Biomanufacturing is an advanced manufacturing method that integrates biology, chemistry, and engineering. It utilizes renewable biomass and biological organisms as production media to scale up the production of target products through fermentation. Compared with petrochemical routes, biomanufacturing offers significant advantages in reducing CO₂ emissions, lowering energy consumption, and cutting costs. With the development of systems biology and synthetic biology and the accumulation of bioinformatics data, the integration of information technologies such as artificial intelligence, large models, and high-performance computing with biotechnology is propelling biomanufacturing into a data-driven era. This paper reviews the latest research progress on databases, knowledge bases, and large language models for biomanufacturing. It explores the development directions, challenges, and emerging technical methods in this field, aiming to provide guidance and inspiration for scientific research in related areas.
Biotechnology/methods* ; Knowledge Bases ; Synthetic Biology ; Databases, Factual ; Artificial Intelligence ; Systems Biology ; Computational Biology ; Fermentation

The announcement of the 9th edition of TNM staging system for thymic tumors was one of the highlights at the World Conference on Lung Cancer 2023. The revision, based on a larger and more detailed database, provides changes and confirmation from the last system. The 9th edition of TNM staging system aims to balance statistical significance and clinical feasibility. The birth of an improved TNM staging system heralds the changes that will follow in clinical practice and scientific research.

ObjectiveTo investigate the mechanism of action and main active components of Xiaoyaosan in the treatment of diabetic mellitus-induced erectile dysfunction （DMED）. MethodStreptozotocin （STZ） was used to induce a diabetic rat model. The therapeutic efficacy of Xiaoyaosan was evaluated by measuring intracavernous pressure/mean arterial pressure （ICP/MAP） and using Masson's trichrome staining. The main active components， key targets， and potential signaling pathways of Xiaoyaosan for the treatment of DMED were predicted by network pharmacology and molecular docking. The predicted results were then validated by in vitro and in vivo experiments. ResultThe ICP/MAP measurements and Masson's staining results showed that compared with the results in the control group， the erectile function of rats in the model group was significantly reduced （P<0.01）， and the ratio of smooth muscle/collagen fibers was significantly reduced （P<0.01）. After treatment with Xiaoyaosan， compared with the results in the model group， the ICP/MAP value of the diabetic rats was significantly elevated （P<0.01）， and the ratio of smooth muscle/collagen fibers was significantly higher （P<0.01）. The results of network pharmacology showed that Xiaoyaosan acted on key targets such as albumin （ALB）， protein kinase B1 （Akt1）， interleukin-6 （IL-6）， and tumor necrosis factor （TNF） through its main active components， including quercetin， kaempferol， β-sitosterol， and stigmasterol. These components were involved in the regulation of the advanced glycation end-products/receptor for advanced glycation end-products （AGE/RAGE） signaling pathway and the phosphoinositide 3-kinases（PI3K）/Akt signaling pathway in diabetic complications. The results of molecular docking showed that the key components of Xiaoyaosan had good binding capabilities with core targets， with β-sitosterol showing the strongest binding affinity with ALB. In vivo experiments demonstrated that Xiaoyaosan could significantly increase the protein and mRNA expression of ALB and Akt1 in serum， and inhibit the expression of IL-6 and TNF-α. It also significantly upregulated the expression of protein and mRNA of phosphorylation（p）-PI3K and p-Akt， and inhibited the RAGE expression. The results of cellular thermal shift assay （CETSA） showed that β-sitosterol could significantly inhibit the degradation of ALB protein. ConclusionXiaoyaosan may restore erectile function in diabetic rats by modulating targets such as ALB， Akt1， IL-6， and TNF， and through the RAGE/PI3K/Akt signaling pathway， and its main active component is likely β-sitosterol.

ObjectiveTo evaluate the reliability of Foot Posture Index (FPI-6) for Chinese adolescent idiopathic scoliosis (AIS) patients. MethodsFrom July, 2021 to April, 2022, 35 AIS patients were recruited from Guangdong Second Hospital of Traditional Chinese Medicine and non-specially. They were evaluated with FPI-6 by two raters on the same days, and by one of the raters a week later. The intra-class correlation coefficient (ICC) of inter-rater and test-retest was calculated and Bland-Altman diagram was drawn; the correlation among the items score and total score was analyzed with Spearman correlation coefficient. ResultsThe ICCs were above 0.75 except talar head palpation, and eversion and inversion of the calcaneus. There was no significant difference in foot posture classification among the three evaluation results (χ² = 4.000, P > 0.05). There was a significant positive correlation between each item score and total score (r > 0.3, P < 0.01). ConclusionFPI-6 is reliable for people with mild AIS.

Constraint-based genome-scale metabolic network models (genome-scale metabolic models, GEMs) have been widely used to predict metabolic phenotypes. In addition to stoichiometric constraints, other constraints such as enzyme availability and thermodynamic feasibility may also limit the cellular phenotype solution space. Recently, extended GEM models considering either enzymatic or thermodynamic constraints have been developed to improve model prediction accuracy. This review summarizes the recent progresses on metabolic models with multiple constraints (MCGEMs). We presented the construction methods and various applications of MCGEMs including the simulation of gene knockout, prediction of biologically feasible pathways and identification of bottleneck steps. By integrating multiple constraints in a consistent modeling framework, MCGEMs can predict the metabolic bottlenecks and key controlling and modification targets for pathway optimization more precisely, and thus may provide more reliable design results to guide metabolic engineering of industrially important microorganisms.
Genome ; Metabolic Engineering ; Metabolic Networks and Pathways/genetics* ; Models, Biological ; Thermodynamics

Graph-theory-based pathway analysis is a commonly used method for pathway searching in genome-scale metabolic networks. However, such searching often results in many pathways biologically infeasible due to the presence of currency metabolites (e.g. H⁺, H₂O, CO₂, ATP etc.). Several methods have been proposed to address the problem but up to now there is no well-recognized methods for processing the currency metabolites. In this study, we proposed a new method based on the function of currency metabolites for transferring of functional groups such as phosphate. We processed most currency metabolites as pairs rather than individual metabolites, and ranked the pairs based on their importance in transferring functional groups, in order to make sure at least one main metabolite link exists for any reaction. The whole process can be done automatically by programming. Comparison with existing approaches indicates that more biologically infeasible pathways were removed by our method and the calculated pathways were more reliable, which may facilitate the graph-theory-based pathway design and visualization.
Genome ; Metabolic Networks and Pathways

In recent years, with the continuous studies on tumor metabonomics, more and more results have shown that changes of metabolism play important roles in the occurrence and development of malignant tumor. Carcinogenic factors can destroy the metabolic balance of human body, induce metabolic reprogramming, and then mediate a variety of biological behaviors to partici-pate in the proliferation and invasion of cancer cells. Lipids provide the body with the necessary energy and essential fatty acids, and a variety of lipid molecules and metabolites are involved in cell signal transduction. Lipid metabolism is an important link in the metabolic system of the body, and the relationship between the occurrence and development of pancreatic cancer and lipid metabo-lism is not clear. The purpose of this paper is to reveal the changes of lipid metabolism in pancreatic cancer, summarize some preclinical studies and clinical trials, and deeply explain the research status of abnormal lipid metabolism associated with pancreatic cancer, so as to provide new ideas for the study of pancreatic cancer pathogenesis and accurate treatment.

Pancreatic cancer is a rapidly progressive and highly malignancy of the digestive system. In recent years, the diagnosis and treatment of pancreatic cancer has been in a slow stage of development, and the 5-year survival rate of patients remains very low. The main objective of translational medicine is to remove the barriers between basic medical research and clinical medical applications, to achieve practical integration between laboratory and clinic, and to accelerate the translation of the results obtained from basic research into clinical diagnosis, evaluation and treatment of diseases, thus promoting the development of life sciences. With the rapid development of the concept and technology of translational medicine, its application in the early diagnosis of pancreatic cancer can bring new hope for effectively improving the overall prognosis of patients. The authors comprehensively analyzed the latest research progress of translational medicine in the early diagnosis of pancreatic cancer in order to improve the early diagnosis and long-term survival of pancreatic cancer patient.

Objective:To investigate the clinical features, risk factors and prognosis of Clostridium difficile infection/colonization (CDI/CDC) in emergency intensive care unit (EICU) of Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, then provides theoretical basis for clinical treatment. Methods:A retrospective case-control study was conducted. The data of EICU patients admitted to Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine from June 2016 to June 2020 were collected. Taking the CDI/CDC patients as research objects [ Clostridium difficile (CD) positive group] and the CD negative patients with the same gender and age difference less than 5 years who were admitted to the hospital during the same period as the control (CD negative group). Demographic information, risk factors, prognosis and stool samples were collected. Single factor analysis and binary Logistic regression were used to analyze the CD positive infection rate, risk factors, and hospital death of patients with different clinical characteristics. Results:About 487 patients in EICU were included, 76 cases were taken into CD positive group, CD positive rate was 15.6%, including CDI 11 cases, CDC 65 cases. Among the CD positive group, all of the cases used proton pump inhibitor (PPI), and 75 cases used at least one antibiotic. Seventy-six CD negative patients with or without diarrhea (CD negative group) were included in this study. Among them, 75 patients used PPI and 74 patients used at least one antibiotic. Univariate analysis showed that acute physiology and chronic health evaluation Ⅱ (APACHEⅡ), duration of hospitalization, and carbapenem use were the risk factors for CDI/CDC. There were significant differences in the above indicators between CD positive group and CD negative group [APACHEⅡ: 18.0 (12.2, 25.8) vs. 10.0 (7.0, 14.0), duration of hospitalization (days): 46.0 (30.5, 72.5) vs. 18.5 (9.2, 37.0), proportion of carbapenems: 81.6% (62/76) vs. 64.5% (49/76), all P < 0.05]. Binary Logistic analysis regression analysis showed that APACHEⅡ score [odds ratio ( OR) = 0.802, 95% confidence interval (95% CI) was 0.730-0.882, P < 0.01] and duration of hospitalization ( OR = 0.960, 95% CI was 0.942-0.978, P < 0.01) were independent risk factors for CDI/CDC. There was no difference in overall mortality between the CD positive group and CD negative group [27.6% (21/76) vs. 38.2% (29/76), P = 0.167]. Conclusions:Critically ill patients in EICU routinely use PPI and antibiotics, and the use of antibiotics does not affect the CD positive rate. The independent risk factors of CDI/CDC are the APACHEⅡ score and the duration of hospitalization, but fecal CD positive has no obvious influence on death.

Thymic epithelial tumors are the most common tumors in anterior mediastinum. They are used to be considered rare in incidence, with an indolent nature of biological behaviors, which led to the lack of high level evidence obtained from prospective randomized controlled trials to guide the clinical treatment. At present, the experience of diagnosis and treatment of thymic tumors varies greatly in different regions. And there are still many problems remain to be solved. This paper aims to establish a standardized surgical treatment based on the latest researches in surgical indications, resection extent, surgical approach, lymph node dissection and postoperative management of thymic tumors.