Background: Cancer is a leading cause of mortality in Palestine. The number of cancer cases is increasing, whereas the late stage of diagnosis is common for the majority of cases. Modern diagnostics and medicine are contributing to more positive outcomes for patients when diagnosed early; however, the holistic approach to patient care, patient satisfaction, quality of life (QOL), and survivorship are often overlooked. Patients with cancer are usually treated by physicians and other health professionals employing the “medical model” without considering other factors that might positively affect their treatment. For this pioneering survey, the Functional Assessment of Chronic Illness Therapy-General (FACT-G) tool was used. This study aimed to measure the satisfaction of patients with cancer undergoing outpatient treatments and assess their QOL.Materials and Methods: The FACT-G scale in Arabic has four sections, measuring physical, emotional, social, and functional well-being, was used in a survey of 203 patients with cancer currently undergoing chemotherapy, radiotherapy, and hormonal therapies. Patients were surveyed in the summer of 2019, within 1 year of diagnosis when they were outpatients, all of whom were attending a major cancer center in a Palestinian hospital.Results: Emotional well-being scored the lowest  5.45)) whereas social/family well-being scored the highest , mean 22, (SD ±  5.78). The overall mean for the four sections was 63.57 (SD 12.44).Conclusion: To ensure better management of symptoms and treatments, important indicators are now available for health professionals and researchers to learn more about the QOL of patients. Evaluating the physical, social, emotional, and functional states of patients with cancer undergoing outpatient treatments enabled us to learn more about the struggles they face while understanding how they were coping during their cancer journey. The cancer burden is increasing in Palestine. According to the Palestinian Ministry of Health, the cancer incidence rate was 117.8/100,000 populations in 2019. There were 3,174 new cancer cases in the West Bank, with breast cancer being the most common cancer , with an incidence rate of 19.9 per 100,000 populations. This was followed by colon cancer (12.6%), lung cancer (7.2%), thyroid cancer (5.2%), leukemia (4.9%), and bladder cancer (4.7%). Mortality rates were 41.9 and 36 deaths per 100,000 people in the West Bank and Gaza, respectively. Data from the Gaza Strip is not available. According to Al Waheidi in Gaza, “a lack of complete and reliable data remains a major challenge.”4Worldwide, cancer is a leading cause of death, accounting for nearly 10 million deaths in 2020.Late diagnosis of cancer is a persistent problem in the country, with at least 60% of cases being diagnosed at stage 3 or 4, which often results in more aggressive treatments and poorer outcomes. The World Health Organization (WHO) projections for the Eastern Mediterranean region state that 630,000 cancer deaths will occur in 2030, an increase of nearly 57% from 2015.5Quality of life (QOL) is important in cancer care because it influences both the disease and treatment. As effective methods of treatment and detection have led to an increase in the number of long-term survivors, healthcare providers should understand the factors that may contribute to the QOL of their patients.This study mainly aimed to assess the health-related (HR)-QOL of Palestinian patients with cancer by using a validated questionnaire. Patients who participated in this survey came from all backgrounds and from all parts of the country. Arab women share different cultures, norms, and beliefs compared with Western women, and studies have shown that patient-based outcomes could be affected by cultural experiences and ethnic backgrounds.QOL is a multi-dimensional construct that affects all aspects of a person’s life including physical health, mental and social well-being, and functional factors. It is also influenced by cultural, ethical, personal, and religious values. Many Muslims believe that death and illness are the will of Allah (God) and cannot be avoided or stopped. Abu Huraira reported Allah’s Messenger, peace be upon him, saying: “For every misfortune, illness, anxiety, grief, or harm that afflicts a Muslim -even the harm is caused by the pricking of a thorn - Allah removes some of his sins.” They see illness as a test from God. While religion encourages seeking advice and treatment, Islam also teaches that tolerating pain without medications or treatments will lead to greater rewards in the hereafter. This belief helps the patients to cope.Islam is the dominant religion in Palestine, 98% are Sunni Muslims, with a population of >4.8 million in the West Bank and Gaza. The Palestinian society and family structure is extended, with frequent family gatherings, children are living at home until they are married. The decision-making for families usually involves numerous relatives. Christian and Muslim families have similar values and traditions, such as respect for the elderly and care for the weak and ill.Family support for patients is another factor that affects QOL.In Palestine, limited access to care and financial constraints play an important role in the QOL of patients with cancer. The health sector suffers economically and has a weak infrastructure. The Palestinian Authority (government) provides health cover for patients with cancer, but the overall health expenditures are insufficient to meet demands. The total health expenditure per capita in Palestine  was USD 282.2 in 2015, whereas the Palestinian Central Bureau of Statistics reported that at least 40% of costs must be paid by the patients and their families. Palliative care is not a priority and is not covered by governmental health insurance, which covers the majority of the population. However, the non-governmental sector attempts to educate health professionals, improve basic services, and expand diagnostic and psychosocial support. The first support group for women living with cancer began in 2000, which was established by Patient’s Friends Society-Jerusalem, a non-governmental organization. Their work encompasses psychosocial support, lymphedema care, education, advice, etc., for women and their families from the West Bank and Gaza. Health professionals received some training in oncology and palliative care, but such trainings are donor dependent and services are sporadic.The West Bank has two governmental hospitals and two non-governmental hospitals that provide curative and palliative care treatments, whereas Gaza has three hospitals. Radiotherapy is not available in the West Bank or Gaza. As the referrals of Palestinian patients are approved and they obtain travel permits from the Israeli occupation forces, they may access radiotherapy at Augusta Victoria Hospital, Jerusalem.Palliative care and a specialized focus on HR-QOL are limited and are in their infancy in Palestine. Moreover, very little data and research about HR-QOL for patients with cancer are available in Palestine, which may indicate the lack of concern, awareness, or interest in this field.10 This questionnaire is designed for self-assessment.This study utilized the Functional Assessment of Cancer Therapy – General (FACT-G) questionnaire (Part 2 of the research), which has 27 items designed to measure four domains of the HR-QOL in patients with cancer: physical, social, emotional, and functional well-being. The FACT-G is one of the most widely used patient reported outcome measures in cancer research.The FACT-G survey scores physical well-being , social/family well-being , emotional well-being , and functional well-being .All questions in the FACT-G use a 5-point rating scale . Provided that >50% of the items comprising a subscale are answered, a subscale score is computed as the pro-rated sum of the item responses for that subscale. The FACT-G total score is computed as the sum of the four subscale scores provided that the overall item response is at least 80%  and has a possible range of 0–108 points.In addition to using this tool, a section (Part 1) was developed to survey demographic characteristics. These variables included age, sex, education, and monthly family income. Questions about metastasis and comorbid conditions, developed by the authors, were also included. Patients reported if they had metastasis or any chronic medical conditions. Recruitment and data collection were completed in 1 month during July 2019.The study enrolled adult patients with cancer who had been diagnosed at least 1 year previously and were attending a major referral hospital in Jerusalem. Patients with cancer came from all over the country and were receiving cancer treatment and/or follow up in the outpatient units (n = 203). A total of 157 (77.3%) patients were recruited from the West Bank and 46 (22.7%) from the Gaza Strip. The response rate was 98.5%.All the patients were diagnosed with solid tumors .All FACT-G scales were scored so that a higher score indicated a better QOL. To achieve this, we reversed response scores on negatively phrased questions and then summed item responses. The negatively phrased questions that were reverse coded were in the subscales. In cases where individual questions were skipped, scores were pro-rated using the average of the other answers in the scale. The total FACT-G score was obtained by summing individual subscale scores (PWB+EWB+SWB+FWB). Total scores for the disease-, treatment-, and condition-specific subscales were obtained by summing all subscale scores (PWB+EWB+SWB+FWB). and possible associations between QOL and the following variables were analyzed: sex, age, education level, marital status, type of cancer, time since diagnosis.Means and standard deviations (SD) were used to describe all domains . Data were tabulated using the IBM SPSS Statistics, version 22.0 ,The inter-reliability coefficient of FACT-G was indicated by Cronbach’s alpha 0.91, indicating high internal consistency. This result meets the criteria that Hahn et al. discussed in their article on “Precision of health-related quality of life data compared with other clinical measures.” They stated that “common thresholds for acceptable reliability are >0.70 for group-level applications and >0.90 for individual level applications.”Patient characteristics are demonstrated in  ± SD total scores of the PWB, SWB, EWB, and FWB subscales of FACT-G are depicted in the following table. The maximum possible score is 108.The meanp = 0.001)). The total mean and standard deviation scores of the items of PWB, SWB, EWB, and FWB subscales of the FACT-G are presented in As shown in In this study, the most common cancers included breast, colon, stomach, and chronic myeloid leukemia (CML). Twenty-six patients reported metastatic cancer. In p = 0.16). Women scored slightly higher in the PWB, FWB, and SWB subscales , whereas men scored slightly higher for PWB (15.88/SD 6.02 in men vs. 14.72/SD 7.07 in women). These differences were not significant.SWB scored the highest, with no significant difference between sex, scoring a mean of 22 (SD 5.75) of a total of 28. These are similar to the findings of Conrad et al.16EWB scored the lowest, with “I am losing hope in the fight against my illnesses” and “I worry about dying” being the worst among male and female respondents equally . Similarly, in their study of Indian patients, Nayak et al. found that the fear of recurrence (76%) had the most effect on EWB. QOL depends on many variables, such as access to information, sound physician–patient communications, and participation in the decision-making process including treatment options. Studies have shown that high levels of support, regardless of source, improve the ability to cope. Rockoff et al. analyzed 100 patients with breast cancer and survivors and found that better interaction and communications with health professionals (30%) and access to information (25%) could improve the treatment process and QOL. Coping was made more difficult by the clinical process (25%), perceived lack of control (17%), and fear of cancer and death (20%).Evaluating the QOL of patients with cancer is increasingly important. Non-communicable diseases (NCDs) in patients with cancer are associated with a poorer QOL and higher mortality than in patients without NCDs. According to the WHO, NCDs are the leading cause of death and a major economic and social burden in Palestine. For example, in the Palestinian population in the West Bank, Gaza, and east Jerusalem, there is a high prevalence of diabetes, with 15.3% compared with the worldwide prevalence of 6%. The World Diabetes Foundation further reports that anecdotal information from several sources suggested that the rate could be much higher, 18%–21%. Of the total diabetic population in Palestine, 4.4% and 95.3% are diagnosed with type 1 and 2 diabetes, respectively.Patient data results may vary among populations and patients and should be considered in assessing patients and planning for their care. stated that “increase in comorbidities can have significant implications for cancer patients.” Therefore, it is important to consider comorbid conditions when studying quality of care and survivorship. In the present study, all patients were currently receiving various treatments; some traveled long to receive care, and at least 13% were living with metastatic disease. None reported secondary cancers, but this was only ascertained from their self-reporting. While patients have the right to know their diagnosis, many reported not being told about the extent of their disease or prognosis.Clearly, 43% of the patients reported comorbidities, which were NCDs. Moreover, 16% of our patients reported having diabetes, whereas 21.5% reported having hypertension. Roy et al. They also stated that culture affects communication, decision-making, response to symptoms, treatment choices, and emotional expression at the end of life. Faith and spirituality are the keys to culture, which provide patients enormous comfort and solace. In Islam, of which the majority of our samples are adherents, all life aspects are viewed within the context of religion. These findings are similar to those of Rockoff et al.18 In that study, women reported that the most difficult stage of cancer experience was its diagnosis. We might conclude that the study participants had moved on from this difficult stage and were adapting or coping better.The most highly-scored section was the SWB (22/28 score). The family is very important in the Palestinian culture, and generally, they offer as much support as possible. Similar experiences were found by Turkish and Moroccan patients in Europe.Generally, women scored slightly higher on the FACT-G  than men . Young men (aged < 18 years) and older men (60 years) tended to score less, whereas women scored low in the PWB, which may be because the majority of female respondents had breast surgeries affecting self-image, etc.A patient with cancer stated: “Quality of life is so important after cancer, but many of us have a very poor QOL and are expected to just be grateful that we are still alive. It is so hard when everything you had before cancer is gone. Just being alive is not enough for me.”22Islam MS points out that “with the improvement of therapies patients with malignancies are living longer but the physical, social and psychological impacts on them often negatively impacts their QOL. Surviving cancer is a chronic life-altering condition’ which needs a holistic approach to patient care.”To our knowledge, this was the first survey conducted in Palestine using the FACT-G Arabic version. This study indicated that patients with cancer experience symptoms such as nausea, feeling ill, and other problems, mostly emotional, that affect their QOL. As health professionals, it is incumbent on us to work together to ensure that patients receive timely care and support and thus improve their QOL. The main issues are symptom management and the need to use strategies that will empower patients to have a better sense of control over their illness and treatment. If we are to improve care, healthcare providers, including the government which is the largest healthcare provider in the country, and the academia should invest and commit to improving services; educate physicians, nurses, and other healthcare service personnel; support research; and implement strategies to help patients with cancer and their families.We believe that this study will encourage other professionals to continue to, explore, and assess meaningful data and factors that affect patients and design interventions to improve QOL. This should be the future to ensure quality cancer services.“The author(s) declare(s) that there is no conflict of interest regarding the publication of this article.”We would like to acknowledge the contribution of FACIT.org who provided the tools and advice.


Primary warm-antibody autoimmune hemolytic anemia (w-AIHA) is prone to recurrence in children. In this study, we aimed to identify risk indicators for the early recurrence of primary w-AIHA and construct an effective recurrence risk assessment model.This was a retrospective cohort study. The clinical data of patients hospitalized with primary w-AIHA in the Department of Hematology and Oncology, Children's Hospital of Chongqing Medical University, between 1 January 2018 and 30 September 2021, were collected at the initial diagnosis. Univariate and multivariate logistic regression analyses were used to determine risk indicators for the early recurrence of primary w-AIHA in children, and ROC curve and Kaplan–Meier survival analyses were used for verification. Finally, a risk assessment model for early recurrence in children with primary w-AIHA was constructed using Cox regression and visualized using a nomogram. The model was also verified internally and externally.P = 0.009, 0.047, respectively). The mean corpuscular hemoglobin concentration (MCHC) is a protective factor (P = 0.040). According to the ROC curve and Kaplan–Meier survival analyses, children with primary w-AIHA whose blood type was O or had an MCHC of <313.5 pg/fL or a Ret of ≥0.161×1012/L had a higher risk of early recurrence . The blood types (O), MCHCs, and Rets of 56 patients were incorporated into the Cox regression model, and the recurrence risk assessment model for children with primary w-AIHA was successfully constructed and visualized using a nomogram. The calibration curves and decision-curve analysis (DCA) suggested that the risk model has clinical applicability and effectiveness.This study included 62 children with primary w-AIHA. Of which, 18 experienced recurrence 1 year after the initial diagnosis. The univariate and multivariate logistic regression analyses showed that type O blood and the reticulocyte count (Ret) were risk indicators for the early recurrence of pediatric primary w-AIHA (12/L have a higher risk of early recurrence. The risk assessment model for the early recurrence of pediatric primary w-AIHA constructed in this study has good clinical applicability and effectiveness.Children with type O blood and an MCHC value of <313.5 pg/fL or a Ret value of ≥0.161×10 The ia (PCH) . w-AIHA ia (PCH) –10.The diagnosis of w-AIHA is based on clinical manifestations and actual tests when necessary, especially the direct antiglobulin test (DAT) and the indirect antiglobulin test (IAT) , 12. CorTherefore, we conducted a retrospective study to screen the risk indicators for the early recurrence of primary w-AIHA in children and to build a risk assessment model for disease recurrence to help guide the selection of treatment options for clinical patients with primary w-AIHA.via telephone if there were missing data.Single-center data were retrieved consecutively from the Children's Hospital of Chongqing Medical University between January 2018 and December 2021 . The diaThe medical record data included demographic and clinically relevant information on the patients. Demographic information, including sex, age, weight, and height, was collected. The clinically relevant information included the ABO blood type, Rh blood type, results from routine blood tests, liver function, renal function, electrolytes, the autoantibody spectrum, results from the Coombs test, immune protein and complement levels, and haptoglobin levels. Treatment characteristics included suspended red blood cell (sRBC) infusion, washed red blood cell (wRBC) infusion, and glucocorticoid pulse treatment . Prednisolone was given orally within 3–6 months after the initial diagnosis. Depending on the changes in hemolysis, the drug was gradually reduced to withdrawal.To explore the risk indicators for the early recurrence of primary w-AIHA in children, the follow-up time and disease outcome of patients were collected in this study. In combination with the pathogenesis and development of primary w-AIHA , 2, the Based on the results of the different tests for each clinical index, univariate and multivariate logistic regression analyses were performed to determine the independent risk indicators for the early recurrence of pediatric primary w-AIHA. The Youden index of each independent risk factor was obtained according to the receiver operating characteristic (ROC) curve, and the influence of each independent risk factor on disease recurrence was verified using the Kaplan–Meier survival analysis.Based on the random number table method, 62 patients were divided into a training cohort and a validation cohort at a ratio of 9.3:1. Depending on the results of the multivariate logistic regression analysis, the Cox regression analysis was performed based on the independent risk indicators of early recurrence in the training cohort, and the risks of relapse at 6 months and 1 year after the initial diagnosis of primary w-AIHA in children were visualized in the form of a nomogram. The prediction efficiency of the Cox regression analysis for short-term recurrence was verified using internal and external validations.t-tests were used to test the significance of continuous variables that conformed to a normal distribution. The Mann–Whitney U tests or non-parametric tests were used to test the significance of continuous variables that did not conform to a normal distribution. For all statistical tests, a P < 0.05 was considered statistically significant, while a P < 0.01 was considered statistically highly significant. SPSS version 23.0 software (IBM Corp.) and the Hmisc package, the rms package, and the rmda package  were used for the statistical analyses.Pearson's chi-squared tests or Fisher's exact probability tests were used for categorical variables. Two-tailed In this study, a total of 62 patients  with primary w-AIHA were included, with age fluctuating from 0.36 to 14.67 years and a median of 2.46 years. 18 of these cases relapsed within 1 year after the diagnosis. P = 0.024), while the other blood types of these two groups were not significantly different (P > 0.05). Other variables, such as the red blood cell (RBC) count, hemoglobin (Hb) level, mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), and reticulocyte count (Ret), were significantly different between the two groups, with P-values of 0.015, 0.025, 0.020, 0.004, and 0.038, respectively. However, there were no significant differences in variables such as the Rh blood type, the Coombs test results, the white blood cell (WBC) count, the platelet (PLT) count, mean corpuscular hemoglobin (MCH), the liver and kidney function-related variables, or different therapies (P > 0.05).The ABO blood type was not significantly different between the recurrence and non-recurrence groups. However, type O blood was significantly different between the two groups . Similarly, patients with a higher Ret were more likely to experience early recurrence , and patients with a lower MCHC were more likely to experience early recurrence than those with a higher MCHC . The prediction model obtained using the multivariate logistic regression analysis can integrate the above three clinical variables with the highest specificity and Youden index, as shown in From the results, it can be observed that patients with type O blood were more likely to experience early recurrence than patients with other blood types  were included in this study. The shortest recurrence time was 11 days, and the longest recurrence time was 304 days. Among the other 44 patients with primary w-AIHA who did not experience early recurrence, the minimum follow-up time was 189 days, and the maximum follow-up time was 1,425 days. From the results of the multivariate logistic regression and ROC curve analyses of independent risk indicators, we divided each index into two groups according to the cutoff point of every indicator. We verified the relationship between every indicator and the occurrence of early relapse using Kaplan–Meier survival analysis .HR = 2.640, 95% CI is 1.040–6.660, P = 0.040). Patients with an MCHC value of <313.5 pg/fL had a significantly higher risk of early recurrence than patients with an MCHC value of ≥313.5 pg/fL . Patients with a Ret value of ≥ 0.161×1012/L had a significantly higher risk of early recurrence than patients with a Ret value of <0.161×1012/L .The results of survival analysis demonstrated that patients with type O blood had a significantly higher risk of early recurrence than patients without type O blood , as shown in To verify the relationship between the early recurrence of pediatric primary w-AIHA and these risk indicators, patients were divided into different risk grades based on their blood type, MCHC, and Ret at baseline. Therefore, high-risk patients were defined as those with all risk indicators at baseline. Intermediate-high-risk patients were defined as those with two of three risk indicators at baseline. Intermediate-low-risk patients were defined as those with only one of three risk indicators at baseline. Low-risk patients were defined as those with no risk indicators at baseline. The Kaplan–Meier survival analysis confirmed that the higher the risk grade at baseline, the higher the probability of early recurrence, especially in the high-risk and intermediate-high-risk patients (n = 56) and a verification cohort (n = 6) at a ratio of 9.3:1. According to the multivariate logistic regression analysis results, risk indicators  in the training cohort were incorporated into the Cox regression model. A nomogram was drawn using R and is shown in 12/L (69 points) on routine blood examination at the initial diagnosis. For this patient, the final score was 117 points, the recurrence probability at 6 months after the initial diagnosis was 0.817, and the recurrence probability at 1 year was 0.547. These values suggested that this patient was at a high risk of recurrence. Patient 2 (ID num. 11150263) had type B blood (0 points), an MCHC of 360 (10 points), and a Ret of 0.08 × 1012/L (10 points) on routine blood examination at the initial diagnosis, and the final score of this patient was 20 points. The recurrence probability in 6 months after the initial diagnosis was 0.722, and the recurrence probability in 1 year after the initial diagnosis was 0.420, suggesting that this patient was at low risk of recurrence.To test the predictive efficiency of the prediction model, 62 patients with primary w-AIHA were divided into a training cohort  and actual outcomes at 6 months and 1 year after the initial diagnosis, as shown in CI is 0.561–0.831), and for the validation cohort, the C-index was 0.670 (95% CI is 0.534–0.806). These results suggested that the risk model based on the Cox regression prediction model for the early recurrence of primary w-AIHA patients has a certain predictive ability and can aid in clinical applications. However, the sample size of this study was small, and more sample data are needed for external validation.The C-index was calculated to evaluate the predictive efficiency of the Cox regression prediction model, as shown in Autoimmune hemolytic anemia is an anemic disease with erythrocyte destruction that exceeds bone marrow compensation due to immune system dysfunction and the production of autoantibodies , 2. HoweHelicobacter pylori, Salmonella typhi, and Plasmodium falciparum . According to studies on the pathogenesis of w-AIHA, autoantibodies, the complement system, phagocytes, cytotoxic CD8+ T cells and NK cells performing ADCC, B and T lymphocytes (including CD4+ T regulatory (Treg) cells), and cytokines play important roles in the pathogenesis of w-AIHA  was found to be a protective factor for the early recurrence of primary w-AIHA in children, and the ROC curve analysis and survival analysis showed that patients with primary w-AIHA with an MCHC value of ≥313.5 pg/fL at the initial diagnosis had a lower recurrence rate. In this study, the multivariate logistic regression analysis showed that Ret was an independent risk factor for the early recurrence of primary w-AIHA in children . The ROC curve analysis and survival analysis also showed that patients with a Ret value of ≥0.161 × 1012/L at the initial diagnosis had a higher early recurrence rate. To the best of our knowledge, both the MCHC and Ret can directly or indirectly reflect the hematopoietic function of bone marrow. In patients with w-AIHA, hemolysis and hematopoiesis often occur simultaneously in the bone marrow. When the degree of hemolysis exceeds the compensation of hematopoietic capacity, the patient will be anemic. Based on the results of the MCHC and Ret, we concluded that the compensatory increase in bone marrow hematopoiesis in patients with primary w-AIHA may not represent physiological bone marrow hematopoiesis but rather a pathological process of excessive hematopoiesis through the mobilization of naive erythroid primitive cells. The direct consequence of this process is an increase in the Ret. At the same time, some RBCs with large volumes are also released into the blood, resulting in an increased MCV and decreased MCHC , internal carotid artery stenosis, and hepatocellular carcinoma (HCC) metastasis –31. Basesed MCHC , which cAs an autoimmune disease, it is expected that immune cells play an important role in the pathogenesis and progression of AIHA , 33. HowCI is 0.561–0.831) in the training cohort and 0.322 (95% CI is 0.171–0.473) in the validation cohort. However, due to the limited sample size, this model needs external validation with a larger sample size to test its stability and accuracy.To develop a more suitable risk model for clinical evaluation, we included data from patients with type O blood, a low MCHC, and a high Ret in the Cox regression model and visualized the risk of recurrence at 6 months and 1 year after the initial diagnosis using a nomogram. By using internal and external validations, the risk assessment model was proven to have high clinical differentiation and application value; the C-index was 0.696  during the first hospitalization. All 62 patients included received first-line drug therapy, such as infusion of suspended red blood cells, washed red blood cells, and glucocorticoid pulses during their initial hospitalization; no second-line drugs or combination regimens were involved. However, there was no significant association between these first-line treatment options and early recurrence in children with primary w-AIHA. This suggests that red blood cell infusion therapy can only improve Hb levels and oxygen supply in the tissues of the patient in the short term but the Hb levels and oxygen supply cannot be maintained in the long term.Rituximab  is a second-line treatment for w-AIHA, especially for refractory AIHA , 35. In The limitations of this study included the following: this was a single-center retrospective cohort study. The analyzed laboratory parameters were obtained from the date of admission and represent the values from a single center. Since pediatric primary w-AIHA is a rare disease, small sample size is inevitable. In the next phase of the study, we hope to obtain more recognition and cooperation from other hospitals' departments of hematology and oncology to verify the results of this study in the future.In summary, we used the multivariate logistic regression analysis to identify the risk indicators for the early recurrence of primary w-AIHA in children and constructed a risk assessment model and visualized it using a nomogram with a high clinical value to predict the recurrence risk at 6 months and 1 year after the initial diagnosis of pediatric primary w-AIHA using the Cox regression model. This prediction model can help patients choose an optimal time to stop taking medication or determine further treatment options.Based on the results of the current study, our team will closely monitor the clinical presentation and indications of children with w-AIHA at high risk of recurrence in the next phase of the study, focusing on the benefit analysis of early application or combination of second-line drugs in children with w-AIHA at a high risk of recurrence.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of the Children's Hospital of Chongqing Medical University. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.JL drafted the manuscript. XX and LX directed statistical methods. YW and XA analyzed and interpreted the results. YZ, LH, and KZ performed the data curation and analysis. XY, WY, and JQ collected the data. JY reviewed the manuscript. All authors read and approved the final manuscript.This work was supported by 2022 Research Projects of Chongqing Municipal Health and Health Commission (No. 2022WSJK005).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Identifying new biomarkers is necessary and important to diagnose and treat malignant lung cancer. However, existing protein marker detection methods usually require complex operation steps, leading to a lag time for diagnosis. Herein, we developed a rapid, minimally invasive, and convenient nucleic acid biomarker recognition method, which enabled the combined specific detection of 11 lung cancer typing markers in a microliter reaction system after only one sampling. The primers for the combined specific detection of 11 lung cancer typing markers were designed and screened, and the microfluidic chip for parallel detection of the multiple markers was designed and developed. Furthermore, a miniaturized microfluidic-based analyzer was also constructed. By developing a microfluidic chip and a miniaturized nucleic acid analyzer, we enabled the detection of the mRNA expression levels of multiple biomarkers in rice-sized tissue samples. The miniaturized nucleic acid analyzer could detect ≥10 copies of nucleic acids. The cell volume of the typing reaction on the microfluidic chip was only 0.94 μL, less than 1/25 of that of the conventional 25-μL Eppendorf tube PCR method, which significantly reduced the testing cost and significantly simplified the analysis of multiple biomarkers in parallel. With a simple injection operation and reverse transcription loop-mediated isothermal amplification (RT-LAMP), real-time detection of 11 lung cancer nucleic acid biomarkers was performed within 45 min. Given these compelling features, 86 clinical samples were tested using the miniaturized nucleic acid analyzer and classified according to the cutoff values of the 11 biomarkers. Furthermore, multi-biomarker analysis was conducted by a machine learning model to classify different subtypes of lung cancer, with an average area under the curve (AUC) of 0.934. This method shows great potential for the identification of new nucleic acid biomarkers and the accurate diagnosis of lung cancer. According to the American Cancer Society, the incidence of lung cancer will be the second-highest among all cancers in 2021, and the mortality rate will be first . In ChinAs the gold standard for a definite diagnosis, the pathological sectioning method detects lung cancer protein biomarkers. Tumor biomarkers are produced and secreted by tumor cells during the oncogenesis and development of malignant tumors . In an eThe “central dogma” indicates that mRNA is the precursor of protein, and mRNA expression is correlated with protein levels . ConsideReverse transcription (RT)-PCR is widely used in mRNA detection for its high sensitivity and specificity. However, RT-PCR cannot meet the requirements of rapid diagnosis because multiple temperature cycles are required, necessitating a lengthy detection time and a large real-time fluorescence detector . AlternaSeveral studies demonstrate that examining combinations of multiple biomarkers can improve sensitivity and specificity . For exaHerein, we introduced a machine learning model with discriminative feature selection and feature transformation by margin maximization to perform multi-biomarker analysis to obtain more accurate, reliable, and understandable predictions in a minimally invasive manner than conventional single biomarker analysis. To the best of our knowledge, this is the first investigation involving mRNA biomarkers in lung cancer diagnosis. From a point-of-care perspective, this method has various advantages such as simplicity, ease of use, low cost, and real-time results. More importantly, because of its painless and minimally invasive nature, we believe that our assessment system for lung cancer will simplify physical examination processes and significantly improve patients’ medical experiences.A total of 86 subjects were recruited at the Emergency General Hospital  from March 2017 to January 2019. Included patients were stage II to stage IV. Patients with other unrelated diseases were excluded from the subject group to eliminate errors caused by irrelevant factors, with the exception of the pulmonary metastasis group. Patients with different malignancies, such as esophageal cancer and thyroid cancer, were included in the pulmonary metastasis group. The clinical features of the subjects are listed in Carcinoembryonic antigen (CEA), cytokeratin fragment 19 (CYFRA21-1), squamous cell carcinoma antigen (SCC), neuron-specific enolase (NSE), and pro-gastrin-releasing peptide (ProGRP) are serological markers for lung cancer recommend by the American Committee on Clinical Biochemistry, the European Expert Group on Tumor Markers, and the Chinese diagnostic and therapeutic specifications for primary lung cancer (2015 Edition). Joint use can improve specificity and sensitivity in clinical application. Among them, NSE and ProGRP are ideal indicators for diagnosing SCLC , CEA, CYThe mRNA levels of the 11 biomarkers in the tissue samples were measured by RT-LAMP, as shown in https://primerexplorer.jp/elamp4.0.0/index.html). A specific fragment of each biomarker was selected as the target by comparing related gene sequences in the NCBI . First, two outer primers (F3 and B3) and two inner primers (FIP and BIP) were designed, and then two loop primers (LF and LB) were additionally designed to accelerate the reaction rate. The specificities of these primers were verified by Basic Local Alignment Search Tool (BLAST) analysis , and the formation of primer dimers was assessed and excluded in primer design. After these steps, the LAMP primers for the 11 lung cancer biomarkers were synthesized by Sangon Biotech . Every set of primers was double-checked by practical experiments, including the limit of detection (LOD) analysis, linearity analysis, and specificity analysis. Only primer sets that passed all of the tests and performed best were chosen for each of the 11 biomarkers. Among them, the sequences of the LAMP primers for ProGRP are listed as a sample in LAMP primers for the 11 lung cancer biomarkers were designed using the LAMP primer design software Primer Explorer version 4  layers—a substrate layer and a top layer. The substrate layer contains microstructures such as channels and cells, and the top layer could be adhered to the substrate layer with double-sided tape. The radius of the microfluidic chip is 31 mm, and the total thickness is 1.2 mm. LAMP primers targeting the mRNAs of the 11 typing biomarkers and one internal reference  were designed and pre-embedded with 0.1% agarose on the bio-reactor cells of the microfluidic chip. The chip’s 24 bioreactor cells contain two repetitions of the 11 typing biomarkers, one internal GAPDH reference, and one negative quality control. After sampling and heating to 50°C, the low melting point agarose melted, and the pre-embedded primers were released into the reaction mixture. The primers participated in the LAMP reaction at 65°C, while agarose had no impact on the amplification . During As shown in The optic model includes an incident light path and a fluorescent receiving light path. A schematic diagram of the optic model is shown in t-test. All statistical analyses were two-sided, and a significance level of P< 0.05 was used. The cutoff values were decided by comparing the mRNA expression levels of the 11 biomarkers with different histology, and the mRNA expression levels of each biomarker were compared to the cutoff value of that biomarker. The status of each biomarker was considered high expression if the mRNA level was equal to or exceeded the cutoff value. Otherwise, it was considered a low expression.Statistical analyses were performed using Microsoft Excel. The correlation of mRNA expression with different clinical features was analyzed using Student’s To evaluate the performances of the biomarkers, sensitivity and specificity were calculated and compared. Sensitivity is defined as true positive/, and specificity is defined as true negative/. By summarizing sensitivity and specificity at different threshold levels, a receiver operating characteristic (ROC) curve  was plotTo analyze the relationship between the mRNA expression of multiple biomarkers and different subtypes of lung cancer, we proposed a rapid diagnosis model with discriminative feature selection and feature transformation by margin maximization. This machine learning-based model jointly takes all of the biomarker features as inputs and comprises three steps: recursive feature elimination (RFE)-based feature selection , large mi-th subject whose subtype class is X as the input and recursively eliminates one marker feature at a time, which results in Specifically, all of the 11 mRNA expression biomarkers comprise a 22-dimensional input feature The LMNN  feature is (PCA) .w and b construct the dividing plane, and φ is a linear or Gaussian kernel. We searched the kernel type and other hyper-parameters in our model using the grid-search method.The feature transformation module transforms the s-dimensional feature  machine  construcTo best use all of the subjects in our experiment and explore the general performance of our model, we used three-fold cross-validation to split the dataset into training and test sets, which were repeated 10 times with different random partitions. The input feature of each biomarker was normalized using the natural logarithm before being fed into the model. The specific feature selection and linear transformation were based on the statistical analysis of all of the subjects. The output of the final SVM classifier was set to probability form, which means that the classification threshold can flexibly be adjusted to meet different sensitivity and specificity requirements in the application process.6, 105, 104, 103, 102, or 10 copies) plasmids were used to evaluate the performance of the LAMP primers. Each reaction was repeated three times, and the negative control group (using dH2O instead of plasmid) was also established. R2) of 0.9438. For all of the 11 selected biomarkers, the LOD and linearity analyses of their LAMP primers were conducted in the same way. We found that the assay could detect as few as 10 copies of NSE, ProGRP, and CD56, and 102 copies of the other eight biomarkers. All of the biomarkers displayed good linearity with an R2 > 0.89, indicating the relative quantification reliability of the assay.Serially diluted  were used to react with the LAMP primers of one marker each time, and all 11 primers were tested in turn. The template concentration was 10The mRNA levels of the 11 biomarkers were evaluated and compared among different histology types: benign, NSCLC (including LUAD and LUSC), SCLC, metastatic lung cancer, and primary lung cancer (including NSCLC and SCLC). Among these biomarkers, three were correlated with LUSC, one was correlated with metastasis, and five were correlated with SCLC. For CA125 and TTF-1, there were no significant expression differences observed between different histology types.p = 0.003), LUAD (p = 0.001), and SCLC (p = 0.003) (p = 0.031). On the contrary, the SYN expression in LUSC was lower than in benign tissue (p = 0.035) and SCLC (p = 0.028). The expression levels of EGFR were correlated with metastasis. mRNA expression increased in groups with metastatic lung cancer compared to the benign (p = 0.001) and primary lung cancer (p = 0.000) groups  . The SCC) groups .p = 0.038). The ProGRP expression in SCLC was higher than in benign tissue (p = 0.030) and LUSC (p = 0.017). The CD56 expression in SCLC was higher than in the benign (p = 0.032), LUAD (p = 0.035), and LUSC (p = 0.004) groups (p = 0.044) and NSCLC (p = 0.021) (p = 0.005) and LUAD (p = 0.018) groups.The mRNA expression levels of CEA, ProGRP, CD56, IDH1, and NSE were correlated with SCLC. The CEA expression in SCLC was higher than in LUSC  groups . The IDH= 0.021) . The NSEAfter determining the cancer subtype each biomarker could distinguish, all 86 clinical samples were classified according to each of the cutoff values of the 11 biomarkers. Briefly, for each biomarker, a high-mRNA expression sample was regarded as the specific subtype, and a low-mRNA expression sample was regarded as one of the other subtypes. 65. However, in our study, the mRNA expression levels of CEA and IDH1 in SCLC were higher than in NSCLC. There may be several reasons for these results. First, the number of SCLC samples used in our study was small (only six). Second, SCLC is acknowledged to be more malignant than NSCLC. Finally and most importantly, other studies measured protein rather than mRNA levels, and mRNA expression is not completely synchronized with protein expression. Further studies should be conducted to confirm our results.CEA is recommended by the NACB  guidelines for NSCLC diagnosis when combined with CYFRA21-1, and IDH1 is used as a blood biomarker for the diagnosis of NSCLCJointly considering multiple biomarkers, we evaluated the performance of the introduced machine learning classification model for identifying different subtypes of lung cancer. The model was applied to five binary class settings: benign and malignant, adenocarcinoma and non-adenocarcinoma, squamous carcinoma and non-squamous carcinoma, SCLC and non-SCLC, and pulmonary metastasis and non-pulmonary metastasis. By summarizing the sensitivity and specificity at different threshold levels, an ROC curve  was plotThe performance of the five binary classification models is shown in In general, benign and SCLC subjects were relatively easy to identify. A total of nine biomarkers were chosen to judge benign and malignant lung cancers, with an AUC score of 0.963; seven biomarkers could be used to distinguish SCLC from NSCLC, and the sensitivity was 0.983. Thus, this assay could accurately classify the main classes of lung cancer. Pulmonary metastasis could also be recognized by 10 biomarkers, including EGFR. Compared to single biomarker analysis with EGFR, combined analysis of the biomarkers increased the sensitivity and specificity. As for the classification of NSCLC, the AUC scores of adenocarcinoma and squamous carcinoma were slightly lower. However, all of the AUC scores are approximately 0.88 or greater, and the average score is 0.934. Therefore, this promising average performance suggests the validity of using mRNA biomarkers for the minimally invasive and rapid diagnosis of lung cancer. Although some biomarkers were not significant for specific binary classifications, the combination of multiple biomarkers was an improvement over the use of single biomarkers.By far, clinical lung cancer diagnosis techniques such as chest X-rays, CT scans, and pathological sectioning methods are the most widely used for lung cancer, yet none of them are sensitive and specific enough for the identification of new biomarkers. Although immunoassays are sensitive and selective for the early diagnosis of lung cancer, disadvantages remain because they are time-consuming, expensive, multistep, and often require large and expensive equipment. Despite the fact that molecular biology methods such as RT-PCR can be powerful to detect tumor cells, it should be noted that these methods require complicated manual operations, multiple instruments, and experienced operators to perform the analyses. In addition, methods based on EP tubes or multi-well plates consume >25 μL of samples and reagents, and thus, large amounts of tissue must be sampled. Furthermore, multiple samplings are also needed for typing, which is harmful to the operator and difficult to achieve, for many diseased tissues do not meet the requirements of multiple sampling.In recent years, various types of factors, such as cell-free DNA, circulating tumor cells, and exosomes in bodily fluids, have been analyzed for the detection of lung cancer. Cell-free DNA and circulating tumor cells are present in very small amounts, resulting in the need for special collection devices, and expression levels are hard to obtain in most cases . Lung caOur assay uses histopathologic biopsy and detects mRNA biomarkers corresponding to protein tumor markers. Such multi-biomarker analysis based on machine learning is a general method and can be applied to liquid biopsies as well. For data acquisition, nucleic acid analysis based on the bronchoscope sampling method has obvious advantages. As a minimally invasive technique, it requires only rice-sized tissue samples. One sampling can detect 11 biomarkers at the same time and enable accurate typing and identification. The operation is also simple and rapid (within 45 min), with low cost for small typing reaction cells (only 0.94 μL), less than 1/25 of the conventional 25 μLEP tube test method.AI is a powerful tool in biomedical research that is used to analyze deep features and connections among lesions and pathological disorders. In this study, we first used machine learning techniques to build a correlation graph from minimally invasive mRNA biomarkers to lung cancer subtypes. The model, jointly considering all mRNA biomarkers, was a great improvement over single biomarker analysis.However, our study still has some challenges. First, the data scale in our study includes only 86 subjects, which may limit the performance of our models. Expanding the number of subjects would improve the robustness and reliability of our method. Second, the expression levels of mRNA biomarkers in the biopsy samples were first applied to the specific classification of lung cancer. Diagnosis based on protein is the traditional method and also the gold standard. Based on this view, it is more accurate. However, the detection of protein usually requires a large sample volume, complicated manual processing steps, and a lengthy time to generate final results. Furthermore, precise typing is still challenging in the clinic. Thus, we attempted to use mRNA as a new target and achieved quite good classification results, but further research should be performed to verify the assay. With larger datasets and improvements in deep learning technology in the future, we believe this study can be evaluated more thoroughly.It is hoped that the minimally invasive and rapid AI diagnosis of lung cancer can be used as a guide to enter grassroots communities and even families to enable timely screening, long-term tracking detection, and health monitoring of lung cancer or other diseases. Once abnormalities are found, physicians can use minimally invasive methods to quickly perform multi-index typing and precise molecular diagnosis for personalized treatment. Then, the non-invasive method could be used to longitudinally track patients to evaluate the treatment effect.Herein, we developed a rapid, minimally invasive, and convenient nucleic acid biomarker recognition method, which enabled the combined specific detection of 11 lung cancer typing markers in a microliter reaction system after only one sampling. This method uses a miniaturized microfluidic-based nucleic acid analyzer combined with deep learning and machine learning.R2 = 0.9938). This significantly reduced the testing cost and significantly simplified the process of detecting multiple subtypes in parallel. To leverage multiple biomarkers together for the typing of lung cancer, a machine learning-based approach is proposed with discriminative feature selection and feature transformation by margin maximization. A total of 86 clinical samples were tested using the miniaturized nucleic acid analyzer and classified by the multi-biomarker analysis based on the machine learning model. The importance of each biomarker in identifying cancer subtypes was analyzed via a machine learning approach and achieved an average AUC of 0.934 on five binary classification tasks. This assay could distinguish benign from malignant lung cancer and also classify LUAD and LUSC in the NSCLC group. Moreover, the metastasis of lung cancer could be distinguished with an AUC score of 0.9. These promising results highlight the prospect of minimally invasive, rapid, and precise typing diagnosis of lung cancer using mRNA biomarkers in clinics.In this method, the primers for the combined detection of 11 lung cancer typing markers were designed and screened, the microfluidic chip for the parallel detection of the markers was designed and developed, and a miniaturized microfluidic-based analyzer was also constructed. We found that differences in the mRNA expression of multiple lung cancer typing biomarkers can be used to classify histology types from rice-sized tissue samples collected by bronchoscopy. Lung cancer subtypes could be identified within 45 min. The volume of each reaction cell was only 0.94 μL, and the sensitivity was as low as 10 copies with good linearity (


The objective of the study was to explore the CT and ultrasound features and clinical significance of perivascular epithelioid cell tumor (PEComa) of the liver.Eleven hepatic PEComa patients treated in our hospital were retrospectively analyzed based on the characteristics of the imaging results of the patients, including conventional ultrasound, CDFI, contrast-enhanced ultrasound (CEUS), and contrast-enhanced CT (CECT).CT scans showed that all lesions were hypodense. Ultrasonography showed that lesions were either hyperechoic , hypoechoic , isoechoic , or heterogeneously echoic . CDFI showed that most of the lesions had an abundant blood supply . Whether on CT scan or ultrasonography, the margins of the lesions were dominated by clear margins. Ultrasonography revealed more features: hyperechoic patterns around lesions  and lateral shadow . The CDFI showed that large blood vessels were observed around the lesions . CECT shows two enhancement patterns: “fast in and fast out (FIFO)”  and “fast in and slow out (FISO)” . CEUS shows that all lesions had the enhancement pattern of “FISO,” which was different from CECT. All lesions displayed rapid enhancement during HAP in CEUS during 7–20 s. Four patients (36.36%) washed out at 60–180 s, another four (36.36%) washed out at 180–300 s, and the remaining three patients (27.27%) showed no signs of washout even at 360 s.Some imaging features, such as clear margins, peripheral hyperechoic around the lesion, lateral shadow, the large blood vessels around lesions, and the “FISO” enhancement pattern, may indicate expansive growth of the tumor and be helpful in the diagnosis of PEComa. Ultrasound images may provide more details for clinical reference. PEComa (perivascular epithelioid cell tumor) is a mesenchymal tumor with histological and immunophenotypic features of perivascular epithelioid cells . In 1992PEComa tumors originating from the liver are rare, which are often misdiagnosed because of the atypical imaging features . As we aTherefore, further research on the imaging characteristics of PEComas as a rare disease is of significant clinical value, which is beneficial to our in-depth understanding of the occurrence and development of this disease and the diagnosis, treatment, and prognosis of this disease in clinical work. In our study, 11 patients with hepatic PEComa treated in our hospital over the past ten years were retrospectively analyzed based on the characteristics of their imaging results, including conventional ultrasound (US), color Doppler flow imaging (CDFI), CEUS, and CECT, and pathologic analysis. Some results may provide important references for our clinical work.The data of all patients with PEComa admitted to our hospital from January 2008 to December 2018 were collected. To be included in the study, the patients had to meet the following inclusion criteria: (1) the patient had undergone a liver CEUS examination; (2) the patient had received an abdominal CECT at the same time as the CEUS examination; and (3) the lesion was surgically removed, and the diagnosis of PEComa was confirmed by pathology. The patient was excluded if one of the following exclusion criteria was met: (1) the patient did not receive a CEUS and a concurrent abdominal CECT; or (2) the pathologic diagnosis was not definitive.via the cubital vein using a high-pressure syringe at 3.5 ml/s. Triphasic, dynamic CT was performed. The hepatic arterial phase (HAP), portal venous phase (PVP), and delayed phase were 20–25 s, 60 s, and 90–120 s, respectively, after the start of the injection.A Lightspeed VCT 64-slice CT scanner  was used. The scan range was from the top of the liver to a section 2 cm lower than the inferior border of the liver. A contrast agent containing 1%–2% iodine was orally administered before the examination. The slice thickness was 5 mm without reconstruction intervals. A plain CT scan was performed first, and then a bolus injection of 80–100 ml of iopromide (a contrast agent containing 300 mg/ml of iodine) was administered The GE  LOGIQ E9 and LOGIQ 9 color Doppler ultrasound scanners were used in this study. The scanner is equipped with C1-5 (LOGIQ E9) and 4C (LOGIQ 9) abdominal probes. The frequencies were 2.8–5.0 MHz and 2.0–4.0 MHz for LOGIQ E9 and LOGIQ 9, respectively. Conventional ultrasound, CDFI, and CEUS were performed to examine the livers of the patients. SonoVue  was used as the contrast agent and configured according to the instructions. The patient received a bolus injection of SonoVue through the anterior cubital vein, with 1.5–2.4 ml given at each injection. The lesions were inspected continuously throughout the HAP (0–30 s) and PVP (31–120 s). A full liver scan was performed at the delayed phase (120–360 s) to detect whether there were other abnormal lesions with hyper-enhancement or hypo-enhancement. Ten minutes after the first CEUS scan, a second CEUS scan was performed on the suspected lesion to assess the status of enhancement and washout. Each CEUS scan lasted for at least 6 min, and the footage was stored. The imaging characteristics of the lesions examined using conventional ultrasound, CDFI, and CEUS were recorded.All images were independently reviewed by two radiologists or sonographers who had 10–20 years of experience in the interpretation of abdominal CT/CECT and ultrasound/CDFI/CEUS images. The final decisions were reached by consensus.Tumors surgically removed from all patients were subjected to pathologic examinations. Histopathological evaluation included routine hematoxylin and eosin (HE) staining and immunohistochemical staining. Melanocytic markers include HMB-45 and Melan.A and smooth muscle markers include SMA. Pathological examinations and specimen handling were performed by experienced liver pathologists. The cells were positive for human melanoma black-45 (HMB45) and Melan.A on immunohistochemical staining, confirming that the lesion was a PEComa.This study received institutional review board approval and informed patient consent.SPSS 13.0 software was used for data analysis. Continuous variables were expressed as means ± SD. The comparison between the two examination methods was performed by McNemar’s test. P <0.05 was statistically significant.A total of 11 patients were included in this study. All patients were diagnosed with PEComa by pathological examination. The clinical characteristics of the patients are shown in In the evaluation of lesions, CT, US, and CDFI were performed. These results are shown in In the evaluation of the margin of the lesions, the two examination methods showed some features that suggested the possibility of expansile growth 3. WhethAll patients received an abdominal CECT scan Figure 2p = 0.004) (p = 0.008)  ; that is= 0.004) , 13. TheFocal lesions are common among liver diseases, and the most common are HCC, hepatic hemangioma, and hepatic cysts. All these diseases present some apparent features on imaging examination, which is very helpful for noninvasive clinical diagnosis of focal liver lesions . HoweverThe non-enhanced scan is a commonly used screening method in clinical practice . In thisIn the examination of the lesions, all lesions showed low density, which was an important feature of PEComa by CT scan. This was similar to the literature report . We did The blood supply of the lesion is closely related to the growth of the lesion. CDFI provides a good technical means for blood supply tests. For PEComas, CDFI demonstrated that lesions had an abundant blood supply, similar to primary HCC. The feature of abundant blood supply may be helpful for the choice of treatment methods, such as anti-angiogenic therapy , 23, 24 In clinical practice, enhanced imaging examinations have become one of the most important test approaches for detecting and diagnosing focal liver lesions . A largeIn this study, we retrospectively analyzed the imaging data of all PEComa patients. CECT scans showed that most of the lesions manifested with two enhancement patterns: “fast in and fast out” and “fast in and slow out,” with the former being predominant. However, on CT imaging, the most common types of liver malignancies, such as hepatocellular carcinoma, predominantly manifest the “fast in and fast out” enhancement pattern, whereas hyperplastic nodules of the liver manifest the “fast in and slow out” enhancement pattern (rapid enhancement in the HAP and slightly high density or iso-density in the PVP and delayed phases) . TherefoAs a new technology, CEUS has played an important role in the diagnosis and treatment of tumors , 27. In Therefore, compared with CT and CECT, ultrasonography can provide more imaging features, which may be beneficial to the diagnosis and treatment of PEComa. For example, some liver lesions, such as hyperplastic nodules, often do not have an abundant blood supply, and few are surrounded by large blood vessels. These features are markedly different from those of PEComa. FNH has special imaging features, such as central scarring , 31. TheIn summary, we retrospectively analyzed the imaging features of PEComas in 11 patients using two types of imaging tests: CT/CECT and US/CDFI/CEUS. The lesions were not found to display any apparent specific characteristics on CT or CECT, indicating that these tests were of little help in the diagnosis of the disease. However, ultrasound imaging presented clear and specific imaging manifestations of the lesions in the patients, which were helpful in the diagnosis of PEComa. Evidently, more patients with PEComa are still needed to further explore and identify relevant imaging features of the disease.The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by the Ethics Committee of Peking University Cancer Hospital & Institute. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.XG and WW performed drafted the manuscript and the study design. XG, WW, HT, QY, JW, HW, YW, MM, KY, and WY performed the imaging studies of the patients and the data analysis. XG, HT, HW, and WW take responsibility for the data collection and sorting. All authors contributed to the article and approved the submitted version.This study was received funding from the Capital Health Research and Development (Grant Number 2020-2-2152), the Beijing Science and Technology Planning Project (Grant Number Z131107002213147), and the Natural Science Foundation of Beijing (Grant Number 7222172).We thank Prof. Minhua Chen for her help in the research.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Both office mean BP and 24 h-systolic BP in the first trimester were higher in women with versus those without PE (p ≤ 0.001). In women with chronic hypertension (cHT), PE occurred in 55%; office SBP (p = 0.769) and 24 h-SBP (p = 0.589) were similar between those with and those without PE. Regarding biochemistry, in cHT, plasma urea and creatinine were higher in PE women than in those without cHT (p = 0.001 and p = 0.004 for the differences in both parameters). These differences were not observed in normotensives. In normotensives, mean BP was the best predictor of PE [ROC curve = 0.91 (95%CI 0.82–0.99)], best cut-off = 80.3 mmHg. In cHT, plasma urea and creatinine were the best predictors of PE, with ROC curves of 0.94 (95%CI 0.84–1.00) and 0.93 (95%CI 0.83–1.00), respectively. In the first trimester of pregnancy, the strongest predictor of PE in normotensive women is office mean BP, while in cHT, renal parameters are the strongest predictors. Otherwise, office BP is non-inferior to 24 h ambulatory BP to predict PE.Preeclampsia (PE) is characterized by the new onset of hypertension (HT) and proteinuria beyond the 20th week of gestation. We aimed to find the best predictor of PE and find out if it is different in women with or without HT. Consecutively attended pregnant women were recruited in the first trimester of pregnancy and followed-up. Laboratory and office and 24 h-ambulatory blood pressure (BP) data were collected. PE occurred in 6.25% of normotensives ( Preeclampsia (PE) is a multi-system progressive disorder characterized by the new onset of hypertension and proteinuria or significant end-organ dysfunction after the 20th week of gestation . The preHT in PE is a consequence of vasoconstriction phenomena and increased peripheral vascular resistance. So far, the best-known predictor of PE is mean arterial blood pressure (MBP), which increases at early stages of gestation . FurtherIn this study, we aimed to assess which hemodynamic or biochemical parameters determined in the first trimester predict PE, and whether they are different in normotensive and cHT pregnant women. In addition, we have looked for possible differences in the predictive value of BP as measured in an office or ambulatory setting.This prospective cohort study was conducted at the Hypertension and Vascular Risk Unit of the Nephrology Department of the Hospital del Mar in Barcelona from December 2015 to June 2018. Participants were recruited at the time of the routine first-trimester scan (13.7 ± 2 weeks of gestation). Exclusion criteria were multiple pregnancy, age below 18 years and chronic kidney disease. A total of 144 singleton pregnant women were eligible to enter the study and provided the written informed consent. The local ethics committee approved the study protocol® . BP measurement was performed according to the European Society of Hypertension Guidelines for office blood pressure measurement [Arterial BP was measured by using an automatic calibrated device . Likewise, based on the estimation of the ROC curve, indicative cut-offs were established for the prediction of PE for each of the parameters with statistically significant differences and the corresponding sensitivity, specificity, and positive and negative predictive values were calculated.A database was created by using SPSS . Some specific analyses were also performed using the STATA program. Variables following normal distribution are summarized as mean ± S.D. and categorical data are presented as frequencies and percentages. Data with non-normal distribution are summarized as median and interquartile range (IQR). For normally distributed quantitative variables, groups were compared using the Student’s n = 124) and pregnant women with a history of cHT (n = 20) were separately analyzed. Sixteen (80%) women of this latter group were on antihypertensive treatment.We evaluated 144 consecutively recruited pregnant women in their first trimester of gestation. Normotensive pregnant women  determined in the first trimester of pregnancy are shown in Laboratory parameters are shown in The ability of BP parameters (both office and 24-h ambulatory BP) to predict PE is shown in Given that the women with cHT who developed sPE had higher values of plasma urea and creatinine concentrations than those with unaffected pregnancies, the accuracy of these parameters to predict sPE was calculated. As shown in Blood pressure measurement is a marker of quality in prenatal care. The relationship between BP and the development of PE has been widely demonstrated , but thiAs early as in the first trimester of pregnancy, we found that office BP is a strong predictor of the development of PE in previously normotensive women, but not in those with cHT. Among all the evaluated hemodynamic parameters, office MBP is the strongest predictor of further PE development. On the contrary, in pregnant women with cHT, neither MBP nor any of the other office or ambulatory BP parameters were good predictors of PE. Similarly, Rovida et al.  found a However, in these mentioned studies, the prevalence of pregnant women with cHT was almost residual, around 0.5–1.4%. In pregnant women with normal-high BP levels (SBP = 130–139 and/or DBP = 80–89 mmHg) . In our Of note, we observed a higher percentage of non-Caucasian ethnicity in pregnant women with cHT as compared to normotensive women. Nevertheless, we consider that the results in the renal biochemical parameters are not influenced by this condition, although this should be validated in larger samples.The second important finding refers to the best method for measuring BP in pregnant women, at least in relation to the prediction of PE. In our study, it is worth highlighting the systematic approach followed to determine office BP. This was carried out strictly in accordance with the recommendations of current HT guidelines , i.e., rIn summary, the prediction of PE in the first trimester differs between normotensive pregnant women and pregnant women with cHT. In normotensive pregnant women, the strongest predictor of PE is the determination of BP, and in particular office MBP, with the best cut-off point being 80.3 mmHg. In pregnant women with cHT, biochemical parameters in the first trimester, mostly plasma urea and creatinine, can detect those pregnant women with a higher risk of developing sPE, with the best cut-off values for plasma creatinine and urea being 0.54 mg/dl and 18 mg/dl, respectively. The early detection of the population at higher risk of developing PE or sPE with such easily available markers allows early initiation of prophylactic acetylsalicylic acid treatment before 16 weeks of gestation. Nevertheless, due to defined study limitation, which is number of cases, results should be treated as initial/preliminary findings, whereas so important to be analysed in perspective of bigger study groups.Office MBP is the main predictor of PE in normotensive pregnant women, but we point to laboratory parameters as the most important factor to predict sPE in women with cHT. We provide cut-off values for office MBP and plasma urea levels to predict PE in normotensive and cHT pregnant women as determined in the first trimester, respectively. An accurate measurement of office BP is not inferior to 24 h-ABPM to predict PE.


Sleep efficiency of <80% based on actigraphy was defined as insomnia as self-reported difficulty falling asleep or waking up at night three to four times per week. It is known that adequate sleep is very important for human wellbeing, affecting people's work and life, insomnia will seriously damage our daily life. There is no recognized non-drug treatment. Studies have found that Taijiquan has a positive effect on insomnia patients. This systematic review and meta-analysis will evaluate the effect of Taijiquan on insomnia.To find all randomized controlled trials exploring the effects of Taijiquan on insomnia patients in Chinese and English, eight databases  were searched. The retrieval time is from database construction to October 2021. Searches were conducted in both English and Chinese language. A meta-analysis by mean difference (MD) and 95% confidence interval (CI) was performed with RevMan 5.3. The risk of bias for each study was accounted for according to the Cochrane Handbook. Our primary outcome was Pittsburg Sleep Quality Index. We explored sources of heterogeneity by comparing effect sizes across different types of etiology, country, control group, and intervention type. The protocol was pre-registered with PROSPERO, CRD42021284511.P < 0.01]; There is insufficient evidence of improvement in patients with cerebrovascular disease ; 8-form, 10-form or 24-form Yang's Taijiquan had the same effect in improving PSQI . When there is no treatment, exercise, exercise and health education as the control, taijiquan has a significant effect on insomnia treatment, and there is no difference in efficacy compared with cognitive behavioral therapy and health education  alone.Twenty-one RCTs published between 2004 and 2021 with 2,022 participants were included in this study. Twenty-one randomized controlled studies showed that Tai Chi significantly improved PSQI scores in patients with cancer, muscle fibrosis, and sub-health insomnia [MD = −1.16, 95% CI , The results of the study showed that Taijiquan significantly improved sleep quality in healthy adults and patients with chronic diseases, which suggests that Taijiquan may be considered as an alternative behavioral therapy in the treatment of insomnia. In the future, more high-quality, well-controlled randomized trials are needed to better inform clinical decisions. Insomnia is very common in the population, which is characterized by difficulty starting or maintaining sleep, along with symptoms such as irritability or fatigue when awake . AdequatAt present, the treatment methods for insomnia mainly include drug therapy , cognitiStudies have shown that Taijiquan, as a new intervention, has a good effect on insomnia. Irwin et al.  observedTherefore, we sought to summarize existing high-quality studies on Taijiquan intervention for insomnia, and overcome the limitations of the previous Meta-analysis, to seek a higher level of evidence-based medical evidence.We conducted a comprehensive search for all published and unpublished RCTs of Taijiquan for patients with insomnia or other diseases with sleep complaints, in both Chinese and English language. We searched four English databases—Pubmed, Embase, Cochrane library, Web of Science, and four Chinese databases—CNKI, CBM, VIP, and Wanfang Data, from their inception to October 20, 2021. The search strategy is outlined in 1) Randomized and controlled design2) Sample size ≥303) Duration of intervention ≥1 week4) Use a suitable control intervention 5) Have measurable results for sleep, any form of scale, or objective electrophysiological indicators6) Any form of Taijiquan7) Full text available and can get enough data.We excluded duplicate reports, reviews, conference abstracts and letters, trials enrolling patients with non-related subject research, and data that were incomplete or not obtainable. In addition, after the researchers reviewed the full text and discussed for many times, the articles identified as having serious quality defects, such as data confusion, and the articles with obvious flaws in the study design were also excluded.The two authors (DMH and ZCL) independently searched and screened the retrieved literature. Unqualified trials were excluded, and the differences were resolved through discussion between the two authors. For problems that cannot be solved through discussion, consult the third author (YH) jointly to assess whether the trials met the inclusion criteria.Some baseline information is extracted from the original studies, and they include the first author and published year, sample of patients, age, sex, outcome, intervention, frequency in two groups, and follow-up period. Data are extracted independently by two investigators (DMH and ZCL), and discrepancies are resolved by consensus. We have contacted the corresponding author to obtain the data when necessary. The primary outcome is Pittsburgh Sleep Quality Index (PSQI), PSQI is the most widely used sleep assessment tool with good reliability and validity , 18. It Two review authors (DMH and ZCL) independently evaluated the risk of bias for each study according to the Cochrane Handbook for Systematic Reviews of Interventions. Disagreements were resolved by discussion or by consultation with a third reviewer (YH), when necessary. The following domains were assessed: sequence generation, allocation concealment, blinding of participants, providers and outcome assessors, completeness of outcome data, selective outcome reporting, and other sources of bias. Each potential source of bias was classified as either high, low, or unclear.I2 statistic was used to evaluate the heterogeneity revealed by data analysis. The interpretation of the I2 statistic is as follow (Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.1.2008):Review Manager (RevMan) version 5.3 software was used for the meta-analysis. Since this meta-analysis included only continuous data, we used the mean difference (MD) and 95% confidence interval (CI) for analysis. If the data was not available in the article, and the authors could not be contacted, estimates were made using the known data and the formula in the Cochrane Handbook for Systematic Reviews of Interventions. The 10–40%: might not be important30–60%: may represent moderate heterogeneity50–90%: may represent substantial heterogeneity75–100%: considerable heterogeneity.If substantial heterogeneity (above 50%) was detected, a random-effects model was used in the meta-analysis, where appropriate, subgroup or sensitivity analyses were performed to explore the source of heterogeneity.The review searched literature from eight databases. The study included 21 articles from seven countries—four from China, 12 from the United States, one from Iran, one from Italy, one from Turkey, one from Japan, and one from Germany. Their characteristics are presented in For the interventions, 15 articles trace back or describe in detail the types of taijiquan. eight studies used 24 forms of Yang's Taijiquan, and four studies used 8-form Yang style Taijiquan. Three studies used 10-form Yang style Taijiquan. Taijiquan lasts for a minimum of 12 weeks and a maximum of 24 months. Most are 3–6 months. The frequency of Taijiquan varies from 1 to 5 times per week .According to the Cochrane Handbook for Systematic Reviews of Interventions, we assessed the risk of bias in the included literature. The results are shown in According to our retrieval results and the characteristics of the included studies, most of the studies used PSQI as the outcome indicator, while other outcome indicators could not be meta-analyzed due to the lack of a sufficient number of studies.P < 0.00001] , 0.00001] . However 0.0001] , FurtherP < 0.00001] and the heterogeneity is small  . When the Nguyen et al. , and the meta-analysis still showed a stable, significant effect  , n et al.  study wa0.00001] , 1.2.1. 0.00001] , 1.2.6;  0.0010] , 1.2.4.  = 0.27] , 1.2.3.  = 0.20] , 1.2.5. In this systematic review and meta-analysis, we identified 21 RCTs of 2022 individuals from seven countries. Overall, taijiquan has a better effect on insomnia improvement compared with exercise and health education alone, and subgroup analyses found that tai chi was as effective as cognitive behavioral therapy in improving insomnia. In terms of different diseases, we found that Taijiquan significantly improved cancer, fibromyalgia, and insomnia in normal elderly people, while there seemed to be no significant difference in patients with cerebrovascular disease. Compared with other studies, Taijiquan was equally effective for Americans and Chinese. There are no influences that have a significant effect on Asians. This systematic evaluation includes all the studies on Taijiquan intervention for insomnia in both Chinese and English, and the research objects include both healthy people and various patients, the old and the young, which is a relatively complete systematic evaluation of Taijiquan intervention for insomnia. Additionally, since no adverse events were reported, Taijiquan could be promoted as a safe intervention for improving sleep quality.Insomnia is a common problem, with about a quarter of adults suffering from insomnia. Body and mind exercise is a hot topic in the intervention treatment of insomnia. Taijiquan was gradually formed in the late Ming and early Qing Dynasties. It is a centuries-old martial art that combines physical movement and relaxation and is a traditional Chinese sport that has spread worldwide in recent years, more than five million people practice Tai Chi in the US alone . At presThe exact biological mechanism of Taijiquan in treating insomnia is not clear, Compared to simple exercise training, current hypotheses suggest that Taijiquan may improve sleep outcomes by reducing sympathetic activity and stimulating the parasympathetic nervous system, restoring the homeostasis balance of sympathetic/parasympathetic function . As a loThis systematic review has some advantages and limitations. We conducted a relatively comprehensive systematic review, and the patient types included cancer, fibromyalgia and normal elderly people, etc. There were many diseases, so we could objectively evaluate the efficacy of Taijiquan on insomnia. Compared with previous systematic reviews , we inclIn reviewing almost all about Taijiquan to improve insomnia, the high quality of research, we believe that Taijiquan to improve insomnia is convincing, however, the effects of different groups for different styles of Taijiquan treatment is not clear, Taijiquan differences between different age also needs to continue to study, different intervention dose and frequency of the need to continue to study. In addition, further research is needed on the physiological mechanism of Taijiquan in improving insomnia. Future research directions require more large-sample, multi-center, high-quality randomized controlled trials. It is necessary to further optimize the application of different types of Taijiquan in insomnia.In conclusion, our meta-analysis showed that Taijiquan can improve sleep quality and improve insomnia. It provides evidence for taijiquan to treat different insomnia people and improve sleep quality. Subgroup analysis showed that Taijiquan can also improve insomnia caused by different diseases (except cerebrovascular diseases), which can be used as a supplement and alternative treatment for insomnia. There was no difference in the efficacy of different forms of Taijiquan, and there was no significant difference in the effect of Taijiquan on improving sleep between Chinese and Americans.The original contributions presented in the study are included in the article/DH and ZL conceptualized the study design, search and filter the title and abstract of the article, and confirmed the data and statistical analysis. YW and XW drafted and supplemented the methodology. HL and YH solved the difference. YH provided the funds. YC and XL modified their English and provided help in data analysis. JQ and JC are responsible for supervision and quality control. All authors provided information about the direction of research and the contents of the manuscript. All authors approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Autism Spectrum (AS) is defined primarily by differences in social interactions, with impairments in sensory processing also characterizing the condition. In the search for neurophysiological biomarkers associated with traits relevant to the condition, focusing on sensory processing offers a path that is likely to be translatable across populations with different degrees of ability, as well as into animal models and across imaging modalities. In a prior study, a somatosensory neurophysiological signature of AS was identified using magnetoencephalography (MEG). Specifically, source estimation results showed differences between AS and neurotypically developing (NTD) subjects in the brain response to 25-Hz vibrotactile stimulation of the right fingertips, with lower inter-trial coherence (ITC) observed in the AS group. Here, we examined whether these group differences can be detected without source estimation using scalp electroencephalography (EEG), which is more commonly available in clinical settings than MEG, and therefore offers a greater potential for clinical translation. To that end, we recorded simultaneous whole-head MEG and EEG in 14 AS and 10 NTD subjects (age 15–28 years) using the same vibrotactile paradigm. Based on the scalp topographies, small sets of left hemisphere MEG and EEG sensors showing the maximum overall ITC were selected for group comparisons. Significant differences between the AS and NTD groups in ITC at 25 Hz as well as at 50 Hz were recorded in both MEG and EEG sensor data. For each measure, the mean ITC was lower in the AS than in the NTD group. EEG ITC values correlated with behaviorally assessed somatosensory sensation avoiding scores. The results show that information about ITC from MEG and EEG signals have substantial overlap, and thus EEG sensor-based ITC measures of the AS somatosensory processing biomarker previously identified using source localized MEG data have a potential to be developed into clinical use in AS, thanks to the higher accessibility to EEG in clinical settings. Autism Spectrum (AS) is a defined primarily by differences in social interactions relative to neurotypical individuals, with differences in sensory processing also characterizing the condition . DiffereMotivated by such findings, and in particular by findings of different behavioral responses to vibrotactile stimuli in AS , we prevGroup comparison analyses of these two components of the response showed that cortically-constrained MEG source estimates of the response showed lower ITC in the AS than the NTD group in the 50-Hz component in the primary somatosensory cortex (S1), with a large effect size, and higher ITC in the 25-Hz component in the secondary somatosensory cortex (S2), with a more moderate effect size. The simple and accessible design, using passive vibrotactile stimulation, makes it a compelling potential translational target for populations that are more deeply affected by AS, or to younger participants that would not be able to participate in more demanding paradigms. However, the MEG setup and the focus on data at the source level are not ideal for translation, as MEG resources are relatively scarce, and source space analyses typically require specialized skills. That said, electroencephalography (EEG) and MEG tend to capture similar information , which More specifically, MEG and EEG source estimation  procedures help to dissociate between contributions from multiple simultaneously active brain regions . HoweverThe translation from MEG to EEG is in theory feasible because MEG and EEG signals have a common physiological origin, namely, electrical currents associated with neural activity. The sources of the MEG and EEG signals are described in terms of active “primary” currents, mostly corresponding to post-synaptic dendritic currents in cortical pyramidal neurons . Thus, sHere, we examined whether the group differences observed in MEG source estimates reported by Khan et al.  using thFourteen AS participants and ten NTD control participants were studied. No participants were excluded, as data from all participants was of sufficiently high quality. Parents of participants ages 15–17 years, and all adult participants ages 18 and up, provided informed consent according to protocols approved by the Massachusetts General Hospital and Institutional Review Board (IRB). Participants ages 14–17 provided assent  in addition to parental consent.Som). Data on the AASP were collected for all but one NTD participant.Phenotypic data collected from all participants are summarized in via a long tube; the subjects could not hear sounds associated with the stimulation. The stimuli were presented while participants were watching a silent video of their choice. Participants were instructed to not pay attention to the stimulation and not move their hands, which we ensured were resting comfortably on a pillow. The sequence of stimuli was controlled using the MATLAB Psychophysics Toolbox.1Vibrotactile stimulation consisted of pulses applied to the right index finger at 25 Hz using a custom made pneumatic tactile stimulator with latex tactor tips, based on a published design . The stiMEG and EEG data were simultaneously acquired using a Neuromag Vectorview system  in a magnetically shielded room . The system included 306 MEG channels , and a 70-channel EEG cap with nose reference and two electrooculogram channels. The data were band-pass filtered between 0.1 and 330 Hz prior to sampling at 1,000 Hz. The position of the head was continuously recorded during the data acquisition using four head position indicator (HPI) coils attached to the scalp. The locations of the HPI coils, three anatomical landmarks (nasion and auricular points), all EEG electrodes, and multiple additional scalp surface points were measured using a Fastrak digitizer (Polhemus).Channels with excessive noise were identified with the Autoreject software using the algorithm’s default parameters , and excTo compute the ITC for the somatosensory event-related responses, the epoched sensor data were transformed to the time-frequency domain using Morlet wavelet decomposition in the frequency range of 20–80 Hz. The number of cycles for each wavelet was 1/3 of the frequency value. The time step was 3.03 ms and the frequency step was 1 Hz. ITC is a measure of consistency of the phase of oscillatory responses across trials ; ITC valg, which provides a correction for small sample sizes  and recording modality (MEG and EEG). Because all these measures are correlated, correction for multiple (here four) comparisons using the Bonferroni correction, which assumes independence, is too conservative. Furthermore, the premise for the comparisons was to reproduce specific us study . TherefoTo further examine the relationship between the MEG and EEG ITC measures, a population-wide (AS and NTD combined) multimodal analysis was performed. A correlation matrix was computed using Pearson’s correlation. The effective rank of the MEG and EEG ITC measures at 25 and 50 Hz across subjects was evaluated using Principal Component Analysis (PCA).Grand average  somatosensory evoked responses to the vibrotactile stimulation in one representative MEG and one representative EEG sensor are shown in The spatial distributions of the ITC for the 25 and 50-Hz response components, averaged over the 250–1,000 ms time window are shown in For statistical analyses, we selected a small set of sensors (3 MEG planar gradiometers and 5 EEG electrodes) that showed large ITC values in the 250–1,000 ms time window in the population-wide averages . Note thp = 0.028 , Hedges’s g = 0.76 (effect size); MEG 50 Hz: p = 0.014, g = 0.75; EEG 25 Hz: p = 0.033, g = 0.75, EEG 50 Hz: p = 0.012, g = 0.88. Because the groups differed significantly on NVIQ, we then tested whether NVIQ values correlated with ITC values. No significant correlations between NVIQ and any of the ITC values were found in either group.When averaging across the entire steady-state time window, 250–1,000 ms, the ITC values were significantly lower in the AS than in the NTD group for both modalities . For MEGr = 0.76, p = 0.01  and r = 0.85, p = 0.02 (50-Hz); for the AS group, r = 0.50, p = 0.06 (25-Hz) and r = 0.77, p = 0.001 (50-Hz). Population wide, the correlations were: r = 0.67, p = 0.0004 (25-Hz) and r = 0.86, p < 10–7 (50-Hz).The MEG and EEG ITC measures in individual subjects were significantly correlated for both subject groups : for theResults of population-wide analysis of the relationship between the MEG and EEG ITC measures are shown in p = 0.04 for the 25-Hz ITC, and p = 0.02 for 50-Hz ITC, which however, would not survive a correction for multiple comparisons.Lastly, in Khan et al.  the ITC Differences between AS and NTD groups in steady-state somatosensory evoked responses were detected in both EEG and MEG sensor data. More specifically, lower ITC values in the AS than in the NTD group were found for both the 25-Hz response component as well as for the 50-Hz response component, at twice the stimulation frequency. Thus, in our small set of subjects, we detected similar group differences in the 50-Hz component of the response, using the same vibrotactile paradigm, as those in the MEG source estimation study of Khan et al. . These rIndeed, the ITC measures obtained with MEG and EEG sensor data were notably correlated, and analysis of the relationship between the MEG and EEG measures suggested that the two response components, 25-Hz ITC and 50-Hz ITC, may provide more complementary information than the use of the two recording modalities do. This is not unexpected, considering the common physiological origin of the MEG and EEG signals, yet at the same time this could not be assumed to be the case without verification, given the known differences in MEG and EEG signals as well.There were some notable differences between the present results and the prior study. Khan et al.  found loDespite the differences between the two studies at the 25-Hz ITC responses, the observed group differences in 50-Hz ITC are sufficient for considering future potential clinical applications, and the advantages of the potential for clinical translation may outweigh the greater precision possible with source localization. Indeed, it is encouraging that the sensor EEG data showed group differences consistent with the source space analyses of S1 in the prior study, even if not every detail or nuance of the original study were captured. This is because the most robust results would still be captured by EEG, while higher accessibility raises the potential of clinical usefulness, for instance to objectively assess the extent of somatosensory processing differences in AS individuals and to customize treatment plans accordingly. Another potential avenue would be to then use the same paradigm as an intervention biomarker, to assess whether interventions aimed at easing sensory processing burdens in AS were, in fact, effective at the neurophysiological level.p-values observed in this study would not survive a correction for multiple comparisons; however, because the different sensory processing scores are not independent and the MEG and EEG values are also not independent, the extent to which these p-values need to be corrected is not clear. Furthermore, the observed correlations are in line with the results of our prior study. Thus, although these correlations in and of themselves are not significant after correction, it is nonetheless encouraging that even with a small sample size, there is a trend in the direction of our prior result, supporting a correlation between EEG responses and behaviorally assessed somatosensory processing measures, as expected.Also encouraging is the indication of a potential correlation of the ITC values obtained using EEG with the sensory profile as assessed behaviorally. The Some limitations of the study need noting. In particular, while the results are consistent with prior findings of EEG-measured responses to vibrotactile stimulation in a neurotypical population , and larIn conclusion, this study was motivated by the findings that somatosensory processing differences are common in AS , 49, 50,The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Massachusetts General Hospital Institutional Review Board. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.SK and TK designed the research. SA, SG, JA, NM, ZN, and TK collected the data. NM performed the behavioral assessments. RJ supervised the assessments and made final diagnosis decisions as applicable. SA, SG, MH, SK, and TK analyzed the data. SA, SG, SK, and TK wrote the manuscript. All authors contributed to the scientific discussion and approved the submitted version.