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

Prolonged total treatment time due to radiotherapy interruptions is detrimental to local tumor control.There are multiple causes that contribute to the occurrence of interruption events during radiotherapy,including public holidays,machine breakdown and maintenance,and radiotherapy complications.If treatment interruption events are unavoidable during radiotherapy,compensatory approaches should be taken to minimize the effects of radiotherapy interruptions on tumor control.Herein the study provides a summary on the causes and influence of radiotherapy interruptions,the ideas of interruption compensation,and the biological models of radiotherapy interruption compensation,such as nominal standard dose,cumulative radiation effect,time-dose fractionation factors,biologically effective dose models,etc.Additionally,the compensatory calculation for radiotherapy interruption in nasopharyngeal carcinoma is taken as an example to provide a reference for the quantitative compensation calculation for radiotherapy interruption in clinic.

Background The serious air pollution of highway toll booths poses a high occupational exposure risk to toll collectors. It is urgent to develop purification methods suitable for airborne particles and microbial pathogens in highway toll booths. Objective To verify the purification effect of low temperature plasma air purifiers on airborne particles and microbes in highway toll booths. Methods Based on controlled-intervention design, we selected three toll booths in an expressway toll station as on-site experimental locations for 6 d (no-intervention period: the low-temperature plasma purifier was turned off in the first three days; intervention period: the purifier was turned on from 9:00 to 17:00 in the following three days). The indoor and outdoor PM_2.5 and PM₁₀ concentrations were continuously monitored during the study. At 9:00, 12:00, and 17:00 of every day during the experiment, indoor and outdoor air samples were collected to analyze the concentration of airborne culturable colonies with a plankton sampler. Airborne particle samples were collected in the outermost exit continuously from 9:00 to 17:00 every day during the experiment using a medium flow particulate sampler, and the species and relative abundance of fungi and bacteria contained in the samples were analyzed by gene sequencing. Independent-sample t test was used to compare the concentration of indoor PM_2.5, PM₁₀, and culturable colonies between the intervention period and the non-intervention period. α diversity analysis, β diversity analysis, and t test were used to compare the diversity and relative abundance of specific species of bacteria and fungi, as well as typical pathogenic bacteria and fungi in the samples between the non-intervention period and the intervention period to reflect the purification effect of low temperature plasma air purifier on airborne PM_2.5, PM₁₀, and microorganisms. Results During the intervention period, the mean indoor concentrations of PM_2.5, PM₁₀, and culturable colonies were lower than those of the no-intervention period (P<0.01 or P<0.001). The ratios of indoor to outdoor concentration (I/O) of PM_2.5 and PM₁₀ during the intervention period were significantly lower than those of the no-intervention period (P<0.001), except the I/O of culturable colonies. Compared with the average concentration at 9:00, the average cleaning rates at 12:00 and 17:00 for PM_2.5 were 49.0% and 46.1%, for PM₁₀ were 49.7% and 45.4%, for airborne culturable colonies were 50.8% and 49.9%, respectively. The β diversity analysis showed that there were significant differences in composition at the level of species of bacteria, and at the levels of genus and species of fungi between the intervention and the no-intervention periods. The relative abundances of 10 species of bacteria such as Lactobacillus and 7 species of fungi such as Torula in the intervention period were significantly lower than those in the non-intervention period, but the relative abundances of fungi such as unclassified_f_cladosporiaceae, trichomerium, and cercospora were higher (P<0.05). For typical pathogenic bacteria, the relative abundances of Lactobacillus and Clostridium_sensu_stricto_1 during the intervention period were 73.5% and 86.9% lower than those in the no-intervention period, and the relative abundance of Talaromyces was 53.5% lower (P<0.05). Conclusion Low temperature plasma air purifier has a good purification effect on indoor PM_2.5, PM₁₀, and culturable colonies in highway toll booths, and likely a limited effect on some fungi.

Prolonged total treatment time due to radiotherapy interruptions is detrimental to local tumor control.There are multiple causes that contribute to the occurrence of interruption events during radiotherapy,including public holidays,machine breakdown and maintenance,and radiotherapy complications.If treatment interruption events are unavoidable during radiotherapy,compensatory approaches should be taken to minimize the effects of radiotherapy interruptions on tumor control.Herein the study provides a summary on the causes and influence of radiotherapy interruptions,the ideas of interruption compensation,and the biological models of radiotherapy interruption compensation,such as nominal standard dose,cumulative radiation effect,time-dose fractionation factors,biologically effective dose models,etc.Additionally,the compensatory calculation for radiotherapy interruption in nasopharyngeal carcinoma is taken as an example to provide a reference for the quantitative compensation calculation for radiotherapy interruption in clinic.

[Abstract] Objective: To investigate the expression of tight junction protein claudin-7 (CLDN-7) in pancreatic cancer and its correlation with the clinicopathological features and prognosis of pancreatic cancer patients. Methods: Oncomine, GEPIA and GEO databases were used to comprehensively analyze the mRNA expression level of CLDN-7 in pancreatic cancer, and Kaplan-Meier Plotter database was used to analyze the relationship between the expression of CLDN-7 and the survival prognosis of pancreatic cancer patients. Immunohistochemical staining was used to detect the protein level of CLDN-7 in 44 cases of pancreatic cancer tissues and 31 cases of para-cancerous tissues resected in the Department of General Surgery of the Second Hospital of Lanzhou University from 2015 to 2018, and the relationship between CLDN-7 expression and clinicopathological characteristics and prognosis of patients was also analyzed. GO (Gene Ontology) analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis were conducted to analyze the possible signaling pathways that CLDN-7 may involve in and their main functions, which were further verified in TCGA and GEPIA databases. Results: Analysis of both the databases and the clinical samples showed that CLDN-7 was significantly over-expressed in pancreatic cancer tissues, and its high expression was correlated with clinical prognosis of pancreatic cancer patients; moreover, CLDN-7 expression was an independent factor affecting the overall survival time of pancreatic cancer patients (all P<0.05). GO analysis and KEGG pathway enrichment analysis confirmed that CLDN-7 was involved in DNA damage repair and glucose metabolism in pancreatic cancer patients. TCGA and GEPIA database validation showed that CLDN-7 expression in pancreatic cancer was significantly and positively correlated with the expression of DNA damage repair related genes (POLD4, SMUG1, NTHL1) and glucose metabolism related genes (ALDOA, TALDO1, PGLS) (all P<0.01). Conclusion: CLDN-7 is highly expressed in pancreatic cancer and indicates a worse clinical prognosis; moreover, CLDN-7 is associated with DNA damage repair and intratumoral glucose metabolism in pancreatic cancer.

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

Abstract: To investigate the influence of acute myocardial infarction(AMI) combined with hypertension on its circadian rhythm. Methods: A total of 1 006 cases of AMI who underwent emergency percutaneous coronary intervention(PCI) surgery were collected continuously, and they were divided into a combined hypertension group and a non-combined hypertension group according to whether it was combined with hypertension. The day was divided into 4 and 12 time periods in units of 6 hours and 2 hours, and the number of cases and differences between the two groups in each time period were compared. Results: After propensity score matching(PSM), the two groups had different onsets in the 4 time periods of 0:00—5:59, 6:00—11:59, 12:00—17:59 and 18:00—23:59(P=0.014,0.045,0.035,0.016). After further subdividing the time into 12 time periods in units of 2 hours, the morning peak of the onset time of the hypertensive group was 10:00—11:59(P=0.004), and there was another peak at 2:00—3:59 in the morning(P=0.002). Multivariate Logistic regression indicated that compared with non-combined hypertension, AMI with hypertension had an increased risk of onset in the morning(6:00—11:59)(OR, 1.440; 95%CI, 1.089-1.904;P=0.011). Conclusion Hypertension affects the circadian rhythm of the onset of AMI and the peak time of onset, and it is a risk factor for the onset of AMI in the morning peak period(6:00—11:59).

Chimeric antigen receptor T (CAR-T) cell has achieved excellent efficacy in hematological tumors, especially for lymphoma. Many products have been approved to market all over the world, and 2 products targeting CD19 have been approved to treat relapsed and refractory large B-cell lymphoma in China. The current experiences of using CAR-T cells come from previous clinical studies. How to use CAR-T cells in a standardized and rationalized way is still a challenge faced by our clinicians. Based on the CAR-T cell treatment experiences from Peking University Cancer Hospital and the latest research progresses in CAR-T in China and abroad, this article will elaborate on patient screening, peripheral blood mononuclear cell collection, bridging treatment, lymphocyte depletion chemotherapy, CAR-T cell infusion, the monitoring and treatment of adverse events after infusion, and long-term follow-up after infusion, in order to guide clinicians to better use CAR-T cell and to bring maximum benefits to patients.

Genome-scale metabolic network models have been successfully applied to guide metabolic engineering. However, the conventional flux balance analysis only considers stoichiometry and reaction direction constraints, and the simulation results cannot accurately describe certain phenomena such as overflow metabolism and diauxie growth on two substrates. Recently, researchers proposed new constraint-based methods to simulate the cellular behavior under different conditions more precisely by introducing new constraints such as limited enzyme content and thermodynamics feasibility. Here we review several enzyme-constrained models, giving a comprehensive introduction on the biological basis and mathematical representation for the enzyme constraint, the optimization function, the impact on the calculated flux distribution and their application in identification of metabolic engineering targets. The main problems in these existing methods and the perspectives on this emerging research field are also discussed. By introducing new constraints, metabolic network models can simulate and predict cellular behavior under various environmental and genetic perturbations more accurately, and thus can provide more reliable guidance to strain engineering.
Enzymes ; metabolism ; Genome ; genetics ; Metabolic Engineering ; Metabolic Networks and Pathways ; genetics ; Models, Biological ; Thermodynamics