Histopathology language-image representation learning for fine-grained digital pathology cross-modal retrieval.

Large-scale digital whole slide image (WSI) datasets analysis have gained significant attention in computer-aided cancer diagnosis. Content-based histopathological image retrieval (CBHIR) is a technique that searches a large database for data samples matching input objects in both details and semantics, offering relevant diagnostic information to pathologists. However, the current methods are limited by the difficulty of gigapixels, the variable size of WSIs, and the dependence on manual annotations. In this work, we propose a novel histopathology language-image representation learning framework for fine-grained digital pathology cross-modal retrieval, which utilizes paired diagnosis reports to learn fine-grained semantics from the WSI. An anchor-based WSI encoder is built to extract hierarchical region features and a prompt-based text encoder is introduced to learn fine-grained semantics from the diagnosis reports. The proposed framework is trained with a multivariate cross-modal loss function to learn semantic information from the diagnosis report at both the instance level and region level. After training, it can perform four types of retrieval tasks based on the multi-modal database to support diagnostic requirements. We conducted experiments on an in-house dataset and a public dataset to evaluate the proposed method. Extensive experiments have demonstrated the effectiveness of the proposed method and its advantages to the present histopathology retrieval methods. The code is available at https://github.com/hudingyi/FGCR.

Constructing Dynamic Anode/Electrolyte Interfaces Coupled with Regulated Solvation Structures for Long-Term and Highly Reversible Zinc Metal Anodes.

Aqueous zinc ion batteries (AZIBs) show a great potential for next-generation energy storage due to their high safety and high energy density. However, the severe side reactions of zinc negative electrode largely hinder the further application of AZIBs. Herein, trace tris(hydroxymethyl)aminomethane (Tris) additive with rich lone-pair-electrons and zincophilic sites is firstly introduced to achieve long-term and highly reversible Zn plating/stripping. Specifically, Tris not only regulates the solvation structure of Zn2+, but is also adsorbed vertically on the Zn anode surface with a changed coordination intensity during the plating/stripping process of Zn to generate an in situ dynamic adsorption layer for the first time. The dynamic adsorption layer could successively attract the solvated Zn2+ and then promote the de-solvation of the solvated Zn2+ owing to the orientation polarization with regularly-changed applied electric field, the volume rejection effect, and strong intermolecular force towards H2O of the vertically-adsorbed Tris. Therefore, an improved Zn2+-transport kinetics as well as the inhibition of side reactions of Zn anode are successfully realized. Accordingly, the Zn||Zn symmetric cell provides an ultra-long cycle life of 2600 h. Furthermore, the Zn||MnO2 full cell with Tris could demonstrate a high capacity and structural stability for practical applications.

Structural characteristics and stability analysis of coconut oil body and its application for loading ß-carotene.

In this work, we investigated structural characteristics and stability analysis of the coconut oil body (COB) and its application for loading ß-carotene (ß-CA). The COB contained neutral lipids (81.1 ± 2.1 %), membrane proteins (0.6 ± 0.0 %), and moistures (18.3 ± 3.2 %), in which the molecular weights of membrane proteins ranged from 12 kDa to 40 kDa, as analyzed by the SDS-PAGE. The COB exhibited a small droplet diameter (5.1 ± 0.3 µm) with a monomodal diameter distribution, as reflected by the dynamic light scattering. The COB showed stable states at alkaline pH values (pH 8-10) and instability against ionic strengths (50-200 mmol/L) and thermal treatment (30-90℃) after analyzing the instability indexes. COB-based emulsions were favorable for the loading and retention of ß-CA, as reflected by free fatty acids release rates and bioaccessibility in the simulated gastrointestinal digestion. This study will contribute to using the coconut oil bodies for loading bioactive nutraceuticals to enhance their bioaccessibility.

A Key-Points Based Anchor-Free Cervical Cell Detector.

Cervical cell detection is crucial to cervical cytology screening at early stage. Currently most cervical cell detection methods use anchor-based pipeline to achieve the localization and classification of cells, e.g. faster R-CNN and YOLOv3. However, the anchors generally need to be pre-defined before training and the detection performance is inevitably sensitive to these pre-defined hyperparameters (e.g. number of anchors, anchor size and aspect ratios). More importantly, these preset anchors fail to conform to the cells with different morphology at inference phase. In this paper, we present a key-points based anchor-free cervical cell detector based on YOLOv3. Compared with the conventional YOLOv3, the proposed method applies a key-points based anchor-free strategy to represent the cells in the initial prediction phase instead of the preset anchors. Therefore, it can generate more desirable cell localization effect through refinement. Furthermore, PAFPN is applied to enhance the feature hierarchy. GIoU loss is also introduced to optimize the small cell localization in addition to focal loss and smooth L1 loss. Experimental results on cervical cytology ROI datasets demonstrate the effectiveness of our method for cervical cell detection and the robustness to different liquid-based preparation styles (i.e. drop-slide, membrane-based and sedimentation).

Kernel Attention Transformer for Histopathology Whole Slide Image Analysis and Assistant Cancer Diagnosis.

Transformer has been widely used in histopathology whole slide image analysis. However, the design of token-wise self-attention and positional embedding strategy in the common Transformer limits its effectiveness and efficiency when applied to gigapixel histopathology images. In this paper, we propose a novel kernel attention Transformer (KAT) for histopathology WSI analysis and assistant cancer diagnosis. The information transmission in KAT is achieved by cross-attention between the patch features and a set of kernels related to the spatial relationship of the patches on the whole slide images. Compared to the common Transformer structure, KAT can extract the hierarchical context information of the local regions of the WSI and provide diversified diagnosis information. Meanwhile, the kernel-based cross-attention paradigm significantly reduces the computational amount. The proposed method was evaluated on three large-scale datasets and was compared with 8 state-of-the-art methods. The experimental results have demonstrated the proposed KAT is effective and efficient in the task of histopathology WSI analysis and is superior to the state-of-the-art methods.

Autofluorescence imaging-assisted medical thoracoscopy in the diagnosis of malignant pleural disease.

BACKGROUND: Medical thoracoscopy (MT) does not always provide a conclusive diagnosis of pleural diseases because the endoscopic appearance of pleural diseases can be misleading. Autofluorescence imaging (AFI) is an effective assistive diagnostic tool. However, its clinical application for pleural disease remains controversial. OBJECTIVES: This prospective study evaluated the clinical usefulness of AFI-assisted MT for diagnosis of malignant pleural diseases. METHODS: Patients with unexplained pleural effusion admitted to our clinics between December 2018 and September 2021 were enrolled. We performed white-light thoracoscopy (WLT) first, and then AFI, during MT. Images of endoscopic real-time lesions were recorded under both modes. Pleural biopsy specimens were analyzed pathologically. Between-groups differences in diagnostic sensitivity, specificity, positive-predictive value (PPV), and negative-predictive value (NPV) were assessed using 95% confidence intervals (CI). Receiver operating characteristic curves and decision curve analyses were employed to analyze the diagnostic efficiency of these two modes. RESULTS: Of 126 eligible patients, 73 cases were diagnosed with malignant pleural disease. A total of 1292 biopsy specimens from 492 pleural sites were examined for pathological changes. The diagnostic sensitivity, PPV, and NPV of AFI were 99.7%, 58.2%, and 99.2%, respectively. AFI was significantly superior to WLT, which had a sensitivity of 79.7%, PPV of 50.7%, and NPV of 62.8%. Subgroup analysis showed that the AFI type III pattern was significantly more specific for pleural malignant disease than that of WLT. CONCLUSIONS: AFI could further improve the diagnostic efficacy of MT by providing better visualization, convenience, and safety.

Synthesis, Thermal and Mechanical Properties of Fully Biobased Poly (hexamethylene succinate-co-2,5-furandicarboxylate) Copolyesters.

Poly (hexamethylene succinate) (PHS) is a biobased and biodegradable polyester. In this research, two fully biobased high-molecular-weight poly (hexamethylene succinate-co-2,5-furandicarboxylate) (PHSF) copolyesters with low hexamethylene furandicarboxylate (HF) unit contents (about 5 and 10 mol%) were successfully synthesized through a two-step transesterification/esterification and polycondensation method. The basic thermal behavior, crystal structure, isothermal crystallization kinetics, melting behavior, thermal stability, and tensile mechanical property of PHSF copolyesters were studied in detail and compared with those of PHS. PHSF showed a decrease in the melt crystallization temperature, melting temperature, and equilibrium melting temperature while showing a slight increase in the glass transition temperature and thermal decomposition temperature. PHSF copolyesters displayed the same crystal structure as PHS. Compared with PHS, PHSF copolyesters showed the improved mechanical property. The presence of about 10 mol% of HF unit increased the tensile strength from 12.9 ± 0.9 MPa for PHS to 39.2 ± 0.8 MPa; meanwhile, the elongation at break also increased from 498.5 ± 4.78% to 1757.6 ± 6.1%.

Functional Properties and Preservative Effect of P-Hydroxybenzoic Acid Grafted Chitosan Films on Fresh-Cut Jackfruit.

In the present study, p-hydroxybenzoic acid-grafted chitosan (PA-g-CS) conjugates with different grafting degrees were synthesized by a free radical-regulated grafting approach. The conjugates were further developed into films by casting, and their characteristics and preservative effects on fresh-cut jackfruit were evaluated. Compared to the CS film, the PA-g-CS film showed comprehensive performance improvements, including enhancements of water solubility, anti-ultraviolet capacity, antioxidation, and antibacterial activity. Moreover, compared with CS film, some appreciable and favorable changes of physical properties were observed in the PA-g-CS films, which included water vapor permeability, oxygen permeability, surface morphology, moisture content, and mechanical intensity. Furthermore, compared to CS alone, the application of PA-g-CS films to fresh-cut jackfruit exerted a beneficial effect on the quality of products, as indicated by the inhibition of weight loss, softening, and membrane damage, the maintenance of soluble solids and ascorbic acids contents, as well as a reduced bacterial count and a higher sensory score. Among these PA-g-CS films, the best preservation effect was achieved with the highest degree of grafting (PA-g-CS III). The results suggested that the PA-g-CS film has the potential to be explored as a new type of packaging material for the preservation of fresh-cut fruits and vegetables.

'Stateful' threshold switching for neuromorphic learning.

Memristors have promising prospects in developing neuromorphic chips that parallel the brain-level power efficiency and brain-like computational functions. However, the limited available ON/OFF states and high switching voltage in conventional resistive switching (RS) constrain its practical and flexible implementations to emulate biological synaptic functions with low power consumption. We present 'stateful' threshold switching (TS) within the millivoltage range depending on the resistive states of RS, which originates from the charging/discharging parasitic elements of a memristive circuit. Fundamental neuromorphic learning can be facilely implemented based on a single memristor by utilizing four resistive states in 'stateful' TS. Besides the metaplasticity of synaptic learning-forgetting behaviors, multifunctional associative learning, involving acquisition, extinction, recovery, generalization and protective inhibition, was realized with nonpolar operation and power consumption of 5.71 pW. The featured 'stateful' TS with flexible tunability, enriched states, and ultralow operating voltage will provide new directions toward a massive storage unit and bio-inspired neuromorphic system.

Correction: 'Stateful' threshold switching for neuromorphic learning.

Correction for ''Stateful' threshold switching for neuromorphic learning' by Zhijian Zhong et al., Nanoscale, 2022, DOI: 10.1039/d1nr05502j.

Constructing Atomic Fe and N Co-doped Hollow Carbon Nanospheres with a Polymer Encapsulation Strategy for High-Performance Lithium-Sulfur Batteries with Accelerated Polysulfide Conversion.

As competitive next-generation rechargeable batteries, lithium-sulfur batteries (LSBs) suffer from the shuttle effect and the sluggish kinetics of intermediate polysulfides during charge and discharge processes, adversely affecting their electrochemical performances and actual applications. Herein, we demonstrate a polymer encapsulation strategy to synthesize atomic Fe and N co-doped hollow carbon nanospheres (Fe-NHC) with Fe-Nx sites for modifying commercial PP separator of LSBs to suppress the shuttle effect and promote the kinetics of intermediate polysulfides. Benefiting from the excellent structural design, the doped-N with positive charges could effectively adsorb negatively charged soluble polysulfides, help attract the soluble polysulfides to the Fe atoms and boost the catalytic transformation of the soluble polysulfides. Additionally, such a thin carbon shell could provide a short mass diffusion pathway and hence promote the adsorption and the catalytic conversion. Therefore, the battery with the Fe-NHC/PP separator delivers outstanding cycling and rate performances. At the large current density of 1 C, the specific capacity is 1079 mA h g-1 and maintains a low loss of 0.076 % per cycle within 500 cycles. Even at a harsh current density of 4 C, a high capacity of 824 mA h g-1 is still achieved, indicating the advantage of the Fe-NHC/PP separator in LSBs.

Significantly Enhanced Crystallization of Poly(ethylene succinate-co-1,2-propylene succinate) by Cellulose Nanocrystals as an Efficient Nucleating Agent.

Poly(ethylene succinate-co-1,2-propylene succinate) (PEPS) is a novel aliphatic biodegradable polyester with good mechanical properties. Due to the presence of methyl as a side group, the crystallization rate of PEPS is remarkably slower than that of the poly(ethylene succinate) homopolymer. To promote the potential application of PEPS, the effect of cellulose nanocrystals (CNC) on the crystallization behavior, crystalline morphology, and crystal structure of PEPS was investigated in this research with the aim of increasing the crystallization rate. CNC enhanced both the melt crystallization behavior of PEPS during the cooling process and the overall crystallization rate during the isothermal crystallization process. The crystallization rate of PEPS became faster with an increase in CNC content. The crystalline morphology study directly confirmed the heterogeneous nucleating agent role of CNC. The crystal structure of PEPS remained unchanged in the composites. On the basis of the interfacial energy, the nucleation mechanism of PEPS in the composites was further discussed by taking into consideration the induction of CNC.

Encoding histopathology whole slide images with location-aware graphs for diagnostically relevant regions retrieval.

Content-based histopathological image retrieval (CBHIR) has become popular in recent years in histopathological image analysis. CBHIR systems provide auxiliary diagnosis information for pathologists by searching for and returning regions that are contently similar to the region of interest (ROI) from a pre-established database. It is challenging and yet significant in clinical applications to retrieve diagnostically relevant regions from a database consisting of histopathological whole slide images (WSIs). In this paper, we propose a novel framework for regions retrieval from WSI database based on location-aware graphs and deep hash techniques. Compared to the present CBHIR framework, both structural information and global location information of ROIs in the WSI are preserved by graph convolution and self-attention operations, which makes the retrieval framework more sensitive to regions that are similar in tissue distribution. Moreover, benefited from the graph structure, the proposed framework has good scalability for both the size and shape variation of ROIs. It allows the pathologist to define query regions using free curves according to the appearance of tissue. Thirdly, the retrieval is achieved based on the hash technique, which ensures the framework is efficient and adequate for practical large-scale WSI database. The proposed method was evaluated on an in-house endometrium dataset with 2650 WSIs and the public ACDC-LungHP dataset. The experimental results have demonstrated that the proposed method achieved a mean average precision above 0.667 on the endometrium dataset and above 0.869 on the ACDC-LungHP dataset in the task of irregular region retrieval, which are superior to the state-of-the-art methods. The average retrieval time from a database containing 1855 WSIs is 0.752 ms. The source code is available at https://github.com/zhengyushan/lagenet.

Rapid large-scale preparation of polysaccharides from jackfruit peel waste by high-speed countercurrent chromatography and their antioxidant and hypoglycemic activities.

Polysaccharides with antioxidant and hypoglycemic activities were first isolated from jackfruit (Artocarpus heterophyllus Lam.) peel through the one-step high-speed countercurrent chromatography. The separation process was completed using the polymer two-phase aqueous system constituted by PEG1000-K2 HPO4 -KH2 PO4 -H2 O (0.8:1.25:1.25:6.5, w/w). For every separation process, two main polysaccharides, namely, fraction-1 and fraction-2 (165 and 225 mg, respectively) were obtained from a 2.0 g crude sample. As suggested by high-performance gel permeation chromatography, jackfruit peel polysaccharides had the mean molecular weight values of 113.3 and 174.3 kDa, separately. Physicochemical analysis suggested that two polysaccharides were dominant in galacturonic acid, galactose, rhamnose, arabinose, glucose, mannose, as well as fucose, which were highly esterified. Biological activity analysis showed that fraction-1 exhibited stronger antioxidant activity in vitro and hypoglycemic activity in streptozotocin-induced diabetic mice compared with fraction-2. The results suggest that polysaccharide fraction-1 may be developed as a potential functional food supplement.

Synthesis, Thermal Behavior, and Mechanical Properties of Fully Biobased Poly(Hexamethylene 2,5-Furandicarboxylate-Co-Sebacate) Copolyesters.

In this research, three fully biobased poly(hexamethylene 2,5-furandicarboxylate-co-sebacate) (PHFSe) copolyesters with low contents of hexamethylene sebacate (HSe) unit (10 mol%, 20 mol%, and 30 mol%) were successfully synthesized through a two-step transesterification/esterification and polycondensation method. The chemical structure and actual composition of PHFSe copolyesters were confirmed by hydrogen nuclear magnetic resonance. The thermal behavior and mechanical property of PHFSe copolyesters were investigated and compared with those of the poly(hexamethylene 2,5-furandicarboxylate) (PHF) homopolymer. Both PHFSe copolyesters and PHF showed the high thermal stability. The basic thermal parameters, including glass transition temperature, melting temperature, and equilibrium melting temperature, gradually decreased with increasing the HSe unit content. PHFSe copolyesters crystallized more slowly than PHF under both the nonisothermal and isothermal melt crystallization conditions; however, they crystallized through the same crystallization mechanism and crystal structure. In addition, the mechanical property, especially the elongation at break of PHFSe copolyesters, was obviously improved when the HSe unit content was greater than 10 mol%. In brief, the thermal and mechanical properties of PHF may be easily tuned by changing the HSe unit content to meet various practical end-use requirements.

Baseline neutrophil-lymphocyte ratio is associated with outcomes in patients with castration-resistant prostate cancer treated with Docetaxel in South China.

ABSTRACT: The aim of this study is to investigate the association between baseline neutrophil-to-lymphocyte ratio (NLR) and progression-free survival (PFS), overall survival (OS) and radiological response in castration-resistant prostate cancer patients treated with docetaxel.Forty-one prostate cancer patients who were treated with docetaxel were selected. Univariable and multivariable Cox regression models were used to predict the association of baseline NLR as a dichotomous variable with PFS and OS after chemotherapy initiation.In Kaplan-Meier analysis, the median PFS (9.8 vs 7.5 months, P = .039, Fig. 1) and OS (17.6 vs 14.2 months, P = .021, Fig. 2) was higher in patients who did not have an elevated NLR than in those with an elevated NLR. In univariate analysis, the pretreatment NLR was significantly associated with PFS (P = .049) and OS (P = .023). In multivariable analysis, patients with a NLR of >3 were at significantly higher risk of tumor progress (hazard ratio 2.458; 95% confidence interval 1.186-5.093; P = .016) and death (hazard ratio 3.435; 95% CI 1.522-7.750; P = .003)than patients with a NLR of ⩽3.NLR may be an independent predictor of PFS and OS in castration-resistant prostate cancer patients treated with docetaxel. The findings require validation in further prospective, big sample-sized studies.

Implication of Increased Serum IL-31 for Primary Biliary Cholangitis.

Interleukin-31 (IL-31) has diverse biological functions. Increased IL-31 has been found in some skin and autoimmune diseases. There has been no study reporting the association between IL-31 and primary biliary cholangitis (PBC). This study was designed to determine serum IL-31 level and to explore its diagnostic value for PBC as well as the association of IL-31 with inflammatory and fibrotic progression. 60 PBC patients, 32 age- and sex-matched patients with chronic hepatitis B (CHB) and 30 age- and sex-matched healthy controls (HC) were recruited. The sera were detected for IL-31, IL-4, interferon gamma (IFN-γ), IL-17 and other laboratory indicators. Serum IL-31 levels were significantly higher in PBC patients (median, IQR, 20.6, 16.7-26.2, pg/ml) than CHB patients (median, IQR, 11.3, 8.0-13.0, pg/ml) and HC (median, IQR, 11.0, 10.0-12.2 pg/ml) (P < .001). Serum IL-31 performed well for identifying PBC, especially for antimitochondrial antibodies (AMA)-negative PBC with AUC of 0.900, optimal cutoff value of 13.6 pg/ml, sensitivity of 87.5% and specificity of 83.9%. Serum IL-31 was positively correlated with platelet count (r = 0.368, P = .004), but negatively with FIB4 (r = -0.307, P = .017) and histological stages (r = -0.364, P = .004) in PBC patients. It was also significantly correlated with IFN-γ (r = 0.404, P = .001) and IL-4 (r = 0.291, P = .026), but not with IL-17 (r = 0.151, P = .259) in PBC patients. Serum IL-31 is increased in and may be a useful marker for PBC, in particular, for AMA-negative PBC. Furthermore, it is inversely associated with fibrotic progression of PBC.

Stain Standardization Capsule for Application-Driven Histopathological Image Normalization.

Color consistency is crucial to developing robust deep learning methods for histopathological image analysis. With the increasing application of digital histopathological slides, the deep learning methods are probably developed based on the data from multiple medical centers. This requirement makes it a challenging task to normalize the color variance of histopathological images from different medical centers. In this paper, we propose a novel color standardization module named stain standardization capsule based on the capsule network and the corresponding dynamic routing algorithm. The proposed module can learn and generate uniform stain separation outputs for histopathological images in various color appearance without the reference to manually selected template images. The proposed module is light and can be jointly trained with the application-driven CNN model. The proposed method was validated on three histopathology datasets and a cytology dataset, and was compared with state-of-the-art methods. The experimental results have demonstrated that the SSC module is effective in improving the performance of histopathological image analysis and has achieved the best performance in the compared methods.

Diagnostic Regions Attention Network (DRA-Net) for Histopathology WSI Recommendation and Retrieval.

The development of whole slide imaging techniques and online digital pathology platforms have accelerated the popularization of telepathology for remote tumor diagnoses. During a diagnosis, the behavior information of the pathologist can be recorded by the platform and then archived with the digital case. The browsing path of the pathologist on the WSI is one of the valuable information in the digital database because the image content within the path is expected to be highly correlated with the diagnosis report of the pathologist. In this article, we proposed a novel approach for computer-assisted cancer diagnosis named session-based histopathology image recommendation (SHIR) based on the browsing paths on WSIs. To achieve the SHIR, we developed a novel diagnostic regions attention network (DRA-Net) to learn the pathology knowledge from the image content associated with the browsing paths. The DRA-Net does not rely on the pixel-level or region-level annotations of pathologists. All the data for training can be automatically collected by the digital pathology platform without interrupting the pathologists' diagnoses. The proposed approaches were evaluated on a gastric dataset containing 983 cases within 5 categories of gastric lesions. The quantitative and qualitative assessments on the dataset have demonstrated the proposed SHIR framework with the novel DRA-Net is effective in recommending diagnostically relevant cases for auxiliary diagnosis. The MRR and MAP for the recommendation are respectively 0.816 and 0.836 on the gastric dataset. The source code of the DRA-Net is available at https://github.com/zhengyushan/dpathnet.