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The objective of this article is to provide an operational definition of recovery from alcohol use disorder (AUD) to facilitate the consistency of research on recovery and stimulate further research. The construct of recovery has been difficult to operationalize in the alcohol treatment and recovery literature. Several formal definitions of recovery have been developed but have limitations because 1) they require abstinence from both alcohol and substance use, 2) they do not include the DSM-5 diagnostic criteria for AUD as part of the recovery process (i.e., no focus on remission from AUD), 3) they do not link remission and cessation from heavy drinking to improvements in biopsychosocial functioning and quality-of-life constructs, and 4) they do not distinguish between alcohol and other drug use. The authors present a newly developed National Institute on Alcohol Abuse and Alcoholism (NIAAA) definition of recovery from DSM-5 AUD based on qualitative feedback from key recovery stakeholders (e.g., researchers, clinicians, and recovery specialists). The definition views recovery as both a process of behavioral change and an outcome and incorporates two key components of recovery, namely, remission from DSM-5 AUD and cessation from heavy drinking, a nonabstinent recovery outcome. The NIAAA definition of recovery also emphasizes the importance of biopsychosocial functioning and quality of life in enhancing recovery outcomes. This new NIAAA definition of recovery is an operational definition that can be used by diverse stakeholders to increase consistency in recovery measurement, stimulate research to better understand recovery, and facilitate the process of recovery.The fact that animal models fail to replicate human disease faithfully is now being widely accepted by researchers across the globe. As a result, they are exploring the use of alternatives to animal models. The time has come to refine our experimental practices, reduce the numbers and eventually replace the animals used in research with human-derived and human-relevant 3-D disease models. Oncoseek Bio-Acasta Health, which is an innovative biotechnology start-up company based in Hyderabad and Vishakhapatnam, India, organises an annual International Conference on 3Rs Research and Progress. In 2021, this conference was on 'Advances in Research Animal Models and Cutting-Edge Research in Alternatives'. This annual conference is a platform that brings together eminent scientists and researchers from various parts of the world, to share recent advances from their research in the field of alternatives to animals including new approach methodologies, and to promote practices to help refine animal experiments where alternatives are not available. This report presents the proceedings of the conference, which was held in hybrid mode (i.e. virtual and in-person) in November 2021.

We aimed to determine the association between beta-blocker or statin drug use and the future risk of symptomatic intracranial hemorrhage or persistent/progressive focal neurological deficit from cerebral cavernous malformations (CCM).

The population-based Scottish Audit of Intracranial Vascular Malformations prospectively identified adults resident in Scotland first diagnosed with CCM during 1999 to 2003 or 2006 to 2010. We compared the association between beta-blocker or statin drug use after first presentation and the occurrence of new intracranial hemorrhage or persistent/progressive focal neurological deficit due to CCM for up to 15 years of prospective follow-up. We confirmed proportional hazards and used survival analysis with multivariable adjustment for age, intracranial hemorrhage at CCM presentation, and brain stem CCM location.

Sixty-three (21%) of 300 adults used beta-blockers (27/63 [43%] used propranolol), and 73 (24%) used statin drugs over 3634 person-years of follow-up. At baseline, the only statistically significant imbalances in prespecified potential confounders were age by statin use and intracranial hemorrhage at presentation by beta-blocker use. Beta-blocker use was associated with a lower risk of new intracranial hemorrhage or persistent/progressive focal neurological deficit (adjusted hazard ratio, 0.09 [95% CI, 0.01-0.66];

=0.018). Statin use was associated with a nonsignificant lower risk of intracranial hemorrhage or persistent/progressive focal neurological deficit (adjusted hazard ratio, 0.37 [95% CI, 0.01-1.07];

=0.067).

Beta-blocker, but not statin, use was associated with a lower risk of intracranial hemorrhage or persistent/progressive focal neurological deficit in patients with CCM.

Beta-blocker, but not statin, use was associated with a lower risk of intracranial hemorrhage or persistent/progressive focal neurological deficit in patients with CCM.

Lp(a) (lipoprotein(a)) contributes to cardiovascular disease mainly through proatherogenic and proinflammatory effects. Here, we aimed to evaluate whether a residual stroke risk of Lp(a) would remain when the LDL-C (low-density lipoprotein cholesterol) and inflammatory levels are maintained low.

This prospective cohort study included 9899 patients with ischemic stroke or transient ischemic attack from the Third China National Stroke Registry who had measurements of plasma Lp(a) and were followed up for 1 year. Cutoffs were set at the 50 mg/dL for Lp(a). LDL-C was corrected for Lp(a)-derived cholesterol (LDL-Cc [LDL-C corrected]) and cutoffs were set at 55 and 70 mg/dL.The threshold values of IL-6 (interleukin 6) and hsCRP (high-sensitive C-reactive protein) were the median 2.65 ng/L and 2 mg/L. Multivariable-adjusted hazard ratio (HR) were calculated using Cox regression models for each category to investigate the associations of Lp(a) with stroke recurrence within 1 year.

Among all patients, those withischemic attack. However, at low LDL-Cc or IL-6 levels, the elevated Lp(a) -associated stroke recurrence risk was attenuated in a secondary prevention setting.

Increased Lp(a) was significantly associated with stroke recurrence risk in patients with ischemic stroke/transient ischemic attack. see more However, at low LDL-Cc or IL-6 levels, the elevated Lp(a) -associated stroke recurrence risk was attenuated in a secondary prevention setting.DNMT1 is the main enzyme that uses the information on DNA methylation patterns in the parent strand and methylates the daughter strand in freshly replicated hemimethylated DNA. It is widely known that DNMT1 is a component of the epigenetic machinery mediating gene repression via increased promoter methylation. However, recent data suggest that DNMT1 can also modulate gene expression independent of its catalytic activity and participates in multiple processes including the cell cycle, DNA damage repair and stem cell function. This review summarizes the noncanonical functions of DNMT1, some of which are clearly independent of maintenance methylation. Finally, phenotypic data on altered DNMT1 levels suggesting that maintenance of optimal levels of DNMT1 is vital for normal development and health is presented.

Recent studies revealed that various inflammatory and nutritional indexes were associated with prognosis in esophageal cancer (EC). However, these studies only evaluated one or two indexes, and the prognostic value of these indexes individually or in combination is unclear. This study aimed to construct an integrative score based on various inflammatory and nutritional indexes for prognosis in resectable

squamous cell carcinoma (ESCC).

A total of 421 consecutive patients were randomly divided into either a training or validation cohort at a ratio of 73 for retrospective analysis. Using logic regression analyses, independent risk factors from peripheral blood indexes were screened to construct an integrative score. The associations regarding the integrative score, clinical characteristics, cancer-specific survival (CSS), and overall survival (OS) were analyzed.

Out of 20 indexes, hemoglobin (HB), C-reactive protein to albumin ratio (CAR), and platelet to lymphocyte ratio (PLR) were independent risk factors based on logical regression analyses. Then, an integrative score with the optimal cut-off value of .67 was established according to the Combination Of HB, CAR, and PLR (COHCP). The area under the curve (AUC) indicated higher predictive ability of COHCP on prognosis than other indicators. Multivariate analyses revealed that COHCP serves as an independent prognostic score. Patients with COHCP low group (≤.67) had better 5-year CSS (57.3% vs 13.5%,

< .001) and OS (51.1% vs 12.3%,

< .001) than those with high group, respectively. Finally, the nomogram based on COHCP was established and validated regarding CSS and OS, which can accurately and effectively predict individual survival in resected ESCC.

The COHCP was a novel, simple, and useful predictor in resectable ESCC. The COHCP-based nomogram may accurately and effectively predict survival.

The COHCP was a novel, simple, and useful predictor in resectable ESCC. The COHCP-based nomogram may accurately and effectively predict survival.

To determine the age-adjusted association between colorectal cancer (CRC) risk factors and CRC prevalence among long-haul truck drivers (aged 21-85), after adjustment for age.

Pooled cross-sectional analysis using Commercial Driver Medical Exam (CDME) data. Setting. National survey data from January 1, 2005, to October 31, 2012.

47,786 commercial motor vehicle drivers in 48 states.

CRC prevalence was the primary outcome; independent variables included demographics, body mass index (BMI), and concomitant medical conditions.

Kruskal-Wallis tests to analyze continuous variables; Fischer's exact tests to analyze categorical variables; univariate and multivariable logistic regression for rare events (Firth method) to quantify the association between the independent variables of interest and CRC prevalence. Odds ratios (ORs) and 95% confidence intervals (CIs) were adjusted for age, gender, years with current employer, year of exam, and BMI in a multivariate logistic regression.

Many factors were statistically significant. Obesity (OR = 3.14; 95% CI = 1.03-9.61) and increasing age (OR = 1.10 per year; 95% CI = 1.07-1.13) were significantly associated with CRC prevalence. Truckers with 4 or more concomitant medical conditions were significantly more likely to have CRC (OR = 7.03; 95% CI = 1.83-27.03).

Our findings highlight mutable risk factors and represent an opportunity for intervention that may decrease CRC morbidity and mortality among truck drivers, a unique population in the United States estimated to live up to 16years less than the general population.

Our findings highlight mutable risk factors and represent an opportunity for intervention that may decrease CRC morbidity and mortality among truck drivers, a unique population in the United States estimated to live up to 16 years less than the general population.

Patellofemoral osteoarthritis (PFOA) has a high prevalence and is assessed on axial radiography of the patellofemoral joint (PFJ). A deep learning (DL)-based approach could help radiologists automatically diagnose and grade PFOA via interpreting axial radiographs.

To develop and assess the performance of a DL-based approach for diagnosing and grading PFOA on axial radiographs.

A total of 1280 (dataset 1) axial radiographs were retrospectively collected and utilized to develop the high-resolution network (HRNet)-based classification models. The ground truth was the interpretation from two experienced radiologists in consensus according to the K-L grading system. A binary-class model was trained to diagnose the presence (K-L 2∼4) or absence (K-L 0∼1) of PFOA. A multi-class model was used to grade the stage of PFOA, i.e. from K-L 0 to K-L 4. Model performances were evaluated using the receiver operating characteristics (ROC), confusion matrix, and the corresponding evaluation metrics (positive predictive value [PPV], negative predictive value [NPV], F1 score, sensitivity, specificity, accuracy) of the internal test set (n = 129) from dataset 1 and an external validation set (dataset 2, n = 187).