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Abstract Background Chlamydia and gonorrhea notifications are rapidly rising in men who have sex with men (MSM). Currently, there are limited data on the prevalence of chlamydia and gonorrhea across various anatomical sites. Our study aimed to explore the prevalence, association and changing trends of urethral and rectal chlamydia and gonorrhea among MSM in Guangdong Province, China. Methods We analyzed data among MSM attending sexually transmitted infections (STI) clinics in the Guangdong governmental sentinel network between 2018 and 2022. Chi-square tests were used to compare the difference, Join-point regressions for analyzing changing trends, and multivariate logistic regressions for examining associated factors. Results We included 4856 men in the analysis. Rectal chlamydia significantly increased from 13.8% to 26.4% over the past 5 years (average annual percentage change [AAPC] 19.2%, 95%CI 1.0-40.6, p = 0.043). After adjusting for covariates, chlamydia infection positively associated with main venue used to seek sexual partners (aOR = 2.31, 95%CI 1.17–4.55), having regular sexual partners in the past 6 months (aOR = 3.32, 95%CI 1.95–5.64), receiving HIV counselling and testing services (aOR = 2.94, 95%CI 1.67–5.17), receiving peer education (aOR = 1.80, 95%CI 1.14–2.83), infection with syphilis (aOR = 2.02, 95%CI 1.02–4.01) and infection with gonorrhea (aOR 7.04, 95% CI 3.01–16.48). Gonorrhea infection positively associated with having regular sexual partners in the past 6 months (aOR = 3.48.95%CI 1.16–10.49), and infection with chlamydia (aOR 7.03, 95% CI 2.99–16.51). Conclusions To conclude, our findings reveal a high prevalence of chlamydia infections among MSM, particularly in the rectal area. Comprehensive chlamydia and gonorrhea health services are necessary for MSM to improve sexual health.

Abstract Background Female sex workers (FSW) are particularly vulnerable to unintended pregnancy. Research examining the experience of unintended pregnancy due to commercial sex among Chinese FSW, however, is limited. This study aimed to examine the prevalence and correlates of unintended pregnancy due to commercial sex among FSW in China. Methods In 2021, a cross-sectional study was conducted among 1257 FSW in five cities from Guangdong provinces in South China. Data were collected on social-demographic characteristics, sexual behaviors, experience of unintended pregnancy due to commercial sex and its pregnancy outcome, as well as experience of abortion in lifetime. Multivariable logistic regression analysis was employed to identify factors associated with unintended pregnancy. Results Among the 1257 FSW, 19.3% reported having at least one unintended pregnancy due to commercial sex. Of those, 96.7% chose to terminate the pregnancy through induced abortion, and 40.5% reported undergoing multiple induced abortions in their lifetime. Multivariable logistic regression indicated that FSW working in current location over one year (adjusted Odds Ratio (aOR): 2.82, 95% CI 1.71–4.64) and having more than seven clients in the past week (aOR: 4.53, 95% CI 2.74–7.51) were more likely to have had unintended pregnancy due to commercial sex. Working in high tier (aOR: 0.21, 95% CI 0.14–0.30) and consistent condom use with clients in the past month (aOR: 0.16, 95% CI 0.10–0.23) were associated with a lower proportion of FSW having ever had unintended pregnancy. Conclusions Unintended pregnancy are prevalent among FSW in South China. Interventions aimed at reducing the prevalence of unintended pregnancy and enhancing post-abortion care could be necessary among Chinese FSW.

Intelligent recognition technology for underground safety violations in coal mines has become the primary means of safety management and information acquisition. However, the accuracy of intelligent recognition is reduced by factors such as low illumination, point light sources, and high dust in the underground spatial environment. To overcome those problems, this paper proposes a multi-weight fusion image enhancement method, which achieves the fusion enhancement of image brightness and illumination balance. The monitoring image brightness is increased by using the Gamma algorithm. Based on the brightness enhancement, the HSV spatial transformation is carried out to keep the hue component and saturation component unchanged, the illumination component is extracted by using a multi-scale Gaussian function, and then the regions where the illumination component is too strong and too weak are adjusted by using an improved two-dimensional gamma function to achieve an illumination equalization. Combining the three weights of Laplacian contrast, luminance, and saturation and fusing the luminance-enhanced and illuminance-balanced images by Gaussian and Laplacian pyramids, the intelligent surveillance image enhancement is achieved. Through the experimental verification of the intelligent recognition of helmets in mine monitoring, the image enhancement method proposed in this paper and the MSR, MSRCP, MSRCR, and AMSRCR algorithms are evaluated in terms of image evaluation indexes such as standard deviation, peak signal-to-noise ratio, and information entropy, and the peak signal-to-noise ratio is improved by 32.44% on average compared with other algorithms, the standard deviation is improved by 115.38% on average compared with the original image, and the average improvement in standard deviation is 115.38% compared with the original image and 47.30% compared with other algorithms, and the accuracy of helmet recognition reaches 86.7%, an average improvement of 47.52% compared with other algorithms. The results show that the algorithm in this paper can effectively improve the contrast and clarity of mine images, reduce the halo phenomenon, and significantly improve the accuracy of target recognition in intelligent mine monitoring. It can lay a solid foundation for the intelligent identification of safety violations in underground coal mines.

BackgroundSeasonal influenza continues to pose a substantial public health challenge for older adults residing in rural areas worldwide. Vaccination remains the most efficacious means of preventing influenza. This study aimed to investigate the extent of influenza vaccine coverage and identify the factors influencing vaccine uptake among older adults in rural regions of south China.MethodsA cross-sectional study utilizing convenience sampling was conducted in two rural sites in Guangdong Province. Individuals needed to meet specific inclusion criteria: (1) attainment of 60 years of age or older; (2) originating from rural households; (3) demonstrating a voluntary desire to partake in the survey, either through written or verbal informed consent. Data encompassed variables such as socio-demographic information, influenza infection and vaccination history, knowledge and attitudes toward influenza vaccination, and perceived beliefs regarding the influenza vaccine. Univariate and multivariable logistic regression analyses were employed to ascertain the factors associated with influenza vaccine utilization. In the multivariable model, adjustments were made for gender, age, legal marital status, highest educational attainment, and monthly income.ResultsA total of 423 participants were ultimately included in this study, with the majority falling within the age range of 60–75 years (81.3%). Only one-third of the participants had received an influenza vaccine in the past year (30.0%). Notably, nearly half of the older adults exhibited hesitancy toward influenza vaccination (45.1%). The multivariable analysis revealed that rural older people with a robust understanding of influenza vaccines and a positive attitude toward them (adjusted odds ratio [aOR] = 2.60, 95% confidence interval [CI]: 1.41–4.81), along with a high level of trust in vaccination service providers (aOR = 2.58, 95% CI: 1.01–6.63), were positively associated with receiving influenza vaccination in the past year.ConclusionThis study reveals a low rate of influenza vaccine uptake among older adults residing in rural areas of south China. Given the limited adoption of influenza vaccination and the significant threat it poses, there is an urgent imperative to devise precise interventions aimed at enhancing the effectiveness of influenza vaccination programs.

The study explored the impact of water management on rice cultivation in mercury-contaminated paddy soil. The objective was to analyze the characteristics of mercury translocation by converting flooded soils to dry farming (non-flooded) to alleviate mercury accumulation in rice grains. The experiment was conducted over three consecutive rice-growing seasons, employing two distinct water management models: a continuously flooded rice cultivation mode and a flooded rice planting mode in the first season, followed by a non-flooded rice farming mode in the second and third seasons. The results showed that the change from flooded to non-flooded rice cultivation patterns presented extremely excellent environmental potential for inhibiting the uptake of both methylmercury and total mercury in rice. When transitioning from flooded cultivation to dry farming, the concentration of methylmercury and total mercury in the grains of non-flooded rice decreased by 87.15 % and 9.57 %, respectively, compared to that in the grains of flooded rice. In the third season, the methylmercury and total mercury in the grains of non-flooded rice decreased further by 95.03 % and 69.45 %, respectively. This study verified that the conversion of rice cultivation from flooded to non-flooded is an efficient strategy for suppressing the accumulation of methylmercury in rice grains, and it might offer a promising solution for managing soil mercury risks and ensuring the safety of rice for human consumption.

Abstract Background Radiotherapy interruption (RTI) prolongs the overall total treatment time and leads to local control loss in many cancers, but it is unclear in esophageal cancer. We aimed to evaluate the influence of RTI on the overall survival (OS), progression-free survival (PFS), and local-regional recurrence-free survival (LRFS) of patients with esophageal cancer undergoing chemoradiotherapy. Methods A total of 299 patients with esophageal squamous cell carcinoma from 2017 to 2019 were retrospectively analyzed to investigate the effect of RTI on OS, PFS, and LRFS. The delayed time of radiotherapy interruption was calculated as the actual radiation treatment time minus the scheduled time. The univariate and multivariate analyses were performed by the COX proportional hazards regression models, and the survival analysis was performed through the Kaplan‒Meier method, and compared with the log-rank test. Results The 3-year OS, PFS, and LRFS rates were 53.0%, 42.0%, and 48.0%, respectively. The univariate and multivariate analyses showed that the delayed time > 3 days was an independent adverse prognostic factor for OS (HR = 1.68, 95% CI 1.10–2.55, p = 0.016), and LRFS (HR = 1.74, 95% CI 1.18–2.57, p = 0.006). The patient with a delayed time of > 3 days had poorer survival rates of OS, and LRFS than patients with a delayed time of ≤ 3 days (OS, p = 0.047; LRFS, p = 0.013), and the survival outcomes of patients with shorter delayed time (1–3 days) were slightly different from the patients without interruptions. The impact of delay time on PFS is not statistically significant, but the survival outcomes of the two groups were slightly different. Conclusion There was a significant correlation between delayed time and local control of esophageal cancer. The delayed time for more than 3 days might decrease the survival outcome, and increase the local recurrence risk.

Abstract The structure of rocks plays a crucial role in their failure process. However, it is ignored that the interactions between rock internal structure and the effect of its own evolution on the rock fracture process. To investigate the effect between the evolution law of rock regionalized structures and their interaction relationships during failure. We conducted an experiment using visual acoustic imaging monitoring to study rock failure, introducing a new concept of characteristics of rock structure—regionalized structures. The findings reveal three main types of regionalized structures in rocks: skeleton regions, variable regions, and damage regions. These structures combine to form four categories of complex rock structures: block-type support skeletons, point column-type support skeletons, suspension-type weak support skeletons, and no skeletons. During the failure process, we found that these regionalized structures worked together synergistically to control rock failure. Although the evolutionary relationships among the structures show some similarities, the final fracture states vary significantly. Stress and strain distribution patterns clearly demonstrate that variations in the force capacities and roles of the regionalized structures influence the synergistic evolutionary relationships, ultimately impacting the mode of rock failure. This work provides new insights for further research on rock failure mechanisms and can significantly contribute to preventing rock engineering disasters related to regionalized structures.

Abstract Background Depression is a common chronic debilitating disease with a heavy social burden. single nucleotide polymorphisms (SNPs) can affect the function of microRNAs (miRNAs), which is in turn associated with neurological diseases. However, the association between SNPs located in the promoter region of miR-17-92 and the risk of depression remains unclear. Therefore, we investigated the association between rs982873, rs9588884 and rs1813389 polymorphisms in the promoter region of miR-17-92 and the incidence of depression in a Chinese population. Methods we used GWAS (Genome-wide association study) and NCBI (National Center for Biotechnology Information) to screen three SNPs in the miR-17-92 cluster binding sites. A case-control study (including 555 cases and 541 controls) was conducted to investigate the relationship between the SNPs and risk of depression in different regions of China. The gene sequencing ii was used to genotype the collected blood samples. Results the following genotypes were significantly associated with a reduced risk of depression: rs982873 TC (TC vs. TT: OR = 0.72, 95% CI, 0.54–0.96, P = 0.024; TC/CC vs. TT: OR = 0.74, 95% Cl, 0.56–0.96, P = 0.025); CG genotype of rs9588884 (CG vs. CC: OR = 0.74, 95% CI, 0.55–0.98, P = 0.033; CG/GG vs. CC: OR = 0.75, 95% Cl, 0.57–0.98, P = 0.036); and AG genotype of rs1813389 (AG vs. AA: OR = 0.75, 95% CI, 0.57-1.00, P = 0.049; AG/GG vs. AA: OR = 0.76, 95% Cl, 0.59-1.00, P = 0.047). Stratified analysis showed that there was no significant correlation between the three SNPS and variables such as family history of suicidal tendency (P > 0.05). Conclusions our findings suggest that rs982873, rs9588884, and rs1813389 polymorphisms may be associated with protective factors for depression.

Coal-rock interface recognition technology is one of the key technologies for intelligent mining in coal mines. Based on high-frequency radar wave detection technology, high-precision detection of coal-rock interfaces can be achieved with mining, but there are still safety risks for equipment caused by rib spalling and roof caving in ultra-high mining heights (≥6 m) in mines, as well as spatial restrictions on equipment passing through during sudden changes in mining height (mining height ≤2 m). Based on previous work, this paper proposes a rapid dynamic detection system and method for coal-rock interfaces in mines using nodal GPR. The main contents include: ① Explaining the principle of the nodal GPR observation system in mines, designing a coal-rock interface recognition observation system plan and radar antenna sensor installation method based on the actual environment of the mine working face; ② Studying and proposing a nodal acquisition control system and information interaction transmission design plan to achieve dynamic data acquisition, control, and storage; ③ Studying and proposing enhanced processing methods for sensor detection data and coal-rock interface recognition algorithms based on nodal acquisition methods and radar reflection echo characteristics of coal-rock interfaces, which can effectively achieve intelligent recognition and tracking of coal-rock interfaces, as well as calculation of coal seam thickness and spatial coordinates. To verify the feasibility of this method, multiple geological radar antenna sensors with a center frequency of 1.5 GHz were used for physical model verification experiments, and a comparative analysis of nodal data acquisition and continuous data acquisition results was conducted. The experimental results show that both nodal and continuous acquisition methods can effectively identify coal-rock interfaces. Compared with continuous acquisition methods, the nodal detection method proposed in this paper can achieve rapid and dynamic repetitive data acquisition, with a single acquisition time controlled within 10 seconds, an average error of 1.07 cm for coal seam thickness detection results, a maximum error of 1.47 cm, and an average error percentage of 7.64%. This method provides technical support for dynamic high-precision detection of coal-rock interfaces in intelligent mining in mines.

Automatic modal identification via automatically interpreting the stabilization diagram provides key technique in bridge structural health monitoring. This paper reviews the progress in the area of automatic modal identification based on interpreting the stabilization diagram. The whole identification process is divided into four steps from establishing the stabilization diagram to removing the outliers in the identification results. The criteria and algorithms used in each step in the existing studies are carefully summarized and classified. Comparisons between typical methods in cleaning and interpreting the stabilization diagram are also conducted. Real structure benchmarks used in the existing studies to validate the proposed automatic modal identification methods are also summarized. Based on the review and comparison, the specific ratio method for cleaning the stabilization diagram, the hierarchical clustering method for interpreting the stabilization diagram and the adjusted boxplot for removing the outliers in the identification results are the most suitable methods for each step. The key point of automatic modal identification based on interpreting the stabilization diagram has also discussed, and it is recommended to pay more attention to cleaning the stabilization diagram. Future study about automatic modal identification under situation with very few sensors deployed should be more concerned. This review aims to help researchers and practitioners in implementing existing automatic modal identification algorithms effectively and developing more suitable and practical methods for civil engineering structures in the future.

ABSTRACTSpatial prediction is essential for obtaining the spatial distribution of geographic variables and selecting appropriate covariates for this process can be challenging, especially for non-expert users. For easing the burden of selecting the appropriate covariates, two case-based reasoning strategies, namely the most-similar-case and covariate-classification strategies, have been proposed for automated covariate selection. The former may suggest nonessential covariates due to its case-level reasoning way. And the latter with covariate-level reasoning may overlook related covariates and recommend fewer covariates than the case-level reasoning. In this study, we propose a new strategy of integrating case-level and covariate-level reasoning to effectively leverage the strengths of both previous strategies while also addressing their limitations. The proposed strategy is validated through a case study of automatically selecting covariates for digital soil mapping under reasoning with a case base containing 189 cases. The leave-one-out evaluation demonstrated that our proposed strategy outperformed the previous two strategies.

Abstract Immune checkpoint inhibitors targeting the programmed cell death-1 (PD-1) protein significantly improve survival in patients with advanced non-small-cell lung cancer (NSCLC), but its impact on early-stage ground-glass opacity (GGO) lesions remains unclear. This is a single-arm, phase II trial (NCT04026841) using Simon’s optimal two-stage design, of which 4 doses of sintilimab (200 mg per 3 weeks) were administrated in 36 enrolled multiple primary lung cancer (MPLC) patients with persistent high-risk (Lung-RADS category 4 or had progressed within 6 months) GGOs. The primary endpoint was objective response rate (ORR). T/B/NK-cell subpopulations, TCR-seq, cytokines, exosomal RNA, and multiplexed immunohistochemistry (mIHC) were monitored and compared between responders and non-responders. Finally, two intent-to-treat (ITT) lesions (pure-GGO or GGO-predominant) showed responses (ORR: 5.6%, 2/36), and no patients had progressive disease (PD). No grade 3–5 TRAEs occurred. The total response rate considering two ITT lesions and three non-intent-to-treat (NITT) lesions (pure-solid or solid-predominant) was 13.9% (5/36). The proportion of CD8+ T cells, the ratio of CD8+/CD4+, and the TCR clonality value were significantly higher in the peripheral blood of responders before treatment and decreased over time. Correspondingly, the mIHC analysis showed more CD8+ T cells infiltrated in responders. Besides, responders’ cytokine concentrations of EGF and CTLA-4 increased during treatment. The exosomal expression of fatty acid metabolism and oxidative phosphorylation gene signatures were down-regulated among responders. Collectively, PD-1 inhibitor showed certain activity on high-risk pulmonary GGO lesions without safety concerns. Such effects were associated with specific T-cell re-distribution, EGF/CTLA-4 cytokine compensation, and regulation of metabolism pathways.

Abstract To tackle misdiagnosis in lung cancer screening with low‐dose computed tomography (LDCT), we aimed to compile a genome atlas for differentiating benign, preinvasive, and invasive lung nodules and characterize their molecular pathogenesis. We collected 432 lung nodule tissue samples from Chinese patients, spanning benign, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA). We performed comprehensive sequencing, examining somatic variants, gene expressions, and methylation levels. Our findings uncovered EGFR and TP53 mutations as key drivers in ‐ early lung cancer development, with EGFR mutation frequency increasing with disease progression. Both EGFR mutations and EGF/EGFR hypo‐methylation activated the EGFR pathway, fueling cancer growth. Transcriptome analysis identified four lung nodule subtypes (G1‐4) with distinct molecular features and immune cell infiltrations: EGFR‐driven G1, EGFR/TP53 co‐mutation G2, inflamed G3, stem‐like G4. Estrogen/androgen response was associated with the EGFR pathway, proposing a new therapy combining tyrosine kinase inhibitors with antiestrogens. Preinvasive nodules exhibited stem cell pathway enrichment, potentially hindering invasion. Epigenetic regulation of various genes was essential for lung cancer initiation and development. This study provides insights into the molecular mechanism of neoplastic progression and identifies potential diagnostic biomarkers and therapeutic targets for lung cancer.

In invasive lung adenocarcinoma (LUAD), patients with micropapillary (MIP) or solid (SOL) components had a significantly poorer prognosis than those with only lepidic (LEP), acinar (ACI) or papillary (PAP) components. It is interesting to explore the genetic features of different histologic subtypes, especially the highly aggressive components.Based on a cohort of 5,933 patients, this study observed that in different tumor size groups, LUAD with MIP/SOL components showed a different prevalence, and patients with ALK alteration or TP53 mutations had a higher probability of developing MIP/SOL components. To control individual differences, this research used spatial whole-exome sequencing (WES) via laser-capture microdissection of five patients harboring these five coexistent components and identified genetic features among different histologic components of the same tumor. In tracing the evolution of components, we found that titin (TTN) mutation might serve as a crucial intratumor potential driver for MIP/SOL components, which was validated by a cohort of 146 LUAD patients undergoing bulk WES. Functional analysis revealed that TTN mutations enriched the complement and coagulation cascades, which correlated with the pathway of cell adhesion, migration, and proliferation.Collectively, the histologic subtypes of invasive LUAD were genetically different, and certain trunk genotypes might synergize with branching TTN mutation to develop highly aggressive components.

Short-term energy-consumption prediction is the basis of anomaly detection, real-time scheduling, and energy-saving control in manufacturing systems. Most existing methods focus on single-node energy-consumption prediction and suffer from difficult parameter collection and modelling. Although several methods have been presented for multinode energy-consumption prediction, their prediction performance needs to be improved owing to a lack of appropriate knowledge guidance and learning networks for complex spatiotemporal relationships. This study presents a symmetric spatiotemporal learning network (SSTLN) with a sparse meter graph (SMG) (SSTLN-SMG) that aims to predict multiple nodes based on energy-consumption time series and general process knowledge. The SMG expresses process knowledge by abstracting production nodes, material flows, and energy usage, and provides initial guidance for the SSTLN to extract spatial features. SSTLN, a symmetrical stack of graph convolutional networks (GCN) and gated linear units (GLU), is devised to achieve a trade-off not only between spatial and temporal feature extraction but also between detail capture and noise suppression. Extensive experiments were performed using datasets from an aluminium profile plant. The experimental results demonstrate that the proposed method allows multinode energy-consumption prediction with less prediction error than state-of-the-art methods, methods with deformed meter graphs, and methods with deformed learning networks.

IntroductionLanguage delay cannot be ignored, and there is an urgent need to determine therapies that elicit better results in a short period. However, whether transcranial direct current stimulation (tDCS) alone or in combination with other therapies can promote recovery of language and cognitive function in children with language delay remains unknown. This study aims to explore the effects of tDCS combined with language-cognitive training and home-based rehabilitation on language and cognitive ability in children with language delay.MethodsChildren with language delay who visited the Department of rehabilitation medicine or the pediatric outpatient clinic of the First People’s Hospital of Foshan from January 2019 to December 2021, totaling 190 in number, were included and randomly divided into 4 groups, i.e., the family guidance group, the tDCS group, the language-cognitive training group, and the comprehensive training group. The family guidance group (47 cases) received home training. The tDCS group (46 cases) received home training and tDCS treatment. The language- cognitive training group (49 cases) adopted home training and language-cognitive training. The comprehensive training group (48 cases) took home training, language-cognitive training, and tDCS treatment. All groups received training 5 times a week for 4 weeks. The Sign-significant relations (S-S) test was applied to evaluate the language comprehension, language expression, basic learning ability, and attitude of communication of the children.ResultsThe language-cognitive training group and the comprehensive training group showed improvement after treatment (p < 0.05) regarding basic learning ability. The communication attitude of the four groups improved after intervention (p < 0.05). Particularly, the comprehensive training group had maximum improvement after intervention. No serious adverse reactions such as epilepsy, headache, and behavioral abnormalities were found.ConclusiontDCS combined with language-cognitive training and home training can improve language and cognitive ability in children with language delay.

To enhance the stability and anti-inflammatory efficacy of dihydromyricetin (DYM), suitable excipients were selected for the development of a self-microemulsifying drug delivery system (SMEDDS). The formulated SMEDDS exhibited remarkable drug loading (117.47 ± 4.5 mg/g) and encapsulation rates (93.98 ± 3.6 %). Transmission electron microscope (TEM) revealed the nanoscale and spherical morphology of DYM-SMEDDS. Stability assessments demonstrated that DYM-SMEDDS maintained a consistent uniform small particle size after various cycles of exposure. In vitro release curve exhibited that DYM-SMEDDS released 91.27 ± 1.44 % of DYM within 24 h, surpassing the suspension by 2-fold. Furthermore, in vivo studies indicated that DYM-SMEDDS significantly inhibited the levels of pro-inflammatory factors, while promoting the activity of antioxidant enzymes (p

Abstract Purpose Lung cancer (LC) and breast cancer (BC) are the most common causes of brain metastases (BMs). Time from primary diagnosis to BM (TPDBM) refers to the time interval between initial LC or BC diagnosis and development of BM. This research aims to identify clinical, molecular, and therapeutic risk factors associated with shorter TPDBM. Methods We retrospectively reviewed all diagnosed LC and BC patients with BM at Harbin Medical University Cancer Hospital from 2016 to 2020. A total of 570 patients with LC brain metastasis (LCBM) and 173 patients with breast cancer brain metastasis (BCBM) patients who met the inclusion criteria were enrolled for further analysis. BM free survival time curves were generated using Kaplan–Meier analyses. Univariate and multivariate Cox regression analyses were applied to identify risk factors associated with earlier development of BM in LC and BC, respectively. Results The median TPDBM was 5.3 months in LC and 44.4 months in BC. In multivariate analysis, clinical stage IV and M1 stage were independent risk factors for early development of LCBM. LC patients who received chemotherapy, targeted therapy, pulmonary radiotherapy, and pulmonary surgery had longer TPDBM. For BC patients, age ≥ 50 years, Ki67 ≥ 0.3, HER2 positive or triple‐negative breast cancer subtype, advanced N stage, and no mastectomy were correlated with shorter TPDBM. Conclusions This single‐institutional study helps identify patients who have a high risk of developing BM early. For these patients, early detection and intervention could have clinical benefits.

Abstract Background Sparganosis is a worldwide food-borne parasitic disease caused by spargana infection, which infects the muscle of frogs and snakes as well as many tissues and organs in humans. There are currently no viable treatments for sparganosis. Understanding spargana’s nutrition source and carbohydrate metabolism may be crucial for identifying its energy supply and establishing methods of treatment for sparganosis. Methods Using an amino acid analyzer and nutrient concentration detection kits, we assessed nutrient concentrations in the muscles of Fejervarya limnocharis and Pelophylax plancyi infected or not infected with spargana. Quantitative polymerase chain reaction (PCR) was used to quantify the major enzymes involved in five glucose metabolism pathways of spargana developing in vivo. We also used quantitative PCR to assess key enzymes and transcriptome sequencing to explore the regulation of carbohydrate metabolic pathways in vitro in response to different 24-h food treatments. Results Infected muscle tissues had considerably higher concentrations of glucogenic and/or ketogenic amino acids, glucose, and glycogen than non-infected muscle tissues. We discovered that the number of differentially expressed genes in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was larger in low-glucose than in other dietary groups. We examined differences in the expression of genes producing amino acid transporters, glucose transporters, and cathepsins in spargana grown in various nutritional environments. In the normal saline group, only the major enzymes in the tricarboxylic acid cycle (TCA), glycogenesis, and glycogenolysis pathways were expressed. The l-glutamine group had the greatest transcriptional levels of critical rate-limiting enzymes of gluconeogenesis and glycogenesis. Furthermore, the low-glucose group had the highest transcriptional levels of critical rate-limiting enzymes involved in the TCA, glycolytic, and glycogenolysis pathways. Surprisingly, when compared to the in vitro culturing groups, spargana developing in vivo exhibited higher expression of these critical rate-limiting enzymes in these pathways, with the exception of the pentose phosphate pathway. Conclusions Spargana have a variety of nutritional sources, and there is a close relationship between nutrients and the carbohydrate metabolism pathways. It takes a multi-site approach to block nutrient absorption and carbohydrate metabolism pathways to provide energy to kill them. Graphical Abstract

Abstract Background Low-frequency noise may cause changes in cognitive function. However, there is no established consensus on the effect of low-frequency noise on cognitive function. Therefore, this systematic review and meta-analysis aimed to explore the relationship between low-frequency noise exposure and cognitive function. Methods We conducted a systematic review and identified original studies written in English on low-frequency noise and cognition published before December 2022 using the PsycINFO, PubMed, Medline, and Web of Science databases. The risk of bias was evaluated according to established guidelines. A random-effects meta-analysis was performed where appropriate. To explore the association between low-frequency noise exposure and cognitive function, we reviewed eight relevant studies. These studies covered cognitive functions grouped into four domains: attention, executive function, memory, and higher-order cognitive functions. The data extraction process was followed by a random-effects meta-analysis for each domain, which allowed us to quantify the overall effect. Results Our analysis of the selected studies suggested that interventions involving low-frequency noise only had a negative impact on higher-order cognitive functions (Z = 2.42, p = 0.02), with a standardized mean difference of -0.37 (95% confidence interval: -0.67, -0.07). A moderate level of heterogeneity was observed among studies (p = 0.24, I2 = 29%, Tau2 = 0.03). Conclusions Our study findings suggest that low-frequency noise can negatively impact higher-order cognitive functions, such as logical reasoning, mathematical calculation, and data processing. Therefore, it becomes important to consider the potential negative consequences of low-frequency noise in everyday situations, and proactive measures should be taken to address this issue and mitigate the associated potential adverse outcomes.

Cells constitute the fundamental units of living organisms. Investigating individual differences at the single-cell level facilitates an understanding of cell differentiation, development, gene expression, and cellular characteristics, unveiling the underlying laws governing life activities in depth. In recent years, the integration of single-cell manipulation and recognition technologies into detection and sorting systems has emerged as a powerful tool for advancing single-cell research. Raman cell sorting technology has garnered attention owing to its non-labeling, non-destructive detection features and the capability to analyze samples containing water. In addition, this technology can provide live cells for subsequent genomics analysis and gene sequencing. This paper emphasizes the importance of single-cell research, describes the single-cell research methods that currently exist, including single-cell manipulation and single-cell identification techniques, and highlights the advantages of Raman spectroscopy in the field of single-cell analysis by comparing it with the fluorescence-activated cell sorting (FACS) technique. It describes various existing Raman cell sorting techniques and introduces their respective advantages and disadvantages. The above techniques were compared and analyzed, considering a variety of factors. The current bottlenecks include weak single-cell spontaneous Raman signals and the requirement for a prolonged total cell exposure time, significantly constraining Raman cell sorting technology’s detection speed, efficiency, and throughput. This paper provides an overview of current methods for enhancing weak spontaneous Raman signals and their associated advantages and disadvantages. Finally, the paper outlines the detailed information related to the Raman cell sorting technology mentioned in this paper and discusses the development trends and direction of Raman cell sorting.

Single-cell isolation stands as a critical step in single-cell studies, and single-cell ejection technology based on laser induced forward transfer technology (LIFT) is considered one of the most promising methods in this regard for its ability of visible isolating single cell from complex samples. In this study, we improve the LIFT technology and introduce optical vortex laser-induced forward transfer (OV-LIFT) and flat-top laser-induced forward transfer (FT-LIFT) by utilizing spatial light modulator (SLM), aiming to enhance the precision of single-cell sorting and the cell’s viability after ejection. Experimental results demonstrate that applying vortex and flat-top beams during the sorting and collection process enables precise retrieval of single cells within diameter ranges of 50 μm and 100 μm, respectively. The recovery rates of Saccharomyces cerevisiae and Escherichia coli DH5α single cell ejected by vortex beam are 89 and 78%, by flat-top beam are 85 and 57%. When employing Gaussian beam sorting, the receiving range extends to 400 μm, with cultivation success rates of S. cerevisiae and E. coli DH5α single cell are 48 and 19%, respectively. This marks the first application of different mode beams in the ejection and cultivation of single cells, providing a novel and effective approach for the precise isolation and improving the viability of single cells.

Abstract Introduction Treatment strategies for depression based on interventions for glucose and lipid metabolism disorders are receiving increasing attention. Investigating the mechanism of their antidepressant effect and exploring new diagnostic and therapeutic biomarkers have attracted increasing attention. Dulaglutide, a long‐acting GLP‐1 receptor agonist, has been reported to alleviate cognitive deficits and neuronal damage. However, the antidepressant effect of dulaglutide and, especially, the underlying mechanism are still poorly understood. In this study, we aimed to explore the underlying biomarkers of depression and potential modulatory targets of dulaglutide in chronic mild stress (CMS) mice. Methods Sixty mice were randomly divided into a control group (CON group), a CMS+Vehicle group (CMS+Veh group), a CMS+0.3 mg/kg dulaglutide group (Low Dula group), and a CMS+0.6 mg/kg dulaglutide group (High Dula group). Numerous behavioral tests, mainly the open field test, forced swimming test, and tail suspension test, were applied to evaluate the potential effect of dulaglutide treatment on anxiety‐ and depression‐like behaviors in mice exposed to chronic stress. Furthermore, a liquid chromatography–tandem mass spectrometry‐based metabolomics approach was utilized to investigate the associated mechanisms of dulaglutide treatment. Results Three weeks of dulaglutide treatment significantly reversed depressive‐like but not anxiety‐like behaviors in mice exposed to chronic stress for 4 weeks. The results from the metabolomics analysis showed that a total of 20 differentially expressed metabolites were identified between the CON and CMS+Veh groups, and 46 metabolites were selected between the CMS+Veh and High Dula groups in the hippocampus of the mice. Comprehensive analysis indicated that lipid metabolism, amino acid metabolism, energy metabolism, and tryptophan metabolism were disrupted in model mice that experienced depression and underwent dulaglutide therapy. Conclusion The antidepressant effects of dulaglutide in a CMS depression model were confirmed. We identified 64 different metabolites and four major pathways associated with metabolic pathophysiological processes. These primary data provide a new perspective for understanding the antidepressant‐like effects of dulaglutide and may facilitate the use of dulaglutide as a potential therapeutic strategy for depression.

Prefabricated retaining wall is in line with the development trend of greening and environmental protection of civil engineering, and has a broad application prospect. However, the seismic response of prefabricated retaining wall has not been systematically revealed. Therefore, in this study, a simple fabricated cantilever retaining wall with connecting plate was proposed, and the mechanical properties of prefabricated cantilever retaining under dynamic effect was investigated by the experimental and numerical methods. At first, the physical model experiments of prefabricated cantilever retaining with different vertical plate thicknesses were carried out. Subsequently, the mechanical properties of the prefabricated cantilever retaining were investigated. The research results show that the thickness of retaining wall significantly affects the failure pattern, the larger the thickness, the more complete the broken pattern. In addition, the connection between the vertical plate and the bottom plate is prone to cracks induced by stress concentration, eventually leading to damage. As the thickness of the vertical plate increases, the top stress of the vertical plate decreases but the bottom stress increases. The greater the embedded depth of the vertical plate, the larger the stress at bottom of the vertical plate. Furthermore, the effect of concrete strength on mechanical properties is not obvious. This study provides an idea for the dynamic response research of prefabricated retaining structure.

Users of the digital image correlation method are faced with the problem of poor operability, low repeatability, and lack of standardized specifications for spraying speckles. To solve the problem, the research proposed a rock deformation measurement method that obviates the need to spray speckles. A local binary model was established by using the local binary pattern (LBP) operator based on deep texture features on rock surfaces. The resulting LBP digital speckle pattern can substitute artificial speckle patterns and demonstrates high quality and strong applicability. Based on the LBP digital speckle pattern, the target tracking algorithm was employed to achieve non-contact measurement of the dynamic displacements of rocks. The feasibility and effectiveness of the algorithm in practical application were verified by conducting shear tests on granite and siltstone. Test results show that the deformation characteristics in the displacement nephograms are in line with the measured data pertaining to rock fracturing and conform to the basic characteristics of the shear failure of rocks. The deformation measurement method based on surface texture information can realize non-contact displacement measurement of rocks under conditions without speckles: this obviates the influence of the quality of sprayed speckles on the accuracy of the measurement of deformation.

The current deep learning methods for copy–move forgery detection (CMFD) are mostly based on deep convolutional neural networks, which frequently discard a large amount of detail information throughout convolutional feature extraction and have poor long-range information extraction capabilities. The Transformer structure is adept at modeling global context information, but the patch-wise self-attention calculation still neglects the extraction of details in local regions that have been tampered with. A local-information-refined dual-branch network, LBRT (Local Branch Refinement Transformer), is designed in this study. It performs Transformer encoding on the global patches segmented from the image and local patches re-segmented from the global patches using a global modeling branch and a local refinement branch, respectively. The self-attention features from both branches are precisely fused, and the fused feature map is then up-sampled and decoded. Therefore, LBRT considers both global semantic information modeling and local detail information refinement. The experimental results show that LBRT outperforms several state-of-the-art CMFD methods on the USCISI dataset, CASIA CMFD dataset, and DEFACTO CMFD dataset.

Abstract Background Diabetes mellitus is a prevalent metabolic disease in the world. Previous studies have shown that anesthetics can affect perioperative blood glucose levels which related to adverse clinical outcomes. Few studies have explored the choice of general anesthetic protocol on perioperative glucose metabolism in diabetes patients. We aimed to compare total intravenous anesthesia (TIVA) with total inhalation anesthesia (TIHA) on blood glucose level and complications in type 2 diabetic patients undergoing general surgery. Methods In this double-blind controlled trial, 116 type 2 diabetic patients scheduled for general surgery were randomly assigned to either the TIVA group or TIHA group (n = 56 and n = 60, respectively). The blood glucose level at different time points were measured and analyzed by the repeated-measures analysis of variance. The serum insulin and cortisol levels were measured and analyzed with t-test. The incidence of complications was followed up and analyzed with chi-square test or Fisher’s exact test as appropriate. The risk factors for complications were analyzed using the logistic stepwise regression. Results The blood glucose levels were higher in TIHA group than that in TIVA group at the time points of extubation, 1 and 2 h after the operation, 1 and 2 days after the operation, and were significantly higher at 1 day after the operation (10.4 ± 2.8 vs. 8.1 ± 2.1 mmol/L; P

Background and Objective. The Bispectral Index (BIS) is utilized to guide the depth of anesthesia monitoring during surgical procedures. However, conflicting results regarding the benefits of BIS for depth of anesthesia monitoring have been reported in numerous studies. The purpose of this meta-analysis and systematic review was to assess the effectiveness of BIS for depth of anesthesia monitoring. Search Methods. A systematic search of Ovid-MEDLINE, Cochrane, and PubMed was conducted from inception to April 20, 2023. Clinical trial registers and grey literature were also searched, and reference lists of included studies, as well as related review articles, were manually reviewed. Selection Criteria. The inclusion criteria were randomized controlled trials without gender or age restrictions. The control groups used conventional monitoring, while the intervention groups utilized BIS monitoring. The exclusion criteria included duplicates, reviews, animal studies, unclear outcomes, and incomplete data. Data Collection and Analysis. Two independent reviewers screened the literature, extracted data, and assessed methodological quality, with analyses conducted using R 4.0 software. Main Results. Forty studies were included. In comparison to the conventional depth of anesthesia monitoring, BIS monitoring reduced the postoperative cognitive dysfunction risk (RR = 0.85, 95% CI: 0.73∼0.99, P=0.04), shortened the eye-opening time (MD = −1.34, 95% CI: −2.06∼−0.61, P

Both MW 7.8 and MW 7.5 earthquakes occurred in southeastern Türkiye on February 6, 2023, resulting in numerous buildings collapsing and serious casualties. Understanding the distribution of coseismic surface ruptures and secondary disasters surrounding the epicentral area is important for post-earthquake emergency and disaster assessments. High-resolution Maxar and GF-2 satellite data were used after the events to extract the location of the rupture surrounding the first epicentral area. The results show that the length of the interpreted surface rupture zone (part of) is approximately 75 ​km, with a coseismic sinistral dislocation of 2–3 ​m near the epicenter; however, this reduced to zero at the tip of the southwest section of the East Anatolia Fault Zone. Moreover, dense soil liquefaction pits were triggered along the rupture trace. These events are in the western region of the Eurasian Seismic Belt and result from the subduction and collision of the Arabian and African Plates toward the Eurasian Plate. The western region of Chinese mainland and its adjacent areas are in the eastern section of the Eurasian Seismic Belt, where seismic activity is controlled by the collision of the Indian and Eurasian Plates. Both China and Türkiye have independent tectonic histories.

To understand the mechanism of dark abiotic mercury (Hg) methylation by algae-derived dissolved organic matter (DOM) and effectively manage the environmental risks of mercury methylation in aquaculture areas, we investigated the influence of subfractions of DOM released from algae (Ulothrix sp.) decomposition on mercury methylation. The results showed that the hydrophobic basic component (HOB) in DOM exhibited the most substantial promotion effect on Hg methylation. The methylmercury (MeHg) production in the HOB treatment increased significantly, while the production rate of MeHg (%MeHg represented the concentration ratio of MeHg to THg) in the six subfractions treated solutions decreased significantly with the increase of Hg concentration. The change of the %MeHg was more evident at low Hg concentration, indicating the limited number of binding sites and methyl donors on DOM. As a consequence, Hg(Ⅱ) in the solution could not be converted into MeHg in equal proportion. Furthermore, the production of MeHg in solution was significantly reduced by the decomposed algae DOM, and its concentration was in the range of 0.017–0.085 ng·L−1 (significantly lower than undecomposed algal). The difference between the decomposed and the non-decomposed algae DOM reached a significant level (P

With heightened concern over carbon neutrality and increased energy market fluctuations against the backdrop of increasing global uncertainty, it becomes imperative to thoroughly investigate the information transmission and risk contagion between carbon and energy markets. This paper empirically explores the return and volatility connectedness among carbon and energy markets (electricity, natural gas, crude oil, and coal) from April 2008 to September 2021 by employing the time-frequency domain connectedness approaches. This paper indicates: i) the return connectedness exceeds volatility connectedness, and extreme events can intensify the dynamic changes; ii) the return connectedness is predominantly concentrated at high-frequency, while the volatility connectedness is concentrated at medium- and low-frequency. Net volatility connectedness maintains a consistent direction across all markets in the time-frequency domain. In contrast, net return connectedness exhibits an opposing direction at high-frequency and medium- and low-frequency. iii) the natural gas and coal markets predominantly act as net transmitters in both return and volatility connectedness, while the electricity, crude oil, and carbon markets operate as net receivers. Moreover, during the COVID-19 pandemic, the carbon market emerged as an information receiver in time-frequency domains and acted as a risk transmitter, exporting risk, particularly to the electricity market. These conclusions help investors, high-carbon enterprises, and policymakers to comprehensively understand the carbon-energy relationships, thereby supporting sustainable energy development and low-carbon economic goals. Simultaneously, this paper provides insights for enhancing carbon markets in emerging markets like China.

BackgroundIsocitrate dehydrogenase-wildtype glioblastoma (IDH-wildtype GBM) and IDH-mutant astrocytoma have distinct biological behaviors and clinical outcomes. The location of brain tumors is closely associated not only with clinical symptoms and prognosis but also with key molecular alterations such as IDH. Therefore, we hypothesize that the key brain regions influencing the prognosis of glioblastoma and astrocytoma are likely to differ. This study aims to (1) identify specific regions that are associated with the Karnofsky Performance Scale (KPS) or overall survival (OS) in IDH-wildtype GBM and IDH-mutant astrocytoma and (2) test whether the involvement of these regions could act as a prognostic indicator.MethodsA total of 111 patients with IDH-wildtype GBM and 78 patients with IDH-mutant astrocytoma from the Cancer Imaging Archive database were included in the study. Voxel-based lesion-symptom mapping (VLSM) was used to identify key brain areas for lower KPS and shorter OS. Next, we analyzed the structural and cognitive dysfunction associated with these regions. The survival analysis was carried out using Kaplan–Meier survival curves. Another 72 GBM patients and 48 astrocytoma patients from Harbin Medical University Cancer Hospital were used as a validation cohort.ResultsTumors located in the insular cortex, parahippocampal gyrus, and middle and superior temporal gyrus of the left hemisphere tended to lead to lower KPS and shorter OS in IDH-wildtype GBM. The regions that were significantly correlated with lower KPS in IDH-mutant astrocytoma included the subcallosal cortex and cingulate gyrus. These regions were associated with diverse structural and cognitive impairments. The involvement of these regions was an independent predictor for shorter survival in both GBM and astrocytoma.ConclusionThis study identified the specific regions that were significantly associated with OS or KPS in glioma. The results may help neurosurgeons evaluate patient survival before surgery and understand the pathogenic mechanisms of glioma in depth.

Abstract Background Sugammadex has been reported to lower the incidence of postoperative residual neuromuscular blockade. Despite the advantages, until recently the effects of sugammadex on postoperative pulmonary complications (PPCs) were controversial. We conducted a systematic review and meta-analysis to determine whether reversal with sugammadex was associated with a lower risk of PPCs compared with neostigmine. Methods PubMed, Embase, and Cochrane Central Register of Controlled Trials were searched from inception to May 2022. Randomized controlled trials (RCTs) and observational studies comparing PPCs in patients receiving sugammadex or neostigmine as reversal agent at the end of surgery were included. The primary outcomes focused on PPCs including desaturation, pneumonia, atelectasis, noninvasive ventilation (NIV) and reintubation. Trial sequential analysis was performed on the primary outcomes to confirm whether firm evidence was reached. Results Meta-analysis of included studies showed that the rate of desaturation (43.2% vs 45.0%, RR = 0.82; 95% CI 0.63 to 1.05; p = 0.11) were comparable between the two groups. When looking at other primary outcomes, significantly lower risk of pneumonia (1.37% vs 2.45%, RR = 0.65; 95% CI 0.49 to 0.85; p = 0.002), atelectasis (24.6% vs 30.4%, RR = 0.64; 95% CI 0.42 to 0.98; p = 0.04), NIV (1.37% vs 2.33%, RR = 0.65; 95% CI 0.43 to 0.98; p = 0.04) and reintubation (0.99% vs 1.65%, RR = 0.62; 95% CI 0.43 to 0.91; p = 0.01) in the sugammadex group were detected compared with the neostigmine group. Conclusions We concluded that sugammadex is more effective at reducing the incidence of PPCs including pneumonia, atelectasis, NIV and reintubation compared with neostigmine. Further evidence, preferably from RCTs, is required to confirm these findings.

Abstract Achieving controllable fine-tuning of defects in catalysts at the atomic level has become a zealous pursuit in catalysis-related fields. However, the generation of defects is quite random, and their flexible manipulation lacks theoretical basis. Herein, we present a facile and highly controllable thermal tuning strategy that enables fine control of nanodefects via subtle manipulation of atomic/lattice arrangements in electrocatalysts. Such thermal tuning endows common carbon materials with record high efficiency in electrocatalytic degradation of pollutants. Systematic characterization and calculations demonstrate that an optimal thermal tuning can bring about enhanced electrocatalytic efficiency by manipulating the N-centered annulation–volatilization reactions and C-based sp 3/sp 2 configuration alteration. Benefiting from this tuning strategy, the optimized electrocatalytic anodic membrane successfully achieves >99% pollutant (propranolol) degradation during a flow-through (~2.5 s for contact time), high-flux (424.5 L m−2 h−1), and long-term (>720 min) electrocatalytic filtration test at a very low energy consumption (0.029 ± 0.010 kWh m−3 order−1). Our findings highlight a controllable preparation approach of catalysts while also elucidating the molecular level mechanisms involved.

Abstract Intense debate persists about the timing and magnitude of the wet phases in the East Asia deserts since the late Pleistocene. Here we show reconstructions of the paleohydrology of the East Gobi Desert since the last interglacial using satellite images and digital elevation models (DEM) combined with detailed section analyses. Paleolakes with a total area of 15,500 km2 during Marine Isotope Stage 5 (MIS 5) were identified. This expanded lake system was likely coupled to an 800–1000 km northward expansion of the humid region in East China, associated with much warmer winters. Humid climate across the Gobi Desert during MIS 5 likely resulted in a dustier MIS 4 over East Asia and the North Pacific. A second wet period characterized by an expanded, albeit smaller, lake area is dated to the mid-Holocene. Our results suggest that the East Asian Summer Monsoon (EASM) might have been much weaker during MIS 3.

Recently, numerous spatial prediction methods with diverse characteristics have been developed. Selecting an appropriate spatial prediction method, along with its data preprocessing and parameter settings, presents a challenging task for many users, especially for non-experts. This paper addresses this challenge by exploring the potential of automated machine learning method proposed in artificial intelligent domain to automatically determine the most suitable method among various machine learning methods. As a case study, the automated machine learning method was applied to predict the spatial distribution of soil subgroups in Heshan farm. A total of 110 soil samples and 10 terrain variables were utilized in the designed experiments. To evaluate the performance, the proposed method was compared to each machine learning method with default parameters values or parameters determined by expert knowledge. The results showed that the proposed method typically achieved higher accuracy scores than the two alternative methods. This suggests that automated machine learning performs effectively in scenarios where numerous machine learning methods are available and offers practical utility in reducing the dependence on users’ expertise in spatial prediction. However, a more robust automated framework should be developed to encompass a broader range of spatial prediction methods, such as spatial statistic methods, rather than only focusing on machine learning methods.

Objective Dual-energy computed tomography (DECT) imaging technology opens a new idea and method for analyzing stone composition, which can obtain several quantitative parameters reflecting tissue-related information and energy images different from traditional images. However, the application of DECT in diagnosing urinary calculi remains unknown. This study aims to evaluate the value of DECT in diagnosing urinary calculi by meta-analysis. Methods PubMed, EMBASE, Web of Science, and the Cochrane Library were searched to articles published from the establishment of the databases to April 18, 2023. We reviewed the articles on the diagnosis of urinary calculi detected by DECT, established standards, screened the articles, and extracted data. Two researchers carried out data extraction and the Cohen’s unweighted kappa was estimated for inter-investigator reliability. The quality of the literature was evaluated by the diagnostic test accuracy quality evaluation tool (QUADAS-2). The heterogeneity and threshold effects were analyzed by Meta-Disc 1.4 software, and the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic ratio were calculated. The combined receiver-operating characteristic (ROC) curve was drawn, and the value of DECT in the diagnosis of urinary calculi was evaluated by the area under the curve (AUC). The meta-analysis was registered at PROSPERO (CRD42023418204). Results One thousand and twenty-seven stones were detected in 1,223 samples from 10 diagnostic tests. The analyzed kappa alternated between 0.78-0.85 for the document’s retrieval and detection procedure. The sensitivity of DECT in the diagnosis of urinary calculi was 0.94 (95% CI [0.92–0.96]). The positive likelihood ratio (PLR) of DECT in the diagnosis of urinary stones was 0.91 (95% CI [0.88–0.94]), and the negative likelihood ratio (NLR) was 0.08 (95% CI [0.05–0.11]). The specificity of DECT for detecting urinary calculi was 0.91 (95% CI [0.88–0.94]). The area under the curve of the summary receiver operator characteristic (SROC) was 0.9875. The sensitivity of dual-energy CT in the diagnosis of urinary calculi diameter

Fiscal decentralization, widely believed to be one essential tool to boost economic growth, is typically presented as something that works for developed countries. However, this needs to be investigated, which is what this paper aims to do. This paper investigates the relationship between fiscal decentralization and economic growth, specifically focusing on its applicability in both developed and developing countries. Using cross-sectional data from 23 African and 23 OECD countries, we employ two-stage estimation methods, including two-stage least squares (2SLS), Generalized Method of Moments (GMM), and Limited Information Maximum Likelihood (LIML), to address concerns related to endogeneity. The inclusion of instruments representing country size, ethnoreligious diversity, and administrative structure enhances the analysis. The dependent variable is based on average values for the five-year period between 2015 and 2019, while the explanatory variables are derived from data in 2017, representing the midpoint of the 2013–2021 period. The results highlight the effectiveness of the 2SLS method in estimating the relationship between fiscal decentralization, control variables, instrument variables, and per capita GDP. Empirical findings indicate significant positive impacts of both expenditure decentralization and revenue decentralization on per capita GDP, holding true for both developed and developing countries, with a slightly stronger effect observed in the latter. These results underscore the potential benefits of fiscal decentralization across diverse economies and offer valuable insights for policymakers.The study uses cross-sectional data from 23 African and 23 OECD countries and applies two-stage estimation methods to effectively address the endogeneity issue in the modeling. A variety of such methods in two-stage least squares (2SLS), Generalized Method of Moments (GMM), and Limited Information Maximum Likelihood (LIML) are applied and compared against the ordinary least squares (OLS) method. Variables that represent the size, the ethnoreligious diversity and the type of administrative structure of the countries are employed as instruments. The 2SLS method proved to excellently estimate the relationship between the fiscal decentralization terms as well as other control and instrument variables and the per capita GDP. The findings from the empirical analysis showed that both expenditure decentralization and revenue decentralization have significant positive impacts on per capita GDP of a country. This relationship holds not only for developed countries but also for developing ones, even to a slightly better degree in the latter.

Abstract Background Prior studies have reported conflicting results on the effect of sugammadex on postoperative pulmonary complications (PPCs) and research on this topic in transapical-transcatheter aortic valve implantation (TA-TAVI) was sparse. The current study aimed to investigate whether there were differences in the incidence of PPCs between two muscle relaxant strategies (rocuronium/sugammadex vs. cisatracurium/neostigmine) in patients undergoing TA-TAVI. Methods This retrospective observational study enrolled 245 adult patients underwent TA-TAVI between October 2018 and January 2021. The patients were grouped according to the type of muscle relaxant strategies (115 with rocuronium/sugammadex in the R/S group and 130 with cisatracurium/neostigmine in the C/N group, respectively). Pre- and intraoperative variables were managed by propensity score match (PSM) at a 1:2 ratio. PPCs (i.e., respiratory infection, pleural effusion, pneumothorax, atelectasis, respiratory failure, bronchospasm and aspiration pneumonitis) were evaluated from the radiological and laboratory findings. Results After PSM, 91 patients in the R/S group were selected and matched to 112 patients in the C/N group. Patients in the R/S group showed lower PPCs rate (45.1% vs. 61.6%, p = 0.019) compared to the C/N group. In addition, the R/S group showed significant shorter extubation time (7.2 ± 6.2 vs. 10.3 ± 8.2 min, p = 0.003) and length of hospital stay (6.9 ± 3.3 vs. 8.0 ± 4.0 days, p = 0.034). Conclusion The rocuronium/sugammadex muscle relaxant strategy decreases the incidence of PPCs in patients undergoing TA-TAVI when compared to cisatracurium/neostigmine strategy. Trial registration ChiCTR, ChiCTR2100044269. Registered March 14, 2021-Prospectively registered, http://www.Chictr.org.cn .

Cell misuse and cross-contamination can affect the accuracy of cell research results and result in wasted time, manpower and material resources. Thus, cell line identification is important and necessary. At present, the commonly used cell line identification methods need cell staining and culturing. There is therefore a need to develop a new method for the rapid and automated identification of cell lines. Raman spectroscopy has become one of the emerging techniques in the field of microbial identification, with the advantages of being rapid and noninvasive and providing molecular information for biological samples, which is beneficial in the identification of cell lines. In this study, we built a library of Raman spectra for gastric mucosal epithelial cell lines GES-1 and gastric cancer cell lines, such as AGS, BGC-823, HGC-27, MKN-45, MKN-74 and SNU-16. Five spectral datasets were constructed using spectral data and included the full spectrum, fingerprint region, high-wavelength number region and Raman background of Raman spectra. A stacking ensemble learning model, SL-Raman, was built for different datasets, and gastric cancer cell identification was achieved. For the gastric cancer cells we studied, the differentiation accuracy of SL-Raman was 100% for one of the gastric cancer cells and 100% for six of the gastric cancer cells. Additionally, the separation accuracy for two gastric cancer cells with different degrees of differentiation was 100%. These results demonstrate that Raman spectroscopy combined with SL-Raman may be a new method for the rapid and accurate identification of gastric cancer. In addition, the accuracy of 94.38% for classifying Raman spectral background data using machine learning demonstrates that the Raman spectral background contains some useful spectral features. These data have been overlooked in previous studies.

Abstract The pathogenesis of depression involves cAMP-response element binding protein1 (CREB1) and metabotropic glutamate receptor 7 (GRM7), and their genetic polymorphisms may affect susceptibility to depression. The purpose of this study was to investigate whether the CREB1 polymorphisms rs2253206 and rs10932201 and the GRM7 polymorphism rs162209 are associated with the risk of depression. Using polymerase chain reaction-restriction fragment length polymorphism and DNA sequencing, we analyzed the rs2253206, rs10932201, and rs162209 frequencies in 479 patients with depression and 329 normal controls. The results showed that the rs2253206 and rs10932201 polymorphisms were significantly associated with an increased risk of depression. However, no association was found between rs162209 and depression risk. When the data were stratified for several disease-related variables, none of the three polymorphisms were found to be correlated to onset, disease severity, family history, or suicidal tendency. Thus, the present findings indicate that the CREB1 polymorphisms rs2253206 and rs10932201 may be related to the occurrence of depression.

Abstract Background Valvular heart disease remains common in both developed and developing countries, and it requires timely surgical treatment when necessary. However, the stability of hemodynamics during anesthesia induction in patients undergoing valve replacement surgery is difficult to maintain due to their impaired cardiac function. Remimazolam, a novel and ultrashort-acting intravenous sedative-hypnotic, may be beneficial to stable hemodynamics, but the evidence is limited. Therefore, this study aims to evaluate the effect of remimazolam induction on hemodynamics compared with midazolam and etomidate in patients undergoing valve replacement surgery. Methods This is a prospective, multicenter randomized controlled trial (RCT). Three hundred and sixty-three non-obese adult patients aged 45 to 80 years old undergoing valve surgery with cardiopulmonary bypass will be randomly allocated to receive remimazolam tosilate, midazolam, or etomidate during anesthetic induction. The primary outcome is the incidence of hypotension within 20 min after the administration of investigated drugs. The hypotension is defined as systolic blood pressure (SBP)

In order to study the optimal curing process of large yellow croaker roe, the effect of salt type, salt addition, curing time and curing temperature on the chloride content, volatile salt nitrogen (TVB-N) content, moisture, the total number of colonies, color, texture and sensory evaluation of cured large yellow croaker roe was investigated. On this basis, the curing process of large yellow croaker roe was optimized by response surface methodology with sensory evaluation and large yellow croaker roe as response values. The results showed that the TVB-N content and the total number of colonies of cured large yellow croaker roe with fine salt were lower than those cured with coarse salt. At 10% salt addition, L* value was the highest, and the sensory quality was better. At the curing temperature of 5 ℃, the hardness and chewiness were suitable, and the total number of colonies conformed to relevant standard. When curing for 55 d, the total number of colonies was lower and the sensory evaluation score was the highest. The best process for curing large yellow croaker roe was as follows: The salt addition was 10.69%, the curing temperature was 5.0 ℃, and the curing time was 55.51 d. Under this condition, the sensory score of cured large yellow croaker roe was 82.50 and the total number of colonies was 5.32 lg CFU/g. The obtained cured large yellow croaker roe products had good edible quality.

Litopenaeus vannamei easily blackens during cold storage. To inhibit blackening and improve the storage quality of prawns, in this study, konjac glucomman (KGM)-epigallocatechin gallate (EGCG) topological microgel was formed and used for storage and preservation of prawns to improve their antioxidant properties. The effect of KGM-EGCG topological microgel on inhibiting shrimp blackening was studied by measuring the sensory evaluation score, pH value, TVB-N value, K value, PPO activity, and the effect of changes in the total number of bacteria of KGM-EGCG-treated prawns during storage. SEM and FTIR results showed that during the KGM-EGCG binding process, the number of hydrogen bond connections and the intermolecular force increased. Results also showed that the KGM microgel can effectively embed EGCG and enhance its stability to achieve a better controlled release effect. Compared with the EGCG group and untreated group, KGM-EGCG microgel has better anti-PPO activity and can better maintain the organoleptic quality and inhibit bacterial growth of Litopenaeus vannamei. Therefore, the KGM-EGCG microgel could slow down the increase in pH value, the production of volatile base nitrogen, and the increase in K value, and effectively extend the shelf life of Litopenaeus vannamei from 3 d to 6 d, providing a theoretical basis for the research of KGM functional gel and a reference for the deep processing and value enhancement of green tea and shrimp.

Abstract Background Calcineurin B-like proteins (CBLs) are ubiquitous Ca2+ sensors that mediate plant responses to various stress and developmental processes by interacting with CBL-interacting protein kinases (CIPKs). CBLs and CIPKs play essential roles in acclimatization of crop plants. However, evolution of these two gene families in the genus Medicago is poorly understood. Results A total of 68 CBL and 135 CIPK genes have been identified in five genomes from Medicago. Among these genomes, the gene number of CBLs and CIPKs shows no significant difference at the haploid genome level. Phylogenetic and comprehensive characteristic analyses reveal that CBLs and CIPKs are classified into four clades respectively, which is validated by distribution of conserved motifs. The synteny analysis indicates that the whole genome duplication events (WGDs) have contributed to the expansion of both families. Expression analysis demonstrates that two MsCBLs and three MsCIPKs are specifically expressed in roots, mature leaves, developing flowers and nitrogen fixing nodules of Medicago sativa spp. sativa, the widely grown tetraploid species. In particular, the expression of these five genes was highly up-regulated in roots when exposed to salt and drought stress, indicating crucial roles in stress responses. Conclusions Our study leads to a comprehensive understanding of evolution of CBL and CIPK gene families in Medicago, but also provides a rich resource to further address the functions of CBL-CIPK complexes in cultivated species and their closely related wild relatives.

Three mononuclear copper(II) and nickel(II) complexes, [Cu(L1)(NCS)(CH3OH)] (1), [Cu(L2)(NCS)] (2) and [Ni(L2)(N3)] (3), where L1 and L2 are the monoanionic forms of the Schiff bases N'-(pyridin-2-ylmethylene)picolinohydrazide (HL1) and 4-methyl-2-(((pyridin-2-ylmethyl)imino)methyl)phenol (HL2), have been prepared and characterized by elemental analysis, IR and UV-Vis spectroscopy, as well as single crystal X-ray diffraction studies. The Cu atom in complex 1 is in a square pyramidal coordination, with the three N atoms of the ligand L and the N atom of the thiocyanate ligand in the basal plane, and with the methanol O atom at the apical position. The Cu and Ni atoms in complexes 2 and 3 are in square planar coordination, with the three donor atoms of the Schiff base ligands and the terminal N atoms of thiocyanate and azide ligands. Complexes 1 and 2 inhibit the Jack bean urease with IC50 value of 0.33±0.12 and 0.39±0.10 μmol L–1, respectively. Molecular docking study was performed to investigate the interaction between the complexes and the enzyme.

BackgroundHow volatile anesthetics work remains poorly understood. Modulations of synaptic neurotransmission are the direct cellular mechanisms of volatile anesthetics in the central nervous system. Volatile anesthetics such as isoflurane may reduce neuronal interaction by differentially inhibiting neurotransmission between GABAergic and glutamatergic synapses. Presynaptic voltage-dependent sodium channels (Nav), which are strictly coupled with synaptic vesicle exocytosis, are inhibited by volatile anesthetics and may contribute to the selectivity of isoflurane between GABAergic and glutamatergic synapses. However, it is still unknown how isoflurane at clinical concentrations differentially modulates Nav currents between excitatory and inhibitory neurons at the tissue level.MethodsIn this study, an electrophysiological recording was applied in cortex slices to investigate the effects of isoflurane on Nav between parvalbumin (PV+) and pyramidal neurons in PV-cre-tdTomato and/or vglut2-cre-tdTomato mice.ResultsIsoflurane at clinically relevant concentrations produced a hyperpolarizing shift in the voltage-dependent inactivation and slowed the recovery time from the fast inactivation in both cellular subtypes. Since the voltage of half-maximal inactivation was significantly depolarized in PV+ neurons compared to that of pyramidal neurons, isoflurane inhibited the peak Nav currents in pyramidal neurons more potently than those of PV+ neurons (35.95 ± 13.32% vs. 19.24 ± 16.04%, P = 0.036 by the Mann-Whitney test).ConclusionsIsoflurane differentially inhibits Nav currents between pyramidal and PV+ neurons in the prefrontal cortex, which may contribute to the preferential suppression of glutamate release over GABA release, resulting in the net depression of excitatory-inhibitory circuits in the prefrontal cortex.