ObjectiveTo evaluate the pregnancy outcomes of assisted reproductive technology （ART） in women with a history of thyroid cancer who retained fertility intentions after completing cancer treatment. MethodsA retrospective analysis was performed on 61 patients with a history of thyroid cancer who underwent in vitro fertilization/intracytoplasmic sperm microinjection and embryo transfer （IVF/ICSI-ET）. These patients were included as the case group. A total of 122 non-cancer patients who received ART during the same period were selected as the control group using 1∶2 matching based on age and oocyte retrieval time. Baseline characteristics， outcomes of the first ART cycle， and cumulative pregnancy outcomes were compared between the two groups. ResultsThere was no significant difference in the basic data， the total amount of gonadotropin （Gn） and the days of use between the case group and the control group （P>0.05）. However， the case group had significantly fewer retrieved oocytes， mature oocytes （MII）， lower fertilization and cleavage rates， and fewer transferable and high-quality embryos， as well as fewer embryos transferred during the first cycle （P < 0.05）. However， there was no significant difference in the rate of first embryo implantation and first clinical pregnancy between the two groups （P>0.05）. In the analysis of cumulative outcomes， the two groups did not show statistically significant differences in the cumulative pregnancy rate， clinical pregnancy rate per transfer cycle， the number of oocyte retrieval cycles required per live birth， the number of embryo transfer cycles required per live birth， and the number of embryos used for each live birth （P>0.05）. However， the cumulative live birth rate was significantly lower in the case group compared to the control group （P=0.005）. ConclusionAfter treatment for thyroid cancer， when ART is used to help pregnant women， the pregnancy outcome is comparable to that of women without tumors. Individualized reproductive management and timely fertility preservation strategies are recommended to optimize reproductive outcomes in this population.

Objective: To examine the changing trajectories of sleep problems and teacher support among first year middle school students and their covariant relationship,so as to provide theoretical basis for the prevention strategy of sleep problems for the first year junior high school students. Methods: In September 2020, a multistage cluster random sampling method was used to select 1 027 first year junior high school students from two schools of Anshun and Guiyang cities in Guizhou Province for survey and follow up assessments (T1:September 2020, T2:October 2020, T3:November 2020, T4:December 2020). The Student Perceived Teacher Support Behavior Questionnaire and Pittsburgh Sleep Quality Index Scale were administered to assess sleep problems and teacher support among first year junior high school students. Spearman correlation analysis was used to examine the relationship between sleep problems and teacher support. A multivariate latent growth curve model was employed to analyze the changing trajectories and covariant relationship between teacher support and sleep problems, followed by a multi group analysis. Results: For first year junior high school students, teacher support scores at T1-T4 were 4.00 (3.47, 4.53), 4.00 (3.47, 4.58), 3.95 (3.47, 4.61) and 4.00 (3.48, 4.67), respectively; sleep problem scores were 0.83 (0.50, 1.17), 0.67 (0.50, 1.17), 0.83 (0.50, 1.17) and 0.67 (0.33, 1.17), respectively. Spearman correlation analysis revealed that teacher support and sleep problems were negatively correlated across all four period ( r =-0.28 to -0.14, all P <0.01). Teacher support perceived by students showed a linear increasing trend (intercept=3.98, slope=0.02), while sleep problems showed a linear decreasing trend (intercept=0.86, slope= -0.02 ) (all P <0.05). The multivariate latent growth model indicated that the rate of increase in teacher support after enrollment effectively predicted the rate of decrease in sleep problem levels ( β=-0.34, P <0.01). Multigroup analysis showed that the covariant relationship was not moderated by gender or boarding status (both P >0.05). Conclusions The increase in teacher support experienced by first year junior high school students during the transition period after enrollment, accompanied by a reduction in sleep problems, constitutes a dynamic protective process. The process is not moderated by gender or boarding status.

To investigate the risk factors for acute kidney injury (AKI) following the use of amphotericin B deoxycholate and to develop a predictive model to guide clinical monitoring and intervention.

Objective: To construct a scientific and perfect evaluation index system of infectious disease prevention and control ability in colleges and universities, so as to provide reference tools for colleges and universities to effectively respond to infectious disease. Methods: The initial framework of the evaluation index system of infectious disease prevention and control ability in colleges and universities was constructed by using literature analysis method. Experts familiar with infectious disease prevention and control or school health work were selected to conduct two rounds( n =16，18) of Delphi expert consultation for determining the evaluation index system. Analytical hierarchy process was used to calculate the index weights and combined weights. About 198 prevention and control personnel were conveniently selected from 3 universities in Inner Mongolia Autonomous Region to comprehensively evaluate the evaluation indicators by using fuzzy comprehensive evaluation method. Results: After two rounds of Delphi consultation questionnaire, the effective recovery rates were 80.0% and 90.0%, the expert authority levels were 0.89 and 0.86, the expert harmony coefficients for Kendall W were 0.166 and 0.310, and the variation coefficient of each index was <0.25. Finally, the evaluation index system of infectious disease prevention and control ability of colleges and universities included 4 first level indicators, 14 second level indicators and 75 third level indicators. The weights of prevention and monitoring and early warning, organizational system guarantee, emergency management, rehabilitation and summary were 0.176, 0.476, 0.268 and 0.080, respectively. The top 3 weights of the secondary indexes were 0.623 for infectious disease surveillance and early warning, 0.595 for loss assessment and 0.370 for emergency response. The score of fuzzy comprehensive evaluation of the index system of infectious disease prevention and control ability in colleges and universities was 79.148, suggesting a high level. Conclusion The established evaluation index system of infectious disease prevention and control ability in colleges and universities is scientific and reasonable, which is conducive to provide tool reference for the evaluation of infectious disease prevention and control ability in colleges and universities.

RNA-binding proteins (RBPs) are ubiquitous components within cells, fulfilling essential functions in a myriad of biological processes. These proteins interact with RNA molecules to regulate gene expression at various levels, including transcription, splicing, transport, localization, translation, and degradation. Understanding the intricate network of RBP-RNA interactions is crucial for deciphering the complex regulatory mechanisms that govern cellular function and organismal development. Ultravidet (UV) cross-linking and immunoprecipitation (CLIP) stands out as a powerful approach designed to map the precise locations where RBPs bind to RNA. By using UV light to create covalent bonds between proteins and RNA, followed by immunoprecipitation to isolate the protein-RNA complexes, researchers can identify the direct targets of specific RBPs. The advent of high-throughput sequencing technologies has revolutionized CLIP, enabling the identification of not only the types but also the exact sequences of RNA bound by RBPs on a genome-wide scale. The evolution of CLIP has led to the development of specialized variants, each with unique features that address specific challenges and expand the scope of what can be studied. High-throughput sequencing CLIP (HITS-CLIP) was one of the first advancements, significantly increasing the throughput and resolution of RNA-protein interaction mapping. Photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) introduced the use of photoactivatable ribonucleosides to enhance cross-linking efficiency and specificity, reducing background noise and improving the detection of low-abundance RNA-protein interactions. Individual-nucleotide resolution CLIP (iCLIP) further refined the technique, achieving unprecedented precision by resolving individual nucleotides involved in RBP binding, which is particularly valuable for studying the fine details of RNA structure and function. Despite the remarkable progress, there remains room for improvement in CLIP technology. Researchers continue to seek methods to increase sensitivity, reduce technical variability, and improve the reproducibility of results. Advances in sample preparation, data analysis algorithms, and computational tools are critical for addressing these challenges. Moreover, the application of CLIP to more diverse biological systems, including non-model organisms and clinical samples, requires the development of tailored protocols and the optimization of existing ones. Looking forward, the field of RNA biology is poised to benefit greatly from ongoing innovations in CLIP technology. The exploration of non-canonical RNA-protein interactions, such as those involving long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), promises to reveal new layers of cellular regulation and may lead to the discovery of novel therapeutic targets. Furthermore, integrating CLIP data with other omics approaches, such as proteomics and metabolomics, will provide a more comprehensive understanding of the dynamic interplay between RNA and its binding partners within the cell. In conclusion, the continuous refinement and expansion of CLIP techniques have not only deepened our knowledge of RNA biology but have also opened up new avenues for investigating the molecular underpinnings of health and disease. As the technology matures, it is expected to play an increasingly pivotal role in both basic and applied research, contributing to the advancement of medical science and biotechnology.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Objective: To evaluate the performance of platelet efficacy score (PEscore) in predicting platelet transfusion efficacy in hematological patients. Methods: A total of 485 patients with hematological diseases, including 298 males (62.09±15.45 years) and 187 females (59.17±16.52 years) who received platelet transfusion from January 1, 2021 to December 31, 2024 were enrolled in this study. Clinical data of the patients such as diagnosis, gender, age, number of platelet transfusion, and platelet antibody data were analyzed to investigate the incidence and influencing factors of platelet transfusion refractoriness in hematological patients at our hospital. ROC curve was used to evaluate the performance of PEscore model in predicting platelet transfusion efficacy. The predictive performance of PEscore model was validated by calculating its sensitivity, specificity, and accuracy in 115 clinical cases. Results: The incidence of platelet transfusion refractoriness in 485 cases was 29.90% (145/485). Significant differences (P<0.05) were observed between the effective and ineffective platelet transfusion groups regarding the following factors: diagnosis: lymphoma [55.32% (26/47) vs 44.68% (21/47)], the number of previous platelet transfusions [≥25: 60.78% (31/51) vs 39.22% (20/51)], platelet antibody screening result [positive: 33.76% (53/157) vs 66.24% (104/157)], and platelet transfusion volume (×10 /L) [>6: 62.71% (74/118) vs 37.29% (44/118)]. The area under the ROC curve of PEscore was 0.876. The cut-off points and corresponding sensitivity and specificity were 19.90.59% and 69.44%, respectively. The results of clinical application showed that the sensitivity, specificity and accuracy of the PEscore model for predicting platelet transfusion were 87.50%, 93.41% and 92.17%, respectively. Conclusion: The incidence of platelet transfusion refractoriness in hematological patients is relatively high. PEscore prediction model has a good performance in predicting the effect of platelet transfusion, which can provide a reliable basis for predicting the effect of platelet transfusion in hematological patients before blood transfusion.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male