Predicting the effect of chemicals on fruit using graph neural networks.

The neural network method is a type of machine learning that has made significant advances over the past few years in a variety of fields, particularly text, speech, images, videos, etc. In areas where data is unstructured, traditional machine learning has not been able to surpass the 'glass ceiling'; therefore, researchers have turned to neural networks as auxiliary tools to achieve significant breakthroughs or develop new research methods. An array of computational chemistry challenges can be addressed using neural networks, including virtual screening, quantitative structure-activity relationships, protein structure prediction, materials design, quantum chemistry, and property prediction, among others. This paper proposes a strategy for predicting the chemical properties of fruits by using graph neural networks, and it aims to provide some guidance to researchers and streamline the identification process.

Protein-centric omics analysis reveals circulating complements linked to non-viral liver diseases as potential therapeutic targets.

BACKGROUND/AIMS: To evaluate the causal correlation between complement components and non-viral liver diseases and their potential use as druggable targets. METHODS: We conducted Mendelian randomization (MR) to assess the causal role of circulating complements in the risk of non-viral liver diseases. A complement-centric protein interaction network was constructed to explore biological functions and identify potential therapeutic options. RESULTS: In the MR analysis, genetically predicted levels of complement C1q C chain (C1QC) were positively associated with the risk of autoimmune hepatitis (odds ratio 1.125, 95% confidence interval 1.018-1.244), while complement factor H-related protein 5 (CFHR5) was positively associated with the risk of primary sclerosing cholangitis (PSC;1.193, 1.048- 1.357). On the other hand, CFHR1 (0.621, 0.497-0.776) and CFHR2 (0.824, 0.703-0.965) were inversely associated with the risk of alcohol-related cirrhosis. There were also significant inverse associations between C8 gamma chain (C8G) and PSC (0.832, 0.707-0.979), as well as the risk of metabolic dysfunction-associated steatotic liver disease (1.167, 1.036-1.314). Additionally, C1S (0.111, 0.018-0.672), C7 (1.631, 1.190-2.236), and CFHR2 (1.279, 1.059-1.546) were significantly associated with the risk of hepatocellular carcinoma. Proteins from the complement regulatory networks and various liver diseaserelated proteins share common biological processes. Furthermore, potential therapeutic drugs for various liver diseases were identified through drug repurposing based on the complement regulatory network. CONCLUSION: Our study suggests that certain complement components, including C1S, C1QC, CFHR1, CFHR2, CFHR5, C7, and C8G, might play a role in non-viral liver diseases and could be potential targets for drug development.

The classification of obesity based on metabolic status redefines the readmission of non-Hodgkin's lymphoma-an observational study.

BACKGROUND: The relationship between obesity and non-Hodgkin's lymphoma (NHL) was controversial, which may be due to the crudeness definition of obesity based on body mass index (BMI). As obesity and metabolic abnormalities often coexist, we aimed to explore whether the classification of obesity based on metabolic status can help to evaluate the real impact of obesity on the readmission of NHL. METHODS: In this retrospective cohort study, utilizing the 2018 Nationwide Readmissions Database, we identified NHL-related index hospitalizations and followed them for non-elective readmission. The patients with NHL were classified as metabolically healthy non-obese (MHNO) and obese (MHO) and metabolically unhealthy non-obese (MUNO) and obese (MUO). Readmission rates for each phenotype were calculated at 30-day intervals. Multiple COX regression was used to analyze the association of metabolic-defined obesity with 30-day, 90-day, and 180-day readmission rates in patients with NHL. RESULTS: There were 22,086 index hospitalizations with NHL included. In the multivariate COX regression, MUNO was associated with increased 30-day (HR = 1.113, 95% CI 1.036-1.195), 90-day (HR = 1.148, 95% CI 1.087-1.213), and 180-day readmission rates (HR = 1.132, 95% CI 1.077-1.189), and MUO was associated with increased 30-day (HR=1.219, 95% CI: 1.081-1.374), 90-day (HR = 1.228, 95% CI 1.118-1.348), and 180-day readmission rates (HR = 1.223, 95% CI 1.124-1.33), while MHO had no associations with readmission rates. CONCLUSIONS: The presence of metabolic abnormalities with or without obesity increased the risk of non-selective readmission in patients with NHL. However, obesity alone had no associations with the risk of non-selective readmission, suggesting that interventions for metabolic abnormalities may be more important in reducing readmissions of NHL patients.

Association between the peripheral neutrophil-to-lymphocyte ratio and metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes.

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes frequently co-occur, imposing a tremendous medical burden. A convenient and effective MASLD indicator will be beneficial to the early diagnosis of disease. In the clinical laboratory, the neutrophil-to-lymphocyte ratio (NLR) is a readily accessible hematological marker. This study designed to determine the relation between the NLR and MASLD in type 2 diabetes patients. Methods: Data from 1,151 type 2 diabetes inpatients without infections, malignancy or hematological diseases who were recruited from 2016 through 2022 were analyzed in the retrospective study. The patients were stratified into NLR tertiles (total population: high NLR level > 2.18; middle NLR level: 1.58-2.18; low NLR level < 1.58), with additional subgroup stratification by sex (men: high NLR level > 2.21; middle NLR level: 1.60-2.21; and low NLR level < 1.60; women: high NLR level > 2.12; middle NLR level: 1.53-2.12; and low NLR level < 1.53). After adjusting for confounders (age, sex, weight, Glu, ALT and TG) associated with MASLD, the odds ratio (OR) and the corresponding 95% confidence interval (CI) of the NLR were obtained by using a binary logistic regression analysis to verify the correlation between the NLR and MASLD. Results: Compared to non-MASLD patients, MASLD patients had higher weight, blood glucose, insulin and C-peptide, worse liver function (higher ALT and GGT), lower HDL (all p < 0.05), and lower NLR (p < 0.001). The prevalence of MASLD was 43.75% (high NLR level), 55.21% (middle NLR level) and 52.22% (low NLR level) (p < 0.05). Compared to those of the high NLR level, the adjusted ORs and 95% CIs of the middle and low NLR levels were 1.624 (95% CI: 1.141-2.311) and 1.456 (95% CI: 1.025-2.068), for all subjects, while they were 1.640 (95% CI: 1.000-2.689) and 1.685 (95% CI: 1.026-2.766), for men. Conclusion: A low NLR is associated with a greater risk of MASLD.

Association of obesity and different metabolic status with prognosis in patients with bladder cancer: a retrospective cohort study.

Background and objectives: Patients with bladder cancer (BC) are at high risk for recurrence rates and readmission costs. However, the evidence about obesity and metabolic abnormalities on the BC prognosis was inconsistent. Our primary aim was to determine the impact of obesity and different metabolic status on the readmission risk in patients with BC. Design and methods: We identified 16,649 patients with BC using the 2018 Nationwide Readmissions Database who were hospitalized from January to June 2018 and followed for 180 days. The primary outcome was 180-day readmission. The multivariate Cox regression analysis and ordered logistic regression were performed to analyze data. Results: Obesity and metabolic abnormalities were associated with an increased readmission risk in patients with BC [obesity: adjusted hazard ratio (aHR) = 1.08, 95% confidence interval (CI): 1.01-1.16; hyperglycemia: aHR = 1.11, 95% CI: 1.05-1.17; hypertension: aHR = 1.09, 95% CI: 1.03-1.15]. Compared with non-obese and no metabolic abnormalities, the risk of readmission was significantly increased in patients with metabolic abnormalities, irrespective of obesity (non-obese and metabolic abnormalities: aHR = 1.07, 95% CI: 1.02-1.13; obese and metabolic abnormalities: aHR = 1.20, 95% CI: 1.10-1.31), but not in obese and no metabolic abnormalities. These associations were consistent in patients aged 60 years or older and the surgery group. Moreover, hyperglycemia, hypertension, and a graded increment of metabolic risk were associated with an increased readmission risk. We also found increased length of stay for readmission in patients with obesity and metabolic abnormalities (aOR = 1.17, 95% CI: 1.00-1.36). Conclusion: Obesity with metabolic abnormalities and metabolic abnormalities alone were associated with higher readmission risks in patients with BC. It is suggested that prevention should focus not only on obesity but also on metabolic abnormalities to decrease the risk of readmission.

The Fatty Liver Index, the Strongest Risk Factor for Low Testosterone Level.

INTRODUCTION: The study aimed to determine if hepatic steatosis assessed by fatty liver index (FLI) was an independent risk factor for male low testosterone level and whether the FLI was the strongest risk factor for low testosterone level in two different age groups. METHODS: Two cross-sectional studies were performed. A total of 3,443 male participants (aged 46-75) were recruited into study A (part of lONgitudinal study (REACTION)). Then a total of 267 male participants (aged 25-45) were recruited into study B. Serum total testosterone (TT) and sex hormone-binding globulin (SHBG) levels, indicators for assessing hepatic steatosis were measured. The Pearson correlation and regression analysis were performed to investigate the risk factors for low testosterone level. RESULTS: The FLI had the strongest negative correlation with serum testosterone in the study A (r = -0.436) and B (r = -0.542). Compared with patients with a FLI lower than 30, the risk for low testosterone level increased by 3.48-fold in subjects with a FLI higher than 60 adjusted for potential risk factors in study A. In study B, the odds ratio of low testosterone level in patients with potential hepatic steatosis was 4.26 (1.57-11.60) after adjusted for age and homeostasis model assessment of insulin resistance (HOMA-IR) and 0.59 (0.14-2.60) after adjusted for age, HOMA-IR, waist circumference, body mass index, and SHBG. CONCLUSIONS: FLI was the strongest risk factor for male low testosterone level independent of insulin resistance in male populations of different ages; however, the association can be modulated by SHBG levels in the young. SIGNIFICANCE STATEMENT: In the study, FLI was the strongest negative risk factor for low testosterone level in the Chinese adult male population. The results suggested that hepatic steatosis assessed by the FLI was the main risk factor for male low testosterone level, independent of age, insulin resistance, smoking, and drinking status; however, the association of FLI and TT levels can be modulated by SHBG levels. Taken together these findings indicate that clinical physicians should pay more attention to the FLI index and hepatic steatosis, so that they can take advantage of them for assessing the risk of developing of low testosterone level in the male population.

Association of Obesity Based on Different Metabolic Status with Risk of Gout Occurrence in Patients: A National Study.

BACKGROUND: Obesity often co-exists with metabolic abnormalities, but the results of studies on the relationship between obesity, metabolic abnormalities and the risk of gout are inconsistent. OBJECTIVE: We aimed to study whether there was a mutual regulation between obesity, metabolic abnormalities and the risk of gout. METHOD: We conducted a cross-sectional study to expound the association between obesity based on different metabolic statuses and the risk of gout. Patients were derived from Nationwide Readmission Database (2018 sample). RESULTS: A total of 9,668,330 records were recruited for analysis from January to December. The risk of gout in the obesity group, metabolic abnormalities group and obesity combined with metabolic abnormalities group was 1.67 times (OR=1.67, 95%CI 1.64-1.70), 3.12 times (OR=3.12, 95%CI 3.09-3.15) and 4.27 times (OR=4.27, 95%CI 4.22-4.32) higher than that in the normal control group. For different metabolic components, OR value was highest in hypertension group (OR=2.65, 95%CI 2.60-2.70 and OR=4.85, 95%CI 4.73-4.97), followed by dyslipidemia group (OR=2.23, 95%CI 2.16-2.30 and OR=3.74, 95%CI 3.55-3.95) and in hyperglycemia group (OR=1.73, 95%CI 1.66-1.80 and OR=2.94, 95%CI 2.78-3.11). Fewer components of metabolic syndrome were associated with a lower risk of gout in both nonobese and obese patients. CONCLUSION: When metabolic abnormalities were present, obesity induced a higher risk of gout. Different components of metabolic abnormalities had different effects on the risk of gout occurrence, and the number of metabolic abnormalities was closely related to the risk of gout occurrence. Follow-up and intervention methods targeting obesity and metabolic abnormalities should be considered for patients with gout.

Associations between eating speed and food temperature and type 2 diabetes mellitus: a cross-sectional study.

Objective: This study aimed to evaluate the relationship between eating speed and food temperature and type 2 diabetes mellitus (T2DM) in the Chinese population. Methods: A cross-sectional survey was conducted between December 2020 to March 2022 from the department of Endocrinology at the Shandong Provincial Hospital. All recruited participants were asked to complete structured questionnaires on their eating behaviors at the time of recruitment. Clinical demographic data such as gender, age, height, weight, familial history of T2DM, prevalence of T2DM and various eating behaviors were collected. Univariate and multivariate logistic regression analyses were used to analyze the associations between eating behaviors and T2DM. Results: A total of 1,040 Chinese adults were included in the study, including 344 people with T2DM and 696 people without T2DM. Multivariate logistic regression analysis of the general population showed that gender (OR = 2.255, 95% CI: 1.559-3.260, p < 0.001), age (OR = 1.091, 95% CI: 1.075-1.107, p < 0.001), BMI (OR = 1.238, 95% CI: 1.034-1.483, p = 0.020), familial history of T2DM (OR = 5.709, 95% CI: 3.963-8.224, p < 0.001), consumption of hot food (OR = 4.132, 95% CI: 2.899-5.888, p < 0.001), consumption of snacks (OR = 1.745, 95% CI: 1.222-2.492, p = 0.002), and eating speed (OR = 1.292, 95% CI:1.048-1.591, p = 0.016) were risk factors for T2DM. Conclusion: In addition to traditional risk factors such as gender, age, BMI, familial history of T2DM, eating behaviors associated with Chinese culture, including consumption of hot food, consumption of snacks, and fast eating have shown to be probable risk factors for T2DM.

Evaluating the Impact of Obesity and Different Metabolic Statuses on the Prognosis of Hospitalized Patients with Inflammatory Bowel Disease: A Cohort Study.

INTRODUCTION: Obesity is associated with an increased risk of inflammatory bowel disease (IBD), whereas not all obese individuals have the same effect. In individuals with obesity, the role of metabolic status in the readmission of IBD remains unclear. Our study aimed to evaluate the association between different obesity metabolic phenotypes and the prognosis of IBD patients. METHODS: We conducted a longitudinal cohort study using Nationwide Readmissions Database (NRD) (2018 sample). Out of 12,928,231 discharge records, 63,748 records with a discharge diagnosis of IBD were identified for analysis. Cox proportional hazard ratio (HR) with 95% confidence interval (CI) was calculated, adjusting for potential confounders. RESULTS: During a 180-day follow-up in IBD patients with different obesity metabolic phenotypes, all-cause readmission rate, inpatient mortality rate, unplanned readmission rate, total charge, hospitalized length of stay were statistically different (all p < 0.001). After multivariate Cox regression analysis, IBD patients with metabolically unhealthy nonobese (MUNO) had higher risk of readmission (all-cause and unplanned) (HR 1.04, 95% CI: 1.00-1.08 and HR 1.06, 95% CI: 1.02-1.10), and those with metabolically unhealthy obesity (MUO) had higher risk of unplanned readmission (HR 1.08, 95% CI: 1.02-1.15). In subgroup analysis, both the MUNO group and MUO group had higher risk of readmission (all-cause and unplanned) in the ulcerative colitis (UC) subgroup, but only the MUNO group had higher risk of readmission (all-cause and unplanned) (HR 1.05, 95% CI: 1.00-1.10 and HR 1.06, 95% CI: 1.01-1.12) in the Crohn's disease (CD) subgroup. CONCLUSION: Metabolic abnormalities were associated with an increased risk of readmission in patients with IBD, regardless of obesity.

Determining resuscitation threshold for extremely preterm infants based on the survival rates without severe neurological injury.

Background: Published guidelines on decision-making and resuscitation of extremely preterm infants primarily focus on high-income countries. For rapidly industrializing ones like China, there is a lack of population-based data for informing prenatal management and practice guidelines. Methods: The Sino-northern Neonatal Network conducted a prospective multi-centre cohort study between 1 January 2018 and 31 December 2021. Infants with a gestational age (GA) between 22 (postnatal age in days = 0) and 28 (postnatal age in days = 6) admitted to 40 tertiary NICUs in northern China were included and evaluated for death or severe neurological injury before discharge. Results: For all extremely preterm infants (n = 5838), the proportion of admission to the neonatal was 4.1% at 22-24 weeks, 27.2% at 25-26 weeks, and 75.2% at 27 and 28 weeks. Among 2228 infants admitted to the NICU, 216 (11.1%) were still elected for withdrawal of care (WIC) due to non-medical factors. Survival rates without severe neurological injury were 6.7% for infants at 22-23 weeks, 28.0% at 24 weeks, 56.7% at 24 weeks, 61.7% at 25 weeks, 79.9% at 26 weeks, and 84.5% at 27 and 28 weeks. Compared with traditional criterion at 28 weeks, the relative risk for death or severe neurological injury were 1.53 (95% confidence interval (CI) = 1.26-1.86) at 27 weeks, 2.32 (95% CI = 1.73-3.11) at 26 weeks, 3.62 (95% CI = 2.43-5.40) at 25 weeks, and 8.91 (95% CI = 4.69-16.96) at 24 weeks. The NICUs with higher proportion of WIC also had a higher rate of death or severe neurological injury after maximal intensive care (MIC). Conclusions: Compared to the traditional threshold of 28 weeks, more infants received MIC after 25 weeks, leading to significant increases in survival rates without severe neurological injury. Therefore, the resuscitation threshold should be gradually adjusted from 28 to 25 weeks based on reliable capacity. Registration: China Clinical Trials Registry. ID: ChiCTR1900025234.

Association of obesity under different metabolic status with adverse outcomes in patients with chronic myeloid leukemia: A retrospective cohort study.

BACKGROUND: Little is known about the association between abnormal metabolic obesity states and the outcomes of chronic myeloid leukemia (CML), especially in patients with obesity with different metabolic status. Here, we used the Nationwide Readmissions Database to assess the effects of metabolically defined obesity on adverse outcomes of CML. METHODS: Of the 35 460 557 (weighted) patients, we included 7931 adults with discharge diagnoses of CML from January 1, 2018 to June 30, 2018. The study population was observed until December 31, 2018 and divided into four groups based on body mass index and metabolic status. The primary outcome was the adverse outcomes of CML, including nonremission (NR)/relapse and severe mortality risk. Multivariate logistic regression analysis was performed to analyze data. RESULTS: Metabolically unhealthy normal weight and metabolically unhealthy obesity were all risk factors for adverse outcomes of CML compared with metabolically healthy normal weight (all p < 0.01), and a significant difference was not found in the metabolically healthy obese. Female patients with metabolically unhealthy normal weight and metabolically unhealthy obesity had 1.23-fold and 1.40-fold increased NR/relapse risk, while male patients did not have this risk. Moreover, patients with a higher number of metabolic risk factors or with dyslipidemia were at higher risk of adverse outcomes, regardless of obesity status. CONCLUSIONS: Metabolic abnormalities were associated with adverse outcomes in patients with CML, irrespective of obesity status. Future treatment of patients with CML should consider the effects of obesity on their adverse outcomes under different metabolic status, especially in female patients.

A clinical observation study on the effect of needle-free insulin syringe on blood glucose control and well-being index in patients with early-onset type 2 diabetes mellitus.

Objective: To explore the effect of using needle-free insulin syringe on blood sugar control and well-being index in patients with early-onset type 2 diabetes mellitus. Methods: A total of 42 patients with early-onset type 2 diabetes mellitus treated with insulin aspart 30 injection in a stable condition in the Endocrinology Department of a tertiary hospital from January 2020 to July 2021 were randomly divided into two groups, one group received insulin pen injections followed by needle-free injections, and the other group received needle-free injections followed by insulin pen injections. Transient scanning glucose monitoring was performed during the last two weeks of each injection modality phase. Comparison of the two injection methods in terms of test indicators and differences in injection site pain scores, the number of red spots on the skin at the injection site and the number of bleeding spots on the skin at the injection site. Results: The FBG of the needle-free injection group was lower than that of the Novo Pen group (p<0.05); the 2-hour postprandial blood glucose of the needle-free injection group was lower than that of the Novo Pen group, but there was no statistical significant difference. The amount of Insulin in the needle-free injector group was lower than that in the Novo pen group, but there was no statistical significant difference between the two groups. The WHO-5 score of the needle-free injector group was higher than that of the Novo Pen group(p<0.05); the pain score at the injection site was lower than that of the Novo Pen group (p<0.05). The number of skin red spots using the needle-free syringe was more than that of the Novo pen group(p<0.05); the number of skin bleeding at the site of injection was similar between the two injection methods. Conclusion: Compared to traditional insulin pens, subcutaneous injection of premixed insulin using a needle-free syringe is effective in controlling fasting blood glucose in patients with early onset type 2 diabetes and is less painful at the injection site. In addition, blood glucose monitoring should be strengthened and insulin dosage should be adjusted in a timely manner.

Association between metabolic obesity phenotypes and multiple myeloma hospitalization burden: A national retrospective study.

Background & purpose: Obesity and metabolic disorders were associated with increased risk of MM, a disease characterized by high risk of relapsing and require frequent hospitalizations. In this study, we conducted a retrospective cohort study to explore the association of metabolic obesity phenotypes with the readmission risk of MM. Patients & methods: We analyzed 34,852 patients diagnosed with MM from the Nationwide Readmissions Database (NRD), a nationally representative database from US. Hospitalization diagnosis of patients were obtained using ICD-10 diagnosis codes. According to obesity and metabolic status, the population was divided into four phenotypes: metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). The patients with different phenotypes were observed for hospital readmission at days 30-day, 60-day, 90-day and 180-day. Multivariate cox regression model was used to estimate the relationship between obesity metabolic phenotypes and readmissions risk. Results: There were 5,400 (15.5%), 7,255 (22.4%), 8,025 (27.0%) and 7,839 (35.6%) unplanned readmissions within 30-day, 60-day, 90-day and 180-day follow-up, respectively. For 90-day and 180-day follow-up, compared with patients with the MHNO phenotype, those with metabolic unhealthy phenotypes MUNO (90-day: P = 0.004; 180-day: P = < 0.001) and MUO (90-day: P = 0.049; 180-day: P = 0.004) showed higher risk of readmission, while patients with only obesity phenotypes MHO (90-day: P = 0.170; 180-day: P = 0.090) experienced no higher risk. However, similar associations were not observed for 30-day and 60-day. Further analysis in 90-day follow-up revealed that, readmission risk elevated with the increase of the combined factor numbers, with aHR of 1.068 (CI: 1.002-1.137, P = 0.043, with one metabolic risk factor), 1.109 (CI: 1.038-1.184, P = 0.002, with two metabolic risk factors) and 1.125 (95% CI: 1.04-1.216, P = 0.003, with three metabolic risk factors), respectively. Conclusion: Metabolic disorders, rather than obesity, were independently associated with higher readmission risk in patients with MM, whereas the risk elevated with the increase of the number of combined metabolic factors. However, the effect of metabolic disorders on MM readmission seems to be time-dependent. For MM patient combined with metabolic disorders, more attention should be paid to advance directives to reduce readmission rate and hospitalization burden.

The effects of obesity and metabolic abnormalities on severe COVID-19-related outcomes after vaccination: A population-based study.

Breakthrough SARS-CoV-2 infections of vaccinated individuals are being reported globally, resulting in an increased risk of hospitalization and death among such patients. Therefore, it is crucial to identify the modifiable risk factors that may affect the protective efficacy of vaccine use against the development of severe COVID-19 and thus to initiate early medical interventions. Here, in population-based studies using the UK Biobank database and the 2021 National Health Interview Survey (NHIS), we analyzed 20,362 participants aged 50 years or older and 2,588 aged 18 years or older from both databases who tested positive for SARS-COV-2, of whom 33.1% and 67.7% received one or more doses of vaccine, respectively. In the UK Biobank, participants are followed from the vaccination date until October 18, 2021. We found that obesity and metabolic abnormalities (namely, hyperglycemia, hyperlipidemia, and hypertension) were modifiable factors for severe COVID-19 in vaccinated patients (all p < 0.05). When metabolic abnormalities were present, regardless of obesity, the risk of severe COVID-19 was higher than that of metabolically normal individuals (all p < 0.05). Moreover, pharmacological interventions targeting such abnormalities (namely, antihypertensive [adjusted hazard ratio (aHR) 0.64, 95% CI 0.48-0.86; p = 0.003], glucose-lowering [aHR 0.55, 95% CI 0.36-0.83; p = 0.004], and lipid-lowering treatments [aHR 0.50, 95% CI 0.37-0.68; p < 0.001]) were significantly associated with a reduced risk for this outcome. These results show that more proactive health management of patients with obesity and metabolic abnormalities is critical to reduce the incidence of severe COVID-19 after vaccination.

Changes in Clinical Manifestations Due to AFLD Retyping Based on the New MAFLD Criteria: An Observational Study Based on the National Inpatient Sample Database.

(1) Background: As the introduction of "positive" diagnostic criteria for metabolic dysfunction-associated fatty liver disease (MAFLD) does not exclude alcohol consumption, some patients originally diagnosed with alcoholic fatty liver disease (AFLD) may be diagnosed with dual- etiology fatty liver disease (AFLD&MAFLD), which requires us to urgently explore the impact of the changes in this classification of AFLD on clinical manifestations. (2) Methods: Utilizing data from the Nationwide Inpatient Sample database 2016-2018, a total of 9269 participants with AFLD were selected. With the definition of MAFLD, these patients were further categorized into two groups: single AFLD and AFLD&MAFLD. The primary outcome was the risk of comorbidities and organ failures. The secondary outcomes were the length of stay, total charges, and in-hospital all-cause mortality. (3) Results: The patients with AFLD&MAFLD were older, were predominantly male, and had more comorbidities and organ failures compared to the patients with AFLD. These comorbidities included coronary atherosclerosis, myocardial infarction, cerebrovascular disease, arrhythmia, asthma, chronic obstructive pulmonary disease, and chronic kidney disease (all p values < 0.05). The patients with AFLD&MAFLD were more likely to develop acute and chronic heart and/or kidney failures than those with single AFLD (all p < 0.05). The length of stay and total charges of the patients in the AFLD&MAFLD group were greater than the single AFLD group (p = 0.029 and p < 0.001, respectively). No significant difference in all-cause mortality was observed. (4) Conclusions: The patients with AFLD&MAFLD have more comorbidities and organ failures, longer hospital stays, and higher hospitalization costs than the patients with single AFLD. Hence, patients with dual-etiology fatty liver disease deserve more attention from clinical staff during treatment.

Association between Metabolic Obesity Phenotypes and the Burden of Hospitalized Postmenopausal Patients Concomitant with Osteoporosis: A Retrospective Cohort Study Based on the National Readmission Database.

BACKGROUND: The present definition of obesity based on body mass index (BMI) is not accurate and effective enough to identify hospitalized patients with a heavier burden, especially for postmenopausal hospitalized patients concomitant with osteoporosis. The link between common concomitant disorders of major chronic diseases such as osteoporosis, obesity, and metabolic syndrome (MS) remains unclear. Here, we aim to evaluate the impact of different metabolic obesity phenotypes on the burden of postmenopausal hospitalized patients concomitant with osteoporosis in view of unplanned readmissions. METHODS: Data was acquired from the National Readmission Database 2018. The study population was classified into metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) patients. We estimated the associations between metabolic obesity phenotypes and 30- and 90-day unplanned readmissions. A multivariate Cox Proportional Hazards (PH) model was used to assess the effect of factors on endpoints, with results expressed as HR and 95% CI. RESULTS: The 30-day and 90-day readmission rates for the MUNO and MUO phenotypes were higher than that of the MHNO group (all p < 0.05), whereas no significant difference was found between the MHNO and MHO groups. For 30-day readmissions, MUNO raised the risk mildly (hazard ratio [HR] = 1.110, p < 0.001), MHO had a higher risk (HR = 1.145, p = 0.002), and MUO further elevated this risk (HR = 1.238, p < 0.001). As for 90-day readmissions, both MUNO and MHO raised the risk slightly (HR = 1.134, p < 0.001; HR = 1.093, p = 0.014, respectively), and MUO had the highest risk (HR = 1.263, p < 0.001). CONCLUSIONS: Metabolic abnormalities were associated with elevated rates and risks of 30- or 90-day readmission among postmenopausal hospitalized women complicated with osteoporosis, whereas obesity did not seem to be innocent, and the combination of these factors led to an additional burden on healthcare systems and individuals. These findings indicate that clinicians and researchers should focus not only on weight management but also metabolism intervention among patients with postmenopausal osteoporosis.

Development and Validation of Esophageal Squamous Cell Carcinoma Risk Prediction Models Based on an Endoscopic Screening Program.

Importance: Assessment tools are lacking for screening of esophageal squamous cell cancer (ESCC) in China, especially for the follow-up stage. Risk prediction to optimize the screening procedure is urgently needed. Objective: To develop and validate ESCC prediction models for identifying people at high risk for follow-up decision-making. Design, Setting, and Participants: This open, prospective multicenter diagnostic study has been performed since September 1, 2006, in Shandong Province, China. This study used baseline and follow-up data until December 31, 2021. The data were analyzed between April 6 and May 31, 2022. Eligibility criteria consisted of rural residents aged 40 to 69 years who had no contraindications for endoscopy. Among 161 212 eligible participants, those diagnosed with cancer or who had cancer at baseline, did not complete the questionnaire, were younger than 40 years or older than 69 years, or were detected with severe dysplasia or worse lesions were eliminated from the analysis. Exposures: Risk factors obtained by questionnaire and endoscopy. Main Outcomes and Measures: Pathological diagnosis of ESCC and confirmation by cancer registry data. Results: In this diagnostic study of 104 129 participants (56.39% women; mean [SD] age, 54.31 [7.64] years), 59 481 (mean [SD] age, 53.83 [7.64] years; 58.55% women) formed the derivation set while 44 648 (mean [SD] age, 54.95 [7.60] years; 53.51% women) formed the validation set. A total of 252 new cases of ESCC were diagnosed during 424 903.50 person-years of follow-up in the derivation cohort and 61 new cases from 177 094.10 person-years follow-up in the validation cohort. Model A included the covariates age, sex, and number of lesions; model B included age, sex, smoking status, alcohol use status, body mass index, annual household income, history of gastrointestinal tract diseases, consumption of pickled food, number of lesions, distinct lesions, and mild or moderate dysplasia. The Harrell C statistic of model A was 0.80 (95% CI, 0.77-0.83) in the derivation set and 0.90 (95% CI, 0.87-0.93) in the validation set; the Harrell C statistic of model B was 0.83 (95% CI, 0.81-0.86) and 0.91 (95% CI, 0.88-0.95), respectively. The models also had good calibration performance and clinical usefulness. Conclusions and Relevance: The findings of this diagnostic study suggest that the models developed are suitable for selecting high-risk populations for follow-up decision-making and optimizing the cancer screening process.

Prime Editing in Mammals: The Next Generation of Precision Genome Editing.

The recently established prime editor (PE) system is regarded as next-generation gene-editing technology. This methodology can install any base-to-base change as well as insertions and deletions without the requirement for double-stranded break formation or donor DNA templates; thus, it offers more targeting flexibility and greater editing precision than conventional CRISPR-Cas systems or base editors. In this study, we introduce the basic principles of PE and then review its most recent progress in terms of editing versatility, specificity, and efficiency in mammals. Next, we summarize key considerations regarding the selection of PE variants, prime editing guide RNA (pegRNA) design rules, and the efficiency and accuracy evaluation of PE. Finally, we highlight and discuss how PE can assist in a wide range of biological studies and how it can be applied to make precise genomic corrections in animal models, which paves the way for curing human diseases.

Association of complement components with the risk and severity of NAFLD: A systematic review and meta-analysis.

Background: It is generally believed that complement system is strongly associated with the risk of nonalcoholic fatty liver disease (NAFLD). However, complement system contains a variety of complement components, and the relationship between complement components and the risk and severity of NAFLD is inconsistent. The aim of this meta-analysis was to evaluate the association of complement components with the risk and severity of NAFLD. Methods: We searched PubMed, Embase, Cochrane Library, Google Scholar, Scopus, and ZhiWang Chinese databases from inception to May 2022 for observational studies reporting the risk of NAFLD with complement components. Random-effects meta-analysis was used to obtain pooled estimates of the effect due to heterogeneity. Results: We identified 18 studies with a total of 18560 included subjects. According to recent studies, levels of complement component 3 (C3) (mean difference (MD): 0.43, 95% confidence interval (CI) 0.26-0.60), complement component 4 (C4) (MD: 0.04, 95% CI 0.02-0.07), complement component 5(C5) (MD: 34.03, 95% CI 30.80-37.27), complement factor B (CFB) (MD: 0.22, 95% CI 0.13-0.31) and acylation stimulating protein (ASP) (standard mean difference (SMD): 5.17, 95% CI 2.57-7.77) in patients with NAFLD were significantly higher than those in the control group. However, no statistical significance was obtained in complement factor D (CFD) levels between NAFLD and non-NAFLD (MD=156.51, 95% CI -59.38-372.40). Moreover, the levels of C3, C5, CFB, and ASP in patients with moderate and severe NAFLD were significantly higher than those in patients with mild NAFLD. Except for C4 and CFD, the included studies did not explore the changes in the severity of NAFLD according to the concentration of C4 and CFD. Conclusions: This meta-analysis demonstrates that an increase in complement components including C3, C5, CFB, and ASP is associated with an increased risk and severity of NAFLD, indicating that they may be good biomarkers and targets for the diagnosis and treatment of NAFLD. Systematic review registration: PROSPERO [https://www.crd.york.ac.uk/PROSPERO/], identifier CRD42022348650.