Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

The plant F-box protein more axillary growth 2 (MAX2) is a key factor in the signal transduction of strigolactones (SLs) and karrinkins (KARs). As the main component of the SKP1-CUL1-FBX (SCF) complex ubiquitin ligase E3, MAX2 is responsible for specifically recognizing the target proteins, suppressor of MAX2 1/SMAX1-like proteins (SMAX1/SMXLs), which would be degraded after ubiquitination. It can thereby regulate plant morphogenesis and stress responses. There exist homologous genes of MAX2 in the important grain and oil crop soybean (Glycine max). However, its role in plant defense responses has not been investigated yet. Here, GmMAX2b, a homologous gene of MAX2, was successfully cloned from stressed soybean. Bioinformatics analysis revealed that there were two MAX2 homologous genes, GmMAX2a and GmMAX2b, with a similarity of 96.2% in soybean. Their F-box regions were highly conserved. The sequence alignment and cluster analysis of plant MAX2 homologous proteins basically reflected the evolutionary relationship of plants and also suggested that soybean MAX2 might be a multifunctional protein. Expression analysis showed that plant pathogen infection and salicylic acid treatment induced the expression of GmMAX2b in soybean, which is consistent with that of MAX2 in Arabidopsis. Ectopic expression of GmMAX2b compensated for the susceptibility of Arabidopsis max2-2 mutant to pathogen, indicating that GmMAX2b positively regulated plant disease resistance. In addition, yeast two hybrid technology was used to explore the potential target proteins of GmMAX2b. The results showed that GmMAX2b interacted with SMXL6 and weakly interacted with SMXL2. In summary, GmMAX2b is a positive regulator in plant defense responses, and its expression is induced by pathogen infection and salicylic acid treatment. GmMAX2b might exert its effect through interaction with SMXL6 and SMXL2. This study expands the theoretical exploration of soybean disease resistant F-box and provides a scientific basis for future soybean disease resistant breeding.
Glycine max/metabolism* ; Disease Resistance/genetics* ; Plant Diseases/immunology* ; Plant Proteins/genetics* ; Cloning, Molecular ; Gene Expression Regulation, Plant ; F-Box Proteins/genetics* ; Arabidopsis/genetics* ; Phylogeny

Objective: To explore the effects of sleep on subsequent day physical activity (PA) in children and adolescents, so as to provide a reference for refining PA intervention strategies and further investigating their underlying mechanisms. Methods: Through searching databases including Web of Science Core Collection, PubMed, EBSCOhost, ScienceDirect, Cochrane Library, CNKI, Wanfang and VIP cross sectional, cohort and experimental studies on sleep and subsequent day PA among children and adolescents were identified, with the searching period spanning from database inception to June, 2025. Based on the characteristics of the included literature, two sleep variables[sleep duration (SD) and sleep efficiency (SE)] and three physical activity variables[moderate to vigorous physical activity (MVPA), light physical activity (LPA), and total physical activity (TPA)] were selected. The relationship between these two types of variables was analyzed for pooled effect sizes using Stata 17.0. Results: A total of 14 studies were included, with 64.3% published in 2018 or later, involving 11 361 children and adolescents from 17 countries. Meta analysis results showed that both SD ( ES=0.04, 95%CI =0.01-0.07) and SE ( ES=0.24, 95%CI =0.01-0.47) were positively correlated with subsequent day MVPA (both P <0.05). However, no statistically significant associations were found with LPA ( ES=-0.04, 95%CI =-0.13 to 0.06; ES=-0.02, 95%CI =-0.15 to 0.11) or TPA( ES=0.09, 95%CI =-0.02 to 0.20; ES=0.02, 95%CI = -0.03 to 0.06)(all P >0.05). Subgroup analysis revealed that in the "≤6 years" subgroup, SD and SE were positively correlated with TPA ( ES=0.22, 95%CI =0.09-0.35) and MVPA ( ES=1.19, 95%CI =1.06-1.32), respectively; in the "6-12 years" subgroup, SD was positively correlated with MVPA ( ES=0.05, 95%CI =0.02-0.08); in the "≥12 years" subgroup, SE was positively correlated with LPA ( ES=0.08, 95%CI =0.00-0.16), while SD was negatively correlated with LPA ( ES=-0.23, 95%CI = -0.31 to -0.16) (all P <0.05). Conclusion Adequate SD and good SE can effectively enhance subsequent day MVPA among children and adolescents, although these sleep effects vary by age group.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Purpose To characterize the clinicopathological features of gastrointestinal mesenchymal tumors(GMTs)resected via endoscopic techniques.Methods A retrospective analysis was conducted on 495 cases of endo-scopically resected GMTs.Clinical information,histomorphological findings,immunohistochemical profiles,and mo-lecular characteristics were reviewed.Results The cohort included 495 patients aged 20-78 years(median:53 years).The majority of tumors were located in the stomach(58.8％)and esophagus(36.8％).Histologically,most tumors consisted of spindle cells,with a minority composed of epithelioid cells;fibrocollagenous or myxoid stroma was occasionally observed.Immunohistochemically,leiomyomas showed diffuse positivity for α-SMA(98.8％)and desmin(99.3％),gastrointestinal stromal tumors(GISTs)expressed CD117(99.4％),DOG1(97.6％),and CD34(97.0％),and schwannomas were positive for S-100(93.7％).The predominant tumor types were leiomyomas(54.1％)and GISTs(33.7％),while the remaining 12.2％comprised other rare types.Various endoscopic resection techniques were employed based on the tumors' anatomical depth,including endoscopic submucosal dissection(ESD,40.5％),submucosal tunneling endoscopic resection(STER,17.1％),endoscopic mucosal resection(EMR,16.5％),endoscopic full-thickness resection(EFTR,13.9％),and endoscopic submucosal excavation(ESE,12.0％).EMR and ESD were primarily used for superficial lesions,while deeper tumors with were more often treated with STER,EFTR,and ESE.The rate of negative resection margins was lower in GISTs(72.2％)and other tumors with indistinct margins,compared to leiomyomas(92.6％)and those with well-defined boundaries.Conclusion Leiomyomas and GISTs are the most common gastrointestinal mesenchymal tumors resected via endoscopy.A variety of resection techniques are applicable depending on tumor location and depth.Accurate pathological diagnosis should be based on HE morphology,supplemented by endoscopic findings,margin status,immunohistochemistry,and necessary molecular tests.

Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.