Unmasking Negative Pressure Pulmonary Edema Following Hanging: A Case Series.

Pulmonary edema is a rare mechanism of death that develops after partial hanging, a potential complication that physicians should consider early in the management of these patients. This case series discusses the presentation, evaluation, and treatment course of three patients who had attempted suicide by hanging and were admitted to the hospital. These patients were admitted to the intensive care unit after being stabilized and supportive treatment was provided. In all the cases, a radiological scan of the chest revealed diffuse infiltrates consistent with pulmonary edema on both sides, features of which were also noted during a diagnostic bronchoscopy. After providing the best intensive care in the hospital, two patients clinically improved, and one patient succumbed to cardiac arrest. As most patients will be brought dead to the hospital following hanging, negative pressure pulmonary edema remains underdiagnosed. Thus, this case series enumerates the possible etiologies of negative pressure pulmonary edema and its contribution to death following suicidal hanging.

Strategies for isoniazid preventive therapy in HIV-positive patients who consume alcohol.

WHO guidance to defer isoniazid preventive therapy (IPT) among those with regular alcohol use because of hepatotoxicity concerns may exclude many people living with HIV (PLWH) at high TB risk in these settings.To evaluate hepatotoxicity during TB preventive therapy (TPT) in PLWH who report alcohol use in Uganda over 10 years.We developed a Markov model of latent TB infection, isoniazid preventive therapy (IPT - a type of TPT), and TB disease using data from the Alcohol Drinkers' Exposure to Preventive Therapy for TB (ADEPTT) study. We modeled several treatment scenarios, including no IPT, IPT with liver enzyme monitoring (AST/ALT) during treatment, and IPT with pre-screening using the tuberculin skin test (TST).The no IPT scenario had 230 TB deaths/100,000 population over 10 years, which is more than that seen in any IPT scenario. IPT, even with no monitoring, was preferred over no IPT when population TB disease incidence was >50 in 100,000.For PLWH who report alcohol use in high TB burden settings, IPT should be offered, ideally with regular AST/ALT monitoring. However, even if regular monitoring is not possible, IPT is still preferable to no IPT in almost every modeled scenario..

Stochastic calculus-guided reinforcement learning: A probabilistic framework for optimal decision-making.

Stochastic Calculus-guided Reinforcement learning (SCRL) is a new way to make decisions in situations where things are uncertain. It uses mathematical principles to make better choices and improve decision-making in complex situations. SCRL works better than traditional Stochastic Reinforcement Learning (SRL) methods. In tests, SCRL showed that it can adapt and perform well. It was better than the SRL methods. SCRL had a lower dispersion value of 63.49 compared to SRL's 65.96. This means SCRL had less variation in its results. SCRL also had lower risks than SRL in the short- and long-term. SCRL's short-term risk value was 0.64, and its long-term risk value was 0.78. SRL's short-term risk value was much higher at 18.64, and its long-term risk value was 10.41. Lower risk values are better because they mean less chance of something going wrong. Overall, SCRL is a better way to make decisions when things are uncertain. It uses math to make smarter choices and has less risk than other methods. Also, different metrics, viz training rewards, learning progress, and rolling averages between SRL and SCRL, were assessed, and the study found that SCRL outperforms well compared to SRL. This makes SCRL very useful for real-world situations where decisions must be made carefully.•By leveraging mathematical principles derived from stochastic calculus, SCRL offers a robust framework for making informed choices and enhancing performance in complex scenarios.•In comparison to traditional SRL methods, SCRL demonstrates superior adaptability and efficacy, as evidenced by empirical tests.

Emerging treatment landscape for Guillain-Barré Syndrome (GBS): what's new?

INTRODUCTION: Guillain-Barré syndrome (GBS) is a monophasic immune neuropathic disorder characterized by acute paralysis. A significant portion of patients are left with residual deficits, which presents a considerable global healthcare challenge. The precise mechanisms underlying GBS pathogenesis are not fully elucidated. Recent studies have focused on postinfectious molecular mimicry and identified involvement of IgG autoantibodies and innate immune effectors in GBS. Intravenous immunoglobulins (IVIg) and plasma exchange (PE) are two established evidence-based immunomodulatory treatments for GBS, but a significant proportion of GBS patients fails to respond adequately to either therapy. This emphasizes an urgent need for novel and more potent treatments. AREAS COVERED: We discuss novel immunomodulatory therapies presently at different phases of preclinical and clinical investigation. Some drugs in development target pathophysiologic mechanisms such as IgG autoantibody catabolism and complement activation, which are relevant to GBS. EXPERT OPINION: There is an unmet need for more effective immune therapies for GBS. New immunomodulatory therapies under development may provide more potent options for GBS patients who do not respond to IVIg or PE. Future directions may include incorporating neuroprotective interventions based on evolving understanding of mechanisms underlying nerve injury and axonal degeneration.

Breast Cancer Cells Exhibit Mesenchymal-Epithelial Plasticity Following Dynamic Modulation of Matrix Stiffness.

Mesenchymal-epithelial transition (MET) is essential for tissue and organ development and is thought to contribute to cancer by enabling the establishment of metastatic lesions. Despite its importance in both health and disease, there is a lack of in vitro platforms to study MET and little is known about the regulation of MET by mechanical cues. Here, hyaluronic acid-based hydrogels with dynamic and tunable stiffnesses mimicking that of normal and tumorigenic mammary tissue are synthesized. The platform is then utilized to examine the response of mammary epithelial cells and breast cancer cells to dynamic modulation of matrix stiffness. Gradual softening of the hydrogels reduces proliferation and increases apoptosis of breast cancer cells. Moreover, breast cancer cells exhibit temporal changes in cell morphology, cytoskeletal organization, and gene expression that are consistent with mesenchymal-epithelial plasticity as the stiffness of the matrix is reduced. A reduction in matrix stiffness attenuates the expression of integrin-linked kinase, and inhibition of integrin-linked kinase impacts proliferation, apoptosis, and gene expression in cells cultured on stiff and dynamic hydrogels. Overall, these findings reveal intermediate epithelial/mesenchymal states as cells move along a matrix stiffness-mediated MET trajectory and suggest an important role for matrix mechanics in regulating mesenchymal-epithelial plasticity.

Emerging Themes and Research Frontiers in Suicide Prediction: A Scientometric Analysis.

Suicide remains a critical global health issue despite advancements in mental health treatment. The purpose of this analysis is to emphasize the development, patterns, and noteworthy outcomes of suicide prediction research. It also helps to uncover gaps and areas of under-researched topics within suicide prediction. A scientometric analysis was conducted using Biblioshiny and VOSviewer. To thoroughly assess the academic literature on suicide prediction, various scientometric methodologies such as trend analysis and citation analysis were employed. We utilized the temporal features of the Web of Science to analyze publication trends over time. Author affiliation data were used to investigate the geographic distribution of research. Cluster analysis was performed by grouping related keywords into clusters to identify overarching themes within the literature. A total of 1,703 articles from 828 different sources, spanning from 1942 to 2023, were collected for the analysis. Machine learning techniques might have a big influence on suicide-related event prediction, which would enhance attempts at suicide prevention and intervention. The conceptual understanding of suicide prediction is enhanced by scientometric analysis, which further uncovers the research gap and literature in this area. Suicide prediction research underscores that suicidal behavior is not caused by a single factor but is the result of a complex interplay of multiple factors. These factors may include biological, psychological, social, and environmental factors. Understanding and integrating these factors into predictive models is a theoretical advancement in the field. Unlike previous bibliometric studies in the field of suicide prediction that have typically focused on specific subtopics or data sources, our analysis offers a comprehensive mapping of the entire landscape. We encompass a wide range of suicide prediction literature, including research from medical, psychological, and social science domains, thus providing a holistic overview.

Is urbanization a driver of aboveground biomass allocation in a widespread tropical shrub, Turnera subulata (Turneroideae - Passifloraceae)?

Plant biomass allocation is mainly affected by the environment where each individual grows. In this sense, through the rapid global expansion of impermeable areas, urbanization has strong, albeit poorly understood, consequences on the biomass allocation of plants found in this environment. Nevertheless, the comprehension of biomass allocation processes in urban shrubs remains unclear, because most studies of urban ecology focus on tree species. This is an important gap of knowledge because a great part of urban vegetation is composed of shrubs and their association with trees have positive impacts in urban ecosystem services. In this study, we explored the ecological and potential selective pressure effects of an urbanization gradient on the biomass allocation patterns of aboveground organs of Turnera subulata, a widely distributed tropical shrub. We have demonstrated that, for certain reproductive organs, biomass allocation decreases in locations with higher urbanization. Unlike expected, the biomass of vegetative organs was not affected by urbanization, and we did not observe any effect of urbanization intensity on the variance in biomass allocation to vegetative and reproductive organs. We did not record urbanization-mediated trade-offs in biomass allocation for reproductive and vegetative organs. Instead, the biomass of these structures showed a positive relationship. Our data suggest that urbanization does not result in radical changes in biomass allocation of T. subulata, and neither in the variation of these traits. They indicate that the ability of T. subulata to thrive in urban environments may be associated with life history and morphological mechanisms. Our findings contribute to the understanding of shrub plant responses to urbanization and highlight urbanization as a potential factor in resource allocation differences for different structures and functions in plants living in these environments.

Proton Conducting Neuromorphic Materials and Devices.

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.

Exploring the dynamics of nonlocal coupled systems of fractional q -integro-differential equations with infinite delay.

In this study, we explore a coupled system of fractional integro-differential equations with infinite delay and nonlocal conditions. This system encompasses classical derivatives of different orders and the fractional derivative of Caputo-Fabrizio type, as well as the fractional integral of the q -Riemann-Liouville operator. We introduce a novel definition of the Caputo and Fabrizio differential operators, enhancing the mathematical formulation. Our main focus is to investigate the system's fundamental properties, including existence, uniqueness, and continuous dependence. Through rigorous mathematical analysis, we establish the existence and uniqueness of solutions and examine how small perturbations in initial conditions or parameters impact the solutions. For the numerical aspect, we use the finite-trapezoidal approach, a reliable method for solving fractional integro-differential equations. We provide a concise explanation of the approach and demonstrate its effectiveness through two numerical examples. Overall, this comprehensive study contributes to the understanding of coupled systems with fractional derivatives and infinite delays, with implications for various scientific and engineering fields.

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy.

Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

[The application of artificial intellect in health care: prospects and challenges for science and clinical medicine].

The paper analyses publications data related to issues of application of AI and machine learning systems in medical science and practice. The particular attention is paid to key points of AI application in health care: diagnostics, telemedicine, development of new medications, medical rehabilitation and management decision-making process. Despite broad perspectives of applying the given systems in clinical practice and pharmaceutical industry, there are a number of such unsolved problems as ensuring information security, risk of making erroneous decisions and necessity to change existing normative legal base of health care.

[Risk factors and protective factors for substance abuse among adolescents].

The article presents a brief descriptive review aimed at identifying risk factors and protective factors of drug abuse among adolescents in three important areas - personality, family and society. Individual risk factors are described: high impulsivity, rebelliousness, violation of emotional balance, alexithymia. Family risk factors were prenatal smoking of the mother, and her poor psychological status, low education of parents, the presence of family members who use psychoactive substances. Among the risk factors in society was the presence of peers who abuse drugs in the environment of a teenager. Protective factors are also identified: individual optimism, the desire to preserve their health, etc.

[Some aspects of non-medical use of narcotic substances].

The article presents foreign data on the non-medical use of certain combinations of narcotic drugs, the range of their effects on the body of patients, as well as the development of state response measures and propaganda of the rejection of the use of narcotic drugs among populations at risk. It is noted that the use of narcotic drugs without medical indications is a global public health problem. In addition to the negative impact on health, the use of narcotic drugs aggravates existing mental illnesses, and on the other hand, the presence of mental pathology accelerates the formation of drug addiction.

[The impact of alcohol and other psychoactive substance use during the covid-19 pandemic: problems and consequences].

This article discusses issues related to the use of surfactants during the COVID-19 pandemic. The global nature of this crisis has had a significant impact on the lives of people around the world, including their mental health. The introduction of quarantine and «isolation¼ measures have become one of the measures to control the spread of the disease, but such restrictions have led to various adverse psychological reactions such as anxiety, depression, post-traumatic stress disorder, as well as cases of self-mutilation and even suicide. All of these factors can negatively affect other aspects of health and lead to increased use of alcohol and other psychoactive substances. Stress, social isolation, the unpredictability of the future, loss of a job or income - all these can be motivating factors for people to turn to alcohol or other substances in search of relaxation or emotional support. However, such strategies are short-term and irrational, since alcohol consumption only worsens the mental state and further increases the risk of developing mental problems.

The ethical significance of user-control in AI-driven speech-BCIs: a narrative review.

AI-driven brain-computed interfaces aimed at restoring speech for individuals living with locked-in-syndrome are paired with ethical implications for user's autonomy, privacy and responsibility. Embedding options for sufficient levels of user-control in speech-BCI design has been proposed to mitigate these ethical challenges. However, how user-control in speech-BCIs is conceptualized and how it relates to these ethical challenges is underdetermined. In this narrative literature review, we aim to clarify and explicate the notion of user-control in speech-BCIs, to better understand in what way user-control could operationalize user's autonomy, privacy and responsibility and explore how such suggestions for increasing user-control can be translated to recommendations for the design or use of speech-BCIs. First, we identified types of user control, including executory control that can protect voluntariness of speech, and guidance control that can contribute to semantic accuracy. Second, we identified potential causes for a loss of user-control, including contributions of predictive language models, a lack of ability for neural control, or signal interference and external control. Such a loss of user control may have implications for semantic accuracy and mental privacy. Third we explored ways to design for user-control. While embedding initiation signals for users may increase executory control, they may conflict with other aims such as speed and continuity of speech. Design mechanisms for guidance control remain largely conceptual, similar trade-offs in design may be expected. We argue that preceding these trade-offs, the overarching aim of speech-BCIs needs to be defined, requiring input from current and potential users. Additionally, conceptual clarification of user-control and other (ethical) concepts in this debate has practical relevance for BCI researchers. For instance, different concepts of inner speech may have distinct ethical implications. Increased clarity of such concepts can improve anticipation of ethical implications of speech-BCIs and may help to steer design decisions.

Navigating the Web of Influence: A Bibliometric Analysis of Social Media Addiction.

Social media addiction is a behavioral dependency characterized by excessive and compulsive use of social media platforms, leading to negative impacts on various aspects of an individual's life. Bibliometric analysis is a research method used to quantitatively analyze academic literature, such as articles, books, and conference papers. It involves the application of statistical and mathematical tools to study the patterns and trends in scientific publications. This bibliometric study provides a comprehensive analysis of the literature on social media addiction, revealing patterns and dynamics within the field. Utilizing Web of Science for bibliographic data, the study employs advanced bibliometric tools like Biblioshiny and CiteSpace to map the scientific landscape. Annual scientific production, top contributing authors, key sources, trending topics, and thematic maps were identified using Biblioshiny. Additionally, network visualizations, such as co-citation networks of authors, time zone network visualizations of keyword co-occurrence, and timeline network visualizations of country collaborations, were created using CiteSpace. Our findings present an increasing trend in publications over the years, highlighting a growing recognition of social media addiction's significance. We detail the most relevant authors and sources, pinpointing key contributors and influential journals that shape the discourse. Trend topics analysis uncovers the prevalent themes, with "internet addiction" and "adolescents" at the forefront, reflecting the field's concentration on the younger population. The thematic map categorizes the research into motor themes (driving research areas), basic themes (fundamental and well-established areas), and niche themes (specialized and emerging topics), providing insight into the central and evolving topics. The study also delves into the co-occurrence of all keywords and the co-citation of authors, illustrating the interconnected nature of the research community. A timeline network visualization of country collaborations underscores the global scope of research efforts. Importantly, the study identifies critical research gaps such as underexplored demographics and emerging digital concerns and discusses practical implications, including the need for targeted intervention programs and informed policy-making. Collectively, this study charts the trajectory of social media addiction research and lays a foundation for future explorations to address identified lacunae.

Hydrazone-Linked Donor-Acceptor Covalent Organic Polymer as a Heterogeneous Photocatalyst for C-S Bond Formation.

In the realm of solar energy utilization, there is a growing focus on designing and implementing effective photocatalytic systems, for the conversion of solar energy into valuable chemical fuels. The potential of Covalent Organic Polymers (COPs) as photocatalysts for visible-light-driven organic transformation has been widely investigated, positioning them as promising candidates in this field. In the design of COPs, introducing a donor-acceptor arrangement facilitates the transfer of electrons from the donor to the acceptor, creating a charge transfer complex and leading to enhanced conductivity and improved charge separation. Here we present a novel hydrazone-linked covalent organic polymer ETBC-PyHz containing TPE donor and pyridine acceptor. Utilizing this, an efficient method has been developed for an oxidative cross-coupling reaction involving C-S bond formation. This process involves arylhydrazines and arenethiols, and results in the production of unsymmetrical diaryl sulfides via the formation of aryl and thioarene radicals. This conversion holds significant importance because the byproducts produced during the process are nitrogen and water, making it environmentally benign.

Genetic Variations in TrkB.T1 Isoform and Their Association with Somatic and Psychological Symptoms in Individuals with IBS.

Irritable bowel syndrome (IBS), a disorder of gut-brain interaction, is often comorbid with somatic pain and psychological disorders. Dysregulated signaling of brain-derived neurotrophic factor (BDNF) and its receptor, tropomyosin-related kinase B (TrkB), has been implicated in somatic-psychological symptoms in individuals with IBS. We investigated the association of 10 single nucleotide polymorphisms (SNPs) in the regulatory 3' untranslated region (UTR) of NTRK2 (TrkB) kinase domain-deficient truncated isoform (TrkB.T1) and BDNF Val66Met SNP with somatic and psychological symptoms and quality of life in a cohort from the United States (U.S.) (IBS n=464; healthy controls n=156). We found that the homozygous recessive genotype (G/G) of rs2013566 in individuals with IBS is associated with worsened somatic symptoms, including headache, back pain, joint pain, muscle pain, and somatization as well as diminished sleep quality, energy level and overall quality of life. Validation using United Kingdom BioBank (UKBB) data confirmed the association of rs2013566 with increased likelihood of headache. Several SNPs (rs1627784, rs1624327, rs1147198) showed significant associations with muscle pain in our U.S. cohort. These 4 SNPs are predominantly located in H3K4Me1-enriched regions, suggesting their enhancer and/or transcription regulation potential. Our findings suggest that genetic variation within the 3'UTR region of the TrkB.T1 isoform may contribute to comorbid conditions in individuals with IBS, resulting in a spectrum of somatic and psychological symptoms impacting their quality of life. These findings advance our understanding of the genetic interaction between BDNF/TrkB pathways and somatic-psychological symptoms in IBS, highlighting the importance of further exploring this interaction for potential clinical applications. PERSPECTIVE: This study aims to understand the genetic effects on IBS-related symptoms across somatic, psychological, and quality of life domains, validated by UKBB data. The rs2013566 homozygous recessive genotype correlates with worsened somatic symptoms and reduced quality of life, emphasizing its clinical significance.

Emergence of imported cutaneous leishmaniasis caused by Leishmania major: a case series from Kerala, India.

Cutaneous leishmaniasis (CL) is often considered a 'great imitator' and is the most common form of leishmaniasis. The Leishmania species responsible for CL varies among countries, as these species exhibit specific distribution patterns. The increased mobility of people across countries has resulted in the imported incidences of leishmaniasis caused by non-endemic species of Leishmania. During 2023, we confirmed three CL cases caused by L. major from Kerala, India, and upon detailed investigation, these were identified to be imported from the Middle East and Kazakhstan regions. This is the first report of CL caused by L. major from Kerala. The lesion morphology, detection of anti-rK 39 antibody and Leishmania parasite DNA from the blood samples were the unique observations of these cases. Kerala, being an emerging endemic zone of visceral leishmaniasis (VL) and CL, the imported incidences of leishmaniasis by non-endemic species can pose a significant threat, potentially initiating new transmission cycles of leishmaniasis caused by non-endemic species.