A review on carbon-based biowaste and organic polymer materials for sustainable treatment of sulfonamides from pharmaceutical wastewater.

Frequent detection of sulfonamides (SAs) pharmaceuticals in wastewater has necessitated the discovery of suitable technology for their sustainable remediation. Adsorption has been widely investigated due to its effectiveness, simplicity, and availability of various adsorbent materials from natural and artificial sources. This review highlighted the potentials of carbon-based adsorbents derived from agricultural wastes such as lignocellulose, biochar, activated carbon, carbon nanotubes graphene materials as well as organic polymers such as chitosan, molecularly imprinted polymers, metal, and covalent frameworks for SAs removal from wastewater. The promising features of these materials including higher porosity, rich carbon-content, robustness, good stability as well as ease of modification have been emphasized. Thus, the materials have demonstrated excellent performance towards the SAs removal, attributed to their porous nature that provided sufficient active sites for the adsorption of SAs molecules. The modification of physico-chemical features of the materials have been discussed as efficient means for enhancing their adsorption and reusable performance. The article also proposed various interactive mechanisms for the SAs adsorption. Lastly, the prospects and challenges have been highlighted to expand the knowledge gap on the application of the materials for the sustainable removal of the SAs.

CRISPR-Cas System: A New Dawn to Combat Antibiotic Resistance.

Antimicrobial resistance (AMR) can potentially harm global public health. Horizontal gene transfer (HGT), which speeds up the emergence of AMR and increases the burden of drug resistance in mobile genetic elements (MGEs), is the primary method by which AMR genes are transferred across bacterial pathogens. New approaches are urgently needed to halt the spread of bacterial diseases and antibiotic resistance. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), an RNA-guided adaptive immune system, protects prokaryotes from foreign DNA like plasmids and phages. This approach may be essential in limiting horizontal gene transfer and halting the spread of antibiotic resistance. The CRISPR-Cas system has been crucial in identifying and understanding resistance mechanisms and developing novel therapeutic approaches. This review article investigates the CRISPR-Cas system's potential as a tool to combat bacterial AMR. Antibiotic-resistant bacteria can be targeted and eliminated by the CRISPR-Cas system. It has been proven to be an efficient method for removing carbapenem-resistant plasmids and regaining antibiotic susceptibility. The CRISPR-Cas system has enormous potential as a weapon against bacterial AMR. It precisely targets and eliminates antibiotic-resistant bacteria, facilitates resistance mechanism identification, and offers new possibilities in diagnostics and therapeutics.

Outbreak of Multidrug-resistant Acinetobacter baumannii in a Tertiary Health Center from Northwestern Nigeria.

Background: In spite of its global notoriety and WHO alarm, Acinetobacter baumannii is still an understudied critical-priority pathobiont in Nigeria. We characterized its antimicrobial susceptibility profile and resistance genes during an outbreak. Materials and Methods: This cross-sectional study involved collection of patients' urine samples and swabs from unit staff's hands and ward environments for the identification of A. baumannii strains using standard morphologic and biochemical methods. The disk diffusion method was used to assess the antimicrobial susceptibility profile of the isolates with the production of extended-spectrum beta-lactamases (ESBLs) confirmed by the combined disk test screening method. Characterization of the resistance genes of the ESBL producers was carried out using polymerase chain reaction polymerase chain reaction technique. Results: A.total of eight (six clinical and two nonclinical) A. baumannii isolates were identified. The overall isolate susceptibility and resistance rates to all the antimicrobial agents was 56.3% (27/48) and 35.4% (17/48), respectively. Similarly, all (8/8; 100.00%) isolates were susceptible to meropenem and 75.0% (6/8) to ampicillin-sulbactam while 62.5% (5/8) were resistant to trimethoprim-sulfamethoxazole and 50.0% (4/8) to each of ciprofloxacin and ceftazidime. In addition, 37.5% (3/8) of the isolates were multidrug resistant (MDR) with nonclinical isolates exhibiting more antimicrobial resistance than their clinical counterparts (9/12%-75.0% vs. 8/36%-22.2%). Phenotypic detection and molecular characterization revealed three ESBL-producing isolates that each harbored blaSHV and blaTEM genes with blaCTX-M gene being absent. Conclusion: MDR strains of A. baumannii harboring blaSHV and blaTEM genes were recovered from clinical and environmental sources during the outbreak, which was contained with preventive measures recommended.

Résumé En dépit des alertes faites par l'organisation mondiale de la Santé (OMS), Acinetobacter baumannii demeure un pathobiont sous-étudié et très peu priorisé au Nigeria. Nous avons procedé à sa caractérisation phénotypique et génotypique en dressant son profil de sensibilité aux antimicrobiens et ainsi que les gènes de résistance impliqués au cours d'une épidémie. Matériel et méthodes: Cette étude transversale a consisté à collecter des échantillons d'urine de patients et des écouvillons des mains du personnel des soins et de l'environnement hospitalier. L'identification des souches d' A. baumannii était faite par des méthodes bactériologiques standard. le profil de sensibilité aux antimicrobiens des isolats a été faite par la méthode de diffusion de disque , les bêta-lactamases à spectre étendu (BLSE) étaient recherchée par la méthode de dépistage combinée de disque ainsi que leur caractérisation moléculaire par la mise en évidence des gènes de résistance BLSE à l'aide d'une PCR (réaction en chaîne par polymérase). Résultats: Au total, huit isolats d'A. baumannii (6 cliniques et 2 de l'environnement) ont été identifiés. Les taux globaux de sensibilité et de résistance des isolats à tous les agents antimicrobiens étaient respectivement de 56,3 % (27/48) et de 35,4 % (17/48). De même, tous les isolats (8/8 ; 100,00 %) étaient sensibles au méropénème et 75,0 % (6/8) à l'ampicilline-sulbactam, tandis que 62,5 % (5/8) étaient résistants au triméthoprime-sulfaméthoxazole et 50,0 % (4/8) à la ciprofloxacine et à la ceftazidime. En outre, 37,5 % (3/8) des isolats étaient multirésistants (MDR), les isolats non cliniques présentant une plus grande résistance aux antimicrobiens que leurs homologues cliniques (9/12 %-75,0 % contre 8/36 %-22,2 %). La détection phénotypique et la caractérisation moléculaire ont révélé trois isolats producteurs de BLSE qui hébergeaient chacun les gènes blaSHV et blaTEM, le gène blaCTX-M étant absent. Conclusion: Des souches multirésistantes d'A. baumannii portant les gènes blaSHV et blaTEM ont été identifiées sur des prélevements cliniques et environnementaux au cours de l'épidémie, qui a été gerée grâce aux mesures préventives recommandées. Mots-clés: Surveillance de la résistance aux antimicrobiens, blaSHV carbapénème, pathogène ESKAPE, infections associées aux soins de santé, pratiques de prévention et de contrôle des infections, one health, uropathogènes.

A systematic quantitative approach comprehensively defines domain-specific functional pathways linked to Schizosaccharomyces pombe heterochromatin regulation.

Heterochromatin plays a critical role in regulating gene expression and maintaining genome integrity. While structural and enzymatic components have been linked to heterochromatin establishment, a comprehensive view of the underlying pathways at diverse heterochromatin domains remains elusive. Here, we developed a systematic approach to identify factors involved in heterochromatin silencing at pericentromeres, subtelomeres, and the silent mating type locus in Schizosaccharomyces pombe. Using quantitative measures, iterative genetic screening, and domain-specific heterochromatin reporters, we identified 369 mutants with different degrees of reduced or enhanced silencing. As expected, mutations in the core heterochromatin machinery globally decreased silencing. However, most other mutants exhibited distinct qualitative and quantitative profiles that indicate domain-specific functions. For example, decreased mating type silencing was linked to mutations in heterochromatin maintenance genes, while compromised subtelomere silencing was associated with metabolic pathways. Furthermore, similar phenotypic profiles revealed shared functions for subunits within complexes. We also discovered that the uncharacterized protein Dhm2 plays a crucial role in maintaining constitutive and facultative heterochromatin, while its absence caused phenotypes akin to DNA replication-deficient mutants. Collectively, our systematic approach unveiled a landscape of domain-specific heterochromatin regulators controlling distinct states and identified Dhm2 as a previously unknown factor linked to heterochromatin inheritance and replication fidelity.

Assessing Risk of Health Outcomes From Brain Activity in Sleep: A Retrospective Cohort Study.

Background and Objectives: Patterns of electrical activity in the brain (EEG) during sleep are sensitive to various health conditions even at subclinical stages. The objective of this study was to estimate sleep EEG-predicted incidence of future neurologic, cardiovascular, psychiatric, and mortality outcomes. Methods: This is a retrospective cohort study with 2 data sets. The Massachusetts General Hospital (MGH) sleep data set is a clinic-based cohort, used for model development. The Sleep Heart Health Study (SHHS) is a community-based cohort, used as the external validation cohort. Exposure is good, average, or poor sleep defined by quartiles of sleep EEG-predicted risk. The outcomes include ischemic stroke, intracranial hemorrhage, mild cognitive impairment, dementia, atrial fibrillation, myocardial infarction, type 2 diabetes, hypertension, bipolar disorder, depression, and mortality. Diagnoses were based on diagnosis codes, brain imaging reports, medications, cognitive scores, and hospital records. We used the Cox survival model with death as the competing risk. Results: There were 8673 participants from MGH and 5650 from SHHS. For all outcomes, the model-predicted 10-year risk was within the 95% confidence interval of the ground truth, indicating good prediction performance. When comparing participants with poor, average, and good sleep, except for atrial fibrillation, all other 10-year risk ratios were significant. The model-predicted 10-year risk ratio closely matched the observed event rate in the external validation cohort. Discussion: The incidence of health outcomes can be predicted by brain activity during sleep. The findings strengthen the concept of sleep as an accessible biological window into unfavorable brain and general health outcomes.

Promoting the suitability of graphitic carbon nitride and metal oxide nanoparticles: A review of sulfonamides photocatalytic degradation.

The widespread consumption of pharmaceutical drugs and their incomplete breakdown in organisms has led to their extensive presence in aquatic environments. The indiscriminate use of antibiotics, such as sulfonamides, has contributed to the development of drug-resistant bacteria and the persistent pollution of water bodies, posing a threat to human health and the safety of the environment. Thus, it is paramount to explore remediation technologies aimed at decomposing and complete elimination of the toxic contaminants from pharmaceutical wastewater. The review aims to explore the utilization of metal-oxide nanoparticles (MONPs) and graphitic carbon nitrides (g-C3N4) in photocatalytic degradation of sulfonamides from wastewater. Recent advances in oxidation techniques such as photocatalytic degradation are being exploited in the elimination of the sulfonamides from wastewater. MONP and g-C3N4 are commonly evolved nano substances with intrinsic properties. They possessed nano-scale structure, considerable porosity semi-conducting properties, responsible for decomposing wide range of water pollutants. They are widely applied for photocatalytic degradation of organic and inorganic substances which continue to evolve due to the low-cost, efficiency, less toxicity, and more environmentally friendliness of the materials. The review focuses on the current advances in the application of these materials, their efficiencies, degradation mechanisms, and recyclability in the context of sulfonamides photocatalytic degradation.

Properties of Self-Compacting Concrete Produced with Optimized Volumes of Calcined Clay and Rice Husk Ash-Emphasis on Rheology, Flowability Retention and Durability.

The durability of concrete requires a dense microstructure which can be achieved by using self-compacting concrete (SCC). Both calcined clay (CC) and rice husk ash (RHA) are promising supplementary cementitious materials (SCMs) that can partially replace cement, but their use in SCC is critical due to their higher water demand (WD) and specific surface area (SSA) compared to cement. The effect of partial substitution of cement at 20 vol-% with binary and ternary blends of CC and RHA on flowability retention and durability of SCC was investigated. The empirical method of SCC design was adopted considering the physical properties of both CC and RHA. The deformability of the SCC was evaluated using the slump flow and J-ring tests. The T500 time and the V-funnel test were used to assess the viscosity of the SCC. The flowability retention was monitored by the plunger method, and flow resistance was determined based on the rheological measurements of SCC. The evolution of the hydrate phases of the binder in SCC was determined by thermogravimetric analysis, while the durability was evaluated by a rapid chloride migration test. Cement partial replacement with 20 vol-% CC has no significant effect on fresh SCC, flowability retention, compressive strength and durability properties. On the other hand, 20 vol-% RHA requires a higher dosage of SP to achieve self-compactability and increase the viscosity of SCC. Its flowability retention is only up to 30 min after mixing and exhibited higher flow resistance. It consumes more calcium hydroxide (CH) and improves the compressive strength and chloride resistance of SCC. The ternary blending with CC and RHA yielded better fresh SCC properties compared to the binary blend with RHA, while an improved chloride penetration resistance could be achieved compared to the binary CC blend.

An overview on human exposure, toxicity, solid-phase microextraction and adsorptive removal of perfluoroalkyl carboxylic acids (PFCAs) from water matrices.

Perfluoroalkyl carboxylic acids (PFCAs) are sub-class of perfluoroalkyl substances commonly detected in water matrices. They are persistent in the environment, hence highly toxic to living organisms. Their occurrence at trace amount, complex nature and prone to matrix interference make their extraction and detection a challenge. This study consolidates current advancements in solid-phase extraction (SPE) techniques for the trace-level analysis of PFCAs from water matrices. The advantages of the methods in terms of ease of applications, low-cost, robustness, low solvents consumption, high pre-concentration factors, better extraction efficiency, good selectivity and recovery of the analytes have been emphasized. The article also demonstrated effectiveness of some porous materials for the adsorptive removal of the PFCAs from the water matrices. Mechanisms of the SPE/adsorption techniques have been discussed. The success and limitations of the processes have been elucidated.

Ecological footprint, globalization, and economic growth: evidence from Asia.

This study aims to investigate the relationship between environmental rationality and economic activities that accelerate environmental indicators in Asia. In the ecosphere, the environment is a predator of human consumption. The continent Asia holding more than 60% of the world's population is vulnerable to environmental deployment. The purpose of the study is to find the link between economic growth, globalization, biocapacity, energy intensity, and renewable energy to the ecological footprint (EFP) in Asian countries for the period of 1990-2017. For empirics, the econometric techniques applied are panel OLS, fixed effects, random effects, fully modified-OLS, DOLS, and generalized methods of moments techniques. The results prove that by increasing the share of renewable energy in total energy consumption the environmental quality is improved. The Pedroni cointegration test shows a long-term relationship exists between globalization, economic growth, and the environment. The results of all techniques show the similar effectiveness of all used economic indicators in the model that disturbs the environment with different intensities in each test. The results of FM-OLS show that with a 1% increase in economic growth, globalization, biocapacity, and population density the ecological footprint increases by 0.55%, 0.08%, 0.06%, and 0.03%, respectively. However, renewable energy improves the environment by 0.04%. The Granger causality analysis revealed a bidirectional causality between ecological footprint and globalization and between EFP and energy intensity. This study recommends that Asian countries should make sustainable environmental policies to protect the environment from further damage.

Sound and light levels in intensive care units in a large urban hospital in the United States.

Intensive care units (ICUs) may disrupt sleep. Quantitative ICU studies of concurrent and continuous sound and light levels and timings remain sparse in part due to the lack of ICU equipment that monitors sound and light. Here, we describe sound and light levels across three adult ICUs in a large urban United States tertiary care hospital using a novel sensor. The novel sound and light sensor is composed of a Gravity Sound Level Meter for sound level measurements and an Adafruit TSL2561 digital luminosity sensor for light levels. Sound and light levels were continuously monitored in the room of 136 patients (mean age = 67.0 (8.7) years, 44.9% female) enrolled in the Investigation of Sleep in the Intensive Care Unit study (ICU-SLEEP; Clinicaltrials.gov: #NCT03355053), at the Massachusetts General Hospital. The hours of available sound and light data ranged from 24.0 to 72.2 hours. Average sound and light levels oscillated throughout the day and night. On average, the loudest hour was 17:00 and the quietest hour was 02:00. Average light levels were brightest at 09:00 and dimmest at 04:00. For all participants, average nightly sound levels exceeded the WHO guideline of < 35 decibels. Similarly, mean nightly light levels varied across participants (minimum: 1.00 lux, maximum: 577.05 lux). Sound and light events were more frequent between 08:00 and 20:00 than between 20:00 and 08:00 and were largely similar on weekdays and weekend days. Peaks in distinct alarm frequencies (Alarm 1) occurred at 01:00, 06:00, and at 20:00. Alarms at other frequencies (Alarm 2) were relatively consistent throughout the day and night, with a small peak at 20:00. In conclusion, we present a sound and light data collection method and results from a cohort of critically ill patients, demonstrating excess sound and light levels across multiple ICUs in a large tertiary care hospital in the United States. ClinicalTrials.gov, #NCT03355053. Registered 28 November 2017, https://clinicaltrials.gov/ct2/show/NCT03355053.

Calcined Clays from Nigeria-Properties and Performance of Supplementary Cementitious Materials Suitable for Producing Level 1 Concrete.

In this work, four naturally occurring (two kaolinite-rich and two smectite-rich) clay samples were collected from different areas around the Ashaka cement production plant, located in Gombe State, Nigeria and calcined in a laboratory. The mineralogical characterization of the clays was carried out by XRD. The hydration kinetics of the calcined clay-cement systems were monitored by isothermal calorimetry. Workability was determined using the flow table method. The reactivity of the calcined clays was determined from the solubility of Si and Al ions and the strength activity index. All calcined clays studied met the requirements of ASTM C618 for the use of natural pozzolans as a partial replacement for hydraulic cement. The metasmectite clays yielded a higher specific surface area, increased water demand, and less reactive Si and Al ions compared to the metakaolin clays. The two calcined clay groups require the addition of superplasticizer to achieve a workability class similar to the Portland cement mortar system. They can be used to replace Portland cement at replacement levels of up to 45%, in combination with limestone powder to form an LC3 cement, thereby achieving at least a "Level 1" reduction in greenhouse gas emissions.

Sleep staging in the ICU with heart rate variability and breathing signals. An exploratory cross-sectional study using deep neural networks.

Introduction: To measure sleep in the intensive care unit (ICU), full polysomnography is impractical, while activity monitoring and subjective assessments are severely confounded. However, sleep is an intensely networked state, and reflected in numerous signals. Here, we explore the feasibility of estimating conventional sleep indices in the ICU with heart rate variability (HRV) and respiration signals using artificial intelligence methods Methods: We used deep learning models to stage sleep with HRV (through electrocardiogram) and respiratory effort (through a wearable belt) signals in critically ill adult patients admitted to surgical and medical ICUs, and in age and sex-matched sleep laboratory patients Results: We studied 102 adult patients in the ICU across multiple days and nights, and 220 patients in a clinical sleep laboratory. We found that sleep stages predicted by HRV- and breathing-based models showed agreement in 60% of the ICU data and in 81% of the sleep laboratory data. In the ICU, deep NREM (N2 + N3) proportion of total sleep duration was reduced (ICU 39%, sleep laboratory 57%, p < 0.01), REM proportion showed heavy-tailed distribution, and the number of wake transitions per hour of sleep (median 3.6) was comparable to sleep laboratory patients with sleep-disordered breathing (median 3.9). Sleep in the ICU was also fragmented, with 38% of sleep occurring during daytime hours. Finally, patients in the ICU showed faster and less variable breathing patterns compared to sleep laboratory patients Conclusion: The cardiovascular and respiratory networks encode sleep state information, which, together with artificial intelligence methods, can be utilized to measure sleep state in the ICU.

Epilepsy diagnosis using a clinical decision tool and artificially intelligent electroencephalography.

OBJECTIVE: To construct a tool for non-experts to calculate the probability of epilepsy based on easily obtained clinical information combined with an artificial intelligence readout of the electroencephalogram (AI-EEG). MATERIALS AND METHODS: We performed a chart review of 205 consecutive patients aged 18 years or older who underwent routine EEG. We created a point system to calculate the pre-EEG probability of epilepsy in a pilot study cohort. We also computed a post-test probability based on AI-EEG results. RESULTS: One hundred and four (50.7%) patients were female, the mean age was 46 years, and 110 (53.7%) were diagnosed with epilepsy. Findings favoring epilepsy included developmental delay (12.6% vs 1.1%), prior neurological injury (51.4% vs 30.9%), childhood febrile seizures (4.6% vs 0.0%), postictal confusion (43.6% vs 20.0%), and witnessed convulsions (63.6% vs 21.1%); findings favoring alternative diagnoses were lightheadedness (3.6% vs 15.8%) or onset after prolonged sitting or standing (0.9% vs 7.4%). The final point system included 6 predictors: Presyncope (-3 points), cardiac history (-1), convulsion or forced head turn (+3), neurological disease history (+2), multiple prior spells (+1), postictal confusion (+2). Total scores of ≤1 point predicted <5% probability of epilepsy, while cumulative scores ≥7 predicted >95%. The model showed excellent discrimination (AUROC: 0.86). A positive AI-EEG substantially increases the probability of epilepsy. The impact is greatest when the pre-EEG probability is near 30%. SIGNIFICANCE: A decision tool using a small number of historical clinical features accurately predicts the probability of epilepsy. In indeterminate cases, AI-assisted EEG helps resolve uncertainty. This tool holds promise for use by healthcare workers without specialty epilepsy training if validated in an independent cohort.

An enigma: case series of vesical calculi from prolonged and neglected indwelling catheter.

Vesical calculus is a common condition with familiar aetiology in our environment as it is obtained in other parts of the world. Notwithstanding, uncommon aetiology of this pathology still exists though rarely encountered especially where out-of-pocket payment is the norm for accessing health care services. This is a report of three patients with varying indications for indwelling vesical catheter insertion via urethral or suprapubic route and who developed vesical calculus from prolonged and neglected indwelling vesical catheter. These cases are indeed an enigma in contemporary surgical patient care. We share our experience in the care of these patients and to underscore the extra role expected of health care providers in adequate patient education, close attention to guidance and counseling during patients' visits to health facilities.

Discovering functional connectivity features characterizing multiple sclerosis phenotypes using explainable artificial intelligence.

Multiple sclerosis (MS) is a neurological condition characterized by severe structural brain damage and by functional reorganization of the main brain networks that try to limit the clinical consequences of structural burden. Resting-state (RS) functional connectivity (FC) abnormalities found in this condition were shown to be variable across different MS phases, according to the severity of clinical manifestations. The article describes a system exploiting machine learning on RS FC matrices to discriminate different MS phenotypes and to identify relevant functional connections for MS stage characterization. To this end, the system exploits some mathematical properties of covariance-based RS FC representation, which can be described by a Riemannian manifold. The classification performance of the proposed framework was significantly above the chance level for all MS phenotypes. Moreover, the proposed system was successful in identifying relevant RS FC alterations contributing to an accurate phenotype classification.

Industrialization, energy consumption, and environmental pollution: evidence from South Asia.

This study has been carried out to analyze the contribution of industrialization and energy consumption by keeping the role of urbanization on environmental pollution for South Asia. The study used Augmented Mean Group (AMG), Common Correlated Effects Mean Group (CCEMG) analysis, Westerlund co-integration test, and Dumitrescu-Hurlin causality test for the panel of South Asia covering the period 1984-2016. To measure the status of environmental pollution, CO2 is taken as a proxy indicator, and industrialization is measured by the industrial value-added. The results of AMG demonstrate that industrialization and energy consumption are significant indicators of environmental pollution and these empirical findings are also confirmed by the CCEMG model. The long-run co-integration between industrialization, energy use, urbanization, capital, and environmental pollution is also confirmed by the Westerlund co-integration test. The findings of the Dumitrescu-Hurlin causality test also confirmed the bidirectional causality between industrialization and pollution. A unidirectional causality is observed from energy consumption to pollution. The study suggests formulating policies for energy-efficient technologies in the industrial sector and the high-speed pattern of urbanization.

High prevalence of sleep-disordered breathing in the intensive care unit - a cross-sectional study.

PURPOSE: Sleep-disordered breathing may be induced by, exacerbate, or complicate recovery from critical illness. Disordered breathing during sleep, which itself is often fragmented, can go unrecognized in the intensive care unit (ICU). The objective of this study was to investigate the prevalence, severity, and risk factors of sleep-disordered breathing in ICU patients using a single respiratory belt and oxygen saturation signals. METHODS: Patients in three ICUs at Massachusetts General Hospital wore a thoracic respiratory effort belt as part of a clinical trial for up to 7 days and nights. Using a previously developed machine learning algorithm, we processed respiratory and oximetry signals to measure the 3% apnea-hypopnea index (AHI) and estimate AH-specific hypoxic burden and periodic breathing. We trained models to predict AHI categories for 12-h segments from risk factors, including admission variables and bio-signals data, available at the start of these segments. RESULTS: Of 129 patients, 68% had an AHI ≥ 5; 40% an AHI > 15, and 19% had an AHI > 30 while critically ill. Median [interquartile range] hypoxic burden was 2.8 [0.5, 9.8] at night and 4.2 [1.0, 13.7] %min/h during the day. Of patients with AHI ≥ 5, 26% had periodic breathing. Performance of predicting AHI-categories from risk factors was poor. CONCLUSIONS: Sleep-disordered breathing and sleep apnea events while in the ICU are common and are associated with substantial burden of hypoxia and periodic breathing. Detection is feasible using limited bio-signals, such as respiratory effort and SpO2 signals, while risk factors were insufficient to predict AHI severity.

Ventricular septal rupture after delayed STEMI: A modern management approach.

BACKGROUND: Myocardial infarction associated ventricular septal rupture (VSR) is a potentially catastrophic complication. Though surgical repair remains the definitive treatment, outcomes are poor with high mortality rates.Case and Management: We present the case of a 62-year-old male who presented with a delayed STEMI leading to a VSR and cardiogenic shock. His management strategy included early percutaneous VSR closure and use of an intra-aortic balloon pump and inotropes. This served as a bridge to definitive surgical VSR patch repair while allowing hemodynamic stabilization, end-organ recovery, and myocardial tissue stabilization. CONCLUSION: Mechanical support devices such as intra-aortic balloon pump and Impella combined with percutaneous closure options can serve as a bridge to definitive surgery for VSR. This requires rapid mobilization of a multi-disciplinary structural heart team including advanced imagers, structural interventionalists, and surgeons.

Analyzing preventive precautions to limit spread of COVID-19.

With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples' sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions.