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

Numerical model for geothermal energy utilization from double pipe heat exchanger in abandoned oil wells

  The number of abandonded wells are increasing in the late period of oilfield development. The utilization of these abandonded oil wells is promising and environment-friendly for geothermal development. In this study, a numerical model for geothermal heating is derived from a double pipe heat exchanger in abandoned oil wells. The main influencing factors of injection rate, injection time, and the types of filler in casing annulus on temperature profiles and outlet temperature have been considered in this model. The influences of injection rate on heat-mining rate are then discussed. Results show that the double pipe heat exchanger can gain higher temperature at the outlet when the casing annulus is filled by liquid other than dry cement under the given parameter combination. The outlet temperature decreases with the increase in injection rate and injection time. The temperature rapidly decreases in the first 40 days during the injection process. The balance between heat mining rate and outlet temperature is important for evaluating a double pipe heat exchanger in abandoned oil wells. This work may provide a useful tool for a field engineer to estimate the temperature of liquid in wellhead and evaluate the heat transfer efficiency for double pipe heat exchanger in abandoned oil wells.Cited as: Lin, Z., Liu, K., Liu, J., Geng, D., Ren, K., Zheng, Z. Numerical model for geothermal energy utilization from double pipe heat exchanger in abandoned oil wells. Advances in Geo-Energy Research, 2021, 5(2): 212-221, doi: 10.46690/ager.2021.02.1

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

SAM-dependent enzyme-catalysed pericyclic reactions in natural product biosynthesis.

Pericyclic reactions-which proceed in a concerted fashion through a cyclic transition state-are among the most powerful synthetic transformations used to make multiple regioselective and stereoselective carbon-carbon bonds. They have been widely applied to the synthesis of biologically active complex natural products containing contiguous stereogenic carbon centres. Despite the prominence of pericyclic reactions in total synthesis, only three naturally existing enzymatic examples (the intramolecular Diels-Alder reaction, and the Cope and the Claisen rearrangements) have been characterized. Here we report a versatile S-adenosyl-l-methionine (SAM)-dependent enzyme, LepI, that can catalyse stereoselective dehydration followed by three pericyclic transformations: intramolecular Diels-Alder and hetero-Diels-Alder reactions via a single ambimodal transition state, and a retro-Claisen rearrangement. Together, these transformations lead to the formation of the dihydropyran core of the fungal natural product, leporin. Combined in vitro enzymatic characterization and computational studies provide insight into how LepI regulates these bifurcating biosynthetic reaction pathways by using SAM as the cofactor. These pathways converge to the desired biosynthetic end product via the (SAM-dependent) retro-Claisen rearrangement catalysed by LepI. We expect that more pericyclic biosynthetic enzymatic transformations remain to be discovered in naturally occurring enzyme 'toolboxes'. The new role of the versatile cofactor SAM is likely to be found in other examples of enzyme catalysis

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

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

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

New insights into the cortex-to-stele ratio show it to effectively indicate inter- and intraspecific function in the absorptive roots of temperate trees

The cortex-to-stele ratio (CSR), as it increases from thin- to thick-root species in angiosperms, is theorised to effectively reflect a compensation for the ‘lag’ of absorption behind transportation. But it is still not known if this compensatory effect exists in gymnosperm species or governs root structure and function within species. Here, anatomical, morphological, and tissue chemical traits of absorptive roots were measured in three temperate angiosperm and three gymnosperm species. Differences in the CSR and the above functional traits, as well as their intraspecific associations, were analyzed and then compared between angiosperms and gymnosperms. At the intraspecific level, the CSR decreased with increasing root order for all species. The expected functional indication of the CSR was consistent with decreases in specific root length (SRL) and N concentration and increases in the C to N ratio (C:N ratio) and the number of and total cross-sectional area of conduits with increasing root order, demonstrating that the CSR indicates the strength of absorption and transportation at the intraspecific level, but intraspecific changes are due to root development rather than the compensatory effect. These trends resulted in significant intraspecific associations between the CSR and SRL (R2 = 0.36 ~ 0.80), N concentration (R2 = 0.48 ~ 0.93), the C:N ratio (R2 = 0.47 ~ 0.91), and the number of (R2 = 0.21 ~ 0.78) and total cross-sectional area (R2 = 0.29 ~ 0.72) of conduits in each species (p< 0.05). The overall mean CSR of absorptive roots in angiosperms was four times greater than in gymnosperms, and in angiosperms, the CSR was significantly higher in thick- than in thin-rooted species, whereas in gymnosperms, the interspecific differences were not significant (p > 0.05). This suggests that the compensation for the lag of absorption via cortex thickness regulation was stronger in three angiosperm species than in three gymnosperm species. In addition, there was poor concordance between angiosperms and gymnosperms in the relationships between CSRs and anatomical, morphological, and tissue chemical traits. However, these gymnosperm species show a more stable intraspecific functional association compared to three angiosperm species. In general, absorptive root CSRs could manifest complex strategies in resource acquisition for trees at both intra- and interspecific levels

Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review

For invasive breast cancer, immunohistochemical (IHC) techniques are often used to detect the expression level of human epidermal growth factor receptor-2 (HER2) in breast tissue to formulate a precise treatment plan. From the perspective of saving manpower, material and time costs, directly generating IHC-stained images from hematoxylin and eosin (H&E) stained images is a valuable research direction. Therefore, we held the breast cancer immunohistochemical image generation challenge, aiming to explore novel ideas of deep learning technology in pathological image generation and promote research in this field. The challenge provided registered H&E and IHC-stained image pairs, and participants were required to use these images to train a model that can directly generate IHC-stained images from corresponding H&E-stained images. We selected and reviewed the five highest-ranking methods based on their PSNR and SSIM metrics, while also providing overviews of the corresponding pipelines and implementations. In this paper, we further analyze the current limitations in the field of breast cancer immunohistochemical image generation and forecast the future development of this field. We hope that the released dataset and the challenge will inspire more scholars to jointly study higher-quality IHC-stained image generation.Comment: 13 pages, 11 figures, 2table