Capsicum chinense Jacq.-derived glutaredoxin (CcGRXS12) alters redox status of the cells to confer resistance against pepper mild mottle virus (PMMoV-I)

KEY MESSAGE

The CcGRXS12 gene protects plants from cellular oxidative damage that are caused by both biotic and abiotic stresses. The protein possesses GSH-disulphide oxidoreductase property but lacks Fe-S cluster assembly mechanism. Glutaredoxins (Grxs) are small, ubiquitous and multi-functional proteins. They are present in different compartments of plant cells. A chloroplast targeted Class I GRX (CcGRXS12) gene was isolated from Capsicum chinense during the pepper mild mottle virus (PMMoV) infection. Functional characterization of the gene was performed in Nicotiana benthamiana transgenic plants transformed with native C. chinense GRX (Nb:GRX), GRX-fused with GFP (Nb:GRX-GFP) and GRX-truncated for chloroplast sequences fused with GFP (Nb:Δ2MGRX-GFP). Overexpression of CcGRXS12 inhibited the PMMoV-I accumulation at the later stage of infection, accompanied with the activation of salicylic acid (SA) pathway pathogenesis-related (PR) transcripts and suppression of JA/ET pathway transcripts. Further, the reduced accumulation of auxin-induced Glutathione-S-Transferase (pCNT103) in CcGRXS12 overexpressing lines indicated that the protein could protect the plants from the oxidative stress caused by the virus. PMMoV-I infection increased the accumulation of pyridine nucleotides (PNs) mainly due to the reduced form of PNs (NAD(P)H), and it was high in Nb:GRX-GFP lines compared to other transgenic lines. Apart from biotic stress, CcGRXS12 protects the plants from abiotic stress conditions caused by H2O2 and herbicide paraquat. CcGRXS12 exhibited GSH-disulphide oxidoreductase activity in vitro; however, it was devoid of complementary Fe-S cluster assembly mechanism found in yeast. Overall, this study proves that CcGRXS12 plays a crucial role during biotic and abiotic stress in plants.

Expression and Immobilization of Tannase for Tannery Effluent Treatment from Lactobacillus plantarum and Staphylococcus lugdunensis: A Comparative Study

Agro-industrial discharges have higher concentrations of tannins and have been a significant cause of pollution to water bodies and soil surrounding the agro-industries. So in this study, toxic tannic acid is into commercially valuable gallic acid from the tannery effluent using immobilized microbial tannase. Tannase genes were isolated from Lactobacillus plantarum JCM 1149 (tanLpl) and Staphylococcus lugdunensis MTCC 3614 (tanA). Further, these isolated tannese genes were cloned and expressed in BL 21 host using pET 28a as an expression vector,  and immobilized in sodium alginate beads. Vegetable tannery effluent was treated by tannase-immobilized beads at 25 °C and 37 °C, where liberated gallic acid was analyzed using TLC and NMR to confirm the tannin reduction. Further, both immobilized tannases exhibited excellent reusability up to 15 cycles of regeneration without significant reduction in their activity. Moreover, we also showed that immobilized tannases tanLpl and tanA activity remained unaffected compared to the free enzyme in the presence of metal ions. Further, tanA activity remained unaffected over a wide range of pH, and tanLpl showed high thermal stability. Thus, immobilized tannase tanLpl and tanA provide a possible solution for tannery effluent treatment depending upon industry requirements and reaction composition/effluent composition, one can choose a better-immobilized tannase among the two as per the need-based requirement.

Genetic mapping of quantitative trait loci associated with drought tolerance in chickpea (Cicer arietinum L.)

Elucidation of the genetic basis of drought tolerance is vital for genomics-assisted breeding of drought tolerant crop varieties. Here, we used genotyping-by-sequencing (GBS) to identify single nucleotide polymorphisms (SNPs) in recombinant inbred lines (RILs) derived from a cross between a drought tolerant chickpea variety, Pusa 362 and a drought sensitive variety, SBD 377. The GBS identified a total of 35,502 SNPs and subsequent filtering of these resulted in 3237 high-quality SNPs included in the eight linkage groups. Fifty-one percent of these SNPs were located in the genic regions distributed throughout the genome. The high density linkage map has total map length of 1069 cm with an average marker interval of 0.33 cm. The linkage map was used to identify 9 robust and consistent QTLs for four drought related traits viz. membrane stability index, relative water content, seed weight and yield under drought, with percent variance explained within the range of 6.29%-90.68% and LOD scores of 2.64 to 6.38, which were located on five of the eight linkage groups. A genomic region on LG 7 harbors quantitative trait loci (QTLs) explaining > 90% phenotypic variance for membrane stability index, and > 10% PVE for yield. This study also provides the first report of major QTLs for physiological traits such as membrane stability index and relative water content for drought stress in chickpea. A total of 369 putative candidate genes were identified in the 6.6 Mb genomic region spanning these QTLs. In-silico expression profiling based on the available transcriptome data revealed that 326 of these genes were differentially expressed under drought stress. KEGG analysis resulted in reduction of candidate genes from 369 to 99, revealing enrichment in various signaling pathways. Haplotype analysis confirmed 5 QTLs among the initially identified 9 QTLs. Two QTLs, qRWC1.1 and qYLD7.1, were chosen based on high SNP density. Candidate gene-based analysis revealed distinct haplotypes in qYLD7.1 associated with significant phenotypic differences, potentially linked to pathways for secondary metabolite biosynthesis. These identified candidate genes bolster defenses through flavonoids and phenylalanine-derived compounds, aiding UV protection, pathogen resistance, and plant structure.The study provides novel genomic regions and candidate genes which can be utilized in genomics-assisted breeding of superior drought tolerant chickpea cultivars.

Recent Development and Application of "Nanozyme" Artificial Enzymes-A Review

Nanozymes represent a category of nano-biomaterial artificial enzymes distinguished by their remarkable catalytic potency, stability, cost-effectiveness, biocompatibility, and degradability. These attributes position them as premier biomaterials with extensive applicability across medical, industrial, technological, and biological domains. Following the discovery of ferromagnetic nanoparticles with peroxidase-mimicking capabilities, extensive research endeavors have been dedicated to advancing nanozyme utilization. Their capacity to emulate the functions of natural enzymes has captivated researchers, prompting in-depth investigations into their attributes and potential applications. This exploration has yielded insights and innovations in various areas, including detection mechanisms, biosensing techniques, and device development. Nanozymes exhibit diverse compositions, sizes, and forms, resembling molecular entities such as proteins and tissue-based glucose. Their rapid impact on the body necessitates a comprehensive understanding of their intricate interplay. As each day witnesses the emergence of novel methodologies and technologies, the integration of nanozymes continues to surge, promising enhanced comprehension in the times ahead. This review centers on the expansive deployment and advancement of nanozyme materials, encompassing biomedical, biotechnological, and environmental contexts.

Vitamin C fortification: need and recent trends in encapsulation technologies

The multifaceted role of vitamin C in human health intrudes several biochemical functions that are but not limited to antioxidant activity, homoeostasis, amino acid synthesis, collagen synthesis, osteogenesis, neurotransmitter production and several yet to be explored functions. In absence of an innate biosynthetic pathway, humans are obligated to attain vitamin C from dietary sources to maintain its optimal serum level (28 μmol/L). However, a significant amount of naturally occurring vitamin C may deteriorate due to food processing, storage and distribution before reaching to the human gastrointestinal tract, thus limiting or mitigating its disease combating activity. Literature acknowledges the growing prevalence of vitamin C deficiency across the globe irrespective of geographic, economic and population variations. Several tools have been tested to address vitamin C deficiency, which are primarily diet diversification, biofortification, supplementation and food fortification. These strategies inherit their own advantages and limitations. Opportunely, nanotechnology promises an array of delivery systems providing encapsulation, protection and delivery of susceptible compounds against environmental factors. Lack of clear understanding of the suitability of the delivery system for vitamin C encapsulation and fortification; growing prevalence of its deficiency, it is a need of the hour to develop and design vitamin C fortified food ensuring homogeneous distribution, improved stability and enhanced bioavailability. This article is intended to review the importance of vitamin C in human health, its recommended daily allowance, its dietary sources, factors donating to its stability and degradation. The emphasis also given to review the strategies adopted to address vitamin c deficiency, delivery systems adopted for vitamin C encapsulation and fortification.

Adsorption isotherm, kinetics and response surface methodology optimization of cadmium (Cd) removal from aqueous solution by chitosan biopolymers from cephalopod waste

The present investigation was aimed to explore the cadmium removal efficiency, mechanism and characterization of Chitosan biopolymers from cephalopods waste. The extracted chitosan has showed good yield of 32% and with high minerals, ash and moisture content. In the Fourier-transform infrared spectroscopy (FT-IR) analysis multiple active functional groups of Amine, Amine, Hydroxyl were found between 612 and 3424 cm^-1 and the sugar signals such as N-acetyl glucosamine (GlcNAc) and H-1 [GlcN (H-1D), GlcNAc (H-1A)] were identified in Chitosan by ¹H Nuclear Magnetic Resonance (NMR). The Crystalline, rough surface, micropores characters were observed in Chitosan surface by Scanning Electron Microscope (SEM) analysis and the pores played a key role in adsorption process. The Cd ions removal was performed by batch experiment and the results were revealed that the pH, temperature, time and dosage highly influenced the process and the optimum condition was discovered through RSM for pH 7, temperature 42.5 °C, time 220 min and dosage of sorbent 1 g/L respectively. The kinetics models of the Cd removal were carried out and the results revealed that the Pseudo-second order is more suitable and fit for removal than Pseudo-first order model. Chitosan surface characters and functional groups played a big role in adsorption process and Chitosan can be alternative eco-friendly, low cost and highly efficient sorbent for heavy metal removal in effluent treatment plants.

Assessment of metal contaminants along the Bay of Bengal - Multivariate pollution indices

The spatial concentration of heavy metals (Mn, Ni, Cu, Co, Zn, Cd, and Pb) was studied in coastal areas (n = 9) including water (n = 27) and sediment (n = 27) in the Palk Bay, India to understand the metal pollution due to prevailing natural and anthropogenic activities. Pollution indices like metal index (MI), geoaccumulation index (Igeo), contamination factor (CF), pollution load index (PLI) and potential ecological risk (PER) were calculated based on the background/reference value. The values of MI index indicated that water was free of metals, whereas Igeo, CF, PLI and PER indicated moderate contamination of sediment in monsoon. Cadmium concentrations were the highest irrespective of the indices (Igeo: 0.04-1.42, Cf: 0.36-0.74, PLI: 0.36-0.74, and PER: 76.89-143.36) indicating moderate pollution. The Principal Component Analysis (PCA) affirmed that Cd was positively correlated with stations indicating anthropogenic sources of Cd contamination.

Lipid ROS- and Iron-Dependent Ferroptotic Cell Death in Unicellular Algae Chlamydomonas reinhardtii

The phenomenon of heat stress leading to ferroptosis-like cell death has recently been observed in bacteria as well as plant cells. Despite recent findings, the evidence of ferroptosis, an iron-dependent cell death remains unknown in microalgae. The present study aimed to investigate if heat shock could induce reactive oxygen species (ROS) and iron-dependent ferroptotic cell death in Chlamydomonas reinhardtii in comparison with RSL3-induced ferroptosis. After RSL3 and heat shock (50 °C) treatments with or without inhibitors, Chlamydomonas cells were evaluated for cell viability and the induction of ferroptotic biomarkers. Both the heat shock and RSL3 treatment were found to trigger ferroptotic cell death, with hallmarks of glutathione-ascorbic acid depletion, GPX5 downregulation, mitochondrial dysfunction, an increase in cytosolic calcium, ROS production, lipid peroxidation, and intracellular iron accumulation via heme oxygenase-1 activation (HO-1). Interestingly, the cells preincubated with ferroptosis inhibitors (ferrostatin-1 and ciclopirox) significantly reduced RSL3- and heat-induced cell death by preventing the accumulation of Fe²⁺ and lipid ROS. These findings reveal that ferroptotic cell death affects the iron homeostasis and lipid peroxidation metabolism of Chlamydomonas, indicating that cell death pathways are evolutionarily conserved among eukaryotes.

Exploring invasive weed biochar as soil amendment: A study on fodder oats productivity and soil biological properties

Biochar is known for the improvement of soil health, fertility, crop productivity, and quality in many agro-ecosystems globally, but information regarding fodder yield, quality, and soil microbial activity responses to biochar application remains very limited. The objective of this study was to prepare biochar from invasive weeds, i.e., Parthenium hysterophorus L. and Lantana camara L., and use it as a soil amendment along with inorganic fertilizers for oats (Avena sativa L.) growth, fodder yield, quality, and soil microbial activities in a two-year pot experiment. Treatments were comprised of control, 100% RDF (Recommended dose of fertilizers), 75% RDF along with three doses (2.5, 5.0, and 10 t/ha) of Parthenium hysterophorus L. biochar (PB) and Lantana camara L. biochar (LB), PB (10 t/ha), and LB (10 t/ha). Results showed that application of 75% RDF along with 10 t/ha LB gave significantly higher green (∼8%) and dry (∼7.8%) fodder yield and crude protein (∼6%) and decreased acid detergent fibre (ADF) and neutral detergent fibre (NDF) by 5.70 and 6.04% as compared to the 100% RDF treatment. The same treatment had a significantly higher population of bacteria (7.33 × 10⁸ colony forming unit (CFU)/g soil), alkaline phosphatase activity (19.56 μg pNP/g soil/h), microbial biomass carbon (156.67 μg/g soil) and dehydrogenase activity (12.59 μg TPF/g/24 h), whereas the maximum fungal population (13.33 × 10⁴ CFU/g soil) and acid phosphatase activity (14.45 μg pNP/g soil/h) were found in 75% RDF along with 10 t/ha PB and control treatment, respectively. This study concluded that application of invasive weed biochar along with inorganic fertilizers can benefit fodder yield and quality of oats by increasing plant height and number of tillers directly and by improving nutrient availability and water holding capacity (WHC) of soil indirectly, besides improving soil health. The findings from this study will provide a potential strategy for invasive weed management.

Range grasses to improve soil properties, carbon sustainability, and fodder security in degraded lands of semi-arid regions

Tropical grasses are the primary source of forage for livestock and a valuable resource for improving soil health and environmental sustainability in semi-arid regions. A study was carried out in a semi-arid region of central India to determine the short-term (6-year) impact of nine range grasses on soil physio-chemical and biological properties, carbon stock, and forage security. The experiment was carried out in a randomized block design with three replications. Results show that the majority of the grass roots were distributed in the upper soil layer (0-10 cm, 63.5-76.5 %), and then in the middle (10-20 cm, 21.3-25 %) and lower (20-30 cm, 2.2-11.5 %) layers. Perennial tussock grass (Heteropogon contortus (L.) P. Beauv. ex Roem. & Schult) had a higher root volume (2219 mm³), followed by Guinea grass [Megathyrsus maximus (Jacq.) B.K. Simon & S.W.L. Jacobs] (1860 mm³). A lower soil bulk density (BD, 1.11-1.23 g cm^-3), higher gravimetric water content (GMW, 14.0-17.8 %), and soil organic carbon (0.38-0.73 %) were recorded for grass-cultivated plots compared to the barren land (1.38 g cm^-3, 13.0 %, and 0.28 %, respectively). The perennial tussock grass and Guinea grass resulted in the highest soil microbial biomass carbon (SMBC, 70.1 mg kg^-1 soil) and enzyme activities (dehydrogenase, 17.09 μg TPF g^-1 day^-1 and fluorescein diacetate activity 4.94 μg fluorescein g^-1 h^-1). The considerable improvement in soil properties with minimal inputs resulted in a higher sustainable yield index and carbon sustainability index in plots planted with Guinea grass (0.9 and 89.29) and perennial tussock grass (0.89 and 71.61). Therefore, the cultivation of either Guinea grass or perennial tussock grass as an intercrop or sole crop in the semi-arid environment can be an ecologically sound strategy to improve soil health, C sequestration, and fodder supply.

Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run

We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2  M_{⊙} and 1.0  M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14  yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200]  Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2  M_{⊙}<m_{PBH}<1.0  M_{⊙} is f_{PBH}≡Ω_{PBH}/Ω_{DM}≲6%. This improves existing constraints on primordial black hole abundance by a factor of ∼3. The other is a dissipative dark matter model, in which fermionic dark matter can collapse and form black holes. The upper limit on the fraction of dark matter black holes depends on the minimum mass of the black holes that can be formed: the most constraining result is obtained at M_{min}=1  M_{⊙}, where f_{DBH}≡Ω_{DBH}/Ω_{DM}≲0.003%. These are the first constraints placed on dissipative dark models by subsolar-mass analyses.

Predicting the Growth of F. proliferatum and F. culmorum and the Growth of Mycotoxin Using Machine Learning Approach

In distinct parts of the food web, Fusarium culmorum and Fusarium preserving the relationship can germinate and grow zearalenone (ZEA) and fumonisins (FUM), accordingly. Antimicrobial drugs used to combat these fungi and toxic metabolites raise the risk of hazardous residue in food products, as well as the development of fungus tolerance. For modeling fungal growth and pathogenicity under separate water action (a q ) (0.96 and 0.99) and surface temp (20 and 28°C) tyrannies, several machine learning (ML) methodologies (artificial neural, regression trees, and extreme rise enhanced trees) and multiple regression model (MLR) were used also especially in comparison. GR and mycotoxin levels inside the environment often reduced as EOC concentrations grew, although some treatment in association with specific a q and temperature values caused ZEA production. In terms of predicting the growth rate of F. culmorum and F. maintaining the relationship and the production of ZEA and FUM, random forest techniques outperformed neural network models and extreme gradient boosted trees. The MLR option was the most inefficient. It is the first research to look at the ML potential of bio EVOH products containing EOCs and ambient variables of F. culmorum and F. proliferatum development, as well as the generation of zearalenone and fumonisins. The findings show that these entire novel wrapping technologies, in tandem using machine learning techniques, could be useful in predicting and controlling the dangers connected with fungal species or biotoxins in foodstuff.

Sinapis arvensis-Wild Mustard as an AntiSection inflammatory Agent: An In-vitro Study

Introduction: Inflammation is body’s immune response to harmful stimulus. Commonly used conventional antiinflammatory agents are Non-Steroidal Anti-inflammatory Drugs (NSAIDs). But on prolonged long-term use, it causes serious adverse events. So, the search towards natural agents which have anti-inflammatory property are increasing nowadays. Sinapis arvensis is an annual flowering plant which has proven multipurpose medicinal phytoconstituents. Aim: To evaluate in-vitro anti-inflammatory effects of flower extracts of Sinapis arvensis with diclofenac as standard. Materials and Methods: This in-vitro study assessed the laboratory based anti-inflammatory activity, performed using Bovine Serum Albumin (BSA) assay in December 2021 at Sree Balaji Medical College and Hospital, Chennai, Tamil Nadu, India. BSA at pH of 6.8 generated denatured proteins. The anti-inflammatory activity of the sample (flower extracts of Sinapis arvensis) and standard (Diclofenac) was assessed by adding to BSA and percentage of inhibition of denaturation were calculated using the formula based on the absorbance measured. Descriptive statistics was used for analysis of collected data. Results: The concentration-dependent inhibition of protein denaturation was observed for both Sinapis arvensis and Diclofenac. At 100 µg concentration, percentage of inhibition reached up to 81.8% and 100% for Sinapis arvensis and Diclofenac, respectively. Conclusion: The present study showed that flower extracts of Sinapis arvensis exhibited concentration dependent antiinflammatory property invitro which proves to be nearly equivalent with that of the standard Diclofenac.

Ectopic expression of bacterial 1-aminocyclopropane 1-carboxylate deaminase in Chlamydomonas reinhardtii enhances algal biomass and lipid content under nitrogen deficit condition

1-Aminocyclopropane-1-carboxylate (ACC) deaminase is a well-known bacterial producing enzyme that helps plants to overcome stress conditions by modulating ethylene biosynthesis. However, the functional role of ACC deaminase and ethylene in microalgae during stress remains to be explored. In this study, to investigate the role of ACC deaminase (acds) from Pseudomonas putida UW4 in enhancing the biomass and lipid content of Chlamydomonas under nitrogen deficit condition. The synthetic codon-optimized acds gene was cloned into vector pChlamy_4 and introduced into Chlamydomonas. Results indicated that Chlamydomonas-expressing acds lines showed significant tolerance to nitrogen-deficit by reducing the ethylene content. The biomass, chlorophyll content and photosynthetic activity of acds-expressing lines were significantly increased during nitrogen deficit condition. Moreover, the intracellular lipid and fatty acid content were much higher in acds-expressing lines than the wild-type. In terms of stress alleviation, the transgenic lines displayed increased antioxidant enzymes, reduced ROS and lipid peroxidation levels.

1262 Audit of MRI IAM (Internal Auditory Meatus) Requests at Darlington Memorial Hospital and Review of The Literature

Aim

To assess if the MRI IAM scans are being requested as suggested in NICE guidelines Draft 2017 for consultations. Educate and implement any changes if needed to minimise unnecessary investigations.

Method

Retrospective data collection of 1000 data. Variables included hearing loss (HL), tinnitus (T), dizziness (D) and other lateralized symptoms. Audiograms assessed for asymmetrical HL at decibel level ≥20 Db at a frequency of 0.5 kHz, 1.0 kHz, 2.0 kHz. MRI of IAM assessed if a cerebellar pontine angle (CPA) lesion was presented.

Results

853 (85.3%) met criteria. 16/1000 (1.6%) MRI showed CPA lesion. All 16 cases had unilateral sensorineural hearing loss (SNHL) and met NICE guidelines criteria.

Discussion

Limited value in the scanning of asymptomatic patients, those who do not fit audiometric guidelines, those bilateral symptoms or those with unilateral tinnitus without audiometric asymmetry. Very few studies were found in the literature in relation to symptoms associated with positive findings of CPA lesion. Our results indicate unilateral SNHL were linked with positive findings of MRI and it is similar findings in the literature. We recommend that patients who present with asymmetrical SNHL with this audiometric asymmetrical characteristic of 20Db or more will need an urgent MRI IAM as part of their diagnostic workup.

Sentimental analysis from imbalanced code-mixed data using machine learning approaches

Knowledge discovery from various perspectives has become a crucial asset in almost all fields. Sentimental analysis is a classification task used to classify the sentence based on the meaning of their context. This paper addresses class imbalance problem which is one of the important issues in sentimental analysis. Not much works focused on sentimental analysis with imbalanced class label distribution. The paper also focusses on another aspect of the problem which involves a concept called "Code Mixing". Code mixed data consists of text alternating between two or more languages. Class imbalance distribution is a commonly noted phenomenon in a code-mixed data. The existing works have focused more on analyzing the sentiments in a monolingual data but not in a code-mixed data. This paper addresses all these issues and comes up with a solution to analyze sentiments for a class imbalanced code-mixed data using sampling technique combined with levenshtein distance metrics. Furthermore, this paper compares the performances of various machine learning approaches namely, Random Forest Classifier, Logistic Regression, XGBoost classifier, Support Vector Machine and Naïve Bayes Classifier using F1- Score.

Prevalence of early hip OA features on MRI in high-impact athletes. The femoroacetabular impingement and hip osteoarthritis cohort (FORCe) study

OBJECTIVE

To compare early hip osteoarthritis (OA) features on magnetic resonance imaging (MRI) in high-impact athletes with and without hip and/or groin pain, and to evaluate associations between early hip OA features, the International Hip Outcome Tool (iHOT33) and Copenhagen Hip and Groin Outcome Score (HAGOS).

DESIGN

This case-control study evaluated data of the femoroacetabular impingement and hip osteoarthritis cohort (FORCe). One hundred and eighty-two symptomatic (hip and/or groin pain >6 months and positive flexion-adduction-internal-rotation (FADIR) test) and 55 pain-free high-impact athletes (soccer or Australian football (AF)) without definite radiographic hip OA underwent hip MRI. The Scoring Hip Osteoarthritis with MRI (SHOMRI) method quantified and graded the severity of OA features. Each participant completed the iHOT33 and HAGOS.

RESULTS

Hip and/or groin pain was associated with higher total SHOMRI (0-96) (mean difference 1.4, 95% CI: 0.7-2.2), labral score (adjusted incidence rate ratio (aIRR) 1.33, 95% CI: 1.1-1.6). Differences in prevalence of cartilage defects, labral tears and paralabral cysts between symptomatic and pain-free participants were inconclusive. There was a lower prevalence of effusion-synovitis in symptomatic participants when compared to pain-free participants (adjusted odds ratio (aOR) 0.46 (95% CI: 0.3-0.8). Early hip OA features were not associated with iHOT33 or HAGOS.

CONCLUSIONS

A complex and poorly understood relationship exists between hip and/or groin pain and early hip OA features present on MRI in high-impact athletes without radiographic OA. Hip and/or groin pain was associated with higher SHOMRI and labral scores.

Molecular analysis of Bacillus velezensis KB 2216, purification and biochemical characterization of alpha-amylase

Alpha-amylase producing strain KB 2216 was identified as Bacillus velezensis. The growth pattern showed that 72 h is the optimum incubation period of amylase production, which is a stationary period for the strain. By the purification process, maximum alpha-amylase activity was achieved up to 418.25 U/mL at 72 h of incubation, which was purified with 4.74 folds, 4230.32 U/mg specific activity, with 31.35% yield. The strain was found to produce an oligomeric alpha-amylase, namely Amy3. Amy3 was a trimeric macromolecule of 195 kDa with 62, 64, and 66 kDa subunits, as revealed by zymogram and SDS PAGE analyses. Amy3 was highly active at 55 °C and pH 5.5. It had shown the highest stability at pH 5.0-5.5 and between 0 ̊C and 4 ̊C. It did not require any metal cofactors, but it was inhibited by Ag²⁺, Hg²⁺ and Cd²⁺ divalent cations. Glucose and maltose were shown to be the end products of soluble starch digestion by Amy3. These interesting properties of Amy3 may be useful for many biotechnological applications in the future.

Enhanced Biosynthesis Synthesis of Copper Oxide Nanoparticles (CuO-NPs) for their Antifungal Activity Toxicity against Major Phyto-Pathogens of Apple Orchards

PURPOSE

The present study made an attempt to develop copper nanoparticles (Cu-NP) with antifungal property using green synthesis method. Copper oxide nanoparticles (CuO-NPs) botanically synthesized using Neem leaf extract (Azadirachta indica A. Juss) were characterized by using different techniques like; UV-visible spectrophotometry, FTIR, XRD, SEM and TEM.

METHODS

Materials were chosen the disease free and fresh Azadirachta indica A. Juss were collected and identified at Center of Biodiversity and Taxonomy. The plant samples were vigorously washed with distilled water then shade dried followed by sterilization with 0.1% mercuric chloride for 20 s and again it was washed with distilled water. 15 g powder form of plant material was added to 200 ml double distilled, CO₂ free and deionized water and kept in shaker at 80°C and 1500 rpm for six hours. After agitation, the extract was separated by regular centrifugation at 10,000 rpm followed by filtration by using whatmann filter paper. The final volume of 100 ml of supernatant was collected as pure extract and stored in cool place for further use.

RESULTS

The final results confirm a significant inhibition of CuO-NPs for the test fungi. Additionally, CuO-NPs demonstrated an enhanced effect when combined with Neem leaf extract. A total of 20-30% improvement in activity was noticed after combination, which correlates with commonly used synthetic fungicides. The toxicity results reveal that A. indica extract and their combined fractions with CuO-NP were less toxic to the test seeds of experimental plant while as bulk Cu followed by biosynthesized CuO-NPs influenced the germination rate as compared to control pots.

CONCLUSIONS

The study drops a concern of research and offers a promising route of developing Copper based green fungicides that can help to combat with modern issues of synthetic fungicides. An average size of 80 ± 15 nm monoclinic cupric oxide (CuO) and cubic cuprous oxides (Cu₂O) nanocrystals that existed in mixed form were successfully developed.

Evaluating satellite-based evapotranspiration estimates for hydrological applications in data-scarce regions: A case in Ethiopia

Water resource development opens up opportunities for improving smallholder farmer livelihoods in sub-Saharan Africa; however, implementation of water resource interventions to ensure sustainability hinges on the availability of sufficient quantity and quality data for monitoring, analysis and planning. Such data is often acquired through instrumentation of water resources (e.g. stream flow monitoring) or the use of hydrological models. In sub-Saharan Africa, data scarcity has limited the ability to monitor and make appropriate decisions for water resource allocation and use. Data derived from remote sensing has been considered a viable option to fill this gap; however, there is limited research in the region that evaluate the quality of the remotely sensed based datasets. This study evaluated actual evapotranspiration (AET) estimates derived from Advanced Very High Resolution Radiometer (AVHRR AET) images and Moderate Resolution Imaging Spectrometer (MOD16 AET) images using estimates from a grid-based Soil and Water Assessment Tool (SWAT). The SWAT model was set up for the entire country of Ethiopia, and calibrated and validated using observed streamflow at several meso-scale watersheds in which satisfactory model performance was obtained. AET estimates from the calibrated and validated SWAT model were then used to evaluate remotely sensed based AET for three landscapes. The AVHRR AET better agreed with the SWAT-simulated AET than the MOD16 AET, although the AVHRR AET overestimated the SWAT-simulated AET in all of the landscapes. Both remotely sensed AET products showed better agreement with the SWAT-simulated AET over agriculture dominated landscapes compared to grassland and forest dominated landscapes. The findings of the study suggest that remotely sensed based AET may help to fine-tune hydrological models in agricultural landscapes in data-scarce regions to improve studies on the impacts of water management interventions aiming to ensure environmental sustainability while enhancing agricultural production, and household income and nutrition.

Power Spectral Density Computation and Dominant Frequencies Identification from the Vibration Sensor Output under Random Vibration Environment

The objective of the modal and spectral analysis is to determine the vibration characteristics of structures such as natural frequencies, dominant frequencies and mode shapes. Such modal and spectral analyses have major relevance to the study of the dynamic properties of the structures undergoing dynamic vibration. Methods for the estimation of the power spectral density and identification of the dominant frequencies from the sensor responses under random vibrating environment are presented in this paper. Periodogram using FFT, Welch Method and MUSIC algorithm are used to analyse the known frequency sinusoids with additive white noise and output of the vibration sensor mounted on the test object. The resultant spectra obtained using the methods and their corresponding errors with the reference spectrum are analysed. The Welch method is further studied with three different windows, namely, Hann, Hamming and Blackman-Harris and with three different overlapping criteria viz. 0%, 25% and 50%. The same algorithm and methodology were adopted and compared in two different platforms: Mathematical Model Simulation and Hardware-In-Loop-Simulation. It is observed from the results that Welch Method with 25% overlap used in combination either with Hann or Blackman-Harris window yields more accurate results, compared to other combinations. Also, 25% overlap provides better execution time trade-off compared to 50% overlap.

Understanding the genetic aspects of resistance to antidepressants treatment

Major depression disorder (MDD) is an extremely prevalent disorder and is expected to be the second leading cause of disease burden by 2020 according to the World Health Organisation (WHO). Moreover, this disease burden is predicted to rise in the next 20 years. Antidepressant medications are vital in the therapy of major depression. However, approximately 30-60% of patients treated with current antidepressant drugs fail to attain remission of depressive symptoms leading to drug resistance. Such patients account for a disproportionately great burden of disease, as supported by cost, augmented disability, and suicidal incidents. Antidepressants resistance remains to challenge mental health care professionals, and more relevant research relating newer medications is necessitated to enhance the quality of life of patients with depression. Enhancement in response rates continues the major challenge in antidepressant research, thus a wealth of potentials still exists concerning the antidepressant resistance for the management of major depression. However, the mechanisms causing resistance to antidepressant treatment remain unknown. Hence, clinical and basic research in understanding the fundamental mechanism of antidepressant resistance should remain a key priority. One potential source accounting for these differences in treatment outcome is genetic variations. The pharmacological mechanisms behind antidepressant response are only partly known but genetic factors play a significant role. Future research of risk factors should assist to advance the understanding of the mechanisms underlying drug resistance in mood disorders and contribute to progress their therapeutic management. Thus, psychiatrists could rely on more effective approaches to treat depressive episodes, reducing the incidence of further drug resistance. This review critically summarises the author's view on many aspects of treatment resistance, specific genetic biomarkers, potential strategies and clinical relevance from both clinical and preclinical studies in drug resistance to antidepressant therapies. Finally, this will allow us to suggest possible recommendations and innovative treatment strategies to improve therapeutic outcomes in managing antidepressant resistance.

Sunlight-Driven Photocatalytic Degradation of Methyl Orange Based on Bismuth Ferrite (BiFeO₃) Heterostructures Composed of Interconnected Nanosheets

Herein, we report the facile microwave-assisted synthesis, characterization and photocatalytic degradation applications of Bismuth ferrite heterostructures composed of interconnected nanosheets (BHNs). The synthesized materials were subjected to several analytical studies such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), Fourier transform infrared (FTIR) spectroscopy and UV-visible spectroscopy in order to examine the morphological, structural, optical and photo catalytic properties. The structural and morphological characterizations confirmed the rhombohedral perovskite crystal structure and the formation of heterostructures composed of interconnected nanosheets for the synthesized material. The compositional characterization revealed that the synthesized material is bismuth ferrite with high purity. The BHNs were further used as efficient photocatalyst for the photocatalytic degradation of highly hazardous pollutant methyl orange under sunlight irradiation. The sunlight driven photocatalytic experiments revealed ~86% photodegradation of methyl orange dye in 150 min. The presented work revealed that the synthesized BHNs are excellent material for the photocatalytic degradation of various organic contaminants and hazardous pollutants.

Visible-Light Driven Photocatalytic Degradation of Eosin Yellow (EY) Dye Based on NiO-WO₃ Nanoparticles

Herein, we report a simple synthesis, characterization and photocatalytic degradation application of composite NiO-WO₃ nanoparticles. The nanoparticles were synthesized by facile low-temperature method and characterized by several techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and UV-Vis diffuse reflectance spectra (DRS). The synthesized NiO-WO₃ nanoparticles were used as efficient photocatalyst for the photocatalytic degradation of Eosin yellow (EY) dye. Interestingly, the synthesized photocatalytic exhibited a significant visible-light driven photocatalytic degradation of Eosin yellow (EY) dye. Under optimized conditions (pH = 5, catalyst dosage = 3 μM and initial dye concentration= 1.0 g/L), the obtained photo degradation of EY dye was above 95% in 180 min under visible light irradiation. Remarkably, reusability of the prepared photocatalyst was also observed and the photo-degradation reactions follow the pseudo-first-order model.

SWAT ungauged: Water quality modeling in the Upper Mississippi River Basin

Improving model performance in ungauged basins has been a chronic challenge in watershed model application to understand and assess water quality impacts of agricultural conservation practices, land use change, and climate adaptation measures in large river basins. Here, we evaluate a modified version of SWAT2012 (referred to as SWAT-EC hereafter), which integrates an energy balanced soil temperature module (STM) and the CENTRUY-based soil organic matter algorithm, for simulating water quality parameters in the Upper Mississippi River Basin (UMRB), and compare it against the original SWAT2012. Model evaluation was performed for simulating streamflow, sediment, and nitrate-N (NO₃-N) and total nitrogen (TN) loadings at three stations near the outlets of UMRB. The model comparison was conducted without parameter calibration in order to assess their performance under ungauged conditions. The results indicate that SWAT-EC outperformed SWAT2012 for stream flow and NO₃-N and TN loading simulation on both monthly and annual scales. For sediment, SWAT-EC performed better than SWAT2012 on a monthly time step basis, but no noticeable improvement was found at the annual scale. In addition, the performance of the uncalibrated SWAT-EC was comparable to other calibrated SWAT models reported in previous publications with respect to sediment and NO₃-N loadings. These findings highlight the importance of advancing process representation in physically-based models to improve model credibility, particularly in ungauged basins.

Global soil, landuse, evapotranspiration, historical and future weather databases for SWAT Applications

Large-scale distributed watershed models are data-intensive, and preparing them consumes most of the research resources. We prepared high-resolution global databases of soil, landuse, actual evapotranspiration (AET), and historical and future weather databases that could serve as standard inputs in Soil and Water Assessment Tool (SWAT) models. The data include two global soil maps and their associated databases calculated with a large number of pedotransfer functions, two landuse maps and their correspondence with SWAT's database, historical and future daily temperature and precipitation data from five IPCC models with four scenarios; and finally, global monthly AET data. Weather data are 0.5° global grids text-formatted for direct use in SWAT models. The AET data is formatted for use in SWAT-CUP (SWAT Calibration Uncertainty Procedures) for calibration of SWAT models. The use of these global databases for SWAT models can speed up the model building by 75-80% and are extremely valuable in areas with limited or no physical data. Furthermore, they can facilitate the comparison of model results in different parts of the world.

Depression and self-harm from adolescence to young adulthood in sexual minorities compared with heterosexuals in the UK: a population-based cohort study

Background

There are few population-based cohort studies of the emergence, development, and persistence of mental health problems in sexual minorities compared with heterosexuals. We compared trajectories of depressive symptoms in sexual-minority adolescents and heterosexual adolescents from when they were aged 10 to 21 years, and examined self-harm at ages 16 and 21 years.

Methods

The study included 4828 adolescents born between April 1, 1991, and Dec 31, 1992, from the Avon Longitudinal Study of Parents and Children birth cohort (Bristol, UK) who reported their sexual orientation when aged 16 years. Depressive symptoms were assessed with the short Mood and Feelings Questionnaire at seven timepoints between ages 10 and 21 years. A self-harm questionnaire was completed at ages 16 and 21 years. Analyses were linear multilevel models with growth curves (depressive symptoms), logistic multilevel models (self-harm in the previous year at ages 16 and 21 years), and multinomial regression (lifetime self-harm with and without suicidal intent at age 21 years).

Findings

At age 10, depressive symptoms were higher in sexual minorities than in heterosexuals and increased with age to a larger extent. Depressive symptoms increased at each timepoint by 0·31 points in hetereosexuals, and by 0·49 points in sexual minorities. Sexual-minority adolescents were more likely than heterosexual adolescents to report self-harm in the previous year at ages 16 and 21 years, with no evidence that this estimate decreased with age. At aged 21, sexual minorities were more likely to report lifetime self-harm (ie, on at least one previous occasion) with suicidal intent than heterosexuals.

Interpretation

Mental health disparities between heterosexuals and sexual minorities are present early in adolescence and increase throughout the school years, persisting to young adulthood. Prevention of these mental health problems and early intervention must be a priority.

P5706Finding predictors and causes of cardiac surgery ICU readmission using machine learning and causal inference

Background

“Bounce-back” to the intensive care unit (ICU) occurs when patients return to the ICU for critical changes in clinical status within the same hospital admission. Bounce-backs post-cardiac surgery increase resource utilisation, total cost of care, are associated with higher mortality and morbidity. However, prediction of bounce-back has proved to be challenging. Previous work addressed the feasibility of predicting bounce-back, but these models required significant physician input to design and calibrate the predictive variables.

Purpose

We aimed to develop an automated machine learning model that would identify patients at risk of bounce-back by selecting the most relevant variables from those available before onset of bounce-back. Additionally, we highlight the differences between predictive and causal inference, to demonstrate that purely associative methods of prediction can mislead clinical decision-making.

Methods

Clinical records of adult cardiac surgery patients between 2011 to 2016 were collected from our institutional Society for Thoracic Surgeons (STS) database and our institutional electronic health record (EHR) system. For bounce-back prediction, an L1 regularised logistic regression model was applied, which also automatically determined important variables with highest prediction effect from the initial 151 variables. For causal inference, the g-computation algorithm was used to compare the differences between causal and predictive regression effects. We quantified the performance of our system on clinically relevant metrics such as specificity, sensitivity, and area under the ROC curve (AUC).

Results

Of the 6189 patients, 357 (5.7%) bounced back to the ICU. The prediction model achieved an AUC score of 0.75 (0.03) and 22% specificity at 95% sensitivity, Further analysis showed 79% of the false positive patients had faced other severe postoperative complications but none of the false negative patients had downstream complications. Subsequent causal analysis revealed that the actual causal effects of treatments differed from the predictive model estimates, e.g. administration of intra-operative tranexamic acid increased the probability of bounce-back by 13% but its causal effect on bounce-back after removing confounders was negligible (an increase of only 0.5%).

Conclusions

Our predictive machine-learning model can successfully predict patients at risk of ICU bounce-backs, using linked STS registry data with the comprehensive electronic health record. The prediction model automatically detects important subset of variables. In addition, we note that causal and predictive model estimates of the same parameters differed, indicating that reliance on predictive models for interventional clinical decision-making may not be appropriate.

Acknowledgement/Funding

National Institutes of Health, Office of Naval Research, Defense Advanced Research Projects Agency

Microbiome digital signature of MCR genes - an in silico approach to study the diversity of methanogenic population in laboratory-developed and pilot-scale anaerobic digesters

The production of biogas by anaerobic digestion (AD) of organic/biological wastes has a firm place in sustainable energy production. A simple and cost-effective anaerobic jar at a laboratory scale is a prerequisite to study the microbial community involved in biomass conversion and releasing of methane gas. In this study, a simulation was carried out using a laboratory-modified anaerobic-jar-converted digester (AD1) with that of a commercial/pilot-scale anaerobic digester (AD2). Taxonomic profiling of biogas-producing communities by means of high-throughput methyl coenzyme-M reductase α-subunit (mcrA) gene amplicon sequencing provided high-resolution insights into bacterial and archaeal structures of AD assemblages and their linkages to fed substrates and process parameters. Commonly, the bacterial phyla Euryarchaeota, Chordata, Firmicutes and Proteobacteria appeared to dominate biogas communities in varying abundances depending on the apparent process conditions. Key micro-organisms identified from AD were Methanocorpusculum labreanum and Methanobacterium formicicum. Specific biogas production was found to be significantly correlating to Methanosarcinaceae. It can be implied from this study that the metagenomic sequencing data was able to dissect the microbial community structure in the digesters. The data gathered indicates that the anaerobic-jar system could throw light on the population dynamics of the methanogens at laboratory scale and its effectiveness at large-scale production of bio-methane. The genome sequence information of non-cultivable biogas community members, metagenome sequencing including assembly and binning strategies will be highly valuable in determining the efficacy of an anaerobic digester.

A review of the safety of MRI in cochlear implant patients with retained magnets

The number of patients with cochlear implants (CIs) is increasing due to expanding indications, and improving CI services. Furthermore, as the use of imaging increases in clinical medicine, it is increasingly likely that patients with CIs will require a magnetic resonance imaging (MRI) examination during their lifetime. Therefore it is important that clinicians are aware of the safety aspects and manufacturer recommendations for CI patients with retained magnets. This article summarises guidelines from all major CI manufacturers and reviews the published literature on the safety of MRI in CI patients with magnets in situ. The most commonly reported complication of MRI in CI patients was pain. Other significant complications included magnet displacement, depolarisation, and polarity reversal. Artefacts caused by the CI remain an issue, but may be reduced by the use of specific sequences. Manufacturer recommendations should be followed to reduce the risk of complications, although complications may occur even when guidelines are followed. For this reason, the indication for imaging these patients should be reviewed, and patients should be appropriately counselled and consented.

A Systematic Review of Group Social Skills Interventions, and Meta-analysis of Outcomes, for Children with High Functioning ASD

Group social skills interventions (GSSIs) are a commonly offered treatment for children with high functioning ASD. We critically evaluated GSSI randomised controlled trials for those aged 6–25 years. Our meta-analysis of outcomes emphasised internal validity, thus was restricted to trials that used the parent-report social responsiveness scale (SRS) or the social skills rating system (SSRS). Large positive effect sizes were found for the SRS total score, plus the social communication and restricted interests and repetitive behaviours subscales. The SSRS social skills subscale improved with moderate effect size. Moderator analysis of the SRS showed that GSSIs that include parent-groups, and are of greater duration or intensity, obtained larger effect sizes. We recommend future trials distinguish gains in children’s social knowledge from social performance.

Mental health and behavioural problems in children with XXYY: a comparison with intellectual disabilities

BACKGROUND

The phenotype of children with XXYY has predominantly been defined by comparison to other sex chromosome aneuploidies trisomies affecting male children; however, the intellectual ability of children with XXYY is lower than children with other sex chromosome aneuploidies trisomies. It is not known to what extent the phenotype identified to date is specific to XXYY, rather than a reflection of lower IQ. This study evaluates the mental health and behaviour of children with XXYY, in comparison to children with intellectual disabilities of heterogeneous genetic origin.

METHODS

Fifteen children with XXYY and 30 controls matched for age (4-14 years), sex and intellectual ability were ascertained from the IMAGINE ID study. IMAGINE ID participants have intellectual disabilities due to genetic anomalies confirmed by National Health Service Regional Genetic Centre laboratories. The mental health and behaviour of participants was examined with the Development and Well-being Assessment and the Strengths and Difficulties Questionnaire.

RESULTS

Children with XXYY experienced significantly more frequent and intense temper outbursts than the control group.

CONCLUSION

Our results suggest that temper outbursts may be specifically associated with the XXYY phenotype. These problems have a significant impact on the daily lives of boys with XXYY and their families. It is crucial to ensure that families are well supported to manage these difficulties.