The occurrence of atrial fibrillation (AF) represents clinical deterioration in acutely unwell patients and leads to increased morbidity and mortality. Prediction of the development of AF allows early intervention. Using the AmsterdamUMCdb, clinically relevant variables from patients admitted in sinus rhythm were extracted over the full duration of the ICU stay or until the first recorded AF episode occurred. Multiple logistic regression was performed to identify risk factors for AF. Input variables were automatically selected by a sequential forward search algorithm using cross-validation. We developed three different models: For the overall cohort, for ventilated patients and non-ventilated patients. 16,144 out of 23,106 admissions met the inclusion criteria. 2,374 (12.8%) patients had at least one AF episode during their ICU stay. Univariate analysis revealed that a higher percentage of AF patients were older than 70 years (60% versus 32%) and died in ICU (23.1% versus 7.1%) compared to non-AF patients. Multivariate analysis revealed age to be the dominant risk factor for developing AF with doubling of age leading to a 10-fold increased risk. Our logistic regression models showed excellent performance with AUC.ROC > 0.82 and > 0.91 in ventilated and non-ventilated cohorts, respectively. Increasing age was the dominant risk factor for the development of AF in both ventilated and non-ventilated critically ill patients. In non-ventilated patients, risk for development of AF was significantly higher than in ventilated patients. Further research is warranted to identify the role of ventilatory settings on risk for AF in critical illness and to optimise predictive models. Atrial Fibrillation (AF) is the commonest arrhythmia worldwide and increases the risk of stroke and heart failure . AF is cLarge repositories of Electronic Health Records have been used to develop risk prediction for AF in the general population using machine learning algorithms. A recent risk prediction model, developed for the general population, the CHARGE-AF (The Cohorts for Heart and Aging Research in Genomic Epidemiology AF) score, predicts an individual’s 5-year risk of new AF using clinical variables including age, ethnicity, height, weight, blood pressure, medication and comorbidities . Due to In addition, risk factors for developing AF in the general population compared to critically ill patients may vary substantially. Traditional risk factors associated with AF in the community include structural and valvular heart disease, neither of which is clearly related to AF in critical illness . In addiOver the last decade, the use of various modelling techniques for AF has grown exponentially  and inclTo date models focusing on prediction and detection of AF are mainly based on data from the Medical Information Mart for Intensive Care (MIMIC) III database, which comprises data obtained in a single large tertiary care centre in the United States. So far, European databases have not been used to identify risk factors or to construct prediction models for AF in critical illness. The Amsterdam University Medical Centers Database (AmsterdamUMCdb), endorsed by the European Society of Intensive Care Medicine (ESICM), is the first freely accessible European intensive care unit (ICU) database .Here we present a logistic regression model for the prediction of AF in critical illness using the AmsterdamUMCdb database . In addiWe used data from the AmsterdamUMCdb, a freely available database, accessible after completing the mandatory training and guaranteeing the involvement of a practising intensivist in the research team to provide domain expertise. The database contains data from a 32-bed mixed surgical-medical academic ICU and a 12-bed high-dependency unit (medium care unit) . For patAdmissions with more than 35% missing data were excluded from the analysis. In the remaining cases, missing data for numeric variables were imputed with the median of the corresponding variable, and for categorical variables, they were imputed with the mode. Admissions and variables with dynamic features were converted into tabular representations by extracting their means.Patients were considered to have been ventilated if they were explicitly recorded in the database as having been ventilated, i.e., patients that have associated an item in table “processitems” indicating ‘Ventilate’. In addition, patients that did not have an explicit record in the “processitems” table of having been ventilated, but had O2 concentration or FiO2 records associated with their admission, were also classified as ventilated. This definition includes patients receiving invasive and non-invasive ventilatory support.The outcome to be predicted in this model was the first documented episode of AF in patients admitted to ICU in sinus rhythm. As a previous history of AF is not coded in the AmsterdamUMC database, this outcome does not discriminate between new onset and pre-existing AF.For univariate analysis, medians and interquartile ranges were calculated for continuous variables and frequencies and proportions for categorical variables. Differences between AF vs. non-AF patients were assessed using Kruskal-Wallis rank sum and Chi-square tests. Acute Physiology And Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores were calculated upon admission to ICU.0,…,βK} are the logarithms of the OR, which are estimated by maximum likelihood  to elucidate associations, in the form of odds ratios (OR), between the factors and the occurrence of AF. LR models the outcome probability or risk to be ‘1’ (positive class) as kelihood .k≠0=0), and in each step, the variable that most improves the performance on the validation set is added , e.g., for albumin and calcium, only calcium was selected. Subsequently, pairwise correlations between variables were calculated to verify that the variables included in the study were not highly collinear (above 0.7 using Pearson correlation). Relevant input variables were automatically selected using a sequential forward search algorithm using 3-fold cross-validation. The selection algorithm starts with a baseline model  curve. We report AUC means and confidence intervals (CI) for the full patient cohort, and ventilated and non-ventilated patients separately. Due to the class imbalance in the datasets, we also produced precision-recall curves to evaluate the three models developed. Their baselines were determined by the ratio of positives (P) and negatives (N) as y = P / (P + N) .R version 3.6.3 was used for all analyses.From a total of 23,106 admissions extracted, patients < 18 years of age, multiple admissions and cases with > 35% missing data were excluded, resulting in 18,518 analysable cases, of which 2,374 were patients with AF patients, while 16,144 had no episodes of AF reported . A totalUnivariate statistical comparisons between AF and non-AF groups of patients are displayed in The developed models were able to predict the first occurrence of AF in patients admitted to critical care in sinus rhythm for all the patients in the selection group, and specifically in ventilated and non-ventilated patients, with AUC performances of 0.836 (CI: 0.833–0.838), 0.820 (CI: 0.818–0.823) and 0.912 (CI: 0.883–0.942), respectively. Additionally, the performance of disease severity scores (APACHE II and SOFA) was compared to the developed model (results in The odds ratios (OR) for the total cohort, and the ventilated and non-ventilated patients are presented in Despite an increasing number of publications about AF in critically ill patients, its precipitants in this population are poorly understood. In this research, we identify modifiable and non-modifiable risk factors to build a logistic regression model for the prediction of a first episode of AF during admission to ICU. We analyse data from the AmsterdamUMCdb, which contains a total of 23,106 ICU admissions. Previous prediction models for AF in critical illness  are baseIn this research, we calculate the means of time series of vital signs, laboratory results and respiratory data to build an LR model for the development of the first episode of AF in patients admitted to ICU with documented sinus rhythm. Depending on ventilation status, our model achieved very good to excellent performance measures with an AUC of 0.82 in ventilated and 0.912 in non-ventilated cohorts. The precision-recall curves  also supSince the occurrence of AF in critical illness is associated with disease severity, we used established critical care risk scores, such as APACHE II or SOFA, calculated on admission to ICU, for comparison. Our model performed significantly better in all cohorts. This may be partly explained by the limited number of variables included in the conventional risk prediction scores APACHE II and SOFA. Furthermore, the use of time series may improve model performance as dynamic changes are considered. In conclusion, while well established for mortality prediction, APACHE II and SOFA on admission are not suitable to predict AF in ICU and more specific scores are needed to identify patients at risk before the clinical onset of this arrhythmia which has repeatedly been associated with higher mortality , 28.We have identified increasing age as the most important predictor of the development of AF in our analysis. Advancing age has been known as a risk factor for AF in the general population for several decades . Within While acute respiratory failure has been recognised as a risk factor for AF in several studies , 15, it Our study has several limitations. We performed internal cross-validation, but external validation of our model is required for generalisability across different ICU databases and before clinical implementation can be pursued. Additionally, missing data were imputed with the median/mode, which is a simple and computationally rapid approach. Alternatively, missing data imputation methods such as regression-based imputation or multiple imputation by chained equations (MICE) could be considered.Our model was built to predict new episodes of AF in patients admitted to critical care in sinus rhythm. Insufficient information was available in the database regarding the previous medical history of paroxysmal or pre-existing AF. Thus, our model cannot predict new-onset AF, as patients with a known diagnosis of AF may also present in sinus rhythm on admission and develop episodes of AF later in their stay. Finally, in addition to the requirement for models differentiating between ventilation modes, further targeted models for individual ICU subpopulations are required, e.g., patients with sepsis, as they may display a different risk profile.Within the AmsterdamUMC database, several variables are presented as ranges only, e.g., age, weight and height. This limits the analyses that can be performed. For example, it was impossible to calculate Body Mass Index, which is why weight and height had to be considered as separate variables in our model.In addition to the requirement for specific models for mechanically ventilated patients, further targeted models for individual ICU subpopulations such as septic patients are required, as they may display a different risk profile.We present a logistic regression model for risk prediction of new episodes of AF in critical illness using the AmsterdamUMCdb database. Our model demonstrates very good performance in ventilated patients and excellent performance in non-ventilated patients. Further work is required to exploit the potential that different ML methods to model risk prediction for new episodes of AF in various cohorts of critically ill patients.https://amsterdammedicaldatascience.nl/#amsterdamumcd.Publicly available datasets were analyzed in this study. This data can be found here: Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.SO-M and MP extracted and prepared the data. SO-M, IO, and MP conducted the analysis and evaluated the results. IW and BJ provided the clinical expertise and wrote the first draft of the manuscript. All authors were involved in the study design, the selection of relevant variables from the dataset, contributed to the writing, reviewing and editing, and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This study investigated the association between relative hand grip strength (HGS) and glycemic status, such as impaired fasting glucose (IFG) and diabetes, using data from the Korea National Health and Nutrition Examination Survey (KNHANES).We performed a cross-sectional study using the data from the KNHANES of 27,894 individuals from 2014 to 2019. Relative HGS was defined as the absolute HGS divided by body mass index and divided into quartiles in men and women. Odds ratios (OR) for diabetes and IFG were calculated using multivariate logistic regression analysis. All analyses were stratified by sex, and subgroup analysis was age-stratified.P for trend <0.001). ORs and 95% CI of the lowest relative HGS quartile for diabetes were higher in the younger age group than that of the older age group . ORs and 95% CI for IFG was similar with the trend of ORs for diabetes .The lowest relative HGS quartile had a significant increase in the risk for diabetes  and IFG . The ORs for diabetes and IFG according to the decreasing quartiles of relative HGS gradually increased in both sexes (Lower relative HGS was associated with a higher risk of not only diabetes but also IFG in both sexes. These trends were stronger in younger adults than in older adults. Insulin resistance is a preceding finding in individuals with prediabetes and type 2 diabetes mellitus (DM). Inflamed and dysfunctional adipocytes from the fat tissue is known to be the basis of development of insulin resistance during the initial stages of the disease, which simultaneously initiate or exacerbate insulin resistance in the muscle and liver . The skeHandgrip strength (HGS) is a simple and reliable tool for measuring the maximum voluntary force of the hands, and it is an indicator of the muscle quality that reflects muscle strength and muscle mass . Low HGSIndividuals with prediabetes have abnormal carbohydrate metabolism, but their glucose levels do not meet the criteria for diabetes, which is an important clinical entity in terms of risk factors for progression to diabetes and cardiovascular disease . RecentlThe KNHANES is a nationwide cross-sectional survey performed annually using a stratified, multistage probability sampling method, and is representative of the general Korean population. We analyzed data from 2014 to 2019, which were included in the sixth, seventh, and eighth KNHANES, and when the HGS values were examined in these health examination surveys ,35. Of tThe KNHANES was approved by the Institutional Review Board of the Korea Centers for Disease Control and Prevention, and all participants provided written informed consent. The study protocol was approved by the Institutional Review Board of the Pusan National University (IRB no. 05-2022-111).Data from the KNHANES comprised health interviews, health examinations, and nutrition surveys. Sociodemographic factors and medical history were assessed through health interviews, including self-reported questionnaires, and personal interviews with trained staff, which included questions on household income level, education level, smoking status, amount of alcohol intake, physical activity, and past medical history. The smoking status was classified into three groups, i.e., never smokers, ex-smokers, or current smokers on the basis of lifetime smoking status. Never smokers were defined as those who had never smoked or had smoked <5 packs of cigarettes in their lifetime. Ex-smokers were defined as those who smoked ≥5 packs of cigarettes in their lifetime and were not presently smoking at the time of the survey. Current smokers were defined as those who had smoked ≥5 packs of cigarettes in their lifetime and were presently smoking at the time of the survey. Alcohol consumption status was classified into three groups: nondrinkers, light drinkers (<30 g/day), and moderate-to-heavy drinkers (≥30 g/day) on the basis of the amount of alcohol per day. Physically active subjects were defined as individuals who performed ≥150 min of moderate-intensity activity or ≥75 min of vigorous intensity activity per week. In the KNHANES data, household income was divided into sex- and age-specific quartiles of low, middle-low, middle-high, and high based on equalized household income, which was calculated by dividing the monthly household income by the square root of the number of household members. We recategorized the quartiles into tertiles by combining the middle-low and middle-high quartiles into the middle tertile.2). Waist circumference (WC) was measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest during exhalation. Blood pressure (BP) was measured using a standard mercury sphygmomanometer after resting for 5 min in the sitting position. Systolic and diastolic BP were the average of the last two values among the three repetitive measures at 5-minute intervals.Trained nurses performed anthropometric measurements. BMI was calculated as weight (kg) divided by height squared , triglyceride, and high-density lipoprotein (HDL) cholesterol levels were measured using a Hitachi 7600 Automatic Analyzer . HbA1c levels were analyzed using G8 automated high-performance liquid chromatography .The KNHANES included HGS testing in 2014 to assess muscle strength . A digitDiabetes was defined as the presence of any of the following findings: FPG level ≥126 mg/dL, an HbA1c level ≥6.5%, self -reported physician’s diagnosis of diabetes, or current use of anti-diabetic medications . IFG wasWe performed a complex sample analysis considering the stratified multistage probability sampling design of the KNHANES. We used integrated weights from 2014 to 2019 for the analysis. The relative HGS was categorized into the following quartile groups: Q1 (lowest group), Q2, Q3, and Q4 (highest group). Because of sex-specific differences in relative HGS, all analyses were performed separately for men and women. The baseline characteristics of the participants were compared using the complex sample generalized linear model for continuous variables and complex sample crosstab analysis for categorical variables. Data are presented as weighted means or percentages with standard error (SE) for continuous and categorical variables, respectively. We used weighted linear regression analysis to determine an age-adjusted association between relative HGS and continuous variables. The odds ratios (ORs) and 95% confidence intervals (CI) for diabetes or IFG were calculated using the weighted logistic regression analysis. We used the rms package in R  to draw the restricted cubic spline curve of the ORs for diabetes and IFG. In addition, we conducted subgroup analysis according to age . A two-tailed P value of <0.05 was considered statistically significant. SPSS version 24  was used for all the calculations and analyses.P <0.001), whereas HDL cholesterol level and absolute HGS showed a positive correlation with relative HGS (P <0.001).A total of 12,246 men and 15,648 women were enrolled in this study. The relative HGS for men were as follows: Q1, 0.459–2.808; Q2, 2.809–3.240; Q3, 3.241–3.686; and Q4, 3.687–6.312. For women, they were as follows: Q1, 0.406–1.680; Q2, 1.681–2.021; Q3, 2.022–2.361; and Q4, 2.362–4.129. The baseline characteristics of men and women according to relative HGS are presented in Tables P for trend <0.001). When the relative HGS value decreased by 1, the risk of diabetes was significantly increased in both men  and women . Considering the median of relative HGS  as the reference value, as the relative HGS increased, the risk of diabetes decreased, and as the relative HGS decreased, the risk of diabetes increased in both sexes  . CompareIn this cross-sectional study, using the representative national data from KNHANES, from 2014 to 2019, we found that the groups with lower relative HGS reported higher ORs not only for diabetes but also for IFG in both the sexes. As the quartile of relative HGS decreased, the ORs for diabetes and IFG gradually increased for both the sexes. Additionally, considering the median relative HGS  as the reference value, increased relative HGS was associated with a lower risk of DM and IFG, whereas decreased relative HGS was associated with a higher risk of DM and IFG. Furthermore, we observed that the relationship between relative HGS and glycemic status was more prominent in the younger age group than in the older age group.A number of previous studies investigated the association of HGS, as a proxy for muscle strength with diabetes; however, the results have been conflicting. Some studies showed that HGS is inversely associated with type 2 DM ,37–42 whGrip strength is inversely associated with serum glucose levels in a linear regression model in several studies ,17,19,46The pathophysiological mechanism underlying the relationship between muscle strength and glycemic status is not fully understood, but several explanations have been suggested. Increased skeletal muscle strength because of exercise training contributes to improved insulin action, glucose disposal, and enhanced muscle glycogen storage by increasing skeletal muscle GLUT4 expression . SkeletaThe use of allometric scales for removing the body size effect in HGS has been proposed, and Neto et al. suggested that body height is the best body size variable for normalization of HGS among older adults . RecentlIn this study, we showed that groups with a lower relative HGS were associated with a higher risk of diabetes and IFG in both men and women. Furthermore, we conducted a subgroup analysis stratified by age, which is the most important factor influencing glycemic status and HGS. Chun et al. investigated grip strength measures according to age group in Koreans . They shThis study had certain limitations. First, we used cross-sectional data, and therefore could not clarify the causal relationship. Although we demonstrated that the FPG and HbA1c levels had a significant inverse correlation with relative HGS, we could not exclude the effect of antidiabetic agents on grip strength in patients with diabetes. Second, we could not evaluate the glycemic status of impaired glucose tolerance because the KNHANES conducted between 2014 and 2019 did not investigate the 75 g oral glucose tolerance test. Although prediabetes can be defined by FPG, 2-hour glucose levels after a 75 g oral glucose tolerance test, and HbA1c ; we chosIn conclusion, a lower relative HGS was associated with a higher risk of not only diabetes but also IFG in both the sexes. In addition, this relationship was more prominent in the younger age group. On the basis of our study findings, we suggest that both, increasing HGS and decreasing BMI, intensify the protective effect of IFG and diabetes, and this protective effect is more pronounced in young adults than in older adults. Further studies are required to clarify the causal relationship and the pathophysiology underlying this relationship.


Klinefelter syndrome (KS) is a common cause of non-obstructive azoospermia (NOA). Advances in fertility preservation (FP) techniques, such as the use of microdissection testicular sperm extraction (micro-TESE), have improved sperm retrieval rates (SRR) up to 40–50% in this population. Age has been suggested to have an impact on FP, postulating that sperm production may deteriorate over time due to germ cell loss. As such, sperm retrieval for patients with KS at a younger age has been proposed to further improve SRR; however, whether such practice pragmatically improves SRR is yet to be determined, and controversy remains with concerns over trauma caused by FP procedures on further impairment of testicular function. There has also been a debate on the ethics of performing FP procedures in the pediatric population. Optimizing FP for patients with KS invariably requires a holistic multidisciplinary approach. This review aimed to evaluate the latest evidence in performing FP in pediatric patients with KS, and discuss the controversy surrounding such practice. Hormonal changes in patients with KS during childhood and the use of hormonal manipulation to optimize SSR in this population have also been reviewed. Klinefelter Syndrome (KS) is a chromosomal disorder in which there is at least one extra X chromosome when compared with the normal male karyotype of 46, XY. It has an estimated prevalence of 1 in 500–600 males, with approximately two-thirds diagnosed in adulthood at a mean age of 27.5 years , accounting for ~10% of all patients with azoospermia . As suchThe current focus of pediatric KS treatment surrounds targeting endocrine deficits to improve growth, muscle mass, and prevent delayed puberty. Recent investigations in patients with KS and NOA have demonstrated a time-sensitive pattern of germ cell depletion, suggesting younger age is a potential positive predictor of success in sperm retrieval . The rolThe endocrinology of men with KS is typically recognized by a hormone profile of high serum follicle-stimulating hormone (FSH), low luteinizing hormone (LH), and low testosterone levels; however, various significant changes occur from birth to adulthood that impacts spermatogenesis in patients with KS.During early development in males with KS, the first peak of testosterone occurs at “mini-puberty,” which involves the activation of the hypothalamus-pituitary-gonadal axis within the first 3–6 months of life. During this time, testosterone, FSH, and LH levels can reach pubertal or even adult levels; however, there is contrasting evidence on whether testosterone levels are comparatively lower inpatients with KS during mini-puberty to healthy males, suggesting a role of Leydig cell dysfunction occurring early in childhood , but a rin-situ hybridization (FISH) study in 10 patients with KS   with KS . Surgica with KS –18.n =11) (n = 2) (n = 4)  , in 4.2% (n = 2) , in 7.7% (n = 4) , and in  (n = 4) , 23. The (n = 4)  of eightSurgical retrieval remains the most utilized and reliable method of retrieving sperm in patients with KS.Conventional testicular sperm extraction (cTESE) was used prior to the late 1990s for harvesting sperm in patients with KS, where testicular parenchyma is biopsied through incisions in the tunica albuginea to obtain random seminiferous tubule specimens to search for sperm; however, this technique was disappointing, with reported SRR of only 25 to 40% . Postulavia TESE in a pediatric setting was first reported in 2001 by Damani et al. (p < 0.01). Although these results appeared to be encouraging, available literature investigating FP in young patients with KS has limited sample sizes, and the reported wide range of SRRs is likely due to variation in testosterone pre-treatment, mosaicism/non-mosaicism, and level of testicular dysfunction. As such, no current guidelines exist on optimal timing for FP in KS.Sperm retrieval i et al. , who suci et al. . Unlike i et al. . Early Fi et al. . This isi et al. . Bryson i et al.  conducteOn the contrary, several studies showed low or comparable SRRs in young men with KS. Plotton et al.  used spein vitro spermatogonial stem cell (SCC) propagation and auto-transplantation has been explored recently to provide another means of treating patients with KS and NOA. A meta-analysis  in response to LH are critical for spermatogenesis. Normally, endogenous testosterone directly inhibits GnRH and LH release at the hypothalamus and pituitary levels, leading to downstream attenuation of testosterone production ; howeverTestosterone supports the development of secondary sexual characteristics, adequate bone mass, and improved muscle strength. Furthermore, testosterone therapy has been shown to have an important role in reducing the risk of cardiovascular diseases and metabolic syndrome in patients with KS ; howeverp = 0.98). Alternatively, Schiff et al. (n = 5) who had previously been treated with exogenous androgens and to obtain the return of spermatogenesis after testosterone, patients may require a washout and recovery period of years. It has been reported that the median time to recover normal sperm production of 20 × 106 ml−1 sperm after discontinuation of testosterone therapy is between 3 and 6 months, with recovery in 100% of men at 24 months  or 14–16 years (37%) , though Other types of medications can be used to increase endogenous and, in particular, intratesticular testosterone production to stimulate spermatogenesis. The human chorionic gonadotropin (hCG) acts by stimulating partially functioning Leydig cells and increase testosterone production. Long-term use of hCG alone can induce spermatogenesis in a high percentage of patients but further improvement is generated with the addition of FSH. In studies performed in men with hypogonadotropic hypogonadism, trials of hCG alone (given for 14–20 months) resulted in the induction of spermatogenesis in 70%  and 50% Choice of TRT modality, administration, timing, hormone target levels, and monitoring are therefore important factors affecting FP outcomes. Further investigation into these therapies to improve spermatogenesis could be evaluated in a pediatric setting to maximize FP potential.Special considerations need to be made for the ethical and psychological aspects of exploring FP in childhood. In particular, ethical dilemmas surrounding FP in pediatric patients with KS ought to be discussed with patients and parents, and risk-benefit consideration must be evaluated prior to proceeding. During counseling, it is essential to address the rights of the children to an open future, perhaps justifying parental consent to explore FP measures in children with KS to provide the best opportunity to reproduce genetically in adulthood. Pediatric patients may need multiple consultations to understand the complex issues surrounding their future fertility, as was described by Rives et al.  who founIn the UK, storage of sperm is regulated by the Human Fertilisation and Embryology Authority (HFEA), which released the HFEA Act that outlines that patients under 18 years of age are able to consent to sperm storage if they are considered competent  . HoweverThese concerns, as well as the multi-system involvement of FP in KS, may be further addressed by utilizing a multi-disciplinary team (MDT) approach. Similar approaches have been utilized in pediatric FP in cancer patients and could be used as a foundation to build a similar model in patients with KS.There is growing evidence to support the benefit of carrying out FP in adolescent patients with KS, although controversies remain, and such practice is still in its infancy. A lack of large-scale studies is required to establish if such a practice should be recommended. Ethical dilemmas concerning FP in pediatric patients with KS remain, and discussions should be carried out with the patient and his parents in a multi-disciplinary setting to make shared decisions.CP, AC, AG, and WL wrote sections of the manuscript. CP formulated the first draft. All authors contributed to manuscript revision, read and approved the submitted version, and conception and design of the study.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.


Refractory complex concentrated alloys (RCCAs) have drawn increasing attention recently owing to their balanced mechanical properties, including excellent creep resistance, ductility, and oxidation resistance. The mechanical and thermal properties of RCCAs are directly linked with the elastic constants. However, it is time consuming and expensive to obtain the elastic constants of RCCAs with conventional trial-and-error experiments. The elastic constants of RCCAs are predicted using a combination of density functional theory simulation data and machine learning (ML) algorithms in this study. The elastic constants of several RCCAs are predicted using the random forest regressor, gradient boosting regressor (GBR), and XGBoost regression models. Based on performance metrics R-squared, mean average error and root mean square error, the GBR model was found to be most promising in predicting the elastic constant of RCCAs among the three ML models. Additionally, GBR model accuracy was verified using the other four RHEAs dataset which was never seen by the GBR model, and reasonable agreements between ML prediction and available results were found. The present findings show that the GBR model can be used to predict the elastic constant of new RHEAs more accurately without performing any expensive computational and experimental work. RCCAs are refractory complex concentrated alloys with complicated compositions . Unlike Several theoretical density functional theory (DFT) studies ,12,13,143B, ABC, A2BC, ABCD, and ABCDE, where each A, B, C, D, and E represents one of the above refractory elements. The diagrams of different SQS structures of RCCAs used in the dataset are shown in 3B, ABC, A2BC, ABCD, and ABCDE supercell structures is 8, 16, 36, 32, 64, and 125, respectively. To calculate the elastic constants, i.e., C11, C12, and C44 of RCCAs, the Vienna Ab initio simulation package (VASP) [−5 eV/atom and 10−5 eV/Å, correspondingly. A smearing parameter of 0.2 eV was used in the Methfessel–Paxton method [i, and i. The elastic constants of 370 RCCAs are computed from the DFT calculations. By utilizing strain matrix e, altering the Bravais lattice vectors R =  to R′ = , a deformation of the unit cell is generated, and the elastic constants are obtained,The database contains binary, ternary, quaternary, and quinary RCCAs having BCC structures with refractory elements of Cr, Hf, Ta, Ti, Mo, Nb, W, Re, Zr, and V. The thermo-calc-2019 package with ThermoCalc’s high-entropy alloy database  is emploe (VASP)  was usede (VASP) ,44 simule (VASP) . The elee (VASP) . In all n method . The sta11, C12, and C44.Due to the deformation, total crystal energy will change. The Le Page and Saxe  symmetrymixS) [mixH) [mixS divided by the ΔmixH and multiplied by alloys’ average melting temperature (MT) [χ), and valence electron concentration (VEC) of RCCAs [VEC, ΔmixS, ΔmixH, δ, and χ, to determine the phase in multi-principle element alloys. Khakurel et al. [VEC, geometrical parameter, δ, and melting temperature play essential roles in determining the modulus of CCAs. The geometrical parameter (λ), which is defined by ΔmixS divided by the square of δ, has also been added as a descriptor in this work. The above-selected ten numeric descriptors are calculated using the following Equations (3)–(12), shown in Selecting the meaningful physical descriptors is a critical component of an ML algorithm, and the optimal choice usually depends on the target variable under investigation. It is essential to select the descriptors whose value can be predicted with any DFT computations to save computational costs. Initially, ten numeric descriptors of RCCAs and one categorical data  are chosen for ML models, and numeric descriptors are calculated using the Python program. The mechanical and thermal characteristics of the alloy’s elemental constituents are used to calculate these descriptors. The RCCAs descriptors are entropy of mixing (ΔSmix) , enthalp) [Hmix) , the temure (MT) . Materiaure (MT) . As a reof RCCAs  are alsoof RCCAs ,24,25,26of RCCAs  used 118l et al.  used somth and jth element. th element. In equations of 2), and mean absolute error (MAE) are calculated for each ML model to evaluate its performance. The most satisfactory model with high performance during the training and testing phases is further used to predict the elastic constants of four experimental and simulation data. These data are entirely new to the model to predict elastic constants. The workflow of this work, as explained above, is illustrated in There are 370 RCCAs data points from the DFT calculation. A total of 90% of data were utilized for training, and 10% were used to test and validate the results. The three ML models used in this work are random forest (RF) regressor, gradient boosting regressor (GBR), and XGBoost (XGB) through the Scikit-learn library , which iVEC, and it has been removed from the descriptor list. Since there is no substantial dependency between any two of the remaining descriptors, all metrics should be incorporated into the ML model. Therefore, the number of descriptors reduce from 11 to 9.Before applying the ML models, the Pearson correlation coefficients (p) between each pair of descriptors are calculated, and the results are shown using the triangular heatmap in n represent the DFT elastic constants, ML-predicted elastic constants, mean of all elastic constants, and sample size, respectively.The elastic constant for RCCAs was predicted from the dataset by employing three ML methods: RF, GBR, and XGBoost. The dataset is randomly divided into a training and a testing set with a 9 to 1 ratio. For each approach, hyper tunning is done with a cross-validation score of 5. The different tuned hyperparameter of three ML models obtained from the Grid search method is shown in 2, and RMSE of all three models are shown in 2 close to 1.0 with low MAE and RMSE will result in better performance. It is hard to distinguish which model performs well on the dataset if only R2 is analyzed. Analyzing results from 2 value than the other two ML models indicating its higher prediction accuracy of elastic constant. The R2 value for all models ranges from 0.76–0.97 for the training and testing datasets. Similar value of R2 was found by Trostianchyn et al. [2 value of their ensemble ML model greater than 0.7. In this work, considering the different performance metrics of the GBR among other models, it is considered to be the optimal model.The performance metrics MAE, Rn et al.  while prThe GBR model optimizes the bias while training the dataset and repeatedly trains the trees in the entire process to avoid the early paralysis of trees during the training data which results in better performance in prediction. The performance metrics of all 3 ML models are listed in 11 predicted by the ML model for NbTaTiV matches the experimental value reported in Lee’s study very well [Furthermore, four experimental and simulation data of RCCAs available in the previous publications ,17 were ery well . The preVEC and MT hold the top two positions in predicting the elastic constants. From the previous findings, it is interesting to note the role of the VEC descriptor, which has the top position in descriptor importance in determining the crystal structure [VEC is the essential feature in determining Young’s modulus of complex concentrated alloys in their ML models [The Shapley Additive exPlanations (SHAP) method explains how each descriptor influences the ML by calculating the Shapley values . All thetructure ,23,24,25tructure ,60,61, atructure  of HEAs.L models . MoreoveL models  also fouVEC, MT, and GP values with lower omega values are favorable for developing a higher elastic constant in refractory alloys. The VEC value positively influences the elastic constant of RHEAs; the greater the VEC, the higher the elastic constant, and vice versa. This observation is quite similar to Guo et al. findings [VEC is less than 6.87, the solid solution phase of the BCC is more stable due to solid strengthening caused by lattice distortion. Similar phenomena is observed from the PCP, when VEC lies between 5 to 6.3, the elastic constant becomes higher and it could be due to the lattice distortion. The lattice distortion is also formed when different size elements are mixed, and this mixing will force the atoms to move from their original position and result in lattice distortion. Previous work has also described the significance and importance of VEC in physical characteristics and phase stability in alloys [VEC, which holds the top position in features importance while predicting the hardness of RHEAs using the RF model. They also highlight that VEC is important in charge transfer, which impacts RHEA strength because of lattice distortion. So far, the lattice distortion study is still in progress, and it is done by simulation only. Experimental measurement of lattice distortion in alloys is needed to get further knowledge about the contribution of each element to the elastic properties of RHEAs. The second top descriptor is melting temperature. According to the PCA plot, RHEAs with higher melting temperatures favor the elastic constant of materials. The RHEAs consisting of elements Re, W, Ta, and Mo which have higher VEC and MT, have increased the alloy’s elastic constant. Additional visualization using the contour plot is plotted to see the relationship between top important features VEC and MT with elastic constants. VEC and MT. The original value of VEC and MT is normalized to get the smooth graph. The right-hand side color bar denotes the values of elastic constant in GPa. According to the contour plot, elastic constants of RHEAs increased with higher MT and VEC values. If MT is higher in RHEAs, with low VEC, then the alloy will have low elastic constants. A similar color pattern graph is obtained for all elastic constants as a function of VEC and MT. As a result, it is necessary to consider MT and VEC to get high elastic constants. The change in elastic constants with change in materials stability will help to improve the mechanical properties.Using the SHAP value, the relevance ranking of various descriptors provides a numerical correlation between the input descriptors and target descriptors. Further details between the descriptors and elastic constant can be explored using the data visualization techniques and the concept of material. The parallel coordinate plot (PCP) of the dataset is plotted to display the correlations of the descriptor with the elastic constants, and it is shown in findings , which sn alloys ,54,64,65n alloys  about thIn terms of elastic constant, Vasquez et al.  reportedAs the availability of elastic constants for RCCAs is very limited, this study demonstrates the methodology of estimating the elastic constants for RCCAs based on the ML models using a database constructed from DFT calculations. A total of 370 instances of data were created with the help of DFT computational simulations. The used database is relatively small, but as previous studies show, ML can successfully be applied to a small dataset. As an example, Islam et al.  also use11, C12, and C44, the R2 value of testing data of the GBR model were 0.97, 0.803, and 0.787, respectively. The GBR model has a high R2 value and low MAE and RMSE error than RF and XGB ML models and is promising for predicting the elastic constant of RHEAs. The elastic constants of alloys MoNbTiVZr, MoNbTiZr, NbTiVZr, and NbTaTiV predicted by the GBR model are consistent with the current simulation and experimental findings, which validate its prediction accuracy and applicability. The feature importance from SHAP and PCP plot shows that the VEC and MT are the most influential features affecting the elastic constants of RHEAs. The dataset created in this study using CALPHAD and DFT modeling could help scientists to construct RHEAs that can endure extreme temperatures and pressures. Compared to the computationally expensive DFT calculation and experimentally tedious trial-and-error methods for calculating the elastic constants, ML methods can be applied to predict the elastic constant of any novel refractory high-entropy alloys with very low costs, and hence helps on designing RHEAs to meet the industry demands. The GBR model is not capable of predicting the elastic constants of RHEAs at different temperatures and therefore future work should be focused on creating an ML model that can predict the elastic constants at varying temperatures.In this study, three popular ML methods, namely random forest regressor, gradient boosting regressor, and decision tree regression models, were used for predicting the elastic properties of RCCAs. The ML model consists of eight different descriptors of RCCAs. GBR performs very well as compared with the other two ML models. While predicting elastic constants C


In a multiple stepwise regression analysis, the best determinants of LVEF were %RDA for zinc , presence of coronary artery disease  and age . Furthermore, %RDA for zinc , female sex , beta-blocker use , body mass index  and heart rate  had an independent effect on TAPSE. In conclusion, in individuals of very advanced age, lower zinc intake is associated with poorer cardiac function. Therefore, increasing the recommended zinc intake in this group deserves consideration.The elderly is a group at particularly high cardiovascular risk. The coexistence of chronic diseases and use of multiple medications creates the need to look for non-pharmacological agents to improve cardiovascular health in that population. In view of reports on the potential role of zinc in enhancing pathways of myocardial tissue repair, the aim of this study was to evaluate the association between dietary zinc intake and cardiac structure and function in individuals of advanced age. The study group included 251 community-dwelling patients, with a median age of 80 years. Dieta 6.0 software was used for calculation of zinc consumption. Percentage of Recommended Dietary Allowance (RDA) for zinc correlated with left ventricular ejection fraction (LVEF) (r = 0.196,  Cardiovascular diseases are widely spread in the general population, being not only the leading cause of death in developed countries but also generating high healthcare-related costs. The prevalence and incidence of hypertension, coronary artery disease or heart failure have been rising, especially in the older population ,2,3.Advanced age is one of the key non-modifiable risk factors of adverse cardiovascular events. Apart from pharmacotherapy, guidelines on cardiovascular disease prevention emphasize non-pharmacological management aimed at improving general health . Along wA proper diet not only provides the necessary nutrients and energy but also constitutes the most important source of antioxidants. There are numerous reports on omega-3 fatty acids, polyphenols, vitamins and their effect on the cardiovascular system, while zinc is one of the most important minerals with antioxidant properties. In developed countries, the microelement often fails to receive much attention as severe zinc deficiencies are rare. However, it is well-known that its deficiency may play an important role in the aging process and in the etiology of many chronic diseases, such as neurodegenerative diseases, immunosenescence, atherosclerosis, or cancer . It has The role of zinc as an essential microelement that affects myocardial and vascular properties in multiple physiologic pathways has been previously emphasized ,9,10,11.The elderly is a group at particularly high cardiovascular risk. The coexistence of multiple chronic diseases and polypharmacy creates the need to look for non-pharmacological agents to improve cardiovascular health in that population. In view of reports on a potential role of zinc in enhancing pathways of myocardial tissue repair, the aim of our study was to evaluate the association between dietary zinc intake and parameters of cardiac function in individuals of advanced age.The study population included 270 community-dwelling individuals between the ages of 77 and 91, patients of an outpatient geriatric clinic.Initially, patients older than 80 years were targeted and referred for echocardiographic assessment. Since in this age group there were too few individuals without exclusion criteria, ultimately, patients four years younger were also allowed. The exclusion criteria were acute or uncontrolled chronic inflammatory process, end-stage chronic or neoplastic disease, hemodialysis therapy, mental or functional inability to participate in the study, the use of zinc supplementation and lack of patient consent. All the patients underwent clinical assessment including a review of medical history and basic demographic information, physical examination, dietary assessment and echocardiography. Following an evaluation of cardiac parameters, 19 patients with atrial fibrillation present on examination were excluded from further analysis.After taking accurate anthropometric measurements—body mass, height, waist circumference assessed with the RADWAG personal scale weight  and SECA measuring tape —the following indices were calculated: body mass index (BMI) and the waist-to-height ratio (WHtR). The level of education is presented as the number of years of education.The study was approved by the Bioethics Committee of the Medical University of Lodz in accordance with the Declaration of Helsinki (RNN/345/08/KB). All the patients gave their written consent for participation in the study.The level of zinc consumption was assessed using a modified 24 hour interview method ,19. To dZinc consumption in milligrams was calculated with the use of Diet 6.0 software , based on the Polish base of the composition and nutritional value of food ,23. The Transthoracic echocardiography was performed by the same investigator using a Vivid S70 ultrasound system . The parameters of cardiac structure and function were assessed according to the guidelines of the American Society of Echocardiography and the European Association of Cardiovascular Imaging ,26. InteThe normality of distribution was verified using the Shapiro–Wilk test. Variables without a normal distribution were presented as median value and quartile range (from 25% to 75% quartile), with a normal distribution as median and standard deviations. Between groups, the quantitative variables were compared using the one-way ANOVA or Mann–Whitney U test and the qualitative variables using the chi-square test or Fischer’s exact test. The correlations between the numerical data were analyzed through Spearman‘s correlation coefficient.p ≤ 0.05. The analyses were performed with the use of Statistica 13.1 .Stepwise multiple regressions were performed to adjust the potential relationship between selected echo results , zinc intake and variables that were statistically significant in univariate analyzes. In accordance with the guidelines specified in the literature, sex, age, BMI, diseases  and medication intake  were taken into account. Qualitative variables were included in the model as dichotomized. Statistical significance was set at n = 180) in relation to men (n = 71) reflects the demographic situation in Poland. In 2019 the sex index for seniors 75+ was 0.51 [The study population included 251 elderly individuals who appeared to be homogenous in terms of age and anthropometric parameters. The difference in the numbers of women (was 0.51 . It was The detailed baseline characteristics of the studied population are presented in The echocardiographic parameters are presented in p < 0.05), and TAPSE . Moreover, negative correlation was observed with LVMI . In the sex-based analysis, there was a significant association between zinc intake—expressed as both %RDA and milligrams—and LVEF in women , and TAPSE in men . These relationships are presented in As regards the whole population, %RDA for zinc intake was significantly positively correlated with LVEF , presence of coronary artery disease  and age  were the best determinants of LVEF as a dependent variable . Presence of diabetes or hypertension, medications used , BMI and heart rate were not significant in the univariate analyses; they were not included in the multiple regression.The results of the performed multiple stepwise regression indicate that zinc analyzed as %RDA , female sex , beta-blocker use , BMI  and heart rate  had a statistically significant effect on TAPSE .However, in the case of TAPSE, both BMI and heart rate showed a statistically significant correlation  and in one-way ANOVA, sex, statins and beta-blockers were statistically important. All the variables were entered into the regression model. Ultimately, %RDA for zinc (p = 0.008) and presence of hypertension  determinate the E/E’ ratio as a dependent variable . Sex, zinc intake expressed as %RDA, BMI, presence of coronary artery disease, diabetes or previous MI did not affect the E/E’ ratio.The results of the performed multiple stepwise regression indicate that only age , the presence of hypertension , and additionally by BMI  and sex—female ; R2 = 0.20; p < 0.0001 for the model.Furthermore, the LVMI was determined by age , in addition to age .A majority of the study population had normal LV systolic function, with median LVEF value at 60%, with no difference observed in relation to sex. The association between age and LV systolic function varies across studies—authors report LVEF to decrease, not to change or to increase with age ,39,40,42Moreover, the structure and function of the heart may be strongly affected by hypertension, which plays a major role in cardiac hypertrophy and diastolic dysfunction. These relationships were also revealed in the results of our research, where only age and hypertension significantly influenced the E/E’ ratio value in multiple stepwise analysis. Similarly, the factors associated with LVMI were age, sex, presence of hypertension and BMI.In the context of cardiovascular diseases, zinc plays an invaluable cardio- and vascular-protective role as it is involved in many cellular processes ,47,48. Ap < 0.001) was observed after six months of Se/Zn infusion treatment as compared to an untreated group, which indicates reversibility of cardiac tissue damage in these patients. Similar findings were published by Rosenblum et al. as a case report of young women with anorexia nervosa and newly developed severe heart failure in whom increase of LVEF from a very low to normal value after zinc supplementation was observed [The most important echocardiographic parameter of LV systolic function is LVEF ,25. The observed . In our observed ,51. The p < 0.05) in the studied population. In the analysis by sex, there was a stronger association with E/E’ ratio , and also a positive correlation with E’ in the men; however, the relationships were not observed in the women. In our results, dietary zinc intake—assessed as %RDA—negatively correlates with LVMI , which may have a beneficial clinical value for age- or disease-related cardiac remodeling. This finding is consistent with a previous study by Huang et al. who reported a significant inverse relationship between serum zinc levels and LV mass  or LVMI  in patients with LV hypertrophy [p = 0.001) [p = 0.003), and LAVI I , however, not with LV mass or LVMI. Although previous studies as well as our own have examined different populations, all the results suggest a positive role of zinc in the mechanisms associated with diastolic dysfunction, regardless of underlying diseases. However, it is noteworthy that serum zinc levels do not reflect accurately the nutritional status at the individual level.E/E’ ratio is one of the main parameters used in the evaluation of LV diastolic function, next to LVMI, RWT, LAVI and tricuspid regurgitation velocity . We obseertrophy . There aAs recommended, echocardiographic assessment of RV function should include at least one of the RV parameters . TAPSE—aWhat appears to be a new finding of our study is the occurrence of a statistically significant positive correlation between zinc consumption and TAPSE, especially in men. This relationship with RV systolic function was also confirmed according to S’ RV—the parameter determined by another echocardiographic method—that positively correlates with dietary zinc intake  in men. Moreover, daily zinc intake was an independent factor affecting TAPSE value, apart from BMI, female sex, heart rate and use of beta blockers.It should be acknowledged that the study was conducted with a group of volunteers representing the Central European population, Caucasians only. Therefore, the results may be different in other cultures. The 24 hour dietary recall questionnaire has some limitations, such as the omission of dietary ingredients or recall bias.Moreover, echocardiographic assessment did not include measurement of global longitudinal strain (GLS)—a more sensitive determinant of myocardial dysfunction. Furthermore, not all the cardiac parameters could be determined in each participant; this, however, corresponds to everyday practice, where individual body structure may limit image quality. Additionally, we assessed only dietary zinc intake in relation to echocardiographic parameters; other methods of assessing zinc status in the body have not been analyzed.To the best of our knowledge, this is the first paper showing a relationship of dietary zinc intake and echocardiographic assessment in older people. In individuals of very advanced age, some parameters of cardiac function are related to zinc intake and a lower level of the micronutrient is associated with poorer heart contractility and relaxation.Results of correlations and multiple stepwise regressions showed that %RDA of zinc from diet was one of the most important determinants of both LVEF and TAPSE in the studied population. In this regard, the results suggest that adequate dietary zinc intake may improve cardiac function in the elderly, regardless of age- or sex-related cardiac remodeling. Some gender differences were observed, but they require further confirmation.Given the beneficial effect of zinc on the echocardiographic parameters, as well as the fact that the main dietary sources of zinc for older adults have low bioavailability, increasing the zinc recommendations for this group of people should be considered.


Excessive brain iron depositions were found in both patients with Parkinson’s disease (PD) and those with type 2 diabetes mellitus (T2DM). The present study aimed to explore iron deposition and heterogeneity in the extrapyramidal system in PD patients with T2DM using quantitative susceptibility mapping (QSM) and further to reveal the effect of T2DM on the changes in brain iron in patients with PD.W, VW) and high iron region  were measured on the bilateral caudate nucleus (CN), the putamen (PUT), the globus pallidus (GP), the substantia nigra (SN), the red nucleus (RN) and the dentate nucleus (DN). Clinical and laboratory data were recorded, especially for the Hoehn and Yahr (H-Y) stage, the Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), the Hamilton Depression Rating Scale (HAMD), and the Hamilton Anxiety Rating Scale (HAMA). All QSM data were compared between PDDM and PDND groups and correlated with clinical and laboratory data.A total of 38 PD patients with T2DM (PDDM), 30 PD patients without T2DM (PDND), and 20 asymptomatic control subjects (CSs) were recruited for this study. All subjects underwent multiple MRI sequences involving enhanced gradient echo T2 star weighted angiography (ESWAN). The magnetic sensitivity values (MSV) and volume of the whole nuclei (MSVRII/VW of the left CN was significantly increased in the PDDM group. Significantly higher MSVW and MSVRII were also found in the PDDM group, including bilateral SN of MSVW, right PUT, and bilateral CN, GP, and SN of MSVRII. The H-Y stage of the PDDM group was significantly higher than that of the PDND group. The MSVRII of bilateral RN of the PDDM group was positively correlated with the HAMA scores. HDL, DBP, and SBP levels were associated with MSVRII of right CN in the PDDM group.Compared to the PDND group, the VT2DM could aggravate the disease severity and anxiety in patients with PD. The iron distribution of deep gray matter nuclei in PD patients with T2DM was significantly heterogeneous, which was related to blood pressure and blood lipids. Parkinson’s disease (PD) is a common aging-related chronic neurodegenerative disease of the central nervous system. Recently, some epidemiological studies demonstrated that T2DM can increase the risk of PD . An analin vivo. Thus, QSM is widely used for detecting overdose of iron deposition to assist PD diagnosis. It can accurately reflect both the spatial distribution of tissue susceptibility and the quantitative information of the regional iron content within gray nuclei . All patients were admitted to the Department of Neurology in our hospital. A total of 68 clinically diagnosed patients with PD from June 2016 to April 2021 were enrolled and recorded as the PD group. The PD diagnosis criteria adopted the 2015 Movement Disorders Society (MDS) criteria for Parkinson’s disease diagnosis . The exc2 × 24 cm2, slice thickness = 1 mm, slice gap = 0 mm, matrix = 256 × 256).All subjects underwent a routine MRI and enhanced gradient echo T2 star weighted angiography (ESWAN) on a 3.0T GE Signa HDXT scanner from America with a dedicated eight-channel head coil. The ESWAN parameters were kept the same  software was used for the post-processing of ESWAN images. SPIN software was used to distinguish the original amplitude map and the phase map of ESWAN images; then, the QSM image was obtained by processing the original amplitude and the phase map by the susceptibility weighted imaging mapping (SWIM) module in the software.W) and the R II region (MSVRII) were recorded, as well as the volumes of the whole nucleus (VW) and the R II region (VRII) were done. After 7 months, the same doctor measured the QSM parameters of all patients with PD again.The regions of interest (ROIs) were selected in the bilateral extrapyramidal system, including the CN, the PUT, the globus pallidus (GP), the SN, the RN, and the dentate nucleus (DN), as seen in t-test  or the Mann–Whitney U test  were used to compare the MSVw, MSVRII, VW, VRII, VRII/VW, and clinical data between two groups. The Pearson correlation analysis  or the Spearman correlation analysis  was used to analyze the relations between MSVRII and the MMSE score, the MoCA score, the HAMA score, the HAMD score, and the H-Y stage in the PDDM group. A false discovery rate (FDR) was performed to correct the multiple comparisons. A multiple linear regression analysis analyzed independent related factors of the MSVRII in the PDDM group. In order to eliminate the collinearity among independent variables, the TG and LDL were removed from the independent variables after the collinearity analysis of independent variables.Data analyses were performed using SPSS (version 26.0). To evaluate the reliability of the interobserver, the intraclass correlation coefficients (ICCs) were calculated. Independent-samples P = 0.000), there were no differences in the clinical data and clinical laboratory indicators  between the two groups . Compared to the PDND group, a significant increase in the H-Y stage (P = 0.011) score was found in the PDDM group, while the MMSE score, the MoCA score, the HAMA score, and the HAMD score were also found to be higher but without a statistic difference.The clinical laboratory indicators, the H-Y stage, and neuropsychological scale assessments are summarized in W of the PDDM group was increased in most of the nuclei, except for left DN. Differences were only found in the right SN  and the left SN   . Compared to the PDND group, the MSVrection) . MSVRII rection) .W and VRII between the two groups , and the VRII/VW increased in the PDDM group  and the left CN  showed a positive correlation with the HAMA scores in the PDDM group  and was negatively correlated with the DBP  and HDL levels   . The regIn the present study, we used the QSM threshold method to compare and analyze the iron content in both the high iron zone and the whole iron zone in the deep gray matter nuclei of the PDDM and PDND groups. It was found that T2DM aggravated not only extrapyramidal iron deposition but also its homogeneity in patients with PD. In addition, we also found that, although T2DM did not affect the whole volume of gray matter nuclei in patients with PD, it increased the relative volume of high-iron areas in the gray matter nuclei, further indicating that T2DM leads to uneven iron distribution in gray matter nuclei in patients with PD. We also found that SBP, DBP, and HDL were independent influencing factors of iron distribution in patients with PDDM.The central nervous system requires iron for many metabolic processes, and it will suffer from disturbed function whether the iron is excessive or lacking. Iron plays a pivotal role in many physiological functions, including neuronal metabolism, DNA synthesis, oxygen transport, mitochondrial respiration, nerve transmission, and myelination . ExcessiOur results showed that H-Y staging in the PDDM group was significantly higher than that in the PDND group, and there were no significant differences in cognitive scores, depression, and anxiety symptoms between the two groups. Our results suggested that T2DM would accelerate the disease process in patients with PD. One case-control research indicated that PD patients with T2DM scored higher on the severity scale including the H-Y stage than those with PD . A retroIn out study, we found that, compared to the PDND group, the iron contents in the bilateral SN were increased in the PDDM group for the whole nucleus area, which suggests that T2DM may aggravate the local iron deposition in the gray matter nuclei of patients with PD. Previous studies showed that iron accumulation in the SN of patients with PD is abnormal, especially in the dense part of the SN. Studies found excessive iron accumulation in the SN and the RN of patients with PD . ExcessiThe distribution of iron in the gray matter nuclei is uneven . To furtW and VRII between the two groups. We suggested that T2DM did not affect the volume of gray matter nucleus in patients with PD. Through FreeSurfer analysis, Pagano et al. showed no differences in subcortical nuclei volumes between the PDDM group and the PDND group  and SBP levels is significant for maintaining iron deposition, and sometimes HDL can be higher than normal . Previous research showed that HDL was directly involved in anti-inflammatory and antioxidant effects that would reduce iron release from ferritin and that inadequate HDL was associated with an increased risk of neuronal degeneration  The sample size was small; thus, a larger sample size is needed to reduce errors. (2) The ROIs in this study were manually placed, inevitably leading to some errors. (3) This study did not consider the effect of insulin and other drug treatments on brain iron deposition, which may interfere with the results to a certain extent. (4) The subthalamic nucleus is an essential structure in the extrapyramidal system. It failed to be accurately measured on QSM because of its small size and poor distinction from the adjacent organization. More accurate measurement methods are needed. (5) The age spectrum of patients in the PDDM and PDND groups included in this study was wide, and considering the influence of age on the iron content in neurodegenerative diseases, we need to stratify patients by age to refine the iron deposition changes further.In summary, based on the QSM threshold method, we identified that T2DM could aggravate iron deposition and its heterogeneity in extrapyramidal gray matter nuclei in patients with PD, which was consistent with the severity and anxiety of the disease of PD. Iron deposition in patients with \PDDM correlates with HDL, DBP, and SBP, suggesting that managing blood pressure and blood lipids is necessary for patients with PDDM.The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.The studies involving human participants were reviewed and approved by PJ-KS-KY-2021-121. The patients/participants provided their written informed consent to participate in this study.WL: conceptualization, data curation, formal analysis, methodology, visualization, and writing—original draft. BG: conceptualization, formal analysis, methodology, and writing—original draft. WD, YJ, JY, RH, YL, NL, and YZ: data curation, formal analysis, investigation, and writing—reviewing and editing. QS: conceptualization, supervision, project administration, and writing—reviewing and editing. YM: conceptualization, funding acquisition, methodology, supervision, and writing—reviewing and editing. All authors contributed to the article and approved the submitted version.


The effect of SKY continued until Day 30 for Professional Fulfillment and had positive and negative effects. Findings suggest that SKY elevated Professional Fulfillment among HCPs during the COVID-19 pandemic and reduced their work exhaustion and the negative effect on their mental health. SKY can aid HCPs in maintaining their well-being when faced with unprecedented challenges.Demanding work-life and excessive workload, the conflict between professional and personal lives, problems with patients and those related to the occurrence of death and high risk for their own life are a few factors causing burnout, disengagement, and dissatisfaction in the professional lives of healthcare professionals (HCPs). The situation worsened during the COVID-19 pandemic. It is of utmost importance to find effective solutions to mitigate the stress and anxiety adversely affecting the mental well-being and professional lives of HCPs. This study was designed to examine the efficacy of Sudarshan Kriya Yoga (SKY) for alleviating work exhaustion, improving Professional Fulfillment, and influencing positivity among HCPs during COVID-19. In a comparative observation before the intervention (Pre), after the intervention (Post), and 30 days after the intervention (Day 30) in the Experimental Group (29 physicians) and Control Group (27 physicians), it was found that immediately after SKY, HCPs experienced a significant improvement in Professional Fulfillment ( Since March 2020, there have been over 154.8 million confirmed cases of COVID-19 and more than 3,236,104 deaths worldwide  is a yogic breathing technique with a beneficial impact on stress, mental health, depression, sleep, social connectedness, and overall quality of life among youth, healthy adults, cancer, and HIV patients . FurtherA vaccine for COVID 19 has been developed, and the first round of vaccination is underway. However, the question of how best to address the mental health issues arising from post-pandemic stress, economic recession, and fear of social interactions remains unresolved.Under circumstances where the effectiveness of vaccination is not completely known, the timeline for regaining economic stability and creating COVID-19-free environments also remains unknown. It becomes imperative to find solutions to support HCPs on the frontlines to protect, maintain and boost their wellbeing. It is time to enlist and study every strategy available to us to help those responsible for society’s health. In such circumstances, it was hypothesized that SKY would be beneficial to mitigate the adverse effects of a pandemic like work exhaustion and disengagement among frontliners. This study was designed to observe the impact of SKY on alleviating work exhaustion, improving Professional Fulfillment, and influencing positivity among HCPs during COVID-19.A comparative observational study design was implemented among HCPs to observe the effect of SKY on the two groups: the Experimental Group and the Control Group. The assessments took place between July 2020 and October 2020. The study was conducted online, keeping in mind HCPs’ busy schedules and isolation protocols due to COVID-19 patient care. Conducting an interview or applying mixed methods in study design was not possible due to their work prioritization. The subjects in the Experimental Group were assessed at three time points: before the intervention (Pre), after the intervention (Post) on Day 4 to observe the immediate effects of the intervention, and 30 days after the daily practice of the intervention (Day 30). The Control Group was assessed on the first day of the study and had received no intervention. A team that was not directly involved in the study collected data at Medanta to reduce demand characteristics. The data were collected utilizing standardized questionnaires on resilience, Professional Fulfillment, and mood from HCPs who underwent an online SKY Workshop. The study was carried out in collaboration with two institutions—Sri Sri Institute for Advanced Research and Medanta Institute of Education and Research (MIER). The Medanta Institutional Ethics Committee approved this study (reference number MICR-1106/2020).Study participants were recruited from Medanta Hospital. The institute is located in Sector 38, Gurgaon, Haryana, India. During the pandemic, Medanta was one of the foremost institutions taking care of COVID-19 patients in Delhi NCR, the capital city of India. The inclusion criteria for study participants were direct exposure to COVID-19 patients, no previous experience of SKY, and a willingness to participate in the study. The doctors practicing in the study field from July 2020 to October 2020 were included in the study. All the working professionals from Medanta were called and informed about the details of the study over the phone. They were also informed that their participation in the study was voluntary. Those who gave voluntary consent to participate in the study were included, and their informed consent was obtained. The institutional review board of Medanta approved the study. Pregnant women and those unable or unwilling to practice SKY were excluded from the study. There was no compensation or cost to participate in this study, and the medical records and personal information of the HCPs were kept confidential.via Zoom. There was no in-person social contact during the workshop or during the study duration due to the SKY intervention. The workshops were limited to 15 participants and were led by experienced yoga instructors. Each session was led by two trainers to ensure individual attention. The workshop lasted for 4 days, 2 h daily. The Experimental Group attended only SKY sessions due to their hectic schedule and did not participate in any other forms of yoga, meditation, or physical or social activities. In total, 4–5 workshops were conducted over 2 weeks for all study participants. Study participants were allowed to join either the morning, afternoon, or evening batch, depending on their preference and availability. After completion, regular follow-up sessions were conducted every morning and evening for 30 days, maintaining attendance logs. A follow-up call was made once a week to enhance retention. In the Experimental Group, a total of 29 HCPs contributed to pre- and post-study assessments. Three participants were excluded from the study due to their inability to practice SKY for the entire 30 days, leaving 26 of them to participate on Day 30. From the Control Group, 27 HCPs participated; however, it was impossible to provide them with any wellness program or treatment due to their busy schedule and the pandemic. The flow diagram of study is represented in the The study was conducted during the peak of the first wave in India. The subjects were healthcare providers who were actively tending to COVID-19 patients; hence, their time and availability were under severe constraints. All study participants attended SKY workshops from their place of comfort, either an office, clinic, COVID center, or their home. However, most of the study participants were staying near COVID care centers. SKY workshops were conducted online Sudarshan Kriya Yoga is a method of cyclical controlled breathing and meditation practice. A typical SKY session lasts for 30 m and consists of four distinct yogic breathing stages . Ujjayi involves becoming aware of the conscious sensation of the breath touching the throat. This slow breathing technique is done at a rate of 2–4 breaths per minute (bpm). During Bhastrika, the air is rapidly inhaled and forcefully exhaled at a rate of 20 bpm. Three 1-min rounds of Bhastrika are followed by a few minutes of normal breathing. Next, Om is chanted three times with very prolonged expiration. Lastly, Sudarshan Kriya rhythmic breathing is performed at three different speeds: slow (20 bpm), medium (40–50 bpm), and fast (60–80 bpm). A SKY session is conducted in a seated position with the eyes closed.Sudarshan Kriya Yoga was taught to participants in a 4-day online breathing and meditation workshop. The duration of the workshop was a total of 8 h (a 2-h session each day) and was taught by video conference. The workshops were led by experienced SKY instructors trained by the Art of Living Foundation. The participants were given home practice and were encouraged to practice daily. The home practice was 25 m long.The Stanford Professional Fulfillment Index is a 16-item Professional Fulfillment scale that assesses the degree of intrinsic positive reward an individual receives from their work, including happiness, meaningfulness, contribution, self-worth, satisfaction, and feeling in control when dealing with difficult problems at work. It is divided into three domains: Professional Fulfillment, work exhaustion, and interpersonal disengagement. Responders were asked to rate every item on a 5-point Likert scale . For the domain of Professional Fulfillment, higher scores indicated higher Professional Fulfillment. For the domain of Work Exhaustion, higher scores indicated greater Exhaustion, and for Interpersonal Disengagement, a higher score indicated greater interpersonal disengagement. Test-retest reliability estimates 0.80 for overall burnout (α = 0.92). This 16-item small scale measured both burnout and Professional Fulfillment and was developed for use among physicians in any healthcare setting. It is sensitive, reliable, and not time-consuming to complete. Compared with the Maslach Burnout Inventory, the PFI burnout scale sensitivity and specificity in identifying those with burnout were found to be 72 and 84%, respectively .Positive and Negative Affect Scale (PANAS) : positivBoth the standardized tools mentioned above have been used in several studies in India and are highly used in yogic interventional studies.The study population was frontline workers with busy schedules. Keeping in mind the critical nature of the HCPs’ work and the associated paucity of time, we kept the time for assessments to a minimum. Accordingly, PFI and PANAS were found suitable for this study. Due to the aforementioned reasons, other research methodologies such as interviews and group discussions were not found to be suitable for the study population.t-test (paired and unpaired). Pearson Correlation was calculated in the Experimental Group to find the linear correlation between the two variables. Cronbach’s alpha was used to determine the internal consistency and reliability of the data, while Cohen’s d value was used to determine the effect size within the Experimental Group.Participants from the Experimental (SKY) group were assessed at three time points: pre, post, and day 30. A team not directly involved in the study collected data at Medanta to reduce demand characteristics. Data from the Experimental and Control Groups were compared using two-way MANOVA at a significance level of 0.05. For the Experimental Group, data were matched in pairs of pre–post, pre-day 30, and pre–post-day 30. Sample size analysis was performed using G-Power. Data were recorded in Microsoft Excel, and analyses with the appropriate graphical presentation were performed using the IBM Corp. Demographic variables are tabulated and graphically represented using proportions (%). The Chi-square or Fisher’s exact tests were used to compare groups for categorical data. Wherever applicable, quantitative data are presented with mean and standard deviation (SD) and analyzed using the Student’s Demographic details for the SKY and Control Group are shown in d value for different domains in the SKY group, indicating small-to-large size effects for different domains. Using G-power, the effect size was 0.76 (medium effect size) when alpha was 0.05, and the power of the study was 80% . Table 5F = 5.3, p < 0.001; Wilk’s λ = 0.28, partial η2 = 0.72]. There was no statistically significant difference observed between the males and females or interaction between the group and gender when compared at three different time points.There was a statistically significant difference between the two groups when compared at three different time points, once pre and twice post-intervention . The mean value increased from 17.5 to 19.2 in the Experimental Group immediately after the intervention. A similar effect was observed on the 30-day assessment .At the baseline assessment, SKY and Control scored similarly for Professional Fulfillment. After practicing SKY, the HCPs in the Experimental Group scored significantly higher in the Professional Fulfillment domain than those in the Control Group . Average values dropped from 5.00 to 3.30. This effect did not last until Day 30, probably because of increased workload and a steady increase in the number of COVID-19 patients.After experiencing SKY, work exhaustion was significantly reduced among the HCPs from the Experimental Group compared to those from the Control Group  when an intragroup comparison was performed in the SKY group; it was found that interpersonal disengagement scores reduced significantly with the following values: pre-mean: 4.60; post-mean: 3.72; day 30 mean: 2.60, p-value: 0.51 (Pre and Post), and p-value: 0.02 (Pre-day 30)  = 4.03; p < 0.05; partial η2 = 0.08] for PA and  for NA. The same effect was observed at the Day 30 assessment:  for PA and  for NA. The PA mean value increased from 37.7 to 42.6. Immediately after the intervention, the NA mean value in the Experimental Group decreased immediately from 22.3 to 17.2 and 17.0 on day 30.The SKY group showed significant improvement in positive and NA post-intervention compared to the Control Group: [For positive and NA, Cronbach’s alpha demonstrated excellent internal consistency with α > 0.9 at all three-time assessment points. For the SKY group, the effect size of the intervention varied from −0.5 to −0.7 for pre–post and pre-day 30, indicating a medium-sized effect for both domains . AccordiThe COVID-19 pandemic has been a crucial time for science. Impressive efforts have been made to develop a vaccine against COVID-19 and to investigate the pandemic’s impact on the physical and mental health of human beings. HCPs were found to be the most affected by the pandemic due to increased stress and work exhaustion, which, in turn, affected their quality of life . Many haThis study observed the impact of SKY on HCPs working in COVID-19 care units, where the stress was at its peak. Overall, the results of this study for different assessed parameters suggest that SKY has a significant and positive impact on HCPs’ mental health and work engagement.Healthcare professionals’ Professional Fulfillment was adversely affected during COVID-19 . As percThis study is the first to examine the impact of SKY on Professional Fulfillment. It provides elemental evidence for the significant improvement in Professional Fulfillment among HCPs with SKY practice despite greater work exhaustion.Work exhaustion refers to work-related stress or burnout and includes both physical and emotional exhaustion. Stress is experienced when we have too much to do and too little energy or time. For HCPs, the burden of patient care, long and tiring work hours, and inadequate availability of effective medications or treatments are significant factors contributing to stress.Research studies on SKY have found it useful in relieving stress, anxiety, major depression, and mood disorders . SKY hasBoth brain and heart functions affect mental stress. SKY plays a significant role in effectively reducing mental stress, improving human stress tolerance and enhancing cognitive performance . It was Interpersonal disengagement is the withdrawal from social interaction. According to After practicing SKY, HCPs scored higher for PA, suggesting that they were full of energy and enthusiasm. The NA also reduced, showing a reduction in sadness and lethargy and increased mental peace. Study results indicate that SKY helped HCPs improve their mood and have a positive outlook. It also helped alleviate the response to negative experiences. Previous research has demonstrated that SKY helps manage emotions and feelings , which iThere have been an inadequate number of studies assessing the impact of yoga and meditation practices among HCPs during COVID-19. The study done by The findings of this study have certain limitations. The number of doctors practicing in the study field during the specified period from July 2020 to October 2020 was the study sample that restricted the study to a small sample size. Given their busy schedules, time constraints were the greatest challenge to engaging HCPs in a study during a crisis such as the COVID-19 pandemic. This hampered the ability to conduct detailed demographic assessments, resulting in four dropouts in the Experimental Group on Day 30. Social distancing and lockdown further restricted this study and required the study intervention to be delivered online. However, this was an opportunity for exploratory rather than an explanatory research design, which had to overlook randomization, active control, recall bias, non-respondent biases, and explanations to rule out alternatives in methodologies. There is scope for further research into multicentric research.Although many research studies have been conducted globally to observe the impact of the COVID-19 pandemic on mental health, stress, and work exhaustion among HCPs, very few have focused on investigating the efficacy of yogic interventions as an option to reduce stress and work exhaustion while also improving mental health in HCPs during the pandemic.p = 0.04) immediately after the intervention among HCPs compared to their colleagues in the Control Group. The SKY effect was maintained on Professional Fulfillment, even after 30 days of continued SKY practice (p = 0.02). Findings also indicate that, as compared to the Control Group, SKY helped reduce work exhaustion (p = 0.01) and the negative impact (p < 0.001) of the pandemic immediately after the intervention. However, within the Experimental Group, the levels of work exhaustion were found to have increased on Day 30 of SKY practice. Intriguingly, their 30. SKY helped HCPs increase Professional Fulfillment, reducing the negative interpersonal disengagement that was not affected by increased work exhaustion. In fact, the levels of interpersonal disengagement significantly reduced (p = 0.05) on Day 30 impact and interpersonal disengagement and handled work exhaustion during the peak of the pandemic.In this unique pilot study, it was found that SKY can aid HCPs in maintaining their well-being when confronted with unprecedented challenges. SKY elevated Professional Fulfillment . The patients/participants provided their written informed consent to participate in this study.All authors made significant contributions, reviewed and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


N = 38) and without (N = 37) the deficit syndrome. The prevalence of the HG duplication pattern bilaterally was higher in the whole schizophrenia group than in 59 matched healthy controls. Furthermore, the prevalence of right HG duplication was significantly higher in the deficit schizophrenia group than in the non-deficit schizophrenia group. The HG pattern in schizophrenia was not associated with clinical variables, including illness duration, medication, and symptom severity, while right HG duplication correlated with higher scores for Proxy for the Deficit Syndrome. The present results suggest that the prominent neurodevelopmental pathology associated with gyral formation of HG may contribute to enduring negative symptomatology in schizophrenia.Deficit syndrome schizophrenia is a characteristic subtype defined by persistent negative symptoms and poor functional outcomes; however, the biological mechanisms underlying this specific subtype have not yet been elucidated in detail. The present magnetic resonance imaging study examined the prevalence of duplicated Heschl’s gyrus (HG), a potential neurodevelopmental marker, in schizophrenia patients with ( Schizophrenia is characterized by substantial clinical and biological heterogeneity, where negative symptoms are a core component that mainly account for long-term disability and poor functional outcomes in patients with the disorder , 2. The in utero (Recent magnetic resonance imaging (MRI) studies on schizophrenia revealed an increased prevalence of a duplicated Heschl’s gyrus (HG) pattern –17, whicin utero , 19. Thiin utero  and chroin utero  stages] in utero –17 of scin utero , 16, as in utero , is assoin utero . It may Therefore, we herein used MRI to investigate and compare duplicated HG patterns in the D-Sz and non-deficit subtype of schizophrenia (ND-Sz) with those in matched healthy controls. We had previously explored brain characteristics of our D-Sz cohort and found gross morphological changes associated with early neurodevelopment  and graThirty-eight patients with D-Sz, 37 with ND-Sz, and 59 healthy control subjects were enrolled in the present study . We havevia a structured clinical interview  of cells had expected counts <5) was employed for group comparisons of demographic and clinical data.A one-way analysis of variance (ANOVA) or the χ2 test to evaluate group differences  in HG gyrification pattern distributions in each hemisphere. Because the HG duplication was more prevalent in the patients especially for D-Sz, the odds ratio was calculated to estimate the relationship between HG duplication and relative risk of schizophrenia and its subtype. The relationships between HG patterns and clinical variables  were assessed by an analysis of covariance (ANCOVA) with age as a covariate, followed by Duncan’s test. p < 0.05 was considered to indicate a significant difference.We used the χThe score for the blunted affect subscale was significantly higher in the D-Sz group than in the ND-Sz group, while delusions, hallucinations, and attention deficits were more severe in the ND group . On the N = 75) and healthy controls (N = 59) revealed significant differences for both the left  and right  hemispheres ; right, χ2 = 10.22, p = 0.001, odds ratio = 3.33 ] (p = 0.034); the results obtained remained essentially the same ] . We thenthe same .2 = 0.50, p = 0.779; right, χ2 = 7.23, p = 0.027). The prevalence of right HG duplication was significantly higher in the D-Sz subgroup than in the ND-Sz subgroup  .In subgroup comparisons between the D- and ND-Sz groups, a significant difference was only observed for the right hemisphere ] . When onFurthermore, there was no significant effect of sex on HG duplication in the controls, the schizophrenia group as a whole, or each schizophrenia subgroup.F = 4.66, p = 0.034; post hoc test, p = 0.034]. This difference in the PDS score was especially evident between patients with CPD  and those with the single pattern  . On the other hand, the left HG pattern in the schizophrenia group as a whole did not affect these clinical variables.The HG pattern did not affect the onset age, duration of illness, medications, or symptom ratings  in the D- and ND-Sz subgroups. As predicted by significant contribution of right HG duplication to the D-Sz (described above), in the schizophrenia group as a whole, patients with the right duplicated pattern had a significantly higher PDS score  than those with right single HG  of healthy adults –30. The in utero , 19; dupin utero , 32 and in utero  after biin utero  and sociin utero . Therefoin utero , may be in utero  revealedin utero , our hypThe present results on HG duplication patterns were not influenced by illness chronicity or medication, supporting previous neuroimaging findings suggesting a prominent early neurodevelopmental pathology in D-Sz [e.g., small adhesio interthalamica  and gyriSeveral potential confounding factors in the present study need to be addressed. First, the present study was partly limited by its small sample size for each schizophrenia subgroup. Due to its reliability and stability, the PDS score has been widely used to classify patients into the D and ND subgroups in biological , 37–39 aIn summary, this preliminary MRI study demonstrated that the prevalence of HG duplication was higher in patients with schizophrenia, particularly those with the deficit syndrome subtype who typically exhibit enduring negative symptomatology and poor functional outcomes. Although the HG duplication itself is observed in healthy subjects and there is considerable overlap on the HG pattern distribution between D- and ND-Sz subgroups, it is possible that, in combination with other brain characteristics, the HG pattern in the early stages of schizophrenia may have potential as a prognostic biomarker of worse long-term functioning.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 Committee on Medical Ethics of the University of Toyama. The patients/participants provided their written informed consent to participate in this study.MS and TT conceived the idea and methodology of this study. TT conducted the statistical analyses and wrote the manuscript. DS and HK recruited the participants and were involved in clinical and diagnostic assessments. TT and DS analyzed the MRI data. KN provided the technical support for MRI scanning and data processing. AF managed the MRI and clinical data. MS and YT contributed to the writing and editing of the manuscript. All authors contributed to and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.