Continuous manufacturing, as an innovative pharmaceutical production model, offers advantages such as high production efficiency and ease of control compared to traditional batch production, aligning with the future trend of drug production moving toward greater efficiency and intelligence. However, the development of continuous manufacturing technology in wet granulation has been slow. On one hand, this is closely related to its high technical complexity, substantial equipment investment costs, and stringent process control requirements. On the other hand, the long-term use of the traditional batch production model has created strong path dependence, and the lack of mature standardized processes further increases the difficulty of technological transformation. To promote the deep integration of wet granulation technology with continuous manufacturing, this review systematically outlines the current application of wet granulation in continuous manufacturing. It focuses on the development of key technologies such as online detection, process modeling, and process scale-up, with the aim of providing a reference for process innovation and application in wet granulation.
Drug Compounding/instrumentation* ; Technology, Pharmaceutical/methods* ; Drugs, Chinese Herbal/chemistry* ; Models, Theoretical

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

OBJECTIVES: To study the clinical and genetic characteristics of osteopetrosis (OPT) in children. METHODS: A retrospective analysis was performed on the clinical data of 14 children with OPT. Whole-exome sequencing was used to detect pathogenic genes, and clinical phenotypes and genotypic features were summarized. RESULTS: Among the 14 children (10 males and 4 females), the median age at diagnosis was 8 months. Clinical manifestations included systemic osteosclerosis (14 cases, 100%), anemia (12 cases, 86%), infections (10 cases, 71%), thrombocytopenia (9 cases, 64%), hepatosplenomegaly (8 cases, 57%), and developmental delay (5 cases, 36%). Malignant osteopetrosis (MOP) cases had lower platelet counts, creatine kinase isoenzyme, and serum calcium levels, but higher white blood cell counts, lactate dehydrogenase, and alkaline phosphatase levels compared to non-MOP cases (P<0.05). Genetic testing identified 15 variants in 12 patients, including 8 variants in the CLCN7 gene (53%), 6 in the TCIRG1 gene (40%), and 1 in the TNFRSF11A gene (7%). Three novel CLCN7 variants were identified: c.2351G>C, c.1215-43C>T, and c.1534G>A. All four patients with TCIRG1 variants exhibited MOP clinical phenotypes. Of the seven patients with CLCN7 variants, 4 presented with intermediate OPT, 2 with benign OPT, and 1 with MOP. CONCLUSIONS Clinical phenotypes of OPT in children are heterogeneous, predominantly involving CLCN7 and TCIRG1 gene variants, with a correlation between clinical phenotypes and genotypes.
Humans ; Osteopetrosis/genetics* ; Male ; Female ; Infant ; Child, Preschool ; Retrospective Studies ; Vacuolar Proton-Translocating ATPases/genetics* ; Child ; Chloride Channels/genetics* ; Mutation ; Receptor Activator of Nuclear Factor-kappa B

OBJECTIVE: To analyze two families with inherited dysfibrinogenemia, and explore the molecular pathogenic mechanisms. METHODS: The coagulation indexes of the probands and their family members were detected. The FGA, FGB, and FGG exons and their flanking sequences were amplified by PCR, and the mutation sites were identified by sequencing. SIFT, PolyPhen2, LRT, ReVe, MutationTaster, phyloP, and phastCons bioinformatics software were used to predict the functional impact of the mutation sites. Protein structure and amino acid conservation analysis of the variant were conducted using PyMOL and Clustal X software. RESULTS: The thrombin time (TT) of the proband in family 1 was prolonged to 37.00 s, and Fg∶C decreased to 0.52 g/L. The TT of the proband in family 2 was 20.30 s, and Fg∶C was 1.00 g/L, which was lower than the normal range. Genetic analysis revealed that the proband in family 1 had a heterozygous mutation c.80T>C in FGA, resulting in the substitution of phenylalanine 27 with serine (Phe27Ser). The proband in family 2 had a heterozygous mutation c.1007T>A in FGG, resulting in the substitution of methionine 336 with lysine (Met336Lys). Bioinformatics software prediction analysis indicated that both mutations were deleterious variants. PyMOL mutation models revealed that the Aα chain mutation (Phe27Ser) in family 1 and γ chain mutation (Met336Lys) in family 2 resulted in alterations in spatial structure and reduced protein stability. Clustal X results showed that both Aα Phe27 and γMet336 were highly conserved across homologous species. CONCLUSION Heterozygous mutations of FGA gene c.80T>C and FGG gene c.1007T>A are both pathogenic variants, causing inherited dysfibrinogenemia.
Female ; Humans ; Male ; Afibrinogenemia/genetics* ; Fibrinogen/genetics* ; Heterozygote ; Mutation ; Pedigree

Objective To investigate the clinical phenotypes and genotypes of children with congenital fibrinogen disorder(CFD).Methods A retrospective analysis was conducted on the clinical data of 16 children with CFD.Polymerase chain reaction was used to amplify all exons and flanking sequences of the FGA,FGB,and FGG genes,and sequencing was performed to analyze mutation characteristics.Results Among the 16 children,there were 9 boys(56%)and 7 girls(44%),with a median age of 4 years at the time of attending the hospital.Among these children,9(56%)attended the hospital due to bleeding events,and 7(44%)were diagnosed based on preoperative examination.The children with bleeding events had a significantly lower fibrinogen activity than those without bleeding events(P<0.05).Genetic testing was conducted on 12 children and revealed a total of 12 mutations,among which there were 4 novel mutations,i.e.,c.80T>C and c.1368delC in the FGA gene and c.1007T>A and C.1053C>A in the FGG gene.There were 2 cases of congenital afibrinogenemia caused by null mutations of the FGA gene,with relatively severe bleeding symptoms.There were 7 cases of congenital dysfibrinogenemia mainly caused by heterozygous missense mutations of the FGG and FGA genes,and their clinical phenotypes ranged from asymptomatic phenotype to varying degrees of bleeding.Conclusions The clinical phenotypes of children with CFD are heterogeneous,and the severity of bleeding is associated with the level of fibrinogen activity,but there is a weak association between clinical phenotype and genotype.

Aim To explore the efficacy of levosimendan on hypoxia pulmonary hypertension through animal experiments, and to further explore the potential mechanism of action using network pharmacological methods and molecular docking technique. Methods The rat model of hypoxia pulmonary hypertension was constructed to detect right heart systolic pressure and right heart remodeling index. HE , Masson, and VG staining were core targets were screened out. GO and KEGG pathway enrichment analysis were performed using the DAVID database. Molecular docking of the core targets was performed with the AutoDock software. Results The results of animal experiments showed that levosimendan had obvious therapeutic effect on hypoxia pulmonary hypertension. The network pharmacology results showed that SRC, HSP90AA1, MAPK1, PIK3R1, AKT1, HRAS, MAPK14, LCK, EGFR and ESR1 used to analyze the changes of rat lung histopathology. Search the Swiss Target Prediction, DrugBank Online, BatMan, Targetnet, SEA, and PharmMapper databases were used to screen for drug targets. Disease targets were retrieved from the GeneCards, OMIM databases. The "drug-target-disease" network was constructed after identification of the two intersection targets. The protein interaction network was constructed and the were the key targets to play a therapeutic role. Molecular docking showed good docking of levosimendan with all the top five core targets with degree values. Conclusions Levosimendan may exert a therapeutic effect on hypoxia-induced pulmonary hypertension through multiple targets.

Objective To establish a method for the simultaneous determination of aconitine,neoaconitine,hypaconitine,benzoyl aconitine,benzoyl mesaconine and benzoylhypacoitine in Xiaozhong ointment by UPLC-TQD-MS.Methods ACQUITY UPLC BEH C18 column(50 mm ×2.1 mm,1.7 μm),mobile phase 0.1％formic acid water(A)-acetonitrile(B),gradient elution,column temperature 40 ℃,flow rate 0.3 mL·min-1,injection volume 5 μL;electrospray ionization source(ESI+)and multiple reaction monitoring(MRM)were used for mass spectrometry analysis.Results The concentration of aconitine,new aconitine,hypaconitine,benzoyl aconitine,benzoyl new aconitine and benzoyl hypaconitine were 1.0-100.0 ng·mL-1,respectively,the average recovery were 98.62％-101.24％.The mass fractions of the six components were 0.18,0.33,0.38,0.43,0.28,0.06μg·g-1.Conclusion The method can be used to determine the content of 6 aconitine-type alkaloids in Xiaozhong ointment,and provide reference for the quality evaluation and clinical safe use of Xiaozhong ointment.

In order to study the compounds from Glechoma longituba (Nakai) Kupr. and explore the substance bases of its dissipating blood stasis, MCI, silica gel, Sephadex LH-20, ODS column chromatography and preparative thin layer chromatography were used to isolate and purify the compounds. The structures were identified by MS, 1D NMR, and 2D NMR spectra analysis, etc. Eight triterpenoids were isolated from dichloromethane fraction of ethanol extract from G. longituba and identified as 2α,3α,16β-trihydroxy-13α,27-cyclours-11-en-28-oic acid (1), 28-norurs-12-ene-3β,17β-diol (2), 28-norolean-12-ene-3β,17β-diol (3), oleanonic acid (4), 3β,13β-dihydroxyurs-11-en-28-oic acid (5), uvaol (6), oleanolic acid (7), ursolic acid (8). Compound 1 is a new hexacyclic triterpene with 13α,27-cyclopropane structure, named euscaphic acid H; compounds 2 and 3 were isolated from Lamiaceae for the first time while compounds 4 and 5 were isolated from this genus. The in vitro anticoagulant activity of triterpenoids was evaluated by four coagulation indexes (activated partial thromboplastin time, APTT; thrombin time, TT; prothrombin time, PT; fibrinogen, FIB). Among them, compounds 1 and 6 showed obvious anticoagulant effects.

OBJECTIVE: To explore the genotyping characteristics of human fecal Escherichia coli( E. coli) and the relationships between antibiotic resistance genes (ARGs) and multidrug resistance (MDR) of E. coli in Miyun District, Beijing, an area with high incidence of infectious diarrheal cases but no related data. METHODS: Over a period of 3 years, 94 E. coli strains were isolated from fecal samples collected from Miyun District Hospital, a surveillance hospital of the National Pathogen Identification Network. The antibiotic susceptibility of the isolates was determined by the broth microdilution method. ARGs, multilocus sequence typing (MLST), and polymorphism trees were analyzed using whole-genome sequencing data (WGS). RESULTS: This study revealed that 68.09% of the isolates had MDR, prevalent and distributed in different clades, with a relatively high rate and low pathogenicity. There was no difference in MDR between the diarrheal (49/70) and healthy groups (15/24). CONCLUSION We developed a random forest (RF) prediction model of TEM.1 + baeR + mphA + mphB + QnrS1 + AAC.3-IId to identify MDR status, highlighting its potential for early resistance identification. The causes of MDR are likely mobile units transmitting the ARGs. In the future, we will continue to strengthen the monitoring of ARGs and MDR, and increase the number of strains to further verify the accuracy of the MDR markers.
Humans ; Escherichia coli/genetics* ; Escherichia coli Infections/epidemiology* ; Multilocus Sequence Typing ; Genotype ; Beijing ; Drug Resistance, Multiple, Bacterial/genetics* ; Anti-Bacterial Agents/pharmacology* ; Diarrhea ; Microbial Sensitivity Tests

Humans ; Diabetes Mellitus, Type 2/epidemiology* ; Air Pollution/adverse effects* ; Air Pollutants/toxicity* ; Risk Assessment ; Particulate Matter ; Environmental Exposure