Respiratory syncytial virus-associated mortality among young infants in Karachi, Pakistan: A prospective postmortem surveillance study

Background: Respiratory syncytial virus (RSV) is an important cause of infant morbidity and mortality and a potential target for maternal immunization strategies. However, data on the role of RSV in young infant deaths in developing countries are limited.Methods: We conducted a community-based mortality surveillance from August 2018-March 2020 for infants ≤6 months in Karachi, Pakistan. We tested (reverse transcription-polymerase chain reaction) nasopharyngeal swabs from deceased infants for presence of RSV. We performed verbal autopsies and calculated odds of RSV-associated mortality with 95% CIs and used multivariable logistic regression to evaluate associations.Results: We collected 490 nasopharyngeal specimens from 1280 eligible infant deaths. There were 377/490 (76.9%) live births and 14/377 (3.7%; 95% CI: 1.8-5.6) were RSV positive. Most deaths occurred in neonates (254/377; 67.4%), males (226/377; 59.9%), and respiratory illnesses (206/377; 54.6%). Postneonatal age (10/14, 71.4%; OR: 5.5; 95% CI: 1.7-18.0), respiratory symptoms (12/14, 85.7%; OR: 5.2; 1.2-23.7), and high RSV season (9/14, 64.3%; OR: 4.4; 1.4-13.3) were associated with RSV mortality. In multivariable logistic regression analysis, respiratory symptoms (OR: 6.6; 95% CI: 1.3-32.5), RSV seasonality (6.1; 1.8-20.4), and age (9.2; 2.6-33.1) were significant predictors of RSV-associated mortality.Conclusions: RSV has a significant mortality burden in early infancy in Karachi, Pakistan. Age, RSV seasonality, and respiratory symptoms were significant predictors of RSV-associated mortality. Our findings have implications for clinical management of young infants with cold-like symptoms, policy development, and research regarding maternal immunization against RSV during pregnancy, in resource-constrained, low-income, and vaccine-hesitant populations

A Fully Automated and Explainable Algorithm for the Prediction of Malignant Transformation in Oral Epithelial Dysplasia

Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. Its grading suffers from significant inter-/intra- observer variability, and does not reliably predict malignancy progression, potentially leading to suboptimal treatment decisions. To address this, we developed a novel artificial intelligence algorithm that can assign an Oral Malignant Transformation (OMT) risk score, based on histological patterns in the in Haematoxylin and Eosin stained whole slide images, to quantify the risk of OED progression. The algorithm is based on the detection and segmentation of nuclei within (and around) the epithelium using an in-house segmentation model. We then employed a shallow neural network fed with interpretable morphological/spatial features, emulating histological markers. We conducted internal cross-validation on our development cohort (Sheffield; n = 193 cases) followed by independent validation on two external cohorts (Birmingham and Belfast; n = 92 cases). The proposed OMTscore yields an AUROC = 0.74 in predicting whether an OED progresses to malignancy or not. Survival analyses showed the prognostic value of our OMTscore for predicting malignancy transformation, when compared to the manually-assigned WHO and binary grades. Analysis of the correctly predicted cases elucidated the presence of peri-epithelial and epithelium-infiltrating lymphocytes in the most predictive patches of cases that transformed (p < 0.0001). This is the first study to propose a completely automated algorithm for predicting OED transformation based on interpretable nuclear features, whilst being validated on external datasets. The algorithm shows better-than-human-level performance for prediction of OED malignant transformation and offers a promising solution to the challenges of grading OED in routine clinical practice

Development and validation of a multivariable model for prediction of malignant transformation and recurrence of oral epithelial dysplasia

Background: Oral epithelial dysplasia (OED) is the precursor to oral squamous cell carcinoma which is amongst the top ten cancers worldwide. Prognostic significance of conventional histological features in OED is not well established. Many additional histological abnormalities are seen in OED, but are insufficiently investigated, and have not been correlated to clinical outcomes. Methods: A digital quantitative analysis of epithelial cellularity, nuclear geometry, cytoplasm staining intensity and epithelial architecture/thickness is conducted on 75 OED whole-slide images (252 regions of interest) with feature-specific comparisons between grades and against non-dysplastic/control cases. Multivariable models were developed to evaluate prediction of OED recurrence and malignant transformation. The best performing models were externally validated on unseen cases pooled from four different centres (n = 121), of which 32% progressed to cancer, with an average transformation time of 45 months. Results: Grade-based differences were seen for cytoplasmic eosin, nuclear eccentricity, and circularity in basal epithelial cells of OED (p &lt; 0.05). Nucleus circularity was associated with OED recurrence (p = 0.018) and epithelial perimeter associated with malignant transformation (p = 0.03). The developed model demonstrated superior predictive potential for malignant transformation (AUROC 0.77) and OED recurrence (AUROC 0.74) as compared with conventional WHO grading (AUROC 0.68 and 0.71, respectively). External validation supported the prognostic strength of this model. Conclusions: This study supports a novel prognostic model which outperforms existing grading systems. Further studies are warranted to evaluate its significance for OED prognostication.</p

Seasonal effects on reconciliation in Macaca Fuscata Yakui

Dietary composition may have profound effects on the activity budgets, levelof food competition, and social behavior of a species. Similarly, in seasonally breeding species, the mating season is a period in which competition for mating partners increases, affecting amicable social interactions among group members. We analyzed the importance of the mating season and of seasonal variations in dietary composition and food competition on econciliation in wild female Japanese macaques (Macaca fuscata yakui) on Yakushima Island, Japan. Yakushima macaques are appropriate subjects because they are seasonal breeders and their dietary composition significantly changes among the seasons. Though large differences occurred between the summer months and the winter and early spring months in activity budgets and the consumption of the main food sources, i.e., fruits, seeds, and leaves, the level of food competition and conciliatory tendency remained unaffected. Conversely,conciliatory tendency is significantly lower during the mating season than in the nonmating season. Moreover, conciliatory tendency is lower when 1 or both female opponents is in estrous than when they are not. Thus the mating season has profound effects on reconciliation, whereas seasonal changes in activity budgets and dietary composition do not. The detrimental effects of the mating season on female social relationships and reconciliation may be due to the importance of female competition for access to male partners in multimale, multifemale societies

Do Fruit Nutrients Affect Subgrouping Patterns in Wild Spider Monkeys (Ateles geoffroyi)?

One of the main costs of group living is feeding competition. Fission–fusion dynamics are thought to be a strategy to avoid overt competition for food resources. We tested whether food abundance and quality affected such dynamics in a species characterized by a high degree of fission–fusion dynamics. We collected data on 22 adult and subadult spider monkeys (Ateles geoffroyi) living in a large community in the protected area of Otoch Ma’ax Yetel Kooh, Yucatan, Mexico. We recorded subgroup size and fission events as well as fruit abundance during 12 mo and conducted nutritional analyses on the fruit species that the study subjects consumed most. We found no effect of fruit abundance or nutritional quality of recently visited food patches on individual fission decisions, but the amount of protein in the food patches visited over the course of the day was a good predictor of subgroup size. While the absence of support for a relationship between fruit characteristics and fission decisions may be due to the short temporal scale of the analysis, our findings relating subgroup size to the amount of protein in the visited food patches over the course of the day may be explained by individual spider monkeys attempting to obtain sufficient protein intake from their fruit-based diet. © 2016 Springer Science+Business Media New Yor

Multiomic analyses implicate a neurodevelopmental program in the pathogenesis of cerebral arachnoid cysts

Cerebral arachnoid cysts (ACs) are one of the most common and poorly understood types of developmental brain lesion. To begin to elucidate AC pathogenesis, we performed an integrated analysis of 617 patient-parent (trio) exomes, 152,898 human brain and mouse meningeal single-cell RNA sequencing transcriptomes and natural language processing data of patient medical records. We found that damaging de novo variants (DNVs) were highly enriched in patients with ACs compared with healthy individuals (P = 1.57 × 10-33). Seven genes harbored an exome-wide significant DNV burden. AC-associated genes were enriched for chromatin modifiers and converged in midgestational transcription networks essential for neural and meningeal development. Unsupervised clustering of patient phenotypes identified four AC subtypes and clinical severity correlated with the presence of a damaging DNV. These data provide insights into the coordinated regulation of brain and meningeal development and implicate epigenomic dysregulation due to DNVs in AC pathogenesis. Our results provide a preliminary indication that, in the appropriate clinical context, ACs may be considered radiographic harbingers of neurodevelopmental pathology warranting genetic testing and neurobehavioral follow-up. These data highlight the utility of a systems-level, multiomics approach to elucidate sporadic structural brain disease

Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative (GENFI) cohort

Abstract Biomarkers that can predict disease progression in individuals with genetic frontotemporal dementia are urgently needed. We aimed to identify whether baseline MRI-based grey and white matter abnormalities are associated with different clinical progression profiles in presymptomatic mutation carriers in the GENetic Frontotemporal dementia Initiative. 387 mutation carriers were included (160 GRN, 160 C9orf72, 67 MAPT), together with 240 non-carrier cognitively normal controls. Cortical and subcortical grey matter volumes were generated using automated parcellation methods on volumetric 3 T T1-weighted MRI scans, while white matter characteristics were estimated using diffusion tensor imaging. Mutation carriers were divided into two disease stages based on their global CDR®+NACC-FTLD score: presymptomatic (0 or 0.5) and fully symptomatic (1 or greater). W-scores in each grey matter volumes and white matter diffusion measures were computed to quantify the degree of abnormality compared to controls for each presymptomatic carrier, adjusting for their age, sex, total intracranial volume, and scanner type. Presymptomatic carriers were classified as “normal” or “abnormal” based on whether their grey matter volume and white matter diffusion measure w-scores were above or below the cut point corresponding to the 10th percentile of the controls. We then compared the change in disease severity between baseline and one year later in both the “normal” and “abnormal” groups within each genetic subtype, as measured by the CDR®+NACC-FTLD sum-of-boxes score and revised Cambridge Behavioural Inventory total score. Overall, presymptomatic carriers with normal regional w-scores at baseline did not progress clinically as much as those with abnormal regional w-scores. Having abnormal grey or white matter measures at baseline was associated with a statistically significant increase in the CDR®+NACC-FTLD of up to 4 points in C9orf72 expansion carriers, and 5 points in the GRN group as well as a statistically significant increase in the revised Cambridge Behavioural Inventory of up to 11 points in MAPT, 10 points in GRN, and 8 points in C9orf72 mutation carriers. Baseline regional brain abnormalities on MRI in presymptomatic mutation carriers are associated with different profiles of clinical progression over time. These results may be helpful to inform stratification of participants in future trials