ObjectiveThis paper aims to investigate the differential mechanisms underlying the staged therapeutic effects of Qijia Rougan formula on liver fibrosis using proteomic technology. MethodsThe staged rat model of liver fibrosis was established by subcutaneous injection of carbon tetrachloride （CCl₄） and olive oil. One hundred and four SD rats were randomized into thirteen groups：a normal group，a two-week model group，a four-week model group，a six-week model group，an eight-week model group，a two-week Qijia Rougan formula group，a four-week Qijia Rougan formula group，a six-week Qijia Rougan formula group，an eight-week Qijia Rougan formula group，a two-week compound Biejia Ruangan tablet group，a four-week Compound Biejia Ruangan Tablet group，a six-week Compound Biejia Ruangan Tablet group，and an eight-week compound Biejia Ruangan tablet group. After two weeks of drug intervention，liver tissue and abdominal aortic blood samples were collected from the rats for testing. Hematoxylin-eosin （HE） staining，Masson staining，and Picro Sirius red staining were used to observe pathological damage and collagen fiber deposition in liver tissues. Immunohistochemistry （IHC） was employed to detect the contents of fibrosis markers in liver tissues. The contents of liver function indicators in the serum were measured using a fully automated biochemical analyzer，and the levels of liver fibrosis indicators in the serum were assessed by enzyme-linked immunosorbent assay （ELISA）. Liver tissues from the normal group，each model group，and each Qijia Rougan formula group were subjected to label-free quantitative proteomic analysis to identify differential proteins among the groups，with key proteins validated by Western blot. Finally，bioinformatics analysis was performed on the differential proteins. Results（1） The staged rat model of liver fibrosis constructed with CCl₄ and olive oil showed pathological results at the 2^nd，4^th，6^th，and 8^th weeks of modeling that were consistent with the Metavir standards for the F1，F2，F3，and F4 stages. Compared with those in the normal control group，the protein expressions of α-smooth muscle actin （α-SMA） and Collagen Ⅰ were significantly increased in each stage （P<0.05）. The levels of liver function indicators in the serum，including alanine aminotransferase （ALT），aspartate aminotransferase （AST），alkaline phosphatase （ALP），direct bilirubin （DBIL），and total bilirubin （TBil） in each model group，were significantly elevated in each stage （P<0.01）. The levels of liver fibrosis indicators in the serum，including procollagen Ⅲ peptide （PⅢP），type Ⅳ collagen（Ⅳ-C），hyaluronic acid （HA），and laminin （LN） in each model group，were significantly increased in each stage （P<0.05，P<0.01）. This study successfully established a staged rat model of liver fibrosis. （2） Compared with the model groups at each stage，the administration groups showed a reduction in hepatocyte ballooning degeneration，a more orderly arrangement of hepatocytes，and a decrease of inflammatory cell infiltration. The blue-stained collagen fibers became significantly thinner and finer，with reduced and narrowed fibrous septa. The areas of collagen fibers and Picro Sirius red staining were reduced （P<0.05）. The positive areas of α-SMA and Collagen Ⅰ expression were significantly decreased （P<0.05）. The levels of ALT，AST，ALP，DBIL，and TBil in the rats of the model groups at each stage were significantly reduced （P<0.05，P<0.01）. The levels of PⅢP，Ⅳ-C，HA，and LN in the rats of the model groups at each stage were significantly decreased （P<0.05）. Among these，the improvements in all indicators were most significant in the F3 stage （P<0.01）.（3） The proteomic results show that a total of 165 differential proteins exhibit a callback trend when comparing the model groups at four stages with the normal group，and when comparing the Qijia Rougan formula group with the model group. Western blot analysis reveals that the levels of NAD（P）H：quinone oxidoreductase 1 （NQO1），mitogen-activated protein kinase 1 （MAPK1），arginase 1 （Arg1），and glutathione S-transferase α1 （GSTA1） were consistent with the proteomic results. Bioinformatics results reveal that 165 differentially expressed proteins are enriched in multiple signaling pathways. Notably，signaling pathways such as drug metabolism-cytochrome P450，arginine biosynthesis，and the peroxisome proliferator-activated receptor （PPAR） signaling pathway were found to be closely associated with liver fibrosis，suggesting that the Qijia Rougan formula may exert its staged regulatory effects on liver fibrosis by regulating these pathways. ConclusionThe Qijia Rougan formula may achieve staged regulation of liver fibrosis by regulating drug metabolism-cytochrome P450，arginine biosynthesis，and the PPAR signaling pathway.

Objective:To construct a deep learning model based on YOLOV8-Seg algorithm to conduct automatic segmentation for the central gland(CG)and peripheral zone(PZ)of prostate,so as to provide a reliable basis for clinical diagnosis and treatment.Methods:The sequence data of T2-weighted imaging(T2WI)of horizontal relaxation time of 158 patients were selected from a public data set of magnetic resonance imaging(MRI)for prostate MRI,which was provided by the Charité University Hospital in Berlin,were selected.The all data were divided into a training set(109 cases),a validation set(16 cases),and a test set(33 cases)as the ratio of 7 to1 to 2.A lightweight asymmetric decoupled head(LADH)structure and the large kernel UniRepLKNetBlock module were integrated into the YOLOV8-Seg algorithm to enhance the capabilities of model's extraction feature,and the new model was named as YOLOV8-URLK.The assessment model with mean Average Precision(mAP),Dice Similarity Coefficient(DSC),95%Hausdorff Distance(HD95),and Average Surface Distance(ASD)was adopted to segment performance of the detection at prostate CG and PZ.Comparative experiments were conducted among that and YOLOV8-Seg,TransU-Net,and U-Net network,so as to validate the effectiveness of YOLOV8-URLK for detection and segmentation at prostate zone.Results:On the test set,the mAP@0.5(box)of YOLOV8-URLK model was 0.878,and the mean Dice coefficients,the mean HD95 values and the ASD values of that at CG and PZ were respectively(0.867,17.123 and 1.461)and(14.902,0.898 and 1.112).On the test set,the mAP@0.5(box)of YOLOV8-Seg model was 0.860,and the mean Dice coefficients of that at CG and PZ were 0.851 and 0.884,the mean HD95 values of that at them were 19.174 and 15.298,and ASD values of that at them were 1.781 and 1.219,respectively.On test set,the mean Dice coefficients of TransU-Net model at CG and PZ were 0.864 and 0.824,and the mean HD95 values of that at them were 18.134 and 19.402,and ASD values of that at them were 1.698 and 1.717,respectively.On the test set,the mean Dice coefficients of the U-Net model at CG and PZ were 0.857 and 0.690,and the mean HD95 values of that at them were 18.976 and 26.934,and ASD values of that at them were 1.753 and 2.135.The YOLOV8-URLK model can better reappear the segmentation trend of manual annotations.Conclusion:The YOLOV8-URLK model demonstrates higher precision in the detection and segmentation of MRI images of prostate,which were superior to YOLOV8-Seg,TransU-Net and U-Net.It can enhance the efficiency of the detection and segmentation.

The therapeutic effects of transcranial magnetic stimulation (TMS) are closely related to the structure of the stimulation coil. Based on this, this study designed an A-word coil and proposed a multi-strategy fusion multi-objective slime mould algorithm (MSSMA) aimed at optimizing the stimulation depth, focality, and intensity of the coil. MSSMA significantly improved the convergence and distribution of the algorithm by integrating a dual-elite guiding mechanism, a hyperbolic tangent control strategy, and a hybrid polynomial mutation strategy. Furthermore, compared with other stimulation coils, the novel coil optimized by the MSSMA demonstrates superior performance in terms of stimulation depth. To verify the optimization effects, a magnetic field measurement system was established, and a comparison of the measurement data with simulation data confirmed that the proposed algorithm could effectively optimize coil performance. In summary, this study provides a new approach for deep TMS, and the proposed algorithm holds significant reference value for multi-objective engineering optimization problems.
Algorithms ; Transcranial Magnetic Stimulation/instrumentation* ; Equipment Design ; Humans

Biomanufacturing harnesses engineered cells for the large-scale production of biochemicals, biopharmaceuticals, biofuels, and biomaterials, playing a vital role in mitigating global environmental crises, achieving carbon peaking and neutrality, and driving the green transformation of the economy and society. The effective design and construction of these engineered cells require precise and comprehensive computational models. Recent technological breakthroughs including high-throughput sequencing, mass spectrometry, spectroscopy, and microfluidic devices, coupled with advances in data science, artificial intelligence, and automation, have enabled the rapid acquisition of large-scale biological datasets, thereby facilitating a deeper understanding of cellular dynamics and the construction of mechanism-based models with enhanced accuracy. This review systematically summarises the mathematical frameworks employed in cellular modelling. It begins by evaluating prevalent mathematical paradigms, such as network topology analyses, stochastic processes, and kinetic equations, critically assessing their applicability across various contexts. The discussion then categorises modelling strategies for specific cellular processes, including cellular growth and division, morphogenesis, DNA replication, transcriptional regulation, metabolism, signal transduction, and quorum sensing. We also examine the recent progress in developing whole-cell models through the integration of diverse cellular processes. The review concludes by addressing key challenges such as data scarcity, unknown mechanisms, multi-dimensional data integration, and exponentially escalating computational complexity. Overall, this work consolidates the mathematical models for the precise simulation of cellular processes, thereby enhancing our understanding of the molecular mechanisms governing cellular functions and contributing to the future design and optimisation of engineered organisms.
Models, Biological ; Cell Physiological Phenomena ; Cell Engineering/methods* ; Humans

Biomanufacturing has emerged as a crucial driving force for efficient material conversion through engineered cells or cell-free systems. However, the intrinsic spatiotemporal heterogeneity, complexity, and dynamic characteristics of these processes pose significant challenges to systematic understanding, optimization, and regulation. This review summarizes essential methodologies for multi-omics data acquisition and analyses for bioprocesses and outlines modelling approaches based on multi-omics data. Furthermore, we explore practical applications of multi-omics and modelling in fine-tuning process parameters, improving fermentation control, elucidating stress response mechanisms, optimizing nutrient supplementation, and enabling real-time monitoring and adaptive adjustment. The substantial potential offered by integrating multi-omics with computational modelling for precision bioprocessing is also discussed. Finally, we identify current challenges in bioprocess optimization and propose the possible solutions, the implementation of which will significantly deepen understanding and enhance control of complex bioprocesses, ultimately driving the rapid advancement of biomanufacturing.
Fermentation ; Genomics/methods* ; Biotechnology/methods* ; Proteomics/methods* ; Models, Biological ; Metabolomics/methods* ; Bioreactors ; Multiomics

Objective:To construct a deep learning model based on YOLOV8-Seg algorithm to conduct automatic segmentation for the central gland(CG)and peripheral zone(PZ)of prostate,so as to provide a reliable basis for clinical diagnosis and treatment.Methods:The sequence data of T2-weighted imaging(T2WI)of horizontal relaxation time of 158 patients were selected from a public data set of magnetic resonance imaging(MRI)for prostate MRI,which was provided by the Charité University Hospital in Berlin,were selected.The all data were divided into a training set(109 cases),a validation set(16 cases),and a test set(33 cases)as the ratio of 7 to1 to 2.A lightweight asymmetric decoupled head(LADH)structure and the large kernel UniRepLKNetBlock module were integrated into the YOLOV8-Seg algorithm to enhance the capabilities of model's extraction feature,and the new model was named as YOLOV8-URLK.The assessment model with mean Average Precision(mAP),Dice Similarity Coefficient(DSC),95%Hausdorff Distance(HD95),and Average Surface Distance(ASD)was adopted to segment performance of the detection at prostate CG and PZ.Comparative experiments were conducted among that and YOLOV8-Seg,TransU-Net,and U-Net network,so as to validate the effectiveness of YOLOV8-URLK for detection and segmentation at prostate zone.Results:On the test set,the mAP@0.5(box)of YOLOV8-URLK model was 0.878,and the mean Dice coefficients,the mean HD95 values and the ASD values of that at CG and PZ were respectively(0.867,17.123 and 1.461)and(14.902,0.898 and 1.112).On the test set,the mAP@0.5(box)of YOLOV8-Seg model was 0.860,and the mean Dice coefficients of that at CG and PZ were 0.851 and 0.884,the mean HD95 values of that at them were 19.174 and 15.298,and ASD values of that at them were 1.781 and 1.219,respectively.On test set,the mean Dice coefficients of TransU-Net model at CG and PZ were 0.864 and 0.824,and the mean HD95 values of that at them were 18.134 and 19.402,and ASD values of that at them were 1.698 and 1.717,respectively.On the test set,the mean Dice coefficients of the U-Net model at CG and PZ were 0.857 and 0.690,and the mean HD95 values of that at them were 18.976 and 26.934,and ASD values of that at them were 1.753 and 2.135.The YOLOV8-URLK model can better reappear the segmentation trend of manual annotations.Conclusion:The YOLOV8-URLK model demonstrates higher precision in the detection and segmentation of MRI images of prostate,which were superior to YOLOV8-Seg,TransU-Net and U-Net.It can enhance the efficiency of the detection and segmentation.

Objective To analyze the expression and role of the disulfidptosis-related gene PDZ and LIM domain protein 1(PDLIM1)in various tumors.Methods The expression of PDLIM1 mRNA was analyzed by Xiantao website.The diagnostic and prognostic capabilities of PDLIM1 in 33 types of tumors were explored using the Xiantao website and Sangerbox 3.0 data analysis platform.The correlation between PDLIM1 and clinical classification and its staging was analyzed by the TISIDB database.The correlation between PDLIM1 and tumor immunity was analyzed by Sangerbox 3.0 data analysis platform and Kaplan-Meier Plotter database.Protein-protein interaction networks(PPI)were constructed by STRING database and Cytoscape,and were enriched by Sangerbox 3.0 data analysis platform.Finally,the GSCA website was applied to acquire the expression of PDLIM1 mRNA and its sensitivity to drugs.Results There was heterogeneity in the expression of PDLIM1 mRNA among 33 tumors.PDLIM1 had good diagnostic ability in cholangiocarcinoma(CHOL),glioblastoma multiforme(GBM),kidney renal clear cell carcinoma(KIRC),lung adenocarcinoma(LUAD),ovarian cancer(OV),pancreatic cancer(PAAD),skin cutaneous melanoma(SKCM)and testicular germ cell tumor(TGCT).High expression of PDLIM1 mRNA in glioma,low-grade glioma(LGG),KIPAN,GBM,uveal melanoma(UVM),and adrenocortical carcinoma(ACC)suggested poor prognosis,while low expression in sarcoma suggested poor prognosis.PALIM1 mRNA expression was correlated with the classification of head and neck squamous cell carcinoma(HNSC),kidney renal papillary cell carcinoma(KIRP),uterine corpus endometrial carcinoma(UCEC),uterine carcinosarcomas(UCS),and UVM as well as the staging of cervical squamous cell carcinoma and endocervical adenocarcinoma(CESC),HNSC,UCEC,and LGG.PDLIM1 was significantly associated with immune infiltration of 36 tumors led by prostateadenocarcinoma(PRAD),and was found to have a relatively good prognosis after immunotherapy in patients with high PDLIM1 mRNA expression.PDLIM1 exerted effects on organisms mainly through its involvement in the regulation of actin cytoskeleton,cell adhesion,and cancer-related pathways,and was sensitive to various drugs led by Isoliquiritigenin.Conclusion PDLIM1 was closely related to the clinical prognosis and immune infiltration of a variety of tumors,and it is expected to be a cancer diagnostic and prognostic biomarker or therapeutic target.

Humans ; Oxaliplatin/therapeutic use* ; Albumin-Bound Paclitaxel/therapeutic use* ; Stomach Neoplasms/pathology* ; Paclitaxel/therapeutic use* ; Adenocarcinoma/pathology* ; Chemotherapy, Adjuvant ; Nanoparticles ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use*

Objective To observe the effect of mild hypothermia on myocardial β-adrenergic receptor (β-AR) signal pathway after cardiopulmonary resuscitation (CPR) in pigs with cardiac arrest (CA) and explore the mechanism of myocardial protection. Methods Healthy male Landraces were collected for reproducing the CA-CPR model (after 8-minute untreated ventricular fibrillation, CPR was implemented). The animals were divided into two groups according to random number table (n = 8). In the mild hypothermia group, the blood temperature of the animals was induced to 33 ℃ and maintained for 6 hours within 20 minutes after return of spontaneous circulation (ROSC) by using a hypothermia therapeutic apparatus. In the control group, the body temperature of the animals was maintained at (38.0±0.5)℃ with cold and warm blankets. The heart rate (HR), mean arterial pressure (MAP), the maximum rate of increase or decrease in left rentricular pressure (+dp/dt max)were measured during the course of the experiment. The cardiac output (CO) was measured by heat dilution methods before CA (baseline), and 0.5, 1, 3, 6 hours after ROSC respectively, the venous blood was collected to detect the concentration of cTnI. Left ventricular ejection fraction (LVEF) was measured with cardiac ultrasound before CA and 6 hours after ROSC. Animals were sacrificed at 6 hours after ROSC and the myocardial tissue was harvested quickly, the mRNA expression of β1-AR in myocardium was detected by reverse transcription-polymerase chain reaction (RT-PCR), the contents of adenylate cyclase (AC) and cyclic adenosine monophosphate (cAMP) were detected by enzyme linked immunosorbent assay (ELISA), the protein content of G protein-coupled receptor kinase 2 (GRK2) was detected by Western Blot. Results After successful resuscitation, the HR of both groups were significantly higher than the baseline values, CO, ±dp/dt max were significantly decreased, MAP were not significantly changed, serum cTnI levels were significantly increased. Compared with the control group, HR at 0.5, 1, 3 hours after ROSC were significantly decreased in mild hypothermia group (bpm: 142.80±12.83 vs. 176.88±15.14, 115.80±11.48 vs. 147.88±18.53, 112.60±7.40 vs. 138.50±12.02, all 1 < 0.01), CO was significantly increased at 1 hours and 3 hours after ROSC (L/min: 3.97±0.40 vs. 3.02±0.32, 4.00±0.11 vs. 3.11±0.59, both 1 < 0.01), +dp/dt max at 3 hours and 6 hours was also significantly increased after ROSC [+dp/dt max (mmHg/s): 3 402.5±612.7 vs. 2 130.0±450.6, 3 857.5±510.4 vs. 2 562.5±633.9; -dp/dt max (mmHg/s): 2 935.0±753.2 vs. 1 732.5±513.6, 3 520.0±563.6 vs. 2 510.0±554.3, all 1 < 0.05], the cTnI was significantly decreased at 3 hours and 6 hours afher ROSC (μg/L: 1.39±0.40 vs. 3.24±0.78, 1.46±0.35 vs. 3.78±0.93, both 1 < 0.01). The left at 6 hours after ROSC in both groups was decreased as compared with that before CA. The LVEF in the mild hypothermia group was higher than that in the control group (0.52±0.04 vs. 0.40±0.05, 1 < 0.05). The mRNA expression of β1-AR, and concentrations of AC and cAMP in hypothermia group were significantly higher than those in control group [β1-AR mRNA (2-ΔΔCT): 1.18±0.39 vs. 0.55±0.17, AC (ng/L):197.0±10.5 vs. 162.0±6.3, cAMP (nmol/L): 1 310.58±48.82 vs. 891.25±64.95, all 1 < 0.05], GRK2 was lower than that in the control group (GRK2/GAPDH: 0.45±0.05 vs. 0.80±0.08, 1 < 0.05). Conclusion Mild hypothermia can reduce the degree of cardiac function injury after CPR, and its mechanism may be related to the reduction of impaired myocardial β-AR signaling after CPR.

Objective To investigate the antimicrobial resistance of clinical isolates in Tongling People′s Hospital during 2013. Methods A total of 2 281 nonduplicate clinical isolates were collected.Kirby-Bauer disc diffusion method was employed to study the antimicrobial susceptibility.The data were analyzed with WHONET 5.6 software according to CLSI 2012 breakpoints. Results The top 5 most frequently isolated microorganisms were E.coli (479,21.0%),K.pneumoniae (360,15.8%),A. baumannii (271,11.9%),P .aeruginosa (240,10.5%),S.aureus (171,7.5%).Gram negative and gram positive microorganisms accounted for 76.5% and 23.5%,respectively.The prevalence of methicillin-resistant strains in S.aureus (MRSA)and coagulase negative Staphylococcus (MRCNS)was 38.6% and 73.1%,respectively.The resistance rates of MR strains to beta-lactams and other antimicrobial agents were much higher than those of MS strains.No staphylococcal strain was found resistant to vancomycin or teicoplanin.E.faecalis showed relatively lower resistance to penicillin,ampicillin and nitrofurantoin.E.faecium strains were more resistant than E.faecalis to most of the antibiotics tested.Approximately 50.5% of E.coli and 44.5% of Klebsiella isolates produced extended-spectrum beta-lactamases (ESBLs).The ESBLs-respectively.And 29.8% and 23.4% of the P .aeruginosa strains were resistant to imipenem and meropenem.Nearly all (94.0%)P .aeruginosa isolates were susceptible to amikacin.Conclusions There appears a trend of increasing resistance in the clinical bacterial isolates in this hospital,especially the carbapenem-resistant Enterobacteriaceae,which is of great concern.It is mandatory to take effective antibiotic policy and infection control measures.