ObjectiveFat infiltration has been shown to be closely related to muscle mass loss and a variety of muscle diseases. This study proposes a method based on phase-angle electrical impedance tomography (ΦEIT) to visualize the electrical characteristic response caused by muscle fat infiltration, aiming to provide a new technical means for early non-invasive detection of muscle mass deterioration. MethodsThis study was divided into two parts. First, a laboratory pork model was constructed to simulate different degrees of fat infiltration by injecting1 ml or 2 ml of emulsified fat solution into different muscle compartments, and the phase angle images were reconstructed using ΦEIT. Second, a human experiment was conducted to recruit healthy subjects (n=8) from two age groups (20-25 years old and 26-30 years old). The fat content percentage η_fat of the left and right legs was measured by bioelectrical impedance analysis (BIA), and the phase angle images of the left and right calves were reconstructed using ΦEIT. The relationship between the global average phase angle Φ_M and the spatial average phase angle Φ_Mi of each muscle compartment and fat infiltration was further analyzed. ResultsIn the laboratory pork model, the grayscale value of the image increased with the increase of η_fat and Φ_M showed a downward trend. The results of human experiments showed that at the same fat content percentage, the Φ_M of the 26-30-year-old group was about 20%-35% lower than that of the 20-25-year-old group. The fat content percentage was significantly negatively correlated with Φ_M. In addition, the M₂ (soleus) compartment was most sensitive to fat infiltration, and the spatial average phase angles of the M₂ (soleus), M₃ (tibialis posterior and flexor digitorum longus), and M₄ (tibialis anterior, extensor digitorum longus, and peroneus longus) compartments all showed significant inter-group differences. ConclusionΦEIT imaging can effectively distinguish different degrees of fat infiltration, especially in deep, small or specially located muscles, showing high sensitivity, demonstrating the potential application of this method in local muscle mass monitoring and early non-invasive diagnosis.

Most chemical medicines have polymorphs. The difference of medicine polymorphs in physicochemical properties directly affects the stability, efficacy, and safety of solid medicine products. Polymorphs is incomparably important to pharmaceutical chemistry, manufacturing, and control. Meantime polymorphs is a key factor for the quality of high-end drug and formulations. Polymorph prediction technology can effectively guide screening of trial experiments, and reduce the risk of missing stable crystal form in the traditional experiment. Polymorph prediction technology was firstly based on theoretical calculations such as quantum mechanics and computational chemistry, and then was developed by the key technology of machine learning using the artificial intelligence. Nowadays, the popular trend is to combine the advantages of theoretical calculation and machine learning to jointly predict crystal structure. Recently, predicting medicine polymorphs has still been a challenging problem. It is expected to learn from and integrate existing technologies to predict medicine polymorphs more accurately and efficiently.

Coronary restenosis is an important cause of poor long-term prognosis in patients with coronary heart disease. Here, we show that lysine methyltransferase SMYD2 expression in the nucleus is significantly elevated in serum- and PDGF-BB-induced vascular smooth muscle cells (VSMCs), and in tissues of carotid artery injury-induced neointimal hyperplasia. Smyd2 overexpression in VSMCs (Smyd2-vTg) facilitates, but treatment with its specific inhibitor LLY-507 or SMYD2 knockdown significantly inhibits VSMC phenotypic switching and carotid artery injury-induced neointima formation in mice. Transcriptome sequencing revealed that SMYD2 knockdown represses the expression of serum response factor (SRF) target genes and that SRF overexpression largely reverses the inhibitory effect of SMYD2 knockdown on VSMC proliferation. HDAC3 directly interacts with and deacetylates SRF, which enhances SRF transcriptional activity in VSMCs. Moreover, SMYD2 promotes HDAC3 expression via tri-methylation of H3K36 at its promoter. RGFP966, a specific inhibitor of HDAC3, not only counteracts the pro-proliferation effect of SMYD2 overexpression on VSMCs, but also inhibits carotid artery injury-induced neointima formation in mice. HDAC3 partially abolishes the inhibitory effect of SMYD2 knockdown on VSMC proliferation in a deacetylase activity-dependent manner. Our results reveal that the SMYD2-HDAC3-SRF axis constitutes a novel and critical epigenetic mechanism that regulates VSMC phenotypic switching and neointimal hyperplasia.

The n-butanol fraction of Alpinia oxyphylla Fructus 70% ethanol extract was separated and purified using column chromatography with MCI Gel CHP-20, Sephadex LH-20, ODS, and silica gel, combined with semi preparative liquid phase and TLC separation methods. One new halogenated 4,5-seco-eudesmane sesquiterpenoid and two new eremophilane sesquiterpenoids were isolated and purified from the n-butanol fraction of Alpinia oxyphylla Fructus. The structures of the isolated compounds were identified using modern spectroscopic methods (1D, 2D NMR, UV, IR, MS, etc.), and the absolute configuration of the new compounds were determined using the methods of calculated ECD and induced ECD.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Objective To study the bioequivalence of test and reference olmesartan tablet in Chinese healthy subjects after single dose under fasting and fed conditions.Methods A single-center,random,open,single-dose,two-preparations,double-period,crossover study was adopted.A total of 48 healthy adult male and female subjects(24 cases of fasting test and 24 cases of fed test)were included in the random crossover administration.Single oral dose 20 mg of test and reference were taken under fasting and postprandial conditions,respectively.Plasma concentration of olmesartan in plasma were determined by liquid chromatography tandem mass spectrometry.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin 8.0 software.Results The main pharmacokinetic parameters of the test and reference preparations of olmesartan tablets in the fasting group were as follows:Cmax were(653.06±133.53)and(617.37±151.16)ng·mL-1,AUC0-t were(4 201.18±1 035.21)and(4 087.38±889.99)ng·mL-1·h,AUC0-∞ were(4 254.30±1 058.90)and(4 135.69±905.29)ng·mL-1·h.The main pharmacokinetic parameters of the test and reference preparations of olmesartan tablets in the postprandial group were as follows:Cmax were(574.78±177.05)and(579.98±107.74)ng·mL-1,AUC0-t were(3 288.37±866.06)and(3 181.51±801.06)ng·mL-1·h,AUC0-∞ were(3 326.11±874.26)and(3 242.01±823.09)ng·mL-1·h.Under fasting and postprandial conditions,the 90％confidence intervals of the main pharmacokinetic parameters of the test and reference preparations are both 80.00％-125.00％.Conclusion Under fasting and postprandial conditions,a single oral dose of test and reference preparations olmesartan tablets in Chinese healthy adult volunteers showed bioequivalence.

Objective:To assess the efficacy of different fusion strategies involving the convolutional block attention module (CBAM) and Unet for automatic pancreas segmentation in enhanced CT images of patients with acute pancreatitis.Methods:A retrospective analysis was conducted on 1 158 patients with acute pancreatitis admitted to the Affiliated Hospital of North Sichuan Medical College between January 1st, 2016 and July 30th, 2021. Among them, 141 patients with first-episode acute pancreatitis were randomly categorized into mild, moderate, and severe cases. The test set comprised 5 mild and 15 severe cases, while the remaining 126 cases were used for training. Within the training set, 20% of the data was randomly allocated as the validation set. Different fusion paths of the CBAM and Unet networks were trained, utilizing the Dice similarity coefficient, Hausdorff distance (HD), and pixel accuracy (PA) as evaluation metrics. The model demonstrating the best performance on the validation set was selected and evaluated on the test set. Additionally, the Unet model was combined with the attention gate attention mechanism (AttentionUnet) in the skip connection, and the ResBlock replaced the original convolution module (ResUnet) in the Unet network. Moreover, the skip connection branch module of feature extraction was integrated with CBAM (ResUnet_CBAM) for comparison.Results:Unet_CBAM achieved better results on the test set with a Dice value of 80.06%, a HD value of 3.765 9 and a PA value of 0.992 3, all surpassing other fusion strategies. The segmentation accuracy of the pancreatic region in CT images of acute pancreatitis patients was notably enhanced compared to Unet and its related variant networks.Conclusions:The Unet network integrated into CBAM after skip connection can better perform pancreatic segmentation on enhanced CT images of patients with acute pancreatitis and can effectively improve the efficiency of relevant personnel in pancreatic segmentation on enhanced CT images of patients with acute pancreatitis.

Objective To investigate the clinical characteristics of female migraine patients with patent foramen ovale(PFO)and design a risk prediction model for PFO in female migraine patients(migraineur patients PFO risk prediction model,MPRPM).Methods Female migraine patients who visited Zhongshan Hospital,Fudan University from Jun 1,2019 to Dec 31,2022 were included.Preoperative information and follow-up results after discontinuation of medication were collected.Patients were divided into PFO-positive and PFO-negative groups based on transesophageal echocardiography results.A multivariate Logistic regression model and a random forest model were constructed,and the random forest model was validated multidimensionally.Key features were selected based on the mean decrease accuracy(MDA)to construct MPRPM.Results A total of 305 female patients were included in the study,with 204 patients in the PFO-positive group and 101 patients in the PFO-negative group.Multivariate Logistic regression analysis showed that age at migraine onset,attack frequency,severe impact on life during attacks,exercise-related headaches,menstruation-induced headaches,aura migraines,and a history of cryptogenic stroke were predictive factors for PFO positivity.The random forest model effectively predicted the incidence of PFO in female migraine patients,with an AUC of 0.895(95%CI:0.847-0.943).MPRPM demonstrated a sensitivity of 71.6%and specificity of 91.1%(AUC:0.862,95%CI:0.818-0.906,P<0.001).The optimal cut-off value was 2.5 points.Patients correctly classified by the model showed a higher rate of symptom improvement compared to incorrectly classified patients(94.3%vs.82.0%,P=0.023).Conclusion We identified predictive factors for PFO in migraine patients.MPRPM can provide guidance in the diagnostic process and therapeutic decision-making for female migraine patients,assist in patient triage,and reduce the healthcare burden.