Efficient Rh-Catalyzed Chemo- and Enantioselective Hydrogenation of 2-CF3-Chromen/Thiochromen-4-ones.

A Rh-catalyzed highly chemo- and enantioselective hydrogenation of 2-CF3-chromen/thiochromen-4-ones was successfully established achieving excellent selectivity and high turnover numbers. Under mild conditions, a series of 2-CF3-chromen-4-ones were hydrogenated to provide the corresponding chiral 2-CF3-chroman-4-ones with excellent enantioselectivities (up to 99.9% ee) and achieve high turnover numbers (TON of up to 11,800). Moreover, the obtained hydrogenation products were also successfully transformed into other derivatives including the important intermediate of plasmepsin inhibitors with maintained enantiopurity.

Rh-Catalyzed Asymmetric Hydrogenation of α-Substituted Alkenyl Sulfones: Highly Chemo- and Enantioselective Access to Chiral Sulfones.

Rh-(R,R)-f-spiroPhos complex-catalyzed asymmetric hydrogenation of α-substituted alkenyl sulfones has been achieved, affording the chiral γ-keto sulfones and simple α-alkyl-substituted sulfones in high yields (96-99%) with excellent chemo-/enantioselectivities (86-96% ee) and high turnover numbers (TONs) of up to 4000. The method provides an efficient and high-enantioselectivity strategy for chiral γ-keto sulfones and simple α-substituted sulfones under mild conditions. Moreover, the obtained hydrogenation product was transformed into other important chiral α-substituted sulfones.

Artificial intelligence and bioinformatics analyze markers of children's transcriptional genome to predict autism spectrum disorder.

Introduction: Autism spectrum disorder (ASD), characterized by difficulties in social interaction and communication as well as restricted interests and repetitive behaviors, is extremely challenging to diagnose in toddlers. Early diagnosis and intervention are crucial however. Methods: In this study, we developed a machine learning classification model based on mRNA expression data from the peripheral blood of 128 toddlers with ASD and 126 controls. Differentially expressed genes (DEGs) between ASD and controls were identified. Results: We identified genes such as UBE4B, SPATA2 and RBM3 as DEGs, mainly involved in immune-related pathways. 21 genes were screened as key biomarkers using LASSO regression, yielding an accuracy of 86%. A neural network model based on these 21 genes achieved an AUC of 0.88. Discussion: Our findings suggest that the identified neurotransmitters and 21 immune-related biomarkers may facilitate the early diagnosis of ASD. The mRNA expression profile sheds light on the biological underpinnings of ASD in toddlers and potential biomarkers for early identification. Nevertheless, larger samples are needed to validate these biomarkers.

The comparisons of vitamin D3 levels in IgA vasculitis across different subgroups and healthy children: a comparative study.

Background: IgA vasculitis is the most common form of vasculitis in children. Vitamin D deficiency has been observed to contribute to immune function and the pathogenesis of various immune diseases. However, at present, only a few studies with small sample sizes have shown that IgA vasculitis patients have lower vitamin D levels than healthy children. Thus, we conduct a large study to investigate the significance of serum 25-hydroxyvitamin D3 (25(OH)D) levels of children with IgA vasculitis across different subgroups and healthy children. Methods: In this retrospective study, 1,063 children were recruited from the Ningbo Women and Children's Hospital between February 2017 and October 2019, including 663 patients hospitalized with IgA vasculitis and 400 healthy examination children who served as the control group at the same time. There wasn't any bias in the season. The healthy group came from children who underwent normal physical examination. The 663 IgA vasculitis patients were then divided into the IgA vasculitis-nephritis and non-IgA vasculitis-nephritis groups, streptococcal-infection and no-streptococcal-infection groups, gastrointestinal-involvement and no-gastrointestinal-involvement groups, and joint-involvement and no-joint-involvement groups. The serum 25(OH)D levels at disease onset were analyzed. All the participants were followed up for 6 months from the date of onset. Results: The serum 25(OH)D levels of the IgA vasculitis group (15.47±6.58 ng/mL) were significantly lower than those of the healthy control group (22.48±6.24 ng/mL) (P<0.01). There were no significant differences in terms of age and sex between the IgA vasculitis and healthy control group. Further, among the IgA vasculitis patients serum 25(OH)D levels were reduced in the IgA vasculitis-nephritis (12.99±4.92 ng/mL), streptococcal-infection (14.2±6.06 ng/mL), and gastrointestinal-involvement (14.43±6.33 ng/mL) groups (P=0.00, 0.004, 0.002, respectively). The vitamin D levels with IgA vasculitis were significantly lower in winter and spring than summer and autumn. Conversely, the joint-involvement group did not show a significant reduction in vitamin D levels compared to no joints involved group. Conclusions: IgA vasculitis patients have reduced vitamin D levels, which suggests that vitamin D deficiency may be involved in the development of IgA vasculitis. Vitamin D supplementation may reduce the incidence of IgA vasculitis, and maintaining high vitamin D levels in IgA vasculitis patients may prevent renal damage.

Maternal exposure to fine particulate matter and brain-derived neurotrophic factor (BDNF) in the fetus: A prospective cohort study.

Maternal exposure to ambient fine particulate matter (PM2.5) during pregnancy has been associated with impaired neurobehavioral development in children. However, the specific mechanism remains unclear. Brain derived neurotrophic factor (BDNF) is an important growth factor in the nervous system. We evaluated the associations of maternal PM2.5 exposures with fetal BDNF in the umbilical cord blood in a prospective cohort study. A total of 711 eligible mother-infant pairs from the Shanghai Birth Cohort were included in the current study. Daily maternal exposures to ambient PM2.5 were assessed with a gap-filling approach at 1 * 1 km2 resolution based on self-reported home addresses. The concentrations of BDNF in the cord blood were measured by ELISA. A linear regression model was applied to evaluate the association of maternal ambient PM2.5 exposure with fetal BDNF level at birth. The median concentration of BDNF was 13,403 pg/ml. Vaginal deliveries and female infants had higher BDNF levels than cesarean deliveries and male infants. One natural log (ln) unit increase in maternal PM2.5 exposure during the second trimester was significantly associated with - 0.20 (95% CI: -0.36, -0.05) ln-unit decrease in BDNF level in all births. These effects were stronger and more significant in vaginal deliveries and in male infants. Our study suggests that BDNF in the cord blood may serve as a potential biomarker in assessing the neurodevelopmental effects of maternal PM2.5 exposure.

Modulation of electromagnetic wave absorption via porosity in Pechini-derived carbon guided by a random network model.

It is well established that porosity in carbon materials can benefit electromagnetic wave absorption by providing stronger interfacial polarization, better impedance matching, multiple reflections, and lower density, but an in-depth assessment is still lacking on this issue. The random network model describes the dielectric behavior of a conduction-loss absorber-matrix mixture with two parameters related to the volume fraction and conductivity, respectively. In this work, the porosity in carbon materials was tuned by a simple, green, and low-cost Pechini method, and the mechanism of how porosity affects EM wave absorption was investigated quantitatively based on the model. It was discovered that porosity was crucial for the formation of a random network, and a higher specific pore volume led to a larger volume fraction parameter and a lower conductivity parameter. Guided by the high throughput parameter sweeping based on the model, the Pechini-derived porous carbon could achieve an effective absorption bandwidth of 6.2 GHz at 2.2 mm. This study further verifies the random network model, unveiling the implication and influencing factors of the parameters, and opens a new path to optimize the electromagnetic wave absorption performance of conduction-loss materials.

A Scalable Balz-Schiemann Reaction Protocol in a Continuous Flow Reactor.

The demand for aromatic fluorides is steadily increasing in the pharmaceutical and fine chemical industries. The Balz-Schiemann reaction is a straightforward strategy for preparing aryl fluorides from aryl amines, via the preparation and conversion of diazonium tetrafluoroborate intermediates. However, significant safety risks exist in handling the aryl diazonium salts when scaling up. In order to minimize the hazard, we present a continuous flow protocol that has been successfully performed at a kilogram scale that eliminates the isolation of aryl diazonium salts while facilitating efficient fluorination. The diazotization process was performed at 10 °C with a residence time of 10 min, followed by a fluorination process at 60 °C with a residence time of 5.4 s with about 70% yield. The reaction time has been dramatically reduced by introducing this multi-step continuous flow system.

Application of weighted co-expression network analysis and machine learning to identify the pathological mechanism of Alzheimer's disease.

Aberrant deposits of neurofibrillary tangles (NFT), the main characteristic of Alzheimer's disease (AD), are highly related to cognitive impairment. However, the pathological mechanism of NFT formation is still unclear. This study explored differences in gene expression patterns in multiple brain regions [entorhinal, temporal, and frontal cortex (EC, TC, FC)] with distinct Braak stages (0- VI), and identified the hub genes via weighted gene co-expression network analysis (WGCNA) and machine learning. For WGCNA, consensus modules were detected and correlated with the single sample gene set enrichment analysis (ssGSEA) scores. Overlapping the differentially expressed genes (DEGs, Braak stages 0 vs. I-VI) with that in the interest module, metascape analysis, and Random Forest were conducted to explore the function of overlapping genes and obtain the most significant genes. We found that the three brain regions have high similarities in the gene expression pattern and that oxidative damage plays a vital role in NFT formation via machine learning. Through further filtering of genes from interested modules by Random Forest, we screened out key genes, such as LYN, LAPTM5, and IFI30. These key genes, including LYN, LAPTM5, and ARHGDIB, may play an important role in the development of AD through the inflammatory response pathway mediated by microglia.

The Application of Consensus Weighted Gene Co-expression Network Analysis to Comparative Transcriptome Meta-Datasets of Multiple Sclerosis in Gray and White Matter.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination, which leads to the formation of white matter lesions (WMLs) and gray matter lesions (GMLs). Recently, a large amount of transcriptomics or proteomics research works explored MS, but few studies focused on the differences and similarities between GMLs and WMLs in transcriptomics. Furthermore, there are astonishing pathological differences between WMLs and GMLs, for example, there are differences in the type and abundance of infiltrating immune cells between WMLs and GMLs. Here, we used consensus weighted gene co-expression network analysis (WGCNA), single-sample gene set enrichment analysis (ssGSEA), and machine learning methods to identify the transcriptomic differences and similarities of the MS between GMLs and WMLs, and to find the co-expression modules with significant differences or similarities between them. Through weighted co-expression network analysis and ssGSEA analysis, CD56 bright natural killer cell was identified as the key immune infiltration factor in MS, whether in GM or WM. We also found that the co-expression networks between the two groups are quite similar (density = 0.79), and 28 differentially expressed genes (DEGs) are distributed in the midnightblue module, which is most related to CD56 bright natural killer cell in GM. Simultaneously, we also found that there are huge disparities between the modules, such as divergences between darkred module and lightyellow module, and these divergences may be relevant to the functions of the genes in the modules.

Public auditing for real-time medical sensor data in cloud-assisted HealthIIoT system.

With the advancement of industrial internet of things (IIoT), wireless medical sensor networks (WMSNs) have been widely introduced in modern healthcare systems to collect real-time medical data from patients, which is known as HealthIIoT. Considering the limited computing and storage capabilities of lightweight HealthIIoT devices, it is necessary to upload these data to remote cloud servers for storage and maintenance. However, there are still some serious security issues within outsourcing medical sensor data to the cloud. One of the most significant challenges is how to ensure the integrity of these data, which is a prerequisite for providing precise medical diagnosis and treatment. To meet this challenge, we propose a novel and efficient public auditing scheme, which is suitable for cloud-assisted HealthIIoT system. Specifically, to address the contradiction between the high real-time requirement of medical sensor data and the limited computing power of HealthIIoT devices, a new online/offline tag generation algorithm is designed to improve preprocessing efficiency; to protect medical data privacy, a secure hash function is employed to blind the data proof. We formally prove the security of the presented scheme, and evaluate the performance through detailed experimental comparisons with the state-of-the-art ones. The results show that the presented scheme can greatly improve the efficiency of tag generation, while achieving better auditing performance than previous schemes.

Application of Machine Learning and Weighted Gene Co-expression Network Algorithm to Explore the Hub Genes in the Aging Brain.

Aging is a major risk factor contributing to neurodegeneration and dementia. However, it remains unclarified how aging promotes these diseases. Here, we use machine learning and weighted gene co-expression network (WGCNA) to explore the relationship between aging and gene expression in the human frontal cortex and reveal potential biomarkers and therapeutic targets of neurodegeneration and dementia related to aging. The transcriptional profiling data of the human frontal cortex from individuals ranging from 26 to 106 years old was obtained from the GEO database in NCBI. Self-Organizing Feature Map (SOM) was conducted to find the clusters in which gene expressions downregulate with aging. For WGCNA analysis, first, co-expressed genes were clustered into different modules, and modules of interest were identified through calculating the correlation coefficient between the module and phenotypic trait (age). Next, the overlapping genes between differentially expressed genes (DEG, between young and aged group) and genes in the module of interest were discovered. Random Forest classifier was performed to obtain the most significant genes in the overlapping genes. The disclosed significant genes were further identified through network analysis. Through WGCNA analysis, the greenyellow module is found to be highly negatively correlated with age, and functions mainly in long-term potentiation and calcium signaling pathways. Through step-by-step filtering of the module genes by overlapping with downregulated DEGs in aged group and Random Forest classifier analysis, we found that MAPT, KLHDC3, RAP2A, RAP2B, ELAVL2, and SYN1 were co-expressed and highly correlated with aging.

Enantioselective Synthesis of Chiral Phosphonates via Rh/f-spiroPhos Catalyzed Asymmetric Hydrogenation of ß,ß-Disubstituted Unsaturated Phosphonates.

The first asymmetric hydrogenation of ß,ß-diaryl unsaturated phosphonates has been realized for synthesis of ß,ß-diaryl chiral phosphonates with excellent enantioselectivities (up to 99.9% ee) catalyzed by the Rh-(R,R)-f-spiroPhos complex. Furthermore, this catalyst also exhibits comparably excellent performance for ß-aryl-ß-alkyl unsaturated phosphonates providing the corresponding chiral phosphonates with up to 99.9% ee values. This methodology provides a straightforward access to asymmetric synthesis of chiral phosphonates.

Enantioselective Synthesis of Chiral Substituted 2,4-Diketoimidazolidines and 2,5-Diketopiperazines via Asymmetric Hydrogenation.

An enantioselective hydrogenation of 5-alkylidene-2,4-diketoimidazolidines (hydantoins) and 3-alkylidene-2,5-ketopiperazines catalyzed by the Rh/f-spiroPhos complex under mild conditions has been developed, which provides an efficient approach to the highly enantioselective synthesis of chiral hydantoins and 2,5-ketopiperazine derivatives with high enantioselectivities up to 99.9% ee.

Perfluoroalkyl substances in early pregnancy and risk of hypertensive disorders of pregnancy: A prospective cohort study.

BACKGROUND: Perfluoroalkyl substances (PFASs) were reported to be associated with hypertensive disorders of pregnancy (HDP) but the results were inconsistent and prospective data are scarce. We aimed to examine these associations in a large prospective birth cohort study in Shanghai, China. METHODS: A total of 10 PFASs were measured by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS-MS) in the plasma samples from 3220 women who were enrolled during early pregnancy and gave birth to a singleton live birth between 2013 and 2016. The outcomes included gestational hypertension (GH), preeclampsia (PE) and overall HDP. Associations of these outcomes with each PFASs were estimated by multivariable logistic regression and expressed as odd ratios (ORs) and 95% confidence intervals (95% CIs). Potential non-linear association between PFASs and HDP was examined with restricted cubic spline model. To handle the potential confounding by correlated PFASs, we applied elastic net regression (ENR) to identify independent PFASs components of outcomes. RESULTS: Among all singleton live births, the incidence rates of GH and PE were 2.0% and 2.2%, respectively. Overall, PFASs did not show a significant and consistent pattern of the associations with GH, PE or overall HDP, both before and after controlling for potential confounders. ENR model confirmed the results that there was no independently predictive role of PFASs on GH, PE or overall HDP. CONCLUSIONS: In this large prospective cohort study, maternal plasma concentration of PFASs in early pregnancy were not associated with GH, PE or overall HDP in singleton livebirths.

Anisomycin inhibits angiogenesis in ovarian cancer by attenuating the molecular sponge effect of the lncRNA­Meg3/miR­421/PDGFRA axis.

Angiogenesis has an important role in tumour cell growth and metastasis. Anisomycin has been shown to inhibit tumour cell growth. However, whether anisomycin can inhibit angiogenesis of tumours has not been reported. The present study demonstrated that there was a positive correlation between tumour angiogenesis and the number of CD44+/CD133+ serous human ovarian cancer stem cells (HuOCSCs). Subsequently, it was confirmed that anisomycin significantly inhibited the proliferation, invasion, tumorigenic ability and tumour angiogenesis of HuOCSCs. Gene expression profiling by cDNA microarrays revealed that the expression levels of vascular endothelial cell markers, platelet­derived growth factors, Notch pathway components and 27 tumour angiogenesis­related genes were significantly decreased in the anisomycin­treated group compared with the control group. Further experiments demonstrated that the expression levels of endogenous long non­coding RNA (lncRNA) maternally expressed 3 (Meg3) were significantly decreased in anisomycin­treated HuOCSCs, whereas the expression levels of microRNA (miR)­421 were significantly increased. The results of luciferase reporter assays indicated that, when miR­421 was overexpressed in cells, the luciferase activities of wild­type platelet derived growth factor receptor α (PDGFRA) 3' untranslated region and Meg3 reporter plasmids were significantly decreased. Overexpression of miR­421 in HuOCSCs significantly enhanced the anisomycin­mediated inhibition of HuOCSC proliferation. Taken together, the present results demonstrated that anisomycin inhibited the activation downstream of the Notch1 pathway by attenuating the molecular sponge effect of the lncRNA­Meg3/miR­421/PDGFRA axis, ultimately inhibiting angiogenesis, proliferation and invasion in ovarian cancer cells.

Is ELABELA a reliable biomarker for hypertensive disorders of pregnancy?

OBJECTIVE: We aimed to examine the ELABELA levels at different stages of pregnancy among normotensive controls and women with hypertensive disorders of pregnancy (HDP). STUDY DESIGN: A total of 336 blood samples of 169 women were collected from pre-pregnancy, the first, second, and third trimesters. Women were divided into the following six groups: 1) non-pregnant healthy women; 2) healthy pregnant controls; 3) chronic hypertension; 4) gestational hypertension; 5) preeclampsia; and 6) preeclampsia superimposed on chronic hypertension. ELABELA plasma concentrations were measured by human ELA Elisa Kit (Peninsula Laboratories International, Inc. USA). Kruskal-Wallis test was used to test whether ELABELA level in each type of HDP differed from that in gestational week-matched normotensive controls. MAIN OUTCOME MEASURES: Hypertensive disorders of pregnancy. RESULTS: In the first trimester, patients with gestational hypertension had higher ELABELA level than gestational week-matched normotensive controls [median (ng/ml): 31.9, (IQR (ng/ml): 16.3, 47.6) vs. 19.7 (13.7, 23.2), p = 0.03]. In the second trimester, the levels were 49.2 (32.2, 69.1) vs 24.0 (13.0, 32.6) (p = 0.002), respectively. The level for gestational hypertensive women in the third trimester did not differ significantly from that of normotensive women [43.8 (30.8, 62.7) vs 25.0 (12.3, 74.0), p = 0.82]. The ELABELA levels were similar between preeclamptic women and normotensive controls throughout pregnancy. CONCLUSIONS: Maternal blood ELABELA levels in the first and second trimesters were elevated in women who developed gestational hypertension late in pregnancy, but the ELABELA level bears no significant relationship with preeclampsia during any stage of pregnancy.

Prenatal diagnosis of methylmalonic aciduria from amniotic fluid using genetic and biochemical approaches.

OBJECTIVES: This study reported the clinical prenatal diagnosis experience of families affected by methylmalonic acidemia (MMA) evaluated at a single prenatal diagnosis center over 8 years, and the reliability of a biochemical approach for prenatal diagnosis was analyzed. METHODS: Prenatal diagnosis data for 187 MMA families referred to our center from 2009 to 2016 were reviewed retrospectively. The results of the genetic analysis and biochemical approach were compared. RESULTS: A total of 41 MMA-affected pregnancies (21%) were identified. The biochemical analysis could identify the true status of 99.5% of fetuses. The diagnostic sensitivities of the propionylcarnitine (C3) level, the C3 to acetylcarnitine (C2) ratio (C3/C2), the methylmalonic acid, and methylcitrate levels in the amniotic fluid were 95.1%, 100%, 100%, and 82.9%, respectively, and the specificities were 98.7%, 99.3%, 97.4%, and 96.7%, respectively. CONCLUSIONS: The biochemical analysis could be optionally used in the prenatal diagnosis of MMA, especially in cases where the genetic results are inconclusive. Among the four tested biochemical markers, C3/C2 appeared to be the most reliable.

A simple model to predict risk of gestational diabetes mellitus from 8 to 20 weeks of gestation in Chinese women.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse perinatal outcomes. Screening for GDM and applying adequate interventions may reduce the risk of adverse outcomes. However, the diagnosis of GDM depends largely on tests performed in late second trimester. The aim of the present study was to bulid a simple model to predict GDM in early pregnancy in Chinese women using biochemical markers and machine learning algorithm. METHODS: Data on a total of 4771 pregnant women in early gestation were used to fit the GDM risk-prediction model. Predictive maternal factors were selected through Bayesian adaptive sampling. Selected maternal factors were incorporated into a multivariate Bayesian logistic regression using Markov Chain Monte Carlo simulation. The area under receiver operating characteristic curve (AUC) was used to assess discrimination. RESULTS: The prevalence of GDM was 12.8%. From 8th to 20th week of gestation fasting plasma glucose (FPG) levels decreased slightly and triglyceride (TG) levels increased slightly. These levels were correlated with those of other lipid metabolites. The risk of GDM could be predicted with maternal age, prepregnancy body mass index (BMI), FPG and TG with a predictive accuracy of 0.64 and an AUC of 0.766 (95% CI 0.731, 0.801). CONCLUSIONS: This GDM prediction model is simple and potentially applicable in Chinese women. Further validation is necessary.

Aspirin use during pregnancy and hypoxia-related placental pathology.

OBJECTIVE: Aspirin has been shown to prevent preeclampsia. But the mechanisms remain unclear despite that improved placental circulation is considered as an underlying contributor. Our aim was to examine the hypoxia-related morphological and histopathological placental measures in relation to aspirin use during pregnancy. STUDY DESIGN: We used the Collaborative Perinatal Project (CPP) data, which is a cohort study conducted in the U.S. from 1959 to 1976. A total of 23, 604 women who had information on placental pathology and aspirin intake during pregnancy were included in the analysis. Among them, 1474 women had a history of hypertension or preeclampsia/eclampsia and were classified as a high-risk population; the rest were considered as a low-risk population. 47 placenta measures considered to be relevant to hypoxia were selected to build a composite hypoxia- related placenta index. The generalized linear mixed model was used to fit the relationship between aspirin and placental pathology. MAIN OUTCOME MEASURES: Hypoxia-related placental pathology. RESULTS: Aspirin use during pregnancy was associated with a reduced risk of hypoxia-related placental pathology in the high-risk population [the adjusted odds ratio and 95% confidence interval in the 1st, 2nd, and 3rd trimesters: 0.55 (0.31, 1.00), 0.76 (0.49, 1.17), and 0.53 (0.29, 0.94), respectively]. Longer duration of aspirin use in pregnancy tended to have a lower risk of hypoxia-related placental pathologies in the high-risk population. CONCLUSIONS: Aspirin use during pregnancy reduced risks of hypoxia-related placental pathologies in the high-risk women for preeclampsia. The duration of aspirin use determined its effects.

Copy number variation profile in noninvasive prenatal testing (NIPT) can identify co-existing maternal malignancies: Case reports and a literature review.

OBJECTIVE: The coexistence of maternal malignancy and pregnancy has received increasing attention in Noninvasive prenatal testing (NIPT) studies. Malignancy in pregnant women potentially affects the copy number variation (CNV) profile in NIPT results. Only one case of hematologic cancer has been reported in a Hong-Kong pregnant women, and solid tumors have never been reported in pregnant Chinese women. CASE REPORT: The patients with dysgerminoma and cervical cancer showed aberrant chromosomal aneuploidies in NIPT and concordant patterns of genome disruption in tumor tissues. The genomic aberrations in the gastric cancer patient had similar copy number variation pattern of gastric cancer. CONCLUSION: The findings in this study and the literature review further validate the effect of maternal malignancy on the copy number variation profile in NIPT data and strengthen the possibility of detecting malignant tumors with NIPT in the future.