Microbial community has an important impact on the whole brewing system and flavor formation during the pit fermentation of soy sauce flavor Baijiu(SFB).However,the spatiotemporal structure and succession of microbial...Microbial community has an important impact on the whole brewing system and flavor formation during the pit fermentation of soy sauce flavor Baijiu(SFB).However,the spatiotemporal structure and succession of microbial communities in the pit fermented grains,as well as the key habitat factors driving microbial community assembly at different spatial locations,are still unclear.In this study,we were the first to comprehensively analyze the similarities and differences in the microbial community structure and succession of pit surface,middle and bottom during the 1-7 rounds of pit fermentation.The fungalα-diversity of pit surface was the lowest,while the bacterialα-diversity was the highest in the pit surface.There were significant spatiotemporal differences in the distribution of dominant microorganisms during different rounds of pit surface,middle and bottom,and the types of dominant bacterial genera in the pit middle and bottom are more diverse than those in the pit surface.Most biomarkers(Streptococcus,Planifolium,etc.)of pit surface showed aerobic characteristics,while most bio-markers(Comamonas,Trichomonascus,etc.)of pit middle and bottom are anaerobic microorganisms.Further-more,the content of titratable acidity,starch and pH were the key driving factors for the assembly of microbial communities in the pit surface,middle and bottom,respectively.The dominant bacterial genera of pit surface,middle and bottom mainly promote microbial growth metabolism,other secondary metabolism and nucleoside metabolism,respectively,leading to differences in the growth enrichment and secondary metabolism of mi-crobial community in the pit fermented grains.This work comprehensively revealed the spatiotemporal differ-ences of microbial community structure and succession,and corresponding environmental driving factors during the 1-7 rounds of pit fermentation of SFB,providing scientific guidance for regulating the microbial community structure and high-level production in the brewing process of SFB.展开更多
Background:Chemotherapy stands as a recommended approach for all stages of pancreatic cancer.However,its efficacy stratification remains obscure.Genomic sequencing is extensively applied across diverse diseases.This s...Background:Chemotherapy stands as a recommended approach for all stages of pancreatic cancer.However,its efficacy stratification remains obscure.Genomic sequencing is extensively applied across diverse diseases.This study aims to explore the potential genomic markers in relation to the decision-making of chemotherapy.Methods:A total of 140 patients with pancreatic cancer were categorized into chemotherapy-first group and adjuvant chemo-therapy group.The genomic alterations were detected from the next-generation sequencing using surgical or fine-needle-biopsy specimens.Chemotherapy response was defined according to objective response based on the RECIST criteria(version 1.1).Results:In the chemotherapy-first group,the patients who harbored higher tumor mutation burden(TMB)levels had significant shorter progress-free survival(PFS)than that with low TMB levels(hazard ratio[HR]=30.362,P=.002).No independent risk factors were found to be correlated with chemoresistance in patients receiving chemotherapy at first(all P>.05).In the adjuvant chemotherapy group,the increased carbohydrate antigen 125(CA125)level of more than 35 U/mL potentially elucidated a shorter period of DFS(HR=3.695,P=.020).Conclusion:Our study indicated that a high level of TMB may predict earlier tumor progression in pancreatic cancer patients received chemotherapy at first.The elevation of CA125 presents itself as a predictive indicator for postoperative chemotherapy patients’tumor recurrence,whereas gene mutations remain unrelated to this phenomenon.展开更多
Multi-modal large language models(MLLMs)have demonstrated impressive performance in vision-language tasks across a wide range of domains.However,the large model scale and associated high computational cost pose signif...Multi-modal large language models(MLLMs)have demonstrated impressive performance in vision-language tasks across a wide range of domains.However,the large model scale and associated high computational cost pose significant challenges for training and deploying MLLMs on consumer-grade GPUs or edge devices,thereby hindering their widespread application.In this work,we introduce Mini-InternVL,a series of MLLMs with parameters ranging from 1 billion to 4 billion,which achieves 90% of the performance with only 5% of the parameters.This significant improvement in efficiency and effectiveness makes our models more accessible and applicable in various real-world scenarios.To further promote the adoption of our models,we are developing a unified adaptation framework for Mini-InternVL,which enables our models to transfer and outperform specialized models in downstream tasks,including autonomous driving,medical image processing,and remote sensing.We believe that our models can provide valuable insights and resources to advance the development of efficient and effective MLLMs.展开更多
基金supported by Guizhou Provincial Science and Technology Projects of China(ZK[2021 general 093]),the Fund of Zunyi Technology and Big data Bureau,Moutai institute Joint Science and Technology Research and Development Project(ZunShiKeHe HZ Zi[2023]108,[2021]305)+1 种基金Research Foundation for Scientific Scholars of Moutai Institute(mygccrc[2022]005)Moutai Institute&Guangzhou YueHui Cosmetics Co.,Ltd.cooperation research and development project(XYNJ20230089).
文摘Microbial community has an important impact on the whole brewing system and flavor formation during the pit fermentation of soy sauce flavor Baijiu(SFB).However,the spatiotemporal structure and succession of microbial communities in the pit fermented grains,as well as the key habitat factors driving microbial community assembly at different spatial locations,are still unclear.In this study,we were the first to comprehensively analyze the similarities and differences in the microbial community structure and succession of pit surface,middle and bottom during the 1-7 rounds of pit fermentation.The fungalα-diversity of pit surface was the lowest,while the bacterialα-diversity was the highest in the pit surface.There were significant spatiotemporal differences in the distribution of dominant microorganisms during different rounds of pit surface,middle and bottom,and the types of dominant bacterial genera in the pit middle and bottom are more diverse than those in the pit surface.Most biomarkers(Streptococcus,Planifolium,etc.)of pit surface showed aerobic characteristics,while most bio-markers(Comamonas,Trichomonascus,etc.)of pit middle and bottom are anaerobic microorganisms.Further-more,the content of titratable acidity,starch and pH were the key driving factors for the assembly of microbial communities in the pit surface,middle and bottom,respectively.The dominant bacterial genera of pit surface,middle and bottom mainly promote microbial growth metabolism,other secondary metabolism and nucleoside metabolism,respectively,leading to differences in the growth enrichment and secondary metabolism of mi-crobial community in the pit fermented grains.This work comprehensively revealed the spatiotemporal differ-ences of microbial community structure and succession,and corresponding environmental driving factors during the 1-7 rounds of pit fermentation of SFB,providing scientific guidance for regulating the microbial community structure and high-level production in the brewing process of SFB.
基金This study was supported by the National Key Research&Development Program(No.2020YFA0804300/2020YFA 0804301)the National Natural Science Foundation of China(Nos.U20A20378 and 82273338)the Joint Program of Science and Education Department of State Administration of Traditional Chinese Medicine and Zhejiang Provincial Administration of Traditional Chinese Medicine(No.GZY-ZJ-KJ-23025).
文摘Background:Chemotherapy stands as a recommended approach for all stages of pancreatic cancer.However,its efficacy stratification remains obscure.Genomic sequencing is extensively applied across diverse diseases.This study aims to explore the potential genomic markers in relation to the decision-making of chemotherapy.Methods:A total of 140 patients with pancreatic cancer were categorized into chemotherapy-first group and adjuvant chemo-therapy group.The genomic alterations were detected from the next-generation sequencing using surgical or fine-needle-biopsy specimens.Chemotherapy response was defined according to objective response based on the RECIST criteria(version 1.1).Results:In the chemotherapy-first group,the patients who harbored higher tumor mutation burden(TMB)levels had significant shorter progress-free survival(PFS)than that with low TMB levels(hazard ratio[HR]=30.362,P=.002).No independent risk factors were found to be correlated with chemoresistance in patients receiving chemotherapy at first(all P>.05).In the adjuvant chemotherapy group,the increased carbohydrate antigen 125(CA125)level of more than 35 U/mL potentially elucidated a shorter period of DFS(HR=3.695,P=.020).Conclusion:Our study indicated that a high level of TMB may predict earlier tumor progression in pancreatic cancer patients received chemotherapy at first.The elevation of CA125 presents itself as a predictive indicator for postoperative chemotherapy patients’tumor recurrence,whereas gene mutations remain unrelated to this phenomenon.
基金supported by the National Key R&D Program of China(Nos.2022ZD0160102 and 2022ZD0161300)the National Natural Science Foundation of China(Nos.62376134 and 62372223).
文摘Multi-modal large language models(MLLMs)have demonstrated impressive performance in vision-language tasks across a wide range of domains.However,the large model scale and associated high computational cost pose significant challenges for training and deploying MLLMs on consumer-grade GPUs or edge devices,thereby hindering their widespread application.In this work,we introduce Mini-InternVL,a series of MLLMs with parameters ranging from 1 billion to 4 billion,which achieves 90% of the performance with only 5% of the parameters.This significant improvement in efficiency and effectiveness makes our models more accessible and applicable in various real-world scenarios.To further promote the adoption of our models,we are developing a unified adaptation framework for Mini-InternVL,which enables our models to transfer and outperform specialized models in downstream tasks,including autonomous driving,medical image processing,and remote sensing.We believe that our models can provide valuable insights and resources to advance the development of efficient and effective MLLMs.
