Drosophila melanogaster larvae are classified as herbivores and known to feed on non-carnivorous diet under normal conditions. However, when nutritionally challenged these larvae exhibit cannibalistic behaviour by consuming a diet composed of larger conspecifics. Herein, we report that cannibalism in Drosophila larvae is confined not only to scavenging on conspecifics that are larger in size, but also on their eggs. Moreover, such cannibalistic larvae develop as normally as those grown on standard cornmeal medium. When stressed, Drosophila melanogaster larvae can also consume a carnivorous diet derived from carcasses of organisms belonging to diverse taxonomic groups, including Musca domestica, Apis mellifera, and Lycosidae sp. While adults are ill-equipped to devour conspecific carcasses, they selectively oviposit on them and also consume damaged cadavers of conspecifics. Thus, our results suggest that nutritionally stressed Drosophila show distinct as well as unusual feeding behaviours that can be classified as detritivorous, cannibalistic and/or carnivorous.

Background Hepatitis C virus (HCV) infections are amongst the leading public health concerns in Pakistan with a high disease burden. Despite the availability of effective antiviral treatments in the country the disease burden in general population has not lowered. This could be attributed to the asymptomatic nature of this infection that results in lack of diagnosis until the late symptomatic stage. To better estimate and map HCV infections in the country a population-based analysis is necessary for an effective control of the infection. Methods Serologic samples of ~66,000 participants from all major cities of the Punjab province were tested for anti-HCV antibodies. The antibody-based seroprevalence was associated with socio-demographic variables including geographical region, age, gender and sex, and occupation. Results Overall serological response to HCV surface antigens was observed in over 17% of the population. Two of the districts were identified with significantly high prevalence in general population. Analysis by occupation showed significantly high prevalence in farmers (over 40%) followed by jobless and retired individuals, laborers and transporters. A significant difference in seroprevalence was observed in different age groups amongst sex and genders (male, female and transgender) with highest response in individuals of over 40 years of age. Moreover, most of the tested IDUs showed positive response for anti-HCV antibody. Conclusion This study represents a retrospective analysis of HCV infections in general population of the most populated province of Pakistan to identify socio-demographic groups at higher risk. Two geographical regions, Faisalabad and Okara districts, and an occupational group, farmers, were identified with significantly high HCV seroprevalence. These socio-demographic groups are the potential focused groups for follow-up studies on factors contributing to the high HCV prevalence in these groups towards orchestrating effective prevention, control and treatment.

Boolean modelling of biological networks is a well-established technique for abstracting dynamical biomolecular regulation in cells. Specifically, decoding linkages between salient regulatory network states and corresponding cell fate outcomes can help uncover pathological foundations of diseases such as cancer. Attractor landscape analysis is one such methodology which converts complex network behavior into a landscape of network states wherein each state is represented by propensity of its occurrence. Towards undertaking attractor landscape analysis of Boolean networks, we propose an Attractor Landscape Analysis Toolbox (ATLANTIS) for cell fate discovery, from biomolecular networks, and reprogramming upon network perturbation. ATLANTIS can be employed to perform both deterministic and probabilistic analyses. It has been validated by successfully reconstructing attractor landscapes from several published case studies followed by reprogramming of cell fates upon therapeutic treatment of network. Additionally, the biomolecular network of HCT-116 colorectal cancer cell line has been screened for therapeutic evaluation of drug-targets. Our results show agreement between therapeutic efficacies reported by ATLANTIS and the published literature. These case studies sufficiently highlight the in silico cell fate prediction and therapeutic screening potential of the toolbox. Lastly, ATLANTIS can also help guide single or combinatorial therapy responses towards reprogramming biomolecular networks to recover cell fates.

Sedentary life styles coupled with high-calorie diets and unhealthy social habits such as smoking, have put an ever-increasing number of people at risk of cardiovascular disorders (CVD), worldwide. A concomitant increase in the prevalence of type 2-diabetes (hyperglycemia), a risk factor for CVD, has further contributed towards escalating CVD-related mortalities. The increase in number of cases of type 2-diabetes underscores the importance of early diagnosis of cardiovascular disease in those with diabetes. In this work, we have evaluated the sensitivity and specificity of dyslipidemia and proinflammatory cytokines to be used as biomarkers for predicting the risk of CVD in those with diabetes. We hypothesize that interplay between dyslipidemia and diabetes-induced low-grade inflammation in those with type 2-diabetes increases the risk of CVD. A total of 215 participants were randomly recruited from the Cameron County Hispanic Cohort (CCHC). Of these, 99% were Mexican Americans living on Texas-Mexico border. Levels of cytokines, adipokines and lipid profile were measured. Cardiovascular disease (CVD) for this study was defined as prior diagnosis of heart attack, angina and stroke, while diabetes was defined by fasting blood glucose (FBG) of > 100 mg/dL and HbA1c of > 6.5, in accordance with American Diabetes Association (ADA) guidelines. Depending on type and distribution of data, various statistical tests were performed. Our results demonstrated higher rates of heart attack (14% vs 11.8%) and stroke (19.8% vs 10%) in those with diabetes as compared to non-diabetes. The odds of having a heart attack were eight times higher in the presence of elevated triglycerides and pro-inflammatory markers (TNFα and IL6) as compared to presence of pro-inflammatory markers only. The odds for heart attack among those with diabetes, increased by 20 fold in presence of high levels of triglycerides, TNFα, and IL6 when coupled with low levels of high-density lipid cholesterol (HDL-C). Lastly, our analysis showed that poorly controlled diabetes, characterized by HbA1c values of > 6.5 increases the odds of stroke by more than three fold. The study quantifies the role of lipid profile and pro-inflammatory markers in combination with standard risk factors towards predicting the risk of CVD in those with type 2-diabetes. The findings from the study can be directly translated for use in early diagnosis of heart disease and guiding interventions leading to a reduction in CVD-associated mortality in those with type 2-diabetes.

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