Retrograde movements determine effective stem cell numbers in the intestine.

The morphology and functionality of the epithelial lining differ along the intestinal tract, but tissue renewal at all sites is driven by stem cells at the base of crypts1-3. Whether stem cell numbers and behaviour vary at different sites is unknown. Here we show using intravital microscopy that, despite similarities in the number and distribution of proliferative cells with an Lgr5 signature in mice, small intestinal crypts contain twice as many effective stem cells as large intestinal crypts. We find that, although passively displaced by a conveyor-belt-like upward movement, small intestinal cells positioned away from the crypt base can function as long-term effective stem cells owing to Wnt-dependent retrograde cellular movement. By contrast, the near absence of retrograde movement in the large intestine restricts cell repositioning, leading to a reduction in effective stem cell number. Moreover, after suppression of the retrograde movement in the small intestine, the number of effective stem cells is reduced, and the rate of monoclonal conversion of crypts is accelerated. Together, these results show that the number of effective stem cells is determined by active retrograde movement, revealing a new channel of stem cell regulation that can be experimentally and pharmacologically manipulated.

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches.

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimers, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.

Assessing the validity of driver gene identification tools for targeted genome sequencing data.

Motivation: Most cancer driver gene identification tools have been developed for whole-exome sequencing data. Targeted sequencing is a popular alternative to whole-exome sequencing for large cancer studies due to its greater depth at a lower cost per tumor. Unlike whole-exome sequencing, targeted sequencing only enables mutation calling for a selected subset of genes. Whether existing driver gene identification tools remain valid in that context has not previously been studied. Results: We evaluated the validity of seven popular driver gene identification tools when applied to targeted sequencing data. Based on whole-exome data of 14 different cancer types from TCGA, we constructed matching targeted datasets by keeping only the mutations overlapping with the pan-cancer MSK-IMPACT panel and, in the case of breast cancer, also the breast-cancer-specific B-CAST panel. We then compared the driver gene predictions obtained on whole-exome and targeted mutation data for each of the seven tools. Differences in how the tools model background mutation rates were the most important determinant of their validity on targeted sequencing data. Based on our results, we recommend OncodriveFML, OncodriveCLUSTL, 20/20+, dNdSCv, and ActiveDriver for driver gene identification in targeted sequencing data, whereas MutSigCV and DriverML are best avoided in that context. Availability and implementation: Code for the analyses is available at https://github.com/SchmidtGroupNKI/TGSdrivergene_validity.

Evaluation of HIV-1 derived lentiviral vectors as transductors of Mucopolysaccharidosis type IV a fibroblasts.

Mucopolysaccharidosis type IVA (MPS IVA) is a lysosomal storage disease produced by the deficiency of the N-acetylgalactosamine-6-sulfate sulfatase (GALNS) enzyme, leading to glycosaminoglycans (GAGs) accumulation. Since currently available treatments remain limited and unspecific, novel therapeutic approaches are essential for the disease treatment. In an attempt to reduce treatment limitations, gene therapy rises as a more effective and specific alternative. We present in this study the delivery assessment of GALNS and sulfatase-modifying factor 1 (SUMF1) genes via HIV-1 derived lentiviral vectors into fibroblasts from MPS IVA patients. After transduction, we determined GALNS enzymatic activity, lysosomal mass change, and autophagy pathway impairment. Additionally, we computationally assessed the effect of mutations over the enzyme-substrate interaction and phenotypic effects. The results showed that the co-transduction of MPS IVA fibroblasts with GALNS and SUMF1 cDNAs led to a significant increase in GALNS enzyme activity and a reduction of lysosomal mass. We show that patient-specific differences in cellular response are directly associated with the set of mutations on each patient. Lastly, we present new evidence supporting autophagy impairment in MPS IVA due to the presence and changes in autophagy proteins in treated MPS IVA fibroblasts. Our results offer new evidence that demonstrate the potential of lentiviral vectors as a strategy to correct GALNS deficiency.

Machine Learning Neuroprotective Strategy Reveals a Unique Set of Parkinson Therapeutic Nicotine Analogs.

AIMS: Present a novel machine learning computational strategy to predict the neuroprotection potential of nicotine analogs acting over the behavior of unpaired signaling pathways in Parkinson's disease. BACKGROUND: Dopaminergic replacement has been used for Parkinson's Disease (PD) treatment with positive effects on motor symptomatology but low progression and prevention effects. Epidemiological studies have shown that nicotine consumption decreases PD prevalence through neuroprotective mechanisms activation associated with the overstimulation of signaling pathways (SP) such as PI3K/AKT through nicotinic acetylcholine receptors (e.g α7 nAChRs) and over-expression of anti-apoptotic genes such as Bcl-2. Nicotine analogs with similar neuroprotective activity but decreased secondary effects remain as a promissory field. OBJECTIVE: The objective of this study is to develop an interdisciplinary computational strategy predicting the neuroprotective activity of a series of 8 novel nicotine analogs over Parkinson's disease. METHODS: We present a computational strategy integrating structural bioinformatics, SP manual reconstruction, and deep learning to predict the potential neuroprotective activity of 8 novel nicotine analogs over the behavior of PI3K/AKT. We performed a protein-ligand analysis between nicotine analogs and α7 nAChRs receptor using geometrical conformers, physicochemical characterization of the analogs and developed manually curated neuroprotective datasets to analyze their potential activity. Additionally, we developed a predictive machine-learning model for neuroprotection in PD through the integration of Markov Chain Monte-Carlo transition matrix for the 2 SP with synthetic training datasets of the physicochemical properties and structural dataset. RESULTS: Our model was able to predict the potential neuroprotective activity of seven new nicotine analogs based on the binomial Bcl-2 response regulated by the activation of PI3K/AKT. CONCLUSION: Hereby, we present a robust novel strategy to assess the neuroprotective potential of biomolecules based on SP architecture. Our theoretical strategy can be further applied to the study of new treatments related to SP deregulation and may ultimately offer new opportunities for therapeutic interventions in neurodegenerative diseases.

Structural and functional computational analysis of nicotine analogs as potential neuroprotective compounds in Parkinson disease.

As the mechanism of interaction between nicotinic receptors with nicotine analogs is not yet fully understood, information at molecular level obtained from computational calculations is needed. In this sense, this work is a computational study of eight nicotine analogs, all with pyrrolidine ring modifications over a nicotine-based backbone optimized with B3LYP-D3/aug-cc-pVDZ. A molecular characterization was performed focusing on geometrical parameters such as pseudo-rotation angles, atomic charges, HOMO and LUMO orbitals, reactivity indexes and intermolecular interactions. Three analogs, A2 (3-(1,3-dimethyl-4,5-dihydro-1h-pirazole-5-yl) pyridine), A3 (3-(3-methyl-4,5-dihydro-1H-pyrazol-5-yl)-pyridine) and A8 (5-methyl-3-(pyridine-3-yl)-4,5-dihydroisoxazole), were filtered suggesting putative neuroprotective activity taking into account different reactivity values, such as their lowest hardness: 2.37 eV (A8), 2.43 eV (A2) and 2.56 eV (A3), compared to the highest hardness value found: 2.71 eV for A5 (3-((2S,4R)-4-(fluoromethyl)-1-methylpyrrolidine-2-il) pyridine), similar to the value of nicotine (2.70 eV). Additionally, molecular docking of all 8 nicotine analogs with the α 7 nicotinic acetylcholine receptor (α 7 nAChR) was performed. High values of interaction between the receptor and the three nicotine analogs were obtained: A3 (-7.1 kcal/mol), A2 (-6.9 kcal/mol) and A8 (-6.8 kcal/mol); whereas the affinity energy of nicotine was -6.4 kcal/mol. Leu116 and Trp145 are key residues in the binding site of α 7 nAChR interacting with nicotine analogs. Therefore, based upon these results, possible application of these nicotine analogs as neuroprotective compounds and potential implication at the design of novel Parkinson's treatments is evidenced.

Change in the Pattern of Posttransplantation Anemia in Kidney Receptors: Sex Role in Recipients and Type of Donor.

OBJECTIVE: Posttransplant anemia (PTA) in kidney recipients is a complication that has repercussions mainly of cardiovascular consequence. The objective of this study is to determine the prevalence of anemia, as well as the relationship between kidney recipient and donor sex, in the presence or absence of anemia at 12 months after kidney transplant (KT). MATERIAL AND METHODS: Observational, longitudinal study of KTs made over a 5-year period, from 2013 to 2017, in a renal transplant unit from La Raza National Health Care Medical Center. Three hundred twenty-eight records were analyzed. Hemoglobin (Hb) and the presence or absence of anemia according to the definition by the World Health Organization were analyzed. The association between kidney recipient sex and donor type (living or deceased) was evaluated. Analysis of central tendency and dispersion were performed and the mean difference was established with χ2 test or Student t test. Significance level was set at P < .05. RESULTS: The mean Hb (standard deviation) before KT was 10.38 (2.16) g/dL; Hb at 12 months was 14.47 (2.37) g/dL with an absolute increase of 4.09 g/dL. Before KT, male kidney recipients had a mean Hb of 10.54 (2.17) g/dL. At 12 months post-KT, mean Hb was 15.33 (2.25) with a change of 4.79 g/dL. Before KT, female kidney recipients had a mean Hb of 10.16 (2.13) g/dL. At 12 months post-KT, mean Hb was 13.31 (2.01) with a change of 3.15 g/dL. The difference between both sexes was 1.64 g/dL at the end of 12 months. Sixteen out of 152 (10.5%) patients had a serum creatinine (Cr) < 1.2 mg/dL and anemia; 36 out of 176 (20.5%) patients had a Cr ≥ 1.2 mg/dL and anemia (P = .014). In the bivariate logistic regression with an odds ratio of 2.047 (95% confidence interval, 1027-4078; P = .042) for higher Cr levels and the presence of persistent anemia. CONCLUSIONS: There is a prevalence of anemia in female kidney recipients and recipients of kidneys from deceased donors. There is a higher risk of persistent anemia in the case of patients with some degree of graft failure at 12 months.