Exploring the structure and stability of β-dipeptide – A quantum chemical and molecular dynamics study

Density functional theory (DFT) calculations followed by molecular dynamics study has been performed to analyze the structure and stability of β-dipeptide structures in aqueous medium. From DFT study, three local minima with folded conformations and one local minimum with unfolded conformation have been identified. In gas phase, the most stable β-dipeptide has a folded conformation with a weak hydrogen bonding. The interaction of water molecules, approximated from the first solvation shell, also confirms the folded conformation to be the most stable structure. The DFT optimized β-dipeptide conformers have been simulated in explicit water to evaluate the tendency of folded and unfolded state formation. Simulations confirmed the transition of the structure from folded to unfolded and vice versa and further indicated the former to happen rapidly within a few pico second time scale

Depression, anxiety, stress and its correlates among urban school going adolescents in Tamilnadu, India

Background: Undetected and untreated mental disorders can impair a person’s ability to perform at school or work place, cope with daily activities of life and can lead to severe psychiatric disorders and consequences later in their life. Study objective was to determine the prevalence and patterns of depression, anxiety and stress among 400 school going adolescents belonging to classes 10th to 12th of Tirunelveli district, Tamilnadu, India.Methods: Burden of Depression, anxiety and stress was assessed using DASS21 questionnaire. Chi-square test was done using SPSS software version 21 to test for statistical significance.Results: Overall prevalence of depression, anxiety and stress was 73.6%, 86.5% and 24.7% respectively. Depression (p value=0.01), Anxiety (p value = 0.005) and stress (p value = 0.007) were significantly observed more among 10th class students when compared with other classes.Conclusions: The present study has identified a higher prevalence of depression, anxiety and stress among students. This warrants immediate action of creating awareness among teachers and parents in early identification and treatment to prevent serious consequences in later life

Social-sine cosine algorithm-based cross layer resource allocation in wireless network

Cross layer resource allocation in the wireless networks is approached traditionally either by communications networks or information theory. The major issue in networking is the allocation of limited resources from the users of network. In traditional layered network, the resource are allocated at medium access control (MAC) and the network layers uses the communication links in bit pipes for delivering the data at fixed rate with the occasional random errors. Hence, this paper presents the cross-layer resource allocation in wireless network based on the proposed social-sine cosine algorithm (SSCA). The proposed SSCA is designed by integrating social ski driver (SSD) and sine cosine algorithm (SCA). Also, for further refining the resource allocation scheme, the proposed SSCA uses the fitness based on energy and fairness in which max-min, hard-fairness, proportional fairness, mixed-bias and the maximum throughput is considered. Based on energy and fairness, the cross-layer optimization entity makes the decision on resource allocation to mitigate the sum rate of network. The performance of resource allocation based on proposed model is evaluated based on energy, throughput, and the fairness. The developed model achieves the maximal energy of 258213, maximal throughput of 3.703, and the maximal fairness of 0.868, respectively

Knowledge and practice about contraception among married women in reproductive age group in a rural area of Tirunelveli district, Tamil Nadu, India: a cross-sectional study

Background: Unmet need for contraception is still high in developing countries because of various reasons and poses a great challenge to the success of family welfare programme Assessing the knowledge and filling the gap is essential for successful functioning of the programme and for reducing the unmet need.Methods: A cross-sectional study was conducted to assess the knowledge and practices on contraception among 100 married women in reproductive age group (15-49 years) residing in a Rural Health centre area of Tirunelveli district, Tamil Nadu, South India.Results: Among the 100 participants, common known methods of contraception were IUD (56%), permanent sterilization (38%), Pills (21%) and Condoms (14%). Out of 100 participants, only 38 were using contraception. Among the 62 who are not using any method of contraception, 30 are willing to practice contraception after motivation and among them 27 prefer to use temporary methods. Fear of side effects was most common reason stated for not using contraception.Conclusions: Knowledge and practice related to contraception among the participants were observed to be less. Health education campaigns emphasizing the need of family planning and about the services available in the government health facilities has to be organized regularly

Generic Paddy Plant Disease Detector (GP2D2): An Application of the Deep-CNN Model

Rice is the primary food for almost half of the world’s population, especially for the people of Asian countries. There is a demand to improve the quality and increase the quantity of rice production to meet the food requirements of the increasing population. Bulk cultivation and quality production of crops need appropriate technology assistance over manual traditional methods. In this work, six popular Deep-CNN architectures, namely AlexNet, VGG-19, VGG-16, InceptionV3, MobileNet, and ResNet-50, are exploited to identify the diseases in paddy plants since they outperform most of the image classification applications. These CNN models are trained and tested with Plant Village dataset for classifying the paddy plant images into one of the four classes namely, Healthy, Brown Spot, Hispa, or Leaf Blast, based on the disease condition. The performance of the chosen architectures is compared with different hyper parameter settings. AlexNet outperformed other convolutional neural networks (CNNs) in this multiclass classification task, achieving an accuracy of 89.4% at the expense of a substantial number of network parameters, indicating the large model size of AlexNet. For developing mobile applications, the ResNet-50 architecture was adopted over other CNNs, since it has a comparatively smaller number of network parameters and a comparable accuracy of 86.1%. A fine-tuned ResNet-50 architecture supported mobile app, “Generic Paddy Plant Disease Detector (GP2D2)” has been developed for the identification of most commonly occurring diseases in paddy plants. This tool will be more helpful for the new generation of farmers in bulk cultivation and increasing the productivity of paddy. This work will give insight into the performance of CNN architectures in rice plant disease detection task and can be extended to other plants too

Multivariate analysis of histopathological features as prognostic factors in fifty cases of thyroid neoplasm: a retrospective study done at tertiary care centre

Background: Number of prognostic factors for thyroid carcinoma have been identified including age, gender and tumor characteristics, such as histology and stage. The importance of these factors as independent predictors of survival for patients with differentiated thyroid carcinoma has been extensively studied but remains uncertain. Methods: A retrospective analysis of 50 thyroid carcinomas was made to assess prognostic factors including histological variants from September 2019 to February 2022 at our centre. The surgical and histopathological data were studied. Results: 72% patients had papillary thyroid cancer. Multivariate analysis was done and factors showing prognostic significance were tumour size, extrathyroid extension, extranodal extension, lymphovascular, perineural invasion, histological type, necrosis, focality, capsular invasion were found to have poor prognosis. Conclusions: There are histopathological factors which can modify the course and influence the line of treatment of thyroid neoplasms

Tumor necrosis factor inhibitor therapy but not standard therapy is associated with resolution of erosion in the sacroiliac joints of patients with axial spondyloarthritis

INTRODUCTION: Radiography is an unreliable and insensitive tool for the assessment of structural lesions in the sacroiliac joints (SIJ). Magnetic resonance imaging (MRI) detects a wider spectrum of structural lesions but has undergone minimal validation in prospective studies. The Spondyloarthritis Research Consortium of Canada (SPARCC) MRI Sacroiliac Joint (SIJ) Structural Score (SSS) assesses a spectrum of structural lesions (erosion, fat metaplasia, backfill, ankylosis) and its potential to discriminate between therapies requires evaluation. METHODS: The SSS score assesses five consecutive coronal slices through the cartilaginous portion of the joint on T1-weighted sequences starting from the transitional slice between cartilaginous and ligamentous portions of the joint. Lesions are scored dichotomously (present/absent) in SIJ quadrants (fat metaplasia, erosion) or halves (backfill, ankylosis). Two readers independently scored 147 pairs (baseline, 2 years) of scans from a prospective cohort of patients with SpA who received either standard (n = 69) or tumor necrosis factor alpha (TNFα) inhibitor (n = 78) therapy. Smallest detectable change (SDC) was calculated using analysis of variance (ANOVA), discrimination was assessed using Guyatt’s effect size, and treatment group differences were assessed using t-tests and the Mann–Whitney test. We identified baseline demographic and structural damage variables associated with change in SSS score by univariate analysis and analyzed the effect of treatment by multivariate stepwise regression adjusted for severity of baseline structural damage and demographic variables. RESULTS: A significant increase in mean SSS score for fat metaplasia (P = 0.017) and decrease in mean SSS score for erosion (P = 0.017) was noted in anti-TNFα treated patients compared to those on standard therapy. Effect size for this change in SSS fat metaplasia and erosion score was moderate (0.5 and 0.6, respectively). Treatment and baseline SSS score for erosion were independently associated with change in SSS erosion score (β = 1.75, P = 0.003 and β = 0.40, P < 0.0001, respectively). Change in ASDAS (β = −0.46, P = 0.006), SPARCC MRI SIJ inflammation (β = −0.077, P = 0.019), and baseline SSS score for fat metaplasia (β = 0.085, P = 0.034) were independently associated with new fat metaplasia. CONCLUSION: The SPARCC SSS method for assessment of structural lesions has discriminative capacity in demonstrating significantly greater reduction in erosion and new fat metaplasia in patients receiving anti-TNFα therapy

Structure and Reactivity of Halogenated GC PNA Base Pairs – A DFT Approach

The present study explored the structural and reactivity relationship of halogenated G-C PNA base pairs using density functional theory (DFT) calculations. The halogens such as F, Cl, and Br are substituted by replacing H atoms involved in H-bonds of the base pairs. All structures were optimized using the B3LYP/6-311++G** theory level, and positive frequencies confirmed their equilibrium states. To understand the structural variations of the considered halogenated systems, the bond distances of R─X, R─H, and X/H•••Y and the bond angles of R─X•••Y were analyzed. The obtained structural parameters and interaction energies are comparable with the previous theoretical reports. In addition, the interaction energies (Eint) and quantum molecular descriptors (QMD) are also calculated to understand the difference between halogenated PNA systems and their non-halogenated counterparts. In this study, the enhancement in the reactivity properties &nbsp;of halogenated PNA systems has been demonstrated, which indicates their improved responsive characteristics in various chemical reactions. Based on the available results, the halogenated PNA systems, carefully considering their substitutional position, facilitate better accommodation for the triplex formation of dsDNA/dsRNA. Therefore, it is concluded that the improved reactivity properties of halogenated PNA base pairs would make them potential candidates for various biological applications

Transcriptomic-metabolomic reprogramming in EGFR-mutant NSCLC early adaptive drug escape linking TGFβ2-bioenergetics-mitochondrial priming.

The impact of EGFR-mutant NSCLC precision therapy is limited by acquired resistance despite initial excellent response. Classic studies of EGFR-mutant clinical resistance to precision therapy were based on tumor rebiopsies late during clinical tumor progression on therapy. Here, we characterized a novel non-mutational early adaptive drug-escape in EGFR-mutant lung tumor cells only days after therapy initiation, that is MET-independent. The drug-escape cell states were analyzed by integrated transcriptomic and metabolomics profiling uncovering a central role for autocrine TGFβ2 in mediating cellular plasticity through profound cellular adaptive Omics reprogramming, with common mechanistic link to prosurvival mitochondrial priming. Cells undergoing early adaptive drug escape are in proliferative-metabolic quiescent, with enhanced EMT-ness and stem cell signaling, exhibiting global bioenergetics suppression including reverse Warburg, and are susceptible to glutamine deprivation and TGFβ2 inhibition. Our study further supports a preemptive therapeutic targeting of bioenergetics and mitochondrial priming to impact early drug-escape emergence using EGFR precision inhibitor combined with broad BH3-mimetic to interrupt BCL-2/BCL-xL together, but not BCL-2 alone