Maximum mouth opening (MMO) was increased significantly in female population in comparison with males . Incisor displacement at MMO showed higher values for control groups compared with TMD subjects . Evidence is still needed, considering the great variety of devices and parameters used for arthrokinematics. The present study suggests standardising outcomes, design, and population of the future studies in order to obtain more reliable and repeatable values.The aim of this review was to answer the following PICO question: “Do TMJ kinematic parameters (intervention and comparison) show efficacy for assessment of mandibular function (Outcome) both in asymptomatic and TMD subjects? (Population)”. PubMed, Scopus, Web of Science, Embase, Central databases were searched. The inclusion criteria were (1) performed on human, (2) English only, (3) on healthy, symptomatic or surgically altered TMJ, (4) measured dynamic kinematics of mandible or TMJ (5) with six degrees of freedom. To assess the Risk of Bias, the Joanna Briggs Institute tool for non-randomised clinical studies was employed. A pairwise meta-analysis was carried out using STATA v.17.0 (Stata). The heterogeneity was estimated using the Q value and the inconsistency index. Ninety-two articles were included in qualitative synthesis, nine studies in quantitative synthesis. The condylar inclination was significantly increased in female (effect size 0.03°, 95% CI: −0.06, 0.12,  The temporomandibular joint is a bilateral synovial joint between the temporal bone and the mandible, that function as one unit. Since the TMJ is connected to the mandible, the right and left joints must function together and therefore are not independent of each other. TMJ represents the only mobile joint in the skull. Mandibular stability and movements are essential to perform normal jaw function like biting, chewing, swallowing, and speech . Loss ofTemporomandibular disorders (TMD) are a group of heterogeneous clinical situations with multifactorial aetiology which can be related with musculoskeletal pain, joint noise and functional problems. TMD are a significant public health problem, and they represent one of the most common musculoskeletal conditions resulting in pain and disability  which maThe treatment of muscle-related pain in TMD commonly consisted of occlusal splint devices, behavioural therapies and other conservative non-pharmacological approaches such as manual therapy, laser therapy, transcutaneous electrical nerve stimulation (TENS) and dry needling. Conservative and physical therapies are recommended for the initial treatment of TMD ,10,11.Mandibular kinematics measurements are used for clinical purpose such as study of dynamic occlusion in prosthodontic restorations, orthodontic and gnathological therapies, and for screening of temporomandibular dysfunction . The corMandibular kinematics techniques can be classified in four categories: mechanical linkage systems, magnetic tracking systems, video motion analysis and radiographic tracking .TMD are closely connected to mandibular movement and function, for that reason could be important to have an early and objective diagnosis. Therefore, the aim of this systematic review and meta-analysis is to demonstrate if and which kinematic parameters are useful to diagnose musculoskeletal jaw’s disorders, in order to assess clinical efficacy of this diagnostic tool for treatment planning. The outcome of this study may be useful also to lead future research studies on TMJ kinematic and its correlation to TMD.This review followed the guidelines of the preferred reporting items for systematic reviews (PRISMA) . The goaParticipants/Population: Patients who are affected by temporomandibular disorders diagnosed according to diagnostic criteria for temporomandibular disorders (DC/TMD) for clinical and research applications, in particular myofascial pain, anterior disk displacement with or without joint noises, arthralgia, osteoarthritis and osteoarthrosis for at least three months. No particular limitations about patients age.Intervention: TMD conservative treatment and non-surgical intervention. There were no restrictions of the duration of intervention.Comparator (s): Asymptomatic subjects with different types of occlusion. No limitations about subjects age.Outcome(s): Maximum mouth opening is distance between the incisal edge of the maxillary central incisors to the incisal edge of the mandibular central incisors at the midline when the mouth is open as wide as possible. Incisor displacement at MMO (IP-MMO) is the distance between the incisor point from the medial sagittal plane during maximum mouth opening. Condylar inclination represents the angle of the condyle translating down the condylar eminence as the mandible moves. Horizontal and sagittal angles are decomposition of the mandibular trajectory on the three planes of space.Time: follow up at 6 mouths.The eligibility criteria were planned considering the following population, intervention, comparison and outcome (PICO) question: “Do TMJ kinematic parameters (intervention and comparison) show efficacy for assessment of mandibular function (Outcome) both in asymptomatic and TMD subjects? (Population)”. We only included studies performed on humans and written in English. Moreover, opinion-based papers, perspectives, conference papers, book chapters, case reports and abstract were excluded. We also considered the cross-references of the included articles and reviews. The studies that met the following criteria: focused on healthy, symptomatic or surgically altered TMJ, measured dynamic kinematic of mandible or TMJ with six degrees of freedom were all included for qualitative and if found eligible quantitative analysis.A search for articles in the following electronic databases was carried out: PubMed, Scopus, Web of Science, Embase, Central. The databases were searched up until 2 January 2022. The key words used were: “temporomandibular joint” OR “TMJ” OR “mandible” OR “temporomandibular joint disorder” OR “TMD” AND “kinematics” OR “jaw motion” OR “motion analysis” OR “biomechanics”. A mix of medical subject headings and free key words were used. Only the studies published in English were included. The articles were manually checked for relevant articles to be included in the review. Once duplicates were removed, titles and abstracts were screened PRISMA flowchart was used to summarise the selection process .Search strategy was implemented and tested by three researchers independently . All articles and abstract which met the selection criteria were included in the review. Three reviewers screened all the titles and abstract independently, those that seemed suitable were included in the full text review. When the information provided in the abstract and title were inadequate to determine eligibility, articles were included in full text review. Any disagreement among the reviewers was resolved by comparison discussion. At least two studies have to be considered to perform the meta-analysis, even if studies can be meaningfully pooled and provided their results are sufficiently ‘similar’ .https://www.microsoft.com/en-in/, accessed on 10 April 2022). A set of standard variables included was validated by discussing with all the reviewers. The validation was done based on the outcomes included in the previous literature used to assess the TMJ kinematics. The following items were extracted whenever possible: authors, year, country, journal, sponsor, study design, number, mean age and gender of the participants, number of test group, number of control group, TMJ condition, diagnostic tool, kinematic parameters analysed, mean values, number of samples in each group and standard deviation for groups. For each parameter, unit of measurement was specified. Data such as gender, study design, diagnostic tool, different TMD conditions for respective outcomes were used as sub-group analysis.Data from the included articles were extracted by three independent reviewers and organised into a data sheet using Microsoft Excel 2013  (degree and mm), Condylar inclination (degrees), horizontal (degrees) and sagittal angle (degrees) and linear displacement of the interincisal point at maximum mouth opening (IP)-MMO (mm) which are five parameters that represent an index of TMJ movement three-dimensionally. If different units of measure were identified, for the same parameter, we excluded them from quantitative synthesis and reported them in qualitative synthesis.The risk of bias assessment of the included NRTCs was performed by three independent reviewers. The JBI—the Joanna Briggs Institute tool was used to assess the methodological quality of case control studies, cohort studies, cross sectional studies and case series. Each study was assessed according to predefined criteria. The JBI model of evidence-based healthcare conceptualises evidence-based practice as clinical decision-making that considers the best available evidence; the context in which care is delivered; client preference; and the professional judgement of the health professional . The strCondylar inclination represents the angle of the condyle translating down the condylar eminence as the mandible moves. In this meta-analysis, the angle is evaluated during protrusive movement of the mandible and is measured in degrees.The maximum mouth opening (MMO) has been defined as “the greatest distance between the incisal edge of the maxillary central incisors to the incisal edge of the mandibular central incisors at the midline when the mouth is open as wide as possible” ,20. MMO Incisor displacement at MMO (IP-MMO) is the distance between the incisor point from the medial sagittal plane during maximum mouth opening, the unit of measure is millimetre.Horizontal and sagittal angles are the indexes of mandibular movement which could be discomposed in three dimensions of space. These parameters are measures in degrees.For continuous outcomes, we pooled data with the mean difference (MD), or standardised mean difference (SMD) if different measures were used to assess the same outcome. If the data are given for each patient, then we used the data to calculate the mean and sd using STATA software v17.0. The mean and sd were collected as mentioned in the published papers and there was no conversion of the values and the units of measure for pairwise comparison. If there were different levels of measure, then we would collect data in categorised form and use it in subgroup analysis.MMO was analysed using as a reference point the value described by Travell  who meas2 is ≤50%, it suggests that there is negligible statistical heterogenicity and the fixed effects model will be employed. If the I2 is >50% we explored sources of heterogenicity by subgroup analysis and meta regression. If there was no clinical heterogenicity, the random effects model was used to perform the meta-analysis.A meta-analysis was carried out only when there were at least two studies of similar comparisons reporting the same outcomes and unit of measure. A pairwise meta-analysis was carried out using STATA v.17.0 (Stata). The heterogeneity between each study was estimated using the Q value and the inconsistency index (I2 test). If the IThe initial research identified 28619 titles; 10017 remained after duplicates removal. Out of the remaining titles, 184 articles were considered potentially eligible and after a full text revision, verification of inclusion and exclusion criteria was carried out. Sixty-seven studies were excluded because the topic was not related to the review, two were studies on animals, seven on robotic actuators, one did not respect the six degree of freedom and four were systematic reviews. At the end of this stage, 92 were selected for qualitative synthesis. Eventually after outcomes assessment, eight comparative studies were selected for meta-analysis , linear incisal displacement at MMO (IP-MMO), and horizontal and sagittal angle, which are mandibular motion indices at maximum opening. For each parameter the mean and standard deviation were recorded. The studies included for quantitative synthesis were Wieckiewicz et al. 2014; Baqaien et al. 2007; Reichender et al. 2013; Ferrario et al. 2005; Gallo et al. 1997; Mapelli 2016; Ugolini 2018; Mapelli 2016; Ugolini 2017.p = 0.00) (p = 0.65)  . Conside = 0.00) . A subgr = 0.65) .2 = 90.12% which indicates the studies were highly heterogeneous in characteristics. The pooled effect has passed the line of no effect, hence there exists statistically significant difference between the male and female groups in MMO outcome. The results were favouring females who showed higher values of MMO  included and MMO outcome . Childrep = 0.05), the overall effect size being 0.16 mm  (95% CI)  .2 = 0%, H2 = 1.00, p = 0.56). As for IP-MMO, the overall effect size was 0.16   .2 = 78.89%, H2 = 4.74, p = 0.85). The overall effect size was −0.09 degrees   was reported in four studies ,30,36,38However, several limitations existed; therefore, the results should be interpreted with caution. First, the large panel of the existing arthrokinematics parameters and units of measure adopted by the different studies, which make difficult to compare clinical data. Second, modifications in head posture and reference point could affect the movement path of the mandible. In the absence of standardisation, this may give rise to a considerable variability. Third, heterogeneities among studies were often observed, which may be caused by differences in study populations and the high number of diagnostic tools that could be used for each study’ purpose. Fourth, the study design: most studies are case series with a higher risk of bias in data interpretation.This meta-analysis shows that TMJ kinematic parameters are useful for mandibular function assessment in clinical practice, but studies included demonstrated that there is a need for data standardisation and establish a gold standard as a reference point. The current studies have heterogeneity in terms of outcomes and variables included. To improve the methods of strategies, the authors suggest carrying out future well-designed case-control studies to improve the level of evidence. Finally, it would be good if future studies compared the various diagnostic methods using the same parameters and units of measurement in order to be able to compare more data more reliably.We concluded that, there is high heterogeneity among the majority of the outcomes except condylar inclination. Considering this factor, the interpretation should be done with caution and take a meaning full message that, the kinematic parameters are an important and useful tool for TMJ evaluation, both to evaluate function and dysfunction. There is a need of well-designed case-control or cohort studies that can add further evidence. The present review suggests standardising outcomes, study design, type of diagnostic devices used to assess the kinametics and population selection in the future studies. This would improve and add reliable and repeatable values.A well-designed case-control studies would be beneficial in order to increase the level of evidence on the clinical significance of kinematics;The literature in the present review demonstrated varying diagnostic tools and measurements for different outcomes. It would be beneficial if the different diagnostic tools are used along with a standard of care;The present review highlighted different outcome measures and it would benefit if the case-control studies with MMO outcome as standard method would be measured along with the different outcomes which can have similar dimensions or unit of measurement;There are varying groups compared in the studies highlighted within this review. Comparing the groups that include, the TMD and the pre-surgical, post-surgical would bridge the gap in the evidence;Majority of studies included in this review lack sample size calculations. Therefore, it is highly recommended to use appropriate sample size calculations for respective studies.


Various ablation techniques have been successfully applied in tumor therapy by locally destroying tumor. In the process of tumor ablation, a large number of tumor cell debris is released, which can be used as a source of tumor antigens and trigger a series of immune responses. With the deepening of the research on the immune microenvironment and immunotherapy, researches exploring tumor ablation and immunity are continuously published. However, no research has systematically analyzed the intellectual landscape and emerging trends for tumor ablation and immunity using scientometric analysis. Therefore, this study aimed to conduct a bibliometric analysis to quantify and identify the status quo and trend of tumor ablation and immunity.Data of publications were downloaded from the Web of Science Core Collection database. CiteSpace and VOSviewer were used to conduct bibliometric analysis to evaluate the contribution and co-occurrence relationship of different countries/regions, institutions and authors in the field, and to determine the research hotspots in this field.Jibing Chen and Xianzheng Zhang might have a keen interest in tumor ablation and immunity, with more publications . Among the top 10 co-cited authors, Castano AP (284 citations) was ranked first, followed by Agostinis P (270 citations) and Chen Qian (246 citations). According to the co-occurrence and cluster analysis, the results indicated that the focus of research was “photothermal therapy” and “immune checkpoint blockade”.By searching in the database, a total of 3531 English articles published between 2012 and 2021 were obtained. We observed rapid growth in the number of publications since 2012. The two most active countries were China and the United States, with more than 1,000 articles. Chinese Academy of Sciences contributed the most publications (n = 153). In the past decade, the neighborhood of tumor ablation domain immunity has been paid more and more attention. Nowadays, the research hotspots in this field are mainly focused on exploring the immunological mechanism in photothermal therapy to improve its efficacy, and the combination of ablation therapy and immune checkpoint inhibitor therapy. Currentnenergy) . New tecnenergy) –5. It isnenergy) . With thnenergy) –10.Immunity means that the immune system removes alien components or mutated self-components through a series of immune responses of immune cells, to maintain the balance of the immune microenvironment of the body . In receAcademic journals have published a big deal of papers exploring tumor ablation and immunity in the past decade. However, no attempts have been made to analyze the data on publications systematically. Bibliometrics is a useful method to probe into the most impactful authors, papers, or countries/regions, construct collaboration networks, and identify research hotspots in particular areas , 19. In Data between 2012 and 2021 in the field of tumor ablation and immunity were obtained from Web of Science Core Collection (WoSCC) database on August 6, 2022. The database source was limited to Science Citation Index Expanded (SCIE) and publication types to “article”. The main search terms were “tumor ablation”, “immunity”, and “immune response”. The detailed search strategy is presented in the A bibliometric program, VOSviewer  is used to perform the co-occurrence of authors/institutes/countries/journals. In VOSviewer, the size of the node reflects the number of researches or co-occurrence frequencies, the size of the links indicates the co-occurrence frequencies of two nodes, and the same color of node represents the same cluster . CiteSpaAccording to the retrieval criteria, a total of 3,531 papers published between 2012 and 2021 were retrieved from the WOS database. As shown in A total of 3,531 articles were from 83 countries/regions and 3121 institutions. The top 10 institutions are mainly located in China(n=4), the United States(n=4) and France(n=2) in Jibing Chen (n=14) was ranked first, followed by Xianzheng Zhang (n=13) and Feifan Zhou (n=13). Among the top 10 co-cited authors, three authors had co-citations over 200. Castano AP (284 co-citations) was ranked first, followed by Agostinis P (270 co-citations), and Chen Qian (246 co-citations). The network map of co-authorship and co-cited relationship were constructed by VOSviewer  = 13.312) published the most papers, followed by Plos One , Photodiagnosis and Photodynamic Therapy , and Biomaterials . Among the top 10 journals, 50.00% had IF higher than 10.000, and ACS Nano  is the academic journal with the highest IF.In total, 844 academic journals have published research investigating tumor ablation and immunity. In the top 10 journals, 80.00% of the journals published more than 50 articles Table 2.CA- A Cancer Journal for Clinicians by Agostinis P et al. and the article entitled “Photothermal therapy with immune-adjuvant nanoparticles together with checkpoint blockade for effective cancer immunotherapy” published in Nature Communications by Chen Q et al. have been co-cited more than 100 times, which indicates that these two articles have a significant impact in the field of tumor ablation and immunity. Besides, VOSviewer is used to construct the network map of co-cited references . As shown in the timeline view  and USA (n=1273) contributed the most to publications on tumor ablation and immunity, followed by the Germany (n=266) and Japan(n=190). Of the top 10 institutions that published the most research items, China and USA respectively contributed four of the top 10 institutions, followed by the France with two institutions. These findings may suggest that Chinese and American researchers continue to delve into the neighborhood of tumor ablation and immunity. Close collaborations were observed between countries/regions and institutions; however, collaborations between agencies were found to be stronger than those between countries, indicating that international collaborations should be strengthened.Castano AP (284 co-citations) was ranked first, followed by Agostinis P (270 co-citations) and Chen Qian (246 co-citations). Furthermore, Among the top ten co-cited literature, the first and second-ranked literature were from Agostinis P and Chen Qian, respectively. As excellent researchers, professor Castano AP and Agostinis P are devoted to the research of photodynamic therapy. Castano AP not only systematically expounded and summarized this therapy, but also explored how photodynamic therapy can kill tumors through immune function  and other languages. Second, although the WoSCC database is still updating, the study includes the vast majority of articles published in the neighborhood of tumor ablation and immunity between 2012 and 2021, and the new data may not affect the results. Third, we may not include all the tumor ablation methods in the search strategy due to the complexity of ablation techniques, which leads to a certain selection bias in our results. Finally, most of the information was extracted by bibliometrics software, so our results may also be biased. For example, we cannot rule out the possibility that some authors have the same acronym and some keywords have different expressions.We used bibliometrics software to conduct a relatively comprehensive and objective analysis of the neighborhood of tumor ablation and immunity, and explored the frontiers of research in this field. In general, exploring the immunological mechanism in photothermal therapy to improve its efficacy, and the combination of ablation therapy and immune checkpoint inhibitor therapy are the main focus of tumor ablation and immunity in the future.The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author/s. Requests to access the datasets should be directed to shenh25@mail2.sysu.edu.cn.HS wrote the paper. GH and BL tracked the paper. LW and YZ collected the data. All authors contributed to the article and approved the submitted version.


Body-weight-supported treadmill training (BWSTT) combined with functional electrical stimulation (FES) is considered an effective intervention method to improve gait parameters in stroke patients. In this article, we compared the effect of BWSTT combined with FES and BWSTT only on gait parameters in stroke patients.Two researchers searched for literature published before January 5, 2021, in seven Chinese and English databases including PubMed, Web of Science, Cochrane Library, Ovid, CNKI, Wanfang Data, and VIP. Meta-analysis was then performed on various data collected, namely, 10 Meters Walking Test (10MWT), gait speed, Fugl-Meyer Assessment (FMA), Berg Balance Scale (BBS), Modified Barthel Index (MBI), Comprehensive Spasticity Scale (CSS), Functional Ambulation Category (FAC), and Ankle Range of Motion (AROM).A total of 14 studies were included in the meta-analysis, in which 945 stroke patients participated. In these 14 studies, the participants were randomly divided into a test group and a control group. The test group received BWSTT combined with FES, while the control group received BWSTT only. Meta-analysis showed that when compared to BWSTT, BWSTT combined with FES had a better effect on FAC, AROM, 10MWT, CSS, MBI, FMA, gait speed, and BBS of stroke patients. However, the effect of BWSTT combined with FES on BBS was not significant in the medium exercise group when compared to that of BWSTT. Also, the effect of BWSTT combined with FES on gait speed was not significant in the large exercise group when compared to that of BWSTT only.BWSTT combined with FES is more effective than BWSTT only for improving gait parameters in stroke patients.https://www.crd.york.ac.uk/prospero/#recordDetails, CRD42022299636. Stroke is a kind of cerebrovascular disease that is characterized by high mortality and high disability, and poses a serious health risk to people . AlthougBody-weight-supported treadmill training (BWSTT) combined with functional electrical stimulation (FES) is an effective method for improving gait parameters in stroke patients. BWSTT is a functional training method that is based on the reorganization of brain function and neuroplasticity . It invoAt present, BWSTT combined with FES is being widely used in clinical practice to treat stroke patients, as this combined intervention has been proven to have a good effect on the gait parameters of the patients. Hesse et al.  studied Research showed that BWSTT combined with FES could effectively reduce lower limb spasms, droop, varus, and other adverse conditions in stroke patients . HoweverTo study the effect of BWSTT combined with FES on the gait parameters of stroke patients, we conducted a meta-analysis and systematic evaluation according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA) statement , which hTwo researchers independently searched electronic resource databases, including Web of Science, PubMed, Cochrane Library, Ovid, CNKI, WanFang, and VIP, for randomized controlled trials related to the subject. The search covered all data up to January 5, 2021, and included a bibliography of the articles to prevent omission. A target word (stroke) and an intervention word  were searched for in all the databases. Based on multiple previous studies, all searches used a topical search and a related-term search. The search terms included gait training, walking training, treadmill training, weight support treadmill training, stroke, cerebrovascular disease, hemiplegia, SAH, functional electrical stimulation, FES, etc. The search strategy for all the databases is presented in The basic inclusion criterion was that all randomized controlled trials published in Chinese and English, without restriction on the age or sex of stroke patients should be included. The detailed inclusion criteria were (a) studies of stroke patients diagnosed with cerebral infarction or cerebral hemorrhage identified through Computer Tomography (CT) or Magnetic Resonance Imaging (MRI); (b) studies in which the participants were in stable condition, conscious, and able to cooperate to complete all assessments and receive motor instructions; (c) studies in which the patients did not have various osteoarticular or neuromuscular diseases that affect walking ability; (d) studies in which BWSTT and FES were used as the main intervention method for stroke exercise in the test group; (e) studies in which only BWSTT was used as the main intervention method for stroke exercise in the control group; (f) relevant studies that included relevant indicators of gait parameters.Exclusion criteria were: (a) studies in which the main intervention method was not BWSTT combined with FES in the test group; (b) studies in which the main intervention method was not BWSTT only in the control group; (c) repeated articles or articles with incomplete data; (d) studies published in languages other than English or Chinese.Two researchers (JQW and LYZ) extracted and imported the searched articles into Endnote X9, and deleted duplicated articles. They initially screened the articles based on the titles and abstracts, and then screened them again based on the main text. When they had differing opinions on the inclusion of a paper during the screening process, they decided whether to include the article or not by consulting with a third researcher (YG). The descriptive information present in the articles was extracted and incorporated into the database by the third researcher. This included the article title, country, year of publication, name of the first author, sample size (number of participants in the experiment group and the control group), gender of the sample size, intervention methods of the experiment group and the control group, and the changes  in the research parameters. All this information was recorded in an Excel spreadsheet and verified by all three researchers.Using the Cochrane Risk of Bias tool present in the Cochrane Manual and Review Manager 5.4.1 software , two resI2 statistic were used to test for heterogeneity. When the heterogeneity was p > 0.1 and I2 > 50%, subgroup analysis was conducted based on the total exercise volume. Since the intervention in the test group was BWSTT combined with FES, the differences in the exercise intensity among the selected studies were not considered in this study. The total exercise volume was determined based on the total exercise time. The included studies were divided into three subgroups based on the total exercise volume—small exercise group , medium exercise group , and large exercise group . The total exercise volume (in seconds) was equal to the intervention time of BWSTT combined with FES per day multiplied by the intervention days of BWSTT combined with FES per week multiplied by the total number of weeks of combined intervention (one month was considered to have 4 weeks). If the between-group heterogeneity was too large or the number of articles was too small for subgroup analysis, descriptive analysis was conducted. Sensitivity analysis was conducted if necessary, and funnel plot and Egger's test were used to assess possible publication bias. The trim and filling method was used to correct the possible bias, and the cause of the publication bias was identified through meta-regression.Review Manager 5.4.1 and Stata 17.0 were used for the meta-analysis. As the articles had the same continuous outcome variables and the same units of measurement, weighted mean difference was calculated. In case the mean and standard deviations of the studied indicators were not published, they were estimated based on pre- and post-intervention values according to the Cochrane Handbook for Systematic Reviews of Interventions. Owing to the differences in the study designs and study populations, the random effects model was used in the meta-analysis, assuming that the effect sizes were different among studies. Q statistic and A total of 10,150 articles were retrieved from various Chinese and foreign language databases. Three thousand one hundred thirty repetitive articles were removed using Document Manager. Five Thousand nine hundred thirty-five irrelevant articles were removed by reading titles and abstracts, and 1,041 relevant articles were identified by reading through relevant meta-analysis literature and systematic reviews. Finally, 44 potentially eligible articles were selected. Out of these, unqualified articles were excluded by reading full texts, and 14 controlled experiments were selected for the study .A total of 945 subjects were included in the 14 selected articles. The basic characteristics of the included studies are presented in Two independent reviewers (JQW and LYZ) conducted the risk of bias assessment. In total, 14 studies had adequate random sequence generation. With respect to “selection bias,” 3 studies had adequate allocation concealment, while 11 did not give enough information. With respect to “performance bias,” 4 studies blinded participants and researchers, while 10 did not give enough information. Overall, 5 studies reported a blinded outcome assessment, while 9 did not give enough information. Fourteen studies provided complete outcome data. For all the studies, bias reporting was not mentioned because the protocol was not described. With respect to “other bias,', 14 studies did not give enough information , 3.The purpose of this study was to compare the difference between the effects of BWSTT combined with FES and BWSTT only in improving gait parameters in stroke patients. Gait parameters mainly included data from 10 Meters Walking Test (10MWT), Gait Speed, Fugl-Meyer Assessment (FMA), Berg Balance Scale (BBS), Modified Barthel Index (MBI), Comprehensive Spasticity Scale (CSS), Functional Ambulation Category (FAC), and Ankle Range of Motion (AROM) indicators. Meta-analysis and subgroup analysis were conducted for all research indicators.Exercise load was used as a classification index for the subgroup analysis, and the total intervention time of BWSTT combined with FES was used as a measurement standard for exercise load. The exercise groups were classified as follows: small exercise group with an intervention time of < 50,000 s, medium exercise group with an intervention time of 50,000–100,000 s, and large exercise group with an intervention time of more than 100,000 s. Subgroup analysis based on this classification could better examine the differences between the effects of BWSTT combined with FES and that of BWSTT only, and further explore whether exercise load has any effect on gait parameters in stroke patients, and if so, which effect is better.I2 = 0%; p < 0.00001), the medium exercise group , and the large exercise group    (BWSTT combined with FES had a better effect on the MBI (0.00001) , AROM (I0.00001) , and FAC 0.0001)  of the sI2 = 29%; p = 0.005)    and gait0.00001)  of the sI2 = 33%; p < 0.00001) (The effect of BWSTT combined with FES on CSS in the medium and large exercise groups (0.00001)  was moreP < 0.05 as significant publication bias. Finally, we used the cut-and-fill method to evaluate the effect of publication bias on the results. Meta-analysis showed that there was heterogeneity in the FMA, gait speed, and FAC, so sensitivity analysis was performed. The Egger's test revealed that the P-values of all the above indexes were > 0.05, .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.


Cardiovascular comorbidities (CVCs) affect the overall survival (OS) of patients with colorectal cancer (CRC). However, a prognostic evaluation system for these patients is currently lacking.This study aimed to develop and validate a nomogram, which takes CVCs into account, for predicting the survival of patients with CRC.In total, 21,432 patients with CRC were recruited from four centers in China between January 2011 and December 2017. The nomogram was constructed, based on Cox regression, using a training cohort , and validated using a validation cohort . The discrimination and calibration of the model were assessed by the concordance index and calibration curve. The clinical utility of the model was measured by decision curve analysis (DCA). Based on the nomogram, we divided patients into three groups: low, middle, and high risk.CI: 0.708–0.720) in the training cohort and 0.742 (95% CI: 0.725–0.759) in the validation cohort. The calibration curve and DCA showed the reliability of the model. The cutoff values of the three groups were 68.19 and 145.44, which were also significant in the validation cohort (p < 0.001).Independent risk factors selected into our nomogram for OS included age, metastasis, malignant ascites, heart failure, and venous thromboembolism, whereas dyslipidemia was found to be a protective factor. The c-index of our nomogram was 0.714 (95% Taking CVCs into account, an easy-to-use nomogram was provided to estimate OS for patients with CRC, improving the prognostic evaluation ability. Colorectal cancer (CRC) is the third most common cancer and the fifth most common cause of cancer-related deaths (8.6%) in China, which imposes a heavy burden on the healthcare system , 2. IncrThe TNM staging system of the 8th edition of the American Joint Committee on Cancer (AJCC) is widely used in prognosis prediction for patients with CRC. However, it may be inapplicable to patients with CVCs because it only includes cancer-related variables . To inteIn this study, we aimed to develop and validate a prediction model, which was visualized as a nomogram, for the OS of patients with CRC and CVCs, and stratify patients into three risk groups. This nomogram may provide a more individualized prognosis for these patients and guide the selection of treatment regimens.Data present in this study were collected through a computer-assisted personal interview system from January 2011 to December 2017. We collected information on newly diagnosed primary CRC inpatients from four cancer specialized hospitals in China . The data for birthdays, gender, diagnosis dates, and the information of diagnosis were abstracted from hospital discharge records. Each record had information on up to 30 diagnoses, which were used to identify comorbidities of patients. The follow-up information was collected by clinic visit, hospitalization, or telephone call.The exclusion criteria were as follows: (1) patients who were under the age of 18 or over the age of 90; (2) pathologically confirmed benign cancers or cancer-like diseases; (3) patients with more than one cancer; and (4) patients who had incomplete data. A total of 21,432 patients were selected in the final dataset. We divided the dataset into a training cohort  and a validation cohort . The study was conducted in accordance with the Institutional Review Board of the participating hospitals and informed consent was waived because the data were de-identified.The CVCs in our study defined as the pre-existing cardiovascular diseases when cancer was diagnosed included: hypertension, diabetes, coronary artery disease, heart failure, dyslipidemia, atrial fibrillation, cerebrovascular disease, pericardial effusion, and venous thromboembolism. The cancer-related variables in our study included: age of diagnosis, gender, metastasis , malignant pleural effusion, and malignant ascites. Continuous variables were translated into categorical variables.1 Overall survival (OS) was defined as the time from the cancer diagnosis to the patient’s death or censored at the time of the last follow-up. Variables were screened by univariate Cox regression analysis (p < 0.10), and every variable of CVCs and cancer was included in the process of variables screening. Variables selected from the screening process were subjected to a multivariable Cox regression analysis model (“nomogram model”) which was used to develop the nomogram. Furthermore, the backward stepwise and forward stepwise methods were used to identify the combination of variables, and the two methods were compared by the value of the Akaike information criterion (AIC). We examined the proportional hazard assumption by plotting the log minus log survival curves and found it to hold. A decision curve analysis (DCA) was conducted to determine the clinical usefulness of the prediction model by quantifying the net benefits at different threshold probabilities  and R version 4.4.0.bilities . To evalp < 0.05 was considered to be statistically significant.The discrimination and calibration of the nomogram model were assessed by the concordance index (c-index) and calibration curve which were subjected to 1,000 bootstrap resamples for internal validation, and the validation cohort was used in external validation. The clinical utility of the “nomogram model” and “cancer model” was compared by DCA. We calculated the nomogram score of each patient and used the x-tile software   to dividA total of 19,102 patients with CRC were included in the training cohort, the mean age was 59.06 ± 12.33 years with 57.2% male, and 7,124 (37.3%) patients died of all causes . The valHR] = 1.194 (1.130–1.261), p < 0.001, All variables except gender were selected using the univariable Cox regression analysis  and wereCI: 0.708–0.720) while in the validation cohort was 0.742 (95% CI: 0.725–0.759), which indicated acceptable discrimination. The calibration curves in the training cohort and validation cohort were closely aligned with the 45 degrees diagonal. It revealed good concordance between the nomogram predicted probabilities and the observed probabilities .We divided patients into three groups: low risk (0–68.19), middle risk (68.19–145.44), and high risk (>145.44) according to their nomogram scores by x-tile software . The surThe information of 21,432 patients with CRC cancers was collected in our study. We developed and validated a nomogram, which combined cancer and CVC variables, for survival prediction. Compared with only focusing on cancer-related variables, the addition of CVCs variables could provide individual prognostic information and guide clinical decision-making. To our knowledge, this is the first nomogram assessing the prognostic impact of CVCs in patients with CRC.With the differences in comorbidities definitions, study populations, and cancer types, it is difficult to state with certainty how common the CVCs are . HoweverIn recent years, various prognostic models of CRC have been described –15. Despp < 0.001].Heart failure, which has the highest score among CVCs in our nomogram, is one of the most significant risk factors for prognosis in patients with CRC. It is consistent with the study of Gross et al., which showed that about 9% of patients with stage I–III colorectal cancer died due to heart failure, and heart failure was the most significant comorbidity affecting the OS . Heart fCancer is a significant risk factor for venous thromboembolism (VTE). Thrombotic events sometimes may become the first manifestation of cancer . ResearcHowever, the interaction between CVCs and cancer is sometimes protective. Although some studies on the relationship between dyslipidemia and cancer considered dyslipidemia as a protective factor , 36, theThe TNM staging system is still the “golden standard” for CRC prognosis in clinics. However, as a classifier that groups patients into ordered risk strata, the lack of CVCs factors caused its inability to deal with heterogeneity within risk groups caused by CVCs. Thus, the risk calculators (such as nomograms), which could utilize multiple prognostic factors to provide more individualized risk estimates, gained increasing popularity. To improve the quality and acceptability of the risk models for patients with cancer, AJCC has put forward the acceptance criteria for risk models for individualized prognosis . HoweverAlthough our study had a large sample size, there were still some limitations. First, we could not be sure of the causal relationship between CVCs and CRC because the time of CVCs emerging was not recorded, so the impact of CVCs on the prognosis of patients with CRC was our point. Second, the therapeutic regimens of CRC developed rapidly during the data collection period, but the database lacked detailed treatment regimens. Considering that some anticancer therapies potentially have cardiotoxicity, adding more treatment-related variables to the nomogram or developing different nomograms based on different therapies is meaningful. Third, our nomogram did not include molecular or genetic biomarkers that had prognostic value. However, considering the high cost of biomarkers tests, our nomogram may also be easier to apply in the clinic.In this study, two CVCs and three cancer-associated characteristics were identified as risk factors for the prognosis of patients with CRC, whereas dyslipidemia exerted a protective effect. Taking CVCs into account, we developed and validated a nomogram that could estimate OS for patients with CRC. It may improve the prognostic evaluation ability and facilitate individualized patient management.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.This study was reviewed and approved by and conducted in accordance with the Institutional Review Boards of Yunnan Cancer Hospital, Jiangxi Cancer Hospital, Chongqing Cancer Hospital, and Yuncheng Central Hospital. The requirement of written informed consent was waived because the data were deidentified.HW and DL: conception of design and analysis, and interpretation of data. HW, DL, JSY, WY, YQ, ZY, WG, MZ, HA, XZ, SQ, XG, JGY, HX, JW, TW, TT, HL, ZB, and YM: data collection and drafting of the manuscript or revising it critically for important intellectual content. JSY and WY: final approval of the manuscript submitted. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Maternal-Fetal Attachment (MFA) delineates the emotional, cognitive, and behavioral aspects that mothers develop toward the unborn baby during pregnancy. The literature indicates that optimal attachment in pregnancy represents a protective factor for the mother-child attachment bond after birth and child development outcomes. To date, there are few studies that have investigated associated factors of MFA. This study sets out to explore the association between perceived parental bonds and maternal-fetal bonding in pregnant women, accounting for factors such as psychological distress, socio-demographic and obstetric characteristics.In this cross-sectional study, 1,177 pregnant women answered the Parental Bonding Instrument, the Maternal-Fetal Attachment Scale, State-Trait Anxiety Inventory (STAI-Y), and Beck-Depression Inventory (BDI-II).We found out that perceived maternal and paternal care had significant direct effects on maternal-infant bonding during the pregnancy period when controlling for some confounders, including gestational age and mother age among others. Such maternal and paternal perceived care effects were not mediated by levels of psychological distress, which in turn resulted to be a “borderline” significant predictor of prenatal attachment. Interestingly, the gestational age and the mother age emerged to have a significant and synergic nonlinear effect, suggesting the influence on the MFAS of the gestational age depends on the values of the mother age, and likewise, the effect of mother age on MFAS depends on the gestational week.This study expands our knowledge of the intergenerational transmission of attachment pointing out the effects of a woman’s perceived bond in relation to her parental figures during the development of the prenatal attachment process. Findings also suggests that parenting support interventions may have benefits that are realized across generations. The experience of pregnancy has a strong impact on women’s lives. It is a unique period that might produce specific difficulties for the future mothers, adapting to this challenge through positive and negative reactions . ConsideA key element that might be associated with prenatal attachment is the woman’s perceived bond in relation to own parental figures during her childhood and adolescence, denominated parental bond. Bowlby states that the mother’s psychological state during parenting is related to “a long history of interpersonal relations within her family of origin” , suggestFurthermore, during the transition to parenthood, which is a time of intense psychological change, women are also at risk for the onset of psychological distress. The World Health Organization reports that about 10% of pregnant women experience psychological distress, especially anxiety and depression that generally leads to adverse outcomes for early mother-child bonding (WHO). Prenatal anxiety, depression, and stress can result in pregnancy complications, as well as difficulties in the establishment of the mother-infant bond, which adversely affects the pregnant women’s attachment process, which is essential to the baby’s psychological development. Some authors suggested that psychological distress may compromise capacity to feel adequate in her new role as mother or be related with a general state of detachment that also affects her ability to bond with the fetus . AdditioThe study’s aim is to examine how parental bonding and psychological distress are associated with maternal fetal attachment in a broad sample of pregnant women. Our pre-analyses conjectures are reported in The study was authorized by the University of Calabria Ethics Committee (Protocol number: 0013005). The study was conducted in accordance with the Declaration of Helsinki. Data collection took place from 14 March and 25 April 2020 among pregnant Italian women. The study was conducted through an anonymous, web-based, cross-sectional survey developed with Google Forms, and was supported by two local non-governmental associations, the “Associazione di Volontariato Mammachemamme” and the “Movimento di Psicologia Perinatale”. The survey’s URL was sent to the participants through social media, emails, and advertisements in Italian prenatal and natal clinics. The inclusion criteria were as follows: willing to participate, having reading skills and language comprehension to complete the self-report questionnaire, no history of mental disorders or substance abuse and drug addiction. The intent of the study was explained to the participants, who gave formal consent and did not receive any reward.A questionnaire containing items about the mother’s age, civil status, educational level, disease history, number of children, gestational age, history of abortion, pregnancy complication was used to collect the socio-demographic and obstetrics data.Maternal–fetal attachment in pregnant women were measured through the Maternal–Fetal Attachment Scale (MFAS) . The MFAPrenatal bonding was measured through the PBI . The PBITo estimate levels of state and trait anxiety, the survey used is the State-Trait Anxiety Inventory (STAI-Y) . The iteDepression levels were measured through the Beck-Depression Inventory (BDI-II), consisting of 21 self-report items . This scSymmetric relationships among numeric variables were investigated by means of the Pearson correlation coefficients. The parental perceived bonds are represented by two pairs of variables for both mother and father, namely: the maternal/paternal perceived care (MPC and PPC) and the maternal/paternal perceived over-protection (MPO and PPO). To quantify their effects on the maternal-fetus attachment (MFAS), we ran a regression model for the expected value of MFAS as a function of MPC, PPC, MPO, and PPO, also including additional variables such as mother age, previous childbirth, gestational age and psychological distress (STAI-2 and BDI). Moreover, to assess if the parental bonds effects on MFAS were also partially “mediated” by the psychological distress, specifically the STAI-2 and BDI-II variables, we fitted a second regression model having the STAI-2 and BDI-II as a response and the same aforementioned factors as covariates. Taking the two fitted regression models as input, we carried out mediation analysis  to estimP-value was set at 0.05. All statistical analyses were done using the software R (version 4.0.5) and packages mediation , and the mean gestational age ranging from 5 to 41 weeks 26.28 ± 8.9. Most of the participants were married  and nearly half of them had University degrees (46.6%). With respect to pregnancy aspects, the 42,7% had previous pregnancies, the 26,6% reported history of abortion, and the 13,2% had pregnancy complication.The mean total score on the MFAS was 91.8, and the mean subscale score were: 16.6 (Differentiation of self), 19.2 (Interaction with the fetus), 20.4 (Attributing characteristics and intentions), 17.9 (Giving of Self), 17.7 (Role taking). The mean total score for STAI Form Y-2 and BDI-II was 43.9 and 12.4, respectively. 63.4% of women had no depressive symptoms, 18.9% had mild depressive symptoms, 14.2% had moderate symptoms and only 3.5% severe symptoms. On the Trait-Anxiety scores, 23.2% had mild trait anxiety levels, 31.1% had moderate levels and 28% had severe levels. Among the anxiety levels, out of 1,179 women 36.6% had mild state anxiety levels, 20.4% had moderate levels, and 7% had severe levels.p = 0.022) and paternal (p = 0.004) perceived care is significatively and positively associated with MFAS, sharing a somewhat similar effect on the response; on the other hand, no significant effect was found for the overprotection scores, i.e., MPO and PPO. Moreover, we found no evidence against linearity in the effects of MPC/MPO and PPC/PPO on the MFAS and also no relevant interaction terms between such variables were deemed to be significant, suggesting no synergic effect on the response.We fit a regression model including the MFAS score as the outcome variable and the parental bonds scores, namely MPC, MPO, PPC, and PPO. Also, socio-demographic/obstetric characteristics, depression symptoms, and trait anxiety were entered simultaneously as explanatory variables. Results reported in p-value (p = 0.059). Depression level (BDI-II score) appears not to be related to the fetus stimulus. To investigate the mediating role of STAI-form Y2 in the relationships between MFAS and MPC/PPC we ran a mediation analysis by fitting the “mediator” regression model having the STAI-form-2 as response and the same covariates of the outcome model  exhibiting a somewhat borderline but noteworthy me model : resultsWe found strong evidence that both MPC and PPC have a significant effect on fetus attachment. As a sensitivity analysis, we also checked for possible non-linear and synergic effects, but no evidence was found.p = 0.038), Differentiation of self from fetus (p = 0.044), and Interaction with fetus (p = 0.009); while PPC is a significant predictor of Role Taking (p = < 0.001) and Attributing characteristics to fetus (p = 0.024). Results are summarized in In addition, we repeated the regression analysis with all five MFAS subscales as outcome variables. Results showed that MPC is a significant predictor of Role Taking  and the log transformation for the gestational age. Interestingly, the gestational age and the mother age emerged to have a significant and synergic non-linear effect, suggesting the influence on the MFAS of the gestational age depends on the values of the mother age, and likewise, the effect of mother age depends on the gestational week. Non-linearity in both covariates was modeled The objective of this study was to evaluate the effects of perceived parental bonding on maternal prenatal attachment, after controlling for relevant psychological distress symptoms, and socio-demographic and obstetric variables. The main findings revealed that perceived maternal and paternal care both had significant direct effects on maternal–infant bonding during the pregnancy period, indicating that the pregnant women who perceived high parental care during their childhood and adolescence had positive maternal-fetal relationships. Psychological distress was considered as the observed variable that acts as a mediator in the model, however, the effect of parental care on MFA is not mediated by levels of anxiety or depression. Further, no significant relations were found between the perceived maternal/paternal control and MFAS scores. These findings accord with that of Another important finding was that state anxiety resulted to be a “borderline” significant predictor of prenatal attachment after adjusting for the other socio-demographic and obstetric information. We found that women who have a higher state of anxiety may experience a lower quality of maternal-fetal attachment. In accordance with the present results, previous studies have demonstrated that anxiety is one of the strongest predictors of poor psychological well-being in pregnant women and of lower quality of MFA . It is pIn the multivariable analysis, gestational age and the age of the woman appear to influence prenatal attachment. As expected, gestational age showed a positive association with MFA. These results corroborate the findings of a great deal of the previous works. It has been demonstrated that prenatal attachment behaviors increase with advancing gestational age and the latter is associated with a positive effect on the fetus such as thinking about her involvement in the dyadic interaction, and interaction and maternal planning . Hence, Some limitations deserve mention. The first limitation of the study is the lack of a representative group of at-risk pregnant women. The inclusion/exclusion criteria precluded some at-risk pregnant women from participating in the study as women with psychopathological disorders or women with a history of mental disorders or adverse experiences during the past years. Several studies detected that a history of mental health problems or adverse experiences prior to pregnancy is associated with a decreased quality of mother-fetus interaction . Thus, fIntergenerational transmission of parenting has been documented in different samples population studies and countries. However, previous studies have mainly focused on the mother-child attachment bond after birth. This study expands our knowledge on the effects of a woman’s perceived bond in relation to her parental figures during childhood and adolescence on the prenatal attachment process in a large population cohort of pregnant women. The results of this study indicate that maternal and paternal care parenting may affect the maternal-fetal bonding of the expectant mother positively. This heightens the hypothesis that parenting support and treatment may have advantages that are realized across generations. Further, by determining mothers’ attachment style and the status of maternal-fetal attachment during pregnancy, in time interventions and education could be planned for improving these interactions and consequently improve the mother-child attachment during and after pregnancy.francesco.craig@unical.it.Dataset will be shared in accordance with explicit external requirements. Requests to access these datasets should be directed to FC substantial contributions to the conception, interpretation of data for the work, and revising it critically for important intellectual content, and drafting the work. MG substantial contributions to the conception, interpretation of data for the work, and revising it critically for important intellectual content. PT final approval of the version to be published. VM performed the statistical analysis, interpretation of data for the work, and drafting the work. JC design of the work and drafting the work. AA and IM design of the work and acquisition of data. FT revising it critically for important intellectual content. ACe and ACo final approval of the version to be published. All authors contributed to the article and approved the submitted version.


Background: Mothers are not only the axis of an ecological subsystem for their children but are also capable of creating a significant emotional and psychological environment through constant and direct interaction. This leads to interactions and emotional connections with the children, supportive behaviors, and a long-term commitment to their upbringing and development. Aims: This study examined the relationship between maternal emotional intelligence (EI) and demographics on the availability of motor affordances in the home environment that are conducive to their child’s motor development. Methods: Mothers (N = 451) and homes of children aged 18–42 months were assessed using the Persian version of Affordances in the Home Environment for Motor Development-Self-Report (AHEMD-SR) and the Bar-On Emotional Intelligence Questionnaire. In addition, mothers’ physical activity (PA) experience and demographic data were collected. Results: Analyses indicated significant correlations between mothers’ education, level of PA, and income with EI and motor affordances. Conclusions: EI, PA experience, and select mother demographics were important to the availability of motor affordances in the home. One could also speculate, based on previous research, that such provision may affect the future motor development of the child. Future research should include a younger and more diverse population. Research clearly indicates that the environment plays a critical role in childhood development. That is, an optimal level of development occurs with a stimulating environment and strong contextual support; support that is rooted in the home. Whereas considerable past research supports the notion, contemporary inquiries, including reviews, demonstrate that the home environment plays a vital role in physical and mental development and well-being ,2,3. ConWithin the home, our interests are in the provision of affordances that promote child motor development. Founded strongly in Gibsonian theory, affordances are agents of and events in the environment that afford the individual potential for perception and action; action that results in learning and development of a skill and/or a part of the cognitive/musculoskeletal systems. Affordances include toys, apparatus, materials, availability of space, and stimulation and nurturing by parents (and others). In summary, the home environment has the potential to provide a plethora of opportunities that can be conducive to stimulating child motor development, especially at an early age ,9.Affordances in the Home Environment for Motor Development (AHEMD) for children 18 to 42 months of age [Over the last decade, a substantial body of research points to the observation that the level of motor affordances in the home may have a negative or positive impact on child motor development; that is, higher levels of affordance provision are significantly associated with higher levels of motor development, and alternatively, lower levels are related to poorer motor behavior ,12,13,14s of age ; the forUnderscoring our interests are the factors that underlie the level of affordance provision, in this case, the emotional intelligence (EI) of the mother. According to Mayer and Salovey , EI refeA review of research associated with the mother-child dyad clearly shows that the quality of the interactions between this dyad can both positively and negatively influence cognitive, language, motor, and social outcomes ,28. In cThis study involved 451 Iranian mothers with children aged 18 to 24 months. The average age was 27.82 ± 8.55 months (52% boys and 48% girls). They were selected using a multi-stage cluster sampling method involving selected health centers in four urban cities in Iran. Because of the COVID-19 virus presence at the time of this study, 36 centers were randomly selected from among the accessible urban health centers, of which only 19 centers accepted the invitation to participate. Participating mothers were sent, mostly via e-mails, the qualification criteria, participation materials, and consent forms provided by the health centers. After consent was received, mothers were sent weblinks to complete the EI and AHEMD questionnaires. Included with the weblinks was a brief explanation regarding how to complete the forms. This was carried out instead of a more direct face-to-face data collection due to virus restrictions limiting such exposure. For those mothers who preferred, phone calls and/or written materials were provided.The qualification criteria stated that mothers had to be at least 16 years of age, have a high-school equivalent diploma, have a child living with the parent(s) since birth, and the child had no mental or physical impairment. This investigation was approved by the Ethics Committee of Urmia University (IR.URMIA.REC.1400.009). Mothers were assured that all information would be confidential and any results would be published without family member identification.In addition to the EI and AHEMD questionnaires (described in subsequent sections), an online questionnaire accompanied the weblinks/and written materials for the collection of the mother’s age, occupation (employed or home caretaker), income, and PA experience. The AHEMD questionnaire asked questions about the child’s gender and age. PA was asked as a general question regarding the mother’s experience (past and present) with sports and/or a regular exercise routine. This was collected using a 5-option Likert scale: none (no experience history), less than one year, between 1 and 2 years, between 2 and 3 years, and more than 3 years.Bar-On Emotional Quotient Inventory (EQ-I) was used to assess mothers’ EI [The hers’ EI . The selhers’ EI . Others hers’ EI ,35, inclhers’ EI .Affordance in the Home Environment for Motor Development–Self-Report (AHEMD-SR) was used to evaluate the quality and quantity of motor affordances. The instrument was designed for children 18 to 42 months of age [The s of age . This ses of age . A totals of age ,18,37. Is of age .t-student parametric tests and one-way variance analysis (ANOVA) with follow-up analyses using the Bonferroni statistic. To gain insight on age, child age was categorized and analyzed into four groups: 18–23, 24–29, 30–36, and 37–42 months. In addition, structural equation modeling was used to map and determine the relationships between the mothers’ EI and AHEMD variables. The significance level was set at p < 0.05.Descriptive statistics were used to describe the data, frequency, mean, standard deviation, normality (Shapiro–Wilk test), and the parity of variances (Levene’s test). Pearson correlation tests, Spearman, and Eta were used to determine the relationships between the variables. To examine the effect of independent variables on the dependent variable, a simple and stepwise linear regression coefficient was used. Group comparisons were performed using SD = ± 8.55) and an age range of 18 to 42 months. A weak and significant correlation was obtained between total AHEMD score and age (p < 0.05). Among different dimensions of the AHEMD, the only significant relationship was observed between age and Toys  . The significant difference between the age and toys was associated with children in age groups of 18 to 23 months and 36 to 42 months (p < 0.001). Children aged 36 to 42 months had more toys than children in the other age groups, especially 18 to 23 months old. There was no significant relationship between the child’s age and the mother’s EI and its dimensions.Participants included 236 (52%) boys and 215 (48%) girls with an average age of 27.82 months (M = 32.37 ± 5.70). Results of the correlation between maternal age and total AHEMD showed a positive and significant relationship . Toys was the only dimension among other home dimensions that had a significant relationship with maternal age . There was no significant relationship between maternal age and the mother’s EI and its domains.Maternal age at the time of study ranged from 20 to 46 years (p < 0.05), and the difference between those values was significant . Employed mothers had higher EI than those not employed. When comparing employed and not employed mothers, of the five EI domains, two were significantly different, stress management  and general mood . That is, employed mothers had a better level of general mood skills and stress management than housewives. Furthermore, there was a significant relationship between the mother’s education level and EI .Sixty-six percent  of mothers were housewives, of whom 66% had a high school diploma and/or post-graduate education; of those, 70% had bachelor’s (38%) and 32% reported master’s/doctoral degrees, thirty-two percent (32%) were employed outside of the home. Statistical analysis showed that the correlation between a mother’s EI score and occupation was significant , with a significant difference . It appears that employed mothers were able to provide a richer environment of motor affordances. Furthermore, the AHEMD dimensions of Toys  and IS  showed a positive and significant correlation with mothers’ occupation. Regarding maternal education and AHEMD dimensions, there were significant differences with IS  and Toys . That is, as mothers’ education increased, IS and Toy availability increased. Mothers with postgraduate/doctoral education had the highest number of toys in the home. The only significant difference between IS and education level was with the two groups of mothers with bachelor’s and master’s/doctoral degrees (p < 0.05); the homes of higher-educated mothers provided more inside space.Complementing those findings was a significant relationship between total AHEMD score and maternal occupation . Typically, as mothers’ education level increased so did the economic status of the family. Relatedly, there was a significant relationship between total AHEMD score and family income level . In other words, mothers whose family income was higher revealed higher EI scores.Family income, according to national standards, was divided into three groups: low (36%), average (32%), and high (32%). To no surprise, comparative differences between income and mothers’ education level indicated a significant difference . According to the results of the linear regression analyses, PA experience accounted for 27% of the total AHEMD score. Post hoc tests revealed that mothers who had 1 to more than 3 years of experience had higher AHEMD scores than mothers who had less than 1 year. Within the AHEMD dimensions, the only significant relationship was with Toys  and the IS . EI results indicated significant relationships between PA experience and two domains: general mood  and intrapersonal skills .Regarding participation in physical activities, 40% responded with no ‘regular’ experience, 20% reported less than 1 year, 14% between 1 and 2 years, 9% 2 and 3 years, and 17% responded as more than 3 years. Results indicated that there was a significant relationship between level of experience and total AHEMD scores  between EI and total AHEMD, and a significant relationship between AHEMD and all EI domains except adaptability skills (y skills . In addi2R) was 0.03, which indicates that 3% of the changes in EI were related to changes in the AHEMD. Furthermore, the beta coefficient for total AHEMD was equal to 0.16, which shows that the ratio of change in EI with AHEMD was equal to 0.16. This means that a unit increase in the standard deviation of EI led to an increase of 0.16 in the standard deviation of total AHEMD.To investigate the effect of EI on AHEMD scores, linear regression analyses  revealedp < 0.001) in four stages. In the first stage, mothers’ PA experience (2R = 0.08) was included in the model as the best predictor of total AHEMD. In general, 16% (2R = 0.16) of the variance related to total AHEMD was explained only by mothers’ PA experience, income, age, and EI.Stepwise regression analyses were used  to deter2R = 0.14) of the AHEMD variance was related to the variance of PA experience, family income, maternal age, and EI. These results indicated that the most impactful variables on total AHEMD were family income, PA experience, maternal age, and EI.Next, to determine the relationships between the variables affecting total AHEMD, a structural model  was drawThis cross-sectional study was conducted to determine the effect of mothers’ EI and select mother demographics on the provision of motor affordances in the home environment; affordances that have been shown to promote child motor development. Our findings indicated that affordance provision increased with increasing maternal and child age, especially with Toys and IS (inside space). This result was in line with our expectations. An interesting note with the present data, mothers who had more than one child and completed their second child’s information for this study had greater levels of motor affordances, especially in the dimension of Toys. The reason for this could be due to the experience gained both in terms of the mother’s age and awareness of the needs of their second child.In the present study, mother demographics played a prominent role in the presence of motor affordances. We found that income, education, and occupation (employed outside the home/home caretaker) had a significant relationship with home affordance availability. We wish to note that the examination of mothers’ occupation in this context had not been previously reported. Of course, it should be noted that even home caretakers with higher education and a good level of family income also provided ‘adequate’ affordances. Therefore, in line with previous studies, higher family income and parental education are associated with the provision of richer home affordances, especially in the dimensions of fine- and gross motor toys ,29.Regarding our primary variable maternal EI and mother demographics, a few findings are worthy of note. First, employed and more highly educated mothers, who also had a good SES, had higher EI scores than home caretakers with less education and lower SES levels. Speculatively, several factors could account for the difference. Employed mothers, due perhaps to greater communication and presence in social environments, have more opportunities to exchange ideas and obtain additional care information ; therefoAnother novel variable we examined, PA experience, presented some interesting insight. Mothers who reported more experience, 1 year to more than 3 years, compared to no experience, provided a greater level of motor affordances. Speculatively, mothers with more experience in PA are more aware of the benefits and need for such, for themselves and their children. This idea is in line with the studies of Sugihara and colleagues  and MoriTotal EI alone explained the total AHEMD score. Regarding the specific EI characteristics, with the exception of interpersonal skills, all other domains  had a significant correlation with total AHEMD. Previous studies have reported that lack of control and lack of care for negative emotions and the presence of stress and anxiety lead to disruptions in the quality and quantity of toy affordances , and subAs noted earlier, research has established that there is a significant relationship between the level of home motor affordances and a child’s motor development ,16,47. WAll research encompasses some limitations, and this study is no exception. Although we studied a relatively large sample from four urban cities, we recommend an extension to the study of more diverse groups, including rural areas. Second, our study included the age range of 18 to 42 months. A considerable body of research on motor affordances has been conducted on younger children using the AHEMD-IS (infant version for ages 3–18 months). Finally, PA experience was asked in the form of a general question. It is recommended that the qualitative level and type of PA, and even physical fitness of both parents and its relationship with EI and AHEMD be investigated in future research. Finally, because of the COVID-19 virus presence at the time of this study, all questionnaires were completed online, therefore there was no data collection monitoring.The current study adds to an increasing body of evidence with our finding that maternal EI was related to the level of motor affordances in the home; the higher the EI, the greater the level of affordances. The overall effect was compounded by mothers’ PA experience, income, mother age, and education. Our findings underscore the conclusion of an extensive literature review by Yang and colleagues  noting t


We formulated and tested ensemble learning models to classify axial length (AXL) from choroidal thickness (CT) as indicated on fovea-centered, 2D single optical coherence tomography (OCT) images.Retrospective cross-sectional study.We analyzed 710 OCT images from 355 eyes of 188 patients. Each eye had 2 OCT images.The CT was estimated from 3 points of each image. We used five machine-learning base algorithms to construct the classifiers. This study trained and validated the models to classify the AXLs eyes based on binary (AXL < or > 26 mm) and multiclass  classifications.No features were redundant or duplicated after an analysis using Pearson’s correlation coefficient, LASSO-Pattern search algorithm, and variance inflation factors. Among the positions, CT at the nasal side had the highest correlation with AXL followed by the central area. In binary classification, our classifiers obtained high accuracy, as indicated by accuracy, recall, positive predictive value (PPV), negative predictive value (NPV), F1 score, and area under ROC curve (AUC) values of 94.37, 100, 90.91, 100, 86.67, and 95.61%, respectively. In multiclass classification, our classifiers were also highly accurate, as indicated by accuracy, weighted recall, weighted PPV, weighted NPV, weighted F1 score, and macro AUC of 88.73, 88.73, 91.21, 85.83, 87.42, and 93.42%, respectively.Our binary and multiclass classifiers classify AXL well from CT, as indicated on OCT images. We demonstrated the effectiveness of the proposed classifiers and provided an assistance tool for physicians. Myopia is a common disease among Asian people, and its incidence has increased worldwide. Holden et al.  estimateEyes with a spherical equivalence (SE) of less than -6.00 D were defined as having high myopia, and high myopia is correlated with axial length longer than 26.0 mm , 4. HighArtificial intelligence (AI) is being used in medicine. In ophthalmology, color fundus images are commonly used for machine training in disease diagnosis, such as for diabetic retinopathy (DR), , 17 age-In this study, we focused on the relationship between CT and AXL. Since OCT is a common exam in clinics for patients with retinal diseases, glaucoma, and cataract surgery, it is meaningful to access more information from the existed exam images. With SD-OCT images from eyes with different refraction status and AXL, we investigated the utility of machine learning algorithms for predicting AXL and proposed a multiclass classifier of AXL by means of the CTs . In thisThis retrospective cohort study adhered to the tenets of the Declaration of Helsinki. This study was approved by the Institutional Review Board of Fu Jen Catholic University Hospital (FJUH).Patients with OCT image findings taken from and who underwent AXL evaluation in CY Tsai’s and CJ Huang’s clinics in the ophthalmology department at FJUH at any period from Sep. 2017 to Dec. 2019 were included in this study. We collected comprehensive information for participants’ sex, age, body height, body weight, and best-corrected visual acuity , 30. PatSpectralis SD-OCT equipment  was used to evaluate CT in both eyes; OCT was performed in the daytime. Cross-sectional and longitudinal scanning was performed in each eye . The SD-The AXL of the eyes was evaluated by a non-contact technique by using a Lenstar LS 900 platform .This data set had 11 features , which wThis study trained and validated the classifiers, which predicted the class of AXL of each eye using binary and multiclass classifications. In binary classification, we classified eyes into AXL < 26 mm and AXL> 26 mm; in multiclass classification, we classified eyes into AXL < 22 mm, 22 mm> AXL < 26 mm, and AXL > 26 mm –34.In this study, we analyzed 710 OCT images from 355 eyes of 188 patients. However, 710 images are quite low for a CNN algorithm. An appropriate number of samples depends on the specific problem, and it should be tested for each case individually. But a rough rule of thumb is to train a CNN algorithm with a data set larger than 5,000 samples for effective generalization of the problem. Our previous study used data augmentation to increase this study’s image samples and utilized a CNN algorithm to construct the image classifier through OCT images. However, the image classifier obtains a low accuracy. For obtaining satisfactory results, this research does not use simple algorithms to construct the linear classifier and selects state-of-the-art or strong algorithms to construct the non-linear classifier. Therefore, the selected algorithms are BNN, SVM, RF, AdaBoost, and XGBoost. RF, AdaBoost, and XGBoost are also the ensemble learning.Essentially, ensemble learning algorithms feature the combination of several weak classifiers to form a strong one with bagging or boosting approaches. The bagging approach trains many individual models in a parallel way, and each model is trained by a random subset of the data. Boosting approach trains a bunch of individual models in a sequential manner, and each individual model learns from mistakes made by the previous model. The Ensemble learning algorithms obtain less bias, less variance, and better results than traditional machine learning in general. Friedman et al.  indicaten_estimators (the number of estimators), the n_estimators means the number of the individual model will be performed. Therefore, ensemble learning algorithms always spend much more time than BNN and SVM calculation time.The RF, AdaBoost, and XGBoost are based on the bagging, boosting, and hybrid bagging and boosting approaches. AdaBoost, one of the first boosting algorithms adapted to solve practical problems, uses multiple iterations to create a strong learner by iteratively adding weak learners. Gradient boosting, a generalization of AdaBoost, is one of the most powerful techniques for building predictive models. The main objective of gradient boosting is to minimize the loss function by adding weak learners using a gradient descent algorithm. XGBoost is an extension of gradient-boosted decision trees and has the following advantages: regularized learning, gradient tree boosting, and shrinkage with column subsampling. Since the used ensemble learning algorithms in this study always have the hyperparameter—feature standardization, data splitting, feature selection, hyperparameter Optimization, and Oversampling of Imbalanced Data.The processes of this study are exhibited in To reduce the training phase’s processing time, we standardized numerical features by removing their means and scaling to unit variance through the formula as follows.Feature with normalization = (feature – feature’s mean)/feature’s standard deviation.feature selection, hyperparameter optimization, and oversampling. Finally, the test set was used to evaluate all metrics of each set {algorithm, hyperparameters search method, oversampling method} in Evaluation step of process 2 in The 355 tuples in this imbalanced data were collected from 188 patients with 355 eyes. Each tuple represented a completely eyeball’s six choroidal thicknesses based on cross-sectional and longitudinal scanning images. This study used 3 methods: Pearson’s correlation coefficient (Pearson), variance inflation factor (VIF), and least absolute shrinkage and selection operator (Lasso) to evaluate and select the appropriate features based on the training set. In the training set, one tuple only contained one eye’s features. Therefore, the feature selection can purely evaluate the relationships of the features within one eye. The three feature selection methods were performed sequentially independently, and any feature detected as redundant or useless by any method will be removed in this step.r indicated the linear relationship between a given feature and class label. The VIF measured how substantially the variance of an independent feature was influenced by other independent features. If the VIF of the target feature was > 10, we eliminated the target feature. Lasso performs covariate selection by forcing the sum of the absolute value of the regression coefficients to be less than a fixed value, which forced certain coefficients to be 0. The order of importance of input features made the fitted model more interpretable. LASSO utilized the L1 penalty to select the most feature at once based on a given lambda value. Compared with LASSO, Elastic net used a penalty mixed L1 and L2 norms, and Elastic net is hard to obtain the clear order of importance input features.Pearson’s Finally, 100 different lambda values  with descending order were used in LASSO, and we only kept the lambda values that LASSO selection an additional new significant feature in S Each algorithm had its hyperparameters that need to be tuned because the appropriate hyperparameters were very different for the algorithm applied in a different dataset. That is, different hyperparameters will most influence the performances of an algorithm. The search scopes for consideration of hyperparameters for all algorithms in this study  were listed in Grid search searched the performances with all combinations of hyperparameters with the specific fixed values in their scopes. Random and Hyperopt searches selected the hyperparameters’ with the possible real numbers from the specific intervals; therefore, random search and Hyperopt search selected more floating values for the hyperparameters that were not listed in the grid search. The numbers of grid search and random search were the same. The speed of Hyperopt search was much slower than grid search and random search because Hyperopt analyzes and improves the values of hyperparameters after each iteration; therefore, the search number of Hyperopt was 1/2 that of grid search. In For each search in the three search methods, stratified fivefold cross-validation (CV) was used to evaluate the performance of the current hyperparameters. Although the fivefold CV will take a 5-times validation time than the holdout method, the trained model will not be easy to overfit for a specific validation set and reduce the bias and variance of the performance estimate.For each split of fivefold CV, we oversampled the training fold to avoid the imbalanced issue. The use of this technique increased the number of samples of the smaller-sized categories for the sample sizes to be consistent among all categories. The oversampled samples of smaller-sized categorized of the training fold appeared only in the training fold. This study used three oversampling techniques as follows.Random oversampling (ROS): Randomly sample the tuples in the categories of smaller sample sizes.x and its k-nearest neighbor samples xj. Select one individual xj and create a new sample based on the linear combination of xi and Synthetic minority oversampling technique (SMOTE): For the categories of smaller sample sizes, find a sample Adaptive synthetic sampling (ADASYN): ADASYN is a technique based on the SMOTE algorithm for generating synthetic data. The difference between ADASYN and SMOTE is that ADASYN implements a methodology that detects those samples of the minority class found in spaces dominated by the majority class to generate samples in the lower density areas of the minority class. ADASYN focuses on those samples of the minority class that are difficult to classify because they are in a low-density area.Finally, the numbers of training and validation folds with the three oversampling techniques and original data set are presented in Because the data set in this study was imbalanced and had many classes, accuracy alone was not sufficient to indicate the classifiers’ performance. Therefore, accuracy, recall (sensitivity), PPV (precision), NPV, F1 score, Specificity, and AUC were used for binary classification. For multiclass classification, this study used accuracy, weighted recall (sensitivity), weighted PPV, weighted NPV, weighted F1 score, weighted Specificity, and macro AUC where macro AUC is the macro average of multiple one-vs-rest AUCs. Five algorithms , three hyperparameter optimizations , and four oversampling techniques  were used to construct classifiers with training set based on the best hyperparameters obtained in Hyperparameter Optimization for binary and multiclass classifications. The numbers of training and test sets with the three oversampling techniques and original data set are presented in t-test by another person in our group.For evaluation of AXL prediction from human eyes, 2 ophthalmologists and two medical students were asked to predict AXL of the eyes by the 10 features . They were blind to the AXL during prediction, and the results were checked and compared with the results from AI algorithm with In this study, 710 OCT images of 355 eyes (172 left and 183 right) of 188 patients were collected. All patients had complete sex, age, body height, and body weight data in their medical records. In total, 87 (46.28%) men and 101 (53.72%) women participated. The average age was 66.49 ± 9.73 years, average body height was 159.8 ± 8.72 cm, and average body weight was 64.8 ± 12.1 kg . The aveP < 0.05). Age had the strongest correlation, followed by height, Choroid-CN, Choroid-LM, Choroid-CM, Choroid-LU, Choroid-LD, Choroid-CT, gender, and weight. Height and weight had positive correlations with AXL, and men had longer AXL, but the other features had negative correlation with AXL , Classifier 5 (AdaBoost with grid search and ROS oversampling), Classifier 6 (XGBoost with grid search and SMOTE oversampling), and Classifier 7 (XGBoost with random search and ROS oversampling) have different best metrics. Classifier 4 obtains the best PPV and Specificity of 92.21 and 93.37%. Classifier 5 obtains the best accuracy, weighted recall, and weighted F1 score of 88.73, 88.73, and 87.43%, respectively. Classifier 6 and Classifier 7 obtain the best macro AUC (93.51%) and weighted NPC, respectively.Among all metrics, F1-score is the main metric in this study because F1-score seeks the balance of Recall and PPV for the imbalanced dataset. In clinical application, it can help doctors utilize the ensemble learning with the balance of positive prediction and effective medical resource use. However, assessing a model with the best F1-score and poor other metrics is inappropriate. It is still very important to comprehensively consider all metrics. Based on Based on Based on The appropriate values of hyperparameters of classifiers in To compare the results of AXL prediction based on the 10 features between the proposed classifiers and ophthalmologists, we recruited 2 ophthalmologists and 2 medical students to predict AXL in binary and multiclass classification based on the same 10 features. In the results, the accuracy was 48.61–69.44%, PPV (weighted) was 61.50–76.08%, Recall (weighted) was 48.61–69.44%, F1 score (weighted) was 54.29–71.92%, NPV (weighted) was 38.77–53.71%, and AUC (macro) was 49.07–63.03%. The results were considerably less accurate than those from our developed classifiers in H0:pHuman≥pAI and H1:pHuman < pAI, where pHuman and pAI are the metrics of human performances and proposed classifiers, respectively. The comparison and test results are listed in To compare the AXL class prediction between the proposed classifiers and ophthalmologists, we recruited two ophthalmologists (OPHs) and two medical students to compare binary and multiclass classification based on the same test set with ten features (without AXL feature). Since the test set size is over 30, this study used the test of proportion to verify the performance of results. The null and alternative hypotheses are In In this study, we proposed that Classifiers 1–6 can predict AXL by means of patients’ age, sex, height, weight, and CT measured from OCT images. Studies have reported that CT is negatively correlated with AXL, and people with high myopia tend to have a thinner choroid –11. HoweRegarding myopia prediction, Varadarajan et al.  developer indicates the linear relationship between a given feature and class label. The p value indicates the probability that a feature is uncorrelated with the class label, per the method of Kowalski  complete experiments], thus enabled our model to have high accuracies.This study has several limitations. First, our sample size was relatively small, especially those with AXL < 22 mm or > 26 mm; the distribution of AXLs is also relatively imbalanced. Second, the process of collecting the 10 features was time consuming. Considerable time and effort were required to measure the thickness of the choroid of 6 positions from 2 OCT images of each eye and to collect data on sex, age, weight, and height of each of the participants. Among the features we recorded, AXL did not increase with age after adulthood, and weight may change without change of AXL; these potentially induced bias in our results. Third, the manual measurement of CT may cause bias or inconsistency. Future studies should address these limitations, and we expect to conduct more investigations using a larger data set on the classification and diagnosis of eye diseases which may be revealed by SD-OCT.We demonstrated the effectiveness of the proposed classifiers in classification prediction from medical data and provided an assistance tool for physicians.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 Fu Jen Catholic University Hospital, Fu Jen Catholic University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.CY-T and H-CL: conceptualization and writing – original preparation. H-CL: methodology and software. C-YT, H-YC, and C-JH: data collection. H-CL and P-HC: formal analysis. C-YT, H-YC, L-SW, and P-HC: writing – review and edition. C-YT: supervision. H-CL, L-SW, and P-HC: funding acquisition. All authors have read and agreed to the published 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.