Tag: nevin manimala

Environ Res. 2023 Jun 10:116391. doi: 10.1016/j.envres.2023.116391. Online ahead of print.

ABSTRACT

The societal costs of air pollution have historically been measured in terms of premature deaths (including the corresponding values of statistical lives lost), disability-adjusted life years, and medical costs. Emerging research, however, demonstrated potential impacts of air pollution on human capital formation. Extended contact with pollutants such as airborne particulate matter among young persons whose biological systems are still developing can result in pulmonary, neurobehavioral, and birth complications, hindering academic performance as well as skills and knowledge acquisition. Using a dataset that tracks 2014-2015 incomes for 96.2% of Americans born between 1979 and 1983, we assessed the association between childhood exposure to fine particulate matter (PM_2.5) and adult earnings outcomes across U.S. Census tracts. After accounting for pertinent economic covariates and regional random effects, our regression models indicate that early-life exposure to PM_2.5 is associated with lower predicted income percentiles by mid-adulthood; all else equal, children raised in high pollution tracts (at the 75th percentile of PM_2.5) are estimated to have approximately a 0.51 decrease in income percentile relative to children raised in low pollution tracts (at the 25th percentile of PM_2.5). For a person earning the median income, this difference corresponds to a $436 lower annual income (in 2015 USD). We estimate that 2014-2015 earnings for the 1978-1983 birth cohort would have been ∼$7.18 billion higher had their childhood exposure met U.S. air quality standards for PM_2.5. Stratified models show that the relationship between PM_2.5 and diminished earnings is more pronounced for low-income children and for children living in rural environments. These findings raise concerns about long-term environmental and economic justice for children living in areas with poor air quality where air pollution could act as a barrier to intergenerational class equity.

PMID:37308068 | DOI:10.1016/j.envres.2023.116391

Am J Cardiol. 2023 Jun 10;200:78-86. doi: 10.1016/j.amjcard.2023.05.036. Online ahead of print.

ABSTRACT

Risk prediction scores for long-term outcomes after transcatheter aortic valve implantation (TAVI) or surgical aortic valve replacement (SAVR) are lacking. This study aimed to develop preprocedural risk scores for 5-year clinical outcomes after TAVI or SAVR. This analysis included 1,660 patients at an intermediate surgical risk with severe aortic stenosis randomly assigned to TAVI (n = 864) or SAVR (n = 796) from the SURTAVI (Surgical Replacement and Transcatheter Aortic Valve Implantation) trial. The primary end point was a composite of all-cause mortality or disabling stroke at 5 years. The secondary end point was a composite of cardiovascular mortality or hospitalizations for valve disease or worsening heart failure at 5 years. Preprocedural multivariable predictors of clinical outcomes were used to calculate a simple risk score for both procedures. At 5 years, the primary end point occurred in 31.3% of the patients with TAVI and 30.8% of the patients with SAVR. Preprocedural predictors differed between TAVI and SAVR. Baseline anticoagulant use was a common predictor for events in both procedures, whereas male sex and a left ventricular ejection fraction <60% were significant predictors for events in patients with TAVI and SAVR, respectively. A total of 4 simple scoring systems were created based on these multivariable predictors. The C-statistics of all models were modest but performed better than the contemporary risk scores. In conclusion, preprocedural predictors of events differ between TAVI and SAVR, necessitating separate risk models. Despite the modest predictive value of the SURTAVI risk scores, they appeared superior to other contemporary scores. Further research is needed to strengthen and validate our risk scores, possibly by including biomarker and echocardiographic parameters.

PMID:37307783 | DOI:10.1016/j.amjcard.2023.05.036

Leg Med (Tokyo). 2023 Jun 6;64:102280. doi: 10.1016/j.legalmed.2023.102280. Online ahead of print.

ABSTRACT

In both forensic and archaeological domains, the discovery of incomplete human remains is a frequent occurrence. Nevertheless, the estimation of biological profiles from such remains presents a challenge due to the absence of crucial skeletal elements, such as the skull and pelvis. This study aimed to assess the utility of the proximal femur in the forensic identification process by creating a web application for osteometric analysis of the proximal femur. The aim was to determine the sex and stature of an individual from radiographs of the left anteroposterior femur. To accomplish this, an automated method was developed for acquiring linear measurements from radiographic images of the proximal femur using Python tools. The application of Hough techniques and Canny edge detection was utilized to generate linear femoral dimensions from radiographs. A total of 354 left femora were radiographed and measured by the algorithm. The sex classification model employed in this study was the Naïve Bayes algorithm (accuracy = 91.2 %). Results indicated that Gaussian process regression (GPR) was the most effective method for estimating stature (mean error = 4.68 cm, SD = 3.93 cm). The proposed web application holds the potential to serve as a valuable asset in the realm of forensic investigations in Thailand, particularly in the estimation of biological profiles from fragmentary skeletal remains.

PMID:37307774 | DOI:10.1016/j.legalmed.2023.102280

Gait Posture. 2023 Jun 2;104:43-50. doi: 10.1016/j.gaitpost.2023.05.026. Online ahead of print.

ABSTRACT

BACKGROUND: CMT is a clinically and genetically heterogenous disease with varying degrees of progression. Different foot deformities, gait and movement patterns are observed. In order to achieve an improved, targeted treatment strategy, the participants are divided into characteristic groups using a mathematical cluster analysis based on the data from the three-dimensional foot kinematics during walking.

METHODS: Outpatients from age 5-64 years (N = 33 participants, 62 feet) with a proven CMT type 1 (N = 16, 31 feet) or CMT without any further type assignment (N = 17, 31 feet) were retrospectively analyzed. After a standard clinical examination, participants underwent 3D gait analysis using the Oxford Foot Model. To classify the movement patterns, a k-means cluster analysis was calculated based on the principal component analysis (PCA) of the foot kinematics data. Gait parameters, clinical parameters and X-ray data were statistically tested.

RESULTS: The cluster analysis divided the gait data of the participants into two groups. Cluster 1 (N = 21 participants, 34 feet) showed increased dorsiflexion of the hindfoot and increased plantarflexion of the forefoot with cavus position in the sagittal plane, a hindfoot inversion and forefoot pronation with hindfoot varus in the frontal plane and in the transversal plane a forefoot adduction. Cluster 2 (N = 17 participants, 28 feet) deviated significantly from the norm mainly in the frontal plane and were characterized by a strong eversion of the hindfoot with a supination in the forefoot.

DISCUSSION: Based on the findings, the resultant clusters can be interpreted as cavovarus feet (cluster 1) and pes valgus (cluster 2). The most reliable variables in the 3D gait analysis to classify CMT feet with regard to significance are the ones in the frontal plane. This subdivision of participants goes hand in hand with the various necessary guidelines for orthopedic treatment.

PMID:37307763 | DOI:10.1016/j.gaitpost.2023.05.026

Gait Posture. 2023 Jun 2;104:22-30. doi: 10.1016/j.gaitpost.2023.05.028. Online ahead of print.

ABSTRACT

BACKGROUND: Gait analysis relies on the accurate and precise identification of anatomical landmarks to provide reliable and reproducible data. More specifically, the precision of marker placement among repeated measurements is responsible for increased variability in the output gait data.

RESEARCH QUESTION: The objective of this study was to quantify the precision of marker placement on the lower limbs by a test-retest procedure and to investigate its propagation to kinematic data.

METHODS: The protocol was tested on a cohort of eight asymptomatic adults involving four evaluators, with different levels of experience. Each evaluator performed, three repeated marker placements for each participant. The standard deviation was used to calculate the precision of the marker placement, the precision of the orientation of the anatomical (segment) coordinate systems, and the precision of the lower limb kinematics. In addition, one-way ANOVA was used to compare the intra-evaluator marker placement precision and kinematic precisions among the different levels of the evaluator’s experience. Finally, a Pearson correlation between marker placement precision and kinematic precision was analyzed.

RESULTS: Results have shown a precision of skin markers within 10 mm and 12 mm for intra-evaluator and inter-evaluator, respectively. Analysis of kinematic data showed good to moderate reliability for all parameters apart from hip and knee rotation that demonstrated poor intra- and inter-evaluator precision. Inter-trial variability was observed reduced than intra- and inter-evaluator variability. Moreover, experience had a positive impact on kinematic reliability since evaluators with higher experience showed a statistically significant increase in precision for most kinematic parameters. However, no correlation was observed between marker placement precision and kinematic precision which indicates that an error in the placement of one specific marker can be compensated or enhanced, in a non-linear way, by an error in the placement of other markers.

PMID:37307761 | DOI:10.1016/j.gaitpost.2023.05.028

Phytomedicine. 2023 Jun 2;117:154897. doi: 10.1016/j.phymed.2023.154897. Online ahead of print.

ABSTRACT

BACKGROUND: Natural products are an important source for discovering novel drugs due to their various pharmacological activities. Salvia miltiorrhiza Burge (Danshen) has been shown to have promising therapeutic potential in the management of heart diseases, making it a candidate for cardiovascular drug discovery. Currently, there is limited quantitative analysis of the phosphorylation levels of Danshen-derived natural products on a proteome-wide, which may bias the study of their mechanisms of action.

PURPOSE: This study aimed to evaluate the global signaling perturbation induced by Danshen-derived bioactive compounds and their potential relationship with myocardial ischemia/reperfusion (IR) injury therapy.

STUDY DESIGN: We employed quantitative proteome and phosphoproteome analysis to identify dysregulated signaling in IR injury hearts from mice. We compared changes induced by Danshen-derived compounds based on IR-associated phospho-events, using an integrative approach that maps relative abundance of proteins and phosphorylation sites.

METHODS: Isobaric chemical tandem mass tags (TMT) labeled multiplexing strategy was used to generate unbiased quantitative proteomics and phosphoproteomics data. Highly accurate and precise TMT quantitation was performed using the Orbitrap Fusion Tribrid Mass Spectrometer with synchronous precursor selection MS3 detection mode. Mass spectrometric raw files were analyzed with MaxQuant (2.0.1.0) and statistical and bioinformatics analysis was conducted with Perseus (1.6.15).

RESULTS: We quantified 3661 proteins and over 11,000 phosphosites in impaired heart tissue of the IR mice model, expanding our knowledge of signaling pathways and other biological processes disrupted in IR injury. Next, 1548 and 5545 differently expressed proteins and phosphosites were identified by quantifying the proteome and phosphoproteome of H9c2 cells treated by five Danshen bioactive compounds respectively. Results revealed the vast differences in abilities of five Danshen-derived bioactive compounds to regulate phosphorylation modifications in cardiomyocytes, with dihydrotanshinone I (DHT) showing potential for protecting against IR injury by modulating the AMPK/mTOR signaling pathway.

CONCLUSIONS: This study provides a new strategy for analyzing drug/natural product-regulated phosphorylation modification levels on a proteome-wide scale, leading to a better understanding of cell signaling pathways and downstream phenotypic responses.

PMID:37307738 | DOI:10.1016/j.phymed.2023.154897

Braz J Otorhinolaryngol. 2023 Apr 21;89(4):101273. doi: 10.1016/j.bjorl.2023.04.001. Online ahead of print.

ABSTRACT

OBJECTIVE: Idiopathic Sudden Sensorineural Hearing Loss (ISSHL) is an otologic emergency, and an early prediction of prognosis may facilitate proper treatment. Therefore, we investigated the prognostic factors for predicting the recovery in patients with ISSHL treated with combined treatment method using machine learning models.

METHODS: We retrospectively reviewed the medical records of 298 patients with ISSHL at a tertiary medical institution between January 2015 and September 2020. Fifty-two variables were analyzed to predict hearing recovery. Recovery was defined using Siegel’s criteria, and the patients were categorized into recovery and non-recovery groups. Recovery was predicted by various machine learning models. In addition, the prognostic factors were analyzed using the difference in the loss function.

RESULTS: There were significant differences in variables including age, hypertension, previous hearing loss, ear fullness, duration of hospital admission, initial hearing level of the affected and unaffected ears, and post-treatment hearing level between recovery and non-recovery groups. The deep neural network model showed the highest predictive performance (accuracy, 88.81%; area under the receiver operating characteristic curve, 0.9448). In addition, initial hearing level of affected and non-affected ear, post-treatment (2-weeks) hearing level of affected ear were significant factors for predicting the prognosis.

CONCLUSION: The deep neural network model showed the highest predictive performance for recovery in patients with ISSHL. Some factors with prognostic value were identified. Further studies using a larger patient population are warranted.

LEVEL OF EVIDENCE: Level 4.

PMID:37307713 | DOI:10.1016/j.bjorl.2023.04.001

J Environ Manage. 2023 Jun 10;342:118343. doi: 10.1016/j.jenvman.2023.118343. Online ahead of print.

ABSTRACT

The wine-making industry drives tourism and rural revitalization in several countries. Meanwhile, winemaking generates wastewater at all production stages, mainly from cleaning of equipment, floors, vessels, and bottles. This review presents a comprehensive analysis with statistical characteristics on the overall quality and generation rate of winery wastewater since 2007, identifies the technologies used by wineries in pilot- and full-scale wastewater treatment systems, and offers insights on practical wastewater treatment at small wineries. The median wastewater generation rate has been reduced to 1.58 L/L-wine, with a weekly peaking factor of 1.6-3.4 and monthly peaking factor of 2.1-2.7. Winery wastewater is acidic and of high organic strength. The organic substances are largely biodegradable and constituent concentrations do not exceed 50% inhibitory levels for biological treatment. However, the small ratios of nitrogen and phosphorus to biochemical oxygen demand indicate substantial needs to supplement nutrients for aerobic biological treatment. The frequency of processes used to pretreat winery wastewater was in the order of sedimentation > coarse screening > equalization > neutralization. The most frequently reported treatment methods were constructed wetland, activated sludge process, membrane bioreactor, and anaerobic digestion. Advanced oxidation processes have been pilot tested for polishing. The best wastewater management practice at small wineries is physical pretreatment, followed by land-based treatment systems. Covered anaerobic lagoons and underground digesters are practicable anaerobic digestion designs to reduce organic loading to land-based treatment systems. Research is needed to develop sufficient design criteria for the best practicable treatment processes and compare land-based treatment systems at pilot and full scales.

PMID:37307695 | DOI:10.1016/j.jenvman.2023.118343

J Vet Cardiol. 2023 May 6;48:19-30. doi: 10.1016/j.jvc.2023.05.003. Online ahead of print.

ABSTRACT

INTRODUCTION/OBJECTIVES: Dogs with severe subaortic stenosis (SAS) are at risk of dying suddenly from fatal arrhythmias. Survival is not improved when treated with pure beta-adrenergic receptor (β)-blockers; however, the effect of other antiarrhythmic drugs on survival is unknown. Sotalol is both a β-blocker and a class III antiarrhythmic drug; the combination of these differing mechanisms may provide benefit to dogs with severe SAS. The primary objective of this study was to compare survival in dogs with severe SAS that were treated with either sotalol or atenolol. The secondary objective was to evaluate the effect of pressure gradient (PG), age, breed, and aortic regurgitation on survival.

ANIMALS: Forty-three client-owned dogs.

MATERIALS AND METHODS: Retrospective cohort study. Medical records of dogs diagnosed with severe SAS (PG ≥ 80 mmHg) between 2003 and 2020 were reviewed.

RESULTS: No statistical difference was identified in survival time between dogs treated with sotalol (n = 14) and those treated with atenolol (n = 29) when evaluating all-cause mortality (p=0.172) or cardiac-related mortality (p=0.157). Of the dogs that died suddenly, survival time was significantly shorter in dogs treated with sotalol compared to those treated with atenolol (p=0.046). Multivariable analysis showed that PG (p=0.002) and treatment with sotalol (p=0.050) negatively influenced survival in the dogs that died suddenly.

CONCLUSIONS: Sotalol did not have a significant effect on survival overall but may increase the risk of sudden death in dogs with severe SAS compared to atenolol.

PMID:37307692 | DOI:10.1016/j.jvc.2023.05.003

Cytokine. 2023 Jun 10;169:156269. doi: 10.1016/j.cyto.2023.156269. Online ahead of print.

ABSTRACT

BACKGROUND: Management of Graves’ ophthalmopathy (GO) is still a challenge in Graves’ disease (GD). Moreover, 40% of GD patients show radiological muscle enlargement without clinically apparent GO. Delayed treatment of GO may lead to deterioration in prognosis.

METHODS: Thirty GD patients with overt hyperthyroidism were included in this study, 17 of whom either had GO at diagnosis or developed GO during the study period. Samples were collected at the beginning of the study, at 6 months, and at 24 months. Plasma samples were analyzed for 92 cytokines using the Olink Target 96 inflammation panel.

RESULTS: After adjustment for multiplicity testing using the false discovery rate approach, soluble programmed death ligand 1 (sPD-L1) and fibroblast growth factor 23 (FGF-23) were significantly elevated in GO patients.

CONCLUSION: Using a broad cytokine panel we show that patients with Graves’ ophthalmopathy have elevated PD-L1 and FGF-23 levels. The findings support previous suggestions that PD-L1 may serve as a treatment target.

PMID:37307688 | DOI:10.1016/j.cyto.2023.156269