ost in promiscuity? An evolutionary and biochemical evaluation of HSD10 function in cardiolipin metabolism.

Multifunctional proteins are challenging as it can be difficult to confirm pathomechanisms associated with disease-causing genetic variants. The human 17ß-hydroxysteroid dehydrogenase 10 (HSD10) is a moonlighting enzyme with at least two structurally and catalytically unrelated functions. HSD10 disease was originally described as a disorder of isoleucine metabolism, but the clinical manifestations were subsequently shown to be linked to impaired mtDNA transcript processing due to deficient function of HSD10 in the mtRNase P complex. A surprisingly large number of other, mostly enzymatic and potentially clinically relevant functions have been attributed to HSD10. Recently, HSD10 was reported to exhibit phospholipase C-like activity towards cardiolipins (CL), important mitochondrial phospholipids. To assess the physiological role of the proposed CL-cleaving function, we studied CL architectures in living cells and patient fibroblasts in different genetic backgrounds and lipid environments using our well-established LC-MS/MS cardiolipidomic pipeline. These experiments revealed no measurable effect on CLs, indicating that HSD10 does not have a physiologically relevant function towards CL metabolism. Evolutionary constraints could explain the broad range of reported substrates for HSD10 in vitro. The combination of an essential structural with a non-essential enzymatic function in the same protein could direct the evolutionary trajectory towards improvement of the former, thereby increasing the flexibility of the binding pocket, which is consistent with the results presented here.

ScreenLife Capture: An open-source and user-friendly framework for collecting screenomes from Android smartphones.

As our interactions with each other become increasingly digitally mediated, there is growing interest in the study of people's digital experiences. To better understand digital experiences, some researchers have proposed the use of screenomes. This involves the collection of sequential high-frequency screenshots which provide detailed objective records of individuals' interaction with screen devices over time. Despite its usefulness, there remains no readily available tool that researchers can use to run their own screenome studies. To fill this gap, we introduce ScreenLife Capture, a user-friendly and open-source software to collect screenomes from smartphones. Using this tool, researchers can set up smartphone screenome studies even with limited programming knowledge and resources. We piloted the tool in an exploratory mixed-method study of 20 college students, collecting over 740,000 screenshots over a 2-week period. We found that smartphone use is highly heterogeneous, characterized by threads of experiences. Using in-depth interviews, we also explored the impact that constant background surveillance of smartphone use had on participants. Participants generally had slight psychological discomfort which fades after a few days, would suspend screen recording for activity perceived to be extremely private, and recounted slight changes in behavior. Implications for future research is discussed.

Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups.

The general linear model (GLM) is a widely popular and convenient tool for estimating the functional brain response and identifying areas of significant activation during a task or stimulus. However, the classical GLM is based on a massive univariate approach that does not explicitly leverage the similarity of activation patterns among neighboring brain locations. As a result, it tends to produce noisy estimates and be underpowered to detect significant activations, particularly in individual subjects and small groups. A recently proposed alternative, a cortical surface-based spatial Bayesian GLM, leverages spatial dependencies among neighboring cortical vertices to produce more accurate estimates and areas of functional activation. The spatial Bayesian GLM can be applied to individual and group-level analysis. In this study, we assess the reliability and power of individual and group-average measures of task activation produced via the surface-based spatial Bayesian GLM. We analyze motor task data from 45 subjects in the Human Connectome Project (HCP) and HCP Retest datasets. We also extend the model to multi-run analysis and employ subject-specific cortical surfaces rather than surfaces inflated to a sphere for more accurate distance-based modeling. Results show that the surface-based spatial Bayesian GLM produces highly reliable activations in individual subjects and is powerful enough to detect trait-like functional topologies. Additionally, spatial Bayesian modeling enhances reliability of group-level analysis even in moderately sized samples (n=45). Notably, the power of the spatial Bayesian GLM to detect activations above a scientifically meaningful effect size is nearly invariant to sample size, exhibiting high power even in small samples (n=10). The spatial Bayesian GLM is computationally efficient in individuals and groups and is convenient to implement with the open-source BayesfMRI R package.

Resurrection of the ancestral RH5 invasion ligand provides a molecular explanation for the origin of P. falciparum malaria in humans.

Many important infectious diseases are the result of zoonoses, in which pathogens that normally infect animals acquire mutations that enable the breaching of species barriers to permit the infection of humans. Our understanding of the molecular events that enable host switching are often limited, and yet this is a fundamentally important question. Plasmodium falciparum, the etiological agent of severe human malaria, evolved following a zoonotic transfer of parasites from gorillas. One gene-rh5-which encodes an essential ligand for the invasion of host erythrocytes, is suspected to have played a critical role in this host switch. Genome comparisons revealed an introgressed sequence in the ancestor of P. falciparum containing rh5, which likely allowed the ancestral parasites to infect both gorilla and human erythrocytes. To test this hypothesis, we resurrected the ancestral introgressed reticulocyte-binding protein homologue 5 (RH5) sequence and used quantitative protein interaction assays to demonstrate that this ancestral protein could bind the basigin receptor from both humans and gorillas. We also showed that this promiscuous receptor binding phenotype of RH5 was shared with the parasite clade that transferred its genome segment to the ancestor of P. falciparum, while the other lineages exhibit host-specific receptor binding, confirming the central importance of this introgression event for Plasmodium host switching. Finally, since its transfer to humans, P. falciparum, and also the RH5 ligand, have evolved a strong human specificity. We show that this subsequent restriction to humans can be attributed to a single amino acid mutation in the RH5 sequence. Our findings reveal a molecular pathway for the origin and evolution of human P. falciparum malaria and may inform molecular surveillance to predict future zoonoses.

Bayesian inference for generalized linear mixed models with predictors subject to detection limits: an approach that leverages information from auxiliary variables.

This paper is motivated from a retrospective study of the impact of vitamin D deficiency on the clinical outcomes for critically ill patients in multi-center critical care units. The primary predictors of interest, vitamin D2 and D3 levels, are censored at a known detection limit. Within the context of generalized linear mixed models, we investigate statistical methods to handle multiple censored predictors in the presence of auxiliary variables. A Bayesian joint modeling approach is proposed to fit the complex heterogeneous multi-center data, in which the data information is fully used to estimate parameters of interest. Efficient Monte Carlo Markov chain algorithms are specifically developed depending on the nature of the response. Simulation studies demonstrate the outperformance of the proposed Bayesian approach over other existing methods. An application to the data set from the vitamin D deficiency study is presented. Possible extensions of the method regarding the absence of auxiliary variables, semiparametric models, as well as the type of censoring are also discussed.

Primary cutaneous versus salivary gland origin mucoepidermoid carcinoma.

Mucoepidermoid carcinoma (MEC) is a malignant glandular epithelial neoplasm that most commonly arises in the major salivary glands. Primary cutaneous MEC is very rare. There is a particular diagnostic challenge in determining the primary site of MEC when it is found in skin overlying the parotid gland. Attention to a combination of morphologic findings may be helpful. However, differentiation of primary cutaneous MEC from secondary cutaneous involvement by a parotid MEC may be unnecessary once the parotid gland is infiltrated. We report the case of a 54-year-old male with a 2-cm asymptomatic mass overlying the right parotid gland, which was managed by excision of the affected skin, right total parotidectomy, and right neck dissection. Histopathologic and immunohistochemical findings were consistent with a cutaneous intermediate-grade MEC. Postoperative radiotherapy was deferred. The patient showed no evidence of recurrence or metastasis at 2 months before self-discontinuing follow-up. To our knowledge, this is only the second reported case of MEC involving the parotid gland, but of overlying primary cutaneous origin.

ANOPOW FOR REPLICATED NONSTATIONARY TIME SERIES IN EXPERIMENTS.

We propose a novel analysis of power (ANOPOW) model for analyzing replicated nonstationary time series commonly encountered in experimental studies. Based on a locally stationary ANOPOW Cramér spectral representation, the proposed model can be used to compare the second-order time-varying frequency patterns among different groups of time series and to estimate group effects as functions of both time and frequency. Formulated in a Bayesian framework, independent two-dimensional second-order random walk (RW2D) priors are assumed on each of the time-varying functional effects for flexible and adaptive smoothing. A piecewise stationary approximation of the nonstationary time series is used to obtain localized estimates of time-varying spectra. Posterior distributions of the time-varying functional group effects are then obtained via integrated nested Laplace approximations (INLA) at a low computational cost. The large-sample distribution of local periodograms can be appropriately utilized to improve estimation accuracy since INLA allows modeling of data with various types of distributions. The usefulness of the proposed model is illustrated through two real data applications: analyses of seismic signals and pupil diameter time series in children with attention deficit hyperactivity disorder. Simulation studies, Supplementary Materials (Li, Yue and Bruce, 2023a), and R code (Li, Yue and Bruce, 2023b) for this article are also available.

Template independent component analysis with spatial priors for accurate subject-level brain network estimation and inference.

Independent component analysis is commonly applied to functional magnetic resonance imaging (fMRI) data to extract independent components (ICs) representing functional brain networks. While ICA produces reliable group-level estimates, single-subject ICA often produces noisy results. Template ICA is a hierarchical ICA model using empirical population priors to produce more reliable subject-level estimates. However, this and other hierarchical ICA models assume unrealistically that subject effects are spatially independent. Here, we propose spatial template ICA (stICA), which incorporates spatial priors into the template ICA framework for greater estimation efficiency. Additionally, the joint posterior distribution can be used to identify brain regions engaged in each network using an excursions set approach. By leveraging spatial dependencies and avoiding massive multiple comparisons, stICA has high power to detect true effects. We derive an efficient expectation-maximization algorithm to obtain maximum likelihood estimates of the model parameters and posterior moments of the latent fields. Based on analysis of simulated data and fMRI data from the Human Connectome Project, we find that stICA produces estimates that are more accurate and reliable than benchmark approaches, and identifies larger and more reliable areas of engagement. The algorithm is computationally tractable, achieving convergence within 12 hours for whole-cortex fMRI analysis.

Daptomycin-nonsusceptible, vancomycin-intermediate, methicillin-resistant Staphylococcus aureus endocarditis.

Due to the emergence of Staphylococcus aureus with reduced vancomycin susceptibility, newer antibiotics, including daptomycin, have been used to treat methicillin-resistant S aureus infections. Daptomycin is a cyclic lipopeptide that is approved to treat S aureus bacteremia and right-sided endocarditis, and reports of S aureus with reduced susceptibility to daptomycin are infrequent. To our knowledge, the present report describes the first Canadian case of daptomycin-nonsusceptible, vancomycin-intermediate S aureus infection.

Étant donné l'émergence d'infections à Staphylococcus aureus peu sensibles à la vancomycine, de nouveaux antibiotiques, y compris la daptomycine, sont utilisés pour traiter les infections à S aureus résistant à la méthicilline (SARM). La daptomycine est un lipopeptide cyclique approuvé pour le traitement de la bactériémie à S aureus et de l'endocardite du cœur droit, et les déclarations de S aureus peu sensibles à la daptomycine sont peu fréquentes. En autant que nous le sachions, le présent rapport est le premier cas d'infection à S aureus ayant une résistance intermédiaire à la vancomycine et sans sensibilité à la daptomycine au Canada.

Aquabots.

Soft robots, made from elastomers, easily bend and flex, but deformability constraints severely limit navigation through and within narrow, confined spaces. Using aqueous two-phase systems we print water-in-water constructs that, by aqueous phase-separation-induced self-assembly, produce ultrasoft liquid robots, termed aquabots, comprised of hierarchical structures that span in length scale from the nanoscopic to microsciopic, that are beyond the resolution limits of printing and overcome the deformability barrier. The exterior of the compartmentalized membranes is easily functionalized, for example, by binding enzymes, catalytic nanoparticles, and magnetic nanoparticles that impart sensitive magnetic responsiveness. These ultrasoft aquabots can adapt their shape for gripping and transporting objects and can be used for targeted photocatalysis, delivery, and release in confined and tortuous spaces. These biocompatible, multicompartmental, and multifunctional aquabots can be readily applied to medical micromanipulation, targeted cargo delivery, tissue engineering, and biomimetics.

Bayesian semiparametric intensity estimation for inhomogeneous spatial point processes.

In this work we propose a fully Bayesian semiparametric method to estimate the intensity of an inhomogeneous spatial point process. The basic idea is to first convert intensity estimation into a Poisson regression setting via binning data points on a regular grid, and then model the log intensity semiparametrically using an adaptive version of Gaussian Markov random fields to smooth the corresponding counts. The inference is carried by an efficient Markov chain Monte Carlo simulation algorithm. Compared to existing methods for intensity estimation, for example, parametric modeling and kernel smoothing, the proposed estimator not only provides inference regarding the dependence of the intensity function on possible covariates, but also uses information from the data to adaptively determine the amount of smoothing at the local level. The effectiveness of using our method is demonstrated through simulation studies and an application to a rainforest dataset.

Retroperitoneal liposarcoma in an adult patient with Down syndrome.

Retroperitoneal liposarcoma is a rare solid tumour of mesenchymal origin with an incidence of 2.5 per million population. We report what is, to the best of our knowledge, the first case in the English literature of retroperitoneal liposarcoma in an adult patient with Down syndrome. The tumour was surgically resected with no use of adjuvant chemotherapy or radiation. No recurrence was found at follow-up 2 months postoperatively. Clinicians should consider retroperitoneal liposarcoma in the differential diagnosis of abdominal distention in adult patients with Down syndrome.

NRAS mutant E132K identified in young-onset sporadic colorectal cancer and the canonical mutants G12D and Q61K affect distinct oncogenic phenotypes.

Recent data show a global increase in colorectal cancer (CRC) cases among younger demographics, which portends poorer prognosis. The cause of rising incidence is uncertain, and its mutational landscape remains largely unexplored, including those in genes of the epidermal growth factor receptor pathway. Among these are NRAS mutants where there is paucity of functional studies compared to KRAS. Here, the novel NRAS mutant E132K, identified in three tumor samples from Filipino young-onset, sporadic colorectal cancer patients, was investigated for its effects on different cancer hallmarks, alongside the NRAS canonical mutants G12D and Q61K which are yet poorly characterized in the context of CRC. The novel NRAS mutant E132K and the canonical G12D and Q61K mutants show resistance to apoptosis, cytoskeletal reorganization, and loss of adhesion. In contrast to activating KRAS mutations, including the analogous KRAS G12D and Q61K mutations, all three NRAS mutants have no apparent effect on cell proliferation and motility. The results highlight the need to characterize isoform- and mutation-specific oncogenic phenotypes which can have repercussions in disease management and choice of therapeutic intervention. Further analyses of young-onset versus late-onset CRC datasets are necessary to qualify NRAS E132K as a biomarker for the young-onset subtype.

A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis.

Cortical surface fMRI (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, dimension reduction, removal of extraneous tissue types, and improved alignment of cortical areas across subjects, it is also more compatible with common assumptions of Bayesian spatial models. However, as no spatial Bayesian model has been proposed for cs-fMRI data, most analyses continue to employ the classical general linear model (GLM), a "massive univariate" approach. Here, we propose a spatial Bayesian GLM for cs-fMRI, which employs a class of sophisticated spatial processes to model latent activation fields. We make several advances compared with existing spatial Bayesian models for volumetric fMRI. First, we use integrated nested Laplacian approximations (INLA), a highly accurate and efficient Bayesian computation technique, rather than variational Bayes (VB). To identify regions of activation, we utilize an excursions set method based on the joint posterior distribution of the latent fields, rather than the marginal distribution at each location. Finally, we propose the first multi-subject spatial Bayesian modeling approach, which addresses a major gap in the existing literature. The methods are very computationally advantageous and are validated through simulation studies and two task fMRI studies from the Human Connectome Project.

Induction of EGFP expression in Pichia pastoris during co-culture with human endothelial cell line.

While Pichia pastoris has been developed into a versatile recombinant protein expression system, there are only few studies that have investigated the efficacious use of this yeast with human cells. In this study, we demonstrated that P. pastoris can be cultured under mammalian cell culture conditions and co-cultured with human endothelial cells. Co-cultures did not affect endothelial cell morphology or viability. Additionally, P. pastoris was induced to express enhanced green fluorescence protein when co-cultured with human endothelial cell line EA.hy926 under mammalian cell culture conditions. Our study provides data to support the use of P. pastoris as a vehicle for direct delivery of recombinant proteins to mammalian cells during co-culture.

Phenotypic characterization of the novel, non-hotspot oncogenic KRAS mutants E31D and E63K.

KRAS proto-oncogene, GTPase (KRAS) functions as a molecular switch at the apex of multiple signaling pathways controlling cell proliferation, differentiation, migration, and survival. Canonical KRAS mutants, such as those in codons 12 and 13, produce constitutively active oncoproteins that short-circuit epidermal growth factor receptor (EGFR)-initiated signaling, resulting in dysregulated downstream effectors associated with cellular transformation. Therefore, anti-EGFR therapy provides little to no clinical benefit to patients with activating KRAS mutations. Current genotyping procedures based on canonical mutation detection only account for ~40% of non-responders, highlighting the need to identify additional predictive biomarkers. In the present study, two novel non-hotspot KRAS mutations were functionally characterized in vitro: KRAS E31D was identified from a genetic screen of colorectal cancer specimens at the UP-National Institutes of Health. KRAS E63K is curated in the Catalogue of Somatic Mutations in Cancer database. Similar to the canonical mutants KRAS G12D and KRAS G13D, NIH3T3 cells overexpressing KRAS E31D and KRAS E63K showed altered morphology and were characteristically smaller, rounder, and highly refractile compared with their non-transformed counterparts. Filamentous actin staining also indicated cytoplasmic shrinkage, membrane ruffling, and formation of pseudopod protrusions. Further, they displayed higher proliferative rates and higher migratory rates in scratch wound assays compared with negative controls. These empirical findings suggest the activating impact of the novel KRAS mutations, which may contribute to resistance to anti-EGFR therapy. Complementary studies to elucidate the molecular mechanisms underlying the transforming effect of the rare mutants are required. In parallel, their oncogenic capacity in vivo should also be investigated.