To assess the prospective association of two diet quality scores based on the Nova food classification with BMI gain.2) increase of ≥5 % was coded as BMI gain.The NutriNet-Brasil cohort is an ongoing web-based prospective study with continuous recruitment of participants aged ≥ 18 years since January 2020. A short 24-h dietary recall screener including ‘yes/no’ questions about the consumption of whole plant foods (WPF) and ultra-processed foods (UPF) was completed by participants at baseline. The Nova-WPF and the Nova-UPF scores were computed by adding up positive responses regarding the consumption of thirty-three varieties of WPF and twenty-three varieties of UPF, respectively. Participants reported their height at baseline and their weight at both baseline and after approximately 15 months of follow-up. A 15-month BMI , whereas increasing quintiles of the Nova-WPF score were linearly associated with lower risk . We identified a moderate inverse correlation between the two scores (–0·33) and a partial mediating effect of the alternative score: 15 % for the total effect of the Nova-UPF score and 25 % for the total effect of the Nova-WPF score.The Nova-UPF and Nova-WPF scores are independently associated with mid-term BMI gain further justifying their use in diet quality monitoring systems. These are formulations of processed food substances  and cosmetic additives  created by the industry as profitable and attractive alternatives to unprocessed or minimally processed foods and their culinary preparations. Various UPF attributes of acting through known, plausible, or suggested physiologic and behavioural mechanisms relate them to several chronic diseases including the risk of overweight and obesity,4. Furthermore, a 4-week crossover randomised clinical trial, with twenty weight-stable adults, showed that, compared to a diet with no UPF, a diet with 83 % of energy from UPF caused a substantial increase in ad libitum calorie intake and consequent weight gain.The metric most frequently used in studies that have employed Nova to assess the quality of diets and their impact on health is the dietary share, in calories or grams, of UPF. One cohort study observed that the dietary contribution of Nova unprocessed/minimally processed foods was inversely associated with overweight risk. Furthermore, it is well established that a diet based on a variety of unprocessed or minimally processed foods, predominantly plants, has a protective effect on health including the prevention of overweight/obesity and other obesity-related diseases.Although less often, the dietary share of Nova unprocessed/minimally processed foods has also been used to assess the quality of diets and their impact on health. These foods include unprocessed plant- and animal-sourced foods and those that were submitted to removal of inedible or undesired parts, chilling, freezing, pasteurisation, fermentation, boiling, drying, grinding and other processes that do not add salt, sugar, fat, or any other food substance to the original foodsHowever, the estimation of the dietary contribution of Nova groups requires detailed knowledge of total food intake which demands complex, high-cost and time-consuming data collection instruments such as 24-h dietary recalls. Aiming for simpler metrics that could be used in surveillance systems, authors of the Nova classification designed a short 24-h dietary recall screener that enables the calculation of two scores to capture the consumption of unprocessed or minimally processed whole plant foods (WPF) and UPF. The current study aims to assess the association of these two Nova diet quality scores with weight gain in the NutriNet-Brasil cohort study.. The study, approved by the ethics committee of the School of Public Health from São Paulo University (process No. 88455417.8.0000.5421), recruits volunteers mainly through campaigns using traditional media , as well as social medias of digital influencers and the ones created for the study. More than 100 000 volunteers have already registered at the study digital platform (https://nutrinetbrasil.fsp.usp.br/). In a web interface, volunteers answer baseline and follow-up questionnaires. These include web-based 24-h dietary recalls, alternating the short screener and the complete recall, as well as questionnaires about health status (including weight and height) and aspects potentially associated with diet and health, such as sociodemographic characteristics, physical activity, smoking, and other health-related behaviours.Participants are enrolled at NutriNet-Brasil, an ongoing web-based cohort study with continuous recruitment of residents aged ≥18 years from all Brazilian regions since 26 January 2020. The NutriNet-Brasil primary aim is to investigate the prospective association between characteristics of the diet and health outcomes related to chronic non-communicable diseases in Brazil. These food items include thirty-three varieties of unprocessed or minimally processed WPF  and twenty-three varieties of UPF   used in the current study is a low-burden survey questionnaire including checkbox format questions about the consumption of selected food items on the previous days) Table . VarietiThe current study used the Nova 24-h screener completed by participants at baseline, on three non-consecutive days over the period of 2 weeks (2 weekdays and 1 weekend day), starting on the same day they register at the study platform. Based on the responses to each screener, two diet quality scores were calculated: the Nova score of WPF (Nova-WPF score) and the Nova score of UPF (Nova-UPF score).The Nova-WPF score was computed by adding up positive responses regarding the day before consumption of each of the thirty-three varieties of unprocessed or minimally processed WPF (therefore ranging from zero to thirty-three), whereas the Nova-UPF score was computed by adding up positive responses regarding the day before consumption of the twenty-three varieties of UPF (therefore ranging from zero to twenty-three). The complete list of the food items included in each score is described in Table . A validation study of both scores was conducted in a random sample of 812 NutriNet-Brasil cohort participants using a full 24-h recall as the reference dietary intake method. The prevalence-adjusted and bias-adjusted kappa (Pabak) index was used to assess the degree of agreement in the classification of participants according to the quintiles of the dietary energy share of WPF and UPF in the diet  and quintiles of the Nova diet quality scores. The Pakab index with values greater than 0·80 indicates an almost perfect agreement: 0·61 to 0·80, a substantial agreement; 0·41 to 0·60, moderate; 0·21 to 0·40, fair; and equal to or less than 0·20, slight agreement. The validation study available in preprint version showed substantial agreement between participants classified, alternatively, across quintiles of the Nova-WPF scores and quintiles of the dietary energy share of all WPF  as well as between participants classified across quintiles of the Nova-UPF score and quintiles of the energy share of all UPF .The Nova-UPF score had been previously validated in a clientele of primary health services from the city of São Paulo, with a similar agreement. The relative BMI change in the period between the two dates, expressed as a percentage of the initial BMI, was then standardised for the exact period of 15 months.Participants self-reported their height in metres with two decimal points at baseline. At both the baseline and approximately 15 months after baseline (mean 14·9 (±1·2) months; min. 11·0 to max. 18·0 months), participants also self-reported the date they measured their weight for the last time and their weight measured in kg. The BMI in each date was calculated as the weight in kilograms divided by the height in squared metres (kg/m²).Data on demographics, socio-economic characteristics and health behaviours were self-reported by the participants at the baseline. The baseline covariates included sex , age , schooling level (0–11/≥ 12 years of schooling), region of residence in Brazil (North/Northeast/Midwest/Southeast/South), smoking status (never/former/current), diet for weight loss (no/yes) and physical activity (insufficiently active/active). Physical activity was assessed with the Global Physical Activity Questionnaire (GPAQ). According to GPAQ’s data processing guidelines, we summed the time spent on work, transport, and leisure-time physical activity and classified using the cut-off points of 150 min of moderate-intensity physical activity, 75 min of vigorous-intensity physical activity, or combination of moderate- and vigorous-intensity physical activity achieving at least 600 MET-minutes/week. We consider insufficiently active participants below these cut-off points and active those with physical activity values equal to or greater than those of the cut-off pointsn 1690), women who were pregnant at baseline or became pregnant during the follow-up period (n 355), participants with implausible initial or 15-month BMI values (<15 or ≥60 kg/m²) (n 20), outliers for 15-month BMI change (< 0·1 centile (–10·19 kg) or > 99·9 centile (+7·63 kg), (n 15)) and participants with incomplete data for covariates (n 443).Data were extracted for analysis on January 2022 and included 12 074 participants who had completed the Nova 24-h screener at baseline in three non-consecutive days and had self-reported their height at baseline and their weight and date they measured their weight for the last time both at baseline and at the 15th month of follow-up. We excluded participants who reported weight measured more than 2 months before baseline or more than 6 months before the 15-month follow-up questionnaire  was first assessed using restricted cubic spline linear regression with knots at the 10th, 50th and 90th centiles of the Nova score distribution with adjustment for all the previously mentioned study covariates. The statistical significance of linear and non-linear terms was evaluated using Wald tests.The association between each Nova dietary quality score and the 15-month change in BMI  version 14.0; a n 9551), overall and according to quintiles of the Nova dietary quality scores. Higher Nova-WPF scores were significantly associated with older age, higher education (≥12 years of schooling), not currently smoking, not being on weight loss diet, physically active status and having lower BMI at the baseline. Higher Nova-UPF scores were significantly associated with being male and younger, having lower education (<12 years of schooling), being insufficiently active, having higher BMI at the baseline, and living in the more economically developed South and Southeast Brazilian regions. An inverse correlation was observed between the Nova-WPF score and the Nova-UPF score at the baseline  (data not shown).Table 2) (with slight departure from linearity) and a direct dose–response association in the case of the Nova-UPF score (with no departure from linearity) . Table In this large prospective study with participants from all Brazilian regions, we have shown that quintiles of new diet quality scores based on the day before intake of unprocessed or minimally processed WPF and UPF, as defined by Nova food classification system, were associated, respectively, with lower and higher risk of 15-month BMI gain of ≥ 5 %. We also identified a moderate inverse correlation between the two scores (–0·33) and the partial mediating effect of the alternative score: 25 % of the protective effect of Nova-WPF score on BMI gain could be explained by its inverse correlation with the Nova-UPF score, while 15 % of the risk effect of the Nova-UPF score could be explained by its inverse correlation with the Nova-WPF score.. Some of these studies also have shown that these risks remained largely unchanged after adjusting for the dietary contribution of unprocessed/minimally processed fruit and vegetables,20,21. Likewise, an inverse association between the dietary contribution of Nova unprocessed/ minimally processed foods and risk of overweight has been previously described.Direct comparisons of these findings with other studies are not possible because this is the first study that employed the two new Nova scores to study their association with health outcomes. However, in consistency with our results, previous studies have observed a direct association between the overall dietary contribution of UPF with both short- and long-term risk for weight gain and the risk of overweight/obesity and the more recently demonstrated negative effects of UPF on energy density, sugar, saturated fat, Na, fibre, and protein contents,23, non-nutrient bioactive compound intakes and total water intake. Lower or greater exposure to a modified food matrix, cosmetic food additives, trans fatty acids, plastic packaging contaminants, or neo-formed processing contaminants, and a disturbed gut microbiota profile and integrity may be additional pathways explaining the opposite associations of BMI gain with the Nova-WPF and the Nova-UPF scores.Several pathways may explain the independent and opposite association between each of the two Nova diet quality scores and the risk of BMI gain. One possible route is the well-known positive effects of WPF on dietary parameters critical to weight gainThe persistent effect of each score on the risk of BMI gain after adjusting for the alternative score indicates that strategies to prevent weight gain should promote diets that are simultaneously rich in whole plant foods and reduced in UPF. These results highlight the importance of including both scores in surveillance systems that monitor population diet quality.The strengths of this study relate to its prospective design and large sample size, as well as the baseline assessment in three non-consecutive days of the intake of WPF and UPF using a data collection tool specifically developed to capture the consumption of these foods in Brazil.,33. This lower contrast would tend to reduce the magnitude of the association of each score with BMI gain.There are also some limitations that should be considered in the interpretation of our findings. This study was undertaken on volunteer participants of a cohort study on diet and health that may have a more health-conscious behaviour than the general population including more homogenous and heathier diets. This could have determined the lower contrast between extreme quintiles of each score observed in this study as compared with the overall Brazilian population. Among the Brazilian population aged 18 years or older, self-reported measurements of weight and height were shown to be a valid method to estimate anthropometric data.The self-reporting of anthropometric data may have introduced classification bias regarding BMI gain. However, a previous similar study with French participants observed a high concordance between web-based self-reported and objectively measured weight and heightFurthermore, non-differential social desirability bias may increase the chances of overestimating Nova-WPF or underestimating Nova-UPF scores, as well as underestimating the self-reported weight gain, biasing the studied associations towards the null.Finally, given the observational design of the study, residual confounding arising from unadjusted factors or imprecise measurement of self-reported covariates cannot be ruled out, limiting our capacity to make causal inferences.The current study shows that Nova-UPF and Nova-WPF scores are independently associated with mid-term BMI gain further justifying the use of both scores in diet quality monitoring systems.


Disulfidptosis is a newly discovered form of cell death. Not yet clearly classified as programmed cell death or accidental cell death. This study aimed to create a novel disulfidptosis-related lncRNA index (DLI) that can be used to predict survival and chemotherapy drugs sensitivity in patients with cervical cancer. First of all, we found lncRNAs associated with disulfidptosis between cervical cancer tissues and normal tissues. By LASSO-Cox analysis, overlapping lncRNAs were then used to construct lncRNA index associated with disulfidptosis, which can be served to predict the prognosis of patients with CC, especially the chemotherapy drugs sensitivity. ROC curves and PCA based on DLI and clinical signatures were developed and demonstrated to have good predictive potential. In addition, differences in immune cell subset infiltration and differences in immune checkpoint expression between high-DLI and low-DLI groups were analyzed, and we investigated the relationship between the DLI and tumor mutation burden (TMB). In summary, we constructed a lncRNA prediction index associated with disulfidptosis. This has important clinical implications, including improving the predictive value of cervical cancer patients and providing a biomarker for cervical cancer guiding individualized treatment. The global age-standardized incidence of CC varies substantially among countries, with reported rates ranging from fewer than 13 cases to 1 case per 70,000 women. Noteworthy, CC is the chief cause of cancer-related deaths among women in low- and middle-income countries3. It is widely known that high-risk HPV strains are associated with CC. C While HPV is necessary for the transformation of cervical epithelial cells, other co-factors and molecular procedures also the occurrence of CC5. Therefore, the exploration of novel potential biomarkers and underlying mechanisms is important for predicting the prognosis and improving the treatment of CC.In recent years, a remarkable surge in global cancer incidence and associated mortality rates has been reported. Cervical cancer (CC) ranks fourth in terms of the highest mortality and incidence rates among women globally6. It plays an essential role in the development of an organism, acts as a host defense mechanism against pathogens and maintains homeostasis. However, excessive activation of the PCD pathway exerts detrimental effects and may lead to disease development7. At least 12 types of PCD that are implicated in the development of malignant tumors. In glucose-deficient SLC7A11−high cancer cells, the excessive accumulation of disulfide molecules causes abnormal disulfide bonding between actin cytoskeletal proteins, thus disrupting their organization and eventually leading to the collapse of the actin network and cell death. This effect, known as disulfidptosis, effectively inhibits the growth of malignant tumors with any apparent toxicity to normal tissues9. This process of disulfidptosis involves glycogen accumulation, energy metabolism, mitochondrial respiration and disulfide regulation. The genes responsible for regulating these processes have been identified from published literature. For instance, GYS1 induces glycogen accumulation10; LRPPRC affects mitochondrial autophagy by regulating energy metabolism11; NDUFA11 and NDUFS1 maintain the mitochondrial structure and function12; NUBPL is involved in the mitochondrial respiratory chain13; OXSM is involved in glycogen regulation14; NCKAP1, RPN1, SLC3A2, and SLC7A11 are involved in the regulation of disulfidptosis9. Therefore, further investigations on disulfidptosis, the genes affecting glucose and lipid metabolism, and the underlying mechanism of disulfidptosis will aid in the identification of potential novel targets of this disease.Cell death is a crucial process for human health. In 2018, the Cell Death Nomenclature Committee classified this process into accidental cell death (ACD) and regulatory cell death (RCD). RCD, also known as programmed cell death (PCD), is a fully physiological form of cell death15. Among them, long ncRNAs (lncRNAs) are implicated in cancer development, indicated by their mutations and dysregulated expression. lncRNAs can promote tumorigenesis and metastasis, while also possessing tumor-suppressive and pro-cancer functions16. As such, lncRNAs hold immense promise as novel biomarkers and therapeutic targets for cancer17. For instance, the lncRNA SNHG1 is involved in the migration and invasion of CC18. Considerably linked with tumor size, FIGO stage, and lymph node metastasis, The lncRNA FALEC has shown substantially elevated levels in the plasma of CC patients. Additionally, overexpression of lncRNA FALEC promotes HeLa cell invasion and proliferation19. However, to date, the specific disease targets and underlying mechanisms through which lncRNA regulate disulfidptosis-related genes and affect the prognosis of CC by means of disulfidptosis remain unexplored. We extracted RNA sequencing data of patients with CC from publicly accessed databases and used bioinformatics methods to screen for lncRNAs associated with disulfidptosis related-genes (such as GYS1 etc.) that have predictive prognostic significance. This study intended to identify ncRNA-based biological targets for predicting CC prognosis, discover potential chemotherapeutic drugs targeting ncRNAs, and unravel the mechanisms underlying disulfidptosis in CC.Non-coding RNAs (ncRNAs) represent a novel class of transcripts. That, although mostly not translated into proteins, play crucial roles in various cellular and physiological functionshttps://www.cancer.gov/). The Perl programming language (version 5.32.1.1) was used to organize data for subsequent analysis. The CNV profile of disulfidptosis-associated genes in CC was assessed by constructing a lollipop plot, and the R package “RCircos” was utilized to map the variant loci on the chromosome. Additionally, waterfall plots were constructed to detect the mutations existing in disulfidptosis-associated genes in CC. Among 289 cervical cancer samples, we screened these ten genes for somatic mutations in 29 samples and counted the somatic mutation frequencies.Transcriptomic data, clinicopathological data, copy number variation (CNV) data, and single nucleotide variation (SNV) data of patients with CC  from The Cancer Genome Atlas (TCGA) database . The best prediction model was determined using the penalty parameter calculated through 1000-fold cross-validation with a p-value of 0.05.Details of ten disulfidptosis-related genes were manually compiled from the literature. Pearson correlation analysis was performed to evaluate the relationship between disulfidptosis-related genes and lncRNAs, which was visualized using Sankey diagrams. The criteria for deducing the association were |RlncRNA represents the link between a lncRNA and the survival of patients with CC. and explncRNA represents the expression level of that particular lncRNA.The final formula for establishing the disulfidptosis-associated lncRNA index (DLI) is as follows:In addition, we validated the expression differences of the lncRNAs screened using the Wilcox test to test whether there were expression differences between normal and tumor tissues in the TCGA dataset.To assess the predictive value of the DLI in CC, we conducted validation analyses in each of the three cohorts: TCGA cohort, training cohort, and testing cohort. In the TCGA cohort, patients with CC were categorized into low-risk (< median) or high-risk (≥ median) groups based on median scores of DLI (Risk). Kaplan–Meier curves depicting overall survival (OS) and progression-free survival (PFS) were generated using the R packages “survminer” and “survival,” and the differences between the risk groups were calculated. Scatter plots, risk curves, and heatmaps were constructed to confirm the distribution of risk values among patients in different risk groups and to deduce the risk of CC-associated death.Univariate and multivariate COX regression analyses were performed to evaluate the independence of DLI relative to other clinical characteristics. Receiver operating characteristic curves (ROC) were generated to assess the sensitivity and specificity of prognostic predictive value of the DLI when compared with other clinicopathological characteristics in patients with CC.Principal component analysis (PCA) analysis was employed to compare the risk definition and spatial distribution of patients based on various genetic classifications. This analysis facilitates the clinical utilization of the DLI and provides a comprehensive evaluation of patient prognosis. We integrated the prognostic characteristics  of patients with CC to calculate the predictive power on 1-, 3- and 5-years OS. Furthermore, multivariate Cox regression and stepwise regression analysis were performed to identify independent predictors Column plots were constructed, and nomoscore was calculated, which serves as a predictive tool for the outcomes of patients with CC. A nomogram was developed using the R package "regplot".We used gene ontology (GO) to analyze the differential genes between high- and low-DLI groups using the "clusterProfiler" R package. In addition. We used GSEA software (version 6.2) to perform a gene set enrichment analysis (GSEA) and identify the primary pathways of action in the high- and low-DLI groups. The statistical significance of the screen was set at P < 0.05 and the false discovery rate (FDR) q < 0.05.https://tcia.at/home).We evaluated immune cell infiltration in TCGA samples using seven methods. The “GSVA” and “GSEABase” R packages are used to calculate differences in immune function between different risk groups. A box plot was also used to show the differences in immune checkpoint and immune cell infiltration between high- and low-DLI groups. Immunophenoscore (IPS) obtained from The Cancer Immunome Atlas (TCIA) database  between high- and low-risk groups. The Wilcoxon test was used to analyse survival differences between high- and low-mutation groups, and for joint survival analysis with different DLI groups. KM curves were used to visualise survival analysis.20 for drug sensitivity prediction. The IC50 value represents the sensitivity of the chemotherapeutic drug in the cell lines of this cancer type. Higher IC50 values mean that the drug is less sensitive and a higher dose is required to achieve the same efficacy. It fits the gene expression profile of a tissue to the half-maximal inhibitory concentration (IC50) of a cancer cell line to the economics of Drug Sensitivity in Cancer (GDSC). Download details from GDSC on molecular indicators of drug sensitivity and response in cancer cells20 to generate models that can be applied to CC transcriptomics data. The data from our high- and low-DLI groups were correlated with the expression profile data from GDSC, and then unpaired t-tests were used to compare the differences in IC50 of chemotherapeutic agents between the high and low DLI groups. A sensitivity score was then performed to forecast the IC50 for each drug's half-maximal inhibitory concentration in CC patients.Drug sensitivity was calculated using the "oncopredict" software package. This package was developed by Maeser et al.Software used in this study included R language and PERL, GSEA software (version). p < 0.05 (marked with *) was considered statistically significant.NDUFA11, the remaining nine genes showed significant differences in expression. Additionally, we investigated the CNV of the 10 genes in CC and observed that the CNVs were predominantly deletions. Notably, NDUF11 and NDUFS1 showed the highest number of copy number deletions  analysis on the differentially expressed genes between the low-DLI and high-DLI groups. The analysis revealed that the differentially expressed genes were enriched mainly in the regulation of peptidase activity and function Fig. A,B. Furt+T cells and CD8+T cells in the high-DLI group. Furthermore, we analyzed the differences in immune checkpoints between the two groups  for patients in the high-risk and low-risk groups. We discovered that regardless of the positive or negative status of CTLA4 and programmed death ligand 1 (PD-L1), the IPSs were lower in the high-risk group than in the low-risk group, indicating a potentially better response to immunotherapy  and KMT2C was significantly higher in the low-DLI group than in the high-DLI group. While further analyzing the predictive role of TMB on OS, we observed that the high-mutation group combined with the low-DLI group had the most favorable prognosis, whereas the low-mutation group combined with the high-DLI group had the worst prognosis  is crucial for tumor prognosis. The mutations in different DLI groups are depicted in Fig. sis Fig. C.Figure 50 values of various chemotherapeutic drugs in different risk groups using the Genomics of Drug Sensitivity in Cancer (GDSC) database. The results demonstrated that the IC50 values for all commonly used chemotherapeutic agents in CC were higher in the high-DLI group than in the low-DLI group. Specifically, the sensitivity to chemotherapeutic drugs was higher in the low-DLI group than in the high-DLI group  cell proliferation, migration and invasion, as well as acceleration of HCC cell apoptosis24. However, in our study, ZSCAN16-AS1 was highly expressed in the low-DLI group, a finding that is inconsistent with its expression in HCC. We believe this inconsistency is attributed to the heterogeneity of tumors. However, this finding should be confirmed in future studies on CC apart from elucidating the underlying mechanism. AC083799.1 as well as AC023043.1 are part of predictive models for the prognosis of endometrial cancer25 and kidney cancer26, respectively. Nevertheless, AL021707.6 and LINC02356 have not been reported yet, presenting a direction for future research in CC.In the present research, we investigated the expression of disulfidptosis-related genes in CC and observed that these ten genes had upregulated expression in tumor tissues. Consequently, we identified lncRNAs associated with upstream-elements and used a machine learning approach to screen for five lncRNAs differentially expressed lncRNAs with prognostic and predictive ability. These five lncRNAs were used to construct a DLI for CC. This index demonstrated the ability to predict the risk of death, OS, and PFS in patients with CC, with better outcomes observed in the low-DLI group. We conducted a literature survey on the five lncRNAs that comprising the index and discovered that three of the lncRNAs had been previously reported in studies on other cancer types. For instance, silencing of We conducted further validation to assess the independence, accuracy, and specificity of the DLI in prognostic prediction for CC. Independent prognostic analysis verified that the index could serve as a prognostic factor independent of other clinical characteristics. The ROC curve demonstrated that the diagnostic accuracy and predictive accuracy of the index were superior to those of other clinical factors, while the C-index curve indicated a higher specificity than that for other clinical factors. Furthermore, the risk score derived from the index was more widely applicable and provided a clearer definition of patient management stratification than other genetic characteristics. The Nomoscores, calculated in conjunction with other clinical factors, improved the accuracy of the prognostic assessment for patients. These validations collectively indicate that the DLI exhibits superior independence, accuracy and specificity and can be used as a target for prognostic prediction in CC.28. Currently, programmed death ligand 1 (PD-L1) expression is utilized in clinical practice to identify patients with CC who may benefit from immune checkpoint inhibitor therapy. However, recent information suggests that PD-L1 may not be a completely reliable biomarker for patient selection29. Therefore, we conducted further analysis of the immune microenvironment between the high- and low-DLI groups based on the index. Our findings revealed that immune functions  were enriched mainly in the high-DLI group. Conversely, several algorithms for immune infiltration indicated a greater enrichment of CD4+ T cells and CD8+ T cells in the low-DLI group than in the high-DLI group. This disparity can be explained by the prolonged presence of tumor antigens and inflammatory stimuli in the high-DLI group, leading to T-cell exhaustion30, and weakened tumor-killing ability, thus resulting in a worse prognosis. Based on these findings, we believe that strategies aimed at alleviating T-cell exhaustion and enhancing effector T-cell function hold promise as potential therapeutic directions for improving the prognosis of patients with CC.The immune environment, which is the most critical part of the tumor microenvironment, plays a crucial role in the regulating disease progression and response to anticancer therapyTNFRSF18, TNFRSF4, TNFRSF24, TNFRSF14 were significantly upregulated in the low-DLI group. The tumor necrosis factor (TNF), TNF receptor (TNFR), and TNF/TNFR superfamily (TNFSF/TNFRSF) include 29 receptors and 19 ligands that play a crucial role in controlling cellular processes. Communication routes mediated by TNFSF and TNFRSF are essential for various developmental, homeostatic, and stimulus-responsive processes in vivo32. Members of the TNF family have been shown potential as novel targets for tumor immunotherapy33. CD44, another important clinical target, is commonly regarded as a cancer stem cell (CSC) marker in various malignancies. High expression of CD44 significantly upregulate stumorigenic processes such as cell proliferation, metastasis, invasion, migration, and stemness34. Our study revealed upregulated CD44 expression in the high-DLI groups, consistent with the findings of previous studies. VTCN1 is also a well-reported immunotherapeutic target that promotes invasive metastasis in multiple cancer types including ovarian cancer26. In CC, VTCN1 expression facilitates the immunosuppressive microenvironment by promoting the production of IL-10 and transforming growth factor(TGF)-β1, contributing to the progression of cervical carcinogenesis35. However, in our study, we observed the elevated VTCN1 expression in the low-DLI group, which may attributed to the complex microenvironment of the tumor, and this finding should be validated in further investigations. Regarding the prediction of immunotherapy efficacy, IPS scores were calculated for the two DLI groups. The results indicated that the IPS score of the low- DLI group was higher than that of the high-DLI group in all four gene groups, suggesting that the low-DLI group has higher immunogenicity, while the high-DLI group may receive more benefit from immunotherapy strategies involving CTLA-4 blockers and PD-L1 blockers. These findings suggest that the index could serve as a reference for patient selection of immunotherapy regimens.In terms of immune checkpoint expression, 37. Our study suggested no significant difference in total TMB between the high-DLI and low-DLI groups. However, TTN exhibited a considerably higher mutation frequency in the low-DLI group than in the high-DLI group, making it the gene with the largest difference in mutation frequency. TTN mutations are identified as prognostic factor in a variety of diseases, although their effect differs among different cancer types. For example, TTN mutations are positively associated with prognosis in lung squamous cell carcinoma (LUSC)38, but the association may differ in thyroid cancer39. Survival analysis also demonstrated that high TMB combined with low-DLI resulted in the most favorable prognosis. Future studies should further investigate whether the improved prognosis is attributed to increased TTN mutations.TMB is associated with clinical response to immune checkpoint blockade therapy in certain tumors41.The recommended chemotherapy regimens involve platinum-based agents, paclitaxel or docetaxel used in combination with platinum-based agents42. However, platinum drugs, which are non-specific chemotherapeutic agents, often cause severe systemic adverse reactions, and the recurrence and distant metastasis rates of CC after chemotherapy remain high at 40%43. Therefore, other chemotherapeutic agents have been extensively studied in CC treatment. Clinical trials investigating the use of vincristine for CC treatment have also been conducted44. Our findings indicated elevated IC50 values for oxaliplatin, docetaxel, paclitaxel, and vincristine in the high-DLI group, suggesting that the low-DLI group exhibited better chemotherapy sensitivity than the high-DLI group. This can be directly applied to the clinical selection of commonly used chemotherapeutic agents.The sensitivity of chemotherapy in patients with CC notably affects prognosis. Simultaneous chemotherapy and radiotherapy (concurrent chemoradiation therapy) plus brachytherapy is the standard-of-care treatment for CC beyond locally advanced stages45. Erlotinib treatment sensitizes CSCs to paclitaxel treatment in vitro and in vivo46, Alpelisib demonstrates antitumor effects and enhances cisplatin efficacy through the PI3K/AKT pathway in PIK3CA mutant CC cells47. The expression of AL021707.6 as well as ZSCAN16-AS1 showed interesting correlation with the IC50 of these drugs, indicating a new direction in the study of targeting drugs in CC.Furthermore, our study derived novel findings by refining the prediction of the expression of the five lncRNAs in DLI in relation to the sensitivity to targeted drugs. For instance, Dactolisib, a dual PI3K and mTORC1/2 inhibitor has shown potential benefits in CC treatmentZSCAN16-AS1, AC083799.1, AL021707.6, and LINC02356 can be used as protective factors, while AC023043.1 can be used as a risk factor. The high-DLI group may exhibit increased sensitivity to immunotherapy, while the low-DLI group is more likely to benefit from chemotherapy. Clinically, detecting of the expression levels of these five lncRNAs can be used to predict the prognosis of patients with CC, guiding immunotherapy predictions, and aid the selection of chemotherapeutic agents and targeted drugs.Combining the aforementioned predictions, we conclude that the risk classification of patients based on the risk scoring model constructed by disulfidptosis-related lncRNA provides valuable insights. We developed a DLI consisting of five lncRNAs. Of these five lncRNAs, Our study still has some shortcomings. First, our study was based on a public database with limited sample size and lack of external data set validation. Secondly, we need to implement further experimental programs to confirm our study. In addition, the mechanism by which our model affects the prognosis of still needs further investigation.Our study defined five lncRNAs associated with disulfidptosis, and their index was shown to predict the prognosis of CC patients with independence, accuracy, and specificity, which could predict patient survival and facilitate clinical management of patients in a stratified manner combined with clinical characteristics. In addition, it could be used as a predictive target for the prognosis and treatment of CC, as well as a guide for the sensitivity of patients to immunotherapy and chemotherapy.Supplementary Figure S1.


There is an ongoing debate on the COVID-19 infection fatality rate (IFR) and the impact of COVID-19 on overall population mortality. Here, we addressed these issues in a community in Germany with a major superspreader event analyzing deaths over time and auditing death certificates in the community.18 deaths that occurred within the first six months of the pandemic had a positive test for SARS-CoV-2. Six out of 18 deaths had non-COVID-19 related causes of death (COD). Individuals with COVID-19 COD typically died of respiratory failure (75%) and tended to have fewer reported comorbidities (p = 0.029). Duration between first confirmed infection and death was negatively associated with COVID-19 being COD (p = 0.04). Repeated seroprevalence essays in a cross-sectional epidemiological study showed modest increases in seroprevalence over time, and substantial seroreversion (30%). IFR estimates accordingly varied depending on COVID-19 death attribution. Careful ascertainment of COVID-19 deaths is important in understanding the impact of the pandemic. There is ongoing debate on the population-specific COVID-19 fatality rates (IFRs) and on the impact of COVID-19 on overall population mortality in various settings14. It is important to mention that especially countries in Latin America have been deeply affected by the COVID-19 pandemic, where until now Peru, Brazil, and Mexico have the highest mortality rates per 100,000 inhabitants worldwide15.The COVID-19 pandemic has been associated with considerable mortality at a global level, but estimates about the total number of deaths have varied widely across populations, demographics, and countries17. However, biases often exist in such studies. Two main concerns are whether the surveyed sample is representative of the general population and whether people who get infected do not develop or lose their detectable antibodies over time. The validation of the number of COVID-19-related deaths has received less attention, but both over- and under-counting may occur18. COVID-19 deaths may have been underestimated in particular in some locations at the beginning of the pandemic when testing was limited, or because determining the cause of death (COD) in the elderly or those with multiple comorbidities was difficult. Conversely, COVID-19 deaths may have been over-attributed, e.g. if based on a positive SARS-CoV-2 test without a relevant clinical picture. Auditing of death certificates and/or medical records may help re-assess COVID-19 death attribution. For example, auditing efforts decreased the number of COVID-19 deaths in Alameda County and Santa Clara county by about a quarter compared with those that had been originally reported20.The IFR would be a robust marker for the severity of a virus-induced disease if the number of infected individuals (IFR denominator), as well as the number of deaths (IFR numerator) could be correctly measured. The number of infected individuals can be inferred by seroprevalence studies, and many such studies have been done21. However, questions emerged whether early during the pandemic COVID-19-related deaths may have been missed, mislabeled, or underestimated. Therefore, in the currently presented work, we analyzed deaths in the studied community over time and audited death certificates during the early phase of the pandemic. Specifically, we requested official death certificates of individuals who died in the community between March and October of 2020 and analyzed in detail the underlying causes of their deaths. Furthermore, we also assessed seroprevalence with repeated surveys over a year and specifically assessed seroreversion. These analyses allow for obtaining better insights into IFR estimates and on the impact of the pandemic in this intensively-studied community.Here, we address these issues in a community that witnessed the first major SARS-CoV-2 outbreak in Germany, as carnival festivities around February 15, 2020 were followed by a massive outbreak. To investigate this outbreak, we previously reported a seroepidemiological observational study that found a modest IFROur study was designed to understand possible overestimation of COVID-19-related deaths early during the pandemic, as well as the assessment of seroprevalence with repeated surveys over a year in the same community that witnessed the first major SARS-CoV-2 outbreak in Germany. Therefore, the study was divided in two arms: (1) The analyze of death certificates with reference to COVID-19 related causes of death according to WHO guidelines. (2) The assessment of seroprevalence based on a longitudinal cohort study which started early during the pandemic and lasted for 12 months. During this period, pharyngeal swabs and blood samples were collected from study participants at three different time points and analyzed for SARS-CoV-2 RNA in the swabs, as well as the antibody response against SARS-CoV-2 spike (S) and nucleocapsid (N).Between March and October 2020, 104 inhabitants of the studied community  died, according to information we obtained from the state office for information and technology in North Rhine-Westphalia (Germany). With permission from the government of North Rhine-Westphalia (Germany), the state attorneys provided us with the death certificates of 77 subjects. Out of the remaining 27 deaths, none was attributed to COVID-19  and a consensus was achieved by applying the following procedures: We extracted information about gender, date of birth, date of death, COD, comorbidities, and any SARS-CoV-2 infection on record with the corresponding date of the first positive test. We classified causes of death in the following categories: respiratory failure; sepsis; cardiovascular disease (CVD); liver failure; kidney failure; cancer; other as well as comorbidities in the categories: respiratory; sepsis; CVD; liver malfunction; kidney malfunction; cancer; neurological; diabetes; unknown; other. We also compared the number of deaths attributed to COVID-19 in the data submitted by the authorities to the national death counts versus the number of deaths attributed to COVID-19 after our audit. In attributing deaths to COVID-19 in our audit of death certificates, we followed the guidance of the WHO guidelines. Accordingly, the outcome of a COVID-19-related death is defined as resulting from a clinically compatible illness in a probable or confirmed COVID-19 case, unless there is a clear alternative COD that cannot be related to COVID-19 disease (e.g. trauma) and death due to COVID-19 may not be attributed to another disease (e.g. cancer). In addition, there should be no period of complete recovery from COVID-19 between illness and deathTo eliminate potential bias resulting from grouping the deceased based on COVID-19-related COD, three authors independently analyzed the death certificates. Each death was initially classified into categories, and then analyzed strictly in accordance with the guidelines of the WHO, as described above. In the next step, consensus was reached among the three authors, and the deaths were categorized as either COVID-19-related COD or non-COVID-19-related COD. However, since we did not have access to the full medical records of the deceased, we cannot rule out the possibility that some of the certificates indicating COVID-19 as the COD might have failed to report the existence of comorbidities as well.p-values were simulated using Monte-Carlo simulations with 50,000 replications to consistently approximate the small sample distributions under the null hypotheses23. The one-sided two-sample Kolmogorov–Smirnov test was applied to test for a location shift in the number of days from a positive COVID-19 test and death between individuals with or without COVID-19 underlying cause of death (COD). The direction of this one-sided test was determined by the ex-ante clinical experience that SARS-CoV-2-associated death occurs relatively early after infection; this experience is confirmed by the data showing an empirical first-order stochastic dominance for the group of individuals who had no COVID-19 underlying COD. A logistic regression model is used to analyze the association between the probability of a SARS-CoV-2-associated death and the number of days from a positive COVID-19 test until death. Missing and unknown values were not imputed since these concerned only very few data points: there were two missing values in the number of days from positive COVID-19 test until death, and there was one missing value in the age variable. Binomial confidence intervals are computed using the Clopper-Pearson method. All confidence intervals were computed using a 95% coverage probability. The statistical analysis was carried out using version 4.1.1 of the R Language for Statistical Computing .Parametric normality assumptions were not applied to avoid distributional misspecifications in moderate to small samples where a central limit theorem may not be applicable. Fisher's exact two-sided test was used to test for independence between two-factor variables with two levels (2 × 2 designs). Pearson’s Chi-squared test was used to test for independence between factor variables and Pearson’s’ Chi-squared goodness-of-fit test was used to test hypotheses about categorical distributions. For both chi-square tests, the There are clear data protection laws in Germany under which circumstances researcher can obtain identifiable information. Under §8 of the regional German burial act, we are allowed to analyze death certificates when there is justifiable public interest. Therefore, this analysis was classified as important and the Ministry of Health in North Rhine-Westphalia (Germany) approved the request for access to the death certificates and the district attorney of every city where the patients died provided the certificate. The original study was approved by the Ethics Committee of the Medical Faculty of the University of Bonn . However, only a very limited number of employees of the Institute of Virology  had access to the complete death certificates and data from the death certificates which was shared with external contributors  was fully anonymized.21. This provided us with the advantage of having baseline data for time point 0 in our longitudinal survey. The criteria for initial enrollment was described in Streeck et al.21. Briefly, enrollment was based on a sample of 600 persons contained in the civil register of the community. Sampling was done randomly with the side condition that all 600 persons had different surnames, as it was assumed that different surnames were likely to indicate different households. In total, a dataset from 919 participants was analyzed in the original study. For the seroprevalence follow-up survey described here, these 919 participants were invited again via letter to participate in at least one of the three follow-up visits in October 2020 (Visit 1), January 2021 (Visit 2), and April 2021 (Visit 3). The only inclusion criterion was enrollment and sampling in our previous study. The exclusion criteria for participation were individuals who were unavailable on the day of sampling and requested a later appointment, or did not want to provide blood specimen and/or a pharyngeal swab, or had medical issues that made sampling impossible. However, individuals who did not participate in visit 1 were not excluded from being invited to visit 2 and 3. The total number of participants was 603 and for each visit was: Visit 1 (603), Visit 2 (570), and Visit 3 (475)  using enzyme-linked immunosorbent assays (ELISA) on the EUROIMMUN Analyzer I platform. According to the manufacturer’s instructions, a result was considered positive when a ratio  of 0.8 or higher was reached. In addition, the Roche Elecsys® N ELISA was used to determine antibody response against the nucleocapsid (N) of SARS-CoV-2. The result is given in COI (cutoff index), which is positive between 1.0 and approximately 250. Further, we estimated for each visit after the original one how many participants had undergone seroreversion, defined as a ratio of IgG below 0.8. For SARS-CoV-2 RT-PCR, first viral RNA isolation from pharyngeal swabs was performed on the day of sampling on the chemagic™ Prime™ instrument platform (Perkin Elmer) using the chemagic Viral 300 assay, or via the AltoStar® Purification Kit 1.5 (CE-IVD) on the AltoStar® AM16, according to manufacturer’s instructions, respectively. RT-PCR for two viral targets (E and S genes) was performed on isolated RNA samples via the RealStar® SARS-CoV-2 RT-PCR kit 1.0 (Altona Diagnostics). Internal control Ct values were within an acceptable range in all assays.Planning and conduct of the study were supported by the Clinical Study Core Unit of the Study Center Bonn (SZB). Support included protocol and informed consent development following specifications of the WHO with regards to pandemic events, data management, submission to the ethics committee, clinical trial monitoring and quality control. Study data were collected and managed using REDCap electronic data capture tool. REDCap is a secure, web-based software platform designed to support data capture for research studies, providing (1) an intuitive interface for validated data capture; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for data integration and interoperability with external sources. Questionnaire data were recorded on site using paper case report forms and were entered into the electronic study database using double data entry by trained study personnel.Especially during the early phase of the SARS-CoV-2 pandemic, poorly or incorrectly executed pharyngeal swabs had a negative impact on the quality and results of SARS-CoV-2 RNA detection via PCR. To prevent differences in quality, all pharyngeal swabs in this study were performed by trained medical personnel to ensure consistent quality. Furthermore, it is known that the IgG-ELISA used from EUROIMMUNE had a sensitivity of 90.9% and a specificity of 99.1% according to the manufacture. To eliminate this bias, IgG values were corrected for sensitivity and specificity.21. Infection rates obtained from IgG measurements were corrected for misclassification bias using the matrix method24, based on sensitivity and specificity values reported by the manufacturer ELISA . Confidence intervals for the infection rates were computed using a bootstrap procedure based on 10,000 bootstrap samples with clustering on household-level by resampling individuals in household clusters with replacement25. As the bootstrapped data do not show severe abnormalities and the sample sizes are large, we estimate confidence intervals by the 2.5th and 97.5th percentiles of the bootstrap distribution. The generated bootstrap distribution was symmetrical and close to Gaussian . To analyze seroreversion, defined as IgG values below the ratio of 0.8, we analyzed participants who were IgG(+) at baseline and participated at least in one of the three follow-up visits. Important to note, we excluded participants who were SARS-CoV-2 vaccinated, which would cause an increase in IgG levels. Wilcoxon sign-rank tests are used to statistically evaluate the change of IgG ratio with time. Here, the resulting p-values were adjusted for multiple testing following the Bonferroni-Holm procedure. Confidence Intervals (CIs) for the IFR were computed by dividing the number of deaths by the CI limits of the estimated number of infected. We estimated IFR using different acquisition periods  as this has been a debated issue in previous meta-analyses of IFR27. The numbers of SARS-CoV-2-associated deaths in the studied community for given lengths of acquisition periods can be considered fixed as the data acquisition corresponded to a complete survey of all recorded SARS-CoV-2-associated deaths in the community during the study period. In addition, we generated also separate IFR estimates for the ages groups 0–54, 55–74, and > 75 years. Additional statistical analysis is described in the For sample size calculations, see the previous studyhttps://www.drks.de, identification number DRKS00021306). The study was conducted in accordance with good clinical (GCP) and epidemiological practice (GEP) standards as well as comply with the guidelines of the Declaration of Helsinki (2013) and applied the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.The original study was approved by the Ethics Committee of the Medical Faculty of the University of Bonn  and has been registered at the German Clinical Trials Register ) with cases of ARDS and respiratory failure, pneumonia, septic shock, and multi organ failure as COD. The death certificates of these 12 patients stated that they were admitted to the hospital with an acute SARS-CoV-2 infection, where their state of health deteriorated rapidly. Most of the cases were admitted with already advanced pneumonia, which developed into ARDS with subsequent multiple organ failure or septic shock as additional COD. Conversely, in six out of 18 deaths ) with confirmed SARS-CoV-2 infection, we identified other factors to be the underlying COD. Two individuals died as a result of acute kidney failure after lactic acidosis and exsiccosis. They both had a medical history of diabetes mellitus type II, chronic obstructive pulmonary disease (COPD), and dementia, and in both cases their state of health deteriorated rapidly due to the underlying diabetes mellitus. Additionally, they had refused to eat and drink as a result of dementia, which ultimately led to acute kidney failure and exsiccosis. One individual had decompensated cardiac insufficiency with a medical history of food refusal, COPD, epilepsy, and Korsakov's disease, while another had a history of advanced and metastasized oesophageal carcinoma. The death certificates of these cases described a progressively deteriorating general condition of the patient, with eventual death from their underlying illnesses. Lastly, there was one case of acute liver and kidney failure as stated COD with no documented comorbidity on the death certificate and one case of cardiovascular failure as well as respiratory insufficiency with a medical history of diabetes and cardiovascular disease. In the latter case, it was noted, that the individual had previously recovered from SARS-CoV-2 infection. In addition, five out of the six individuals died three to six months after confirmed SARS-CoV-2 infection and more importantly the death certificates of all six cases reported recovery from COVID-19, which implies a period of complete recovery from COVID-19 between illness and death. Therefore, these cases do not fulfill the criteria of the WHO guidelines to be counted as COVID-19 deaths. Overall, only 12 out of 18 deaths with confirmed SARS-CoV-2 infection died because of COVID-19 between March and October 2020. During the same time period (March to October 2020), the authorities had reported 15 COVID-19 deaths to the national COVID-19 death countsNext, we analyzed differences in age, COD, and comorbidities among all deaths that had occurred in the studied community. Therefore, we grouped the 77 deaths into three mutually exclusive groups . There were no statistically significant differences in the age distribution   Fig. . The numFigure 21, and ask them to participate in at least one of the three follow-up visits  this is coherent with the recently published cause-of-death statistics of 2020 for Germany from the Federal Statistical Office26. Interestingly, during the same time period (March to October 2020), the authorities had reported 15 COVID-19 deaths to the national COVID-19 death counts28. Therefore, apparently three of the deaths that were not caused by COVID-19 had been officially reported as COVID-19 deaths.The published WHO guidelines define a COVID-19-associated death as a death resulting from a clinically compatible illness, in a probable or confirmed COVID-19 case, unless there is a clear alternative cause of death29. Reported studies of COVID-19-associated deaths in Germany and the UK determined septic shock, multi organ failure, and respiratory failure as the most common immediate COVID-19 underlying COD, often due to suppurative pulmonary infection and diffuse alveolar damage32. Our findings for our studied community are consistent with this, as 75% of the COVID-19-associated deaths died from respiratory failure in combination with septic shock and multi organ failure. Furthermore, it was described that smoking, or some comorbidities like cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 deaths in association with age30. Although we do not see significant associations with age or specific comorbidities (probably due to the low number of cases), we determined kidney failure, lactic acidosis or cancer as the main causes in non-COVID-19 associated deaths. These findings support the importance of looking more carefully into the deaths of individuals with a confirmed SARS-CoV-2 infection and taking into account the individual’s medical history along with their most recent medical data and symptoms.Recent publications have highlighted difficulties in counting deaths with COVID-19 underlying COD and the need for continuous surveillance of mortality records35. It was reported that the median length between symptom onset and hospitalization ranged between three and 10.4 days, depending on the age of the patient34. However, the length of stay in hospital for patients who died eventually was an additional six to seven days as reported in a Belgian study34, and for China35 the estimated mean time from symptom onset to death was 18.8 days. Although a positive PCR test for SARS-CoV-2 does not necessarily coincide with the onset of symptoms, the results are consistent with our findings. Individuals in our studied community with SARS-CoV-2-associated deaths had a median of 18 days between positive PCR-test and death, whereas individuals with no COVID-19-underlying COD had a longer time span with a median of 144 days. The likelihood to die of COVID-19 decreased sharply with longer follow-up markedly after confirmed SARS-CoV-2 infection.Recent publications on COVID-19 disease progression analyzed the length of stay in the hospital and survival time36. It is possible that many of the COVID-19 fatalities in the community might have been in people with limited life expectancy, regardless of whether they were institutionalized or not. Obviously, one has to be cautious with these inferences, especially given the relatively small number of deaths. Of note, eventually the overall number of deaths in the community for the calendar year 2020 (n = 157) was similar to the calendar years 2018 (n = 156) and 2015 (n = 158) but higher than other previous recent years. However, this was likely influenced by the hard lockdown in the community in March and April 2020.Evaluation of the deaths per month and age stratum showed a peak of deaths in March 2020 and it was concentrated in people over 70, consistent with the age of the early COVID-19 fatalities. We could not retrieve information on how many of these individuals might have been nursing home residents. However, this specific community has a high proportion of its population residing in nursing homes 21. However, we documented substantial rates of seroreversion, which is in agreement with some other studies44. Although IgM, IgA, and IgG antibodies can arise nearly simultaneously, it is known that IgM/IgA antibodies decay more rapidly than IgG, which can persist for at least several months46. Nevertheless, some studies have found higher rates of seroreversion, e.g. one investigation found a median time to seroreversion for IgG being only 55 days38, but this may include false positives at initial screening. Nonetheless, seroreversion likely causes the number of infected individuals to be substantially underestimated and thus the IFR to be overestimated38. This may apply even to our early April 2020 survey that happened within two months of the superspreader event.Furthermore, repeated seroprevalence surveys showed that seroprevalence changed only modestly in the fall of 2020 and beyond as compared with our previously published results on seroprevalence in April 202021, we noticed that the tested sample had a lower proportion of documented RT-PCR infections than the overall community population (2.39% versus 3.08%). Correction for this factor would decrease IFR estimates by 29% (e.g. from 0.36%–0.62% to 0.28%–0.48%). The sampling deviation was seen also, even more prominently in the follow-up surveys, where only 2 participants tested positive by RT-PCR . It may reflect the fact that participants  may be more health conscious; or alternatively, less likely to perform RT-PCR testing since they are tested for antibodies. We also observed that our original seroprevalence study sample was under-representative of individuals infected during the main carnival event, the Kappensitzung, where participants had very high infection rates47, three times higher than the general population of the community by April 2020. It should be noted that different studies have shown the possibility that individuals were already infected with SARS-CoV-2 prior to the first documented COVID-19 case in the community, which can also contribute to higher infection rates and should be considered for mortality profiles50. Due to the small number of cases, we were not able to exclude that this may have been entirely due to chance but the pattern is consistent with the possibility that seroprevalence is underestimated . These observations highlight the difficulty of using seroprevalence samples and repeated surveys to assess the number of infected individuals in a population.Estimates of the number of people infected in the population may also be affected by the representativeness of the surveyed sample. In our original seroprevalence survey in April 202051. It should be noted that due to the study design, the results of this study can only be representative for this specific community. Overall, in seroprevalence studies where only a tiny portion of the population is selected for serological testing  one should remain cautious, as errors in counting deaths, seroprevalence, and other sources of uncertainty may have a larger impact.Our observations show that the calculation of IFRs needs to be done very carefully and that their interpretations need to take into account all possible influencing factors. In our study, overestimation  of COVID-19 deaths and underestimation  of seroprevalence may have inflated the IFR estimate. Additional variability in the estimates may be introduced by the time window used for capturing deaths, its relationship to the time window of the seroprevalence, and the assumptions made about the delay in developing antibodies and in dying after infection. In the case of this specific community, these uncertainties would probably still be captured by the original confidence interval that we reported for IFR in our original publication and that allowed for uncertainty in the number of deaths . Moreover, the exact case mix of infected individuals can have a major impact on the IFR, given the extremely steep age gradient that has been documented before and which we also saw prominently in the community data21, the age group of 70 years or older is over-represented within the death certificates and the 919 invited individuals compared to the studied community, the state of NRW and Germany. The reasons for this could be that elderly people have higher risk because severe cases are presumed to be more likely to occur in this age group; and secondly, due to retirement may have had more time to participate in a seroepidemiological observational study. (2) There was no access to the full medical records of the deceased due to data protection laws in Germany. Under §8 of the regional German burial act, we were allowed to analyze death certificates when there is justifiable public interest. We are aware that this cannot substitute for the full medical records and therefore, we cannot exclude the possibility that some of the certificates where the COD was COVID-19 simply failed to report also existing comorbidities.Possible limitations of this study include the following: 1) as shown in Supplementary Table  as shownIn conclusion, our in-depth assessment of the fatality impact of COVID-19 in the studied community shows a relatively low fatality rate in this community with deaths concentrated entirely in the elderly, but seroprevalence estimates that go into IFR calculations need careful considerations of their time window, potential seroreversion, and representativeness. Importantly, COVID-19 deaths may have been over counted and the relative contribution of over- and under-counting of COVID-19 deaths needs careful auditing across multiple other locations.Supplementary Information.


Cognitive training shows promising effects for improving cognitive domains in individuals with mild cognitive impairment (MCI), including the crucial predictive factor of executive function (EF) for dementia prognosis. Few studies have paid sufficient emphasis on the training-induced effects of cognitive training programs, particularly with regards to targeting EF. A process-based multi-task adaptive cognitive training (P-bM-tACT) program targeting EF is required to examine direct, transfer, and sustainability effects in older adults with MCI.This study aimed to evaluate the direct effects of a P-bM-tACT program on EF, the transfer effects on untrained cognitive domains, and further explore the sustainability of training gains for older adults with MCI in the community.In a single-blind, randomized controlled trial, 92 participants with MCI were randomly assigned to either the intervention group, participating in a P-bM-tACT program  or the wait-list control group, accepting a health education program on MCI . The direct and transfer effects of the P-bM-tACT program were assessed at baseline, immediately after 10 weeks of training, and the 3-month follow-up. Repeated measures analysis of variance and a simple effect test were used to compare the direct and transfer effects over the 3-time points between the two groups.The P-bM-tACT program yielded a greater benefit of direct and transfer effects in the intervention group participants than in the wait-list control group. Combined with the results of simple effect tests, the direct and transfer effects of participants in the intervention group significantly increased immediately after 10 weeks of training compared to the baseline , and these effects were maintained at the 3-month follow-up . Besides, the acceptability of the cognitive training program was established with a high adherence rate of 83.4%.The P-bM-tACT program exerted positive direct and transfer effects on the improvement of cognitive function, and these effects were sustained for 3 months. The findings provided a viable and potential approach to improving cognitive function in older adults with MCI in the community.www.chictr.org.cn; Number Registry: ChiCTR1900020585).The trial was registered at Chinese Clinical Trials Registry on 09/01/2019 (The online version contains supplementary material available at 10.1186/s12888-023-04917-3. Mild cognitive impairment (MCI) is considered a critical window of opportunity to prevent/intervene and therapeutic intervention of dementia . ExecutiPrevious studies suggested that cognitive training is a potentially effective way to improve EF in older adults with MCI , 7. Two Additionally, prior studies indicated that the benefits of process-based cognitive training are typically limited to the specific cognitive functions associated with training domains , 13. GivNoteworthy, previous studies have shown that adaptive cognitive training, which involves the dynamic adjustment of training task demands based on an individual’s current level of performance, is associated with a more significant transfer effect than non-adaptive . BuildinTo address the above-mentioned issues, we developed a P-bM-tACT program based on our study protocol , targetiWhat is the advantage of a P-bM-tACT program in older adults with MCI? We hypothesized that older adults with MCI who participated in the P-bM-tACT program would have a better EF performance.Whether the P-bM-tACT program could engender transfer effects and modify the functions of untrained cognitive domains. We further hypothesized that there were transfer effects in work memory and psychomotor speed would be evoked by the P-bM-tACT program.Whether potential direct and transfer effects related to the P-bM-tACT program could be sustained over time after the short-term intervention. We further hypothesized that all training gains would have sustainability effects.This study was conducted at a community healthcare service center in Huzhou City, China, from March 2019 to March 2022 as a randomized controlled trial with a 3-month follow-up assessment. This study was registered at Clinical Trials.gov ChiCTR1900020585 on 19 January 2019. Results are reported in accordance with the CONSORT Consolidated Standards of Trials statement for non-pharmacological interventions and have obtained ethical approval from the Medical Ethics Committee of the Third People’s Huzhou Hospital of Zhejiang Province (NO.2018-030). All eligible participants voluntarily signed the written informed consent after being fully informed of the study purpose and procedures by the research assistant.Community-dwelling older adults aged 60 years and over were recruited from community senior centers and healthcare centers in the Wuxing district. Our staff distributed recruitment leaflets, and local healthcare providers also helped to make referrals to our study. Individuals who showed interest were invited for an in-person interview to screen for eligibility by three trained staff. A total of 448 potential individuals who complained of subjective memory impairment were screened in the first eligibility assessments. The second round of eligibility assessments included demographics and health characteristics , functional assessment of activities of daily, and general cognitive function. A trained neurologist-psychiatrist examined the potential participants to provide the final diagnosis of MCI. Individuals who met the following inclusion and exclusion criteria were invited to enroll  were given an intervention manual with detailed instructions and attended approximately 3 h of video conferencing training. All cognitive tasks commence with in-person instruction provided and supervised by the three trained registered community nurses following a standardized intervention protocol. Participants followed the same training schedule and were reminded via phone call to complete their training program if missing over one week by two research coordinators. Participants who failed to complete the task within the fixed time were given proper technique guides. In addition, extra training was offered for participants not finishing the cognitive training. The research coordinator would oversee the compliance of all participants at each session. All participants received bi-weekly phone calls during follow-up to balance the contact effect and reduce the loss rate.A self-designed questionnaire was used to collect demographic data and health characteristics at baseline, including age, gender, education level, residence, marital status, monthly income, occupation, living area, intellectual activity, and overall cognition function.The direct effect related to training gains was EF. The transfer effects related to training gains included near transfer effect (working memory) and far transfer effect (psychomotor speed).Measurements directly relating to the training’s target cognitive domain could be more accurate and efficient in evaluating the possible cognitive effects of the intervention . In thisThe transfer effects related to training gains by the P-bM-tACT program included near transfer effects (working memory) and far transfer effects (psychomotor speed). This study measured the working memory by two subtests, including Digit span forward and backward from the Wechsler Adult Intelligence Scale-Revised . SensitiThe following formula was used to calculate the adherence rate of the P-bM-tACT program: the number of practice programs /30 times  ×100%.Data collection was conducted in the community healthcare center. Three trained assessors blinded to the participant group conducted a set of variable assessments. The basic characteristics were measured at baseline (T0); The outcome variables, including EF , working memory  and psychomotor speed  were measured at baseline, immediately after 10-week of training (T1), and the 3-month follow-up (T2). A more detailed account of study assessments and timelines was illustrated in Supplementary Table All statistical analyses were performed using SPSS 21.0 . The method of exploratory analysis  was used to test the distribution state of the data. The chi-square test , independent-samples t-test , and Wilcoxon Rank Sum Test  were used to examine the difference between groups on baseline demographic and outcome variables. A repeated-measures ANOVA was performed for 3-time points to evaluate the effect of group factors, time factors, and the interaction between time × group on the outcomes variables. A simple effect test was used to examine the difference among groups within each time point and between the 3-time points within each group when the interactions of time×group were significant. Effect size, one of the critical indicators to explain the potential clinical significance, was calculated using Cohen’s d .As shown in the CONSORT flow diagram, 448 older adults in the community were screened, 92 were recruited and assigned to the intervention group or the wait-list control group at a 1:1 ratio randomly  and a far transfer effect . One predominant hypothesis assumes that transfer effects are likely to occur if the trained and untrained cognitive domains share a common neural network or rely on similar neural activations , it is eIn this study, the near transfer effect on working memory was observed after the intervention and was found to be sustained over 3-month follow-up period. It is well-established that performance on working memory, as assessed by the digit span test, is associated with executive control or brain regions where EF dominates, such as the left frontal lobe and posterior parietal white matter –45. PrevThe results of this study indicated that after 10-week of training intervention, the far transfer effect in psychomotor speed was observed and sustained over 3-month follow-up period. Previous studies have mostly utilized reaction time and finger tapping tests to evaluate psychomotor speed, attention control, and cognitive flexibility , 52. In The persistent effect of training, one of the most valuable cognitive training features, has been found to be an important precipitating factor in reducing the risk of progressive dementia due to MCI . This stTwo strong points need to be highlighted in this study. Firstly, we demonstrated the effectiveness, feasibility, and acceptability of a nurse-led cognitive training program for older adults with MCI in the community setting. In China, where community healthcare resources are limited, access to professional cognitive and mental health therapists is only available in a few large cities . TherefoThis study offers important implications for nursing practice in community settings. The nurse-led health management P-bM-tACT program, developed in this study is an encouraging step towards involving community nurses in the cognitive health of older adults with MCI. Community nurses can provide cognitive education and self-management activities to promote cognitive health in community-dwelling older adults with MCI. Therefore, specialized cognitive training skills for community nurses are essential to successfully implement cognitive training programs. Second, given the direct and transfer effects on cognitive benefits of the P-bM-tACT program, nurses at the primary health services center should encourage older adults with MCI to engage in periodic cognitive training. Actions should be taken to enhance adherence to cognitive training among older adults with MCI, such as dynamic adjustment of difficulty of the training task, peer or family support, and schedule development. These healthy behaviors will reinforce and prolong the beneficial effect of training in older adults with MCI.Several limitations of this study need to be mentioned. The sample population in this study may not fully represent the overall characteristics of older adults with MCI due to the exclusion of those with color blindness and education levels below the primary school. Future studies will be critical to confirm the applicability of these benefits to diverse populations. Besides, we employed a wait-list control group instead of an active control group, as a previous study showed that the effect size might be similar between active control and passive control . The debThe growing interest in cognitive interventions for MCI promoted the need to increase its application to prevent or slow further cognitive decline. The presented study confirmed that the P-bM-tACT program enabled older adults with MCI to improve and sustain training effects (direct and transfer effect) and demonstrated the sustainability of training-induced effects over time. Future research with medical imageology data is proposed to identify the mechanisms through which transfer effects produce and to refine the understanding of the transferability scope and limits.Below is the link to the electronic supplementary material.Supplementary Material 1? Instruments for the P-bM-tACT program.Supplementary Material 2? Supplement Table 1-Training tasks of the P-bM-tACT program.Supplementary Material 3? Supplement Table 2-Summary of study assessments and timelines.