The purpose of this study was to explore the association between benevolent childhood experiences (BCEs) and uncertainty stress among Chinese university students by network analysis.A total of 1,830 university students from three Chinese cities were recruited. Respondents' BCEs and uncertainty stress were self-reported using online questionnaire. The structure of the BCEs-uncertainty stress and related centrality indicators were examined for this sample.The overall network model showed that “no ways to suit the important changes in life” was the most influential, followed by “all things are not going well,” “feel that there is nothing to do,” and “worry about the future.” And in this network, the most influential bridge symptom was “having a positive self-concept.”The central symptoms of the BCEs-uncertainty stress network should be prioritized as targets in interventions and prevention efforts to reduce uncertainty stress among Chinese university students. Improving university students' positive self-concept is important to alleviate the level of uncertainty stress among Chinese university students. University students are passing through a critical transitory period , 2. In gSeveral psychosocial stressors  for unceGenerally, the studies of uncertainty stress always take the uncertainty stress measure as a whole and determine the state of uncertainty stress by calculating composite scores. The importance of measuring not only whether symptoms have changed, but also the interactions between individual symptoms has recently been highlighted by a newly developed symptom network perspective –30. So fwww.wjx.com). All participants gave their consent to participate in the study and allowed their data to be used for the research. Finally, from March to May 2021, the online questionnaire interviewed a total of 2022 students. Following the exclusion of individuals with missing data for key variables, an analysis sample of 1,830 was used (response rate: 90.50%). The Medical Ethics Committee of Xuzhou Medical University granted ethical approval for this study.Twenty-five universities in three Chinese cities  were used to recruit participants. To begin, schools were chosen using a stratified sampling method based on school levels as indicators. A total of 25 universities were selected. Second, classes in each university were selected using a stratified random sampling method based on majors, and then cluster sampling was used in each class. Data were collected by using an online survey platform (The following data was collected: age (in years), residence status , gender , grade (freshman/sophomore/junior/senior), monthly disposable funds (in RMB: ≤1000/1001-2000/2001-3000/>3000), and only child (yes/no).The standard Perceived Stress Questionnaire, which has acceptable reliability and validity was used to assess uncertainty stress . It has The BCEs scale , which cThe demographic characteristics of the sample were presented using descriptive statistics by SPSS version 25.0. Next, we performed a network analysis on network estimation and network stability.R program (version 4.1.0) was used to conduct network analysis. Each item is represented as a node in the network analysis layout, and the connection between two nodes is depicted as an edge . CorrelaThe R package “bootnet” (Version 1.4.3) was used to conduct all network stability evaluations . Firstlyn = 1830). The mean age was 20.1 years (SD = 1.2), 56.6% of the sample were from urban areas. The sample consisted of 30.5% males, 45.4% of them were sophomores, and approximately four-fifths (79.1%) had monthly disposable funds between 1001 and 2000 Yuan. The mean of BCEs total scores was 18.7 (SD = 1.8) and mean of uncertainty stress total scores was 23.2 (SD = 9.0). The specific information of the BCEs scale items and uncertainty stress scale items are shown in The network structure of BCEs and uncertainty stress among Chinese university students was shown in In terms of strength, the node US.9 (no ways to suit the important changes in life) has the highest node strength in the BCEs-uncertainty stress network among Chinese university students, indicating that the node US.9 (no ways to suit the important changes in life) was the most influential, followed by nodes US.2 , US.10 (feel that there is nothing to do), and US.7 (worry about the future) . On the Concerning the accuracy of the current network, the results of bootstrap 95% CI for edges demonstrate that 95% CIs were narrow, indicating that edges are trustworthy, as shown in The best metric for detecting nodes is bridge strength. In terms of bridge symptoms , BCEs.9 To the best of our knowledge, this is the first exploratory study to use network analysis as a method of examining association between BCEs and uncertainty stress among Chinese university students. Analyses indicated the node US.9 (no ways to suit the important changes in life) was the most influential symptom within the BCEs- uncertainty stress network. Experiences and events disturb a person's established and routinized patterns of behavior, resulting in life changes . UncertaIn this BCEs-uncertainty stress network, the most influential bridge symptom was “having a positive self-concept” (BCEs.9), where “having a positive self-concept” (BCEs.9) showed a high bridge centrality. When the genuine self is lost and an identity crisis arises, psychological difficulties occur, implying that self-concept should be a target of therapies to alleviate psychological disorders . It is cNot only for the university level, BCEs can have lifelong effects on mental health and physical health . BCEs imSeveral limitations should be noted. First, due to the non-experimental, cross-sectional study design, causal relations between symptoms of BCEs and uncertainty stress could not be determined. Second, data were collected based on participants' self-report, and the possibility of recall bias could not be excluded. Third, the sample were only collected from three cities of China, thus the results may not representative of all university students in China. Although these limitations are existed, there is a big strength of this study should be noted. Unlike previous studies that used total scale scores to assess psychological status, the analytical approach in this study emphasized the association between each item within the scale and identified the most influential item between the scales, which is not widely used. Future research could begin with this approach, examining which items of the scale should be given more weight and determining which clinical interventions should be implemented first.The central symptoms of the BCEs-uncertainty stress network should be prioritized as targets in interventions and prevention efforts to reduce uncertainty stress among Chinese university students. Improving university students' positive self-concept is important to alleviate the level of uncertainty stress among Chinese university students.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 Medical Ethics Committee of Xuzhou Medical University. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.WW and CZ conceived the idea for the study. WW, YX, QZ, and CZ obtained the data. YP, WW, and JW cleared up the datasets. YP, WW, JT, NY, YL, and JW performed the data analyses. WW and YP interpreted the results of the data analyses and wrote the manuscript with the participation of other authors. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China [82003484], Natural Science Fund for Colleges and Universities in Jiangsu Province [20KJB330005].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.


For different numbers of epochs, hidden layers, dense layers, and different units in hidden layers, the RSME values measured for 1D CNN, LSTM, GRU and Bi-LSTM models are 1.12, 1.57, 1.69 and 1.54, respectively. The best MAPE value is 1.855, which is found for the LSTM model. Therefore, our findings indicate that LSTM can be used for bin emptiness or fullness prediction for improved planning and management due to its proven resilience and increased forecast accuracy.The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, the municipality is unable to cope with the increase in garbage, and many urban areas are becoming increasingly difficult to manage. The advancement of technology allows researchers to transmit data from municipal bins using smart IoT (Internet of Things) devices. These bin data can contribute to a compelling analysis of waste management instead of depending on the historical dataset. Thus, this study proposes forecasting models comprising of 1D CNN  long short-term memory (LSTM), gated recurrent units (GRU) and bidirectional long short-term memory (Bi-LSTM) for time series prediction of public bins. The execution of the models is evaluated by Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Coefficient determination (R Waste management is one of the greatest concerns anywhere in the world . The ranMunicipal waste generation is noted to be composite and does not have any direct relationship between causes and effects concerning multiple aspects . BroadlyTo overcome the problems and challenges of waste management, researchers are working from different perspectives such as municipal solid waste, organic waste, industry or chemical waste, medical waste and of waste recycling ,15,16,17On the other hand, several researchers reported that various models and hybrid techniques have been used to predict municipal waste used for quantity estimation, segregation and recycling of solid waste . An artiThis paper aims to analyze and forecast future trends in waste generation from the dataset generated by sensors located in smart bins. This study explores the potential deep-learning methods applied to the smart bin dataset to predict waste generation. The key idea behind these deep-learning models is to acquire a trustworthy estimation model so that the waste management authority can rely on the historical data generated from the bins. Specifically, the paper attempts to answer the following research questions: (1) How can deep learning models be used to forecast waste generation for helping decision-makers in waste-collection operations? and (2) What is the best model to forecast future waste generation? In many digital waste administration perspectives, big data analytics can be used to incorporate machine learning and artificial intelligence. Gupta et al.  surveyedFrom an ecological perspective, deep-learning algorithms have been considered by several researchers to estimate waste generation ,29,30,312. Abbasi and El Hanandeh [As summarised in Hanandeh  considerHanandeh , and theHanandeh  have conWaste administration mainly depends on the waste data produced from different bins placed in various places. Hence, the challenge from the managerial perspective is to have the proper vacant schedules, appropriate bin placement and uncertainty prediction. Thus, this paper focuses on four models such as 1D CNN, LSTM, GRU and Bi-LSTM for estimating future waste generation.2 and RMSE performance indices have been measured. Then, considering the advantages and disadvantages in evaluating the performance and comparing between the models, five phases were accomplished by: (1) collecting the data generated from the public bins, (2) investigating and envisioning the data, (3) training the four categories of deep-learning models, (4) testing the models, and (5) mining and comparing the outcomes. To achieve the target of this study, we trained these four models  to forecast the waste generation from public bin data produced by sensors. To evaluate the performance of the models, MAE, MAPE, RFor different applications in various sectors, the deep-learning procedures have shown the significant contributions of development reside in the literature. This section describes the basic principle of four deep learning models that will be used for waste generation prediction using smart bin data, namely 1D CNN, LSTM, GRU and Bi-LSTM.Due to the gradient difficulties in deep neural or recurrent networks, the LSTM architecture was introduced by Hochreiter and Schmidhuber to overcome the problems in training long-term dependencies ,37. The The computing of the LSTM network is the mapping of the input sequence, i.e., In Equations (1)–(3), the activation of the input, output, and forget gates are denoted by GRU is a model that chooses a new kind of hidden unit by utilizing the architecture of the LSTM unit ,39. GRU GRU has exemplified its adequacy in an assortment of applications requiring consecutive or temporal information . The traz in Equation (7), controls both input and forget gates. The forget gate is open and the input gate is closed while the z value is 0. However, the forget gate is closed, and the input gate is open when z is 0. At each step, the previous t signifies the linear exclamation between the current Here, a gate controller, Due to its design, an LSTM network can execute only the forward passes on consecutive information, which eventually implies the unidirectional model of data processing . An instThe bidirectional RNN encompasses two different hidden layers with similar output but in reverse orientation. Following the construction of BiLSTM, the output layer includes the previous and future information. For BiLSTM, the input sequence 2 and RMSE are applied to estimate the performance of the proposed models. Here, Four performance measures such as MAE, MAPE, R to zero .(12)MAERMSE is specified in Equation (13)  as(13)RMAPE is specified in Equation (14)  as(14)M2 is specified in Equation (15) [Rion (15)  as(15)Rhttps://data.gov.au [We have used data obtained from public bins from a particular council located in Wyndham city, Melbourne, Australia. These data were obtained from the data portal: a.gov.au . It contUnderstanding the data trends and behaviors is essential and valuable while dealing with data analysis. Moreover, this observation evaluates the meaningful identification of the fact produced by the data . Figure This section presents the results on the deep-learning models that are trained-tested. Finally, the model performances are evaluated through statistical indices. For sequential forecasting, the 1D CNN, LSTM, GRU and BiLSTM methods are chosen. The waste generation dataset is divided into training samples of 80% consisting of 292 days and a test sample of 73 days. The performance of the deep learning models is calculated by executing MAE and RMSE standard statistical error measurement indices. The total experiment and the simulations are executed in Google-Colab  and encoThe dataset comprises the feature of the bin status (fullness threshold) and timestamp. The unscaled data take longer for the convergence activities. The MinMaxScaler  estimator will fit the training data set in the case of normalizing the training and test data sets, and the same estimator will be utilized to transform both training and test data sets. The shape of the uniqueness of disseminating data is preserved by MinMaxScaler. Furthermore, it also maintains valuable information about outliers and scales the data to a limited range of values. 2 and RMSE. The smallest value of MAE and RMSE is considered the best model. Following the criteria, we found that LSTM is the best compared to the others. The RMSE value for the LSTM model is the lowest. Therefore, LSTM is more efficient at forecasting long-term dependencies in comparison to 1D CNN, GRU and BiLSTM. For all the four models, the optimizer is Adam, batch size is 70 and epochs are 20. It is worth mentioning here that all the aforementioned parameters are modified through trial and error. The next step is to calculate the train and test error calculation for the 1D CNN, LSTM, GRU and BiLSTM models. The error values are illustrated in 2 of the LSTM model are the lowest with the values 1.579 and 0.925, respectively. Therefore, LSTM is more capable of forecasting waste generation trends than 1D CNN, GRU and BiLSTM are, with a very low variance between others. The visual description of the predicted and actual outcomes of the training dataset for four models is illustrated in The correctness of the models is tabulated in 2) of 0.90. Chhay et al. [2 are 228.53, 0.0143, 450.84, and 0.931, respectively. Abbasi and El Hanandeh [2 (0.99–0.83), MAE (0.001–335.03), RMSE (0.002–498.43), and MAPE (3.39 × 10−6–0.07). Lin et al. [The proposed models in this paper can be considered reliable and acceptable for waste estimation. y et al.  have conHanandeh  considerWaste generation is predicted by different seasonal periods such as daily, weekly, monthly or yearly, and a few researchers have used the gross or total amount of waste data produced by the bins as a whole for a particular region ,30,33,34In this study, deep learning methods can be observed to have a noteworthy impact on technological advances, particularly in creating diverse time-series-based forecast models. This study aims to examine the predictive models while applying the data coming from endpoints such as sensors, rather than using the human-made historical dataset. The predictive analysis for waste generation revealed different behavior originating from different sources located within a council. 2 0.925 and RMSE 1.579. In addition, 1D CNN, LSTM, GRU and BiLSTM have shown robustness and much-enhanced forecasting when assessed with actual numbers representing less estimate errors. The changes in the waste generation period have various significant values that could interrupt the waste collection, transportation and disposal process. Therefore, detailed knowledge of these changes revealed from the deep-learning method could immensely help waste management authorities during emergencies or for estimating a proper vacant schedule to ensure a better sustainable environment for the citizens and local council. The deep learning models are used for waste generation analysis using the dataset produced from the sensors located in the bin. For practical implications, these deep learning models can be modified and adopted by waste management authorities to acquire a reliable waste analytic system while relying on the data produced from the bins. Waste generation forecasting is the primary stage for waste management and waste disposal processes. The study has applied four types of deep-learning algorithms such as 1D CNN, LSTM, GRU and BiLSTM for predicting waste generation. To test the effectiveness of the four models, performance measure metrics are calculated. The result reveals that LSTM outperformed the other models with an MAE of 0.602, MAPE 1.855, RIn future work, we will be exploring different factors such as organizational, socioeconomic factors and public utility investment that might have an impact on waste generation. Another study can also be done to identify the influential factors through the in-depth study intervention for the development of a more optimized and cost-efficient waste management system.


To evaluate the efficacy and safety of extracorporeal shockwave therapy (ESWT) for postherpetic neuralgia.Randomized single-blind clinical study.Patients with postherpetic neuralgia.Patients were randomly divided into the control group and the ESWT group. The control group received conventional treatment while the ESWT group received conventional treatment and ESWT. The primary outcome is pain degree as assessed by the numeric rating scale (NRS), and secondary outcomes include brief pain inventory (BPI), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Pittsburgh Sleep Quality Index (PSQI). Data were collected at baseline and at weeks 1, 4, and 12. Linear mixed-effects models were applied to repeated measurement data.The scores on the NRS, BPI, SAS, SDS, and PSQI decreased over time in both groups. The NRS and SDS scores of the ESWT group were statistically lower than the control group. There was no time × group interaction in the mixed model analysis. Baseline age was correlated with NRS scores and BPI scores, and invasive treatment was related to PSQI scores, with no interaction effect for baseline confounders observed. No adverse events were observed during the process of this trial.Extracorporeal shockwave therapy combined with conventional treatment could relieve pain and improve the psychological state in patients with postherpetic neuralgia without serious adverse effects. Postherpetic neuralgia (PHN) is defined as persistent pain lasting more than 3 months after the onset of shingles , which iA shockwave is a type of transient pressure fluctuation generated by electromagnetic, electrohydraulic, or piezoelectric devices . As an eChiCTR.org.cn . The initial version of the protocol was published  and registered at ublished . ConsoliPatients were recruited from September 2019 to September 2020 in the pain department of West China Hospital. After being informed of the procedures and possible complications of the study, they decided whether to participate in this study. Then, more detailed information was collected to assess the eligibility. The inclusion criteria included adults diagnosed with PHN according to the Consensus of Chinese experts on PHN ; had an After signing the informed consent, the participants were allocated into the control group or the ESWT group (1:1). In this process, a researcher was in charge of preparing the sealed opaque envelopes, which contained random numbers generated by EXCEL table. Another researcher was responsible for assigning the envelope to participants randomly, and then a shockwave therapist decided whether to perform shockwave therapy according to the random numbers in envelopes. The assessors and statisticians were blinded to randomization and did not participate in the treatment.The control group received conventional treatment, such as medication and invasive interventional therapy, while the ESWT group received conventional treatment and extracorporeal shockwave therapy. Conventional treatment remained stable during the study period in patients receiving ESWT. The detailed therapeutic schedule is shown in Extracorporeal shockwave therapy was performed by a skilled therapist with a radial extracorporeal shockwave generator . As shown in T-test, while data that did not conform with normal distribution were presented as median (the upper and lower quartiles) and analyzed by the Mann–Whitney U-test. Categorical data were presented as frequency (percentage) and compared by the χ2 test. In the analysis of repeated measurement data, intention-to-treat (ITT) analysis was conducted with the missing data replaced by using the last observation carried forward (LOCF) imputation method. Linear mixed-effects models were applied to longitudinal data, and restricted maximum likelihood (REML) with an unstructured covariance matrix was used. In the 2 groups (ESWT vs. control), 4 time points , and the time × group interaction were considered as fixed effects, while baseline confounders, such as age, sex, body mass index (BMI), invasive treatment, and PHN nerve segments as covariates. IBM SPSS Statistics 26 was used for statistical analysis. All tests were two-sided, with p < 0.05 indicating statistical significance.The sample size was estimated with the superiority test (α = 0.05 and β = 0.2). According to a previous study , we calcIn this study, 109 patients were recruited and assessed for eligibility and a total of 100 patients were included. After being randomized in a 1:1 ratio to the two groups, they received their allocated treatment. At week 1, 4 patients were lost to follow-up, 15 patients were lost to follow-up at week 4, and 31 patients were lost to follow-up at week 12. Finally, 69 patients finished 12-week follow-up. The data of all participates were included in the ITT analysis .There were no significant differences between the ESWT group and the control group in age, gender, body mass index (BMI), PHN localization, PHN duration, medication therapy, and invasive therapy, suggesting that the baselines were comparable .p < 0.001) with lower BMI (p = 0.026) than patients who finished follow-up, while there was no significant difference in sex, PHN nerve segments, PHN duration, medication therapy, invasive therapy, and per capital invasive therapy course  and BMI (p = 0.031) between the two groups. In 69 patients who finished 12-week follow-up, there were no significant difference in demographic and baseline characteristics between the ESWT group and the control group , then the model was refitted without the time × group interaction term (p = 0.027) and time (p < 0.001). The NRS scores decreased over time, and the NRS scores of the ESWT group were statistically lower than the control group.The scores and trends of baseline and post-treatment NRS scores are shown in ion term . The finThe scores and trends of baseline and post-treatment BPI, SAS, SDS, and PSQI scores are shown in p > 0.05). After readjusting the model without the time × group interaction term, the final model showed that SDS scores were statistically associated with group (p = 0.003) and the BPI, SAS, SDS, and PSQI scores were statistically associated with time  years in the ESWT group and 67.4 (11.2) years in the control group. Similarly, a previous study suggested that the risk of PHN rose sharply between 50 and 79 years . AdvanceThe reason for patients' being lost to follow-up was that nobody answered the phone. The demographic and baseline characteristics of lost patients indicated that they were significantly older (73.61 years) than patients who finished follow-up (64.94 years). Patients who did not answer the phone might be related to the low smartphone adoption and unskilled use of smartphone in Chinese elderly people .Considering that pain is an emotional experience and sense is the gold standard of pain , the resInteraction effects for baseline confounders, such as age, sex, BMI, invasive treatment, and PHN nerve segments were explored in this study, and no interaction effect for baseline confounders was observed. PHN duration was not added into this analysis because of some outliers. The result indicated that the age was correlated with the NRS and BPI scores. Hyperalgesia is more common in elderly population, as well as prolonged pain development and less effective medication, which might influence the quality of life . FurtherIn a systematic review, 20.7% of patients developed transient pain, swelling, petechiae, and other side effect after ESWT , which wThere are some limitations. Further studies with objective measurement and therapeutic mechanism are needed. Furthermore, a high proportion (31%) of patients were lost to follow-up, which could introduce potential bias. Some old patients had difficulty in telephone use and were lost to follow-up. Optimizing follow-up protocol and extending follow-up may be necessary in the future. In addition, the single-blind method may have the risk of bias. More double-blind and multicenter studies would be needed to confirm the result.In conclusion, ESWT combined with conventional treatment could relieve pain and improve the psychological state of patients with PHN without serious adverse effects. Further randomized clinical studies are needed to confirm these results, so that ESWT could be used as a safe and effective complementary treatment for PHN.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 West China Hospital, Sichuan University, Chengdu, China . The patients/participants provided their written informed consent to participate in this study.LC designed this randomized controlled trial, collected the data, and wrote the article. PY and LY performed the statistical analysis, revised the manuscript, and provided final approval to the version of the study. AQ performed treatment in this study. TZ revised the manuscript and gave final approval to the version of the study. All authors discussed the results and commented on the manuscript.This study is supported by grant 2019HXFH069 from the 1·3·5 project for disciplines of excellence—Clinical Research Incubation Project, West China Hospital, Sichuan University, the grant 2018JY0105 from the Science and Technology Department of Sichuan Province, CYTD17-05 Innovation grant of the Chengdu Medical College and CYFY-GQ01 Startup foundation for Distinguished Scholars of the First Affiliated Hospital of Chengdu Medical College, and 1·3·5 project for disciplines of excellence (ZYJC21008), West China Hospital, Sichuan University (to TZ). These projects will not participate in any aspect of the trial, including design, data collection, analysis, or interpretation.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.


The intrahypothalamic phenotype of hypothalamic hamartomas (HH) is associated with epilepsy, and the parahypothalamic phenotype usually leads to central precocious puberty but not neurological comorbidities or seizures. No study has confirmed the pathological role of parahypothalamic hamartomas in epileptogenesis, and the underlying mechanism is yet to be elucidated.We aimed to investigate whether parahypothalamic hamartomas are intrinsically epileptogenic and elucidate the underlying pathway of epileptogenesis.We reviewed 92 patients with HH-related epilepsy, categorized them by the classification system of Delalande and Fohlen, and further classified Type I  into the following three groups based on the relationship between the lesion and mammillary bodies (MB): entirely invaded (Group 1), partially connected (Group 2), and not connected at all (Group 3). We examined different anatomical features with their relationship to clinical manifestations. Stereoelectroencephalography (SEEG) was implanted in both HH and extra-HH cortices in different groups to identify the epileptogenic zone. Corticocortical evoked potentials (CCEPs) were also used to determine the pathological correlation among different regions to determine the related epileptogenic network.p = 0.213), and lesions horizontally oriented from the tuber cinereum without connection to MB were not involved in seizure genesis. CCEP indicated a pathological connection among HH, middle cingulate cortex, and insular cortex.A total of 13 patients presented with parahypothalamic HH and 10 (76.9%) presented with non-GS only, with late-onset age and normal cognitive development, which is different from classical clinical features. SEEG showed that HH is intrinsically epileptogenic in MB-involved parahypothalamic groups. No statistical difference was found in onset age (The parahypothalamic HH can also cause epilepsy and is different from classic HH-related seizures, by non-GS only with the late-onset age and normal cognitive development. MB is proven to be related to non-GS by the mamillo-cingulate-cortex pathway. Hypothalamic hamartomas (HH) are rare, and neurodevelopmental lesions formed from heterotopic neurons and glia within and around the hypothalamus. They arise from the floor of the third ventricle, tuber cinereum (TC), or mammillary bodies (MB) . The claIn this study, we characterized many patients with parahypothalamic HH with epilepsy, from a clinical, anatomic, and electrophysiological point of view and tried to interpret the results with the present knowledge of the epilepsy manifestation and the relationship with anatomical features to elucidate the underlying mechanism of seizure genesis in parahypothalamic cases.http://people.cas.sc.edu/rorden/mricron/index.html) and superimposed on the 3D T1 images with spectrum set at 60–80% transparency , T2 axial and coronal sequences of 3-mm thickness, and FLAIR axial, coronal, sagittal sequences of 3-mm thickness, which allowed the visualization in sagittal and coronal planes to better characterize the connection of the hamartoma to the hypothalamus. Interictal [18F] fluorodeoxyglucose (FDG)-PET was also performed and co-registered to the corresponding 3D T1 images using SPM12  and magnetic resonance-guided laser interstitial thermal therapy (MRgLITT).To determine the role of HH in seizure genesis and/or to guide stereotactic ablation, stereoelectroencephalography (SEEG) was designed as per the two strategies:1 Strategy A: Less than five electrodes were implanted only within the target of HH, mainly for SEEG-guided RFTC by the same recording electrodes. This strategy was applied to the HH cases with a typical history of GS, and the size of the lesion was deemed suitable for RFTC .2 Strategy B: More than five electrodes were implanted in HH and different extra-HH cortical regions to confirm whether HH was the epileptogenic zone (EZ). Criteria for this strategy mainly involved the following 2 situations:a Patients who suffered from epilepsy with a HH presentation on neuroimages, but with no history of GS.b Patients with a typical history of GS but non-GS were not meaningfully controlled after HH-aiming surgeries.For all patients, the primary target was the HH, and SEEG electrodes or laser probes were planned to cover the attachment as much as possible in order to make a complete disconnection during ablation. For Strategy B, extra-HH electrode positioning was established in each patient based on the hypotheses about the localization of the EZ according to semiology, scalp EEG, and neuroimaging results.Long-term recordings were acquired using intracerebral multiple contact electrodes . The signals were recorded on the NIHON KOHDEN video-EEG monitoring system, sampling at 1,000 or 2,000 Hz to capture several seizures in each patient who underwent SEEG. All seizure episodes recorded by SEEG were visually reviewed by two reviewers and then discussed with a senior neurophysiologist.For cases with SEEG implantation of Strategy B, direct electrical stimulation was performed with a pulse duration of 300 ms and an intensity of 1–5 mA. In addition, cortico-cortical evoked potentials (CCEP) were also performed. The methodology has been described in detail in a previous study .via telephone. The seizure outcomes were established according to Engel's outcome classification system, and Engel class 1A was considered to be seizure-free after the surgery.The postoperative outcomes were determined by a clinic visit or t-test was applied to test the differences among the groups. Statistical tests were performed with the software Statistical Package for the Social Sciences (SPSS) for Windows (version 26). p < 0.05 was considered to indicate statistical significance.The demographic features were analyzed. The age at epilepsy onset was described as mean, range, and/or standard deviation. An independent sample We reviewed a total of 92 epileptic patients with HHs (63 men and 29 women), and the mean age of the patients was 10.5 ±9.1 years (range: 1.8–46 years). A total of 13 patients fulfilled the criterion of Type I  and were categorized by the modified classification that was previously mentioned . Among tIn Group 1 (MB entirely invaded), the hypothalamic connection was established only on one side of the subventricular floor by a sessile attachment, and the contralateral MB was preserved. In this group, five patients fulfilled the anatomical criterion, the mean age at seizure onset was 6.2 ± 3.9 years (range 1–11), and the mean duration of epilepsy before the surgical evaluation was 2.1 ± 1.7 years (range 0.5–5). A total of three patients presented with NGS, which included tonic seizure, FIAS, and FBTCS. A total of four patients were treated with HH-aiming ablation , and all of them received seizure freedom with a mean follow-up of 18 months (range: 11–37 months). Patient 8 was implanted with an SEEG plan, and his GS vanished after HH-resection, but FBTCS relapsed. SEEG confirmed that HH was EZ. After LITT, his seizure was present with less frequency till 3 months, which could probably be explained by the “running down” phenomenon .In Group 2 , HH adhered to both TC and MB outside the third ventricle. In this way, the lesion was bilaterally connected to MB by its caudal part. Therefore, we observed narrow attachments on both sides of the coronal plane. One epileptic-side attachment and interictal discharges and the laterality of hypometabolism were consistent with it. A total of five patients fulfilled the anatomical criterion, the median age at seizure onset was 9.6 ± 4.0 years (range: 5–16), and the mean duration of epilepsy before the surgical evaluation was 5.8 ± 2.9 years (range: 2–10 years). A total of four patients were NGS, and only one patient had a history of GS. However, unlike the classic clinical course, Patient 4 started GS at the age of 5 years, and tonic seizures started at the same time. All these patients underwent SEEG, and two of them were planted with extra-HH regions. One patient did not record the habitual seizures after SEEG monitoring; therefore, subsequent surgery was not considered. The other patient proved HH as EZ and underwent HH-ablation with the other three patients. All four cases received seizure freedom, and the only GS patient (Pt 4) experienced a running-down period of 6 months.In Group 3 , HH was horizontally oriented from TC. Therefore, the lesion adhered to the subventricular floor only by a pedunculated attachment, thereby being suspended and sparing the MB. A total of three patients fulfilled the anatomical criterion, and all of them never suffered from GS, with a very late seizure onset age , and showed normal cognitive and physiological development. The mean duration of epilepsy before the surgical evaluation was 5.7 years (range: 1–15). Patient 1 underwent a previous surgery of standard anterior temporal lobectomy for both the seizure and semiology. The results of EEG monitoring showed that the right temporal region was the epileptogenic focus . HoweverThe following three categories of lesions are established for the anatomic configuration of the parahypothalamic HH:(1) Lesions are horizontally oriented from TC without being connected to MB. They are presented with NGS and are not involved in seizure genesis.(2) Lesions are simultaneously connected to MB and TC. They always show bilateral attachments to MB with one side being epileptic. HH is the epileptogenic zone, and most patients (80%) presented NGS with a good outcome after HH-aiming ablation.(3) Lesions that adhere to one side of the subventricular floor showed a sessile attachment to the hypothalamus, with a higher rate of GS compared with Group 2. HH is the EZ, and 60% of the patients presented NGS with a good outcome after HH-aiming ablation.p = 0.213).Interictal epileptiform discharges were generally present in the anterior quadrants with spikes localizing over the frontal and/or temporal regions. The ictal EEG can show diffused attenuation without a clear onset zone. Similarly, PET-CT results showed asymmetric cerebral hypometabolism over frontal, temporal, or even parietal lobes. Both of them were usually concordant with the side of attachment of unilateral HH or greater attachment in asymmetric HH. The detailed features of the patients are presented in Stimulation of different regions of gray matter can produce different CCEPs under normal baseline conditions, which requires consideration of the baseline response while determining the effects of epilepsy . A totalTo the best of our knowledge, no study has elucidated the pathogenetic role underlying HH in patients with epilepsy without GS. In this study, we proved that parahypothalamic HH can also cause epilepsy by SEEG, and this type of epilepsy is very different from classic HH-related seizures. NGS is in most cases with a very late-onset age and normal cognition. MB is speculated to be related to non-GS in patients with HH by the MB-cingulate-cortex pathway.Hypothalamic hamartomas are developmental malformations that involve the small hypothalamic area located between the infundibular stalk and MB. Pedunculate hamartomas are characterized by adhering to the inferior surface of the hypothalamus, often with a thin stalk that arises from the region of TC and MB (corresponding to Groups 2 and 3), whereas sessile hamartomas are characterized by broad-based attachment to the hypothalamus , 21. TheHypothalamic hamartomas have strong anatomical–clinical correlations in the clinical presentation, and each phenotype is associated with a typical clinical spectrum , 11. DifAll these results from previous studies and our cohort suggest that parahypothalamic hamartomas play a very specific role in the pathophysiology of seizure genesis. Different epileptogenic networks based on related anatomic features and pathways should be concerned as a reasonable explanation. An agreement exists that hamartomas associated with epilepsy have a sessile displacing attachment to the hypothalamus, whereas those associated with precocious puberty alone are pedunculated, which implied barely distortion within the third ventricle . As a reCompared with intrahypothalamic HH, parahypothalamic HH has very different anatomical features. The vertical plane of the third ventricle included lateral hypothalamic nuclei and fornix, and other important tracts were rarely affected. In this way, the structures from the horizontal plane of the third ventricle can be better investigated, including MB, TC, and infundibulum. Since the infundibulum was thought to be associated with the clinical manifestation of PP , 21, MB via MB showing late onset age and multiple seizure types, similar to secondary epileptic progression in patients with typical GS. HH seizures usually occur in <1 year in the case of GS and between the ages of 2 and 7 years in the case of additional focal seizure types , and minor(s)' legal guardian/next of kin, for the publication of any potentially identifiable images or data included in this article.CL: acquisition of data, statistical analysis, and drafting of the manuscript. WH, CZ, XW, and XS: acquisition and interpretation of data and revising the manuscript for intellectual content. ZZ, XY, and ZG: acquisition and analysis of data. JM: interpretation of data and statistical analysis. KZ: study design, study supervision, and final revision of the manuscript for intellectual content. All authors contributed to the article and approved the submitted version.This project was supported by the Capital's Funds for Health Improvement and Research (2022-1-1071 and 2020-2-1076), the National Natural Science Foundation of China (82071457), and the National Key R&D Program of China (2021YFC2401201).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.


Through the analysis of tissue microarray (TMA) samples from colorectal cancer (CRC) patients and bioinformatical analyses of public databases and our clinical dataset, this study identifies the different expressions of CD163 in various tissues, the presence of the receptor in TME, the interaction with other biological processes and a positive correlation between CD163 dysfunction and worse prognosis. Therefore, CD163 can be used as a new biomarker to predict patient prognosis. p-value < 0.05). Through tumor microenvironment (TME) analysis, we found a potential influence of CD163 on immune cell infiltration. Furthermore, the enrichment analysis indicated the possible interaction with other proteins and biological pathways. (4) Conclusions: CD163 is expressed differently in CRC tissue and is a negative prognostic factor. Its expression is associated with the TME and tumor purity of CRC. Considering all results, CD163 has the potential to be a predictive biomarker in the investigation of CRC. (1) Background: CD163, a specific macrophage receptor, affects the progression of malignant tumors. Unfortunately, the regulation and expression of CD163 are poorly understood. In this study, we determined the expressions of CD163 in TMA samples from CRC patients and combined them with patient data from several Swedish hospitals. (2) Methods: The expressions of CD163 in tissue samples from CRC patients were examined. After combining 472 CRC patients’ gene expression and 438 CRC patients’ clinical data with the TCGA database, 964 cases from the GEO database, and experimental expression data from 1247 Swedish CRC patients, we selected four genes  and analyzed the tumor-infiltrating immune cells (TICs) and CRC prognosis. (3) Results: Based on histopathological TMA analysis, CD163 was strongly expressed in the stroma of both normal and cancer tissues, and the expressions in normal and cancer cells varied from negative to strong. The results from public databases show decreased expression of CD163 in cancer tissue compared to normal mucosa (|log FC| > 1 and FDR < 0.01), and it is a negative prognostic factor for CRC patients ( Colorectal cancer (CRC) is the second most common malignant tumor in women and the third most common in men. Approximately 900,000 deaths are attributed to this cancer each year, making it the cancer with the fourth highest mortality. Therefore, CRC is an important public health problem ,2. AccorResearch has recently shown that the tumor microenvironment (TME) plays a vital role in tumor development, including initiation, chronic inflammation, tumor progression, and therapy response. The TME contains tumor-adjacent stromal cells and surrounding immune cells. Among the stromal cells, macrophages have an important influence on tumor progression and affect tumor properties known to be important targets of cancer therapy . CD163 is commonly regarded as the receptor of hemoglobin transmembrane scavenger, a specific protein in macrophages, and its expression and gene polymorphism are representatively changed in inflammation  and otheProgrammed cell death ligand 1 (PD-L1) has been regarded as an efficient biomarker to predict the response to immunotherapy. It can be expressed on the surface of tumor cells and inflammatory cells, and after binding with T cells, activated T cells can be suppressed and inactivated . Anti-PDThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) are two of the major global clinical gene databases. They contain large amounts of information on different types of cancer, such as demographic information, high-throughput gene expression, and DNA polymorphism. By data mining, we can analyze the relationships among the clinical treatments, the regulation of gene expression, the mutation of genes, and the occurrence and development of a specific cancer .To examine the role of CD163 in CRC development, patient survival as well as its relationships with other biomarkers in the present study, we examined CD163 expression in normal and cancer tissues from Swedish CRC patients and further analyzed the relationship between CD163 expression and patient outcomes, including survival. Using different methods of bioinformatics, including gene expression difference analysis, survival analysis, gene set enrichment analysis, and tumor-infiltrating immune cell analysis, and combined with histopathological observation, we discovered the diversity between tumor and normal tissues, the relationship between the expression and mutation of CD163, and its effects on the prognosis of CRC patients. CD163 can therefore be considered a novel biomarker for prognosis, disease progression monitoring, and treatment response.This study included 1247 primary CRC patients from several hospitals in Sweden between 1972 and 2014. The clinicopathological data included sex, age, tumor location, TNM stage, differentiation, growth pattern, treatment, survival, and other detailed information. Normal and cancer tissues were used for the experiments to examine the polymorphism and expression of numerous proteins.IHC for CD163 was performed using 4 μm tissue sections, including normal mucosa, primary tumor, and metastasis in the lymph nodes from paraffin-embedded specimens. The specimens were deparaffinized in Aqua de Par 10 Ancillary reagent  for 20 min after being kept at 65 °C for 2 h. All sections were then placed into a pressure cooker Decloaking Chamber NexGen configured in a temperature cycle to achieve a maximum of 110 °C for 5 min to perform heat-induced epitope retrieval using Borg Decloaker RTU antigen retrieval solution (BD1000). The slides were then rinsed in tap water before being washed in tris-buffered saline (TBS). Primary antibody against human CD163 (10D6), abcam, Waltham, MA, USA) was fully automated on Leica Bond3 at 1:100 dilution for 15 min; post-primary for 8 min, polymer for 8 min, peroxide for 5 min, DAB chromogen for 10 min, and counterstain HTX for 5 min. The intensity of the brown color was scored by two pathologists separately using -, +, ++, and +++ scores, corresponding to negative, slight, moderate, and strong expressions. In the GDC database of TCGA (download date: 24 May 2022), we selected adenoma and adenocarcinoma samples in the colon and rectum (TCGA-COAD and TCGA-READ) to obtain gene expressions (FPKM), simple nucleotide variations (SNPs) and clinical data. In this study, we downloaded 472 cases of gene expression data , and the number of files was 530, including 488 cancer samples and 42 samples adjacent to cancer.Stemming from the GEO database, as shown in p-value and control the false positive rate, and the constraint of this study was |logFC| > 1 and FDR < 0.01. Finally, we made a volcano plot with all differentially expressed genes to give an overview of the difference distribution and intersected the 3177 DEGs with 55 genes from the Swedish clinical database to obtain the intersectional genes for subsequent research. Afterwards, we continued the difference analysis on the expression of the selected genes with gene expression data from 5 GEO databases  to validate the results.We performed difference analysis on the FPKM data of colorectal cancer in TCGA. We searched the differentially expressed genes (DEGs) between the tumor tissues and normal tissues with the Wilcoxon rank-sum test using R . First, Cox regression is a semi-parametric analysis method that assumes that each risk factor’s role does not change with time ,29,30. Ip-value. The survival curve of CD163 was drawn by using the survminer package in R.With the CD163 expression data and clinical features from Swedish hospitals, we analyzed the relationship between high or low CD163 expression and the 5-year survival rate by performing Kaplan–Meier survival analysis. According to the principle of the Kaplan–Meier method , samplesp-value < 0.01). The ten highest related biological processes were drawn by the enrichplot package in R. After that, we used the GSVA algorithm to evaluate the score of hallmark gene sets. Wilcox’s rank test was utilized to assess the significance.GSEA is an analysis method used to obtain an enrichment score by calculating the correlation between phenotype and each molecular mechanism . A totalThen, according to the Pearson correlation coefficient for CD163 and 13163 other genes in TCGA, 228 genes were selected as the co-expression with CD163 (|Pearson coefficient| > 0.6). A protein–protein interaction (PPI) network was constructed for these co-expression genes related to CD163 using the STRING database , with a To further explore the correlation of CD163 expression with the immune microenvironment, we applied GSVA analysis and CIBERSORT computational methods  to evaluThe workflow of our research process is described in As shown in According to the screening conditions in this study (|logFC| > 1 and FDR < 0.01), we obtained 3177 DEGs, of which 1942 were up-regulated genes and 1235 were down-regulated genes in CRC. Using a volcano map of all DEGs a and crop-value = 0.02) had statistical significance, and for GSE39582, there were three genes: CD163, LOX, and BCL2, with statistical meaning. According to This study used R to perform the univariate Cox analysis based on gene expression data. We calculated and presented each gene’s hazard ratio and 95% confidence interval a,b. The p < 0. 05. For the normal groups, there was no statistically significant difference (Log-rank p > 0.05) between the low and high expression groups, but the trend had a pattern similar to that in the tissue groups, which indicates that a low expression was related to better prognosis.The CD163 expression data were divided into four groups: tumor tissue with high or low cellular expression, normal tissue with different cellular expression, tumor tissue with high/low expression in the stroma, and normal tissue with different stroma expressions. The data were generally either derived from inside cells or from the adjacent stroma. The results are shown in As per all RNA-seq samples in the TCGA database, infiltration progression was estimated and visualized by heatmap using ssGSEA evaluation a, reflecAs shown in In this study, we analyzed the expressions of CD163 and other genes in CRC and evaluated their relationships to clinical outcomes in CRC patients. After analyzing data from public databases using gene expressional difference analysis, we found that CD163 expression in CRC was lower compared to normal tissue. Up-regulated CD163 expression seemed to be a negative prognostic factor for CRC based on the Cox analysis, which was also confirmed by survival analysis based on clinical CD163 expression data. Enrichment analysis and protein–protein interactions networks showed that CD163 was related to several molecular functions and hallmark pathways. Thus, based on these findings, we propose that CD163 could be regarded as a biomarker for tumor progression and clinical outcomes in CRC, where a low expression may be seen in the early stages of development, and high expression may suggest invasion, metastasis, and a low survival rate. In accordance with this study, our previous studies on CD163 have also shown positive expression in approximately 20% of CRC patients and its relationship to early local recurrence, short survival time, decreased apoptotic activity , and adv+ TAM cells and the tumor cells and the density of CD163+ TAM cells could be considered independent predictive indicators for the prognosis of cancer. A higher density of CD163+ TAM cells and a shorter distance could be regarded as a clinical and pathological risk factor for breast cancer. Another study by Krijgsman et al. [+ TAMs are also known to be associated with epithelial–mesenchymal transition (EMT), the mesenchymal circulating tumor cell ratio, and a poor prognosis of CRC [+ TAM [The TME has a vital influence on tumor progression and prognosis. TAM is one important component of the TME and plays a crucial role in the infiltration, invasion, and metastasis of tumors. Therefore, specific biomarkers on TAM, such as CD163, can be highly clinically relevant to evaluate the response to the treatment of cancer . Accordin et al.  showed tn et al. . Followin et al. ,46,47,48n et al. . Therefon et al. . Meanwhis of CRC , in accos of CRC . HoweverC [+ TAM  might haCompared to previous findings, our study is the first to combine data from several huge public databases with experimental data to study the possible function and effects of CD163, focusing on TME and TILs in CRC patients. Previous studies have performed their analyses on CD163 related to the number, distribution, and phenotype comparing tumor and normal tissue/patients. We have deepened the understanding of the influence of CD163 on CRC prognosis and also the possible effects on 22 types of lymphocytes, tumor purity, immune check-points such as PD-L1, and the potential involvement of CD163 in different CRC-relevant cancer hallmark pathways and biological processes. Limitations in this study mainly revolve around the raw data from the hospitals. Certain gene expression data were not able to be retrieved, which may influence the accuracy, precision, and power of the statistical analyses. Reasons for the lack of certain gene data might be due to poor follow-up, old experimental methods, or outdated information systems. In our study, although the overall number of cancer cases was enough to obtain good-quality results, more data and cases about CD163 are still needed because of unequal distribution after grouping based on age and sex, which may explain the lack of differences in the survival analysis. This study showcases the function and multiple relationships of CD163 in CRC to further define the value of CD163 as a potential biomarker in the prognostic prediction and assessment of CRC. We analyzed CD163 from three dimensions: genomics, histopathology, and epidemiology, which increases its relevance to real disease. Studies on the downstream and upstream regulators of CD163 and comprehensive mechanical mapping of CD163 are needed.In this study, we examined CD163 expression in normal and cancer tissues using multiple cohorts of patients and investigated how the dysregulation of CD163 was associated with tumor TME and TICs, as well as patient prognosis at the level of transcriptome and proteome. Based on these findings, we propose that CD163 could be used as a biomarker for evaluating CRC development and determining the prognosis of patients. The results may even provide data needed for further research on developing valuable CRC surveillance programs and designing efficient therapies for patients.


Achilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors  and the risk of AT.Univariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT.P=2.0×10-3), and the odds ratios  is 1.44 (1.14−1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI.Univariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (The causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden. The Achilles tendon is the largest, most powerful tendon of the human body, which connects muscles, including gastrocnemius and soleus, to the heel bone . It playMendelian randomization (MR) can infer causality between exposure and disease outcomes by using genetic variants as instrumental variables . GeneticIn this study, univariable MR was performed to screen for potential causal association among ten putative risk factors  and AT. The causal effect of AT on BMI was studied using bidirectional MR. Multivariable MR was conducted to investigate the BMI-independent effect of other obesity-related traits, such as waist-hip ratio (WHR), on AT. To our knowledge, this is the first MR study to systematically infer the causality between clinical risk factors and AT.MR uses genetic variation, mostly single nucleotide polymorphisms (SNPs), as instrumental variables (IVs) to investigate the causality between traits and diseases. Valid instrumental variables need to fulfill three assumptions : (1) IVsP<5×10–8) were extracted from the GWAS datasets from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and/or the UK Biobank (UKB)  were used.The SNPs for anthropometric measurements including BMI, waist circumference (WC), hip circumference (HC), WHR, whole-body fat mass (WBFM), whole-body fat-free mass (WBFFM), and whole-body fat percentage (WBF%) that reached a genome-wide significance level (nk (UKB) , 16. Theescribed . The Axiescribed , 19. Forescribed , whereasescribed , 22. Theescribed . Geneticescribed , 25. IVsescribed , 26. Genescribed , 28. Theescribed , and allescribed . If the P<1× 10-5 because no SNP reached a genome-wide significant association with AT (P<5×10–8). This strategy of relaxing the threshold has been employed in MR studies  method, MR-Egger method, weighted median method, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO). In the IVW method, the Wald ratio for each of the IVs will be meta-analysed to examine the causal association. The IVW method assumes that all included genetic variants are effective instrumental variables, which is different from the MR-Egger method, which remains functional if all IVs are invalid. Moreover, MR-Egger uses an intercept term to examine potential pleiotropy. The weighted median method is intermediate and requires that the valid variable must be at least 50%. MR-PRESSO can detect and exclude potential outliers in MR analyses, providing results with a pleiotropy correction. Heterogeneity was examined using the Cochrane Q value. The effect of each included IV on the causal association was addressed by the leave-one-out method, which removed each SNP individually and analyzes the estimate of the remaining SNPs by using IVW methods. Scatter plots were generated to visualize the MR results. Power estimation was performed using an online tool . In the  studies , 33. Mul studies , Mendeli studies , and MR- studies .P<5.0×10-3), and the OR (95% CIs) was 1.44 (1.14-1.81) for AT per 1-SD increase in BMI (P=0.15) (P=0.62) in the causality analysis between BMI and AT  were selected as IVs for AT in the bidirectional MR. A significant level of heterogeneity was detected in the analyses (Twelve SNPs associated with AT at a relaxed threshold (P=0.01) (Pthreshold=0.05/6). Because obesity-related traits are highly related to BMI, we also performed multivariable MR analysis, and the results indicated that none of these traits were causally associated with the risk of AT after adjusting for BMI  Figure 3In this study, we tested the potential causal association between ten putative AT risk factors and the risk of AT by using a two-sample MR design and identified the causality between high BMI and increased risk of AT. Bidirectional MR revealed that an elevated risk of AT was not causally associated with increased BMI. Furthermore, multivariable MR analysis indicated that other anthropometric parameters, such as WHR, were not likely to be associated with the risk of AT.Obesity is a global epidemic, and our results suggest that weight control is effective and necessary for the prevention and control of AT. Compared with intrinsic factors such as age and sex, overweight and obesity are more easily to control and therefore can serve as promising targets for AT if they casually lead to an increased risk of AT development and/or progression. However, conventional epidemiological studies have presented inconclusive evidence of an association between BMI and AT risk . One stuTendons are mechanically sensitive tissues that respond to mechanical loads of varying magnitudes, frequencies, and durations . HoweverIn addition to obesity, epidemiological evidence suggests the presence of other potential clinical risk factors for AT. For example, an elevated risk of AT has been found in the United States military personnel with moderate alcohol use . Acute rThis study has several strengths. First, the MR design reduced biases introduced by residual confounding and reverse causality, which may lead to false-positive results in conventional observational studies. Second, the two-sample MR analysis using summary statistics from independent, large GWAS for exposures and outcomes separately improved the statistical power to examine their causal association. Third, the use of multiple SNPs as IVs for each of the putative clinical risk factors of AT enabled us to analyze potential directional pleiotropy. Furthermore, we employed numerous methods, such as MR-Egger, multivariable MR, and MR-PRESSO, for sensitivity analyses to detect and adjust for pleiotropy. Fourth, the bias introduced by population stratification was reduced in our analyses because the majority of the participants in the original GWAS were European. This study also has several limitations. First, compared with other diseases  studied in MR, the number of AT cases used in the production of the GWAS summary statistics was relatively small, leading to a reduced statistical power to reveal the causal association with the exposures included in this study. Second, although we employed multiple MR methods to deal with the potential directional pleiotropy, as a theoretical weakness of the MR studies, the remaining pleiotropy could not be completely ruled out.This comprehensive MR study has revealed a causal association between BMI and the risk of AT, suggesting that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.The original contributions presented in the study are included in the article/The GWAS included in this work were approved by their relevant review board, and informed consent were given by all participants.SL and YM designed the study. LH and TY performed the statistical analyses, and drafted the manuscript. WZ and BW critically reviewed the manuscript. All authors contributed to the article and approved the submitted version.This study is supported by the Capital’s Funds for Health Improvement and Research (Grant No. 2020-2-7036).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.


Geriatric syndromes (GSs) and aging-associated diseases (AADs) are common side effects of aging. They are affecting the lives of millions of older adults and placing immense pressure on healthcare systems and economies worldwide. It is imperative to study the factors causing these conditions and develop a holistic framework for their management. The so-called long-lived individuals—people over the age of 90 who managed to retain much of their health and functionality—could be holding the key to understanding these factors and their health implications. We analyzed the health status and lifestyle of the long-lived individuals and identified risk factors for GSs. Family history greatly contributes to the health and prevention of cognitive decline in older adults. Lifestyle and certain socioeconomic factors such as education, the age of starting to work and retiring, job type and income level, physical activity, and hobby were also associated with certain GSs. Moreover, the levels of total protein, albumin, alpha-1 globulins, high-density lipoprotein, free triiodothyronine, and 25-hydroxyvitamin D were direct indicators of the current health status. The proposed mathematical model allows the prediction of successful aging based on family history, social and economic factors, and life-long physical activity . Population aging refers to a rise in the number of people over the working age. The World Health Organization projects that by 2050, more than two billion people worldwide will be over the age of 60 . Russia Until recently, loss of functionality, or independence, and other health issues were believed to be inevitable companions of aging. However, as the number of people of an advanced age has grown worldwide, the so-called phenomenon of healthy longevity has gained more and more attention. Healthy longevity is a successful aging, whereby people well over the age of 90, also referred to as long-living people, demonstrate high physical, psychological and social functioning, and delayed onset of AADs and GSs. This phenomenon could hold the key to understanding age-associated risk factors and developing timely prevention strategies aimed at countering senescence and improving the quality of life.instance, far more people live well into their old age in the so-called blue zones  [A number of studies have identified factors that could promote successful aging, including a healthy diet and moderate food intake, regular physical activity, and a socially active lifestyle , environta Rica) ,8,9. Theta Rica) . Geneticta Rica) .In Russia, there has been no comprehensive study on long-living individuals. The Federal State Statistics Service (Rosstat) reports that there are over 30 million people aged 60 and above in Russia . A surveThe present study was carried out in Moscow; therefore, its results cannot be extrapolated to the entire Russian Federation. For instance, the average life expectancy in Moscow is 75 years , while the average life expectancy in Russia is 67 years . RecruitReversing the damage caused by AADs and GSs is more often than not an impossible task. Therefore, effective prevention is crucial. The present study presents an integrated approach to exploring the phenomenon of longevity that included factoring in detailed medical history, risk factor assessment, a comprehensive scale- and survey-based geriatric assessment, and blood testing; the blood test results have been biobanked for further research. This is the first large-scale study on longevity in Russia that made it possible to determine the prevalence of GSs and AADs in older adults  and establish the relationships between various factors and healthy longevity.We studied 2020 participants with a verified age of at least 90 years from Moscow and the Moscow region. All participants signed an informed consent form for blood and biomaterial collection and at least two follow-up visits by a physician. The Local Ethics Committee of the Russian Gerontological Research and Clinical Center approved the study . The participant recruitment was carried out with the assistance of social and geriatric services of Moscow and the Moscow region. The recruitment process is presented in Frailty syndrome, diagnosed using the Short Physical Performance Battery;Cognitive impairment, assessed by the Mini-Mental State Examination (MMSE) and clock-drawing test;Frontal lobe dysfunction, assessed using the Frontal Assessment Battery (FAB) test;Chronic pain, assessed based on the questionnaire presented in the Anxiety disorder, assessed based on the questionnaire presented in the Risk of falls, assessed based on the questionnaire presented in the Sensory deficit, assessed based on the questionnaire presented in the Depression, diagnosed using the Five-Item Geriatric Depression Scale (GDS-5);Sarcopenia, diagnosed using the SARC-F questionnaire  and hand-held dynamometry;Risk of malnutrition, assessed based on the Mini Nutritional Assessment ;Fecal or urinary incontinence, self-reported;Dependence in ADL (activity of daily living), assessed based on the Barthel index;Dependence in IADL , assessed based on the Lawton scale;Polypragmasia, defined as a simultaneous administration of 5 or more medications;Orthostatic hypotension, measured using the standard diagnostic procedure .We analyzed participants’ medical history, socioeconomic and health status, lifetime risk factors for chronic disease and current; factored in all medications taken by the participants; conducted a comprehensive geriatric assessment and screening for 15 GSs following the clinical guidelines of the Russian Ministry of Health :Frailty We used an ordinary least squares Linear Regression Model (Python 3.8 package. Statsmodels) with age and sex as covariates to establish associations between the GSs and factors.1, x2, and x3 are sex, age, and factors, respectively.Data modeling function:p-value.To obtain β we minimized the sum of square differences of the observed and predicted syndrome values, F-tested the significance of the independent variables, and calculated the To avoid multiple testing problems, we applied the Bonferroni correction.The Agglomerative Clustering algorithm from the Python 3.8 package scikit-learn 0.24.2 was used for clustering.To measure the probability of longevity, classification was performed using Logistic Regression  with:p-value < 0.002, significance for all baseline characteristics  and 1516 women (75%) of the average age of 93 ± 2.5 years old (with a maximum of 107 and a minimum of 90 years old). The long-living men were more physically active than the long-living women. On average, all participants had 1 ± 1 AADs with a higher prevalence of certain AADs in men (cancer and CVD) and received 5 ± 2 medications. The most common GSs were sensory deficits and dependence in ADL and IADL. Moreover, many GSs were more common in women. Overall, women had more GSs (mean = 9.74) than men (mean = 8.61) . Physical activity was associated with a lower prevalence of cognitive impairment in participants who had engaged in intellectually demanding activities .Lifelong physical activity was correlated with a lower prevalence of sarcopenia, dependence ADL and IADL, and the risk of malnutrition. Physical activity was positively correlated with a higher risk of falls, orthostatic hypotension, and frontal lobe dysfunction. However, it should be noted that physical activity implies both physical activities in a broad sense and hard labor. These correlations were significant only in participants who had engaged mainly in heavy physical labor .To divide 1696 participants into groups, we performed clusterization based on the presence of AADs  and scores on MMSE, FAB, and SPPB. This resulted in two clusters   and included more men than Cluster 0. Family history analysis showed that the risk of cognitive decline in Cluster 1 was three times lower than in Cluster 0. Cluster 1 participants shared the following socioeconomic characteristics: they had higher levels of education; had started to work on average two years earlier, and had retired on average three years later than their peers; they had more intellectually demanding occupations and earned more. Women in this group experienced the onset of menopause on average three years later than their peers. These participants also demonstrated higher functionality. Physical examination revealed that they had a larger waist circumference, higher weight, and a higher BMI. They performed better on the Clock-drawing and Age is-not-a-barrier tests, and had lower Charlson comorbidity indices. They self-assessed their health and quality of life much higher compared to other participants; led a more socially and physically active lifestyle; had fewer physical limitations; were more religious and had lifelong hobbies.Other differences are presented in p-value for difference 1.1 × 10−5).To identify participants with the highest number of health problems, we clustered the least successful aging group based on the following factors: presence of cognitive decline, frailty, sensory deficit, and ADDs. We obtained two clusters  ;Physical activity for the most part of one’s life;Mother’s age at death;Father’s age at death;Income at the peak of the career ;Total number of children;Area of residence ;Type of job ;Former dog owner ;Former cat owner ;Disability ;Marital status ;Age of retirement;Age of starting to work;Hobby ;Education ;Religion ;Grip strength;Based on the clustering described in The model was trained on 694 samples and tested on 174 samples. We obtained f1 score = 0.72 and AUC = 0.68; precision = 0.83 and recall = 0.64. We also factored in the age of menopause onset as a distinguishing factor. The sample size was thus 483 for training and 121 (women only) for testing. The AUC increased to 0.69, the f1-score to 0.73, the precision to 0.84, and the recall remained unchanged. The age of menopause onset showed the highest coefficient (0.7). This model included the following most significant factors: age, sex, hobby, religion, education, age of retirement, physical activity, family history of cognitive decline, and, for women, the age of menopause onset.The present study was a comprehensive assessment of the unique population group—long-lived men and women. Both in this study and on a larger population scale, long-lived women outnumber long-lived men; however, we analyzed the gender differences and discovered that women suffered from more GSs and were less physically active. This fact confirms the so-called male–female health-survival paradox . TherefoThe clusterization and individual association analysis revealed that no dementia in family history greatly contributes to the preservation of cognitive functions, physical activity, and physical fitness in very old adults. Similar results obtained in studies of younger participants support these findings ,21.Working from an early age, lower levels of education, and physical labor for most of one’s life were associated with many GSs. Other studies ,23 suppoSocialization was another important promoter of healthy longevity. Those participants who more frequently had guests over and had hobbies suffered from fewer GSs. Owning a cat or dog was associated with stronger and healthier muscles. Remarkably, having religious beliefs was to a certain extent a protective factor associated with healthy longevity. This has previously been confirmed in several studies ,29.Physical activity is known to play an important role in the prevention of ADDs. It also lowers the risk of GSs and increases functionality in older adults . A systeIt is noteworthy that the successful aging cluster participants had higher BMIs and larger waist circumferences, which demonstrates a protective effect of a slightly increased body weight in old adults .p-value = 3.21 × 10−6, coefficient of correlation—0.14). Women who gave birth to their first child when they were under 25 years of age were characterized by a lower level of education  and lower income at the peak of their careers . This fact constitutes a limitation of the study. Moreover, all participants were from Moscow and the Moscow region.Successful aging is a complex phenomenon that depends on a variety of medical, socioeconomic, and environmental factors. It can be linked to potentially modifiable habits and lifestyles. Different statistical methods showed that physical and social activity, economic well-being, and higher levels of education could be associated with successful aging. Further research of this phenomenon could help identify modifiable factors that promote successful aging in all groups of the population.


Dietary fiber and vitamin C has been reported to play a possible role in tumorigenesis. However, few studies have estimated their association with oral cancer risk. In this project, we investigated the relationship between dietary fiber and vitamin C and oral cancer risk in adults in Southern China.382 patients newly diagnosed with oral cancer were matched to 382 hospital derived controls by frequency matching in age and sex. Pre-diagnostic consumption of dietary fiber and vitamin C intake were measured through food frequency questionnaire. Association between nutrients intake and oral cancer risk were evaluated by logistic regression. OR value and 95% confidence interval was calculated.Ptrend< 0.001). Compared with the lowest tertile, the adjusted OR of the top tertile of dietary fiber was 0.47 . While the adjusted OR of the highest tertile was 0.60  compared with the lowest tertile of vitamin C.Intake of dietary fiber and vitamin C was significantly lower in oral cancer patients (8.15 g/day) than in control participants (8.88 g/day). Increased dietary fiber or vitamin C intake was linked to a decreased incidence of OC after adjustment of age, marital status, residence, BMI, occupation, education, tobacco smoking, alcohol consumption and family history of cancer Dietary intake of fiber and vitamin C were lower in oral cancer patients than in control participants. Dietary fiber and vitamin C were inversely related to risk of oral cancer risk. Oral cancer accounted for 40% of cancers of the head and neck, which includes squamous cell carcinomas of the tongue, floor of the mouth, buccal mucosa, lips, hard and soft palate, and gingival . At the The findings of a significant systematic study released by the World Cancer Research Fund (WCRF) in 2019 indicated that adopting a diet rich in wholegrains, vegetables, fruit, and legumes may protect against cancer . As theyIn 2015 , the IntThus the study was conducted to explore the potential link between dietary fiber and vitamin C consumption and the incidence of oral cancer in southern China. The aforementioned nutrients, we expected, would be inversely connected to the risk of oral cancer.A hospital-based case-control study was conducted in Fujian Province, China. From September 2016 to July 2020, oral cancer patients were recruited at the Department of Mouth & Maxillofacial Surgery, First Affiliated Hospital of Fujian Medical University. All patients were newly diagnosed primary oral cancer verified by histology. Patients with recurring or metastasized cancer, as well as those who had already had chemotherapy or radiation, were excluded. During the same time period, control subjects were selected from the same hospital's health examination center and were frequency matched to cases by age (10-year group) and sex. All subjects included were Chinese Han men and women between the ages of 18 and 80 who had resided in Fujian for at least 10 years.In accordance with the Declaration of Helsinki, all subjects provided written informed permission. The investigation protocol was granted by the Institutional Review Board of Fujian Medical University . Face-to-face interviews with study subject were performed by professional interviewers (unless the subject was too ill to respond). Finally, 382 oral patients and 382 control participants were included in the study.Food frequency questionnaire was used to evaluate individuals' usual dietary habits during the previous year (FFQ). Majority food category include staple foods, beans and bean products, vegetables, fruits, animal foods, bacteria, algae, and nuts, beverages, and soups. The researchers gathered data on portion size and food consumption frequency. Subjects were informed food images to assist them measure their dietary consumption. By multiplying the intake frequency by the intake quantity and dividing it by 365 days, the average amount of each food item ingested (g/d) was determined. The Chinese Food Composition Tables  was used2-test or Fisher's exact test. The t-test was used to compare differences of continuous variables between the two groups when the data was normally distributed, and the Wilcoxon rank sum test was used when the data was skewed. Adjusted odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were determined with the lowest tertile of dietary fiber and vitamin C consumption as reference. The regression residual approach was used to adjust nutrient intake by total energy consumption. All of the data was analyzed using Stata software version 15.0. All p-values in this study are two-sided, and statistical significance was evaluated at the 0.05 level.For categorical variables, differences of demographic features and dietary data between cases and controls were assessed using the χThere were 764 individuals in total, of which 422 were men and 342 were women. P < 0.001) and fruits  were the major source of dietary fiber, followed by soy foods, algae, nuts and grain, which are all related to dietary fiber intake, as data shown in P < 0.001), fruits , algae and nuts  showed strong correlation with Vitamin C intake. Grains, soy food, meat and eggs, dairy, pickles and processed meat are not significantly related to vitamin C intake.Compared with the controls, the intake of dietary fiber and vitamin C was significantly lower among cases . The aveCI: 0.37–0.74; Ptrend = 0.0006) for dietary fiber, and the ORs was 0.65  for vitamin C. After adjusting for age, marital status, residence, BMI, occupation and education, the individuals in the highest tertile of the intake of dietary fiber tended to have lower odds for oral cancer  compared with those in the lowest tertile and a consistent result was observed in vitamin C . The result remained significant after further adjustment for tobacco smoking, alcohol consumption and family history of cancer, with ORs= 0.47  for dietary fiber, and 0.60  for vitamin C. Moreover, similarly association was observed when we treated the intake of dietary fiber and vitamin C as a continuous variable in the rude model, and adjusted models. The OR value of dietary fiber was 0.9337 , while the OR value of vitamin C was 0.9974  in model 2.OR = 0.43; 95% CI: 0.25–0.76; Ptrend< 0.001) and those without alcohol consumption . While association between intake of vitamin C and the risk of oral cancer remained significant in female  and those without alcohol consumption  compared with male and drinkers.We also investigated whether the relationship between dietary fiber and vitamin C intake and oral cancer varies with different status of sex, smoking, alcohol consumption and family history of cancer , 5. The In this case-control designed study, we observed that higher dietary fiber and vitamin C consumption were related to a lower risk of oral cancer after adjustment of potential confounding factors. These findings are in accordance with the conclusions of two previous meta-analysis studies , 33.Kawakita et al., etc., summarized and analyzed 10 case-control studies participating in the International Head and Neck Cancer Epidemiology consortium in a meta-analysis in 2017 , in whicAlthough further researches are needed to validate this conclusion, numerous molecular pathways have been postulated to explain why fiber consumption protects against oral cancer. Dietary fiber appears to have an anti-inflammatory effect , 41, thrAs for the relationship between vitamin C and cancer, many researchers have reported the beneficial effects of vitamin C on cancer –51 in boHowever, potential limitations of our study should also be notified. Firstly, we could not rule out the possibility of selection bias due to the hospital-based case-control study design, although the hospital covered most of the oral cancer cases from the selected area and we recruited control participant from the same hospital. Secondly, it was meaningful to study the relevance as a case-control study, but this information was not available. While the case and control participation rates were high, it is still possible that participating controls were more health conscious than the general population, thus biasing risk estimates away from the null. Thirdly, recall bias and measurement error in dietary assessment using an FFQ is difficult to avoid in a case-control study. Thus, the associations observed between dietary fiber, vitamin C and oral cancer should be interpreted cautiously.In conclusion, the current investigation found that greater dietary fiber and vitamin C intakes were linked to a lower incidence of oral cancer in a southeastern Chinese population. Given the limitations of hospital-based case-control studies, further well-designed, particularly large-scale cohort studies, are needed to corroborate our findings.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 Institutional Review Board of Fujian Medical University. The patients/participants provided their written informed consent to participate in this study.JW (1st author), FL, and YF conceptualized the original idea for the study and have been involved in data collection, data analysis, and manuscript drafting. JQ assisted in statistical analysis. All authors have made substantial contributions to conception and design of the study, have read and approved the manuscript.This study was supported by Fujian Natural Science Foundation Program under Grant 2020J01639, Technology Development Fund from the Department of Education of Fujian Province Grant Number: 2019L3006 and Fujian Provincial Health Technology Project under Grant No. 2018-1-57.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.