Nitrogen-containing bisphosphonates are associated with reduced risk of pneumonia in patients with hip fracture

The objective of this work was to study the risk of pneumonia and pneumonia mortality among patients receiving nitrogen‐containing bisphosphonates (N‐BPs), non‐N‐BP anti‐osteoporosis medications, and no anti‐osteoporosis medications after hip fracture. We studied a historical cohort using a population‐wide database. Patients with first hip fracture during 2005–2015 were identified and matched by time‐dependent propensity score. The cohort was followed until December 31, 2016, to capture any pneumonia and pneumonia mortality. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox‐proportional hazards regression. Absolute risk difference (ARD) and number needed to treat (NNT) were calculated. We identified 54,047 patients with hip fracture. Of these, 4041 patients who received N‐BPs and 11,802 without anti‐osteoporosis medication were propensity score–matched. N‐BPs were associated with a significantly lower risk of pneumonia compared with no treatment (6.9 versus 9.0 per 100 person‐years; HR 0.76; 95% CI, 0.70 to 0.83), resulting in an ARD of 0.02 and NNT of 46. A similar association was observed with pneumonia mortality (HR 0.65; 95% CI, 0.56 to 0.75). When N‐BPs were compared with non‐N‐BP anti‐osteoporosis medications, the association remained significant. N‐BPs were associated with lower risks of pneumonia and pneumonia mortality. Randomized controlled trials are now required to determine whether N‐BPs, non–vaccine‐based medications, can reduce pneumonia incidence in high risk groups

The Combination of Curaxin CBL0137 and Histone Deacetylase Inhibitor Panobinostat Delays KMT2A-Rearranged Leukemia Progression

Rearrangements of the Mixed Lineage Leukemia (MLL/KMT2A) gene are present in approximately 10% of acute leukemias and characteristically define disease with poor outcome. Driven by the unmet need to develop better therapies for KMT2A-rearranged leukemia, we previously discovered that the novel anti-cancer agent, curaxin CBL0137, induces decondensation of chromatin in cancer cells, delays leukemia progression and potentiates standard of care chemotherapies in preclinical KMT2A-rearranged leukemia models. Based on the promising potential of histone deacetylase (HDAC) inhibitors as targeted anti-cancer agents for KMT2A-rearranged leukemia and the fact that HDAC inhibitors also decondense chromatin via an alternate mechanism, we investigated whether CBL0137 could potentiate the efficacy of the HDAC inhibitor panobinostat in KMT2A-rearranged leukemia models. The combination of CBL0137 and panobinostat rapidly killed KMT2A-rearranged leukemia cells by apoptosis and significantly delayed leukemia progression and extended survival in an aggressive model of MLL-AF9 (KMT2A:MLLT3) driven murine acute myeloid leukemia. The drug combination also exerted a strong anti-leukemia response in a rapidly progressing xenograft model derived from an infant with KMT2A-rearranged acute lymphoblastic leukemia, significantly extending survival compared to either monotherapy. The therapeutic enhancement between CBL0137 and panobinostat in KMT2A-r leukemia cells does not appear to be mediated through cooperative effects of the drugs on KMT2A rearrangement-associated histone modifications. Our data has identified the CBL0137/panobinostat combination as a potential novel targeted therapeutic approach to improve outcome for KMT2A-rearranged leukemia

Genetical genomics: spotlight on QTL hotspots

No abstract available

Determinants of medication adherence to antihypertensive medications among a Chinese population using Morisky medication adherence scale

<b>Background and objectives</b> Poor adherence to medications is one of the major public health challenges. Only one-third of the population reported successful control of blood pressure, mostly caused by poor drug adherence. However, there are relatively few reports studying the adherence levels and their associated factors among Chinese patients. This study aimed to study the adherence profiles and the factors associated with antihypertensive drug adherence among Chinese patients.<p></p> <b>Methods</b> A cross-sectional study was conducted in an outpatient clinic located in the New Territories Region of Hong Kong. Adult patients who were currently taking at least one antihypertensive drug were invited to complete a self-administered questionnaire, consisting of basic socio-demographic profile, self-perceived health status, and self-reported medication adherence. The outcome measure was the Morisky Medication Adherence Scale (MMAS-8). Good adherence was defined as MMAS scores greater than 6 points (out of a total score of 8 points).<p></p> <b>Results</b> From 1114 patients, 725 (65.1%) had good adherence to antihypertensive agents. Binary logistic regression analysis was conducted. Younger age, shorter duration of antihypertensive agents used, job status being employed, and poor or very poor self-perceived health status were negatively associated with drug adherence.<p></p> <b>Conclusion</b> This study reported a high proportion of poor medication adherence among hypertensive subjects. Patients with factors associated with poor adherence should be more closely monitored to optimize their drug taking behavior

Gauging the Effectiveness of Educational Technology Integration in Education: What the Best-Quality Meta-Analyses Tell Us

This chapter examines quantitative research in the literature of technology integration in education from the perspective of the meta-analyses of primary studies conducted from 1982 to 2015. The intent is to identify and review the best of these meta-analyses. Fifty-two meta-analyses were originally identified and evaluated for methodological quality using the Meta-Analysis Methodological Quality Review Guide (MMQRG), and the best 20 were selected and are included for review here. Some describe the effects of technology integration within specific content areas and some are more general. Technology integration in education is one of the most fluid areas of research, reflecting the incredible pace of the evolution of computer-based tools and applications. Just navigating through the vast primary empirical literature presents a real challenge to those interested in evaluating the educational effectiveness of technology. Systematic reviews in the field are numerous and quite diverse in their methodological quality, introducing potential bias in the interpretation of findings (Bernard RM, Borokhovski E, Schmid RF, Tamim RM. J Comput High Educ 26(3):183–209, 2014), thus bringing into question their applied value. This chapter identifies and reviews the best of these meta-analyses. In addition to overall statistical analyses of this collection, the findings of six of the most recent and best meta-analyses (after 2010) are summarized in more detail. The discussion focuses on the interpretation of the current findings, considers future alternatives to primary research in this area, and examines how meta-analysts might address them

Solution structure of a repeated unit of the ABA-1 nematode polyprotein allergen of ascaris reveals a novel fold and two discrete lipid-binding sites

Parasitic nematode worms cause serious health problems in humans and other animals. They can induce allergic-type immune responses, which can be harmful but may at the same time protect against the infections. Allergens are proteins that trigger allergic reactions and these parasites produce a type that is confined to nematodes, the nematode polyprotein allergens (NPAs). These are synthesized as large precursor proteins comprising repeating units of similar amino acid sequence that are subsequently cleaved into multiple copies of the allergen protein. NPAs bind small lipids such as fatty acids and retinol (Vitamin A) and probably transport these sensitive and insoluble compounds between the tissues of the worms. Nematodes cannot synthesize these lipids, so NPAs may also be crucial for extracting nutrients from their hosts. They may also be involved in altering immune responses by controlling the lipids by which the immune and inflammatory cells communicate. We describe the molecular structure of one unit of an NPA, the well-known ABA-1 allergen of Ascaris and find its structure to be of a type not previously found for lipid-binding proteins, and we describe the unusual sites where lipids bind within this structur

Using Network Component Analysis to Dissect Regulatory Networks Mediated by Transcription Factors in Yeast

Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA) to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs) perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request

Preclinical efficacy of azacitidine and venetoclax for infant KMT2A-rearranged acute lymphoblastic leukemia reveals a new therapeutic strategy

Infants with KMT2A-rearranged B-cell acute lymphoblastic leukemia (ALL) have a dismal prognosis. Survival outcomes have remained static in recent decades despite treatment intensification and novel therapies are urgently required. KMT2A-rearranged infant ALL cells are characterized by an abundance of promoter hypermethylation and exhibit high BCL-2 expression, highlighting potential for therapeutic targeting. Here, we show that hypomethylating agents exhibit in vitro additivity when combined with most conventional chemotherapeutic agents. However, in a subset of samples an antagonistic effect was seen between several agents. This was most evident when hypomethylating agents were combined with methotrexate, with upregulation of ATP-binding cassette transporters identified as a potential mechanism. Single agent treatment with azacitidine and decitabine significantly prolonged in vivo survival in KMT2A-rearranged infant ALL xenografts. Treatment of KMT2A-rearranged infant ALL cell lines with azacitidine and decitabine led to differential genome-wide DNA methylation, changes in gene expression and thermal proteome profiling revealed the target protein-binding landscape of these agents. The selective BCL-2 inhibitor, venetoclax, exhibited in vitro additivity in combination with hypomethylating or conventional chemotherapeutic agents. The addition of venetoclax to azacitidine resulted in a significant in vivo survival advantage indicating the therapeutic potential of this combination to improve outcome for infants with KMT2A-rearranged ALL

Attention-dependent modulation of cortical taste circuits revealed by granger causality with signal-dependent noise

We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention