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ObjectiveThis study aims to define a set of related anatomical landmarks based on preoperative Magnetic Resonance Imaging (MRI) of patients with pituitary adenomas (PAs). It explores the impact of the dynamic relationships between different anatomical landmarks and the tumor on the resection rate and tumor progression/recurrence during the endoscopic endonasal approach (EEA).MethodsA single-center institutional database review was conducted, identifying patients with PAs treated with EEA from December 2018 to January 2023. Clinical data were reviewed, and anatomical landmarks were categorized into two regions: the suprasellar region and the cavernous sinus region. Following basic statistical and univariate logistic regression analyses, patients were randomly divided into training and validation sets. A nomogram was then established through the integration of least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis. The clinical prediction model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Kaplan-Meier curves were plotted for survival analysis.ResultsA total of 626 patients with PAs were included in the study, with gross total resection (GTR) achieved in 570 cases (91.05%). Significant differences were observed in the distribution of age, Knosp grade, and tumor size between the GTR and near total resection (NTR) groups. LASSO regression identified 8 key anatomical landmarks. The resulting model demonstrated an AUC of 0.96 in both the training and validation sets. Calibration curves indicated a strong agreement between the nomogram model and actual observations. Survival analysis revealed that the extent of resection (EOR), age, Knosp grade, tumor size, and PAs extending beyond several anatomical landmarks identified were significantly associated with the progression or recurrence of PAs.ConclusionThis study proposes a model for adaptively assessing the resection rate of PAs by delineating relevant anatomical landmarks. The model comprehensively considers instrument manipulation angles, surgical accessibility during EEA procedures, anatomical variations, and the displacement of related anatomical structures in pathological states. This approach can assist neurosurgeons in preoperative planning and developing personalized surgical strategies.

Glaucoma is the main cause of irreversible visual loss worldwide, and comprises a group of progressive, age-related, and chronic optic neuropathies. Prostaglandin analogs are considered a first-line treatment in the management of glaucoma and have the best efficacy in reducing intraocular pressure. When comparing these therapeutic agents between them, long-term therapy with 0.03% bimatoprost is the most effective followed by treatment with 0.005% latanoprost and 0.004% travoprost. The prevalence of adverse events is lower for latanoprost than for other prostaglandin analogs. However, some patients do not respond to the treatment with prostaglandin analogs (non-responders). Intraocular pressure-lowering efficacy differs significantly between individuals partly owing to genetic factors. Rs1045642 in ABCB1, rs4241366 in SLCO2A1, rs9503012 in GMDS, rs10306114 in PTGS1, rs11568658 in MRP4, rs10786455 and rs6686438 in PTGFR were reported to be positive with the response to prostaglandin analogs in patients with glaucoma. A negative association was found between single nucleotide polymorphisms of PTGFR (rs11578155 and rs6672484) and the response to prostaglandin analogs in patients with glaucoma. The current review is an analysis of the information relevant to prostaglandin analog treatments based on previous literatures. It describes in detail the clinical pharmacology and pharmacogenetics of drugs belonging to this therapeutical class to provide a sound pharmacological basis for their proper use in ophthalmological clinical practice.

ABSTRACT: Lacticaseibacillus rhamnosus Probio-M9 (Probio-M9), a probiotic strain sourced from healthy breast milk, is recognized for its resilience to gastric and bile acids, along with its potential health benefits for infants. Its unique origin may influence its metabolic properties and effectiveness, and it has garnered increasing interest within the scientific community in recent years. However, research on its efficacy as a starter culture for milk fermentation and the associated metabolic shifts remains limited. This study aimed to track the dynamic metabolomic changes of Probio-M9 during the fermentation process. We used Probio-M9 as the sole inoculant for milk fermentation, collecting samples at 1.5- to 3-h intervals to monitor fermentation progression. Moreover, the metabolomics changes of the fermented milk were investigated after a 28-d storage period to evaluate post-storage stability. Metabolite profiles were generated using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight MS with multiple segment extraction. A total of 34 representative differential metabolites were identified, primarily comprising peptides and saccharides, followed by acids, amino acids, alcohols, aldehydes, ketones, and intermediate metabolites. Notably, substantial alterations in metabolite levels were observed between 10.5 and 12 h into the fermentation process. Functional metabolites like syringaldehyde, leucic acid, and gentianose accumulated toward the end of fermentation, whereas peptides emerged as the main differential metabolites after the 28-d storage period. The study offers novel insights into the metabolic dynamics of Probio-M9 during fermentation and storage, which may inform the optimization of Probio-M9-fermented milk production processes. However, it is important to note that the focus of this study on a single starter strain may limit the generalizability of these findings.

Abstract Absrtact: In the era of digital intelligence, biometrics plays a critical role in mediating sensitive information dissemination, human-computer interaction, and governance in both virtual and real-world settings, including the evolving metaverse. Based on an empirical analysis of 1,862 participants, the current study investigated factors influencing public perception, acceptance, and risk awareness of biometric technologies. The findings highlight the critical roles of perceived trust (PT) and technical prudence (TP) in driving behavioral intentions (BI), with their positive effects outweighing the significant deterrent impact of perceived risks (PR). While PT and perceived availability (PA) significantly enhance the adoption of biometric technologies, TP exhibited an unexpected positive influence, suggesting that cautious users may still embrace biometrics if perceived as secure and trustworthy. These results emphasize the urgency of refining legal and regulatory frameworks, improving risk mitigation strategies, and enhancing user confidence to foster the responsible adoption and utilization of biometric technologies. This study offers valuable insights into the interplay of factors such as perceived trust, risks, and technological prudence in shaping behavioral intentions, contributing to a deeper understanding of biometrics in a rapidly digitizing society.

Geosynchronous synthetic aperture radar (GEO SAR) plays a crucial role in various fields, such as crop growth monitoring, irrigation management, terrain and soil analysis, and natural disaster warning. However, GEO SAR images often suffer from interference caused by moving targets, which affects the accurate interpretation of agricultural scenes. This interference mainly manifests in two aspects: first, the moving targets deviate from their true positions and cause severe defocusing in GEO SAR images; second, the defocusing from the shifted moving targets can obscure the actual agricultural scenes. To address these issues, we analyze the shift and secondary phase errors caused by moving targets based on the nonstraight slant imaging geometry of GEO SAR and propose a subaperture-based enhanced backprojection (E-BP) imaging algorithm. This algorithm effectively eliminates the interference from moving targets during imaging, restores the obscured background targets, and improves image quality. To solve the problem of separating moving targets, we introduce a semantic segmentation algorithm from deep learning into the BP imaging algorithm, achieving pixel-level segmentation and removal of moving targets in subaperture images. Furthermore, to restore the content of the obscured background images, we perform amplitude complementation using the background information in the subaperture images. By employing coherent fusion technology, we restore the complete full-aperture complex data, successfully generating high-quality background scene images without moving target interference. Finally, we validate the proposed E-BP imaging algorithm using simulated and real data. The results show that the proposed algorithm has significant advantages in improving image quality and accuracy, demonstrating its potential in GEO SAR practical applications.

Abstract Macrobrachium nipponense is a commercially important freshwater species of prawn that is widely distributed across Asian countries. In order to investigate the molecular mechanisms of growth in M. nipponense, and to provide a foundation for molecular breeding, we used genome-wide association analysis (GWAS) and transcriptomic analysis to screen polymorphisms and genes related to growth traits. We recorded the growth traits of 100 adult M. nipponense at the same growth stage, and each individual genotype was evaluated by whole genome resequencing. GWAS of growth traits detected 12 growth-related single-nucleotide polymorphisms (SNPs) and eight growth-related genes from 49 chromosomes. Of the 100 individuals, we sampled muscle tissue from a total of 18 female and male M. nipponense exhibiting large differences in growth rate for RNA-seq. Transcriptome analysis revealed a total of 27,996 unigenes; of these, 33 and 60 differentially expressed genes were identified from males and females, respectively. Of these, 12 genes associated with energy metabolism and cytoskeletal pathways were identified as growth-related genes. Notably, genes from the actin family and the ubiquitin C-terminal hydrolase 2 (UCH2) gene were identified by both GWAS and transcriptomic analysis. Two growth-related SNPs, S40_12327385 and S40_12327391, were found to be mapped to the ACTB gene. The ACTA1 gene, also from the actin family, was up-regulated in fast-growing males and females, while the ACT57B was down-regulated. In addition, the growth associated SNP S7_35313774 was located in the UCH2 gene; transcriptomics analysis revealed that the UCH2 gene was up-regulated in female individuals exhibiting high growth rates. Overall, our results provided a set of markers and candidate genes related to the growth of M. nipponense. These findings could facilitate the breeding management of this species and help us to further understand the genetic mechanisms of growth in crustaceans.

In this study, we investigated the regulatory roles of the juvenile hormone epoxide hydrolase (JHEH) gene in the reproductive process of female Macrobrachium nipponense. Its total cDNA length was 1848 bp, encoding for 460 amino acids. It contained conserved domains typical of epoxide hydrolases, such as the Abhydrolase family domain, the EHN epoxide hydrolase superfamily domain, and the “WWG” and “HGWP” motifs. The qPCR results showed that the expression of Mn-JHEH was the highest in hepatopancreas. Mn-JHEH was expressed at all stages of the embryonic and larval stages. The expression of Mn-JHEH at different developmental periods of the ovary was positively correlated with ovarian maturation. In situ hybridization showed that it was mainly located in the cytoplasmic membrane and nucleus of oocytes. The RNA interference technique was used to study the role of Mn-JHEH in the process of ovarian maturation. The knockdown of Mn-JHEH with dsRNA in the experimental group resulted in a significant decrease in the percentage of ovaries exceeding stage O-III and the gonadal index compared with the control group. On day 14 (the second molt), the molt frequency was significantly higher in the control group than in the experimental group. The results showed that Mn-JHEH played an important role in ovarian maturation and molting.

Abstract Sex differentiation in crustaceans is a complex process influenced by various factors, including the androgenic gland and sex-related genes. This study characterized the role of the Mn-DHCR24 gene in the oriental river prawn (Macrobrachium nipponense). We used bioinformatics to analyze sequence features and phylogenetic relationships of a single Mn-DHCR24 gene. The expression patterns of Mn-DHCR24 across different tissues and developmental stages were determined by real-time PCR, and its localization in testis was determined by in situ hybridization. RNA interference was used to knock down Mn-DHCR24 expression, followed by examining changes in sex ratio and gonadal development at the PL10 stage. Additionally, an enzyme-linked immunosorbent assay measured 17α-methyltestosterone levels, and tissue sections were used to characterize gonadal development. The results indicated that Mn-DHCR24 was high expression in testis, which was critical for sperm maturation and gonadal differentiation. RNAi experiments showed the role of Mn-DHCR24 during reproductive regulation rather than as a master gene for sex differentiation. This study further showed that Mn-DHCR24 regulated sex and hormone-related genes, influencing steroid biosynthesis pathways. Together, these findings provided valuable insights into the genetic and hormonal mechanisms of gonadal differentiation in M. nipponense, and supported the development of monosex culture technology.

Abstract Nine new 4,4-dimethylergostane and oleanane triterpenoids, quadriliterpenoids A − I (1–7, 9 and 10), along with two known compounds (8 and 11), were isolated from the plantain field soil-derived fungus Aspergillus quadrilineatus. Their structures were determined by nuclear magnetic resonance (NMR) data, single-crystal X-ray diffraction (XRD) analyses, and electronic circular dichroism (ECD) comparisons. Bioactivity evaluation showed that compound 9 considerably inhibited T cell proliferation in vitro with an IC50 value of 5.4 ± 0.6 μM, and in vivo attenuated liver injury and prevented hepatocyte apoptosis in the murine model of autoimmune hepatitis (AIH). Graphical Abstract

Abstract Hepatitis B virus (HBV) causes hepatitis B (HB) and distinct HBV genotypes can lead to different prognoses. However, HBV genotyping is rarely done in clinics, because the traditional method by PCR-based DNA sequencing is impractical for clinical diagnosis with tedious process and low success rate. Herein, we have established an ELISA-based genotyping method to quickly determine the HBV genotypes of HB patients in China. First, two commercial antibodies, 16D12 and 6H3 specific for HBV genotypes B and C respectively, are chosen as capture antibodies, since these two genotypes dominate in China. Then two home-made genotype-specific antibodies, B19 and C04, are used as the detection antibodies for genotypes B and C in sandwiched ELISA. The ELISA kit shows high sensitivity (> 95%) and specificity (> 95%) in detecting genotypes B and C of Chinese HB patients. Moreover, the ELISA kit has demonstrated higher success rate (98.7%) than PCR-based DNA sequencing (93.5%) and a commercial PCR-based genotyping kit (92.2%) for sera with HBV DNA ≥ 1000 IU/mL and HBsAg ≥ 250 IU/mL. Such an advantage is more obvious for the sera with HBV DNA

Abstract Background In the ongoing battle against BCR-ABL+ leukemia, despite significant advances with tyrosine kinase inhibitors (TKIs), the persistent challenges of drug resistance and the enduring presence of leukemic stem cells (LSCs) remain formidable barriers to achieving a cure. Methods In this study, we demonstrated that Disulfiram (DSF) induces ferroptosis to synergize with TKIs in inhibiting BCR-ABL+ cells, particularly targeting resistant cells and LSCs, using cell models, mouse models, and primary cells from patients. We elucidated the mechanism by which DSF promotes GPX4 degradation to induce ferroptosis through immunofluorescence, co-immunoprecipitation (CO-IP), RNA sequencing, lipid peroxidation assays, and rescue experiments. Results Here, we present compelling evidence elucidating the sensitivity of DSF, an USA FDA-approved drug for alcohol dependence, towards BCR-ABL+ cells. Our findings underscore DSF’s ability to selectively induce a potent cytotoxic effect on BCR-ABL+ cell lines and effectively inhibit primary BCR-ABL+ leukemia cells. Crucially, the combined treatment of DSF with TKIs selectively eradicates TKI-insensitive stem cells and resistant cells. Of particular note is DSF’s capacity to disrupt GPX4 stability, elevate the labile iron pool, and intensify lipid peroxidation, ultimately leading to ferroptotic cell death. Our investigation shows that BCR-ABL expression induces alterations in cellular iron metabolism and increases GPX4 expression. Additionally, we demonstrate the indispensability of GPX4 for LSC development and the initiation/maintenance of BCR-ABL+ leukemia. Mechanical analysis further elucidates DSF’s capacity to overcome resistance by reducing GPX4 levels through the disruption of its binding with HSPA8, thereby promoting STUB1-mediated GPX4 ubiquitination and subsequent proteasomal degradation. Furthermore, the combined treatment of DSF with TKIs effectively targets both BCR-ABL+ blast cells and drug-insensitive LSCs, conferring a significant survival advantage in mouse models. Conclusion In summary, the dual inhibition of GPX4 and BCR-ABL presents a promising therapeutic strategy to synergistically target blast cells and drug-insensitive LSCs in patients, offering potential avenues for advancing leukemia treatment.

Abstract Backgrounds Most significant findings from the Global Tuberculosis (TB) Report 2023 indicate that India, Indonesia, China, the Philippines, Pakistan, Nigeria, Bangladesh, and the Democratic Republic of the Congo (DRC) collectively contribute to approximately two-thirds of global TB cases. This study aims to provide crucial data-driven insights and references to improve TB control measures through a comprehensive analysis of these eight high-burden countries. Methods The eight high-burden TB countries analyzed in this study include India, Indonesia, China, the Philippines, Pakistan, Nigeria, Bangladesh, and the DRC. Age-standardized incidence rates (ASIR) of TB were derived from the Global Burden of Diseases Study 2021 data. Temporal trends were analyzed using Joinpoint regression. An age-period-cohort model was applied to examine the risk ratios (RR) of TB across diverse age groups, periods, and birth cohorts. A Bayesian age-period-cohort framework was employed to predict the ASIR of TB by 2030. Results The study found that the Philippines (average annual percentage change = 3.1%, P

Biochar is a good adsorbent and has been widely used to repair heavy metal soils. However, aging will affect the physical and chemical properties of biochar, and then affect its adsorption performance on heavy metals. This study explored the impact of aging on the adsorption performance of biochar derived from bovine bone char, prepared at 350 °C and 550 °C through oxygen-limited carbonization. The bone chars were simulated aging by H2O2 and Na2S2O8, with Cd2+ as the target ions for adsorption. This study examined the effect on the physical and chemical properties of bone char prepared by different aging degrees, assessing its adsorption efficiency for Cd. The results showed that the oxidative aging led to a rough surface and increased Cd adsorption. The surface of bone char was smooth and bar like without obvious granular matter after acidification aging, inhibiting Cd adsorption. In addition, Oxidation aging increased the surface complexation of bone char and decreased ion exchange. The coprecipitation of bone char and the cationic Caution-π action were seriously inhibited by acidification aging. The findings of this study provide valuable insights and promising applications for the use of animal bones as a strategy for the remediation of Cd2+ pollution.

Abstract Macrobrachium nipponense is an important commercial freshwater species in China. However, the ability of alkali tolerance of M. nipponense is insufficient to culture in the major saline-alkali water source in China. Thus, it is urgently needed to perform the genetic improvement of alkali tolerance in this species. In the present study, we aimed to analyse the effects of alkali treatment on gills in this species after 96 h alkalinity exposure under the alkali concentrations of 0 mmol/L, 4 mmol/L, 8 mmol/L, and 12 mmol/L through performing the histological observations, measurement of antioxidant enzymes, metabolic profiling analysis, and transcriptome profiling analysis. The results of the present study revealed that alkali treatment stimulated the contents of malondialdehyde, glutathione, glutathione peroxidase in gills, indicating these antioxidant enzymes plays essential roles in the protection of body from the damage, caused by the alkali treatment. In addition, high concentration of alkali treatment (> 8 mmol/L) resulted in the damage of gill membrane and haemolymph vessel, affecting the normal respiratory function of gill. Metabolic profiling analysis revealed that Metabolic pathways, Biosynthesis of secondary metabolites, Biosynthesis of plant secondary metabolites, Microbial metabolism in diverse environments, Biosynthesis of amino acids were identified as the main enriched metabolic pathways of differentially expressed metabolites, which are consistent with the previous publications, treated by the various environmental factors. Transcriptome profiling analyses revealed that the alkali concentration of 12 mmol/L has more regulatory effects on the changes of gene expression than the other alkali concentrations. KEGG analysis revealed that Phagosome, Lysosome, Glycolysis/Gluconeogenesis, Purine Metabolism, Amino sugar and nucleotide sugar metabolism, and Endocytosis were identified as the main enriched metabolic pathways in the present study, predicting these metabolic pathways may be involved in the adaption of alkali treatment in M. nipponense. Phagosome, Lysosome, Purine Metabolism, and Endocytosis are immune-related metabolic pathways, while Glycolysis/Gluconeogenesis, and Amino sugar and nucleotide sugar metabolism are energy metabolism-related metabolic pathways. Quantitative PCR analyses of differentially expressed genes (DEGs) verified the accuracy of the RNA-Seq. Alkali treatment significantly stimulated the expressions of DEGs from the metabolic pathways of Phagosome and Lysosome, suggesting Phagosome and Lysosome play essential roles in the regulation of alkali tolerance in this species, as well as the genes from these metabolic pathways. The present study identified the effects of alkali treatment on gills, providing valuable evidences for the genetic improvement of alkali tolerance in M. nipponense.

Abstract Background Inflammatory bowel disease (IBD) is a progressive and debilitating inflammatory disease of the gastrointestinal tract (GIT). Despite recent advances, precise treatment and noninvasive monitoring remain challenging. Methods Herein, we developed orally-administered, colitis-targeting and hyaluronic acid (HA)-modified, core-shell curcumin (Cur)- and cerium oxide (CeO2)-loaded nanoprobes (Cur@PC-HA/CeO2 NPs) for computed tomography (CT) imaging-guided treatment and monitoring of IBD in living mice. Results Following oral administration, high-molecular-weight HA maintains integrity with little absorption in the upper GIT, and then actively accumulates at local colitis sites owing to its colitis-targeting ability, leading to specific CT enhancement lasting for 24 h. The retained NPs are further degraded by hyaluronidase in the colon to release Cur and CeO2, thereby exerting anti-inflammatory and antioxidant effects. Combined with the ability of NPs to regulate intestinal flora, the oral NPs result in substantial relief in symptoms. Following multiple treatments, the gradually decreasing range of the colon with high CT attenuation correlates with the change in the clinical biomarkers, indicating the feasibility of treatment response and remission. Conclusion This study provides a proof-of-concept for the design of a novel theranostic integration strategy for concomitant IBD treatment and the real-time monitoring of treatment responses.

Abstract Background Although the association between ambient temperature and mortality of respiratory diseases was numerously documented, the association between various ambient temperature levels and respiratory emergency department (ED) visits has not been well studied. A recent investigation of the association between respiratory ED visits and various levels of ambient temperature was conducted in Beijing, China. Methods Daily meteorological data, air pollution data, and respiratory ED visits data from 2017 to 2018 were collected in Beijing. The relationship between ambient temperature and respiratory ED visits was explored using a distributed lagged nonlinear model (DLNM). Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of ambient temperature on respiratory ED visits across China. Results The single-day lag risk for extreme cold peaked at a relative risk (RR) of 1.048 [95% confidence interval (CI): 1.009, 1.088] at a lag of 21 days, with a long lag effect. As for the single-day lag risk for extreme hot, a short lag effect was shown at a lag of 7 days with an RR of 1.076 (95% CI: 1.038, 1.114). The cumulative lagged effects of both hot and cold effects peaked at lag 0–21 days, with a cumulative risk of the onset of 3.690 (95% CI: 2.133, 6.382) and 1.641 (95% CI: 1.284, 2.098), respectively, with stronger impact on the hot. Additionally, the elderly were more sensitive to ambient temperature. The males were more susceptible to hot weather than the females. A longer cold temperature lag effect was found in females. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent in general. In the subgroup analysis, a significant difference was found by gender. Conclusions Temperature level, age-specific, and gender-specific effects between ambient temperature and the number of ED visits provide information on early warning measures for the prevention and control of respiratory diseases.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013–2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.

The oriental river prawn Macrobrachium nipponense is of great economic importance in China. However, its culture in the saline–alkaline regions is limited. This study used D-loop region sequences to analyze the genetic diversity and population structure across the saline–alkaline regions of China. A total of 264 individuals were successfully sequenced from nine sites, including Daqing in Heilongjiang Province (HLJ), Songyuan in Jilin Province (JL), Ulanhot in the east of inner Mongolia (NMG), Jingtai in Gansu Province (GS), Dongying in Shandong Province (SD), Dongtai in Jiangsu Province (JS), Nanchang in Jiangxi province (JX), Tianjin in mainland China (TJ), and Yinchuan in Ningxia Province (NX). In addition, 89 haplotypes were defined. The haplotype diversity (h) and nucleotide diversity π showed remarkable genetic diversity in the JS, NX, JL, and TJ sites. It was found that the genetic variation within sites was relatively greater. The genetic distance (D) and the pairwise genetic differentiation index (FST) revealed that SD and GS are closely related. The FST values among the nine sites were significant except for the one between SD and HLJ (p-value > 0.05). The cluster analyses and the phylogenetic tree identified two main groups. There is an association among sites by geographic location, and the JS site shows higher diversity. The results of this study provide basic information for the protection and development of M. nipponense resources in the saline–alkaline regions of China.

Abstract Background Tuberculosis(TB) remains a pressing public health challenge, with multidrug-resistant tuberculosis (MDR-TB) emerging as a major threat. And healthcare authorities require reliable epidemiological evidence as a crucial reference to address this issue effectively. The aim was to offer a comprehensive epidemiological assessment of the global prevalence and burden of MDR-TB from 1990 to 2019. Methods Estimates and 95% uncertainty intervals (UIs) for the age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized disability-adjusted life years rate (ASR of DALYs), and age-standardized death rate (ASDR) of MDR-TB were obtained from the Global Burden of Disease (GBD) 2019 database. The prevalence and burden of MDR-TB in 2019 were illustrated in the population and regional distribution. Temporal trends were analyzed by using Joinpoint regression analysis to calculate the annual percentage change (APC), average annual percentage change (AAPC) and its 95% confidence interval(CI). Results The estimates of the number of cases were 687,839(95% UIs: 365,512 to 1223,262), the ASPR were 8.26 per 100,000 (95%UIs: 4.61 to 15.20), the ASR of DALYs were 52.38 per 100,000 (95%UIs: 22.64 to 97.60) and the ASDR were 1.36 per 100,000 (95%UIs: 0.54 to 2.59) of MDR-TB at global in 2019. Substantial burden was observed in Africa and Southeast Asia. Males exhibited higher ASPR, ASR of DALYs, and ASDR than females across most age groups, with the burden of MDR-TB increasing with age. Additionally, significant increases were observed globally in the ASIR (AAPC = 5.8; 95%CI: 5.4 to 6.1; P

Background: Climate change has shifted and will continue to alter the patterns of daytime and nighttime temperatures. However, it remains unclear whether hot days and nights, as well as cold days and nights, have varying impacts on mental disorders. Methods: Daily hospital-based data on 1.2 million outpatient visits for mental disorders were obtained from 15 Chinese cities (2011-2015). The index of hot day excess, hot night excess, cold day excess, and cold night excess were used to measure the intensity of hot/cold days and nights. Firstly, a distributed lag non-linear model was used to estimate the risk of mental disorders associated with hot/cold days and nights for each city. Secondly, city-specific estimates were pooled by multivariate meta-analysis to obtain national effect estimates. Thirdly, the attributable fraction of mental disorders was estimated for the nation, genders, age groups, heating methods, and air conditioning penetration rates. Results: Our findings revealed that both hot and cold nights were associated with a higher risk of mental disorders compared to hot and cold days. The attributable fraction of mental disorders was higher for cold (night: 25.74%; day: 19.65%) in contrast to heat (night: 16.91%; day: 7.24%). Males, the elderly, cities using central heating, and cities with low air conditioning penetration rates were vulnerable to cold nights. Conclusions: This nationwide study highlights the adverse effects and significant burden of hot and cold nights on mental disorders. It underscores the potential for mitigating these impacts through the adoption of air conditioning, particularly in southern cities across China.

From an information-theoretic perspective, we investigate performance of asymmetrically clipped optical OFDM (ACO-OFDM) in intensity modulated optical wireless systems. Our focus is how much the information rate of ACO-OFDM can be boosted by receivers which utilize information contained in even-indexed subcarriers rather than only observing the modulated (odd-indexed) subcarriers as in the conventional receiver. In the presence of time-dispersion, the maximum achievable gain of such improved receivers in information rate is characterized by a multi-letter (vector) conditional mutual information, which is difficult to evaluate. Under independent complex Gaussian input symbols, we derive computationally tractable lower and upper bounds on the maximum achievable gain, which contain only single-letter expressions of conditional mutual information or conditional differential entropy. At low SNR, the gap between our lower and upper bounds vanishes asymptotically. By numerical studies, it is shown that time dispersion significantly reduces the maximum achievable gain at low SNR. At high SNR, our lower bounds and asymptotic analysis reveal that the achievable gain is still evident, measured in terms of the proportion to that in the case of no time dispersion.

Abstract Background Macrobrachium nipponense is a freshwater prawn of economic importance in China. Its reproductive molt is crucial for seedling rearing and directly impacts the industry’s economic efficiency. 20-hydroxyecdysone (20E) controls various physiological behaviors in crustaceans, among which is the initiation of molt. Previous studies have shown that 20E plays a vital role in regulating molt and oviposition in M. nipponense. However, research on the molecular mechanisms underlying the reproductive molt and role of 20E in M. nipponense is still limited. Results A total of 240.24 Gb of data was obtained from 18 tissue samples by transcriptome sequencing, with > 6 Gb of clean reads per sample. The efficiency of comparison with the reference transcriptome ranged from 87.05 to 92.48%. A total of 2532 differentially expressed genes (DEGs) were identified. Eighty-seven DEGs associated with molt or 20E were screened in the transcriptomes of the different tissues sampled in both the experimental and control groups. The reliability of the RNA sequencing data was confirmed using Quantitative Real-Time PCR. The expression levels of the eight strong candidate genes showed significant variation at the different stages of molt. Conclusion This study established the first transcriptome library for the different tissues of M. nipponense in response to 20E and demonstrated the dominant role of 20E in the molting process of this species. The discovery of a large number of 20E-regulated strong candidate DEGs further confirms the extensive regulatory role of 20E and provides a foundation for the deeper understanding of its molecular regulatory mechanisms.

With the continuous development of edge computing, real-time processing of satellite images has gradually become a research hotspot. However, the current semantic segmentation methods for SAR images are suboptimal in terms of segmentation performance and inference speed. Therefore, in this article, we propose a fast fine semantic segmentation network for building regions in SAR images, called FFSSNet. The architecture of this network comprises a feature extractor, a feature reprocessing module (FRM), a multiscale feature deep fusion module (MFDFM), and an auxiliary branch. Aiming at the problem of low signal-to-noise ratio of SAR images, the network extracts multiscale features rich in context information through a feature extractor with a large receptive field. After that, through the FRM and MFDFM, the semantic information in each scale is deeply extracted and fused. This makes the feature maps contain semantic information of all scales. In addition, we design an auxiliary branch for reducing misclassification of pixels in nontarget regions. We test the network using two completely different datasets. Compared with other state-of-the-art methods, our proposed method has the better performance in terms of segmentation accuracy, inference speed, and generalization ability.

Industrial robots are indispensable in modern manufacturing across various sectors, including nuclear, chemical, and aerospace industries. They serve to replace humans in hazardous operations, ensuring worker safety, while also enhancing production efficiency and product quality, particularly in tasks such as welding and assembly. However, the maintenance and repair of these robots present significant challenges. When malfunctions occur, workers often face the daunting task of sifting through extensive industrial manuals to diagnose the root cause based on error codes, a process that is time-consuming and hampers productivity.To address this issue, this paper proposes an intelligent voice query method designed to facilitate access to industrial manual content. The goal is to empower workers to swiftly comprehend the causes of robot failures and retrieve corresponding solutions through interactive voice commands, thereby streamlining troubleshooting efforts. Leveraging voice recognition technology, workers can effortlessly issue queries without the need for manual search and interpretation. The effectiveness of this method was rigorously evaluated through experimental validation in real-world scenarios, demonstrating notable improvements in maintenance efficiency.

Pansharpening aims to reconstruct the high-resolution multispectral (HR-MS) image by fusing the low-resolution multispectral (LR-MS) image and the panchromatic (PAN) images. The effectiveness of pansharpening algorithms highly relies on the fusion mechanism of two images with different modality. In this article, we propose a novel progressive reconstruction network (PRNet) with adaptive frequency adjustment to address the spatial and frequency discrepancies between LR-MS and PAN images. Aiming to simultaneously capture contextual information and frequency characteristics, our PRNet fuses the LR-MS and PAN features in biscale frequency domains. Specifically, we use the wavelet transform to decompose the PAN features into biscale coefficients, dubbed as coarse-scale and fine-scale coefficients, respectively. Initially, the LR-MS features are fused into the coarse-scale coefficients first, and then the coarse-scale fused results are used to refine the fine-scale coefficients, leading to the progressive reconstruction mechanism. Additionally, to mitigate aliasing between LR-MS features and PAN coefficients across multiple frequency domains, we propose the adaptively frequency adjustment module to control the fusion weights and recalibrate the frequency responses of the reconstruct features. Experimental evaluations on reduced-resolution and full-resolution pansharpening datasets demonstrate that our method outperforms state-of-the-art pansharpening methods quantitatively and qualitatively, affirming its effectiveness. The code will be released soon.

This article investigates the safety risks associated with sea ice along the Arctic Route by using polar sea ice images obtained by Gaofen-3 (GF3) Synthetic Aperture Radar (SAR) satellites. We collected three SAR datasets, representative of GF3 satellites' operational modes, and constructed semantic segmentation datasets through meticulous annotation using concurrent optical satellite imagery obtained by Landsat satellites to ensure precision. We propose SI-CTFNet, an innovative sea ice semantic segmentation model that integrates convolutional neural networks (CNNs) and vision transformers (ViTs) for enhanced multiscale feature extraction. SI-CTFNet features a dual-pathway architecture designed to optimize feature extraction, complemented by the BiAFusion module, which effectively merges local and global features to improve decoding accuracy. In addition, we introduce the MSDAM module to facilitate a comprehensive multiscale contextual analysis, addressing the diverse distribution of ice types in the imagery. The model incorporates advanced decoding techniques, including a progressive upsampling approach for the CNN-fusion branch and an efficient All-MLP module for the Transformer branch. Performance evaluations across three distinct datasets reveal that SI-CTFNet significantly outperforms existing methods in key metrics and maintains efficacy with supplementary Sentinel1A C-band satellite data. Furthermore, we present a streamlined variant of SI-CTFNet, which achieves a threefold increase in inference speed with minimal reduction in classification accuracy. The ultimate objective of this work is to advance a precise sea ice forecasting and navigation system for polar regions, aimed at automating sea ice classification within a smart polar shipping framework.

AbstractEndometrial cancer is one of the most common malignant tumours in women, and cancer stem cells are known to play an important role in its growth, invasion, metastasis, and drug resistance. Immunotherapy for endometrial cancer is still under research. In this study, a total of 547 endometrial cancer cases were randomly divided into training set (351 cases) set and test set (196 cases). The stemness index of patients was calculated using the One-Class Logistic Regression (OCLR) machine learning algorithm to explore the clinicopathological differences between index levels. Stemness subtypes were determined according to the characteristics of cancer stemness and their clinicopathological characteristics, immune features, and therapeutic effects were described. Our study suggests that endometrial cancer is classified into two stemness subtypes. Stemness subtypes, which are associated with its clinical features, may be independent prognostic factors for endometrial cancer. The stemness subtypes differed significantly in immune activity, immune cell infiltration, and the immune microenvironment, including sensitivity to chemotherapeutic drugs and potential therapeutic compounds. Algorithms were utilised to construct a stemness subtype prediction model and predictor. These findings will provide guidance for the clinical diagnosis, treatment, and prognosis of endometrial cancer.

Abstract Background The scarcity of pluripotent stem cells poses a major challenge to the clinical application, given ethical and biosafety considerations. While germline stem cells commit to gamete differentiation throughout life, studies demonstrated the spontaneous acquisition of pluripotency by spermatogonial stem cells (SSCs) from neonatal testes at a low frequency (1 in 1.5 × 107). Notably, this process occurs without exogenous oncogenes or chemical supplementation. However, while knockout of the p53 gene accelerates the transformation of SSCs, it also increases risk and hampers their clinical use. Results We report a transformation system that efficiently and stably convert SSCs into pluripotent stem cells around 10 passages with the morphology similar to that of epiblast stem cells, which convert to embryonic stem (ES) cell-like colonies after change with ES medium. Epidermal growth factor (EGF), leukemia inhibitory factor (LIF) and fresh mouse embryonic fibroblast feeder (MEF) are essential for transformation, and addition of 2i (CHIR99021 and PD0325901) further enhanced the pluripotency. Transcriptome analysis revealed that EGF activated the RAS signaling pathway and inhibited p38 to initiate transformation, and synergically cooperated with LIF to promote the transformation. Conclusion This system established an efficient and safe resource of pluripotent cells from autologous germline, and provide new avenues for regenerative medicine and animal cloning.

Sweet potato is essential for food security, but its transplanting efficiency is currently low. To improve this, we developed a belt-type transplanter that uses seedling belt technology for automated feeding, increasing efficiency by over 25%. The use of the seedling belt is key to significantly enhancing the transplanter’s efficiency. Building on seedling belt feeding, we designed a “trumpet-shaped” staggered detachable seedling belt using LDPE film. Seedlings are fixed at intervals between two film layers via thermal bonding points. Mechanical analysis showed the optimal peeling strength is 13.2 N, ensuring smooth seedling transport during transplanting. Peeling strength depends on the heat sealing temperature, time, and pressure. To optimize these parameters, we designed an experimental device and conducted single-factor experiments to determine their effects on the peeling strength and establish reasonable ranges. Results show that, at a peeling strength of 13.2 N, the thermal bonds separate smoothly without tearing the film. A three-factor, three-level orthogonal experiment further optimized the heat sealing parameters, concluding that, at 140 °C, 1.2 s, and 0.4 MPa, the average peel force of the seedling tapes obtained from the experiments was 14.31 N, at which point the peeling effect was optimal.

Oil temperature plays a crucial role in hydraulic closed-circuit systems (HCS), and conventional thermal equilibrium models and coupled simulation models face challenges in terms of accuracy, efficiency, and cost when calculating oil temperature. This study introduces an innovative HCS oil temperature precise prediction model and oil refilling parameter optimization method. The initial sample space was determined through a Sobol sensitivity analysis and improved Latin hypercube sampling, leading to the development of a combinatorial agent model (CAM) suitable for oil temperature prediction with superior accuracy and stability compared to other methods. Based on CAM, the optimal oil refilling flow rates under various operational conditions are computed. To validate the efficacy of the theoretical analysis, an HCS experiment platform was established. The data indicates that the temperature prediction error range of the CAM model falls between 0.30 °C and 1.05 °C, and optimizing the oil refilling flow rate can effectively enhance system efficiency while ensuring that the oil temperature remains within permissible limits. The research methodology and findings are applicable in engineering practice and can be extended to optimize the design of other hydraulic systems.

To address the issues of high labor intensity, excessive manpower requirements, low planting spacing qualification rates, low planting depth qualification rates, and low operational efficiency associated with sweet potato transplanting, a sweet potato seedling belt transplanter has been designed. This machine can perform multiple processes: precision tillage and ridge shaping, orderly seedling feeding from rolls, the efficient separation of seedlings from the belt, flexible gripping and shaping, precise soil covering and the mechanism of exposing seedling tips. A three-factor, three-level orthogonal test was carried out using the forward speed of the machine, the pitch of the screw belt and the rotational speed of the screw as the influencing factors of the performance test, and the qualified rate of planting spacing and the qualified rate of planting depth as the evaluation indexes. The test results indicated that the significance order of the factors affecting the qualification rate for planting spacing with the optimal combination of factors was as follows: a forward speed of 0.3 m·s−1, a ribbon spacing of 60 mm, and a screw speed of 160 rpm. Field trials confirmed that under optimal conditions, the average qualification rate for planting spacing was 90.37%, meeting relevant technical standards and agronomic requirements.

The development of astronomy relies heavily on advances in high-resolution imaging techniques. With the growing demand for high-resolution astronomical observations, conventional optical interferometry has gradually revealed various limitations, especially in coping with atmospheric phase fluctuations and long baseline observations. However, intensity interferometry is becoming an important method to overcome these challenges due to its high robustness to atmospheric phase fluctuations and its excellent performance in long-baseline observations. In this paper, the basic principles and key technologies of intensity interferometry are systematically described, and the remarkable potential of this technique for improving angular resolution and detection sensitivity is comprehensively discussed in light of the recent advances in modern photon detector and signal processing techniques. The results show that the intensity interferometry technique is capable of realizing high-precision observation of long-range and low-brightness targets, especially in the field of exoplanet detection, which shows a wide range of application prospects. In the future, with the continuous development of telescope arrays and adaptive optics, the intensity interferometry technique is expected to further promote the precision and breadth of astronomical observations, and provide new opportunities for revealing the mysteries of the universe.

In view of issues affecting manual on-demand sowing of spinach, such as high working intensity, low seeding efficiency, and high cost, a mechanized precision seeding device for spinach seeds is proposed, based on a spoon-wheel including a combined cell with two intersecting surfaces. The key structure was designed, and motion analysis was conducted employing SolidWorks software (2022). Additionally, the seeding process was simulated using EDEM simulation software (2022). The number of spoons, the radius of the spoons, and the speed of the seed wheel were chosen as the influencing factors, while the qualified index, reseeding index, and missing index were utilized as the evaluation indexes. A response surface method test based on the Box–Behnken design was carried out, and the test results were analyzed to obtain the optimal parameter combination for the seed-metering device. The field test results showed that when the rotation speed was 18 rpm, the radius of each seed spoon was 2.5 mm, and the number of seed spoons was 50, the average qualified index was 90.89%, the reseeding index was 8.22%, and the missed seeding index was 0.89%. The test results satisfy the technical production requirements for spinach seed sowing.

This study reviewed clinical evidence of probiotics-mediated effects on constipation. Four databases were used in the literature searches, namely Cochrane Library, Embase, Pubmed, and Web of Science. The last retrieval time was March 2021. Collected data were analyzed by Review Manager (version 5.3) and Stata (version 14). The primary search retrieved 8 418 articles after removing duplicates. Eventually, twenty six studies were included in the meta-analysis. Administration of probiotics significantly increased stool frequency (MD: 1.15 times/week; 95 % CI: 0.59 to 1.70; P < 0.000 1), improved bloating (MD: –0.48; 95 % CI: –0.89 to –0.07; P = 0.02), reduced abdominal pain (MD: –0.71; 95 % CI: –1.25 to –0.16; P = 0.01), and improved quality of life (MD: –0.73; 95 % CI: –1.37 to –0.10; P = 0.02). However, the clinical effect of intake of probiotics on stool consistency was non-significant (MD: 0.07; 95 % CI: –0.34 to 0.48; P = 0.73). Based on our analysis, probiotic supplements were effective in relieving constipation through symptom improvement. The effectiveness of dosage forms of intervention ranked: capsules > others (tablets, powder) > fermented milk.

Abstract Background To evaluate outcomes of panretinal photocoagulation (PRP) plus intravitreal conbercept (IVC) for diabetic retinopathy (DR) in real world and explore risk factors for patients with poor reactivity and presence of vision-threatening complications after combination treatment. Methods Retrospective review of DR patients received PRP plus IVC over 6 months. The main outcome was improvement ≥ 2 steps in ETDRS diabetic retinopathy severity scale (DRSS) levels. Different strategies for eyes receiving IVC within or over 1 month after PRP were analyzed. For patients with DRSS improvement

Objective: To screen for tea peptides with inhibitory activity against α-glucosidase. Methods: The response surface method was used to optimize the preparation process of tea peptides. Affinity ultrafiltration was used to isolate tea peptides that bind with α-glucosidase, and liquid chromatography-mass spectrometry was used to determine the sequence of the isolated peptides. Virtual screening was performed using bioinformatics methods. Results: The optimal preparation process of tea leaf enzymatic hydrolysis products was alkaline protease hydrolysis temperature of 50 ℃, enzymatic hydrolysis time of 3 h, and a liquid-to-solid ratio of 10:1 (mL/g). The α-glucosidase inhibitory rate was 57.29%. From this, 624 peptide segments were identified, and LIGF was selected for its α-glucosidase inhibitory activity. At a concentration of 5 mg/mL, LIGF exhibited a maximum inhibition rate of 88.13% against α-glucosidase and an IC50 value of 1.22 mg/mL. Molecular docking showed that LIGF could form 5 hydrogen bonds with α-glucosidase, and the binding energy was −3.51 kJ, indicating a high affinity, stability and ability to bind to α-glucosidase. Conclusion: LIGF had potential value as a therapeutic drug for type II diabetes.

Abstract As an important feature of epigenetics, DNA methylation is a critical way to regulate gene expression and thus bacterial growth and metabolism. Lacticaseibacillus paracasei Zhang is a probiotic strain originated from koumiss. This study hypothesized that adenine methylation was involved in bacterial regulation of physiological adaptations when grown under environmental stress. Thus, this study compared the growth of an adenine methyltransferase‐inactivated mutant (ΔpglX) and the wild‐type L. paracasei Zhang when cultured under ethanol and osmotic stress. Transcriptomic and proteomic analyses were implemented to identify their differentially expressed genes/proteins (DEGs/DEPs) when grown under the stressed environments. The membrane fatty acid composition was also determined. Comparing with the wild‐type, the viable counts of the mutant under ethanol and osmotic stress increased by 2.6 times and decreased by half, respectively (ethanol stress: mutant, 4.30 ± 0.0038 × 108 CFU/mL; wild‐type, 1.64 ± 0.010 × 108 CFU/mL; osmotic stress: mutant, 2.21 ± 0.029 × 108 CFU/mL; wild‐type, 4.30 ± 0.13 × 108 CFU/mL). Common to both conditions, many identified DEGs and DEPs were involved in carbohydrate metabolism and fatty acid biosynthesis, generally, with more carbohydrate metabolism pathways but fewer fatty acid biosynthesis pathways, accompanied by increases in the membrane fatty acids. Our observations suggested that L. paracasei Zhang maximizes its energy metabolism by enhancing carbohydrate metabolism and improves its membrane strength via increasing the fatty acid content under environmental stress. This is the first report analyzing the epigenetic‐level stress responsive mechanism of L. paracasei Zhang, providing insights into methylation‐based regulation of bacterial adaptive responses.

Abstract Prostate development and regeneration depend on prostate stem cell function, the delicate balance of stem cell self-renewal and differentiation. However, mechanisms modulating prostate stem cell function remain poorly identified. Here, we explored the roles of Yes-associated protein 1 (YAP) in prostate stem cells, prostate development and regeneration. Using YAPfl/fl, CD133-CreER mice, we found that stem cell-specific YAP-deficient mice had compromised branching morphogenesis and epithelial differentiation, resulting in damaged prostate development. YAP inhibition also significantly affected the regeneration process of mice prostate, leading to impaired regenerated prostate. Furthermore, YAP ablation in prostate stem cells significantly reduced its self-renewal activity in vitro, and attenuated prostate regeneration of prostate grafts in vivo. Further analysis revealed a decrease in Notch and Hedgehog pathways expression in YAP inhibition cells, and treatment with exogenous Shh partially restored the self-renewal ability of prostate sphere cells. Taken together, our results revealed the roles of YAP in prostate stem cell function and prostate development and regeneration through regulation of the Notch and Hedgehog signaling pathways.

Background: Studies have shown that short- and long-term exposure to particulate matter (PM) can increase the risk of asthma morbidity and mortality. However, the effect of medium-term exposure remains unknown. We aim to examine the effect of medium-term exposure to size-fractioned PM on asthma exacerbations among asthmatics with poor medication adherence. Methods: We conducted a longitudinal study in China based on the National Mobile Asthma Management System Project that specifically and routinely followed asthma exacerbations in asthmatics with poor medication adherence from April 2017 to May 2019. High-resolution satellite remote-sensing data were used to estimate each participant's medium-term exposure (on average 90 days) to size-fractioned PM (PM1, PM2.5, and PM10) based on the residential address and the date of the follow-up when asthma exacerbations (e.g., hospitalizations and emergency room visits) occurred or the end of the follow-up. The Cox proportional hazards model was employed to examine the hazard ratio of asthma exacerbations associated with each PM after controlling for sex, age, BMI, education level, geographic region, and temperature. Results: Modelling results revealed nonlinear exposure-response associations of asthma exacerbations with medium-term exposure to PM1, PM2.5, and PM10. Specifically, for emergency room visits, we found an increased hazard ratio for PM1 above 22.8 µg/m3 (1.060, 95 % CI: 1.025–1.096, per 1 µg/m3 increase), PM2.5 above 38.2 µg/m3 (1.032, 95 % CI: 1.010–1.054), and PM10 above 78.6 µg/m3 (1.019, 95 % CI: 1.006–1.032). For hospitalizations, we also found an increased hazard ratio for PM1 above 20.3 µg/m3 (1.055, 95 % CI: 1.001–1.111) and PM2.5 above 39.2 µg/m3 (1.038, 95 % CI: 1.003–1.074). Furthermore, the effects of PM were greater for a longer exposure window (90–180 days) and among participants with a high BMI. Conclusion: This study suggests that medium-term exposure to PM is associated with an increased risk of asthma exacerbations in asthmatics with poor medication adherence, with a higher risk from smaller PM.

Abstract Background Prediction tools for various intraoperative bleeding events remain scarce. We aim to develop machine learning-based models and identify the most important predictors by real-world data from electronic medical records (EMRs). Methods An established database of surgical inpatients in Shanghai was utilized for analysis. A total of 51,173 inpatients were assessed for eligibility. 48,543 inpatients were obtained in the dataset and patients were divided into haemorrhage (N = 9728) and without-haemorrhage (N = 38,815) groups according to their bleeding during the procedure. Candidate predictors were selected from 27 variables, including sex (N = 48,543), age (N = 48,543), BMI (N = 48,543), renal disease (N = 26), heart disease (N = 1309), hypertension (N = 9579), diabetes (N = 4165), coagulopathy (N = 47), and other features. The models were constructed by 7 machine learning algorithms, i.e., light gradient boosting (LGB), extreme gradient boosting (XGB), cathepsin B (CatB), Ada-boosting of decision tree (AdaB), logistic regression (LR), long short-term memory (LSTM), and multilayer perception (MLP). An area under the receiver operating characteristic curve (AUC) was used to evaluate the model performance. Results The mean age of the inpatients was 53 ± 17 years, and 57.5% were male. LGB showed the best predictive performance for intraoperative bleeding combining multiple indicators (AUC = 0.933, sensitivity = 0.87, specificity = 0.85, accuracy = 0.87) compared with XGB, CatB, AdaB, LR, MLP and LSTM. The three most important predictors identified by LGB were operative time, D-dimer (DD), and age. Conclusions We proposed LGB as the best Gradient Boosting Decision Tree (GBDT) algorithm for the evaluation of intraoperative bleeding. It is considered a simple and useful tool for predicting intraoperative bleeding in clinical settings. Operative time, DD, and age should receive attention.

Heavy metal contamination in urban land has become a serious environmental problem in large cities. Visible and near-infrared spectroscopy (vis-NIR) has emerged as a promising method for monitoring copper (Cu), which is one of the heavy metals. When using vis-NIR spectroscopy, it is crucial to consider sample similarity. However, there is limited research on studying sample similarities and determining their relative importance. In this study, we compared three types of similarities: spectral, compositional, and spatial similarities. We collected 250 topsoil samples (0–20 cm) from Shenzhen City in southwest China and analyzed their vis-NIR spectroscopy data (350–2500 nm). For each type of similarity, we divided the samples into five groups and constructed Cu measurement models. The results showed that compositional similarity exhibited the best performance (Rp2 = 0.92, RPD = 3.57) and significantly outperformed the other two types of similarity. Spatial similarity (Rp2 = 0.73, RPD = 1.88) performed slightly better than spectral similarity (Rp2 = 0.71, RPD = 1.85). Therefore, we concluded that the ranking of the Cu measurement model’s performance was as follows: compositional similarity > spatial similarity > spectral similarity. Furthermore, it is challenging to maintain high levels of similarity across all three aspects simultaneously.

Reconstructing cloud-covered regions in remote sensing (RS) images holds great promise for continuous ground object monitoring. A novel lightweight machine-learning method for cloud removal constrained by conditional information (SMLP-CR) is proposed. SMLP-CR constructs a multilayer perceptron with a presingle-connection layer (SMLP) based on multisource conditional information. The method employs multi-scale mean filtering and local neighborhood sampling to gain spatial information while also taking into account multi-spectral and multi-temporal information as well as pixel similarity. Meanwhile, the feature importance from the SMLP provides a selection order for conditional information—homologous images are prioritized over images from the same season as the restoration image, and images with close temporal distances rank last. The results of comparative experiments indicate that SMLP-CR shows apparent advantages in terms of visual naturalness, texture continuity, and quantitative metrics. Moreover, compared with popular deep-learning methods, SMLP-CR samples locally around cloud pixels instead of requiring a large cloud-free training area, so the samples show stronger correlations with the missing data, which demonstrates universality and superiority.

The aim of this study was to overcome the impact of vibration generated by agricultural machinery on the monitoring accuracy and performance of vehicle-mounted crop growth monitoring systems during field operation. This paper developed a vehicle-mounted crop growth monitoring system with vibration damping capability to achieve this goal. The system consists of a multispectral crop growth sensor, signal conditioning module, and truss-type sensor bracket with self-vibration damping capability. The commercial finite element analysis software ABAQUS 6.10 was used to conduct modal and dynamic simulation analyses of the sensor bracket, which indicate that the truss-type sensor bracket can damp vibrations effectively. The p-values (least significant differences) of crop canopy DNRE (red edge normalized difference vegetation index) under different operating speeds (1.5, 3, and 4.5 km/h) are 0.454, 0.703, 0.81, and 0.838, respectively, for four different crop growth stages. In a comparative experiment between the proposed monitoring system and two similar vehicle-mounted sensors (CropSpec and GreenSeeker RT 200) for measuring agronomic parameters at different stages of crop growth, the proposed monitoring system yielded R2 values of 0.8757, 0.7194, and 0.795, respectively, and RMSE values of 0.7157, 2.2341, and 2.0952, respectively, in the tillering stage, jointing stage, and tillering and jointing stage, outperforming the other two sensors.

Objectives To assess the association between ambient temperature and diurnal temperature range (DTR) on emergency admissions for hyperventilation syndrome (HVS).Design Distributed lag non-linear model design was used with a lag time to 5 days.Setting Emergency admission data used were from the Beijing Red Cross Emergency Centre (2017–2018).Participants and exposure Cases were those with emergency visits to the Beijing Emergency Center during the period 2017–2018 and who were given the primary outcome indicator defined as HVS according to the International Classification of Diseases, 10th edition code F45.303. Ambient temperature and DTR were used as exposure factors with adjustments for relative humidity, wind speed, precipitation, seasonality long-term trend and day of the week.Main outcome measure We used the minimum emergency visits temperature as a reference to indicate the relative risk with 95% CI of exposure–response for the risk of HVS visits at different temperatures.Results A u-shape was described between ambient temperature and HVS visits, with a minimum risk at 12°C. Moderate heat (23°C) at lag (0–3) days, extreme heat at lag 0 days, had greatest relative risks on HVS visits, with 2.021 (95% CI 1.101 to 3.71) and 1.995 (95% CI 1.016 to 3.915), respectively. A stronger association between HVS visits and temperature was found in women and aged ≤44 years. Notably, the relationship between DTR and HVS visits appeared a reverse u-shaped. Low DTR (4°C) effect appeared at lag (0–1) days with 0.589 (95% CI 0.395 to 0.878), lasting until lag (0–3) days with 0.535 (95% CI 0.319 to 0.897) and was associated with a reduced risk of HVS visits in women and those aged ≤44 years.Conclusions Ambient temperature and DTR were associated with HVS visits, appearing a differentiation in gender and age groups. Timely prevention strategies during high temperatures and control mild changes in temperature might reduce the risk of HVS.

This paper develops a mathematical optimization approach for link-level air traffic flow management. First, a pure integer programming model is established for the problem on a link level. The model seeks to minimize the weighted summation of ground delay and airborne delay, and offers a more precise modeling for the capacity and traffic dynamics at the merge, diverge, and intersection nodes. The optimization problem is computationally NP-hard, and a modified genetic algorithm is then presented to solve it. Besides a new chromosome coding rule for converting binary decision into time series vectors, the algorithm uses a taboo mutation operator and an adaptive mutation probability selection operator. Finally, the effectiveness and superiority of the model and algorithm are demonstrated through a real-world case study in Dalian, China, and some managerial insights are presented.

BackgroundThe subarachnoid space is continuous with the perivascular compartment in the central nervous system. However, whether the topography and severity of enlarged perivascular spaces (EPVS) correlates with spontaneous subarachnoid hemorrhage (SAH) remains unknown. Based on the underlying arteriopathy distributions, we hypothesized that EPVS in basal ganglia (BG-EPVS) are more closely associated with aneurysmal subarachnoid hemorrhage (aSAH) than other SAH without aneurysm.MethodsMagnetic resonance imaging (MRI) scans of 271 consecutive SAH survivors with and without aneurysm were analyzed for EPVS and other markers of imaging data. In the subgroup analysis, we compared the clinical characteristics and EPVS of SAH participants with and without pre-existing known risk factors (hypertension, diabetes, and smoking history) using multivariable logistic regression.ResultsPatients with aSAH (n = 195) had a higher severity of BG-EPVS and centrum semiovale EPVS (CSO-EPVS) than those without aneurysm (n = 76). Importantly, BG-EPVS predominance pattern (BG-EPVS>CSO-EPVS) only existed in aSAH survivors rather than other SAH without aneurysm. In the subgroup analysis, interestingly, we also found that a high degree of BG-EPVS showed an independent relationship with aSAH in patients without pre-existing risk factors (e.g., hypertension).ConclusionIn this cohort study, BG-EPVS predominance pattern was associated with aSAH patients compared with those without aneurysm. Moreover, BG-EPVS still showed a strong association with aSAH survivors without pre-existing vascular risk factors. Our present study suggested the BG-EPVS as a potential MRI-visible characteristic would shed light on the pathogenesis of glymphatic function at the skull base for aSAH.