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The security of HTTPS fundamentally relies on SSL/TLS certificates issued by Certificate Authorities (CAs), which, however, are vulnerable to be compromised to issue unauthorized certificates (i.e., certificates issued without domains’ permission). Current countermeasures such as Certificate Transparency (CT) can only detect unauthorized certificates rather than preventing them. In this article, we present Pistis , a framework for issuing authorized and trusted certificates with the distributed ledger and Trusted Execution Environment (TEE) technology. In Pistis , TEE nodes validate whether the domain in a requested certificate passes the domain ownership validation (i.e., under corresponding applicants’ control) and submit attested results to a smart contract in the distributed ledger. The smart contract issues a certificate to the applicant when an attested result shows a pass. Therefore, Pistis can ensure its issued certificates are authorized due to the domain ownership validation mechanism in the TEE. Furthermore, as the issued certificates are stored in a Merkle Patricia Tree (MPT) in Pistis , they are trusted and can be verified by a normal user easily. The security of Pistis is formally proved in the Universally Composable (UC) framework. Compared with state-of-the-art, Pistis avoids potential damages by preventing unauthorized certificates from issuing.

Despite increasingly emerging applications, a primary concern for blockchain to be fully practical is the inefficiency of data query. Direct queries on the blockchain take much time by searching every block, while indirect queries on a blockchain database greatly degrade the authenticity of query results. To conquer the authenticity problem, we propose a Verifiable Query Layer (VQL) that can be deployed in the cloud to provide both efficient and verifiable data query services for blockchain systems. The middleware layer extracts data from the underlying blockchain system and efficiently reorganizes them in databases. To prevent falsified data from being stored in the middleware, a cryptographic fingerprint is calculated based on each constructed database. The database fingerprint will be first verified by miners and then written into the blockchain. Moreover, public users can verify the entire databases or several databases that interest them in the middleware layer. We implement VQL together with the verification schemes and conduct extensive experiments based on a practical blockchain system. The evaluation results demonstrate that VQL can efficiently support various data query services and guarantee the authenticity of query results for blockchain systems.

Introduction Mechanical force is attributed to the formation of tumor blood vessels, influences cancer cell invasion and metastasis, and promotes reprogramming of the energy metabolism. Currently, therapy strategies for the tumor microenvironment are being developed progressively. The purpose of this article is to discuss the molecular mechanism, diagnosis, and treatment of mechanical force in urinary tract cancers and outline the medications used in the mechanical microenvironment. Areas covered This review covers the complex mechanical elements in the microenvironment of urinary system malignancies, focusing on mechanical molecular mechanisms for diagnosis and treatment. Expert opinion The classification of various mechanical forces, such as matrix stiffness, shear force, and other forces, is relatively straightforward. However, little is known about the molecular process of mechanical forces in urinary tract malignancies. Because mechanical therapy is still controversial, it is critical to understand the molecular basis of mechanical force before adding mechanical therapy solutions.

Purpose of Review Inhaled environmental exposures cause over 12 million deaths per year worldwide. Despite localized efforts to reduce environmental exposures, tobacco smoking and air pollution remain the urgent public health challenges that are contributing to the growing prevalence of respiratory diseases. The purpose of this review is to describe the mechanisms through which inhaled environmental exposures accelerate lung aging and cause overt lung disease. Recent Findings Environmental exposures related to fossil fuel and tobacco combustion and occupational exposures related to silica and coal mining generate oxidative stress and inflammation in the lungs. Sustained oxidative stress causes DNA damage, epigenetic instability, mitochondrial dysfunction, and cell cycle arrest in key progenitor cells in the lung. As a result, critical repair mechanisms are impaired, leading to premature destruction of the lung parenchyma. Summary Inhaled environmental exposures accelerate lung aging by injuring the lungs and damaging the cells responsible for wound healing. Interventions that minimize exposure to noxious antigens are critical to improve lung health, and novel research is required to expand our knowledge of therapies that may slow or prevent premature lung aging.

As semiconductor technology scales, modern microprocessors are more vulnerable to transient faults. Software-level fault tolerance schemes are promising because they can improve reliability effectively without extra hardware. Redundant Multi-threading (RMT) uses off-the-shelf cores as redundancy to achieve error resilience. Latest software RMT fault-tolerance models do not effectively cope with transient faults occurring on multiple components during the application execution, resulting in a large number of silent data corruptions (SDC). To address this challenge, we propose FERNANDO, a software-level RMT runtime fault tolerance scheme which provides enhanced error detection and comprehensive error recovery by Triple-Modular Redundancy (TMR). On an ARM Cortex-A57 like simulated microprocessor, we performed probability model transient fault injection experiments in different components of all cores. The results demonstrate that, compared to the state-of-the-art technique, FERNANDO can reduce the SDC rate by about 86.67 percent and optimize the execution time overhead by about 19.64 percent.

Summary Background Pregnancy is associated with deteriorations in maternal bone strength and heightened susceptibility to bone fractures. We aimed to investigate whether ambient particulate matter (PM)2·5 concentrations were associated with bone strength during pregnancy. Methods In this longitudinal cohort study, we analysed longitudinal data from women participating in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort in Mexico City, Mexico. Eligible women were aged 18 years or older, at less than 20 weeks' gestation at the time of recruitment, planning to stay in Mexico City for the next 3 years, without heart or kidney disease, did not use steroids or anti-epileptic drugs, were not daily consumers of alcohol, and had access to a telephone. Daily ambient PM2·5 concentrations were estimated from a spatio-temporal model that was based on the individual's address. Trabecular bone strength was measured using quantitative ultrasound from the radius of the middle finger and cortical bone strength from the proximal phalanx of the middle finger, during the second trimester, third trimester, and 1 and 6 months post partum. Bone strength T scores were modelled with PM2·5 concentrations using linear mixed models and distributed lag models. Findings Adjusting for multiple exposure windows, each 10 ug/m3 increase in PM2·5 exposure concentrations in the first trimester was associated with a 0·18 SD decrease (95% CI −0·35 to −0·01; p=0·033) in ultrasound speed-of-sound (SOS) T score of trabecular bone strength from the second trimester until 6 months post partum. Similarly, each 10 μg/m3 increase in third trimester PM2·5 exposure was associated with a 0·18 SD decrease (–0·36 to −0·01; p=0·044) in the SOS T score of trabecular bone strength from the third trimester until 6 months post partum. PM2·5 exposure in the first month post partum was associated with a 0·20 SD decline (–0·39 to −0·01; p=0·043) in cortical bone strength until 6 months post partum. Interpretation Ambient PM2·5 exposure during and after pregnancy was associated with diminished trabecular and cortical bone strength. Early pregnancy PM2·5 exposure was associated with a greater decline in bone strength later during pregnancy. Late pregnancy and early post-partum exposures adversely affected the post-partum bone strength recovery. Technological and policy solutions to reduce PM2·5 pollution could improve public health by reducing bone fracture risk. Funding US National Institute of Environmental Health Sciences.

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death among women. Various mechanisms are involved in the initiation and progression of breast cancer. Metabolic dysregulation has been associated with increasing breast cancer incidence and mortality. However, little is known about how metabolic disease regulates the development and progression of breast cancer at the molecular level. Here, using a hybridization capture-based panel including 124 cancer-associated genes, we performed targeted next-generation sequencing of tumor tissues and matched blood samples from 20 postmenopausal patients with primary breast cancer, in which 6 cases suffered from preexisting metabolic disorders including hypertension, type 2 diabetes, and coronary heart disease. We took only the protein-altering variants and identified 170 somatic mutations of 59 genes. Among these, 40 mutated genes were found in the metabolic disease group, and 33 mutated genes were found in the non–metabolic disease group. Importantly, nonsynonymous mutations of 26 genes (MSH3, BRAF, MLH3, MTOR, DDR2, ALK, etc.) were uniquely present in the metabolic disease group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed to investigate biological functions and key pathways of somatic mutations. TP53, PIK3CA, and PTEN were the top three commonly mutated genes at a higher frequency compared with the Cancer Genome Atlas (TCGA) data, and several novel but infrequent mutations in other genes were also found. Although further studies are required to validate these variants, our results are the first to suggest a specific molecular profile of breast cancer with preexisting metabolic disease.

High luminescence efficiency of the halide perovskite absorber layer in perovskite solar cells (PVSCs) will reduce the open-circuit voltage (Voc) loss and further increase the cell efficiency. Still, while quasi-2D-structure perovskite films exhibit high emissivity in light-emitting devices, quasi-2D PVSCs show severe Voc loss associated with non-radiative recombination. Here we demonstrate how the use of highly luminescent PEA0.2BA1.8MA3Pb4I13 in quasi-2D PVSCs allows, via Cl− passivation and heat-light post-co-treatment, a champion external electroluminescence quantum efficiency around 2.3% and a record low Voc deficit of 0.36 eV. To our knowledge, this is the lowest Voc loss for quasi-2D PVSCs and among the lowest for any type of PVSCs. As a result, high performance quasi-2D PVSCs are obtained, with a Voc up to 1.29 V and 15.81% efficiency, showing excellent stability, and retain 98% of the original efficiency after heating at 85 °C for 1590 h. This work paves the way toward highly luminescent and efficient quasi-2D PVSCs.

A DNA fingerprint database is an efficient, stable, and automated tool for plant molecular research that can provide comprehensive technical support for multiple fields of study, such as pan-genome analysis and crop breeding. However, constructing a DNA fingerprint database for plants requires significant resources for data output, storage, analysis, and quality control. Large amounts of heterogeneous data must be processed efficiently and accurately. Thus, we developed plant SNP database management system (PSNPdms) using an open-source web server and free software that is compatible with single nucleotide polymorphism (SNP), insertion–deletion (InDel) markers, Kompetitive Allele Specific PCR (KASP), SNP array platforms, and 23 species. It fully integrates with the KASP platform and allows for graphical presentation and modification of KASP data. The system has a simple, efficient, and versatile laboratory personnel management structure that adapts to complex and changing experimental needs with a simple workflow process. PSNPdms internally provides effective support for data quality control through multiple dimensions, such as the standardized experimental design, standard reference samples, fingerprint statistical selection algorithm, and raw data correlation queries. In addition, we developed a fingerprint-merging algorithm to solve the problem of merging fingerprints of mixed samples and single samples in plant detection, providing unique standard fingerprints of each plant species for construction of a standard DNA fingerprint database. Different laboratories can use the system to generate fingerprint packages for data interaction and sharing. In addition, we integrated genetic analysis into the system to enable drawing and downloading of dendrograms. PSNPdms has been widely used by 23 institutions and has proven to be a stable and effective system for sharing data and performing genetic analysis. Interested researchers are required to adapt and further develop the system.

Background/Aim Adiposity trajectories reflect dynamic process of growth and may predict later life health better than individual measures. Prenatal phthalate exposures may program later childhood adiposity, but findings from studies examining these associations are conflicting. We investigated associations between phthalate biomarker concentrations during pregnancy with child adiposity trajectories. Methods We followed 514 mother-child pairs from the Mexico City PROGRESS cohort from pregnancy through twelve years. We measured concentrations of nine phthalate biomarkers in 2nd and 3rd trimester maternal urine samples to create a pregnancy average using the geometric mean. We measured child BMI z-score, fat mass index (FMI), and waist-to-height ratio (WHtR) at three study visits between four and 12 years of age. We identified adiposity trajectories using multivariate latent class growth modeling, considering BMI z-score, FMI, and WHtR as joint indicators of latent adiposity. We estimated associations of phthalates biomarkers with class membership using multinomial logistic regression. We used quantile g-computation to estimate the potential effect of the total phthalate mixture and assessed effect modification by sex. Results We identified three trajectories of child adiposity, a “low-stable”, a “low-high”, and a “high-high” group. A doubling of the sum of di (2-ethylhexyl) phthalate metabolites (ΣDEHP), was associated with 1.53 (1.08, 2.19) greater odds of being in the “high-high” trajectory in comparison to the “low-stable” group, whereas a doubling in di-isononyl phthalate metabolites (ΣDiNP) was associated with 1.43 (1.02, 2.02) greater odds of being in the “low-high” trajectory and mono (carboxy-isononyl) phthalate (MCNP) was associated with 0.66 (0.45, 97) lower odds of being in the “low-high” trajectory. No sex-specific associations or mixture associations were observed. Conclusions Prenatal concentrations of urinary DEHP metabolites, DiNP metabolites, and MCNP, a di-isodecyl phthalate metabolite, were associated with trajectories of child adiposity. The total phthalate mixture was not associated with early life child adiposity.

BACKGROUND AND AIM: Previous research have suggested the link between air pollution and epigenetic changes such as microRNA expression. In this study, we examined whether short- and long-term expos...

BACKGROUND AND AIM: Perfluoroalkyl substances (PFAS), the “forever chemicals”, accumulate mainly in the liver and have various adverse health effects. Little is known about the mechanistic pathways...

BACKGROUND AND AIM: The gut microbiome is important in modulating health in childhood. Metal exposures affect multiple health outcomes, but their ability to modify bacterial communities in children...

At present, many industrial applications urgently need a real-time high-accuracy automatic counting algorithm to realize the counting function of various objects. Some scholars are studying the use of deep learning algorithms to count objects in industrial applications. However, facing closely arranged and different objects, deep learning algorithms cannot achieve this function. Aiming at the application background of regular cuboids counting with a wide range of requirements, this paper provides a real-time high-accuracy automatic counting algorithm based on a deep understanding of the scene and a comprehensive use of multiple computer vision technologies. The algorithm can meet the stringent requirements of industrial applications and realize real-time high-accuracy automatic counting of closely arranged cuboids. And there is no requirement for whether the surfaces of the cuboids are the same, and there is no need to prepare the template pictures of the cuboids in advance. The algorithm mainly uses the characteristics of gaps between cuboids, and adopts improved Hough line detection to identify gaps, and finally realizes the counting function. The algorithm proposed in this paper has been verified on the counting of pillboxes in the industrial application of smart pharmacies. Compared with the deep learning algorithm, it has the characteristics of good interpretability, good generalization, fast speed and high accuracy.

Haotian Wu,1,2 Song Liu,1,2 Chunxia Li,3 Zhaohui Song1,2 1Department of Orthopaedic Surgery, The 3rd Hospital of Hebei Medical University, Shijiazhuang, 050051, Hebei, People’s Republic of China; 2Key Laboratory of Biomechanics of Hebei Province, Shijiazhuang, 050051, Hebei, People’s Republic of China; 3Department of Imaging Medicine, General Hospital of Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia 010017, People’s Republic of ChinaCorrespondence: Haotian WuDepartment of Orthopaedic Surgery, The 3rd Hospital, Hebei Medical University, No. 139 Ziqiang Road, Shijiazhuang, 050051, People’s Republic of China, Tel +86-311-88603682Fax +86-311-87023626Email liu18633031986@163.comAim: This study aims to present a modified Laboratory Risk Indicator for Necrotizing Fasciitis (m-LRINEC) scoring system and to evaluate its ability in discriminating necrotizing fasciitis (NF) from other severe soft-tissue infections.Methods: Patients with NF diagnosed by surgical findings in our institution between January 2014 and December 2020 were included as the case group, matched by controls with severe soft-tissue infections other than NF in a ratio of 2:1, based on demographics, calendar time and immunosuppressant status. Patients’ demographics, comorbidities and laboratory test results were extracted from medical records. Logistic regression analyses were used to determine the association with NF after adjustment for confounders, whereby m-LRINEC was developed. Receiver operating characteristics (ROC) curves and the area under the curve (AUC) were used to evaluate its discriminating ability.Results: There were 177 patients included, 59 in the NF group and 118 in the non-NF group. We added comorbid diabetes and kidney disease to the original LRINEC scoring system, used high-sensitivity C-reactive protein (HCRP) to replace the CRP and redefined the cut-off values for the other four variables, to develop the m-LRINEC system. The cut-off value for m-LRINEC was 17 points, with corresponding sensitivity of 93.2% and specificity of 86.9%, and the AUC was 0.935 (95% CI 0.892 to 0.977; p< 0.001).Conclusion: The m-LRINEC scoring system shows a high sensitivity and specificity in discriminating NF from other severe soft-tissue infections. Patients with an m-LRINEC score of > 17 points should have a high index of suspicion for the presence of NF. The validity of the m-LRINEC needs to be confirmed in studies with larger samples and better design.Keywords: necrotizing fasciitis, factors, biomarkers, scoring system, m-LRINEC

With the development of big data technology, predicting users’ purchasing intentions through historical data of users' purchasing behaviors has become an essential strategy for companies to carry out precision marketing and increase sales volume. The data of users’ purchasing behavior is characterized by a large amount, substantial variability, and potential long-term dependency. Therefore, the bidirectional long short-term memory neural network (BiLSTM) model is used in this paper to predict the user's purchasing behavior. First, the model takes user ID as the benchmark of the sequence, capturing the fluctuation law of the user purchase volume and fully mine the long-term dependency of user's purchasing behavior. Second, the BiLSTM model adaptively extracts features, realizes "end-to-end" prediction of user purchase behavior, and reduces feature engineering's subjectivity. This paper verifies the effectiveness of this method based on the real user purchasing behavior data sets. The experiment results prove that the BiLSTM method has high accuracy in the prediction of user purchase behavior.

Supplemental Digital Content is available in the text., Background: Previous studies suggest a negative association between prenatal polybrominated diphenyl ethers (PBDEs) exposure and child cognitive and psychomotor development. However, the timing of the relationship between PBDE exposure and neurodevelopment is still unclear. We examined the association between PBDE concentration at two different prenatal times (early and late pregnancy) and cognitive function in children 6–8 years of age. Methods: Eight hundred pregnant women were recruited between 2007 and 2009 from Sherbrooke, Canada. Four PBDE congeners (BDE-47, -99, -100, and -153) were measured in maternal plasma samples collected during early pregnancy (12 weeks of gestation) and at delivery. At 6–8 years of age, 355 children completed a series of subtests spanning multiple neuropsychologic domains: verbal and memory skills were measured using the Wechsler Intelligence Scale for Children, Fourth Edition; visuospatial processing using both Wechsler Intelligence Scale for Children, Fourth Edition and Neuropsychological Assessment second edition; and attention was assessed through the Test of Everyday Attention for Children. Additionally, parents completed subtests from the Developmental Coordination Disorder Questionnaire to measure child motor control. We used linear regression and quantile g-computation models to estimate associations of PBDE congener concentrations and psychologic test scores. Results: In our models, no significant associations were detected between PBDE mixture and any of the child psychologic scores. BDE-99 concentration at delivery was nominally associated with higher scores on short-term and working memory while a decrease in spatial perception and reasoning was nominally associated with higher BDE-100 concentration at delivery. Conclusion: Overall, our results did not show a significant association between PBDEs and child cognitive and motor development.

In order to create more attractive graffiti works, the Internet of Things technology is used to collect people’s preference information data, and then cloud computing and big data analysis are applied to calculate and analyze the data, so as to get more design elements in line with people’s preferences, providing more material for the creators of graffiti art and facilitating their further creation of graffiti. In recent years, graffiti art, as a kind of postmodern marginal cultural art, has great expressiveness and creativity, which makes graffiti art widely used. Particularly in visual communication design, graffiti art has more characteristics and is deeply loved by the people. With the continuous development of science and technology, Internet of Things technology and cloud computing have acquired more information for many fields, thus assisting the field to complete deeper analysis and research. However, there are few applications in the field of graffiti art. Therefore, this paper combines cloud computing and Internet of Things to obtain more visual communication design elements to provide material for the creator, which is conductive for their continuing creation.

In order to achieve information visualization, realize good interaction between users and information, and meet the needs of users, this study first studied the interaction behavior of the user when using the smartphone was studied, and analyzed the visual factors of the smartphone interface were analyzed from the user sensory interaction level, and the user operation mode level, from the expression of visual form to the commonly used interface mode and User Interface (UI) component space. On this basis, the situational visual expression of the scene in different interaction scenarios was analyzed. Secondly, the basic theory of visual design of smartphone application interface was explained from the perspectives of aesthetics, semiotics and Gestalt psychology, In other words, the visual design of the application interface should be metaphorical, highlighting the key points in the overall visual style, and conforming to the user’s psychological model. At the same time, in order to meet the user’s personalized needs for control, it must add customized options. Finally, the model of the interface visual design method of the interdisciplinary “Shared Communication” system for the interface design of the mobile APP was constructed, and the case of Didi Chuxing was analyzed, which preliminarily confirmed the feasibility of the construction of the interface visual design method model of the “Shared Communication” system.

Renal cell carcinoma is a highly heterogeneous cancer group, and the complex microenvironment of the tumor provides appropriate immune evasion opportunities. The molecular mechanism of immune escape in renal cell carcinoma is currently a hot issue, focusing primarily on the major complex of histocompatibility, immunosuppressive cells, their secreted immunosuppressive cytokines, and apoptosis molecule signal transduction. Immunotherapy is the best treatment option for patients with metastatic or advanced renal cell carcinoma and combination immunotherapy based on a variety of principles has shown promising prospects. Comprehensive and in-depth knowledge of the molecular mechanism of immune escape in renal cell carcinoma is of vital importance for the clinical implementation of effective therapies. The goal of this review is to address research into the mechanisms of immune escape in renal cell carcinoma and the use of the latest immunotherapy. In addition, we are all looking forward to the latest frontiers of experimental combination immunotherapy.

Background This study was done to observe the incidence of Osteo-line on the femur neck and to explore the clinical application of Osteo-line in osteotomy. Methods Eighty-nine adult femur specimens were selected to observe the incidence of Osteo-line on the femur neck. From August 2015 to January 2019, a total of 278 patients who completed unilateral hip arthroplasty at the Third Hospital of Hebei Medical University were retrospectively included. Patients who accepted osteotomy via Osteo-line on the femur neck were defined as the experimental group (n = 139), and patients who accepted osteotomy via traditional method (The femoral distance 1.5 cm above the trochanter was retained for osteotomy by visual inspection.) were defined as the control group (n = 139). According to the postoperative pelvic X-ray, Photoshop was used to evaluate the leg length discrepancy (LLD) by the CFR-T-LT method. Results Among the 89 specimens, the incidence of anterior Osteo-line was 75.28%, and the incidence of posterior Osteo-line was 100%. According to the clinical application results, the incidence of anterior Osteo-line on the femur neck was 80%, and the incidence of posterior Osteo-line was 100%. The Osteo-line was clearer than those on the femoral specimens. Twenty-six cases had LLD greater than 1 cm (9.29%), including 2 cases in the experimental group and 24 cases in the control group. The average postoperative LLD in the experimental group (0.19 ± 0.38 mm) was significantly shorter than in the control group (0.54 ± 0.51 mm)(P = 0.005). Conclusion The incidence of Osteo-line on the femur neck was high, and patients who accepted osteotomy via Osteo-line on the femur neck can achieve shorter postoperative LLD than the control group.

Autophagy is a treatment target for many disorders, including cancer, and its specific role is becoming increasingly well known. In tumors, researchers pay attention to microribonucleic acids (miRNAs) with regulatory effects to develop more effective therapeutic drugs for autophagy and find new therapeutic targets. Various studies have shown that autophagy-related miRNAs play an irreplaceable role in different tumors, such as miR-495, miR-30, and miR-101. These miRNAs are associated with autophagy resistance in gastric cancer, non-small cell lung cancer, and cervical cancer. In recent years, autophagy-related miRNAs have also been reported to play a role in autophagy in urinary system tumors. This article reviews the regulatory effects of autophagy-related miRNAs in kidney, bladder, and prostate cancer and provides new ideas for targeted therapy of the three major tumors of the urinary system.

Studies have reported associations between phthalates, a family of ubiquitous environmental contaminants, and metabolic complications of pregnancy, but no study has considered these outcomes beyond...

Background Prenatal phthalate exposures may affect processes that underlie offspring cardiometabolic health, but findings from studies examining these associations are conflicting. We examined associations between biomarkers of phthalate exposures during pregnancy with child lipid and adipokine levels. Methods Data were from 463 mother-child pairs in the PROGRESS cohort of Mexico City. We quantified 15 phthalate metabolites in 2nd and 3rd trimester maternal urine samples and created an average pregnancy measure using the geometric mean. We evaluated the 15 metabolites as nine biomarkers, including four metabolite molar sums. We measured fasting serum triglycerides, non-HDL cholesterol, leptin, and adiponectin in children at the six-year follow-up visit (mean = 6.8 years). We estimated associations using linear regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) and assessed effect modification by sex. Results In BKMR and WQS models, higher concentrations of the total mixture of phthalate biomarkers were associated with lower triglycerides (β = −3.7% [-6.5, −0.78] per 1 unit increase in WQS biomarker index) and non-HDL cholesterol (β = −2.0 [-3.7, −0.25] ng/ml per increase in WQS biomarker index). Associations between individual biomarkers and child outcomes were largely null. We observed some evidence of effect modification by child sex for mono-3-carboxypropyl phthalate (β = 19.4% [1.26, 40.7] per doubling of phthalate) and monobenzyl phthalate (β = −7.6% [-14.4, -0.23]) in girls for adiponectin. Conclusions Individual prenatal phthalate biomarkers were not associated with child lipid or adipokine levels. Contrary to our hypothesis, the total phthalate mixture was associated with lower child triglycerides and non-HDL cholesterol.

Importance Despite evidence of an association between prenatal acetaminophen exposure and attention-deficit/hyperactivity disorder (ADHD) in offspring, the drug is not contraindicated during pregnancy, possibly because prior studies have relied on maternal self-report, failed to quantify acetaminophen dose, and lacked mechanistic insight. Objective To examine the association between prenatal acetaminophen exposure measured in meconium (hereinafter referred to as meconium acetaminophen) and ADHD in children aged 6 to 7 years, along with the potential for mediation by functional brain connectivity. Design, Setting, and Participants This prospective birth cohort study from the Centre Hospitalier Universite de Sherbrooke in Sherbrooke, Quebec, Canada, included 394 eligible children, of whom 345 had meconium samples collected at delivery and information on ADHD diagnosis. Mothers were enrolled from September 25, 2007, to September 10, 2009, at their first prenatal care visit or delivery and were followed up when children were aged 6 to 7 years. When children were aged 9 to 11 years, resting-state brain connectivity was assessed with magnetic resonance imaging. Data for the present study were collected from September 25, 2007, to January 18, 2020, and analyzed from January 7, 2019, to January 22, 2020. Exposures Acetaminophen levels measured in meconium. Main Outcomes and Measures Physician diagnosis of ADHD was determined at follow-up when children were aged 6 to 7 years or from medical records. Resting-state brain connectivity was assessed with magnetic resonance imaging; attention problems and hyperactivity were assessed with the Behavioral Assessment System for Children Parent Report Scale. Associations between meconium acetaminophen levels and outcomes were estimated with linear and logistic regressions weighted on the inverse probability of treatment to account for potential confounders. Causal mediation analysis was used to test for mediation of the association between prenatal acetaminophen exposure and hyperactivity by resting-state brain connectivity. Results Among the 345 children included in the analysis (177 boys [51.3%]; mean [SD] age, 6.58 [0.54] years), acetaminophen was detected in 199 meconium samples (57.7%), and ADHD was diagnosed in 33 children (9.6%). Compared with no acetaminophen, detection of acetaminophen in meconium was associated with increased odds of ADHD (odds ratio [OR], 2.43; 95% CI, 1.41-4.21). A dose-response association was detected; each doubling of exposure increased the odds of ADHD by 10% (OR, 1.10; 95% CI, 1.02-1.19). Children with acetaminophen detected in meconium showed increased negative connectivity between frontoparietal and default mode network nodes to clusters in the sensorimotor cortices, which mediated an indirect effect on increased child hyperactivity (14%; 95% CI, 1%-26%). Conclusions and Relevance Together with the multitude of other cohort studies showing adverse neurodevelopment associated with prenatal acetaminophen exposure, this work suggests caution should be used in administering acetaminophen during pregnancy. Research into alternative pain management strategies for pregnant women could be beneficial.

Background: Distal tibia shaft fractures have a high risk of mal-alignment when treated with intramedullary nailing (IMN). Permanent blocking screws (BSs) and temporary blocking pins (BPs) are often used as supplements to help IMN get good alignment. The purpose of this study was to compare the clinical and radiographic outcomes of temporary BPs and permanent BSs for distal tibia shaft fractures.Methods: From March 2014 to May 2019, a total of 89 patients with distal tibia shaft fractures were included in this retrospective study and divided into two groups. All fractures were located below the isthmus but 4 cm above the tibial plafond. The differences in operating time, intraoperative bleeding, fibula plate fixation, number of BP/BS, initial and final alignment, loss of reduction, fracture healing time, and postoperative complications were analyzed. Functional outcomes of the ankle were assessed with the American Orthopedic Foot and Ankle Society (AOFAS) score.Results: All patients underwent a minimum follow-up of 13 months. The operating time was (73.9±6.1) min and (80.2±8.6) min in the BP group and BS group, respectively (P < 0.05); intraoperative bleeding was (88.2±18.0) mL and (92.9±26.6) mL, respectively (P > 0.05); initial reduction deformity in coronal plane was (0.5±2.3) degrees and (0.9±2.3) degrees, respectively (P > 0.05); final alignment deformity in coronal plane was (1.2±2.7) degrees and (1.3±2.4) degrees, respectively (P > 0.05); initial reduction deformity in sagittal plane was (0.6±2.2) degrees and (0.6±2.4) degrees, respectively (P > 0.05); final alignment deformity in sagittal plane was (0.9±2.3) degrees and (1.0±2.2) degrees, respectively (P > 0.05); As for the loss of reduction, there was no significant difference in sagittal plane between the two groups(P > 0.05). Although the loss of reduction in the coronal plane of the BP group (0.8±0.7 degrees) is statistically higher than that of the BS group (0.5±0.5 degrees), the small difference was not clinically important (P < 0.05). No significant differences were found between the two groups in fracture healing time, AOFAS score and complications (P > 0.05).Conclusion: Both temporary BP and permanent BS can help achieve equivalent overall alignment. However, BP technique is simpler and takes less time.

BACKGROUND: Parabens, which are used as a preservative in foods and personal care products, are detected in nearly 100% of human urine samples. Exposure to parabens is associated with DNA damage, male infertility, and endocrine disruption in adults, but the effects of prenatal exposure are unclear. In part, this is due to inadequate assessment of exposure in maternal urine, which may only reflect maternal rather than fetal exposure. To address this gap, we examined the association of prenatal methylparaben measured in meconium with preterm birth, gestational age, birthweight, maternal thyroid hormones, and child Attention-Deficit Hyperactivity Disorder (ADHD) at 6-7 years. DESIGN: Data come from the GESTation and the Environment (GESTE) prospective observational pregnancy cohort in Sherbrooke, Quebec, Canada. Participants were 345 children with data on ADHD among 394 eligible pregnancies in women age ≥18 years with no known thyroid disease before pregnancy and meconium collected at delivery. Methylparaben was measured in meconium. Birthweight, gestational age, and maternal thyroid hormones at

Neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) are inflammatory demyelinating diseases of the central nervous system. Exosomal microRNAs (miRNAs) are emerging biomarkers for demyelinating diseases. In this study, 52 aquaporin-4 antibody serum-positive NMOSD patients, 18 relapsing-remitting multiple sclerosis (RRMS) patients and 17 healthy controls (HCs) were included for the next-generation sequencing (NGS). To validate the NGS results, the valuable miRNAs were selected for validation by real-time quantitative polymerase chain reaction in another cohort of patients, comprising 31 NMOSD patients and 14 HCs. In addition, these miRNAs were also validated in a longitudinal study. NGS data revealed the exosomal miRNAs profile in NMOSD patients was different from HCs. Among those potential exosomal miRNAs which can distinguish NMOSD status, hsa-miR-122-3p and hsa-miR-200a-5p were the most abundant miRNAs. In addition, hsa-miR-122-3p and hsa-miR-200a-5p were significantly upregulated in the serum exosome of relapsing NMOSD compared with that in remitting NMOSD. Hsa-miR-122-3p and hsa-miR-200a-5p had positive correlations with disease severity in NMOSD patients. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the MAPK, Wnt and Ras signaling pathways were enriched. Further biological function analysis demonstrated that these two miRNAs might be involved in the immunoregulation of NMOSD pathogenesis. Our results indicated that miRNAs delivered by exosomes could be applied as potential biomarkers for NMOSD.

The high variability and somatic stability of DNA fingerprints can be used to identify individuals, which is of great value in plant breeding. DNA fingerprint databases are essential and important tools for plant molecular research because they provide powerful technical and information support for crop breeding, variety quality control, variety right protection, and molecular marker-assisted breeding. Building a DNA fingerprint database involves the production of large amounts of heterogeneous data for which storage, analysis, and retrieval are time and resource consuming. To process the large amounts of data generated by laboratories and conduct quality control, a database management system is urgently needed to track samples and analyze data. We developed the plant international DNA-fingerprinting system (PIDS) using an open source web server and free software that has automatic collection, storage, and efficient management functions based on merging and comparison algorithms to handle massive microsatellite DNA fingerprint data. PIDS also can perform genetic analyses. This system can match a corresponding capillary electrophoresis image on each primer locus as fingerprint data to upload to the server. PIDS provides free customization and extension of back-end functions to meet the requirements of different laboratories. This system can be a significant tool for plant breeders and can be applied in forensic science for human fingerprint identification, as well as in virus and microorganism research.

Phthalates are associated with several adverse health outcomes, but few studies have evaluated phthalate exposures in Mexican populations, particularly pregnant women. Between 2007 and 2011, 948 pregnant women from Mexico City were recruited as part of the PROGRESS cohort. We quantified 17 metabolites of phthalates and phthalate alternatives in urine samples collected during the second and third trimesters and examined temporal trends of metabolite concentrations, within-person reproducibility, and relations of individual metabolites with sociodemographic, lifestyle, and occupational factors. Concentrations of mono-2-ethyl-5-carboxypentyl terephthalate, a metabolite of the alternative phthalate di-2-ethylhexyl terephthalate, increased monotonically from 2007 to 2010 (31% per year; 95% confidence interval = 23 and 39%). We observed moderate to high correlations among metabolites collected at the same visit, but there was high variability between second and third trimester phthalate metabolite concentrations (intraclass correlation coefficients = 0.17-0.35). In general, higher socioeconomic status was associated with higher phthalate concentrations. Some metabolites were associated with maternal age and education, but no consistent patterns were observed. Women working in the home and those who worked in administration had higher concentrations of several phthalate metabolites relative to students, professionals, and those in customer service. Biomonitoring efforts are warranted to investigate present and future exposure trends and patterns.

Background and Purpose— The relationship between infarct dimensions and neurological progression in patients with acute pontine infarctions remains unclear. This study aimed to investigate the morphometric predictive value of magnetic resonance imaging for early neurological deterioration (END) in acute pontine infarction. Methods— We included all patients admitted to our department having an acute ischemic stroke in the pons. The ventrodorsal length multiplied by thickness was measured as parameters of infarct size. END was defined as an incremental increase in the National Institutes of Health Stroke Scale score by ≥1 point in motor power, or ≥2 points in the total score within the first week after admission. Results— We enrolled 407 patients, and 114 (28.0%) patients were diagnosed with END. Adjusted logistic regression analyses showed the maximum length multiplied by thickness was independently associated with END (odds ratio, 4.580 [95% CI, 2.909–7.210]). The sensitivity, specificity, and area under the curve were 77.2%, 79.2%, and 0.843, respectively, in the receiver operating characteristic curve analysis of maximum length multiplied by thickness for predicting END. Conclusions— These results suggest that the maximum length multiplied by thickness may be a possible predictor in the evaluation of progression with isolated acute pontine infarction. The extent of the pontine infarction along the conduction tract may contribute to deterioration.

Background and Objective: Low serum levels of bilirubin and albumin are associated with multiple autoimmune diseases, but their role in anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is unknown. Methods: Serum bilirubin and albumin levels were evaluated in 60 patients with anti-NMDAR encephalitis, 50 cryptococcal encephalitis, and 145 healthy controls (CTLs). Of the 60 anti-NMDAR encephalitis patients, 30 had a follow-up evaluation at 3 months after admission. Results: Serum bilirubin and albumin levels were both significantly lower in anti-NMDAR encephalitis than in CTLs, and serum bilirubin levels were significantly lower in anti-NMDAR encephalitis than in cryptococcal encephalitis. Serum bilirubin levels were significantly lower in patients with psychiatric symptoms, with severe impairment, and with limited responses to treatment than those without psychiatric symptoms, with mild impairment, and with favorable responses to treatment, respectively. A follow-up evaluation of 30 patients revealed that the modified Rankin Scale scores were significantly decreased after treatment. Serum bilirubin significantly associated with serum albumin, and plasma hemoglobin. Conclusions: Our results revealed for the first time an association between the serum levels of bilirubin in the anti-NMDAR encephalitis. Further studies investigating the role of bilirubin and albumin in anti-NMDAR encephalitis are required.

Background Pregnancy induces numerous cardiovascular and metabolic changes. Alterations in these sensitive processes may precipitate long-term post-delivery health consequences. Studies have reported associations between phthalates and metabolic complications of pregnancy, but no study has investigated metabolic outcomes beyond pregnancy. Objectives To examine associations of exposure to phthalates during pregnancy with post-delivery metabolic health. Design We quantified 15 urinary phthalate biomarker concentrations during the second and third trimesters among 618 pregnant women from Mexico City. Maternal metabolic health biomarkers included fasting blood measures of glycemia [glucose, insulin, Homeostatic Model Assessment of Insulin Resistance [HOMA-IR], % hemoglobin A1c (HbA1c%)] and lipids (total, high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol, triglycerides), at 4–5 and 6–8 years post-delivery. To estimate the influence of the phthalates mixture, we used Bayesian weighted quantile sum regression and Bayesian kernel machine regression; for individual biomarkers, we used linear mixed models. Results As a mixture, higher urinary phthalate biomarker concentrations during pregnancy were associated with post-delivery concentrations of plasma glucose (interquartile range [IQR] difference: 0.13 SD, 95%CrI: 0.05, 0.20), plasma insulin (IQR difference: 0.06 SD, 95%CrI: −0.02, 0.14), HOMA-IR (IQR difference: 0.08 SD, 95% CrI: 0.01, 0.16), and HbA1c% (IQR difference: 0.15 SD, 95%CrI: 0.05, 0.24). Associations were primarily driven by mono-2-ethyl-5-carboxypentyl terephthalate (MECPTP) and the sum of dibutyl phthalate biomarkers (∑DBP). The phthalates mixture was associated with lower HDL (IQR difference: −0.08 SD, 95%CrI: −0.16, −0.01), driven by ∑DBP and monoethyl phthalate (MEP), and higher triglyceride levels (IQR difference: 0.15 SD, 95%CrI: 0.08, 0.22), driven by MECPTP and MEP. The overall mixture was not associated with total cholesterol and LDL. However, ∑DBP and MEP were associated with lower and higher total cholesterol, respectively, and MECPTP and ∑DBP were associated with lower LDL. Conclusions Phthalate exposure during pregnancy is associated with adverse long-term changes in maternal metabolic health. A better understanding of timing of the exact biological changes and their implications on metabolic disease risk is needed.

Background Several studies have suggested that global DNA methylation in circulating white blood cells (WBC) is associated with breast cancer risk. Methods To address conflicting results and concerns that the findings for WBC DNA methylation in some prior studies may reflect disease effects, we evaluated the relationship between global levels of WBC DNA methylation in white blood cells and breast cancer risk in a case-control study nested within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) cohort. A total of 428 invasive breast cancer cases and 419 controls, frequency matched on age at entry (55–59, 60–64, 65–69, ≥70 years), year of entry (on/before September 30, 1997, on/after October 1, 1997) and period of DNA extraction (previously extracted, newly extracted) were included. The ratio of 5-methyl-2’ deoxycytidine [5-mdC] to 2’-deoxyguanine [dG], assuming [dG] = [5-mdC] + [2’-deoxycytidine [dC]] (%5-mdC), was determined by liquid chromatography-electrospray ionization-tandem mass spectrometry, an especially accurate method for assessing total genomic DNA methylation. Results Odds ratio (OR) estimates and 95% confidence intervals (CI) for breast cancer risk adjusted for age at entry, year of entry, and period of DNA extraction, were 1.0 (referent), 0.89 (95% CI, 0.6–1.3), 0.88 (95% CI, 0.6–1.3), and 0.84 (95% CI, 0.6–1.2) for women in the highest compared to lowest quartile levels of %5md-C (p for trend = .39). Effects did not meaningfully vary by time elapsed from WBC collection to diagnosis. Discussion These results do not support the hypothesis that global DNA hypomethylation in WBC DNA is associated with increased breast cancer risk prior to the appearance of clinical disease.

We evaluate the performance of four machine learning methods for modeling and predicting FCC solute diffusion barriers. More than 200 FCC solute diffusion barriers from previous density functional theory (DFT) calculations served as our dataset to train four machine learning methods: linear regression (LR), decision tree (DT), Gaussian kernel ridge regression (GKRR), and artificial neural network (ANN). We separately optimize key physical descriptors favored by each method to model diffusion barriers. We also assess the ability of each method to extrapolate when faced with new hosts with limited known data. GKRR and ANN were found to perform the best, showing 0.15 eV cross-validation errors and predicting impurity diffusion in new hosts to within 0.2 eV when given only 5 data points from the host. We demonstrate the success of a combined DFT + data mining approach towards solving materials science challenges and predict the diffusion barrier of all available impurities across all FCC hosts., Comment: 13 pages, 4 figures

Orbital angular momentum (OAM), an emerging and fascinating degree of freedom, has highlighted an innovation in communication and optical manipulation field. The beams with different OAM state, which manifest as the phase front “twisting” of electromagnetic waves, are mutually orthogonal, which is exactly what a new freedom applied to practical communication eagers for. Herein, we proposed a novel millimeter-wave OAM modulation technique by electrically optical phase controlling. By modulating OAM and phase of optical-millimeter-wave synchronously, the multi-modulation: quadrature orbital angular momentum modulation (QOM) communication system at W band is structured and simulated, allowing a 50 Gbit/s signal transmitting with bit-error rates less than 10−4. Our work might suggest that OAM could be compounded to more complex multi-modulation signal, and revealed a new insight into OAM based high capacity wireless and radio-over-fiber communication.

Network applications require traffic to sequence through multiple types of middleboxes to enhance network functions, e.g., providing security and guaranteeing performance. Sequenced-middlebox policy routing on top of regular layer 2/3 flow routing is challenging to be flexibly managed by network administrators. In addition, various types of middlebox resources concurrently obtained by numerous applications complicate network-resource management. Furthermore, middlebox failures can lead to a lack of security and the malfunction of entire network. In this paper, we formulate a mixed-integer linear programming problem to achieve a network load-balancing objective in the context of sequenced-middlebox policy routing. Our global routing approach manages network resources efficiently by simplifying candidate-path selections, balancing the entire network and using the simulated annealing algorithm. Moreover, in case of middlebox failures, we design a fast recovery mechanism by exploiting the remaining link and middlebox resources locally. To the best of our knowledge, this is the first work to handle failures in sequenced-middlebox scenarios using OpenFlow. Finally, we implement proposed routing approaches on Mininet testbed and evaluate experiments' scalability, assessing the effectiveness of the approaches. Results of the optimization on a test topology include an increase up to 26.4% of the throughput with respect to a sequenced shortest-path routing.

This study aimed to evaluate the functional outcomes and mortality following hip fracture surgery in elderly patients, and to identify the associated risk factors. Between January 2016 and December 2017, 480 consecutive patients were finally included for data analyses. The Harris score and Barthel index were used to evaluate the hip function and ability to perform activities of daily living (ADL). Univariate and multivariate logistics regression analyses were performed to determine the independent risk factors for mortality, poor hip function or poor ability to perform ADL. The mortality rate was 15.6% (75/480). In the survivors, poor outcome developed in 133 (32.8%) patients and poor ADL was in 72 (17.8%) patients. The independent factors that influenced mortality were advanced age (p = 0.033), male gender (0.031), living in rural area (p 7 days (p = 0.020), postoperative drainage use (p = 0.034), WBC > 10 × 109/L (p = 0.005), reduced RBC (p = 0.011), PLT 200 U/L (p = 0.003). The independent factors that influenced the hip function were male gender (p = 0.009), WBC > 10 × 109/L (p 7 days (p = 0.027), postoperative drainage use (p = 0.010), elevated WBC (p = 0.020), lower HGB (p

This paper presents a novel method used for detecting blade imbalance occurring on wind turbines based on multi-variable spectrum imaging and convolutional neural network (CNN). The balance and imbalance conditions were simulated with the aid of commercial wind turbine design software Bladed. Simulation results including generator speed, generator torque and nacelle X acceleration were obtained and processed with Fourier transform to generate the combined spectral images, which were then fed to a CNN model in order to extract and learn the fault features. The effectiveness of the proposed method was validated through comparison with single variable CNN and fully-connected neural network. Results demonstrate that this method is capable of detecting aerodynamic imbalance and mass imbalance with high accuracy and high efficiency.

Single-object tracking, also known as visual tracking, on the drone platform attracts much attention recently with various applications in computer vision, such as filming and surveillance. However, the lack of commonly accepted annotated datasets and standard evaluation platform prevent the developments of algorithms. To address this issue, the Vision Meets Drone Single-Object Tracking (VisDrone-SOT2018) Challenge workshop was organized in conjunction with the 15th European Conference on Computer Vision (ECCV 2018) to track and advance the technologies in such field. Specifically, we collect a dataset, including 132 video sequences divided into three non-overlapping sets, i.e., training (86 sequences with 69, 941 frames), validation (11 sequences with 7,046 frames), and testing (35 sequences with 29, 367 frames) sets. We provide fully annotated bounding boxes of the targets as well as several useful attributes, e.g., occlusion, background clutter, and camera motion. The tracking targets in these sequences include pedestrians, cars, buses, and animals. The dataset is extremely challenging due to various factors, such as occlusion, large scale, pose variation, and fast motion. We present the evaluation protocol of the VisDrone-SOT2018 challenge and the results of a comparison of 22 trackers on the benchmark dataset, which are publicly available on the challenge website: http://www.aiskyeye.com/. We hope this challenge largely boosts the research and development in single object tracking on drone platforms Refereed/Peer-reviewed

Object detection is a hot topic with various applications in computer vision, e.g., image understanding, autonomous driving, and video surveillance. Much of the progresses have been driven by the availability of object detection benchmark datasets, including PASCAL VOC, ImageNet, and MS COCO. However, object detection on the drone platform is still a challenging task, due to various factors such as view point change, occlusion, and scales. To narrow the gap between current object detection performance and the real-world requirements, we organized the Vision Meets Drone (VisDrone2018) Object Detection in Image challenge in conjunction with the 15th European Conference on Computer Vision (ECCV 2018). Specifically, we release a large-scale drone-based dataset, including 8, 599 images (6, 471 for training, 548 for validation, and 1, 580 for testing) with rich annotations, including object bounding boxes, object categories, occlusion, truncation ratios, etc. Featuring a diverse real-world scenarios, the dataset was collected using various drone models, in different scenarios (across 14 different cities spanned over thousands of kilometres), and under various weather and lighting conditions. We mainly focus on ten object categories in object detection, i.e., pedestrian, person, car, van, bus, truck, motor, bicycle, awning-tricycle, and tricycle. Some rarely occurring special vehicles (e.g., machineshop truck, forklift truck, and tanker) are ignored in evaluation. The dataset is extremely challenging due to various factors, including large scale and pose variations, occlusion, and clutter background. We present the evaluation protocol of the VisDrone-DET2018 challenge and the comparison results of 38 detectors on the released dataset, which are publicly available on the challenge website: http://www.aiskyeye.com/. We expect the challenge to largely boost the research and development in object detection in images on drone platforms.

With the ubiquitous usage of digital devices, social networks and industrial sensors, heterogeneous data explosively increase. Metric learning can boost the classification performance via jointly learning a set of distance metrics from heterogeneous data. The metric learning algorithms are affected by the noisy doublets, i.e., the similar and dissimilar sample pairs. It is also a challenging issue to balance commonality and individuality for multi-view metric learning. To address the above issues, in this paper, we propose a novel multi-task group sparse regression metric learning (MT-SRML) for heterogeneous classification. Metric learning is formulated as sparse regression problem. The group sparse regularization on the repression coefficients of the doublets can restrain the effect of the noisy sample pairs jointly for multiple views. Experiments on heterogeneous data show that the proposed MT-SRML outperforms the state-of-the art metric learning algorithms in terms of both accuracy and efficiency.

STUDY QUESTION: Are sperm mitochondrial DNA copy number (mtDNAcn) and deletion rate (mtDNAdel) associated with odds of fertilization and high embryo quality at Days 3 and 5? SUMMARY ANSWER: Higher sperm mtDNAcn and mtDNAdel were associated with lower odds of high quality Day 3 embryos and transfer quality Day 5 embryos, both of which were primarily driven by lowered odds of fertilization. WHAT IS KNOWN ALREADY: Sperm mtDNAcn and mtDNAdel have been previously associated with poor semen parameters and clinical male infertility. One prior study has shown that mtDNAdel is associated with lower fertilization rates. However, it is unknown whether these characteristics are linked with ART outcomes. STUDY DESIGN, SIZE, DURATION: This prospective observational study included 119 sperm samples collected from men undergoing ART in Western Massachusetts. ART outcomes were observed through to Day 5 post-insemination. PARTICIPANTS/MATERIALS, SETTINGS, METHODS: As part of the Sperm Environmental Epigenetics and Development Study (SEEDS), 119 sperm samples were collected from men undergoing ART in Western Massachusetts. Sperm mtDNAcn and mtDNAdel were measured via triplex probe-based qPCR. Fertilization, Day 3 embryo quality and Day 5 embryo quality measures were fitted with mtDNAcn and mtDNAdel using generalized estimating equations. MAIN RESULTS AND THE ROLE OF CHANCE: After adjusting for male age and measurement batches, higher sperm mtDNAcn and mtDNAdel were associated with lower odds of fertilization (P = 0.01 and P < 0.01), high quality Day 3 embryos (P = 0.02 for both) and transfer quality Day 5 embryos (P = 0.01 and P = 0.09). However, the associations of mtDNAcn and mtDNAdel with Day 3 high quality status and Day 5 transfer quality status were attenuated in models restricted to fertilized oocytes. Sperm mtDNAcn and mtDNAdel remained statistically significant in models adjusted for both male age and semen parameters, although models including both mtDNA markers generally favoured mtDNAdel. LIMITATIONS, REASONS FOR CAUTION: Our sample only included oocytes and embryos from 119 couples and thus large diverse cohorts are necessary to confirm the association of sperm mtDNA biomarkers with embryo development. WIDER IMPLICATIONS OF THE FINDINGS: To our knowledge, our study is the first to assess the associations of sperm mtDNAcn and mtDNAdel with fertilization and embryo quality. The biological mechanism(s) underlying these associations are unknown. Multivariable models suggest that sperm mtDNAcn and mtDNAdel provide discrimination independent of age and semen parameters; therefore, future investigation of the utility of sperm mtDNA as a biomarker for ART outcomes is warranted. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by Grant (K22-ES023085) from the National Institute of Environmental Health Sciences. The authors declare no competing interests. TRIAL REGISTRATION NUMBER: N/A.