Nano-biosensors for Diagnosing Infectious and Lifestyle-Related Disease of Human: An Update

At present time, a variety of infectious and lifestyle diseases are becoming lifethreatening day by day. Development in technology and immergence of nanoscience helped to provide a better health care system. Based on the working mechanism nano-biosensors are of majorly two types: electrochemical nanobiosensor and optical nano-biosensor. Nanomaterials used in the nano-biosensor increased their efficacy, sensitivity, and selectivity of the device. Different diseases have different biomarkers to get detected such as, absorption of cholesterol oxidase detect cholesterol, glaucoma in a diabetes patient is detected by cytokine Interleukin 12 in tear, C-reactive protein is detected for liver inflammation, the SARS virus is detected by N-protein and miRNA is a potential biomarker of cancers, especially colorectal cancer. Hitherto, identification of a biomarker for a specific disease is the major work. The accuracy of nanobiosensor in diagnosing diseases put them in demand in the biomedical field. But the major drawback comes with the cost-effectiveness and use of nanomaterial in health sectors focussing on any toxicological impact of the nano-biosensor on health in long run. In this chapter, we present an overview of the working mechanism of different nano-biosensors in diagnosing different infectious and lifestyle diseases. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Immune System Development Processes with Special Emphasis on Relationship to Potential Mechanisms of MIS-C

Development of the mammalian immune system requires the intersection of myriad internal and external signals, from the migration of pluripotent stem cells to interactions with the vaginal microbiome during partuition to environmental factors that shape immune processes throughout life. Because the sequence of immune developmental events is fairly transcripted across time, multiple windows of susceptibility exist that can lead to immune dysfunction when these developmental events are perturbed. Additionally, early-life immune dysfunction can persist, leading to increased disease risk across the lifespan. Immune dysfunction can present functionally as suppression, hyperresponsivity, or inappropriate inflammation and molecularly, may involve multiple cells and signaling pathways. Thus, scenarios that lead to multisystem inflammatory syndrome in children (MIS-C) can be complex and multifaceted. This presentation will consider windows of susceptibility as well as external factors that may increase the risk of MIS-C.

Information technology & media sociology in a (still) pandemic world

The current period of disruptive social change is inextricably bound up with new means and modes of communication, information, and media streams. The Communication, Information Technologies & Media Sociology section of the American Sociological Association (CITAMS) locates these factors at the center of our collective interests, investigating them through a plethora of methods, theories, and empirical cases. Each year, CITAMS runs a special issue in ICS showcasing select works presented at the previous year's American Sociological Association conference and the affiliated Media Sociology preconference. Papers in the 2022 CITAMS Special Issue reflect a social context defined by a prolonged global pandemic and wrought by democratic uncertainty. Across these social circumstances, technology and media loom large. Simultaneously, everyday life continues and classic CITAMS scholarship sustains relevance for the ways people interact, construct identity, consume, and mobilize. All of this and more are contained in the pages of this year's Special Issue, from which readers can get a sense of what CITAMS has to offer and consider how their own work may fit within the broad CITAMS umbrella. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Novel social distancing detector using local binary pattern in comparison with principal component analysis to improve accuracy

The objective is to detect Novel Social Distancing using Local Binary Pattern (LBP) in comparison with Principal Component Analysis (PCA). Social Distance deduction is performed using Local Binary Pattern(N=20) and Principal Component Analysis(N=20) algorithms. Google AI open Images dataset is used for image detection. Dataset contains more than 10,000 images. Accuracy of Principal Component Analysis is 89.8% and Local Binary Pattern is 93.9%. There exists a statistical significant difference between LBP and PCA with (p<0.05). Local Binary Pattern appears to perform significantly better than Principal Component Analysis for Social Distancing Detection. © 2023 Author(s).

Don't let corona become our only story

This chapter is about, what impact can the corona crisis have on our mental health? Besides the relational tensions that can arise from living on top of each other, many of us are also stuck in one negative story. The chapter is about the importance making room for stories that are not about corona. It discusses about work that consisting of broadening people's horizon by letting participants discover that they consist of multiple stories. This will have an enormous impact on the mental well-being of a large part of the population, which will have lots of consequences. That is why it is important to actively make room for other stories right now, in the middle of the pandemic. Memories from the past and dreams for the future. This is a responsibility one has to take towards one's own mental health (and resilience), just as we have to do for others. Sharing other stories and making sure people don't get stuck in that one difficult story is just as much part of caring about each other and will help us get through this crisis healthier. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

[Cross-sectional study on the use of masks among occupational groups with high-risk positions for overseas import and pollution transmission].

Objective: To investigate the wearing of masks and the knowledge of masks among high-risk positions for overseas import and pollution transmission. Methods: From May 14 to 17, 2022, a convenient sampling method was used to conduct an online survey among 963 workers in high-risk positions for overseas import and pollution transmission in Beijing. The behaviors of individual use and wearing masks, the distribution and supervision of the unit, the knowledge of personal mask protection and the subjective feelings of wearing masks were analyzed. The χ(2) test and logistic regression model were used to analyze the influencing factors of the correct selection of masks. Results: The majority of the workers in high-risk positions for overseas import and pollution transmission were male (86.0%, 828/963), age concentration in 18-44 years old (68.2%, 657/963), and the majority of them had college or bachelor degrees (49.4%, 476/963). 79.4%(765/963) of the workers chose the right type of masks, female, 45-59 years old and high school education or above were the risk factors for correct selection of masks (P <0.05). Workers had good behaviors such as wearing/removing masks, but only 10.5% (101/963) could correctly rank the protective effect of different masks. 98.4% (948/963) of the workers believed that their work units had provided masks to their employees, and 99.1% (954/963) and 98.2%(946/963) of them had organized training and supervision on the use of masks, respectively. 47.4%(456/963) of the workers were uncomfortable while wearing masks. Conclusion: The overall selection and use of masks among occupational groups in high-risk positions for overseas import and pollution transmission in China need to be further standardized. It is necessary to strengthen supervision and inspection on the use of masks among occupational groups, and take improvement measures to improve the comfort of wearing masks.

Infectious diseases and social distancing under state-dependent probabilities.

We analyze the implications of infectious diseases and social distancing in an extended SIS framework to allow for the presence of stochastic shocks with state dependent probabilities. Random shocks give rise to the diffusion of a new strain of the disease which affects both the number of infectives and the average biological characteristics of the pathogen causing the disease. The probability of such shock realizations changes with the level of disease prevalence and we analyze how the properties of the state-dependent probability function affect the long run epidemiological outcome which is characterized by an invariant probability distribution supported on a range of positive prevalence levels. We show that social distancing reduces the size of the support of the steady state distribution decreasing thus the variability of disease prevalence, but in so doing it also shifts the support rightward allowing eventually for more infectives than in an uncontrolled framework. Nevertheless, social distancing is an effective control measure since it concentrates most of the mass of the distribution toward the lower extreme of its support.

Unpaid Family Caregiving-The Next Frontier of Gender Equity in a Postpandemic Future.

This Viewpoint discusses how the COVID-19 pandemic has spotlighted the critical role of unpaid family caregiving.

Quantifying optimal resource allocation strategies for controlling epidemics.

Frequent emergence of communicable diseases is a major concern worldwide. Lack of sufficient resources to mitigate the disease burden makes the situation even more challenging for lower-income countries. Hence, strategy development for disease eradication and optimal management of the social and economic burden has garnered a lot of attention in recent years. In this context, we quantify the optimal fraction of resources that can be allocated to two major intervention measures, namely reduction of disease transmission and improvement of healthcare infrastructure. Our results demonstrate that the effectiveness of each of the interventions has a significant impact on the optimal resource allocation in both long-term disease dynamics and outbreak scenarios. The optimal allocation strategy for long-term dynamics exhibits non-monotonic behaviour with respect to the effectiveness of interventions, which differs from the more intuitive strategy recommended in the case of outbreaks. Further, our results indicate that the relationship between investment in interventions and the corresponding increase in patient recovery rate or decrease in disease transmission rate plays a decisive role in determining optimal strategies. Intervention programmes with decreasing returns promote the necessity for resource sharing. Our study provides fundamental insights into determining the best response strategy when controlling epidemics in resource-constrained situations.