UNASSIGNED: The primary aim of the study is to evaluate the morphological form of the maxillary first premolar using 2D geomorphometry and evaluate the sexually dimorphic characteristics.
UNASSIGNED: The present study was carried out on standardized photographs of right Maxillary first premolar from 120 dental casts (60 male and 60 females). Twenty landmarks (based on geometric and anatomic evidence) were marked on the tooth using TPSdig software and analysed using Morpho J applying procrustes analysis and discriminant function analysis.
UNASSIGNED: The results showed similar centroid sizes between gender (p = 0.541). Procrustes ANOVA for shape analysis showed a greater dimorphism between sexs (f value of 1.35; p value=0.0793).  Discriminant function analysis based on the procrustes coordinates showed an overall accuracy of 74.2 % in classifying sex based on the landmark coordinates with correct classification of  48/60 (80.00%) females and 41/60 (68.33) males.
UNASSIGNED: Shape of the tooth can be measured objectively using geometric morphometric methods which can be utilized to identify the sex of an individual. The enamel is derived from ectoderm and once formed does not change during the life. The tooth\'s structure and shape are determined by the sex chromosomes, which is well represented as sexual dimorphism. The study evaluates the occlusal and contact area morphology of premolars. These are important parameters considered during restorative treatment, functional rehabilitation and forensic investigations.

UNASSIGNED: Current epidemiological evidence points to an association between micronutrient (MN) intake and sarcopenia, but studies have focused on single MN, and no combined effects on MNs have been reported. The aim of this study was to investigate the relationship between different MN intake patterns and sarcopenia and skeletal muscle mass.
UNASSIGNED: We performed a population-based cross-sectional study, with a total of 5,256 U.S. adults aged 20-59 years, and we collected total daily MN intake and appendicular skeletal muscle mass measured by Dual-Energy X-ray Absorptiometry (DXA). Principal component analysis (PCA) was used to obtain nutrient patterns and principal component scores based on the intake of 14 MNs, and logistic regression analysis was used to assess the effects of single MN and MN intake patterns on sarcopenia and muscle mass.
UNASSIGNED: We defined three MN intake patterns by PCA: (1) adherence to VitB-mineral, high intake of vitamin B and minerals; (2) adherence to VitAD-Ca-VB12, high intake of vitamin A, vitamin D, calcium and vitamin B12; and (3) adherence to Antioxidant Vit, high intake of antioxidant vitamins A, C, E, and K. These three nutrient patterns explained 73.26% of the variance of the population. A negative association was observed between most single MN intakes and sarcopenia, and after adjusting for confounders, adherence to the highest tertile of the three nutrient patterns was associated with a lower risk of sarcopenia and relatively higher skeletal muscle mass compared to the lowest adherence. In subgroup analysis, MN intake patterns were significantly correlated with sarcopenia in middle-aged females.
UNASSIGNED: Nutritional patterns based on MN intake were significantly related to sarcopenia, indicating that MNs interact with each other while exerting their individual functions, and that MN dietary patterns may provide promising strategies for preventing the loss of muscle mass, with further prospective studies warranted in the future.

The effect of dietary patterns on lung cancer risk is currently debated. In this study, we evaluated the association between different \"a posteriori\" dietary patterns and lung cancer risk. The search was carried out (February 2023) through Scopus, Web of Science, and PubMed databases. Meta-analysis was performed by a random-effects model using risk values (RR and OR) extracted from the 12 selected studies. Two main dietary patterns were identified and named \"Western/meat\" and \"Healthy/prudent\". The highest adherence to the \"Western/meat\" dietary pattern significantly increased the lung cancer risk (OR = 1.39; 95% CI: 1.17-1.65; p = 0.0002) while the highest adherence to the \"Healthy/prudent\" pattern reduced it (OR = 0.65; 95% CI: 0.51-0.83; p = 0.001). A linear trend between both dietary patterns and lung cancer risk was observed. However, a statistically significant inverse dose-response trend was found only for the \"Healthy/prudent\" dietary pattern (regression coefficient = -0.0031, p = 0.003). Subgroup analyses showed that the \"Western/meat\" pattern significantly increased the lung cancer risk in former (n = 4) (OR = 1.93, 95% CI: 1.11-3.36) and current smokers (n = 7) (OR = 1.35, 95% CI: 1.06-1.71). Similarly, the \"Healthy/prudent\" pattern exerts a protective effect on former (n = 4) (OR = 0.61, 95% CI: 0.44-0.85) and current smokers (n = 8) (OR = 0.64, 95% CI: 0.46-0.88). For both dietary patterns, no significant effect was observed on never-smokers.

Forward feed multilayered perception and central composite rotatable design were used to model the nonthermal plasma (NTP) experimental data in artificial neural network (ANN) and response surface methodology, respectively. The ANN was found to be more accurate in modeling the experimental dataset. The NTP process parameters (voltage and time) were optimized for pineapple juice within the range of 25-45 kV and 120-900 s using an ANN coupled with the genetic algorithm (ANN-GA). After 176 generations of GA, the ANN-GA approach produced the optimal condition, 38 kV and 631 s, and caused the inactivation of peroxidase (POD) and bromelain by 87.24% and 51.04%, respectively. However, 100.32% of the overall antioxidant capacity and 89.96% of the ascorbic acid were maintained in the optimized sample with a total color change (ΔE) of less than 1.97 at all plasma treatment conditions. Based on optimal conditions, NTP provides a sufficient level of POD inactivation combined with excellent phenolic component extractability and high antioxidant retention. Furthermore, plasma treatment had an insignificant effect (p > 0.05) on the physicochemical attributes (pH, total soluble solid, and titratable acidity) of juice samples. From the intensity peak of the Fourier-transform infrared spectroscopy analysis, it was found that the sugar components and phenolic compounds of plasma-treated juice were effectively preserved compared to the thermal-treated juice.

BACKGROUND: Sulfasalazine and pentoxifylline are co-prescribed together to treat psoriasis and pemphigus vulgaris. Sulfasalazine is an anti-inflammatory, immunosuppressant, and antibiotic drug, while pentoxifylline is a vasodilator and immunosuppressant. The spectra of the two drugs and plasma suffer from severe overlap.
OBJECTIVE: This work aims to simultaneously determine sulfasalazine and pentoxifylline in their binary mixture and spiked human plasma by the assessment of their UV spectral data.
METHODS: Two model updated chemometric methods were established using principal component regression and partial least-squares regression models. The two models were validated in accordance with the U.S. Food and Drug Administration guidelines for bioanalysis and were applied for the determination of both drugs in synthetic mixtures or spiked human plasma.
RESULTS: Accuracy and precision were within the accepted limits. In addition, three different assessment methods were used to evaluate the environmental greenness of the proposed models.
CONCLUSIONS: The two updated models are simple, rapid, sensitive, and precise, and could be easily applied in QC laboratories for determination of sulfasalazine and pentoxifylline, without any preliminary separation steps or interference from plasma matrix.
CONCLUSIONS: Two updated chemometric models called principlal component regression and partial least-squares regression were established for determination of sulfasalazine and pentoxifylline in spiked human plasma using UV spectrophotometric data.

The impact of environmental pollution in air and water is reflected mainly in the soil ecosystem as it impairs soil functions. Also, since the soil is the habitat for billions of organisms, the biodiversity is in turn altered. Microbes are precise sensors of ecological contamination, and bacteria have a key and important function in terms of bioremediation of the contaminated soil. Hence in the current work, we aimed at assessing the unidentified bacterial population through Illumina MiSeq sequencing technology and their community structural changes in different levels of petroleum-contaminated soil and sludge samples (aged, sludge, and leakage soil) to identify unique bacteria for their potential application in remediation. The studies showed that major bacterial consortiums namely, Proteobacteria (57%), Alphaproteobacteria (31%), and Moraxellaceae (23%) were present in aged soil, whereas Proteobacteria (52%), Alphaproteobacteria (33%), and Rhodobacteraceae (28%) were dominantly found in sludge soil. In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. In addition, we also analyzed various physicochemical properties of soil including pH, temperature, salinity, electrical conductivity, alkalinity, total carbon, total organic matter, nitrogen, phosphorus and potassium to calculate the soil quality index (SQI). The SQI of aged, sludge and leakage soil samples were 0.73, 0.64, and 0.89, respectively. These findings show the presence of unexplored bacterial species which could be applied for hydrocarbon remediation and further they can be exploited for the same.

Hypertension is one of the most significant risk factors for many cardiovascular diseases. At different stages of hypertension development, various pathophysiological processes can play a key role in the manifestation of the hypertensive phenotype and of comorbid conditions. Accordingly, it is thought that when diagnosing and choosing a strategy for treating hypertension, it is necessary to take into account age, the stage of disorder development, comorbidities, and effects of emotional-psychosocial factors. Nonetheless, such an approach to choosing a treatment strategy is hampered by incomplete knowledge about details of age-related associations between the numerous features that may contribute to the manifestation of the hypertensive phenotype. Here, we used two groups of male F2(ISIAHxWAG) hybrids of different ages, obtained by crossing hypertensive ISIAH rats (simulating stress-sensitive arterial hypertension) and normotensive WAG rats. By principal component analysis, the relationships among 21 morphological, physiological, and behavioral traits were examined. It was shown that the development of stress-sensitive hypertension in ISIAH rats is accompanied not only by an age-dependent (FDR < 5%) persistent increase in basal blood pressure but also by a decrease in the response to stress and by an increase in anxiety. The plasma corticosterone concentration at rest and its increase during short-term restraint stress in a group of young rats did not have a straightforward relationship with the other analyzed traits. Nonetheless, in older animals, such associations were found. Thus, the study revealed age-dependent relationships between the key features that determine hypertension manifestation in ISIAH rats. Our results may be useful for designing therapeutic strategies against stress-sensitive hypertension, taking into account the patients\' age.

For the past 25 years, medical imaging has been extensively used for clinical diagnosis. The main difficulties in medicine are accurate disease recognition and improved therapy. Using a single imaging modality to diagnose disease is challenging for clinical personnel. In this paper, a novel structural and spectral feature enhancement method in NSST Domain for multimodal medical image fusion (MMIF) is proposed. Initially, the proposed method uses the Intensity, Hue, Saturation (IHS) method to generate two pairs of images. The input images are then decomposed using the Non-Subsampled Shearlet Transform (NSST) method to obtain low frequency and high frequency sub-bands. Next, a proposed Structural Information (SI) fusion strategy is employed to Low Frequency Sub-bands (LFS\'s). It will enhance the structural (texture, background) information. Then, Principal Component Analysis (PCA) is employed as a fusion rule to High Frequency Sub-bands (HFS\'s) to obtain the pixel level information. Finally, the fused final image is obtained by employing inverse NSST and IHS. The proposed algorithm was validated using different modalities containing 120 image pairs. The qualitative and quantitative results demonstrated that the algorithm proposed in this research work outperformed numerous state-of-the-art MMIF approaches.

Photoplethysmography (PPG) signals are widely used in clinical practice as a diagnostic tool since PPG is noninvasive and inexpensive. In this article, machine learning techniques were used to improve the performance of classifiers for the detection of cardiovascular disease (CVD) from PPG signals. PPG signals occupy a large amount of memory and, hence, the signals were dimensionally reduced in the initial stage. A total of 41 subjects from the Capno database were analyzed in this study, including 20 CVD cases and 21 normal subjects. PPG signals are sampled at 200 samples per second. Therefore, 144,000 samples per patient are available. Now, a one-second-long PPG signal is considered a segment. There are 720 PPG segments per patient. For a total of 41 subjects, 29,520 segments of PPG signals are analyzed in this study. Five dimensionality reduction techniques, such as heuristic- (ABC-PSO, cuckoo clusters, and dragonfly clusters) and transformation-based techniques (Hilbert transform and nonlinear regression) were used in this research. Twelve different classifiers, such as PCA, EM, logistic regression, GMM, BLDC, firefly clusters, harmonic search, detrend fluctuation analysis, PAC Bayesian learning, KNN-PAC Bayesian, softmax discriminant classifier, and detrend with SDC were utilized to detect CVD from dimensionally reduced PPG signals. The performance of the classifiers was assessed based on their metrics, such as accuracy, performance index, error rate, and a good detection rate. The Hilbert transform techniques with the harmonic search classifier outperformed all other classifiers, with an accuracy of 98.31% and a good detection rate of 96.55%.

The study of medicinal plants with their traditional uses and related pharmacological studies has received more attention during the past several decades around the world. The Malayali tribes of the Javadhu Hills in the Eastern Ghats rely heavily on a system of traditional medicine for healthcare. A qualitative ethnographic method with a semi-structured questionnaire was used to interview 52 people across 11 localities in the Javadhu Hills. In the data analysis, descriptive statistics such as Use reports (UR), frequency of citations (FC), relative frequency of citations (RFC), informant agreement ratio (IAR), fidelity level (FL), and informant consensus factor (FIC) were studied. In the current investigation, 146 species from 52 families and 108 genera were discovered to treat 79 diseases. Leguminosae and Apocynaceae were the dominant families (12 species each). The most frequently used life form was the herb and the plant part were the leaf. The majority were being harvested from natural resources. Most medicines were taken orally. The most frequently cited species are Moringa oleifera and Syzygium cumini. The illnesses were divided into 21 categories. The majority of the plants mentioned are utilised to increase human immunity and health. The principal ailment (general health) was revealed by two-way cluster analysis and PCA. The species Litsea decanensis, Phoebe paniculata, Commiphora caudata, etc., were new records for the Javadhu hills according to a comparison between the current study and previous local and regional research. Documenting novel ethnomedicinal species and their therapeutic applications will encourage more phytochemical and pharmacological research and may even result in the creation of new medications. Furthermore, the study\'s significant novelty is that principle component analysis and two-way cluster analysis clearly revealed that the species that are used to treat various diseases, as well as species that are closely associated with treating specific ailment categories, are distinct. Significantly, species recorded in this study rely on maintaining and improving general body health of humans.