Primary adrenal lymphoma presenting as neurolymphomatosis: A case report.

RATIONALE: Primary adrenal lymphoma (PAL) is a very rare and highly aggressive disease. Neurolymphomatosis (NL) is a rare manifestation of lymphoma characterized by the infiltration of lymphoma cells into peripheral nerves, resulting in neurological symptoms. To date, there have been very few reported cases of PAL with NL. By reviewing the entire treatment process of the patient, we aim to enhance recognition of PAL complicated with NL and guide clinicians to pay attention to the diagnosis of such diseases. Early recognition and diagnosis of NL are crucial for appropriate management and treatment decisions. PATIENT CONCERNS: We report a case of PAL in a 64-year-old female whose initial symptoms were pain and weakness in the left leg, which progressively worsened. In the half month before admission, the patient also showed signs of cranial nerve damage, such as diplopia and facial asymmetry. DIAGNOSIS: Computed tomography of the abdomen revealed an occupying lesion in the left adrenal region. Electromyography and somatosensory evoked potential examination of the extremities suggested left lumbar plexus damage and complete damage to the right facial nerve. Adrenal biopsy confirmed diffuse large B-cell lymphoma. INTERVENTIONS: The patient was treated with the R-CHOP scheme (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) combined with lenalidomide. OUTCOME: After 6 rounds of chemotherapy, the symptoms improved slightly. However, the condition progressed, and the patient passed away 1 year later. LESSONS: Due to the nonspecific clinical presentation, patients with neurological damage should be alerted to the possibility of PAL and need to be evaluated thoroughly.

Tuning charge transport by manipulating concentration dependent single-molecule absorption configurations.

Understanding and tuning charge transport in molecular junctions is pivotal for crafting molecular devices with tailored functionalities. Here, we report a novel approach to manipulate the absorption configuration within a 4,4'-bipyridine (4,4'-BPY) molecular junction, utilizing the scanning tunneling microscope break junction technique in a concentration-dependent manner. Single-molecule conductance measurements demonstrate that the molecular junctions exhibit a significant concentration dependence, with a transition from high conductance (HC) to low conductance (LC) states as the concentration decreases. Moreover, we identified an additional conductance state in the molecular junctions besides already known HC and LC states. Flicker noise analysis and theoretical calculations provided valuable insights into the underlying charge transport mechanisms and single-molecule absorption configurations concerning varying concentrations. These findings contribute to a fundamental comprehension of charge transport in concentration-dependent molecular junctions. Furthermore, they offer promising prospects for controlling single-molecule adsorption configurations, thereby paving the way for future molecular devices.

Gut microbial co-metabolite 2-methylbutyrylcarnitine exacerbates thrombosis via binding to and activating integrin α2ß1.

Thrombosis represents the leading cause of death and disability upon major adverse cardiovascular events (MACEs). Numerous pathological conditions such as COVID-19 and metabolic disorders can lead to a heightened thrombotic risk; however, the underlying mechanisms remain poorly understood. Our study illustrates that 2-methylbutyrylcarnitine (2MBC), a branched-chain acylcarnitine, is accumulated in patients with COVID-19 and in patients with MACEs. 2MBC enhances platelet hyperreactivity and thrombus formation in mice. Mechanistically, 2MBC binds to integrin α2ß1 in platelets, potentiating cytosolic phospholipase A2 (cPLA2) activation and platelet hyperresponsiveness. Genetic depletion or pharmacological inhibition of integrin α2ß1 largely reverses the pro-thrombotic effects of 2MBC. Notably, 2MBC can be generated in a gut-microbiota-dependent manner, whereas the accumulation of plasma 2MBC and its thrombosis-aggravating effect are largely ameliorated following antibiotic-induced microbial depletion. Our study implicates 2MBC as a metabolite that links gut microbiota dysbiosis to elevated thrombotic risk, providing mechanistic insight and a potential therapeutic strategy for thrombosis.

Sliding ferroelectricity and the moiré effect in Janus bilayer MoSSe.

Two-dimensional van der Waals layered materials have attracted extensive attention in the field of low-dimensional ferroelectricity, on account of their readily delaminated structure and high-density information storage advantages. Here, we report the sliding ferroelectricity and moiré effects on the ferroelectricity in Janus bilayer MoSSe based on first-principles calculations. We focus on the changes of in-plane and out-of-plane polarizations due to sliding, and the calculations demonstrate that the in-plane and out-of-plane polarizations can be switched simultaneously by sliding. In addition, in moiré-twisted bilayer MoSSe, the complex stacking pattern and significant interlayer distance suppress the interlayer charge transfer, and the ferroelectric polarization is effectively suppressed. The polarization in the large-angle twisted structure is small but its direction can be adjusted by changing the twist angle. Our results emphasize the importance of low-dimensional ferroelectrics in van der Waals structures and pave a way for the search of sliding ferroelectric materials, as well as enriching the research on the ferroelectricity of large-angle twisted structures.

Diagnostic value of liver stiffness measurement combined with risk scores for esophagogastric variceal bleeding in patients with hepatitis B cirrhosis.

PURPOSE: To assess the predictive value of liver stiffness measurement (LSM) and three bleeding risk scoring systems for esophagogastric varices bleeding (EGVB) in patients with hepatitis B cirrhosis during hospitalization. METHODS: In this study, 210 patients who had hepatitis B cirrhosis were selected as the subjects. They were categorized into two groups based on whether EGVB occurred during hospitalization: a bleeding group (70 cases) and a non-bleeding group (140 cases). Logistic regression was used to analyze the factors related to the occurrence of EGVB, and the diagnostic performance was evaluated using a receiver operating characteristic (ROC) curve. RESULTS: Significant differences were observed between the two groups in systolic blood pressure, platelet count, albumin, urea nitrogen, LSM, pre-endoscopic Rockall score (PRS), Glasgow-Blatchford score (GBS), and AIMS65 score (P < 0.05). The correlation analysis showed that LSM had significant positive relationship with PRS, GBS and AIMS65 score. Logistic regression analysis revealed that LSM and GBS score were independent risk factors for EGVB occurrence during hospitalization. ROC curve analysis showed that the combined prediction model of LSM and GBS score had the best prediction performance for EGVB occurrence, with an ROC curve area of 0.811, which was significantly better than the three risk scoring systems (P < 0.05), but similar to the predicted value of LSM (P = 0.335). CONCLUSIONS: The combination of LSM and GBS score can significantly improve the predictive efficacy of EGVB occurrence in patients with hepatitis B cirrhosis during hospitalization, which has important clinical significance for patients' prognosis.

Zinc-a2-Glycoprotein Acts as a Component of PNN to Protect Hippocampal Neurons from Apoptosis.

In the adult mouse brain, perineuronal net (PNN), a highly structured extracellular matrix, surrounds subsets of neurons. The AZGP1 gene encodes zinc-2-glycoprotein (ZAG) is a lipid-mobilizing factor. However, its expression and distribution in the adult brain have been controversial. Here, for the first time, we demonstrate that the secreted ZAG is localized to Wisteria floribunda agglutinin (WFA)-positive PNNs around parvalbumin (PV)-expressing interneurons in the hippocampus, cortex, and a number of other PNN-bearing neurons and co-localizes with aggrecan, one of the components of PNNs. Few ZAG-positive nets were seen in the area without WFA staining by chondroitinase ABC (ChABC) which degrades glycosaminoglycans (GAGs) from the chondroitin sulfate proteoglycans (CSPGs) in the PNN. Reanalysis of single-cell sequencing data revealed that ZAG mRNA was mainly expressed in oligodendrocyte lineages, specifically in olfactory sheathing cells. The ZAG receptor ß3 adrenergic receptor (ß3AR) is also selectively co-localized with PV interneurons and CA2 pyramidal neurons in the hippocampus. In addition, molecular docking provides valuable new insights on how GAGs interfere with ZAG and ZAG/ß3AR complex. Finally, our results indicated that human recombinant ZAG could significantly inhibit serum derivation-induced cell apoptosis in HT22 cells. Our combined experimental and theoretical approach raises a unique hypothesis namely that ZAG may be a crucial functional attribute of PNNs in the brain to protect neuronal cell from apoptosis.

Interleukin-6 Facilitates Acute Myeloid Leukemia Chemoresistance via Mitofusin 1-Mediated Mitochondrial Fusion.

Acute myeloid leukemia (AML), an aggressive hematopoietic malignancy, exhibits poor prognosis and a high recurrence rate largely because of primary and secondary drug resistance. Elevated serum IL6 levels have been observed in patients with AML and are associated with chemoresistance. Chemoresistant AML cells are highly dependent on oxidative phosphorylation (OXPHOS), and mitochondrial network remodeling is essential for mitochondrial function. However, IL6-mediated regulation of mitochondrial remodeling and its effectiveness as a therapeutic target remain unclear. We aimed to determine the mechanisms through which IL6 facilitates the development of chemoresistance in AML cells. IL6 upregulated mitofusin 1 (MFN1)-mediated mitochondrial fusion, promoted OXPHOS, and induced chemoresistance in AML cells. MFN1 knockdown impaired the effects of IL6 on mitochondrial function and chemoresistance in AML cells. In an MLL::AF9 fusion gene-induced AML mouse model, IL6 reduced chemosensitivity to cytarabine (Ara-C), a commonly used antileukemia drug, accompanied by increased MFN1 expression, mitochondrial fusion, and OXPHOS status. In contrast, anti-IL6 antibodies downregulated MFN1 expression, suppressed mitochondrial fusion and OXPHOS, enhanced the curative effects of Ara-C, and prolonged overall survival. In conclusion, IL6 upregulated MFN1-mediated mitochondrial fusion in AML, which facilitated mitochondrial respiration, in turn, inducing chemoresistance. Thus, targeting IL6 may have therapeutic implications in overcoming IL6-mediated chemoresistance in AML. IMPLICATIONS: IL6 treatment induces MFN1-mediated mitochondrial fusion, promotes OXPHOS, and confers chemoresistance in AML cells. Targeting IL6 regulation in mitochondria is a promising therapeutic strategy to enhance the chemosensitivity of AML.

Collagen-related gene expression level predicts the prognosis and immune therapy response.

BACKGROUND: Gastric cancer patients responded differently to the same treatment strategy and had various prognoses for the lack of biomarkers to guide the therapy choice. METHODS: RNA data of a local gastric cancer cohort with 103 patients were processed and used to explore potential treatment guiding factors. Cluster analysis was performed by non-negative matrix factorization. The expression level of collagen-related genes was evaluated by ssGSEA named collagen score (CS). Data from TCGA, ACRG, and an immune therapy cohort were utilized to explore prognosis and efficacy. Prognostic predictive power of CS was assessed using the nomogram. RESULTS: In our study, local RNA data were processed by cluster analysis, and it was found that cluster 2 contained a worse tumor infiltration status. The GSEA result showed that collagen-related pathways were differentially activated in two clusters. In TCGA and ACRG cohorts, the CS can be used as an independent prognostic factor (TCGA OS: p = 0.018, HR = 3.5; ACRG OS: p = 0.014, HR = 4.88). An immunotherapy cohort showed that the patients with higher CS had a significantly worse ORR (p = 0.0025). The high CS group contained several cell death pathways down-regulated and contained the worse tumor microenvironment. The nomogram demonstrated the survival prediction capability of collagen score. CONCLUSION: CS was verified as an independent prognostic factor and potentially reflected the therapeutic effect of immunotherapy. The CS could provide a new way to evaluate the clinical prognosis and response information helping develop the collagen-targeted treatment.

Critical Roles of Protein Arginine Methylation in the Central Nervous System.

A remarkable post-transitional modification of both histones and non-histone proteins is arginine methylation. Methylation of arginine residues is crucial for a wide range of cellular process, including signal transduction, DNA repair, gene expression, mRNA splicing, and protein interaction. Arginine methylation is modulated by arginine methyltransferases and demethylases, like protein arginine methyltransferase (PRMTs) and Jumonji C (JmjC) domain containing (JMJD) proteins. Symmetric dimethylarginine and asymmetric dimethylarginine, metabolic products of the PRMTs and JMJD proteins, can be changed by abnormal expression of these proteins. Many pathologies including cancer, inflammation and immune responses have been closely linked to aberrant arginine methylation. Currently, the majority of the literature discusses the substrate specificity and function of arginine methylation in the pathogenesis and prognosis of cancers. Numerous investigations on the roles of arginine methylation in the central nervous system (CNS) have so far been conducted. In this review, we display the biochemistry of arginine methylation and provide an overview of the regulatory mechanism of arginine methyltransferases and demethylases. We also highlight physiological functions of arginine methylation in the CNS and the significance of arginine methylation in a variety of neurological diseases such as brain cancers, neurodegenerative diseases and neurodevelopmental disorders. Furthermore, we summarize PRMT inhibitors and molecular functions of arginine methylation. Finally, we pose important questions that require further research to comprehend the roles of arginine methylation in the CNS and discover more effective targets for the treatment of neurological diseases.

Red Blood Cell Distribution Width as a Potential Valuable Survival Predictor in Hepatitis B Virus-related Hepatocellular Carcinoma.

Objectives: Red blood cell distribution width (RDW) is a widely used clinical parameter recently deployed in predicting various cancers. This study aimed to evaluate the prognostic value of RDW in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Methods: We conducted a retrospective study of 745 patients with HBV-related HCC, 253 patients with chronic hepatitis B (CHB), and 256 healthy individuals to compare their hematological parameters and analyze their RDW levels. Potential risk factors for long-term all-cause mortality in patients with HBV-related HCC were predicted using Multivariate Cox regression. A nomogram was generated, and its performance was evaluated. Results: The RDW of patients with HBV-related HCC was significantly higher than that of those with CHB and healthy controls. In the former, splenomegaly, liver cirrhosis, larger tumor diameter, multiple tumor number, portal vein tumor thrombus, and lymphatic or distant metastasis were significantly increased, and the later the Child-Pugh grade and Barcelona clinic liver cancer stage, the higher the RDW. Furthermore, multivariate Cox regression analysis identified RDW as an independent risk factor for predicting long-term all-cause mortality in patients with HBV-related HCC. Finally, we successfully generated a nomogram incorporating RDW and validated its predictive ability. Conclusions: RDW is a potentially valuable hematological marker for predicting the survival and prognosis of patients with HBV-related HCC. The nomogram incorporating RDW can be used as an effective tool to plan the individualized treatment of such patients.

Semi-supervised nuclei segmentation based on multi-edge features fusion attention network.

The morphology of the nuclei represents most of the clinical pathological information, and nuclei segmentation is a vital step in current automated histopathological image analysis. Supervised machine learning-based segmentation models have already achieved outstanding performance with sufficiently precise human annotations. Nevertheless, outlining such labels on numerous nuclei is extremely professional needing and time consuming. Automatic nuclei segmentation with minimal manual interventions is highly needed to promote the effectiveness of clinical pathological researches. Semi-supervised learning greatly reduces the dependence on labeled samples while ensuring sufficient accuracy. In this paper, we propose a Multi-Edge Feature Fusion Attention Network (MEFFA-Net) with three feature inputs including image, pseudo-mask and edge, which enhances its learning ability by considering multiple features. Only a few labeled nuclei boundaries are used to train annotations on the remaining mostly unlabeled data. The MEFFA-Net creates more precise boundary masks for nucleus segmentation based on pseudo-masks, which greatly reduces the dependence on manual labeling. The MEFFA-Block focuses on the nuclei outline and selects features conducive to segment, making full use of the multiple features in segmentation. Experimental results on public multi-organ databases including MoNuSeg, CPM-17 and CoNSeP show that the proposed model has the mean IoU segmentation evaluations of 0.706, 0.751, and 0.722, respectively. The model also achieves better results than some cutting-edge methods while the labeling work is reduced to 1/8 of common supervised strategies. Our method provides a more efficient and accurate basis for nuclei segmentations and further quantifications in pathological researches.

Clinical Significance of Serum IgG4 in the Diagnosis and Treatment Response of IgG4-Related Disease in Adults of Southwest China: A Retrospective Study.

Background: There is no standard cut-off value of serum IgG4 concentration and serum IgG4/total IgG ratio for the diagnosis of IgG4-related disease (IgG4-RD) or as a marker of treatment responses. We aimed to explore this issue through a retrospective cohort analysis of adults in southwest China. Methods: The diagnostic performance of serum IgG4 concentration and IgG4/IgG ratio for IgG4-RD was evaluated in a retrospective analysis of 177 adults newly diagnosed as having IgG4-RD and 877 adults without IgG4-RD. Dynamic analysis was performed to evaluate the significance of serum IgG4 concentration on IgG4-RD treatment responses. Results: The serum IgG4 concentration differed according to sex. The optimal cut-off values of serum IgG4 concentration and IgG4/IgG ratio for IgG4-RD diagnosis were 1.92 g/L and 0.12 in males and 1.83 g/L and 0.11 in females, respectively. For patients with serum IgG4 concentration >2.01 g/L, the cut-off values in the total population were >3.00 g/L and 0.19, respectively. The median serum IgG4 concentration decreased over time, and the decrease rate increased over time. The serum IgG4 concentration significantly decreased at >1 week post-treatment (P=0.004), and the median decrease rate was close to 50% at >4 weeks post-treatment. Conclusions: Serum IgG4 can be a good indicator for IgG4-RD diagnosis; however, different diagnostic cut-off values should be determined according to sex. The decreasing rate is more conducive than the serum IgG4 concentration to monitor treatment efficacy. The IgG4/IgG ratio did not improve the diagnostic efficacy for IgG4-RD.

Predicting peritoneal recurrence in gastric cancer with serosal invasion using a pathomics nomogram.

Peritoneal recurrence is the most frequent and lethal recurrence pattern in gastric cancer (GC) with serosal invasion after radical surgery. However, current evaluation methods are not adequate for predicting peritoneal recurrence in GC with serosal invasion. Emerging evidence shows that pathomics analyses could be advantageous for risk stratification and outcome prediction. Herein, we propose a pathomics signature composed of multiple pathomics features extracted from digital hematoxylin and eosin-stained images. We found that the pathomics signature was significantly associated with peritoneal recurrence. A competing-risk pathomics nomogram including carbohydrate antigen 19-9 level, depth of invasion, lymph node metastasis, and pathomics signature was developed for predicting peritoneal recurrence. The pathomics nomogram had favorable discrimination and calibration. Thus, the pathomics signature is a predictive indicator of peritoneal recurrence, and the pathomics nomogram may provide a helpful reference for predicting an individual's risk in peritoneal recurrence of GC with serosal invasion.

Gut microbiota in pre-clinical rheumatoid arthritis: From pathogenesis to preventing progression.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive polyarthritis that leads to cartilage and bone damage. Pre-clinical RA is a prolonged state before clinical arthritis and RA develop, in which autoantibodies (antibodies against citrullinated proteins, rheumatoid factors) can be present due to the breakdown of immunologic self-tolerance. As early treatment initiation before the onset of polyarthritis may achieve sustained remission, optimize clinical outcomes, and even prevent RA progression, the pre-clinical RA stage is showing the prospect to be the window of opportunity for RA treatment. Growing evidence has shown the role of the gut microbiota in inducing systemic inflammation and polyarthritis via multiple mechanisms, which may involve molecular mimicry, impaired intestinal barrier function, gut microbiota-derived metabolites mediated immune regulation, modulation of the gut microbiota's effect on immune cells, intestinal epithelial cells autophagy, and the interaction between the microbiome and human leukocyte antigen alleles as well as microRNAs. Since gut microbiota alterations in pre-clinical RA have been reported, potential therapies for modifying the gut microbiota in pre-clinical RA, including natural products, antibiotic therapy, fecal microbiota transplantation, probiotics, microRNAs therapy, vitamin D supplementation, autophagy inducer-based treatment, prebiotics, and diet, holds great promise for the successful treatment and even prevention of RA via altering ongoing inflammation. In this review, we summarized current studies that include pathogenesis of gut microbiota in RA progression and promising therapeutic strategies to provide novel ideas for the management of pre-clinical RA and possibly preventing arthritis progression.

Automated measurement of spine indices on axial MR images for lumbar spinal stenosis diagnosis using segmentation-guided regression network.

PURPOSE: Automated measurement of spine indices on axial magnetic resonance (MR) images plays a significant role in lumbar spinal stenosis diagnosis. Existing direct spine indices measurement approaches fail to explicitly focus on the task-specific region or feature channel with the additional information for guiding. We aim to achieve accurate spine indices measurement by introducing the guidance of the segmentation task. METHODS: In this paper, we propose a segmentation-guided regression network (SGRNet) to achieve automated spine indices measurement. SGRNet consists of a segmentation path for generating the spine segmentation prediction and a regression path for producing spine indices estimation. The segmentation path is a U-Net-like network which includes a segmentation encoder and a decoder which generates multilevel segmentation features and segmentation prediction. The proposed segmentation-guided attention module (SGAM) in the regression encoder extracts the attention-aware regression feature under the guidance of the segmentation feature. Based on the attention-aware regression feature, a fully connected layer is utilized to output the accurate spine indices estimation. RESULTS: Experiments on the open-access Lumbar Spine MRI data set show that SGRNet achieves state-of-the-art performance with a mean absolute error of 0.49 mm and mean Pearson correlation coefficient of 0.956 for four indices estimation. CONCLUSIONS: The proposed SGAM in SGRNet is capable of improving the performance of spine indices measurement by focusing on the task-specific region and feature channel under the guidance of the segmentation task.

Two Novel Functional Mutations in Promoter Region of SCN3B Gene Associated with Atrial Fibrillation.

The sodium voltage-gated channel beta subunit 3 (SCN3B) plays a crucial role in electrically excitable cells and conduction tissue in the heart. Some previous studies have established that genetic modification in sodium voltage-channel genes encoding for the cardiac ß-subunits, such as SCN1B, SCN2B, SCN3B and SCN4B, can result in atrial fibrillation (AF). In the current study, we identified two rare variants in 5'UTR (NM_018400.4: c.-324C>A, rs976125894 and NM_018400.4: c.-303C>T, rs1284768362) of SCN3B in two unrelated lone AF patients. Our further functional studies discovered that one of them, the A allele of c.-324C>A (rs976125894), can improve transcriptional activity and may raise SCN3B expression levels. The A allele of c.-324C>A (rs976125894) has higher transcriptional activity when it interacts with GATA4, as we confirmed transcription factor GATA4 is a regulator of SCN3B. To the best of our knowledge, the current study is the first to demonstrate that the gain-of-function mutation of SCN3B can produce AF and the first to link a mutation occurring in the non-coding 5'UTR region of SCN3B to lone AF. The work also offers empirical proof that GATA4 is a critical regulator of SCN3B gene regulation. Our findings may serve as an encyclopedia for AF susceptibility variants and can also provide insight into the investigation of the functional mechanisms behind AF variants discovered by genetic methods.

Prognostic and predictive value of a pathomics signature in gastric cancer.

The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer (GC). Pathomics, which is based on the development of digital pathology, is an emerging field that might improve clinical management. Herein, we propose a pathomics signature (PSGC) that is derived from multiple pathomics features of haematoxylin and eosin-stained slides. We find that the PSGC is an independent predictor of prognosis. A nomogram incorporating the PSGC and TNM staging system shows significantly improved accuracy in predicting the prognosis compared to the TNM staging system alone. Moreover, in stage II and III GC patients with a low PSGC (but not in those with a high PSGC), satisfactory chemotherapy benefits are observed. Therefore, the PSGC could serve as a prognostic predictor in patients with GC and might be a potential predictive indicator for decision-making regarding adjuvant chemotherapy.

Nuclei segmentation of HE stained histopathological images based on feature global delivery connection network.

The analysis of pathological images, such as cell counting and nuclear morphological measurement, is an essential part in clinical histopathology researches. Due to the diversity of uncertain cell boundaries after staining, automated nuclei segmentation of Hematoxylin-Eosin (HE) stained pathological images remains challenging. Although better performances could be achieved than most of classic image processing methods do, manual labeling is still necessary in a majority of current machine learning based segmentation strategies, which restricts further improvements of efficiency and accuracy. Aiming at the requirements of stable and efficient high-throughput pathological image analysis, an automated Feature Global Delivery Connection Network (FGDC-net) is proposed for nuclei segmentation of HE stained images. Firstly, training sample patches and their corresponding asymmetric labels are automatically generated based on a Full Mixup strategy from RGB to HSV color space. Secondly, in order to add connections between adjacent layers and achieve the purpose of feature selection, FGDC module is designed by removing the jumping connections between codecs commonly used in UNet-based image segmentation networks, which learns the relationships between channels in each layer and pass information selectively. Finally, a dynamic training strategy based on mixed loss is used to increase the generalization capability of the model by flexible epochs. The proposed improvements were verified by the ablation experiments on multiple open databases and own clinical meningioma dataset. Experimental results on multiple datasets showed that FGDC-net could effectively improve the segmentation performances of HE stained pathological images without manual interventions, and provide valuable references for clinical pathological analysis.

Polarization-based probabilistic discriminative model for quantitative characterization of cancer cells.

We propose a polarization-based probabilistic discriminative model for deriving a set of new sigmoid-transformed polarimetry feature parameters, which not only enables accurate and quantitative characterization of cancer cells at pixel level, but also accomplish the task with a simple and stable model. By taking advantages of polarization imaging techniques, these parameters enable a low-magnification and wide-field imaging system to separate the types of cells into more specific categories that previously were distinctive under high magnification. Instead of blindly choosing the model, the L0 regularization method is used to obtain the simplified and stable polarimetry feature parameter. We demonstrate the model viability by using the pathological tissues of breast cancer and liver cancer, in each of which there are two derived parameters that can characterize the cells and cancer cells respectively with satisfactory accuracy and sensitivity. The stability of the final model opens the possibility for physical interpretation and analysis. This technique may bypass the typically labor-intensive and subjective tumor evaluating system, and could be used as a blueprint for an objective and automated procedure for cancer cell screening.

A robust spin-dependent Seebeck effect and remarkable spin thermoelectric performance in graphether nanoribbons.

The generation of spin currents is a significant issue in spintronics. A spin current can be induced by a temperature gradient in the spin-dependent Seebeck effect, which has attracted growing interest over recent years. Herein we propose spin caloritronic devices based on magnetic graphether nanoribbons and investigate the spin thermoelectric properties by first-principles calculations. Owing to the symmetrical spin-resolved transmission spectra, our devices exhibit a robust spin-dependent Seebeck effect and could generate a pure spin current. Moreover, they manifest a high spin Seebeck coefficient and a giant spin figure of merit. Our findings demonstrate that graphether-nanoribbon-based devices possess remarkable spin thermoelectric performance, and might be promising candidates for spin caloritronics.