Impact of COVID 19 in antenatal patient with gestational diabetes mellitus and vice a versa: a retrospective study

Background: The objective of this study is to compare the incidence, severity and feto-maternal outcome of antenatal Coronavirus disease 2019 (COVID-19) positive patients with GDM vs non GDM patients.Methods: This is a retrospective observational study. The study was carried out in department of Obstetrics and Gynecology, GSVM Medical College, Kanpur from March 2020 to December 2020. All the antenatal women with COVID 19 positive status who were admitted during this period were enrolled in the study. Analysis were made on the basis of observation regarding the severity of symptoms COVID 19 disease, oxygen requirements, mode of delivery and neonatal outcome in GDM vs non GDM COVID positive antenatal patient.Results: A total of 421 COVID positive antenatal patients were enrolled of which 21 patients were having GDM and 400 were non GDM. Of these 21 patients, 14 (66.7%) were diagnosed with GDM after admission while 7 patients i.e., 33.3% were already diagnosed GDM before admission in current pregnancy. Of these 21 (42.9%) antenatal COVID pt with GDM majority shows mild symptoms of COVID 19, however the severity of fever, myalgia and cough was increased in GDM compared to Non GDM Group. While in non GDM Group, majority of patients were asymptomatic (44.3%) and severity was also less.Conclusions: It is also evident that patients with GDM had longer duration of hospital stay, higher incidence of caesarean delivery and oxygen requirements

Uncovering the effect of waterlogging stress on plant microbiome and disease development: current knowledge and future perspectives

Waterlogging is a constant threat to crop productivity and ecological biodiversity. Plants face multiple challenges during waterlogging stress like metabolic reprogramming, hypoxia, nutritional depletion, reduction in gaseous exchange, pH modifications, microbiome alterations and disease promotion all of which threaten plants survival. Due to global warming and climatic change, the occurrence, frequency and severity of flooding has dramatically increased posing a severe threat to food security. Thus, developing innovative crop management technologies is critical for ensuring food security under changing climatic conditions. At present, the top priority among scientists is to find nature-based solutions to tackle abiotic or biotic stressors in sustainable agriculture in order to reduce climate change hazards to the environment. In this regard, utilizing plant beneficial microbiome is one of the viable nature based remedial tool for mitigating abiotic stressors like waterlogging. Beneficial microbiota provides plants multifaceted benefits which improves their growth and stress resilience. Plants recruit unique microbial communities to shield themselves against the deleterious effects of biotic and abiotic stress. In comparison to other stressors, there has been limited studies on how waterlogging stress affects plant microbiome structure and their functional traits. Therefore, it is important to understand and explore how waterlogging alters plant microbiome structure and its implications on plant survival. Here, we discussed the effect of waterlogging stress in plants and its microbiome. We also highlighted how waterlogging stress promotes pathogen occurrence and disease development in plants. Finally, we highlight the knowledge gaps and areas for future research directions on unwiring how waterlogging affects plant microbiome and its functional traits. This will pave the way for identifying resilient microbiota that can be engineered to promote their positive interactions with plants during waterlogging stress

Exogenous coenzyme Q10 modulates MMP-2 activity in MCF-7 cell line as a breast cancer cellular model

<p>Abstract</p> <p>Background/Aims</p> <p>Matrix Metalloproteinases 2 is a key molecule in cellular invasion and metastasis. Mitochondrial ROS has been established as a mediator of MMP activity. Coenzyme Q₁₀contributes to intracellular ROS regulation. Coenzyme Q₁₀beneficial effects on cancer are still in controversy but there are indications of Coenzyme Q₁₀complementing effect on tamoxifen receiving breast cancer patients.</p> <p>Methods</p> <p>In this study we aimed to investigate the correlation of the effects of co-incubation of coenzyme Q10 and N-acetyl-L-cysteine (NAC) on intracellular H2O2 content and Matrix Metalloproteinase 2 (MMP-2) activity in MCF-7 cell line.</p> <p>Results and Discussion</p> <p>Our experiment was designed to assess the effect in a time and dose related manner. Gelatin zymography and Flowcytometric measurement of H2O2 by 2'7',-dichlorofluorescin-diacetate probe were employed. The results showed that both coenzyme Q10 and N-acetyl-L-cysteine reduce MMP-2 activity along with the pro-oxidant capacity of the MCF-7 cell in a dose proportionate manner.</p> <p>Conclusions</p> <p>Collectively, the present study highlights the significance of Coenzyme Q₁₀effect on the cell invasion/metastasis effecter molecules.</p

Nucleic acid-based fluorescent probes and their analytical potential

It is well known that nucleic acids play an essential role in living organisms because they store and transmit genetic information and use that information to direct the synthesis of proteins. However, less is known about the ability of nucleic acids to bind specific ligands and the application of oligonucleotides as molecular probes or biosensors. Oligonucleotide probes are single-stranded nucleic acid fragments that can be tailored to have high specificity and affinity for different targets including nucleic acids, proteins, small molecules, and ions. One can divide oligonucleotide-based probes into two main categories: hybridization probes that are based on the formation of complementary base-pairs, and aptamer probes that exploit selective recognition of nonnucleic acid analytes and may be compared with immunosensors. Design and construction of hybridization and aptamer probes are similar. Typically, oligonucleotide (DNA, RNA) with predefined base sequence and length is modified by covalent attachment of reporter groups (one or more fluorophores in fluorescence-based probes). The fluorescent labels act as transducers that transform biorecognition (hybridization, ligand binding) into a fluorescence signal. Fluorescent labels have several advantages, for example high sensitivity and multiple transduction approaches (fluorescence quenching or enhancement, fluorescence anisotropy, fluorescence lifetime, fluorescence resonance energy transfer (FRET), and excimer-monomer light switching). These multiple signaling options combined with the design flexibility of the recognition element (DNA, RNA, PNA, LNA) and various labeling strategies contribute to development of numerous selective and sensitive bioassays. This review covers fundamentals of the design and engineering of oligonucleotide probes, describes typical construction approaches, and discusses examples of probes used both in hybridization studies and in aptamer-based assays

Ecophysiological studies for boosting commercial production of tuberous roots of <i style="">Chlorophytum boriviilianum</i> Sant ET Fernan

60-63This paper presents ecophysiological studies of tuberous roots of safed moosli (Chlorophytum borivilianum), a powerful aphrodisiac, for boosting its commercial production. Average weight of tuberous roots produced at the end of growing season from propagule root tubers soaked in 0.75% of potassium sulphate or a mixture (100 ppm) of equal quantities of IAA (indole acetic acid) and kinetin prior to sowing led to three times higher production than control. Pretreatment with potassium salts are only negligibly lower than those produced under very costly hormones, giving higher profits to safed moosli culivators

Hybrid FiST_CNN approach for Feature Extraction for Vision-Based Indian Sign Language Recognition

Indian sign language (ISL) is the commonly used language by the deaf-mute community in the Indian continent. Effective feature extraction is essential for the automatic recognition of gestures. This paper aims at developing an efficient feature extraction technique using FAST, SIFT, and CNN. Features from Fast Accelerated Segment Test(FAST) with Scale-invariant Feature Transformation(SIFT) are used to detect and compute features, respectively. CNN is used for classification with the hybridization of FAST-SIFT features. The system is implemented and tested using the python-based library Keras. The results of the proposed techniques have been tested on 34 gestures of ISL (24 alphabet sets and 10 digit sets) and then compared with the CNN and SIFT_CNN, and it is also tested on two publicly available datasets on Jochen Trisech Dataset(JTD) and NUS-II dataset. The proposed study outperformed some existing ISLR works with an accuracy of 97.89%, 95.68%, 94.90% and 95.87% for ISL-alphabets, MNIST, JTD and NUS-II, respectively.</jats:p

Hybrid FiST_CNN approach for Feature Extraction for Vision-Based Indian Sign Language Recognition

Indian sign language (ISL) is the commonly used language by the deaf-mute community in the Indian continent. Effective feature extraction is essential for the automatic recognition of gestures. This paper aims at developing an efficient feature extraction technique using FAST, SIFT, and CNN. Features from Fast Accelerated Segment Test(FAST) with Scale-invariant Feature Transformation(SIFT) are used to detect and compute features, respectively. CNN is used for classification with the hybridization of FAST-SIFT features. The system is implemented and tested using the python-based library Keras. The results of the proposed techniques have been tested on 34 gestures of ISL (24 alphabet sets and 10 digit sets) and then compared with the CNN and SIFT_CNN, and it is also tested on two publicly available datasets on Jochen Trisech Dataset(JTD) and NUS-II dataset. The proposed study outperformed some existing ISLR works with an accuracy of 97.89%, 95.68%, 94.90% and 95.87% for ISL-alphabets, MNIST, JTD and NUS-II, respectively.</jats:p