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Abstract As a traditional Chinese medicine formula used in clinical practice for an extended period, Suxin-Hugan-Fang (SXHGF) exhibits excellent anti-inflammatory properties. However, the efficacy of SXHGF in treating ulcerative colitis (UC) and its mechanism of action are still unclear. In this study, the therapeutic effects of SXHGF on UC were evaluated using network pharmacology and experimental validation, while also investigating its mechanism of action. By administering DSS to C57BL/6 mice to construct a mouse model of ulcerative colitis, the therapeutic effect of SXHGF on ulcerative colitis was evaluated based on weight loss percentage, disease activity index, colon length changes, and pathological conditions as indicators. The main chemical components of SXHGF were determined by LC-MS-QTOF method. The potential targets and mechanisms of action of SXHGF in the treatment of UC were inferred using bioinformatics methods, and further validated through ELISA, IHC, and Western blotting assays. The experimental results demonstrate that SXHGF can suppress oxidative stress and oxidative damage in the colon tissue of UC mice, and alleviate DSS-induced ulcerative colitis by inhibiting the JAK2/STAT3 and NFκB pathways.

Abstract To investigate the effect of pyrolysis temperature on the adsorption behavior of the emerging organic pollutant tris-(1-chloro-2-propyl) phosphate (TCIPP) on biochar, corn stover was used as raw materials to prepare biochars at different pyrolysis temperatures (250, 350, 500, 700 °C) through limited oxygen carbonization. Elemental analysis, Boehm titration, FTIR, XPS, and other analytical methods were used to reveal the effect of pyrolysis temperature on the physicochemical properties of biochar and its mechanism of TCIPP adsorption. The results showed that the pyrolysis temperature had a significant impact on the physicochemical properties of biochar. As the pyrolysis temperature increases, the specific surface area of biochar rises from 3.083 m2/g to 435.573 m2/g, the pH value increases from 6.60 to 10.66, the mass percentage of C increases from 63.10 to 80.58%, and the mass percentage of O decreases from 26.42 to 9.20%. Additionally, the hydrophobicity and aromaticity of biochar also increase with rising pyrolysis temperature, while its polarity decreases. Boehm titration, FTIR, and XPS analysis showed that the total amount of functional groups on the surface of biochar decreased relatively with increasing temperature. Functional groups such as -OH, C = C/C = O, and C-O-C participated in the adsorption of TCIPP on biochar, and ester groups were produced after adsorption. The adsorption process of TCIPP on biochar fits best with the pseudo-second-order equation, indicating that the adsorption process is mainly chemical adsorption, and the main rate-controlling stage is intraparticle diffusion. The isothermal adsorption results were more in line with the Temkin model, indicating that the adsorption process of TCIPP on biochar was mainly surface adsorption. As the pyrolysis temperature increases, the maximum adsorption capacity of biochar increases from 0.8837 mg/g to 2.2574 mg/g. The adsorption process of TCIPP on biochar mainly included pore filling, hydrogen bonding, P-π interaction, hydrophobic interaction, and electrostatic attraction. Among them, pore filling, P-π interaction, and hydrophobic interaction were significantly enhanced with increasing temperature, while hydrogen bonding was relatively weakened. This study will provide a theoretical basis and technical support for the removal of TCIPP from water using biochar adsorption.

Abstract Chronic rhinosinusitis (CRS) is a prevalent inflammatory airway disease affecting over 10% of the global population, leading to considerable socio-economic impacts, especially in developing countries. The pathogenesis of CRS is multifactorial, involving potential contributions from both genetic and environmental factors. While the influence of allergic and autoimmune diseases on CRS has been observed, the causal relationships between these diseases and CRS remain unclear. We extracted data from large-scale genome-wide association studies (GWAS) and utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the causal relationships between CRS and ten autoimmune and allergic diseases, including asthma, allergic rhinitis (AR), atopic dermatitis (AD), psoriasis, type 1 diabetes (T1D), hypothyroidism, celiac disease (CeD), multiple sclerosis (MS), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE). Additionally, we conducted colocalization analysis to determine whether the allergic/autoimmune diseases showing statistical causal relationships with CRS are driven by the same genetic variants. The MR analysis identified that AR (OR = 1.30; 95% CI = 1.21–1.40; P = 3.26E−13), asthma (OR = 1.35; 95% CI = 1.25–1.45; P = 1.35E−14), and AD (OR = 1.17; 95% CI = 1.06–1.30; P = 0.003) were significantly associated with an increased risk of developing CRS. Interestingly, psoriasis (OR = 0.05; 95% CI = 0.01–0.37; P = 0.004) appeared to have a protective effect against CRS. Associations for T1D and hypothyroidism were also suggestive as potential risk factors for CRS. No significant associations in the reverse MR analysis, suggesting a one-directional relationship. Colocalization analysis indicated that asthma (PP.H4 = 0.99) shared the same genetic variant (IL-33 rs3939286) with CRS. In conclusion, our study confirmed the causal relationships between allergic and autoimmune diseases (AR, asthma, AD, and psoriasis) and CRS. Notably, we identified a shared genetic variant, rs3939286 in the IL-33 gene, between asthma and CRS, suggesting that targeting the IL-33 pathway may provide a therapeutic strategy for both diseases.

Abstract Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Its complexity is influenced by various signal transduction networks that govern cellular proliferation, survival, differentiation, and apoptosis. The pathogenesis of CRC is a testament to the dysregulation of these signaling cascades, which culminates in the malignant transformation of colonic epithelium. This review aims to dissect the foundational signaling mechanisms implicated in CRC, to elucidate the generalized principles underpinning neoplastic evolution and progression. We discuss the molecular hallmarks of CRC, including the genomic, epigenomic and microbial features of CRC to highlight the role of signal transduction in the orchestration of the tumorigenic process. Concurrently, we review the advent of targeted and immune therapies in CRC, assessing their impact on the current clinical landscape. The development of these therapies has been informed by a deepening understanding of oncogenic signaling, leading to the identification of key nodes within these networks that can be exploited pharmacologically. Furthermore, we explore the potential of integrating AI to enhance the precision of therapeutic targeting and patient stratification, emphasizing their role in personalized medicine. In summary, our review captures the dynamic interplay between aberrant signaling in CRC pathogenesis and the concerted efforts to counteract these changes through targeted therapeutic strategies, ultimately aiming to pave the way for improved prognosis and personalized treatment modalities in colorectal cancer.

Abstract Objectives Preterm delivery rates have increased obviously worldwide over the past decade, yet reliable epidemiological studies on the incidence of preterm birth and temporal trends are not available in Hainan, The Free Trade Port in China. We aimed to describe the rate of preterm birth and trends between 2010 and 2021 and to primarily explore risk factors associated with preterm birth in Hainan, China. Methods This was an observational study was based on data from the Hainan Provincial Birth Certificate System (HPBCS) for live births between 1 January 2010 and 31 December 2021. We included pregnancies resulting in at least one live birth, with newborns born at a gestational age of 28 weeks or greater, or with a birth weight of 1000 g or more. The outcome were preterm birth rates and their trends over time. Potential risk factors were collected, including infant gender, maternal age, paternal age, maternal ethnicity, paternal ethnicity, home address, and single or multiple pregnancies. The logistic regression model was used to assess the relationship between preterm birth and potential risk factors. Results A total of 1,537,239 live births and 86,328 preterm births were investigated, giving a total preterm birth rate of 5.62%. The overall preterm birth rate increased from 4.47% in 2010 to 7.12% in 2021 (compound annual growth rate [CAGR] 4.32). The CAGR of late preterm birth is consistent with the overall preterm birth rate (4.32%). The fastest growth is observed in the rate of very preterm births (5.53%), while the rate of moderate preterm births exhibits the slowest growth (3.87%). Infant gender, multiple pregnancy, home address, parental age, and ethnicity had significant effects on preterm birth. Conclusion The preterm birth rate was increasing year by year from 2010 to 2021 in Hainan, The Free Trade Port in China. Incidence of preterm births in Hainan Province in relation to multiple pregnancies, infant sex, parental age, parental race and residential address.

Abstract Background Blotched snakehead (Channa maculata) displays significant sexual dimorphism, with males exhibiting faster growth rates and larger body sizes compared to females. The cultivation of the all-male population of snakeheads holds substantial economic and ecological value. Nonetheless, the intricate processes governing the development of bipotential gonads into either testis or ovary in C. maculata remain inadequately elucidated. Therefore, it is necessary to determine the critical time window of sex differentiation in C. maculata, providing a theoretical basis for sex control in production practices. Methods The body length and weight of male and female C. maculata were measured at different developmental stages to reveal when sexual dimorphism in growth initially appears. Histological observations and spatiotemporal comparative transcriptome analyses were performed on ovaries and testes across various developmental stages to determine the crucial time windows for sex differentiation in each sex and the sex-related genes. Additionally, qPCR and MG2C were utilized to validate and locate sex-related genes, and levels of E2 and T were quantified to understand sex steroid synthesis. Results Sexual dimorphism in growth became evident starting from 90 dpf. Histological observations revealed that morphological sex differentiation in females and males occurred between 20 and 25 dpf or earlier and 30–35 dpf or earlier, respectively, corresponding to the appearance of the ovarian cavity or efferent duct anlage. Transcriptome analyses revealed divergent gene expression patterns in testes and ovaries after 30 dpf. The periods of 40–60 dpf and 60–90 dpf marked the initiation of molecular sex differentiation in females and males, respectively. Male-biased genes (Sox11a, Dmrt1, Amh, Amhr2, Gsdf, Ar, Cyp17a2) likely play crucial roles in male sex differentiation and spermatogenesis, while female-biased genes (Foxl2, Cyp19a1a, Bmp15, Figla, Er) could be pivotal in ovarian differentiation and development. Numerous biological pathways linked to sex differentiation and gametogenesis were also identified. Additionally, E2 and T exhibited sexual dimorphism during sex differentiation and gonadal development. Based on these results, it is hypothesized that in C. maculata, the potential male sex differentiation pathway, Sox11a–Dmrt1–Sox9b, activates downstream sex-related genes (Amh, Amhr2, Gsdf, Ar, Cyp17a2) for testicular development, while the antagonistic pathway, Foxl2/Cyp19a1a, activates downstream sex-related genes (Bmp15, Figla, Er) for ovarian development. Conclusions This study provides a comprehensive overview of gonadal dynamic changes during sex differentiation and gametogenesis in C. maculata, establishing a scientific foundation for sex control in this species.

Abstract Objective To determine the prevalence of and risk factors for overweight and obese among Chinese children and adolescents. Methods This analytical cross-sectional study included 16,640 children and adolescents aged 6–18 years across four provinces of China in 2016. Physical characteristics and responses to questionnaires were analyzed. Body Mass Index (BMI) and the prevalence of overweight and obesity were calculated. Results Among children and adolescents, the overall prevalence of overweight and obesity in 2016 in four regions of China was 27.2% and 29.6%, respectively. Among different stages and sexes, the highest prevalence of obesity (15.8%) was observed in adolescent boys. From childhood to adolescence, the obesity rate among boys increased by 0.7% (from 15.1% to 15.8%), while the obesity rate among girls decreased by 0.9% (from 10.8% to 9.9%). Children and adolescents who were overweight or obese had significantly higher systolic blood pressures, larger waist circumferences and larger hip sizes than those with a normal BMI. Logistic regression analyses identified thirteen factors associated with overweight or obesity in children and adolescents. Conclusions Our results indicate that the prevalence of overweight and obesity is high among children and adolescents, especially among male adolescents in four regions of China. A suitable intervention program should not only help parents understand the serious risk of childhood obesity but also, more importantly, help to encourage a healthy lifestyle among children and adolescents.

Abstract We report a breakthrough in the hardware implementation of energy-efficient all-spin synapse and neuron devices for highly scalable integrated neuromorphic circuits. Our work demonstrates the successful execution of all-spin synapse and activation function generator using domain wall-magnetic tunnel junctions. By harnessing the synergistic effects of spin-orbit torque and interfacial Dzyaloshinskii-Moriya interaction in selectively etched spin-orbit coupling layers, we achieve a programmable multi-state synaptic device with high reliability. Our first-principles calculations confirm that the reduced atomic distance between 5d and 3d atoms enhances Dzyaloshinskii-Moriya interaction, leading to stable domain wall pinning. Our experimental results, supported by visualizing energy landscapes and theoretical simulations, validate the proposed mechanism. Furthermore, we demonstrate a spin-neuron with a sigmoidal activation function, enabling high operation frequency up to 20 MHz and low energy consumption of 508 fJ/operation. A neuron circuit design with a compact sigmoidal cell area and low power consumption is also presented, along with corroborated experimental implementation. Our findings highlight the great potential of domain wall-magnetic tunnel junctions in the development of all-spin neuromorphic computing hardware, offering exciting possibilities for energy-efficient and scalable neural network architectures.

Abstract Exercise is recognized to play an observable role in improving human health, especially in promoting muscle hypertrophy and intervening in muscle mass loss‐related diseases, including sarcopenia. Recent rapid advances have demonstrated that exercise induces the release of abundant cytokines from several tissues (e.g., liver, muscle, and adipose tissue), and multiple cytokines improve the functions or expand the numbers of adult stem cells, providing candidate cytokines for alleviating a wide range of diseases. Muscle satellite cells (SCs) are a population of muscle stem cells that are mitotically quiescent but exit from the dormancy state to become activated in response to physical stimuli, after which SCs undergo asymmetric divisions to generate new SCs (stem cell pool maintenance) and commit to later differentiation into myocytes (skeletal muscle replenishment). SCs are essential for the postnatal growth, maintenance, and regeneration of skeletal muscle. Emerging evidence reveals that exercise regulates muscle function largely via the exercise‐induced cytokines that govern SC potential, but this phenomenon is complicated and confusing. This review provides a comprehensive integrative overview of the identified exercise‐induced cytokines and the roles of these cytokines in SC function, providing a more complete picture regarding the mechanism of SC homeostasis and rejuvenation therapies for skeletal muscle.

Polarization camera based on CMOS sensor and nano wire-grid technology have found widespread applications in medical diagnostics, remote sensing and industrial inspection. However, the limited filtering properties of wire-grid polarizers and the small field-of-view provided by conventional microlens restrict the energy efficiency of these systems while also increasing their cost, size and weight. In this study, we propose an innovative approach that integrates focusing and splitting of polarization states into a single-layer all-dielectric metasurface. This metasurface enables full-Stokes polarization imaging for a wide field-of-view conical light. The design of the metasurface utilizes a phase compensation method to effectively focus orthogonal polarized conical light onto the central pixel of the CMOS sensor. Theoretical analysis demonstrates that this metasurface can accurately detect full-Stokes parameters within ±20° incident cone angles with an average efficiency reaching 83.0%. The angle can be extended to ±90° with an average efficiency exceeding 80%. We fabricated a three super-pixel metasurface prototype, and experimental measurements reveal its ability to efficiently focus and split three pairs of orthogonal polarization states under ±11° conical angle incidence with an average focusing efficiency of 68.1%. This study presents a promising solution for achieving wide field-of-view and high-efficiency polarization detection in integrated CMOS systems.

BackgroundThe human epidermal growth factor receptor 2 gene (HER2) has been identified as a potential therapeutic target in lung adenocarcinoma (LUAD). Non-invasive positron emission tomography (PET) imaging provides a reliable strategy for in vivo determination of HER2 expression through whole-body detection of abnormalities. The PET tracer 68Ga-NOTA-MAL-Cys-MZHER2:342 has shown promising results for HER2-positive breast and gastric cancers. This study aims to evaluate the performance of 68Ga-NOTA-MAL-Cys-MZHER2:342in vitro and in vivo models and in clinical patients with HER2-positive LUAD.MethodsNOTA-MAL-Cys-MZHER2:342 was synthesized and labeled with 68Ga. Cell uptake, cell binding ability, and stability studies of 68Ga-NOTA-MAL-Cys-MZHER2:342 were assessed both in the Calu-3 lung cancer (LC) cell line and normal mice. In vivo assessment in tumor-bearing mice was conducted using microPET imaging and biodistribution experiments. Additionally, preliminary PET/CT imaging analysis was performed on HER2-positive LC patients.Results68Ga-NOTA-MAL-Cys-MZHER2:342 was prepared with a radiochemical purity (RCP) exceeding 95%. The tracer demonstrated high cell uptake in HER2-overexpressing Calu-3 cells, with an IC50 of 158.9, an adequate 1.73 nM. Good stability was exhibited both in vitro and in vivo. MicroPET imaging of Calu-3-bearing mice revealed high tumor uptake and notable tumor-to-background ratios. Positive outcomes were also observed in two HER2-positive LUAD patients.Conclusion68Ga-NOTA-MAL-Cys-MZHER2:342 demonstrated satisfactory stability, sensitivity, and specificity. These findings suggest that 68Ga-NOTA-MAL-Cys-MZHER2:342 PET/CT imaging provides a novel tool for non-invasive visual assessment of HER2 expression in LUAD patients.

BackgroundAmidst the expansion of student enrollment in higher education, the well-being and retention rates of students have emerged as important concerns. Resilience, especially academic resilience, a multidimensional construct that can lead to academic success in adversity, is pivotal in enabling students to successfully cope with academic challenges. While the Academic Resilience Scale-30 (ARS-30) has been validated as an effective instrument in various languages, its applicability for Chinese students in higher education remains unexplored.ObjectiveThis study aims to translate and validate the ARS-30 in Chinese, assessing its reliability and validity among Chinese college students in higher education.MethodsA convenience sample of 1,542 students participated in this study. The inventory included the demographic form, Chinese version of ARS-30 (C-ARS-30), 10-item Connor Davidson Resilience Scale (CD-RISC-10), and General Self-Efficacy Scale (GSES). The assessment of validity was conducted by analyzing content validity, construct validity, convergent and discriminant validity, as well as criterion-related validity. Construct validity was evaluated through Confirmatory Factor Analysis (CFA), Exploratory Factor Analysis (EFA) and Exploratory Structural Equation Modeling (ESEM). Reliability analysis was performed using Cronbach’s alpha and test–retest reliability.ResultsThe C-ARS-30 demonstrated commendable content validity, with the CVI value of items ranging from 0.833 to 1.000, and a total scale CVI of 0.986. ESEM analysis revealed a solid four-factor structure, maintaining the scale’s 30 items with excellent fit indices (χ2/df = 2.647, CFI = 0.937, TLI = 0.915, RMSEA = 0.057, SRMR = 0.027). The total score of C-ARS-30 exhibited positive correlations with the CD-RISC-10 (r = 0.542) and the GSES (r = 0.488). The scale demonstrated high internal consistency (Cronbach’s α = 0.930) and test–retest reliability (0.794, p

Cisplatin is commonly used in treating osteosarcoma, however, chemoresistance reduces its efficacy and results in a poor prognosis. Lycorine, a Chinese herbal medicine component, possesses anti-tumor and anti-inflammatory properties. This study aims to investigate the combined impact of lycorine and cisplatin on osteosarcoma and its molecular mechanism. The combination of lycorine and cisplatin exhibited a synergistic effect evaluated by MTT and Zheng-Jun Jin’s method. Lycorine and cisplatin synergistically inhibit proliferation, migration, invasion, and induce apoptosis of osteosarcoma cells. Pharmacological analysis predicts 13 key targets, including Wnt/β-Catenin and STAT3. After treatment with this combination, key molecules in Wnt/β-Catenin and STAT3 pathways were significantly inhibited. In an orthotopic tumor model, the combination significantly reduces lung metastasis. The present work suggests that a combination of lycorine with cisplatin can effectively inhibit OS cells by suppressing the Wnt/β-Catenin and STAT3 signaling pathways synergistically. This is expected to enhance the therapeutic effect of OS.

Background: Qingdu Fang (QDF) is a traditional Chinese herbal formula with remarkable clinical effect in the treatment of HR-HPV, but its mechanism remains unclear. In this study, UPLC-QTOF-MS was used to detect its components, network pharmacology was used to explore the traditional Chinese medicine monomers and their related targets for the treatment of HR-HPV in QDF. Molecular docking and in vitro experiments were performed to verify the results.Methods: QDF constituents and active compounds were identified using UPLC-QTOF-MS analysis. TCMSP and GeneCard databases were used to identify active components, targets, and potential therapeutic targets in HR-HPV. PPI network was constructed using the String database to analyze protein-protein interactions. Cytoscape3.7.2 was used to construct PPI networks, while GO enrichment and KEGG pathway analyses with R. The effect of QDF on H8 cell proliferation was measured using the CCK-8 method, and apoptosis and cell cycle was assessed with flow cytometry. The effects of QDF on PI3K/AKT pathway were detected by Western blotting.Results: A total of 27 compounds were identified on QDF by UPLC-QTOF-MS. Base on Network pharmacology,a total of 254 target genes are involved in the action of QDF on cervical HR-HPV. PPI analysis suggested that TP53, JUN, AKT1, STAT3, TNF and IL6 were potential targets for QDF treatment of HR-HPV. Molecular docking shows that two compounds have strong binding activity with AKT1. CCK-8 and morphological observation have shown that QDF inhibits H8 cell proliferation in a dose-dependent manner. Flow cytometry experiments suggest that QDF induces apoptosis and cell cycle arrest in H8 cells. Western blotting experiments reveal that QDF inhibits the PI3K/AKT signaling pathway.Conclusion: QDF has a multi-faceted therapeutic approach for HR-HPV, targeting inflammation, oxidation, and apoptosis. It induces apoptosis in H8 cells by inhibiting the PI3K/AKT pathway.

Abstract Background Allergic diseases exert a considerable impact on global health, thus necessitating investigations into their etiology and pathophysiology for devising effective prevention and treatment strategies. This study employs a Mendelian randomization (MR) analysis and meta-analysis to identify metabolite targets potentially associated with allergic diseases. Methods A two-sample MR analysis was conducted to explore potential causal relationships between circulating and urinary metabolites and allergic diseases. Exposures were derived from a genome-wide association study (GWAS) of 486 circulating metabolites and a GWAS of 55 targeted urinary metabolites. Outcome data for allergic diseases, including atopic dermatitis (AD), allergic rhinitis (AR), and asthma, were obtained from the FinnGen biobank in Europe (cohort 1) and the Biobank Japan in Asia (cohort 2). MR results from both cohorts were combined using a meta-analysis. Results MR analysis identified 50 circulating metabolites and 6 urinary metabolites in cohort 1 and 54 circulating metabolites and 2 urinary metabolites in cohort 2 as potentially causally related to allergic diseases. A meta-analysis of the MR results revealed stearoylcarnitine (OR 8.654; 95% CI 4.399−17.025; P = 4.06E-10) and 1-arachidonoylglycerophosphoinositol (OR 2.178; 95% CI 1.388−3.419; P = 7.15E-04) as the most reliable causal circulating metabolites for asthma and AR, respectively. Further, histidine (OR 0.734; 95% CI: 0.594−0.907; P = 0.004), tyrosine (OR 0.601; 95% CI: 0.380−0.952; P = 0.030), and alanine (OR 0.280; 95% CI: 0.125−0.628; P = 0.002) emerged as urinary metabolites with the greatest protective effects against asthma, AD, and AR, respectively. Conclusions Imbalances in numerous circulating and urinary metabolites may be implicated in the development and progression of allergic diseases. These findings have significant implications for the development of targeted strategies for the prevention and treatment of allergic diseases.

Abstract Background NAT10 is the firstly recognized RNA acetyltransferase that participates in multiple cellular biological processes and human disease. However, the role of N-acetyltransferase 10 (NAT10) in ankylosing spondylitis (AS) is still poorly elaborated. Methods Fifty-six patients with New-Onset AS, 52 healthy controls (HC), 20 patients with rheumatoid arthritis (RA) and 16 patients with systemic lupus erythematosus (SLE) were recruited from The First Afliated Hospital of Nanchang University, and their clinical characteristics were recorded. The expression level of NAT10 in peripheral blood mononuclear cell (PBMC) was examined using reverse transcription-quantitative PCR analysis. The correlations between the expression level of NAT10 in the New-Onset AS patients and disease activity of AS were examined, and receiver operating characteristic (ROC) curves were built to evaluate predictive value in AS. Univariate analysis and multivariate regression analysis were used to analyze the risk factors and construct predictive model. Results The mRNA expressions of NAT10 in PBMC from new-onset AS patients were significantly low and there were negative correlation between mRNA NAT10 and ASDAS-CRP, BASDIA in new-onset AS patients. ROC analysis suggested that mRNA NAT10 has value in distinguishing new-onset AS patients from HC, RA and SLE. Furthermore, a novel predictive model based on mRNA NAT10 and neutrophil percentages (N%) was constructed for distinguishing new-onset AS patients from HC (AUC = 0.880, sensitivity = 84.62%, specificity = 76.92%) and the predictive model correlated with the activity of new-onset AS. Furthermore, the predictive model could distinguish new-onset AS patients from RA and SLE (AUC = 0.661, sensitivity = 90.38%, specificity = 47.22%). Moreover, the potential predictive value of the combination of predictive model-HLA-B27 for AS vs. HC with a sensitivity of 92.86% (39/42), a specificity of 100.00% (52/52) and an accuracy of 96.81% (91/94) was superior to that of HLA-B27, which in turn had a sensitivity of 84.44% (38/45), a specificity of 100.00% (52/52) and an accuracy of 92.78% (90/97). Conclusion The present study suggested that the decreased mRNA NAT10 may play a role in AS pathogenesis and predictive model based on mRNA NAT10 and N% act as bioindicator for forecast and progression of diseases.

Sketch image retrieval is an important branch of the image retrieval field, mainly relying on sketch images as queries for content search. The acquisition process of sketch images is relatively simple and in some scenarios, such as when it is impossible to obtain photos of real objects, it demonstrates its unique practical application value, attracting the attention of many researchers. Furthermore, traditional generalized sketch image retrieval has its limitations when it comes to practical applications; merely retrieving images from the same category may not adequately identify the specific target that the user desires. Consequently, fine-grained sketch image retrieval merits further exploration and study. This approach offers the potential for more precise and targeted image retrieval, making it a valuable area of investigation compared to traditional sketch image retrieval. Therefore, we comprehensively review the fine-grained sketch image retrieval technology based on deep learning and its applications and conduct an in-depth analysis and summary of research literature in recent years. We also provide a detailed introduction to three fine-grained sketch image retrieval datasets: Queen Mary University of London (QMUL) ShoeV2, ChairV2 and PKU Sketch Re-ID, and list common evaluation metrics in the sketch image retrieval field, while showcasing the best performance achieved for these datasets. Finally, we discuss the existing challenges, unresolved issues and potential research directions in this field, aiming to provide guidance and inspiration for future research.

Mesona chinensis Benth. (or Platostoma palustre (Blume) A. J. Paton), an edible and medicinal plant, is the main ingredient in black jelly, Hsian-tsao tea, and beverages, and its processed products are popular in China as well as in Southeast Asian countries. Previous studies have shown that the alcohol extract of Mesona chinensis Benth. (MC) can reduce the accumulation of oleic acid and ameliorate hyperlipidemia. However, researchers have not yet determined whether it could improve intestinal permeability and metabolic dysfunction by controlling gut microbial dysbiosis and thus reducing hyperlipidemia. This study aimed to explore the potential mechanism by which MC regulates metabolic function disorders in hyperlipidemic high-fat diet (HFD)-fed rats and mice from the perspective of gut microbiota. This study analyzed the effects of MC on metabolic indices related to hyperlipidemia in HFD-fed rats and the abundance and diversity of the gut microbiota via 16S rRNA V3–4 region pyrosequencing to investigate the regulation of the gut microbiota by MC. We further confirmed that MC ameliorates hyperlipidemia by regulating the gut microbiota by simultaneously administering antibiotics and MC to C57BL/6 mice and measuring their metabolic indices. These results indicate that MC reduces the lipid concentration in the serum of HFD-fed rats, thereby significantly alleviating hyperlipidemia, and regulates the abundance ratio and diversity of the gut microbiota, thereby exerting a beneficial effect on hyperlipidemia. Our further antibiotic experiments in mice revealed that the administration of MC was unable to reduce body weight or serum and organ lipid concentrations in the antibiotic-treated group of hyperlipidemic mice. This study provides evidence that the microbiota is an alternative target for the antihyperlipidemic effect of MC.

Osteosarcoma is a differentiation-deficient disease, and despite the unique advantages and great potential of differentiation therapy, there are only a few known differentiation inducers, and little research has been done on their targets. Cell differentiation is associated with an increase in mitochondrial content and activity. The metabolism of some tumor cells is characterized by impaired oxidative phosphorylation, as well as up-regulation of aerobic glycolysis and pentose phosphate pathways. Leucine-containing zipper and EF-hand transmembrane protein 1 (LETM1) is involved in the maintenance of mitochondrial morphology and is closely associated with tumorigenesis and progression, as well as cancer cell stemness. We found that MG63 and 143B osteosarcoma cells overexpress LETM1 and exhibit abnormalities in mitochondrial structure and function. Knockdown of LETM1 partially restored the mitochondrial structure and function, inhibited the pentose phosphate pathway, promoted oxidative phosphorylation, and led to osteogenic differentiation. It also inhibited spheroid cell formation, proliferation, migration, and invasion in an in vitro model. When LETM1 was knocked down in vivo, there was reduced tumor formation and lung metastasis. These data suggest that mitochondria are aberrant in LETM1-overexpressing osteosarcoma cells, and knockdown of LETM1 partially restores the mitochondrial structure and function, inhibits the pentose phosphate pathway, promotes oxidative phosphorylation, and increases osteogenic differentiation, thereby reducing malignant biological behavior of the cells.

The blotched snakehead (Channa maculata) is a freshwater species of economic importance, widely distributed throughout Southeast Asia and Southern China. The comprehension of genetic regulatory mechanisms underlying growth traits, particularly body weight, is paramount for the advancement and economic viability of blotched snakehead aquaculture. Despite its importance, limited investigations have been undertaken regarding the growth properties of this species. To enhance our grasp of the genetic regulation mechanisms dictating growth traits and identify pertinent genetic loci, the inaugural genome-wide association study (GWAS) was executed. In this study, eight growth traits of 500 blotched snakeheads were measured and whole genome resequencing (WGS) were conducted. Genetic parameters were estimated for the eight traits, revealing moderate to high heritability (0.2245–0.5184) for seven traits, while one exhibited low heritability (0.1081). A comprehensive set of 2, 225, 993 high-quality SNPs were identified in the 500 blotched snakehead individuals, and the mixed linear model in GEMMA was applied for GWAS analysis. A total of 51 significant SNPs related to the seven growth traits were identified, and 112 genes were obtained by scanning 50 kb upstream and downstream regions. Thirteen genes harboring significant SNP sites were considered as important candidate genes, and these genes were associated with organelle formation, signal transduction, cell proliferation, and muscle growth. Notably, the HS6ST1 gene was significantly associated with body weight, body length and total length, designating it as a key candidate gene. This investigation makes a substantive contribution to our comprehension of the genetic architecture governing growth traits in the blotched snakehead, establishing a robust foundation for future initiatives in molecular marker-assisted selection and breeding strategies.

BackgroundsImproving quality of life (QOL) is one of the main aims of lung transplantation (LTx). There is a need to identify those who have poor quality of life early. However, research addressing inter individual quality of life variability among them is lacking. This study aims to identify group patterns in quality of life among lung transplant recipients and examine the predictors associated with quality of life subgroups.MethodsIn total, 173 lung transplant recipients were recruited from one hospital in Guangdong Province between September 2022 and August 2023. They were assessed using the Lung Transplant Quality of Life scale (LT-QOL), Mindful Attention Awareness Scale (MAAS), Life Orientation Test-Revised scale (LOT-R), and Positive and Negative Affect Scale (PANAS). Latent profile analysis was used to identify QOL subtypes, and logistic regression analysis was used to examine the associations between latent profiles and sociodemographic and psychosocial characteristics.ResultsTwo distinct QOL profiles were identified: “low HRQOL” profile [N = 53 (30.94%)] and “high HRQOL” profile [N = 120 (69.06%)]. Single lung transplant recipients, and patients who reported post-transplant infection, high levels of negative emotion or low levels of mindfulness and optimism were significantly correlated with the low QOL subgroup.ConclusionUsing the domains of the LT-QOL scale, two profiles were identified among the lung transplant recipients. Our findings highlighted that targeted intervention should be developed based on the characteristics of each latent class, and timely attention must be paid to patients who have undergone single lung transplantation, have had a hospital readmission due to infection, exhibit low levels of optimism, low levels of mindfulness or high negative emotions.

Abstract Time‐delayed reservoir computing with marked strengths of friendly hardware implementation and low training cost is regarded as a promising solution to realize time and energy‐efficient time series information processing and thus receives growing attention. However, achieving a sufficient number of reproducible reservoir states remains a significant challenge, which severely limits its computing performance. Here, an electric‐double‐layer‐coupled oxide‐based electrolyte‐gated transistor with a shared gate and varying channel lengths is developed to construct a deep time‐delayed reservoir computing system. A variety of short‐term synaptic responses related to inherent ion‐electron‐coupled dynamics at the electrolyte/channel interface are demonstrated, reflecting a flexibly regulable channel current. Different stable and tunable relaxation responses corresponding to varying channel lengths are obtained to enrich reservoir states combined with virtual nodes ways. The spoken‐digit classification and Hénon map prediction tasks are implemented with high accuracy (≈92.2%) and ultralow normalized root mean square error (≈0.013), respectively, validating the significant improvement of the computing performance by introducing additional relaxation responses. This work opens a promising pathway in exploiting oxide‐based electrolyte‐gated transistors for realizing temporal information processing hardware systems.

Duchenne muscular dystrophy (DMD MIM#310200) is a degenerative muscle disease caused by mutations in the dystrophin gene located on Xp21.2. The clinical features encompass muscle weakness and markedly elevated serum creatine kinase levels. An 8-year-old Chinese boy was diagnosed with Duchenne muscular dystrophy (DMD). Whole exome gene sequencing was conducted and the Sanger method was used to validate sequencing. A deletion (c.5021del) in exon 35 of the dystrophin gene was identified, which was predicted to generate a frameshift mutation and create an early termination codon (p.Leu1674CysfsTer47). It has a pathogenic effect against dystrophin in the muscle cell membrane of the patient. As such, prednisone treatment at a dose of 0.75 mg/kg.d was administered. After one month, a notable reduction in fall frequency was observed. Our new finding will expand the pathogenic mutation spectrum causing DMD.

Microlens array combined with CMOS sensors have recently been the subject of intensive research due to their ability to significantly enhance imaging sensitivity. However, existing microlens arrays suffer from a limited field-of-view, necessitating complex lens assemblies that increase system cost, size and weight. In this study, we present a novel approach utilizing a single layer metalens array composed of low loss and high-index α-Si materials. The metalens array was designed using a phase compensation method to efficiently focus conical light with arbitrary cone angles onto the center pixels of the CMOS sensor. Theoretical analysis demonstrates that the metalens is capable of focusing ± 20° conical light with an impressive efficiency of 83.6 %, which can be extended to arbitrary cone angles. Experimental results reveal a measured focusing efficiency of 73 % under an incidence angle of ± 8.3° for conical light, representing an improvement of 8 % compared to parallel light incidence. This research presents a promising solution for wide-field-of-view metalens arrays in integrated CMOS imaging systems.

Abstract Aim To identify latent profiles of nurses’ subjective well‐being (SWB) and explore its association with social support and professional self‐concept. Design This study used an online survey and cross‐sectional latent profile analysis design. Methods A total of 1009 nurses from 30 hospitals in Guangdong Province, China, were selected using convenience sampling. An online questionnaire survey comprising the following scales was distributed: Index of Well‐Being, Nurses’ Professional Self‐concept Questionnaire and Multidimensional Scale of Perceived Social Support. Nurses’ SWB was examined and categorized into profiles using nine Index of Well‐being items as explicit variables and ordinal logistic regression analysis was performed to explore factors related to the distinct categories. Results Nurses’ SWB was divided into four latent profiles: extremely low, low, moderate and high. Regression analysis showed that social support and professional self‐concept influenced SWB. There were statistically significant differences in age, title, working years, social support and professional self‐concept among nurses in the different well‐being categories. Ordered logistic regression analysis showed that social support and professional self‐concept are associated with different SWB profiles.

It is well established that increased peripheral helper T cells (TPH) and follicular helper T cells (TFH) was found in systemic lupus erythematosus (SLE) patients. However, the expression patterns and immunomodulatory roles of TIGIT and PD1 on TPH/TFH in SLE are poorly understood. The expression patterns of TIGIT and PD1 on TPH and TFH cells were examined using flow cytometry and their expression patterns in SLE patients were then further evaluated for their correlation with auto-antibodies, disease activity and severity, B cell differentiation. Logistic regression was used to analyze the risk factors. And the receiver operating characteristic curves and logistic regression model were created to evaluate the predicting role in SLE. TIGIT±PD1+TPH, TIGIT±PD1+TFH cells in the peripheral blood of SLE patients were upregulated, whereas TIGIT+PD1−TFH was downregulated. TIGIT ± PD1+TPH, TIGIT ± PD1+TFH cells positively correlated with auto-antibodies production, disease activity and severity, whereas TIGIT+PD1−TFH cells negatively correlated. TIGIT ± PD1+TPH, TIGIT−PD1+TFH were positively correlated with the frequency of plasmablasts. Furthermore, higher TIGIT+PD1+TPH and TIGIT+PD1+TFH were shown to be risk factors for SLE, whereas TIGIT+PD1−TFH was found to be a protective factor, according to logistic regression analysis. A further logistic regression model showed that combination of TPH/TFH and routine blood indicators may has potential predicting value for SLE, with AUC of 0.957. The increased TIGIT ± PD1+TPH, increased TIGIT ± PD1+TFH, decreased TIGIT+PD1−TFH correlates with disease severity and activity, may boost our comprehending of the role of TIGIT and PD1 on TPH/TFH in SLE, and a logistic regression model based on combination of TPH/TFH and routine blood indicators shows prominent value for predicting SLE.

Existing methods of measuring energy consumption require complex statistics and computing. A real-time and globally applicable approach for comparing energy consumption across different cities is still lacking. Additionally, the nonlinear relationships and varying thresholds of energy consumption in relation to economic activities and urbanization remain unconfirmed. This study aims to fill these gaps by utilizing Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data in 2015 and a top-down approach based on a multiple regression model to examine energy consumption in global cities employing a redefined urban boundary. It also explores the accurate relationship between energy consumption, population density (as a proxy of urbanization), and per capita gross domestic product (GDP) across different regions and urban sizes using generalized additive models and regression models. High-resolution gridded population and GDP datasets covering the entire planet are utilized for this purpose. The study also estimates the development potentiality. The study yields followings outcomes: Firstly, the top 30 cities with the highest per capita energy consumption account for over 0.66% of the total per capita energy consumption of all cities. Secondly, in East Asia (EA) and Southeast Asia (SEA), the per capita energy consumption decreases when per capita GDP reaches $40,000 and $75,000, respectively, while it remains stable in cities located in Western Europe (WE) and North America (NA) as per capita GDP increases. Thirdly, the per capita energy consumption declines with increasing urban population density until reaching 10,000 person/km2, 22,000 person/km2, and 4000 person/km2 in EA, SEA, and NA, respectively. Fourthly, in Central Asia (CA), megacities can save over 100 Mbtu/population when per capita GDP increases by $1000 compared to big cities. This pioneering study provides a comparable investigation of energy consumption at the global city level, exploring its relationship with urbanization and economy by employing a unified calculation standard. It will facilitate long-term energy-saving policies and urban planning strategies.

Abstract Background Estrogen receptor beta (ERβ, Esr2) plays a pivotal role in folliculogenesis and ovulation, yet its exact mechanism of action is mainly uncharacterized. Results We here performed ERβ ChIP-sequencing of mouse ovaries followed by complementary RNA-sequencing of wild-type and ERβ knockout ovaries. By integrating the ERβ cistrome and transcriptome, we identified its direct target genes and enriched biological functions in the ovary. This demonstrated its strong impact on genes regulating organism development, cell migration, lipid metabolism, response to hypoxia, and response to estrogen. Cell-type deconvolution analysis of the bulk RNA-seq data revealed a decrease in luteal cells and an increased proportion of theca cells and a specific type of cumulus cells upon ERβ loss. Moreover, we identified a significant overlap with the gene regulatory network of liver receptor homolog 1 (LRH-1, Nr5a2) and showed that ERβ and LRH-1 extensively bound to the same chromatin locations in granulosa cells. Using ChIP-reChIP, we corroborated simultaneous ERβ and LRH-1 co-binding at the ERβ-repressed gene Greb1 but not at the ERβ-upregulated genes Cyp11a1 and Fkbp5. Transactivation assay experimentation further showed that ERβ and LRH-1 can inhibit their respective transcriptional activity at classical response elements. Conclusions By characterizing the genome-wide endogenous ERβ chromatin binding, gene regulations, and extensive crosstalk between ERβ and LRH-1, along with experimental corroborations, our data offer genome-wide mechanistic underpinnings of ovarian physiology and fertility.

Over the past 2 decades, cancer stem cells (CSCs) have been identified as the root cause of cancer occurrence, progression, chemoradioresistance, recurrence, and metastasis. Targeting CSCs is a novel therapeutic strategy for cancer management and treatment. Liver cancer (LC) is a malignant disease that can endanger human health. Studies are increasingly suggesting that changes in the liver mechanical microenvironment are a primary driver triggering the occurrence and development of liver cancer. In this review, we summarize current understanding of the roles of the liver mechano-microenvironment and liver cancer stem cells (LCSCs) in liver cancer progression. We also discuss the relationship between the mechanical heterogeneity of liver cancer tissues and LCSC recruitment and metastasis. Finally, we highlight potential mechanosensitive molecules in LCSCs and mechanotherapy in liver cancer. Understanding the roles and regulatory mechanisms of the mechano-microenvironment and LCSCs may provide fundamental insights into liver cancer progression and aid in further development of novel therapeutic strategies.

Abstract Background Recently developments in the field of positive psychology have provided new perspectives for understanding the connection between individual variation in Quality of life (QoL) and positive aspects of human potential, strengths, and resources, commanding increasing attention. This study aimed to examine self-reported quality of life (QoL) profiles and the association of QoL profiles with positive psychosocial characteristics in Chinese older adults. Methods A convenient sample of 354 older adults in nursing homes was recruited from Guangdong Province, China, between November 2020 and January 2021. Latent Profile Analysis (LPA) was conducted to explore QoL profiles using the four WHOQOL-BREF domains as input variables. Multinomial logistic regression was performed to explore the association between latent profiles and predictors. Results LPA identified three latent QoL profiles: “low QoL with poor psychological health” (18.1%), “moderate QoL” (46.0%) and “high QoL” (35.9%). Frequency of weekly activity, optimism, gratitude, and social support were associated with the increased likelihood of belonging to the moderate-to-high QoL classes. Furthermore, Class 2 (moderate QoL group, reference) was compared with Class3 (high QoL group), higher frequency of weekly physical activity and spending more time on physical activity exhibited higher odds of belonging to high QoL class. Conclusion Using the domains of the WHOQOL-BREF scale, the QoL profiles Chinese older adults can be identified. We found that psychosocial variables and demographic characteristic, including lower level of optimism and gratitude, lack of social support, low frequency of physical activity, and shorter activity duration time, heighten the risk for lower levels of QoL. Identifying classification may help focus on those at elevated risk for poor QoL and for developing tailored QoL improvement programs.

Objective To examine the prevalence and influencing factors of sleep duration among school-age children in Hainan province for improving sleep quality of the children. Methods Totally 25 162 children aged 6 – 12 years in 86 primary schools in Hainan province were recruited with stratified multistage random sampling. A self-designed questionnaire on demographics, sleep time and its associates was answered online by the children′s parents during November 2021 – January 2022. Logistic regression model was used to explore influencing factors of insufficient sleep in the children. ResultsFor the 24 200 children included in the final analysis, the parents-reported average weekday and weekend nighttime sleep time were 8.79 ± 0.81 and 9.51 ± 0.98 hours and the average total sleep time were 10.06 ± 1.18 and 11.62 ± 1.20 hours, respectively. Based on the parents′ reports, the prevalence of insufficient sleep (total sleep time < 10 hours/per day) was 30.8% and the prevalence linearly increased significantly with the increment of age among the children (P < 0.05). Logistic regression model analysis showed that the children with following characteristics were at significantly increased risk of having insufficient sleep time: aged 11 – 12 years (versus aged 6 – 7 years: odds ratio [OR] = 1.59, 95% confidence interval [95%CI]: 1.43 – 1.77); with paternal education of college and above (versus primary school: OR = 1.36, 95%CI: 1.15 – 1.60); from core families (versus from families of other types: OR = 1.13, 95%CI: 1.01 – 1.26) or from stem families (versus from families of other types: OR = 1.14, 95%CI: 1.04 – 1.36); having daily outdoor sports time of less than one hour (versus 2 hours and more: OR = 1.69, 95%CI: 1.42 – 2.00); and having daily screen exposure time of 2 hours and longer (versus that of less than one hour: OR = 1.34, 95%CI: 1.18 – 1.51). ConclusionInsufficient sleep time, especially insufficient nighttime sleep time, is prevalent among school-age children in Hainan province and at elder age, with higher paternal education, from core or stem families, less outdoor sports time, and longer screen exposure time are significant risk factors for insufficient sleep time in the school-age children.

Abstract Breast cancer metastasis is a complex, multi-step process, with high cellular heterogeneity between primary and metastatic breast cancer, and more complex interactions between metastatic cancer cells and other cells in the tumor microenvironment. High-resolution single-cell transcriptome sequencing technology can visualize the heterogeneity of malignant and non-malignant cells in the tumor microenvironment in real time, especially combined with spatial transcriptome analysis, which can directly compare changes between different stages of metastatic samples. Therefore, this study takes single-cell analysis as the first perspective to deeply explore special or rare cell subpopulations related to breast cancer metastasis, systematically summarizes their functions, molecular features, and corresponding treatment strategies, which will contribute to accurately identify, understand, and target tumor metastasis-related driving events, provide a research basis for the mechanistic study of breast cancer metastasis, and provide new clues for its personalized precision treatment.

Abstract Neuromorphic computing aims to emulate the computing processes of the brain by replicating the functions of biological neural networks using electronic counterparts. One promising approach is dendritic computing, which takes inspiration from the multi-dendritic branch structure of neurons to enhance the processing capability of artificial neural networks. While there has been a recent surge of interest in implementing dendritic computing using emerging devices, achieving artificial dendrites with throughputs and energy efficiency comparable to those of the human brain has proven challenging. In this study, we report on the development of a compact and low-power neurotransistor based on a vertical dual-gate electrolyte-gated transistor (EGT) with short-term memory characteristics, a 30 nm channel length, a record-low read power of ~3.16 fW and a biology-comparable read energy of ~30 fJ. Leveraging this neurotransistor, we demonstrate dendrite integration as well as digital and analog dendritic computing for coincidence detection. We also showcase the potential of neurotransistors in realizing advanced brain-like functions by developing a hardware neural network and demonstrating bio-inspired sound localization. Our results suggest that the neurotransistor-based approach may pave the way for next-generation neuromorphic computing with energy efficiency on par with those of the brain.

Abstract Background Increasing evidence suggests that hepatocellular carcinoma (HCC) stem cells (LCSCs) play an essential part in HCC recurrence, metastasis, and chemotherapy and radiotherapy resistance. Multiple studies have demonstrated that stemness-related genes facilitate the progression of tumors. However, the mechanism by which stemness-related genes contribute to HCC is not well understood. Here, we aim to construct a stemness-related score (SRscores) model for deeper analysis of stemness-related genes, assisting with the prognosis and individualized treatment of HCC patients.Further, we found that the gene LPCAT1 was highly expressed in tumor tissues by immunohistochemistry, and sphere-forming assay revealed that knockdown of LPCAT1 inhibited the sphere-forming ability of hepatocellular carcinoma cells. Methods We used the TCGA-LIHC dataset to screen stemness-related genes of HCC from the MSigDB database. Prognosis, tumor microenvironment, immunological checkpoints, tumor immune dysfunction, rejection, treatment sensitivity, and putative biological pathways were examined. Random forest created the SRscores model. The anti-PD-1/anti-CTLA4 immunotherapy, tumor mutational burden, medication sensitivity, and cancer stem cell index were compared between the high- and low-risk score groups. We also examined risk scores for different cell types using single-cell RNA sequencing data and correlated transcription factor activity in cancer stem cells with SRscores genes. Finally, we tested core marker expression and biological functions. Results Patients can be divided into two subtypes (Cluster1 and Cluster2) based on the TCGA-LIHC dataset's identification of 11 stemness-related genes. Additionally, a SRscores was developed based on subtypes. Cluster2 and the group with the lowest SRscores had superior survival and immunotherapy response than Cluster1 and the group with the highest SRscores. The group with a high SRscores was significantly more enriched in classical tumor pathways than the group with a low SRscores. Multiple transcription factors and SRscores genes are correlated. The core gene LPCAT1 is highly expressed in rat liver cancer tissues and promotes tumor cell sphere formation. Conclusion A SRscores model can be utilized to predict the prognosis of HCC patients as well as their response to immunotherapy.

Due to their excellent light transmission, heat resistance, corrosion resistance, high mechanical strength, and other characteristics, transparent materials have been widely used in emerging industries such as aviation, aerospace, microelectronics, interconnected communication, etc. Compared with the traditional mechanical processing and chemical processing of transparent materials, laser processing, with such characteristics as a high peak power, high energy density, and non-contact processing, has a lot of obvious advantages in processing efficiency and accuracy. In this paper, some of the recent research advancements concerning the laser processing of transparent materials are introduced in detail. Firstly, the basic mechanism of the interaction between the laser and material is briefly summarized on the time scale. The differences in principle between nanosecond, picosecond, and femtosecond pulse laser processing are analyzed. Then, the main technical means of the nanosecond laser processing of transparent materials are summarized. Next, the main application directions of the ultrafast laser processing of transparent materials are discussed, including the preparation of optical waveguide devices, periodic structure devices, micropores, and microchannels. Finally, this paper summarizes the prospects for the future development of laser processing transparent materials.

The plectin gene can encode a cytoskeletal linking protein, plectin, known for its interaction with three critical components of the cellular cytoskeleton: intermediate filaments, microtubules, and actin filaments. In recent years, more and more studies have reported that plectin is closely related to tumorigenesis and development, exhibiting both tumor-suppressive and tumor-promoting functions. Here, we first introduce the molecular structure and function of plectin, and then we summarize the current understanding of the crucial role of plectin in cancer progression. Finally, we also discuss the possible reasons for the different roles of plectin expression in various types of cancer and highlight the double-edged sword role of plectin in tumor progression. The review aims to deepen the comprehensive understanding of plectin’s role in cancer and further help to develop novel therapeutic strategies and drug targets.

In order to improve the efficiency of fine segmentation and obstacle removal in the road of tea plantation in hilly areas, a lightweight and high-precision DR-YOLO instance segmentation algorithm is proposed to realize environment awareness. Firstly, the road data of tea gardens in hilly areas were collected under different road conditions and light conditions, and data sets were generated. YOLOv8n-seg, which has the highest operating efficiency, was selected as the basic model. The MSDA-CBAM and DR-Neck feature fusion network were added to the YOLOv8-seg model to improve the feature extraction capability of the network and the feature fusion capability and efficiency of the model. Experimental results show that, compared with the YOLOv8-seg model, the DR-YOLO model proposed in this study has 2.0% improvement in AP@0.5 and 1.1% improvement in Precision. In this study, the DR-YOLO model is pruned and quantitatively compressed, which greatly improves the model inference speed with little reduction in AP. After deploying on Jetson, compared with the YOLOv8n-seg model, the Precision of DR-YOLO is increased by 0.6%, the AP@0.5 is increased by 1.6%, and the inference time is reduced by 17.1%, which can effectively improve the level of agricultural intelligent automation and realize the efficient operation of the instance segmentation model at the edge.

As a member of the pattern recognition receptor (PRR) class, scavenger receptor class B type 1 (SRB1) plays a key role in innate immunity. Grass carp (Ctenopharyngodon idellus) ranks among the most extensively cultivated freshwater aquaculture species in China. However, little is known about the function of SRB1 in C. idellus. In this research study, a SRB1 gene was identified in C. idellus, named CiSRB1. The full-length cDNA of CiSRB1 is 2486 bp long, with an open reading frame (ORF) of 2486 bp encoding a 497 amino acid (aa) protein containing a conserved CD36 domain. The identified genomic DNA length of CiSRB1 is 20,042 bp, including 12 exons and 11 introns. The predictive analysis of protein interactions revealed that CiSRB1 could interact with the outer capsid proteins of typical GCRV strains. The tissue distribution of CiSRB1 exhibited age-dependent characteristics. CiSRB1 displayed the highest expression in the intestines and moderate levels in muscle, spleen, liver, and brain of one-year-old grass carp while maintaining relatively low levels in three-year-old grass carp. Following grass carp reovirus (GCRV) infection, notable upregulation of CiSRB1 transcripts was observed in major immune tissues (gills, intestines, spleen, and liver). Furthermore, significant differences were found between one-year-old and three-year-old grass carp, with lower CiSRB1 expression levels being detected in the older group. Additionally, a distinct response to GCRV infection was observed in one-year-old and three-year-old grass carp. It was found that one-year-old individuals had a mortality rate of up to 84% 6 days post-infection (dpi), whereas all three-year-old counterparts survived after GCRV infection. The analysis of GCRV copy numbers across tissues revealed substantially higher levels in one-year-old grass carp compared with their older counterparts, confirming the existence of age-dependent susceptibility to GCRV infection in grass carp. Combined with these results, it was speculated that the decline in cell-surface CiSRB1 expression with age may impede reovirus binding to host cells, potentially explaining why older grass carp demonstrated enhanced resistance to GCRV infection. This observation accentuates the importance of CiSRB1 in the context of GCRV infection and provides insights into age-dependent susceptibility to reovirus.

Bolting and flowering of vegetables are induced by vernalization in their early growth stage. This phenomenon is called premature bolting, and it has caused massive losses in production of vegetables such as cabbage, celery, carrot, radish, and spinach, etc. This review aimed to summarize studies on bolting and flowering pathways, physiological and biochemical changes, and underlined molecular mechanisms of various vegetable crop bolting involving genome and transcriptome analysis, and its association with vegetable breeding. This review could provide basic knowledge to carry out research on vegetable genetics and breeding and vegetable cultivation.

Microcystins (MCs), being among the most concerned cyanobacterial toxins and with acute hepatotoxic effects, can induce liver damage and even lead to liver cancer after long-term intake. Addition to existing in contaminated water and aquatic products, MCs can also be accumulated in crops via polluted irrigation water, which could increase the health risk of human. In this paper, we systematically reviewed the enrichment characteristics of MCs in different crops and their toxicities to those crops. The potential health risks from MCs residues in edible parts of crops were also discussed.

Abstract Background Long non-coding RNA (lncRNA) plays a vital role in tumor proliferation, migration, and treatment. Since it is challenging to standardize the gene expression levels detected by different platforms, the signatures composed of many immune-related single lncRNAs are still inaccurate. Utilizing a gene pair formed of two immune-related lncRNAs and strategically assigning values can effectively meet the demand for a higher-accuracy dual biomarker combination. Methods Co-expression and differential expression analyses were performed on immune genes and lncRNAs data from The Cancer Genome Atlas and the ImmPort database to obtain differentially expressed immune-related lncRNAs for pairwise pairing. The prognostic-related differentially expressed immune-related lncRNAs (PR-DE-irlncRNAs) pairs were then identified by univariate Cox regression and used for lasso regression to construct a prognostic model. Various methods were used to validate the predictive prognostic performance of the model. Additionally, we explored the potential guiding value of the model in immunotherapy and chemotherapy and constructed a nomogram suitable for efficient prognosis prediction. Mechanistic exploration of anti-tumor immunity and mutational perspectives are also included. We also analyzed the correlation between the model and immune checkpoint inhibitors (ICIs)-related, N6-methyadenosine (m6A)-related, and multidrug resistance genes. Results We used a total of 20 pairs of PR-DE-irlncRNAs to create a prognosis model. Quantitative real-time polymerase chain reaction experiments further verified the abnormal expression of 11 lncRNAs in HNSCC cells. Various methods have confirmed the excellent performance of the model in predicting patient prognosis. We reasoned that lncRNAs/TP53 mutation might play a positive/negative anti-tumor role through the immune system by multi-perspective analyses. Finally, it was found that the prognostic model was closely related to immunotherapy and chemotherapy as well as the expression of ICIs/m6A/multidrug resistance-related genes. Conclusion The prognostic model performs excellently in predicting the prognosis of patients and provides the potential value of practical guidance for treatment.

Wolfberry, also known as goji berry or Lycium barbarum, is a highly valued fruit with significant health benefits and nutritional value. For more efficient and comprehensive usage of published L. barbarum genomic data, we established the Wolfberry database. The utility of the Wolfberry Genome Database (WGDB) is highlighted through the Genome browser, which enables the user to explore the L. barbarum genome, browse specific chromosomes, and access gene sequences. Gene annotation features provide comprehensive information about gene functions, locations, expression profiles, pathway involvement, protein domains, and regulatory transcription factors. The transcriptome feature allows the user to explore gene expression patterns using transcripts per kilobase million (TPM) and fragments per kilobase per million mapped reads (FPKM) metrics. The Metabolism pathway page provides insights into metabolic pathways and the involvement of the selected genes. In addition to the database content, we also introduce six analysis tools developed for the WGDB. These tools offer functionalities for gene function prediction, nucleotide and amino acid BLAST analysis, protein domain analysis, GO annotation, and gene expression pattern analysis. The WGDB is freely accessible at https://cosbi7.ee.ncku.edu.tw/Wolfberry/. Overall, WGDB serves as a valuable resource for researchers interested in the genomics and transcriptomics of L. barbarum. Its user-friendly web interface and comprehensive data facilitate the exploration of gene functions, regulatory mechanisms, and metabolic pathways, ultimately contributing to a deeper understanding of wolfberry and its potential applications in agronomy and nutrition.

Objective: The aim of this study is to comprehensively investigate the prevalence and distribution patterns of three common genetic variants associated with hearing loss (HL) in Chinese neonatal population. Methods: Prior to June 30, 2023, an extensive search and screening process was conducted across multiple literature databases. R software was utilized for conducting meta-analyses, cartography, and correlation analyses. Results: Firstly, our study identified a total of 99 studies meeting the inclusion criteria. Notably, provinces such as Qinghai, Tibet, Jilin, and Heilongjiang lack large-scale genetic screening data for neonatal deafness. Secondly, in Chinese newborns, the carrier frequencies of GJB2 variants (c.235delC, c.299_300delAT) were 1.63 % (95 %CI 1.52 %–1.76 %) and 0.33 % (95 %CI 0.30 %–0.37 %); While SLC26A4 variants (c.919-2A > G, c.2168A > G) exhibited carrier rates of 0.95 % (95 %CI 0.86 %–1.04 %) and 0.17 % (95 %CI 0.15 %–0.19 %); Additionally, Mt 12S rRNA m.1555 A > G variant was found at a rate of 0.24 % (95 % CI 0.22 %–0.26 %). Thirdly, the mutation rate of GJB2 c.235delC was higher in the east of the Heihe-Tengchong line, whereas the mutation rate of Mt 12S rRNA m.1555 A > G variant exhibited the opposite pattern. Forthly, no significant correlation exhibited the opposite pattern of GJB2 variants, but there was a notable correlation among SLC26A4 variants. Lastly, strong regional distribution correlations were evident between mutation sites from different genes, particularly between SLC26A4 (c.919-2A > G and c.2168A > G) and GJB c.299_300delAT. Conclusions: The most prevalent deafness genes among Chinese neonates were GJB2 c.235delC variant, followed by SLC26A4 c.919-2A > G variant. These gene mutation rates exhibit significant regional distribution characteristics. Consequently, it is imperative to enhance genetic screening efforts to reduce the incidence of deafness in high-risk areas.

To evaluate the effects of dietary protein on reproductive performance, egg quality and larval health of the blotched snakehead Channa maculata, three groups were designed: a high protein group (HP) with 48% protein content, a low protein group (LP) with 44% protein content, and a control group (C) fed with commercial feed containing 40% protein. The results demonstrated that the HP diet significantly enhanced maternal absolute fecundity, egg size and offspring health; however, it had no impact on fertilization rate and hatching rate. The maternal plasma levels of 11-ketotestosterone, 17β-estradiol, and vitellogenin in the HP group were found to be significantly higher compared to those in the C group. Plasma SOD activity and T-AOC capacity in the HP group were significantly higher than those in the C group, while MDA content showed an opposite trend. The trend of T-AOC in 7 days post-hatching larvae exhibited a consistent pattern with that observed in the maternal. Metabolomics and transcriptomics results indirectly indicated that the differences in reproductive and egg quality of the broodstock were associated with the regulation of arachidonic acid metabolism, steroid hormone biosynthesis, cholesterol metabolism, glycerophospholipid metabolism, and glycerolipid metabolism. The expression levels of star, zp3, foxo3, tgf-β, ghr, igf, cyp17a1, and cyp19a1 genes associated with reproduction and were significantly upregulated in the HP group. By depleting the abundance of metabolites in key pathway such as the pentose phosphate pathway, glycolysis/gluconeogenesis, nicotinate and nicotinamide metabolism, vitamin B6 metabolism within the ovary, there is an elevation in arachidonic acid metabolite abundance, thereby facilitating ovarian maturation and regulating egg quality. In conclusion, the high protein diet may affect the reproductive process and egg quality by inducing an upregulation of TGF-beta signaling pathway and ovarian steroidogenesis and arachidonic acid metabolism, leading to increased plasma cholesterol levels and enhanced steroid hormone synthesis.

In this work, the requirement of using high‐precision (HP) signals is lifted and the circuits for implementing deep learning algorithms in memristor‐based hardware are simplified. The use of HP signals is required by the backpropagation learning algorithm since the gradient descent learning rule relies on the chain product of partial derivatives. However, it is both challenging and biologically implausible to implement such an HP algorithm in noisy and analog memristor‐based hardware systems. Herein, it is demonstrated that the requirement for HP signals handling is not necessary and more efficient deep learning can be achieved when using a binary stochastic learning algorithm. The new algorithm proposed in this work modifies elementary neural network operations, which improves energy efficiency by two orders of magnitude compared to traditional memristor‐based hardware and three orders of magnitude compared to complementary metal–oxide–semiconductor‐based hardware. It also provides better accuracy in pattern recognition tasks than the HP learning algorithm benchmarks.

Addressing the challenge of household loads and the concentrated power consumption of electric vehicles during periods of low electricity prices is critical to mitigate impacts on the utility grid. In this study, we propose a multi-objective particle swarm algorithm-based optimal scheduling method for household microgrids. A household microgrid optimization model is formulated, taking into account time-sharing tariffs and users’ travel patterns with electric vehicles. The model focuses on optimizing daily household electricity costs and minimizing grid-side energy supply variances. Specifically, the mathematical model incorporates the actual input and output power of each distributed energy source within the microgrid as optimization variables. Furthermore, it integrates an analysis of capacity variations for energy storage batteries and electric vehicle batteries. Through arithmetic simulation within the Pareto optimal solution set, the model identifies the optimal solution that effectively mitigates fluctuations in energy input and output on the utility side. Simulation results confirm the effectiveness of this strategy in reducing daily household electricity costs. The proposed optimization approach not only improves the overall quality of electricity consumption but also demonstrates its economic and practical feasibility, highlighting its potential for broader application and impact.