxi province originated from inter-lineage recombination between the GX-BS09-2023 (G2a) and CH-JN547228-2011 (G1a) strains. In addition, the S1 gene of the G2a and G2b subgroup strains shared many mutations and insertions. There were common mutations of N143D and P235L in the G2a subgroup. Evolutionary analysis revealed that all Guangxi strains belonged to the G2 genotype. These strains have spread rapidly since the PEDV variant strains that emerged in 2010, weakened until 2021, and then remained stable. In conclusion, the results revealed the latest genetic evolution of circulating PEDV strains in Guangxi province in recent years, providing important information for preventing and controlling PEDV infection. Currently, the G2a subgroup strains are the predominant strains circulating in pig herds in Guangxi province, southern China.

Adipocytes are crucial for maintaining energy balance. Adipocyte differentiation involves distinct stages, including the orientation stage, clone amplification stage, clone amplification termination stage, and terminal differentiation stage. Understanding the regulatory mechanisms governing adipogenic differentiation is essential for comprehending the physiological processes and identifying potential biomarkers and therapeutic targets for metabolic diseases, ultimately improving glucose and fat metabolism. Adipogenic differentiation is influenced not only by key factors such as hormones, the peroxisome proliferator-activated receptor (PPAR) family, and the CCATT enhancer-binding protein (C/EBP) family but also by noncoding RNA, including microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA). Among these, lncRNA has been identified as a significant regulator in adipogenic differentiation. Research has demonstrated various ways in which lncRNAs contribute to the molecular mechanisms of adipogenic differentiation. Throughout the adipogenesis process, lncRNAs modulate adipocyte differentiation and development by influencing relevant signaling pathways and transcription factors. This review provides a brief overview of the function and mechanism of lncRNAs in adipogenic differentiation.

IntroductionHepatocellular carcinoma (HCC) is an aggressive malignancy, and CCL18, a marker of M2 macrophage activation, is often associated with tumor immune suppression. However, the role of CCL18 and its signaling pathway in HCC is still limited. Our study focuses on investigating the prognostic impact of CCL18 and its signaling pathway in HCC patients and biological functions in vitro.MethodsHCC-related RNA-seq data were obtained from TCGA, ICGC, and GEO. The 6 hub genes with the highest correlation to prognosis were identified using univariate Cox and LASSO regression analysis. Multivariate Cox regression analysis was performed to assess their independent prognostic potential and a nomogram was constructed. In vitro experiments, including CCK8, EdU, RT-qPCR, western blot, and transwell assays, were conducted to investigate the biological effects of exogenous CCL18 and 6 hub genes. A core network of highly expressed proteins in the high-risk group of tumors was constructed. Immune cell infiltration was evaluated using the ESTIMATE and CIBERSORT packages. Finally, potential treatments were explored using the OncoPredict package and CAMP database.ResultsWe identified 6 survival-related genes (BMI1, CCR3, CDC25C, CFL1, LDHA, RAC1) within the CCL18 signaling pathway in HCC patients. A nomogram was constructed using the TCGA_LIHC cohort to predict patient survival probability. Exogenous CCL18, as well as overexpression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1, can promote proliferation, migration, invasion, stemness, and increased expression of PD-L1 protein in LM3 and MHCC-97H cell lines. In the high-risk group of patients from the TCGA_LIHC cohort, immune suppression was observed, with a strong correlation to 21 immune-related genes and suppressive immune cells.ConclusionExogenous CCL18 promotes LM3 and MHCC-97H cells proliferation, migration, invasion, stemness, and immune evasion. The high expression of BMI1, CCR3, CDC25C, CFL1, LDHA, and RAC1 can serve as a biomarkers for immune evasion in HCC.

Summary: Autophagy is crucial for degrading and recycling cellular components. Fusion between autophagosomes and lysosomes is pivotal, directing autophagic cargo to degradation. This process is driven by STX17-SNAP29-VAMP8 and STX7-SNAP29-YKT6 in mammalian cells. However, the interaction between STX17 and YKT6 and its significance remain to be revealed. In this study, we challenge the notion that STX17 and YKT6 function independently in autophagosome-lysosome fusion. YKT6, through its SNARE domain, forms a complex with STX17 and SNAP29 on autophagosomes, enhancing autophagy flux. VAMP8 displaces YKT6 from this complex, leading to the formation of the fusogenic complex STX17-SNAP29-VAMP8. We demonstrated that the YKT6-SNAP29-STX17 complex facilitates both lipid and content mixing driven by STX17-SNAP29-VAMP8, suggesting a priming role of YKT6 for efficient membrane fusion. Our results provide a potential regulation mechanism of autophagosome-lysosome fusion, highlighting the importance of YKT6 and its interactions with STX17 and SNAP29 in promoting autophagy flux.

IntroductionHyperuricemia, characterized by elevated serum uric acid levels, has garnered significant attention in cardiovascular research due to its potential association with coronary heart disease (CHD). While some studies suggest hyperuricemia as a risk factor of CHD, others present conflicting findings. A systematic review and dose-response meta-analysis is warranted to comprehensively summarize the previous studies and determine the association between hyperuricemia and CHD, thereby supporting clinical practice and future studies in this field.MethodsIn this study, we will comprehensively search Medline, EMBase, Cochrane Central, ICTRP, and ClinicalTrials.gov, from inception to December 31, 2024. Prospective or retrospective cohort studies and case-control studies investigating the association between hyperuricemia and CHD will be included. Two independent reviewers will conduct study selection, data extraction, and risk of bias assessment. The primary outcome will be the pooled relative risk of CHD associated with hyperuricemia by using random-effect model. Dose-response meta-analysis will be performed with linear and non-linear model to explore the the magnitude and direction of the association between serum uric acid levels and CHD risk. Subgroup analyses will be conducted based on uric acid test approaches and corresponding cut-off values and human races. Sensitivity analyses will assess the robustness of the results with leave-one-out method, while publication bias will be evaluated using funnel plots, Egger's test, and Begg's test. We will further use GRADE to evaluate the quality of the evidences provided by our systematic review.Expected resultsFrom this systematic review and dose-response meta-analysis, we hope out findings will provide reliable conclusion and data support on the association between hyperuricemia and CHD. The transparent and replicable methodologies outlined in this protocol contribute to advancing understanding of hyperuricemia as a potentially modifiable risk factor for CHD, thus supporting evidence-based strategies for cardiovascular disease management.ConclusionsThis protocol describes a rigorous plan to systematically review and analyze the quantitative association between hyperuricemia and CHD risk. In a word, we will help further clinical practice and scientific studies in this field.Trial registrationThis protocol was registered in PROSPERO CRD42024538553.

International trade is an important part of the world economy, and the rapid development of big data and complex network theory provides the possibility of an in-depth study of international trade networks. This study constructs the international trade flow gravity model and international trade flow index system on the basis of the clustered dynamic panel gravity model. It explores the influencing factors of national trade flow and the fitting effect of the international trade gravity model through factor analysis and regression analysis of variables in the system. The sample data’s KMO value is 0.834, according to the results, and there is a significant correlation between the variables. The degree of explanation of the public factors to the original variables is more than 0.5, and the variance contribution rate of trade structure, marketized structure, population and macroeconomics, international capital, and exchange rate reaches 71.832%, which makes the factor analysis more effective. The R² value of the trade gravity model reaches 0.837, with a remarkable effect. Among the sample countries, the highest trade flow potential is the United States (125,467.0), while the lowest is Portugal (512.4). The national GDP and population have a significant effect on international trade flows. The volume of each trading country should be used as a reference basis for conducting trade transactions when conducting international trade.

Abstract Background Triple-negative breast cancer (TNBC) possesses special biological behavior and clinicopathological characteristics, which is highly invasive and propensity to metastasize to lymph nodes, leading to a worse prognosis than other types of breast cancer. Thus, the development of an effective therapeutic method is significant to improve the survival rate of TNBC patients. Results In this work, a liposome-based theranostic nanosystem (ILA@Lip) was successfully prepared by simultaneously encapsulating IR 780 as the photosensitizer and lenvatinib as an anti-angiogenic agent, together with banoxantrone (AQ4N) molecule as the hypoxia-activated prodrug. The ILA@Lip can be applied for the near-infrared (NIR) fluorescence diagnostic imaging of TNBC and its lymph node metastasis for multimodal therapy. Lenvatinib in ILA@Lip can inhibit angiogenesis by cutting oxygen supply, thereby leading to enhanced hypoxia levels. Meanwhile, large amounts of reactive oxygen species (ROS) were produced while IR 780 was irradiated by an 808 nm laser, which also rapidly exhausted oxygen in tumor cells to worsen tumor hypoxia. Through creating an extremely hypoxic in TNBC, the conversion of non-toxic AQ4N to toxic AQ4 was much more efficiency for hypoxia-activated chemotherapy. Cytotoxicity assay of ILA@Lip indicated excellent biocompatibility with normal cells and tissues, but showed high toxicity in hypoxic breast cancer cells. Also, the in vivo tumors treated by the ILA@Lip with laser irradiation were admirably suppressed in both subcutaneous tumor model and orthotopic tumor models. Conclusion Utilizing ILA@Lip is a profound strategy to create an extremely hypoxic tumor microenvironment for higher therapeutic efficacy of hypoxia-activated chemotherapy, which realized collective suppression of tumor growth and has promising potential for clinical translation.

With the increase in the number of distributed energy resources (DERs) and electric vehicles (EVs), it is particularly important to solve the problem of EV charging station siting and capacity determination under the distribution network considering a large proportion of DERs. This paper proposes a bi-level planning model for EV charging stations that takes into account the characteristics of the spatial–temporal distribution of charging loads under an uncertain environment. First, the Origin–Destination (OD) matrix analysis method and the real-time Dijkstra dynamic path search algorithm are introduced and combined with the Larin Hypercube Sampling (LHS) method to establish the EV charging load prediction model considering the spatial and temporal distribution characteristics. Second, the upper objective function with the objective of minimizing the cost of EV charging station planning and user charging behavior is constructed, while the lower objective function with the objective of minimizing the cost of distribution network operation and carbon emission cost considering the uncertainty of wind power and photovoltaics is constructed. The constraints of the lower-layer objective function are transformed into the upper-layer objective function through Karush–Kuhn–Tucker (KKT) conditions, the optimal location and capacity of charging stations are finally determined, and the model of EV charging station siting and capacity determination is established. Finally, the validity of the model was verified by planning the coupled IEEE 33-node distribution network with the traffic road map of a city in southeastern South Dakota, USA.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3−.

Abstract Background Angiogenesis and tissue repair in chronic non-healing diabetic wounds remain critical clinical problems. Engineered MSC-derived exosomes have significant potential for the promotion of wound healing. Here, we discuss the effects and mechanisms of eNOS-rich umbilical cord MSC exosomes (UCMSC-exo/eNOS) modified by genetic engineering and optogenetic techniques on diabetic chronic wound repair. Methods Umbilical cord mesenchymal stem cells were engineered to express two recombinant proteins. Large amounts of eNOS were loaded into UCMSC-exo using the EXPLOR system under blue light irradiation. The effects of UCMSC-exo/eNOS on the biological functions of fibroblasts and vascular endothelial cells in vitro were evaluated. Full-thickness skin wounds were constructed on the backs of diabetic mice to assess the role of UCMSC-exo/eNOS in vascular neogenesis and the immune microenvironment, and to explore the related molecular mechanisms. Results eNOS was substantially enriched in UCMSCs-exo by endogenous cellular activities under blue light irradiation. UCMSC-exo/eNOS significantly improved the biological functions of cells after high-glucose treatment and reduced the expression of inflammatory factors and apoptosis induced by oxidative stress. In vivo, UCMSC-exo/eNOS significantly improved the rate of wound closure and enhanced vascular neogenesis and matrix remodeling in diabetic mice. UCMSC-exo/eNOS also improved the inflammatory profile at the wound site and modulated the associated immune microenvironment, thus significantly promoting tissue repair. Conclusion This study provides a novel therapeutic strategy based on engineered stem cell-derived exosomes for the promotion of angiogenesis and tissue repair in chronic diabetic wounds. Graphic Abstract

Abstract Aims Given recent suggestions that serum levels of insulin‐like growth factor‐binding protein 7 (IGFBP7) may identify patients who derive greater cardiorenal benefits from treatment with sodium‐glucose transport 2 inhibitors (SGLT2i), this exploratory sub‐analysis of the EMPA‐HEART CardioLink‐6 randomized controlled trial evaluated the association between serum levels of IGFBP7 and empagliflozin‐mediated left ventricular mass regression. Methods and results The EMPA‐HEART CardioLink‐6 trial used gold‐standard cardiac magnetic resonance imaging to detect change in left ventricular mass indexed to body surface area (LVMi) following 6 months of treatment with empagliflozin or matching placebo in 97 patients with type 2 diabetes and coronary artery disease. Serum samples were collected at baseline and analysed for IGFBP7 using an enzyme‐linked immunosorbent assay. A multivariate linear regression model was used to assess the association between IGFBP7 and baseline LVMi. A linear model adjusting for baseline differences in LVMi was used to test the relationship between baseline IGFBP7 level, change in LVMi over 6 months, and treatment arm. Of the 97 patients enrolled, 74 had complete covariate data and were included in our analysis. No association between baseline IGFBP7 and baseline LVMi was found [baseline LVMi: 0.14 g/m2 (95% CI: −0.29 g/m2 to 0.57 g/m2) per 1 ng/mL higher baseline IGFBP7]. In addition, no difference between patients treated with empagliflozin versus matching placebo was found when evaluating the association between serum IGFBP7, 6 month change in LVMi, and treatment arm [empagliflozin 6 month change in LVMi: 0.25 g/m2 (95% CI: −0.17 g/m2 to 0.67 g/m2) per 1 ng/mL higher IGFBP7 vs. matching placebo 6 month change in LVMi: 0.07 g/m2 (95% CI: −0.21 g/m2 to 0.35 g/m2) per 1 ng/mL higher IGFBP7; Pinteraction = 0.49]. Additional sensitivity analysis assessing IGFBP7 as a categorical variable (above/below the median) showed no significant association between IGFBP7, 6 month change in LVMi, and treatment arm. Conclusions Our study provides insight into the generalizability of IGFBP7 as a surrogate marker of cardiac remodelling in patients with type 2 diabetes and coronary artery disease. Our results suggest that SGLT2i‐mediated reverse cardiac remodelling may be independent of IGFBP7 levels. Further investigations evaluating the association between IGFBP7 and SGLT2i are suggested to understand if and how IGFBP7 levels may modulate benefits received from SLGT2i.

Essential proteins play a vital role in biological processes, and the combination of gene expression profiles with Protein-Protein Interaction (PPI) networks can improve the identification of essential proteins. However, gene expression data are prone to significant fluctuations due to noise interference in topological networks. In this work, we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise fluctuation. We then proposed the Pearson Jaccard coefficient (PJC) that consisted of continuous and discrete similarities in the gene expression data. Using the graph theory as the basis, we fused the newly proposed similarity coefficient with the existing network topology prediction algorithm at each protein node to recognize essential proteins. This strategy exhibited a high recognition rate and good specificity. We validated the new similarity coefficient PJC on PPI datasets of Krogan, Gavin, and DIP of yeast species and evaluated the results by receiver operating characteristic analysis, jackknife analysis, top analysis, and accuracy analysis. Compared with that of node-based network topology centrality and fusion biological information centrality methods, the new similarity coefficient PJC showed a significantly improved prediction performance for essential proteins in DC, IC, Eigenvector centrality, subgraph centrality, betweenness centrality, closeness centrality, NC, PeC, and WDC. We also compared the PJC coefficient with other methods using the NF-PIN algorithm, which predicts proteins by constructing active PPI networks through dynamic gene expression. The experimental results proved that our newly proposed similarity coefficient PJC has superior advantages in predicting essential proteins.

Medical knowledge graphs (MKGs) are the basis for intelligent health care, and they have been in use in a variety of intelligent medical applications. Thus, understanding the research and application development of MKGs will be crucial for future relevant research in the biomedical field. To this end, we offer an in-depth review of MKG in this work. Our research begins with the examination of four types of medical information sources, knowledge graph creation methodologies, and six major themes for MKG development. Furthermore, three popular models of reasoning from the viewpoint of knowledge reasoning are discussed. A reasoning implementation path (RIP) is proposed as a means of expressing the reasoning procedures for MKG. In addition, we explore intelligent medical applications based on RIP and MKG and classify them into nine major types. Finally, we summarize the current state of MKG research based on more than 130 publications and future challenges and opportunities.

Abstract Atopic dermatitis (AD) is a common inflammatory skin disease. Matrine is the main component of the traditional Chinese medicine Sophora flavescens, and it poses good therapeutic effects on inflammatory diseases. This study aimed to explore the pharmacological effects of matrine on AD and its underlying mechanism. An AD mouse model and inflamed human epidermal keratinocyte cells (HaCaT) cells were established. Histopathological aspects were examined using hematoxylin and eosin staining, toluidine blue staining, and immunohistochemistry. The mRNA and protein expressions were assessed using quantitative real‐time polymerase chain reaction and Western blot, respectively. The secretions of cytokines and chemokines were examined by enzyme‐linked immunosorbent assay. Flow cytometry was carried out to analyze the proportions of T‐helper (Th) 1 and Th2 cells. Herein, our results displayed that matrine diminished AD symptoms and decreased heat shock protein 90 (Hsp90) expression. Matrine decreased the Th2 cytokine levels in the ear tissues and serum, and it also significantly repressed inflammatory cytokines (thymus activation regulated chemokine and interleukin‐6) secretions by repressing the Hsp90/NF‐κB signaling axis in inflamed HaCaT cells. Furthermore, matrine inhibited Th2 differentiation of CD4+ T cells when co‐cultured with inflamed HaCaT cells. Matrine can regulate the Th1/Th2 inflammatory response by inhibiting the Hsp90/NF‐κB signaling axis to alleviate AD. Therefore, it may be a candidate for AD treatment.

Casein and α-lactalbumin (α-LA) are the main allergens in cow's milk, which can affect the skin, respiratory system, and gastrointestinal tract, even cause anaphylactic shock. Developing a rapid and sensitive detection method of casein and α-LA is still pursued. Herein, a surface-enhanced Raman scattering based lateral flow assay (SERS-LFA) method for rapid and highly sensitive detection of milk allergens in food was established for effectively preventing allergic symptoms. Gold@silver nanoparticles (Au@Ag NPs) were synthesized as SERS active substrate to prepare the antibody-modified SERS Probe and SERS-LFA strips toward casein and α-LA were assembled according to the sandwich mode. The detection results were calculated according to colorimetric and Raman signal. The introduction of SRES signal significantly increased the sensitivity of detection with the limit of detection (LOD) of 0.19 ng/mL and 1.74 pg/mL, and exhibited an excellent linear relationship within the range of 0.55–791.50 ng/mL and 0.1 pg/mL–100.0 ng/mL for casein and α-LA, respectively. Furthermore, SERS-LFA strips was highly specific with the recovery rates for corresponding 80.36 %–105.12 % and 85.73 %–118.22 % for casein and α-LA, respectively. Therefore, the SERS-LFA could be in great potential to develop a unique allergen detection method.

Abstract Research on biomarker-driven therapy and immune check-point blockade in non-small cell lung cancer (NSCLC) is rapidly evolving. The width and depth of clinical trials have also dramatically improved in an unprecedented speed. The personalized treatment paradigm evolved every year. In this review, we summarize the promising agents that have shifted the treatment paradigm for NSCLC patients across all stages, including targeted therapy and immunotherapy using checkpoint inhibitors. Based on recent evidence, we propose treatment algorithms for NSCLC and propose several unsolved clinical issues, which are being explored in ongoing clinical trials. The results of these trials are likely to impact future clinical practice.

Abstract Knowledge of shale pore structure characteristics is crucial to understand gas storage and seepage mechanisms. Organic matter (OM) pores are considered the most important pore type in shale, and one of the currently significant research questions focuses on the spatial distribution and connectivity of OM pores. To answer this question, typical OM‐rich siliceous shale samples from the Lower Silurian Longmaxi Formation were comprehensively investigated using focused ion beam scanning electron microscopy. A three‐dimensional model of the OM‐rich region of interest was segmented and reconstructed based on numerous two‐dimensional slices. The types of OM were found to control the development of organic pores, and OM pores including honeycomb‐shaped pores, spongy‐shaped pores, and slit‐like irregular pores are mainly formed in the pyrobitumen. The pore structure parameters of the OM‐rich ROI revealed that the pore size distribution of honeycomb‐shaped OM pores formed in the pyrobitumen was mainly distributed in the range of 10–50 and 80–100 nm, while the throat equivalent diameter distribution demonstrated a unimodal curve with the main peak located at approximately 30 nm. Pore connectivity analysis further indicated that pyrobitumen also contained several isolated nano‐pores, and pores with diameters smaller than 40 nm were poorly connected. Furthermore, permeability simulation revealed clear discrepancies in different directions owing to the heterogeneity of the OM pores. These findings provide experimental evidence for the assessment of shale gas resources and their development potential.

This study aims to investigate the influence of punctum image in destinations on tourists’ behavioral intentions. The study proposes the concepts of punctum and studium image based on semiology and uses an interpretable moderated mediation model to examine the effects of punctum image, studium image, flow experience, and human interaction on behavioral intention. The proposed research collected data from 440 tourists who visited a destination and used a structural equation model to analyze the relationships among the variables. The study employed bootstrapping to test the significance of the mediating effects and conducted a moderated mediation analysis to examine the moderating role of human interaction. The findings of the study indicate that punctum image has a positive effect on studium image and behavioral intention. Studium image is found to mediate the relationship between punctum image and behavioral intention. Additionally, the study shows that there are multiple mediations of studium image and flow experience between punctum image and behavioral intention. Finally, the study finds that human interaction plays a moderating role in two of the mediating effects. The results of this research have important theoretical and managerial implications. The study highlights the importance of punctum image in destination branding and suggests that destinations should focus on creating memorable and distinctive images to attract tourists. The study also emphasizes the role of studium image and flow experience in shaping tourists’ behavioral intentions, which could help destinations to design more effective marketing strategies. Finally, the study underscores the importance of human interaction in shaping tourists’ experiences and suggests that destinations should focus on providing high-quality human interactions to enhance tourists’ experiences and satisfaction. The use of an interpretable moderated mediation model in this study enhances the interpretability and practical applicability of the results for decision-makers.

The purpose of drug discovery is to identify new drugs, and the solubility of drug molecules is an important physicochemical property in medicinal chemistry, that plays a crucial role in drug discovery. In solubility prediction, high-precision computational methods can significantly reduce the experimental costs and time associated with drug development. Therefore, artificial intelligence technologies have been widely used for solubility prediction. This study utilized the attention layer in mechanism in the deep learning model to consider the atomic-level features of the molecules, and used gated recurrent neural networks to aggregate vectors between layers. It also utilized molecular fragment technology to divide the complete molecule into pairs of fragments, extracted characteristics from each fragment pair, and finally fused the characteristics to predict the solubility of drug molecules. We compared and evaluated our method with five existing models using two performance evaluation indicators, demonstrating that our method has better performance and greater robustness.

Abstract Stage III non‐small cell lung cancer (NSCLC) encompasses a group of diseases with high heterogeneity. Such patients should actively receive comprehensive treatments. It is imperative for all stage III NSCLC patients to receive consultation with a multiple disciplinary team, which allows the development of a proposal for clinical diagnosis and treatment. In this consensus, stage III NSCLC is divided into two types (operable and inoperable) according to different clinical conditions. Resectable NSCLC is further subdivided into two conditions (with or without driver genes). For each clinical scenario, this consensus emphasizes that the foundation of any medical decisions regarding the optimal diagnostic or therapy procedure is scientific evidence from clinical research. Finally, based on the level of evidence and strength of recommendations, this consensus provides recommendations for the management of stage III NSCLC from six perspectives. The objective of this consensus is to help clinicians choose the best treatment and promote the standardization of stage III NSCLC diagnosis and treatment in China.

Integrating the brain structural and functional connectivity features is of great significance in both exploring brain science and analyzing cognitive impairment clinically. However, it remains a challenge to effectively fuse structural and functional features in exploring the complex brain network. In this paper, a novel brain structure-function fusing-representation learning (BSFL) model is proposed to effectively learn fused representation from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) for mild cognitive impairment (MCI) analysis. Specifically, the decomposition-fusion framework is developed to first decompose the feature space into the union of the uniform and unique spaces for each modality, and then adaptively fuse the decomposed features to learn MCI-related representation. Moreover, a knowledge-aware transformer module is designed to automatically capture local and global connectivity features throughout the brain. Also, a uniform-unique contrastive loss is further devised to make the decomposition more effective and enhance the complementarity of structural and functional features. The extensive experiments demonstrate that the proposed model achieves better performance than other competitive methods in predicting and analyzing MCI. More importantly, the proposed model could be a potential tool for reconstructing unified brain networks and predicting abnormal connections during the degenerative processes in MCI.

Pancreatic β-cell compensation is a major mechanism in delaying T2DM progression. Here, the authors show that circGlis3 levels are affected by QKI and FUS expression, and that increasing circGlis3 lengthens β-cell compensation via enhancing insulin secretion and reducing apoptosis.

Currently, the alteration of external factors during crude oil extraction easily disrupts the thermodynamic equilibrium of asphaltene, resulting in the continuous flocculation and deposition of asphaltene molecules in crude oil. This accumulation within the pores of reservoir rocks obstructs the pore throat, hindering the efficient extraction of oil and gas, and consequently, affecting the recovery of oil and gas resources. Therefore, it is crucial to investigate the principles of asphaltene deposition inhibition and the synthesis of asphaltene inhibitors. In recent years, the development of nanotechnology has garnered significant attention due to its unique surface and volume effects. Nanoparticles possess a large specific surface area, high adsorption capacity, and excellent suspension and catalytic abilities, exhibiting unparalleled advantages compared with traditional organic asphaltene inhibitors, such as sodium dodecyl benzene sulfonate and salicylic acid. At present, there are three primary types of nanoparticle inhibitors: metal oxide nanoparticles, organic nanoparticles, and inorganic nonmetal nanoparticles. This paper reviews the recent advancements and application challenges of nanoparticle asphaltene deposition inhibition technology based on the mechanism of asphaltene deposition and nano-inhibitors. The aim was to provide insights for ongoing research in this field and to identify potential future research directions.

Knowledge of the interaction mechanisms between shale and CH4/CO2 is crucial for the implementation of CO2 sequestration with enhanced CH4 recovery (CS-EGR) in shale reservoir. As one of the main constituents of shale, clay minerals can profoundly affect the storage capacity of gases in nanopores. In this paper, the adsorption behaviors of both CO2 and CH4 on montmorillonite, illite as well as kaolinite under dry condition are investigated by Grand Canonical Monte Carlo (GCMC) simulation. The results exhibit that the maximum adsorption capacity of single-component CH4 and CO2 is associated with the types of clay crystals. Specifically, the montmorillonite has the strongest adsorption capacity for CO2, followed by illite and kaolinite, while the sequence in maximum adsorption capacity of CH4 is predicted in the order of kaolinite > montmorillonite > illite. These discrepancies are closely related to the characteristics of adsorbate molecules as well as the different structures of clay crystals. Meanwhile, the maximum adsorption capacity of CH4 in studied clay minerals gradually decreases as pore size increases, while nanopores with 2-nm basal spacing demonstrate the highest adsorption capacity for CO2. In addition, it is observed that the studied clay minerals tend to preferentially adsorb CO2 rather than CH4 during binary gas mixtures simulation. The selectivity of CH4/CO2 mixtures in montmorillonite and kaolinite exhibits various performances as the adsorption pressure increases, with the selectivity in montmorillonite being the largest, especially at low pressure. The cation exchange significantly enhances the electrostatic interaction with CO2 molecules, leading to a higher loading of CO2 as well as larger value of selectivity. These findings can provide basis and guidance for the CS-EGR project in shale reservoirs.

Abstract Proteins are the building blocks of life, carrying out fundamental functions in biology. In computational biology, an effective protein representation facilitates many important biological quantifications. Most existing protein representation methods are derived from self‐supervised language models designed for text analysis. Proteins, however, are more than linear sequences of amino acids. Here, a multimodal deep learning framework for incorporating ≈1 million protein sequence, structure, and functional annotation (MASSA) is proposed. A multitask learning process with five specific pretraining objectives is presented to extract a fine‐grained protein‐domain feature. Through pretraining, multimodal protein representation achieves state‐of‐the‐art performance in specific downstream tasks such as protein properties (stability and fluorescence), protein‒protein interactions (shs27k/shs148k/string/skempi), and protein‒ligand interactions (kinase, DUD‐E), while achieving competitive results in secondary structure and remote homology tasks. Moreover, a novel optimal‐transport‐based metric with rich geometry awareness is introduced to quantify the dynamic transferability from the pretrained representation to the related downstream tasks, which provides a panoramic view of the step‐by‐step learning process. The pairwise distances between these downstream tasks are also calculated, and a strong correlation between the inter‐task feature space distributions and adaptability is observed.

The skin is heterogeneous and exerts strong scattering and aberration onto excitation light in multiphoton microscopy (MPM). Shifting to longer excitation wavelengths may help reduce skin scattering and aberration, potentially enabling larger imaging depths. However, previous demonstrations of skin MPM employ excitation wavelengths only up to the 1700[Formula: see text]nm window, leaving an open question as to whether longer excitation wavelengths are suitable for deep-skin MPM. Here, in order to explore the longer-wavelength territory, first, we demonstrate characterization of the broadband transmittance of excised mouse skin, revealing a high transmittance window at 2200[Formula: see text]nm. Then, we demonstrate third-harmonic generation (THG) imaging in mouse skin in vivo excited at this window. With 9[Formula: see text]mW optical power on the skin surface operating at 1[Formula: see text]MHz repetition rate, we can get THG signals of 250[Formula: see text][Formula: see text]m below the skin surface. Comparative THG imaging excited at the 1700[Formula: see text]nm window shows that as imaging depth increases, THG signals decay even faster than those excited at 2200[Formula: see text]nm. Our results thus uncover the 2200[Formula: see text]nm window as a new, promising excitation window potential for deep-skin MPM.