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Abstract Metal‐organic frameworks (MOFs), renowned for structural diversity and design flexibility, exhibit potential in catalysis. However, the pursuit of higher catalytic activity through defects often compromises stability, requiring a delicate balance. Traditional trial‐and‐error method for optimizing synthesis parameters within the complex chemical space is inefficient. Herein, taking the typical MOF UiO‐66(Ce) as an illustrative example, a closed loop workflow is built, which integrates machine learning (ML)‐assissted prediction, multi‐objective optimization (MOO) and experimental preparation to synergistically optimize the defect content and thermal stability of UiO‐66(Ce) for efficient hydrogenation of dicyclopentadiene (DCPD). An automatic data extraction program ensures data accuracy, establishing a high‐quality database. ML is employed to explore the intricate synthesis‐structure‐property correlations, enabling precise delineation of pure‐phase subspace and accurate predictions of properties. After two iterations, MOO model identifies optimal protocols for high defect content (>40%) and thermal stability (>300°C). The optimized UiO‐66(Ce) exhibits superior catalytic performance in hydrogenation of DCPD, validating the precision and reliability of our methodology. This ML‐assisted approach offers a valuable paradigm for solving the trade‐off riddle in materials field.

ObjectivesThe study aimed to estimate the role of liver fibrosis in the association between occupational physical activity (OPA) and blood pressure (BP), which is modified by lifestyle factors.MethodsThe questionnaire survey and physical examination were completed among 992 construction workers in Wuhan, China. Associations between OPA or lifestyle factors and liver fibrosis indices and blood pressure were assessed using generalized additive models. The mediation analysis was used to evaluate the role of liver fibrosis in the association between OPA and lifestyle factors and BP.ResultsModerate/high OPA group workers had an increased risk of liver fibrosis [odds ratio (OR) = 1.69, 95% confidence intervals (CI): 1.16–2.47, P < 0.05] compared with low OPA group workers. Smoking or drinking alcohol was related to liver fibrosis (aspartate aminotransferase to platelet ratio index: OR = 2.22, 95% CI: 1.07–4.62 or OR = 2.04, 95% CI: 1.00–4.15; P < 0.05). Compared with non-drinkers, drinkers were related to a 2.35-mmHg increase in systolic blood pressure (95% CI: 0.09–4.61), and a 1.60-mmHg increase in diastolic blood pressure (95% CI: 0.08–3.13; P < 0.05). We found a significant pathway, “OPA → liver fibrosis → blood pressure elevation,” and lifestyle factors played a regulatory role in the pathway.ConclusionOPA or lifestyle factors were associated with liver fibrosis indices or BP in construction workers. Furthermore, the association between OPA and BP may be partially mediated by liver fibrosis; lifestyle factors strengthen the relationship between OPA and BP and the mediation role of liver fibrosis in the relationship.

Abstract Background Ralstonia mannitolilytica, a newly emerging opportunistic pathogen worldwide, has been reported to be responsible for human pneumonia, septicemia and meningitis. This is the first report of a case of Ralstonia mannitolilytica sepsis after elective cesarean delivery. Case presentation A 25-year-old woman, gravida 1 para 0, was scheduled for an elective cesarean delivery at 39+ 1 weeks of gestation. Sudden high fever and decreased blood pressure occurred a short time after the operation. Ralstonia mannitolilytica was identified in her blood culture 5 days after the operation. Based on the presence of sepsis and septic shock, massive fluid replacement, blood transfusion, vasoactive agents, imipenem/cilastatin and cefoperazone sulbactam sodium were applied. She was discharged after intensive care without complications. Conclusions Although the incidence of sepsis due to Ralstonia mannitolilytica is relatively low, once infection occurs in a puerpera, severe symptoms develop abruptly. Thus, prompt diagnosis and appropriate treatment are key to the cure.

Intramuscular fat (IMF) is an important regulator that determines meat quality, and its content is closely related to flavor, tenderness, and juiciness. Many studies have used quantitative proteomic analysis to identify proteins associated with meat quality traits in livestock, however, the potential candidate proteins that influence IMF in donkey muscle are not fully understood. In this study, we performed quantitative proteomic analysis, with tandem-mass-tagged (TMT) labeling, with samples from the longissimus dorsi (LD) muscle of the donkey. A total of 585,555 spectra were identified from the six muscle samples used in this study. In total, 20,583 peptides were detected, including 15,279 unique peptides, and 2,540 proteins were identified. We analyzed differentially abundant proteins (DAPs) between LD muscles of donkeys with high (H) and low (L) IMF content. We identified 30 DAPs between the H and L IMF content groups, of which 17 were upregulated and 13 downregulated in the H IMF group. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of these DAPs revealed many GO terms (e.g., bone morphogenetic protein (BMP) receptor binding) and pathways (e.g., Wnt signaling pathway and Hippo signaling pathway) involved in lipid metabolism and adipogenesis. The construction of protein–protein interaction networks identified 16 DAPs involved in these networks. Our data provide a basis for future investigations into candidate proteins involved in IMF deposition and potential new approaches to improve meat quality in the donkey.

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The microbial community structure and diversity of Jiang-flavor Daqu (TS, WS, WM, MH and DJ) from different areas of Maotai town were analyzed by using the third-generation nanopore sequencing platform, and its physicochemical indexes and characteristic flavor substances were measured. The results showed that there were some similarities and differences between Daqu in different areas of Maotai town. In terms of microbial community structure, Bacillus, Saccharopolyspora, Weissella, Staphylococcus and Streptomyces were the common dominant bacterial genera in the five Daqu samples. Among them, Bacillus was the absolute dominant bacteria in MH and DJ. Aspergillus and Penicillium were the common dominant fungal genera, and the proportions of Lichtheimia and Saccharomycopsis in TS, WM and MH were significantly higher than those in DJ and WS. Compared with TS and WM, network correlation analysis showed that MH, DJ and WS had stronger interactions among dominant bacteria. In addition, redundancy analysis (RDA) showed that Weissella was positively correlated with esterification power, liquefaction power, saccharification power, acetic acid, ethyl acetate, ethyl lactate and n-pentanol. Lichtheimia was positively correlated with liquefaction power, saccharification power, acetic acid, isovaleric acid, 2,3-butanediol, phenylacetaldehyde and dibutyl phthalate. Saccharomycopsis was positively correlated with esterification power and ethyl acetate. Bacillus was positively correlated with 2,3,5,6-tetramethylpyrazine, propionic acid, isovaleric acid, dibutyl phthalate, 2,3-butanediol and phenacetaldehyde.