Unsupervised underwater imaging based on polarization and binocular depth estimation.

Scattering caused by suspended particles in the water severely reduces the radiance of the scene. This paper proposes an unsupervised underwater restoration method based on binocular estimation and polarization. Based on the correlation between the underwater transmission process and depth, this method combines the depth information and polarization information in the scene, uses the neural network to perform global optimization and the depth information is recalculated and updated in the network during the optimization process, and reduces the error generated by using the polarization image to calculate parameters, so that detailed parts of the image are restored. Furthermore, the method reduces the requirement for rigorous pairing of data compared to previous approaches for underwater imaging using neural networks. Experimental results show that this method can effectively reduce the noise in the original image and effectively preserve the detailed information in the scene.

Principal and independent genomic components of brain structure and function.

The highly polygenic and pleiotropic nature of behavioural traits, psychiatric disorders and structural and functional brain phenotypes complicate mechanistic interpretation of related genome-wide association study (GWAS) signals, thereby obscuring underlying causal biological processes. We propose genomic principal and independent component analysis (PCA, ICA) to decompose a large set of univariate GWAS statistics of multimodal brain traits into more interpretable latent genomic components. Here we introduce and evaluate this novel methods various analytic parameters and reproducibility across independent samples. Two UK Biobank GWAS summary statistic releases of 2240 imaging-derived phenotypes (IDPs) were retrieved. Genome-wide beta-values and their corresponding standard-error scaled z-values were decomposed using genomic PCA/ICA. We evaluated variance explained at multiple dimensions up to 200. We tested the inter-sample reproducibility of output of dimensions 5, 10, 25 and 50. Reproducibility statistics of the respective univariate GWAS served as benchmarks. Reproducibility of 10-dimensional PCs and ICs showed the best trade-off between model complexity and robustness and variance explained (PCs: |rz - max| = 0.33, |rraw - max| = 0.30; ICs: |rz - max| = 0.23, |rraw - max| = 0.19). Genomic PC and IC reproducibility improved substantially relative to mean univariate GWAS reproducibility up to dimension 10. Genomic components clustered along neuroimaging modalities. Our results indicate that genomic PCA and ICA decompose genetic effects on IDPs from GWAS statistics with high reproducibility by taking advantage of the inherent pleiotropic patterns. These findings encourage further applications of genomic PCA and ICA as fully data-driven methods to effectively reduce the dimensionality, enhance the signal to noise ratio and improve interpretability of high-dimensional multitrait genome-wide analyses.

Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives.

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

Super-resolution non-line-of-sight imaging based on temporal encoding.

Non-line-of-sight (NLOS) imaging techniques have the ability to reconstruct objects beyond line-of-sight view, which would be useful in a variety of applications. In transient NLOS techniques, a fundamental problem is that the time resolution of imaging depends on the single-photon timing resolution (SPTR) of a detector. In this paper, a temporal super-resolution method named temporal encoding non-line-of-sight (TE-NLOS) is proposed. Specifically, by exploiting the spatial-temporal correlation among transient images, high-resolution transient images can be reconstructed through modulator encoding. We have demonstrated that the proposed method is capable of reconstructing transient images with a time resolution of 20 picoseconds from a detector with a limited SPTR of approximately nanoseconds. In systems with low time jitter, this method exhibits superior accuracy in reconstructing objects compared to direct detection, and it also demonstrates robustness against miscoding. Utilizing high-frequency modulation, our framework can reconstruct accurate objects with coarse-SPTR detectors, which provides an enlightening reference for solving the problem of hardware defects.

Prognostic significance of PD-L1 expression in pancreatic cancer: evidence from an updated meta-analysis.

Recent studies revealed that programmed cell death ligand 1 (PD-L1) expression was associated with unfavorable prognosis in various solid tumors, but its clinical relevance for pancreatic cancer has not yet been well established. This meta-analysis summarizes the potential prognostic value of PD-L1 in pancreatic cancer. A quantitative meta-analysis was performed by a systematic search of databases including PubMed, EMBASE, Web of Science, Cochrane library, Scopus and Ovid for eligible studies on the prognostic significance of PD-L1 in pancreatic cancer patients. Pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) were calculated to evaluate the strength of the link between PD-L1 expression and clinical prognosis of patients. Seventeen eligible studies with 2669 patients were included in our study. A significant association was observed between PD-L1 abundance and poor overall survival (OS) of patients with pancreatic cancers, with a pooled hazard ratio (HR) of 1.902, 95% CI: 1.657-2.184. Sensitivity analysis confirmed the reliability of our results. Subgroup analysis shows that differences in regions and detection methods of PD-L1 did not change the overall predictive value of PD-L1 for poor prognosis in pancreatic cancer patients. This meta-analysis indicated that the expression of PD-L1 is associated with a worse OS in pancreatic cancer patients. Additionally, PD-L1 may act as a potential parameter for predicting poor prognosis and thus providing a promising target for anticancer therapy in pancreatic cancer.

Helicobacter pylori infection increases the risk of nonalcoholic fatty liver disease: Possible relationship from an updated meta-analysis.

BACKGROUND: The relationship between Helicobacter pylori (H pylori) infection and nonalcoholic fatty liver disease (NAFLD) has long been debated. Although it has been investigated in many observational studies, the results remain controversial. Therefore, we performed an updated meta-analysis to assess the association between H pylori infection and risk of NAFLD by collecting relevant articles. METHODS: Literature collections were conducted by searching PubMed, EMBASE, Web of Science and Cochrane Library databases. Pooled odds ratios with corresponding 95% confidence intervals were calculated to estimate the strength of the link between H pylori infection and NAFLD using Stata 12.0 software. RESULTS: 28 studies with 68,047 cases of NAFLD patients and 134,866 controls were finally included in the meta-analysis. Overall, The results suggested a 27.5% increased risk of developing NAFLD in patients with H pylori infection (odds ratios 1.275 95% confidence intervals 1.179-1.379), although significant heterogeneity was observed. There is no significant publication bias observed based on the funnel plot and Begg test. Subgroup analysis revealed that variables of the study design, study region, publication year, and the method of diagnosing H pylori and NAFLD all contribute to the high heterogeneity, while the positive correlation was seen in all subgroup analysis. CONCLUSION: This meta-analysis disclosed 1.275-fold increased risk of the occurrence and development of NAFLD in H pylori (+) group compared with the H pylori (-) group, indicating that H pylori is a serious risk factor in patients susceptible to NAFLD.

Genetic liability to major psychiatric disorders contributes to multi-faceted quality of life outcomes in children and adults.

Importance: Psychiatric disorders can have an immense impact on socioeconomic, physical, and social-psychological facets of life. Psychiatric disorders are also highly heritable. Under a liability threshold model, an important question arises as to what extent genetic liability for psychiatric disorders relates to, and possibly impacts on, different aspects of quality of life in the general population. Objective: To characterize the link between psychiatric genetic liability and diverse aspects of quality of life in childhood and adulthood. Design setting and participants: We used data from two multi-site, population-based cohorts, i.e. preadolescent children in the USA enrolled at age 9-10 years from the Adolescent Brain Cognitive Development (ABCD) study (N=4,645) and white British adults between age 40-69 years from the UK Biobank (UKB) study (N=377,664). Due to the current limitations of our genetic methods, only data from unrelated individuals of European descent could be included. Main outcomes and measures: To derive robust measures capturing multiple domains of quality of life in each of the cohorts, we integrated an array of measurements of academic, economic, and physical status, as well as social well-being, in a second-level three-factor confirmatory factor analysis. The genetic liabilities to seven major psychiatric disorders were quantified by a set of polygenic scores (PGSs) derived from the largest genome-wide association studies to date, independent of the target cohorts, of major depressive disorder (MDD, N=142k-173k), anxiety disorders (ANX, N=22k-144k), attention-deficit/hyperactivity disorder (ADHD, N=226k), autism spectrum disorder (ASD, N=55k), schizophrenia (SCZ, N=130k), bipolar disorder (BIP, N=353k-414k), and cannabis use disorder (CUD, N=384k). Using general linear models we assessed associations between PGSs and the estimated latent factors, controlling for age, sex, site, genotyping batch, plate, and genetic ancestry. Results: In each cohort, three latent factors indexing distinct but correlated quality of life domains, (1) educational performance and cognition (Edu, in ABCD) / social economic status (SES, in UKB), (2) physical health (Hea), (3) adverse social experience (Adv, in ABCD) / social well-being (Soc, in UKB), were estimated with excellent model fit indices. In addition, a general factor was derived that captured the covariances between the three latent factors (QoL). In the ABCD cohort, ADHD-PGS was significantly associated with Edu (ß = -0.13, t = -8.29, p = 1.53e-16), Adv (ß = -0.09, t = -5.79, p = 7.81e-09), and general QoL (ß = -0.14, t = -8.74, p = 3.37e-18) factors. In the UKB cohort, all examined disorder PGSs were significantly associated with the general QoL latent factor and at least one first-order subdomain, with ADHD-PGS (ß = -0.06 ~ -0.10, t = -29.1 ~ -52.5, p < 5.91e-186) and MDD-PGS (ß = -0.04 ~ -0.07, t = -23.8 ~ -36.3, p < 3.63e-125) showing the largest effects. Conclusions and relevance: The present study reveals an inverse relationship between psychiatric genetic liabilities and multiple quality of life metrics, with ADHD-associated genetic risk being the main contributor in both children and adults, and MDD additionally showing effects in adults. All effect sizes observed were small, as expected. Understanding potential real-world outcomes of quantitative measures of disorder-related genetic risks in the general population can provide a scientific foundation for societal intervention and policy-making processes, with profound implications for promoting a flourishing society.

A novel method for the direct detection of light stabilizer Tinuvin 622 in polymer additives by gel permeation chromatography combined with multi-angle laser light scattering.

Tinuvin 622, an oligomeric light stabilizer, is widely used in plastics to reduce light and heat induced degradation and extend their service life, therefore its detection is of great importance for quality control of plastic products. However, the classical analytical methods of Tinuvin 622, such as chromatography and mass spectrometry, are difficult to achieve direct qualitative and quantitative analysis, and simultaneously to obtain the molecular weight and molecular weight distribution information. Herein, we propose for the first time the combination of gel permeation chromatography with multi-angle laser light scattering as a simple and direct method to detect Tinuvin 622 in polymers and simultaneously to obtain its molecular weight distribution information. The linearity of the method was good in the concentration range of 0.1-5.0 mg/mL Tinuvin 622 with correlation coefficient (R2 = 0.9999), and the recoveries of Tinuvin 622 at three addition levels ranged from 94.0% to 98.7%, with relative standard deviations of no more than 1.73%. The proposed method has been successfully used to detect Tinuvin 622 in actual samples of polymer additives. Compared with existing analytical methods, Tinuvin 622 has a single peak shape in our method, which is easy to identify and quantify accurately; more importantly, our method can simultaneously characterize the molecular weight and molecular weight distribution of Tinuvin 622, which makes up for the shortcomings of other approaches and provides a new tool for quality monitoring of polymer additives.

Prior-free imaging unknown target through unknown scattering medium.

Imaging through scattering medium based on deep learning has been extensively studied. However, existing methods mainly utilize paired data-prior and lack physical-process fusion, and it is difficult to reconstruct hidden targets without the trained networks. This paper proposes an unsupervised neural network that integrates the universal physical process. The reconstruction process of the network is irrelevant to the system and only requires one frame speckle pattern and unpaired targets. The proposed network enables online optimization by using physical process instead of fitting data. Thus, large-scale paired data no longer need to be obtained to train the network in advance, and the proposed method does not need prior information. The optimization of the network is a physical-based process rather than a data mapping process, and the proposed method also increases the insufficient generalization ability of the learning-based method in scattering medium and targets. The universal applicability of the proposed method to different optical systems increases the likelihood that the method will be used in practice.

Non-invasive imaging through scattering medium and around corners beyond 3D memory effect.

The three-dimensional (3D) memory effect (ME) has been shown to exist in a variety of scattering scenes. Limited by the scope of ME, speckle correlation technology only can be applied in a small imaging field of view (FOV) with a small depth of field (DOF). In this Letter, an untrained neural network is constructed and used as an optimization tool to restore the targets beyond the 3D ME range. The autocorrelation consistency relationship and the generative adversarial strategy are combined. Only single frame speckle and unaligned real targets are needed for online optimization; therefore, the neural network does not need to train in advance. Furthermore, the proposed method does not need to conduct additional modulation for the system. This method can reconstruct not only hidden targets behind the scattering medium, but also targets around corners. The combination strategy of the generative adversarial framework with physical priors used to decouple the aliasing information and reconstruct the target will provide inspiration for the field of computational imaging.

Analysis of Hepatic Lipid Metabolism and Immune Function During the Development of Collagen-Induced Arthritis.

The liver is essential for metabolic and immune functions and has been linked to systemic inflammatory diseases. However, the role of the liver is still elusive during the development of rheumatoid arthritis (RA), although there have been indeed some reports. We used label-free quantitative proteomics and experimental verification in this study to reveal the hepatic lipid metabolism and immune function during collagen-induced arthritis (CIA) development. The proteomics results revealed that the role of the liver differs in different phases of CIA rats. In terms of specific performance, hepatic lipid metabolism, which is primarily concerned with cholesterol, triacylglycerol, and phospholipid, was significantly influenced in the CIA induction phase, whereas the immune function, which includes binding of granulocytes, adhesion of immune cells, etc., was affected considerably at the peak phase of CIA rats compared to normal rats. Finally, the hepatic dynamic changes in CIA rats were further confirmed using targeted metabolomics and ELISA. We found that most fatty acids of the liver in the CIA induction phase were significantly decreased, and proteins related to complement activation and migration or adhesion of immune cells including C3, MMP-8, CTSZ, and S100A9 were significantly increased in the liver of CIA rats in the peak phase. Our findings indicated that the lipid metabolism and immune function of the liver were influenced in CIA rats. Thus, the conditions of the liver during RA development should be considered in therapeutic and nutritional interventions.

Longitudinal association of maternal dietary patterns with antenatal depression: Evidence from the Chinese Pregnant Women Cohort Study.

BACKGROUND: Limited evidence to show the longitudinal associations between maternal dietary patterns and antenatal depression (AD) from cohort studies across the entire gestation period. METHODS: Data came from the Chinese Pregnant Women Cohort Study. The qualitative food frequency questionnaire (Q-FFQ) and Edinburgh Postnatal Depression Scale (EPDS) were used to collect diet and depression data. Dietary patterns were derived by using factor analysis. Generalized estimating equation models were used to analyze the association between diet and AD. RESULTS: A total of 4139 participants finishing 3-wave of follow-up were finally included. Four constant diets were identified, namely plant-based, animal-protein, vitamin-rich and oily-fatty patterns. The prevalence of depression was 23.89%, 21.12% and 22.42% for the first, second and third trimesters. There were reverse associations of plant-based pattern (OR:0.85, 95%CI:0.75-0.97), animal-protein pattern (OR:0.85, 95%CI:0.74-0.99) and vitamin-rich pattern (OR:0.58, 95%CI:0.50-0.67) with AD, while a positive association between oily-fatty pattern and AD (OR:1.47, 95%CI:1.29-1.68). Except for the plant-based pattern, other patterns had linear trend relationships with AD (Ptrend < 0.05). Moreover, a 1-SD increase in vitamin-rich pattern scores was associated with a 20% lower AD risk (OR:0.80, 95%CI:0.76-0.84), while a 1-SD increase in oily-fatty pattern scores was associated with a 19% higher risk (OR:1.19, 95%CI:1.13-1.24). Interactions between dietary patterns and lifestyle habits were observed. LIMITATIONS: The self-reported Q-FFQ and EPDS may cause recall bias. CONCLUSIONS: There are longitudinal associations between maternal dietary patterns and antenatal depression. Our findings are expected to provide evidence for a dietary therapy strategy to improve or prevent depression during pregnancy.

Hippocampal-Medial Prefrontal Event Segmentation and Integration Contribute to Episodic Memory Formation.

How do we encode our continuous life experiences for later retrieval? Theories of event segmentation and integration suggest that the hippocampus binds separately represented events into an ordered narrative. Using a functional Magnetic Resonance Imaging (fMRI) movie watching-recall dataset, we quantified two types of neural similarities (i.e., "activation pattern" similarity and within-region voxel-based "connectivity pattern" similarity) between separate events during movie watching and related them to subsequent retrieval of events as well as retrieval of sequential order. We demonstrated that compared with forgotten events, successfully remembered events were associated with distinct "activation patterns" in the hippocampus and medial prefrontal cortex. In contrast, similar "connectivity pattern" between events were associated with memory formation and were also relevant for retaining events in the correct order. We applied the same approaches to an independent movie watching fMRI dataset as validation and highlighted again the role of hippocampal activation pattern and connectivity pattern in memory formation. We propose that distinct activation patterns represent neural segmentation of events, while similar connectivity patterns encode context information and, therefore, integrate events into a narrative. Our results provide novel evidence for the role of hippocampal-medial prefrontal event segmentation and integration in episodic memory formation of real-life experience.

Association of gestational anemia with pregnancy conditions and outcomes: A nested case-control study.

BACKGROUND: Gestational anemia is a serious public health problem that affects pregnant women worldwide. Pregnancy conditions and outcomes might be associated with the presence of gestational anemia. This study investigated the association of pregnancy characteristics with anemia, exploring the potential etiology of the disease. AIM: To assess the association of pregnancy parameters with gestational anemia. METHODS: A nested case-control study was conducted based on the Chinese Pregnant Women Cohort Study-Peking Union Medical College Project (CPWCS-PUMC). A total of 3172 women were included. Patient characteristics and gestational anemia occurrence were extracted, and univariable and multivariable logistic regression models were used to analyze the association of pregnancy parameters with gestational anemia. RESULTS: Among the 3172 women, 14.0% were anemic, 46.4% were 25-30 years of age, 21.9% resided in eastern, 15.7% in middle, 12.4% in western 18.0% in southern and 32.0% in northern regions of China. Most women (65.0%) had a normal prepregnancy body mass index. Multivariable analysis found that the occurrence of gestational anemia was lower in the middle and western regions than that in the eastern region [odds ratio (OR) = 0.406, 95% confidence interval (CI): 0.309-0.533, P < 0.001)], higher in the northern than in the southern region (OR = 7.169, 95%CI: 5.139-10.003, P < 0.001), lower in full-term than in premature births (OR = 0.491, 95%CI: 0.316-0.763, P = 0.002), and higher in cases with premature membrane rupture (OR=1.404, 95%CI: 1.051-1.876, P = 0.02). CONCLUSION: Gestational anemia continues to be a health problem in China, and geographical factors may contribute to the situation. Premature birth and premature membrane rupture may be associated with gestational anemia. Therefore, we should vigorously promote local policy reformation to adapt to the demographic characteristics of at-risk pregnant women, which would potentially reduce the occurrence of gestational anemia.

Dissecting the Molecular Mechanism of Wang-Bi Capsule in the Treatment of Experimental Rheumatoid Arthritis Based on Synovial Tissue Proteomic Analysis.

Wang-Bi capsule (WB) is a traditional Chinese medicine formula and has been applied for rheumatoid arthritis (RA) treatment for many years. However, its underlying molecular mechanisms still remain unclear. In this study, collagen-induced arthritis (CIA) rats were used to observe the therapeutic effect of WB used at different time points, and the proteomic analysis of synovial tissue was applied to reveal its basic molecular mechanisms. The results demonstrated that WB not only effectively ameliorated the symptoms and synovitis, but also downregulated the serum levels of inflammatory cytokines/chemokines in CIA rats. Furthermore, the proteomic analysis of synovial tissue showed that WB could regulate several signaling pathways associated with inflammation or cell migration, such as "IL-1 signaling," "IL-8 signaling," and "CXCR4 signaling." The expression levels of proteins including matrix metalloproteinase 3 (MMP3), MMP19, lipopolysaccharide-binding protein (LBP), serine/threonine kinase interleukin-1 receptor-associated kinase 4 (IRAK4), and actin-related protein 2/3 complex subunit 5 (ARPC5) in these pathways were downregulated significantly by WB when compared with the model group. In sum, this study indicated that WB had obvious inhibitory effects on synovitis of CIA rats, and the mechanisms of which may be involved in downregulating the expression levels of several key proteins including MMP3, MMP19, LBP, IRAK4, and ARPC5.

Investigation of optimal gestational weight gain based on the occurrence of adverse pregnancy outcomes for Chinese women: a prospective cohort study.

OBJECTIVE: To investigate recommendations for appropriate gestational weight gain (GWG) of Chinese females. METHODS: In total of 3,172 eligible women in the first trimester were recruited into the Chinese Pregnant Women Cohort Study (CPWCS) project. Pregnancy complications and outcomes were collated using the hospital medical records system. The method of occurrence of participants with adverse pregnancy outcomes (Occurrence Method) was conducted to calculate the recommended total GWG for each participant's pre-pregnancy BMI. Occurrence Method data were judged against the Institute of Medicine (IOM) and Japanese recommended criteria in terms of the total occurrence of adverse pregnancy outcomes of pregnant women with appropriate weight gain. RESULTS: The most frequent GWG was ≥ 14 kg and < 16 kg (19.4%), followed by ≥ 10 kg and < 12 kg (15.5%) and ≥ 12 kg and < 14 kg (15.2%). The most frequently occurring adverse pregnancy outcomes were cesarean sections for underweight (30.0%), normal weight (40.4%), overweight (53.6%) and obese (53.7%) women. A large for gestational age (LGA) accounted for 18.0% of the overweight and 20.9% of the obesity group. Gestational diabetes mellitus (GDM) occurred in 16.9% of overweight and 23.1% of obese women. The recommended total GWG in a Chinese women population is ≥ 8 and < 12 kg if underweight, ≥ 12 and < 14 kg for normal weight, ≥ 8.0 and < 10.0 kg if overweight, and < 8 kg for women with obesity. CONCLUSIONS: Current Chinese recommendations provide the optimal ranges of GWG to minimize the occurrence of undesirable pregnancy outcomes for each group of pre-pregnancy BMIs in a Chinese population. TRIAL REGISTRATION: Registered with ClinicalTrials ( NCT03403543 ).

Transcriptomics-based analysis of the mechanism by which Wang-Bi capsule alleviates joint destruction in rats with collagen-induced arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease accompanied with joint destruction that often leads to disability. Wang-Bi capsule (WB), a traditional Chinese medicine-based herbs formula, has exhibited inhibition effect on joint destruction of collagen-induced arthritis (CIA) animal model in our previous study. But its molecular mechanisms are still obscure. METHODS: CIA rats were treated intragastrical with WB for eight weeks, and the effect of joints protection were evaluated by hematoxylin and eosin (H&E) staining, safranin O fast green staining, tartrate-resistant acid phosphatase (TRAP) staining and micro­CT scanning analysis. The transcriptomic of tarsal joints were used to investigate how WB alleviated joint destruction. RESULTS: The histological examination of ankle joints showed WB alleviated both cartilage damage and bone destruction of CIA rats. This protective effect on joints were further evidenced by micro-CT analysis. The transcriptomic analysis showed that WB prominently changed 12 KEGG signaling pathways ("calcium signaling pathway", "cAMP signaling pathway", "cell adhesion molecules", "chemokine signaling pathway", "complement and coagulation cascades", "MAPK signaling pathway", "NF-kappa B signaling pathway", "osteoclast differentiation", "PI3K-Akt signaling pathway", "focal adhesion", "Gap junction" and "Rap1 signaling pathway") associated with bone or cartilage. Several genes (including Il6, Tnfsf11, Ffar2, Plg, Tnfrsf11b, Fgf4, Fpr1, Siglec1, Vegfd, Cldn1, Cxcl13, Chad, Arrb2, Fgf9, Egfr) regulating bone resorption, bone formation and cartilage development were identified by further analysis. Meanwhile, these differentially expressed genes were validated by real-time quantitative PCR. CONCLUSIONS: Overall, the protective effect of WB treatment on joint were confirmed in CIA rats, and its basic molecular mechanisms may be associated with regulating some genes (including Il6, Tnfsf11, Ffar2 and Plg etc.) involved in bone resorption, bone formation and cartilage development.

Cohort profile: the Chinese Pregnant Women Cohort Study and Offspring Follow-up (CPWCSaOF).

PURPOSE: A multicentre prospective cohort study, known as the Chinese Pregnant Women Cohort Study (CPWCS), was established in 2017 to collect exposure data during pregnancy (except environmental exposure) and analyse the relationship between lifestyle during pregnancy and obstetric outcomes. Data about mothers and their children's life and health as well as children's laboratory testing will be collected during the offspring follow-up of CPWCS, which will enable us to further investigate the longitudinal relationship between exposure in different periods (during pregnancy and childhood) and children's development. PARTICIPANTS: 9193 pregnant women in 24 hospitals in China who were in their first trimester (5-13 weeks gestational age) from 25 July 2017 to 26 November 2018 were included in CPWCS by convenience sampling. Five hospitals in China which participated in CPWCS with good cooperation will be selected as the sample source for the Chinese Pregnant Women Cohort Study (Offspring Follow-up) (CPWCS-OF). FINDINGS TO DATE: Some factors affecting pregnancy outcomes and health problems during pregnancy have been discovered through data analysis. The details are discussed in the 'Findings to date' section. FUTURE PLANS: Infants and children and their mothers who meet the criteria will be enrolled in the study and will be followed up every 2 years. The longitudinal relationship between exposure (questionnaire data, physical examination and biospecimens, medical records, and objective environmental data collected through geographical information system and remote sensing technology) in different periods (during pregnancy and childhood) and children's health (such as sleeping problem, oral health, bowel health and allergy-related health problems) will be analysed. TRAIL REGISTRATION NUMBER: CPWCS was registered with ClinicalTrials.gov on 18 January 2018: NCT03403543. CPWCS-OF was registered with ClinicalTrials.gov on 24 June 2020: NCT04444791.

Traditional Chinese medicine symptom normalization approach leveraging hierarchical semantic information and text matching with attention mechanism.

Traditional Chinese medicine (TCM) symptom normalization is difficult because the challenges of the symptoms having different literal descriptions, one-to-many symptom descriptions and different symptoms sharing a similar literal description. We propose a novel two-step approach utilizing hierarchical semantic information that represents the functional characteristics of symptoms and develop a text matching model that integrates hierarchical semantic information with an attention mechanism to solve these problems. In this study, we constructed a symptom normalization dataset and a TCM normalization symptom dictionary containing normalization symptom words, and assigned symptoms into 24 classes of functional characteristics. First, we built a multi-label text classifier to isolate the hierarchical semantic information from each symptom description and count the corresponding normalization symptoms and filter the candidate set. Then we designed a text matching model of mixed multi-granularity language features with an attention mechanism that utilizes the hierarchical semantic information to calculate the matching score between the symptom description and the normalization symptom words. We compared our approach with other baselines on real-world data. Our approach gives the best performance with a Hit@ 1, 3, and 10 of 0.821, 0.953, and 0.993, respectively, and a MeanRank of 1.596, thus outperforming significantly regarding the symptom normalization task. We developed an approach for the TCM symptom normalization task and demonstrated its superior performance compared with other baselines, indicating the promise of this research direction.

Association among pre-pregnancy body mass index, gestational weight gain and neonatal birth weight: a prospective cohort study in China.

BACKGROUND: This study aims to explore the relationships between pre-pregnancy body mass index (BMI), gestational weight gain (GWG), rate of GWG during the second and third trimesters (GWGrate) and birth weight among Chinese women. METHODS: Women were enrolled by 24 hospitals in 15 different provinces in mainland China from July 25th, 2017 to 26 November 2018. Pre-pregnancy BMI, GWG and GWGrate were calculated and divided in to different groups. The multinomial logistic regression model and restrictive cubic spline model were used to explore the relationships. RESULTS: Of the 3585 participants, women who were underweight, had insufficient GWG or GWGrate had 1.853-, 1850- or 1.524-fold higher risks for delivering small-for-gestational-age (SGA) infant compared with women who had normal BMI, sufficient GWG or GWGrate. Women who were overweight/obese, had excessive GWG or GWGrate had 1.996-, 1676- or 1.673-fold higher risks for delivering large-for-gestational-age (LGA) infant. The effects of GWG and GWGrate on birth weight varied by pre-pregnancy BMI statuses. Dose-response analysis demonstrated L-shaped and S-shaped relationships between pre-pregnancy BMI, GWG, GWGrate and neonatal birth weight. CONCLUSIONS: Pre-pregnancy BMI, GWG or GWGrate were associated with neonatal birth weight among Chinese women. Both body weight before and during pregnancy should be maintained within the recommendations to prevent abnormal birth weight.