Visual authenticating hazardous adulterant phenolphthalein in slimming foods: Target-mimicking hapten epitope improved immunoassay

Screening for the hazardous adulterant phenolphthalein (PTH) in slimming foods is necessary. Herein, the linkage of the PTH target epitope with various spacer arms was proposed for hapten design, aiming to produce highly sensitive and specific antibodies targeting PTH. To understand the influence of spacer arms on epitope, comprehensive evaluations were conducted using computer-aided chemistry and animal immunization. The resulting antibody exhibited maximal half-inhibitory concentration (IC50) of 0.25 ng/mL. Then, a lateral flow immunoassay (LFIA) was established with detection capability for screening (CCβ) of less than 140, 240, and 25 ng/g for PTH in tea, instant coffee, and oral liquid, respectively. Furthermore, blind sample results agreed well with LFIA and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Therefore, this work not only provides a robust tool for detecting PTH adulteration but also suggests that the careful pairing of spacer arms with hapten epitope is a key factor in advancing rational hapten design.

Global attention based GNN with Bayesian collaborative learning for glomerular lesion recognition

BACKGROUND

Glomerular lesions reflect the onset and progression of renal disease. Pathological diagnoses are widely regarded as the definitive method for recognizing these lesions, as the deviations in histopathological structures closely correlate with impairments in renal function.

METHODS

Deep learning plays a crucial role in streamlining the laborious, challenging, and subjective task of recognizing glomerular lesions by pathologists. However, the current methods treat pathology images as data in regular Euclidean space, limiting their ability to efficiently represent the complex local features and global connections. In response to this challenge, this paper proposes a graph neural network (GNN) that utilizes global attention pooling (GAP) to more effectively extract high-level semantic features from glomerular images. The model incorporates Bayesian collaborative learning (BCL), enhancing node feature fine-tuning and fusion during training. In addition, this paper adds a soft classification head to mitigate the semantic ambiguity associated with a purely hard classification.

RESULTS

This paper conducted extensive experiments on four glomerular datasets, comprising a total of 491 whole slide images (WSIs) and 9030 images. The results demonstrate that the proposed model achieves impressive F1 scores of 81.37%, 90.12%, 87.72%, and 98.68% on four private datasets for glomerular lesion recognition. These scores surpass the performance of the other models used for comparison. Furthermore, this paper employed a publicly available BReAst Carcinoma Subtyping (BRACS) dataset with an 85.61% F1 score to further prove the superiority of the proposed model.

CONCLUSION

The proposed model not only facilitates precise recognition of glomerular lesions but also serves as a potent tool for diagnosing kidney diseases effectively. Furthermore, the framework and training methodology of the GNN can be adeptly applied to address various pathology image classification challenges.

DeepTree: Pathological Image Classification Through Imitating Tree-Like Strategies of Pathologists

Digitization of pathological slides has promoted the research of computer-aided diagnosis, in which artificial intelligence analysis of pathological images deserves attention. Appropriate deep learning techniques in natural images have been extended to computational pathology. Still, they seldom take into account prior knowledge in pathology, especially the analysis process of lesion morphology by pathologists. Inspired by the diagnosis decision of pathologists, we design a novel deep learning architecture based on tree-like strategies called DeepTree. It imitates pathological diagnosis methods, designed as a binary tree structure, to conditionally learn the correlation between tissue morphology, and optimizes branches to finetune the performance further. To validate and benchmark DeepTree, we build a dataset of frozen lung cancer tissues and design experiments on a public dataset of breast tumor subtypes and our dataset. Results show that the deep learning architecture based on tree-like strategies makes the pathological image classification more accurate, transparent, and convincing. Simultaneously, prior knowledge based on diagnostic strategies yields superior representation ability compared to alternative methods. Our proposed methodology helps improve the trust of pathologists in artificial intelligence analysis and promotes the practical clinical application of pathology-assisted diagnosis.

Simultaneous identification of three emergent stimulant laxative adulterants in slimming foods using only one antibody

Stimulant laxatives were recently found to be abused in slimming foods, resulting in harmful effects on consumers. To ensure the safety of relative products, sensitive yet multiplex immunoassays are crucial in rapid screening of stimulant laxatives. However, there are few immunoassays for these substances, and even less for broad-specific recognition. Thus, in this work, four theoretically promising haptens of emerging stimulant laxative bisacodyl were rationally designed using molecular modeling and synthesized to immune animals, whose feasibility was confirmed by the obtained broad-specific antibody. Based on this unique antibody, a highly sensitive multiplex competitive indirect enzyme-linked immunosorbent assay (ciELISA) was established with low limits of detection for bisacodyl, sodium picosulfate, and BHPM (0.23, 13.68, and 0.11 ng/mL). In spiked sample recovery test and real sample detection, this ciELISA exhibited acceptable consistency with the validation method, demonstrating high accuracy and applicability of our method. This reliable multiplex ciELISA proceeds the rapid screening of stimulant laxatives in slimming foods.

Efficacy of the induced pluripotent stem cell derived and engineered CD276-targeted CAR-NK cells against human esophageal squamous cell carcinoma

Introduction

Chimeric antigen receptor natural killer (CAR-NK) cells have been found to be successful in treating hematologic malignancies and present potential for usage in solid tumors.

Methods

In this study, we created CD276-targeted CAR-expressing NK cells from pluripotent stem cells (iPSC CD276-targeted CAR-NK cells) and evaluated their cytotoxicity against esophageal squamous cell carcinoma (ESCC) using patient-specific organoid (PSO) models comprising of both CD276-positive and CD276-negative adjacent epithelium PSO models (normal control PSO, NC PSO) as well as primary culture of ESCC cell models. In addition, in vitro and in vivo models such as KYSE-150 were also examined. iPSC NK cells and NK-free media were used as the CAR-free and NK-free controls, respectively.

Results

The positive CD276 staining was specifically detected on the ESCC membrane in 51.43% (54/105) of the patients of all stages, and in 51.35% (38/74) of stages III and IV. The iPS CD276-targeted CAR-NK cells, comparing with the iPS NK cells and the NK-free medium, exhibited specific and significant cytotoxic activity against CD276-positive ESCC PSO rather than CD276-negative NC PSO, and exhibited significant cytotoxicity against CD276-expressing cultured ESCC cells, as well as against CD276-expressing KYSE-150 in vitro and in BNDG mouse xenograft.

Discussion

The efficacy of the iPSC CD276-targeted CAR-NK cells demonstrated by their successful treatment of CD276-expressing ESCC in a multitude of pre-clinical models implied that they hold tremendous therapeutic potential for treating patients with CD276-expressing ESCC.

An ultra-sensitive biosensor based on surface plasmon resonance and weak value amplification

An ultra-sensitive phase plasmonic sensor combined with weak value amplification is proposed for the detection of IgG, as a model analyte. Phase detection is accomplished by self-interference between the p-polarization and the s-polarization of the light. With the principles of weak value amplification, a phase compensator is used to modulate the coupling strength and enhance the refractive index sensitivity of the system. On a simple Au-coated prism-coupled surface plasmon resonance (SPR) structure, the scheme, called WMSPR, achieves a refractive index sensitivity of 4.737 × 104 nm/RIU, which is about three times higher than that of the conventional phase-based approach. The proposed WMSPR biosensor gives great characteristics with a high resolution of 6.333 × 10-8 RIU and a low limit of detection (LOD) of 5.3 ng/mL. The results yield a great scope to promote the optimization of other SPR biosensors for high sensitivity.

Efficacy of MUC1-targeted CAR-NK cells against human tongue squamous cell carcinoma

Introduction

The clinical efficacy of CAR-NK cells against CD19-expressing blood cancers has been demonstrated, and they have shown potential for treating solid tumors as well. However, the efficacy of CAR-NK cells for treating human oral tongue squamous cell carcinoma (OTSCC) has not been examined.

Methods

We assessed MUC1 expression in human OTSCC tissue and a cell line using immunohistochemistry and immunofluorescence. We constructed NK cells that express CAR targeted to MUC1 from pluripotent stem cells (iPSC-derived MUC1-targeted CAR-NK cells) and evaluated their effectiveness against OTSCC in vitro using the xCELLigence Real-Time Cell Analysis system and CCK8 assay, and in vivo by measuring xenograft growth daily in BNDG mice treated with MUC1-targeted CAR-NK cells. As controls, we used iPSC-derived NK cells and NK-free media, which were CAR-free and blank, respectively.

Results

MUC1 expression was detected in 79.5% (66/83) of all OTSCC patients and 72.7% (24/33) of stage III and IV. In stage III and IV MUC1 positive OTSCC, 63.6% (21/33) and 48.5% (16/33) patients had a MUC1-positive cancer cell rate of more than 50% and 80%, respectively. The iPSC-derived MUC1-targeted CAR-NK cells exhibited significant cytotoxicity against MUC1-expressing OTSCC cells in vitro, in a time- and dose-dependent manner, and showed a significant inhibitory effect on xenograft growth compared to both the iPSC-derived NK cells and the blank controls. We observed no weight loss, severe hematological toxicity or NK cell-mediated death in the BNDG mice.

Conclusion

The MUC1-targeted CAR-NK cells had significant efficacy against human OTSCC, and their promising therapeutic response warrants further clinical trials.

Human dental pulp stem cells have comparable abilities to umbilical cord mesenchymal stem/stromal cells in regulating inflammation and ameliorating hepatic fibrosis

Hepatic fibrosis, also called cirrhosis, have wide prevalence worldwide for long yeas. Recently, many treatments for liver cirrhosis made marked progress, especially the umbilical cord-derived mesenchymal stromal cells (UCMSC) therapy. However, limited recourses and potential immune-related issues become the obstacles on UCMSC popularization in clinic. Therefore, we took dental pulp stem cells (DPSCs) into the consideration, since autologous DPSCs can be easily obtained without any ethnic or immune-related issues that heterogenous UCMSCs could encounter. We systematically compared the effects of both cell types and found that DPSCs had similar results to UCMSCs in regulating inflammation and reversing hepatic fibrosis. In our study, co-culturing T cells and PBMSCs showed that DPSCs have the ability to inhibit the proliferation of inflammatory cells and downregulate relevant inflammatory factors. In vitro and in vivo sterility tests confirmed the bio-safety of DPSCs. Moreover, the 1 year-aged mouse model demonstrated that DPSCs successfully reversed hepatic fibrosis. Overall, DPSCs demonstrated comparable effectiveness to UCMSCs in regulating inflammation and reversing hepatic fibrosis, particularly in the aged mouse model that represents middle-aged and elderly humans. Since autologous DPSCs avoid potential immune-related issues that heterogenous UCMSCs could encounter, they may be a better choice for stem cell-related therapies.

Discovery of a Highly Potent and Selective MYOF Inhibitor with Improved Water Solubility for the Treatment of Gastric Cancer

Myoferlin (MYOF) mediates the growth and metastasis of various cancers as an emerging therapeutic target by regulating exocytosis and endocytosis. However, the previously reported MYOF inhibitor, 6y, failed to be a favorable candidate agent due to its poor physicochemical properties, such as water solubility, in preclinical studies. Naturally, a novel range of MYOF inhibitors was synthesized and optimized based on the lead compound 6y. The optimal compound HJ445A potently repressed the proliferation of gastric cancer cells with IC50 values of 0.16 and 0.14 μM in MGC803 and MKN45, respectively. Moreover, HJ445A bound to the MYOF-C2D domain with a KD of 0.17 μM, and HJ445A prevented the migration of gastric cancer cells by reversing the epithelial-mesenchymal transition (EMT) process and inhibited the colony formation of the MKN45 cells in a concentration-dependent manner. Notably, the water solubility of HJ445A was significantly improved compared to 6y, with about 170-fold enhancement. Additionally, HJ445A also demonstrated superior antitumor efficacy in vivo.

BME-free primary patient-specific organoids obtained with a one-day mimicking method to replicate the corresponding tumor for personalized treatment options

Introduction

In cancer treatment, every minute counts. Due to the unpredictable behavior of cancer cells caused by continuous mutations, each cancer patient has a unique situation and may or may not respond to a specific drug or treatment. The process of finding an effective therapy can be time-consuming, but cancer patients do not have the luxury of time for trial and error. Therefore, a novel technology to fast generate a patient relevant organoid for the therapies selecting is urgently needed.

Methods

Utilizing the new organoid technology by specially dissolving the mesenchyme in tumor tissues acquired from cancer patients, we realized the work of creating patient-specific organoids (PSO) within one day.

Results

PSO properties reflect those of its respective original in vivo tumor tissue and can be utilized to perform various in vitro drug sensitivity tests to identify the most effective clinical treatment for patients. Additionally, PSO can aid in assessing the efficacy of immune cell therapies.

Discussion

Organoid technology has advanced significantly in recent years. However, current cancer organoid methods involve creating 3D tumor tissue from 2D cancer cells or cell clusters, primarily for cancer research purposes aimed at investigating related molecular and cellular mechanisms of tumor development. These methods are research-driven, not tailored towards clinical applications, and cannot provide personalized information for individual patients. PSO filled the gap of clinic-driven and time-saving method for the personalized therapies selecting to the cancer patients.

MSCohi-O lenses for long-term retention of mesenchymal stem cells on ocular surface as a therapeutic approach for chronic ocular graft-versus-host disease

Chronic ocular graft-versus-host disease (oGVHD) is a common complication of allogeneic hematopoietic stem cell transplantation (allo-HSCT) and can lead to vision loss if not diagnosed and treated promptly. Currently, no approved drugs exist for oGVHD treatment. However, umbilical cord-derived mesenchymal stem cells (UCMSCs) have known immunoregulatory properties and have been employed in clinical trials for immune-mediated diseases. To address oGVHD, the application of UCMSCs to the ocular surface is a logical approach. Intravenous administration of UCMSCs poses risks, necessitating topical and local delivery. Retaining UCMSCs on the ocular surface remains a challenge. To overcome this, we invented mesenchymal stem cell-coating high oxygen-permeable hydrogel lenses combining UCMSCs and machinery to enable the long-term retention of UCMSCs on the ocular surface. Animal model experiments demonstrated that these lenses effectively retained UCMSCs, providing therapeutic benefits by decreasing corneal inflammation and damage, and inhibiting immune rejection and response, all crucial aspects in oGVHD treatment.

End-to-end affine registration framework for histopathological images with weak annotations

BACKGROUND AND OBJECTIVE

Histopathological image registration is an essential component in digital pathology and biomedical image analysis. Deep-learning-based algorithms have been proposed to achieve fast and accurate affine registration. Some previous studies assume that the pairs are free from sizeable initial position misalignment and large rotation angles before performing the affine transformation. However, large-rotation angles are often introduced into image pairs during the production process in real-world pathology images. Reliable initial alignment is important for registration performance. The existing deep-learning-based approaches often use a two-step affine registration pipeline because convolutional neural networks (CNNs) cannot correct large-angle rotations.

METHODS

In this manuscript, a general framework ARoNet is developed to achieve end-to-end affine registration for histopathological images. We use CNNs to extract global features of images and fuse them to construct correspondent information for affine transformation. In ARoNet, a rotation recognition network is implemented to eliminate great rotation misalignment. In addition, a self-supervised learning task is proposed to assist the learning of image representations in an unsupervised manner.

RESULTS

We applied our model to four datasets, and the results indicate that ARoNet surpasses existing affine registration algorithms in alignment accuracy when large angular misalignments (e.g., 180 rotation) are present, providing accurate affine initialization for subsequent non-rigid alignments. Besides, ARoNet shows advantages in execution time (0.05 per pair), registration accuracy, and robustness.

CONCLUSION

We believe that the proposed general framework promises to simplify and speed up the registration process and has the potential for clinical applications.

CD22 is a potential target of CAR-NK cell therapy for esophageal squamous cell carcinoma

BACKGROUND

Chimeric antigen receptor NK (CAR-NK) cell therapy is one of the most promising immunotherapies. Although it has shown a significant therapeutic effect in hematologic malignancies, few successes have been obtained in solid tumors including esophageal squamous cell carcinoma (ESCC). The major reasons are lack of specific cell surface antigens and complex tumor microenvironment. Here we identify CD22, a well-known tumor surface marker in hematologic malignancies, is expressed in ESCC, possibly serving as a potential target of CAR-NK cell therapy.

METHODS

The expression of 13 tumor cell surface antigens used clinically was analyzed in patients from The Cancer Genome Atlas (TCGA) database. Also, mRNA expression were detected in 2 ESCC cell lines and 2 patients samples by qCPR. Then according to Venn diagram, CD22 was selected for further investigation. Following this, the expression of CD22 by immunofluorescence (IF) in ESCC cell lines and by immunohistochemistry (IHC) in 87 cases of human ESCC samples was detected respectively. On the basis of H-score results, the correlation between CD22 expression and clinical parameters was analyzed. As a proof, the efficacy of CD22-targeted CAR-NK cells against ESCC cell lines was performed by a real-time cell analyzer (RTCA) platform.

RESULTS

KYSE-140 and KYSE-150 cell lines displayed surface expression of CD22. IHC showed an 80.46% (70/87) positive rate in ESCC patient samples. Among these, cell membranous expression of CD22 was observed in 27.59% (24/87) patient samples. Through chi-square test, expression of CD22 in ESCC was associated with lymph node metastasis while it was no related to the depth of tumor invasion and clinical stage. Engineered CD22-targeted CAR-NK cells exhibited inhibitory growth capability against ESCC cell lines (p < 0.0001).

CONCLUSIONS

CD22 is a potential tumor surface antigen capable of being targeted by CAR-NK cells in ESCC. And potential therapeutics for ESCC may be developed based on immune cells expressing anti-CD22 CAR. The study also indicates that CD22 CAR-NK cells could be used in other cancers and more in vivo experiments are needed.

Mesothelin-targeted CAR-NK Cells Derived From Induced Pluripotent Stem Cells Have a High Efficacy in Killing Triple-negative Breast Cancer Cells as Shown in Several Preclinical Models

The emergence of immunotherapy has introduced a promising, novel approach to cancer treatment. While multiple chimeric antigen receptor (CAR) T-cell therapies have demonstrated remarkable clinical efficacy against leukemia, their effect on solid tumors has been limited. One potential option for treating solid tumors is the engineering of natural killer (NK) cells with CARs. Mesothelin (MSLN), a tumor differentiation antigen, is expressed on triple-negative breast cancer (TNBC) cells, making it a potential target for CAR-NK therapy in the treatment of TNBC. We first constructed induced pluripotent stem cells with stable anti-MSLN-CAR expression and subsequently differentiated these cells into mesothelin-targeted CAR-NK (MSLN-NK) cells. We then assessed the effects of MSLN-NK cells on TNBC cells both in vitro (using the MDA-MB-231 cell line), in vivo (in a CDX mouse model), and ex vivo (using patient-specific primary cells and patient-specific organoids), in which MSLN surface expression was confirmed. Our CDX study results indicated that MSLN-NK cells effectively killed MDA-MB-231 (MD231) cells in vitro, reduced tumor growth in the CDX mouse model of TNBC, and lysed patient-specific primary cells and patient-specific organoids derived from the tumor samples of TNBC patients. Our data demonstrated that MSLN-NK cells had high efficacy on killing TNBC cells in in vitro, in vivo, and ex vivo. Therefore, MSLN-NK could be a promising treatment option for TNBC patients.

Identifying fungicide difenoconazole as illegal growth regulator in vegetable: Computer-aided hapten similarity to enhance immunoassay sensitivity

Difenoconazole, a fungicide with broad-spectrum properties, has recently been found to have been used illegally used as a plant growth regulator in Brassica campestris, with the intent of inducing thick stems and dark green leaves. However, analysts have encountered challenges in implementing a rapid surveillance screening approach for this purpose. In this study, a novel hapten was designed to improve the analytical performance of difenoconazole immunoassay. Specifically, the triazole of the original hapten was replaced with a benzene ring, guided by molecular simulation. This led to the development of a very sensitive antibody and the subsequent development of a competitive indirect enzyme linked immunosorbent assay (ciELISA) for the detection of difenoconazole in vegetable samples. The assay exhibited a working range of 0.16 ng mL^-1 to 9.64 ng mL^-1, with a detection limit of 0.05 ng mL^-1. Upon analysis of blind samples, a strong correlation was observed between the ciELISA and HPLC-MS/MS methods. As a result, the proposed technique may prove to be an excellent tool for the rapid detection of difenoconazole overuse and adulteration in vegetables.

Discovery of Pyrimidinediamine Derivatives as Potent Methuosis Inducers for the Treatment of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a leading malignancy among women that currently lack effective targeted therapeutic agents, and the limitations of treatment have prompted the emergence of new strategies. Methuosis is a novel vacuole-presenting cell death modality that promotes tumor cell death. Hence, a series of pyrimidinediamine derivatives were designed and synthesized through evaluation of their abilities that inhibit proliferation as well as induce methuosis against TNBC cells. Among them, JH530 showed excellent anti-proliferative activities and vacuolization capacity in TNBC. The mechanism research indicated that JH530 caused cell death through inducing methuosis of cancer cells. Furthermore, JH530 inhibited tumor growth remarkably in the HCC1806 xenograft model without an apparent decrease in body weight. Overall, JH530 is a methuosis inducer that displayed remarkable suppression of TNBC growth in vitro and in vivo, which provides a basis for the future progress of more small molecules for TNBC treatment.

Ultra-precise weak measurement-based interfacial biosensors

In this study, an interfacial biosensing scheme with ultra-precision is proposed. The scheme uses weak measurement techniques to ensure ultra-high sensitivity of the sensing system while improving the stability of the system through self-referencing and pixel point averaging, thus achieving ultra-high detection accuracy of biological samples. In specific experiments, we have used the biosensor in this study to perform specific binding reaction experiments for protein A and Mouse IgG with a detection line of 2.71 ng/mL for IgG. In addition, the sensor is non-coated, simple in structure, easy to operate, and low in cost of use.

Discovery of a Potent and Oral Available Complex I OXPHOS Inhibitor That Abrogates Tumor Growth and Circumvents MEKi Resistance

Targeting oxidative phosphorylation (OXPHOS) has emerged as a promising therapeutic strategy for cancer therapy. Here, we discovered a 1H-1,2,3-triazole derivative HP661 as a highly potent and orally available OXPHOS inhibitor that effectively blocked the activity of mitochondrial complex I. HP661 specifically compromised the mitochondrial oxygen consumption of high-OXPHOS lung cancer cells but not that of low-OXPHOS lung cancer cells or normal cells in the low nanomolar range. Notably, mitogen-activated protein kinase kinase (MEK) inhibitor (trametinib)-resistant lung cancer cells with high levels of OXPHOS also showed marked sensitivity to HP661, as indicated by decreased clonogenic growth and increased cell apoptosis upon treatment. In a mouse model of high-OXPHOS lung cancer, HP661 treatment not only significantly suppressed tumor growth but also augmented the therapeutic efficacy of trametinib by impairing tumor mitochondrial respiration. In summary, we identified HP661 as a highly effective OXPHOS inhibitor to abrogate the growth of high OXPHOS-dependent tumors and conquer high OXPHOS-mediated drug resistance.

Unsupervised domain adaptive tumor region recognition for Ki67 automated assisted quantification

PURPOSE

Ki67 is a protein associated with tumor proliferation and metastasis in breast cancer and acts as an essential prognostic factor. Clinical work requires recognizing tumor regions on Ki67-stained whole-slide images (WSIs) before quantitation. Deep learning has the potential to provide assistance but largely relies on massive annotations and consumes a huge amount of time and energy. Hence, a novel tumor region recognition approach is proposed for more precise Ki67 quantification.

METHODS

An unsupervised domain adaptive method is proposed, which combines adversarial and self-training. The model trained on labeled hematoxylin and eosin (H&E) data and unlabeled Ki67 data can recognize tumor regions in Ki67 WSIs. Based on the UDA method, a Ki67 automated assisted quantification system is developed, which contains foreground segmentation, tumor region recognition, cell counting, and WSI-level score calculation.

RESULTS

The proposed UDA method achieves high performance in tumor region recognition and Ki67 quantification. The AUC reached 0.9915, 0.9352, and 0.9689 on the validation set and internal and external test sets, respectively, substantially exceeding baseline (0.9334, 0.9167, 0.9408) and rivaling the fully supervised method (0.9950, 0.9284, 0.9652). The evaluation of automated quantification on 148 WSIs illustrated statistical agreement with pathological reports.

CONCLUSION

The model trained by the proposed method is capable of accurately recognizing Ki67 tumor regions. The proposed UDA method can be readily extended to other types of immunohistochemical staining images. The results of automated assisted quantification are accurate and interpretable to provide assistance to both junior and senior pathologists in their interpretation.

Unpaired virtual histological staining using prior-guided generative adversarial networks

Fibrosis is an inevitable stage in the development of chronic liver disease and has an irreplaceable role in characterizing the degree of progression of chronic liver disease. Histopathological diagnosis is the gold standard for the interpretation of fibrosis parameters. Conventional hematoxylin-eosin (H&E) staining can only reflect the gross structure of the tissue and the distribution of hepatocytes, while Masson trichrome can highlight specific types of collagen fiber structure, thus providing the necessary structural information for fibrosis scoring. However, the expensive costs of time, economy, and patient specimens as well as the non-uniform preparation and staining process make the conversion of existing H&E staining into virtual Masson trichrome staining a solution for fibrosis evaluation. Existing translation approaches fail to extract fiber features accurately enough, and the decoder of staining is unable to converge due to the inconsistent color of physical staining. In this work, we propose a prior-guided generative adversarial network, based on unpaired data for effective Masson trichrome stained image generation from the corresponding H&E stained image. Conducted on a small training set, our method takes full advantage of prior knowledge to set up better constraints on both the encoder and the decoder. Experiments indicate the superior performance of our method that surpasses the previous approaches. For various liver diseases, our results demonstrate a high correlation between the staging of real and virtual stains (ρ=0.82; 95% CI: 0.73-0.89). In addition, our finetuning strategy is able to standardize the staining color and release the memory and computational burden, which can be employed in clinical assessment.

Near-infrared fluorescence-assisted thoracoscopic diverticulectomy of esophageal diverticulum: a case report

BACKGROUND

Esophageal diverticulum is a rare condition that requires treatment only when symptoms are present. Surgery has been considered to be the only curative option for symptomatic cases. The most popular procedure is diverticulectomy. Clear and intact exposure of the diverticulum's neck is the basis for safe and effective diverticulectomy.

CASE PRESENTATION

We herein report a case of a 57 year-old woman with an epiphrenic diverticulum. VATS diverticulectomy was scheduled. To better identify the diverticulum neck, we injected indocyanine green (ICG) into the diverticulum through the endoscopic channel, and the diverticulum wall and neck were clearly visible under near-infrared (NIR) fluorescence. With the help of this method, diverticulectomy was successfully performed.

CONCLUSION

This case shows that NIR fluorescence with ICG is safe, simple and reliable and can be used for diverticulectomy.

STAT3 inhibitor BBI608 reduces patient-specific primary cell viability of cervical and endometrial cancer at a clinical-relevant concentration

PURPOSE

Aberrant activation of STAT3 signal pathway promotes tumor progression in many solid tumor types, including cervical cancer and endometrial cancer. BBI608, the STAT3 inhibitor had been reported in previous studies for restraining cancer stem cells. However, whether BBI608 is available for inhibiting the proliferation of cervical cancer or endometrial cancer remains poorly understood. This study investigated the anti-tumor effect and molecular mechanism of BBI608 on the patient-specific primary cells (PSPC) generated from cervical and endometrial cancer in vitro.

METHODS

PSPCs were obtained from four patients via biopsy. The cell viability was analyzed by the CCK8 assay. The PSPCs were treated with various concentrations of BBI608 or/and paclitaxel; and then, western blot was applied to investigate the expression of phosphorylated STAT3 (pSTAT3).

RESULTS

The PSPCs cell viability was reduced after treated with BBI608 at a lower concentration. Western blot results showed a reduction trend of pSTAT3 after PSPCs treated with BBI608. Our results demonstrated that BBI608 at the certain concentrations worked well in reducing the cell viability of PSPC from the patients who suffered from cervical cancer and endometrial cancer.

CONCLUSIONS

In this study, the patient-specific primary cell (PSPC) was used as the pre-clinical model for investigating the efficiency of BBI608 in reducing cancer cells viability. BBI608, at a clinical-relevant concentration, had valid efficiency in PSPCs from the patients. The dose of drugs treatment and the measured results were more valuable for further guiding clinical trials.

In Situ Detection of Electrochemical Reaction Surface Area by Optical Weak Measurement

The surface area is key to electrochemical systems, including those in electrocatalysis and energy storage. Studies have shown that the surface area of the electrocatalyst directly affects the electrochemical activity, adsorption performance, and stability of the electrocatalyst. This paper used an optical weak measurement (WM) method, which has little impact on the analyte, to measure the reaction surface area (RSA) that actually participated in the electrochemical reaction. Then compared the RSA obtained by the WM with the total surface area (TSA) obtained by the standard Brunauer-Emmett-Teller (BET) measurement and the active surface area (ASA) obtained by the electrochemical double-layer capacitance (EDLC) method. Their growth trend was consistent, indicating the reliability of the WM method. Compared with the above two methods, the WM method is an in situ detection and easy to operate experimentally, which can help researchers to consider the effect of surface area on electrocatalyst performance more rationally.

Development of a highly sensitive immunoassay for detecting aminopyrine abuse in herbal tea

With the popularity of herbal tea in China, many food fraudsters have added illegal drugs to herbal tea to enhance its functions, among which aminopyrine is widely abused as an antipyretic and analgesic. Presently, there is no immunoassays for aminopyrine, and it is difficult to achieve real-time detection in the field. Based on a polyclonal antibody of aminopyrine with high specificity and sensitivity, an optimal combination of coating antigen/antibody was obtained by screening different coating antigens. On this basis, a sensitive ic-ELISA method was established to detect aminopyrine in herbal tea. The detection limit of the ic-ELISA was 0.18 ng mL^-1, which was much lower than the 100 ng mL^-1 required as a standard. The method had good consistency with LC-MS in the detection of actual samples and could be used as a reliable method for the detection of aminopyrine in herbal tea.

Expression site agnostic histopathology image segmentation framework by self supervised domain adaption

MOTIVATION

With the sites of antigen expression different, the segmentation of immunohistochemical (IHC) histopathology images is challenging, due to the visual variances. With H&E images highlighting the tissue structure and cell distribution more broadly, transferring more salient features from H&E images can achieve considerable performance on expression site agnostic IHC images segmentation.

METHODS

To the best of our knowledge, this is the first work that focuses on domain adaptive segmentation for different expression sites. We propose an expression site agnostic domain adaptive histopathology image semantic segmentation framework (ESASeg). In ESASeg, multi-level feature alignment encodes expression site invariance by learning generic representations of global and multi-scale local features. Moreover, self-supervision enhances domain adaptation to perceive high-level semantics by predicting pseudo-labels.

RESULTS

We construct a dataset with three IHCs (Her2 with membrane stained, Ki67 with nucleus stained, GPC3 with cytoplasm stained) with different expression sites from two diseases (breast and liver cancer). Intensive experiments on tumor region segmentation illustrate that ESASeg performs best across all metrics, and the implementation of each module proves to achieve impressive improvements.

CONCLUSION

The performance of ESASeg on the tumor region segmentation demonstrates the efficiency of the proposed framework, which provides a novel solution on expression site agnostic IHC related tasks. Moreover, the proposed domain adaption and self-supervision module can improve feature domain adaption and extraction without labels. In addition, ESASeg lays the foundation to perform joint analysis and information interaction for IHCs with different expression sites.

An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images

BACKGROUND

Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy.

METHODS

We designed a regional multiple-instance learning algorithm to predict the OBMC based on hematoxylin-eosin (H&E) staining slides alone. We collected 1041 cases from eight different hospitals and labeled 26,431 regions of interest to train the model. The performance of the model was assessed by ten-fold cross validation and external validation. Under the guidance of top3 predictions, we conducted an IHC test on 175 cases of unknown origins to compare the consistency of the results predicted by the model and indicated by the IHC markers. We also applied the model to identify whether there was tumor or not in a region, as well as distinguishing squamous cell carcinoma, adenocarcinoma, and neuroendocrine tumor.

FINDINGS

In the within-cohort, our model achieved a top1-accuracy of 91.35% and a top3-accuracy of 97.75%. In the external cohort, our model displayed a good generalizability with a top3-accuracy of 97.44%. The top1 consistency between the results of the model and the immunohistochemistry markers was 83.90% and the top3 consistency was 94.33%. The model obtained an accuracy of 98.98% to identify whether there was tumor or not and an accuracy of 93.85% to differentiate three types of cancers.

INTERPRETATION

Our model demonstrated good performance to predict the OBMC from routine histology and had great potential for assisting pathologists with determining the OBMC accurately.

FUNDING

National Science Foundation of China (61875102 and 61975089), Natural Science Foundation of Guangdong province (2021A15-15012379 and 2022A1515 012550), Science and Technology Research Program of Shenzhen City (JCYJ20200109110606054 and WDZC20200821141349001), and Tsinghua University Spring Breeze Fund (2020Z99CFZ023).

Phase Contrast Image-Based Rapid Antimicrobial Susceptibility Testing of Bacteria in Liquid Culture Media

Currently, the world is facing the problem of bacterial resistance, which threatens public health, and bacterial antimicrobial susceptibility testing (AST) plays an important role in biomedicine, dietary safety and aquaculture. Traditional AST methods take a long time, usually 16-24 h, and cannot meet the demand for rapid diagnosis in the clinic, so rapid AST methods are needed to shorten the detection time. In this study, by using an in-house built centrifuge to centrifuge bacteria in a liquid medium onto the inner wall of the bottom surface of a counting plate, and using a phase contrast microscope to track bacterial growth under the effect of different antibiotic concentrations, the results of the minimum inhibitory concentration (MIC) of bacteria under the effect of antibiotics can be obtained in as early as 4 h. We used a combination of E. coli and tigecycline and obtained MIC results that were consistent with those obtained using the gold standard broth micro-dilution method, demonstrating the validity of our method; due to the time advantage, the complete set can be used in the future for point of care and clinical applications, helping physicians to quickly obtain the MIC used to inhibit bacterial growth.

B-cell Lymphoma 6 Inhibitors: Current Advances and Prospects of Drug Development for Diffuse Large B-cell Lymphomas

B-cell lymphoma 6 (BCL6) is a transcriptional repressor that regulates the differentiation of B lymphocytes and mediates the formation of germinal centers (GCs) by recruiting corepressors through the BTB domain of BCL6. Physiological processes regulated by BCL6 involve cell activation, differentiation, DNA damage, and apoptosis. BCL6 is highly expressed when the gene is mutated, leading to the malignant proliferation of cells and drives tumorigenesis. BCL6 overexpression is closely correlated with tumorigenesis in diffuse large B-cell lymphoma (DLBCL) and other lymphomas, and BCL6 inhibitors can effectively inhibit some lymphomas and overcome resistance. Therefore, targeting BCL6 might be a promising therapeutic strategy for treating lymphomas. Herein, we comprehensively review the latest development of BCL6 inhibitors in diffuse large B-cell lymphoma and discuss the overview of the pharmacophores of BCL6 inhibitors and their efficacies in vitro and in vivo. Additionally, the current advances in BCL6 degraders are provided.

Facile Fabrication of Highly Quantum Dot/AuNP-Loaded Tags for a Dual-Modal Colorimetric/Reversed Ratiometric Fluorescence Immunochromatographic Assay

Developing an easily-prepared, sensitive, and accurate point-of-need immunochromatographic assay (ICA) is significant in food safety screening, clinical diagnosis, and environmental monitoring. However, the current single-modal ICAs are limited in certain instinct drawbacks that restrict analytical performances. Herein, we introduce an ultrasensitive dual-modal colorimetric/reversed ratiometric fluorescence ICA based on facilely prepared immunoprobes with a high loading capacity of red quantum dots and AuNPs. By smartly integrating these red-colored/fluorescent signal probes with an immobilized green quantum dot antigen on the test lines, discrete "turn-on" visual inspection and reversed ratiometric quantification via a portable smartphone-based analyzer were accomplished. As an application, this method was employed to detect 11 phosphodiesterase-5 inhibitors in health foods with ultralow detection limits (0.0028-0.045 ng/mL), high repeatability (coefficient of variations of 0.3-1.91%), and reasonable accuracy (recoveries of 86.6-107%). The proposed method was further validated by the authorized liquid chromatography with tandem mass spectrometry method in actual sample detection. This new assay format can be extended to ultrasensitive flexible detection of other food contaminants, environmental pollutants, or tumor biomarkers within minutes, and it just requires simply prepared signal reporters, easy-to-operate procedures, and a low-cost miniaturized analyzer.

Demonstration of a New Characterization Method for Weak Measurement

In this work, the difference between the weak measurement method and the weak value amplification process and the classical measurement process is thoroughly discussed, and the transition conditions of the weak value enhancement are obtained. A transition mode of the weak measurement and the classical measurement is proposed for the first time, and a better fitting model of the measurement results is found by performing a systematic analysis. On top of that, the importance of the new fitting method for the application of the weak measurement system is verified during the industrial production of organic molecular -nucleic acid, protein, polysaccharide-hydrolysis or synthesis. At the same time, a variety of spectral characterization methods are proposed and the advantages and disadvantages of the different characterization methods are analyzed through carrying out experiments. Consequently, the wide implementation of weak measurement-based detection technology is attained.

Multiplex optical bioassays for food safety analysis: Toward on-site detection

Food safety analysis plays a significant role in controlling food contamination and supervision. In recent years, multiplex optical bioassays (MOBAs) have been widely applied to analyze multiple hazards due to their efficiency and low cost. However, due to the challenges such as multiplexing capacity, poor sensitivity, and bulky instrumentation, the further application of traditional MOBAs in food screening has been limited. In this review, effective strategies regarding food safety MOBAs are summarized, such as spatial-resolution modes performed in multi-T lines/dots strips or arrays of strip/microplate/microfluidic chip/SPR chip and signal-resolution modes employing distinguishable colorimetric/luminescence/fluorescence/surface plasma resonance/surface-enhanced Raman spectrum as signal tags. Following this, new trends on how to design engineered sensor architecture and exploit distinguishable signal reporters, how to improve both multiplexing capacity and sensitivity, and how to integrate these formats into smartphones so as to be mobile are summarized systematically. Typically, in the case of enhancing multiplexing capacity and detection throughput, microfluidic array chips with multichannel architecture would be a favorable approach to overcome the spatial and physical limitations of immunochromatographic assay (ICA) test strips. Moreover, noble metal nanoparticles and single-excitation, multiple-emission luminescence nanomaterials hold great potential in developing ultrasensitive MOBAs. Finally, the exploitation of innovative multiplexing strategy hybridized with powerful and widely available smartphones opens new perspectives to MOBAs. In future, the MOBAs should be more sensitive, have higher multiplexing capacity, and easier instrumentation.

Protein and Water Distribution Across Visual Axis in Mouse Lens: A Confocal Raman MicroSpectroscopic Study for Cold Cataract

Purpose: The aims of the study were to investigate cellular mechanisms of cold cataract in young lenses of wild-type C57BL/6J (B6WT) mice treated at different temperatures and to test a hypothesis that cold cataract formation is associated with the changes in lens protein and water distribution at different regions across lens fiber cells by Raman spectroscopy (RS).

Methods: RS was utilized to scan the mouse lens at different regions with/without cold cataract. Three regions with various opacification along the equatorial axis in the anterior–posterior lens section were scanned. The intensity ratio of Raman bands at 2,935 and 3,390 cm⁻¹ (I_p/I_w) were used to evaluate lens protein and water distribution. We further determined water molecular changes through Gaussian profiles of water Raman spectra.

Results: Three specific regions 1, 2, and 3, located at 790–809, 515–534, and 415–434 μm away from the lens center, of postnatal day 14 B6WT lenses, were subjected to RS analysis. At 37°C, all three regions were transparent. At 25°C, only region 3 became opaque, while at 4°C, both regions 2 and 3 showed opacity. The sum of the difference between I_p/I_w and the value of linear fitting line from scattered-line at each scanning point was considered as fluctuation degree (FD) in each region. Among different temperatures, opaque regions showed relatively higher FD values (0.63 and 0.79 for regions 2 and 3, respectively, at 4°C, and 0.53 for region 3 at 25°C), while transparent regions provided lower FD values (less than 0.27). In addition, the decrease in Gaussian peak II and the rising of Gaussian peak III and IV from water Raman spectra indicated the instability of water molecule structure in the regions with cold cataract.

Conclusion: Fluctuation degrees of RS data reveal new mechanistic information about cold cataract formation, which is associated with uneven distribution of lens proteins and water across lens fiber cells. It is possible that RS data partly reveals cold temperature-induced redistribution of lens proteins such as intermediate filaments in inner fiber cells. This lens protein redistribution might be related to unstable structure of water molecules according to Gaussian profiles of water RS.

[Research progress on three-dimensional printed interbody fusion cage]

Spinal fusion is a standard operation for treating moderate and severe intervertebral disc diseases. In recent years, the proportion of three-dimensional printing interbody fusion cage in spinal fusion surgery has gradually increased. In this paper, the research progress of molding technology and materials used in three-dimensional printing interbody fusion cage at present is summarized. Then, according to structure layout, three-dimensional printing interbody fusion cages are classified into five types: solid-porous-solid (SPS) type, solid-porous-frame (SPF) type, frame-porous-frame (FPF) type, whole porous cage (WPC) type and others. The optimization process of three-dimensional printing interbody fusion cage and the advantages and disadvantages of each type are analyzed and summarized in depth. The clinical application of various types of 3D printed interbody fusion cage was introduced and summarized later. Lastly, combined with the latest research progress and achievements, the future research direction of three-dimensional printing interbody fusion cage in molding technology, application materials and coating materials is prospected in order to provide some reference for scholars engaged in interbody fusion cage research and application.

Imaging Sensor for the Detection of the Flow Battery Via Weak Value Amplification

Flow battery electrodes are vital for performing redox reactions, and an in-depth understanding of reaction kinetics and spatial distribution differences in electrodes is very important for improving the efficiency of electrochemical reactions. In this study, a reflection-type phase-sensitive weak measurement imaging system was developed for the detection of flow batteries. The phase difference between two polarization components in total internal reflection caused by electrode redox processes was measured by weak value amplification. The resulting refractive index resolution of the imaging system was estimated to be 2.8-4.2 × 10^-6 RIU. The real-time monitoring ability of the system was demonstrated by linear sweep voltammetry tests of vanadium redox batteries. Compared to traditional optical methods, the proposed weak measurement imaging sensor did not require coating, as it can be used in acid electrolytes of vanadium flow batteries. Meanwhile, the weak value amplification effect led to a higher resolution than the total internal reflection system shown in our previous work, thereby resulting in more accurate detection of electrochemical reactions. In sum, the proposed sensor looks very promising for the detection of electrochemical reactions in flow batteries, water splitting, electrochemical corrosion, and electrocatalysis.

Specific detection of glucose by an optical weak measurement sensor

Diabetes is an important public health problem and finding quick testing methods with high accuracy, reliability, and convenience are important to control the blood glucose of diabetic patients. In this study, a sensor based on a weak measurement scheme was developed for the specific detection of glucose for the first time. The detection of glucose using the proposed method was completed by the high sensitivity and resolution of the weak measurement based on optical rotation detection, as well as the change in the optical rotation before and after the specific oxidation of glucose. The resolution of the as-obtained glucose sensor was around 2.71×10-3 g/L (1.50×10-2 mmol/L), and the detection range was 0-11 g/L (0-61 mmol/L).

Unpaired Stain Transfer Using Pathology-Consistent Constrained Generative Adversarial Networks

Pathological examination is the gold standard for the diagnosis of cancer. Common pathological examinations include hematoxylin-eosin (H&E) staining and immunohistochemistry (IHC). In some cases, it is hard to make accurate diagnoses of cancer by referring only to H&E staining images. Whereas, the IHC examination can further provide enough evidence for the diagnosis process. Hence, the generation of virtual IHC images from H&E-stained images will be a good solution for current IHC examination hard accessibility issue, especially for some low-resource regions. However, existing approaches have limitations in microscopic structural preservation and the consistency of pathology properties. In addition, pixel-level paired data is hard available. In our work, we propose a novel adversarial learning method for effective Ki-67-stained image generation from corresponding H&E-stained image. Our method takes fully advantage of structural similarity constraint and skip connection to improve structural details preservation; and pathology consistency constraint and pathological representation network are first proposed to enforce the generated and source images hold the same pathological properties in different staining domains. We empirically demonstrate the effectiveness of our approach on two different unpaired histopathological datasets. Extensive experiments indicate the superior performance of our method that surpasses the state-of-the-art approaches by a significant margin. In addition, our approach also achieves a stable and good performance on unbalanced datasets, which shows our method has strong robustness. We believe that our method has significant potential in clinical virtual staining and advance the progress of computer-aided multi-staining histology image analysis.

A Review of Intelligent Driving Pedestrian Detection Based on Deep Learning

Pedestrian detection is a specific application of object detection. Compared with general object detection, it shows similarities and unique characteristics. In addition, it has important application value in the fields of intelligent driving and security monitoring. In recent years, with the rapid development of deep learning, pedestrian detection technology has also made great progress. However, there still exists a huge gap between it and human perception. Meanwhile, there are still a lot of problems, and there remains a lot of room for research. Regarding the application of pedestrian detection in intelligent driving technology, it is of necessity to ensure its real-time performance. Additionally, it is necessary to lighten the model while ensuring detection accuracy. This paper first briefly describes the development process of pedestrian detection and then concentrates on summarizing the research results of pedestrian detection technology in the deep learning stage. Subsequently, by summarizing the pedestrian detection dataset and evaluation criteria, the core issues of the current development of pedestrian detection are analyzed. Finally, the next possible development direction of pedestrian detection technology is explained at the end of the paper.

Single-emission dual-enzyme magnetosensor for multiplex immunofluorometric assay of adulterated colorants in chili seasoning

In this work, a single-emission, dual-enzyme immunofluorometric magnetosensor was fabricated to simultaneously detect three illegal colorants in chili seasoning. Specifically, two enzymatic reactions catalyzed by horse radish peroxidase-labeled Rhodamine (RhB) antibody and glucose oxidase-labeled Sudan dyes (SuDs) antibody were performed within a functional microfluidic chip, leading to production of strongly fluorescent Resorufin. In addition, a compact analyzer assisted by a smartphone was developed to quantify signals. Compared with the available multiplex optical biosensors, this work demonstrated four superiorities: 1) Simple optical structure. Only single wavelength excitation/emission module was needed; 2) High multiplexing capacity through spatial resolution and signal resolution; 3) Precise determination by discriminant analysis; 4) Easy-operated and high-throughput parallel detection on 16-channel chips. Ultralow detection limits for RhB (0.0072 ng/mL), Sudan I (0.0040 ng/mL) and Sudan II (0.0260 ng/mL) were obtained by this magnetosensor, which opens a new approach in field detection of multiplex illegal dyes in food system.

In situ detection of electrochemical reaction by weak measurement

In the field of electrochemical energy storage systems, the use of in situ detection technology helps to study the mechanism of electrochemical reaction. Our group has previously in situ detected the electrochemical reaction in vanadium flow batteries by total internal reflection (TIR) imaging. In order to further improve the detection resolution, in this study, the weak measurement (WM) method was introduced to in situ detect the electrochemical reaction during the linear sweep voltammetry or the cyclic voltammetry tests with quantitative measurement of the absolute current density, which lays a foundation for replacing the TIR for two-dimensional imaging of electrochemical reactions in vanadium flow batteries, oxygen/hydrogen evolution reaction, surface treatments, electrochemical corrosion and so on.

Current Opinion Regarding Multidisciplinary Cancer Clinic Utilization for the Management of Prostate Cancer

Objectives:

Multidisciplinary cancer clinic (MDC) is an evaluation option for the management of prostate cancer (PCa). The purpose of MDC is to provide the patient with a comprehensive assessment and risk/benefit discussion of all pertinent treatment options. Our objective was to obtain a contemporary measure and analysis of urologists’ opinion regarding PCa MDC.

Material and Methods:

We created a 14-item questionnaire for respondent baseline characteristics, subjective and objective inquiries regarding MDC for PCa management. The survey was distributed through email to members of the Society of Urologic Oncology and the Endourological Society. Data were analyzed using R (R Core team, 2017).

Results:

One hundred and seven (51%) respondents reported participation in MDC; the majority of which were male (97.6%), academic (61.4%) urologists with urologic oncology fellowship training (50%), and >20 years in practice (40.3%). MDC patients were most commonly referrals (78.5%) and with high-risk disease (Gleason sum 8–10) (83.2%). A majority of the respondents felt that MDC was very or extremely beneficial for PCa research (45% and 19%, respectively) and treatment (35% and 20%, respectively). Responses dissuading the use of MDC included lack of infrastructure (41%) and time commitment (21%). On multivariate analysis, urologists with >10 years in practice were less likely to find MDC beneficial in the management of PCa (11–20 years, P = 0.028 and >20 years P = 0.009).

Conclusion:

A contemporary sampling of urologists’ opinion and practice patterns alludes to the benefits that advocate for and the resource demand that hinders routine use of MDC for PCa evaluation. Urologist training and practice environment can affect participation in PCa MDC.

Development and Validation of Machine Learning-based Model for the Prediction of Malignancy in Multiple Pulmonary Nodules: Analysis from Multicentric Cohorts

PURPOSE

Nodule evaluation is challenging and critical to diagnose multiple pulmonary nodules (MPNs). We aimed to develop and validate a machine learning-based model to estimate the malignant probability of MPNs to guide decision-making.

EXPERIMENTAL DESIGN

A boosted ensemble algorithm (XGBoost) was used to predict malignancy using the clinicoradiologic variables of 1,739 nodules from 520 patients with MPNs at a Chinese center. The model (PKU-M model) was trained using 10-fold cross-validation in which hyperparameters were selected and fine-tuned. The model was validated and compared with solitary pulmonary nodule (SPN) models, clinicians, and a computer-aided diagnosis (CADx) system in an independent transnational cohort and a prospective multicentric cohort.

RESULTS

The PKU-M model showed excellent discrimination [area under the curve; AUC (95% confidence interval (95% CI)), 0.909 (0.854-0.946)] and calibration (Brier score, 0.122) in the development cohort. External validation (583 nodules) revealed that the AUC of the PKU-M model was 0.890 (0.859-0.916), higher than those of the Brock model [0.806 (0.771-0.838)], PKU model [0.780 (0.743-0.817)], Mayo model [0.739 (0.697-0.776)], and VA model [0.682 (0.640-0.722)]. Prospective comparison (200 nodules) showed that the AUC of the PKU-M model [0.871 (0.815-0.915)] was higher than that of surgeons [0.790 (0.711-0.852), 0.741 (0.662-0.804), and 0.727 (0.650-0.788)], radiologist [0.748 (0.671-0.814)], and the CADx system [0.757 (0.682-0.818)]. Furthermore, the model outperformed the clinicians with an increase of 14.3% in sensitivity and 7.8% in specificity.

CONCLUSIONS

After its development using machine learning algorithms, validation using transnational multicentric cohorts, and prospective comparison with clinicians and the CADx system, this novel prediction model for MPNs presented solid performance as a convenient reference to help decision-making.

Open Surface Droplet Microfluidic Magnetosensor for Microcystin-LR Monitoring in Reservoir

Establishing rapid, simple, and in situ detection of microcystin-LR (MC-LR) in drinking water sources is of significant importance for human health. To ease the situation that current methods cannot address, an open surface droplet microfluidic magnetosensor was designed and validated to quantify MC-LR in reservoir water, which is capable of (1) MC-LR isolation via MC-LR antibody-conjugated magnetic beads, (2) parallel and multistep analytical procedures in 15-array power-free and reusable active droplet microfluidic chips, (3) immunoassay incubation and fluorescence excitation within a miniaturized multifunctional 3D-printing optosensing accessory, and (4) signal read-out and data analysis by a user-friendly Android app. The proposed smartphone-based fluorimetric magnetosensor exhibited a low limit of detection of 1.2 × 10^-5 μg/L in the range of 10^-4 μg/L to 100 μg/L. This integrated and high throughput platform was utilized to draw an MC-LR contamination map for six reservoirs distributed in the Pearl River delta, Guangdong Province. It promises to be a simple and successful quantification method for MC-LR field detection, bringing many benefits to rapid on-site screening.

Effects of quercetin on cadmium-induced toxicity in rat urine using metabonomics techniques

This study aimed to analyse the protective effects of quercetin on the toxicity of cadmium (Cd) using metabonomics techniques. Sixty male Sprague-Dawley rats were randomly divided into six groups (n = 10): control group (C), low-dose quercetin-treated group (Q1; 10 mg/kg bw/day), high-dose quercetin-treated group (Q2; 50 mg/kg bw/day), Cd-treated group (D; 4.89 mg/kg bw/day), low-dose quercetin plus Cd-treated group (DQ1) and high-dose quercetin plus Cd-treated group (DQ2). The rats continuously received quercetin and Cd via gavage and drinking water for 12 weeks, respectively. The rat urine samples were collected for metabonomics analysis. Finally, 10 metabolites were identified via the metabonomics profiles of the rat urine samples. Compared with the control group, the intensities of taurine, phosphocreatine, l-carnitine and uric acid were significantly decreased (p < 0.01) and those of LysoPC (18: 2 (9Z, 12Z)), guanidinosuccinic acid, dopamine, 2,5,7,8-tetramethyl-2(2'-carboxyethyl)-6-hydroxychroman and allantoic acid were significantly increased (p < 0.01) in the Cd-treated group. However, the intensities of the aforementioned metabolites had restorative changes in the high-dose quercetin plus Cd-treated groups unlike those in Cd-treated group (p < 0.01 or p < 0.05). Results indicated that quercetin exerts protective effects on Cd-induced toxicity by regulating energy and lipid metabolism, enhancing the antioxidant defence system and protecting liver and kidney function and so on.

The pentose phosphate pathway regulates chronic neuroinflammation and dopaminergic neurodegeneration

BACKGROUND

Metabolic dysfunction and neuroinflammation are increasingly implicated in Parkinson's disease (PD). The pentose phosphate pathway (PPP, a metabolic pathway parallel to glycolysis) converts glucose-6-phosphate into pentoses and generates ribose-5-phosphate and NADPH thereby governing anabolic biosynthesis and redox homeostasis. Brains and immune cells display high activity of glucose-6-phosphate dehydrogenase (G6PD), the rate-limiting enzyme of the PPP. A postmortem study reveals dysregulation of G6PD enzyme in brains of PD patients. However, spatial and temporal changes in activity/expression of G6PD in PD remain undetermined. More importantly, it is unclear how dysfunction of G6PD and the PPP affects neuroinflammation and neurodegeneration in PD.

METHODS

We examined expression/activity of G6PD and its association with microglial activation and dopaminergic neurodegeneration in multiple chronic PD models generated by an intranigral/intraperitoneal injection of LPS, daily subcutaneous injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 6 days, or transgenic expression of A53T α-synuclein. Primary microglia were transfected with G6PD siRNAs and treated with lipopolysaccharide (LPS) to examine effects of G6PD knockdown on microglial activation and death of co-cultured neurons. LPS alone or with G6PD inhibitor(s) was administrated to mouse substantia nigra or midbrain neuron-glia cultures. While histological and biochemical analyses were conducted to examine microglial activation and dopaminergic neurodegeneration in vitro and in vivo, rotarod behavior test was performed to evaluate locomotor impairment in mice.

RESULTS

Expression and activity of G6PD were elevated in LPS-treated midbrain neuron-glia cultures (an in vitro PD model) and the substantia nigra of four in vivo PD models. Such elevation was positively associated with microglial activation and dopaminergic neurodegeneration. Furthermore, inhibition of G6PD by 6-aminonicotinamide and dehydroepiandrosterone and knockdown of microglial G6PD attenuated LPS-elicited chronic dopaminergic neurodegeneration. Mechanistically, microglia with elevated G6PD activity/expression produced excessive NADPH and provided abundant substrate to over-activated NADPH oxidase (NOX2) leading to production of excessive reactive oxygen species (ROS). Knockdown and inhibition of G6PD ameliorated LPS-triggered production of ROS and activation of NF-кB thereby dampening microglial activation.

CONCLUSIONS

Our findings indicated that G6PD-mediated PPP dysfunction and neuroinflammation exacerbated each other mediating chronic dopaminergic neurodegeneration and locomotor impairment. Insight into metabolic-inflammatory interface suggests that G6PD and NOX2 are potential therapeutic targets for PD.

[An interlaboratory comparison study on the detection of RUNX1-RUNX1T1 fusion transcript levels and WT1 transcript levels]

Objective: To investigate the current status and real performance of the detection of RUNX1-RUNX1T1 fusion transcript levels and WT1 transcript levels in China through interlaboratory comparison. Methods: Peking University People's Hospital (PKUPH) prepared the samples for comparison. That is, the fresh RUNX1-RUNX1T1 positive (+) bone morrow nucleated cells were serially diluted with RUNX1-RUNX1T1 negative (-) nucleated cells from different patients. Totally 23 sets with 14 different samples per set were prepared. TRIzol reagent was added in each tube and thoroughly mixed with cells for homogenization. Each laboratory simultaneously tested RUNX1-RUNX1T1 and WT1 transcript levels of one set of samples by real-time quantitative PCR method. All transcript levels were reported as the percentage of RUNX1-RUNX1T1 or WT1 transcript copies/ABL copies. Spearman correlation coefficient between the reported transcript levels of each participated laboratory and those of PKUPH was calculated. Results: ①RUNX1-RUNX1T1 comparison: 9 samples were (+) and 5 were (-) , the false negative and positive rates of the 20 participated laboratories were 0 (0/180) and 5% (5/100) , respectively. The reported transcript levels of all 9 positive samples were different among laboratories. The median reported transcript levels of 9 positive samples were from 0.060% to 176.7%, which covered 3.5-log. The ratios of each sample's highest to the lowest reported transcript levels were from 5.5 to 12.3 (one result which obviously deviated from other laboratories' results was not included) , 85% (17/20) of the laboratories had correlation coefficient ≥0.98. ②WT1 comparison: The median reported transcript levels of all 14 samples were from 0.17% to 67.6%, which covered 2.6-log. The ratios of each sample's highest to the lowest reported transcript levels were from 5.3-13.7, 62% (13/21) of the laboratories had correlation coefficient ≥0.98. ③ The relative relationship of the reported RUNX1-RUNX1T1 transcript levels between the participants and PKUPH was not always consistent with that of WT1 transcript levels. Both RUNX1-RUNX1T1 and WT1 transcript levels from 2 and 7 laboratories were individually lower than and higher than those of PKUPH, whereas for the rest 11 laboratories, one transcript level was higher than and the other was lower than that of PKUPH. Conclusion: The reported RUNX1-RUNX1T1 and WT1 transcript levels were different among laboratories for the same sample. Most of the participated laboratories reported highly consistent result with that of PKUPH. The relationship between laboratories of the different transcript levels may not be the same.

Weak measurement-based sensor for the rapid identification of L(+)-ascorbic acid and D(-)-isoascorbic acid

The ability to identify L(+)-ascorbic acid from D(-)-isoascorbic acid in medicinal products is of practical interest. Based on the method of frequency domain weak measurement, a set of common optical path sensors for identification of L(+)-ascorbic acid and D(-)-isoascorbic acid is established. By quantificationally analyzing the magnitude and offset direction of the spectral central wavelength, a good identification of the concentration and the optically active forms of ascorbic acid has been achieved. The sensitivity and resolution of the sensor for optical rotation can reach 34.35 nm/° and ${5.53} \times {{10}^{ - 5}}^\circ $5.53×10^{-5 ∘}, respectively. The detection resolution for L(+)-ascorbic acid is ${2.00} \times {{10}^{ - 4}}\;{\rm mol}/{\rm mL}$2.00×10^-4mol/mL, and that for D(-)-isoascorbic acid is ${2.73} \times {{10}^{ - 4}}\;{\rm mol}/{\rm mL}$2.73×10^-4mol/mL. The potential of the sensor in the detection of transparent but optically inactive impurities has been verified by comparative experiments of sodium chloride solution. The sensor also has been applied to identify medicinal vitamin C tablets, which verified the feasibility of the method in optically active pharmaceutical solutions with water-insoluble, optically inactive impurities. Since the sensor has the advantages of high precision, real-time, high robustness, and being non-destructive, it has a great prospect in the field of drug detection containing chiral molecules.