Are real-time assessments of self-reported experiences and wearable sensor data useful in predicting near-term suicidal thoughts?In this prognostic study with 102 participants, young adults completed 4 daily mobile-based surveys and wore a sensor wristband for 8 weeks after an emergency department visit. Models incorporating self-reported information from mobile-based assessments achieved good prediction of next-day suicidal ideation, whereas sensor-based assessments, alone or in combination with self-reported data, had poor prediction performance.These results suggest that self-reported risk factors have utility in identifying near-term suicidal thoughts, with implications for decision algorithms guiding risk monitoring and interventions during high-risk care transitions. This prognostic study investigates whether various combinations of self-reported ecological momentary assessments (EMAs) and sensor-based assessments are capable of predicting next-day suicidal ideation. Advancements in technology, including mobile-based ecological momentary assessments (EMAs) and passive sensing, have immense potential to identify short-term suicide risk. However, the extent to which EMA and passive data, particularly in combination, have utility in detecting short-term risk in everyday life remains poorly understood.To examine whether and what combinations of self-reported EMA and sensor-based assessments identify next-day suicidal ideation.In this intensive longitudinal prognostic study, participants completed EMAs 4 times daily and wore a sensor wristband (Fitbit Charge 3) for 8 weeks. Multilevel machine learning methods, including penalized generalized estimating equations and classification and regression trees (CARTs) with repeated 5-fold cross-validation, were used to optimize prediction of next-day suicidal ideation based on time-varying features from EMAs  and sensor data . Young adult patients who visited an emergency department with recent suicidal ideation and/or suicide attempt were recruited. Identified via electronic health record screening, eligible individuals were contacted remotely to complete enrollment procedures. Participants (aged 18 to 25 years) completed 14 708 EMA observations (64.4% adherence) and wore a sensor wristband approximately half the time (55.6% adherence). Data were collected between June 2020 and July 2021. Statistical analysis was performed from January to March 2023.The outcome was presence of next-day suicidal ideation.Among 102 enrolled participants, 83 (81.4%) were female; 6 (5.9%) were Asian, 5 (4.9%) were Black or African American, 9 (8.8%) were more than 1 race, and 76 (74.5%) were White; mean (SD) age was 20.9 (2.1) years. The best-performing model incorporated features from EMAs and showed good predictive accuracy , whereas the model that incorporated features from sensor data alone showed poor prediction . Sensor-based features did not improve prediction when combined with EMAs. Suicidal ideation-related features were the strongest predictors of next-day ideation. When suicidal ideation features were excluded, an alternative EMA model had acceptable predictive accuracy . Both EMA models included features at different timescales reflecting within-day, end-of-day, and time-varying cumulative effects.In this prognostic study, self-reported risk factors showed utility in identifying near-term suicidal thoughts. Best-performing models required self-reported information, derived from EMAs, whereas sensor-based data had negligible predictive accuracy. These results may have implications for developing decision algorithms identifying near-term suicidal thoughts to guide risk monitoring and intervention delivery in everyday life. Although many factors can increase risk for suicidal ideation and behavior, postacute care transitions, such as following emergency department (ED) or inpatient services, are linked to increased vulnerability.3 Identifying heightened suicide risk during high-risk periods will likely require approaches that are sensitive to its complex and time-varying nature. Prior research shows that single risk factors assessed weeks or months apart have a weak association with suicidal thoughts and behavior.5 Moreover, suicidal thoughts are far from static and fluctuate considerably within short intervals, from one day to the next or several hours apart.8 In line with national research priorities calling for improved understanding of short-term suicide risk,9 examining what combinations of risk factors may signal impending  suicidal thoughts is an important step toward informing short-term risk detection and intervention targets.Preventing suicide mortality, the second leading cause of death in adolescents and young adults,12 Given the complexity of suicide risk, additional research is needed to examine how time-varying affective, cognitive, and interpersonal experiences may come together, beyond individual associations, to confer short-term risk. Another key weakness of existing EMA studies lies in their overreliance on self-reporting, which may increase respondent burden and decreased engagement over time.14 Passive sensing can be used to collect objective data without requiring direct input from individuals, thus holding great potential in identifying suicidal ideation and behavior.16 For example, passive data could be used to unobtrusively detect processes that map onto suicide risk factors, such as sleep, distress captured by heart rate, social interaction patterns, or physical activity as proxy of withdrawal or mood.17 However, empirical evidence supporting the utility of passive data in predicting short-term suicidal ideation or behavior remains limited.Real-time assessments leveraging mobile and wearable sensor technologies offer unique opportunities to identify short-term suicide risk. Mobile-based ecological momentary assessments (EMAs), which rely on repeated measurement of self-reported experiences in daily life, are increasingly applied in suicide prevention research, with the majority of studies to date focusing on delineating proximal relationship between individual risk factors and suicidal ideation.18 others highlighted either lack of next-day association19 or an indirect link.20 Moreover, recent studies incorporating sensor-based assessment of sleep19 and physiological distress21 point to passive data having a relatively weaker association with near-term suicidal thoughts compared with self-reported information from EMAs. This suggests that the association between passive data and suicide risk-related outcomes may be more nuanced and warrants further investigation.To date, studies integrating EMA and passive sensing to identify short-term suicide risk have primarily focused on the association between sleep disturbance and suicidal ideation, with mixed results. While sensor-based assessments of sleep were shown to predict proximal (next-day) suicidal ideation by some,17 Investigating which combination of EMA and passive features are most promising in predicting proximal suicidal thoughts in everyday life is a critical step in the development of timely interventions that can address elevations in suicidal thoughts . To our knowledge, no prior studies have examined what combinations of EMA and passive predictors are optimal in identifying short-term suicidal ideation during high-risk care transitions.In this study of young adults with a recent ED visit, we expand on existing literature to examine the utility of sensor-based and EMA data in predicting short-term suicidal thoughts. Specifically, we applied machine learning models incorporating time-varying predictors from EMAs and a wearable sensor, separately and then in combination, to identify next-day suicidal ideation. We initially considered different theoretically informed and clinically informed predictors derived from EMAs  and from sensor-based assessments, measured with a commercial sensor wristband, that map onto relevant risk factors .22), administered routinely, and supplemented with EHR data. Exclusion criteria included altered mental state , cognitive impairment, transfer to jail or police custody, or other reasons preventing contact . Of the 911 individuals who had EHRs screened, 429 individuals (47.1%) met initial eligibility and were contacted by email and/or phone. Of these, 289 did not respond to contacts (67.4%), 4 (0.9%) responded but could not be enrolled , 16 (3.7%) declined participation, and 120 provided study consent (28.0%). A total of 110 participants were enrolled, with the analytic sample restricted to the 102 who continued in the study (3 withdrew) and had consecutive follow-up data . To describe sample characteristics, self-reported race and ethnicity data were obtained.Participants were ED patients (aged 18 to 25 years) recruited between June 2020 and May 2021. Electronic health records (EHRs) were screened for last-month suicide attempt and/or last-week suicidal ideation based on the Columbia-Suicide-Severity Rating Scale (C-SSRSTRIPOD) reporting guideline.23 Study consent and enrollment procedures, including enrollment in MetricWire and Fitbit mobile applications, were completed by telephone. Participants were subsequently mailed a sensor wristband (Fitbit Charge 3). Data collection began after all enrollment procedures were completed, a mean (SD) of 8.75 (3.71) days after ED visit. For 8 weeks, participants completed 4 EMAs between 9:30am and 9:30pm, randomly sampled within 4 time blocks , and were compensated up to $304 based on adherence. Participants were also asked to wear the study-provided sensor wristband, with weekly automated reminders to wear and charge the device. EMA completion across 102 participants was 64.4% (14 708 out of 22 848 possible). Sensor wristband adherence was 55.6%  for 98 participants with any sensor wristband data .The study was approved by the University of Michigan institutional review board and followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis  and, as part of the last EMA of the day, in reference to the entire day (daily-level ideation). A binary suicidal ideation indicator was obtained based on both observation-level and daily-level responses to capture any reported suicidal ideation each day.Participants indicated whether they experienced suicidal ideation and, if present, duration of ideation. The question was modeled after the C-SSRS items.24 Participants responded to items in reference to the last hour (at each EMA occasion) and in reference to the entire day (evening EMA) or prior day (morning EMA). Additional information is provided in eMethods 1 in Hopelessness was measured with an item modeled after the Brief Hopelessness Scale.25Connectedness and burdensomeness were each measured using items from the Interpersonal Needs Questionnaire (INQ).26Agitation was measured with an item modeled after the Brief Agitation Measure.27Worry and rumination were each assessed with an item derived from prior EMA studies of rumination and worry.28Self-efficacy to refrain from suicidal action was assessed with an item from the Self-Assessed Expectations of Suicide Risk Scale.29Positive and negative affect was measured with 5 items derived from the PANAS.31Thoughts about death frequency and duration together with suicidal ideation frequency and duration were measured with items based on the C-SSRS22; when thoughts of suicide were present, a follow-up item assessed ideation intensity. Based on items from prior EMA studies of suicide risk,32 we assessed presence of nonsuicidal self-injury (NSSI) and extent of engaging in coping behavior incorporating cognitive, noncognitive , and support-seeking strategies. Presence of a negative interpersonal event  was based on prior studies of interpersonal suicide warning signs.34Alcohol consumption, in standard drinks from none to 10 or greater, was measured with an item from a prior daily study of substance use35 and was categorized from none to 5 or more. Sleep quality was assessed with an item from the PROMIS sleep measure.36Self-reported constructs were assessed with single-item measures based on existing scales, adapted in prior EMA research to reduce response burden.Resting heart rate, Total steps, and Sleep duration . For a metric of daily-level Heart rate variability, we derived the root mean squared successive differences (RMSSD) of R-R interval estimates based on raw 1-minute heart rate. The average of the successive differences was computed over 5-minute intervals37 and subsequently averaged to calculate daily-level RMSSD. Additional details are in eMethods 2 in We collated data from participants’ sensor wristbands using Fitabase, a research platform that enables data transfer. The following daily-level metrics were obtained: t: (1) time-varying cumulative person-specific mean for each day t ; (2) deviation of day-level t observation from the time-varying cumulative person-specific mean; (3) previous day t observation; and (4) maximum within-day observation for each day t. Features were entered into prediction models.For each day, we constructed a set of features derived from constructs assessed multiple times with EMAs  as well as once-daily (evening EMA or morning EMA), in addition to features from sensor-based assessments. We calculated the following EMA and sensor-based features in a manner that preserved temporality of data, capturing information available up to day 38 using PGEE package in R.39 We used this regularization method because it is suitable for the longitudinal data and multiple features available.38 Features with nonzero coefficients  were included in CART models. Using the glmertree R package, we used a generalized linear mixed-effects model tree (GLMM tree) algorithm,40 which flexibly captures interactions and nonlinearity among the features, while accounting for the longitudinal  structure of the data. This approach iteratively estimates (1) the tree  given an offset of random effects and (2) the random effects given the structure of the tree. Models were built without missing data imputation. However, all models included a missingness indicator for each day . We also included time indicators . eMethods 3 and 4 in 41 The k-fold cross-validated procedure partitions the sample into k folds to test model performance on an independent data set, by reserving k − 1 folds for training and leaving the kth fold for testing for all folds k = 1, …, K. In this application of stratified blocked cross-validation, participants served as blocks (observations from a given participant are kept within the same fold), with individuals endorsing high and low proportion of ideation days kept balanced across the folds. As the primary prediction performance metric, we examined mean with corresponding standard error of cross-validated area under the receiver operating characteristic curve (AUC), which ranges from 0.5 (chance predictive accuracy) to 1.0 (perfect predictive accuracy). To compute variable importance from the mixed-effects CART, we used a variance-based method42 using the vip package in R.43 Analyses were performed in R version 4.2.2  from January to March 2023.To address the primary objective of predicting next-day suicidal ideation, we applied mixed-effects classification and regression trees (CARTs) using features from EMAs, sensor-based assessments, and their combination. Features were first selected via penalized generalized estimating equations (PGEE)Among 102 enrolled participants, 83 (81.4%) were female; 6 (5.9%) were Asian, 5 (4.9%) were Black or African American, 9 (8.8%) were more than 1 race, and 76 (74.5%) were White; the mean (SD) age was 20.9 (2.1) years . At indeOver the 8-week follow-up period, suicidal ideation was reported on 2197 EMA occasions (14.9%) by 89 participants (87.3%), with an additional 202 ideation disclosures reported in reference to the entire day (last survey of the day). Thus, any suicidal ideation was reported on 1346 observation days (33.4%) by 90 participants (88.2%). eFigure 1 in 44 to ensure congruent sample sizes with EMA models, mean (SE) results were similar for sensor-based  and combined  models. Additionally, we assessed model performance without features explicitly asking about thoughts of killing self. eFigure 4 in In this prognostic study of young adults, we applied machine learning methods to optimize prediction of near-term suicidal ideation following an ED visit. The goal was to examine whether and what combinations of self-reported EMA and unobtrusive sensor-based data identify next-day suicidal thoughts. Our main findings were that passive sensing data did not meaningfully contribute to predicting next-day suicidal thoughts, that strongest proximal predictors included self-reported suicidal thoughts, and that predictive performance was driven by near-term experiences that accumulate and those representing shifts in functioning.46 While more streamlined, reliance on self-report alone may require relatively more attention to engagement, particularly if EMA monitoring is used more frequently or over extended periods.Models with EMA features had best predictive accuracy (mean [SE] AUC of 0.84 [0.02]), whereas sensor-based data, whether alone or in combination with EMAs, showed poor prediction. It is important to emphasize that sensor-based assessments included indices of physiological arousal (heart rate) and regulation (activity and sleep), and it is possible that other passive data  may have yielded different results. Relatedly, it may be that constructs underlying these objective markers were relatively less important in predicting next-day ideation, as the goal was to identify features that optimize prediction of short-term suicidal thoughts. For example, neither sensor-based nor self-reported sleep were retained in selected models. Nevertheless, these results are consistent with recent studies integrating passive sensing suggesting weak associations with suicide risk-related outcomes, particularly over and above self-reported metrics.47 Our results additionally highlight that near-term suicidal thoughts can be adequately predicted when excluding features measuring thoughts of killing self. While predictive accuracy for this alternative model was relatively lower (mean [SE] AUC of 0.76 [0.02] vs 0.84 [0.02]), foregoing direct queries about suicidal thoughts may be more practical in some contexts or offer an acceptable option if there are concerns about disclosures.49 Importantly, results from either model  could be used to inform just-in-time adaptive interventions (JITAIs)51 which use decision rules to guide when real-time support should be provided. Understanding the conditions in which individuals are at increased risk for experiencing near-term suicidal thoughts is an important step in developing JITAIs that deliver support to prevent or ameliorate the risk.52The strongest predictors of next-day suicidal ideation were related to recent suicidal ideation, with key features reflecting end-of-day suicidal thoughts, time-varying cumulative suicidal thoughts, and change in suicidal thinking. The finding that suicidal ideation is a robust predictor of subsequent ideation in the near-term may not be surprising given its close relevance to the outcome and is consistent with other intensive longitudinal studies.24 and further highlights the importance of attending to how time-varying experiences not only change but also accumulate in the near-term to give rise to suicidal ideation in everyday life . Future research is needed to examine the benefits of modeling more rapid or extreme shifts in functioning together with dynamic experiences spanning over days prior. While much research to date has focused on the former, capturing real-time experiences across a spectrum of timescales could offer additional insights into how the risk for suicide is shaped in everyday life.In the current study, it was also notable that most important predictors incorporated different time scales, including end-of-day ratings, within-day averages, highest within-day scores (maximum), person-specific cumulative means, and deviations from cumulative means. The fact that prediction was driven by proximal experiences as well as their cumulative effect (time-varying cumulative means) is consistent with a study of high-risk adolescents55; however, early evidence suggests these tools can produce meaningful data related to different mental health outcomes.57 Nevertheless, this is an important consideration as technology is improving and given growing interest in wearable sensors with the practical advantage of larger-scale use. While our focus is on time-varying predictors, future extensions could investigate initial clinical and demographic data as well as optimal frequency of assessments to balance practical concerns  and predictive accuracy. Furthermore, the extent to which real-time data predict suicide attempts represents an important future direction. We selected PGEE and multilevel CART over alternative machine learning methods to maximize interpretability; however, future studies could apply different machine learning strategies to identify near-term risk. While we used repeated 5-fold cross-validation, an even more rigorous future validation should involve replication in an independent sample.This study had limitations. Generalizability of results is limited by the sample being composed of primarily female and White participants. Sensor-based assessments for sleep, activity, and heart rate were measured with emerging wearable sensor technology that may introduce more error than criterion standard laboratory assessmentsIn this prognostic study seeking to identify proximal predictors of suicidal thoughts following ED discharge, predictors derived from EMAs yielded the highest predictive accuracy, whereas passive predictors, alone or in combination with EMAs, had negligible predictive accuracy. Strongest predictors of next-day suicidal thoughts were related to prior suicidal ideation and encompassed different timescales. The fact that wearable devices did not outperform self-reporting in this and prior studies points to greater utility of EMAs in predicting short-term suicidal ideation, warranting additional examination in different samples. Additionally, these results have implications for developing decision rules, based on prediction algorithms, that guide the delivery of support in real time to prevent or ameliorate proximal risk for suicidal thoughts.


Tumor vasculature abnormality creates a microenvironment that is not suitable for anti-tumor immune response and thereby induces resistance to immunotherapy. Remodeling of dysfunctional tumor blood vessels by anti-angiogenic approaches, known as vascular normalization, reshapes the tumor microenvironment toward an immune-favorable one and improves the effectiveness of immunotherapy. The tumor vasculature serves as a potential pharmacological target with the capacity of promoting an anti-tumor immune response. In this review, the molecular mechanisms involved in tumor vascular microenvironment-modulated immune reactions are summarized. In addition, the evidence of pre-clinical and clinical studies for the combined targeting of pro-angiogenic signaling and immune checkpoint molecules with therapeutic potential are highlighted. The heterogeneity of endothelial cells in tumors that regulate tissue-specific immune responses is also discussed. The crosstalk between tumor endothelial cells and immune cells in individual tissues is postulated to have a unique molecular signature and may be considered as a potential target for the development of new immunotherapeutic approaches. Tumor vasculature is characterized by an abnormal vessel structure with impaired perfusion and is caused by an imbalance between pro- and anti-angiogenic signaling within tumors . An abnoVascular endothelial growth factor (VEGF) plays a significant role in tumor angiogenesis, and as such, there has been a focus on the development of VEGF pathway-targeted therapeutics with the aim of tumor angiogenesis inhibition by tumor nutrient deprivation . PatientTumor angiogenesis has been implicated in tumor growth and immunosuppression, as well as treatment response . Under nSeveral negative angiogenic factors have been identified, including thrombospondin-1 (TSP-1) , tissue As a growing tumor needs nutrients to meet its demand, cancer cells promote angiogenesis in favor of angiogenic stimulation by the release of pro-angiogenic factors to stimulate new vessel growth. In addition to directly supporting tumor growth, abnormal tumor vascular networks also regulate the tumor immune microenvironment by shaping a hypoxic, acidic, and oxidative TME to facilitate tumor progression.+ T cells suppression by Treg cells [Decreased local blood flow to the TME leads to hypoxia and inhibits leukocyte migration. In fact, the hypoxia-inducible transcription factors (HIFs), including HIF-1α, HIF-2α, and HIF-3α  mediate eg cells . Targetieg cells . These rA typical characteristic associated with abnormal tumor vessels is an acidic TME. Dysregulated energy metabolism results in the accumulation of lactate and a decrease in glucose concentration, resulting in tumor acidification . RegionsLow oxygen supply due to a lack of regular tumor vasculature creates a hypoxic TME. It has been shown that hypoxia increases ROS production mainly through tumor mitochondria, and the mitochondrial ROS can also stabilize HIF and activate the HIF-VEGF axis under hypoxia to promote angiogenesis, thereby fostering a TME with oxidative stress . EmerginThe chaotic tumor vasculature, which consists of vessels with abnormal morphology and high permeability, indicates dysregulated pathways governing vessel formation. This also compromises vascular function through an alteration of the interplay between endothelium and immune cells via multiple mechanisms and leads to tumor cells evading immune surveillance.The recruitment of immune cells from blood to inflamed tissues is dependent on their adhesion to ECs, followed by extravasation and infiltration into tissues. This process requires the expression of adhesion molecules, such as E-selectin, intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion protein 1 (VCAM-1), and VE-cadherin in ECs . HoweverAdditionally, pro-inflammatory signaling elicited by tumor ECs also plays a role in the regulation of immune cell recruitment. Dysfunctional ECs with gene expression profiles mimicking tumor ECs increased the NF-κB-p65 and pSTAT3 levels in the nucleus, suggesting the induction of pro-inflammatory signaling. Indeed, GM-CSF, IL-8, and IL-6 overexpression with reduced levels of anti-inflammatory cytokines, confirmed the pro-inflammatory phenotype in TME. Dysfunctional EC properties, including increased proliferation, permeability, and monocyte adhesion, have also been observed in this phenotype . A recenAlthough abnormal tumor vasculature inhibits leukocyte recruitment, tumor EC malfunction preferentially attracts and recruits pro-tumoral immune populations. For example, Clever-1, a scavenger and adhesion receptor, regulates monocytes/macrophages and Treg tumor infiltration when expressed in tumor ECs . Clever-+ T cells and an augmented anti-tumor immune response [+ T cell depletion hinders tumor blood vessel remodeling [In contrast to EC-mediated tumor recruitment of pro-tumoral immune cell types, the activation of ECs also induces anti-tumor T lymphocyte entry into tumors. EC stimulation with the agonist of innate immune sensor melanoma differentiation-associated protein 5 (MDA5) induced the production of type I interferon and T cell-recruiting chemokines, such as CXCL9 and CXCL10, leading to increased tumor-infiltrating CD8response . In addiresponse . Conversmodeling . These r+ T cells. More importantly, tumor-associated HEVs are predictive factors for a better response in patients with metastatic melanoma on combined treatment with anti-PD-1 and anti-CTLA-4 immunotherapy [+ T and NK cells, suggesting a mutual regulation of tumor vessels and anti-tumor immune effector cells [HEVs are specialized postcapillary venules that express sulfated sialomucins, which interact with L-Selectin/CD62L-expressed naïve lymphocytes, leading to migration into the lymph nodes . HEVs arotherapy . Furtherotherapy . Notablyotherapy . Consistotherapy ,89. Receor cells . Thus, sSince ECs are the interior lining of blood vessels, ECs are key components of the vascular system. Although these cells share some common features, they do not have homogeneous phenotypes across tissues or even within a single tissue . The fun+ T cell differentiation into mature effector T cells with tumoricidal activity, thereby suppressing anti-tumor immunity [ECs in tumors leverage distinct mechanisms to regulate tumor progression by modulating the immune microenvironment. LSECs have been reported to suppress the naïve CD8immunity . Expressimmunity . In lungimmunity . In addiimmunity , but alsimmunity . CollectGiven that abnormal vascular networks in tumor masses play a critical role in regulating the anti-tumor immune response, targeting tumor blood vessels to establish a favorable microenvironment for the accessibility of anti-tumor effector immune cells reveals an approach to improve the therapeutic efficacy of immunotherapy.The development of a normal vascular structure depends on the balance between angiogenic stimulators  and angiogenic inhibitors such as TSP-1. The imbalance resulting from excessive stimulators in the TME leads to the development of an abnormal and dysfunctional vasculature structure. Therefore, restoring the balance in the angiogenic process may restore the vessel structure in tumors. Since abnormal tumor vasculature results in the inhibition of immune cell infiltration, which leads to immunotherapy resistance, the normalization of tumor vascular networks to promote effector immune cell entry into tumors is a potential strategy to improve the efficacy of ICB . Given tChimeric antigen receptor (CAR)-based immunotherapy may be critical in overcoming the barriers derived from aberrant tumor vasculature to improve T cell tumor infiltration. CAR contains an extracellular domain from a single-chain variable fragment (scFv) antibody for antigen recognition linked to a cytoplasmic signaling domain, which consists of a costimulatory fragment to activate T cells when engaged with specific tumor antigens . Thus, t+ Treg cells, which were induced by anti-angiogenic treatments. Notably, the inhibition of TAMs reduced Treg cell infiltration [+Gr1+ myeloid cells with high gene expression, implicated in their mobilization and recruitment, play an important role in the anti-VEGF treatment resistance [Although VEGF blockade exhibits promising anti-cancer therapeutic efficacy, by normalizing tumor vasculature, the optimal time and dosage of anti-VEGF treatments have been proposed to be the determinants for effective vessel normalization ,117. Durltration , suggestltration ,124. Inhltration . Interesltration , suggestltration . In factltration . In addisistance . Collect+ T cell infiltration and simultaneously decreases tumor-infiltrating Tregs [+ T cells and markers related to activated immune responses, such as MHC molecules, effector T cells, and CX3CL1 chemokine [The immunosuppressive effects of tumor vascular networks provide a rationale for combining inhibitors targeting the tumor vasculature with immune checkpoint blockade for cancer treatment. Bevacizumab, a monoclonal antibody against VEGF as a cancer treatment, increases the dendritic cell (DC) population, improving their T cell stimulatory capacity . A recenng Tregs . These rng Tregs ,135,136.ng Tregs . Patientng Tregs . In accohemokine . ClinicaThe tumor vasculature comprises abnormal and dysfunctional blood vessel networks that results in an immunosuppressive microenvironment that supports tumor progression. The dual blockade of angiogenic activation and immune checkpoint-mediated inhibitory pathways has led to remarkable advances in the treatment of cancers. However, the potency of combination therapy may be hindered due to the heterogeneity of endothelial cells across and within tissues. Therefore, clinical manipulation of organ-specific ECs by targeting their unique molecular features may inform the development of novel strategies to maximize patient response to immunotherapy. In addition, long-term clinical trials are necessary for the evaluation of the durable clinical benefits of combination therapies for cancer treatment.


NOTE: the Github website will be released upon publication and the R package is available for review through google drive: https://drive.google.com/drive/folders/1KgecmUoon9-h2Dg1rPCyEGFPOp28Ols3?usp=sharingMulti-omics sequencing is expected to become clinically routine within the next decade and transform clinical care. However, there is a paucity of viable and interpretable genome-wide modeling methods that can facilitate rational selection of patients for tailored intervention. Here we develop an integral genomic signature-based method called iGenSig-Rx as a white-box tool for modeling therapeutic response based on clinical trial datasets with improved cross-dataset applicability and tolerance to sequencing bias. This method leverages high-dimensional redundant genomic features to address the challenges of cross-dataset modeling, a concept similar to the use of redundant steel rods to reinforce the pillars of a building. Using genomic datasets for HER2 targeted therapies, the iGenSig-Rx model demonstrates stable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We expect that iGenSig-Rx as a class of biologically interpretable multi-omics modeling methods will have broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx.


High titers of anti-NMDAR1 IgG autoantibodies were found in the brains of patients with anti-NMDAR1 encephalitis that exhibits psychosis, impaired memory, and many other psychiatric symptoms in addition to neurological symptoms. Low titers of blood circulating anti-NMDAR1 IgG autoantibodies are sufficient to robustly impair spatial working memory in mice with intact blood-brain barriers (BBB). On the other hand, anti-NMDAR1 autoantibodies were reported to protect against neuronal excitotoxicity caused by excessive glutamate in neurological diseases. Activation of extrasynaptic NMDARs is responsible for neuronal excitotoxicity, whereas activation of synaptic NMDARs within the synaptic cleft is pro-survival and essential for NMDAR-mediated neurotransmission. Unlike small IgG, IgM antibodies are large and pentameric (diameter of ~30 nm). It is plausible that IgM anti-NMDAR1 autoantibodies may be restricted to bind extrasynaptic NMDARs and thereby specifically inhibit neuronal excitotoxicity, but physically too large to enter the synaptic cleft (width: 20–30 nm) to suppress synaptic NMDAR-mediated neurotransmission in modulation of cognitive function and neuronal pro-survival signaling. Hence, blood circulating anti-NMDAR1 IgM autoantibodies are both neuroprotective and pro-cognitive, whereas blood circulating anti-NMDAR1 IgG and IgA autoantibodies are detrimental to cognitive function. Investigation of anti-NMDAR1 IgM autoantibodies may open up a new avenue for the development of long-lasting preventive and therapeutic IgM anti-NMDAR1 autoantibodies that protect from neuronal excitotoxicity in many neurological diseases and psychiatric disorders. Consistently, ~0.1%–0.2% of blood circulating antibodies were reported to nonspecifically cross the BBB regardless of antibody IgG or IgM isotype [High titers of anti-NMDAR1 IgG autoantibodies are found in the brains of patients with anti-NMDAR1 encephalitis that exhibits psychosis, impaired memory, and many other psychiatric symptoms in addition to neurological symptoms . Mice caze d = 2. in mice  isotype . Interes isotype –9. HowevNeuronal excitotoxicity is the primary mechanism for neuronal injury in neurological diseases  (e.g., sAnti-NMDAR1 autoantibodies in blood were reported to provide protections against neuronal excitotoxicity caused by excessively released glutamate in stroke and epilepsy , but werSuppressing glutamate excitotoxicity has been the focus of drug discovery for neurological diseases, neurodegenerative diseases, and psychiatric disorders. Current small molecule NMDAR anatgonists including memantine lack sufficient specificity to target extrasynaptic NMDARs for suppression of excitotoxicity without also inhibiting synaptic NMDARs that are pro-survival and essential for cognition. Psychotomimetic side effects are common for these small molecules. In contrast, IgM anti-NMDAR1 autoantibodies cannot access synaptic NMDARs but specifically inhibit extrasynaptic NMDARs to suppress glutamate excitotoxicity, indicating a superior specificity. Furthermore, IgM anti-NMDAR1 autoantibodies may be pro-cognitive in healthy persons, since suppression of extrasynaptic NMDARs by low doses of memantine improves cognition in both humans and animals. At last, in contrast to small molecule NMDAR anatgonists that have a half-life of a few hours, IgM antibodies have a half-life of ~ 5–8 days in human blood. Therefore, IgM anti-NMDAR1 autoantibodies may provide a feasible early prevention against excitotoxicity from stroke or traumatic brain injury where the BBB is disrupted, long-lasting neuroprotection in Alzheimer’s disease where the BBB may be compromised, and cognitive enhancement in schizophrenia and other psychiatric disorders where a baseline level of the IgM autoantibodies crossovering the BBB may be beneficial.


FABP4, fatty acid synthase, FASN; and stearoyl-CoA desaturase, SCD) in the ribeye (Longissimus thoracis et lumborum) muscle of Tattykeel Australian White (TAW) lambs fed fortified omega-3 diets and correlations with fatty acids. To answer the research question, “are there differences in the expression of lipogenic genes between control, MSM whole grain and omega-3 supplemented lambs?”, we tested the hypothesis that fortification of lamb diets with omega-3 will lead to a down-regulation of lipogenic genes. Seventy-five six-month old TAW lambs were randomly allocated to the (1) omega-3 oil-fortified grain pellets, (2) unfortified grain pellets (control) or (3) unfortified MSM whole grain pellets diet supplements to generate three treatments of 25 lambs each. The feeding trial lasted 47 days.The concept of the functional nutritional value of health-beneficial omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA) is becoming a phenomenon among red meat consumers globally. This study examined the expressions of three lipogenic genes  whole grain diet compared to the omega-3 and control diets. A negative correlation was observed between FASN gene expression and intramuscular fat (IMF), eicosapentaenoic acid (EPA), total polyunsaturated fatty acids (PUFA), omega-6 polyunsaturated fatty acids (n-6 PUFA) and monounsaturated fatty acids (MUFA). The FABP4 gene expression was positively correlated (P < 0.05) with EPA and docosahexaenoic acid (DHA).From the Kruskal-Wallis test, the results showed a striking disparity in lipogenic gene expression between the three dietary treatments in which the FABP4 and FASN genes perform an important role in the biosynthesis of fatty acids in the ribeye muscle of TAW lambs, and supplementary diet composition is an important factor influencing their expressions.Taken together, this study’s results suggest that The online version contains supplementary material available at 10.1186/s12864-023-09771-x. However, the fold changes in gene expression did not follow a normal distribution pattern, hence we used a non-parametric approach in our analysis instead of an individual-level model. Also, the samples emanated from lambs of the same age and breed, hence animal variability would have been at a minimum, if not negligible. Therefore, we used the quantile regression methodology instead of the classical linear regression, because the quantile regression analysis is robust to outliers and enables the estimation of all the conditional quantiles of the response variable instead of the mean as depicted below:As gene expression data can exhibit variability and may not always follow a normal distribution, a non-parametric approach provides a suitable alternative for hypothesis testing. Therefore, in this study, data on gene expression, fat melting point (FMP), intramuscular fat (IMF), and fatty acids profiles of TAW MARGRA lamb were analysed using nonparametric statistics in R version 4.0.1. Kruskal-Wallis tests with Bonferroni’s adjusted p-values were used to test for differences in fold changes among dietary treatments. Relationships between variables were explored using Spearman correlation analysis. The effect of gene expression (fold change) on FMP, IMF, and fatty acids was investigated using a quantile regression model. Quantile regression, an extension of linear regression, is often preferred to linear regression because it is robust to outliers  and thusWhere The comparison between quantile regression and linear regression models is depicted in the Supplementary Fig. Below is the link to the electronic supplementary material.Supplementary Material 1


Escherichia coli TGT exchanges the target G on anRNA of interest for chemically modified preQ1 substrates linked toa small-molecule reporter such as biotin or a fluorophore. While extendingthe substrate scope of RNA transglycosylases to include DNA wouldenable numerous applications, it has been previously reported thatTGT is incapable of modifying native DNA. Here, we demonstrate thatTGT can in fact recognize and label specific DNA substrates. Throughiterative testing of rationally mutated DNA hairpin sequences, wedetermined the minimal sequence requirements for transglycosylationof unmodified DNA by E. coli TGT. Controllingsteric constraint in the DNA hairpin dramatically affects labelingefficiency, and, when optimized, can lead to near-quantitative site-specificmodification. We demonstrate the utility of our newly developed DNA-TAGsystem by rapidly synthesizing probes for fluorescent Northern blottingof spliceosomal U6 RNA and RNA FISH visualization of the long noncodingRNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1).The ease and convenience of the DNA-TAG system will provide researcherswith a tool for accessing a wide variety of versatile and affordablemodified DNA substrates.Bacterial tRNA guanine transglycosylases (TGTs) catalyzethe exchangeof guanine for the 7-deazaguanine queuine precursor, prequeuosine1(preQ1). While the native nucleic acid substrate for bacterial TGTsis the anticodon loop of queuine-cognate tRNAs, the minimum recognitionsequence for the enzyme is a structured hairpin containing the targetG nucleobase in a “UGU” loop motif. Previous work hasestablished an RNA modification system, RNA-TAG, in which  In addition,a number of alternative techniques exist that rely on chemical orenzymatic modification of nucleobases or the sugar backbone.11 Techniques that employ enzymes offer several advantages over thoserelying on chemical modification as they occur in mild and aqueousconditions, are precisely targeted, and are typically very efficient.The deoxyribose backbone of DNA affords aqueous stability that islacking in its RNA counterpart, and as such, chemically functionalizedsingle-stranded DNAs (ssDNA) are widely used in biotechnology. Currentmethods for enzymatic modification of DNA include the 3′ insertionof modified nucleobases using terminal deoxynucleotidyltransferase(TdT), the 5′ insertion of modified phosphate groups, and thetransfer of click handles to a target adenosine (mTAG).14 Unfortunately, the small-molecule substrate tolerance and precisionof insertion for enzyme-mediated ssDNA modification strategies hasbeen limited. The improved ability to site-specifically label ssDNAwith enzymes in mild aqueous conditions could have significant applicationsgiven the broad use of ssDNA in diagnostics, therapeutics, materialsresearch, imaging, detection, and chemical barcoding.17Probe-modified oligonucleotides have widespreadapplications inimaging, diagnostics, nanotechnology, and medicine.19 TGTs catalyze the exchangeof guanine for 7-deazaguanine derivatives on the anticodon loop ofqueuine-cognate tRNAs.20 These enzymaticmodifications are present across all three kingdoms of life, differingslightly in their small-molecule and tRNA substrate counterparts.It had previously been shown that the entire tRNA structure is notnecessary for the enzymatic activity of Escherichiacoli TGT toward RNA substrates, but rather, the minimumrecognition sequence is a short 17-nucleotide hairpin , which contains a uridine-flankedtarget guanine in its loop.21 In RNA-TAG, E. coli TGT recognizes this minimal hairpin incorporatedinto an RNA of interest and catalyzes the exchange of the target guaninefor synthetic derivatives of the natural preQ1 substrate that areconjugated to functional groups such as fluorophores or affinity ligands.18 We have demonstrated the utility of RNA-TAGin a range of applications including RNA biotinylation for proteomicsstudies, controlling mRNA translation, and light-activated CRISPRgene editing in cells.27Previously, our group developed RNA transglycosylationat guanosine(RNA-TAG) to site-specifically label RNA using bacterial tRNA guaninetransglycosylase (TGT).20 This suggests that the lackof the exocyclic 2′ hydroxyl groups on the backbone of DNAsubstrates would not impair E. coli TGT recognition or activity. However, previous work had deemed E. coli TGT incapable of acting on unmodified DNAsubstrates and showed that unnatural nucleobase substitutions (T →dU) of the thermally stabilized 4 base-pair extended-stem mini helix(dECYMH) were required for efficient recognition.28Extending the RNA-TAG system to work on DNA would enable one-step,site-specific labeling of ssDNA substrates, increasing the accessibilityof small-molecule-modified DNA oligonucleotides and further enablingapplications of ssDNA in nanotechnology, therapeutics, and basic research.The exchange of guanine for preQ1 by TGT is electronically dependenton the guanine nucleobase and the endocyclic oxygen of the ribosebackbone.E. coli TGT. Indeed, through iterative testing of rationally designed DNAhairpin sequences, we were able to reveal the minimal sequence requirementsfor DNA substrate recognition by the enzyme (S3), enablingdevelopment of a technique we term DNA transglycosylation at deoxyguanosine,or DNA-TAG. DNA-TAG enables the one-step, site-specific labeling ofssDNA substrates bearing a minimal 17-nucleotide hairpin motif withsynthetic preQ1 substrates conjugated to functional groups such asbiotin and fluorophores . However, it was also reported that when all “T”nucleobases in the hairpin were replaced with “U”, theenzyme was able to recognize and form the covalent intermediate witha deoxyribose-based substrate (dUdECYMH).28 While we confirmed only trace modification (less than 5% by densitometry)of dECYMH with our preQ1-biotin probe . For all DNA substrate modification experiments, we reliedon an established oligonucleotide gel shift assay.27 Observation of an upward gel shift of theproduct in relation to the starting material reports an increase inmass from the enzymatic exchange of guanine for a preQ1-biotin small-moleculereporter conjugate in which all U residues were replaced with 5-meU (rT). Surprisingly,we found that this substrate had a nearly quantitative turnover, similarto the wild-type RNA hairpin  of the extended-stem tRNAin probe 2A,B, theonjugate 2B,C. It  hairpin 2B,C, indTyr, tRNAHis, tRNAAsp, and tRNAAsn. While eachof these four tRNAs have the same “UGU” minimal recognitionelement, the rest of the anticodon loop sequence varies. Therefore,we decided that hairpin substrates based on these alternative tRNAswould be a good starting point for engineering a novel DNA-TAG substrate.Adapting the already established nomenclature, and to account formutations, we refer to the 17-nucleotide wild-type hairpins as dECY-0, dECH-0, dECD-0, and dECN-0, corresponding tothe hairpins derived from tRNATyr, tRNAHis,tRNAAsp, and tRNAAsn, respectively. Mutant hairpinsare referred to using a sequential numbering scheme based on theirparent hairpin . All hairpins were treatedwith E. coli TGT and preQ1-biotin andthe resulting products analyzed via urea polyacrylamide gel electrophoresis(PAGE) gel shift. Interestingly, both the dECH-0 and dECD-0, hairpinsshowed an appreciable increase in TGT labeling activity compared totheir dECY-0 counterpart, with labeled product increasing from ∼5to ∼40% by densitometry (S1). Wenote that dECN-0 shows a shift indicative of degradation rather thanmodification, a phenomenon that is consistent for most oligos bearinga 3′T .While the data was included here for completeness, it is outside thescope of this work and will not be discussed further. The approximateincrease in labeling of the dECH-0 and dECD-0 substrates to 40% waspromising, but not comparable to the near-quantitative labeling observedwith RNA-TAG.18 To further improve theDNA-TAG substrate, we next sought to determine the importance of thestems and/or loops for each of the tRNA-derived hairpins. We designedcomposite substrates, swapping the stems and loops of all four cognateDNA analogs. All hairpins with the aspartate-based loop (dECD) demonstratedlabeling of over 40%, with the histidine stem-aspartate loop substratereaching over 50% by densitometry . The results of this experiment suggested thatwhile both the stem and the loop sequences contribute to the abilityof TGT to turnover a given substrate, the loop sequence plays themore critical role in substrate compatibility, in line with previousobservations during biochemical and structural studies of the enzymeand tRNA substrate.29Based on these observations, we hypothesized that,rather thana fundamental incompatibility of TGT with DNA oligonucleotides, theseeming inability of TGT to modify DNA was steric and could be overcomeby using an alternative DNA substrate. Previous studies have focusedon derivatives of the 17-nucleotide ECY-A1 and 25-nucleotide ECYMHhairpins which are derived from the anticodon loop of the tyrosinetRNA containing the GUA anticodon. However, all four tRNAs with GUNanticodons are substrates for TGT, including tRNAitometry 2D and S1Figure S2). These experiments confirmed the importanceof the loop and led us to design and test another 31 mutants . This round of mutants produced optimalDNA-TAG substrates and revealed the minimal substrate loop requirementfor efficient recognition and modification of DNA by TGT to be eitherYTGTCCY or YTGTYCC, where Y represents smaller pyrimidine bases (Cor T), further corroborating our hypothesis that steric effects playa major role in substrate recognition . Nearly all of the anticodon-basedhairpins were appreciably labeled regardless of the stem sequence,apart from some apparent multilabeling and degradation products, similarto that seen for dECN-0. Ultimately, our data suggest that, with theright loop, the stem is far less important, as 16 DNA hairpins withdifferent stem sequences are nearly quantitatively labeled by E. coli TGT .We decided to move forwardwith the dECH-0 substrate for furtherdevelopment and designed nine hairpin mutants . We analyzedthe kinetics of preQ1-biotin insertion by TGT and found that modificationwas nearly complete after 4 h . To confirm the result of our gel shift assay, we verified labelingwith liquid chromatography–mass spectrometry analysis (LCMS).The LC trace showed a clear product peak with the expected mass, matchingthe conclusion derived from urea PAGE gel shift analysis . To confirm that the base being exchangedby the enzyme was the expected G residue, we tested whether dECH-10ΔC(CTGGATTCTCCTTCCAG) could be modified with TGT andfound that the mutant hairpin remained unlabeled .While any of the 16 substratesare valid candidates for use withDNA-TAG, we performed subsequent experiments with dECH-10 and confirmed with high-resolution mass spectrometry .Having optimized DNA hairpin labeling byTGT, we sought to explorethe utility of our newly developed DNA-TAG system. A key benefit ofRNA-TAG is the wide substrate tolerance of the enzyme for preQ1 derivatives.We compared the substrate tolerance for DNA modification and foundthat, similar to RNA, TGT can modify the dECH-10 substrate with avariety of functional preQ1 probes in high yield. We used the establishedgel shift assay to assess TGT’s ability to modify dECH-10 withvarious probes: preQ1-biotin, TAMRA, Cy5, Alexa Fluor 647, Alexa Fluor488, and Silicon Rhodamine . Additionally, we tested the ability of DNA-TAG to insert multiplelabels into a single DNA oligonucleotide. Indeed, TGT modificationof transcripts bearing two hairpins either in tandem at the same end or separated at oppositeends  was observed via gel shift and confirmedwith liquid chromotography–electrospray ionization-time offlight-mass spectometry (LC-ESI-TOF-MS) . Our experiments demonstrated that DNA-TAG has the potentialto be used in a range of applications as it is compatible with severalsmall-molecule probes varying in size and overall charge. Furthermore,DNA-TAG can be used for labeling DNA oligonucleotides at a locationof choice, both singly or in tandem.DNA-TAG modificationof DNA requires that a TGT recognition harpinbe appended to the DNA of interest. We purchased 59 mer DNA constructscontaining 5′, 3′, and internal hairpins and testedthe extent of their labeling. All three hairpin adducts were efficientlylabeled using the preQ1-biotin probe  U6 RNA or crude total RNA from U2OScellular extracts were separated via urea PAGE in dilution series.The gels were transferred to a nitrocellulose membrane, incubatedwith the SiR-labeled antisense probe, and the signal was detectedvia fluorescence scanning. The DNA-TAG generated U6 Northern blotprobe was successful in detecting the U6 RNA in a dose-dependent mannerwith a reliable R2 value when analyzedvia linear fit for both IVT and cellular U6 RNA .38 Imaging signalscan be increased with a variety of strategies, including increasingthe number of probes or reporter molecules39 and using turn-on intercalating dyes, such as thiazole orange, tominimize background.17 A standard smFISHprobe set is made up of 30–48 distinct probes which tile thetarget transcript.40 Given the large numberof probes required, probe set synthesis can be very costly and needsto be high-yielding. While labeled probe sets can be purchased commerciallyor generated using TdT along with a limited set of accepted ddUTP-fluorophores,DNA-TAG offers a unique strategy for quickly generating affordableprobe sets with a wide small-molecule substrate scope.41 We tested the ability of DNA-TAG to generatea fluorescent-tiled antisense oligo probe set against metastasis-associatedlung adenocarcinoma transcript 1 (MALAT1).Next, we used DNA-TAG to generate probe sets forsingle-moleculeFISH (smFISH), a powerful technique that has been widely used to visualizespecific DNA and RNA species in cells using tiled antisense probeslabeled with fluorescent reporters.42 Using the Stellaris probe design tool, a setof 48 unique antisense oligonucleotide probe sequences was generatedto target MALAT1 and appended with DNA-TAG hairpins. We designed twodistinct probe sets containing either one or two TGT modificationsites. To maintain consistency between the sets, both constructs hadtwo hairpins, with the single modification set containing one hairpinbearing the “TGT” minimal recognition element and theother containing the inactive “TCT” minimal recognitionelement (Tables S7 and S8). The probeswere individually purchased from a commercial vendor (Integrated DNATechnologies), pooled, and fluorescently labeled using TGT and preQ1-TAMRA.The combined oligonucleotide probe set was then purified by spin filtration.U2OS cells were treated with either a DNA-TAG-labeled TAMRA probeset, an orthogonal Quasar 570-labeled commercial probe set (Stellaris),or a combination of the two. As expected for MALAT1, treatment withall probe sets resulted in punctate stains localized in the nucleiof the cells, with both DNA-TAG labeled probe sets colocalizing withthe Stellaris probe set . The latter observation may be due to the well-knownself-quenching of TAMRA and further optimization of fluorophore spacingmay result in improved signals.43 A singleexperimental design was shown here; however, our strategy should beamenable with a variety of amplification strategies, for instance,by including additional hairpins on each probe to increase the fluorescencesignal. We note that the additional bulk of the TAG hairpin and spacingbetween probes should be considered when using this technology forFISH.MALAT1 is an abundantlong non-coding RNA (lncRNA) found in thenuclei of cells that is implicated in cancers including those affectingthe lungs, breasts, prostate, pancreas, glia, and blood.robe set 4. The si45Beyond being central to life, nucleic acidshave proven to be invaluabletools in both basic and biomedical research. Harnessing the unparalleledprogrammability afforded by oligonucleotides requires tools to installfunctional handles or facilitate detection. Furthermore, increasingthe availability, versatility, and diversity of oligonucleotide toolsis critical to the continued advancement of their use in multiplefields. We have shown that bacterial TGT enzymes, which normally modifytRNA, can be repurposed to site-specifically label DNA. Enzymaticmodification using the DNA-TAG methodology facilitates the one-step,site-specific insertion of a variety of functional small moleculesinto ssDNA substrates of interest for downstream applications. Thissystem is compatible with both internal and terminal insertions ofthe hairpin sequence into DNAs of interest, is tolerant of tandemmodifications, and works with a variety of small-molecule substrates.We believe that future studies will lead to further optimization ofthe labeling conditions, reducing the time and costs of the reaction.While the possible biological relevance of our findings is unclear,it is worth noting that recent studies have discovered 7-deazaguaninemodifications in phage DNA.DNA-TAG allowsan inexpensive and straightforward method by whichresearchers can quickly label several DNA oligos in a single step,either simultaneously or in parallel, followed by short spin columnpurification. We have demonstrated that, with a one-time upfront costof materials needed for small-molecule probe synthesis and proteinexpression, DNA-TAG offers researchers a versatile, affordable meansto generate fluorescent DNA probes of their choice from commerciallyavailable DNA oligonucleotides for applications including fluorescentNorthern blotting and smFISH.


SARS-CoV-2 is known to manifest a robust innate immune response. However, little is known about inflammatory influences from maternal SARS-CoV-2 infection or maternal mRNA vaccination upon the fetus. In addition, it is unknown if Vitamin D deficiency influences fetal homeostasis or if an anti-inflammatory mechanism to the development of possible innate cytokines or acute phase reactants by the maternal/fetal dyad, in the form of cortisol elevations, occur. In addition, effects on Complete Blood Count (CBC) are not known.To evaluate the neonatal acute phase reactants and anti-inflammatory responses after maternal SARS-CoV-2 disease or mRNA vaccination.n = 97) were collected consecutively, and were categorized into 4 groups; no SARS-CoV-2 or vaccination exposure (Control), Vaccinated mothers, maternal SARS-CoV-2 disease positive/IgG titer positive fetal blood, and maternal SARS-CoV-2 positive/IgG titer negative fetal blood. SARS-CoV-2 IgG/IgM/IgA titers, CBC, CRP, ferritin, cortisol, and Vitamin D were obtained to examine the possible development of an innate immune response and possible anti-inflammatory response. Student's t-test, Wilcoxon rank-sum, and Chi-squared with Bonferroni corrections were used to compare groups. Multiple imputations were performed for missing data.Samples and medical records reviews from mother/baby dyads (p = 0.001) and SARS-CoV-2 positive/IgG positive (p = 0.009) as compared to the control group suggesting an attempt to maintain homeostasis in these groups. Measurements of ferritin, CRP, and vitamin D did not reach statistical significance. CBC showed no variation, except for the mean platelet volume (MPV), which was elevated in babies whose mothers were vaccinated (p = 0.003) and SARS-CoV-2 positive/IgG positive (p = 0.007) as compared to the control group.Cortisol was higher in babies of both mothers who were vaccinated (Acute phase reactant elevations were not noted in our neonates. Vitamin D levels were unchanged from homeostatic levels. Cord blood at birth, showed Cortisol and MPV higher in vaccinated and SARS-CoV-2 IgG positive mother/baby dyads as compared to the Control group, indicating that possible anti-inflammatory response was generated. The implication of possible inflammatory events and subsequent cortisol and/or MPV elevation effects upon the fetus after SARS-CoV-2 disease or vaccination is unknown and merits further investigation. To dateProtection from COVID-19 infection is an important part of prenatal care. Neonates must rely on both innate immune responses such as cytokine interferon type 1, which has anti-viral properties, the success of maternal defeat of the infection, and maternally acquired transplacental antibodies for protection from disease . MultiplWith the activation of inflammation and stress, it is likely the mother may mount an anti-inflammatory response to resolve these influences during both infection and vaccination. The neonate also possesses several hormones to affect immune homeostasis if influenced by infection or maternal immune responses. Vitamin D and cortisol are the predominate hormones helping to maintain neonatal anti-inflammatory stance and reestablishing homeostasis. Vitamin D is frequently placental in origin, and cortisol levels in the mother are known to be partially placentally transferred to the fetus –21. In aWe hypothesize that innate immune response in both vaccination and COVID-19 disease may increase neonatal exposure to innate cytokines, yielding an inflammatory response by generation of acute phase reactants with associated homeostatic generation of anti-inflammatory elevation of cortisol and Vitamin D levels. In this study, we will assess this hypothesis by evaluating cord blood acute phase reactants ferritin and CRP and any inflammatory influence on the CBC. In addition, we will test whether a corresponding compensatory elevation in cord blood anti-inflammatory hormones of cortisol and Vitamin D in the setting of maternal COVID-19 disease or post-immunization is found.2.This prospective cohort study sought to collect cord blood samples with either documented maternal SARS-CoV-2 exposure and/or vaccination in pregnancy or mothers who lacked prior SARS-CoV-2 exposure and/or vaccination in pregnancy, however only 97 were found to meet our inclusion criteria during our period of sample collection. Samples were collected consecutively, at Cabell Huntington Hospital's labor and delivery department in Huntington, West Virginia, United States, followed by medical chart reviews of the mother and neonate charts to extract all pertinent data. Exclusion criteria were mothers who were transferred from an outside facility, infants born with congenital defects or disease, any mother/infant dyad who was missing critical information for our dataset, and any mother/infant dyad whose placenta didn't yield enough cord blood for testing. Additional inclusion criteria included neonates delivered after 32 weeks gestational age to ensure transference of immunoglobulins. Dyads that failed screening for technical reasons  or arrival of the research team in an insufficient time to collect blood due to expected clotting of fetal vessels were not recorded. One-hundred-six samples were collected, and the resulting 97 samples from the cohort of mother/baby dyads were divided into four groups; Control: SARS-CoV-2 negative mothers with no history of vaccination and SARS-CoV-2 IgG negative fetal blood; Vaccinated: vaccinated mothers/IgG positive fetal blood. Unvaccinated/SARS-CoV-2(+)/IgG(+): non-vaccinated SARS-CoV-2 positive/IgG positive fetal blood; Unvaccinated/SARS-CoV-2(+)/IgG(−): non-vaccinated SARS-CoV-2 positive/IgG negative fetal blood. Maternal and neonatal demographics, including birthweights and clinical variables were obtained from a medical records review. A minimum of 6 cc umbilical cord blood was obtained in the first few  minutes after placental delivery. A portion of serum from the fetal blood was sent to Cincinnati Children's Hospital Nephrology Lab, Cincinnati, Ohio, United States, for analysis of SARS-CoV-2 specific IgG, IgM, and IgA antibody titers. SARS-CoV-2 specific IgA was obtained to exclude the possibility of maternal blood contamination, as immunologically, the neonate cannot generate IgA immunoglobulin until 2–3 weeks after birth; at the same time, these IgA levels are amply found in the maternal bloodstream , 25. CBC2.1.t-test and Welch's t-test were used for comparing parametric continuous data between study groups. The Wilcoxon rank-sum test was used to compare non-parametric continuous data between study groups. Pearson's chi-squared test and Fisher's exact test were used for comparing proportional differences in categorical data between study groups. Bonferroni correction was conservatively applied for all multiple comparisons; hence, we considered statistical significance to be a p-value < 0.0167. Multiple imputations, using univariate interval regression models, were used for missing CBC data that were missing completely at random (MCAR). Data were evaluated for any gross deviations from statistical testing assumptions.Descriptive statistics were used to characterize infant and maternal metrics. Mean (standard deviation), and median  were used for parametric and non-parametric data, respectively. The Modified Levene's test was used to compare the variance of continuous data between study groups. Student's 3.A total of 106 cord blood samples were collected from May 2021 to August 2022 after placental delivery. Nine samples were excluded due to missing data, which prevented them from being assigned to a study group. The final study population included 97 samples that were divided into four groups based on maternal SARS-CoV-2 exposure/vaccination and the presence or absence of neonatal SARS-CoV-2 specific IgG.p = 0.005). Respiratory distress syndrome (RDS) was lower in the Unvaccinated/SARS-CoV-2(+)/IgG(+) group compared to the Control group . Neonatal abstinence syndrome (NAS) was lower in the Unvaccinated/SARS-CoV-2(+)/IgG(+) group compared to the Control group . In addition, a greater proportion of vaccinated mothers intended to exclusively breastfeed compared to unvaccinated mothers (Control) (83% vs. 53% p = 0.001).All vaccinated mothers received mRNA vaccine as they were the only regionally available vaccines during the period of study collection. Vaccination and SARS-CoV-2 exposure data are included in p = 0.033); however, this was not statistically significant after the Bonferroni corrections (p = 0.001) and the Unvaccinated/SARS-CoV2(+)/IgG(+)  compared to the Control group (p = 0.002) and Unvaccinated/SARS-CoV2(+)/IgG(+)  compared to the Control group, it did not rise to the level associated with a change due to inflammation , as well as our infants born to mothers who had COVID-19 several weeks prior to delivery, mounting a measurable IgG response (Unvaccinated/SARS-CoV-2(+)/IgG(+)). In these two groups, cortisol was 100% and 60% higher as compared to our Control group respectively. There is evidence that maternal cortisol can cross the placenta and is also thought to be a marker of neonatal stress suggesting that this hormone is critical to maintaining maternal/fetal homeostasis . Our eleand IL-6 . Our novOur prospective, proof of concept, single-centered study, was small. A larger sample size in the future would enable more robust findings; however, to account for our sample size, we utilized conservative effect estimates calculated using Bonferroni corrections to limit the risk of type I statistical errors. Future studies would be illuminating to include maternal blood sampling to verify cytokine and complement levels and maternal cortisol findings to corroborate our study. Due to the rapid onset of the COVID-19 pandemic, multiple health systems and electronic medical records were not prepared to document patient encounters during the pandemic. As such, our documentation relied on an EMR review of PCP records for testing results or vaccination cards provided by mothers who brought this data to the delivery room. Key strengths of our study were the completeness of our dataset and requiring limited utilization of imputations for missing data. Our novel study demonstrated a statistically significant increase in cortisol which is needed to control neonatal inflammation, but acute phase reactant elevations were not noted. As such, our study may not have accounted for early timing to detect very early innate immune responses and subsequent production of ferritin or CRP yet yielded the downstream anti-inflammatory result of elevated neonatal cortisol levels. In addition, future studies of mothers with long COVID-19 might determine if the development of heightened cortisol levels is due to smoldering inflammation.We hypothesized in this novel study that either COVID-19 disease or the mRNA vaccine might have inflammatory effects on fetal indices of inflammation such as CBC, ferritin, and CRP. While the CBC showed no variation, but for MPV, the clinical implications of MPV variation at birth are not known. In this novel study attempting to define inflammatory and anti-inflammatory changes notable to a fetus after maternal COVID disease or vaccination, we found that cortisol levels were elevated in these dyads. This finding is important because cortisol may be an important anti-inflammatory response to the innate immune system activation associated with COVID-19 disease or the mRNA vaccine. In addition, a cortisol elevation may provide a hypothesis for previous research determining the lack of fetal gene expression of innate cytokines during maternal COVID-19 infection. Future studies of both maternal and fetal cytokine and complement responses to disease and mRNA vaccination will help elucidate how mother/infant dyads achieve homeostasis in the face of inflammatory challenges.


Physio-psycho-socioeconomical health comprehensively declines during aging, the complexity of which is challenging to measure. Among the complexity, multiple chronic disorders continuously cumulated during aging, further aggravating the challenge.A population-based survey on Comprehensive Ageing Health Assessment was conducted in older adults (age >  = 60) enrolled from hospital settings and community settings in 13 working centers in six subnational regions in China. Cross-sectional datasets of 8,093 older participants with approximately complete assessment results were collected for the present analysis. Individual’s multi-disease or multi-symptom was respectively scored by summing coexistent multiple diseases or multiple symptoms by respective weighting efficient for Self-Rated Health (SRH). Individual’s age-dependent health decline was further summed of four SRH-weighted scores for daily function , physical mobility (an average of three metrics), cognitive function  and mental being  plus multi-disease score (MDS) and multi-symptom score (MSS).Multi-disease patten among 18 diseases or multi-symptom pattern among 15 symptoms was latent-clustered in the older adults, the optimal outcome of which was categorized into high, moderate or low aging-associated clusters, respectively. Percentage distribution was compared between overall health decline score and multi-disease pattern cluster or multi-symptom patten cluster. A new variable of difference between MDS and MSS (hereinafter terming DMM) that displayed linear variation with socioeconomic factors was further fitted using multilevel regression analyses by substantial adjustments on individual confounders (level-1) and subnational region variation (level-2).Consistent gradient distribution was shown between health decline and multimorbidity pattern cluster in the older adults. DMM was found linearly varied with personal education attainment and regional socioeconomic status. Using optimally fitted stratification of DMM , an independent U-shaped interrelated tendency was shown between health decline, multi-disease and multi-symptom, which could be well explained by regional disparities in socioeconomic status.Newly developed metrics for age-dependent health decline and aging-associated multimorbidity patten were preliminarily validated from within. The new variable of optimally fitted categorization of DMM might function as a practical indicator aiding in improving the cost-effectiveness and reduce inequity of healthcare delivery for older adults in developing countries.The online version contains supplementary material available at 10.1186/s12939-023-02024-z. The age-dependent multidimensional health decline is challenging to assess due to its internal complexity and contextual cumulation –3. AgeinA national face-to-face survey of Comprehensive Assessment of Ageing Health was launched in China in October 2011 using a goal-oriented scale that combined dozens of widely used scales. The compound scale comprised eight components, including demographics, physio-pathological status (coexistence of claimed multi-disease and multi-symptom), daily life function, lifelong lifestyles, cognitive status, mental being, socioeconomic status and healthcare utilization based on the framework of Comprehensive Geriatric Assessment (CGA)  was weighted by Self-Rated Health (SRH) using a dichotomized outcome (positive/negative) in the present population-based older samples . The oddAge-dependent health decline was scored by summing a function decline scored by activities of daily living (ADL), a physical mobility decline scored by an average time for three mobility tests , a cognitive decline measured by the Mini-Mental State Examine (MMSE) and a likelihood of depression using the geriatric depression scale (GDS), and a coexistence of multimorbidity by scored multi-disease adding scored multi-symptom. Except for the MDS and MSS, the remaining scores could be directly obtained from the national dataset. For an old adult, each domain decline was weighted by his/her SRH prior to summation. Also, normalization was employed prior to summing to avoid bias , 19.The national and subnational health decline score was profiled by age, gender, setting, residency, educational attainment and personal income, two latter variables of which are regarded as conventional proxies of socioeconomic status during ageing , 21. TheThe national and subnational multi-disease (using MDS) and multi-symptom (using MSS) profiles were profiled by age, gender, setting, residency, educational attainment and personal income. Data mining was employed to reveal a novel variable of the difference between MDS and MSS, herein termed DMM (MDS—MSS). The distributed correlation was profiled between DMM and each of three socioeconomic variables individually and regionally.The national multi-disease pattern clusters and multi-symptom clusters were categorized into three aging-associated subgroups, i.e., low aging-associated cluster, moderate aging-associated cluster and high aging-associated cluster, for multi-disease patten or multi-symptom pattern respectively.The percentage distribution was compared between the subpopulations categorized by age-dependent health decline score and the subpopulations categorized by aging-associated cluster for multi-disease pattern or for multi-symptom pattern.Using datamining, a newly variable of difference between MDS and MMS arose, which displayed a socioeconomic interrelationship. Using two-level regression model, associated multi-disease score as well as multi-symptom score was “disentangled” by substantially adjusting low-level individual confounders  and high-level regional variation. The DMM was iteratively fitted from its lowest value of -0.04, to its highest value of + 0.04 at different intervals. The optimal fit was considered when the independent interrelationship between age-related health decline and multi-disease score as well as multi-symptom score could be well explained.Data mining was conducted step by step according to the respective references. The flow diagram for the stepwise roadmap is shown in Fig. The present data analysis used datasets from 8,093 older participants with high-quality data. The majority 77.41%) were registered as urban residents based on the Chinese Hu-Kou system, indicating the rapid urbanization in China. In addition, as the National Project was carried out in respective metropolitan centers, only a small proportion of rural elderly individuals could be successfully enrolled from remote rural communities, which unavoidably led to sampling bias. Consistently, the present representative aging population was characterized by a high proportion of people who had a high education level . Notably, we included only those within the 90% quartile of claimed income in the current datasets, as the claimed income varied substantially, with few reporting incomes beyond “reasonable range”. Therefore, the sample size is slightly smaller for the income quartile. The sociodemographic characteristics of the elderly population in China are outlined in Table % were reThe sex-dependent prevalence of 33 age-related conditions (18 common chronic diseases and 15 common chronic symptoms) was initially profiled with the respective Odds Ratio (OR) weighted by SRH, and the overall findings were consistent with previous studies . A notabUsing the obtained MDS and MSS, national and sub-national multi-disease and multi-symptom status were profiled by age, gender, setting, residency, educational attainment and personal income Table . An age-To validate the present developed metrics on age-related health decline, multimorbidity was re-assessed by highly heterogeneous multimorbidity patterns in the same older samples via latent-based analysis. BIC-optimized clustering yielded four multi-disease pattern and four multi-symptom pattern as respectively optimal cluster for chronic coexistent pattern harboring the highest probability of coexistence in the present old population , a moderate health decline (-1.34≤score≤-1.03) and the largest health decline (score>-1.03). These three subpopulations were further compared by age, gender, setting, residency, educational attainment and personal income , indicating a low cost-effectiveness of health-care overutilization. In contrast, regions with a higher MSS than MDS reflected the presence of inadequate healthcare, which commonly occurred in relatively deprived regions, suggesting a markedly aggravated health decline (P<0.001). Similarly, an MDS similar to the MSS might indicate appreciated healthcare, which occurred in economically moderately developed regions (P=0.002), leading to cost-effective performance in healthcare delivery. Therefore, we considered the interval of DMM as optimal (DMM=0.02). Using DMM=0.02 as categorization, health decline score, multi-diseases score and multi-symptom score linearly increased with advanced age, particularly in the old-old subpopulation. Moreover, the most marked increase in health decline was seen in the hospital setting comparing with its counterpart, strongly validating the multilevel model.As we revealed that the difference between MDS and MSS (DMM) is closely linked to socioeconomic variables, we used multilevel regressions to determine if an optimal DMM categorization aiding in disentangling the complicated interrelationship among health decline, multi-disease score and multi-symptom score. After multiple fitting iterations, an optimal stratification of DMM (DMM=0.02) was acquired, based on which an intriguingly independent U-shaped interrelated tendency between health decline, MDS and MSS was revealed Fig.  by substP>0.05). The complicated decline was explained by the notably increased multi-symptom score (P<0.05) which could not be well attenuated by mildly decreased multi-disease score (P<0.05). High social stresses, ongoing intense lifestyle and high expectancy on wellbeing might increase the mental burden and SRH-adjusted symptoms in the older adults in highly industrialized metropolitan, with overall health decline intact. For Northeast China with relatively lower socioeconomic status comparing to the reference region, the health decline was significantly mitigated, largely explained by both decreased multi-symptom score and decreased multi-disease score. It was noted that the minus magnitude of health decline was much higher than that summing minus magnitude of multi-disease and multi-symptom, indicating a high cost-effectiveness of healthcare access. For the Northwest China with much lower socioeconomic status comparing to the reference region, the health decline was significantly aggravated, largely explained by considerably high multi-symptom score, paradoxically with decreased multi-disease score. It indicates an attributable insufficiency of healthcare access lacking disease awareness, with high likelihood of no management. The outline of the U-shaped tendency indicated that the overall health decline was exponentially functioned with the multiple coexistence of multi-diseases and multi-symptoms. Due to the present analysis, the optimal interval of DMM could not only help to disentangle the complexity from within the contextual complexity of health decline, but offer an alternative scale for public health policies to reduce healthcare access inequity in the old adults. China is experiencing undergoing inequality in healthcare delivery and access [In this study, we attempted to disentangle the complexity of age-dependent multi-dimensional health decline, particularly focusing on multimorbidity (multi-disease and multi-symptom) characterized as one of core constituted domains of health, in a population-based sample harboring 8,093 older Chinese adults from six subnational regions. For overall health decline, a widely used outcome of SRH, which exhibits an independent correlation with each of the health domains , was appd access , 40, demThere are several weaknesses in the study. First, the analysis was conducted based on cross-sectional datasets with no cohort validation, as the complexity of multidimensional health decline with contextual variation highly hampered this. Second, the sample size was relatively small regarding to the largest ageing population in the world. Third, other ageing-related health burdens, such as disability, were not considered because very few disabled individuals were found in the original datasets. Fourth, the lifelong risk factors were not cumulated into the burden of multimorbidity coexistence, as it was an age-attenuated  and age-Two metrics were obtained for age-dependent health decline and for aging- associated multimorbidity pattern in the older adults in China, being validated from within. It was revealed a new variable of difference between multi-disease score and multi-symptom score characterized with a socioeconomic trait. An independent U-shaped tendency was shown between health decline, multi-disease and multi-symptom at an optimally fitted categorization of DMM in older Chinese adults, which was well explained by regional socioeconomic healthcare delivery inequities. The categorization of an optimal DMM might be a practical indicator to estimate whether an ageing-related healthcare inequality exist and how healthcare delivery be cost-effective in ageing developing countries.Additional file 1: Supplementary File S1. The compound scales designed for the National project for Comprehensive Ageing Health Assessment (CAHA) in 2012 (English Version) A compound scale comprising eight components was constructed based on Comprehensive Geriatrics Assessment (CGA) framework by a panel of multidisciplined experts for a national population-based survey. English version was particularly translated from the original Chinese version for the present publication. Supplementary File S2. The national sampling profile in Comprehensive Ageing Health Assessment (CAHA) in China, 2012 A goal-guided national project was carried out in six subnational regions covering approximately two-third of Chinese population and nearly 80% of China’s GDP in 2012 http://data.stats.gov.cn.The central cities in these regions included three centrally-administrated municipalities  and four capital cities . A constructed scale was used for the national assessment with Department/Ward of 13 top hospitals. The distribution details of sampling numbers and settings are presented in Supplementary File S2. Additional file 2.