Fast Polynomial Kernel Classification for Massive Data

In the era of big data, it is highly desired to develop efficient machine learning algorithms to tackle massive data challenges such as storage bottleneck, algorithmic scalability, and interpretability. In this paper, we develop a novel efficient classification algorithm, called fast polynomial kernel classification (FPC), to conquer the scalability and storage challenges. Our main tools are a suitable selected feature mapping based on polynomial kernels and an alternating direction method of multipliers (ADMM) algorithm for a related non-smooth convex optimization problem. Fast learning rates as well as feasibility verifications including the convergence of ADMM and the selection of center points are established to justify theoretical behaviors of FPC. Our theoretical assertions are verified by a series of simulations and real data applications. The numerical results demonstrate that FPC significantly reduces the computational burden and storage memory of the existing learning schemes such as support vector machines and boosting, without sacrificing their generalization abilities much.Comment: arXiv admin note: text overlap with arXiv:1402.4735 by other author

Human cytomegalovirus IE1 downregulates Hes1 in neural progenitor cells as a potential E3 ubiquitin ligase

This work was supported by: National Natural Science Foundation of China http://www.nsfc.gov.cn/; #81620108021: Fetal Brain Maldevelopment Caused by Sox2 Downregulation during Congenital Cytomegalovirus Infection; #31600145: The mechanism of HCMV-IE1 regulating Hes1 expression and rhythm in neural progenitor cells; #81571355: Construction of Murine Cytomegalovirus Derived viral tools for Specific Glia Tracing; #81271850: The regulation mechanism of HCMV infection on Notch signaling pathway in NPCs; and Sino-Africa Joint Research Center, Chinese Academy of Sciences http://www.sinafrica.cas.cn/; #SAJC201605: Geographical distribution and genetic variation of pathogens in Africa. This work is tightly linked to or is an important component of the above list projects, and is financially supported by all the fundings.Congenital human cytomegalovirus (HCMV) infection is the leading cause of neurological disabilities in children worldwide, but the mechanisms underlying these disorders are far from well-defined. HCMV infection has been shown to dysregulate the Notch signaling pathway in human neural progenitor cells (NPCs). As an important downstream effector of Notch signaling, the transcriptional regulator Hairy and Enhancer of Split 1 (Hes1) is essential for governing NPC fate and fetal brain development. In the present study, we report that HCMV infection downregulates Hes1 protein levels in infected NPCs. The HCMV 72-kDa immediate-early 1 protein (IE1) is involved in Hes1 degradation by assembling a ubiquitination complex and promoting Hes1 ubiquitination as a potential E3 ubiquitin ligase, followed by proteasomal degradation of Hes1. Sp100A, an important component of PML nuclear bodies, is identified to be another target of IE1-mediated ubiquitination. A C-terminal acidic region in IE1, spanning amino acids 451 to 475, is required for IE1/Hes1 physical interaction and IE1-mediated Hes1 ubiquitination, but is dispensable for IE1/Sp100A interaction and ubiquitination. Our study suggests a novel mechanism linking downregulation of Hes1 protein to neurodevelopmental disorders caused by HCMV infection. Our findings also complement the current knowledge of herpesviruses by identifying IE1 as the first potential HCMV-encoded E3 ubiquitin ligase.Publisher PDFPeer reviewe

NF-κB and AP-1 are required for the lipopolysaccharide-induced expression of MCP-1, CXCL1, and Cx43 in cultured rat dorsal spinal cord astrocytes

TLR4 and Cx43 signaling in dorsal spinal cord has been shown to be involved in the development of neuropathic pain. However, it is not clear whether TLR4 signaling is associated with the expression of MCP-1, CXCL1, and Cx43 in LPS (lipopolysaccharide)-treated rat dorsal spinal cord astrocytes under in vitro condition. In the present study, we found that TLR4 antagonist TAK-242 significantly inhibited LPS-induced MCP-1, CXCL1, and Cx43 expression, suggesting the role of TLR4 in response to LPS in cultured dorsal spinal cord astrocytes. Application of TAK-242 significantly blocked LPS-induced NF-κB and AP-1 activity and the expression of MCP-1, CXCL1 and Cx43. Furthermore, NF-κB inhibitor PDTC and AP-1 inhibitor SR11302 significantly blocked LPS-induced MCP-1, CXCL1, and Cx43 expression. DNA-binding activity of NF-κB, its effect on MCP-1 expression was suppressed by PDTC and SR11302. On the other hand, DNA-binding activity of AP-1, its effect on CXCL1 or Cx43 expression was also suppressed by PDTC and SR11302. In addition, PDTC was found to inhibit the nuclear translocation of AP-1 and the expression of c-Jun induced by LPS, which suggested that NF-κBp65 is essential for the AP-1 activity. Similarly, SR11302 significantly blocked LPS-induced the nuclear translocation of NF-κBp65 and the expression of NF-κBp65 induced by LPS. Pretreatment with CBX, Gap26, or Gap19 (Cx43 blockers) significantly inhibited abnormal astrocytic hemichannel opening and chemokines (MCP-1 and CXCL1) release in LPS-stimulated astrocytes. In summary, cell culture experiments revealed that LPS stimulation could evoke TLR4 signaling with the subsequent activation of NF-κB and AP-1, resulting in the expression of MCP-1, CXCL1, and Cx43. TLR4 activation increased Cx43 hemichannel, but not gap-junction activities and induced the release of the MCP-1 and CXCL1 from astrocytes via Cx43 hemichannel. These findings may help us to understand the role of astrocytic signaling in inflammatory response within dorsal spinal cord tissue

Maternal exposure to ambient air pollution and congenital heart defects in China

Background: Evidence of maternal exposure to ambient air pollution on congenital heart defects (CHD) has been mixed and are still relatively limited in developing countries. We aimed to investigate the association between maternal exposure to air pollution and CHD in China.Method: This longitudinal, population-based, case-control study consecutively recruited fetuses with CHD and healthy volunteers from 21 cities, Southern China, between January 2006 and December 2016. Residential address at delivery was linked to random forests models to estimate maternal exposure to particulate matter with an aerodynamic diameter of ≤1 µm (PM1), ≤2.5 µm, and ≤10 µm as well as nitrogen dioxides, in three trimesters. The CHD cases were evaluated by obstetrician, pediatrician, or cardiologist, and confirmed by cardia ultrasound. The CHD subtypes were coded using the International Classification Diseases. Adjusted logistic regression models were used to assess the associations between air pollutants and CHD and its subtypes.Results: A total of 7055 isolated CHD and 6423 controls were included in the current analysis. Maternal air pollution exposures were consistently higher among cases than those among controls. Logistic regression analyses showed that maternal exposure to all air pollutants during the first trimester was associated with an increased odds of CHD (e.g., an interquartile range [13.3 µg/m3] increase in PM1 was associated with 1.09-fold ([95% confidence interval, 1.01-1.18]) greater odds of CHD). No significant associations were observed for maternal air pollution exposures during the second trimester and the third trimester. The pattern of the associations between air pollutants and different CHD subtypes was mixed.Conclusions: Maternal exposure to greater levels of air pollutants during the pregnancy, especially the first trimester, is associated with higher odds of CHD in offspring. Further longitudinal well-designed studies are warranted to confirm our findings

Management of granulomatous lobular mastitis: an international multidisciplinary consensus (2021 edition)

Granulomatous lobular mastitis (GLM) is a rare and chronic benign inflammatory disease of the breast. Difficulties exist in the management of GLM for many front-line surgeons and medical specialists who care for patients with inflammatory disorders of the breast. This consensus is summarized to establish evidence-based recommendations for the management of GLM. Literature was reviewed using PubMed from January 1, 1971 to July 31, 2020. Sixty-six international experienced multidisciplinary experts from 11 countries or regions were invited to review the evidence. Levels of evidence were determined using the American College of Physicians grading system, and recommendations were discussed until consensus. Experts discussed and concluded 30 recommendations on historical definitions, etiology and predisposing factors, diagnosis criteria, treatment, clinical stages, relapse and recurrence of GLM. GLM was recommended as a widely accepted definition. In addition, this consensus introduced a new clinical stages and management algorithm for GLM to provide individual treatment strategies. In conclusion, diagnosis of GLM depends on a combination of history, clinical manifestations, imaging examinations, laboratory examinations and pathology. The approach to treatment of GLM should be applied according to the different clinical stage of GLM. This evidence-based consensus would be valuable to assist front-line surgeons and medical specialists in the optimal management of GLM.Improving the Ability of Diagnosis and Treatment of Difficult Disease

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions