Tuberculosis of the Gallbladder

Analysis of 5 patients with gallbladder tuberculosis who had open cholecystectomy and review of literature have shown that, although still rare it presents as a part of systemic miliary tuberculosis, abdominal tuberculosis, isolated gallbladder tuberculosis and as acalculus cholecystitis in anergic patients. There are no pathognomonic signs, the diagnosis depends on suspicion of tuberculosis, peroperative findings and histological examination

From Text to MITRE Techniques: Exploring the Malicious Use of Large Language Models for Generating Cyber Attack Payloads

This research article critically examines the potential risks and implications arising from the malicious utilization of large language models(LLM), focusing specifically on ChatGPT and Google's Bard. Although these large language models have numerous beneficial applications, the misuse of this technology by cybercriminals for creating offensive payloads and tools is a significant concern. In this study, we systematically generated implementable code for the top-10 MITRE Techniques prevalent in 2022, utilizing ChatGPT, and conduct a comparative analysis of its performance with Google's Bard. Our experimentation reveals that ChatGPT has the potential to enable attackers to accelerate the operation of more targeted and sophisticated attacks. Additionally, the technology provides amateur attackers with more capabilities to perform a wide range of attacks and empowers script kiddies to develop customized tools that contribute to the acceleration of cybercrime. Furthermore, LLMs significantly benefits malware authors, particularly ransomware gangs, in generating sophisticated variants of wiper and ransomware attacks with ease. On a positive note, our study also highlights how offensive security researchers and pentesters can make use of LLMs to simulate realistic attack scenarios, identify potential vulnerabilities, and better protect organizations. Overall, we conclude by emphasizing the need for increased vigilance in mitigating the risks associated with LLMs. This includes implementing robust security measures, increasing awareness and education around the potential risks of this technology, and collaborating with security experts to stay ahead of emerging threats

Field and laboratory comparative evaluation of rapid malaria diagnostic tests versus traditional and molecular techniques in India

<p>Abstract</p> <p>Background</p> <p>Malaria presents a diagnostic challenge in most tropical countries. Microscopy remains the gold standard for diagnosing malaria infections in clinical practice and research. However, microscopy is labour intensive, requires significant skills and time, which causes therapeutic delays. The objective of obtaining result quickly from the examination of blood samples from patients with suspected malaria is now made possible with the introduction of rapid malaria diagnostic tests (RDTs). Several RDTs are available, which are fast, reliable and simple to use and can detect <it>Plasmodium falciparum </it>and non-falciparum infections or both. A study was conducted in tribal areas of central India to measure the overall performance of several RDTs for diagnosis of <it>P. falciparum </it>and non-falciparum infections in comparison with traditional and molecular techniques. Such data will be used to guide procurement decisions of policy makers and programme managers.</p> <p>Methods</p> <p>Five commercially available RDTs were tested simultaneously in field in parallel with peripheral blood smears in outbreak-affected areas. The evaluation is designed to provide comparative data on the performance of each RDT. In addition, molecular method i.e. polymerase chain reaction (PCR) was also carried out to compare all three methods.</p> <p>Results</p> <p>A total of 372 patients with a clinical suspicion of malaria from Bajag Primary Health Centre (PHC) of district Dindori and Satanwada PHC of district Shivpuri attending the field clinics of Regional Medical Research Centre were included in the study. The analysis revealed that the First Response Malaria Antigen pLDH/HRP2 combo test was 94.7% sensitive (95% CI 89.5-97.7) and 69.9% specific (95% CI 63.6-75.6) for <it>P. falciparum</it>. However, for non-falciparum infections (<it>Plasmodium vivax</it>) the test was 84.2% sensitive (95% CI 72.1-92.5) and 96.5% specific (95% CI 93.8-98.2). The Parascreen represented a good alternative. All other RDTs were relatively less sensitive for both <it>P. falciparum </it>and non-falciparum infections.</p> <p>Conclusions</p> <p>The results in this study show comparative performance between microscopy, various RDTs and PCR. Despite some inherent limitation in the five RDTs tested, First Response clearly has an advantage over other RDTs. The results suggest that RDTs could play and will play an important role in malaria diagnosis.</p

DMAPT: Study of Data Mining and Machine Learning Techniques in Advanced Persistent Threat Attribution and Detection

Modern-day malware is intelligent enough to hide its presence and perform stealthy operations in the background. Advance Persistent Threat (APT) is one such kind of malware attack on sensitive corporate and banking networks to stay there for a long time undetected. In real-time corporate networks, identifying the presence of intruders is a big challenging task for security experts. Recent APT attacks like Carbanak, The Big Bang, and Red Echo attack (targeting the Indian power sector) are ringing alarms globally. New data exfiltration methods and advancements in malware techniques are the two main reasons for rapid and robust APT evolution. Although many traditional and hybrid methods are available to detect this stealthy malware, the number of target-specific attacks are increasing rapidly at global level. Attackers have been crafting payloads resistant to malware sandbox environments so that traditional sandboxing techniques may not work with these APT malware detection. In this paper, we shed light on various Data Mining, Machine Learning techniques and frameworks used in both Attribution and Detection of APT malware. Added to this, our work highlight GAP analysis and need for paradigm shift in existing techniques to deal with evolving modern APT malware

Multiple exciton generation in VO2

Multiple exciton generation (MEG) is a widely studied phenomenon in semiconductor nanocrystals and quantum dots, aimed at improving the energy conversion efficiency of solar cells. MEG is the process wherein incident photon energy is significantly larger than the band gap, and the resulting photoexcited carriers relax by generating additional electron-hole pairs, rather than decaying by heat dissipation. Here, we present an experimental demonstration of MEG in a prototype strongly correlated material, VO2, through photocurrent spectroscopy and ultrafast transient reflectivity measurements, both of which are considered the most prominent ways for detecting MEG in working devices. The key result of this paper is the observation of MEG at room temperature (in a correlated insulating phase of VO2), and the estimated threshold for MEG is 3Eg. We demonstrate an escalated photocurrent due to MEG in VO2, and quantum efficiency is found to exceed 100%. Our studies suggest that this phenomenon is a manifestation of expeditious impact ionization due to stronger electron correlations and could be exploited in a large number of strongly correlated materials.Comment: 6 pages, 5 figures, Physical Review

Does rapid urbanization aggravate health disparities? Reflections on the epidemiological transition in Pune, India

Background: Rapid urbanization in low- and middle-income countries reinforces risk and epidemiological transition in urban societies, which are characterized by high socioeconomic gradients. Limited availability of disaggregated morbidity data in these settings impedes research on epidemiological profiles of different population subgroups. Objective: The study aimed to analyze the epidemiological transition in the emerging megacity of Pune with respect to changing morbidity and mortality patterns, also taking into consideration health disparities among different socioeconomic groups. Design: A mixed-methods approach was used, comprising secondary analysis of mortality data, a survey among 900 households in six neighborhoods with different socioeconomic profiles, 46 in-depth interviews with laypeople, and expert interviews with 37 health care providers and 22 other health care workers. Results: The mortality data account for an epidemiological transition with an increasing number of deaths due to non-communicable diseases (NCDs) in Pune. The share of deaths due to infectious and parasitic diseases remained nearly constant, though the cause of deaths changed considerably within this group. The survey data and expert interviews indicated a slightly higher prevalence of diabetes and hypertension among higher socioeconomic groups, but a higher incidence and more frequent complications and comorbidities in lower socioeconomic groups. Although the self-reported morbidity for malaria, gastroenteritis, and tuberculosis did not show a socioeconomic pattern, experts estimated the prevalence in lower socioeconomic groups to be higher, though all groups in Pune would be affected. Conclusions: The rising burden of NCDs among all socioeconomic groups and the concurrent persistence of communicable diseases pose a major challenge for public health. Improvement of urban health requires a stronger focus on health promotion and disease prevention for all socioeconomic groups with a holistic understanding of urban health. In order to derive evidence-based solutions and interventions, routine surveillance data become indispensable

Metabolomics-Driven Mining of Metabolite Resources:Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants

Therapeutic efficacy of artemether–lumefantrine for the treatment of uncomplicated Plasmodium falciparum malaria from three highly malarious states in India

Additional file 1. Flowchart showing site-wise enrolment and follow-up profile