Effect of Recombinant Cytokines on the Expression of Natural Killer Cell Receptors from Patients with TB or/and HIV Infection

BACKGROUND: NK cells express several specialized receptors through which they recognize and discriminate virally-infected/tumor cells efficiently from healthy cells and kill them. This ability to lyse is regulated by an array of inhibitory or activating receptors. The present study investigated the frequency of various NK receptors expressed by NK cell subsets from HIV-infected TB patients. The effect of IL-15+IL-12 stimulation on the expression of NK receptors was also studied. METHODOLOGY/PRINCIPAL FINDINGS: The study included 15 individuals each from normal healthy subjects, pulmonary tuberculosis patients, HIV-infected individuals and patients with HIV and tuberculosis co-infection. The expression of NK cell receptors was analyzed on two NK cell subsets within the peripheral blood: CD16+CD3- and CD56+CD3- using flow cytometry. The expression of inhibitory receptors (CD158a, CD158b, KIRp70, CD85j and NKG2A) on NK subsets was increased in HIV, when compared to NHS. But the response in HIV-TB was not uniform. Stimulation with IL-15+IL-12 dropped (p<0.05) the expression of CD85j and NKG2A in HIV. The basal expression of natural cytotoxicity receptors (NKp30 and NKp46) on NK cell subsets was lowered (p<0.05) in HIV and HIV-TB as compared to NHS. However, the expression of NKp44 and NKG2D was elevated in HIV. Enhanced NKp46 and NKG2D expression was observed in HIV with IL-15+IL-12 stimulation. The coreceptor NKp80 was found to be expressed in higher numbers on NK subsets from HIV compared to NHS, which elevated with IL-15+IL-12 stimulation. The expression of NK receptors and response to stimulation was primarily on CD56+CD3- subset. CONCLUSIONS/SIGNIFICANCE: IL-15+IL-12 has an immunomodulatory effect on NK cell subsets from HIV-infected individuals viz down-regulation of iNKRs, elevation of activatory receptors NKp46 and NKG2D, and induction of coreceptor NKp80. IL-15+IL-12 is not likely to be of value when co-infected with TB probably due to the influence of tuberculosis

Contribution of infection and vaccination to population-level seroprevalence through two COVID waves in Tamil Nadu, India.

This study employs repeated, large panels of serological surveys to document rapid and substantial waning of SARS-CoV-2 antibodies at the population level and to calculate the extent to which infection and vaccination separately contribute to seroprevalence estimates. Four rounds of serological surveys were conducted, spanning two COVID waves (October 2020 and April-May 2021), in Tamil Nadu (population 72 million) state in India. Each round included representative populations in each district of the state, totaling ≥ 20,000 persons per round. State-level seroprevalence was 31.5% in round 1 (October-November 2020), after India's first COVID wave. Seroprevalence fell to 22.9% in round 2 (April 2021), a roughly one-third decline in 6 months, consistent with dramatic waning of SARS-Cov-2 antibodies from natural infection. Seroprevalence rose to 67.1% by round 3 (June-July 2021), with infections from the Delta-variant induced second COVID wave accounting for 74% of the increase. Seroprevalence rose to 93.1% by round 4 (December 2021-January 2022), with vaccinations accounting for 63% of the increase. Antibodies also appear to wane after vaccination. Seroprevalence in urban areas was higher than in rural areas, but the gap shrunk over time (35.7 v. 25.7% in round 1, 89.8% v. 91.4% in round 4) as the epidemic spread even in low-density rural areas

Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges

Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is a need for an automated system that can flag missed polyps during the examination and improve patient care. Deep learning has emerged as a promising solution to this challenge as it can assist endoscopists in detecting and classifying overlooked polyps and abnormalities in real time, improving the accuracy of diagnosis and enhancing treatment. In addition to the algorithm’s accuracy, transparency and interpretability are crucial to explaining the whys and hows of the algorithm’s prediction. Further, conclusions based on incorrect decisions may be fatal, especially in medicine. Despite these pitfalls, most algorithms are developed in private data, closed source, or proprietary software, and methods lack reproducibility. Therefore, to promote the development of efficient and transparent methods, we have organized the “Medico automatic polyp segmentation (Medico 2020)” and “MedAI: Transparency in Medical Image Segmentation (MedAI 2021)” competitions. The Medico 2020 challenge received submissions from 17 teams, while the MedAI 2021 challenge also gathered submissions from another 17 distinct teams in the following year. We present a comprehensive summary and analyze each contribution, highlight the strength of the best-performing methods, and discuss the possibility of clinical translations of such methods into the clinic. Our analysis revealed that the participants improved dice coefficient metrics from 0.8607 in 2020 to 0.8993 in 2021 despite adding diverse and challenging frames (containing irregular, smaller, sessile, or flat polyps), which are frequently missed during a routine clinical examination. For the instrument segmentation task, the best team obtained a mean Intersection over union metric of 0.9364. For the transparency task, a multi-disciplinary team, including expert gastroenterologists, accessed each submission and evaluated the team based on open-source practices, failure case analysis, ablation studies, usability and understandability of evaluations to gain a deeper understanding of the models’ credibility for clinical deployment. The best team obtained a final transparency score of 21 out of 25. Through the comprehensive analysis of the challenge, we not only highlight the advancements in polyp and surgical instrument segmentation but also encourage subjective evaluation for building more transparent and understandable AI-based colonoscopy systems. Moreover, we discuss the need for multi-center and out-of-distribution testing to address the current limitations of the methods to reduce the cancer burden and improve patient care

Rates of Prevalent Colorectal Cancer Occurrence in Persons 75 Years of Age and Older: A Population-Based National Study.

BACKGROUND/AIMS: There is a lack of studies describing the epidemiology of colorectal cancer (CRC) in patients aged 75 years and older (elderly). Current guidelines recommend against routine screening colonoscopies in this population. We sought to describe the epidemiology of CRC in the elderly, utilizing a large, population-based database as this may impact screening guidelines in this population. METHODS: Utilizing a commercial database (Explorys Inc, Cleveland, OH), we identified a cohort of patients with a first-ever diagnosis of CRC between 2012 and 2017 based on the Systematized Nomenclature of Medicine-Clinical Terms. We calculated the rate of first-ever CRC occurrence in the elderly, described age, race, and gender-based rates of new CRC diagnoses, and identified associated conditions for new CRC in the elderly. RESULTS: The rate of first-ever CRC in the elderly (aged 75 and above) was 102.6/100,000 persons. The rate of new CRC was higher in males than females and in African Americans than Caucasians and Asians. There was a higher prevalence of right than left colon cancer. The rate of new CRC was higher in elderly with certain comorbidities. CONCLUSION: The rate of new CRC diagnosis in the elderly was substantially greater compared to the overall population. Screening would be justified especially if a patient\u27s life expectancy warrants it particularly if the patient has specific associated conditions that increase the risk for CRC