117 research outputs found
INVESTIGATION OF PHYTOCHEMICAL, MINERAL CONTENT, AND PHYSIOCHEMICAL PROPERTY OF A POLYHERBAL EXTRACT
Get PDFObjective: The objective of the present study was to investigate the phytochemical, mineral content, and physiochemical properties of a polyherbal extract (PE). Methods: Fresh plants Punica granatum (rind), Catharanthus roseus, Gymnema sylvestre, Cissus quadrangularis, Garcinia cambogia, Tinospora cordifolia, Terminalia Arjuna, Urginea indica, Ficus racemosa were selected for the PE. The plants were collected from various areas in and around Coimbatore district. The plants were washed, air dried, and coarsely powdered. 10 g of each plant powder has undergone various extract analysis for its phytochemical screening. The coarse extract called PE is been tested for physiochemical properties and its mineral content. Results: The presence of secondary metabolites such as flavonoids, glycosides, phenolic compounds, and tannins in all the extract but highest in the hydroethanolic extract. The physiochemical properties showed the appropriate pH and solubility of PE
Raising against the trauma of parenting: A trans woman's existent experience in stuck in the middle with you
Get PDFAbstract
The term ‘Transgender’ is used to describe people who
hold a different gender identity than their birth sex.
Many transgenders are prescribed hormones and Sex
Reassignment Surgeries by their doctors to change their
bodies as part of the process of transition. Sometimes,
not everyone in the transgender community will take
these steps to live to their inner identity. A transsexual is
one who wishes to transition to the sex he/she
identifies. Jennifer Finney Boylan is a highly praised
trans woman author and professor. She is an activist,
and her involvement in social activities for LGBT
people, especially transgenders, are highly notable. The
work Stuck in the Middle with You: A Memoir of
Parenting in Three Genders is a memoir about Boylan,
and her transition from a man to a woman while being
married and raising a family. It explores how changes in
gender roles affect one’s viewpoint of our family as
parents. This paper deals with how Boylan’s memoir
reflects her role as a trans parent, and it also explores her
journey from being a dad to both mom and dad
Worrying Leads to Reduced Concreteness of Problem Elaborations: Evidence for the Avoidance Theory of Worry
Get PDFBoth lay concept and scientific theory have embraced the view that nonpathological worry may be helpful for defining and analyzing problems. To evaluate the quality of problem elaborations, concreteness is a key variable. Two studies with nonclinical student samples are presented in which participants elaborated topics associated with different degrees of worry. In Study 1, participants' elaborations were assessed using problem elaboration charts; in Study 2, they were assessed using catastrophizing interviews. When participants' problem elaborations were rated for concreteness, both studies showed an inverse relationship between degree of worry and concreteness: The more participants worried about a given topic the less concrete was the content of their elaboration. The results challenge the view that worry may promote better problem analyses. Instead they conform to the view that worry is a cognitive avoidance response
Leser-Trélat Syndrome in a Male with Breast Carcinoma and Eyelid Basal Cell Carcinoma
No full text<b><i>Purpose:</i></b> Leser-Trélat syndrome consists of appearance of a solid tumor-like carcinoma breast, colon, or stomach following eruption of multiple seborrheic keratoses (SK) of the skin. We present an unusual and possibly the first case report of Leser-Trélat syndrome in a male patient with a history of mastectomy for breast carcinoma who presented to us with a second malignancy in the form of basal cell carcinoma (BCC) of the lower eyelid. <b><i>Procedure:</i></b> A 75-year-old male presented in 2014 with a history of modified radical mastectomy for infiltrating ductal carcinoma of the left breast which was performed 11 years prior to the day of presentation. Breast carcinoma was diagnosed following eruption of multiple SK at the same time. In the previous 3 years he noted a nodulo-ulcerative growth over the lateral aspect of the right lower eyelid which was clinically diagnosed as BCC. Mass excision under frozen section control and lid reconstruction was performed. Diagnosis of BCC was confirmed on histopathological examination of the excised specimen. <b><i>Results and Conclusions:</i></b> Though a previously unobserved entity, our case supports the importance of Leser-Trélat sign and its relevance to affected individuals, as early recognition and prompt treatment of a low-stage cancer offers good prognosis.</jats:p
Brassica juncea and Medicago sativa as Phytoremediators for the Removal of Chromium and Arsenic
Get PDFThis work aims to examine the effectiveness of phytoremediation, a process that uses Brassica juncea (Indian Mustard) and Medicago sativa (Alfalfa) plants to remediate contaminated soil with Cr and Ar. An economical and ecologically appropriate way to remove, immobilize, and degrade contaminants from soil and water is through phytoremediation. With this experiment, plants can grow in a controlled environment with different Cr and Ar concentrations in soil and the addition of organic compost. This entails evaluating the plants’ capacity to absorb metal, monitoring variations in the concentrations of metal in the plants’ roots, stems, leaves, and seeds, and looking into how organic matter affects the efficiency of phytoremediation. The findings showed that plants accumulated large amounts of chromium and arsenic across all experimental plants, but the highest accumulation was observed in the root system, which suggested that the plants were involved in the process of rhizofiltration. The roots pick up much more of the metals than the aerial of the plant, including stems, leaves, and seeds, thereby minimizing metal translocation to the parts of the plant that can be ingested by animals and, in turn, humans. This is a fundamental criterion for phytoremediation for assurance of a safe and effective process. Overall, the present study underscores the ability of phytoremediation in the remediation of heavy metal-polluted soils, especially under the use of organic growing media. It has made me understand the usefulness of this method for the effective and efficient cleaning of the soil in comparison with traditional methods, which could benefit the environment and future cost savings. Further research should be concerned with field-scale experiences and examine the potential of phytoremediation approaches in the range of environmental conditions
Analysis of Plants, Helianthus annuus (Sunflower) and Gossypium herbaceum (Cotton), for the Control of Heavy Metals Chromium and Arsenic Using Phytoremediation Techniques
Get PDFHeavy metal pollution released into the surface environment poses a significant threat, being hazardous to both the environment and living organisms. Phytoremediation thus appears as a viable technique to address heavy metal pollution in soils impacted by industrial effluents. To identify the growth performance of sunflower and cotton seeds under various concentrations of arsenic and chromium present in the tannery industrial wastewater in the Chengalpattu region, and to identify the accumulation of Arsenic(As)As and chromium (Cr) in the roots, shoots, and soil of these plants. This paper examined the usefulness of sunflower (Helianthus annuus) and cotton (Gossypium herbaceum) in eradicating Cr and As-polluted soils originating from tannery wastewater. In this experiment, Completely Randomized Block Design (CBRD) testing was performed, and the samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The accumulation of Cr in sunflowers was 120 mg.kg-1 in the roots and 25 mg.kg-1 in the above-ground parts. As accumulated to 85 mg.kg-1 in the roots and 15 mg.kg-1 in the above-ground parts. Similarly, cotton plants accumulated 90 mg.kg-1 of Cr in the roots and 20 mg.kg-1 in the above-ground parts. As accumulation in cotton plants was 100 mg.kg-1 in the roots and 30 mg.kg-1 in the aboveground parts. The study inferred that, in comparison to the other plants, the concentrations of Cr in sunflower roots were significantly higher, but cotton was found to have a better ability to take up As in the roots as well as in the aerial parts of the plant. It hence demonstrates the applicability of sunflower and cotton to support phytoremediation efforts sustainably within industrial environments to mitigate pollution and improve the quality of the soil
Unusual Constriction Zones in the Major Porins OmpU and OmpT from Vibrio cholerae
Get PDFThe outer membranes (OM) of many Gram-negative bacteria contain general porins, which form nonspecific, large-diameter channels for the diffusional uptake of small molecules required for cell growth and function. While the porins of Enterobacteriaceae (e.g., E. coli OmpF and OmpC) have been extensively characterized structurally and biochemically, much less is known about their counterparts in Vibrionaceae. Vibrio cholerae, the causative agent of cholera, has two major porins, OmpU and OmpT, for which no structural information is available despite their importance for the bacterium. Here we report high-resolution X-ray crystal structures of V. cholerae OmpU and OmpT complemented with molecular dynamics simulations. While similar overall to other general porins, the channels of OmpU and OmpT have unusual constrictions that create narrower barriers for small-molecule permeation and change the internal electric fields of the channels. Together with electrophysiological and in vitro transport data, our results illuminate small-molecule uptake within the Vibrionaceae. Pathania et al. describe the X-ray structures of the major Vibrio cholerae porins, OmpU and OmpT. The channels have narrow pore sizes and altered internal electric fields due to the presence of additional, unusual constriction elements. In addition, the interaction of deoxycholate and carbapenems with OmpU and OmpT are reported
Effect of polyherbal extract on TCA cycle enzymes and heart tissue histology in isoproterenol induced myocardial rats
No full textOptimisation of the Hybrid Feature Learning Algorithm for RUL estimation
No full textA B S T R A C TIn recent years, machine learning (ML) algorithms have been used tominimize maintenance costs and identify problems early in the auto-motive sector. The breakdown of a component or equipment impactsthe performance and cost, and hence it is considered a crucial stepin various domains. To fulfill this purpose, different approaches canbe considered to improve the application in real-world problems. Thedetermination of an asset’s residual useful life of a component at aspecific time is known as "remaining useful life" (RUL). The exten-sive evolution of data makes it challenging to analyze and interprethigh-level and valuable features from the data. The issue arises inall disciplines, and the automotive industry is no exception, giventhe large number of sensors to consider. Existing RUL research hasnot given much thought to the influence of high dimensionality dataon component maintenance and deterioration. The fundamental pur-pose of feature selection (FS) is to select a subset of features from thedata without compromising model performance. Lately, the trend ofresearch in feature selection has been based on bio-inspired methods.This work proposes a hybrid approach to the FS problem that com-bines Ant Colony Optimization (ACO) and Particle Swarm Optimiza-tion (PSO). When tested on public datasets, our results demonstrate arise in regression accuracy and a reduction in the number of selectedfeatures. ACO-PSO applies advantage from ACO to handle directlywith nominal attributes and uses advantage from PSO to handle con-tinuous features, utilizing the "the best of both worlds" in a singlealgorithm. This approach is combined with the random forest classi-fier for choosing the relevant and appropriate features. To gain betterresults from the algorithm, the performance of these approaches iscompared and the feature set with the best accuracy has been usedfor regression tasks. The results are evaluated in 5 public domaindatasets as well, and results show an increase in accuracy for the re-gression and the reduction of selected features number
Optimisation of the Hybrid Feature Learning Algorithm for RUL estimation
No full textA B S T R A C TIn recent years, machine learning (ML) algorithms have been used tominimize maintenance costs and identify problems early in the auto-motive sector. The breakdown of a component or equipment impactsthe performance and cost, and hence it is considered a crucial stepin various domains. To fulfill this purpose, different approaches canbe considered to improve the application in real-world problems. Thedetermination of an asset’s residual useful life of a component at aspecific time is known as "remaining useful life" (RUL). The exten-sive evolution of data makes it challenging to analyze and interprethigh-level and valuable features from the data. The issue arises inall disciplines, and the automotive industry is no exception, giventhe large number of sensors to consider. Existing RUL research hasnot given much thought to the influence of high dimensionality dataon component maintenance and deterioration. The fundamental pur-pose of feature selection (FS) is to select a subset of features from thedata without compromising model performance. Lately, the trend ofresearch in feature selection has been based on bio-inspired methods.This work proposes a hybrid approach to the FS problem that com-bines Ant Colony Optimization (ACO) and Particle Swarm Optimiza-tion (PSO). When tested on public datasets, our results demonstrate arise in regression accuracy and a reduction in the number of selectedfeatures. ACO-PSO applies advantage from ACO to handle directlywith nominal attributes and uses advantage from PSO to handle con-tinuous features, utilizing the "the best of both worlds" in a singlealgorithm. This approach is combined with the random forest classi-fier for choosing the relevant and appropriate features. To gain betterresults from the algorithm, the performance of these approaches iscompared and the feature set with the best accuracy has been usedfor regression tasks. The results are evaluated in 5 public domaindatasets as well, and results show an increase in accuracy for the re-gression and the reduction of selected features number
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