Vitamin B12 insufficiency and deficiency: a review of nondisease risk factors.

Vitamin B12 deficiency and insufficiency can lead to both hematological and neurological impairments. This review examines nondisease causes and risk factors associated with dietary availability, such as eating habits, food processing, cooking techniques, and bioavailability, as well as increased physiological needs and iatrogenic factors linked to medication use or surgical procedures. As a result of these nondisease influences, groups at higher risk include vegans, vegetarians, older adults, individuals with limited diets, breastfed and preterm infants, and those who primarily consume foods prepared or cooked in ways that reduce vitamin B12 content, as well as individuals on certain medications or who have undergone specific surgeries. Recognizing these diverse risk factors helps develop strategies for prevention and intervention to minimize the adverse health effects related to B12 deficiency and insufficiency.

Strengths and Weaknesses of ChatGPT Models for Scientific Writing About Medical Vitamin B12: Mixed Methods Study.

BACKGROUND: ChatGPT is a large language model developed by OpenAI designed to generate human-like responses to prompts. OBJECTIVE: This study aims to evaluate the ability of GPT-4 to generate scientific content and assist in scientific writing using medical vitamin B12 as the topic. Furthermore, the study will compare the performance of GPT-4 to its predecessor, GPT-3.5. METHODS: The study examined responses from GPT-4 and GPT-3.5 to vitamin B12-related prompts, focusing on their quality and characteristics and comparing them to established scientific literature. RESULTS: The results indicated that GPT-4 can potentially streamline scientific writing through its ability to edit language and write abstracts, keywords, and abbreviation lists. However, significant limitations of ChatGPT were revealed, including its inability to identify and address bias, inability to include recent information, lack of transparency, and inclusion of inaccurate information. Additionally, it cannot check for plagiarism or provide proper references. The accuracy of GPT-4's answers was found to be superior to GPT-3.5. CONCLUSIONS: ChatGPT can be considered a helpful assistant in the writing process but not a replacement for a scientist's expertise. Researchers must remain aware of its limitations and use it appropriately. The improvements in consecutive ChatGPT versions suggest the possibility of overcoming some present limitations in the near future.

An Analytical Method for Determining N-Nitrosodimethylamine and N-Nitrosodiethylamine Contamination in Irbesartan, Olmesartan and Metformin by UPLC-APCI-MS/MS in Tablet Dosage Form.

N-nitrosamine pollutants are probable carcinogens. Regulatory agencies declared their presence in the drugs unsafe for human consumption and demanded their recall. Using ultra-performance liquid chromatography-atmospheric pressure chemical ionization-tandem mass spectrometry (UPLC-APCI-MS/MS) in tablet dosage form based on International Conference on Harmonization (ICH) tripartite guideline criteria, we aim to develop and test a new approach for identifying and validating nitrosamine-contaminants, N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) in irbesartan, olmesartan and metformin. The column was Phenomenex Luna-C18, 100 × 3.0 mm and 3.0 µm. A mobile gradient phase of formic acid in either water or methanol separated the impurities. NDMA and NDEA had retention times of 0.85 and 2.55 min, respectively. The detector's linearity was established at concentrations ranging from 0.6 to 100 ng/mL. R2 for NDMA and NDEA were 0.9996 and 0.9998, respectively, with a linear response function established at 0.6-100 ng/mL. Limit of detection and limit of quantification for NDMA and NDEA were 0.35, 0.29 and 0.55, 0.37 ng/mL, respectively. On average, recovery rates for NDMA and NDEA ranged from 96.0 to 98.4 and 96.2 to 98.0%, respectively. The relative standard deviation for NDMA and NDEA was 3.46 and 2.69, respectively. According to the ICH guidelines, the developed method was quick, sensitive and valid. The pharmaceutical formulations of irbesartan, olmesartan and metformin may be regularly examined using the approach provided here.

Vitamin B12 binding to mutated human transcobalamin, in-silico study of TCN2 alanine scanning and ClinVar missense mutations/SNPs.

Many missense mutations/SNPs of the TCN2 gene (which yield Transcobalamin (TC)) were reported in the literature but no study is available about their effect on binding to vitamin B12(B12) at the structural level experimentally nor computationally. Predict the effect of TC missense mutations/SNPs on binding affinity to B12 and characterize their contacts to B12 at the structural level. TC-B12 binding energy difference from the wildtype (ΔΔGmut) was calculated for 378 alanine scanning mutations and 76 ClinVar missense mutations, repeated on two distinct X-ray structures of holoTC namely 2BB5 and 4ZRP. Destabilizing mutations then went through 100 ns molecular dynamics simulation to study their effect on TC-B12 binding at the structural level employing 2BB5 structure. Out of the studied 454 mutations (378 alanine mutations + 76 ClinVar mutations), 19 were destabilizing representing 17 amino acid locations. Mutation energy results show a neutral effect on B12 binding of several missense SNPs reported in the literature including I23V, G94S, R215W, P259R, S348F, L376S, and R399Q. Compared to the wildtype, all the destabilizing mutations have higher average RMSD-Ligand in the last 25% of the MD simulation trajectories and lower average hydrogen bond count while the other parameters vary. Previously reported TCN2 SNPs with an unknown effect on TC-B12 binding were found to have a neutral effect in the current study based on mutation energy calculations. Also, we reported 17 possible amino acids that destabilize TC-B12 binding upon mutation (four listed in ClinVar) and studied their structural effect computationally.

Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis.

CD36 (cluster of differentiation 36) is a membrane protein involved in lipid metabolism and has been linked to pathological conditions associated with metabolic disorders, such as diabetes and dyslipidemia. A case-control study was conducted and included 177 patients with type-2 diabetes mellitus (T2DM) and 173 control subjects to study the involvement of CD36 gene rs1761667 (G>A) and rs1527483 (C>T) polymorphisms in the pathogenesis of T2DM and dyslipidemia among Jordanian population. Lipid profile, blood sugar, gender and age were measured and recorded. Also, genotyping analysis for both polymorphisms was performed. Following statistical analysis, 10 different neural networks and machine learning (ML) tools were used to predict subjects with diabetes or dyslipidemia. Towards further understanding of the role of CD36 protein and gene in T2DM and dyslipidemia, a protein-protein interaction network and meta-analysis were carried out. For both polymorphisms, the genotypic frequencies were not significantly different between the two groups (p > 0.05). On the other hand, some ML tools like multilayer perceptron gave high prediction accuracy (≥ 0.75) and Cohen's kappa (κ) (≥ 0.5). Interestingly, in K-star tool, the accuracy and Cohen's κ values were enhanced by including the genotyping results as inputs (0.73 and 0.46, respectively, compared to 0.67 and 0.34 without including them). This study confirmed, for the first time, that there is no association between CD36 polymorphisms and T2DM or dyslipidemia among Jordanian population. Prediction of T2DM and dyslipidemia, using these extensive ML tools and based on such input data, is a promising approach for developing diagnostic and prognostic prediction models for a wide spectrum of diseases, especially based on large medical databases.

Docking-generated multiple ligand poses for bootstrapping bioactivity classifying Machine Learning: Repurposing covalent inhibitors for COVID-19-related TMPRSS2 as case study.

In the present work we introduce the use of multiple docked poses for bootstrapping machine learning-based QSAR modelling. Ligand-receptor contact fingerprints are implemented as descriptor variables. We implemented this method for the discovery of potential inhibitors of the serine protease enzyme TMPRSS2 involved the infectivity of coronaviruses. Several machine learners were scanned, however, Xgboost, support vector machines (SVM) and random forests (RF) were the best with testing set accuracies reaching 90%. Three potential hits were identified upon using the method to scan known untested FDA approved drugs against TMPRSS2. Subsequent molecular dynamics simulation and covalent docking supported the results of the new computational approach.

Association of Breastfeeding Duration with Susceptibility to Allergy, Influenza, and Methylation Status of TLR1 Gene.

Background and Objectives: This study aimed to investigate the possible association between exclusive breastfeeding duration during early infancy and susceptibility to allergy and influenza in adulthood. Furthermore, we also investigated the association of breastfeeding duration with DNA methylation at two sites in the promoter of the toll-like receptor-1 (TLR1) gene, as well as the association between DNA methylation of the toll-like receptor-1 (TLR1) gene and susceptibility to different diseases. Materials and Methods: Blood samples were collected from 100 adults and classified into two groups according to breastfeeding duration (<6 months and ≥6 months) during infancy. Subjects were asked to complete a questionnaire on their susceptibilities to different diseases and sign a consent form separately. Fifty-three samples underwent DNA extraction, and the DNA samples were divided into two aliquots, one of which was treated with bisulfite reagent. The promoter region of the TLR1 gene was then amplified by polymerase chain reaction (PCR) and sequenced. Results: We found a significant association between increased breastfeeding duration and a reduction in susceptibility to influenza and allergy, as well asa significant reduction in DNA methylation within the promoter of the TLR1 gene. No association was found between DNA methylation and susceptibility to different diseases. Conclusions: The findings demonstrate the significance of increased breastfeeding duration for improved health outcomes at the gene level.

The soluble transcobalamin receptor (sCD320) in relation to Alzheimer's disease and cognitive scores.

The soluble transcobalamin receptor (sCD320) is present in cerebrospinal fluid and correlates with the dementia-related biomarkers phospho-tau and total-tau. Here we present data on the relation of sCD320 to Alzheimer's disease and scores of cognitive tests. Lumbar cerebrospinal fluid samples from 42 pathologically-confirmed cases of Alzheimer's disease and 25 non-demented controls were analyzed for sCD320 employing an in-house ELISA. The participants' cognitive functions were tested using the Cambridge Cognition Examination (CAMCOG) and the Mini-Mental State Examination (MMSE). There was no significant difference in the median CSF sCD320 concentration between patients and controls. The median (2.5-97.5 percentiles) sCD320 for all participants (n = 67) was 15 (3-29) pmol/L. We observed a non-linear correlation between sCD320 and cognitive scores. Spearman's correlation between sCD320 and total CAMCOG scores was 0.627 (n = 16, p = .009) for CAMCOG scores ≤27, and -0.293 (n = 39, p = .071) for CAMCOG scores ≥68. Spearman's correlation between sCD320 and both the low (≤9) and high (≥16) total MMSE scores was 0.274, -0.363 (n = 18, 44), p = .272, .016, respectively. In conclusion, sCD320 cannot be employed as a biomarker for differentiating Alzheimer dementia patients from controls. Further studies are warranted to explore the non-linear correlations between sCD320 and scores of cognitive function.

First trimester serum levels of the soluble transcobalamin receptor, holo-transcobalamin, and total transcobalamin in relation to preeclampsia risk.

BACKGROUND: Human placenta expresses CD320, a receptor that ensures the uptake of holo-transcobalamin (holoTC). Soluble CD320 (sCD320) is present in the circulation and its concentration increases during pregnancy. AIMS: To investigate a possible association of sCD320, holoTC and total transcobalamin (TC) with the risk of subsequent preeclampsia using serum samples from asymptomatic first trimester pregnant women. Moreover, we aimed to establish reference intervals of the aforementioned biomarkers for first trimester pregnant women who remained healthy throughout pregnancy. STUDY DESIGN: This study was a retrospective case-control study that we performed on biobank serum samples. Cases (n = 50) and controls (n = 198) (matched for gestational age and date of sample collection) were asymptomatic women in early pregnancy [median (range) gestational age = 10 (8-12) weeks]. Cases developed preeclampsia while the controls remained normotensive throughout pregnancy. We measured the serum concentration of sCD320, holoTC, and total TC by using in-house ELISA methods. RESULTS: First trimester median concentrations of sCD320, holoTC and total TC were not significantly different between cases and controls. The odd ratio for developing preeclampsia based on exposure to low or high levels of sCD320, holoTC or total TC at first trimester was not significant. The reference intervals (2.5-97.5% percentiles (median)) derived from the controls were 50-170 (90) pmol\L for sCD320, 20-140 (70) pmol\L for holoTC and 560-1300 (810) pmol\L for total TC. CONCLUSIONS: The risk of preeclampsia is not predicted by first trimester serum concentrations of sCD320, holoTC or total TC. The first trimester reference intervals for the three parameters is reported.

The soluble transcobalamin receptor (sCD320) is present in cerebrospinal fluid and correlates to dementia-related biomarkers tau proteins and amyloid-beta.

BACKGROUND: Cellular uptake of vitamin B12 (B12) demands binding of the vitamin to transcobalamin (TC) and recognition of TC-B12 (holoTC) by the receptor CD320. Recently, we identified a soluble form of CD320 (sCD320) in human plasma. Here we present data on the occurrence of this soluble receptor in cerebrospinal fluid (CSF) and show its correlations to dementia-related biomarkers tau proteins and amyloid-beta. METHODS: We collected 223 cerebrospinal fluid samples and corresponding plasma samples (n = 46). We measured CSF and plasma sCD320, holoTC and total TC employing in-house ELISA methods and CSF phospho-tau (181P) (p-tau), total tau (t-tau) and amyloid-beta 1-42 (Aß) (n = 177) employing commercial ELISA kits (Innogenetics Company). Size exclusion chromatography was performed on a Superdex 200 column. RESULTS: The median sCD320 concentration in CSF (14 pmol/L) is around five times lower than in plasma (72 pmol/L). No correlation was observed between plasma and CSF sCD320 levels (n = 46), while the behavior upon size exclusion chromatography was the same. In CSF, sCD320 correlates to holoTC and total TC (Spearman's correlation (Rs) = 0.325, 0.232 (n = 218, 217) respectively, p < 0.01). Interestingly, sCD320 correlates to p-tau and t-tau (Rs = 0.599, 0.569 (n = 173, 176) respectively, p < 0.001) and to Aß (Rs = 0.265, p < 0.001 (n = 177)). CONCLUSION: We document for the first time the occurrence of sCD320 in human CSF. We report that the concentration of sCD320 correlates to the dementia-related biomarkers p-tau, t-tau and Aß.

The soluble receptor for vitamin B12 uptake (sCD320) increases during pregnancy and occurs in higher concentration in urine than in serum.

BACKGROUND: Cellular uptake of vitamin B12 (B12) demands binding of the vitamin to transcobalamin (TC) and recognition of TC-B12 (holoTC) by the receptor CD320, a receptor expressed in high quantities on human placenta. We have identified a soluble form of CD320 (sCD320) in serum and here we present data on the occurrence of this soluble receptor in both serum and urine during pregnancy. METHODS: We examined serum from twenty-seven pregnant women (cohort 1) at gestational weeks 13, 24 and 36 and serum and urine samples from forty pregnant women (cohort 2) tested up to 8 times during gestational weeks 17-41. sCD320, holoTC, total TC and complex formation between holoTC and sCD320 were measured by in-house ELISA methods, while creatinine was measured on the automatic platform Cobas 6000. Size exclusion chromatography was performed on a Superdex 200 column. RESULTS: Median (range) of serum sCD320 increased from 125 (87-839) pmol/L (week 15) to reach a peak value of 199 (72-672) pmol/L (week 35) then dropped back to its baseline level just before birth (week 40). Around one third of sCD320 was precipitated with holoTC at all-time points studied. The urinary concentration of sCD320 was around two fold higher than in serum. Urinary sCD320/creatinine ratio correlated with serum sCD320 and reached a peak median level of 53 (30-101) pmol/mmol creatinine (week 35). sCD320 present in serum and urine showed the same elution pattern upon size exclusion chromatography. CONCLUSION: We report for the first time that sCD320 is present in urine and in a higher concentration than in serum and that serum and urine sCD320 increase during pregnancy. The high urinary concentration and the strong correlation between urinary and serum sCD320 suggests that sCD320 is filtered in the kidney.