Age-Related Gene Expression Differences in Monocytes from Human Neonates, Young Adults, and Older Adults.

A variety of age-related differences in the innate and adaptive immune systems have been proposed to contribute to the increased susceptibility to infection of human neonates and older adults. The emergence of RNA sequencing (RNA-seq) provides an opportunity to obtain an unbiased, comprehensive, and quantitative view of gene expression differences in defined cell types from different age groups. An examination of ex vivo human monocyte responses to lipopolysaccharide stimulation or Listeria monocytogenes infection by RNA-seq revealed extensive similarities between neonates, young adults, and older adults, with an unexpectedly small number of genes exhibiting statistically significant age-dependent differences. By examining the differentially induced genes in the context of transcription factor binding motifs and RNA-seq data sets from mutant mouse strains, a previously described deficiency in interferon response factor-3 activity could be implicated in most of the differences between newborns and young adults. Contrary to these observations, older adults exhibited elevated expression of inflammatory genes at baseline, yet the responses following stimulation correlated more closely with those observed in younger adults. Notably, major differences in the expression of constitutively expressed genes were not observed, suggesting that the age-related differences are driven by environmental influences rather than cell-autonomous differences in monocyte development

Maxillofacial prosthodontics practice profile:A survey of non-United States prosthodontists

Abstract Background This study surveyed non-United States maxillofacial prosthodontists (MFP) to determine their practice profile and rationale for pursuing an MFP career. Methods Email addresses for the MFP were obtained from the International Society for Maxillofacial Rehabilitation, American Academy of Maxillofacial Prosthetics, and International Academy for Oral Facial Rehabilitation. Emails with a link to the electronic survey program were sent to each participant. Chi-square and Mann–Whitney-U tests were used to investigate the influence of formal MFP training on professional activities and type of treatments provided. Results One hundred twelve respondents (response rate 39%) from 33 nationalities returned the survey. The top three reasons for pursuing an MFP career were personal satisfaction, prosthodontics residency exposure, and mentorship. The predominant employment setting was affiliation with a university (77%). There were significant differences between respondents with and without formal MFP training regarding provision of surgical treatments (P = 0.021) and dental oncology (P = 0.017). Most treatments were done together with otolaryngology, oral surgery (68%) and head and neck surgery (61%). Practitioners not affiliated with a university spent significantly more time in clinical practice (P = 0.002), whereas respondents affiliated with universities spent significantly more time in teaching/training (P = 0.008) and funded research (P = 0.015). Conclusions Personal satisfaction is the most important factor in a decision to choose an MFP career. Most of the MFPs work at a university and within a multidisciplinary setting. There were differences regarding type of treatments provided by respondents with and without formal MFP training

Assessment of Hypertension Using Clinical Electrocardiogram Features: A First-Ever Review

Hypertension affects an estimated 1.4 billion people and is a major cause of morbidity and mortality worldwide. Early diagnosis and intervention can potentially decrease cardiovascular events later in life. However, blood pressure (BP) measurements take time and require training for health care professionals. The measurements are also inconvenient for patients to access, numerous daily variables affect BP values, and only a few BP readings can be collected per session. This leads to an unmet need for an accurate, 24-h continuous, and portable BP measurement system. Electrocardiograms (ECGs) have been considered as an alternative way to measure BP and may meet this need. This review summarizes the literature published from January 1, 2010, to January 1, 2020, on the use of only ECG wave morphology to monitor BP or identify hypertension. From 35 articles analyzed (9 of those with no listed comorbidities and confounders), the P wave, QTc intervals and TpTe intervals may be promising for this purpose. Unfortunately, with the limited number of articles and the variety of participant populations, we are unable to make conclusions about the effectiveness of ECG-only BP monitoring. We provide 13 recommendations for future ECG-only BP monitoring studies and highlight the limited findings in pregnant and pediatric populations. With the advent of convenient and portable ECG signal recording in smart devices and wearables such as watches, understanding how to apply ECG-only findings to identify hypertension early is crucial to improving health outcomes worldwide

Cervical ripening at home or in-hospital-prospective cohort study and process evaluation (CHOICE) study: a protocol.

IntroductionThe aim of the cervical ripening at home or in-hospital-prospective cohort study and process evaluation (CHOICE) study is to compare home versus in-hospital cervical ripening to determine whether home cervical ripening is safe (for the primary outcome of neonatal unit (NNU) admission), acceptable to women and cost-effective from the perspective of both women and the National Health Service (NHS).Methods and analysisWe will perform a prospective multicentre observational cohort study with an internal pilot phase. We will obtain data from electronic health records from at least 14 maternity units offering only in-hospital cervical ripening and 12 offering dinoprostone home cervical ripening. We will also conduct a cost-effectiveness analysis and a mixed methods study to evaluate processes and women/partner experiences. Our primary sample size is 8533 women with singleton pregnancies undergoing induction of labour (IOL) at 39+0 weeks' gestation or more. To achieve this and contextualise our findings, we will collect data relating to a cohort of approximately 41 000 women undergoing IOL after 37 weeks. We will use mixed effects logistic regression for the non-inferiority comparison of NNU admission and propensity score matched adjustment to control for treatment indication bias. The economic analysis will be undertaken from the perspective of the NHS and Personal Social Services (PSS) and the pregnant woman. It will include a within-study cost-effectiveness analysis and a lifetime cost-utility analysis to account for any long-term impacts of the cervical ripening strategies. Outcomes will be reported as incremental cost per NNU admission avoided and incremental cost per quality adjusted life year gained.Research ethics approval and disseminationCHOICE has been funded and approved by the National Institute of Healthcare Research Health Technology and Assessment, and the results will be disseminated via publication in peer-reviewed journals.Trial registration numberISRCTN32652461

Identification of MCI individuals using structural and functional connectivity networks

Different imaging modalities provide essential complementary information that can be used to enhance our understanding of brain disorders. This study focuses on integrating multiple imaging modalities to identify individuals at risk for mild cognitive impairment (MCI). MCI, often an early stage of Alzheimer’s disease (AD), is difficult to diagnose due to its very mild or insignificant symptoms of cognitive impairment. Recent emergence of brain network analysis has made characterization of neurological disorders at a whole-brain connectivity level possible, thus providing new avenues for brain diseases classification. Employing multiple-kernel Support Vector Machines (SVMs), we attempt to integrate information from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) for improving classification performance. Our results indicate that the multimodality classification approach yields statistically significant improvement in accuracy over using each modality independently. The classification accuracy obtained by the proposed method is 96.3%, which is an increase of at least 7.4% from the single modality-based methods and the direct data fusion method. A cross-validation estimation of the generalization performance gives an area of 0.953 under the receiver operating characteristic (ROC) curve, indicating excellent diagnostic power. The multimodality classification approach hence allows more accurate early detection of brain abnormalities with greater sensitivity

Enriched white matter connectivity networks for accurate identification of MCI patients

Mild cognitive impairment (MCI), often a prodromal phase of Alzheimer’s disease (AD), is frequently considered to be good target for early diagnosis and therapeutic interventions of AD. Recent emergence of reliable network characterization techniques has made it possible to understand neurological disorders at a whole-brain connectivity level. Accordingly, we propose an effective network-based multivariate classification algorithm, using a collection of measures derived from white-matter (WM) connectivity networks, to accurately identify MCI patients from normal controls. An enriched description of WM connections, utilizing six physiological parameters, i.e., fiber count, fractional anisotropy (FA), mean diffusivity (MD), and principal diffusivities (λ1, λ2, λ3), results in six connectivity networks for each subject to account for the connection topology and the biophysical properties of the connections. Upon parcellating the brain into 90 regions-of-interest (ROIs), these properties can be quantified for each pair of regions with common traversing fibers. For building an MCI classifier, clustering coefficient of each ROI in relation to the remaining ROIs is extracted as feature for classification. These features are then ranked according to their Pearson correlation with respect to the clinical labels, and are further sieved to select the most discriminant subset of features using a SVM-based feature selection algorithm. Finally, support vector machines (SVMs) are trained using the selected subset of features. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy given by our enriched description of WM connections is 88.9%, which is an increase of at least 14.8% from that using simple WM connectivity description with any single physiological parameter. A cross-validation estimation of the generalization performance shows an area of 0.929 under the receiver operating characteristic (ROC) curve, indicating excellent diagnostic power. It was also found, based on the selected features, that portions of the prefrontal cortex, orbitofrontal cortex, parietal lobe and insula regions provided the most discriminant features for classification, in line with results reported in previous studies. Our MCI classification framework, especially the enriched description of WM connections, allows accurate early detection of brain abnormalities, which is of paramount importance for treatment management of potential AD patients

Synergistic use of glycomics and single-molecule molecular inversion probes for identification of congenital disorders of glycosylation type-1

Congenital disorders of glycosylation type 1 (CDG-I) comprise a group of 27 genetic defects with heterogeneous multisystem phenotype, mostly presenting with nonspecific neurological symptoms. The biochemical hallmark of CDG-I is a partial absence of complete N-glycans on transferrin. However, recent findings of a diagnostic N-tetrasaccharide for ALG1-CDG and increased high-mannose N-glycans for a few other CDG suggested the potential of glycan structural analysis for CDG-I gene discovery. We analyzed the relative abundance of total plasma N-glycans by high resolution quadrupole time-of-flight mass spectrometry in a large cohort of 111 CDG-I patients with known (n = 75) or unsolved (n = 36) genetic cause. We designed single-molecule molecular inversion probes (smMIPs) for sequencing of CDG-I candidate genes on the basis of specific N-glycan signatures. Glycomics profiling in patients with known defects revealed novel features such as the N-tetrasaccharide in ALG2-CDG patients and a novel fucosylated N-pentasaccharide as specific glycomarker for ALG1-CDG. Moreover, group-specific high-mannose N-glycan signatures were found in ALG3-, ALG9-, ALG11-, ALG12-, RFT1-, SRD5A3-, DOLK-, DPM1-, DPM3-, MPDU1-, ALG13-CDG, and hereditary fructose intolerance. Further differential analysis revealed high-mannose profiles, characteristic for ALG12- and ALG9-CDG. Prediction of candidate genes by glycomics profiling in 36 patients with thus far unsolved CDG-I and subsequent smMIPs sequencing led to a yield of solved cases of 78% (28/36). Combined plasma glycomics profiling and targeted smMIPs sequencing of candidate genes is a powerful approach to identify causative mutations in CDG-I patient cohorts

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered ( Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients

Niacin-mediated rejuvenation of macrophage/microglia enhances remyelination of the aging central nervous system

Abstract: Remyelination following CNS demyelination restores rapid signal propagation and protects axons; however, its efficiency declines with increasing age. Both intrinsic changes in the oligodendrocyte progenitor cell population and extrinsic factors in the lesion microenvironment of older subjects contribute to this decline. Microglia and monocyte-derived macrophages are critical for successful remyelination, releasing growth factors and clearing inhibitory myelin debris. Several studies have implicated delayed recruitment of macrophages/microglia into lesions as a key contributor to the decline in remyelination observed in older subjects. Here we show that the decreased expression of the scavenger receptor CD36 of aging mouse microglia and human microglia in culture underlies their reduced phagocytic activity. Overexpression of CD36 in cultured microglia rescues the deficit in phagocytosis of myelin debris. By screening for clinically approved agents that stimulate macrophages/microglia, we have found that niacin (vitamin B3) upregulates CD36 expression and enhances myelin phagocytosis by microglia in culture. This increase in myelin phagocytosis is mediated through the niacin receptor (hydroxycarboxylic acid receptor 2). Genetic fate mapping and multiphoton live imaging show that systemic treatment of 9–12-month-old demyelinated mice with therapeutically relevant doses of niacin promotes myelin debris clearance in lesions by both peripherally derived macrophages and microglia. This is accompanied by enhancement of oligodendrocyte progenitor cell numbers and by improved remyelination in the treated mice. Niacin represents a safe and translationally amenable regenerative therapy for chronic demyelinating diseases such as multiple sclerosis

Correction to: Niacin-mediated rejuvenation of macrophage/microglia enhances remyelination of the aging central nervous system.

The article Niacin‑mediated rejuvenation of macrophage/microglia enhances remyelination of the aging central nervous system, written by Khalil S. Rawji, Adam M.H. Young, Tanay Ghosh, Nathan J. Michaels, Reza Mirzaei, Janson Kappen, Kathleen L. Kolehmainen, Nima Alaeiilkhchi, Brian Lozinski, Manoj K. Mishra, Annie Pu, Weiwen Tang, Salma Zein, Deepak K. Kaushik, Michael B. Keough, Jason R. Plemel, Fiona Calvert, Andrew J. Knights, Daniel J. Gaffney, Wolfram Tetzlaff, Robin J. M. Franklin and V. Wee Yong, was originally published electronically on the publisher's internet