Ecotoxicological risk assessment of triclosan, an emerging pollutant in a riverine and estuarine ecosystems: A comparative study.

Triclosan (TCS), an antibacterial biocide, pervades water and sediment matrices globally, posing a threat to aquatic life. In densely populated cities like Mumbai, rivers and coastal bodies demand baseline TCS data for ecotoxicological assessment due to the excessive use of personal care products comprising TCS. This pioneering study compares spatiotemporal TCS variations and risks in freshwater and marine ecosystems employing multivariate analysis of physicochemical parameters. Over five months (January to May 2022), Mithi River exhibited higher TCS concentrations (water: 1.68 µg/L, sediment: 3.19 µg/kg) than Versova Creek (water: 0.49 µg/L, sediment: 0.69 µg/kg). Principal component analysis revealed positive correlations between TCS and physicochemical parameters. High-risk quotients (>1) underscore TCS threats in both water bodies. This study furnishes crucial baseline data, emphasizing the need for effective treatment plans for TCS in effluent waters released into the adjacent aquatic systems.

Environmental, economic, and social sustainability in aquaculture: the aquaculture performance indicators.

Aquaculture is a rapidly growing food production technology, but there are significant concerns related to its environmental impact and adverse social effects. We examine aquaculture outcomes in a three pillars of sustainability framework by analyzing data collected using the Aquaculture Performance Indicators. Using this approach, comparable data has been collected for 57 aquaculture systems worldwide on 88 metrics that measure social, economic, or environmental outcomes. We first examine the relationships among the three pillars of sustainability and then analyze performance in the three pillars by technology and species. The results show that economic, social, and environmental outcomes are, on average, mutually reinforced in global aquaculture systems. However, the analysis also shows significant variation in the degree of sustainability in different aquaculture systems, and weak performance of some production systems in some dimensions provides opportunity for innovative policy measures and investment to further align sustainability objectives.

Post-tubercular Lumbosacral Kyphotic Deformity in a 11-Year-Old Child: A Case Report.

CASE: An 11-year-old girl with intact neurology presented with a lumbosacral kyphotic deformity due to healed tuberculosis. Radiological imaging showed sagittal balanced spine with compensatory thoracic lordosis and cervical kyphosis. She underwent L4 and L5 posterior vertebral column resection (PVCR) with posterior instrumentation from L2 to pelvis. The patient demonstrated immediate correction of compensatory curves postoperatively. At 3-year follow-up, she returned to her activities of daily living with Oswestry Disability Index and Scoliosis Research Society scores of 12 and 4.8% respectively. CONCLUSION: Pediatric post-tubercular deformities in the lumbosacral region are rare. They can cause secondary changes in other regions, such as the loss of thoracic kyphosis or cervical lordosis. These deformities should be addressed at an early age to prevent structural changes in compensatory curves.

Review of environmental challenges in the Bangladesh aquaculture industry.

The increasing population and plateaued capture fishery landings have led to increasing demand for aquaculture products. However, environmental challenges are critical barriers to the sustainable development of aquaculture in developing countries. This review critically evaluates the environmental barriers facing aquaculture development in Bangladesh while laying out a roadmap for future development and spatial planning. An increase in the area used for aquaculture most often results in increasing pressure on natural resources such as land, water, energy, and the sources used for feed. Some of the negative externalities that this review focuses on are effluent discharge, the spread of diseases, and conflicts over land use with other ecosystem users. A way forward is to internalize these negative externalities and their costs into production decisions by farmers. Formulation of incentive-based pragmatic regulations can pave a forward path to increased environmental sustainability.

Hypoxia sensing requires H2S-dependent persulfidation of olfactory receptor 78.

Oxygen (O2) sensing by the carotid body is critical for maintaining cardiorespiratory homeostasis during hypoxia. Hydrogen sulfide (H2S) signaling is implicated in carotid body activation by low O2. Here, we show that persulfidation of olfactory receptor 78 (Olfr78) by H2S is an integral component of carotid body activation by hypoxia. Hypoxia and H2S increased persulfidation in carotid body glomus cells and persulfidated cysteine240 in Olfr78 protein in heterologous system. Olfr78 mutants manifest impaired carotid body sensory nerve, glomus cell, and breathing responses to H2S and hypoxia. Glomus cells are positive for GOlf, adenylate cyclase 3 (Adcy3) and cyclic nucleotide-gated channel alpha 2 (Cnga2), key molecules of odorant receptor signaling. Adcy3 or Cnga2 mutants exhibited impaired carotid body and glomus cell responses to H2S and breathing responses to hypoxia. These results suggest that H2S through redox modification of Olfr78 participates in carotid body activation by hypoxia to regulate breathing.

A Systematic Review and Meta-Analysis on Effectiveness of Mineralocorticoid Receptor Antagonists in Reducing the Risk of Atrial Fibrillation.

Mineralocorticoid receptor antagonists (MRAs) are known to improve clinical outcomes in heart failure, particularly heart failure with reduced ejection fraction. However, the effect of MRAs on the incidence of and recurrence of atrial fibrillation (AF) is not well established. Therefore, databases, such as PubMed, EMBASE, and Cochrane Central, were searched from inception to September 2021 for randomized controlled trials of MRAs with AF as an outcome. Risk ratios (RRs) with 95% confidence interval (CIs) were combined using the random-effects model. A total of 10 randomized controlled trials (n = 11,356) were included. Our pooled analysis demonstrates that MRAs reduce the risk of AF occurrence by 23% compared with the control therapy (RR 0.77, 95% CI 0.65 to 0.91, p = 0.003, I2 = 40%). Subgroup analysis demonstrated that MRAs reduced the risk of both new-onset AF (RR 0.84, 95% CI 0.61 to 1.16, p = 0.28, I2 = 43%) and recurrent AF (RR 0.73, 95% CI 0.59 to 0.90, p = 0.004, I2 = 26%) similarly; p interaction = 0.48. Our meta-analysis concludes that MRAs reduce the risk of development of AF overall, with consistent effects in new-onset and recurrent AF.

Overview and knowledge of prosthodontic diagnostic aids among interns and post graduates - A cross-sectional questionnaire study.

Aim: This study aims to evaluate and compare the knowledge of prosthodontic diagnostic aids among interns and postgraduates. Settings and Design: A questionnaire survey was conducted to assess and compare the knowledge of prosthodontic diagnostic aids among interns and postgraduates. Based on the pilot study with alpha error 5% and a power of study 80%, the sample size was estimated to be 858 for each group. Materials and Methods: The self constructed questionnaire consisted of 3 sections, of which each section had 5 questions, a total of 15 questions validated by a team of 6 experts. The questionnaire was distributed electronically among interns and postgraduates in various dental colleges across India. Data were collected and subjected to statistical analysis. Statistical Analysis: All outcomes of this survey were analyzed using an independent t test. The Mann- Whitney test was used to determine the significance of two groups. Results: From the results obtained, it was found that interns (mean: 6.90; standard deviation: 2.442) had less knowledge regarding diagnostic tools than postgraduate students (mean: 8.76; standard deviation: 1.818). Conclusion: Diagnostic aids simplifies the process of diagnosis and treatment planning. Moreover, the knowledge of diagnostic aids among younger generation permits them to redefine the way dentistry is practiced and at the same time helps to provide better treatment results and achieve the utmost for the profession. Adequate knowledge of diagnostic aids is the need of the hour. Dental professionals should constantly update knowledge regarding various diagnostic aids in Prosthodontics, so as to arrive at optimum diagnosis and treatment plan with longer prognosis.

Pre- and post-pandemic seafood purchasing behavior in the U.S.

The global COVID-19 pandemic resulted in an unprecedented economic shock in current times. Previous literature on consumer shopping behaviors during economic downturns is limited, and studies specific to seafood focused primarily on supply-side shocks. A national survey was conducted using an online platform from February 22 to April 6, 2021 that targeted 100 seafood consumers in each of 20 market areas across the U.S. Following data cleaning, 1908 usable responses were obtained. Results documented significant changes in consumer shopping behaviors. Significantly greater percentages of meals (generally and of seafood) were consumed at home and fewer away from home, as expected. Demographic differences were found in shopping behaviors by age, education, income, and gender, but not by ethnic group. Frequency of shopping decreased in 2020, but the expenditure per shopping trip did not, resulting in less overall spending for groceries as compared to 2019. Respondents were less likely to purchase seafood for takeout or for home delivery of prepared meals as compared to general meals because of concerns over quality, freshness, and safety of seafood. Half of respondents consumed approximately the same amount of seafood as before the pandemic; with 31% reporting decreased seafood consumption, and only 19% increased seafood consumption. Thus, study results provide evidence of a pandemic-imposed shift to consuming greater proportions of seafood meals at-home than away-from-home, and not an overall increase in seafood consumption. The choice of species eaten most often did not differ pre- and post-pandemic. Those respondents who reported decreased seafood consumption in 2020 did so primarily because of: 1) its expense, given reduced incomes from working fewer hours or being laid off; 2) unwillingness to prepare fish at home for the smell and "mess", or being uncomfortable preparing it; or 3) simply not preferring or liking seafood well enough to eat it more frequently. Those who reported increasing seafood consumption did so primarily because it was considered to be a healthy food choice. Additional work is needed to further examine consumption and shopping behaviors throughout the recovery in 2021 and 2022.

Analysis of Deep Learning Techniques for Dental Informatics: A Systematic Literature Review.

Within the ever-growing healthcare industry, dental informatics is a burgeoning field of study. One of the major obstacles to the health care system's transformation is obtaining knowledge and insightful data from complex, high-dimensional, and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, heterogeneous, poorly documented, and generally unstructured electronic health records, imaging, sensor data, and text. There were still certain restrictions even after many current techniques were used to extract more robust and useful elements from the data for analysis. New effective paradigms for building end-to-end learning models from complex data are provided by the most recent deep learning technology breakthroughs. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for dental informatics problems and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to some drawbacks and the need for better technique development and provide new perspectives about this exciting new development in the field.

Recent Advancements in Emerging Technologies for Healthcare Management Systems: A Survey.

In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and Blockchain technologies have quickly gained pace as a new study niche in numerous collegiate and industrial sectors, notably in the healthcare sector. Recent advancements in healthcare delivery have given many patients access to advanced personalized healthcare, which has improved their well-being. The subsequent phase in healthcare is to seamlessly consolidate these emerging technologies such as IoT-assisted wearable sensor devices, AI, and Blockchain collectively. Surprisingly, owing to the rapid use of smart wearable sensors, IoT and AI-enabled technology are shifting healthcare from a conventional hub-based system to a more personalized healthcare management system (HMS). However, implementing smart sensors, advanced IoT, AI, and Blockchain technologies synchronously in HMS remains a significant challenge. Prominent and reoccurring issues such as scarcity of cost-effective and accurate smart medical sensors, unstandardized IoT system architectures, heterogeneity of connected wearable devices, the multidimensionality of data generated, and high demand for interoperability are vivid problems affecting the advancement of HMS. Hence, this survey paper presents a detailed evaluation of the application of these emerging technologies (Smart Sensor, IoT, AI, Blockchain) in HMS to better understand the progress thus far. Specifically, current studies and findings on the deployment of these emerging technologies in healthcare are investigated, as well as key enabling factors, noteworthy use cases, and successful deployments. This survey also examined essential issues that are frequently encountered by IoT-assisted wearable sensor systems, AI, and Blockchain, as well as the critical concerns that must be addressed to enhance the application of these emerging technologies in the HMS.

Applicability of Adults 2015 American Thyroid Association Differentiated Thyroid Cancer Guidelines for Postoperative Risk Stratification and Postradioiodine Treatment Dynamic Risk Stratification in Pediatric Population.

Purpose This retrospective study aimed to study the applicability of 2015 adult American Thyroid Association (ATA) differentiated thyroid cancer (DTC) postoperative risk stratification and guidelines in the pediatric population for evaluating the number of metastatic lymph nodes in the postoperative risk stratification and postradioactive iodine (RAI) treatment dynamic risk stratification (DRS) using response to treatment (RTT) reclassification. In addition, the effect of pubertal status and gender was assessed on disease presentation and prognosis. Methods Data of 63 DTC patients aged 20 years or less, stratified into prepubertal, pubertal, and postpubertal age groups, was divided into low, intermediate, and high-risk groups using pediatric ATA recurrence risk stratification. Forty-seven patients were classified as responders (excellent and indeterminate responses) and incomplete responders (biochemical and structurally incomplete responses) by assessing the RTT at 1.5 years follow-up similar to recommendation of 2015 adult DTC ATA guidelines. Results Female-to-male ratio showed a trend of gradual increase with increasing age. Significantly more responders were observed in low- and intermediate-risk groups than in high-risk group ( p = 0.0013; p = 0.017, respectively), while prepubertal group had more extensive (N1b) disease. Using DRS at follow-up of 1.5 year, pubertal and postpubertal groups showed significantly better response to RAI. More female than male patients showed response and took significantly less time to respond to RAI ( p = 0.003). Conclusion RAI response in pediatric DTC depends on pubertal status, gender, and number of malignant nodes. DRS using RTT classification may be applicable early at 1.5 years after initial therapy in different pubertal age and risk groups.

Base Mediated Diazirination via Iodine(III) Reagents.

Herein, we described an efficient method for the construction of highly functionalized diazirines from the carbohydrazide and diazo-substituted hypervalent iodine reagents. Unambiguous transformation has been designed with user applicable and easy practicable conditions. Remarkably, d-glucose, menthol, aspirin, proline, and lithocholic acid were efficiently diazirinated. Furthermore, the method is mild, robust, and highly selective, which successfully converted a variety of aryl, alkyl, benzyl, and heterocyclic hydrazides into the corresponding diazirine derivatives.

Interlinked Hamstrings for Combined Anterolateral and Anterior Cruciate Ligament Reconstruction: A Novel Technique for ALL.

Background: Anterolateral ligament (ALL) reconstruction provides rotational stability in patients undergoing anterior cruciate ligament (ACL) reconstruction. The aim of this study was to assess the outcome of patients who underwent combined ACL and ALL reconstruction with a novel anatomic technique using hamstring tendon autograft and fixed loop suspensory device. Methods: From 2016 to 2018, 25 patients who underwent combined reconstruction of ACL and ALL in our Institution were evaluated retrospectively. International Knee Documentation Committee (IKDC) Score, Tegner Lysholm Knee Score, grade of pivot shift was assessed at a final follow-up. Results: Mean follow-up was 31.5 months (28-42). Mean IKDC (81.5) and Tegner Lysholm (82.8) Knee Scores improved significantly at a final follow-up, with all knees demonstrating negative pivot shift. All patients had good outcomes at 2 years follow-up with no graft failure and with no residual instability. Conclusion: ACL and ALL reconstruction using this technique described for the anterolateral instability of the knee was satisfactory in our patients. This technique is simple, easily reproducible and avoids additional implants for ALL in the tibia. Level of evidence: IV.

Epicardial pacemaker insertion in a preterm very low birth weight neonate - An anaesthetic challenge.

Congenital complete heart block (CCHB) has an incidence of one in 20,000 live births and carries a 20% risk of mortality. The hemodynamic instability due to bradycardia and asystole due to the increasing metabolic demands can be avoided by appropriate antenatal planning, timely delivery and initiation of medical treatment and early pacemaker insertion. In this report, we discuss the anaesthetic challenges of permanent epicardial pacemaker insertion with good outcomes in a 32-week gestational age 1380 grams neonate within a few hours of birth.

Thromboelastography determined dynamics of blood coagulation and its correlation with complications and outcomes in patients with coronavirus disease 2019.

BACKGROUND: Coronavirus disease 2019 (COVID-19) causes abnormalities in the hemostatic system, collectively known as COVID-associated coagulopathy. The dynamics of clot formation are best discerned by whole-blood viscoelastic tests, such as thromboelastography (TEG). We aimed to assess the various abnormalities seen on TEG and explored the predictors of outcomes in these patients. METHODS: Thromboelastography was performed for 28 patients with COVID-19 using an automated thromboelastogram. The hemostatic condition was categorized as hypercoagulable in 17 (63%), hypocoagulable in 2 (7%), and normal in 8 (30%) based on TEG variables, such as reaction time , time until clot reaches a fixed strength, alpha angle, maximum amplitude, and clotting index. Laboratory parameters and clinical outcomes were compared between hypercoagulable and normal groups. RESULTS: Twenty-seven patients with a median age of 50 years (interquartile range, 40-60 years), male-to-female ratio of 0.9:1, median C-reactive protein of 25.7 (10.9-108.8) mg/L, serum ferritin of 693 (317-1031) µg/L, and albumin 2.9 (2.6-3.3) g/dL were included. The median prothrombin time/international normalized ratio and activated partial thromboplastin time were within normal range in the hypercoagulable and normal groups. The severity of COVID-19 was mild in 6 (22.2%), moderate in 2 (7.4%), and severe in 19 (70.4%) patients. Twenty-eight-day mortality among patients with hypocoagulable and hypercoagulable states was higher than normal coagulation status. (log-rank test, P = .002). CONCLUSIONS: Hypercoagulable state, together with a severe inflammatory state, is common in patients with COVID-19, despite thromboprophylaxis. TEG assesses coagulation status better than conventional coagulation tests. Coagulation abnormalities are associated with poor outcomes.

A Novel Rank Aggregation-Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction.

The high dimensionality of software metric features has long been noted as a data quality problem that affects the performance of software defect prediction (SDP) models. This drawback makes it necessary to apply feature selection (FS) algorithm(s) in SDP processes. FS approaches can be categorized into three types, namely, filter FS (FFS), wrapper FS (WFS), and hybrid FS (HFS). HFS has been established as superior because it combines the strength of both FFS and WFS methods. However, selecting the most appropriate FFS (filter rank selection problem) for HFS is a challenge because the performance of FFS methods depends on the choice of datasets and classifiers. In addition, the local optima stagnation and high computational costs of WFS due to large search spaces are inherited by the HFS method. Therefore, as a solution, this study proposes a novel rank aggregation-based hybrid multifilter wrapper feature selection (RAHMFWFS) method for the selection of relevant and irredundant features from software defect datasets. The proposed RAHMFWFS is divided into two stepwise stages. The first stage involves a rank aggregation-based multifilter feature selection (RMFFS) method that addresses the filter rank selection problem by aggregating individual rank lists from multiple filter methods, using a novel rank aggregation method to generate a single, robust, and non-disjoint rank list. In the second stage, the aggregated ranked features are further preprocessed by an enhanced wrapper feature selection (EWFS) method based on a dynamic reranking strategy that is used to guide the feature subset selection process of the HFS method. This, in turn, reduces the number of evaluation cycles while amplifying or maintaining its prediction performance. The feasibility of the proposed RAHMFWFS was demonstrated on benchmarked software defect datasets with Naïve Bayes and Decision Tree classifiers, based on accuracy, the area under the curve (AUC), and F-measure values. The experimental results showed the effectiveness of RAHMFWFS in addressing filter rank selection and local optima stagnation problems in HFS, as well as the ability to select optimal features from SDP datasets while maintaining or enhancing the performance of SDP models. To conclude, the proposed RAHMFWFS achieved good performance by improving the prediction performances of SDP models across the selected datasets, compared to existing state-of-the-arts HFS methods.

Pulmonary Function, Mental and Physical Health in Recovered COVID-19 Patients Requiring Invasive Versus Non-invasive Oxygen Therapy: A Prospective Follow-Up Study Post-ICU Discharge.

Background Survivors of COVID-19 pneumonia may have residual lung injury and poor physical and mental health even after discharge. We hypothesized that COVID-19 severe acute respiratory distress syndrome (ARDS) patients needing mechanical ventilation may be at a greater risk of deterioration in pulmonary function, mental health, and quality of life (QOL). This study analyses the differences in pulmonary function, mental health, and QOL after recovery, in patients having received non-invasive oxygen therapy versus invasive mechanical ventilation during ICU stay. Methods Patients aged >18 years, who had completed 3 months post ICU discharge, with moderate to severe COVID-19 ARDS, were consecutively enrolled from May 1 to July 31, 2021. Patients were allocated into Group A - having required high flow nasal cannula (HFNC)/non-invasive ventilation (NIV) and Group B - having received invasive mechanical ventilation. Pulmonary function tests, 6-minute walk test (6-MWT), and health-related quality of life were compared. Results Of the 145 eligible patients, 31 were lost to follow-up and 21 died. Seventy-four patients were allocated into Groups A (57 patients) and B (17 patients). In Group A, abnormal forced expiratory volume in first second (FEV1), forced vital capacity (FVC), forced expiratory flow in mid-half of FVC (FEF25-75), and peak expiratory flow rate (PEFR) values were obtained in 27 (47.37%), 43 (75.44%), 11 (19.3%), and 25 (43.86%) patients, and in Group B, in 13 (76.47%), 17 (100%), 1 (5.88%), and 8 (47%) patients, respectively. No patient had abnormal FEV1/FVC. All Group B patients had a restrictive pattern in spirometry as compared to 77% in Group A. Group B had a lower arterial partial pressure of oxygen (PaO2) (p=0.0019), % predicted FVC (p<0.0001), % predicted FEV1 (p=0.001), and 6-MWT distance (p<0.001). The physical component score in the short-form survey 12 questionnaire was higher in group A, p<0.001, whereas the mental component score was comparable. Conclusions Patients requiring invasive mechanical ventilation (MV) have a greater risk of impaired pulmonary function and reduced QOL post-ICU discharge. This warrants a greater need for following these patients for better rehabilitation.

An Adaptive Rank Aggregation-Based Ensemble Multi-Filter Feature Selection Method in Software Defect Prediction.

Feature selection is known to be an applicable solution to address the problem of high dimensionality in software defect prediction (SDP). However, choosing an appropriate filter feature selection (FFS) method that will generate and guarantee optimal features in SDP is an open research issue, known as the filter rank selection problem. As a solution, the combination of multiple filter methods can alleviate the filter rank selection problem. In this study, a novel adaptive rank aggregation-based ensemble multi-filter feature selection (AREMFFS) method is proposed to resolve high dimensionality and filter rank selection problems in SDP. Specifically, the proposed AREMFFS method is based on assessing and combining the strengths of individual FFS methods by aggregating multiple rank lists in the generation and subsequent selection of top-ranked features to be used in the SDP process. The efficacy of the proposed AREMFFS method is evaluated with decision tree (DT) and naïve Bayes (NB) models on defect datasets from different repositories with diverse defect granularities. Findings from the experimental results indicated the superiority of AREMFFS over other baseline FFS methods that were evaluated, existing rank aggregation based multi-filter FS methods, and variants of AREMFFS as developed in this study. That is, the proposed AREMFFS method not only had a superior effect on prediction performances of SDP models but also outperformed baseline FS methods and existing rank aggregation based multi-filter FS methods. Therefore, this study recommends the combination of multiple FFS methods to utilize the strength of respective FFS methods and take advantage of filter-filter relationships in selecting optimal features for SDP processes.

Intestinal parasitic infections and its trends: a 5-year findings from a tertiary care centre, Puducherry, South India.

Intestinal parasitic infection (IPI) constitute a global health burden causing clinical morbidity in 450 million people. Many of these are women of reproductive age and children in developing countries. Mass deworming programmes with improvement in lifestyle are likely to reduce the intensity and prevalence of infection over the years. Hence, we aimed to assess the prevalence of intestinal parasitic infections among patients in a tertiary healthcare setting and to examine its time trends. A descriptive cross-sectional study was done using routinely collected data in a tertiary care hospital in South India. Details of examination of stool samples for the presence of intestinal helminth and protozoan ova/cysts, over the period of 5 years (2014-2019) were extracted from laboratory register and hospital information system. The presence of intestinal parasitic infection was determined by stool microscopy (direct wet mount and concentration techniques). Of the total 3267 stool samples, 303 (9.3%) had at least one parasite; 3.9% (93/3267) with helminths and 2.5% (81/3267) Entamoeba and multi-parasitism was seen in 0.14%. Stool samples from more than 18 years age had high positivity rate than others. Majority of the helminth infections were caused by Ascaris (57%) followed by hookworm (42%). Initially IPI which was 10.9% in 2014 declined to 10% in 2016 and attained a peak of 12.4% in 2017 then decreased to 6.7% in 2018. Nearly one out of ten patients had a parasitic infection. Prevalence surveys in the community followed by strengthening the deworming procedures will reduce the burden of IPIs.