Long-term monitoring of outdoor natural gamma absorbed dose rate in air in Bengaluru, Karnataka, India.

This research forms a part of the comprehensive Indian Environmental Radiation Monitoring Network program, focusing on the continuous measurement of absorbed dose rate in outdoor air due to natural gamma radiation (cosmic and terrestrial) in Bengaluru, Karnataka, India. Over the course of a decade (2013-2023), data were collected from 41 monitoring locations in the city using permanently field-installed Geiger-Mueller detector-based environmental radiation monitors. This paper presents an analysis of the extensive long-term monitoring results. The mean absorbed gamma dose rate in outdoor air across the monitoring locations ranged from 84 ± 9 to 156 ± 4 nGy.h-1, with a calculated mean value of 124 ± 15 nGy.h-1. The estimated mean annual effective dose due to outdoor natural gamma radiation varied from 0.10 ± 0.01 to 0.19 ± 0.01 mSv.y-1, with an overall mean of 0.15 ± 0.02 mSv.y-1.

Brief webcam test of hand movements predicts episodic memory, executive function, and working memory in a community sample of cognitively asymptomatic older adults.

INTRODUCTION: Low-cost simple tests for preclinical Alzheimer's disease are a research priority. We evaluated whether remote unsupervised webcam recordings of finger-tapping were associated with cognitive performance in older adults. METHODS: A total of 404 cognitively-asymptomatic participants (64.6 [6.77] years; 70.8% female) completed 10-second finger-tapping tests (Tasmanian [TAS] Test) and cognitive tests (Cambridge Neuropsychological Test Automated Battery [CANTAB]) online at home. Regression models including hand movement features were compared with null models (comprising age, sex, and education level); change in Akaike Information Criterion greater than 2 (ΔAIC > 2) denoted statistical difference. RESULTS: Hand movement features improved prediction of episodic memory, executive function, and working memory scores (ΔAIC > 2). Dominant hand features outperformed nondominant hand features for episodic memory (ΔAIC = 2.5), executive function (ΔAIC = 4.8), and working memory (ΔAIC = 2.2). DISCUSSION: This brief webcam test improved prediction of cognitive performance compared to age, sex, and education. Finger-tapping holds potential as a remote language-agnostic screening tool to stratify community cohorts at risk for cognitive decline.

Exercise-Related Physical Activity Relates to Brain Volumes in 10,125 Individuals.

BACKGROUND: The potential neuroprotective effects of regular physical activity on brain structure are unclear, despite links between activity and reduced dementia risk. OBJECTIVE: To investigate the relationships between regular moderate to vigorous physical activity and quantified brain volumes on magnetic resonance neuroimaging. METHODS: A total of 10,125 healthy participants underwent whole-body MRI scans, with brain sequences including isotropic MP-RAGE. Three deep learning models analyzed axial, sagittal, and coronal views from the scans. Moderate to vigorous physical activity, defined by activities increasing respiration and pulse rate for at least 10 continuous minutes, was modeled with brain volumes via partial correlations. Analyses adjusted for age, sex, and total intracranial volume, and a 5% Benjamini-Hochberg False Discovery Rate addressed multiple comparisons. RESULTS: Participant average age was 52.98±13.04 years (range 18-97) and 52.3% were biologically male. Of these, 7,606 (75.1%) reported engaging in moderate or vigorous physical activity approximately 4.05±3.43 days per week. Those with vigorous activity were slightly younger (p < 0.00001), and fewer women compared to men engaged in such activities (p = 3.76e-15). Adjusting for age, sex, body mass index, and multiple comparisons, increased days of moderate to vigorous activity correlated with larger normalized brain volumes in multiple regions including: total gray matter (Partial R = 0.05, p = 1.22e-7), white matter (Partial R = 0.06, p = 9.34e-11), hippocampus (Partial R = 0.05, p = 5.96e-7), and frontal, parietal, and occipital lobes (Partial R = 0.04, p≤1.06e-5). CONCLUSIONS: Exercise-related physical activity is associated with increased brain volumes, indicating potential neuroprotective effects.

Monitoring of outdoor natural gamma absorbed dose rate in air in Hyderabad, Telangana, India.

The Indian Environmental Radiation Monitoring Network continuously monitors the outdoor natural gamma absorbed dose rate in air at different locations throughout India by employing Geiger-Mueller (GM) detector-based field-installed environmental radiation monitors (ERMs). Hyderabad, Telangana, India is known to have high natural background radiation levels due to the presence of high concentrations of primordial radionuclides in its granitic rocks. There are a total of 59 ERMs installed at various locations across Hyderabad. Long-term monitoring data of these locations are presented in this paper. The mean values of outdoor natural gamma absorbed dose rate in air at the monitoring locations were found to vary in the range of 104-258 nGy.h-1 with a mean of 193 ± 40 nGy.h-1. The mean annual effective dose due to outdoor natural gamma radiation was estimated to be 0.24 ± 0.05 mSv.y-1. Analysis of the long-term seasonal variation of outdoor natural gamma absorbed dose rate in air showed that the same was lowest during monsoons.

Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals.

Abdominal fat is increasingly linked to brain health. A total of 10,001 healthy participants were scanned on 1.5T MRI with a short whole-body MR imaging protocol. Deep learning with FastSurfer segmented 96 brain regions. Separate models segmented visceral and subcutaneous abdominal fat. Regression analyses of abdominal fat types and normalized brain volumes were evaluated, controlling for age and sex. Logistic regression models determined the risk of brain total gray and white matter volume loss from the highest quartile of visceral fat and lowest quartile of these brain volumes. This cohort had an average age of 52.9 ± 13.1 years with 52.8% men and 47.2% women. Segmented visceral abdominal fat predicted lower volumes in multiple regions including: total gray matter volume (r = -.44, p<.001), total white matter volume (r =-.41, p<.001), hippocampus (r = -.39, p< .001), frontal cortex (r = -.42, p<.001), temporal lobes (r = -.44, p<.001), parietal lobes (r = -.39, p<.001), occipital lobes (r =-.37, p<.001). Women showed lower brain volumes than men related to increased visceral fat. Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 5.9; age 40-59, OR = 5.4; 60-80, OR = 5.1) and low white matter volume: (age 20-39: OR = 3.78; age 40-59, OR = 4.4; 60-80, OR = 5.1). Higher subcutaneous fat is related to brain volume loss. Elevated visceral and subcutaneous fat predicted lower brain volumes and may represent novel modifiable factors in determining brain health.

Countrywide monitoring of absorbed dose rate in air due to outdoor natural gamma radiation in India.

The Indian Environmental Radiation Monitoring Network continuously monitors, throughout India, the absorbed dose rate in air due to outdoor natural gamma radiation, by using Geiger-Mueller detector-based standalone environmental radiation monitors. The network consists of 546 monitors spread across 91 monitoring locations distributed all over the country. In this paper, the countrywide long-term monitoring results are summarised. The measured mean dose rate of the monitoring locations followed a log-normal distribution and ranged from 50 to 535 nGy.h-1 with a median value of 91 nGy.h-1. Due to outdoor natural gamma radiation, the average annual effective dose was estimated to be 0.11 mSv.y-1.

Increased CD4/CD8 Lymphocyte ratio predicts favourable neoadjuvant treatment response in gastric cancer: A prospective pilot study.

BACKGROUND: Despite optimal neoadjuvant chemotherapy only 40% of gastric cancer tumours achieve complete or partial treatment response. In the absence of treatment response, neoadjuvant chemotherapy in gastric cancer contributes to adverse events without additional survival benefit compared to adjuvant treatment or surgery alone. Additional strategies and methods are required to optimize the allocation of existing treatment regimens such as FLOT chemotherapy (5-Fluorouracil, Leucovorin, Oxaliplatin and Docetaxel). Predictive biomarkers detected using immunohistochemistry (IHC) methods may provide useful data regarding treatment response. AIM: To investigate the utility of CD4, CD8, Galectin-3 and E-cadherin in predicting neoadjuvant FLOT chemotherapy tumour response in gastric adenocarcinoma. METHODS: Forty-three adult patients with gastric adenocarcinoma, of which 18 underwent neoadjuvant chemotherapy, were included in a prospective clinical cohort. Endoscopic biopsies were obtained from gastric cancer and normal adjacent gastric mucosa. Differences in expression of Galectin-3, E-cadherin, CD4+ and CD8+ molecules between tumours with and without treatment response to neoadjuvant chemotherapy were assessed with IHC. Treatment response was graded by clinical pathologists using the Tumour Regression Score according to the College of American Pathologists criteria. Treatment response was defined as complete or near complete tumour response, whereas partial or poor/no response was defined as incomplete. Digital IHC images were annotated and quantitatively assessed using QuPath 0.3.1. Biomarker expression between responsive and incomplete response tumours was assessed using a two-sided Wilcoxon test. Biomarker expression was also compared between normal and cancer tissue and between 15 paired tumour samples before and after chemotherapy. We performed a preliminary multivariate analysis and power analysis to guide future study. Statistical analyses were completed using R 4.1.2. RESULTS: The ratio between CD4+ and CD8+ lymphocytes was significantly greater in treatment responsive tumours (Wilcoxon, P = 0.03). In univariate models, CD4+/CD8+ ratio was the only biomarker that significantly predicted favourable treatment response (Accuracy 86%, P < 0.001). Using a glmnet multivariate model, high CD4+/CD8+ ratio and low Galectin-3 expression were the most influential variables in predicting a favourable treatment response. Analyses of paired samples found that FLOT chemotherapy also results in increased expression of CD4+ and CD8+ tumour infiltrating lymphocytes (Paired Wilcoxon, P = 0.002 and P = 0.008, respectively). Our power analysis suggests future study requires at least 35 patients in each treatment response group for CD8 and Galectin-3 molecules, whereas 80 patients in each treatment response group are required to assess CD4 and E-cadherin biomarkers. CONCLUSION: We demonstrate that an elevated CD4+/CD8+ Ratio is a promising IHC-based biomarker to predict favourable treatment response to FLOT neoadjuvant chemotherapy in locally advanced gastric cancer.

Dichotomous Nitric Oxide-Dependent Post-Translational Modifications of STAT1 Are Associated with Ipilimumab Benefits in Melanoma.

Although Ipilimumab (anti-CTLA-4) is FDA-approved for stage III/IV melanoma adjuvant treatment, it is not used clinically in first-line therapy, given the superior relapse-free survival (RFS)/toxicity benefits of anti-PD-1 therapy. However, it is important to understand anti-CTLA-4's mechanistic contribution to combination anti-PD-1/CTLA-4 therapy and investigate anti-CTLA-4 therapy for BRAF-wild type melanoma cases reresected after previous adjuvant anti-PD-1 therapy. Our group published that nitric oxide (NO) increased within the immune effector cells among patients with longer RFS after adjuvant ipilimumab, whereas NO increased within the immune suppressor cells among patients with shorter RFS. Herein, we measured the post-translational modifications of STAT1 (nitration-nSTAT1 and phosphorylation-pSTAT1) that are important for regulating its activity via flow cytometry and mass spectrometry approaches. PBMCs were analyzed from 35 patients undergoing adjuvant ipilimumab treatment. Shorter RFS was associated with higher pSTAT1 levels before (p = 0.007) and after (p = 0.036) ipilimumab. Ipilimumab-treated patients with high nSTAT1 levels before and after therapy in PBMCs experienced decreased RFS, but the change in nSTAT1 levels before and after ipilimumab therapy was associated with longer RFS (p = 0.01). The measurement of post-translational modifications in STAT1 may distinguish patients with prolonged RFS from ipilimumab and provide mechanistic insight into responses to ipilimumab combination regimens.

Harnessing Innate Immunity to Treat Mycobacterium tuberculosis Infections: Heat-Killed Caulobacter crescentus as a Novel Biotherapeutic.

Tuberculosis, caused by Mycobacterium tuberculosis (Mtb), is a serious and devastating infectious disease worldwide. Approximately a quarter of the world population harbors latent Mtb infection without pathological consequences. Exposure of immunocompetent healthy individuals with Mtb does not result in active disease in more than 90% individuals, suggesting a defining role of host immunity to prevent and/or clear early infection. However, innate immune stimulation strategies have been relatively underexplored for the treatment of tuberculosis. In this study, we used cell culture and mouse models to examine the role of a heat-killed form of a non-pathogenic microbe, Caulobacter crescentus (HKCC), in inducing innate immunity and limiting Mtb infection. We also examined the added benefits of a distinct chemo-immunotherapeutic strategy that incorporates concurrent treatments with low doses of a first-line drug isoniazid and HKCC. This therapeutic approach resulted in highly significant reductions in disseminated Mtb in the lungs, liver, and spleen of mice compared to either agent alone. Our studies demonstrate the potential of a novel innate immunotherapeutic strategy with or without antimycobacterial drugs in controlling Mtb infection in mice and open new avenues for the treatment of tuberculosis in humans.

Murine and Human Gastric Tissue Establishes Organoids after 48 Hours of Cold Ischemia Time during Shipment.

An inadequate supply of fresh tissue is a major limitation of three-dimensional patient-derived gastric organoid research. We propose that tissue procurement for organoid culture could be increased by developing a cold storage shipment protocol for fresh surgical tissues. Sixty stomach specimens from C57BL/6J mice were resected, of which forty-five were stored in Hank's Balanced Salt (HBSS), University of Wisconsin (UW), or Histidine-Tryptophan-Ketoglutarate (HTK) solutions for subsequent organoid culture. Stomachs were dissociated and processed into gastric organoids as fresh tissue or after transport at 4 °C for 24 or 48 h. All gastric organoid cultures were established and maintained for 10 passages. Cold storage for 24 or 48 h did not significantly affect organoid viability. Although cold storage was associated with decreased organoid growth rate, there were no differences in viability, cytotoxic dose response, or LGR5 and TROY stem cell gene expression compared to organoids prepared from fresh tissue. As a proof of concept, six human gastric cancer organoids were established after 24 or 48 h of storage. Patient-derived gastric organoids from mouse and human gastric tissue can be established after 48 h of cold ischemia. Our method, which only requires ice packs, standard shipping containers, and HBSS is feasible and reliable. This method does not affect the reliability of downstream dose-response assays and maintains organoid viability for at least 10 passages. The shipment of fresh tissue for organoid procurement could serve to enhance multicenter collaboration and achieve more elaborate or controlled organoid experimentation.

Anti-Mycobacterial Activity of Flavonoid and Pyrimidine Compounds.

We evaluated the anti-mycobacterial effect of a flavonoid 5,7-dihydroxy-2-(4-hydroxyphenyl) 4H-chromen-4-one (1) and two pyrimidines, 4-hydroxy-2-dimethylamino-5-nitroso-6-aminopyrimidine (2) and 2-chloro-5-n-nonylpyrimidine (3) in vitro against Mycobacterium tuberculosis (M. tuberculosis, H37Ra) and Mycobacterium avium (M. avium), using a Microplate Alamar Blue Assay (MABA). The effects of the compounds 1-3 in combination with first- and second-line anti-TB drugs isoniazid, rifampicin, cycloserine, and clarithromycin on the growth of M. tuberculosis and M. avium were also evaluated in in vitro assays. As a single agent, compounds 1 and 2 exhibited modest activity while compound 3 was the most effective against M. tuberculosis and M. avium. When compounds 1-3 were evaluated at lower than 50% of their inhibitory concentrations in a two-drug combination with isoniazid or rifampicin, they showed additive to synergistic interactions. This inhibitory effect was improved when each of the three compounds was tested together in a three-drug combination with two of the first-line anti-TB drugs. Compounds 1-3 also demonstrated strong synergistic interaction in combination with cycloserine and clarithromycin in inhibiting the growth of M. tuberculosis and M. avium, respectively. This study demonstrated that compounds 1-3 have potential to be developed as effective anti-TB agents with combined use.

Moving towards intelligent telemedicine: Computer vision measurement of human movement.

BACKGROUND: Telemedicine video consultations are rapidly increasing globally, accelerated by the COVID-19 pandemic. This presents opportunities to use computer vision technologies to augment clinician visual judgement because video cameras are so ubiquitous in personal devices and new techniques, such as DeepLabCut (DLC) can precisely measure human movement from smartphone videos. However, the accuracy of DLC to track human movements in videos obtained from laptop cameras, which have a much lower FPS, has never been investigated; this is a critical gap because patients use laptops for most telemedicine consultations. OBJECTIVES: To determine the validity and reliability of DLC applied to laptop videos to measure finger tapping, a validated test of human movement. METHOD: Sixteen adults completed finger-tapping tests at 0.5 Hz, 1 Hz, 2 Hz, 3 Hz and at maximal speed. Hand movements were recorded simultaneously by a laptop camera at 30 frames per second (FPS) and by Optotrak, a 3D motion analysis system at 250 FPS. Eight DLC neural network architectures (ResNet50, ResNet101, ResNet152, MobileNetV1, MobileNetV2, EfficientNetB0, EfficientNetB3, EfficientNetB6) were applied to the laptop video and extracted movement features were compared to the ground truth Optotrak motion tracking. RESULTS: Over 96% (529/552) of DLC measures were within +/-0.5 Hz of the Optotrak measures. At tapping frequencies >4 Hz, there was progressive decline in accuracy, attributed to motion blur associated with the laptop camera's low FPS. Computer vision methods hold potential for moving us towards intelligent telemedicine by providing human movement analysis during consultations. However, further developments are required to accurately measure the fastest movements.

The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer's disease and estimate 5-year risks of cognitive decline and dementia.

BACKGROUND: The worldwide prevalence of dementia is rapidly rising. Alzheimer's disease (AD), accounts for 70% of cases and has a 10-20-year preclinical period, when brain pathology covertly progresses before cognitive symptoms appear. The 2020 Lancet Commission estimates that 40% of dementia cases could be prevented by modifying lifestyle/medical risk factors. To optimise dementia prevention effectiveness, there is urgent need to identify individuals with preclinical AD for targeted risk reduction. Current preclinical AD tests are too invasive, specialist or costly for population-level assessments. We have developed a new online test, TAS Test, that assesses a range of motor-cognitive functions and has capacity to be delivered at significant scale. TAS Test combines two innovations: using hand movement analysis to detect preclinical AD, and computer-human interface technologies to enable robust 'self-testing' data collection. The aims are to validate TAS Test to [1] identify preclinical AD, and [2] predict risk of cognitive decline and AD dementia. METHODS: Aim 1 will be addressed through a cross-sectional study of 500 cognitively healthy older adults, who will complete TAS Test items comprising measures of motor control, processing speed, attention, visuospatial ability, memory and language. TAS Test measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 (p-tau181). Aim 2 will be addressed through a 5-year prospective cohort study of 10,000 older adults. Participants will complete TAS Test annually and subtests of the Cambridge Neuropsychological Test Battery (CANTAB) biennially. 300 participants will undergo in-person clinical assessments. We will use machine learning of motor-cognitive performance on TAS Test to develop an algorithm that classifies preclinical AD risk (p-tau181-defined) and determine the precision to prospectively estimate 5-year risks of cognitive decline and AD. DISCUSSION: This study will establish the precision of TAS Test to identify preclinical AD and estimate risk of cognitive decline and AD. If accurate, TAS Test will provide a low-cost, accessible enrichment strategy to pre-screen individuals for their likelihood of AD pathology prior to more expensive tests such as blood or imaging biomarkers. This would have wide applications in public health initiatives and clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05194787 , 18 January 2022. Retrospectively registered.

Assessment of in-cabin noise of wide-body aircrafts.

The aviation industry has seen dramatic growth over the decades till the recent disruption due to the COVID-19 pandemic. Moreover, long-haul routes with a distance of more than 4000 km are common for major airlines worldwide. Therefore, aircraft cabin noise assessment is essential, especially in long-haul flights, for passenger and flight crew health wellness. In this paper, the cabin noise of five wide-body aircraft, namely Airbus A330-300ER, A350-900, A380-800, and Boeing B777-200ER and B787-900, was recorded using a calibrated in-house developed smartphone application. The sound pressure levels of in-cabin noise have been measured on two different decibel scales, namely, A-weighted [dB(A)] and C-weighted scales [dB(C)]. The sound pressure levels of Airbus A380-800 were lowest among selected models, while the in-cabin pressure level values of Airbus A350-900 were maximum. However, the difference in decibel levels between the aircraft is minimal as it is within 3 dB.

Applications of artificial intelligence to aid early detection of dementia: A scoping review on current capabilities and future directions.

BACKGROUND & OBJECTIVE: With populations aging, the number of people with dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases are due to Alzheimer's disease (AD) pathology and there is a 10-20 year 'pre-clinical' period before significant cognitive decline occurs. We urgently need, cost effective, objective biomarkers to detect AD, and other dementias, at an early stage. Risk factor modification could prevent 40% of cases and drug trials would have greater chances of success if participants are recruited at an earlier stage. Currently, detection of dementia is largely by pen and paper cognitive tests but these are time consuming and insensitive to the pre-clinical phase. Specialist brain scans and body fluid biomarkers can detect the earliest stages of dementia but are too invasive or expensive for widespread use. With the advancement of technology, Artificial Intelligence (AI) shows promising results in assisting with detection of early-stage dementia. This scoping review aims to summarise the current capabilities of AI-aided digital biomarkers to aid in early detection of dementia, and also discusses potential future research directions. METHODS & MATERIALS: In this scoping review, we used PubMed and IEEE Xplore to identify relevant papers. The resulting records were further filtered to retrieve articles published within five years and written in English. Duplicates were removed, titles and abstracts were screened and full texts were reviewed. RESULTS: After an initial yield of 1,463 records, 1,444 records were screened after removal of duplication. A further 771 records were excluded after screening titles and abstracts, and 496 were excluded after full text review. The final yield was 177 studies. Records were grouped into different artificial intelligence based tests: (a) computerized cognitive tests (b) movement tests (c) speech, conversion, and language tests and (d) computer-assisted interpretation of brain scans. CONCLUSIONS: In general, AI techniques enhance the performance of dementia screening tests because more features can be retrieved from a single test, there are less errors due to subjective judgements and AI shifts the automation of dementia screening to a higher level. Compared with traditional cognitive tests, AI-based computerized cognitive tests improve the discrimination sensitivity by around 4% and specificity by around 3%. In terms of speech, conversation and language tests, combining both acoustic features and linguistic features achieve the best result with accuracy around 94%. Deep learning techniques applied in brain scan analysis achieves around 92% accuracy. Movement tests and setting smart environments to capture daily life behaviours are two potential future directions that may help discriminate dementia from normal aging. AI-based smart environments and multi-modal tests are promising future directions to improve detection of dementia in the earliest stages.

Characterizing the cortical pathways underlying visual trigger induced urinary urgency incontinence by functional MRI.

AIMS: Visual triggers have long been recognized clinically to stimulate urgency urinary incontinence (UUI). Current pathophysiology recognizes the importance of cortical control over micturition but there is no standardized methodology for clinicians to study the impact of visual triggers. Our aim was to develop an imaging protocol able to characterize the brain's response to personalized visual triggers, providing a methodology for evaluation on connectivity within the brain in patients with visually triggered urinary urgency. METHODS: A magnetic resonance imaging (MRI) methodology specific for urologic use was developed. A 3T-Elition Scanner was first used to acquire static structural images. These images were then used to define approximately 200 brain regions of interest (ROI) using a validated brain atlas. Then, real-time functional MRI (fMRI) scans were conducted during natural bladder filling, where study subjects were shown randomized block sequences of visual stimuli comprised of both subject-specific trigger images and neutral images. The fMRI scan data were merged to identify key ROI underlying UUI. RESULTS: Dynamic fMRI scans were conducted in 10 subjects, 4 with trigger-induced UUI, 2 with trigger-induced urgency, and 4 with no urgency or leakage to visual triggers. No subjects with UUI history lost continence during imaging, but all four subjects reported sensations of urgency in response to their own subject-specific trigger images. The ROI identified were the periaqueductal gray, anterior cingulate gyrus, pons, and prefrontal cortex. We found increased activity in the prefrontal cortex and limbic system ROI in response to subject-specific visual triggers of UUI. CONCLUSIONS: This information provides proof of principle for further exploration of subject-specific trigger image evaluation using fMRI to explore causation in patients with UUI.

A Large Intraoral Lipoma: Case Report.

Lipomas of the oral cavity are uncommon. Here we report a case of 85 year old female presenting with a progressively increasing large growth in the oropharynx which was diagnosed as lipoma on histopathology. The clinicoradiological and histopathological findings are discussed. To the best of our knowledge; this is one of the largest intraoral lipoma reported in India till date. The present case highlights the need to be aware of intraoral lipomas which can present as large growths at this unusual site so as to avoid any unwarranted aggressive surgery.

Hand tremor detection in videos with cluttered background using neural network based approaches.

With the increasing prevalence of neurodegenerative diseases, including Parkinson's disease, hand tremor detection has become a popular research topic because it helps with the diagnosis and tracking of disease progression. Conventional hand tremor detection algorithms involved wearable sensors. A non-invasive hand tremor detection algorithm using videos as input is desirable but the existing video-based algorithms are sensitive to environmental conditions. An algorithm, with the capability of detecting hand tremor from videos with a cluttered background, would allow the videos recorded in a non-research environment to be used. Clinicians and researchers could use videos collected from patients and participants in their own home environment or standard clinical settings. Neural network based machine learning architectures provide high accuracy classification results in related fields including hand gesture recognition and body movement detection systems. We thus investigated the accuracy of advanced neural network architectures to automatically detect hand tremor in videos with a cluttered background. We examined configurations with different sets of features and neural network based classification models. We compared the performance of different combinations of features and classification models and then selected the combination which provided the highest accuracy of hand tremor detection. We used cross validation to test the accuracy of the trained model predictions. The highest classification accuracy for automatically detecting tremor (vs non tremor) was 80.6% and this was obtained using Convolutional Neural Network-Long Short-Term Memory and features based on measures of frequency and amplitude change.

The Genome-Wide Binding Profile for Human RE1 Silencing Transcription Factor Unveils a Unique Genetic Circuitry in Hippocampus.

Early studies in mouse neurodevelopment led to the discovery of the RE1 Silencing Transcription Factor (REST) and its role as a master repressor of neuronal gene expression. Recently, REST was reported to also repress neuronal genes in the human adult brain. These genes were found to be involved in pro-apoptotic pathways; and their repression, associated with increased REST levels during aging, were found to be neuroprotective and conserved across species. However, direct genome-wide REST binding profiles for REST in adult brain have not been identified for any species. Here, we apply this approach to mouse and human hippocampus. We find an expansion of REST binding sites in the human hippocampus that are lacking in both mouse hippocampus and other human non-neuronal cell types. The unique human REST binding sites are associated with genes involved in innate immunity processes and inflammation signaling which, on the basis of histology and recent public transcriptomic analyses, suggest that these new target genes are repressed in glia. We propose that the increases in REST expression in mid-adulthood presage the beginning of brain aging, and that human REST function has evolved to protect the longevity and function of both neurons and glia in human brain.SIGNIFICANCE STATEMENT The RE1 Silencing Transcription Factor (REST) repressor has served historically as a model for gene regulation during mouse neurogenesis. Recent studies of REST have also suggested a conserved role for REST repressor function across lower species during aging. However, direct genome-wide studies for REST have been lacking for human brain. Here, we perform the first genome-wide analysis of REST binding in both human and mouse hippocampus. The majority of REST-occupied genes in human hippocampus are distinct from those in mouse. Further, the REST-associated genes unique to human hippocampus represent a new set related to innate immunity and inflammation, where their gene dysregulation has been implicated in aging-related neuropathology, such as Alzheimer's disease.

Brain connectivity during simulated balance in older adults with and without Parkinson's disease.

Individuals with Parkinson's disease often experience postural instability, a debilitating and largely treatment-resistant symptom. A better understanding of the neural substrates contributing to postural instability could lead to more effective treatments. Constraints of current functional neuroimaging techniques, such as the horizontal orientation of most MRI scanners (forcing participants to lie supine), complicates investigating cortical and subcortical activation patterns and connectivity networks involved in healthy and parkinsonian balance control. In this cross-sectional study, we utilized a newly-validated MRI-compatible balance simulator (based on an inverted pendulum) that enabled participants to perform balance-relevant tasks while supine in the scanner. We utilized functional MRI to explore effective connectivity underlying static and dynamic balance control in healthy older adults (n = 17) and individuals with Parkinson's disease while on medication (n = 17). Participants performed four tasks within the scanner with eyes closed: resting, proprioceptive tracking of passive ankle movement, static balancing of the simulator, and dynamic responses to random perturbations of the simulator. All analyses were done in the participant's native space without spatial transformation to a common template. Effective connectivity between 57 regions of interest was computed using a Bayesian Network learning approach with false discovery rate set to 5%. The first 12 principal components of the connection weights, binomial logistic regression, and cross-validation were used to create 4 separate models: contrasting static balancing vs {rest, proprioception} and dynamic balancing vs {rest, proprioception} for both controls and individuals with Parkinson's disease. In order to directly compare relevant connections between controls and individuals with Parkinson's disease, we used connections relevant for predicting a task in either controls or individuals with Parkinson's disease in logistic regression with Least Absolute Shrinkage and Selection Operator regularization. During dynamic balancing, we observed decreased connectivity between different motor areas and increased connectivity from the brainstem to several cortical and subcortical areas in controls, while individuals with Parkinson's disease showed increased connectivity associated with motor and parietal areas, and decreased connectivity from brainstem to other subcortical areas. No significant models were found for static balancing in either group. Our results support the notion that dynamic balance control in individuals with Parkinson's disease relies more on cortical motor areas compared to healthy older adults, who show a preference of subcortical control during dynamic balancing.