Objective To explore the value of the time to positivity(TTP)combined with inflammatory indicators for identifying coagulase-negative Staphylococcus(CoNS)bloodstream infection and contamination in tumor patients.Methods A retrospective analysis was performed on totally 368 tumor patients with blood culture-positive admitted to the hospital from September 2022 to April 2023,and 47 patients with blood cul-ture-positive CoNS and complete clinical data were selected as research objects.The patients were divided into CoNS infection group(24 cases)and CoNS contamination group(23 cases)according to the diagnostic criteria of bloodstream infection and in combination with the clinical manifestations and laboratory examination re-sults.In addition,5 tumor patients with blood culture Staphylococcus aureus positive admitted to the hospital during the same period were selected as the control group.The TTP,percentage of immature granulocytes(IG%),absolute value of immature granulocytes(IG#),white blood cell count(WBC),neutrophil percent-age(NE%),neutrophil-to-lymphocyte ratio(NLR),C-reactive protein(CRP)and procalcitonin(PCT)levels in all groups were compared.Results Among the 47 patient isolates of CoNS from blood cultures,Staphylo-coccus hominis was the most common,accounting for 42.55%.There were significant differences in TTP,NE%,NLR and CRP levels between CoNS infection group,CoNS contamination group and control group(P<0.05).The TTP in CoNS infection group was shorter than that in CoNS contamination group,and the levels of NE%,NLR,CRP and PCT were higher than those in CoNS contamination group,with statistical sig-nificance(P<0.05).TTP combined with NLR,CRP and PCT had the largest area under the curve,which was 0.971(P<0.000 1),with a sensitivity of 91.67%,specificity of 95.65%,likelihood ratio of 21.08,positive predictive value of 91.67%,negative predictive value of 95.65%,and an accuracy of 93.62%.Conclusion TTP combined with NLR,CRP and PCT have important clinical value in the differential diagnosis of CoNS blood-stream infection and contamination in tumor patients.

Cardiovascular disease and cancer are the two leading chronic conditions contributing to global mortality. With the rising incidence of cancer, the prevalence of cancer therapy-related cardiovascular complications has also increased, driving the development of the emerging field of cardio-oncology. The advancement of precision medicine offers new opportunities for the individualized and targeted management of cardiovascular toxicities associated with cancer treatment. Artificial intelligence (AI) has the potential to overcome traditional limitations in medical data integration, dynamic monitoring, and interdisciplinary collaboration, thereby accelerating the application of precision medicine in cardio-oncology. By enabling personalized treatment and reducing cardiovascular complications in cancer patients, AI serves as a critical tool in this domain. This article provides an in-depth interpretation of the 鈥淎rtificial intelligence to enhance precision medicine in cardio-oncology: a scientific statement from the American Heart Association鈥?aiming to inform the integration of AI into precision medicine in China. The goal is to promote its application in the management of cardiovascular diseases related to cancer therapy and to achieve precision management in this context.

BACKGROUND:Knee osteoarthritis is a common degenerative disease that significantly impacts patients'quality of life and increases the societal healthcare burden.Early and accurate diagnosis of knee osteoarthritis is crucial for the treatment and prognosis of patients.Traditional diagnostic methods are not only subjective and time-consuming but also do not guarantee consistently high accuracy.OBJECTIVE:To develop an automatic diagnostic method for knee osteoarthritis based on deep learning,utilizing deep learning networks to improve diagnostic accuracy and efficiency.METHODS:A new network model,YOLOV8-ViT,was proposed by replacing the backbone network of YOLOv8n with the Efficient-ViT network and incorporating attention mechanisms for the automatic identification and classification of X-ray images of knee osteoarthritis.The experimental dataset included 5 078 X-ray images of patients with knee osteoarthritis obtained from the Third Affiliated Hospital of Guangzhou University of Chinese Medicine.Three imaging physicians annotated the sites of knee osteoarthritis and classified them according to the Kellgren-Lawrence grading standard using Labelme software,and the results were combined.The evaluation indicators used in this study included Precision,F1 score,mean average precision(mAP),Recall,val/box_loss,val/cls_loss,and val/dfl_loss.RESULTS AND CONCLUSION:The experimental results showed that the YOLOV8-ViT model outperformed the YOLOv5n,YOLOv8n,and YOLOv9n models in terms of precision,mAP50,mAP50-95,F1 score,and Recall,while lowering val/box_loss,val/cls_loss,and val/dfl_loss by 0.496,0.45,and 0.523;1.037,0.305,and 0.728;and 0.267,0.654,and 0.854,respectively.These experimental data validate that this model has high detection accuracy.

Objective To evaluate the performance of an improved DeepSurv model for survival analysis in lung cancer patients,and investigate key factors affecting the prognosis of lung cancer.Methods The lung cancer data from the SEER database(2018-2021)was used in the study,and the DeepSurv model was optimized by incorporating a self-attention mechanism,a residual network,a LIME module and an entropy regularization term to enhance prediction accuracy and interpretability.Model performance was assessed using C-index and Brier score,and the improved model was utilized to evaluate the effects of various features on the prognosis of lung cancer.Results The improved DeepSurv model achieved a C-index of 0.852 and a Brier score of 0.139.Feature importance analysis identified age as the primary determinant of the survival of lung cancer patients.Conclusion The improved DeepSurv model outperforms both the Cox proportional hazards model and the original DeepSurv model in terms of accuracy,robustness and interpretability,offering a novel methodology for personalized medicine and survival analysis.

A converged network based on deep learning is proposed to realize the efficient and accurate diagnosis of diabetic retinopathy.Both data augmentation technology and generative adversarial network are used to augment the fundus images in EyePACS dataset for effectively addressing the problem of uneven classification of fundus images.The proposed model uses Inception-Resnet-V2 as the main network,and incorporates deep residual shrinkage network and pyramid split attention module for effectively filtering out the irrelevant information in the feature learning process and focusing on the lesion information,thereby improving the network's ability to capture important features.Experimental results show that the optimized model achieves accuracy,recall,specificity,sensitivity,and F1 score of 0.951,0.950,0.990,0.950,and 0.950,respectively,without the need to specify lesion characteristics in advance,demonstrating its superiority in evaluation indicators.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Insulin-like growth factor 2 (IGF2) is a critical endocrine mediator implicated in male reproductive physiology. To investigate the correlation between IGF2 protein levels and various aspects of male infertility, specifically focusing on sperm quality, inflammation, and DNA damage, a cohort of 320 male participants was recruited from the Women's Hospital, Zhejiang University School of Medicine (Hangzhou, China) between 1 st January 2024 and 1 st March 2024. The relationship between IGF2 protein concentrations and sperm parameters was assessed, and Spearman correlation and linear regression analysis were employed to evaluate the independent associations between IGF2 protein levels and risk factors for infertility. Enzyme-linked immunosorbent assay (ELISA) was used to measure IGF2 protein levels in seminal plasma, alongside markers of inflammation (tumor necrosis factor-alpha [TNF-α] and interleukin-1β [IL-1β]). The relationship between seminal plasma IGF2 protein levels and DNA damage marker phosphorylated histone H2AX (γ-H2AX) was also explored. Our findings reveal that IGF2 protein expression decreased notably in patients with asthenospermia and teratospermia. Correlation analysis revealed nuanced associations between IGF2 protein levels and specific sperm parameters, and low IGF2 protein concentrations correlated with increased inflammation and DNA damage in sperm. The observed correlations between IGF2 protein levels and specific sperm parameters, along with its connection to inflammation and DNA damage, underscore the importance of IGF2 in the broader context of male reproductive health. These findings lay the groundwork for future research and potential therapeutic interventions targeting IGF2-related pathways to enhance male fertility.
Humans ; Male ; Insulin-Like Growth Factor II/metabolism* ; Infertility, Male/genetics* ; DNA Damage ; Adult ; Inflammation/metabolism* ; Spermatozoa/metabolism* ; Semen Analysis ; Semen/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Histones/metabolism* ; Interleukin-1beta/metabolism*

Objective:To explore the protocol for handgrip exercise stress echocardiography by comparing different maximal voluntary contraction（MVC）handgrip groups with bicycle exercise stress.Methods:Forty-one healthy volunteers were enrolled prospectively from June to October 2024 in Tangdu Hospital and utilized a color Doppler echocardiography system，supine cycle ergometer，and handgrip dynamometer to collect echocardiographic data at baseline，during handgrip exercises at 20%（3 min），30%（3 min），and 40%（2 min）of MVC，and spine bicycle exercise stress at peak. Parameters measured included left ventricular ejection fraction（EF），stroke volume（SV），cardiac output（CO），mitral inflow E-wave and A-wave velocities，lateral and septal mitral annular e' velocities，E/A and E/e' ratios，global longitudinal strain（GLS），left atrial reservoir strain（LAS R），conduit strain（LAS CD），and contractile strain（LAS CT）. The non-invasive myocardial work indices were also assessed，including global work index（GWI），global constructive work（GCW），global wasted work（GWW），and global work efficiency（GWE）. Statistical analyses were performed using repeated measures analysis of variance，with corrected paired t-test for comparisons between two exercise stress states. Results:Compared with the baseline state，heart rate，blood pressure，CO、GWI、GCW、GWW and LAS CT gradually increased，while EF、E/A、GLS、GWE、LAS R and LAS CD gradually decreased under 20%，30% and 40% of MVC states. The changes were most obvious at 40% of MVC state，which was selected for the handgrip exercise stress echocardiography protocol.Compared with the peak of bicycle exercise，at 40% of MVC，heart rate was significantly lower［（81.2 ± 9.7）bpm vs.（164.6 ± 11.3）bpm， P<0.05）］，systolic blood pressure was slightly lower［（152.9 ± 13.2）mmHg vs.（165.1 ± 20.4）mmHg， P<0.05］，diastolic blood pressure was higher［（96.0 ± 9.5）mmHg vs.（89.5 ± 10.9）mmHg， P<0.05］，GLS was lower［（19.1 ± 1.5）% vs.（23.5 ± 1.7）%， P<0.05］，GWI was similar［（2 254.2 ± 417.3）mmHg% vs.（2 227.5 ± 389.0）mmHg%， P>0.05］，but GWE was higher［（95.3 ± 2.0）% vs.（93.7 ± 2.0）%， P<0.05］，and LAS R was lower［（39.4 ± 4.2）% vs.（43.9 ± 4.1）%， P<0.05］. Conclusions:The 40% of MVC lasting 2 min can cause the most significant handgrip-related changes in cardiac function and can be used as the standard protocol for handgrip exercise stress echocardiography. Handgrip stress exercise can cause significant changes in cardiac systole，diastole，and work performance，showing different characteristics compared with bicycle exercise stress.