A vaccine targeting the RBD of the S protein of SARS-CoV-2 induces protective immunity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a respiratory disease called coronavirus disease 2019 (COVID-19), the spread of which has led to a pandemic. An effective preventive vaccine against this virus is urgently needed. As an essential step during infection, SARS-CoV-2 uses the receptor-binding domain (RBD) of the spike protein to engage with the receptor angiotensin-converting enzyme 2 (ACE2) on host cells1,2. Here we show that a recombinant vaccine that comprises residues 319-545 of the RBD of the spike protein induces a potent functional antibody response in immunized mice, rabbits and non-human primates (Macaca mulatta) as early as 7 or 14 days after the injection of a single vaccine dose. The sera from the immunized animals blocked the binding of the RBD to ACE2, which is expressed on the cell surface, and neutralized infection with a SARS-CoV-2 pseudovirus and live SARS-CoV-2 in vitro. Notably, vaccination also provided protection in non-human primates to an in vivo challenge with SARS-CoV-2. We found increased levels of RBD-specific antibodies in the sera of patients with COVID-19. We show that several immune pathways and CD4 T lymphocytes are involved in the induction of the vaccine antibody response. Our findings highlight the importance of the RBD domain in the design of SARS-CoV-2 vaccines and provide a rationale for the development of a protective vaccine through the induction of antibodies against the RBD domain.

Serum matrix metalloproteinase-7 for discriminating biliary atresia: a diagnostic accuracy and validation study.

BACKGROUND: Prompt and precise differential diagnosis of biliary atresia (BA) among cholestatic patients is of great importance. Matrix metalloproteinase-7 (MMP-7) holds great promise as a diagnostic marker for BA. This study aimed to investigate the accuracy of age-specific serum MMP-7 for discriminating BA from other cholestatic pediatric patients. METHODS: This was a single center diagnostic accuracy and validation study including both retrospective and prospective cohorts. Serum MMP-7 concentrations were measured using an ELISA kit, the trajectory of which with age was investigated in a healthy infants cohort aged 0 to 365 days without hepatobiliary diseases (n = 284). Clinical BA diagnosis was based on intraoperative cholangiography and subsequent histological examinations. The diagnostic accuracy of age-specific cutoffs of serum MMP-7 were assessed in a retrospective cohort of cholestatic patients (n = 318, with 172 BA) and validated in a prospective cohort (n = 687, including 395 BA). RESULTS: The MMP-7 concentration declines non-linearly with age, showing higher levels in healthy neonates as well as higher cutoff value in neonatal cholestasis. The area under the ROC curve (AUROC) was 0.967 (95% confidence interval [CI]: 0.946-0.988) for the retrospective cohort, and the cutoff of 18 ng/mL yielded 93.0% (95%CI: 88.1-96.3%), 93.8% (95%CI: 88.6-97.1%), 94.7% (95%CI: 90.1-97.5%), and 91.9% (95%CI: 86.4-95.8%) for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), respectively. The performance of MMP-7 was successfully validated in the larger prospective cohort, resulting in a diagnostic sensitivity of 95.9% (379/395; 95% CI: 93.5-97.7%), a specificity of 87.3% (255/292; 95% CI: 83.0-90.9%), a PPV of 91.1% (379/416; 95% CI: 87.9-93.7%), and a NPV of 94.1% (255/271; 95% CI: 90.6-96.6%), respectively. Besides, higher cutoff value of 28.1 ng/mL achieved the best sensitivity, specificity, PPV, and NPV for infants aged 0-30 days, which was 86.4% (95% CI: 75.0-94.0%), 95.5% (95% CI: 77.2-99.9%), 98.1% (95% CI: 89.7-100%), and 72.4% (95% CI: 52.8-87.3%), respectively. CONCLUSIONS: The serum MMP-7 is accurate and reliable in differentiating BA from non-BA cholestasis, showing its potential application in the diagnostic algorithm for BA and significant role in the future research regarding pathogenesis of BA.

A perfusion host-microbe bioreactor (HMB) system that captures dynamic interactions of secreted metabolites between epithelial cells cocultured with a human gut anaerobe.

The human microbiota impacts a variety of diseases and responses to therapeutics. Due to a lack of robust in vitro models, detailed mechanistic explanations of host-microbiota interactions cannot often be recapitulated. We describe the design and development of a novel, versatile and modular in vitro system that enables indirect coculture of human epithelial cells with anaerobic bacteria for the characterization of host-microbe secreted metabolite interactions. This system was designed to compartmentalize anaerobes and human cells in separate chambers conducive to each organism's requisite cell growth conditions. Using perfusion, fluidic mixing, and automated sample collection, the cells continuously received fresh media, while in contact with their corresponding compartments conditioned supernatant. Supernatants from each chamber were collected in a cell-free time-resolved fashion. The system sustained low oxygen conditions in the anaerobic chamber, while also supporting the growth of a representative anaerobe (Bacteroides thetaiotaomicron) and a human colonic epithelial cell line (Caco-2) in the aerobic chamber. Caco-2 global gene expression changes in response to coculture with B. thetaiotaomicron was characterized using RNA sequencing. Extensive, targeted metabolomics analysis of over 150 central carbon metabolites was performed on the serially collected supernatants. We observed broad metabolite changes in host-microbe coculture, compared to respective mono-culture controls. These effects were dependent both on sampling time and the compartment probed (apical vs. basolateral). Coculturing resulted in the depletion of several important metabolites, including guanine, uridine 5'-monophosphate, asparagine, and thiamine. Additionally, while Caco-2 cells cultured alone predominantly affected the basolateral metabolite milieu, increased abundance of 2,3-dihydroxyisovalerate and thymine on the basolateral side, occurred when the cells were cocultured with B. thetaiotaomicron. Thus, our system can capture the dynamic, competitive and cooperative processes between host cells and gut microbes.

Learning from vertically distributed data across multiple sites: An efficient privacy-preserving algorithm for Cox proportional hazards model with variable selection.

OBJECTIVE: To develop a lossless distributed algorithm for regularized Cox proportional hazards model with variable selection to support federated learning for vertically distributed data. METHODS: We propose a novel distributed algorithm for fitting regularized Cox proportional hazards model when data sharing among different data providers is restricted. Based on cyclical coordinate descent, the proposed algorithm computes intermediary statistics by each site and then exchanges them to update the model parameters in other sites without accessing individual patient-level data. We evaluate the performance of the proposed algorithm with (1) a simulation study and (2) a real-world data analysis predicting the risk of Alzheimer's dementia from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). Moreover, we compared the performance of our method with existing privacy-preserving models. RESULTS: Our algorithm achieves privacy-preserving variable selection for time-to-event data in the vertically distributed setting, without degradation of accuracy compared with a centralized approach. Simulation demonstrates that our algorithm is highly efficient in analyzing high-dimensional datasets. Real-world data analysis reveals that our distributed Cox model yields higher accuracy in predicting the risk of Alzheimer's dementia than the conventional Cox model built by each data provider without data sharing. Moreover, our algorithm is computationally more efficient compared with existing privacy-preserving Cox models with or without regularization term. CONCLUSION: The proposed algorithm is lossless, privacy-preserving and highly efficient to fit regularized Cox model for vertically distributed data. It provides a suitable and convenient approach for modeling time-to-event data in a distributed manner.

Differences in clinical characteristics of early-onset and late-onset severe acute respiratory syndrome coronavirus 2 infections in neonates.

Differences in clinical characteristics of early-onset and late-onset severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in neonates remain unclear. This study aimed to determine whether there are differences in the main clinical, radiological, and laboratory features of early-onset and late-onset SARS-CoV-2 infections in neonates. This single-center, prospective cohort study enrolled neonates with SARS-CoV-2 infection from December 7, 2022, to January 3, 2023, and evaluated their clinical characteristics during hospitalization. All neonates (N = 58) infected with SARS-CoV-2 within 28 days of birth who were admitted to the neonatal intensive care unit of Taizhou Hospital were included. These neonates were classified into the early-onset (diagnosed within 7 days of birth) and late-onset (diagnosed more than 7 days after birth) groups. The symptoms, treatment, and prognosis of SARS-CoV-2 infection were the main study outcomes. The incidence of hospitalization attributable to SARS-CoV-2 infection was 10.6% (58 of 546 neonates) in Linhai. Sixteen (28%) of the 58 SARS-CoV-2 infections were early-onset cases, and 42 (72%) were late-onset cases. The common symptoms among the late-onset group were fever (p < 0.001) and cough (p < 0.001). Neonates with late-onset SARS-CoV-2 infection (p < 0.001) were significantly more likely to develop pneumonia.  Conclusion: The clinical symptoms and rates of pneumonia caused by SARS-CoV-2 infection in neonates differed between the early-onset and late-onset groups. Different clinical management is necessary for neonates with early-onset and late-onset SARS-CoV-2 infections. What is Known: • Neonates are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). • Differences in clinical characteristics of early-onset and late-onset SARS-CoV-2 infections in neonates remain unclear. What is New: • Fever and cough were the most common symptoms among neonates with late-onset infection. • Neonates with late-onset SARS-CoV-2 infection were more likely to develop pneumonia.

Meta-analysis of the Efficacy and Safety of Pembrolizumab in the Treatment of Advanced Gastric Cancer and Gastroesophageal Junction Cancer.

●Introduction: Pembrolizumab have been approved for the first-line treatment of patients with advanced gastric cancer (GC) and gastroesophageal junction (GEJ) cancer. However, the results of several clinical trials are not entirely consistent, and the dominant population of first-line immunotherapy for advanced GC/GEJ still needs to be precisely determined. ●Purpose: The aim of this meta-analysis was to assess the efficacy and safety of pembrolizumab in the treatment of advanced GC/GEJ. ●Methods: We conducted computerized searches across multiple databases, including PubMed, Cochrane Library, Web of Science, and Embase. We established the inclusion criteria to comprise randomized clinical trials examining the efficacy of pembrolizumab in late-stage GC/GCJ cancer. We conducted a meta-analysis of outcome measures using STATA 14.0 software. ●Results: A total of six studies involving 1,448 cases were included in this analysis. The results of the meta-analysis indicate that, when compared to chemotherapy, patients in the pembrolizumab group experienced a significant reduction in the risk of mortality in terms of overall survival (OS) (HR=0.72, 95% CI: 0.65-0.79, p<0.01). In terms of progression-free survival (PFS), pembrolizumab was associated with a similar PFS as compared to chemotherapy (HR=0.88, 95% CI: 0.73-1.07, p=0.206). Subgroup analyses based on PD-L1 expression levels indicated a significantly longer PFS with pembrolizumab in subgroups of patients with PD-L1 CPS≥10, but not in these with PD-L1 CPS≥1 and PD-L1 CPS≥5. Subgroup analyses based on distinct geographical regions revealed a comparable effect of PFS in patients residing in Asia or the USA. Subgroup analysis based on tumor sites consistently demonstrated a similar effect of PFS in patients with EC/GEJ tumors and GC patients. ●Conclusion: Our findings demonstrated that pembrolizumab led to a significant extension in OS and ORR, along with a favorable tolerability profile compared to chemotherapy. Furthermore, the observed survival benefits were particularly pronounced in subgroup patients with a CPS of ≥10. Given the potential limitations inherent in our study, it is imperative to underscore the necessity for further large-scale RCTs to corroborate our results. ●Keywords: gastro-esophageal junction cancer, meta-analysis, chemotherapy, pembrolizumab.

Association of cord blood Ang-1 and sCD105 levels with bronchopulmonary dysplasia in preterm infants.

BACKGROUND: To investigate the relationship between cord blood levels of Angiopoietin-1 (Ang-1) and S-endoglin (sCD105) and bronchopulmonary dysplasia (BPD) in preterm infants. METHODS: Sixty-one preterm infants admitted to the neonatal intensive care unit of the study hospital between July 2021 and September 2022 were included. Cord blood was collected after the birth of premature infants. Ang-1 and sCD105 levels were quantified using the vascular endothelial growth factor enzyme-linked immunosorbent assay. Preterm infants were divided into BPD and non-BPD groups, and differences in Ang-1 and sCD105 levels between the two groups were compared. A binary logistic model was used to assess the association between low and high levels Ang-1 and BPD in preterm infants. RESULTS: In the study, there were 20 preterm infants with BPD (32.8%) and 41 preterm infants with non-BPD (67.2%). Ang-1 concentration levels were lower in the BPD group than in the non-BPD group (7105.43 (5617.01-8523.00) pg/ml vs. 10488.03 (7946.19-15962.77) pg/ml, P = 0.027). However, the sCD105 concentration levels were not significantly different between the BPD and non-BPD groups (P = 0.246). A median Ang-1 concentration of 8800.40 pg/ml was calculated. Logistic regression analysis showed that after adjusting for gestational age, birth weight, and maternal prenatal steroid hormone application, the odds ratio (OR) was 8.577 for the risk of BPD in preterm infants with Ang-1 concentrations of ≤ 8800.40 pg/ml compared to those with Ang-1 concentrations of > 8800.40 pg/ml (OR: 8.577, 95% confidence interval: 1.265-58.155, P = 0.028). CONCLUSION: Our study indicated that Ang-1 levels in the cord blood of preterm infants may be associated the risk of BPD. In the future, we will continue to conduct study with large samples.

Research progress in spike mutations of SARS-CoV-2 variants and vaccine development.

The coronavirus disease 2019 (COVID-19) pandemic can hardly end with the emergence of different variants over time. In the past 2 years, several variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), such as the Delta and Omicron variants, have emerged with higher transmissibility, immune evasion and drug resistance, leading to higher morbidity and mortality in the population. The prevalent variants of concern (VOCs) share several mutations on the spike that can affect virus characteristics, including transmissibility, antigenicity, and immune evasion. Increasing evidence has demonstrated that the neutralization capacity of sera from COVID-19 convalescent or vaccinated individuals is decreased against SARS-CoV-2 variants. Moreover, the vaccine effectiveness of current COVID-19 vaccines against SARS-CoV-2 VOCs is not as high as that against wild-type SARS-CoV-2. Therefore, more attention might be paid to how the mutations impact vaccine effectiveness. In this review, we summarized the current studies on the mutations of the SARS-CoV-2 spike, particularly of the receptor binding domain, to elaborate on how the mutations impact the infectivity, transmissibility and immune evasion of the virus. The effects of mutations in the SARS-CoV-2 spike on the current therapeutics were highlighted, and potential strategies for future vaccine development were suggested.

Biphasic chemotaxis of Escherichia coli to the microbiota metabolite indole.

Bacterial chemotaxis to prominent microbiota metabolites such as indole is important in the formation of microbial communities in the gastrointestinal (GI) tract. However, the basis of chemotaxis to indole is poorly understood. Here, we exposed Escherichia coli to a range of indole concentrations and measured the dynamic responses of individual flagellar motors to determine the chemotaxis response. Below 1 mM indole, a repellent-only response was observed. At 1 mM indole and higher, a time-dependent inversion from a repellent to an attractant response was observed. The repellent and attractant responses were mediated by the Tsr and Tar chemoreceptors, respectively. Also, the flagellar motor itself mediated a repellent response independent of the receptors. Chemotaxis assays revealed that receptor-mediated adaptation to indole caused a bipartite response-wild-type cells were attracted to regions of high indole concentration if they had previously adapted to indole but were otherwise repelled. We propose that indole spatially segregates cells based on their state of adaptation to repel invaders while recruiting beneficial resident bacteria to growing microbial communities within the GI tract.

Fine-mapping and replication of EWAS loci harboring putative epigenetic alterations associated with AD neuropathology in a large collection of human brain tissue samples.

INTRODUCTION: Our previous epigenome-wide association study (EWAS) of Alzheimer's disease (AD) in human brain identified 71 CpGs associated with AD pathology. However, due to low coverage of the Illumina platform, many important CpGs might have been missed. METHODS: In a large collection of human brain tissue samples (N = 864), we fine-mapped previous EWAS loci by targeted bisulfite sequencing and examined their associations with AD neuropathology. DNA methylation was also linked to gene expression of the same brain cortex. RESULTS: Our targeted sequencing captured 130 CpGs (∼1.2 kb), 93 of which are novel. Of the 130 CpGs, 57 sites (only 17 included in previous EWAS) and 12 gene regions (e.g., ANK1, BIN1, RHBDF2, SPG7, PODXL) were significantly associated with amyloid load. DNA methylation in some regions was associated with expression of nearby genes. DISCUSSION: Targeted methylation sequencing can validate previous EWAS loci and discover novel CpGs associated with AD pathology.

Digital cognitive behavior therapy for insomnia improving sleep quality: a real-world study.

BACKGROUND: Digital cognitive behavior therapy for insomnia (dCBT-I) is an effective treatment in alleviating insomnia. This study examined the effect of dCBT-I for improving sleep quality in patients with insomnia complaints from a clinical population in a real-world setting. METHODS: The study included 6,002 patients aged 18 years and above with primary complaints of dissatisfying sleep from a sleep clinic in a psychiatric hospital from November 2016 to April 2021. Patients were diagnosed with insomnia, anxiety disorders, or anxiety comorbid with insomnia or depression according to ICD-10. A mobile app was developed for self-reported assessment and delivering dCBT-I interventions and treatment prescriptions to participants. The primary outcome was change in global sleep quality measured by the Pittsburgh Sleep Quality Index (PSQI). At 8- and 12-week follow-up, 509 patients were reassessed. Data were analyzed with non-parametric tests for repeated measures. RESULTS: Patients treated with dCBT-I monotherapy were younger, with a more frequent family history of insomnia compared to those with medication monotherapy and those with combined dCBT-I and medication therapy. Improvements of sleep quality from baseline to 8-week follow-up were significant in each treatment type. Compared to 8-week follow-up, PSQI scores at 12-week were significantly decreased in the depression group receiving combined therapy and in the anxiety group treated with dCBT-I monotherapy and with combined therapy. A time-by-treatment interaction was detected in anxiety patients indicating differential reduction in PSQI scores over time between different treatment options. CONCLUSION: The current findings suggest dCBT-I is a practical and effective approach for lessening insomnia symptoms, especially for patients with anxiety symptoms suggesting with a more extended intervention period (i.e., 12 weeks). TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR1900022699).

Lymph-Node-Targeted Cholesterolized TLR7 Agonist Liposomes Provoke a Safe and Durable Antitumor Response.

Toll-like receptor (TLR) agonists as the potent stimulants of an innate immune system hold promises for applications in anticancer immunotherapy. However, most of them are limited in the clinical translation due to the uncontrolled systemic inflammatory response. In the current study, 1V209, a small molecule TLR7 agonist, was conjugated with cholesterol (1V209-Cho) and prepared into liposomes (1V209-Cho-Lip). 1V209-Cho-Lip exerted minimal toxic effects and enhanced the transportation ability in lymph nodes (LNs) compared with 1V209. 1V209-Cho-Lip treatment inhibited tumor progression in CT26 colorectal cancer, 4T1 breast cancer, and Pan02 pancreatic ductal cancer models through inducing effective DC activation and eliciting CD8+ T cell responses. Furthermore, 1V209-Cho-Lip induced tumor-specific memory immunity to inhibit cancer recurrence and metastasis. These results indicate that cholesterol conjugation with 1V209 is an effective approach to target lymph nodes and to reduce the adverse effects. This work provides a rational basis for the distribution optimization of TLR agonists for potential clinical use.

Mendelian randomization analysis identified genes pleiotropically associated with central corneal thickness.

OBJECTIVE: To prioritize genes that were pleiotropically or potentially causally associated with central corneal thickness (CCT). METHODS: We applied the summary data-based Mendelian randomization (SMR) method integrating summarized data of genome-wide association study (GWAS) on CCT and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with CCT. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analyses were done for participants of European and East Asian ancestries, separately. RESULTS: We identified multiple genes showing pleiotropic association with CCT in the participants of European ancestry. CLIC3 (ILMN_1796423; PSMR = 4.15 × 10- 12), PTGDS (ILMN_1664464; PSMR = 6.88 × 10- 9) and C9orf142 (ILMN_1761138; PSMR = 8.09 × 10- 9) were the top three genes using the CAGE eQTL data, and RP11-458F8.4 (ENSG00000273142.1; PSMR = 5.89 × 10- 9), LCNL1 (ENSG00000214402.6; PSMR = 5.67 × 10- 8), and PTGDS (ENSG00000107317.7; PSMR = 1.92 × 10- 7) were the top three genes using the GTEx eQTL data. No genes showed significantly pleiotropic association with CCT in the participants of East Asian ancestry after correction for multiple testing. CONCLUSION: We identified several genes pleiotropically associated with CCT, some of which represented novel genes influencing CCT. Our findings provided important leads to a better understanding of the genetic factors influencing CCT, and revealed potential therapeutic targets for the treatment of primary open-angle glaucoma and keratoconus.

Cognitive and brain cytokine profile of non-demented individuals with cerebral amyloid-beta deposition.

BACKGROUND: Brain inflammation has been increasingly associated with early amyloid accumulation in Alzheimer's disease models; however, evidence of its occurrence in humans remains scarce. To elucidate whether amyloid deposition is associated with neuroinflammation and cognitive deficits, we studied brain inflammatory cytokine expression and cognitive decline in non-demented elderly individuals with and without cerebral amyloid-beta deposition. METHODS: Global cognition, episodic, working, and semantic memory, perceptual speed, visuospatial ability, and longitudinal decline (5.7 ± 3.6 years) in each cognitive domain were compared between elderly individuals (66-79 years) with and without cerebral amyloid-beta deposition. The expression of 20 inflammatory cytokines was analyzed in frozen temporal, parietal, and frontal cortices and compared between older individuals with and without amyloid-beta deposition in each brain region. Correlation analyses were performed to analyze associations between amyloid-beta load, cytokine expression, and cognitive decline. RESULTS: Individuals with cortical amyloid-beta deposition displayed deficits and a faster rate of cognitive decline in perceptual speed as compared with those individuals without amyloid-beta. This decline was positively associated with cortical amyloid-beta levels. Elderly individuals with amyloid-beta deposition had higher levels of IL-1ß, IL-6, and eotaxin-3 in the temporal cortex accompanied by an increase in MCP-1 and IL-1ß in the parietal cortex and a trend towards higher levels of IL-1ß and MCP-1 in the frontal cortex as compared with age-matched amyloid-free individuals. Brain IL-1ß levels displayed a positive association with cortical amyloid burden in each brain region. Finally, differential cytokine expression in each cortical region was associated with cognitive decline. CONCLUSIONS: Elderly individuals with amyloid-beta neuropathology but no symptomatic manifestation of dementia, exhibit cognitive decline and increased brain cytokine expression. Such observations suggest that increased cytokine expression might be an early event in the Alzheimer's continuum.

Patient-Derived Tumor Xenografts Plus Ex Vivo Models Enable Drug Validation for Tenosynovial Giant Cell Tumors.

INTRODUCTION: Tenosynovial giant cell tumor (TGCT) is a locally aggressive tumor with colony-stimulating factor 1 receptor (CSF1R) signal expression. However, there is a lack of better in vivo and ex vivo models for TGCT. This study aims to establish a favorable preclinical translational platform, which would enable the validation of efficient and personalized therapeutic candidates for TGCT. PATIENTS AND METHODS: Histological analyses were performed for the included patients. Fresh TGCT tumors were collected and sliced into 1.0-3.0 mm3 sections using a sterilized razor blade. The tumor grafts were surgically implanted into subrenal capsules of athymic mice to establish patient-derived tumor xenograft (PDTX) mouse models. Histological and response patterns to CSF1R inhibitors evaluations were analyzed. In addition, ex vivo cultures of patient-derived explants (PDEs) with endpoint analysis were used to validate TGCT graft response patterns to CSF1R inhibitors. RESULTS: The TGCT tumor grafts that were implanted into athymic mice subrenal capsules maintained their original morphological and histological features. The "take" rate of this model was 95% (19/20). Administration of CSF1R inhibitors (PLX3397, and a novel candidate, WXFL11420306) to TGCT-PDTX mice was shown to reduce tumor size while inducing intratumoral apoptosis. In addition, the CSF1R inhibitors suppressed circulating nonspecific monocyte levels and CD163-positive cells within tumors. These response patterns of engrafts to PDTX were validated by ex vivo PDE cultures. CONCLUSIONS: Subrenal capsule supports the growth of TGCT tumor grafts, maintaining their original morphology and histology. This TGCT-PDTX model plus ex vivo explant cultures is a potential preclinical translational platform for locally aggressive tumors, such as TGCT.

Progress of artificial intelligence in diabetic retinopathy screening.

Diabetic retinopathy (DR) is one of the leading causes of blindness worldwide, and the limited availability of qualified ophthalmologists restricts its early diagnosis. For the past few years, artificial intelligence technology has developed rapidly and has been applied in DR screening. The upcoming technology provides support on DR screening and improves the identification of DR lesions with a high sensitivity and specificity. This review aims to summarize the progress on automatic detection and classification models for the diagnosis of DR.

Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.

AIMS: To establish an automated method for identifying referable diabetic retinopathy (DR), defined as moderate nonproliferative DR and above, using deep learning-based lesion detection and stage grading. MATERIALS AND METHODS: A set of 12,252 eligible fundus images of diabetic patients were manually annotated by 45 licenced ophthalmologists and were randomly split into training, validation, and internal test sets (ratio of 7:1:2). Another set of 565 eligible consecutive clinical fundus images was established as an external test set. For automated referable DR identification, four deep learning models were programmed based on whether two factors were included: DR-related lesions and DR stages. Sensitivity, specificity and the area under the receiver operating characteristic curve (AUC) were reported for referable DR identification, while precision and recall were reported for lesion detection. RESULTS: Adding lesion information to the five-stage grading model improved the AUC (0.943 vs. 0.938), sensitivity (90.6% vs. 90.5%) and specificity (80.7% vs. 78.5%) of the model for identifying referable DR in the internal test set. Adding stage information to the lesion-based model increased the AUC (0.943 vs. 0.936) and sensitivity (90.6% vs. 76.7%) of the model for identifying referable DR in the internal test set. Similar trends were also seen in the external test set. DR lesion types with high precision results were preretinal haemorrhage, hard exudate, vitreous haemorrhage, neovascularisation, cotton wool spots and fibrous proliferation. CONCLUSIONS: The herein described automated model employed DR lesions and stage information to identify referable DR and displayed better diagnostic value than models built without this information.

Silver nanoparticles and silver ions cause inflammatory response through induction of cell necrosis and the release of mitochondria in vivo and in vitro.

Owing to the excellent antibacterial and antiviral activity, silver nanoparticles have a widespread use in the food and pharmaceutical industries. With the increase in the production and use of the related products, the potential hazard of silver nanoparticles has aroused public attention. The main purpose of this study is to explore the toxicity of silver nanoparticles and induction of lung inflammation in vitro and in vivo. Here, we validated that small amounts of silver ions dissolved from silver nanoparticles caused the depolarization of plasma membrane, resulting in an overload of intracellular sodium and calcium, and eventually led to the cell necrosis. The blockers of calcium or sodium channels inversed the toxicity of silver ions. Then, we instilled silver nanoparticles or silver nitrate (50 µg per mouse) into the lungs of mice, and this induced pulmonary injury and mitochondrial content release, led to the recruitment of neutrophils to the lung tissue via p38 MAPK pathway. Altogether, these data show that released silver ions from nanoparticles induced cell necrosis through Na+ and Ca2+ influx and triggered pulmonary inflammation through elevating mitochondrial-related contents released from these necrotic cells.

Monitoring Recessions: A Bayesian Sequential Quickest Detection Method.

Monitoring business cycles faces two potentially conflicting objectives: accuracy and timeliness. To strike a balance between the dual objectives, we develop a Bayesian sequential quickest detection method to identify turning points in real time and propose a sequential stopping time as a solution. Using four monthly indexes of real economic activity in the US, we evaluate the method's real-time ability to date the past five recessions. The proposed method identifies similar turning point dates as the National Bureau of Economic Research (NBER), with no false alarms, but on average dates peaks 4 months faster and troughs 10 months faster relative to the NBER announcement. The timeliness of our method is also notable compared to the dynamic factor Markov-switching model - the average lead time is about 5 months in dating peaks and 2 months in dating troughs.