Biology subjects

Murphy, B.

Publications and source records attributed to Murphy, B..

27 records · Page 2Linked to original sources

bioRxiv2021

Deep learning identifies pathological abnormalities predictive of graft loss in kidney transplant biopsies

BackgroundInterstitial fibrosis, tubular atrophy, and inflammation are major contributors to renal allograft failure. Here we seek an objective, quantitative pathological assessment of these lesions to improve predictive utility. MethodsWe constructed a deep-learning-based pipeline recognizing normal vs. abnormal kidney tissue compartments and mononuclear leukocyte (MNL) infiltrates from Periodic acid-Schiff (PAS) stained slides of transplant biopsies (training: n=60, testing: n=33) that quantified pathological lesions specific for interstitium, tubules and MNL infiltration. The pipeline was applied to 789 whole slide images (WSI) from baseline (n=478, pre-implantation) and 12-month post-transplant (n=311) protocol biopsies in two independent cohorts (GoCAR: 404 patients, AUSCAD: 212 patients) of transplant recipients to correlate composite lesion features with graft loss. ResultsOur model accurately recognized kidney tissue compartments and MNLs. The digital features significantly correlated with Banff scores, but were more sensitive to subtle pathological changes below the thresholds in Banff scores. The Interstitial and Tubular Abnormality Score (ITAS) in baseline samples was highly predictive of 1-year graft loss (p=2.8e-05), while a Composite Damage Score (CDS) in 12-month post-transplant protocol biopsies predicted later graft loss (p=7.3e-05). ITAS and CDS outperformed Banff scores or clinical predictors with superior graft loss prediction accuracy. High/intermediate risk groups stratified by ITAS or CDS also demonstrated significantly higher incidence of eGFR decline and subsequent graft damage. ConclusionsThis deep-learning approach accurately detected and quantified pathological lesions from baseline or post-transplant biopsies, and demonstrated superior ability for prediction of posttransplant graft loss with potential application as a prevention, risk stratification or monitoring tool.

pathology↗

bioRxiv2020

Collagen fibre-mediated mechanical damage increases calcification of bovine pericardium for use in bioprosthetic heart valves

In cases of aortic stenosis, bioprosthetic heart valves (BHVs), with leaflets made from glutaraldehyde fixed bovine pericardium (GLBP), are often implanted to replace the native diseased valve. Widespread use of these devices, however, is restricted due to inadequate long-term durability owing specifically to premature leaflet failure. Mechanical fatigue damage and calcification remain the primary leaflet failure modes, where glutaraldehyde treatment is known to accelerate calcification. The literature in this area is limited, with some studies suggesting mechanical damage increases calcification and others that they are independent degenerative mechanisms. In this study, specimens which were non-destructively pre-sorted according to collagen fibre architecture and then uniaxially cyclically loaded until failure or 1 million cycles, were placed in an in-vitro calcification solution. Measurements of percentage volume calcification demonstrated that the weakest specimen group (those with fibres aligned perpendicular to the load) had statistically significantly higher volumes of calcification when compared to those with a high fatigue life. Moreover, SEM imaging revealed that ruptured and damaged fibres presented binding sites for calcium to attach; resulting in more than 4 times the volume of calcification in fractured samples when compared to those which did not fail by fatigue. To the authors knowledge, this study quantifies for the first time, that mechanical damage drives calcification in commercial-grade GLBP and that this calcification varies spatially according to localised levels of damage. These findings illustrate that not only is calcification potential in GLBP exacerbated by fatigue damage, but that both failure phenomena are underpinned by the unloaded collagen fibre organisation. Consequently, controlling for GLBP collagen fibre architecture in leaflets could minimise the progression of these prevalent primary failure modes in patient BHVs.

bioengineering↗

bioRxiv2020

Explainable AI reveals key changes in skin microbiome associated with menopause, smoking, aging and skin hydration

Alterations in the human microbiome have been observed in a variety of conditions such has asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial intelligence with rich microbiome datasets can offer an improved understanding of the microbiomes role in our health. To gain actionable insights it is essential to consider both the predictive power and the transparency of the models by providing explanations for the predictions. We combine the effort of collecting a corpus of leg skin microbiome samples of two healthy cohorts of women with the development of an explainable artificial intelligence (EAI) approach that provides accurate predictions of phenotypes and explanations. The explanations are expressed in terms of variations in the abundance of key microbes that drive the predictions. We predict skin hydration, subjects age, pre/post-menopausal status and smoking status from the leg skin microbiome. The key changes in microbial composition linked to skin hydration can accelerate the development of personalised treatments for healthy skin, while those associated with age may offer insights into the skin aging process. The leg microbiome signatures associated with smoking and menopausal status are consistent with previous findings from oral/respiratory tract microbiomes and vaginal microbiomes respectively. This suggests that easily accessible microbiome samples could be used to investigate health-related phenotypes, offering potential for non-invasive diagnosis and condition monitoring. Our EAI approach sets the stage for new work focused on understanding the complex relationships between microbial communities and phenotypes. Our approach can be applied to predict any conditions from microbiome samples and has the potential to accelerate the development of microbiome-based personalised therapeutics and non-invasive diagnostics.

bioinformatics↗

bioRxiv2020

Enhanced specificity of high sensitivity somatic variant profiling in cell-free DNA via paired normal sequencing: design, validation, and clinical experience of the MSK-ACCESS liquid biopsy assay

Circulating cell-free DNA (cfDNA) from blood plasma of cancer patients can be used to interrogate somatic tumor alterations non-invasively or when adequate tissue is unavailable. We have developed and clinically implemented MSK-ACCESS (Analysis of Circulating cfDNA to Evaluate Somatic Status), an NGS assay for detection of very low frequency somatic alterations in select exons and introns of 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 98% for a priori mutation profiling. To evaluate the performance and utility of MSK-ACCESS, we report results from the first 681 prospective blood samples (617 patients) that underwent clinical analysis to guide patient management. Somatic mutations, copy number, and/or structural variants were detected in 73% of the samples, and 56% of these circulating-tumor DNA (ctDNA) positive samples had clinically actionable alterations. The utilization of matched white blood cell sequencing allowed retention of somatic alterations while filtering out over 10,000 germline and clonal hematopoiesis variants, thereby greatly enhancing the specificity of the assay. Taken together, our experience illustrates the importance of analyzing a matched normal sample when interpreting cfDNA results and highlights the potential of cfDNA profiling to guide treatment selection, monitor treatment response, and identify mechanisms of treatment resistance.

genomics↗

bioRxiv2020

The neural representation of force across grasp types in motor cortex of humans with tetraplegia

Intracortical brain-computer interfaces (iBCIs) have the potential to restore hand grasping and object interaction to individuals with tetraplegia. Optimal grasping and object interaction require simultaneous production of both force and grasp outputs. However, since overlapping neural populations are modulated by both parameters, grasp type could affect how well forces are decoded from motor cortex in a closed-loop force iBCI. Therefore, this work quantified the neural representation and offline decoding performance of discrete hand grasps and force levels in two participants with tetraplegia. Participants attempted to produce three discrete forces (light, medium, hard) using up to five hand grasp configurations. A two-way Welch ANOVA was implemented on multiunit neural features to assess their modulation to force and grasp. Demixed principal component analysis was used to assess for population-level tuning to force and grasp and to predict these parameters from neural activity. Three major findings emerged from this work: 1) Force information was neurally represented and could be decoded across multiple hand grasps (and, in one participant, across attempted elbow extension as well); 2) Grasp type affected force representation within multi-unit neural features and offline force classification accuracy; and 3) Grasp was classified more accurately and had greater population-level representation than force. These findings suggest that force and grasp have both independent and interacting representations within cortex, and that incorporating force control into real-time iBCI systems is feasible across multiple hand grasps if the decoder also accounts for grasp type. Significance StatementIntracortical brain-computer interfaces (iBCIs) have emerged as a promising technology to potentially restore hand grasping and object interaction in people with tetraplegia. This study is among the first to quantify the degree to which hand grasp affects force-related - or kinetic - neural activity and decoding performance in individuals with tetraplegia. The study results enhance our overall understanding of how the brain encodes kinetic parameters across varying kinematic behaviors -- and in particular, the degree to which these parameters have independent versus interacting neural representations. Such investigations are a critical first step to incorporating force control into human-operated iBCI systems, which would move the technology towards restoring more functional and naturalistic tasks.

neuroscience↗

bioRxiv2019

A classification of functional pitcher types in Nepenthes (Nepenthaceae).

We classify Nepenthes species into 12 functional pitcher types, based on combinations of traits that appear to comprise different syndromes for capturing nutrients, usually from animals. For nine of these types the trapping syndromes are already documented, six targeting live animals (hence carnivorous), and three targeting other nutrient sources (non-carnivorous). Yet, for three pitcher types here is no previous documentation of the syndrome and we do not yet know what sources of nutrients are being targeted. Mapping all these pitcher types on the latest, near comprehensive species-level phylogenomic tree of Nepenthes (Murphy et al. 2019) shows that apart from the ancestral pitcher type 1, most of the remaining pitcher types have evolved independently, in different parts of the phylogenetic tree, usually in several different places. Each of the 12 pitcher types is characterised morphologically and illustrated, its trapping syndrome discussed, and example species are given. An identification key to the 12 pitcher types is presented. The possibility of additional pitcher types being present is discussed. O_FIG O_LINKSMALLFIG WIDTH=96 HEIGHT=200 SRC="FIGDIR/small/852137v1_fig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@bbfa57org.highwire.dtl.DTLVardef@13084e7org.highwire.dtl.DTLVardef@658770org.highwire.dtl.DTLVardef@19eca44_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOType 1 (Fig. 1).C_FLOATNO Ancestral (N. mirabilis) These species have upper pitchers which are more-or-less ovoid-cylindric in shape. The basal, ovoid part, often but not always a little wider than the upper part, is usually separated from the upper, usually cylindrical part by a "hip" or raised ridge that girdles the circumference of the pitcher on the exterior (also present in the six species of pitcher types 7, 8 and 10). Examination of the inner surface shows that the "hip" divides the glossy, broad, basal, fluid-containing, digestive, part (referred to as the "detentive" zone by Macfarlane (1908) because prey are detained here) from the upper opaque, dull, off-white to slightly purple, waxy or "pruinose" zone. This waxy zone is referred to as the "conductive" zone by Macfarlane because it helps conducts the insects downwards to the detentive zone with the digestive fluid. Such type 1 pitchers are shown in Fig. 1, exemplified by the upper pitchers of Nepenthes mirabilis (Lour.) Druce. The waxy zone is so-called because its surface is made up of numerous minute platelets of wax, each platelet like a roof-tile and held on a fragile stalk from the underlying surface. Juniper et al. (1989) documented how the waxy zone functions to prevent animals, usually insects, from leaving the pitchers once they have fallen in. Pressure from a foot placed on a wax "tile" will result in the stalk breaking, so that the insect loses its foothold and may fall back into the pitcher. C_FIG O_FIG O_LINKSMALLFIG WIDTH=111 HEIGHT=200 SRC="FIGDIR/small/852137v1_fig12.gif" ALT="Figure 12"> View larger version (39K): org.highwire.dtl.DTLVardef@1f13b4borg.highwire.dtl.DTLVardef@6bc534org.highwire.dtl.DTLVardef@1600959org.highwire.dtl.DTLVardef@5ee42_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOPitcher type 12. (Fig. 12).C_FLOATNO Flat lip (N. jacquelineae Nepenthes jacquelineae (Sumatra, Sect. Montanae) and N. platychila Ch.C.Lee (Borneo, Sect C.Clarke et al.).. Regiae, Lee 2002) both have all the features of type 3 pitchers: widely funnel-shaped to cup-shaped, non-waxy upper parts of pitchers draining into a more slender cylindrical lower part with viscous liquid. Both species however differ from all type 3 species in their very large, flat, dark red peristomes which can be up to 3.5 cm wide in N. jacquelineae. These peristomes have been speculated to act as a landing platform for large flying insects such as blattid cockroaches and moths, which might act with the contrasting lighter, green pitcher body as a light trap for such prey. It is also possible that such prey are lured into a precarious place above the mouth by the copious nectar produced from the lower surface of the lid from large nectar glands 1.5 mm diam. (Clarke 2001). The morphological convergence between the pitchers of these two species is remarkable. Further investigation of the prey trapped in the wild would be desirable for both species. Nepenthes echinostoma Hook.f. is a species closely related to N. mirabilis but with a remarkably flat and extended peristome which resembles type 3, although it has a different pitcher shape and inner surface C_FIG

plant biology↗

bioRxiv2019

A phylogenomic analysis of Nepenthes (Nepenthaceae)

Nepenthaceae is one of the largest carnivorous plant families and features ecological and morphological adaptations indicating an impressive adaptive radiation. However, investigation of evolutionary and taxonomic questions is hindered by poor phylogenetic understanding, with previous molecular studies based on limited loci and taxa. We use high-throughput sequencing with a target-capture methodology based on a 353-loci, probe set to recover sequences for 197 samples, representing 151 described or putative Nepenthes species. Phylogenetic analyses were performed using supermatrix and maximum quartet species tree approaches. Our analyses confirm five Western outlier taxa, followed by N. danseri, as successively sister to the remainder of the group. We also find mostly consistent recovery of two major Southeast Asian clades. The first contains common or widespread lowland species plus a Wallacean-New Guinean clade. Within the second clade, sects. Insignes and Tentaculatae are well supported, while geographically defined clades representing Sumatra, Indochina, Peninsular Malaysia, Palawan, Mindanao and Borneo are also consistently recovered. However, we find considerable conflicting signal at the site and locus level, and often unstable backbone relationships. A handful of Bornean taxa are inconsistently placed and require further investigation. We make further suggestions for a modified infra-generic classification of genus Nepenthes.

evolutionary biology↗

bioRxiv2019

Prediction of rapid kidney function decline using machine learning combining blood biomarkers and electronic health record data

IntroductionIndividuals with type 2 diabetes (T2DM) or the APOL1 high-risk genotype (APOL1) are at increased risk of rapid kidney function decline (RKFD) as compared to the general population. Plasma biomarkers representing inflammatory and kidney injury pathways have been validated as predictive of kidney disease progression in several studies. In addition, routine clinical data in the electronic health record (EHR) may also be utilized for predictive purposes. The application of machine learning to integrate biomarkers with clinical data may lead to improved identification of RKFD.\n\nMethodsWe selected two subpopulations of high-risk individuals: T2DM (n=871) and APOL1 high risk genotype of African Ancestry (n=498), with a baseline eGFR [≥] 45 ml/min/1.73 m2 from the Mount Sinai BioMe Biobank. Plasma levels of tumor necrosis factor 1/2 (TNFR1/2), and kidney injury molecule-1 (KIM-1) were measured and a series of supervised machine learning approaches including random forest (RF) were employed to combine the biomarker data with longitudinal clinical variables. The primary objective was to accurately predict RKFD (eGFR decline of [≥] 5 ml/min/1.73 m2/year) based on an algorithm-produced score and probability cutoffs, with results compared to standard of care.\n\nResultsIn 871 participants with T2DM, the mean age was 61 years, baseline estimated glomerular filtration rate (eGFR) was 74 ml/min/1.73 m2, and median UACR was 13 mg/g. The median follow-up was 4.7 years from the baseline specimen collection with additional retrospective data available for a median of 2.3 years prior to plasma collection. In the 498 African Ancestry patients with high-risk APOL1 genotype, the median age was 56 years, median baseline eGFR was 83 ml/min/1.73 m2,and median UACR was 11 mg/g. The median follow-up was 4.7 years and there was additional retrospective data available for 3.1 years prior to plasma collection. Overall, 19% with T2DM, and 9% of the APOL1 high-risk genotype experienced RKFD. After evaluation of three supervised algorithms: random forest (RF), support vector machine (SVM), and Cox survival, the RF model was selected. In the training and test sets respectively, the RF model had an AUC of 0.82 (95% CI, 0.81-0.83) and 0.80 (95% CI, 0.78-0.82) in T2DM, and an AUC of 0.85 (95% CI, 0.84-0.87) and 0.80 (95% CI, 0.73-0.86) for the APOL1 high-risk group. The combined RF model outperformed standard clinical variables in both patient populations. Discrimination was comparable in two sensitivity analyses: 1) Using only data from [≤] 1 year prior to baseline biomarker measurement and 2) In individuals with eGFR [≤]60 and/or albuminuria at baseline. The distribution of RFKD probability varied in the two populations. In patients with T2DM, the RKFD score stratified 18%, 49%, and 33% of patients to high-, intermediate-, and low-probability strata, respectively, with a PPV of 53% in the high-probability group and an NPV of 97% in the low-probability group. By comparison, in the APOL1 high-risk genotype, the RKFD score stratified 7%, 23%, and 70% of patients to high-, intermediate-, and low-probability strata, respectively, with a 46% PPV in the high-probability and an NPV of 98% NPV in the low-probability group.\n\nConclusionsIn patients with T2DM or of African Ancestry with the high-risk APOL1 genotype, a RF model derived from plasma biomarkers and longitudinal EHR data significantly improved prediction of rapid kidney function decline over standard clinical models. With further validation, this approach may be valuable in aiding clinicians in identifying patients who would benefit most from early and more aggressive follow-up to mitigate kidney disease progression.

epidemiology↗

bioRxiv2019

Towards a real-world brain-computer interface for image retrieval

Brain decoding -- the process of inferring a persons momentary cognitive state from their brain activity -- has enormous potential in the field of human-computer interaction. In this study we propose a zero-shot EEG-to-image brain decoding approach which makes use of state-of-the-art EEG preprocessing and feature selection methods, and which maps EEG activity to biologically inspired computer vision and linguistic models. We apply this approach to solve the problem of identifying viewed images from recorded brain activity in a reliable and scalable way. We demonstrate competitive decoding accuracies across two EEG datasets, using a zero-shot learning framework more applicable to real-world image retrieval than traditional classification techniques.

neuroscience↗