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Abstract Background The role of proximal tubular autophagy in repairing kidney injury following ischemia remains unclear. Methods In this study, we utilized mice with conditional deletion of the Atg5 gene in proximal tubules and monitored the long-term dynamic regulation of autophagy following ischemic acute kidney injury (AKI). Results The results showed that Atg5-deficient proximal tubule epithelial cells exhibited damaged mitochondria, concentric membranes, and lysosomal accumulation 24 h after ischemia/reperfusion. However, 28 days after ischemia/reperfusion, concentric membrane bodies remained, but lysosomal accumulation was no longer observed. Notably, the absence of Atg5 in renal tubular epithelial cells impaired renal function and led to increased tubular cell proliferation and oxidative stress in the early stage of injury. However, during the repair period following AKI, Atg5 deficiency exhibited no significant difference in the expression of proliferating cell nuclear antigen (PCNA) and 4-hydoxynonenal (4HNE), suggesting that the improvement in renal fibrosis associated with Atg5 deficiency is unlikely to result from its effect on cell proliferation or reactive oxygen species levels. Additionally, Atg5 deficiency inhibits the secretion of profibrotic factor fibroblast growth factor 2 (FGF2) from the early stage of renal injury to the recovery stage of AKI, indicating that autophagy-specific regulation of FGF2 secretion is a dynamic process overlapping with other stages of injury. Furthermore, increased co-localization of ATG5 with 4HNE and FGF2 was observed in patient samples. Conclusion In summary, our results suggest that the dynamic regulation of autophagy on key molecules involved in kidney injury and repair varies with the stage of kidney injury. Graphical Abstract

Purpose – This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems. Design/methodology/approach – A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data. Findings – First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained. Originality/value – The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

In this paper, we introduce a challenging Global Large-scale Ship Database (GLSD), designed specifically for ship detection tasks. The designed GLSD database includes a total of 212,357 annotated instances from 152,576 images. Based on the collected images, we propose 13 ship categories that widely exist in international routes. These categories include Sailing boat, Fishing boat, Passenger ship, Warship, General cargo ship, Container ship, Bulk cargo carrier, Barge, Ore carrier, Speed boat, Canoe, Oil carrier, and Tug. The motivations for developing GLSD include the following: 1) providing a refined and extensive ship detection database that benefits the object detection community, 2) establishing a database with exhaustive labels (bounding boxes and ship class categories) in a uniform classification scheme, and 3) providing a large-scale ship database with geographic information (covering more than 3000 ports and 33 routes) that benefits multi-modal analysis. Additionally, we discuss the evaluation protocols corresponding to image characteristics in GLSD and analyze the performance of selected state-of-the-art object detection algorithms on GLSD, aiming to establish baselines for future studies.

Abstract The clinical efficacy of immune checkpoint blockade (ICB) therapy is significantly compromised in the metabolically disordered tumor microenvironment (TME), posing a formidable challenge that cannot be ignored in current antitumor strategies. In this study, TME‐responsive nanoparticles (HMP1G NPs) loaded with 1‐methyltryptophan (1‐MT; an indoleamine 2,3‐dioxygenase 1 [IDO1] inhibitor,) and S‐nitrosoglutathione (GSNO; a nitric oxide donor) is developed to enhance the therapeutic efficacy of 1‐MT‐mediated ICB. The HMP1G NPs responded to H+ and glutathione in the TME, releasing Mn2+, GSNO, and 1‐MT. The released Mn2+ catalyzed the production of abundant reactive oxygen species and nitric oxide from hydrogen peroxide and GSNO, and the generated nitric oxide, synergistically with 1‐MT, inhibited the accumulation of kynurenine mediated by IDO1 in the tumor. Mechanistically, HMP1G NPs downregulated tumor cell‐derived IDO1 via the aryl hydrocarbon receptor/signal transducer and activator of transcription 3/interleukin signaling axis to improve kynurenine/tryptophan metabolism and immunosuppression. In a murine breast cancer model, treatment with HMP1G NPs elicited effective antitumor immunity and enhanced survival outcomes. This study highlights a novel nano‐platform that simultaneously improves metabolism and enhances ICB efficacy to achieve a new and efficient antitumor strategy.

Giant pandas (Ailuropoda melanoleuca) serve as flagship species for global biodiversity conservation. Establishing wildlife corridors and introducing edible bamboo species into their understory can enhance giant panda migration and mitigate their vulnerability to human activities and climate change. This study employs the MaxEnt model to analyze habitat suitability for giant pandas and edible bamboo, using the principle of least-cost paths to construct potential ecological corridors while also identifying suitable bamboo species for planting. Results revealed that (1) the habitat suitability index was high in the study region’s central area but low at the periphery, with fragmentation observed, particularly in the northeastern mountains; (2) eight giant panda habitat patches (C1–C8) and nine potential ecological corridors were identified, where C1–C6 patches were small and corridors exhibited low connectivity; and (3) four bamboo species were suitable for planting in the corridors, identified by overlaying corridor layers with bamboo suitability maps. Among the bamboo species, Fargesia spathacea is considered most adaptable, capable of occupying over 40% of the corridor area, followed by Fargesia robusta, recommended for widespread planting in corridor habitats. These findings underscore the importance of strategic habitat management and bamboo restoration in promoting the long-term survival of giant pandas.

Background: Fatigue is often accompanied by comorbid sleep disturbance and psychiatric distress following the COVID-19 infection. However, identifying individuals at risk for developing post-COVID fatigue remains challenging. This study aimed to identify the neurobiological markers underlying fatigue susceptibility and further investigate their effect on COVID-19-related neuropsychiatric symptoms. Methods: Individuals following a mild SARS-CoV-2 infection (COV+) underwent neuropsychiatric measurements (n = 335) and MRI scans (n = 271) within 1 month (baseline), and 191 (70.5 %) of the individuals were followed up 3 months after infection. Sixty-seven healthy controls (COV−) completed the same recruitment protocol. Results: Whole-brain voxel-wise analysis showed that gray matter volume (GMV) during the acute phase did not differ between the COV+ and COV− groups. GMV in the right dorsolateral prefrontal cortex (DLPFC) and left dorsal anterior cingulate cortex (dACC) were associated with fatigue severity only in the COV+ group at baseline, which were assigned to the frontal system and limbic system, respectively. Furthermore, fatigue mediated the associations between volume differences in fatigue susceptibility and COVID-related sleep, post-traumatic stress disorder, anxiety and depression. Crucially, the initial GMV in the right DLPFC can predict fatigue symptoms 3 months after infection. Conclusions: We provide novel evidence on the neuroanatomical basis of fatigue vulnerability and emphasize that acute fatigue is an important link between early GMV in the frontal-limbic regions and comorbid neuropsychiatric symptoms at baseline and 3 months after infection. Our findings highlight the role of the frontal-limbic system in predisposing individuals to develop post-COVID fatigue.

Background The proportion and impact of minimal pleural effusion (PE) on prognosis remain blurred in operable non-small cell lung cancer (NSCLC) patients who reported minimal PE on imaging. Methods Clinical and prognostic data of operable NSCLC patients who presented no distant metastasis, no direct pleural invasion, but minimal PE on preoperative imaging were retrospectively analyzed. The patients were divided into surgical (81 cases) and non-surgical (10 cases) cohorts. Potential or suspected malignant PE or pleural metastases were confirmed by surgery. The overall survival (OS) was analyzed by Kaplan-Meier curve and prognostic factors by multivariate Cox regression. Results The surgical cohort reported no pleural invasion on preoperative imaging and no pleural metastases by postoperative pathology, with an overall median disease-free survival of 36.7 (28.6, 44.7) months and a median OS of 59.8 (45.7, 73.2) months, with the latter significantly longer in the surgical cohort than in the non-surgical cohort (59.8 months vs 20.37 months, P < 0.001). Multivariate analysis indicated surgical treatment as an independent prognostic factor for OS. Conclusion Malignant PE is rare in operable NSCLC patients who report the presence of minimal PE but no distant metastasis or direct pleural invasion on preoperative imaging. Surgery may be the preferred treatment for these patients.

Abstract In the past decades, substantial progress has been made in human action recognition. However, most existing studies and datasets for human action recognition utilise still images or videos as the primary modality. Image‐based approaches can be easily impacted by adverse environmental conditions. In this paper, the authors propose combining RGB images and point clouds from LiDAR sensors for human action recognition. A dynamic lateral convolutional network (DLCN) is proposed to fuse features from multi‐modalities. The RGB features and the geometric information from the point clouds closely interact with each other in the DLCN, which is complementary in action recognition. The experimental results on the JRDB‐Act dataset demonstrate that the proposed DLCN outperforms the state‐of‐the‐art approaches of human action recognition. The authors show the potential of the proposed DLCN in various complex scenarios, which is highly valuable in real‐world applications.

NAD(P)H:quinone oxidoreductase 1 (NQO1) is overexpressed in most solid cancers, emerging as a promising target for tumor-selective killing. β-Lapachone (β-Lap), an NQO1 bioactivatable drug, exhibits significant antitumor effects on NQO1-positive cancer cells by inducing immunogenic cell death (ICD) and enhancing tumor immunogenicity. However, the interaction between β-Lap-mediated antitumor immune responses and neutrophils, novel antigen-presenting cells (APCs), remains unknown. This study demonstrates that β-Lap selectively kills NQO1-positive murine tumor cells by significantly increasing intracellular ROS formation and inducing DNA double strand breaks (DSBs), resulting in DNA damage. Treatment with β-Lap efficiently eradicates immunocompetent murine tumors and significantly increases the infiltration of tumor-associated neutrophils (TANs) into the tumor microenvironment (TME), which plays a crucial role in the drug’s therapeutic efficacy. Further, the presence of β-Lap-induced antigen medium leads bone marrow-derived neutrophils (BMNs) to directly kill murine tumor cells, aiding in dendritic cells (DCs) recruitment and significantly enhancing CD8+ T cell proliferation. β-Lap treatment also drives the polarization of TANs toward an antitumor N1 phenotype, characterized by elevated IFN-β expression and reduced TGF-β cytokine expression, along with increased CD95 and CD54 surface markers. β-Lap treatment also induces N1 TAN-mediated T cell cross-priming. The HMGB1/TLR4/MyD88 signaling cascade influences neutrophil infiltration into β-Lap-treated tumors. Blocking this cascade or depleting neutrophil infiltration abolishes the antigen-specific T cell response induced by β-Lap treatment. Overall, this study provides comprehensive insights into the role of tumor-infiltrating neutrophils in the β-Lap-induced antitumor activity against NQO1-positive murine tumors.

The wire arc additive manufacturing (WAAM) process often results in geometric inaccuracies in the produced struts, highlighting the need for in-situ monitoring. Industrial cameras struggle to capture accurate images due to interference from arc light and metal radiation. This study introduces a real-time visual reconstruction method that leverages regions of interest (ROI) to enhance profile accuracy. Initially, the melt pool is analyzed and segmented from a series of frames to establish an initial strut profile. This profile then serves as the ROI for segmenting the solidified weld bead regions, yielding a more precise strut profile. Comparative analysis shows that the proposed method achieves a high Intersection Over Union (IOU) score of 0.911 and an Average Symmetric Surface Distance (ASD) error of 0.355 mm, demonstrating both accuracy and robustness. Additionally, the inclination angle and diameter are extracted from the reconstructed profiles.

Abstract In this paper, a class of fractional Sturm–Liouville advection–dispersion equations with instantaneous and noninstantaneous impulses is considered, in particular, the nonlinearities discussed here include Caputo fractional derivatives. Since the nonlinear terms contain fractional derivatives, this problem does not directly have variational structure, we need to combine critical point theory and an iterative method to deal with such problems. Finally, the existence of at least one nontrivial solution is proved by the mountain pass theorem and the iterative method. At the same time, an example is given to illustrate the main result.

In this paper, we investigated the nonlinear vibration characteristics and time-delay feedback controllability of a fractional horizontal roll system, which is described by a fractional Duffing-van der Pol oscillator under an external harmonic excitation. We focused on the resonance of fractional roller systems and conducted corresponding vibration control. The amplitude-frequency equations of primary resonance and superharmonic resonance were obtained using the multiple scale method. The amplitude-frequency characteristic curves of the system with different parameters were presented, and the influence of system parameters on the curves was analyzed. In addition, the time-delay feedback controller was designed to control the parameter excitation vibration. The numerical simulation results have verified the effectiveness of the time-delay controller in eliminating the jumping and hysteresis phenomena of the rolling system. The comparisons of approximate analytical solution and numerical solution was fulfilled, and the result certifies the correctness and satisfactory precision of the approximately analytical solution. The analysis results provide certain theoretical guidance for the vibration reduction of the horizontal nonlinear roller system.

Abstract Background Hypertension (HTN) involves genetic variability in the renin‐angiotensin system and influences antihypertensive response. We previously reported that angiotensinogen (AGT) messenger RNA (mRNA) is endogenously bound by miR‐122‐5p and rs699 A > G decreases reporter mRNA in the microRNA functional‐assay PASSPORT‐seq. The AGT promoter variant rs5051 C > T is in linkage disequilibrium (LD) with rs699 A > G and increases AGT transcription. The independent effect of these variants is understudied due to their LD therefore we aimed to test the hypothesis that increased AGT by rs5051 C > T counterbalances AGT decreased by rs699 A > G, and when these variants occur independently, it translates to HTN‐related phenotypes. Methods We used in silico, in vitro, in vivo, and retrospective models to test this hypothesis. Results In silico, rs699 A > G is predicted to increase miR‐122‐5p binding affinity by 3%. Mir‐eCLIP results show rs699 is 40–45 nucleotides from the strongest microRNA‐binding site in the AGT mRNA. Unexpectedly, rs699 A > G increases AGT mRNA in an AGT‐plasmid‐cDNA HepG2 expression model. Genotype‐Tissue Expression (GTEx) and UK Biobank analyses demonstrate liver AGT expression and HTN phenotypes are not different when rs699 A > G occurs independently from rs5051 C > T. However, GTEx and the in vitro experiments suggest rs699 A > G confers cell‐type‐specific effects on AGT mRNA abundance, and suggest paracrine renal renin‐angiotensin‐system perturbations could mediate the rs699 A > G associations with HTN. Conclusions We found that rs5051 C > T and rs699 A > G significantly associate with systolic blood pressure in Black participants in the UK Biobank, demonstrating a fourfold larger effect than in White participants. Further studies are warranted to determine if altered antihypertensive response in Black individuals might be due to rs5051 C > T or rs699 A > G. Studies like this will help clinicians move beyond the use of race as a surrogate for genotype.

Abstract Culture-dependent and metagenomic binning techniques were employed to gain an insight into the diversification of gut bacteria in Rhinopithecius bieti, a highly endangered primate endemic to China. Our analyses revealed that Bacillota_A and Bacteroidota were the dominant phyla. These two phyla species are rich in carbohydrate active enzymes, which could provide nutrients and energy for their own or hosts’ survival under different circumstances. Among the culturable bacteria, one novel bacterium, designated as WQ 2009T, formed a distinct branch that had a low similarity to the known species in the family Sphingobacteriaceae, based on the phylogenetic analysis of its 16S rRNA gene sequence or phylogenomic analysis. The ANI, dDDH and AAI values between WQ 2009T and its most closely related strains S. kitahiroshimense 10CT, S. pakistanense NCCP-246T and S. faecium DSM 11690T were significantly lower than the accepted cut-off values for microbial species delineation. All results demonstrated that WQ 2009T represent a novel genus, for which names Rhinopithecimicrobium gen. nov. and Rhinopithecimicrobium faecis sp. nov. (Type strain WQ 2009T = CCTCC AA 2021153T = KCTC 82941T) are proposed.

Abstract Training large neural networks on big datasets requires significant computational resources and time. Transfer learning reduces training time by pre-training a base model on one dataset and transferring the knowledge to a new model for another dataset. However, current choices of transfer learning algorithms are limited because the transferred models always have to adhere to the dimensions of the base model and can not easily modify the neural architecture to solve other datasets. On the other hand, biological neural networks (BNNs) are adept at rearranging themselves to tackle completely different problems using transfer learning. Taking advantage of BNNs, we design a dynamic neural network that is transferable to any other network architecture and can accommodate many datasets. Our approach uses raytracing to connect neurons in a three-dimensional space, allowing the network to grow into any shape or size. In the Alcala dataset, our transfer learning algorithm trains the fastest across changing environments and input sizes. In addition, we show that our algorithm also outperformance the state of the art in EEG dataset. In the future, this network may be considered for implementation on real biological neural networks to decrease power consumption.

Background The clinical characteristics and survival outcomes of patients who underwent concomitant coronary artery bypass grafting during septal myectomy have not been well studied. Methods and Results We reviewed patients who underwent both septal myectomy and coronary artery bypass grafting from 2009 to 2020. Causes of concomitant grafting and their impact on survival were analyzed. The median follow‐up period was 5.1 years. A total of 320 patients underwent both grafting and myectomy. Of these, 69.7% and 28.1% underwent grafting attributed to atherosclerotic coronary artery disease and myocardial bridging, respectively. Patients who underwent grafting for coronary artery disease tended to be older, had a longer bypass time, and required more grafts compared with patients undergoing procedures because of myocardial bridging (all P95% and improved functional class of >90%.

ABSTRACT Background Lymph node metastasis (LNM) is a critical factor affecting the outcomes of head and neck squamous cell carcinoma (HNSCC) and the main reason for treatment failure. This study was designed to examine the effects of the key genes involved in the LNM of HNSCC. Methods Tissue samples (HNSCC) were examined by transcriptome sequencing, and the core genes associated with LNM were detected via bioinformatics analysis. The functions of these core genes were then validated using the TCGA biological database and their effects on the propagation, invasion, and metastasis of HNSCC cells were evaluated through cell culture experiments. Moreover, the effect of core gene expression on the LNM capability of HNSCC was confirmed via a footpad xenograft mice model. Results In the findings, a key gene involved in the LNM of HNSCC was identified as SLC7A2. It was correlated with adverse clinical prognosis and expressed with low expression in HNSCC tissues. As shown in cell culture experiments, FaDu and SCC15 cell growth, invasion, and migration were inhibited when SLC7A2 was overexpressed. Further, cell apoptosis was stimulated, and lymphangiogenesis was suppressed through the downregulation of CPB2 expression. Animal studies demonstrated that the growth and LNM of HNSCC cells were inhibited by SLC7A2 overexpression. Conclusion It is concluded that SLC7A2 is involved in HNSCC lymphatic metastasis by controlling CPB2 function. The results are anticipated to offer new directions for the effective treatment of HNSCC.

BackgroundHepatocellular carcinoma (HCC) patients exhibiting portal vein tumor thrombosis (PVTT) face a high risk of rapid malignant progression and poor outcomes, with this issue being compounded by a lack of effective treatment options. The integration of bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) datasets focused on samples from HCC patients with PVTT has the potential to yield unprecedented insight into the dynamic changes in the tumor microenvironment (TME) and associated immunological characteristics in these patients, providing an invaluable tool for the reliable prediction of disease progression and treatment responses.MethodsscRNA-seq data from both primary tumor (PT) and PVTT cells were downloaded from the Gene Expression Omnibus (GEO) database, while the International Cancer Genome Consortium (ICGC) and Cancer Genome Atlas (TCGA) databases were used to access bulk RNA-seq datasets. scRNA-seq, clustering, GSVA enrichment, mutational profiling, and predictive immunotherapeutic treatment analyses were conducted using these data with the goal of systematically assessing the heterogeneity of PT and PVTT cells and establishing a model capable of predicting immunotherapeutic and prognostic outcomes in patients with HCC.ResultsThese analyses revealed that PVTT cells exhibited patterns of tumor proliferation, stromal activation, and low levels of immune cell infiltration, presenting with immune desert and immune rejection-like phenotypes. PT cells, in contrast, were found to exhibit a pattern of immunoinflammatory activity. Core PVTT-associated genes were clustered into three patterns consistent with the tumor immune rejection and immune desert phenotypes. An established clustering model was capable of predicting tumor inflammatory stage, subtype, TME stromal activity, and patient outcomes. PVTT signature genes were further used to establish a risk model, with the risk scores derived from this model providing a tool to evaluate patient clinicopathological features including clinical stage, tumor differentiation, histological subtype, microsatellite instability status, and tumor mutational burden. These risk scores were also able to serve as an independent predictor of patient survival outcomes, responses to adjuvant chemotherapy, and responses to immunotherapy. In vitro experiments were used to partially validate the biological prediction results.ConclusionThese results offer new insight into the biological and immunological landscape of PVTT in HCC patients, By utilizing individual patient risk scores, providing an opportunity to guide more effective immunotherapeutic interventional efforts.

Abstract The development of cost-effective and eco-friendly fertilizers is crucial for enhancing iron (Fe) uptake in crops and can help alleviate dietary Fe deficiencies, especially in populations with limited access to meat. This study focused on the application of MgFe-layered double hydroxide nanoparticles (MgFe-LDHs) as a potential solution. We successfully synthesized and characterized MgFe-LDHs and observed that 1–10 mg/L MgFe-LDHs improved cucumber seed germination and water uptake. Notably, the application of 10 mg/L MgFe-LDHs to roots significantly increased the seedling emergence rate and growth under low-temperature stress. The application of 10 mg/L MgFe-LDHs during sowing increased the root length, lateral root number, root fresh weight, aboveground fresh weight, and hypocotyl length under low-temperature stress. A comprehensive analysis integrating plant physiology, nutrition, and transcriptomics suggested that MgFe-LDHs improve cold tolerance by upregulating SA to stimulate CsFAD3 expression, elevating GA3 levels for enhanced nitrogen metabolism and protein synthesis, and reducing levels of ABA and JA to support seedling emergence rate and growth, along with increasing the expression and activity of peroxidase genes. SEM and FTIR further confirmed the adsorption of MgFe-LDHs onto the root hairs in the mature zone of the root apex. Remarkably, MgFe-LDHs application led to a 46% increase (p

Abstract Background Patients with hypopharyngeal carcinoma (HPC) have a poor prognosis mainly because of lymphatic metastasis. This research aimed to determine the PKM2 role in lymphatic metastasis in HPC and the underlying molecular mechanism contributing to this phenomenon. Methods PKM2 in HPC was studied for its expression and its likelihood of overall survival using TCGA dataset. Western blotting, qRT-PCR, and IHC were employed to confirm PKM2 expression. Methods including gain- and loss-of-function were used to examine the PKM2 role in HPC metastasis in vitro and in vivo. In vitro and in vivo studies also confirmed lymphatic metastasis’s mechanism. Results Prominent PKM2 overexpression was seen in patients with lymphatic metastasis of HPC, and there was an inherent relationship between a high PKM2 level and poor prognosis. In vitro research showed that knocking down PKM2 decreased tumor cell invasion, migration, and proliferation while promoting apoptosis and inhibiting epithelial-mesenchymal transition, but overexpressing PKM2 had the reverse effect. Animal studies suggested that PKM2 may facilitate tumor development and lymphatic metastasis. Conclusions Our findings suggest that PKM2 may be a tumor’s promoter gene of lymphatic metastasis, which may promote lymphatic metastasis of HPC by regulating epithelial-mesenchymal transition. PKM2 may be a biomarker of metastatic potential, ultimately providing a basis for exploring new therapeutic targets.

Abstract Background The underrepresentation of human genomic resources from Southern Chinese populations limited their health equality in the precision medicine era and complete understanding of their genetic formation, admixture, and adaptive features. Besides, linguistical and genetic evidence supported the controversial hypothesis of their origin processes. One hotspot case was from the Chinese Guangxi Pinghua Han people (GPH), whose language was significantly similar to Southern Chinese dialects but whose uniparental gene pool was phylogenetically associated with the indigenous Tai-Kadai (TK) people. Here, we analyzed genome-wide SNP data in 619 people from four language families and 56 geographically different populations, in which 261 people from 21 geographically distinct populations were first reported here. Results We identified significant population stratification among ethnolinguistically diverse Guangxi populations, suggesting their differentiated genetic origin and admixture processes. GPH shared more alleles related to Zhuang than Southern Han Chinese but received more northern ancestry relative to Zhuang. Admixture models and estimates of genetic distances showed that GPH had a close genetic relationship with geographically close TK compared to Northern Han Chinese, supporting their admixture origin hypothesis. Further admixture time and demographic history reconstruction supported GPH was formed via admixture between Northern Han Chinese and Southern TK people. We identified robust signatures associated with lipid metabolisms, such as fatty acid desaturases (FADS) and medically relevant loci associated with Mendelian disorder (GJB2) and complex diseases. We also explored the shared and unique selection signatures of ethnically different but linguistically related Guangxi lineages and found some shared signals related to immune and malaria resistance. Conclusions Our genetic analysis illuminated the language-related fine-scale genetic structure and provided robust genetic evidence to support the admixture hypothesis that can explain the pattern of observed genetic diversity and formation of GPH. This work presented one comprehensive analysis focused on the population history and demographical adaptative process, which provided genetic evidence for personal health management and disease risk prediction models from Guangxi people. Further large-scale whole-genome sequencing projects would provide the entire landscape of southern Chinese genomic diversity and their contributions to human health and disease traits.

Abstract Targeting ferroptosis, an iron-dependent form of regulated cell death triggered by the lethal overload of lipid peroxides, in cancer therapy is impeded by our limited understanding of the intersection of tumour’s metabolic feature and ferroptosis vulnerability. In the present study, arginine is identified as a ferroptotic promoter using a metabolites library. This effect is mainly achieved through arginine’s conversion to polyamines, which exerts their potent ferroptosis-promoting property in an H2O2-dependent manner. Notably, the expression of ornithine decarboxylase 1 (ODC1), the critical enzyme catalysing polyamine synthesis, is significantly activated by the ferroptosis signal——iron overload——through WNT/MYC signalling, as well as the subsequent elevated polyamine synthesis, thus forming a ferroptosis-iron overload-WNT/MYC-ODC1-polyamine-H2O2 positive feedback loop that amplifies ferroptosis. Meanwhile, we notice that ferroptotic cells release enhanced polyamine-containing extracellular vesicles into the microenvironment, thereby further sensitizing neighbouring cells to ferroptosis and accelerating the “spread” of ferroptosis in the tumour region. Besides, polyamine supplementation also sensitizes cancer cells or xenograft tumours to radiotherapy or chemotherapy through inducing ferroptosis. Considering that cancer cells are often characterized by elevated intracellular polyamine pools, our results indicate that polyamine metabolism exposes a targetable vulnerability to ferroptosis and represents an exciting opportunity for therapeutic strategies for cancer.

Indoor air quality and energy efficiency are instrumental aspects of school facility design and construction, as they directly affect the physical well-being, comfort, and academic output of both pupils and staff. The challenge of balancing the need for adequate ventilation to enhance indoor air quality with the goal of reducing energy consumption has long been a topic of debate. The implementation of mixed-mode ventilation systems with automated controls presents a promising solution to address this issue. However, a comprehensive literature review on this subject is still missing. To address this gap, this review examines the potential application of mixed-mode ventilation systems as a solution to attaining improved energy savings without compromising indoor air quality and thermal comfort in educational environments. Mixed-mode ventilation systems, which combine natural ventilation and mechanical ventilation, provide the versatility to alternate between or merge both methods based on real-time indoor and outdoor environmental conditions. By analyzing empirical studies, case studies, and theoretical models, this review investigates the efficacy of mixed-mode ventilation systems in minimizing energy use and enhancing indoor air quality. Essential elements such as operable windows, sensors, and sophisticated control technologies are evaluated to illustrate how mixed-mode ventilation systems dynamically optimize ventilation to sustain comfortable and healthy indoor climates. This paper further addresses the challenges linked to the design and implementation of mixed-mode ventilation systems, including complexities in control and the necessity for climate-adaptive strategies. The findings suggest that mixed-mode ventilation systems can considerably lower heating, ventilation, and air conditioning energy usage, with energy savings ranging from 20% to 60% across various climate zones, while also enhancing indoor air quality with advanced control systems and data-driven control strategies. In conclusion, mixed-mode ventilation systems offer a promising approach for school buildings to achieve energy efficiency and effective ventilation without sacrificing indoor environment quality.

Chalcogen bonds (ChBs) involving selenium have attracted substantial scholarly interest in past years owing to their fundamental roles in various chemical and biological fields. However, the effect of the valency state of the electron-deficient selenium atom on the characteristics of such ChBs remains unexplored. Herein, we comparatively studied the σ-hole-type Se∙∙∙O ChBs between SeF2/SeF4 and a series of oxygen-bearing Lewis bases, including water, methanol, dimethyl ether, ethylene oxide, formaldehyde, acetaldehyde, acetone, and formic acid, using ab initio computations. The interaction energies of these chalcogen-bonded heterodimers vary from −5.25 to −11.16 kcal/mol. SeF2 participates in a shorter and stronger ChB than SeF4 for all the examined heterodimers. Such Se∙∙∙O ChBs are closed-shell interactions, exhibiting some covalent character for all the examined heterodimers, except for SeF4∙∙∙water. Most of these chalcogen-bonded heterodimers are predominantly stabilized through orbital interactions between the lone pair of the O atom in Lewis bases and the σ*(Se–F) antibonding orbitals of Lewis acids. The back-transfer of charge from the lone pair of selenium into the σ* or π* antibonding orbitals of Lewis bases is also observed for all systems. Energy decomposition analysis reveals that the electrostatic component significantly stabilizes the targeted heterodimers, while the induction and dispersion contributions cannot be ignored.

Background: Tumor necrosis (TN) is a common feature in lung squamous cell carcinoma (LSCC), which could provide useful predictive and prognostic information. Objectives: This study aimed to investigate the effect of pretreatment pulmonary TN (PTN) on the prognosis of first-line anti-programmed cell death 1 (PD-1)/PD ligand 1 (PD-L1) inhibitor in advanced LSCC. Design: We conducted a retrospective study to analyze the association between the presence of PTN and clinical outcomes in advanced LSCC patients treated with anti-PD-1/PD-L1 inhibitors. Methods: Data from 240 eligible patients were collected from 27 hospitals across China between 2016 and 2020. The presence of PTN was assessed using contrast-enhanced chest computed tomography (CT) imaging at baseline. We utilized the Cox proportional-hazards regression model to analyze the association between PTN and clinical outcomes. In addition, to account for potential confounding factors and ensure comparability between groups, we employed propensity score-matching (PSM) analysis. Results: In the overall patient cohort, the presence of PTN was 39.6%. The median follow-up duration was 20.3 months. The positive PTN group exhibited a notably inferior median progression-free survival (PFS; 6.5 months vs 8.6 months, p = 0.012) compared to the negative PTN group. Within the Cox proportional-hazards regression model, PTN emerged as an independent predictor of unfavorable PFS (hazard ratio (HR) = 1.354, 95% confidence interval (CI): 1.002–1.830, p = 0.049). After PSM, the median PFS for the positive PTN group (6.5 months vs 8.0 months, p = 0.027) remained worse than that of the negative PTN group. Multivariate analyses also further underscored that the presence of PTN independently posed a risk for shorter PFS (HR = 1.494, 95% CI: 1.056–2.112, p = 0.023). However, no statistically significant difference in overall survival was observed between the two groups. Conclusion: Our study suggests that the presence of PTN on baseline contrast-enhanced chest CT is a potential negative prognostic imaging biomarker for the outcome of anti-PD-1/PD-L1 inhibitor therapy in advanced LSCC. Further studies are warranted to validate these findings and explore the underlying mechanisms.

To realize transparent monitoring and resilience improvement of low-voltage distribution network, both the data acquisition scope and frequency have been greatly expanded. Cloud-edge collaboration leverages the edge server’s real-time response capabilities and the cloud server’s robust data processing power to enhance the performance of high-frequency data acquisition processing. Nonetheless, it continues to confront challenges such as the entanglement of optimization variables, the presence of uncertain information, and a lack of awareness regarding acquisition frequencies. In this paper, we propose a machine learning-based cloud-edge collaborative data processing optimization algorithm to minimize the weighted sum of data processing delay and device energy consumption for distribution network resilience improvement. The joint optimization problem is decoupled into device-edge data offloading subproblem and edge-cloud data splitting subproblem, which are solved by the proposed upper confidence bound (UCB) based frequency-aware device-edge data offloading optimization algorithm and the exponential-weight algorithm for exploration and exploitation (EXP3) based edge-cloud data splitting optimization algorithm, respectively. Simulation results show that the proposed algorithm is superior to existing algorithms in performances of energy consumption and total processing delay.

BackgroundWhile several studies have noted a higher SII correlates with multiple diseases, research on the association between SII and atopic dermatitis remains limited. Our cross-sectional study seeks to examine the association between SII and atopic dermatitis among outpatient US adults.MethodsThis compensatory cross-sectional study utilized NHANES data from 2001–2006 cycles, conducting sample-weighted multivariate logistic regression and stratified analysis of sub-groups.ResultsHigher levels of SII were positively associated with an increased risk of atopic dermatitis in adults with BMI

BackgroundCardioembolic Stroke (CS) and Atrial Fibrillation (AF) are prevalent diseases that significantly impact the quality of life and impose considerable financial burdens on society. Despite increasing evidence of a significant association between the two diseases, their complex interactions remain inadequately understood. We conducted bioinformatics analysis and employed machine learning techniques to investigate potential shared biomarkers between CS and AF.MethodsWe retrieved the CS and AF datasets from the Gene Expression Omnibus (GEO) database and applied Weighted Gene Co-Expression Network Analysis (WGCNA) to develop co-expression networks aimed at identifying pivotal modules. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the shared genes within the modules related to CS and AF. The STRING database was used to build a protein-protein interaction (PPI) network, facilitating the discovery of hub genes within the network. Finally, several common used machine learning approaches were applied to construct the clinical predictive model of CS and AF. ROC curve analysis to evaluate the diagnostic value of the identified biomarkers for AF and CS.ResultsFunctional enrichment analysis indicated that pathways intrinsic to the immune response may be significantly involved in CS and AF. PPI network analysis identified a potential association of 4 key genes with both CS and AF, specifically PIK3R1, ITGAM, FOS, and TLR4.ConclusionIn our study, we utilized WGCNA, PPI network analysis, and machine learning to identify four hub genes significantly associated with CS and AF. Functional annotation outcomes revealed that inherent pathways related to the immune response connected to the recognized genes might could pave the way for further research on the etiological mechanisms and therapeutic targets for CS and AF.

Background and purposeArteriosclerotic cerebral small vessel disease (aCSVD) is a cause of cognitive impairment, dementia, and stroke. Developing a better understanding of the risk factor of aCSVD is key to reducing the incidence of these conditions. This study investigated the association between intracranial arterial calcification (IAC) and total cerebral small vessel disease (CSVD) burden score.Materials and methodsThis is a retrospective study, the subjects were transient ischemic attack (TIA) or acute ischemic stroke (AIS) patients. The data of 303 inpatients admitted to our study hospital between December 2018 and July 2020 were analyzed. Four imaging markers of CSVD (lacunes, white matter hyperintensities, cerebral microbleeds, and enlarged perivascular spaces) were evaluated by magnetic resonance imaging, and a total CSVD burden score was calculated. The experimental group was divided into four subgroups according to total CSVD burden score (1–4 points). Patients without CSVD (0 points) served as the control group. Head computerized tomography (CT) scans were used to assess ICA, using Babiarz’s method. The correlations between IAC and single imaging markers of CSVD were determined using Spearman’s rank correlation. Binary logic regression analysis and multivariate ordered logic regression analysis were used to determine the associations between IAC and aCSVD.ResultsIAC was positively correlated with total CSVD burden score (r = 0.681), deep white matter hyperintensities (r = 0.539), periventricular white matter hyperintensities (r = 0.570), cerebral microbleeds (r = 0.479), lacunes (r = 0.541), and enlarged perivascular spaces (r = 0.554) (all p

BackgroundPsoriasis is a chronic dermatological condition characterized by a complex pathogenesis that impacts approximately 3% of adults in the United States and brings enormous social burdens. For many diseases, the systemic immune-inflammatory index (SII), defined as neutrophils × platelets/lymphocytes, has been recognized as a prognostic indicator. Therefore, we conducted a cross-sectional study to assess the association between SII and psoriasis among outpatient US adults.MethodsIn this cross-sectional study, we used data on the US adults 20 to 59 years of age from the National Health and Nutrition Examination Survey (NHANES) spanning 2003–2006 and 2009–2014. Sample-weighted logistic regression and stratified analysis of subgroups were used.ResultsAmong the 16,831 adults, there were 8,801 women and 8,030 men, with a psoriasis prevalence rate of 3.0%. A fully adjusted model revealed a positive association between a SII higher than 479.15 × 109/L and a high risk of psoriasis. According to subgroup analysis and interaction testing (p for interaction > 0.05), age, sex, alcohol drinking status, marital status, and body mass index (BMI) were not significantly correlated with this positive association.ConclusionOur findings suggested that SII higher than 479.15 × 109/L was positively associated with a high risk of psoriasis among outpatient US adults. To the best of our knowledge, this is the first cross-sectional study using NHANES data focused on the risk of higher SII on psoriasis among outpatient US adults. The outcomes of this cross-sectional serve to supplement previous research, indicating a need for larger-scale prospective cohorts for further validation.

Necroptosis is implicated in the pathogenesis of ischemic stroke. However, the mechanism underlying the sequential recruitment of receptor-interacting protein kinase 1 (RIPK1) and N-ethylmaleimide-sensitive fusion ATPase (NSF) in initiating necroptosis remains poorly understood, and the role of NSF in ischemic stroke is a subject of controversy. Here, we utilized a recently emerging RNA-targeting CRISPR system known as CasRx, delivered by AAVs, to knockdown Ripk1 mRNA and Nsf mRNA around the ischemic brain tissue. This approach resulted in a reduction in infarct and edema volume, as well as an improvement in neurological deficits assessed by Bederson score, RotaRod test, and Adhesive removal test, which were achieved by RIPK1/receptor-interacting protein kinase 3/mixed lineage kinase domain-like protein signaling pathway involved in neuronal necroptosis. In conclusion, the downregulation of Ripk1 mRNA and Nsf mRNA mediated by CRISPR-CasRx holds promise for future therapeutic applications aimed at ameliorating cerebral lesions and neurological deficits following the ischemic stroke.

PurposeLymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC).MethodsThis cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell’s concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach.ResultsIndependent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability.ConclusionLODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.

Abstract Objective To investigate whether T2-weighted imaging (T2WI)-based intratumoral and peritumoral radiomics can predict extranodal extension (ENE) and prognosis in patients with resectable rectal cancer. Methods One hundred sixty-seven patients with resectable rectal cancer including T3T4N + cases were prospectively included. Radiomics features were extracted from intratumoral, peritumoral 3 mm, and peritumoral-mesorectal fat on T2WI images. Least absolute shrinkage and selection operator regression were used for feature selection. A radiomics signature score (Radscore) was built with logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each Radscore. A clinical-radiomics nomogram was constructed by the most predictive radiomics signature and clinical risk factors. A prognostic model was constructed by Cox regression analysis to identify 3-year recurrence-free survival (RFS). Results Age, cT stage, and lymph node-irregular border and/or adjacent fat invasion were identified as independent clinical risk factors to construct a clinical model. The nomogram incorporating intratumoral and peritumoral 3 mm Radscore and independent clinical risk factors achieved a better AUC than the clinical model in the training (0.799 vs. 0.736) and validation cohorts (0.723 vs. 0.667). Nomogram-based ENE (hazard ratio [HR] = 2.625, 95% CI = 1.233–5.586, p = 0.012) and extramural vascular invasion (EMVI) (HR = 2.523, 95% CI = 1.247–5.106, p = 0.010) were independent risk factors for predicting 3-year RFS. The prognostic model constructed by these two indicators showed good performance for predicting 3-year RFS in the training (AUC = 0.761) and validation cohorts (AUC = 0.710). Conclusion The nomogram incorporating intratumoral and peritumoral 3 mm Radscore and clinical risk factors could predict preoperative ENE. Combining nomogram-based ENE and MRI-reported EMVI may be useful in predicting 3-year RFS. Critical relevance statement A clinical-radiomics nomogram could help preoperative predict ENE, and a prognostic model constructed by the nomogram-based ENE and MRI-reported EMVI could predict 3-year RFS in patients with resectable rectal cancer. Key points • Intratumoral and peritumoral 3 mm Radscore showed the most capability for predicting ENE. • Clinical-radiomics nomogram achieved the best predictive performance for predicting ENE. • Combining clinical-radiomics based-ENE and EMVI showed good performance for 3-year RFS. Graphical Abstract

Abstract Background Lung cancer is one of the most common tumors in the world, and metastasis is one of the major causes of tumor-related death in lung cancer patients. Tumor-associated macrophages (TAMs) are a major component of the tumor microenvironment (TME) and are frequently associated with tumor metastasis in human cancers. However, the regulatory mechanisms of TAMs in lung cancer metastasis remain unclear. Methods Single-cell sequencing analysis of lung cancer and normal tissues from public databases and from 14 patients who underwent surgery at Zhongshan Hospital was performed. In vitro co-culture experiments were performed to evaluate the effects of TAMs on lung cancer migration and invasion. Changes in the expression of IL-6, STAT3, C/EBPΒ, and EMT pathway were verified using RT-qPCR, western blotting, and immunofluorescence. Dual luciferase reporter assays and ChIP were used to reveal potential regulatory sites on the transcription factor sets. In addition, the effects of TAMs on lung cancer progression and metastasis were confirmed by in vivo models. Results TAM infiltration is associated with tumor progression and poor prognosis. IL-6 secreted by TAMs can activate the JAK2/STAT3 pathway through autocrine secretion, and STAT3 acts as a transcription factor to activate the expression of C/EBPβ, which further promotes the transcription and expression of IL-6, forming positive feedback loops for IL6-STAT3-C/EBPβ-IL6 in TAMs. IL-6 secreted by TAMs promotes lung cancer progression and metastasis in vivo and in vitro by activating the EMT pathway, which can be attenuated by the use of JAK2/STAT3 pathway inhibitors or IL-6 monoclonal antibodies. Conclusions Our data suggest that TAMs promote IL-6 expression by forming an IL6-STAT3-C/EBPβ-IL6 positive feedback loop. Released IL-6 can induce the EMT pathway in lung cancer to enhance migration, invasion, and metastasis. The use of IL-6-neutralizing antibody can partially counteract the promotion of LUAD by TAMs. A novel mechanism of macrophage-promoted tumor progression was revealed, and the IL6-STAT3-C/EBPβ-IL6 signaling cascade may be a potential therapeutic target against lung cancer. Graphical Abstract IL-6 secreted by TAM acts on itself to promote STAT3 phosphorylation, and pSTAT3 transfers into the nucleus, promotes the expression of C/EBPβ. C/EBPβ is able to further promote IL-6 expression, which forms positive feedback for IL-6 secretion. IL-6 secreted by TAMs acts on lung cancer to promote their metastasis through activation of EMT.

Abstract Loess-paleosol sequences have been used in Asia to study climate and environmental changes during the Quaternary. The scarcity of age control datasets and proxy indices analysis data for Asian loess has limited our understanding of loess depositional processes and the reconstruction of paleoclimatic changes from loess-paleosol records. In this study, we present a dataset that includes 1785 quartz optically stimulated luminescence ages and 1038 K-feldspar post-infrared infrared stimulated luminescence ages from 128 loess-paleosol sequences located in different regions of Asia. We generate 38 high-resolution age-depth models of loess records based on the provided datasets. We provide data on 12,365 grain size records, 14,964 magnetic susceptibility records, 2204 CaCO3 content records, and 3326 color reflection records. This dataset contains the most detailed and accurate chronologies and proxy index data for loess records in Asia yet published. It provides fundamental data for understanding the spatial-temporal variations in loess depositional processes and climatic changes across the continent during the mid-late Quaternary.

Abstract Background The hydrolysis and transphosphatidylation of phospholipase D (PLD) play important roles in the interconversion of phospholipids (PLs), which has been shown to profoundly impact lipid metabolism in plants. In this study, the effect of the PLD1 gene of Schizochytrium limacinum SR21 (S. limacinum SR21) on lipid metabolism was investigated. Results PLD1 knockout had little impact on cell growth and lipid production, but it significantly improved the percentage of polyunsaturated fatty acids in lipids, of which docosahexaenoic acid (DHA) content increased by 13.3% compared to the wild-type strain. Phospholipomics and real-time quantitative PCR analysis revealed the knockout of PLD1 reduced the interexchange and increased de novo synthesis of PLs, which altered the composition of PLs, accompanied by a final decrease in phosphatidylcholine (PC) and an increase in phosphatidylinositol, lysophosphatidylcholine, and phosphatidic acid levels. PLD1 knockout also increased DHA content in triglycerides (TAGs) and decreased it in PLs. Conclusions These results indicate that PLD1 mainly performs the transphosphatidylation activity in S. limacinum SR21, and its knockout promotes the migration of DHA from PLs to TAGs, which is conducive to DHA accumulation and storage in TAGs via an acyl CoA-independent pathway. This study provides a novel approach for identifying the mechanism of DHA accumulation and metabolic regulation strategies for DHA production in S. limacinum SR21.

Most of the existing remote sensing image super-resolution (SR) methods based on deep learning tend to learn the mapping from low-resolution (LR) images to high-resolution (HR) images directly. But they ignore the potential structure and texture consistency of LR and HR spaces, which cause the loss of high-frequency information and produce artifacts. A structure-texture dual preserving method is proposed to solve this problem and generate pleasing details. Specifically, we propose a novel edge prior enhancement strategy that uses the edges of LR images and the proposed interactive supervised attention module (ISAM) to guide SR reconstruction. First, we introduce the LR edge map as a prior structural expression for SR reconstruction, which further enhances the SR process with edge preservation capability. In addition, to obtain finer texture edge information, we propose a novel ISAM in order to correct the initial LR edge map with high-frequency information. By introducing LR edges and ISAM-corrected HR edges, we build LR–HR edge mapping to preserve the consistency of LR and HR edge structure and texture, which provides supervised information for SR reconstruction. Finally, we explore the salient features of the image and its edges in the ascending space, and restored the difference between LR and HR images by residual and dense learning. A large number of experimental results on Draper and NWPU-RESISC45 datasets show that our model is superior to several advanced SR algorithms in both objective and subjective image quality.

Remote sensing images exhibit rich texture features and strong autocorrelation. Although the super-resolution (SR) method of remote sensing images based on convolutional neural networks (CNN) can capture rich local information, the limited perceptual field prevents it from establishing long-distance dependence on global information, leading to the low accuracy of remote sensing image reconstruction. Furthermore, it is difficult for existing SR methods to be deployed in mobile devices due to their large network parameters and high computational demand. In this study, we propose a lightweight distillation CNN-Transformer SR architecture, named DCTA, for remote sensing SR, addressing the aforementioned issues. Specifically, the proposed DCTA first extracts the coarse features through the coarse feature extraction layer and then learns the deep features of remote sensing at different scales by fusing the feature distillation extraction module of CNN and Transformer. In addition, we introduce the feature fusion module at the end of the feature distillation extraction module to control the information propagation, aiming to select the informative components for better feature fusion. The extracted low-resolution (LR) feature maps are reorganized through the up-sampling module to obtain high-resolution (HR) feature maps with high accuracy to generate high-quality HR remote sensing images. The experiments comparing different methods demonstrate that the proposed approach performs well on multiple datasets, including NWPU-RESISC45, Draper, and UC Merced. This is achieved by balancing reconstruction performance and network complexity, resulting in both competitive subjective and objective results.

Abstract The biochar amendment plays a vital role in maintaining soil health largely due to its effects on soil microbial communities. However, individual cases and the variability in biochar properties are not sufficient to draw universal conclusions. The present study aimed to reveal how the biochar application affects soil microbial communities. Metadata of 525 ITS and 1288 16S rRNA sequencing samples from previous studies were reanalyzed and machine learning models were applied to explore the dynamics of soil microbial communities under biochar amendment. The results showed that biochar considerably changed the soil bacterial and fungal community composition and enhanced the relative abundances of Acidobacteriota, Firmicutes, Basidiomycota, and Mortierellomycota. Biochar enhanced the robustness of the soil microbial community but decreased the interactions between fungi and bacteria. The random forest model combined with tenfold cross-validation were used to predict biomarkers of biochar response, indicating that potentially beneficial microbes, such as Gemmatimonadetes, Microtrichales, Candidatus_Kaiserbacteria, and Pyrinomonadales, were enriched in the soil with biochar amendment, which promoted plant growth and soil nutrient cycling. In addition, the biochar amendment enhanced the ability of bacteria to biosynthesize and led to an increase in fungal nutrient patterns, resulting in an increase in the abundance and diversity of saprophytic fungi that enhance soil nutrient cycling. The machine learning model more accurately revealed how biochar affected soil microbial community than previous independent studies. Our study provides a basis for guiding the reasonable use of biochar in agricultural soil and minimizing its negative effects on soil microecosystem. Graphical Abstract

Abstract Plastid ribosomal proteins play a crucial role in the growth and development of plants, mainly in the gene expression and translation of key genes in chloroplasts. While some information is known about the regulatory processes of plastid ribosomal proteins in various plant species, there is limited knowledge about the underlying mechanisms in rice. In this study, ethyl methanesulfonate (EMS) mutagenesis was used to generate a new mutant called wlp3 (white leaf and panicle3), characterized by white or albino leaves and panicles, which exhibited this phenotype from the second leaf stage until tillering. Furthermore, after a certain period, the newly emerging leaves developed the same phenotype as the rice variety ZH11, while the albino leaves of wlp3 showed an incomplete chloroplast structure and significantly low chlorophyll content. A transition mutation (T to C) at position 380 was identified in the coding region of the LOC_Os03g61260 gene, resulting in the substitution of isoleucine by threonine during translation. WLP3 encodes the ribosomal L18 subunit, which is localized in the chloroplast. Complementation experiments confirmed that LOC_Os03g61260 was responsible for the albino phenotype in rice. WLP3 has high expression in the coleoptile, leaves at the three-leaf stage, and panicles at the heading stage. Compared to the wild-type (WT), wlp3 exhibited reduced chlorophyll synthesis and significantly decreased expression levels of genes associated with plastid development. Yeast two-hybrid (Y2H) analysis revealed that WLP3 interacts with other ribosomal subunits, to influence chloroplast development. These results contribute to a better understanding of the underlying molecular mechanisms of chloroplast development and plastid gene translation.

Corn is widely cultivated on a global scale. However, high temperatures during storage and transportation can lead to thermal damage to the kernels, negatively impacting their quality. Traditional methods for identifying heat-damaged grains primarily rely on manual inspection, which is characterized by low efficiency and accuracy. This study proposes a novel identification method that integrates laser ultrasonic signals with infrared image texture features. A pulsed laser stimulates the seeds to generate laser ultrasonic signals, while an infrared camera captures infrared images of the seeds. We extract time-domain, frequency-domain, and Hilbert-domain features from the laser ultrasonic signals, in addition to texture features from the infrared images. These features are combined using Canonical Correlation Analysis (CCA). Subsequently, the fused features are classified using a Backpropagation (BP) neural network, Support Vector Machine (SVM), and Particle Swarm Optimization–Support Vector Machine (PSO–SVM). The results indicate that the recognition rate achieved with the fused ‘signal-image’ features reaches 99.17%, providing a novel approach for detecting heat-damaged corn seeds.

COVID-19 is an enveloped virus with a single-stranded RNA genome. The surface of the virus contains spike proteins, which enable the virus to attach to host cells and enter the interior of the cells. After entering the cell, the virus exploits the host cell’s mechanisms for replication and dissemination. Since the end of 2019, COVID-19 has spread rapidly around the world, leading to a large-scale epidemic. In response to the COVID-19 pandemic, the global scientific community quickly launched vaccine research and development. Vaccination is regarded as a crucial strategy for controlling viral transmission and mitigating severe cases. In this paper, we propose a novel mathematical model for COVID-19 infection incorporating vaccine-induced immunization failure. As a cornerstone of infectious disease prevention measures, vaccination stands as the most effective and efficient strategy for curtailing disease transmission. Nevertheless, even with vaccination, the occurrence of vaccine immunization failure is not uncommon. This necessitates a comprehensive understanding and consideration of vaccine effectiveness in epidemiological models and public health strategies. In this paper, the basic regeneration number is calculated by the next generation matrix method, and the local and global asymptotic stability of disease-free equilibrium point and endemic equilibrium point are proven by methods such as the Routh–Hurwitz criterion and Lyapunov functions. Additionally, we conduct fractional-order numerical simulations to verify that order 0.86 provides the best fit with COVID-19 data. This study sheds light on the roles of immunization failure and fractional-order control.

The purpose of this study is to provide some criteria for the existence and multiplicity of solutions for a class of fractional advection–dispersion coupled systems with nonlinear Sturm–Liouville conditions and instantaneous and non-instantaneous impulses. Specifically, the existence is derived through the Nehari manifold method, and the proof of multiplicity is based on Bonanno and Bisci’s critical point theorem, which does not require proof that the functional satisfies the Palais–Smale condition. Finally, to illustrate the obtained results, an example is provided.

In the evolving realm of ergonomics, there is a growing demand for enhanced comfortability, visibility, and accessibility in the operation of engineering machinery. This study introduces an innovative approach to assess the ergonomics of a driller’s cabin by utilizing a digital human. Through the utilization of inertial motion capture sensors, the method enables the operation of a virtual driller animated by real human movements, thereby producing more precise and realistic human–machine interaction data. Additionally, this study develops a simplified model for the human upper limbs, facilitating the calculation of joint forces and torques. An ergonomic analysis platform, encompassing a virtual driller’s cabin and a digital human model, is constructed using Unity 3D. This platform enables the quantitative evaluation of comfortability, visibility, and accessibility. Its versatility extends beyond the current scope, offering substantial support for product development and enhancement.

Abstract Layered double hydroxides (LDHs) have been widely used in the field of plant engineering, such as DNA/RNA transformation and enhancing plant disease resistance. However, few studies have examined the direct effects of LDHs on plants and their potential utility as nanofertilizers. In this study, the retention capacity of Cu/Fe-layered double hydroxide nanoparticles (CuFe-LDHs) was assessed by comparative experiments on vegetables. The results showed that the retention of CuFe-LDHs in leafy vegetables was high, such as lettuce. Phenotypic analysis revealed that the fresh and dry weights of lettuce leaves were both increased by spraying 10–100 μg/mL CuFe-LDHs. Using the optimal concentration of 10 μg/mL, we conducted further experiments to elucidate the mechanism of CuFe-LDHs promoting lettuce growth. It was found that the application of CuFe-LDHs had a significant effect on growth and induced physiological, transcriptomic, and metabolomic changes, including an increase in the chlorophyll b content, net photosynthetic rate, and intercellular carbon dioxide concentration, as well as modifications in gene expression patterns and metabolite profiles. This work provides compelling evidence that CuFe-LDHs can efficiently adsorb on the surface of lettuce leaves through hydrogen bonding, promote lettuce growth, mitigate the toxicity of heavy metal ions compared to their raw materials at the same concentration and offer a molecular-scale insight into the response of leafy vegetables to CuFe-LDHs. Graphical Abstract

Abstract Background This study’s objective was to investigate the predictors for severe anemia, severe leukopenia, and severe thrombocytopenia when amphotericin B deoxycholate-based induction therapy is used in HIV-infected patients with talaromycosis. Methods A total of 170 HIV-infected patients with talaromycosis were enrolled from January 1st, 2019, to September 30th, 2020. Results Approximately 42.9%, 20.6%, and 10.6% of the enrolled patients developed severe anemia, severe leukopenia, and severe thrombocytopenia, respectively. Baseline hemoglobin level 73.4 µmol/L (OR = 2.573, 95% CI: 1.157 ~ 5.723), AST/ALT ratio > 1.6 (OR = 2.479, 95% CI: 1.167 ~ 5.266), sodium level ≤ 136 mmol/liter (OR = 4.342, 95% CI: 1.747 ~ 10.789), and a dose of amphotericin B deoxycholate > 0.58 mg/kg/d (OR = 2.504, 95% CI:1.066 ~ 5.882) were observed to be independent risk factors associated with the development of severe anemia. Co-infection with tuberculosis (OR = 3.307, 95% CI: 1.050 ~ 10.420), and platelet level (per 10 × 109 /L) (OR = 0.952, 95% CI: 0.911 ~ 0.996) were shown to be independent risk factors associated with the development of severe leukopenia. Platelet level

Background Previous studies have shown that self-rated health would be used as a simple assessment indicator for frailty, and individuals with poor self-rated health status are at higher risk of frailty. However, the association between self-rated health and frailty may be different and the effectiveness of self-rated health in frailty assessment may vary in apathetic older adults. Objective To explore the moderating role of apathy in the association between self-rated health and frailty among community-dwelling older adults, so as to provide theoretical guidance for the application of the self-rated health in the assessment of frailty in apathetic older adults. Methods From November 2021 to March 2022, a total of 384 community-dwelling older adults were selected as respondents by convenience sampling method, including 179 cases in Nanjing Dongshan Community and 205 cases in Lianyungang Qinghu Community. Questionnaire surveys were conducted using the General Information Questionnaire, Fried Frailty Phenotyp (FFP) , Geriatric Depression Scale (GDS-3) , and the self-reported health (SRH) . Generalized linear model was used to analyze the association between self-rated health and frailty of community-dwelling older adults. The model 1 of the SPSS macro program process compiled by Hayes was used to analyze the moderating role of apathy on the association between the self-rated health and frailty, with simple slope analyze performed and simple slope graphs plotted. Results The median FFP and SRH item scores of 384 community-dwelling older adults were 1.00 (2.00) and 4.00 (1.00) , respectively, with the detection rate of apathy of 55.5% (213/384) . The results of the generalized linear model showed that the relationship between the self-rated health and frailty of community-dwelling older adults was significant (b=0.310, P

Summary: The USP7 deubiquitinase regulates proteins involved in the cell cycle, DNA repair, and epigenetics and has been implicated in cancer progression. USP7 inhibition has been pursued for the development of anti-cancer therapies. Here, we describe the discovery of potent and specific USP7 inhibitors exemplified by FX1-5303. FX1-5303 was used as a chemical probe to study the USP7-mediated regulation of p53 signaling in cells. It demonstrates mechanistic differences compared to MDM2 antagonists, a related class of anti-tumor agents that act along the same pathway. FX1-5303 synergizes with the clinically approved BCL2 inhibitor venetoclax in acute myeloid leukemia (AML) cell lines and ex vivo patient samples and leads to strong tumor growth inhibition in in vivo mouse xenograft models of multiple myeloma and AML. This work introduces new USP7 inhibitors, differentiates their mechanism of action from MDM2 inhibition, and identifies specific opportunities for their use in the treatment of AML.

IntroductionIn recent years, the perceptual capabilities of robots have been significantly enhanced. However, the task execution of the robots still lacks adaptive capabilities in unstructured and dynamic environments.MethodsIn this paper, we propose an ontology based autonomous robot task processing framework (ARTProF), to improve the robot's adaptability within unstructured and dynamic environments. ARTProF unifies ontological knowledge representation, reasoning, and autonomous task planning and execution into a single framework. The interface between the knowledge base and neural network-based object detection is first introduced in ARTProF to improve the robot's perception capabilities. A knowledge-driven manipulation operator based on Robot Operating System (ROS) is then designed to facilitate the interaction between the knowledge base and the robot's primitive actions. Additionally, an operation similarity model is proposed to endow the robot with the ability to generalize to novel objects. Finally, a dynamic task planning algorithm, leveraging ontological knowledge, equips the robot with adaptability to execute tasks in unstructured and dynamic environments.ResultsExperimental results on real-world scenarios and simulations demonstrate the effectiveness and efficiency of the proposed ARTProF framework.DiscussionIn future work, we will focus on refining the ARTProF framework by integrating neurosymbolic inference.