Effects of copper sulphate stress on the morphological and biochemical characteristics of Spinacia oleracea and Avena sativa.

Plants are subjected to various biotic and abiotic stresses that significantly impact their growth and productivity. To achieve balanced crop growth and yield, including for leafy vegetables, the continuous application of micronutrient is crucial. This study investigates the effects of different concentrations of copper sulphate (0, 75, 125, and 175 ppm) on the morphological and biochemical features of Spinacia oleracea and Avena sativa. Morphological parameters such as plant height, leaf area, root length, and fresh and dry weights were optimized at a concentration of 75 ppm copper sulfate. At this concentration, chlorophyll a & b levels increased significantly in Spinacia oleracea (462.9 and 249.8 𝜇𝑔/𝑔), and Avena sativa (404.7 and 437.63𝜇𝑔/𝑔). However, carotenoid content and sugar levels in Spinacia oleracea were negatively affected, while sugar content in Avena sativa increased at 125 ppm (941.6 µg/ml). Protein content increased in Spinacia oleracea (75 ppm, 180.3 µg/ml) but decreased in Avena sativa. Phenol content peaked in both plants at 75 ppm (362.2 and 244.5 µg/ml). Higher concentrations (175 ppm) of copper sulfate reduced plant productivity and health. Plants exposed to control and optimal concentrations (75 and 125 ppm) of copper sulpate exhibited the best health and growth compared to those subjected to higher concentrations. Maximum plant height, leaf area, root length, fresh and dry weights were observed at lower concentrations (75 and 125 ppm) of copper sulfate, while higher concentrations caused toxicity. Optimal copper sulfate levels enhanced chlorophyll a, chlorophyll b, total chlorophyll, protein, and phenol contents but inhibited sugar and carotenoid contents in both Spinacia oleracea and Avena sativa. Overall, increased copper sulfate treatment adversely affected the growth parameters and biochemical profiles of these plants.

Complete mitochondrial genomes of edible mushrooms: features, evolution, and phylogeny.

Edible mushrooms are an important food source with high nutritional and medicinal value. They are a useful source for studying phylogenetic evolution and species divergence. The exploration of the evolutionary relationships among these species conventionally involves analyzing sequence variations within their complete mitochondrial genomes, which range from 31,854 bp (Cordyceps militaris) to 197,486 bp (Grifolia frondosa). The study of the complete mitochondrial genomes of edible mushrooms has emerged as a critical field of research, providing important insights into fungal genetic makeup, evolution, and phylogenetic relationships. This review explores the mitochondrial genome structures of various edible mushroom species, highlighting their unique features and evolutionary adaptations. By analyzing these genomes, robust phylogenetic frameworks are constructed to elucidate mushrooms lineage relationships. Furthermore, the exploration of different variations of mitochondrial DNA presents novel opportunities for enhancing mushroom cultivation biotechnology and medicinal applications. The mitochondrial genomic features are essential for improving agricultural practices and ensuring food security through improved crop productivity, disease resistance, and nutritional qualities. The current knowledge about the mitochondrial genomes of edible mushrooms is summarized in this review, emphasising their significance in both scientific research and practical applications in bioinformatics and medicine.

Decoding LY6G6D in colorectal cancer: Unraveling biomarker potential and therapeutic insights.

Colorectal cancer (CRC) poses a significant global health challenge with high morbidity and mortality rates. This study investigates the role of LY6G6D, a member of the LY6/uPAR superfamily, in CRC. Employing a bioinformatic approach, we analyzed LY6G6D expression across different cancer types, compared it with known oncogenes in CRC, explored the involved genomic alterations, and assessed associated clinicopathological characteristics. LY6G6D exhibited aberrant expression, particularly elevated in CRC adenocarcinoma and highly specific to tumor tissues when compared with other oncogenes, despite its comparatively low frequency of genomic alteration. Subsequently, tumor immune infiltration analysis revealed distinct associations, primarily indicating a negative correlation, suggesting immune down-regulation. Survival analysis in context of LY6G6D was conducted with Kaplan-Meier (KM) curves, indicating a 10% risk of disease recurrence in the case of elevated expression. Additionally, we constructed a 3D protein model of LY6G6D through ab-inito approach. The protein model was validated, followed by conservation analysis and active site identification. Active site identification of LY6G6D's final predicted model revealed some similar sites that were estimated to be conserved. Target-guided drug molecules were collected and molecular docking was executed, proposing Cardigin (Digitoxin) and Manzamine A as potential therapeutic candidates. In conclusion, LY6G6D emerges as a significant biomarker for diagnostic and therapeutic applications in CRC, highlighting its multifaceted role in tumorigenesis. The proposed drugs present avenues for further investigations.

New insight into the dynamics of non-Newtonian Powell-Eyring fluid conveying tiny particles on Riga plate with suction and injection.

The purpose of the current work is to determine how a magnetic field, nonlinear thermal radiation, a heat source or sink, a Soret, and activation energy affect bio-convective nanofluid flow across a Riga plate in terms of heat transfer qualities. The major goal of this investigation is to enhance the heat transfer rate. The flow problem is demonstrated in the form of a collection of PDEs. Since the generated governing differential equations are nonlinear, we use a suitable similarity transformation to change them from partial to ODEs. The bvp4c package in MATLAB is used to numerically solve the streamlined mathematical framework. The impacts of numerous parameters on temperature, velocity, concentration, and motile microorganisms profiles are examined through graphs. Whereas, skin friction and Nusselt number are illustrated using tables. As the magnetic parameter values are raised, the velocity profile is seen to decrease and the temperature curve exhibits the opposite tendency. Additionally, the heat transfer rate expands as the nonlinear radiation heat factor is enhanced. Moreover, the outcomes in this investigation are more consistent and precise than in earlier ones.

Antrodia camphorata and coenzyme Q0 , a novel quinone derivative of Antrodia camphorata, impede HIF-1α and epithelial-mesenchymal transition/metastasis in human glioblastoma cells.

Antrodia camphorata (AC) and Coenzyme Q0 (CoQ0 ), a novel quinone derivative of AC, exhibits antitumor activities. The present study evaluated EMT/metastasis inhibition and autophagy induction aspects of AC and CoQ0 in human glioblastoma (GBM8401) cells. Our findings revealed that AC treatment (0-150 µg/mL) hindered tumor cell proliferation and migration/invasion in GBM8401 cells. Notably, AC treatment inhibited HIF-1α and EMT by upregulating epithelial marker protein E-cadherin while downregulating mesenchymal proteins Twist, Slug, Snail, and ß-catenin. There was an appearance of the autophagy markers LC3-II and p62/SQSTM1, while ATG4B was downregulated by AC treatment. We also found that CoQ0 (0-10 µM) could inhibit migration and invasion in GBM8401 cells. In particular, E-cadherin was elevated and N-cadherin, Vimentin, Twist, Slug, and Snail, were reduced upon CoQ0 treatment. In addition, MMP-2/-9 expression and Wnt/ß-catenin pathways were downregulated. Furthermore, autophagy inhibitors 3-MA or CQ reversed the CoQ0 -elicited suppression of migration/invasion and metastasis-related proteins (Vimentin, Snail, and ß-catenin). Results suggested autophagy-mediated antiEMT and antimetastasis upon CoQ0 treatment. CoQ0 inhibited HIF-1α and metastasis in GBM8401 cells under normoxia and hypoxia. HIF-1α knockdown using siRNA accelerated CoQ0 -inhibited migration. Finally, CoQ0 exhibited a prolonged survival rate in GBM8401-xenografted mice. Treatment with Antrodia camphorata/CoQ0 inhibited HIF-1α and EMT/metastasis in glioblastoma.

The prevalence of deep Venous thrombosis of the lower extremity in hospitalised bedridden orthopaedic patients: a pilot study.

OBJECTIVE: To determine the prevalence of objectively confirmed deep vein thrombosis of lower extremities in bedridden hospitalised orthopaedic patients who received no thromboprophylaxis. METHODS: The prospective cross-sectional study was conducted at Dr Ruth Pfau Civil Hospital, Karachi, from April to June 2021, and included all patients aged ≥40 years admitted for intended major lower limb surgery and expected to be confined to the bed for at least 4 days. Duplex ultrasound scanning of both legs was used to confirm deep vein thrombosis. Data was analysed using SPSS 22. RESULTS: Of the 104 subjects, 60(57.6%) were males and 44(42.3%) were females. The overall mean age was 51.9±7.4 years. The most common type of fracture was the neck of femur 28(26.9%). The mean delay between the fracture and admission was 6.44±4.9 days. The mean length of hospital stay was 12.76±3.8 days. The overall prevalence of deep vein thrombosis was 16(15.3% and none of these patients had any symptom at all. CONCLUSIONS: There was 15.3% prevalence of deep vein thrombosis. Considering that the condition is potentially lethal, routine prophylaxis for all at-risk patients should be encouraged.

Undergraduate research in medical schools in Pakistan: Relevance, Needs, and Importance.

Recent trends in medical education demand practicing physicians to be competent in playing multiple roles. Life-long learning skills underpinned by research & scholarly activity will enable them to play these roles adequately. Therefore, the introduction of structured training in research during early undergraduate years is pivotal. This would enable trainee physicians to develop essential skills; the institutions will grow in terms of visibility & ranking; the trainers and supervisors will be satisfied in terms of research productivity and, most importantly the patients will benefit in terms of improved clinical outcomes.

In silico analysis and expression profiling of Expansin A4, BURP domain protein RD22-like and E6-like genes associated with fiber quality in cotton.

BACKGROUND: To supply high-quality cotton fibre for the textile industry, the development of long, strong and fine fibre cotton varieties is imperative. An interlinked approach was used to comprehend the role of fibre genes by analyzing interspecific progenies of cotton species. Wild Gossypium species and races are rich source of genetic polymorphism due to environmental dispersal and continuous natural selection. These genetic resources hold mass of outclass genes that can be used in cotton improvement breeding programs to exploit possible traits such as fibre quality, abiotic stress tolerance, and disease and insect resistance. Therefore, use of new molecular techniques such as genomics, transcriptomics and bioinformatics is very important to utilize the genetic potential of wild species in cotton improvement programs. METHODS: Interspecific lines and Gossypium species used in the study were grown at Central Cotton Research Institute (CCRI), Multan. After retrieving DNA sequence of the genes from NCBI, the primers for gene expression and full-length gene sequence were designed. Expression profiling of Expansin A4, BURP Domain protein RD22-like and E6-like fibre genes was performed through Real Time PCR. BLAST and DNA sequence alignment was conducted for sequence comparison of interspecific lines and Gossypium species. Different in silico analysis were used for characterization of fibre genes and identification of cis acting promoter elements in promoter region. RESULTS: Variable expression of genes related to fibre development was observed at different stages. BLAST and DNA sequence alignment demonstrated resemblance of interspecific lines with G. hirsutum. In silico analysis on the sequence data also confirmed the role of Expansin A4, BURP Domain protein RD22-like and E6-like fibre genes in fibre development. Genetic engineering is also recommended by transferring E6-like, Expansin A4 and BURP Domain RD22-like genes in local cotton cultivars. Similarly, several stress tolerant and light responsive cis acting elements were identified through promotor analysis, which may contribute for fibre development in the breeding programs. CONCLUSION: Expansin A4, BURP Domain RD22-like and E6-like have positive role in fibre development with variable expression at fiber length and strength associated stages.

Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach.

Bitcoin (BTC)-the first cryptocurrency-is a decentralized network used to make private, anonymous, peer-to-peer transactions worldwide, yet there are numerous issues in its pricing due to its arbitrary nature, thus limiting its use due to skepticism among businesses and households. However, there is a vast scope of machine learning approaches to predict future prices precisely. One of the major problems with previous research on BTC price predictions is that they are primarily empirical research lacking sufficient analytical support to back up the claims. Therefore, this study aims to solve the BTC price prediction problem in the context of both macroeconomic and microeconomic theories by applying new machine learning methods. Previous work, however, shows mixed evidence of the superiority of machine learning over statistical analysis and vice versa, so more research is needed. This paper applies comparative approaches, including ordinary least squares (OLS), Ensemble learning, support vector regression (SVR), and multilayer perceptron (MLP), to investigate whether the macroeconomic, microeconomic, technical, and blockchain indicators based on economic theories predict the BTC price or not. The findings point out that some technical indicators are significant short-run BTC price predictors, thus confirming the validity of technical analysis. Moreover, macroeconomic and blockchain indicators are found to be significant long-term predictors, implying that supply, demand, and cost-based pricing theories are the underlying theories of BTC price prediction. Likewise, SVR is found to be superior to other machine learning and traditional models. This research's innovation is looking at BTC price prediction through theoretical aspects. The overall findings show that SVR is superior to other machine learning models and traditional models. This paper has several contributions. It can contribute to international finance to be used as a reference for setting asset pricing and improved investment decision-making. It also contributes to the economics of BTC price prediction by introducing its theoretical background. Moreover, as the authors still doubt whether machine learning can beat the traditional methods in BTC price prediction, this research contributes to machine learning configuration and helping developers use it as a benchmark.

An Overview of the Recent Progress in Polymeric Carbon Nitride Based Photocatalysis.

Recently, polymeric carbon nitride (g-C3 N4 ) as a proficient photo-catalyst has been effectively employed in photocatalysis for energy conversion, storage, and pollutants degradation due to its low cost, robustness, and environmentally friendly nature. The critical review summarized the recent development, fundamentals, nanostructures design, advantages, and challenges of g-C3 N4 (CN), as potential future photoactive material. The review also discusses the latest information on the improvement of CN-based heterojunctions including Type-II, Z-scheme, metal/CN Schottky junctions, noble metal@CN, graphene@CN, carbon nanotubes (CNTs)@CN, metal-organic frameworks (MOFs)/CN, layered double hydroxides (LDH)/CN heterojunctions and CN-based heterostructures for H2 production from H2 O, CO2 conversion and pollutants degradation in detail. The optical absorption, electronic behavior, charge separation and transfer, and bandgap alignment of CN-based heterojunctions are discussed elaborately. The correlations between CN-based heterostructures and photocatalytic activities are described excessively. Besides, the prospects of CN-based heterostructures for energy production, storage, and pollutants degradation are discussed.

A New Benzothiazin-functionalized Calix[4]arene-based Fluorescent Chemosensor for the Selective Detection of Co2+ Ion.

Calixarenes, which have a great place in supramolecular chemistry, have become the most prominent macrocyclic compounds in synthetic organic chemistry due to their easy synthesis and functionalization. In this study, p-tert-butyl calix[4]arene dihydrazide derivative was synthesized and then reacted with 3-oxo-3,4-dihydro-2 H-benzo[b][1,4] thiazin-2-ylideneacetyl chloride to prepare new calixarene based chromophore compound 4. The structure of the synthesized compound was elucidated by spectroscopic methods such as 1H NMR 13C NMR and FT-IR spectroscopy. Chromogenic and fluorescence properties of compound 4 were evaluated. It was observed from both studies that compound 4 was Co2+ selective and shows fluorescence Switched-off behavior. Stoichiometry, binding constant and the detection limit were calculated. The stoichiometry between compound 4 and Co2+ was found to be 1:1. The binding constant value (K) was calculated as 666.67 M- 1 using Benesi-Hildebrand equation, while the detection limit for Co2+ ion was calculated as 0.0465 µM.

Petroleum oil and products recovery from oily sludge: Characterization and analysis of pyrolysis products.

Oily sludge (OS) has attracted special interest because of its hazardous nature and high potential as an energy resource. This study investigated the oil recovery from OS by thermal cracking and catalytic pyrolysis. The oil yield increased when the temperature exceeded 450 °C and reached a maximum (76.84 wt%) at 750 °C. Catalysts significantly improved the quality of oil produced during catalytic pyrolysis. Aromatic hydrocarbons were dominant (10.01-52.69%) in pyrolysis oil (PO) from OS catalytic pyrolysis, and the catalysts significantly reduced the presence of oxygen heterocycles. In addition, KOH and CaO reduced the ID (D-band peak intensity)/IG (G-band peak intensity) of OS char (OC) and increased the degree of graphitization. Owing to its higher iodine adsorption value and methylene blue (MB) adsorption value, OC exhibits potential as an adsorbent. The environmental assessment and potential applications of OC, along with possible reaction mechanisms and kinetic characteristics, are also discussed.

Using Multiplexed CRISPR/Cas9 for Suppression of Cotton Leaf Curl Virus.

In recent decades, Pakistan has suffered a decline in cotton production due to several factors, including insect pests, cotton leaf curl disease (CLCuD), and multiple abiotic stresses. CLCuD is a highly damaging plant disease that seriously limits cotton production in Pakistan. Recently, genome editing through CRISPR/Cas9 has revolutionized plant biology, especially to develop immunity in plants against viral diseases. Here we demonstrate multiplex CRISPR/Cas-mediated genome editing against CLCuD using transient transformation in N. benthamiana plants and cotton seedlings. The genomic sequences of cotton leaf curl viruses (CLCuVs) were obtained from NCBI and the guide RNA (gRNA) were designed to target three regions in the viral genome using CRISPR MultiTargeter. The gRNAs were cloned in pHSE401/pKSE401 containing Cas9 and confirmed through colony PCR, restriction analysis, and sequencing. Confirmed constructs were moved into Agrobacterium and subsequently used for transformation. Agroinfilteration in N. benthamiana revealed delayed symptoms (3-5 days) with improved resistance against CLCuD. In addition, viral titer was also low (20-40%) in infected plants co-infiltrated with Cas9-gRNA, compared to control plants (infected with virus only). Similar results were obtained in cotton seedlings. The results of transient expression in N. benthamiana and cotton seedlings demonstrate the potential of multiplex CRISPR/Cas to develop resistance against CLCuD. Five transgenic plants developed from three experiments showed resistance (60-70%) to CLCuV, out of which two were selected best during evaluation and screening. The technology will help breeding CLCuD-resistant cotton varieties for sustainable cotton production.

The Histone Demethylase KDM3A, Increased in Human Pancreatic Tumors, Regulates Expression of DCLK1 and Promotes Tumorigenesis in Mice.

BACKGROUND & AIMS: The histone lysine demethylase 3A (KDM3A) demethylates H3K9me1 and H3K9Me2 to increase gene transcription and is upregulated in tumors, including pancreatic tumors. We investigated its activities in pancreatic cancer cell lines and its regulation of the gene encoding doublecortin calmodulin-like kinase 1 (DCLK1), a marker of cancer stem cells. METHODS: We knocked down KDM3A in MiaPaCa-2 and S2-007 pancreatic cancer cell lines and overexpressed KDM3A in HPNE cells (human noncancerous pancreatic ductal cell line); we evaluated cell migration, invasion, and spheroid formation under hypoxic and normoxic conditions. Nude mice were given orthotopic injections of S2-007 cells, with or without (control) knockdown of KDM3A, and HPNE cells, with or without (control) overexpression of KDM3A; tumor growth was assessed. We analyzed pancreatic tumor tissues from mice and pancreatic cancer cell lines by immunohistochemistry and immunoblotting. We performed RNA-sequencing analysis of MiaPaCa-2 and S2-007 cells with knockdown of KDM3A and evaluated localization of DCLK1 and KDM3A by immunofluorescence. We analyzed the cancer genome atlas for levels of KDM3A and DCLK1 messenger RNA in human pancreatic ductal adenocarcinoma (PDAC) tissues and association with patient survival time. RESULTS: Levels of KDM3A were increased in human pancreatic tumor tissues and cell lines, compared with adjacent nontumor pancreatic tissues, such as islet and acinar cells. Knockdown of KDM3A in S2-007 cells significantly reduced colony formation, invasion, migration, and spheroid formation, compared with control cells, and slowed growth of orthotopic tumors in mice. We identified KDM3A-binding sites in the DCLK1 promoter; S2-007 cells with knockdown of KDM3A had reduced levels of DCLK1. HPNE cells that overexpressed KDM3A formed foci and spheres in culture and formed tumors and metastases in mice, whereas control HPNE cells did not. Hypoxia induced sphere formation and increased levels of KDM3A in S2-007 cells and in HPNE cells that overexpressed DCLK1, but not control HPNE cells. Levels of KDM3A and DCLK1 messenger RNA were higher in human PDAC than nontumor pancreatic tissues and correlated with shorter survival times of patients. CONCLUSIONS: We found human PDAC samples and pancreatic cancer cell lines to overexpress KDM3A. KDM3A increases expression of DCLK1, and levels of both proteins are increased in human PDAC samples. Knockdown of KDM3A in pancreatic cancer cell lines reduced their invasive and sphere-forming activities in culture and formation of orthotopic tumors in mice. Hypoxia increased expression of KDM3A in pancreatic cancer cells. Strategies to disrupt this pathway might be developed for treatment of pancreatic cancer.

Lewis Base-Switched [3 + 3] and [4 + 2] Annulation Reactions of δ-Acetoxy Allenoates with Cyclic N-Sulfonyl Imines: Divergent Synthesis of Functionalized α-Pyridyl Acetates and Teraryl Scaffolds.

Under metal-free conditions, δ-acetoxy allenoates react with cyclic N-sulfonyl imines (sulfamidate imines/sulfonyl imines) to afford functionalized 2-pyridinyl acetates (α-pyridyl acetates) or teraryl motifs by a simple Lewis base switch. Thus, while DBU/Na2CO3 combination-directed [3 + 3] annulation involves sulfonyl elimination via O-S or C-S bond cleavage, affording 2-pyridinyl acetates, Ph3P-catalyzed [4 + 2] annulation leads to functionalized teraryls via Mannich coupling and C-N bond cleavage with retention or cleavage of the sulfamoyloxy group depending on the reaction conditions.

Enhanced Oil Recovery by Potential Biosurfactant-Producing Halo-thermotolerant Bacteria Using Soil Washing and Sand-Packed Glass Column Techniques.

Biosurfactants offer numerous advantages over the chemical surfactants, especially in energy and environment-related applications. Microbial enhanced oil recovery (MEOR) is a technique to recover oil from reservoirs by using microbes and their metabolites. In present study, total sixteen morphologically distinct bacterial strains isolated from different salty areas of the district Khairpur Mir's, Pakistan, were investigated for their MEOR potential. Screening assays for thermotolerance and halotolerance declared 7 out of 16 (43.75%) bacterial isolates as thermotolerant (capable of growing in the temperature range 60-70 °C) and halotolerant (tolerating NaCl concentrations up to 17%, w/v). Moreover, five of them were screened as biosurfactant producers. Among, the lowest surface tension reduction was achieved with biosurfactants produced by the strains KJ2MO (27.8 mN/m) and KJ2SK (29.3 mN/m). The biosurfactant activity was found stable at temperature (100-121 °C, 1 h) and pH (4-10). Moreover, maximum oil recovery was obtained with biosurfactant of bacterial strain KJ2MO (54.7%, 51.25%) followed by KJ2SK (44.7%, 40.5%), KJ1WB (37%, 35.5%) and KJ2MD (37.8%, 31.9%) by using either techniques, i.e., soil washing and sand-packed column, respectively. Moreover, the potent species were identified as Pseudomonas pseudoalcaligenes KJ1WB, Bacillus aerius KJ2MD, Bacillus licheniformis KJ2SK, and Bacillus subtilis KJ2MO using 16S rRNA ribo-typing. The investigated species were found to be promising biosurfactants producers having potential for enhanced oil recovery and could be used in other environmental applications like bioremediation.

Performance Evaluation of Convolutional Neural Network for Hand Gesture Recognition Using EMG.

Electromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still insufficient for natural control. Recent advancements in deep learning have shown tremendous progress in biosignal processing. Multiple architectures have been proposed yielding high accuracies (>95%) for offline analysis, yet the delay caused due to optimization of the system remains a challenge for its real-time application. From this arises a need for optimized deep learning architecture based on fine-tuned hyper-parameters. Although the chance of achieving convergence is random, however, it is important to observe that the performance gain made is significant enough to justify extra computation. In this study, the convolutional neural network (CNN) was implemented to decode hand gestures from the sEMG data recorded from 18 subjects to investigate the effect of hyper-parameters on each hand gesture. Results showed that the learning rate set to either 0.0001 or 0.001 with 80-100 epochs significantly outperformed (p < 0.05) other considerations. In addition, it was observed that regardless of network configuration some motions (close hand, flex hand, extend the hand and fine grip) performed better (83.7% ± 13.5%, 71.2% ± 20.2%, 82.6% ± 13.9% and 74.6% ± 15%, respectively) throughout the course of study. So, a robust and stable myoelectric control can be designed on the basis of the best performing hand motions. With improved recognition and uniform gain in performance, the deep learning-based approach has the potential to be a more robust alternative to traditional machine learning algorithms.

Evaluation of blood lead levels by atomic absorption spectrometry in school going children of northern areas of Pakistan.

OBJECTIVE: To evaluate blood lead levels and assess their correlation with academic performance in school children. METHODS: The cross-sectional study was conducted at the Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology, Rawalpindi, Pakistan, from January to December, 2017, and comprised school children in Rawalpindi, Pakistan, and Hajira, Azad Jammu and Kashmir. About 5 ml of venous blood was collected in potassium-ethylenediaminetetraacetic acid tubes for lead levels, haemoglobin and plasma ferritin. The preceding three years' academic performance, rated as excellent, good, fair and poor, of the subjects was categorised on a specifically-designed proforma. Data was analysed using SPSS 24. RESULTS: Of the 400 subjects, 205 (50.25%) were females. The overall mean age was 9.15±2.8 years. Mean level of lead was 4.3±2.6 µg/dL, and difference in values was significant between children of Hajira and Rawalpindi (p<0.05). Mean haemoglobin was 12.9±0.919g/dL and mean ferritin was 49.17±16.0ng/ml. Of the total, 85(21.3%) showed excellent school performance, 162(40.5%) good, 113(28.3%) fair and 40(10%) showed poor performance. Significant negative association was found between school performance and mean blood lead level (p>0.05). No significant difference was found in terms of gender and age with school performance of both regions. CONCLUSIONS: Majority of school going children in northern Pakistan were found to have lead levels ≤ 5µg/dL which is a level of concern as it is inversely related to academic performance.

Biochemical spectrum of parathyroid disorders diagnosed at a tertiary care setting.

OBJECTIVE: To determine the clinical and biochemical pattern of parathyroid disorders in a tertiary care setting.. METHODS: The cross-sectional study was conducted at the Armed Forces Institute of Pathology, Rawalpindi, Pakistan, from September 2017 to February 2018, and comprised patients with suspected parathyroid disorders. A panel of biochemical tests were used for diagnosis of parathyroid disorders, which included parathyroid hormone levels, total calcium, ionized calcium, inorganic phosphorus, alkaline phosphatase, magnesium, total vitamin D and urinary calcium-to-creatinine ratio. SPSS 24 was used for data analysis. RESULTS: Of the 384 subjects, 248(65%) were male and 136(35%) were female. Overall mean age was 48±19years. Of the total, 302(786%) had parathyroid issues, with 244(81%) having secondary hyperparathyroidism. Mean serum total calcium, phosphorus, ionized calcium, magnesium and total vitamin D were 8.98±1.52 mg/dl, 4.0±1.30 mg/dl, 4.65±0.52 mg/dl, 2.11±0.27 mg/dl and 20.5±8.52 ngml respectively. Of the patients diagnosed with secondary hyperparathyroidism, 72.2% patients had chronic kidney disease and 20.2% had isolated vitamin D deficiency. CONCLUSIONS: Parathyroid disorders had significant impact on bone health. Moreover, secondary hyperparathyroidism was seen to be emerging as a major endocrine problem, especially in chronic kidney disease patients and vitamin D-deficient individuals.

Pleotropic role of RNA binding protein CELF2 in autophagy induction.

We previously reported that ionizing radiation (IR) mediates cell death through the induction of CUGBP elav-like family member 2 (CELF2), a tumor suppressor. CELF2 is an RNA binding protein that modulates mRNA stability and translation. Since IR induces autophagy, we hypothesized that CELF2 regulates autophagy-mediated colorectal cancer (CRC) cell death. For clinical relevance, we determined CELF2 levels in The Cancer Genome Atlas (TCGA). Role of CELF2 in radiation response was carried out in CRC cell lines by immunoblotting, immunofluorescence, autophagic vacuole analyses, RNA stability assay, quantitative polymerase chain reaction and electron microscopy. In vivo studies were performed in a xenograft tumor model. TCGA analyses demonstrated that compared to normal tissue, CELF2 is expressed at significantly lower levels in CRC, and is associated with better overall 5-year survival in patients receiving radiation. Mechanistically, CELF2 increased levels of critical components of the autophagy cascade including Beclin-1, ATG5, and ATG12 by modulating mRNA stability. CELF2 also increased autophagic flux in CRC. IR significantly induced autophagy in CRC which correlates with increased levels of CELF2 and autophagy associated proteins. Silencing CELF2 with siRNA, mitigated IR induced autophagy. Moreover, knockdown of CELF2 in vivo conferred tumor resistance to IR. These studies elucidate an unrecognized role for CELF2 in inducing autophagy and potentiating the effects of radiotherapy in CRC.