Imbalanced graph learning via mixed entropy minimization.

Imbalanced datasets, where the minority class is underrepresented, pose significant challenges for node classification in graph learning. Traditional methods often address this issue through synthetic oversampling techniques for the minority class, which can complicate the training process. To address these challenges, we introduce a novel training paradigm for node classification on imbalanced graphs, based on mixed entropy minimization (ME). Our proposed method, GraphME, offers a 'free imbalance defense' against class imbalance without requiring additional steps to improve classification performance. ME aims to achieve the same goal as cross-entropy-maximizing the model's probability for the correct classes-while effectively reducing the impact of incorrect class probabilities through a "guidance" term that ensures a balanced trade-off. We validate the effectiveness of our approach through experiments on multiple datasets, where GraphME consistently outperforms the traditional cross-entropy objective, demonstrating enhanced robustness. Moreover, our method can be seamlessly integrated with various adversarial training techniques, leading to substantial improvements in robustness. Notably, GraphME enhances classification accuracy without compromising efficiency, a significant improvement over existing methods. The GraphME code is available at: https://github.com/12chen20/GraphME .

Sex differences in the risk of excessive daytime sleepiness in mild and moderate ischaemic stroke patients: a retrospective database study.

BACKGROUND: Excessive daytime sleepiness (EDS) is a common complication of stroke that has a detrimental effect on patients' daily life and functional recovery. The clinical characteristics and risk factors for poststroke EDS may differ between males and females. METHODS: A retrospective study based on hospital medical records was conducted on patients with a diagnosis of stroke who participated in polysomnographic monitoring at the Affiliated Hospital of Yangzhou University from February 2022 to May 2024. Baseline data, laboratory test data, polysomnographic data, and related scale scores were retrospectively collected. The Epworth Sleepiness Scale (ESS) score was used to assess EDS after stroke. Binary logistic regression was used to determine the risk factors for daytime sleepiness. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Statistical analysis was performed via IBM SPSS 26.0. RESULTS: ESS scores were higher in males than in females, whereas females had higher Pittsburgh Sleep Quality Index (PSQI) scores and Hospital Anxiety and Depression Scale (HADS) scores. Male sex and higher depression scores were risk factors for EDS; among male patients, higher anxiety scores were a risk factor for EDS, whereas smoking was a protective factor. Depression, a higher arousal index and a reduced proportion of N3 sleep periods were risk factors for EDS in females. CONCLUSIONS: The characteristics and influencing factors of EDS differ between the sexes in patients with mild and moderate ischaemic stroke. Our study may provide evidence and guidance for clinical diagnosis and treatment. Interventional studies are needed to assess the impact of treating these risk factors in the future.

Improving prediction performance of general protein language model by domain-adaptive pretraining on DNA-binding protein.

DNA-protein interactions exert the fundamental structure of many pivotal biological processes, such as DNA replication, transcription, and gene regulation. However, accurate and efficient computational methods for identifying these interactions are still lacking. In this study, we propose a method ESM-DBP through refining the DNA-binding protein sequence repertory and domain-adaptive pretraining based the general protein language model. Our method considers the lacking exploration of general language model for DNA-binding protein domain-specific knowledge, so we screen out 170,264 DNA-binding protein sequences to construct the domain-adaptive language model. Experimental results on four downstream tasks show that ESM-DBP provides a better feature representation of DNA-binding protein compared to the original language model, resulting in improved prediction performance and outperforming the state-of-the-art methods. Moreover, ESM-DBP can still perform well even for those sequences with only a few homologous sequences. ChIP-seq on two predicted cases further support the validity of the proposed method.

CSLens: Towards Better Deploying Charging Stations via Visual Analytics -- A Coupled Networks Perspective.

In recent years, the global adoption of electric vehicles (EVs) has surged, prompting a corresponding rise in the installation of charging stations. This proliferation has underscored the importance of expediting the deployment of charging infrastructure. Both academia and industry have thus devoted to addressing the charging station location problem (CSLP) to streamline this process. However, prevailing algorithms addressing CSLP are hampered by restrictive assumptions and computational overhead, leading to a dearth of comprehensive evaluations in the spatiotemporal dimensions. Consequently, their practical viability is restricted. Moreover, the placement of charging stations exerts a significant impact on both the road network and the power grid, which necessitates the evaluation of the potential post-deployment impacts on these interconnected networks holistically. In this study, we propose CSLens, a visual analytics system designed to inform charging station deployment decisions through the lens of coupled transportation and power networks. CSLens offers multiple visualizations and interactive features, empowering users to delve into the existing charging station layout, explore alternative deployment solutions, and assess the ensuring impact. To validate the efficacy of CSLens, we conducted two case studies and engaged in interviews with domain experts. Through these efforts, we substantiated the usability and practical utility of CSLens in enhancing the decision-making process surrounding charging station deployment. Our findings underscore CSLens's potential to serve as a valuable asset in navigating the complexities of charging infrastructure planning.

Photoinduced Palladium-Catalyzed Radical Germylative Arylation of Alkenes with Chlorogermanes.

We describe a visible light-induced palladium-catalyzed radical germylative arylation of alkenes with easily accessible chlorogermanes. This protocol provides expedient access to germanium-substituted indolin-2-ones in good to excellent yields under mild reaction conditions. The key step for this strategy lies in the reductive activation of germanium-chloride bonds with an excited palladium complex under visible light irradiation. The involvement of germanium radicals was evidenced by electron paramagnetic resonance spectroscopy experiments.

Porous Magnetic Soft Grippers for Fast and Gentle Grasping of Delicate Living Objects.

Magnetic soft grippers have attracted intensive interest due to their untethered controllability, rapid response, and biological safety. However, manipulating living objects requires a simultaneous increase in shape adaptability and gripping force, which are typically mutually exclusive. Increasing the magnetic particle content enhances the magnetic strength but also increases the elastic modulus, leading to low adaptability and high impact force. Here, a porous magnetic soft gripper (PMSG) is developed by integrating a porous structure into a magnetic silicone elastomer. The design of porous hard magnetic composite is characterized by high magnetization, low modulus, and rough surface. It offers the PMSG good compliance, high gripping force, and low impact force at fast gripping. The PMSG is capable of performing a variety of tasks, including the fast and gentle grasping of delicate living objects. The study provides insight into the design of novel magnetic grippers and may offer a promising outlook for biomedical or scientific applications in the manipulation of delicate organisms.

Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province.

The United States Environmental Protection Agency (USEPA) Four-step-Method (FSM) is a straightforward and extensively utilized tool for evaluating regional health risks, However, the complex and heterogeneous groundwater environment system causes great uncertainty in the assessment process. Triangular stochastic simulation (TSS) possesses certain advantages in solving uncertainty problems, but its inadequacy with discrete data reveals limitations in this aspect. To solve the above problems, this study proposes to construct trapezoidal fuzzy number-Monte Carlo stochastic simulation (TFN-MCSS) to compensate for the shortcomings of the first two methods. This method adopted trapezoidal fuzzy number (TFN) analysis to comprehensively consider the characteristics of a large dispersion of water quality monitoring data and the uncertainty of the human health risk assessment (HHRA) process. Concurrently, to overcome the subjectivity and uncertainty of artificially determining the interval of TFN in traditional methods, the slope was used to select the most probable interval value (TMPIV) of TFN combined with the α-truncated set technique (α-TST) and MCSS. Based on these, a TFN-MCSS was constructed and applied to groundwater HHRA in western Jilin Province. First, the groundwater chemical characteristic determination and water quality evaluation in western Jilin were performed to identify the main pollution indicators, and the health risk effects of pollutants in groundwater of different aquifers at different time periods on adults and children were evaluated using the TFN-MCSS. The uncertainty and sensitivity were analyzed, and the primary risk control indicators were identified and compared to FSM and TSS. The results reveal that TFN-MCSS was more sensitive to data and could reduce the uncertainty of assessment process. It indicated that over a 10-year period, the health risks associated with unconfined groundwater (UW) and confined water (CW) decreased by greater than 52 %. However, the highest total non-carcinogenic risk index (THI) was 1.3-fold higher than the safety threshold, and this posed a health risk.

Emission characteristics of lead and particulate matter from lead and zinc smelters in China.

Understanding the emission characteristics of particulate matter and associated heavy metals is essential for assessing their environmental and health impacts post-emission, as well as for identifying potential control technologies for the sources. Here, a field test was conducted at two advanced smelting plants equipped with comprehensive air pollution control devices. The particles emitted from different stages of lead and zinc smelting exhibited bi-modal size distributions, with peaks observed in PM0.1-1.0 and PM2.5-10, respectively. Particulate-bound Pb was identified as the predominant Pb species in the flue gas, primarily originating from ore crushing. Consequently, over 80 % of Pb was emitted in the form of coarse particles, a marked contrast to coal-fired power plants where Pb concentrated on fine particles. High efficiencies in Pb removal were achieved by dust collectors, flue gas purification systems, and acid plants with desulfurization systems, resulting in overall Pb emission factors in lead and zinc smelting were only 89.3 and 2.60 g t-1 (of metal production), respectively. Importantly, the contribution of gas-phase Pb, which accounts for approximately 16.6 % of total emissions, must not be neglected in future emission monitoring and control efforts.

A first report of Streptococcus iniae infection of the spotted sea bass (Lateolabrax maculates).

This study marks the first occasion that Streptococcus iniae has been isolated, identified, and characterized as the causative pathogen in spotted sea bass (Lateolabrax maculates). Infected fish exhibited a range of external symptoms, including scale loss, bleeding from the jaw, anus, and tail, among other signs, as well as internal manifestations such as congested liver, splenomegaly, branchial anemia, yellow fat syndrome, and intestinal edema. Notably, exophthalmia and meningoencephalitis-typical symptoms associated with previous S. iniae infections-were not observed. A predominant bacterial isolate (designated 10S01) was recovered from the pure culture of spleen of a diseased spotted sea bass in Zhuhai, China. The strain was then subjected to Gram staining, biochemical profiling, and molecular confirmation through 16S rRNA and gyrB gene, corroborating its identity as S. iniae. Pathogenicity was assessed by intraperitoneal injection challenge in spotted sea bass weighing approximately 13 g/fish, revealing a LD50 of 74 cfu/g-fish. The 10S01 strain demonstrated the ability to colonize various organs, including the spleen, liver, kidney, and brain, with a relatively higher affinity for the spleen. Furthermore, antimicrobial susceptibility testing indicated that the 10S01 strain was sensitive to 14 tested antibiotics, particularly chloramphenicol, ciprofloxacin, clarithromycin, florfenicol, ofloxacin, rifampicin, and trimethoprim/sulfamethoxazole, highlighting these as preferred treatments for S. iniae infections in spotted sea bass. These findings contribute significantly to our understanding of S. iniae pathogenesis and inform the prompt and appropriate antibiotic treatment of S. iniae infections.

Intramolecular Hosomi-Sakurai Reaction for the Synthesis of Benzoxasiloles.

A Lewis acid-catalyzed intramolecular Hosomi-Sakurai reaction of o-(allylsilyl)benzaldehyde/ketone has been developed. The reaction proceeds through simultaneous C-Si bond cleavage and C-C bond reconstruction. This protocol provides a rapid approach for the synthesis of allyl-substituted benzoxasiloles under mild conditions.

MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA-disease associations prediction.

MicroRNAs (miRNAs) synergize with various biomolecules in human cells resulting in diverse functions in regulating a wide range of biological processes. Predicting potential disease-associated miRNAs as valuable biomarkers contributes to the treatment of human diseases. However, few previous methods take a holistic perspective and only concentrate on isolated miRNA and disease objects, thereby ignoring that human cells are responsible for multiple relationships. In this work, we first constructed a multi-view graph based on the relationships between miRNAs and various biomolecules, and then utilized graph attention neural network to learn the graph topology features of miRNAs and diseases for each view. Next, we added an attention mechanism again, and developed a multi-scale feature fusion module, aiming to determine the optimal fusion results for the multi-view topology features of miRNAs and diseases. In addition, the prior attribute knowledge of miRNAs and diseases was simultaneously added to achieve better prediction results and solve the cold start problem. Finally, the learned miRNA and disease representations were then concatenated and fed into a multi-layer perceptron for end-to-end training and predicting potential miRNA-disease associations. To assess the efficacy of our model (called MUSCLE), we performed 5- and 10-fold cross-validation (CV), which got average the Area under ROC curves of 0.966${\pm }$0.0102 and 0.973${\pm }$0.0135, respectively, outperforming most current state-of-the-art models. We then examined the impact of crucial parameters on prediction performance and performed ablation experiments on the feature combination and model architecture. Furthermore, the case studies about colon cancer, lung cancer and breast cancer also fully demonstrate the good inductive capability of MUSCLE. Our data and code are free available at a public GitHub repository: https://github.com/zht-code/MUSCLE.git.

MUC4 O-GlcNAcylation Regulates the Epithelial Phenotype in Conjunctival Epithelial Cells.

In the present study, our aim was to explore the role of MUC4 in IL-4-stimulated conjunctival epithelial cells and the underlying mechanisms. Human recombinant IL-4 was employed in human conjunctival epithelial cells (HConEpic) cells, and MUC4 shRNA (sh-MUC4) was constructed to explore the functional role of MUC4. The protein level of MUC4, O-GlcNAc transferase (OGT), O-GlcNAc hydrolase (OGA), zonula occludens 1 (ZO-1), gap junction protein beta 2 (GJB2), claudin-8 (CLDN8), and E-cadherin were detected by Western blot in HConEpic cells, the interaction between MUC4 and OGT/OGA was assessed by co-immunoprecipitation (IP) and Western blot in 293T cells. Our results showed that IL-4 significantly up-regulated MUC4 and OGT protein levels in HConEpic cells, while down-regulated OGA protein level. Also, IL-4 down-regulated ZO-1, GJB2, CLDN8, and E-cadherin protein levels in HConEpic cells, while which was markedly reversed by sh-MUC4. Additionally, OGT inhibitor significantly reduced MUC4 protein level, and elevated ZO-1, GJB2, CLDN8, and E-cadherin protein levels in HConEpic cells, while OGA inhibitor resulted in the opposite results. Furthermore, in addition to the interaction between OGT/OGA and MUC4, Co-IP and Western blot also revealed the alteration of MUC4 O-GlcNAcylation in 293T cells treated with OGT/OGA inhibitor. Above findings suggested that OGT/OGA inhibitor regulated MUC4 protein level by affecting MUC4 O-GlcNAcylation to regulate ZO-1, GJB2, CLDN8, and E-cadherin protein levels in HConEpic cells, which was achieved via inhibiting the interaction between OGT/OGA and MUC4. This study may provide a better understanding of the pathogenesis of allergic conjunctivitis (AC).

Patterns of peripartum depression and anxiety during the pre-vaccine COVID-19 pandemic.

BACKGROUND: Pregnant people are vulnerable to new or worsening mental health conditions. This study aims to describe prevalence and course of depression and anxiety symptoms in pregnancy during the pre-vaccine COVID-19 pandemic. METHODS: This is a prospective cohort study of pregnant individuals with known or suspected COVID-19. Participants completed Edinburgh Postnatal Depression Scale (EPDS) and Generalized-Anxiety Disorder-7 (GAD-7) questionnaires, screening tools for depression and anxiety, at 34weeks gestational age, 6-8weeks postpartum, and 6months postpartum. Prevalence of elevated depressive and anxiety symptoms at each visit was described. Univariable logistic regression analysis was used to determine the association between demographic and clinical factors and those with elevated depression or anxiety symptoms. RESULTS: 317 participants were included. The prevalence of elevated antepartum depression symptoms was 14.6%, 10.3%, and 20.6% at 34weeks gestational age, 6-8weeks postpartum, and 6months postpartum, respectively. The rate of elevated anxiety symptoms was 15.1%, 10.0%, and 17.3% at 34weeks gestational age, 6-8weeks postpartum, and 6months postpartum, respectively. A prior history of depression and/or anxiety (p's < 0.03), as well as higher EPDS and GAD-7 scores at enrollment (p's < 0.04) associated with elevated depression and anxiety symptoms throughout pregnancy and the postpartum period. Quarantining during pregnancy was associated with elevated anxiety symptoms at 34weeks gestational age in univariate (P = 0.027) analyses. COVID-19 diagnosis and hospitalization were not associated with elevated depression or anxiety symptoms. CONCLUSIONS: Elevated depression and anxiety symptoms were prevalent throughout pregnancy and the postpartum period, particularly in those with prior depression and/or anxiety and who quarantined. Strategies that target social isolation may mitigate potential adverse consequences for pregnant people, and continued vigilance in recognition of depression and anxiety in pregnancy should be considered.

Effect of GnRH Active Immunisation on Reproductive Performance of Male Sprague Dawley Rats.

To investigate the effect of active immunisation with gonadotropin-releasing hormone (GnRH) on the reproductive function in male Sprague Dawley (SD) rats, 24 42-day-old rats were randomly assigned to treatment with GnRH6-MAP, GnRH-OVA, a surgical castration group, and a blank control group. Each rat in the treatment groups was intramuscularly injected at 6, 8, and 10 weeks of age. The serum concentrations of testosterone (T), follicle-stimulating hormone (FSH), luteinising hormone (LH), and anti-GnRH antibodies were determined using enzyme-linked immunosorbent assays. The results showed that active immunisation with recombinant GnRH6-MBP and GnRH-OVA significantly increased the serum levels of anti-GnRH antibodies and reduced the serum concentrations of testosterone compared to the black control. Eight weeks after immunisation, the rats' testes were surgically removed for morphological evaluation, showing atrophy of the convoluted vasculature, relative emptying of the lumen, and insignificant differentiation of spermatogonial cells, which were increased in weight and volume compared with the blank control group. These findings indicated that active immunisation with GnRH can lead to testicular atrophy and reduce gonadal hormone concentrations, suggesting that GnRH is a highly effective immunogen.

A Scalable and Robust Chloroplast Genotyping Solution: Development and Application of SNP and InDel Markers in the Maize Chloroplast Genome.

Maize(Zea mays. L) is a globally important crop, and understanding its genetic diversity is crucial for plant breeding phylogenetic analyses and comparative genetics. While nuclear markers have been extensively used for mapping agriculturally important genes, they are limited in recognizing characteristics, such as cytoplasmic male sterility and reciprocal cross hybrids. In this study, we performed next-generation sequencing of 176samples, and the maize cultivars represented five distinct groups. A total of 89 single nucleotide polymorphisms (SNPs) and 11 insertion/deletion polymorphisms (InDels) were identified. To enable high-throughput detection, we successfully amplified and confirmed 49 SNP and InDel markers, which were defined as a Varietal Chloroplast Panel (VCP) using the Kompetitive Allele Specific PCR (KASP). The specific markers provided a valuable tool for identifying chloroplast groups. The verification experiment, focusing on the identification of reciprocal cross hybrids and cytoplasmic male sterility hybrids, demonstrated the significant advantages of VCP markers in maternal inheritance characterization. Furthermore, only a small subset of these markers is needed to provide useful information, showcasing the effectiveness of these markers in elucidating the artificial selection process of elite maize lines.

SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival.

Accurately predicting the survival rate of cancer patients is crucial for aiding clinicians in planning appropriate treatment, reducing cancer-related medical expenses, and significantly enhancing patients' quality of life. Multimodal prediction of cancer patient survival offers a more comprehensive and precise approach. However, existing methods still grapple with challenges related to missing multimodal data and information interaction within modalities. This paper introduces SELECTOR, a heterogeneous graph-aware network based on convolutional mask encoders for robust multimodal prediction of cancer patient survival. SELECTOR comprises feature edge reconstruction, convolutional mask encoder, feature cross-fusion, and multimodal survival prediction modules. Initially, we construct a multimodal heterogeneous graph and employ the meta-path method for feature edge reconstruction, ensuring comprehensive incorporation of feature information from graph edges and effective embedding of nodes. To mitigate the impact of missing features within the modality on prediction accuracy, we devised a convolutional masked autoencoder (CMAE) to process the heterogeneous graph post-feature reconstruction. Subsequently, the feature cross-fusion module facilitates communication between modalities, ensuring that output features encompass all features of the modality and relevant information from other modalities. Extensive experiments and analysis on six cancer datasets from TCGA demonstrate that our method significantly outperforms state-of-the-art methods in both modality-missing and intra-modality information-confirmed cases. Our codes are made available at https://github.com/panliangrui/Selector.

Smartwatch detection of new-onset monomorphic ventricular tachycardia in pregnancy.

Smartwatches provide health tracking in various ways and there has been a recent rise in reporting cardiac arrhythmias. While original studies focused on atrial fibrillation, fewer reports have been made on other arrhythmias especially in pregnancy. We report a pregnant patient who presented at 34 weeks' gestation with palpitations. An ECG recorded through her Apple Watch showed ventricular tachycardia. Hospital ECG confirmed monomorphic ventricular tachycardia likely caused by increased sympathetic tone from the gravid state. She was admitted to the cardiac intensive care unit for close monitoring with intravenous anti-arrhythmic agents; however, the rhythm persisted. She underwent a caesarean delivery and the arrhythmia resolved post partum. She later underwent a catheter ablation, after which she discontinued all anti-arrhythmic medications with no recurrence. This case highlights the importance of requesting relevant digital health information, if available, from patients in our modern era. Controlled clinical studies are needed to validate such practices.

Evaluation of the immunoprotective effect of the recombinant Eimeria intestinalis rhoptry protein 25 and rhoptry protein 30 on New Zealand rabbits.

BACKGROUND: Rabbit coccidiosis is a parasitism caused by either one or multiple co-infections of Eimeria species. Among them, Eimeria intestinalis is the primary pathogen responsible for diarrhea, growth retardation, and potential mortality in rabbits. Concerns regarding drug resistance and drug residues have led to the development of recombinant subunit vaccines targeting Eimeria species as a promising preventive measure. The aim of this study was to assess the immunoprotective efficacy of recombinant subunit vaccines comprising EiROP25 and EiROP30 (rhoptry proteins (ROPs)) against E. intestinalis infection in rabbits. METHODS: Cloning, prokaryotic expression, and protein purification were performed to obtain EiROP25 and EiROP30. Five groups of fifty 35-day-old Eimeria-free rabbits were created (unchallenged control group, challenged control group, vector protein control group, rEiROP25 group, and rEiROP30 group), with 10 rabbits in each group. Rabbits in the rEiROP25 and rEiROP30 groups were immunized with the recombinant proteins (100 µg per rabbit) for primary and booster immunization (100 µg per rabbit) at a two-week intervals, and challenged with 7 × 104 oocysts per rabbit after an additional two-week interval. Two weeks after the challenge, the rabbits were euthanized for analysis. Weekly collections of rabbit sera were made to measure changes in specific IgG and cytokine level. Clinical symptoms and pathological changes after challenge were observed and recorded. At the conclusion of the animal experiment, lesion scores, the relative weight increase ratio, the oocyst reduction rate, and the anticoccidial index were computed. RESULTS: Rabbits immunized with rEiROP25 and rEiROP30 exhibited relative weight gain ratios of 56.57% and 72.36%, respectively. Oocysts decreased by 78.14% and 84.06% for the rEiROP25 and rEiROP30 groups, respectively. The anticoccidial indexes were 140 and 155. Furthermore, there was a noticeable drop in intestinal lesions. After the primary immunization with rEiROP25 and rEiROP30, a week later, there was a notable rise in specific IgG levels, which remained elevated for two weeks following challenge (P < 0.05). Interleukin (IL)-2 levels increased markedly in the rEiROP25 group, whereas IL-2, interferon gamma (IFN-γ), and IL-4 levels increased substantially in the rEiROP30 group (P < 0.05). CONCLUSION: Immunization of rabbits indicated that both rEiROP25 and rEiROP30 are capable of inducing an increase in specific antibody levels. rEiROP25 triggered a Th1-type immune protection response, while rEiROP30 elicited a Th1/Th2 mixed response. EiROP25 and EiROP30 can generate a moderate level of immune protection, with better efficacy observed for EiROP30. This study provides valuable insights for the promotion of recombinant subunit vaccines targeting rabbit E. intestinalis infection.

Copper-Catalyzed Asymmetric Synthesis of Silicon-Stereogenic Benzoxasiloles.

A Cu-catalyzed asymmetric synthesis of silicon-stereogenic benzoxasiloles has been realized via intramolecular Si-O coupling of [2-(hydroxymethyl)phenyl]silanes. Cu(I)/difluorphos is found to be an efficient catalytic system for enantioselective Si-C bond cleavage and Si-O bond formation. In addition, kinetic resolution of racemic substituted [2-(hydroxymethyl)phenyl]silanes using Cu(I)/ PyrOx (pyridine-oxazoline ligands) as the catalytic system is developed to afford carbon- and silicon-stereogenic benzoxasiloles. Ring-opening reactions of chiral benzoxasiloles with organolithiums and Grignard reagents yield various enantioenriched functionalized tetraorganosilanes.

Catalytic Synthesis of Silanols by Hydroxylation of Hydrosilanes: From Chemoselectivity to Enantioselectivity.

As a crucial class of functional molecules in organosilicon chemistry, silanols are found valuable applications in the fields of modern science and will be a potentially powerful framework for biologically active compounds or functional materials. It has witnessed an increasing demand for non-natural organosilanols, as well as the progress in the synthesis of these structural features. From the classic preparative methods to the catalytic selective oxidation of hydrosilanes, electrochemical hydrolysis of hydrosilanes, and then the construction of the most challenging silicon-stereogenic silanols. This review summarized the progress in the catalyzed synthesis of silanols via hydroxylation of hydrosilanes in the last decade, with a particular emphasis on the latest elegant developments in the desymmetrization strategy for the enantioselective synthesis of silicon-stereogenic silanols from dihydrosilanes.