GhEXL3 participates in brassinosteroids regulation of fiber elongation in Gossypium hirsutum.

Cotton fiber (Gossypium hirsutum) serves as an ideal model for investigating the molecular mechanisms of plant cell elongation at the single-cell level. Brassinosteroids (BRs) play a crucial role in regulating plant growth and development. However, the mechanism by which BR influences cotton fiber elongation remains incompletely understood. In this study, we identified EXORDIUM-like (GhEXL3) through transcriptome analysis of fibers from BR-deficient cotton mutant pagoda 1 (pag1) and BRI1-EMS-SUPPRESSOR 1 (GhBES1.4, encoding a central transcription factor of BR signaling) overexpression cotton lines. Knockout of GhEXL3 using CRISPR/Cas9 was found to impede cotton fiber elongation, while its overexpression promoted fiber elongation, suggesting a positive regulatory function for GhEXL3 in fiber elongation. Furthermore, in vitro ovule culture experiments revealed that the overexpression of GhEXL3 partially counteracted the inhibitory effects of brassinazole (BRZ) on cotton fiber elongation, providing additional evidence of GhEXL3 involvement in BR signaling pathways. Moreover, our findings demonstrate that GhBES1.4 directly binds to the E-box (CACGTG) motif in the GhEXL3 promoter region and enhances its transcription. RNA-seq analysis revealed that overexpression of GhEXL3 upregulated the expression of EXPs, XTHs, and other genes associated with fiber cell elongation. Overall, our study contributes to understanding the mechanism by which BR regulates the elongation of cotton fibers through the direct modulation of GhEXL3 expression by GhBES1.4.

An exploratory Q-matrix estimation method based on sparse non-negative matrix factorization.

Cognitive diagnostic assessment (CDA) is widely used because it can provide refined diagnostic information. The Q-matrix is the basis of CDA, and can be specified by domain experts or by data-driven estimation methods based on observed response data. The data-driven Q-matrix estimation methods have become a research hotspot because of their objectivity, accuracy, and low calibration cost. However, most of the existing data-driven methods require known prior knowledge, such as initial Q-matrix, partial q-vector, or the number of attributes. Under the G-DINA model, we propose to estimate the number of attributes and Q-matrix elements simultaneously without any prior knowledge by the sparse non-negative matrix factorization (SNMF) method, which has the advantage of high scalability and universality. Simulation studies are carried out to investigate the performance of the SNMF. The results under a wide variety of simulation conditions indicate that the SNMF has good performance in the accuracy of attribute number and Q-matrix elements estimation. In addition, a set of real data is taken as an example to illustrate its application. Finally, we discuss the limitations of the current study and directions for future research.

RNA m6A modification regulates cell fate transition between pluripotent stem cells and 2-cell-like cells.

N6-methyladenosine (m6A) exerts essential roles in early embryos, especially in the maternal-to-zygotic transition stage. However, the landscape and roles of RNA m6A modification during the transition between pluripotent stem cells and 2-cell-like (2C-like) cells remain elusive. Here, we utilised ultralow-input RNA m6A immunoprecipitation to depict the dynamic picture of transcriptome-wide m6A modifications during 2C-like transitions. We found that RNA m6A modification was preferentially enriched in zygotic genome activation (ZGA) transcripts and MERVL with high expression levels in 2C-like cells. During the exit of the 2C-like state, m6A facilitated the silencing of ZGA genes and MERVL. Notably, inhibition of m6A methyltransferase METTL3 and m6A reader protein IGF2BP2 is capable of significantly delaying 2C-like state exit and expanding 2C-like cells population. Together, our study reveals the critical roles of RNA m6A modification in the transition between 2C-like and pluripotent states, facilitating the study of totipotency and cell fate decision in the future.

Real-world data on ALK rearrangement test in Chinese advanced non-small cell lung cancer (RATICAL): a nationwide multicenter retrospective study.

BACKGROUND: Anaplastic lymphoma kinase (ALK) test in advanced non-small cell lung cancer (NSCLC) can help physicians provide target therapies for patients harboring ALK gene rearrangement. This study aimed to investigate the real-world test patterns and positive rates of ALK gene rearrangements in advanced NSCLC. METHODS: In this real-world study (ChiCTR2000030266), patients with advanced NSCLC who underwent an ALK rearrangement test in 30 medical centers in China between October 1, 2018 and December 31, 2019 were retrospectively analyzed. Interpretation training was conducted before the study was initiated. Quality controls were performed at participating centers using immunohistochemistry (IHC)-VENTANA-D5F3. The positive ALK gene rearrangement rate and consistency rate were calculated. The associated clinicopathological characteristics of ALK gene rearrangement were investigated as well. RESULTS: The overall ALK gene rearrangement rate was 6.7% in 23,689 patients with advanced NSCLC and 8.2% in 17,436 patients with advanced lung adenocarcinoma. The quality control analysis of IHC-VENTANA-D5F3 revealed an intra-hospital consistency rate of 98.2% (879/895) and an inter-hospital consistency rate of 99.2% (646/651). IHC-VENTANA-D5F3 was used in 53.6%, real-time polymerase chain reaction (RT-PCR) in 25.4%, next-generation sequencing (NGS) in 18.3%, and fluorescence in-situ hybridization (FISH) in 15.9% in the adenocarcinoma subgroup. For specimens tested with multiple methods, the consistency rates confirmed by IHC-VENTANA-D5F3 were 98.0% (822/839) for FISH, 98.7% (1,222/1,238) for NGS, and 91.3% (146/160) for RT-PCR. The overall ALK gene rearrangement rates were higher in females, patients of ≤ 35 years old, never smokers, tumor cellularity of > 50, and metastatic specimens used for testing in the total NSCLC population and adenocarcinoma subgroup (all P < 0.05). CONCLUSIONS: This study highlights the real-world variability and challenges of ALK test in advanced NSCLC, demonstrating a predominant use of IHC-VENTANA-D5F3 with high consistency and distinct clinicopathological features in ALK-positive patients. These findings underscore the need for a consensus on optimal test practices and support the development of refined ALK test strategies to enhance diagnostic accuracy and therapeutic decision-making in NSCLC.

Succinate dehydrogenase A deficient renal cell carcinoma: A rare renal tumor distinct from typical Succinate dehydrogenase deficient renal cell carcinoma.

Succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC) is a rare subtype of RCC classified as a molecularly defined RCC in the fifth edition of the WHO. Most gene alterations in patients with SDH-deficient RCC involve the SDHB subunit, with less involvement of the SDHC, SDHA, and SDHD subunits. Four cases of SDHA-deficient RCC have been reported in the literature, of which one case was associated with an NF2 gene mutation. Herein, we report six novel SDHA-deficient RCC cases, including two cases with NF2 gene mutations. In contrast to the typical morphology of SDH-deficient RCC, the six tumors mainly displayed glandular, sheet-like, or papillary growth patterns with prominent nucleoli (Grades 2-3), among which two cases with NF2 mutations had prominent nucleoli (Grade 3), large transparent vacuoles in the cytoplasm, and a large number of lymphocytes in the stroma. Six tumors showed negative immunohistochemical staining for SDHA and SDHB, and three cases presented with high expression of PD-L1. Second-generation sequencing revealed novel pathogenic somatic SDHA gene mutation and NF2 gene mutations in six and two tumors, respectively. Follow-up data were collected for the six patients with a follow-up time ranging from 7 to 268 months, and all six patients have survived to date. One patient received targeted therapy for tumor metastasis to the lungs after seven months, and another patient with an NF2 gene mutation received immunotherapy for lymph node metastasis revealed during surgery. SDHA-deficient RCCs with NF2 gene mutations have the ability to metastasize but might respond well to immunotherapy. For the first time, we report the largest number of SDHA-deficient RCC cases and comprehensively investigate their clinicopathological and molecular features to provide important guidance for diagnosis and clinical immunotherapy.

Interface-constrained catalytic hairpin assembly permits highly sensitive SERS signaling of miRNA.

The rapid and precise monitoring of peripheral blood miRNA levels holds paramount importance for disease diagnosis and treatment monitoring. In this study, we propose an innovative research strategy that combines the catalytic hairpin assembly reaction with SERS signal congregation and enhancement. This combination can significantly enhance the stability of SERS detection, enabling stable and efficient detection of miRNA. Specifically, our paper-based SERS detection platform incorporates a streptavidin-modified substrate, biotin-labeled catalytic hairpin assembly reaction probes, 4-ATP, and primer-co-modified gold nanoparticles. In the presence of miRNA, the 4-ATP and primer-co-modified gold nanoparticles can specifically recognize the miRNA and interact with the biotin-labeled CHA probes to initiate an interfacial catalytic hairpin assembly reaction. This enzyme-free high-efficiency catalytic process can accumulate a large amount of biotin on the gold nanoparticles, which then bind to the streptavidin on the substrate with the assistance of the driving liquid, forming red gold nanoparticle stripes. These provide a multitude of hotspots for SERS, enabling enhanced signal detection. This innovative design achieves a low detection limit of 3.47 fM while maintaining excellent stability and repeatability. This conceptually innovative detection platform offers new technological possibilities and solutions for clinical miRNA detection.

Causal effects of PM2.5 exposure on neuropsychiatric disorders and the mediation via gut microbiota: A Mendelian randomization study.

BACKGROUND: Growing evidence has revealed the impacts of exposure to fine particulate matter (PM2.5) and dysbiosis of gut microbiota on neuropsychiatric disorders, but the causal inference remains controversial due to residual confounders in observational studies. METHODS: This study aimed to examine the causal effects of exposure to PM2.5 on 4 major neuropsychiatric disorders (number of cases = 18,381 for autism spectrum disorder [ASD], 38,691 for attention deficit hyperactivity disorder [ADHD], 67,390 for schizophrenia, and 21,982 cases for Alzheimer's disease [AD]), and the mediation pathway through gut microbiota. Two-sample Mendelian randomization (MR) analyses were performed, in which genetic instruments were identified from genome-wide association studies (GWASs). The included GWASs were available from (1) MRC Integrative Epidemiology Unit (MRC-IEU) for PM2.5, PMcoarse, PM10, and NOX; (2) the Psychiatric Genomics Consortium (PGC) for ASD, ADHD, and schizophrenia; (3) MRC-IEU for AD; and (4) MiBioGen for gut microbiota. Multivariable MR analyses were conducted to adjust for exposure to NOX, PMcoarse, and PM10. We also examined the mediation effects of gut microbiota in the associations between PM2.5 exposure levels and neuropsychiatric disorders, using two-step MR analyses. RESULTS: Each 1 standard deviation (1.06 ug/m3) increment in PM2.5 concentrations was associated with elevated risk of ASD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.00-2.02), ADHD (1.51, 1.15-1.98), schizophrenia (1.47, 1.15-1.87), and AD (1.57, 1.16-2.12). For all the 4 neurodevelopmental disorders, the results were robust under various sensitivity analyses, while the MR-Egger method yielded non-significant outcomes. The associations remained significant for all the 4 neuropsychiatric disorders after adjusting for PMcoarse, while non-significant after adjusting for NOX and PM10. The effects of PM2.5 exposure on ADHD and schizophrenia were partially mediated by Lachnospiraceae and Barnesiella, with the proportions ranging from 8.31% to 15.77%. CONCLUSIONS: This study suggested that exposure to PM2.5 would increase the risk of neuropsychiatric disorders, partially by influencing the profile of gut microbiota. Comprehensive regulations on air pollutants are needed to help prevent neuropsychiatric disorders.

A comprehensive evaluation of influencing factors of neonicotinoid insecticides (NEOs) in farmland soils across China: First focus on film mulching.

Neonicotinoid insecticide (NEO) residues in agricultural soils have concerning and adverse effects on agroecosystems. Previous studies on the effects of farmland type on NEOs are limited to comparing greenhouses with open fields. On the other hand, both NEOs and microplastics (MPs) are commonly found in agricultural fields, but their co-occurrence characteristics under realistic fields have not been reported. This study grouped farmlands into three types according to the covering degree of the film, collected 391 soil samples in mainland China, and found significant differences in NEO residues in the soils of the three different farmlands, with greenhouse having the highest NEO residue, followed by farmland with film mulching and farmland without film mulching (both open fields). Furthermore, this study found that MPs were significantly and positively correlated with NEOs. As far as we know this is the first report to disclose the association of film mulching and MPs with NEOs under realistic fields. Moreover, multiple linear regression and random forest models were used to comprehensively evaluate the factors influencing NEOs (including climatic, soil, and agricultural indicators). The results indicated that the random forest model was more reliable, with MPs, farmland type, and total nitrogen having higher relative contributions.

[Analysis of dissatisfaction and related factors following total hip arthroplasty in patients with Crowe type â ¢-â £ developmental dysplasia of the hip].

OBJECTIVE: To investigate the satisfaction of patients with Crowe Ⅲ-Ⅳ developmental dysplasia of the hip(DDH) after total hip arthroplasty and the related factors. METHODS: A retrospective study included 169 patients with Crowe type Ⅲ-Ⅳ DDH who underwent total hip arthroplasty between March 2013 and March 2018. Patients were surveyed through WeChat, covering overall satisfaction with the operation, satisfaction with ten daily functions, and the top five questions perceived to have a great impact on daily life. Preoperative and postoperative hip function was evaluated by Harris score. RESULTS: One hundred and forty-five questionnaires were received, with a follow-up period ranging from 1 to 5 years with an average of (3.23±1.22) years. Among these patients, 118 patients were satisfied with the surgical outcomes, while 27 patients were dissatisfied, with the overall satisfaction rate of 81.38%(118/145). The top five problems affecting patient life were postoperative hip pain, limb length discrepancy, walking, stair climbing, and squatting. There were no statistical differences in age, sex, body mass index, preoperative Harris scores (P>0.05). However, the dissatisfied group had lower postoperative Harris scores. Postoperative hip pain and limb length discrepancy were identified as direct factors contributing to postoperative surgical dissatisfaction. CONCLUSION: Total hip arthroplasty for patients with Crowe type Ⅲ-Ⅳ DDH is challenging. Postoperative hip pain (mild or severe) and limb length discrepancy (>2 cm) are independent risk factors for postoperative dissatisfaction.

RGS20 promotes non-small cell lung carcinoma proliferation via autophagy activation and inhibition of the PKA-Hippo signaling pathway.

BACKGROUND: Novel therapeutic targets are urgently needed for treating drug-resistant non-small cell lung cancer (NSCLC) and overcoming drug resistance to molecular-targeted therapies. Regulator of G protein signaling 20 (RGS20) is identified as an upregulated factor in many cancers, yet its specific role and the mechanism through which RGS20 functions in NSCLC remain unclear. Our study aimed to identify the role of RGS20 in NSCLC prognosis and delineate associated cellular and molecular pathways. METHODS: Immunohistochemistry and lung cancer tissue microarray were used to verify the expression of RGS20 between NSCLC patients. CCK8 and cell cloning were conducted to determine the proliferation ability of H1299 and Anip973 cells in vitro. Furthermore, Transcriptome sequencing was performed to show enrichment genes and pathways. Immunofluorescence was used to detect the translocation changes of YAP to nucleus. Western blotting demonstrated different expressions of autophagy and the Hippo-PKA signal pathway. In vitro and in vivo experiments verified whether overexpression of RGS20 affect the proliferation and autophagy of NSCLC through regulating the Hippo pathway. RESULTS: The higher RGS20 expression was found to be significantly correlated with a poorer five-year survival rate. Further, RGS20 accelerated cell proliferation by increasing autophagy. Transcriptomic sequencing suggested the involvement of the Hippo signaling pathway in the action of RGS20 in NSCLC. RGS20 activation reduced YAP phosphorylation and facilitated its nuclear translocation. Remarkably, inhibiting Hippo signaling with GA-017 promoted cell proliferation and activated autophagy in RGS20 knock-down cells. However, forskolin, a GPCR activator, increased YAP phosphorylation and reversed the promoting effect of RGS20 in RGS20-overexpressing cells. Lastly, in vivo experiments further confirmed role of RGS20 in aggravating tumorigenicity, as its overexpression increased NSCLC cell proliferation. CONCLUSION: Our findings indicate that RGS20 drives NSCLC cell proliferation by triggering autophagy via the inhibition of PKA-Hippo signaling. These insights support the role of RGS20 as a promising novel molecular marker and a target for future targeted therapies in lung cancer treatment.

Electrochemical desulfurative formation of C-N bonds through selective activation of inert C(sp3)-S bonds.

In this study, we introduce an efficient, metal-free electrocatalytic desulfurative protocol for forming C-N bonds by selectively activating inert C(sp3)-S bonds of alkyl thioethers. This method offers a straightforward and environmentally friendly approach for modification of heterocyclic compounds from readily accessible thioethers. Preliminary mechanistic investigations suggest that the reaction proceeds via a carbocation intermediate. Furthermore, successful synthesis on a 10-gram scale was achieved in a continuous flow electrochemical reactor.

Enhanced and Sustainable Removal of Indoor Formaldehyde by Naturally Porous Bamboo Activated Carbon Supported with MnOx: Synergistic Effect of Adsorption and Oxidation.

Novel bamboo activated carbon (BAC) catalysts decorated with manganese oxides (MnOx) were prepared with varying MnOx contents through a facile one-step redox reaction. Due to the physical anchoring effect of the natural macropore structure for catalyst active components, homogeneous MnOx nanoparticles (NPs), and high specific surface area over catalyst surface, the BAC@MnOx-N (N = 1, 2, 3, 4, 5) catalyst shows encouraging adsorption and catalytic oxidation for indoor formaldehyde (HCHO) removal at room temperature. Dynamic adsorption and catalytic activity experiments were conducted. The higher Smicro (733 m2/g) and Vmicro/Vt (82.6%) of the BAC@MnOx-4 catalyst could facilitate its excellent saturated and breakthrough adsorption capacity (5.24 ± 0.42 mg/g, 2.43 ± 0.22 mg/g). The best performer against 2 ppm HCHO is BAC@MnOx-4 catalyst, exhibiting a maximum HCHO removal efficiency of 97% for 17 h without any deactivation as RH = 0, which is higher than those of other MnOx-based catalysts. The average oxidation state and in situ DRIFTS analysis reveal that abundant oxygen vacancies on the BAC@MnOx-4 catalyst could be identified as surface-active sites of decomposing HCHO into the intermediate species (dioxymethylene and formate). This study provides a potential approach to deposit MnOx nanoparticles onto the BAC surface, and this hybrid BAC@MnOx material is promising for indoor HCHO removal at room temperature.

Cross-Video Pedestrian Tracking Algorithm with a Coordinate Constraint.

Pedestrian tracking in surveillance videos is crucial and challenging for precise personnel management. Due to the limited coverage of a single video, the integration of multiple surveillance videos is necessary in practical applications. In the realm of pedestrian management using multiple surveillance videos, continuous pedestrian tracking is quite important. However, prevailing cross-video pedestrian matching methods mainly rely on the appearance features of pedestrians, resulting in low matching accuracy and poor tracking robustness. To address these shortcomings, this paper presents a cross-video pedestrian tracking algorithm, which introduces spatial information. The proposed algorithm introduces the coordinate features of pedestrians in different videos and a linear weighting strategy focusing on the overlapping view of the tracking process. The experimental results show that, compared to traditional methods, the method in this paper improves the success rate of target pedestrian matching and enhances the robustness of continuous pedestrian tracking. This study provides a viable reference for pedestrian tracking and crowd management in video applications.

Pollution characteristics and affecting factors of phthalate esters in agricultural soils in mainland China.

Phthalate esters (PAEs), the most commonly produced and used plasticizers, are widely used in plastic products and agroecosystems, posing risks to agricultural products and human health. However, current research on PAE pollution characteristics in agricultural soils in China is not comprehensive; affecting factors and relationships with microplastics and plasticizer organophosphate esters have not been sufficiently considered. In this study, farmland soil samples were collected with field questionnaires on a national scale across mainland China. The results showed that the detection rate of PAEs was 100% and the Σ16PAEs concentrations were 23.5 - 903 µg/kg. The level of PAEs was highest in the greenhouse, and significantly higher than that in mulched farmland (p < 0.05). The PAE concentration in northwestern China was the lowest among different physical geographic zones. PAEs in farmlands posed a low cancer risk to Chinese people. PAE pollution in farmlands was significantly (p < 0.05) affected by agronomic measures (such as disposal method), environmental factors, and socioeconomic factors. Overall, PAEs were significantly and positively correlated (p < 0.05) with organophosphate esters but not with microplastics. This study aims to provide scientific data for relevant prevention and control policies, as well as actionable recommendations for pollution reduction.

Multi-Contrast Complementary Learning for Accelerated MR Imaging.

Thanks to its powerful ability to depict high-resolution anatomical information, magnetic resonance imaging (MRI) has become an essential non-invasive scanning technique in clinical practice. However, excessive acquisition time often leads to the degradation of image quality and psychological discomfort among subjects, hindering its further popularization. Besides reconstructing images from the undersampled protocol itself, multi-contrast MRI protocols bring promising solutions by leveraging additional morphological priors for the target modality. Nevertheless, previous multi-contrast techniques mainly adopt a simple fusion mechanism that inevitably ignores valuable knowledge. In this work, we propose a novel multi-contrast complementary information aggregation network named MCCA, aiming to exploit available complementary representations fully to reconstruct the undersampled modality. Specifically, a multi-scale feature fusion mechanism has been introduced to incorporate complementary-transferable knowledge into the target modality. Moreover, a hybrid convolution transformer block was developed to extract global-local context dependencies simultaneously, which combines the advantages of CNNs while maintaining the merits of Transformers. Compared to existing MRI reconstruction methods, the proposed method has demonstrated its superiority through extensive experiments on different datasets under different acceleration factors and undersampling patterns.

Characteristics of dissolved organic matter (DOM) in Chinese farmland soils under different climate zone types: A molecular perspective.

Interactions between dissolved organic matter (DOM) and surrounding environments are highly complex. Understanding DOM at the molecular level can contribute to the management of soil pollution and safeguarding agricultural fields. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) has enabled a molecular-level understanding of DOM. Accordingly, in this study, we investigated soil samples from 27 different regions of mainland China with various soil types and climatic characteristics. Based on the geographical features of the four typical climatic zones in mainland China (temperate monsoon, temperate continental, subtropical monsoon, and Qinghai-Tibet Plateau climates), we employed high-resolution mass spectrometry to determine the molecular diversity of DOM under different climatic conditions. The results indicated that lignin and tannin-like substances were the most active categories of DOM in the soils. Collectively, the composition and unsaturation of DOM molecules are influenced by sunlight, precipitation, temperature, and human activity. All climatic regions contained a substantial number of characteristic molecules, with CHO and CHON constituting over 80%, and DOM containing nitrogen and sulfur was relatively more abundant in the monsoon regions. The complex composition of DOM incorporates various active functional groups, such as -NO2 and -ONO2. Furthermore, soil DOM in the monsoon regions showed higher unsaturation and facilitated various (bio) biochemical reactions in the soil.

Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.

BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baseline and restage enhanced computed tomography (CT) images and clinical characteristics to predict the response of metastatic lymph nodes to neoadjuvant chemotherapy (NACT) in locally advanced gastric cancer (LAGC). METHODS: We prospectively enrolled 112 patients with LAGC who received NACT from January 2021 to August 2022. After applying the inclusion and exclusion criteria, 98 patients were randomized 7:3 to the training cohort (n = 68) and validation cohort (n = 30). We established and compared three radiomics signatures based on three phases of CT images before and after NACT, namely radiomics-baseline, radiomics-delta, and radiomics-restage. Then, we developed a clinical model, DL model, and a nomogram to predict the response of LAGC after NACT. We evaluated the predictive accuracy and clinical validity of each model using the receiver operating characteristic curve and decision curve analysis, respectively. RESULTS: The radiomics-delta signature was the best predictor among the three radiomics signatures. So, we developed and validated a DL delta radiomics nomogram (DLDRN). In the validation cohort, the DLDRN produced an area under the receiver operating curve of 0.94 (95% confidence interval, 0.82-0.96) and demonstrated adequate differentiation of good response to NACT. Furthermore, the DLDRN significantly outperformed the clinical model and DL model (p < 0.001). The clinical utility of the DLDRN was confirmed through decision curve analysis. CONCLUSIONS: In patients with LAGC, the DLDRN effectively predicted a therapeutic response in metastatic lymph nodes, which could provide valuable information for individualized treatment.