Immune checkpoint inhibitor (ICI)-induced myocarditis is rare but fatal. Because of the rapid course of ICI-induced myocarditis, understanding of clinical course is only possible through information from case reports. We report a case of pembrolizumab-induced myocarditis in which we were able to document the course of electrocardiographic changes from onset to death. A 58-year-old woman with stage IV lung adenocarcinoma, who had completed her first cycle of pembrolizumab, carboplatin, and pemetrexed, was admitted with pericardial effusion. She underwent pericardiocentesis after admission. A second cycle of chemotherapy was administered 3 weeks after the first cycle. Twenty-two days after admission, she developed a mild sore throat and tested positive for SARS-CoV-2 antigen. She was diagnosed with mild coronavirus disease 2019 (COVID-19), isolated, and treated with sotrovimab. Thirty-two days after admission, an electrocardiogram showed monomorphic ventricular tachycardia (VT). Suspecting myocarditis caused by pembrolizumab, the patient was started on daily methylprednisolone after coronary angiography and endocardial biopsy. Eight days after the start of methylprednisolone administration, she was considered to have passed the acute stage. However, four days later, R-on-T phenomenon triggered polymorphic VT and she died. The impact of viral infections such as COVID-19 on patients be treated with immune checkpoint inhibitors is still unknown and we need to be careful with systemic management after viral infections. The advent of immune checkpoint inhibitors (ICIs) has revolutionized cancer treatment. ICIs sustain T-cell activation and exert the anti-tumor effects by blocking immunosuppressive signaling from antigen-presenting cells and tumor cells . CurrentRecently, the coronavirus disease 2019 (COVID-19) pandemic has had a major impact on healthcare. COVID-19 is an acute respiratory illness caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is known that some COVID-19 patients develop cytokine release syndrome (CRS), in which inflammation-inducing cytokines are increased and the immune system is activated -7. TheorA 58-year-old female with a smoking history of at least 35 pack years had no medical history of dyslipidemia, diabetes mellitus, hypertension or other medical conditions, and no family history of coronary artery disease. She received her second COVID-19 vaccination 6 manths ago and no other vaccinations. She was diagnosed with left lower lobular adenocarcinoma of the lung that had metastasized to the left hilar and right mediastinal lymph nodes, invading the pericardium. The tumor was negative for epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), with a programmed death ligand 1 (PD-L1) tumor proportion score (TPS) of 25%. She visited her previous physician complaining of dyspnea after completing her first cycle of pembrolizumab, carboplatin, and pemetrexed 9 days earlier. Subsequently, she was referred to our hospital due to a worsening pericardial effusion on computed tomography (CT) scan Figure 1On initial examination, she was afebrile with a blood pressure of 125/78 mm Hg, a heart rate of 124 beats/min, and an oxygen saturation of 97% on 3 liters per minute of oxygen administration. Blood tests showed no elevation of creatine kinase (CK), creatine kinase–myocardial band (CK-MB) or troponin T. Electrocardiogram showed sinus tachycardia and low-voltage QRS complexes  immediately after EMB. The following day, CK and CK-MB decreased on blood test Figure 3This is the first report of pembrolizumab-induced myocarditis after COVID-19 infection and is also a valuable case in which electrocardiographic changes of myocarditis could be recorded in detail. Although the patient died as a result of arrhythmia, we were able to confirm that corticosteroids are markedly effective in the acute phase of pembrolizumab-induced myocarditis.Myocarditis is an inflammatory disease of the myocardium caused by viral infection, autoimmunity, or drugs . The defICI-induced myocarditis occurs when ICIs maintain T lymphocyte activity, T lymphocytes infiltrate the myocardium, and the immune response is excessive . The medOn the other hand, COVID-19-associated myocarditis is thought to result from direct damage to the myocardium by the virus and myocardial damage by the host’s immune response . The exaThis patient developed myocarditis 41 days after the first dose of pembrolizumab and 11 days after SARS-CoV-2 infection. Myocardial tissue showed histological findings of acute lymphocytic myocarditis. The timing of onset and histological findings of myocarditis were consistent with both pembrolizumab-induced myocarditis and COVID-19-associated myocarditis. We considered pembrolizumab-induced myocarditis most likely since that myocarditis improved markedly after corticosteroid administration. However, COVID-19-associated myocarditis also causes myocardial damage due to the immune response, so it cannot be completely ruled out. COVID-19 infection has been reported to increase the risk of serious irAEs and may have triggered the development of pembrolizumab-induced myocarditis in this case .An electrocardiogram is a simple test that records the heart’s electrical signals and is often used to detect arrhythmias and myocardial disorders. In this case, symptoms of myocarditis, such as palpitations and chest pain, were not present at first, and it was difficult to suspect myocarditis from the symptoms alone. However, we were able to suspect myocarditis at an early stage based on elevated CK and electrocardiographic changes. In addition, frequent ECG testing after the onset of myocarditis made it possible to document ECG changes during the course of treatment for myocarditis. Poor prognostic factors in electrocardiograms of acute myocarditis have been reported as pathological Q wave, wide QRS complex, QRS/T angle ≥ 100°, prolonged QT interval, high-degree atrioventricular block and malignant ventricular tachyarrhythmia –32. TherThere have been several case reports of successful treatment of pembrolizumab-induced myocarditis –36. HoweThere are several limitations in the present case report. First, it was difficult to perform an CMR on COVID-19-infected patients at our institution, and second, we were unable to perform a viral genome study of myocardial tissue. A viral genome study of myocardial tissue might have brought us closer to identifying the cause of myocarditis.We report a case of pembrolizumab-induced myocarditis that developed after COVID-19 infection, in which we were able to document the course of electrocardiographic changes from onset to death. In myocarditis, elevated myocardial markers and electrocardiographic changes may precede clinical symptoms, so regular myocardial marker measurements and electrocardiographic testing are important. In addition, ECG examination is useful even after the start of treatment, since the prognosis may be inferred from ECG changes. Early diagnosis of pembrolizumab-induced myocarditis is important because early administration of corticosteroids may improve the prognosis. The impact of viral infections such as COVID-19 on patients with ICIs is unknown, and the appearance of irAEs after infection should be noted.The original contributions presented in the study are included in the article. Further inquiries can be directed to the corresponding author.The manuscript was drafted by KN and KM. KN, KM, YS, JU, ST, HT, SA, AI, and MM examined and treated the patient. NY performed the histopathological assessment. YA gave clinical advice. All authors contributed to the article and approved the submitted version.


Anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease (anti-MDA5 DM-ILD) is a disease with high mortality. We sought to develop an effective and convenient prediction tool to estimate mortality risk in patients with anti-MDA5 DM-ILD and inform clinical decision-making early.This prognostic study included Asian patients with anti-MDA5 DM-ILD hospitalized at the Nanjing Drum Hospital from December 2016 to December 2020. Candidate laboratory indicators were retrospectively collected. Patients hospitalized from 2016 to 2018 were used as the discovery cohort and applied to identify the optimal predictive features using a least absolute shrinkage and selection operator (LASSO) logistic regression model. A risk score was determined based on these features and used to construct the mortality risk prediction model in combination with clinical characteristics. Results were verified in a temporal validation comprising patients treated between 2019 and 2020. The primary outcome was mortality risk within one year. The secondary outcome was overall survival. The prediction model’s performance was assessed in terms of discrimination, calibration, and clinical usefulness.This study included 127 patients,  and temporal validation  cohorts. Five optimal features were selected by LASSO logistic regression in the discovery cohort (n = 87) and used to construct a risk score, including lymphocyte counts, CD3+CD4+ T-cell counts, cytokeratin 19 fragment (CYFRA21-1), oxygenation index, and anti-Ro52 antibody. The retained predictive variables in the final prediction model were age, Heliotrope, fever, and risk score, and the most predictive factor was the risk score. The prediction model showed good discrimination , good calibration , and fair clinical usefulness in the discovery cohort. The results were verified among patients in the temporal validation cohort (n = 38). We successfully divided patients into three risk groups with very different mortality rates according to the predictive score in both the discovery and validation cohorts .We developed and validated a mortality risk prediction tool with good discrimination and calibration for Asian patients with anti-MDA5 DM-ILD. This tool can offer individualized mortality risk estimation and inform clinical decision-making. Dermatomyositis (DM), as one idiopathic inflammatory myopathy (IIM), is an idiopathic inflammatory disease with inflammatory, immune-mediated organ damage. This disease can affect multiple organs, including the lung, muscle, skin, joints, and heart , 2. InteRapid progression interstitial lung disease (RPILD), as a typical manifestation, is characterized by progressive deterioration of dyspnea and hypoxemia within three months. Despite immediately receiving an aggressive combined treatment of corticosteroids and immunosuppressive agents, more than 50% of anti-MDA5 DM-RPILD patients still experience a fatal outcome in the disease course due to resistance to the treatment , 10. In Several potential parameters for distinguishing anti-MDA5 DM RPILD from anti-MDA5 DM non-RPILD and predicting survival in anti-MDA5 DM patients have been found, including demographics, imaging features, and laboratory indicators –21. AmonPatients with anti-MDA5 DM-ILD hospitalized at the Department of Respiratory and Critical Care Medicine in Nanjing Drum Tower Hospital between December 2016 and December 2020 were screened. Patients with overlapping syndromes or malignant tumors, such as systemic sclerosis, Sjogren’s syndrome, and lung cancer, were excluded. All the patients were aged above 18 years and had a follow-up period of at least 12 months. The Ethics Committee of the Nanjing Drum Tower Hospital approved the study protocol. Written informed consent was waived due to the nature of the retrospective study and anonymous processing of individual data. This retrospective prognostic study was reported following the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) reporting guideline and conducted under the Declaration of Helsinki.DM was diagnosed according to the Bohan and Peter criteria . The diaClinical data for all patients were extracted from reviewing the medical records. Demographic information, such as the age of onset, sex, and clinical manifestations, including heliotrope sign, Gottron’s sign, Mechanic’s hands, Skin ulceration, Arthralgia, muscle weakness, and fever was obtained. The survival data were collected by reviewing the medical records or over telephone calls. Self-reported clinical manifestations were also recorded if they did complain at the follow-up.This study detected MSAs and MAAs in patients using an immunoblotting method  by the same central lab while patients were first admitted to the hospital. Laboratory indicators were collected, including routine blood tests , myositis antibodies, C-reactive protein (CRP), creatine kinase (CK), lactic dehydrogenase (LDH), and arterial blood gas analysis . If available, baseline pulmonary function testing parameters were recorded, including forced vital capacity predicted (FVC%) and diffusing capacity of the lung for carbon monoxide predicted (DLCO%).Chest HRCT was performed in 127 patients at admission. Imaging appearances are mainly described as organizing pneumonia (OP) patterns and nonspecific interstitial pneumonia (NSIP) patterns combined with OP. Variables with missing values included CYFRA21-1 (n=5) and OI (n=1). The missing patterns are presented in The primary outcome was mortality risk within one year. The secondary outcome was overall survival. Continuous variables are presented as medians and interquartile ranges (IQRs) and were compared using the Mann–Whitney U test. Categorical variables were described as frequencies and percentages and compared using the χ2 test or Fisher’s exact test. Multiple imputations of the missing values were performed using a multivariable imputation by chained equations algorithm. Time-to-event data were estimated using the Kaplan–Meier method. We developed the prediction tool using a discovery cohort (n = 89) comprising patients with anti-MDA5 DM-ILD who underwent treatment between December 2016 and December 2018. The prediction tool was developed in two steps.In the first step, a least absolute shrinkage and selection operator (LASSO) logistic regression model, along with 10-fold cross-validation, was applied to select the optimal predictive features among the candidate blood indicators in the discovery cohort. A risk score was subsequently constructed based on the corresponding coefficients of optimal features identified in the LASSO logistic regression using lambda.1 se. In the second step, the risk score and clinical characteristics were included in a stepwise multivariate logistic regression model. Model selection was based on the likelihood ratio test with Akaike’s information criterion (AIC) as the stopping rule. The model with the smallest AIC was selected as the optimal model and was further applied to develop the final prediction tool. The performance of the prediction tool was assessed for discrimination, calibration, and clinical usefulness. The discriminative ability was measured using the area under the receiver operating characteristic (AUC) curves. Bootstrapping with 2000 replicates was performed to generate the AUCs and corresponding 95% confidence intervals (CIs). Calibration was examined by the Hosmer–Lemeshow goodness-of-fit test, Brier score, and observed versus predicted graphs. Clinical usefulness was assessed using decision curve analysis (DCA). Data from an independent cohort of patients with anti-MDA5 DM-ILD who underwent treatment from January 2019 to December 2020 were used for temporal validation.All statistical analyses were performed in R version 4.2.0 . A two-sided P value of less than 0.05 was considered significant.This study included a total of 127 Asian patients  and temporal validation  cohorts based on year of diagnosis. Descriptive statistics of patients in the discovery and temporal validation cohorts are summarized in +CD4+ T cells, cytokeratin 19 fragment (CYFRA211), oxygenation index (OI), and anti-Ro52 antibody  in the univariate logistic regression analysis. In the stepwise multivariate modeling, we identified the optimal model with the lowest AIC of 72.53. The risk score was an important independent predictor . Other variables, including age, Heliotrope, and fever, were also retained in the optimal model Figure 2The prediction tool showed good discrimination in the discovery cohort, with an AUC of 0.915  at admission were associated with acute epithelial cell damage and excessive inflammation. They might participate in disease progression, leading to death. In addition, CYFRA21-1 is a specific marker for lung cancer and is mainly expressed in alveolar and bronchial epithelial cells , 33. DobIn the current study, the frequency of anti-Ro52 antibodies in anti-MDA5 DM-ILD patients was 74.7%. Anti-Ro52 antibodies, the most common myositis-associated autoantibodies (MAAs), often co-occur with anti-MDA5 antibodies. Anti-Ro52 antibodies coexisting with anti-MDA5 antibodies could more frequently cause disease progression, leading to unfavorable outcomes , 35. Our+ T-cell counts in peripheral blood is higher in anti-MDA5 DM-RPILD patients than in non-RPILD patients  had a tendency to benefit from the administration of two or more immunosuppressive drugs, while low-risk patients showed not benefit. Nevertheless, the finding is a hypothesized one and could be affected by potential confounding factors. A large prospective cohort is needed to examine the finding and to draw more reliable conclusions.Our study has several limitations. First, our ability to perform serial analysis of clinical parameters was limited because of the lack of data, such as lung function, which was understandable given the severity of anti-MDA5 DM-ILD. Therefore, we applied the oxygenation index as a surrogate indicator. Though not perfect, it may partially reflect the patient’s lung function. Second, this was a retrospective, single-institution study. All patients were Asians. Further multicenter external validation, especially in other racial populations, should be performed to verify our prediction model’s predictive ability and generalizability in future studies. Third, all patients in the study were Asians, the algorithm is only applicable at the moment to Asian populations. Lastly, artificial intelligence (AI) represents computer processes that allow performing complex data analyses with the least human intervention , 16. TheIn conclusion, based on baseline clinical and laboratory indicators, we developed and validated a predictive tool with good predictive ability in Asian patients with anti-MDA5 DM-ILD. It accurately estimates individual mortality risk, which helps inform clinical decision-making early.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 Ethics Committee of the Nanjing Drum Tower Hospital. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.YX and XG had full access to all the data in the study and took responsibility for the data’s integrity and the data analysis’s accuracy. XG, WL, and YY contributed equally to this study. Concept and design: YX, MH, and XG. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: XG, WaL, and YY. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: All authors. Obtained funding: YX, MH and XG. Administrative, technical, or material support: YX and MH. Supervision: YX, XG, MiC. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China (Grant No. 82070064), the Special Fund for Clinical Research from the Affiliated Drum Tower Hospital of Nanjing University Medical School (2021-LCYJ-PY-05), and the Special Fund for Clinical Research (Single Disease Database) from the Affiliated Drum Tower Hospital of Nanjing University Medical School (2021-LCYJ-DBZ-06).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.


Body image concerns are prevalent among young adults, who may be vulnerable to developing body image concerns because of particular risk factors associated with this life period. With technological advancements, digital mobile health  apps are cost-effective and scalable interventions. Thus, mHealth apps can be explored as a form of prevention effort to alleviate body image concerns in young adults.In this randomized controlled trial, we examined the effectiveness of a self-guided mHealth app in improving body image and self-compassion in a sample of university students.Participants (N=310) were randomized to a 9-day self-guided body image and self-compassion mHealth app (n=149) and to an active waitlist control group (n=161), where they completed a similarly structured 9-day program on cooperation. Both programs consisted of content learning and activities such as quizzes, with the number and length of activities matched for both programs. Measures were obtained at baseline, upon completion of the programs (after the intervention), and at 4-week follow-up.P<.001) and improvements in body appreciation (P<.001) and self-compassion (P=.001) compared with the active waitlist control group after the intervention. Similarly, for male participants after the intervention, a significant reduction was found in the intervention group in body dissatisfaction (P<.001) after the intervention as well as improvements in body appreciation (P=.02) and self-compassion (P=.047). The effects were maintained at 4-week follow-up for female participants on body dissatisfaction (P<.001), body appreciation (P<.001), and self-compassion (P=.02) but not for male participants. On body image risk factors, significant reductions were found for female participants after the intervention for thin-ideal internalization (P<.001), peer pressure (P=.002), and media pressure (P<.001) after the intervention, while the effects were only maintained for thin-ideal internalization (P=.008) and media pressure (P=.01) at 4-week follow-up, compared with the active waitlist control group. As for male participants, no intervention effects were found both after the intervention and at follow-up for all body image risk factors of muscularity internalization, peer pressure, and media pressure. Both apps were acceptable and participants engaged equally across the intervention and active waitlist control groups, as indicated on a measure of app engagement (P=.76).The intervention group for female participants reported significant reduction in body dissatisfaction (This study provides preliminary evidence for a self-guided mHealth app in improving body image concerns and self-compassion in young adult university students. Future studies should include longer follow-ups, and examine its effects with the wider populations of young adults.ClinicalTrials.gov NCT04977973; https://clinicaltrials.gov/ct2/show/NCT04977973 Body image problems are highly prevalent among adolescents and young adults and have been frequently implicated in the development and maintenance of problematic eating behaviors ,2 and boIndividuals tend to engage in upward appearance comparison, whereby they compare their appearance to others whom they perceive to be more attractive . ConsequExposure to media contributes to appearance-ideal internalization and appearance comparison. Media and social networking platforms are filled with ideal-looking images of the self and others which are often skewed representations of reality ,16. ThroAmong peers, appearance-focused comparison and appearance-related conversations and activities may also increase body dissatisfaction as they increase individuals’ awareness of their bodies, strengthen the internalization of appearance ideals, and negatively alter personal attitudes and beliefs in relation to beauty standards .Apart from sociocultural influences, ruminative cognitive styles have been associated with greater body dissatisfaction . RuminatPositive body image is characterized as being accepting, appreciating, and respecting of our bodies through attending to the body’s needs, protecting ourselves against unrealistic body ideals, having broader conceptualizations of beauty, and filtering information in a body-protective manner ,23. In qBody Project adopted dissonance-based approaches in a group setting by having participants voluntarily critique and take a counterattitudinal stance against the thin-ideal in verbal, written, and behavioral activities . Da. Da56]. The effectiveness of a self-guided mobile phone application in improving the way we see ourselves and our bodies) to reduce the demand characteristics of the participants.Participants first read the Participation Information Sheet on Qualtrics. After providing informed consent, participants completed measures on body image, body image risk factors, and self-compassion to obtain baseline ratings. Thereafter, participants were randomized to 1 of 2 conditions, intervention or active waitlist control, using simple randomization procedures. In this study, blinding of participants was marginally feasible as the content of the intervention programs that the participants engaged in were different in nature. However, participants were not outwardly informed of the real function of each intervention condition or of the real nature of the study being to evaluate the effectiveness of the body image program. The title of the study made known to participants was kept general .Participants filled out the same questionnaires upon program completion (postintervention measure) and after 4 weeks (follow-up measure). The feedback questionnaire was administered only after the intervention.After the 6-week data collection period, participants were debriefed about the purpose and real intent of the study. Participants in the active waitlist control group were given access to the body image program.Body Image Ideals Questionnaire (BIQ ) is a 22The Body Appreciation Scale-2  is a 10-The Sociocultural Attitudes Toward Appearance Questionnaire-4 Revised  measuresSelf-Compassion Scale-Short Form  is a 12-App Engagement Scale  is a 7-it tests were also conducted to determine if participants who withdrew or could not continue because of technical difficulties differed significantly from those who remained in the study on any demographic and outcome measures. This informed of attrition-related bias, if any. Finally, missing scores on the App Engagement Scale (AES) were substituted using mean substitution [Statistical analyses were conducted using SPSS . As previous research has found that female and male participants’ body image are dissimilar and that they respond differently to intervention programs ,63, analtitution .P<.05. Partial eta squared (pη2) was the effect size reported for ANCOVA, while eta squared (η2) was the effect size reported for 2-tailed t tests and ANOVA.An analysis of covariance (ANCOVA) examined if changes in outcome measures after intervention and at follow-up were significantly different in the intervention group compared with the active waitlist control group. ANCOVA is the recommended analysis for the inferential test of intervention effects . By contA total of 313 participants completed questionnaires at baseline, 296 (94.57%) participants completed questionnaires after the intervention, and 291 (92.97%) participants completed questionnaires at follow-up .P=.03). AES rated after the intervention did not differ significantly between female and male participants (P=.51) and between the intervention and active waitlist control groups (P=.76).The intervention and active waitlist control groups did not differ significantly on demographic variables and most outcome measures at baseline , and 4. t tests did not reveal any attrition-related biases across demographic and outcome variables (P>.10).Intent-to-treat analyses were conducted for participants who were lost to follow-up by carrying forward their last reported scores. Missing scores for AES were substituted with the mean score. Independent 2-tailed P>.20), except BIQ for male participants. The assumption of homogeneity of regression slopes were violated in 2 variables for female participants . For these variables, 1-way ANOVA was conducted using differences in scores between baseline and after the intervention and baseline and follow-up, respectively.Most outcome variables met the assumption tests for ANCOVA. The homogeneity of variance assumption was violated for a small number of outcome measures. However, because of the robustness of ANCOVA when sample sizes in each group are relatively equal , analysiOn body image measures, the intervention group reported significantly lower body dissatisfaction, and significantly higher body appreciation, after the intervention and at follow-up, compared with the active waitlist control group. The effect sizes were between moderate to large at both postintervention and follow-up. On thin-ideal internalization, the intervention group reported significantly lower internalization of thin-ideal scores after the intervention and at follow-up, compared with the active waitlist control group, with small to moderate effect sizes after the intervention and at follow-up. Significant score reductions were found on measures of peer and media pressure after the intervention in the intervention group, compared with the active waitlist control group, with small to moderate effect sizes. At follow-up, a significant difference was only found for reduction in media pressure, and no significant difference was found for peer pressure. Finally, significant differences were found for the self-compassion measure after the intervention and at follow-up, compared with the active waitlist control group .Male participants in the intervention group reported significantly lower scores on body dissatisfaction after the intervention, compared with the active waitlist control group, with a large effect size. Male participants in the intervention group also reported significantly higher scores for body appreciation and self-compassion after the intervention, compared with the active waitlist control group, with effect sizes ranging from small to moderate. No intervention effects were found after the intervention for muscularity internalization, peer pressure, and media pressure, and at follow-up for all measures .This RCT evaluated the effectiveness of a self-guided mHealth app in improving body image and self-compassion in a sample of Asian university students. Our study extended the findings of previous studies by showing that cognitive dissonance and self-compassion approaches delivered on a mobile-based platform can be beneficial in improving body image and self-compassion in young adults.eBody Project after the intervention [Our hypotheses for female participants were largely supported. Except for peer pressure whereby intervention effects were not found at follow-up, the intervention group reported significant improvements on body image, body image risk factors, and self-compassion at both postintervention and follow-up, compared with the active waitlist control group. Consistent with past research on longer web-based or face-to-face interventions, our findings showed that a 9-day mobile-based program using cognitive dissonance and self-compassion approaches can reduce body dissatisfaction and its risk factors, improve body appreciation, and improve self-compassion after the intervention and at follow-up in female adults ,44,51,69rvention . Furtherrvention  by demonrvention , the effBody 4 All and Body Project M, which found significant improvements in male participants on body satisfaction, body appreciation, dissatisfaction with fat and muscularity, appearance comparison, and internalization of cultural appearance ideals, with some effects sustained at their respective follow-ups [P=.79 and P=.89), peer pressure (P=.10 and P=.32), and media pressure (P=.68 and P=.44) did not reach statistical significance after intervention and at follow-up, there was a trend observed toward male participants in the intervention group reporting lower scores of muscularity internalization and media and peer pressure after the intervention.Our hypotheses for male participants were partially supported. Unlike findings from llow-ups ,38, our Overall, our findings provide preliminary support for the use of cognitive dissonance and self-compassion approaches on an mHealth app to reduce body image concerns and improve self-compassion in students. On the basis of the cognitive dissonance theory and the dual pathway model ,70, guidBodiMojo’s 6-week mobile-based intervention, our 9-day mobile-based intervention revealed comparable small to moderate effect sizes in self-compassion after the intervention for female and male participants. Compared with BodiMojo and the face-to-face programs of the Body Project, our study found similar or larger effect sizes for body image in both sexes after the intervention [Consistent with rvention ,45,71. Trvention , brieferAlthough significant improvements in self-compassion were found for male participants after the intervention, the effect was weaker, and not significant at follow-up. As self-compassion has been identified as a crucial factor in reducing body dissatisfaction and enhancing body appreciation in female and male participants ,73,74, tSex differences in self-compassion may explain the lack of follow-up effects for self-compassion in male participants. A meta-analysis conducted by Yarnell et al  suggesteSeveral reasons are conceivable why peer pressure did not reveal differential effects for male participants and for female participants at follow-up. During this developmental phase as a young adult, interpersonal relationships are crucial for female and male participants ,80. FemaThe lack of significant reduction in the internalization of muscularity after the intervention and at follow-up may be accounted for by at least 2 possible reasons. First, adaptations made to our mixed-sex body image program to incorporate male body image concerns may be insufficient in addressing muscular-ideal internalization in a targeted manner. For example, the terminology being changed to “ideal appearances” and insufficient examples for male participants may have led to an inadequate understanding of concerns related to muscular-ideal internalization, thus watering down the intervention effects for male participants. Second, male participants may be less engaged in the body image program than female participants, because of the lack of masculine points of reference . AlthougFinally, the lack of group differences on media pressure for male participants was unexpected, as media literacy was previously found to be effective in reducing pressures from media influences . A possiFirst, some causal conclusions can be drawn . The useThis study has some limitations. First, student participants may limit the generalizability of findings, as university students and the public may differ in factors such as level of education . Hence, The sample size for male participants in our study was small despite additional recruitment efforts and thus was likely underpowered. Moreover, in view of sex differences in body image, more research is required to better understand ways to increase the effectiveness of mobile-based body image programs for male participants in a mixed-sex format and address muscularity concerns. To capture male participants’ body image concerns more accurately, male-specific measures such as Male Body Attitudes Scale  can be uFinally, in light of increasing studies which found self-compassion to mediate the effects of body image interventions, future studies can examine self-compassion as a mechanism of change. It would also be beneficial to obtain qualitative feedback from participants on elements of the body image program, such as their perception of the tone or number of intervention messages, to evaluate the effectiveness of the program.Overall, this RCT provides preliminary but encouraging support for the effectiveness of a self-guided mHealth body image app using cognitive dissonance and self-compassion approaches for university students. Mobile-based well-being programs are cost-effective and accessible and can thus be widely disseminated to benefit the masses. Future research should seek to further enhance the program’s effectiveness with the wider young adult population.


White matter changes in individuals at ultra-high risk for psychosis (UHR) may be involved in the transition to psychosis. Sleep-wake disturbances commonly precede the first psychotic episode and predict development of psychosis. We examined associations between white matter microstructure and sleep-wake disturbances in UHR individuals compared to healthy controls (HC), as well as explored the confounding effect of medication, substance use, and level of psychopathology.Sixty-four UHR individuals and 35 HC underwent clinical interviews and diffusion weighted imaging. Group differences on global and callosal mean fractional anisotropy (FA) was tested using general linear modeling. Sleep-wake disturbances were evaluated using the subjective measures disturbed sleep index (DSI) and disturbed awakening index (AWI) from the Karolinska Sleep Questionnaire, supported by objective sleep measures from one-night actigraphy. The primary analyses comprised partial correlation analyses between global FA/callosal FA and sleep-wake measures. Secondary analyses investigated multivariate patterns of covariance between measures of sleep-wake disturbances and FA in 48 white matter regions of interest using partial least square correlations.F = 14.56, p < 0.001) and lower callosal FA  compared to HC. Subjective sleep-wake disturbances were significantly higher among the UHR individuals . Lower callosal FA was correlated with increased wake after sleep onset  and increased sleep fragmentation index  in UHR individuals. Multivariate analyses identified a pattern of covariance in regional FA which were associated with DSI and AWI in UHR individuals (p = 0.028), but not in HC. Substance use, sleep medication and antipsychotic medication did not significantly confound these associations. The association with objective sleep-wake measures was sustained when controlling for level of depressive and UHR symptoms, but symptom level confounded the covariation between FA and subjective sleep-wake measures in the multivariate analyses.Ultra-high risk for psychosis individuals displayed lower global FA (Compromised callosal microstructure in UHR individuals was related to objectively observed disruptions in sleep-wake functioning. Lower FA in ventrally located regions was associated with subjectively measured sleep-wake disturbances and was partly explained by psychopathology. These findings call for further investigation of sleep disturbances as a potential treatment target. The ultra-high risk state of psychosis (UHR) designates a putative prodromal phase of psychosis  and is dThe influence of sleep-wake disturbances on the development of psychopathology has increasingly been acknowledged. Sleep-wake disturbances can be evaluated using self-report questionnaires regarding a specific period , but they are vulnerable to recall-bias . ObjectiCerebral white matter (WM) changes have been shown to be implicated in the pathophysiology of psychotic disorders  includinPsychosis has been conceptualized as a global brain disorder of dysconnectivity . Global Global approaches may conceal information derived from informed hypotheses on associations between specific symptoms and predefined WM regions of interest (ROIs). The main commissural tract in the brain is corpus callosum (CC), which is critical for the interhemispheric information transfer and coordination of functional activity . CC has Substance use disorder is significantly more common in UHR individuals  and patiA study from our group showed that antipsychotic medication affected WM microstructure in frontal fasciculi in antipsychotic naïve patients with first episode psychosis . AdditioIn this study, we examine the association between global and regional WM microstructure and sleep-wake disturbances in UHR individuals compared to HC. We hypothesize, that lower mean global FA as well as lower FA in CC are associated with more severe sleep-wake disturbances. Secondly, we investigate potential covariation between FA in all ROIs and sleep-wake disturbances. Finally, we exploratively investigate if these potential associations may be explained by substance use, medication (antipsychotics and sleep medicine), and psychopathology (depressive symptoms and UHR symptoms).Cross-sectional data were derived from The FOCUS-trial . The maiData for the current study was collected at baseline from help-seeking individuals meeting at least one of the three UHR-criteria according to the Comprehensive Assessment of At-Risk Mental States (CAARMS) : attenuaAxis I and selected Axis II diagnoses  were examined using the Structured Clinical Interview for DSM-IV (SCID) . To examAll clinical assessments were conducted by experienced psychologists and medical doctors with comprehensive training in the assessment instruments. Inter-rater reliability was assessed in the main trial using intra-class correlations for clinical outcomes, revealing excellent inter-rater reliability .The subjectively experienced sleep quality was assessed with a modified version of the Karolinska Sleep Questionnaire  both durThe objective sleep-wake measures were obtained using an actigraph. An actiwatch  was worn on the non-dominant wrist for 24 h. Data were collected with a sampling rate of 30 Hz and 1-min epochs were used to score wake and sleep pattern. Data were analyzed with ActiGraph Sleep Analysis . The actigraph measures applied in this study were: total sleep time (TST), wake after sleep onset (WASO) (minutes spend awake after sleep had occurred), sleep efficiency (SE) , and sleep fragmentation index (SFI) . The actigraph was accompanied by a sleep diary reporting bedtime, awakening time, and medicine intake.The subjective sleep measures are regarded as primary in the analyses as they cover the last four weeks and must be considered more representative than one-night actigraphy. In our analyses we include both the subjective and the objective sleep-wake measures and consider whether the objective measures support the findings of the subjective measures.b = 1.000 s/mm2) directions and one non-diffusion weighted (b = 0 s/mm2) in opposite phase encoding directions were acquired, enabling correction for susceptibility distortions  version 25.0, . Descriptive variables were reported as percent, means, and standard deviations. Chi-square tests and general linear modelling (GLM) were used to compare UHR individuals to HC on descriptive variables. Effect of group on mean global FA and callosal FA were tested using GLM with age, sex, relative and absolute motion in scanner as covariates.p < 0.05.Partial correlation analyses were performed in SPSS to test covariation between mean FA in the CC and the subjective and objective measures of sleep-wake disturbances, including age, sex, relative and absolute motion in scanner as covariates. Primary analyses tested the effect of group with ANOVA . All tests were corrected for multiple comparisons using the Benjamin–Hochberg procedure with an FDR of Post-hoc, we tested the potential effect of substance use, medication, and psychopathology by including each substance as well as a composite score for substance use, medication (antipsychotics and sleep medicine yes/no), and measure of psychopathology [depressive (MADRS score) or UHR-symptoms (CAARMS composite score)] as covariates, along with age, sex, relative and absolute motion in scanner in the partial correlation model. Post-hoc tests were uncorrected for multiplicity.Group differences on the 48 ROIs were tested with multivariate GLM using the MATLAB software (version 2021a) including age, sex, relative and absolute motion as covariates.p-value based on non-rotated sampling distribution of singular values  analysis  was perfr values . For ther values . LVs witreported . The relreported . Detailsn = 45). Finally, post-hoc analyses explored a potential mediation effects of levels of psychopathology on significant associations between regional FA and sleep-wake measures using Process for SPSS by In planned exploratory analyses, we entered substance use, medication (antipsychotics and sleep medication), and psychopathology  as covariates in the multivariate PLS-C. In addition, we performed sensitivity analyses on a reduced sample of antipsychotic free UHR individuals , and lower FA in CC  when compared to HC . The significant pattern indicated that 22/48 ROIs contributed reliably with lower FA in UHR individuals (p = 0.001) bilaterally: middle cerebellar peduncle; genu, body, and splenium of CC; posterior limb of internal capsule; superior corona radiata; posterior thalamic radiation; external capsule; and superior longitudinal fasciculus. Left hemisphere: retrolenticular part of internal capsule; posterior corona radiata; sagittal stratum; cingulum; and tapetum. Right hemisphere: cerebral peduncle; anterior corona radiata; and cingulum hippocampus  and across the last four weeks . The AWI was significantly higher  in the UHR-group, both the preceding night  and across the last four weeks .We found a significant difference between groups on the subjective sleep-wake measures . The UHRF = 12.83, p = 0.001) and TST  and significantly lower WASO  and SFI   .Among the UHR individuals, two had a history and one had a current diagnosis of substance use disorder. Six UHR individuals had an earlier and none had a current diagnosis of dependence, which was in accordance with the eligibility criteria.2 18.07, p = 0.001) compared to HC, and a significantly lower consumption of alcohol . Although not significant, we noticed that three UHR individuals had a daily or almost daily use of cannabis, compared to no HC. Likewise, no HC had ever used simulants , where three UHR individuals had tried it, and one had a monthly use  diagnosed with an affective disorder, n = 37 (57.8%) with an anxiety disorder, and n = 21 (32.4%) diagnosed with a personality disorder  reported current use of antipsychotic medication in low dosages. Of other medications which may affect sleep, one UHR individual reported current treatment of a benzodiazepine, 6 melatonin, and 15 reported current use of antidepressants (Thirty-eight (59.4%) of the sample were antipsychotic-naïve and ressants .p = 0.011, r = −0.337) as well as with SFI  in UHR individuals , SE , WASO , and SFI  remained significant after controlling for multiplicity. However, in the within-group analyses we could not confirm the significant correlation between callosal FA, AWI and SE among the UHR individuals, and no significant correlations between global or callosal mean FA were identified in HC. The partial correlation analyses were also performed on the reduced sample of antipsychotic free UHR individuals (n = 45), which showed identical results . Post-hoc sensitivity analyses including all HC and a subsample of antipsychotic free UHR individuals showed a strong association (omnibus test p = 0.031) between a pattern of disturbed sleep-wake measures  and widespread lower FA in 24/48 WM regions explaining 69.89% of the covariance (LV1 p = 0.032) (see p = 0.028) but not in HC (omnibus test p = 0.290). In UHR individuals, one significant latent variable (LV) was identified: LV3 explained 15% of the covariance (p = 0.013). LV3 comprised a pattern where higher FA in fornix, along with lower FA in left and right corticospinal tract, left cerebral peduncle, left medial lemniscus, and left cingulum (hippocampus) contributed reliably. This pattern of regional FA was associated with a pattern of more severely disturbed sleep (DSI) and awakening (AWI) contributing reliably , AWI , SE , WASO , and SFI  (uncorrected). No other substances were correlated to sleep-wake measures  and AWI to UHR-symptoms  , sleep medication , UHR-symptoms , and depressive symptoms  as covariates  . When povariates .post-hoc sensitivity analyses on a reduced sample of antipsychotic free UHR individuals we found a borderline significant association between a pattern of disturbed sleep-wake measures  and lower FA in 7/48 WM regions explaining 11.38% of the covariance  .In the multivariate PLS-C, we found no effect of entering substance use, antipsychotic medication, and sleep medication as covariates on the overall result . HoweverTo the best of our knowledge, this is the first study in individuals at UHR investigating associations between WM microstructure and subjective and objective sleep-wake measures and how common clinical confounders may affect this association.As expected, UHR individuals presented with lower FA compared to HC at a global as well as at a regional level in CC. This result was supported in the multivariate test including all 48 ROIs. The finding is in accordance with the majority of studies in UHR individuals reporting subtle and widespread WM alterations . We idenAs hypothesized, lower FA in CC was associated with poorer outcomes in objective sleep-wake measures in UHR individuals, although no group difference in the actigraphy outcomes were observed. Lower FA was linked to more time spend awake after sleep had occurred and restlessness during the sleep period, indicating more disrupted sleep in UHR individuals, but not in HC. Nonetheless, when testing all participants, the identical associations remained significant after correction for multiplicity, which may reflect a problem with power due to the smaller sample of HCs. The indication that associations between regional FA and disturbed sleep-wake measures are more pronounced in the patient group than in HC was corroborated by the multivariate PLS-C within-group analyses on all ROIs. Interestingly, this perspective has become increasingly acknowledged, as several studies have concluded that contrary to HC, behavioral measures appear more vigorously associated with and dependent on the structural characteristics of WM in UHR individuals and patients with first-episode schizophrenia . A similIn the full sample, the subjective sleep-wake measure AWI was significantly correlated with FA in CC but contrary to our expectations we did not find any firm associations between DSI and FA in CC. However, the overall association between sleep-wake disturbances and lower FA in widespread WM regions was corroborated in the sensitivity PLS-C analyses including both HCs and antipsychotic free UHR individuals . Hence, Although it is difficult to compare results across diverse patient populations, The multivariate correlation test revealed a link between the Karolinska sleep measures of DSI and AWI contributing reliably as indicative of sleep-wake disturbances, associated with a pattern of lower FA in 5 ROIs, as well as higher FA in fornix contributing reliably. The ROIs contributing reliably appear mainly to be located ventrally, which is in accordance with previous research locating sleep-wake regulation to sub-thalamic circuits in the brainstem . We specInterestingly, FA in CC did not contribute reliably, which indicates that the subjective sleep-wake disturbances may predominantly be linked to other WM networks, compared to the actigraphy measures. Our result may reflect the notion that different aspects of sleep-wake regulation potentially is linked to specialized and differentiated neuronal circuits and corresponding structural networks . Sleep-wThe directionality of FA may depend on the patient sample or region of interest . FA is aOur results indicate, that although use of nicotine may affect sleep measures, no substance use affected the association between WM and sleep in CC. Previous studies have reported mixed results, a metanalysis found that substance use disorder  was associated with FA in CC, but for cannabis and nicotine the results were mixed . Howeverpost hoc sensitivity PLS-C analyses on antipsychotic-free UHR individuals indicated a potential effect of antipsychotic medication on the association between sleep-wake measures and FA. The pattern of sleep-wake disturbances in antipsychotic free UHR individuals indicated that mainly reduced sleep-time (lower TST) and disturbed sleep (higher DSI) contributed reliably to the covariation with lower regional FA , the model did not fulfill requirements for establishing a mediation effect, although all other requirements were met and a significant mediation effect appeared to be present, showing that level of depressive symptoms mediated the association between FA in fornix and DSI. We believe this trend level association may be due to reduced power, hence reflecting a Type 2 error. A recent study demonstrated how diffusion metrics within the CC partially mediated the associations between poor sleep quality/high stress and depressive symptomatology  as well as the level of UHR-symptoms (CAARMS) appeared to confound the association between regional FA and AWI as well as DSI suggesting that the subjective sleep-wake measures may be more susceptible for level of psychopathology. Moreover, the group difference between UHR individuals and HCs on AWI and DSI were highly significant. As a result of this finding, we  AWI/DSI . As one matology . To confPLS-C can be difficult to interpret due to the complexity of linking multivariate data patterns. Furthermore, we did not identify any clear interaction effect. However, repeating the within-group analyses from the primary analyses appeared to confirm aspects of our univariate findings and contribute with additional and more specific information on the associations between WM ROIs and sleep-wake disturbances.post-hoc. Furthermore, the matching between HC and UHR individuals in the main trial was not complete in this subsample. Further, we would optimally have cross-validated our results in an independent sample. As this was not possible, the results must be interpreted cautiously and should be evaluated as hypothesis generating with a need for replication in a larger sample. Nonetheless, we trust the consistent associations across multiple tests to represent a valuable contribution indicative of specific associations between regional WM and sleep in a group of vulnerable patients.A general limitation to the study is the fact that the analyses were secondary to an RCT and this research question was formulated The actigraphy measures were only recorded for a 24-h period, which makes it susceptible to individual and spurious variations. Actigraphy tends to overestimate sleep length and efficiency compared to polysomnography, and overestimation is more pronounced in individuals with sleep-wake disturbances than in healthy individuals . To miniStrengths of this study comprise the consistent use of relevant covariates along with a meticulous examination of potential confounders. Furthermore, we believe this is the first study to investigate links between WM and sleep-wake disturbances in UHR individuals. Although our findings call for replication in larger samples, our results may contribute with preliminary hypotheses regarding neurobiological underpinnings of a modifiable risk factor for developing psychosis. Future perspectives of examining the relationship between brain structure/functioning and sleep parameters might be suggested to include AI techniques. With this approach multiple sources of information from advanced MR-scans, biological measures of sleep continuity/architecture and subjective measures of sleep quality could be modeled for purposes of prediction and eventually choice of treatment.UHR individuals presented with lower global and callosal mean FA compared to HC. In UHR individuals, compromised callosal microstructure was associated with disturbed objectively measured sleep-wake functioning which was not confounded by substance use or medication. Subjectively measured sleep-wake disturbances were associated with a pattern of lower FA in ventrally located WM regions in UHR individuals. This association was not confounded by substance use or medication, but level of depressive and UHR symptoms partly explained it, pointing to a complex interaction between biological factors and psychopathology as determinants of the sleep-wake pattern. These findings suggest sleep disturbances as a potential treatment target, but future longitudinal studies are needed to address the direction of causality.The original contributions presented in this study are included in the article/The studies involving human participants were reviewed and approved by the Committee on Health Research Ethics of the Capital Region in Denmark (H-6-2013-015). The patients/participants provided their written informed consent to participate in this study.JRs: analyzing data and writing up results. DN: designing study, preparing dataset, extracting/analyzing actigraphy data, and reviewing/writing. LG: study coordination, collecting data, and reviewing/writing. MJ: processing actigraphy data and reviewing/writing. AG: processing actigraphy data and reviewing/writing. JRg: processing MRI data and reviewing/writing. PJ: reviewing/writing. BG MN, and BE: financing and reviewing/writing. LB: designing study, financing and supervising JRs, and reviewing/writing. TK: conceptualizing and designing study, analyzing data, supervising JRs, and writing up results. All authors contributed to the article and approved the submitted version.


Low-carbon agriculture is essential for protecting the global climate and sustainable agricultural economics. Since China is a predominantly agricultural country, the adoption of low-carbon agricultural technologies by local farmers is crucial. The past literature on low-carbon technologies has highlighted the influence of demographic, economic, and environmental factors, while the psychological factors have been underexplored. A questionnaire-based approach was used to assess the psychological process underlying the adoption of low-carbon agricultural technologies by 1,114 Chinese rice farmers in this paper, and structural equation modeling (SEM) was empirically employed to test our theoretical model. The results indicated that farmers’ low-carbon production attitude and behavioral efficiency perception directly and positively affected the adoption of low-carbon agricultural technologies and indirectly affected it via low-carbon production intention. Besides, production implementation cost and socio-environmental factor could moderate the direct effects of low-carbon production attitude, behavioral efficiency perception, and low-carbon production intention on farmers’ adoption of low-carbon agricultural technologies. In this respect, socio-environmental factor yielded more significant moderating effects. Additionally, this research provides policy implications for promoting low-carbon agricultural technologies in developing countries and regions. A low-carbon economy represents a novel approach implemented by many countries for economic development and protection against global warming . As a deExtant research on low-carbon production generally includes three aspects. The first one is the evaluation of low-carbon agricultural production. For example, In some developing countries, low-carbon agricultural materials  and technologies (such as intermittent irrigation and straw returning) with well-documented emission reduction effects have been gradually promoted in major agricultural production areas . HoweverThe adoption of low-carbon technologies by rice farmers refers to the use of low-carbon agricultural materials and management measures to reduce agricultural greenhouse gas emissions and improve the agricultural ecological environment . In thisAccording to the theory of planned behavior (TPB), an attitude is a positive or negative evaluation of a given behavior , and a pAccordingly, rice farmers’ cognition and evaluation of climate change and low-carbon agriculture and their environmental awareness of soil, water quality, atmosphere, and other surrounding environments impact their intention and adoption of low-carbon technologies. Furthermore, there may be a close relationship between rice farmers’ attitude toward adopting low-carbon technologies and the perceived efficiency of adoption behavior. Consequently, rice farmers’ low-carbon production attitude  significantly affects their behavioral efficiency perception , low-carbon production intention, and adoption of low-carbon technologies. The following hypotheses were proposed:H1a: Low-carbon cognition of rice farmers has a positive effect on their value perception.H1b: Low-carbon cognition of rice farmers has a positive effect on their self-efficacy.H1c: Low-carbon cognition of rice farmers has a positive effect on their low-carbon production intention.H1d: Low-carbon cognition of rice farmers has a positive effect on their adoption of low-carbon technologies.H2a: Environmental awareness of rice farmers has a positive effect on their value perception.H2b: Environmental awareness of rice farmers has a positive effect on their self-efficacy.H2c: Environmental awareness of rice farmers has a positive effect on their low-carbon production intention.H2d: Environmental awareness of rice farmers has a positive effect on their adoption of low-carbon technologies.According to the rational behavior theory and TPB, individual behavior efficiency perception or perceived behavior control can predict behavioral intention and implementation . MoreoveOn these grounds, rice farmers’ value perception of low-carbon agricultural technologies , as well as self-efficacy  may positively affect their low-carbon production intention and adoption of low-carbon technologies . ConsequH3a: Value perception of rice farmers has a positive effect on their self-efficacy.H3b: Value perception of rice farmers has a positive effect on their low-carbon production intention.H3c: Value perception of rice farmers has a positive effect on their adoption of low-carbon technologies.H4a: Self-efficacy of rice farmers has a positive effect on their low-carbon production intention.H4b: Self-efficacy of rice farmers has a positive effect on their adoption of low-carbon technologies.Based on the TPB, individual behavioral intention positively affects the occurrence of behavior . A positH5: Low-carbon production intention of rice farmers may significantly affect their adoption of low-carbon technologies.According to the above analysis, farmers’ attitude, behavioral efficiency perception, and intention will influence their adoption of low-carbon technologies. However, some studies have emphasized that farmers’ behavioral intention may not translate into actual behavior under the influence of some moderating variables . This phFirst, production implementation cost indicates the cost of adopting low-carbon agricultural technologies, including traditional farming habit and risk tolerance. Low-carbon agricultural materials and production technologies may increase investment and risk, leading to enhanced production costs and discouraging farmers from adopting low-carbon production . MeanwhiSecond, it is widely acknowledged that farmers live in social groups, and their behavior is affected by the territorial socio-environmental factors. In this study, emphasis was placed on the cultural background and social environment of rice farmers, including the cultural background of small-scale farmers, government-led promotion, and group effect. Some researchers found that external environmental factors can change farmers’ behavior . For exaH6a: Production implementation cost moderates the effect of rice farmers’ low-carbon production attitude on their adoption of low-carbon technologies.H6b: Production implementation cost moderates the effect of rice farmers’ behavioral efficiency perception on their adoption of low-carbon technologies.H6c: Production implementation cost moderates the effect of rice farmers’ low-carbon production intention on their adoption of low-carbon technologies.H7a: Socio-environmental factor moderates the effect of rice farmers’ low-carbon production attitude on their adoption of low-carbon technologies.H7b: Socio-environmental factor moderates the effect of rice farmers’ behavioral efficiency perception on their adoption of low-carbon technologies.H7c: Socio-environmental factor moderates the effect of rice farmers’ low-carbon production intention on their adoption of low-carbon technologies.Overall, from the perspective of the psychological mechanism of information processing, rice farmers’ adoption of low-carbon technologies results from a mindset change where the perceived value of such behavior is integrated into their mindset, which can be seen as a mindsponge-based information process . Indeed,Consequently, the theoretical framework of this research was established .Hubei province, well-established as the top rice-producing region with the highest output in China, was used as the representative area for investigating Chinese rice farmers’ adoption of low-carbon technologies. We conducted a questionnaire survey based on the theoretical model see  in threeAs mentioned earlier, this research investigated rice farmers’ low-carbon production attitude in terms of low-carbon cognition and environmental awareness. Regarding rice farmers’ low-carbon cognition, this study was based on the scales of To conform to the characteristics of Chinese rural culture, this paper assessed the production implementation cost from two aspects: traditional farming habit and risk tolerance. The traditional farming habit investigated the costs of transformation, including deep plowing habit and extensive production mode. Moreover, the risk tolerance included rice farmers’ judgment on climate change risk and their risk preference for adopting low-carbon technologies. Furthermore, many small-scale rice farmers in China were managed by village committees. Therefore, the social environment factor was measured from three aspects: cultural background of small farmer, government-led promotion, and influence of group effect. Among them, the cultural background of smallholders included self-discipline consciousness and conservative mentality. Besides, the government-led promotion contained subsidy promotion and punishment regulation. Finally, the influence of group effect was associated with conformity psychology and convergence behavior.After completing the draft of the questionnaire, the researchers revised it twice. First, the experts related to agronomy evaluated the rationality of the questionnaire, and the researchers adjusted the content according to the evaluation results. Next, a preliminary survey was conducted on representative rice farmers and village cadres, and the researchers modified the questionnaire measurement items according to the survey results. The final measurement items related to rice farmers’ adoption of low-carbon technologies are shown in Structural equation modeling (SEM) was constructed to empirically test the theoretical framework of farmers’ adoption of low-carbon technologies. Besides, the mediating effect of low-carbon production intention was verified by causal steps approach, and the moderating effects of production implementation cost and socio-environmental factor were tested by hierarchical regression. The specific methods were described as follows:This study employed SEM to explore the latent relationships between rice farmers’ adoption behavior and influencing factors see . SEM is X and Λy represent the correlation coefficient matrix between exogenous latent variables, endogenous latent variables, and their corresponding observational variables, respectively; δ and ε are the measurement error vectors of the exogenous and endogenous observational variables; B represents the matrix of structural coefficients among endogenous latent variables, reflecting the mutual influence between endogenous latent variables ; Γ is the structure coefficient matrix between exogenous and endogenous latent variables, indicating the causal effect of exogenous latent variables X  on endogenous latent variables Y (low-carbon production intention and adoption of low-carbon technologies); and ζ is the random error vector of the structural equation.where X represents the exogenous latent variable vector, including rice farmers’ low-carbon cognition, environmental awareness, value perception, and self-efficacy; ξ represents the observational variables of the exogenous latent variables; Y represents the vector of the endogenous latent variable, reflecting the low-carbon production intention and the adoption of low-carbon technologies; η represents the observational variables of the endogenous latent variables. ΛCausal steps approach has been widely used to test the effectiveness of mediating variables in the social science field. In this study, causal steps approach was utilized to examine the mediating effect of low-carbon production intention. There are three steps to judge the mediating effect: the first is to test the relationship between key independent variables  and dependent variable ; the second is to examine the effect of key independent variables on the mediating variables; and the third is to analyze the effects of key independent variables and mediating variables on the dependent variable. In addition, we can calculate the marginal effect of the key independent variables to compare the strength of the role of mediating variable.Hierarchical regression is a multiple regression method used to determine the order of different variables in the regression equation theoretically or according to the actual needs of researchers. In this study, hierarchical regression was utilized to examine the moderating effect of situational variables . Specifically, explanatory variables, moderating variables, and interaction terms were successively introduced into the regression model. A comparison of the three models’ square sum of partial regression was conducted to determine whether moderating variables and interaction terms significantly affect the dependent variables. Moreover, a moderating effect was observed when the moderating variable and interaction term significantly affected the dependent variables.The rice farmers’ socio-demographic and farm characteristics are shown in n = 944) implementing this technology. Moreover, the average cognition level of straw returning was significantly higher than other low-carbon agricultural technologies, substantiating that straw burning prohibition and comprehensive utilization in Hubei province achieved remarkable achievements. Besides, 33.66% of rice farmers (n = 375) sprayed abamectin-containing biological pesticide, and 30.79% (n = 343) adopted intermittent irrigation. However, only 17.68% (n = 197) of farmers adopted the soil testing formula fertilizer.According to the survey results see , straw rSPSS 22.0 and AMOS 22.0 were used to test the reliability and validity of the questionnaire measurement scale see . The oveCFA was used to test the convergent validity of the scale see . The res2) expansion driven by large samples, the ratio between Chi-square to the degree of freedom (χ2/df) was selected as an indicator of fitness (2/df = 2.351 (<3), GFI = 0.969 (>0.90), AGFI = 0.953 (>0.90), CFI = 0.969 (>0.90), NFI = 0.947 (>0.90), IFI = 0.969 (>0.90), TLI = 0.957 (>0.90), RMSEA = 0.035 (<0.08), CN (0.01) = 609 (>200). The results suggested a good consistency between the theoretical model and the practical data. After deleting insignificant paths between latent variables according to the modification indices, the standardized path coefficient are shown in To solve the issue of Chi-square value  and the socio-environmental factor . As previously described by As shown in As seen in We found that environmental awareness strongly affected the adoption of low-carbon technologies for rice farmers with high socio-environmental factor, suggesting that improving their environmental awareness can effectively encourage them to engage in low-carbon production see . BesidesCompared to rice farmers with low socio-environmental factor, the positive effect of self-efficacy on adopting low-carbon technologies was more potent for rice farmers with high socio-environmental factor see . AccordiFor rice farmers with low socio-environmental factor, low-carbon production intention positively influenced their adoption of low-carbon technologies see . Consequn = 1,114), the theoretical model was empirically tested by SEM.In the present study, the adoption rates of soil testing formula fertilizer, biological pesticide, intermittent irrigation, and straw returning by sample rice farmers were 17.68%, 33.66%, 30.79%, and 84.74%, respectively. This finding suggested that the straw burning ban and comprehensive utilization management in Hubei province achieved remarkable achievements, but the adoption rates of other low-carbon agricultural technologies were dismal. Over the years, much emphasis has been placed on the effects of demographic , economiImportantly, we found that when farmers lacked basic cognition of climate change, low-carbon technologies, and environmental awareness, they could not perceive the value of adopting low-carbon technologies, further hindering intention formation and the actual adoption behavior. Compared to the literature , our theMeanwhile, growing evidence suggests that unique abilities and circumstances often limit the transformation from individual intention to actual behavior, described as the phenomenon of “high intention—low behavior” . Unlike This research provides four critical connotations for the policymakers of developing countries that aim to popularize low-carbon agriculture to protect the global climate. First of all, since the low-carbon production attitude of farmers has a positive effect on the adoption of low-carbon technologies mediated by the effect of low-carbon production intention, improving farmers’ attitude and intention can effectively promote low-carbon agricultural technologies. Low-carbon agricultural knowledge and technical training are key to improving farmers’ attitude toward low-carbon production and increasing low-carbon production intention. Governments of developing countries can improve the popularization of low-carbon agricultural knowledge with the help of new media platforms. Importantly, intensive, comprehensive, and sustainable low-carbon agricultural knowledge propaganda is a reasonable way to activate and arouse farmers’ intention toward low-carbon production from the psychological level.Secondly, besides the direct positive effect, farmers’ behavioral efficiency perception also positively affects the adoption of low-carbon technologies mediated by low-carbon production intention. Therefore, improving farmers’ behavioral efficiency perception is necessary for promoting low-carbon agriculture. Specifically, agricultural research institutes can refine low-carbon technologies such as intermittent irrigation and straw returning and provide low-carbon agricultural production guidance to enhance farmers’ confidence and perception of efficiency in implementing low-carbon production.Moreover, given that the implementation costs of low-carbon agriculture hinder farmers from adopting low-carbon agricultural technologies, government subsidies may be a solution. Indeed, in most developing countries, agricultural income is the primary source for farmers, and agricultural production costs are critical to their livelihoods. Accordingly, improving the subsidies for low-carbon agriculture and reducing the low-carbon production costs of farmers are paramount approaches to promoting low-carbon agriculture. Furthermore, ecological compensation should be incorporated into the agricultural subsidies, which is beneficial to reduce the direct and hidden costs of low-carbon production for farmers and stimulate their enthusiasm for participating in low-carbon production.Last but not least, the production activities of farmers occur in a specific social environment. Therefore, the need for establishing a green and low-carbon social environment should be emphasized. A green and low-carbon social environment will induce environmental awareness and higher self-efficacy in farmers, who are more likely to engage in low-carbon production. However, socio-environmental factor negatively moderates the effect of farmers’ low-carbon production intention on the adoption of low-carbon technologies, which leads to the phenomenon of “high intention—low behavior” of farmers in low-carbon production. More precisely, although the low-carbon production social environment may help improve the subjective intention of farmers, the effect of low-carbon production intention on the adoption of low-carbon technologies will be less significant if farmers live in an environment bereft of knowledge of low-carbon agricultural materials and professional field management equipment. Consequently, low-carbon agricultural information promotion and low-carbon agricultural technologies training are crucial for individual farmers and critical to creating a green and low-carbon social environment, which fosters farmers to carry out low-carbon production. At the same time, the infrastructure, machinery, and equipment required for low-carbon agriculture are heavy financial burdens for farmers. The low-carbon agricultural production loan policies and agricultural materials subsidies are practical methods to reduce these costs.The empirical results reported herein should be considered in light of some limitations. As shown above, rice cultivation is the main occupation of most farmers, and rice yield and economic returns are of great importance to them. Whether farmers finally adopt low-carbon agricultural technologies depends on psychological factors  and the actual financial benefits. In addition, the financial benefits of adopting those technologies can affect farmers’ psychological perceptions of low-carbon agriculture. Given that the returns on investment of farmers’ adoption behavior were not studied in this paper, we could not analyze how the economic benefits of adopting low-carbon agricultural technologies affect the psychological changes of farmers. Based on the above analysis, we believe that the psychology related to farmers’ adoption behavior of low-carbon agricultural technologies is a topic worth exploring in the future. Moreover, experimental data could be used to validate the theoretical model proposed in this paper. Finally, the cost and benefit data of low-carbon production can be accurately collected in field experiments to further study the mechanism underlying the influence of economic factors affecting psychological cognition and the actual behavior of farmers.The previous literature on farmers’ adoption of low-carbon technologies has highlighted demographic, economic, and environmental factors , while fThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by the National Natural Science Foundation of China (Project No. 72003051) and the Ministry of Education of Humanities and Social Science of China (Project No. 19YJC790048). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.LJ conceived and designed the study and performed the empirical analysis of survey data. HQH contributed significantly to manuscript preparation. SH, HYH, and YL was put forward valuable idea and participated in wrote the manuscript. All authors contributed to the article and approved the submitted version.


Cuproptosis is a new modality of cell death regulation that is currently considered as a new cancer treatment strategy. Nevertheless, the prognostic predictive value of cuproptosis-related lncRNAs in breast cancer (BC) remains unknown. Using cuproptosis-related lncRNAs, this study aims to predict the immune microenvironment and prognosis of BC patients. and develop new therapeutic strategies that target the disease.The Cancer Genome Atlas (TCGA) database provided the RNA-seq data along with the corresponding clinical and prognostic information. Univariate and multivariate Cox regression analyses were performed to acquire lncRNAs associated with cuproptosis to establish predictive features. The Kaplan-Meier method was used to calculate the overall survival rate (OS) in the high-risk and low-risk groups. High risk and low risk gene sets were enriched to explore functional discrepancies among risk teams. The mutation data were analyzed using the “MAFTools” r-package. The ties of predictive characteristics and immune status had been explored by single sample gene set enrichment analysis (ssGSEA). Last, the correlation between predictive features and treatment condition in patients with BC was analyzed. Based on prognostic risk models, we assessed associations between risk subgroups and immune scores and immune checkpoints. In addition, drug responses in at-risk populations were predicted.We identified a set of 11 Cuproptosis-Related lncRNAs , based on which to construct the risk model. In comparison to the high-risk group, the low-risk patients lived longer (p < 0.001). Moreover, cuproptosis-related lncRNA profiles can independently predict prognosis in BC patients. The AUC values for receiver operating characteristics (ROC) of 1-, 3-, and 5-year risk were 0.849, 0.779, and 0.794, respectively. Patients in the high-risk group had lower OS than those in the low-risk group when they were divided into groups based on various clinicopathological variables. The tumor burden mutations (TMB) correlation analysis showed that high TMB had a worse prognosis than low-TMB, and gene mutations were found to be different in high and low TMB groups, such as PIK3CA (36% versus 32%), SYNE1 (4% versus 6%). Gene enrichment analysis indicated that the differential genes were significantly concentrated in immune-related pathways. The predictive traits were significantly correlated with the immune status of BC patients, according to ssGSEA results. Finally, high-risk patients showed high sensitivity in anti-CD276 immunotherapy and conventional chemotherapeutic drugs such as imatinib, lapatinib, and pazopanib.We successfully constructed of a cuproptosis-related lncRNA signature, which can independently predict the prognosis of BC patients and can be used to estimate OS and clinical treatment outcomes in BRCA patients. It will serve as a foundation for further research into the mechanism of cuproptosis-related lncRNAs in breast cancer, as well as for the development of new markers and therapeutic targets for the disease. Breast cancer (BC) is a cancer that affects mainly women and is a major factor in mortality worldwide . BC has Cuproptosis is a new regulatory cell death pattern that mainly relies on the direct binding of fatty acyl components of the tricarboxylic acid (TCA) cycle of mitochondrial respiration, distinguished from other regulatory cell death features like pyroptosis, ferroptosis and apoptosis. With the accumulation of acylated protein and the subsequent decrease in iron-sulfur cluster protein, the cells died due to protein toxic stress. Copper is a vital cofactor for all organisms, but it can become poisonous if density exceed the threshold value maintained by evolutionarily conservative steady-state mechanisms. Current studies have found significant changes in copper content in serum and tumor tissues in some tumor patients –14. In aLong non-coding RNA (lncRNA) means a non-coding RNA that is more than 200 nucleotides in length , 19. IncIn this study, we established a predictive features and internal validation on the basis of cuproptosis-related lncRNAs. We further analyzed its underlying value in predicting the diagnosis, prognosis, chemotherapy response, and tumor immune infiltration of patients with BC.https://portal.gdc.cancer.gov/); Data were obtained for 1089 alive patients with lncRNA expression. Fifty-two genes related to cuproptosis were downloaded from the genecard database and previous literature . .By combining the risk score with the clinicopathological characteristics of patients’ age, phase, and TNM stage, a nomogram that can forecast patients with BRCA’s 1-, 3-, and 5-year survival was developed. We verified that predicted survival is consistent with actual survival by using a calibration curve.Somatic changes in the BRCA cohort were obtained from the TCGA database. TMB was defined as the number of somatic, coding, base substitution, and indel mutations per megabase in the genome tested using non-synonymous and transcoding indels at the 5% limit of detection. The “MAF Tools” R package  has beenIn accordance with the median risk score, patients with BC were distinguish between high-risk team and low-risk team. The error detection rate (FDR) < 0.05 and | log2fold change (FC) > 1| were used as screening standard for obtaining cuproptosis-related genes (DEGs) with divergence in expression. We utilize the “ggplot2” package for GO and KEGG analysis. The difference was regarded as statistically significant when the P value was less than 0.05.The relative ratio of infiltrating immune cells was calculated using the ssGSEA and CIBERSORT R scripts. In exploring the correlation during risk rating values and immunologically infiltrating cells, we used a Spearman rank correlation analysis.To assess the role of predictive features in forecasting response to BRCA therapy, we computed the maximum inhibitory concentration (IC50) half of the common chemotherapeutic agents used to the clinical treatment of BC. In order to compare the IC50 values between high-risk and low-risk teams, the Wilcoxon signed rank test was used.All data analyses were executed using the R software (version 4.0.2). The expression of cuproptosis-related DEGs in both normal and cancer tissues was examined using Wilcoxon’s test. Using univariate Cox regression analysis, the association between cuproptosis-related lncRNA and overall survival (OS) was examined, and lasso- Cox analysis was applied to sift cuproptosis-related lncRNA to set up predictive features. The Kaplan-Meier approach and the logarithmic rank examine were used to compare the OS of patients in the high-risk team and the low-risk team. The ROC curve was plotted using the “survivalROC” package, and the area under the curve (AUC) value was calculated.We identified 1136 lncRNA associated with cuproptosis , B cells, CD8+T cells, T follicle helper cells (Tfh) cells, T helper type 1 (Th1) cells, Tumor Infiltrating Lymphocytes (TIL) were strikingly different between the high-and low-risk teams  with these lncRNA. Among them, LIAS was a vital driving factor for the death of copper . At presSince the prognosis of patients in the high-risk team and the low-risk team was different, enrichment analysis was enforced to study possible divergences between the high-risk team and the low-risk team. Besides, we discovered that in biological process (BP), enriched in humoral immune response, protein activation cascade. The cellular component was enriched in the immune globulin complex and immunoglobulin receptor binding. More importantly, KEGG was enriched in IL-17 signaling pathway, completion and colonization cascades, NF-κB signaling pathway. Enrichment results showed that differential genes with high risk were closely linked to tumor and immune-related pathways.Subsequently, ssGSEA results indicated that activated dendritic cells (ADCs), CD8+T cells, B cells, and tumor-infiltrating lymphocytes (TILs) were markedly different between the high-risk and low-risk teams. The IFN response was lower in the high-risk team than in the low-risk team for cytolytic activity, human leukocyte antigen (HLA), and Type II immune function score, inflammation promotion. These results of the survey suggested that immune function is more inactive in high-risk teams. Aside from increased tumor immune cell infiltration, the high-risk group was associated with decreased antitumor immunity, and HLA and type I IFN responses scored lower in the high-risk teams. Therefore, in breast cancer, reduced antitumor immunity in high-risk teams could explain the poor prognosis. Our study also indicated that high-risk patients may be susceptible to anti-CD276 immunotherapy and conventional chemotherapy drugs imatinib, lapatinib, and pazopanib, but resistant to bosutinib, cisplatin, cytarabine, gefitinib, gemcitabine, lenalidomide, nilotinib, paclitaxel, and sunitinib. This proved that high-risk individuals can obtain a benefit from the combined immunotherapy and chemotherapy, providing a basis for precise and individualized treatment of BC patients.However, there were some limitations in our study. Firstly, we only used data from the TCGA database for internal validation, and we needed data from other databases for external validation to test the predictive signature’s applicability further. Secondly, the mechanism of action of cuproptosis-related lncRNA in BC needed to be further verified through experiments.The cuproptosis-related lncRNA signature, in conclusion, can independently predict a patient’s prognosis for BC and provides evidence for a potential cuproptosis-related lncRNA mechanism in BC and its response to clinical therapy.The original contributions presented in the study are included in the article/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 for participation was not required for this study in accordance with the national legislation and the institutional requirements.J-SY and JZ conceived and designed the study. Z-RJ, P-PB, and L-HY performed the experiments. L-ZJ and L-MY analyzed the data. Z-RJ wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors thank reviewers for helpful comments on the manuscript.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.