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The affected mango genes include those with potential economic importance such as 6945 genes for defense/resistance/immune response, 323 genes for fruit development, and 338 genes for anthocyanin production.

To date, this is the first sequencing effort to comprehensively analyze genome-wide variants essential for the development of genome-wide markers specific to these mango species native to the Philippines. This study provides an important genomic resource that can be used for the genetic improvement of mangoes.

To date, this is the first sequencing effort to comprehensively analyze genome-wide variants essential for the development of genome-wide markers specific to these mango species native to the Philippines. This study provides an important genomic resource that can be used for the genetic improvement of mangoes.

To compare differences in choriocapillaris flow deficit (CC FD) in multifocal choroiditis (MFC) between two treatment arms using optical coherence tomography angiography (OCTA).

In this prospective randomized clinical trial, patients were randomized to either Group 1 which received standard tapering dose of oral corticosteroids, or Group 2 which received additional dexamethasone implant (or intravitreal methotrexate). The patients were followed-up until 12 weeks using OCTA and other imaging tools. CC FD and visual acuity between the two groups were compared at each visit.

Twenty-five subjects (17 males; 25 eyes) were studied (11 eyes in Group 1). There were no differences between the visual acuity or CC FD (1.12 versus 1.08 mm

 ; p = 0.86) at baseline between the groups. However, patients in Group 2 achieved better visual acuity (0.32 ± 0.23 versus 0.15 ± 0.11; p = 0.025) and CC FD (0.54 versus 0.15 mm

 ; p = 0.008) at 12 weeks.

OCTA is a useful tool in monitoring the CC FD recovery after treatment in MFC. Patients receiving intravitreal corticosteroid/methotrexate in addition to systemic corticosteroid showed greater resolution of CC FD on OCTA compared to those receiving only oral corticosteroids.

OCTA is a useful tool in monitoring the CC FD recovery after treatment in MFC. Patients receiving intravitreal corticosteroid/methotrexate in addition to systemic corticosteroid showed greater resolution of CC FD on OCTA compared to those receiving only oral corticosteroids.

Little is known about the perceived impact of the COVID-19 pandemic and subsequent lockdown measures on young patients with tic disorders. Previous studies focused on clinician and parent ratings of tic severity, whereas the only international self-report data are available for adult populations. We present the first findings from a case-control study on children and adolescents with tics during lockdown in Italy.

We surveyed 49 patients aged 6-18years and 245 matched controls with a newly developed questionnaire covering socio-demographic and clinical data, as well as lockdown-related changes to daily life activities.

About half (53.2%) of the Italian school-age patients who took part in our survey experienced changes in tic severity during lockdown. Perceived increases in tic severity (29.8%) were reported more often than decreases (23.4%). selleck products Analogous trends were reported for perceived restlessness and, more significantly, irritability, whereas changes in pain symptoms were less common and were similar in both directions. The presence of tics was associated with increased difficulties with remote learning (p = 0.01), but decreased feelings of missing out on social interactions with schoolmates (p = 0.03).

Self-reported data on the impact of COVID-19 lockdown in school-age patients with tic disorders indicate perceived changes in tic severity, as well as restlessness and irritability, in about half of the cases. These findings could guide both clinicians and teachers in the implementation of targeted adjustments in the delivery of care and educational strategies, respectively.

Self-reported data on the impact of COVID-19 lockdown in school-age patients with tic disorders indicate perceived changes in tic severity, as well as restlessness and irritability, in about half of the cases. These findings could guide both clinicians and teachers in the implementation of targeted adjustments in the delivery of care and educational strategies, respectively.

Wilson's disease (WD) is a genetic disorder with pathological copper accumulation and associated clinical symptoms in various organs, particularly the liver and brain. Neurological disease is assessed with the clinical Unified Wilson's Disease Rating Scale (UWDRS). There is a lack of quantitative objective markers evaluating brain involvement. Recently, a semiquantitative brain magnetic resonance imaging (MRI) scale has been proposed, which combines acute toxicity and chronic damage measures into a total score. The relationship between MRI brain pathology and the MRI scale with disease form and neurological severity was studied in a large cohort.

We retrospectively assessed 100 newly diagnosed treatment-naïve patients with WD with respect to brain MRI pathology and MRI scores (acute toxicity, chronic damage, and total) and analyzed the relationship with disease form and UWDRS part II (functional impairment) and part III (neurological deficits) scores.

Most patients had the neurological form of WD (55%) followed by hepatic (31%) and presymptomatic (14%). MRI examination revealed WD-typical abnormalities in 56% of patients, with higher pathology rates in neurological cases (83%) than in hepatic (29%) and presymptomatic (7%) cases. UWDRS part II and III scores correlated with the MRI acute toxicity score (r = 0.55 and 0.55, respectively), chronic damage score (r = 0.39 and 0.45), and total score (0.45 and 0.52) (all P < 0.01).

Brain MRI changes may be present even in patients without neurological symptoms, although not frequently. The semiquantitative MRI scale correlated with the UWDRS and appears to be a complementary tool for severity of brain injury assessment in WD patients.

Brain MRI changes may be present even in patients without neurological symptoms, although not frequently. The semiquantitative MRI scale correlated with the UWDRS and appears to be a complementary tool for severity of brain injury assessment in WD patients.

Post-ChAdOx1 vaccine (AZD1222) adverse events following immunization (AEFI) are uncommon. Recently described neurological events include thrombocytopenia with thrombosis syndrome (TTS) with cerebral venous thrombosis and Guillain-Barré syndrome. There are very few AEFI reports following COVID vaccination from India, because of underreporting or other factors. A few cases of acute transverse myelitis (ATM) and post-vaccinal encephalitis have also been reported.

Over 11months, in 2 districts of Kerala, India, 8.19 million people were vaccinated with the ChAdOx1 vaccine.

During this period, we encountered five cases of autoimmune central nervous system (CNS) AEFI following ChAdOX1 (Oxford/AstraZeneca, Covishield™) vaccination. These included three cases of acute disseminated encephalomyelitis (ADEM), one case of opsoclonus myoclonus ataxia syndrome (OMAS), and one case of limbic encephalitis. The calculated crude incidence of post-ChAdOX1 autoimmune CNS AEFI was approximately 0.24 cases per million for encephalitis and 0.36 per million for ADEM. This was compared to the crude annual incidence of community-acquired ADEM worldwide (3.2-4 per million) and the crude annual incidence of community-acquired encephalitis in India (8.35-10 per million).

There was no increase in the incidence of post-vaccination CNS AEFI (ADEM or encephalitis) as compared to the community incidence of ADEM or encephalitis. While this emphasizes the safety of ChAdOX1 nCoV-19 vaccination for COVID-19, it is important to recognize these post-vaccination autoimmune syndromes early to initiate immunosuppressive therapy.

There was no increase in the incidence of post-vaccination CNS AEFI (ADEM or encephalitis) as compared to the community incidence of ADEM or encephalitis. While this emphasizes the safety of ChAdOX1 nCoV-19 vaccination for COVID-19, it is important to recognize these post-vaccination autoimmune syndromes early to initiate immunosuppressive therapy.

Methyl CpG binding protein 2 (MeCP2) is essential for the normal function of mature neurons. Mutations in the MECP2 gene are the main cause of Rett syndrome (RTT). Gene mutations have been identified throughout the gene and the mutation effect is mainly correlated with its type and location.

In this study, a series of in silico algorithms were applied for analyzing the functional consequences of 3 novel gene missense mutations (D121A, S359Y, and P403S) and a rarely reported one with suspicious effect (R133H) on RettBASE. Besides, a ROC curve analysis was performed to investigate the critical factors affecting variant pathogenicity.

(1) The ROC curve analysis for a retrieved set of MeCP2 variants showed that physicochemical characters do not significantly affect variant pathogenicity; (2) PREM PDI tool revealed that both D121A and R133H mainly contribute to disease progression via reducing MeCP2 affinity to DNA; (3) GPS v5.0 software indicated that P403S may correlate with altered protein phosphorylation; however, no defective protein interaction has been already documented. (4) The applied computational algorithms failed to explore any informative pathogenic mechanism for the S359Y variant.

The conducted approach might provide an efficient prediction model for the effect of MECP2 variants that are located in MBD and CTD.

The conducted approach might provide an efficient prediction model for the effect of MECP2 variants that are located in MBD and CTD.Robust estimation of exposure response analysis relies on correct specification of the model structure with traditional parametric approach. However, the assumptions of the handcrafted model may not always hold or verifiable. Here, we conducted a simulation study to assess the performance of machine learning-based techniques in exposure-response (E-R) analysis where data were generated by a complicated nonlinear system under one dose level. Two analysis options involving machine learning were evaluated. The first option was based on marginal structural model with inverse probability weighting, where machine learning (ML) was employed to improve the performance of propensity score estimation. The simulation results showed that propensity score predicted by ML was more robust than traditional multinomial logistic regression in terms of adjusting the confounding effects and unbiasedly estimating the E-R relationship. The second option estimated the E-R relationship by employing artificial neural network as a universal function approximator to the data generating mechanism, without the requirement of accurately hand-crafting the whole simulation system. The results demonstrated that the trained network was able to correctly predict the treatment effects across a certain range of adjacent dose levels. In contrast, traditional regression provided biased predictions, even when all confounders were included in the model. Our study demonstrated that ML may serve as a powerful tool for pharmacometrics analysis with its prediction flexibility in a nonlinear system and its capacity of approximating the ground truth.