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OBJECTIVE: Clinical practice guidelines (CPGs) for Integrated Traditional Chinese and Western Medicine (TCM and WM) are important medical documents used to assist medical decision-making and are of great significance for standardizing clinical pathways. However, due to the constraints of text format, it is difficult for Integrated TCM and WM CPGs to play a real role in medical practice. In addition, how to standardize the structure and semantic relationships between Integrated TCM and WM CPG knowledge, and realize the construction of computable, sharable and reliable CPGs, remains an urgent issue to be addressed. Therefore, we are proposing an ontology of CPGs for Integrated TCM and WM. METHODS: We first initialized domain concepts and relationships to ensure the accuracy of the ontology knowledge structure. We then screened CPGs that meet the standards for Integrated TCM and WM, analyzed and classified the contents, and extracted the common structures. Based on the seven-step ontology construction method combined with inference-complement, referring to the representation methods and hierarchical relationships of terms and concepts in MeSH, ICD-10, SNOMED-CT, and other ontologies and terminology sets, we formed the concept structure and semantic relationship tables for the ontology. We also achieved the matching and mapping between the ontology and reference ontologies and term sets. Next, we defined the aspects and constraints of properties, selected multiple Integrated TCM and WM CPGs as instances to populate, and used ontology reasoning tools and formulated defined inference rules to reason and extend the ontology. Finally, we evaluated the performance of the ontology. RESULTS: The content of the Integrated TCM and WM CPGs is divided into nine parts: basic information, background, development method, clinical question, recommendation, evidence, conclusion, result, and reason for recommendations. The Integrated TCM and WM CPG ontology has 152 classes and defines 90 object properties and 114 data properties, with a maximum classification depth of 4 layers. The terms of disease, drug and examination item names in the ontology have been standardized. CONCLUSIONS: This study proposes an Integrated TCM and WM CPG ontology. The ontology adopts a modular design, which has both sharing and scaling ability, and can express rich guideline knowledge. It provides important support for the semantic processing and computational application of guideline documents.

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BACKGROUND: Abnormal biological behaviour of keratinocytes (KCs) is a critical pathophysiological manifestation of psoriasis. Ferroptosis is programmed cell death induced by the accumulation of lipid reactive oxygen species (ROS) in the presence of increased intracellular iron ions or inhibition of GPX4. OBJECTIVES: The purpose of this study was to investigate the effects of ferroptosis on the biological behaviour of Keratinocytes (KCs) in psoriasis vulgaris and its possible regulatory mechanisms in clinical samples, cells, and mouse models. METHODS: We first examined the differences in the expression of GPX4 and 4-HNE between psoriasis and normal human lesions. And detected KRT6, FLG, and inflammatory cytokines after inducing ferroptosis in animal and cell models by RT-qPCR, Western blot, immunohistochemistry, and flow cytometry. RESULTS: We found that GPX4 was decreased and that the oxidation product 4-hydroxy-2-nonenal (HNE) was increased in the skin lesions of patients with psoriasis vulgaris. The expression level of GPX4 correlates with the severity of skin lesions. Moreover, inducing ferroptosis promoted the expression of FLG and reduced the expression of KRT6 and inflammatory cytokines in vitro, and alleviated the phenotype of skin lesions in vivo. LIMITATIONS: Our study has limitations, notably small sample size. Larger clinical trials are necessary to investigate the association between ferroptosis and disease progression further. More research is necessary to explore how the ferroptosis inducer RSL3 regulates the abnormal biological behaviour of KCs at both cellular and animal levels and establish ferroptosis inhibitors as controls. CONCLUSIONS: This study confirms the existence of ferroptosis in psoriatic lesions, which may be inversely correlated with disease severity. The ferroptosis inducer RSL3 ameliorated psoriatic symptoms by improving the abnormal biological behaviour of KCs.

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Modelos Animales de Enfermedad , Ferroptosis , Queratinocitos , Fosfolípido Hidroperóxido Glutatión Peroxidasa , Psoriasis , Psoriasis/patología , Psoriasis/metabolismo , Psoriasis/inmunología , Ferroptosis/fisiología , Queratinocitos/metabolismo , Queratinocitos/patología , Humanos , Animales , Ratones , Proyectos Piloto , Fosfolípido Hidroperóxido Glutatión Peroxidasa/metabolismo , Fosfolípido Hidroperóxido Glutatión Peroxidasa/genética , Aldehídos/metabolismo , Femenino , Masculino , Adulto , Queratina-6/metabolismo , Citocinas/metabolismo , Piel/patología , Piel/metabolismo , Piel/inmunología , Persona de Mediana Edad , Resorcinoles/farmacología , Especies Reactivas de Oxígeno/metabolismo , Carbolinas

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It is essential to systematically consider social, economic, and natural endowments in managing and allocating water resources. However, few studies have comprehensively quantitatively evaluated the allocation of regional water resources from a socio-hydrology perspective and provided recommendations. To explore this research gap, we have constructed a tightly coupled framework that integrates system dynamics models and optimization algorithms to carry out an innovative redistribution of water resources in Shaanxi Province. The system dynamics model simulation results showed that the error was almost always within 10% over the research period, indicating robust simulation capability and laying a solid foundation for subsequent model coupling. The coupled model achieves convergence in approximately 30 generations by formulating the optimization problem with four individual objectives. Optimizing four objectives concurrently results in convergence around the 150th generation. The optimized Pareto solution sets visually demonstrate the trade-offs between different objectives. In the optimized water allocation schedule, the water consumption in Yulin exhibits a change of 1.22 ×108m3, reflecting the most significant optimization effects on agricultural and domestic water allocation. The results indicated that the comprehensive Gini coefficient typically ranged between 0.2 and 0.3. Over the period from the year 2010-2021, the Gini coefficient exhibited a declining trend, signifying a positive trajectory in water resource allocation throughout the research period and a high level of fairness. The annual total green WF of grain in Weinan was the highest at 14.26 ×108m3, followed by Xianyang at 9.52 ×108m3, and the lowest in Tongchuan at 0.54 ×108m3. The annual average amount of blue WF of grain is the highest in Hanzhong, at 11.33 ×108m3, followed by Weinan at 9.60 ×108m3, and the lowest in Tongchuan at 0.14 ×108m3. The coupled framework proposed in this study exhibits significant innovation, scalability, and practical efficiency. It can inspire future research and decision-making and holds the potential for application in other regions.

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Hidrología , Recursos Hídricos , Humanos , Modelos Teóricos , Abastecimiento de Agua , Agricultura , Conservación de los Recursos Naturales , Agua , Algoritmos

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BACKGROUND: In recent years, there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data (RCD). These studies rely on algorithms to identify specific health conditions (e.g. diabetes or sepsis) for statistical analyses. However, there has been substantial variation in the algorithm development and validation, leading to frequently suboptimal performance and posing a significant threat to the validity of study findings. Unfortunately, these issues are often overlooked. METHODS: We systematically developed guidance for the development, validation, and evaluation of algorithms designed to identify health status (DEVELOP-RCD). Our initial efforts involved conducting both a narrative review and a systematic review of published studies on the concepts and methodological issues related to algorithm development, validation, and evaluation. Subsequently, we conducted an empirical study on an algorithm for identifying sepsis. Based on these findings, we formulated specific workflow and recommendations for algorithm development, validation, and evaluation within the guidance. Finally, the guidance underwent independent review by a panel of 20 external experts who then convened a consensus meeting to finalize it. RESULTS: A standardized workflow for algorithm development, validation, and evaluation was established. Guided by specific health status considerations, the workflow comprises four integrated steps: assessing an existing algorithm's suitability for the target health status; developing a new algorithm using recommended methods; validating the algorithm using prescribed performance measures; and evaluating the impact of the algorithm on study results. Additionally, 13 good practice recommendations were formulated with detailed explanations. Furthermore, a practical study on sepsis identification was included to demonstrate the application of this guidance. CONCLUSIONS: The establishment of guidance is intended to aid researchers and clinicians in the appropriate and accurate development and application of algorithms for identifying health status from RCD. This guidance has the potential to enhance the credibility of findings from observational studies involving RCD.

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Algoritmos , Estado de Salud , Estudios Observacionales como Asunto , Humanos , Estudios Observacionales como Asunto/métodos , Estudios Observacionales como Asunto/normas , Reproducibilidad de los Resultados , Recolección de Datos/métodos , Recolección de Datos/normas , Recolección de Datos/estadística & datos numéricos

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Developmental exposure to nonylphenol (NP) results in irreversible impairments of the central nervous system (CNS). The neural precursor cell (NPC) pool located in the subgranular zone (SGZ), a substructure of the hippocampal dentate gyrus, is critical for the development of hippocampal circuits and some hippocampal functions such as learning and memory. However, the effects of developmental exposure to NP on this pool remain unclear. Thus, our aim was to clarify the impacts of developmental exposure to NP on this pool and to explore the potential mechanisms. Animal models of developmental exposure to NP were created by treating Wistar rats with NP during pregnancy and lactation. Our data showed that developmental exposure to NP decreased Sox2-and Ki67-positive cells in the SGZ of offspring. Inhibited activation of Shh signaling and decreased levels of its downstream mediators, E2F1 and cyclins, were also observed in pups developmentally exposed to NP. Moreover, we established the in vitro model in the NE-4C cells, a neural precursor cell line, to further investigate the effect of NP exposure on NPCs and the underlying mechanisms. Purmorphamine, a small purine-derived hedgehog agonist, was used to specifically modulate the Shh signaling. Consistent with the in vivo results, exposure to NP reduced cell proliferation by inhibiting the Shh signaling in NE-4C cells, and purmorphamine alleviated this reduction in cell proliferation by restoring this signaling. Altogether, our findings support the idea that developmental exposure to NP leads to inhibition of the NPC proliferation and the NPC pool depletion in the SGZ located in the dentate gyrus. Furthermore, we also provided the evidence that suppressed activation of Shh signaling may contribute to the effects of developmental exposure to NP on the NPC pool.

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Proliferación Celular , Giro Dentado , Proteínas Hedgehog , Células-Madre Neurales , Fenoles , Ratas Wistar , Transducción de Señal , Animales , Giro Dentado/efectos de los fármacos , Giro Dentado/metabolismo , Giro Dentado/citología , Células-Madre Neurales/efectos de los fármacos , Células-Madre Neurales/metabolismo , Células-Madre Neurales/citología , Proteínas Hedgehog/metabolismo , Fenoles/farmacología , Fenoles/toxicidad , Femenino , Embarazo , Ratas , Transducción de Señal/efectos de los fármacos , Proliferación Celular/efectos de los fármacos , Purinas/farmacología , Morfolinas/farmacología , Efectos Tardíos de la Exposición Prenatal/inducido químicamente , Efectos Tardíos de la Exposición Prenatal/metabolismo , Masculino , Factores de Transcripción SOXB1/metabolismo , Línea Celular

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Dried blood spot (DBS) technique has become a new popular topic in anti-doping field in recent years due to its advantages of sample stability and easy operation. It can be employed as a supplementary method to routine urine analysis. However, the small volume of DBS samples (usually 10-20 µL) significantly reduces the application value of this technique. Therefore, the development of sensitive detection methods for the analysis of prohibited substances in DBS is particularly important. In this study, based on the characteristics of low molecular mass peptide (LMMP) drugs, systematic optimization strategies were utilized for the first time to establish a sensitive detection method for LMMPs in DBS. Without using DMSO to enhance mass spectrometry ionization efficiency of peptides, the limits of detection (LOD) ranged between 0.05 and 3.74 ng/mL, significantly better than the previously reported method (0.5-20 ng/mL). This method was validated according to the guidelines of the World Anti-Doping Agency (WADA), and corresponding post-administration study was conducted, demonstrating that the method could be applied to routine analysis of LMMP drugs in DBS. Moreover, since DMSO is not involved, this method also has the potential to simultaneously detect both LMMP and small molecular drugs.

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Background: The impact of altitude on the prognosis of patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI) deserves further discussion and research. Methods: We conducted a post hoc analysis of a prospective observational study involving 5453 patients post-PCI, divided into medium-altitude and low-altitude groups. To control for confounding factors, propensity score matching was employed to pair patients with similar baseline characteristics between the two groups. The impact of altitude factors on patients' prognosis post-PCI was examined through endpoint events over a 2-year follow-up period. Results: During the 2-year follow-up, patients at medium altitude exhibited a lower risk of MACE (including cardiovascular mortality, myocardial infarction, revascularization, and stroke) compared to those at low altitude (1196 versus 1196 patients [medium-altitude versus low-altitude, respectively]; hazard ratio [HR], 0.781 [95 % CI, 0.629-0.969]; P = 0.025) during 2-year follow-up. Even after excluding stroke, a significant difference in heart-related adverse events (HRAE) persisted between the two groups (HR, 0.794; 95 % CI, 0.636-0.991; P = 0.042). The incidences of individual MACE components were not significantly different between the two groups. Conclusions: Patients post-PCI residing at medium altitude exhibited a lower risk of 2-year MACE compared to those at low altitude. Further research is necessary to provide more robust evidence.

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Lattice dynamics are critical to photovoltaic material performance, governing dynamic disorder, hot-carrier cooling, charge-carrier recombination, and transport. Soft metal-halide perovskites exhibit particularly intriguing dynamics, with Raman spectra exhibiting an unusually broad low-frequency response whose origin is still much debated. Here, we utilize ultra-low frequency Raman and infrared terahertz time-domain spectroscopies to provide a systematic examination of the vibrational response for a wide range of metal-halide semiconductors: FAPbI3, MAPbI x Br3-x , CsPbBr3, PbI2, Cs2AgBiBr6, Cu2AgBiI6, and AgI. We rule out extrinsic defects, octahedral tilting, cation lone pairs, and "liquid-like" Boson peaks as causes of the debated central Raman peak. Instead, we propose that the central Raman response results from an interplay of the significant broadening of Raman-active, low-energy phonon modes that are strongly amplified by a population component from Bose-Einstein statistics toward low frequency. These findings elucidate the complexities of light interactions with low-energy lattice vibrations in soft metal-halide semiconductors emerging for photovoltaic applications.

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CONTEXT: Glucagon plays a role in the development of type 2 diabetes, yet its role in prediabetes (preDM) remains uncertain. OBJECTIVE: To evaluate glucagon levels in the fasting state and its response to glucose inhibition in preDM through meta-analysis. METHODS: A systematic search across Pubmed, Embase, Web of Science, and Cochrane Library identified studies assessing glucagon levels during 75 g oral glucose tolerance test (OGTT) in both preDM and normal glucose tolerance (NGT) cohorts. Data on glucagon, glucose, and insulin were pooled using a random-effect model. RESULTS: Although glucagon levels decreased in both preDM and NGT groups upon glucose challenge, glucagon levels at 0 hours, 0.5 hours, 1 hour, and 1.5 hours in preDM were significantly higher compared to NGT, despite higher glucose levels at all time points and higher insulin levels at 0 hours, 1 hour, 1.5 hours, and 2 hours during OGTT. Subgroup analysis revealed that in studies using the radioimmunoassay method, glucagon levels in preDM were higher at 0.5 hours and 1 hour than NGT, while in studies using the ELISA method, glucagon levels were similar to those of the NGT group despite higher glucose in preDM compared to NGT. Fasting glucagon level was inadequately suppressed in both impaired glucose tolerance (IGT) and impaired fasting glucose (IFG). Responsiveness to glucose inhibition was preserved in IFG, while glucagon level in IGT group at 0.5 hours after glucose intake was not suppressed and was higher than NGT. CONCLUSION: Glucagon was not adequately suppressed during OGTT in preDM. Glucagon dysregulation is a contributing mechanism underlying both IFG and IGT.

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Glucemia , Glucagón , Prueba de Tolerancia a la Glucosa , Estado Prediabético , Humanos , Glucagón/sangre , Estado Prediabético/sangre , Estado Prediabético/metabolismo , Glucemia/análisis , Glucemia/metabolismo , Diabetes Mellitus Tipo 2/sangre , Diabetes Mellitus Tipo 2/metabolismo , Insulina/sangre , Ayuno/sangre

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BACKGROUND: Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there is no consensus on SAP prediction, and application of existing predictors is limited. The aim of this study was to develop a machine learning model to predict SAP after sICH. METHODS: We retrospectively reviewed 748 patients diagnosed with sICH and collected data from 4 dimensions-demographic features, clinical features, medical history, and laboratory tests. Five machine learning algorithms-logistic regression, gradient boosting decision tree, random forest, extreme gradient boosting, and category boosting-were used to build and validate the predictive model. We also applied recursive feature elimination with cross-validation to obtain the best feature combination for each model. Predictive performance was evaluated by area under the receiver operating characteristic curve. RESULTS: SAP was diagnosed in 237 patients. The model developed by category boosting yielded the most satisfactory outcomes overall with area under the receiver operating characteristic curves in the training set and test set of 0.8307 and 0.8178, respectively. CONCLUSIONS: The incidence of SAP after sICH in our center was 31.68%. Machine learning could potentially provide assistance in the prediction of SAP after sICH.

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Hemorragia Cerebral , Aprendizaje Automático , Neumonía , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Estudios Retrospectivos , Hemorragia Cerebral/complicaciones , Accidente Cerebrovascular/complicaciones , Valor Predictivo de las Pruebas , Anciano de 80 o más Años , Pronóstico

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Atmospheric nitrogen deposition can alter soil microbial communities and further impact the structure and function of forest ecosystems. However, most studies are focused on positive or negative effects after nitrogen addition, and few studies pay attention to its interruption. In order to investigate whether interruption after different levels of short-term N additions still benefit soil health, we conducted a 2-year interruption after a 4-year short-term nitrogen addition (10 and 20 kg N·hm-2·yr-1) experiment; then, we compared soil microbial diversity and structure and analyzed soil physicochemical properties and their correlations before and after the interruption in Larix olgensis forest soil in northeast China. The results showed that soil ecological stabilization of Larix olgensis forest further improved after the interruption compared to pre-interruption. The TN, C:P, N:P, and C:N:P ratios increased significantly regardless of the previous nitrogen addition concentration, and soil nutrient cycling was further promoted. The relative abundance of the original beneficial microbial taxa Gemmatimonas, Sphingomonas, and Pseudolabrys increased; new beneficial bacteria Ellin6067, Massilia, Solirubrobacter, and Bradyrhizobium appeared, and the species of beneficial soil microorganisms were further improved. The results of this study elucidated the dynamics of the bacterial community before and after the interruption of short-term nitrogen addition and could provide data support and a reference basis for forest ecosystem restoration strategies and management under the background of global nitrogen deposition.

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BACKGROUND: Simulation is widely utilized in medical education. Exploring the effectiveness of high-fidelity simulation of clinical research within medical education may inform its integration into clinical research training curricula, finally cultivating physician-scientist development. METHODS: Standard teaching scripts for both clinical trial and cross-sectional study simulation were designed. We recruited undergraduates majoring in clinical medicine at 3th grade into a pre-post intervention study. Additionally, a cross-sectional survey randomly selected medical undergraduates at 4th or 5th grade, medical students in master and doctor degree as external controls. Self-assessment scores of knowledge and practice were collected using a 5-point Likert scale. Changes in scores were tested by Wilcoxon signed-rank test and group comparisons were conducted by Dunn's tests with multiple corrections. Multivariable quantile regressions were used to explore factors influencing the changes from baseline. RESULTS: Seventy-eight undergraduates involved the clinical trial simulation and reported improvement of 1.60 (95% CI, 1.48, 1.80, P < 0.001) in knowledge and 1.82 (95% CI, 1.64, 2.00, P < 0.001) in practice score. 83 undergraduates involved in the observational study simulation and reported improvement of 0.96 (95% CI, 0.79, 1.18, P < 0.001) in knowledge and 1.00 (95% CI, 0.79, 1.21, P < 0.001) in practice. All post-intervention scores were significantly higher than those of the three external control groups, P < 0.001. Higher agreement on the importance of clinical research were correlated with greater improvements in scores. Undergraduates in pre-post study showed high confidence in doing a future clinical research. CONCLUSION: Our study provides evidence supporting the integration of simulation into clinical research curriculum for medical students. The importance of clinical research can be emphasized during training to enhance learning effect.

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Investigación Biomédica , Curriculum , Educación de Pregrado en Medicina , Estudiantes de Medicina , Humanos , Educación de Pregrado en Medicina/métodos , Estudios Transversales , Femenino , Masculino , Investigación Biomédica/educación , Competencia Clínica , Entrenamiento Simulado , Evaluación Educacional

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Self-management is important for patients suffering from cerebrovascular events after neurosurgical procedures. An increasing number of artificial intelligence (AI)-assisted tools have been used in postoperative health management. ChatGPT is a new trend dialog-based chatbot that could be used as a supplemental tool for seeking health information. Responses from ChatGPT version 3.5 and 4.0 toward 13 questions raised by experienced neurosurgeons were evaluated in this exploratory study for their consistency and appropriateness blindly by the other three neurosurgeons. The readability of response text was investigated quantitively by word count and the Gunning Fog and Flesch-Kincaid indices. Results showed that the chatbot could provide relatively stable output between the two versions on consistency and appropriateness (χ² = 0.348). As for readability, there was a higher demand for readers to comprehend the output text in the 4.0 version (more counts of words; lower Flesch-Kincaid reading ease score; and higher Flesch-Kincaid grade level). In general, the capacity of ChatGPT to deliver effective health information is still under debate.

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The functional performance of immune cells relies on a complex transcriptional regulatory network. The three-dimensional structure of chromatin can affect chromatin status and gene expression patterns, and plays an important regulatory role in gene transcription. Currently available techniques for studying chromatin spatial structure include chromatin conformation capture techniques and their derivatives, chromatin accessibility sequencing techniques, and others. Additionally, the recently emerged deep learning technology can be utilized as a tool to enhance the analysis of data. In this review, we elucidate the definition and significance of the three-dimensional chromatin structure, summarize the technologies available for studying it, and describe the research progress on the chromatin spatial structure of dendritic cells, macrophages, T cells, B cells, and neutrophils.

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BACKGROUND: Breast cancer is the most prevalent cancer among women globally, and surgical procedures continue to be the primary treatment. However, over 50% of patients experience preoperative anxiety due to the unknown and fear associated with surgery. Although drug therapy is commonly used to address this anxiety, its side effects have led to a heated debate regarding its effectiveness. Consequently, non-pharmacological therapies, such as preoperative education, have emerged as an alternative approach to alleviate anxiety. WeChat, a widely popular social media platform, offers a public platform that can potentially be utilized for effective preoperative education. This study aims to evaluate the use of WeChat public platform as a tool for preoperative education in patients undergoing breast surgery. METHODS: This is a prospective, randomized, and controlled trial will involve 392 adult women scheduled for breast cancer resection. Participants will be randomly assigned to either the WeChat education group or the regular group. In addition to regular preoperative visits, the WeChat education group will also watch science videos through the WeChat public platform. The regular group will only receive education from ward nurses during preoperative visits. The primary outcome measure will be the incidence of preoperative anxiety, defined by scores of the State Anxiety Inventory (SAI) exceeding 40 points. Secondary outcome measures include the incidence of severe anxiety (SAI > 44) on the day before surgery, incidence of anxiety 72 h after surgery, incidence of severe anxiety 72 h after surgery, NRS scores for pain at rest and during activity 24, 48, and 72 h after surgery, incidence of nausea and vomiting within 24 h after surgery, subjective sleep score at 1 week postoperatively, quality of life QoR-15 scores at 1 and 3 months postoperatively, incidence of chronic pain at 3 months postoperatively, bowel function recovery, length of hospital stay, and hospitalization expenses. DISCUSSION: This is the first clinical trial to investigate the use of WeChat public platform for delivering preoperative education on perioperative anxiety in breast cancer patients. By utilizing the renowned WeChat public platform, our study aims to improve patient outcomes by providing video education that explains the disease, surgery, and anesthesia in a more accessible manner, thereby reducing the incidence of perioperative anxiety. If our hypothesis is confirmed, this non-pharmacological approach can be universally acknowledged as a cost-effective and practical method in clinical care. Its application can also be extended to other medical fields beyond breast cancer. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05291494. Registered on 29 December 2021.

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Neoplasias de la Mama , Calidad de Vida , Adulto , Humanos , Femenino , Neoplasias de la Mama/cirugía , Estudios Prospectivos , Ansiedad/diagnóstico , Ansiedad/etiología , Ansiedad/prevención & control , Cuidados Preoperatorios/métodos , Ensayos Clínicos Controlados Aleatorios como Asunto

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Cancer is an aging-related disease, while aging plays an important role in the development process of tumor, thus the two are inextricably associated. Telomere attrition is one of the recognized hallmark events of senescence. Hence, targeting telomerase which could extends telomere sequences to treat tumors is widely favored. Cancer cells rely on high activity of telomerase to maintain a strong proliferative potential. By inhibiting the expression or protein function of telomerase, the growth of cancer cells can be significantly suppressed. In addition, the human immune system itself has a defense system against malignant tumors. However, excessive cell division results in dramatic shortening on telomeres and decline in the function of immune organs that facilitates cancer cell evasion. It has been shown that increasing telomerase activity or telomere length of these immune cells can attenuate senescence, improve cellular viability, and enhance the immunosuppressive microenvironment of tumor. In this paper, we review the telomerase-targeting progress using different anti-tumor strategies from the perspectives of cancer cells and immune cells, respectively, as well as tracking the preclinical and clinical studies of some representative drugs for the prevention or treatment of tumors.

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Implementation of clinical practice guidelines (CPG) is a complex and challenging task. Computer technology, including artificial intelligence (AI), has been explored to promote the CPG implementation. This study has reviewed the main domains where computer technology and AI has been applied to CPG implementation. PubMed, Embase, Web of science, the Cochrane Library, China National Knowledge Infrastructure database, WanFang DATA, VIP database, and China Biology Medicine disc database were searched from inception to December 2021. Studies involving the utilization of computer technology and AI to promote the implementation of CPGs were eligible for review. A total of 10429 published articles were identified, 117 met the inclusion criteria. 21 (17.9%) focused on the utilization of AI techniques to classify or extract the relative content of CPGs, such as recommendation sentence, condition-action sentences. 47 (40.2%) focused on the utilization of computer technology to represent guideline knowledge to make it understandable by computer. 15 (12.8%) focused on the utilization of AI techniques to verify the relative content of CPGs, such as conciliation of multiple single-disease guidelines for comorbid patients. 34 (29.1%) focused on the utilization of AI techniques to integrate guideline knowledge into different resources, such as clinical decision support systems. We conclude that the application of computer technology and AI to CPG implementation mainly concentrated on the guideline content classification and extraction, guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration. The AI methods used for guideline content classification and extraction were pattern-based algorithm and machine learning. In guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration, computer techniques of knowledge representation were the most used.

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Inteligencia Artificial , Sistemas de Apoyo a Decisiones Clínicas , Humanos , Algoritmos , Computadores , Tecnología

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[This corrects the article DOI: 10.1021/acsenergylett.3c01368.].

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The dried blood spot (DBS) is a novel alternative matrix used in 2022 Beijing Winter Olympics and Paralympics. It is capable of distinguishing anabolic androgenic steroid (AAS) esters without the gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) confirmation. In this study, a method for detection of 22 anabolic steroid esters in DBS based on ultra-high liquid chromatography-mass spectrometry (UPLC-MS) with parallel reaction monitoring (PRM) was developed and validated. Methoxylamine was used as the derivatization reagent to improve the sensibility. Specificity, limit of detection (LOD), linearity, stability, robustness, and carryover were evaluated. Steroid esters are nine testosterone esters, six nandrolone esters, five boldenone esters, methenolone enanthate, and trenbolone acetate. UV spectra were determined by HPLC. And density functional theory (DFT) calculation methods could provide theoretical UV spectra data. Three basis set of B3LYP/6-31G(d), B3LYP/6-31+G(d, p), and WB97XD/6-31+G(d, p) were used for the geometry optimizations and TD-DFT calculation. The average deviation (%RD) of B3LYP/6-31+G(d) for all 44 ester oximes are less than 3.0%. This study for the first time provides a method to tentatively identify the 44 E/Z configurations of steroid oxime products.