Aluminum toxicity induced Alzheimer's Disease and its potential treatment using antioxidants - a review

Abstract Over the years, a handful of drugs have been approved to be used in the fight against Alzheimer's Disease but unfortunately none of these drugs have proven to be solid-treatments. Alzheimer's Disease is one of the most prominent diseases observed in the elderly population. In this review article, we discuss how aluminum toxicity can lead to neuro degeneration. Aluminum is abundantly present on the earth's crust and hence becomes easily accessible to man. This makes it an obvious choice in the preparation of numerous substances, packaging, etc. Such wide usage of the metal can pave an easy access to the body, leading to toxicities. Aluminum toxicity has been linked to oxidative stress which has an established relation with neurodegeneration and mitochondrial damage. We also discuss how consumption of antioxidants can be useful in combating oxidative stress.

ProMoCell and ProModb: Web services for analyzing interaction-based functionally localized protein modules in a cell.

The modular organization of a cell which can be determined by its interaction network allows us to understand a mesh of cooperation among the functional modules. Therefore, cellular-level identification of functional modules aids in understanding the functional and structural characteristics of the biological network of a cell and also assists in determining or comprehending the evolutionary signal. We develop ProMoCell that performs real-time Web scraping for generating clusters of the cellular level functional units of an organism. ProMoCell constructs the Protein Locality Graphs and clusters the cellular level functional units of an organism by utilizing experimentally verified data from various online sources. Also, we develop ProModb, a database service that houses precomputed whole-cell protein-protein interaction network-based functional modules of an organism using ProMoCell. Our Web service is entirely synchronized with the KEGG pathway database and allows users to generate spatially localized protein modules for any organism belonging to the KEGG genome using its real-time Web scraping characteristics. Hence, the server will host as many organisms as is maintained by the KEGG database. Our Web services provide the users a comprehensive and integrated tool for an efficient browsing and extraction of the spatial locality-based protein locality graph and the functional modules constructed by gathering experimental data from several interaction databases and pathway maps. We believe that our Web services will be beneficial in pharmacological research, where a novel research domain called modular pharmacology has initiated the study on the diagnosis, prevention, and treatment of deadly diseases using functional modules.

Protein Interaction Network-based Deep Learning Framework for Identifying Disease-Associated Human Proteins.

Infectious diseases in humans appear to be one of the most primary public health issues. Identification of novel disease-associated proteins will furnish an efficient recognition of the novel therapeutic targets. Here, we develop a Graph Convolutional Network (GCN)-based model called PINDeL to identify the disease-associated host proteins by integrating the human Protein Locality Graph and its corresponding topological features. Because of the amalgamation of GCN with the protein interaction network, PINDeL achieves the highest accuracy of 83.45% while AUROC and AUPRC values are 0.90 and 0.88, respectively. With high accuracy, recall, F1-score, specificity, AUROC, and AUPRC, PINDeL outperforms other existing machine-learning and deep-learning techniques for disease gene/protein identification in humans. Application of PINDeL on an independent dataset of 24320 proteins, which are not used for training, validation, or testing purposes, predicts 6448 new disease-protein associations of which we verify 3196 disease-proteins through experimental evidence like disease ontology, Gene Ontology, and KEGG pathway enrichment analyses. Our investigation informs that experimentally-verified 748 proteins are indeed responsible for pathogen-host protein interactions of which 22 disease-proteins share their association with multiple diseases such as cancer, aging, chem-dependency, pharmacogenomics, normal variation, infection, and immune-related diseases. This unique Graph Convolution Network-based prediction model is of utmost use in large-scale disease-protein association prediction and hence, will provide crucial insights on disease pathogenesis and will further aid in developing novel therapeutics.

Evaluation of the Role of Routine Laboratory Biomarkers in COVID-19 Patients: Perspective from a Tertiary Care Hospital in India.

To evaluate the role of routine laboratory biomarkers like C Reactive Protein (CRP), Lactate Dehydrogenase (LDH), Interleukin 6 (IL6), Ferritin, Creatinine, Procalcitonin (PCT), Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Serum Albumin, Total Bilirubin (T Bil), High Sensitive Troponin I (hs troponin I), N Terminal-pro B-type Natriuretic Peptide (NT proBNP), Blood Urea Nitrogen (BUN) and Blood Gases in COVID 19 patients who are admitted with SARS CoV-2 positive test results by real-time reverse transcriptase polymerase chain reaction (rRT PCR) in Kokilaben Dhirubhai Ambani Hospital & Medical Research Institute, Mumbai, India. 100 individuals detected with COVID-19 belonging to the age group 12-83 years (median age 62 years) within the period of 1st March 2020 to 10th July 2020 were studied. The case group consisted of 72 males and 28 females. 40 healthy adults without any history or clinical evidence suggestive of COVID-19 and without any comorbidities, like diabetes, hypertension chronic lung disease, cardiac disease, cancer, and immune-compromised individuals were considered as a control group for the study. Routine laboratory findings of these 100 patients were used to evaluate the abnormalities found in COVID-19 patients. Statistical analysis was carried out on the data after determining whether the data had a normal/log-normal distribution and their significance was determined by calculating the p-value. The percentage of patients showing a decrease or increase from the normal value was calculated. Trend analysis was carried out for the 100 patients considered in the case group. Among them, 6 patients were used as representatives to show the trend in these biomarkers during the course of hospital stay. These 5 severe cases consisted of 2 adult males, 2 adult females, and 1 adolescent girl. This selection is to demonstrate the representation of COVID-19 infection in adult males and females and pediatric multisystem inflammatory syndrome associated with COVID-19 in the younger age group. One mild case (adult male) was also selected in the case study. We found a significant increase in mean values of AST, ALT, Total Billirubin, Creatinine, CRP, PCT, LDH, IL6, Ferritin, Lactate, hsTroponin I, NT Pro BNP and decrease in mean values of Albumin, SO2, and PO2 in COVID 19 cases than control. We applied Receiver Operating Curve (ROC) curve to discriminate case population more precisely than the control population. Therefore, Routine laboratory biomarkers appear to play a significant role in COVID-19 patients.

High-Performance Whole-Cell Simulation Exploiting Modular Cell Biology Principles.

One of the grand challenges of this century is modeling and simulating a whole cell. Extreme regulation of an extensive quantity of model and simulation data during whole-cell modeling and simulation renders it a computationally expensive research problem in systems biology. In this article, we present a high-performance whole-cell simulation exploiting modular cell biology principles. We prepare the simulation by dividing the unicellular bacterium, Escherichia coli (E. coli), into subcells utilizing the spatially localized densely connected protein clusters/modules. We set up a Brownian dynamics-based parallel whole-cell simulation framework by utilizing the Hamiltonian mechanics-based equations of motion. Though the velocity Verlet integration algorithm possesses the capability of solving the equations of motion, it lacks the ability to capture and deal with particle-collision scenarios. Hence, we propose an algorithm for detecting and resolving both elastic and inelastic collisions and subsequently modify the velocity Verlet integrator by incorporating our algorithm into it. Also, we address the boundary conditions to arrest the molecules' motion outside the subcell. For efficiency, we define one hashing-based data structure called the cellular dictionary to store all of the subcell-related information. A benchmark analysis of our CUDA C/C++ simulation code when tested on E. coli using the CPU-GPU cluster indicates that the computational time requirement decreases with the increase in the number of computing cores and becomes stable at around 128 cores. Additional testing on higher organisms such as rats and humans informs us that our proposed work can be extended to any organism and is scalable for high-end CPU-GPU clusters.

An unusual neurological presentation: systemic lupus erythematosus mimicking central nervous system infection.

Systemic lupus erythematosus (SLE) is an autoimmune multisystem disease. Childhood-onset SLE is extremely rare and comprises only 10% to 20% of all cases. In this case report, we present a 9-year-old boy from northeastern India who presented with fever, cough, vague abdominal pain, lethargy and swelling of face and legs. Initial impression was one of sepsis with central nervous system (CNS) involvement and was treated accordingly. Detailed clinical examination with subsequent laboratory and imaging studies clinched the diagnosis of SLE. The patient showed rapid resolution of symptoms with immunoglobulins, cyclophosphamide and steroid therapy. A brief discussion on childhood neuropsychiatric lupus syndrome and SLE with CNS infections is included here.

A network-based zoning for parallel whole-cell simulation.

Motivation: In Computational Cell Biology, whole-cell modeling and simulation is an absolute requirement to analyze and explore the cell of an organism. Despite few individual efforts on modeling, the prime obstacle hindering its development and progress is its compute-intensive nature. Towards this end, little knowledge is available on how to reduce the enormous computational overhead and which computational systems will be of use. Results: In this article, we present a network-based zoning approach that could potentially be utilized in the parallelization of whole-cell simulations. Firstly, we construct the protein-protein interaction graph of the whole-cell of an organism using experimental data from various sources. Based on protein interaction information, we predict protein locality and allocate confidence score to the interactions accordingly. We then identify the modules of strictly localized interacting proteins by performing interaction graph clustering based on the confidence score of the interactions. By applying this method to Escherichia coli K12, we identified 188 spatially localized clusters. After a thorough Gene Ontology-based analysis, we proved that the clusters are also in functional proximity. We then conducted Principal Coordinates Analysis to predict the spatial distribution of the clusters in the simulation space. Our automated computational techniques can partition the entire simulation space (cell) into simulation sub-cells. Each of these sub-cells can be simulated on separate computing units of the High-Performance Computing (HPC) systems. We benchmarked our method using proteins. However, our method can be extended easily to add other cellular components like DNA, RNA and metabolites. Availability and implementation: . Supplementary information: Supplementary data are available at Bioinformatics online.

ST2 elevation in heart failure, predictive of a high early mortality.

BACKGROUND: Soluble suppression of tumorigenicity-2 (sST2) is a novel biomarker shown to be useful for prognostic assessment in heart failure (HF). However, very limited data exists about its prognostic utility in patients with HF in India. METHODS: We studied 150 patients [mean age 67.7 ± 13.3, 93 (62%) males], hospitalized with clinical HF, irrespective of their left ventricular ejection fraction (LVEF). HF was confirmed by N-terminal probrain natriuretic peptide (NT-proBNP) value above 125 ng/L. Primary end point was death or cardiac transplant at 1-year follow-up, with additional telephonic follow-up performed at 2 years. The clinical outcomes were correlated with the sST2 values obtained at the time of initial hospitalization. RESULTS: HF was ischemic in origin in 82.0% patients. The primary outcome occurred in 9.3% patients at the end of 1-year follow-up and in 16.7% patients at the end of 2 years. The patients who had events had significantly higher NT-proBNP and sST2 values, but there was no difference in the clinical characteristics, cause of HF, baseline LVEF, or serum creatinine. The patients with elevated sST2 levels (>35 ng/mL) had substantially higher event rates than those with normal sST2 levels (13.7% vs 0.0% at 1-year, P = 0.005; 22.5% vs 4.2% at 2-years, P = 0.004). On multivariate analysis, sST2 was the strongest predictor of adverse outcomes at both 1-year and 2-year follow-ups. CONCLUSION: In patients hospitalized for HF, elevated sST2 >35 ng/mL at the time of initial hospitalization was associated with significantly high mortality over a 2-year period. The prognostic value of sST2 was incremental to that of NT-proBNP. These findings suggest that a single elevated sST2 value at the time of hospitalization should alert the physicians about the high risk of adverse outcomes and should help facilitate timely intensification of HF treatment.

Ameliorative role of ethyl-acetate fraction of methanolic leaf extract of Camellia sinensis (green tea) on streptozotocin-induced diabetes linked testicular hypofunction in albino rat: A dose-dependent biochemical and genomic transection study.

Background The present investigation focuses the diabetes-induced testicular hypofunction and its possible correction by the effective dose of ethyl-acetate fraction of methanolic extract of Camellia sinensis leaves through dose-dependent study in streptozotocin-induced diabetic rat. Methods The androgenic, spermiological, oxidative stress and apoptosis sensors along with testicular genomic sensors were evaluated in a dose-dependent fashion (50 mg or 100 mg or 200 mg/kg body weight). Activities of hepatic transaminases for toxicity assessment were also measured. Results Increased level of fasting blood glucose, testicular cholesterol, seminal vesicular fructose along with a low count, motility and viability of epididymal sperm, low activities of testicular Δ5, 3ß-hydroxy steroid dehydrogenase (HSD), 17ß-HSD, testicular antioxidant enzymes (catalase and superoxide dismutase) and low plasma level of testosterone were noted in diabetic rat in respect to the control. After oral administration of said fraction to diabetic rat, levels of above sensors were resettled toward the control. A significant decrease in the number of different generations of germ cells at the stage VII of spermatogenesis in diabetic rat was noted which were recovered significantly toward the control in the fraction-treated diabetic group. It was supported by the correction in gene expression of testicular Δ5, 3ß- HSD, 17ß- HSD, Bcl-2 and Bax in the fraction-treated diabetic group. Conclusions The threshold dose of ethyl-acetate fraction of methanolic extract of C. sinensis leaves is 100 mg/kg body weight for the recovery of testicular hypofunction in a diabetic rat model.

Standardization of Free Thyroxine Measurements Allows the Adoption of a More Uniform Reference Interval.

BACKGROUND: The IFCC Committee for Standardization of Thyroid Function Tests intended to standardize free thyroxine (FT4) immunoassays. We developed a Système International d'Unités traceable conventional reference measurement procedure (RMP) based on equilibrium dialysis and mass spectrometry. We describe here the latest studies intended to recalibrate against the RMP and supply a proof of concept, which should allow continued standardization efforts. METHODS: We used the RMP to target the standardization and reference interval (RI) panels, which were also measured by 13 manufacturers. We validated the suitability of the recalibrated results to meet specifications for bias (3.3%) and total error (8.0%) determined from biological variation. However, because these specifications were stringent, we expanded them to 10% and 13%, respectively. The results for the RI panel were reported as if the assays were recalibrated. We estimated all but 1 RI using parametric statistical procedures and hypothesized that the RI determined by the RMP was suitable for use by the recalibrated assays. RESULTS: Twelve of 13 recalibrated assays had a bias, meeting the 10% specification with 95% confidence; for 7 assays, this applied even for the 3.3% specification. Only 1 assay met the 13% total error specification. Recalibration reduced the CV of the assay means for the standardization panel from 13% to 5%. The proof-of-concept study confirmed our hypothesis regarding the RI but within constraints. CONCLUSIONS: Recalibration to the RMP significantly reduced the FT4 immunoassays' bias, so that the RI determined by the RMP was suitable for common use within a margin of 12.5%.

Harmonization of Serum Thyroid-Stimulating Hormone Measurements Paves the Way for the Adoption of a More Uniform Reference Interval.

BACKGROUND: The IFCC Committee for Standardization of Thyroid Function Tests developed a global harmonization approach for thyroid-stimulating hormone measurements. It is based on a multiassay method comparison study with clinical serum samples and target setting with a robust factor analysis method. Here we describe the Phase IV method comparison and reference interval (RI) studies conducted with the objective to recalibrate the participating assays and demonstrate the proof-of-concept. METHODS: Fourteen manufacturers measured the harmonization and RI panel; 4 of them quantified the harmonization and first follow-up panel in parallel. All recalibrated their assays to the statistically inferred targets. For validation, we used desirable specifications from the biological variation for the bias and total error (TE). The RI measurements were done with the assays' current calibrators, but data were also reported after transformation to the new calibration status. We estimated the pre- and postrecalibration RIs with a nonparametric bootstrap procedure. RESULTS: After recalibration, 14 of 15 assays met the bias specification with 95% confidence; 8 assays complied with the TE specification. The CV of the assay means for the harmonization panel was reduced from 9.5% to 4.2%. The RI study showed improved uniformity after recalibration: the ranges (i.e., maximum differences) exhibited by the assay-specific 2.5th, 50th, and 97.5th percentile estimates were reduced from 0.27, 0.89, and 2.13 mIU/L to 0.12, 0.29, and 0.77 mIU/L. CONCLUSIONS: We showed that harmonization increased the agreement of results from the participating immunoassays, and may allow them to adopt a more uniform RI in the future.

Monitoring the stability of the standardization status of FT4 and TSH assays by use of daily outpatient medians and flagging frequencies.

Clinicians diagnose thyroid dysfunction based on TSH and FT4 testing. However, the current lack of comparability between assays limits the optimal use of laboratory data. The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) gave a mandate to the Committee for Standardization of Thyroid Function Tests (C-STFT) to resolve this limitation by standardization. Recently, the Committee members and their partners felt ready to set the step towards the technical recalibration. However, before implementation, they were furthered by the Food and Drugs Administration (FDA) to develop a tool to assess the sustainability of the new calibration basis. C-STFT began to use 2 online applications, i.e., the "Percentiler" and "Flagger", with the intention to assess their utility for this purpose. The tools monitor the course of instrument-specific moving medians of outpatient results (Percentiler) and flagging rates (Flagger) from data of individual laboratories grouped by instrument/assay peer. They additionally document the mid- to long-term medians, hence, are quality indicators of stability of performance of both laboratories and peers/assays. Here, the first experiences built up in the pre-standardization phase are reported. They suggest the suitability of both applications to document the sustainability of the calibration basis in the post-standardization phase.

Physical, physicochemical and nutritional characteristics of Bhoja chaul, a traditional ready-to-eat dry heat parboiled rice product processed by an improvised soaking technique.

Bhoja chaul is a traditional whole rice product processed by the dry heat parboiling technique of low amylose/waxy paddy that is eaten after soaking in water and requires no cooking. The essential steps in Bhoja chaul making are soaking paddy in water, roasting with sand, drying and milling. In this study, the product was prepared from a low amylose variety and a waxy rice variety by an improvised laboratory scale technique. Bhoja chaul prepared in the laboratory by this technique was studied for physical, physicochemical, and textural properties. Improvised method shortened the processing time and gave a product with good textural characteristics. Shape of the rice kernels became bolder on processing. RVA studies and DSC endotherms suggested molecular damage and amylose-lipid complex formation by the linear B-chains of amylopectin, respectively. X-ray diffractography indicated formation of partial B-type pattern. Shifting of the crystalline region of the XRD curve towards lower values of Bragg's angle was attributed to the overall increase in inter-planar spacing of the crystalline lamellae. Resistant starch was negligible. Bhoja chaul may be useful for children and people with poor state of digestibility.

A Progress Report of the IFCC Committee for Standardization of Thyroid Function Tests.

BACKGROUND: The IFCC Committee for Standardization of Thyroid Function Tests aims at equivalence of laboratory test results for free thyroxine (FT4) and thyrotropin (TSH). OBJECTIVES: This report describes the phase III method comparison study with clinical samples representing a broad spectrum of thyroid disease. The objective was to expand the feasibility work and explore the impact of standardization/harmonization in the clinically relevant concentration range. METHODS: Two sets of serum samples (74 for FT4, 94 for TSH) were obtained in a clinical setting. Eight manufacturers participated in the study (with 13 FT4 and 14 TSH assays). Targets for FT4 were set by the international conventional reference measurement procedure of the IFCC; those for TSH were based on the all-procedure trimmed mean. The manufacturers recalibrated their assays against these targets. RESULTS: All FT4 assays were negatively biased in the mid- to high concentration range, with a maximum interassay discrepancy of approximately 30%. However, in the low range, the maximum deviation was approximately 90%. For TSH, interassay comparability was reasonable in the mid-concentration range, but worse in the pathophysiological ranges. Recalibration was able to eliminate the interassay differences, so that the remaining dispersion of the data was nearly entirely due to within-assay random error components. The impact of recalibration on the numerical results was particularly high for FT4. CONCLUSIONS: Standardization and harmonization of FT4 and TSH measurements is feasible from a technical point of view. Because of the impact on the numerical values, the implementation needs careful preparation with the stakeholders.

Life tables adjusted for comorbidity more accurately estimate noncancer survival for recently diagnosed cancer patients.

OBJECTIVES: To provide cancer patients and clinicians with more accurate estimates of a patient's life expectancy with respect to noncancer mortality, we estimated comorbidity-adjusted life tables and health-adjusted age. STUDY DESIGN AND SETTING: Using data from the Surveillance Epidemiology and End Results-Medicare database, we estimated comorbidity scores that reflect the health status of people who are 66 years of age and older in the year before cancer diagnosis. Noncancer survival by comorbidity score was estimated for each age, race, and sex. Health-adjusted age was estimated by systematically comparing the noncancer survival models with US life tables. RESULTS: Comorbidity, cancer status, sex, and race are all important predictors of noncancer survival; however, their relative impact on noncancer survival decreases as age increases. Survival models by comorbidity better predicted noncancer survival than the US life tables. The health-adjusted age and national life tables can be consulted to provide an approximate estimate of a person's life expectancy, for example, the health-adjusted age of a black man aged 75 years with no comorbidities is 67 years, giving him a life expectancy of 13 years. CONCLUSION: The health-adjusted age and the life tables adjusted by age, race, sex, and comorbidity can provide important information to facilitate decision making about treatment for cancer and other conditions.

Validation Protocol: First Step of a Lean-Total Quality Management Principle in a New Laboratory Set-up in a Tertiary Care Hospital in India.

Method validation is pursued as the first step in establishing Lean-Total Quality Management in a new clinical laboratory, in order to eliminate error in test results. Validation of all the new tests were done (with particular reference to alkaline phosphatase) by verifying reference intervals, analytical accuracy and precision, inter-assay and intra-assay variations, analytical sensitivity, limit of detection, linearity and reportable range, i.e. (i) Analytical measurement range (AMR) and (ii) Clinically reportable range (CRR). Our obtained reference range was within that of the manufacturer's and showed high degree of analytical accuracy between two laboratories (r(2) = 0.99). Precision was comparable with the manufacturer's claim with inter-assay variation CV 1.04% and intra-assay variation CV 1.54%. Lowest limit of detection was 1.0324 ± 0.007 with CV 0.34%. AMR was also verified with CV 1.26 and 0.69%, for level 1 and level 2 control sera, respectively. The assay was linear with different dilutions. Lean concept was also verified with high recovery percentage. Validation ensures that accurate and precise results are reported in a clinically relevant turn around time.

Correlates of children and parents being physically active together.

BACKGROUND: Co-physical activity (between parents and children), as an outcome variable, and its correlates have not been examined previously. The purpose of this study was to investigate correlates of co-physical activity among a nationally representative sample of 9- to 13-year-old children and their parents. METHODS: Data were from the 2004 Youth Media Campaign Longitudinal Survey, a national survey of 5177 child-parent dyads. Parents of 9- to 13-year-old children were asked to report co-physical activity. Parents and children responded to a series of sociodemographic, behavioral, and psychosocial measures. Co-physical activity was treated as a dichotomous variable (ie, some or none). Logistic regression was used to assess associations of correlates directly and possible interactions between correlates. RESULTS: More than three-quarters of parents reported co-physical activity at least 1 day in the prior week. Age, race/ethnicity, sports team participation, eating meals together, parental confidence to influence the child's organized activity, and the child's perception of parental support were significantly associated with co-physical activity. CONCLUSION: The majority of respondents reported participating in co-physical activity, and multiple sociodemographic, behavioral, and psychosocial correlates were significantly associated with co-physical activity. This study provides insight for physical activity interventions that might involve parents.

Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases.

There have been articles on comparing methods for global clustering evaluation and cluster detection in disease surveillance, but power and sample size (SS) requirements have not been explored for spatially correlated data in this area. We are developing such requirements for tests of spatial clustering and cluster detection for regional cancer cases. We compared global clustering methods including Moran's I, Tango's and Besag-Newell's R statistics, and cluster detection methods including circular and elliptic spatial scan statistics (SaTScan), flexibly shaped spatial scan statistics, Turnbull's cluster evaluation permutation procedure, local indicators of spatial association, and upper-level set scan statistics. We identified eight geographic patterns that are representative of patterns of mortality due to various types of cancer in the U.S. from 1998 to 2002. We then evaluated the selected spatial methods based on state- and county-level data simulated from these different spatial patterns in terms of geographic locations and relative risks, and varying SSs using the 2000 population in each county. The comparison provides insight into the performance of the spatial methods when applied to varying cancer count data in terms of power and precision of cluster detection.