Effectiveness of IMPUTE ADT-1 mobile application in children with autism spectrum disorder: An interim analysis of an ongoing randomized controlled trial.

Objectives: IMPUTE Inc., a software firm dedicated to healthcare technology, has developed a mobile medical application known as IMPUTE ADT-1 for children with autism spectrum disorder (ASD) based on the principle of applied behavior analysis. Materials and Methods: The primary objective of this trial was to compare the efficacy of add-on treatment with IMPUTE ADT-1 in children with ASD aged two to six years as compared to standard care alone for 12 weeks (in terms of change in Autism Diagnostic Observation Schedule [ADOS-2] scores). The secondary objective of the study was to assess the compliance with IMPUTE ADT-1 among participants and also to evaluate the feedback of parents regarding IMPUTE ADT-1 at the end of 12 weeks. The application provides personalized programs tailored to each user's needs, and the program evolves based on the user's progress. It also utilizes face tracking, eye tracking, and body tracking to gather behavior-related information for each child and apply it in reinforcement learning employing artificial intelligence-based algorithms. Results: Till the time of interim analysis, 37 and 33 children had completed 12-week follow-up in IMPUTE ADT-1 and control arm. At 12 weeks, as compared to baseline, change in social affect domain, repetitive ritualistic behavior domain, total ADOS-2 score, and ADOS-2 comparison score was better in the intervention group as compared to the control group (P < 0.001 for all). A total of 30 (81%), 28 (75%), and 29 (78%) caregivers in the IMPUTE ADT-1 group believed that the ADT-1 app improved their child's verbal skills, social skills, and reduced repetitive behavior, respectively. Conclusion: IMPUTE ADT-1 mobile application has the efficacy to improve the severity of autism symptoms in children. Parents of these children also feel that the application is beneficial for improving the socialization and verbal communication of their children.

Trial-history biases in evidence accumulation can give rise to apparent lapses in decision-making.

Trial history biases and lapses are two of the most common suboptimalities observed during perceptual decision-making. These suboptimalities are routinely assumed to arise from distinct processes. However, previous work has suggested that they covary in their prevalence and that their proposed neural substrates overlap. Here we demonstrate that during decision-making, history biases and apparent lapses can both arise from a common cognitive process that is optimal under mistaken beliefs that the world is changing i.e. nonstationary. This corresponds to an accumulation-to-bound model with history-dependent updates to the initial state of the accumulator. We test our model's predictions about the relative prevalence of history biases and lapses, and show that they are robustly borne out in two distinct decision-making datasets of male rats, including data from a novel reaction time task. Our model improves the ability to precisely predict decision-making dynamics within and across trials, by positing a process through which agents can generate quasi-stochastic choices.

Predicting intracranial involvement: Unveiling perineural spread in COVID-19-associated mucormycosis, a novel phenomenon.

This study aimed to investigate the risk factors associated with intracranial involvement in COVID-19-associated mucormycosis (CAM) and to develop a nomogram model for predicting the risk of intracranial involvement, with a specific focus on perineural spread. An ambispective analysis was conducted on 275 CAM patients who received comprehensive treatment. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors, and a nomogram was created based on the results of the multivariable analysis. The performance of the nomogram was evaluated using a receiver operating characteristic (ROC) curve, and the discriminatory capacity was assessed using the area under the curve (AUC). The model's calibration was assessed through a calibration curve and the Hosmer Lemeshow test. In the results, the multivariable logistic regression analysis revealed that age (OR: 1.23, 95% CI 1.06-3.79), HbA1c (OR: 7.168, 95% CI 1.724-25.788), perineural spread (OR: 6.3, 95% CI 1.281-19.874), and the disease stage were independent risk factors for intracranial involvement in CAM. The developed nomogram demonstrated good discriminative capacity with an AUC of 0.821 (95% CI 0.713-0.909) as indicated by the ROC curve. The calibration curve showed that the nomogram was well-calibrated, and the Hosmer Lemeshow test yielded a P-value of 0.992, indicating a good fit for the model. In conclusion, this study found that CAM particularly exhibits perineural spread, which is a predictive factor for intracranial involvement. A nomogram model incorporating age, HbA1c, disease stage, and perineural spread was successfully developed for predicting intracranial involvement in CAM patients in both in-patient and out-patient settings.

Discovery of perineural spread in COVID-19-associated mucormycosis reveals a new predictive model for intracranial complications which is crucial for early intervention.

Development and validation of a predictive model assessing the risk of seizure recurrence in children with neurocysticercosis.

INTRODUCTION: Neurocysticercosis (NCC) is a significant factor contributing to the incidence of seizures in developing countries. While numerous studies have investigated the recurrence of seizures in NCC, their reliability is often limited. METHODS: We assessed the socio-demographic, clinical, and neuroimaging details of 161 children with seizures caused by NCC. We monitored them for seizure recurrence over a 6-month follow-up period. We divided the children into two groups: those with seizure recurrence and those without. Subsequently, we identified predictive factors associated with seizure recurrence through univariate analysis, followed by multivariate binary logistic regression. We evaluated the prognostic model for discrimination and calibration and then internally validated it using the bootstrap method. RESULTS: A total of 23 children experienced breakthrough seizures. In multivariate analysis, the presence of epileptiform abnormalities in electroencephalogram (EEG), more than 5 NCC lesions, the presence of perilesional edema greater than 2 cm in maximum dimension, and a cluster of seizures before presentation were significantly associated with seizure recurrence (p < 0.05). These factors were included in the final NEPC (Number of NCC lesions, Epileptiform EEG abnormality, Perilesional edema, and Cluster of seizures) score. The final model exhibited good discrimination (AUC = 89.1 %; 95 % CI=80.5-95.3 %, p < 0.001) and calibration (p = 0.54). A score of 4 appeared to be the optimal threshold for discriminating between individuals with and without seizure recurrence, with sensitivity and specificity values of 85 % and 87 %, respectively. Interrater reliability was very strong between two pediatric neurologists and strong between a pediatric neurologist and a pediatric neurology trainee resident (k = 0.92 and 0.86, respectively). CONCLUSION: The NEPC score demonstrates good sensitivity and specificity in predicting seizure recurrence in pediatric children with NCC.

Transitions in dynamical regime and neural mode underlie perceptual decision-making.

Perceptual decision-making is the process by which an animal uses sensory stimuli to choose an action or mental proposition. This process is thought to be mediated by neurons organized as attractor networks 1,2 . However, whether attractor dynamics underlie decision behavior and the complex neuronal responses remains unclear. Here we use an unsupervised, deep learning-based method to discover decision-related dynamics from the simultaneous activity of neurons in frontal cortex and striatum of rats while they accumulate pulsatile auditory evidence. We show that contrary to prevailing hypotheses, attractors play a role only after a transition from a regime in the dynamics that is strongly driven by inputs to one dominated by the intrinsic dynamics. The initial regime mediates evidence accumulation, and the subsequent intrinsic-dominant regime subserves decision commitment. This regime transition is coupled to a rapid reorganization in the representation of the decision process in the neural population (a change in the "neural mode" along which the process develops). A simplified model approximating the coupled transition in the dynamics and neural mode allows inferring, from each trial's neural activity, the internal decision commitment time in that trial, and captures diverse and complex single-neuron temporal profiles, such as ramping and stepping 3-5 . It also captures trial-averaged curved trajectories 6-8 , and reveals distinctions between brain regions. Our results show that the formation of a perceptual choice involves a rapid, coordinated transition in both the dynamical regime and the neural mode of the decision process, and suggest pairing deep learning and parsimonious models as a promising approach for understanding complex data.

Trial-history biases in evidence accumulation can give rise to apparent lapses.

Trial history biases and lapses are two of the most common suboptimalities observed during perceptual decision-making. These suboptimalities are routinely assumed to arise from distinct processes. However, several hints in the literature suggest that they covary in their prevalence and that their proposed neural substrates overlap - what could underlie these links? Here we demonstrate that history biases and apparent lapses can both arise from a common cognitive process that is normative under misbeliefs about non-stationarity in the world. This corresponds to an accumulation-to-bound model with history-dependent updates to the initial state of the accumulator. We test our model's predictions about the relative prevalence of history biases and lapses, and show that they are robustly borne out in two distinct rat decision-making datasets, including data from a novel reaction time task. Our model improves the ability to precisely predict decision-making dynamics within and across trials, by positing a process through which agents can generate quasi-stochastic choices.

Unveiling the Silent Struggle: A Teen's Battle With Heart Failure Masking Takayasu Arteritis.

We hereby report a 17-year-old adolescent who presented with heart failure with an underlying diagnosis of Takayasu arteritis. Her clinical complaints were intermittent fever, claudication pain in the left upper limb, New York Heart Association (NYHA) grade III dyspnea, and episodes of dizziness for the past two years. On examination, she was unconscious, had absent peripheral pulses, and had severe hypotension. Diagnostic investigations revealed anemia, deranged renal and liver functions, cardiomegaly on chest X-rays, and severe coarctation of the aorta on echocardiography. Further imaging with CT aortography highlighted extensive arterial wall thickening. Laboratory findings included elevated inflammatory markers and negative autoimmune and infectious markers, confirming the diagnosis of large vessel vasculitis (Takayasu arteritis) with heart failure with reduced ejection fraction (LVEF 20-25%) in NYHA class III. The patient was managed with a combination of antihypertensive medications, diuretics, and immunosuppressive therapy. Subsequent follow-up demonstrated improvement in heart failure symptoms and inflammatory markers. This case emphasizes the challenging diagnostic and therapeutic considerations in managing Takayasu arteritis with concurrent cardiovascular complications in the adolescent population.

Impact of Drug Conjugation on Thermal and Metabolic Stabilities of Aglycosylated and N-Glycosylated Antibodies.

N-linked glycosylation is one of the most common and complex posttranslational modifications that govern the biological functions and physicochemical properties of therapeutic antibodies. We evaluated thermal and metabolic stabilities of antibody-drug conjugates (ADCs) with payloads attached to the C'E loop in the immunoglobulin G (IgG) Fc CH2 domain, comparing the glycosylated and aglycosylated Fc ADC variants. Our study revealed that introduction of small-molecule drugs into an aglycosylated antibody can compensate for thermal destabilization originating from structural distortions caused by elimination of N-linked glycans. Depending on the conjugation site, glycans had both positive and negative effects on plasma stability of ADCs. The findings highlight the importance of consideration for selection of conjugation site to achieve desirable physicochemical properties and plasma stability.

A Clinico-Pathological Study of Allergic Fungal Rhinosinusitis at a Tertiary Care Center of Western Rajasthan.

Allergic fungal rhinosinusitis (AFRS) is a non-invasive fungal sinusitis resulting from an immunologic response to the presence of extra mucosal fungal hyphae in the sinuses. Here we studied clinicopathological characteristics of AFRS among patients of chronic rhinosinusitis with nasal polyposis who underwent Functional Endoscopic Sinus Surgery (FESS) at a tertiary care in western Rajasthan. Standard ethical protocol was followed for the present study. We did a prospective study on admitted patients of chronic rhinosinusitis with nasal polyposis in the department of Otorhinolaryngology and Head & neck surgery, Dr. S. N. Medical College, Jodhpur from January 2018 to August 2019, who underwent FESS. The patient's history, clinical and endoscopic findings with radiological features were recorded. Biopsy specimens were sent for fungal staining, culture, and histopathology. As per Bent and Kuhn criteria, 25 cases out of 100 were diagnosed as AFRS, mean age was 27.46 ± 13.36. Nasal obstruction and nasal discharge were the most common symptoms. On histopathological examination fungal hyphae found in 18 cases (72%), allergic mucin in 25 cases (100%) and eosinophilic infiltrate in 20 cases (80%). Fungal culture positive in 15 cases (60%) of AFRS. In which aspergillus flavus present in 12 (80%). Allergic fungal rhinosinusitis should be considered as an important differential diagnosis in patients with chronic rhinosinusitis with nasal polyposis and for this surgery should be the treatment of choice.

Epley's Manoeuvre: A Single Line Treatment for Posterior Semicircular Canal Benign Paroxysmal Positional Vertigo.

Benign Paroxysmal Positional Vertigo (BPPV) is the commonest cause of peripheral vertigo. Displaced free floating otoconia in the semicircular canals are responsible for brief attacks of vertigo and nystagmus. Epley's manoeuvre relocates these particles into the utricle. Here we studied the efficacy of Epley's manoeuvre in posterior semicircular canal BPPV without labyrinthine sedatives. 120 patients presented with positional vertigo were included in the study based on positive Dix- hallpike test from August 2018 to July 2019. These patients were treated with only the Epley's manoeuvre and followed up for 6 months. Patients who were previously on labyrinthine sedatives were advised to stop them and treated with only the Epley's manoeuvre. In our study of 120 patients, mean age was 43.5 yrs. Females (52.5%) were commonly affected. Left side posterior semicircular involvement was more than the right side. Epley's manoeuvre had 90% efficacy at 1st week and 100% efficacy at 4th week. Duration of vertigo had significant association (p < 0.01) with the number of sessions required. There was significant improvement in the duration of vertigo attack (p < 0.0001) and frequency of attack (p < 0.0001) before and after the manoeuvre. Epley's manoeuvre lead to significant (p < 0.001) improvement in the quality of life of affected patients measured by DHI scoring. In our 6 months follow up, 10 recurrences occurred having significant (p < 0.01) association with the duration of vertigo attack. Only Epley's manoeuvre without any labyrinthine sedatives is an effective treatment for posterior semicircular canal BPPV patients. It also improves the quality of life of affected patients.