Gasdermin D licenses MHCII induction to maintain food tolerance in small intestine.

The intestinal epithelial cells (IECs) constitute the primary barrier between host cells and numerous foreign antigens; it is unclear how IECs induce the protective immunity against pathogens while maintaining the immune tolerance to food. Here, we found IECs accumulate a less recognized 13-kD N-terminal fragment of GSDMD that is cleaved by caspase-3/7 in response to dietary antigens. Unlike the 30-kD GSDMD cleavage fragment that executes pyroptosis, the IEC-accumulated GSDMD cleavage fragment translocates to the nucleus and induces the transcription of CIITA and MHCII molecules, which in turn induces the Tr1 cells in upper small intestine. Mice treated with a caspase-3/7 inhibitor, mice with GSDMD mutation resistant to caspase-3/7 cleavage, mice with MHCII deficiency in IECs, and mice with Tr1 deficiency all displayed a disrupted food tolerance phenotype. Our study supports that differential cleavage of GSDMD can be understood as a regulatory hub controlling immunity versus tolerance in the small intestine.

LACC1 bridges NOS2 and polyamine metabolism in inflammatory macrophages.

The mammalian immune system uses various pattern recognition receptors to recognize invaders and host damage and transmits this information to downstream immunometabolic signalling outcomes. Laccase domain-containing 1 (LACC1) protein is an enzyme highly expressed in inflammatory macrophages and serves a central regulatory role in multiple inflammatory diseases such as inflammatory bowel diseases, arthritis and clearance of microbial infection1-4. However, the biochemical roles required for LACC1 functions remain largely undefined. Here we elucidated a shared biochemical function of LACC1 in mice and humans, converting L-citrulline to L-ornithine (L-Orn) and isocyanic acid and serving as a bridge between proinflammatory nitric oxide synthase (NOS2) and polyamine immunometabolism. We validated the genetic and mechanistic connections among NOS2, LACC1 and ornithine decarboxylase 1 (ODC1) in mouse models and bone marrow-derived macrophages infected by Salmonella enterica Typhimurium. Strikingly, LACC1 phenotypes required upstream NOS2 and downstream ODC1, and Lacc1-/- chemical complementation with its product L-Orn significantly restored wild-type activities. Our findings illuminate a previously unidentified pathway in inflammatory macrophages, explain why its deficiency may contribute to human inflammatory diseases and suggest that L-Orn could serve as a nutraceutical to ameliorate LACC1-associated immunological dysfunctions such as arthritis or inflammatory bowel disease.

The DNA Methylcytosine Dioxygenase Tet2 Sustains Immunosuppressive Function of Tumor-Infiltrating Myeloid Cells to Promote Melanoma Progression.

Ten-Eleven-Translocation-2 (Tet2) is a DNA methylcytosine dioxygenase that functions as a tumor suppressor in hematopoietic malignancies. We examined the role of Tet2 in tumor-tissue myeloid cells and found that Tet2 sustains the immunosuppressive function of these cells. We found that Tet2 expression is increased in intratumoral myeloid cells both in mouse models of melanoma and in melanoma patients and that this increased expression is dependent on an IL-1R-MyD88 pathway. Ablation of Tet2 in myeloid cells suppressed melanoma growth in vivo and shifted the immunosuppressive gene expression program in tumor-associated macrophages to a proinflammatory one, with a concomitant reduction of the immunosuppressive function. This resulted in increased numbers of effector T cells in the tumor, and T cell depletion abolished the reduced tumor growth observed upon myeloid-specific deletion of Tet2. Our findings reveal a non-cell-intrinsic, tumor-promoting function for Tet2 and suggest that Tet2 may present a therapeutic target for the treatment of non-hematologic malignancies.

General synthesis of two-dimensional van der Waals heterostructure arrays.

Two-dimensional van der Waals heterostructures (vdWHs) have attracted considerable interest1-4. However, most vdWHs reported so far  are created by an arduous micromechanical exfoliation and manual restacking process5, which-although versatile for proof-of-concept demonstrations6-16 and fundamental studies17-30-is clearly not scalable for practical technologies. Here we report a general synthetic strategy for two-dimensional vdWH arrays between metallic transition-metal dichalcogenides (m-TMDs) and semiconducting TMDs (s-TMDs). By selectively patterning nucleation sites on monolayer or bilayer s-TMDs, we precisely control the nucleation and growth of diverse m-TMDs with designable periodic arrangements and tunable lateral dimensions at the predesignated spatial locations, producing a series of vdWH arrays, including VSe2/WSe2, NiTe2/WSe2, CoTe2/WSe2, NbTe2/WSe2, VS2/WSe2, VSe2/MoS2 and VSe2/WS2. Systematic scanning transmission electron microscopy studies reveal nearly ideal vdW interfaces with widely tunable moiré superlattices. With the atomically clean vdW interface, we further show that the m-TMDs function as highly reliable synthetic vdW contacts for the underlying WSe2 with excellent device performance and yield, delivering a high ON-current density of up to 900 microamperes per micrometre in bilayer WSe2 transistors. This general synthesis of diverse two-dimensional vdWH arrays provides a versatile material platform for exploring exotic physics and promises a scalable pathway to high-performance devices.

Oxygen vacancy-engineered titanium-based perovskite for boosting H2O activation and lower-temperature hydrolysis of organic sulfur.

Modulation of water activation is crucial to water-involved chemical reactions in heterogeneous catalysis. Organic sulfur (COS and CS2) hydrolysis is such a typical reaction involving water (H2O) molecule as a reactant. However, limited by the strong O-H bond in H2O, satisfactory CS2 hydrolysis performance is attained at high temperature above 310 °C, which is at the sacrifice of the Claus conversion, strongly hindering sulfur recovery efficiency improvement and pollution emissions control of the Claus process. Herein, we report a facile oxygen vacancy (VO) engineering on titanium-based perovskite to motivate H2O activation for enhanced COS and CS2 hydrolysis at lower temperature. Increased amount of VO contributed to improved degree of H2O dissociation to generate more active -OH, due to lower energy barrier for H2O dissociation over surface rich in VO, particularly VO clusters. Besides, low-coordinated Ti ions adjacent to VO were active sites for H2O activation. Consequently, complete conversion of COS and CS2 was achieved over SrTiO3 after H2 reduction treatment at 225 °C, a favorable temperature for the Claus conversion, at which both satisfying COS and CS2 hydrolysis performance and improved sulfur recovery efficiency can be obtained simultaneously. Additionally, the origin of enhanced hydrolysis activity from boosted H2O activation by VO was revealed via in-depth mechanism study. This provides more explicit direction for further design of efficacious catalysts for H2O-involved reactions.

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the NeuronMotif algorithm to interpret such neurons. Given any convolutional neuron (CN) in the network, NeuronMotif first generates a large sample of sequences capable of activating the CN, which typically consists of a mixture of patterns. Then, the sequences are "demixed" in a layer-wise manner by backward clustering of the feature maps of the involved convolutional layers. NeuronMotif can output the sequence motifs, and the syntax rules governing their combinations are depicted by position weight matrices organized in tree structures. Compared to existing methods, the motifs found by NeuronMotif have more matches to known motifs in the JASPAR database. The higher-order patterns uncovered for deep CNs are supported by the literature and ATAC-seq footprinting. Overall, NeuronMotif enables the deciphering of cis-regulatory codes from deep CNs and enhances the utility of CNN in genome interpretation.

GPro: generative AI-empowered toolkit for promoter design.

MOTIVATION: Promoters with desirable properties are crucial in biotechnological applications. Generative AI (GenAI) has demonstrated potential in creating novel synthetic promoters with significantly enhanced functionality. However, these methods' reliance on various programming frameworks and specific task-oriented contexts limits their flexibilities. Overcoming these limitations is essential for researchers to fully leverage the power of GenAI to design promoters for their tasks. RESULTS: Here, we introduce GPro (Generative AI-empowered toolkit for promoter design), a user-friendly toolkit that integrates a collection of cutting-edge GenAI-empowered approaches for promoter design. This toolkit provides a standardized pipeline covering essential promoter design processes, including training, optimization, and evaluation. Several detailed demos are provided to reproduce state-of-the-art promoter design pipelines. GPro's user-friendly interface makes it accessible to a wide range of users including non-AI experts. It also offers a variety of optional algorithms for each design process, and gives users the flexibility to compare methods and create customized pipelines. AVAILABILITY AND IMPLEMENTATION: GPro is released as an open-source software under the MIT license. The source code for GPro is available on GitHub for Linux, macOS, and Windows: https://github.com/WangLabTHU/GPro, and is available for download via Zenodo repository at https://zenodo.org/doi/10.5281/zenodo.10681733.

Unveil cis-acting combinatorial mRNA motifs by interpreting deep neural network.

SUMMARY: Cis-acting mRNA elements play a key role in the regulation of mRNA stability and translation efficiency. Revealing the interactions of these elements and their impact plays a crucial role in understanding the regulation of the mRNA translation process, which supports the development of mRNA-based medicine or vaccines. Deep neural networks (DNN) can learn complex cis-regulatory codes from RNA sequences. However, extracting these cis-regulatory codes efficiently from DNN remains a significant challenge. Here, we propose a method based on our toolkit NeuronMotif and motif mutagenesis, which not only enables the discovery of diverse and high-quality motifs but also efficiently reveals motif interactions. By interpreting deep-learning models, we have discovered several crucial motifs that impact mRNA translation efficiency and stability, as well as some unknown motifs or motif syntax, offering novel insights for biologists. Furthermore, we note that it is challenging to enrich motif syntax in datasets composed of randomly generated sequences, and they may not contain sufficient biological signals. AVAILABILITY AND IMPLEMENTATION: The source code and data used to produce the results and analyses presented in this manuscript are available from GitHub (https://github.com/WangLabTHU/combmotif).

RNA m6A demethylase ALKBH5 regulates the development of γδ T cells.

γδ T cells are an abundant T cell population at the mucosa and are important in providing immune surveillance as well as maintaining tissue homeostasis. However, despite γδ T cells' origin in the thymus, detailed mechanisms regulating γδ T cell development remain poorly understood. N6-methyladenosine (m6A) represents one of the most common posttranscriptional modifications of messenger RNA (mRNA) in mammalian cells, but whether it plays a role in γδ T cell biology is still unclear. Here, we show that depletion of the m6A demethylase ALKBH5 in lymphocytes specifically induces an expansion of γδ T cells, which confers enhanced protection against gastrointestinal Salmonella typhimurium infection. Mechanistically, loss of ALKBH5 favors the development of γδ T cell precursors by increasing the abundance of m6A RNA modification in thymocytes, which further reduces the expression of several target genes including Notch signaling components Jagged1 and Notch2. As a result, impairment of Jagged1/Notch2 signaling contributes to enhanced proliferation and differentiation of γδ T cell precursors, leading to an expanded mature γδ T cell repertoire. Taken together, our results indicate a checkpoint role of ALKBH5 and m6A modification in the regulation of γδ T cell early development.

Efficacy and safety of rademikibart (CBP-201), a next-generation mAb targeting IL-4Rα, in adults with moderate to severe atopic dermatitis: A phase 2 randomized trial (CBP-201-WW001).

BACKGROUND: Rademikibart (CBP-201) is a next-generation IL-4 receptor alpha-targeting antibody. OBJECTIVE: We sought to evaluate rademikibart in adults with moderate to severe atopic dermatitis. METHODS: A total of 226 patients were randomized, double-blind, to subcutaneous rademikibart (300 mg every 2 weeks [Q2W], 150 mg Q2W, 300 mg every 4 weeks [Q4W]; plus 600-mg loading dose) or placebo. Randomization began in July 2020. The trial was completed in October 2021. RESULTS: The WW001 phase 2 trial achieved its primary end point: significant percent reduction from baseline in least-squares mean Eczema Area Severity Index (EASI) to week 16 with rademikibart 300 mg Q2W (-63.0%; P = .0007), 150 mg Q2W (-57.6%; P = .0067), 300 mg Q4W (-63.5%; P = .0004) versus placebo (-39.7%). EASI scores decreased significantly with 300 mg Q2W and Q4W at the earliest assessment (week 2), with no evidence of plateauing by week 16. Significant improvements were also observed in secondary end points, including pruritus. Across the primary and secondary end points, efficacy tended to be comparable with 300 mg Q2W and Q4W dosing. Rademikibart and placebo had similar, low incidence of treatment-emergent adverse events (TEAEs) (48% vs 54%), serious TEAEs (1.8% vs 3.6%), TEAEs leading to treatment discontinuation (1.2% vs 1.8%), conjunctivitis of unspecified cause (2.9% vs 0%), herpes (0.6% vs 1.8%), and injection-site reactions (1.8% vs 1.8%). Although no discontinuations were attributed to coronavirus disease 2019, pandemic-related restrictions likely had an impact on trial conduct. CONCLUSIONS: Rademikibart was efficacious and well tolerated at Q2W and Q4W intervals. Q4W dosing is a more convenient frequency than approved for current therapies.

Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer.

Mounting evidence has highlighted the multifunctional characteristics of glutamine metabolism (GM) in cancer initiation, progression and therapeutic regimens. However, the overall role of GM in the tumour microenvironment (TME), clinical stratification and therapeutic efficacy in patients with ovarian cancer (OC) has not been fully elucidated. Here, three distinct GM clusters were identified and exhibited different prognostic values, biological functions and immune infiltration in TME. Subsequently, glutamine metabolism prognostic index (GMPI) was constructed as a new scoring model to quantify the GM subtypes and was verified as an independent predictor of OC. Patients with low-GMPI exhibited favourable survival outcomes, lower enrichment of several oncogenic pathways, less immunosuppressive cell infiltration and better immunotherapy responses. Single-cell sequencing analysis revealed a unique evolutionary trajectory of OC cells from high-GMPI to low-GMPI, and OC cells with different GMPI might communicate with distinct cell populations through ligand-receptor interactions. Critically, the therapeutic efficacy of several drug candidates was validated based on patient-derived organoids (PDOs). The proposed GMPI could serve as a reliable signature for predicting patient prognosis and contribute to optimising therapeutic strategies for OC.

Unveiling the Multielectron Acceptor Properties of π-Expanded Pyracylene: Reversible Boat to Chair Conversion.

In this work, the chemical reduction of a hybrid pyracylene-hexa-peri-hexabenzocoronene (HPH) nanographene was investigated with different alkali metals (Na, K, Rb) to reveal its remarkable multielectron acceptor abilities. The UV-vis and 1H NMR spectroscopy monitoring of the stepwise reduction reactions supports the existence of all intermediate reduction states up to the hexaanion for HPH. Tuning the experimental conditions enabled the synthesis of the HPH anions with gradually increasing reduction states (up to -5) isolated with different alkali metal ions as crystalline materials. The single-crystal X-ray diffraction structure analysis demonstrates that the highly negatively charged HPH anions (-4 and -5) exhibit a drastic geometry change from boat-shaped (observed in the neutral parent, mono- and dianions) to a chair conformation, which was proved to be fully reversible by NMR spectroscopy. DFT calculations show that this geometry change is induced by an enhanced interaction between the coordinated metal ions and negatively charged HPH core in the chair conformation.

JEBIN: analyzing gene co-expressions across multiple datasets by joint network embedding.

The inference of gene co-expression associations is one of the fundamental tasks for large-scale transcriptomic data analysis. Due to the high dimensionality and high noises in transcriptomic data, it is difficult to infer stable gene co-expression associations from single dataset. Meta-analysis of multisource data can effectively tackle this problem. We proposed Joint Embedding of multiple BIpartite Networks (JEBIN) to learn the low-dimensional consensus representation for genes by integrating multiple expression datasets. JEBIN infers gene co-expression associations in a nonlinear and global similarity manner and can integrate datasets with different distributions in linear time complexity with the gene and total sample size. The effectiveness and scalability of JEBIN were verified by simulation experiments, and its superiority over the commonly used integration methods was proved by three indexes on real biological datasets. Then, JEBIN was applied to study the gene co-expression patterns of hepatocellular carcinoma (HCC) based on multiple expression datasets of HCC and adjacent normal tissues, and further on latest HCC single-cell RNA-seq data. Results show that gene co-expressions are highly different between bulk and single-cell datasets. Finally, many differentially co-expressed ligand-receptor pairs were discovered by comparing HCC with adjacent normal data, providing candidate HCC targets for abnormal cell-cell communications.

Deep Learning-Based Stratification of Gastric Cancer Patients from Hematoxylin and Eosin-Stained Whole Slide Images by Predicting Molecular Features for Immunotherapy Response.

Determining the molecular characteristics of cancer patients is crucial for optimal immunotherapy decisions. The aim of this study was to screen immunotherapy beneficiaries by predicting key molecular features from hematoxylin and eosin-stained images based on deep learning models. An independent data set from Asian gastric cancer patients was included for external validation. In addition, a segmentation model (Horizontal-Vertical Network) was used to quantify the cellular composition of tumor stroma. The model performance was evaluated by measuring the area under the curve (AUC). The tumor extraction model achieved an AUC of 0.9386 and 0.9062 in the internal and external test sets, respectively. The stratification model could predict the immunotherapy-sensitive subtypes (AUC range, 0.8685 to 0.9461), the genetic mutations (AUC range, 0.8283 to 0.9225), and the pathway activity (AUC range, 0.7568 to 0.8612) fairly accurately. In external validation, the prediction performance of Epstein-Barr virus and programmed cell death ligand 1 expression status achieved AUCs of 0.7906 and 0.6384, respectively. The segmentation model identified a relatively high proportion of inflammatory cells and connective cells in some immunotherapy-sensitive subtypes. The deep learning-based models potentially may serve as a valuable tool to screen for the beneficiaries of immunotherapy in gastric cancer patients.

Discovery of metabolite biomarkers for odontogenic keratocysts.

INTRODUCTION: Odontogenic keratocysts (OKCs) are locally aggressive and have a high rate of recurrence, but the pathogenesis of OKCs is not fully understood. We aimed to investigate the serum metabolomic profile of OKCs and discover potential biomarkers. METHODS: Metabolomic analysis was performed on 42 serum samples from 22 OKC patients and 20 healthy controls (HCs) using gas chromatography‒mass spectrometry to identify dysregulated metabolites in the OKC samples. LASSO regression and receiver operating characteristic (ROC) curve analyses were used to select and validate metabolic biomarkers and develop diagnostic models. RESULTS: A total of 73 metabolites were identified in the serum samples, and 24 metabolites were dysregulated in the OKC samples, of which 4 were upregulated. Finally, a diagnostic panel of 10 metabolites was constructed that accurately diagnosed OKCs (sensitivity of 100%, specificity of 100%, area under the curve of 1.00). CONCLUSION: This study is the first to investigate the metabolic characteristics and potential metabolic biomarkers in the serum of OKC patients using GC‒MS. Our study provides further evidence to explore the pathogenesis of OKC.

Bending a Cumulene with Electrons: Stepwise Chemical Reduction and Structural Study of a Tetraaryl[4]Cumulene.

Chemical reduction of a [4]cumulene with cesium metal was explored, and the structural changes stemming from electron acquisition are detailed using X-ray crystallography. It is found that the [4]cumulene undergoes dramatic geometric changes upon stepwise reduction, including bending of the cumulenic core and twisting of the endgroups from orthogonal to planar. The structural deformation is consistent with early theoretical reports that suggest that the twisting should occur upon reduction of both even and odd [n]cumulenes. The current results, on the other hand, are inconsistent with a previous experimental study of a [3]cumulene in which the predicted twisting is not observed upon reduction. DFT calculations reveal that the barrier to deformation is an order of magnitude lower in a [3]cumulene than a [4]cumulene, allowing the barrier to be overcome in the solid-state.

Increased resected lymph node stations improved survival of esophageal squamous cell carcinoma.

BACKGROUND: Neoadjuvant chemoradiotherapy (nCRT) and surgery have been recommended as the standard treatments for locally advanced esophageal squamous cell carcinoma (ESCC). In addition, nodal metastases decreased in frequency and changed in distribution after neoadjuvant therapy. This study aimed to examine the optimal strategy for lymph node dissection (LND) in patients with ESCC who underwent nCRT. METHODS: The hazard ratios (HRs) for overall survival (OS) and disease-free survival (DFS) were calculated using the Cox proportional hazard model. To determine the minimal number of LNDs (n-LNS) or least station of LNDs (e-LNS), the Chow test was used. RESULTS: In total, 333 patients were included. The estimated cut-off values for e-LNS and n-LNS were 9 and 15, respectively. A higher number of e-LNS was significantly associated with improved OS (HR: 0.90; 95% CI 0.84-0.97, P = 0.0075) and DFS (HR: 0.012; 95% CI: 0.84-0.98, P = 0.0074). The e-LNS was a significant prognostic factor in multivariate analyses. The local recurrence rate of 23.1% in high e-LNS is much lower than the results of low e-LNS (13.3%). Comparable morbidity was found in both the e-LNS and n-LND subgroups. CONCLUSION: This cohort study revealed an association between the extent of LND and overall survival, suggesting the therapeutic value of extended lymphadenectomy during esophagectomy. Therefore, more lymph node stations being sampled leads to higher survival rates among patients who receive nCRT, and standard lymphadenectomy of at least 9 stations is strongly recommended.

Predicting new-baseline glomerular filtration rate (NBGFR) after donor nephrectomy: validation of a split renal function (SRF)-based formula.

BACKGROUND: Accurate prediction of post-donor nephrectomy (DN) glomerular filtration rate is potentially useful for evaluating and counselling living kidney donors. Currently, there are limited tools to evaluate post-operative new-baseline glomerular filtration rate (NBGFR) in kidney donors. We aim to validate a conceptually simple formula based on split renal function (SRF) previously developed for radical nephrectomy patients. METHODS: Eighty-three consecutive patients who underwent DN from 2010 to 2016 were included. Pre-operative CT imaging and functional data including pre-DN baseline Global GFR (108.2 ± 13.2 mL/min/1.73m2) were included. Observed NBGFR was defined as the latest eGFR 3-12 months post-DN. SRF, defined as volume of the contralateral non-resected kidney normalised by total volume of kidneys, was determined from pre-operative cross-sectional imaging (49.2 ± 2.36%). The equation derived from Rathi et al. is as detailed: Predicted NBGFR = 1.24 × (Global GFR Pre-DN) x (SRF). RESULTS: The relationship between predicted NBGFR (66.0 ± 8.29 mL/min/1.73m2) and observed NBGFR (74.9 ± 16.4 mL/min/1.73m2) was assessed by evaluating correlation coefficients, bias, precision, accuracy, and concordance. The new SRF-based formula for NBGFR prediction correlated strongly with observed post-operative NBGFR (Pearson's r = 0.729) demonstrating minimal bias (median difference = 7.190 mL/min/1.73m2) with good accuracy (96.4% within ± 30%, 62.7% within ± 15%) and precision (IQR of bias = - 0.094 to 16.227). CONCLUSION: The SRF-based formula was also able to accurately discriminate all but one patient to an NBGFR of > 45 mL/min/1.73m2. We utilised the newly developed SRF-based formula for predicting NBGFR in a living kidney donor population. Counselling of donor post-operative renal outcomes may then be optimised pre-operatively.

Trickier than It Looks: Isomerization between Five- and Six-Coordinated Zinc in Heterometallic Li2Zn2 Molecule.

This report describes the synthesis and characterization of two heterobimetallic Li-Zn coordination isomers [Li2Zn2(tbaoac)6] (tbaoac = tert-butyl acetoacetato) that have been isolated separately by the same stoichiometric reaction run in different organic solvents. The 6-coordinated zinc isomer (6-Zn) was synthesized in acetone with high yield, while the 5-coordinated one (5-Zn) was readily obtained from ethanol. The 5-Zn isomer has a low solubility in organic solvents such as alkanes and haloalkanes, while its 6-Zn counterpart exhibits a good solubility in almost all common solvents. Two isomeric molecules feature similar centrosymmetric tetranuclear cyclic assemblies, which are different in their arrangement of tbaoac ligands. While all ligands act as µ2-type in the structure of 5-Zn, the two tbaoac groups chelating Li appear as µ3-type in 6-Zn, thus providing an additional coordination for Zn ions. However, the real structural transformation between these isomers was shown to be more complex than simply making or breaking a couple of Zn-O bonds. X-ray single-crystal structure analysis, powder X-ray diffraction, multinuclear NMR, DART mass spectrometry, ICP-OES analysis, and TGA have been employed for the characterization of the isomers. The combination of powder X-ray diffraction and 1H NMR investigation revealed that 6-Zn isomer can be quantitatively transformed to 5-Zn in ethanol, while the reverse conversion instantly takes place in acetone.

Homoleptic Rare-Earth-Metal Sandwiches with Dibenzo[a,e]cyclooctatetraene Dianions.

A family of rare-earth complexes [RE(III) = Y, La, Gd, Tb, Dy, and Er] with doubly reduced dibenzo[a,e]cyclooctatetraene (DBCOT) has been synthesized and structurally characterized. X-ray diffraction analysis confirms that all products of the [RE(DBCOT)(THF)4][RE(DBCOT)2] composition consist of the anionic sandwich [RE(DBCOT)2]- and the cationic counterpart [RE(DBCOT)(THF)4]+. Within the sandwich, two elongated π decks are slightly bent toward the metal center (avg. 7.3°) with a rotation angle of 35.9-37.6°. The RE(III) ion is entrapped between the central eight-membered rings of DBCOT2- in a η8 fashion. The trends in the RE-COT bond lengths are consistent with the variations of the ionic radii of RE(III) centers. The 1H NMR spectra of the diamagnetic Y(III) and La(III) analogues illustrate the distinct solution behavior for the cationic and anionic parts in this series. Magnetic measurements for the Dy analogue reveal single-molecule magnetism, which was rationalized by considering the effect of crystal-field splitting for both building units analyzed by electronic structure calculations.