Predicting the number of microorganisms has excellent application in the food industry. It helps in predicting and managing the storage time and food safety. This study aimed to establish a new, simple, and effective model for predicting the number of microorganisms. The dimensional analysis model (DAM) was established based on dimensionless analysis and the Pi theorem. It was then applied to predict the number of in Niuganba (NGB), a traditional Chinese fermented dry-cured beef, which was prepared and stored at 278 K, 283 K, and 288 K. Finally, the internal and external validation of the DAM was performed using six parameters including , , root mean square error (RMSE), standard error of prediction (%SEP), , and . High and and low RMSE and %SEP values indicated that the DAM had high accuracy in predicting the number of microorganisms and the storage time of NGB samples. Both and values were close to 1. The correlation between the observed and predicted numbers of was high. The study showed that the DAM was a simple, unified and effective model to predict the number of microorganisms and storage time.
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http://dx.doi.org/10.3389/fmicb.2022.820539 | DOI Listing |
Glob Health Res Policy
January 2025
Center for Public Health and Epidemic Preparedness and Response, Peking University, Haidian District, 38Th Xueyuan Road, Beijing, 100191, China.
Background: As population aging intensifies, it becomes increasingly important to elucidate the casual relationship between aging and changes in population health. Therefore, our study proposed to develop a systematic attribution framework to comprehensively evaluate the health impacts of population aging.
Methods: We used health-adjusted life expectancy (HALE) to measure quality of life and disability-adjusted life years (DALY) to quantify the burden of disease for the population of Guangzhou.
BMC Psychol
January 2025
Department of kindergarten, Faculty of Education, Taiz University, Taiz, Yemen.
Background: Emotions are a fundamental part of life and play a critical role in shaping individuals' experiences Effectively regulating emotions in socially appropriate ways is essential for navigating life successfully. This study investigated the impact of seven sadness regulation strategies on depression and anxiety and examined the mediating role of ER in the relationship between sadness regulation and depression and anxiety.
Method: A cross-sectional design was employed with 350 participants (144 men, 206 women) aged 18 to 35.
Cancer Cell Int
January 2025
Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510080, China.
Background: Patients with lung adenocarcinoma (LUAD) receiving drug treatment often have an unpredictive response and there is a lack of effective methods to predict treatment outcome for patients. Dendritic cells (DCs) play a significant role in the tumor microenvironment and the DCs-related gene signature may be used to predict treatment outcome. Here, we screened for DC-related genes to construct a prognostic signature to predict prognosis and response to immunotherapy in LUAD patients.
View Article and Find Full Text PDFMol Cancer
January 2025
Department of Medical and Surgical Sciences for Children and Adults, University of Modena and Reggio Emilia, via Campi, 287, Modena, 41125, Italy.
B cells have emerged as central players in the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC). However, although there is clear evidence for their involvement in cancer immunity, scanty data exist on the characterization of B cell phenotypes, bioenergetic profiles and possible interactions with T cells in the context of NSCLC. In this study, using polychromatic flow cytometry, mass cytometry, and spatial transcriptomics we explored the intricate landscape of B cell phenotypes, bioenergetics, and their interaction with T cells in NSCLC.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Department of Pharmacy, Hangzhou Third People's Hospital, Hangzhou Third Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Background: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA. METHODS: In this study, differential gene expression analysis, immune status assessment, weighted correlation network analysis (WGCNA), and functional enrichment analysis were performed to identify shared genes associated with both immunological response and AA.
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