Self-regulation of the nuclear pore complex enables clogging-free crowded transport.

Nuclear pore complexes (NPCs) are the main conduits for macromolecular transport into and out of the nucleus of eukaryotic cells. The central component of the NPC transport mechanism is an assembly of intrinsically disordered proteins (IDPs) that fills the NPC channel. The channel interior is further crowded by large numbers of simultaneously translocating cargo-carrying and free transport proteins. How the NPC can efficiently, rapidly, and selectively transport varied cargoes in such crowded conditions remains ill understood. Past experimental results suggest that the NPC is surprisingly resistant to clogging and that transport may even become faster and more efficient as the concentration of transport protein increases. To understand the mechanisms behind these puzzling observations, we construct a computational model of the NPC comprising only a minimal set of commonly accepted consensus features. This model qualitatively reproduces the previous experimental results and identifies self-regulating mechanisms that relieve crowding. We show that some of the crowding-alleviating mechanisms-such as preventing saturation of the bulk flux-are "robust" and rely on very general properties of crowded dynamics in confined channels, pertaining to a broad class of selective transport nanopores. By contrast, the counterintuitive ability of the NPC to leverage crowding to achieve more efficient single-molecule translocation is "fine-tuned" and relies on the particular spatial architecture of the IDP assembly in the NPC channel.

Silk-protein-based gradient hydrogels with multimode reprogrammable shape changes for biointegrated devices.

Biocompatible and morphable hydrogels capable of multimode reprogrammable, and adaptive shape changes are potentially useful for diverse biomedical applications. However, existing morphable systems often rely on complicated structural designs involving cumbersome and energy-intensive fabrication processes. Here, we report a simple electric-field-activated protein network migration strategy to reversibly program silk-protein hydrogels with controllable and reprogrammable complex shape transformations. The application of a low electric field enables the convergence of net negatively charged protein cross-linking networks toward the anode (isoelectric point plane) due to the pH gradient generated in the process, facilitating the formation of a gradient network structure and systems suitable for three-dimensional shape change. These tunable protein networks can be reprogrammed or permanently fixed by control of the polymorphic transitions. We show that these morphing hydrogels are capable of conformally interfacing with biological tissues by programming the shape changes and a bimorph structure consisting of aligned carbon nanotube multilayers and the silk hydrogels was assembled to illustrate utility as an implantable bioelectronic device for localized low-voltage electrical stimulation of the sciatic nerve in a rabbit.

Kinetic cooperativity resolves bidirectional clogging within the nuclear pore complex.

As the main gatekeeper of the nucleocytoplasmic transport in eukaryotic cells, the nuclear pore complex (NPC) faces the daunting task of facilitating the bidirectional transport of a high volume of macromolecular cargoes while ensuring the selectivity, speed, and efficiency of this process. The competition between opposing nuclear import and export fluxes passing through the same channel is expected to pose a major challenge to transport efficiency. It has been suggested that phase separation-like radial segregation of import and export fluxes within the assembly of intrinsically disordered proteins that line the NPC pore could be a mechanism for ensuring efficient bidirectional transport. We examine the impact of radial segregation on the efficiency of bidirectional transport through the NPC using a coarse-grained computational model of the NPC. We find little evidence that radial segregation improves transport efficiency. By contrast, surprisingly, we find that NTR crowding may enhance rather than impair the efficiency of bidirectional transport although it decreases the available space in the pore. We identify mechanisms of this novel crowding-induced transport cooperativity through the self-regulation of cargo density and flux in the pore. These findings explain how the functional architecture of the NPC resolves the problem of efficient bidirectional transport, and provide inspiration for the alleviation of clogging in artificial selective nanopores.

Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study.

BACKGROUND: Accurate diagnosis of breast lesions and discrimination of axillary lymph node (ALN) metastases largely depend on radiologist experience. PURPOSE: To develop a deep learning-based whole-process system (DLWPS) for segmentation and diagnosis of breast lesions and discrimination of ALN metastasis. STUDY TYPE: Retrospective. POPULATION: 1760 breast patients, who were divided into training and validation sets (1110 patients), internal (476 patients), and external (174 patients) test sets. FIELD STRENGTH/SEQUENCE: 3.0T/dynamic contrast-enhanced (DCE)-MRI sequence. ASSESSMENT: DLWPS was developed using segmentation and classification models. The DLWPS-based segmentation model was developed by the U-Net framework, which combined the attention module and the edge feature extraction module. The average score of the output scores of three networks was used as the result of the DLWPS-based classification model. Moreover, the radiologists' diagnosis without and with the DLWPS-assistance was explored. To reveal the underlying biological basis of DLWPS, genetic analysis was performed based on RNA-sequencing data. STATISTICAL TESTS: Dice similarity coefficient (DI), area under receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and kappa value. RESULTS: The segmentation model reached a DI of 0.828 and 0.813 in the internal and external test sets, respectively. Within the breast lesions diagnosis, the DLWPS achieved AUCs of 0.973 in internal test set and 0.936 in external test set. For ALN metastasis discrimination, the DLWPS achieved AUCs of 0.927 in internal test set and 0.917 in external test set. The agreement of radiologists improved with the DLWPS-assistance from 0.547 to 0.794, and from 0.848 to 0.892 in breast lesions diagnosis and ALN metastasis discrimination, respectively. Additionally, 10 breast cancers with ALN metastasis were associated with pathways of aerobic electron transport chain and cytoplasmic translation. DATA CONCLUSION: The performance of DLWPS indicates that it can promote radiologists in the judgment of breast lesions and ALN metastasis and nonmetastasis. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 3.

Attention-based deep learning for breast lesions classification on contrast enhanced spectral mammography: a multicentre study.

BACKGROUND: This study aims to develop an attention-based deep learning model for distinguishing benign from malignant breast lesions on CESM. METHODS: Preoperative CESM images of 1239 patients, which were definitely diagnosed on pathology in a multicentre cohort, were divided into training and validation sets, internal and external test sets. The regions of interest of the breast lesions were outlined manually by a senior radiologist. We adopted three conventional convolutional neural networks (CNNs), namely, DenseNet 121, Xception, and ResNet 50, as the backbone architectures and incorporated the convolutional block attention module (CBAM) into them for classification. The performance of the models was analysed in terms of the receiver operating characteristic (ROC) curve, accuracy, the positive predictive value (PPV), the negative predictive value (NPV), the F1 score, the precision recall curve (PRC), and heat maps. The final models were compared with the diagnostic performance of conventional CNNs, radiomics models, and two radiologists with specialised breast imaging experience. RESULTS: The best-performing deep learning model, that is, the CBAM-based Xception, achieved an area under the ROC curve (AUC) of 0.970, a sensitivity of 0.848, a specificity of 1.000, and an accuracy of 0.891 on the external test set, which was higher than those of other CNNs, radiomics models, and radiologists. The PRC and the heat maps also indicated the favourable predictive performance of the attention-based CNN model. The diagnostic performance of two radiologists improved with deep learning assistance. CONCLUSIONS: Using an attention-based deep learning model based on CESM images can help to distinguishing benign from malignant breast lesions, and the diagnostic performance of radiologists improved with deep learning assistance.

Detection and classification of breast lesions using multiple information on contrast-enhanced mammography by a multiprocess deep-learning system: A multicenter study.

Objective: Accurate detection and classification of breast lesions in early stage is crucial to timely formulate effective treatments for patients. We aim to develop a fully automatic system to detect and classify breast lesions using multiple contrast-enhanced mammography (CEM) images. Methods: In this study, a total of 1,903 females who underwent CEM examination from three hospitals were enrolled as the training set, internal testing set, pooled external testing set and prospective testing set. Here we developed a CEM-based multiprocess detection and classification system (MDCS) to perform the task of detection and classification of breast lesions. In this system, we introduced an innovative auxiliary feature fusion (AFF) algorithm that could intelligently incorporates multiple types of information from CEM images. The average free-response receiver operating characteristic score (AFROC-Score) was presented to validate system's detection performance, and the performance of classification was evaluated by area under the receiver operating characteristic curve (AUC). Furthermore, we assessed the diagnostic value of MDCS through visual analysis of disputed cases, comparing its performance and efficiency with that of radiologists and exploring whether it could augment radiologists' performance. Results: On the pooled external and prospective testing sets, MDCS always maintained a high standalone performance, with AFROC-Scores of 0.953 and 0.963 for detection task, and AUCs for classification were 0.909 [95% confidence interval (95% CI): 0.822-0.996] and 0.912 (95% CI: 0.840-0.985), respectively. It also achieved higher sensitivity than all senior radiologists and higher specificity than all junior radiologists on pooled external and prospective testing sets. Moreover, MDCS performed superior diagnostic efficiency with an average reading time of 5 seconds, compared to the radiologists' average reading time of 3.2 min. The average performance of all radiologists was also improved to varying degrees with MDCS assistance. Conclusions: MDCS demonstrated excellent performance in the detection and classification of breast lesions, and greatly enhanced the overall performance of radiologists.

Identification of mutation patterns and circulating tumour DNA-derived prognostic markers in advanced breast cancer patients.

BACKGROUND: The correlations between circulating tumour DNA (ctDNA)-derived genomic markers and treatment response and survival outcome in Chinese patients with advanced breast cancer (ABC) have not been extensively characterized. METHODS: Blood samples from 141 ABC patients who underwent first-line standard treatment in Peking University Cancer Hospital were collected. A next-generation sequencing based liquid biopsy assay (PredicineCARE) was used to detect somatic mutations and copy number variations (CNVs) in ctDNA. A subset of matched blood samples and tumour tissue biopsies were compared to evaluate the concordance. RESULTS: Overall, TP53 (44.0%) and PIK3CA (28.4%) were the top two altered genes. Frequent CNVs included amplifications of ERBB2 (24.8%) and FGFR1 (8.5%) and deletions of CDKN2A (3.5%). PIK3CA/TP53 and FGFR1/2/3 variants were associated with drug resistance in hormone receptor-positive (HR +) and human epidermal growth factor receptor 2-positive (HER2 +) patients. The comparison of genomic variants across matched tumour tissue and ctDNA samples revealed a moderate to high concordance that was gene dependent. Triple-negative breast cancer (TNBC) patients harbouring TP53 or PIK3CA alterations had a shorter overall survival than those without corresponding mutations (P = 0.03 and 0.008). A high ctDNA fraction was correlated with a shorter progression-free survival (PFS) (P = 0.005) in TNBC patients. High blood-based tumor mutation burden (bTMB) was associated with a shorter PFS for HER2 + and TNBC patients (P = 0.009 and 0.05). Moreover, disease monitoring revealed several acquired genomic variants such as ESR1 mutations, CDKN2A deletions, and FGFR1 amplifications. CONCLUSIONS: This study revealed the molecular profiles of Chinese patients with ABC and the clinical validity of ctDNA-derived markers, including the ctDNA fraction and bTMB, for predicting treatment response, prognosis, and disease progression. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT03792529. Registered January 3rd 2019, https://clinicaltrials.gov/ct2/show/NCT03792529 .

The Role of Cohesiveness in the Permeability of the Spatial Assemblies of FG Nucleoporins.

Nuclear pore complexes (NPCs) conduct selective, bidirectional transport across the nuclear envelope. The NPC passageway is lined by intrinsically disordered proteins that contain hydrophobic phenylalanine-glycine (FG) motifs, known as FG nucleoporins (FG nups), that play the key role in the NPC transport mechanism. Cohesive interactions among the FG nups, which arise from the combination of hydrophobic, electrostatic, and other forces, have been hypothesized to control the morphology of the assemblies of FG nups in the NPC, as well as their permeability with respect to the transport proteins. However, the role of FG nup cohesiveness is still vigorously debated. Using coarse-grained polymer theory and numerical simulations, we study the effects of cohesiveness on the selective permeability of in vitro FG nup assemblies in different geometries that have served as proxies for the morphological and transport properties of the NPC. We show that in high-density FG nup assemblies, increase in cohesiveness leads to the decrease in their permeability, in accordance with the accepted view. On the other hand, the permeability of low-density assemblies is a nonmonotonic function of the cohesiveness, and a moderate increase in cohesiveness can enhance permeability. The density- and cohesiveness-dependent effects on permeability are explained by considering the free-energy cost associated with penetrating the FG nup assemblies. We discuss the implications of these findings for the organization and function of the NPC.

[Quality Analysis of Peanut Seed by Visible/Near-Infrared Spectra].

In this paper, three representative varieties of peanut seeds were selected for the experiment based on visible/near-infrared reflectance spectroscopy living in the wavelength rang from 600 to 1 100 nm. Firstly, spectral datas ware collected by the near-infrared fiber optic spectrometer, and the spectral features of the original spectral dates were extracted by the wavelet analysis. Then the principal component analysis (PCA) was used for cluster analysis of spectral features. Finally, the four principal components were applied as the inputs, the varieties category as the output and the Mahalanobis distance as the discriminant function of the recognition model, so a linear discriminant analysis model was established. In the 50 samples of each varieties, 30 samples were randomly selected as the training set, and the remaining 20 samples as the predictor set. The recognition model for three peanut varieties have a recognition rate of 95% on average. As the experimental results show that this method is reliable and effectively, and a new method to distinguish and discriminate the quality of peanut seeds was put forword.

Development of ovalbumin implants with different spatial configurations for treatment of peripheral nerve injury.

Peripheral nerve injury (PNI) seriously affects the health and life of patients, and is an urgent clinical problem that needs to be resolved. Nerve implants prepared from various biomaterials have played a positive role in PNI, but the effect should be further improved and thus new biomaterials is urgently needed. Ovalbumin (OVA) contains a variety of bioactive components, low immunogenicity, tolerance, antimicrobial activity, non-toxicity and biodegradability, and has the ability to promote wound healing, cell growth and antimicrobial properties. However, there are few studies on the application of OVA in neural tissue engineering. In this study, OVA implants with different spatial structures (membrane, fiber, and lyophilized scaffolds) were constructed by casting, electrospinning, and freeze-drying methods, respectively. The results showed that the OVA implants had excellent physicochemical properties and were biocompatible without significant toxicity, and can promote vascularization, show good histocompatibility, without excessive inflammatory response and immunogenicity. The in vitro results showed that OVA implants could promote the proliferation and migration of Schwann cells, while the in vivo results confirmed that OVA implants (the E5/70% and 20 kV 20 µL/min groups) could effectively regulate the growth of blood vessels, reduce the inflammatory response and promote the repair of subcutaneous nerve injury. Further on, the high-throughput sequencing results showed that the OVA implants up-regulated differential expression of genes related to biological processes such as tumor necrosis factor-α (TNF-α), phosphatidylinositide 3-kinases/protein kinase B (PI3K-Akt) signaling pathway, axon guidance, cellular adhesion junctions, and nerve regeneration in Schwann cells. The present study is expected to provide new design concepts and theoretical accumulation for the development of a new generation of nerve regeneration implantable biomaterials.

Enhanced home-field advantage in deep soil organic carbon decomposition: Insights from soil transplantation in subtropical forests.

Climate change affects microbial community physiological strategies and thus regulates global soil organic carbon (SOC) decomposition. However, SOC decomposition by microorganisms, depending on home-field advantage (HFA, indicating a faster decomposition rate in 'Home' than 'Away' conditions) or environmental advantage (EA, indicating a faster decomposition rate in warmer-wetter environments than in colder-drier environments) remains unknown. Here, a soil transplantation experiment was conducted between warmer-wetter and colder-drier evergreen broadleaved forests in subtropical China. Specifically, soil samples were collected along a 60 cm soil profile, including 0-15, 15-30, 30-45, and 45-60 cm layers after one year of transplantation. SOC fractions, soil chemical properties, and microbial communities were evaluated to assess where there was an HFA of EA in SOC decomposition, along with an exploration of internal linkages. Significant HFAs were observed, particularly in the deep soils (30-60 cm) (P < 0.05), despite the lack of a significant EA along a soil profile, which was attributed to environmental changes affecting soil fungal communities and constraining SOC decomposition in 'Away' conditions. The soils transplanted from warmer-wetter to colder-drier environments changed the proportions of Mortiereltomycota or Basidiomycota fungal taxa in deep soils. Furthermore, the shift from colder-drier to warmer-wetter environments decreased fungal α-diversity and the proportion of fungal necromass carbon, ultimately inhibiting SOC decomposition in 'Away' conditions. However, neither HFAs nor EAs were significantly present in the topsoil (0-30 cm), possibly due to the broader adaptability of bacterial communities in these layers. These results suggest that the HFA of SOC decomposition in deep soils may mostly depend on the plasticity of fungal communities. Moreover, these results highlight the key roles of microbial communities in the SOC decomposition of subtropical forests, especially in deep soils that are easily ignored.

A drug-free cardiovascular stent functionalized with tailored collagen supports in-situ healing of vascular tissues.

Drug-eluting stent implantation suppresses the excessive proliferation of smooth muscle cells to reduce in-stent restenosis. However, the efficacy of drug-eluting stents remains limited due to delayed reendothelialization, impaired intimal remodeling, and potentially increased late restenosis. Here, we show that a drug-free coating formulation functionalized with tailored recombinant humanized type III collagen exerts one-produces-multi effects in response to injured tissue following stent implantation. We demonstrate that the one-produces-multi coating possesses anticoagulation, anti-inflammatory, and intimal hyperplasia suppression properties. We perform transcriptome analysis to indicate that the drug-free coating favors the endothelialization process and induces the conversion of smooth muscle cells to a contractile phenotype. We find that compared to drug-eluting stents, our drug-free stent reduces in-stent restenosis in rabbit and porcine models and improves vascular neointimal healing in a rabbit model. Collectively, the one-produces-multi drug-free system represents a promising strategy for the next-generation of stents.

A strategy for mechanically integrating robust hydrogel-tissue hybrid to promote the anti-calcification and endothelialization of bioprosthetic heart valve.

Bioprosthetic heart valve (BHV) replacement has been the predominant treatment for severe heart valve diseases over decades. Most clinically available BHVs are crosslinked by glutaraldehyde (GLUT), while the high toxicity of residual GLUT could initiate calcification, severe thrombosis, and delayed endothelialization. Here, we construed a mechanically integrating robust hydrogel-tissue hybrid to improve the performance of BHVs. In particular, recombinant humanized collagen type III (rhCOLIII), which was precisely customized with anti-coagulant and pro-endothelialization bioactivity, was first incorporated into the polyvinyl alcohol (PVA)-based hydrogel via hydrogen bond interactions. Then, tannic acid was introduced to enhance the mechanical performance of PVA-based hydrogel and interfacial bonding between the hydrogel layer and bio-derived tissue due to the strong affinity for a wide range of substrates. In vitro and in vivo experimental results confirmed that the GLUT-crosslinked BHVs modified by the robust PVA-based hydrogel embedded rhCOLIII and TA possessed long-term anti-coagulant, accelerated endothelialization, mild inflammatory response and anti-calcification properties. Therefore, our mechanically integrating robust hydrogel-tissue hybrid strategy showed the potential to enhance the service function and prolong the service life of the BHVs after implantation.

IKVAV functionalized oriented PCL/Fe3O4 scaffolds for magnetically modulating DRG growth behavior.

The re-bridging of the deficient nerve is the main problem to be solved after the functional impairment of the peripheral nerve. In this study, a directionally aligned polycaprolactone/triiron tetraoxide (PCL/Fe3O4) fiber scaffolds were firstly prepared by electrospinning technique, and further then grafted with IKVAV peptide for regulating DRG growth and axon extension in peripheral nerve regeneration. The results showed that oriented aligned magnetic PCL/Fe3O4 composite scaffolds were successfully prepared by electrospinning technique and possessed good mechanical properties and magnetic responsiveness. The PCL/Fe3O4 scaffolds containing different Fe3O4 concentrations were free of cytotoxicity, indicating the good biocompatibility and low cytotoxicity of the scaffolds. The IKVAV-functionalized PCL/Fe3O4 scaffolds were able to guide and promote the directional extension of axons, the application of external magnetic field and the grafting of IKVAV peptides significantly further promoted the growth of DRGs and axons. The ELISA test results showed that the AP-10 F group scaffolds promoted the secretion of nerve growth factor (NGF) from DRG under a static magnetic field (SMF), thus promoting the growth and extension of axons. Importantly, the IKVAV-functionalized PCL/Fe3O4 scaffolds could significantly up-regulate the expression of Cntn2, PCNA, Sox10 and Isca1 genes related to adhesion, proliferation and magnetic receptor function under the stimulation of SMF. Therefore, IKVAV-functionalized PCL/Fe3O4 composite oriented scaffolds have potential applications in neural tissue engineering.

Biomimetic-inspired piezoelectric ovalbumin/BaTiO3 scaffolds synergizing with anisotropic topology for modulating Schwann cell and DRG behavior.

The treatment of peripheral nerve injury is a clinical challenge that tremendously affected the patients' health and life. Anisotropic topographies and electric cues can simulate the regenerative microenvironment of nerve from physical and biological aspects, which show promising application in nerve regeneration. However, most studies just unilaterally emphasize the effect of sole topological- or electric- cue on nerve regeneration, while rarely considering the synergistic function of both cues simultaneously. In this study, a biomimetic-inspired piezoelectric topological ovalbumin/BaTiO3 scaffold that can provide non-invasive electrical stimulation in situ was constructed by combining piezoelectric BaTiO3 nanoparticles and surface microtopography. The results showed that the incorporation of piezoelectric nanoparticles could improve the mechanical properties of the scaffolds, and the piezoelectric output of the scaffolds after polarization was significantly increased. Biological evaluation revealed that the piezoelectric topological scaffolds could regulate the orientation growth of SCs, promote axon elongation of DRG, and upregulate the genes expression referring to myelination and axon growth, thus rapidly integrated chemical-mechanical signals and transmitted them for effectively promoting neuronal myelination, which was closely related to peripheral neurogenesis. The study suggests that the anisotropic surface topology combined with non-invasive electronic stimulation of the ovalbumin/BaTiO3 scaffolds possess a promising application prospect in the repair and regeneration of peripheral nerve injury.

Effects of long-term no-tillage and different stover mulching amounts on soil carbon and nitrogen contents and enzyme activities of carbon and nitrogen cycle in Mollisols.

To understand the effects of different stover mulching amounts in no-tillage on soil carbon and nitrogen contents and enzyme activities, finding a stover mulching amount which can meet the requirement of soil carbon and nitrogen accumulation while maximizing economic benefits, we conducted a long-term conservation tillage field experiment since 2007 in Mollisols area of Northeast China. We analyzed soil carbon and nitrogen contents, enzyme activities and economic benefits under conventional tillage (Control, CT), no-tillage without stover mulching (NT0), no-tillage with 33% stover mulching (NT33), no-tillage with 67% stover mulching (NT67), and no-tillage with 100% stover mulching (NT100) before planting in May 2020. The results showed that compared with CT, NT0 did not affect soil organic carbon (SOC) and total nitrogen (TN) contents, but increased soil organic carbon recalcitrance and decreased the availability of dissolved organic nitrogen (DON) and ammonium nitrogen. Compared with NT0, no-tillage with stover mulching significantly increased SOC contents in 0-10 cm layer and increased with the amounts of stover. In addition, NT67 and NT100 significantly increased SOC stocks, facilitating the accumulation of soil organic matter. The effects of different stover mulching amounts on soil nitrogen content in 0-10 cm layer were different. Specifically, NT33 increased DON content and DON/TN, NT67 increased DON content, while NT100 increased TN content. Compared with CT, NT0 decreased peroxidase (POD) activity in 0-10 cm layer. Compared with NT0, NT33 increased ß-glucosidase (ßG), cellobiase (CB), 1,4-ß-N-acetylglucosaminidase (NAG), polyphenol oxidase (PPO) and POD activities, while NT67 only increased CB, NAG and POD activities in 0-10 cm soil layer, both alleviated microbial nutrient limitation. NT100 increased PPO activity in 10-20 cm layer. NT33 increased carbon conversion efficiency of stover compared with NT100, and had the highest economic benefit. In all, no-tillage with 33% stover mulching was the optimal strategy, which could promote nutrient circulation, boost stover utilization efficiency, improve the quality of Mollisols, and maximize guaranteed income.

Artificial intelligence-based classification of breast lesion from contrast enhanced mammography: a multicenter study.

PURPOSE: The authors aimed to establish an artificial intelligence (AI)-based method for preoperative diagnosis of breast lesions from contrast enhanced mammography (CEM) and to explore its biological mechanism. MATERIALS AND METHODS: This retrospective study includes 1430 eligible patients who underwent CEM examination from June 2017 to July 2022 and were divided into a construction set (n=1101), an internal test set (n=196), and a pooled external test set (n=133). The AI model adopted RefineNet as a backbone network, and an attention sub-network, named convolutional block attention module (CBAM), was built upon the backbone for adaptive feature refinement. An XGBoost classifier was used to integrate the refined deep learning features with clinical characteristics to differentiate benign and malignant breast lesions. The authors further retrained the AI model to distinguish in situ and invasive carcinoma among breast cancer candidates. RNA-sequencing data from 12 patients were used to explore the underlying biological basis of the AI prediction. RESULTS: The AI model achieved an area under the curve of 0.932 in diagnosing benign and malignant breast lesions in the pooled external test set, better than the best-performing deep learning model, radiomics model, and radiologists. Moreover, the AI model has also achieved satisfactory results (an area under the curve from 0.788 to 0.824) for the diagnosis of in situ and invasive carcinoma in the test sets. Further, the biological basis exploration revealed that the high-risk group was associated with the pathways such as extracellular matrix organization. CONCLUSIONS: The AI model based on CEM and clinical characteristics had good predictive performance in the diagnosis of breast lesions.

Novel Use of Circulating Tumor DNA to Identify Muscle-invasive and Non-organ-confined Upper Tract Urothelial Carcinoma.

BACKGROUND: Optimal patient selection for neoadjuvant chemotherapy prior to surgical extirpation is limited by the inaccuracy of contemporary clinical staging methods in high-risk upper tract urothelial carcinoma (UTUC). OBJECTIVE: To investigate whether the detection of plasma circulating tumor DNA (ctDNA) can predict muscle-invasive (MI) and non-organ-confined (NOC) UTUC. DESIGN, SETTING, AND PARTICIPANTS: Plasma cell-free DNA was prospectively collected from chemotherapy-naïve, high-risk UTUC patients undergoing surgical extirpation and sequenced using a 152-gene panel and low-pass whole-genome sequencing. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: To test for concordance, whole-exome sequencing was performed on matching tumor samples. The performance of ctDNA for predicting MI/NOC UTUC was summarized using the area under a receiver-operating curve, and a variant count threshold for predicting MI/NOC disease was determined by maximizing Youden's J statistic. Kaplan-Meier methods estimated survival, and Mantel-Cox log-rank testing assessed the association between preoperative ctDNA positivity and clinical outcomes. RESULTS AND LIMITATIONS: Of 30 patients enrolled prospectively, 14 were found to have MI/NOC UTUC. At least one ctDNA variant was detected from 21/30 (70%) patients, with 52% concordance with matching tumor samples. Detection of at least two panel-based molecular alterations yielded 71% sensitivity at 94% specificity to predict MI/NOC UTUC. Imposing this threshold in combination with a plasma copy number burden score of >6.5 increased sensitivity to 79% at 94% specificity. Furthermore, the presence of ctDNA was strongly prognostic for progression-free survival (PFS; 1-yr PFS 69% vs 100%, p < 0.001) and cancer-specific survival (CSS; 1-yr CSS 56% vs 100%, p = 0.016). CONCLUSIONS: The detection of plasma ctDNA prior to extirpative surgery was highly predictive of MI/NOC UTUC and strongly prognostic of PFS and CSS. Preoperative ctDNA demonstrates promise as a biomarker for selecting patients to undergo neoadjuvant chemotherapy prior to nephroureterectomy. PATIENT SUMMARY: Here, we show that DNA from upper tract urothelial tumors can be detected in the blood prior to surgical removal of the kidney or ureter. This circulating tumor DNA can be used to predict that upper tract urothelial carcinoma is invasive into the muscular lining of the urinary tract and may help identify those patients who could benefit from chemotherapy prior to surgery.

[Spectral properties of light migration in apple fruit tissue].

The present paper simulates laser wavelength 632 and 750 nm Gaussian beam migration in apple fruit tissue using Monte-Carlo method, and researches the spectral properties of absorption and scattering. It was shown that the special energy distribution characteristics of Gaussian beam influenced the diffusion of the laser in the tissue, the reflection, absorption and transmittance of 750 nm by tissue are lower, there are more photons interacting with tissue within the tissue, and they can more clearly reflect the information within the tissue. So, the transmission characteristics of the infrared light were relatively strong in biology tissue, which was convenient for researching biology tissue.

Bacterial community structure and assembly dynamics hinge on plant litter quality.

Litter decomposition is a fundamental ecosystem process controlling the biogeochemical cycling of energy and nutrients. Using a 360-day lab incubation experiment to control for environmental factors, we tested how litter quality (low C/N deciduous vs. high C/N coniferous litter) governed the assembly and taxonomic composition of bacterial communities and rates of litter decomposition. Overall, litter mass loss was significantly faster in soils amended with deciduous (DL) rather than coniferous (CL) litter. Communities degrading DL were also more taxonomically diverse and exhibited stochastic assembly throughout the experiment. By contrast, alpha-diversity rapidly declined in communities exposed to CL. Strong environmental selection and competitive biological interactions induced by molecularly complex, nutrient poor CL were reflected in a transition from stochastic to deterministic assembly after 180 days. Constraining how the diversity and assembly of microbial populations modulates core ecosystem processes, such as litter decomposition, will become increasingly important under novel climate conditions, and as policymakers and land managers emphasize soil carbon sequestration as a key natural climate solution.