Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

ObjectiveTo address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill‑posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low‑to‑high dimensional mapping process, this study proposes a multi‑scale attention and dynamic sparse mask fusion network (MADS‑Net). The proposed method aims to enhance high‑resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast‑screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging. MethodsThe proposed network adopts a strategy of “locate first, reconstruct later”. It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion‑level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small‑sized target regions. ResultsExperimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as0.060 6±0.031 6, and a PSNR of (23.893 9±2.685 3) dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference. ConclusionThe results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model’s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

Objective To investigate the relationship between monocyte-to-lymphocyte ratio(MLR),sys-temic immune inflammation index(SII),and mean platelet volume to platelet count ratio(MPR)and the prognosis of maintenance hemodialysis patients with chronic kidney disease(CKD).Methods The medical re-cords of totally 152 patients with CKD who received maintenance hemodialysis in the hospital from July 2022 to September 2023 were retrospectively analyzed.The patients were divided into the death group and the sur-vival group according to the prognosis.General data such as age,gender,height,weight,and dialysis age,as well as clinical and laboratory indicators such as blood cell count,hemoglobin,albumin,blood creatinine,blood urea,and blood uric acid were collected and analyzed.MLR,SII and MPR were calculated for each patient,and multivariate Logistic regression analysis was used to identify risk factors affecting the survival prognosis of CKD patients after maintenance hemodialysis treatment,and receiver operating characteristic(ROC)curve was used to evaluate the predictive value of the above indicators for patients'prognosis.Results Among 152 CKD patients,11.8%died,and the main causes of death include cardiovascular events,infections,multiple or-gan failure,and so on.Compared with the survival group,the levels of blood urea,blood uric acid,MLR,SII and MPR in the death group were significantly increased(P<0.05).Multivariate Logistic regression analysis revealed that MLR,SII and MPR were independent risk factors affecting the survival prognosis of CKD pa-tients after receiving maintenance hemodialysis treatment(P<0.05).ROC curve analysis showed that the are-a under the curve(AUC)of MLR for predicting the survival prognosis of CKD patients after maintenance he-modialysis treatment was 0.783,the cut off value was 0.58,the sensitivity was 72.22%,and the specificity was 76.87%.The AUC of SII for predicting the survival prognosis of CKD patients after maintenance hemodi-alysis treatment was 0.714,the cut off value was 480.50,the sensitivity was 66.67%,and the specificity was 70.15%.The AUC of MPR for predicting the survival prognosis of CKD patients after maintenance hemodial-ysis treatment was 0.706,the cut off value was 0.095,the sensitivity was 61.11%,and the specificity was 75.37%.The AUC of the combined detection was 0.843,which was better than the individual predictions(P<0.05).Conclusion MLR,SII and MPR are closely related to the prognosis of maintenance hemodialysis patients with CKD,and these indexes could be used as important reference for assessing the prognosis of pa-tients,which could help in the clinical decision-making and the development of individualized treatment plans.

Objective To explore the relationship between C-reactive protein/albumin ratio(CAR)and the disease severity in patients with severe pneumonia,and its predictive value for 28-day mortality risk.Methods A retrospective analysis was conducted on 152 patients with severe pneumonia admitted to Fuyang People's Hospital from January 2020 to January 2022.They were divided into non-critical illness group(n=51),critical illness group(n=63),and extremely critical illness group(n=38)based on the disease severity.The clinical data such as age and gender of patients was collected,and Pearson correlation analysis was used to explore the correlation between CAR and the severity of illness[determined by Acute Physiology and Chronic Health Evaluation Ⅱ(APACHE Ⅱ)score].Multivariate logistic regression was employed to identify independent influencing factors of the severity of illness.According to the survival status of patients after 28 days of treatment,they were divided into survival group(n=107)and death group(n=45).CAR was categorized into quintiles(Q1-Q5),and multivariate logistic regression analysis was conducted to explore the correlation between CAR and 28-day mortality risk in severe pneumonia patients.A restricted cubic spline(RCS)model was used to analyze the dose-response relationship between CAR and mortality risk.The predictive value of CAR and related indicators for patient mortality risk was evaluated using the receiver operating characteristic curve(ROC).Results CAR was significantly positively correlated with the severity of the disease(APACHE Ⅱ score)(r=0.716,P<0.05).Neutrophil/lymphocyte ratio(NLR),blood lactate(Lac),and high CAR were independent risk factors for the disease severity in patients with severe pneumonia(P<0.05).After adjusting for confounding factors,the mortality risk increased with the increase of CAR(P<0.05).Subgroup analysis of the screened confounding factors revealed that the correlation between CAR and 28-day mortality risk in severe pneumonia patients remained stable across different APACHE Ⅱ scores,GCS scores,SOFA scores,white blood cell counts(WBC),neutrophils(NEU),red cell volume distribution width(RDW),procalcitonin(PCT),and Lac,with interactions observed between NLR and Lac subgroups(P<0.05).The RCS model indicated that there was no non-linear dose-response relationship between CAR and 28-day mortality risk in patients with severe pneumonia of different genders.ROC curve analysis showed that CAR,Lac,and NLR had good predictive value for 28-day mortality in severe pneumonia patients,with the combined predictive efficacy being significantly higher than that of individual indicators.Conclusion There is a close relationship between CAR and the progression and prognosis of severe pneumonia,making it a new approach to assessing the severity of illness and predicting mortality risk in patients.

Objective To address challenges such as the complex anatomical structure of the trigeminal nerve,difficulties in hands-on teaching,and the lack of integration with clinical knowledge,a virtual simulation-based experimental course was designed and implemented,with its application effectiveness analyzed.Methods The course was structured around the framework of"Exploring the Trigeminal Nerve-Examination of Trigeminal Neuralgia-Simulation of Surgical Treatment".It was applied in the human anatomy laboratory course for eight-year clinical medicine students through the following steps,goal refinement,key point analysis,instructional design,implementation,performance evaluation,and questionnaire surveys.Results The course integrated detailed trigeminal nerve anatomy with interdisciplinary knowledge from neurology and neurosurgery,thoroughly analyzing its functions.This approach helped students deeply understand the medical principle of"structure determines function"and efficiently master the content.Exam scores on trigeminal nerve-related questions improved significantly,and the virtual simulation course received the highest satisfaction rating among all human anatomy laboratory courses.Conclusion This course integrates virtual simulation technology with clinical medical education,and established a teaching loop of"basic anatomy-clinical diagnosis-surgical intervention".It effectively addresses core challenges in traditional teaching,such as abstract structures,difficulties in operation,and disconnection from clinical practice.The result demonstrates that this model not only enhances knowledge acquisition and test scores but also fosteres students' clinical thinking of"structure determines function",and receives high satisfaction.Therefore it may provide an innovative and scalable solution for medical course education reform.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.