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al or paternal exposure to TFL when compared with the general population. However, the sample was too small to draw firm conclusions.

Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune inflammatory disorder that causes significant changes in brain connectivity and visual impairment. Degree centrality (DC), a graph-based assessment of network organization was performed to explore the connectivity changes in NMOSD patients and their correlation with clinical consequences.

Twenty-two NMOSD patients and 22 healthy controls (HC) were included. Participants underwent visual acuity examination and resting-state functional magnetic resonance imaging (fMRI) of the brain. We first performed DC analysis to identify voxels that showed changes in whole-brain functional connectivity (FC) with other voxels. DC was calculated by the fMRI graph method and comparison between the two groups was done by two-sample t-test. GraphPad Prism was used to assess the association between DC changes and clinical consequences.

Out of the 22 NMOSD patients, 7 (31.82%) had ON once while 15 (68.18%) had ON twice or more. Decreased DC value (P<0.001) in the left frontal superior orbital gyrus (ORBsup), left angular gyrus (ANG) and right parietal superior gyrus (SPG) was found in NMOSD patients when compared with healthy controls respectively. Reduced visual acuity significantly correlated (R

=0.212, P=0.040) with DC values in SPG while the frequency of ON significantly correlated (R

=0.04, P=0.040) with DC values in the ANG in NMOSD patients.

NMOSD patients experience neural network dysfunction which may be associated with their clinical implications.

NMOSD patients experience neural network dysfunction which may be associated with their clinical implications.Over the past few decades, in silico modeling of organ systems has significantly furthered our understanding of their physiology and biomechanical function. In spite of the relative importance of the digestive system in normal functioning of the human body, there is a scarcity of high-fidelity models for the upper gastrointestinal tract including the esophagus and the stomach. In this work, we present a detailed numerical model of the upper gastrointestinal tract that not only accounts for the fiber architecture of the muscle walls, but also the multiphasic components they help transport during normal digestive function. Construction details for 3D models of representative stomach geometry are presented along with a simple strategy for assigning circular and longitudinal muscle fiber orientations for each layer. We developed a fully resolved model of the stomach to simulate gastric peristalsis by systematically activating muscle fibers embedded in the stomach. Following this, for the first time, we simulate gravity-driven bolus emptying into the stomach due to density differences between ingested contents and fluid contents of the stomach. Finally, we present a case of retrograde flow of fluid from the stomach into the esophagus, resembling the phenomenon of acid reflux. 1-Methylnicotinamide This detailed computational model of the upper gastrointestinal tract provides a foundation for future models to investigate the biomechanics of acid reflux and probe various strategies for gastric bypass surgeries to address the growing problem of obesity.Sleep is imperative for a healthy life as it rejuvenates memory, cognitive performance, cell repair and eliminates waste from the muscles. Sleep-related disorders such as insomnia, narcolepsy, sleep-disordered breathing (SDB), periodic leg movement (PLM), and bruxism lead to hormonal imbalance, slower reaction time, memory problems, depression, and headaches. This adversity of sleep disorder gained the attention of many sleep researchers. To examine the reasons for sleep disorders, it is imperative to monitor and analyze the sleep of the affected patients. The conventional method of monitoring sleep and identifying the sleep disorders using polysomnographic (PSG) recording is a complicated and cumbersome task in which multiple physiological signals with multiple modalities are recorded for a long (overnight) duration. The PSG recordings are carried out in sophisticated sleep laboratories and cannot be considered suitable for real-time sleep monitoring. Thus, a simple and patient-convenient system is highly dedeployed in a portable home-based environment to identify the type of sleep disorders automatically.Continuous ambulatory cardiac monitoring plays a critical role in early detection of abnormality in at-risk patients, thereby increasing the chance of early intervention. In this study, we present an automated ECG classification approach for distinguishing between healthy heartbeats and pathological rhythms. The proposed lightweight solution uses quantized one-dimensional deep convolutional neural networks and is ideal for real-time continuous monitoring of cardiac rhythm, capable of providing one output prediction per second. Raw ECG data is used as the input to the classifier, eliminating the need for complex data preprocessing on low-powered wearable devices. In contrast to many compute-intensive approaches, the data analysis can be carried out locally on edge devices, providing privacy and portability. The proposed lightweight solution is accurate (sensitivity of 98.5% and specificity of 99.8%), and implemented on a smartphone, it is energy-efficient and fast, requiring 5.85 mJ and 7.65 ms per prediction, respectively.

The purpose of this study was to identify individual characteristics that are associated with communicative participation after total laryngectomy (TL).

This study was a single-institution investigation of individuals who had undergone TL. Data were collected at a single timepoint via patient self-report and medical record review. Thirty-five participants completed a questionnaire containing a communication survey as well as several published, validated instruments. Independent variables included characteristics related to demographics, health and medical history, social network composition, and communication. The dependent variable was communicative participation, which was assessed using the Communicative Participation Item Bank (CPIB). Correlations between the independent variables and CPIB scores were calculated to assess the influence of these characteristics on communicative participation. The study participants were subdivided into three distinct groups based on whether their primary method of commTL did not demonstrate worse communicative participation than those using spoken methods. Surprisingly, CPIB scores did not decline as a result of social distancing.

Young, nonstuttering children around the world have been shown to hold negative stuttering attitudes characterized by limited knowledge about stuttering and how to be a helpful listener. Educational programming using the Attitude Change & Tolerance program (Weidner, 2015, InterACT) has shown promise in improving American children's stuttering attitudes (Weidner, St. Louis, & Glover, 2018), but the utility of the program in other countries is unknown. The purpose of this study was to examine the efficacy of the InterACT program among nonstuttering Polish children.

This study was a replication of Weidner etal. (2018). Participants included 43 nonstuttering preschool and first grade Polish children. Children's stuttering attitudes were measured using the Public Opinion Survey of Human Attributes-Stuttering/Child (Weidner & St. Louis, 2014) before and after participating in the Polish translation of the InterACT program.

Pre-post results showed statistically significant improvements in children's overall stuttering attitudes. Most notably, children became more knowledgeable about how to be a supportive listener.

This study provides further evidence that young children worldwide have uninformed or negative stuttering attitudes, which are amenable to improvement. It also provides support for the translatability and cultural relevance of the InterACT program.

This study provides further evidence that young children worldwide have uninformed or negative stuttering attitudes, which are amenable to improvement. It also provides support for the translatability and cultural relevance of the InterACT program.

Corpus callosotomy is a palliative surgical procedure for patients with drug-resistant epilepsy and suffering from drop attacks, which are a source of major deterioration in quality of life and can be responsible for severe traumatic injury. The objective of this study is to identify clinical markers that would predict a better outcome in terms of drop attacks and other types of epileptic seizures.

We reviewed a retrospective series of children who underwent complete corpus callosotomy at our institution, between January 1998 and February 2019. We analyzed the neurological and cognitive pre- and postoperative status, radiological datas, and electroencephalography (EEG) monitoring data.

Fifty children underwent a complete callosotomy at a mean age of 7.5 years. The median postoperative follow-up was 42.5 months. Forty-one patients (82%) had a favorable outcome, 29 (58%) of them becoming totally free of drop attacks. Statistical analysis of correlation between outcome of drop attacks and the characteristi epileptic drop attacks. Aside from a better surgical outcome for children with tonic seizures causing the falls, the lack of any other significant prognostic factor implies that no patient should a priori be excluded from this palliative surgical indication.

There are contradictory data on differential effect of docetaxel based on BMI in patients with breast and prostate cancer. We performed an exploratory analysis to determine if the benefit of docetaxel in patients with metastatic castration-resistant prostate cancer (mCRPC) is modified by BMI.

We performed a post hoc analysis of the data retrieved from the ENTHUSE M1C study. BMI (kg/m

) was categorized as 18.5 to <25 as lean; 25 to <30 as overweight; and ≥30 as obese. Cox regression models were constructed to determine the impact of BMI on progression-free survival (PFS) and overall survival (OS).

A total of 466 patients were eligible for the current analysis. The median PFS was 7.3, 7.7 and 8.4 months (hazard ratio [HR], 0.92; 95% confidence interval [CI], 0.81 to 1.06; P=0.261) in lean, overweight and obese patients. The median OS was 16.6, 20.1 and 21.4 months (HR, 0.75; 95% CI, 0.63 to 0.89; P=0.002) for lean, overweight and obese patients. After adjusting for baseline and tumor characteristics, there was no association of BMI with PFS (overweight, HR, 0.89; 95% CI, 0.71 to 1.13; P=0.353; obese, HR, 0.86; 95% CI, 0.66 to 1.13; P=0.277) while overweight (HR, 0.68; 95% CI, 0.51 to 0.89; P=0.006) and obese (HR, 0.59; 95% CI, 0.41 to 0.83; P=0.003) patients had significantly better OS compared with lean patients.

There was no effect of BMI on PFS in patients with mCRPC receiving docetaxel. Interestingly, overweight and obese patients had a longer OS compared with lean patients, which is in contradiction to a recent study in breast cancer; and warrants further investigation.

There was no effect of BMI on PFS in patients with mCRPC receiving docetaxel. Interestingly, overweight and obese patients had a longer OS compared with lean patients, which is in contradiction to a recent study in breast cancer; and warrants further investigation.