Astrocytic trans-Differentiation Completes a Multicellular Paracrine Feedback Loop Required for Medulloblastoma Tumor Growth.

The tumor microenvironment (TME) is critical for tumor progression. However, the establishment and function of the TME remain obscure because of its complex cellular composition. Using a mouse genetic system called mosaic analysis with double markers (MADMs), we delineated TME evolution at single-cell resolution in sonic hedgehog (SHH)-activated medulloblastomas that originate from unipotent granule neuron progenitors in the brain. First, we found that astrocytes within the TME (TuAstrocytes) were trans-differentiated from tumor granule neuron precursors (GNPs), which normally never differentiate into astrocytes. Second, we identified that TME-derived IGF1 promotes tumor progression. Third, we uncovered that insulin-like growth factor 1 (IGF1) is produced by tumor-associated microglia in response to interleukin-4 (IL-4) stimulation. Finally, we found that IL-4 is secreted by TuAstrocytes. Collectively, our studies reveal an evolutionary process that produces a multi-lateral network within the TME of medulloblastoma: a fraction of tumor cells trans-differentiate into TuAstrocytes, which, in turn, produce IL-4 that stimulates microglia to produce IGF1 to promote tumor progression.

PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data.

Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO, http://pcaontology.net/ and http://pcaontology.net/mobile/.

Mosaic analysis with double markers reveals tumor cell of origin in glioma.

Cancer cell of origin is difficult to identify by analyzing cells within terminal stage tumors, whose identity could be concealed by the acquired plasticity. Thus, an ideal approach to identify the cell of origin is to analyze proliferative abnormalities in distinct lineages prior to malignancy. Here, we use mosaic analysis with double markers (MADM) in mice to model gliomagenesis by initiating concurrent p53/Nf1 mutations sporadically in neural stem cells (NSCs). Surprisingly, MADM-based lineage tracing revealed significant aberrant growth prior to malignancy only in oligodendrocyte precursor cells (OPCs), but not in any other NSC-derived lineages or NSCs themselves. Upon tumor formation, phenotypic and transcriptome analyses of tumor cells revealed salient OPC features. Finally, introducing the same p53/Nf1 mutations directly into OPCs consistently led to gliomagenesis. Our findings suggest OPCs as the cell of origin in this model, even when initial mutations occur in NSCs, and highlight the importance of analyzing premalignant stages to identify the cancer cell of origin.

The CREB1/WNK1 axis promotes the tumorigenesis of ovarian cancer via regulating HIF-1.

The aim of this study was to explore the functions and molecular mechanisms of the WNK lysine deficient protein kinase 1 (WNK1) in the development of ovarian cancer. Firstly, loss- and gain-of-function assays were carried out and subsequently cell proliferation, apoptosis, invasion and migration were detected. Furthermore, WNK1 action on glucose uptake, lactate production and adenosine triphosphate (ATP) level were assessed. The roles of WNK1 on cisplatin resistance were explored using CCK-8, colony formation, and flow cytometry in vitro. Immunohistochemistry, Western blot and qRT-PCR were conducted to determine the protein and mRNA expression. Additionally, tumor growth in vivo was also monitored. We found that the overexpression of WNK1 predicted a bad prognosis of ovarian cancer patients. WNK1 enhanced the malignant behavior and facilitated glycolysis of ovarian cancer cells. Moreover, WNK1 increased cisplatin resistance in ovarian cancer cells. Mechanistically, we found that WNK1 expression was promoted by CREB1 at the transcriptional level. And CREB1 could facilitate ovarian cancer cells malignant behavior through target upregulating WNK1. Besides, we also showed that WNK1 facilitated the malignant behavior by accelerating HIF-1 expression. In xenograft tumor tissues, the downregulation of WNK1 significantly reduced HIF-1α expression. These data demonstrated that the CREB1/WNK1 axis could promote the tumorigenesis of ovarian cancer via accelerating HIF-1 expression, suggesting that the CREB1/WNK1 axis could be a potential target during the therapy of ovarian cancer.

zMADM (zebrafish mosaic analysis with double markers) for single-cell gene knockout and dual-lineage tracing.

As a vertebrate model organism, zebrafish has many unique advantages in developmental studies, regenerative biology, and disease modeling. However, tissue-specific gene knockout in zebrafish is challenging due to technical difficulties in making floxed alleles. Even when successful, tissue-level knockout can affect too many cells, making it difficult to distinguish cell autonomous from noncell autonomous gene function. Here, we present a genetic system termed zebrafish mosaic analysis with double markers (zMADM). Through Cre/loxP-mediated interchromosomal mitotic recombination of two reciprocally chimeric fluorescent genes, zMADM generates sporadic (<0.5%), GFP+ mutant cells along with RFP+ sibling wild-type cells, enabling phenotypic analysis at single-cell resolution. Using wild-type zMADM, we traced two sibling cells (GFP+ and RFP+) in real time during a dynamic developmental process. Using nf1 mutant zMADM, we demonstrated an overproliferation phenotype of nf1 mutant cells in comparison to wild-type sibling cells in the same zebrafish. The readiness of zMADM to produce sporadic mutant cells without the need to generate floxed alleles should fundamentally improve the throughput of genetic analysis in zebrafish; the lineage-tracing capability combined with phenotypic analysis at the single-cell level should lead to deep insights into developmental and disease mechanisms. Therefore, we are confident that zMADM will enable groundbreaking discoveries once broadly distributed in the field.

ViMRT: a text-mining tool and search engine for automated virus mutation recognition.

MOTIVATION: Virus mutation is one of the most important research issues which plays a critical role in disease progression and has prompted substantial scientific publications. Mutation extraction from published literature has become an increasingly important task, benefiting many downstream applications such as vaccine design and drug usage. However, most existing approaches have low performances in extracting virus mutation due to both lack of precise virus mutation information and their development based on human gene mutations. RESULTS: We developed ViMRT, a text-mining tool and search engine for automated virus mutation recognition using natural language processing. ViMRT mainly developed 8 optimized rules and 12 regular expressions based on a development dataset comprising 830 papers of 5 human severe disease-related viruses. It achieved higher performance than other tools in a test dataset (1662 papers, 99.17% in F1-score) and has been applied well to two other viruses, influenza virus and severe acute respiratory syndrome coronavirus-2 (212 papers, 96.99% in F1-score). These results indicate that ViMRT is a high-performance method for the extraction of virus mutation from the biomedical literature. Besides, we present a search engine for researchers to quickly find and accurately search virus mutation-related information including virus genes and related diseases. AVAILABILITY AND IMPLEMENTATION: ViMRT software is freely available at http://bmtongji.cn:1225/mutation/index.

A novel bispecific antibody drug conjugate targeting HER2 and HER3 with potent therapeutic efficacy against breast cancer.

Antibody drug conjugate (ADC) therapy has become one of the most promising approaches in cancer immunotherapy. Bispecific targeting could enhance the efficacy and safety of ADC by improving its specificity, affinity and internalization. In this study we constructed a HER2/HER3-targeting bispecific ADC (BsADC) and characterized its physiochemical properties, target specificity and internalization in vitro, and assessed its anti-tumor activities in breast cancer cell lines and in animal models. The HER2/HER3-targeting BsADC had a drug to antibody ratio (DAR) of 2.89, displayed a high selectivity against the target JIMT-1 breast cancer cells in vitro, as well as a slightly higher level of internalization than HER2- or HER3-monospecific ADCs. More importantly, the bispecific ADC potently inhibited the viability of MCF7, JIMT-1, BT474, BxPC-3 and SKOV-3 cancer cells in vitro. In JIMT-1 breast cancer xenograft mice, a single injection of bispecific ADC (3 mg/kg, i.v.) significantly inhibited the tumor growth with an efficacy comparable to that caused by combined injection of HER2 and HER3-monospecific ADCs (3 mg/kg for each). Our study demonstrates that the bispecific ADC concept can be applied to development of more potent new cancer therapeutics than the monospecific ADCs.

ViMIC: a database of human disease-related virus mutations, integration sites and cis-effects.

Molecular mechanisms of virus-related diseases involve multiple factors, including viral mutation accumulation and integration of a viral genome into the host DNA. With increasing attention being paid to virus-mediated pathogenesis and the development of many useful technologies to identify virus mutations (VMs) and viral integration sites (VISs), much research on these topics is available in PubMed. However, knowledge of VMs and VISs is widely scattered in numerous published papers which lack standardization, integration and curation. To address these challenges, we built a pilot database of human disease-related Virus Mutations, Integration sites and Cis-effects (ViMIC), which specializes in three features: virus mutation sites, viral integration sites and target genes. In total, the ViMIC provides information on 31 712 VMs entries, 105 624 VISs, 16 310 viral target genes and 1 110 015 virus sequences of eight viruses in 77 human diseases obtained from the public domain. Furthermore, in ViMIC users are allowed to explore the cis-effects of virus-host interactions by surveying 78 histone modifications, binding of 1358 transcription regulators and chromatin accessibility on these VISs. We believe ViMIC will become a valuable resource for the virus research community. The database is available at http://bmtongji.cn/ViMIC/index.php.

Performance of ChatGPT on Chinese national medical licensing examinations: a five-year examination evaluation study for physicians, pharmacists and nurses.

BACKGROUND: Large language models like ChatGPT have revolutionized the field of natural language processing with their capability to comprehend and generate textual content, showing great potential to play a role in medical education. This study aimed to quantitatively evaluate and comprehensively analysis the performance of ChatGPT on three types of national medical examinations in China, including National Medical Licensing Examination (NMLE), National Pharmacist Licensing Examination (NPLE), and National Nurse Licensing Examination (NNLE). METHODS: We collected questions from Chinese NMLE, NPLE and NNLE from year 2017 to 2021. In NMLE and NPLE, each exam consists of 4 units, while in NNLE, each exam consists of 2 units. The questions with figures, tables or chemical structure were manually identified and excluded by clinician. We applied direct instruction strategy via multiple prompts to force ChatGPT to generate the clear answer with the capability to distinguish between single-choice and multiple-choice questions. RESULTS: ChatGPT failed to pass the accuracy threshold of 0.6 in any of the three types of examinations over the five years. Specifically, in the NMLE, the highest recorded accuracy was 0.5467, which was attained in both 2018 and 2021. In the NPLE, the highest accuracy was 0.5599 in 2017. In the NNLE, the most impressive result was shown in 2017, with an accuracy of 0.5897, which is also the highest accuracy in our entire evaluation. ChatGPT's performance showed no significant difference in different units, but significant difference in different question types. ChatGPT performed well in a range of subject areas, including clinical epidemiology, human parasitology, and dermatology, as well as in various medical topics such as molecules, health management and prevention, diagnosis and screening. CONCLUSIONS: These results indicate ChatGPT failed the NMLE, NPLE and NNLE in China, spanning from year 2017 to 2021. but show great potential of large language models in medical education. In the future high-quality medical data will be required to improve the performance.

Highly Stable Amide-Functionalized Zirconium-Organic Frameworks: Synthesis, Structure, and Methane Storage Capacity.

With the development of crystalline porous materials toward methane storage, the stability issue of metal-organic framework (MOF) materials has caused great concern despite high working capacity. Considering the high stability of zirconium-based MOFs and effective functions of amide groups toward gas adsorption, herein, a series of UiO-66 type of Zr-MOFs, namely, Zr-fcu-H/F/CH3/OH, were successfully designed and synthesized by virtue of amide-functionalized dicarboxylate ligands bearing distinct side groups (i.e., -H, -F, -CH3, and -OH) and ZrCl4 in the presence of trifluoroacetic acid as the modulator. Single-crystal X-ray diffraction and topology analyses reveal that these compounds are archetypal fcu MOFs encompassing octahedral and tetrahedral cages, respectively. The N2 sorption isotherms and acid-base stability tests demonstrate that the materials possess not only relatively high surface areas, pore volumes, and appropriate pore sizes but also great hydrolytic stabilities ranging pH = 3-11. Furthermore, the volumetric methane storage working capacities of Zr-fcu-H, Zr-fcu-F, Zr-fcu-CH3, and Zr-fcu-OH at 298/273 K and 80 bar are 187/217, 175/193, 167/187, and 154/171 cm3 (STP) cm-3, respectively, which indicate that the zirconium-based crystalline porous materials are capable of storing relatively high amounts of methane.

Long-term passaging of pseudo-typed SARS-CoV-2 reveals the breadth of monoclonal and bispecific antibody cocktails.

The continuous emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants poses challenges to the effectiveness of neutralizing antibodies. Rational design of antibody cocktails is a realizable approach addressing viral immune evasion. However, evaluating the breadth of antibody cocktails is essential for understanding the development potential. Here, based on a replication competent vesicular stomatitis virus model that incorporates the spike of SARS-CoV-2 (VSV-SARS-CoV-2), we evaluated the breadth of a number of antibody cocktails consisting of monoclonal antibodies and bispecific antibodies by long-term passaging the virus in the presence of the cocktails. Results from over two-month passaging of the virus showed that 9E12 + 10D4 + 2G1 and 7B9-9D11 + 2G1 from these cocktails were highly resistant to random mutation, and there was no breakthrough after 30 rounds of passaging. As a control, antibody REGN10933 was broken through in the third passage. Next generation sequencing was performed and several critical mutations related to viral evasion were identified. These mutations caused a decrease in neutralization efficiency, but the reduced replication rate and ACE2 susceptibility of the mutant virus suggested that they might not have the potential to become epidemic strains. The 9E12 + 10D4 + 2G1 and 7B9-9D11 + 2G1 cocktails that picked from the VSV-SARS-CoV-2 system efficiently neutralized all current variants of concern and variants of interest including the most recent variants Delta and Omicron, as well as SARS-CoV-1. Our results highlight the feasibility of using the VSV-SARS-CoV-2 system to develop SARS-CoV-2 antibody cocktails and provide a reference for the clinical selection of therapeutic strategies to address the mutational escape of SARS-CoV-2.

Darinaparsin (ZIO-101) enhances the sensitivity of small-cell lung cancer to PARP inhibitors.

Small-cell lung cancer (SCLC) is an aggressive high-grade neuroendocrine carcinoma of the lung associated with early metastasis and an exceptionally poor prognosis. Little progress has been made in developing efficacious targeted therapy for this recalcitrant disease. Herein, we showed that H3.3, encoded by two genes (H3F3A and H3F3B), was prominently overexpressed in SCLC. Darinaparsin (ZIO-101), a derivative of arsenic trioxide, dose- and time-dependently inhibited the viability of SCLC cells in an H3.3-dependent manner. More importantly, ZIO-101 treatment resulted in substantial accumulation of H3.3 and PARP1 besides induction of G2/M cell cycle arrest and apoptosis in SCLC cells. Through integrative analysis of the RNA-seq data from Cancer Cell Line Encyclopedia dataset, JNCI and Genomics of Drug Sensitivity in Cancer 2 datasets, we found that H3F3A expression was negatively correlated with the IC50 values of PARP inhibitors (PARPi). Furthermore, co-targeting H3.3 and PARP1 by ZIO-101 and BMN673/olaparib achieved synergistic growth inhibition against SCLC in vitro and in vivo. In conclusion, it is feasible to target H3.3 by ZIO-101 to potentiate the response rate of PARPi in SCLC patients.

Eltrombopag modulates the phenotypic evolution and potential immunomodulatory roles of monocytes/macrophages in immune thrombocytopenia.

Primary immune thrombocytopenia (ITP) is an acquired autoimmune hemorrhagic disease. Loss of immune tolerance plays a crucial role in the pathogenesis of ITP. Monocytes and macrophages play an indispensable role in the pathophysiology of hematopoietic malignancies and have been implicated as key players in platelet destruction. Approximately 80% of adult patients with ITP exhibit corticosteroid treatment failure or become dependent, requiring novel therapy. Thrombopoietin (TPO) receptor agonists (TPO-RAs) have been used clinically to manage ITP effectively, however, little is known about the effect of TPO-RAs on monocyte and macrophage modulation in adult ITP. In this study, we investigated the phenotypic evolution and potential immunomodulatory roles of monocytes/macrophages in ITP patients receiving eltrombopag therapy. Results showed that the peripheral monocyte count positively correlated with IFN-γ/IL-4 ratio in ITP patients. Moreover, numerous phenotype-associated genes in ITP macrophages exhibited diverse responses, and ITP macrophages exhibited more M1-related characteristics. After eltrombopag therapy, the peripheral monocyte count and IFN-γ/IL-4 ratio significantly decreased in ITP patients. M1-related characteristics of ITP macrophages were partially reversed by eltrombopag. Therefore, this study revealed eltrombopag restored the monocyte dynamics and the associated Th1/Th2 imbalance, and partially reversed the M1-related characteristics of the ITP macrophages, which suggest the potential vital roles of TPO-RAs in regulating the monocyte/macrophage plasticity in ITP.

What is the context? Primary immune thrombocytopenia (ITP) is an acquired autoimmune hemorrhagic disease. Loss of immune tolerance plays a crucial role in the pathogenesis of ITP.Monocytes and macrophages play an indispensable role in the pathophysiology of hematopoietic malignancies and have been implicated as key players in platelet destruction.Approximately 80% of adult patients with ITP exhibit corticosteroid treatment failure or become dependent, requiring novel therapy. Thrombopoietin (TPO) receptor agonists (TPO-RAs) have been used clinically to manage ITP effectively, however, little is known about the effect of TPO-RAs on monocyte and macrophage modulation in ITP.What is new?In this study, we investigated the phenotypic evolution and potential immunomodula-tory roles of monocytes/macrophages in ITP patients receiving eltrombopag therapy.The expansion of peripheral monocytes positively correlated with IFN-γ/IL-4 ratio in ITP patients.ITP macrophages exhibited more M1-related characteristics.After eltrombopag therapy, the peripheral monocyte count and IFN-γ/IL-4 ratio significantly decreased in ITP patients.M1-related characteristics of ITP macrophages were partially reversed by eltrombopag.What is the impact?This study provides evidence that the potential vital roles of TPO-RAs in regulating the monocyte/macrophage plasticity in ITP.

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19.

BACKGROUND: Biomedical relation extraction (RE) is of great importance for researchers to conduct systematic biomedical studies. It not only helps knowledge mining, such as knowledge graphs and novel knowledge discovery, but also promotes translational applications, such as clinical diagnosis, decision-making, and precision medicine. However, the relations between biomedical entities are complex and diverse, and comprehensive biomedical RE is not yet well established. OBJECTIVE: We aimed to investigate and improve large-scale RE with diverse relation types and conduct usability studies with application scenarios to optimize biomedical text mining. METHODS: Data sets containing 125 relation types with different entity semantic levels were constructed to evaluate the impact of entity semantic information on RE, and performance analysis was conducted on different model architectures and domain models. This study also proposed a continued pretraining strategy and integrated models with scripts into a tool. Furthermore, this study applied RE to the COVID-19 corpus with article topics and application scenarios of clinical interest to assess and demonstrate its biological interpretability and usability. RESULTS: The performance analysis revealed that RE achieves the best performance when the detailed semantic type is provided. For a single model, PubMedBERT with continued pretraining performed the best, with an F1-score of 0.8998. Usability studies on COVID-19 demonstrated the interpretability and usability of RE, and a relation graph database was constructed, which was used to reveal existing and novel drug paths with edge explanations. The models (including pretrained and fine-tuned models), integrated tool (Docker), and generated data (including the COVID-19 relation graph database and drug paths) have been made publicly available to the biomedical text mining community and clinical researchers. CONCLUSIONS: This study provided a comprehensive analysis of RE with diverse relation types. Optimized RE models and tools for diverse relation types were developed, which can be widely used in biomedical text mining. Our usability studies provided a proof-of-concept demonstration of how large-scale RE can be leveraged to facilitate novel research.

Extracting laboratory test information from paper-based reports.

BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the digitization of information from these paper-based reports. However, the digitization of paper-based laboratory reports into a structured data format can be challenging due to their non-standard layouts, which includes various data types such as text, numeric values, reference ranges, and units. Therefore, it is crucial to develop a highly scalable and lightweight technique that can effectively identify and extract information from laboratory test reports and convert them into a structured data format for downstream tasks. METHODS: We developed an end-to-end Natural Language Processing (NLP)-based pipeline for extracting information from paper-based laboratory test reports. Our pipeline consists of two main modules: an optical character recognition (OCR) module and an information extraction (IE) module. The OCR module is applied to locate and identify text from scanned laboratory test reports using state-of-the-art OCR algorithms. The IE module is then used to extract meaningful information from the OCR results to form digitalized tables of the test reports. The IE module consists of five sub-modules, which are time detection, headline position, line normalization, Named Entity Recognition (NER) with a Conditional Random Fields (CRF)-based method, and step detection for multi-column. Finally, we evaluated the performance of the proposed pipeline on 153 laboratory test reports collected from Peking University First Hospital (PKU1). RESULTS: In the OCR module, we evaluate the accuracy of text detection and recognition results at three different levels and achieved an averaged accuracy of 0.93. In the IE module, we extracted four laboratory test entities, including test item name, test result, test unit, and reference value range. The overall F1 score is 0.86 on the 153 laboratory test reports collected from PKU1. With a single CPU, the average inference time of each report is only 0.78 s. CONCLUSION: In this study, we developed a practical lightweight pipeline to digitalize and extract information from paper-based laboratory test reports in diverse types and with different layouts that can be adopted in real clinical environments with the lowest possible computing resources requirements. The high evaluation performance on the real-world hospital dataset validated the feasibility of the proposed pipeline.

Application of CUBE-STIR MRI and high-frequency ultrasound in contralateral cervical 7 nerve transfer surgery.

OBJECTIVE: The objective of the study was to investigate the feasibility of CUBE-SITR MRI and high-frequency ultrasound for the structural imaging of the brachial plexus to exclude neoplastic brachial plexopathy or structural variation and measure the lengths of anterior and posterior divisions of the C7 nerve, providing guidelines for surgeons before contralateral cervical 7 nerve transfer. METHODS: A total of 30 patients with CNS and 20 with brachial plexus injury were enrolled in this retrospective study. All patients underwent brachial plexus CUBE-STIR MRI and high-frequency ultrasound, and the lengths of the anterior and posterior divisions of C7 nerve were measured before surgery. Precise length of anterior and posterior divisions of contralateral C7 nerve was measured during surgery. RESULTS: MRI-measured lengths of anterior and posterior divisions of C7 nerves were positively correlated with that measured during surgery (anterior division, r = 0.94, p < .01; posterior division, r = 0.92, p < .01). High agreement was found between MRI-measured and intra-surgery measured length of anterior and posterior divisions of C7 nerve by BLAD-ALTMAN analysis. Ultrasonography could feasibly image supraclavicular C7 nerve and recognize small variant branches derived from middle trunk of C7 nerve root, which could be dissected intra-operatively and confirmed by electromyography during the procedure of contralateral C7 nerve transfer. CONCLUSION: CUBE-STIR MRI had advantages for the imaging of the brachial plexus and measurement of the length of root-trunk-anterior/posterior divisions of C7 nerve. The clinical role of ultrasonography may be a simple way of evaluating general condition of C7 nerve and provide guidelines for contralateral C7 nerve transfer surgery.

Resampling-Detection-Network-Based Robust Image Watermarking against Scaling and Cutting.

Watermarking is an excellent solution to protect multimedia privacy but will be damaged by attacks such as noise adding, image filtering, compression, and especially scaling and cutting. In this paper, we propose a watermarking scheme to embed the watermark in the DWT-DCT composite transform coefficients, which is robust against normal image processing operations and geometric attacks. To make our scheme robust to scaling operations, a resampling detection network is trained to detect the scaling factor and then rescale the scaling-attacked image before watermark detection. To make our scheme robust to cutting operations, a template watermark is embedded in the Y channel to locate the cutting position. Experiments for various low- and high-resolution images reveal that our scheme has excellent performance in terms of imperceptibility and robustness.

Ultrasensitive and Visual Electrochemiluminescence Ratiometry Based on a Constant Resistor-Integrated Bipolar Electrode for MicroRNA Detection.

In this work, a new electrochemiluminescence (ECL) platform was constructed for detecting the prostate cancer marker microRNA-141 (miRNA-141) on a constant resistor-integrated closed bipolar electrode (BPE). It consisted of two reservoirs and a constant resistor, and both ends were connected to the anode of the driving electrode and the cathode of BPE. The cathode of BPE was modified with boron nitride quantum dots (BNQDs), and the anode reservoir was the [Ru(bpy)3](PF6)2/TPrA system. After introducing a certain amount of hairpin DNA 3 (H3) and ferrocene-labeled single-stranded DNA (Fc-ssDNA) on the surface of the BNQDs, the ECL emission signal of the BNQDs was difficult to be observed by the naked eye, while [Ru(bpy)3](PF6)2 emitted a strong and visible ECL signal. In the presence of the target, bipedal DNA assembled by catalytic hairpin assembly (CHA) took away the Fc-ssDNA and the ECL intensity of the BNQDs was enlarged, and as the concentration of miRNA-141 increased to the cutoff value, yellow-green light was visible by the naked eye. Meanwhile, the red emission signal of [Ru(bpy)3](PF6)2/TPrA became weakened. Thus, an ultrasensitive "color switch" ECL biosensor for detection of miRNA-141 was constructed and endowed with a wide linear range from 10-17 to 10-7 M and a detection limit of 10-17 M (S/N = 3). This study provides the potential for investigating portable devices in the detection of low-concentration nucleic acids.

[Evaluation of methodological and reporting quality of domestic clinical guidelines for hyperuricemia].

This study aims to evaluate the methodological and reporting quality of diagnosis and treatment guidelines for hyperuricemia as well as the expert consensuses and promote the understanding and application of the diagnosis and treatment guidelines for hyperuricemia. With "hyperuricemia" "guidelines" "consensus" "recommendations" as the key words in titles, the authors searched for the published clinical guidelines on hyperuricemia in Chinese against CNKI, Wanfang, VIP, Medlive and the official website of the industry association. The retrieval time limit was until May 31, 2021. The appraisal of guidelines for research and evaluation Ⅱ(AGREEⅡ) and the reporting items for practice guidelines in health care(RIGHT) were employed to evaluate the methodological quality and reporting quality of 14 guidelines/consensuses included. The average scores of the guidelines/consensuses were 80.85%(48.61%-98.61%) for the domain of scope and purpose, 34.52%(0-69.44%) for the domain of stakeholder involvement, 35.53%(6.25%-92.19%) for the domain of rigor of development, 55.85%(23.61%-86.11%) for the domain of clarity of presentation, 26.19%(0-76.04%) for the domain of applicability, and 21.42%(0-50.00%) for the domain of editorial independence. Nine guidelines/consensuses were of medium overall quality with grade B recommendation, and five guidelines/consensuses were of poor quality with grade C recommendation. The RIGHT classified the fourteen guidelines/consensuses into one of high reporting quality, three of medium reporting quality, and ten of low reporting quality. The results of this study indicate that the standardization and rigor of the methodological quality and the reporting quality of the clinical guidelines/consensuses for hyperuricemia in China remain to be strengthened.

Mosaic Analysis with Double Markers reveals IGF1R function in granule cell progenitors during cerebellar development.

During cerebellar development, granule cell progenitors (GCPs) proliferate exponentially for a fixed period, promoted by paracrine mitogenic factor Sonic Hedgehog (Shh) secreted from Purkinje cells (PCs). Dysregulation of Shh signaling leads to uncontrolled GCP proliferation and medulloblastoma. Serendipitously our previous work discovered insulin-like growth factor 1 (IGF1) as another key driver for medulloblastoma, which led to the current investigation into the role of IGF1 in GCPs during normal development. While the IGF1R conditional knockout model revealed GCP defects in anterior cerebellum, the posterior cerebellum was mostly intact, likely owing to incomplete excision of floxed alleles. To circumvent this hurdle, we enlisted a mouse genetic system called Mosaic Analysis of Double Markers (MADM), which sporadically generates homozygous null cells unequivocally labeled with GFP and their wildtype sibling cells labeled with RFP, enabling phenotypic analysis at single-cell resolution. Using MADM, we found that loss of IGF1R resulted in a 10-fold reduction of GCs in both anterior and posterior cerebellum; and that hindered S phase entry and increased cell cycle exit collectively led to this phenotype. Genetic interaction studies showed that IGF1 signaling prevents GCP cell cycle exit at least partially through suppressing the level of p27kip1, a negative regulator of cell cycle. Finally, we found that IGF1 is produced by PCs in a temporally regulated fashion: it is highly expressed early in development when GCPs proliferate exponentially, then gradually decline as GCPs commit to cell cycle exit. Taken together, our studies reveal IGF1 as a paracrine factor that positively regulates GCP cell cycle in cooperation with Shh, through dampening the level of p27 to prevent precocious cell cycle exit. Our work not only showcases the power of phenotypic analysis by the MADM system but also provides an excellent example of multi-factorial regulation of robust developmental programs.