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A three-component defluorinative haloalkylation of alkenes with trifluoromethyl compounds and TBAX (X = Cl, Br) via dual photoredox/copper catalysis is reported. The mild conditions are compatible with a wide array of activated trifluoromethyl aromatics bearing diverse substituents, and various nonactivated terminal and internal alkenes, enabling straightforward access to synthetically valuable γ-gem-difluoroalkyl halides with high efficiency. Mechanistic studies indicate that the [Cu] complexes not only serve as XAT catalysts but also facilitate the SET reduction of trifluoromethyl groups by photocatalysts. Additionally, the resulting alkyl halide products can serve as versatile conversion intermediates for the synthesis of a diverse range of γ-gem-difluoroalkyl compounds.
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Objective: The research aims to develop an advanced and precise lung cancer screening model based on Convolutional Neural Networks (CNN). Methods: Based on the health medical big data platform of Shandong University, we developed a VGG16-Based CNN lung cancer screening model. This model was trained using the Computed Tomography scans data of patients from Pingyi Traditional Chinese Medicine Hospital in Shandong Province, from January to February 2023. Data augmentation techniques, including random resizing, cropping, horizontal flipping, color jitter, random rotation and normalization, were applied to improve model generalization. We used five-fold cross-validation to robustly assess performance. The model was fine-tuned with an SGD optimizer (learning rate 0.001, momentum 0.9, and L2 regularization) and a learning rate scheduler. Dropout layers were added to prevent the model from relying too heavily on specific neurons, enhancing its ability to generalize. Early stopping was implemented when validation loss did not decrease over 10 epochs. In addition, we evaluated the model's performance with Area Under the Curve (AUC), Classification accuracy, Positive Predictive Value (PPV), and Negative Predictive Value (NPV), Sensitivity, Specificity and F1 score. External validation used an independent dataset from the same hospital, covering January to February 2022. Results: The training and validation loss and accuracy over iterations show that both accuracy metrics peak at over 0.9 by iteration 15, prompting early stopping to prevent overfitting. Based on five-fold cross-validation, the ROC curves for the VGG16-Based CNN model, demonstrate an AUC of 0.963 ± 0.004, highlighting its excellent diagnostic capability. Confusion matrices provide average metrics with a classification accuracy of 0.917 ± 0.004, PPV of 0.868 ± 0.015, NPV of 0.931 ± 0.003, Sensitivity of 0.776 ± 0.01, Specificity of 0.962 ± 0.005 and F1 score of 0.819 ± 0.008, respectively. External validation confirmed the model's robustness across different patient populations and imaging conditions. Conclusion: The VGG16-Based CNN lung screening model constructed in this study can effectively identify lung tumors, demonstrating reliability and effectiveness in real-world medical settings, and providing strong theoretical and empirical support for its use in lung cancer screening.
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This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Additionally, Bayesian co-localization analyses were used to examine associations of specific loci across traits. Our study discovered significant genomic correlations and shared loci, indicating complex genetic interactions among these metabolic diseases. We found several shared single nucleotide variants and risk loci, notably highlighting the role of the immune system and endocrine pathways in these diseases. Particularly, rs2476601 and its associated gene PTPN22 appear to play a crucial role in the connection between type 2 diabetes mellitus, hypothyroidism/mucous oedema and hypoglycaemia. These findings enhance our understanding of the genetic underpinnings of these diseases and open new potential avenues for targeted therapeutic and preventive strategies. The results underscore the importance of considering pleiotropic effects in deciphering the genetic architecture of complex diseases, especially metabolic ones.
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Pleiotropía Genética , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Desequilibrio de Ligamiento , Enfermedades Metabólicas , Polimorfismo de Nucleótido Simple , Humanos , Enfermedades Metabólicas/genética , Polimorfismo de Nucleótido Simple/genética , Desequilibrio de Ligamiento/genética , Teorema de Bayes , Análisis de la Aleatorización Mendeliana , Diabetes Mellitus Tipo 2/genética , Epistasis GenéticaRESUMEN
BACKGROUND: The adverse prognostic impact of diabetes on hypertrophic cardiomyopathy (HCM) is poorly understood. We sought to explore the underlying mechanisms in terms of structural and functional remodelling in HCM patients with coexisting diabetes (HCM-DM). METHODS: A total of 45 HCM-DM patients were retrospectively included. Isolated HCM controls (HCM patients without diabetes) were matched to HCM-DM patients in terms of maximal wall thickness, age, and gender distribution. Left ventricular (LV) and atrial (LA) performance were evaluated using cardiac magnetic resonance feature tracking strain analyses. The associations between diabetes and LV/LA impairment were investigated by univariable and multivariable linear regression. RESULTS: Compared with the isolated HCM controls, the HCM-DM patients had smaller end-diastolic volume and stroke volume, lower ejection fraction, larger mass/volume ratio and impaired strains in all three directions (all P < 0.05). In terms of the LA parameters, HCM-DM patients presented impaired LA reservoir and conduit strain/strain rate (all P < 0.05). Among all HCM patients, comorbidity with diabetes was independently associated with a low LV ejection fraction (ß = - 6.05, P < 0.001) and impaired global longitudinal strain (ß = 1.40, P = 0.007). Moreover, compared with the isolated HCM controls, HCM-DM patients presented with more myocardial fibrosis according to late gadolinium enhancement, which was an independent predictor of impaired LV global radial strain (ß = - 45.81, P = 0.008), LV global circumferential strain (ß = 18.25, P = 0.003), LA reservoir strain (ß = - 59.20, P < 0.001) and strain rate (ß = - 2.90, P = 0.002). CONCLUSIONS: Diabetes has adverse effects on LV and LA function in HCM patients, which may be important contributors to severe manifestations and outcomes in those patients. The present study strengthened the evidence of the prevention and management of diabetes in HCM patients.
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Función del Atrio Izquierdo , Cardiomiopatía Hipertrófica , Diabetes Mellitus , Imagen por Resonancia Cinemagnética , Valor Predictivo de las Pruebas , Volumen Sistólico , Función Ventricular Izquierda , Remodelación Ventricular , Humanos , Masculino , Femenino , Persona de Mediana Edad , Cardiomiopatía Hipertrófica/diagnóstico por imagen , Cardiomiopatía Hipertrófica/fisiopatología , Cardiomiopatía Hipertrófica/complicaciones , Estudios Retrospectivos , Anciano , Diabetes Mellitus/epidemiología , Diabetes Mellitus/fisiopatología , Diabetes Mellitus/diagnóstico , Factores de Riesgo , Adulto , Pronóstico , Disfunción Ventricular Izquierda/fisiopatología , Disfunción Ventricular Izquierda/diagnóstico por imagen , Disfunción Ventricular Izquierda/etiología , Comorbilidad , Remodelación AtrialRESUMEN
CF2-containing compounds hold significant potential in drug discovery, organic synthesis, and materials science. However, synthesizing various CF2-containing building blocks from a single compound remains challenging. Here, we present a Cu-catalyzed, switchable defluoroborylation and hydrodefluorination of trifluoromethylated alkynes, yielding four types of CF2-containing compounds. The chemo- and regio-selective sp2/sp3 1,2-diborylation and sp2 monoborylation of 1-(trifluoromethyl)alkynes are controlled by adjusting the solvent and ligand quantity. Additionally, altering the base allows selective generation of gem-difluoroalkenes or difluoromethylalkenes. Notably, our method prevents over-defluorination of the CF3 group on unsaturated C-C bonds during nucleophilic additions, preserving the pharmaceutically valuable CF2 group. Experimental data and density functional theory (DFT) calculations elucidate the regioselectivities of Cu-Bpin addition and the regulatory role of the ligand in selective deborylation processes.
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OBJECTIVE: To explore the main factors affecting early dental caries among preschool children aged 3-6 years in Xingtai City to formulate effective preventive measures. METHODS: A cross-sectional study was conducted on 570 preschool children aged 3-6 years in Xingtai City through questionnaire surveys and oral examinations to understand their dental caries situation. Multifactorial logistic regression analysis was used to analyse the main influencing factors for the occurrence of dental caries in preschool children. RESULTS: Univariate analysis showed statistically significant differences in age (χ2 = 2.636, p = 0.008), father's education level (χ2 = 4.207, p < 0.001), mother's education level (χ2 = 4.217, p < 0.001), daily tooth brushing frequency (χ2 = 3.160, p = 0.002), age of starting tooth brushing (χ2 = 8.756, p < 0.001), mouth rinsing after meals (χ2 = 89.401, p < 0.001), Streptococcus mutans positivity (χ2 = 133.503, p < 0.001), non-sweet snack consumption frequency (χ2 = 5.962, p < 0.001), snack flavour preference (χ2 = 116.119, p < 0.001), use of fluoridated toothpaste (χ2 = 75.639, p < 0.001), regular oral examinations (χ2 = 98.711, p < 0.001), sugary drink consumption frequency (χ2 = 10.370, p < 0.001) and sweet food consumption frequency (χ2 = 9.261, p < 0.001) between the caries and non-caries groups. Multifactorial analysis revealed that older age (odds ratio [OR] = 5.342, 95% confidence interval [CI]: 1.434-6.631), later initiation of tooth brushing (OR = 3.244, 95% CI: 2.413-5.424), S. mutans positivity (OR = 5.357, 95% CI: 4.529-8.563), high snack consumption frequency (OR = 3.452, 95% CI: 2.634-5.442), high sugary drink consumption frequency (OR = 4.414, 95% CI: 2.534-6.451) and high sweet food consumption frequency (OR = 4.531, 95% CI: 3.421-6.354) were risk factors for dental caries. Higher father's educational level (OR = 0.724, 95% CI: 0.564-0.891), higher mother's educational level (OR = 0.641, 95% CI: 0.601-0.813), high daily tooth brushing frequency (OR = 0.572, 95% CI: 0.423-0.864), mouth rinsing after meals (OR = 0.743, 95% CI: 0.643-0.813), use of fluoridated toothpaste (OR = 0.657, 95% CI: 0.553-0.931) and regular oral examinations (OR = 0.443, 95% CI: 0.352-0.747) were protective factors against dental caries (all p < 0.05). CONCLUSION: Multiple factors result in early dental caries in preschool children aged 3-6 years; however, the most influential factors are older age and high snack consumption, as well as high sugary and sweet food/drink consumption.
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Caries Dental , Cepillado Dental , Humanos , Caries Dental/epidemiología , Caries Dental/prevención & control , Preescolar , Estudios Transversales , Masculino , Femenino , Niño , Cepillado Dental/estadística & datos numéricos , Factores de Riesgo , Escolaridad , Bocadillos , Encuestas y Cuestionarios , Factores de Edad , Streptococcus mutans/aislamiento & purificaciónRESUMEN
OBJECTIVE: Phenotypic misclassification in genetic association analyses can impact the accuracy of PRS-based prediction models. The bias reduction method proposed by Tong et al. (2019) has demonstrated its efficacy in reducing the effects of bias on the estimation of association parameters between genotype and phenotype while minimizing variance by employing chart reviews on a subset of the data for validating phenotypes, however its improvement of subsequent PRS prediction accuracy remains unclear. Our study aims to fill this gap by assessing the performance of simulated PRS models and estimating the optimal number of chart reviews needed for validation. METHODS: To comprehensively assess the efficacy of the bias reduction method proposed by Tong et al. in enhancing the accuracy of PRS-based prediction models, we simulated each phenotype under different correlation structures (an independent model, a weakly correlated model, a strongly correlated model) and introduced error-prone phenotypes using two distinct error mechanisms (differential and non-differential phenotyping errors). To facilitate this, we used genotype and phenotype data from 12 case-control datasets in the Alzheimer's Disease Genetics Consortium (ADGC) to produce simulated phenotypes. The evaluation included analyses across various misclassification rates of original phenotypes as well as quantities of validation set. Additionally, we determined the median threshold, identifying the minimal validation size required for a meaningful improvement in the accuracy of PRS-based predictions across a broad spectrum. RESULTS: This simulation study demonstrated that incorporating chart review does not universally guarantee enhanced performance of PRS-based prediction models. Specifically, in scenarios with minimal misclassification rates and limited validation sizes, PRS models utilizing debiased regression coefficients demonstrated inferior predictive capabilities compared to models using error-prone phenotypes. Put differently, the effectiveness of the bias reduction method is contingent upon the misclassification rates of phenotypes and the size of the validation set employed during chart reviews. Notably, when dealing with datasets featuring higher misclassification rates, the advantages of utilizing this bias reduction method become more evident, requiring a smaller validation set to achieve better performance. CONCLUSION: This study highlights the importance of choosing an appropriate validation set size to balance between the efforts of chart review and the gain in PRS prediction accuracy. Consequently, our study establishes a valuable guidance for validation planning, across a diverse array of sensitivity and specificity combinations.
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Enfermedad de Alzheimer , Fenotipo , Humanos , Enfermedad de Alzheimer/genética , Genotipo , Estudios de Casos y Controles , Predisposición Genética a la Enfermedad , Estudios de Asociación Genética/métodos , Estudio de Asociación del Genoma Completo/métodos , Polimorfismo de Nucleótido Simple , Simulación por Computador , Modelos GenéticosRESUMEN
OBJECTIVE: In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like Generative Pre-trained Transformers (GPTs) and Llama present a significant opportunity for extracting relations related to acupoint locations from textual knowledge sources. This study aims to explore the performance of LLMs in extracting acupoint-related location relations and assess the impact of fine-tuning on GPT's performance. MATERIALS AND METHODS: We utilized the World Health Organization Standard Acupuncture Point Locations in the Western Pacific Region (WHO Standard) as our corpus, which consists of descriptions of 361 acupoints. Five types of relations ("direction_of", "distance_of", "part_of", "near_acupoint", and "located_near") (n = 3174) between acupoints were annotated. Four models were compared: pre-trained GPT-3.5, fine-tuned GPT-3.5, pre-trained GPT-4, as well as pretrained Llama 3. Performance metrics included micro-average exact match precision, recall, and F1 scores. RESULTS: Our results demonstrate that fine-tuned GPT-3.5 consistently outperformed other models in F1 scores across all relation types. Overall, it achieved the highest micro-average F1 score of 0.92. DISCUSSION: The superior performance of the fine-tuned GPT-3.5 model, as shown by its F1 scores, underscores the importance of domain-specific fine-tuning in enhancing relation extraction capabilities for acupuncture-related tasks. In light of the findings from this study, it offers valuable insights into leveraging LLMs for developing clinical decision support and creating educational modules in acupuncture. CONCLUSION: This study underscores the effectiveness of LLMs like GPT and Llama in extracting relations related to acupoint locations, with implications for accurately modeling acupuncture knowledge and promoting standard implementation in acupuncture training and practice. The findings also contribute to advancing informatics applications in traditional and complementary medicine, showcasing the potential of LLMs in natural language processing.
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AIMS: Phyllodes tumours (PTs) are relatively common fibroepithelial tumours comprising epithelial and stromal component. Usually, PTs show a spindle cell morphology with a fibroblast phenotype, while some tumour cells exhibit epithelioid morphological features and sarcomatoid transformation. However, the molecular characteristics of this morphology subset remain unclear. This study aimed to summarise the clinicopathological, morphological and molecular characteristics of seven cases of PT with epithelioid features. METHODS: Morphological and clinicopathological characteristics were observed and retrieved. Immunohistochemistry, immunofluorescence and electron microscope were performed on seven cases of epithelioid PT to explore immunophenotypic and ultrastructural characteristics. Transcriptomic and proteomic analyses were conducted to compare differentially expressed genes and proteins between epithelioid PT and classical PT. RESULTS: Patients with epithelioid PT exhibit a high recurrence rate (42.8%). Morphologically, in addition to having epithelioid cytological features, neoplastic stromal cells exhibit moderate to marked atypia and often exhibit sarcomatoid transformation, similar to the characteristics of borderline PT. Transcriptomic and proteomic analyses demonstrated that epithelioid PTs are distinct from classical PTs in gene expression and protein abundance levels. Immunohistochemical analysis showed that among all differentially expressed proteins, epithelioid PT showed abnormal p16/retinoblastoma expression patterns, similar to those of malignant PT. CONCLUSIONS: Epithelioid PT has unique morphological characteristics, biological behaviour and protein expression profile, which meets the diagnostic criteria of borderline PT and is prone to sarcomatoid transformation. It may be a special morphological subgroup of borderline PT and has partial characteristics of malignant PT, which should be taken seriously in pathological diagnosis and clinical management.
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2,5-Diformylfuran (DFF) is a significant biomass-derived compound with diverse applications in novel furan-based materials, fragrances, fuel additives, and drug synthesis. A pivotal challenge in DFF synthesis is developing a method to produce DFF under mild conditions using sustainable feedstocks. In this study, an affordable 4-hydroxy-2,2,6,6-tetramethylpiperidine (TEMPOL)- assisted Cu(OAc)2 catalytic system for aerobic oxidation reaction of HMF to DFF in liquid sunlight methanol solvent was developed. The effects of parameters such as metal species, catalyst amount, solvent species, ligand structure, and reaction temperature were systematically investigated. The evolution of product distribution in the reaction solution at various times was monitored and analyzed using 1H-NMR spectroscopy. FT-IR and ESI-MS characterizations were employed to integrate experimental findings and elucidate the reaction mechanism. The highest DFF yield of 96% and complete conversion of HMF were obtained. Furthermore, a total DFF yield of 68.6% was achieved from fructose using a two-steps method, demonstrating the potential for scalable production. The establishment of this catalytic system presents a novel approach for the selective preparation of DFF from sustainable feedstocks.
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Endometrial polyps commonly contribute to female infertility, and hysteroscopic resection is the established surgical approach for their treatment. Numerous resection methods are available, with the most used and cost-effective options being cold resection employing micro-scissors or hot resection using an electric loop. However, both methods involve sharp resection, posing a challenge in achieving complete polyp removal while avoiding damage to the uterine endometrium. To address this issue, this study proposes an innovative approach: the combined use of the 6 Fr micro-scissors and forceps under hysteroscopy. The method entails utilizing 6 Fr micro-scissors to initially remove large polyps, followed by using 6 Fr micro-forceps to extract the remaining polyp tissue expeditiously and bluntly near the basal layer of the endometrium. This approach not only prevents surgical damage to the basal layer of the endometrium but also mitigates the risk of residual polyps resulting from incomplete resection. This method is particularly suitable for women with fertility requirements, offering additional considerations for the selection of treatment options for endometrial polyp resection.
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Histeroscopía , Pólipos , Femenino , Histeroscopía/métodos , Histeroscopía/instrumentación , Pólipos/cirugía , Humanos , Enfermedades Uterinas/cirugía , Instrumentos Quirúrgicos , Endometrio/cirugía , Endometrio/patologíaRESUMEN
The spontaneous formation of cyclodextrin (CD)-oil inclusion complexes (ICs) and their further growth into patterned crystals present a bottom-up route to the fabrication of periodic macroscopic structure. Although the inclusion processes are well established for the molecules, understanding intermediate structures during the crystal growth and emerging of persistent crystalline order has been lacking. Here we build a hierarchy of oriented micro/nanostructures of CD-oil ICs in solution by choosing different oil guests including several straight-chain alkanes of C12, C14 and C16, oleic acid (OA), glycerol trioleate (TG) and soybean oil (SO), in an attempt to reveal the roles of oil guests in the formation of their crystallites. Remarkably, the ICs tend to grow into clusters and terminate at a certain finite size as long columns or lamella plates with well-defined facets, dependent on the type of oil used. For the first time, we report a non-equilibrium growth of crystallites with surface faceting directed by the guests by means of Arching and Bundling.
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BACKGROUND: Cervical spine fracture-dislocations in patients with ankylosing spondylitis (AS) are mostly unstable and require surgery. However, osteoporosis, one of the comorbidities for AS, could lead to detrimental prognoses. There are few accurate assessments of bone mineral density in AS patients. AIM: To analyze Hounsfield units (HUs) for assessing bone mineral density in AS patients with cervical fracture-dislocation. METHODS: The HUs from C2 to C7 of 51 patients obtained from computed tomography (CT) scans and three-dimensional reconstruction of the cervical spine were independently assessed by two trained spinal surgeons and statistically analyzed. Inter-reader reliability and agreement were assessed by interclass correlation coefficient. RESULTS: The HUs decreased gradually from C2 to C7. The mean values of the left and right levels were significantly higher than those in the middle. Among the 51 patients, 25 patients (49.02%) may be diagnosed with osteoporosis, and 16 patients (31.37%) may be diagnosed with osteopenia. CONCLUSION: The HUs obtained by cervical spine CT are feasible for assessing bone mineral density with excellent agreement in AS patients with cervical fracture-dislocation.
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2D ferroelectric materials have attracted extensive research interest due to potential applications in nonvolatile memory, nanoelectronics and optoelectronics. However, the available 2D ferroelectric materials are scarce and most of them are limited by the uncontrollable preparation. Herein, a novel 2D ferroelectric material AgCrS2 is reported that are controllably synthesized in large-scale via salt-assist chemical vapor deposition growth. By tuning the growth temperature from 800 to 900 °C, the thickness of AgCrS2 nanosheets can be precisely modulated from 2.1 to 40 nm. Structural and nonlinear optical characterizations demonstrate that AgCrS2 nanosheet crystallizes in a non-centrosymmetric structure with high crystallinity and remarkable air stability. As a result, AgCrS2 of various thicknesses display robust ferroelectric polarization in both in-plane (IP) and out-of-plane (OOP) directions with strong intercorrelation and high ferroelectric phase transition temperature (682 K). Theoretical calculations suggest that the ferroelectricity in AgCrS2 originates from the displacement of Ag atoms in AgS4 tetrahedrons, which changes the dipole moment alignment. Moreover, ferroelectric switching is demonstrated in both lateral and vertical AgCrS2 devices, which exhibit exotic nonvolatile memory behavior with distinct high and low resistance states. This study expands the scope of 2D ferroelectric materials and facilitates the ferroelectric-based nonvolatile memory applications.
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BACKGROUND: Limited research has explored the potential association between the Triglyceride-Glucose (TyG) and mortality, especially in individuals with Helicobacter pylori (H. pylori) infection. This study seeks to investigate the correlation between the TyG index and H. pylori infection and investigate whether the associations between the TyG index exposure and all-cause mortality are mediated by H. pylori infection. METHODS: The study utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018, incorporating a final sample size of 2,187 participants. Both univariable and multivariable-adjusted logistic regression analyses were employed to examine the relationship between H. pylori infection and relevant covariates. To assess the association between TyG index, and all-cause mortality in individuals with or without H. pylori infection, Cox regression analysis, and restricted regression cubic spline analysis were implemented. RESULTS: A significant positive correlation was observed between the TyG index and an elevated risk of H. pylori infection [OR 1.157, 95% CI (1.383 ~ 1.664)]. This correlation persisted even after adjusting for confounding factors [OR 1.189, 95% CI (1.003, 1.411), P < 0.05]. Furthermore, in patients with positive H. pylori infection, a noteworthy nonlinear correlation between the TyG index and all-cause mortality was identified (P = 0.0361). With an increase in the TyG index, all-cause mortality exhibited a corresponding rise, particularly following adjustment for all potential confounding factors. Conversely, in patients with negative H. pylori infection, no significant association was observed between the TyG index and all-cause mortality after adjusting for potential confounding factors. CONCLUSION: A higher TyG index was linked to increased H. pylori infection risks. Participants in the higher quantile group of the TyG index are positively associated with higher all-cause mortality compared to the higher quantile group of the TyG index in H. pylori-positive participants instead of H. pylori-negative participants.
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AIMS: The relationship between frailty and mortality among individuals with varying diabetic statuses represents a burgeoning area of concern and scholarly interest within the medical community. However, there are limited studies that explore the relationship between frailty and mortality, as well as cause-specific mortality among individuals with non-diabetes, prediabetes, and diabetes patients. Hence, this study aims to investigate the relationship between the frailty statues and all-cause mortality, as well as cause-specific mortality in individuals with varying diabetic statuses using the data in the NHANES database. METHODS: The study utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018, incorporating a final sample size of 57, 098 participants. Both univariable and multivariable-adjusted logistic regression analyses, as well as Cox regression analysis were employed to examine the relationship between frailty index (FI) and mortality. RESULTS: This study, found a significant positive correlation between the frailty and the increased risk of all-cause mortality non-diabetic [OR 4.277, 95%CI (3.982, 4.594), P < 0.001], prediabetic [OR 2.312, 95%CI (2.133, 2.506), P < 0.001], and diabetic patients [OR 3.947, 95%CI (3.378, 4.611), P < 0.001]. This correlation still existed even after adjusting for confounding factors including age, sex, BMI, poverty, fasting insulin, education, smoke, alcohol drink, waist, hypertension, hyperlipidemia, fasting glucose, HbA1c, eGFR, creatinine and total bilirubin. Our result also suggested a significant positive correlation between the frailty index and the increased risk of CVD mortality among non-diabetic [OR 3.095, 95%CI (2.858, 3.352), P < 0.001] and prediabetic [OR 5.985, 95%CI (5.188, 6.904), P < 0.001] individuals. However, in patients with diabetes, the correlation between frailty and CVD mortality lost significance after adjusting for possible confounding factors [OR 1.139, 95%CI (0.794, 1.634), P > 0.05]. CONCLUSION: A nonlinear relationship has been identified between the FI and all-cause mortality, as well as CVD mortality in non-diabetic and pre-diabetic population. In diabetic patients, there was a significant positive correlation between the frailty and the increased risk of all-cause mortality, but not with CVD mortality. Renal function and liver function might potentially acted as an intermediary factor that elevated the risk of CVD mortality in frail patients with diabetes.
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The widespread adoption of small-molecule fluorescence detection methodologies in scientific research and industrial contexts can be ascribed to their inherent merits, including elevated sensitivity, exceptional selectivity, real-time detection capabilities, and non-destructive characteristics. In recent years, there has been a growing focus on small-molecule fluorescent probes engineered with sulfur elements, aiming to detect a diverse array of biologically active species. This review presents a comprehensive survey of sulfur-based fluorescent probes published from 2017 to 2023. The diverse repertoire of recognition sites, including but not limited to N, N-dimethylthiocarbamyl, disulfides, thioether, sulfonyls and sulfoxides, thiourea, thioester, thioacetal and thioketal, sulfhydryl, phenothiazine, thioamide, and others, inherent in these sulfur-based probes markedly amplifies their capacity for detecting a broad spectrum of analytes, such as metal ions, reactive oxygen species, reactive sulfur species, reactive nitrogen species, proteins, and beyond. Owing to the individual disparities in the molecular structures of the probes, analogous recognition units may be employed to discern diverse substrates. Subsequent to this classification, the review provides a concise summary and introduction to the design and biological applications of these probe molecules. Lastly, drawing upon a synthesis of published works, the review engages in a discussion regarding the merits and drawbacks of these fluorescent probes, offering guidance for future endeavors.
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Colorantes Fluorescentes , Azufre , Colorantes Fluorescentes/química , Azufre/química , Azufre/análisis , Humanos , AnimalesRESUMEN
Dissecting the regulatory mechanisms controlling mammalian transcripts from production to degradation requires quantitative measurements of mRNA flow across the cell. We developed subcellular TimeLapse-seq to measure the rates at which RNAs are released from chromatin, exported from the nucleus, loaded onto polysomes, and degraded within the nucleus and cytoplasm in human and mouse cells. These rates varied substantially, yet transcripts from genes with related functions or targeted by the same transcription factors and RNA-binding proteins flowed across subcellular compartments with similar kinetics. Verifying these associations uncovered a link between DDX3X and nuclear export. For hundreds of RNA metabolism genes, most transcripts with retained introns were degraded by the nuclear exosome, while the remaining molecules were exported with stable cytoplasmic lifespans. Transcripts residing on chromatin for longer had extended poly(A) tails, whereas the reverse was observed for cytoplasmic mRNAs. Finally, machine learning identified molecular features that predicted the diverse life cycles of mRNAs.