Dementia assessment and management in primary care settings: a survey of current provider practices in the United States.

BACKGROUND:Primary care providers (PCPs) are typically the first to screen and evaluate patients for neurocognitive disorders (NCDs), including mild cognitive impairment and dementia. However, data on PCP attitudes and evaluation and management practices are sparse. Our objective was to quantify perspectives and behaviors of PCPs and neurologists with respect to NCD evaluation and management. METHODS:A cross-sectional survey with 150 PCPs and 50 neurologists in the United States who evaluated more than 10 patients over age 55 per month. The 51-item survey assessed clinical practice characteristics, and confidence, perceived barriers, and typical practices when diagnosing and managing patients with NCDs. RESULTS:PCPs and neurologists reported similar confidence and approaches to general medical care and laboratory testing. Though over half of PCPs performed cognitive screening or referred patients for cognitive testing in over 50% of their patients, only 20% reported high confidence in interpreting results of cognitive tests. PCPs were more likely to order CT scans than MRIs, and only 14% of PCPs reported high confidence interpreting brain imaging findings, compared to 70% of specialists. Only 21% of PCPs were highly confident that they correctly recognized when a patient had an NCD, and only 13% were highly confident in making a specific NCD diagnosis (compared to 72 and 44% for neurologists, both p < 0.001). A quarter of all providers identified lack of familiarity with diagnostic criteria for NCD syndromes as a barrier to clinical practice. CONCLUSIONS:This study demonstrates how PCPs approach diagnosis and management of patients with NCDs, and identified areas for improvement in regards to cognitive testing and neuroimaging. This study also identified all providers' lack of familiarity with published diagnostic criteria for NCD syndromes. These findings may inform the development of new policies and interventions to help providers improve the efficacy of their decision processes and deliver better quality care to patients with NCDs

Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry.

Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC) adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05). Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection

Dysregulated Erythroid Mg2+ Efflux in Type 2 Diabetes

CEECIND/01053/2017 UIDB/04647/2020 UIDP/04647/2020Hyperglycemia is associated with decreased Mg2+ content in red blood cells (RBC), but mechanisms remain unclear. We characterized the regulation of Mg2+ efflux by glucose in ex vivo human RBC. We observed that hemoglobin A1C (HbA1C) values correlated with Na+-dependent Mg2+ efflux (Na+/Mg2+ exchange) and inversely correlated with cellular Mg content. Treatment of cells with 50 mM D-glucose, but not with sorbitol, lowered total cellular Mg (2.2 ± 0.1 to 2.0 ± 0.1 mM, p < 0.01) and enhanced Na+/Mg2+ exchange activity [0.60 ± 0.09 to 1.12 ± 0.09 mmol/1013 cell × h (flux units, FU), p < 0.05]. In contrast, incubation with selective Src family kinase inhibitors PP2 or SU6656 reduced glucose-stimulated exchange activation (p < 0.01). Na+/Mg2+ exchange activity was also higher in RBC from individuals with type 2 diabetes (T2D, 1.19 ± 0.13 FU) than from non-diabetic individuals (0.58 ± 0.05 FU, p < 0.01). Increased Na+/Mg2+ exchange activity in RBC from T2D subjects was associated with lower intracellular Mg content. Similarly increased exchange activity was evident in RBC from the diabetic db/db mouse model as compared to its non-diabetic control (p < 0.03). Extracellular exposure of intact RBC from T2D subjects to recombinant peptidyl-N-glycosidase F (PNGase F) reduced Na+/Mg2+ exchange activity from 0.98 ± 0.14 to 0.59 ± 0.13 FU (p < 0.05) and increased baseline intracellular Mg content (1.8 ± 0.1 mM) to normal values (2.1 ± 0.1 mM, p < 0.05). These data suggest that the reduced RBC Mg content of T2D RBC reflects enhanced RBC Na+/Mg2+ exchange subject to regulation by Src family kinases and by the N-glycosylation state of one or more membrane proteins. The data extend our understanding of dysregulated RBC Mg2+ homeostasis in T2D.publishersversionpublishe

Long-Chain Fatty Acid Combustion Rate Is Associated with Unique Metabolite Profiles in Skeletal Muscle Mitochondria

Incomplete or limited long-chain fatty acid (LCFA) combustion in skeletal muscle has been associated with insulin resistance. Signals that are responsive to shifts in LCFA beta-oxidation rate or degree of intramitochondrial catabolism are hypothesized to regulate second messenger systems downstream of the insulin receptor. Recent evidence supports a causal link between mitochondrial LCFA combustion in skeletal muscle and insulin resistance. We have used unbiased metabolite profiling of mouse muscle mitochondria with the aim of identifying candidate metabolites within or effluxed from mitochondria and that are shifted with LCFA combustion rate.Large-scale unbiased metabolomics analysis was performed using GC/TOF-MS on buffer and mitochondrial matrix fractions obtained prior to and after 20 min of palmitate catabolism (n = 7 mice/condition). Three palmitate concentrations (2, 9 and 19 microM; corresponding to low, intermediate and high oxidation rates) and 9 microM palmitate plus tricarboxylic acid (TCA) cycle and electron transport chain inhibitors were each tested and compared to zero palmitate control incubations. Paired comparisons of the 0 and 20 min samples were made by Student's t-test. False discovery rate were estimated and Type I error rates assigned. Major metabolite groups were organic acids, amines and amino acids, free fatty acids and sugar phosphates. Palmitate oxidation was associated with unique profiles of metabolites, a subset of which correlated to palmitate oxidation rate. In particular, palmitate oxidation rate was associated with distinct changes in the levels of TCA cycle intermediates within and effluxed from mitochondria.This proof-of-principle study establishes that large-scale metabolomics methods can be applied to organelle-level models to discover metabolite patterns reflective of LCFA combustion, which may lead to identification of molecules linking muscle fat metabolism and insulin signaling. Our results suggest that future studies should focus on the fate of effluxed TCA cycle intermediates and on mechanisms ensuring their replenishment during LCFA metabolism in skeletal muscle

Allelic Diversity at Abiotic Stress Responsive Genes in Relationship to Ecological Drought Indices for Cultivated Tepary Bean, Phaseolus acutifolius A. Gray, and Its Wild Relatives

Some of the major impacts of climate change are expected in regions where drought stress is already an issue. Grain legumes are generally drought susceptible. However, tepary bean and its wild relatives within Phaseolus acutifolius or P. parvifolius are from arid areas between Mexico and the United States. Therefore, we hypothesize that these bean accessions have diversity signals indicative of adaptation to drought at key candidate genes such as: Asr2, Dreb2B, and ERECTA. By sequencing alleles of these genes and comparing to estimates of drought tolerance indices from climate data for the collection site of geo-referenced, tepary bean accessions, we determined the genotype x environmental association (GEA) of each gene. Diversity analysis found that cultivated and wild P. acutifolius were intermingled with var. tenuifolius and P. parvifolius, signifying that allele diversity was ample in the wild and cultivated clade over a broad sense (sensu lato) evaluation. Genes Dreb2B and ERECTA harbored signatures of directional selection, represented by six SNPs correlated with the environmental drought indices. This suggests that wild tepary bean is a reservoir of novel alleles at genes for drought tolerance, as expected for a species that originated in arid environments. Our study corroborated that candidate gene approach was effective for marker validation across a broad genetic base of wild tepary accessions

Top-Down Characterisation of an Antimicrobial Sanitiser, Leading from Quenchers of Efficacy to Mode of Action

We developed a top-down strategy to characterise an antimicrobial, oxidising sanitiser, which has diverse proposed applications including surface-sanitisation of fresh foods, and with benefits for water resilience. The strategy involved finding quenchers of antimicrobial activity then antimicrobial mode of action, by identifying key chemical reaction partners starting from complex matrices, narrowing down reactivity to specific organic molecules within cells. The sanitiser electrolysed-water (EW) retained partial fungicidal activity against the food-spoilage fungus Aspergillus niger at high levels of added soils (30–750 mg mL-1), commonly associated with harvested produce. Soil with high organic load (approx. 98 mg g-1) gave stronger EW inactivation. Marked inactivation by a complex organics mix (YEPD medium) was linked to its protein-rich components. Addition of pure proteins or amino acids (≤1 mg mL-1) fully suppressed EW activity. Mechanism was interrogated further with the yeast model, corroborating marked suppression of EW action by the amino acid methionine. Pre-culture with methionine increased resistance to EW, sodium hypochlorite, or chlorine-free ozonated water. Overexpression of methionine sulfoxide reductases (which reduce oxidised methionine) protected against EW. Fluoroprobe-based analyses indicated that methionine and cysteine inactivate free chlorine species in EW. Intracellular methionine oxidation can disturb cellular FeS-clusters and we showed that EW treatment impairs FeS-enzyme activity. The study establishes the value of a top-down approach for multi-level characterisation of sanitiser efficacy and action. The results reveal proteins and amino acids as key quenchers of EW activity and, among the amino acids, the importance of methionine oxidation and FeS-cluster damage for antimicrobial mode-of-action

A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in a Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are repeatedly revisited, and allows associations of more than one state to the same syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network hypothesis of how syntax is controlled within the premotor song nucleus HVC, and suggests that adaptation and many-to-one mapping from neural substrates to syllables are important features of the neural control of complex song syntax