Iridium(III) carbene complexes as potent girdin inhibitors against metastatic cancers.

Many cancer-driving protein targets remain undruggable due to a lack of binding molecular scaffolds. In this regard, octahedral metal complexes with unique and versatile three-dimensional structures have rarely been explored as inhibitors of undruggable protein targets. Here, we describe antitumor iridium(III) pyridinium-N-heterocyclic carbene complex 1a, which profoundly reduces the viability of lung and breast cancer cells as well as cancer patient-derived organoids at low micromolar concentrations. Compound 1a effectively inhibits the growth of non-small-cell lung cancer and triple-negative breast cancer xenograft tumors, impedes the metastatic spread of breast cancer cells, and can be modified into an antibody-drug conjugate payload to achieve precise tumor delivery in mice. Identified by thermal proteome profiling, an important molecular target of 1a in cellulo is Girdin, a multifunctional adaptor protein that is overexpressed in cancer cells and unequivocally serves as a signaling hub for multiple pivotal oncogenic pathways. However, specific small-molecule inhibitors of Girdin have not yet been developed. Notably, 1a exhibits high binding affinity to Girdin with a Kd of 1.3 µM and targets the Girdin-linked EGFR/AKT/mTOR/STAT3 cancer-driving pathway, inhibiting cancer cell proliferation and metastatic activity. Our study reveals a potent Girdin-targeting anticancer compound and demonstrates that octahedral metal complexes constitute an untapped library of small-molecule inhibitors that can fit into the ligand-binding pockets of key oncoproteins.

Characterization of AST-001 non-clinical pharmacokinetics: A novel selective AKR1C3-activated prodrug in mice, rats, and cynomolgus monkeys.

AST-001 is a chemically synthesized inactive nitrogen mustard prodrug that is selectively cleaved to a cytotoxic aziridine (AST-2660) via aldo-keto reductase family 1 member C3 (AKR1C3). The purpose of this study was to investigate the pharmacokinetics and tissue distribution of the prodrug, AST-001, and its active metabolite, AST-2660, in mice, rats, and monkeys. After single and once daily intravenous bolus doses of 1.5, 4.5, and 13.5 mg/kg AST-001 to Sprague-Dawley rats and once daily 1 h intravenous infusions of 0.5, 1.5, and 4.5 mg/kg AST-001 to cynomolgus monkeys, AST-001 exhibited dose-dependent pharmacokinetics and reached peak plasma levels at the end of the infusion. No significant accumulation and gender differences were observed after 7 days of repeated dosing. In rats, the half-life of AST-001 was dose independent and ranged from 4.89 to 5.75 h. In cynomolgus monkeys, the half-life of AST-001 was from 1.66 to 5.56 h and increased with dose. In tissue distribution studies conducted in Sprague-Dawley rats and in liver cancer PDX models in female athymic nude mice implanted with LI6643 or LI6280 HepG2-GFP tumor fragments, AST-001 was extensively distributed to selected tissues. Following a single intravenous dose, AST-001 was not excreted primarily as the prodrug, AST-001 or the metabolite AST-2660 in the urine, feces, and bile. A comprehensive analysis of the preclinical data and inter-species allometric scaling were used to estimate the pharmacokinetic parameters of AST-001 in humans and led to the recommendation of a starting dose of 5 mg/m2 in the first-in-human dose escalation study.

Comparative evaluation of multiparametric lumbar MRI radiomic models for detecting osteoporosis.

BACKGROUND: Osteoporosis is a serious global public health issue. Currently, there are few studies that explore the use of multiparametric MRI radiomics for osteoporosis detection. The purpose of this study was to compare the performance of radiomics features from multiple MRI sequences (T1WI, T2WI and T1WI combined with T2WI) for detecting osteoporosis in patients. METHODS: A retrospective analysis was performed on 160 patients who had undergone dual-energy X-ray absorptiometry(DXA) and lumbar magnetic resonance imaging (MRI) at our hospital. Among them, 86 patients were diagnosed with abnormal bone mass (osteoporosis or low bone mass), and 74 patients were diagnosed with normal bone mass based on the DXA results. Sagittal T1-and T2-weighted images of all patients were imported into the uAI Research Portal (United Imaging Intelligence) for image delineation and radiomics analysis, where a series of radiomic features were obtained. A radiomic model that included T1WI, T2WI, and T1WI+T2WI was established using features selected by LASSO regression. We used ROC curve analysis to evaluate the predictive efficacy of each model for identifying bone abnormalities and conducted decision curve analysis (DCA) to evaluate the net benefit of each model. Finally, we validated the model in a sample of 35 patients from different health care institution. RESULTS: The T1WI + T2WI radiomics model showed better screening performance for patients with abnormal bone mass. In the training group, the sensitivity was 0.758, the specificity was 0.78, and the accuracy was 0.768 (AUC =0.839, 95% CI=0.757-0.901). In the validation group, the sensitivity was 0.792, the specificity was 0.875, and the accuracy was 0.833 (AUC =0.86, 95% CI=0.73-0.943).The DCA also showed that the combined model had better net benefits. In the external validation group, the sensitivity was 0.764, the specificity was 0.833, and the accuracy was 0.8 (AUC =0.824, 95% CI 0.678-0.969). CONCLUSIONS: Radiomics-based multiparametric MRI can be used for the quantitative analysis of lumbar MRI and for accurately screening patients with abnormal bone mass.

Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomography.

OBJECTIVES: Aimed to develop a nomogram model based on deep learning features and radiomics features for the prediction of early hematoma expansion. METHODS: A total of 561 cases of spontaneous intracerebral hemorrhage (sICH) with baseline Noncontrast Computed Tomography (NCCT) were included. The metrics of hematoma detection were evaluated by Intersection over Union (IoU), Dice coefficient (Dice), and accuracy (ACC). The semantic features of sICH were judged by EfficientNet-B0 classification model. Radiomics analysis was performed based on the region of interest which was automatically segmented by deep learning. A combined model was constructed in order to predict the early expansion of hematoma using multivariate binary logistic regression, and a nomogram and calibration curve were drawn to verify its predictive efficacy by ROC analysis. RESULTS: The accuracy of hematoma detection by segmentation model was 98.2% for IoU greater than 0.6 and 76.5% for IoU greater than 0.8 in the training cohort. In the validation cohort, the accuracy was 86.6% for IoU greater than 0.6 and 70.0% for IoU greater than 0.8. The AUCs of the deep learning model to judge semantic features were 0.95 to 0.99 in the training cohort, while in the validation cohort, the values were 0.71 to 0.83. The deep learning radiomics model showed a better performance with higher AUC in training cohort (0.87), internal validation cohort (0.83), and external validation cohort (0.82) than either semantic features or Radscore. CONCLUSION: The combined model based on deep learning features and radiomics features has certain efficiency for judging the risk grade of hematoma. CLINICAL RELEVANCE STATEMENT: Our study revealed that the deep learning model can significantly improve the work efficiency of segmentation and semantic feature classification of spontaneous intracerebral hemorrhage. The combined model has a good prediction efficiency for early hematoma expansion. KEY POINTS: • We employ a deep learning algorithm to perform segmentation and semantic feature classification of spontaneous intracerebral hemorrhage and construct a prediction model for early hematoma expansion. • The deep learning radiomics model shows a favorable performance for the prediction of early hematoma expansion. • The combined model holds the potential to be used as a tool in judging the risk grade of hematoma.

The loss of B7-H4 expression in breast cancer cells escaping from T cell cytotoxicity contributes to epithelial-to-mesenchymal transition.

BACKGROUND: B7 homology 4 (B7-H4), a potential target for cancer therapy, has been demonstrated to inhibit T cell cytotoxicity in the early stages of breast cancer. However, B7-H4 manipulating breast tumor immune microenvironment (TIME) in the tumor progression remains unknown. METHODS: We engineered T cells with B7-H4-specific chimeric antigen receptors (CARs) and performed a T cell co-culture assay to characterize B7-H4 expression level in breast cancer cells escaping from T cell cytotoxicity. We generated B7-H4 knockout (KO) and overexpression (OE) breast cancer cells to determine the epithelial-to-mesenchymal transition (EMT) and stemness characteristics in vitro and in vivo, including tumor proliferation, migration, metastasis and chemoresistance. The Cancer Genome Atlas breast cancer database was accessed to investigate the correlation between B7-H4 expression levels and EMT characteristics in patients with breast cancer. RESULTS: Our result found that B7-H4 expression level was significantly reduced in a subset of breast cancer cells that escaped from the cytotoxicity of B7-H4 CAR-T cells. Compared with wild type cells, B7-H4 KO cells prompt EMT and stemness characteristics, including migration, invasion and metastasis, and OE cells vice versa. The increase in H3K27me3 in KO cells confirmed the epigenetic reprogramming of cancer stem cells. The IC50 of doxorubicin or oxaliplatin significantly increased in KO cells, which was in agreement with a decrease in OE cells. Moreover, a trend of downregulated B7-H4 from stage I to stage II breast cancer patients indicates that the low-expressing B7-H4 breast cancer cells escaping from TIME have spread to nearby breast lymph nodes in the cancer progression. CONCLUSIONS: Our study illuminates the novel role of renouncing B7-H4 in breast cancer cells through immune escape, which contributes to EMT processes and provides new insights for breast cancer treatments.

Visible-Light Photoredox-Catalyzed Three-Component Reaction of Carbazoles with Alkenes and S-(Difluoromethyl)sulfonium Salt: A Practical Approach to Access Difluoroalkyl-Functionalized Carbazoles.

A mild and elegant multicomponent protocol for construction of CF2H-containing carbazoles was accomplished by visible-light photoredox catalysis with formation of two new C-C bonds in a single step to deliver a wide variety of structurally diverse difluoroalkylated carbazoles in moderate to good yields, featuring mild reaction conditions, synthetic simplicity, broad substrates, and good functional group tolerance.

Risk stratification by nomogram of deep learning radiomics based on multiparametric magnetic resonance imaging in knee meniscus injury.

PURPOSE: To construct and validate a nomogram model that integrated deep learning radiomic features based on multiparametric MRI and clinical features for risk stratification of meniscus injury. METHODS: A total of 167 knee MR images were collected from two institutions. All patients were classified into two groups based on the MR diagnostic criteria proposed by Stoller et al. The automatic meniscus segmentation model was constructed through V-net. LASSO regression was performed to extract the optimal features correlated to risk stratification. A nomogram model was constructed by combining the Radscore and clinical features. The performance of the models was evaluated by ROC analysis and calibration curve. Subsequently, the model was simulated by junior doctors in order to test its practical application effect. RESULTS: The Dice similarity coefficients of automatic meniscus segmentation models were all over 0.8. Eight optimal features, identified by LASSO regression, were employed to calculate the Radscore. The combined model showed a better performance in both the training cohort (AUC = 0.90, 95%CI: 0.84-0.95) and the validation cohort (AUC = 0.84, 95%CI: 0.72-0.93). The calibration curve indicated a better accuracy of the combined model than either the Radscore or clinical model alone. The simulation results showed that the diagnostic accuracy of junior doctors increased from 74.9 to 86.2% after using the model. CONCLUSION: Deep learning V-net demonstrated great performance in automatic meniscus segmentation of the knee joint. It was reliable for stratifying the risk of meniscus injury of the knee by nomogram which integrated the Radscores and clinical features.

Dihydroartemisinin engages liver fatty acid binding protein and suppresses metastatic hepatocellular carcinoma growth.

Dihydroartemisinin non-covalently binds liver fatty acid binding protein (FABP1) with micromolar affinity, acts as a FABP1-dependent peroxisome proliferator-activated receptor alpha agonist and inhibits metastatic hepatocellular carcinoma growth.

DNA topoisomerase 2-associated proteins PATL1 and PATL2 regulate the biogenesis of hERG K+ channels.

The human ether-a-go-go-related gene (hERG) K+ channel conducts a rapidly activating delayed rectifier K+ current (IKr), which is essential for normal electrical activity of the heart. Precise regulation of hERG channel biogenesis is critical for serving its physiological functions, and deviations from the regulation result in human diseases. However, the mechanism underlying the precise regulation of hERG channel biogenesis remains elusive. Here, by using forward genetic screen, we found that PATR-1, the Caenorhabditis elegans homolog of the yeast DNA topoisomerase 2-associated protein PAT1, is a critical regulator for the biogenesis of UNC-103, the ERG K+ channel in C. elegans. A loss-of-function mutation in patr-1 down-regulates the expression level of UNC-103 proteins and suppresses the phenotypic defects resulted from a gain-of-function mutation in the unc-103 gene. Furthermore, downregulation of PATL1 and PATL2, the human homologs of PAT1, decreases protein levels and the current density of native hERG channels in SH-SY5Y cells and human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Knockdown of PATL1 and PATL2 elongates the duration of action potentials in hiPSC-CMs, suggesting that PATL1 and PATL2 affect the function of hERG channels and hence electrophysiological characteristics in the human heart. Further studies found that PATL1 and PATL2 interact with TFIIE, a general transcription factor required for forming the RNA polymerase II preinitiation complex, and dual-luciferase reporter assays indicated that PATL1 and PATL2 facilitate the transcription of hERG mRNAs. Together, our study discovers that evolutionarily conserved DNA topoisomerase 2-associated proteins regulate the biogenesis of hERG channels via a transcriptional mechanism.

Progress on research and development in diabetes mellitus.

Diabetes mellitus is a kind of metabolic disease characterized by hyperglycemia resulting from insulin insufficiency and insulin resistance. It has become one of the major diseases threatening human health. In this paper, we analyze the current R&D status of diabetes from the aspects of papers, patents, drugs and industrial development. The results show that scientific outcomes are increasing steadily and the hot topics are diabetic complications and epidemiological research. In terms of technology development, large pharmaceutical companies, such as Janssen Pharmaceutical, Lilly pharmaceutical, Boehringer Ingelheim, are actively engaged in diagnosis, treatment and management of diabetes. By March 23 2022, 207 drugs have been launched and a large number of candidate drugs are in the pre-clinical and clinical stage. In terms of industrial development, the potential diabetes market is huge and the digital management of diabetes is developing rapidly. China has certain strength in diabetes research and development. In the future, measures should be taken to strengthen the transformation of research outcomes, and promote product development to meet China's huge needs of diabetes cares.

Overexpression of miR-3653 is Associated with HPV Infection and Serves as a Biomarker in Patients with Cervical Cancer.

Background: Human papillomavirus (HPV) is a major cause of cervical cancer (CC) occurrence. This study aimed to explore whether abnormal microRNA (miR)-3653 is associated with HPV infection and to investigate the clinical value of miR-3653 in the diagnosis and prognosis of CC. Methods: Tumor tissues and adjacent non-cancerous tissues were collected from 136 patients with CC. Cervical tissues from 101 patients with uterine fibroids were collected as controls. The expression of miR-3653 was measured by quantitative real-time PCR. The ability of miR-3653 to discriminate between HPV positive (HPV+) and HPV negative (HPV-) CC patients, and to discriminate patients from controls was assessed by receiver operating characteristic analysis. Kaplan-Meier curves and Log rank tests were used to evaluate the relationship of miR-3653 with survival of CC patient. Whether miR-3653 could function as a prognostic indicator was evaluated by univariate and multivariate Cox analyses. Results: miR-3653, highly expressed in CC tissues, was associated with HPV infection, tumor diameter, International Federation of Gynecology and Obstetrics (FIGO) stage and lymph node metastasis in CC patients. Additionally, miR-3653 was increased in HPV+ controls, CC patients and CC cells. Moreover, miR-3653 could screen HPV+ controls, screen HPV+ patients and screen CC patients. Furthermore, miR-3653 was associated with the survival of CC patients (log-rank P < 0.001) and could serve as an independent prognostic indicator for CC patients. Conclusion: miR-3653, increased in CC, is related to HPV infection and may serve as a diagnostic and prognostic biomarker for CC patients.

Radiomics Based on DCE-MRI Improved Diagnostic Performance Compared to BI-RADS Analysis in Identifying Sclerosing Adenosis of the Breast.

Purpose: Sclerosing adenosis (SA) is a benign lesion that could mimic breast carcinoma and be evaluated as malignancy by Breast Imaging-Reporting and Data System (BI-RADS) analysis. We aimed to construct and validate the performance of radiomic model based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) compared to BI-RADS analysis to identify SA. Methods: Sixty-seven patients with invasive ductal carcinoma (IDC) and 58 patients with SA were included in this retrospective study from two institutions. The 125 patients were divided into a training cohort (n= 88) from institution I and a validation cohort from institution II (n=37). Dynamic contrast-enhanced sequences including one pre-contrast and five dynamic post-contrast series were obtained for all cases with different 3T scanners. Single-phase enhancement, multi-phase enhancement, and dynamic radiomic features were extracted from DCE-MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression and cross-validation was performed to build the radscore of each single-phase enhancement and the final model combined multi-phase and dynamic radiomic features. The diagnostic performance of radiomics was evaluated by receiver operating characteristic (ROC) analysis and compared to the performance of BI-RADS analysis. The classification performance was tested using external validation. Results: In the training cohort, the AUCs of BI-RADS analysis were 0.71 (95%CI [0.60, 0.80]), 0.78 (95%CI [0.67, 0.86]), and 0.80 (95%CI [0.70, 0.88]), respectively. In single-phase analysis, the second enhanced phase radiomic signature achieved the highest AUC of 0.88 (95%CI [0.79, 0.94]) in distinguishing SA from IDC. Nine multi-phase radiomic features and two dynamic radiomic features showed the best predictive ability for final model building. The final model improved the AUC to 0.92 (95%CI [0.84, 0.97]), and showed statistically significant differences with BI-RADS analysis (p<0.05 for all). In the validation cohort, the AUC of the final model was 0.90 (95%CI [0.75, 0.97]), which was higher than all BI-RADS analyses and showed statistically significant differences with one of the BI-RADS analysis observers (p = 0.03). Conclusions: Radiomics based on DCE-MRI could show better diagnostic performance compared to BI-RADS analysis in differentiating SA from IDC, which may contribute to clinical diagnosis and treatment.

Pectin methyltransferase QUASIMODO2 functions in the formation of seed coat mucilage in Arabidopsis.

Pectin, cellulose, and hemicelluloses are major components of primary cell walls in plants. In addition to cell adhesion and expansion, pectin plays a central role in seed mucilage. Seed mucilage contains abundant pectic rhamnogalacturonan-I (RG-I) and lower amounts of homogalacturonan (HG), cellulose, and hemicelluloses. Previously, accumulated evidence has addressed the role of pectin RG-I in mucilage production and adherence. However, less is known about the function of pectin HG in seed coat mucilage formation. In this study, we analyzed a novel mutant, designated things fall apart2 (tfa2), which contains a mutation in HG methyltransferase QUASIMODO2 (QUA2). Etiolated tfa2 seedlings display short hypocotyls and adhesion defects similar to qua2 and tumorous shoot development2 (tsd2) alleles, and show seed mucilage defects. The diminished uronic acid content and methylesterification degree of HG in mutant seed mucilage indicate the role of HG in the formation of seed mucilage. Cellulosic rays in mutant mucilage are collapsed. The epidermal cells of seed coat in tfa2 and tsd2 display deformed columellae and reduced radial wall thickness. Under polyethylene glycol treatment, seeds from these three mutant alleles exhibit reduced germination rates. Together, these data emphasize the requirement of pectic HG biosynthesis for the synthesis of seed mucilage, and the functions of different pectin domains together with cellulose in regulating its formation, expansion, and release.

Dysregulated circulating miR-4429 serves as a novel non-invasive biomarker and is correlated with EGFR mutation in patients with non-small cell lung cancer.

This study aimed to investigate the correlation between microRNA (miR)-4429 and epidermal growth factor receptor (EGFR), the expression and clinical significance of miR-4429 in patients with non-small cell lung cancer (NSCLC), and the relationship between miR-4429 and EGFR mutation in NSCLC patients. Blood samples were collected from 122 NSCLC patients and 72 healthy volunteers. miR-4429 expression and EGFR mRNA expression were detected by real-time quantitative PCR. Correlation between miR-4429 and EGFR was evaluated by dual­luciferase reporter assay and the Pearson correlation analysis. The ability of serum miR­4429 to discriminate between NSCLC patients and healthy controls, and to discriminate between EGFR wild-type (EGFR-W) and EGFR mutant-type (EGFR-M) patients was assessed using receiver operating characteristic analysis. The relationship between miR-4429 and NSCLC patients' survival was identified by Kaplan-Meier survival curves and log-rank test. The prognostic value of miR-4429 in NSCLC patients was evaluated by Cox regression analysis. miR-4429 could directly bind to EGFR. Serum miR-4429, decreased in NSCLC patients, was negatively correlated with serum EGFR mRNA expression in NSCLC patients. Additionally, miR-4429 had a high diagnostic value for screening NSCLC patients from healthy controls, and was independently correlated with survival prognosis of NSCLC patients. Moreover, miR­4429 was decreased in EGFR-M patients, which had a certain screening ability for EGFR­M patients. Our findings indicate that miR-4429 is negatively correlated with EGFR in NSCLC, and may function as a diagnostic and prognostic biomarker for NSCLC patients. Additionally, miR-4429 is associated with EGFR mutation in NSCLC patients.

Progress on familial hypercholesterolemia.

Familial hypercholesterolemia (FH) is an autosomal inherited disease characterized by a significant increase in low density lipoprotein cholesterol (LDL-C), tendon xanthoma and premature coronary artery disease (PCAD). In this paper, we analyze the current research status of FH, summarize the reported mutation gene loci in Chinese FH patients and treatment for them, and elaborate the current status of patents and drug researches. The results show that scientific outcomes of FH are increasing with a good developmental trend and the most popular topics of FH study are pathogenesis, treatment of FH, and research on juvenile FH patients. In terms of patents, large pharmaceutical companies, such as Regeneron Pharmaceuticals Inc, AstraZeneca Plc, Merck & Co Inc, are actively engaged in FH detection, diagnosis and treatment. In addition, 12 drugs have been launched in the United States, Japan, Europe and other countries or regions, bringing hope to FH patients.

Exosomal microRNA-588 from M2 polarized macrophages contributes to cisplatin resistance of gastric cancer cells.

BACKGROUND: Gastric cancer is a prevalent malignant cancer with a high incidence and significantly affects the health of modern people globally. Cisplatin (DDP) is one of the most common and effective chemotherapies for patients with gastric cancer, but DDP resistance remains a severe clinical challenge. AIM: To explore the function of M2 polarized macrophages-derived exosomal microRNA (miR)-588 in the modulation of DDP resistance of gastric cancer cells. METHODS: M2 polarized macrophages were isolated and identified by specific markers using flow cytometry analysis. The exosomes from M2 macrophages were identified by transmission electron microscopy and related markers. The uptake of the PKH67-labelled M2 macrophages-derived exosomes was detected in SGC7901 cells. The function and mechanism of exosomal miR-588 from M2 macrophages in the modulation of DDP resistance of gastric cancer cells was analyzed by CCK-8 assay, apoptosis analysis, colony formation assay, Western blot analysis, qPCR analysis, and luciferase reporter assay in SGC7901 and SGC7901/DDP cells, and by tumorigenicity analysis in nude mice. RESULTS: M2 polarized macrophages were isolated from mouse bone marrow stimulated with interleukin (IL)-13 and IL-4. Co-cultivation of gastric cancer cells with M2 polarized macrophages promoted DDP resistance. M2 polarized macrophages-derived exosomes could transfer in gastric cancer cells to enhance DDP resistance. Exosomal miR-588 from M2 macrophages contributed to DDP resistance of gastric cancer cells. miR-588 promoted DDP-resistant gastric cancer cell growth in vivo. miR-588 was able to target cylindromatosis (CYLD) in gastric cancer cells. The depletion of CYLD reversed miR-588 inhibition-regulated cell proliferation and apoptosis of gastric cancer cells exposed to DDP. CONCLUSION: In conclusion, we uncovered that exosomal miR-588 from M2 macrophages contributes to DDP resistance of gastric cancer cells by partly targeting CYLD. miR-588 may be applied as a potential therapeutic target for the treatment of gastric cancer.

LINC01420 Serves as a Novel Prognostic Biomarker and Promotes Cell Proliferation, Migration, and Invasion by Suppressing miR-149-5p in Gastric Cancer.

Gastric cancer (GCa) is the most common human health-threatening malignancy, and its high incidence and poor prognosis. Previous studies have shown that long non-coding RNAs (lncRNAs) are aberrantly expressed in a variety of tumors and are involved in tumor progression. This study aimed to investigate the regulatory role of LINC01420 in GCa cell proliferation migration and invasion, and search for new prognostic biomarkers for GCa. The expression levels of LINC01420 and miR-149-5p in GCa cells were analyzed with reverse transcription-quantitative PCR. Kaplan Meier survival analysis and Cox regression were used to analyze the prognostic value. Luciferase reporter assay was used to detect the interaction between LINC01420 and miR-149-5p. The effects of LINC01420/miR-149-5p axis on GCa cell proliferation, migration and invasion were assessed by CCK-8 and Transwell assays. LINC01420 expression levels were significantly increased in tissues and cell lines of GCa. Kaplan Meier curve results showed that overexpression of LINC01420 predicted poor prognosis. Silencing LINC01420 could inhibit the proliferation migration and invasion of GCa cells. The luciferase reporter assay results indicated that miR-149-5p might be a target of LINC01420 and mediate the effects of LINC01420 on GCa cell proliferation and migration and invasion. In conclusion, this study demonstrates an important regulatory role of the LINC01420/miR-149-5p axis in GCa progression and it provides a novel and significant biomarker for GCa treatment and prognosis.

Current status and future perspectives of rare disease research.

Rare diseases refer to diseases with low incidence. Currently, there are over 8000 rare diseases in the world. Effective prevention and treatment of rare diseases is an important part of 'healthy China'. In this paper, status and drug development of rare diseases were reported. These results indicate that research on rare diseases is growing rapidly driven by technology and policy. The hotspots include the identification of gene mutations, the development of therapies, and the key points of technology include the development of drugs for rare diseases, the development of viral vectors for gene therapy, and the diagnosis and management system for rare diseases. In terms of drug development, 880 drugs have been launched by December 28, 2020, and a large number of drugs are in the pre-clinical stage. Generally, a new technology or drug is applicable to various diseases. In the future, with policy support and the development of emerging technologies such as gene editing, more and more rare diseases will be diagnosed and intervened early, even be cured, and the quality of life of patients is expected to be improved.

Acute liver failure with thrombotic microangiopathy due to sodium valproate toxicity: A case report.

BACKGROUND: Sodium valproate is widely used in the treatment of epilepsy in clinical practice. Most adverse reactions to sodium valproate are mild and reversible, while serious idiosyncratic side effects are becoming apparent, particularly hepatotoxicity. Herein, we report a case of fatal acute liver failure (ALF) with thrombotic microangiopathy (TMA) caused by treatment with sodium valproate in a patient following surgery for meningioma. CASE SUMMARY: A 42-year-old man who received antiepileptic treatment with sodium valproate after surgery for meningioma exhibited extreme fatigue, severe jaundice accompanied by oliguria, soy sauce-colored urine, and ecchymosis. His postoperative laboratory values indicated a rapid decreased platelet count and hemoglobin level, severe liver and kidney dysfunction, and disturbance of the coagulation system. He was diagnosed with drug-induced liver failure combined with TMA. After plasma exchange combined with hemoperfusion, pulse therapy with high-dose methylprednisolone, and blood transfusion, his liver function deteriorated, and finally, he died. CONCLUSION: ALF with TMA is a rare and fatal adverse reaction of sodium valproate which needs to be highly valued.

A target-oriented algorithm for maintaining serum calcium stability automatically in regional citrate anticoagulation.

BACKGROUND: Regional citrate anticoagulation (RCA) for renal replacement therapy is widely practiced in critically ill patients. However, concern exists regarding its labor-intensiveness for monitoring and the associated hypocalcemia. In this study, we provided an algorithm for prescribing RCA and evaluated its safety in patients. METHODS: During 18 hemofiltration treatments with calcium-free replacement solution, participants were randomized to receive algorithm-based or trial-and-error RCA protocol. The effluent volume, post-filter and in vivo ionized calcium (iCa), and calcium in the sera and effluents were periodically measured at an interval of 1 to 2 h. RESULTS: For patients received algorithm-based RCA protocol, no one had a serum iCa less than 0.9 mmol/L, and none needed calcium supplement adjustment to maintain serum calcium stability. For patients accepted trial-and-error protocol, all patients had a serum iCa below 0.9 mmol/L, their serum iCa and calcium levels fluctuated dramatically, and all patients need additional calcium supplement adjustment during RCA. None of the participants showed a post-filter iCa > 0.4 mmol/L. CONCLUSION: We provided a safe algorithm for calculating calcium supplementation doses that could maintain serum calcium stability without additional adjustment during RCA.