The presence of metastatic tumor cells in regional lymph nodes is considered as a significant indicator for inferior prognosis. This study aimed to construct some predictive models to quantify the probability of lymph node metastasis (LNM) and survival rate of patients with soft tissue sarcoma (STS) with LNM.Research data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017, and data of patients with STS from our medical institution were collected to form an external testing set. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for developing LNM. On the basis of the identified variables, we developed a diagnostic nomogram to predict the risk of LNM in patients with STS. Those patients with STS presenting with LNM were retrieved to build a cohort for identifying the independent prognostic factors through univariate and multivariate Cox regression analysis. Then, two nomograms incorporating the independent prognostic predictors were developed to predict the overall survival (OS) and cancer-specific survival (CSS) for patients with STS with LNM. Kaplan–Meier (K-M) survival analysis was conducted to study the survival difference. Moreover, validations of these nomograms were performed by the receiver operating characteristic curves, the area under the curve, calibration curves, and the decision curve analysis (DCA).https://tyxupup.shinyapps.io/probabilityofLNMforSTSpatients/, https://tyxupup.shinyapps.io/OSofSTSpatientswithLNM/, and https://tyxupup.shinyapps.io/CSSofSTSpatientswithLNM/. The areas under the curve (AUCs) of diagnostic nomogram were 0.839 in the training set, 0.811 in the testing set, and 0.852 in the external testing set. For prognostic nomograms, the AUCs of 24-, 36-, and 48-month OS were 0.820, 0.794, and 0.792 in the training set and 0.759, 0.728, and 0.775 in the testing set, respectively; the AUCs of 24-, 36-, and 48-month CSS were 0.793, 0.777, and 0.775 in the training set and 0.775, 0.744, and 0.738 in the testing set, respectively. Furthermore, calibration curves suggested that the predicted values were consistent with the actual values. For the DCA, our nomograms showed a superior net benefit across a wider scale of threshold probabilities for the prediction of risk and survival rate for patients with STS with LNM.A total of 16,601 patients with STS from the SEER database were enrolled in our study, of which 659 (3.97%) had LNM at the initial diagnosis. K-M survival analysis indicated that patients with LNM had poorer survival rate. Sex, histology, primary site, grade, M stage, and T stage were found to be independently related with development of LNM in patients with STS. Age, grade, histology, M stage, T stage, chemotherapy, radiotherapy, and surgery were identified as the independent prognostic factors for OS of patients with STS with LNM, and age, grade, M stage, T stage, radiotherapy, and surgery were determined as the independent prognostic factors for CSS. Subsequently, we constructed three nomograms, and their online versions are as follows: These newly proposed nomograms promise to be useful tools in predicting the risk of LNM for patients with STS and individualized survival prediction for patients with STS with LNM, which may help to guide clinical practice. Soft tissue sarcoma (STS) refers to a group of uncommon mesenchymal malignancies, only accounting for approximately 1% of all solid tumors , 3. UnfoCompared with the most common lung metastases, lymph node metastasis (LNM) is a more rare but equally vital prognostic factor, with the overall prevalence varying from 1.7% to 5.9% . The 5-yGiven the low incidence of LNM in STS, it is relatively difficult to acquire enough positive research cases in a single institution. The Surveillance, Epidemiology, and End Results (SEER) database is the largest publicly available dataset, which collects data from 18 cancer registries and involves about 30% of the US population . In thisAll the information of patients diagnosed with STS was extracted from the SEER database by SEER * Stat software version 8.4.0. The inclusion criteria of our study sample were as follows (1): patients diagnosed with STS between 2004 and 2017; and (2) patients were diagnosed by histological confirmation. In addition, the exclusion criteria were as follows: (1) STS was not the first malignant tumor and more than one primary tumor; (2) patients for whom the following information was unknown, including age, race, sex, histology, grade, stage TNM, marital status, surgery, and lymph node dissection (LND); and (3) the survival time less than 1 month. All of the eligible patients with STS were used to form the diagnostic study cohort and those patients with STS with LNM were included in the prognostic study cohort. In this study, TNM staging was transferred to the eighth edition of the AJCC/UICC TNM staging system. The detailed selection process of patients and the workflow of study are shown in On the basis of the clinicopathological characteristics provided in the SEER database and published literatures, the following eight variables were collected to identify the independent LNM-related risk factors, including age, sex, race, histology, grade, M stage, T stage and primary site. In addition, other four treatment variables  and one sociological variable  were collected to identify the independent prognostic factors for patients with STS with LNM. In these variables, grade was classified into well differentiation (I–II) and poor differentiation (III–IV). The primary site included extremity, trunk, and head and neck. Moreover, quantitative data were classified as categorical data, including non-elderly patients and elderly patients (<65 and ≥65 years). OS, the time between the date of disease diagnosis and the date of death from any reasons, was determined to be one of the endpoint of this study. In addition, considering that cancer-specific survival (CSS) was, to some extent, more closely related to tumor-mediated patient prognosis, it might provide more precise guidance for the treatment of patients with STS with LNM. CSS was defined as another study endpoint.All selected patients with STS and patients with STS with LNM were both randomly divided into training sets and testing sets in a ratio of 7:3 approximately. The chi-square test was used to compare differences between the training set and the testing set. The training sets were used to construct and validate nomograms, and the testing sets were used to validate nomograms. In the part of construction and validation of the diagnostic nomogram, the external testing set was formed for the external validation using the information from another regional population to assess the extrapolation of the model. First, the Kaplan–Meier (K-M) survival analysis with the log-rank test was performed to compare the survival probability between patients with STS with LNM and without LNM and investigate differences of OS and CSS between LNM-positive patients with and those without distant metastasis (DM). Then, univariate and multivariate logistic regression analyses were used to explore independent LNM-related risk factors in patients with STS in diagnostic study cohort. The relevance between predictors and LNM was shown by odd ratios and corresponding 95% confidence intervals (CIs). The correlation between clinicopathological characteristics and survival rate of patients with STS with LNM was estimated by univariate and multivariate Cox analyses. The hazard ratios and corresponding 95% CIs were calculated. Finally, on the basis of the results of logistic analyses and Cox analyses, the diagnostic nomogram and prognostic nomograms were constructed by “rms” package in R software, respectively. Meanwhile, three corresponding web-based calculators were further established on the basis of the nomograms using the “Dynnom” package.The receiver operating characteristic (ROC) curves and C-index values were used to evaluate the discrimination of the nomogram. The higher value of area under the curves (AUC) indicated better discrimination. The calibration curve was carried out to evaluate the consistence between actual outcomes and predicted outcomes. In addition, the decision curve analysis (DCA) curves were performed to calculate the net benefit of the predictive model, which can show the clinical practicability. In addition, a k-fold (k = 10) cross-validation method was performed to validate prognostic nomograms.https://www.r-project.org/). P-value <0.05 (both sides) was regarded as statistically markedly.Furthermore, we calculated the total score of each patient with STS with LNM using these prognostic nomograms, and they were divided into two subgroups based on the median total score. The K-M survival analysis with the log-rank test was performed to evaluate the ability in stratifying patients with STS with LNM according to the risk of mortality. Statistical analysis and mapping involved in our study were conducted in SPSS 26.0 and R software version 4.0.2 , a testing set , and an external testing set (N = 181). As described in K-M survival analysis was used to compare OS and CSS survival probability between patients with STS with LNM and without LNM. The results showed that the OS and CSS rates of patients with STS with LNM were greatly worse than that of patients without LNM (https://tyxupup.shinyapps.io/probabilityofLNMforSTSpatients/). The AUC values of the nomogram in the training set, the testing set, and the external testing set were 0.839 , 0.811 , and 0.852 , which indicated a good discrimination of the nomogram  and the testing set (N = 196). The basic demographic, pathological, and treatment characteristics of the patients with STS with LNM in two sets are listed in https://tyxupup.shinyapps.io/OSofSTSpatientswithLNM/ and https://tyxupup.shinyapps.io/CSSofSTSpatientswithLNM/) to predict 24-, 36-, and 48-month OS and CSS probability of patients with STS with LNM  had concomitant DM, and the prognosis of patients with STS with N1M1 stage was poorer than those with N1M0 stage . MoreoveAt present, the potential benefit of LND remains controversial. Several previous studies have studied the effect of LND and suggested that it could lengthen survival time of patients with STS with LNM , 47. NevThere were several limitations in this study. First, this work was a retrospective study, and selection bias inevitably existed. Second, detailed treatment information and some other potentially relevant variables were not recorded in the SEER database. Future research could add tumor markers and gene expression variables to this base to develop a more comprehensive and superior predictive model. Finally, although the robust extrapolation of diagnostic nomogram had been confirmed with data from another cohort in Asia, because of the rarity of LNM in patients with STS, two prognostic nomograms were still not externally validated in the clinical setting; thus, their clinical value in other populations was unknown and the information derived from those should be used with caution.In this study, we determined the independent risk factors and the prognostic factors of patients with STS with LNM and developed three web-based nomograms to identify patients with STS at high risk of LNM and then to estimate survival outcome for these patients, which might help to guide clinical practice. Further testing and validation based on the data from large multicenter prospective studies were needed to confirm the generalization capability of prognostic nomograms in clinical application.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethics approval was exempted by the local ethics committee and the informed consent was also not required in this study.YT and DZ conceived of and designed the study. YT, YP, and YC collected the clinical data and literature review. YT conducted the statistical analysis. YT, LJ, YP, and YG generated the figures and tables. YT wrote the manuscript. YT and DZ revised the manuscript. DZ supervised the research. All authors critically read the manuscript to improve intellectual content. All authors read and approved the final manuscript.


Scarlet fever is an acute respiratory infectious disease that endangers public health and imposes a huge economic burden. In this paper, we systematically studied its spatial and temporal evolution and explore its potential ecological drivers. The goal of this research is to provide a reference for analysis based on surveillance data of scarlet fever and other acute respiratory infectious illnesses, and offer suggestions for prevention and control.This research is based on a spatiotemporal multivariate model (Endemic-Epidemic model). Firstly, we described the epidemiology status of the scarlet fever epidemic in Sichuan Province from 2016 to 2019. Secondly, we used spatial autocorrelation analysis to understand the spatial pattern. Thirdly, we applied the endemic-epidemic model to analyze the spatiotemporal dynamics by quantitatively decomposing cases into endemic, autoregressive, and spatiotemporal components. Finally, we explored potential ecological drivers that could influence the spread of scarlet fever.From 2016 to 2019, the incidence of scarlet fever in Sichuan Province varied much among cities. In terms of temporal distribution, there were 1–2 epidemic peaks per year, and they were mainly concentrated from April to June and October to December. In terms of transmission, the endemic and temporal spread were predominant. Our findings imply that the school holiday could help to reduce the spread of scarlet fever, and a standard increase in Gross Domestic Product (GDP) was associated with 2.6 folds contributions to the epidemic among cities.Scarlet fever outbreaks are more susceptible to previous cases, as temporal spread accounted for major transmission in many areas in Sichuan Province. The school holidays and GDP can influence the spread of infectious diseases. Given that covariates could not fully explain heterogeneity, adding random effects was essential to improve accuracy. Paying attention to critical populations and hotspots, as well as understanding potential drivers, is recommended for acute respiratory infections such as scarlet fever. For example, our study reveals GDP is positively associated with spatial spread, indicating we should consider GDP as an important factor when analyzing the potential drivers of acute infectious disease.The online version contains supplementary material available at 10.1186/s12889-022-14469-y. Acute respiratory infection (ARI) is one of the leading causes of morbidity and mortality worldwide. Every year, approximately 156 million instances of acute respiratory infections are reported, with children under the age of 5 and those over the age of 65 being the most vulnerable , ARIs raWhile it is critical to have heightened vigilance regarding emerging high-risk respiratory infections, we should not lose sight of those re-emerging infectious diseases with high incidence and outbreaks. A typical example of emerging infectious diseases is COVID-19, which caused a heavy burden on public health and the economy. As of 1 July 2022, there have been 545,226,550 confirmed cases of COVID-19, including 6,334,728 deaths [However, developing vaccines, viral mutations, and the growing problem of antibiotic-resistant bacteria pose remarkable challenges in the prevention of ARIs such as scarlet fever . TherefoIn order to solve the above problems and to better explore the infectious disease on surveillance data, Held  et al. pAs for the spatiotemporal study of scarlet fever, most studies concentrated on dynamics of the epidemic part  –20, ignoMost spatiotemporal research of ARIs is based on the surveillance data of infectious diseases and a limited number of covariates, the urgency of the analysis, the accessibility of covariates, and the result of instability are the main challenges. In this paper, we took scarlet fever as an example, using the EE model to decompose the transmission into three dimensions: endemic, epidemic within city, and epidemic among cities. We also explore the effects of ecological factors in these dimensions. We hope our study can provide a reference for scarlet fever and other ARIs.According to Chinese Infectious Diseases Law, when doctors identify any probable, clinical, or laboratory-confirmed case of scarlet fever, they need to report the case to the Notifiable Infectious Diseases Reporting Information System (NIDRIS) within 24 h .The data of reported cases  of scarlet fever were collected by the Nationwide Notifiable Infectious Diseases Reporting Information System (NIDRIS), which was used under license and not publicly available. We extracted data on scarlet fever in 2016–2019 of the Sichuan province from the NIDRIS, and the data included the number of cases, and patient data on age, sex, and date of disease onset, diagnosis, and address limited to cities. Because all the data in our study were anonymous and without access to the identity information of the patients, and hence, informed consent were waived by the ethics committee of the Sichuan Center for Disease Control and Prevention. The research has been approved by the ethics committee of the Sichuan Center for Disease Control and Prevention (SCCDCIRB-2022-185).Sichuan Statistical Yearbook (http://tjj.sc.gov.cn/scstjj/c105855/nj.shtml), which included population, population density, number of health institutions, number of primary schools, number of kindergartens, passenger-kilometers of Highways and Gross Domestic Product (GDP).Additionally, we collected data on ecological factors from the 2, ranking fifth in China. Sichuan consists of 21 cities and prefectures, with the fourth largest population and the sixth GDP in China. The development of social and economic conditions varies between cities and prefectures in the province.Sichuan province, located in the hinterland of southwest China, between 26°03′ -34 °19′ N and 97°21′ -108 °33′ E, is located in the upper reaches of the Yangtze River and covers an area of 486,000 kmI statistics to calculate the spatial autocorrelation [ωij denotes the weight matrix, X denotes the variable of interest , and I can range from − 1 to 1 where:i)1: The variable of interest is perfectly dispersed;ii)0: The variable of interest is randomly dispersed;iii)1: The variable of interest is perfectly clustered together.We cleaned and analyzed the data using R version 4.0.2. Count data were expressed by frequency and incidence. Firstly, we described the characteristics of population distribution and spatiotemporal distribution of scarlet fever. Secondly, we applied Global Moran’s relation . The forI  test statistics to explore the clusters or outliers in the study area. For the spatial unit i, the formula is defined as [S2 denotes the variance, the value of Ii can disclose spatial clusters or outliers. There are five categories according to the value: high-high, low-low, high-low, low-high, and non-significant. The high-high and low-low areas represent spatial clusters, while the high-low and low-high areas were the outliers. The spatial analysis was conducted by GeoDa 1.20.Thirdly, we used Anselin’s Local Moran’ fined as :2\documeWe adopted the Endemic-epidemic model developed by Held and Paul  to decomYi, t in the region i = 1,…,21 during weeks t = 1,…208. Yi, t follows a negative binomial distribution with the mean μit and overdispersion parameter ψ > 0. We decomposed the transmission into three component as follows:νiteit): infections from outside the study area or from indirect transmission endemic component : reproduction of scarlet fever within city i autogressive component .neighborhood component , indicated no significant spatial autocorrelation of scarlet fever incidence during 2016–2019 in Sichuan province. For Local Moran’s I, as shown in Fig. In our study, the global Moran’s The main transmission is resulted from endemic, including Ganzi, Aba, Ya’an, Meishan, Dazhou, and Bazhong.The main transmission is epidemic within city, including Mianyang, Chengdu, Leshan, and Liangshan.The main transmission are resulted from epidemic within city and endemic, including Ziyang, Neijiang, Zigong, Yibin, Luzhou, Suining, Nanchong, Guang’an, Guangyuan, Deyang, and Panzhihua.Figure Fig. ATable Aνit, λit and ϕit) in the three components of infections to vary for each city as random effects. The results of the final model were shown in Table Because ecological factors could not fully explain the spatiotemporal variation of transmission mechanisms and incidence levels, we allowed the intercept . Moreover, we studied the potential ecological factors that could influence the spread of scarlet fever. Our study could improve epidemiological understanding of scarlet fever, depict the epidemiology status of the scarlet fever epidemic, capture the transmission pattern of scarlet fever, and provide clues for the future prevention and control of acute infectious diseases such as scarlet fever.In our study, males outnumbered females in all patients, according to statistics, which is consistent with previous studies , 39. ThiOur results are consistent with previous studies, the overall incidence of scarlet fever rises in recent years, and the southeast area has more cases than the northwest . We alsoAlthough our results showed there were no spatial autocorrelation of scarlet fever in Sichuan in 2016–2019, we still conducted spatiotemporal analysis for three reasons: Firstly, previous simulation study domonstrated that significant covariate effect in multiple regression but not in univariate regression . The mulAs for the components of transmission of scarlet fever, endemic and autoregressive components accounted for major proportions of transmission in many areas in Sichuan province. This could be due to acute respiratory infections causing symptoms quickly, making relocation to another place unlikely . BecauseThe disparity in ecological conditions will finally cause health inequality . In our To improve the accuracy of our model, we incorporated random effects. If regions showed heterogeneity that cannot be explained by covariates, random effects may be able to capture this unexplained element of the model , especiaCompare to traditional mathematical models, the EE model can study spatiotemporal dynamics from three dimensions: endemic, epidemic within city, and epidemic among cities. And also qualifies the effect of covariates from the above aspects. It could provide more information, such as the main transmission of scarlet fever in this paper—cases are predominantly affected by local past cases rather than cases in other areas and so on. In addition, it allowed random effects to capture more realism in the model.There are several limitations in our study. As for the surveillance data, not all infected individuals seek medical care . As for With the prevalence of new respiratory infections and the global “resurgence” of historical infectious diseases such as scarlet fever, it is critical to optimize public health prevention and control strategies in the absence of targeted vaccines. Globally, acute respiratory infections are the major reason for morbidity and mortality in children under 5 . ScarletBy analyzing the data of scarlet fever from 2016 to 2019 in Sichuan Province, we explored the transmission pattern of this infectious disease from the endemic, temporal and spatial dimensions. Furthermore, we established the ecological factors that could influence transmission. Our work could benefit to optimize strategies for the prevention, detection, and management of scarlet fever and ARI.In this paper, we took scarlet fever in Sichuan province as an example to explore the spatiotemporal transmission rules and potential ecological drivers. Firstly, We discovered that the majority of reported cases were transferred via local previous cases as well as external or indirect transmission through environmental sources. Secondly, we also found ecological factors could also influence the spread of acute respiratory infections such as scarlet fever. For example, school holidays could reduce transmission whereas GDP could boost the spread of scarlet fever. According to our findings, we should focus more on improving environmental disinfection and dealing with earlier occurrences. Because most ARIs lack viable vaccinations, public health initiatives remain critical in combating them. To maximize methods for the prevention, identification, and management of acute respiratory infectious illnesses, a focus on critical populations and hotspots is required, as well as an understanding of how ecological variables promote the spread of acute respiratory infectious diseases.Additional file 1: Table A1. The meaning and value of covariates. Table A2. Demographic characteristics of scarlet fever in Sichuan Province, 2016–2019. Fig. A1. Time series of scarlet fever counts in 21 cities (/prefectures) of Sichuan province from 2016 to 2019. Figure A2. The fitted values for 21 cities (/prefectures) in Sichuan Province during 2016–2019. Fig. A3. The estimated multiplicative effect of seasonality on the endemic mean. Table A3. Model selection and comparison. Table A4. Model without spatial term. Table A5. The estimates of random effects. Fig. A4. Spatial connectivity weights. Fig. A5. The matrix of cities showing the connectivity weights.


Although numerous studies have described the application of artificial intelligence (AI) in diabetic retinopathy (DR) screening among diabetic populations, studies among populations in rural areas are rare. The purpose of this study was to evaluate the application value of an AI-based diagnostic system for DR screening in rural areas of midwest China.In this diagnostic accuracy study, diabetes mellitus (DM) patients in the National Basic Public Health Information Systems of Licheng County and Lucheng County of Changzhi city from July to December 2020 were selected as the target population. A total of 7824 eyes of 3933 DM patients were enrolled in this screening; the patients included 1395 males and 2401 females, with an average age of 19–87 years (63±8.735 years). All fundus photographs were collected by a professional ophthalmologist under natural pupil conditions in a darkroom using the Zhiyuan Huitu fundus image AI analysis software EyeWisdom. The AI-based diagnostic system and ophthalmologists were tasked with diagnosing the photos independently, and the consistency rate, sensitivity and specificity of the two methods in diagnosing DR were calculated and compared.P = 0.566, P>0.05), and the AI-based diagnostic system had high consistency with the ophthalmologists’ diagnostic results (κ = 0.752).The prevalence rates of DR according to the ophthalmologist and AI diagnoses were 22.7% and 22.5%, respectively; the consistency rate was 81.6%. The sensitivity and specificity of the AI system relative to the ophthalmologists’ grades were 81.2%  and 94.3% (95% CI: 93.7% 94.8%), respectively. There was no significant difference in diagnostic outcomes between the methods (χ2 = 0.329, Our research demonstrated that DR patients in rural area hospitals can be screened feasibly. Compared with that of the ophthalmologists, however, the accuracy of the AI system must be improved. The results of this study might lend support to the large-scale application of AI in DR screening among different populations. Diabetic retinopathy (DR) is a complication of progressive diabetic mellitus (DM), capable of damaging retinal vessels, resulting in microaneurysms, retinal exudation, vitreous hemorrhage, retinal traction and so on, and eventually leading to vision loss and even blindness in DM patients. The prevalence of DR among DM patients is 34.6% worldwide, 10.2% of whom suffer visually impaired retinopathy . Thus, iTo date, many methods for DR screening have been proposed, including traditional screening methods, telemedicine and artificial intelligence (AI). Traditional screening methods include fundus photography, scanning laser ophthalmoscopy (SLO), fundus fluorescein angiography (FFA), and optical coherence tomography (OCT). However, neither traditional screening methods nor telemedicine can meet the needs of a growing number of DM patients because ophthalmologists are required to analyze and classify their fundus photos; the accuracy of this classification is affected by the ophthalmologist’s clinical experience, subjectivity, and fatigue, and the entire process is time consuming and requires a large amount of engineering .AI is a relatively new branch of computer science used to research and develop technologies and application systems based on human intelligence. The rapid development of computers has led to the gradual incorporation of AI as the mainstream technology in various scientific research fields . AI was A large number of studies , 13, 14 To solve these problems, we conducted AI diagnosis system-assisted DR screening in rural areas of Changzhi city, Central and Western China, to evaluate the accuracy of using AI in DR screening in rural areas. This study may be of great application value not only for other rural areas of midwest China but also for the regions of other countries with similar socioeconomic backgrounds.This study is a prospective clinical trial of DR screening based on an AI diagnostic system . An epidemiological investigation was conducted with all diabetic patients who met the inclusion criteria. Fundus images were collected and uploaded to the AI system, and the results were automatically graded according to the international DR staging system. The fundus images were collected and graded by an ophthalmologist, and the results were compared with those of the AI system to evaluate the reliability of AI. The flow chart of this study is shown in http://www.chictr.org.cn/showproj.aspx?proj=53446, registered on May 13, 2020). The procedures of this study were performed in accordance with the Declaration of Helsinki. All participants signed informed consent forms.This study was approved by the Evaluation Committee of Changzhi Heji Hospital in Shanxi Province   registration in the National Basic Public Health Information System, awareness of the purpose of the clinical trial and voluntary participation, and signing of the informed consent form ; and (2) type 1 or type 2 DM, male or female sex, and age ≥ 18 years.Exclusion criteria: (1) inability to cooperate with the examination due to serious physical and/or other diseases; (2) refractive media opacity ; (3) poor quality of the acquired image; (4) incomplete screening data, lack of AI results or physician results; and (5) inability to determine DR grading after fundus laser surgery.This prospective study was planned to begin on July 1, 2021, and end on November 30, 2021. The contact information of all the included patients was obtained through the Basic Public Health Information System of Changzhi city. All primary care physicians in the study area are required to register cases of DM in this system. The DM patients were contacted by the general practitioner who is in charge of the community (village) where the patients live. If they could not be contacted, door-to-door notifications were made to each patient through the village committee. DR screening was performed at the local community hospital at an appointed time. The same Zeiss VISUCA500 fundus camera  was used for both counties. Preliminary data, such as age, sex, DM medical history and medication method, and whether DR was diagnosed, were collected. The primary examination was completed with a slit lamp by the chief physician, and patients with corneal leukoplakia, severe cataracts and other eye diseases were excluded. For each eye of every patient, two photographs, including one 45-degree photo centered on the macula  and the The less severely diseased eye of each patient was used for the final diagnosis following a DR grading standard based on the International Clinical Diabetic Retinopathy Scale (ICDRs) . The funhttps://www.nmpa.gov.cn/directory/web/nmpa/xxgk/ggtg/ylqxpzhzhcchpgg/20210714171346191.html) used in this study is an AI-based fundus imaging analysis software integrated into the picture archiving and communication system (PACS), an online retinal image analysis system, that can upload retinal photos, automatically grade DR, and produce single page reports. It has been tested with many different types of fundus cameras during the development of the model, such as the Topcon TRC-NW400, Raymond TNF506, and Center Vue DRS, and has shown good results, with both sensitivity and specificity reaching more than 93%, showing high homogeneity. The ophthalmologist who took the fundus images collected and uploaded patient information to the PACS, including patient name, sex, age, time of diagnosis of DM, visual acuity, and intraocular pressure, and matched it with each image [The Zhiyuan Huitu fundus image AI analysis software EyeWisdom , and the χ2 test was performed to compare between groups. Continuous data are presented as the mean ± deviation, and the The performance of the AI algorithm was evaluated using the ophthalmologist’s diagnostic results as a reference standard. Kappa (κ) statistics were used to quantify and evaluate the degree of consistency between the AI-based diagnostic system and the ophthalmologist’s diagnosis results: κ≥0.75 indicated good consistency between the two methods; κ between 0.40–0.75 indicated that the consistency of the diagnostic results of the two methods was moderate; and κ<0.4 indicated poor consistency in the diagnostic results between the two methods. Sensitivity and specificity were used to evaluate the accuracy of the AI-based diagnostic system in screening DR.A total of 3933 patients were initially involved in DR screening in this study, and 3796 DM patients were finally included; 137 patients were excluded because they could not complete the examinations due to the presence of serious physical and/or other diseases. The included patients consisted of 1394 patients from Licheng and 2402 patients from Lucheng, aged from 19 to 87 years, with an average age of 63.03±8.718 years. Among them, 1395 were male, including 519 from Licheng and 876 from Lucheng, and 2401 DM patients were female, including 875 from Licheng and 1526 from Lucheng. A total of 3722 right eyes and 3709 left eyes were initially enrolled, for a total of 7431 eyes. Of these, 577 (7.76%) eyes were reported as "unreadable" by the AI software, including 481 eyes reported as "unreadable" by the ophthalmologists due to severe cataracts and/or corneal leukoplakia or other reasons that led to refractive media opacity . A totalt = 1.425, P = 0.075; 2 = 0.220, P = 0.639; 2 = 3.051, P = 0.081; There were no significant differences in age  in 5295 (77.3%); the remaining 1559 eyes had different degrees of DR (22.7%). The AI diagnosed NDR in 5310 eyes (77.4%); the remaining 1544 eyes (22.5%) had different degrees of DR. Additionally, to provide a more convincing result, we also analyzed the 577 eyes excluded by the AI system. The detailed results are summarized in P<0.05), and the DR diagnostic rate between the two methods were nearly identical, suggesting that the two methods have strong agreement and can be used in the same study in similar areas, thus supporting the application of AI software in DR screening. There was no significant difference in accuracy between the two methods , suggesting that the two methods were complementary.The diagnostic results of the 6854 eyes in the ophthalmologists’ diagnosis group and the AI diagnosis group are shown in P<0.05). Then, considering the correlation between the two eyes, we performed another person-level analysis, randomly selecting the diagnosis of one eye as the final diagnosis (P<0.05). In addition, 96 of the 577 excluded eyes were identified and diagnosed by the ophthalmologists. Including these eyes in the analysis, random eyes were counted for the final result by individual. For the convenience of calculation, the results of the contralateral eyes were taken as the final result for the eyes that could not be diagnosed by AI; the sensitivity and specificity were 81.2% (95% CI: 79.2%-83.1%) and 93.8% (95% CI: 93.1%-94.4%), respectively. Although the specificity was reduced, the ophthalmologists and AI were still considered to have a good consistency.Considering that we are attempting to promote early screening, we performed a person-level analysis to compare the ophthalmologists’ and AI results, using the less severely diseased eye for the final diagnosis . The seniagnosis . The senP<0.05), although the AI performed slightly worse.In clinical practice, at least moderate NPDR requires intervention, while mild DR only requires blood glucose control and regular follow-up. Therefore, we compared the diagnoses of moderate and severe NPDR and PDR requiring intervention with that of mild NPDR (which does not require intervention) . A satisP<0.05) and Licheng , respectively. For Licheng, the sensitivity and specificity were 93.2% (95% CI: 90.5%-95.2%) and 98.0% (95% CI: 97.2%-98.5%), respectively. The sensitivity and specificity were 75.5% (95% CI: 72.7%-78.0%) and 92.0% (95% CI: 91.0%-92.9%), respectively, for Lucheng. We also examined the misdiagnosed eyes and the 577 eyes excluded by the AI. We found that image quality played a significant role in these cases; some images could be recognized by the AI but not accurately diagnosed due to refractive media opacity. Finally, we compared the performance for the two counties , and theThis study assessed the accuracy of AI automatic analysis software in DR screening. To the best of our knowledge, large-scale DR screening in rural areas has not been conducted in central and western China, and the results of this study showed no obvious difference between the AI and ophthalmologists’ classification results. Therefore, AI-assisted DR screening can be feasibly applied and developed in rural hospitals.Studies have shown that the prevalence of DR in eastern China and rural areas is higher than that in central and western China and cities, respectively, which may be related to income, education, medical conditions and dietary habits , 21, 22.The results of the DR Study Group and the Early Treatment DR Study Group confirmed that timely and effective treatment can prevent severe vision loss in 90% of DR patients and reduce the blindness rate from 50% to less than 5% . InitialP<0.05), suggesting that the method of DR screening conducted by AI has strong repeatability and can be used for identical studies in similar areas, thus promoting the application of AI software in DR screening to the benefit of more rural areas. More DM patients can be screened by DR to achieve early prevention, early diagnosis and early treatment. However, according to this study, there was a discrepancy in the AI-ophthalmologist consistency between Lucheng and Licheng . The possible reason for this discrepancy might be that the population bases of the two counties were different and the prevalence of DR was also different. Nevertheless, our study showed that the overall consistency rate between AI and ophthalmologists was satisfactory (81.6%), and therefore, this AI system can be used for DR screening in rural areas.At present, there are many studies on the application of AI in DR screening. Based on fundus photography, Abràmoff et al.  showed aThis study also had some limitations. New DM patients who had not been included in the National Basic Public Health Information System of Changzhi were not included in this study. Although the AI software can automatically grade retinal images, it cannot overcome physiological limitations, such as unsatisfactory retinal photos from patients with small pupils and cloudy lenses. Second, the AI-based diagnostic system has difficulty diagnosing macular cystoid edema with only fundus color images. Therefore, the AI-based diagnostic system cannot accurately classify macular cystoid edema caused by DR; this matter is an important drawback that will be improved in the future.In conclusion, compared with that of the ophthalmologists’, the sensitivity of the AI software system in screening DR was slightly lower, but the difference in the diagnostic accuracy rate was not obvious; additionally, the AI system had a similar specificity to that achieved in other research studies. The AI diagnosis system for screening DR in rural areas is feasible, but the accuracy needs to be further improved. Establishment of the AI system requires the reading of and training with many images, but this will help alleviate ophthalmologists’ imaging reading habits and will be conducive to DR patients in rural areas receiving timely, effective and accurate treatment. The AI software in this study needs to be further improved to improve its the photo reading quality and accuracy to provide a method and platform for large-scale DR screening.S1 File(XLSX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(DOCX)Click here for additional data file.


Hand, foot and mouth disease (HFMD) is a serious infectious disease which has become a public health problem. A multi-regional study was conducted in this study to explore the relationship between temperature and HFMD in different regions and the source of heterogeneity, and further detect the effect modifiers such as socio-economic factors, medical and health factors and meteorological factors.The data on daily reported HFMD cases and meteorological data from 2010 to 2019 in Chongqing were collected. Thirty-eight districts and counties of Chongqing were divided into 6 regions. The distributed lag nonlinear model (DLNM) was applied to assess the effect of daily mean temperature on HFMD at region level with the pooled effect estimates from multivariate meta-regression model analysis. Stratified analyses by gender, age and children’s type were also conducted. Potential modifiers were considered in meta regression to explore the source of heterogeneity.There were nonlinear relationships with an inverted V-shape between temperature and HFMD. A maximum cumulative relative risk (CRR) of 1.22 : 1.12–1.34) peaked at 23.8 °C, and the risk appeared immediately and lasted for the whole 14 days. Compared with other groups, warm temperature had a stronger effect on children aged 0–1 and scattered children, while cold temperature had a stronger effect on female, children aged 3–6 and childcare children with an M-shape. We found that socio-economic factors, medical health factors and meteorological factors were significantly associated with heterogeneity. Density of medical technical personnel, urbanization rate and density of health care institutions were the main modifiers for explaining heterogeneity of 26.10%, 24.90% and 24.86% respectively which were revealed by meta-analysis.There was a significant nonlinear correlation between temperature and HFMD. Compared with other groups, children aged 0–1 and scattered children were more susceptible to warm temperature, while female, children aged 3–6 and childcare children were more susceptible to cold temperature. Socio-economic factors, medical health factors and meteorological factors may be the source of the heterogeneity. Therefore, local governments should consider different temperature–HFMD relationships between different regions and populations when formulating appropriate preventive measures.https://doi.org/10.1265/ehpm.22-00133.The online version contains supplementary material available at   Nowadays, climate change is considered as one of the greatest challenges threatening human health . ControlHand, foot and mouth disease (HFMD) is one of the legal class C infectious diseases in China which is caused by a variety of enterovirus infections . The disChongqing is located in the southwest of China, in the middle and upper reaches of the Yangtze River. It is dominated by mountainous terrain. Affected by the terrain drop, the climate and economic development of each region in Chongqing are significantly different, with the typical characteristics of a dichotomy between a large city and a large rural area. Based on the above, the internal incidence of infectious diseases in the Chongqing often shows strong heterogeneity on the basis of commonality. Therefore, in order to analyze the influence of temperature on HFMD and explore the source of its heterogeneity, this study took Chongqing as the research area. According to the economic and climatic characteristics, Chongqing were divided into 6 regions, and a multi-region analysis was conducted. This study aimed to assess the impact of temperature on HFMD and to examine potential effect modification by socio-economic factors, medical and health factors and meteorological factors in six regions in Chongqing, China, with DLNM and multivariate meta-regression model analysis. The findings can provide useful information to the development and implementation of appropriate regional intervention strategies.2, of which the mountainous area accounts for about 75% of the total area. Chongqing has 38 districts/counties and a total population of 31.2 million by the end of 2019. According to the geographical features, meteorological characteristics [Chongqing is located in the southwest of China, with a total area of 82,400 kmeristics , economieristics  of HFMD,http://www.cdpc.chinacdc.cn), including the basic social demographic information of HFMD cases. In mainland China, HFMD has been monitored and reported as a class C notifiable disease since 2008. The diagnostic criteria of HFMD were based on the clinical criteria set by the Hand, Foot and Mouth Disease Control and Prevention Guide published by the National Health Commission of the People’s Republic of China [The daily data of HFMD cases from 1 January 2010 to 31 December 2019 in 38 districts and counties of Chongqing were obtained from China Information System for Disease Control and Prevention  represents the expected number of HFMD cases on day t. α is the intercept. γl represents coefficient; tempt,l represents the cross-basic of temperature and time.In the first stage, a time-series DLNM with quasi-Poisson regression was applied to assess the effect of daily mean temperature on daily reported HFMD in the 6 regions respectively. The bi-dimensional exposure-lag-response relationship between temperature and HFMD was described through a cross-basis function , using n2 statistic [In the second stage, the region-specific estimates obtained from the first stage model were then combined through multivariate meta-analysis to reveal the pooled exposure–response relationship , and we tatistic . GoodnesAll data analyses were performed in R 4.2.0, with the “dlnm” package to fit the DLNM and “mvmeta” package to conduct multivariate meta-analysis. Two-sided P values less than 0.05 were considered as statistically significant.Table Figure Table Figure Figure Figure 2 suggested that 73.32% of heterogeneity was due to actual difference of 6 regions. According to the P values of Wald test and I2, nine modifiers were associated with temperature-HFMD relationship, including longitude, urbanization rate, per capita GDP, density of health care institutions, density of medical technical personnel, temperature, humidity and sunshine hours, which were significantly related to the heterogeneity for decreasing I2. In particular, density of medical technical personnel could explain the largest proportion of heterogeneity with ΔI2 equal to 26.10%. Urbanization rate and density of health care institutions could explain heterogeneity of 24.90% and 24.86%, respectively. Besides, we displayed the modification effects of urbanization rate, density of medical technical personnel, sunshine hours and longitude, which could reduce the heterogeneity to 27.00%.The results of random-effect meta-analysis (intercept-only) and multivariate meta-regression with a meta-predictor in the second stage were shown in Table Figure In this study, we found that the daily cases of HFMD in Chongqing had a semiannual peak with a relatively obvious seasonality. The first peak was concentrated in late spring and early summer (April–July), and the second peak was in autumn (October–December). This was because the climatic conditions during this period, such as temperature, humidity, and sunlight, were suitable for the survival and reproduction of pathogens. A study  showed tIn the present study, we pooled the overall cumulative effect of 6 regions which showed an approximately inverted “V”-shape which was consistent with the results in other studies , 32, andFrom 2010 to 2019 in Chongqing, the number of HFMD cases was 1.39 times higher in males than in females, but the effect of cold temperature on HFMD was slightly higher in females than in males, which was similar to the results of a study in Beijing . It has Socio-economic factors, medical and health factors and geo-meteorological factors were taken into account as potential effect modifiers in this study. The results suggested nine modifiers were related to temperature-HFMD relationship. We found that in areas with lower urbanization rates and lower per capita GDP, the warm temperature had a stronger effect on HFMD. According to the study , the higThe present study also had some limitations. First, the present study selected 38 districts and counties in Chongqing and divided them into 6 regions, so the findings may not be well generalized to other locations in different climatic zones. Second, the modifiers in this study only explained a part of heterogeneity, there were many other modifiers need to be collected. Third, due to data limitations, we did not control the effect of air pollution on HFMD.In conclusion, we conducted a two-stage analysis to investigate the effect of temperature on HFMD in 6 regions and further detect the effect modifiers. We found there were nonlinear relationships between temperature and HFMD, with a maximum CRR of 1.22 (95% CI: 1.12–1.34) at 23.8 °C. In general, the warm temperature had a stronger effect on HFMD. Compared with other groups, children aged 0–1 and scattered children were more susceptible to warm temperature, while female, children aged 3–6 and childcare children were more susceptible to cold temperature. Besides, the warm temperature had a stronger effect in areas with lower economic development and poorer health care. The results can also help local authorities take corresponding interventions and measures to control HFMD development before reaching the peak risks.


Intramural hematoma (IMH) is considered a part of acute aortic syndromes (AAS), a group of life-threatening aortic diseases with a similar presentation that appears to have different clinical manifestations and pathological and survival characteristics. AAS comprises three major entities, namely, aortic dissection (AD), IMH, and PAU. IMH-like classic AD is classified using Stanford and DeBakey classification systems to indicate the aortic area involved.Early diagnosis and treatment of AAS are crucial for survival; however, diagnosis of IMH may be delayed and challenging due to atypical presentation, investigation findings, and case progression. In this report, we describe a case of delayed and challenging diagnosis of a Stanford type A IMH that was managed surgically with a good outcome. Acute aortic syndrome (AAS) describes a group of life-threatening aortic diseases (ADs). It comprises three major entities, namely, AD, intramural hematoma (IMH), and penetrating aortic ulcer (PAU) . The aorIMH is classified using Stanford type A or B and DeBakey classification systems to indicate the aortic area involved. Most patients 50-85%) with IMH have Stanford type B. Clinical manifestations are similar in AAS patients, i.e., chest pain such as classic AD aortic pain. Rarely, patients may present with syncope, anterior spinal pain syndrome, hoarseness, or acute renal insufficiency . Conclus5% with IAs CTA exposes patients to radiation and large doses of intravenous contrast, and transesophageal echocardiogram (TEE) and MRI may not be available or performed at the appropriate time, there are ongoing attempts to find simple and available methods that can help clinicians avoid misdiagnosis and overtesting of AAS. For that aim, studies have shown the importance of D-dimer and Aortic Dissection Detection Risk Score (ADD-RS) in the diagnosis of AAS. D-dimer is a useful screening tool to identify patients who do not have acute aortic dissection using a cutoff of 500 ng/mL. A level below this value is highly predictive of excluding dissection . ADD-RS The incidence of initial misdiagnosis of AAS is up to 40% and may be more common when the ascending aorta is involved ,15. PeriPatients with AAS can present with a non-specific complaint or progress atypically which makes early diagnosis difficult. This report presents a case of delayed and challenging diagnosis of Stanford type A IMH that progressed to classic aortic dissection which was managed successfully by surgery to repair the aorta.We present the case of a 47-year-old male Sri Lankan patient with a history of hypertension and type 2 diabetes mellitus on regular medications. The patient also had a history of right kidney hydronephrosis three years before presentation, which completely resolved during follow-up. The patient had no other cardiac risk factors, no cardiac history, no surgical history, and no family history of cardiac disease or sudden cardiac death. Apart from medication for hypertension and diabetes, the patient denied using any other medications.The patient presented to the emergency department with sudden onset of central chest pain that started two hours before the presentation. The pain was severe, continuous, and radiated to the back. There were no associated symptoms and had no other complaints.The patient’s vital signs and measurements were as follows: height: 165 cm, weight: 81 kg: temperature: 36.6°C , blood pressure: right arm 105/62 mmHg and left arm 110/67 mmHg, heart rate: 73 beats/minute, respiratory rate: 18 breaths/minute, oxygen saturation: 100% on room air.On presentation, the patient was conscious and oriented and was still complaining of chest pain despite receiving morphine (IV 5 mg). Jugular venous pressure was not raised. Pulse was synchronized and equal in four limbs (no pulse deficit). On heart examination, S1-S2 was normal and regular, without murmurs or additional sounds. The chest was clear. On examination of the abdomen, it was soft and non-tender, without scars, organomegaly, and masses. On examination of the central nervous system, the patient was alert, with no focal neurological findings. Lower limbs: There was no pitting edema in the lower limbs, with no signs of deep vein thrombosis.The electrocardiogram (ECG) showed sinus rhythm and low voltage with non-specific ST-T changes Figure . Right aThe patient’s troponin T was <10 ng/L, white blood cell (WBC) count was 9,400/µL, hemoglobin was 12.6 g/dL, platelet count was 270,000/µL, and international normalized ratio (INR) was 1.1. Thyroid, renal, and liver functions were normal. D-dimer was 0.30 mg/L. Other lab tests were unremarkable.Due to continuous chest pain and mediastinal widening on chest X-ray, CTA with contrast was requested to rule out AD. CTA showed thickening of the intimal wall with atherosclerotic calcification without any evidence of dissection or aneurysmal dilation Figure .Transthoracic echocardiography showed an ejection fraction (EF) of 68%, which indicated a normal study Figure .The patient was admitted under cardiology care as a case of chest pain for evaluation with a possible diagnosis of acute coronary syndrome. Anti-ischemic treatment was initiated .On the evening of the admission day (after 15 hours of admission), the patient was still complaining of chest pain, and he developed severe epigastric pain and vomiting. At that time, he was vitally stable. No new ECG changes and no elevation in cardiac enzymes were noted. Physical examination showed no new findings. Troponin T: four sets negative), WBC count 9,400 to 12,200/µL, C-reactive protein (CRP) 65 mg/L, lipase 14 U/L , D-dimer 0.30 mg/L, and procalcitonin 0.32 ng/mL.Due to severe epigastric pain and vomiting, the patient was evaluated by the general surgeon who advised to hold antiplatelet and anticoagulants as the patient possibly needed surgery. Moreover, the patient stayed on pain management medication , oral antidiabetics, antihypertensives, and antibiotics until he was transferred to CT surgery.The general surgeon requested abdominal ultrasound and X-ray. The abdominal X-ray was normal. Abdominal ultrasound was also normal except for a right cortical kidney Figures , 6.On the second day of admission, the patient was still complaining of chest pain, severe epigastric pain, and vomiting, and he developed a low-grade fever. He appeared uncomfortable and vitally stable, with no new ECG changes. On examination, no new findings were noted. TroponinT five sets were negative.The general surgery and urology teams evaluated the patient (who was cleared from their side). He was also evaluated by the internal medicine team because of abdominal pain, vomiting, and fever. They suggested an infection workup, blood culture aerobic and anaerobic, procalcitonin, and urinalysis to rule out urinary tract infection.On the third, fourth, and fifth day of admission, the patient was still complaining of epigastric pain, vomiting, and high-grade fever (39°C). On examination, there were no new significant findings. On ECG, there were no new changes. Troponin T five sets were negative. There was a significant elevation of inflammatory markers. WBC count increased from 9,400 to 12,200 to 13,600/µL. CRP from 65 to 359 mg/L. Blood culture showed no growth. At that time, the patient was re-evaluated by the internal medicine team which suggested starting ceftriaxone 2 g IV OD and to follow-up with a urine dipstick, urine culture, and blood culture.On the sixth day of admission, the patient had the same complaints, with no new findings. Because of the fever and elevation of inflammatory markers, the infectious disease team was consulted, and they suggested changing ceftriaxone to piperacillin/tazobactam. They also suggested repeating septic workup, and abdomen/pelvic CT to rule out any collection.CT of the abdomen and pelvis was done which showed that the patient had an abdominal AD; hence, CT with contrast for the whole aorta was done which showed Stanford type A AD Figure .Once the patient was diagnosed with AAD, he was promptly transferred to a CT surgeon where he underwent cardiothoracic surgery for aortic repair. According to the CT surgeon’s report, the patient was found to have type A AD caused by intramural hematoma that extended from the aortic root and involved the ascending arch of the aorta and beyond. No intimal tear was seen. The ascending aorta was excised and replaced by an interposition graft. The patient had a smooth hospital course and was discharged in a good condition. The patient underwent regular follow-ups in the cardiothoracic outpatient clinic. A follow-up CT for the whole aorta was done twice after surgery (six months and 18 months), which showed no evidence of a complicated graft or recent AD.IMH is a new entity of AD that ranges from 5-25% of AAS. It is more prevalent in the elderly and women . The finHowever, the diagnosis of AAS is frequently mistaken for other etiologies that cause chest pain, with the most common being acute coronary syndrome. The incidence of initial misdiagnosis is up to 40% and may be more common when the ascending aorta is involved ,15.In our case, four factors contributed to the difficulty and delay of the diagnosis. The first CT scan of the whole aorta (which was done on the first day of admission) did not show any evidence of AAD, rather there was a mild thickness in the wall of the aorta which was considered by the radiology team to be atherosclerotic changes. Transthoracic echocardiography was negative for AAD. There was a low probability of AAD according because ADD-RS was 1 and D-dimer was 300 ng/mL cut-off (<500 ng/mL). There was an abnormal progression of the patient after a few hours of admission as he had a fever and an elevation in the inflammatory markers as follows: temperature 39°C, WBC count 9,400/µL to 12,200/µL to 136,00/µL; and CRP 65 mg/L to 359 mg/L.The diagnosis of AD was confirmed on the sixth day based on the results of the second CT scan (done on the sixth day of admission) that showed findings of classic type A AD. The diagnosis of AAS was not present at the time of admission based on the first CT of the whole aorta with contrast (done upon admission) that showed only thickness of the aortic wall which was considered by the radiology team as atherosclerotic changes, without evidence of dissection or aneurysmal dilation Figure .The possibility of IMH was diagnosed retrospectively on the sixth day of admission based on the result of the second CTA, as it was believed that the classical signs of AAD of the second CTA probably resulted from the progression of IMH which was excluded upon admission because of the previously mentioned reasons. Second, the CT report confirmed the presence of extensive type A AD caused by IMH that extended from the aortic root to involve the ascending aorta and the arch of the aorta and beyond. No intimal tear was noted.When the diagnosis of AD was confirmed, the CT surgeon was informed, and the patient promptly underwent cardiothoracic surgery for aortic repair.Our patient also developed high-grade fever and significant elevation of inflammatory markers which may occur in patients with AAD. The presence of these features, especially CRP elevation, is considered a sign of poor prognosis and is associated with high morbidity and mortality ,19.As noted above, there were several challenges in this case (imaging and laboratory test results in addition to case progression) that contributed to the delay in the diagnosis of AAS. We believe that these findings have not been discussed before in the literature which adds to the uniqueness of this case report.AAS describes a group of life-threatening conditions that should be a part of the differential diagnosis of patients presenting with chest pain because early diagnosis and treatment of AAS are crucial for patient survival. Because the diagnosis of AD can be misleading, normal imaging findings should be reviewed if there is a high suspicion of AAS. Repeating imaging or using different modalities may be required in certain cases. Unfortunately, some findings  may misguide clinicians from the right diagnosis. Therefore, it is important to correlate investigation results with clinical findings, especially in the presence of persistent symptoms. Finally, correlating investigation results with clinical findings and knowing the uncommon and atypical presentations of the disease can save effort and time to reach the diagnosis.


The aim of the present study is to explore the relationships between cognitive–behavioral patterns of perfectionism in the context of competitive sport and both prosociality and aggressiveness in a sample of adolescents competing in federated sports. A cross-sectional and non-randomized study was designed using a selective methodology on a sample of adolescents (N = 234) competing in federated sports. Scales to assess aggressiveness, perfectionism, prosocial behavior, and competitiveness were administrated. The results show that as age increases, prosocial behaviors increase and aggressive behaviors and competitiveness decrease, while there was no one significant perfectionist tendency. Competitiveness showed a direct relationship with aggressive (positive) and prosocial behaviors (negative). Self-oriented perfectionistic behavior showed a direct and significant relationship with prosocial behaviors, but no significant relationship with aggressive responses. As P-SP and P-OD tendencies increased, significantly smaller links were shown with prosocial behaviors, but greater links were shown with aggressive behaviors. A path (mediation) model showed a positive and predictive relationship with aggressive behaviors and a negative relationship with prosocial altruistic behaviors. The negative influence of criticism from significant figures in their environment and unrealistic expectations about their performance are relevant to difficulties in self-regulating social relationships in adolescents. Hence, it is a challenge to promote prosocial resources  in the face of the early angst of young athletes, who put their maturity to the test under conditions of high pressure and demands. The present study continues to reinforce the line drawn on perfectionism and prosocial development in young people in sports contexts where young people, measured early on according to their performance, can accentuate and deepen competitive tendencies that alter their adaptive and self-regulatory capacities, as well as their psychosocial projection. A context that measures the individual by their performance is characterized by strong social pressure , a fixatHowever, when family members and/or coaches do not provide support or consider age-related, maturational developmental processes , a youngMultidimensional models of perfectionism have been proposed in the past decade ,16,17. APerfectionism, which is linked to achievement orientations, arises in performance contexts and drives individuals to attempt to stand out, excel, and seek perfection. On an interpersonal level, perfectionism affects the way we relate and connect with people. According to the perfectionism social disconnection model SDPM; ,21) The World Health Organization  emphasizAlthough there is no research on perfectionist social disconnection in young people who practice competitive sports, it is a model that could explain the psychological experience of young people subjected to high pressure in sport at an early age. Rice et al.  differenAggressiveness  is a derivation of the anxiety mechanism because it presents a reflexive emotional response  to not being able to handle or control a situation . It is nParticipation in organized sports offers young athletes a wealth of opportunities for social interaction   which caThe aim of the present study is to explore the relationships between cognitive–behavioral patterns of perfectionism in the context of competitive sport and both prosociality and aggressiveness in a sample of adolescents competing in federated sports. To this end, and accounting for gender, the hypothetical model  suggestsyears; DE = 2.96) from different sports clubs and federations participated in the study. A descriptive analysis yielded evidence that there were more boys than girls in terms of the proportion federated in their sport (♂54.25% vs. ♀26.43%) and that boys reported higher feelings of competitiveness in sport than girls (♂64.31% vs. ♀41.36). Boys were typically more involved in the practice of collective sports than girls (♂47.87% vs. ♀19.28), while a higher proportion of girls described themselves as “not at all competitive” (♀35% vs. ♂19.14%) and as having a higher feeling of competitiveness in academics (♀40.42% vs. ♂ 12.14%).A sample of 234 adolescents  and the center (management teams), who were also informed of the objectives of the study, the voluntary nature of participation, and the fact that participants had absolute freedom to leave the study at any time. In addition, the informed consent form included information concerning the form of contact with the researchers and their commitment to confidentiality and the anonymity of the participants, as well as the methodological rigor that would be applied to the information provided. An online Google Form application was developed with response templates for the evaluation instruments. Teaching tablets or smartphones were used to administer the questionnaires. The questionnaires were administered at a single designated time in the classroom, without the presence of the teaching staff and in the presence of the research staff, guaranteeing the anonymity and confidentiality of the data obtained. The latter could answer any questions that arose during the completion of the questionnaires. The questionnaires and their administration protocol complied with the provisions of the University of Granada Ethics Committee (1726/CEIH/2020).Sociodemographics. An ad-hoc self-report form was designed with the aim of answering some general questions about the sample collected ).2/gl = 29.78; p = 0.00; CFI = 0.93; NNFI = 0.92; CFI = 0.92; SRMR = 0.08; RMSEA = 0.03).Physical and verbal aggression. For the measurement of this variable, we used the Spanish adaptation of the Physical and Verbal Aggression Questionnaire (AFV) , which i2/gl = 32.45; p = 0.00; CFI = 0.90; NNFI = 0.92; CFI = 0.94; SRMR = 0.07; RMSEA = 0.04).Perfectionism. The Spanish version of the Multidimensional Perfectionism Scale (MPS) by , adapted2/gl = 23.17; p = 0.01; CFI = 0.91; NNFI = 0.92; CFI = 0.96; SRMR = 0.08; RMSEA = 0.03).Prosocial Behavior. The Adolescent Prosocial Tendencies Scale  was applt-tests of mean differences (by gender) were performed. The Pearson correlation showed a linear relationship (p < 0.05) between all the variables under study. A mediation analysis of the observed variables was performed using the maximum likelihood estimation method. A model was run to test the direct path between patterns of perfectionism, prosocial behavior, and aggressive tendencies. Error variances were allowed to correlate with each other, and the indirect pathway between patterns of perfectionism, and aggressive behavior through prosocial behavior was tested. The effect of sex, subjective competitiveness perception, and age was controlled for to test the robustness of the results. Finally, a multi-group analysis was performed to examine differences in the hypothesized model according to gender. An incremental chi-square test and an incremental NFI test were performed to examine whether there was a significant change between a restricted and an unrestricted model for different genders [Initially, a descriptive analysis of the sample  and consistency of measurement tests  were performed . The nor genders . Statist genders ,49.t-test analyses by gender did not show significantly higher means in any perfectionistic tendency but did show significantly higher means in altruistic prosociality in girls (<0.05). In contrast, boys showed significantly higher differences in subjective competitiveness perception relative to girls (=0.00). The multi-group analysis showed non-significant differences between the model without constrictions and the model with constrictions χ2  = 6.21 (n.s). The first model, with constrictions, assumes that all relationships between variables are equal for boys and girls, whereas in the second model, without constrictions, all coefficients are estimated in both groups. Since there are no differences between them, the model with more degrees of freedom is the most appropriate. This result supports the structural invariance of the model in both genders, which increases the generalizability and applicability of the model.Correlation analyses  showed l2 (df = 36) = 61.74; p = 0.04, CFI = 0.991, RMSEA = 0.039). In both the first model (for boys)  = 7.82; p < 0.01) and the second (for girls)  = 10.37; p < 0.02), significantly adequate fits were achieved.Once the non-existence of differences was verified and the covariances were restricted so that they were equalized according to gender, and taking into account the higher degrees of significance between the variables in the correlation analysis, different estimations were performed to reach a path analysis from perfectionistic tendencies to aggressive behaviors , and this provided a good fit with the data (Xp = 0.00) and aggressive behaviors (p < 0.01) showed a predictive and positive relation, altruistic prosocial behaviors exerted a protective value for aggressive behaviors in young athletes (p = 0.00).1), while prosocial behavior would exert a protective influence on the relation between perfectionism and aggressive tendencies in young athletes (H2). As expected, the present findings suggest that a perfectionist orientation  can lead to more conflicts and difficulties in social relationships in contexts where there is a high perception of competitiveness. Importantly, the findings also yield evidence that altruistic prosocial behaviors might attenuate the link between perfectionism and aggression.The contingencies that govern and operate in youth behavior depend on the interaction of the person with his or her environment, and this is important to consider in order to better understand how persons will act in a specific context . FederatThe main findings suggest that altruistic prosocial behaviors significantly weakened the relation between socially prescribed perfectionism and aggressive behaviors. It is precisely socially prescribed perfectionism—the most complicated perfectionist orientation to interpret  and the Prior research shows that behaving prosocially is significantly related to achievement tendencies ,56,59. IThere were some interesting gender-related findings. In the present study, regarding socially prescribed and other-oriented forms of perfectionism, there were no significant differences between boys and girls, which is consistent with prior research conducted in other performance contexts  ,62,63. TInterestingly, both the positive relationship between competitiveness and aggressive tendencies and the negative relationship between competitiveness and prosocial tendencies alleviate doubts raised in earlier research ,66,67,68It is necessary to point out some of the limitations of this study. The sample size, although relevant, requires us to be scrupulous when making generalizations based on the data, or when drawing comparisons with other samples in which different types of sports contexts are considered . It is also important to maintain the precautions derived from the cross-sectional condition of the study’s design, as well as the contextualization of young people in different conditions of sporting competitiveness . Finally, regarding permits and access to athletes, difficulties involving contact, bureaucratic delays, and waiting times due to ethical protocols  were experienced. Future research should continue to explore the relations between these variables and involve study participants from other regions and countries, and from other sports modalities. Stronger inferences concerning causality and the direction of effects would be possible with stronger study designs , and this would enable us to better establish evidence concerning the impact of perfectionist orientations on prosocial and aggressive behaviors in competitive sports contexts.The present study contributes to our understanding of the relations between perfectionism and prosocial and aggressive development in young people in sports contexts. The perfectionist orientation in competitive sports contexts is inevitable; it is inherent to the act of surpassing oneself and achieving sporting goals. Hence, it is important to prepare young athletes  to cope with and manage both their emotional and behavioral processes and social relationships in sporting contexts. In young players, the criticisms of significant figures in their environment or the creation of unrealistic expectations concerning their performance  can create contexts of unhealthy rivalry, endangering the generation of prosocial bonds at the cost of winning or not losing. It is in these emotional states that the difficulty to self-regulate in social relationships will be greater, and in which behaviors intend to satisfy the demands and alleviate the discomfort of sporting pressure will be observed.Some practical implications can be pointed out for sports professionals involved in the training of young athletes. First, providing positive support to young athletes can contribute to the development of individual traits that allow them to adapt to the demands of the competitive context and develop positive psychosocial skills for the enhancement of their sports careers. In addition, it is essential that the adults  surrounding young athletes pay attention and undertake efforts to improve their involvement during training and matches, regulating and projecting demands that favor the sporting development of their children/athletes.Promoting pro-social resources is a challenge in the face of the early angst of young athletes who put their maturity to the test under conditions of high pressure and demands. These strategies, if internalized and incorporated by coaches and parents, but also by the young athletes themselves, will favor adequate motivational climates, positive transformation through adult leadership, the incorporation of reasonableness in the work of understanding sports rivalry, and socioemotional improvements in competing and overcoming challenges in sports training, as well as the psychological adaptation of young athletes.


Gevuina avellana Mol., Proteaceae) is a native tree of Chile and Argentina of edible fruit-type nut. We applied two approaches to contribute to the development of strategies for mitigation of the effects of climate change and anthropic activities in G. avellana. It corresponds to the first report where both tools are integrated, the MaxEnt model to predict the current and future potential distribution coupled with High-Resolution Melting Analysis (HRM) to assess its genetic diversity and understand how the species would respond to these changes. Two global climate models: CNRM-CM6-1 and MIROC-ES2L for four Shared Socioeconomic Pathways: 126, 245, 370, and 585  were evaluated. The annual mean temperature (43.7%) and water steam (23.4%) were the key factors for the distribution current of G. avellana (AUC = 0.953). The future prediction model shows to the year 2040 those habitat range decreases at 50% (AUC = 0.918). The genetic structure was investigated in seven natural populations using eight EST-SSR markers, showing a percentage of polymorphic loci between 18.69 and 55.14% and low genetic differentiation between populations . According to the discriminant analysis of principal components (DAPC) we identified 10 genetic populations. We conclude that high-priority areas for protection correspond to Los Avellanos and Punta de Águila populations due to their greater genetic diversity and allelic richness.The Chilean hazelnut ( Gevuina avellana Mol. is a native tree of Chile and Argentina, monotypic of the genus Gevuina (Proteaceae) . The. TheGevue family . In Chilcuttings ,14,15,16cuttings . At the cuttings . A phylo contain ,22,23. Gsymptoms . Varioussymptoms ,27,28,29symptoms ,32,33. Tsymptoms ,35.Native plants are one of our most powerful tools for protecting and conserving healthy and resilient ecosystems. Successful native plant restoration facilitates the conservation of innumerable species interactions, such as between plants, their consumers, and their pollinators, that provide the foundation of ecosystem services upon which humans and wildlife depend . When thThe maximum entropy modeling (MaxEnt) is a multivariate approach that estimates the distribution of a species by finding the probability distribution of maximum entropy, subject to constraints representing our incomplete information about the distribution . The maxMonitoring global biodiversity from space through remote sensing geospatial patterns has a high potential to add to our knowledge acquired by field observation. Nevertheless, some essential biodiversity variables (EBVs) are not directly measurable by remote sensing from space, specifically the EBV class genetic composition . To asseG. avellana Mol. present in Chile. It corresponds to the first known report of the genetic structure and spatial distribution described for the species in the Region, which was developed mainly in natural populations that are not part of the National System of Protected Wilderness Areas of the State (SNASPE) administered by the National Forest Corporation (CONAF). At the same time, another of the objectives of this research is to propose an alternative methodology that may successfully replace more expensive molecular analyses or difficult interpretation, which could benefit conservation genetic studies using the analysis of HRM, which once optimized; is a fast, low-cost technique, especially when massive plant genotyping is required. Finally, the study aims at professionals interested in the conservation or ecological restoration of plants  who wish to incorporate in their research alternative methodologies to their areas of specialization. When species of which little or nothing is known, it is advisable to use MaxEnt Model and HRM Analysis as a strategy for gathering rapid and integral information.The present work seeks to contribute to the knowledge of the northernmost known natural populations of G. avellana distribution at the regional level. Therefore, it was relevant and transcendental for the successful development of the research to rely on the empirical and ancestral knowledge that we were able to record from the local peasant communities. These communities base part of their subsistence economy on the collection of fruits that they later market locally, either as dried or processed fruits (mainly as flour). As a result of this collaborative work and information provided by the locals and transmitted generationally, we were able to categorize geographically, phenologically, and phenotypically several centuries-old, natural populations of G. avellana not previously described that, for the most part, were part of peasants’ properties or other private sectors surrounding them. With this, we were able to select, evaluate and rescue trees using tissue culture techniques (unpublished data) with contrasting characteristics of interest and adapted to the edaphoclimatic zones of the region  where the presence of in Range . A totalin Range . G. avellana in Central Chile (Maule Region) and project the possible variations that this habitat could suffer under different environmental scenarios, twenty-three different environmental variables were analyzed using the MaxEnt tool. Validation of our model allowed us to arrive at AUC values of 0.953 for the potential current habitat of G. avellana, indicating that the prediction results are very accurate, which can be used for subsequent analysis , and their ideal habitat would move and concentrate in the highest sectors of the Andes mountains in height ranges that go from 520 to 1200 meters above sea level or higher.avellana , Table 2G. avellana. G. avellana from each population, using the EST-SSR marker Ga38. The shape of the melting curves revealed the difference between the genotypes and showed that all genotypes could be easily distinguished based on their melting curves.The genotypes tested with eight EST-SSR markers and selected as HRM Standard or Reference Profile  generated unique melting curves over different temperature ranges . The molecular markers evaluated subsequently in each population allowed the detection between three and five melting curves . Figure G. avellana. The optimal combination of the eight EST-SSR markers allowed the discrimination of all the individuals analyzed. On the other hand, the effective number of alleles per locus (Ne) for the total of the local populations was 1.40 ranging from 1.18 (Canelillo) to 1.55 (Punta de Águila). The coefficient of genetic differentiation (GST = 0.0431) indicates that 4.31% of the genetic diversity is found between populations and 95.69% within populations. The percentage of polymorphism in the analyzed populations remained in a range of 18.69%–55.14%, with the populations of Punta de Águila and Los Avellanos showing the highest percentages of polymorphism . The situation that is maintained for these populations when analyzing Private alleles (Pa) whose values range between 59 for the Punta de Águila population and 53 for Los Avellanos.G. avellana analyzed indicate that the highest percentage of variation is within the populations with 95%. followed by the genetic diversity present among the populations, with a total of 5% of the observed variance. Genetic differentiation between populations was moderate  (The results of molecular variance (AMOVA) for the seven populations of < 0.001) .The value of the Bayesian information criterion (BIC) based on the binary matrix (0 and 1) with the combined data of the eight EST-SSR markers showed that clusters useful to describe the data are K = 10 .ST) in all populations fluctuated between 0.0339 and 0.0368  Group 10 is made up of genotypes from Las Lomas, Roblería, Los Avellanos, Armerillo, and Punta de Águila; and (c) Group 8 is represented by genotypes from all populations.G. avellana described in the present work was developed by guiding us in the historical structure of ecological niche modeling reported in other publications ..G. avellThe advantage of HRM analysis is that Real-Time PCR system software provides a table of dissociation temperature data automatically (including clustering graphs), and for the construction of the binary matrix, only must be analyzed the forms of melting curves, which makes the process something fast, precise, easy to interpret and analyze, and above all, an independent process, since high-cost external services are not required to obtain results. Even more, when it is required to analyze small fragments , it alloG. avellana plants propagated by in vitro culture , it allows us to know genetic clusters that can be biologically meaningful structures and reflect interesting biological processes. For this, we must define the number of clusters that are useful to describe our data . DAPC ca country .G. avellana populations present in the Maule Region, information that will allow the local community and government entities to make conscientious, better informed and objective decisions in a timely manner when implementing strategies aimed at guaranteeing effective plans for the conservation, recovery, make visible, and potential use of the species.Based on the Model MaxEnt results and HRM Analysis, we could make some decisions in terms of conservation. For example, if we aim to protect populations containing significant genetic variability  in areasG. avellana, due to its ethnobotanical characteristics, is a species with a high potential for domestication [G. avellana is restricted to the collection of its fruits in their natural state; however, less than thirty percent of the total inventory is considered suitable for collection, due to the difficult access to the populations and their high dispersion space [Native plants are often promoted to solve various environmental sustainability issues . Promotitication . The exptication , though tication . Severaltication . Currenton space . Thus, ion space .2 and associated shifts in temperature and precipitation are all expected to impact plant ecophysiology, distribution, and interactions with other organisms [Currently, climate change is becoming a serious challenge around the world, with significant threats to food security, ecosystems, economic stability, and water resources . The imprganisms . Accordirganisms . The charganisms . To mitirganisms . A recomrganisms .G. avellana, generating the greatest amount of information that could be quickly socialized and transferable in such a way as to encourage and invite the scientific community, farmers, local community, and government agencies to develop and accelerate conservation strategies and ecologically sustainable use of the species. Our biotechnological approach allowed us to contribute significantly to one of the key and fundamental questions in this type of study related to what and where to restore. The criteria that we address to develop an effective plan for conversation and/or sustainable use in G. avellana not only considered a survey of genetic and ecological information of the species in the region but also included the development of a fast and efficient system of in vitro propagation of individuals of high genetic and phytosanitary quality selected based on their genetic, phenotypic, phenological plasticity, and agroforestry characteristics of productive interest (unpublished data). This point is really important since Chile has committed to restoring 600.000 ha of native forest by the year 2035; however, the quantity and quality of native plants that are required to be produced were not considered; When evaluating whether the nurseries currently meet the minimum seedling quality standards based on their morphophysiological attributes, it was concluded that the restoration commitments desired by 2035 would not be achieved until 2181 [G. avellana, due to its agroforestry and productive characteristics, should be seriously considered as an alternative for the development of a crop of regional interest. If we consider, for example, that the commercial plantations in the Maule Region of its homonymous European Hazelnut (Corylus avellana L.) have increased their representation significantly, going from 30 ha in 1999 to 24.455 ha in 2021, with a representation of this species at the country level by over 80%, becoming, in addition, the fourth most important fruit crop at the country level [G. avellana as an ecological crop, more environmentally friendly, and with regional identity is a completely viable alternative to implement. However, at this point, we consider that the social, cultural, ecological, and environmental focus should not be lost; therefore, we propose not to think of G. avellana for the development of a massive monoculture but rather the development of a “domestication limited to small-scale” fully regulated (through Technology Transfer), which allows both the conservation of genetic diversity and the sustainable use of the species and specifically contributes to improving the local communities’ quality of life. These communities are made up mostly of peasants whose families own small extensions of land that they have inherited generationally, where there are remnants of native forests—that is, fragmented forests of native species, including G. avellana. Lands that, due to the edaphoclimatic and topographical conditions of the area, are generally not suitable for the establishment of other types of crops that allow the development of agricultural activities. These lands have soils with low water availability, often eroded, with streams that are difficult to access, where, in addition, in the case of G. avellana, although there are natural populations within these lands, the production of its fruits is uneven and insufficient and makes it unfeasible to base the family economy on a permanent and profitable activity. Under this social and cultural reality, and as there are no incentives from the state towards these communities to protect and maintain these native resources, the peasants and locals who own these lands dedicate themselves to working in other economic activities, and with regard to the management of the use of their land, they often make decisions to sell part of it (invoking the change in land use regulations) or they simply choose to cut down the remnants of native forest to replace them with forest plantations and more economically lucrative fruit trees such as Pine (Pinus radiata), Eucalyptus  and, in recent years, European hazelnut (Corylus avellana). According to the above, and with the information generated in this study, it is feasible to develop an adequate platform for multipurpose technology transfer in G. avellana and transform it into an adequate alternative for reforestation, since its benefits and scope in different areas  have not been really valued or dimensioned.Based on the above, our focus of attention was focused on making visible a phytogenetic resource that is almost unknown at the regional level and with great potential for domestication and exploitation, such as til 2181 . With rery level , thinkinGevuina avellana Mol. located in two Andean sectors of the Maule Region  , located between 34°41′ and 36° 33′ south latitude A. Young untains) . These pG. avellana in Chile was obtained from Global Biodiversity Information Facility   A. The cuG. avellana based on its current presence dataset. In particular, 22 bioclimatic layers and one topographic variable (elevation) were obtained from the WorldClim database . Variables were retrieved at a spatial resolution of 30 arc-seconds (~1 km) for the current distribution and 2.5 arc-minutes (~21 Km) for future distributions. Projections of future climate change to predict the potential distribution of G. avellana were evaluated using the so-called Scenario Model Intercomparison Project (ScenarioMIP) under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Two global climate models (GCMs), CNRM-CM6-1 and MIROC-ES2L for the four shared socioeconomic pathways (SSPs), 126, 245, 370, and 585  were evaluated.Twenty-three variables were retrieved as predictors to model the potential environmental niche of The georeferenced longitude and latitude variables were analyzed with QGIS version 3.20 software and duplicate data were eliminated. Geographic location map was made through the Geographical Information System (GIS) using tools ArcGIS (ArcMap 10.03 software). The coordinates were exported to CVS format and the climatic variables in ASCII format, both integrated into MaxEnt software version 3.4.4 for further analysis . First, www.retsch.com (accessed on 20 September 2022)). To carry out the exploratory analysis of the genetic variability of the populations, genomic DNA was extracted from 60 trees from different natural populations of G. avellana. They were selected based on characteristics of interest (G. avellana populations.The genomic DNA was extracted from 500 mg of lyophilized leaves of Chilean hazelnut according to the protocol CTAB described by . The leaTM (Thermo Fisher) and displayed in 1% agarose gel electrophoresis. The final concentration was adjusted to 10 ng µL−1.The nucleic acids purity and concentration were estimated on a Multiskan Sky HighG. avellana [G. Avellana, because their characteristics were adequate for analysis HRM [For the exploratory analysis of the genetic variability of individuals of interest, the so-called Nonanchored Inter Simple Sequence Repeat (ISSR) markers were used . Differeavellana ,81,82. Wysis HRM .G. avellana is summarized in nine steps described in Figure 13. This consisted of selecting adult trees from the seven populations under study with contrasting phenological and phenotypic characteristics of different kinds  and introduce explants of each one of them through tissue culture techniques (in vitro culture) that would allow having a core collection representative of the diversity found. That is, DNA sample variants were isolated and conventional PCR conditions were standardized on these genotypes with expressed sequence tag-simple sequence repeat (EST-SSR) markers described for the species [The strategy designed to apply the HRM analysis in  species . Of a toG. avellana genotypes that presented variations in their nucleotide sequences were selected and evaluated by HRM. To assess the reproducibility of the HRM method, PCR reactions were performed in triplicate for each genotype for the eight EST-SSR primers  . For the primers , Step 8.ulations , Step 9.G. avellana Mol. were genotyped with eight expressed sequence tag-simple sequence repeat (EST-SSR) markers, based on a cDNA library of the species: Ga94, Ga38, Ga88, Ga90, Ga36, Ga7d, Ga92, and Ga49 [−1 (1 µL of each) were used directly in 10 µL reaction volumes containing 1X Kapa HRM Fast Master Kit , 2.5 mM MgCl2, and 200 nM of each primer. PCR amplification, DNA melting, and end point fluorescence level acquiring PCR amplifications were performed on AriaMx Real-Time PCR System . PCR protocol was established for all SSRs, under the following conditions: 40 cycles of denaturation at 95 °C for 10 s, annealing at 60 °C for 30 s, and extension at 72 °C for 20 s. High-resolution melting analysis was performed after PCR amplification at the temperature ramping and fluorescence acquisition setting recommended by the manufacturer, which is, the temperature ramping up to 95 °C and rising by 0.2 °C/10 s.The populations of and Ga49 . NucleicG. avellana from seven natural populations of the Maule Region were analyzed. HRM profiles of each individual were compared to representative standard curves for each marker (HRM Standard) . Then, we established a directory with the data using the following parameters: (1) dat <- read.table (binary data matrix in TXT format), (2) obj <- genind to define how our data is composed , (3) parameter “grp<-find.clusters (max.n.clust = 40)” to define and form the population groups, and (4) parameter “dapc1<-dapc ” were used to choose the PCs, number of clusters, and the number of eigenvalues that explained the highest percentage of the accumulated variance”, which finally allowed obtaining the basic scatterplots using function (5) “scatter (dapc1)”.Two hundred and eighty trees of tandard) . One Bintandard)  GenAlex tandard)  and Adegtandard) . DAPC is Jombart . Using gG. avellana with HRM analysis can be a fast and cost-effective tool, suitable to replace other genotyping technologies such as DNA sequencing by capillary electrophoresis. We conclude that the HRM methodology described in this work can be used as a reference and applied to the study of other native species of interest.It was shown that EST-SSR genotyping in G. avellana Mol. They are located in the Andean sectors of the Coastal Range and Los Andes range, areas that, by the year 2040, will decrease by 50%, moving mainly to the Andes range above 1200 meters above sea level. Along with this, according to analysis HRM and the discriminant analysis of principal components (DAPC) we conclude that high-priority areas for protection correspond to Los Avellanos and Punta de Águila populations due to their greater genetic diversity and allelic richness.Based on the ecological niche modeling developed by MaxEnt, we determined that currently the ideal areas in the Maule Region to establish G. avellana, and the interest shown in wanting to be part of a solution to a problem that affects us all as a society related to negative anthropogenic impacts and climate change on our plant genetic resources, we conclude that the key for a successful implementation of a conservation program in G. avellana, is to actively include the participation of the peasant community to maintain this synergy between them and the scientific world.According to the valuable interaction that allowed us to establish a synergy between the real needs of the peasant community dedicated to the activity of collection of fruits in