Background: An imbalance of redox homeostasis participates in tumorigenesis, proliferation, and metastasis, which results from the production of reactive oxygen species (ROS). However, the biological mechanism and prognostic significance of redox-associated messenger RNAs (ramRNAs) in lung adenocarcinoma (LUAD) still remain unclear.Methods: Transcriptional profiles and clinicopathological information were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) of LUAD patients. A total of 31 overlapped ramRNAs were determined, and patients were separated into three subtypes by unsupervised consensus clustering. Biological functions and tumor immune-infiltrating levels were analyzed, and then, differentially expressed genes (DEGs) were identified. The TCGA cohort was divided into a training set and an internal validation set at a ratio of 6:4. Least absolute shrinkage and selection operator regression were used to compute the risk score and determine the risk cutoff in the training set. Both TCGA and GEO cohort were distinguished into a high-risk or low-risk group at the median cutoff, and then, relationships of mutation characteristics, tumor stemness, immune differences, and drug sensitivity were investigated.Results: Five optimal signatures  were selected. Patients in the high-risk group had poorer prognosis, higher tumor mutational burden, overexpression of PD-L1, and lower immune dysfunction and exclusion score compared with the low-risk group. Cisplatin, docetaxel, and gemcitabine had significantly lower IC50 in the high-risk group.Conclusion: This study constructed a novel predictive signature of LUAD based on redox-associated genes. Risk score based on ramRNAs served as a promising biomarker for prognosis, TME, and anti-cancer therapies of LUAD. Lung cancer has been the leading cause of cancer-related deaths for many years worldwide . DespiteReactive oxygen species (ROS) are a cluster of short-lived molecules, which can oxidize other molecules and subsequently transition rapidly between species . In cancTumorigenesis is associated with not only genetic alteration of cancer cells but also the tumor microenvironment (TME), which includes the extracellular matrix, blood vessels, oxygen, and inflammatory cells . IncreasThis study identified prognostic and differentially expressed redox-associated genes based on the data downloaded from online cohorts. Subsequently, active and inhibited biological functions and pathways were determined. The immune-infiltrating levels and differentially expressed genes (DEGs) were also investigated. To examine the effectiveness of the model, the nomogram, survival analysis, independent prognostic analysis, TME, and drug sensitivity with the risk were explored and validated in an external cohort.http://www.gsea-msigdb.org/gsea/index.jsp), an integrated web server providing annotated gene sets of distinct species. The transcriptional profile of LUAD patients was downloaded in The Cancer Genome Atlas  including 59 normal tissues and 535 tumor tissues along with the corresponding clinicopathological phenotypes of patients with cancer single-nucleotide variant (SNV) information. The RNA sequencing data were formatted in transcripts per kilobase million and processed by log2 transformation. Since the prognostic information of CPTAC-3 is not available, we excluded the cohort from our study. Another independent cohort (GSE36471) of Gene Expression Omnibus  was chosen to validate the results externally. The rationale of selecting this cohort included the two reasons. First, the follow-up information can be obtained, which can be used for survival analysis. Second, the overlapped genes sequenced in this dataset with TCGA contained the candidates responsible for the redox signature. Statistical and bioinformatics analyses in this study were conducted using the R program (version 3.6.3 and 4.0.5).The list of redox-associated mRNAs (ramRNAs) was extracted from 20 gene sets of the Molecular Signatures Database  (log FC)|>1.5 and p < 0.01. Then, the overlapped ramRNAs were included in K-means consensus clustering to classify LUAD patients into different subtypes based on their expression levels by using the ConsensusClusterPlus package.A univariate Cox proportional hazard regression was performed to screen for survival-related ramRNAs in LUAD with the threshold of Kaplan–Meier (KM) analysis was conducted to estimate the statistical differences of survival outcomes among the clustering subtypes. To assess relationships between clustering and tumor purity, the “Estimation of Stromal and Immune cells in Malignant Tumors using Expression data” (ESTIMATE) algorithm  and Wilcp < 0.001 were included in the univariate Cox model. Significant ramRNAs were used to perform further dimension reduction through a weighted random forest and sliding window sequential forward feature selection by curtailing out-of-bag (OOB) error rate  curves and AUC values of 1-, 2-, and 3-year survival probability were adopted to reveal the accuracy and sensitivity of the prediction. The relationships between the survival status and risk score were investigated with the strategy of statistical difference measured by the Wilcoxon rank-sum test. Principal component analysis (PCA) was performed to visualize the discrimination of the model. Independent prognostic factors were determined by a univariate and a multivariate Cox proportional hazard regression with the clinicopathological phenotype information in the training set, validation set, and TCGA cohort. In addition, a nomogram model was developed based on the TCGA phenotype information and validated by calibration and concordance index (C-index). Decision curve analysis (DCA) was conducted to compare the net benefit between the risk score and traditional staging system.http://xena.ucsc.edu/) was examined. Moreover, GSEA was employed to screen for a significantly enriched biological process in the low- and high-risk groups.The top 20 mutated genes in the low- and high-risk groups were analyzed, respectively. Furthermore, the correlation between the risk and tumor mutational burden (TMB) of each sample was estimated by Spearman’s correlation coefficients. Patients with TMB information were divided into a low-TMB and a high-TMB group at the optimal cutoff for survival. Afterward, risk and TMB groups were integrated as four types of combinations: L-Risk + L-TMB, L-Risk + H-TMB, H-Risk + L-TMB, and H-Risk + H-TMB. The survival differences among the re-constructed subtypes were tested by the KM method. Stemness indices calculated by machine learning were recognized as a novel potential biomarker in anti-cancer therapies recently . In the http://timer.cistrome.org/). The immune-infiltrating differences and PD-L1 expression levels between risk subtypes were evaluated by the Wilcoxon rank-sum test. Furthermore, immune dysfunction and exclusion of immune escape mechanisms in LUAD according to Tumor Immune Dysfunction and Exclusion  were explored along with risk groups.To explore the immune differences between the low- and high-risk groups, the KW test was used to investigate the varieties of risk scores among multiple immunophenotypes, including wound healing (C1), IFN-gamma dominant (C2), inflammatory (C3), lymphocyte depleted (C4), and TGF-beta dominant (C6). The information of tumor immune-infiltrating levels estimated by TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCPCOUNTER, XCELL, and EPIC was acquired from the TIMER database (50) based on transcriptional expression profiles between the low- and high-risk groups.The pRRophetic package  was adopp < 0.001, p < 0.001), gender (p < 0.001), pathologic stage (p < 0.05), and tumor status (p < 0.01) had significant differences among the clustering subtypes (p < 0.001).The workflow of the present study is shown in subtypes . As showGSVA functional enrichment revealed that Cluster A was markedly enriched in pathways such as xenobiotic metabolism mediated by cytochrome P450, phenylalanine metabolism, steroid hormone biosynthesis, and drug metabolism induced by cytochrome P450 compared with Cluster B ; pathwayp < 0.05 out of 112 DEGs . TMB was also positively correlated with the risk score with the coefficient of 0.38 and p < 0.001 (p < 0.001).The KW test demonstrated that Cluster C exhibited the lowest risk score  was positively associated with the risk score while that of B cells (by TIMER), activated mast cells (by CIBERSORT), and M2 macrophages (by QUANTISEQ) were negatively associated with the risk score , docetaxel (p < 0.001), and gemcitabine (p = 0.006) had significantly lower IC50 in the high-risk group (p < 0.001) held higher IC50 in the high-risk group (Chemosensitivity of drugs for anti-LUAD therapies such as cisplatin (sk group , while esk group .In this study, differentially expressed survival-related ramRNAs were screened to identify the novel subtypes of LUAD with consensus clustering based on the TCGA dataset. Patients were classified into three groups, and there were statistical differences in KM survival analysis. GSVA functional enrichment analysis for distinct subtypes revealed that metabolic pathways such as phenylalanine, tyrosine, and histidine were activated in Cluster A, which promoted essential amino acid metabolism and tumorigenesis ; cytogenDEGs were further determined between each of the two clusters and obtained overlapped targets for feature selection. Subsequently, by integrating both conventional statistical methods like univariate Cox regression and machine learning strategy including weighted random forest with sliding window sequential forward feature selection, we reduced the dimension of the data structure for LASSO regression to develop an effective prognostic risk model with the median cutoff. It was illustrated that high-risk patients had poorer survival outcomes compared with low-risk patients, which was consistent in the training set, validation set, and GEO cohort. Also, each optimal signature showed differences in KM survival for LUAD patients. Thus, these agents can be potential biomarkers for prognostic prediction. ROC analysis demonstrated that AUCs reached 0.70, indicating that our model had promising accuracy and sensitivity. PCA also demonstrated an optimal discrimination of risk.Nomograms have been acknowledged as a tailored tool with a single numerical prediction of the probability of an event for cancer prognosis . This stThen, the correlations were explored among clustering subtypes, risk, and mutation characteristics. The KW test showed patients from Cluster C had the lowest risk score and better survival, which fit well with the KM result of clustering subtypes. Previous studies demonstrated that MUC16 mutation associated with response to immune checkpoint inhibitors in solid tumors and TP53 mutation status had potential predictive values for response to PD-1 blockade immunotherapy in LUAD . Our res+ Th1/Th2, whereas the risk score was negatively correlated with cells such as B cells, neutrophils, NK cells, and T-cell regulatory. These reflected that high-risk LUAD patients had stronger immunosuppression and weaker immunoreactivity.Immune regulation is pivotal to the development and progression of LUAD affected by the proportion of infiltrating immune cells . The risTIDE is an inventive computational protocol to screen two factors, including the induction of T-cell dysfunction and the prevention of T-cell infiltration in tumor tissues, which has been validated as an effective biomarker of prognostic prediction . Our res50 of chemotherapeutics such as cisplatin, docetaxel, and gemcitabine, while erlotinib had higher IC50 in the high-risk group. The aforementioned results indicated these signatures of out model might play a vital role in tumor cell sensitivity or resistance. However, as the database is limited, the half maximal inhibitory concentration of more target therapy and immunotherapy drugs are not investigated in this study and requires more research to confirm and explore the findings.Finally, drug sensitivity analyses implied that the low-risk group was related to higher ICHowever, some limitations should be considered in this study. First, we only used retrospective datasets for this study, and a multi-center prospective clinical cohort of LUAD samples is a necessity to verify the stability of phenotyping. In addition, further experiments are still needed to investigate the relationship between the redox signature and immunotherapy and reveal how ramRNAs affect genomic instability. In the future, the combination of ramRNAs and immunotherapy may be a promising strategy for LUAD treatment.In conclusion, this study successfully constructed a novel predictive signature of lung adenocarcinoma based on redox-associated genes, which had optimal prognostic values and affected TME cell-infiltrating characterization. Moreover, the model helps researchers understand the association between redox and tumorigenesis. This study contributes to guiding more effective strategies for TMB and anti-tumor immunotherapy.


Neuraminidase (NA) is an important surface protein on influenza virions, playing an essential role in the viral life cycle and being a key target of the immune system. Despite the importance of NA-based immunity, current vaccines are focused on the hemagglutinin (HA) protein as the target for protective antibodies, and the amount of NA is not standardized in virion-based vaccines. Antibodies targeting NA are predominantly protective, reducing infection severity and viral shedding. Recently, NA-specific monoclonal antibodies have been characterized, and their target epitopes have been identified. This review summarizes the characteristics of NA, NA-specific antibodies, the mechanism of NA inhibition, and the recent efforts towards developing NA-based and NA-incorporating influenza vaccines. Influenza is an acute respiratory infection that causes significant global morbidity and mortality annually, as well as a large economic burden . In addiThe primary mechanism of protection against influenza infection is vaccination. Live-attenuated, split-inactivated, and recombinant protein platforms are all currently used in influenza vaccines . CurrentViruses from the family Orthomyxoviridae are enveloped viruses characterized by having eight segmented, negative-sense RNA genomes . There aThe influenza life cycle begins with HA attachment to sialic-acid (SA) receptors on the host cell surface . SA is fNA is assembled as a homotetramer of approximately 240 kDa in size and is anchored in the envelope of the virus . Each ofThe constant immune pressure on influenza viruses leads to the generation of new strains with minor changes in their structure in a process called antigenic drift, rendering pre-existing antibodies potentially less effective . ConsequCompared to HA, less is known about antibody epitopes and antigenic sites on NA. Characterizing these epitopes will help in understating the antigenic drift of NA and future universal vaccine development. In order to characterize and identify NA antigenic sites, several studies were carried out using mAbs and/or recombinant NA proteins ,62,63,64Vaccination is the best approach available to prevent influenza virus infections. The most commonly used vaccine is the split inactivated influenza vaccine . The quaNA content in vaccines correlates with anti-NA antibody response rates ,83. IncrSignificant progress has been made on the path toward a universal influenza vaccine. Neuraminidase is currently a major focus among scientists to reach that goal. NA usually shows lower antigenic drift rates compared to HA. Anti-NA antibodies have been shown to be cross-protective after being challenged with different influenza strains. In addition to NA, there are other targets for a universal vaccine, including the M2 ion channel and the HA stem, as well as some HA head approaches ,99. Sinc


Endotracheal tube (ETT) malposition is common in neonatal intubation. Recommendations for ETT insertion depths predominantly address orotracheal intubation. The aim of this study was to develop gestational age-, weight-, and length-based curve charts and tables for nasotracheal ETT insertion depth recommendations in neonates.In this retrospective single-center study, the individual optimal ETT insertion depths in neonates were determined by evaluating postintubation radiographic images. Gestational age-, weight-, and length-based best-fit curves and tables were generated using regression analysis to calculate related ETT insertion depths. The insertion depths predicted by the models were compared with previously published recommendations.R2 values between 0.766 and 0.837. The insertion depths predicted by the models revealed certain deviations when compared with four previously published recommendations for nasotracheal ETT depth estimation in neonates.We analyzed intubations of 178 neonates . Applying sigmoidal logistic regression models, curves, and tables revealed The charts and tables developed in this study enable a fast and accurate determination of recommended nasotracheal ETT insertion depths in neonates. Endotracheal intubation in neonates is a potentially life-saving procedure in the delivery room and the neonatal intensive care unit. Precise positioning of the endotracheal tube (ETT) is essential to reduce the incidence of complications, including atelectasis, barotrauma, pneumothorax, unplanned extubation, post-extubation stridor, and asymmetrical surfactant distribution .Chest radiography is the gold standard for confirming the correct ETT position . NeverthNumerous recommendations, most of which refer to orotracheal intubation, have been proposed to achieve correct tube placement within the trachea in neonates –7. HowevThe aim of this study was to develop gestational age (GA)-, weight-, and length-based charts and tables to determine recommendations for correct nasotracheal ETT insertion depths based on a significant cohort of neonates.®, Siemens Healthcare, Erlangen, Germany; ICM®, Draeger, Luebeck, Germany). Extracted information included sex, GA, weight, length, and ETT insertion depth.Intubated pediatric patients admitted to the neonatal intensive care unit of our tertiary perinatal center from January 2017 to March 2021 were retrospectively evaluated. Clinical patient data were obtained by reviewing the hospital’s healthcare information systems . Routine postintubation chest radiography was conducted in an anterior-posterior position, with a focus-to-film distance of 100 cm, and the child’s head placed in the midline position. Radiographs were taken with the mobile digital radiography systems Samsung GM60 (January 2017 to January 2018) and Samsung GM85 (February 2018 to March 2021) in combination with the digital flat panel X-ray detector S3025-W . Two different investigators measured the tip-to-carina distance independently on the radiograph images. Patients were excluded if the radiograph’s quality was too poor to identify ETT tip and carina. Interobserver discrepancies were resolved by re-evaluation.The patients were allocated into predefined categories for GA, weight, and length . A distiEthical approval for this study (WF-x159/20) was provided by the ethical committee of the local medical chamber.Statistical analysis was performed using SPPS, version 27  and GraphPad Prism 9 . Data on neonatal demographics were expressed as the median and range for continuous variables and as counts and percentages for categorical variables.R2 values were calculated to determine the goodness-of-fit for each regression model.The individual optimal ETT insertion depth was plotted against GA, weight, and length for all neonates. The best-fit curves for proposed ETT insertion depths were calculated using linear and non-linear regression models. The 95% prediction bands enclosing the area that included 95% of future data points were generated. The target ETT insertion depths based on our data and previously published recommendations were plotted for comparison.Study criteria were met by 178 patients , of whicR2 values revealed a more accurate fit of the regression models for weight and length-related curves than the GA-related curve  compared to length-based (R2 = 0.814) or GA-based (R2 = 0.766) estimations. This is consistent with the findings of Maiwald et al. demonstrating a goodness-of-fit for the weight- and GA-based regression models  similar to our study.Consistent with the findings of previous studies, the relationship to the optimal ETT depth was linear for GA and body length and non-linear for body weight  13, 17), 1713, 1We identified four published recommendations for nasotracheal ETT insertion depth in neonates –15. The So far, no length-based recommendations for nasotracheal ETT depths have been published. However, length-related guidance demonstrated a similar accuracy as weight and may be especially useful in the delivery room setting, where the body length can be easily determined.The charts and tables presented in this study enable a rapid recommendation of ETT insertion depths and can be a valuable initial guiding tool for neonatal intubation. However, the accuracy and performance of our recommendations require prospective validation.This study has some limitations. Due to the study’s retrospective design, we estimated the optimal ETT depths using indirect methods. Our clinical routine includes conducting chest X-rays with the head in a neutral position. However, we could not verify the degree of the head-neck flexion in this retrospective study.We present accurate recommendations for nasotracheal ETT insertion depths for neonates as charts and tables based on a large data set.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ärztekammer Hamburg. Written informed consent from the participants’ legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.CE: conceptualization, methodology, formal analysis, writing—original draft, and project administration. KS: methodology, formal analysis, and investigation. MW, JH, and DS: visualization and writing—review and editing. PD: methodology, formal analysis, writing—review and editing, supervision, and project administration. All authors contributed to the article and approved the submitted version.


JCI, Dupont, Berg, and co-authors provide strong evidence that impaired placental perfusion, placental ischemia, increased soluble fms-like tyrosine kinase 1 (sFLT1), and a maternal preeclampsia–like phenotype are associated with an inability to upregulate the l-tryptophan–derived l-kynurenine pathway during pregnancy in mice with blunted renal reserve. These surprising revelations underscore the curious quiddity of l-tryptophan.For patients and caregivers to be fully informed about how living organ donation or prior kidney injury affects future health, we need to better understand the role of kidney reserve in physiological adaptation, especially during pregnancy. Importantly, epidemiological studies reason that live kidney donors are at increased risk for developing preeclampsia, a hypertensive disorder of pregnancy with serious implications for maternal and fetal health. Despite the import of this finding, the mechanistic basis for this increased risk is not understood. In this issue of the  It is encoded by triplet UGG, the odd person out in the trio of translation-termination codons . Diverse chemical modifications of l-tryptophan yield a remarkable variety of tryptophan-derived indole structures; more than 600 indoles are known. Indoles with known physiologic functions include the neurotransmitter 5-hydroxytryptamine (serotonin) and vitamin B3 (one form of which is niacin), among others. Other indoles have more curious stories. Collectively, the indoles are compounds containing a benzene ring fused to a five-membered, nitrogen-containing pyrrole ring. The name is a portmanteau of indigo and oleum, as indole was first synthesized from indigo dye and oleum. The distinctive color of “blue-gold” indigo shadows human clothing history from the traditional dress of Saharan Tuaregs to contemporary denim blue jeans. An uncommon feature of urinary tract infections is purple urine, which reflects the curious accumulation of urinary indigo and indirubin dyes that are derived from gut metabolism of l-tryptophan. It is hard to imagine how indigo dye, serotonin, and niacin all share a common chemical indole structure. In this issue of the JCI, Dupont, Berg, and colleagues provide insight into the role of another indole-derived product, specifically, l-tryptophan–derived l-kynurenine, during pregnancy  in the kynurenine pathway to kynurenine, kynurenic acid, and xanthurenic acid, which further allows l-tryptophan to be converted to α ketoglutarate and oxidized or, when necessary, used in the synthesis of nicotinamide and nicotinamide adenine dinucleotide (NAD)  . Kidney l injury . Kynurenl injury . In renal injury , 8.JCI, Dupont, Berg, and co-authors report that outbred mice with reduced renal reserve had impaired physiological adaptations during pregnancy  increases 50%, and renal blood flow increases 80%, with subsequent decreases in serum creatinine, urea, and uric acid values. Thresholds for thirst and the release of antidiuretic hormone release are depressed. The changes observed in total body sodium and intravascular volume that are orchestrated by the kidneys require an adequate reserve of kidney function in order to mediate these adaptive changes. In this issue of the l-tryptophan metabolites, especially components of the l-kynurenine pathway, are important for pregnancy adaptation  in the liver or indoleamine-2,3-dioxygenase (IDO1 or IDO2) outside of the liver (l-tryptophan to l-kynurenine in extrahepatic tissues, Dupont, Berg, and colleagues examined the role of IDO1 in regulating serum l-kynurenine levels during pregnancy, especially in the setting of reduced renal reserve (l-tryptophan metabolism via the l-kynurenine pathway is upregulated as a result of placental IDO expression. Previous studies in mice genetically deficient in the IDO enzyme suggested that blocking l-tryptophan conversion to l-kynurenine in the placenta could lead to impaired placentation and pregnancy complications such as preeclampsia (l-tryptophan deficiency, possibly due to upregulation of l-tryptophan–metabolizing TDO and IDO enzymes in other organs or impaired renal l-tryptophan resorption. l-Tryptophan is needed to support the increased protein synthesis observed in fetal and uterine tissues, and expression of the IDO enzyme in the placenta diverts l-tryptophan to the l-kynurenine pathway. The authors argue that l-tryptophan deficiency due to kidney impairment is even more pronounced in the pregnant state (What pathways are implicated? Most of the free tryptophan in a cell is degraded through the he liver . Becauseenase IDO or IDO2 clampsia . Dupont,enase IDO or IDO2 nt state .l-kynurenine pathway may be one of the key pathways mediating the renal adaptation of pregnancy. Enhanced l-kynurenine biotransformation provides an important adaptive response in the pregnant state. This biotransformation is deficient when renal mass and/or functional reserve is compromised, potentially setting the stage for preeclampsia.Epidemiological studies indicate that living kidney donors are at increased risk for developing preeclampsia, a hypertensive disorder of pregnancy with serious implications for maternal and fetal health , 19. Mor


Medication non-adherence, i.e., patients not taking medications as prescribed, diminishes clinical outcomes and quality of life. This phenomenon is endemic, leading to an estimated 200,000 premature deaths and 125 billion Euros of excess healthcare costs each year in Europe alone [Medication adherence (MA) consists of three interrelated phases: initiation (first dose taken), implementation (daily regimen management) and discontinuation (last dose taken) . In SwitThe high prevalence and consequences of medication non-adherence have attracted considerable attention over the past 30 years. Researchers, clinicians and policymakers search for improved methods to assess this phenomenon and its determinants, along with effective MA-enhancing multifaceted interventions tailored to patients’ needs .In 2011, the UK’s National Health Service (NHS) introduced the largest-ever national evidence-based MA intervention: the New Medicine Service (NMS) . After cWhile evidence on addressing medication non-adherence is available, translation of that evidence into real-world clinical practice remains challenging. In Switzerland, no adherence-focused national programs or guidelines have been developed, implemented or evaluated .https://www.cost.eu/actions/CA19132/) in 2020 was well-timed [Therefore, the launch of the European Network to Advance Best practices and technoLogy on medication adherencE (ENABLE), a Cooperation in Science and Technology (COST) Action  connect Swiss and international stakeholders; and 2) initiate MA priority-setting, particularly regarding implementation of MA interventions and technologies.Seventy-five participants including researchers, clinicians, healthcare industry delegates and one policymaker, from 34 countries took part. Keynote lectures and an interprofessional roundtable highlighted the state-of-the-art MA understanding regarding the place for digital technology in real-world settings, alongside strategies to address non-adherence. Priorities to move toward a more favourable, multilevel ecosystem for developing, implementing and maintaining MA interventions in Switzerland were discussed. While the highest priority was identified as support to the implementation of MA interventions in real-world settings, education, research and policy measures were also highlighted .The ideas discussed were organized into a framework —partly fWhile MA is a major public health concern that warrants high-priority treatment by health authorities, it remains absent from Swiss policymakers’ agendas. As a first step, raising awareness for MA and promoting research are needed to change the mindset and attitudes of the population, health care professionals (HCPs), and all other stakeholders.To achieve synergies, stakeholders must work interprofessionally, fine-tuning their actions, and engaging their responsibilities to collaboratively monitor and maximize MA in the ecosystem. Connecting innovative ecosystems in Switzerland  and public-private-partnerships will foster further MA development .While reimbursement of MA interventions -by health insurers- will enhance adoption of these interventions in clinical practice, the scientific basis to support reimbursement should go beyond demonstration of MA improvement. A clear value statement is needed in which the effects of MA interventions guarantee favorable clinical outcomes .Along with shared decision-making and therapeutic education, the patient-as-partner paradigm is critical to raise MA awareness and for mutual learning.However, efforts should not only target the individual level. Building trusting partnerships and communication across all HCPs and patients reinforces MA by decreasing conflicting information and ensuring continuity of care. Emphasizing MA interventions, behavioural training and interprofessional competencies should be integrated within the training curricula of all involved HCPs  to develop competencies vital to MA management in clinical practice. Integrated care models powered by digitalization provide fertile ground for these efforts and innovations.Measuring MA and its determinants in routine practice enables researchers to know when patients have MA difficulties or underlying non-adherence risk factors and provides an informed basis for clinical decision-making. In routine practice, adherence should be treated both as a patient’s fifth vital sign and as a system-level indicator of quality of care. Technology  can be helpful, but must be designed to match patients’ and HCPs’ preferences.Internationally, research evidence underscores the value of multilevel interventions, monitoring and equipping HCPs to address MA , 4. HoweFirst, key interprofessional cross-sectoral stakeholders need to be identified to address MA in the multilevel ecosystem and to determine contextually appropriate multilevel MA interventions. Every step will need to fit within a national Swiss MA strategy.Second, efforts towards coordinated care models must be strengthened and tailored to facilitate MA management. Technology-based innovations and digital health infrastructure  and use of new technologies  and methodologies  have the potential to facilitate or contribute directly to interventions. Importantly, technology literacy needs to be concurrently enhanced at the patient and HCP levels.Third, contextually appropriate implementation strategies  need to be integrated using a multilevel approach.Fourth, research funding schemes must be adapted to provide opportunities for MA research . Researchers should be encouraged to expand their foci from traditional efficacy/effectiveness research to include evaluation of implementation strategies for MA interventions in real-world settings.Finally, to maximize impact, the synergies between bottom-up and top-down approaches, public/private initiatives and interprofessional collaborations are required to power much-needed change.The Swiss COST ENABLE conference built on its participants’ critical knowledge, competencies and experience of interprofessional dynamics to define priorities to tackle MA as a major public health issue. One point was clear: translating MA-relevant evidence into real-world outcomes demands multilevel approaches.Through the Swiss ENABLE conference, diverse presenters and participants committed to raising MA awareness. Regarding the knowledge and practice gap, an initial consensus was reached on three early steps: provide the foundations for MA-supportive ecosystems, translate effective interventions into clinical practice and promote research into MA-enhancing technologies. The Swiss strategies discussed here will potentially inform research activities, policies and implementation of MA interventions across Europe.


Recent innovations in single-cell chromatin accessibility sequencing (scCAS) have revolutionized the characterization of epigenomic heterogeneity. Estimation of the number of cell types is a crucial step for downstream analyses and biological implications. However, efforts to perform estimation specifically for scCAS data are limited. Here, we propose ASTER, an ensemble learning-based tool for accurately estimating the number of cell types in scCAS data. ASTER outperformed baseline methods in systematic evaluation on 27 datasets of various protocols, sizes, numbers of cell types, degrees of cell-type imbalance, cell states and qualities, providing valuable guidance for scCAS data analysis.https://aster.readthedocs.io/ under the MIT License. It can be seamlessly integrated into existing scCAS analysis workflows. The source code is available at https://github.com/biox-nku/aster.ASTER along with detailed documentation is freely accessible at Bioinformatics online. Rapid advances in single-cell chromatin accessibility sequencing (scCAS) technologies, such as single-cell assay for transposase-accessible chromatin with sequencing, have enabled the characterization of epigenomic heterogeneity and the interrogation of gene regulation at an unprecedented resolution. A number of embedding and clustering methods have been proposed to identify groups of cells with similar epigenomic patterns in scCAS data . HoweverSeveral methods have been proposed specifically for cell-type number estimation in single-cell RNA sequencing (scRNA-seq) data , and theaccurately estimate the number of cell types in scCAS data.To address this need, we propose a Python package named ASTER to Given a peak-by-cell scCAS data rategies . Firstlyegies  and estimation deviation  as recommended in a recent benchmark study , includiAs shown in To mimic protocols that generate sparser scCAS data, we downsampled the reads in BoneMarrowA, which provides cell-type labels after fluorescent-activated cell sorting. ASTER consistently outperformed other methods when the dropout rate varied from 5% to 90% . We alsoBased on comprehensive experiments on multiple datasets, ASTER provides an accurate way to estimate the number of cell types in scCAS data. We anticipate that ASTER will provide a valuable guidance and greatly assist with refining cell ontology in scCAS data analysis.btac842_Supplementary_DataClick here for additional data file.


Acremonium chrysogenum, plays a major and demanding role in both producing modern antibiotics and developing new ones. CPC serves as a core compound for producing semi-synthetic cephalosporins that can control infections with different resistance mechanisms. We therefore summarize our latest knowledge about the CPC biosynthetic pathway and its regulation in the fungal host. Finally, we describe how CPC serves as a key lead generation source for the in vitro and better, in vivo synthesis of 7-aminocephalosporanic acid (7-ACA), the major core compound for the pharmaceutical synthesis of current and future semi-synthetic cephalosporins.Antibiotics are antibacterial compounds that interfere with bacterial growth, without harming the infected eukaryotic host. Among the clinical agents, beta-lactams play a major role in treating infected humans and animals. However, the ever-increasing antibiotic resistance crisis is forcing the pharmaceutical industry to search for new antibacterial drugs to combat a range of current and potential multi-resistant bacterial pathogens. In this review, we provide an overview of the development, innovation, and current status of therapeutic applications for beta-lactams with a focus on semi-synthetic cephalosporins. Cephalosporin C (CPC), which is a natural secondary metabolite from the filamentous fungus •Latest literature on cephalosporin generations•Biotechnical production of cephalosporins•In vivo production of 7-ACA The modern medicinal era is basically marked by the discovery of penicillin in 1928 by Alexander Fleming in London, a significant milestone that saved countless human lives from lethal infectious diseases Fleming . The larFollowing the successful discovery of penicillin, three other main classes of beta-lactam antibiotics based on natural secondary metabolites were developed over the last century. These were cephalosporins and carbapenems, comprising a bicyclic nucleus resembling penicillin’s core chemical structure, discovered in 1948 and 1976, and subsequently in 1981, monobactam antibiotics, which represent a unique class of beta-lactam antibiotics characterized by a monocyclic system  and narrow-spectrum penicillins  are most active against Gram-positive organisms, while the broad-spectrum penicillins  are active against both Gram-positive and Gram-negative bacteria  exceeded the number of narrow- and wide-spectrum penicillins  as recorded by the healthcare database from 2004 to 2014 mentioned above  was the first cephalosporin antibiotic compound isolated. Its chemical structure was characterized soon after its discovery by Giuseppe Brotzu from Italy in 1945 , which cross-link the linear glycopeptides to form a 3-dimensional structure. As a characteristic feature of beta-lactam antibiotics, cephalosporins bind to PBPs by mimicking the structure of glycopeptides, irreversibly inhibiting bacterial cell wall production   or some species from Enterobacteriaceae    have been suggested to enhance bactericidal action, even in the presence of a certain level of resistance to the antibiotic alone , in 2017, cephalosporins represented 11.6% of antibiotic consumption in the community , the vancomycin-resistant enterococci (VRE) and MRSA pathogens were prioritized for enhanced surveillance, control, and research activities investigating new active ingredients.As a milestone in modern medicine, the discovery of antibiotics has saved countless lives following medical procedures such as surgery and when treating numerous infectious diseases. However, the improper use of antibiotics threatens our health system and ability to save lives. In Europe, about 33,000 people die every year due to infections caused by antibiotic-resistant bacteria  in 2020, under the trade name Fetroja  is exclusively produced by the filamentous fungus cefT gene, encoding a putative efflux pump, was reported to be involved in CPC export . These three amino acids are catalyzed to form the tripeptide ACV by the ACV-synthetase in the cytosol. Cyclization of the ACV molecule is mediated by isopenicillin N (IPN) synthase. From here on, the biosynthesis pathways differ for different groups of beta-lactam antibiotics. In cephalosporin biosynthesis, the resulting IPN is isomerized to penicillin N through the two-component epimerases located in peroxisomes. The subsequent reaction occurs in the cytosol again, where penicillin N is converted to deacetoxycephalosporin C (DAOC) by DAOC synthetase. Here, the five-membered thiazolidine ring attached to the beta-lactam ring is expanded to the six-membered dihydrothiazine ring, which is the distinctive structure of cephalosporins. DAOC side chain modification facilitated by a cytoplasmic hydroxylase follows, generating deacetylcephalosporin C (DAC). Finally, acetyltransferase adds an acetyl-CoA (coenzyme A) group to DAC to produce CPC. CPC is actively secreted from the fungal cytosol to the extracellular space as a natural antibacterial substance. However, the transport mechanism is still unclear, although the A. chrysogenum genes encoding CPC biosynthetic enzymes have been investigated by many research groups at their mRNA levels in different phases of fermentation, with or without additional supplements, or under different growth media conditions. Several studies indicated that various regulatory factors such as methionine, glucose, and ambient pH alter transcriptional levels of biosynthetic genes, initiating the regulation of CPC biosynthesis  is another example that modulates the ATP level in fungal cells, thus regulating the energy supply for CPC biosynthesis   is the fundamental substrate of most of the semi-synthetic cephalosporins. Some cephalosporins, such as oral cefadroxil and cefalexin from the first-generation cephalosporins, are derived from 7-amino-deacetoxycephalosporanic acid (7-ADCA). These effective cephalosporins are chemically derived by various side chain modifications on the C-3 and C-7 positions of 7-ACA, establishing broad and robust antibacterial activity and high chemical stability . The second enzyme is the GL-7-ACA acylase which converts GL-7-ACA to the final product 7-ACA. GL-7-ACA acylase is a heterologous recombinant protein produced and isolated from E. coli, and applied in vitro as an immobilized biocatalyst  Fig. . CCAs haE. coli (Li et al. CCAs are synthesized as inactive precursor polypeptides and then undergo a post-translational enzymatic activation process. The molecular mechanism is well characterized via site-directed mutagenesis and protein mass spectrometry analysis (Kim and Kim The challenge of applying CCA in industrial production is that CCA takes GL-7-ACA as a primary substrate and shows low activity with CPC. In the last two decades, many studies have been performed on the engineering potential of CCAs. Some acylases or glutaryl amidases were modified to efficiently cleave the acyclic amide bond in CPC (Kim and Hol E. coli (Groeger et al. A. chrysogenum. Mass spectrometry analysis showed that the bacterial enzyme is processed successfully in the fungal cell, and the active enzyme is secreted into the culture supernatant. Using optimized fermentation-incubation conditions, the researchers observed a 30% conversion rate from CPC to 7-ACA. It is to be anticipated that transfer of this laboratory approach to industrial production lines will require adaptation to large manufacturing scales and facilities. Nevertheless, this straightforward approach minimizes sophisticated manufacturing processes, and would be ecologically and economically beneficial for sustainable antibiotic production.Pharmaceutical companies have used highly active CCAs for one-step conversion since 2006, applied as an immobilized biocatalyst produced by A. chrysogenum plays a crucial role as the industrial producer of CPC, the substrate for the enzymatic production of 7-ACA. Therefore, investigating the CPC-producing fungus A. chrysogenum and novel 7-ACA production methods is highly attractive for industrial and economic reasons.Cephalosporin antibiotics are widely prescribed for various bacterial infections in the community and, more importantly, for severe infectious diseases in hospitals caused by antibiotic-resistance bacteria. Most semi-synthetic cephalosporins are derived from the core building block 7-ACA by chemically modifying side chains. Here, A. chrysogenum strain improvements. Meanwhile, another approach to reducing manufacturing costs is minimizing the enzymatic processes after the fermentation steps. One-step direct conversion from CPC to 7-ACA has been achieved in vitro using CCA on an industrial scale (Groeger et al. Discovering environmentally harmless and sustainable manufacturing processes would undoubtedly benefit future pharmaceutical processes. The industry has constantly been seeking solutions for lowing manufacturing costs. For that, industrial companies have accomplished maximizing CPC yields from fungal fermentation via routinely performed


Various constraint-based optimization approaches have been developed for the computational analysis and design of metabolic networks. Herein, we present StrainDesign, a comprehensive Python package that builds upon the COBRApy toolbox and integrates the most popular metabolic design algorithms, including nested strain optimization methods such as OptKnock, RobustKnock and OptCouple as well as the more general minimal cut sets approach. The optimization approaches are embedded in individual modules, which can also be combined for setting up more elaborate strain design problems. Advanced features, such as the efficient integration of GPR rules and the possibility to consider gene and reaction additions or regulatory interventions, have been generalized and are available for all modules. The package uses state-of-the-art preprocessing methods, supports multiple solvers and provides a number of enhanced tools for analyzing computed intervention strategies including 2D and 3D plots of user-selected metabolic fluxes or yields. Furthermore, a user-friendly interface for the StrainDesign package has been implemented in the GUI-based metabolic modeling software CNApy. StrainDesign provides thus a unique and rich framework for computational strain design in Python, uniting many algorithmic developments in the field and allowing modular extension in the future.https://github.com/klamt-lab/straindesign) and is also part of the latest CNApy package.The StrainDesign package can be retrieved from PyPi, Anaconda and GitHub ( Various constraint-based methods have been developed for the computer-aided design of metabolic networks and for the targeted optimization of microbial cell factories. As the first method of its kind, OptKnock .https://zenodo.org/record/4700490), CNApy , CNApy . A singlHerein, we present the Python package StrainDesign, which aims to provide an integrated and extendable framework for MILP-based strain optimization approaches. StrainDesign also offers tools for the efficient analysis of calculated design strategies and a developed interface for CNApy provides the option to access most features and methods of the package via a user-friendly graphical environment.The StrainDesign package integrates currently four of the most popular MILP-based strain design approaches RobustKnock , OptCoupThere are various features, options and parameters that can be used for the specification of design problems, for example, allowance of interventions on reaction or gene level, regulatory interventions, reaction (or) gene additions, number of solutions to be calculated, the maximal number of allowed interventions, allowance of sub-optimal  solutions to speed-up calculations and many others.The computational pipeline is largely standardized for all design problems and involves a comprehensive preprocessing routine. As one building block, if the user demands to compute intervention sets operating on genes, gene–protein-reaction associations are compressed and integrated into the metabolic network structure as described in With its supported features, StrainDesign can emulate several other computational strain design approaches including gMCS , OptKnocA collection of canonical linear-programming-based analysis tools complements the actual design algorithm. These tools are, on the one hand, useful to analyze a wild type’s metabolism  and to formulate, from this information, realistic strain design goals. On the other hand, these analysis tools are indispensable for validating and evaluating computed strain designs regarding their fitness and production capacities. Analysis methods integrated in the StrainDesign package include flux balance analysis (FBA), FVA, true yield optimization through linear-fractional programming . StrainDThe StrainDesign Python package operates on COBRApy models. Since COBRApy ships with the open-source MILP solver GLPK, no further packages are required for small-scale computations. The more powerful MILP solvers IBM CPLEX, Gurobi and the open-source alternative SCIP . The latest CNApy package (release 1.1.1) contains the GUI interface for StrainDesign.StrainDesign can be retrieved from the package indexes PyPi and Anaconda. Source code, examples and documentation are available on GitHub  with multi-level (nested) optimization approaches. Together with the different supported intervention types, a huge variety of design problems can be formulated and state-of-the-art network compression techniques allow their efficient treatment also in large-scale networks. Regarding MEWpy and cameo, two existing Python-based packages for metabolic network design, our toolbox complements MEWpy, which focuses on evolutionary algorithms for strain design, and it has only a small overlap (OptKnock) with cameo. The StrainDesign toolbox can be used in Python scripts or programs or accessed via the GUI of CNApy. The integration of further strain optimization techniques in the future is facilitated by a modular structure of the computational pipeline.P.S.: investigation, software (main developer), writing . P.S.B.: software , writing (review and editing). A.V.K.: software (efmtool interface and testing), writing (review). S.K.: Supervision, funding acquisition, software (testing), writing (review and editing).This work was supported by the German Federal Ministry of Education and Research [de.NBI partner project ‘ModSim’ (FKZ: 031L104B)] and by the European Research Council [721176].Conflict of Interest: none declared.


The research model was empirically evaluated by surveying 326 customers who have shopped through the community e-commerce platforms. The results indicate that e-service quality  positively affects customer engagement behavior. Besides, customer trust and perceived risk play a mediating role between e-service quality and customer engagement behavior. This study offers recommendations to managers on how to build an attractive community e-commerce platform to stimulate customer engagement behavior.Customer engagement behavior is a critical success factor for community e-commerce. While many community e-commerce websites are currently improving service quality to enhance customer engagement behavior, little is known about how such e-services affect customer engagement behavior. Building upon the  The emergence of e-commerce platform has changed the way of traditional retail trading, fundamentally breaking the limitation of time and space, and providing enterprises and customers with a convenient interactive platform. It is more convenient for customers to realize their purchasing and social needs on the e-commerce platform, and customer engagement behavior has become a critical determinant for the success of e-commerce platforms . In highCommunity e-commerce involves an interactive and sharing e-commerce model, which drives the completion of customers’ purchase transactions through social interaction, information sharing, and content generation among members in a virtual community  What impact does the e-service quality of community e-commerce platforms have on customer engagement behavior? To explain the impact of e-service quality, this study developed a research model that connects the e-service quality of community e-commerce platforms  to customer engagement behavior, through customer trust and perceived risk. In so doing, this study investigated: (RQ2) How do customer trust and perceived risk mediate the relationship between e-service quality and customer engagement behavior?To better understand if and how the e-service quality of community e-commerce platform influences customer engagement behavior, this study systematically explored the effects generated by the e-service quality of community e-commerce platform . This study is guided by two research questions: stimulus-organism-response (SOR) model can be used to understand the effect of websites’ characteristics on customer behaviors  and virtual community . HoweverHowever, because community e-commerce shopping entails significant human-computer interaction and interpersonal interaction, it is necessary to consider both the e-service and customer perception thereof together. In the community e-commerce literature, preliminary evidence suggests that the e-services of community e-commerce platforms may affect consumers differently depending on their unique needs . HoweverThe SOR model emphasizes that certain factors in the environment (stimulus) influence the internal emotional and cognitive states of an individual (organism), and thereby influence the individual’s behavior (response) . AccordiGiven the different perspectives of these studies, various factors have been suggested to measure customers’ perceived state, such as trust and perceived risk. From the results of these studies, the SOR model not only is well suitable for explaining how a certain website stimulus  affects customer perception, and then affects customer engagement behavior. By establishing a causal relationship between stimulus, organism, and response, it also provides a reasonable mechanism to track the effects caused by the e-service quality of community e-commerce platform. The e-services of community e-commerce platforms are designed to stimulate specific cognitive perceptions of customers to increase purchase intention and social interaction . NumerouService quality has been widely recognized as a prerequisite for customer perception . E-serviE-service quality has different dimensions, suggesting that there are different ways to influence customer perception in a specific environment. System design, which provides the basis for all other dimensions of e-service quality, is composed of functions that provide customers with personalized interface presentations, covering all processes of customer page browsing, information search, and community selection , this study draws on two factors, customer trust and perceived risk. Literature suggests that customer trust and perceived risk can significantly influence customer behavior . MoreoveTrust appears between two parties who act consciously in altruism . In a spPerceived risk is an uncertain subjective psychological evaluation produced by customers in the purchase decision process . This unAlthough many studies have explored the role of customer trust and perceived risk in the field of e-commerce and e-service , most ofCustomer engagement behavior is a critical factor for e-commerce platform to realize value co-creation . CustomeCustomer engagement behavior is usually expressed as the spontaneous behavior of customers, and it is the behavioral manifestation of customers participating in the process of value co-creation . In the Considering that customer engagement behavior in community e-commerce relies on e-services to participate in the interaction process, not just customer perception. Therefore, our study combines a stimulus-organism-response model to test critical antecedents that impact customer engagement behavior on community e-commerce platform. Specifically, the e-service quality  of community e-commerce platform acts as stimulus to influence customer trust and perceived risk (O), which subsequently affects customer engagement behavior (R). Additionally, since trust affects customers’ attitudes toward community e-commerce platform, we believe that customers’ trust in platforms affects customers’ perceived risk. The effect of the e-service quality of e-commerce platform on customer trust can be explained by the information system model. Applied in the e-commerce context, the information system success model shows that the system quality, information quality, and service quality have an impact on customers’ experience perception . In partE-service features of different dimensions have a cumulative effect on customer trust . For insH1a: System design positively influences customer trust in the platform.H1b: Intelligent fulfillment positively influences customer trust in the platform.H1c: Security assurance positively influences customer trust in the platform.H1d: Interactive service positively influences customer trust in the platform.In the e-commerce context, E-commerce platform reduces perceived risk through various service modes . For insH2a: System design negatively influences customer perceived risk.H2b: Intelligent fulfillment negatively influences customer perceived risk.H2c: Security assurance negatively influences customer perceived risk.H2d: Interactive service negatively influences customer perceived risk.While the connection between perceived usefulness and trust has widely been investigated in the e-commerce literature, different opinions exist on whether customer trust influences perceived risk or perceived risk influences customer trust. In this context, studies focusing on initial online trust argue that when customers may already believe in a shopping platform, customers trust the platform to reduce the risk of technology through security protocols/functions, thereby reducing customer perceived risk . TherefoThe interrelationship between trust and perceived risk exists throughout the customer’s purchase and consumption process . At the H3: Customer trust negatively influences customer perceived risk.Initial evidence has also been reported that customer trust in the platform can facilitate the formation of customer engagement. In the e-commerce context, only when customers have enough trust in the e-commerce platform can they engage in social interaction and purchase on the platform for a long time . The truH4: Customer trust positively influences customer engagement behavior.With respect to the effect of perceived risk on customer engagement behavior, H5: Customer perceived risk negatively influences customer engagement behavior.Community e-commerce divides customers in the form of virtual communities, usually adding personalized interest circles, group buying and other service navigation functions. At the same time, the interaction between customers and members of their community also greatly improves the customer’s perception of service quality . CustomeThe e-service quality of the community e-commerce platform stimulates customer engagement behavior by improving customer trust. High levels of system design, intelligent fulfillment, security assurance, and interactive service can bring a more convenient and comfortable shopping environment to customers . This efThe customer’s perceived risk may affect the customer’s expectation of using the community e-commerce platform. By improving the e-service quality of the community e-commerce platform, customers can reduce the perceived risk of the platform and improve the customer perceived value and subsequent willingness to use it . The sysH6: Customer trust mediates the effects of system design (H6a), intelligent fulfillment (H6b), security assurance (H6c), and interactive service (H6d) on customer engagement behavior.H7: Customer perceived risk mediates the effects of system design (H7a), intelligent fulfillment (H7b), security assurance (H7c), and interactive service (H7d) on customer engagement behavior.In conclusion, considering the relationship between e-service quality, customer perception, and customer engagement behavior of community e-commerce platform, based on the above theoretical background and SOR paradigm, this study proposed a research model to investigate how the e-service quality influences customer engagement behavior through customer trust and perceived risk, as shown in This study adopts the survey method to collect data for empirical tests. This questionnaire includes eight variables, the measurements of which are derived from previous studies. Combining the development characteristics of the community e-commerce platform and the consumer’s consumption experience habits, some items have been fine-tuned to adapt to the context of this study. Since all items were originally developed in English, the forward-backward translation procedure was used to ensure translation accuracy. All the items are translated into Chinese and then back-translated into English. The consistency of the two versions is checked to guarantee that Chinese scales can effectively convey the expected meanings of all the items. In addition, this study made reasonable modifications to the questionnaire through group interviews and guidance from relevant experts to improve the comprehensibility of the questionnaire.1, which is among the largest professional research data collection service platform in China. This survey is aimed at customers of community e-commerce platforms, and randomly invited people who have recent online shopping experiences on community e-commerce platforms to distribute questionnaires for the survey. To ensure the quality of the survey sample data, a paid bonus was set up to encourage respondents to fill in the questionnaire carefully. Meanwhile, during the questionnaire collection, the questionnaire whose filling time is less than 90 s is deleted to improve the validity of the survey data. In total, 326 valid questionnaires were received from March to April 2022.Considering that community e-commerce platforms mainly carry out e-commerce transactions based on virtual communities, this study adopts the form of an online survey. The distribution and collection of questionnaires mainly rely on Wenjuanxing platformstrongly disagree, 5 = strongly agree), and the respondents are required to choose according to their actual situation. The items of system design, intelligent fulfillment, security assurance, and interactive service are adapted from The relevant variables in this study adopt a 5-point Likert scale to measure each item  and 37.4% were male (n = 122). Most of the respondents were ages between 18 and 24 years , and most have a bachelor’s degree . The majority of the respondents were enterprise staff , followed by students . In terms of customer experience, 53.1% of the respondents have 1–3 years of experience using community e-commerce platforms .The demographic statistics of the study’s respondents are presented in This research uses Cronbach’s alpha and Composite Reliability (CR) to analyze the reliability of the model. Furthermore, this research tested the discrimination validity. As shown in 2/df = 2.503 > 3, RMSEA = 0.061 < 0.100, CFI = 0.953, NNFI = 0.924, IFI = 0.934, which are all higher than the minimum fitting standard value of 0.9. This further indicated that there was no common method bias in this study.Because this study collected data by questionnaire, the validity of the survey data may be affected by common method bias. Therefore, this study collected questionnaires anonymously to ensure the rigor of the research process. In addition, this study also conducted Harman’s single factor test to check for possible method bias. According to the test results, all the extracted factors explained less than 50% of the total variance, and the first variance explained by one factor was 37.751%, indicating that the common method bias of the sample data was not a major concern in this study. At the same time, according to the results of the fit of the one-factor model, χP < 0.001), intelligent fulfillment , security assurance , and interactive service  is positively associated with customer trust. These results show that H1a–H1d are all supported. This is in line with similar studies (P < 0.001), intelligent fulfillment , security assurance , and interactive service  is negatively associated with customer perceived risk. These results indicate that H2a–H2d are also supported. Customers are prone to perceived risks due to low e-service quality, in line with similar studies ( studies . Consist studies . TherefoP < 0.001), thus supporting H3. There is a negative relationship between customer trust and uncertainty perception, which is in line with with previous studies (P < 0.001), and perceived risk is negatively correlated with customer engagement behavior . These findings, respectively, support H4 and H5. Therefore, the results show that customer trust has a positive impact on customer engagement behavior, while perceived risk has a negative impact on customer engagement behavior, in line with similar studies  of community e-commerce platform has a significant impact on customer cognition (including customer trust and perceived risk), which is positively associated with customer engagement behavior. Additionally, the empirical results indicate that customer trust and perceived risk have significant positive impacts on customer engagement behavior, and play a mediating role between e-service quality and customer engagement behavior. More specifically, the e-service quality of community e-commerce platform influences the customer engagement behavior through the partial effect of customer trust and perceived risk.The results of this research make important contributions to the literature. First, this research employed the SOR model to investigate how e-service quality impacts customer engagement behavior by the mediation effect of customer trust and perceived risk. The present study primarily focuses on the environmental characteristics and individual drivers that stimulate customer engagement behavior in community e-commerce platforms. Previous e-commerce studies have separately examined the important roles of e-service quality and customer perception in shaping the customer decision-making process . HoweverSecond, this research explored the relationship between community e-commerce and e-service quality. With the promotion of precision marketing on the Internet, personalization and communization have changed the way many people live online. Community e-commerce has changed many aspects of traditional e-commerce, but previous studies have not investigated the impacts of these changes . TherefoFinally, this study recognizes the crucial role of customer trust and perceived risk in influencing the e-service quality of community e-commerce and customer engagement behavior. Because community e-commerce is a form of social commerce with high participation, customer trust and low-risk perceptions are important foundations for customers to participate in community activities and experience consumption. Although some studies have shown that e-commerce platform can build customer trust in social interactions , it is sThe current research presents several practical implications for the management of community e-commerce platforms. First, community e-commerce managers should improve the e-service quality of community e-commerce platform, including system design, intelligent fulfillment, security assurance, and interactive service. For example, they could optimize the system design of community e-commerce platform, and reasonably handle shopping and social functions. Community e-commerce platform companies can make full use of new media such as graphics and text, video, and live broadcasts to enhance customers’ interest, and improve the shopping and social interaction functions such as websites, mobile apps, mini-programs, and video numbers. In addition, they could use high-tech such as artificial intelligence and block chain to strengthen the security and reliability of community e-commerce platform, and they can also subdivide different communities and customers in the community e-commerce platform to improve the response service.Second, the results of this study show that the e-service quality of community e-commerce platform can positively influence customer engagement behavior through customer trust and perceived risk. Therefore, community e-commerce operators should consider doing so to strengthen customer community belonging. For example, they can regularly investigate experience evaluation through big data analysis and random questionnaires, and timely adjust their marketing strategies. In addition, managers can carry out personalized marketing activities through virtual communities to attract more customers to participate in community interactions. When customers actively participate in social interactions, customers’ trust in the platform can be enhanced, and it is more likely to stimulate customer engagement behavior.This study has several limitations. First, customer engagement behavior is a dynamic behavior and may evolve over time, as may customer perception and the development of e-service. Thus, future research can consider the longitudinal exploration of customer engagement behavior. Second, this study focuses on the mediating effects of customer trust and perceived risk, and does not further analyze whether this effect is affected by other boundaries, such as corporate social responsibility, corporate reputation and big data management, under the background of digital transformation . RegardiWith the rapid development of community e-commerce, it has become more and more important to stimulate customer engagement behavior in virtual communities. This research focuses on e-service quality and other factors that promote customer engagement behaviors on community e-commerce platform. Findings indicate that improving the e-service quality  has a strong positive effect on stimulating customer engagement behavior. Furthermore, this study found that customer trust and perceived risk significantly contribute to improvements in customer engagement behavior. The present study advances the current understanding of customers’ activities on community e-commerce platform by empirically showing that e-service quality of community e-commerce platform increases customers’ trust in the platform, and reduces customers’ perceived risk, thereby representing an effective strategy for increasing customer engagement behavior. This study suggests that community e-commerce should improve the e-service quality in system design, intelligent fulfillment, security assurance, and interactive service, cultivate customers’ trust in the platform, and reduce customers’ risk perception of the platform, because these perceptions significantly affect customer engagement behavior.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants or patients/participants legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.WF contributed to the conceptualization, methodology, statistical analysis, data curation, and writing. BS contributed to the revision, investigation, supervision, funding acquisition, and project administration. XD contributed to the revision. All authors contributed to the manuscript revision and read and approved the submitted version.


Attributional style (AS) indicates cognitive dispositions for explaining positive and negative events. People with pessimistic АS explain failure with stable and global causes. Previous studies and meta-analyses  showed that pessimistic AS for failures is a reliable predictor of depression and ill-being, but the possible mediators of such relations are understudied.Our main objective was to analyse relations of pessimistic AS for success and failure with mental health. We hypothesized that pessimistic AS would be a predictor of low mental health mediated by self-esteem, dispositional optimism, and gratitude.A cross-sectional study was conducted on a sample of 261 adults  using a 24-item attributional style questionnaire , mental well-being scale , self-esteem scale , gratitude questionnaire , and LOT .A path model of effects of pessimistic AS in positive and negative situations on mental ill-being was developed. The model with three mediators fits the data very well: CFI=0.990; RMSEA=0.048. The pessimistic attributional style for positive events was a significant predictor of mental ill-being mediated by self-esteem, dispositional optimism, and gratitude while the indirect effect of pessimistic AS for failures on mental ill-being (controlling for age) was not significant.Only the pessimistic AS for successes but not for failures was a significant predictor of mental ill-being which underline the importance of stable and global attributions of positive life events for mental health.


Thyroid cancer is the most prevalent endocrine malignancy and the reported incidence of thyroid cancer has continued to increase in recent years. Since 2019, coronavirus disease 2019 (COVID-19) has been spreading worldwide in a global pandemic. COVID-19 aggravates primary illnesses and affects disease management; relevant changes include delayed diagnosis and treatment. The thyroid is an endocrine organ that is susceptible to autoimmune attack; thus, thyroid cancer after COVID-19 has gradually attracted attention. Whether COVID-19 affects the diagnosis and treatment of thyroid cancer has also attracted the attention of many researchers. This review examines the literature regarding the influence of COVID-19 on the pathogenesis, diagnosis, and treatment of thyroid cancer; it also focuses on drug therapies to promote research into strategies for improving therapy and management in thyroid cancer patients with COVID-19.  Thyroid cancer is the most prevalent endocrine malignancy worldwide . The repIn December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began to spread worldwide; it has caused the coronavirus disease 2019 (COVID-19) global pandemic . The mai.The pathogenesis of thyroid cancer includes gene mutation, rearrangement and fusion, abnormal gene expression, and signaling pathway abnormalities . Most MT. The first protein is the SARS-CoV-2 main protease, conserved among coronaviruses with no human homolog; it is mainly responsible for viral transcription and replication , and pharmacotherapy. Surgical resection is often the first-line treatment approach. Total thyroidectomy is recommended for most DTCs, MTCs, macroscopic metastatic invasive PTCs, and follicular thyroid carcinomas with vascular infiltration . Most paThe spread of COVID-19 has brought unprecedented challenges to the surgical resection treatment of thyroid cancer. Both diagnostic and therapeutic procedures expose patients to the risk of COVID-19 infection. Moreover, conventional follow-up visits have been postponed in relation to the threat of COVID-19 infection. Because of social distancing restrictions and operating room shortages, all procedures that may nebulize breathing and digest secretions  are restricted because they will increase the risk of infection . Thus, dMost DTCs and MTCs are slow-growing tumors; surgical treatment can be postponed or elective. There are no significant differences in tumor size and lymph node metastasis between patients with delayed treatment ≤180 days and those without delayed treatment . HoweverPreoperative considerations must be more comprehensive in a pandemic situation . Pulmona131I treatment is a vital tool for thyroid cancer treatment; it involves the irradiation of residual thyroid or unresectable/incompletely resected thyroid cancer , as well as frequent mutations in genes such as RET, BRAF, and RAS. The phosphoinositide 3-kinase/Akt/mTOR and mitogen-activated protein kinase signaling pathways have critical roles in thyroid cancer; several MKIs block tyrosine kinase receptors, thus preventing angiogenesis and tumor growth through these two pathways . MKIs acVandetanib is the first FDA-approved drug for the treatment of advanced MTC. Vandetanib selectively blocks epidermal growth factor receptor, VEGFR, and RET-tyrosine kinase . HereditCOVID-19 is often associated with a cytokine storm response involving inflammatory cytokines, which leads to multiple organ dysfunction. Importantly, MKIs have anti-inflammatory and cytokine inhibitory activities. They may be used for broader spectrum antiviral therapy and can reduce the possibility of life-threatening diseases caused by respiratory virus infection-related lung injury . MKIs maCabozantinib blocks VEGFR, c-MET, and RET; it is the second FDA-approved drug for the treatment of progressive and symptomatic MTC . CompareThe COVID-19 pandemic has required more careful selection of targeted drugs. Experts recommend continued use of cabozantinib in patients without obvious contraindications . Thus faSorafenib is approved for the treatment of RAI-refractory DTC. It blocks VEGFR, platelet-derived growth factor, fibroblast growth factor, and RET receptors . Three pSorafenib has been reported to exhibit antiviral effects. It prevents viral egress by Rift Valley fever virus through the inhibition of valosin-containing protein function . A new cSimilarly, lopinavir/ritonavir should be used with caution in patients receiving sorafenib. Patients with thyroid cancer who received MKIs reportedly experienced more COVID-19 virus infections, compared to patients who did not receive MKIs . Among pSimilar to other MKIs, lenvatinib exerts its actions by targeting tumor angiogenesis . It is mvia high-throughput docking. They found that lenvatinib and remdesivir have obvious synergistic effects, which can inhibit SARS-CoV-2 replication. They validated this finding with cellular experiments; importantly, this synergistic inhibition was not caused by blocking interactions with VEGFR or platelet-derived growth factor receptor. The synergistic effect may be related to more efficient inhibition of viral transcription and replication processes, rather than any effect on early stages of the viral replication cycle. Locantore et al. reported the first case of a lenvatinib-treated thyroid cancer patient who developed COVID-19. The patient was diagnosed with DTC and had bilateral lung metastases; the patient was administered lenvatinib and exhibited partial response to treatment, along with reduction of lung metastases. Subsequently, the patient had a positive SARS-CoV-2 test result during treatment; the disease was initially asymptomatic, then progressed to cough and diarrhea after a few days. However, it did not progress to anosmia or fever; the patient continued lenvatinib and underwent daily monitoring of vital signs. Twenty-one days later, SARS-CoV-2 test results were negative, and no additional adverse events occurred , and important NTRK that treats tumors harboring oncogenic forms of these proteins  are effective for the treatment of thyroid cancer, mainly through the inhibition of VEGFR, fibroblast growth factor 1/2, platelet-derived growth factor receptor, and RET receptors . In a phDuring the COVID-19 pandemic, there have been attempts to identify the potential effects of these drugs on patients with COVID-19. Kinase inhibitors have clear roles in reducing the infectivities of viruses such as Ebola and hepatitis C, suggesting that drugs such as sunitinib may be effective against SARS-CoV-2 . Girgis Pralsetinib is a selective RET receptor inhibitor approved by the FDA for the treatment of RET fusion-positive non-small cell lung cancer . SubbiahEverolimus is an inhibitor of the mTOR serine/threonine kinase signal transduction pathway . The FDAEverolimus-mediated mTOR inhibition may help to manage COVID-19 by reducing conventional T lymphocyte proliferation, attenuating the cytokine storm phenomenon, and maintaining regulatory T cell growth and activity . HoweverThe development and approval of cancer-specific immunotherapy has led to new avenues and methods for the treatment of malignant tumors . Thus faThe impact of COVID-19 on thyroid cancer is unprecedented. It affects the diagnosis, treatment, and management of thyroid cancer. Diagnosis is delayed and treatment requires more careful choices. However, in the case of the gradual normalization of the epidemic situation, the treatment of thyroid cancer should continue. Compared to surgery and RAI treatment, drug therapy appears to be a safer option. Some targeted therapies  have demonstrated robust effects on thyroid cancer, and some drugs are also effective in treating COVID-19. If appropriate drugs and safe doses can be selected, it will be better for patients with thyroid cancer combined with COVID-19. However, the drug dosage and safety must be validated in future studies.FH and XS: Conceptualization, Writing - Review and Editing. NQ, ZH, and ZS: Methodology, Software, Visualization, Writing - Original Draft. CK and NH: Visualization, Writing- Review. All authors contributed to the article and approved the submitted version.This study was supported by grants from National Natural Science Foundation of China , Natural Science Foundation of Shandong Province (ZR2020MH106), Shandong Province Higher Educational Science and Technology Program for Youth Innovation (2020KJL004), and Doctor Startup Fund of Affiliated Hospital of Weifang Medical University (2020BSQD01).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In addition, we found a large proportion of plasma cells and macrophages in TCGA-COADREAD. Finally, a prognostic nomogram of ferroptosis-related genes was established, including age, sex, grade and other predicted values. To summary, we established a prognostic model of colorectal cancer (CRC) based on ferroptosis-related genes and further explored the relationship between these genes with immune microenvironment.Colorectal cancer (CRC) remains a common malignant tumor of digestive tract with high incidence rate and high mortality in the worldwide. The current clinical treatments of CRC often fail to achieve satisfactory results. Searching for more effective prediction or prognosis biomarkers, or developing more targeted therapeutic schedule may help to improve the outcomes of CRC patients. Here, we tried to study the effect of ferroptosis-related genes on CRC prognosis and make it clearer that ferroptosis has connection with immune environment. First, we obtained gene expression data of CRC and normal tissues, as well as corresponding clinical data from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were intersected with ferroptosis-related gene set downloaded from FerrDb database, and 93 abnormally expressed ferroptosis-related genes were obtained. Then, these genes were analyzed for functional enrichment. Univariate Cox regression and multivariate Cox regression analyses were performed to establish prognostic model based on ferroptosis-related genes. In the process of exploring the correlation between prognostic genes and immune infiltration, we found that these genes were closely related to B cells, CD8 According to statistics in 2021, colorectal cancer (CRC) ranks third in morbidity and second in mortality worldwide, seriously affects human health and brings heavy economic burden . EspeciaFerroptosis, which was first proposed in 2012, is a non-apoptotic and iron-dependent form of cell death characterized by the accumulation of reactive oxygen species (ROS) . It is sPrevious studies on ferroptosis in tumors mainly focused on the abnormally expressed ferroptosis-related genes, which have close connections with tumors, by screening the relative database through bioinformatic analysis. Here, we want to further analyse ferroptosis-related factors that have connections with immune microenvironment. In our study, CRC expression data together with corresponding patients’ information from TCGA and GEO databases were screened and cross-referenced with FerrDB database to identify differentially expressed genes (DEGs) associated with ferroptosis. The prognostic genes were further screened and prognostic model was established to predict the prognosis of CRC patients. Meanwhile, we analyzed the association between ferroptosis-related genes and tumor microenvironment in CRC, enhancing our understanding of the relationship between ferroptosis and immune cell abundance. In a word, our results provide a novel ferroptosis-related model for prognosis analysis of CRC patients and further verified the relationship between ferroptosis and immune microenvironment, which may contribute to the immunotherapy in the future.https://www.ncbi.nlm.nih.gov/geo), we downloaded RNA expression data including normal and tumor tissues from GEO: GSE21510, GSE44861, GSE62321 and GSE79793, and obtained RNA expression data as well as clinical information of patients from GEO: GSE41258. All the above data are normalized by log2-scale transformation to ensure standardization. The gene symbols with multiple probes were calculated using mean expression levels. We also obtained the level three HTSEQ-FPKM format RNA sequencing data in CRC project from TCGA database (https://www.cancer.gov/tcga/), named TCGA-COADREAD. A total of 644 matched patients’ clinical information and sample information were obtained. In addition, a total of 388 ferroptosis-related genes  were obtained from FerrDb database (http://www.zhounan.org/ferrdb/legacy/index.html) as candidate genes. Detailed information about these genes are shown in From the GEO database . The cutoff of the p-value was 0.01. Enriched terms were selected to construct the network, and similar terms were connected with edges. The cutoff value of similarity is 0.3. STRING (http://string.embl.de/) was used to predict PPI information. Then, we established PPI networks using Cytoscape. And the MCODE algorithm was performed to identify the key modules. The cutoff of the p-value was 0.05.The GO and Kyoto Encyclopedia of Genes (KEGG) analysis were performed using a gene annotation and analysis resource Metascape  and GEO: GSE41258 datasets  to establish prognostic markers of ferroptosis-related genes. Univariate Cox analysis of OS was conducted to identify ferroptosis-related genes with significant prognostic value, and http://timer.cistrome.org/) to analyze the relationship between prognostic genes and tumor immune infiltrating cells. Then, the R package “estimate” was used to calculate the immune score of TCGA-COADREAD to obtain the stromal score, immune score, and ESTIMATE score of prognostic genes. And a Kaplan-Meier survival curve was plotted to evaluate the relationship between immune score and patient survival time. CIBERSORTx (https://cibersortx.stanford.edu/) was used to evaluate the proportion of immune cell infiltration in tissues from TCGA-COADREAD and GEO: GSE41258 datasets to clarify the relationship between prognostic genes and immune cell infiltration. In addition, we also used ssGSEA algorithm to calculate the distribution of various immune cells and draw violin plots.To determining the immune correlation of prognostic genes, we used TIMER2.0 database  was used to visualize the observed rates against nomogram-predicted probabilities.2FC > 1, p-value < 0.05) and 471 down-regulated genes  were obtained from GEO: GSE21510. A total of 141 genes showed upregulation and 261 genes showed downregulation were obtained from GEO: GSE44861. In addition, 254 genes with high expression and 715 genes with low expression were found in GEO: GSE62321, 46 genes with high expression and 241 genes with low expression were found in GEO: GSE79793. The heat maps of the four datasets are showed in Four GEO datasets were selected as data sources, and the information is listed in We performed functional analysis by Metascape to investigate the underlying mechanisms of abnormally expressed ferroptosis-related genes in CRC. The gene ontology (GO) analysis results revealed that the dysregulated ferroptosis-related genes were mainly enriched in response to stimulus, metabolic process and positive regulation of biological process . It is wp = 0.023). Similarly, the ROC curve indicated that the model had an ideal prediction effect  2.0 database, we found that these three prognostic genes were associated with B cells, CD8s in CRC . Next, ws in CRC . Further+ T cells, dendritic cells and macrophages were statistically significant  accounted for a large proportion of infiltrating immune cells in TCGA-COADREAD . We usednificant . In addinificant .Furthermore, we explored the expression of PD-1 and CTLA4 in the low-risk group and high-risk group. It was demonstrated that patients in the high-risk group had a higher expression level of PD-1 and a lower expression level of CTLA-4 in TCGA-COADREAD cohort . But we Finally, we used the results of the multivariate analysis to establish a predictive ferroptosis-related prognostic nomogram. We used nomogram to predict the 1-year, 2-years, and 3-years OS for identifying the predictive value of age, gender, pathologic stage, TNM stage, and risk score . This no+ T cells, which can in turn affect the efficacy of tumor immunotherapy. Therefore, further study of ferroptosis-related genes in CRC may help to determine the tumor prognosis. Moreover, it is meaningful, to some degree, to make it clearer about the relationship between ferroptosis and tumor immune microenvironment, which can guide for the immunotherapy of CRC.At the moment, surgical resection, chemotherapy, targeted therapy and immunotherapy are the main clinical treatments for CRC . The optIn our study, we focused on ferroptosis-related genes and their effect on prognosis and sought to explore the relationship between these genes and tumor immune microenvironment. First, we analyzed the DEGs in GEO: GSE21510, GSE44861, GSE62321 and GSE79793 datasets, and intersected them with ferroptosis gene set in FerrDb database. We identified 93 ferroptosis-related genes in CRC this time. Functional analysis of these genes revealed that they were involved in immune system processes and may play roles in the immune microenvironment. Univariate Cox and multivariate Cox regression analysis were used to identify the most significant prognostic genes, which were ATG7, MAPK9 and MMD. Then, the risk score was calculated and the prognostic model was established, which was verified in GEO: GSE41258. Next, we found that these three ferroptosis-related prognostic genes were closely related to immune cells by using the TIMER 2.0 database. CIBERSORT algorithm was performed to evaluate the immune cell infiltration of the tumor immune microenvironment.+ T cells were significantly different in the two groups. They though it could be a biomarker for immune checkpoint therapy in CRC Patients (In recent years, there have been several bioinformatic studies about tumor associated ferroptosis-related genes in CRC. Moreover, some of them also explored the relationship between ferroptosis-related genes and immune microenvironment. Pan et al. reported a ferroptosis-related prognostic model based on eight genes, AKR1C1, ALOX12, ATP5MC3, CARS1, HMGCR, CRYAB, FDFT1, and PHKG2. They divided the patients in two groups according to the expression pattern of these genes and CD8Patients . Zheng ePatients . BesidesPatients . Immune Patients . AccordiATG7, an important member in the autophagy process, participates in autophagosome formation and maturation . It alsoIn conclusion, our study established a prognostic model of CRC based on ferroptosis-related genes ATG7, MAPK9, and MMD and further verified its good predictive effect. The establishment of this model and related immune analysis confirmed the influence of immune microenvironment on the prognosis of CRC, which may benefit for clinical diagnosis and outcome judgment of CRC in the future.