Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Metabolic reprogramming of terminally exhausted CD8+ T cells by IL-10 enhances anti-tumor immunity.

T cell exhaustion presents one of the major hurdles to cancer immunotherapy. Among exhausted CD8+ tumor-infiltrating lymphocytes, the terminally exhausted subset contributes directly to tumor cell killing owing to its cytotoxic effector function. However, this subset does not respond to immune checkpoint blockades and is difficult to be reinvigorated with restored proliferative capacity. Here, we show that a half-life-extended interleukin-10-Fc fusion protein directly and potently enhanced expansion and effector function of terminally exhausted CD8+ tumor-infiltrating lymphocytes by promoting oxidative phosphorylation, a process that was independent of the progenitor exhausted T cells. Interleukin-10-Fc was a safe and highly efficient metabolic intervention that synergized with adoptive T cell transfer immunotherapy, leading to eradication of established solid tumors and durable cures in the majority of treated mice. These findings show that metabolic reprogramming by upregulating mitochondrial pyruvate carrier-dependent oxidative phosphorylation can revitalize terminally exhausted T cells and enhance the response to cancer immunotherapy.

Programming inactive RNA-binding small molecules into bioactive degraders.

Target occupancy is often insufficient to elicit biological activity, particularly for RNA, compounded by the longstanding challenges surrounding the molecular recognition of RNA structures by small molecules. Here we studied molecular recognition patterns between a natural-product-inspired small-molecule collection and three-dimensionally folded RNA structures. Mapping these interaction landscapes across the human transcriptome defined structure-activity relationships. Although RNA-binding compounds that bind to functional sites were expected to elicit a biological response, most identified interactions were predicted to be biologically inert as they bind elsewhere. We reasoned that, for such cases, an alternative strategy to modulate RNA biology is to cleave the target through a ribonuclease-targeting chimera, where an RNA-binding molecule is appended to a heterocycle that binds to and locally activates RNase L1. Overlay of the substrate specificity for RNase L with the binding landscape of small molecules revealed many favourable candidate binders that might be bioactive when converted into degraders. We provide a proof of concept, designing selective degraders for the precursor to the disease-associated microRNA-155 (pre-miR-155), JUN mRNA and MYC mRNA. Thus, small-molecule RNA-targeted degradation can be leveraged to convert strong, yet inactive, binding interactions into potent and specific modulators of RNA function.

Tristetraprolin impairs myc-induced lymphoma and abolishes the malignant state.

Myc oncoproteins directly regulate transcription by binding to target genes, yet this only explains a fraction of the genes affected by Myc. mRNA turnover is controlled via AU-binding proteins (AUBPs) that recognize AU-rich elements (AREs) found within many transcripts. Analyses of precancerous and malignant Myc-expressing B cells revealed that Myc regulates hundreds of ARE-containing (ARED) genes and select AUBPs. Notably, Myc directly suppresses transcription of Tristetraprolin (TTP/ZFP36), an mRNA-destabilizing AUBP, and this circuit is also operational during B lymphopoiesis and IL7 signaling. Importantly, TTP suppression is a hallmark of cancers with MYC involvement, and restoring TTP impairs Myc-induced lymphomagenesis and abolishes maintenance of the malignant state. Further, there is a selection for TTP loss in malignancy; thus, TTP functions as a tumor suppressor. Finally, Myc/TTP-directed control of select cancer-associated ARED genes is disabled during lymphomagenesis. Thus, Myc targets AUBPs to regulate ARED genes that control tumorigenesis.

Quantitative, in situ visualization of intracellular insulin vesicles in pancreatic beta cells.

Characterizing relationships between Zn2+, insulin, and insulin vesicles is of vital importance to the study of pancreatic beta cells. However, the precise content of Zn2+ and the specific location of insulin inside insulin vesicles are not clear, which hinders a thorough understanding of the insulin secretion process and diseases caused by blood sugar dysregulation. Here, we demonstrated the colocalization of Zn2+ and insulin in both single extracellular insulin vesicles and pancreatic beta cells by using an X-ray scanning coherent diffraction imaging (ptychography) technique. We also analyzed the elemental Zn2+ and Ca2+ contents of insulin vesicles using electron microscopy and energy dispersive spectroscopy (EDS) mapping. We found that the presence of Zn2+ is an important characteristic that can be used to distinguish insulin vesicles from other types of vesicles in pancreatic beta cells and that the content of Zn2+ is proportional to the size of insulin vesicles. By using dual-energy contrast X-ray microscopy and scanning transmission X-ray microscopy (STXM) image stacks, we observed that insulin accumulates in the off-center position of extracellular insulin vesicles. Furthermore, the spatial distribution of insulin vesicles and their colocalization with other organelles inside pancreatic beta cells were demonstrated using three-dimensional (3D) imaging by combining X-ray ptychography and an equally sloped tomography (EST) algorithm. This study describes a powerful method to univocally describe the location and quantitative analysis of intracellular insulin, which will be of great significance to the study of diabetes and other blood sugar diseases.

Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology.

Personalized treatment strategies for cancer frequently rely on the detection of genetic alterations which are determined by molecular biology assays. Historically, these processes typically required single-gene sequencing, next-generation sequencing, or visual inspection of histopathology slides by experienced pathologists in a clinical context. In the past decade, advances in artificial intelligence (AI) technologies have demonstrated remarkable potential in assisting physicians with accurate diagnosis of oncology image-recognition tasks. Meanwhile, AI techniques make it possible to integrate multimodal data such as radiology, histology, and genomics, providing critical guidance for the stratification of patients in the context of precision therapy. Given that the mutation detection is unaffordable and time-consuming for a considerable number of patients, predicting gene mutations based on routine clinical radiological scans or whole-slide images of tissue with AI-based methods has become a hot issue in actual clinical practice. In this review, we synthesized the general framework of multimodal integration (MMI) for molecular intelligent diagnostics beyond standard techniques. Then we summarized the emerging applications of AI in the prediction of mutational and molecular profiles of common cancers (lung, brain, breast, and other tumor types) pertaining to radiology and histology imaging. Furthermore, we concluded that there truly exist multiple challenges of AI techniques in the way of its real-world application in the medical field, including data curation, feature fusion, model interpretability, and practice regulations. Despite these challenges, we still prospect the clinical implementation of AI as a highly potential decision-support tool to aid oncologists in future cancer treatment management.

Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants.

BACKGROUND: While circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated. METHODS: We conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry. RESULTS: We identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33-3.37) and 0.49 (0.40-0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses. CONCLUSIONS: Our study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.

Effect of inactivated vaccine boosters against severe and critical COVID-19 during the Omicron BA.5 wave: A retrospective analysis of hospitalized patients in China.

Few real-world analyses of the ability of vaccines to protect against severe COVID-19 have been published. In this real-world study, we compared the prevalence of severe or critical COVID-19 between patients at our hospital who were not vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or who had been vaccinated partial, full, or booster course with the CoronaVac, containing inactivated virus propagated in Vero cells. Data from electronic health records were retrospectively analyzed for 4090 inpatients with COVID-19 who were treated at West China Hospital, Chengdu between December 6, 2022 and February 14, 2023. Clinicodemographic characteristics and COVID-19 severity were compared among patients who had been vaccinated 0, 1, 2 or more times with inactivated vaccine CoronaVac. To evaluate vaccine effectiveness over time, we plotted Kaplan-Meier curves with the percentage of patients with the outcome of severe or critical COVID-19 from the time of their last vaccine dose according to vaccination status. Ordinal logistic regression was used to assess associations between vaccination status and COVID-19 severity. Cox regression was used to identify risk factors for severe or critical COVID-19. Among the 4090 patients, 171 had been vaccinated partial and 423 twice with the full CoronaVac regimens, while 905 had been vaccinated three times (boosted). The prevalence of severe or critical COVID-19 among patients was 11 percentage points lower among those vaccinated (40%) at least twice than among those unvaccinated (51%) (p＜0.001), while it was 10% points lower among those who had received a booster (41%) than among those unvaccinated (51%) (p＜0.001). Protection against severe or critical COVID-19 due to vaccination was significantly weakened by being older than 65 years, being male, or having diabetes, chronic heart disease, autoimmune disease, or chronic lung disease. Completing a full course of immunization with inactivated vaccine CoronaVac against SARS-CoV-2 can reduce the risk of severe or critical COVID-19 due to the Omicron BA.5 subvariant.

Costunolide ameliorates angiotensin II-induced atrial inflammation and fibrosis by regulating mitochondrial function and oxidative stress in mice: A possible therapeutic approach for atrial fibrillation.

Atrial fibrillation (AF) is a cardiac disease characterized by disordered atrial electrical activity. Atrial inflammation and fibrosis are involved in AF progression. Costunolide (COS) is a sesquiterpene lactone containing anti-inflammatory and anti-fibrotic activities. This study aims to explore the underlying mechanisms by which COS protects against AF. Male C57BL/6 mice (8- to 10-week-old) were infused with angiotensin (Ang) II for 3 weeks. Meanwhile, different doses of COS (COS-L: 10 mg/kg, COS-H: 20 mg/kg) were administered to mice by intragastric treatment. The results showed irregular and rapid heart rates in Ang II-treated mice. Moreover, the levels of inflammatory cytokines and fibrotic factors were elevated in mice. COS triggered a reduction of Ang II-induced inflammation and fibrosis, which conferred a protective effect. Mechanistically, mitochondrial dysfunction with mitochondrial respiration inhibition and aberrant ATP levels were observed after Ang II treatment. Moreover, Ang-II-induced excessive reactive oxygen species caused oxidative stress, which was further aggravated by inhibiting Nrf2 nuclear translocation. Importantly, COS diminished these Ang-II-mediated effects in mice. In conclusion, COS attenuated inflammation and fibrosis in Ang-II-treated mice by alleviating mitochondrial dysfunction and oxidative stress. Our findings represent a potential therapeutic option for AF treatment.

Investigating causal associations between pneumonia and lung cancer using a bidirectional mendelian randomization framework.

BACKGROUND: Pneumonia and lung cancer are both major respiratory diseases, and observational studies have explored the association between their susceptibility. However, due to the presence of potential confounders and reverse causality, the comprehensive causal relationships between pneumonia and lung cancer require further exploration. METHODS: Genome-wide association study (GWAS) summary-level data were obtained from the hitherto latest FinnGen database, COVID-19 Host Genetics Initiative resource, and International Lung Cancer Consortium. We implemented a bidirectional Mendelian randomization (MR) framework to evaluate the causal relationships between several specific types of pneumonia and lung cancer. The causal estimates were mainly calculated by inverse-variance weighted (IVW) approach. Additionally, sensitivity analyses were also conducted to validate the robustness of the causalty. RESULTS: In the MR analyses, overall pneumonia demonstrated a suggestive but modest association with overall lung cancer risk (Odds ratio [OR]: 1.21, 95% confidence interval [CI]: 1.01 - 1.44, P = 0.037). The correlations between specific pneumonia types and overall lung cancer were not as significant, including bacterial pneumonia (OR: 1.07, 95% CI: 0.91 - 1.26, P = 0.386), viral pneumonia (OR: 1.00, 95% CI: 0.95 - 1.06, P = 0.891), asthma-related pneumonia (OR: 1.18, 95% CI: 0.92 - 1.52, P = 0.181), and COVID-19 (OR: 1.01, 95% CI: 0.78 - 1.30, P = 0.952). Reversely, with lung cancer as the exposure, we observed that overall lung cancer had statistically crucial associations with bacterial pneumonia (OR: 1.08, 95% CI: 1.03 - 1.13, P = 0.001) and viral pneumonia (OR: 1.09, 95% CI: 1.01 - 1.19, P = 0.037). Sensitivity analysis also confirmed the robustness of these findings. CONCLUSION: This study has presented a systematic investigation into the causal relationships between pneumonia and lung cancer subtypes. Further prospective study is warranted to verify these findings.

Immune checkpoint inhibitor plus chemotherapy as first-line treatment for non-small cell lung cancer with malignant pleural effusion: a retrospective multicenter study.

BACKGROUND: Immune checkpoint inhibitors (ICI) combined with chemotherapy are efficacious for treating advanced non-small cell lung cancer (NSCLC); however, the effectiveness of this approach in the malignant pleural effusion (MPE) population is unclear. This study evaluated ICI plus chemotherapy in NSCLC patients with MPE. METHODS: Patients from 3 centers in China with NSCLC and MPE who received ICI plus chemotherapy (ICI Plus Chemo) or chemotherapy alone (Chemo) between December 2014 and June 2023 were enrolled. Clinical outcomes and adverse events (AEs) were compared. RESULTS: Of 155 eligible patients, the median age was 61.0 years old. Males and never-smokers accounted for 73.5% and 39.4%, respectively. Fifty-seven and 98 patients received ICI Plus Chemo or Chemo, respectively. With a median study follow-up of 10.8 months, progression-free survival (PFS) was significantly longer with ICI Plus Chemo than with Chemo (median PFS: 7.4 versus 5.7 months; HR = 0.594 [95% CI: 0.403-0.874], P = 0.008). Median overall survival (OS) did not differ between groups (ICI Plus Chemo: 34.2 versus Chemo: 28.3 months; HR = 0.746 [95% CI: 0.420-1.325], P = 0.317). The most common grade 3 or worse AEs included decreased neutrophil count (3 [5.3%] patients in the ICI Plus Chemo group vs. 5 [5.1%] patients in the Chemo group) and decreased hemoglobin (3 [5.3%] versus 10 [10.2%]). CONCLUSIONS: In patients with untreated NSCLC with MPE, ICI plus chemotherapy resulted in significantly longer PFS than chemotherapy and had a manageable tolerability profile, but the effect on OS may be limited.

Prognostic Value of the Glasgow Prognostic Score in Non-Small Cell Lung Cancer Patients Receiving Immunotherapy: A Meta-Analysis.

BACKGROUND: The Glasgow Prognostic Score (GPS) has proven to be a good biomarker for lung cancer prognosis. However, its usefulness in lung cancer patients receiving checkpoint inhibitor immunotherapy remains controversial. Therefore, we performed a meta-analysis to explore the prognostic value of the GPS in non-small cell lung cancer patients receiving immunotherapy. METHODS: PubMed, Web of Science, Scopus, and Embase were systematically searched for relevant studies up to May 31, 2023, and hazard ratios (HRs) with 95% confidence intervals (95% CIs) were merged to investigate the prognostic value of the GPS for overall survival (OS) and progression-free survival (PFS). RESULTS: Seven studies comprising 833 patients were included in the primary analysis, and the pooled results indicated that a higher baseline GPS was associated with poorer OS and PFS in non-small cell lung cancer patients treated with immune checkpoint inhibitors (ICIs) (OS: HR = 1.95, 95% CI: 1.47-2.58, p < 0.01; PFS: HR = 1.63, 95% CI: 1.26-2.11, p < 0.01). These findings were robust after subgroup and sensitivity analyses. CONCLUSIONS: The GPS can serve as a biomarker in non-small cell lung cancer patients receiving immunotherapy with significant prognostic value; however, these findings require more prospective evidence for validation.

Deep learning for malignancy risk estimation of incidental sub-centimeter pulmonary nodules on CT images.

OBJECTIVES: To establish deep learning models for malignancy risk estimation of sub-centimeter pulmonary nodules incidentally detected by chest CT and managed in clinical settings. MATERIALS AND METHODS: Four deep learning models were trained using CT images of sub-centimeter pulmonary nodules from West China Hospital, internally tested, and externally validated on three cohorts. The four models respectively learned 3D deep features from the baseline whole lung region, baseline image patch where the nodule located, baseline nodule box, and baseline plus follow-up nodule boxes. All regions of interest were automatically segmented except that the nodule boxes were additionally manually checked. The performance of models was compared with each other and that of three respiratory clinicians. RESULTS: There were 1822 nodules (981 malignant) in the training set, 806 (416 malignant) in the testing set, and 357 (253 malignant) totally in the external sets. The area under the curve (AUC) in the testing set was 0.754, 0.855, 0.928, and 0.942, respectively, for models derived from baseline whole lung, image patch, nodule box, and the baseline plus follow-up nodule boxes. When baseline models externally validated (follow-up images not available), the nodule-box model outperformed the other two with AUC being 0.808, 0.848, and 0.939 respectively in the three external datasets. The resident, junior, and senior clinicians achieved an accuracy of 67.0%, 82.5%, and 90.0%, respectively, in the testing set. The follow-up model performed comparably to the senior clinician. CONCLUSION: The deep learning algorithms solely mining nodule information can efficiently predict malignancy of incidental sub-centimeter pulmonary nodules. CLINICAL RELEVANCE STATEMENT: The established models may be valuable for supporting clinicians in routine clinical practice, potentially reducing the number of unnecessary examinations and also delays in diagnosis. KEY POINTS: • According to different regions of interest, four deep learning models were developed and compared to evaluate the malignancy of sub-centimeter pulmonary nodules by CT images. • The models derived from baseline nodule box or baseline plus follow-up nodule boxes demonstrated sufficient diagnostic accuracy (86.4% and 90.4% in the testing set), outperforming the respiratory resident (67.0%) and junior clinician (82.5%). • The proposed deep learning methods may aid clinicians in optimizing follow-up recommendations for sub-centimeter pulmonary nodules and may lead to fewer unnecessary diagnostic interventions.

Neurological complications during the Omicron COVID-19 wave in China: A cohort study.

BACKGROUND AND PURPOSE: The aim was to investigate the neurological complications associated with coronavirus disease 19 (COVID-19) during the 2022 Omicron wave. METHODS AND ANALYSIS: The medical records of a cohort of people admitted to neurological wards of three participating tertiary centres in Sichuan from 12 December 2022 to 12 January 2023 were reviewed. Demographics and clinical data were obtained and analysed with an interest in COVID-19-related new-onset or worse neurological symptoms. The current data were also compared in two centres with similar data from the same period 12 months earlier. RESULTS: In all, 790 people were enrolled, of whom 436 were positive for COVID-19. Ninety-nine had new onset COVID-related neurological problems, or their known neurological condition deteriorated during the wave. There was a significant difference in demographics from the findings amongst admissions 12 months earlier as there was an increase in the average age, the incidence of encephalitis and encephalopathy, and mortality rates. One hundred and one received COVID-specific antivirals, intravenous glucocorticoids and intravenous immunoglobulin therapy. No differences were seen between these and those who did not use them. CONCLUSION: New-onset neurological conditions, particularly encephalitis and encephalopathy, increased significantly during this period. Deterioration of existing neurological conditions, such as seizure exacerbation, was also observed. A large-scale treatment trial of people with COVID-19 infection presenting with neurological disorders is still needed.

Risk factors, outcomes, and epidemiological and etiological study of hospitalized COVID-19 patients with bacterial co-infection and secondary infections.

BACKGROUND: As a common complication of viral respiratory tract infection, bacterial infection was associated with higher mortality and morbidity. Determining the prevalence, culprit pathogens, outcomes, and risk factors of co-infection and secondary infection occurring in hospitalized patients with coronavirus disease 2019 (COVID-19) will be beneficial for better antibiotic management. METHODS: In this retrospective cohort research, we assessed clinical characteristics, laboratory parameters, microbiologic results, and outcomes of laboratory-confirmed COVID-19 patients with bacterial co-infection and secondary infection in West China Hospital from 2022 December 2nd to 2023 March 15th. RESULTS: The incidence of bacterial co-infection and secondary infection, as defined by positive culture results of clinical specimens, was 16.3% (178/1091) and 10.1% (110/1091) respectively among 1091 patients. Acinetobacter, Klebsiella, and Pseudomonas were the most commonly identified bacteria in respiratory tract samples of COVID-19 patients. In-hospital mortality of COVID-19 patients with co-infection (17.4% vs 9.5%, p = 0.003) and secondary infection (28.2% vs 9.5%, p < 0.001) greatly exceeded that of COVID-19 patients without bacterial infection. Cardiovascular disease (1.847 (1.202-2.837), p = 0.005), severe COVID-19 (1.694 (1.033-2.778), p = 0.037), and critical COVID-19 (2.220 (1.196-4.121), p = 0.012) were proved to be risk factors for bacterial co-infection, while only critical COVID-19 (1.847 (1.202-2.837), p = 0.005) was closely related to secondary infection. CONCLUSIONS: Bacterial co-infection and secondary infection could aggravate the disease severity and worsen clinical outcomes of COVID-19 patients. Notably, only critical COVID-19 subtype was proved to be an independent risk factor for both co-infection and secondary infection. Therefore, standard empirical antibiotics was recommended for critically ill COVID-19 rather than all the inpatients according to our research.

Endothelial TIE1 Restricts Angiogenic Sprouting to Coordinate Vein Assembly in Synergy With Its Homologue TIE2.

BACKGROUND: Vascular growth followed by vessel specification is crucial for the establishment of a hierarchical blood vascular network. We have shown that TIE2 is required for vein development while little is known about its homologue TIE1 (tyrosine kinase with immunoglobulin-like and EGF [epithelial growth factor]-like domains 1) in this process. METHODS: We analyzed functions of TIE1 as well as its synergy with TIE2 in the regulation of vein formation by employing genetic mouse models targeting Tie1, Tek, and Nr2f2, together with in vitro cultured endothelial cells to decipher the underlying mechanism. RESULTS: Cardinal vein growth appeared normal in TIE1-deficient mice, whereas TIE2 deficiency altered the identity of cardinal vein endothelial cells with the aberrant expression of DLL4 (delta-like canonical Notch ligand 4). Interestingly, the growth of cutaneous veins, which was initiated at approximately embryonic day 13.5, was retarded in mice lack of TIE1. TIE1 deficiency disrupted the venous integrity, displaying increased sprouting angiogenesis and vascular bleeding. Abnormal venous sprouts with defective arteriovenous alignment were also observed in the mesenteries of Tie1-deleted mice. Mechanistically, TIE1 deficiency resulted in the decreased expression of venous regulators including TIE2 and COUP-TFII (chicken ovalbumin upstream promoter transcription factor, encoded by Nr2f2, nuclear receptor subfamily 2 group F member 2) while angiogenic regulators were upregulated. The alteration of TIE2 level by TIE1 insufficiency was further confirmed by the siRNA-mediated knockdown of Tie1 in cultured endothelial cells. Interestingly, TIE2 insufficiency also reduced the expression of TIE1. Combining the endothelial deletion of Tie1 with 1 null allele of Tek resulted in a progressive increase of vein-associated angiogenesis leading to the formation of vascular tufts in retinas, whereas the loss of Tie1 alone produced a relatively mild venous defect. Furthermore, the induced deletion of endothelial Nr2f2 decreased both TIE1 and TIE2. CONCLUSIONS: Findings from this study imply that TIE1 and TIE2, together with COUP-TFII, act in a synergistic manner to restrict sprouting angiogenesis during the development of venous system.

Activated non-neuronal cholinergic system correlates with non-type 2 inflammation and exacerbations in severe asthma.

BACKGROUND: Non-neuronal cholinergic system (NNCS) contributes to various inflammatory airway diseases. However, the role of NNCS in severe asthma (SA) remains largely unexplored. OBJECTIVE: To explore airway NNCS in SA. METHODS: In this prospective cohort study based on the Australasian Severe Asthma Network in a real-world setting, patients with SA (n = 52) and non-SA (n = 104) underwent clinical assessment and sputum induction. The messenger RNA (mRNA) levels of NNCS components and proinflammatory cytokines in the sputum were detected using real-time quantitative polymerase chain reaction, and the concentrations of acetylcholine (Ach)-related metabolites were evaluated using liquid chromatography coupled with tandem mass spectrometry. Asthma exacerbations were prospectively investigated during the next 12 months. The association between NNCS and future asthma exacerbations was also analyzed. RESULTS: Patients with SA were less controlled and had worse airway obstruction, a lower bronchodilator response, higher doses of inhaled corticosteroids, and more add-on treatments. The sputum mRNA levels of NNCS components, such as muscarinic receptors M1R-M5R, OCT3, VACHT, and ACHE; proinflammatory cytokines; and Ach concentration in the SA group were significantly higher than those in the non-SA group. Furthermore, most NNCS components positively correlated with non-type (T) 2 inflammatory profiles, such as sputum neutrophils, IL8, and IL1B. In addition, the mRNA levels of sputum M2R, M3R, M4R, M5R, and VACHT were independently associated with an increased risk of moderate-to-severe asthma exacerbations. CONCLUSION: This study indicated that the NNCS was significantly activated in SA, leading to elevated Ach and was associated with clinical features, non-T2 inflammation, and future exacerbations of asthma, highlighting the potential role of the NNCS in the pathogenesis of SA. CLINICAL TRIAL REGISTRATION: ChiCTR-OOC-16009529 (http://www.chictr.org.cn).

Mitochondrial haplogroups and cognitive progression in Parkinson's disease.

Mitochondria are a culprit in the onset of Parkinson's disease, but their role during disease progression is unclear. Here we used Cox proportional hazards models to exam the effect of variation in the mitochondrial genome on longitudinal cognitive and motor progression over time in 4064 patients with Parkinson's disease. Mitochondrial macro-haplogroup was associated with reduced risk of cognitive disease progression in the discovery and replication population. In the combined analysis, patients with the super macro-haplogroup J, T, U# had a 41% lower risk of cognitive progression with P = 2.42 × 10-6 compared to those with macro-haplogroup H. Exploratory analysis indicated that the common mitochondrial DNA variant, m.2706A>G, was associated with slower cognitive decline with a hazard ratio of 0.68 (95% confidence interval 0.56-0.81) and P = 2.46 × 10-5. Mitochondrial haplogroups were not appreciably linked to motor progression. This initial genetic survival study of the mitochondrial genome suggests that mitochondrial haplogroups may be associated with the pace of cognitive progression in Parkinson's disease over time.

Correction: Ionic migration induced loss analysis of perovskite solar cells: a poling study.

Correction for 'Ionic migration induced loss analysis of perovskite solar cells: a poling study' by Xue Zheng et al., Phys. Chem. Chem. Phys., 2022, 24, 7805-7814, https://doi.org/10.1039/D1CP05450C.