Microarray-Based CD38 Peptide Probe Screening for Multiple Myeloma Imaging.

Assessing CD38 expression in vivo has become a significant element in multiple myeloma (MM) therapy, as it can be used to detect lesions and forecast the effectiveness of treatment. Accurate diagnosis requires a multifunctional, high-throughput probe screening platform to develop molecular probes for tumor-targeted multimodal imaging and treatment. Here, we investigated a microarray chip-based strategy for high-throughput screening of peptide probes for CD38. We obtained two new target peptides, CA-1 and CA-2, from a 105 peptide library with a dissociation constant (KD) of 10-7 M. The specificity and affinity of the target peptides were confirmed at the molecular and cellular levels. Peptide probes were labeled with indocyanine green (ICG) dye and 68Ga-DOTA, which were injected into a CD38-positive Ramos tumor-bearing mouse via its tail vein, and small animal fluorescence and positron emission tomography (PET) imaging showed that the peptide probes could show specific enrichment in the tumor tissue. Our study shows that a microchip-based screening of peptide probes can be used as a promising imaging tool for MM diagnosis.

Overexpression of Soybean GmWRI1a Stably Increases the Seed Oil Content in Soybean.

WRINKLED1 (WRI1), an APETALA2/ethylene-responsive-element-binding protein (AP2/EREBP) subfamily transcription factor, plays a crucial role in the transcriptional regulation of plant fatty acid biosynthesis. In this study, GmWRI1a was overexpressed in the soybean cultivar 'Dongnong 50' using Agrobacterium-mediated transformation to generate three transgenic lines with high seed oil contents. PCR and Southern blotting analysis showed that the T-DNA was inserted into the genome at precise insertion sites and was stably inherited by the progeny. Expression analysis using qRT-PCR and Western blotting indicated that GmWRI1a and bar driven by the CaMV 35S promoter were significantly upregulated in the transgenic plants at different developmental stages. Transcriptome sequencing results showed there were obvious differences in gene expression between transgenic line and transgenic receptor during seed developmental stages. KEGG analysis found that the differentially expressed genes mainly annotated to metabolic pathways, such as carbohydrated metabolism and lipid metabolism. A 2-year single-location field trial revealed that three transgenic lines overexpressing GmWRI1a (GmWRI1a-OE) showed a stable increase in seed oil content of 4.97-10.35%. Importantly, no significant effect on protein content and yield was observed. Overexpression of GmWRI1a changed the fatty acid composition by increasing the linoleic acid (C18:2) content and decreasing the palmitic acid (C16:0) content in the seed. The three GmWRI1a-OE lines showed no significant changes in agronomic traits. The results demonstrated that the three GmWRI1a overexpression lines exhibited consistent increases in seed oil content compared with that of the wild type and did not significantly affect the seed yield and agronomic traits. The genetic engineering of GmWRI1a will be an effective strategy for the improvement of seed oil content and value in soybean.

NEAWalk: Inferring missing social interactions via topological-temporal embeddings of social groups.

Real-world network data consisting of social interactions can be incomplete due to deliberately erased or unsuccessful data collection, which cause the misleading of social interaction analysis for many various time-aware applications. Naturally, the link prediction task has drawn much research interest to predict the missing edges in the incomplete social network. However, existing studies of link prediction cannot effectively capture the entangling topological and temporal dynamics already residing in the social network, thus cannot effectively reasoning the missing interactions in dynamic networks. In this paper, we propose the NEAWalk, a novel model to infer the missing social interaction based on topological-temporal features of patterns in the social group. NEAWalk samples the query-relevant walks containing both the historical and evolving information by focusing on the temporal constraint and designs a dual-view anonymization procedure for extracting both topological and temporal features from the collected walks to conduct the inference. Two-track experiments on several well-known network datasets demonstrate that the NEAWalk stably achieves superior performance against several state-of-the-art baseline methods.

Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori.

BACKGROUND: 20-hydroxyecdysone (20E) plays important roles in insect molting and metamorphosis. 20E-induced autophagy has been detected during the larval-pupal transition in different insects. In Bombyx mori, autophagy is induced by 20E in the larval fat body. Long non-coding RNAs (lncRNAs) function in various biological processes in many organisms, including insects. Many lncRNAs have been reported to be potential for autophagy occurrence in mammals, but it has not been investigated in insects. RESULTS: RNA libraries from the fat body of B. mori dissected at 2 and 6 h post-injection with 20E were constructed and sequenced, and comprehensive analysis of lncRNAs and mRNAs was performed. A total of 1035 lncRNAs were identified, including 905 lincRNAs and 130 antisense lncRNAs. Compared with mRNAs, lncRNAs had longer transcript length and fewer exons. 132 lncRNAs were found differentially expressed at 2 h post injection, compared with 64 lncRNAs at 6 h post injection. Thirty differentially expressed lncRNAs were common at 2 and 6 h post-injection, and were hypothesized to be associated with the 20E response. Target gene analysis predicted 6493 lncRNA-mRNA cis pairs and 42,797 lncRNA-mRNA trans pairs. The expression profiles of LNC_000560 were highly consistent with its potential target genes, Atg4B, and RNAi of LNC_000560 significantly decreased the expression of LNC_000560 and Atg4B. These results indicated that LNC_000560 was potentially involved in the 20E-induced autophagy of the fat body by regulating Atg4B. CONCLUSIONS: This study provides the genome-wide identification and functional characterization of lncRNAs associated with 20E-induced autophagy in the fat body of B. mori. LNC_000560 and its potential target gene were identified to be related to 20-regulated autophagy in B. mori. These results will be helpful for further studying the regulatory mechanisms of lncRNAs in autophagy and other biological processes in this insect model.

Public interest in Raynaud's phenomenon: A Google Trends analysis.

Raynaud's phenomenon is a common disorder affecting body extremities and other vascular beds. As infodemiological methods have developed, online search tools could be used to explore the public interest of the disease. The study aimed to determine the annual trend, seasonal pattern, and associated topics of Raynaud's phenomenon. Google Trends was used to collect the data. "Raynaud syndrome" was selected as the search term. Data on monthly relative search volume (RSV) were collected from four selected countries (United States, United Kingdom, Australia, and New Zealand) and globally. Related topics were obtained, and annual-related topics were also collected for analysis. The maximum RSV appeared in January 2019, and the minimum value was observed in August 2011. The peak for RSV occurred in winter, and the bottom appeared in summer. In top related topics, "Maurice Raynaud" was the most related. In rising related topics, disease manifestations and autoimmune connective diseases were highly concerned. For annual-related topics, associated diseases were attracting more attention over time. The population is interested in related diseases, pathogenesis, and treatment. There was a peak in winter for searching and supported the importance of season variation on the impact of Raynaud's phenomenon.

Cutaneous manifestations of the Coronavirus Disease 2019 (COVID-19): A brief review.

COVID-19, first appeared in December 2019 in Wuhan, China, has been spreading quickly throughout the world. We reviewed the evidence on cutaneous manifestations of COVID-19 based on PubMed database. The searching strategy was (COVID* or coronavirus*) and (dermatol* or skin* or cutaneous*). The publication time was limited to 2019 onward. After independent review by two authors, 14 studies with 228 confirmed cases were included in the analysis. A total of 60 patients developed skin rashes, and the age ranged from 8 to 84. Exanthematous eruptions potentially related to COVID-19 infection were highly variable and heterogeneous. Skin lesions mainly appeared erythematous, urticarial, and vesicular (chicken pox-like or varicelliform). Petechiae rash, livedo reticularis, and reactivation of oral HSV-1 were also observed in single cases. Newly reported eruptions like vascular lesions and peculiar (perniosis-like) skin lesions caused concern among dermatologists. Exanthems were widely distributed and were primarily located on the trunk. Associated symptoms, latency time, treatment, and prognosis were also carefully summarized. This study reviewed the recently published COVID-19 studies with skin manifestations, which may pave the way for further research.

Contributions of dermatologists to COVID-19 research: A brief systematic review.

Coronavirus disease 2019 (COVID-19) has been declared a pandemic. We conducted a systematic review to reveal the contribution of dermatologists in COVID-19 research. Two hundred and ninety-eight articles were included and classified into cutaneous manifestations of COVID-19, operating experience against COVID-19, mechanisms and treatment of COVID-19, disinfection and personal protective equipment (PPE)-related skin diseases, and other topics. The value of these articles and their impact on clinical impact were discussed and we hope that dermatologists can have a better understanding of these areas from this study.

Microarray Chip-Based High-Throughput Screening of Neurofilament Light Chain Self-Assembling Peptide for Noninvasive Monitoring of Alzheimer's Disease.

Alzheimer's disease (AD) starts decades before cognitive symptoms develop. Easily accessible and cost-effective biomarkers that accurately reflect AD pathology are essential for both monitoring and therapeutics of AD. Neurofilament light chain (NfL) levels in blood and cerebrospinal fluid are increased in AD more than a decade before the expected onset, thus providing one of the most promising blood biomarkers for monitoring of AD. The clinical practice of employing single-molecule array (Simoa) technology for routine use in patient care is limited by the high costs. Herein, we developed a microarray chip-based high-throughput screening method and screened an attractive self-assembling peptide targeting NfL. Through directly "imprinting" and further analyzing the sequences, morphology, and affinity of the identified self-assembling peptides, the Pep-NfL peptide nanosheet with high binding affinity toward NfL (KD = 1.39 × 10-9 mol/L), high specificity, and low cost was characterized. The superior binding ability of Pep-NfL was confirmed in AD mouse models and cell lines. In the clinical setting, the Pep-NfL peptide nanosheets hold great potential for discriminating between patients with AD (P < 0.001, n = 37), mild cognitive impairment (P < 0.05, n = 26), and control groups (n = 30). This work provides a high-throughput, high-sensitivity, and economical system for noninvasive tracking of AD to monitor neurodegeneration at different stages of disease. The obtained Pep-NfL peptide nanosheet may be useful for assessing dynamic changes in plasma NfL concentrations to evaluate disease-modifying therapies as a surrogate end point of neurodegeneration in clinical trials.

Slow Mohs micrographic surgery for nail apparatus melanoma in situ.

BACKGROUND: Nail apparatus melanoma is a malignant tumor with a high incidence in Chinese melanoma patients. Slow Mohs micrographic surgery is an emerging technique for treating nail apparatus melanoma in situ (NAMIS). OBJECTIVE: This study evaluated the efficacy and safety of slow Mohs micrographic surgery for treating NAMIS. METHODS: Patients were enrolled in this retrospective study and treated in a single center from October 1, 2016, to June 30, 2022. Each patient underwent standard slow Mohs micrographic surgery, and follow-up was regularly conducted at clinics. RESULTS: Ten patients were enrolled in the study. Two patients underwent one Mohs stage, seven underwent two Mohs stages, and one underwent seven Mohs stages. The resection margin ranged from 5 to 25 mm. No severe complications were reported in the treatment, and recurrence of NAMIS was not observed during the follow-up period. CONCLUSION: Slow Mohs micrographic surgery is a valuable surgical method to treat NAMIS that preserves digit function and can be well tolerated by patients.

UniSKGRep: A unified representation learning framework of social network and knowledge graph.

The human-oriented applications aim to exploit behaviors of people, which impose challenges on user modeling of integrating social network (SN) with knowledge graph (KG), and jointly analyzing two types of graph data. However, existing graph representation learning methods merely represent one of two graphs alone, and hence are unable to comprehensively consider features of both SN and KG with profiling the correlation between them, resulting in unsatisfied performance in downstream tasks. Considering the diverse gap of features and the difficulty of associating of the two graph data, we introduce a Unified Social Knowledge Graph Representation learning framework (UniSKGRep), with the goal to leverage the multi-view information inherent in the SN and KG for improving the downstream tasks of user modeling. To the best of our knowledge, we are the first to present a unified representation learning framework for SN and KG. Concretely, the SN and KG are organized as the Social Knowledge Graph (SKG), a unified representation of SN and KG. For the representation learning of SKG, first, two separate encoders in the Intra-graph model capture both the social-view and knowledge-view in two embedding spaces, respectively. Then the Inter-graph model is learned to associate the two separate spaces via bridging the semantics of overlapping node pairs. In addition, the overlapping node enhancement module is designed to effectively align two spaces with the consideration of a relatively small number of overlapping nodes. The two spaces are gradually unified by continuously iterating the joint training procedure. Extensive experiments on two real-world SKG datasets have proved the effectiveness of UniSKGRep in yielding general and substantial performance improvement compared with the strong baselines in various downstream tasks.

Outcomes and prognosis of non-small cell lung cancer patients who underwent curable surgery: a protocol for a real-world, retrospective, population-based and nationwide Chinese National Lung Cancer Cohort (CNLCC) study.

INTRODUCTION: Surgery is one of the main approaches for the comprehensive treatment of early and locally advanced non-small cell lung cancer (NSCLC). This study conducts a nationwide multicentre study to explore factors that could influence the outcomes of patients with I-IIIA NSCLC who underwent curable surgery in real-world scenarios. METHODS AND ANALYSIS: All patients diagnosed with NSCLC between January 2013 and December 2020 will be identified from 30 large public medical services centres in mainland China. The algorithm of natural language processing and artificial intelligence techniques were used to extract data from electronic health records of enrolled patients who fulfil the inclusion criteria. Six categories of parameters are collected and stored from the electronic records, then the parameters will be structured as a high-quality structured case report form. The code book will be compiled and each parameter will be classified and designated a code. In addition, the study retrieves the survival status and causes of death of patients from the Chinese Centre for Disease Control and Prevention. The primary endpoints are overall survival and the secondary endpoint is disease-free survival. Finally, an online platform is formed for data queries and the original records will be stored as secure electronic documents. ETHICS AND DISSEMINATION: The study has been approved by the Ethical Committee of the Chinese Academy of Medical Sciences. Study findings will be disseminated via presentations at conferences and publications in open-access journals. This study has been registered in the Chinese Trial Register (ChiCTR2100052773) on 11 May 2021, http://www.chictr.org.cn/showproj.aspx?proj=136659. TRIAL REGISTRATION NUMBER: ChiCTR2100052773.

Risk factors for mortality in patients with anti-MDA5 antibody-positive dermatomyositis: A meta-analysis and systematic review.

OBJECTIVES: To determine the prognostic factors of dermatomyositis with anti-melanoma differentiation-associated gene 5 (MDA5) antibody, a rare disease and often complicated by life-threatening, rapidly progressive interstitial lung disease. METHODS: Herein, we searched the Medline, Embase, and Cochrane Library databases and extracted studies published before August 23, 2022. Pooled analysis of hazard ratios (HRs) or odds ratios was used to identify prognostic factors for mortality among patients with anti-MDA5 antibody-positive dermatomyositis (MDA5+ DM). RESULTS: Twenty-nine cohorts with 2,645 patients were included in this meta-analysis. Factors related to poor prognosis included old age (HR 1.54, 95% confidence interval (CI) 1.41-1.69, p < 0.01), male sex (HR 2.07, 95% CI 1.34-3.18, p < 0.01), rapidly progressive interstitial lung disease (RP-ILD) (HR 9.34, 95% CI 6.39-13.6, p < 0.01), high levels of ferritin (HR 1.05, 95% CI 1.01-1.08, p < 0.01), C-reactive protein (CRP) (HR 1.12, 95% CI 1.06-1.19, p < 0.01), creatine kinase (HR 1.05, 95% CI 1.03-1.07, p < 0.01), and lactate dehydrogenase (LDH) (HR 1.27, 95% CI 1.12-1.45, p < 0.01), whereas oxygen index (HR 0.990, 95% CI 0.988-0.992, p < 0.01), partial pressure of oxygen (HR 0.933, 95% CI 0.906-0.961, p < 0.01), forced vital capacity (HR 0.962, 95% CI 0.928-0.998, p = 0.038), and lymphocyte count (HR 0.421, 95% CI 0.282-0.629, p < 0.01) were associated with better outcomes. CONCLUSIONS: Old age, male sex, hypoxemia, low forced vital capacity, lymphocytopenia, and high levels of ferritin, CRP, creatine kinase, and LDH are risk factors for mortality in patients with MDA5+ DM. However, a cautious interpretation of these results and further quality investigation are warranted.

[Stoichiometric Imbalance of Abandoned Grassland Under Precipitation Changes Regulate Soil Respiration].

As a key factor of global climate change, precipitation can affect soil respiration. Microorganisms are the key drivers of soil respiration, but the relationship between microbial stoichiometry and respiration in vulnerable habitat areas under different precipitation gradients is unclear. In this study, five precipitation gradients were simulated on a typical abandoned grassland in the loess hilly region. Soil respiration, nutrients, microbial biomass, and extracellular enzymes were measured, and the microbial measurement characteristics were calculated. The results showed that:①soil respiration (SR) increased significantly under rainfed treatment but decreased significantly under D50 treatment. ②Precipitation changes affected the stoichiometric imbalance, and the N:P imbalance of the active resource pool presented a u-shaped trend, whereas the C:P imbalance changed significantly only in 2019, with a trend of P50>P25>CK>D25>D50. Additionally, the stoichiometric imbalance was caused by the soil stoichiometry. In 2019, the C:P imbalance of the active resource pool showed a trend of P50>P25>CK>D25>D50, whereas the N:P imbalance of the active resource pool showed a u-shaped trend, and the stoichiometric imbalance was caused by soil stoichiometry changes. ③Soil ß-1,4-glucosidase (BG) enzyme decreased with increasing precipitation, and the sum activities of ß-1,4-N-acetylglucosaminidase (NAG) and leucine aminopeptidase (LAP) significantly decreased during two years of rainfall reduction treatment. The activity of alkaline phosphatase (ALP) significantly increased under increasing rainfall but significantly decreased under decreasing rainfall. BG:(NAG+LAP) and BG:ALP were significantly decreased under increasing precipitation conditions but significantly increased under decreasing precipitation conditions. ④The partial least squares path model (PLS-PM) showed that precipitation had an impact on soil respiration through influencing C:P stoichiometric imbalance and soil enzyme stoichiometric ratio. These results highlight the importance of stoichiometric imbalances in regulating soil respiration and may help predict how they are caused by precipitation change control carbon cycling and nutrient flow in terrestrial ecosystems.

Case report: Checkpoint inhibitor pneumonitis with positive anti-melanoma differentiation-associated gene 5 antibodies in a patient with lung cancer.

With the widespread use of immune checkpoint inhibitors to treat various cancers, pulmonary toxicity has become a topic of increasing concern. Anti-melanoma differentiation-associated gene 5 (anti-MDA5) antibodies are strongly associated with rapidly progressive interstitial lung disease (RP-ILD) in patients with clinically amyopathic dermatomyositis. However, anti-MDA5 antibody expression has not been reported in patients with immune-related adverse events. We present the case of a 74-year-old man with lung adenocarcinoma who developed RP-ILD after treatment with immune checkpoint inhibitors. Further investigation revealed multiple autoantibodies, including anti-MDA5 antibodies. He initially responded to systemic glucocorticoids, immunosuppressants, and tocilizumab but eventually died from worsening pneumomediastinum. This case is the first one to suggest that checkpoint inhibitor pneumonitis can present as RP-ILD with positive anti-MDA5 antibodies, which may be predictive of a poor prognosis.

Identification of blood metabolites linked to the risk of cholelithiasis: a comprehensive Mendelian randomization study.

BACKGROUND AND AIMS: Observational and Mendelian randomization (MR) studies have identified several modifiable risk factors of cholelithiasis. However, there is limited evidence about the causal effect of blood metabolites on the cholelithiasis risk. METHODS: To have a comprehensive understanding to causal relations between blood metabolites and cholelithiasis, for the primary discovery, we applied two MR methods to explore the associations between 249 circulating metabolites and cholelithiasis. For secondary validations, we replicated the examinations using another metabolic dataset with 123 metabolites. The summary statistics of cholelithiasis were retrieved from FinnGen Consortium Release 5 and UK Biobank. Inverse-variance weighted, weight median and MR-egger methods were used for calculating causal estimates. Furthermore, Bayesian model averaging MR (MR-BMA) method was employed to detect the dominant causal metabolic traits with adjustment for pleiotropy effects. RESULTS: In the primary analysis, sphingomyelin showed consistent protective causal associations with cholelithiasis; while plasma cholesterol-associated traits showed generally inverse correlation with cholelithiasis risk. Notably, large numbers of traits within the (un)saturated fatty acid category demonstrated significant causal effects. Secondary analyses demonstrated similar results, with traits related to the levels of bisallylic groups in fatty acids showing protective effects. Lastly, MR-BMA analyses discovered that the degree of unsaturation plays a predominant role in reducing the risk of cholelithiasis. CONCLUSION: Our MR study provides a complete atlas of associations between plasma metabolites on cholelithiasis risk. It highlighted that genetically predicted sphingomyelin and degree of unsaturation of fatty acid were causally associated with the reduced risk of cholelithiasis.

Tofacitinib for extraintestinal manifestations of inflammatory bowel disease: A literature review.

BACKGROUND AND AIMS: Extraintestinal manifestations (EIMs) are commonly seen in patients with inflammatory bowel disease (IBD); management of EIMs is difficult and increases the primary disease burden. Recently, tofacitinib (TOF) was reported to be a promising option for treatment of EIMs. We aimed to review published articles and report experience to date. METHODS: The PubMed, Cochrane Library, and Web of Science databases were searched to identify eligible studies. The inclusion criteria were as follows: confirmed diagnosis of IBD; definitive EIMs; treatment with TOF; human study and published in English. The Newcastle-Ottawa Scale score and Cochrane Collaboration's tool for assessing risk of bias were used to determine the quality of the selected studies. RESULTS: Twenty-three studies met the inclusion criteria and were included. For nonrandomized studies, 16 were low quality, 5 were moderate quality, and 1 was high quality. For the one randomized controlled trial, the overall bias risk was low. The most concerning EIMs were dermatological manifestations, rheumatologic manifestations, and others, such as primary sclerosing cholangitis, autoimmune hepatitis, uveitis, and Takayasu arteritis. After administering doses of 5-20 mg/d TOF, the included studies reported varying degrees of clinical remission for both the primary disease and EIMs, except for musculoskeletal EIMs. CONCLUSION: TOF might benefit EIMs in IBD, especially ulcerative colitis, and elevated dosages and longer treatment times may increase its effectiveness. Manifestation-specific results and large prospective studies are highly warranted.

Artificial intelligence in melanoma: A systematic review.

BACKGROUND: Melanoma accounts for the majority of skin cancer deaths. Artificial intelligence has been applied in many types of cancers, and in melanoma in recent years. However, no systematic review summarized the application of artificial intelligence in melanoma. AIMS: This study aims to systematically review previously published articles to explore the application of artificial intelligence in melanoma. MATERIALS & METHODS: PubMed database was used to search the eligible publications on August 1, 2020. The query term was "artificial intelligence" and "melanoma." RESULTS: A total of 51 articles were included in this review. Artificial intelligence technique is mainly used in the evaluation of dermoscopic images, other image segmentation and processing, and artificial intelligence diagnosis system. DISCUSSION: Artificial intelligence is also applied in metastasis prediction, drug response prediction, and prognosis of melanoma. Besides, patients' perspectives of artificial intelligence and collaboration of human and artificial intelligence in melanoma also attracted attention. The query term might not include all articles, and we could not examine the algorithms that were built without publication. CONCLUSION: The performance of artificial intelligence in melanoma is satisfactory and the future for potential applications is enormous.

CaSee: A lightning transfer-learning model directly used to discriminate cancer/normal cells from scRNA-seq.

Single-cell RNA sequencing (scRNA-seq) is one of the most efficient technologies for human tumor research. However, data analysis is still faced with technical challenges, especially the difficulty in efficiently and accurately discriminating cancer/normal cells in the scRNA-seq expression matrix. If we can address these challenges, we can have a deeper understanding of the intratumoral and intertumoral heterogeneity. In this study, we developed a cancer/normal cell discrimination pipeline called pan-Cancer Seeker (CaSee) devoted to scRNA-seq expression matrix, which is based on the traditional high-quality pan-cancer bulk sequencing data using transfer learning. CaSee is the first tool directly used to discriminate cancer/normal cells in the scRNA-seq expression matrix, with much wider application fields and higher efficiency than copy number variation (CNV) method which requires corresponding reference cells. CaSee is user-friendly and can adapt to a variety of data sources, including but not limited to scRNA tissue sequencing data, scRNA cell line sequencing data, scRNA xenograft cell sequencing data and scRNA circulating tumor cell sequencing data. It is compatible with mainstream sequencing technology platforms, 10× Genomics Chromium, Smart-seq2, and Microwell-seq. Here, CaSee pipeline exhibited excellent performance in the multicenter data evaluation of 11 retrospective cohorts and one independent dataset, with an average discrimination accuracy of 96.69%. In general, the development of a deep-learning based, pan-cancer cell discrimination model, CaSee, to distinguish cancer cells from normal cells will be compelling to researchers working in the genomics, cancer, and single-cell fields.

Murine models of rosacea: a review.

Rosacea is a chronic inflammatory disease characterized by facial flushing, erythema, telangiectasia, papules, and pustules. Its pathogenesis has not been fully understood. In 2017, the global ROSacea COnsensus (ROSCO) panel updated the diagnosis, classification, and assessment of rosacea. Phenotype-based treatments and long-term managements have also been recommended. Murine models are a powerful tool in unveiling and dissecting the mechanisms of human diseases. Here, we summarized murine models of rosacea developed or used in previous research, including LL-37 intradermal injection model, KLK-5-induced inflammation model, croton oil inflammation model, 12-O-Tetradecanoylphorbol-13-acetate inflammation model, arachidonic acid inflammation model, RTX-induced vasodilation model, and UVB-induced model. LL-37 injection model has become the most intensively used model in rosacea research. Each model could show the pathophysiological and clinical features of rosacea to some extent. However, no model can show the full picture of the characteristics of rosacea. Improving existed murine models, developing new murine models, and applying them to pathogenesis and treatment research on rosacea are highly warranted in the future.

Co-delivery of phagocytosis checkpoint and STING agonist by a Trojan horse nanocapsule for orthotopic glioma immunotherapy.

Rationale: Cancer immunotherapy has demonstrated significant antitumor activity in a variety of tumors; however, extensive infiltration of immunosuppressive tumor-associated macrophages (TAMs) in the glioblastoma (GBM) tumor microenvironment (TME) and the existence of the blood-brain barrier (BBB) might lead to failure of the checkpoint blockade therapy. Methods: Herein, we have developed a smart "Trojan horse" BBB-permeable nanocapsule termed "NAcp@CD47" to deliver anti-CD47 antibodies and stimulator of interferon genes (STING) agonists into GBM tissues in a stealth-like manner to reshaped the immune microenvironment by switching the phenotype of microglia and macrophages. Results: Both in vitro and in vivo studies demonstrate that NAcp@CD47 could effectively penetrate the BBB, increase the polarization of M1-phenotype TAMs, help reduce tumor immunosuppression, and inhibit the orthotopic GBM growth by phagocytosis of macrophages and microglia. Conclusions: Our findings indicate that the well-designed NAcp@CD47 not only enhances the phagocytosis of cancer cells but also efficiently enhance antitumor immunogenicity and reverses immune suppression to convert uninflamed "cold" tumors into "hot" tumors.