Introduction There is a high prevalence of depression in developing countries, and low mental health literacy has been hypothesized as one of the main causes of increasing rates of mental illness in a population. This study aimed to capture an image of the current attitude and perceptions towards victims of clinical depression in Pakistan and to assess the impact of those beliefs. Methods A cross-sectional study was conducted with 400 people, chosen through non-probability consecutive sampling, from Karachi, Pakistan. A questionnaire was designed to evaluate the overall perception of depression including its causes, manifestations and treatment options. Descriptive statistics were used and p-values less than 0.05 calculated using the chi-square test were considered significant. Results Most of the participants comprehended depression as a natural feeling of sadness rather than a mental disorder. The vast majority cited increased stress (72.2%) and physical/ emotional trauma (51.3%) as the main causes of depression. The most popularly associated symptoms were sadness (53.3%), irritability (53.3%), inability to perform daily tasks (52.8%), and changes in sleeping patterns (52%). Participants believed depression to be best treated by talking to someone trustworthy (59.5%), praying to God (56.5%) and consulting a psychologist/psychiatrist (52.3%). There was a significant association between the participants’ level of education and their perception of clinical depression (p=0.026). Conclusion Our study showed a skewed perception of depression with the majority only acknowledging it as a natural feeling of sadness. However, stress was seen as a major perpetrator and the importance of a good support system was acknowledged by most participants. Level of education was revealed to be the most important factor that influenced these beliefs. Effective community-based programs and policies based on these public views will help develop an accessible and autonomous support system for patients with mental illnesses.

Introduction The aim of the study was to explore the association between the intake of specific food substances and the sleeping patterns of medical students. Methods A cross-sectional study was conducted with 440 medical students, aged 18-24 years, chosen through non-probability consecutive sampling from Karachi, Pakistan. The Pittsburgh sleep quality index (PSQI) was used to measure sleep quality and a self-made questionnaire that categorized foods according to their nutritional constitutions was used to measure the frequency of food consumption. Associations were evaluated using the chi-square test with the level of significance taken as p < 0.05 and strength of significance determined using Cramer’s V. logistic regression to predict good sleep quality. Results Significant associations were found with soybeans, whole grains, processed meats, leafy greens, dark chocolate, spices, dairy products, products high in fat and sugar, lima beans, and carbohydrates in relation to sleep quality, with soybeans exhibiting a particularly stronger relationship. The odds of good sleep quality were 2.5 times more likely with soybean intake, 3.26 times more likely with carbohydrates, and 6.57 times more likely with lima beans. Intake of papayas was associated with reduced sleep quality. Conclusion Intake of certain food substances has a significant association with sleep quality. Clinical trials focusing on the nutritional basis of these associations can lead to a new integrated focus on functional foods to combat poor sleep and sleep-related diseases.

Objective Sun exposure is a primary preventable risk factor for skin cancer. Sunscreen has been shown to reduce the risk of certain skin cancers such as squamous cell carcinoma and melanoma. We aimed to assess the prevalence and predictors of sunscreen use among medical students in Karachi. Methods A multi-center cross-sectional study was conducted among 578 students from multiple medical universities in Karachi, Pakistan. The levels of use of sunscreen were recorded using a comprehensive questionnaire consisting of 29 questions. Descriptive statistics were used and p-values less than 0.05 calculated using the chi-square test were considered significant. Results A majority (n=441, 73.9%) of the participants in this study were female students. Sunscreen use was prevalent in 415 (69.5%) participants. Female students were more aware of the risk of skin cancer from extended sun exposure (n=186, 72.4%). Sunscreen use was significantly associated with gender (p<0.001) and the propensity to get sunburned easily (p=0.001). Few (n=19, 5.0%) students reported being well-versed regarding skin cancer and its risk factors. Most participants were aware of the use of sunscreen for sunburn prevention (n=473, 79.2%), though knowledge of the additional benefits of sunscreen, such as the prevention of skin cancer (n=257, 43.0%) and aging (n=199, 33.3%), was lacking. Conclusion There is an evident lack of knowledge of the importance of sunscreen protection among medical students, particularly regarding the prevention of skin cancer and skin aging. However, an overall positive attitude was observed regarding the use of sunscreen among female students. Medical students are an imperative part of our future healthcare system and should be adequately informed on sunscreen benefits and skin cancer prevention.

Objective This article systematically reviews current literature on the efficacy and efficiency of selective serotonin reuptake inhibitors (SSRIs) in the treatment of patients with frontotemporal lobar degeneration (FTLD), with a particular focus on behavior and cognitive functions. Methods A search was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines using CENTRAL, MEDLINE, and Cochrane Library databases. Eleven randomized controlled trials and open-label studies looking at the effects of SSRIs on FTLD patients were included. A random-effects meta-analysis was performed, consisting of 3 randomized and controlled studies that used the neuropsychiatric inventory to assess SSRI intervention. Results The meta-analysis shows a combined mean reduction of 10.17 points (95% confidence interval, 18.14–2.19; P = 0.01) on the neuropsychiatric inventory with SSRI treatment in FTLD patients. The I 2 calculated for this study was 62% (P = 0.07), which represents moderate heterogeneity among the studies. The Egger regression test (P = 0.526) did not show a publication bias. Sensitivity analysis showed no significant change. Conclusions The current meta-analysis supports SSRIs as an intervention for management of behavioral symptoms of FTLD. Marked improvements were seen in disinhibition, irritability, aggression, and aberrant motor activity across studies. However, apathy/loss of empathy did not show similarly promising results. A deteriorative effect on cognition was seen associated with SSRI use.

Rapid progress is being made in the development of next-generation sequencing (NGS) technologies, allowing repeated findings of new genes and a more in-depth analysis of genetic polymorphisms behind the pathogenesis of a disease. In a field such as psychiatry, characteristic of vague and highly variable somatic manifestations, these technologies have brought great advances towards diagnosing various psychiatric and mental disorders, identifying high-risk individuals and towards more effective corresponding treatment. Psychiatry has the difficult task of diagnosing and treating mental disorders without being able to invariably and definitively establish the properties of its illness. This calls for diagnostic technologies that go beyond the traditional ways of gene manipulation to more advanced methods mainly focusing on new gene polymorphism discoveries, one of them being NGS. This enables the identification of hundreds of common and rare genetic variations contributing to behavioral and psychological conditions. Clinical NGS has been useful to detect copy number and single nucleotide variants and to identify structural rearrangements that have been challenging for standard bioinformatics algorithms. The main objective of this article is to review the recent applications of NGS in the diagnosis of major psychiatric disorders, and hence gauge the extent of its impact in the field. A comprehensive PubMed search was conducted and papers published from 2013-2018 were included, using the keywords, “schizophrenia” or “bipolar disorder” or “depressive disorder” or “attention deficit disorder” or “autism spectrum disorder” and “next-generation sequencing”