Multi-image-feature-based hierarchical concrete crack identification framework using optimized svm multi-classifiers and d–s fusion algorithm for bridge structures

Cracks in concrete can cause the degradation of stiffness, bearing capacity and durability of civil infrastructure. Hence, crack diagnosis is of great importance in concrete research. On the basis of multiple image features, this work presents a novel approach for crack identification of concrete structures. Firstly, the non-local means method is adopted to process the original image, which can effectively diminish the noise influence. Then, to extract the effective features sensitive to the crack, different filters are employed for crack edge detection, which are subsequently tackled by integral projection and principal component analysis (PCA) for optimal feature selection. Moreover, support vector machine (SVM) is used to design the classifiers for initial diagnosis of concrete surface based on extracted features. To raise the classification accuracy, enhanced salp swarm algorithm (ESSA) is applied to the SVM for meta-parameter optimization. The Dempster–Shafer (D–S) fusion algorithm is utilized to fuse the diagnostic results corresponding to different filters for decision making. Finally, to demonstrate the effectiveness of the proposed framework, a total of 1200 images are collected from a real concrete bridge including intact (without crack), longitudinal crack, transverse crack and oblique crack cases. The results validate the performance of proposed method with promising results of diagnosis accuracy as high as 96.25%

Autophagy fights disease through cellular self-digestion

Autophagy, or cellular self-digestion, is a cellular pathway involved in protein and organelle degradation, with an astonishing number of connections to human disease and physiology. For example, autophagic dysfunction is associated with cancer, neurodegeneration, microbial infection and ageing. Paradoxically, although autophagy is primarily a protective process for the cell, it can also play a role in cell death. Understanding autophagy may ultimately allow scientists and clinicians to harness this process for the purpose of improving human health.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62766/1/nature06639.pd

Loss of UGP2 in brain leads to a severe epileptic encephalopathy, emphasizing that bi-allelic isoform-specific start-loss mutations of essential genes can cause genetic diseases.

Developmental and/or epileptic encephalopathies (DEEs) are a group of devastating genetic disorders, resulting in early-onset, therapy-resistant seizures and developmental delay. Here we report on 22 individuals from 15 families presenting with a severe form of intractable epilepsy, severe developmental delay, progressive microcephaly, visual disturbance and similar minor dysmorphisms. Whole exome sequencing identified a recurrent, homozygous variant (chr2:64083454A > G) in the essential UDP-glucose pyrophosphorylase (UGP2) gene in all probands. This rare variant results in a tolerable Met12Val missense change of the longer UGP2 protein isoform but causes a disruption of the start codon of the shorter isoform, which is predominant in brain. We show that the absence of the shorter isoform leads to a reduction of functional UGP2 enzyme in neural stem cells, leading to altered glycogen metabolism, upregulated unfolded protein response and premature neuronal differentiation, as modeled during pluripotent stem cell differentiation in vitro. In contrast, the complete lack of all UGP2 isoforms leads to differentiation defects in multiple lineages in human cells. Reduced expression of Ugp2a/Ugp2b in vivo in zebrafish mimics visual disturbance and mutant animals show a behavioral phenotype. Our study identifies a recurrent start codon mutation in UGP2 as a cause of a novel autosomal recessive DEE syndrome. Importantly, it also shows that isoform-specific start-loss mutations causing expression loss of a tissue-relevant isoform of an essential protein can cause a genetic disease, even when an organism-wide protein absence is incompatible with life. We provide additional examples where a similar disease mechanism applies

Informatics Technology Mimics Ecology: Dense, Mutualistic Collaboration Networks Are Associated with Higher Publication Rates

Information technology (IT) adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT) from the literature

AMFR dysfunction causes autosomal recessive spastic paraplegia in human that is amenable to statin treatment in a preclinical model

Hereditary spastic paraplegias (HSP) are rare, inherited neurodegenerative or neurodevelopmental disorders that mainly present with lower limb spasticity and muscle weakness due to motor neuron dysfunction. Whole genome sequencing identified bi-allelic truncating variants in AMFR, encoding a RING-H2 finger E3 ubiquitin ligase anchored at the membrane of the endoplasmic reticulum (ER), in two previously genetically unexplained HSP-affected siblings. Subsequently, international collaboration recognized additional HSP-affected individuals with similar bi-allelic truncating AMFR variants, resulting in a cohort of 20 individuals from 8 unrelated, consanguineous families. Variants segregated with a phenotype of mainly pure but also complex HSP consisting of global developmental delay, mild intellectual disability, motor dysfunction, and progressive spasticity. Patient-derived fibroblasts, neural stem cells (NSCs), and in vivo zebrafish modeling were used to investigate pathomechanisms, including initial preclinical therapy assessment. The absence of AMFR disturbs lipid homeostasis, causing lipid droplet accumulation in NSCs and patient-derived fibroblasts which is rescued upon AMFR re-expression. Electron microscopy indicates ER morphology alterations in the absence of AMFR. Similar findings are seen in amfra-/- zebrafish larvae, in addition to altered touch-evoked escape response and defects in motor neuron branching, phenocopying the HSP observed in patients. Interestingly, administration of FDA-approved statins improves touch-evoked escape response and motor neuron branching defects in amfra-/- zebrafish larvae, suggesting potential therapeutic implications. Our genetic and functional studies identify bi-allelic truncating variants in AMFR as a cause of a novel autosomal recessive HSP by altering lipid metabolism, which may potentially be therapeutically modulated using precision medicine with statins

RNF185, a Novel Mitochondrial Ubiquitin E3 Ligase, Regulates Autophagy through Interaction with BNIP1

Autophagy is an evolutionarily conserved catabolic process that allows recycling of cytoplasmic organelles, such as mitochondria, to offer a bioenergetically efficient pathway for cell survival. Considerable progress has been made in characterizing mitochondrial autophagy. However, the dedicated ubiquitin E3 ligases targeting mitochondria for autophagy have not been revealed. Here we show that human RNF185 is a mitochondrial ubiquitin E3 ligase that regulates selective mitochondrial autophagy in cultured cells. The two C-terminal transmembrane domains of human RNF185 mediate its localization to mitochondrial outer membrane. RNF185 stimulates LC3II accumulation and the formation of autophagolysosomes in human cell lines. We further identified the Bcl-2 family protein BNIP1 as one of the substrates for RNF185. Human BNIP1 colocalizes with RNF185 at mitochondria and is polyubiquitinated by RNF185 through K63-based ubiquitin linkage in vivo. The polyubiquitinated BNIP1 is capable of recruiting autophagy receptor p62, which simultaneously binds both ubiquitin and LC3 to link ubiquitination and autophagy. Our study might reveal a novel RNF185-mediated mechanism for modulating mitochondrial homeostasis through autophagy

Key mechanisms governing resolution of lung inflammation

Innate immunity normally provides excellent defence against invading microorganisms. Acute inflammation is a form of innate immune defence and represents one of the primary responses to injury, infection and irritation, largely mediated by granulocyte effector cells such as neutrophils and eosinophils. Failure to remove an inflammatory stimulus (often resulting in failed resolution of inflammation) can lead to chronic inflammation resulting in tissue injury caused by high numbers of infiltrating activated granulocytes. Successful resolution of inflammation is dependent upon the removal of these cells. Under normal physiological conditions, apoptosis (programmed cell death) precedes phagocytic recognition and clearance of these cells by, for example, macrophages, dendritic and epithelial cells (a process known as efferocytosis). Inflammation contributes to immune defence within the respiratory mucosa (responsible for gas exchange) because lung epithelia are continuously exposed to a multiplicity of airborne pathogens, allergens and foreign particles. Failure to resolve inflammation within the respiratory mucosa is a major contributor of numerous lung diseases. This review will summarise the major mechanisms regulating lung inflammation, including key cellular interplays such as apoptotic cell clearance by alveolar macrophages and macrophage/neutrophil/epithelial cell interactions. The different acute and chronic inflammatory disease states caused by dysregulated/impaired resolution of lung inflammation will be discussed. Furthermore, the resolution of lung inflammation during neutrophil/eosinophil-dominant lung injury or enhanced resolution driven via pharmacological manipulation will also be considered

Enhancing Biological and Biomechanical Fixation of Osteochondral Scaffold: A Grand Challenge

Osteoarthritis (OA) is a degenerative joint disease, typified by degradation of cartilage and changes in the subchondral bone, resulting in pain, stiffness and reduced mobility. Current surgical treatments often fail to regenerate hyaline cartilage and result in the formation of fibrocartilage. Tissue engineering approaches have emerged for the repair of cartilage defects and damages to the subchondral bones in the early stage of OA and have shown potential in restoring the joint's function. In this approach, the use of three-dimensional scaffolds (with or without cells) provides support for tissue growth. Commercially available osteochondral (OC) scaffolds have been studied in OA patients for repair and regeneration of OC defects. However, some controversial results are often reported from both clinical trials and animal studies. The objective of this chapter is to report the scaffolds clinical requirements and performance of the currently available OC scaffolds that have been investigated both in animal studies and in clinical trials. The findings have demonstrated the importance of biological and biomechanical fixation of the OC scaffolds in achieving good cartilage fill and improved hyaline cartilage formation. It is concluded that improving cartilage fill, enhancing its integration with host tissues and achieving a strong and stable subchondral bone support for overlying cartilage are still grand challenges for the early treatment of OA

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings The global TFR decreased from 2.72 (95% uncertainty interval [UI] 2.66-2.79) in 2000 to 2.31 (2.17-2.46) in 2019. Global annual livebirths increased from 134.5 million (131.5-137.8) in 2000 to a peak of 139.6 million (133.0-146.9) in 2016. Global livebirths then declined to 135.3 million (127.2-144.1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2.1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27.1% (95% UI 26.4-27.8) of global livebirths. Global life expectancy at birth increased from 67.2 years (95% UI 66.8-67.6) in 2000 to 73.5 years (72.8-74.3) in 2019. The total number of deaths increased from 50.7 million (49.5-51.9) in 2000 to 56.5 million (53.7-59.2) in 2019. Under-5 deaths declined from 9.6 million (9.1-10.3) in 2000 to 5.0 million (4.3-6.0) in 2019. Global population increased by 25.7%, from 6.2 billion (6.0-6.3) in 2000 to 7.7 billion (7.5-8.0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58.6 years (56.1-60.8) in 2000 to 63.5 years (60.8-66.1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.Peer reviewe