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.

In recent years, remarkable advances have been made in lung transplantation regarding donor evaluation, perioperative support, and immune regulation, laying a foundation for improving the long-term survival of recipients. The rational application of extended criteria donor lungs and the popularization of ex vivo lung perfusion technology have enhanced the utilization efficiency and safety of marginal donor lungs. Refined assessment of risk factors such as donors’ smoking history and infectious status has reduced the incidence of primary graft dysfunction and postoperative infection. In terms of recipient management, individualized assessment systems have been gradually optimized. The standardized application of intraoperative extracorporeal membrane oxygenation and the development of minimally invasive surgical techniques have effectively alleviated perioperative injuries. The optimization of postoperative immunosuppressive regimens and advances in rejection monitoring technologies have further improved the long-term survival of grafts. Nevertheless, chronic graft dysfunction and recurrent or refractory infections remain the major bottlenecks restricting long-term prognosis. Future research should focus on expanding donor sources, improving the repair quality of marginal donor lungs, promoting precise immunosuppression and anti-infection strategies, and comprehensively enhancing the long-term survival rate and quality of life of lung transplant recipients.

The collateral disease theory stands as one of the most instructive frameworks for elucidating the pathology of Mycoplasma pneumoniae pneumonia （MPP）. Its characteristic pathological features—toxin damaging collaterals， dysfunction of Qi collaterals， and protracted illness involving collaterals—closely align with the manifestations of cytokine storms， immune dysregulation， and chronic damage induced by M. pneumoniae （MP）. Drug-resistant MP further exacerbates these manifestations and poses challenges in clinical treatment， making it essential to clarify the intrinsic relationship between the collateral disease theory and MPP. However， existing studies still lack relevant elaboration， resulting in a gap in guidance by traditional Chinese medicine （TCM） theory in clinical practice. Considering the instructive， scientific， and necessary role of the collateral disease theory in MPP， this paper thoroughly elucidates the pathological manifestations of MPP and the core evolutionary characteristics of collateral damage， and further provides a scientific interpretation from the perspective of collateral disease on the clinical efficacy and mechanism of TCM treatment of MPP over the past five years. This review aims to reveal the intrinsic relationship between the collateral disease theory and MPP， enrich the scientific connotation of TCM theory， and bridge the gap in TCM theoretical guidance， thereby providing scientific research clues for TCM treatment of MPP.

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.

Post-stroke aphasia(PSA)is one of the common complications of stroke,which seriously affects the compliance of rehabilitation training and daily life of patients.Repetitive transcranial magnetic stimulation(rTMS)is a common method for the treatment of PSA in recent years,which can accurately regulate the speech center,and stimulate or inhibit the corresponding targets,to achieve the purpose of neural function remodeling.This article analyzes and summarizes the research on the application of rTMS in PSA at home and abroad,as well as related evaluation indicators,to provide the theoretical basis for the scientific application of rTMS in PSA in the future.

Objective:To investigate the efficacy and safety of metallic stent implantation for the treatment of central airway malacia following lung transplantation.Methods:Clinical data of 14 recipients who underwent metallic stent implantation for central airway malacia after lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from January 2023 to June 2024 were retrospectively analyzed. Clinical symptoms, modified Medical Research Council (mMRC) dyspnea scale scores, Karnofsky Performance Status (KPS) scores, and pulmonary function were evaluated before and 2 weeks after stent implantation. The incidence of post-implantation complications was recorded during follow-up.Results:Among the 14 recipients, 13 were male and 1 was female, with a mean age of (57.29±10.93) years (range: 27-71 years). All patients successfully underwent metallic stent placement in a single attempt, with no serious intraoperative complications. Clinical symptoms such as dyspnea improved significantly after stent implantation. Compared with pre-treatment values, mMRC scores decreased [3.00 (2.00, 4.00) vs 1.00 (1.00, 2.00), P<0.001], KPS scores increased [30.00 (10.00, 32.50) vs 80.00 (60.00, 90.00), P=0.001], and forced expiratory volume in one second (FEV 1) improved [(1.25±0.42) L vs (1.74±0.38) L, P=0.006]. Postoperative complications included granulation tissue formation (7 cases), epithelialization within the stent (3 cases), and mucus plugging (4 cases). As of the last follow-up in September 2024, eight patients had their stents successfully removed, and one patient had died due to cytomegalovirus infection. Conclusions:Metallic stent implantation can significantly relieve clinical symptoms of central airway malacia after lung transplantation, improve quality of life, and shows a favorable safety profile.

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.

AIM To study the effects of Jiaotai Pills and their single composition drugs on high-fat diet-induced hypothalamic inflammation in obese mice.METHODS C57BL/6J mice were randomly divided into the normal group(15 mice)and the high-fat group(75 mice).The mice given 12 weeks of high-fat diet feeding were further randomly divided into the model group,the Jiaotai Pills group,the Coptis chinensis group,the Cinnamomum cassia group and the positive metformin group,with 15 mice in each group.After 6 weeks of administration,the mice had their body weight and fasting blood glucose(FBG)levels detected;their hypothalamic expressions of IL-1β,IL-6,TNF-α and Socs3 mRNA detected by RT-qPCR;their hypothalamic expressions of TLR4,MyD88,IKKβ and activated NF-κB protein detected by Western blot;their hypothalamic expressions of Iba1 and GFAP detected by immunohistochemistry;and their ultrastructural changes of nerve tissues observed using transmission electron microscopy(TEM).RESULTS Compared with the model group,each drug group displayed decreased hypothalamic expressions of IL-1β,IL-6,TNF-α and Socs3 mRNA(P＜0.01),and improved number and morphology of nerve cells revealed by TEM.The groups intervened with Jiaotai Pills,or Coptis chinensis,or metformin shared decreased body weight and FBG levels(P＜0.05);decreased protein expressions of TLR4,MyD88,IKKβ and p-NF-κB(P＜0.05);and decreased number of hypothalamic astrocytes and microglia(P＜0.05).Additionally,decreased p-NF-κB protein expression was observed in the Cinnamomum cassia group(P＜0.05).CONCLUSION Jiaotai Pills and their single composition drugs can improve high-fat diet-induced hypothalamic inflammation in obese mice.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.