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Abstract Ion channels in retinal pigment epithelial (RPE) cells are crucial for retinal health and vision functions. Defects in such channels are intricately associated with the development of various retinopathies that cause blindness. Human pluripotent stem cells (hPSC)-derived RPE cells, including those from human-induced pluripotent stem cells (hiPSC) and human embryonic stem cells (hESC), have been used as in vitro models for investigating pathogenic mechanisms and screening potential therapeutic strategies for retinopathies. Therefore, the cellular status of hPSC-RPE cells, including maturity and physiologic functions, have been widely explored. Particularly, research on ion channels in hPSC-RPE cells can lead to the development of more stable models upon which robust investigations and clinical safety assessments can be performed. Moreover, the use of patient-specific hiPSC-RPE cells has significantly accelerated the clinical translation of gene therapy for retinal channelopathies, such as bestrophinopathies. This review consolidates current research on ion channels in hPSC-RPE cells, specifically Kir7.1, Bestrophin-1, CLC-2, and CaV1.3, providing a foundation for future research.

The integrative regeneration of both articular cartilage and subchondral bone remains an unmet clinical need due to the difficulties of mimicking spatial complexity in native osteochondral tissues for artificial implants. Layer-by-layer fabrication strategies, such as 3D printing, have emerged as a promising technology replicating the stratified zonal architecture and varying microstructures and mechanical properties. However, the dynamic and circulating physiological environments, such as mass transportation or cell migration, usually distort the pre-confined biological properties in the layered implants, leading to undistinguished spatial variations and subsequently inefficient regenerations. This study introduced a biomimetic calcified interfacial layer into the scaffold as a compact barrier between a cartilage layer and a subchondral bone layer to facilitate osteogenic–chondrogenic repair. The calcified interfacial layer consisting of compact polycaprolactone (PCL), nano-hydroxyapatite, and tasquinimod (TA) can physically and biologically separate the cartilage layer (TA-mixed, chondrocytes-load gelatin methacrylate) from the subchondral bond layer (porous PCL). This introduction preserved the as-designed independent biological environment in each layer for both cartilage and bone regeneration, successfully inhibiting vascular invasion into the cartilage layer and preventing hyaluronic cartilage calcification owing to devascularization of TA. The improved integrative regeneration of cartilage and subchondral bone was validated through gross examination, micro-computed tomography (micro-CT), and histological and immunohistochemical analyses based on an in vivo rat model. Moreover, gene and protein expression studies identified a key role of Caveolin (CAV-1) in promoting angiogenesis through the Wnt/β-catenin pathway and indicated that TA in the calcified layer blocked angiogenesis by inhibiting CAV-1.

With the development of a new generation of information technology, smart elderly care plays an important role in promoting the construction of elderly care services. The emerging application tools provide door-to-door meal service for urban elderly groups, solving meal problems for special and ordinary elderly with different priority levels and penalty costs of violating time windows. Based on this, considering the personalized needs of the elderly group, this study examines the route optimization problem of cooperative delivery of elderly meals by trucks and robots, and builds a mixed integer programming model to minimize the total cost of the system. For large-scale problems, this study designs an improved adaptive large neighbourhood search algorithm that incorporates simulated annealing algorithm and artificial bee colony algorithm to avoid falling into local optimality. Experiments have proved feasibility and effectiveness of the algorithm and proposed the corresponding management insights from the aspects of delivery efficiency and service quality.

Abstract Excess body weight (EBW) increases the risk of colorectal cancer (CRC) and is linked to lower colonoscopy compliance. Here, we extensively analyzed 981 metagenome samples from multiple cohorts to pinpoint the specific microbial signatures and their potential capability distinguishing EBW patients with CRC. The gut microbiome displayed considerable variations between EBW and lean CRC. We identify 44 and 37 distinct multi-kingdom microbial species differentiating CRC and controls in EBW and lean populations, respectively. Unique bacterial-fungal associations are also observed between EBW-CRC and lean-CRC. Our analysis revealed specific microbial functions in EBW-CRC, including D-Arginine and D-ornithine metabolism, and lipopolysaccharide biosynthesis. The best-performing classifier for EBW-CRC, comprising 12 bacterial and three fungal species, achieved an AUROC of 0.90, which was robustly validated across three independent cohorts (AUROC = 0.96, 0.94, and 0.80). Pathogenic microbial species, Anaerobutyricum hallii, Clostridioides difficile and Fusobacterium nucleatum, are EBW-CRC specific signatures. This work unearths the specific multi-kingdom microbial signatures for EBW-CRC and lean CRC, which may contribute to precision diagnosis and treatment of CRC.

Ischemic stroke is a major cause of mortality and disability worldwide, with limited treatment options available in clinical practice. The emergence of stem cell therapy has provided new hope to the field of stroke treatment via the restoration of brain neuron function. Exogenous neural stem cells are beneficial not only in cell replacement but also through the bystander effect. Neural stem cells regulate multiple physiological responses, including nerve repair, endogenous regeneration, immune function, and blood-brain barrier permeability, through the secretion of bioactive substances, including extracellular vesicles/exosomes. However, due to the complex microenvironment of ischemic cerebrovascular events and the low survival rate of neural stem cells following transplantation, limitations in the treatment effect remain unresolved. In this paper, we provide a detailed summary of the potential mechanisms of neural stem cell therapy for the treatment of ischemic stroke, review current neural stem cell therapeutic strategies and clinical trial results, and summarize the latest advancements in neural stem cell engineering to improve the survival rate of neural stem cells. We hope that this review could help provide insight into the therapeutic potential of neural stem cells and guide future scientific endeavors on neural stem cells.

Summary: Dysregulated macrophage polarization from pro-inflammatory M1 to anti-inflammatory M2 phenotypes underlies impaired cutaneous wound healing. This study reveals Vγ4+ γδ T cells spatiotemporally calibrate macrophage trajectories during skin repair via sophisticated interferon-γ (IFN-γ) conditioning across multiple interconnected tissues. Locally within wound beds, infiltrating Vγ4+ γδ T cells directly potentiate M1 activation and suppress M2 polarization thereby prolonging local inflammation. In draining lymph nodes, infiltrated Vγ4+ γδ T cells expand populations of IFN-γ-competent lymphocytes which disseminate systemically and infiltrate into wound tissues, further enforcing M1 macrophages programming. Moreover, Vγ4+γδ T cells flushed into bone marrow stimulate increased IFN-γ production, which elevates the output of pro-inflammatory Ly6C+monocytes. Mobilization of these monocytes continually replenishes the M1 macrophage pool in wounds, preventing phenotypic conversion to M2 activation. Thus, multi-axis coordination of macrophage activation trajectories by trafficking Vγ4+ γδ T cells provides a sophisticated immunological mechanism regulating inflammation timing and resolution during skin repair.

Current therapeutic strategies for ischemic stroke fall short of the desired objective of neurological functional recovery. Therefore, there is an urgent need to develop new methods for the treatment of this condition. Exosomes are natural cell-derived vesicles that mediate signal transduction between cells under physiological and pathological conditions. They have low immunogenicity, good stability, high delivery efficiency, and the ability to cross the blood–brain barrier. These physiological properties of exosomes have the potential to lead to new breakthroughs in the treatment of ischemic stroke. The rapid development of nanotechnology has advanced the application of engineered exosomes, which can effectively improve targeting ability, enhance therapeutic efficacy, and minimize the dosages needed. Advances in technology have also driven clinical translational research on exosomes. In this review, we describe the therapeutic effects of exosomes and their positive roles in current treatment strategies for ischemic stroke, including their anti-inflammation, anti-apoptosis, autophagy-regulation, angiogenesis, neurogenesis, and glial scar formation reduction effects. However, it is worth noting that, despite their significant therapeutic potential, there remains a dearth of standardized characterization methods and efficient isolation techniques capable of producing highly purified exosomes. Future optimization strategies should prioritize the exploration of suitable isolation techniques and the establishment of unified workflows to effectively harness exosomes for diagnostic or therapeutic applications in ischemic stroke. Ultimately, our review aims to summarize our understanding of exosome-based treatment prospects in ischemic stroke and foster innovative ideas for the development of exosome-based therapies.

Background: Sarcopenia is an intrinsic factor that leads to balance disorders and falls in older adults. However, the characterization of sarcopenia-related postural balance deficits remains unclear. Aims: This study aimed to explore the balance performance and postural control strategy in older adults with sarcopenia during static stance tasks using force platforms and surface electromyography. Methods: Older adults with right-sided dominance were recruited, including 27 adults with sarcopenia and 27 healthy counterparts. Postural sway was measured with eyes open/closed on rigid/compliant surfaces. The time- and frequency-domain indexes of bilateral lower extremity muscle activity were simultaneously recorded. Results: The postural sway and activity of multiple lower extremity muscles in the sarcopenia group were increased (P

The rapid digital revolution in recent decades has resulted in an overwhelming amount of information, particularly in the realm of modern education systems and related materials. This phenomenon, often referred to as information overload, necessitates the development of educational systems that can effectively search, classify, and categorize this vast amount of available information. Of utmost importance for such educational information systems is the safeguarding of personal data, which refers to information that can identify an individual or their family. School records, for example, contain various types of personal data such as the individual’s name, address, contact details, disciplinary history, as well as their grades and progress checks. Even if individuals choose to make this data public, it remains inherently personal. Another category of data involves more sensitive topics such as student biometrics (e.g. fingerprints, photographs), religious beliefs, health information (e.g. allergies), or dietary restrictions, which may imply religious or health-related aspects. Processing data in this category can pose risks to individuals; hence, strict rules and appropriate consent are necessary to ensure their protection. To address these challenges, this research paper proposes a zero-knowledge proof intelligent recommendation system designed to protect students’ data privacy in the digital age. The proposed method incorporates an Intelligent Recommendation System (IRS) that utilizes an optimized version of the Matrix Factorization technique, calculated as an Eulerian Walk chart. Furthermore, the Schnorr Zero-Knowledge Proof format, based on the discrete logarithm problem, ensures the privacy of personal data during message exchange between educational entities.

AbstractPaecilomyces variotii extract “ZhiNengCong” (ZNC) has been confirmed to be a high activity plant immune inducer, but its application effect and appropriate concentration in different crops and different environmental conditions need to be further verified. This study set up six treatments, including three ZNC concentration levels (0, 5, and 20 ng/mL) and two Ralstonia solanacearum (Rs) inoculation levels (with and without), to explore the effect of ZNC application on the growth and disease resistance of peppers. The results showed that ZNC application (particularly 5 ng/mL ZNC) increased the basal biomass of the pepper plant and promoted root growth. 5 ng/mL ZNC can improve photosynthetic performance (net photosynthetic rate, transpiration rate and chlorophyll content averagely increased 20.2%, 33.7% and 16.0%, respectively) and antioxidant enzyme activities (particularly, catalase activity averagely increased 38.9%) of peppers more efficient than 20 ng/mL. Moreover, 5 ng/mL ZNC significantly increased Rs resistance of pepper, while 20 ng/mL ZNC did not show this effect. In conclusion, 5 ng/mL ZNC had the most significant effects on the growth-promoting and disease resistance of peppers, indicating good application prospects in agricultural practice.

Abstract Echocardiography is essential in evaluating fetal cardiac anatomical structures and functions when clinicians conduct early treatment and screening for congenital heart defects, a common and intricate fetal malformation. Nevertheless, the prenatal detection rate of fetal CHD remains low since the peculiarities of fetal cardiac structures and the variousness of fetal CHD. Precisely segmenting four cardiac chambers can assist clinicians in analyzing cardiac morphology and further facilitate CHD diagnosis. Hence, we design a dual-path chain multi-scale gated axial-transformer network (DPC-MSGATNet) that simultaneously models global dependencies and local visual cues for fetal ultrasound (US) four-chamber (FC) views and further accurately segments four chambers. Our DPC-MSGATNet includes a global and a local branch that simultaneously operates on an entire FC view and image patches to learn multi-scale representations. We design a plug-and-play module, Interactive dual-path chain gated axial-transformer (IDPCGAT), to enhance the interactions between global and local branches. In IDPCGAT, the multi-scale representations from the two branches can complement each other, capturing the same region’s salient features and suppressing feature responses to maintain only the activations associated with specific targets. Extensive experiments demonstrate that the DPC-MSGATNet exceeds seven state-of-the-art convolution- and transformer-based methods by a large margin in terms of F1 and IoU scores on our fetal FC view dataset, achieving a F1 score of 96.87 $$\%$$ % and an IoU score of 93.99 $$\%$$ % . The codes and datasets can be available at https://github.comQiaoSiBo/DPC-MSGATNet .

Rice, a major food crop in China, contributes significantly to international food stability. Advances in rice genome sequencing, bioinformatics, and transgenic techniques have catalyzed Chinese researchers’ discovery of novel genes that control rice yield. These breakthroughs in research also encompass the analysis of genetic regulatory networks and the establishment of a new framework for molecular design breeding, leading to numerous transformative findings in this field. In this review, some breakthroughs in rice yield traits and a series of achievements in molecular design breeding in China in recent years are presented; the identification and cloning of functional genes related to yield traits and the development of molecular markers of rice functional genes are summarized, with the intention of playing a reference role in the following molecular design breeding work and how to further improve rice yield.

The leaf inclination angle is an important agronomic rice trait and an indicator of ideal plant architecture, yield and revenue. Based on 120 recombinant inbred lines (RILs) obtained from crossing of the F1 generation of the indica rice cultivar Huazhan as the male parent and the japonica rice cultivar Nekken2 as the female parent, followed by inbreeding for 12 generations, the leaf inclination angle of the first, second and third leaves from the top of the plants were analyzed. At the same time, quantitative trait locus (QTL) mapping of the leaf inclination angle was performed using encrypted genetic maps constructed for this population. A total of 33 QTLs were detected, including two related to the first leaf inclination angle (FLIA), nine related to the second leaf inclination angle (SLIA) (highest Lod value of 5.94), and 22 related to the third leaf inclination angle (TLIA) (highest Lod value of 8.53). At the same time, candidate genes analysis were conducted on the detected QTLs’ intervals, and a total of 15 candidate genes were screened. The expression levels of candidate genes were detected by RT-qPCR, we found that LOC_Os03g46920, LOC_Os03g52630, LOC_Os04g24328, LOC_Os08g25380, LOC_Os09g23200, LOC_Os09g32080, LOC_Os09g35940, LOC_Os09g37330 and LOC_Os09g37495 displayed extremely significant differences in expression between the parents. The results showed that these genes may be the cause of the difference in leaf inclination. The present study provided substantial foundation for the further validation of the function of leaf inclination angle genes and molecular breeding practices.

Premature senescence is a common occurrence in rice production, and seriously affects rice plants’ nutrient utilization and growth. A total of 120 recombinant inbred lines (RILs) were obtained from successive self-crossing of F12 generations derived from Huazhan and Nekken2. The superoxide dismutase (SOD) activity, malondialdehyde (MDA), content and catalase (CAT) activity related to the anti-senescence traits and enzyme activity index of rice were measured for QTL mapping using 4858 SNPs. Thirteen QTLs related to anti-senescence were found, among which the highest LOD score was 5.70. Eighteen anti-senescence-related genes were found in these regions, and ten of them differed significantly between the parents. It was inferred that LOC_Os01g61500, LOC_Os01g61810, and LOC_Os04g40130 became involved in the regulation of the anti-senescence molecular network upon upregulation of their expression levels. The identified anti-senescence-related QTLs and candidate genes provide a genetic basis for further research on the mechanism of the molecular network that regulates premature senescence.

Soil salinization has a serious influence on rice yield and quality. How to enhance salt tolerance in rice is a topical issue. In this study, 120 recombinant inbred line populations were generated through nonstop multi-generation selfing using a male indica rice variety Huazhan (Oryza sativa L. subsp. indica cv. ‘HZ’) and a female variety of Nekken2 (Oryza sativa L. subsp. japonica cv. ‘Nekken2’) as the parents. Germination under 80 mM NaCl conditions was measured and analyzed, and quantitative trait locus (QTL) mapping was completed using a genetic map. A total of 16 salt-tolerance QTL ranges were detected at bud stage in rice, which were situated on chromosomes 3, 4, 6, 8, 9, 10, 11, and 12. The maximum limit of detection was 4.69. Moreover, the qST12.3 was narrowed to a 192 kb region on chromosome 12 using map-based cloning strategy. Statistical analysis of the expression levels of these candidate genes under different NaCl concentrations by qRT-PCR revealed that qST12.3 (LOC_Os12g25200) was significantly down-regulated with increasing NaCl concentration, and the expression level of the chlorine-transporter-encoding gene LOC_Os12g25200 in HZ was significantly higher than that of Nekken2 under 0 mM NaCl. Sequencing analysis of LOC_Os12g25200 promoter region indicated that the gene expression difference between parents may be due to eight base differences in the promoter region. Through QTL mining and analysis, a plurality of candidate genes related to salt tolerance in rice was obtained, and the results showed that LOC_Os12g25200 might negatively regulate salt tolerance in rice. The results provide the basis for further screening and cultivation of salt-tolerant rice varieties and have laid the foundation for elucidating further molecular regulation mechanisms of salt tolerance in rice.

Rationale: Chronic wounds associated with diabetes exact a heavy burden on individuals and society and do not have a specific treatment. Exosome therapy is an extension of stem cell therapy, and RNA interference (RNAi)-based therapy is a type of advanced precision therapy. Based on the discovery of chronic wound-related genes in diabetes, we combined exosome therapy and RNAi therapy through an engineering approach for the treatment of diabetic chronic wounds. Methods: We combined exosome therapy and RNAi therapy to establish a precision therapy for diabetes-associated wounds via an engineered exosome approach. Results: First, chronic diabetic wounds express low levels of miR-31-5p compared with nondiabetic wounds, and an miR-31-5p mimic was shown to be effective in promoting the proliferation and migration of three wound-related cell types in vitro. Second, bioinformatics analysis, luciferase reporter assays and western blotting suggested that miR-31-5p promoted angiogenesis, fibrogenesis and reepithelization by inhibiting factor-inhibiting HIF-1 (HIF1AN, also named FIH) and epithelial membrane protein-1 (EMP-1). Third, engineered miR-31 exosomes were generated as a miR-31-5p RNAi therapeutic agent. In vivo, the engineered miR-31 exosomes promoted diabetic wound healing by enhancing angiogenesis, fibrogenesis and reepithelization. Conclusion: Engineered miR-31 exosomes are an ideal disease pathophysiology-initiated RNAi therapeutic agent for diabetic wounds.

Plant lesion mimics refer to necrotic spots spontaneously produced by the plant without mechanical damage, pathogen invasion, and adversity stress. Here, we isolated and characterized two rice (Oryza sativa L) mutants, namely, spl88-1 (spotted leaf88-1) and spl88-2 (spotted leaf88-2), which were identified from an ethyl methanesulfonate-mutagenized japonica cultivar Xiushui 11 population. Physiological and biochemical experiments indicated that more ROS accumulated in spl88-1 and spl88-2 than in wild type. spl88-1 and spl88-2 displayed spontaneous cell death and enhanced their resistance to bacterial blight by affecting the expression of defense-related genes. We isolated SPL88 by map-based cloning, which encoded a highly conserved Cullin protein. A single base deletion was detected in spl88-1 and spl88-2, in which the 132nd base C of SPL88-1 and the 381th base T of SPL88-2 were deleted, causing premature termination of protein translation. SPL88 was expressed in root, stem, leaf, leaf sheath, and panicle. The Cullin protein was localized in the cytoplasm and nucleus. The aforementioned results indicate that SPL88 regulates the growth and development of rice by affecting the expression of defense-related genes.

Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so -called connectomes. The data that can comprise of up to 108 individual EM images must be assembled into a volume, requiring seamless 2D registration from physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render Trautman and Saalfeld (2019) services used in the volume assembly of the brain of adult Drosophila melanogaster (Zheng et al. 2018). It achieves high throughput by operating only on image meta-data and transformations. ASAP is modular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (Yin et al. 2020); Microns Consortium et al. (2021) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

Electron microscopy (EM) is the gold standard for biological ultrastructure but acquisition speed is slow, making it unsuitable for large volumes. Here the authors present a parallel imaging pipeline for continuous autonomous imaging with six transmission EMs to image 1 mm3 of mouse cortex in less than 6 months.

Information and communication technologies play an important role in education. This fact was emphasized even more due to the significant upheavals, globally, caused by the pandemic of COVID-19 and because distance education uses tools of modern technology that prove to be significantly important. Particularly, virtual reality immersion systems, which may include 3D spatial representations, multisensory interaction channels, and real-time intuitive physical interaction, can extend the learning process by providing learners with stimuli that represent a real advanced training environment. In the present work, based on the most modern technologies of computational intelligence, virtual and augmented reality, wireless communications, and space-sensitive positioning applications, an Artificial Intelligent Virtual Reality (AI-VR) interactive model for distance education is presented. This is a case study of escape-room-type educational application, wherewith appropriate practices and methodologies promote individual and collective participation, enhance the active role of the learner, personalize the educational experience, and upgrade the process of participation in distance education, strengthening and assisting role of the educator. Specifically, a Newton polynomial is used for max-polynomials arising from the stereoscopic problem of augmented reality used to indirectly indicate the number of linear regions in order to optimize the problem. The proposed application is related to the training course of agricultural education and methods of modernization of crops, including additional sound, 3D graphics, and short film projection. The history-space-objects relationship takes and evolves with various versions such as the parts of the story to be unlocked as the trainee moves from one tool to the next or the story to guide the trainee to explore the space-time continuum, giving a new dimension to the technological development of agricultural education and the methods of modernization of crops. This finding shows that they learn best when they receive information in a style that incorporates visual, auditory, and kinetic stimuli so that learning improves when learners can examine an idea or concept using a multidimensional approach.

Four new alkaloids (1–4) belonging to rare examples of bis-amide matrine-type were isolated from the seeds of sophora alopecuroides. Their structures including absolute configuration were determined by extensive spectroscopic analysis, electronic circular dichroism (ECD) interpretation, and X-ray diffraction crystallography. Chemically, bis-amide matrine-type alkaloids can provide new molecular template for structural modification. Compounds 3–4 displayed obvious anti-inflammatory effects based on the inhibition of two key pro-inflammatory cytokines [tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6)] in a dose-dependent manner, with IC50 values from 35.6 to 45.8 μm.

Seven new clerodane diterpenoids, crassifolins Q−W (1–7), along with five known analogues (8–12), were isolated from the roots of Croton crassifolius. Their structures were identified by comprehensive spectroscopic analysis (UV, IR, NMR, and HR-ESI-MS), and their absolute configurations were determined by ECD spectra and X-ray crystallography. The activities of compounds 1–5 against inflammatory cytokines IL-6 and TNF-α levels on LPS-induced RAW 264.7 macrophages were assessed, and compound 5 showed the most significant activity with the secretion levels of IL-6 and TNF-α at 32.78 and 12.53%, respectively. Moreover, compounds 1–5 were screened for their anti-angiogenesis using a human umbilical vein endothelial cells in vitro mode; the results showed all of them exhibited obvious anti-angiogenesis activities, in particular, compound 5 showed the strongest anti-angiogenesis effect in the range of 6.25–50 μM.

With the rapid growth of the Internet-of-Things (IoT), security issues for the IoT are becoming increasingly serious. Memory leaks are a common and harmful software defect for IoT programs running on resource-limited devices. Static analysis is an effective method for memory leak detection, however, because the existing methods cannot fully describe the memory state of IoT programs at run time, false positives and false negatives frequently occur. To improve the precision of memory leak detection, we propose an abstract memory model SeqMM to describe sequential storage structures. SeqMM differs from other abstract memory models in its ability to handle both points-to analysis and numerical analysis of pointers, which contributes to eliminating false positives in defect detection. In addition, based on the analysis of the sequential storage structure, we introduce the analysis of its operations in C programs, including transfer operations and predicate operations. Moreover, we present a memory leak detection algorithm by determining the state of the program points related to allocated memory blocks. The experimental results of five real projects indicate that the false positive rates of DTSC_SeqMM, Klocwork12 and DTSC_RSTVL are 29.0%, 15.0% and 40.6% respectively, and the corresponding false negative rates are 0%, 22.7% and 13.6%.

Cancer is a highly heterogeneous disease, which leads to the fact that even the same cancer can be further classified into different subtypes according to its pathology. With the multi-omics data widely used in cancer subtypes identification, effective feature selection is essential for accurately identifying cancer subtypes. However, the feature selection in the existing cancer subtypes identification methods has the problem that the most helpful features cannot be selected from a biomolecular perspective, and the relationship between the selected features cannot be reflected. To solve this problem, we propose a method for feature selection to identify cancer subtypes based on the heterogeneity score of a single gene: HSSG. In the proposed method, the sample-similarity network of a single gene is constructed, and pseudo-F statistics calculates the heterogeneity score for cancer subtypes identification of each gene. Finally, we construct gene-gene networks using genes with higher heterogeneity scores and mine essential genes from the networks. From the seven TCGA data sets for three experiments, including cancer subtypes identification in single-omics data, the performance in feature selection of multi-omics data, and the effectiveness and stability of the selected features, HSSG achieves good performance in all. This indicates that HSSG can effectively select features for subtypes identification.

Repair and reconstruction of critical-sized bone defects has always been a difficult task in orthopedics. Hypoxia inducible factor-1α (HIF-1α) plays an important role in bone defect repair, it has the dual function of promoting osteogenesis and vascular regeneration, but it is quickly degraded by the body under normoxic conditions. Previously we prepared mutant HIF-1α, which has been shown to efficiently maintain cellular expression under normoxic conditions. In this study, we evaluated for the first time the role of exosomes of rat bone marrow mesenchymal stem cell carry mutant HIF-1α (BMSC-Exos-HIF1α) in repairing critical-sized bone defects. Evaluation of the effects of BMSC-Exos-HIF1α on bone marrow mesenchymal stem cells (BMSCs) proliferation and osteogenic differentiation by cell proliferation assay, alkaline phosphatase activity assay, alizarin red staining, real-time quantitative polymerase chain reaction. BMSC-Exos-HIF1α was loaded onto the β-TCP stent implanted in the bone defect area using a rat cranial critical-sized bone defect model, and new bone formation and neovascularization were detected in vivo by micro-CT, fluorescence labeling analysis, Microfil perfusion, histology and immunohistochemical analysis. In vitro results showed that BMSC-Exos-HIF1α stimulated the proliferation of BMSCs and up-regulated the expression level of bone-related genes, which was superior to bone marrow MSC exosomes (BMSC-Exos). In vivo results showed that BMSC-Exos-HIF1α combined with β-TCP scaffold promoted new bone regeneration and neovascularization in the bone defect area, and the effect was better than that of BMSC-Exos combined with β-TCP scaffold. In this study, the results showed that BMSC-Exos-HIF1α stimulated the proliferation and osteogenic differentiation of BMSCs and that BMSC-Exos-HIF1α combined with β-TCP scaffolds could repair critical-sized bone defects by promoting new bone regeneration and neovascularization.

In recent years, with the rapid development of information technology and the extensive coverage of the Internet, the information age has come, and data is gradually becoming one of the important factors in the production of various manufacturing and operational entrepreneurs. With the development of society, people have higher and higher requirements for indoor planning. People no longer only pursue the beauty of a simple natural environment, but also pursue the beauty of the natural environment, their unique personality and spiritual pursuit. This article firstly studies some development issues and trends of interior decoration design, and then discovers the application of big data in interior decoration design through literature research. Finally, the questionnaire surveyed the interior decoration design style and product selection. The survey results showed that about 50% of the choice of style chose simple style, and 70%-80% of consumers chose natural materials for decoration products. It can be seen that, the interior decoration design is simpler, and the natural style develops.

Automated program repair is an effective way to ensure software quality and improve software development efficiency. At present, there are many methods and tools of automated program reapir in real world, but most of them have low repair accuracy, resulting in a large number of incorrect patches in the generated patches. To solve this problem, we propose a patch quality evaluation method based on semantic distance, which measures the semantic distance of patches by using features of interval distance, output coverage, and path matching. For each evaluation feature, we give a quantitative formula to obtain a specific distance value and use the distance to calculate the recommended patch value to measure the quality of the patch. Our quality evaluation method evaluated 279 patches from previous program repair tools, including Nopol, DynaMoth, ACS, jGenProg, and CapGen. This quality evaluation method successfully arranged the correct patches before the plausible but incorrect patches, and it recommended the higher-ranked patches to users first. On this basis, we compared our evaluation method with the existing evaluation methods and judged the evaluation ability of each feature. We showed that our proposed patch quality evaluation method can improve the repair accuracy of repair tools.

The alarms of the program-semantic defect-detection report based on static analysis include defects and false positives. The repair of defects and the elimination of false positives are time-consuming and laborious, and new defects may be introduced in the process. To solve these problems, the safe constraints interval of related variables and methods are proposed for the semantic defects in the program, and proposes a functionally equivalent no-side-effect program-semantic defect repair and false-positive elimination strategy based on the test-equivalence theory. This paper realizes the automatic repair of the typical semantic defects of Java programs and the automatic elimination of false positives by adding safe constraint patches. After the repair, the program functions are equivalent and the status of each program point is within the safety range, so that the functions before and after the defect repair are consistent, and the functions and semantics before and after the false positives are eliminated. We have evaluated our approach by repairing 5 projects; our results show that the repair strategy does not require manual confirmation of alarms, automated repair of the program effectively, shortened the repair time greatly, and ensured the correctness of the program after the repair.

Recently, software, especially CPS and Internet of Things (IoT), increasingly have high requirements for quality, while program defects exist inevitably duo to the high complexity. Program defect repair faces serious challenges in that such repairs require considerable manpower, and the existing automatic repair approaches have difficulty generating correct patches efficiently. This paper proposes an automatic method for repairing semantic defects in Java programs based on restricted sets which refer to the interval domains of related variables that can trigger program semantic defects. Our work introduces a repair mechanism symmetrically combining defect patterns and repair templates. First, the program semantic defects are summarized into defect patterns according to their grammar and semantic features. A repair template for each type of defect pattern is predefined based on a restricted-set. Then, for each specific defect, a patch statement is automatically synthesized according to the repair template, and the detected defect information is reported by the static detection tool (DTSJava). Next, the patch location is determined by the def-use chain of defect-related variables. Finally, we evaluate the patches generated by our method using DTSJava. We implemented the method in the defect automatic repair prototype tool DTSFix to verify the effect of repairing the semantic defects detected by DTSJava in 6 Java open-source projects. The experimental results showed that 109 of 129 program semantic defects were repaired.

To improve the efficacy of closed reduction and wire guiding during intramedullary nail internal fixation in femoral shaft fractures.A novel instrument was designed and manufactured. Sixty-eight patients were enrolled from February 2011 to December 2013. The instrument designed was used during the operation in the experimental group, but not in the control group.All patients exhibited fracture union, excluding 1 patient in the experimental group and 2 in the control group who had non-union; all of whom achieved fracture union with reoperation. There were no statistically significant differences in operative blood loss or duration of hospital stay between the groups (P > 0.05). The operative time, frequency of wire drilling, and number of open reduction cases, were significantly smaller in the experimental group than in the control group (P < 0.05).Femoral shaft fractures are difficult to reduce using general methods; the novel instrument showed high clinical value and proved effective and safe in assisting with closed reduction and intramedullary nail fixation for femoral shaft fractures.ChiCTR ChiCTR-ICR-15007335.

Colorectal cancer (CRC) exhibits pronounced heterogeneity and is categorized into four widely accepted consensus molecular subtypes (CMSs) with unique tumor microenvironments (TMEs). However, the intricate landscape of the microbiota and host-microbiota interactions within these TMEs remains elusive. Using RNA-sequencing data from The Cancer Genome Atlas, we analyzed the host transcriptomes and intratumoral microbiome profiles of CRC samples. Distinct host genes and microbial genera were identified among the CMSs. Immune microenvironments were evaluated using CIBERSORTx and ESTIMATE, and microbial coabundance patterns were assessed with FastSpar. Through LASSO penalized regression, we explored hostmicrobiota associations for each CMS. Our analysis revealed distinct host gene signatures within the CMSs, which encompassed ferroptosis-related genes and specific immune microenvironments. Moreover, we identified 293, 153, 66, and 109 intratumoral microbial genera with differential abundance, and host-microbiota associations contributed to distinct TMEs, characterized by 829, 1,270, 634, and 1,882 robust gene-microbe associations for each CMS in CMS1–CMS4, respectively. CMS1 featured inflammation-related HSF1 activation and gene interactions within the endothelin pathway and Flammeovirga. Integrin-related genes displayed positive correlations with Sutterella in CMS2, whereas CMS3 spotlighted microbial associations with biosynthetic and metabolic pathways. In CMS4, genes involved in collagen biosynthesis showed positive associations with Sutterella, contributing to disruptions in homeostasis. Notably, immune-rich subtypes exhibited pronounced ferroptosis dysregulation, potentially linked to tissue microbial colonization. This comprehensive investigation delineates the diverse landscapes of the TME within each CMS, incorporating host genes, intratumoral microbiota, and their complex interactions. These findings shed light on previously uncharted mechanisms underpinning CRC heterogeneity and suggest potential therapeutic targets. NEW & NOTEWORTHY This study determined the following: 1) providing a comprehensive landscape of consensus molecular subtype (CMS)-specific tumor microenvironments (TMEs); 2) constructing CMS-specific networks, including host genes, intratumoral microbiota, and enriched pathways, analyzing their associations to uncover unique patterns that demonstrate the intricate interplay within the TME; and 3) revealing a connection between immune-rich subtypes and ferroptosis activation, suggesting a potential regulatory role of the microbiota in ferroptosis dysregulation of the colorectal cancer TME. [ABSTRACT FROM AUTHOR]