Search

The fibroblast growth factor receptor (FGFR) is a crucial receptor tyrosine kinase involved in essential biological processes, including growth, development, and tissue repair. However, FGFR gene mutations, including amplification, fusion, and mutation, can disrupt epigenetics, transcriptional regulation, and tumor microenvironment interactions, leading to cancer development. Targeting these kinase mutations with small molecule drugs or antibodies has shown clinical benefits. For example, erdafitinib is approved for treating locally advanced or metastatic urothelial cancer patients with FGFR2/FGFR3 mutations, and pemigatinib is approved for treating cholangiocarcinoma with FGFR2 fusion/rearrangement. Effective screening of FGFR variant patients is crucial for the clinical application of FGFR inhibitors. Various detection methods, such as polymerase chain reaction, next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry, are available, and their selection should be based on diagnostic and treatment decision-making needs. Our developed expert consensus aims to standardize the diagnosis and treatment process for FGFR gene mutations and facilitate the practical application of FGFR inhibitors in clinical practice.

Abstract Background Circular RNAs (circRNAs) are highly stable regulators, often accumulated in mammalian brains and thought to serve as “memory molecules” that govern the long process of aging. Mounting evidence demonstrated circRNA dysregulation in the brains of Alzheimer’s disease (AD) patients. However, whether and how circRNA dysregulation underlies AD progression remains unexplored. Methods We combined Poly(A)-tailing/RNase R digestion experimental approach with CARP, our published computational framework using pseudo-reference alignment for more sensitive and accurate circRNA detection to identify genome-wide circRNA dysregulation and their downstream pathways in the 5xFAD mouse cerebral cortex between 5 and 7 months of age, a critical window marks the transition from reversible to irreversible pathogenic progression. Dysregulated circRNAs and pathways associated with disease progression in 5xFAD cortex were systematically compared with circRNAs affected in postmortem subcortical areas of a large human AD cohort. A top-ranked circRNA conserved and commonly affected in AD patients and 5xFAD mice was depleted in cultured cells to examine AD-relevant molecular and cellular changes. Results We discovered genome-wide circRNA alterations specifically in 5xFAD cortex associated with AD progression, many of which are commonly dysregulated in the subcortical areas of AD patients. Among these circRNAs, circGigyf2 is highly conserved and showed the highest net reduction specifically in the 7-month 5xFAD cortex. CircGIGYF2 level in AD patients’ cortices negatively correlated with dementia severity. Mechanistically, we found multiple AD-affected splicing factors that are essential for circGigyf2 biogenesis. Functionally, we identified and experimentally validated the conserved roles of circGigyf2 in sponging AD-relevant miRNAs and AD-associated RNA binding proteins (RBPs), including the cleavage and polyadenylation factor 6 (CPSF6). Moreover, circGigyf2 downregulation in AD promoted silencing activities of its sponged miRNAs and enhanced polyadenylation site processing efficiency of CPSF6 targets. Furthermore, circGigyf2 depletion in a mouse neuronal cell line dysregulated circGigyf2-miRNA and circGigyf2-CPSF6 axes and potentiated apoptotic responses upon insults, which strongly support the causative roles of circGigyf2 deficiency in AD neurodegeneration. Conclusions Together, our results unveiled brain circRNAs associated with irreversible disease progression in an AD mouse model that is also affected in AD patients and identified novel molecular mechanisms underlying the dysregulation of conserved circRNA pathways contributing to AD pathogenesis.

Abstract Background Recent research has demonstrated that the use of artificial intelligence (AI) in radiotherapy (RT) has significantly streamlined the process for physicians to treat patients with tumors; however, bibliometric studies examining the correlation between AI and RT are not available. Providing a thorough overview of the knowledge structure and research hotspots between AI and RT was the main goal of the current study. Method A search was conducted on the Web of Science Core Collection (WoSCC) database for publications pertaining to AI and RT between 2003 and 2023. VOSviewers, CiteSpace, and the R program “bibliometrix” were used to do the bibliometric analysis. Results The analysis comprised 615 publications from 64 countries, with USA and China leading the pack. Since 2017, there have been more and more publications about RT and AI every year. The research center that made the biggest contribution to this topic was Maastricht University. The most articles published journal in this field was Frontiers in Oncology, while Medical Physics received the greatest number of citations. Dekker Andre is the author with the greatest number of published articles, while Philippe Lambin was the most often co-cited author. In the newly identified research hotspots, “autocontouring algorithm”, “deep learning”, and “machine learning” stand out as the main terms. Conclusion In fact, our bibliometric analysis offers insightful information on current research directions and advancements pertaining to the use of AI in RT. For academics looking to understand the connection between AI and RT, this study is a great resource because it highlights current research frontiers and hot trends.

Abstract Background Observational studies have shown a link between autoimmune diseases and schizophrenia, with conflicting conclusions. Due to the existence of confounding factors, the causal link between autoimmune diseases and schizophrenia is still unknown. Method We conducted a comprehensive Mendelian randomization (MR) analysis of schizophrenia and ten common autoimmune diseases in individuals of European descent using genome-wide association studies (GWASs). To evaluate the relationships between autoimmune diseases and schizophrenia, inverse variance weighted, MR-RAPS, Bayesian weighted MR, constrained maximum likelihood, debiased IVW, MR-Egger, and weighted median were utilized. Several sensitivity analyses were performed to ensure the reliability of the study's results. Results Our findings reveal that genetically predicted ankylosing spondylitis is related to an increased risk of schizophrenia, whereas celiac disease, type 1 diabetes, and systemic lupus erythematosus are associated with a lower risk of schizophrenia. In the reverse MR analysis, our study indicated that genetically predicted schizophrenia is linked to higher risks of ankylosing spondylitis, Crohn's disease, ulcerative colitis, inflammatory bowel disease, and psoriasis. Neither multiple sclerosis nor rheumatoid arthritis have been linked to schizophrenia, and vice versa. Conclusion Despite contradicting some other observational reports, this study showed support for a causal link between autoimmune diseases and schizophrenia. To gain a better understanding of the mechanisms underlying the development of immune-mediated schizophrenia, additional research is required to identify potential mechanisms identified in observational studies.

Abstract This study aimed to identify predictive factors for the prognosis of acute-on-chronic liver disease (AoCLD) due to both hepatitis B virus (HBV) and alcohol and to develop prognostic models to improve treatment management. AoCLD patients with HBV and alcohol as etiological factors were selected from two multicenter prospective cohorts (NCT02457637,NCT03641872) and included in separate training and validation cohorts (n = 180 and n = 148). In the training cohort, the CATCH-LIFE A nomogram (based on age, bilirubin, international normalized ratio, serum sodium, and hepatic encephalopathy score) and CATCH-LIFE B nomogram (based on age, bilirubin, international normalized ratio, serum albumin, white blood cell, platelet count, and hepatic encephalopathy score) had discriminatory ability for predicting 28-day (c-indexes of 0.910 and 0.899) and 90-day mortality (c-indexes of 0.878 and 0.887, respectively). The area under the curve values for 28-day and 90-day mortality prediction by the CATCH-LIFE A nomogram were 0.922 (95% CI : 0.874, 0.971) and 0.905 (0.856, 0.956), respectively, while those for the CATCH-LIFE B nomogram were 0.916(0.861,0.972) and 0.915 (0.866,0.964), respectively. Similar performance results were observed in the validation cohort. Optimal cut-off scores for each nomogram could be used for patient stratification in high- and low-risk groups, and the high-risk groups showed shorter survival times than the low-risk groups in both the training and validation cohorts. Two nomograms constructed from the first short-term follow-up data from patients with AoCLD due to combined HBV infection and alcohol exposure showed good predictive performance for 28-day and 90-day mortality and might be used to guide clinical management.

Abstract Background The primary objective of this investigation was to compare the nominal central ablation depth with the achieved central corneal stromal ablation depth after StreamLight transepithelial photorefractive keratectomy (tPRK) for myopia with WaveLight® laser by Alcon Laboratories, TX, USA. Methods This ambispective study encompassed a retrospective analysis of 40 eyes who underwent treatment for myopia and astigmatism, followed by a prospective examination conducted 6–9 months postoperatively. Pre- and postoperative Avanti spectral-domain optical coherence tomography (SD-OCT; Optovue Inc., CA, USA) provided stromal and epithelial thickness maps. The difference between pre- and postoperative central stromal thicknesses at the corneal vertex was used to calculate the achieved stromal thickness ablation depth. This value was then compared with the corresponding central nominal depth on the laser ablation planning map. Results A total of 40 eyes (OD/OS:18/22) of 40 patients (31.4 ± 9.2 years) were available for evaluation. The mean treated spherical equivalent was − 2.98 ± 1.46 D. The mean nominal and achieved central stromal ablation depths were 51.22 µm and 59.67 μm, respectively, showing a mean stromal excessive ablation of 16.50%. The mean pre- and postoperative central epithelial thicknesses were 53.74 μm and 59.31 μm, respectively, showing a mean postoperative thickness increase of 10.46%. This increase in the epithelial thickness rendered the mean postoperative pachymetry reduction to 54.11 μm, only 2.33% greater than the mean nominal ablation depth. Conclusions The study revealed a central stromal ablation 16.50% greater than the nominal ablation depth. This excessive stromal removal was largely compensated for by the increase in epithelial thickness, resulting in a mean difference between the nominal ablation depth and the achieved central corneal pachymetry reduction of only 2.33%. This significant excessive central stromal ablation must be taken into consideration in the calculation of the residual stromal thickness.

Abstract Objective The study aims to explore the relationship between modifiable lifestyle factors (physical activity, sedentary time, body composition, muscle strength) and mental health, and predict future changes in mental health. Methods A cross-sectional survey was conducted on 133 men (age: 29.03 ± 6.605 years, BMI: 23.58 ± 2.688 kg/m²) to assess baseline body composition, muscle strength, sedentary time, and mental health, with follow-up at 3 months. F-tests were employed to compare the differences in mental health on sedentary time and body composition variables. Spearman correlation analysis was used to examine correlations between variables. Results Spearman’s correlation analysis showed that sedentary time, muscle strength and mental health of the subjects were significantly correlated. BMI, BFM, BFMI, PBF were higher in subjects with ≥ 4 h of sedentary time than in the other two shorter sedentary time groups. Subjects with higher PBF (p = 0.047, η 2 = 0.030) and BFM (p = 0.032, η 2 = 0.035) had severer depression. Subjects who sat for ≥ 4 h at a time were more severely depressed than those who sat for 2–4 h (p = 0.020). Change in depression was significantly negatively correlated with BMI, BFM, BFMI and PBF. Subjects with higher PBF (p = 0.023, η 2 = 0.050) and BFM (p = 0.005, η 2 = 0.075) at the baseline had less change in depression. Conclusion A Significant correlation was found between sedentary time, body composition and mental health, and baseline body composition predicted changes in mood three months later.

Abstract Understanding the mechanisms controlling forest carbon accumulation is crucial for predicting and mitigating future climate change. Yet, it remains unclear whether the dominance of ectomycorrhizal (EcM) trees influences the carbon accumulation of entire forests. In this study, we analyzed forest inventory data from over 4000 forest plots across Northeast China. We find that EcM tree dominance consistently exerts a positive effect on tree, soil, and forest carbon stocks. Moreover, we observe that these positive effects are more pronounced during unfavorable climate conditions, at lower tree species richness, and during early successional stages. This underscores the potential of increasing the dominance of native EcM tree species not only to enhance carbon stocks but also to bolster resilience against climate change in high-latitude forests. Here we show that forest managers can make informed decisions to optimize carbon accumulation by considering various factors such as mycorrhizal types, climate, successional stages, and species richness.

Abstract Soybean is a major source of protein and edible oil worldwide. Originating from the Huang-Huai-Hai region, which has a temperate climate, soybean has adapted to a wide latitudinal gradient across China. However, the genetic mechanisms responsible for the widespread latitudinal adaptation in soybean, as well as the genetic basis, adaptive differentiation, and evolutionary implications of theses natural alleles, are currently lacking in comprehensive understanding. In this study, we examined the genetic variations of fourteen major gene loci controlling flowering and maturity in 103 wild species, 1048 landraces, and 1747 cultivated species. We found that E1, E3, FT2a, J, Tof11, Tof16, and Tof18 were favoured during soybean improvement and selection, which explained 75.5% of the flowering time phenotypic variation. These genetic variation was significantly associated with differences in latitude via the LFMM algorithm. Haplotype network and geographic distribution analysis suggested that gene combinations were associated with flowering time diversity contributed to the expansion of soybean, with more HapA clustering together when soybean moved to latitudes beyond 35°N. The geographical evolution model was developed to accurately predict the suitable planting zone for soybean varieties. Collectively, by integrating knowledge from genomics and haplotype classification, it was revealed that distinct gene combinations improve the adaptation of cultivated soybeans to different latitudes. This study provides insight into the genetic basis underlying the environmental adaptation of soybean accessions, which could contribute to a better understanding of the domestication history of soybean and facilitate soybean climate-smart molecular breeding for various environments.

Abstract Despite the promise of cold atmospheric plasma (CAP) for cancer treatment, the challenges associated with the treatment of solid tumors and penetration depth limitations remain, restricting its clinical application. Here, biological evidence is provided that the killing effect of CAP treatment is confined to less than 500 µm subcutaneously and the actual biological dose decreased gradually with depth for the first time, indicating that the limited penetration depth has become an urgent problem that demands immediate solutions. Significantly, it is showed that different from high‐dose treatments, CAP decreased the doses to the low‐dose range but still exhibited anti‐tumor effects via mitotic catastrophe. Unlike radiotherapy or chemotherapy, low‐dose CAP treatment induces mitochondrial structural damage and dysfunction, disrupts energy metabolism and redox balance, and results in mitotic catastrophe. Collectively, these findings suggest that better understanding and taking full advantage of the dose‐response gradient effect of CAP is a potential strategy to prompt its clinical application beyond improving CAP penetration.

ABSTRACT Tuberculosis (TB) remains a major global health problem, and there is an urgent need for rapid, sensitive, and easy-to-use diagnostic technologies to improve TB diagnosis. In this study, we developed the nested multi-enzyme isothermal rapid amplification (nestMIRA) assay for TB. We designed several pairs of primers and probes targeting the IS6110 sequence of Mycobacterium tuberculosis (Mtb) and performed combinatorial testing to optimize the performance of the TB nestMIRA assay. The reaction can be performed at a constant temperature of approximately 40°C and completed within 30 minutes in the same tube without opening the central cap. There has been no cross-reactivity with common non-tuberculous mycobacteria (NTB) and respiratory pathogens. The TB nestMIRA assay has a minimum detection limit of 5 copies/μL for H37Rv genomic DNA and a limit of quantification of 100 CFU/ml. To test the diagnostic performance of the TB nestMIRA assay, we conducted a 163-person clinical cohort study using comprehensive reference standards as the gold standard for clinical diagnosis. Our study showed that TB nestMIRA performed slightly better than GeneXpert MTB/RIF (Xpert) (85.27% vs. 82.17%) and significantly better than culture (55.81%) and acid-fast bacillus (AFB) smear (38.76%). The TB nestMIRA assay offers speed, specificity, sensitivity, and convenience. We believe that it has the potential to be a rapid alternative for TB diagnosis, particularly in resource-limited settings.IMPORTANCEIn this study, we have successfully developed a method called nested multi-enzyme isothermal rapid amplification (nestMIRA) for the detection of Mycobacterium tuberculosis (Mtb). This method involves a two-step thermostatic amplification process in the same tube and can be read using fluorescence and lateral flow dipstick (LFD) assays. It is known to be rapid, specific, and highly sensitive. Our method has shown promising results in the detection of clinical specimens, and we believe that it can be a valuable tool for the rapid detection of Mtb in a clinical setting.

Lately, the ongoing issue of haze pollution in multiple cities across China has had a profound impact on the residents’ wellbeing and overall health. The urgent necessity to address haze pollution is undeniable. Meanwhile, the rapidly evolving digital economy has sprung up as a pivotal driver for China’s economic growth, providing innovative approach to tackle haze pollution. This research explores the impact of the digital economy on haze pollution through utilizing the big data pilot zone as a quasi-natural experiment. Panel data from 280 prefecture-level cities in China is adopted, covering the period from 2011 through 2020. This analysis incorporates various models, namely, difference-in-differences model (DID), mediation effect model, and difference-in-differences spatial Durbin model. The findings highlight the substantial contributions of digital economy in alleviating haze pollution. Furthermore, these findings hold true even after a series of rigorous robustness checks. The constraint influence of the digital economy on haze pollution is particularly prominent in metropolitan areas, cities with elevated administrative levels, primary environmental protection cities, as well as economically developed cities. Financial development and technological innovation serve as important mechanisms through which the digital economy suppresses haze pollution. After accounting for spatial factors, the digital economy exhibits consequential spillover effects, leading to substantial inhibition of haze pollution in surrounding cities as well as locally. The novel aspects of this paper are as follows: Firstly, it regards the establishment of big data experimental zones as the exogenous policy shock of digital economy and employs a multi period DID model to evaluate the impact of the digital economy on haze pollution. Secondly, it explores the transmission pathways through which the digital economy affects haze pollution from the perspectives of financial development and technological innovation. Thirdly, it investigates the heterogeneous characteristics of the impact of the digital economy on haze pollution. Fourthly, it examines the spatial spillover effects of the digital economy on haze pollution from the perspective of spatial econometrics.

Abstract Radiotherapy (RT) is often administered, either alone or in combination with other therapies, for most malignancies. However, the degree of tumor oxygenation, damage to adjacent healthy tissues, and inaccurate guidance remain issues that result in discontinuation or failure of RT. Here, a multifunctional therapeutic platform based on Ir@WO3−x is developed which simultaneously addresses these critical issues above for precision radiosensitization. Ir@WO3−x nanoreactors exhibit strong absorption of X‐ray, acting as radiosensitizers. Moreover, ultrasmall Ir enzyme‐mimic nanocrystals (NCs) are decorated onto the surface of the nanoreactor, where NCs have catalyst‐like activity and are sensitive to H2O2 in the tumor microenvironment (TME) under near infrared‐II (NIR‐II) light stimulation. They efficiently catalyze the conversion of H2O2 to O2, thereby ameliorating hypoxia, inhibiting the expression of HIF‐1α, and enhancing RT‐induced DNA damage in cancerous tissue, further improving the efficiency of RT. Additionally, in response to high H2O2 levels in TME, the Ir@WO3−x nanoreactor also exerts peroxidase‐like activity, boosting exogenous ROS, which increases oxidative damage and enhances ROS‐dependent death signaling. Furthermore, Ir@WO3−x can serve as a high‐quality computed tomography contrast agent due to its high X‐ray attenuation coefficient and generation of pronounced tumor‐tissue contrast. This report highlights the potential of advanced health materials to enhance precision therapeutic modalities.

BackgroundPer- and poly-fluoroalkyl substances (PFAS) are a class of emerging persistent organic pollutants, and their negative health impacts have been widely concerned. There is a lack of epidemiological studies on the associations of PFAS exposure with lipid homeostasis. ObjectiveTo investigate the associations of perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) exposure with blood lipid levels and dyslipidemia in middle-aged and elderly women. MethodsThis study was based on 795 middle-aged and elderly women from a female sub-cohort of the Dongfeng-Tongji cohort study, excluding the participants without blood lipid measurements and/or reported use of lipid-lowering drugs at baseline. The concentrations of plasma PFOS and PFOA were measured by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The concentrations of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured using an automatic analyzer. The normally distributed continuous variables were presented as mean ± standard deviation (\begin{document}$ \bar{x}\pm s) $\end{document}, while the skewedly distributed continuous variables were presented as median (M) and the 25th and 75th percentiles (P25, P75). Generalized linear models (GLM), generalized additive models (GAM), and logistic regression models were applied to evaluate the associations of PFOS and PFOA exposure with blood lipid levels and the risk of dyslipidemia. Stratified analyses were also implemented to explore potential modification effects of sociodemographic characteristics, lifestyles, and menopause on associations of PFOS and PFOA exposure and blood lipids. ResultsThe \begin{document}$ \bar{x}\pm s $\end{document} of baseline age for the study participants was (59.4±8.6) years old, and their baseline body mass index (BMI) was (24.3±3.4) kg·m−2. The M (P25, P75) of baseline plasma concentrations for PFOS and PFOA were 9.96 (6.24, 15.09) μg·L−1 and 1.20 (0.84, 1.80) μg·L−1 respectively. The GLM analysis showed that plasma concentration of PFOS was positively associated with serum HDL-C [b (95%CI): 0.04 (0.01, 0.07)]. The plasma concentration of PFOA was also positively associated with serum TC [b (95%CI): 0.05 (0.02, 0.08)] and serum LDL-C [b (95%CI): 0.05 (0.01, 0.09)]. No significant association was observed between plasma PFOS and serum TC, TG, or LDL-C, nor between plasma PFOA and serum TG or HDL-C. The stratified analyses showed that the association between PFOA and LDL-C was significant among the participants aged

Abstract Matching abbreviated names with their full names (full-abbr matching) plays a key role in data integration, address matching, information retrieval, and other fields. Traditional full-abbr matching technology often encounters issues related to near homophones and near homoglyphs. First, a near-homophone full-abbr matching model based on Simbert and VGG was first proposed, which integrates character and speech features, leveraging a speech recognition model and combining a brain-like cognitive learning dual-process mechanism which involves linguistic knowledge and neural network together. Second, to address the problem of near-homoglyph full-abbr matching in Chinese, a DenseNet-based model that fuses glyph structure and image features was proposed, in which statistical feature extractors are employed to extract feature vectors for glyphic features including stroke, Wubi and structural features separately. Lastly, the near-homophone model and the near-homoglyph model are coupled to work together in the full-abbr matching task, in which expert knowledge is used as a component of the feature optimizer. Experimental results showed that the integrated model significantly increased the matching accuracy to 87.5%, demonstrating a 12.3% improvement.

Abstract Background The interrelation between metabolic syndrome (MetS) and Parkinson’s disease (PD) likely arises from shared pathological mechanisms. This study thus aims to examine the impact of MetS and its components on PD. Methods This study utilized data extracted from the National Health and Nutrition Examination Survey database spanning 1999 to 2020. The random forest algorithm was applied to fill in the missing data. Propensity score optimal full matching was conducted. The data were adjusted by total weights derived from both sampling and matching weights. The weighted data were utilized to create multifactor logistic regression models. Odds ratios (ORs) and average marginal effects, along with their corresponding 95% confidence intervals (CIs), were calculated. Results MetS did not significantly affect the risk of PD (OR: 1.01; 95% CI: 0.77, 1.34; P = 0.92). Hypertension elevated the risk of PD (OR: 1.33; 95% CI: 1.01, 1.76; P = 0.045), accompanied by a 0.26% increased probability of PD occurrence (95% CI: 0.01%, 0.52%; P = 0.04). Diabetes mellitus (DM) had a 1.38 times greater likelihood of developing PD (OR:1.38; 95% CI: 1.004, 1.89; P = 0.046), corresponding to a 0.32% increased probability of PD occurrence (95% CI: -0.03%, 0.67%; P = 0.07). Nevertheless, no correlation was observed between hyperlipidemia, waist circumference and PD. Conclusion MetS does not affect PD; however, hypertension and DM significantly increase the risk of PD.

Abstract Background This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians. Methods Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model. Results The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841–0.949) and 0.835 (95%CI: 0.740–0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821–0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP. Conclusion Our model’s good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

The high recurrence rate of cervical cancer is a leading cause of cancer deaths in women. 5-Fluorouracil (5-FU) is an antitumor drug used to treat many types of cancer, but its diminishing effectiveness and side effects limit its use. Norcantharidin (NCTD), a demethylated derivative of cantharidin, exhibits various biological activities. Here, we investigated whether NCTD could potentiate 5-FU to induce cervical cancer cell death. To assess the cell viability and synergistic effects of the drugs, cell counting kit-8 and colony formation assays were performed using HR-HPV-positive cervical cancer cell lines. Annexin V-FITC/PI staining and TUNEL assays were performed to confirm the induction of apoptosis. The synergistic effect of NCTD on the antitumor activity of 5-FU was analyzed using network pharmacology, molecular docking, and molecular dynamics simulations. Apoptosis-related proteins were examined using immunoblotting. The combination of NCTD and 5-FU was synergistic in cervical cancer cell lines. Network pharmacological analysis identified 10 common targets of NCTD and 5-FU for cervical cancer treatment. Molecular docking showed the strong binding affinity of both compounds with CA12, CASP9, and PTGS1. Molecular dynamics simulations showed that the complex system of both drugs with caspase-9 could be in a stable state. NCTD enhanced 5-FU-mediated cytotoxicity by activating apoptosis-related proteins. NCTD acts synergistically with 5-FU to inhibit cervical cancer cell proliferation. NCTD enhances 5-FU-induced apoptosis in cervical cancer cell lines via the caspase-dependent pathway.

The development of multi-functional hydrogels is necessary to meet the needs of flexible sensors in different application scenarios. A conductive hydrogel with high toughness, adhesion, self-healing and anti-freezing properties was prepared. The hydrogel was synthesized by in-situ polymerization of acrylic acid in glycerol hydrate solution system of gelatin and aluminum ion, and then cryogenically refrigerated. After low temperature treatment, the triple helix structure produced by the self-assembly of the gelatin in the hydrogel increases the cross-linking density of the hydrogel, and forms a double network with polyacrylic acid to improve its mechanical properties (stress up to 85.7 kPa, strain up to 1428 %). In addition, this triple helix structure can dissociate and recombine at different temperatures, and interact with other dynamic bonds (hydrogen bonds, Al3+ coordination) in the system, so that the hydrogel has excellent self-healing ability (healing rate up to 86.8 %). Because the system contains a large number of -OH, -NH2 and -COOH groups, it can adhere to the surface of various materials through hydrogen bonding. The free Al3+ makes the hydrogel obtain good electrical conductivity and strain sensitivity (GF=3.01), and the strain sensor assembled by it has a stable and accurate monitoring effect on the fine movements of human body such as various joint movements and pronunciation. Additionally, the presence of glycerol provides anti-freezing properties, ensuring flexibility and electrical conductivity even at low temperatures (-20 ◦C). This hydrogel is a promising candidate for intelligent wearable devices in extreme environments such as snow and ice sports.

Glucocorticoid receptors are distributed in various cells of the body and participate in the regulation of metabolism and immunity in response to glucocorticoids. RNA m6A methylation participates in various metabolic and inflammatory responses, yet it remains elusive whether m6A is involved in GR regulation during immune activation. Here, we observed uncoupled GR responses with increased mRNA yet suppressed protein levels in the LPS-challenged broilers chicken liver, in association with global elevation of RNA m6A methylation, especially in the expression of METTL3 and YTHDF2. Further analysis using isolated primary hepatocytes and Kupffer cells revealed that such uncoupled GR responses and m6A hypermethylation occurred specifically in KCs. The same GR and m6A responses were reproduced in LPS-activated KC cell line, implying a possible role of m6A in the post-transcriptional suppression of GR in KC. Indeed, m6A inhibitor cycloleucine alleviated LPS-induced GR protein suppression, whilst GR antagonist RU486 had no effect on global m6A methylation in KC. We observed that YTHDF2 siRNA can alleviate LPS-induced GR mRNA stability decrease. Subsequently, specific m6A sites on GR were predicted and verified. Mutation m6A sites and luciferase reporter assay was also applied to validate these findings. Mechanistically, m6A methylation on the transcripts of GR impairs its mRNA stability in a YTHDF2-dependent manner, which leads to the decrease of its protein. Our study indicates successive roles of RNA m6A modification in the down regulation of GR expression, which provides new drug targets for epigenetic therapy of liver inflammation.

Objectives To estimate the interaction between economic status (ES) and healthy lifestyle in long COVID among Chinese older people infected with SARS-CoV-2.Design A cross-sectional study based on the Peking University Health Cohort in Anning, Yunnan.Setting All primary health institutions in Anning, Yunnan Province, China, from April to May 2023.Participants A total of 4804 people aged 60 and older infected with SARS-CoV-2 were included in this study.Primary and secondary outcome measures Long COVID was measured by participants’ self-reported symptoms using structured questionnaires. ES was measured by last-month personal income, and participants’ ES was defined as low if their income was below the per capita monthly income of local residents. Lifestyle score was equal to the number of healthy behaviours (including smoking, drinking, weight, exercise and diet) and grouped using the median score as the cut-off point. Univariate and multivariate logistic models were employed to estimate the association of ES with long COVID. Interaction between ES and lifestyle in long COVID was assessed by multiplicative interaction term.Results We enrolled a total of 4804 participants infected with SARS-CoV-2, of whom 57.3% (2754 of 4804) had at least one long COVID symptom. Fatigue (1546, 56.1%), cough (1263, 45.9%) and muscle pain (880, 32.0%) were the top three common symptoms. Patients with low ES had a 48% (adjusted OR: 1.48; 95% CI 1.22, 1.82) increased risk of long COVID. A significant interaction was observed between ES and lifestyle (p value for interaction

The sedimentary environment and organic matter (OM) accumulation are vital indicators for shale gas exploration. However, research on deep shale gas systems is relatively limited; moreover, the exploration of deep shale gas in the southeastern Sichuan Basin has entered a period of stagnation. In this study, systematic geochemical analysis of Wufeng (WF) and the first member of the Longmaxi (Long-1) deep shale samples from the recently drilled DY7 well in the Dingshan area of the Sichuan Basin is carried out, and the longitudinal variations in major and trace elements are revealed. The differences in the WF, lower section of the Long-1 (Long-11) and upper section of the Long-1 (Long-12) shales are studied in terms of redox conditions, paleoproductivity, terrigenous detrital input, sedimentation rate and paleoclimate, and the different main controlling factors of OM accumulation for these three layers are discussed. The WF shale has a higher TOC content (mean: 5.73%), the Long-11 shale has a high TOC content (mean: 2.89%), while the Long-12 shale has a low TOC content (mean: 1.44%). For the WF shale, due to complex geological events and large fluctuations in element contents, its TOC content is poorly correlated with these indices, redox and paleoproductivity proxies have a positive association with the Long-11 shale’s TOC content, but negatively correlated with terrigenous input and sedimentation rate indices. The formation of these two sets of organic-rich shales (TOC > 2%) is jointly controlled by good preservation conditions. In contrast, the TOC content of the WF shale is higher than that of the Long-11 shale as the result that terrigenous input and sedimentation rate of the Long-11 shale represent the dilution and destruction of OM, which is different from the former. During the Long-12 depositional period, the water column experienced weak reducing conditions and low productivity, and its high terrigenous debris input further diluted the OM, leading to a low TOC content.

Background This study aims to assess the efficacy and safety of Endostar in the management of locally advanced cervical cancer. Methods This retrospective, 2-center study enrolled 41 patients with locally advanced cervical cancer between June 2017 and December 2020. The patients were subjected to a combination of Endostar and chemoradiotherapy until they experienced disease progression or an unacceptable level of toxicity. The patients in the Endostar combined chemoradiotherapy (E + CRT) and CRT groups were matched 1:1 based on clinical features, including age, disease stage, and pathological type. The therapeutic efficacy and safety outcomes were compared between the 2 groups. Results Early treatment response: the CR rates in E + CRT and CRT groups were 48.8% and 26.8%, respectively ( χ 2 = 4.20, P

Introduction: Eplerenone is approved for the treatment of hypertension as well as symptomatic heart failure with reduced ejection fraction (HFrEF) following an acute myocardial infarction. However, the adverse events (AEs) have not been systematically analyzed. The aim of this study was to identify adverse drug reactions (ADRs) related to eplerenone using the FDA Adverse Event Reporting System (FAERS) database. By identifying previously unreported AEs, the study could potentially contribute to updating the drug’s label.Methods: In order to find significant AEs, four algorithms, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and Empirical Bayesian Geometric Mean (EBGM), were used to analyze the signal strength of the ADRs connected to eplerenone that were gathered from the FAERS database over the previous 20 years.Results: From 2004Q1 to 2023Q4, a total of 20, 629, 811 reported cases were gathered from the FAERS database for this study. After processing the data and filtering, 1,874 case reports were analyzed. Of these cases, 1,070 AEs were identified, 128 of which were eplerenone-related ADRs. We investigated the occurrence of ADRs induced by eplerenone in 27 organ systems. Our study showed that the AEs listed in the medication’s package insert correspond with those listed in the literature, including hyperkalemia and increased creatinine. Additionally, the prescription label for eplerenone does not include all system organ class (SOC) terms, like Vascular disorders, hepatobiliary Disorders, etc.Discussion: The study used multiple algorithms to quantify the signal strength and then identified any previously unrecognized ADRs, further studies are needed to confirm the association of ADRs with eplerenone. The findings of this study may provide important insights into the safety profile of eplerenone, ensure that healthcare providers have up-to-date information about their potential risks and help guide them in the correct use of the drug.

Objective: Invasive lung adenocarcinoma（ILA） with micropapillary (MPP)/solid (SOL) components has a poor prognosis. Preoperative identification is essential for decision-making for subsequent treatment. This study aims to construct and evaluate a super-resolution（SR） enhanced radiomics model designed to predict the presence of MPP/SOL components preoperatively to provide more accurate and individualized treatment planning. Methods: Between March 2018 and November 2023, patients who underwent curative intent ILA resection were included in the study. We implemented a deep transfer learning network on CT images to improve their resolution, resulting in the acquisition of preoperative super-resolution CT (SR-CT) images. Models were developed using radiomic features extracted from CT and SR-CT images. These models employed a range of classifiers, including Logistic Regression (LR), Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Random Forest, Extra Trees, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Multilayer Perceptron (MLP). The diagnostic performance of the models was assessed by measuring the area under the curve (AUC). Result: A total of 245 patients were recruited, of which 109 (44.5 %) were diagnosed with ILA with MPP/SOL components. In the analysis of CT images, the SVM model exhibited outstanding effectiveness, recording AUC scores of 0.864 in the training group and 0.761 in the testing group. When this SVM approach was used to develop a radiomics model with SR-CT images, it recorded AUCs of 0.904 in the training and 0.819 in the test cohorts. The calibration curves indicated a high goodness of fit, while decision curve analysis (DCA) highlighted the model's clinical utility. Conclusion: The study successfully constructed and evaluated a deep learning（DL）-enhanced SR-CT radiomics model. This model outperformed conventional CT radiomics models in predicting MPP/SOL patterns in ILA. Continued research and broader validation are necessary to fully harness and refine the clinical potential of radiomics when combined with SR reconstruction technology.

Abstract Deoxynivalenol (DON) is a prevalent toxin causing severe liver damage through hepatocellular oxidative stress. However, the underlying mechanisms and effective therapeutic approaches remain unknown. Here, the unique role of the xenobiotic metabolism factor pregnane X receptor (PXR) in mediating DON‐induced hepatocellular oxidative stress is investigated. Treatment with the PXR agonist 3‐indole‐propionic acid (IPA) alleviates DON‐induced oxidative stress and liver injury both in vitro and in vivo. Mechanistically, it is discovered for the first time that PXR agonist IPA directly transactivates the m6A demethylase FTO expression, leading to site‐specific demethylation and decreased abundance of YTHDC1‐bound Malat1 lncRNA at single‐nucleotide resolution. The diminished m6A modification of Malat1 lncRNA reduces its stability and augments antioxidant pathways governed by NRF2, consequently mitigating DON‐induced liver injury. Furthermore, Malat1 knockout mice exhibit decreased DON‐induced liver injury, emphasizing the role of Malat1 lncRNA in oxidative stress. Collectively, the findings establish that PXR‐mediated m6A‐dependent Malat1 lncRNA expression determines hepatocyte oxidative stress via m6A demethylase FTO, providing valuable insights into the potential mechanisms underlying DON‐induced liver injury and offers potential therapeutic strategies for its treatment.

Abstract Background Helicobacter pylori (H. pylori), according to a number of recent observational studies, is connected to atherosclerosis (AS). However, the link between H. pylori and AS is debatable. Methods In order to calculate the causal relationship between H. pylori and AS, we employed a two-sample Mendelian randomization (MR) analysis. The data for H. pylori were obtained from the IEU GWAS database ( https://gwas.mrcieu.ac.uk/datasets/ ) and the data for AS were obtained from the Finngen GWAS database ( https://r5.finngen.fi/ ). We selected single nucleotide polymorphisms with a threshold of 5 × 10–6 from earlier genome-wide association studies. MR was performed mainly using the inverse variance weighted (IVW) method. To ensure the reliability of the findings, We performed a leave-one-out sensitivity analysis to test for sensitivity. F-value was used to test weak instrument. Results A positive causal relationship between H. pylori OMP antibody levels and peripheral atherosclerosis was shown by our two-sample MR analysis (odds ratio (OR) = 1.33, 95% confidence interval (CI) = 1.14–1.54, P = 0.26E-03) using IVW. Additionally, there was a causative link between coronary atherosclerosis and H. pylori VacA antibody levels (IVW OR = 1.06, 95% CI = 1.01–1.10, P = 0.016). All the F-values were above 10. Conclusions This MR study discovered a causal link between H. pylori and AS. Different antibodies have different effects, so future researches are needed to figure out the exact mechanisms behind this link.

Abstract This study aimed to examine the correlation between post-traumatic growth (PTG), spiritual well-being (SWB), perceived social support (PSS), and demographic and clinical factors in Chinese gynecological cancer patients. Through convenience sampling, we conducted a cross-sectional study of 771 adult patients with gynecological cancer. The European Organization for Research and Treatment for Cancer Quality of Life Questionnaire-Spiritual Well-being 32 (EORTC QLQ-SWB32), Post-traumatic Growth Inventory (PTGI), and Multidimensional Scale of Perceived Social Support (MSPSS) were used to measure SWB, PTG, and PSS. A Multiple Linear Regression Model was used to determine the possible factors contributing to PTG. The subscale with the highest centesimal score in the PTGI was the Appreciation of Life Scale, and the lowest was New Possibility. Gynecologic cancer patients with younger ages (B = − 0.313, P = 0.002), perceived more family support (B = 1.289, P

Abstract Background Though (1S, 3R)-RSL3 has been used widely in basic research as a small molecular inducer of ferroptosis, the toxicity on normal cells and poor pharmacokinetic properties of RSL3 limited its clinical application. Here, we investigated the synergism of non-thermal plasma (NTP) and low-concentration RSL3 and attempted to rise the sensitivity of NSCLC cells on RSL3. Methods CCK-8 assay was employed to detect the change of cell viability. Microscopy and flowcytometry were applied to identify lipid peroxidation, cell death and reactive oxygen species (ROS) level respectively. The molecular mechanism was inspected with western blot and RT-qPCR. A xenograft mice model was adopted to investigate the effect of NTP and RSL3. Results We found the synergism of NTP and low-concentration RSL3 triggered severe mitochondria damage, more cell death and rapid ferroptosis occurrence in vitro and in vivo. NTP and RSL3 synergistically induced xCT lysosomal degradation through ROS/AMPK/mTOR signaling. Furthermore, we revealed mitochondrial ROS was the main executor for ferroptosis induced by the combined treatment. Conclusion Our research shows NTP treatment promoted the toxic effect of RSL3 by inducing more ferroptosis rapidly and provided possibility of RSL3 clinical application. Graphical Abstract Video Abstract

Abstract Background Prostate cancer is the second most frequent cancer and the fifth leading cause of cancer-related deaths in men. Prostate-specific membrane antigen (PSMA) as a target has gained increasing attention. This research aims to investigate and understand how altering size of PEG impacts the in vitro and in vivo behavior and performance of PSMA inhibitors, with a specific focus on their pharmacokinetic characteristics and targeting properties. Results Two 68Ga-labeled PSMA-targeted radiotracers were developed, namely [68Ga]Ga-PP4-WD and [68Ga]Ga-PP8-WD, with varying sizes of polyethylene glycol (PEG). [68Ga]Ga-PP4-WD and [68Ga]Ga-PP8-WD had excellent affinity for PSMA with IC50 being 8.06 ± 0.91, 6.13 ± 0.79 nM, respectively. Both tracers enabled clear visualization of LNCaP tumors in PET images with excellent tumor-to-background contrast. They also revealed highly efficient uptake and internalization into LNCaP cells, increasing over time. The biodistribution studies demonstrated that both radioligands exhibited significant and specific uptake into LNCaP tumors. Furthermore, they were rapidly cleared through the renal pathway, as evidenced by [68Ga]Ga-PP4-WD and [68Ga]Ga-PP8-WD showing a tenfold and a fivefold less in renal uptake, respectively, compared to [68Ga]Ga-Flu-1 in 30 min. Both in vitro and in vivo experiments demonstrated that PEG size significantly impacted tumor-targeting and pharmacokinetic properties. Conclusions These radiotracers have demonstrated their effectiveness in significantly reducing kidney uptake while maintaining the absorbed dose in tumors. Both radiotracers exhibited strong binding and internalization characteristics in vitro, displayed high specificity and affinity for PSMA in vivo.

Abstract Background Jianli pig, a renowned indigenous breed in China, has the characteristics of a two-end black (TEB) coat color, excellent meat quality, strong adaptability and increased prolificacy. However, there is limited information available regarding the genetic diversity, population structure and genomic regions under selection of Jianli pig. On the other hand, the genetic mechanism of TEB coat color has remained largely unknown. Results In this study, the whole genome resequencing of 30 Jianli pigs within a context of 153 individuals representing 13 diverse breeds was performed. The population structure analysis revealed that Jianli pigs have close genetic relationships with the Tongcheng pig breed, their geographical neighbors. Three methods (observed heterozygosity, expected heterozygosity, and runs of homozygosity) implied a relatively high level of genetic diversity and, a low inbreeding coefficient in Jianli compared with other pigs. We used Fst and XP-EHH to detect the selection signatures in Jianli pigs compared with Asian wild boar. A total of 451 candidate genes influencing meat quality (CREBBP, ADCY9, EEPD1 and HDAC9), reproduction (ESR1 and FANCA), and coat color (EDNRB, MITF and MC1R), were detected by gene annotation analysis. Finally, to fine-map the genomic region for the two-end black (TEB) coat color phenotype in Jianli pigs, we performed three signature selection methods between the TEB coat color and no-TEB coat color pig breeds. The current study, further confirmed that the EDNRB gene is a candidate gene for TEB color phenotype found in Chinese pigs, including Jinhua pigs, and the haplotype harboring 25 SNPs in the EDNRB gene may promote the formation of TEB coat color. Further ATAC-seq and luciferase reporter assays of these regions suggest that the 25-SNPs region was a strong candidate causative mutation that regulates the TEB coat color phenotype by altering enhancer function. Conclusion Our results advanced the understanding of the genetic mechanism behind artificial selection, and provided further resources for the protection and breeding improvement of Jianli pigs.

Abstract Background There is mounting proof that rheumatoid arthritis (RA) and cognitive decline are related. These studies, however, have not all been uniform, and others have not discovered such a correlation. It is essential to investigate the link between RA and cognitive decline. Method We conducted a Mendelian randomization analysis utilizing three different publicly accessible RA GWAS summary datasets and a variety of meticulously verified instrumental variables. We mostly used inverse variance weighting (IVW), as well as MR-Egger, weighted median, MR-PRESSO, and several sensitivity analyses, to figure out the link between RA and cognitive impairment (CI). Results Our MR study identified the causality between RA and declining cognitive performance (β = − 0.010, 95% CI of − 0.017 to − 0.003, P = 4.33E−03) and cognitive function (β = − 0.029, 95% CI of − 0.053 to − 0.005, P = 1.93E−02). The consistent direction of the connection is revealed by sensitivity analysis utilizing the weighted median and the MR-Egger method. Furthermore, we reproduced our findings across two additional RA datasets and found identical outcomes, strengthening the validity of our findings. Conclusion This study offers proof of causality between RA and an increased risk of CI. Our findings highlight the importance of examining RA patients for cognitive ability, which may open up fresh ideas for the prevention of CI.

The fusion genes NRG1 and NRG2, members of the epidermal growth factor (EGF) receptor family, have emerged as key drivers in cancer. Upon fusion, NRG1 retains its EGF-like active domain, binds to the ERBB ligand family, and triggers intracellular signaling cascades, promoting uncontrolled cell proliferation. The incidence of NRG1 gene fusion varies across cancer types, with lung cancer being the most prevalent at 0.19 to 0.27%. CD74 and SLC3A2 are the most frequently observed fusion partners. RNA-based next-generation sequencing is the primary method for detecting NRG1 and NRG2 gene fusions, whereas pERBB3 immunohistochemistry can serve as a rapid prescreening tool for identifying NRG1-positive patients. Currently, there are no approved targeted drugs for NRG1 and NRG2. Common treatment approaches involve pan-ERBB inhibitors, small molecule inhibitors targeting ERBB2 or ERBB3, and monoclonal antibodies. Given the current landscape of NRG1 and NRG2 in solid tumors, a consensus among diagnostic and treatment experts is proposed, and clinical trials hold promise for benefiting more patients with NRG1 and NRG2 gene fusion solid tumors.

Abstract The gas therapy is drawing increasing attention in the treatment of many diseases including cancer. As one of gas signaling molecules, carbon monoxide (CO) has been proved to exert anti-cancer effects via triggering multiple cell death types, such as autophagy, apoptosis and necrosis. Here, we showed that low concentration CO delivered from CO-releasing molecule 3 (CORM-3) effectively induced ferroptosis, known as a novel proinflammatory programmed cell death, in vitro and in vivo. Mechanistically, we found that CO triggered ferroptosis by modulating the ROS/GSK3β/GPX4 signaling pathway, resulting in the accumulation of lipid hydroperoxides and the occurrence of ferroptosis. We think our findings provide novel insights into the anti-cancer mechanisms of CO, and suggest that CO could potentially be exploited as a novel ferroptosis inducer for cancer treatment in the future.

Abstract High-efficiency medium-range wireless power transfer using magnetically coupled resonators requires a wireless data link between the contactless coils to regulate power. Multiplexing the power transfer channel as the information channel is a cost-effective solution for the communication. However, existing technologies cannot transmit data across the medium-range magnetically coupled resonators channel without substantially affecting power transfer. Here we show a power-electronics-converters based wireless power and information dual transfer system in which the information signals are modulated on one dc side of the inverter/rectifier, and transmitted through a conventional medium-range wireless power transfer system, and then demodulated on the other dc side. Using the frequency mixer characteristic of the inverter/rectifier, information is modulated onto the sideband of the power carrier and transmitted through the medium-range channel. Finally, we prototyped a 6.78 MHz system capable of transferring 45 W power across a one-meter distance with 62% efficiency and 60 kb/s bitrate for half-duplex communication.

The UAV landing process has higher requirements for automatic flight control systems due to factors such as wind disturbances and strong constraints. Considering the proven effective adaptation of the out-of-loop L1 adaptive control (OLAC) system proposed in previous studies, this paper applies it to landing control to enhance robustness and control accuracy in the presence of complex uncertainties. Based on modern control theory, an LQR-based OLAC algorithm for multi-input–multi-output (MIMO) systems is proposed, which is conducive to the coupling control of the flight attitude mode. To evaluate the robustness of the designed system, an equivalence stability margin analysis method for nonlinear systems is proposed based on parameter linearization. Along with a detailed autonomous landing strategy, including trajectory planning, control, and guidance, the effectiveness of the proposed methods is verified on a high-fidelity simulation platform. The Monte–Carlo simulation is implemented in the time domain, and the results demonstrate that OLAC exhibits strong robustness and ensures the state variables strictly meet the flight safety constraints.

Abstract Background Sarcopenia is highly prevalent among patients with colorectal cancer (CRC). Computed tomography (CT)‐based assessment of low skeletal muscle index (SMI) is widely used for diagnosing sarcopenia. However, there are conflicting findings on the association between low SMI and overall survival (OS) in CRC patients. The objective of this study was to investigate whether CT‐determined low SMI can serve as a valuable prognostic factor in CRC. Methods We collected data from patients with CRC who underwent radical surgery at our institution between June 2020 and November 2021. The SMI at the third lumbar vertebra was calculated using CT scans, and the cutoff values for defining low SMI were determined using receiver operating characteristic curves. Univariate and multivariate analyses were performed to assess the associations between clinical characteristics and postoperative major complications. Results A total of 464 patients were included in the study, 229 patients (46.7%) were classified as having low SMI. Patients with low SMI were older and had a lower body mass index (BMI), a higher neutrophil to lymphocyte ratio (NLR), and higher nutritional risk screening 2002 (NRS2002) scores compared to those with normal SMI. Furthermore, patients with sarcopenia had a higher rate of major complications (10.9% vs. 1.3%; p

AimThis study aims to evaluate the relationship between the Composite Dietary Antioxidant Index (CDAI) and the prevalence and recurrence of kidney stones.MethodsData from the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2014 were used in this cross-sectional analysis. The CDAI was derived by standardizing the intake of dietary antioxidants from 24 h dietary recalls. The study assessed the prevalence and recurrence of kidney stones based on questionnaire responses. The association between the CDAI and both the prevalence and recurrence of kidney stones was investigated using multivariable logistic regression. Subgroup analyses and interaction tests further evaluated the robustness of this relationship.ResultsThe study included 20,743 participants, and the reported incidence and recurrence rates of kidney stones were 9.09 and 2.90%, respectively. After stratifying the CDAI into tertiles, an inverse trend was observed in both kidney stones’ prevalence and recurrence probabilities with increasing CDAI levels. Adjusting for confounding factors, individuals in the top tertile had a 23% lower prevalence of kidney stones (OR = 0.77, 95% CI: 0.66, 0.90, p = 0.0011) and a 39% lower recurrence rate (OR = 0.61, 95% CI: 0.47, 0.80, p = 0.0003) than those in the bottom tertile. In addition, interaction tests showed that age, gender, body mass index, hypertension, and diabetes did not significantly affect the relationship between CDAI levels and kidney stone prevalence and recurrence rates.ConclusionOur study suggests that increased levels of CDAI are associated with reduced incidence and recurrence rates of kidney stones. Therefore, increasing the intake of dietary antioxidants may be an effective strategy for preventing kidney stones and their recurrence.

Background and aimsCervical cancer, a prevalent gynecological malignant tumor, poses a significant threat to women’s health and lives. Immune checkpoint inhibitor (ICI) therapy has emerged as a promising avenue for treating cervical cancer. For patients with persistent or recurrent metastatic cervical cancer, If the sequence of dead receptor ligand-1 (PD-L1) is positive, ICI show significant clinical efficacy. PD-L1 expression serves as a valuable biomarker for assessing ICI therapeutic efficacy. However, the complex tumor immune microenvironment (TIME), encompassing immune cell composition and tumor-infiltrating lymphocyte (TIL) status, also exerts a profound influence on tumor immunity and prognosis. Given the remarkable strides made by ICI treatments in improving the survival rates of cervical cancer patients, it becomes essential to identify a comprehensive biomarker that integrates various TIME aspects to enhance the effectiveness of ICI treatment. Therefore, the quest for biomarkers linked to multiple facets of TIME in cervical cancer is a vital pursuit.MethodsIn this study, we have developed an Immune-Associated Gene Prognostic Index (IRGPI) with remarkable prognostic value specifically for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The Cancer Genome Atlas CESC dataset (n = 305) was meticulously analyzed to pinpoint key immune-related genes via weighted gene co-expression network analysis and differential gene expression assays. Subsequently, we employed Cox regression analysis to construct the IRGPI. Furthermore, the composition of immune cells and TIL status were examined using CIBERSORT and TIDE. Tumor expression of Epigen, LCN10, and P73 were determined with immunohistochemistry.ResultsThe resulting IRGPI, composed of EPGN, LCN10, and TP73 genes, displayed a strong negative correlation with patient survival. The discovery was validated with a patient cohort from our hospital. The IRGPI not only predicts the composition of immune cell subtypes such as Macrophages M1, NK cells, Mast cells, Plasma cells, Neutrophils, Dendritic cells, T cells CD8, and T cells CD4 within CESC, but also indicates TIL exclusion, dysfunction, and PD-1 and PD-L1 expression. Therefore, the IRGPI emerges as a promising biomarker not only for prognostic assessment but also for characterizing multiple immune features in CESC. Additionally, our results underscored the significant associations between the IRGPI and immune cell composition, TIL exclusion, and dysfunction, along with PD-1 and PD-L1 expression in the TIME.ConclusionConsequently, the IRGPI stands out as a biomarker intimately connected to both the survival and TIME status of CESC patients, offering potential insights into immunotherapy strategies for CESC.

The solutions for the electrostatic interacting force between a particle and a plane typically assume that the plane is infinite and the particle can be approximated as a point charge. Nevertheless, the prerequisites of underlying assumptions of these calculations remain unspecified, resulting in the inability to assess the reliability of the results and constraining the practical applicability of analytical models. In this paper, the authors introduce the particle–coated plane electrostatic interaction model by employing the re-expansion method. Additionally, the multipole–coated plane electrostatic interaction model is presented using the image multipole method. An analysis of the assumptions’ prerequisites is conducted, considering a relative error of less than 2 % as the approximate standard. The findings indicate that, irrespective of the material properties of the particle and plane, the radius of the planar plate must exceed three times the distance between the particle’s center and the plane to satisfy the infinite plane assumption. When the distance between the particle’s center and the plane surpasses three times the radius, it is permissible to approximate the charged particle as a point charge. The study presented in this paper establishes a standard for prior estimation of the departure range in existing analytical models related to particle–plane electrostatic interaction. This work also serves as a theoretical basis for the practical application of these models in engineering.

Background: Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment. Objective: This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers. Design: A retrospective case control, diagnostic accuracy study. Methods: This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21–83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines. Results: The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively. Conclusion: This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

Abstract Background This study aimed to identify distinct patterns within the symptom cluster of fatigue, pain, and sleep disturbance among ovarian cancer patients receiving chemotherapy, to determine the factors predicting these patterns and their impact on quality of life. Methods The longitudinal study collected data from 151 ovarian cancer patients at three time points: before chemotherapy (T0), after the first chemotherapy cycle (T1), and following the completion of four cycles of chemotherapy (T2). Latent profile analysis and latent transition analysis were used to identify symptom patterns and evaluate changes in symptom patterns. A bias‐adjusted three‐step approach was utilized to examine predictor variables and distal outcomes associated with latent class membership. Results Three symptom patterns emerged: “All Low,” “Moderate” (T0)/“Low pain and high sleep disturbance” (T1 and T2), and “All High.” Patients with lower educational attainment and higher levels of anxiety and depression were found to be at an elevated risk of belonging to the “All High” class. All quality‐of‐life domains showed significant differences among the three subgroups, following an “All Low” > “All High” pattern (p

Abstract Background The timings of reproductive life events have been examined to be associated with various psychiatric disorders. However, studies have not considered the causal pathways from reproductive behaviors to different psychiatric disorders. This study aimed to investigate the nature of the relationships between five reproductive behaviors and twelve psychiatric disorders. Methods Firstly, we calculated genetic correlations between reproductive factors and psychiatric disorders. Then two-sample Mendelian randomization (MR) was conducted to estimate the causal associations among five reproductive behaviors, and these reproductive behaviors on twelve psychiatric disorders, using genome-wide association study (GWAS) summary data from genetic consortia. Multivariable MR was then applied to evaluate the direct effect of reproductive behaviors on these psychiatric disorders whilst accounting for other reproductive factors at different life periods. Results Univariable MR analyses provide evidence that age at menarche, age at first sexual intercourse and age at first birth have effects on one (depression), seven (anxiety disorder, ADHD, bipolar disorder, bipolar disorder II, depression, PTSD and schizophrenia) and three psychiatric disorders (ADHD, depression and PTSD) (based on p

Abstract Recently developed enzymes for the depolymerization of polyethylene terephthalate (PET) such as FAST-PETase and LCC-ICCG are inhibited by the intermediate PET product mono(2-hydroxyethyl) terephthalate (MHET). Consequently, the conversion of PET enzymatically into its constituent monomers terephthalic acid (TPA) and ethylene glycol (EG) is inefficient. In this study, a protein scaffold (1TQH) corresponding to a thermophilic carboxylesterase (Est30) was selected from the structural database and redesigned in silico. Among designs, a double variant KL-MHETase (I171K/G130L) with a similar protein melting temperature (67.58 °C) to that of the PET hydrolase FAST-PETase (67.80 °C) exhibited a 67-fold higher activity for MHET hydrolysis than FAST-PETase. A fused dual enzyme system comprising KL-MHETase and FAST-PETase exhibited a 2.6-fold faster PET depolymerization rate than FAST-PETase alone. Synergy increased the yield of TPA by 1.64 fold, and its purity in the released aromatic products reached 99.5%. In large reaction systems with 100 g/L substrate concentrations, the dual enzyme system KL36F achieved over 90% PET depolymerization into monomers, demonstrating its potential applicability in the industrial recycling of PET plastics. Therefore, a dual enzyme system can greatly reduce the reaction and separation cost for sustainable enzymatic PET recycling.

Abstract In the construction industry, ensuring the safety performance of a project relies heavily on the effective allocation of safety resources. As the importance of mental health in the construction industry increases, evolutionary game theory can be used to analyze the interaction mechanism of various factors affecting safety performance during the construction phase. The objective of this paper is to construct an analytical model that combines evolutionary game theory with genetic algorithms from the perspective of Leader-Member Exchange Ambivalence. The model aims to quantify and compare the various factors that influence achieving the expected safety state and identify the specific necessary constraints. Initially, we analyzed the relationships among construction site employees, divided them into superiors and subordinates, and established a game model and payoff matrix based on the research background. Next, we introduced genetic algorithms into the model via the replicator dynamic equation for optimization. We adjusted the coefficients of safety risk level, psychological expected return, moral identity, and other factors to simulate various construction site scenarios. Simulation and optimization results indicate that genetic algorithms provide more accurate reference values for safety resource allocation compared to preset or manually assigned values.

Abstract Background Exercise rehabilitation training is an important measure for improving the prognosis of patients with hip fractures. However, the particular program that works effectively and the efficiency of exercise therapy are still controversial. Objective To compare the effects of usual postoperative care combined with rehabilitation based on exercise prescription on motor function and complications in elderly patients who underwent surgery for hip fracture. Methods This was an observational study. A total of 71 elderly patients with hip fractures who were treated with hip arthroplasty and internal fixation of the proximal femur with an intramedullary nail at Suzhou Municipal Hospital from October 2020 to December 2021 were included; 11 cases were excluded (eight cases were excluded due to loss of follow-up, two due to deaths from other causes, and one due to other reasons). Finally, 60 patients (18 males and 42 females) were included. Patients were randomly assigned to the control (n = 30) and experimental (n = 30) groups using a random number generator. Patients in the control group received usual postoperative care, whereas those in the experimental group received usual postoperative care combined with rehabilitation training based on the principles of exercise prescription. We recorded the motor function (Harris hip score), daily living ability (Barthel Index), and complications at discharge and 1, 3, and 6 months postoperatively for statistical analysis. Results The Harris hip score and Barthel Index score were significantly higher at 1, 3, and 6 months postoperatively than at discharge in both groups (p

Over 70% of leiomyoma (LM) harbor MED12 mutations, primarily in exon 2 at c.130-131 (GG). Myometrial cells are the cell origin of leiomyoma, but the MED12 mutation status in non-neoplastic myometrial cells is unknown. In this study, we investigated the mutation burden of MED12 in myometrium. As traditional Sanger or even NGS sequencing may not be able to detect MED12 mutations that are lower than 0.1% in the testing sample, we used duplex deep sequencing analysis (DDS) to overcome this limitation. Tumor-free myometria (confirmed by pathology evaluation) were dissected, and genomic DNA from MED12 exon 2 (test) and TP53 exon 5 (control) were captured by customer-designed probe sets, followed by DDS. Notably, DDS demonstrated that myometrial cells harbored a high frequency of mutations in MED12 exon 2 and predominantly in code c.130-131. In contrast, the baseline mutations in other coding sequences of MED12 exon 2 as well as in the TP53 mutation hotspot, c.477-488 were comparably low in myometrial cells. This is the first report demonstrating a non-random accumulation of MED12 mutations at c.130-131 sites in non-neoplastic myometrial cells which provide molecular evidence of early somatic mutation events in myometrial cells. This early mutation may contribute to the cell origin for uterine LM development in women of reproductive age.

Aiming at the problem that the Osprey Optimization Algorithm (OOA) does not have high optimization accuracy and is prone to falling into local optimum, an Improved Osprey Optimization Algorithm Based on a Two-Color Complementary Mechanism for Global Optimization (IOOA) is proposed. The core of the IOOA algorithm lies in its unique two-color complementary mechanism, which significantly improves the algorithm’s global search capability and optimization performance. Firstly, in the initialization stage, the population is created by combining logistic chaos mapping and the good point set method, and the population is divided into four different color groups by drawing on the four-color theory to enhance the population diversity. Secondly, a two-color complementary mechanism is introduced, where the blue population maintains the OOA core exploration strategy to ensure the stability and efficiency of the algorithm; the red population incorporates the Harris Hawk heuristic strategy in the development phase to strengthen the ability of local minima avoidance; the green group adopts the strolling and wandering strategy in the searching phase to add stochasticity and maintain the diversity; and the orange population implements the optimized spiral search and firefly perturbation strategies to deepen the exploration and effectively perturb the local optimums, respectively, to improve the overall population diversity, effectively perturbing the local optimum to improve the performance of the algorithm and the exploration ability of the solution space as a whole. Finally, to validate the performance of IOOA, classical benchmark functions and CEC2020 and CEC2022 test sets are selected for simulation, and ANOVA is used, as well as Wilcoxon and Friedman tests. The results show that IOOA significantly improves convergence accuracy and speed and demonstrates high practical value and advantages in engineering optimization applications.