Unlocking the potential of SiO2 and CeO2 nanoparticles for arsenic mitigation in Vigna mungo L. Hepper (Blackgram).

In this study, the interaction effects of NaAsO2 (1 and 5 µM), SiO2 NPs (10 and 100 mg/L) and CeO2 NPs (10 and 100 mg/L) were assessed in Vigna mungo (Blackgram). The treatment of NaAsO2, SiO2, CeO2-NPs and combinations of NPs & As were applied to blackgram plants under hydroponic conditions. After its application, the morpho-physiological, antioxidant activity, and phytochemical study were evaluated. At 10 and 100 mg/L of SiO2 and CeO2-NPs, there was an increase in antioxidative enzymatic activity (p < 0.05) and reactive oxygen species (ROS). However, substantial ROS accumulation was observed at 1 and 5 µM NaAsO2 and 100 mg/L SiO2 NPs (p < 0.05). Additionally, at such concentrations, there is a substantial reduction in photosynthetic pigments, nitrogen fixation, chlorosis, and plant development when compared to controls (p < 0.05). The combination of SiO2 and CeO2 NPs (10 and 100 mg/L) with NaAsO2 decreased superoxide radical and hydrogen peroxide and improved SOD, CAT, APX, GR, and chlorophyll pigments (p < 0.05). Further FTIR results were evaluated for documenting elemental and phytochemical analysis.

Synthesis and characterization of CeO2 and SiO2 nanoparticles and their effect on growth parameters and the antioxidant defense system in Vigna mungo L. Hepper.

Engineered nanoparticles (NPs) have recently attracted a lot of attention after being tested in various agricultural plants. This paper reports the green synthesis of CeO2 NPs and SiO2 NPs from leaf extracts of Nyctanthes arbor-tristis. The physical characteristics of the produced nanoparticles were then determined using UV-visible spectroscopy, transmission electron microscopy (TEM), fluorescence spectroscopy, and Fourier transform infrared spectroscopy (FTIR). Furthermore, the interaction effects of cerium oxide NPs (C1, C2, and C3) and silicon dioxide NPs (S1, S2, and S3) at 10 mg/L on blackgram (Vigna mungo L.) were evaluated. CeO2 and SiO2 NPs treatments enhanced the growth performance of the plants by causing a decrease in superoxide radical (SOR) and H2O2 via improving antioxidant enzymes. These findings imply that the size and shape of CeO2 and SiO2 NPs provide defense against oxidative damage to the blackgram.

Accurate detection of brain tumor using optimized feature selection based on deep learning techniques.

An unusual increase of nerves inside the brain, which disturbs the actual working of the brain, is called a brain tumor. It has led to the death of lots of lives. To save people from this disease timely detection and the right cure is the need of time. Finding of tumor-affected cells in the human brain is a cumbersome and time- consuming task. However, the accuracy and time required to detect brain tumors is a big challenge in the arena of image processing. This research paper proposes a novel, accurate and optimized system to detect brain tumors. The system follows the activities like, preprocessing, segmentation, feature extraction, optimization and detection. For preprocessing system uses a compound filter, which is a composition of Gaussian, mean and median filters. Threshold and histogram techniques are applied for image segmentation. Grey level co-occurrence matrix (GLCM) is used for feature extraction. The optimized convolution neural network (CNN) technique is applied here that uses whale optimization and grey wolf optimization for best feature selection. Detection of brain tumors is achieved through CNN classifier. This system compares its performance with another modern technique of optimization by using accuracy, precision and recall parameters and claims the supremacy of this work. This system is implemented in the Python programming language. The brain tumor detection accuracy of this optimized system has been measured at 98.9%.

A review on blockchain for DNA sequence: security issues, application in DNA classification, challenges and future trends.

In biological science, the study of DNA sequences is considered an important factor because it carries the genomic details that can be used by researchers and doctors for the early prediction of disease using DNA classification. The NCBI has the world's largest database of genetic sequences, but the security of this massive amount of data is currently the greatest issue. One of the options is to encrypt these genetic sequences using blockchain technology. As a result, this paper presents a survey on healthcare data breaches, the necessity for blockchain in healthcare, and the number of research studies done in this area. In addition, the report suggests DNA sequence classification for earlier disease identification and evaluates previous work in the field.

Nanotechnology: the Alternative and Efficient Solution to Biofouling in the Aquaculture Industry.

Biofouling is a global issue in aquaculture industries. It adversely affects marine infrastructure (ship's hulls, mariculture cages and nets, underwater pipes and filters, building materials, probes, and sensor devices). The estimated cost of managing marine biofouling accounts for 5-10% of production cost. Non-toxic foul-release coating and biocide-based coating are the two current approaches. Recent innovation and development of a surface coating with nanoparticles such as photocatalytic zinc oxide nanocoating on fishing nets, copper oxide nanocoating on the water-cooling system, and silver nanoparticle coating to inhibit microalgal adhesion on submerged surfaces under natural light (photoperiod) could present meaningful anti-biofouling application. Nanocoating of zinc, copper, and silver oxide is an environmentally friendly surface coating strategy that avoid surface adhesion of bacteria, diatoms, algal, protozoans, and fungal species. Such nanocoating could also provide a solution to strains tolerant to Cu, Zn, and Ag. This draft of the special issue demonstrates the anti-biofouling potential of various metal and metal oxide nanoparticle coating to combat aquaculture industry biofouling problems.

Assessing the SpO2 in a random population - Looking for the best among fingers.

Context: Pulse oximetry is one of the most revolutionary methods used to monitor the patients in the clinical setting, particularly intensive care and anesthesia. We usually use the index or middle finger to measure SpO2 values, but little is known about the inter-digital differences that exist between the fingers. Aim: We aim to compare the peripheral capillary oxygen saturation among fingers of both hands. A total of 93 healthy volunteers aged between 18 and 50 years participated in the study. Materials and Methods: Their SpO2 values were recorded from each finger with at least 1 minute of resting interval. Their blood pressure, heart rate, and body temperature were recorded as well. Result: A total of 930 measurements were obtained from 93 volunteers. The highest average SpO2 value of right-handed volunteers was measured from the left little finger (98.48 ± 0.62) of right-handed volunteers, and it was statistically significant when compared with the right ring finger, right little finger, left thumb, left index, left middle finger, and left ring finger. The highest average SpO2 from left-handed volunteers was obtained from the right index finger, but it was statistically insignificant. Conclusion: We assume ethnic and climatic differences to play a role in contradictory results noted from previous studies conducted, and this needs to be investigated further. It is recommended that multiple readings may be obtained from other fingers as well before coming to any conclusion as inter-finger variability cannot be ignored.

A comprehensive tool for rapid and accurate prediction of disease using DNA sequence classifier.

In the current pandemic situation where the coronavirus is spreading very fast that can jump from one human to another. Along with this, there are millions of viruses for example Ebola, SARS, etc. that can spread as fast as the coronavirus due to the mobilization and globalization of the population and are equally deadly. Earlier identification of these viruses can prevent the outbreaks that we are facing currently as well as can help in the earlier designing of drugs. Identification of disease at a prior stage can be achieved through DNA sequence classification as DNA carries most of the genetic information about organisms. This is the reason why the classification of DNA sequences plays an important role in computational biology. This paper has presented a solution in which samples collected from NCBI are used for the classification of DNA sequences. DNA sequence classification will in turn gives the pattern of various diseases; these patterns are then compared with the samples of a newly infected person and can help in the earlier identification of disease. However, feature extraction always remains a big issue. In this paper, a machine learning-based classifier and a new technique for extracting features from DNA sequences based on a hot vector matrix have been proposed. In the hot vector representation of the DNA sequence, each pair of the word is represented using a binary matrix which represents the position of each nucleotide in the DNA sequence. The resultant matrix is then given as an input to the traditional CNN for feature extraction. The results of the proposed method have been compared with 5 well-known classifiers namely Convolution neural network (CNN), Support Vector Machines (SVM), K-Nearest Neighbor (KNN) algorithm, Decision Trees, Recurrent Neural Networks (RNN) on several parameters including precision rate and accuracy and the result shows that the proposed method gives an accuracy of 93.9%, which is highest compared to other classifiers.

Molecular mechanisms of action of epigallocatechin gallate in cancer: Recent trends and advancement.

Epigallocatechin gallate (EGCG), also known as epigallocatechin-3-gallate, is an ester of epigallocatechin and gallic acid. EGCG, abundantly found in tea, is a polyphenolic flavonoid that has the potential to affect human health and disease. EGCG interacts with various recognized cellular targets and inhibits cancer cell proliferation by inducing apoptosis and cell cycle arrest. In addition, scientific evidence has illustrated the promising role of EGCG in inhibiting tumor cell metastasis and angiogenesis. It has also been found that EGCG may reverse drug resistance of cancer cells and could be a promising candidate for synergism studies. The prospective importance of EGCG in cancer treatment is owed to its natural origin, safety, and low cost which presents it as an attractive target for further development of novel cancer therapeutics. A major challenge with EGCG is its low bioavailability which is being targeted for improvement by encapsulating EGCG in nano-sized vehicles for further delivery. However, there are major limitations of the studies on EGCG, including study design, experimental bias, and inconsistent results and reproducibility among different study cohorts. Additionally, it is important to identify specific EGCG pharmacological targets in the tumor-specific signaling pathways for development of novel combined therapeutic treatments with EGCG. The present review highlights the ongoing development to identify cellular and molecular targets of EGCG in cancer. Furthermore, the role of nanotechnology-mediated EGCG combinations and delivery systems will also be discussed.

Natural product-based nanoformulations for cancer therapy: Opportunities and challenges.

Application of natural product-based nanoformulations for the treatment of different human diseases, such as cancer, is an emerging field. The conventional cancer therapeutic modalities, including surgery, chemotherapy, immunotherapy, radiotherapy has limited achievements. A larger number of drawbacks are associated with these therapies, including damage to proliferating healthy tissues, structural deformities, systemic toxicity, long-term side effects, resistance to the drug by tumor cells, and psychological problems. The advent of nanotechnology in cancer therapeutics is recent; however, it has progressed and transformed the field of cancer treatment at a rapid rate. Nanotherapeutics have promisingly overcome the limitations of conventional drug delivery system, i.e., low aqueous solubility, low bioavailability, multidrug resistance, and non-specificity. Specifically, natural product-based nanoformulations are being intentionally studied in different model systems. Where it is found that these nanoformulations has more proximity and reduced side effects. The nanoparticles can specifically target tumor cells, enhancing the specificity and efficacy of cancer therapeutic modalities which in turn improves patient response and survival. The integration of phytotherapy and nanotechnology in the clinical setting may improve pharmacological response and better clinical outcome of patients.

Superior Vena Cava Syndrome due to Pulmonary Tuberculosis: A Rare Presentation.

Superior vena cava syndrome (SVCS) is a disease entity with notable signs and symptoms that cannot go unnoticed by clinicians and taken as a clear sign of infiltrative mediastinal involvement, usually caused by neoplasms in this location, however other causes of benign origin can also present with these symptoms. This unusual case highlights the fact that tuberculosis should also be kept in mind as a differential diagnosis in patients presenting with symptoms of SVC obstruction. A timely diagnosis and appropriate treatment leads to cure.

Correction: Photocatalytic antibacterial performance of TiO2 and Ag-doped TiO2 against S. aureus. P. aeruginosa and E. coli.

[This corrects the article DOI: 10.3762/bjnano.4.40.].

COVID-19 Outcomes in Postmenopausal and Perimenopausal Females: Is Estrogen Hormone Attributing to Gender Differences?

BACKGROUND: Globally, case fatality rate is more in males compared to females. Some studies have suggested. It is hypothesized that estrogen hormone may decrease susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS CoV-2.). OBJECTIVE: The objective of the study was to evaluate the gender differences in SARS CoV-2 outcomes and to analyze if there are any differences in outcomes in premenopausal females compared to postmenopausal females. MATERIALS AND METHODS: Patients tested positive for SARS CoV-2 through real-time reverse transcription-polymerase chain reaction by Thermo Fischer Taqpath assay approved by the Indian Council of Medical Research were included in the study. The data obtained was analyzed for the epidemiological, clinical, and laboratory characteristics from their medical records. RESULTS: The mortality rate in females was 12.6%, whereas mortality in males was 19.4%. In between-group analysis, 8.6% (16/185) of females died in premenopausal age group versus 12.8% (27/211) in postmenopausal group. The proportion of females who expired due to COVID significantly differ by age and postmenopausal status X2 (1, n = 293) = 7.2, the P value is 0.007. The difference is statistically significant at P < 0.05. Postmenopausal women were more likely to expire due to COVID-19 infection compared to premenopausal women. CONCLUSION: The mortality rate in postmenopausal age group was greater than mortality in premenopausal females emphasizing the protection provided by estrogens hormone in them. Postmenopausal women are also at higher risk of severe COVID-19 infection than premenopausal women. Mortality is greater in males compared to females, further strengthening the role of estrogens.

Cheese whey to biohydrogen and useful organic acids: A non-pathogenic microbial treatment by L. acidophilus.

The burgeoning organic waste and continuously increasing energy demands have resulted in significant environmental pollution concerns. To address this issue, the potential of different bacteria to produce biogas/biohydrogen from organic waste can be utilized as a source of renewable energy, however these pathogenic bacteria are not safe to use without strict contact isolation. In this study the role of safe food grade lactic acid bacteria (Lactobacillus spp.) was investigated for production of biogas from cheese waste with starting hexose concentration 32 g/L. The bacterium Lactobacillus acidophilus was identified as one of the major biogas producers at optimum pH of 6.5. Further the optimum inoculum conditions were found to be 12.5% at inoculum age of 18 h. During the investigation the maximum biogas production was observed to be 1665 mL after 72 hours of incubation at pH 6.5. The biogas production was accompanied with production of other valuable metabolites in the form of organic acids including pyruvate, propionate, acetate, lactate, formate and butyrate. Thus this research is paving way for nonpathogenic production of biohydrogen from food waste.