Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Objective To explore the effect of influenza vaccination on the prevention of respiratory tract infection in preschool children. Methods The clinical data of 400 preschool children (1-6 years old) who were diagnosed with respiratory tract infection for the first time in department of pediatrics of Xi'an Third Hospital and second department of respiratory medicine of Xi'an Children's Hospital were retrospectively analyzed from January 2023 to December 2023, including acute bronchitis, upper respiratory tract infection and pneumonia. According to the actual influenza vaccination status, the patients were divided into vaccination group (n=210) and non-vaccination group (n=190). The incidence of respiratory tract infection was compared between both groups. The fever duration, average course of disease, hospitalization rate, clinical symptoms scores (fever, cough, nasal congestion, sore throat), inflammation indicators [C-reactive protein (CRP), white blood cell count (WBC), neutrophil percentage (NE%)] and recurrence rate after 6 months of follow-up were compared. Results The incidence of respiratory tract infection in the vaccination group was significantly lower than that in the non-vaccination group (21.43% vs 43.16%, P<0.05), and the hospitalization rate was significantly lower compared with that in the non-vaccination group (P<0.05). The scores of fever, cough, nasal congestion and sore throat were lower in the vaccination group than those in the non-vaccination group (P<0.05), and the CRP, WBC and NE% were significantly lower compared to the non-vaccination group (P<0.05). After 6 months of follow-up, the recurrence rate in the vaccination group was 11.11% (5/45), which was significantly lower than 26.83% (22/82) in the non-vaccination group (χ²=0.038, P=4.288<0.05). Conclusion Influenza vaccination can effectively reduce the incidence of respiratory tract infection in preschool children, relieve the symptoms and shorten the disease course after infection. Its preventive effect on influenza is particularly significant, suggesting the importance of strengthening influenza vaccination in preschool children.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Medicinal plant underground diseases, typified by root rot, directly result in a significant reduction in both the yield and quality of traditional Chinese medicine(TCM) because of its hidden occurrence and difficulty in prevention and control. Prevention and control measures depending on chemical pesticides bring potential risks to the safety of TCM and easily cause environmental pollution. The introduction of the new version of Good Agricultural Practice for Chinese Crude Drugs(GAP) and the enhancement of pesticide residue limit standards for TCM and decoction pieces in Chinese Pharmacopoeia(2025 edition) have elevated the requirements for green and efficient disease prevention and control technologies of TCM. This paper provided a comprehensive overview of the advancements over the past two decades in the diversity of pathogens, characteristics and hazards associated with disease occurrence, the main prevention and control agents currently registered, and the prevention and control techniques for TCM root rot. In light of the environmental backdrop of global climate change and the increasing frequency of disastrous climates, coupled with the challenges encountered in root rot prevention and control amidst the new paradigm of large-scale and standardized cultivation of TCM, the paper proposed the key direction of basic research and the application strategy for new technologies that integrate "early prevention and control-soil health-digital monitoring", including precise pathogen identification and early disease diagnosis, exploration of host disease resistance mechanisms and disease-resistant breeding, field soil health and ecological regulation, monitoring of fungicide resistance and rational pesticide use, as well as the integration of digital technology and intelligent plant protection. The ultimate goal is to advance the application of green plant protection technology in TCM, thereby providing robust scientific and technological support to ensure the healthy and sustainable development of the TCM agriculture sector.
Plant Diseases/microbiology* ; Plant Roots/microbiology* ; Plants, Medicinal/growth & development* ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVES: To investigate the effects of methylenetetrahydrofolate reductase (MTHFR) rs1801133 and γ-glutamyl hydrolase (GGH) rs11545078 gene polymorphisms on plasma concentrations and toxicity following high-dose methotrexate (MTX) therapy in children with acute lymphoblastic leukemia (ALL). METHODS: Children with ALL treated at the Xuzhou Children's Hospital of Xuzhou Medical University from January 2021 to April 2024 were selected for this study. Genotypes of MTHFR rs1801133 and GGH rs11545078 were determined using multiplex polymerase chain reaction. MTX plasma concentrations were measured by enzyme-multiplied immunoassay technique, and toxicity was graded according to the Common Terminology Criteria for Adverse Events version 5.0. The relationships between MTHFR rs1801133 and GGH rs11545078 genotypes and both MTX plasma concentrations and associated toxicities were analyzed. RESULTS: In the low-risk ALL group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 72 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05), and the GGH rs11545078 genotype was associated with increased MTX plasma concentrations at 48 hours (P<0.05). In the intermediate- to high-risk group, the MTHFR rs1801133 genotype was associated with the occurrence of reduced hemoglobin (P<0.05), and the GGH rs11545078 genotype was associated with the occurrence of thrombocytopenia (P<0.05). CONCLUSIONS Detection of MTHFR rs1801133 and GGH rs11545078 genotypes can be used to predict increased MTX plasma concentrations and the occurrence of toxic reactions in high-dose MTX treatment of ALL, enabling timely interventions to enhance safety.
Humans ; Methotrexate/toxicity* ; Methylenetetrahydrofolate Reductase (NADPH2)/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/blood* ; Male ; Female ; Child ; Child, Preschool ; gamma-Glutamyl Hydrolase/genetics* ; Antimetabolites, Antineoplastic/adverse effects* ; Infant ; Polymorphism, Genetic ; Adolescent ; Genotype ; Polymorphism, Single Nucleotide

OBJECTIVES: To evaluate the effectiveness of single-balloon and double-balloon enteroscopy in diagnosing pediatric small bowel diseases and assess the diagnostic efficacy of computed tomography enterography (CTE) for small bowel diseases using enteroscopy as the reference standard. METHODS: Clinical data from 576 children who underwent enteroscopy at Hunan Children's Hospital between January 2017 and December 2023 were retrospectively collected. The children were categorized based on enteroscopy type into the single-balloon enteroscopy (SBE) group (n=457) and double-balloon enteroscopy (DBE) group (n=119), and the clinical data were compared between the two groups. The sensitivity and specificity of CTE for diagnosing small bowel diseases were evaluated using enteroscopy results as the standard. RESULTS: Among the 576 children, small bowel lesions were detected by enteroscopy in 274 children (47.6%).There was no significant difference in lesion detection rates or complication rates between the SBE and DBE groups (P>0.05), but the DBE group had deeper insertion, longer procedure time, and higher complete small bowel examination rate (P<0.05). The complication rate during enteroscopy was 4.3% (25/576), with 18 cases (3.1%) of mild complications and 7 cases (1.2%) of severe complications, which improved with symptomatic treatment, surgical, or endoscopic intervention. Among the 412 children who underwent CTE, the sensitivity and specificity for diagnosing small bowel diseases were 44.4% and 71.3%, respectively. CONCLUSIONS SBE and DBE have similar diagnostic efficacy for pediatric small bowel diseases, but DBE is preferred for suspected deep small bowel lesions and comprehensive small bowel examination. Enteroscopy in children demonstrates relatively good overall safety. CTE demonstrates relatively low sensitivity but comparatively high specificity for diagnosing small bowel diseases.
Retrospective Studies ; Treatment Outcome ; Double-Balloon Enteroscopy/statistics & numerical data* ; Single-Balloon Enteroscopy/statistics & numerical data* ; Humans ; Male ; Female ; Child ; Operative Time ; Tomography, X-Ray Computed/statistics & numerical data* ; Sensitivity and Specificity ; Intestine, Small/surgery* ; Intestinal Diseases/surgery*

OBJECTIVE: To analyze the significance of total vitamin D (tVD), total procollagen type I amino-terminal propeptide (tPINP) and β-CrossLaps (β-CTx) in the staging and prognosis of patients with multiple myeloma (MM). METHODS: A total of 54 patients with newly diagnosed MM admitted to the Second Affiliated Hospital of Fujian Medical University from 2020 to 2022 were selected as the observation group (MM group), and 50 healthy persons who underwent physical examinations in our hospital were selected as the control group. The expression levels of tVD, tPINP and β-CTx in the two groups were detected by chemiluminescence method. The differences in the expression levels of tVD, tPINP and β-CTx among MM patients at different ISS stages were analyzed. The expression levels of tVD, tPINP and β-CTx in MM patients with different levels of hemoglobin (Hb), serum calcium (Ca), creatinine (Crea), albumin (ALB), β₂-microglobulin (β₂-MG) and lactate dehydrogenase (LDH) were compared. The correlations between the expression levels of tVD, tPINP, β-CTx and the aforementioned clinical parameters were analyzed, respectively. The relationship between the expression levels of tVD, tPINP, β-CTx and the progression-free survival (PFS) of MM patients was analyzed. RESULTS: The expression level of tVD in the MM group was significantly lower than that in the control group (21.73±14.45 ng/ml vs 30.78±9.94 ng/ml, P =0.022). The expression level of β-CTx in the MM group was significantly higher than that in the control group (1.43±0.99 ng/ml vs 0.53±0.29 ng/ml, P =0.013). The tVD level in MM patients with ISS stage I-II was significantly higher than that of MM patients with ISS stage III (29.50±14.59 ng/ml vs 12.62±7.73 ng/ml, P =0.028), indicating that the higher the ISS stage, the lower the tVD level. The tPINP and β-CTx levels in MM patients with high Ca levels (>2.65 mmol/L) were significantly higher than those in patients with low Ca levels (≤2.65 mmol/L) (P =0.016, P =0.021). The tVD level of MM patients was positively correlated with the ALB level (r =0.570), tPINP was positively correlated with Ca and β₂-MG levels (r =0.791,r =0.673), and β-CTx was positively correlated with tPINP level (r =0.616). The PFS of the low tVD expression group was significantly lower than that of the high tVD expression group (P =0.041). CONCLUSION The expression level of tVD is decreased in MM patients, which can be used as an indicator to evaluate the disease stage and prognosis of the patients. The β-CTx expression level is increased in MM patients. tPINP and β-CTx may be correlated with clinical symptoms such as osteolytic lesions and renal function changes in MM patients.
Humans ; Multiple Myeloma/pathology* ; Procollagen/blood* ; Vitamin D/blood* ; Prognosis ; Peptide Fragments/blood* ; Collagen Type I/blood* ; Female ; Male ; Middle Aged ; Aged ; Neoplasm Staging

OBJECTIVE: To summarize the relevant evidence of testicular cancer patients' fertility management which provides a basis for fertility guidance for young testicular cancer patients. METHODS: The evidence, guidelines, expert consensus, evidence summary, systematic review and Meta-analysis on fertility-related clinical decision-making were searched from computer decision support systems, relevant guideline websites, evidence-based databases, original research databases, and professional association websites at home and abroad. The search period was set dating from the establishment of the database to July 2024. Two researchers with evidence-based nursing research background independently completed the quality evaluation, evidence extraction and summary of the literature. RESULTS: A total of 21 articles were selected, including 4 clinical decisions, 8 guidelines, 4 expert consensuses, 3 systematic reviews and 2 Meta-analyses. Thirty-three pieces of best evidence from six aspects were summarized, including fertility assessment, fertility counseling, fertility preservation timing, fertility preservation regimen, anti-tumor therapy and fertility, and contraceptive timing. CONCLUSION The best evidence summarized in this study provides a basis for clinical medical staff to carry out fertility management in testicular cancer patients. In clinical application, medical staff need to fully consider the patient's wishes in combination with the clinical situation, and promote the maximum benefit of the patient, so as to further improve the life quality of the patients.
Humans ; Male ; Evidence-Based Medicine ; Fertility ; Fertility Preservation ; Testicular Neoplasms/therapy* ; Systematic Reviews as Topic

OBJECTIVE: To investigate the anti-tumor effects of cinobufacini (CINO) on hepatocellular carcinoma (HCC) induced by des-gamma-carboxy-prothrombin (DCP) and to uncover the underlying mechanisms. METHODS: The inhibitory effect of CINO on HCC cell proliferation was evaluated using the cell counting kit-8 method, and the apoptosis rate was quantified using flow cytometry. Immunofluorescence and Western blot analyses were used to investigate the differential expression of proteins associated with cell growth, apoptosis, migration, and invasion pathways after CINO treatment. The therapeutic potential of CINO for HCC was confirmed, and the possibility of combining cinobufacini with c-Met inhibitor for the treatment of primary HCC was further validated by in vivo experiments. RESULTS: Under the induction of DCP, CINO inhibited the activity of HCC cells, induced apoptosis, and inhibited migration and invasion. Upon the induction of DCP, CINO regulated c-Met activation and the activation of the phosphatidylinositol-3 kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase kinase/extracellular signal-regulated kinase (MEK/ERK) pathways. In a mouse model of HCC, CINO exhibited significant antitumor effects by inhibiting the phosphorylation of c-Met and the downstream PI3K/AKT and MEK/ERK pathways in tumor tissues. CONCLUSIONS CINO inhibited HCC cell growth, promoted apoptosis, and suppressed HCC cell invasion and migration by targeting c-Met and PI3K/AKT and MEK/ERK signaling pathways under DCP induction.
Carcinoma, Hepatocellular/drug therapy* ; Proto-Oncogene Proteins c-met/metabolism* ; Liver Neoplasms/drug therapy* ; Signal Transduction/drug effects* ; Animals ; Humans ; Cell Movement/drug effects* ; Apoptosis/drug effects* ; Cell Proliferation/drug effects* ; Amphibian Venoms/therapeutic use* ; Cell Line, Tumor ; Neoplasm Metastasis ; Cell Survival/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Neoplasm Invasiveness ; Mice, Inbred BALB C ; Mice, Nude ; Mice ; Male ; Bufanolides/therapeutic use* ; Protein Precursors ; Prothrombin ; Biomarkers