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Maturity-onset diabetes of young ‘MODY’ type 6 is a rare form of monogenic diabetes caused by mutations in neuronal differentiation 1 (NEUROD1). Clinical features vary in a large spectrum in terms of age and body mass index (BMI) at diagnosis. Here, we reported the youngest patient with a NEUROD1 variant to the best of our knowledge. A 2.1-year-old girl was referred to pediatric endocrinology clinic for elevated fasting BG (104 mg/dL) which was detected at another center where she had been evaluated for loss of appetite. Her maternal aunt and uncle had been diagnosed with type 2 diabetes mellitus (DM) at the age of 40 and 45 years; they were obese (BMI: 30.2 and 30.6 kg/m2). At the age of 3.7 years old, she was hospitalized for buccal cellulitis and plasma glucose concentration was 239 mg/dL at admission. Targeted next-generation sequencing (NGS) was performed considering the stress induced hyperglycemia without serious illness, negative islet cell antibodies and insulin autoantibodies, age at the presentation, and family history of DM. NGS analysis revealed a previously reported heterozygous missense variant in NEUROD1. Segregation studies showed that the identified variant was inherited from her 44-year-old mother with a BMI of 27.2 kg/m2 and a normal oral glucose tolerance test. Heterozygous NEUROD1 mutations cause low-penetrant diabetes that is heterogeneous in terms of clinical features as some patients fulfill the classic MODY definition and others are mimicking type 2 DM. Clinical manifestations and family history should be carefully evaluated in patients with stress induced hyperglycemia to identify candidate cases for molecular testing, and proper follow-up should be initiated in affected individuals.

Glucose 6 phosphate dehydrogenase (G6PD) is expressed in all tissues and is necessary to maintain oxidant stress capacity of cells. G6PD deficiency is the most common enzymopathy in humans and is among the important causes of hemolytic anemia. It has been reported that severe hemolytic anemia due to G6PD deficiency may develop in newly diagnosed diabetes, especially during the correction of hyperglycemia. To date, nine cases have been published. Genetic analysis was not performed for G6PD deficiency in these published patients. We present a case of hemolytic anemia due to G6PD deficiency secondary to newly diagnosed type 1 diabetes mellitus. Genetic testing was performed for the index patient and revealed a previously reported missense pathogenic variant (c.653C>T; p.Ser218Phe) in the G6PD gene.

We have developed a silver-based hafnium oxide (HfO2/Ag/HfO2) thin film deposition device through electron beam evaporation on a commercial glass substrate at various substrate temperatures. An atomic force microscope (AFM) was used to investigate the surface characteristics of developed HfO2/Ag/HfO2 tri-layer device and optical properties were investigated by using dual beam spectrophotometer. The SiN AFM tip was illuminated by blue (488 nm) or green (532 nm) laser light. Overall transmittance values changed from 40 to 80%, 56 to 74% and 25 to 100% in ultraviolet-visible-infrared (UV-VIS-IR) regions when the glass substrate was at room temperature, 100oC and 150oC, respectively. Percentage reflectance values were found to be almost constant when the glass substrate was at room temperature and 100oC. Further increases in the glass substrate temperature up to 150oC caused reflectance of the thin film HfO2/Ag/HfO2 film to increase by around 70% in the VIS-IR regions. [ABSTRACT FROM AUTHOR]

This paper proposes two novel approaches based on feature weighting and model selection for building more accurate kNN ensembles. The first approach identifies the nearest observations using a feature weighting scheme concerning the response variable via support vectors. A randomly selected subset of features is used for the feature weighting and model construction. After building a sufficiently large number of base models on bootstrap samples, a subset of the models is selected based on out-of-bag prediction error for the final ensemble. The second approach builds base learners build on random subsamples instead of bootstrap samples with a random subset of features. The method uses feature weighting while building the models. The remaining observations from each sample are used to assess the corresponding base learner and select a subset of the models for the final ensemble. The suggested ensemble methods are assessed on 12 benchmark datasets against other classical methods, including kNN-based models. The analyses reveal that the proposed methods are often better than the others.

High pressure investigations of matter involve the study of strong shock wave dynamics within the materials which gives rise to many thermal effects leading to dissociation of molecules, ionization of atoms, and radiation emission, etc. The response of materials experiencing a strong shock can be determined by its shock Hugoniot calculations which are frequently applied in numerical and experimental studies in inertial confinement fusion, laboratory astrophysical plasma, etc. These studies involve high energy density plasmas in which the radiation plays an important role in determining the energy deposition and maximum compressibility achieved by the shock within material. In this study, we present an investigation for the effect of radiation pressure on the maximum compressibility of the material using shock Hugoniot calculations. In shock Hugoniot calculations, an equation of state (EOS) is developed in which electronic contributions for EOS calculations are taken from an improved screened hydrogenic model with –l splitting (I-SHML) [High Energy Density Physics (2018) 26 48] under local thermodynamic equilibrium (LTE) conditions. The thermal ionic part calculations are adopted from the state of the art Cowan model while the cold ionic contributions are adopted from the scaled binding energy model. The Shock Hugoniot calculations are carried out for sodium and iron plasmas and our calculated results show excellent agreement with published results obtained by using either sophisticated self-consistent models or the first principle study. [ABSTRACT FROM AUTHOR]

Ensembles based on $k$ NN models are considered effective in reducing the adverse effect of outliers, primarily, by identifying the closest observations to a test point in a given training data. Class label of the test point is estimated by taking a majority-vote of the nearest observations’ class labels. While identifying the closest observations, certain training patterns might possess high regulatory power than the others. Therefore, assigning weights to observations and then calculating weighted distances are deemed important in addressing this scenario. This paper proposes a $k$ NN ensemble that identifies nearest observations based on their weighted distance in relation to the response variable via support vectors. This is done by building a large number of $k$ NN models each on a bootstrap sample from the training data along with a randomly selected subset of features from the given feature space. The estimated class of the test observation is decided via majority voting based on the estimates given by all the base $k$ NN models.The ensemble is assessed on 14 benchmark and simulated datasets against other classical methods, including $k$ NN based models using Brier score, classification accuracy and Kappa as performance measures. On both the benchmark and simulated datasets, the proposed ensemble outperformed the other competing methods in majority of the cases. It gave better overall classification performance than the other methods on 8 datasets. The analyses on simulated datasets reveal that the proposed method is effective in classification problems that involve noisy features in the data. Furthermore, feature weighting and randomization also make the method robust to the choice of $k$ , i.e., the number of nearest observations in a base model.

This study proposes a supervised feature selection technique for classification in high dimensional binary class problems by adding robustness in the conventional Fisher Score. The proposed method utilizes the more robust measure of location i.e. the Median and measure of dispersion known as Rousseeuw and Croux statistic ( $Q_{n}$ ). Initially minimum subset of genes is identified by the Greedy search approach, which is then combined with the top ranked genes obtained via the proposed Robust Fisher Score (RFish). Finally to remove redundancy in the selected genes, Least Absolute Shrinkage and Selection Operator (LASSO) has been applied. The proposed method is validated on five publicly available datasets. The results of the proposed method are compared with six well known feature selection methods based on prediction performance via Random Forest (RF), Support Vector Machine (SVM) and $k$ Nearest Neighbour ( $k$ -NN) classifiers. Box-plots and Bar-plots of the results of the proposed method and all the other methods considered in the manuscript are also given. The Results show that the proposed method (RFish) performs better than all the other methods in majority of the cases. The paper gives a detailed simulation study to further assess the proposed method.

Systemic pseudohypoaldosteronism (PHA) is a rare, salt-wasting syndrome that is caused by inactivating variants in genes encoding epithelial sodium channel subunits. Hyponatremia, hyperkalemia, metabolic acidosis, increased aldosterone and renin levels are expected findings in PHA. Clinical management is challenging due to high dose oral replacement therapy. Furthermore, patients with systemic PHA require life-long therapy. Here we report a patient with systemic PHA due to SCNN1B variant whose hyponatremia and hyperkalemia was detected at the 24th hour of life. Hyperkalemia did not improve with conventional treatments and dialysis was required. He also developed myocarditis and hypertension in follow-up. Challenges for diagnosis and treatment in this patient are discussed herein. In addition, published evidence concerning common features of patients with SCNN1B variant are reviewed.

INTRODUCTION: It was aimed to evaluate the etiology, clinical, laboratory and imaging findings and treatment methods of patients who have admitted with acute pancreatitis (AP) and progressed to chronic pancreatitis (CP) with ARP (acute recurrent pancreatitis). METHODS: The data of children under the age of 18 years who were admitted to our hospital between January 2013-July 2020 and were diagnosed with acute, acute recurrent or chronic pancreatitis according to INSPPIRE diagnostic criteria were evaluated retrospectively. RESULTS: There were 77 patients who were followed-up with the diagnosis of acute pancreatitis. Pancreatitis attack did not recur in 53/77 patients and no underlying cause was found in 35.84% (19/53) of the patients. The most common factor in those whose cause could be determined was gallstones (15.1%) (8/53). The pancreatitis attack recurred in 24 (31%) of the patients. Congenital anomalies (9/24) and hereditary pancreatitis (5/24) were the most common causes of pancreatitis in these patients and these factors were a risk factor for the recurrence of pancreatitis attack. There was no difference between the groups in terms of complications (p=0.423); however, chronicity was more common in the group with ARP (p=0.003). DISCUSSION AND CONCLUSION: Beside the pancreatitis is a rare disease in childhood, with the increase of awareness and increased accessibility to diagnostic imaging methods, more and more pancreatitis is diagnosed day by day. Idiopathic acute pancreatitis cases still constitute the largest group. If other causes are excluded in these cases, it is important to investigate congenital anomalies, genetic and metabolic etiologies.

The effect of training data size on machine learning methods has been well investigated over the past two decades. The predictive performance of tree based machine learning methods, in general, improves with a decreasing rate as the size of training data increases. We investigate this in optimal trees ensemble (OTE) where the method fails to learn from some of the training observations due to internal validation. Modified tree selection methods are thus proposed for OTE to cater for the loss of training observations in internal validation. In the first method, corresponding out-of-bag (OOB) observations are used in both individual and collective performance assessment for each tree. Trees are ranked based on their individual performance on the OOB observations. A certain number of top ranked trees is selected and starting from the most accurate tree, subsequent trees are added one by one and their impact is recorded by using the OOB observations left out from the bootstrap sample taken for the tree being added. A tree is selected if it improves predictive accuracy of the ensemble. In the second approach, trees are grown on random subsets, taken without replacement-known as sub-bagging, of the training data instead of bootstrap samples (taken with replacement). The remaining observations from each sample are used in both individual and collective assessments for each corresponding tree similar to the first method. Analysis on 21 benchmark datasets and simulations studies show improved performance of the modified methods in comparison to OTE and other state-of-the-art methods.

Kaynakların iyi yönetimi ve bölgede yaşayan halkın yaşam kalitesinin artırılmasını da göz önüne alan "yerelde kalkınma" anlayışı kentlerin yaşanabilirliği ve kalkınması için mihenk taşıdır. Aralık 2012'de çıkarılan 6360 sayılı kanun ile büyükşehir belediyesi sayılabilmek için gerekli olan nüfus sayısı değiştirilmiş, yerel yönetimlerin kamu kişilikleri kaldırılmış veya düzenlenmiş ve aynı zamanda yeni izleme ve koordinasyon başkanlıklarının kurulmasının önü açılmıştır. 30 büyükşehir belediyesinde, kentsel alanlarla kırsal alanlar arasındaki iletişimi güçlendirecek “Büyükkent Yönetimi” olarak tanımlanan yeni bir oluşum ortaya çıkmıştır. Yerel yönetimlerin başarısı küresel gelişmeleri de dikkate alarak kurumu geliştirebilmesi, yerelin uygulamalarını küresel ölçekte de tanıtabilmesi, sunabilmesi ve yenilikler getirebilmesine bağlıdır. Bu nedenle yerel yönetimler ekonomik kalkınma doğrultusunda verilerin doğru bilgilere dönüştürülmesi için çaba sarf ederek, örneğin İzmir Modeli kapsamında, Tarımsal Gelişme ve Yerleşme Stratejisi kapsamında da Yerelden Kırsal Kalkınma, Yenilikçi Ortak Kullanımlar, Yerellikte Yaratıcılık, Çevre ve Atık Yönetiminde Doğa Asıllı Çözümler gibi politikalarla çalışmalarına yön vermişlerdir. Uygulamalarda küçük toprak sahiplerinin korunması ve yönlendirilmesi, tarımda verimliliğin artırılması ve pazarlama darboğazlarının giderilmesi için kooperatifler ve birlikler teşvik edilmiş, ekolojik sürdürülebilirlik konusunda yürütülen projeler aracılığıyla sürdürülebilirliğin diğer alt boyutu ekonomik sürdürülebilirlik konusu ivmelendirilmiştir. Çalışma; ekonomik ve teknolojik gelişmeleri temel alan, Türkiye’ de ekonomik değişim, sosyal değişim ve çevresel değişimi bütünleştirmeye yönelik bu çabaları destekleyen politikalardan biri olan tarımsal politikaları Büyükşehir Belediyeleri süreçleri kapsamında ele almakta, kırsal kesim ile kent arasındaki iletişimi ve işbirliğini güçlendirmeye dayalı iyileştirme önerileri sunarak, yaşanılan ve yaşanabilecek zorlukların giderilmesine yardımcı olacak bir model önerisi sunmaktadır.

In this paper, a novel feature selection method called Robust Proportional Overlapping Score (RPOS), for microarray gene expression datasets has been proposed, by utilizing the robust measure of dispersion, i.e., Median Absolute Deviation (MAD). This method robustly identifies the most discriminative genes by considering the overlapping scores of the gene expression values for binary class problems. Genes with a high degree of overlap between classes are discarded and the ones that discriminate between the classes are selected. The results of the proposed method are compared with five state-of-the-art gene selection methods based on classification error, Brier score, and sensitivity, by considering eleven gene expression datasets. Classification of observations for different sets of selected genes by the proposed method is carried out by three different classifiers, i.e., random forest, k-nearest neighbors (k-NN), and support vector machine (SVM). Box-plots and stability scores of the results are also shown in this paper. The results reveal that in most of the cases the proposed method outperforms the other methods.

Abstract Objectives: The aim of this study is to filter out the most informative genes that mainly regulate the target tissue class, increase classification accuracy, reduce the curse of dimensionality, and discard redundant and irrelevant genes. Methods: This paper presented the idea of gene selection using bagging sub-forest (BSF). The proposed method provided genes importance grounded on the idea specified in the standard random forest algorithm. The new method is compared with three state-of-the art methods, i.e., Wilcoxon, masked painter and proportional overlapped score (POS). These methods were applied on 5 data sets, i.e. Colon, Lymph node breast cancer, Leukemia, Serrated colorectal carcinomas, and Breast Cancer. Comparison was done by selecting top 20 genes by applying the gene selection methods and applying random forest (RF) and support vector machine (SVM) classifiers to assess their predictive performance on the datasets with selected genes. Classification accuracy, Brier score, and sensitivity have been used as performance measures. Results: The proposed method gave better results than the other methods using both random forest and SVM classifiers on all the datasets among all the feature selection methods. Conclusion: The proposed method showed improved performance in terms of classification accuracy, Brier score and sensitivity, and hence, could be used as a novel method for gene selection to classify tissue samples into their correct classes. Key Words: Gene selection, classification, random forest, cancer, microarray gene expression.

Poor seedling germination and growth can result in large financial losses for farmers, thus, there is an urgent need for sustainable agricultural techniques to enhance seed germination and early growth. As an outcome, sustainable agriculture-which emphasizes the smart and effective utilization of resources-has gained popularity worldwide. At numerous levels, the field of nanotechnology is capable of significant benefit in achieving sustainable agricultural practices. Zinc oxide nanoparticles (ZnO NPs) have been shown to have biostimulatory properties and serve as effective solutions for addressing environmental and biotic stressors. The purpose of this study, investigating Salvadora persica halophytic leaf extract -synthesized zinc oxide nanoparticles (S-ZnONPs) as nano-priming agents to ensure okra seeds germinated under stress-free conditions. From an application perspective, we examined the effect of seed priming with varying concentrations of S-ZnO NPs (0, 20 and 40 ppm) for 18 and 24 h of soaking. Results indicated that the germination rate of hybrid variety improved with 20 ppm at 18 h, increasing by 58.22%, while mean germination time reduced by 24.62%. An enhancement trend was observed in the shoot, root length, shoot and root fresh weight, shoot and root dry weight of hybrid variety at 20ppm with 18 h priming by 34.2, 84.3, 80.2, 47.4, 50.3, and 36.2%, respectively. However, chlorophyll pigments chl a, chl b, and carotenoids was significantly raised in desi variety by 42.4, 79.31, and 142.29% with 20 ppm at 18 h priming. Hydrogen per oxide decreased up to 87.8% with 40 ppm at 24 h in hybrid variety, while, in desi variety H 2 O 2 was reduced 88.3% with 20 ppm at 24 h. Non enzymatic antioxidant activities such as ascorbic acid, was highly increased 130.6% in hybrid at 24 h priming with 20 ppm dose. Flavonoids raised in same variety by 166.1% with 20 ppm at 18 h. Proline content was increased by 144.5% with 40ppm at 18 h. Moreover, Antioxidant enzymes, superoxide dismutase, peroxidase and catalase were significantly increased in both varieties with both levels of S-ZnO NPs and priming time. This cost-effective and environmentally safe technique to produce nanoparticles of different halophytic plants can maximize resource utilization, supporting sustainable agriculture by minimizing adverse environmental effects without compromising efficiency., (© 2024. The Author(s).)

Globally, salinity is an important abiotic stress in agriculture. It induced oxidative stress and nutritional imbalance in plants, resulting in poor crop productivity. Applying silicon (Si) can improve the uptake of macronutrients. On the other hand, using biochar as a soil amendment can also decrease salinity stress due to its high porosity, cation exchange capacity, and water-holding capacity. That's why the current experiment was conducted with novelty to explore the impact of silicon nanoparticle-based biochar (Si-BC) on wheat cultivated on salt-affected soil. There were 3 levels of Si-BC, i.e., control (0), 1% Si-BC1, and 2.5% Si-BC2 applied in 3 replicates under 0 and 200 mM NaCl following a completely randomized design. Results showed that treatment 2.5% Si-BC2 performed significantly better for the enhancement in shoot and root length, shoot and root fresh weight, shoot and root dry weight, number of leaves, number of tillers, number of spikelets, spike length, spike fresh and dry weight compared to control under no stress and salinity stress (200 mM NaCl). A significant enhancement in chlorophyll a (~ 18%), chlorophyll b (~ 22%), total chlorophyll (~ 20%), carotenoid (~ 60%), relative water contents (~ 58%) also signified the effectiveness of treatment 2.5% Si-BC2 than control under 200 mM NaCl. In conclusion, treatment 2.5% Si-BC2 can potentially mitigate the salinity stress in wheat by regulating antioxidants and improving N, K concentration, and gas exchange attributes while decreasing Na and Cl concentration and electrolyte leakage. More investigations at the field level are recommended for the declaration of treatment 2.5% Si-BC2 as the best amendment for alleviating salinity stress in different crops under variable climatic conditions., (© 2024. The Author(s).)

Chemical modifications of CRISPR-Cas nucleases help decrease off-target editing and expand the biomedical applications of CRISPR-based gene manipulation tools. Here, we found that epigenetic modifications of guide RNA, such as m6A and m1A methylation, can effectively inhibit both the cis - and trans -DNA cleavage activities of CRISPR-Cas12a. The underlying mechanism is that methylations destabilize the secondary and tertiary structure of gRNA which prevents the assembly of the Cas12a-gRNA nuclease complex, leading to decreased DNA targeting ability. A minimum of three adenine methylated nucleotides are required to completely inhibit the nuclease activity. We also demonstrate that these effects are reversible through the demethylation of gRNA by demethylases. This strategy has been used in the regulation of gene expression, demethylase imaging in living cells and controllable gene editing. The results demonstrate that the methylation-deactivated and demethylase-activated strategy is a promising tool for regulation of the CRISPR-Cas12a system., Competing Interests: The authors declare no competing financial interest., (This journal is © The Royal Society of Chemistry.)

Chromium is a highly toxic heavy metal. High concentrations of Cr (III) can affect metabolic processes in plants, resulting in different morphological, physiological, and biochemical defects. Agricultural practices such as sewage irrigation, over-fertilization, and sewage sludge application contribute significantly to Cr contamination. It can reduce the growth of plants by affecting the activity of antioxidant enzymes. The materials in nano form play an important role in nano-remediation and heavy metals absorption due to their high surface area and micropores. This research was conducted to study the potential of foliar application of nanobiochar/nBC (100 mg/L -1 and 150 mg/L -1 ) for mitigation of Cr (III) stress (200 mg/kg and 300 mg/kg) in black cumin (Nigella sativa) plants. The results showed that increased Cr stress (300 mg/kg) decreased the plant growth parameters, chlorophyll content, total soluble sugars, and proteins. However, increased the level of hydrogen peroxide (H 2 O 2 ) and malondialdehyde acetate (MDA) as a result of the activity of antioxidant enzymes (Catalase, Superoxide dismutase, peroxidase dismutase, and ascorbic peroxidase) increased in Nigella sativa seedlings. Foliar application of the nBC (100 mg/L -1 ) increased plant growth parameters, chlorophyll content, and osmoprotectants, while decreasing the levels of oxidative stress markers (H 2 O 2 and MDA). Furthermore, with the application of nBC, the antioxidant enzyme activity considerably improved. Improved antioxidant activity shows that nBC helped to decrease oxidative stress, which in return improved the growth of Nigella sativa seedlings. Overall, present study findings concluded that foliar application of nBC in Nigella sativa seedlings improved growth, chlorophyll, and antioxidant enzymes. The nBC treatment of 100 mg/L -1 showed better results compared to 150 mg/L -1 under chromium stress., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)

Chromium (Cr) is a hazardous metal that has a significant risk of transfer from soil to edible parts of food crops, including shoot tissues. Reduction of Cr accumulation is required to lower the risk of Cr-exposed in humans and animals feeding on metal-contaminated parts of such plant. Zea mays is a global staple crop irrigated intensively with Cr-contaminated water. Consequently, the objective of this study was to investigate that FI-stabilized ZnO NPs could be used as an eco-friendly and efficient amendment to reduced Cr uptake and toxicity in Zea mays. To investigate the growth parameters, physiological, oxidative stress and biochemical parameters under different Cr-VI concentrations (10.0, 15.0, and 20.0 ppm). Cr exposed Z. mays plants exhibited substantially reduced plant biomass, chlorophyll contents, and altered antioxidant enzyme activity compared to untreated control. The results revealed that foliar application of Fagonia-ZnO-NPs helps eliminate the harmful effects of Cr (VI), which can enter plants through soil pollution. Increased levels of proline, soluble sugars and various antioxidant enzymes reflected this. Mean comparisons showed that Cr stress led to a 33-50% reduction in fresh shoot weight, 73-170% in fresh root weight, 16-34% shoot length, 9.5-129% root length, Chlorophyll contents 20-33% (Chl a), 18-27% (Chl b) and 17-27% (car), 14-33% total soluble sugars, 54-170% proline content, 7-7.5% POD, 0.66-75% CAT and 32-77% APX enzyme activities compared to untreated plants. Application of FI-stabilized ZnO NPs led to an increase 21-77% in fresh shoot weight, 22-45%, fresh root weight, 3-35% shoot length, 24-154% root length, Chlorophyll contents 39-60% (Chl a), 15-79% (Chl b) and 28-82% (car), 19-52% total soluble sugars, 21-55% proline content, 14-43% POD, 34-95% CAT and 130-186% APX enzyme activities under 10, 15 and 20 ppm Cr stress respectively, compared to Cr-treated plants. However, the principal component analysis revealed that chlorophyll contents, carotenoid, CAT, APX and length were in the same group and showed a positive correlation. These data collectively suggest that phytostabilized zinc oxide NPs may be an eco-friendly solution to mitigate Cr toxicity in agricultural soils and crop plants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)

Among heavy metals, cadmium (Cd) is one of the toxic metals, which significantly reduce the growth of plants even at a low concentration. Cd interacts with various plant mechanisms at the physiological and antioxidant levels, resulting in decreased plant growth. This research was conducted to exploit the potential of synergistic application of zinc oxide nanoparticles (ZnO NPs) and Moringa oleifera leaf extract in mitigation of Cd stress in linseed ( Linum usitatissimum L.) plants. The main aim of this study was to exploit the role of M. oleifera leaf extract and ZnO NPs on Cd-exposed linseed plants. Cd concentrations in the root and shoot of linseed plants decreased after administration of MZnO NPs. Growth parameters of plants, antioxidant system, and physiochemical parameters decreased as the external Cd level increased. The administration of MZnO NPs to the Cd-stressed linseed plant resulted in a significant increase in growth and antioxidant enzymes. Furthermore, the antioxidative enzymes superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) exhibited a considerable increase in the activity when MZnO NPs were applied to Cd-stressed seedlings. The introduction of MZnO NPs lowered the levels of malondialdehyde (MDA) and hydrogen peroxide (H 2 O 2 ) in the linseed plant grown in Cd-toxic conditions. The NPs decreased electrolyte leakage (EL) in Cd-stressed linseed leaves and roots. It was concluded that synergistic application of ZnO NPs and M. oleifera leaf extract alleviated Cd stress in linseed plants through enhanced activity of antioxidant enzymes. It is proposed that role of MZnO NPs may be evaluated for mitigation of numerous abiotic stresses., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ramzan, Ayub, Shah, Naz, Shah, Malik, Sardar, Telesiński, Kalaji, Dessoky and Elgawad.)

In the current study, dahllite/hydroxyapatite/collagen filler extracted via calcination of wasted chicken bone was blended with PSf polymer to obtain highly biocompatible, and antifoulant hemodialysis membranes. FTIR and Raman spectroscopic analysis was done to obtain information about the bonding chemistry of the obtained filler. The intermolecular interaction that existed between dahllite/hydroxyapatite/collagen filler and pristine PSf was confirmed by Raman spectroscopic study. The PSf polymer exhibited a sponge-like structure owing to its high thickness and slow exchange with non-solvent in coagulation bath whilst the instantaneous de-mixing course produced finger-like capillaries in dahllite/hydroxyapatite/collagen filler based PSf membranes as exposed by SEM photographs. The presence of different wt. % of filler composition in the PSf matrix improved the mechanical strength as revealed by fatigue analysis. The hydrophilic character improved by 78% while leaching consistency adjusted to 0%-4%. Pure water permeation (PWP) flux improved by nine times. The pore profile improved with the addition of filler as revealed by hydrophilicity experiment, PWP flux, and SEM micrographs. Fouling evaluation results disclosed that filler based membranes showed 36% less adsorption of protein (BSA) solution together with more than 84% flux recovery ratio. The biocompatibility valuation analysis unveiled that membranes composed of filler showed extended prothrombin and thrombin coagulation times, reduced activation of fibrinogen mass, and less adhesion of plasma proteins in comparison with pristine PSf membrane. The adsorption capacity of fabricated membranes for urea and creatinine improved by 31% (in the case of urea) and 34% (in the case of creatinine) in contrast with pristine PSf membrane. The overall results showed that the M-3 membrane was optimized in terms of surface properties, protein adhesion, anticoagulation activity, and adsorption amount of urea and creatinine.

Silver nanowires (AgNWs) with ultrahigh purity and high yield were successfully synthesized by employing a modified facile polyol method using PVP as a capping and stabilizing agent. The reaction was carried out at a moderate temperature of 160 °C under mild stirring for about 3 h. The prepared AgNWs exhibited parallel alignment on a large scale and were characterized by UV-vis spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), and PL spectroscopy. The luminescent AgNWs exhibited red emission, which was accredited to deep holes. The SEM results confirmed the formation of AgNWs of 3.3 to 4.7 µm in length with an average diameter of about 86 nm, that is, the aspect ratio values of the AgNWs exceeded 45. An ink consisting of hydroxyethyl cellulose (HEC) and AgNWs was transferred to polyethylene terephthalate (PET) films by simple mechanical pressing. The PET films retained transparency and flexibility after the ink coating. The maximum transmittance value of as-prepared PET films in the visible region was estimated to be about 92.5% with a sheet resistance value of ca. 20 Ω/sq. This makes the films a potential substitute to commonly used expensive indium tin oxide (ITO) in the field of flexible optoelectronics., (Copyright © 2021, Naz et al.)

High resistance to antimicrobials is associated with biofilm formation responsible for infectious microbes to withstand severe conditions. Therefore, new alternatives are necessary as biofilm inhibitors to control infections. In this study, the antimicrobial and antibiofilm activities of Fagonia indica extracts were evaluated against MDR clinical isolates. The extract exhibited its antibiofilm effect by altering adherence and disintegration of bacterial cell wall. Fagonia indica has antibacterial effect as minimum inhibitory concentration (MIC) values ranging from 125 to 500 µg mL-1 and minimum bactericidal concentration (MBC) value was 500-3000 µg mL-1 against multidrug resistant (MDR) clinical isolates. The extract exhibited its antibiofilm effect by altering adherence and disintegration of bacterial cell wall. Fagonia indica had antibacterial effect as minimum inhibitory concentration (MIC) values ranging from 125 to 500 µg mL-1 and minimum bactericidal concentration (MBC) value was 500-3000 µg mL-1 against MDR isolates. The maximum inhibitory effects of Fagonia indica chloroform extract on biofilm formation was observed on Staphylococcus aureus (71.84%) followed by Klebsiella pneumoniae (70.83%) after 48 hrs showing that inhibition is also time dependent. Our results about bacterial cell protein leakage indicated that MDR isolates treated with chloroform extract of Fagonia indica showed maximum protein leakage of K. pneumoniae (59.14 µg mL-1) followed by S. aureus (56.7 µg mL-1). Cell attachment assays indicated that chloroform extract resulted in a 43.5-53.5% inhibition of cell adherence to a polystyrene surface. Our results revealed that extracts of Fagonia indica significantly inhibited biofilm formation among MDR clinical isolates, therefore, could be applied as antimicrobial agents and cost effective biofilm inhibitor against these MDR isolates.

Non-covalent electrostatic interaction between amide nitrogen and carbonyl carbon of shorter chain length of polyvinylpyrrolidone (PVP-k25) was developed with in-house carboxylic oxidized multiwall carbon nanotubes (O-MWCNT) and then blended with Polyethersulfone (PES) polymer. FTIR analysis was utilized to confirm bonding nature of nano-composites (NCs) of O-MWCNT/PVP-k25 and casting membranes. Non-solvent induces phase separation process developed regular finger-like channels in composite membranes whereas pristine PES exhibited spongy entities as studied by cross sectional analysis report of FESEM. Further, FESEM instrument was also utilized to observe the dispersion of O-MWCNT/PVP based nanocomposite (NCs) with PES and membranes leaching phenomena analysis. Contact angle experiments described 24% improvement of hydrophilic behaviour, leaching ratio of additives was reduced to 1.89%, whereas water flux enhanced up to 6 times. Bovine serum albumin (BSA) and lysozyme based antifouling analysis shown up to 25% improvement, whereas 84% of water flux was regained after protein fouling than pristine PES. Anticoagulant activity was reported by estimating prothrombin, thrombin, plasma re-calcification times and production of fibrinogen cluster with platelets-adhesions photographs and hemolysis experiments. Composite membranes exhibited 3.4 and 3 times better dialysis clearance ratios of urea and creatinine solutes as compared to the raw PES membrane., (Copyright © 2019 Elsevier B.V. All rights reserved.)

This work is the first report describing the solution grown 3D manganese oxide nanofibrous (MnO 2 NFs) mesh and its potential for the simultaneous detection of biomolecules such as ascorbic acid and uric acid. The mesh is synthesized by a facile, one-pot, and cost-effective hydrothermal approach without using any template or structure directing compound. The morphology consists of randomly placed nanofibres possessing a diameter in the range of 10-25 nm, and length of several micron; constituting a highly porous and flexible material. The electrochemical potential was examined by recording cyclic voltammetry signals towards ascorbic acid and uric acid. The special mesh morphology offers a large surface area to promote enhanced electrochemical activity, and also provided a macroporous network that supported efficient mass transport. Additionally, the strong electronic cloud and roughness of MnO 2 NFs mesh facilitated the fast oxidation of species at very low potential. The lower detection limit was found to be 1.33 µM (S/N = 3) and 1.03 µM (S/N = 3) for ascorbic acid and uric acid, respectively. The MnO 2 NFs mesh modified electrodes can robustly differentiate both of them by giving well separate signals (Δ = 500 mV) indicating capability of the material towards selective detection. The sensor has been successfully applied to human blood and urine samples and the recoveries were found statistically significant. These results demonstrate the practical feasibility of 3D mesh to develop sensors for the accurate diagnosis of clinically important molecules., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background & Objectives: Lipoprotein-A has been recognized as a risk factor for ischemic heart diseases. Myocardial infarction (MI) is common complication of ischemic heart disease. Diabetes play an incremental role in the development of coronary artery disease (CAD), however still there are conflicting data regarding the relationship of Lipoprotein-B and MI. We therefore wanted to evaluate the relationship of Lipo-B, MI and diabetes mellitus. Our objective was to determine the non-fasting Apo-lipoprotein B and triglycerides level among type II diabetic patients with ischemic heart disease and to compare with type II diabetic without ischemic heart disease., Methods: This was cross sectional study where two groups of patients were recruited in the study, Group-I included patient with Ischemic Heart Disease and diabetes while Group-II comprised of diabetes without Ischemic Heart Disease. Age, sex and basic demographic matching was done between the two groups. Data were collected using random sample. The comparative approach was used to see the role of diabetes in the elevation of Apo-lipoprotein B level, which is a risk factor for Ischemic heart diseases., Results: Two hundred forty eight patients (Cases: 123 Diabetic with myocardial infarction and (Control: 125 Diabetic without myocardial infarction) were included in the study. Mean Apo-B among diabetic patients with myocardial infarction was high (68.3±24.23 ng/ml) compared to non-cardiac patients (49.97±33.880 ng/ml) with a p <0.000. Marked difference was also observed in triglycerides levels where it was found very high (301.4±55.1 mg/dL) in patients of diabetes with myocardial infarction as compared to subjects without MI (137.7±84.7 mg/dL). There was positive correlation between Apo-lipoprotein and Triglycerides (P value=039)., Conclusion: Based on the study result it was concluded that Apo-lipoprotein and triglycerides in diabetic patients with myocardial infarction, had higher levels compared to diabetic patients without Myocardial infarction and this could be a consequence of increase in age, insulin resistance and deficiency of insulin in the body. We also found positive correlation between Apo-lipoprotein and Triglycerides.

In the structure of the title compound, [CdCl2(C4H8N2S)2], the Cd(II) atom is coordinated by two chloride ions and two 1,3-diazinane-2-thione (Diaz) mol-ecules through their S atoms. The geometry around the Cd(II) atom is distorted tetra-hedral, with bond angles in the range 101.55 (7)-117.91 (8)°. The CH2 groups of one Diaz ligand are disordered over two sets of sites with an occupancy ratio of 0.711 (12):0.289 (12). The mol-ecular structure is stabilized by intra-molecular N-H⋯Cl hydrogen-bonding inter-actions, generating a butterfly syn conformation. Inter-molecular N-H⋯Cl and N-H⋯S inter-actions lead to the formation of a three-dimensional network structure. The structure has been determined from a crystal twinned by nonmerohedry, by a 180° rotation around the reciprocal c axis. The twin ratio refined to 0.8866 (6):0.1134 (6).

TRAIL mediated signaling in cancer cells has emerged as one amongst the most deeply studied molecular phenomenon. Data obtained through genetic studies has highlighted highly polymorphic nature of DR4 and in accordance with this concept, we aimed to investigate the association between Colorectal cancer and polymorphisms in TRAIL and DR4 gene. We selected 100 patients with colorectal cancer and 100 healthy, sex and age matched volunteers randomly. C626G and A1322G in DR4 gene were analyzed using Polymerase Change Reaction (PCR) - Restriction Fragment Length Polymorphism (RFLP) and Amplification Refractory Mutation System (ARMS) techniques. PCR-RFLP was used to study TRAIL 1595 C>T. TRAIL gene 1595 C>T genotypes percentage in colorectal cancer patients was statistically non-significant. CC was 43% in patients and 50% in controls. CT was 45% in patients and 43% in controls. TT was 12% in patients and 7% in controls. C allele was 0.655% in cancer patients and 0.715% in controls. T allele was 0.345% in patients and 0.285% in controls. DR4 gene 626 C>G genotypes percentage analysis indicated that CC was 28% in patients and 2% in controls. GC was 42% in patients and 40% in controls. GG was 30% in patients and 58% in controls. CC was statistically significant (p=0.00000207) in cancer patients. C allele was 0.49% in patients and 0.22% in controls. G allele was 0.51% in patients and 0.78% in controls. For DR4 A1322G, homozygous GG genotype was 36% in the patients and in controls. There was statistically insignificant difference (p> 0.05). The heterozygous GT genotype was 30% in patients and 29% in controls. This difference was statistically insignificant (p value > 0.05). Similarly, the homozygous genotype TT of the minor allele was (35%) in controls and patients (34 %). This difference was also statistically insignificant (p value > 0.05). C allele was 0.51% in patients and 0.5% in controls. T allele was 0.49% in patients and 0.495% in controls. Future studies must converge on a larger sample size, sporadic mutations of DR4 and TRAIL and expression profiling.

Autosomal recessive hypotrichosis is a rare form of human genetic disorder characterized by sparse to absent hair on scalp and rest of the body of affected individuals. Over the past few years at least five autosomal recessive forms of hypotrichosis loci have been mapped on different human chromosomes. In the present study, we report localization of another novel autosomal recessive hypotrichosis locus on human chromosome 10q11.23-22.3 in a four generation consanguineous Pakistani family. All the four patients in the family showed typical features of hereditary hypotrichosis including sparse hair on the scalp and rest of the body. Human genome scan using highly polymorphic microsatellite markers mapped the disease locus to a large region on chromosome 10. This novel locus maps to 29.81 cM (28.5 Mb) region, flanked by markers D10S538 and D10S2327 on chromosome 10q11.23-22.3. A maximum multipoint LOD score of 3.26 was obtained with several markers in this region. DNA sequence analysis of exons and splice-junction sites of four putative candidate genes (P4HA1, ZNF365, ZMYND17, MYST4), located in the linkage interval, were sequenced but were negative for functional sequence variants.

Background: Autosomal recessive hypotrishosis (LAH2) is a rare form of alopecia characterized by sparse hair on scalp, sparse to absent eyebrows and eyelashes, and sparse auxiliary and body hair. However, affected male individuals have normal beard hair. Mutations in lipase H (LIPH) gene, located on chromosome 3q26.33, have been shown to be responsible for LAH2 type of hypotrichosis., Objectives: To search for pathogenic mutations in LIPH gene at LAH2 locus in Pakistani families demonstrating autosomal recessive hypotrichosis., Methods: In the present study we have ascertained two large unrelated consanguineous Pakistani families (A and B) inherited autosomal recessive form of hypotrichosis. Linkage in these families was searched by genotyping microsatellite markers linked to autosomal recessive hypotrichosis loci LAH1, LAH2 and LAH3. Affected individuals showed homozygosity to the microsatellite markers tightly linked to LIPH gene at LAH2 locus on chromosome 3q26.33. These families were then subjected to direct sequencing of the LIPH gene., Results: Sequence analysis of the LIPH gene revealed two novel missense mutations (c.2T>C; p.M1T and c.322T>C; p.W108R) in the two families., Conclusion: The mutations reported here are the first missense mutations identified in the LIPH gene, which extend the body of evidences implicating the LIPH gene in the pathogenesis of human hereditary hair loss.