The hypoxic microenvironment is involved in the tumorigenesis of ovarian cancer (OC). Therefore, we aim to develop a non-invasive radiogenomics approach to identify a hypoxia pattern with potential application in patient prognostication.Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. Meanwhile, multiple hypoxia-related subtypes were identified by unsupervised consensus analysis and LASSO–Cox regression analysis. Subsequently, diversified bioinformatics algorithms were used to explore the immune microenvironment, prognosis, biological pathway alteration, and drug sensitivity among different subtypes. Finally, optimal radiogenomics biomarkers for predicting the risk status of patients were developed by machine learning algorithms.One hundred forty sHRGs and three types of hypoxia-related subtypes were identified. Among them, hypoxia-cluster-B, gene-cluster-B, and high-risk subtypes had poor survival outcomes. The subtypes were closely related to each other, and hypoxia-cluster-B and gene-cluster-B had higher hypoxia risk scores. Notably, the low-risk subtype had an active immune microenvironment and may benefit from immunotherapy. Finally, a four-feature radiogenomics model was constructed to reveal hypoxia risk status, and the model achieved area under the curve (AUC) values of 0.900 and 0.703 for the training and testing cohorts, respectively.As a non-invasive approach, computed tomography-based radiogenomics biomarkers may enable the pretreatment prediction of the hypoxia pattern, prognosis, therapeutic effect, and immune microenvironment in patients with OC. Ovarian cancer (OC) has the highest mortality rate among gynecologic cancers. Surgery and platinum-based chemotherapy are the mainstays of care for individuals with OC . MeanwhiRM) were found to express PD-1 and LAG-3, and the triggering of inhibitory receptors may lead to dysfunction that may limit the effectiveness of TRM in inhibiting tumor growth (Hypoxia impacts the tumor microenvironment (TME) , angioger growth . The attr growth . TherefoAt present, a large number of studies have revealed the genesis of cancer through omics analysis. In lung cancer, key genes for disease progression were identified by various bioinformatics methods . InteresHence, there have been many studies focusing on radiogenomics in ovarian cancer in recent years, but they mainly focused on the prediction of Classification of Ovarian Cancer (CLOVAR)  and BRCAIn this research, we collected the genomic data of 630 OC patients and then constructed three types of subtypes using hypoxia-related genes or hypoxia pattern regulator expression. We assessed the predictive value of the hypoxia subtypes and correlated it with TME. In addition, we developed a nine-gene next-generation sequencing panel for clinical application, and it may represent different hypoxic statuses. As for radiomics, a CT imaging signature based on the nine-gene panel classification was obtained using the radiomics algorithm. In a word, our findings revealed the critical role of hypoxia in TME and immunotherapy for OC patients. Most importantly, the CT imaging-based radiogenomics signature can make non-invasive predictions prior to treatment.p-value <0.05 were set as the thresholds  were screened using univariate Cox regression analysis in all hypoxia pattern-related regulators. Next, least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis (stepwise method) were used to identify genes involved in a panel. We used the appropriate λ and Akaike information criterion (AIC) to control robustness in the model. All the above modeling processes were carried out in the TCGA-OV cohort. The hypoxia risk score was calculated as follows:Firstly, prognostic genes  with the same formula. Subsequently, we divided all patients into high- and low-risk groups with the median score in the TCGA cohort. Finally, PCA, ROC, Kaplan–Meier, and Cox regression analyses were used to validate the prognostic value of the nine-gene panel in each cohort.Zhang et al. identified a glycolysis-related gene signature for OC patients . Zhou etp-value <0.05 was regarded as statistically significant. As for the hypoxia pattern regulators, Gene Ontology (GO)   and Kyotogy (GO)  functionThe pRRophetic package worked by utilizing gene expression and drug sensitivity data in cancer cell lines, and then the models were applied to the gene expression data from primary tumor biopsies . We usedWe used the MutSigCV package  to selecA total of 97 contrast-enhanced CT images of the abdomen and pelvis were selected from the Cancer Imaging Archive (TCIA) , which wConsidering the characteristics of the pelvic masses, we used arterial phase data from enhanced CT for the study. Manual segmentation was performed using ITK-SNAP in the cross-sectional layer of the largest tumor region. All patients were selected for repeat region of interest (ROI) segmentation 30 days after the initial segmentation, which was performed by different radiologists. The diversity in voxel sizes leads to variations in feature values, so for reconstruction with different voxel sizes, we used a voxel size resampling strategy to select reproducible image features: spline interpolation resamples all images to the same 1 × 1 mm pixel size. In addition, the voxel intensities within the ROI are discretized into a limited intensity range of 64 bins. Ultimately, we extracted 806 radiomics features from the ROI of each OC patient using PyRadiomics (V 2.0.0) . Originap <0.05 was considered statistically significant.All statistical analyses were performed using the R software (v.4.0.1) and Python (v.3.7.6). Detailed statistical methods for transcriptome data processing are covered in the above section. Five hundred and ten DEGs were identified in the normoxia- and hypoxia-cultured OC cell lines  and hypoxia-cluster-B (282 patients) , gene-cluster-B (152 patients), and gene-cluster-C (234 patients)  were included in the LASSO regression analysis  with the same formula. Subsequently, we divided all patients with OC into high- and low-risk groups with the median score in the training cohort. To explore the relationship between the three subtypes, namely, hypoxia patterns, pattern-related regulator subtypes, and hypoxia risk group, we visualized the relationship using the Sankey diagram  as a classifier, we extracted the radiomics features from these CT images for the established radiogenomics signature. A total of 1,008 models were constructed by combining different methods  has been proven to play an important role in promoting OC chemoresistance, tumor metastasis, and immunosuppression . The higAlthough hypoxia patterns could differentiate clinical outcomes and immune perturbations in OC patients, the underlying regulators in different patterns are unknown. We found significantly altered pathways in the enrichment analysis, including the MAPK signaling pathway, Wnt signaling pathway, ECM–receptor interaction, and PI3K–Akt signaling pathway. As a classic cancer pathway, these pathways have been widely reported in ovarian cancer , 63. HowAlthough the hypoxia patterns can predict differences in survival and immune characteristics, molecular subtypes were studied based on populations. The above method cannot accurately predict the hypoxia risk status of each patient, so we used the RNA expression of nine hypoxia pattern-associated regulators for clinical application with hypoxia risk score. Most patients with poor prognosis in molecular subtypes were closely related to patients in the high-risk group, and hypoxia-cluster-B and gene-cluster-B had higher hypoxia risk score. Of the nine genes, some of them were shown to be involved in the regulation of biological functions in ovarian cancer, such as TGFBI which is involved in polyploid cell formation and in response to paclitaxel ; extraceZ-score method for normalization, the PCC method for feature preprocessing, the RFE method for dimensionality reduction, and the logistic regression method for calculating coefficient. Using the above radiomics signature, the AUC values of the training set and the test set were 0.900 and 703, respectively. There is extensive heterogeneity at the genomic level in primary OC and peritoneal implants, and single-site biopsy sequencing clearly does not meet our requirements  research on other tumors , we specThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/SF and TX conceived and designed the study. YS was responsible for the materials. SF drafted the article. YS, SL, YG, XJ, and KZ revised the article critically. All authors provided their final approval of the submitted version.This study was supported by the National Natural Science Foundation of China (No. 82072078), Jiangsu Province Key Research and Development Project (SBE2020741118), and Postgraduate Research & Practice Innovation Program of Jiangsu Province.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.


Background: Alkaline phosphatase (ALP) and albumin (ALB) have been shown to be associated with coronary artery disease (CAD), and it has been reported that alkaline phosphatase-to-albumin ratio (AAR) is associated with the liver damage and poorer prognosis of patients with digestive system malignancy. Moreover, several previous studies showed that there was a higher incidence of malignancy in CAD patients. However, to our knowledge, the relationship between AAR and long-term adverse outcomes in CAD patients after undergoing percutaneous coronary intervention (PCI) has not been investigated. Therefore, we aim to access the relation between AAR and long-term adverse outcomes in post-PCI patients with CAD.Methods: A total of 3378 post-PCI patients with CAD were enrolled in the retrospective Clinical Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI (CORFCHD-ZZ) study from January 2013 to December 2017. The median duration of follow-up was 37.59 ± 22.24 months. The primary end point was long-term mortality including all-cause mortality (ACM) and cardiac mortality (CM). The secondary end points were major adverse cardiac events (MACEs) and major adverse cardiac and cerebrovascular events (MACCEs).Results: Kaplan–Meier analyses showed that an increased AAR was positively correlated with incidences of long-term ACM , CM , MACEs  and MACCEs . Multivariate Cox regression analyses showed that the elevated AAR was an independent predictor of long-term ACM , CM , MACEs  and MACCEs .Conclusion: An elevated AAR is a novel independent predictor of long-term adverse outcomes in CAD patients following PCI. In a red-dimer . With thd-dimer , such asd-dimer  subanalyd-dimer  which shd-dimer . In addi657, heme-depleted sGC and NOXs. It is well-known that several mechanisms are involved in the pathogenesis of CAD such as inflammatory response [ALP could be activated by oxidative stress, and its increase was also associated with oxidative stress . Oxidatiresponse ,7, metabresponse ,5 and atresponse . Furtherresponse . In addiresponse . A similresponse . On the response  and its response ,33. A loresponse . Furtherresponse . More reresponse .Considering that increased ALP and reduced ALB levels in serum were significantly associated with the pathogenesis of CAD and contributed to the initiation, progress and prognosis of CAD, plus our findings from a cohort study with a large sample, thus we thought that AAR may be a reasonable and feasible biomarker to predict long-term adverse outcomes in post-PCI patients with CAD.First, there were some unavailable baseline ALP and ALB data from a few patients in our study, and the removal of these patients contributed to the reduction in study sample size. Second, we did not take atrial fibrillation into consideration in the exclusion criteria. Third, it was not considered whether fracture healing, some bone diseases and corticosteroids had some influences on AAR. Fourth, we only collected the baseline data, so it was unknown whether dynamic change of these variables affected the end points. Fifth, our study was a single, retrospective study and only evaluate the relation between AAR and long-term adverse outcomes in post-PCI patients with CAD from China, thus the findings still need to be further demonstrated in other populations.An elevated AAR is a novel independent predictor of long-term adverse outcomes in CAD patients after undergoing PCI, such as mortality, MACEs and MACCEs, and it is worth utilizing in clinical practice.Click here for additional data file.


The results showed that the COP real-time visual feedback training provided by smart wearable devices can better reduce postural sway and improve body balance ability than general training, when standing quietly.Balance control with an upright posture is affected by many factors. This study was undertaken to investigate the effects of real-time visual feedback training, provided by smart wearable devices for COP changes for healthy females, on static stance. Thirty healthy female college students were randomly divided into three groups . Enhanced visual feedback on the screen appeared in different directions, in the form of fluctuations; the visual feedback balance training group received real-time visual feedback from the Podoon APP for training, while the non-visual feedback balance training group only performed an open-eye balance, without receiving real-time visual feedback. The control group did not do any balance training. The balance training lasted 4 weeks, three times a week for 30 min each time with 1–2 day intervals. After four weeks of balance training, the results showed that the stability of human posture control improved for the one leg static stance for the visual feedback balance training group with smart wearable devices. The parameters of COP max displacement, COP velocity, COP radius, and COP area in the visual feedback balance training group were significantly decreased in the one leg stance ( Balance ability refers to the human body’s ability to adjust automatically to maintain postural stability when it moves or is subjected to external forces . BalanceIn recent years, sensorimotor integration technology has been used to provide VF to improve the balance ability of people with disabilities and at high-risk of falls. Previous studies have indicated that internal feedback on one’s own postural sway can be obtained through VF, so that the body can control its posture changes more autonomously . In a stVF training to control body posture helps improve the body’s ability to maintain balance and achieve stable standing. It can stabilize the body posture and significantly improve static and dynamic balance ability . PreviouOur previous research explored the immediate effect of visual feedback provided by intelligent devices on the posture control of different genders . It was Thirty healthy female college students were recruited and randomly assigned to the visual feedback balance training group (VFT), non-visual feedback balance training group (NVFT), or no balance training control group (CG), with 10 persons in each group. The basic characteristics of the participants, concerning age , height , and weight  in the VFT, NVFT, and CG groups were recorded. Meanwhile, there were no significant differences among the three groups. Exclusion criteria: any past history of injury or treatment of the lower limbs, any neurological or vascular deficit affecting balance, pain and swelling near the ankle and foot, or visual or vestibular impairment . The parA force plate  was used to calculate kinematic data: COP anteroposterior max displacement, COP mediolateral max dis-placement, COP anteroposterior velocity, COP mediolateral velocity, COP radius, and COP area. The force plate signals were collected at a sampling frequency of 300 Hz. In order to avoid the impact of different wear and tear during the test, all participants wore the same experimental tights and uniform sports shoes. The sports shoe incorporated a smart insole . The smaThe VF training group wore the experimental tights and uniform training shoes with smart insoles and used the Podoon APP on the iPad Pro during training. The NVF training group wore the same experimental tights and training shoes without smart wearable devices.Participants were recruited prior to the experiment, and their foot length was measured. Then, a smart foot pad matching their foot length was selected and cut. The participants had a five-minute warm-up run on a treadmill at 6 km/h to activate the lower extremity muscles for better balance control and one minute of rest. After the preparation, the thirty female college students were randomly divided into VFT, NVFT, or CG groups and completed tests before training as a pre-test. The pre-test consisted of 6 items, including one leg stance non-visual feedback (OLS-NF), one leg stance-visual feedback (OLS-VF), tandem stance (dominant leg in back)-non visual feedback (TSDL-NF), tandem stance (dominant leg in back)-visual feedback (TSDL-VF), tandem stance (non-dominant leg in back)-non visual feedback (TSNDL-NF), and tandem stance (non-dominant leg in back)-visual feedback (TSNDL-VF). Each item was measured three times, each time for 10 s. In order to ensure the consistency of the test, subjects in the study were all selected to have the right leg dominant. OLS is defined as the participant using the dominant leg to stand, while the non-supported leg was flexed at the knee with the plantar surface of the foot stabilized on the knee of the supporting leg . TS is dAfter the pre-test, the participants underwent four weeks balance training, three times a week for 30 min each time, with 1-2 day intervals. Training included the VFT using Podoon APP to perform OLS/TS-VF balance training. The NVFT was given an open-eye balance training without Podoon APP participation on OLS/TS-NF. The control group did not do any training. The iPad Pro with Podoon APP was located at an eye-level height, 1 m apart from the participants. Participants in the VFT were asked to keep the dynamic point in the central circle as much as possible.A priori power analysis  showed that a minimum of 10 participants was required on the basis of conventional α (0.05) and β (0.80) values, with an effect size of 3.05. t-test between the pre-test and post-test for post-hoc comparison. The level of significance was set at α < 0.05.In this study, the average values of three measurements for each item in each subject were calculated and used for statistical analysis. MATLAB  was used for statistical analysis. The experiment used a mixed design two-way analysis of variance (ANOVA) (3 Group × 2 Times) to compare the differences between the pre-test and post-test of the three groups  in the six items: one leg stance non-visual feedback (OLS-NF), one leg stance-visual feedback (OLS-VF), tandem stance (dominant leg in back)-non visual feedback (TSDL-NF), tandem stance (dominant leg in back)-visual feedback (TSDL-VF), tandem stance (non-dominant leg in back)-non visual feedback (TSNDL-NF), and tandem stance (non-dominant leg in back)-visual feedback (TSNDL-VF). When the interaction was found to be significant, we used least significant difference comparisons between the three groups and p < 0.05). In addition, COP max displacement, COP velocity, COP radius, and COP area after intervention were significantly lower than that before intervention, except for the CG group. The effect from these interventions for the above COP parameter varied from weak to moderate across the balance conditions.After four weeks of balance training with different interventions, balance postures were assessed immediately after the training was completed. The position balance of VFT was significantly improved in OLS when compared with pre (p < 0.05). For the OLS-NF, post hoc analyses revealed that the COPML/AP max displacement of the visual feedback balance training group decreased after visual feedback balance training and the COPML max displacement of the non-visual feedback balance training group also decreased after traditional balance training. p < 0.05). For the OLS-VF, post hoc analyses revealed that the COPML/AP max displacement of the visual feedback balance training group decreased after visual feedback balance training. p < 0.05). Post hoc analyses revealed that the COPML/COPAP max displacement between the pre-test and the post-test decreased in TSNDL-NF, TSNDL-VF, TSDL-NF, and TSDL-VF.p < 0.05). For the OLS-NF, post hoc analyses revealed that the COPML/AP velocity of the visual feedback balance training group decreased after visual feedback balance training.p < 0.05). For the OLS-VF, post hoc analyses revealed that the COPML/AP velocity of the visual feedback balance training group decreased after visual feedback balance training; post hoc analyses revealed that the COPML/AP velocity of NVFT decreased after traditional balance training.p < 0.05). Post hoc analyses revealed that the COPML/COPAP velocity between the pre-test and the post-test decreased in TSNDL-NF, TSNDL-VF, TSDL-NF, and TSDL-VF.p < 0.05). For the OLS-NF, post hoc analyses revealed that the COP radius of the visual feedback balance training group and the COP area of the visual feedback balance training group decreased after visual feedback balance training. p < 0.05). For the OLS-VF, post hoc analyses revealed that the COP radius of the visual feedback balance training group and the COP area of the visual feedback balance training group decreased after visual feedback balance training.p < 0.05). Post hoc analyses revealed that the COP radius and COP area between the pre-test and the post-test decreased in TSNDL-NF, TSNDL-VF, TSDL-NF, and TSDL-VF.The purpose of this study was to explore balance training effects for healthy females, with a real-time VF technique of COP changes provided by smart wearable devices, on static balance postural control. After four weeks of balance training, the results showed that visual feedback training can improve healthy female stability of postural control by OLS and TS static balance training with a VFT intelligent app.ML and COPAP displacement with VFT demonstrated that the participants could control body sway in a considerably more stable manner with the help of real-time VF information. A past study had shown that real-time visual feedback can provide sensory information to the central nervous system (CNS), helping to reduce motor output variability [ML and COPAP max displacement may have been due to the increased proprioceptive integration ability and the stability of motor output with VF training. In addition, visual feedback balance training can increase muscle activity around the ankle and isokinetic muscle strength to improve balance ability [In this study, the decrease in COPiability . Visual iability . In addiiability . Therefo ability . TherefoML velocity and the COPAP velocity in the VFT may have been caused by the goal-directed movement of the ankle and hip joint mechanism, regulated by the CNS during VF training. In addition, past studies have found that balance training stimulates proprioception and increases sensory motor nerve signal transmission to improve balance control ability [Previous studies have found that the smaller the displacement velocity, the better the balance control ability when using VF training . In this ability , while b ability . TherefoPrevious studies have shown that the COP radius and the COP area can reflect the static stability of the human body in the process of OLS; the larger the COP area and COP radius, the worse the stability . TherefoA limitation of this study is that the experiment was conducted in a small sample of participants, and the small amount of training the participants received may not have been sufficient to measure the adaptation effect of the training. Therefore, although the value of COP of VFT after training was higher than CG/NVFT, the training effect needs more samples for further verification. In addition, the study only assessed the static standing of female subjects in stable postures, and no further discussion was made of postural balance with an unstable plane/external disturbance or the involvement of male subjects; our future research will address these issues.Visual feedback training may increase the participants’ visual information and promote the integration of the central nervous system, thereby assisting proprioception to reduce the center of pressure movement and enhance balance ability. In this study, the healthy females increased their balance ability after visual feedback training and found that the need for visual feedback in the balanced posture on one foot was significantly higher than that with two feet. It is particularly important to use smart wearable devices to improve the body’s ability to maintain balance.


Coronary artery disease (CAD) is a major contributor to morbidity and mortality worldwide. Myocardial ischemia may occur in patients with normal or non-obstructive CAD on invasive coronary angiography (ICA). The comprehensive evaluation of coronary CT angiography (CCTA) integrated with fractional flow reserve derived from CCTA (CT-FFR) to CAD may be essential to improve the outcomes of patients with non-obstructive CAD. China CT-FFR Study-2 (ChiCTR2000031410) is a large-scale prospective, observational study in 29 medical centers in China. The primary purpose is to uncover the relationship between the CCTA findings (including CT-FFR) and the outcome of patients with non-obstructive CAD. At least 10,000 patients with non-obstructive CAD but without previous revascularization will be enrolled. A 5-year follow-up will be performed. The primary endpoint is the occurrence of major adverse cardiovascular events (MACE), including all-cause mortality, non-fatal myocardial infarct, unplanned revascularization, and hospitalization for unstable angina. Clinical characteristics, laboratory and imaging examination results will be collected to analyze their prognostic value. Cardiovascular disease is a worldwide disease, but China is one of the countries with the heaviest disease burden . Since tCoronary CT angiography (CCTA) is a widely used non-invasive imaging modality to evaluate CAD and has demonstrated a high diagnostic performance in detecting obstructive and non-obstructive CAD on invasive coronary angiography (ICA) . LikewisCoronary CT angiography-derived FFR (CT-FFR) has been reported to be a potential alternative to provide a physiological evaluation of the entire coronary artery tree, with high diagnostic accuracy in stable CAD patients compared with invasive FFR, the gold standard . MoreoveThe aims of this study are to (1) establish a large cohort of patients with non-obstructive CAD based on the Chinese population and conduct a long-term follow-up observation and (2) explore the predictive value of CT-FFR for MACE in patients with non-obstructive CAD beyond the clinical and anatomical factors.http://www.chictr.org.cn (ChiCTR2000031410). This study is partially supported by the National Key Research and Development Program of China (no. 2017YFC0113400), Jiangsu Provincial Key Research and Development Program (no. BE2020699), and Key Program of the National Natural Science Foundation of China (no. 81830057) for LJZ.This is a prospective, observational, multicenter registry study. The trial protocol and written informed consent forms have been reviewed and approved by the clinical trial ethics committee at Jinling Hospital, Medical School of Nanjing University , and by each center before the initiation of the investigation. All enrolled patients will provide written informed consent at admission for their data collection and utilization for future anonymous studies. The study has been registered on We aim to include ten thousand patients referred for CCTA examination by physicians for the evaluation of suspected or known CAD and subsequently diagnosed as non-obstructive CAD by CCTA   but with1) The patient must sign a written informed consent before any study procedures.2) Non-obstructive coronary CAD by CCTA .1) Refusal to participate.2) <18 years or >80 years.3) Pregnancy or lactation.4) Allergy to iodinated contrast agents.5) Previous revascularization (PCI or CABG).6) Previous cardiac transplantation or valvular surgery.7) Any life-threatening condition or severe co-morbidity.8) Patients with poor image quality studies, unsuitable for further analysis.9) Coronary artery fistula and anomalous origin.10) Complex congenital heart disease.11) Missing data.During the initial screening stage (conducted by each center), any patients who meet any one of the above 1-7 exclusion criteria will be excluded. The final enrollment will be determined by the core laboratory  after double-checking the data, re-evaluating coronary artery stenosis and image quality.Baseline clinical characteristics will be obtained through an electronic questionnaire for each participating patient at enrollment, including age, sex, height, weight, diabetes mellitus, hypertension, hyperlipidemia, smoking, drinking, positive CAD family history, clinical symptoms, all patient-reported examinations, medications, and surgeries associated with the cardiovascular disease within 6 months –5. DiabeAll CCTA acquisitions will be performed in each medical center using CT scanners with ≥64 detector rows. A non-contrast enhanced coronary calcium scoring study will be obtained before the CCTA examination. The specific scanning protocols are consistent with the routine clinical practice of CCTA in each medical center. Nitroglycerin and beta-blockers will be administered according to the standard practice of each center. Baseline scanning characteristics will be obtained through an electronic questionnaire for each participating patient after CCTA examination, such as scanning equipment, scanning protocols, the name, concentration, dosage and injection rate of iodinated contrast agent, average heart rate during scanning, and the usage of nitroglycerin and beta-blockers. All the Digital Imaging and Communications in Medicine (DICOM) files will be transferred to the core laboratory online or offline for image quality and coronary stenosis assessment after the initial screening in each center. After double-checking the data, subjects who meet the inclusion criteria will be finally enrolled and informed by the core laboratory.The CCTA images will be evaluated in consensus by two cardiovascular radiologists  at the core laboratory. Image quality assessment will be performed using a four-point Likert scale as follows: 4 = excellent ; 3 = good (mild blurring and minor motion artifacts); 2 = acceptable (moderate blurring and mild motion artifacts or minor discontinuity); and 1 = non-diagnostic (severe motion artifacts or discontinuity made the coronary artery structures not differentiable). Patients with poor image quality (score = 1) unsuitable for further analysis will be excluded .The coronary artery is divided into 17 segments according to the American Heart Association (AHA) classification . The rigTo quantify coronary plaque calcification, the Agatston score (AS) will be calculated for each patient by multiplying the calcified lesion area by the maximum density of a single target lesion in this area using a semiautomated software  . Based oQuantitative plaque analysis will be performed by a group of observers using a semiautomated software . The following plaque parameters will be assessed: %DS ; plaque length; MLD and minimal lumen area (MLA); plaque volume (defined as vessel volume minus lumen volume), such as the total volume, the volume of calcification components (>350 HU), lipid components (<30 HU), fiber-fatty components (30–130 HU) and fibrous components (131–350 HU) ; plaque http://18.224.14.19/calcApp/) according to the previous study , CAD-RADS 2 (25–49% stenosis), and CAD-RADS 3 (50–69% stenosis). On a per-segment/vessel/patient basis, CAD-RADS categories will be evaluated based on the maximal stenosis. According to the AHA classification, the number of segments ≥1.5 mm diameter with any calcified, non-calcified, or mixed plaque will be recorded, regardless of the degree of stenosis, for the calculation of segment involvement score (SIS). The maximum SIS value that can be derived is 17 for each patient. A comprehensive CTA risk score will be calculated using an online calculator , PR, punctate calcification (SC), and napkin ring sign (NRS) . LAP is All CT-FFR values will be calculated by using an automated software . The “Shukun-FFR” software consists of two main components, the coronary arteries segmentation model and the computational fluid dynamics (CFD) simulation model. Specifically, a modified V-Net is first used to to segment coronary arteries from the CCTA image firstly . Then, wOutcomes will be ascertained by phone contact with the patient (or family member if needed), reviewing medical records or consulting with the attending physicians, if possible, and adjudicated blindly by an independent clinical event committee according to ACC/AHA standards and the fourth universal definition of MI by reviewing symptoms, cardiac laboratory biomarker data, electrocardiogram results, and cardiovascular imaging findings , 32.The primary endpoint is the occurrence of MACE at follow-up, defined as a composite of all-cause death, non-fatal MI, unplanned revascularization (at least 60 days after the CCTA examination), and hospitalization for unstable angina. Death cases consist of cardiovascular death, non-cardiovascular death, and undetermined cause of death. Cardiovascular death includes death attributable to sudden cardiac death, acute MI, heart failure, cardiovascular bleeding, stroke, cardiovascular procedure, and other cardiovascular causes, such as pulmonary embolism. When a definite non-cardiovascular cause is documented, a cardiovascular reason for death could be excluded. Non-fatal MI consists of ST-segment elevation myocardial infarction (STEMI) and non–STEMI. Unstable angina is defined as the symptoms of ischemic chest pain at rest, and the final diagnosis is myocardial ischemia with objective evidence but without elevation of cardiac biomarkers. For the primary endpoints, the first occurrence timepiont of any one of the above events will be recorded. The follow-up duration is recorded as the interval from baseline CCTA examination to the day of follow-up.Secondary endpoints include cardiovascular death, atrial fibrillation, non-fatal MI, non-fatal stroke, unplanned revascularization, hospitalization for unstable angina, medication adjustment, invasive or non-invasive cardiovascular tests, cumulative radiation exposure from all cardiovascular tests, and total cardiac costs. Medication adjustment includes the increase or decrease of the drug dose and the new addition or discontinuation of medications. For the secondary endpoints, the time of the occurrence for any one of the above events should be recorded.Telephone follow-up will be performed for each enrollee annually by the follow-up team of each medical center until the completion of the 5-year follow-up. The follow-up team in each center includes at least one nurse, one cardiovascular radiologist, and one cardiovascular physician. The follow-up team will first contact the patient via a phone call. If it is unsuccessful, the personal contact will be called for updated information. After documentation of three unsuccessful attempts (on three different days over 1 month) by the follow-up team, a subject will be considered lost to telephone follow-up. If the outcome of this subject cannot be traced through the medical record system, the subject will eventually be deemed to be lost to follow-up. The follow-up team of the core laboratory will randomly select 10% of the subjects from each other medical center for review to confirm the authenticity of the follow-up data.Data management and coordination will be performed by the core laboratory. Study investigators in each medical center will collect all text data regarding baseline clinical characteristics, laboratory results, medical/interventional treatments and outcomes and enter them into a web-based electronic case report form. All imaging data will be transmitted to the core laboratory in an anonymous form. A reference number will be assigned to every single enrolled patient. The final China CT-FFR Study-2 database, including text and imaging data, will be constructed from the individual and valid databases, which will be provided by each participating center. Centers providing forms with more than 5% of missing values will be excluded from the final China CT-FFR Study-2 database.The study was started in November 2019, and initially included 24 medical centers from all 13 regions of Jiangsu Province . Due to t-tests, paired t-tests, or ANOVA tests will be conducted for the comparison of normally distributed continuous data, as appropriate. The difference analysis of non-normally distributed data will be performed by using the non-parametric test. Categorical variables will be expressed as presented as numbers and frequencies or percentages. Pearson's chi-squared test or the likelihood ratio will be used to compare the differences of categorical data between groups, as appropriate. Univariate and multivariate Cox proportional hazard models will be performed to calculate the hazard ratio (HR) with a 95% CI and to estimate the association between variables and the hazards of MACE. Kaplan-Meier plots with the log-rank tests will be generated to estimate cumulative rates of MACE. The receiver operating characteristics (ROC) curve analysis will be performed to determine the optimal cut-off values of quantitative data. The area under the curve (AUC) for each model will be compared. The patient's annual total cardiac cost will be compared using the non-parametric Wilcoxon rank-sum test or a two-sample t-test. Intraclass correlation coefficient (ICC) and Spearman correlation coefficient will be used to assess the inter- and intra-observer agreement. Considering the selection bias and potential heterogeneity between 29 centers, a center effect analysis will be performed. If there is a central effect, a stratified analysis and sensitivity analysis will be performed, or it will be adjusted as a random factor. A p ≤ 0.05 is considered statistically significant.According to the Kolmogorov-Smirnov test, continuous data will be categorized as normally or non-normally distributed data. Mean ± SD will be used to express the quantitative variables for uniformity of presentation, regardless of the distribution. Independent sample p = 0.10)  . The inc = 0.10) , 36. In  = 0.10) . The pre = 0.10) . However = 0.10) . Althoug = 0.10) , 29, 39.Despite its strengths, this study has some limitations. First, this is a large observational registry, which has inherent limitations, such as selection bias and potential heterogeneity between centers. Second, most of the medical centers are from the same province, resulting in a lack of external verification. Third, there is no uniform scanning protocol for baseline CCTA, the scanning characteristics should be adjusted during subsequent data analysis. The scanning protocols of each center will be recorded for the central effect analysis. If there is a central effect, a stratified analysis and sensitivity analysis will be performed, or it will be adjusted as a random factor. Fourth, no blood or other biological samples will be collected at the baseline of this study, which may cause some critical information to be missed.The China CT-FFR Study-2 is a prospective, observational, multicenter registry study. At least 10,000 patients with non-obstructive CAD will be enrolled from 29 medical centers in China. Baseline clinical information and CCTA findings (such as CT-FFR) will be collected. A 5-year follow-up will be performed by phone contact to ascertain the outcomes of patients. To the best of our knowledge, this is the largest prospective observable study to explore the relationship between CT-FFR and prognosis in China. Based on the excellent performance of CT-FFR for diagnosing myocardial ischemia and its predictive value for future risk of MACE, we believe that the China CT-FFR Study-2 will be helpful to provide unique risk stratification of patients with non-obstructive CAD.The studies involving human participants were reviewed and approved by Clinical Trial Ethics Committee of General Hospital of Eastern Theater Command. The patients/participants provided their written informed consent to participate in this study.LJZ and GML contributed to conception and design of the study. FZ was a major contributor in writing the manuscript. FZ, QC, XLu, WC, ZL, and BZ made the equal contribution to this study. QC, ZL, QL, TT, and XLiu contributed to data collection. LJZ, GML, XY, XLi, XLu, WC, BZ, LG, HGa, YS, HW, DW, FX, DJ, SH, HL, CP, HGu, LX, XW, JY, JJ, HZ, XF, YX, and WX organized the database. UJS and CEG contributed to the language revisions. All authors contributed to manuscript revision, read, and approved the submitted version.This study was funded by the National Key Research and Development Program of China (no. 2017YFC0113400), the Jiangsu Provincial Key Research and Development Program (no. BE2020699), and the Key Program of the National Natural Science Foundation of China (no. 81830057) for LJZ. XLi was funded by the National Natural Science Foundation of China (no. 82071897).UJS is a consultant for and/or receives research support from Bayer, Bracco, Elucid Bio, Guerbet, HeartFlow, Keya Medical, and Siemens Healthineers. The remaining 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.


Past studies have reported emotional intelligence (EI) as a relevant factor in development and maintenance of eating disorders (ED), as well as in increasing self-esteem and reducing anxiety. Similarly, research has showed that anxiety and self-esteem are positively and negatively associated to ED criteria, respectively. However, no prior studies have yet tested the multiple intervening roles of both self-esteem and anxiety as potential mediators of the association between EI and ED symptomatology. The present study aims to bridge these gaps by testing a sequential path model. Specifically, we examine the potential sequential mediation effects of self-esteem-anxiety on the link between EI and ED. A sample composed of 516 Spanish undergraduate students and community adults completed measures of EI, self-esteem, anxiety, and ED symptomatology. The results show that high levels of EI were positively associated with self-esteem and negatively associated with anxiety and ED symptoms. Anxiety was positively associated to ED symptoms, while self-esteem levels were negatively linked to ED symptoms. Moreover, path analyses showed that self-esteem and anxiety fully mediated the relationship between EI and ED symptoms in sequence. These findings suggest that EI plays a key role in reducing symptomatology of ED through increased self-esteem and reduced anxiety symptoms, providing novel evidence regarding psychological mechanisms through which EI contributes to a reduction of ED symptomatology. Implications for assessing and improving these psychological resources in ED preventive programs are discussed. Eating disorders (ED) are persistent disturbances of eating or eating-related behaviors that result in significant impairments in psychosocial functioning and physical health (American Psychiatric Association (APA), Theoretical background and empirical evidence have supported the idea that deficits in the processing and managing of emotions play a key role in the development and maintenance of ED  is a relatively new construct related to emotions that comprises a set of basic emotional skills. From an ability perspective, EI is defined as “the ability of people to perceive, use, understand and manage emotions”  moderated the association between levels of anxiety/depression and greater deterioration of ED  play a relevant mediating role between EI and ED symptoms. For example, prior findings have found that social anxiety mediated the relationship between EI and ED risk Li, . Thus, HIn sum, there is empirical support for the link between EI, higher self-esteem, and reduced anxiety, as well as between levels of self-esteem and anxiety and ED symptomatology. It has also been pointed out that individuals with higher EI use their ability to maintain a global feeling of self-worth when appropriate and effectively manage a distressed mood when faced with negative events that are considered key in the development of ED symptoms. Hence, the assessment of self-esteem and anxiety as potential mediators in the association between EI and the symptomatology of ED seems to be justified . EI predicts higher levels of self-esteem and lower levels of anxiety. These variables, in turn, independently predict lower levels of ED symptomatology.Hypothesis 3. . Self-esteem and anxiety might serve as mediators in a sequential mediation model between EI and ED symptoms; that is, EI positively predicts self-esteem, leading to lower levels of anxiety, further decreasing ED symptomatology.SD = 14.76)  located in Southern Spain. Their ages ranged from 18 to 77 years, with a mean age of 38.89 years (.76) see . Given t.76) see  and that.76) see , we haveThe educational level in the present sample was as follows: 15 (2.9%) had no formal education, 73 (14.1%) had a primary-level education, 120 (23.3%) had not completed secondary school, 57 (11.0%) had completed secondary school, 186 (36.0%) had completed University Studies, and 65 (12.6%) had post-graduate studies.The percentage of at-risk participants  was 6.2% (32 out of 516).University and community participants were solicited using non-probabilistic convenience sampling techniques via an online survey format. A student-recruited sampling methodology was used following guidelines by Wheeler et al. , which aThe following well-validated measures were used.The Wong Law Emotional Intelligence Scale ; younger participants scored marginally significantly higher than older ones in ED symptoms and anxiety (ps < 0.10) and significantly lower in self-esteem (p <0.001). Therefore, sex and age were entered as covariates to control any potential confounding effects.After calculating descriptive statistics and computing the bivariate correlation between EI, self-esteem, anxiety, and ED symptoms, the SPSS macro PROCESS Hayes,  was usedDescriptive statistics, response ranges, normative data, reliability coefficients, and correlations among the study variables are presented in We examined whether the relationship between EI and ED symptoms was sequentially mediated by self-esteem and anxiety. Both age and sex were added as control variables. Results of the mediation analyses are presented in SE = 0.03; 95% CI = −0.15, −0.04). Second, anxiety was found to mediate the association between EI and ED symptoms [EI → Anxiety → ED symptoms] . Third, the sequential pathway of EI → Self-esteem → Anxiety → ED symptoms, was significant . Accordingly, higher levels of EI were serially associated with higher self-esteem, lower anxiety, and finally lower ED symptoms. Thus, the residual direct pathway between EI and ED symptoms was no longer significant . Therefore, self-esteem and anxiety fully mediated the link between EI and ED symptoms. This final serial mediation model was significant, accounting for 11% of the variance in ED symptoms .As shown in The present study examined whether self-esteem and anxiety, which previous literature confirm as relevant variables related to ED symptomatology, mediated the relationship between EI and ED symptomatology within a Spanish college student and community sample.The results of path analyses showed that self-esteem and anxiety play a fully sequential mediating role between EI and ED symptomatology, suggesting that EI was positively linked to higher self-esteem and lower anxiety, which in turn predicted lower levels of ED symptoms. The findings support the notion that EI decreases ED symptoms indirectly, suggesting that higher self-esteem and decreased anxiety may be possible underlying mechanisms through which emotional abilities contribute to reducing ED symptoms. These results are consistent with previous studies that found a mediating role for anxiety in the relationship between EI and ED  are more likely to have higher levels of self-esteem, which would lead to lower levels of anxiety, which in turn would lead to lower ED symptomatology. These findings open the door to future research concerning the role of emotional competences in ED symptoms; it might be fundamental to consider both levels of self-esteem and anxiety when working with adults who display both deficits in EI and ED symptoms. Also, this research supports the relevance of including training to improve EI skills, foster self-esteem, and reduce anxiety symptoms as a specific treatment for ED or even as additional components of the CBT-Eb.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 Research Ethics Committee of the University of Málaga (104-2020-H). The patients/participants provided their written informed consent to participate in this study.MP-F, JR-M, and NE created and organized the study. MP-F and JR-M collected the data. MP-F and NE analyzed the data, critically reviewed the manuscript, and provided constructive comments. JR-M wrote the first draft. MP-F wrote the reviewed draft. All authors contributed to the article and approved the submitted version.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.


Poor academic performance and failure can cause undesired effects for students, schools, and society. Understanding why some students fail while their peers succeed is important to enhance student performance. Therefore, this study explores the differences in the learning process between high- and low-achieving pre-clinical medical students from a theory of action perspective.n = 14) and low-achieving students (n = 5), enrolled in pre-clinical medical studies at the Universiti Malaya, Malaysia. Data were collected through reflective journals and semi-structured interviews. Regarding journaling, participants were required to recall their learning experiences of the previous academic year. Two analysts coded the data and then compared the codes of high- and low-achieving students. The third analyst reviewed the codes. Themes were identified iteratively, working towards comparing the learning processes of high- and low-achieving students.This study employed a qualitative instrumental case study design intended to compare two groups of students—high-achieving students (Data analysis revealed four themes—motivation and expectation, study methods, self-management, and flexibility of mindset. First, high-achieving students were more motivated and had higher academic expectations than low-achieving students. Second, high-achieving students adopted study planning and deep learning approaches, whereas low-achieving students adopted superficial learning approaches. Third, in contrast to low-achieving students, high-achieving students exhibited better time management and studied consistently. Finally, high-achieving students proactively sought external support and made changes to overcome challenges. In contrast, low-achieving students were less resilient and tended to avoid challenges.This study found four themes describing the differences between high- and low-achieving pre-clinical medical students: motivation and expectation, study methods, self-management, and flexibility of mindset.Based on the theory of action approach, high-achieving pre-clinical medical students are fundamentally different from their low-achieving peers in terms of their governing variables, with the positive governing variables likely to have guided them to act in a manner beneficial to and facilitating desirable academic performance.Governing variable-based remediation may help students interrogate the motives of their actions.Based on the theory of action, high-achieving students utilize positive governing variables, whereas low-achieving students are driven by negative governing variables. Hence, governing variable-based remediation is needed to help low-achieving students interrogate the motives behind their actions and realign positive governing variables, actions, and intended outcomes. Poor academic performance and failure are unfavourable outcomes that should be addressed as early as possible . A recenA comparison of high- and low-achieving medical students may elucidate effective and ineffective learning processes as these students represent the extreme ends of academic achievement –10. SeveSome scholars have qualitatively examined academic failure  and acadHow did the learning processes between high- and low-achieving students differ?In order to conduct an in-depth exploration of the learning processes of high- and low-achieving students, this study adopted a qualitative instrumental case study design . More spThis study was conducted at the Universiti Malaya, the oldest and highest-ranking public university in Malaysia, from September 2019 to July 2020. Ethical approval was obtained from the Universiti Malaya Research Ethics Committee (UM.TNC2/UMREC − 647), and written consent forms were obtained from all participants prior to the study.In Malaysia, medical education entails a five-year undergraduate program. Top performing high school graduates  typically enter medical school at the age of 19 or 20. Medical graduates are required to undergo mandatory two-year internships at public hospitals before obtaining their licences to practice medicine unsupervised. Gaining acceptance into the medical program is highly competitive. For admission to the Universiti Malaya, applicants are required to possess excellent high school examination results and perform well in both the BioMedical Admissions Test (BMAT) and multiple mini-interviews. Accordingly, the annual intake is approximately only 160 students, the majority of whom are 19 years old. The medical curriculum consists of two stages: a two-year pre-clinical medical stage and a three-year clinical stage. Additionally, curriculum content is horizontally and vertically integrated . Year 1 This study adopts a theory of action approach to examine the differences between high- and low-achieving first-year students at a Malaysian university. According to the theory of action approach, human actions are derived from mental variables that consciously or unconsciously govern respective actions ,25. ThesIn respect to academic success, the theory of action contends that positive governing variables  lead to positive actions (e.g. consistency in studying), resulting in intended outcomes (i.e. success). In contrast, negative governing variables  lead to negative actions (e.g. procrastination), resulting in unintended outcomes (i.e. failure) . AcademiBy identifying the positive governing variables and actions of high-achieving students and correcting the negative governing variables and actions of low-achieving students enrolled in medical education, this study provides insights for the design of interventions intended to enhance academic success among medical students .The selected medical school has pre-clinical assessments on the mastery of basic and clinical sciences knowledge (e.g. a written knowledge-based assessment and anatomy and pathology spot tests), clinical skills , public health (e.g. key feature questions), and professionalism (e.g. a reflective portfolio). The written knowledge-based assessment—that is, summative assessment—results are given as a numerical score, whereas the other types of assessment only indicate a satisfactory or unsatisfactory outcome. The written knowledge-based assessment consists of multiple-choice questions examining students’ understanding of normal and pathological human structures, functions, and behaviours relevant to a diagnosis, management plans, and the prevention of health problems in the integrated curriculum . Students who fail any assessment are required to repeat the entire academic year.This study selected cases based on assessment results for the 2019/2020 academic year. As students obtained satisfactory results in all assessments except the written knowledge-based assessment, cases were selected based on their performance in the knowledge-based assessment. This selection indicates that high achievement was confined to the cognitive domain. Based on their score in the written knowledge-based assessment, students were invited to a meeting at the beginning of the 2020/2021 year, where the researchers explained the aims, procedures, and measures of the study and ensured participant confidentiality.Following this process, 31 students who scored in the ninetieth percentile in the written knowledge-based assessment were identified as high-achieving students ,29 and ivia email and returned their completed reflective journals by replying to the sender, thereby ensuring confidentiality. Only the student support officer had access to these emails. All communications between individual students and the student support officer were private. Participants were allocated two weeks to complete their reflective journals.We collected data using reflective journals and semi-structured interviews. For the reflective journals, we used a Microsoft Word document template that contained a list of questions, with a text box provided for each question. The questions were designed according to Gibbs’ reflective cycle and intended to encourage participants to reflect on and describe their experiences in the previous academic year . Gibbs’ Following the submission of the reflective journals, semi-structured one-to-one interviews were conducted. Guided by the theory of action approach, interview questions were developed to investigate what (i.e. actions) students did in their previous academic year and why (i.e. governing variables) . The intReflective journals and interviews complemented each other. First, important questions were repeated across methods to verify students’ learning approaches . Second, the interviews sought further clarification on students’ responses in the reflective journals , thereby aligning the reflective journals and interviews.This study, including all data collection, was conducted in English. English is a compulsory subject in both primary and secondary education in Malaysia and is commonly used in daily communication. English is the medium of instruction in the medical program at the Universiti Malaya, with all students expected to be fluent in both written and spoken English.This study employed thematic analysis to examine data. The thematic analysis comprises a set of procedures to identify and describe patterns in the data . This stReflective journals and interview transcriptions were saved as Microsoft Word documents and imported into QDA Miner Lite 2.0, a free computer-assisted qualitative analysis software program for analyzing textual data. Using QDA Miner Lite 2.0, two analysts independently searched and coded “what did students do?” and “why did they do this?” for Year 1 high-achieving students. Discussions were held to compare the initial codes and solve discrepancies. Using the agreed-upon codes, the two coders subsequently coded Year 2 high-achieving students. Discussions were held again to verify that there were no newly emergent codes. An identical coding process was applied to analyze Year 1 and Year 2 low achieving students.a priori fixed and polarized notions that there will be differences. The two analysts identified eight corresponding patterns; for example, “better time management” among high-achieving students corresponded with “poor time management” among low-achieving students. Subsequently, related patterns were fitted into a theme; for instance, the two patterns of “time management” and “consistency in studies” were categorized under the theme of “self-management.” As participants’ responses in interviews/reflective journals exposed their identities as high- or low-achieving students, the data could not be blinded. Therefore, the third analyst reviewed the coding results to minimize bias. All excerpts were reviewed to ensure that there was no bias in the selection of quotes. The three analysts deduced that data saturation had been achieved as codes were repeated among participants, with low-achieving students noting that they should have taken the actions practiced by high-achieving students [Once all data were coded, the two analysts compared the codes of high- and low-achieving students. The two analysts were careful to avoid students . We usedstudents . Triangustudents .A total of 19 pre-clinical medical students participated in this study. These participants consisted of eight Year 1 students and eleven Year 2 students, the majority of whom were either 19 or 20 years old. Their demographics in terms of years of study, age, and gender are summarized in Data analysis produced four themes: motivation and expectation, study methods, self-management, and flexibility of mindset.High- and low-achieving students exhibited differences in terms of intrinsic motivation and academic expectations. In respect to intrinsic motivation, high-achieving students expressed an interest in medicine, finding the study of the human body and mysteries of medicine fascinating. In contrast, low-achieving students doubted their decision to pursue a medical degree, exhibited little to no interest in medicine, and admitted to feeling lost and aimless in their studies. Low-achieving students also expressed feeling frustrated after observing students from non-medical degree programs have more time to engage in social activities and considered their medical degree a barrier preventing them from enjoying their favourite activities.In terms of academic expectations, high-achieving students set higher expectations for themselves in terms of academic outcomes, such as aiming to obtain the Dean’s Award and graduating on time. In contrast, low-achieving students had lower expectations and simply wanted to pass their exams. During the interviews, low-achieving students mentioned the need to set higher academic expectations.High- and low-achieving students exhibited differences in their study methods, particularly in terms of planning their studies and their approach to learning. In regard to the former, high-achieving students planned their studies for upcoming weeks, including what they should prepare before attending classes and what to review after classes. By planning ahead, high-achieving students felt secure and calm ahead of classes or exams. In contrast, low-achieving students did not create systematic study plans ahead of time but acted according to their mood at the time. However, low-achieving students noted that they had prepared study plans for the 2020/2021 academic year, which helped them be more organized in their studies compared to the previous year.In respect to the learning approach, high-achieving students attempted to comprehend the medical content by relating different learning topics with one another. For instance, if they learned a pre-clinical topic, they endeavoured to associate it with clinical practices. They thus avoided merely memorizing the medical content without comprehensively understanding and exploring the reasoning behind the body function mechanism. In contrast, low-achieving students adopted superficial learning, typically feeling satisfied with simply skimming or scanning the lecture notes with no clear objective. They also admitted to skipping topics they found less interesting.High- and low-achieving students exhibited two differences in terms of self-management, namely, time management and consistency of studying. First, high-achieving students demonstrated better time management than low-achieving students, allocating an appropriate amount of time for studies, friends, family, and relaxation. In contrast, low-achieving students tended to procrastinate studying for examinations until the last minute. However, during the interviews, low-achieving students recognized their lack of time-management skills and were determined to avoid procrastinating going forward.In respect to consistency of studying, high-achieving students studied consistently and kept up with the topics discussed in classes. They also repeatedly reviewed their lecture notes to ensure that they were mastering the knowledge and ability to apply it in the future. Although low-achieving students attempted to study consistently, they eventually gave up when the content became challenging. Low-achieving students thus lacked consistency in studying and tended to prioritize enjoying themselves rather than studying.High- and low-achieving students exhibited two differences in the flexibility of their mindsets, specifically in terms of their exposure to vulnerability and willingness to seek support, and in their willingness to adapt to changes. First, when facing academic and emotional challenges, high-achieving students regularly turned to their peers and family members for support, who encouraged them to strive for better results. In contrast, low-achieving students were reluctant to show weakness to those around them, tending to believe that neither their family members nor peers would understand their struggles and potentially invalidate them. However, during the interviews, low-achieving students claimed to have changed their mindset regarding showing vulnerability and seeking support, acknowledging the importance of reaching out to family, friends, and lecturers when facing challenges. By seeking support from peers and lecturers, low-achieving students found themselves better equipped to face challenges in their studies.With respect to students’ willingness to adapt to change, high-achieving students recalled trying a variety of study methods until they identified the most suitable method for medical studies. In this regard, they noted changing their duration of the study, approach to revision, and use of technology to improve the effectiveness of their studying. In contrast, low-achieving students continued using the same study method despite realizing that it was ineffective. Low-achieving students appeared less resilient and more likely to avoid challenges.Based on the qualitative data from a small number of students, this study indicated that high-achieving students exhibited greater degrees of motivation and self-expectation, more effective study methods, better self-management, and more flexible mindsets compared to their low-achieving peers. These differences can be explained using a theory of action framework, which contends that positive actions increase the likelihood of attaining favourable academic achievements. This section discusses this study’s theoretical and practical implications, as well as its limitations.The findings of this study correspond with those of the existing literature. Like previous studies ,10,16,37Correspondingly, negative governing variables may have guided students to act in a way that negatively impacted their academic outcomes . SimilarThe similarity between the results of this study and those of previous research indicates similar characteristics of high- and low-achieving students across national contexts. Malaysian students are not alone in respect to the challenges of excelling in medical studies. As such, international collaboration and the sharing of resources between medical schools may prove invaluable to address this common issue.The findings of this study have important practical implications as they demonstrate the value of effective remediation for early-stage medical students underpinned by a theory of action approach. This result is particularly important insofar as remediation should be extensively mapped into a learning theory to ensure sound design . Indeed,More specifically, this study proposes governing variable-based remediation. Per via guiding or self-reflection on one’s actions.Through governing variable-based remediation, students can be taught to identify their own Negative Enabling Pathways and recognize the misalignment of negative governing variables and intended outcomes. They can subsequently work on developing a Positive Enabling Pathway to realign their governing variables and actions with their intended outcomes . Interrovia journaling and the interview helped these students shift from a Negative Enabling Pathway to a Positive Enabling Pathway. However, this postulation remains preliminary and requires further evidence. In this respect, interventions involving the application of governing variable-based remediation are needed to evaluate and further develop the model proposed by this study. Such remediation could provide guided steps to help students identify, reflect on, and correct their governing variables [In this study, several low-achieving students informed the interviewer that they had made some changes similar to the actions of high-achieving students. Arguably, the process of reflecting on their previous year ariables . Guided ariables  to suppoHowever, remediation is meaningless if students do not embrace it. In this study, the low achieving students failed to seek help when they needed it. This resistance to seeking help might be due to the effects of learned helplessness  and impoFirst, this qualitative instrumental case study was conducted at a single institution, indicating that the explanation illustrated in Second, differences in the learning process are not the only explanation for academic success or failure. While the determinants of academic performance are multifactorial ,40, thisThird, while one-time individual interviews were in-depth and practical, this may have condensed discussion of the learning processes that occurred over the year and overlooked some details. Future investigations should consider conducting follow-up interviews with participants.Fourth, case selection was confined to cognitive acquisition . The findings of this study do not explain students’ performance differences in other types of assessment, namely, attitudes and skills acquisition. Using similar methods to those employed in this study, future studies should consider investigating the differences in various types of assessment. Such research may prove useful in demonstrating the generalizability of differences between high- and low-achieving students in respect to the learning process.Fifth, low-achieving students were less responsive to participating in this study despite receiving the same presentation of the study’s aim and procedures and being assured that all data were confidential. This low participation rate may be attributable to the fact that low-achieving students tend to be unwilling to share their experiences and feelings due to low self-esteem . In imprFinally, to be empathic and ethical, researchers did not request that high- or low-achieving students justify their decision not to participate in the study. Future studies may wish to investigate reasons for refusing to participate in such research, as this could aid in developing a better engagement plan.Our study has several limitations as follows:Learning improvements for both high- and low-achieving pre-clinical medical students should be taken into consideration in order to review their governing variables, which, in turn, influence their learning processes. Furthermore, low-achieving pre-clinical medical students must interrogate the motives of their actions and realign their positive governing variables, actions, and intended outcomes.


Our first study objective was to describe event-level sexual risk and substance use trends among gbMSM. Our second study objective was to describe substances associated with event-level sexual risk. (2) Methods: Data come from the Momentum Health Study in Vancouver, British Columbia and participants were recruited from 2012–2015, with follow-up until 2018. Stratified by self-reported HIV status, we used generalized estimating equations to assess trends of sexual event-level substance use and assessed interactions between substance use and time period on event-level higher risk sex defined as condomless anal sex with an HIV serodifferent or unknown status partner. (3) Results: Event-level higher risk anal sex increased across the study period among HIV-negative/unknown  and HIV-positive gbMSM . Among HIV-negative/unknown gbMSM, event-level erectile drug use increased, while alcohol use decreased over the study period. Overall, interactions between substance use and time on higher risk anal sex were not statistically significant, regardless of serostatus. However, we found a number of time-specific significant interactions for erectile drugs, poppers, Gamma-hydroxybutyrate (GHB), crystal methamphetamine and ecstasy/MDMA use among HIV-negative/unknown gbMSM. (4) Conclusion: Significant differences in substance use trends and associated risks exist and are varied among gbMSM by serostatus. These findings provide a more comprehensive understanding of the effects of event-level substance use on sexual risk through longitudinal follow-up of nearly six years. Rates of sexually transmitted infections (STI) are rising in Canada and are highly concentrated among gay, bisexual, and other men who have sex with men (gbMSM) . FurtherSubstance use is a significant factor in influencing sexual risk-taking behaviors, such as CAS. Previous literature on substance use patterns among gbMSM indicates variability in different substance types and distinct classes of substances, such as club drug use, sex drug use and conventional drug use . A systeThe association between substance use and sexual risk relates to situational events, which are highly contextual and may vary in terms of substances used, partner characteristics, condom usage, and sexual acts. To address these limitations, various event-level approaches focusing on specific sexual encounters and substance use within highly restricted time periods before or during sex may provide nuanced understanding . A revieUsing event-level longitudinal data to measure STI sexual risk, our first study objective was to describe event-level sexual risk and substance use trends in Vancouver during treatment as prevention scale-up (TasP) over a six-year period . Our secData are from the Momentum Health Study, a prospective longitudinal, bio-behavioral study of gbMSM in Vancouver, British Columbia. Participants were recruited from February 2012 to February 2015 using respondent-driven sampling (RDS). RDS recruitment involved initial “seed” participants, who were recruited through community partner agencies and online advertisements on gbMSM social networking websites and apps. The full RDS methodology of our study has been published elsewhere . To be eThe primary outcome variable was higher risk anal sex, which was defined as any CAS with an HIV serodifferent or unknown status partner. Participants were asked to complete a “partner matrix” of a repeating set of questions about their last sexual encounter with each of up to five of their most recent sexual partners within the past six months (maximum of five partners). Sexual encounters that did not include anal sex were excluded in this analysis. Condom use was reported for each partner, and participants indicated their use/non-use as the receptive and insertive partner. Any form of CAS (receptive or insertive) was included in this analysis. The partner’s HIV serostatus was obtained by asking participants if they knew their partner(s)’s HIV status before having sex, what the partner’s status was, and how they knew their partner’s status (if they knew). From these, we determined if the partner’s serostatus was positive, negative, or unknown.The primary explanatory factors were time  and substance use. Time of event was assessed with a six-month period prevalence between study visits over the course of almost six years. Event-level factors were collected for each partner and reported sexual event. Participants indicated the number of male sexual partners, the number of months since they first had sex with each partner, and the number of times they had anal sex with each partner in the past six months (per act). Participants indicated the month and year of the last sexual event with each partner, which was used to conduct a change over time analysis. For each sexual event, participants indicated their anal sex positions , their level of certainty regarding their partner’s HIV status before sex, whether they expected they would have sex with this partner again, and whether they received any goods, money, drugs, or services in return for sex. Participants reported their own and their partner’s substance use in the two hours prior to and during each sexual event, which included any alcohol, cannabis, erectile drugs, poppers (amyl nitrate), crystal methamphetamine, GHB, and MDMA.Psychosocial variables included the HIV treatment optimism-skepticism scale  , the 11-Demographic variables included participants’ age, sexual orientation, race/ethnicity, annual income, education, residence, and relationship status. We also asked a series of potential HIV prevention or risk-reduction practices , PrEP usage, escort work and attending group sex events in the past six months. For HIV-positive gbMSM, we utilized the study linkage to the BC Centre for Excellence in HIV/AIDS’s Drug Treatment Program administrative database to assess treatment adherence and viral load .p-value <0.05. RDS weighting was not applied, given that the analysis is based on event-level data. We included post hoc lost-to-follow-up analyses (LTFU) in determining significant differences between participants who did not complete the study and our final sample. All analyses were conducted using SAS version 9.4 .We limited our analyses to the sexual-event level and stratified participants by self-reported HIV status. Generalized estimating equations (GEE) were used to construct hierarchical logistic regression models, adjusting for participant interdependence in the data (events within participants as main clusters and each visit as sub-clusters). We examined trends over time with higher risk anal sex and substance use. Furthermore, we also tested interactions for substances and time to assess whether their associations with higher risk anal sex significantly changed over the study period. Odds ratio per six-months are presented, and significance was assessed as a The median follow-up time for participants was 3.03 years. 549 HIV-negative/unknown gbMSM reported 8121 anal sexual events, of which 17.9% included CAS with a serodifferent or unknown status partner. Among the 213 HIV-positive gbMSM at baseline, 3454 anal sexual events were reported, of which 27.9% included CAS with a serodifferent or unknown status partner. Full descriptive statistics on the sample stratified by HIV status can be found in In our GEE, higher risk anal sex was significantly associated with greater use of poppers, erectile drug use, ecstasy/MDMA use, GHB use, and crystal methamphetamine use among HIV-negative/unknown gbMSM; only poppers use was significantly associated with greater odds of higher risk anal sex for HIV-positive gbMSM. Full results can be found in p = 0.009). We found event-level CAS increased over the study period , anal sex with HIV-negative partners increased over the study period , and anal sex with HIV-positive gbMSM increased over the study period . In relation to event-level substance use among HIV-negative/unknown gbMSM over the study period, event-level alcohol use decreased  , and erectile drug use increased  . Full results can be found in For trends among HIV-negative/unknown gbMSM, we found that higher risk anal sex events increased over time  . In relation to event-level substance use, we found that popper use decreased over time  . Full results can be found in For trends among HIV-positive gbMSM, our model found higher risk anal sex increased over time  , which may influence the use of substances, sexual behaviors, and the relationship between these. Fourth, we could not distinguish between medically prescribed erectile drugs and non-medically prescribed. However, the prevalence of recreational erectile drug use among gbMSM is high, and erectile drug use (regardless of the prescription) has been identified as an important indicator of sexual risk in existing literature ,40. FiftOur findings indicate that sexual risk is associated with event-level substance use, behavioral and psychosocial factors. These findings provide a more comprehensive understanding of the effects of event-level substance use on sexual risk among Canadian gbMSM through longitudinal follow-up. Moreover, future interventions must address increasing rates of sexual risk through continued education on STIs, increased access to safer sex materials, and continued preventative screening. Understanding the nuances of individual substances as well as polysubstance use will be beneficial in developing targeted interventions for substance-using gbMSM in managing sexual risk. By focusing on separate sexualized events with different partners and substances used, sexual risk programs can target strategies for reducing risk in certain scenarios and how individuals can apply this knowledge to future sexual events.


As one of the clinical triad in Huntington's disease (HD), cognitive impairment has not been widely accepted as a disease stage indicator in HD literature. This work aims to study cognitive impairment thoroughly for prodromal HD individuals with the data from a 12-year observational study to determine whether Mild Cognitive Impairment (MCI) in HD gene-mutation carriers is a defensible indicator of early disease. Prodromal HD gene-mutation carriers evaluated annually at one of 32 worldwide sites from September 2002 to April 2014 were evaluated for MCI in six cognitive domains. Linear mixed-effects models were used to determine age-, education-, and retest-adjusted cut-off values in cognitive assessment for MCI, and then the concurrent and predictive validity of MCI was assessed. Accelerated failure time (AFT) models were used to determine the timing of MCI , and dementia, which was defined as MCI plus functional loss. Seven hundred and sixty-eight prodromal HD participants had completed all six cognitive tasks, had MRI, and underwent longitudinal assessments. Over half  of the participants had MCI at study entry, and half of these had single-domain MCI. Compared to participants with intact cognitive performances, prodromal HD with MCI had higher genetic burden, worsened motor impairment, greater brain atrophy, and a higher likelihood of estimated HD onset. Prospective longitudinal study of those without MCI at baseline showed that 48% had MCI in subsequent visits and data visualization suggested that single-domain MCI, two-domain MCI, and dementia represent appropriate cognitive impairment staging for HD gene-mutation carriers. Findings suggest that MCI represents an early landmark of HD and may be a sensitive enrichment variable or endpoint for prodromal clinical trials of disease modifying therapeutics. It is well-known that Huntington's disease (HD) manifests as a triad of clinical symptoms ; however, its diagnosis continues to rely primarily on the presence of motor impairment . Along wMild cognitive impairment (MCI) has been used to describe individuals who experience cognitive difficulties greater than expected for their age but who fall short of a diagnosis of dementia. It has generally been reported that individuals with MCI progress to dementia more rapidly than their cognitively intact peers –10. DespHTT gene  to enroll in formal clinical trials . HoweverHTT gene , there iOur analysis relies on PREDICT-HD, which is an observational study with a large cohort of individuals with the gene mutation for HD who were clinically determined to be free of motor diagnosis at study entry based on traditional motor criteria. There are two main goals of this study: the first is to classify the gene-expanded individuals as either having MCI or not based on the controls (not gene-expanded) and to examine the extent to which the classification is valid; the second goal is to estimate the timing of MCI and construct a model for the evolution of cognitive impairment over time, from cognitively-intact to MCI to dementia. The results will be informative for evaluating the extent to which MCI in HD gene-mutation carriers is a defensible indicator of early disease potentially appropriate as an endpoint in preventive trials.n = 8) through 2017. All individuals enrolled in PREDICT-HD had independently undergone predictive testing for HD and know their genetic finding. All study participants underwent annual evaluation.The PREDICT-HD study was a 12-year prospective observational study at 32 sites in six countries  from September, 2002 to April, 2014. The study recruited a total of 1,155 HD gene-expanded individuals and 317 controls (not gene-expanded) individuals who were mainly family members of the gene-expanded individuals. The gene-expanded individuals (CAG length >35) previously underwent independent genetic testing for the HD gene-expansions, and had diagnostic confidence level (DCL) ratings of the Unified Huntington's Disease Rating Scale (UHDRS) <4 at the study entry. Ancillary studies supported continuation of this research at a reduced number of sites  and is shared in dbGaP.Ethical standards were reviewed at the primary grant institution and all participating sites. All participants signed a written informed consent allowing data sharing for future research. The multi-site research study is identified on Since cognitive assessment was comprehensive in the PREDICT-HD study, we used previous findings to choose a smaller discrete set of cognitive tasks. Harrington et al.  conducteMRI acquisitions were collected using high resolution anatomical MR images at 32 collection sites (53 unique scanners) using General Electric, Phillips, and Siemens scanners with field strengths of 1.5 T (Tesla) or 3 T. T1 images at each site were obtained using three-dimensional (3D) T1-weighted inversion recovery turboflash (MP-RAGE) sequences. Each imaging data set was processed through data processing pipelines optimized for data harmonization across multiple sites (BAW-REF) (BAW-REF) . The fulBAW-REF) , 27, andBAW-REF) .Genetic burden was defined using the CAG repeat length by age product, or CAP (0) for each individual research participant, i.e., CAP = Age0 × (CAG-−33.66). Thus, individuals with higher genetic burden/CAP scores are statistically nearer to motor diagnosis  from the UHDRS  who scored each research participant on the UHDRS Diagnostic Confidence Level (DCL) . DCL ranTotal Functional Capacity (TFC) is a type of activities of daily living scale from the UHDRS. Specifically, the TFC is a clinician-rated measure of functional capacity based on a standardized interview with the participant and available family members of current independent functioning in these domains: finances, driving, living independently, bathing, feeding, and walking. The scale ranges from 1 to 13 and any loss in independence is considered abnormal for persons without disability.The analysis consisted of three steps, the first being the classification of gene-expanded individuals as MCI performed at each visit, the second step was to use MCI status at baseline to predict the timing of HD onset, the third step was to demarcate stages in longitudinal cognitive decline. For the first step, a control-referenced (or norm-referenced) approach to MCI classification was used, which is in the same spirit as in the general approach often used in Alzheimer's , Parkinst-test for continuous variables and chi-square tests for categorical variables. At study entry, brain atrophies for prodromal HD participants in terms of percentage loss of brain volume were compared to the mean of control individuals. Several structures were considered, including caudate, putamen, globus pallidus, total gray matter, total white matter, and 95% confidence intervals were estimated. For all the comparisons, the significance level was set at 0.05.As a check on the validity of the classification, for each cognitive domain several baseline variables were compared between individuals with MCI and those who were cognitively intact. Comparisons of baseline variables were conducted using The second step in the analysis was to formulate a prediction model for examining the ability of MCI status at baseline to predict the timing of the HD onset indicated by motor diagnosis, adjusting for covariates. All 1,155 gene-expanded individuals were used for the analysis. MCI status at study entry was coded into one of three impairment levels: 0-No; 1-Yes; 2-unknown, with the latter being due to missing observations. Flexible accelerated failure time (AFT) models with interval-censored  observatThe third and final step was to stage the cognitive impairment for each prodromal HD individual, based on the following taxonomy assumed to be ordered in time. Cognitively-intact: no evidence of MCI or other cognitive impairment; MCI-Single: MCI classification in only one cognitive domain; MCI-Duo: MCI classification in two cognitive domains; MCI-Multiple: MCI classification in three or more cognitive domains; dementia (DM): HD-specific dementia defined as MCI classification in any domain with at least a one-point loss on the TFC. For each interval-censored stage of cognitive impairment , we fitted a Weibull AFT model for the onset age using both CAG and CAG  as predininds-dac@mail.nih.gov.All data, including raw and processed images, are provided in dbGaP PREDICT-HD Huntington's Disease Study: p <0.0001) than the HD gene-expanded individuals with a mean age 44.1 years  and received comparable education with a mean education year 14.9 years , though statistically different at level 0.05 (p = 0.012) due to large sample size. 64.8% and 98.9% of the control individuals were women and white, respectively, which were not statistically different from the gene-expanded individuals at level 0.05.In the PREDICT-HD study, the HD gene-expanded individuals had a mean age 39.9 years , a mean education year 14.5 years , 64.4% were women, and 97.1% were white. The control individuals were statistically a little older (p = 0.014) had a statistically significant effect and contributed to prediction of HD onset above and beyond genetic burden (CAP) and motor abnormality (TMS).For the prodromal HD individuals who were cognitively intact at baseline, 343 had follow-up observations for cognitive assessments. Among them, 48% were classified for having MCI during follow-up: 92 showed single domain MCI, 31 showed MCI in two domains and 40 had MCI in three or more cognitive domains see .Cognitive impairment has long been documented among individuals with prodromal HD , 35, 36.As a whole, our results provide biological and prognostic validity for MCI in prodromal HD. For our sample, MCI was prevalent at baseline, affecting more than half the sample. Furthermore, for those who did not have MCI at baseline, about half were classified as MCI over time. Longitudinal MCI trends suggest that gene-expanded individuals start with single-domain MCI, then develop multiple-domain MCI and eventually dementia.The supporting evidence for the MCI classification at baseline is compelling. Compared with cognitively intact prodromal HD individuals at study entry, brain atrophy was significantly worse among those who showed MCI in any of six domains. The results of brain atrophy reference to the control group shown in These findings have clinical and research implications for individuals at HD risk. First, our results support the viewpoint that MCI should be recognized as a clinically important early landmark event in the course of HD parallel to its importance in both Alzheimer's and Parkinson's diseases. Early clinical identification of MCI can facilitate future planning for individuals with HD and their families. Second, while MCI has largely been used as a means for identifying a population to enroll in clinical trials for Alzheimer's disease, the high prevalence of MCI among prodromal HD individuals and the significant biological and prognostic validity for HD diagnosis suggest that MCI has potential value as a study endpoint in clinical trials for disease modification. Finally, MCI may prove an enrichment strategy for the design of clinical trials. For example, utilizing the presence or absence of MCI within a cohort of individuals with prodromal HD could seek to reduce heterogeneity within a prodromal sample and further clarify the probable nearness to clinical onset of motor symptoms and thus formal diagnosis of HD.n = 915) with the Mayo Clinic Study of Aging  suggested that though dementia incidence rates were similar across studies, heterogeneity was observed in hazard ratios and positive predictive values across cognitive domains .Publicly available datasets were analyzed in this study. This data can be found at: National Center for Biotechnology Information (NCBI) dbGaP, ClinicalTrials.gov Identifier: NCT00051324, Neurobiological Predictors of Huntington's Disease (PREDICT-HD). The patients/participants provided their written informed consent to participate in this study.The studies involving human participants were reviewed and approved by Ethical standards were reviewed at the primary grant institution and all participating sites. All participants signed a written informed consent allowing data sharing for future research. The multi-site research study is identified on YZ and JP conceived and designed the study. YZ, JZ, and JP acquired, analyzed, or interpreted the data, and drafted the manuscript. CG, JL, HJ, VM, DS, and KS provided critical insights on intellectual content and important revision of the manuscript. YZ and JZ conducted statistical analysis. JP and YZ obtained funding to conduct this study. All authors contributed to the article and approved the submitted version.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.