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The global interest in market prediction has driven the adoption of advanced technologies beyond traditional statistical models. This paper explores the use of machine learning and deep learning techniques for stock market forecasting. We propose a comprehensive approach that includes efficient feature selection, data preprocessing, and classification methodologies. The wavelet transform method is employed for data cleaning and noise reduction. Feature selection is optimized using the Dandelion Optimization Algorithm (DOA), identifying the most relevant input features. A novel hybrid model, 3D-CNN-GRU, integrating a 3D convolutional neural network with a gated recurrent unit, is developed for stock market data analysis. Hyperparameter tuning is facilitated by the Blood Coagulation Algorithm (BCA), enhancing model performance. Our methodology achieves a remarkable prediction accuracy of 99.14%, demonstrating robustness and efficacy in stock market forecasting applications. While our model shows significant promise, it is limited by the scope of the dataset, which includes only the Nifty 50 index. Broader implications of this work suggest that incorporating additional datasets and exploring different market scenarios could further validate and enhance the model's applicability. Future research could focus on implementing this approach in varied financial contexts to ensure robustness and generalizability. [ABSTRACT FROM AUTHOR]

Chest X-Ray (CXR) images provide most anatomical details and the abnormalities on a 2D plane. Therefore, a 2D view of the 3D anatomy is sometimes sufficient for the initial diagnosis. However, close to fourteen commonly occurring diseases are sometimes difficult to identify by visually inspecting the images. Therefore, there is a drift toward developing computer-aided assistive systems to help radiologists. This paper proposes a deep learning model for the classification and localization of chest diseases by using image-level annotations. The model consists of a modified Resnet50 backbone for extracting feature corpus from the images, a classifier, and a pixel correlation module (PCM). During PCM training, the network is a weight-shared siamese architecture where the first branch applies the affine transform to the image before feeding to the network, while the second applies the same transform to the network output. The method was evaluated on CXR from the clinical center in the ratio of 70:20 for training and testing. The model was developed and tested using the cloud computing platform Google Colaboratory (NVidia Tesla P100 GPU, 16 GB of RAM). A radiologist subjectively validated the results. Our model trained with the configurations mentioned in this paper outperformed benchmark results. [ABSTRACT FROM AUTHOR]

Context: Hair strength depends on integrity of protein structure, aging, and chemical effects and its exposure to mechanical (combing and curling) and thermal (hair drying and straightening) stimuli. Aims: The aim of this study is to correlate the mechanical properties such as tensile yield stress and tensile modulus of single hair fibers with thermal properties such as melting enthalpy and melting point obtained by differential scanning calorimetry. Materials and Methods: Single hair fibers covering seven decades of age were cut 2 cm above the scalp. Tensile specimens were prepared using single fibers with gauge length of 20 mm, and test was carried out with speed of 20 mm/min. For thermal analysis, 2-3 mg of hair samples were cut to 0.5 mm length and loaded in aluminum pan and heated at a rate of 10°C/min from 30°C to 280°C. Data Analysis: Tensile yield stress (determined at the onset of stress constancy at ~3% strain) and tensile modulus were determined using Origin software. The same software was used to plot the thermal data as heat flow (W/g)-temperature diagrams and to determine the peak temperature and peak area (melting enthalpy) by creating a sigmoidal baseline. Results: The typical values of tensile modulus, yield stress, and maximum stress obtained were 5.1 ± 0.5 GPa, 109 ± 9 MPa, and 161 ± 24 MPa, respectively. Further, typical values of melting enthalpy and peak temperature determined were 6.29 ± 0.20 J/g and 235°C ± 0.6°C, respectively. Conclusions: Mechanical yield stress and melting enthalpy were compared, and it was found that a good nonlinear (sigmoidal) correlation was obtained. The nonlinear correlation seems to provide an accurate representation of a composite keratin structure wherein the % crystallinity exhibits a range, and also, crystalline and amorphous regions are intertwined and intricate in nature. [ABSTRACT FROM AUTHOR]

Background: There has been much debate in the past about whether honey is harmful to the teeth, mostly as part of the debate about raw sugar versus refined sugar and the results have been equivocal. However, what has not been taken into account is that honey varies markedly in the potency of its antibacterial activity. Manuka (Leptospermum scoparium) honey from New Zealand has been found to have substantial levels of non-peroxide antibacterial activity associated with an unidentified phytochemical component, denoted as Unique Manuka Factor (UMF). Aims: Considering the potential antimicrobial effects of manuka honey, the present study attempted to investigate effects of twice daily use of manuka honey with UMF 19.5 on salivary levels of Mutans streptococci in children. Study Design: The investigation was a stratified comparison of two parallel groups of children who either used manuka honey with regular tooth brushing regimen or continued only with regular tooth brushing regimen twice daily under professional supervision for a 21-day period. A total of three salivary samples were taken from each individual at baseline, day 10, and day 21; colony counts of Streptococcus mutans (S. mutans) were determined. All data was subjected to paired T-test and Wilcoxon's signed ranks sum for intra-and intergroup comparisons respectively. Results: Children using manuka honey showed statistically significant reductions in salivary S. mutans after 10 and 21 days. Conclusion: Manuka honey with UMF 19.5 may be considered as an effective adjunctive oral hygiene measure for reducing colony counts in children. [ABSTRACT FROM AUTHOR]

Background: Prediction of short stretches in protein sequences capable of forming amyloid-like fibrils is important in understanding the underlying cause of amyloid illnesses thereby aiding in the discovery of sequence-targeted anti-aggregation pharmaceuticals. Due to the constraints of experimental molecular techniques in identifying such motif segments, it is highly desirable to develop computational methods to provide better and affordable in silico predictions. Results: Accurate in silico prediction techniques of amyloidogenic peptide regions rely on the cooperation between informative features and classifier design. In this research article, we propose one such efficient fibril prediction implementation exploiting heterogeneous features based on bio-physio-chemical (BPC) properties, auto-correlation function of carefully selected amino acid indices and atomic composition within a protein fragment of amino acids in a window. In an attempt to get an optimal number of BPC features, an evolutionary Support Vector Machine (SVM) integrating a novel implementation of hybrid Genetic Algorithm termed Memetic Algorithm and SVM is utilized. Five prediction modules designed using Artificial Neural Network (ANN) models are trained with independent and integrated features in order to validate the fibril forming motifs. The results provide evidence that incorporating new feature namely auto-correlation function besides BPC, attempt to strengthen the sequence interaction effect in forming the feature vector thereby obtaining better prediction quality in terms of sensitivity, specificity, Mathews Correlation Coefficient and Area under the Receiver Operating Characteristics curve. Conclusion: A significant improvement in performance is observed by introducing features like auto-correlation function that maintains sequence order effect, in addition to the conventional BPC properties selected through a novel optimization strategy to predict the peptide status - amyloidogenic or non-amyloidogenic. The proposed approach achieves acceptable results, comparable to most online predictors. Besides, it compensates the lacuna in existing amyloid fibril prediction tools by maintaining equilibrium between sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Background: The literature is replete with studies establishing Streptococcus mutans as a major player in the formation of pit and fissure caries in all dentitions. Salivary bacterial levels in turn are related to the number of colonized surfaces. Therefore, decreasing the salivary levels of S. mutans would have a great benefit in decreasing the incidence of dental diseases. Aims: Keeping in mind the potential antimicrobial effects of saturated saline and alum solutions, the present study was attempted to compare and evaluate the effects of saturated saline rinse and 0.02 M alum mouthrinse on salivary S. mutans levels in children. Materials and Methods: The investigation was a double-blind, stratified comparison of three parallel groups of children who used either saturated saline rinse, 0.02 M alum mouthrinse or distilled water (placebo) rinse twice daily under professional supervision for a 21-day period. A total of three saliva samples were taken from each individual - at baseline, on the 10th day and on the 21st day, and colony counts of S. mutans were determined. All data were subjected to statistical analysis using Wilcoxon's Signed Ranks Sum and Mann-Whitney "U" test. Results and Conclusions: Children using saturated saline rinse and alum rinse showed statistically significant reductions in salivary S. mutans counts after 10 days and also after 21 days. After 21 days, the saturated saline rinse and alum rinse groups showed statistically significant differences over the placebo rinse group. Again, the alum rinse group showed a statistically significant difference over the saturated saline rinse group. [ABSTRACT FROM AUTHOR]

Internal Hernias are defined as "The protrusion of viscera through a normal or abnormal opening within the boundaries of the peritoneal cavity" which account for 0.5 - 5.8% of small bowel obstructions while Autopsy incidence is 0.2% to 2%. Hernial defect may be congenital or acquired, the latter being the more common variety. Types: Paraduodenal (53%), Pericaecal (13%), Foramen of Winslow (8%), Intersigmoid (6%), Transmesenteric (8%), Retroanastomotic (1-4%), Supravescical and pelvic (6%).Para duodenal Hernias are the most common internal abdominal hernias accounting for half of reported cases. They are basically congenital in origin representing entrapment of small intestine beneath the mesentery of colon probably occurring due to abnormal embryologic rotation of midgut and variation in peritoneal fixation and vascular folds. Among the paraduodenal hernias left sided hernias predominate, right being less common. We present one such rare case of a congenital, right paraduodenal hernia into the Intermesocolic fossa of Brosike. [ABSTRACT FROM AUTHOR]

Epidermoid cysts are developmental, benign, cutaneous cysts which are commonly found on face followed by trunk and neck. They account for approximately 80% of follicular cysts of the skin. They are slow growing lesions and remain asymptomatic until or unless secondarily infected. They occasionally have tendency to develop into a malignancy. We describe a case of giant epidermoid cyst of posterior part of external ear, a location where very few cases have been reported in the literature. Since cyst was attached to the external ear, esthetics was also one of the important concern apart from the cyst getting infected, as they cause disfigurement of the face. The cyst was excised surgically. Histopathology confirmed the presumptive diagnosis of Epidermoid cyst. Two-years after the resection there was no recurrence. Due to the possibility of the cyst to transform into a malignancy and for appropriate diagnosis, histopathological examination remains a gold standard for confirmatory diagnosis. [ABSTRACT FROM AUTHOR]

This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been withdrawn at the request of the authors, editor and publisher. The publisher regrets that an error occurred which led to the premature publication of this paper. The publisher apologizes to the readers for this unfortunate erro

Chest X-Ray (CXR) images provide most anatomical details and the abnormalities on a 2D plane. Therefore, a 2D view of the 3D anatomy is sometimes sufficient for the initial diagnosis. However, close to fourteen commonly occurring diseases are sometimes difficult to identify by visually inspecting the images. Therefore, there is a drift toward developing computer-aided assistive systems to help radiologists. This paper proposes a deep learning model for the classification and localization of chest diseases by using image-level annotations. The model consists of a modified Resnet50 backbone for extracting feature corpus from the images, a classifier, and a pixel correlation module (PCM). During PCM training, the network is a weight-shared siamese architecture where the first branch applies the affine transform to the image before feeding to the network, while the second applies the same transform to the network output. The method was evaluated on CXR from the clinical center in the ratio of 70:20 for training and testing. The model was developed and tested using the cloud computing platform Google Colaboratory (NVidia Tesla P100 GPU, 16 GB of RAM). A radiologist subjectively validated the results. Our model trained with the configurations mentioned in this paper outperformed benchmark results., Supplementary Information: The online version contains supplementary material available at 10.1007/s13534-022-00249-5., Competing Interests: Conflict of interestNone., (© The Author(s) 2022.)

Purpose: The present study investigates the phytosynthesis of silver nanoparticles (AgNPs) using Perilla frutescens leaf extract, which acts as a reducing agent for the conversion of silver ions (Ag+) into AgNPs. P. frutescens leaf synthesized AgNPs (PF@AgNPs) were evaluated for biomedical properties including antibacterial, antioxidant and anticancer activities., Materials and Methods: PF@AgNPs were synthesized using P. frutescens leaf extract and silver nitrate solution. The morphology and physical properties of PF@AgNPs were studied by spectroscopic techniques including, UV-Vis, FTIR, TEM, XRD, DLS, and TGA. Antibacterial activity of PF@AgNPs was evaluated by disk diffusion assay. Antioxidant activity of PF@AgNPs was checked by 2.2-diphenyl-1-picrylhydrazyl (DPPH), and 2.2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) free radical scavenging assays. Anticancer activity of PF@AgNPs was checked by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay. Cytotoxic effects of PF@AgNPs on most susceptible cancer cell lines were observed by phase contrast microscopy., Results: PF@AgNPs showed surface plasmon resonance peak at 461 nm. XRD pattern showed that the PF@AgNPs were face-centered cubic crystals with a mean size of 25.71 nm. TEM analysis revealed the different shapes (spherical, rhombic, triangle, and rod) of PF@AgNPs. Zeta potential value (-25.83 mV) indicated that PF@AgNPs were long-term stable and not agglomerated. A low polydispersity index value (0.389) indicated the monodispersity of PF@AgNPs. TGA revealed the high thermal stability of PF@AgNPs. PF@AgNPs exhibited maximum inhibition against Escherichia coli , followed by Bacillus subtilis and Staphylococcus aureus . PF@AgNPs showed maximum inhibition of 68.02 and 62.93% against DPPH and ABTS-free radicals, respectively. PF@AgNPs showed significant anticancer activity against human colon cancer (COLO205) and prostate adenocarcinoma (LNCaP). PF@AgNPs exhibited apoptotic effects on LNCaP cells including cell shrinkage, membrane blebbing, chromatin condensation, fragmentation of nuclei, and formation of apoptotic bodies., Conclusion: The present study reports the successful synthesis of PF@AgNPs using P. frutescens leaf extract. The synthesized PF@AgNPs are FCC crystals, monodispersed, long-term stable, and non-agglomerated. The observed antibacterial, antioxidant, and anticancer activities demonstrate the potential biomedical applications of PF@AgNPs., Competing Interests: All the authors report no conflicts of interest in this work., (© 2021 Reddy et al.)

A library of 1-benzyl-N-(2-(phenylamino)pyridin-3-yl)-1H-1,2,3-triazole-4-carboxamides (7a-al) have been designed, synthesized and screened for their anti-proliferative activity against some selected human cancer cell lines namely DU-145, A-549, MCF-7 and HeLa. Most of them have shown promising cytotoxicity against lung cancer cell line (A549), amongst them 7f was found to be the most potent anti-proliferative congener. Furthermore, 7f exhibited comparable tubulin polymerization inhibition (IC 50 value 2.04 µM) to the standard E7010 (IC 50 value 2.15 µM). Moreover, flow cytometric analysis revealed that this compound induced apoptosis via cell cycle arrest at G 2 /M phase in A549 cells. Induction of apoptosis was further observed by examining the mitochondrial membrane potential and was also confirmed by Hoechst staining as well as Annexin V-FITC assays. Furthermore, molecular docking studies indicated that compound 7f binds to the colchicine binding site of the β-tubulin. Thus, 7f exhibits anti-proliferative properties by inhibiting the tubulin polymerization through the binding at the colchicine active site and by induction of apoptosis., (Copyright © 2018 Elsevier Inc. All rights reserved.)

A series of imidazopyridinyl-1,3,4-oxadiazole conjugates were synthesized and investigated for their cytotoxic activity and some compounds showed promising cytotoxic activity. Compound 8q (NSC: 763639) exhibited notable growth inhibition that satisfies threshold criteria at single dose (10μM) on all human cancer cell lines. This compound was further evaluated at five dose levels (0.01, 0.1, 1, 10 and 100μM) to obtain GI 50 values ranging from 1.30 to 5.64μM. Flow cytometric analysis revealed that compound 8q arrests the A549 cells in sub G1 phase followed by induction of apoptosis which was further confirmed by Annexin-V-FITC, Hoechst nuclear staining, caspase 3 activation, measurement of mitochondrial membrane potential and ROS generation. Topo II mediated DNA relaxation assay results showed that conjugate 8q could significantly inhibit the activity of topo II. Moreover, molecular docking studies also indicated binding to the topoisomerase enzyme (PDBID 1ZXN)., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The PI3K/Akt/mTOR signaling pathway plays a key regulatory function in cell survival, proliferation, migration, metabolism and apoptosis. Aberrant activation of the PI3K/Akt/mTOR pathway is found in many types of cancer and thus plays a major role in breast cancer cell proliferation. In our previous studies, benzo[b]furan derivatives were evaluated for their anticancer activity and the lead compounds identified were 26 and 36. These observations prompted us to investigate the molecular mechanism and apoptotic pathway of these lead molecules against breast cancer cells. Benzo[b]furan derivatives (26 and 36) were evaluated for their antiproliferative activity against human breast cancer cell lines MCF-7 and MDA MB-231. These compounds (26 and 36) have shown potent efficiency against breast cancer cells (MCF-7) with IC50 values 0.057 and 0.051μM respectively. Cell cycle analysis revealed that these compounds induced cell cycle arrest at G2/M phase in MCF-7 cells. Western blot analysis revealed that these compounds inhibit the PI3K/Akt/mTOR signaling pathway and induced mitochondrial mediated apoptosis in human breast cancer cells (MCF-7)., (Copyright © 2016 Elsevier Inc. All rights reserved.)