Clinical features of anemia in membranous nephropathy patients: a Chinese cohort study

BACKGROUND

Anemia is a common complication in patients with progressive chronic kidney disease. This cohort study evaluated the prevalence, clinical features and prognosis of membranous nephropathy (MN) with anemia.

METHODS

We retrospectively analyzed a cohort of MN patients diagnosed using renal biopsy between February 2012 and February 2018. The clinical and pathological characteristics at baseline were recorded, and the outcomes (hemoglobin, proteinuria and renal function) during follow-ups were also evaluated. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors for anemia in MN patients. The MN patients were divided according to the therapeutic effect they experienced as follows: without-anemia, completely corrected anemia, standard anemia treatment and nonstandard anemia treatment groups. We compared the rate of complete remission of MN and renal end-point events among the four groups.

RESULTS

The median age of 483 patients was 42.43 (26.59, 50.20) years at the time of MN diagnosis. The prevalence of anemia at baseline was 23.81%, and the cumulative prevalence was 50.72%. There were 133 cases of mild anemia, 103 cases of moderate anemia and 9 cases of severe anemia; in addition, there were 228 cases of normocytic anemia and 17 cases of microcytic hypochromic anemia. Multivariate logistic regression indicated that acute renal tubule injury >5% (OR = 1.634, 95% CI 1.034, 2.581; p = 0.035), total protein level (OR = 0.949, 95% CI 0.923, 0.975; p < 0.001), cholesterol level (OR = 0.833, 95% CI 0.749, 0.926, p = 0.001), hypokalemia (OR = 2.612, 95% CI 1.227, 5.560, p = 0.013) and hypophosphatemia (OR = 2.653, 95% CI 1.303, 5.403, p = 0.007) were independent risk factors for anemia in MN patients. The complete remission rate of MN patients without anemia was significantly higher than that of anemia patients who exhibited treatment failure. The incidence of renal endpoint events was different among the four groups.

CONCLUSION

The anemia experienced by MN patients is mainly mild and moderate, normocytic anemia. The pathological features of acute renal tubular injury and clinical nutritional status are independent risk factors for anemia. There were differences in renal prognosis among anemia patients with different treatment outcomes.

Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks

Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful technique for studying gene expression patterns at the single-cell level. Inferring gene regulatory networks (GRNs) from scRNA-seq data provides insight into cellular phenotypes from the genomic level. However, the high sparsity, noise and dropout events inherent in scRNA-seq data present challenges for GRN inference. In recent years, the dramatic increase in data on experimentally validated transcription factors binding to DNA has made it possible to infer GRNs by supervised methods. In this study, we address the problem of GRN inference by framing it as a graph link prediction task. In this paper, we propose a novel framework called GNNLink, which leverages known GRNs to deduce the potential regulatory interdependencies between genes. First, we preprocess the raw scRNA-seq data. Then, we introduce a graph convolutional network-based interaction graph encoder to effectively refine gene features by capturing interdependencies between nodes in the network. Finally, the inference of GRN is obtained by performing matrix completion operation on node features. The features obtained from model training can be applied to downstream tasks such as measuring similarity and inferring causality between gene pairs. To evaluate the performance of GNNLink, we compare it with six existing GRN reconstruction methods using seven scRNA-seq datasets. These datasets encompass diverse ground truth networks, including functional interaction networks, Loss of Function/Gain of Function data, non-specific ChIP-seq data and cell-type-specific ChIP-seq data. Our experimental results demonstrate that GNNLink achieves comparable or superior performance across these datasets, showcasing its robustness and accuracy. Furthermore, we observe consistent performance across datasets of varying scales. For reproducibility, we provide the data and source code of GNNLink on our GitHub repository: https://github.com/sdesignates/GNNLink.

Uterine Tumor Resembling Ovarian Sex Cord Tumors: 23 Cases Indicating Molecular Heterogeneity With Variable Biological Behavior

Uterine tumor resembling ovarian sex cord tumor (UTROSCT) is a rare mesenchymal neoplasm that mainly harbors NCOA1-3 rearrangements with partner genes ESR1 or GREB1 . Here, we explored 23 UTROSCTs by targeted RNA sequencing. The association between molecular diversity and clinicopathologic features was investigated. The mean age of our cohort was 43 years (23-65 y). Only 15 patients (65%) were originally diagnosed with UTROSCTs. Mitotic figures ranged from 1 to 7/10 high power fields, of primary tumors and increased from 1 to 9/10 high power fields in recurrent tumors. Five types of gene fusions were identified in these patients, including GREB1::NCOA2 (n=7), GREB1::NCOA1 (n=5), ESR1::NCOA2 (n=3), ESR1::NCOA3 (n=7), and GTF2A1::NCOA2 (n=1). To our knowledge, our group included the largest cohort of tumors with GREB1::NCOA2 fusions. Recurrences were most common in patients with GREB1::NCOA2 fusion (57%), followed by 40% ( GREB1::NCOA1 ), 33% ( ESR1::NCOA2 ), and 14% ( ESR1::NCOA3 ). The recurrent patient who harbored an ESR1::NCOA2 fusion was characterized by extensive rhabdoid features. Both of the recurrent patients who harbored GREB1::NCOA1 and ESR1::NCOA3 had the largest tumor sizes in their own gene alteration groups, and another recurrent GREB1::NCOA1 patient had extrauterine involvement. The GREB1 -rearranged patients were of older age, larger tumor size, and higher stage than non- GREB1 -rearranged patients ( P =0.004, 0.028, and 0.016, respectively). In addition, the GREB1 -rearranged tumors presented more commonly as intramural masses rather than non- GREB1 -rearranged tumors presenting as polypoid/submucosal masses ( P =0.021). Microscopically, nested and whorled patterns were frequently seen in GREB1- rearranged patients ( P =0.006). Of note, estrogen receptor expression was weaker than progesterone receptor in all 12 GREB1- rearranged tumors, whereas the similar staining intensity of estrogen receptor and progesterone receptor was observed in all 11 non- GREB1- rearranged tumors ( P <0.0001). This study demonstrated that UTROSCTs were present at a younger age in the Chinese population. The genetic heterogeneity of UTROSCTs was correlated with variable recurrence rate. Tumors with GREB1::NCOA2 fusions are more likely to recur compared with those with other genetic alterations.

Risk-reducing salpingo-oophorectomy among Chinese women at increased risk of breast and ovarian cancer

BACKGROUND

Risk-reducing salpingo-oophorectomy (RRSO) is recommended for women at increased risk of breast and ovarian cancer. We launched a prospective study of women receiving RRSO, including those with mutations in genes beyond BRCA1/2.

PATIENTS AND METHODS

80 women were enrolled for RRSO with sectioning and extensively examining the fimbriae (SEE-FIM) protocol between October 2016 and June 2022. The majority of participants had inherited susceptibility gene mutations or a family history suggesting ovarian cancer risk, while patients with isolated metastatic high-grade serous cancer of unknown origin were also included.

RESULTS

Overall, two patients had isolated metastatic high-grade serous cancer with unknown origin, and four patients had family histories but refused to take genetic tests. The rest 74 patients harbored deleterious susceptible gene, including 43 (58.1%) with BRCA1 mutation, and 26 (35.1%) with BRCA2 mutation, respectively. Other mutated genes included ATM (1), BRIP1(1), PALB2(1), MLH1(1) and TP53 (1) in each patient. Among the 74 mutation carriers, three (4.1%) cancers were recognized, one (1.4%) was found to have serous tubal intraepithelial carcinoma (STIC), and five patients (6.8%) was diagnosed with serous tubal intraepithelial lesions (STILs). P53 signature was recognized in 24 patients (32.4%). For other genes, MLH1 mutation carrier had endometrial atypical hyperplasia and p53 signature in fallopian tubes. The germline TP53 mutation carrier had STIC in the surgical specimens. Evidence for precursor escape was also recognized in our cohort.

CONCLUSION

Our study demonstrated clinic-pathological findings of patients at increased risk of breast and ovarian cancer, and expand the clinical application of SEE-FIM protocol.

Metadynamics simulations of ligands binding to protein surfaces: a novel tool for rational drug design

Structure-based drug design protocols may encounter difficulties to investigate poses when the biomolecular targets do not exhibit typical binding pockets. In this study, by providing two concrete examples from our labs, we suggest that the combination of metadynamics free energy methods (validated against affinity measurements), along with experimental structural information (by X-ray crystallography and NMR), can help to identify the poses of ligands on protein surfaces. The simulation workflow proposed here was implemented in a widely used code, namely GROMACS, and it could straightforwardly be applied to various drug-design campaigns targeting ligands' binding to protein surfaces.

A Review of the Application of Multi-modal Deep Learning in Medicine: Bibliometrics and Future Directions

In recent years, deep learning has been applied in the field of clinical medicine to process large-scale medical images, for large-scale data screening, and in the diagnosis and efficacy evaluation of various major diseases. Multi-modal medical data fusion based on deep learning can effectively extract and integrate characteristic information of different modes, improve clinical applicability in diagnosis and medical evaluation, and provide quantitative analysis, real-time monitoring, and treatment planning. This study investigates the performance of existing multi-modal fusion pre-training algorithms and medical multi-modal fusion methods and compares their key characteristics, such as supported medical data, diseases, target samples, and implementation performance. Additionally, we present the main challenges and goals of the latest trends in multi-modal medical convergence. To provide a clearer perspective on new trends, we also analyzed relevant papers on the Web of Science. We obtain some meaningful results based on the annual development trends, country, institution, and journal-level research, highly cited papers, and research directions. Finally, we perform co-authorship analysis, co-citation analysis, co-occurrence analysis, and bibliographic coupling analysis using the VOSviewer software.

Gene Regulatory Network Inference Using Convolutional Neural Networks from scRNA-seq Data

In recent years, with the rapid development of single-cell sequencing technology, this brings new opportunities and challenges to reconstruct gene regulatory networks. On the one hand, scRNA-seq data reveal statistical information of gene expression at single-cell resolution, which is beneficial to construct gene expression regulatory networks. On the other hand, the noise and dropout of single-cell data bring great difficulties to the analysis of scRNA-seq data, resulting in lower accuracy of gene regulatory networks reconstructed by traditional methods. In this article, we propose a novel supervised convolutional neural network (CNNSE), which can extract gene expression information from 2D co-expression matrices of gene doublets and identify interactions between genes. Our method can avoid the loss of extreme point interference by constructing a 2D co-expression matrix of gene pairs and significantly improve the regulation precision between gene pairs. And the CNNSE model is able to obtain detailed and high-level semantic information from the 2D co-expression matrix. Our method achieves satisfactory results on simulated data [accuracy (ACC): 0.712, F1: 0.724]. On two real scRNA-seq datasets, our method exhibits higher stability and accuracy in inference tasks compared with other existing gene regulatory network inference algorithms.

Predictions of the Poses and Affinity of a Ligand over the Entire Surface of a NEET Protein: The Case of Human MitoNEET

Human NEET proteins contain two [2Fe-2S] iron-sulfur clusters, bound to three Cys residues and one His residue. They exist in two redox states. Recently, these proteins have revealed themselves as attractive drug targets for mitochondrial dysfunction-related diseases, such as type 2 diabetes, Wolfram syndrome 2, and cancers. Unfortunately, the lack of information and mechanistic understanding of ligands binding to the whole functional, cytoplasmatic domain has limited rational drug design approaches. Here, we use an enhanced sampling technique, volume-based metadynamics, recently developed by a team involving some of us, to predict the poses and affinity of the 2-benzamido-4-(1,2,3,4-tetrahydronaphthalen-2-yl)-thiophene-3-carboxylate ligand to the entire surface of the cytoplasmatic domain of the human NEET protein mitoNEET (mNT) in an aqueous solution. The calculations, based on the recently published X-ray structure of the complex, are consistent with the measured affinity. The calculated free energy landscape revealed that the ligand can bind in multiple sites and with poses other than the one found in the X-ray. This difference is likely to be caused by crystal packing effects that allow the ligand to interact with multiple adjacent NEET protein copies. Such extra contacts are of course absent in the solution; therefore, the X-ray pose is only transient in our calculations, where the binding free energy correlates with the number of contacts. We further evaluated how the reduction and protonation of the Fe-bound histidine, as well as temperature, can affect ligand binding. Both such modifications introduce the possibility for the ligand to bind in an area of the protein other than the one observed in the X-ray, with no or little impact on affinity. Overall, our study can provide insights on the molecular recognition mechanisms of ligand binding to mNT in different oxidative conditions, possibly helping rational drug design of NEET ligands.

A smartphone-adaptable chromogenic and fluorogenic sensor for rapid visual detection of toxic hydrazine in the environment

Hydrazine is an essential chemical in industries, but its high toxicity poses great threats to human health and environmental safety. Hence, it is of great significance to monitor the hydrazine in environment. In this work, we presented a chromogenic and fluorogenic dual-mode sensor RA for the detection of hydrazine based on nucleophilic substitution reaction. A linear relationship was obtained between the fluorescence intensity and the concentrations of N₂H₄ ranging from 0 to 35 μM (R² = 0.9936). The sensor can determine hydrazine with fast response (within 12 min), low limit of detection (0.129 μM) and high selectivity. RA was successfully used to detect N₂H₄ in real water samples with good recoveries and the results corresponded to the standard method. Furthermore, the sensor-coated portable test papers were fabricated, which can visually quantify hydrazine solutions with obvious fluorescence transformation from colorless to red. Moreover, RA-loaded papers were used to create a smartphone-adaptable RGB values analytical method for quantitative N₂H₄ detection.

Non-diabetic urine glucose in idiopathic membranous nephropathy

This study aims to analyze the characteristics of idiopathic membranous nephropathy (iMN) with nondiabetic urine glucose during the follow-up. We retrospectively analyzed the data of 1313 patients who were diagnosed iMN. The prevalence of nondiabetic urine glucose during follow-up was 10.89%. There were significant differences between the patients with nondiabetic urine glucose and those without urine glucose in gender, hypertension ratio, proteinuria, N-acetyl-β-glucosaminidase, retinol binding protein, serum albumin, serum creatinine (Scr), cholesterol, triglyceride and positive anti-phospholipase A2 receptor antibody ratio, glomerular sclerosis ratio, acute and chronic tubular injury lesion at baseline. To exclude the influence of the baseline proteinuria and Scr, case control sampling of urine glucose negative patients was applied according to gender, baseline proteinuria and Scr. The proteinuria nonremission (NR) ratio was 45.83 versus 12.50% of the urine glucose positive group and case control group. Partial remission (PR) ratio of the two groups was 36.46 versus 23.96% and complete remission (CR) ratio was 19.79% versus 63.54%, respectively. Patients with urine glucose had higher risk of 50% estimated glomerular filtration rate (eGFR) reduction. Cox regression showed that urine glucose and baseline Scr were risk factors of 50% reduction of eGFR. Urine glucose remission ratio of the patients with proteinuria NR, PR, and CR was 13.33, 56.25, and 94.73% (p < 0.005). Patients who got urine glucose remission also had better renal survival. In conclusion, non-diabetic urine glucose was closely related to proteinuria. It could be applied as a tubular injury marker to predict renal function.

Reconstructing gene regulatory networks of biological function using differential equations of multilayer perceptrons

BACKGROUND

Building biological networks with a certain function is a challenge in systems biology. For the functionality of small (less than ten nodes) biological networks, most methods are implemented by exhausting all possible network topological spaces. This exhaustive approach is difficult to scale to large-scale biological networks. And regulatory relationships are complex and often nonlinear or non-monotonic, which makes inference using linear models challenging.

RESULTS

In this paper, we propose a multi-layer perceptron-based differential equation method, which operates by training a fully connected neural network (NN) to simulate the transcription rate of genes in traditional differential equations. We verify whether the regulatory network constructed by the NN method can continue to achieve the expected biological function by verifying the degree of overlap between the regulatory network discovered by NN and the regulatory network constructed by the Hill function. And we validate our approach by adapting to noise signals, regulator knockout, and constructing large-scale gene regulatory networks using link-knockout techniques. We apply a real dataset (the mesoderm inducer Xenopus Brachyury expression) to construct the core topology of the gene regulatory network and find that Xbra is only strongly expressed at moderate levels of activin signaling.

CONCLUSION

We have demonstrated from the results that this method has the ability to identify the underlying network topology and functional mechanisms, and can also be applied to larger and more complex gene network topologies.

Structure-Based Screening Reveals a Ligand That Stabilizes the [2Fe-2S] Clusters of Human mitoNEET and Reduces Ovarian Cancer Cell Proliferation

Human NEET proteins play an important role in a variety of diseases, including cancer. Using the recently published X-ray structure of the human mNT-M1 complex, we screened a commercial chemical compound library and identified a new human mitoNEET (mNT) binding ligand (NTS-01). Biochemical investigations revealed that NTS-01 specifically binds to the human mNT protein and stabilizes its [2Fe-2S] clusters under oxidative conditions in vitro. Treatment of ovarian cancer cells with NTS-01 induces ovarian cancer (SKOV-3) mitochondrial fragmentation (fission) and reduces ovarian cancer cell proliferation in a 2D single-layer cell culture, as well as in a 3D-spheroids culture. The NTS-01 molecule represents therefore a new lead compound for further drug design studies attempting to develop efficient treatment against ovarian cancer.

The Association of R-Loop Binding Proteins Subtypes with CIN Implicates Therapeutic Strategies in Colorectal Cancer

Chromosomal instability (CIN) covers approximately 65 to 70% of colorectal cancer patients and plays an essential role in cancer progression. However, the molecular features and therapeutic strategies related to those patients are still controversial. R-loop binding proteins (RLBPs) exert significant roles in transcription and replication. Here, integrative colorectal cancer proteogenomic analysis identified two RLBPs subtypes correlated with distinct prognoses. Cluster I (CI), represented by high expression of RLBPs, was associated with the CIN phenotype. While Cluster II (CII) with the worst prognosis and low expression of RLBPs was composed of a high percentage of patients with mucinous adenocarcinoma or right-sided colon cancer. The molecular feature analysis revealed that the active RNA processing, ribosome synthesis, and aberrant DNA damage repair were shown in CI, a high inflammatory signaling pathway, and lymphocyte infiltration was enriched in CII. In addition, we revealed 42 tumor-associated RLBPs proteins. The CI with high expression of tumor-associated proteins was sensitive to drugs targeting genome integrity and EGFR in both cell and organoid models. Thus, our study unveils a significant molecular association of the CIN phenotype with RLBPs, and also provides a powerful resource for further functional exploration of RLBPs in cancer progression and therapeutic application.

Efficacy of long-term repeated rituximab treatment in refractory phospholipase A2 receptor-antibody-related membranous nephropathy

Aims: To evaluate the efficacy of long-term repeated rituximab treatment in refractory PLA2R-Ab-related membranous nephropathy (MN). Materials & methods: Rituximab was administered at a single dose of 375 mg/m² and repeated if peripheral B-cell levels were >5/ul in 46 patients with refractory PLA2R-Ab-related MN. Results: The median frequency of rituximab treatment was 3 (IQR 2.0-4.0). A total of 32 (32/46) patients achieved remission (completed remission [CR] or partial remission [PR]) over a median time of 17.0 months, and 10 patients eventually progressed to CR. The proportion of serum PLA2R-Ab depletion was 73.91% (34/46) over a median time of 9 months. Antibody depletion preceded proteinuria remission. Conclusions: Long-term repeated rituximab treatment achieved high kidney and immunological response rates in refractory PLA2R-Ab related MN, and antibody depletion was a prerequisite for proteinuria remission.

Multiple Poses and Thermodynamics of Ligands Targeting Protein Surfaces: The Case of Furosemide Binding to mitoNEET in Aqueous Solution

Human NEET proteins, such as NAF-1 and mitoNEET, are homodimeric, redox iron-sulfur proteins characterized by triple cysteine and one histidine-coordinated [2Fe-2S] cluster. They exist in an oxidized and reduced state. Abnormal release of the cluster is implicated in a variety of diseases, including cancer and neurodegeneration. The computer-aided and structure-based design of ligands affecting cluster release is of paramount importance from a pharmaceutical perspective. Unfortunately, experimental structural information so far is limited to only one ligand/protein complex. This is the X-ray structure of furosemide bound to oxidized mitoNEET. Here we employ an enhanced sampling approach, Localized Volume-based Metadynamics, developed by some of us, to identify binding poses of furosemide to human mitoNEET protein in solution. The binding modes show a high variability within the same shallow binding pocket on the protein surface identified in the X-ray structure. Among the different binding conformations, one of them is in agreement with the crystal structure’s one. This conformation might have been overstabilized in the latter because of the presence of crystal packing interactions, absent in solution. The calculated binding affinity is compatible with experimental data. Our protocol can be used in a straightforward manner in drug design campaigns targeting this pharmaceutically important family of proteins.

An anti-diabetic drug targets NEET (CISD) proteins through destabilization of their [2Fe-2S] clusters

Elevated levels of mitochondrial iron and reactive oxygen species (ROS) accompany the progression of diabetes, negatively impacting insulin production and secretion from pancreatic cells. In search for a tool to reduce mitochondrial iron and ROS levels, we arrived at a molecule that destabilizes the [2Fe-2S] clusters of NEET proteins (M1). Treatment of db/db diabetic mice with M1 improved hyperglycemia, without the weight gain observed with alternative treatments such as rosiglitazone. The molecular interactions of M1 with the NEET proteins mNT and NAF-1 were determined by X-crystallography. The possibility of controlling diabetes by molecules that destabilize the [2Fe-2S] clusters of NEET proteins, thereby reducing iron-mediated oxidative stress, opens a new route for managing metabolic aberration such as in diabetes.

[Metagenomic data-analysis reveals enrichment of lipopolysaccharide synthesis in the gut microbiota of atrial fibrillation patients]

Objective: To investigate the functional changes of key gut microbiota (GM) that produce lipopolysaccharide (LPS) in atrial fibrillation (AF) patients and to explore their potential role in the pathogenesis of AF. Methods: This was a prospective cross-sectional study. Patients with AF admitted to Beijing Chaoyang Hospital of Capital Medical University were enrolled from March 2016 to December 2018. Subjects with matched genetic backgrounds undergoing physical examination during the same period were selected as controls. Clinical baseline data and fecal samples were collected. Bacterial DNA was extracted and metagenomic sequencing was performed by using Illumina Novaseq. Based on metagenomic data, the relative abundances of KEGG Orthology (KO), enzymatic genes and species that harbored enzymatic genes were acquired. The key features were selected via the least absolute shrinkage and selection operator (LASSO) analysis. The role of GM-derived LPS biosynthetic feature in the development of AF was assessed by receiver operating characteristic (ROC) curve, partial least squares structural equation modeling (PLS-SEM) and logistic regression analysis. Results: Fifty nonvalvular AF patients (mean age: 66.0 (57.0, 71.3), 32 males(64%)) were enrolled as AF group. Fifty individuals (mean age 55.0 (50.5, 57.5), 41 males(82%)) were recruited as controls. Compared with the controls, AF patients showed a marked difference in the GM genes underlying LPS-biosynthesis, including 20 potential LPS-synthesis KO, 7 LPS-biosynthesis enzymatic genes and 89 species that were assigned as taxa harbored nine LPS-enzymatic genes. LASSO regression analysis showed that 5 KO, 3 enzymatic genes and 9 species could be selected to construct the KO, enzyme and species scoring system. Genes enriched in AF group included 2 KO (K02851 and K00972), 3 enzymatic genes (LpxH, LpxC and LpxK) and 7 species (Intestinibacter bartlettii、Ruminococcus sp. JC304、Coprococcus catus、uncultured Eubacterium sp.、Eubacterium sp. CAG:251、Anaerostipes hadrus、Dorea longicatena). ROC curve analysis revealed the predictive capacity of differential GM-derived LPS signatures to distinguish AF patients in terms of above KO, enzymatic and species scores: area under curve (AUC)=0.957, 95%CI: 0.918-0.995, AUC=0.940, 95%CI 0.889-0.991, AUC=0.972, 95%CI 0.948-0.997. PLS-SEM showed that changes in lipopolysaccharide-producing bacteria could be involved in the pathogenesis of AF. The key KO mediated 35.17% of the total effect of key bacteria on AF. After incorporating the clinical factors of AF, the KO score was positively associated with the significantly increased risk of AF (OR<0.001, 95%CI:<0.001-0.021, P<0.001). Conclusion: Microbes involved in LPS synthesis are enriched in the gut of AF patients, accompanied with up-regulated LPS synthesis function by encoding the LPS-enzymatic biosynthesis gene.

Single-cell chromatin accessibility landscape in kidney identifies additional cell-of-origin in heterogenous papillary renal cell carcinoma

Papillary renal cell carcinoma (pRCC) is the most heterogenous renal cell carcinoma. Patient survival varies and no effective therapies for advanced pRCC exist. Histological and molecular characterization studies have highlighted the heterogeneity of pRCC tumours. Recent studies identified the proximal tubule (PT) cell as a cell-of-origin for pRCC. However, it remains elusive whether other pRCC subtypes have different cell-of-origin. Here, by obtaining genome-wide chromatin accessibility profiles of normal human kidney cells using single-cell transposase-accessible chromatin-sequencing and comparing the profiles with pRCC samples, we discover that besides PT cells, pRCC can also originate from kidney collecting duct principal cells. We show pRCCs with different cell-of-origin exhibit different molecular characteristics and clinical behaviors. Further, metabolic reprogramming appears to mediate the progression of pRCC to the advanced state. Here, our results suggest that determining cell-of-origin and monitoring origin-dependent metabolism could potentially be useful for early diagnosis and treatment of pRCC.

qRT-PCR-based DNA homologous recombination-associated 4-gene score predicts pathologic complete response to platinum-based neoadjuvant chemotherapy in triple-negative breast cancer

PURPOSE

Cumulative evidence suggests that the addition of platinum agents as neoadjuvant chemotherapy (NACT) could improve the pathologic complete response (pCR) rate in triple-negative breast cancer (TNBC). We aimed to develop a DNA homologous recombination (HR)-associated gene expression score to predict tumor sensitivity to platinum-based NACT in TNBC.

METHODS

A retrospective cohort of 127 patients who were diagnosed with TNBC and received platinum-based NACT in Fudan University Shanghai Cancer Center from 2012 to 2017 was included in this study. Using quantitative reverse transcription-polymerase chain reaction (qRT-PCR), the expression levels of eight HR-associated genes were analyzed from formalin-fixed paraffin-embedded core-needle biopsy samples obtained before NACT. A random forest model was built to estimate the weight of each gene expression level and clinicopathological factors. The training set was used to modulate parameters and select the best model. The performance of the final model was evaluated in the validation set.

RESULTS

A 4-gene (BRCA1, XRCC5, PARP1, and RAD51) scoring system was developed. TNBC patients with a higher score had a nearly fourfold likelihood of achieving pCR to platinum-based NACT compared with patients with a lower score [odds ratio (OR) = 3.878; P < 0.001]. At the cutoff value of - 2.644, the 4-gene scoring system showed high sensitivity in predicting pCR in the breast (93.0%) and pCR in the breast/axilla (91.8%), while at the cutoff value of - 1.969, the 4-gene score showed high specificity for pCR in the breast (85.7%) and pCR in the breast/axilla (80.8%).

CONCLUSION

The qRT-PCR-based 4-gene score has the potential to predict pCR to platinum-based NACT in TNBC.

Interpretable Diagnosis for Whole-Slide Melanoma Histology Images Using Convolutional Neural Network

At present, deep learning-based medical image diagnosis had achieved high performance in several diseases. However, the black-box nature of the convolutional neural network (CNN) limits their role in diagnosis. In this study, a novel interpretable diagnosis pipeline using the CNN model was proposed. Furthermore, a sizeable melanoma database that contains 841 digital whole-slide images (WSIs) was built to train and evaluate the model. The model achieved strong melanoma classification ability (0.962 areas under the receiver operating characteristic, 0.887 sensitivity, and 0.925 specificity). Moreover, the proposed model outperformed the existing schemes in terms of accuracy that is 20 pathologists (0.933 vs 0.732 accuracy). Finally, the gradient-weighted class activation mapping (Grad-CAM) method was used to show the inner logic of the proposed model and its feasibility to improve diagnosis process in healthcare. The mechanism of feature heat maps which is visualized through a saliency mapping has demonstrated that features learned or extracted by the proposed model are compatible with the accepted pathological features. Conclusively, the proposed model provides a rapid and accurate diagnosis by locating the distinctive features of melanoma to build doctors' trust in the CNNs' diagnosis results.

Automated Diagnosis and Localization of Melanoma from Skin Histopathology Slides Using Deep Learning: A Multicenter Study

In traditional hospital systems, diagnosis and localization of melanoma are the critical challenges for pathological analysis, treatment instructions, and prognosis evaluation particularly in skin diseases. In literature, various studies have been reported to address these issues; however, a prominent smart diagnosis system is needed to be developed for the smart healthcare system. In this study, a deep learning-enabled diagnostic system is proposed and implemented that it has the capacity to automatically detect malignant melanoma in whole slide images (WSIs). In this system, the convolutional neural network (CNN), sophisticated statistical method, and image processing algorithms were integrated and implemented to locate benign and malignant lesions which are extremely useful in the diagnoses process of melanoma disease. To verify the exceptional performance of the proposed scheme, it is implemented in a multicenter database, which has 701 WSIs (641 WSIs from Central South University Xiangya Hospital (CSUXH) and 60 WSIs from the Cancer Genome Atlas (TCGA)). Experimental results have verified that the proposed system has achieved an area under the receiver operating characteristic curve (AUROC) of 0.971. Furthermore, the lesion area on the WSIs is represented by its degree of malignancy. These results show that the proposed system has the capacity to fully automate the diagnosis and localization problem of the melanoma in the smart healthcare systems.

The Classification of Six Common Skin Diseases Based on Xiangya-Derm: Development of a Chinese Database for Artificial Intelligence

Background

Skin and subcutaneous disease is the fourth-leading cause of the nonfatal disease burden worldwide and constitutes one of the most common burdens in primary care. However, there is a severe lack of dermatologists, particularly in rural Chinese areas. Furthermore, although artificial intelligence (AI) tools can assist in diagnosing skin disorders from images, the database for the Chinese population is limited.

Objective

This study aims to establish a database for AI based on the Chinese population and presents an initial study on six common skin diseases.

Methods

Each image was captured with either a digital camera or a smartphone, verified by at least three experienced dermatologists and corresponding pathology information, and finally added to the Xiangya-Derm database. Based on this database, we conducted AI-assisted classification research on six common skin diseases and then proposed a network called Xy-SkinNet. Xy-SkinNet applies a two-step strategy to identify skin diseases. First, given an input image, we segmented the regions of the skin lesion. Second, we introduced an information fusion block to combine the output of all segmented regions. We compared the performance with 31 dermatologists of varied experiences.

Results

Xiangya-Derm, as a new database that consists of over 150,000 clinical images of 571 different skin diseases in the Chinese population, is the largest and most diverse dermatological data set of the Chinese population. The AI-based six-category classification achieved a top 3 accuracy of 84.77%, which exceeded the average accuracy of dermatologists (78.15%).

Conclusions

Xiangya-Derm, the largest database for the Chinese population, was created. The classification of six common skin conditions was conducted based on Xiangya-Derm to lay a foundation for product research.

The two redox states of the human NEET proteins' [2Fe-2S] clusters

The NEET proteins constitute a unique class of [2Fe–2S] proteins. The metal ions bind to three cysteines and one histidine. The proteins’ clusters exist in two redox states; the oxidized protein (containing two Fe^III ions) can transfer the cluster to apo-acceptor protein(s), while the reduced form (containing one ferrous ion) remains bound to the protein frame. Here, we perform in silico and in vitro studies on human NEET proteins in both reduced and oxidized forms. Quantum chemical calculations on all available human NEET proteins structures suggest that reducing the cluster weakens the Fe–N^His and Fe–S^Cys bonds, similar to what is seen in other Fe–S proteins (e.g., ferredoxin and Rieske protein). We further show that the extra electron in the [2Fe–2S]⁺ clusters of one of the NEET proteins (mNT) is localized on the His-bound iron ion, consistently with our previous spectroscopic studies. Kinetic measurements demonstrate that the mNT [2Fe–2S]⁺ is released only by an increase in temperature. Thus, the reduced state of human NEET proteins [2Fe–2S] cluster is kinetically inert. This previously unrecognized kinetic inertness of the reduced state, along with the reactivity of the oxidized state, is unique across all [2Fe–2S] proteins. Finally, using a coevolutionary analysis, along with molecular dynamics simulations, we provide insight on the observed allostery between the loop L2 and the cluster region. Specifically, we show that W75, R76, K78, K79, F82 and G85 in the latter region share similar allosteric characteristics in both redox states.

Development and Validation of a Simple-to-Use Nomogram for Predicting the Upgrade of Atypical Ductal Hyperplasia on Core Needle Biopsy in Ultrasound-Detected Breast Lesions

Background

The rate of carcinoma upgrade for atypical ductal hyperplasia (ADH) diagnosed on core needle biopsy (CNB) is variable on open excision. The purpose of the present study was to develop and validate a simple-to-use nomogram for predicting the upgrade of ADH diagnosed with ultrasound (US)-guided core needle biopsy in patients with US-detected breast lesions.

Methods

Two retrospective sets, the training set (n = 401) and the validation set (n = 186), from Fudan University Shanghai Cancer Center between January 2014 and December 2019 were retrospectively analyzed. Clinicopathological and US features were selected using univariate and multivariable logistic regression, and the significant features were incorporated to build a nomogram model. Model discrimination and calibration were assessed in the training set and validation set.

Results

Of the 587 ADH biopsies, 67.7% (training set: 267/401, 66.6%; validation set: 128/186, 68.8%) were upgraded to cancers. In the multivariable analysis, the risk factors were age [odds ratio (OR) 2.739, 95% confidence interval (CI): 1.525–5.672], mass palpation (OR 3.008, 95% CI: 1.624–5.672), calcifications on US (OR 4.752, 95% CI: 2.569–9.276), ADH extent (OR 3.150, 95% CI: 1.951–5.155), and suspected malignancy (OR 4.162, CI: 2.289–7.980). The model showed good discrimination, with an area under curve (AUC) of 0.783 (95% CI: 0.736–0.831), and good calibration (p = 0.543). The application of the nomogram in the validation set still had good discrimination (AUC = 0.753, 95% CI: 0.666–0.841) and calibration (p = 0.565). Instead of surgical excision of all ADHs, if those categorized with the model to be at low risk for upgrade were surveillanced and the remainder were excised, then 63.7% (37/58) of surgeries of benign lesions could have been avoided and 78.1% (100/128) malignant lesions could be treated in time.

Conclusions

This study developed a simple-to-use nomogram by incorporating clinicopathological and US features with the overarching goal of predicting the probability of upgrade in women with ADH. The nomogram could be expected to decrease unnecessary surgery by nearly two-third and to identify most of the malignant lesions, helping guide clinical decision making with regard to surveillance versus surgical excision of ADH lesions.

Clinicopathological features and outcomes of SLE patients with renal injury characterised by thrombotic microangiopathy

OBJECTIVES

Non-immune complex (IC)-mediated renal thrombotic microangiopathy (TMA) has been reported in patients with systemic lupus erythematosus (SLE), but most studies included patients with both renal TMA and IC-mediated lupus nephritis (LN). In this study, the clinicopathological features and outcomes of renal injury characterised by only renal TMA were retrospectively analyzed.

METHODS

Patients with glomerular and/or vascular TMA in the absence of subendothelial or epithelial immune deposits were screened from 2,332 biopsied of SLE patients. The TMA lesions were divided into glomerular, vascular or both. Acute tubular-interstitial injury was semi-quantitatively analyzed. The podocyte foot process effacement (FPE) was measured by electronic microscopy.

RESULTS

Two hundred fifty-seven (11.0%) renal biopsies revealed TMA, among which 237 biopsies showed TMA coexisting with LN, and 20 (0.9%) biopsies had only renal TMA without or with only mesangial immune deposits. All patients manifested with acute kidney injury and haematological disorders. Among them, 11 (55%) required renal replacement therapy, 12 (60%) had nephrotic syndrome and 13 (65.0%) showed microvascular haemolytic anaemia with thrombocytopenia. Seventeen (85%) biopsies revealed both glomerular TMA and vascular TMA, two had only glomerular TMA and one had vascular TMA. Eight (40%) had no glomerular immune deposits and 12 (60%) showed only mesangial immune deposits. The acute tubulointerstitial injury in patients requiring dialysis was more severe than those not needing dialysis ((43.6 ± 24.9) % vs. (21.7 ± 20.1) %, p = 0.047). FPE of podocytes was positively correlated with proteinuria (r² = 0.347, p = 0.006). All patients received high-dose methylprednisolone pulse therapy. Four patients received plasma exchange. The renal function of 11 patients requiring dialysis initially recovered after 16.0 (interquartile range [IQR] 9.0, 30.0) days of treatment. During the follow-up of 58.0 (IQR 36.0, 92.3) months, remission was achieved in 19 (95%) patients; only one patient had no response. No patient died or progressed to end-stage renal disease; six patients (30%) relapsed.

CONCLUSION

Renal TMA, usually accompanying severe renal injury, was not uncommon in SLE patients with renal disease and should be distinguished from immune complex-mediated severe classes of LN. Early intensive immunosuppressive treatment may be associated with a good long-term renal outcome. Key Points • Most previous reports of renal TMA in SLE patients were associated with severe types of immune complex-mediated lupus nephritis; • Renal TMA with glomerular pauci-immune or only mesangial immune deposits was found in SLE patients and clinically presented with severe acute renal injury but good renal outcome; • Renal TMA should be considered as a unique type of SLE-associated renal injury.

[Establishment and test results of an artificial intelligence burn depth recognition model based on convolutional neural network]

Objective: To establish an artificial intelligence burn depth recognition model based on convolutional neural network, and to test its effectiveness. Methods: In this evaluation study on diagnostic test, 484 wound photos of 221 burn patients in Xiangya Hospital of Central South University (hereinafter referred to as the author's unit) from January 2010 to December 2019 taken within 48 hours after injury which met the inclusion criteria were collected and numbered randomly. The target wounds were delineated by image viewing software, and the burn depth was judged by 3 attending doctors with more than 5-year professional experience in Department of Burns and Plastic Surgery of the author's unit. After marking the superficial partial-thickness burn, deep partial-thickness burn, or full-thickness burn in different colors, the burn wounds were cut according to 224×224 pixels to obtain 5 637 complete wound images. The image data generator was used to expand images of each burn depth to 10 000 images, after which, images of each burn depth were divided into training set, verification set, and test set according to the ratio of 7.0∶1.5∶1.5. Under Keras 2.2.4 Python 2.8.0 version, the residual network ResNet-50 of convolutional neural network was used to establish the artificial intelligence burn depth recognition model. The training set was input for training, and the verification set was used to adjust and optimize the model. The judging accuracy rate of various burn depths by the established model was tested by the test set, and precision, recall, and F1_score were calculated. The test results were visualized to generate two-dimensional tSNE cloud chart through the dimensionality reduction tool tSNE, and the distribution of various burn depths was observed. According to the sensitivity and specificity of the model for the recognition of 3 kinds of burn depths, the corresponding receiver operator characteristics (ROC) curve was drawn, and the area under the ROC curve was calculated. Results: (1) After the testing of the test set, the precisions of the artificial intelligence burn depth recognition model for the recognition of superficial partial-thickness burn, deep partial-thickness burn, or full-thickness burn were 84% (1 095/1 301), 81% (1 215/1 499) and 82% (1 395/1 700) respectively, the recall were 73% (1 095/1 500), 81% (1 215/1 500) and 93% (1 395/1 500) respectively, and the F1_scores were 0.78, 0.81, and 0.87 respectively. (2) tSNE cloud chart showed that there was small overlapping among different burn depths in the test results for the test set of artificial intelligence burn depth recognition model, among which the overlapping between superficial partial-thickness burn and deep partial-thickness burn and that between deep partial-thickness burn and full-thickness burn were relatively more, while the overlapping between superficial partial-thickness burn and full-thickness burn was relatively less. (3) The area under the ROC curve for 3 kinds of burn depths recognized by the artificial intelligence burn depth recognition model was ≥0.94. Conclusions: The artificial intelligence burn depth recognition model established by ResNet-50 network can rather accurately identify the burn depth in the early wound photos of burn patients, especially superficial partial-thickness burn and full-thickness burn. It is expected to be used clinically to assist the diagnosis of burn depth and improve the diagnostic accuracy.

Clinicopathologic Features and Outcomes in Fibronectin Glomerulopathy: A Case Series of 19 Patients

Aims: To describe the characteristics and prognosis of 19 patients with fibronectin glomerulopathy (FNG) and evaluate prognostic factors associated with poor renal outcomes.

Methods: Included in this retrospective study was 19 FNG patients in Nanjing Glomerulonephritis Registry system. Associations between the clinical parameters, pathological features, and renal outcomes were evaluated by Kaplan-Meier survival analysis.

Results: Of the 19 FNG patients included in this study, 8 (42.1%) were women. The median age of the 19 FNG patients was 31 (17–71) years, and the median disease duration 48 (1–175) months at diagnosis. At the time of renal biopsy, the mean serum creatinine (Scr) was 1.22 ± 0.16 mg/dl and urinary protein was 6.24 ± 0.97 mg/24 h. Renal biopsy showed a lobular appearance with cellular mesangial nodules expanded by matrix in 14 cases. After a median follow-up period of 87 months (interquartile range 34–114.5 months), 8 FNG patients developed renal function decline, including 7 progressing into end-stage renal disease (ESRD) and 1 presenting with by a 2-fold-increase in Scr. Scr and proteinuria remained stable in the remaining 11 patients. Kaplan-Meier survival analysis showed that nephrotic range proteinuria (P = 0.022) and focal glomerular sclerosis (P = 0.028) were associated with renal function decline.

Conclusions: Nephrotic range proteinuria and focal glomerular sclerosis were associated with renal function decline during the follow-up period of the FNG patients in our series. FNG Patients at risk of renal function decline should be identified preferentially and given more progressive and effective therapies to prevent further disease progression.

HLA-B27 Negativity Is Associated With Renal Function Decline in Patients With Ankylosing Spondylitis and Secondary IgA Nephropathy

This study aimed to determine the impact of HLA-B27 on clinical phenotype and renal function during follow-up periods in patients with ankylosing spondylitis (AS) and secondary IgA nephropathy (IgAN). This single-center retrospective study included 71 AS patients with secondary IgAN. Renal function decline was defined as a mean eGFR decline of more than 5 mL/min/1.73 m² per year or progression into the dialysis stage. The association between HLA-B27 status and renal function decline was evaluated by univariable and multivariable Cox regression analyses. The results showed that seven (9.85%) of the 71 included patients were HLA-B27-negative. The median follow-up period was 4.0 years. HLA-B27-negative patients showed higher levels of uric acid (UA) than those who were HLA-B27-positive. Pathologically, a higher percentage of globally sclerotic glomeruli was observed in HLA-B27-negative patients. Survival analysis indicated that HLA-B27 negativity was associated with a significantly higher probability of renal function decline than HLA-B27 positivity. This significant association was also found in subgroup analyses of patients with either substantial proteinuria (more than 1.0 g per day) or interstitial fibrosis and tubular atrophy. Multivariable analysis showed that HLA-27 negativity was independently associated with renal function decline (HR 6.58; 95% CI 1.65 to 26.21; p = 0.008). In conclusion, HLA-B27 negativity is associated not only with a higher level of UA and a higher percentage of globally sclerotic glomeruli in AS patients with secondary IgAN but with renal function decline during follow-up periods.

CDE++: Learning Categorical Data Embedding by Enhancing Heterogeneous Feature Value Coupling Relationships

Categorical data are ubiquitous in machine learning tasks, and the representation of categorical data plays an important role in the learning performance. The heterogeneous coupling relationships between features and feature values reflect the characteristics of the real-world categorical data which need to be captured in the representations. The paper proposes an enhanced categorical data embedding method, i.e., CDE++, which captures the heterogeneous feature value coupling relationships into the representations. Based on information theory and the hierarchical couplings defined in our previous work CDE (Categorical Data Embedding by learning hierarchical value coupling), CDE++ adopts mutual information and margin entropy to capture feature couplings and designs a hybrid clustering strategy to capture multiple types of feature value clusters. Moreover, Autoencoder is used to learn non-linear couplings between features and value clusters. The categorical data embeddings generated by CDE++ are low-dimensional numerical vectors which are directly applied to clustering and classification and achieve the best performance comparing with other categorical representation learning methods. Parameter sensitivity and scalability tests are also conducted to demonstrate the superiority of CDE++.

Specifically targeting cancer proliferation and metastasis processes: the development of matriptase inhibitors

Matriptase is a type II transmembrane serine protease, which has been suggested to play critical roles in numerous pathways of biological developments. Matriptase is the activator of several oncogenic proteins, including urokinase-type plasminogen activator (uPA), hepatocyte growth factor (HGF) and protease-activated receptor 2 (PAR-2). The activations of these matriptase substrates subsequently lead to the generation of plasmin, matrix metalloproteases (MMPs), and the triggers for many other signaling pathways related to cancer proliferation and metastasis. Accordingly, matriptase is considered an emerging target for the treatments of cancer. Thus far, inhibitors of matriptase have been developed as potential anti-cancer agents, which include small-molecule inhibitors, peptide-based inhibitors, and monoclonal antibodies. This review covers established literature to summarize the chemical and biochemical aspects, especially the inhibitory mechanisms and structure-activity relationships (SARs) of matriptase inhibitors with the goal of proposing the strategies for their future developments in anti-cancer therapy.

Characterization of thromboelastography of patients with different pathological types of nephrotic syndrome

To investigate the changes in blood coagulability as measured by thromboelastography (TEG) in patients with nephrotic syndrome of different etiologies as well as in patients with venous thromboembolic events (VTE).From January 2013 to October 2017, patients who were diagnosed as idiopathic membranous nephropathy (IMN), minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) were enrolled into this retrospective study in which their clinical characteristics, including TEG variables, were investigated. According to the presence or absence of VTE, the patients with IMN were divided into 2 groups of VTE and non-VTE. The risk factors of VTE were analyzed with logistic regression.Significant differences in TEG parameters were found among the 3 groups of patients with R and K values lower, while the α-angle, maximum amplitude (MA) and confidence interval (CI) values higher, in the IMN group than those in the MCD and FSGS groups (P < .01). Multiple linear regression analysis indicated that the histologic subtype was an independent relevant factor of K time, angle, MA, and CI values. Multivariate logistic regression analysis revealed that serum albumin and CI value were independent risk factors of VTE (P < .05).The results showed that IMN patients may have higher whole blood coagulability than MCD and FSGS patients. The hypercoagulability in IMN patients may be attributed to platelet hyperactivity and the accelerated fibrin-platelet interaction. Hypoproteinemia and increased CI value were independent risk factors of VTE in IMN.

The complete mitogenome of Hong Kong paradise fish (Macropodus hongkongensis), an endemic freshwater fish in South China

The first complete mitogenome of Hong Kong paradise fish (Macropodus hongkongensis) was determined in this study. The assembled mitogenome is 16,494 bp and consisted of 13 protein-coding genes, 22 tRNAs, 2 rRNAs, and a control region. Nucleotide composition of the complete mitogenome is 30.6% A, 24.8% C, 14.8% G, and 29.8% T, with an A + T bias of 60.4%. The maximum-likelihood tree based on 13 protein-coding genes showed that M. erythropterus was the closest related species to M. hongkongensis.

A novel tumor and mitochondria dual-targeted photosensitizer showing ultra-efficient photodynamic anticancer activities

We designed and synthesized a simple, but highly effective photosensitizer (G-Mito-Pc), which can precisely target the mitochondria of epidermal growth factor receptor (EGFR)-overexpressing cancer cells, to achieve dual targeting function at both cell and organelle levels in cancer therapy. We further explored the possible molecular mechanism of the enhanced bioactivity of G-Mito-Pc compared to that of the reference photosensitizer using molecular dynamics simulations on their interactions with a physiologically relevant mitochondrial membrane model.

Complete remission of both immunoglobulin light chain amyloidosis and psoriasis after autologous hematopoietic stem cell transplantation: A case report

RATIONALE

Immunoglobulin light chain amyloidosis (AL amyloidosis) is characterized by the deposition of abnormal amyloid protein produced by a pathological plasma cell clone in various organs and soft tissues. Hematopoietic stem cell transplantation (HSCT) is an effective way to treat AL amyloidosis. Psoriasis is a common autoimmune disease (AID) and HSCT is a potential treatment for severe AIDs. We report a rare case of AL amyloidosis coincidence with psoriasis obtained continuous complete remission of the 2 diseases by autologous hematopoietic stem cell transplantation (ASCT).

PATIENT CONCERNS

A 58-year-old man with a 30-year history of psoriasis complaining of edema and hypotension for 2 weeks was referred to our institution. His urine protein was quantified 2.83 g/day, without hematuria and decrease of glomerular filtration rate.

DIAGNOSIS

Renal biopsy confirmed AL amyloidosis and multiple myeloma was excluded by bone marrow cytomorphologic examination.

INTERVENTIONS

Chemotherapy regimen based on bortezomib and thalidomide had achieved hematologic partial remission, but the kidney had no response and psoriasis was still active. Furthermore, he received a standard myeloablative conditioning with high dose melphalan followed by ASCT.

OUTCOMES

The erythema with slivery scales of psoriasis vulgaris gradually improved and almost disappeared after granulocyte implantation. He obtained persistent hematological complete remission, organ response and recovery of psoriasis.

LESSONS

We report a rare case of AL amyloidosis coincidence with psoriasis treated by ASCT. The outcome of this patient indicated that ASCT has therapeutic values both in AL amyloidosis and AIDs.

PD-L1 Nanobody Competitively Inhibits the Formation of the PD-1/PD-L1 Complex: Comparative Molecular Dynamics Simulations

The anti-PD-L1 monoclonal antibody (mAb) targeting PD-1/PD-L1 immune checkpoint has achieved outstanding results in clinical application and has become one of the most popular anti-cancer drugs. The mechanism of molecular recognition and inhibition of PD-L1 mAbs is not yet clear, which hinders the subsequent antibody design and modification. In this work, the trajectories of PD-1/PD-L1 and nanobody/PD-L1 complexes were obtained via comparative molecular dynamics simulations. Then, a series of physicochemical parameters including hydrogen bond, dihedral angle distribution, pKa value and binding free energy, and so forth, were all comparatively analyzed to investigate the recognition difference between PD-L1 and PD-1 and nanobody. Both LR113 (the amino acid residues in PD-L1 are represented by the lower left sign of L) and LR125 residues of PD-L1 undergo significant conformational change after association with mAbs, which dominates a strong electrostatic interaction. Solvation effect analysis revealed that solvent-water enhanced molecular recognition between PD-L1 and nanobody. By combining the analyses of the time-dependent root mean squared fluctuation (RMSF), free energy landscape, clustering and energy decomposition, the potential inhibition mechanism was proposed that the nanobody competitively and specifically bound to the β-sheet groups of PD-L1, reduced the PD-L1’s flexibility and finally blocked the formation of PD-1/PD-L1 complex. Based on the simulation results, site-directed mutagenesis of ND99 (the amino acid residues in Nano are displayed by the lower left sign of N) and NQ116 in the nanobody may be beneficial for improving antibody activity. This work offers some structural guidance for the design and modification of anticancer mAbs based on the structure of the PD-1/PD-L1 complex.

[Molecular recognition mechanism and motion of HCV NS3/4A protease with Faldaprevir analogue]

Faldaprevir analogue molecule (FAM) has been reported to effectively inhibit the catalytic activity of HCV NS3/4A protease, making it a potential lead compound against HCV. A series of HCV NS3/4A protease crystal structures were analyzed by bioinformatics methods, and the FAM-HCV NS3/4A protease crystal structure was chosen for this study. A 20.4 ns molecular dynamics simulation of the complex consists of HCV NS3/4A protease and FAM was conducted. The key amino acid residues for interaction and the binding driving force for the molecular recognition between the protease and FAM were identified from the hydrogen bonds and binding free energy analyses. With the driving force of hydrogen bonds and van der Waals, FAM specifically bind to the active pocket of HCV NS3/4A protease, including V130-S137, F152-D166, D77-D79 and V55, which agreed with the experimental data. The effect of R155K, D168E/V and V170T site-directed mutagenesis on FAM molecular recognition was analyzed for their effect on drug resistance, which provided the possible molecular explanation of FAM resistance. Finally, the system conformational change was explored by using free energy landscape and conformational cluster. The result showed four kinds of dominant conformation, which provides theoretical basis for subsequent design of Faldaprevir analogue inhibitors based on the structure of HCV NS3/4A protease.

An effective HIV-1 integrase inhibitor screening platform: Rationality validation of drug screening, conformational mobility and molecular recognition analysis for PFV integrase complex with viral DNA

As an important target for the development of novel anti-AIDS drugs, HIV-1 integrase (IN) has been widely concerned. However, the lack of a complete accurate crystal structure of HIV-1 IN greatly blocks the discovery of novel inhibitors. In this work, an effective HIV-1 IN inhibitor screening platform, namely PFV IN, was filtered from all species of INs. Next, the 40.8% similarity with HIV-1 IN, as well as the high efficiency of virtual screening and the good agreement between calculated binding free energies and experimental ones all proved PFV IN is a promising screening platform for HIV-1 IN inhibitors. Then, the molecular recognition mechanism of PFV IN by its substrate viral DNA and six naphthyridine derivatives (NRDs) inhibitors was investigated through molecular docking, molecular dynamics simulations and water-mediated interactions analyses. The functional partition of NRDs IN inhibitors could be divided into hydrophobic and hydrophilic ones, and the Mg²⁺ ions, water molecules and conserved DDE motif residues all interacted with the hydrophilic partition, while the bases in viral DNA and residues like Tyr212, Pro214 interacted with the hydrophobic one. Finally, the free energy landscape (FEL) and cluster analyses were performed to explore the molecular motion of PFV IN-DNA system. It is found that the association with NRDs inhibitors would obviously decrease the motion amplitude of PFV IN-DNA, which may be one of the most potential mechanisms of IN inhibitors. This work will provide a theoretical basis for the inhibitor design based on the structure of HIV-1 IN.

Apolipoprotein A-1-related amyloidosis 2 case reports and review of the literature

RATIONALE

Apolipoprotein A-1 (ApoA-1)-related amyloidosis is characterized by the deposition of ApoA-1 in various organs and can be either hereditary or nonhereditary. It is rare and easily misdiagnosed. Renal involvement is common in hereditary ApoA-1 amyloidosis, but rare in the nonhereditary form.

PATIENT CONCERNS

We reported two cases with ApoA-1 amyloidosis, a 64-year-old man suffering from nephrotic syndrome and a 40-year-old man with nephrotic syndrome and splenomegaly. Renal biopsies revealed glomerular, interstitial and vascular amyloid deposits and positive phospholipase A2 receptor staining in the glomerular capillary loop in case 1, and mesangial amyloid deposits in case 2.

DIAGNOSES

After immunostaining failed to determine the specific amyloid protein, proteomic analysis of amyloid deposits by mass spectrometry was performed and demonstrated the ApoA-1 origin of the amyloid. Genetic testing revealed no mutation of the APOA1 gene in case 1 but a heterozygous mutation, Trp74Arg, in case 2. Case 1 was thus diagnosed as nonhereditary ApoA-1 associated renal amyloidosis with membranous nephropathy, and case 2 as hereditary ApoA-1 amyloidosis with multiorgan injuries (kidney and spleen) and a positive family history.

INTERVENTIONS

Case 1 was treated with glucocorticoid combined with cyclosporine. Case 2 was treated with calcitriol and angiotensin converting enzyme inhibitors.

OUTCOMES

Two cases were followed up for 5 months and 2 years, respectively; and case 1 was found to have attenuated proteinuria while case 2 had an elevation of cholestasis indices along with renal insufficiency.

LESSONS

Proteomic analysis by mass spectrometry of the amyloid deposits combined with genetic analysis can provide accurate diagnosis of ApoA-1 amyloidosis. Besides, these 2 cases expand our knowledge of ApoA-1-related renal amyloidosis.

Pancreatic metastasis from invasive pleomorphic lobular carcinoma of the breast: a rare case report

Background

Invasive pleomorphic lobular carcinoma (PLC) is an aggressive subtype of invasive lobular carcinoma of the breast, which has its own histopathological and biological features. The metastatic patterns for PLC are distinct from those of invasive ductal carcinoma. In addition, pancreatic metastasis from PLC is extremely rare.

Case presentation

We report a rare case of a 48-year-old woman presenting with clinical gastrointestinal symptoms and pancreatic metastasis of PLC. The pancreatic tumor was composed of pleomorphic tumor cells arranged in the form of solid sheets and nests and as single files, with frequent mitotic figures, nucleolar prominence, high nuclear to cytoplasmic ratio and loss of cohesion. The malignant cells were positive for p120 (cytoplasmic) and GATA3 and negative for estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, E-cadherin, gross cystic disease fluid protein 15 and mammaglobin, which indicated a lobular carcinoma phenotype of the breast.

Conclusions

To the best of our knowledge, this is one of the few reported cases in the literature of pancreatic metastasis of invasive lobular carcinoma of the breast, of which the definitive diagnosis was obtained only after surgery. Rare metastasis sites should be considered, particularly, when a patient has a medical history of PLC.

[Correlation between androgen receptor expression and surrogate molecular subtypes in invasive breast carcinoma]

Objective: To investigate androgen receptor(AR)expression in invasive breast carcinoma and the correlation with surrogate molecular breast carcinoma subtypes. Methods: Immunohistochemical staining of AR and other biomarkers was performed in a cohort of 870 cases of primary invasive breast carcinomas collected from August to December, 2016. The association of AR expression with different histological and surrogate molecular subtypes was analyzed. Results: The positive expression rate of AR in the immunohistochemistry-based surrogate subtypes was 96.3%(207/215) for Luminal A, 89.8%(378/421) for Luminal B, 82.4%(75/91) for HER2 overexpression and 37.1%(53/143) for triple negative breast carcinoma, with significant differences among the four groups (P<0.01). AR correlated positively with the expression of ER(P<0.01), PR(P<0.01), HER2(P=0.007), GATA3(P<0.01), GCDFP15(P<0.01)and mammaglobin(P<0.01), while negatively with the expression of Ki-67(P<0.01), CK5/6(P<0.01)and CK14(P<0.01). Conclusions: AR exhibits a high expression in invasive breast carcinoma, which is mainly correlated with ER-positive breast carcinoma. Regardless of the relatively low expression rate, AR is a potential therapeutic target in triple negative breast carcinoma.