Poly[(μ4-benzene-1,3,5-tricarboxyl­ato)bis­(N,N-dimethyl­formamide)­cerium(III)]

The asymmetric unit of the title rare earth coordination polymer, [Ce(C9H3O6)(C3H7NO)2]n, contains one eight-coordinated Ce3+ ion, one benzene-1,3,5-tricarboxyl­ate (BTC) ligand and two coordinated N,N-dimethyl­formamide (DMF) mol­ecules. The Ce3+ ion is coordinated by six O atoms from four carboxyl­ate groups of the BTC ligands and by two O atoms from two terminal DMF mol­ecules

Poly[di-μ2-chlorido-tri-μ2-terephthalato-tetra­lead(II)]

The title compound, [Pb4(C8H4O4)3Cl2]n, consists of a three-dimensional inorganic–organic hybrid framework. The asymmetric unit contains two Pb2+ cations, one Cl− anion and one and a half terephthalate anions, the latter being completed by inversion symmetry. The two Pb2+ cations are each surrounded by five O atoms and one Cl atom in the form of irregular polyhedra. The cations are linked by μ2-O and μ2-Cl atoms into binuclear units, which are further extended through Pb—O inter­actions into an undulated inorganic layer parallel to (001). These layers are connected along [001] by the terephthalate groups into a three-dimensional framework

A sex-specific association of common variants of neuroligin genes (NLGN3 and NLGN4X) with autism spectrum disorders in a Chinese Han cohort

<p>Abstract</p> <p>Background</p> <p>Synaptic genes, <it>NLGN3 </it>and <it>NLGN4X</it>, two homologous members of the neuroligin family, have been supposed as predisposition loci for autism spectrum disorders (ASDs), and defects of these two genes have been identified in a small fraction of individuals with ASDs. But no such rare variant in these two genes has as yet been adequately replicated in Chinese population and no common variant has been further investigated to be associated with ASDs.</p> <p>Methods</p> <p>7 known ASDs-related rare variants in <it>NLGN3 </it>and <it>NLGN4X </it>genes were screened for replication of the initial findings and 12 intronic tagging single nucleotide polymorphisms (SNPs) were genotyped for case-control association analysis in a total of 229 ASDs cases and 184 control individuals in a Chinese Han cohort, using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry.</p> <p>Results</p> <p>We found that a common intronic variant, SNP rs4844285 in <it>NLGN3 </it>gene, and a specific 3-marker haplotype X^A-X^G-X^T(rs11795613-rs4844285-rs4844286) containing this individual SNP were associated with ASDs and showed a male bias, even after correction for multiple testing (SNP allele: P = 0.048, haplotype:P = 0.032). Simultaneously, none of these 7 known rare mutation of <it>NLGN3</it> and <it>NLGN4X</it> genes was identified, neither in our patients with ASDs nor controls, giving further evidence that these known rare variants might be not enriched in Chinese Han cohort.</p> <p>Conclusion</p> <p>The present study provides initial evidence that a common variant in <it>NLGN3 </it>gene may play a role in the etiology of ASDs among affected males in Chinese Han population, and further supports the hypothesis that defect of synapse might involvement in the pathophysiology of ASDs.</p

Poly[(μ4-benzene-1,3,5-tricarboxyl­ato)bis­(dimethyl sulfoxide-κO)­neodymium(III)]

The asymmetric unit of the title compound, [Nd(C9H3O6)(C2H6OS)2]n, contains one Nd3+ ion, one benzene-1,3,5-tricarb­oxy­lic ligand and two coordinating dimethyl sulfoxide mol­ecules. The Nd3+ ion is coordinated by six O atoms from four carboxyl­ate groups of the benzene-1,3,5-tricarboxyl­ate ligands and two O atoms from two dimethyl sulfoxide mol­ecules. The metal-organic cluster formed upon symmetry expansion of the asymmetric unit consists of two metal atoms and four benzene-1,3,5-tricarboxyl­ate groups, creating a paddle-wheel-type building block arrangement. The remaining coordination sites are occupied by additional benzene-1,3,5-tricarboxyl­ate groups and dimethyl sulfoxide mol­ecules, forming a three-dimensional polymeric rare earth metal-organic framework structure

Direct single-molecule dynamic detection of chemical reactions.

Single-molecule detection can reveal time trajectories and reaction pathways of individual intermediates/transition states in chemical reactions and biological processes, which is of fundamental importance to elucidate their intrinsic mechanisms. We present a reliable, label-free single-molecule approach that allows us to directly explore the dynamic process of basic chemical reactions at the single-event level by using stable graphene-molecule single-molecule junctions. These junctions are constructed by covalently connecting a single molecule with a 9-fluorenone center to nanogapped graphene electrodes. For the first time, real-time single-molecule electrical measurements unambiguously show reproducible large-amplitude two-level fluctuations that are highly dependent on solvent environments in a nucleophilic addition reaction of hydroxylamine to a carbonyl group. Both theoretical simulations and ensemble experiments prove that this observation originates from the reversible transition between the reactant and a new intermediate state within a time scale of a few microseconds. These investigations open up a new route that is able to be immediately applied to probe fast single-molecule physics or biophysics with high time resolution, making an important contribution to broad fields beyond reaction chemistry

Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides

Objectives: To develop and validate a deep learning (DL)-based primary tumor biopsy signature for predicting axillary lymph node (ALN) metastasis preoperatively in early breast cancer (EBC) patients with clinically negative ALN. Methods: A total of 1,058 EBC patients with pathologically confirmed ALN status were enrolled from May 2010 to August 2020. A DL core-needle biopsy (DL-CNB) model was built on the attention-based multiple instance-learning (AMIL) framework to predict ALN status utilizing the DL features, which were extracted from the cancer areas of digitized whole-slide images (WSIs) of breast CNB specimens annotated by two pathologists. Accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curves, and areas under the ROC curve (AUCs) were analyzed to evaluate our model. Results: The best-performing DL-CNB model with VGG16_BN as the feature extractor achieved an AUC of 0.816 (95% confidence interval (CI): 0.758, 0.865) in predicting positive ALN metastasis in the independent test cohort. Furthermore, our model incorporating the clinical data, which was called DL-CNB+C, yielded the best accuracy of 0.831 (95%CI: 0.775, 0.878), especially for patients younger than 50 years (AUC: 0.918, 95%CI: 0.825, 0.971). The interpretation of DL-CNB model showed that the top signatures most predictive of ALN metastasis were characterized by the nucleus features including density ($p$ = 0.015), circumference ($p$ = 0.009), circularity ($p$ = 0.010), and orientation ($p$ = 0.012). Conclusion: Our study provides a novel DL-based biomarker on primary tumor CNB slides to predict the metastatic status of ALN preoperatively for patients with EBC. The codes and dataset are available at https://github.com/bupt-ai-cz/BALNMPComment: Update Table 1 and corresponding description

Molecular characterization of immunogenic cell death indicates prognosis and tumor microenvironment infiltration in osteosarcoma

IntroductionOsteosarcoma (OS) is a highly aggressive bone malignancy with a poor prognosis, mainly in children and adolescents. Immunogenic cell death (ICD) is classified as a type of programmed cell death associated with the tumor immune microenvironment, prognosis, and immunotherapy. However, the feature of the ICD molecular subtype and the related tumor microenvironment (TME) and immune cell infiltration has not been carefully investigated in OS.MethodsThe ICD-related genes were extracted from previous studies, and the RNA expression profiles and corresponding data of OS were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database. The ICD-related molecular subtypes were classed by the "ConsensusclusterPlus" package and the construction of ICD-related signatures through univariate regression analysis. ROC curves, independent analysis, and internal validation were used to evaluate signature performance. Moreover, a series of bioinformatic analyses were used for Immunotherapy efficacy, tumor immune microenvironments, and chemotherapeutic drug sensitivity between the high- and low-risk groups.ResultsHerein, we identified two ICD-related subtypes and found significant heterogeneity in clinical prognosis, TME, and immune response signaling among distinct ICD subtypes. Subsequently, a novel ICD-related prognostic signature was developed to determine its predictive performance in OS. Also, a highly accurate nomogram was then constructed to improve the clinical applicability of the novel ICD-related signature. Furthermore, we observed significant correlations between ICD risk score and TME, immunotherapy response, and chemotherapeutic drug sensitivity. Notably, the in vitro experiments further verified that high GALNT14 expression is closely associated with poor prognosis and malignant progress of OS.DiscussionHence, we identified and validated that the novel ICD-related signature could serve as a promising biomarker for the OS's prognosis, chemotherapy, and immunotherapy response prediction, providing guidance for personalized and accurate immunotherapy strategies for OS