Objective To explore the factors affecting the quality of psychological assistance hotline connections in Shaanxi Province, and to provide a basis for optimizing services. Methods A total of 149 calls with suicidal tendencies were included from January to March 2022, and data were collected by 31 trained assessors through standardized questionnaires (general information, suicide risk, emotional intensity, and wiring characteristics). Results The results showed that 56.38% of the callers were female, with age groups concentrated between ≤ 18 years old (29.53%) and 19-34 years old (43.62%). The call duration was mainly between 31 and 45 minutes (50.34%). Operators conducted a suicide risk assessment on the callers, with 38.9% having a comprehensive assessment, 38.9% having an incomplete assessment, and 22.1% having no assessment. The main mental disorders of the callers were depression (48.32%), anxiety (15.44%), and bipolar disorder (14.77%), with 25.50% having comorbidities of ≥ 2 disorders. Emotional scores were as follows: depression (4.11 ± 0.76), sadness (3.97 ± 1.03), and despair (3.78 ± 1.05). There were significant differences in depression, anger, despair, and sadness among the callers with different levels of danger (t=4.79, 3.35, 15.79, 4.24, all P<0.05). Women had higher levels of fear than men (t=3.10, P<0.01). The longer the call duration, the higher the level of despair (t=5.66, P<0.01). Multiple regression analysis showed that incomplete suicide risk assessment by operators (B=-2.36), general procedures for operators' connections (B=5.44), and technical factors (B=2.01) significantly affected the quality of psychological assistance hotlines (all P<0.05). Conclusion Callers with suicidal tendencies generally have serious mental and psychological problems and prominent negative emotions. Strengthening the suicide risk assessment ability of operators and standardizing processes and service attitudes are key to improving the quality of psychological assistance hotlines.

Objective To explore the relationship between intestinal flora imbalance and pulmonary function in patients with chronic obstructive pulmonary disease (COPD), and to analyze the related influencing factors. Methods A total of 310 patients with COPD who were admitted to Air Force Military Medical University Tangdu Hospital from June 2022 to December 2024 were retrospectively analyzed. Based on intestinal flora status, the enrolled patients were classified into imbalance group (n=83) and non-imbalance group (n=227). Logistic regression analysis was conducted to analyze the independent related factors of intestinal flora imbalance in COPD patients. Based on the above factors, a prediction model was constructed, and ROC curve analysis model was applied to analyze the predictive value of the model on intestinal flora imbalance. Results Logistic regression analysis revealed that age, IL-6, albumin, pulmonary function, long-term bed rest and long-term use of antibiotics were related to intestinal flora imbalance in COPD patients (all P<0.05). ROC results of the Logistic prediction model showed that the area under the curve, sensitivity, specificity and 95%CI were 0.961, 0.880, 0.996 and 0.932-0.989 respectively. Conclusion The intestinal flora imbalance in patients with COPD is closely related to lung function, age, inflammatory status, nutritional indicators, activity ability and antibiotic use.

ObjectiveTo analyze the epidemiological and etiological characteristics of a cluster of human metapneumovirus (HMPV) infection in a kindergarten in Gongshu District of Hangzhou City in May 2024, and to provide reference for the prevention and control of similar outbreaks. MethodsAn on-site investigation was conducted using an epidemiological case investigation form. Throat swab specimens collected from cases were screened for 13 respiratory pathogens using real-time fluorescent polymerase chain reaction (PCR). For HMPV nucleic acid positive specimens, the F gene of HMPV was used as the target gene for amplification and sequencing. The sequencing results were then compared with sequences in GenBank database to determine the virus subtypes and perform phylogenetic analyses. ResultsThe outbreak occurred in a kindergarter junior class with a total of 28 preschoolers and 3 teachers and childcare workers. A total of 11 cases (10 preschoolers and 1 teacher) were identified, including 8 male cases and 3 female cases. Clinical manifestations included fever in all 11 cases (100.00%), cough in 8 cases (72.72%), catarrhal symptoms in 4 cases (36.36%), and headache in 3 cases (27.27%). All symptoms were mild, and no severe cases were observed. A total of 11 throat swab samples were collected. Real-time fluorescent PCR test results showed that 3 samples were positive for HMPV nucleic acid, 2 samples were positive for both HMPV and Streptococcus pneumoniae, and 1 sample was positive for both HMPV and rhinovirus. The sequences of the 6 HMPV nucleic acid positive specimens were amplified and analyzed using specific primers, and all were determined to be HMPV subtype A2b. The F gene fragment sequence showed the highest similarity to PV081665.1/Brazil/2024 (99.65%), and also exhibited high similarity to PP683455.1/Indonesia/2021 (99.48%), PV016275.1/Beijing/2024 (99.31%), and PV052230.1/USA/2024 (99.13%). ConclusionThis cluster of acute respiratory tract infection was caused by HMPV subtype A2b, with co-infection of rhinovirus and Streptococcus pneumoniae. The F gene fragment sequences of the HMPV in this outbreak were highly homologous to those of the A2b strains isolated from Brazil, Beijing, Indonesia, and the the United States.

Background: This study was performed to characterize the incidence, costs, and risk factors associated with renal and cardiovascular adverse outcomes following primary percutaneous coronary intervention (pPCI) in patients with ST-elevation myocardial infarction (STEMI). Methods: Patients with STEMI who underwent pPCI using iso-osmolar contrast were enrolled at 39 centers. The incidence of acute kidney injury (AKI) and major adverse renal and cardiovascular events (MARCE) was analyzed, as well as inpatient costs. Logistic regression analysis was performed to identify risk factors. Results: Among 2,293 patients, the incidence of AKI and MARCE within 72 hours post-pPCI was 4.14% (n = 95) and 4.40% (n = 101), respectively. AKI and/or MARCE were associated with systolic blood pressure (AKI: odds ratio [OR], 1.009; 95% confidence interval [CI], 1.000–1.018), hypertension (AKI: OR, 1.815; 95% CI, 1.133–2.906; MARCE: OR, 1.760;95% CI, 1.118–2.769), anterior wall infarction (AKI: OR, 1.895; 95% CI, 1.196–3.004; MARCE:OR, 1.939; 95% CI, 1.240–3.032), Killip class (AKI: OR, 1.465; 95% CI, 1.117–1.922; MARCE:OR, 1.467; 95% CI, 1.131–1.903), and serum creatinine (SCr; MARCE: OR, 1.006; 95% CI, 1.000–1.012). Hospitalization costs for patients with STEMI who developed AKI or MARCE were significantly higher than for those without AKI (9,595 ± 5,795 vs. 8,279 ± 3,872 USD, P = 0.003) or without MARCE (9,890 ± 5,616 vs. 8,255 ± 3,859 USD, P < 0.001). Conclusions In patients with STEMI undergoing pPCI with iso-osmolar contrast, the incidence of AKI and MARCE was associated with higher hospitalization costs. Systolic blood pressure, hypertension, anterior wall infarction, Killip class, and SCr were identified as risk factors for these outcomes.

Definitive chemoradiotherapy (dCRT) has become a cornerstone in the treatment of locally advanced esophageal cancer; however, local control remains suboptimal, and persistent lesions or locoregional recurrences after treatment are not uncommon. For patients without distant metastases but with local failure, whether surgical intervention can still offer curative potential remains a major clinical dilemma. Salvage esophagectomy (SE) offers potential long-term survival for selected patients, but this procedure is performed in the context of severe fibrosis, impaired local blood supply, and obscured anatomical planes following chemoradiotherapy, resulting in significantly higher perioperative risk compared to primary esophagectomy. Consequently, controversies exist regarding patient selection, preoperative restaging, choice of surgical approach, extent of lymphadenectomy, gastrointestinal reconstruction, and perioperative management. In recent years, with the refinement of restaging modalities such as PET/CT, the accumulation of experience in high-volume centers, and emerging evidence from clinical studies, the clinical role of SE has gradually shifted from a "high-risk salvage measure" to a "selective curative strategy aimed at achieving long-term survival in carefully selected patients". Nevertheless, standardized guidelines for patient selection, technical approaches, and perioperative management are still lacking. Based on current evidence and clinical experience, experts organized by the Integrated Esophageal Cancer Committee of Chinese Anti-Cancer Association systematically reviewed key issues regarding SE, including its definition, indications, preoperative evaluation, choice of surgical approach, lymphadenectomy, gastrointestinal reconstruction, and perioperative management, and formulated a Chinese expert consensus. This consensus aims to provide guidance for standardized assessment, appropriate referral, individualized surgical decision-making, and optimized perioperative management of patients with locoregional failure after dCRT. Ultimately, this will increase the likelihood of R0 resection, reduce the risk of severe complications, and promote the safer, more judicious, and standardized implementation of SE in high-risk scenarios.

Objective To compare the performance of 7 Chinese-developed GenAI models (DeepSeek, Wenxin Yiyan, Tongyi, Doubao, Kimi, Hunyuan, and iFLYTEK Spark) in responding to common diseases of the pediatric genitourinary system and to explore their potential applications.Methods A total of 80 questions covering basic disease information, diagnosis, treatment, and prognosis related to “hypospadias, hydronephrosis, and cryptorchidism” were developed as prompts.The models were tested under 3 modes:“quick thinking, ”“deep thinking, ” and “deep thinking + internet access.” The results were evaluated in a blinded review by two pediatric urologists.The responses were graded into 4 levels—A, B, C, and D—based on accuracy, completeness, and relevance.The proportions of responses rated as A and A+B were statistically analyzed and compared across the different models/modes.Results The “deep thinking” mode of DeepSeek demonstrated the best performance, with 88% of responses rated as A and 96% rated as A+B.DeepSeek (deep thinking + internet access), Doubao (quick thinking), Hunyuan (deep thinking), and Doubao (deep thinking + internet access) followed closely, also showing excellent response capabilities.Among the top 5 models/modes, significant differences were observed in the proportion of Alevel responses (P＜0.05), while differences in the proportion of A+B-level responses were not statistically significant (P＞0.05).Conclusion Certain Chinese-developed GenAI models, represented by DeepSeek (deep thinking), demonstrate significant application potential.However, they still cannot consistently provide recommendations rated at the A+B level (recommended grade or higher) with 100% accuracy.In clinical practice, both doctors and patients should view GenAI as an auxiliary tool for education and information acquisition rather than as a final decision-making authority.All information must be reviewed and confirmed by professional physicians.

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.

Objective To explore the relationship between osteoporosis and carotid atherosclerosis in patients with coronary heart disease aged≥60 years and analyze prevention suggestions. Methods The clinical data of 380 patients with coronary heart disease aged≥60 years who underwent various examinations in the hospital between April 2024 and April 2025 were retrospectively analyzed. According to the bone mineral density (BMD) classification criteria, the patients were divided into osteoporosis group and non-osteoporosis group. The differences in general data and carotid atherosclerosis-related indicators were compared between osteoporosis group and non-osteoporosis group. Pearson method was used to analyze the correlation between carotid atherosclerosis indicators and clinical indicators in patients with coronary heart disease aged≥60 years. According to the IMT detection thickness in patients with coronary heart disease and osteoporosis aged≥60 years were divided into IMT thickening group and IMT non-thickening group and between plaque group and non-plaque group, and the differences in BMD and bone metabolism indicators were compared. Binary logistics analysis was adopted to analyze the risk factors of IMT thickening and carotid plaque formation in patients with coronary heart disease≥60 years old. Results Age and duration of osteoporosis group TC、LDL-C、CTX、 Carotid artery IMT and carotid atherosclerosis degree were higher than those in the non osteoporosis group, the difference was statistically significant (P<0.05). BMI, OPG, OCN, 25 (OH) D, BMD, carotid artery elasticity coefficient were lower than those in the non osteoporosis group, the difference was statistically significant (P<0.05). Carotid IMT, carotid atherosclerosis degree, and carotid elasticity coefficient were significantly correlated with age, course of disease, TC, LDL-C, CTX, BMI, OPG, OCN, BMD, and 25 (OH) D of coronary heart disease patients ≥60 years old (P<0.05). OPG, OCN, BMD and 25(OH)D in IMT thickening group and plaque group were lower compared to IMT non-thickening group and non-plaque group (P<0.05) while CTX was significantly higher than that in IMT non-thickening group and non-plaque group (P<0.05). Binary logistics regression analysis showed that OPG, OCN, BMD, 25(OH)D and CTX were associated with IMT thickening in patients with coronary heart disease and osteoporosis aged≥60 years (P<0.05). OPG, OCN and BMD were associated with carotid plaque formation in patients with coronary heart disease complicated with osteoporosis aged≥60 years (P<0.05). Conclusion There is a significant correlation between osteoporosis and arteriosclerosis in patients with coronary heart disease aged≥60 years. As the bone mass decreases, the manifestations of arteriosclerosis become become more and more obvious, which needs attention and prevention.

Chikungunya fever(CHIKF)is a mosquito-borne infectious disease caused by Chikungunya virus(CHIKV)infection,which has become a significant public health threat of global concern in recent years.The acute phase of CHIKF is primarily characterized by sudden high fever,severe polyarthralgia,and rash.The disabling arthralgia may progress to chronic arthritis,with symptoms lasting for months or even years.This not only severely reduces patients'quality of life and impairs their labor capacity,but also imposes a heavy socioeconomic burden.In recent years,significant progress has been made in CHIKF-related research.This review elaborates on the latest research achievements in the fields of the disease's epidemiology,clinical manifestations,pathogenic mechanisms,immune response,diagnostic techniques,and prevention and treatment strategies,aiming to provide comprehensive and in-depth references for researchers and clinicians in relevant fields.

Objective To explore the anatomical landmarks and segmentation method for the intraoperative identification of the cervical segment of the internal carotid artery by studying cadaveric dissections with an endoscopic transoral medial pterygomandibular fold approach and to investigate its clinical significance.Methods The head specimens of five fresh frozen cadavers were dissected in the anatomical laboratory of the Surgical Treatment Technology Innovation Unit of Nasal Skull Base Tumor in Eye&ENT Hospital of Fudan University.The parapharyngeal space was dissected layer by layer through the endoscopic transoral medial pterygomandibular fold approach,and the location marks of parapharyngeal internal carotid artery(ppICA)and adjacent structures of ppICA were anatomically studied.The anatomical landmarks associated with ppICA were observed and characterized,and the ppICA was segmented anatomically according to its adjacent structures.Then,the length of each ppICA segment was measured.Results Muscle structures were essential anatomical landmarks for an endoscopic transoral pterygoid medial approach that identifies mandibular folds.The first layer of muscles included the superior pharyngeal constrictor,tensor veli palatini,and medial pterygoid muscles.The second layer includes the stylopharyngeus,styloglossus,longus capitis,and levator veli palatini muscles.The stylopharyngeal and levator veli palatini muscles were close to the ppICA and were reliable landmarks for locating the ppICA.Furthermore,the ppICA was divided into three segments according to their positional relationship with the ppICA.The first segment of ppICA(P1 ICA)was located between the greater horn plane of the hyoid bone and the intersection plane between the upper margin of stylopharyngeal muscle and ppICA.The second segment of ppICA(P2 ICA)was between the plane where the upper edge of the stylopharyngeal muscle intersected with the ppICA and the plane where the projection of inferior edge of the levator veli palatini muscle intersected with the ppICA.The third segment of ppICA(P3 ICA)was between the intersection of the lower margin projection of the levator veli palatini muscle and ppICA and the external orifice of the carotid canal.The P2 ICA was within an anatomical region bounded by the levator veli palatini muscle,longus capitis muscle,and stylopharyngeus muscle.This region was termed"ICA window"in this paper measured under the cadaver head specimen,the lengths of P1 ICA,P2 ICA,and P3 ICA were(36.5±7.3)mm,(15.5±1.6)mm,(7.4±1.7)mm respectively.Conclusion The muscular structure refers to the relatively constant anatomical reference landmarks within the endoscopic transoral medial pterygomandibular fold.The stylopharyngeus and levator veli palatini muscles are reliable landmarks for precisely locating and segmenting the ppICA,thus having essential clinical implications.