Impact of metabolic disorders on gallstone disease and perioperative recovery after laparoscopic cholecystectomy.

BACKGROUND: Gallstone disease (GSD), nonalcoholic fatty liver disease (NAFLD), metabolic dysfunction-associated fatty liver disease (MAFLD), and metabolic syndrome (MetS) are common medical disorders worldwide. This study aimed to ascertain how NAFLD, MAFLD, MetS, and other factors affect the development of GSD, and how the GSD-associated factors influence patient recovery after laparoscopic cholecystectomy (LC). METHODS: We included 200 patients who were diagnosed with GSD and underwent LC between January 2017 and February 2022. A total of 200 subjects without GSD and "non-calculous causes" during the same period were also included as controls. We compared the metabolic disorder differences between GSD patients and controls. Furthermore, we sub-grouped patients based on the comorbidities of preoperative NAFLD, MAFLD, and MetS, and compared the impacts of these comorbidities on short-term post-LC functional recovery of the patients. RESULTS: The prevalence of NAFLD and MetS were higher in GSD patients (P < 0.05). Based on multivariate logistic regression analysis, hyperglycemia [odds ratio (OR) = 2.2, 95% confidence interval (CI): 1.4-3.4, P = 0.001] and low high-density lipoprotein cholesterol (HDL-C) level (OR = 1.8, 95% CI: 1.1-3.1, P = 0.048) were linked to GSD. NAFLD and MetS linked to liver enzymes after LC (P < 0.05). MetS also linked to the levels of inflammatory indicators after LC (P < 0.05). The obesity, hyperlipidemia, low HDL-C level, and hyperglycemia linked to liver enzymes after LC (P < 0.05). Hyperlipidemia, low HDL-C level, and hypertension linked to inflammation after LC (P < 0.05). CONCLUSIONS: The prevalence of GSD may be linked to NAFLD and MetS. Hyperglycemia and low HDL-C level were independent risk factors of GSD.

Complex impacts of gallstone disease on metabolic syndrome and nonalcoholic fatty liver disease.

Background: Patients with gallstone disease (GSD) often have highly co-occurrence with metabolic syndrome (MetS) and Nonalcoholic fatty liver disease (NAFLD) both associated with insulin resistance (IR). Meanwhile, highly prevalence of NAFLD was found in patients who received cholecystectomy. However, the associations of GSD with MetS, NAFLD is inconsistent in the published literature. And risk of cholecystectomy on NAFLD is unclear. Methods: We searched the Medline EMBASE and WOS databases for literature that met our study topic. To be specific, studies with focus on associations between GSD and MetS/NAFLD, and risk evaluation on cholecystectomy and NAFLD incidence were enrolled for further analysis. The random effect model was used to calculate the combined relative ratio (RR) and odds ratio (OR)and 95% confidence interval (CI). Results: Seven and six papers with focus on connections between GSD and NAFLD/MetS prevalence. Correspondingly, seven papers with focus on risk of cholecystectomy on NAFLD occurrence were also enrolled into meta-analysis. After pooling the results from individual study, patients with GSD had higher risk of MetS (OR:1.45, 95%CI: 1.23-1.67, I2 = 41.1%, P=0.165). Risk of GSD was increased by 52% in NAFLD patients (pooled OR:1.52, 95%CI:1.24-1.80). And about 32% of increment on NAFLD prevalence was observed in patients with GSD (pooled OR: 1.32, 95%CI:1.14-1.50). With regard to individual MetS components, patients with higher systolic blood pressure were more prone to develop GSD, with combined SMD of 0.29 (96%CI: 0.24-0.34, P<0.05). Dose-response analysis found the GSD incidence was significantly associated with increased body mass index (BMI) (pooled OR: 1.02, 95%CI:1.01-1.03) in linear trends. Patients who received cholecystectomy had a higher risk of post-operative NAFLD (OR:2.14, 95%CI: 1.43-2.85), P<0.05). And this impact was amplified in obese patients (OR: 2.51, 95%CI: 1.95-3.06, P<0.05). Conclusion: Our results confirmed that controls on weight and blood pressure might be candidate therapeutic strategy for GSD prevention. And concerns should be raised on de-novo NAFLD after cholecystectomy.

Graft-to-recipient weight ratio exerts nonlinear effects on prognosis by interacting with donor liver macrosteatosis.

Aim: To investigate the interactions between the graft-to-recipient weight ratio (GWRWR) and other risk factors responsible for inferior allograft outcomes. Methods: A total of 362 patients who received liver transplantation (LT) were enrolled. Indicators such as graft/recipient weight and other prognostic factors were collected. Comparisons of indicators and survival analysis were performed in groups categorized by the GWRWR. Interactions of large-for-size grafts (LFSGs) with graft macrosteatosis (MaS) were evaluated in terms of relative excess risk caused by interaction (RERI) and attributable proportion (AP). Cytoscape visualized the role of LFSGs in the risk profile for poor prognosis. Results: Based on the GWRWR, LT cases can be categorized into three subgroups, standard (1%-2.5%), optimal (2.5%-3.0%), and inferior prognosis (>3.0%). Survival analysis confirmed clear separations in cases categorized by the above-defined limits on the GWRWR (P < 0.05). LFSGs caused inferior prognosis by initiating positive interactions with MaS severity. Conclusion: The GWRWR exerted nonlinear effects on prognosis in deceased donor LT cases. LFSGs (GWRWR > 3.0%) caused inferior outcomes, while grafts sized within (2.5%-3.0%) had optimal post-transplant prognosis. MaS increased the risk of poor prognosis by exerting positive synergistic effects on LFSGs.

Progress on SARS-CoV-2 3CLpro Inhibitors: Inspiration from SARS-CoV 3CLpro Peptidomimetics and Small-Molecule Anti-Inflammatory Compounds.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) currently poses a threat to human health. 3C-like proteinase (3CLpro) plays an important role in the viral life cycle. Hence, it is considered an attractive antiviral target protein. Whole-genome sequencing showed that the sequence homology between SARS-CoV-2 3CLpro and SARS-CoV 3CLpro is 96.08%, with high similarity in the substrate-binding region. Thus, assessing peptidomimetic inhibitors of SARS-CoV 3CLpro could accelerate the development of peptidomimetic inhibitors for SARS-CoV-2 3CLpro. Accordingly, we herein discuss progress on SARS-CoV-2 3CLpro peptidomimetic inhibitors. Inflammation plays a major role in the pathophysiological process of COVID-19. Small-molecule compounds targeting 3CLpro with both antiviral and anti-inflammatory effects are also briefly discussed in this paper.

Application of bioreactor technology for cell culture-based viral vaccine production: Present status and future prospects.

Bioreactors are widely used in cell culture-based viral vaccine production, especially during the coronavirus disease 2019 (COVID-19) pandemic. In this context, the development and application of bioreactors can provide more efficient and cost-effective vaccine production to meet the global vaccine demand. The production of viral vaccines is inseparable from the development of upstream biological processes. In particular, exploration at the laboratory-scale is urgently required for further development. Therefore, it is necessary to evaluate the existing upstream biological processes, to enable the selection of pilot-scale conditions for academic and industrial scientists to maximize the yield and quality of vaccine development and production. Reviewing methods for optimizing the upstream process of virus vaccine production, this review discusses the bioreactor concepts, significant parameters and operational strategies related to large-scale amplification of virus. On this basis, a comprehensive analysis and evaluation of the various process optimization methods for the production of various viruses (SARS-CoV-2, Influenza virus, Tropical virus, Enterovirus, Rabies virus) in bioreactors is presented. Meanwhile, the types of viral vaccines are briefly introduced, and the established animal cell lines for vaccine production are described. In addition, it is emphasized that the co-development of bioreactor and computational biology is urgently needed to meet the challenges posed by the differences in upstream production scales between the laboratory and industry.