Increased alcohol intake is associated with radiographic severity of knee and hand osteoarthritis in men.

Observational studies have shown controversial associations between alcohol intake and radiographic osteoarthritis (OA). This study investigated whether this association was causal using a Mendelian randomization (MR) study in a population-based cohort in Korean. The study enrolled 2429 subjects (1058 men, 1371 women) from the Dong-gu Study. X-rays of the hand and knee joints were scored using a semi-quantitative grading system to calculate the total score of the hand and knee joints. ALDH2 rs671 genotyping was performed by high-resolution melting analysis. MR instrumental variable analysis and observational multivariable regression analysis were used to estimate the association between genetically predicted alcohol intake and the radiographic severity of OA. Subjects with the G/G genotype had a higher current alcohol intake than those with the G/A and A/A genotypes in both men and women (all P < 0.001). Men with the G/G genotype had higher total knee (P < 0.001) and hand scores (P = 0.042) compared to those with the G/A and A/A genotypes after adjusting for age and body mass index, but not in women. In the observational multivariable regression analysis, each alcohol drink per day in men was associated with increased knee (P = 0.001) and hand joint scores (P = 0.013) after adjustment, but not in women. In our MR analysis, utilizing ALDH2 rs671 genotypes as instrumental variables for alcohol consumption, has shown a significant link between each additional daily alcohol drink and increased radiographic joint severity in men.

Machine Learning Algorithms Predict Successful Weaning From Mechanical Ventilation Before Intubation: Retrospective Analysis From the Medical Information Mart for Intensive Care IV Database.

BACKGROUND: The prediction of successful weaning from mechanical ventilation (MV) in advance of intubation can facilitate discussions regarding end-of-life care before unnecessary intubation. OBJECTIVE: We aimed to develop a machine learning-based model that predicts successful weaning from ventilator support based on routine clinical and laboratory data taken before or immediately after intubation. METHODS: We used the Medical Information Mart for Intensive Care IV database, which is an open-access database covering 524,740 admissions of 382,278 patients in Beth Israel Deaconess Medical Center, United States, from 2008 to 2019. We selected adult patients who underwent MV in the intensive care unit (ICU). Clinical and laboratory variables that are considered relevant to the prognosis of the patient in the ICU were selected. Data collected before or within 24 hours of intubation were used to develop machine learning models that predict the probability of successful weaning within 14 days of ventilator support. Developed models were integrated into an ensemble model. Performance metrics were calculated by 5-fold cross-validation for each model, and a permutation feature importance and Shapley additive explanations analysis was conducted to better understand the impacts of individual variables on outcome prediction. RESULTS: Of the 23,242 patients, 19,025 (81.9%) patients were successfully weaned from MV within 14 days. Using the preselected 46 clinical and laboratory variables, the area under the receiver operating characteristic curve of CatBoost classifier, random forest classifier, and regularized logistic regression classifier models were 0.860 (95% CI 0.852-0.868), 0.855 (95% CI 0.848-0.863), and 0.823 (95% CI 0.813-0.832), respectively. Using the ensemble voting classifier using the 3 models above, the final model revealed the area under the receiver operating characteristic curve of 0.861 (95% CI 0.853-0.869), which was significantly better than that of Simplified Acute Physiology Score II (0.749, 95% CI 0.742-0.756) and Sequential Organ Failure Assessment (0.588, 95% CI 0.566-0.609). The top features included lactate and anion gap. The model's performance achieved a plateau with approximately the top 21 variables. CONCLUSIONS: We developed machine learning algorithms that can predict successful weaning from MV in advance to intubation in the ICU. Our models can aid the appropriate management for patients who hesitate to decide on ventilator support or meaningless end-of-life care.

Differential DNA damage repair and PARP inhibitor vulnerability of the mammary epithelial lineages.

It is widely assumed that all normal somatic cells can equally perform homologous recombination (HR) and non-homologous end joining in the DNA damage response (DDR). Here, we show that the DDR in normal mammary gland inherently depends on the epithelial cell lineage identity. Bioinformatics, post-irradiation DNA damage repair kinetics, and clonogenic assays demonstrated luminal lineage exhibiting a more pronounced DDR and HR repair compared to the basal lineage. Consequently, basal progenitors were far more sensitive to poly(ADP-ribose) polymerase inhibitors (PARPis) in both mouse and human mammary epithelium. Furthermore, PARPi sensitivity of murine and human breast cancer cell lines as well as patient-derived xenografts correlated with their molecular resemblance to the mammary progenitor lineages. Thus, mammary epithelial cells are intrinsically divergent in their DNA damage repair capacity and PARPi vulnerability, potentially influencing the clinical utility of this targeted therapy.

Structural insight into crystal structure of helicase domain of DDX53.

DEAD box helicase proteins are a family of RNA helicases that participate in various RNA metabolisms such as RNA unwinding, RNA processing, and RNPase activities. A particular DEAD box protein, the DDX53 protein, is primarily expressed in cancer cells and plays a crucial role in tumorigenesis. Numerous studies have revealed that DDX53 interacts with various microRNA and Histone deacetylases. However, its molecular structure and the detailed binding interaction between DDX53 and microRNA or HDAC is still unclear. In this study, we used X-ray crystallography to investigate the 3D structure of the hlicase C-terminal domain of DDX53, and successfully determined its crystal structure at a resolution of 1.97 Å. Subsequently, a functional analysis of RNA was conducted by examining the binding properties thereof with DDX53 by transmission electron microscopy and computing-based molecular docking simulation. The defined 3D model of DDX53 not only provides a structural basis for the fundamental understanding of DDX53 but is also expected to contribute to the field of anti-cancer drug discovery such as structure-based drug discovery and computer-aided drug design.

Association Between Plasma Homocysteine Level and Mortality: A Mendelian Randomization Study.

BACKGROUND AND OBJECTIVES: In previous studies, high homocysteine levels were associated with high cardiovascular mortality. However, these results were inconsistent with those of randomized controlled trials. We aimed to evaluate the causal role of homocysteine on all-cause and cardiovascular mortality using Mendelian randomization (MR) analysis. METHODS: This study included the 10,005 participants in the Namwon Study. In conventional observational analysis, age, sex, survey years, lifestyles, body mass index, comorbidities, and serum folate level were adjusted using multivariate Cox proportional regression. MR using 2-stage least squares regression was used to evaluate the association between genetically predicted plasma homocysteine levels and mortality. Age, sex, and survey years were adjusted for each stage. The methylenetetrahydrofolate reductase (MTHFR) polymorphism was used as an instrumental variable for predicting plasma homocysteine levels. RESULTS: Observed homocysteine levels were positively associated with all-cause (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.26-1.54) and cardiovascular (HR, 1.62; 95% CI, 1.28-2.06) mortality when plasma homocysteine levels doubled. However, these associations were not significant in MR analysis. The HRs of doubling genetically predicted plasma homocysteine levels for all-cause and cardiovascular mortality were 0.99 (95% CI, 0.62-1.57) and 1.76 (95% CI, 0.54-5.77), respectively. CONCLUSIONS: This MR analysis did not support a causal role for elevated plasma homocysteine concentrations in premature deaths.

Regioselective Access to 1,2,4-Triazole-Fused N-Heterocycle, Pyrrolo[1,2-a][1,2,4]triazolo[5,1-c]pyrazine, via Double Dehydrative Cyclizations.

A highly efficient and regioselective approach to a novel 1,2,4-triazole-fused N-heterocyclic scaffold, pyrrolo[1,2-a][1,2,4]triazolo[3,4-c]pyrazine, was established by base-promoted reaction of pyrrole-2-carbonitrile-derived substrate with acyl hydrazide where domino double ring closures comprised of enamine formation, attack on nitrile, and cyclodehydration enabled sequential construction of pyrazine and 1,2,4-triazole ring systems with formation of three C-N bonds.

Effect Modification of Kidney Function on the Non-linear Association Between Serum Calcium Levels and Cardiovascular Mortality in Korean Adults.

OBJECTIVES: This study aimed to evaluate the potential interaction between kidney function and the non-linear association between serum calcium levels and cardiovascular disease (CVD) mortality. METHODS: This study included 8927 participants enrolled in the Dong-gu Study. Albumin-corrected calcium levels were used and categorized into 6 percentile categories: <2.5th, 2.5-25.0th, 25.0-50.0th, 50.0-75.0th, 75.0-97.5th, and >97.5th. Restricted cubic spline analysis was used to examine the non-linear association between calcium levels and CVD mortality. Cox proportional hazard regression was used to estimate hazard ratios (HRs) for CVD mortality according to serum calcium categories. All survival analyses were stratified by the estimated glomerular filtration rate. RESULTS: Over a follow-up period of 11.9±2.8 years, 1757 participants died, of whom 219 died from CVD. A U-shaped association between serum calcium and CVD mortality was found, and the association was more evident in the low kidney function group. Compared to the 25.0-50.0th percentile group for serum calcium levels, both low and high serum calcium tended to be associated with CVD mortality (<2.5th: HR, 6.23; 95% confidence interval [CI], 1.16 to 33.56; >97.5th: HR, 2.56; 95% CI, 0.76 to 8.66) in the low kidney function group. In the normal kidney function group, a similar association was found between serum calcium levels and CVD mortality (<2.5th: HR, 1.37; 95% CI, 0.58 to 3.27; >97.5th: HR, 1.65; 95% CI, 0.70 to 3.93). CONCLUSIONS: We found a non-linear association between serum calcium levels and CVD mortality, suggesting that calcium dyshomeostasis may contribute to CVD mortality, and kidney function may modify the association.

Association Between Serum Bilirubin and Atrial Fibrillation: A Mendelian Randomization Study.

BACKGROUND AND OBJECTIVES: The association between bilirubin and atrial fibrillation (AF) has been evaluated previously in observational studies but with contradictory results. This study evaluated the causal association between serum bilirubin level and AF using Mendelian randomization (MR) analysis. METHODS: This cross-sectional study includes 8,977 participants from the Dong-gu Study. In the observational analysis, multivariate logistic regression was performed to evaluate the association between bilirubin and prevalent AF. To evaluate the causal association between bilirubin and AF, MR analysis was conducted by using the UGT1A1 rs11891311 and rs4148323 polymorphisms as instrumental variables. RESULTS: Elevated serum bilirubin levels were associated with an increased risk for AF in observational analysis (total bilirubin: odds ratio [OR], 1.31; 95% confidence interval [95% CI], 1.15-1.48 per 1 standard deviation [SD]; direct bilirubin: OR, 1.31; 95% CI, 1.18-1.46 per 1 SD), whereas the genetically predicted serum bilirubin levels in MR analysis did not show this association (total bilirubin: OR, 1.02; 95% CI, 0.67-1.53 per 1 SD; direct bilirubin: OR, 1.03; 95% CI, 0.61-1.73 per 1 SD). CONCLUSIONS: Genetically predicted bilirubin levels were not associated with prevalent AF. Thus, the observational association between serum bilirubin levels and AF may be non-causal and affected by reverse causality or unmeasured confounding.

Multidimensional Nomogram to Predict Postoperative Pancreatic Fistula after Minimally Invasive Pancreaticoduodenectomy.

BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) is an inherently severe risk of pancreatic resection. Previous research has proposed models that identify risk factors and predict CR-POPF, although these are rarely applicable to minimally invasive pancreaticoduodenectomy (MIPD). This study aimed to evaluate the individual risks of CR-POPF and to propose a nomogram for predicting POPF in MIPD. PATIENTS AND METHODS: We retrospectively reviewed the medical records of 429 patients who underwent MIPD. In the multivariate analysis, the Akaike information criterion stepwise logistic regression method was used to select the final model to develop the nomogram. RESULTS: Of 429 patients, 53 (12.4%) experienced CR-POPF. On multivariate analysis, pancreatic texture (p = 0.001), open conversion (p = 0.008), intraoperative transfusion (p = 0.011), and pathology (p = 0.048) were identified as independent predictors of CR-POPF. The nomogram was developed based on patient, pancreatic, operative, and surgeon factors by using the following four additional clinical factors as variables: American Society of Anesthesiologists class ≥ III, size of pancreatic duct, type of surgical approach, and < 40 cases of MIPD experience. CONCLUSIONS: A multidimensional nomogram was developed to predict CR-POPF after MIPD. This nomogram and calculator can help surgeons anticipate, select, and manage critical complications.

C3 Functionalization of Indolizines via HFIP-Promoted Friedel-Crafts Reactions with (Hetero)arylglyoxals.

A highly efficient Friedel-Crafts type hydroxyalkylation at the C3 position of indolizines with (hetero)arylglyoxals has been achieved by the action of hexafluoroisopropanol (HFIP) under mild reaction conditions, leading to direct access to a variety of polyfunctionalized indolizines in excellent yields. Installation of more diverse functional groups at the C3 site of indolizine scaffold was realized via further elaboration of the resulting α-hydroxyketone moiety, allowing for expansion of indolizine chemical space.

Folate deficiency is associated with increased radiographic severity of osteoarthritis in knee joints but not in hand joints.

OBJECTIVES: No previous studies have explored the effect of folate deficiency on the severity of osteoarthritis (OA). Therefore, we investigated the relationship between folate level and features on knee and hand radiographs in a large, population-based OA cohort. METHODS: Among 9,260 subjects enrolled in the Dong-gu study, 2,489 who had knee and hand joint radiographs were included. Of these, subjects with a history of amputation or total knee replacement were excluded. Serum folate levels were measured using blood samples collected at the time of enrolment and stored. A semi-quantitative system was used to grade the severity of hand and knee x-ray changes. Linear regression was performed to assess relationships between serum folate levels and knee and hand radiographic scores after adjusting for age, sex, body mass index, smoking, alcohol consumption, education, physical activity, occupation, vitamin D, and ferritin. RESULTS: A total of 2,322 subjects were recruited. After adjusting for confounders, participants with folate deficiency (<4 ng/mL) had higher total (p<0.001), osteophyte (p<0.001), joint space narrowing (p=0.002), tibial attrition (p<0.001), and sclerosis (p=0.005) scores for knee joint radiographs compared to participants with a normal folate level. After adjusting for confounders, the radiographic scores for hand joints did not differ between the groups. CONCLUSIONS: Folate deficiency is associated with increased radiographic severity of OA in knee joints, but not in hand joints. Further studies are needed to explore the differential effects of folate on the severity of knee and hand OA.

Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation.

BACKGROUND: Osteoporosis is one of the diseases that requires early screening and detection for its management. Common clinical tools and machine-learning (ML) models for screening osteoporosis have been developed, but they show limitations such as low accuracy. Moreover, these methods are confined to limited risk factors and lack individualized explanation. OBJECTIVE: The aim of this study was to develop an interpretable deep-learning (DL) model for osteoporosis risk screening with clinical features. Clinical interpretation with individual explanations of feature contributions is provided using an explainable artificial intelligence (XAI) technique. METHODS: We used two separate data sets: the National Health and Nutrition Examination Survey data sets from the United States (NHANES) and South Korea (KNHANES) with 8274 and 8680 respondents, respectively. The study population was classified according to the T-score of bone mineral density at the femoral neck or total femur. A DL model for osteoporosis diagnosis was trained on the data sets and significant risk factors were investigated with local interpretable model-agnostic explanations (LIME). The performance of the DL model was compared with that of ML models and conventional clinical tools. Additionally, contribution ranking of risk factors and individualized explanation of feature contribution were examined. RESULTS: Our DL model showed area under the curve (AUC) values of 0.851 (95% CI 0.844-0.858) and 0.922 (95% CI 0.916-0.928) for the femoral neck and total femur bone mineral density, respectively, using the NHANES data set. The corresponding AUC values for the KNHANES data set were 0.827 (95% CI 0.821-0.833) and 0.912 (95% CI 0.898-0.927), respectively. Through the LIME method, significant features were induced, and each feature's integrated contribution and interpretation for individual risk were determined. CONCLUSIONS: The developed DL model significantly outperforms conventional ML models and clinical tools. Our XAI model produces high-ranked features along with the integrated contributions of each feature, which facilitates the interpretation of individual risk. In summary, our interpretable model for osteoporosis risk screening outperformed state-of-the-art methods.

Which one is better? Laparoscopic versus robotic reconstruction in the remnant soft pancreas with a small pancreatic duct following pancreaticoduodenectomy: a multicenter study with propensity score matching analysis.

BACKGROUND: Evidence of the advantages of robotic pancreaticoduodenectomy (RPD) over laparoscopic pancreaticoduodenectomy (LPD) is limited. Thus, this study aimed to compare the surgical outcomes of laparoscopic reconstruction L-recon) versus robotic reconstruction (R-recon) in patients with soft pancreas and small pancreatic duct. METHOD: Among 429 patients treated with minimally invasive pancreaticoduodenectomy (MIPD) between October 2012 and June 2020 by three surgeons at three institutions, 201 patients with a soft pancreas and a small pancreatic duct (< 3 mm) were included in this study. RESULTS: Sixty pairs of patients who underwent L-recon and R-recon were selected after propensity score matching. The perioperative outcomes were comparable between the reconstruction approaches, with comparable clinically relevant postoperative pancreatic fistula (CR-POPF) rates (15.0% [L-recon] vs. 13.3% [R-recon]). The sub-analysis according to the type of MIPD procedure also showed comparable outcomes, but only a significant difference in postoperative hospital stay was identified. During the learning curve analysis using the cumulative summation by operation time (CUSUMOT), two surgeons who performed both L-recon and R-recon procedures reached their first peak in the CUSUMOT graph earlier for the R-recon group than for the L-recon group (i.e., 20th L-recon case and third R-recon case of surgeon A and 43rd L-recon case and seventh R-recon case of surgeon B). Surgeon C, who only performed R-recon, demonstrated the first peak in the 22nd case. The multivariate regression analysis for risk factors of CR-POPF showed that the MIPD procedure type, as well as other factors, did not have any significant effect. CONCLUSION: Postoperative pancreatic fistula rates and the overall perioperative outcomes of L-recon and R-recon were comparable in patients with soft-textured pancreas and small pancreatic duct treated by experienced surgeons.

No evidence of delay in colorectal cancer diagnosis during the COVID-19 pandemic in Gwangju and Jeonnam, Korea

Objectives: We evaluated whether the coronavirus disease 2019 (COVID-19) pandemic caused delays in the diagnosis and treatment of colorectal cancer (CRC) in Korea, where there have been no regional or hospital lockdowns during the pandemic period. Methods: Data on CRC patients (n=1,445) diagnosed in Gwangju Metropolitan City and Jeonnam Province between January 2019 and December 2021 were assessed. The stage at the time of CRC diagnosis, route to diagnosis, time to initial cancer treatment, and length of hospital admission were compared before and during the COVID-19 pandemic. Logistic regression was also performed to identify factors associated with the risk for diagnosis in an advanced stage. Results: No negative effects indicating a higher CRC stage at diagnosis or delayed treatment during the pandemic were observed. Instead, the risk for an advanced stage at diagnosis (TNM stage III/IV) decreased in CRC patients diagnosed during the pandemic (odds ratio, 0.768; 95% confidence interval, 0.647 to 0.911). No significant differences in the interval from diagnosis to operation or chemotherapy were observed. Conclusion: No negative effects on CRC diagnosis and treatment were found until the end of 2021, which may be related to the small magnitude of the COVID-19 epidemic, the absence of a lockdown policy in Korea, and the rebound in the number of diagnostic colonoscopy procedures in 2021.

Wireless portable bioelectronic nose device for multiplex monitoring toward food freshness/spoilage.

Monitoring food freshness/spoilage is important to ensure food quality and safety. Current methods of food quality monitoring are mostly time-consuming and labor intensive processes that require massive analytical equipment. In this study, we developed a portable bioelectronic nose (BE-nose) integrated with trace amine-associated receptor (TAAR) nanodiscs (NDs), allowing food quality monitoring via the detection of food spoilage indicators, including the biogenic amines cadaverine (CV) and putrescine (PT). The olfactory receptors TAAR13c and TAAR13d, which have specific affinities for CV and PT, were produced and successfully reconstituted in ND structures. TAAR13 NDs BE-nose-based side-gated field-effect transistor (SG-FET) system was constructed by utilizing a graphene micropattern (GM) into which two types of olfactory NDs (TAAR13c ND and TAAR13d ND) were introduced, and this system showed ultrahigh sensitivity for a limit of detection (LOD) of 1 fM for CV and PT. Moreover, the binding affinities between the TAAR13 NDs and the indicators were confirmed by a tryptophan fluorescence quenching assay and biosimulations, in which the specific binding site was confirmed. Gas-phase indicators were detected by the TAAR13 NDs BE-nose platform, and the LODs for CV and PT were confirmed to be 26.48 and 7.29 ppb, respectively. In addition, TAAR13 NDs BE-nose was fabricated with commercial gas sensors as a portable platform for the measurement of NH3 and H2S, multiplexed monitoring was achieved with similar performance, and the change ratio of the indicators was observed in a real sample. The integration of commercial gas sensors on a BE-nose enhanced the accuracy and reliability for the quality monitoring of real food samples. These results indicate that the portable TAAR13 NDs BE-nose can be used to monitor CV and PT over a wide range of concentrations, therefore, the electronic nose platform can be utilized for monitoring the freshness/spoilage step in various foods.

Proteomics-based diagnostic peptide discovery for severe fever with thrombocytopenia syndrome virus in patients.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) virus is an emerging infectious virus which causes severe hemorrhage, thrombocytopenia, and leukopenia, with a high fatality rate. Since there is no approved therapeutics or vaccines for SFTS, early diagnosis is essential to manage this infectious disease. METHODS: Here, we tried to detect SFTS virus in serum samples from SFTS patients by proteomic analysis. Firstly, in order to obtain the reference MS/MS spectral data of SFTS virus, medium from infected Vero cell culture was used for shotgun proteomic analysis. Then, tryptic peptides in sera from SFTS patients were confirmed by comparative analysis with the reference MS/MS spectral data of SFTS virus. RESULTS: Proteomic analysis of culture medium successfully discovered tryptic peptides from all the five antigen proteins of SFTS virus. The comparative spectral analysis of sera of SFTS patients revealed that the N-terminal tryptic peptide of the nucleocapsid (N) protein is the major epitope of SFTS virus detected in the patient samples. The prevalence of the peptides was strongly correlated with the viral load in the clinical samples. CONCLUSIONS: Proteomic analysis of SFTS patient samples revealed that nucleocapsid (N) protein is the major antigen proteins in sera of SFTS patients and N-terminal tryptic peptide of the N protein might be a useful proteomic target for direct detection of SFTS virus. These findings suggest that proteomic analysis could be an alternative tool for detection of pathogens in clinical samples and diagnosis of infectious diseases.

ZnO Nanowire-Based Early Detection of SARS-CoV-2 Antibody Responses in Asymptomatic Patients with COVID-19.

A serological immunoassay based on enzyme-linked immunosorbent assay (ELISA) is a crucial tool for screening and identification of human SARS-CoV-2 seroconversion. Various immunoassays are developed to detect the spike 1 (S1) and nucleocapsid (NP) proteins of SARS-CoV-2; however, these serological tests have low sensitivity. Here, a novel microplate (MP) is developed on which a ZnO nanowire (NW) is fabricated by a modified hydrothermal synthesis method. This plate is coated with SARS-CoV-2 NP and used as a fluorescent immunoassay (FIA) to detect antibodies specific for SARS-CoV-2 NP. Compared with the bare MP, the ZnO-NW MP binds high levels (up to 5 µg mL-1) of SARS-CoV-2 NP tagged to histidine without any surface treatment. A novel serological assay based on the ZnO-NW MP is more sensitive than a commercial immunoassay, enabling early detection (within <5 days of a reverse transcription polymerase chain reaction-confirmed COVID-19 infection) of anti-SARS-CoV-2 NP IgG antibodies in asymptomatic patients with COVID-19. This is the first assay to detect early antibody responses to SARS-CoV-2 in asymptomatic patients. Therefore, this serological assay will facilitate accurate diagnosis of COVID-19, as well as estimation of COVID-19 prevalence and incidence.