Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients.

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

The integration of bulk and single-cell sequencing data revealed the function of FKBP10 in the gastric cancer microenvironment.

Background: Due to the implementation of individualized treatment, the majority of gastric cancer patients have a favorable prognosis, but advanced gastric cancer with recurrence and distant metastasis still plagues some patients. As a member of the FK506-binding protein (FKBP65) family, there is growing evidence that FKBP10 plays a crucial role in tumorigenesis. However, the role of FKBP10 in the tumor microenvironment (TME) has been a prominent issue. Methods: The FKBP10 knockdown efficiency in gastric cancer cells was determined by quantitative real-time polymerase chain reaction (qRT-PCR). Wound healing and transwell analysis were performed to detect variations in cell invasion and migration. We integrated single-cell and bulk sequencing data to further elaborate the impact of FKBP10 and FKBP10-coexpressed genes (FCGs) in the TME via a variety of bioinformatics approaches. Results: Here, we found that FKBP10 knockdown inhibited cell invasion and metastasis. FKBP10 was chiefly expressed in inflammatory cancer-associated fibroblasts (iCAFs), and FCGs principally mediated alterations in extracellular matrix (ECM) organization. Besides, according to nine prognosis-related FCGs, two disparate clusters were identified, and differences in tumor immune infiltration characteristics and immunotherapy response between different clusters were investigated. Conclusions: Our study provides insights into the expression and function of FKBP10 in the microenvironment of gastric cancer.

Metagenome reveals the possible mechanism that microbial strains promote methanogenesis during anaerobic digestion of food waste.

For better understanding the mechanism of microbial strains promoting methane production, four strains Hungatella xylanolytica A5, Bacillus licheniformis B1, Paraclostridium benzoelyticum C2 and Advenella faeciporci E1 were inoculated into anaerobic digestion systems. After bioaugmentation, the cumulative methane production of A5, B1, C2 and E1 groups elevated by 11.68%, 8.20%, 18.21% and 15.67% compared to CK group, respectively. The metagenomic analysis revealed that the species diversity and uniformity of the experimental groups was improved, and hydrolytic acidifying bacteria, represented by Clostridiaceae, Anaerolineaceae and Oscillospiraceae, and methanogens, such as Methanotrichaceae and Methanobacteriaceae, were enriched. Meanwhile, the abundance of key genes in carbohydrate, pyruvate and methane metabolism was increased in the inoculated groups, providing reasonable reasons for more methane production. The strengthening mechanism of microbial strains in this study offered a theoretical foundation for selecting a suitable bioaugmentation strategy to solve the problems of slow start-up and low methane production in anaerobic digestion.

Rational Design of an α-1,3-Fucosyltransferase for the Biosynthesis of 3-Fucosyllactose in Bacillus subtilis ATCC 6051a via De Novo GDP-l-Fucose Pathway.

3-Fucosyllactose (3-FL) is an important oligosaccharide and nutrient in breast milk that can be synthesized in microbial cells by α-1,3-fucosyltransferase (α-1,3-FucT) using guanosine 5'-diphosphate (GDP)-l-fucose and lactose as substrates. However, the catalytic efficiency of known α-1,3-FucTs from various sources was limited due to their low solubility. To enhance the microbial production of 3-FL, the efficiencies of α-1,3-FucTs were evaluated and in Bacillus subtilis (B. subtilis) chassis cells that had been endowed with a heterologous synthetic pathway for GDP-l-fucose, revealing that the activity of FucTa from Helicobacter pylori (H. pylori) was higher than that of any of other reported homologues. To further improve the catalytic performance of FucTa, a rational design approach was employed, involving intracellular evaluation of the mutational sites of M32 obtained through directed evolution, analysis of the ligand binding site diversity, and protein structure simulation. Among the obtained variants, the FucTa-Y218 K variant exhibited the highest 3-FL yield, reaching 7.55 g/L in the shake flask growth experiment, which was 3.48-fold higher than that achieved by the wild-type enzyme. Subsequent fermentation optimization in a 5 L bioreactor resulted in a remarkable 3-FL production of 36.98 g/L, highlighting the great prospects of the designed enzyme and the strains for industrial applications.

Unveiling the potential of novel recyclable deep eutectic solvent pretreatment: Effective separation of lignin from poplar hydrolyzed residue.

To effectively convert the fermentable sugars present in lignocellulosic biomass into biofuels and additional value-added products, it is crucial to remove lignin from the biomass. With the intention of expeditiously remove lignin from poplar wood and improve cellulose saccharification, an innovative ternary deep eutectic solvent (DES) benzyl triethyl ammonium chloride-ethylene glycol-FeCl3 (T-EG-F) was studied for the pretreatment of poplar hydrolyzed residue (PHR). The results revealed that following T-EG-F DES pretreatment at 130 °C for 4 h, the lignin removal rate reached 91.88 %. The effect of DES on PHR and regenerated lignin was comprehensively investigated using X-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), Thermogravimetric (TG) and other characterization methods, providing valuable insights into the mechanism of this innovative biomass pretreatment. Moreover, there was a significant improvement in the enzyme digestibility of the DES pretreatment residue. At 48 h, the enzyme load of 30 FPU/g cellulose achieved a remarkable enzyme digestibility of 97.31 %, and this value exhibited a notable increase of 6.56 times compared to the untreated poplar sample. In addition, the T-EG-F could be recycled and reused. This study demonstrates that the potential of T-EG-F DES pretreatment as a green and efficient method for lignin dissociation from lignocellulosic biomass, offering a promising approach for biomass component separation.

Evaluating the potential of different bioaugmented strains to enhance methane production during thermophilic anaerobic digestion of food waste.

Bioaugmentation technology for improving the performance of thermophilic anaerobic digestion (TAD) of food waste (FW) treatment is gaining more attention. In this study, four thermophilic strains (Ureibacillus suwonensis E11, Clostridium thermopalmarium HK1, Bacillus thermoamylovorans Y25 and Caldibacillus thermoamylovorans QK5) were inoculated in the TAD of FW system, and the biochemical methane potential (BMP) batch study was conducted to assess the potential of different bioaugmented strains to enhance methane production. The results showed that the cumulative methane production in groups inoculated with E11, HK1, Y25 and QK5 improved by 2.05%, 14.54%, 19.79% and 9.17%, respectively, compared with the control group with no inoculation. Moreover, microbial community composition analysis indicated that the relative abundance of the main hydrolytic bacteria and/or methanogenic archaea was increased after bioaugmentation, and the four strains successfully became representative bacterial biomarkers in each group. The four strains enhanced methane production by strengthening starch, sucrose, galactose, pyruvate and methane metabolism functions. Further, the correlation networks demonstrated that the representative bacterial genera had positive correlations with the differential metabolic functions in each bioaugmentation group. This study provides new insights into the TAD of FW with bioaugmented strains.

Improvement of polyhydroxybutyrate production by deletion of csrA in Escherichia coli

BACKGROUND: Poly-3-hydroxybutyrate (PHB) can be efficiently produced in recombinant Escherichia coli by the overexpression of an operon (NphaCAB) encoding PHB synthetase. Strain improvement is considered to be one of critical factors to lower the production cost of PHB in recombinant system. In this study, one of key regulators that affect the cell growth and PHB content was confirmed and analyzed. RESULT: S17-3, a mutant E. coli strain derived from S17-1, was found to be able to achieve high cell density when expressing NphaCAB with the plasmid pBhya-CAB. Whole genome sequencing of S17-3 revealed genetic alternations on the upstream regions of csrA, encoding a global regulator cross-talking between stress response, catabolite repression and other metabolic activities. Deletion of csrA or expression of mutant csrA resulted in improved cell density and PHB content. CONCLUSION: The impact of gene deletion of csrA was determined, dysfunction of the regulators improved the cell density of recombinant E. coli and PHB production, however, the detail mechanism needs to be further clarified.