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Abstract Facing sustainability challenges and the demand for green and high-quality food, smart agriculture has become a key solution, and understanding consumer preferences for its products is crucial for sustainable development. By employing a structural equation model and using the sample data of an online survey conducted in China, this study investigated consumers’ intention to purchase smart agricultural products, thereby examining the effects of value co-creation, cue utilization, attitude, and future orientation. According to the results, cue utilization positively affects value co-creation and attitude. In addition, value co-creation and attitude can promote consumers’ purchase intention. Moreover, future orientation positively moderates the effect of attitude on purchase intention. These findings have substantial practical implications for formulating marketing strategies aimed at promoting the consumption of smart agricultural products. By strengthening the effects of cue utilization, value co-creation, and future orientation, marketers can specifically target consumers and facilitate the transition to more sustainable consumption patterns.

Abstract The expression and biological function of junctional adhesion molecule-like protein (JAML) in colorectal cancer (CRC) remain unclear. Paraffin tissue samples from 50 cases of CRC were collected to determine the expression of JAML. JAML was overexpressed or knock-down in CRC cells to evaluated the proliferation, migration and invasion in vitro and in vivo. Western-blot and others were applied to explore the mechanisms. The study showed that JAML was highly expressed within cancer tissues in 50% (25/50) of patients with CRC, and was correlated with higher TNM stage (p

Abstract Background The cardiometabolic index (CMI) is a novel metric for assessing cardiometabolic health and type 2 diabetes mellitus (DM), yet its relationship with insulin resistance (IR) and prediabetes (preDM) is not well-studied. There is also a gap in understanding the nonlinear associations between CMI and these conditions. Our study aimed to elucidate these associations. Methods We included 13,142 adults from the National Health and Nutrition Examination Survey (NHANES) 2007–2020. CMI was calculated by multiplying the triglyceride-to-high density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Using weighted multivariable linear and logistic regression explored the relationships of CMI with glucose metabolism markers, IR, preDM, and DM. Nonlinear associations were assessed using generalized additive models (GAM), smooth curve fittings, and two-piecewise logistic regression. Results Multivariate regression revealed positive correlations between CMI and glucose metabolic biomarkers, including FBG (β = 0.08, 95% CI: 0.06–0.10), HbA1c (β = 0.26, 95% CI: 0.22–0.31), FSI (β = 4.88, 95% CI: 4.23–5.54), and HOMA-IR (β = 1.85, 95% CI: 1.56–2.14). There were also significant correlations between CMI and increased risk of IR (OR = 3.51, 95% CI: 2.94–4.20), preDM (OR = 1.49, 95% CI: 1.29–1.71), and DM (OR = 2.22, 95% CI: 2.00-2.47). Inverse nonlinear L-shaped associations were found between CMI and IR, preDM, and DM, with saturation inflection points at 1.1, 1.45, and 1.6, respectively. Below these thresholds, increments in CMI significantly correlated with heightened risks of IR, preDM, and DM. Conclusions CMI exhibited inverse L-shaped nonlinear relationships with IR, preDM, and DM, suggesting that reducing CMI to a certain level might significantly prevent these conditions.

Abstract Background In the era of immunotherapy, neoadjuvant immunochemotherapy (NAIC) for the treatment of locally advanced esophageal squamous cell carcinoma (ESCC) is used clinically but lacks of high‐level clinical evidence. This study aimed to compare the safety and long‐term efficacy of NAIC followed by minimally invasive esophagectomy (MIE) with those of neoadjuvant chemotherapy (NAC) followed by MIE. Methods A prospective, single‐center, open‐label, randomized phase III clinical trial was conducted at Henan Cancer Hospital, Zhengzhou, China. Patients were randomly assigned to receive either neoadjuvant toripalimab (240 mg) plus paclitaxel (175 mg/m2) + cisplatin (75 mg/m2) (toripalimab group) or paclitaxel + cisplatin alone (chemotherapy group) every 3 weeks for 2 cycles. After surgery, the toripalimab group received toripalimab (240 mg every 3 weeks for up to 6 months). The primary endpoint was event‐free survival (EFS). The pathological complete response (pCR) and overall survival (OS) were key secondary endpoints. Adverse events (AEs) and quality of life were also assessed. Results Between May 15, 2020 and August 13, 2021, 252 ESCC patients ranging from T1N1‐3M0 to T2‐3N0‐3M0 were enrolled for interim analysis, with 127 in the toripalimab group and 125 in the chemotherapy group. The 1‐year EFS rate was 77.9% in the toripalimab group compared to 64.3% in the chemotherapy group (hazard ratio [HR] = 0.62; 95% confidence interval [CI] = 0.39 to 1.00; P = 0.05). The 1‐year OS rates were 94.1% and 83.0% in the toripalimab and chemotherapy groups, respectively (HR = 0.48; 95% CI = 0.24 to 0.97; P = 0.037). The patients in the toripalimab group had a higher pCR rate (18.6% vs. 4.6%; P = 0.001). The rates of postoperative Clavien‐Dindo grade IIIb or higher morbidity were 9.8% in the toripalimab group and 6.8% in the chemotherapy group, with no significant difference observed (P = 0.460). The rates of grade 3 or 4 treatment‐related AEs did not differ between the two groups (12.5% versus 12.4%). Conclusions The interim results of this ongoing trial showed that in resectable ESCC, the addition of perioperative toripalimab to NAC is safe, may improve OS and might change the standard treatment in the future.

Abstract The study aims to evaluate whether rhythm control by catheter ablation is superior to medical therapy for the patients with atrial fibrillation (AF) and heart failure (HF). The literatures were searched by using PubMed, Cochrane Library, Embase, and Web of Science databases up to 12 October 2023. The randomized controlled trials (RCTs) comparing rhythm control using catheter ablation vs. medical therapy in AF patients with HF were pooled. The primary outcomes included all‐cause mortality, HF re‐hospitalization, and stroke, and the secondary outcomes included left ventricular ejection fraction (LVEF), atrial tachyarrythmia recurrence, quality of life (Minnesota Living with Heart Failure Questionnaire score, MLHFQ score), 6 min walking distance (6MWD), the level of N‐terminal B‐type natriuretic peptide precursor (NT‐proBNP), and adverse events. Nine RCTs involving in 2293 patients met the inclusion criteria. Compared with medical therapy, catheter ablation reduced all‐cause mortality [10.07% (121/1201) vs. 15.26% (175/1147), risk ratio (RR):0.60, 95% confidence interval (CI): 0.48–0.74, P

Abstract Background Circular RNAs (circRNAs), produced by reverse splicing, act as important players in human cancers. We aimed to assess the biological functions of circRNA pituitary homeobox 1 (circ‐PITX1) in non‐small‐cell lung cancer (NSCLC). Methods qRT‐PCR was employed to determine RNA expression. Biological behaviors of NSCLC cells were assessed by CCK‐8, colony formation, EdU assay, flow cytometry, wound healing, and transwell assays. Glutamine catabolism was examined via the measurement of glutamine consumption, α‐ketoglutarate levels, as well as ATP levels. Protein levels were detected by western blot assays. Dual‐luciferase reporter assay and RNA immunoprecipitation (RIP) assay were performed to reveal the mechanism responsible for circ‐PITX1 regulating NSCLC cell malignancy. The murine xenograft model was established to investigate circ‐PITX1's effect on tumor formation. Results Circ‐PITX1 was overexpressed in NSCLC tissue samples and cells. Its low expression repressed NSCLC cell proliferation and motility. Moreover, our data revealed its downregulation inhibited glutamine catabolism and tumor formation and promoted cell apoptosis. In addition, circ‐PITX1 bound to miR‐615‐5p, and its inhibitory effect on tumor cellular behaviors could be reversed after decreasing miR‐615‐5p expression. The miRNA targeted E26 transformation specific‐1 (ETS1), whose upregulation abolished miR‐615‐5p overexpression‐induced effects in NSCLC cells. Furthermore, circ‐PITX1 positively modulated ETS1 production through interaction with miR‐615‐5p. Conclusion Circ‐PITX1 facilitated NSCLC progression via modulating miR‐615‐5p/ETS1 pathway.

Abstract As the Internet of Vehicles advances, the demand for timely data acquisition by vehicle users continues to escalate, albeit confronted with the challenge of excessive data retrieval latency. The emergence of edge computing provides technical support for the development of vehicular networks by caching data in advance to reduce data acquisition latency. Therefore, how to effectively cache and query data becomes a key issue in addressing the timeliness of data acquisition in vehicular networks. In this paper, we investigate an efficient query optimization model to minimize data acquisition latency. Firstly, based on the distribution of data query frequencies across different servers, we propose an edge collaborative caching strategy using a tabu search algorithm. This strategy prioritizes high-traffic data by finding two optimal storage nodes for each high-traffic data in descending order of data popularity, ensuring a backup within the collaborative domain for each data segment. This not only reduces data transmission latency between nodes during task execution but also prevents single-point failures. Secondly, we deploy cuckoo filters on edge nodes to enable rapid localization of cached data nodes when users query data, thus reducing data processing latency. Finally, simulation results demonstrate that the proposed query optimization model outperforms other schemes in terms of average data query latency.

Abstract Background Structural variations play a significant role in genetic diseases and evolutionary mechanisms. Extensive research has been conducted over the past decade to detect simple structural variations, leading to the development of well-established detection methods. However, recent studies have highlighted the potentially greater impact of complex structural variations on individuals compared to simple structural variations. Despite this, the field still lacks precise detection methods specifically designed for complex structural variations. Therefore, the development of a highly efficient and accurate detection method is of utmost importance. Result In response to this need, we propose a novel method called FindCSV, which leverages deep learning techniques and consensus sequences to enhance the detection of SVs using long-read sequencing data. Compared to current methods, FindCSV performs better in detecting complex and simple structural variations. Conclusions FindCSV is a new method to detect complex and simple structural variations with reasonable accuracy in real and simulated data. The source code for the program is available at https://github.com/nwpuzhengyan/FindCSV .

A new species, Ulnaria shun-biseriata sp. nov., was found in the Shun River of Hunan Province, southern China, and its morphology was described based on light and scannning electron microscope obervations. Ulnaria shun-biseriata is characterized by its lanceolate valve outline, apiculate valve apices, slightly undulate valve margins, mostly biseriate striae, variable central area, and closed valvocopula. Many abnormal valves of U. shun-biseriata were observed in the samples investigated and the most frequent morphological abnormalities consisted of a lack of symmetry relative to the apical axis caused by a unilateral expansion in the middle part of the valve.

The Gaofen-3 (GF-3) is a Chinese Synthetic Aperture Radar (SAR) satellite primarily designed for monitoring marine dynamic environments. Compared to spaceborne scatterometers, it can monitor sea surface wind fields with higher spatial resolution. Currently, the spectrum analysis-based algorithms are widely used to extract wind direction from SAR images, but they are susceptible to image noise. To address this issue, this study proposes a wind direction inversion method based on iterative linear fitting, which fully utilises wind streak information at different wavenumbers and improves wind direction inversion accuracy by iteratively removing data points with high noise levels. Twelve GF-3 SAR images were used to validate the proposed algorithm. Experimental results indicate that the root mean square error (RMSE) of the retrieved wind direction is 17.10°. Compared to the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis wind, and the mean absolute deviation is 10.93°Compared to the National Data Buoy Center (NDBC) buoy wind. Compared with the conventional local gradient algorithm, the proposed algorithm achieves higher wind direction inversion accuracy. This study provides a technical support for the operational wind field inversion using Gaofen-3 SAR images.

With the rapid development of Mg alloys, deeper understanding to the thermodynamic and diffusional kinetic behavior of intermetallic compounds (IMCs) is important for studying the effect of alloying elements to the microstructure evolution. Specially, a systematic quantitative investigation on the diffusional growth of IMCs is of great necessity. However, the works studying the elemental diffusion behaviors of multiple-element IMCs are rare in magnesium alloy systems. The current work takes the ternary Mg-Al-Zn system as research target, and combines the diffusion couple technique, phase stability diagrams, in-situ observation technique and numerical inverse method to investigate the temperature-dependent kinetic coefficients. The parabolic growth constant (PGC) and interdiffusion coefficients for Mg solid-solution phase and γ-Mg17Al12, β-Mg2Al3, ε-Mg23Al30, MgZn2, Mg2Zn3, τ-Mg32(Zn, Al)49 and ϕ-Mg5Zn2Al2 IMCs in the Mg-Al-Zn alloy system are determined. By comparing the current experimental with calculation results, the rate-controlling factor of the temperature-dependent diffusion growth of ϕ, τ and ε ternary IMCs in the Mg-Al-Zn system is further discussed in detail.

Abstract Background Metabolic syndrome (MetS) is a risk factor for cardiovascular disease (CVD), and CVD is a major challenge for cancer patients. This study aimed to investigate the prevalence and association of MetS and CVD among adult cancer patients. Methods This cross-sectional study included cancer patients aged > 18 years from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. The prevalence of MetS and CVD was calculated using weighted analysis. Multivariable logistic regression was used to assess the association between MetS and CVD. Results The study included 2658 adult cancer patients, of whom 1260 exhibited MetS and 636 had CVD. The weighted prevalence of MetS and CVD in cancer patients was 45.44%, and 19.23%, respectively. Multivariable logistic regression showed a 79% increased risk in higher CVD prevalence in cancer patients with MetS, with the OR (95% CI) of 1.79 (1.31, 2.44). Notably, obesity, elevated blood pressure (BP), high glucose, and low high density lipoprotein cholesterol (HDL-C) in the MetS components were significantly associated with higher CVD prevalence after adjusting for covariates. Moreover, the risk of CVD prevalence in cancer patients increased with more MetS components. Notably, MetS was more strongly linked to CVD in patients aged

Abstract Fiddler crabs, as coastal ecosystem engineers, play a crucial role in enhancing biodiversity and accelerating the flow of material and energy. Here we show how widespread crab burrows modify the carbon sequestration capacity of different habitats across a large climatic gradient. The process of crab burrowing results in the reallocation of sediment organic carbon and humus. Crab burrows can increase more greenhouse gases emissions compared to the sediment matrix (CO2: by 17–30%; CH4: by 49–141%). Straightforward calculations indicate that these increased emissions could offset 35–134% of sediment carbon burial in these two ecosystems. This research highlights the complex interactions between crab burrows, habitat type, and climate which reveal a potential lower carbon sink function of blue carbon ecosystems than previously expected without considering crab burrows.

Abstract Background Pb stress, a toxic abiotic stress, critically affects maize production and food security. Although some progress has been made in understanding the damage caused by Pb stress and plant response strategies, the regulatory mechanisms and resistance genes involved in the response to lead stress in crops are largely unknown. Results In this study, to uncover the response mechanism of maize to Pb stress phenotype, physiological and biochemical indexes, the transcriptome, and the metabolome under different concentrations of Pb stress were combined for comprehensive analysis. As a result, the development of seedlings and antioxidant system were significantly inhibited under Pb stress, especially under relatively high Pb concentrations. Transcriptome analysis revealed 3559 co-differentially expressed genes(co-DEG) under the four Pb concentration treatments (500 mg/L, 1000 mg/L, 2000 mg/L, and 3000 mg/L Pb(NO3)2), which were enriched mainly in the GO terms related to DNA-binding transcription factor activity, response to stress, response to reactive oxygen species, cell death, the plasma membrane and root epidermal cell differentiation. Metabolome analysis revealed 72 and 107 differentially expressed metabolites (DEMs) under T500 and T2000, respectively, and 36 co-DEMs. KEGG analysis of the DEMs and DEGs revealed a common metabolic pathway, namely, flavonoid biosynthesis. An association study between the flavonoid biosynthesis-related DEMs and DEGs revealed 20 genes associated with flavonoid-related metabolites, including 3 for genistin and 17 for calycosin. Conclusion In summary, the study reveals that flavonoid metabolism plays an important role in response to Pb stress in maize, which not only provides genetic resources for the genetic improvement of maize Pb tolerance in the future but also enriches the theoretical basis of the maize Pb stress response.

Abstract MRI offers new opportunities for detailed visualization of the different layers of the esophageal wall, as well as early detection and accurate characterization of esophageal lesions. Staging of esophageal tumors including extramural extent of disease, and status of the adjacent organ can also be performed by MRI with higher accuracy compared to other imaging modalities including CT and esophageal endoscopy. Although MDCT appears to be the primary imaging modality that is indicated for preoperative staging of esophageal cancer to assess tumor resectability, MDCT is considered less accurate in T staging. This review aims to update radiologists about emerging imaging techniques and the imaging features of various esophageal masses, emphasizing the imaging features that differentiate between esophageal masses, demonstrating the critical role of MRI in esophageal masses. Critical relevance statement MRI features may help differentiate mucosal high-grade neoplasia from early invasive squamous cell cancer of the esophagus, also esophageal GISTs from leiomyomas, and esophageal malignant melanoma has typical MR features. Key Points MRI can accurately visualize different layers of the esophagus potentially has a role in T staging. MR may accurately delineate esophageal fistulae, especially small mediastinal fistulae. MRI features of various esophageal masses are helpful in the differentiation. Graphical Abstract

Abstract Skin cutaneous melanoma (SKCM) is a highly malignant form of skin cancer, known for its unfavorable prognosis and elevated mortality rate. RARRES1, a gene responsive to retinoic acid receptors, displays varied functions in various cancer types. However, the specific role and underlying mechanisms of RARRES1 in SKCM are still unclear. GSE15605 was utilized to analyze the expression of RARRES1 in SKCM. Subsequently, the TCGA and GEO databases were employed to investigate the relationships between RARRES1 and clinicopathological parameters, as well as the prognostic implications and diagnostic efficacy of RARRES1 in SKCM. GO, KEGG, and GSEA analyses were conducted to explore the potential functions of RARRES1. Furthermore, the associations between RARRES1 and immune infiltration were examined. Genomic alterations and promoter methylation levels of RARRES1 in SKCM were assessed using cBioPortal, UALCAN, and the GEO database. Finally, RARRES1 expression in SKCM was validated through immunohistochemistry, and its functional role in SKCM progression was elucidated via in vivo and in vitro experiments. We found that RARRES1 was downregulated in SKCM compared with normal tissues, and this low expression was associated with worse clinicopathological features and poor prognosis of SKCM. The diagnostic efficacy of RARRES1, as determined by ROC analysis, was 0.732. Through GO, KEGG, and GSEA enrichment analysis, we identified 30 correlated genes and pathways that were mainly enriched in the tumor immune microenvironment, proliferation, apoptosis, and autophagy. Additionally, RARRES1 expression was found to be positively related to the infiltration of various immune cells in SKCM, particularly macrophages and T helper cells, among others. Analysis of genomic alterations and promoter methylation revealed that shallow deletion and hypermethylation of the RARRES1 promoter could lead to reduced RARRES1 expression. IHC validation confirmed the downregulation of RARRES1 in SKCM. Moreover, overexpression of RARRES1 inhibited the proliferation and migration of A375 cells, promoted apoptosis, and inhibited autophagic flux. In the mouse xenograft model, RARRES1 overexpression also suppressed SKCM tumor growth. Collectively, these findings suggest that RARRES1 may function as a suppressor and could potentially serve as a prognostic biomarker and therapeutic target for SKCM.

Abstract The RE1 silencing transcription factor (REST) is a driver of sonic hedgehog (SHH) medulloblastoma genesis. Our previous studies showed that REST enhances cell proliferation, metastasis and vascular growth and blocks neuronal differentiation to drive progression of SHH medulloblastoma tumors. Here, we demonstrate that REST promotes autophagy, a pathway that is found to be significantly enriched in human medulloblastoma tumors relative to normal cerebella. In SHH medulloblastoma tumor xenografts, REST elevation is strongly correlated with increased expression of the hypoxia-inducible factor 1-alpha (HIF1α)—a positive regulator of autophagy, and with reduced expression of the von Hippel-Lindau (VHL) tumor suppressor protein – a component of an E3 ligase complex that ubiquitinates HIF1α. Human SHH-medulloblastoma tumors with higher REST expression exhibit nuclear localization of HIF1α, in contrast to its cytoplasmic localization in low-REST tumors. In vitro, REST knockdown promotes an increase in VHL levels and a decrease in cytoplasmic HIF1α protein levels, and autophagy flux. In contrast, REST elevation causes a decline in VHL levels, as well as its interaction with HIF1α, resulting in a reduction in HIF1α ubiquitination and an increase in autophagy flux. These data suggest that REST elevation promotes autophagy in SHH medulloblastoma cells by modulating HIF1α ubiquitination and stability in a VHL-dependent manner. Thus, our study is one of the first to connect VHL to REST-dependent control of autophagy in a subset of medulloblastomas.

Abstract Background White-rot fungi are known to naturally produce high quantities of laccase, which exhibit commendable stability and catalytic efficiency. However, their laccase production does not meet the demands for industrial-scale applications. To address this limitation, it is crucial to optimize the conditions for laccase production. However, the regulatory mechanisms underlying different conditions remain unclear. This knowledge gap hinders the cost-effective application of laccases. Results In this study, we utilized transcriptomic and metabolomic data to investigate a promising laccase producer, Cerrena unicolor 87613, cultivated with fructose as the carbon source. Our comprehensive analysis of differentially expressed genes (DEGs) and differentially abundant metabolites (DAMs) aimed to identify changes in cellular processes that could affect laccase production. As a result, we discovered a complex metabolic network primarily involving carbon metabolism and amino acid metabolism, which exhibited contrasting changes between transcription and metabolic patterns. Within this network, we identified five biomarkers, including succinate, serine, methionine, glutamate and reduced glutathione, that played crucial roles in co-determining laccase production levels. Conclusions Our study proposed a complex metabolic network and identified key biomarkers that determine the production level of laccase in the commercially promising Cerrena unicolor 87613. These findings not only shed light on the regulatory mechanisms of carbon sources in laccase production, but also provide a theoretical foundation for enhancing laccase production through strategic reprogramming of metabolic pathways, especially related to the citrate cycle and specific amino acid metabolism.

Abstract Biomaterials with exceptional performance are crucial for addressing the challenges of complex bone regeneration. Compared with traditional three‐dimensional scaffolds, injectable microspheres enable new strategies for the treatment of irregular bone defects. Biodegradable poly (lactic‐co‐glycolic acid) has found widespread applications as microcarriers of drugs, proteins, and other active macromolecules. Applied to the surface of poly (lactic‐co‐glycolic acid) cage‐like structures (PLGA‐CAS), hydroxyapatite (HA) effectively reduces inflammation while enhancing biological effects. In this study, we loaded the surface of PLGA‐CAS with micro‐ and nano‐hydroxyapatite particles, referred to as μHA/PLGA‐CAS and nHA/PLGA‐CAS, respectively. Subsequently, their material characteristics and biological effects were assessed. The incorporation of hydroxyapatite onto PLGA‐CAS resulted in enhanced surface roughness and hydrophilicity, coupled with improved thermal stability and delayed degradation. Furthermore, μHA/PLGA‐CAS induced osteogenic differentiation of osteoblast precursor cells, while nHA/PLGA‐CAS improved endothelial cell adhesion and stimulated angiogenic differentiation in vitro. Collectively, these findings suggest that μHA/PLGA‐CAS and nHA/PLGA‐CAS, each with distinct characteristics, hold significant potential for application as microcarriers in various biomedical contexts.

Abstract Objective This study aimed to explore metabolic reprogramming in diabetic myocardium subjected to ischemia–reperfusion injury (I/RI) and potential mechanisms. Background Increased vulnerability after I/RI in diabetic myocardium is a major cause of the high prevalence of perioperative adverse cardiac events, and the specific alterations in energy metabolism after I/RI in diabetic myocardium and the impact on increased vulnerability are not fully understood. Methods Metabolomic methods were used to explore the differences and characteristics of metabolites in the heart tissues of four groups, and then, single‐cell RNA sequencing (ScRNA‐seq) was used to explore the potential mechanism of metabolic reprogramming. Results It was found that the fatty acid metabolism of db/db mouse I/RI (DMI) showed a significant upward trend, especially the metabolites of ultra‐long and medium‐long‐chain fatty acids; the metabolic flow analysis found that the U‐13C glucose M + 6 was significantly higher in the C57BL mouse sham operation (NM) group than in the db/db mouse sham operation (DM) group, and in the C57BL mouse I/RI (NMI) than in the DMI group. Compared with the NMI group, the intermediate metabolites of glycolysis and tricarboxylic acid (TCA) cycle were significantly reduced in the DMI group; all comparisons were statistically significant (p

ObjectivesThe aim of this study is to assess the risk factors associated with thrombotic events in obstetric antiphospholipid syndrome (OAPS) patients and to develop a predictive model specifically tailored to predict the risk of postpartum thrombosis in OAPS patients without prior thrombotic events. This research seeks to enhance clinician’s awareness regarding the postpartum care and monitoring of OAPS patients.MethodsA retrospective study was conducted at the First Affiliated Hospital of the Fourth Military Medical University including 269 consecutive inpatients diagnosed with antiphospholipid syndrome (APS) from July 1, 2008 to July 31, 2022. All participants met the 2006 Sydney APS classification criteria or the “non-criteria OAPS classification”. Out of 98 candidate clinical and laboratory parameters considered, 40 potential variables were selected for analysis based on expert opinion. The logistic regression mode with the Least Absolute Shrinkage and Selection Operator (LASSO) were used to identify optimal predictive characteristics. All samples were included in the model building and a nomogram was generated based on these characteristics. The differentiation, calibration, and clinical utility of the predictive model were evaluated using the area under the curve (AUC), calibration curve, and decision curve analysis. The model was also validated by a 1000 bootstrap tests.Results126 patients with OAPS were enrolled, and a total of 89 OAPS patients who had never experienced thrombosis were retrospectively analyzed. After 3 years follow-up, 32.58% of the patients (29/89) developed thrombosis. In order to create, LASSO logistic regression identified three optimal variables: the platelet count less than 125×109/L, more than one positive aPLs (antiphospholipid antibody), and the use of low molecular weight heparin (LMWH) or low dose aspirin (LDA) after delivery. A predictive model was conducted using these three predictive indicators for patients with OAPS who experience thrombosis for the first-time. This prediction model has good distinction, good calibration, and fair clinical practicality.ConclusionOur model has good predictive ability in assessing the risk of thrombosis in patients with OAPS without prior thrombotic events. This model is easy to predict, has good discriminability and calibration, and can be utilized as a routine tool for thrombus screening in OAPS patients.

Background: Acne is a chronic inflammatory skin disease. Photodynamic therapy (PDT) is a highly effective and safe drug-device combination treatment, typically using red and blue light. However, direct comparisons of aminolevulinic acid (ALA)-based PDT using these two light sources are lacking. Therefore, we compared the efficacy and adverse effects of ALA-based 450 nm blue laser-mediated PDT (BL-PDT) and 630 ± 10 nm red light-emitting diode-mediated PDT (RL-PDT) in the treatment of moderate-to-severe acne vulgaris, including analyses of different lesion types. Methods: Sixteen patients with moderate-to-severe acne vulgaris were recruited. All patients underwent BL-PDT on the left side of the face and RL-PDT on the right side. Treatments were administered thrice at 2-week intervals, and follow-up continued for 2 weeks after the final treatment. The average rates of improvement in inflammatory and non-inflammatory acne lesions, IGA (Investigator's Global Assessment) scales, and IGA success rates were calculated. In addition, adverse effects during and after each treatment were recorded. Results: At the 2-week follow-up after the final treatment, the average rates of improvement in total acne, inflammatory, and non-inflammatory lesions were 48.0 %, 63.0 %, and 30.0 % in the BL-PDT group and 42.2 %, 58.1 %, and 27.5 % in the RL-PDT group, respectively. The IGA scores for the two groups decreased by 1.8 and 1.7 points, respectively, and the IGA success rate was 53.3 % in both groups. There were no significant differences between the BL-PDT and RL-PDT groups in any measure of effectiveness. However, the BL-PDT group exhibited more severe adverse effects, especially pain and hyperpigmentation. Conclusions: BL-PDT and RL-PDT have similar efficacies in moderate-to-severe acne vulgaris and are particularly effective for inflammatory acne lesions. RL-PDT benefits from milder adverse effects than those of BL-PDT.

Owing to its tyrosinase inhibitory activity, α-arbutin has been added to several skin care products as a skin-lightening agent. However, the protective effect of α-arbutin against ultraviolet A (UVA)-induced photoaging has not been well investigated. The present study was designed to investigate the photoprotective effect and mechanism of α-arbutin against UVA-induced photoaging. In vitro experiments, HaCaT cells were treated with UVA at a dose of 3 J/cm2 to evaluate the anti-photoaging effect of α-arbutin. α-Arbutin was found to exhibit a strong antioxidant effect by increasing glutathione (GSH) level and inhibiting reactive oxygen species (ROS) production. Meanwhile, α-arbutin markedly improved the expression of sirtuin 3 (SIRT3) and peroxisome proliferator-activated receptor γ coactivator 1 α (PGC-1α) proteins, initiating downstream signaling to increase mitochondrial membrane potential and mediate mitochondrial biogenesis, and improve mitochondrial structure significantly. In vivo analysis, the mice with shaved back hair were irradiated with a cumulative UVA dose of 10 J/cm2 and a cumulative ultraviolet B (UVB) dose of 0.63 J/cm2. The animal experiments demonstrated that α-arbutin increased the expression of SIRT3 and PGC-1α proteins in the back skin of mice, thereby reducing UV-induced skin damage. In conclusion, α-arbutin protects HaCaT cells and mice from UVA damage by regulating SIRT3/PGC-1α signaling pathway.

Routinely collected health data (RCD) including electronic health records, disease registries, health administrative data and wearables data are not specifically collected for research purposes. Analysis of these data poses unique methodological challenges that must be addressed when conducting research, particularly as availability and use increase. This scoping review aimed to identify methodological challenges in research using RCD from existing literature (registered protocol: https://doi.org/10.17605/OSF.IO/EBM4D). We searched 6 electronic databases, including medical, health economics, nursing and psychology research databases, between Jan 2015 and Jan 2023, combining multiple “RCD” and “research” search terms (e.g., epidemiologic, informatics, pharmaceutical research). After screening abstracts and full-texts, we doubly extracted methodological themes, categorizing them into different study stages. We screened more than 23,000 records and included 430 papers. Bias and confounding were the most common methodological issues identified, discussed in relation to both study design and data analysis. Data quality, including data accuracy, validation, completeness, timeliness and cleaning, also posed substantial challenges, particularly during data processing stage. Record linkage and conducting analyses using distributed health networks also pose unique methodological challenges. Heterogeneity, incorporating social determinants of health and statistical models that address methodological challenges are also described in the literature. External validity and reporting are important considerations for RCD research. Our review identified several methodological challenges facing researchers using RCD. These issues should be addressed to ensure methodologically sound research. These findings will inform the development of a standardized protocol template and accompanying educational platform aimed at enhancing methodological quality and transparency when conducting research using RCD.

Equitable access to parks, in alignment with resident needs, is crucial for promoting social equity, justice, and sustainable urban development. However, existing methodologies for evaluating park accessibility often overlook the effect of park popularity and resident choices. To address this limitation, this study introduces an improved two-step floating catchment area (2SFCA) method. This enhanced approach incorporates real-time user data to measure park popularity and employs the Huff model to determine the probability of residents selecting a specific park. By integrating these factors, the study offers a more accurate and robust assessment of park accessibility for residents in Jiangnan Main City, a central district in Nanjing’s urban core. The study utilizes the Gini index and Lorenz curve to appraise the demographic equity of park distribution in the study area. In addition, bivariate spatial autocorrelation analysis is employed to analyze the spatial patterns of park supply and demand. The findings indicate a spatial trend characterized by high accessibility in central locations and reduced accessibility in peripheral areas. Additionally, the northern section exhibits greater accessibility compared to the southern part. The calculated Gini index indicates that the top 10% of the population enjoys access to nearly 36% of the parks, highlighting a significant imbalance. In addition, a spatial mismatch is evident, with significant dislocation between parks and residential areas observed in approximately 29% of residential communities. Simulations conducted in the study demonstrate a marginal improvement in park spatial equity when accounting for park popularity and resident choice. These results emphasize the importance of incorporating these factors in park planning and management strategies. The study advocates for park planning that prioritizes equity and a balance between supply and demand. Moreover, it emphasizes the need for tailored strategies that cater to the unique characteristics of different urban areas.

To address the inefficient data processing performance and excessive resource utilization issues that field-programmable gate array (FPGA)-based SM4 implementations faced, an implementation scheme that adopted both iteration and pipeline in order to reduce resource consumption and improve throughput was proposed. A combination of cyclic key extension and 32 bit pipeline encryption and decryption architecture was adopted by the proposed scheme. The cyclic key extension reduced logical resource consumption, while the 32 bit pipeline encryption and decryption improved data throughput. Additionally, an algebraic S-box that combined linear operations to select an optimal matrix from those generated by different irreducible polynomials was employed. Resource usage and computation overhead was further minimized, thus achieving an increased engineering frequency. Experimental results demonstrate a 43% throughput improvement and a 10% reduction in resource usage compared to the current best scheme.

Sperm head morphology is crucial for male factor infertility diagnosis and assessment of male reproductive potential. Several criteria are available to analyze sperm head morphology, but they are limited by poor methodology comparability and population applicability. This study aimed to explore comprehensive and new normal morphometric reference values for spermatozoa heads in fertile Asian males. An automated sperm morphology analysis system captured 23 152 stained spermatozoa from confirmed fertile males. Of these samples, 1856 sperm head images were annotated by three experienced laboratory technicians as “normal”. We employed 14 novel morphometric features to describe sperm head size (head length, head width, length/width ratio, and girth), shape (ellipse intersection over union, girth intersection over union, short-axis symmetry, and long-axis symmetry), area (head, acrosome, postacrosomal areas, and acrosome area ratio), and degrees of acrosome and nuclear uniformity. This straight-forward method for the morphometric analysis of sperm by accurate visual measurements is clinically applicable. The measured parameters present valuable information to establish morphometric reference intervals for normal sperm heads in fertile Asian males. The presented detailed measurement data will be valuable for interlaboratory comparisons and technician training. In vitro fertilization and andrology laboratory technicians can use these parameters to perform objective morphology evaluation when assessing male fertilization potential.

Abstract High concentrations of organic aerosol (OA) occur in Asian countries, leading to great health burdens. Clean air actions have resulted in significant emission reductions of air pollutants in China. However, long-term nation-wide trends in OA and their causes remain unknown. Here, we present both observational and model evidence demonstrating widespread decreases with a greater reduction in primary OA than in secondary OA (SOA) in China during the period of 2013 to 2020. Most of the decline is attributed to reduced residential fuel burning while the interannual variability in SOA may have been driven by meteorological variations. We find contrasting effects of reducing NOx and SO2 on SOA production which may have led to slight overall increases in SOA. Our findings highlight the importance of clean energy replacements in multiple sectors on achieving air-quality targets because of high OA precursor emissions and fluctuating chemical and meteorological conditions.

Abstract The subfamily Polygonoideae encompasses a diverse array of medicinal and horticultural plants that hold significant economic value. However, due to the lack of a robust taxonomy based on phylogenetic relationships, the classification within this family is perplexing, and there is also a scarcity of reports on the chloroplast genomes of many plants falling under this classification. In this study, we conducted a comprehensive analysis by sequencing and characterizing the complete chloroplast genomes of six Polygonoideae plants, namely Pteroxygonum denticulatum, Pleuropterus multiflorus, Pleuropterus ciliinervis, Fallopia aubertii, Fallopia dentatoalata, and Fallopia convolvulus. Our findings revealed that these six plants possess chloroplast genomes with a typical quadripartite structure, averaging 162,931 bp in length. Comparative chloroplast analysis, codon usage analysis, and repetitive sequence analysis demonstrated a high level of conservation within the chloroplast genomes of these plants. Furthermore, phylogenetic analysis unveiled a distinct clade occupied by P. denticulatum, while P. ciliinrvis displayed a closer relationship to the three plants belonging to the Fallopia genus. Selective pressure analysis based on maximum likelihood trees showed that a total of 14 protein-coding genes exhibited positive selection, with psbB and ycf1 having the highest number of positive amino acid sites. Additionally, we identified four molecular markers, namely petN-psbM, psal-ycf4, ycf3-trnS-GGA, and trnL-UAG-ccsA, which exhibit high variability and can be utilized for the identification of these six plants.

Bulked-segregant analysis by deep sequencing (BSA-seq) is a widely used method for mapping QTL (quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2 populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F3 populations offering notable advantages over F2 populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading (DTH) in a 7200-plant rice F3 population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near 41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F3 populations and multi-environment experiments can achieve high power, resolution, and reliability.

Abstract Clastic rock aquifer of the coal seam roof often constitutes the direct water-filling aquifer of the coal seam and its water-richness is closely related to the risk of roof water inrush. Therefore, the evaluation of the water-richness of clastic rock aquifer is the basic work of coal seam roof water disaster prevention. This article took the 4th coal seam in Huafeng mine field as an example. It combined the empirical formula method and generalized regression neural network (GRNN) to calculate the development height of water-conducting fracture zone, determined the vertical spatial range of water-richness evaluation. Depth of the sandstone floor, brittle rock ratio, lithological structure index, fault strength index, and fault intersections and endpoints density were selected as the main controlling factors. A combination weighting method based on the analytic hierarchy process (AHP), rough set theory (RS), and minimum deviation method (MD) was proposed to determine the weight of the main controlling factors. Introduced the theory of unascertained measures and confidence recognition criteria to construct an evaluation model for the water-richness of clastic rock aquifers, the study area was divided into three zones: relatively weak water-richness zones, medium water-richness zones, and relatively strong water-richness zones. By comparing with the water inrush points and the water inflow of workfaces, the evaluation model's water yield zoning was consistent with the actual situation, and the prediction effect was good. This provided a new idea for the evaluation of the water-richness of the clastic rock aquifer on the roof of the mining coal seam.

Abstract Interval-valued q-rung orthopair fuzzy set (IVq-ROFS) is a powerful tool for dealing with uncertainty. In this paper, we first propose a new method for aggregating multiple IVq-ROFSs, which is easier to understand and implement in the multi-attribute group decision making process compared to current aggregation operators. Secondly, this paper introduces a new fuzzy entropy with parameters based on IVq-ROFS, which is highly flexible due to its adjustable parameters. Based on this, the IVq-ROFS-based attribute weight calculation method is proposed to obtain the objective weights of the attributes, which is more reasonable and objective than the existing methods. Then, for the dimensional differences between the three compromise scores in the original Combined Compromise Solution (CoCoSo) method, the enhanced compromise scores are proposed. These scores are obtained by normalizing the three dependent compromise scores, ensuring that they fall within the same range. Finally, a novel CoCoSo mothed on IVq-ROFS using the proposed fuzzy entropy and enhanced compromise scores is presented. The proposed method is highly adaptable and scalable, not limited to IVq-ROFS. The excellent performance and robustness of the proposed method are verified in sepsis diagnosis applications.

Abstract Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes. Accordingly, through DLSF, we identified two subtypes of the osteoporosis population in Chinese individuals with corresponding molecular phenotypes, i.e., clinical intervention relevant subtypes (CISs), in which bone mineral density benefits response to calcium supplements in 2-year follow-up samples. Many snpGenes associated with these molecular phenotypes reveal diverse candidate biological mechanisms underlying osteoporosis, with xQTL preferences of osteoporosis and its subtypes indicating an omnigenic effect on different biological domains. Finally, these two subtypes were found to have different relevance to prior fracture and different fracture risk according to 4-year follow-up data. Thus, in clinical application, M3S could help us further develop improved diagnostic and treatment strategies for osteoporosis and identify a new composite index for fracture prediction, which were remarkably validated in an independent cohort (166 participants).

Abstract Neurotransmitter-initiated signaling pathway were reported to play an important role in regulating the malignant phenotype of tumor cells. Cancer cells could exhibit a “neural addiction” property and build up local nerve networks to achieve an enhanced neurotransmitter-initiated signaling through nerve growth factor-mediated axonogenesis. Targeting the dysregulated nervous systems might represent a novel strategy for cancer treatment. However, whether intrahepatic cholangiocarcinoma (ICC) could build its own nerve networks and the role of neurotransmitters in the progression ICC remains largely unknown. Immunofluorescence staining and Enzyme-linked immunosorbent assay suggested that ICC cells and the infiltrated nerves could generate a tumor microenvironment rich in acetylcholine that promotes ICC metastasis by inducing epithelial-mesenchymal transition (EMT). Acetylcholine promoted ICC metastasis through interacting with its receptor, alpha 5 nicotine acetylcholine receptor subunits (CHRNA5). Furthermore, acetylcholine/CHRNA5 axis activated GSK3β/β-catenin signaling pathway partially through the influx of Ca2+-mediated activation of Ca/calmodulin-dependent protein kinases (CAMKII). In addition, acetylcholine signaling activation also expanded nerve infiltration through increasing the expression of Brain-Derived Neurotrophic Factor (BDNF), which formed a feedforward acetylcholine-BDNF axis to promote ICC progression. KN93, a small-molecule inhibitor of CAMKII, significantly inhibited the migration and enhanced the sensitivity to gemcitabine of ICC cells. Above all, Acetylcholine/CHRNA5 axis increased the expression of β-catenin to promote the metastasis and resistance to gemcitabine of ICC via CAMKII/GSK3β signaling, and the CAMKII inhibitor KN93 may be an effective therapeutic strategy for combating ICC metastasis.

Pancreatic cancer, one of the most aggressive malignancies, has no effective treatment due to the lack of targets and drugs related to tumour metastasis. SIRT6 can promote the migration of pancreatic cancer and could be a potential target for antimetastasis of pancreatic cancer. However, highly selective and potency SIRT6 inhibitor that can be used in vivo is yet to be discovered. Here, we developed a novel SIRT6 allosteric inhibitor, compound 11e, with maximal inhibitory potency and an IC50 value of 0.98 ± 0.13 μmol/L. Moreover, compound 11e exhibited significant selectivity against other histone deacetylases (HADC1‒11 and SIRT1‒3) at concentrations up to 100 μmol/L. The allosteric site and the molecular mechanism of inhibition were extensively elucidated by cocrystal complex structure and dynamic structural analyses. Importantly, we confirmed the antimetastatic function of such inhibitors in four pancreatic cancer cell lines as well as in two mouse models of pancreatic cancer liver metastasis. To our knowledge, this is the first study to reveal the in vivo effects of SIRT6 inhibitors on liver metastatic pancreatic cancer. It not only provides a promising lead compound for subsequent inhibitor development targeting SIRT6 but also provides a potential approach to address the challenge of metastasis in pancreatic cancer.

Abstract Evidence for the involvement of N6-Methyladenosine (m6A) modification in the etiology and progression of liver fibrosis has emerged and holds promise as a therapeutic target. Insulin-like growth factor 2 (IGF2) mRNA-binding protein 2 (IGF2BP2) is a newly identified m6A-binding protein that functions to enhance mRNA stability and translation. However, its role as an m6A-binding protein in liver fibrosis remains elusive. Here, we observed that IGF2BP2 is highly expressed in liver fibrosis and activated hepatic stellate cells (HSCs), and inhibition of IGF2BP2 protects against HSCs activation and liver fibrogenesis. Mechanistically, as an m6A-binding protein, IGF2BP2 regulates the expression of Aldolase A (ALDOA), a key target in the glycolytic metabolic pathway, which in turn regulates HSCs activation. Furthermore, we observed that active glycolytic metabolism in activated HSCs generates large amounts of lactate as a substrate for histone lactylation. Importantly, histone lactylation transforms the activation phenotype of HSCs. In conclusion, our findings reveal the essential role of IGF2BP2 in liver fibrosis by regulating glycolytic metabolism and highlight the potential of targeting IGF2BP2 as a therapeutic for liver fibrosis.

The objective of this research was to examine the antibiotic resistance and microbiological traits of Klebsiella pneumoniae isolates that were responsible for liver abscesses in Qingdao, China. Between April and September 2022, isolates were taken from 120 patients at three tertiary hospitals. Rapid detection of capsule serotypes (K1, K2) and virulence genes (rmpA, aerobactin) was achieved by using microfluidic-based techniques. Testing for antimicrobial susceptibility was done with the VITEK 2 Compact system. The findings showed that there was a high frequency of extremely virulent K. pneumoniae strains, which are often linked to bacteremia and higher death rates. These strains belonged to the K1 and K2 serotypes and were primarily carrying the aerobactin and rmpA genes. The majority of isolates were antibiotic-sensitive, but the emergence of resistant strains emphasizes the necessity of continuing surveillance. The efficiency of microfluidic platforms for the quick and precise characterization of K. pneumoniae is demonstrated in this work, enabling prompt clinical interventions.

Abstract Background Temporomandibular joint osteoarthritis (TMJOA) is a degenerative cartilage disease. 17β‐estradiol (E2) aggravates the pathological process of TMJOA; however, the mechanisms of its action have not been elucidated. Thus, we investigate the influence of E2 on the cellular biological behaviors of synoviocytes and the molecular mechanisms. Methods Primary fibroblast‐like synoviocytes (FLSs) isolated from rats were treated with TNF‐α to establish cell model, and phenotypes were evaluated using cell counting kit‐8, EdU, Tanswell, enzyme‐linked immunosorbent assay, and quantitative real‐time PCR (qPCR). The underlying mechanism of E2, FTO‐mediated NLRC5 m6A methylation, was assessed using microarray, methylated RNA immunoprecipitation, qPCR, and western blot. Moreover, TMJOA‐like rat model was established by intra‐articular injection of monosodium iodoacetate (MIA), and bone morphology and pathology were assessed using micro‐CT and H&E staining. Results The results illustrated that E2 facilitated the proliferation, migration, invasion, and inflammation of TNF‐α‐treated FLSs. FTO expression was downregulated in TMJOA and was reduced by E2 in FLSs. Knockdown of FTO promoted m6A methylation of NLRC5 and enhanced NLRC5 stability by IGF2BP1 recognition. Moreover, E2 promoted TMJ pathology and condyle remodeling, and increased bone mineral density and trabecular bone volume fraction, which was rescued by NLRC5 knockdown. Conclusion E2 promoted the progression of TMJOA.

Abstract Objective To evaluate the effectiveness of monitoring and managing process quality control indicators in the prevention of constipation among hospitalized patients with acute coronary syndrome (ACS). Methods A total of 512 hospitalized patients diagnosed with ACS between January and June 2022 were screened for inclusion in the study. Ultimately, 456 eligible participants were enrolled and divided into two groups based on the chronological order of admission: the control group and the observation group. Upon admission, both groups of patients received routine constipation prevention measures in the department. However, the observation group was subjected to targeted process quality control management, which included monitoring and managing five indicators related to constipation prevention: correctness of bowel movement recording; usage rate of laxatives; execution rate of physical interventions; implementation rate of constipation prevention education; completion rate of dietary structure and habit assessments. Data were analyzed using SPSS, with t tests and χ2 tests for group comparisons. Results In comparison to the control group, the observation group demonstrated significant advantages in terms of constipation incidence, completion rates of the five process quality control indicators, occurrence rates of adverse cardiac events during defecation, and PHQ‐9 scores before discharge. These disparities demonstrated statistical significance with a p value

This study reported a case of MELAS syndrome presenting as the initial imaging characteristics of Fahr’s syndrome with “near” sudden unexpected death in epilepsy (SUDEP) and lateralized periodic discharges (LPD). The patient, a young boy, experienced loss of consciousness 2 days prior, which was followed by two limb and facial convulsions. He was later found in cardiac arrest during hospitalization, but regained consciousness gradually after receiving cardiopulmonary resuscitation and tracheal intubation. The patient exhibited short stature, intellectual disability, poor sports abilities, and academic performance since childhood, but had no family history. Emergency head computed tomography (CT) revealed high density calcification in bilateral caudate nucleus, lentiform nucleus, thalamus, and dentate nucleus with evidence of an acute process. The patient was transferred to the neurology department where he continued to recover consciousness, though he experienced dysarthria, left limb hemiplegia, and hemiparesthesia. Changes in head magnetic resonance imaging (MRI) findings were noted at admission, 1 month later, and 6 months later. LPD were observed in his video electroencephalogram. The CT urography indicated a narrow left ureteropelvic junction with left hydronephrosis, which was suggestive of ureteropelvic junction obstruction. Ultimately, a diagnosis of near-SUDEP was suspected in this patient, indicating a rare case of MELAS syndrome with near-SUDEP and LPD. The gene tests results revealed the presence of the mitochondrial DNA A3243G mutation, leading to the final diagnosis of MELAS syndrome. This case expands the clinical disease spectrum of the MELAS syndrome.

Summary: This paper presents the design of an ultra-wide-angle multispectral narrow-band absorber for reconstructing infrared spectra. The absorber offers several advantages, including polarization sensitivity, robustness against structural wear, wide azimuthal angle coverage, high narrow-band absorption, and adjustable working wavelength. To accomplish infrared spectrum reconstruction, an absorber is employed as a spectral sampling channel, eliminating the influence of slits or complex optical splitting elements in spectral imaging technology. Additionally, we propose using a truncation regularization algorithm based on the design matrix singular value ratio, namely IReg, which can enable high-precision spectral reconstruction under largely disturbed environments. The results demonstrate that, even when the number of absorption spectrum curve is reduced to a range of 1/2 to 1/3, high-precision spectral reconstruction is achievable for both flat and high-energy steep mid- and long-infrared spectral targets, while effectively accomplishing data dimension reduction.

Four optimization models were proposed to reduce the impact of pollutants from vans on themselves and surrounding vehicles. The adsorption of pollutants on the body of the van in rainy conditions and the diffusion of pollutants into the external environment were numerically investigated using the Discrete Phase Model (DPM) for vans having different wheel brow structures. The pressure distribution on the surface of the van, the surrounding flow field, and the raindrop distributions of various external positions on and around the van were analyzed and compared. The results indicated that the van with externally covered wheel brow model was most effective in inhibiting the diffusion of rainwater pollutants from the van under rainy conditions. Compared with the original model, the reduction in the polluted area was 11.19%, the reduction in the influence of the visual field on the rear vehicle was 25.4%, and the reduction in the diffusion of pollutants on the bodies of the side vehicle was 20.7%.

The E3 enzyme in the UPS pathway is a crucial factor for inhibiting substrate specificity. In Solanaceae, the U-box E3 ubiquitin ligase has a complex relationship with plant growth and development, and plays a pivotal role in responding to various biotic and abiotic stresses. The analysis of the U-box gene family in Solanaceae and its expression profile under different stresses holds significant implications. A total of 116 tobacco NtU-boxs and 56 eggplant SmU-boxs were identified based on their respective genome sequences. Phylogenetic analysis of U-box genes in tobacco, eggplant, tomato, Arabidopsis, pepper, and potato revealed five distinct subgroups (I-V). Gene structure and protein motifs analysis found a high degree of conservation in both exon/intron organization and protein motifs among tobacco and eggplant U-box genes especially the members within the same subfamily. A total of 15 pairs of segmental duplication and 1 gene pair of tandem duplication were identified in tobacco based on the analysis of gene duplication events, while 10 pairs of segmental duplication in eggplant. It is speculated that segmental duplication events are the primary driver for the expansion of the U-box gene family in both tobacco and eggplant. The promoters of NtU-box and SmU-box genes contained cis-regulatory elements associated with cellular development, phytohormones, environment stress, and photoresponsive elements. Transcriptomic data analysis shows that the expression levels of the tobacco and eggplant U-box genes in different tissues and various abiotic stress conditions. Using cultivar Hongda of tobacco and cultivar Yanzhi of eggplant as materials, qRT-PCR analysis has revealed that 15 selected NtU-box genes and 8 SmU-box may play important roles in response to pathogen Ras invasion both in tobacco and eggplant.

IntroductionCistanche salsa (C.A.Mey.) G. Beck is a perennial holoparasitic herb recognized for its medicinal properties, particularly in kidney-tonifying and laxative treatments. Despite its therapeutic potential, little is known about the endophyte communities inhabiting C. salsa and its host plants, and how these microorganisms may impact the production and accumulation of metabolites in C. salsa.MethodsWe conducted a dual analysis focusing on metabolomics of wild C. salsa and microbiome characterization of both C. salsa and its host plant, Kalidium foliatum (Pall.) Moq. The metabolomics analysis revealed variations in metabolite composition across different parts of C. salsa. Additionally, the microbiome analysis involved studying endophytic bacteria and fungi, comparing their community structures between parasitic C. salsa and its host plant.ResultsSignificant variations in metabolite composition were observed through metabolomic profiling, which identified 93 secondary metabolites and 398 primary metabolites across various parts of C. salsa. Emphasis was placed on differences in metabolite composition within the flowers. Microbiome analysis revealed differential community compositions of endophytic bacteria between the parasitic and host plants, whereas differences in endophytic fungi were less pronounced. Certain endophytes, such as Bacteroidota, Proteobacteria, Ascomycota, and Basidiomycota, were associated with the production of specific secondary metabolites in C. salsa, including the plant-specific compound salsaside.DiscussionOur findings highlight the intricate relationship between C. salsa and its endophytic microbiota, suggesting a potential role of these microorganisms in modulating the biosynthesis of bioactive compounds. The differential preferences of endophytic bacteria and fungi across various microenvironments within the parasitic plant system underscore the complexity of these interactions. Further elucidation of these dynamics could enhance our understanding of C. salsa’s medicinal properties and its ecological adaptations as a holoparasitic herb.

ObjectiveTo explore the relationship between serum calcium levels and the prognosis of severe acute osteomyelitis, and to assess the effectiveness of calcium levels in prognostic evaluation.MethodsRelevant patient records of individuals diagnosed with severe acute osteomyelitis were obtained for this retrospective study from the Medical Information Mart for Intensive Care (MIMIC-IV). The study aimed to assess the impact of different indicators on prognosis by utilizing COX regression analysis. To enhance prognostic prediction for critically ill patients, a nomogram was developed. The discriminatory capacity of the nomogram was evaluated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve, in addition to the calibration curve.ResultThe study analyzed a total of 1,133 cases of severe acute osteomyelitis, divided into the survivor group (1,025 cases) and the non-survivor group (108 cases). Significant differences were observed between the two groups in terms of age, hypertension, sepsis, renal injury, and various laboratory indicators, including WBC, PLT, Ca2+, CRP, hemoglobin, albumin, and creatinine (P0.05). To predict the survival time, a nomogram was developed using the aforementioned indicators and achieved an AUC of 0.841. The accuracy of the nomogram was further confirmed by the ROC curve and calibration curve.ConclusionAccording to the findings, this study establishes that a reduction in serum calcium levels serves as a distinct and standalone predictor of mortality among individuals diagnosed with severe acute osteomyelitis during their stay in the Intensive Care Unit (ICU) within a span of two years.

Abstract To determine the dietary structure and its associated factors of tuberculosis (TB) patients in the community. This cross-sectional study analysed the dietary intake of 300 TB patients in two impoverished counties in China. Food intake was collected by using food frequency and two consecutive 24-h dietary review (24hdr) methods. The dietary composition and dietary structure of TB patients were compared with China’s 2022 Dietary Reference Intake (DRIs) and the average reference value of dietary composition (ARC) in China in 2013. Binary logistic regression models were used to explore the factors associated with inadequate intake of animal food, insufficient protein and fat energy supply in patients with TB. The daily intake of various foods in TB patients was measured and the results were as follows: staple foods—median 372.12 g (interquartile range [IQR] 315.87 g); vegetables—median 200.00 g (IQR 205.55 g); fruits—median 20.22 g (IQR 36.82 g); animal foods—median 100.82 g (IQR 180.74 g); dairy products—median 0.00 g (IQR 0.00 g); nuts—median 17.10 g (IQR 29.75 g). The average daily intakes of vegetables, fruits, animal food, dairy products, soy and nuts were lower than those recommended by the DRIs (P

Abstract Background The appropriateness of hypertension thresholds for triggering action to prevent cardiovascular and renal complications among non-White populations in the UK is subject to question. Our objective was to establish ethnicity-specific systolic blood pressure (SBP) cutoffs for ethnic minority populations and assess the efficacy of these ethnicity-specific cutoffs in predicting adverse outcomes. Methods We analyzed data from UK Biobank, which included 444,418 participants from White, South Asian, Black Caribbean, and Black African populations with no history of cardiorenal complications. We fitted Poisson regression models with continuous SBP and ethnic groups, using Whites as the referent category, for the composite outcome of atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease. We determined ethnicity-specific thresholds equivalent to the risks observed in Whites at SBP levels of 120, 130, and 140 mm Hg. We adjusted models for clinical characteristics, sociodemographic factors, and behavioral factors. The performance of ethnicity-specific thresholds for predicting adverse outcomes and associated population-attributable fraction (PAF) was assessed in ethnic minority groups. Results After a median follow-up of 12.5 years (interquartile range, 11.7–13.2), 32,662 (7.4%) participants had incident composite outcomes. At any given SBP, the predicted incidence rate of the composite outcome was the highest for South Asians, followed by White, Black Caribbean, and Black African. For an equivalent risk of outcomes observed in the White population at an SBP level of 140 mm Hg, the SBP threshold was lower for South Asians (123 mm Hg) and higher for Black Caribbean (156 mm Hg) and Black African (165 mm Hg). Furthermore, hypertension defined by ethnicity-specific thresholds was a stronger predictor and resulted in a larger PAF for composite outcomes in South Asians (21.5% [95% CI, 2.4,36.9] vs. 11.3% [95% CI, 2.6,19.1]) and Black Africans (7.1% [95% CI, 0.2,14.0] vs. 5.7 [95% CI, -16.2,23.5]) compared to hypertension defined by guideline-recommended thresholds. Conclusions Guideline-recommended blood pressure thresholds may overestimate risks for the Black population and underestimate risks for South Asians. Using ethnicity-specific SBP thresholds may improve risk estimation and optimize hypertension management toward the goal of eliminating ethnic disparities in cardiorenal complications.

The atmospheric low-level vortex is an important weather system that causes rainstorm and flood in southern China. The vortex induced rainstorm is sudden and local, and its occurence time, intensity and falling area have always been difficult for meteorological forecasting. In order to improve the accuracy of rainstorm prediction in Zhejiang Province and improve the localization application of the prediction model, based on daily precipitation data of Zhejiang Province from 1979 to 2020 and reanalysis dataset from the National Centers for Environmental Prediction Climate Forecast System, climatic characteristics of the heavy rain in Zhejiang Province induced by low-level vortex is studied, the vortex induced rainstorm in Zhejiang mostly occurs in the rainy season and has obvious interannual variation characteristics. Then, the 850 hPa vertical velocity, water vapor flux divergence, velocity divergence, low-level jet, shear line and 700 hPa vertical velocity are used as ingredient factors, and the potential falling area forecast for heavy rain induced by vortex is constructed by using logistic regression algorithm. Finally, the forecast products of the European Medium-Range Weather Prediction Center are used to forecast the rainstorm falling area based on this model, and the actual data of the same period are used for systematic test and weather process test. Results show that the overall performance of the model is good, and the rainstorm prediction ability of 24 h and 12 h ahead is improved, which can increase from 12% accuracy and 20% to around 14% and 40% respectively, and the omission rate drops from more than 75% to around 60%, but there is a certain degree of empty report. The forecast model of Zhejiang Province based on logistic regression method has a good indicator for the prediction of such rainstorm areas, and is of great significance for meteorological disaster prevention and mitigation.

Machine learning (ML) algorithms can accurately extract quantitative patterns from datasets without requiring prior knowledge, playing an increasingly crucial role in tasks such as information extraction from remotely sensed data. This study employs several ML algorithms, including Back Propagation Network (BPN), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), to develop global oceanic chlorophyll-a (Chl-a) concentration inversion models for MODIS/Aqua (MODISA). The models utilize the SeaWiFS Bio-optical Archive and Storage System (SeaBASS) dataset, which contains in situ Chl-a concentration measurements paired with MODISA remote sensing reflectance ( $R_{\mathrm {rs}}$ ) for various water color bands from 2002 to 2017. This study includes the following processing steps. First, the SeaBASS dataset is randomly divided into training dataset and testing dataset. Second the Chl-a concentration inversion models are developed using the training dataset. Third, the testing dataset is utilized to evaluate the developed models. Finally, the inversion experiment is conducted using MODISA data. Experimental results indicate that all ML algorithms achieve higher inversion accuracy compared to the traditional ocean color index (OCI) algorithm. Particularly, the SVR model demonstrates the best performance. Additionally, to address the challenge of multidimensional parameter optimization in ML algorithms, this study introduces the Differential Evolution (DE) algorithm and develops a DE-based SVM model (DE-SVM). Compared to the standard SVM model, the DE-SVM model significantly reduces the mean deviation, mean absolute deviation, and root mean square error of the inverted chlorophyll-a concentration, while increasing the coefficient of determination (R2) from 0.87 to 0.926. These results indicate that the DE-SVM model further improves the inversion accuracy of Chl-a concentration, and holds substantial potential in satellite remote sensing inversion of Chl-a concentration.

Focusing on the challenges of vehicle detection in foggy weather, especially the algorithm of low accuracy caused by small and incomplete targets in adverse weather conditions, a foggy weather vehicle detection algorithm based on improved lightweight YOLOv8 was proposed. Firstly, the dataset was processed through a combination of data transformation, Dehaze Formers and dark channel preprocessing. Secondly, in the main body of YOLOv8, the C2f component was replaced with the dynamic convolution C2f- DCN, enhancing its adaptability to geometric changes in the image. To further improve the detection performance of the classifier, an improved S5attention module based on S2-MLP was introduced. This module utilizes contextual information to capture long-range dependencies and assign weights to different channels based on their relevance to the task at hand. By considering non-local features, the S5attention module helps the model better capture important spatial relationships within the image. Additionally, the feature extraction module was updated to FasterNext, improving the differential convolution’s feature extraction capabilities. The Involution module was also introduced to reduce FLOPs during feature channel fusion and reduce the model’s parameter count. Experimental results show that on the RESIDE foggy weather dataset, the improved algorithm has an mAP50 increase of 4.1% compared with the original algorithm, and the model’s parameter quantity is only 9.06m, with a computational cost reduced from 28.7G to 28.1G. The research model in this article will provide technical support for detecting vehicle targets in foggy weather, ensuring fast and accurate operation.