Development and psychometric evaluation of the patient knowledge of, and attitudes and behaviours towards pressure ulcer prevention instrument (KPUP)

The Patient Knowledge of, and Attitude and Behaviour towards Pressure Ulcer Prevention Instrument (KPUP) was developed and validated using a two-stage prospective psychometric instrument validation study design. In Stage 1, the instrument was designed, and it is psychometrically evaluated in Stage 2. To establish content validity, two expert panels independently reviewed each item for appropriateness and relevance. Psychometric evaluation included construct validity and stability testing of the instrument. The questionnaire was administered to a convenience sample of 200 people aged more than 65 years, living independently in the community; reliability and stability were assessed by test/retest procedures, with a 1-week interval. Mean knowledge scores at 'test' were 11.54/20 (95% CI = 11.10-11.99, SD: 3.07), and 'retest' was 12.24 (95% CI = 11.81-12.66, SD: 2.93). For knowledge, correlation between the test/retest score was positive (r=. 60), attitude section-inter-item correlations ranged from r = -.31 to r = .57 (mean intraclass correlation coefficient of r = .42), and internal consistency for the retest was the same as the test (alpha = .41 for the eight items). For health behaviours, individual inter-item correlations for test items ranged from r = -.21 to r = .41 for the 13 standardised items. Psychometric testing of the KPUP in a sample of older persons in the community provided moderate internal consistency and general high test-retest stability

The Effect of Cone Opsin Mutations on Retinal Structure and the Integrity of the Photoreceptor Mosaic

Purpose. To evaluate retinal structure and photoreceptor mosaic integrity in subjects with OPN1LW and OPN1MW mutations. Methods. Eleven subjects were recruited, eight of whom have been previously described. Cone and rod density was measured using images of the photoreceptor mosaic obtained from an adaptive optics scanning light ophthalmoscope (AOSLO). Total retinal thickness, inner retinal thickness, and outer nuclear layer plus Henle fiber layer (ONL+HFL) thickness were measured using cross-sectional spectral-domain optical coherence tomography (SD-OCT) images. Molecular genetic analyses were performed to characterize the OPN1LW/OPN1MW gene array. Results. While disruptions in retinal lamination and cone mosaic structure were observed in all subjects, genotype-specific differences were also observed. For example, subjects with “L/M interchange” mutations resulting from intermixing of ancestral OPN1LW and OPN1MW genes had significant residual cone structure in the parafovea (∼25% of normal), despite widespread retinal disruption that included a large foveal lesion and thinning of the parafoveal inner retina. These subjects also reported a later-onset, progressive loss of visual function. In contrast, subjects with the C203R missense mutation presented with congenital blue cone monochromacy, with retinal lamination defects being restricted to the ONL+HFL and the degree of residual cone structure (8% of normal) being consistent with that expected for the S-cone submosaic. Conclusions. The photoreceptor phenotype associated with OPN1LW and OPN1MW mutations is highly variable. These findings have implications for the potential restoration of visual function in subjects with opsin mutations. Our study highlights the importance of high-resolution phenotyping to characterize cellular structure in inherited retinal disease; such information will be critical for selecting patients most likely to respond to therapeutic intervention and for establishing a baseline for evaluating treatment efficacy

Root responses to domestication, precipitation and silicification: weeping meadow grass simplifies and alters toughness

Background and aims Plant breeding usually focuses on conspicuous above-ground plant traits, yet roots fundamentally underpin plant fitness. Roots show phenotypic plasticity in response to soil conditions but it is unclear whether domesticated plants respond like their ancestors. We aimed to determine how root traits differed between ancestral and domesticated types of a meadow grass (Microlaena stipoides) under altered regimes of precipitation and soil silicon availability. Methods We subjected the two grass types to three simulated precipitation regimes (ambient, +50%/deluge and −50%/drought) in soil with (Si+) and without (Si−) silicon supplementation and then characterised root biomass, architectural complexity and toughness in addition to shoot traits. Results Domestication increased root tissue density, decreased specific root length (SRL) and decreased root architectural complexity. Domestication also increased root strength under Si− conditions but not Si+ conditions. Fine roots, SRL, architectural complexity and the force required to tear the roots all decreased under deluge. The ancestral and domesticated grasses responded similarly to precipitation, except that the latter had weaker roots (decreased fracture strain) under drought. Conclusions Domestication and increased precipitation caused changes in M. stipoides root traits that could be beneficial against some stresses (e.g. soil compaction, herbivory) but not others (e.g. drought)

Software Development and Market Research Process of Plasma Software Distribution

When trying to find the right software for scientific research, one may have to comb through the internet to acquire a suitable tool. Much of the scientific software online is in mostly unknown web pages where the only way to find the software is to already know about it, be told about it, or find the software by pure chance. Even worse, with few verification systems in place they may try a new program only for it to turn out to be malware. The search for the right software takes time away from the scientists, slowing the overall pace of scientific innovation. Plasma Software Distribution, a web application, intends to remove much of the busywork of finding the software, allowing scientists to do more of the work that improves lives

Bioinformatic Investigation into Mycobacterium phage DuncansLeg

Bacteriophage research is increasingly important to perform as antibacterial resistance becomes more common. The novel phage DuncansLeg was isolated and sequenced by students in the HHMI SEA-PHAGES Phage Discovery course in the fall of 2021 at Coastal Carolina University\u27s campus. The DNA sequence of DuncansLeg (75,593 base pairs) was subjected to bioinformatic auto-annotation, which placed the phage into subcluster L3. The scope of this investigation goes beyond lab work and discovery, instead focusing on applying multiple bioinformatic approaches to refine the genomic auto-annotation and assign potential gene functions where possible. To this end, the bioinformatic programs used to identify coding potential and gene starts were DNA Master, GeneMark, Starterator, and Phamerator. For the assignment of gene functions, pBLAST, HHpred, and synteny data were used in combination to provide evidence for functionality if possible. PECAAN software was then used to centralize data for further analytics. The results of these analyses and specific genomic regions will be discussed in this presentation of data

Exome-wide association study of pancreatic cancer risk

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P=3.27x10(-6); exome-wide statistical significance threshold P<2.5x10(-6)). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35, P=.045). At the suggestive threshold (P<.001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition

QFMatch: multidimensional flow and mass cytometry samples alignment

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples

Some investigations into non passive listening

Our knowledge of the function of the auditory nervous system is based upon a wealth of data obtained, for the most part, in anaesthetised animals. More recently, it has been generally acknowledged that factors such as attention profoundly modulate the activity of sensory systems and this can take place at many levels of processing. Imaging studies, in particular, have revealed the greater activation of auditory areas and areas outside of sensory processing areas when attending to a stimulus. We present here a brief review of the consequences of such non-passive listening and go on to describe some of the experiments we are conducting to investigate them. In imaging studies, using fMRI, we can demonstrate the activation of attention networks that are non-specific to the sensory modality as well as greater and different activation of the areas of the supra-temporal plane that includes primary and secondary auditory areas. The profuse descending connections of the auditory system seem likely to be part of the mechanisms subserving attention to sound. These are generally thought to be largely inactivated by anaesthesia. However, we have been able to demonstrate that even in an anaesthetised preparation, removing the descending control from the cortex leads to quite profound changes in the temporal patterns of activation by sounds in thalamus and inferior colliculus. Some of these effects seem to be specific to the ear of stimulation and affect interaural processing. To bridge these observations we are developing an awake behaving preparation involving freely moving animals in which it will be possible to investigate the effects of consciousness (by contrasting awake and anaesthetized), passive and active listening

AutoGate: automating analysis of flow cytometry data

Nowadays, one can hardly imagine biology and medicine without flow cytometry to measure CD4 T cell counts in HIV, follow bone marrow transplant patients, characterize leukemias, etc. Similarly, without flow cytometry, there would be a bleak future for stem cell deployment, HIV drug development and full characterization of the cells and cell interactions in the immune system. But while flow instruments have improved markedly, the development of automated tools for processing and analyzing flow data has lagged sorely behind. To address this deficit, we have developed automated flow analysis software technology, provisionally named AutoComp and AutoGate. AutoComp acquires sample and reagent labels from users or flow data files, and uses this information to complete the flow data compensation task. AutoGate replaces the manual subsetting capabilities provided by current analysis packages with newly defined statistical algorithms that automatically and accurately detect, display and delineate subsets in well-labeled and well-recognized formats (histograms, contour and dot plots). Users guide analyses by successively specifying axes (flow parameters) for data subset displays and selecting statistically defined subsets to be used for the next analysis round. Ultimately, this process generates analysis “trees” that can be applied to automatically guide analyses for similar samples. The first AutoComp/AutoGate version is currently in the hands of a small group of users at Stanford, Emory and NIH. When this “early adopter” phase is complete, the authors expect to distribute the software free of charge to .edu, .org and .gov users