Mid-Pleistocene links between Asian dust, Tibetan glaciers, and Pacific iron fertilization.

Increasing Asian dust fluxes, associated with late Cenozoic cooling and intensified glaciations, are conventionally thought to drive iron fertilization of phytoplankton productivity in the North Pacific, contributing to ocean carbon storage and drawdown of atmospheric CO2. During the early Pleistocene glaciations, however, productivity remained low despite higher Asian dust fluxes, only displaying glacial stage increases after the mid-Pleistocene climate transition (~800 ka B.P.). We solve this paradox by analyzing an Asian dust sequence, spanning the last 3.6 My, from the Tarim Basin, identifying a major switch in the iron composition of the dust at ~800 ka, associated with expansion of Tibetan glaciers and enhanced production of freshly ground rock minerals. This compositional shift in the Asian dust was recorded synchronously in the downwind, deep sea sediments of the central North Pacific. The switch from desert dust, containing stable, highly oxidized iron, to glacial dust, richer in reactive reduced iron, coincided with increased populations of silica-producing phytoplankton in the equatorial North Pacific and increased primary productivity in more northerly locations, such as the South China Sea. We calculate that potentially bioavailable Fe2+ flux to the North Pacific was more than doubled after the switch to glacially- sourced dust. These findings indicate a positive feedback between Tibetan glaciations, glaciogenic production of dust with enhanced iron bioavailability, and changes in North Pacific iron fertilization. Notably, this strengthened link between climate and eolian dust coincided with the mid-Pleistocene transition to increased storage of C in the glacial North Pacific and more intense northern hemisphere glaciations.

Porcine Deltacoronavirus Infection Disrupts the Intestinal Mucosal Barrier and Inhibits Intestinal Stem Cell Differentiation to Goblet Cells via the Notch Signaling Pathway.

Goblet cells and their secreted mucus are important elements of the intestinal mucosal barrier, which allows host cells to resist invasion by intestinal pathogens. Porcine deltacoronavirus (PDCoV) is an emerging swine enteric virus that causes severe diarrhea in pigs and causes large economic losses to pork producers worldwide. To date, the molecular mechanisms by which PDCoV regulates the function and differentiation of goblet cells and disrupts the intestinal mucosal barrier remain to be determined. Here, we report that in newborn piglets, PDCoV infection disrupts the intestinal barrier: specifically, there is intestinal villus atrophy, crypt depth increases, and tight junctions are disrupted. There is also a significant reduction in the number of goblet cells and the expression of MUC-2. In vitro, using intestinal monolayer organoids, we found that PDCoV infection activates the Notch signaling pathway, resulting in upregulated expression of HES-1 and downregulated expression of ATOH-1 and thereby inhibiting the differentiation of intestinal stem cells into goblet cells. Our study shows that PDCoV infection activates the Notch signaling pathway to inhibit the differentiation of goblet cells and their mucus secretion, resulting in disruption of the intestinal mucosal barrier. IMPORTANCE The intestinal mucosal barrier, mainly secreted by the intestinal goblet cells, is a crucial first line of defense against pathogenic microorganisms. PDCoV regulates the function and differentiation of goblet cells, thereby disrupting the mucosal barrier; however, the mechanism by which PDCoV disrupts the barrier is not known. Here, we report that in vivo, PDCoV infection decreases villus length, increases crypt depth, and disrupts tight junctions. Moreover, PDCoV activates the Notch signaling pathway, inhibiting goblet cell differentiation and mucus secretion in vivo and in vitro. Thus, our results provide a novel insight into the mechanism underlying intestinal mucosal barrier dysfunction caused by coronavirus infection.

BatchDTA: implicit batch alignment enhances deep learning-based drug-target affinity estimation.

Candidate compounds with high binding affinities toward a target protein are likely to be developed as drugs. Deep neural networks (DNNs) have attracted increasing attention for drug-target affinity (DTA) estimation owning to their efficiency. However, the negative impact of batch effects caused by measure metrics, system technologies and other assay information is seldom discussed when training a DNN model for DTA. Suffering from the data deviation caused by batch effects, the DNN models can only be trained on a small amount of 'clean' data. Thus, it is challenging for them to provide precise and consistent estimations. We design a batch-sensitive training framework, namely BatchDTA, to train the DNN models. BatchDTA implicitly aligns multiple batches toward the same protein through learning the orders of candidate compounds with respect to the batches, alleviating the impact of the batch effects on the DNN models. Extensive experiments demonstrate that BatchDTA facilitates four mainstream DNN models to enhance the ability and robustness on multiple DTA datasets (BindingDB, Davis and KIBA). The average concordance index of the DNN models achieves a relative improvement of 4.0%. The case study reveals that BatchDTA can successfully learn the ranking orders of the compounds from multiple batches. In addition, BatchDTA can also be applied to the fused data collected from multiple sources to achieve further improvement.

DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations.

Drug combination therapies are superior to monotherapy for cancer treatment in many ways. Identifying novel drug combinations by screening is challenging for the wet-lab experiments due to the time-consuming process of the enormous search space of possible drug pairs. Thus, computational methods have been developed to predict drug pairs with potential synergistic functions. Notwithstanding the success of current models, understanding the mechanism of drug synergy from a chemical-gene-tissue interaction perspective lacks study, hindering current algorithms from drug mechanism study. Here, we proposed a deep neural network model termed DTSyn (Dual Transformer encoder model for drug pair Synergy prediction) based on a multi-head attention mechanism to identify novel drug combinations. We designed a fine-granularity transformer encoder to capture chemical substructure-gene and gene-gene associations and a coarse-granularity transformer encoder to extract chemical-chemical and chemical-cell line interactions. DTSyn achieved the highest receiver operating characteristic area under the curve of 0.73, 0.78. 0.82 and 0.81 on four different cross-validation tasks, outperforming all competing methods. Further, DTSyn achieved the best True Positive Rate (TPR) over five independent data sets. The ablation study showed that both transformer encoder blocks contributed to the performance of DTSyn. In addition, DTSyn can extract interactions among chemicals and cell lines, representing the potential mechanisms of drug action. By leveraging the attention mechanism and pretrained gene embeddings, DTSyn shows improved interpretability ability. Thus, we envision our model as a valuable tool to prioritize synergistic drug pairs with chemical and cell line gene expression profile.

Anthropogenic effects on soils in the eastern Tibetan Plateau revealed by geochemical elemental characteristics.

The Tibetan Plateau (TP) constitutes a fragile and sensitive ecological environment, which is vulnerable to global climate change and human activities. To investigate the anthropogenic effects on the TP's environmental system is valuable for guiding human responses and adaptations to future environmental changes. In this study, we detailedly analyzed the geochemical elements of four representative soil sections developed on loess from Ganzi, Jinchuan, Aba, and Chuanzhusi in the eastern TP. The chemical elemental profiles distinctly indicated the presence of typical anthropogenic elements (Cu, Zn, Ni, Cr, Pb, Mn, and Fe), underscoring the substantial influence of human activities on TP soil, and showing spatial variance. Our results indicate that anthropogenic impacts were relatively low at Aba and Ganzi, resulting in a deficit of anthropogenic elements at the surface layer. Whereas at Jinchuan and Chuanzhusi, relatively intense anthropogenic impacts have led to the enrichment of anthropogenic elements in the topsoil. We infer that agricultural activities, increased traffic, and expansion of tourism activities were the major factors affecting the anthropogenic elements of TP soils. Our study highlights the impact of human activities on soil geochemical processes in the Tibetan Plateau.

HelixADMET: a robust and endpoint extensible ADMET system incorporating self-supervised knowledge transfer.

MOTIVATION: Accurate ADMET (an abbreviation for 'absorption, distribution, metabolism, excretion and toxicity') predictions can efficiently screen out undesirable drug candidates in the early stage of drug discovery. In recent years, multiple comprehensive ADMET systems that adopt advanced machine learning models have been developed, providing services to estimate multiple endpoints. However, those ADMET systems usually suffer from weak extrapolation ability. First, due to the lack of labelled data for each endpoint, typical machine learning models perform frail for the molecules with unobserved scaffolds. Second, most systems only provide fixed built-in endpoints and cannot be customized to satisfy various research requirements. To this end, we develop a robust and endpoint extensible ADMET system, HelixADMET (H-ADMET). H-ADMET incorporates the concept of self-supervised learning to produce a robust pre-trained model. The model is then fine-tuned with a multi-task and multi-stage framework to transfer knowledge between ADMET endpoints, auxiliary tasks and self-supervised tasks. RESULTS: Our results demonstrate that H-ADMET achieves an overall improvement of 4%, compared with existing ADMET systems on comparable endpoints. Additionally, the pre-trained model provided by H-ADMET can be fine-tuned to generate new and customized ADMET endpoints, meeting various demands of drug research and development requirements. AVAILABILITY AND IMPLEMENTATION: H-ADMET is freely accessible at https://paddlehelix.baidu.com/app/drug/admet/train. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Deep Learning with Geometry-Enhanced Molecular Representation for Augmentation of Large-Scale Docking-Based Virtual Screening.

Structure-based virtual screening has been a crucial tool in drug discovery for decades. However, as the chemical space expands, the existing structure-based virtual screening techniques based on molecular docking and scoring struggle to handle billion-entry ultralarge libraries due to the high computational cost. To address this challenge, people have resorted to machine learning techniques to enhance structure-based virtual screening for efficiently exploring the vast chemical space. In those cases, compounds are usually treated as sequential strings or two-dimensional topology graphs, limiting their ability to incorporate three-dimensional structural information for downstream tasks. We herein propose a novel deep learning protocol, GEM-Screen, which utilizes the geometry-enhanced molecular representation of the compounds docking to a specific target and is trained on docking scores of a small fraction of a library through an active learning strategy to approximate the docking outcome for yet nontraining entries. This protocol is applied to virtual screening campaigns against the AmpC and D4 targets, demonstrating that GEM-Screen enriches more than 90% of the hit scaffolds for AmpC in the top 4% of model predictions and more than 80% of the hit scaffolds for D4 in the same top-ranking size of library. GEM-Screen can be used in conjunction with traditional docking programs for docking of only the top-ranked compounds to avoid the exhaustive docking of the whole library, thus allowing for discovering top-scoring compounds from billion-entry libraries in a rapid yet accurate fashion.

The 3.6-Ma aridity and westerlies history over midlatitude Asia linked with global climatic cooling.

Midlatitude Asia (MLA), strongly influenced by westerlies-controlled climate, is a key source of global atmospheric dust, and plays a significant role in Earth's climate system . However, it remains unclear how the westerlies, MLA aridity, and dust flux from this region evolved over time. Here, we report a unique high-resolution eolian dust record covering the past 3.6 Ma, retrieved from the thickest loess borehole sequence (671 m) recovered to date, at the southern margin of the Taklimakan desert in the MLA interior. The results show that eolian dust accumulation, which is closely related to aridity and the westerlies, indicates existence of a dry climate, desert area, and stable land surface, promoting continuous loess deposition since at least ∼3.6 Ma. This region experienced long-term stepwise drying at ∼2.7, 1.1, and 0.5 Ma, coeval with a dominant periodicity shift from 41-ka cyclicity to 100-ka cyclicity between 1.1 Ma and 0.5 Ma. These features match well with global ice volume variability both in the time and frequency domains (including the Mid-Pleistocene Transition), highlighting global cooling-forced aridity and westerlies climate changes on these timescales. Numerical modeling demonstrates that global cooling can dry MLA and intensify the westerlies, which facilitates dust emission and transport, providing an interpretive framework. Increased dust may have promoted positive feedbacks (e.g., decreasing atmospheric CO2 concentrations and modulating radiation budgets), contributing to further cooling. Unraveling the long-term evolution of MLA aridity and westerlies climate is an indispensable component of the unfolding mystery of global climate change.

ESIPT fluorophores derived from 2,3-dichloro-5,6-dicyano-p-benzoquinone based carbon dots for dual emission and multiple anti-counterfeiting.

Fluorophores and hydrogen bonding interactions play key roles in the fluorescence properties of bottom-up carbon dots. In this work, an excited-state intramolecular proton-transfer (ESIPT) active fluorophore, 5-chloro-6-ethoxy-4,7-dihydroxyisoindoline-1,3-dione (CEDD) and a non-ESIPT 7-cyano-5,8-dihydroxyquinoxaline-6-carboxamide (CDQC) are extracted from 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ) based carbon dots. The enol form of CEDD shows a weak blue, small Stokes shift and short lifetime emission under the aprotic or alkali conditions, but the keto form exhibits a strong green, large Stokes shift and long lifetime emission in a protic or an acidic environment. Due to the lack of the ESIPT process, CDQC has no dual emission characteristics, but shows efficient solid-state emission. By virtue of the ESIPT ability of CEDD, multiple anti-counterfeiting methods are achieved by using hydrogen chloride, ammonia, and fluorescence lifetime imaging, as well as dimethyl sulfoxide as the encryption/decryption tools.

Development and validation of a nomogram for predicting the probability of new vertebral compression fractures after vertebral augmentation of osteoporotic vertebral compression fractures.

INTRODUCTION: New vertebral compression fractures (NVCFs) are adverse events after vertebral augmentation of osteoporotic vertebral compression fractures (OVCFs). Predicting the risk of vertebral compression fractures (VCFs) accurately after surgery is still a significant challenge for spinal surgeons. The aim of our study was to identify risk factors of NCVFs after vertebral augmentation of OVCFs and develop a nomogram. METHODS: We retrospectively reviewed the medical records of patients with OVCFs who underwent percutaneous vertebroplasty (PVP) or percutaneous kyphoplasty (PKP). Patients were divided into the NVCFs group and control group, base on the patients with or without NVCFs within 2 years follow-up period after surgery. A training cohort of 403 patients diagnosed in our hospital from June 2014 to December 2016 was used for model development. The independent predictive factors of postoperative VCFs were determined by least absolute shrinkage and selection operator (LASSO) logistic regression, univariate analysis and multivariate logistic regression analysis. We provided a nomogram for predicting the risk of NVCFs based on independent predictive factors and used the receiver operating characteristic curve (ROC), calibration curve, and decision curve analyses (DCA) to evaluated the prognostic performance. After internal validation, the nomogram was further evaluated in a validation cohort of 159 patients included between January 2017 and June 2018. RESULTS: Of the 403 patients in the training cohort, 49(12.16%) were NVCFs at an average of 16.7 (1 to 23) months within the 2 years follow-up period. Of the 159 patients in the validation cohort, 17(10.69%) were NVCFs at an average of 8.7 (1 to 15) months within the 2 years follow-up period. In the training cohort, the proportions of elderly patients older than 80 years were 32.65 and 13.56% in the NVCFs and control group, respectively (p = 0.003). The percentages of patients with previous fracture history were 26.53 and 12.71% in the NVCFs and control group, respectively (p = 0.010). The volume of bone cement were 4.43 ± 0.88 mL and 4.02 ± 1.13 mL in the NVCFs and Control group, respectively (p = 0.014). The differences have statistical significance in the bone cement leakage, bone cement dispersion, contact with endplate, anti-osteoporotic treatment, post-op Cobb angle and Cobb angle restoration characteristics between the two groups. The model was established by multivariate logistic regression analysis to obtain independent predictors. In the training and validation cohort, the AUC of the nomogram were 0.882 (95% confidence interval (CI), 0.824-0.940) and 0.869 (95% CI: 0.811-0.927), respectively. The C index of the nomogram was 0.886 in the training cohort and 0.893 in the validation cohort, demonstrating good discrimination. In the training and validation cohort, the optimal calibration curves demonstrated the coincidence between prediction and actual status, and the decision curve analysis demonstrated that the full model had the highest clinical net benefit across the entire range of threshold probabilities. CONCLUSION: A nomogram for predicting NVCFs after vertebral augmentation was established and validated. For patients evaluated by this model with predictive high risk of developing postoperative VCFs, postoperative management strategies such as enhance osteoporosis-related health education and management should be considered.

Clinical observation of two bone cement distribution modes after percutaneous vertebroplasty for osteoporotic vertebral compression fractures.

BACKGROUND: Current findings suggest that percutaneous vertebroplasty(PVP) is a suitable therapeutic approach for osteoporotic vertebral compression fractures (OVCFs). The present retrospective study aimed to investigate the differences in clinical efficacy and related complications between the two bone cement distribution modes. METHODS: We retrospectively reviewed the medical records of the patients with single-segment OVCFs who underwent bilateral percutaneous vertebroplasty. Patients were divided into blocky and spongy group according to the type of postoperative bone cement distribution. Clinical efficacy and related complications was compared between the two bone cement distribution modes on 24 h after the operation and last follow-up. RESULTS: A total of 329 patients with an average follow up time of 17.54 months were included. The blocky group included 131 patients, 109 females(83.2 %) and 22 males(16.8 %) with a median age of 72.69 ± 7.76 years, while the Spongy group was made up of 198 patients, 38 females(19.2 %) and 160 males(80.8 %) with a median age of 71.11 ± 7.36 years. The VAS and ODI after operation improved significantly in both two groups. The VAS and ODI in the spongy group was significantly lower than that in the blocky group, 24 h postoperatively, and at the last follow-up. There were 42 cases (12.8 %) of adjacent vertebral fractures, 26 cases (19.8 %) in the blocky group and 16 cases (8.1 %) in the spongy group. There were 57 cases (17.3 %) of bone cement leakage, 18 cases (13.7 %) in blocky group and 39 cases (19.7 %) in the spongy group. At 24 h postoperatively and at the last follow-up, local kyphosis and anterior vertebral height were significantly corrected in both groups, but gradually decreased over time, and the degree of correction was significantly higher in the spongy group than in the block group. The change of local kyphosis and loss of vertebral body height were also less severe in the spongy group at the last follow-up. CONCLUSIONS: Compared with blocky group, spongy group can better maintain the height of the vertebral body, correct local kyphosis, reduce the risk of the vertebral body recompression, long-term pain and restore functions.

Transcriptome sequencing analysis of porcine MDM response to FSL-1 stimulation.

Mycoplasma infection can cause many diseases in pigs, resulting in great economic losses in pork production. Innate immune responses are thought to play critical roles in the pathogenesis of mycoplasma disease. However, the molecular events involved in immune responses remain to be determined. Hence, the object of this study was to use RNA-Seq to investigate the gene expression profiles of the innate immune response mediated by FSL-1 in pig monocyte-derived macrophages (MDMs). The results revealed that 1442 genes were differentially expressed in the FSL-1 group compared with the control groups, of which 777 genes were upregulated and 665 genes were downregulated. KEGG pathway analysis showed that the upregulated genes were mainly involved in innate immune-related pathways including the TNF signaling pathway, cytokine-cytokine receptor interaction, Toll-like receptor signaling pathway, Jak-STAT signaling pathway, chemokine signaling pathway, NOD-like receptor signaling pathway and NF-kappa B signaling pathway. The downregulated genes were only involved in the cGMP-PKG signaling pathway and glycerophospholipid metabolism. Our results showed that FSL-1 stimulation activated the TLR2 signaling pathway and resulted in diverse inflammatory responses. FSL-1 induced the transcription of numerous protein-coding genes involved in a complex network of innate immune-related pathways. We speculate that TNF, IL1B, IL6, NFKB1, NFKBIA, CXCL2, CXCL8, CXCL10, CCL2, CCL4 and CCL5 were the most likely hub genes that play important roles in the above pathways. This study identified the differentially expressed genes and their related signaling pathways, contributing to the comprehensive understanding of the mechanisms underlying host-pathogen interactions during mycoplasma infection and providing a reference model for further studies.

Reversible Ligand-Gated Ion Channel via Interconversion between Hollow Single Helix and Intertwined Double Helix.

Ligand responsiveness is one of the typical mechanisms in biological organization to trigger sophisticated channel switching. Here, we report a new type of helical trimer which can undergo transition between a hollow single helix and an intertwined double helix with no cavity by complexation and decomplexation of Cu ions. In addition, the one dimensional (1D) hollow helical tubes spontaneously generated from single helices via π-π interactions embedded into the lipid bilayers and displayed satisfactory channel stability and efficiency. With the addition of CuI ions and further extraction with ammonia, the disassembly and reassembly of 1D hollow helical tubes gave rise to the reversible switching of channel activity in situ inside the bilayers. The synthetic helical system provides the first model of reversible ligand-gated ion channel by means of dynamic transition between single and double helices, which will be available for developing intelligent artificial nanochannels for potential biological and medicinal applications.

Polymer spacer tunable Purcell-enhanced spontaneous emission in perovskite quantum dots coupled to plasmonic nanowire networks.

Lead halide perovskite quantum dots (PQDs) have recently been proposed as a scalable and color-tunable quantum source, but their slow spontaneous emission creates a mismatch with high-speed nanophotonic devices. Here, we demonstrate fast and bright emission in PQD films coupled to silver nanowire networks (NWKs), in which polyvinyl alcohol (PVA) is used as a spacer to regulate the lossy characteristics of the plasmonic cavity. Compared with bare quartz, the PVA substrate shows a considerable enhancement effect on the apparent emission intensity, but a reduction in the emission rate of PQD excitons. The efficient NWK-PQD coupling generates an increase in the emission intensity of a factor of 6.0 (average 3.4) and simultaneously a 2.4-fold (average 1.9) enhancement in the emission rate. However, an opposite PVA spacer thickness dependence for Purcell factor and quantum yield is observed, indicating that the fast and bright emission would be a trade-off between the Purcell-enhanced radiative rate and large metal loss. These results are believed to provide fundamental guidance on plasmonic cavity design for perovskite-based nanophotonic devices.

Iron-Mediated Synthesis of Isoxazoles from Alkynes: Using Iron(III) Nitrate as a Nitration and Cyclization Reagent.

A simple and direct method for the iron(III) nitrate-mediated synthesis of isoxazoles from alkynes has been developed; both self-coupling and cross-coupling products could be successfully prepared from alkynes. Meanwhile, for the cross-coupling and cyclizing of two different alkynes examined, the iron-mediated system shows a good chemoselectivity for the synthesis of corresponding isoxazoles. In our method, cheap and eco-friendly iron(III) nitrate is used as the nitration and cyclization reagent, and KI is used as the additive; they both play a positive role in this transformation. Furthermore, a different mechanism for the formation of isoxazoles from alkynes has been proposed.

Investigation of Eph-ephrin A1 in the regulation of embryo implantation in sows.

Eph A1 and ephrin A1 (Eph-ephrin A1) is a key receptor-ligand pair of Eph-ephrin system, which plays important roles in the migration and adhesion of cells, tissue morphogenesis and vasculogenesis in mammals. In order to investigate the regulation of Eph-ephrin A1 during porcine embryo implantation, the expressions of mRNA and protein of Eph-ephrin A1 were detected in different reproductive tissues from twelve sows during embryo implantation period on pregnancy day 13, 18 and 24, respectively. Functions of Eph-ephrin A1 on the migration and adhesion of porcine endometrial epithelial cells were analysed by RNA interference (RNAi), transwell migration assays and MTT assays. Results showed that mRNA levels of Eph-ephrin A1 were highly expressed in endometrial attachment site when compared to other reproductive tissues (p < 0.05) and were peaked on pregnancy day 18 during embryo implantation (p < 0.05). Protein levels of Eph-ephrin A1 were highly expressed in endometrial attachment site and were peaked on pregnancy day 18 (p < 0.05). Eph-ephrin A1 proteins were located in endometrial luminal epithelium, stroma of attachment site and inter-attachment site during embryo implantation, and the protein levels were higher during implantation compared to pre-implantation or post-implantation. Furthermore, silencing ephrin A1 gene significantly reduced the migration and adhesion capacity of porcine endometrial epithelial cells. These findings suggest that the Eph-ephrin A1 protein likely targets endometrial attachment site to enhance the migration and adhesion of porcine endometrial epithelial cells around pregnancy day 18 during pregnancy in sows.

Base-Mediated Synthesis of Unsymmetrical 1,3,5-Triazin-2-amines via Three-Component Reaction of Imidates, Guanidines, and Amides or Aldehydes.

A simple and efficient method for the base-mediated synthesis of unsymmetrical 1,3,5-triazin-2-amines has been developed. The protocol uses readily available imidates, guanidines, and amides or aldehydes as the starting materials, cesium carbonate as the base, no catalyst or additive is required, and the three-component reaction provides diverse 1,3,5-triazin-2-amines in moderate to good yields with tolerance of wide functional groups.

One-pot synthesis of 3,5-disubstituted 1,2,4-thiadiazoles from nitriles and thioamides via I2-mediated oxidative formation of an N-S bond.

A simple and practical method for I2-mediated one-pot synthesis of 3-alkyl-5-aryl-1,2,4-thiadiazoles has been developed; the one-pot reaction includes sequential intermolecular addition of thioamides to nitriles, and intramolecular oxidative coupling of N-H and S-H bonds mediated by molecular iodine. Meanwhile the protocol uses readily available nitriles and thioamides as the starting materials, molecular iodine as the oxidant, and generates various 1,2,4-thiadiazoles in moderate to good yields with a wide array of functional groups. This method is an efficient approach for the synthesis of unsymmetrically disubstituted 1,2,4-thiadiazoles.

Insight into the multiple quasi-molecular states in ethylenediamine reduced graphene nanodots.

Recently, graphene nanodots (GNDs) have been frequently considered as inherently heterogeneous systems, leading to multicolor emission under a changeable excitation wavelength. However, an accurate picture of the GNDs and an exhaustive structure-property correlation are still lacking. Using a two dimensional photoluminescence excitation (2D-PLE) map, molecular orbital calculation, reduction level dependent PL analysis, absorption spectroscopy and time-resolved PL spectroscopy, three cases of quasi-molecular PL are determined in ethylenediamine (EDA) reduced GNDs, including the C[double bond, length as m-dash]O related electronic state, graphenol related electronic state and large π-conjugated domains. The graphenol structure is expected to be created via nucleophilic addition-elimination reactions between epoxide groups and EDA, contributing most to the blue-shifted and enhanced PL of GNDs. The multiple quasi-molecular PL provides deeper insights into the commonly called "excitation wavelength dependent PL". An effort is made to utilize the heterogeneous photoluminescence through phosphor-based light-emitting diodes employing reduced GNDs as a phosphor, which are capable of converting blue light into white light.

Copper-catalyzed one-pot synthesis of 1,2,4-triazoles from nitriles and hydroxylamine.

A simple and efficient copper-catalyzed one-pot synthesis of substituted 1,2,4-triazoles through reactions of two nitriles with hydroxylamine has been developed. The protocol uses simple and readily available nitriles and hydroxylamine hydrochloride as the starting materials and inexpensive Cu(OAc)2 as the catalyst, and the corresponding 1,2,4-triazole derivatives are obtained in moderate to good yields. The reactions include sequential intermolecular addition of hydroxylamine to one nitrile to provide amidoxime, copper-catalyzed treatment of the amidoxime with another nitrile, and intramolecular dehydration/cyclization. This finding provides a new and useful strategy for synthesis of 1,2,4-triazole derivatives.