LEDGF1-326 Decreases P23H and Wild Type Rhodopsin Aggregates and P23H Rhodopsin Mediated Cell Damage in Human Retinal Pigment Epithelial Cells

P23H rhodopsin, a mutant rhodopsin, is known to aggregate and cause retinal degeneration. However, its effects on retinal pigment epithelial (RPE) cells are unknown. The purpose of this study was to determine the effect of P23H rhodopsin in RPE cells and further assess whether LEDGF(1-326), a protein devoid of heat shock elements of LEDGF, a cell survival factor, reduces P23H rhodopsin aggregates and any associated cellular damage.ARPE-19 cells were transiently transfected/cotransfected with pLEDGF(1-326) and/or pWT-Rho (wild type)/pP23H-Rho. Rhodopsin mediated cellular damage and rescue by LEDGF(1-326) was assessed using cell viability, cell proliferation, and confocal microscopy assays. Rhodopsin monomers, oligomers, and their reduction in the presence of LEDGF(1-326) were quantified by western blot analysis. P23H rhodopsin mRNA levels in the presence and absence of LEDGF(1-326) was determined by real time quantitative PCR.P23H rhodopsin reduced RPE cell viability and cell proliferation in a dose dependent manner, and disrupted the nuclear material. LEDGF(1-326) did not alter P23H rhodopsin mRNA levels, reduced its oligomers, and significantly increased RPE cell viability as well as proliferation, while reducing nuclear damage. WT rhodopsin formed oligomers, although to a smaller extent than P23H rhodopsin. Further, LEDGF(1-326) decreased WT rhodopsin aggregates.P23H rhodopsin as well as WT rhodopsin form aggregates in RPE cells and LEDGF(1-326) decreases these aggregates. Further, LEDGF(1-326) reduces the RPE cell damage caused by P23H rhodopsin. LEDGF(1-326) might be useful in treating cellular damage associated with protein aggregation diseases such as retinitis pigmentosa

The phylogenetically-related pattern recognition receptors EFR and XA21 recruit similar immune signaling components in monocots and dicots

During plant immunity, surface-localized pattern recognition receptors (PRRs) recognize pathogen-associated molecular patterns (PAMPs). The transfer of PRRs between plant species is a promising strategy for engineering broad-spectrum disease resistance. Thus, there is a great interest in understanding the mechanisms of PRR-mediated resistance across different plant species. Two well-characterized plant PRRs are the leucine-rich repeat receptor kinases (LRR-RKs) EFR and XA21 from Arabidopsis thaliana (Arabidopsis) and rice, respectively. Interestingly, despite being evolutionary distant, EFR and XA21 are phylogenetically closely related and are both members of the sub-family XII of LRR-RKs that contains numerous potential PRRs. Here, we compared the ability of these related PRRs to engage immune signaling across the monocots-dicots taxonomic divide. Using chimera between Arabidopsis EFR and rice XA21, we show that the kinase domain of the rice XA21 is functional in triggering elf18-induced signaling and quantitative immunity to the bacteria Pseudomonas syringae pv. tomato (Pto) DC3000 and Agrobacterium tumefaciens in Arabidopsis. Furthermore, the EFR:XA21 chimera associates dynamically in a ligand-dependent manner with known components of the EFR complex. Conversely, EFR associates with Arabidopsis orthologues of rice XA21-interacting proteins, which appear to be involved in EFR-mediated signaling and immunity in Arabidopsis. Our work indicates the overall functional conservation of immune components acting downstream of distinct LRR-RK-type PRRs between monocots and dicots

How are falls and fear of falling associated with objectively measured physical activity in a cohort of community-dwelling older men?

BACKGROUND: Falls affect approximately one third of community-dwelling older adults each year and have serious health and social consequences. Fear of falling (FOF) (lack of confidence in maintaining balance during normal activities) affects many older adults, irrespective of whether they have actually experienced falls. Both falls and fear of falls may result in restrictions of physical activity, which in turn have health consequences. To date the relation between (i) falls and (ii) fear of falling with physical activity have not been investigated using objectively measured activity data which permits examination of different intensities of activity and sedentary behaviour. METHODS: Cross-sectional study of 1680 men aged 71-92 years recruited from primary care practices who were part of an on-going population-based cohort. Men reported falls history in previous 12 months, FOF, health status and demographic characteristics. Men wore a GT3x accelerometer over the hip for 7 days. RESULTS: Among the 12% of men who had recurrent falls, daily activity levels were lower than among non-fallers; 942 (95% CI 503, 1381) fewer steps/day, 12(95% CI 2, 22) minutes less in light activity, 10(95% CI 5, 15) minutes less in moderate to vigorous PA [MVPA] and 22(95% CI 9, 35) minutes more in sedentary behaviour. 16% (n = 254) of men reported FOF, of whom 52% (n = 133) had fallen in the past year. Physical activity deficits were even greater in the men who reported that they were fearful of falling than in men who had fallen. Men who were fearful of falling took 1766(95% CI 1391, 2142) fewer steps/day than men who were not fearful, and spent 27(95% CI 18, 36) minutes less in light PA, 18(95% CI 13, 22) minutes less in MVPA, and 45(95% CI 34, 56) minutes more in sedentary behaviour. The significant differences in activity levels between (i) fallers and non-fallers and (ii) men who were fearful of falling or not fearful, were mediated by similar variables; lower exercise self-efficacy, fewer excursions from home and more mobility difficulties. CONCLUSIONS: Falls and in particular fear of falling are important barriers to older people gaining health benefits of walking and MVPA. Future studies should assess the longitudinal associations between falls and physical activity

A miRNA-Target Prediction Case Study

Giansanti, V., Castelli, M., Beretta, S., & Merelli, I. (2019). Comparing Deep and Machine Learning Approaches in Bioinformatics: A miRNA-Target Prediction Case Study. In V. V. Krzhizhanovskaya, M. H. Lees, P. M. A. Sloot, J. J. Dongarra, J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, ... R. Lam (Eds.), Computational Science – ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part III (pp. 31-44). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11538 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-22744-9_3MicroRNAs (miRNAs) are small non-coding RNAs with a key role in the post-transcriptional gene expression regularization, thanks to their ability to link with the target mRNA through the complementary base pairing mechanism. Given their role, it is important to identify their targets and, to this purpose, different tools were proposed to solve this problem. However, their results can be very different, so the community is now moving toward the deployment of integration tools, which should be able to perform better than the single ones. As Machine and Deep Learning algorithms are now in their popular years, we developed different classifiers from both areas to verify their ability to recognize possible miRNA-mRNA interactions and evaluated their performance, showing the potentialities and the limits that those algorithms have in this field. Here, we apply two deep learning classifiers and three different machine learning models to two different miRNA-mRNA datasets, of predictions from 3 different tools: TargetScan, miRanda, and RNAhybrid. Although an experimental validation of the results is needed to better confirm the predictions, deep learning techniques achieved the best performance when the evaluation scores are taken into account.authorsversionpublishe

Lean mass, muscle strength, and physical function in a diverse population of men: a population-based cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Age-related declines in lean body mass appear to be more rapid in men than in women but our understanding of muscle mass and function among different subgroups of men and their changes with age is quite limited. The objective of this analysis is to examine racial/ethnic differences and racial/ethnic group-specific cross-sectional age differences in measures of muscle mass, muscle strength, and physical function among men.</p> <p>Methods</p> <p>Data were obtained from the Boston Area Community Health/Bone (BACH/Bone) Survey, a population-based, cross-sectional, observational survey. Subjects included 1,157 black, Hispanic, and white randomly-selected Boston men ages 30-79 y. Lean mass was assessed by dual-energy x-ray absorptiometry. Upper extremity (grip) strength was assessed with a hand dynamometer and lower extremity physical function was derived from walk and chair stand tests. Upper extremity strength and lower extremity physical function were also indexed by lean mass and lean mass was indexed by the square of height.</p> <p>Results</p> <p>Mean age of the sample was 47.5 y. Substantial cross-sectional age differences in grip strength and physical function were consistent across race/ethnicity. Racial/ethnic differences, with and without adjustment for covariates, were evident in all outcomes except grip strength. Racial differences in lean mass did not translate into parallel differences in physical function. For instance, multivariate modeling (with adjustments for age, height, fat mass, self-rated health and physical activity) indicated that whereas total body lean mass was 2.43 kg (approximately 5%) higher in black compared with white men, black men had a physical function score that was approximately 20% lower than white men.</p> <p>Conclusions</p> <p>In spite of lower levels of lean mass, the higher levels of physical function observed among white compared with non-white men in this study appear to be broadly consistent with known racial/ethnic differences in outcomes.</p

Selective modulation of subtype III IP3R by Akt regulates ER Ca2+ release and apoptosis

Ca2+ transfer from endoplasmic reticulum (ER) to mitochondria can trigger apoptotic pathways by inducing release of mitochondrial pro-apoptotic factors. Three different types of inositol 1,4,5-trisphosphate receptor (IP3R) serve to discharge Ca2+ from ER, but possess some peculiarities, especially in apoptosis induction. The anti-apoptotic protein Akt can phosphorylate all IP3R isoforms and protect cells from apoptosis, reducing ER Ca2+ release. However, it has not been elucidated which IP3R subtypes mediate these effects. Here, we show that Akt activation in COS7 cells, which lack of IP3R I, strongly suppresses IP3-mediated Ca2+ release and apoptosis. Conversely, in SH-SY 5Y cells, which are type III-deficient, Akt is unable to modulate ER Ca2+ flux, losing its anti-apoptotic activity. In SH-SY 5Y-expressing subtype III, Akt recovers its protective function on cell death, by reduction of Ca2+ release. Moreover, regulating Ca2+ flux to mitochondria, Akt maintains the mitochondrial integrity and delays the trigger of apoptosis, in a type III-dependent mechanism. These results demonstrate a specific activity of Akt on IP3R III, leading to diminished Ca2+ transfer to mitochondria and protection from apoptosis, suggesting an additional level of cell death regulation mediated by Akt

miREE: miRNA recognition elements ensemble

Abstract Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between sensitivity and specificity. miREE obtains a reasonable trade-off between filtering false positives and identifying targets. miREE tool is available online at http://didattica-online.polito.it/eda/miREE/</p

Pharmacodynamic evaluation of commonly prescribed oral antibiotics against respiratory bacterial pathogens

<p>Abstract</p> <p>Background</p> <p>Upper and lower respiratory tract infections (RTIs) account for a substantial portion of outpatient antibiotic utilization. However, the pharmacodynamic activity of commonly used oral antibiotic regimens has not been studied against clinically relevant pathogens. The objective of this study was to assess the probability of achieving the requisite pharmacodynamic exposure for oral antibacterial regimens commonly prescribed for RTIs in adults against bacterial isolates frequently involved in these processes (<it>S. pneumoniae</it>, <it>H. influenzae</it>, and <it>M. catharralis</it>).</p> <p>Methods</p> <p>Using a 5000-subject Monte Carlo simulation, the cumulative fractions of response (CFR), (i.e., probabilities of achieving requisite pharmacodynamic targets) for the most commonly prescribed oral antibiotic regimens, as determined by a structured survey of medical prescription patterns, were assessed against local respiratory bacterial isolates from adults in São Paulo collected during the same time period. Minimal inhibitory concentration (MIC) of 230 isolates of <it>Streptococcus pneumoniae </it>(103), <it>Haemophilus influenzae </it>(98), and <it>Moraxella catharralis </it>(29) from a previous local surveillance were used.</p> <p>Results</p> <p>The most commonly prescribed antibiotic regimens were azithromycin 500 mg QD, amoxicillin 500 mg TID, and levofloxacin 500 mg QD, accounting for 58% of the prescriptions. Varied doses of these agents, plus gatifloxacin, amoxicillin-clavulanate, moxifloxacin, and cefaclor made up the remaining regimens. Utilizing aggressive pharmacodynamic exposure targets, the only regimens to achieve greater than 90% CFR against all three pathogens were amoxicillin/amoxicillin-clavulanate 500 mg TID (> 91%), gatifloxacin 400 mg QD (100%), and moxifloxacin 400 mg QD (100%). Considering <it>S. pneumoniae </it>isolates alone, azithromycin 1000 mg QD also achieved greater than 90% CFR (91.3%).</p> <p>Conclusions</p> <p>The only regimens to achieve high CFR against all three pathogen populations in both scenarios were gatifloxacin 400 mg QD, moxifloxacin 400 mg QD, and amoxicillin-clavulanate 500 mg TID. These data suggest the need for reconsideration of empiric antibiotic regimen selection among adult patients with RTIs in the São Paulo area. Additionally, this type of study could be used to optimize prescribing patterns in specific regions in light of emerging resistance.</p