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IntroductionMind-wandering is a highly dynamic phenomenon involving frequent fluctuations in cognition. However, the dynamics of functional connectivity between brain regions during mind-wandering have not been extensively studied.MethodsWe employed an analytical approach aimed at extracting recurring network states of multilayer networks built using amplitude envelope correlation and imaginary phase-locking value of delta, theta, alpha, beta, or gamma frequency band. These networks were constructed based on electroencephalograph (EEG) data collected while participants engaged in a video-learning task with mind-wandering and focused learning conditions. Recurring multilayer network states were defined via clustering based on overlapping node closeness centrality.ResultsWe observed similar multilayer network states across the five frequency bands. Furthermore, the transition patterns of network states were not entirely random. We also found significant differences in metrics that characterize the dynamics of multilayer network states between mind-wandering and focused learning. Finally, we designed a classification algorithm, based on a hidden Markov model using state sequences as input, that achieved a 0.888 mean area under the receiver operating characteristic curve for within-participant detection of mind-wandering.DiscussionOur approach offers a novel perspective on analyzing the dynamics of EEG data and shows potential application to mind-wandering detection.

Abstract This study explores the efficacy of various EEG complexity measures in detecting mind wandering during video-based learning. Employing a modified probe-caught method, we recorded EEG data from participants engaged in viewing educational videos and subsequently focused on the discrimination between mind wandering (MW) and non-MW states. We systematically investigated various EEG complexity metrics, including metrics that reflect a system’s regularity like multiscale permutation entropy (MPE), and metrics that reflect a system’s dimensionality like detrended fluctuation analysis (DFA). We also compare these features to traditional band power (BP) features. Data augmentation methods and feature selection were applied to optimize detection accuracy. Results show BP features excelled (mean area under the receiver operating characteristic curve (AUC) 0.646) in datasets without eye-movement artifacts, while MPE showed similar performance (mean AUC 0.639) without requiring removal of eye-movement artifacts. Combining all kinds of features improved decoding performance to 0.66 mean AUC. Our findings demonstrate the potential of these complexity metrics in EEG analysis for mind wandering detection, highlighting their practical implications in educational contexts.

Abstract In the study of brain functional connectivity networks, it is assumed that a network is built from a data window in which activity is stationary. However, brain activity is non-stationary over sufficiently large time periods. Addressing the analysis electroencephalograph (EEG) data, we propose a data segmentation method based on functional connectivity network structure. The goal of segmentation is to ensure that within a window of analysis, there is similar network structure. We designed an intuitive and flexible graph distance measure to quantify the difference in network structure between two analysis windows. This measure is modular: a variety of node importance indices can be plugged into it. We use a reference window versus sliding window comparison approach to detect changes, as indicated by outliers in the distribution of graph distance values. Performance of our segmentation method was tested in simulated EEG data and real EEG data from a drone piloting experiment (using correlation or phase-locking value as the functional connectivity strength metric). We compared our method under various node importance measures and against matrix-based dissimilarity metrics that use singular value decomposition on the connectivity matrix. The results show the graph distance approach worked better than matrix-based approaches; graph distance based on partial node centrality was most sensitive to network structural changes, especially when connectivity matrix values change little. The proposed method provides EEG data segmentation tailored for detecting changes in terms of functional connectivity networks. Our study provides a new perspective on EEG segmentation, one that is based on functional connectivity network structure differences.

Abstract Background With the application of chromosome microarray, next-generation sequencing and other highly sensitive genetic techniques in disease diagnosis, the detection of mosaicism has become increasingly prevalent. This study involved a retrospective analysis of SNP array testing on 4512 prenatal diagnosis samples, wherein the characterization of mosaicism was explored and insights were gained into the underlying mechanisms thereof. Results Using SNP array, a total of 44 cases of mosaicism were identified among 4512 prenatal diagnostic cases; resulting in a detection rate of approximately 1.0%. The prevalence of mosaicism was 4.1% for chorionic villus sample, 0.4% for amniotic fluid, and 1.3% for umbilical cord blood. Of these cases, 29 were mosaic aneuploidy and 15 were mosaic segmental duplication/deletion. Three cases of mosaic trisomy 16 and three cases of mosaic trisomy 22 were diagnosed in the CVS samples, while four cases of mosaic trisomy 21 were detected in amniotic fluid and umbilical cord blood samples. The distribution pattern of mosaicism suggested trisomy rescue as the underlying mechanism. Structurally rearranged chromosomes were observed, including three cases with supernumerary marker chromosomes, three cases with dicentric chromosomes, and one case with a ring chromosome. All mosaic segmental duplication/deletion cases were the result of mitotic non-disjunction, with the exception of one case involving mosaic11q segmental duplication. Conclusion Improved utilization of SNP arrays enables the characterization of mosaicism and facilitates the estimation of disease mechanisms and recurrence.

ProposeTo review published Physical Activity (PA) on the Mental Health of Children and Adolescents aged 5 to 18 years during COVID-19 pandemic-induced school closures.MethodsFrom the database creation to April 2022, 10 databases are retrieved, with 4427 records filtered, 14 included in this research. The research takes Agency for Healthcare Research and Quality (AHRQ) evaluation standards.ResultsThe thesis selects 14 studies from 6 countries, involving 400009 children and adolescents. These studies happened during the lockdown of COVID-19 (from December 2019 to April 2021). During the lockdown of COVID-19, schools were closed, which was considered part of a more extensive lockdown. Schools were closed for 1 to 4 weeks. There were 10 high quality studies (71.4%) and 4 medium quality studies (28.6%). 4 studies report that the pandemic reduces the time of PA but increases the time of watching screen and sitting. 10 studies (71.4%) identify that PA is positive for the mental health, because it helps reduce mental symptoms to a certain extent, especially anxiety, depression, and emotional disorders. 5 studies show that PA may not improve the mental health of children and adolescents under 12 during the pandemic. 4 studies indicate that the influence of PA on mental health of children and adolescents is determined by the amount of activity, including the extent, intensity, frequency, and duration, etc.ConclusionsIn this narrative synthesis of reports from the class suspension period, reports that PA has a improve on the mental health of children and adolescents to a certain extent. it is found that PA may be helpful in reducing mental health symptoms of children and adolescents who are influenced by class suspension because of the COVID-19 pandemic. Therefore, stakeholders of the mental health of children and adolescents around the world should recommend PA because it is a practicable and beneficial way for long-term mental support.

Brain machine interfaces (BMI) connect brains directly to the outside world, bypassing natural neural systems and actuators. Neuronal-activity-to-motion transformation algorithms allow applications such as control of prosthetics or computer cursors. These algorithms lie within a spectrum between bio-mimetic control and bio-feedback control. The bio-mimetic approach relies on increasingly complex algorithms to decode neural activity by mimicking the natural neural system and actuator relationship while focusing on machine learning: the supervised fitting of decoder parameters. On the other hand, the bio-feedback approach uses simple algorithms and relies primarily on user learning, which may take some time, but can facilitate control of novel, non-biological appendages. An increasing amount of work has focused on the arguably more successful bio-mimetic approach. However, as chronic recordings have become more accessible and utilization of novel appendages such as computer cursors have become more universal, users can more easily spend time learning in a bio-feedback control paradigm. We believe a simple approach which leverages user learning and few assumptions will provide users with good control ability. To test the feasibility of this idea, we implemented a simple firing-rate-to-motion correspondence rule, assigned groups of neurons to virtual "directional keys" for control of a 2D cursor. Though not strictly required, to facilitate initial control, we selected neurons with similar preferred directions for each group. The groups of neurons were kept the same across multiple recording sessions to allow learning. Two Rhesus monkeys used this BMI to perform a center-out cursor movement task. After about a week of training, monkeys performed the task better and neuronal signal patterns changed on a group basis, indicating learning. While our experiments did not compare this bio-feedback BMI to bio-mimetic BMIs, the results demonstrate the feasibility of our control paradigm and paves the way for further research in multi-dimensional bio-feedback BMIs.

Dry eye disease (DED) is a common multi-factorial disease that is characterized by tear film instability. Diquafosol tetrasodium (DQS), an ophthalmic solution, has been shown to be beneficial in the treatment of DED. The goal of this study was to provide an update on the safety and efficacy of topical 3% DQS in treating DED patients. A thorough search for all the published randomized controlled trials (RCTs) up to March 31, 2022 in CENTRAL, PubMed, Scopus, and Google Scholar databases was performed. Data were reported as standardized mean difference (SMD) with 95% confidence interval (CI). Modified Jadad scale was used for sensitivity analysis. Funnel plot and Egger's regression test assessed the publication bias. Fourteen RCTs evaluating the safety and efficacy of topical 3% DQS treatment in DED patients were included. Eight included RCTs reported data on the DED after cataract surgery. Overall findings suggest that 3% DQS treatment in DED patients was associated with significantly better improvement at 4 weeks in tear breakup time, Schirmer test, fluorescein staining scores, and Rose Bengal staining score as compared to patients treated with others eye drops including artificial tears or 01% sodium hyaluronate. However, no significant difference in ocular surface disease index was observed. Our findings suggest that 3% DQS treatment is safer and had a superior efficacy compared to artificial tears or sodium hyaluronate for treating DED in general and DED after cataract surgery.

The aim of this study is to explore the potential of technology for detecting mind wandering, particularly during video-based distance learning, with the ultimate benefit of improving learning outcomes. To overcome the challenges of previous mind wandering research in ecological validity, sample balance, and dataset size, this study utilized practical electroencephalography (EEG) recording hardware and designed a paradigm consisting of viewing short-duration video lectures under a focused learning condition and a future planning condition. Participants estimated statistics of their attentional state at the end of each video, and we combined this rating scale feedback with self-caught key press responses during video watching to obtain binary labels for classifier training. EEG was recorded using an 8-channel system, and spatial covariance features processed by Riemannian geometry were employed. The results demonstrate that a radial basis function kernel support vector machine classifier, using Riemannian-processed covariance features from delta, theta, alpha, and beta bands, can detect mind wandering with a mean area under the receiver operating characteristic curve (AUC) of 0.876 for within-participant classification and AUC of 0.703 for cross-lecture classification. Furthermore, our results suggest that a short duration of training data is sufficient to train a classifier for online decoding, as cross-lecture classification remained at an average AUC of 0.689 when using 70% of the training set (about 9 min). The findings highlight the potential for practical EEG hardware in detecting mind wandering with high accuracy, which has potential application to improving learning outcomes during video-based distance learning.

Abstract Background Koalas are infected with the koala retrovirus (KoRV) that exists as exogenous or endogenous viruses. KoRV is genetically diverse with co-infection with up to ten envelope subtypes (A-J) possible; KoRV-A is the prototype endogenous form. KoRV-B, first found in a small number of koalas with an increased leukemia prevalence at one US zoo, has been associated with other cancers and increased chlamydial disease. To better understand the molecular epidemiology of KoRV variants and the effect of increased viral loads (VLs) on transmissibility and pathogenicity we developed subtype-specific quantitative PCR (qPCR) assays and tested blood and tissue samples from koalas at US zoos (n = 78), two Australian zoos (n = 27) and wild-caught (n = 21) in Australia. We analyzed PCR results with available clinical, demographic, and pedigree data. Results All koalas were KoRV-A-infected. A small number of koalas (10.3%) at one US zoo were also infected with non-A subtypes, while a higher non-A subtype prevalence (59.3%) was found in koalas at Australian zoos. Wild koalas from one location were only infected with KoRV-A. We observed a significant association of infection and plasma VLs of non-A subtypes in koalas that died of leukemia/lymphoma and other neoplasias and report cancer diagnoses in KoRV-A-positive animals. Infection and VLs of non-A subtypes was not associated with age or sex. Transmission of non-A subtypes occurred from dam-to-offspring and likely following adult-to-adult contact, but associations with contact type were not evaluated. Brief antiretroviral treatment of one leukemic koala infected with high plasma levels of KoRV-A, -B, and -F did not affect VL or disease progression. Conclusions Our results show a significant association of non-A KoRV infection and plasma VLs with leukemia and other cancers. Although we confirm dam-to-offspring transmission of these variants, we also show other routes are possible. Our validated qPCR assays will be useful to further understand KoRV epidemiology and its zoonotic transmission potential for humans exposed to koalas because KoRV can infect human cells.

Abstract Background The potential correlations between chromosomal abnormalities and craniofacial malformations (CFMs) remain a challenge in prenatal diagnosis. This study aimed to evaluate 118 fetuses with CFMs by applying chromosomal microarray analysis (CMA) and G-banded chromosome analysis. Results Of the 118 cases in this study, 39.8% were isolated CFMs (47/118) whereas 60.2% were non-isolated CFMs (71/118). The detection rate of chromosomal abnormalities in non-isolated CFM fetuses was significantly higher than that in isolated CFM fetuses (26/71 vs. 7/47, p = 0.01). Compared to the 16 fetuses (16/104; 15.4%) with pathogenic chromosomal abnormalities detected by karyotype analysis, CMA identified a total of 33 fetuses (33/118; 28.0%) with clinically significant findings. These 33 fetuses included cases with aneuploidy abnormalities (14/118; 11.9%), microdeletion/microduplication syndromes (9/118; 7.6%), and other pathogenic copy number variations (CNVs) only (10/118; 8.5%).We further explored the CNV/phenotype correlation and found a series of clear or suspected dosage-sensitive CFM genes including TBX1, MAPK1, PCYT1A, DLG1, LHX1, SHH, SF3B4, FOXC1, ZIC2, CREBBP, SNRPB, and CSNK2A1. Conclusion These findings enrich our understanding of the potential causative CNVs and genes in CFMs. Identification of the genetic basis of CFMs contributes to our understanding of their pathogenesis and allows detailed genetic counselling.

Abstract Background Defining the phenotype-genotype correlation of small supernumerary marker chromosomes (sSMCs) remains a challenge in prenatal diagnosis. We karyotyped 20,481 amniotic fluid samples from pregnant women and explored the molecular characteristics of sSMCs using a single nucleotide polymorphism (SNP) array. Results Out of the 20,481 samples, 15 abnormal karyotypes with sSMC were detected (frequency: 0.073%) and the chromosomal origin was successfully identified by SNP array in 14 of them. The origin of sSMCs were mainly acrocentric-derived chromosomes and the Y chromosome. Two cases of sSMC combined with uniparental disomy (UPD) were detected, UPD(1) and UPD(22). More than half of the cases of sSMC involved mosaicism (8/15) and pathogenicity (9/15) in prenatal diagnosis. A higher prevalence of mosaicism for non-acrocentric chromosomes than acrocentric chromosomes was also revealed. One sSMC derived from chromosome 3 with a neocentromere revealed a 24.99-Mb pathogenic gain of the 3q26.31q29 region on the SNP array, which presented as an abnormal ultrasound indicating nasal bone hypoplasia. Conclusion The clinical phenotypes of sSMCs are variable and so further genetic testing and parental karyotype analysis are needed to confirm the characteristics of sSMCs. The SNP array used here allows a detailed characterisation of the sSMC and establishes a stronger genotype-phenotype correlation, thus allowing detailed genetic counselling for prenatal diagnosis.

Task matching in crowdsourcing is designed to provide convenient task information retrieval and has been extensively explored. In general, the task matching process is required to be reliable and to meet privacy requirements. However, most existing privacy-preserving task matching solutions for crowdsourcing focus on privacy issues but ignore the reliability of the process. In this paper, we propose a blockchain-based task matching scheme for crowdsourcing with a secure and reliable matching. Instead of utilizing a centralized cloud server, we employ smart contracts, an emerging blockchain technology, to provide reliable and transparent matching. In this way, data confidentiality and identity anonymity are achieved effectively and efficiently. The extensive privacy analysis and performance evaluation show that our solution is secure and feasible.

This paper proposes a high-capacity scheme for reversible data hiding (RDH) in encrypted images. The proposed scheme is based on a new preprocessing method by bit plane partition. Specifically, the values in the less significant bit planes are reversibly hidden into the other bit planes. Consequently, the room in the less significant bit planes can be vacated to generate a preprocessed image, from which the original image can be recovered by extracting the hidden bit values and writing them back. After encrypting the preprocessed image with a stream cipher, the vacated room can be used to accommodate extra data, which can be retrieved without image decryption. In addition, the embedding capacity can be further increased by adopting an efficient most significant bit (MSB) prediction method before image encryption. Compared with the state-of-the-art RDH schemes for encrypted images, the experimental results show that higher embedding capacity can be achieved with our proposed one. The numerical results are provided to show the performances of the proposed scheme in different cases of bit-plane partition and MSB prediction.

Recently, reversible image data hiding with contrast enhancement (CE) has been proposed so that a contrast-changed image can be converted to its original version when needed. Several reversible image CE methods have been proposed by adopting the technique of reversible data hiding (RDH) to embed the recovery information into the contrast-enhanced images. In these methods, the 1D histogram is calculated and then modified to achieve the effects of histogram equalization (HE). Meanwhile, the 2D histogram has been used in image CE and demonstrated remarkable advantages in improving the image quality. In this paper, the method based on the 2D histogram modification is proposed to perform image CE and RDH simultaneously. In particular, a preprocessing strategy is developed to merge the adjacent bins in 2D histogram to prevent the overflow and underflow of the pixel values due to HE. The changes made in preprocessing is minimized by choosing the lowest bins for merging, while the CE effects can be achieved by expanding the highest bins for data embedding. The experimental results on two sets of test images have clearly demonstrated the efficacy of the proposed method for reversible image CE. The evaluation results are given to show its superior performances in CE and image quality preservation by comparing with the state-of-the-art approaches.

In this paper, we propose a novel secure role re-encryption system (SRRS), which is based on convergent encryption and the role re-encryption algorithm to prevent the privacy data leakage in cloud and it also achieves the authorized deduplication and satisfies the dynamic privilege updating and revoking. Meanwhile, our system supports ownership checking and achieves the proof of ownership for the authorized users efficiently. Specifically, we introduce a management center to handle with the authorized request and establish a role authorized tree (RAT) mapping the relationship of the roles and keys. With the convergent encryption algorithm and the role re-encryption technique, it can be guaranteed that only the authorized user who has the corresponding role re-encryption key can access the specific file without any data leakage. Through role re-encryption key updating and revoking, our system achieves the dynamic updating of the authorized user's privilege. Furthermore, we exploit the dynamic count filters (DCF) to implement the data updating and improve the retrieval of ownership verifying effectively. We conduct the security analysis and the simulation experiment to demonstrate the security and efficiency of our proposed system.

Mobile crowdsensing (MCS) is an emerging data collection paradigm that exploits the potential of individual mobile devices to acquire mass data in a cost-effective manner. One of the important challenges in MCS application is to resist malicious users who provide false data to disturb the system. In the existing work, the reputation management scheme is an effective way to overcome the challenge. However, most reputation management schemes rely on a semi-honest server and process data in the plaintext domain without considering server security and user privacy. In this paper, we integrate the blockchain and edge computing in the MCS scenario to construct a credible and efficient blockchain-based MCS system, called BC-MCS. To resist malicious users, we present a privacy-preserving reputation management scheme based on the proposed system. Furthermore, we design a delegation protocol to solve the inherent problem of user dynamics in the MCS. The prototype system implemented on the Hyperledger Sawtooth and Android client demonstrates that our scheme can achieve higher utility and security levels in handling malicious users compared with the previous centralized reputation management schemes.

Abstract Background Congenital contractural arachnodactyly (CCA) is a rare autosomal dominant condition caused by mutations in the fibrillin 2 gene (FBN2). The primary clinical symptoms of CCA include multiple flexion contractures, arachnodactyly, dolichostenomelia, scoliosis, abnormal pinnae, muscular hypoplasia, and crumpled ears. Methods We used whole‐exome sequencing technology to examine an arthrogryposis multiplex congenita and used Sanger sequencing technology to genetically confirm its family. Results FBN2 c.3344A>T(p.D1115V) was identified in this family with CCA in a pedigree. Prenatal diagnosis and counseling were carried out simultaneously to avoid the birth of the sick fetus. Conclusion The study is on FBN2 variant in CCA, which potentially having implications for genetic counseling and clinical management, our study may provide new insights into the cause and diagnosis of CCA.

Intellectual disability (ID) is a highly inherited neurodevelopmental disorder. A human induced pluripotent stem cell (iPSC) line was generated from peripheral blood mononuclear cells (PBMCs) in a patient with intellectual disability and carrying a haploinsufficiency for PLPPR4. This iPSC line offers a useful resource to investigate the pathogenesis and molecular mechanisms involved in PLPPR4-related ID.

Rapid 3D radiation field evaluation is the key point of occupational dose optimization for design and operation of nuclear power plant. Based on the requirement analysis from designers and operators of nuclear power plant, three key technical issues are identified and solved through the development of the RPOS system, which are rapid calculation of 3D radiation field, reconstruction of the calculated 3D radiation field based on measured data, and occupational dose optimization based on 3D radiation field. Operational measurements of dose rate from in-service nuclear power plants are used to test the RPOS system, which shows that accurate 3D radiation field can be rapidly generated by the RPOS system and effectively used on the occupational dose optimization for on-site workers. The applications of the established rapid 3D radiation field evaluation technique on HPR1000 unit design provide evidence on its feasibility in a large scale, the improvement of radiation protection design efficiency and the enhancement of ALARA assessment and justification for nuclear power plants.

Wireless sensor networks (WSNs) are increasingly gaining impact on our daily lives. They are finding a wide range of applications in various domains, such as health-care, environmental monitoring, and so on. In future, WSNs are expected to be integrated into the Internet of Things (IoT). The integrity of the sensed data is of primary importance in WSN and IoT applications. However, WSN platforms always have very limited resources in terms of battery power, computing, and memory. Therefore, it is a key challenge to design an energy-friendly, lightweight digital signature algorithm for WSN platforms. In this paper, we present precomputation methods for unbalanced oil-vinegar (UOV) signature scheme by exploiting the energy-harvesting capabilities of WSN to enhance the performance of UOV signature. In addition, we combine a circulant method with precomputation in the UOV signature to further reduce the energy cost. Meanwhile, the circulant method reduces the size and the memory overhead of the precomputation tuple. This increases the availability of precomputation and greatly enhances the availability of the overflow energy. By integrating the above-mentioned optimization methods, the cost of UOV signature in a WSN node can be reduced by 93%. This greatly enhances the performance of UOV signature, making it feasible for the practical deployment on resource-constrained wireless sensor platforms.

A publicly verifiable secret sharing (PVSS) scheme enjoys the public verification and the lower cost of communication than VSS scheme. However, the existing PVSS schemes cannot be applied in the scenarios of the devices with low computation ability and do not share the multiple secrets among all participants efficiently. In this paper, an efficient publicly verifiable multi-secret sharing scheme with outsourcing secret reconstruction is proposed. Each participant only spends a small amount of computational cost to recover multiple secrets because of the expensive burden of computation and verifiability is outsourced to the cloud service provider (CSP). Moreover, the CSP knows no information of the secrets, and the participants have the abilities to verify the returned result. We also prove that our scheme is secure under the hardness assumption of the discrete logarithm problem and the modified generalized bilinear inversion problem.

Attribute-based encryption, especially for ciphertext-policy attribute-based encryption, can fulfill the functionality of fine-grained access control in cloud storage systems. Since users' attributes may be issued by multiple attribute authorities, multi-authority ciphertext-policy attribute-based encryption is an emerging cryptographic primitive for enforcing attribute-based access control on outsourced data. However, most of the existing multi-authority attribute-based systems are either insecure in attribute-level revocation or lack of efficiency in communication overhead and computation cost. In this paper, we propose an attribute-based access control scheme with two-factor protection for multi-authority cloud storage systems. In our proposed scheme, any user can recover the outsourced data if and only if this user holds sufficient attribute secret keys with respect to the access policy and authorization key in regard to the outsourced data. In addition, the proposed scheme enjoys the properties of constant-size ciphertext and small computation cost. Besides supporting the attribute-level revocation, our proposed scheme allows data owner to carry out the user-level revocation. The security analysis, performance comparisons, and experimental results indicate that our proposed scheme is not only secure but also practical.

Rainbow is one of the most important signature schemes in multivariate public key cryptography. It enjoys a strong security guarantee and is a promising signature scheme in Post-Quantum Cryptography. However, it suffers from large key size. In this paper, we propose Circulant Rainbow with shorter private key and higher signing efficiency. In Circulant Rainbow, we introduce rotating relations into parts of Rainbow private key to speed up the signing procedure and reduce the private key size. We carefully choose security parameters so that our Circulant Rainbow is secure against all known attacks. In our experiment, Circulant Rainbow is about three times faster than original Rainbow and it can reduce the private key size by about 45%. We also make a comparison of Circulant Rainbow with some traditional signature schemes, the results show that Circulant Rainbow is a promising candidate in Post-Quantum Cryptography.

Objective: This study aimed to determine the rates of different fetal chromosomal abnormalities among women of advanced maternal age in China and to discuss the possible misdiagnosis risks of newer molecular techniques, for selection of appropriate prenatal screening and diagnostic technologies. Materials and Methods: Second trimester amniocentesis and fetal karyotype results of 46,258 women were retrospectively reviewed. All women were ≥ 35 years old with singleton pregnancies. The rates of clinically significant chromosomal abnormalities (CSCAs), incidence of chromosomal abnormalities, and correlations with age were determined. Results: From 2001 to 2010, the proportion of women of advanced maternal age undergoing prenatal diagnosis increased from 20% to 46%. The mean age was 37.4 years (range, 35–46 years). A total of 708 cases of CSCAs, with a rate of 1.53% were found. Trisomy 21 was the most common single chromosome abnormality and accounted for 55.9% of all CSCAs with an incidence of 0.86%. Trisomy 13, trisomy 18, and trisomy 21, the most common chromosome autosomal aneuploidies, accounted for 73.6% of all CSCAs, with a rate of 1.13%. As a group, the most common chromosomal aneuploidies (13/18/21/X/Y) accounted for 93.9% of all abnormalities, with a rate of 1.44%. The incidence of trisomy 21, trisomy 13/18/21 as a group, and 13/18/21/X/Y as a group was significantly greater in women aged 39 years and older (p

Simian foamy viruses (SFVs) are retroviruses present in nearly all nonhuman primates (NHPs), including Old World primates (OWP) and New World primates (NWP). While all confirmed human infections with SFV are from zoonotic transmissions originating from OWP, little is known about the zoonotic transmission potential of NWP SFV. We conducted a longitudinal, prospective study of 56 workers occupationally exposed to NWP in Brazil. Plasma from these workers was tested using Western blot (WB) assays containing NWP SFV antigens. Genomic DNA from blood and buccal swabs was analyzed for the presence of proviral SFV sequences by three nested PCR tests and a new quantitative PCR assay. Exposure histories were obtained and analyzed for associations with possible SFV infection. Ten persons (18%) tested seropositive and two persons were seroindeterminate (3.6%) for NWP SFV. Six persons had seroreactivity over 2-3 years suggestive of persistent infection. All SFV NWP WB-positive workers reported at least one incident involving NWP, including six reporting NWP bites. NWP SFV viral DNA was not detected in the blood or buccal swabs from all 12 NWP SFV seroreactive workers. We also found evidence of SFV seroreversion in three workers suggestive of possible clearance of infection. Our findings suggest that NWP SFV can be transmitted to occupationally-exposed humans and can elicit specific humoral immune responses but infection remains well-controlled resulting in latent infection and may occasionally clear.

Zoonotic transmission of simian retroviruses in West-Central Africa occurring in primate hunters has resulted in pandemic spread of human immunodeficiency viruses (HIVs) and human T-lymphotropic viruses (HTLVs). While simian foamy virus (SFV) and simian T- lymphotropic virus (STLV)-like infection were reported in healthy persons exposed to nonhuman primates (NHPs) in West-Central Africa, less is known about the distribution of these viruses in Western Africa and in hospitalized populations. We serologically screened for SFV and STLV infection using 1,529 specimens collected between 1985 and 1997 from Côte d'Ivoire patients with high HIV prevalence. PCR amplification and analysis of SFV, STLV, and HIV/SIV sequences from PBMCs was used to investigate possible simian origin of infection. We confirmed SFV antibodies in three persons (0.2%), two of whom were HIV-1-infected. SFV polymerase (pol) and LTR sequences were detected in PBMC DNA available for one HIV-infected person. Phylogenetic comparisons with new SFV sequences from African guenons showed infection likely originated from a Chlorocebus sabaeus monkey endemic to Côte d'Ivoire. 4.6% of persons were HTLV seropositive and PCR testing of PBMCs from 15 HTLV seroreactive persons identified nine with HTLV-1 and one with HTLV-2 LTR sequences. Phylogenetic analysis showed that two persons had STLV-1-like infections, seven were HTLV-1, and one was an HTLV-2 infection. 310/858 (53%), 8/858 (0.93%), and 18/858 (2.1%) were HIV-1, HIV-2, and HIV-positive but undifferentiated by serology, respectively. No SIV sequences were found in persons with HIV-2 antibodies (n = 1) or with undifferentiated HIV results (n = 7). We document SFV, STLV-1-like, and dual SFV/HIV infection in Côte d'Ivoire expanding the geographic range for zoonotic simian retrovirus transmission to West Africa. These findings highlight the need to define the public health consequences of these infections. Studying dual HIV-1/SFV infections in immunocompromised populations may provide a new opportunity to better understand SFV pathogenicity and transmissibility in humans.

To understand the cross-talk and specificity of the early responses of plants to salt and drought, we performed physiological and proteome analyses of Brassica napus seedlings pretreated with 245 mM NaCl or 25% polyethylene glycol (PEG) 6000 under identical osmotic pressure (-1.0 MPa). Significant decreases in water content and photosynthetic rate and excessive accumulation of compatible osmolytes and oxidative damage were observed in response to both stresses. Unexpectedly, the drought response was more severe than the salt response. We further identified 45 common differentially expressed proteins (DEPs), 143 salt-specific DEPs and 160 drought-specific DEPs by isobaric tags for relative and absolute quantitation (iTRAQ) analysis. The proteome quantitative data were then confirmed by multiple reaction monitoring (MRM). The differences in the proteomic profiles between drought-treated and salt-treated seedlings exceeded the similarities in the early stress responses. Signal perception and transduction, transport and membrane trafficking, and photosynthesis-related proteins were enriched as part of the molecular cross-talk and specificity mechanism in the early responses to the two abiotic stresses. The Ca2+ signaling, G protein-related signaling, 14-3-3 signaling pathway and phosphorylation cascades were the common signal transduction pathways shared by both salt and drought stress responses; however, the proteins with executive functions varied. These results indicate functional specialization of family proteins in response to different stresses, i.e., CDPK21, TPR, and CTR1 specific to phosphorylation cascades under early salt stress, whereas STN7 and BSL were specific to phosphorylation cascades under early drought stress. Only the calcium-binding EF-hand family protein and ZKT were clearly identified as signaling proteins that acted as cross-talk nodes for salt and drought signaling pathways. Our study provides new clues and insights for developing strategies to improve the tolerance of crops to complex, multiple environmental stresses.

The association of xenotropic murine leukemia virus (MLV)-related virus (XMRV) in prostate cancer and chronic fatigue syndrome reported in previous studies remains controversial as these results have been questioned by recent data. Nonetheless, concerns have been raised regarding contamination of human vaccines as a possible source of introduction of XMRV and MLV into human populations. To address this possibility, we tested eight live attenuated human vaccines using generic PCR for XMRV and MLV sequences. Viral metagenomics using deep sequencing was also done to identify the possibility of other adventitious agents.All eight live attenuated vaccines, including Japanese encephalitis virus (JEV) (SA-14-14-2), varicella (Varivax), measles, mumps, and rubella (MMR-II), measles (Attenuvax), rubella (Meruvax-II), rotavirus (Rotateq and Rotarix), and yellow fever virus were negative for XMRV and highly related MLV sequences. However, residual hamster DNA, but not RNA, containing novel endogenous gammaretrovirus sequences was detected in the JEV vaccine using PCR. Metagenomics analysis did not detect any adventitious viral sequences of public health concern. Intracisternal A particle sequences closest to those present in Syrian hamsters and not mice were also detected in the JEV SA-14-14-2 vaccine. Combined, these results are consistent with the production of the JEV vaccine in Syrian hamster cells.We found no evidence of XMRV and MLV in eight live attenuated human vaccines further supporting the safety of these vaccines. Our findings suggest that vaccines are an unlikely source of XMRV and MLV exposure in humans and are consistent with the mounting evidence on the absence of these viruses in humans.

The gammaretroviruses xenotropic murine leukemia virus (MLV)-related virus (XMRV) and MLV have been reported to be more prevalent in plasma and peripheral blood mononuclear cells of chronic fatigue syndrome (CFS) patients than in healthy controls. Here, we report the complex analysis of whole blood and plasma samples from 58 CFS patients and 57 controls from Canada for the presence of XMRV/MLV nucleic acids, infectious virus, and XMRV/MLV-specific antibodies. Multiple techniques were employed, including nested and qRT-PCR, cell culture, and immunoblotting. We found no evidence of XMRV or MLV in humans and conclude that CFS is not associated with these gammaretroviruses.

BACKGROUND: The association of the xenotropic murine leukemia virus-related virus (XMRV) with prostate cancer continues to receive heightened attention as studies report discrepant XMRV prevalences ranging from zero up to 23%. It is unclear if differences in the diagnostic testing, disease severity, geography, or other factors account for the discordant results. We report here the prevalence of XMRV in a population with well-defined prostate cancers and RNase L polymorphism. We used broadly reactive PCR and Western blot (WB) assays to detect infection with XMRV and related murine leukemia viruses (MLV). METHODOLOGY/PRINCIPAL FINDINGS: We studied specimens from 162 US patients diagnosed with prostate cancer with a intermediate to advanced stage (Gleason Scores of 5-10; moderate (46%) poorly differentiated tumors (54%)). Prostate tissue DNA was tested by PCR assays that detect XMRV and MLV variants. To exclude contamination with mouse DNA, we also designed and used a mouse-specific DNA PCR test. Detailed phylogenetic analysis was used to infer evolutionary relationships. RNase L typing showed that 9.3% were homozygous (QQ) for the R462Q RNase L mutation, while 45.6% and 45.1% were homozygous or heterozygous, respectively. Serologic testing was performed by a WB test. Three of 162 (1.9%) prostate tissue DNA were PCR-positive for XMRV and had undetectable mouse DNA. None was homozygous for the QQ mutation. Plasma from all three persons was negative for viral RNA by RT-PCR. All 162 patients were WB negative. Phylogenetic analysis inferred a distinct XMRV. CONCLUSIONS AND THEIR SIGNIFICANCE: We found a very low prevalence of XMRV in prostate cancer patients. Infection was confirmed by phylogenetic analysis and absence of contaminating mouse DNA. The finding of undetectable antibodies and viremia in all three patients may reflect latent infection. Our results do not support an association of XMRV or MLV variants with prostate cancer.

Background: Modic changes (MCs), vertebral end plate and bone marrow damage observed by magnetic resonance imaging, are an independent risk factor for low back pain. The compositions of and interaction between microbiota and metabolites in the lumbar cartilaginous end plates (LCEPs) of patients with MCs have not been identified. Methods: Patients with lumbar disc degeneration who were undergoing lumbar spinal fusion surgery were recruited between April 2020 and April 2021. LCEPs were collected for 16S rRNA sequencing and liquid chromatography-mass spectrometry (LC/MS)-based targeted metabolomic profiling. Of the 54 patients recruited, 24 had no MCs and 30 had changes classified as Modic type 2 or 3. The primary goal was to identify specific genera of microbiota associated with MCs, and secondary goals included investigating differences in metabolites between patients with and without MCs and exploring the correlation between these metabolites and microorganisms. Results: Investigation of the microbiota community structure revealed that both alpha diversity and beta diversity were significantly different between patients with and without MCs, and the abundances of 26 genera were significantly different between these 2 groups. Metabolomic analysis revealed that 26 metabolites were significantly different between the 2 groups. The unsaturated fatty acid pathway was found to be the main pathway related to MCs. Multiomic correlation analysis suggested that Caulobacteraceae (unclassified) and Mycobacterium, Clostridium, Blautia, and Bifidobacterium at the genus level were linked to dysregulation of fatty acid metabolism, contributing to the pathogenesis of MCs. Conclusions: Our study represents a foundational effort to examine the landscape of the microbiota and metabolites in patients with MCs, informing future studies on the pathogenesis of and targeted therapy for MCs. [ABSTRACT FROM AUTHOR]

Herein, we report a novel rapidly formed hydrogel membrane that is crosslinked by polyetherimide and polyethyleneimine within 10 s. The polyetherimide as the backbone provided rigidity to the hydrogel membrane, and the polyethyleneimine as the crosslinker provided hydrophilicity. The mechanical strength and electrical performance of the hydrogel membranes can be finely regulated by adjusting the ratio of these two polymers. The hydrogel membranes exhibited high proton conductivity (78-124 mS cm-1) from 20 8C to 160 8C (RH = 100%). [ABSTRACT FROM AUTHOR]