Generation of genuine entanglement up to 51 superconducting qubits.

Scalable generation of genuine multipartite entanglement with an increasing number of qubits is important for both fundamental interest and practical use in quantum-information technologies1,2. On the one hand, multipartite entanglement shows a strong contradiction between the prediction of quantum mechanics and local realization and can be used for the study of quantum-to-classical transition3,4. On the other hand, realizing large-scale entanglement is a benchmark for the quality and controllability of the quantum system and is essential for realizing universal quantum computing5-8. However, scalable generation of genuine multipartite entanglement on a state-of-the-art quantum device can be challenging, requiring accurate quantum gates and efficient verification protocols. Here we show a scalable approach for preparing and verifying intermediate-scale genuine entanglement on a 66-qubit superconducting quantum processor. We used high-fidelity parallel quantum gates and optimized the fidelitites of parallel single- and two-qubit gates to be 99.91% and 99.05%, respectively. With efficient randomized fidelity estimation9, we realized 51-qubit one-dimensional and 30-qubit two-dimensional cluster states and achieved fidelities of 0.637 ± 0.030 and 0.671 ± 0.006, respectively. On the basis of high-fidelity cluster states, we further show a proof-of-principle realization of measurement-based variational quantum eigensolver10 for perturbed planar codes. Our work provides a feasible approach for preparing and verifying entanglement with a few hundred qubits, enabling medium-scale quantum computing with superconducting quantum systems.

An atlas of genetic scores to predict multi-omic traits.

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

Evaluating protein cross-linking as a therapeutic strategy to stabilize SOD1 variants in a mouse model of familial ALS.

Mutations in the gene encoding Cu-Zn superoxide dismutase 1 (SOD1) cause a subset of familial amyotrophic lateral sclerosis (fALS) cases. A shared effect of these mutations is that SOD1, which is normally a stable dimer, dissociates into toxic monomers that seed toxic aggregates. Considerable research effort has been devoted to developing compounds that stabilize the dimer of fALS SOD1 variants, but unfortunately, this has not yet resulted in a treatment. We hypothesized that cyclic thiosulfinate cross-linkers, which selectively target a rare, 2 cysteine-containing motif, can stabilize fALS-causing SOD1 variants in vivo. We created a library of chemically diverse cyclic thiosulfinates and determined structure-cross-linking-activity relationships. A pre-lead compound, "S-XL6," was selected based upon its cross-linking rate and drug-like properties. Co-crystallographic structure clearly establishes the binding of S-XL6 at Cys 111 bridging the monomers and stabilizing the SOD1 dimer. Biophysical studies reveal that the degree of stabilization afforded by S-XL6 (up to 24°C) is unprecedented for fALS, and to our knowledge, for any protein target of any kinetic stabilizer. Gene silencing and protein degrading therapeutic approaches require careful dose titration to balance the benefit of diminished fALS SOD1 expression with the toxic loss-of-enzymatic function. We show that S-XL6 does not share this liability because it rescues the activity of fALS SOD1 variants. No pharmacological agent has been proven to bind to SOD1 in vivo. Here, using a fALS mouse model, we demonstrate oral bioavailability; rapid engagement of SOD1G93A by S-XL6 that increases SOD1G93A's in vivo half-life; and that S-XL6 crosses the blood-brain barrier. S-XL6 demonstrated a degree of selectivity by avoiding off-target binding to plasma proteins. Taken together, our results indicate that cyclic thiosulfinate-mediated SOD1 stabilization should receive further attention as a potential therapeutic approach for fALS.

Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice.

Learning is thought to involve changes in glutamate receptors at synapses, submicron structures that mediate communication between neurons in the central nervous system. Due to their small size and high density, synapses are difficult to resolve in vivo, limiting our ability to directly relate receptor dynamics to animal behavior. Here we developed a combination of computational and biological methods to overcome these challenges. First, we trained a deep-learning image-restoration algorithm that combines the advantages of ex vivo super-resolution and in vivo imaging modalities to overcome limitations specific to each optical system. When applied to in vivo images from transgenic mice expressing fluorescently labeled glutamate receptors, this restoration algorithm super-resolved synapses, enabling the tracking of behavior-associated synaptic plasticity with high spatial resolution. This method demonstrates the capabilities of image enhancement to learn from ex vivo data and imaging techniques to improve in vivo imaging resolution.

Tctp, a unique Ing5-binding partner, inhibits the chromatin binding of Enok in Drosophila.

The MOZ/MORF histone acetyltransferase complex is highly conserved in eukaryotes and controls transcription, development, and tumorigenesis. However, little is known about how its chromatin localization is regulated. Inhibitor of growth 5 (ING5) tumor suppressor is a subunit of the MOZ/MORF complex. Nevertheless, the in vivo function of ING5 remains unclear. Here, we report an antagonistic interaction between Drosophila Translationally controlled tumor protein (TCTP) (Tctp) and ING5 (Ing5) required for chromatin localization of the MOZ/MORF (Enok) complex and H3K23 acetylation. Yeast two-hybrid screening using Tctp identified Ing5 as a unique binding partner. In vivo, Ing5 controlled differentiation and down-regulated epidermal growth factor receptor signaling, whereas it is required in the Yorkie (Yki) pathway to determine organ size. Ing5 and Enok mutants promoted tumor-like tissue overgrowth when combined with uncontrolled Yki activity. Tctp depletion rescued the abnormal phenotypes of the Ing5 mutation and increased the nuclear translocation of Ing5 and chromatin binding of Enok. Nonfunctional Enok promoted the nuclear translocation of Ing5 by reducing Tctp, indicating a feedback mechanism between Tctp, Ing5, and Enok to regulate histone acetylation. Therefore, Tctp is essential for H3K23 acetylation by controlling the nuclear translocation of Ing5 and chromatin localization of Enok, providing insights into the roles of human TCTP and ING5-MOZ/MORF in tumorigenesis.

Measuring thermodynamic preferences to form non-native conformations in nucleic acids using ultraviolet melting.

Thermodynamic preferences to form non-native conformations are crucial for understanding how nucleic acids fold and function. However, they are difficult to measure experimentally because this requires accurately determining the population of minor low-abundance (<10%) conformations in a sea of other conformations. Here, we show that melting experiments enable facile measurements of thermodynamic preferences to adopt nonnative conformations in DNA and RNA. The key to this "delta-melt" approach is to use chemical modifications to render specific minor non-native conformations the major state. The validity and robustness of delta-melt is established for four different non-native conformations under various physiological conditions and sequence contexts through independent measurements of thermodynamic preferences using NMR. Delta-melt is faster relative to NMR, simple, and cost-effective and enables thermodynamic preferences to be measured for exceptionally low-populated conformations. Using delta-melt, we obtained rare insights into conformational cooperativity, obtaining evidence for significant cooperativity (1.0 to 2.5 kcal/mol) when simultaneously forming two adjacent Hoogsteen base pairs. We also measured the thermodynamic preferences to form G-C+ and A-T Hoogsteen and A-T base open states for nearly all 16 trinucleotide sequence contexts and found distinct sequence-specific variations on the order of 2 to 3 kcal/mol. This rich landscape of sequence-specific non-native minor conformations in the DNA double helix may help shape the sequence specificity of DNA biochemistry. Thus, melting experiments can now be used to access thermodynamic information regarding regions of the free energy landscape of biomolecules beyond the native folded and unfolded conformations.

Probing Watson-Crick and Hoogsteen base pairing in duplex DNA using dynamic nuclear polarization solid-state NMR spectroscopy.

The majority of base pairs in double-stranded DNA exist in the canonical Watson-Crick geometry. However, they can also adopt alternate Hoogsteen conformations in various complexes of DNA with proteins and small molecules, which are key for biological function and mechanism. While detection of Hoogsteen base pairs in large DNA complexes and assemblies poses considerable challenges for traditional structural biology techniques, we show here that multidimensional dynamic nuclear polarization-enhanced solid-state NMR can serve as a unique spectroscopic tool for observing and distinguishing Watson-Crick and Hoogsteen base pairs in a broad range of DNA systems based on characteristic NMR chemical shifts and internuclear dipolar couplings. We illustrate this approach using a model 12-mer DNA duplex, free and in complex with the antibiotic echinomycin, which features two central adenine-thymine base pairs with Watson-Crick and Hoogsteen geometry, respectively, and subsequently extend it to the ∼200 kDa Widom 601 DNA nucleosome core particle.

Evolutionary analysis of conserved non-coding elements subsequent to whole-genome duplication in opium poppy.

Whole-genome duplication (WGD) leads to the duplication of both coding and non-coding sequences within an organism's genome, providing an abundant supply of genetic material that can drive evolution, ultimately contributing to plant adaptation and speciation. Although non-coding sequences contain numerous regulatory elements, they have been understudied compared to coding sequences. In order to address this gap, we explored the evolutionary patterns of regulatory sequences, coding sequences and transcriptomes using conserved non-coding elements (CNEs) as regulatory element proxies following the recent WGD event in opium poppy (Papaver somniferum). Our results showed similar evolutionary patterns in subgenomes of regulatory and coding sequences. Specifically, the biased or unbiased retention of coding sequences reflected the same pattern as retention levels in regulatory sequences. Further, the divergence of gene expression patterns mediated by regulatory element variations occurred at a more rapid pace than that of gene coding sequences. However, gene losses were purportedly dependent on relaxed selection pressure in coding sequences. Specifically, the rapid evolution of tissue-specific benzylisoquinoline alkaloid production in P. somniferum was associated with regulatory element changes. The origin of a novel stem-specific ACR, which utilized ancestral cis-elements as templates, is likely to be linked to the evolutionary trajectory behind the transition of the PSMT1-CYP719A21 cluster from high levels of expression solely in P. rhoeas root tissue to its elevated expression in P. somniferum stem tissue. Our findings demonstrate that rapid regulatory element evolution can contribute to the emergence of new phenotypes and provide valuable insights into the high evolvability of regulatory elements.

Extension and Fusion of Cyclic Polyantimony Units.

The synthesis and characterization of a series of polyantimony anionic clusters are reported. The products [(NbCp)2Sb10]2-, [MSb13]3- (M = Ru/Fe), and [MSb15]3- (M = Ru/Fe) were isolated as either K(18-crown-6) or K([2.2.2]-crypt) salts. The Sb10 ring contained in the [(NbCp)2Sb10]2- cluster can be viewed as an extension of two envelope-like cyclo-Sb5 units and represents by far the largest monocyclic all-antimony species. The clusters [MSb13]3- and [MSb15]3- (M = Ru/Fe) illustrate the variability of crown-like Sb8 ring motifs and reveal the fusion of different antimony fragments featuring unique Sb-Sb chain-like units. The reported synthetic approaches involve the fabrication of a variety of distinctive polyantimony anionic clusters, enhancing our understanding of the coordination chemistry of heavier group 15 elements.

Electron Divergence of Cuδ- and Pdδ+ in Cu3Pd Alloy-Based Heterojunctions Boosts Concerted C≡C Bond Binding and the Volmer Step for Alkynol Semihydrogenation.

Electrocatalytic semihydrogenation of alkynols presents a sustainable alternative to conventional thermal methodologies for the high-value production of alkenols. The design of efficient catalysts with superior catalytic and energy efficiency for semihydrogenation poses a significant challenge. Here, we present the application of an electron-divergent Cu3Pd alloy-based heterojunction in promoting the electrocatalytic semihydrogenation of alkynols to alkenols using water as the proton source. The tunable electron divergence of Cuδ- and Pdδ+, modulated by rectifying contact with nitrogen-rich carbons, enables the concerted binding of active H species from the Volmer step of water dissociation and the C≡C bond of alkynols on Pdδ+ sites. Simultaneously, the pronounced electron divergence of Cu3Pd facilitates the universal adsorption of OH species from the Volmer step and alkynols on the Cuδ- sites. The electron-divergent dual-center substantially boosts water dissociation and inhibition of completing hydrogen evolution to give a turnover frequency of 2412 h-1, outperforming the reported electrocatalysts' value of 7.3. Moreover, the continuous production of alkenols at industrial-related current density (-200 mA cm-2) over the efficient and durable Cu3Pd-based electrolyzer could achieve a cathodic energy efficiency of 45 mol kW·h-1, 1.7 times the bench-marked reactors, promising great potential for sustainable industrial synthesis.

Molecular classification reveals the sensitivity of lung adenocarcinoma to radiotherapy and immunotherapy: multi-omics clustering based on similarity network fusion.

BACKGROUND: Due to individual differences in tumors and immune systems, the response rate to immunotherapy is low in lung adenocarcinoma (LUAD) patients. Combinations with other therapeutic strategies improve the efficacy of immunotherapy in LUAD patients. Although radioimmunotherapy has been demonstrated to effectively suppress tumors, the underlying mechanisms still need to be investigated. METHODS: Total RNA from LUAD cells was sequenced before and after radiotherapy to identify differentially expressed radiation-associated genes. The similarity network fusion (SNF) algorithm was applied for molecular classification based on radiation-related genes, immune-related genes, methylation data, and somatic mutation data. The changes in gene expression, prognosis, immune cell infiltration, radiosensitivity, chemosensitivity, and sensitivity to immunotherapy were assessed for each subtype. RESULTS: We used the SNF algorithm and multi-omics data to divide TCGA-LUAD patients into three subtypes. Patients with the CS3 subtype had the best prognosis, while those with the CS1 and CS2 subtypes had poorer prognoses. Among the strains tested, CS2 exhibited the most elevated immune cell infiltration and expression of immune checkpoint genes, while CS1 exhibited the least. Patients in the CS2 subgroup were more likely to respond to PD-1 immunotherapy. The CS2 patients were most sensitive to docetaxel and cisplatin, while the CS1 patients were most sensitive to paclitaxel. Experimental validation of signature genes in the CS2 subtype showed that inhibiting the expression of RHCG and TRPA1 could enhance the sensitivity of lung cancer cells to radiation. CONCLUSIONS: In summary, this study identified a risk classifier based on multi-omics data that can guide treatment selection for LUAD patients.

Preferred Orientation Deposition via Multifunctional Gel Electrolyte with Molecular Anchor Enabling Highly Reversible Zn Anode.

The high activity of water molecules results in a series of awful parasitic reaction, which seriously impede the development of aqueous zinc batteries. Herein, a new gel electrolyte with multiple molecular anchors is designed by employing natural biomaterials from chitosan and chlorophyll derivative. The gel electrolyte firmly anchors water molecules by ternary hydrogen bonding to reduce the activity of water molecules and inhibit hydrogen evolution reaction. Meanwhile, the multipolar charged functional groups realize the gradient induction and redistribution of Zn2+ , which drives oriented Zn (002) plane deposition of Zn2+ and then achieves uniform Zn deposition and dendrite-free anode. As a result, it endows the Zn||Zn cell with over 1700 h stripping/plating processes and a high efficiency of 99.4% for the Zn||Cu cell. In addition, the Zn||V2 O5 full cells also exhibit capacity retention of 81.7% after 600 cycles at 0.5 A g-1 and excellent long-term stability over 1600 cycles at 2 A g-1 , and the flexible pouch cells can provide stable power for light-emitting diodes even after repeated bending. The gel electrolyte strategy provides a reference for reversible zinc anode and flexible wearable devices.

Association of sleep fragmentation with general and abdominal obesity: a population-based longitudinal study.

OBJECTIVE: To evaluate the causal relationship between sleep fragmentation (SF) parameters with general and abdominal obesity in free-living conditions. METHODS: SF parameters were assessed by ActiGraph accelerometers for 7 consecutive days. Obesity was measured at baseline and 1-year follow-up with InBody S10 body composition analyzer. RESULTS: At baseline, the mean age of the study population was 18.7 years old (SD = 0.9) and 139 (35.7%) were male. Each 1-unit increase of baseline sleep fragmentation index (SFI) was associated with 0.08 kg/m2-increase of body mass index (BMI) (95% CI: 0.03, 0.14), 0.20%-increase of percentage of body fat (PBF) (95% CI: 0.07, 0.32), 0.15 kg-increase of fat mass (FM) (95% CI: 0.03, 0.27), 0.15 cm-increase of waist circumference (WC) (95% CI: 0.03, 0.26) and 0.91 cm2-increase of visceral fat area (VFA) (95% CI: 0.36, 1.46) at the 1-year follow-up. In addition, each 1-unit increase of baseline SFI was associated with 15% increased risk of general obesity (OR = 1.15, 95% CI = 1.04-1.28; p = 0.006) and 7% increased risk of abdominal obesity (OR = 1.07, 95% CI = 1.01-1.13; p = 0.021) in the following year. CONCLUSIONS: Fragmented sleep is independently associated with an increased risk of both general and abdominal obesity. The result highlights SF as a modifiable risk factor for the prevention and treatment of obesity.

dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using time-course single-cell gene expression data.

Time-course single-cell RNA sequencing (scRNA-seq) data have been widely used to explore dynamic changes in gene expression of transcription factors (TFs) and their target genes. This information is useful to reconstruct cell-type-specific gene regulatory networks (GRNs). However, the existing tools are commonly designed to analyze either time-course bulk gene expression data or static scRNA-seq data via pseudo-time cell ordering. A few methods successfully utilize the information from multiple time points while also considering the characteristics of scRNA-seq data. We proposed dynDeepDRIM, a novel deep learning model to reconstruct GRNs using time-course scRNA-seq data. It represents the joint expression of a gene pair as an image and utilizes the image of the target TF-gene pair and the ones of the potential neighbors to reconstruct GRNs from time-course scRNA-seq data. dynDeepDRIM can effectively remove the transitive TF-gene interactions by considering neighborhood context and model the gene expression dynamics using high-dimensional tensors. We compared dynDeepDRIM with six GRN reconstruction methods on both simulation and four real time-course scRNA-seq data. dynDeepDRIM achieved substantially better performance than the other methods in inferring TF-gene interactions and eliminated the false positives effectively. We also applied dynDeepDRIM to annotate gene functions and found it achieved evidently better performance than the other tools due to considering the neighbor genes.

Prognostic and predictive value of super-enhancer-derived signatures for survival and lung metastasis in osteosarcoma.

BACKGROUND: Risk stratification and personalized care are crucial in managing osteosarcoma due to its complexity and heterogeneity. However, current prognostic prediction using clinical variables has limited accuracy. Thus, this study aimed to explore potential molecular biomarkers to improve prognostic assessment. METHODS: High-throughput inhibitor screening of 150 compounds with broad targeting properties was performed and indicated a direction towards super-enhancers (SEs). Bulk RNA-seq, scRNA-seq, and immunohistochemistry (IHC) were used to investigate SE-associated gene expression profiles in osteosarcoma cells and patient tissue specimens. Data of 212 osteosarcoma patients who received standard treatment were collected and randomized into training and validation groups for retrospective analysis. Prognostic signatures and nomograms for overall survival (OS) and lung metastasis-free survival (LMFS) were developed using Cox regression analyses. The discriminatory power, calibration, and clinical value of nomograms were evaluated. RESULTS: High-throughput inhibitor screening showed that SEs significantly contribute to the oncogenic transcriptional output in osteosarcoma. Based on this finding, focus was given to 10 SE-associated genes with distinct characteristics and potential oncogenic function. With multi-omics approaches, the hyperexpression of these genes was observed in tumor cell subclusters of patient specimens, which were consistently correlated with poor outcomes and rapid metastasis, and the majority of these identified SE-associated genes were confirmed as independent risk factors for poor outcomes. Two molecular signatures were then developed to predict survival and occurrence of lung metastasis: the SE-derived OS-signature (comprising LACTB, CEP55, SRSF3, TCF7L2, and FOXP1) and the SE-derived LMFS-signature (comprising SRSF3, TCF7L2, FOXP1, and APOLD1). Both signatures significantly improved prognostic accuracy beyond conventional clinical factors. CONCLUSIONS: Oncogenic transcription driven by SEs exhibit strong associations with osteosarcoma outcomes. The SE-derived signatures developed in this study hold promise as prognostic biomarkers for predicting OS and LMFS in patients undergoing standard treatments. Integrative prognostic models that combine conventional clinical factors with these SE-derived signatures demonstrate substantially improved accuracy, and have the potential to facilitate patient counseling and individualized management.

Optical transmission of microwave control signal towards large-scale superconducting quantum computing.

With the rapid development of superconducting quantum computing and the implementation of surface code, large-scale quantum computing is emerging as an urgent demand. In a superconducting computing system, the qubit is maintained in a cryogenic environment to avoid thermal excitation. Thus, the transmission of control signals, which are generated at room temperature, is needed. Typically, the transmission of these signals to the qubit relies on a coaxial cable wiring approach. However, in a large-scale computing system with hundreds or even thousands of qubits, the coaxial cables will pose great space and heat load to the dilution refrigerator. Here, to tackle this problem, we propose and demonstrate a direct-modulation-based optical transmission line. In our experiment, the average single-qubit XEB error and control error are measured as 0.139% and 0.014% separately, demonstrating the feasibility of the optical wiring approach and paving the way for large-scale superconducting quantum computing.

A 15-Inflammation-Related Gene Signature Predicts the Prognosis of Patients With Pancreatic Ductal Adenocarcinoma.

Chronic inflammation promotes the development of pancreatic ductal adenocarcinoma (PDAC) and PDAC-related inflammatory tumor microenvironment facilitates tumor growth and metastasis. Thus, we aimed to study the association between inflammatory response and prognosis in patients with PDAC. We conducted the whole transcriptomic sequencing using tissue samples collected from patients diagnosed with PDAC (n = 106) recruited from Shandong Cancer Hospital. We first constructed a prognostic signature using 15 inflammation-related genes in The Cancer Genome Atlas (TCGA) cohort (n = 177) and further validated it in an independent International Cancer Genome Consortium (ICGC) cohort (n = 90) and our in-house cohort. PDAC patients with a higher risk score had poorer overall survival (OS) (P < 0.001; HR, 3.02; 95% CI, 1.94-4.70). The association between the prognostic signature and OS remained significant in the multivariable Cox regression adjusting for age, sex, alcohol exposure, diabetes, and stage (P < 0.001; HR, 2.91; 95% CI, 1.73-4.89). This gene signature also robustly predicted prognosis in the ICGC cohort (P = 0.01; HR, 1.94; 95% CI, 1.14-3.30) and our cohort (P < 0.001; HR, 2.40; 95% CI, 1.45-3.97). Immune subtype C3 (inflammatory) was enriched and CD8+ T cells were higher in patients with a lower risk score (P < 0.05). Furthermore, PDAC patients with higher risk scores were more sensitive to chemotherapy, immunotherapy, and PARP inhibitors (P < 0.05). In sum, we identified a novel gene signature that was associated with inflammatory response for risk stratification, prognosis prediction, and therapy guidance in PDAC patients. Future studies are warranted to validate the clinical utility of the signature.

Updated epithelial barrier dysfunction in chronic rhinosinusitis: Targeting pathophysiology and treatment response of tight junctions.

Tight junction (TJ) proteins establish a physical barrier between epithelial cells, playing a crucial role in maintaining tissue homeostasis by safeguarding host tissues against pathogens, allergens, antigens, irritants, etc. Recently, an increasing number of studies have demonstrated that abnormal expression of TJs plays an essential role in the development and progression of inflammatory airway diseases, including chronic obstructive pulmonary disease, asthma, allergic rhinitis, and chronic rhinosinusitis (CRS) with or without nasal polyps. Among them, CRS with nasal polyps is a prevalent chronic inflammatory disease that affects the nasal cavity and paranasal sinuses, leading to a poor prognosis and significantly impacting patients' quality of life. Its pathogenesis primarily involves dysfunction of the nasal epithelial barrier, impaired mucociliary clearance, disordered immune response, and excessive tissue remodeling. Numerous studies have elucidated the pivotal role of TJs in both the pathogenesis and response to traditional therapies in CRS. We therefore to review and discuss potential factors contributing to impair and repair of TJs in the nasal epithelium based on their structure, function, and formation process.

The vasculogenic mimicry related signature predicts the prognosis and immunotherapy response in renal clear cell carcinoma.

BACKGROUND: Clear cell carcinoma of the kidney is a common urological malignancy characterized by poor patient prognosis and treatment outcomes. Modulation of vasculogenic mimicry in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects. METHODS: We downloaded the data from renal clear cell carcinoma samples and vasculogenic mimicry-related genes to establish a new vasculogenic mimicry-related index (VMRI) using a machine learning approach. Based on VMRI, patients with renal clear cell carcinoma were divided into high VMRI and low VMRI groups, and patients' prognosis, clinical features, tumor immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analyzed. Finally, the function of CDH5 was explored in renal clear cell carcinoma cells. RESULTS: VMRI can be used for prognostic and immunotherapy efficacy prediction in a variety of cancers, which consists of four vasculogenic mimicry-related genes (CDH5, MMP9, MAPK1, and MMP13), is a reliable predictor of survival and grade in patients with clear cell carcinoma of the kidney and has been validated in multiple external datasets. We found that the high VMRI group presented higher levels of immune cell infiltration, which was validated by pathological sections. We performed molecular docking prediction of vasculogenic mimicry core target proteins and identified natural small molecule drugs with the highest affinity for the target protein. Knockdown of CDH5 inhibited the proliferation and migration of renal clear cell carcinoma. CONCLUSIONS: The VMRI identified in this study allows for accurate prognosis assessment of patients with renal clear cell carcinoma and identification of patient populations that will benefit from immunotherapy, providing valuable insights for future precision treatment of patients with renal clear cell carcinoma.

Thiotepa-busulfan-fludarabine-based conditioning as a promising approach prior to allogeneic hematopoietic stem cell transplantation in patients with blastic plasmacytoid dendritic cell neoplasm.

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive myeloid malignancy associated with a poor prognosis. Although allogeneic hematopoietic stem cell transplantation (allo-HSCT) has emerged as a potential treatment strategy for BPDCN, standardized conditioning regimens remain lacking. In this manuscript, we present two cases of BPDCN that were treated with a thiotepa-busulfan-fludarabine (TBF)-based conditioning regimen prior to allo-HSCT. Both cases demonstrated complete remission post-transplantation, sustained donor chimerism, and remission maintenance, suggesting the potential efficacy of the TBF conditioning regimen for BPDCN transplantation. Given the small sample size in our study, we emphasize caution and advocate for larger studies to confirm the efficacy of TBF in the treatment of BPDCN.