Enantioselective [2+2]-cycloadditions with triplet photoenzymes.

Naturally evolved enzymes, despite their astonishingly large variety and functional diversity, operate predominantly through thermochemical activation. Integrating prominent photocatalysis modes into proteins, such as triplet energy transfer, could create artificial photoenzymes that expand the scope of natural biocatalysis1-3. Here, we exploit genetically reprogrammed, chemically evolved photoenzymes embedded with a synthetic triplet photosensitizer that are capable of excited-state enantio-induction4-6. Structural optimization through four rounds of directed evolution afforded proficient variants for the enantioselective intramolecular [2+2]-photocycloaddition of indole derivatives with good substrate generality and excellent enantioselectivities (up to 99% enantiomeric excess). A crystal structure of the photoenzyme-substrate complex elucidated the non-covalent interactions that mediate the reaction stereochemistry. This study expands the energy transfer reactivity7-10 of artificial triplet photoenzymes in a supramolecular protein cavity and unlocks an integrated approach to valuable enantioselective photochemical synthesis that is not accessible with either the synthetic or the biological world alone.

Optical manipulation of electronic dimensionality in a quantum material.

Exotic phenomena can be achieved in quantum materials by confining electronic states into two dimensions. For example, relativistic fermions are realized in a single layer of carbon atoms1, the quantized Hall effect can result from two-dimensional (2D) systems2,3, and the superconducting transition temperature can be considerably increased in a one-atomic-layer material4,5. Ordinarily, a 2D electronic system can be obtained by exfoliating the layered materials, growing monolayer materials on substrates, or establishing interfaces between different materials. Here we use femtosecond infrared laser pulses to invert the periodic lattice distortion sectionally in a three-dimensional (3D) charge density wave material (1T-TiSe2), creating macroscopic domain walls of transient 2D ordered electronic states with unusual properties. The corresponding ultrafast electronic and lattice dynamics are captured by time-resolved and angle-resolved photoemission spectroscopy6 and ultrafast electron diffraction at energies of the order of megaelectronvolts7. Moreover, in the photoinduced 2D domain wall near the surface we identify a phase with enhanced density of states and signatures of potential opening of an energy gap near the Fermi energy. Such optical modulation of atomic motion is an alternative path towards realizing 2D electronic states and will be a useful platform upon which novel phases in quantum materials may be discovered.

Ubiquitous coexisting electron-mode couplings in high-temperature cuprate superconductors.

In conventional superconductors, electron-phonon coupling plays a dominant role in generating superconductivity. In high-temperature cuprate superconductors, the existence of electron coupling with phonons and other boson modes and its role in producing high-temperature superconductivity remain unclear. The evidence of electron-boson coupling mainly comes from angle-resolved photoemission (ARPES) observations of [Formula: see text]70-meV nodal dispersion kink and [Formula: see text]40-meV antinodal kink. However, the reported results are sporadic and the nature of the involved bosons is still under debate. Here we report findings of ubiquitous two coexisting electron-mode couplings in cuprate superconductors. By taking ultrahigh-resolution laser-based ARPES measurements, we found that the electrons are coupled simultaneously with two sharp modes at [Formula: see text]70meV and [Formula: see text]40meV in different superconductors with different dopings, over the entire momentum space and at different temperatures above and below the superconducting transition temperature. These observations favor phonons as the origin of the modes coupled with electrons and the observed electron-mode couplings are unusual because the associated energy scales do not exhibit an obvious energy shift across the superconducting transition. We further find that the well-known "peak-dip-hump" structure, which has long been considered a hallmark of superconductivity, is also omnipresent and consists of "peak-double dip-double hump" finer structures that originate from electron coupling with two sharp modes. These results provide a unified picture for the [Formula: see text]70-meV and [Formula: see text]40-meV energy scales and their evolutions with momentum, doping and temperature. They provide key information to understand the origin of these energy scales and their role in generating anomalous normal state and high-temperature superconductivity.

Fuse feeds as one: cross-modal framework for general identification of AMPs.

Antimicrobial peptides (AMPs) are promising candidates for the development of new antibiotics due to their broad-spectrum activity against a range of pathogens. However, identifying AMPs through a huge bunch of candidates is challenging due to their complex structures and diverse sequences. In this study, we propose SenseXAMP, a cross-modal framework that leverages semantic embeddings of and protein descriptors (PDs) of input sequences to improve the identification performance of AMPs. SenseXAMP includes a multi-input alignment module and cross-representation fusion module to explore the hidden information between the two input features and better leverage the fusion feature. To better address the AMPs identification task, we accumulate the latest annotated AMPs data to form more generous benchmark datasets. Additionally, we expand the existing AMPs identification task settings by adding an AMPs regression task to meet more specific requirements like antimicrobial activity prediction. The experimental results indicated that SenseXAMP outperformed existing state-of-the-art models on multiple AMP-related datasets including commonly used AMPs classification datasets and our proposed benchmark datasets. Furthermore, we conducted a series of experiments to demonstrate the complementary nature of traditional PDs and protein pre-training models in AMPs tasks. Our experiments reveal that SenseXAMP can effectively combine the advantages of PDs to improve the performance of protein pre-training models in AMPs tasks.

Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR.

BACKGROUND: The Alpine Merino is a new breed of fine-wool sheep adapted to the cold and arid climate of the plateau in the world. It has been popularized in Northwest China due to its superior adaptability as well as excellent production performance. Those traits related to body weight, wool yield, and wool fiber characteristics, which are economically essential traits in Alpine Merino sheep, are controlled by QTL (Quantitative Trait Loci). Therefore, the identification of QTL and genetic markers for these key economic traits is a critical step in establishing a MAS (Marker-Assisted Selection) breeding program. RESULTS: In this study, we constructed the high-density genetic linkage map of Alpine Merino sheep by sequencing 110 F1 generation individuals using WGR (Whole Genome Resequencing) technology. 14,942 SNPs (Single Nucleotide Polymorphism) were identified and genotyped. The map spanned 2,697.86 cM, with an average genetic marker interval of 1.44 cM. A total of 1,871 high-quality SNP markers were distributed across 27 linkage groups, with an average of 69 markers per LG (Linkage Group). Among them, the smallest genetic distance is 19.62 cM for LG2, while the largest is 237.19 cM for LG19. The average genetic distance between markers in LGs ranged from 0.24 cM (LG2) to 3.57 cM (LG17). The marker density in the LGs ranged from LG14 (39 markers) to LG1 (150 markers). CONCLUSIONS: The first genetic map of Alpine Merino sheep we constructed included 14,942 SNPs, while 46 QTLs associated with body weight, wool yield and wool fiber traits were identified, laying the foundation for genetic studies and molecular marker-assisted breeding. Notably, there were QTL intervals for overlapping traits on LG4 and LG8, providing potential opportunities for multi-trait co-breeding and further theoretical support for selection and breeding of ultra-fine and meaty Alpine Merino sheep.

Selection signatures of wool color in Gangba sheep revealed by genome-wide SNP discovery.

BACKGROUND: Gangba sheep as a famous breed of Tibetan sheep, its wool color is mainly white and black. Gangba wool is economically important as a high-quality raw material for Tibetan blankets and Tibetan serge. However, relatively few studies have been conducted on the wool color of Tibetan sheep. RESULTS: To fill this research gap, this study conducted an in-depth analysis of two populations of Gangba sheep (black and white wool color) using whole genome resequencing to identify genetic variation associated with wool color. Utilizing PCA, Genetic Admixture, and N-J Tree analyses, the present study revealed a consistent genetic relationship and structure between black and white wool colored Gangba sheep populations, which is consistent with their breed history. Analysis of selection signatures using multiple methods (FST, π ratio, Tajima's D), 370 candidate genes were screened in the black wool group (GBB vs GBW); among them, MC1R, MLPH, SPIRE2, RAB17, SMARCA4, IRF4, CAV1, USP7, TP53, MYO6, MITF, MC2R, TET2, NF1, JAK1, GABRR1 genes are mainly associated with melanin synthesis, melanin delivery, and distribution. The enrichment results of the candidate genes identified 35 GO entries and 19 KEGG pathways associated with the formation of the black phenotype. 311 candidate genes were screened in the white wool group (GBW vs GBB); among them, REST, POU2F1, ADCY10, CCNB1, EP300, BRD4, GLI3, and SDHA genes were mainly associated with interfering with the differentiation of neural crest cells into melanocytes, affecting the proliferation of melanocytes, and inhibiting melanin synthesis. 31 GO entries and 22 KEGG pathways were associated with the formation of the white phenotype. CONCLUSIONS: This study provides important information for understanding the genetic mechanism of wool color in Gangba, and provides genetic knowledge for improving and optimizing the wool color of Tibetan sheep. Genetic improvement and selective breeding to produce wool of specific colors can meet the demand for a diversity of wool products in the Tibetan wool textile market.

2α, 3α, 24-Thrihydroxyurs-12-en-24-ursolic acid enhances the cytotoxic effect of cisplatin on oral cancer cells by down-regulating autophagy.

This study aimed to investigate the effect and mechanism of 2α, 3α, 24-thrihydroxyurs-12-en-24-ursolic acid (TEOA) alone or in combination with cisplatin on oral cancer. TEOA, a pentacyclic triterpenoid compound isolated from the roots of Actinidia eriantha, has demonstrated antitumor activity in preclinical experiments. However, its role in oral cancer remains poorly understood. Our findings revealed that a low concentration of TEOA did not exhibit significant cytotoxicity against oral squamous cell carcinoma cells. However, when combined with cisplatin, TEOA showed a significant therapeutic effect. The combined treatments resulted in a significant inhibition of proliferation and migration and a significant increase in apoptosis of squamous cell carcinoma cells. Cisplatin exposure increased autophagy levels, which may contribute to chemoresistance. Of note, the presence of TEOA significantly inhibited cisplatin-induced autophagy, leading to improved chemotherapy efficacy. Our findings indicate that a mild low dosage of TEOA may enhance the cytotoxic effect of cisplatin by downregulating autophagy in oral cancer cells.

Rapid Mining of Fast Ion Conductors via Subgraph Isomorphism Matching.

The rapidly evolving field of inorganic solid-state electrolytes (ISSEs) has been driven in recent years by advances in data-mining techniques, which facilitates the high-throughput computational screening for candidate materials in the databases. The key to the mining process is the selection of critical features that underline the similarity of a material to an existing ISSE. Unfortunately, this selection is generally subjective and frequently under debate. Here we propose a subgraph isomorphism matching method that allows an objective evaluation of the similarity between two compounds according to the topology of the local atomic environment. The matching algorithm has been applied to discover four structure types that are highly analogous to the LiTi2(PO4)3 NASICON prototype. We demonstrate that the local atomic environments similar to LiTi2(PO4)3 endow these four structures with favorable Li diffusion tunnels and ionic conductivity on par with those of the prototype. By further taking into account the electronic structure and electrochemical stability window, 13 compounds are identified to be potential ISSEs. Our findings not only offer a promising approach toward rapid mining of fast ion conductors without limitation in the compositional range but also reveal insights into the design of ISSEs according to the topology of their framework structures.

Crystal Structure Assignment for Unknown Compounds from X-ray Diffraction Patterns with Deep Learning.

Determining the structures of previously unseen compounds from experimental characterizations is a crucial part of materials science. It requires a step of searching for the structure type that conforms to the lattice of the unknown compound, which enables the pattern matching process for characterization data, such as X-ray diffraction (XRD) patterns. However, this procedure typically places a high demand on domain expertise, thus creating an obstacle for computer-driven automation. Here, we address this challenge by leveraging a deep-learning model composed of a union of convolutional residual neural networks. The accuracy of the model is demonstrated on a dataset of over 60,000 different compounds for 100 structure types, and additional categories can be integrated without the need to retrain the existing networks. We also unravel the operation of the deep-learning black box and highlight the way in which the resemblance between the unknown compound and a structure type is quantified based on both local and global characteristics in XRD patterns. This computational tool opens new avenues for automating structure analysis on materials unearthed in high-throughput experimentation.

Halide Anions Tuning of Lead-Free Perovskite-Type Ferroelectric Semiconductors with Inverse High-Temperature Symmetry Breaking.

There is a noticeable gap in the literature regarding research on halogen-substitution-regulated ferroelectric semiconductors featuring multiple phase transitions. Here, a new category of 1D perovskite ferroelectrics (DFP)2 SbX5 (DFP+ = 3,3-difluoropyrrolidium, X- = I- , Br- , abbreviated as I-1 and Br-2) with twophase transitions (PTs) is reported. The first low-temperature PT is a mmmFmm2 ferroelectric PT, while the high-temperature PT is a counterintuitive inverse temperature symmetry-breaking PT. By the substitution of iodine with bromine, the Curie temperature (Tc) significantly increases from 348 K of I-1 to 374 K of Br-2. Their ferroelectricity and pyroelectricity are improved (Ps value from 1.3 to 4.0 µC cm-2 , pe value from 0.2 to 0.48 µC cm-2  K-1 for I-1 and Br-2), while their optical bandgaps increased from 2.1 to 2.7 eV. A critical slowing down phenomenon is observed in the dielectric measurement of I-1 while Br-2 exhibits the ferroelastic domain. Structural and computational analyses elucidate that the order-disorder movement of cations and the distortion of the chain perovskite [SbX5 ]2- anions skeleton lead to PT. The semiconductor properties are determined by [SbX5 ]2- anions. The findings contribute to the development of ferroelectric semiconductors and materials with multiple PTs and provide materials for potential applications in the optoelectronic field.

Can uric acid affect the immune microenvironment in bladder cancer? A single-center multi-omics study.

Metabolic abnormalities are one of the important factors in bladder cancer (BCa) progression and microenvironmental disturbance. As an important product of purine metabolism, uric acid's (UA) role in BCa metabolism and immunotherapy remains unclear. In this study, we conducted a retrospective analysis of a cohort comprising 39 BCa patients treated with PD-1 and 169 patients who underwent radical cystectomy at Shanghai Tenth People's Hospital. Kaplan-Meier curves and Cox regression analysis showed that the prognosis of patients with high UA is worse (p = 0.007), and high UA is an independent risk factor for cancer specific survival in patients with BCa (p = 0.025). We established a hyperuricemia mouse model with BCa subcutaneous xenografts in vivo. The results revealed that the subcutaneous tumors of hyperuricemia mice had a greater weight and volume in comparison with the control group. Through flow cytometric analysis, the proportion of CD8+ and CD4+ T cells in these subcutaneous tumors was seen to decline significantly. We also evaluated the relationship of UA and BCa by muti-omic analysis. UA related genes were significantly increased in the CD8+ T cell of non-responders to immunotherapy by single-cell sequencing. An 11-gene UA related signature was constructed and the risk score negatively correlated with various immune cells and immune checkpoints. Finally, a nomogram was established using a UA related signature to forecast the survival rate of patients with BCa. Collectively, this study demonstrated that UA was an independent prognostic biomarker for BCa and was associated with worse immunotherapy response.

Event recognition method based on feature synthesizing for a zero-shot intelligent distributed optical fiber sensor.

Phase-sensitive optical time domain reflectometer (Φ-OTDR) is an emergent distributed optical sensing system with the advantages of high localization accuracy and high sensitivity. It has been widely used for intrusion identification, pipeline monitoring, under-ground tunnel monitoring, etc. Deep learning-based classification methods work well for Φ-OTDR event recognition tasks with sufficient samples. However, the lack of training data samples is sometimes a serious problem for these data-driven algorithms. This paper proposes a novel feature synthesizing approach to solve this problem. A mixed class approach and a reinforcement learning-based guided training method are proposed to realize high-quality feature synthesis. Experiment results in the task of eight event classifications, including one unknown class, show that the proposed method can achieve an average classification accuracy of 42% for the unknown class and obtain its event type, meanwhile achieving a 74% average overall classification accuracy. This is 29% and 7% higher, respectively, than those of the ordinary instance synthesizing method. Moreover, this is the first time that the Φ-OTDR system can recognize a specific event and tell its event type without collecting its data sample in advance.

Suppression of DNMT2/3 by proinflammatory cytokines inhibits CtBP1/2-dependent genes to promote the occurrence of atrophic nonunion.

Failure of bone healing after fracture often results in nonunion, but the underlying mechanism of nonunion pathogenesis is poorly understood. Herein, we provide evidence to clarify that the inflammatory microenvironment of atrophic nonunion (AN) mice suppresses the expression levels of DNA methyltransferases 2 (DNMT2) and 3A (DNMT3a), preventing the methylation of CpG islands on the promoters of C-terminal binding protein 1/2 (CtBP1/2) and resulting in their overexpression. Increased CtBP1/2 acts as transcriptional corepressors that, along with histone acetyltransferase p300 and Runt-related transcription factor 2 (Runx2), suppress the expression levels of six genes involved in bone healing: BGLAP (bone gamma-carboxyglutamate protein), ALPL (alkaline phosphatase), SPP1 (secreted phosphoprotein 1), COL1A1 (collagen 1a1), IBSP (integrin binding sialoprotein), and MMP13 (matrix metallopeptidase 13). We also observe a similar phenomenon in osteoblast cells treated with proinflammatory cytokines or treated with a DNMT inhibitor (5-azacytidine). Forced expression of DNMT2/3a or blockage of CtBP1/2 with their inhibitors can reverse the expression levels of BGLAP/ALPL/SPP1/COL1A1/IBSP/MMP13 in the presence of proinflammatory cytokines. Administration of CtBP1/2 inhibitors in fractured mice can prevent the incidence of AN. Thus, we demonstrate that the downregulation of bone healing genes dependent on proinflammatory cytokines/DNMT2/3a/CtBP1/2-p300-Runx2 axis signaling plays a critical role in the pathogenesis of AN. Disruption of this signaling may represent a new therapeutic strategy to prevent AN incidence after bone fracture.

Prognosis prediction and risk stratification of transarterial chemoembolization or intraarterial chemotherapy for unresectable hepatocellular carcinoma based on machine learning.

OBJECTIVE: To develop and validate a risk scoring scale model (RSSM) for stratifying prognostic risk after intra-arterial therapies (IATs) for hepatocellular carcinoma (HCC). METHODS: Between February 2014 and October 2022, 2338 patients with HCC who underwent initial IATs were consecutively enrolled. These patients were divided into training datasets (TD, n = 1700), internal validation datasets (ITD, n = 428), and external validation datasets (ETD, n = 200). Five-years death was used to predict outcome. Thirty-four clinical information were input and five supervised machine learning (ML) algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBT), and Random Forest (RF), were compared using the areas under the receiver operating characteristic (AUC) with DeLong test. The variables with top important ML scores were used to build the RSSM by stepwise Cox regression. RESULTS: The CatBoost model achieved the best discrimination when 12 top variables were input, with the AUC of 0.851 (95% confidence intervals (CI), 0.833-0.868) for TD, 0.817 (95%CI, 0.759-0.857) for ITD, and 0.791 (95%CI, 0.748-0.834) for ETD. The RSSM was developed based on the immune checkpoint inhibitors (ICI) (hazard ratios (HR), 0.678; 95%CI 0.549, 0.837), tyrosine kinase inhibitors (TKI) (HR, 0.702; 95%CI 0.605, 0.814), local therapy (HR, 0.104; 95%CI 0.014, 0.747), response to the first IAT (HR, 4.221; 95%CI 2.229, 7.994), tumor size (HR, 1.054; 95%CI 1.038, 1.070), and BCLC grade (HR, 2.375; 95%CI 1.950, 2.894). Kaplan-Meier analysis confirmed the role of RSSM in risk stratification (p < 0.001). CONCLUSIONS: The RSSM can stratify accurately prognostic risk for HCC patients received IAT. On the basis, an online calculator permits easy implementation of this model. CLINICAL RELEVANCE STATEMENT: The risk scoring scale model could be easily implemented for physicians to stratify risk and predict prognosis quickly and accurately, thereby serving as a more favorable tool to strengthen individualized intra-arterial therapies and management in patients with unresectable hepatocellular carcinoma. KEY POINTS: • The Categorical Gradient Boosting (CatBoost) algorithm achieved the optimal and robust predictive ability (AUC, 0.851 (95%CI, 0.833-0.868) in training datasets, 0.817 (95%CI, 0.759-0.857) in internal validation datasets, and 0.791 (95%CI, 0.748-0.834) in external validation datasets) for prediction of 5-years death of hepatocellular carcinoma (HCC) after intra-arterial therapies (IATs) among five machine learning models. • We used the SHapley Additive exPlanations algorithms to explain the CatBoost model so as to resolve the black boxes of machine learning principles. • A simpler restricted variable, risk scoring scale model (RSSM), derived by stepwise Cox regression for risk stratification after intra-arterial therapies for hepatocellular carcinoma, provides the potential forewarning to adopt combination strategies for high-risk patients.

The Effect of Local Steroid Administration on Idiopathic Granulomatous Mastitis: A Systematic Review andMeta-Analysis.

INTRODUCTION: Idiopathic granulomatous mastitis (IGM) is a rare, benign inflammatory breast disease. Corticosteroids and surgery are the primary treatment options, and a growing number of publications have shown the effectiveness of local steroid administration (intralesional injection and topical corticosteroids). However, less is known about the specific details and effects of this treatment approach. The purpose of this meta-analysis was to summarize the details and evaluate the efficacy of local steroid administration for IGM. METHODS: The PubMed, Embase, Cochrane Library, and SinoMed databases were systematically searched from inception to July 2023 to identify relevant randomized controlled trials. The quality of the included studies was assessed, and meta-analysis and subgroup analysis were conducted to obtain the pooled effect sizes of the outcomes of interest. RESULTS: Eight trials comprising 613 patients were included. Local steroid administration included intralesional injection and topical steroid ointment, and control groups were mainly given systemic therapy (oral steroid) and surgical treatment. The meta-analysis showed that local steroid administration had a significant effect on the response rate (risk ratio [RR] = 1.35, 95% CI = [1.14-1.59], P = 0.0004). The incidence of side effects was also lower than that of systemic treatment (RR = 0.24, 95% CI = [0.13-0.43], P＜0.0001). There was no difference in the recurrence rate (RR = 0.8, 95% CI = [1.42-1.51], P = 0.48). CONCLUSIONS: Local steroid administration can increase the RR and decrease the incidence of side effects for IGM patients. There is no significant difference in the recurrence rate between the local steroid administration group and the control group. Further studies are needed to identify the effect in different stages and among pregnant women.

Differences between chronically Hepatitis B Virus-infected pregnant women with and without intrafamilial infection: from viral gene sequences to clinical manifestations.

INTRODUCTION: This study aimed to investigate the differences between pregnant women with chronic hepatitis B virus (HBV) infection and intrafamilial infection and those without intrafamilial infection. METHODS: HBV DNA was extracted from the sera of 16 pregnant women with chronic hepatitis B (CHB) and their family members for gene sequencing and phylogenetic analyses. A total of 74 pregnant women with CHB were followed up from the second trimester to three months postpartum. Viral markers and other laboratory indicators were compared between pregnant women with CHB with and without intrafamilial infection. RESULTS: The phylogenetic tree showed that HBV lines in the mother-spread pedigree shared a node, whereas there was an unrelated genetic background for HBV lines in individuals without intrafamilial infection. From delivery to three months postpartum, compared with those without intrafamilial infection, pregnant women with intrafamilial infection were related negatively to HBV DNA (ß=-0.43, 95% Confidence Interval [CI]: -0.76 to -0.12, p=0.009), HBeAg (ß=-195.15, 95% CI: -366.35 to -23.96, p=0.027), and hemoglobin changes (ß=-8.09, 95%CI: -15.54 to -0.64, p=0.035) and positively to changes in the levels of alanine aminotransferase (ß=73.9, 95%CI:38.92-108.95, p<0.001) and albumin (ß=2.73, 95% CI:0.23-5.23, p=0.033). CONCLUSION: The mother-spread pedigree spread model differs from that of non-intrafamilial infections. Pregnant women with intra-familial HBV infection have less hepatitis flares and liver damage, but their HBV DNA and HBeAg levels rebound faster after delivery, than those without intra-familial infection by the virus.

Genetic dissection and identification of stripe rust resistance genes in the wheat cultivar Lanhangxuan 121, a cultivar selected from a space mutation population.

Stripe rust is a devastating disease of wheat worldwide. Chinese wheat cultivar Lanhangxuan 121 (LHX121), selected from an advanced line L92-47 population that had been subjected to space mutation breeding displayed a consistently higher level of resistance to stipe rust than its parent in multiple field environments. The aim of this research was to establish the number and types of resistance genes in parental lines L92-47 and LHX121 using separate segregating populations. The first population developed from a cross between LHX121 and susceptible cultivar Xinong 822 comprised 278 F2:3 lines. The second validation population comprised 301 F2:3 lines from a cross between L92-47 and susceptible cultivar Xinong 979. Lines of two population were evaluated for stripe rust response at three sites during the 2018-2020 cropping season. Affymetrix 660 K SNP arrays were used to genotype the lines and parents. Inclusive composite interval mapping detected QTL QYrLHX.nwafu-2BS, QYrLHX.nwafu-3BS, and QYrLHX.nwafu-5BS for resistance in all three environments. Based on previous studies and pedigree information, QYrLHX.nwafu-2BS and QYrLHX.nwafu-3BS were likely to be Yr27 and Yr30 that are present in the L92-47 parent. QYrLHX.nwafu-5BS (YrL121) detected only in LHX121 was mapped to a 7.60 cM interval and explained 10.67-22.57% of the phenotypic variation. Compared to stripe rust resistance genes previously mapped to chromosome 5B, YrL121 might be a new adult plant resistance QTL. Furthermore, there were a number of variations signals using 35 K SNP array and differentially expressed genes using RNA-seq between L92-47 and LHX121 in the YrL121 region, indicating that they probably impair the presence and/or function of YrL121. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01461-0.

Study on the correlation of C-reactive protein/albumin ratio with sudden sensorineural hearing loss complicated by hypertension: a prospective study.

BACKGROUND: Understanding the pathophysiology of sudden sensorineural hearing loss (SSNHL) and identifying its clinical symptoms and associated risk factors are crucial for doctors in order to create effective prevention and therapeutic methods for this prevalent otolaryngologic emergency. METHODS: This study focuses on investigating the correlation between the C-reactive protein/albumin ratio (CAR) and SSNHL complicated by hypertension. In this study, 120 patients diagnosed with SSNHL were divided into groups with and without hypertension, and propensity score matching was used to compare and analyze the severity, type, prognosis, and CAR levels in SSNHL. RESULTS: The results showed that the SSNHL group with hypertension had significantly higher CAR levels, age, hearing curve abnormalities, and more severe hearing loss compared to the control group with isolated SSNHL. These differences were statistically significant (p < 0.001). Among different subtypes of SSNHL, CAR levels increased progressively with the advancement of the condition, and these differences were also statistically significant (p < 0.001). CONCLUSION: In summary, in patients with SSNHL, those with hypertension had higher CAR levels than those without a history of hypertension, and they experienced more severe hearing loss. Moreover, there was a clear correlation between CAR levels and the extent of SSNHL, indicating that greater CAR levels in patients with SSNHL are connected to more severe hearing loss in various hearing patterns and perhaps indicative of a poorer prognosis.

Overexpression of YAP confers radioresistance to esophageal cancer by altering the tumor microenvironment.

This study aimed to investigate the role of yes-associated protein (YAP) in the radiotherapy sensitivity of esophageal squamous cell carcinoma (ESCC). The clonogenic ability of ESCC cells was reduced after YAP silencing and radiotherapy. Overexpression of YAP promoted cell survival and had a synergistic effect with the hypoxic microenvironment. YAP was found to directly regulate hypoxia-inducible factor 1α (HIF-1α). Bioinformatics analysis revealed the involvement of YAP in modulating the tumor immune microenvironment. Inhibition of YAP expression reduced myeloid-derived suppressor cells (MDSCs) and influenced the immunosuppressive state, leading to radio resistance. These findings provide insights into the YAP-HIF-1α interaction and support YAP as a potential target for enhancing radiotherapy sensitivity in esophageal cancer.

Single-cell transcriptome sequencing analysis reveals intra-tumor heterogeneity in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignant tumor of the digestive system that poses a significant threat to human life and health. It is crucial to thoroughly investigate the mechanisms of esophageal carcinogenesis and identify potential key molecular events in its carcinogenesis. Single-cell transcriptome sequencing is an emerging technology that has gained prominence in recent years for studying molecular mechanisms, which may help to further explore the underlying mechanisms of the ESCC tumor microenvironment in depth. The single-cell dataset was obtained from GSE160269 in the Gene Expression Omnibus database, including 60 tumor samples and four paracancer samples. The single-cell data underwent dimensional reduction clustering analysis to identify clusters and annotate expression profiles. Subcluster analysis was conducted for each cellular taxon. Copy number variation analysis of tumor cell subpopulations was performed to primarily identify malignant cells within them. A proposed chronological analysis was performed to obtain the process of cell differentiation. In addition, cell communication, transcription factor analysis, and tumor pathway analysis were also performed. Relevant risk models and key genes were established by univariate COX regression and LASSO analysis. The key genes obtained from the screen were subjected to appropriate silencing and cellular assays, including CCK-8, 5-ethynyl-2'-deoxyuridine, colony formation, and western blot. Single-cell analysis revealed that normal samples contained a large number of fibroblasts, T cells, and B cells, with fewer other cell types, whereas tumor samples exhibited a relatively balanced distribution of cell types. Subclassification analysis of immune cells, fibroblasts, endothelial cells, and epithelial cells revealed their specific spatial characteristics. The prognostic risk model, we constructed successfully, achieved accurate prognostic stratification for ESCC patients. The screened key gene, UPF3A, was found to be significantly associated with the development of ESCC by cellular assays. This process might be linked to the phosphorylation of ERK and P38. Single-cell transcriptome analysis successfully revealed the distribution of cell types and major expressed factors in ESCC patients, which could facilitate future in-depth studies on the therapeutic mechanisms of ESCC.