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Abstract Streptococcus suis (S. suis) is a major pathogen in swine and poses a potential zoonotic threat, which may cause serious diseases. Many toxin-antitoxin (TA) systems have been discovered in S. suis, but their functions have not yet been fully elucidated. In this study, an auto-regulating type II TA system, ParDE, was identified in S. suis serotype 2 strain ZY05719. We constructed a mutant strain, ΔparDE, to explore its functions in bacterial virulence, various stress responses, and biofilm formation capabilities. The toxicity exerted by the toxin ParE can be neutralized by the antitoxin ParD. The β-galactosidase activity analysis indicated that ParDE has an autoregulatory function. An electrophoretic mobility shift assay (EMSA) confirmed that the antitoxin ParD bound to the promoter of ParDE as dimers. In the mouse infection model, the deletion of ParDE in ZY05719 significantly attenuated virulence. ΔparDE also exhibited a reduced anti-oxidative stress ability, and ΔparDE was more susceptible to phagocytosis and killing by macrophages. Moreover, the biofilm formation ability of the ΔparDE strain was significantly enhanced compared to ZY05719. Taken together, these findings indicate that the type II TA system ParDE plays a significant role in the pathogenesis of S. suis, providing new insights into its pathogenic mechanisms.

Abstract. Vascular aging (VA) is a common etiology of various chronic diseases and represents a major public health concern. Intermittent hypoxia (IH) associated with obstructive sleep apnea-hypopnea syndrome (OSAHS) is a primary pathological and physiological driver of OSAHS-induced systemic complications. A substantial proportion of OSAHS patients, estimated to be between 40% and 80%, have comorbidities such as hypertension, heart failure, coronary artery disease, pulmonary hypertension, atrial fibrillation, aneurysm, and stroke, all of which are closely associated with VA. This review examines the molecular and cellular features common to both OSAHS and VA, highlighting decreased melatonin secretion, impaired autophagy, increased apoptosis, increased inflammation and pyroptosis, increased oxidative stress, accelerated telomere shortening, accelerated stem cell depletion, metabolic disorders, imbalanced protein homeostasis, epigenetic alterations, and dysregulated neurohormonal signaling. The accumulation and combination of these features may underlie the pathophysiological link between OSAHS and VA, but the exact mechanisms by which OSAHS affects VA may require further investigation. Taken together, these findings suggest that OSAHS may serve as a novel risk factor for VA and related vascular disorders, and that targeting these features may offer therapeutic potential to mitigate the vascular risks associated with OSAHS.

Abstract Background Chemosensory perception plays a vital role in insect survival and adaptability, driving essential behaviours such as navigation, mate identification, and food location. This sensory process is governed by diverse gene families, including odorant-binding proteins (OBPs), olfactory receptors (ORs), ionotropic receptors (IRs), chemosensory proteins (CSPs), gustatory receptors (GRs), and sensory neuron membrane proteins (SNMPs). The oriental mole cricket (Gryllotalpa orientalis Burmeister), an invasive pest with an underground, phyllophagous lifestyle, causes substantial crop damage. This study characterizes the chemosensory gene repertoire of G. orientalis based on de novo genome assembly and transcriptomic analysis. Results We present a draft genome of G. orientalis at the scaffold level, spanning 2.94 Gb and comprising 10,497 scaffolds. This assembly encodes 19,155 protein-coding genes, including 158 chemosensory genes: 30 odorant receptors (ORs), 64 ionotropic receptors (IRs), ten gustatory receptors (GRs), 28 odorant-binding proteins (OBPs), 25 chemosensory proteins (CSPs), and a single sensory neuron membrane protein (SNMP). Expression analysis indicated that 71 chemosensory genes were actively expressed in the head, thorax, and legs, with ORs and OBPs showing higher expression in the head and legs. In contrast, GRs and IRs were predominantly expressed in the head. Conclusions This study provides the first comprehensive identification of chemosensory gene families in the G. orientalis genome, characterized as a scaffold-level draft genome. These findings provide a basis for future functional studies and highlight the role of chemoreception in the subterranean environment.

Abstract Innovation in microscopy has often been critical in advancing both fundamental science and technological progress. Notably, the evolution of ultrafast near-field optical nano-spectroscopy and nano-imaging has unlocked the ability to image at spatial scales from nanometers to ångströms and temporal scales from nanoseconds to femtoseconds. This approach revealed a plethora of fascinating light-matter states and quantum phenomena, including various species of polaritons, quantum phases, and complex many-body effects. This review focuses on the working principles and state-of-the-art development of ultrafast tip-enhanced and near-field microscopy, integrating diverse optical pump-probe methods across the terahertz (THz) to ultraviolet (UV) spectral ranges. It highlights their utility in examining a broad range of materials, including two-dimensional (2D), organic molecular, and hybrid materials. The review concludes with a spatio-spectral-temporal comparison of ultrafast nano-imaging techniques, both within already well-defined domains, and offering an outlook on future developments of ultrafast tip-based microscopy and their potential to address a wider range of materials.

Abstract Receptor activator of nuclear factor kappa-B ligand (RANKL) initiates a complex signaling cascade that is crucial for inducing osteoclast differentiation and activation. RANKL-induced signaling has been analyzed in detail, and the involvement of TNF receptor-associated factor 6 (TRAF6), calmodulin-dependent protein kinase (CaMK), NF-κB, mitogen-activated protein kinase (MAPK), activator protein-1 (AP-1), and molecules that contain an immunoreceptor tyrosine-based activation motif (ITAM) has been reported. However, the precise molecular steps that regulate RANKL signaling remain largely unknown. Here, we revealed the indispensable role of a class III histone deacetylase (SIRT5) in the processes of RANKL-induced osteoclast differentiation and activation. SIRT5 expression in osteoclasts was increased during osteoclastogenesis upon stimulation with RANKL. The RANKL-induced signaling activation was suppressed in SIRT5-deficient osteoclasts but enhanced by SIRT5 overexpression. Mice with global or conditional monocytic lineage knockout of SIRT5 had increased bone mass and reduced osteoclast numbers. In the cytoplasm, SIRT5 interacted with the scaffold protein JNK-interacting protein 4 (JIP4) to finely regulate MAPK signaling, which was critical for osteoclast differentiation and activation. Pharmacological inhibition of the catalytic activity of SIRT5 effectively reversed bone loss in ovariectomized mice. Taken together, the results of this study reveal that the SIRT5-JIP4 axis is a novel positive regulator that finely regulates RANKL-induced osteoclast differentiation and suggest that targeting this axis is a therapeutic strategy for preventing osteoporotic bone loss. Graphical Abstract

Abstract The retrosplenial cortex (RSP) is a complex brain region with multiple interconnected subregions that plays crucial roles in various cognitive functions, including memory, spatial navigation, and emotion. Understanding the afferent and efferent connectivity of the RSP is essential for comprehending the underlying mechanisms of its functions. Here, via viral tracing and fluorescence micro-optical sectioning tomography (fMOST), we systematically investigated the anatomical organisation of the upstream and downstream circuits of glutamatergic and GABAergic neurons in the dorsal and ventral RSP. The cortical connections of the RSP show laminar organisation in which the input neurons are distributed more in the deeper layers of the upstream cortex. Although different types of neurons have similar upstream circuits, GABAergic neurons show bidirectional connections with the hippocampus, whereas glutamatergic neurons only show unidirectional connections. Moreover, GABAergic neurons receive more inputs from the primary sensory cortex than from the prefrontal cortex and association cortex. The dorsal and ventral subregions have preferred circuits such that the dorsal RSP exhibits spatially topological connections with the dorsal visual cortex and lateral thalamus. The systematic study on long-range connections across RSP subregions and cell types may provide useful information for future revealing of RSP working mechanisms.

This study investigates the innovative pathways for integrating velvet flowers, as an element of intangible cultural heritage (ICH), into modern design. Utilizing a semiotic three-dimensional framework (syntactic, semantics, pragmatics), the study deconstructs and reconstructs the cultural symbols of velvet flowers, aiming to merge traditional craftsmanship with contemporary aesthetics. Through an analysis of the selection, reconstruction, and transformation of meanings within velvet flower symbols, this paper proposes a strategy for converting traditional symbols into a design language that aligns with modern aesthetic values and market demands. The case studies demonstrate how velvet flower symbols retain cultural significance while adapting to the diverse demands of the contemporary market. The findings indicate that the selection and reconstruction of symbols, as well as the extension and transformation of their meanings, are key steps in the innovative design of velvet flowers. Furthermore, by comparing cross-cultural innovation cases, the study highlights the global market potential and cultural adaptability of velvet flower design, with particular attention to market prospects in various regions. The research also examines commercialization strategies, including cross-disciplinary collaboration, brand partnerships, and sustainable development, to expand market reach and enhance brand influence. In conclusion, this study provides a theoretical framework and practical guidance for the modernization and global dissemination of velvet flower craftsmanship.

Abstract Background The refinement of risk stratification in lung adenocarcinoma (LUAD) plays a pivotal role in advancing precision medicine; however, the current staging classification falls short of comprehensiveness, particularly in the case of stage IA patients. We aimed to molecularly stratify LUAD patients especially for stage IA. Methods We analysed tumour heterogeneity and identified highly proliferating cancer cells (HPCs) in LUAD by performing single-cell RNA sequencing (scRNA-seq) analysis, immunohistochemical (IHC) staining using a tissue microarray, flow cytometry and biological experiments. Then, we quantified the content of HPCs in nine LUAD datasets by single-sample gene set enrichment analysis and evaluated the relationship between the percentage of HPCs and overall survival (OS). Next, we analysed the OS predictive effect of HPCs at different LUAD stages, especially for stage I risk stratification. Furthermore, we established a prognostic prediction model based on HPC-associated genes for clinical application. The above findings were validated in another five LUAD datasets. Finally, we explored the relationship between HPCs and the progressive pathological evolution of early-stage LUAD and the driving mutations by scRNA-seq, bulk RNA-seq and IHC staining. Results LUAD tissues carry a small proportion of HPCs, which show potential for malignant proliferation and intense interactions with the microenvironment. A high HPC content is an independent risk factor for OS in LUAD patients, even in stage IA patients. HPCs can be used to establish a cut-off point for the prognosis of stage IA disease, with patients with a higher risk showing a prognosis similar to that of patients with stage IB disease. We built an R package (HSurADs) based on HPC-associated genes, which exhibited good efficacy for the prognostic prediction of LUAD. HPCs gradually increase with the pathological evolution of early-stage LUAD, which may be affected by TP53 mutations. Conclusion The HPC content can be used as a novel prognostic factor for LUAD, especially for stage IA risk stratification.

Abstract Background Ornithine transcarbamylase deficiency exhibits a high degree of clinical heterogeneity, making its screening and classification challenging in some instances. In this study, we first established a simple and stable method for testing ornithine transcarbamylase activity using micro blood from newborns, rather than relying on venous blood. Methods The activity of ornithine transcarbamylase was assessed by measuring the concentration of citrulline produced in the reaction with carbamoyl phosphate and ornithine, using serum, plasma or micro blood. Correlation analysis was evaluated using Sangerbox Tools. The Receiver Operating Characteristic curve was used in SPSS Statistics 17.0 to evaluate the diagnostic efficiency of Ornithine transcarbamylase deficiency. Results A strong linear relationship was observed between ornithine transcarbamylase activity and both micro blood volume and reaction time (R2 = 0.9793, 0.9922 respectively). The intra-coefficient variation and inter-coefficient variation were 11% and 12.5% with a 1-h reaction time, and 6.77% and 9.58% with a 3-h reaction time, respectively. And the inter-coefficient variation was lower than the most widely used colorimetry method (5.1–21.1%). The Limit of Blank was 0.57 nmol/mL/h. The reference interval for normal newborn population is greater than or equal to 39.6 nmol/mL/h. Notably, the method exhibited a 100% sensitivity, surpassing the sensitivity of colorimetry method (94.3%), along with and a specificity of 96.9% for diagnosing ornithine transcarbamylase deficiency. Conclusions We pioneered a method for testing OTC activity that normally carried on venous blood can be effectively performed on microblood heel samples. Meanwhile, our method presents a simpler, more stable and reproducible approach compared to colorimetry.

Abstract In recent years, immune checkpoint inhibitors (ICIs) has emerged as a fundamental component of the standard treatment regimen for patients with head and neck squamous cell carcinoma (HNSCC). However, accurately predicting the treatment effectiveness of ICIs for patients at the same TNM stage remains a challenge. In this study, we first combined multi-omics data (mRNA, lncRNA, miRNA, DNA methylation, and somatic mutations) and 10 clustering algorithms, successfully identifying two distinct cancer subtypes (CSs) (CS1 and CS2). Subsequently, immune-regulated genes (IRGs) and machine learning algorithms were utilized to construct a consensus machine learning-driven prediction immunotherapy signature (CMPIS). Further, the prognostic model was validated and compared across multiple datasets, including clinical characteristics, external datasets, and previously published models. Ultimately, the response of different CMPIS patients to immunotherapy, targeted therapy, radiotherapy and chemotherapy was also explored. First, Two distinct molecular subtypes were successfully identified by integrating immunomics data with machine learning techniques, and it was discovered that the CS1 subtype tended to be classified as “cold tumors” or “immunosuppressive tumors”, whereas the CS2 subtype was more likely to represent “hot tumors” or "immune-activated tumors". Second, 303 different algorithms were employed to construct prognostic models and the average C-index value for each model was calculated across various cohorts. Ultimately, the StepCox [forward] + Ridge algorithm, which had the highest average C-index value of 0.666, was selected and this algorithm was used to construct the CMPIS predictive model comprising 16 key genes. Third, this predictive model was compared with patients’ clinical features, such as age, gender, TNM stage, and grade stage. The findings indicated that this prognostic model exhibited the best performance in terms of C-index and AUC values. Additionally, it was compared with previously published models and it was found that the C-index of CMPIS ranked in the top 5 among 94 models across the TCGA, GSE27020, GSE41613, GSE42743, GSE65858, and META datasets. Lastly, the study revealed that patients with lower CMPIS were more sensitive to immunotherapy and chemotherapy, while those with higher CMPIS were more responsive to radiation therapy and EGFR-targeted treatments. In summary, our study identified two CSs (CS1 and CS2) of HNSCC using multi-omics data and predicted patient prognosis and treatment response by constructing the CMPIS model with IRGs and 303 machine learning algorithms, which underscores the importance of immunotherapy biomarkers in providing more targeted, precise, and personalized immunotherapy plans for HNSCC patients, significantly contributing to the optimization of clinical treatment outcomes.

It is of great significance to search for advanced glycation end products (AGEs) inhibitors with high activity and low side effects from food-borne natural products for the prevention and improvement of related diseases. To elucidate the inhibitory effect of tectoridin on the generation of advanced glycation end products (AGEs), the glycation system of bovine serum protein (BSA)-methylglyoxal (MGO) was established, the effects of tectoridin on the AGEs inhibition, glycation degree, protein oxidation products, protein cross-linking and MGO trapping were investigated by spectroscopy, SDS-PAGE, HPLC, LTQ-Orbitrap MS, and molecular docking. The results showed that tectoridin increased the content of lysine and thiol, reduced the contents of protein carbonylation and protein oxidation products, alleviated the cross-linking structure of BSA. The mono-MGO adduct of tectoridin was identified in the incubation of MGO with tectoridin. Molecular docking results showed that hydrogen bonding and hydrophobic interactions were the major driving forces for stabilizing tectoridin-BSA complexes. Tectoridin was a promising natural AGEs inhibitor. Mechanism analysis revealed that tectoridin alleviated AGEs formation by trapping MGO to form mono-tectoridin-MGO complexes and forming stable tectoridin-BSA complexes. These findings would provide the theoretical basis for the development of tectoridin as a novel, natural and effective inhibitor of AGEs.

Abstract Although third-generation Epidermal growth factor receptor—tyrosine kinase inhibitors (EGFR-TKI) is standard of care for patients with EGFR-mutant Non-small cell lung cancer (NSCLC), little is known about the predictors of response or resistance. Here, we integrated single-cell RNA (scRNA) sequencing, bulk RNA sequencing, multiplexed immunofluorescence and flow cytometry data from pretreatment and post-resistant tumor samples of EGFR-mutant NSCLC patients received third-generation EGFR-TKIs. We show that resistant samples had a markedly enriched CXCR1+ neutrophils infiltration (P

Single-cell Hi-C (scHi-C) techniques have significantly advanced our understanding of the 3D genome organization, providing crucial insights into the spatial genome architecture within individual nuclei. Numerous computational and statistical methods have been developed to analyze scHi-C data, with embedding methods playing a key role. Embedding reduces the dimensionality of complex scHi-C contact maps, making it easier to extract biologically meaningful patterns. These methods not only enhance cell clustering based on chromatin structures but also facilitate visualization and other downstream analyses. Most scHi-C embedding methods incorporate strategies such as normalization and imputation to address the inherent sparsity of scHi-C data, thereby further improving data quality and interpretability. In this review, we systematically examine the existing methods designed for scHi-C embedding, outlining their methodologies and discussing their capabilities in handling normalization and imputation. Additionally, we present a comprehensive benchmarking analysis to compare both embedding techniques and their clustering performances. This review serves as a practical guide for researchers seeking to select suitable scHi-C embedding tools, ultimately contributing to the understanding of the 3D organization of the genome.

The fretting wear of steel wire will reduce the service life of wire rope and severely threaten the safety of mine hoisting. To investigate the influence of torsion on the fretting wear behavior of steel wire, the fretting wear tests of steel wires with spiral contact structure under the action of tensile-torsional coupling forces were conducted, and the fatigue fracture failure mechanism was revealed. The result indicates that the CoF increases with increasing torsional angle. As the cycles increase, the sliding distance between the wires decreases, while the adhesion increases. The fretting area gradually transitions from gross sliding status to partial sliding status. The sliding distance and energy loss between the wires increase with increasing torsional angle. The wear depth and coefficient increase with increasing torsional angle, and the wear level of peak contact structure is more serious than that of valley contact structure. The primary wear mechanisms of steel wire are abrasive wear, adhesive wear and fatigue wear. The fatigue fractograph of steel wire is obviously divided into fatigue source zone, crack growth zone and final fracture zone. Abundant secondary cracks and dimples exist in the final fracture zone, and the fatigue fracture failure mechanism is mainly ductile fracture.

Abstract Objectives To investigate the risk factors for short-term residual low back pain (SRBP) following percutaneous kyphoplasty (PKP) in patients with initial thoracolumbar osteoporotic vertebral compression fractures (OVCFs). Methods The clinical data of 389 patients with primary thoracolumbar OVCFs treated with PKP in our hospital from January 2018 to December 2022 were retrospectively analysed. A numerical rating scale (NRS) was used to evaluate whether SRBP was present 2 days after the operation. Patients with NRS scores > 4 were assigned to the SRBP group, and those with NRS scores ≤ 4 were assigned to the non-SRBP group. The general clinical data and surgical imaging-related data of the two groups were statistically analysed. Risk factors were analysed using binary logistic regression analysis. Results Binary logistic regression analysis showed four independent predictors of SRBP after PKP, including bone mineral density (BMD) (OR = 0.087, P = 0.044), preoperative injured vertebral kyphosis (OR = 1.26, P = 0.01), preoperative thoracolumbar fascia injury (TLFI) (OR = 8.929, P

Abstract Glioblastoma stem cells (GSCs) are pivotal in the recurrence and drug resistance of glioblastoma multiforme (GBM). However, precision therapeutic and diagnostic markers for GSCs have not been fully established. Here, using bioinformatics and experimental analysis, we identified P4HB, a protein disulfide isomerase, as a serum marker that maintains stemness in GSCs through the Wnt/β-catenin signaling pathway. Transcriptional silencing of P4HB induces apoptosis and diminishes stem cell-like characteristics in GSCs. Treatments with the chemical CCF624 or the China National Medical Products Administration (NMPA)-approved securinine significantly prolonged survival in patient-derived xenograft mouse models, underscoring P4HB’s potential as a therapeutic target and presenting an expedited path to clinical application through drug repurposing. Additionally, elevated P4HB levels in patient serum were found to correlate with disease progression, underscoring its utility as a biomarker and its promise for precision medicine.

Abstract Leeches are famous for their high medical value and wide environmental adaptability. Among them, cave leeches are a very fascinating and rare group, which is an important component in the study of adaptive evolution of leeches. However, no study has yet reported a reference genome for this group. In this study, we assembled a high-quality chromosome-level genome of the cave terrestrial leech Sinospelaeobdella cavatuses, through Illumina and PacBio sequencing, alongside chromosome conformation capture techniques. The resulting genome spans 153.67 Mb across 9 pseudochromosomes(range: 11.33 to 23.53 Mb), with a mounting rate of up to 95.37% and features an N50 length of 17.15 Mb. This genome is composed of 35.16% repetitive elements and contains 21180 predicted protein-coding genes. Decoding the S. cavatuses genome not only promotes future studies on study of its phylogeny, evolution, and behavior, but also provides valuable resources for in-depth investigation on adaptive evolution of leech.

This study analyzes the production process of traditional Chinese velvet flowers and their cultural inheritance and innovative applications. Through literature review, case studies, and field research, it explores the historical evolution of velvet flower craftsmanship, its technical characteristics, and its application in modern design. The research shows that velvet flower craftsmanship has been revitalized with the help of intangible cultural heritage protection and modern design, demonstrating new vitality in the fashion and home decor fields. This paper proposes strategies for promoting the global dissemination and sustainable development of velvet flower craftsmanship, guiding the modernization of traditional handicrafts.

Abstract Background The effectiveness of adipose-derived stem cells (ADSCs) in therapy diminishes with age. It has been reported that transcription factors (TFs) play a crucial role in the aging and functionality of stem cells. Nevertheless, there is limited understanding regarding the involvement of TFs in the aging mechanism of ADSCs. Methods RNA sequencing (RNA-seq) was utilized to discern the differentially expressed genes in ADSCs obtained from donors of varying ages. TFs exhibiting significant variations across age groups were identified and subsequently validated. ADSCs were manipulated to exhibit either enhanced expression or reduced levels of HES1 and STAT1 via lentivirus transfection and small interfering RNA (siRNA) techniques. The impact of these genetic alterations on ADSCs’ proliferation, migration, and cellular senescence was assessed using EdU, transwell, and senescence-activated β-galactosidase (SA-β-gal) staining assays. The DNA sequences bound by HES1 were investigated through the CUT & Tag assay. Lastly, the therapeutic efficacy of aged ADSCs with HES1 overexpression was evaluated in skin injury model of male Sprague-Dawley rats. Results 678 genes showed differential expression between ADSCs obtained from young and old donors (Y-ADSCs and O-ADSCs), with 47 of these genes being TFs. Notably, the expression of the TF hairy and enhancer of split 1 (HES1) was notably reduced in ADSCs from old donors. Introducing HES1 overexpression in aged ADSCs resulted in improved cellular function and the suppression of cellular senescence, while reducing HES1 levels in young ADSCs had the opposite effect. Mechanistically, HES1 was found to interact with the promoter region of another TF, signal transducer and activator of transcription 1 (STAT1), to inhibit its transcription. Knocking down STAT1 could fully reverse the negative effects caused by decreased HES1 in ADSCs, leading to a reduction in the secretion of pro-inflammatory cytokines such as TNF-α, IL-6, and IL-8. Ultimately, restoring HES1 expression in aged ADSCs demonstrated enhanced therapeutic potential in promoting skin wound healing. Conclusion HES1 acts as an inhibitor of cellular senescence in the aging progression of ADSCs through the modulation of STAT1 expression, suggesting a promising avenue for rejuvenating senescent ADSCs and improving wound healing.

Abstract This study aimed to observe the characteristics of foot posture asymmetry and abnormal gait in patients with unilateral and bilateral knee osteoarthritis (KOA) and to explore the association between foot posture asymmetry, abnormal gait and the clinical symptoms and severity of KOA. Sixty patients with KOA were allocated as follows: unilateral group (UG; n = 30) and bilateral group (BG; n = 30). We accessed foot posture, foot posture asymmetry, gait and plantar pressure parameters and symmetry index, clinical symptom-related scores and disease severity, and investigated the relationship between these variables. The results showed that the overall percentage of asymmetry and severe asymmetry in foot posture were lower in BG than in UG. There was substantial asymmetry in many gait indicators within the two groups, but no significant differences were observed between the two groups. Moreover, foot posture asymmetry, multiple gait and plantar pressure parameters and symmetry indices were closely related to clinical symptoms and disease severity. In conclusion, both unilateral and bilateral KOA patients have foot posture asymmetry and gait asymmetry, but the foot posture asymmetry of the former is more severe than that of the latter. Intervention for this population should treat simultaneously both knee joints. The evaluation and monitoring of foot posture asymmetry, gait and plantar pressure parameters and symmetry indices can provide a more comprehensive and scientific basis for the prevention and treatment of KOA.

Abstract Background The recent Maternal Immune Activation (MIA) theory suggests maternal systemic inflammation may serve as a mediator in associations between prenatal maternal adversities and neurodevelopmental diseases in offspring. Given the co-exposure to multiple adversities may be experienced by pregnant person, it is unclear whether a quantitative index can be developed to characterize the inflammation related exposure level, and whether this index is associated with neurodevelopmental delays in offspring. Methods Based on Jiangsu Birth Cohort (JBC), a total of 3051 infants were included in the analysis. Inflammation related Prenatal Adversity Index (IPAI) was constructed using maternal data. Neurodevelopmental outcomes were assessed using the Bayley Scales of Infant and Toddler Development, third edition, screening test in one year. Multivariate linear regression and Poisson regression model were performed to analyze the associations between IPAI and neurodevelopment in offspring. Results Compared with “low IPAI” group, offspring with “high IPAI” have lower scores of cognition, receptive communication, expressive communication, and fine motor. The adjusted β were − 0.23 (95%CI: -0.42, -0.04), -0.47 (95%CI: -0.66, -0.28), -0.30 (95%CI: -0.49, -0.11), and − 0.20 (95%CI: -0.33, -0.06). Additionally, the elevated risk for noncompetent development of cognition and receptive communication among “high IPAI” group was observed. The relative risk [RR] and 95% confidence interval [CI] were 1.35 (1.01, 1.69) and 1.37 (1.09, 1.72). Conclusions Our results revealed a significant association between higher IPAI and lower scores across cognition, receptive communication, expressive communication, and fine motor domains, and an increased risk of noncompetent development in the cognition and receptive communication domains.

To examine the effects and mechanisms of Camellia petelotii Chi extract on the rat model of non-alcoholic fatty liver disease (NAFLD), a set of ten SD rats was randomly chosen as the blank group, while the remaining 50 rats were given a high-sugar, high-fat emulsion to develop the model of non-alcoholic fatty liver disease. After 14 days, the rats were separated into different groups based on their serum total cholesterol (TC) levels. These groups included the model group, the simvastatin group (8 mg/kg), and the Camellia petelotii Chi high, medium, and low dose groups (260, 130, 65 mg/kg). The medication was administered continuously for 6 weeks. Before the last administration, an oral glucose tolerance test (OGTT) was performed, and the area under the blood glucose curve (AUC) was calculated. Both serum and liver tissues were collected to examine the concentrations of total cholesterol (TC), triacylglycerol (TG), high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), and free fatty acid (FFA). In addition, TC and TG were measured to evaluate the amount of lipids in the liver, while glutamic-pyruvic transaminase (ALT) and glutamic oxaloacetic transaminase (AST) were examined to assess liver function. The levels of malondialdehyde (MDA) was measured to evaluate the extent of lipid peroxidation in the liver, while the activity of superoxide dismutase (SOD) was also evaluated. Serum inflammatory factors interleukin 6 (IL-6), interleukin 8 (IL-8), and tumor necrosis factor (TNF-α) were determined in rats. Serum insulin (FINS) was measured and the insulin resistance index (HOMA-IR) was calculated. The HE staining technique was employed to examine the pathomorphological alterations in the liver and determine the non-alcoholic fatty liver disease activity score (NAS). The gene and protein expression of Toll-like receptor 4 (TLR-4) and nuclear factor κB (NF-κB) were determined in liver tissue. The results showed that compared with the model group, AUC, HOMA-IR and serum levels of FINS, TG, TC, LDL-C, FFA, ALT, AST, IL-6, IL-8, TNF were significantly lower (P

Abstract Background The aim of this study was to explore the relationships between teaching competence, career development, industrial orientation, and specialty construction in the case of intelligent medicine specialties in universities of traditional Chinese medicine, as well as the influencing factors of specialty construction. Methods Two-stage sampling with unequal probability was conducted to distribute self-administered questionnaires in the fieldwork. A structural equation model was built to investigate the influencing factors of specialty construction. Forty-two teachers were recruited and completed the questionnaire. Results The study found that teaching competence, career development, and industrial orientation positively affect specialty construction at a significant level. Career development and industrial orientation play chain mediating roles in the effect of teaching competence on specialty construction. Conclusions In the construction of intelligent medicine specialties, a professional curriculum system should be built that caters to industrial demand and is combined with industrial development, the traditional mode of teaching should be transformed, and the transformation of theoretical knowledge into practical ability should be promoted. Innovations in teaching modes should be achieved by introducing information technology, and the teacher evaluation system should be optimized.

Abstract Extensive studies indicate that mitochondria dysfunction is pivotal for Alzheimer’s disease (AD) pathogenesis; while cumulative evidence suggests that increased mitochondrial stress response (MSR) may mitigate neurodegeneration in AD, explorations to develop a MSR-targeted therapeutic strategy against AD are scarce. We combined cell biology, molecular biology, and pharmacological approaches to unravel a novel molecular pathway by which NAD+-boosting agent nicotinamide mononucleotide (NMN) regulates MSR in AD models. Here, we report dyshomeostasis plasma UPRmt-mitophagy-mediated MSR profiles in AD patient samples. NMN restores NAD+ metabolic profiles and improves MSR through the ATF4-dependent UPRmt pathway in AD-related cross-species models. At the organismal level, NAD+ repletion with NMN supplementation ameliorates mitochondrial proteotoxicity, decreases hippocampal synaptic disruption, decreases neuronal loss, and brain atrophy in mice model of AD. Remarkably, omics features of the hippocampus with NMN show that NMN leads to transcriptional changes of genes and proteins involved in MSR characteristics, principally within the astrocyte unit rather than microglia and oligodendrocytes. In brief, our work provides evidence that MSR has an active role in the pathogenesis of AD, as reducing mitochondrial homeostasis via atf4 depletion in AD mice aggravates the hallmarks of the disease; conversely, bolstering mitochondrial proteostasis by NMN decreases protein aggregation, restores memory performance, and delays disease progression, ultimately translating to increased healthspan.

Abstract Objective This meta-analysis aims to compare the clinical efficacy of mesh non-fixation and fixation in laparoscopic transabdominal preperitoneal (TAPP) inguinal hernia repair, systematically evaluating the application value of the mesh non-fixation technique in clinical settings. Methods A computerized search of PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov databases was conducted to identify randomized controlled trials (RCTs) comparing mesh non-fixation and fixation in TAPP inguinal hernia repair. Meta-analysis was performed using RevMan 5.3 software, and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) evidence grading system was employed for outcome quality assessment. Publication bias analysis was performed using Begg’s test. A trial sequential analysis (TSA) was performed using TSA 0.9.5.10 Beta software. Results A total of nine RCTs involving 1,879 inguinal hernia patients were included. Meta-analysis results demonstrated that, compared to the fixation group, the non-fixation group exhibited significantly lower seroma occurrence rate [RR = 0.43, 95% CI (0.20, 0.89), P = 0.02, heterogeneity P = 0.28, I²=22%], Visual Analog Scale (VAS) pain score at 6 months postoperatively [MD=-0.21, 95% CI (-0.29, -0.12), P

Abstract Globally, CRC ranks as a principal cause of mortality, with projections indicating a substantial rise in both incidence and mortality by the year 2040. The immunological responses to cancer heavily rely on the function of CD4Tconv. Despite this critical role, prognostic studies on CRC-related CD4Tconv remain insufficient. In this investigation, transcriptomic and clinical data were sourced from TCGA and GEO. Initially, we pinpointed CD4TGs using single-cell datasets. Prognostic genes were then isolated through univariate Cox regression analysis. Building upon this, 101 machine learning algorithms were employed to devise a novel risk assessment framework, which underwent rigorous validation using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, time-dependent ROC curves, nomograms, and calibration plots. Furthermore, GSEA facilitated the examination of these genes’ potential roles. The RS derived from this model was also analyzed for its implications in the TME, and its potential utility in immunotherapy and chemotherapy contexts. A novel prognostic model was developed, utilizing eight CD4TGs that are significantly linked to the outcomes of patients with CRC. This model’s RS showcased remarkable predictive reliability for the overall survival rates of CRC patients and strongly correlated with malignancy levels. RS serves as an autonomous prognostic indicator, capable of accurately forecasting patient prognoses. Based on the median value of RS, patients were categorized into subgroups of high and low risk. The subgroup with higher risk demonstrated increased immune infiltration and heightened activity of genes associated with immunity. This investigation’s establishment of a CD4TGs risk model introduces novel biomarkers for the clinical evaluation of CRC risks. These biomarkers may enhance therapeutic approaches and, in turn, elevate the clinical outcomes for patients with CRC by facilitating an integrated treatment strategy.

The steel industry is considered an important basic sector of the national economy, and its high energy consumption and carbon emissions make it a major contributor to climate change, especially in China. The majority of crude steel in China is produced via the energy- and carbon-intensive blast furnace–basic oxygen furnace (BF–BOF) route, which greatly relies on coking coal. In recent years, China’s steel sector has made significant progress in energy conservation and emission reduction, driven by decarbonization policies and regulations. However, due to the huge output of crude steel, the steel sector still produces 15% of the total national CO2 emissions. The direct reduced iron (DRI) plus scrap–electric arc furnace (EAF) process is currently considered a good alternative to the conventional route as a means of reducing CO2 emissions and the steel industry’s reliance on iron ore and coking coal, since the gas-based DRI plus scrap–EAF route is expected to be more promising than the coal-based one. Unfortunately, almost no DRI is produced in China, seriously restricting the development of the EAF route. Here, we highlight the challenges and pathways of the future development of DRI, with a focus on China. In the short term, replacing natural gas with coke oven gas (COG) and byproduct gas from the integrated refining and chemical sector is a more economically feasible and cleaner way to develop a gas-based route in China. As the energy revolution proceeds, using fossil fuels in combination with carbon capture, utilization, and storage (CCUS) and hydrogen will be a good alternative due to the relatively low cost. In the long term, DRI is expected to be produced using 100% hydrogen from renewable energy. Both the development of deep processing technologies and the invention of a novel binder are required to prepare high-quality pellets for direct reduction (DR), and further research on the one-step gas-based process is necessary.

Abstract Background Adjacent segment disease (ASD) is a common and serious complication that can develop in the mid- to long-term after lumbar fusion surgery. However, the underlying mechanisms of ASD are not yet fully understood. This study aimed to develop and validate a risk prediction model for ASD in patients who underwent transforaminal lumbar interbody fusion (TLIF) for lumbar degenerative diseases. Methods Patients with lumbar degenerative disease who underwent TLIF between January 2015 and December 2016 were included in the retrospective study. The participants were divided into two groups: ASD and non-ASD. Univariate and multivariate logistic regression analyses were performed to identify factors influencing ASD after TLIF surgery. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the model’s discrimination, calibration and clinical value, respectively. Results A total of 11.5% (59/513) of patients developed ASD. Higher BMI, lower BMD, higher disc grade, and reduced disc height were identified as independent risk factors for ASD after TLIF. The model demonstrated good discrimination in both the training and validation sets, with calibration and Hosmer-Lemeshow tests confirming accuracy, and DCA demonstrating clinical applicability. Conclusions The nomogram model demonstrated promise in predicting ASD in patients who underwent TLIF, aiding clinicians in selecting the most suitable surgical approach and optimizing surgical decisions.

ObjectiveTo explore the impact of sex on the efficacy of first-line programmed death-1 (PD-1) blockade plus chemotherapy in patients with advanced lung adenocarcinoma and its potential biological mechanisms. MethodsThe clinical and pathological characteristics and follow-up data of 163 patients with advanced lung adenocarcinoma without driver gene alterations at Shanghai Pulmonary Hospital affiliated to Tongji University from October 2018 to October 2023 were retrospectively collected. Among them, 103 patients received first-line PD-1 blockade plus chemotherapy (51 males and 52 females) and 60 patients received first-line standard platinum-based doublet chemotherapy (39 males and 21 females). Patients were divided into male group and female group. Clinical characteristics, efficacy, progression-free survival (PFS), and overall survival (OS) were compared between the two groups. Kaplan-Meier method was used to plot the survival curves of male and female patients, and log-rank test was used for significance evaluation. Cox proportional hazards model was used to analyze the factors influencing PFS and OS. Multiplex immunofluorescence (mIF) assays were used to analyze the differences of protein expression levels of programmed death-ligand 1 (PD-L1), CD8, CD68, CD4, and FOXP3 between male and female groups in baseline tumor sample. ResultsIn patients receiving first-line PD-1 blockade plus chemotherapy, the median PFS in female group and male group was 13.0 months and 6.8 months, respectively (HR＝0.39, 95%CI 0.25-0.62; P＜0.01). The median OS in female group and male group was 46.2 months and 17.3 months, respectively (HR＝0.30, 95%CI 0.18-0.50; P＜0.01). In patients receiving first-line chemotherapy, the median PFS in female group and male group was 5.7 months and 5.5 months, respectively (P＞0.05); the median OS in female group and male group was 21.7 months and 17.7 months, respectively (P＞0.05). The results of the Cox proportional hazards model showed that sex was an independent factor influencing PFS and OS in patients receiving first-line PD-1 blockade plus chemotherapy (P＜0.05). The results of mIF showed that pretreatment tumor samples of female patients had a significantly higher expression level of CD8 than male patients (P＜0.05), while the expression level of PD-L1, CD68, CD4 and FOXP3 was similar between female and male groups. ConclusionsCompared to male patients, female patients with advanced lung adenocarcinoma benefit more from the first-line PD-1 blockade plus chemotherapy. The increased expression level of CD8 in pretreatment tumor samples of female patients would be the potential mechanism.

Abstract The NLRP3 inflammasome plays a crucial role in inflammatory responses, particularly in alcohol-related liver disease (ALD). Given that NLRP3 has emerged as a potential therapeutic target for ALD, the development of effective inhibitors is of great importance. In this study, we trained 11 regression models, and the results showed that LightGBM, Random Forest, and XGBoost performed the best, achieving R² values of 0.774, 0.755, and 0.719, respectively. Using machine learning models and physical methods, we screened more than 11.5 million compounds from Asinex, Princeton, UkrOrgSynthesis, Chemdiv, Chembridge, Alinda, Enamine, and Lifechemicals, which led to the identification of 26 potential NLRP3 inhibitors. Furthermore, molecular dynamics simulations and MMGBSA binding energy calculations confirmed the stability of the interactions between NLRP3 and three key molecules: 19,655,631 (source Chembridge), 38,214,692 (source Chembridge), and Z1180203703 (source Enamine). Additionally, ADMET analysis revealed their favorable pharmacokinetic properties. This study provides insights and candidate molecules for discovering NLRP3 inhibitors, potentially applicable in treating related diseases.

Abstract This open-label, single-arm, phase 2 trial evaluated the efficacy and safety of neoadjuvant sintilimab combined with anlotinib and chemotherapy, followed by adjuvant sintilimab, for resectable NSCLC. Forty-five patients received anlotinib (10 mg, QD, PO, days 1–14), sintilimab (200 mg, day 1), and platinum-based chemotherapy of each three-week cycle for 3 cycles, followed by surgery within 4–6 weeks. Adjuvant sintilimab (200 mg) was administered every 3 weeks. The primary endpoint was achieving a pathological complete response (pCR). From June 10, 2021 through October 10, 2023, 45 patients were enrolled and composed the intention-to-treat population. Twenty-six patients (57.8%) achieved pCR, and 30 (66.7%) achieved major pathological response (MPR). Forty-one patients underwent surgery. In the per-protocol set (PP set), 63.4% (26/41) achieved pCR, and 73.2% achieved MPR. The median event-free survival was not attained (95% CI, 25.1-NE). During the neoadjuvant treatment phase, grade 3 or 4 treatment-related adverse events were observed in 25 patients (55.6%), while immune-related adverse events were reported in 7 patients (15.6%). We assessed vascular normalization and infiltration of immune-related cells by detecting the expression of relevant cell markers in NSCLC tissues with mIHC. Significant tumor microenvironment changes were observed in pCR patients, including reduced VEGF+ cells and CD4+Foxp3+ Treg cells, and increased perivascular CD4+ T cells, CD39+CD8+ T cells, and M1 macrophages. In conclusion, perioperative sintilimab and neoadjuvant anlotinib plus chemotherapy achieved pCR in a notable proportion of patients with resectable NSCLC and were associated with profound changes in the tumour microenvironment (ClinicalTrials.gov NCT05400070).

In this paper, Index Modulation (IM) aided Generalized Space-Time Block Coding (GSTBC) is proposed, which intrinsically exploits the benefits of IM concept, diversity gain and spatial multiplexing gain. Specifically, the information bits are partitioned into U groups, with each being modulated by IM symbols (i.e. Spatial Modulation (SM), Quadrature SM (QSM),etc). Next, the structure of GSTBC is invoked for each K IM symbol, and a total of μ ​= ​U/K GSTBC codes are transmitted via T time slots. A Block Expectation Propagation (B-EP) detector is designed for the proposed IM-GSTBC structure. Moreover, the theoretical Average Bit Error Probability (ABEP) is derived for our IM-GSTBC system, which is confirmed by the simulation results and helpful for performance evaluation. Simulation results show that our proposed IM-GSTBC system is capable of striking an efficient trade-off between spatial multiplexing gain, spatial diversity gain as well as implementation cost imposed for both small-scale and large-scale MIMO antenna configurations.

Accurate estimation of natural gas consumption plays a crucial role in energy planning, economic stability, environmental protection, and investment decisions. Despite numerous predictive studies related to natural gas consumption, most of these studies focus on univariate prediction tasks, lacking a reasonable and efficient multivariate prediction approach. To obtain precise forecasting results, this paper constructs a new adaptive grey multivariate prediction model called AGMPM(r,N) based on the fractional-order accumulation operation and grey system theory. It is found that AGMPM(r,N) can degenerate into some grey multivariable prediction models by replacing its own hyperparameters, which reflects its uniformity. In addition, the new model is unbiased for some special time series. In particular, the grey wolf optimizer is used to facilitate the model solution process. To validate the effectiveness of AGMPM(r,N), AGMPM(r,N) and 27 competing algorithms (9 natural gas consumption prediction methods, 10 multivariate prediction models, 7 machine learning algorithms and a statistical predictive model) are used to study the natural gas consumption in China. In addition, ablation experiments are executed. The results of experimental analysis show that the MAPE and MAE of AGMPM(r,N) are 2.795% and 89.880, respectively, which are superior to all competing methods and ablation models.

Abstract. Background:. Programmed death 1 (PD-1) blockade plus chemotherapy has become the new first-line standard of care for patients with advanced non-small-cell lung cancer (NSCLC). Yet not all NSCLC patients benefit from this regimen. This study aimed to investigate the predictors of PD-1 blockade plus chemotherapy in untreated advanced NSCLC. Methods:. We integrated clinical, genomic, and survival data from 287 patients with untreated advanced NSCLC who were enrolled in one of five registered phase 3 trials and received PD-1 blockade plus chemotherapy or chemotherapy alone. We randomly assigned these patients into a discovery cohort (n = 125), a validation cohort (n = 82), and a control cohort (n = 80). The candidate genes that could predict the response to PD-1 blockade plus chemotherapy were identified using data from the discovery cohort and their predictive values were then evaluated in the three cohorts. Immune deconvolution was conducted using transcriptome data of 1014 NSCLC patients from The Cancer Genome Atlas dataset. Results:. A genomic variation signature, in which one or more of the 15 candidate genes were altered, was correlated with significantly inferior response rates and survival outcomes in patients treated with first-line PD-1 blockade plus chemotherapy in both discovery and validation cohorts. Its predictive value held in multivariate analyses when adjusted for baseline parameters, programmed cell death ligand 1 (PD-L1) expression level, and tumor mutation burden. Moreover, applying both the 15-gene panel and PD-L1 expression level produced better performance than either alone in predicting benefit from this treatment combination. Immune landscape analyses revealed that tumors with one or more variation in the 15-gene panel were associated with few immune infiltrates, indicating an immune-desert tumor microenvironment. Conclusion:. These findings indicate that a 15-gene panel can serve as a negative prediction biomarker for first-line PD-1 blockade plus chemotherapy in patients with advanced NSCLC.

Due to the lack of design guidance for high-performance Cr–V steel, it is challenging to identify the target steel within a vast design space. In this paper, a design loop combining property-oriented design criteria and machine learning prediction model is proposed. Based on the design criteria, the alloying values of the initial sample and the allowable variation range are given to narrow the search space. Then, the machine learning model is employed to predict properties across all design nodes within the design space. The results suggest that the samples within the design space, meeting the proposed design criteria, demonstrate higher hardness. However, wear resistance decreases rapidly as Cr increases and V/Cr decreases. The predicted optimal sample C2.1V3Cr4Mo2.5 is prepared and its properties are measured, showing that the absolute errors between the measured and predicted values are less than 5%. In addition, C2.1V3Cr4Mo2.5 is more cost-effective than Cr26 and V10. This design loop facilitates the rapid selection of the most promising steel for experimentation and provides a new avenue for the development of wear-resistant alloy steels.

Abstract The traditional control method of doubly fed induction generators (DFIGs) has poor robustness due to the excessive use of machine parameters, and does not fully consider the control conditions of nonideal power grids, resulting in serious fluctuations in current and power under grid disturbances. To solve these problems, model‐free predictive rotor current control (MFPRCC) based on an ultra‐local model is proposed in this article. The ultra‐local model is adaptive because it can accurately emulate the overall structure of the system and estimate the total disturbance of the system in real time. Under a nonideal grid, the cascaded delayed signal cancellation (CDSC) modules are connected in series behind the outer power loop to extract the fundamental component of the rotor current reference. The proposed method is compared with the traditional model predictive rotor current control (MPRCC) method, and the effectiveness of the proposed method is verified on a 1.5 kW DFIG experimental platform.

The Anqing section of the Yangtze (Changjiang) River in Anhui Province, China, is one of the most important migratory routes and distribution of the highly valued diadromous estuarine tapertail anchovy Coilia nasus. In the past, this section has suffered a severe loss of C. nasus resources caused by human activities, especially overfishing and water pollution. Since 2019, a fishing ban policy for the species in the Yangtze River has been introduced in China for resource restoration. Otoliths are calcium carbonate structures, and otolith microchemistry can provide detailed life history information that can be used to compare habitat use between different saline water bodies. To study the habitat history of C. nasus in the Anqing section of the Yangtze River after the implementation of the fishing ban, we examined the microchemical characteristics (Sr and Ca) of otoliths from the long (previously named C. ectenes) and short maxillary (previously named C. brachygnathus) types of anchovy using electron probe X-ray microanalysis (EPMA). Line-transect analysis of Sr/Ca ratios suggested that the short maxillary type of C. nasus could be divided into two groups. The otolith Sr/Ca ratios (calculated and expressed as Sr/Ca ×1, 000) of one group were always < 3.0, indicating their freshwater residency. Those of the other group had phases of low (< 3.0, believed to be indicative of a freshwater habitat) and high values (> 3.0, believed to be indicative of a brackish or seawater habitat), indicating that anchovies not only have a freshwater habitat history with low salinity but also a brackish habitat history with high salinity. The latter group of anchovies were typically anadromous C. nasus, as the Sr/Ca ratio of the otoliths of C. nasus fluctuated significantly and coincided with variations between freshwater and estuarine brackish or seawater (i.e., anchovies experienced not only freshwater habitats but also brackish water habitats at different stages of their life history). The Sr content mapping of EPMA with different color patterns for freshwater (blue), brackish water (green-yellow) and seawater (red) habitats also confirmed the results obtained from the line-transect analysis. Our results demonstrated that the population composition of C. nasus in the Anqing section of the Yangtze river became complex, and there was coexistence of freshwater resident and anadromous C. nasus in the Anqing section of the Yangtze River in Anhui Province, China (i.e., freshwater resident and anadromous short maxillary and anadromous long maxillary type C. nasus). This phenomenon may suggest a restoration of C. nasus resource diversity after the implementation of the fishing ban in the Anqing section of the Yangtze River.

Abstract Peritoneal recurrence (PR) in gastric cancer after curative resection has poor prognosis. Therefore, we aimed to construct a nomogram to predict PR, and establish PR score for risk stratification to guide adjuvant chemotherapy. A total of 315 patients with gastric cancer after radical surgery were included, and randomly stratified into training group (n = 221) and validation group (n = 94). Univariate and multivariate analyses were used to determine predictive factors of PR. The nomogram was constructed to predict the risk of PR. We utilized the time-dependent area under the receiver operating characteristic (ROC) curves (AUCs), calibration curves, and decision curve analysis (DCA) to evaluate the performance of the nomogram. Multivariate analysis showed that tumor site, N stage, preoperative CEA, and postoperative CA199 were independent predictors of PR. A nomogram was constructed to predict PR based on these factors. The AUC value was 0.755 in the training group and 0.715 in the validation group. The calibration curves showed good agreement between prediction and observation in the training and validation groups. The decision curve analysis displayed a good net benefit of the nomogram. The novel PR score was developed and patients were stratified into the low-, medium-, and high -risk groups. For the high-risk group, postoperative adjuvant chemotherapy significantly improved patients' overall survival (OS) and disease-free survival (DFS). The establishment of nomogram facilitates the prediction of PR after radical gastrectomy, and a novel PR score may help guide adjuvant chemotherapy for gastric cancer.

In this paper, efficient signal detectors are designed for Orthogonal Time Frequency Space (OTFS) modulation with Index Modulation (IM) systems. Firstly, the Minimum Mean Squared Error (MMSE) based linear equalizer and its corresponding soft-aided decision are studied for OTFS-IM. To further improve the performance, a Vector-by-Vector-aided Message Passing (VV-MP) detector and its associated soft-decision are proposed, where each IM symbol is considered an entire vector utilized for message calculation and passing. Simulation results are shown that the OTFS-IM system relying on the proposed detectors is capable of providing considerable Bit Error Rate (BER) performance gains over the OTFS and Orthogonal Frequency Division Multiplex (OFDM) with IM systems.

Orbital Angular Momentum (OAM) waves are characterized by helical wave fronts and orthogonality between different modes. Therefore, OAM waves have huge potential in improving wireless communications' channel capacity and radar imaging's resolution. Consequently, the generation and application of OAM waves have attracted a lot of attention. And many methods are proposed to generate OAM waves. Although antenna array is the most popular method of generating OAM waves, OAM waves generated by antenna array have redundant modes. However, all advantages of OAM waves are closely related to infinite OAM modes. Thus, to better apply OAM waves to wireless communications and radar, it is very important to reduce unnecessary OAM modes and improve the OAM mode purity. In order to improve the OAM mode purity, two combined antenna arrays composed of X direction antenna and Y direction antenna array are proposed in this paper. The X direction antenna array and the Y direction antenna array are supplied by the excitations with the same amplitude and fixed phase shift. The overall phase shift of the X direction antenna array is π/2 more or less than that of the Y direction antenna array. The results of formulas and antenna models in CST show that the combined antenna arrays can generate OAM waves with less redundant modes in x component, y component and z component. Besides, the z component carries pure OAM modes.

Background: Histopathology diagnosis is often regarded as the final diagnostic method for malignant tumors; however, it has some drawbacks. This study explored a computer-aided diagnostic method that can be used to identify benign and malignant gastric cancer using histopathological images. Methods: The most suitable process was selected through multiple experiments by comparing multiple methods and features for classification. First, the U-net was applied to segment the image. Next, the nucleus was extracted from the segmented image, and the minimum spanning tree (MST) diagram structure that can capture the topological information was drawn. The third step was to extract the graph-curvature features of the histopathological image according to the MST image. Finally, by inputting the graph-curvature features into the classifier, the recognition results for benign or malignant cancer can be obtained. Results: During the experiment, we used various methods for comparison. In the image segmentation stage, U-net, watershed algorithm, and Otsu threshold segmentation methods were used. We found that the U-net method, combined with multiple indicators, was the most suitable for segmentation of histopathological images. In the feature extraction stage, in addition to extracting graph-edge and graph-curvature features, several basic image features were extracted, including the red, green and blue feature, gray-level co-occurrence matrix feature, histogram of oriented gradient feature, and local binary pattern feature. In the classifier design stage, we experimented with various methods, such as support vector machine (SVM), random forest, artificial neural network, K nearest neighbors, VGG-16, and inception-V3. Through comparison and analysis, it was found that classification results with an accuracy of 98.57% can be obtained by inputting the graph-curvature feature into the SVM classifier. Conclusion: This study created a unique feature, the graph-curvature feature, based on the MST to represent and analyze histopathological images. This graph-based feature could be used to identify benign and malignant cells in histopathological images and assist pathologists in diagnosis.

The discrete element method (DEM) has been extensively utilized to investigate the mechanical properties of granules, particularly their microscopic behavior, overcoming limitations in field tests such as cost, time consumption, and soil condition restrictions. To ensure the development of reliable DEM simulations, proper contact model selection and parameter calibration are essential. In this research, a DEM parameter calibration method that could represent the nonlinear relationship between clayey soil pressure and sinkage at different moisture contents was proposed. Firstly, the sinking modulus K and the soil deformation exponent n were identified to reflect the nonlinear pressure–sinkage relationship. Then, sensitive DEM parameters on the soli pressure–sinkage relationship were investigated and calibrated, and the effect of moisture content on them was explored. Finally, the transfer of soil internal stress during subsidence was analyzed using the constructed discrete element model. The average error of the sinking modulus K and the soil deformation exponent n between the DEM and the experimental result at four moisture contents were 4.7% and 4.9%, respectively. The relative error of soil internal stress between simulation and experiment was 6.7%, 4.4%, and 9.7% at depths of 50 mm, 100 mm, and 150 mm, respectively. The soil particle trajectory, soil internal stress distribution, and variations during plate pressure–sinkage progress were analyzed by the constructed DEM model. The results demonstrated good agreement with theoretical models and experimental findings. The proposed clayey soil DEM modeling process that considers the pressure–sinkage nonlinear relationship at different moisture contents can be applied in machine-soil research.

Controlled environment agriculture (CEA) represents one of the fastest-growing sectors of horticulture. Production in controlled environments ranges from highly controlled indoor environments with 100% artificial lighting (vertical farms or plant factories) to high-tech greenhouses with or without supplemental lighting, to simpler greenhouses and high tunnels. Although food production occurs in the soil inside high tunnels, most CEA operations use various hydroponic systems to meet crop irrigation and fertility needs. The expansion of CEA offers promise as a tool for increasing food production in and near urban systems as these systems do not rely on arable agricultural land. In addition, CEA offers resilience to climate instability by growing inside protective structures. Products harvested from CEA systems tend to be of high quality, both internal and external, and are sought after by consumers. Currently, CEA producers rely on cultivars bred for production in open-field agriculture. Because of high energy and other production costs in CEA, only a limited number of food crops have proven themselves to be profitable to produce. One factor contributing to this situation may be a lack of optimized cultivars. Indoor growing operations offer opportunities for breeding cultivars that are ideal for these systems. To facilitate breeding these specialized cultivars, a wide range of tools are available for plant breeders to help speed this process and increase its efficiency. This review aims to cover breeding opportunities and needs for a wide range of horticultural crops either already being produced in CEA systems or with potential for CEA production. It also reviews many of the tools available to breeders including genomics-informed breeding, marker-assisted selection, precision breeding, high-throughput phenotyping, and potential sources of germplasm suitable for CEA breeding. The availability of published genomes and trait-linked molecular markers should enable rapid progress in the breeding of CEA-specific food crops that will help drive the growth of this industry.

ObjectiveLung cancer—with its global prevalence and critical need for early diagnosis and treatment—is the focus of our study. This study aimed to develop a nomogram based on acoustic–clinical features—a tool that could significantly enhance the clinical prediction of lung cancer.MethodsWe reviewed the voice data and clinical information of 350 individuals: 189 pathologically confirmed lung cancer patients and 161 non-lung cancer patients, which included 77 patients with benign pulmonary lesions and 84 healthy volunteers. First, acoustic features were extracted from all participants, and optimal features were selected by least absolute shrinkage and selection operator (LASSO) regression. Subsequently, by integrating acoustic features and clinical features, a nomogram for predicting lung cancer was developed using a multivariate logistic regression model. The performance of the nomogram was evaluated by the area under the receiver operating characteristic curve (AUC) and the calibration curve. The clinical utility was estimated by decision curve analysis (DCA) to confirm the predictive value of the nomogram. Furthermore, the nomogram model was compared with predictive models that were developed using six additional machine-learning (ML) methods.ResultsOur acoustic–clinical nomogram model demonstrated a strong discriminative ability, with AUCs of 0.774 (95% confidence interval [CI], 0.716–0.832) and 0.714 (95% CI: 0.616–0.811) in the training and test sets, respectively. The nomogram achieved an accuracy of 0.642, a sensitivity of 0.673, and a specificity of 0.611 in the test set. The calibration curve showed excellent agreement between the predicted and actual values, and the DCA curve underscored the clinical usefulness of our nomogram. Notably, our nomogram model outperformed other models in terms of AUC, accuracy, and specificity.ConclusionThe acoustic–clinical nomogram developed in this study demonstrates robust discrimination, calibration, and clinical application value. This nomogram, a unique contribution to the field, provides a reliable tool for predicting lung cancer.

The rising incidence of Alzheimer’s disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibilities for early AD detection. In this study, we introduce retinal vessel segmentation methods based on U-Net ad iterative registration Learning (ReIU), which extract retinal vessel maps from OCT angiography (OCT-A) facilities. Our method achieved segmentation accuracies of 79.1% on the DRIVE dataset, 68.3% on the HRF dataset. Utilizing a multimodal dataset comprising both healthy and AD subjects, ReIU extracted vascular density from fundus images, facilitating primary AD screening with a classification accuracy of 79%. These results demonstrate ReIU’s substantial accuracy and its potential as an economical, non-invasive screening tool for Alzheimer’s disease. This study underscores the importance of integrating multi-modal data and deep learning techniques in advancing the early detection and management of Alzheimer’s disease.

Summary: Impaired bone quality and increased fracture risk are cardinal features of the skeleton in diabetes mellitus. Hyperglycemia-induced oxidative stress is proposed as a potential underlying mechanism, but the precise pathogenic mechanism remains incompletely understood. In this investigation, osteoblasts under high glucose exhibited heightened levels of reactive oxygen species, impaired mitochondrial membrane potential, and profound inhibition of late-stage osteoblast differentiation. Further analyses uncovered that high glucose resulted in the downregulation of the PINK1/Drp1 pathway in osteoblasts, consequently leading to impaired mitophagy. Conversely, the upregulation of PINK1/Drp1 pathway activated mitophagy, which restored the differentiation capacity of osteoblasts. Notably, in an STZ-induced diabetic mouse model, BMP9 upregulated the expression of PINK1/Drp1 in the bone tissue, leading to an improvement in bone quality and bone mineral density. These findings suggest that the PINK1/Drp1 pathway might be a potential therapeutic target to enhance osteogenic differentiation and treat diabetic osteoporosis.

Artificial intelligence (AI) has significantly impacted various fields, including oncology. This comprehensive review examines the current applications and future prospects of AI in lung cancer research and treatment. We critically analyze the latest AI technologies and their applications across multiple domains, including genomics, transcriptomics, proteomics, metabolomics, immunomics, microbiomics, radiomics, and pathomics in lung cancer research. The review elucidates AI’s transformative role in enhancing early detection, personalizing treatment strategies, and accelerating therapeutic innovations. We explore AI’s impact on precision medicine in lung cancer, encompassing early diagnosis, treatment planning, monitoring, and drug discovery. The potential of AI in analyzing complex datasets, including genetic profiles, imaging data, and clinical records, is discussed, highlighting its capacity to provide more accurate diagnoses and tailored treatment plans. Additionally, we examine AI’s potential in predicting patient responses to immunotherapy and forecasting survival rates, particularly in non-small cell lung cancer (NSCLC). The review addresses technical challenges facing AI implementation in lung cancer care, including data quality and quantity issues, model interpretability, and ethical considerations, while discussing potential solutions and emphasizing the importance of rigorous validation. By providing a comprehensive analysis for researchers and clinicians, this review underscores AI’s indispensable role in combating lung cancer and its potential to usher in a new era of medical breakthroughs, ultimately aiming to improve patient outcomes and quality of life.