BACKGROUND:Wogonin is a flavonoid extracted from the root of Scutellaria baicalensis.Previous studies have shown that baicalein has protective effects against cerebral ischemia-reperfusion injury,and can also reduce blood sugar and complications in diabetic mice,but its role and mechanism in diabetic cerebral infarction remain unclear. OBJECTIVE:To explore the effect of wogonin on nerve injury in rats with diabetic cerebral infarction and its mechanism. METHODS:Sprague-Dawley rats were randomly divided into six groups:control group,model group,low-dose wogonin group,medium-dose wogonin group,high-dose wogonin group,and high-dose wogonin+Ras homolog gene family member A(RhoA)activator group.Except for the control group,the other rats were established with diabetes and cerebral ischemia models using intraperitoneal injection of streptozotocin and middle cerebral artery occlusion.Low,medium-and high-dose wogonin groups were intragastrically given 10,20,40 mg/kg wogonin,respectively;high-dose wogonin+RhoA activator group was intragastrically given 40 mg/kg wogonin and intraperitoneally injected 10 mg/kg lysophosphatidic acid;control group and model group were given the same amount of normal saline once a day for 7 consecutive days.Rats in each group were evaluated for neurological deficits and their blood glucose levels were measured after the last dose.TTC staining was applied to detect the volume of cerebral infarction.Hematoxylin-eosin staining was applied to observe pathological changes in brain tissue.ELISA kit was applied to detect tumor necrosis factor-α,interleukin-6,malondialdehyde,and superoxide dismutase levels in brain tissue.Western blot was applied to detect the protein expression of RhoA and Rho-associated protein kinase(ROCK)2 in brain tissue. RESULTS AND CONCLUSION:Compared with the control group,the neuronal structure of rats in the model group was severely damaged,with cell necrosis and degeneration,the neurological deficit score,blood glucose level,and infarct volume were significantly elevated(P<0.05),the levels of tumor necrosis factor-α,interleukin-6,and malondialdehyde,and the protein expression of RhoA and ROCK2 in brain tissue were significantly increased(P<0.05),and the superoxide dismutase level was decreased(P<0.05).Compared with the model group,the low-,medium-,and high-dose wogonin groups showed improved neuronal damage,reduced cell degeneration and necrosis,a significant reduction in neurological deficit score,blood glucose level,infarct volume,and the levels of tumor necrosis factor-α,interleukin-6,and malondialdehyde,and the protein expression of RhoA and ROCK2 in brain tissue,and an increase in the superoxide dismutase level(P<0.05).Compared with the high-dose wogonin group,the high-dose wogonin+RhoA activator group significantly weakened the improvement in the above indexes of rats with diabetic cerebral infarction(P<0.05).To conclude,wogonin can improve the blood glucose level in rats with diabetic cerebral infarction,reduce cerebral infarction and nerve injury,and its mechanism may be related to the inhibition of RhoA/ROCK signaling pathway.

Nanoparticle delivery systems have good application prospects in the field of precision therapy, but the preparation process of nanomaterial has problems such as short in vivo circulation time, easy recognition, and clearance by the immune system in the body. In recent years, biomimetic nanoparticle delivery systems mediated by natural cell membranes have become a research hotspot to address these issues. The natural membrane biomimetic nanoparticle delivery system cleverly integrates the advantages of natural biofilm "autologous" and "artificial" functional carriers by using endogenous cell membranes to modify the surface of nanocarriers, endowing them with characteristics such as tumor targeting, low immunogenicity, and long blood circulation. Currently, biomimetic nanoparticle delivery systems have been used in the treatment of malignant tumors, cardiovascular diseases, bacterial infections, and other diseases. This paper analyzes the development status and current research hotspots of natural cell membrane camouflaged biomimetic nanoparticle delivery systems mainly reviews the latest research progress of red blood cell membrane camouflaged biomimetic nanoparticle delivery systems in the field of disease treatment in recent years. It focuses on exploring the advantages, future development prospects, and limitations of biomimetic nanoparticle delivery systems based on red blood cell membrane camouflage in improving drug delivery, to provide a reference for the in-depth research and development of this system.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

The epidemiology and etiology of three suspected cases of imported skin diphtheria infection in Fujian Province were investigated.Secretion samples of patients with skin damage were collected for isolation and culture of Corynebacterium diphtheriae.Biochemical identification and mass spectrum analysis of pure cultures of suspected C.diphtheriae were conduc-ted,the virulence-related genes,including diphtheria toxin reporter(dtxR),toxin A(toxA),and toxin B(toxB)were detec-ted,and multilocus sequence typing(MLST)was performed.All three cases had typical clinical manifestations of cutaneous diphtheria,and C.diphtheriae was isolated from the damaged skin.The virulence genes of two C.diphtheriae strains isolated from two cases were identified as dtxR(+),toxA(-),and toxB(-),and the MLST type was ST-703.The virulence genes of C.diphtheriae isolated from one case were identified as dtxR(+),toxA(+),toxB(+),and the MLST type was ST-248.There is an increased risk of diphtheria in Fujian Province.C.diphtheriae without diphtheria toxin genes can also cause skin diphtheria.

Objective:To investigate the impact of ionizing radiation(IR)on the structure and function of the testis and pro-vide some strategies for the prevention and treatment of IR-induced damage(IRD).Methods:Using radiation dose simulation,se-men analysis,hormone testing,electron microscopy and single-cell transcriptome sequencing,we assessed and analyzed a case of IRD.We established a mouse model of IRD to validate the results of single-cell sequencing,and investigated the specific biological mecha-nisms of IRD and potential strategies for its intervention.Results:IR at 1-2 Gy significantly reduced sperm concentration and mo-tility,which gradually recovered after 12 months but the percentage of morphologically normal sperm remained low.It also caused im-balanced levels of various steroid hormones,decreased testosterone and dehydroepiandrosterone sulfate,increased progesterone,prolac-tin,luteinizing hormone,and follicle-stimulating hormone.Electron microscopy revealed damages to the testis structure,including loss of germ cells,atrophy of the seminiferous tubules,nuclear membrane depression of the spermatocytes,mitochondrial atrophy and de-formation,and reduction of mitochondrial cristae.Single-cell sequencing indicated significant changes in the function of the Leydig cells and macrophages and disrupted lipid-related metabolic pathways after IRD.Administration of L-carnitine to the mouse model im-proved lipid metabolism disorders and partially alleviated IRD to the germ cells.Conclusion:Ionizing radiation can cause disorders of testicular spermatogenesis and sexual hormones and inhibit lipid metabolism pathways in Leydig cells and macrophages.Improving lipid metabolism can alleviate IRD to germ cells.

AIM To study the chemical constituents from the ethyl acetate fraction of Baccharis trimera(Less.)DC.METHODS The ethyl acetate fraction of B.trimera was isolated and purified by macroporous resin D101,Sephadex LH-20 gel,silica gel and other chromatographic techniques,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Twenty-three compounds were isolated and identified as 15,16-epoxy-15α-methoxy-ent-clerod-3-en-18-oic acid(1),13-epi-15,16-epoxy-15α-methoxy-ent-clerod-3-en-18-oic acid(2),methyltrineracetal(3),epimethyltrineracetal(4),trinerolide(5),15-epitrinerolide(6),18-methylmalonyl-7α-hydroxy-meth-yltrineracetal(7),18-methylmalonyl-7α-hydroxy-epimethyltriner-acetal(8),18-methylmalonyl-methyltrineracetal(9),18-methylmalonyl-epi-methyltrineracetal(10),methy 3,5-dicaffeoylquinate(11),8-dimetho-xyflavone(12),4',7-dihydroxy-5-methoxyflavanone(13),4-(3',4'-dihydroxycinna-moyl)-oxy-methy-lcinnamate(14),3',7-dihydroxy-4',6,8-trimethoxy-flavone(15),erigeroflavanone(16),nepetin(17),4,2',4',β-tetrahydroxy-6'-methoxy-α,β-dihydrochalcone(18),eugeniyl-O-β-D-glucoside(19),7-hydroxyl-5,6,3',4'-tetramethoxylflavone(20),phomoxanthone J(21),18-acetyl-7α-hydroxy-methyltrineracetal(22),18-acetyl-7α-hydroxy-epimethyltrineracetal(23).CONCLUSION Compounds 3-10 and 22-23 are epimers isolated from this plant for the first time.Compounds 11-16,18-21 are first isolated from genus Baccharis.

The current status of exoskeletons was introduced in enhancing individual soldier's battlefield rescue capabilities,promoting the integrated use of battlefield rescue equipment,protecting medical personnel on the battlefield and assisting injured soldiers in rehabilitation training.The challenges of exoskeletons faced in human-machine interaction,power supply endurance,heavy overall structure,restricted movement and high cost were analyzed when applied to medical service support,and some suggestions were proposed accordingly including enhancing technology research and development,integrated application,communication and cooperation and personnel training.References were provided for the application of exoskeletons in China's medical service support.[Chinese Medical Equipment Journal,2024,45(3):71-75]

Objective To explore the influencing factors of mild cognitive impairment(MCI)in patients with atrial fibrillation and diabetes mellitus,and to establish the prediction model,so as to provide guidance for the treatment of MCI in patients with atrial fibrillation and diabetes mellitus.Methods 199 patients with atrial fibrillation and diabetes diagnosed in the second ward of Cardiovascular Department of the Fifth Affiliated Hospital of Zhengzhou University from January 2023 to January 2024 were analyzed.The related factors of MCI in patients with atrial fibrillation and diabetes mellitus were analyzed by univariate analysis and multivariate logistic regres-sion.According to the results of multivariate logistic regression analysis,the prediction model of MCI in patients with atrial fibrillation and diabetes mellitus was established.Results Univariate analysis showed that age(P=0.002 3),homocysteine(P＜0.000 1),fasting blood glucose(P=0.022 5),glycated hemoglobin(P=0.006 6),and blood uric acid(P=0.032 2)were the influencing factors of MCI.Multivariate logistic regression analysis:age(OR=1.08,P=0.000 4),homocysteine(OR=1.37,P＜0.000 1),fasting blood glucose(OR=1.22,P=0.023 5),glycated hemoglobin(OR=1.61,P=0.004 2),and blood uric acid(OR=1.29,P=0.009 1)were the independent influencing factors of MCI.The optimal threshold is when the Youden index(YI=sensitivity+speci-ficity)is maximum.At the optimal threshold,the sensitivity was 0.74,the specificity was 0.80,and the area under the curve(AUC)was 0.809,indicating that the model can effectively predict the occurrence of MCI.Conclusion Age,fasting blood glucose,blood homocysteine,blood uric acid and glycosylated hemoglobin are independent risk factors for MCI in patients with atrial fibrillation and diabetes.The clinical prediction model based on multivariate logistic regression has a certain predictive value for the occurrence of MCI in patients with atrial fibrillation and diabetes mellitus.

Objective:To investigate the efficacy of microscopic decompression in degenerative lumbar spinal stenosis (DLSS) under single percutaneous tubular retractor system.Methods:A retrospective analysis was performed; 117 DLSS patients with imaging manifestations as non-segmental lumbar instability, admitted to Department of Neurosurgery, 900 th Hospital of PLA Joint Logistics Team from October 2018 to April 2023 were enrolled consecutively. These patients failed in strict conservative treatment and then changed to posterior lumbar spinal canal and nerve root decompression by microscopy and percutaneous tubular retractor system. These patients were followed up for 6-50 months. Pain visual analogue score (VAS) and lumbar Oswestry dysfunction index (ODI) were recorded and results of X-rays, CT and MRI of lumbar spines were analyzed 1 d before and 1 week after decompression and at the last follow-up. Modified MacNab criteria were used to evaluate the efficacy at the last follow-up. Results:Among the 117 patients, unilateral laminectomy for unilateral decompression was performed in 56 patients (47.9%) and unilateral laminotomy for bilateral decompression in 61 (52.1%). Single segment decompression was performed in 109 patients (93.2%) and double segment decompression in 8 (6.8%). Dural sac rupture occurred in 4 patients (3.5%), and immediate occlusion was given; no cerebrospinal fluid leakage was noted after decompression. All patients did not experience obvious nerve damage during decompression or intervertebral infection/lumbar instability after decompression. After 18 (13, 24) months of follow-up, VAS scores of the patients at the last follow-up decreased from (5.96±0.85) 1 d before decompression and (1.75±0.61) 1 week after decompression to (1.01±0.59), and lumbar ODI decreased from (63.22±8.33)% 1 d before decompression and (17.66±5.20)% 1 week after decompression to (10.64±3.44)%, with significant differences ( P<0.05). At the last follow-up, modified MacNab criteria indicated 46 patients (39.3%) as excellent, 66 (56.4%) as good, 3 (2.6%) as fair, and 2 (1.7%) as poor, with an excellent/good therapeutic rate of 95.7%. Conclusion:For surgical treatment of DLSS patients without evidenced preoperative spinal instability, personalized unilateral or bilateral spinal canal decompression under microscope by combiningsingle percutaneous tubular retractor system can effectively reduce surgical trauma and achieve satisfactory surgical results.