Resolvin D2-G-Protein Coupled Receptor 18 Enhances Bone Marrow Function and Limits Steatosis and Hepatic Collagen Accumulation in Aging.

Aging is associated with nonresolving inflammation and tissue dysfunction. Resolvin D2 (RvD2) is a proresolving ligand that acts through the G-protein-coupled receptor called GPR18. Unbiased RNA sequencing revealed increased Gpr18 expression in macrophages from old mice, and in livers from elderly humans, which was associated with increased steatosis and fibrosis in middle-aged (MA) and old mice. MA mice that lacked GPR18 on myeloid cells had exacerbated steatosis and hepatic fibrosis, which was associated with a decline in Mac2+ macrophages. Treatment of MA mice with RvD2 reduced steatosis and decreased hepatic fibrosis, correlating with increased Mac2+ macrophages, increased monocyte-derived macrophages, and elevated numbers of monocytes in the liver, blood, and bone marrow. RvD2 acted directly on the bone marrow to increase monocyte-macrophage progenitors. A transplantation assay further demonstrated that bone marrow from old mice facilitated hepatic collagen accumulation in young mice. Transient RvD2 treatment to mice transplanted with bone marrow from old mice prevented hepatic collagen accumulation. Together, this study demonstrates that RvD2-GPR18 signaling controls steatosis and fibrosis and provides a mechanistic-based therapy for promoting liver repair in aging.

Expression of CD25, mast cell markers and T-cell markers in eosinophilic esophagitis.

While eosinophilic esophagitis (EOE) is defined by histologic presence of eosinophils, a few studies have established the presence of mast cells in EOE and even shown their correlation with symptom persistence despite resolution of eosinophils. Expression of aberrant mast cell markers CD25 and CD2 have not been studied in EOE. This study quantifies the number of hotspot cells per high power field expressing CKIT/CD117, tryptase, CD25, CD2 and CD3 by immunohistochemical stains in endoscopic esophageal biopsies of the following three cohorts: (1) established and histologically confirmed EOE, (2) suspected EOE with biopsies negative for eosinophils, and (3) no history of or suspicion for EOE with histologically unremarkable biopsies. In this study, mast cells were highlighted by CKIT and tryptase in EOE, and not seen in other clinically mimicking cases. There were also significantly higher densities of CD25 and pan-T-cell marker staining in EOE cases. These findings suggest an inflammatory cellular milieu in EOE, beyond just eosinophils, that can be demonstrated by immunohistochemistry, and that invite further study into the role that these cells may play in EOE.

Impact of selection bias on polygenic risk score estimates in healthcare settings.

BACKGROUND: Hospital-based biobanks are being increasingly considered as a resource for translating polygenic risk scores (PRS) into clinical practice. However, since these biobanks originate from patient populations, there is a possibility of bias in polygenic risk estimation due to overrepresentation of patients with higher frequency of healthcare interactions. METHODS: PRS for schizophrenia, bipolar disorder, and depression were calculated using summary statistics from the largest available genomic studies for a sample of 24 153 European ancestry participants in the Mass General Brigham (MGB) Biobank. To correct for selection bias, we fitted logistic regression models with inverse probability (IP) weights, which were estimated using 1839 sociodemographic, clinical, and healthcare utilization features extracted from electronic health records of 1 546 440 non-Hispanic White patients eligible to participate in the Biobank study at their first visit to the MGB-affiliated hospitals. RESULTS: Case prevalence of bipolar disorder among participants in the top decile of bipolar disorder PRS was 10.0% (95% CI 8.8-11.2%) in the unweighted analysis but only 6.2% (5.0-7.5%) when selection bias was accounted for using IP weights. Similarly, case prevalence of depression among those in the top decile of depression PRS was reduced from 33.5% (31.7-35.4%) to 28.9% (25.8-31.9%) after IP weighting. CONCLUSIONS: Non-random selection of participants into volunteer biobanks may induce clinically relevant selection bias that could impact implementation of PRS in research and clinical settings. As efforts to integrate PRS in medical practice expand, recognition and mitigation of these biases should be considered and may need to be optimized in a context-specific manner.

Rapid Reorganization of an Academic Infectious Diseases Program During the Coronavirus Disease 2019 Pandemic in Detroit: A Novel Unit-based Group Rounding Model.

The surge of coronavirus disease 2019 (COVID-19) hospitalizations at our 877-bed quaternary care hospital in Detroit led to an emergent demand for Infectious Diseases (ID) consultations. The traditional 1-on-1 consultation model was untenable. Therefore, we rapidly restructured our ID division to provide effective consultative services. We implemented a novel unit-based group rounds model that focused on delivering key updates to teams and providing unit-wide consultations simultaneously to all team members. Effectiveness of the program was studied using Likert-scale survey data. The survey captured data from the first month of the Detroit COVID-19 pandemic. During this period there were approximately 950 patients hospitalized for treatment of COVID-19. The survey of trainees and faculty reported an overall 95% positive response to delivery of information, new knowledge acquisition, and provider confidence in the care of COVID-19 patients. This showed that the unit-based consult model is a sustainable effort to provide care during epidemics.

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables.

Objective: This study aimed to develop a machine learning algorithm to identify key clinical measures to triage patients more effectively to general admission versus intensive care unit (ICU) admission and to predict mortality in COVID-19 pandemic. Materials and methods: This retrospective study consisted of 1874 persons-under-investigation for COVID-19 between February 7, 2020, and May 27, 2020 at Stony Brook University Hospital, New York. Two primary outcomes were ICU admission and mortality compared to COVID-19 positive patients in general hospital admission. Demographic, vitals, symptoms, imaging findings, comorbidities, and laboratory tests at presentation were collected. Predictions of mortality and ICU admission were made using machine learning with 80% training and 20% testing. Performance was evaluated using receiver operating characteristic (ROC) area under the curve (AUC). Results: A total of 635 patients were included in the analysis (age 60±11, 40.2% female). The top 6 mortality predictors were age, procalcitonin, C-creative protein, lactate dehydrogenase, D-dimer and lymphocytes. The top 6 ICU admission predictors are procalcitonin, lactate dehydrogenase, C-creative protein, pulse oxygen saturation, temperature and ferritin. The best machine learning algorithms predicted mortality with 89% AUC and ICU admission with 79% AUC. Conclusion: This study identifies key independent clinical parameters that predict ICU admission and mortality associated with COVID-19 infection. The predictive model is practical, readily enhanced and retrained using additional data. This approach has immediate translation and may prove useful for frontline physicians in clinical decision making under time-sensitive and resource-constrained environment.

The Mediterranean diet, plasma metabolome, and cardiovascular disease risk.

AIMS: To investigate whether metabolic signature composed of multiple plasma metabolites can be used to characterize adherence and metabolic response to the Mediterranean diet and whether such a metabolic signature is associated with cardiovascular disease (CVD) risk. METHODS AND RESULTS: Our primary study cohort included 1859 participants from the Spanish PREDIMED trial, and validation cohorts included 6868 participants from the US Nurses' Health Studies I and II, and Health Professionals Follow-up Study (NHS/HPFS). Adherence to the Mediterranean diet was assessed using a validated Mediterranean Diet Adherence Screener (MEDAS), and plasma metabolome was profiled by liquid chromatography-tandem mass spectrometry. We observed substantial metabolomic variation with respect to Mediterranean diet adherence, with nearly one-third of the assayed metabolites significantly associated with MEDAS (false discovery rate < 0.05). Using elastic net regularized regressions, we identified a metabolic signature, comprised of 67 metabolites, robustly correlated with Mediterranean diet adherence in both PREDIMED and NHS/HPFS (r = 0.28-0.37 between the signature and MEDAS; P = 3 × 10-35 to 4 × 10-118). In multivariable Cox regressions, the metabolic signature showed a significant inverse association with CVD incidence after adjusting for known risk factors (PREDIMED: hazard ratio [HR] per standard deviation increment in the signature = 0.71, P < 0.001; NHS/HPFS: HR = 0.85, P = 0.001), and the association persisted after further adjustment for MEDAS scores (PREDIMED: HR = 0.73, P = 0.004; NHS/HPFS: HR = 0.85, P = 0.004). Further genome-wide association analysis revealed that the metabolic signature was significantly associated with genetic loci involved in fatty acids and amino acids metabolism. Mendelian randomization analyses showed that the genetically inferred metabolic signature was significantly associated with risk of coronary heart disease (CHD) and stroke (odds ratios per SD increment in the genetically inferred metabolic signature = 0.92 for CHD and 0.91 for stroke; P < 0.001). CONCLUSIONS: We identified a metabolic signature that robustly reflects adherence and metabolic response to a Mediterranean diet, and predicts future CVD risk independent of traditional risk factors, in Spanish and US cohorts.

Machine-learning classification of texture features of portable chest X-ray accurately classifies COVID-19 lung infection.

BACKGROUND: The large volume and suboptimal image quality of portable chest X-rays (CXRs) as a result of the COVID-19 pandemic could post significant challenges for radiologists and frontline physicians. Deep-learning artificial intelligent (AI) methods have the potential to help improve diagnostic efficiency and accuracy for reading portable CXRs. PURPOSE: The study aimed at developing an AI imaging analysis tool to classify COVID-19 lung infection based on portable CXRs. MATERIALS AND METHODS: Public datasets of COVID-19 (N = 130), bacterial pneumonia (N = 145), non-COVID-19 viral pneumonia (N = 145), and normal (N = 138) CXRs were analyzed. Texture and morphological features were extracted. Five supervised machine-learning AI algorithms were used to classify COVID-19 from other conditions. Two-class and multi-class classification were performed. Statistical analysis was done using unpaired two-tailed t tests with unequal variance between groups. Performance of classification models used the receiver-operating characteristic (ROC) curve analysis. RESULTS: For the two-class classification, the accuracy, sensitivity and specificity were, respectively, 100%, 100%, and 100% for COVID-19 vs normal; 96.34%, 95.35% and 97.44% for COVID-19 vs bacterial pneumonia; and 97.56%, 97.44% and 97.67% for COVID-19 vs non-COVID-19 viral pneumonia. For the multi-class classification, the combined accuracy and AUC were 79.52% and 0.87, respectively. CONCLUSION: AI classification of texture and morphological features of portable CXRs accurately distinguishes COVID-19 lung infection in patients in multi-class datasets. Deep-learning methods have the potential to improve diagnostic efficiency and accuracy for portable CXRs.

Height, height-related SNPs, and risk of non-melanoma skin cancer.

BACKGROUND: Adult height has been associated with risk of several site-specific cancers, including melanoma. However, less attention has been given to non-melanoma skin cancer (NMSC). METHODS: We prospectively examined the risk of squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) in relation to adult height in the Nurses' Health Study (NHS, n=117 863) and the Health Professionals Follow-up Study (HPFS, n=51 111). We also investigated the relationships between height-related genetic markers and risk of BCC and SCC in the genetic data sets of the NHS and HPFS (3898 BCC cases, and 8530 BCC controls; 527 SCC cases, and 8962 SCC controls). RESULTS: After controlling for potential confounding factors, the hazard ratios were 1.09 (95% CI: 1.02, 1.15) and 1.10 (95% CI: 1.07, 1.13) for the associations between every 10 cm increase in height and risk of SCC and BCC respectively. None of the 687 height-related single-nucleotide polymorphisms (SNPs) was significantly associated with the risk of SCC or BCC, nor were the genetic scores combining independent height-related loci. CONCLUSIONS: Our data from two large cohorts provide further evidence that height is associated with an increased risk of NMSC. More studies on height-related genetic loci and early-life exposures may help clarify the underlying mechanisms.

Investigating the genetic relationship between Alzheimer's disease and cancer using GWAS summary statistics.

Growing evidence from both epidemiology and basic science suggest an inverse association between Alzheimer's disease (AD) and cancer. We examined the genetic relationship between AD and various cancer types using GWAS summary statistics from the IGAP and GAME-ON consortia. Sample size ranged from 9931 to 54,162; SNPs were imputed to the 1000 Genomes European panel. Our results based on cross-trait LD Score regression showed a significant positive genetic correlation between AD and five cancers combined (colon, breast, prostate, ovarian, lung; r g = 0.17, P = 0.04), and specifically with breast cancer (ER-negative and overall; r g = 0.21 and 0.18, P = 0.035 and 0.034) and lung cancer (adenocarcinoma, squamous cell carcinoma and overall; r g = 0.31, 0.38 and 0.30, P = 0.029, 0.016, and 0.006). Estimating the genetic correlation in specific functional categories revealed mixed positive and negative signals, notably stronger at annotations associated with increased enhancer activity. This suggests a role of gene expression regulators in the shared genetic etiology between AD and cancer, and that some shared variants modulate disease risk concordantly while others have effects in opposite directions. Due to power issues, we did not detect cross-phenotype associations at individual SNPs. This genetic overlap is not likely driven by a handful of major loci. Our study is the first to examine the co-heritability of AD and cancer leveraging large-scale GWAS results. The functional categories highlighted in this study need further investigation to illustrate the details of the genetic sharing and to bridge between different levels of associations.

T-Cell Acute Lymphoblastic Leukemia/Lymphoma (T-ALL) With Negative Screening Immaturity Markers and Gamma-Delta Receptor Expression.

T-cell acute lymphoblastic leukemia/lymphoma (T-ALL) is characterized by the combination of T-cell lineage and the presence of immaturity marker(s). Sometimes, the most common immaturity markers for initial flow cytometry screening in T-ALL may be negative, which can be a diagnostic pitfall. When a lack of common first-line immaturity markers is encountered in combination with gamma/delta T-cell receptor expression, a misdiagnosis of mature gamma-delta T-cell leukemia/lymphoma could be rendered. Here, we discuss two T-ALL cases with the absence of common flow cytometry immaturity markers and positive gamma/delta receptor expression.

Enhancing Suicide Risk Prediction With Polygenic Scores in Psychiatric Emergency Settings: Prospective Study.

BACKGROUND: Despite growing interest in the clinical translation of polygenic risk scores (PRSs), it remains uncertain to what extent genomic information can enhance the prediction of psychiatric outcomes beyond the data collected during clinical visits alone. OBJECTIVE: This study aimed to assess the clinical utility of incorporating PRSs into a suicide risk prediction model trained on electronic health records (EHRs) and patient-reported surveys among patients admitted to the emergency department. METHODS: Study participants were recruited from the psychiatric emergency department at Massachusetts General Hospital. There were 333 adult patients of European ancestry who had high-quality genotype data available through their participation in the Mass General Brigham Biobank. Multiple neuropsychiatric PRSs were added to a previously validated suicide prediction model in a prospective cohort enrolled between February 4, 2015, and March 13, 2017. Data analysis was performed from July 11, 2022, to August 31, 2023. Suicide attempt was defined using diagnostic codes from longitudinal EHRs combined with 6-month follow-up surveys. The clinical risk score for suicide attempt was calculated from an ensemble model trained using an EHR-based suicide risk score and a brief survey, and it was subsequently used to define the baseline model. We generated PRSs for depression, bipolar disorder, schizophrenia, suicide attempt, and externalizing traits using a Bayesian polygenic scoring method for European ancestry participants. Model performance was evaluated using area under the receiver operator curve (AUC), area under the precision-recall curve, and positive predictive values. RESULTS: Of the 333 patients (n=178, 53.5% male; mean age 36.8, SD 13.6 years; n=333, 100% non-Hispanic and n=324, 97.3% self-reported White), 28 (8.4%) had a suicide attempt within 6 months. Adding either the schizophrenia PRS or all PRSs to the baseline model resulted in the numerically highest discrimination (AUC 0.86, 95% CI 0.73-0.99) compared to the baseline model (AUC 0.84, 95% Cl 0.70-0.98). However, the improvement in model performance was not statistically significant. CONCLUSIONS: In this study, incorporating genomic information into clinical prediction models for suicide attempt did not improve patient risk stratification. Larger studies that include more diverse participants are required to validate whether the inclusion of psychiatric PRSs in clinical prediction models can enhance the stratification of patients at risk of suicide attempts.

Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

OBJECTIVE: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. METHODS: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. RESULTS: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. CONCLUSIONS: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.

Shared genetic architectures of educational attainment in East Asian and European populations.

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

Oropharyngeal Secondary Syphilis Mimicking Metastatic Lymphoma in an HIV-Positive Patient.

Syphilis is a bacterial infection commonly transmitted by sexual contact. It has variable manifestations and can mimic other disease processes or infections. This report presents the case of a 48-year-old HIV-positive male who was referred to our head and neck clinic with complaints of tonsillar hypertrophy and ulceration accompanied by a one-month history of ipsilateral cervical lymphadenopathy and facial pain in the setting of recent unexplained weight loss and abnormal radiographic imaging of the neck. In-office tonsillar biopsy and fine-needle aspiration of a neck mass revealed a non-diagnostic atypical lymphoid proliferation. Surgical pathology following an open biopsy in the operating room showed Treponema pallidum infection, which was diagnostic for secondary syphilis.

Diagnostic yield and repeat biopsies in rectal and nonrectal colorectal adenocarcinoma: Are we hedging on rectal biopsies?

Patients with rectal cancer undergo more repeat biopsies compared to those with nonrectal colon cancer prior to management. We investigated the factors driving the higher frequency of repeat biopsies in patients with rectal cancer. We compared clinicopathologic features of diagnostic and nondiagnostic (in regard to invasion) rectal (n = 64) and colonic (n = 57) biopsies from colorectal cancer patients and characterized corresponding resections. Despite similar diagnostic yield, repeat biopsy was more common in rectal carcinoma, especially in patients receiving neoadjuvant therapy (p < 0.05). The presence of desmoplasia (odds ratio 12.9, p < 0.05) was a strong predictor of making a diagnosis of invasion in both rectal and nonrectal colon cancer biopsies. Diagnostic biopsies had more desmoplasia, intramucosal carcinoma component and marked inflammation, and less low-grade dysplasia component (p < 0.05). Diagnostic yield of biopsy was higher for tumors with high-grade tumor budding, mucosal involvement by high-grade dysplasia/intramucosal carcinoma without low-grade dysplasia and diffuse surface desmoplasia irrespective of tumor location. Sample size, amount of benign tissue, appearance, and T stage did not affect diagnostic yield. Repeat biopsy of rectal cancer is primarily driven by management implications. Diagnostic yield in colorectal cancer biopsies is multifactorial and is not due to differing pathologists' diagnostic approach per tumor site. For rectal tumors, a multidisciplinary strategic approach is warranted to avoid repeat biopsy when unnecessary.

Vaccine coverage and factors associated with vaccine adherence in persons with HIV at an urban infectious disease clinic.

Information on vaccination rates and factors associated with adherence in persons with HIV (PWH) is limited. We report vaccine adherence in 653 adult PWH attending an urban Infectious Disease Clinic from January 2015 to December 2021. Vaccines evaluated included influenza, pneumococcal, tetanus, hepatitis A virus (HAV) and hepatitis B virus (HBV), human papillomavirus (HPV), and zoster vaccines. Vaccine reminders were triggered at every visit, and all vaccines were accessible in the clinic. The mean age was 50 y (±SD 13), male gender was 78.6%, and black race was 74.3%. The overall adherence to all recommended vaccines was 63.6%. Vaccine adherence was >90% for influenza, pneumococcal, and tetanus, >80% for HAV and HBV, and ≥60% for HPV and zoster vaccines. The main predictor of adherence to all vaccines was ≥2 annual clinic visits (odds ratio [OR] 3.45; 95% confidence interval [CI] 2.36-5.05; p < .001). Other predictors included an assigned primary care provider within the system (OR 2.89 [95% CI 1.71-5.00, p < .001]) and CD4 >200 cell/mm3 at entry into care (OR 1.91 [95% CI 1.24-2.94, p = .0003]). Retention in care combined with vaccine reminders and accessibility of vaccines in the clinic can achieve high vaccine uptake in PWH.

Boosting the power of genome-wide association studies within and across ancestries by using polygenic scores.

Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits. We also present a two-stage meta-analysis strategy whereby, in contributing cohorts, a PGS-adjusted GWAS is rerun using PGSs derived from a first round of a standard meta-analysis. On average, across traits, this approach yields a 1.26-fold increase in the number of detected associations (range 1.07- to 1.76-fold increase). Altogether, our study demonstrates the value of using PGSs to increase the power of GWASs in underrepresented populations and promotes such an analytical strategy for future GWAS meta-analyses.

Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits.

Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.

Tumor Stroma Ratio and Its Significance in Locally Advanced Colorectal Cancer.

Colorectal cancer is the third leading cause of cancer-related death, and its incidence is rising in the younger patient population. In the past decade, research has unveiled several processes (underlying tumorigenesis, many of which involve interactions between tumor cells and the surrounding tissue or tumor microenvironment (TME). Interactions between components of the TME are mediated at a sub-microscopic level. However, the endpoint of those interactions results in morphologic changes which can be readily assessed at microscopic examination of biopsy and resection specimens. Among these morphologic changes, alteration to the tumor stroma is a new, important determinant of colorectal cancer progression. Different methodologies to estimate the proportion of tumor stroma relative to tumor cells, or tumor stroma ratio (TSR), have been developed. Subsequent validation has supported the prognostic value, reproducibility and feasibility of TSR in various subgroups of colorectal cancer. In this manuscript, we review the literature surrounding TME in colorectal cancer, with a focus on tumor stroma ratio.