It has long been debated whether bowel and bladder anxiety are a part of obsessive compulsive spectrum disorder or a variant of agoraphobia with no consensus view yet. Tricyclic antidepressants are reportedly efficacious in such cases and lead to complete resolution of symptoms. Here, we report a 36-year-old male having urges to visit toilet when in public places or where toilets are not easily available and a resulting avoidance of such spaces fearing an episode of incontinence. Symptoms originated 16 years ago when he was in university which compelled him to drop out. We treated him with paroxetine and relaxation therapy to which he responded satisfactorily.
The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation, normally costing USD ~2.6 billion and consuming a mean time span of 12 years. Methods to cut back expenditure and hasten new drug discovery have prompted an arduous and compelling brainstorming exercise in the pharmaceutical industry. The engagement of Artificial Intelligence (AI), including the deep-learning (DL) component in particular, has been facilitated by the employment of classified big data, in concert with strikingly reinforced computing prowess and cloud storage, across all fields. AI has energized computer-facilitated drug discovery. An unrestricted espousing of machine learning (ML), especially DL, in many scientific specialties, and the technological refinements in computing hardware and software, in concert with various aspects of the problem, sustain this progress. ML algorithms have been extensively engaged for computer-facilitated drug discovery. DL methods, such as artificial neural networks (ANNs) comprising multiple buried processing layers, have of late seen a resurgence due to their capability to power automatic attribute elicitations from the input data, coupled with their ability to obtain nonlinear input-output pertinencies. Such features of DL methods augment classical ML techniques which bank on human-contrived molecular descriptors. A major part of the early reluctance concerning utility of AI in pharmaceutical discovery has begun to melt, thereby advancing medicinal chemistry. AI, along with modern experimental technical knowledge, is anticipated to invigorate the quest for new and improved pharmaceuticals in an expeditious, economical, and increasingly compelling manner. DL-facilitated methods have just initiated kickstarting for some integral issues in drug discovery. Many technological advances, such as “message-passing paradigms”, “spatial-symmetry-preserving networks”, “hybrid de novo design”, and other ingenious ML exemplars, will definitely come to be pervasively widespread and help dissect many of the biggest, and most intriguing inquiries. Open data allocation and model augmentation will exert a decisive hold during the progress of drug discovery employing AI. This review will address the impending utilizations of AI to refine and bolster the drug discovery operation.
Coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on mental health, including stress, anxiety, and depression. This study aimed to assess the incidence and severity of mental health issues among individuals diagnosed with COVID-19 infection.A semi-structured proforma for socio-demographic and clinical parameters was used to collect cross-sectional hospital-based data of subjects who tested positive for COVID-19 infection. The Modified Fatigue Impact Scale (MFIS), Hospital Anxiety and Depression Scale (HADS), and Perceived Stress Scale (PSS) were used to assess the presence of physical, psychological, and cognitive symptoms. The presence of anxiety, depression, and stress was based on the cut-off scores for HADS-A (≥8), HADS-D (≥8), and PSS (≥14), respectively.A total of 101 patients comprising 39 (38.6%) males were recruited. Compared to nuclear families, we observed that patients living in joint families had significantly greater severity scores for fatigue [MFIS (p = 0.04)], anxiety [HADS-A (p = 0.004)], depression [HADS-D (p = 0.004)], and stress [PSS (p = 0.02)]. Based on the cut-off scores, we found that 44 (43.6%) patient had anxiety, 41 (40.6%) had depressive, and 72 (71.3%) had moderate to high stress symptoms, respectively. We also observed significantly greater fatigue and anxiety scores, that is, MFIS (p = 0.008) and HADS-A (p = 0.03) in those who received oxygen therapy compared to those who did not. The subjects who received corticosteroids were older (p = 0.01) and had significantly higher stress scores [PSS (p < 0.001)]. The study showed that patients who were assessed more than 3 months post-COVID-19 infection had higher fatigue and depression scores; however, the difference did not reach statistical significance (MFIS P = 0.058; HADS P = 0.059).Our study confirms that COVID-19 infection can cause various adverse mental health issues. Mitigating the hazardous effects of COVID-19 pandemic on mental health should be a top priority for public health to prevent long-term complications.
India suffers from a huge burden of substance abuse and associated morbidity and mortality. Among all substance use, tobacco consumption is the most common and yet the most widely accepted one. This study aimed to estimate the prevalence of tobacco consumption, to find out the type of tobacco products used and to assess the factors influencing tobacco consumption in the slums of Shillong city.A cross-sectional, community-based study was carried out in 330 respondents aged 15 and above. Chi-square test was used to compare proportions, and Student's t-test was used to compare groups for continuous variables.The prevalence of current tobacco consumption was found to be 73.9%, and the rate of quitting was found to be 4.3%. The prevalence of tobacco consumption was observed to be higher in males (52.4%) compared to 21.5% in females. Highly significant statistical association was observed between tobacco consumption and age, gender, and occupation. The statistical association between tobacco consumption and religion and education was found to be statistically significant. Ever use of tobacco in any form as well as smokeless form peaked in 24-34 years, while smoking was more prevalent among 15-24 year olds. The prevalence of smokeless tobacco was higher (47.5%) as compared to the prevalence of smoking (28.2%), closely followed by dual use (24.3%). The most popular smoked and smokeless forms were found to be cigarettes and khaini, respectively.Tobacco consumption was found to be highly prevalent and was much higher than the national average hinting toward its association with higher incidence of various malignancies in the region and calling for immediate action toward propelling its prevention and control by all stakeholders.
Wild mushroom grow abundantly in the tropical belts of India, and they form part of the diet among the ethnic tribes. However, wild mushrooms are toxic, and some cause organ failure, namely fulminant hepatitis and kidney injury. Mushroom poisoning is frequently diagnosed based on clinical suspicion, and death has been reported commonly because of the consumption of amatoxin-containing mushrooms. In this article, we discuss three cases of amatoxin-induced mushroom poisoning that resulted in acute kidney and liver failure, requiring intensive medical management and renal replacement therapy. One of these patients died from irreversible fulminant hepatitis.
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)
