Notes

Electrochemical lowering of fluoroalkyl sulfones for radical fluoroalkylation regarding alkenes.
Whilst much attention is given to eliminating HIV mother-to-child transmission (MTCT), little has been done to ensure the same for hepatitis B virus (HBV) transmission. The introduction of HBV immunization at six weeks of age has reduced HBV horizontal transmission in South Africa. However, in order to eliminate HBV MTCT, further interventions are needed. The risk of hepatitis C virus (HCV) MTCT in HIV-infected (HIV+) African women is not yet well described. This study aimed to determine the rate of HBV and HCV vertical transmission in HIV-exposed infants in South Africa.

Serum samples from infants enrolled in an isoniazid prevention study (P1041) were screened for HBV and HCV serology markers; screening was performed on samples collected at approximately 60 weeks of age of the infants. HBV DNA was quantified in HBsAg positive samples and HBV strains characterized through gene sequencing. All HCV antibody samples with inconclusive results underwent molecular testing.

Three of 821 infants were positive for both HBsAg and HBV DNA. All HBV strains belonged to HBV sub-genotype A1. The rtM204I mutation associated with lamivudine resistance was identified in one infant, a second infant harboured the double A1762T/G1764A BCP mutation. Phylogenetic analysis showed clustering between mother and infant viral genomic sequences. Twenty-one of 821 HIV-exposed infants tested had inconclusive HCV antibody results, none were HCV PCR positive.

This study suggests that HBV vertical transmission is likely to be occurring in HIV-exposed infants in South Africa.. A more robust strategy of HBV prevention, including birth dose vaccination, is required to eradicate HBV MTCT. HCV infection was not detected.
This study suggests that HBV vertical transmission is likely to be occurring in HIV-exposed infants in South Africa.. A more robust strategy of HBV prevention, including birth dose vaccination, is required to eradicate HBV MTCT. HCV infection was not detected.
Clinical studies found that medication for attention-deficit/hyperactivity disorder (ADHD) is effective in coexisting autism spectrum disorder (ASD), but current research is based on small clinical studies mainly performed on children or adolescents. We here use register data to examine if individuals with ADHD and coexisting ASD present differences in the prescribing patterns of ADHD medication when compared to individuals with pure ADHD.

Data with information on filled prescriptions and diagnoses was retrieved from the Swedish Prescribed Drug Register and the National Patient Register. We identified 34,374 individuals with pure ADHD and 5012 individuals with ADHD and coexisting ASD, aged between 3 and 80 years. The first treatment episode with ADHD medications (≥ 2 filled prescriptions within 90 days) and daily doses of methylphenidate during a 3-year period was measured. Odds ratios (ORs) were calculated for the likelihood of being prescribed ADHD medication in individuals with and without ASD and Wilcls with or without ASD. If these differences are due to different medication responses in ASD or due to other factors such as clinicians' perceptions of medication effects in patients with ASD, needs to be further studied.
Sudden death in epilepsy (SUDEP) is a rare disease in US, however, they account for 8-17% of deaths in people with epilepsy. This disease involves complicated physiological patterns and it is still not clear what are the physio-/bio-makers that can be used as an indicator to predict SUDEP so that care providers can intervene and treat patients in a timely manner. For this sake, UTHealth School of Biomedical Informatics (SBMI) organized a machine learning Hackathon to call for advanced solutions https//sbmi.uth.edu/hackathon/archive/sept19.htm .

In recent years, deep learning has become state of the art for many domains with large amounts data. Although healthcare has accumulated a lot of data, they are often not abundant enough for subpopulation studies where deep learning could be beneficial. Taking these limitations into account, we present a framework to apply deep learning to the detection of the onset of slow activity after a generalized tonic-clonic seizure, as well as other EEG signal detection problems exhibiting data paucity.

We conducted ten training runs for our full method and seven model variants, statistically demonstrating the impact of each technique used in our framework with a high degree of confidence.

Our findings point toward deep learning being a viable method for detection of the onset of slow activity provided approperiate regularization is performed.
Our findings point toward deep learning being a viable method for detection of the onset of slow activity provided approperiate regularization is performed.
Sudden Unexpected Death in Epilepsy (SUDEP) has increased in awareness considerably over the last two decades and is acknowledged as a serious problem in epilepsy. However, the scientific community remains unclear on the reason or possible bio markers that can discern potentially fatal seizures from other non-fatal seizures. The duration of postictal generalized EEG suppression (PGES) is a promising candidate to aid in identifying SUDEP risk. selleck kinase inhibitor The length of time a patient experiences PGES after a seizure may be used to infer the risk a patient may have of SUDEP later in life. However, the problem becomes identifying the duration, or marking the end, of PGES (Tomson et al. in Lancet Neurol 7(11)1021-1031, 2008; Nashef in Epilepsia 386-8, 1997).

This work addresses the problem of marking the end to PGES in EEG data, extracted from patients during a clinically supervised seizure. This work proposes a sensitivity analysis on EEG window size/delay, feature extraction and classifiers along with associated hyperps to be able to predict a patient's SUDEP risk.
In recent decades, the prevalence of chronic diseases in children and adolescents has increased significantly. Contextual factors play a central role in the self-regulation of chronic diseases. They influence illness and treatment representations, disease management, and health outcomes. While previous studies have investigated the influence of contextual factors on children's beliefs about their illness, little is known about subjective contextual factors of treatment representations of children and adolescents with chronic diseases, especially in the context of rehabilitation. Therefore, the aim of this qualitative analysis was to examine the contextual factors reported by chronically ill children and adolescents in relation to their treatment representations. Furthermore, we aimed to assign the identified themes to classifications of environmental and personal contextual factors in the context of the International Classification of Functioning, Disability and Health (ICF).

Between July and September 2018, semi-structured interviews were conducted with N = 13 children and adolescents in rehabilitation to explore their rehab-related treatment representations and associated contextual factors.
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