We have demonstrated the utility of a 3D shape and pharmacophore similarity scoring component in molecular design with a deep generative model trained with reinforcement learning. Using Dopamine receptor type 2 (DRD2) as an example and its antagonist haloperidol 1 as a starting point in a ligand based design context, we have shown in a retrospective study that a 3D similarity enabled generative model can discover new leads in the absence of any other information. It can be efficiently used for scaffold hopping and generation of novel series. 3D similarity based models were compared against 2D QSAR based, indicating a significant degree of orthogonality of the generated outputs and with the former having a more diverse output. In addition, when the two scoring components are combined together for training of the generative model, it results in more efficient exploration of desirable chemical space compared to the individual components.The study of the hippocampus across the healthy adult lifespan has rendered inconsistent findings.  https://www.selleckchem.com/products/at13387.html  While volumetric measurements have often been a popular technique for analysis, more advanced morphometric techniques have demonstrated compelling results that highlight the importance and improved specificity of shape-based measures. Here, the MAGeT Brain algorithm was applied on 134 healthy individuals aged 18-81 years old to extract hippocampal subfield volumes and hippocampal shape measurements, namely local surface area (SA) and displacement. We used linear-, second- or third-order natural splines to examine the relationships between hippocampal measures and age. In addition, partial least squares analyses were performed to relate volume and shape measurements with cognitive and demographic information. Volumetric results indicated a relative preservation of the right cornus ammonis 1 with age and a global volume reduction linked with older age, female sex, lower levels of education and cognitive performancal/neurobiology-of-aging/special-issue/105379XPWJP.The phenotyping of the pathophysiology of obstructive sleep apnoea (OSA) lies at the core of tailored treatments and it is one of the most debated topics in sleep medicine research. Recent sophisticated techniques have broadened the horizon for gaining insight into the variability of the endotypic traits in patients with OSA which account for the heterogeneity in the clinical presentation of the disease and consequently, in the outcome of treatment. However, the implementation of these concepts into clinical practice is still a major challenge for both researchers and clinicians in order to develop tailored therapies targeted to specific endotypic traits that contribute to OSA in each individual patient. This review summarizes available scientific evidence in order to point out the links between endotypic traits (pharyngeal airway collapsibility, upper airway neuromuscular compensation, loop gain and arousal threshold) and the most common non-continuous positive airway pressure (CPAP) treatment options for OSA (mandibular advancement device, upper airway surgery, medication therapy, positional therapy) and to clarify to what extent endotypic traits could help to better predict the success of these therapies. A narrative guide is provided; current design limitations and future avenues of research are discussed, with clinical and research perspectives.
  Trend analysis in cancer quantifies the incidence rate and explains the trend and pattern. Breast and cervical cancers are the two most common cancers among Indian women which contributed 39.4 % to the total cancer in India for the year 2020. This study aimed to report the time trends in cancer incidence of breast and cervical cancer using Age-Period-Cohort (APC) model from five Population Based Cancer Registries (PBCRs) in India for the period of 1985-2014.
 
  Age-Period-Cohort model was fitted to five PBCRs of Bangalore, Chennai, Delhi, Bhopal and Barshi rural for breast and cervical cancer for 25-74 age-groups. The Estimated Annual Percent Change (EAPC) was calculated. Rate Ratio (RR) of cohort effects were estimated with a constraint of period slope to be zero (p = 0) since cohort has a stronger association with incidence than period.
 
  A significant increase was noted in breast cancer in all PBCRs (EAPC, Range Delhi, 1.2 % to Bangalore, 2.7 %) while significant decrease in cervical cancer (EAPC, Range Bangalore -2.5 % to Chennai, -4.6 %) from all the PBCRs including Barshi rural during the period. RR estimates for breast cancer showed increasing trend whereas cervical cancer showed decreasing trend in successive birth cohorts across all five PBCRs.
 
  In both breast and cervical cancers, a significant age, cohort and period effect was noted in Bangalore, Chennai and Delhi. Despite period effect, the cohort effect was predominant and it may be attributed to the generational changes in risk factors among cancer breast and cervix.
 In both breast and cervical cancers, a significant age, cohort and period effect was noted in Bangalore, Chennai and Delhi. Despite period effect, the cohort effect was predominant and it may be attributed to the generational changes in risk factors among cancer breast and cervix.
  Mutually increased risks for thyroid and breast cancer have been reported, but the contribution of etiologic factors versus increased medical surveillance to these associations is unknown.
 
  Leveraging large-scale US population-based cancer registry data, we used standardized incidence ratios (SIRs) to investigate the reciprocal risks of thyroid and breast cancers among adult females diagnosed with a first primary invasive, non-metastatic breast cancer (N = 652,627) or papillary thyroid cancer (PTC) (N = 92,318) during 2000-2017 who survived ≥1-year.
 
  PTC risk was increased 1.3-fold [N = 1434; SIR = 1.32; 95 % confidence interval (CI) = 1.25-1.39] after breast cancer compared to the general population. PTC risk declined significantly with time since breast cancer (Poisson regression = P
  <0.001) and was evident only for tumors ≤2 cm in size. The SIRs for PTC were higher after hormone-receptor (HR)+ (versus HR-) and stage II or III (versus stage 0-I) breast tumors. Breast cancer risk was increased 1.2-fold (N = 2038; SIR = 1.