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Abstract Cell‐specific transcriptional regulatory networks (TRNs) play vital roles in plant development and response to environmental stresses. However, traditional single‐cell mono‐omics techniques are unable to directly capture the relationships and dynamics between different layers of molecular information within the same cells. While advanced algorithm facilitates merging scRNA‐seq and scATAC‐seq datasets, accurate data integration remains a challenge, particularly when investigating cell‐type‐specific TRNs. By examining gene expression and chromatin accessibility simultaneously in 16,670 Arabidopsis root tip nuclei, the TRNs are reconstructed that govern root tip development under osmotic stress. In contrast to commonly used computational integration at cell‐type level, 12,968 peak‐to‐gene linkage is captured at the bona fide single‐cell level and construct TRNs at an unprecedented resolution. Furthermore, the unprecedented datasets allow to more accurately reconstruct the coordinated changes of gene expression and chromatin states during cellular state transition. During root tip development, chromatin accessibility of initial cells precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for subsequent differentiation steps. Pseudo‐time trajectory analysis reveal that osmotic stress can shift the functional differentiation of trichoblast. Candidate stress‐related gene‐linked cis‐regulatory elements (gl‐cCREs) as well as potential target genes are also identified, and uncovered large cellular heterogeneity under osmotic stress.

Background: Our objective was to assess the viability and oncological security of a gasless, transaxillary single-incision endoscopic procedure for performing total thyroidectomy and bilateral central neck dissection (TT + BCND). This study focused on patients diagnosed with bilateral papillary thyroid microcarcinoma (PTMC). Method: Between April 2020 and November 2021, 22 patients with bilateral PTMC underwent single-incision, gasless, transaxillary endoscopic TT + BCND. The patients’ clinicopathologic characteristics, surgical completeness and complications were analyzed. Result: Single-incision, gasless, transaxillary endoscopic TT + BCND was successful performed in all patients. The median (IQR) total surgical time was 143 (85–160) min. Only two patients experienced transient unilateral RLN palsy or transient hypocalcemia. All these complications resolved within 1 month after surgery. The median duration of hospital stay after surgery was 4 (3–4.5) days. The median hospitalization expense for these patients was 3848 (3781–4145) USD. The median number of lymph node yielded was 10.5 (8–15). The cosmetic outcomes were well-received by all individuals. Conclusion: In certain cases, gasless, transaxillary endoscopic TT + BCND procedure performed through a single incision proved to be a secure alternative for managing bilateral PTMC.

The classification of ablation images holds significant practical value in thermal protection structures, as it enables the assessment of heat and corrosion resistance of composites. This paper proposes an image‐based deep learning framework to identify the surface texture of carbon/phenolic composites ablative images. First, ablation experiments and collection of surface texture images of carbon/phenolic composites under different thermal environments were conducted in an electric arc wind tunnel. Then, a deep learning model based on a convolutional neural network (CNN) is developed for ablative image classification. The pre‐trained network is ultimately employed as the input for transfer learning. The network's feature extraction layer is trained using the ImageNet dataset, while the global average pooling addresses specific classification tasks. The test results demonstrate that the proposed method effectively classifies the relatively small surface texture dataset, enhances the classification performance of ablative surface texture with an accuracy of up to 97.6%, and exhibits robustness and generalization capabilities. Highlights: The paper proposes a new deep learning classification method for ablative images.A model highly sensitive to small and weak features is built.Transfer learning and data enhancement techniques are introduced into classification. [ABSTRACT FROM AUTHOR]

Covalently locking interacting proteins in situ is an attractive strategy for addressing the challenge of identifying weak and transient protein interactions, yet it is demanding to execute chemical reactions in live systems in a biocompatible, specific, and autonomous manner. Harnessing proximity-enabled reactivity of an unnatural amino acid incorporated in the bait toward a target residue of unknown proteins, here we genetically encode chemical cross-linkers (GECX) to cross-link interacting proteins spontaneously and selectively in live cells. Obviating an external trigger for reactivity and affording residue specificity, GECX enables the capture of low-affinity protein binding (affibody with Z protein), elusive enzyme-substrate interaction (ubiquitin-conjugating enzyme UBE2D3 with substrate PCNA), and endogenous proteins interacting with thioredoxin in E. coli cells, allowing for mass spectrometric identification of interacting proteins and crosslinking sites. This live cell chemistry-based approach should be valuable for investigating currently intangible protein interactions in vivo for better understanding of biology in physiological settings.

Cell‐specific transcriptional regulatory networks (TRNs) play vital roles in plant development and response to environmental stresses. However, traditional single‐cell mono‐omics techniques are unable to directly capture the relationships and dynamics between different layers of molecular information within the same cells. While advanced algorithm facilitates merging scRNA‐seq and scATAC‐seq datasets, accurate data integration remains a challenge, particularly when investigating cell‐type‐specific TRNs. By examining gene expression and chromatin accessibility simultaneously in 16,670 Arabidopsis root tip nuclei, the TRNs are reconstructed that govern root tip development under osmotic stress. In contrast to commonly used computational integration at cell‐type level, 12,968 peak‐to‐gene linkage is captured at the bona fide single‐cell level and construct TRNs at an unprecedented resolution. Furthermore, the unprecedented datasets allow to more accurately reconstruct the coordinated changes of gene expression and chromatin states during cellular state transition. During root tip development, chromatin accessibility of initial cells precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for subsequent differentiation steps. Pseudo‐time trajectory analysis reveal that osmotic stress can shift the functional differentiation of trichoblast. Candidate stress‐related gene‐linked cis‐regulatory elements (gl‐cCREs) as well as potential target genes are also identified, and uncovered large cellular heterogeneity under osmotic stress. [ABSTRACT FROM AUTHOR]

Genetically encoded non-canonical amino acids (ncAAs) with electrophilic moieties are excellent tools to investigate protein-protein interactions (PPIs) both in vitro and in vivo. These ncAAs, including a series of alkyl bromide-based ncAAs, mainly target cysteine residues to form protein-protein cross-links. Although some reactivities towards lysine and tyrosine residues have been reported, a comprehensive understanding of their reactivity towards a broad range of nucleophilic amino acids is lacking. Here we used a recently developed OpenUaa search engine to perform an in-depth analysis of mass spec data generated for Thioredoxin and its direct binding proteins cross-linked with an alkyl bromide-based ncAA, BprY. The analysis showed that, besides cysteine residues, BprY also targeted a broad range of nucleophilic amino acids. We validated this broad reactivity of BprY with Affibody/Z protein complex. We then successfully applied BprY to map a binding interface between SUMO2 and SUMO-interacting motifs (SIMs). BprY was further applied to probe SUMO2 interaction partners. We identified 264 SUMO2 binders, including several validated SUMO2 binders and many new binders. Our data demonstrated that BprY can be effectively used to probe protein-protein interaction interfaces even without cysteine residues, which will greatly expand the power of BprY in studying PPIs.

The heterogeneity of aging has been investigated at cellular and organic levels in the mouse model and human, but the exploration of aging heterogeneity at whole‐organism level is lacking. C. elegans is an ideal model organism for studying this question as they are self‐fertilized and cultured in the same chamber. Despite the tremendous progress made in single‐cell proteomic analysis, there is few single‐worm proteomics studies about aging. Here, we apply single‐worm quantitative mass spectrometry to quantify the heterogenous proteomic changes during aging across individuals, a total of 3524 proteins from 157 C. eleagns individuals were quantified. A reconstructed C. elegans aging trajectory and proteomic landscape of fast‐aging individuals were used to analyze the heterogeneity of C. elegans aging. We characterized inter‐individual proteomic variation during aging and revealed contributing factors that distinguish fast‐aging individuals from their siblings. [ABSTRACT FROM AUTHOR]

In our previous study, we have shown that CRLF1 can promote proliferation and metastasis of papillary thyroid carcinoma (PTC); however, the mechanism is unclear. Herein, we investigated whether the interaction of CRLF1 and MYH9 regulates proliferation and metastasis of PTC cells via the ERK/ETV4 axis. Immunohistochemistry (IHC), qPCR, and Western blotting assays were performed on PTC cells and normal thyroid cells to profile specific target genes. In vitro assays and in vivo assays were also conducted to examine the molecular mechanism. Results showed that CRLF1 directly bound MYH9 to enhance the stability of CRLF1 protein. Inhibition of MYH9 in PTC cells overexpressing CRLF1 significantly reversed malignant phenotypes, and CRLF1 overexpression activated ERK pathway, in vitro, and in vivo. RNA-sequencing revealed that ETV4 is a downstream target gene of CRLF1, which was up-regulated following ERK activation. Moreover, it was revealed that ETV4 is highly expressed in PTC tissues and is associated with poor prognosis. Finally, the ChIP assays showed that ETV4 induces the expression of matrix metalloproteinase 1 (MMP1) by binding to its promoter on PTC cells. Altogether, our study demonstrates that CRLF1 interacts with MYH9, promoting cell proliferation and metastasis via the ERK/ETV4 axis in PTC.

Proteins associate via weak and transient interactions that are challenging to identify in vivo. Here, the authors use a genetically encoded chemical cross-linker to covalently lock interacting proteins in live cells, allowing them to identify the captured proteins by mass spectrometry.

Abstract Background Aging is characterized by a gradual breakdown of cellular structures. Nuclear abnormality is a hallmark of progeria in human. Analysis of age-dependent nuclear morphological changes in Caenorhabditis elegans is of great value to aging research, and this calls for an automatic image processing method that is suitable for both normal and abnormal structures. Results Our image processing method consists of nuclear segmentation, feature extraction and classification. First, taking up the challenges of defining individual nuclei with fuzzy boundaries or in a clump, we developed an accurate nuclear segmentation method using fused two-channel images with seed-based cluster splitting and k-means algorithm, and achieved a high precision against the manual segmentation results. Next, we extracted three groups of nuclear features, among which five features were selected by minimum Redundancy Maximum Relevance (mRMR) for classifiers. After comparing the classification performances of several popular techniques, we identified that Random Forest, which achieved a mean class accuracy (MCA) of 98.69%, was the best classifier for our data set. Lastly, we demonstrated the method with two quantitative analyses of C. elegans nuclei, which led to the discovery of two possible longevity indicators. Conclusions We produced an automatic image processing method for two-channel C. elegans nucleus-labeled fluorescence images. It frees biologists from segmenting and classifying the nuclei manually.

Background: Epstein-Barr virus (EBV) is associated with many epithelial malignancies. A few reports on the association between EBV and thyroid tumorigenesis have been investigated. However, the conclusion is highly contradictory. We aimed to explore the role of EBV in thyroid nodule development and its clinical significance in a cohort from southern China.Method: We conducted a retrospective data abstraction study of patients who underwent thyroidectomy between December 2017 and June 2018. We retrospectively analyzed the clinicopathological parameters and EBV infection status (serological antibodies and in situ hybridization).Result: The cohort comprised 384 patients with newly diagnosed thyroid diseases, including 261 papillary thyroid carcinomas, 87 nodular goiters, 21 follicular adenomas, 12 follicular thyroid carcinomas, and 3 medullary thyroid carcinomas. Forty-two (10.9%) patients were identified as being serological antibody positive. However, there was no association between the clinicopathological parameters and serological antibody positivity. Additionally, none of the patients showed EBER expression in thyroid normal/cancer cell nuclei in in situ hybridization.Conclusion: In this study, no correlation between EBV and thyroid diseases was found in a cohort from southern China.