Synthesis of Isatin-derived Heterocycles with Promising Anticancer Activities.

Isatin or 1H-indole-2,3-dione skeleton has been playing a significant role in drug de-sign and development. Isatin itself and many of its derivatives are widely distributed in naturally occurring bioactive compounds. Various synthetic isatin derivatives were found to possess a broad range of significant pharmacological efficacies especially anti-cancer activity against a wide variety of cancer cell lines. Interestingly, on a few occasions, some isatin-derived scaffolds were reported as more potent than the tested reputed drug molecules. As a result, isatin-derived compounds have been gaining significant attention in cancer-based drug developments. In this re-view, we have summarized literature reported during the last two decades related to the synthesis of structurally diverse isatin-derived scaffolds with promising anti-cancer activities.

Inhibition of autophagy as a novel treatment for neurofibromatosis type 1 tumors.

Neurofibromatosis type 1 (NF1) is a genetic disorder caused by mutation of the NF1 gene that is associated with various symptoms, including the formation of benign tumors, called neurofibromas, within nerves. Drug treatments are currently limited. The mitogen-activated protein kinase kinase (MEK) inhibitor selumetinib is used for a subset of plexiform neurofibromas (PNs) but is not always effective and can cause side effects. Therefore, there is a clear need to discover new drugs to target NF1-deficient tumor cells. Using a Drosophila cell model of NF1, we performed synthetic lethal screens to identify novel drug targets. We identified 54 gene candidates, which were validated with variable dose analysis as a secondary screen. Pathways associated with five candidates could be targeted using existing drugs. Among these, chloroquine (CQ) and bafilomycin A1, known to target the autophagy pathway, showed the greatest potential for selectively killing NF1-deficient Drosophila cells. When further investigating autophagy-related genes, we found that 14 out of 30 genes tested had a synthetic lethal interaction with NF1. These 14 genes are involved in multiple aspects of the autophagy pathway and can be targeted with additional drugs that mediate the autophagy pathway, although CQ was the most effective. The lethal effect of autophagy inhibitors was conserved in a panel of human NF1-deficient Schwann cell lines, highlighting their translational potential. The effect of CQ was also conserved in a Drosophila NF1 in vivo model and in a xenografted NF1-deficient tumor cell line grown in mice, with CQ treatment resulting in a more significant reduction in tumor growth than selumetinib treatment. Furthermore, combined treatment with CQ and selumetinib resulted in a further reduction in NF1-deficient cell viability. In conclusion, NF1-deficient cells are vulnerable to disruption of the autophagy pathway. This pathway represents a promising target for the treatment of NF1-associated tumors, and we identified CQ as a candidate drug for the treatment of NF1 tumors.

Biomarkers in sepsis.

Sepsis is a life-threatening condition characterized by dysregulated host response to infection leading to organ dysfunction. Despite advances in understanding its pathology, sepsis remains a global health concern and remains a major contributor to mortality. Timely identification is crucial for improving clinical outcomes, as delayed treatment significantly impacts survival. Accordingly, biomarkers play a pivotal role in diagnosis, risk stratification, and management. This review comprehensively discusses various biomarkers in sepsis and their potential application in antimicrobial stewardship and risk assessment. Biomarkers such as white blood cell count, neutrophil to lymphocyte ratio, erythrocyte sedimentation rate, C-reactive protein, interleukin-6, presepsin, and procalcitonin have been extensively studied for their diagnostic and prognostic value as well as in guiding antimicrobial therapy. Furthermore, this review explores the role of biomarkers in risk stratification, emphasizing the importance of identifying high-risk patients who may benefit from specific therapeutic interventions. Moreover, the review discusses the emerging field of transcriptional diagnostics and metagenomic sequencing. Advances in sequencing have enabled the identification of host response signatures and microbial genomes, offering insight into disease pathology and aiding species identification. In conclusion, this review provides a comprehensive overview of the current understanding and future directions of biomarker-based approaches in sepsis diagnosis, management, and personalized therapy.

A review on strategies for crop improvement against drought stress through molecular insights.

The demand for food goods is rising along with the world population growth, which is directly related to the yield of agricultural crops around the world. However, a number of environmental factors, including floods, salinity, moisture, and drought, have a detrimental effect on agricultural production around the world. Among all of these stresses, drought stress (DS) poses a constant threat to agricultural crops and is a significant impediment to global agricultural productivity. Its potency and severity are expected to increase in the future years. A variety of techniques have been used to generate drought-resistant plants in order to get around this restriction. Different crop plants exhibit specific traits that contribute to drought resistance (DR), such as early flowering, drought escape (DE), and leaf traits. We are highlighting numerous methods that can be used to overcome the effects of DS in this review. Agronomic methods, transgenic methods, the use of sufficient fertilizers, and molecular methods such as clustered regularly interspaced short palindromic repeats (CRISPRs)-associated nuclease 9 (Cas9), virus-induced gene silencing (VIGS), quantitative trait loci (QTL) mapping, microRNA (miRNA) technology, and OMICS-based approaches make up the majority of these techniques. CRISPR technology has rapidly become an increasingly popular choice among researchers exploring natural tolerance to abiotic stresses although, only a few plants have been produced so far using this technique. In order to address the difficulties imposed by DS, new plants utilizing the CRISPR technology must be developed.

Protein Kinase C (PKC) in Neurological Health: Implications for Alzheimer's Disease and Chronic Alcohol Consumption.

Protein kinase C (PKC) is a diverse enzyme family crucial for cell signalling in various organs. Its dysregulation is linked to numerous diseases, including cancer, cardiovascular disorders, and neurological problems. In the brain, PKC plays pivotal roles in synaptic plasticity, learning, memory, and neuronal survival. Specifically, PKC's involvement in Alzheimer's Disease (AD) pathogenesis is of significant interest. The dysregulation of PKC signalling has been linked to neurological disorders, including AD. This review elucidates PKC's pivotal role in neurological health, particularly its implications in AD pathogenesis and chronic alcohol addiction. AD, characterised by neurodegeneration, implicates PKC dysregulation in synaptic dysfunction and cognitive decline. Conversely, chronic alcohol consumption elicits neural adaptations intertwined with PKC signalling, exacerbating addictive behaviours. By unravelling PKC's involvement in these afflictions, potential therapeutic avenues emerge, offering promise for ameliorating their debilitating effects. This review navigates the complex interplay between PKC, AD pathology, and alcohol addiction, illuminating pathways for future neurotherapeutic interventions.

Epidemiology and Outcomes of Hospitalized Chimeric Antigen Receptor T-Cell (CAR-T) Therapy Patients Who Developed Acute Respiratory Failure.

Objectives:The aim of the study was to examine the incidence, baseline characteristics, and outcomes of Chimeric Antigen Receptor T-cell (CAR-T) therapy admissions in individuals who developed acute respiratory failure (ARF). The study utilized the National Inpatient Sample (NIS) database for the years 2017 to 2020. Methods: The study identified CAR-T cell therapy hospitalizations through the International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS) codes. Patients with acute respiratory failure (ARF) were further classified using specific International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) codes. Descriptive statistics were performed to analyze baseline characteristics, comorbidities, complications, and outcomes. Results: Analysis of the NIS Database identified 5545 CAR-T therapy admissions between 2017 and 2020, revealing a rising trend over time. In our study, we found that hypertension (39%), dyslipidemia (21.7%), and venous thromboembolism (13%) were the most frequently observed comorbidities in CAR-T cell therapy admissions. Acute respiratory failure (ARF) was reported in 7.1% of admissions, and they had higher all-cause in-hospital mortality than CAR-T cell therapy admissions without ARF (32.9% vs 1.3%, P < 0.001). ARF admissions that required invasive mechanical ventilation (IMV) also had higher all-cause in-hospital mortality compared to admissions not requiring IMV (48.9% vs 11.8%, P = 0.001). There was no difference in the mortality rate among admissions with non-Hodgkin's Lymphoma, Multiple Myeloma, and Leukemia that utilized CAR-T therapy. Conclusions: In this largest study to date, we illuminate the incidence and outcomes of CAR-T cell therapy admissions with ARF. Higher mortality rates were observed in CAR-T cell therapy admissions with ARF. The study emphasizes the crucial role of interdisciplinary collaboration in CAR-T patient management and calls for additional research to clarify ARF's etiology and inform effective management strategies.

Exploring the Role of ChatGPT in Cardiology: A Systematic Review of the Current Literature.

Chat Generative Pre-Trained Transformer (ChatGPT) is a chatbot based on a large language model that has gained public interest since its release in November 2022. This systematic review examines the current literature on the potential applications of ChatGPT in cardiology. A systematic literature search was conducted to retrieve all publications on ChatGPT in PubMed, Scopus, MedRxiv, and the Cochrane Library published on or before September 30, 2023. Search terms relating to ChatGPT and cardiology were used. Publications without relevance to ChatGPT and cardiology were excluded. The included publications were divided into cohorts. Cohort A examined ChatGPT's role in improving patient health literacy. Cohort B explored ChatGPT's role in clinical care. Cohort C examined ChatGPT's role in future literature and research. Cohort D included case reports that used ChatGPT. A total of 115 publications were found across all databases. Twenty-four publications met the inclusion criteria and were included in the review. Cohort A-C included a total of 14 records comprised of editorials/letters to the editor (29%), research letters/correspondence (21%), review papers (21%), observational studies (7%), research studies (7%), and short reports (7%). Cohort D included 10 case reports. No relevant systematic literature reviews, meta-analyses, or randomized controlled trials were identified in the search.  Based on this review of the literature, ChatGPT has the potential to enhance patient education, support clinicians providing clinical care, and enhance the development of future literature. However, further studies are needed to understand the potential applications of ChatGPT in cardiology and to address ethical concerns regarding the delivery of medical advice and the authoring of manuscripts.

Complex decision making in a patient with lung cancer with incidentally found fast-growing atrial mass.

Atrial myxomas are typically found in the left atrium and are the most common among overall rare cardiac tumors. Herein, we describe the clinical course of a 72-year-old female with non-small cell lung adenocarcinoma found to have an atrial mass during an imaging for evaluation for lung cancer progression. Differentiating between distinct types of masses can pose a challenge to the treatment team especially in the setting of exiting malignancy. This case demonstrates the complex decision making involved in the diagnosis, and timing of intervention to remove atrial mass in patients with frailty and a fast-growing cardiac mass.

Borophene: a piezocatalyst for water remediation.

Borophene is an emerging two-dimensional material exhibiting exceptional piezocatalytic activity under the influence of ultrasonic vibrations, as exemplified herein by the decomposition of highly stable organic dyes in water. After 6 minutes of exposure, borophene sheets converted up to 92 percent of a mixture of dye molecules at room temperature.

A Study on the Epidemiology of COVID-19-Related Guillain-Barré Syndrome in the United States.

INTRODUCTION: Several neurological complications have been reported with COVID-19, including Guillain-Barré syndrome (GBS). We looked at incidence, baseline characteristics, and in-hospital outcomes of COVID-19-associated GBS in the United States. STUDY DESIGN AND METHODS: We conducted a retrospective analysis using the US National Inpatient Sample database to identify hospitalizations for COVID-19 and GBS, using International Classification of Disease, 10th Revision, codes G610 and G650 for GBS and U071 for COVID-19. The codes used in this study are listed in Supplemental Digital Content 1 (see e Appendix, http://links.lww.com/JCND/A69). RESULTS: In total, 13,705 GBS admissions were recorded nationwide in 2020; of these, 1155 (8.43%) were associated with COVID-19. The frequency of GBS in COVID-19 admissions was 0.07%, compared with 0.08% in non-COVID-19 admissions (P = 0.8166). COVID-19 cohort with GBS had higher utilization of invasive mechanical ventilation (20.8% vs. 11.8%, P < 0.001) in comparison with COVID-19 cohort without GBS. GBS admissions with COVID-19 exhibited significantly higher inpatient mortality (12.2% vs. 3%, P < 0.001) compared with GBS admissions without COVID-19. INTERPRETATION: Our findings underscore GBS as a rare yet severe complication of COVID-19, highlighting a significant difference in mortality when compared with GBS not associated with COVID-19.

Response of coastal phytoplankton to pollution from various sources in the coastal Bay of Bengal.

The coastal ocean receives nutrient pollutants from various sources, such as aerosols, municipal sewage, industrial effluents and groundwater discharge, with variable concentrations and stoichiometric ratios. The objective of this study is to examine the response of phytoplankton to these pollutants in the coastal water under silicate-rich and silicate-poor coastal waters. In order to achieve this, a microcosm experiment was conducted by adding the pollutants from various sources to the coastal waters during November and January, when the water column physicochemical characteristics are different. Low salinity and high silicate concentration were observed during November due to the influence of river discharge contrasting to that observed during January. Among the various sources of pollutants used, aerosols and industrial effluents did not contribute silicate whereas groundwater and municipal sewage contained high concentrations of silicate along with nitrate and phosphate during both the study periods. During November, an increase in phytoplankton biomass was noticed in all pollutant-added samples, except municipal sewage, due to the limitation of growth by nitrate. On the other hand, an increase in biomass and abundance of phytoplankton was observed in all pollutant-added samples, except for aerosol, during January. Increase in phytoplankton abundance associated with decrease in biomass was observed in aerosol-added sample due to co-limitation of silicate and phosphate during January. A significant response of Thalassiothrix sp. was observed for industrial effluent-added sample during November, whereas Chaetoceros sp. and Skeletonema sp. increased significantly during January. Higher increase in phytoplankton biomass was observed during November associated with higher availability of silicate in the coastal waters in January. Interestingly, an increase in the contribution of dinoflagellates was observed during January associated with low silicate in the coastal waters, suggesting that the concentration of silicate in the coastal waters determines the response of the phytoplankton group to pollutant inputs. This study suggested that silicate concentration in the coastal waters must be considered, in addition to the coastal currents, while computing dilution factors for the release of pollutants to the coastal ocean to avoid occurrence of unwanted phytoplankton blooms.

Paediatricians' perspectives in treating lower urinary tract symptoms: a qualitative exploratory needs assessment study.

BACKGROUND: Paediatric lower urinary tract symptoms (LUTS) are common experiences among school-aged children, with prevalence rates reaching as high as 20%. Paediatricians are often first-line stakeholders in providing treatment for these bothersome symptoms, yet there is no formal resource to support them with the treatment of LUTS. Evaluating paediatricians' experiences is an important step in informing health promotion efforts to improve health outcomes in children. This study aims to explore paediatricians' knowledge, beliefs, practice patterns, and perceived barriers and facilitators in providing LUTS care. METHODS: In this qualitative study, we conducted semistructured focus groups of paediatricians within California. Focus groups were conducted via Zoom, and participants were enrolled until thematic saturation was reached. Participants were asked about their current practices, knowledge and beliefs, barriers and facilitators to care, training and education, and responsibility for behaviour and action. Thematic analysis was performed using deductive and inductive approaches; themes were mapped through an iterative, team-based process. RESULTS: 15 paediatricians, aged 30-69 years, with 13 (86.7%) women, were interviewed. Most (11, 73.3%) practised in general outpatient settings. Interviewed paediatricians recognised paediatric LUTS as a common problem that can significantly impact children's well-being. In practice, paediatricians did not actively screen for LUTS beyond the potty-training milestone due to short visit duration and competing healthcare demands. Lack of guidelines, parental mistrust and inadequate clinical education were barriers identified by paediatricians. CONCLUSIONS: Paediatricians expressed a willingness to help patients but indicated several limitations to providing adequate LUTS care. Future professional development work can emphasise guideline development, early screening strategies to support timely intervention and better education for clinicians.

Incidence and inhospital outcomes of coronavirus disease 2019-associated pulmonary aspergillosis in the United States.

OBJECTIVE: The aim of this study was to estimate the predictors, associations, and outcomes of COVID-19-associated pulmonary disease (CAPA) in the United States. STUDY DESIGN AND METHODS: This retrospective cohort study was performed by using the National Inpatient Sample Database 2020 to identify coronavirus disease 2019 (COVID-19) and CAPA hospitalizations. Baseline variables and outcomes were compared between COVID-19 hospitalizations without aspergillosis and those with aspergillosis. These variables were then used to perform an adjusted analysis for obtaining predictors and factors associated with CAPA and its inhospital mortality. RESULTS: Of the 1,020,880 hospitalizations identified with the principal diagnosis of COVID-19, CAPA was identified in 1510 (0.1%) hospitalizations. The CAPA cohort consisted of a higher proportion of males (58%) as well as racial and ethnic minorities (Hispanics, Blacks, and others [including Asian or Pacific islanders, native Americans]). Inhospital mortality was significantly higher (47.35% vs. 10.87%, P < 0.001), the average length of stay was longer (27.61 vs. 7.29 days, P < 0.001), and the mean cost per hospitalization was higher ($121,560 vs. $18,423, P < 0.001) in the CAPA group compared to COVID-19 without aspergillosis. History of solid organ transplant, chronic obstructive pulmonary disease, and venous thromboembolism were associated with higher odds of CAPA among other factors. The use of invasive mechanical ventilation (adjusted odds ratio [aOR] 6.24, P < 0.001), acute kidney injury (aOR 2.02, P = 0.028), and septic shock (aOR 2.07, P = 0.018) were associated with higher inhospital mortality in the CAPA cohort. CONCLUSION: While CAPA is an infrequent complication during hospitalizations for COVID-19, it significantly increases all-cause mortality, prolongs hospital stays, and leads to higher hospital expenses compared to COVID-19 cases without aspergillosis.

Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review.

BACKGROUND: Oral Potentially Malignant Disorders (OPMDs) refer to a heterogenous group of clinical presentations with heightened rate of malignant transformation. Identification of risk levels in OPMDs is crucial to determine the need for active intervention in high-risk patients and routine follow-up in low-risk ones. Machine learning models has shown tremendous potential in several areas of dentistry that strongly suggest its application to estimate rate of malignant transformation of precancerous lesions. METHODS: A comprehensive literature search was performed on Pubmed/MEDLINE, Web of Science, Scopus, Embase, Cochrane Library database to identify articles including machine learning models and algorithms to predict malignant transformation in OPMDs. Relevant bibliographic data, study characteristics, and outcomes were extracted for eligible studies. Quality of the included studies was assessed through the IJMEDI checklist. RESULTS: Fifteen articles were found suitable for the review as per the PECOS criteria. Amongst all studies, highest sensitivity (100%) was recorded for U-net architecture, Peaks Random forest model, and Partial least squares discriminant analysis (PLSDA). Highest specificity (100%) was noted for PLSDA. Range of overall accuracy in risk prediction was between 95.4% and 74%. CONCLUSION: Machine learning proved to be a viable tool in risk prediction, demonstrating heightened sensitivity, automation, and improved accuracy for predicting transformation of OPMDs. It presents an effective approach for incorporating multiple variables to monitor the progression of OPMDs and predict their malignant potential. However, its sensitivity to dataset characteristics necessitates the optimization of input parameters to maximize the efficiency of the classifiers.

ANN multi-layer perceptron for prediction of blood-brain barrier permeable compounds for central nervous system therapeutics.

Endothelial cells produce a semipermeable barrier known as the blood-brain barrier (BBB) to keep undesired chemicals out of the central nervous system (CNS). However, this barrier also restricts the exploration of potential new medications due to insufficient exposure. To address this challenge, machine learning (ML) algorithms can be useful to predict the BBB permeability of chemical compounds. Support vector machines, continuous neural networks, and deep learning approaches have been used to identify compounds that can penetrate the BBB. However, predicting BBB permeability based solely on chemical structure can be difficult. In the current research, we developed an ML model using a large dataset to predict BBB permeability, which could be used for early-stage drug screening of potential CNS medications. Our artificial neural network ANN algorithm exhibited an accuracy of 0.94, specificity of 0.83, sensitivity of 0.97, AUC of 0.96, and MCC of 0.83. These metrics suggest that our model has a high accuracy rate in predicting BBB permeability and therefore has the potential to advance drug discovery efforts in the CNS. This study's outcomes demonstrate the potential for ML models to predict BBB permeability accurately, aiding in the identification of new CNS therapeutic options.Communicated by Ramaswamy H. Sarma.

Efficient axonal transport of endolysosomes relies on the balanced ratio of microtubule tyrosination and detyrosination.

In neurons, the microtubule (MT) cytoskeleton forms the basis for long-distance protein transport from the cell body into and out of dendrites and axons. To maintain neuronal polarity, the axon initial segment (AIS) serves as a physical barrier, separating the axon from the somatodendritic compartment and acting as a filter for axonal cargo. Selective trafficking is further instructed by axonal enrichment of MT post-translational modifications, which affect MT dynamics and the activity of motor proteins. Here, we compared two knockout mouse lines lacking the respective enzymes for MT tyrosination and detyrosination, and found that both knockouts led to a shortening of the AIS. Neurons from both lines also showed an increased immobile fraction of endolysosomes present in the axon, whereas mobile organelles displayed shortened run distances in the retrograde direction. Overall, our results highlight the importance of maintaining the balance of tyrosinated and detyrosinated MTs for proper AIS length and axonal transport processes.

Enhanced Route navigation control system for turtlebot using human-assisted mobility and 3-D SLAM optimization.

An autonomous, power-assisted Turtlebot is presented in this paper in order to enhance human mobility. The turtlebot moves from its initial position to its final position at a predetermined speed and acceleration. We propose an intelligent navigation system that relies solely on individual instructions. When there is no individual present, the Turtlebot remains stationary. Turtlebot utilizes a rotating Kinect sensor in order to perceive its path. Various angles were examined in order to demonstrate the effectiveness of the system in experiments conducted on a U-shaped experimental pathway. The Turtlebot was used as an experimental device during these trials. Based on the U-shaped path, deviations from different angles were measured to evaluate its performance. SLAM (Simultaneous Localization and Mapping) experiments were also explored. We divided the SLAM problem into components and implemented the Kalman filter on the experimental path to address it. The Kalman filter focused on localization and mapping challenges, utilizing mathematical processes considering both the system's knowledge and the measurement tool. This approach allowed us to achieve the most accurate system state estimation possible. The significance of this work extends beyond the immediate application, as it lays the groundwork for advancements in wheelchair navigation research by Dynamic Control. The experiments conducted on a U-shaped pathway not only validate the efficacy of our algorithm but also provide valuable insights into the intricacies of navigating in both forward and reverse directions. These insights are pivotal for refining the navigation algorithm, ultimately contributing to the development of more robust and user-friendly systems for individuals with mobility challenges. The data used for this purpose included actuator input, vehicle location, robot movement sensors, and sensor readings representing the world state. The study provides a strong foundation for future wheelchair navigation research by Dynamic Control. Consequently, we found that navigating the Turtlebot in the reverse direction resulted in a 5%-6% increase in diversion compared to forward navigation, providing valuable insight into further improvement of the navigation algorithm.

Avelumab in the Treatment of Advanced Merkel Cell Carcinoma: A Systematic Review.

BACKGROUND: Avelumab, a programmed death ligand-1 inhibitor, has shown success in providing durable responses for difficult-to-treat Merkel cell carcinomas (MCCs). OBJECTIVE: Evaluate the efficacy and safety of avelumab in the treatment of advanced MCC. METHODS: Studies reporting the use of avelumab as a monotherapy or in combination with other agents in the treatment of stage III or IV (advanced) MCC were included. The primary outcomes were overall response rate, overall survival (OS), and treatment-related adverse events. RESULTS: A total of 48 studies were included, involving 1,565 patients with advanced MCC. Most patients were male (1,051, 67.3%) with stage IV MCC (517, 97.0%). The overall response rate was 46.1% (partial response-25.4% and complete response-20.7%) after a mean follow-up period of 9.5 months. Kaplan-Meier survival curves for the pooled stage III and IV group demonstrated OS rates of 58% at 1 year, 47% at 2 years, and 28% at 5 years after completion of treatment with avelumab (median OS: 23.1 months). The most common treatment-related adverse events consisted of constitutional (44%), gastrointestinal (19%), and dermatologic (12%) symptoms. CONCLUSION: Avelumab monotherapy and combination therapy have shown success in the overall response rate and survival for patients with advanced MCC.