Circular ribonucleic acids (circRNAs) are novel non-coding RNAs that emanate from alternative splicing of precursor mRNA in reversed order across exons. Despite the abundant presence of circRNAs in human genes and their involvement in diverse physiological processes, the functionality of most circRNAs remains a mystery. Like other non-coding RNAs, sub-cellular localization knowledge of circRNAs has the aptitude to demystify the influence of circRNAs on protein synthesis, degradation, destination, their association with different diseases, and potential for drug development. To date, wet experimental approaches are being used to detect sub-cellular locations of circular RNAs. These approaches help to elucidate the role of circRNAs as protein scaffolds, RNA-binding protein (RBP) sponges, micro-RNA (miRNA) sponges, parental gene expression modifiers, alternative splicing regulators, and transcription regulators. To complement wet-lab experiments, considering the progress made by machine learning approaches for the determination of sub-cellular localization of other non-coding RNAs, the paper in hand develops a computational framework, Circ-LocNet, to precisely detect circRNA sub-cellular localization. Circ-LocNet performs comprehensive extrinsic evaluation of 7 residue frequency-based, residue order and frequency-based, and physio-chemical property-based sequence descriptors using the five most widely used machine learning classifiers. Further, it explores the performance impact of K-order sequence descriptor fusion where it ensembles similar as well dissimilar genres of statistical representation learning approaches to reap the combined benefits. Considering the diversity of statistical representation learning schemes, it assesses the performance of second-order, third-order, and going all the way up to seventh-order sequence descriptor fusion. A comprehensive empirical evaluation of Circ-LocNet over a newly developed benchmark dataset using different settings reveals that standalone residue frequency-based sequence descriptors and tree-based classifiers are more suitable to predict sub-cellular localization of circular RNAs. Further, K-order heterogeneous sequence descriptors fusion in combination with tree-based classifiers most accurately predict sub-cellular localization of circular RNAs. We anticipate this study will act as a rich baseline and push the development of robust computational methodologies for the accurate sub-cellular localization determination of novel circRNAs. Non-coding ribonucleic acids (ncRNAs) are now considered important regulatory elements instead of junk sequences . Recent Although circRNAs in mammalian, plant viroids, and yeast cells were discovered around more than 50 years ago , they weStudies have proved that circRNAs can act as RNA-binding protein (RBP) sponges, micro-RNA (miRNA) sponges, parental gene expression modifiers, alternative splicing regulators, and transcription regulators, even a small number of circRNAs can be transformed into peptides or proteins as well ,13,14,15High-throughput sequencing analysis indicates that circRNAs reside in different sub-cellular compartments and primarily perform a variety of regulatory functions by co-localizing . Like meWet-lab experiments are still the most common approaches used to identify sub-cellular localization of different sub-types of ncRNAs. For instance, immunofluorescence confocal microscopy, immunoprecipitation, subcellular fractionation  are beinEmergence of diverse metathesauruses including RNALocate , EnsemblDevelopment of a benchmark circRNA sub-cellular localization prediction dataset using public RNALocate database  which isA comprehensive performance analysis of residue frequency, residue order and frequency, and residue physicochemical property-based sequence descriptors is performed to find an appropriate standalone sequence descriptor for circular RNA sub-cellular localization prediction.A detailed performance impact of K-order sequence descriptor fusion is performed by ensembling similar as well dissimilar genres of statistical representation learning approaches to reap the combined benefits in order to investigate whether sequence descriptor fusion significantly optimizes the statistical representation of circRNA sequences and which K-order sequence descriptor fusion manages to capture more discriminative residue distribution important for sub-cellular localization prediction.Extensive empirical evaluation of 5 different generative, discriminative, and tree-based classifiers using various sequence descriptors is performed to investigate which type of classifier extracts a residue correlation that is important to accurately predict circular RNA sub-cellular localization.An end-to-end computational framework (Circ-LocNet) that explores the performance of seven different standalone sequence descriptors, second-order sequence descriptor fusion, third-order sequence descriptor fusion, and so on all the way up to seventh-order sequence descriptor fusion with the five most widely used machine learning classifiers in order to determine an appropriate combination of sequence descriptor and machine learning classifier for circular RNA sub-cellular localization prediction.Development and deployment of the very first interactive and user-friendly circRNAs sub-cellular localization prediction platform.Considering the downfalls of experimental approaches, there is a lack of computational circRNA sub-cellular localization approaches, and there is also the fact that sub-cellular localization prediction approaches developed for other ncRNAs  cannot bThis section illustrates the performance produced by proposed computational framework Circ-LocNet over the newly developed benchmark dataset using the seven most widely used sequence descriptors and five machine learning classifiers. Further, it describes the performance impact of K-order sequence descriptor fusion where it illustrates the best performance achieved by second-order, third-order, and going all the way up to seventh-order combination of sequence descriptor across five different machine learning classifiers.From all seven different sequence descriptors, five sequence descriptors  achieve peak performance figures with Random Forest, whereas two sequence descriptors  achieve peak performance with XGBoost classifier, while TriMonoKgap, DiMonoKgap, EIIP, ZCurve, and PseudoKNC sequence descriptors produce the worst performance with Naive Bayes classifier; however, K-mer and RCKmer manage to produce decent performances with Naive Bayes classifier. Further, the majority of sequence descriptors produce a decent performance with Adaboost classifier, whereas no sequence descriptor manages to cross the performance of 50% with SVM classifier across both evaluation metrics.In addition, to analyze the true negative rate of the seven different sequence descriptors with respect to five distinct machine learning classifiers, the performance trends of all sequence descriptors are mapped in a specificity spider chart .Analysis of the polygon revealing specificity performance figures  shows thIn order to assess the overall effectiveness of seven sequence descriptors across five different machine learning classifiers mainly by taking all four true positives, true negatives, false positives, and false negatives into account, the performance trends of all sequence descriptors are mapped to MCC  spider cAssessment of the spider chart  revealinFurther, to demonstrate the overall effectiveness of each sequence descriptor by aggregating their performance impact across all five machine learning classifiers, average specificity  and MCC In addition, considering the unique functional paradigm of seven different sequence descriptors, we analyze the impact of different sequence descriptors over the generalizeability of a variety of machine learning classifiers using area under receiver operating characteristic (AU-ROC). Using One-Versus-All setting, receiver operating characteristics (ROC) curves along with peak AU-ROC scores produced by frequency based and physico-chemical property-based sequence descriptor with optimal parameters against five machine learning classifiers are shown in Critical analysis of ROC curves indicates that both K-gap based sequence descriptors show promising performance with decision tree-based classifiers including AdaBoost, XGBoost, Random Forest and discriminative classifier SVM, whereas a combination of K-gap based sequence encoding schemes with generative classifier NB does not prove particularly fruitful. Among all, DiMonoKgap in combination with AdaBoost achieves slightly better degree of separability (86%) as compared to 85% degree of separability achieved by TriMonoKgap using XGBoost classifier. Further, most machine learning classifiers manage to attain a decent AU-ROC score of 80% using K-gap based sequence descriptor. Similarly, all 3 K-mer based sequence descriptors also achieve a better degree of separability with decision tree-based classifiers and discriminative classifiers as well as producing the lowest AU-ROC scores with generative classifier NB. RCKmer manages to cross the mark of 80% using two classifiers, Random Forest and AdaBoost, and K-mer performs even better by achieving higher degree of separability across most machine learning classifiers and crossing the figure of 80% using XGBoost, Random Forest, and AdaBoost classifiers. K-mer attains a peak AU-ROC score of 85% which supersedes RCKmer peak score by 1%. Among all K-mer-based sequence descriptors, PseudoKNC achieves highest degree of separability across most machine learning classifiers, attaining a peak AU-ROC score of 90% with AdaBoost classifier and 86% with XGBoost classifier. Comparing fold curve and physico-chemical property-based sequence descriptors across all five machine learning classifiers reveals that EIIP attains better AU-ROC scores across most classifiers as compared to Z-Curve. Just like other sequence descriptors, EIIP manages to produce promising performance with decision tree-based and discriminative classifiers, achieving the peak AU-ROC of 88% using AdaBoost classifier, whereas Z-Curve crossed the figure of 80% using two decision-tree-based and one generative classifier (NB). Z-Curve attains the peak AU-ROC score of 88% using AdaBoost and the only sequence descriptor which produces a promising performance using NB classifier. Z-Curve in combination with NB produces an AU-ROC score of 87% which outperforms other sequence descriptor-based generative classifier performances by 7%. Among all combinations of sequence descriptors and machine learning classifiers, PseudoKNC achieves the highest AU-ROC score using AdaBoost classifier followed by 88% achieved by Z-Curve and EIIP.To summarize, TriMonoKgap marks the best performance with Random Forest and XGBoost classifiers across most evaluation metrics, whereas Kmer and RCKmer produce better aggregated performance computed using five different classifiers.Statistical representation learning paradigms of residue frequency-based, residue order and frequency-based, and physico-chemical properties-based sequence descriptors largely differ from one another in terms of coverage of residue contextual information, ability to capture residue semantic relatedness, short and long range dependencies, extraction of discriminative features, and residue correlation distribution important to predict sub-cellular localization of circRNAs. We were inspired by the fact that ensemble learning effectively handles bias-variance trade-off to largely improve the robustness and performance of predictive modelling by strategically combining multiple models. In order to generate optimized representation of circRNA sequences, instead of solely relying on standalone sequence descriptors, we perform comprehensive experimentation with K-order sequence descriptor fusion where we integrate similar as well dissimilar genre of sequence descriptors to reap the combined benefits. Mainly, we generate second-order, third-order, and go all the way up to seventh-order combinations of sequence descriptors to comprehensively investigate whether sequence descriptor fusion manages to optimize representation of circRNAs as well as which K-order sequence descriptor fusion most effectively captures the characteristics of sequence residues important to improve circRNA sub-cellular localization prediction performance.To perform K-order sequence descriptor fusion, using seven different sequence descriptors, all possible K-order combination of sequence descriptors are generated and fed to five different machine learning classifiers. For instance, for second-order sequence descriptor fusion, from seven sequence descriptors, every sequence descriptor is combined with only one other sequence descriptor, whereas in third-order sequence descriptor fusion, every sequence descriptor is combined with two other sequence descriptors, and so on. As we have performed experimentation with seven different sequence descriptors, the value of K ranges from two tp seven.To better illustrate the results, In a nutshell, the idea of K-order sequence descriptor fusion proves fruitful as Random Forest classifier manages to outperform the accuracy of 69% and F1-score of 63% achieved through standalone sequence descriptors by 1% through fusing TriMonoKgap and PseudoKNC sequence descriptors, while tree-based machine learning classifiers  and SVM classifier achieve peak performance with the combination of heterogeneous sequence descriptors. Naive Bayes classifier achieves peak performance with the combination of quite similar sequence descriptors. Overall, most machine learning classifiers mark better performance with second-order and third-order sequence descriptor fusion. More specifically, Random Forest and Naive Bayes classifier achieve better performance with second-order sequence descriptor fusion, whereas XGBoost, AdaBoost, and SVM classifier achieve better performance with third-order sequence descriptor fusion.Considering the fact that circRNAs perform a myriad of regulatory functions mainly by co-localizing, accurate determination of circRNA sub-cellular localization is indispensable to understand their association with diverse physiological and pathological processes as well as their potential for biomarker development. A significant number of computational approaches have been developed for sub-cellular localization of different ncRNAs  which primarily leverage a unique combination of a sequence descriptor and machine learning classifier. Evidently, raw sequence-based computational approaches are more scalable, efficient, and appropriate for large-scale determination of ncRNA sub-cellular localization as they do not rely on any expensive resources . However, no researcher has assessed whether residue distribution of circRNA sequences is also informative enough for the determination of circRNA sub-cellular localization. Further, which genre of sequence descriptors and machine learning classifier are more suitable to capture residue semantic relatedness, short- and long-range residue dependencies, positional invariance of residues, and other residue characteristics important for circRNAs sub-cellular localization prediction has not been determined.In this regard, the proposed Circ-LocNet framework explores the performance potential of the seven most extensively used sequence descriptors using five different machine learning classifiers under the hood of two different settings. In the setting of using a standalone sequence descriptor in combination with a machine learning classifier, residue frequency-based sequence descriptors ) most effectively characterize circRNA sequences and tree-based machine learning classifiers best exploit the residue hidden correlations to predict sub-cellular localization of circRNAs. Across all K-gap and K-mer based sequence descriptors, performance is improved with the increase of K-mers or K-gap values. Most residue frequency-based sequence descriptors achieve higher performance with five mers or five gaps. In other settings, the predictive performance of tree-based machine learning classifiers is further improved by K-order sequence descriptor fusion. It is seen that second-order or third-order fusion of heterogeneous sequence descriptors generates more discriminative statistical representation circRNA sequences.Furthermore, considering the small size of the benchmark circRNA dataset and the fact that deep learning classifiers perform better with large training data, in this study, we have performed experimentation with only traditional machine learning classifiers. Besides this, the reasons for not comparing the performance of circular RNA subcellular localization prediction model with subcellular localization prediction models developed for other non-coding RNAs are manifold. First, unlike most non-coding RNA sequences, circRNA sequences are not linear by nature. Moreover, circRNA sequences differ from other non-coding RNA sequences in terms of sequence lengths, distribution of nucleotides, etc. . BesidesIn a nutshell, we consider this a pioneering work of benchmarking the performance of different genre sequence descriptors and machine learning classifiers that will open new horizons for the computational determination of circRNA sub-cellular localization.https://circ_rna_location_predictor.opendfki.de/) and can be used to find sub-cellular localities of circRNAs of different species as well as to validate experimentally identified sub-cellular localities by only using raw circRNA sequences. Unlike web servers developed to categorize biomolecules, find sub-cellular locations, and to predict intera-specie or inter-specie interaction, this web server allows the users to train and optimize different machine learning classifiers from scratch, and perform inference on novel circRNA sequences belonging to existing or new specie under different settings.In order to facilitate biomedical researchers and practitioners, we have developed the very first user-friendly web sever for the proposed circRNA sub-cellular localization prediction framework (Circ-LocNet). This web server is available at  , DNA N4-Genomic sequences are comprised of 4 basic residues . For a genomic sequence of merely 100 residues, number of possible residue order combinations are u et al.  developeu et al. ,63,64,65u et al. ,67,68. Pu et al. , nucleosu et al. , and prou et al. .Given an RNA sequence D having L nucleotides: In this study, we experiment with di-nucleotide, tri-nucleotide, tetra-nucleotide, and penta-nucleotide compositions to represent circRNA sequences for the task of circRNA sub-cellular localization prediction.The Z-curve residue encoding approach was proposed by Zhang et al.  in whichEIIP is a physico-chemical property-based encoding scheme that represents the dissemination of electronion energies across the sequence. EIIP was originally given by Nair et al.  to conveXxKGAP composition makes use of kgaps present in residue sub-sequences. Occurrences of sub-sequences are taken as prediction features . ResearcHere (in Equation ), CdmkgaEquation , for eacIn order to better illustrate the effectiveness of diverse sequence descriptors and to facilitate a rich baseline for circRNA sub-cellular localization task, we perform experimentation with 5 most widely used machine learning classifiers. Specifically, we employ Random Forest (RF), Support Vector Machine (SVM), AdaBoost, XGboost, and Naive Bayes (NB) classifiers, a brief description of which is given below.We utilize an efficient discriminative classifier known as SVM  for circNaive Bayes  is a simClassification trees are also used to predict sub-cellular localization of circRNAs using sequence information. Classification trees leverage a tree-like data structure for efficient sequence classification. Nodes of the tree denote binary decision rules that recursively segregate the feature space whereas the leaves of the tree denote the classes . ClassifWe utilize a renowned tree-based bagging ensemble called Random forest , where tThe first boosting ensemble applied in this study, “AdaBoost", fits a number of weak learners (short decision trees which are slightly superior than random guessing models) on iteratively modified version of underlay data. Afterwards, predictions made by all classifiers on different versions of the dataset are combined using weighted majority voting paradigm to generate the final prediction.Considering the smart penalisation of trees, overall network boosting, proportional compression of leaf nodes, and an effective parameter randomization of renowned XGBoost classifier, we also adapt XGBoost for sub-cellular localization prediction of circRNAs. Several researchers have shown the effectiveness of XGBoost classifier for diverse NLP and bioinformatics tasks .The generation of a benchmark corpus is indispensable to develop machine learning-based applications . We haveAlthough the backsplicing junction of a sequence is specific for circRNA and different from linear mRNA, we have not distinguished common sequences between circRNAs and their host mRNAs and used full circular RNA sequences for training the predictive model. This is primarily due to fact that we have used circular RNA sequences that have been experimentally identified in different subcellular compartments and the prime objective of this study is to complement wet-lab experiments for accurate detection and validation of circular RNA subcellular localizations through the development of robust Artificial Intelligence-based methods.In order to evaluate the performance of computational methodologies, an appropriate selection of evaluation measures is really crucial to draw certain conclusions. Considering the effectiveness and wide adoption of accuracy (ACC), specificity (SP), F1-score, matthews correlation coefficient (MCC), and area under the receiver operating characteristics (AUC-ROC) , we eval+ refers to true positives and false positives whereas O− represents the true negatives and false negatives. The number of positive class sequences which are correctly predicted as positive are represented as In Equation (11), OAccuracy (ACC) refers to the proportion of instances that have been correctly predicted by the classifier out of all instances. Accuracy usually proves misleading for datasets having imbalanced class distribution, while specificity measures the true negative rate, and recall measures true positive rate. Precision indicates up to what percent of positive identifications are actually correct out of all positive predicted instances. F1-score computes a harmonic mean of precision and recall. All three evaluation metrics  are asymmetric as they do not take true negative into account and are greatly influenced by the magnitude of positive class. MCC, on the other hand, takes all 4 entries of the confusion matrix  into account and a high value of MCC indicates that classifier is identifying all corpus classes quite well even if a certain class is disproportionately over- or under-represented.Trivial evaluation metrics compute the classifier performance by making a comparison between actual and predicted sub-cellular localizations. However, receiver operating characteristic curve (ROC) reveals the performance of the classifier at different thresholds by taking actual labels and predicted label probabilities into account. Traditional evaluation metrics such as accuracy only manage to indicate the actual classifier performance when the dataset is highly balanced, which exposes its bias towards class size. Nevertheless, area under the receiver operating characteristics curve (AU-ROC) accurately determines the classifier performance without being effected by the size of corpus classes, indicating that AU-ROC is neither inclined towards positive class nor negative class.K subsets, where Proposed computational framework Circ-LocNet is implemented using an open-source machine learning library called Scikit-Learn . In ordek from 2 to 5. Residue-encoding specific parameters such as K-gap initial range is defined as 2 to 5 following the state-of-the-art sequence representation learning toolkits such as iLearnPlus [Taking the effectiveness of grid search for automated parameter search  into accearnPlus . TurningThis study achieves a number of milestones regarding sub-cellular localization of circular RNAs by performing a pioneering work using Artificial Intelligence. Circ-LocNet identifies important sequence features which largely influence the generalizeability of diverse sub-cellular localization predictors. Using only 1K training samples, Circ-LocNet achieves a peak AU-ROC score of 90%, accuracy of 69%, and F1-score of 63% solely using residue frequency information and a precisely deep decision tree-based classifier. With the current preciseness, time efficiency, and effectiveness of the predictive pipeline, we consider that Circ-LocNet can achieve consistent and production-ready performance as well by just increasing the training data. A compelling future line of current work would be to investigate whether over-sampling and under-sampling approaches are appropriate and good enough to further raise the performance of Circ-LocNet.


The purpose of this secondary-analysis study was to identify never-before-examined factors associated with distinct depressive-symptom trajectories among family caregivers from end-of-life caregiving through the first 2 bereavement years.N=661) were family caregivers who provided end-of-life caregiving for terminally ill cancer patients. Multinomial logistic regressions were conducted to identify modifiable factors associated with caregivers’ seven previously identified depressive-symptom trajectories: minimal-impact resilience, recovery, preloss-depressive-only, delayed symptomatic, relief, prolonged symptomatic, and chronically persistent distressed. Drawing from the stress-appraisal-coping model, modifiable time-varying factors associated with distinct depressive-symptom trajectories were examined in three domains: (1) stressors, (2) stress appraisal, and (3) available resources .Participants (Profound objective caregiving demands were associated with caregivers’ increased likelihood of belonging to more distressing depressive-symptom trajectories than to the minimal-impact-resilience trajectory. But, stronger negative appraisal of end-of-life caregiving increased odds of caregiver membership in preloss-depressive-only and relief trajectories over the recovery, delayed, and prolonged-symptomatic trajectories. Stronger internal coping capacity and perceived social support buffered the tremendous stress of end-of-life caregiving and permanent loss of a relative, as evidenced by higher odds of being in the minimal-impact-resilience and recovery trajectories.Family caregivers’ distinct depressive-symptom trajectories were linked to their preloss caregiving demands, appraisal of negative caregiving impact, personal coping capacity, and perceived social support. Our results highlight actionable opportunities to improve end-of-life-care quality by boosting family caregivers’ coping capacity and enhancing their social support to help them adequately manage daily caregiving loads/burdens thus relieving the emotional toll before patient death and throughout bereavement.The online version contains supplementary material available at 10.1186/s12904-022-01045-9. Family caregivers are a critical constituent in the end-of-life (EOL)-cancer-care system because they bear the brunt of caregiving for terminally ill cancer patients , 2. In tCaregiving for and losing a relative is among the most devastating events one may experience , though . Opportunities to improve EOL-care quality begin with identifying caregivers at risk of profound/prolonged/persistent depressive symptoms from EOL caregiving to bereavement.Furthermore, caregivers respond heterogeneously to caregiving/loss events as shown by belonging to distinct depressive-symptom trajectories , 23, 24.Factors associated with distinct depressive-symptom trajectories have been examined independently during caregiving , 15, 16 The relationship between EOL caregiving and bereavement may be cumulative (wear-and-tear model) or abating (relief model) , 29. TheData for this secondary-analysis study were from two institutional review-board-approved  longitudinal studies on associations of EOL caregiving with and the effectiveness of an advanced care planning intervention on caregivers’ depressive symptoms before and after patient death . DetailsCaregivers were interviewed in person for preloss caregiving experiences  at enrollment and approximately monthly thereafter while providing EOL caregiving until they declined to participate. Time invariant covariates were assessed at baseline. Bereaved caregivers were surveyed for depressive symptoms at 1, 3, 6, 13, 18 and 24 months postloss, whereas internal/external resources were measured at 1-month postloss only.>16 are considered the threshold for severe depressive symptoms ), comorbidity (yes/no), and awareness of the patient’s prognosis. Caregiver prognostic awareness was measured at each assessment by asking caregivers whether they knew their relative’s prognosis, and if so, whether the disease (1) was curable; (2) might recur in the future, but the patient’s life was not currently in danger; or (3) could not be cured and the patient would probably die soon. Caregivers were recognized as accurately knowing the patient’s prognosis only if they chose option 3; inaccurate prognostic awareness reflected not knowing the patient’s prognosis or choosing option 1 or 2.Contextual factors  were trePotential factors associated with caregivers’ membership in the seven distinct depressive-symptom trajectories (see Independent variables) were examined by multinomial logistic regressions while controlling for covariates/contextual factors. Multinomial logistic regressions are flexible enough to allow the researcher to alter the reference category, allowing for all possible group comparisons, while the overall model statistics remain unchanged. Preloss scores of internal and external resources were measured at the first assessment within patient’s last 6 months, whereas postloss scores were measured 1-month postloss. This timeline reflected the two-phase piecewise estimation used to model changes in depressive symptoms from EOL caregiving through the first 2 bereavement years, with time of transitioning into EOL caregiving and time of loss serving as major life transitions for caregivers . The regDetails of associations between variables and membership in each depressive-symptom trajectory are in Tables In the stressor domain, relative to caregivers with low objective caregiving demands, those with profound objective caregiving demands were more likely to be in the more distressing depressive-symptom trajectories than in the minimal-impact-resilience trajectory Table  and in tIn the stress-appraisal domain, compared to those with substantial caregiving burden, caregivers with low and moderate caregiving burden were less likely to be in the preloss-depressive-only and relief trajectories than in the recovery trajectory Table . CaregivIn the psychosocial-resource domain, higher reported preloss coping capacity (sense-of-coherence score) increased the odds that caregivers would be in the recovery trajectory than in all other trajectories, except the delayed-symptomatic trajectory Table . CaregivPerceived preloss social support was not associated with caregivers’ membership in depressive-symptom trajectories, but stronger perceived postloss social support increased the odds that caregivers would be in the minimal-impact-resilience trajectory relative to all other trajectories Table . FurtherOur study examined modifiable factors associated with caregivers’ membership in the distinct depressive-symptom trajectories from EOL caregiving through the first 2 bereavement years based on the stress-appraisal-coping model . All proOur study’s use of data from before and after patient death confirmed both the cumulative-stress (wear-and-tear model) and stress-reduction (relief model) perspectives of caregiving effects on bereavement adjustment . ProfounIn contrast, caregivers with substantial caregiving burden were more likely than those with moderate caregiving burden to be in the relief trajectory than in delayed-symptomatic and prolonged symptomatic trajectories Table . FurtherPersonal coping capacity/adaptive coping strategies have consistently emerged as robust predictors to buffer long-term negative outcomes following aversive circumstances , 20, 26.A similar pattern to the role of sense of coherence in easing depressive symptoms during bereavement was observed for perceived postloss social support, as reported , 18, 27.This study’s strengths lie in its investigation of modifiable factors associated with caregivers to distinct depressive-symptom trajectories from EOL caregiving through the first 2 years of bereavement using information assessed before and after patient death. These strengths allowed us to disentangle the cumulative-stress (wear-and-tear model) and stress-reduction (relief model) perspectives  of EOL-cFamily caregivers of Taiwanese advanced cancer patients follow distinct depressive-symptom trajectories from EOL caregiving through bereavement. Clinical interventions should be prioritized to interrupt the three unfavorable long-lasting and delayed high-level depressive-symptom trajectories, to prevent burnout during caregiving for caregivers in the preloss-depressive-only trajectory, and to facilitate rapid return to healthy emotional functioning for bereaved in the relief trajectory. Furthermore, our findings showed that these trajectories are linked to preloss caregiving demands, appraisal of EOL-caregiving impact, internal coping capacity, and perceived social support. Profound caregiving demands may cumulatively exhaust caregivers, whereas caregivers who appraise EOL caregiving as a substantial burden may feel relief and experience fewer depressive symptoms once their relative dies. Stronger internal coping capacity and external social support may buffer the tremendous stress from EOL caregiving and the permanent loss of a relative. Healthcare professionals should be sensitive to the caregiving needs of caregivers with heavy caregiving demands and provide effective interventions. For example, caregivers’ coping capacity could be boosted and their social support enhanced to help them adequately manage daily caregiving to relieve the emotional toll before patient death and throughout bereavement. These actionable opportunities for high-quality EOL care can facilitate caregivers’ adjustment to the stress of EOL caregiving and bereavement, thus benefiting caregivers and society.Additional file 1.


The SARS-CoV-2 pandemic posed major challenges to employees and companies. Differences between industries and professions in occupational SARS-CoV-2 infection risk (OSIR) became apparent early on. This study examines the mental distress in terms of depression and anxiety symptoms of non-healthcare workers during the first and second Corona waves in Germany.We conducted an online survey from December 2020 to June 2021 among employees from industrial enterprises, local public transport, the public and the financial sector. High and potential OSIR was defined based on job information. Depression and anxiety symptoms were rated with the 4-item Patient Health Questionnaire (PHQ-4). Categorized PHQ-4 scores were modeled with ordinal random-intercept logistic multinomial regression models and presented with odds ratios (OR) and 95% confidence intervals (95% CI).Overall, 516 of 1,545 participants (33.4%) were determined to be at increased OSIR. Anxiety and depression symptoms worsened during the pandemic in all OSIR groups. Risks for more severe depressive and anxiety symptoms were higher among employees with high  and potential OSIR  compared to employees without OSIR. Severity of mental distress differed also by the extent of perceived job protection, interactions with colleagues, work-privacy conflicts, and overcommitment.OSIR had a negative impact on employee’s depressive symptoms and anxiety. Reducing SARS-CoV-2 exposure through workplace protective measures, strengthening interactions among colleagues, and supporting employees with work-privacy conflicts could help better protect employees’ mental health.• The risk for more severe depressive and anxiety symptoms increases with higher occupational SARS-CoV-2 infection risk.• Improvements in SARS-CoV-2 exposure at work, colleague interactions, and work-privacy conflicts could help better protect mental health.


The intestinal tract is composed of different cell lineages with distinct functions and gene expression profiles, providing uptake of nutrients and protection against insults to the gut lumen. Changes in or damage to the cellulosity or local environment of the intestinal tract can cause various diseases. Single-cell RNA sequencing (scRNA-seq) is a powerful tool for profiling and analyzing individual cell data, making it possible to resolve rare and intermediate cell states that are hardly observed at the bulk level. In this review, we discuss the application of intestinal tract scRNA-seq in identifying novel cell subtypes and states, targets, and explaining the molecular mechanisms involved in intestinal diseases. Finally, we provide future perspectives on using single-cell techniques to discover molecular and cellular targets and biomarkers as a new approach for developing novel therapeutics for intestinal diseases. Cells are the smallest structural and functional units of life, and they vary enormously, mainly due to distinct gene expression profiles; thus, almost all organs and tissues are composed of a heterogeneous mixture of cell types. Transcription studies using bulk samples can only measure the average gene expression level in a large population of cells, which is insufficient for studying heterogeneous systems or complex tissues . Since iThe intestinal tract comprises different cell lineages, which fold into millions of crypts and villi. Rapidly dividing intestinal stem cells (ISCs) reside at the bottom of the crypt, giving rise to transit-amplifying (TA) cells that finally differentiate into five different mature intestinal epithelial cell types: enterocytes, Paneth cells, goblet cells, enteroendocrine cells (EECs), and tuft cells . In addi+ ISCs, slow dividing +4 cells located at a position far from the crypt base, and reserve stem cells , behaving as non-conventional antigen-presenting cells that present antigens to T-helper cells. In turn, cytokines secreted by T-helper cells regulate the proliferation and differentiation of Lgr5+ ISCs, in which proinflammatory cytokines (IL-13 and IL-22) promote differentiation and anti-inflammatory cytokines (IL-10) inhibit it. To further explore the regulation behind Lgr5+ ISCs replenishment after injuries, researchers sequenced cells from irradiation-damaged intestines and identified a group of revival stem cells, which appeared in irradiated crypts and specifically expressed several genes involved in inflammatory responses, such as clusterin. They used genetic lineage-tracing tools to validate the hypothesis and finally confirmed that these revival stem cells were extremely rare under homoeostatic conditions and could repopulate the pool of LGR5+ ISCs and replace lost and damaged enterocytes  and distal (ileum) enterocytes were also distinct.Numerous bioinformatics methods and tools have been designed to analyze scRNA-seq data, enabling the acquisition of more information about lineage divergence in the same cell type . Haber ein situ hybridization, and fluorescence-activated cell sorting were the most commonly used single-cell analysis tools  and contribute to CD severity. To clarify the role of commensal microbiota in the maintenance and differentiation of colonic macrophages, hi colon mononuclear phagocytes from both germ-free and specific pathogen-free (SPF) mice and emphasized the unique role of the intestinal microbiota in the development of colon macrophages. They identified seven macrophage subtypes expressing distinct transcription factors or downstream marker genes and discovered two major developmental trajectories from CCR2+ monocyte precursors to colon macrophages. They found the total number of colon macrophages in germ-free mice was lower than that in SPF mice. The two major colon macrophage subtypes, CD11c+CD206intCD121b+ and CD11c−CD206hiCD121b−, showed clearly distinct gene expression profiles, differing abilities for carrying out the endocytosis of macromolecules, and different localization within the lamina propria in relation to other macrophage subtypes.Macrophages are crucial components of the intestinal tract immune system, which modulates inflammation through the secretion of distinct cytokines and the action of phagocytes . HoweverCD122 and T-bet genes, revealing the molecular framework for thymic ILC development from NK1.1− ILC precursors (α-CGRP) was induced in KLRG1+ ILC2s during type 2 intestinal inflammation and that α-CGRP antagonized the proliferation of KLRG1+ ILC2s, indicating that the expression of α-CGRP maintained KLRG1+ ILC2 homeostasis during type 2 intestinal inflammation. The CD4+ regulatory T-cell (Treg) subtypes were categorized according to their distinct degree of non-lymphoid tissue phenotype. Treg recruitment to different tissues showed similar pseudotemporal ordering and gene kinetics. However, the priming and the final stages of functional adaptation in non-lymphoid tissues reflected tissue specificity (Innate Lymphoid Cells (ILCs) are thymus-derived adaptive immune cells that mainly consist of cytotoxic cells and helper-like ILCs . Althougecursors . Previoucificity .Reg gene was specifically expressed at the villi bottoms  and glycoprotein hormone beta 5 (Gbp5). They determined the spatial distribution of EECs subtypes along the length of the midgut using a region-specific gene enrichment algorithm. By processing subtype-enriched transcription factors (TFs), the authors identified a series of class-specific and region-specific TFs that participate in the EEC subtypes specification, which indicates that EECs diversity was co-regulated by class-specific and region-specific TFs, such as Esg, Drm, Exex, and Fer1. In fact, class-specific TFs were controlled by Notch signaling, and region-specific TFs were specified by anterior-posterior body planning during early cell development. + ISCs, EEC subtypes showed a more flexible hormone repertoire than was previously proposed. EECs differentially expressed hormone biosynthesis genes between crypts and villi, and bone morphogenetic protein-4 (BMP4) expression altered the hormone profiles of individual EECs by inducing migration of EECs along the crypt-villus axis , proglucagon (Gcg), neurotensin (Nts), galanin , glucagon-like peptides, serotonin (Tph1), somatostatin (Sst), cholecystokinin (Cck), ghrelin (Ghrl), gastric inhibitory peptide, and tachykinin, which mainly regulate gastrointestinal activity and metabolic processes . EECs sulus axis .+ intestinal capillaries and angiogenic EECs. They found that EECs from different tissues express partially overlapping signature genes, which was based on EC markers (Pecam1 and Cdh5), and excluded contaminating smooth muscle cells (Acta2), fibroblasts (Col1a1), and red blood cells . Capillary EECs showed more heterogeneity than EECs from arterial, venous, and lymphatic tissues, which exhibited a similar transcriptome profile.In addition to the common cell types, scRNA-seq is also widely applied for identifying rare cells, such as tuft cells and proglucagon-expressing cells. in vitro platforms for stem cell biology and disease modeling , structural components, and molecules . Stromal+ effector and exhausted T cells were independently connected with tumor-resident CD8+ effector memory cells, and T-regulatory cells were developmentally linked to several T-helper cell subtypes  population. In CRC, T cells behave as critical elements of the tumor microenvironment. A web-based tool was developed using a comprehensive analysis of the T-cell expression profile and full-length T-cell receptor (TCR) sequencing from peripheral blood, CRC, and adjacent normal tissues. Therefore, this tool enables dissecting the function, development, and migration of CRC T cells using both transcriptome and TCR sequences . Furthersubtypes . A comprsubtypes . Macroph+ macrophage population, two of which were monocyte-like CD64hiCD163− and macrophage-like CD64hiCD163hi cells. CD64hiCD163− cells secreted proinflammatory cytokines, such as IL-1β and IL-23, specifically infiltrating the inflamed colon, which correlated with the endoscopic disease severity score. Moreover, CD64hiCD163− cells can promote Th17/Th1 responses in tissue memory CD4+ T cells through the IL-1β signaling pathway. By comparing the transcriptomes of patients with ulcerative colitis (UC) and healthy individuals, + enterocytes, microfold-like cells, and inflammatory fibroblasts contributed to resistance to anti-TNF treatment. Mapping the risk variants in cell types and pathways identified UC risk genes as cell type-specific and co-regulated within limited cellular subtypes and pathways. +CD142+ subpopulation in neighboring crypts. Moreover, a specifically activated TNFSF14+ mesenchymal subpopulation was observed in colitis, fueling inflammation by slowing epithelial proliferation and contributing to oxidative stress.IBD is associated with inappropriate immune responses to commensal microflora in the intestinal tract . Chapuy The continuous renewal of the intestinal mucosa is motivated by various stimuli that activate molecular pathways that help provide a proper ISCs niche in the crypt . IBD altin utero .The improvement of single-cell technology, increasing gene coverage and stability and reliability, together with the cost reduction of next-generation sequencing technologies, made it possible to dissect the physiological and pathological functions of single-cells . A new uHowever, scRNA-seq has several technical limitations for intestinal applications. The gastrointestinal tract has a complex layered structure . The intDespite the bottleneck associated with single-cell dissociation and data analysis, the application of scRNA-seq in the intestinal tract has resulted in outstanding discoveries. With the development of microfluidic technology in recent years, the number of cells submitted for barcoding and processing for scRNA-seq has increased significantly. As the scale of data collected from transcriptome sequencing continues to grow, together with improvements in analytical methods, scRNA-seq could be a standard tool for discovering pathogenesis, signal networks, and strategies for therapeutics.


Because prolonged viral replication of SARS-CoV-2 is increasingly being recognized among immunocompromised patients, subacute or chronic COVID-19 pneumonia can cause persistent lung damage and may lead to viral escape phenomena. Highly efficacious antiviral therapies in immunosuppressed hosts with COVID-19 are urgently needed. From February 2022, we introduced novel treatment combining antiviral therapies and neutralizing antibodies with frequent monitoring of spike-specific antibody and RT-PCR cycle threshold (Ct) values as indicators of viral load for immunocompromised patients with persistent COVID-19 infection. We applied this treatment to 10 immunosuppressed patients with COVID-19, and all completed treatment without relapse of infection. This may be a potentially successful treatment strategy that enables us to sustain viral clearance, determine optimal timing to stop treatment, and prevent virus reactivation in immunocompromised patients with persistent COVID-19. To the Editor,The coronavirus disease 2019 (COVID-19) pandemic has caused significant morbidity and mortality worldwide. Driven by findings of high-quality randomized trials, management of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has developed rapidly over the past year , 4. ThisFrom February 2022, we introduced a novel treatment combining antiviral and neutralizing antibody-based therapies with monitoring of spike-specific antibody and Ct values as indicators of viral load for immunocompromised patients with persistent COVID-19 infection. Knowledge of specific immune responses to antibody-based therapy in immunosuppressed patients is important, and well-validated quantitative PCR that correlates with both viral culture titres and Ct values may help in clarifying infectious viral shedding, guiding treatments, and assessing outcomes . We examIn an immunosuppressed COVID-19 patient taking tacrolimus hydrate and mycophenolate mofetil following kidney transplantation, we administered remdesivir as antiviral therapy on day 1 along with sotrovimab as neutralizing antibody-based therapy (Fig. As limitations, first, although the progression of SARS-CoV-2 infectious viral shedding and specific immune responses by this treatment are understandable, criteria for frequency of measuring spike-specific antibody and Ct values remain unknown. Second, long-term data on potential viral relapse is unknown. Third, administration of antiviral drugs at above-normal prescription limits based on frequent test results could increase long-term drug and hospitalization costs. Fourth, because the sample size is small, results should be interpreted cautiously. More rigorous research including randomization and larger sample size is needed. Nevertheless, our novel strategy may offer potentially successful treatment for immunocompromised patients with persistent COVID-19.


A 29-year-old man presented with tonic-clonic seizures. Initial MRI showed a lesion centered on the white matter of the left frontal lobe, with restricted diffusion and contrast enhancement on its margins and low rCBV and hypometabolismon PET-CT, suggestive of a tumefactive demyelination lesion . Patient,Demyelinating sentinel lesions preceding CNS lymphomas are a rare entity and its pathophysiology is not fully understood


Vaccine hesitancy (VH) and the challenges faced by healthcare workers (HWs) in evaluating the complex risk-benefit ratio of vaccines’ threaten the effectiveness of vaccination policy. The threat is enhanced when new vaccines are adopted during a pandemic emergency. In Italy, the Emilia-Romagna Region (ERR) created a specialized referral board called Vax-Consilium (VC) to support and guide HWs.During a pandemic emergency, rapid and appropriate vaccine implementation is necessary to protect fragile individuals and to encourage vaccine adherence among exposed groups. Challenges in the realm of vaccination emerge, especially when dealing with patients with a complex medical history or previous vaccine adverse events. HWs were able to consult VC via a standardized digital form after obtaining the patient’s informed consent. After a multidisciplinary and evidence-based evaluation, VC provided a conclusive report on the individual vaccine risk-benefit analysis. No cost is charged to the patient.During the anti-COVID-19 vaccination campaign in 2021, 148 interrogations were submitted to VC: 121 were evaluated, whereas 27 were withdrawn by the HWs or rejected because of insufficient documentation. Mean patient age was 44 years. No absolute contraindication was found, whereas in 23 cases VC recommended immunization with a different vaccine. The disciplines most frequently involved were neurology, angiology and cardiology.VC implementation in EER proved highly effective. Indeed, during the pandemic, anti-COVID-19 vaccination coverage reached >90%. In addition, DTaP-polio-HBV-HIb and MMR vaccination coverage reached >95%. VC proved to be a high-quality public health service. Not only was citizens’ trust in the healthcare system enhanced and was VH reduced, but HWs knowledge improved even in cases not considered in national and international guidelines.• A specialized referral board (Vax-Consilium) could be an effective tool for enhancing citizens’ trust in vaccines.• A specialized referral board (Vax-Consilium) contributes to lowering VH and supporting HWs decision-making process.


Teaching Point: Retropubic cartilaginous cysts are rare, benign lesions originating from the symphysis pubis that should be considered in the differential diagnosis of a small slow-growing retropubic nodule. Figure 1, asterisk) with slightly increased diffusion restriction, which was flagged as a possible malignancy. Subsequent transrectal biopsy and staging showed an intermediate risk prostate carcinoma cT2aN0M0, Gleason score 4+3, for which a robotic-assisted laparoscopic prostatectomy (RALP) was scheduled. During surgery, the urologist visualized a soft tissue nodule located posterior to the symphysis pubis, which had not been mentioned in the MRI-report. He immediately contacted the radiologist to re-assess the MRI scan in order to decide whether it should be resected. On MRI, a well-defined nodular structure measuring 17 mm was identified, lying immediately between the symphysis pubis and the prostate. It showed a heterogeneous intensity on axial  and sagittal  T2WI, and no diffusion restriction. There was clear growth when compared to a prostate MRI from one year prior. A recent single photon-emission computed tomography (SPECT-CT) scan showed degeneration of the symphysis, with the retropubic nodule containing small foci of gas . Because the nodule was identified as a benign retropubic cartilaginous cyst, unrelated to the prostate, it was left alone during the RALP procedure. Six months after surgery, the PSA level remained below 0.03 ng/ml.A 72-year-old man was referred to our department for a magnetic resonance imaging (MRI) scan of the prostate in the work-up of an elevated prostate-specific antigen (PSA). T2-weighted images (T2WI) showed a focal hypo-intense lesion in the right mid-portion of the peripheral zone of the prostate (Retropubic cartilaginous cysts, also called supra- or subpubic cysts depending on their location relative to the symphysis, are rare cystic lesions originating from the symphysis pubis. Almost all reported cases concern multiparous and post-menopausal women with symptoms including urinary voiding difficulties, a painless slow-growing vulvar mass, or pelvic pain and dyspareunia . Our cas


Objective: To investigate the maternal–neonatal outcomes of obstetric deliveries performed in negative pressure isolated delivery rooms (NPIDRs) during the coronavirus disease 2019 (COVID-19) omicron variant pandemic period in a single tertiary center in northern Taiwan. Methods: Confirmed positive and suspected-positive COVID-19 cases delivered in NPIDRs and COVID-19-negative mothers delivered in conventional delivery rooms (CDRs) in the period of 1 May 2022 to 31 May 2022 during the COVID-19 omicron variant pandemic stage were reviewed. The maternal–neonatal outcomes between the two groups of mothers were analyzed. All deliveries were performed following the obstetric and neonatologic protocols conforming to the epidemic prevention regulations promulgated by the Taiwan Centers for Disease Control (T-CDC). Multiple gestations, deliveries at gestational age below 34 weeks, and major fetal anomalies were excluded from this study. Results: A total of 213 obstetric deliveries were included. Forty-five deliveries were performed in NPIDRs due to a positive COVID-19 polymerase chain reaction (PCR) test (n = 41) or suspected COVID-19 positive status (n = 4). One hundred and sixty-eight deliveries with negative COVID-19 PCR tests were performed in CDRs. There was no statistical difference in maternal characteristics between the two groups of pregnant women. All COVID-19-confirmed cases either presented with mild upper-airway symptoms (78%) or were asymptomatic (22%); none of these cases developed severe acute respiratory syndrome. The total rate of cesarean section was not statistically different between obstetric deliveries in NPIDRs and in CDRs . Regardless of delivery modes, poorer short-term perinatal outcomes were observed in obstetric deliveries in NPIDRs: there were significant higher rates of neonatal respiratory distress , meconium-stained amniotic fluid  and newborn intensive care unit admission  in obstetric deliveries performed in NPIDRs than in CDRs. Maternal surgical outcomes were not significantly different between the two groups of patients. There was no vertical transmission or nosocomial infection observed in COVID-19 confirmed cases in this study period. Conclusions: Our study demonstrates that obstetric deliveries for positive and suspected COVID-19 omicron-variant cases performed in NPIDRs are associated with poorer short-term perinatal outcomes. Reasonable use of personal protective equipment in NPIDRs could effectively prevent nosocomial infection during obstetric deliveries for pregnant women infected with the COVID-19 omicron variant. Coronavirus disease 2019 (COVID-19), which is caused by a newly identified coronavirus, was first isolated in Wuhan, China, in December 2019. The global outbreak of COVID-19 has been unprecedented, with more than 550 million cumulative confirmed cases worldwide. Over 6 million lives were ravished by the 2019 novel coronavirus (2019-nCoV) [Since January 2020, the beginning of the global COVID-19 outbreak, the obstetric department of Chang Gung Memorial Hospital, Linkou Branch (Linkou CGMH), has established negative pressure isolated delivery rooms (NPIDRs) . The NPIPrevious studies outside Taiwan have shown that COVID-19 infection in pregnancy is associated with adverse maternal and neonatal outcomes due to maternal physiologic changes and alterations of immune function during pregnancy ,5,6,7. HWe retrospectively reviewed the medical records of confirmed and suspected COVID-19-positive mothers who delivered in NPIDRs and COVID-19 PCR-negative mothers who delivered in CDRs at Linkou CGMH between 1 May 2022 and 31 May 2022. Linkou CGMH, as the nearest and largest tertiary medical center to the Tao-Yuan, Hsinchu, and Miaoli cities in Taiwan, provides 24-hour open access through an emergency department system for referral of COVID-19 confirmed/suspected cases to seek negative pressure facilities or critical obstetric and neonatal care. The inclusion criterion is singleton pregnancy delivered at a gestational age of more than 34 weeks in our hospital during the study period. We excluded multiple gestations, obstetric deliveries at gestational age below 34 weeks, and major fetal anomalies from this study. All patients and their companions receive a government-funded 48-hour-validity COVID-19 PCR test before admission to facilitate patient triage.We defined neonatal respiratory distress as newborns with the following symptoms: signs of tachypnea (rate >60 breaths per minute), cyanosis, expiratory grunting with chest retractions, and nasal flaring regardless of pulmonary or non-pulmonary causes . The sevAll patient baseline characteristics, delivery information, maternal surgical outcomes , and neonatal outcomes  were extracted by medical record. Maternal surgical outcomes were compared separately based on delivery methods. The Institutional Review Board of Chang Gung Memorial Hospital approved this study .The obstetric delivery management protocol has been established since January 2020, conforming to the epidemic prevention guidance and recommendations of the T-CDC, and the protocol has been timely and practically modified in response to COVID-19 outbreak waves. To reduce the risk of in-hospital viral transmission and to preserve medical capacity, patient flow arrangements and the partition of hospital zones are applied based on the COVID-19 PCR test report, travel history, occupation history, contact history, and cluster information of individuals.We defined a COVID-19 confirmed case as a positive result of a COVID-19 PCR test acquired from a nasopharyngeal swab within 14 days, regardless of clinical manifestation. The COVID-19 PCR test sample was collected from a nasopharyngeal swab by HCP, and the result was confirmed by an accredited lab. The cycle threshold (CT) value may indicate the viral load that an infected person harbors. The Department of Laboratory Medicine in our hospital states that if a positive signal is not seen after 39 cycles of amplification, then the PCR test is deemed negative. We defined a COVID-19 suspected case as an individual who has a negative COVID-19 PCR test but has contact history with COVID-19 confirmed cases in the last 7 days, has recent international travel history in the last 14 days, or has flu-like symptoms such as fever, shortness of breath, cough, sore throat, and loss of taste or smell.Those identified as COVID-19 confirmed/suspected cases with the requirement of obstetric care are admitted to the NPIDRs. One obstetrician and one obstetrical nurse stand by at the nurse station of the isolated negative pressure delivery zone. The shift-based work is assigned independently from the CDRs to reduce the risk of in-hospital COVID-19 transmission. HCP put on PPE, including protective coveralls, protective gowns, and N95 respirators in the anteroom before entering the isolation room. Two obstetricians, four obstetrical nurses, and two neonatologists will enter the isolation zone to perform obstetric deliveries; one anesthesiologist and one assistant nurse will join the team if a cesarean section is indicated. Delayed cord clamping continues based on a lack of evidence in vertical transmission . COVID-1Two neonatologists put on PPE and enter the isolation zone of NPIDRs while performing obstetric delivery. The NPIDRs are equipped with infant warmers that are settled more than 2 m from the mother. If an open system ventilator support device such as nasal intermittent positive pressure ventilation, nasal continuous positive airway pressure (CPAP), or nasal cannula is indicated, the use of a high-efficiency particulate air (HEPA) filter between the mask and the T-piece resuscitator is required to minimize the risk of COVID-19 airborne transmission .After initial management of the newborn, the baby is placed into an isolette inside the negative pressure delivery room. The newborn is then transferred to an isolated room in the neonatal intensive care unit (NICU) or intermediate care unit (IMU) through the isolette. All personnel in charge of standby, transfer, and care for the newborn wear aerosol precaution PPE. In terms of COVID-19 laboratory testing and isolation policy after birth, newborns of COVID-19-positive confirmed mothers will take COVID-19 PCR tests with the specimen obtained from the nasopharynx while admitted to the isolated unit; the subsequent test is arranged after 48 h from delivery. If two consecutive tests reveal negative results, the newborn is released from isolation. The newborn who has a positive result in the initial PCR test is transferred to the red zone ward, and a follow-up test is arranged repetitively in 48- to 72-h intervals until two consecutive negative results are obtained. On the other hand, newborns of COVID-19 suspected mothers will receive COVID-19 PCR tests once they are admitted to the isolated unit. If the PCR test is disclosed as negative, the newborn is released from quarantine. Video visits of neonates are provided for COVID-19 confirmed/suspected mothers to help relieve parental anxiety. Newborns with a negative result in the COVID-19 PCR test and no demands for medical care may be discharged. Although direct breastfeeding by COVID-19-infected mothers, immediate skin-to-skin contact after delivery, and rooming-in were not associated with an increased risk of newborn COVID-19 test positivity based on current evidence ,18, the t-test or the Mann–Whitney U-test was used to compare the continuous variables between groups. Qualitative data were compared using the χ2 test or Fisher’s exact test. A p-value of less than 0.05 was considered statistically significant.Statistical analyses were performed with the software package MedCalc  and IBM SPSS . The normality of the data was assessed with the Shapiro–Wilk test. Student’s n = 41) or suspected COVID-19 positive status (n = 4). Of those, 18 cases were cesarean sections and 25 cases were vaginal deliveries; 1 case was an operative vaginal delivery, and 1 case was a vaginal birth after cesarean (VBAC). One hundred and sixty-eight deliveries with negative COVID-19 PCR tests were performed in the CDRs; of those, 64 cases were cesarean deliveries, 93 cases were vaginal deliveries, 10 cases were operative vaginal deliveries, and 1 case was VBAC. The patient baseline demographics and delivery information are summarized in p = 0.016, respectively). Thirty-one cases (68.9%) of COVID-19 confirmed/suspected cases were referred from community hospitals. Thirty-two (78.0%) COVID-19-positive confirmed cases presented with mild upper-airway symptoms; cough (43.9%), sore throat (39.0%), and fever (22.0%) were the predominant symptoms in the present study. Nine (22.0%) COVID-19-positive confirmed mothers were asymptomatic. None of the COVID-19-infected mothers developed severe acute respiratory syndrome, and none of them required ventilator support, administration of anti-viral medication, or intensive care unit admission. Patient information and the clinical manifestation of deliveries performed in the NIPDRs are summarized in A total of 213 obstetric deliveries of singleton pregnancy with gestational age ≥34 weeks are included in this study. The participant selection workflow is shown in Maternal surgical outcomes were compared separately after pairing with delivery modes: vaginal delivery and cesarean section with the same obstetric indications.p < 0.001, respectively) with lower proportions of planned labor induction  were observed in the NPIDR group compared to the CDR group.In subgroup analyses of vaginal delivery, patient characteristics, including age, BMI, gestational age upon admission, proportion of primigravida, maternal medical diseases, GDM, and gestational hypertension disease, were similar between deliveries in the NPIDR and CDR groups. To maintain the medical capacity of the negative pressure facilities, only COVID-19-positive confirmed/suspected patients with emergent obstetric demands such as labor signs, unstable maternal conditions, or fetal distress were admitted to the NPIDRs. In terms of indication for admission, a higher percentage of labor signs  and duration of stay in the delivery units  were significantly shorter in the NPIDR group. Median surgical blood loss, median operative time, and rate of third- and fourth-degree perineal laceration after vaginal delivery showed no significant difference between the two groups. One mother was admitted to our ward again within 14 days from discharge due to delayed postpartum hemorrhage after vaginal delivery in the CDR group, while one re-admission within 14-day event occurred in a COVID-19-infected mother due to postpartum endometritis after vaginal delivery. The 14-day re-admission rate was not significantly different between the two groups of mothers.Information regarding maternal surgical outcomes of vaginal delivery is summarized in To compare maternal surgical outcomes of cesarean section, patients were divided into groups based on different indications of cesarean section; thus, cesarean sections due to obstructive labor, placenta previa, chorioamnionitis, and maternal request were excluded from subgroup comparative analyses . A totalp = 1.000). After initial management of the newborns, all babies in our study had Apgar scores at 5 min of more than 7. Higher rate of meconium-stained amniotic fluid (MSAF) was found in deliveries performed in NPIDRs than in CDRs (7 (4.2%) vs. 10 (22.2%), p < 0.001, respectively). Of the 11 babies from NIPDRs with MSAF were all born by COVID-19-positive confirmed mothers, 2 babies were delivered by emergent cesarean section due to non-reassuring fetal heart rate tracing and 9 babies were delivered by vaginal delivery; 3 neonates had meconium aspiration syndrome (MAS). More newborns delivered in NPIDRs had neonatal respiratory distress comparing to those born in CDRs (18 (40.0%) vs. 18 (10.7%), p < 0.001, respectively). Eighteen newborns who were delivered in NPIDRs with neonatal respiratory distress were all born by COVID-19-positive confirmed mothers; eleven were born by vaginal delivery and seven by cesarean section. Of all babies who presented with neonatal respiratory distress, those who were delivered in NPIDRs had a higher rate of oxygen therapy requirement than those delivered in CDRs (12 (26.7%) vs. 16 (9.5%), p = 0.003, respectively). Downes’ score was applied to evaluate the severity of neonatal respiratory distress; the median Downes’ score showed no significant difference between groups (p = 0.209), and most neonates who had respiratory distress was classified as mild-to-moderate respiratory distress, with Downes’ scores ranging from 2 to 5. Detailed information on the final diagnosis in newborns with neonatal respiratory distress and their demands for oxygen therapy are shown in p < 0.001) and longer median neonatal hospitalization  were also observed from deliveries in the NPIDR group than the CDR group.Perinatal outcomes and clinical presentations of neonates are presented in Based on sequential reports of postnatal COVID-19 PCR tests, no vertical transmission was found.Looking at the records of nosocomial infection surveillance in the HIS, no nosocomial COVID-19 infection was reported among patients and HCP in charge of peripartum care for COVID-19-positive confirmed/suspected cases and their newborns during the study period.Our study demonstrates a poorer short-term neonatal outcome regarding higher NICU admission rate, increased incidence of MSAF, and higher risk of mild neonatal respiratory distress in cases delivered in NPIDRs than in CDRs under the current practice of obstetric delivery management protocol for the COVID-19 omicron variant pandemic. However, the maternal surgical outcomes showed no significant difference between the two groups of patients. Previous reports have found that pregnancy increases the susceptibility and severity of COVID-19 infection, and pregnant women with COVID-19 infection are more likely to be admitted to the intensive care unit or require invasive ventilation, accompanied by increasing maternal death compared to non-pregnant women of reproductive age with COVID-19 infection ,19,20. HRespiratory distress is defined as any signs of increased work in the breathing of neonates, affecting 5% to 7% of all term newborns ,25,26. NIncreased cesarean delivery rates in COVID-19-positive confirmed mothers have been observed in previous studies ,18,35,36The use of PPE during the operation is time-consuming and makes exposure to the operative field more difficult; thus, it probably has adverse effects on the operative time and surgical outcomes . In our We performed COVID-19 PCR tests by nasopharyngeal swab for neonates 1 to 2 times within 48 h from delivery to examine vertical transmission and to preclude the possibility of a positive result due to postpartum horizontal transmission. No vertical transmission was observed based on the current protocol of specimen collection and PCR testing in our study. To precisely identify utero-placental transmission of COVID-19 infection, various fetal tissue specimen collection methods and serologic tests have been investigated in previous studies, with different rates of positive results . AlthougOur study had some limitations. First, this is a retrospective and single-institution study, so the number of cases is limited. Second, we only have the neonatal PCR test from nasopharyngeal swabs to evaluate vertical transmission, and specimen collection of other fetal tissues, including placental tissue, cord-blood, fetal rectal swabs, amniotic fluid, or other neonatal serologic tests, might provide more information regarding the utero-placental transmission of COVID-19. Despite the above limitations, our study shares the largest case series of COVID-19-positive confirmed mothers and their newborns in Taiwan during the COVID-19 omicron variant pandemic period. Furthermore, our study demonstrates the current strategy in our hospital, including COVID-19 PCR screening before admission, patient partition, TOCC risk assessment, and the establishment of practice protocol to ensure a low rate of associated maternal–fetal comorbidities, provide good accessibility to healthcare services in neighborhood areas, reduce the risk of hospital-based COVID-19 transmission, and maintain medical capacity.Our study shows that obstetric deliveries for COVID-19 omicron variant positive and suspected cases performed in NPIDRs with the rational use of PPE are not associated with adverse maternal surgical outcomes, regardless of delivery methods. Short-term perinatal outcomes were poorer in neonates of COVID-19 omicron variant positive confirmed and suspected mothers who delivered in NPIDRs compared to COVID-19-negative mothers who delivered in CDRs, with higher rates of neonatal respiratory distress, MSAF, and NICU admission. These findings might be due to more perinatal stress in obstetric deliveries performed in NPIDRs. Reasonable use of PPE in NPIDRs could effectively prevent COVID-19 nosocomial infection during the delivery of COVID-19 omicron-variant-infected pregnant women.


Liver diseases post-COVID-19 vaccination is extremely rare but can occur. A growing body of evidence has indicated that portal vein thrombosis, autoimmune hepatitis, raised liver enzymes and liver injuries, etc., may be potential consequence of COVID-19 vaccines.To describe the results of a systematic review for new-onset and relapsed liver disease following COVID-19 vaccination.For this systematic review, we searched Proquest, Medline, Embase, PubMed, CINAHL, Wiley online library, Scopus and Nature through the Preferred Reporting Items for Systematic Reviews and Meta Analyses PRISMA guideline for studies on the incidence of new onset or relapsed liver diseases post-COVID-19 vaccination, published from December 1, 2020 to July 31, 2022, with English language restriction.Two hundred seventy-five cases from one hundred and eighteen articles were included in the qualitative synthesis of this systematic review. Autoimmune hepatitis (138 cases) was the most frequent pathology observed post-COVID-19 vaccination, followed by portal vein thrombosis (52 cases), raised liver enzymes (26 cases) and liver injury (21 cases). Other cases include splanchnic vein thrombosis, acute cellular rejection of the liver, jaundice, hepatomegaly, acute hepatic failure and hepatic porphyria. Mortality was reported in any of the included cases for acute hepatic failure , portal vein thrombosis , splanchnic vein thrombosis , jaundice , raised liver enzymes , and autoimmune hepatitis . Most patients were easily treated without any serious complications, recovered and did not require long-term hepatic therapy.Reported evidence of liver diseases post-COIVD-19 vaccination should not discourage vaccination against this worldwide pandemic. The number of reported cases is relatively very small in relation to the hundreds of millions of vaccinations that have occurred and the protective benefits offered by COVID-19 vaccination far outweigh the risks. Vaccinations against coronavirus disease 2019 (COVID-19) is a crucial step in ending the current worldwide pandemic. Vaccines such as Pfizer-BioNTech, Oxford Uni-AstraZeneca, Moderna, Johnson & Johnson, Sinovac-CoronaVac, Covishield, and Sinopharm have been developed rapidly, determined as safe, approved under emergency use authorization since early 2020 and had been used widely. As of 1 May 2022, there have been more than 5 billion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine doses administered globally –5, autoiIn light of newer case reports and case-series studies that were published to describe the incidence of hepatotoxicity in patients who received the COVID-19 vaccines, we provide a systematic review of the current literature to delineate the range of liver diseases that were elicited following COVID-19 vaccination. We expect our review to provide clinicians with a thorough understanding of these rare adverse events.COVID-19” OR “SARS-CoV-2” OR “Severe acute Respiratory Syndrome Coronavirus 2” OR “Coronavirus Disease 2019” OR “2019 novel coronavirus”) AND vaccine OR vaccination AND (“liver histopathology” OR “liver disease” OR “hepatic disease” OR “liver toxicity” OR “hepatotoxicity”). The search was limited to papers published in English between 1 December 2020 and 31 July 2022. Based on the title and abstract of each selected article, we selected those discussing and reporting occurrence of new-onset or relapsed liver disease following SARS-CoV-2 vaccination.We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines PRISMA in conducting this systematic review . The folThe inclusion criteria are as follows: (1) published case reports, case series and cohort studies that focused on new-onset or relapsed liver diseases following SARS-CoV-2 vaccination that included adults as population of interest; (2) studies of experimental or observational design reporting the incidence of new-onset or relapsed liver diseases in patients post-SARS-CoV-2 vaccination; and (3) the language was restricted to English. The exclusion criteria are as follows: (1) studies that did not report data on new-onset or relapsed liver diseases due to SARS-CoV-2 vaccination; (2) studies that did not report details on identified new-onset or relapsed liver disease cases following COVID-19 vaccination; (3) studies that reported new-onset or relapsed liver disease in patients with no history of COVID-19 vaccination; and (4) duplicate publications.Six authors  critically reviewed all of the studies retrieved and selected those judged to be the most relevant. Data were carefully extracted from the relevant research studies independently. Articles were categorized as case report or case-series studies. The following data were extracted from selected studies: authors; publication year; study location; study design and setting; age; proportion of male patients; patient ethnicity; time to hospital presentation with liver pathology from day of vaccination, medical comorbidities; vaccine brand and dose ; if liver pathology is new-onset or relapsed; patient clinical presentation; abnormal laboratory indicators; biopsy examination and radiological imaging findings; treatment given; assessment of study risk of bias; and treatment outcome (survived or died); which are noted in Table The quality assessment of the studies was undertaken mainly based on the modified Newcastle–Ottawa Scale (NOS) to assess the quality of the selected studies . Items rWe examined primarily the proportion of confirmed cases who suffered liver toxicity due to COVID-19 vaccination. This proportion was further classified based on the type of liver pathology induced by the COVID-19 vaccine . Descriptive statistics were used to describe the data. For continuous variables, mean and standard deviation were used to summarize the data; and for categorical variables, frequencies and percentages were reported. Microsoft Excel 2019  was used for all statistical analyses.A total of 1587 publications were identified  was the first most-common liver disease reported following COVID-19 vaccination [eighty-three new onset cases , 127 andPortal vein thrombosis (PVT) was the second most common liver pathology reported following COVID-19 vaccination (fifty-two new-onset cases), with extra-cranial thrombosis (n = 21) , 98, 111Raised liver enzymes (RLEs) was the third most-common disease (twenty-six cases) reported following COVID-19 vaccination from our review  was the fourth most-common disease (twenty-one cases) reported following COVID-19 vaccination from our review [sixteen new onset cases , 122 andSplanchnic vein thrombosis (SVT) was the fifth most-common disease (fourteen cases) reported following COVID-19 vaccination from our review Acute cellular rejection of the liver (ACRL) was the sixth most-common disease (eight cases) reported following COVID-19 vaccination from our review Jaundice was the seventh most-common disease (eight cases) reported following COVID-19 vaccination from our review  was reported in four cases following COVID-19 vaccination from our review [four new onset cases , 78, 128Hepatomegaly was reported in three cases following COVID-19 vaccination from our review , particularly cirrhosis, hepatocellular malignancies, candidates for liver transplantation, and immunosuppressed individuals after liver transplantation appear to be at increased risk of COVID-19 infections, which in turn translates into increased mortality . TherefoSVT including portal, mesenteric, splenic vein thrombosis and the Budd-Chiari syndrome, is a manifestation of unusual site venous thromboembolism . SVT preFrom the one hundred seventy-three cases that were evaluated in our review, Oxford Uni-AstraZeneca 79 cases) , 114, Pf cases , First, while most of the evidence discussed were based on few case series and many case reports, many of these are small and performed in single centers and not necessarily generalizable to the current COVID-19 vaccination settings. Second, all studies included in this review were retrospective in design which could have introduced potential reporting bias due to reliance on clinical case records. Third, the study population included adult patients and hence its results cannot be generalized to pediatric patients. Last, study was not registered in Prospero, an international prospective register of systematic reviews, as this might have added extra work and the merit was mostly limited to the avoidance of duplication.A range of liver diseases post-COIVD-19 vaccination may occur at extremely rare rate and is likely to be immune-mediated. Reported evidence of liver diseases post-COIVD-19 vaccination should not discourage vaccination. The number of reported cases is relatively very small in relation to the hundreds of millions of vaccinations that have occurred and the protective benefits offered by COVID-19 vaccination far outweigh the risks.


Millions of COVID-19 widows worldwide face elevated mental health risks that foreshadow worsening physical health and elevated mortality. It remains unknown whether the excess mental health problems for COVID-19 widows are a result of the “bad death” experiences from COVID-19  or pandemic-induced social changes . This study examines whether older adults whose spouses died of COVID-19 disease have worse mental health  than those whose spouses died from causes other than COVID-19 before and during the pandemic. We used Survey of Health, Ageing and Retirement in Europe data collected before  and during the pandemic  to compare three groups whose spouses died (a) before the pandemic, (b) from COVID-19 during the pandemic, and (c) from non-COVID-19 causes during the pandemic. We find those spouses died from COVID-19 have higher risks of self-reported depression, loneliness, and trouble sleeping than those losing a spouse before the pandemic. However, losing a spouse due to non-COVID-19 causes during the pandemic is not significantly associated with worse mental health compared to pre-pandemic scenarios. During the pandemic, older adults whose spouses died from COVID-19 report higher risks of loneliness than those spouses died from non-COVID-19 causes. This study suggests losing a spouse due to COVID-19 presents unique mental health risks for older adults, clarifying prior theories about mental health impacts of pandemic bereavement.


Controlling the dynamics of mixedcommunities of cell-like entities(protocells) provides a step toward the development of higher-ordercytomimetic behaviors in artificial cell consortia. In this paper,we develop a caged protocell model with a molecularly crowded coacervateinterior surrounded by a non-cross-linked gold (Au)/poly(ethyleneglycol) (PEG) nanoparticle-jammed stimuli-responsive membrane. Thejammed membrane is unlocked by either exogenous light-mediated Au/PEGdissociation at the Au surface or endogenous enzyme-mediated cleavageof a ketal linkage on the PEG backbone. The membrane assembly/disassemblyprocess is used for the controlled and selective uptake of guest protocellsinto the caged coacervate microdroplets as a path toward an all-watermodel of triggerable transmembrane uptake in synthetic protocell communities.Active capture of the guest protocells stems from the high sequestrationpotential of the coacervate interior such that tailoring the surfaceproperties of the guest protocells provides a rudimentary system ofprotocell sorting. Our results highlight the potential for programmingsurface-contact interactions between artificial membrane-bounded compartmentsand could have implications for the development of protocell networks,storage and delivery microsystems, and microreactor technologies. These challenges have been recently addressedusing polymerized siloxane vesicles comprising a single membrane aperturethat functions as a size-selective pore for the capture and expulsionof colloidal particles using an encapsulated phoretic pump to achievenon-equilibrium conditions.19Syntheticcell research offers diverse opportunities to carry outcompartmentalized biomimetic reactions, unravel the foundations ofliving systems, and promote the development of bottom-up syntheticbiology.23 modulation of protein folding/unfolding, association and diffusion,26 rate enhancement of gene expression and mRNA production,29 and promotion of dissipative protein self-assembly.30 Significantly, the molecularly crowded milieu providesan interfacial barrier in water that facilitates the spontaneous captureof microscale objects by contact-dependent interactions,10 offering a potential driving force for colloidaltransport in membrane-bounded coacervate protocells furnished withtriggerable membrane dynamics. In this context, although membranizedcoacervate droplets have been prepared using molecular amphiphiles, surface complexation agents  and surface-active colloids , the boundary layersare structurally persistent and unresponsive to the uptake of externalmicroscale objects. To address this challenge, we develop a membraneconstruction process based on the spontaneous monolayer assembly andnon-equilibrium locking of stimuli-responsive Janus-like ligated gold(Au) nanoparticle surfactants at the water/coacervate droplet interface. Spontaneous membranization of the PDDA/CM-dex coacervate dropletswas accomplished by addition of tannic acid-protected Au nanoparticlesfollowed within a few seconds by (±)-1,2-dithiolane-3-pentanoicacid (thioctic acid)-modified polyethylene glycol . Similarresults were obtained using 2-mercapto-2-thiazoline-modified PEG , a monodentate TA-modified PEG , or a TA-PEG derivative with a decreasedmolecular weight (6 kDa) and acid-cleavable ketal linker propane; S7) in placeof TA-PEG. In general, stabilized droplets were produced under a limitedrange of molar ratios with insufficient or excess TA-PEG resultingin Au/TA-PEG sequestration or exclusion, respectively . In addition, the caged protocellswere not formed when the order of reagent addition was reversed, orboth components were added simultaneously. As the tannic acid-cappedAu nanoparticles alone were readily sequestered by the coacervatedroplets but excluded from the droplets when coacervate-insolubleTA-PEG was added first to homogeneously replace the tannic acid , we attributed localization of theAu/TA-PEG building blocks to the in situ formation of a low-charge,Janus-like nanoparticle surfactant at the droplet/water interface.This was consistent with zeta-potential measurements that showed aconstant near-neutral surface charge for the caged coacervate droplets (PDDA) and carboxymethyl-dextran(CM-dex) at a molar ratio of 4:9 S1. SpontFigure S11). In general, the solutes did not bind strongly to theAu/TA-PEG membrane, presumably due to the steric barrier accompanyingin situ pegylation of the amphiphilic nanoparticles but were partitionedand concentrated within the internal coacervate matrix. In contrast,micrometer-sized objects in the external environment were excludedfrom the caged coacervate droplets.Under ambient conditions, the self-assembled Au/TA-PEGmembraneexhibited high permeability to small molecules, polyelectrolytes,and nanosized objects such as proteins  and polysaccharides . Replacing TA-PEG with monodentateTA-PEG-ME also gave a solid-like membrane, indicating that bidentateligand-mediated cross-linking was not responsible for stabilizationof the Au nanoparticle shell . The absence of ligand cross-linking was consistent with otherobservations, which revealed that dissolving the coacervate interiorof Au/TA-PEG-caged droplets by slow addition of distilled water resultedin concomitant disassembly of the nanoparticle membrane . The jammed membrane was relaxedby light-driven TA-PEG disassociation and release, resulting in progressivetranslocation of the partially de-capped Au nanoparticles into thecoacervate interior and slow disassembly of the outer membrane over10 min (S15). We attributed the light-mediateddissociation at 290–390 nm to coupling between photoexcitedelectrons of the Au nanoparticles and gold–sulfur bond vibrations,44 rather than a photothermal effect associatedwith the surface plasmon resonance (SPR) band, which is also knownto cleave the gold–sulfur bond.45 The photothermal mechanism was ruled out as illumination of thecaged droplets at 500–520 nm (Au nanoparticle SPR band) didnot result in membrane disassembly .We investigated the light-mediatedmembrane dynamics of the Au/TA-PEGand Au/MTA-PEG-caged coacervate droplets by irradiating the samplesat 290–390 nm for several minutes. Fluorescence recovery afterphotobleaching (FRAP) experiments indicated that prior to light-induceddissociation, the Au/TA-PEG nanoparticle surfactants were packed intoa solid-like membrane 2d,e, whiRe-assembly of the nanoparticle membrane was accomplishedby switchingoff the light and using a shear force to drive the sequestered Aunanoparticles back to the coacervate/water interface to initiate rebindingwith TA-PEG 2h. The rFigure S17). Minimal bond cleavage wasobserved at pH values higher than 6.5, while decreasing the pH to5.3 completely hydrolyzed the ketal linkage within 60 min. Additionof glucose to the external solution of a suspension of GOx-containingcaged droplets in the presence of dioxygen resulted in a decreasein pH from 6.4 to 5.8 over 30 min .Membrane unlocking was also achieved under ambientdaylight bychemically induced ligand cleavage and dissociation using GOx-containingcaged coacervate droplets enclosed in a jammed shell of Au/TA-AE-PEG6knanoparticle surfactant building blocks. Cleavage of the ketal groupat different pH values was quantitatively determined by NMR spectroscopyS17. MiniFigure S19] was irradiated at 290–390nm. Unlocking of the membrane occurred increasingly over 6 min, givingrise to translocation of the partially de-capped Au nanoparticlesinto the PDDA/CM-dex coacervate interior and progressive uptake ofthe catalytic microparticles . Given these observations, we used a similar procedureto trigger the contact-dependent uptake and capture of POM-coatedPDDA/ATP coacervate vesicles ,36 withinthe nanoparticle-caged coacervate droplets. Under ambient daylight,the two populations of membrane-bounded protocells remained non-interactive, while the membrane-less PDDA/CM-dexcoacervate droplets spontaneously engulfed the smaller PCVs . Switching on the light source forapproximately 10 min transferred considerable numbers of the PCVsthrough the partially unlocked Au/TA-PEG nanoparticle membrane (Movie 1). The resulting host–guest membranizedcoacervate droplets remained structurally stable under ambient conditionsprovided that the illumination was not prolonged such that completedisassembly of the Au nanoparticle membrane occurred. Once trapped,the guest PCVs underwent a process of slow coalescence (S25), which was attributed to the destabilization of the POM/PDDAmembrane in the presence of the PDDA-enriched matrix of the host protocells.We used the light-inducedunlocking of the structurally stressedAu/TA-PEG nanoparticle membrane as an exogenous mechanism for triggeringthe uptake of external microscale objects 3a. As anS26) and polymer nanoparticles. In general, provided there was an appropriate size mismatch andlow interfacial tension between the host coacervate matrix and theguest protocell membrane, exposure of the mixed populations resultedin spontaneous transmembrane colloidal transfer.As transfer of the PCVs acrossthe unlocked nanoparticle membranewas facilitated by attractive interactions with the exposed PDDA/CM-dexcoacervate phase, we used the combination of light-mediated membranerelaxation and favorable coacervate partitioning to trigger the uptakeand capture of other types of protocells  (S28). This was confirmed by fluorescence-activatedcell sorting (FACS) analysis. Profiles for single populations of RITC-labeledPCVs (As an alternativestrategy, we used the endogenous GOx-mediatedproduction of protons to trigger membrane unlocking and uptake ofPCVs from the external environment. Without glucose, mixed populationsof Au/TA-AE-PEG6k-caged coacervate droplets and PCVs remained non-interactive3f. In coledPCVs 3h andFIledPCVs 3i showedledPCVs 3j. SigniledPCVs 3k.As stimuli-responsiveuptake into the unjammed caged coacervatedroplets was dependent on attractive interactions between the exposedPDDA/CM-dex coacervate core and outer surface of the PCVs or colloidosomes,we reasoned that colloidal transfer would be inhibited even in thepresence of unlocked droplets if repulsive interactions became dominantby appropriate chemical modification of the guest protocell membrane.Thus, it should be possible to establish a mechanism of triggerableprotocell sorting based on the selective uptake by unlocking the cagedcoacervate droplets in the presence of mixed protocell populationsendowed with different affinities for the exposed PDDA/CM-dex coacervatephase. As a proof-of-principle, we used a ternary community comprisingmixtures of GOx-containing Au/TA-AE-PEG6k-caged coacervate dropletsas the host system and RITC-labeled PCVs and FITC-labeled PEG-graftedcolloidosomes as cell-like objects capable of attractive or repulsiveinteractions with the PDDA/CM-dex coacervate phase, respectively 4a. AdditA new protocell model based on the membranizationof coacervatemicrodroplets with a jammed monolayer of stimuli-responsive Janus-likeligated Au/PEG nanoparticle surfactants is described and utilizedfor the contact-dependent selective capture of guest protocells inan all-aqueous environment. The structurally stressed membrane isunlocked by ligand dissociation using an exogenous light source orby chemical cleavage of the nanoparticle surfactant by enzyme-mediatedtransformations within the protocells. As a consequence, exposureof the coacervate interior to the external environment leads to contact-dependentsequestration of selective external colloidal objects that exhibitattractive interactions with the liquid–liquid phase-separatedphase.30 thereby generating artificial cell communities that operate acrossa range of length scales. This approach offers a system view of protocelldesign, providing a route to population-based synergistic behaviorssuch as collective resilience to environmental stress, multiplex tasking,and functional collaboration and specialization. In a wider context,triggerable collective interactivity between compartmentalized microscaleobjects could provide a step toward new applications in biomimeticstorage and delivery and advanced microreactor technology.In general, the combination of triggerable membrane dynamicsandconcomitant presentation of the molecularly crowded interior offersopportunities to design elaborate protocell networks that implementcomplex cytomimetic behaviors such as artificial symbiosis, networking,and sorting. In principle, such higher-level behaviors could be coupledto diverse endogenous functions associated with coacervate-based protocellmodels,