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The Berberidaceae family member Daruharidra has been utilized for the treatment of a variety of ailments. Although the presence of flavonoids, glucosides, phenols, and other compounds has been suggested to be responsible for the medicinal effects of this plant, the molecular components of this plant have not yet been investigated. This investigation tries to evaluate the anti-diabetic properties of the ethanolic extract of this plant. The presence of the alpha-glucosidase inhibitory effect and antioxidant potential in the extracts of Daruharidra (Berberis aristata) was assessed by in vitro assays, including enzyme kinetics studies, assay of % glucose uptake by yeast cells, and superoxide dismutase activity. The results revealed that the extracts enhance the absorption of glucose through the plasma membrane of yeast cells. According to enzyme kinetics, the ethanolic extract had an IC50 value of 17.138 mg ml−1. The type of inhibition as concluded from the double reciprocal plot was found to be competitive. HRLCMS screening of the ethanolic extract was employed to identify leads present in the plant extract and upon analysis major hits were alkaloids in nature. These hits were shortlisted and taken forward for in silico assessment. Docking of the alpha-glucosidase enzyme with HRLCMS hits revealed pirenzepine, platyphylline, dihydroartemisinin, berbamine, and desmethylnefopam against acarbose having excellent binding energies of −9.40, −7.73, −8.11, −7.65, −7.74 and −4.76, respectively. A molecular dynamics simulation was performed for 100 ns. [ABSTRACT FROM AUTHOR]

Introduction: Negative Pressure Wound Therapy (NPWT) is a well-established method to promote wound healing by delivering negative pressure (a vacuum) at the wound site. Enhancement of NPWT techniques may allow an innovative way of treating trauma and orthopaedic wounds which provide unique challenges. We explore the role of negative pressure wound therapy with instillation and dwell time (NPWTi-d-) in the management of trauma and orthopaedic wounds. Materials and Methods: A comprehensive search strategy was conducted using databases of PubMed, Web of Science, Google Scholar, and Cochrane Library with the search words of 'NPWTid' or 'NPWTi-d-' or 'NPWT with instillation' or 'Negative pressure wound treatment with instillation' to generate this narrative review. The mechanism of action of NPWTi-d-, installation solutions and current applications in the trauma and orthopaedic wounds is evaluated. Results: NPWTi-d- provides additional mechanism to promote wound healing in a spectrum of acute and chronic orthopaedic wounds. The technique allows local delivery of hydration and elution of antibiotics to support growth of healthy granulation tissue. Various mechanism of actions contribute in drawing the wound edges together, reduce oedema, help decontamination, deliver local antibiotic and promote healing. Conclusion: NPWTi-d- permits an enhanced, supplementary technique to encourage wound healing in challenging traumatic and orthopaedic wounds. Future applications of NPWTi-d- will depend on cost-effectiveness analysis and development of its application guidelines based on longitudinal, randomized controlled research trials. [ABSTRACT FROM AUTHOR]

Facial expression recognition (FER) in the wild is an active and challenging field of research. A system for automatic FER finds use in a wide range of applications related to advanced human–computer interaction (HCI), human–robot interaction (HRI), human behavioral analysis, gaming and entertainment, etc. Since their inception, convolutional neural networks (CNNs) have attained state‐of‐the‐art accuracy in the facial analysis task. However, recognizing facial expressions in the wild with high confidence running on a low‐cost embedded device remains challenging. To this end, this study presents an efficient dual‐channel ensembled deep CNN (DCE‐DCNN) for FER in the wild. Initially, two DCNNs, namely the DCNNG$$ {\mathrm{DCNN}}_G $$ and DCNNS$$ {\mathrm{DCNN}}_S $$, are trained separately on the grayscale and Scharr‐convolved vertical gradient facial images, respectively. The proposed network later integrates the two pre‐trained DCNNs to obtain the dual‐channel integrated DCNN (DCI‐DCNN). Finally, all three neural networks, namely the DCNNG$$ {\mathrm{DCNN}}_G $$, DCNNS$$ {\mathrm{DCNN}}_S $$, and DCI‐DCNN, are jointly fine‐tuned to get a single dual‐channel‐multi‐output model. The multi‐output model produces three prediction scores for the given input facial image. The prediction scores are thus fused using the max‐voting ensemble scheme to obtain the DCE‐DCNN with the final classification label. On the FER2013, RAF‐DB, NCAER‐S, AffectNet, and CKPlus benchmark FER datasets, the proposed DCE‐DCNN consistently outperforms the two individual DCNNs and numerous state‐of‐the‐art CNNs. Moreover, the network achieves competitive recognition accuracy on all four FER in the wild datasets with reduced memory storage size and parameters. The proposed DCE‐DCNN model with high throughput on resource‐limited embedded devices is suitable for applications that seek real‐time classification of facial expressions in the wild with high confidence. [ABSTRACT FROM AUTHOR]

Abstract Objective: This systematic review aimed to provide comprehensive details on the α-G inhibitory potential of various bioactive compounds derived from natural sources.Methods: A comprehensive literature search was conducted using various databases and search engines, including Science Direct, Google Scholar, SciFinder, Web of Science, and PubMed until May, 2023.Results and conclusions: The enzyme alpha-glucosidase (α-G) is found in the brush border epithelium of the small intestine and consists of duplicated glycoside hydrolase (GH31) domain. It involves the conversion of disaccharides and oligosaccharides into monosaccharides by acting on alpha (1 → 4) and (1 → 6) linked glucose residue. Once absorbed, glucose enters the bloodstream and elevates postprandial glucose, which is associated with the development of type 2 Diabetes (T2D). Epidemic obesity, cardiovascular disease, and nephropathy are linked to T2D. Traditional medicinal plants with α-G inhibitory potential are commonly used to treat T2D due to the adverse effects of currently used α-G inhibitors miglitol, acarbose, and voglibose. Various bioactive compounds derived from natural sources, including lupenone, Wilforlide A, Baicalein, Betulinic acid, Ursolic acid, Oleanolic acid, Katononic acid, Carnosol, Hypericin, Astilbin, lupeol, betulonic acid, Fagomine, Lactucaxanthin, Erythritol, GP90-1B, Procyanidins, Galangin, and vomifoliol retain α-G inhibitory potential for regulating hyperglycaemia. [ABSTRACT FROM AUTHOR]

EGFR (epidermal growth factor receptor), a surface protein on the cell, belongs to the tyrosine kinase family, responsible for cell growth and proliferation. Overexpression or mutation in the EGFR gene leads to various types of cancer, i.e., non-small cell lung cancer, breast, and pancreatic cancer. Bioactive molecules identified in this genre were also an essential source of encouragement for researchers who accomplished the design and synthesis of novel compounds with anticancer properties. World Health Organization (WHO) report states that antibiotic resistance is one of the most severe risks to global well-being, food safety, and development. The world needs to take steps to lessen this danger, such as developing new antibiotics and regulating their use. In this study, 6524 compounds derived from Streptomyces sp. were subjected to drug-likeness filters, molecular docking, and molecular dynamic simulation for 1000 ns to find new triple mutant EGFRCSTMLR (EGFR-L858R/T790M/C797S) inhibitors. Docking outcomes revealed that five compounds showed better binding affinity (− 9.074 to − 9.3 kcal/mol) than both reference drug CH7233163 (− 6.11 kcal/mol) and co-crystallized ligand Osimertinib (− 8.07 kcal/mol). Further, molecular dynamic simulation confirmed that ligand C_42 exhibited the best interaction at the active site of EGFR protein and comprised a better average radius of gyration (3.87 Å) and average SASA (Solvent Accessible Surface Area) (82.91 Å2) value than co-crystallized ligand (4.49 Å, 222.38 Å2). Additionally, its average RMSD (Root Mean Square Deviation) (3.25 Å) and RMSF (Root Mean Square Fluctuation) (1.54 Å) values were highly similar to co-crystallized ligand (3.07 Å, 1.54 Å). Compared to the reference ligand, it also demonstrated conserved H-bond interactions with the residues MET_793 and GLN_791 with strong interaction probability. In conclusion, we have found a potential drug with no violation of the rule of three, Lipinski's rule of five, and 26 other vital parameters having great potential in medicinal and pharmaceutical industries applications and can overcome synthetic drug issues. [ABSTRACT FROM AUTHOR]

Systems for automatic facial expression recognition (FER) have an enormous need in advanced human-computer interaction (HCI) and human-robot interaction (HRI) applications. Over the years, researchers developed many handcrafted feature descriptors for the FER task. These descriptors delivered good accuracy on publicly available FER benchmark datasets. However, these descriptors generate high dimensional features that increase the computational time of the classifiers. Also, a significant proportion of the features are irrelevant and do not provide additional information for facial expression analysis. Adversely, these redundant features degrade the classification accuracy of the FER algorithm. This study presents an alternate, simple, and efficient scheme for FER in static images using the Boosted Histogram of Oriented Gradient (BHOG) descriptor. The proposed BHOG descriptor employs the AdaBoost feature selection algorithm to select important facial features from the original high-dimensional Histogram of Oriented Gradient (HOG) features. The BHOG descriptor with a reduced feature dimension decreases the computational cost without diminishing the recognition accuracy. The proposed FER pipeline tuned on the optimal values of different hyperparameters achieves competitive recognition accuracy on five benchmark FER datasets, namely CK+, JAFFE, RaFD, TFE, and RAF-DB. Also, the cross-dataset experiments confirm the superior generalization performance of the proposed FER pipeline. Finally, the comparative analysis results with existing FER techniques revealed the effectiveness of the pipeline. The proposed FER scheme is computationally efficient and classifies facial expressions in real time. [ABSTRACT FROM AUTHOR]

Introduction: Modern autonomic function tests can assess the degree and spread of autonomic dysfunction non invasively. Cardiovagal, pseudomotor and adrenergic autonomic functions could be assessed in standard laboratory tests. Cardiorespiratory Fitness (CRF) also known as aerobic fitness or maximal aerobic power is typically reported as VO2 max. Aim: To find the relationship between autonomic functional status and maximal aerobic capacity (VO2 max). Materials and Methods: This observational study was conducted in the Research laboratory of Department of Physiology at RUHS College of Medical Sciences, Jaipur Rajasthan, India, from December 2020 to May 2021. The study included 100 apparently healthy students between 18-25 years of age and not practicing any form of exhaustive physical training (cycling, aerobic, skating, scuba diving, professional sports, track and field, water jogging, walking at 5 mph, competitive gymnasium). Autonomic functional status was assessed by various parasympathetic and sympathetic tests. VO2 max was assessed by treadmill test using Graded exercise protocol. To found a correlation between VO2 max and autonomic function test parameters, Pearson’s Pearson correlation test was done. Results: The subjects had a mean age of 21.03±2.45 years, mean height of 1.64±0.08 m, mean weight of 59.66±11.15 kg and mean Body Mass Index (BMI) of 22.08±3.75 kg/m² . Mean height was 1.69±0.06 metre for male subjects and 1.58±0.06 metre for female subjects; mean weight was 62.52±9.52 kg for male subjects and 56.80±11.64 kg for female subjects. Mean BMI was 21.57±3.06 kg/m² for male subjects and 22.59±4.3 kg/ m² for female subjects. Weak positive correlations were found between VO2 max and autonomic function test parameters, such as Valsalva ratio and hand grip blood pressure response, whereas weak negative correlations were found between VO2 max and Expiration/Inspiration (E/I) ratio ratio. VO2 max had a weak positive association (r-value=0.024) with Valsalva ratio and Blood pressure response to hand grip test (r-value=0.111), but a weak negative correlation (r-value=-0.019) with E/I ratio in males. Conclusion: Regular aerobic exercise appears to be associated with decrease in sympathetic responses and increase in parasympathetic responses. The present study indicated the existence of gender differences in autonomic function tests in young adults of 18-25 years of age due to difference. [ABSTRACT FROM AUTHOR]

Anticancer therapy targets Tyrosine kinase (TK) to inhibit signal transduction pathway that regulate various physiological and biochemical processes. Mutation in and around the catalytic domain may lead to conformational changes and activity. The first identified mutation leading to resistance against tyrosine kinase inhibitor (TKI) was observed when Thr at 790 replaced to Met in Epidermal Growth Factor Receptor (EGFR). Third generation EGFR-TKIs bind irreversibly to the Cysteine 797, (ATP-binding pocket). Mutation of Cys 797 to Ser residue (EGFRC797S) causes resistance to third generation TKI. The present study explores allosteric inhibitor of EGFRT790M+C797S mutant TK by molecular modelling techniques using 3,92,945 compounds of Zinc database. Molecular docking study revealed that ZINC000072404720 have similar binding pattern and MM/GBSA free energy as known allosteric inhibitor EAI045. RMSD of EGFRT790M+C797S bound to EAI045 and ZINC000072404720 were quite similar and in acceptable range. Hydrogen bonds after 150ns simulation was observed between Lys 745 and Asp 855 with EAI045 and novel inhibitor showed hydrogen bonding with Lys 745, Leu 788, Thr 854, Asp 855, Phe 856. MM/GBSA free energy was better (-84.09 Kcal/mol) known inhibitor EAI045b (-65.95 Kcal/mol). ZINC000072404720 fulfils drug likeliness property and did not violate Lipinski's rule of five. [ABSTRACT FROM AUTHOR]

Globally, human falls are the second leading cause of deaths induced due to unintentional injuries. These fatalities, in most cases, arise due to a lack of timely medication. Therefore, over the years, there has been an immense demand for systems that can quickly send fall-related information to the caretakers so that the medical relief team can reach on time. The traditional schemes for fall detection using wearable sensors such as accelerometers, gyroscopes, etc., are highly intrusive and generate high false positives in real-world conditions. Consequently, the current research directions in this domain have been toward harnessing the availability of low-cost vision sensors and the power of deep learning. To this end, in this work, we present a dual-stream fused neural network (DSFNN) for fall detection in multi-camera and 360 ∘ video streams. The DSFNN model learns to extract spatial-temporal information using two neural networks, trained independently on the RGB video sequences of fall and non-fall activities and their corresponding single dynamic images. Once trained, the model fuses the prediction scores of the two neural networks using a weighted fusion scheme to obtain the final decision. We assessed the performance of the proposed DSFNN on two multi-camera fall datasets, namely UP-Fall and URFD, and on a new in-house 360 ∘ video dataset of fall and non-fall activities. The evaluation results in terms of different performance metrics demonstrated the superiority of the proposed fall detection scheme. The framework achieved superior performance and outperformed the previous state-of-the-art fall detection methods. For further research and analysis in the fall detection domain, we will make the source code and the in-house fall dataset available to the research community on request. [ABSTRACT FROM AUTHOR]

The EGFR is a clinically important therapeutic drug target in lung cancer. The first‐generation tyrosine kinase inhibitors used in clinics are effective against L858R‐mutated EGFR. However, relapse of the disease due to the presence of resistant mutation (T790M) makes these inhibitors ineffective. This has necessitated the need to identify new potent EGFR inhibitors against the resistant double mutants. Therefore, various machine learning techniques ((instance‐based learner (IBK), naïve Bayesian (NB), sequential minimal optimization (SMO), and random forest (RF)) were employed to develop twelve classification models on three different datasets (high, moderate, and weakly active inhibitors). The models were validated using fivefold cross‐validation and independent validation datasets. It was observed that the random forest‐based models showed best performance. Also, functional groups, PubChem fingerprints, and substructure of highly active inhibitors were compared to inactive to identify structural features which are important for activity. To promote open‐source drug discovery, a tool has been developed, which incorporates the best performing models and allows users to predict the potential of chemical molecules as anti‐TMLR inhibitor. It is expected that the machine learning classification models developed in this study will pave way for identifying novel inhibitors against the resistant EGFR double mutants. [ABSTRACT FROM AUTHOR]

[Display omitted] • Tinospora cordifolia (Giloy) stems extract was employed to synthesize TiO 2 NPs. • Synthesized nanoparticles exhibited broad-spectrum antibacterial activity. • The optical energy band gap of synthesized TiO 2 was 3.13 eV. • TiO 2 NPs exhibited various zone of inhibition against E. coli. • A maximum of 94.43% photocatalytic degradation of Acid Blue 113 dye occurred in 80 min. Green synthesis is a straightforward, non-toxic, cost-effective and eco-friendly method of synthesising nanoparticles. The present study used Tinospora cordifolia plant stem extract to synthesise Titanium (IV) Dioxide nanoparticles (TiO 2 NPs). The plant extract had characterized using Fourier transform infrared spectroscopy (FTIR). Obtained NPs were characterized using scanning electron microscopy (SEM), FTIR and X-ray diffraction (XRD). The XRD pattern demonstrated the anatase phase formation and the existence of nano-crystalline TiO 2 with an average crystallite size of 15.02 nm. The optical characteristics of NPs had identified by UV–Visible Spectroscopy. SEM study revealed that the synthesised nanoparticle was triangular-shaped and the average size of the synthesised NPs was in the range of nanometers. The optical energy band gap of synthesised TiO 2 was 3.13 eV. The average hydrodynamic radius and zeta potential of synthesised TiO 2 NPs were 153.4 nm and −28.4 mV, respectively. Acid Blue 113 was photo-catalytically degraded through green synthesised TiO 2 NPs. Under optimum operating conditions, 94.43% AB 113 degradation occurred in 80 min. The degradation reaction follows pseudo-first-order reaction kinetics having a reaction rate constant value of 0.03362 min−1. The zone of inhibition exhibited by TiO 2 NPs was 13 ± 0.39 and 26.5 ± 0.79 mm corresponding concentrations of 150 and 500 µg/mL, respectively. [ABSTRACT FROM AUTHOR]

Non-steroidal anti-inflammatory drugs (NSAIDs) play an effective chemopreventive action against a variety of cancers. The present study aimed at targeting pro-inflammatory cyclooxygenase (COX) and NF-kB mediated inflammatory pathways in 9,10-dimethylbenzanthracene (DMBA) induced lung cancer in BALB/C mice and chemoprotective action of NSAIDs. Animals were divided into five groups and treated with NSAIDs, intratracheally, daily for a period of 18 weeks. Group 1 as control, received vehicle treatment; Group 2 received single dose of DMBA (10 mg/kg bw); Group 3, 4 and 5 besides DMBA treatment, also received Aspirin (60 mg/kg bw), Celecoxib (6.0 mg/kg bw) and Etoricoxib (0.6 mg/kg bw), respectively. DMBA induce DNA damage, apoptosis and expression of COX-1, COX-2 and NF-kB using immunofluorescence and blot analysis were done. The present study demonstrated the formation of micronuclei, over-expression of COX-2 and NF-kB in DMBA induced lung tumorigenesis and thereby suggesting a marked role of inflammation in the tumour progression. Results indicate the formation of micronuclei in DMBA group, which were significantly reduced in aspirin treated group, and totally absent in the celecoxib and etoricoxib groups. In conclusion, co-administration of etoricoxib and celecoxib has significantly reduced the inflammatory potential of the growing neoplasm in DMBA induced lung cancer in male BALB/C mice. [ABSTRACT FROM AUTHOR]

The polyphagous insect-pest, Helicoverpa armigera, is a serious threat to a number of economically important crops. Chemical application and/or cultivation of Bt transgenic crops are the two strategies available now for insect-pest management. However, environmental pollution and long-term sustainability are major concerns against these two options. RNAi is now considered as a promising technology to complement Bt to tackle insect-pests menace. In this study, we report host-delivered silencing of HaAce1 gene, encoding the predominant isoform of H. armigera acetylcholinesterase, by an artificial microRNA, HaAce1-amiR1. Arabidopsis pre-miRNA164b was modified by replacing miR164b/miR164b* sequences with HaAce1-amiR1/HaAce1-amiR1* sequences. The recombinant HaAce1-preamiRNA1 was put under the control of CaMV 35S promoter and NOS terminator of plant binary vector pBI121, and the resultant vector cassette was used for tobacco transformation. Two transgenic tobacco lines expressing HaAce1-amiR1 was used for detached leaf insect feeding bioassays. Larval mortality of 25% and adult deformity of 20% were observed in transgenic treated insect group over that control tobacco treated insect group. The reduction in the steady-state level of HaAce1 mRNA was 70–80% in the defective adults compared to control. Our results demonstrate promise for host-delivered amiRNA-mediated silencing of HaAce1 gene for H. armigera management. [ABSTRACT FROM AUTHOR]

This study delved into the exploration of novel antidiabetic medications acquired from natural resources, utilizing the Ayurvedic Rasayana herb Hemidesmus indicus through cutting-edge chemoprofiling and molecular modelling techniques. The methanolic extract of Hemidesmus indicus root exhibited the highest extractive yield (24.70 ± 0.08 %) and contained substantial levels of total phenolic and flavonoid content as 154.15 ± 1.24 mg Gallic Acid Equivalent/g extract and 70.61 ± 0.35 Quercetin Equivalent/g extract respectively. Invitro study revealed the potent inhibitory potential of methanolic extract of the herb against essential carbohydrate hydrolytic enzymes α-amylase (IC 50 = 4.19 ± 0.04 mg/ml) and α-glucosidase (IC 50 = 5.78 ± 0.10 mg/ml). Further, the enzyme kinetic study demonstrated the competitive mode of inhibition of both enzymes. HR-LCMS analysis identified the major phytoconstituents present in the extracts, including Solanocapsine, Cyclovirobuxine C, Lucidine B, Zygadenine, Aspidospermidine, silychristin, 3beta-3-Hydroxy-18-lupen-21-one, Manglupenone, and 19-Noretiocholanolone. Molecular docking, molecular dynamic simulation, and MM/GBSA analysis have proved stable, rigid, compact, and folded form of complexes during the entire 100 ns simulation, illustrating Zygadenine, Solanocapsine, and Cyclovirobuxine C as the superior inhibitors of α-A protein, while Zygadenine, Plumieride, and Phlegmarine exhibited greater inhibitory behaviour towards α-G protein than the FDA-approved drug acarbose. Collectively, our findings indicate that the Hemidesmus indicus could be a promising source of α-A and α-G inhibitors, potentially serving as a lead in order to develop medications for type-2 diabetes. [Display omitted] • Solanocapsine, Cyclovirobuxine C, Zygadenine, and Aspidospermidine are the major alkaloids identified from H. indicus. • Alkaloids possess alpha-amylase and alpha-glucosidase inhibition potential. • Competitive mode of inhibition of these enzymes by root extract of H. indicus. • The antidiabetic potential of H. indicus was investigated for the first time by in-Vitro and in silico approach. [ABSTRACT FROM AUTHOR]

Today is world of communication. We transfer the various types of data using Internet and various types of mobile applications. With this communication, the risk of data privacy also increases. Today there are many techniques that are used for the purpose of data privacy like cryptography, steganography etc. Steganography is also of many types like text, image, video, protocol etc. In this paper, we will compare the various image steganography techniques. [ABSTRACT FROM AUTHOR]

Neuroblastoma develops through processes which include cellular dedifferentiation. Ability of tumors to form spheroids is one of the manifestations of dedifferentiation and carcinogenic transformation. To study mechanisms of dedifferentiation of neuroblastoma cells, we generated spheroids and performed a proteomics study to compare the spheroids with parental SK-N-BE2 cells. We observed that dedifferentiation induced extensive changes in the proteome profiles of the cells, which affected more than 30% of detected cellular proteins. Using mass spectrometry, we identified 239 proteins affected by dedifferentiation into spheroids as compared to the parental cells. These proteins represented such regulatory processes as transcription, cell cycle regulation, apoptosis, cell adhesion, metabolism, intracellular transport, stress response, and angiogenesis. A number of potent regulators of stemness, differentiation and cancer were detected as subnetworks formed by the identified proteins. Our validation tissue microarray study of 30 neuroblastoma cases confirmed that two of the identified proteins, DISC1 and DNA-PKcs, had their expression increased in advanced malignancies. Thus, our report unveiled extensive changes of the cellular proteome upon dedifferentiation of neuroblastoma cells, indicated top subnetworks and clusters of molecular mechanisms involved in dedifferentiation, and provided candidate biomarkers for clinical studies. [ABSTRACT FROM AUTHOR]

Background: The response of cells to TGFβ and EGF is mediated by a network of various intracellular regulators. The signaling crosstalk between different regulators is of key importance for tumorigenesis. The crosstalk may explain the modulation of cellular responses to the same regulator by another signaling molecule. As PKN1 - a serine/threonine kinase implicated in tumorigenesis - was identified as potential crosstalk node for TGFβ and EGF signaling, the cellular functions that may be affected by PKN1 in a crosstalk of TGFβ and EGF were explored. Methods: To investigate the contribution of PKN1 to TGFβ and EGF signaling, transiently PKN1-transfected HEC-1-A endometrial cancer cells were generated and subjected to treatment with TGFβ1, EGF, and their combination. Proliferation, apoptosis, invasion, wound healing, and migration assays were performed. The impact of PKN1 on the expression and phosphorylation of intracellular proteins was monitored by immunoblotting. Results: It was demonstrated that PKN1 modulated the responses of HEC-A-1 endometrial cancer cells to TGFβ1 and EGF. PKN1 had an inhibitory effect on the stimulation of cell migration, and PKN1 kinase activity was required for the inhibitory effect of TGFβ and EGF on cell proliferation and invasiveness. It was observed that phosphorylation of Smad2, FAK, and Erk1/2 correlated with responses of the cells to TGFβ1 and EGF. Conclusion: PKN1 modulates TGFβ- and EGF-dependent regulation of cell proliferation, migration, and invasiveness, and therefore is a component of the network signaling downstream of TGFβ and EGF. [ABSTRACT FROM AUTHOR]

Man is always obsessed with fair skin since ages. Beauty, it is said, is skin deep. Not so anymore for consumers especially in India who demand from their beauty products more than just a superficial whitening of their skin tone for a short duration. Hydroquinone is the ?rst choice of topical bleaching agents used in treatment of melasma. It is widely prescribed by physicians and often used by patients without prescription. The principal adverse effects of its chronic use are confetti-like depigmentation and exogenous ochronosis. Exogenous ochronosis is an infrequent dermatosis characterized as a dark blue hyperpigmentation localized where the causing agent was applied. It may be caused by the use of systemic medications such as antimalarials and by the use of topical substances such as phenol, resorcinol, benzene, hydroquinone, which is a phenolic compound with depigmenting action. The pathophysiology of this process is not well clear up to this moment, and the therapeutic measures are not satisfactory either. We hereby, reporting a case of 29 years old female who had been using hydroquinone continuously for six years for fairer complexion and ended up with a night mare. [ABSTRACT FROM AUTHOR]

Hypoxia promotes neural stem cell proliferation, the mechanism of which is poorly understood. Here, we have identified the nuclear orphan receptor TLX as a mediator for proliferation and pluripotency of neural progenitors upon hypoxia. We found an enhanced early protein expression of TLX under hypoxia potentiating sustained proliferation of neural progenitors. Moreover, TLX induction upon hypoxia in differentiating conditions leads to proliferation and a stem cell-like phenotype, along with coexpression of neural stem cell markers. Following hypoxia, TLX is recruited to the Oct-3/4 proximal promoter, augmenting the gene transcription and promoting progenitor proliferation and pluripotency. Knockdown of Oct-3/4 significantly reduced TLX-mediated proliferation, highlighting their interdependence in regulating the progenitor pool. Additionally, TLX synergizes with basic FGF to sustain cell viability upon hypoxia, since the knockdown of TLX along with the withdrawal of growth factor results in cell death. This can be attributed to the activation of Akt signaling pathway by TLX, the depletion of which results in reduced proliferation of progenitor cells. Cumulatively, the data presented here demonstrate a new role for TLX in neural stem cell proliferation and pluripotency upon hypoxia. [ABSTRACT FROM AUTHOR]

Early diagnosis of brain tumor using magnetic resonance imaging (MRI) is vital for timely medication and effective treatment. But, most people living in remote areas do not have access to medical experts and diagnosis facilities. Nevertheless, recent advancement in the Internet of Thing and artificial intelligence is transforming the healthcare system and has led to the development of the Internet of Medical Things (IoMT). An automated brain tumor classification system integrated with the IoMT framework can aid in remotely diagnosing brain tumors. However, the existing methods for brain tumor classification in MRI based on traditional machine learning and deep learning are compute-intensive. Deployment of these methods in the real-world clinical setup poses a serious challenge. Therefore, there is a requirement for robust and compute-efficient techniques for brain tumor classification. To this end, this paper presents a novel lightweight attention-guided convolutional neural network (AG-CNN) for brain tumor classification in magnetic resonance (MR) images. The designed architecture uses channel-attention blocks to focus on relevant regions of the image for tumor classification. Besides, AG-CNN uses skip connections via global-average pooling to fuse features from different stages. This approach helps the network extract enhanced features essential to differentiate tumor and normal brain MR images. To access the efficacy of the designed neural network, we evaluated it on four benchmark brain tumor MRI datasets. The comparison results with the existing state-of-the-art methods revealed the robustness and computational efficiency of the proposed AG-CNN model. The designed brain tumor classification pipeline can be easily deployed on a resource-constrained embedded platform and used in real-world clinical settings to quickly classify brain tumors in MR images. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma (BCC) and squamous cell carcinoma are the most common type of nonmelanoma skin cancers (NMSCs). Bowen's disease (BD), a premalignant condition, has a marginal potential (3-5%) to progress to invasive carcinoma. We report here a rarest of a rare case of multiple pigmented BD with overlying squamous cell cancer along with a giant neglected BCC on the scalp of a 76-year-old man. The occurrence of multiple BD and NMSC in a single patient compelled us to explore the following hypothesis: (1) The multiple precancerous and cancerous lesions can be due to common etiopathogenesis. Chronic ultraviolet exposure, immunosupresssion, human papillomavirus infection, dietary factors, and environmental factors including arsenic exposure were probed in to. (2) There is evolution of precancerous lesions into a different type of cancers in different time frame. (3) The new cancerous lesions are subsequent cancers that developed after neglected untreated primary cancer. [ABSTRACT FROM AUTHOR]

Pollination stands out as the paramount ecosystem service facilitated by insect pollinators, providing benefits to over three quarters of the world’s major crops. The conservation and effective management of honeybees constitute integral components for ensuring the sustainable productivity of cross-pollinated crops. The present study aimed to document the potential pollinators of lucerne in the Bundelkhand region in India, which is known for its subtropical climatic conditions. Further, the foraging behaviour, including foraging rate and speed, was meticulously documented. A total of 13 insect species from seven families across three insect orders were observed visiting lucerne flowers. Hymenopterans comprised the majority of the floral visitors (73.48%), followed by Lepidoptera (26.51%) during the study period. Among them, Apis dorsata (Hymenoptera: Apidae) emerged as the most predominant floral visitor, exhibiting peak activity at 12:00 h with a density of 7.85 bees/m2/10 min. Surprisingly, among the major floral visitors, A. florea has the highest mean foraging rate (number of flowers visited/minute/forager), i.e., 11.56, 11.59 and 10.79 bees/flowers/minute during the initial flowering stage, peak flowering stage and late flowering stage, respectively. However, the foraging speed (time spent by the forager on each flower) was longest in A. dorsata, i.e., 5.05, 3.78 and 5.41 s/flower during initial, peak and late flowering stages, respectively. The findings emphasize the importance of enhancing honeybee activity to boost lucerne seed yield. Further, the outcomes of the study can be leveraged to optimize honeybee colony management, scheduling field operations such as pesticide application and weeding during periods of minimal honeybee activity. [ABSTRACT FROM AUTHOR]

In our day-to-day social interactions, non-verbal cues such as facial emotions play a vital role. These cues assist people in understanding and inferring the hidden emotional state of the individuals. However, blind and visually impaired persons (VIPs) sadly lack access to such cues, which results in impaired interpersonal communication. To alleviate the issue, in this research, we present a proof-of-concept (POC) implementation of a deep learning-inspired vision-based low-cost intelligent embedded system for the haptic rendering of facial emotions to the VIPs. To this end, a novel lightweight shallow convolutional neural network (CNN) has been designed, optimized, and implemented on a resource-constrained embedded platform for the real-time analysis of facial emotions in static images. We evaluated the model on five benchmark FER datasets, namely CK+, RaFD, SFEW, FER2013, and RAF. Also, for real-time performance, the trained CNN is optimized using TensorRT SDK and deployed on the Nvidia Jetson TX2 embedded platform. Comparative analysis results with state-of-the-art FER techniques confirm the efficacy of the designed CNN that achieves competitive recognition accuracy and runs in real-time at a frame processing speed of 40 fps on the Jetson TX2 embedded device. Finally, the embedded FER platform is integrated with a low-cost and user-friendly haptic device to render emotions to the VIPs in the form of vibration cues. A working demo of the developed FER system is available at https://youtu.be/c73Ledn27dQ. [ABSTRACT FROM AUTHOR]

Automatic recognition of facial expressions in the wild is a challenging problem and has drawn a lot of attention from the computer vision and pattern recognition community. Since their emergence, the deep learning techniques have proved their efficacy in facial expression recognition (FER) tasks. However, these techniques are parameter intensive, and thus, could not be deployed on resource-constrained embedded platforms for real-world applications. To mitigate these limitations of the deep learning inspired FER systems, in this paper, we present an efficient dual integrated convolution neural network (DICNN) model for the recognition of facial expressions in the wild in real-time, running on an embedded platform. The designed DICNN model with just 1.08M parameters and 5.40 MB memory storage size achieves optimal performance by maintaining a proper balance between recognition accuracy and computational efficiency. We evaluated the DICNN model on four FER benchmark datasets (FER2013, FERPlus, RAF-DB, and CKPlus) using different performance evaluation metrics, namely the recognition accuracy, precision, recall, and F1-score. Finally, to provide a portable solution with high throughput inference, we optimized the designed DICNN model using TensorRT SDK and deployed it on an Nvidia Xavier embedded platform. Comparative analysis results with the other state-of-the-art methods revealed the effectiveness of the designed FER system, which achieved competitive accuracy with multi-fold improvement in the execution speed. [ABSTRACT FROM AUTHOR]

Protective coatings enriched with different types of chemical additives, functional fillers, and nanostructured materials are gaining immense interest to minimize corrosion. The present work demonstrates the synthesis of chemically functionalized reduced graphene oxide (rmGO) and emeraldine salt form of polyaniline (PANI-ES)-based rmGO-PANI-ES nanocomposites as protective functional fillers for epoxy coating to inhibit mild steel corrosion. The oxidative polymerization of aniline into PANI-ES is initiated on nitrogen-rich active sites of rmGO, and it propagates along the basal plane of rmGO, eventually enwrapped the graphene sheets by interfacially grown PANI-ES. The synthesis of rmGO-PANI-ES nanocomposites and their chemical, morphological, crystalline, and structural characteristics are examined by the FTIR, 13C NMR, XPS, XRD, Raman, SEM, and HRTEM analyses. The multiple interactions between the highly polar nitrogen-rich rmGO-PANI-ES nanocomposites and the epoxy matrix strengthened the coating and increased the hardness and elastic modulus. The corrosion inhibition performance of epoxy coating enriched with the rmGO-PANI-ES nanocomposites is probed by electrochemical impedance spectroscopic (EIS) and salt spray tests using an accelerated corrosive environment (3.5 wt% NaCl). The rmGO-PANI-ES-15 nanocomposite having 0.15 wt% rGO in epoxy coating showed superior corrosion inhibition performance. The total electrochemical impedance of epoxy coating (8.7 ×103 Ω.cm2) increased to 4.7 ×1015 Ω.cm2 after incorporating 1 wt% rmGO-PANI-ES-15 nanocomposite. The enhancement of electrochemical impedance by ∼12 orders of magnitude demonstrates the effectiveness of the rmGO-PANI-ES nanocomposites for corrosion mitigation in a harsh corrosive environment. The high surface area and remarkable structural barrier of the 2D chemically functionalized graphene furnished excellent protective coverage. The PANI-ES of rmGO-PANI-ES nanocomposites formed a passive layer of fully reduced leucoemeraldine base of PANI (PANI-LEB) on the coating-mild steel interface by accepting the electrons, generated during the anodic oxidation of iron. These events collectively increase the impedance by multifolds and inhibit steel corrosion. The present findings revealed that graphene-enriched conductive polymeric nanocomposites-based coatings can be promising solution to mitigate corrosion of metal-based installations in a marine environment. [Display omitted] • Graphene-polyaniline (rmGO-PANI-ES) nanocomposites as protective filler to epoxy coating for corrosion inhibition. • Interfacially grown PANI wrapped the chemically-functionalized graphene in these nanocomposites. • rmGO-PANI-ES strengthened the epoxy coating and increased hardness and elastic modulus. • rmGO-PANI-ES in epoxy coating increased the impedance by 12 orders of magnitude under a harsh corrosive environment. [ABSTRACT FROM AUTHOR]

Corrosion, a major concern in many industries, is primarily accountable for high maintenance costs, material degradation, frequent repair/replacement, and poor lifespan of structural installations. Eventually, corrosion can lead to a high risk of catastrophic equipment failures and environmental threats such as leakage from pipelines and chemical containers. Protective coatings enriched with nanostructured fillers that impart enhancement of corrosion inhibition properties are gaining immense interest. In the present work, nanocomposites comprising N-doped graphene (NGr) wrapped by emeraldine salt form of polyaniline (PANI-ES) are developed as highly effective protective functional fillers to epoxy coatings for mild steel corrosion inhibition. The NGr-PANI-ES nanocomposites furnished excellent structural strengthening to epoxy coatings and are able to impede the penetration of corrodents to a significant extent. The corrosion inhibition performance of the NGr-PANI-ES nanocomposites-based epoxy coatings is evaluated by electrochemical impedance spectroscopy and salt spray tests. The nitrogen incorporation into graphene skeleton introduced ample electron-rich nitrogen-based functionalities as revealed by XPS analysis, which synergistically amplified corrosion inhibition performance with PANI-ES. The NGr-PANI-ES nanocomposites in epoxy coatings enhanced the total impedance in a highly aggressive corrosive electrolyte (3.5 % NaCl) by a magnitude of 12 orders, corroborating with excellent corrosion inhibition performance results based on salt spray tests. The improved corrosion inhibition properties are collectively attributed to the structural barrier by 2D N-doped graphene, compatibility of NGr-PANI-ES nanocomposites with epoxy matrix to strengthen the coatings, and the synergistic inhibition of the anodic reactions by PANI-ES and N-doped graphene that underpin the corrosive events. [Display omitted] • Polyaniline-N-doped graphene (NGr-PANI-ES) nanocomposites for steel corrosion inhibition • NGr-PANI-ES furnished excellent strengthening to epoxy coatings to impede corrodent penetration. • NGr-PANI-ES in epoxy coatings increased total impedance by a magnitude of 12 orders. • NGr-PANI-ES-based coatings showed remarkably high corrosion inhibition against salty fog. [ABSTRACT FROM AUTHOR]

Imbalanced use (form, quantity, and ratio) of nitrogen fertilization can result in decreased grain yields and increased nitrogen loss, leading to adverse effects on overall environmental quality. Globally, limited empirical research has been conducted on the comprehensive effects of different levels of N that can significantly influence wheat agronomic and genotypic traits. Therefore, this study aimed to evaluate wheat genotypes for two consecutive years (2020–2021 and 2021–2022) under different N fertilization treatments: N0 (native N, without external application of N), N75 (½ of the recommended dose of N), and N150 (recommended dose of N). The study findings revealed that 'HD 3249' and 'HD 3117' were the top-performing genotypes in terms of grain yield (5.3 t ha−1; 5.0 t ha−1), straw yield (6.9 t ha−1; 6.7 t ha−1), biological yield (12.2 t ha−1; 11.8 t ha−1), and harvest index (42.9%; 42.4%). In particular, the application of N75 and N150 increased grain yields by 142.6% and 61.3%, respectively; straw yields by 72.3%; and by 110.6% over N0. Furthermore, N levels (N75 and 150) significantly increased the higher concentration of N in grain (23.1% and 33%) and straw (21.1% and 29.8%); N uptake in grain (70.2 and 104.2) and straw (64.8 and 41.5); and total N uptake (68.8% and 101.4%) than N0, respectively. Additionally, correlation analysis revealed that there were positive correlations between yields, harvest index as well as N concentration and uptake. This study identified the two elite genotypes, 'HD 3249' and 'HD 3117', with N150 splits giving a better response, which can be used as selection criteria for developing wheat varieties that are more efficient in using nitrogen, leading to high yields and N uptake. [ABSTRACT FROM AUTHOR]

Optimizing nitrogen (N) inputs is crucial for maximizing wheat yield and ensuring environmental sustainability. Wheat's economic significance in India calls for a comprehensive evaluation of its ecological implications to develop a resilient production system. This study aimed to identify and evaluate ten wheat cultivars for their yield and N-use efficiency under varying nitrogen inputs (control (N0), half of the recommended nitrogen (N75), and the recommended nitrogen (N150)) using the surface application of neem-oil-coated urea. All N inputs were applied in three splits, basal, crown root initiation, and tillering stages, and an experiment was conducted in a split-plot design. The application of N150 gave the highest dry matter accumulation (DMA) at harvesting stage (AHS) (871 g m−2), seed/spike (60), grain yield (GY = 7.4 t ha−1), straw yield (SY = 8.9 t ha−1), harvest index (HI = 45.2%), protein (12.5%), and total uptake of N (TUN) (223 kg ha−1) by the cultivar 'HD 3249', being closely followed by the cultivar 'HD3117'. Six cultivars ('HD 3298', 'HD 3117', 'HD 3249', 'PBW 550', 'HD 3086', 'HD 2967') out of the ten cultivars evaluated responded well to different input treatments with respect to the grain yield efficiency index (GYEI ≥ 1). Regarding N input, N75 and N150 recorded the highest increases in plant height, AHS (16.5%; 21.2%), dry matter accumulation (DMA) at 30 days after sowing (DAS) (37.5%; 64%), DMA-60 DAS (42%; 53%), DMA-90 DAS (39.5%; 52.5%), TILL-30 DAS (19.8%; 26.4%), TILL-60 DAS (33.3%; 44%), TILL-90 DAS (37.2%; 47.2%), seed/spike (8%; 10%), 1000-grain weight (7.8%; 12.2%), and protein content (23.3%; and 33%) when compared with N0. Furthermore, the application of N75 and N150 improved GY (72.1%; 142.6%), SY (61.1%; 110.6%), BY (65.5%; 123%), and HI by 4.4% and 9%, respectively, over N0. Nitrogen addition (N75 and N150) also significantly increased total nitrogen uptake (104.7%; 205.6%), respectively, compared to N0. The correlation analysis revealed a positive association among most of the crop parameters. Overall, our research results suggest that the cultivars 'HD 3249' and 'HD 3117' have the potential to be effective options for improving N utilization efficiency, grain yield, and GYEI in North-West India. [ABSTRACT FROM AUTHOR]

The fall armyworm (FAW), Spodoptera frugiperda is a ruinous insect pest, native to tropical and subtropical regions of western hemisphere. It has recently invaded Indian subcontinent during 2018, causing severe damage to crops of several genera of many plant families. The incidence of FAW infestation ranged from 12% to 74%, indicating its establishment in central India where it poses an immediate and significant economic threat to crop production. Phylogenetic analysis revealed that Jhansi, Uttar Pradesh isolate is closely related to the isolates of southern states of India. Studies on biology of FAW indicated no variation in biological parameters, when reared on fodder maize and fodder sorghum, however recorded longer larval and pupal duration (16.07 and 10.00 days) when reared on artificial diet. The adults laid more number of eggs under crop mosaic condition with varied phenological crop growth stages and the fodder maize (782.33 eggs) was most preferred for oviposition. A total of five parasitoids were recovered from the field collected larvae and also predation by generalist predator, Eocanthecona furcellata (Wolff) was recorded during the study period. [ABSTRACT FROM AUTHOR]

Reproductive processes in domestic pigs have been studied extensively. Pigs are one of the main sources of meat for human consumption and are an established model for investigations into mammalian, including human, reproductive physiology. Studies of the uterus during early pregnancy will lead to a better understanding of mechanisms governing pregnancy. Proteomics provides the possibility to explore endometrial functions in an unbiased way. The aim of the study was to compare endometrium harvested from Days 12-13 and 15-16 of pregnancy with the corresponding days of the oestrous cycle. We identified endometrial proteins that are unique to the early stages of pregnancy (Days 12-13 and 15-16). Twenty-one proteins were identified that were uniquely expressed on the selected days of pregnancy or the oestrous cycle. Out of 21 identified proteins, 14 referred to the pregnancy periods. Systemic analysis of the identified proteins revealed cell adhesion and cytoskeletal organisation as two of the major functions, both of which are important for the establishment and maintenance of pregnancy. Thrombospondin 1 expression was validated using western blotting analysis and the results suggest its involvement in the adhesiveness of the embryo during the peri-implantation period in pigs. [ABSTRACT FROM AUTHOR]

The emerging threat of climate change is posing a scientific conundrum for global food and nutritional security. As a primary staple food, half of the global human population is supported by rice crop. Thus, enhancing rice yield is highly critical to ensure food security. Photosynthesis is the defining physiological process of plants that determines maximum attainable yield. Efficiently capturing solar radiation and converting the carbon assimilates into rice grain is critical to achieve high yield. Genetic interventions to modify the plant architecture for enhanced light capture can improve rice yield significantly. Enhancement of cellular photosynthesis by synthetic biology approaches targeting important nodes of the light harvesting and carbon assimilation pathways are critical for breaking yield ceiling. The possible targets for improving photosynthesis include the light capture, chloroplast electron transport, Calvin cycle enzymes, sugar transport mechanisms, minimization of photorespiration, and improving source–sink relations. Conversion of C3 rice into a C4 type plant is also an option being vigorously pursued. Here, we review the determinants of canopy photosynthesis in rice with special reference to genetic factors and cellular photosynthetic capacity. [ABSTRACT FROM AUTHOR]

In this study, we used proteomics and biological network analysis to evaluate the potential biological processes and components present in the identified proteins of biopsies from cutaneous leishmaniasis (CL) patients infected by Leishmania braziliensis in comparison with normal skin. We identified 59 proteins differently expressed in samples from infected and normal skin. Biological network analysis employing identified proteins showed the presence of networks that may be involved in the cell death mediated by cytotoxic T lymphocytes. After immunohistochemical analyses, the expression of caspase-9, caspase-3, and granzyme B was validated in the tissue and positively correlated with the lesion size in CL patients. In conclusion, this work identified differentially expressed proteins in the inflammatory site of CL, revealed enhanced expression of caspase-9, and highlighted mechanisms associated with the progression of tissue damage observed in lesions. [ABSTRACT FROM AUTHOR]

A new resource efficient FPGA-based hardware architecture for real-time edge detection using Sobel operator for video surveillance applications has been proposed. The choice of Sobel operator is due to its property to counteract the noise sensitivity of the simple gradient operator. FPGA is chosen for this implementation due to its flexibility to provide the possibility to perform algorithmic changes in later stage of the system development and its capability to provide real-time performance, hard to achieve with general purpose processor or digital signal processor, while limiting the extensive design work, time and cost required for application specific integrated circuit. The proposed architecture uses single processing element for both horizontal and vertical gradient computation for Sobel operator and utilised approximately 38% less FPGA resources as compared to standard Sobel edge detection architecture while maintaining real-time frame rates for high definition videos (1920 × 1080 image sizes). The complete system is implemented on Xilinx ML510 (Virtex-5 FX130T) FPGA board. [ABSTRACT FROM AUTHOR]

Introduction: Para adnexal cysts (paraovarian and paratubal) constitutes a homogenous group of cystic lesions originating from mesosalphinx or broad ligament, located in proximity of the fallopian tube and ovary. As with the lesions of the adnexa, paraovarian and paratubal cysts can be neoplastic but are often misinterpreted as true functional cysts. A correct radiological and clinical diagnosis would be useful in order to render necessary treatment. Aim: To highlight the histomorphologic spectrum of the paraadnexal cysts and correlate with clinical findings. Materials and Methods: The present study was a descriptive study conducted in the Department of Pathology, Rajarajeswari Medical College, Bengaluru, Karnataka, India over a period of two years six months. All specimens including salpingoophorectomy specimens which harboured paratubal or paraovarain cysts, or paratubal/paraovarian cysts diagnosed on radiology and resected and sent separately for histopathologic evaluation were sampled and included in the study. All surgically and radiologically proven paratubal and paraovarian cystic lesions were included and solid lesions were excluded. The results were analysed using descriptive statistics. Results: The mean age of diagnoses was 40.1 years and menstrual abnormalities was the most common presentation. Of the Neoplastic cysts, paraovarian cysts (78.6%) were more common than paratubal cysts (21.4%). About 75.4 % were non neoplastic cysts and 24.6% were neoplastic. Conclusion: Para adnexal cysts are often misdiagnosed or not sampled as they are thought of as functional cysts. Present study analysed 114 cases and found that 28 of the cases showed neoplastic cysts, one of them showing a serous borderline tumour, which have the potential to turn malignant. Hence, histopathologic evaluation of these lesions would help in understanding the different histological types that would arise in para adnexal sites which in turn helps in better management of these patients. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review and a comparative study of various hardware/FPGA implementations of Sobel edge detector and explored different architectures for Sobel gradient computation unit in order to show the various trade-offs involved in choosing one over another. The different architectures using pipelining and/or parallelism (key methodologies for improving the performance/frame rates) are explored for gradient computation unit in Sobel edge detector. How the different architectures affected performance (in terms of video frame rate and image size) and area (in terms of FPGA resources usages) has been demonstrated. By exploiting the trade-offs between video frame rate, image size, and FPGA resources a designer should be able to find an optimal architecture for a given application. [ABSTRACT FROM AUTHOR]

Berseem (Trifolium alexandrinum L.) is one of the important legume fodder crops. It is widely grown in Central and Northern parts of India during winter season. Disease symptoms resembling to collar rot was observed in the breeder seed production and research fields of berseem at ICAR-IGFRI, Jhansi, Uttar Pradesh, India in March 2019 and April 2020. Disease incidence was ranged from 15–20% and 20-25% in 2019 and 2020, respectively. Disease symptom appeared as water soaked lesions on surface of collar region followed by the development of rotten areas with white mycelial mass and finally plants were dried. The associated pathogen was isolated and identified as Sclerotium rolfsii (Teleomorph: Athelia rolfsii) on the basis of morphological characters and sequence analysis of ITS, LSU and SSU regions of rDNA. Artificial inoculation of pathogen revealed cent per cent disease incidence and wilting of plants. To best of our knowledge, this is first complete report on etiology of collar rot disease caused by Sclerotium rolfsii on berseem in India. [ABSTRACT FROM AUTHOR]

This article attempts to understand the evolution of groundwater chemistry in the mid Gangetic floodplain through the identification of hydrogeochemical processes including the impact of surface recharge and geological features. Isotopic investigations identified that irrigation return flow is partly responsible for arsenic (As) enrichment through preferential vertical recharge. Further, the floodplain geomorphological attributes and associated As hydrogeochemical behaviour traced through isotopes tracers highlighted that meandering and ox-bow like geomorphological features owing to clay deposition leads to the anoxic condition induced reductive microbial dissolution of As-bearing minerals causing the arsenic contamination in the investigated aquifer of the mid-Gangetic plain (MGP). To achieve the objectives, 146 water samples for water chemistry and 62 samples for the isotopic study were collected from Bhojpur district, Bihar (district bounded by the river Ganges in the north and Son in the east) located in MGP during the pre-monsoon season of 2018. The chemical results revealed high arsenic concentration (BDL to 206 μg.L−1, 32% samples are exceeding the 10 μg.L−1 limit) in the Holocene recent alluviums which are characterized by various geomorphological features such as meander scars and oxbow lake (northern part of the district). Arsenic is more concentrated in the depth range of 15–40 m below ground surface. All other trace metals viz. Ni, Pb, Zn, Cd and Al were found in low concentration except Fe and Mn. The geochemical analyses suggest that rock-water interaction is controlling the hydro-geochemistry while the chemical constituent of the groundwater is mainly controlled by carbonate weathering with limited contribution from silicate weathering. The isotopic signatures revealed that the Son river is recharging groundwater while the groundwater is contributing to the Ganges river. A clear pattern of fast vertical recharge in the arsenic contaminated area is observed in the proximity to the river Ganges with an elevated nitrate concentration resulted from the reduced As dissolution. The origin of groundwater is local precipitation with low to high evaporation enrichment effect which is further indicating the vertical mixing of groundwater from the irrigation return flow and/or recharge from domestic discharge causing enhanced As mobilization through microbial assisted reductive dissolution of As-bearing minerals. • Landscapes like meander scars and oxbow lake enhances the As occurrence in the Holocene Alluvium. • Groundwater evolution is precipitation dependent with low to high evaporation enrichment effect. • δ18O plot illustrated an explicit fast vertical recharge pattern in the As contaminated area. • Vertical mixing with irrigation return flow/sewage governs the As enrichment and mobilization. • Organic carbon enriched clay deposition in the floodplain triggers microbial dissolution of Asminerals. [ABSTRACT FROM AUTHOR]

Existing techniques for Yoga pose recognition build classifiers based on sophisticated handcrafted features computed from the raw inputs captured in a controlled environment. These techniques often fail in complex real-world situations and thus, pose limitations on the practical applicability of existing Yoga pose recognition systems. This paper presents an alternative computationally efficient approach for Yoga pose recognition in complex real-world environments using deep learning. To this end, a Yoga pose dataset was created with the participation of 27 individual (8 males and 19 females), which consists of ten Yoga poses, namely Malasana, Ananda Balasana, Janu Sirsasana, Anjaneyasana, Tadasana, Kumbhakasana, Hasta Uttanasana, Paschimottanasana, Uttanasana, and Dandasana. To capture the videos, we used smartphone cameras having 4 K resolution and 30 fps frame rate. For the recognition of Yoga poses in real time, a three-dimensional convolutional neural network (3D CNN) architecture is designed and implemented. The designed architecture is a modified version of the C3D architecture initially introduced for the recognition of human actions. In the proposed modified C3D architecture, the computationally intensive fully connected layers are pruned, and supplementary layers such as the batch normalization and average pooling were introduced for computational efficiency. To the best of our knowledge, this is among the first studies, which utilized the inherent spatial–temporal relationship among Yoga poses for their recognition. The designed 3D CNN architecture achieved test recognition accuracy of 91.15% on the in-house prepared Yoga pose dataset consisting of ten Yoga poses. Furthermore, on the publicly available dataset, the designed architecture achieved competitive test recognition accuracy of 99.39%, along with multifold improvement in the execution speed compared to the existing state-of-the-art technique. To promote further study, we will make the in-house created Yoga pose dataset publicly available to the research community. [ABSTRACT FROM AUTHOR]

Due to the increasing demand for high-quality and high fiber-yielding cotton (Gossypium spp.), research into the development of stress-resilient cotton cultivars has acquired greater significance. Various biotic and abiotic stressors greatly affect cotton production and productivity, posing challenges to the future of the textile industry. Moreover, the content and quality of cottonseed oil can also potentially be influenced by future environmental conditions. Apart from conventional methods, genetic engineering has emerged as a potential tool to improve cotton fiber quality and productivity. Identification and modification of genome sequences and the expression levels of yield-related genes using genetic engineering approaches have enabled to increase both the quality and yields of cotton fiber and cottonseed oil. Herein, we evaluate the significance and molecular mechanisms associated with the regulation of cotton agronomic traits under both normal and stressful environmental conditions. In addition, the importance of gossypol, a toxic phenolic compound in cottonseed that can limit consumption by animals and humans, is reviewed and discussed. • Biotic and abiotic stress have a significant impact on cotton yield and productivity. • Gossypol is a poisonous phenolic chemical and cottonseed anti-nutrient. • Genetic engineering has helped increase cotton fiber and cottonseed oil quality and yields by identifying and modifying gene sequences and expression levels. • Research done to date on ways to lower gossypol levels in cotton seeds are summarized. [ABSTRACT FROM AUTHOR]

Groundwater is an important source for drinking and irrigation purposes. Due to anthropogenic activities, heavy metals have been leaching due to industrial waste and agricultural activities to the groundwater causing pollution. The assessment of groundwater quality is necessary to reduce the pollution to acceptable levels. Therefore, the aim of this study is to investigate heavy metal concentrations in the groundwater of the villages of Garautha Tehsil, Jhansi where the anthropogenic activities are active. The groundwater samples were analyzed by inductively coupled plasma – mass spectrometry (ICP-MS) and the results were compared to the 2012 Bureau of Indian Standard limits. Three multivariate statistical methods were used to analyze the groundwater quality for irrigation and drinking purposes and to investigate the geological and hydrogeological processes. The results of principal component analysis (PCA) identified four factors responsible for the data structure by illuminating the total variance of 77.83% of the dataset. The majority of groundwater samples contained Al, Co, Cu, Mn, Ni, Cr, Pb, and Fe within the acceptable limits except at few locations. However, the Al, Fe, and Mn concentration were high at a few sites due to rock–water interactions, whereas the concentration of As, Cd, and Zn were lower than their respective permissible limits in all groundwater samples. Furthermore, the groundwater quality for the use of irrigation is found to be acceptable at 19 locations, with only one high result. [ABSTRACT FROM AUTHOR]

The Bundelkhand region of India is suffering from acute water scarcity, raising concern over the potability in the region. Therefore, to develop a baseline data set of groundwater quality, sampling was carried out from the 110 existing shallow hand pumps and tube wells covering the Lalitpur district. Groundwater samples were investigated for hydro-geochemical and isotopic signatures (δ18O and δ2H) to understand the driving factors leading to water quality and its contamination in the region. The results of Hierarchical cluster analysis revealed four different clusters according to their water quality. Cluster 1 and 2 water samples have a good quality of water and these samples fall in the vicinity of major or minor drainage networks of the area. Whereas, clusters 3 and 4 are of deteriorated water quality and located far-off from the drainage networks in the study area. The findings from chemical analysis and chemometric method suggest that the groundwater composition is mainly influenced by rock weathering and anthropogenic activities. Fluoride exposure dosage for the infant and children is twice that of adults in the study area, indicating a stronger impact of fluoride concentration in infants and children. The stable isotopic analysis shows that origin of groundwater is local precipitation, with evaporative enrichment in groundwater. The groundwater of cluster 3 and 4 shows evaporative nature along with high EC and Cl concentration. The variation of concentration of ions in the study area prevails along the groundwater flow direction and surface drainage reveals the control of hydrogeological attributes in the groundwater. [Display omitted] • Geogenic and anthropogenic activity are responsible for deteriorated water quality. • Ions concentration increases along the drainage and groundwater flow direction. • Water with low Ca + Mg ions and high HCO 3 +SO 4 ions and vice-versa are high in F−ions. • High ionic concentration and δ18O signature, supports longer residence time and high rock water interaction. [ABSTRACT FROM AUTHOR]

• Sources and important examples of phenolic bioactives are discussed in the review. • Crucial role of the response surface methodology in extraction of phenolic bioactives is explained in the review. • Green methods for extraction of phenolics are well presented along with optimized values for achieving highest yields. • Mechanism of extraction of green methods are discussed in the review. Phenolic compounds from plant sources have significant health-promoting properties and are known to be an integral part of folk and herbal medicines. Consumption of phenolics is known to alleviate the risk of various lifestyle diseases including cancer, cardiovascular, diabetes, and Alzheimer's. In this context, numerous plant crops have been explored and characterized based on phenolic compounds for their use as supplements, nutraceutical, and pharmaceuticals. The present review highlights some important source of bioactive phenolic compounds and novel technologies for their efficient extraction. These techniques include the use of microwave, ultrasound, and supercritical methods. Besides, the review will also highlight the use of response surface methodology (RSM) as a statistical tool for optimizing the recoveries of the phenolic bioactives from plant-based matrices. [ABSTRACT FROM AUTHOR]

The present study dealt with understanding hydrogeochemical evolution, ascertaining distribution, fate and spatio-temporal variation of arsenic along with comprehending recharge processes and quantification of recharge rate in the central Gangetic plain, India. The arsenic enriched area was observed mostly in the fluvial deposits with younger alluvium. The depth to water levels maps for 1996 and 2016 showed marked spatio-temporal variation and the groundwater recharge rate was estimated to be varied between 0.05 m/year and 0.07 m/year in the study area. The elevated arsenic concentration was noticed in the region, having declined groundwater recharge. A total of 147 water samples were collected from hand pumps (n = 141) and rivers (n = 6) during the pre-monsoon period (May 2016). In addition, about 81 groundwater samples were collected from 27 locations during the pre-monsoon, monsoon and winter 2019 for studying seasonal variability in the hydrogeochemical parameters and isotopic composition of water. Arsenic concentration was found more in the area where deposits of coarser sediment of the Quaternary period was present along the rivers Ganga and Ghaghra. The arsenic concentration was observed higher in the pre-monsoon (maxm. As 641 μg/L), followed by the post-monsoon (425 μg/L) and monsoon season (375 μg/L). The depleted isotopic value and higher D-excess values in groundwater suggested active recharge conditions with precipitation as the major source of recharge in the study area. It is hypothesized that rainwater induced oxygenated water into the aquifer by the process of recharge, which may prompted various biogeochemical reactions due to change in redox conditions and endorsed arsenic sorption in the monsoon season. Thereafter, anoxic conditions prevailed in the post-monsoon season, and finally, in the pre-monsoon season, reducing conditions continued and arsenic released at a rapid rate, which was justified with the seasonal variation of arsenic concentration. [Display omitted] • Depth to water level maps show marked spatio-temporal variation in the study area from year 1996–2016. • GW decline at rate of 0.07 m/yr in the SE region of the study area where elevated arsenic concentration is noticed. • Based on ORP values, reducing conditions exist in the pre-monsoon season and arsenic release at a rapid rate. • Depleted δ18O and higher D-excess values suggest active recharge conditions, and precipitation is the major source. [ABSTRACT FROM AUTHOR]