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Development of methods for the sp2 C-H transformations of allenes has received much attention, and it presents a powerful tool for the synthesis of complicated allene-containing bioactive molecules. With a copper-catalyzed radical relay, sp2 allenic C-H arylation and alkynylation were established herein, using various aryl boronic acids and trimethoxysilyl-substituted alkynes as carbon nucleophiles and using electrophilic N-F reagents as nitrogen-centered radical precursors. These methods featured excellent site selectivity to deliver fully substituted allenes efficiently. Moreover, with silyl-substituted allenes as substrates, a subsequent dual sp2 C-H functionalization process was established as well, which allowed for the divergent synthesis of multifunctionalized allenes, significantly expanding their chemical spaces.
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Background: The predictive value of growth differentiation factor-15 (GDF-15) in coronary microvascular dysfunction (CMD) following primary percutaneous coronary intervention (PPCI) in ST-segment elevation myocardial infarction (STEMI) patients is unclear. Methods: This study continuously recruited STEMI patients treated with PPCI at the Chest Pain Center of Qilu Hospital of Shandong University from April 2023 to December 2023. Blood samples were taken before PPCI and the level of circulating GDF-15 was measured by enzyme-linked immunosorbent assay (ELISA), and the patients were divided into CMD and Control group according to angiographic microvascular resistance (AMR) (cut-off value 2.50 mmHg*s/cm). The differences in GDF-15 expression levels between the two groups were compared, and the predictive value of GDF-15 for CMD was systematically evaluated. Results: A total of 134 patients, with an average age of 59.78 ± 12.69 years and 75.37 % being male, were included in this study. Multivariable logistic regression revealed a significant association between GDF-15 and CMD (adjusted OR = 2.505, 95 % CI: 1.661-3.779, P < 0.001). The area under the curve (AUC) of GDF-15 for CMD was 0.782 (95 % CI: 0.704-0.861), with a sensitivity of 0.795 and specificity of 0.643 in predicting CMD in PPCI. The AUC of the GDF-15 model (Model With GDF-15) was 0.867 (95 % CI: 0.806-0.928), significantly outperforming the clinical baseline model (Model Without GDF-15) (Δ AUC = 0.079, 95 % CI: 0.020-0.138, P = 0.009). Furthermore, the net reclassification improvement (NRI) was 0.854 (95 % CI: 0.543-1.166, P < 0.001), and the integrated discrimination improvement (IDI) was 0.151 (95 % CI: 0.089-0.213, P < 0.001). Conclusions: GDF-15 can serve as a biomarker for predicting the development of CMD in STEMI patients undergoing PPCI.
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Comprehensive studies on the freeze-thaw (F-T) damage mechanism in siliceous slates are lacking. In this study, we investigated the evolutionary characteristics of F-T damage in siliceous slates. To this end, scanning electron microscopy, X-ray diffraction, X-ray fluorescence, and uniaxial compression tests were used to analyze the microstructure, phase composition, porosity, and macroscopic mechanical parameters of siliceous slate with varying initial water content during F-T cycles. The results revealed several insights. (1) The microstructure of siliceous slate undergoes significant change with respect to increasing water content and number of F-T cycles. The rock surface changed from smooth to rough, and the arrangement of the mineral particles changed from tight to loose. (2) More than 80 % of the contents of siliceous slate comprise oxygen, aluminum, silicon, potassium, and iron. In particular, siliceous slate comprises muscovite, quartz, clinochlore, and kaolinite. Both the clinochlore and kaolinite are unstable clay minerals. As clay minerals exhibit strong water absorption and expansion characteristics, kaolinite undergoes strong hydration reactions. Compared to rock samples without F-T cycles in the dry state, the clay mineral content of siliceous slate decreased by nearly 50 %, from 28.8 % to 15.5 %, after 30 F-T cycles in the saturated state. (3) The mechanical parameters of siliceous slates with varying water content decreased exponentially with the number of F-T cycles, while their porosity exhibited a positive correlation with the number of F-T cycles. The degree of deterioration in both increased with increasing water content. Both the number of F-T cycles and the initial water content were observed to wield a significant effect on the deterioration of siliceous slates. (4) The evolution curve of F-T load damage in siliceous slate exhibited characteristics of transitioning from gentle to concave and then to a convex stage of growth. Our results are expected to provide theoretical guidance for the evaluation and prevention of F-T disasters in cold regions.
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Phenotypic switching plays a crucial role in cell fate determination across various organisms. Recent experimental findings highlight the significance of protein compartmentalization via liquid-liquid phase separation in influencing such decisions. However, the precise mechanism through which phase separation regulates phenotypic switching remains elusive. To investigate this, we established a mathematical model that couples a phase separation process and a gene expression process with feedback. We used the chemical master equation theory and mean-field approximation to study the effects of phase separation on the gene expression products. We found that phase separation can cause bistability and bimodality. Furthermore, phase separation can control the bistable properties of the system, such as bifurcation points and bistable ranges. On the other hand, in stochastic dynamics, the droplet phase exhibits double peaks within a more extensive phase separation threshold range than the dilute phase, indicating the pivotal role of the droplet phase in cell fate decisions. These findings propose an alternative mechanism that influences cell fate decisions through the phase separation process. As phase separation is increasingly discovered in gene regulatory networks, related modeling research can help build biomolecular systems with desired properties and offer insights into explaining cell fate decisions.
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Modelos Biológicos , Fenotipo , Procesos Estocásticos , Redes Reguladoras de Genes , Transición de Fase , Separación de FasesRESUMEN
Background: Current surveillance modalities of osteosarcoma relapse exhibit limited sensitivity and specificity. Although circulating tumor DNA (ctDNA) has been established as a biomarker of minimal residual disease (MRD) in many solid tumors, a sensitive ctDNA detection technique has not been thoroughly explored for longitudinal MRD detection in osteosarcoma. Methods: From August 2019 to June 2023, 59 patients diagnosed with osteosarcoma at the First Affiliated Hospital of Sun Yat-sen University were evaluated in this study. Tumor-informed MRD panels were developed through whole exome sequencing (WES) of tumor tissues. Longitudinal blood samples were collected during treatment and subjected to multiplex PCR-based next-generation sequencing (NGS). Kaplan-Meier curves and Log-rank tests were used to compare outcomes, and Cox regression analysis was performed to identify prognostic factors. Findings: WES analysis of 83 patients revealed substantial mutational heterogeneity, with non-recurrent mutated genes accounting for 58.1%. Tumor-informed MRD panels were successfully obtained for 85.5% of patients (71/83). Among 59 patients with successful MRD panel customization and available blood samples, 13 patients exhibited positive ctDNA detection after surgery. Patients with negative post-operative ctDNA had better event-free survival (EFS) compared to those with positive ctDNA, at 1-6 months after surgery, after adjuvant chemotherapy, and more than 6 months after surgery (p < 0.05). In both univariate and multivariate Cox regression analysis, ctDNA results emerged as a significant predictor of EFS (p < 0.05). ctDNA detection preceded positive imaging in 5 patients, with an average lead time of 92.6 days. Thirty-nine patients remained disease-free, with ctDNA results consistently negative or turning negative during follow-up. Interpretation: Our study underscores the applicability of tumor-informed deep sequencing of ctDNA in osteosarcoma MRD surveillance and, to our knowledge, represents the largest cohort to date. ctDNA detection is a significant prognostic factor, enabling the early identification of tumor relapse and progression compared to standard imaging, thus offering valuable insights in guiding osteosarcoma patient management. Funding: The Grants of National Natural Science Foundation of China (No. 82072964, 82072965, 82203798, 82203026), the Natural Science Foundation of Guangdong (No. 2023A1515012659, 2023A1515010302), and the Regional Combination Project of Basic and Applied Basic Research Foundation of Guangdong (No. 2020A1515110010).
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BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have developed prediction model for post-stroke epilepsy (PSE), their accuracy remains insufficient, and their applicability to different populations is uncertain. With the rapid advancement of computer technology, machine learning (ML) offers new opportunities for creating more accurate prediction models. However, the potential of ML in predicting PSE is still not well understood. The purpose of this study was to develop prediction models for PSE among ischemic stroke patients. METHODS: Patients with ischemic stroke from two stroke centers were included in this retrospective cohort study. At the baseline level, 33 input variables were considered candidate features. The 2-year PSE prediction models in the derivation cohort were built using six ML algorithms. The predictive performance of these machine learning models required further appraisal and comparison with the reference model using the conventional triage classification information. The Shapley additive explanation (SHAP), based on fair profit allocation among many stakeholders according to their contributions, is used to interpret the predicted outcomes of the naive Bayes (NB) model. RESULTS: A total of 1977 patients were included to build the predictive model for PSE. The Boruta method identified NIHSS score, hospital length of stay, D-dimer level, and cortical involvement as the optimal features, with the receiver operating characteristic curves ranging from 0.709 to 0.849. An additional 870 patients were used to validate the ML and reference models. The NB model achieved the best performance among the PSE prediction models with an area under the receiver operating curve of 0.757. At the 20â¯% absolute risk threshold, the NB model also provided a sensitivity of 0.739 and a specificity of 0.720. The reference model had poor sensitivities of only 0.15 despite achieving a helpful AUC of 0.732. Furthermore, the SHAP method analysis demonstrated that a higher NIHSS score, longer hospital length of stay, higher D-dimer level, and cortical involvement were positive predictors of epilepsy after ischemic stroke. CONCLUSIONS: Our study confirmed the feasibility of applying the ML method to use easy-to-obtain variables for accurate prediction of PSE and provided improved strategies and effective resource allocation for high-risk patients. In addition, the SHAP method could improve model transparency and make it easier for clinicians to grasp the prediction model's reliability.
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Epilepsia , Aprendizaje Automático , Accidente Cerebrovascular , Humanos , Femenino , Masculino , Epilepsia/diagnóstico , Epilepsia/etiología , Estudios Retrospectivos , Anciano , Persona de Mediana Edad , Accidente Cerebrovascular/complicaciones , Accidente Cerebrovascular Isquémico/complicacionesRESUMEN
BACKGROUND: Cardiovascular consequences of phthalates exposure have been given increasing attention, but the association of phthalates with subclinical cardiovascular disease (CVD) was unknown. Accordingly, this study aimed to investigate the association between phthalates exposure and high-sensitivity cardiac troponin I (hs-cTnI), a marker of myocardial injury, which was detectable in the subclinical stage of CVD. METHODS: Participants aged 6 years or older with available urinary phthalates metabolites and serum hs-cTnI concentrations were included in the National Health and Nutrition Examination Survey 2003-2004 cycle. Multivariable linear regression and weighted quantiles sum (WQS) regression were used to assess the association of hs-cTnI with individual phthalates and their co-exposure. Di-2-ethylhexylphthalate (ΣDEHP), high-molecular-weight phthalate (ΣHMWP), and low-molecular-weight phthalate (ΣLMWP) were defined as the molecular sum of phthalates metabolites in urine. RESULTS: 2241 participants were finally included. The percent change of serum hs-cTnI concentrations related to per 1-standard deviation increase of logarithmic urinary phthalates concentrations was 3.4% (0.1-6.7, P = 0.04) for ΣDEHP, 3.6% (0.3-6.9, P = 0.03) for ΣHMWP, and 3.5% (0.2-6.8, P = 0.04) for ΣLMWP. Co-exposure to phthalates metabolites expressed as the WQS index also demonstrated a positive association with hs-cTnI. A similar association pattern was found in the population with no prior CVD. CONCLUSIONS: This study indicated the potential of phthalates to myocardial injury which may occur even before clinically apparent CVD was identified, emphasizing the significance of reducing phthalates in the prevention of CVD.
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Aurora kinase B (AURKB), an essential regulator in the process of mitosis, has been revealed through various studies to have a significant role in cancer development and progression. However, the specific mechanisms remain poorly understood. This study, therefore, seeks to elucidate the multifaceted role of AURKB in diverse cancer types. This study utilized bioinformatics techniques to examine the transcript, protein, promoter methylation and mutation levels of AURKB. The study further analysed associations between AURKB and factors such as prognosis, pathological stage, biological function, immune infiltration, tumour mutational burden (TMB) and microsatellite instability (MSI). In addition, immunohistochemical staining data of 50 cases of renal clear cell carcinoma and its adjacent normal tissues were collected to verify the difference in protein expression of AURKB in the two tissues. The results show that AURKB is highly expressed in most cancers, and the protein level of AURKB and the methylation level of its promoter vary among cancer types. Survival analysis showed that AURKB was associated with overall survival in 12 cancer types and progression-free survival in 11 cancer types. Elevated levels of AURKB were detected in the advanced stages of 10 different cancers. AURKB has a potential impact on cancer progression through its effects on cell cycle regulation as well as inflammatory and immune-related pathways. We observed a strong association between AURKB and immune cell infiltration, immunomodulatory factors, TMB and MSI. Importantly, we confirmed that the AURKB protein is highly expressed in kidney renal clear cell carcinoma (KIRC). Our study reveals that AURKB may be a potential biomarker for pan-cancer and KIRC.
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Aurora Quinasa B , Biomarcadores de Tumor , Metilación de ADN , Regulación Neoplásica de la Expresión Génica , Neoplasias , Regiones Promotoras Genéticas , Humanos , Pronóstico , Aurora Quinasa B/metabolismo , Aurora Quinasa B/genética , Regiones Promotoras Genéticas/genética , Neoplasias/genética , Neoplasias/inmunología , Neoplasias/patología , Neoplasias/metabolismo , Neoplasias/mortalidad , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Inestabilidad de Microsatélites , Mutación/genética , Femenino , Biología Computacional/métodosRESUMEN
The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.
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Regorafenib is a second-line standard treatment for hepatocellular carcinoma (HCC). However, the efficacy of regorafenib is often limited due to drug resistance, individual differences among patients, and irrational drug use. Radiotherapy (RT) is an important method of localized HCC treatment, and combining RT with other therapies may exert a synergetic antitumor effect. Platelet-derived growth factor receptor-like (PDGFRL) is a tumor suppressor in various solid tumors. However, the function of PDGFRL in HCC is still unknown. In this study, we explored whether regorafenib and RT exert a synergetic effect on the treatment of HCC. The antitumor effect and mechanisms of the combination of regorafenib and RT were verified in a xenograft mouse model in vivo and in HCC cells in vitro. The combination treatment significantly inhibited cell proliferation and promoted apoptosis both in vitro and in vivo. PDGFRL, a potential target of regorafenib, was increased after cumulative treatment in HCC cells, and PDGFRL suppressed HCC cell proliferation and promoted apoptosis by inhibiting STAT3 pathway activation. Furthermore, the cumulative antitumor effect was dependent on the upregulated expression of PDGFRL and inhibition of STAT3 signaling pathway activation in HCC cells. This study increased the understanding of the molecular mechanism underlying the effect of regorafenib plus RT on HCC and provided a theoretical basis for the clinical practice of HCC.
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Apoptosis , Carcinoma Hepatocelular , Proliferación Celular , Neoplasias Hepáticas , Compuestos de Fenilurea , Piridinas , Ensayos Antitumor por Modelo de Xenoinjerto , Carcinoma Hepatocelular/tratamiento farmacológico , Carcinoma Hepatocelular/patología , Carcinoma Hepatocelular/radioterapia , Carcinoma Hepatocelular/metabolismo , Compuestos de Fenilurea/farmacología , Compuestos de Fenilurea/uso terapéutico , Piridinas/farmacología , Piridinas/uso terapéutico , Animales , Neoplasias Hepáticas/tratamiento farmacológico , Neoplasias Hepáticas/patología , Neoplasias Hepáticas/radioterapia , Neoplasias Hepáticas/metabolismo , Humanos , Ratones , Proliferación Celular/efectos de los fármacos , Apoptosis/efectos de los fármacos , Línea Celular Tumoral , Factor de Transcripción STAT3/metabolismo , Ratones Desnudos , Transducción de Señal/efectos de los fármacos , Ratones Endogámicos BALB C , Antineoplásicos/farmacología , Antineoplásicos/uso terapéutico , Masculino , Regulación Neoplásica de la Expresión Génica/efectos de los fármacosRESUMEN
The maximum detection distance is usually the primary concern of magnetic anomaly detection (MAD). Intuition tells us that larger object size, stronger magnetization and finer measurement resolution guarantee a further detectable distance. However, the quantitative relationship between detection distance and the above determinants is seldom studied. In this work, unmanned aerial vehicle-based MAD field experiments are conducted on cargo vessels and NdFeB magnets as typical magnetic objects to give a set of visualized magnetic field flux density images. Isometric finite element models are established, calibrated and analyzed according to the experiment configuration. A maximum detectable distance map as a function of target size and measurement resolution is then obtained from parametric sweeping on an experimentally calibrated finite element analysis model. We find that the logarithm of detectable distance is positively proportional to the logarithm of object size while negatively proportional to the logarithm of resolution, within the ranges of 1 m~500 m and 1 pT~1 µT, respectively. A three-parameter empirical formula (namely distance-size-resolution logarithmic relationship) is firstly developed to determine the most economic sensor configuration for a given detection task, to estimate the maximum detection distance for a given magnetic sensor and object, or to evaluate minimum detectable object size at a given magnetic anomaly detection scenario.
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We aimed to determine whether monitoring tumor-derived exosomal microRNAs (miRNAs) could be used to assess radiotherapeutic sensitivity in patients with locally advanced esophageal squamous cell carcinoma (ESCC). RNA sequencing was employed to conduct a comparative analysis of miRNA expression levels during radiotherapy, focusing on identifying miRNAs associated with progression. Electron microscopy confirmed the existence of exosomes, and co-cultivation assays and immunofluorescence validated their capacity to infiltrate macrophages. To determine the mechanism by which exosomal miR-143-3p regulates the interplay between ESCC cells and M2 macrophages, ESCC cell-derived exosomes were co-cultured with macrophages. Serum miR-143-3p and miR-223-3p were elevated during radiotherapy, suggesting resistance to radiation and an unfavorable prognosis for ESCC. Increased levels of both miRNAs independently predicted shorter progression-free survival (p = 0.015). We developed a diagnostic model for ESCC using serum microRNAs, resulting in an area under the curve of 0.751. Radiotherapy enhanced the release of miR-143-3p from ESCC cell-derived exosomes. Immune cell infiltration analysis at the Cancer Genome Atlas (TCGA) database revealed that ESCC cell-derived miR-143-3p triggered M2 macrophage polarization. Mechanistically, miR-143-3p upregulation affected chemokine activity and cytokine signaling pathways. Furthermore, ESCC cell exosomal miR-143-3p could be transferred to macrophages, thereby promoting their polarization. Serum miR-143-3p and miR-223-3p could represent diagnostic and prognostic markers for patients with ESCC undergoing radiotherapy. Unfavorable prognosis could be linked to the increased levels of ESCC cell-derived exosomal miR-143-3p, which might promote tumor progression by interacting with macrophages.
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Neoplasias Esofágicas , Carcinoma de Células Escamosas de Esófago , Exosomas , Regulación Neoplásica de la Expresión Génica , Macrófagos , MicroARNs , Tolerancia a Radiación , MicroARNs/genética , Humanos , Exosomas/metabolismo , Carcinoma de Células Escamosas de Esófago/genética , Carcinoma de Células Escamosas de Esófago/patología , Carcinoma de Células Escamosas de Esófago/radioterapia , Carcinoma de Células Escamosas de Esófago/metabolismo , Macrófagos/metabolismo , Tolerancia a Radiación/genética , Neoplasias Esofágicas/genética , Neoplasias Esofágicas/radioterapia , Neoplasias Esofágicas/patología , Neoplasias Esofágicas/metabolismo , Línea Celular Tumoral , Masculino , Femenino , Persona de Mediana Edad , Pronóstico , Anciano , Activación de Macrófagos/genéticaRESUMEN
Background: Ischemic stroke (IS) is the leading cause of disability and mortality worldwide. Low-density lipoprotein cholesterol (LDL-C) levels hadno potential risk on ischemic stroke. However, higher LDL-C levels were closely related to IS. Based on two antagonistic viewpoints, a Mendelian randomization (MR) study was designed to evaluate the causal effects of LDL-C levels on IS. Methods: Datasets of LDL-C levels and ischemic stroke were acquired from genome-wide association studies (GWAS). Weighted median method was conducted for main analysis, and MR-Egger and inverse-variance weighted (IVW) methods were performed for auxiliary analyses. Heterogeneity and pleiotropic tests were utilized to confirm the reliability of this study. Results: A total of 359 single nucleotide polymorphisms (SNPs) were associated with LDL-C levels (P < 5 × 10-8) and 337 SNPs were available in ischemic stroke with eliminating outliers. LDL-C levels were significantly associated with ischemic stroke (OR = 1.104, 95%CI = 1.019 - 1.195, P = 1.52 × 10-2). MR-Egger and IVW showed directionally similar estimates (MR-Egger: OR = 1.120, 95%CI = 1.040 - 1.207, P = 3.12 × 10-3; IVW: OR = 1.120, 95%CI = 1.064 - 1.178, P = 1.17 × 10-5). Conclusion: LDL-C levels had causal effects on IS, providing insights into the design of future interventions to reduce the burden of ischemic stroke.
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Photocatalytic solar hydrogen generation, encompassing both overall water splitting and organic reforming, presents a promising avenue for green hydrogen production. This technology holds the potential for reduced capital costs in comparison to competing methods like photovoltaic-electrocatalysis and photoelectrocatalysis, owing to its simplicity and fewer auxiliary components. However, the current solar-to-hydrogen efficiency of photocatalytic solar hydrogen production has predominantly remained low at ≈1-2% or lower, mainly due to curtailed access to the entire solar spectrum, thus impeding practical application of photocatalytic solar hydrogen production. This review offers an integrated, multidisciplinary perspective on photocatalytic solar hydrogen production. Specifically, the review presents the existing approaches in photocatalyst and system designs aimed at significantly boosting the solar-to-hydrogen efficiency, while also considering factors of cost and scalability of each approach. In-depth discussions extending beyond the efficacy of material and system design strategies are particularly vital to identify potential hurdles in translating photocatalysis research to large-scale applications. Ultimately, this review aims to provide understanding and perspective of feasible pathways for commercializing photocatalytic solar hydrogen production technology, considering both engineering and economic standpoints.
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Heavy metal pollution in farmland soil represents a considerable risk to ecosystems and human health, constituting a global concern. Focusing on a key area for the cultivation of special agricultural products in Cangxi County, we collected 228 surface soil samples. We analyzed the concentration, spatial distribution, and pollution levels of six heavy metals (Cr, Cu, Pb, Ni, Zn, and Hg) in the soil. Moreover, we investigated the sources and contribution rates of these heavy metals using Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS) and Positive Matrix Factorization (PMF) models. Our findings indicate that none of the six metals exceeded the pollution thresholds for farmland soils. However, the mean concentrations of Cr and Ni surpassed the background levels of Sichuan Province. A moderate spatial correlation existed between Pb and Ni, attributable to both natural and anthropogenic factors, whereas Zn, Cu, Hg, and Cr displayed a strong spatial correlation, mainly due to natural factors. The spatial patterns of Cr, Cu, Zn, Pb, and Ni were similar, with higher concentrations in the northern and eastern regions and lower concentrations centrally. Hg's spatial distribution differed, exhibiting a broader range of lower values. The single pollution index evaluation showed that Cr and Ni were low pollution, and the other elements were no pollution. The average value of comprehensive pollution index is 0.994, and the degree of pollution is close to light pollution. Predominantly, higher pollution levels in the northern and eastern regions, lower around reservoirs. The PCA/APCS model identified two main pollution sources: agricultural traffic mixed source (65.2%) and natural parent source (17.2%). The PMF model delineated three sources: agricultural activities (32.59%), transportation (30.64%), and natural parent sources (36.77%). Comparatively, the PMF model proved more accurate and reliable, yielding findings more aligned with the study area's actual conditions.
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Agricultura , Metales Pesados , Contaminantes del Suelo , Suelo , Metales Pesados/análisis , China , Contaminantes del Suelo/análisis , Suelo/química , Monitoreo del Ambiente/métodos , Análisis de Componente Principal , Análisis EspacialRESUMEN
OBJECTIVE: To investigate the association between autoimmune diseases (AIDs) and bladder cancer (BC) at the genetic level using Mendelian randomization (MR). METHODS: Single nucleotide polymorphisms (SNPs) associated with the seven AIDs were extracted from the IEU GWAS database, and the SNPs were quality-controlled using strict screening criteria. The association between AIDs and BC risk was assessed by inverse-variance weighted (IVW), MR-Egger regression and Weighted median method. The heterogeneity of SNPs was evaluated by Cochran Q test. MR-Egger intercept test and MR-PRESSO global test were used to test the horizontal pleiotropy of SNPs. Both sides with potential causal associations were validated using the validation set. RESULTS: Our result showed that genetically predicted RA was significantly associated with an increased risk of BC (IVW OR = 1.214, 95 % CI = 1.062-1.388, P = 0.005). MS nominally increased the risk of BC (IVW OR = 1.095, 95 % CI = 1.005-1.193, P = 0.037), consistent with the results of the MR analysis of the BC validation cohort. However SLE, T1D, UC, CD, and MG were not causally associated with BC risk (P > 0.05). The sensitivity analyses showed that there was no heterogeneity or horizontal pleiotropy in our findings. CONCLUSION: This study provides evidence of a causal relationship between AIDs and BC risk at the genetic level, confirming a causal relationship between RA and MS in increasing the risk of BC.
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Enfermedades Autoinmunes , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Análisis de la Aleatorización Mendeliana , Polimorfismo de Nucleótido Simple , Neoplasias de la Vejiga Urinaria , Humanos , Neoplasias de la Vejiga Urinaria/genética , Neoplasias de la Vejiga Urinaria/epidemiología , Enfermedades Autoinmunes/genética , Enfermedades Autoinmunes/epidemiología , Factores de RiesgoRESUMEN
Polypropylene (PP) mesh is commonly used in repairing abdominal wall hernia (AWH). However, the use of synthetic prosthesis comes with the risk of developing a prosthetic infection, resulting in delayed healing, secondary surgery, and potentially increased mortality. To address these issues, a facile surface functionalization strategy for PP mesh based on phytic acid (PA) and polyhexamethylene guanidine (PHMG) was constructed through a one-step co-deposition process, referred to as the PA/PHMG coating. The development of PA/PHMG coating is mainly attributed to the surface affinity of PA and the electrostatic interactions between PA and PHMG. The PA/PHMG coating could be completed within 4 h under mild conditions. The prepared PA/PHMG coatings on PP mesh surfaces exhibited desirable biocompatibility toward mammalian cells and excellent antibacterial properties against the notorious "superbug" methicillin-resistant Staphylococcus aureus (MRSA) and tetracycline-resistant Escherichia coli (TRE). The PA/PHMG-coated PP meshes showed killing ratios of over 99% against MRSA in an infected abdominal wall hernia repair model. Furthermore, histological and immunohistochemical analysis revealed a significantly attenuated degree of neutrophil infiltration in the PA/PHMG coating group, attributed to the decreased bacterial numbers alleviating the inflammatory response at the implant sites. Meanwhile, the pristine PP and PA/PHMG-coated meshes showed effective tissue repair, with the PA/PHMG coating group exhibiting enhanced angiogenesis compared with pristine PP meshes, suggesting superior tissue restoration. Additionally, PP meshes with the highest PHMG weight ratio (PA/PHMG(3)) exhibited excellent long-term robustness under phosphate-buffered saline (PBS) immersion with a killing ratio against MRSA still exceeding 95% after 60 days of PBS immersion. The present work provides a facile and promising approach for developing antibacterial implants.
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Antibacterianos , Staphylococcus aureus Resistente a Meticilina , Polipropilenos , Mallas Quirúrgicas , Polipropilenos/química , Antibacterianos/farmacología , Antibacterianos/química , Staphylococcus aureus Resistente a Meticilina/efectos de los fármacos , Animales , Escherichia coli/efectos de los fármacos , Herniorrafia/instrumentación , Pared Abdominal/cirugía , Pared Abdominal/patología , Materiales Biocompatibles Revestidos/química , Materiales Biocompatibles Revestidos/farmacología , Ratones , Hernia Abdominal/cirugía , Humanos , Pruebas de Sensibilidad MicrobianaRESUMEN
BACKGROUND: Physical activity may be associated with health benefits for people with epilepsy. It remains unclear how the prevalence of physical activity has changed at a national level over the years and whether this prevalence varies between subgroups. METHODS: The National Health and Interview Survey, which was conducted from 2010 to 2017 and again in 2022, was used for our nationally representative study. This study explored the trends and disparities in meeting physical activity guidelines among US individuals with epilepsy and non-epilepsy adults. RESULTS: The prevalence of adults with epilepsy meeting physical activity guidelines was consistently lower and remained unchanged compared to those without epilepsy. Among the population with epilepsy, the prevalence of aerobic physical activity was 38.1 % (95 % CI, 32.6 %-43.5 %) in 2010 and 39.0 % (95 % CI, 33.4 %-44.7 %) in 2017 (P for trend = 0.84), and remained unchanged in 2022 (39.1 %). For muscle-strength training, the prevalence was 17.5 % (95 % CI, 13.3 %-21.7 %) in 2010 and 18.8 % (95 % CI, 14.8 %-22.8 %) in 2017 (P for trend = 0.82). The prevalence for both activities combined was 12.4 % (95 % CI, 8.7 %-16.2 %) in 2010 and 16.6 % (95 % CI, 12.8 %-20.5 %) in 2017 (P for trend = 0.26). The prevalence of aerobic physical activity varied by educational attainment, body mass index, comorbid conditions, alcohol-drinking status, and epilepsy status. CONCLUSION: This study suggests that the adherence rate to meeting physical activity guidelines among US adults with epilepsy was at a low level and had not improved over time. This finding highlights the need for additional nationwide efforts to promote physical activity in the US population with epilepsy.
Asunto(s)
Epilepsia , Ejercicio Físico , Humanos , Epilepsia/epidemiología , Ejercicio Físico/fisiología , Masculino , Adulto , Femenino , Estados Unidos/epidemiología , Persona de Mediana Edad , Prevalencia , Adulto Joven , Anciano , Adolescente , Encuestas EpidemiológicasRESUMEN
Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.