Oral solid dosage forms require processes such as disintegration and dissolution to release the drug before it can be absorbed and utilized by the body. In this manuscript, imaging technology was used to continuously visualize and characterize the in vitro static drug release process of gliclazide modified release tablets from 15 manufacturers, combined with the traditional method of in vitro dissolution testing, to determine the release profile of gliclazide modified release tablets, to evaluate the similarity of the release profiles by using the similarity factor (f₂) method and based on the analysis of the release profiles fitted with a variety of mathematical models. The results indicate that the gliclazide modified release tablets produced by 14 companies are hydrophilic gel matrix tablets. Compared to the reference listed drug, the release profiles of formulations from 11 companies show high similarity (f₂ > 50) to the reference. Among these, formulations with visual characteristics similar to the reference exhibit similar release curves. This study provides an alternative method for the in vitro consistency evaluation of gliclazide modified release tablets, aiming to assess the in vitro release behaviour of generic formulations more accurately and comprehensively.

The Baihe Dihuang Decoction(BDD) is a representative traditional Chinese medicine formula that has been used to treat depression. This study employed metabolomics and network pharmacology to investigate the mechanism of BDD in the treatment of depression. Fifty male Sprague-Dawley(SD) rats were randomly assigned to the normal control group, model group, fluoxetine group, and high-and low-dose BDD groups. A rat model of depression was established through chronic unpredictable mild stress(CUMS), and the behavioral changes were detected by forced swimming test and open field test. Metabolomics technology was used to analyze the metabolic profiles of serum and hippocampal tissue to screen differential metabolites and related metabolic pathways. Additionally, network pharmacology and molecular docking techniques were used to investigate the key targets and core active ingredients of BDD in improving metabolic abnormalities of depression. A "component-target-metabolite-pathway" regulatory network was constructed. BDD could significantly improve depressive-like behavior in CUMS rats and regulate 12 differential metabolites in serum and 27 differential metabolites in the hippocampus, involving tryptophan metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, alanine, aspartate, and glutamate metabolism, tyrosine metabolism, and purine metabolism. Verbascoside, isorbascoside, and regaloside B were the key active ingredients for improving metabolic abnormalities in depression. Epidermal growth factor receptor(EGFR), protooncogene tyrosine-protein kinase(SRC), glycogen synthase kinase 3β(GSK3β), and androgen receptor(AR) were the key core targets for improving metabolic abnormalities of depression. This study offered a preliminary insight into the mechanism of BDD in alleviating metabolic abnormalities of depression through network regulation, providing valuable guidance for its clinical use and subsequent research.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Depression/genetics* ; Antidepressive Agents/chemistry* ; Network Pharmacology ; Hippocampus/drug effects* ; Humans ; Molecular Docking Simulation ; Behavior, Animal/drug effects* ; Disease Models, Animal

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

Objective The purpose of this study was to investigate the bacterial communities of biting midges and ticks collected from three sites in the Poyang Lake area,namely,Qunlu Practice Base,Peach Blossom Garden,and Huangtong Animal Husbandry,and whether vectors carry any bacterial pathogens that may cause diseases to humans,to provide scientific basis for prospective pathogen discovery and disease prevention and control. Methods Using a metataxonomics approach in concert with full-length 16S rRNA gene sequencing and operational phylogenetic unit(OPU)analysis,we characterized the species-level microbial community structure of two important vector species,biting midges and ticks,including 33 arthropod samples comprising 3,885 individuals,collected around Poyang Lake. Results A total of 662 OPUs were classified in biting midges,including 195 known species and 373 potentially new species,and 618 OPUs were classified in ticks,including 217 known species and 326 potentially new species.Surprisingly,OPUs with potentially pathogenicity were detected in both arthropod vectors,with 66 known species of biting midges reported to carry potential pathogens,including Asaia lannensis and Rickettsia bellii,compared to 50 in ticks,such as Acinetobacter lwoffii and Staphylococcus sciuri.We found that Proteobacteria was the most dominant group in both midges and ticks.Furthermore,the outcomes demonstrated that the microbiota of midges and ticks tend to be governed by a few highly abundant bacteria.Pantoea sp7 was predominant in biting midges,while Coxiella sp1 was enriched in ticks.Meanwhile,Coxiella spp.,which may be essential for the survival of Haemaphysalis longicornis Neumann,were detected in all tick samples.The identification of dominant species and pathogens of biting midges and ticks in this study serves to broaden our knowledge associated to microbes of arthropod vectors. Conclusion Biting midges and ticks carry large numbers of known and potentially novel bacteria,and carry a wide range of potentially pathogenic bacteria,which may pose a risk of infection to humans and animals.The microbial communities of midges and ticks tend to be dominated by a few highly abundant bacteria.

Objective To develop a biological safety protection third-level(BSL-3)laboratory based on folding-modular shelters to solve the problems of the existing laboratories in space and function expansion,large-scale deployment and low-cost transportation.Methods The BSL-3 laboratory was composed of a folding combined shelter module,a ventilation and purification module,a power supply and distribution module,a monitoring and communication module,a control system module and an equipment module.The folding combined shelter module used a leveling base frame as the foundation and a lightweight panel as the enclosure mechanism,and was divided into an auxiliary area and a protection protected area;the ventilation and purification module was made up of an air supply unit and an air exhaust unit,the air supply unit was integrated with a fresh-air air conditioner and the exhaust unit was equipped with a main fan,a standby fan and a bag in/bag out filter;the control system module adopted a supervision mode of decentralized control and centralized management,which executed communication with the data server as the center and Profinet protocol and MODBUS-TCP.Results The BSL-3 laboratory proved to meet the requirements of relevant standards in internal microenvironment,airflow direction,airtightness,working condition and disinfection effect.Conclusion The BSL-3 laboratory is compatible with large-scale transport and deployment and facilitates reliable and safe experiments for epidemic prevention and control and cross-regional support.[Chinese Medical Equipment Journal,2024,45(3):41-46]

Targeted therapeutic drugs for acute myeloid leukemia (AML) are showing immense development, thereby laying a solid foundation for the precise treatment of AML patients. The paper reviews four types of targeted drugs that have progressed rapidly for AML treatment (by targeting genes or signaling-pathway alterations, targeting apoptosis-related pathways, targeting cell-surface antigens, and targeting immune-related substances). We look forward to the future development directions of targeted drugs, providing references for hematologists and developers of new drugs for AML.

Objective:To analyze the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization based on Logistic regression model and decision tree model.Methods:This was a cross-sectional study. A total of 236 patients with primary liver cancer after transarterial chemoembolization in The Second Affiliated Hospital of Air Force Military Medical University from March 2021 to June 2022 were conveniently selected as the research subjects. The factors related to delayed nausea and vomiting were collected, and Logistic regression and decision tree models were established, respectively, and the differences between the two models were compared.Results:The incidence of delayed nausea and vomiting of patients with primary liver cancer after transarterial chemoembolization was 45.34% (107/236). Logistic regression model showed that age, anxiety, sleep disorder, emetic risk level of chemotherapeutic drugs, embolic agent type, and pain 24 hours after surgery were the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization(all P<0.05). Decision tree model showed that age, sleep disorder, emetic risk level of chemotherapeutic drugs, embolic agent type, and pain 24 hours after surgery were the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization (all P<0.05). The classification accuracy rates of Logistic regression, decision tree model and combined diagnosis of two models were 72.9%, 71.2% and 72.0% respectively; the areas under the ROC curve were 0.778, 0.781 and 0.806 respectively, with no significant difference (all P>0.05). Conclusions:The analysis results of Logistic regression and decision tree model on the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization are highly consistent, which can be combined to provide a more comprehensive reference for the evaluation and intervention of medical staff.

Tumor microenvironment (TME) is composed of endothelial cells, pericytes, immune cells, cancer-associated fibroblasts (CAFs), cancer stem cells (CSCs), extracellular matrix (ECM) and other components of the complex biological environment. TME interacts with the tumor cells through a large amount of signaling pathways, participates in the process of tumor progression, invasion, and metastasis. Hence, TME has become a potential therapeutic target for cancer treatment, exhibiting excellent therapeutic potential and research value in the field of cancer treatment. Currently, the novel nanotechnology has been widely applied in anticancer therapy, and nanotechnology-mediated drug delivery system is being explored to apply in TME modulation to inhibit tumor progression. Nanotechnology-mediated drug delivery has many advantages over traditional therapeutic modalities, including longer circulation times, improved bioavailability, and reduced toxicity. This review summarized the research of targeted nano-drug delivery based on TME regulation, including regulation strategies based on CSCs, CAFs, immune cells, ECM, tumor vascularization, exosomes, and microbiota. In addition, we summarized the advantages, opportunities, and challenges of TME regulation strategy compared with traditional treatment strategy, which provides a reference for the application of nano-drug delivery system based on TME regulation strategy in tumor precision therapy.

To identify the active constituents in vitro and blood-absorbed ingredients in vivo from Yin Chen Hao decoction provides scientific evidence for probing its prevention and treatment mechanism on acute liver injury. An ultrahigh performance liquid chromatography quadrupole-time of flight-mass spectrometry (UPLC-QTOF/MS) method was applied for analysis of Yin Chen Hao decoction and the serum samples of mice with con-A induced acute liver injury after preventive oral administration for 14 days (the use of all laboratory animals in this study was approved by the Ethics Committee of the Naval Medical University, 19YF1459400). A total of 90 chemical constituents were identified from Yin Chen Hao decoction, mainly were flavonoids, terpenoids, tannins, quinones. 5 prototype compounds were identified in the serum, including chrysophanol, deoxyrhapontin-8-O-gallate, mussaenosidic acid, herniarin, emodin. The established UPLC-QTOF/MS method could efficiently and sensitively identify the constituents in vitro and blood-absorbed ingredients of Yin Chen Hao decoction, primarily clarify the material basis of its hepatoprotective effect, and provided a scientific basis for the quality marker selection and the pharmacodynamic material basis research on the decoction.