ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

Objective:To explore the genetic and clinical characteristics of Guizhou patients with enlarged vestibular aqueduct（EVA） syndrome through combined SLC26A4 variant analysis and clinical phenotype analysis. Methods:Seventy-two EVA patients underwent comprehensive genetic testing using a multiplex PCR-based deafness gene panel and next-generation sequencing（NGS）. The audiological and temporal bone imaging characteristics were compared across mutation subtypes. Results:A total of 27 pathogenic loci of SLC26A4 were detected in 72 patients, including c.919-2A>G in 79.2%（57/72）. A novel deletion（c.1703_1707+6del） was discovered. Among 65 cases, truncated mutations were 89.2%（58/65）, 52.3%（34/65）, 28（43.1%） and 7（10.8%）. No significant differences were observed in the midpoint diameter of the vestibular aqueduct and the incidence of incomplete partitioning typeⅡ（IP-Ⅱ） of the cochlea among the three groups of patients. Moreover, there was no difference in the midpoint diameter of different vestibular pipes or the combination with IP-Ⅱ. Conclusion:The most common mutation site of SLC26A4 in EVA patients in Guizhou is c.919-2A>G, though genotype-phenotype correlations remain elusive. The detection of 27 mutation sites and the discovery of new mutation sites suggested the precise diagnostic significance of NGS technology in EVA patients in Guizhou.
Humans ; Sulfate Transporters ; Vestibular Aqueduct/abnormalities* ; Mutation ; Membrane Transport Proteins/genetics* ; Hearing Loss, Sensorineural/genetics* ; Male ; Female ; Child ; Adolescent ; Child, Preschool ; Adult ; Young Adult ; Phenotype ; High-Throughput Nucleotide Sequencing

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

OBJECTIVE: To explore clinical efficacy of bone cement filling combined with lower extremity arterial balloon dilation in treating Wagner grade Ⅳ diabetic foot (DF). METHODS: From January to October 2024, 9 Wagner grade Ⅳ DF patients with lower extremity vascular occlusion were admitted, including 7 males and 2 females, aged from 51 to 87 years old;5 patients on the left side and 4 patients on the right side. All patients were underwent stageⅠdebridement of the affected foot and bone cement filling, and treated with lower extremity arterial balloon dilation after operation, they were. After the formation of the induced membrane, stageⅡwound repair was performed. The wound healing time and condition were observed. Ankle-brachial index (ABI) was used to evaluate the lower extremity vascular perfusion before operation and 3 months after operation, respectively. RESULTS: The wounds of all 9 patients healed completely, and the healing time ranged from 45 to 65 days. All patients were followed up for at least 6 months without recurrence. The skin of the affected foot wound healed with keratinization, and there was mild scar hyperplasia locally (1 patient had necrosis of the adjacent toe after stageⅠsurgery and was debridement and toe amputation again). The narrowed or occluded blood vessels of the lower extremities were all recanalized. ABI recovered from 0.3 to 0.5 before operation to 1.0 to 1.1 at 3 months after operation. CONCLUSION Bone cement filling combined with lower extremity arterial balloon dilation for the treatment of grade Wagner Ⅳ DF is conducive to promoting healing of the affected foot, effectively preventing secondary ulceration of the affected foot, and clinical therapeutic effect is satisfactory.
Humans ; Male ; Female ; Middle Aged ; Diabetic Foot/surgery* ; Aged ; Bone Cements/therapeutic use* ; Aged, 80 and over ; Lower Extremity/blood supply*

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

From July 23, 2018, to December 31, 2019, a total of 299 219 children in Shandong Province received the fifth dose of the diphtheria, tetanus, and acellular pertussis combined vaccine (DTaP). Among these recipients, the distribution by age was as follows: 20 children under 2 years old (0.01%), 273 996 children aged 2 years (91.57%), 20 242 children aged 3 years (6.76%), 3 932 children aged 4 years (1.31%), 963 children aged 5 years (0.32%), and 66 children aged 6 years and above (0.02%). In total, 1 972 cases of adverse events following immunization (AEFI) were reported after the administration of the fifth dose of DTaP, resulting in an incidence rate of 659.05 per 100 000 doses. Among these, 1 718 cases were classified as common vaccine reactions, with an incidence rate of 574.16 per 100 000 doses, while 247 cases were identified as rare reactions, yielding an incidence rate of 82.55 per 100 000 doses. The incidence of AEFIs, as well as the rates of common and rare reactions, exhibited a significant increasing trend with the number of doses administered (all P<0.001). Among the rare reactions, there were 10 cases classified as severe, resulting in a reported incidence of 3.34 per 100 000 doses.

Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Objective To construct a symptom network in patients with acute type A aortic dissection(ATAAD),so as to provide theoretical basis for the screening of dissection ATAAD during emergency pre-screening triage.Methods There were 433 patients diagnosed with ATAAD during 2019 to 2023 in an emergency department of a tertiary hospital in Wuhan.Their basic information and medical records were reviewed by self-designed data questionnaire.UCINET6.0 software was used to construct a symptom network,analyze the centrality index and determine the core symptoms.Symptom distribution of patients with positive and negative blood pressure in extremities was analyzed in the further.Results The most common symptoms in patients with type A aortic dissection were chest pain(77.37％),back pain(42.96％),and sweating(29.79％).In the symptom network,chest pain had the highest degree(rs=659).The closeness of chest pain,chest tightness,shortness of breath,back pain,nausea and vomiting,limb numbness and fatigue were same(rc=93.33).Fatigue has the highest betweenness(rb=13.69).Patients with positive limbs blood pressure mainly reported chest pain(70.17％),back pain(44.96％),and nausea and vomiting(19.33％),while those with negative limb blood pressure mainly reported chest pain(63.64％),back pain(63.64％),and orosphyalgia(39.40％).Orosphyalgia had the highest degree(rs=20).Conclusion The symptoms of ATAAD are complex and varied in patients.During triage,nurses should measure the limb blood pressure when patients complained chest pain alone or when combined with other hypoperfusion symptoms,such as back pain,chest tightness,sweating,near-death sensation,and shortness of breath.Aortic dissection cannot be ruled out in patients with negative blood pressure when they had chest pain,back pain or orosphyalgia.

Objective:To compare the lung shunt fraction (LSF) of 90Y imaging after 90Y-selective internal radiation therapy (SIRT) and preoperative 99Tc m-macroaggregated albumin (MAA) imaging in patients with liver malignant tumors, and compare the volume and visual score of intrahepatic distribution of both nucleins on SPECT/CT images. Methods:A total of 91 patients with liver malignant tumors (78 males, 13 females; age (56.7±13.7)years; 99 cases) who underwent 90Y-SIRT in the Second Affiliated Hospital of Guangzhou Medical University from November 2022 to June 2024 were retrospectively collected. All patients underwent preoperative 99Tc m-MAA simulation and postoperative 90Y distribution verification by whole-body planar scintigraphy and hepatic SPECT/CT imaging. ROIs of the liver and lungs under the anterior-posterior position were delineated on the planar scintigraphy and LSF of 99Tc m-MAA and 90Y were calculated. The volume of interest (VOI) was drawn on the SPECT/CT images to calculate the nuclide distribution volume of both 99Tc m-MAA and 90Y within the liver. Wilcoxon signed rank test was used to compare the difference between two groups. In addition, the liver was divided into five lobes, namely left lateral lobe, left medial lobe, caudate lobe, right anterior lobe and right posterior lobe. Visual assessment of 90Y and 99Tc m-MAA radioactive distribution was performed ( 90Y and 99Tc m-MAA uptakes were graded on a scale of 0-3, where 0 indicated no nuclide accumulation and 3 indicated heavy accumulation). Kappa consistency test was used to analyze the scores of the corresponding lobes between two groups. Results:LSF for 99Tc m-MAA was 11.60%(4.27%, 15.03%), and LSF for 90Y was 11.80%(9.70%, 13.30%), without significant difference ( Z=-1.50, P=0.134). The distribution volume of 99Tc m-MAA within the liver was 542.63(204.00, 818.00)ml, which was significantly different from that of 90Y (688.69(287.00, 954.00)ml; Z=-7.37, P<0.001). Kappa values of the score of each lobe between 99Tc m-MAA imaging and 90Y imaging were 0.469-0.740 (all P<0.001). Conclusions:99Tc m-MAA simulation is reliable for assessing LSF for 90Y-SIRT. The distribution volume of 99Tc m-MAA is generally smaller than that of 90Y, but the consistency of the visual score of radioactive distribution is high. Overall, 99Tc m-MAA may well simulate the distribution pattern of 90Y-SIRT.