The goal of the study was to assess the relationship between cardioprotective medications, i.e., beta-blockers, angiotensin-converting enzyme inhibitors (ACEIs), calcium channel blockers (CCBs), angiotensin II receptor blockers (ARBs), statins, acetylsalicylic acid (ASA), and periodontitis (PD). Background: Xerostomia increases the risk of PD and is a side effect of some pharmacotherapies. Information about the effect of cardioprotective treatment of periodontal status is scarce. Methods: We studied 562 dentate residents of Krakow at the age of 50 to 70 years. Information about treatment was collected using a standardized questionnaire. The pocket depth and clinical attachment level (CAL) were used to ascertain PD. Multivariate logistic regression was applied to assess the relation between cardioprotective medications and PD. Results: PD was found in 74% of participants. The range of cardioprotective drug use among participants was 7% (ARBs) to 32% (beta-blockers). After adjusting for age, sex, number of teeth, smoking, and education, ASA’s use was related to a lower prevalence of PD in all dentate participants (odds ratio (OR) = 0.63, 95% confidence interval (CI): 0.40–0.99). The use of ARBs and statins was found to be associated with a higher prevalence of PD in persons having ≥6 teeth (odds ratio (OR) = 3.57, 95% CI: 1.06–11.99 and OR = 1.81, 95% CI: 1.03–3.16, respectively). Further adjustment for CVD risk factors, history of coronary heart disease, and other chronic diseases did not attenuate the results. There was no significant relation between PD and the use of other cardioprotective drugs. Periodontitis (PD) is a chronic inflammatory condition that arises from bacterial factors inhabiting dental biofilm and calculus, resulting in damage to teeth and surrounding soft tissues . PD is rThe relationship between PD and cardiovascular disease (CVD) has been widely studied over the past few years ,7,8. TheIt is also well-known that xerostomia increases PD’s risk as saliva’s amount and composition are crucial first lines of defense against pathogens, with disturbances favoring oral infections such as caries and PD . AlthougWe hypothesized that prolonged cardioprotective medication use could negatively affect periodontal status. The goal of the present study was to assess the relationship between the use of cardioprotective medications, including beta-blockers, ACEIs, CCBs, ARBs, statins, ASA, and PD.The study was conducted in accordance with the World Medical Association Declaration of Helsinki. All participants signed an informed consent. The survey protocol was approved by the Bioethics Committee of the Jagiellonian University.This study was performed on a random subsample of 1008 persons (478 men and 530 women), between 50 and 75 years of age, from the 10,728 Polish participants of the Health Alcohol and Psychosocial Factors in Eastern Europe (HAPIEE) Project. Details of the methodology used in the HAPIEE study, which examined a representative sample of residents of Kraków, the second-largest city in Poland, have been published earlier ,30. A brBaseline information included data on health, lifestyle, diet (food frequency), socioeconomic circumstances and psychosocial factors. A short examination included measurement of anthropometric parameters, blood pressure, lung function, assessment of cognitive function, and collection of a fasting venous blood sample. Re-examination included collection of data on healthy aging, economic wellbeing, medical history, and current medication status by face-to-face interview . AdditioPeriodontal clinical parameters were measured for each tooth, except for the third molars. Probing was done on six tooth sites with a 0.25 N force using a periodontal Hu–Friedy probe (model PCPUNC157). Patients were classified according to the broadly used case definition of PD developed by the CDC Periodontal Disease Surveillance Workgroup, based on pocket depth measurements and clinical attachment loss (CAL). CAL (distance from the cemento-enamel junction (CEJ) to the bottom of the pocket/sulcus) was determined using the distance from the CEJ to the free gingival margin (FGM) and the distance from the FGM to the bottom of the pocket/sulcus . For theInformation on age, education , smoking status , history of chronic diseases, and current use of cardioprotective medication was collected using the standardized questionnaire . To asse2 were considered obese.Height and weight were measured according to the standard protocol. Participants with a body mass index (BMI) ≥ 30 kg/mAfter at least 5 min of rest, blood pressure was measured in a sitting position and on the right arm using an Omron M5-1 device. Three measurements in 2 min intervals were taken. The mean of the second and third measurements was used in the analysis. Participants were classified as having hypertension if their blood pressure was ≥140/90 mmHg ,34 or wet-test. Multivariate logistic regression was applied to determine which medications were significantly related to poor periodontal status (PD ≥ 6 and CAL ≥ 6 mm/periodontitis). The analysis was carried out in all dentate (at least one tooth) persons and repeated after restriction to persons who had at least six teeth  to meet the WHO recommendations for dental clinical examination and to follow the practice of the other studies [p < 0.05.Continuous variables were presented as means (standard deviation). The Shapiro–Wilk test was used to assess conformity with a normal distribution. Categorical variables were reported as absolute numbers and percentages, and the differences were tested using the chi-squared test. Differences in mean age and number of teeth were compared with the  studies ,38. StatOf the 1008 persons invited to participate, 909 (430 men and 479 women) underwent an oral examination. Excluded from the further analysis were 347 edentulous participants, among whom none had implants. The analysis was carried out in 562 dentate (one tooth at least) persons (268 men and 294 women). The analysis was then repeated after restriction to 514 persons (251 men and 263 women) who had at least six teeth . Sample selection recruitment and restriction are presented in The frequency of use of particular cardioprotective drugs was similar before and after restriction. Beta-blockers were the most frequently used  and ARBs were the least—about 7% in both groups .There was no significant difference in the proportion of participants with PD between participants with positive and negative history chronic diseases, which are the main indications for using cardioprotective drugs, neither in all dentate persons nor in persons with ≥6 teeth present. For a few participants, information on the history of chronic diseases was missing, so the analysis that used these data involved slightly fewer participants .The percentage of participants with PD using cardioprotective medications is presented in In the multivariate analyses adjusting for age and sex, all dentate participants using ARBs had greater than two and half times higher prevalence of PD (odds ratio (OR) = 2.66, 95% confidence interval (95%CI): 1.01–7.00); the relation was even stronger among persons with at least six teeth . After further controlling for education, smoking, number of teeth, and hypertension or heart failure, the relation between ARBs use and PD remained significant among participants with at least six teeth . In all dentate participants, the estimate of effect remained strong but was no longer statistically significant. Similarly, participants with at least six teeth who were using statins had a higher prevalence of PD by over 80% after controlling for age, sex, education, smoking, number of teeth. Further controlling for hypercholesterolemia, history of myocardial infarction, or his-tory of hospitalized coronary heart disease did not change the results materially . While not achieving statistical significance, the direction and estimates of OR were similar in all dentate persons .Finally, there was an inverse relationship between the use of ASA and PD  in all dentate participants. Adjustment for age, sex, education, smoking, number of teeth, and history of myocardial infarction or history of hospitalized coronary heart or hospitalized chronic osteoarthritis did not attenuate the relation. The direction and estimate of effect were similar in participants with at least six teeth but not achieving statistical significance .Adjustment for the history of other chronic diseases and obesity did not change results materially for ARBs, statins, and ASA. There was no significant relation between PD and the use of remaining drugs studied; however, beta-blockers, ACEIs and CCBs, but not diuretics, had estimates of effect tending to increase PD prevalence.In this study, we found a positive association between the use of cardioprotective medication, specifically ARBs and statins, and PD prevalence. The relationships were stronger with larger dentition. Conversely, the use of ASA was inversely related to the prevalence of PD. These relationships were independent of CVD risk factors and a history of chronic diseases, which usually indicate cardioprotective drugs.Porphyromonas gingivalis, a key pathogen occurring in the polymicrobial biofilm associated with chronic periodontitis [ARBs that block type 1 angiotensin II receptors on blood vessels and cardiac muscle are commonly used to treat hypertension and are considered safe, with no important side effects. There is no evidence that poor periodontal status is related to ARB use, to the best of our knowledge; however, our findings are in line with some previous observations. Several studies have shown a consistent increase in the prevalence of periodontitis in patients with hypertension or metabolic syndrome ,40, patidontitis . Some stdontitis ,46,47; hdontitis .The results on statins, however, might be surprising. Statins were found to decrease biomarkers of periodontal disease . Some evASA is a known nonsteroid anti-inflammatory drug that acts through reducing the prostaglandins, and the negative relationship between its use and PD has been known for a long time . Our resIt is also worth noting that, even while not achieving statistical significance, all of the drugs studied had estimates of effect tending to increase PD, with the exception of diuretics and ASA. This consistency in direction seems to warrant further studies in larger and various samples.Our study, due to its cross-sectional design, does not allow for any firm conclusion on causality. There are other limitations in the interpretation of our results. First, our analysis excluded 347 edentulous participants (with no implants), which was more than one-third of all participants who underwent a dental examination. Although in Poland, tooth loss is mostly due to caries, some excluded patients may have lost teeth due to advanced PD; therefore, the relationships between the use of cardioprotective medications and PD could be even stronger than reported. Further, periodontal indicators depend on the number of teeth and are more reliable if calculated in individuals with at least six teeth . We addrDespite the limitations mentioned above, the study has important strengths. It targeted a random sample of the inhabitants of the second-largest city in Poland, at the age at which most CVD incidents cased occur in Poland . We usedStatins are the most important drugs in the treatment of hypercholesterolemia. As the alternative for ACE inhibitors, ARBs are often recommended as the first-choice drugs in treating hypertension ,34. BothFinally, PD is considered a risk factor for CVD . HoweverThe use of ARBs and statins was found to be related to a higher prevalence of PD. The findings seem plausible but will need to be replicated in various settings, ideally with prospective studies to confirm the association. The inverse relation between the prevalence of PD and ASA’s use supports the postulated protective effect on periodontal tissues.


Emergency Department (ED) crowding is a pervasive problem, yet there have been few comparisons of the extent of, and contributors to, crowding among different types of EDs. The study quantifies and compares crowding metrics for 16 high volume regional, urban and academic EDs in one Canadian province.The National Ambulatory Care Reporting System (NACRS) provided ED presentations by adults to 16 high volume Alberta EDs during April 2010 to March 2015 for this retrospective cohort study. Time to physician initial assessment (PIA), length of stay (LOS) for discharges and admissions were grouped by start hour of presentation and facility. Multiple crowding metrics were created by taking the means, medians , and 90th percentiles of the hourly, ED-specific values. Similarly, proportion left against medical advice (LAMA) and proportion left without being seen (LWBS) were day and ED aggregated. Calculated based on the start of the presentation and the facility and for PIA and LOS. The mean, median, and 90th percentiles for the date and time ED-specific metrics for PIA and LOS were obtained. Summary statistics were used to describe crowding metrics.There were 3,925,457 presentations by 1,420,679 adults. The number of presentations was similar for each sex and the mean age was 46 years. Generally, the three categories of EDs had similar characteristics; however, urban and academic/teaching EDs had more urgent triage scores and a higher percentage of admissions than regional EDs. The median of the PIA-M metric was 1 h23m across all EDs. For discharges, the median of the LOS-M metric was 3h21m whereas the median of the LOS-M metric for admissions was 10h08m. Generally, regional EDs had shorter times than urban and academic/teaching EDs. The median daily LWBS was 3.4% and the median daily LAMA was about 1%.Emergency presentations have increased over time, and crowding metrics vary considerably among EDs and over the time of day. Academic/teaching EDs generally have higher crowding metrics than other EDs and urgent action is required to mitigate the well-known consequences of ED crowding. Emergency Department (ED) crowding occurs when “the demand for emergency services exceeds the ability of an emergency department to provide quality care within appropriate time frames” –3. Many ED crowding is believed to be influenced by multiple factors and in Canadian hospitals, the most important factor leading to ED crowding is the lack of in-patient beds for those presenting to the ED who need to be admitted  . The mulThere is a paucity of literature on the distribution of ED crowding metrics in high volume EDs, including differences among rural, urban community and academic hospitals. In Canada, high volume EDs are known to experience the highest crowding pressure . To addrThis retrospective cohort study used a population-based health administrative database from the province of Alberta, Canada during April 1, 2010, to March 31, 2015. This study was approved by the University of Alberta Health Research Ethics Board. The funding organization  had no input in the conduct and reporting of the study.Alberta is a Canadian province with > 4 million residents and a uniform single-payer health system –the Alberta Health Care Insurance Plan (AHCIP) –that provides medically necessary health care. The Government of Alberta is the custodian of all administrative databases used in our study.n = 5), urban (n = 8), and academic/teaching (n = 3). The academic/teaching EDs see adult patients exclusively. Adult presentations were extracted from the National Ambulatory Care Reporting System (NACRS). Patients, hospital staff, and the public were not involved in or aware of this research.The study population consists of individuals aged ≥18 years who presented to the high volume EDs  during the study period. Visitors to the EDs who were not residents of Alberta at any time during the study period or who were not registered with the AHCIP were not included in the analyses; generally < 1% of all records would be from non-residents of Alberta . The stuThe NACRS database provides information on the dates and times related to an ED presentations, triage level, and disposition status. The date/time variables included the date/time of registration, date/time of triage, date/time of physician initial assessment, date/time of disposition decision, and date/time patient left the ED. The start of the ED presentation was set to be the minimum of the registration and triage dates and times. The start of the presentation was used to define fiscal year, month of year, weekday/weekend, and time of shift . Triage level represents the urgency of ED care required by the individual and is based on the Canadian Emergency Department Triage and Acuity Scale (CTAS) , 12. TheThe NACRS database also provides demographic and geographic data collected at the time of the ED presentation. Age is provided as age in years at date of ED presentation. Sex is either male, female, or other, since other gender details were not collected in the database. The health zone of residence  are reported according to where the person lived at the time of the ED presentation.We used recommended ED crowding metrics  based onThe ED LOS was calculated depending on the disposition: it was calculated as the time from the start of ED presentation until the time the disposition decision for discharged patients or time the patient departed the ED for an in-patient unit if patient was admitted . For disFor each ED facility, all ED presentations that started within the same date and hour (e.g. 08:00–08:59) were calculated and hourly, facility-specific means, medians, and 90th percentiles for PIA and LOS were determined. This approach condensed the multiple individual patient PIAs and LOSs per hour into representative values per hour at each facility to produce the metrics. We refer to the hourly, facility-specific averages as metrics PIA-A and LOS-A for the PIA and LOS, respectively, to allow for easier presentation. Similarly, we use PIA-M and LOS-M to represent the hourly, facility-specific medians of the PIA and LOS, respectively, and PIA-90 and LOS-90 represent the hourly, facility-specific 90th percentiles of the PIA and LOS, respectively. To form day aggregated metrics, the facility specific proportion of LAMA and proportion of LWBS were used for presentations that started on the same date.An a priori protocol and analytic plan was created. Numerical summaries  and counts (percentages) describe patient demographics and ED presentation characteristics. Statistical analyses were conducted in R  .There were 3,925,457 presentations made by 1,420,679 adults to the high volume EDs for all conditions. Table The facility-specific hourly ED crowding metrics were calculated for the 16 EDs. Fourteen facilities were operational for the full 5 years while two urban EDs started at 7 am on January 14, 2013, and May 21, 2014 . Of the 3,925,457 presentations, 3,020,762 were used in the calculation of PIA metrics , 3,029,451 were used in the calculation of ED LOS metrics for discharged , and 580,280 were used in the calculation of ED metrics for admitted (45 presentations ending in admission had time the patient left the ED missing). Further, some facilities and hours had missing values because presentations with non-missing times did not meet the disposition requirements .The median of the PIA-M metric was 1 h23m across all facilities and hours, with presentations in the urban and academic/teaching EDs having a PIA-M of 19 and 28 min higher than the regional EDs, respectively  of presentations had PIA longer than 1 hour and 16.8% (506613) were longer than 3 hours , whereas the urban and academic/teaching EDs had longer medians for LOS-Ms, 3h29m and 4h36m Fig. .For the CTAS 1/2/3 levels, the presentations that ended in discharge had LOSs that were close to the median recommendation of 4 h by CAEP  but larger than the 90th percentile recommendation of 8 h . The performance against CAEP benchmarks remained relatively stable over time . For theThe LOS for presentations ending in admission were considerably longer than those ending in discharge. The median LOS-M for all EDs together was approximately 10 h  had ED LOS longer than the CAEP recommended median LOS of 8 h, and 39.7% (230101) had LOS longer than the CAEP-recommended 90th percentile of 12 h. Initially, the LOSs were becoming closer to the recommendations and then increased in later years eTable . The urbRelatively few ED presentations had a disposition that was classified as LWBS  and even less for LAMA . The median percentage of LWBS was 3.4% in the regional EDs, 3.7% for academic/teaching EDs, and 3.2% for urban EDs Table  for eachThis large population-based study described facility-specific hourly crowding metrics that have been considered indicative of ED crowding  and thatThe first important finding is that ED volumes continue to increase at all sites. The reasons for this observation are multi-factorial. While the annual Alberta population increased from 3.79 to 4.20 million over the study period and the number of ED presentations also increased (1.94 to 2.18 million), the crude rates were relatively stable at 512.4 to 519.8 ED presentations per 1000 population, suggesting that population growth during the study period contributed to ED volume increases , 16. TheDuring our study period, the CAEP recommendations were frequently exceeded, with urban and academic/teaching EDs more likely to exceed the recommendations. For PIA, 63% of the presentations were longer than the recommended median of 1 h. For presentations ending in discharge, presentations in the CTAS 1/2/3 levels were close the median recommendation for LOS; however, the CTAS 4/5 levels had larger LOS than recommendations. For presentation ending in admission, LOSs frequently exceeded recommendations. The pattern of increasing crowding in recent years, with times exceeding the recommendations in the urban and academic/teaching EDs is a concern.We observed important differences in crowding metrics between ED type. While PIA times were similar across ED types, the LOS for both discharged and admitted patients were higher in urban EDs and higher still in academic EDs. This observation may be related to the acuity and complexity of cases seen in academic centres, as witnessed by the higher CTAS scores at presentation, older age and the higher admission percentages. These observed differences also suggest that there are unique operational factors leading to ED crowding that differ among ED type that need to be addressed using site-specific strategies. For example, in academic EDs, consultation and admission processes that rely on hierarchical training team structures may disproportionately contribute to delays in ED and inpatient disposition decisions. Changing admission decision-making processes may be a strategy specific to academic EDs that can improve patient throughput and output. Finally, each ED and region has made efforts to reduce ED overcrowding, and the fidelity, effectiveness of these interventions may have influenced these results.Finally, examples of the consequences of ED crowding are being experienced across the province. In higher volume EDs, with higher acuity, and higher admission percentages, patients are more likely to leave prior to the completion of care. For example, LWBS patients is highest in academic/teaching facilities where PIA is also highest; these proportions “improve” in regional EDs and are best at urban EDs; however, they are never acceptable. In adults, LWBS is often association with frustration and prolonged delays . One couThe strengths of our study include a large sample size from population-based data sources in a geographically large area of Canada. In addition, ED charts are coded by medical record nosologists who are experts in using International Classification of Diseases (ICD) diagnostic codes. The study has several limitations. First, the coders rely on paper-based charts for coding, which are notoriously incomplete and difficult to read in EDs. Second, our results may not be generalizable to other areas of Canada or other jurisdictions with different health care systems. The ED crowding metrics were not tested against important patient outcomes , and we cannot conclude any consequences regarding the degree of overcrowding observed. There are, however, many examples of the negative consequences associated with ED overcrowding, and it would be hard to imagine these not occurring here. Finally, there may be errors in the documented times and some times were not available; however, broadly speaking, these errors are random and likely do not influence our results.Presentations to these urban and regional EDs in Alberta are increasing over time and out of proportion to population growth. Considerable variations in important metrics of ED crowding were observed across three ED categories, which further indicate that academic/teaching sites are under particular strain. Crowding in high-volume EDs in this province frequently exceeds national recommendations, and urgent actions are required to avoid the adverse consequences that portend overcrowding.Additional file 1: eTable S1. Percentages of presentations that exceed recommendations for all years and by fiscal year. eTable S2. Percentages of presentations that exceed recommendations by ED category for all years and by fiscal year. eFigure S1. Median and interquartile range  hourly, facility-specific median physician initial assessment (PIA) times by years and by ED category. eFigure S2. Percent of presentations from all ED that exceeded the CAEP recommendations for medians for physician initial assessment (PIA), length of stay (LOS) for discharges with CTAS 1/2/3, LOS for discharges with CTAS 4/5, and LOS for admissions by ED category and by fiscal year . eFigure S3. Percent of presentations from all ED that exceeded the CAEP recommendations for 90th percentile for physician initial assessment (PIA), length of stay (LOS) for discharges with CTAS 1/2/3, LOS for discharges with CTAS 4/5, and LOS for admissions by ED category and by fiscal year . eFigure S4. Median and interquartile range  for hourly, facility-specific median length of stay (LOS) for discharges by years and by ED category. eFigure S5. Median and interquartile range  for hourly, facility-specific median length of stay (LOS) for admissions by years and by ED category. eFigure S6. Median and interquartile range  of daily, facility-specific percent left without being seen (LWBS) and left against medical advice (LAMA) for all EDs and by ED category. eFigure S7. Median and interquartile range  for daily, facility-specific percent left without being seen (LWBS) by years and by ED category. eFigure S8. Median and interquartile range  for daily, facility-specific percent left against medical advice (LAMA) by years and by ED category.


To fill this vacuum, which might be at the basis of misdiagnoses or simply ignorance of chaperonopathies in patients who would benefit by proper identification of their ailments, we searched the sequenced human genomes available in public databases to determine the range of missense mutations in the single hsp60 gene. A total of 224 missense mutations were identified, including those already characterized. Detailed examination of these mutations was carried out to assess their possible impact on protein structure-function, considering: (a) the properties of individual amino acids; (b) the known functions of the amino acids in the human Hsp60 and/or in the highly similar bacterial ortholog GroEL; (c) the location of the mutant amino acids in the monomers and oligomers; and (d) structure-function relationships inferred from crystal structures. And we also applied a bioinformatics tool for predicting the impact of mutations on proteins. A portion of these genetic variants could have a deleterious impact on protein structure-function, but have not yet been associated with any pathology. Are these variants causing disease with mild clinical manifestations and are, therefore, being overlooked? Or are they causing overt disease, which is misdiagnosed? Our data indicate that more chaperonopathies might occur than is currently acknowledged and that awareness of chaperonopathies among medical personnel will increase their detection and improve patient management.Two chaperonopathies have been linked to mutations in the human  It belongs to the Group I chaperonins and, together with its co-chaperonin Hsp10 (mHsp10 in mitochondria), forms a macromolecular double-ring tetradecameric complex , whose objectives are to reveal novel genes implicated in heart, lung, and blood pathological conditions, using next-generation sequencing of human exomes; and the ClinVar database3, curated by the National Center for Biotechnology Information (NCBI) that collects data on genome variants and their impact on human health.A comprehensive search of known human 4), to assess the effects of hHsp60 gene missense mutations on protein structure/function and possible pathogenicity. PolyPhen-2 predicts the impact of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary parameters and providing three prediction outputs, i.e., “probably damaging”, “possibly damaging”, and “benign” , following the cross references found in the dedicated webpages of the UniprotKB database (P0A6F5 for GroEL and P10809 for hHsp60).5, loading as query the GroEL sequence and as subject the hHsp60 sequence, and using the algorithm parameters given by default.The pairwise sequence alignment was performed using the BLASTp suite of the BLAST alignment tool6 , and a single gap located at residue number 305 of the bacterial chaperonin . As showThe great similarity between the mHsp60 and GroEL monomers was evident also when three-dimensional models were compared .HSPD1 gene were found . The amino acids involved in missense mutations and belonging to the sequence that can be aligned with GroEL were visualized in proteins three-dimensional models , and highlighted in purple in the subject sequence (hHsp60 sequence) of the performed pairwise alignment . Only 16Five key inter-ring contacts in hHsp60 revealed by crystallography  involve The research conducted in the mentioned databases revealed that other potentially interesting missense mutations involve residues  with an unknown function in the human chaperonin. These residues maintain the same identity and/or localization in GroEL , 2A–I. TR221Q, N265S, and V287I are associated with spastic paraplegia. However, the prediction of pathogenicity by the bioinformatics tool was often contradictory with the disease-association for these mutations. The remaining mutations are not disease associated, and PolyPhen-2 predicted a possible damaging effect only for Y233C and E328V .D29G, V98I, and Q461E are hHsp60 missense mutations associated with hypomyelinating leukodystrophy and hereditary spastic paraplegia 13. These residues maintain the same identity  and locaHSPD1 missense mutations can cause Hsp60-genetic chaperonopathies as indicated by the fact that among the identified 224 variants, 27 were associated with a pathological condition. These are spastic paraplegias and hypomyelinating leukodystrophy, as mentioned earlier.The tight association between a defective hHsp60 and neurodegeneration is due to the great sensitivity of neuronal cells to mitochondrial dysfunction .However, despite the clear association between Hsp60 functionality, mitochondrial integrity, and neuronal tissue homeostasis, the role of the chaperonin, when abnormal, as etiologic-pathogenic factor in the development of neurodegenerative diseases is still not widely appreciated. This most likely leads to misinterpretation of clinical-pathological findings and erroneous diagnoses of a range of rare neurological disorders. In fact, except for the three well-known pathogenic mutants, there are no data on the potential pathological significance pertaining to the other variants.The reasons for this scarcity of information are unclear but lack of physician preparedness to identify chaperonopathies may be one, and the other could be the difficulty in the isolation and purification of the mitochondrial chaperonin, whose unstable structure can easily be affected by external factors, hindering investigations on its native structure, function and mechanisms of action . ConsequThese similarities strongly support the notion that also the functions of the amino acids located at equivalent positions in the two sequences are conserved. Noteworthy is the fact that the most conserved amino acids are those responsible for essential functions such as nucleotide binding, intra- or inter-rings contacts, co-chaperonin interaction, and substrate binding.In our work, detailed examination of 15 mutations was carried out to assess their possible impact on hHsp60 structure-function. The data were further enriched with the results obtained with PolyPhen-2, a bioinformatics prediction tool. In addition to the pathogenicity prediction, PolyPhen-2 also provides a multiple sequence alignment showing conservation of the residues involved in the considered mutation in many organisms. This type of information is of interest to appreciate the evolutionary-weighted conservation of these residues. However, in this work we focused only on the similarity between hHsp60 and GroEL.The mutations A34V, D35G, E129K, K133E, K473Q, and S488T occur in residues involved in the inter-ring contacts, and for this reason, they could compromise the formation and the stability of the double-ring tetradecamer, at least in the football complex, impairing the chaperoning function. Regarding the residue at position 34, involved in a symmetric hydrophobic interaction with the same residue from the opposite ring  both theGlu129 and Lys133 of hHsp60 full-length, corresponding to Glu103 and Lys107 in mHsp60, are linked by a salt bridge . Both thAlso S488, corresponding to S462 in mHsp60, which has been recently reported to be involved in inter-ring contacts , was fouOther potentially interesting missense mutations involve residues with an unknown function in human chaperonin. For this reason, we analyzed them considering the bacterial counterpart, in which these residues maintain the same identity and/or localization in the three-dimensional structure and have a known role.14–(mHsp107)2 football complex  wild-type mHsp60 complex . Met55 c complex . So, eve complex , also a  complex . Also th complex .Another interesting residue is Arg221, a basic polar amino acid located within a highly conserved peptide and aligned with the bacterial Arg197, which is one of the polar amino acids exposed to the central cavity, and is involved in a charged intra-ring contact  Braig e. The paiAlso Tyr223, a neutral polar amino acid with an aromatic side chain, is localized in the apical domain in the same highly conserved sequence containing Arg221 and corresponds to bacterial Tyr199 that is involved in substrate binding  Fenton . Thus, i14–(mHsp107)2 football complex  is associated with hereditary spastic paraplegia 13, as reported in the ClinVar database . Also, iAnother important function is the interaction among neighboring monomers that ensures the stability of both single and double-ring complexes. For example, Glu304 in GroEL is a residue involved in this type of interaction and in the substrate binding  and corrThe residues Asp504, Ala505, and Met506 are located in the nucleotide-binding pocket of hHsp60, as inferred from the solved crystal structures . The corWith regard to the three missense mutations in hHsp60 clearly associated with the development of neurodegenerative disease, i.e. D29G, V98I, and Q461E, we would like to report a brief analysis of their intrinsic characteristics in relation also to GroEL. These residues maintain the same identity and localization in GroEL. However, the functions of the corresponding amino acids in GroEL, i.e., Asp5, Val74, and Gln436, have not yet been defined . Asp29, A range of variants of the hHsp60 genes are present in the human genomes sequenced thus far. These variants can be sorted into three groups considering the probability of pathogenicity: mutants unlikely to have an impact on the structure-function of hHsp60 and, therefore, unlikely to be pathogenic, such as M55L and A34V; mutants bound to be pathogenic because of a predictable damaging impact on structure-function of hHsp60 that have already been found associated with disease, i.e. D29G, V98I and Q461E; and mutants with potential for disrupting structure-function of hHsp60, and so likely to be pathogenic. These latter include mutations such as E129K, K133E, N265S, and V287I which have been either associated or not with disease, but with an uncertain/conflicting interpretation. In this regard, the results obtained with the prediction tool were inconclusive since in many cases they disagreed with the impact of an amino acid substitution on protein structure/function and, consequently with the disease-association. Then, the automatic prediction results must be considered with caution.So far, only a few mutants have been directly associated with pathologies, even if many others affect sites in the chaperonin molecule that are critical for proper folding, oligomerization, and chaperoning function and could, therefore, cause disease. Two questions then arise: are there Hsp60 genetic chaperonopathies with mild clinical manifestations that go unnoticed in routine clinical examinations? and/or are there chaperonopathies showing clear clinical symptoms that are misdiagnosed? Both situations are possible, with some degree of probability, because chaperonopathies are not yet taught in medical schools in general and can, therefore, easily be overlooked in practice.It is hoped that specific preparation of medical professionals and their awareness of the existence of chaperonopathies will provide answers to the above questions. Furthermore, discovery of chaperonopathies and assessment of their true incidence starting at birth, or even prenatally, will contribute toward a better understanding of these sometimes-serious disorders and to the developing of specific therapies.https://www.ncbi.nlm.nih.gov/, NP_002147.2; https://www.ncbi.nlm.nih.gov/, NP_418567.1; http://www.wwpdb.org/, 4PJ1; http://www.wwpdb.org/, 3WVL; https://www.ncbi.nlm.nih.gov/clinvar/, HSDP1; https://gnomad.broadinstitute.org/about, HSPD1; and https://evs.gs.washington.edu/EVS/, HSPD1.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: AV gathered the data, materials, and references, wrote the manuscript drafts, and prepared the figures. EC, RA, and FC critically examined the data and references and contributed to the writing. AM critically examined the data and references and contributed to the discussion and the writing. AMG conceived the study, critically examined the data and materials, and contributed to the discussion and the writing. 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.


Jatropha curcas breeding. Thus, the present work aimed to apply the random regression technique and study its possibilities for the analysis of repeated measures in Jatropha curcas breeding. To this end, the grain yield (GY) trait of 730 individuals of 73 half-sib families was evaluated over six years. Variance components were estimated by restricted maximum likelihood, genetic values were predicted by best linear unbiased prediction and RRM were fitted through Legendre polynomials. The best RRM was selected by Bayesian information criterion. According to the likelihood ratio test, there was genetic variability among the Jatropha curcas progenies; also, the plot and permanent environmental effects were statistically significant. The variance components and heritability estimates increased over time. Non-uniform trajectories were estimated for each progeny throughout the measures, and the area under the trajectories distinguished the progenies with higher performance. High accuracies were found for GY in all harvests, which indicates the high reliability of the results. Moderate to strong genetic correlation was observed across pairs of harvests. The genetic trajectories indicated the existence of genotype × measurement interaction, once the trajectories crossed, which implies a different ranking in each year. Our results suggest that RRM can be efficiently applied for genetic selection in Jatropha curcas breeding programs.Random regression models (RRM) are a powerful tool to evaluate genotypic plasticity over time. However, to date, RRM remains unexplored for the analysis of repeated measures in  Jatropha curcas L. ranks among the most relevant crops for biofuel production [Jatropha curcas as an excellent alternative for renewable energy production [oduction ,2. Its hoduction ,3,4.It has a high oil content in its seeds up to 35%), with a high oil-to-biofuel conversion efficiency, compared to other species ,5. After%, with aJatropha curcas is a perennial plant that produces during several years, and in its breeding process, genetic selection has been carried out considering only one harvest [ harvest , several harvest  or sever harvest ,10.It is worth to highlight some specific issues in perennial plant breeding that affect genetic selection. Once repeated measures are taken in the same individuals over time, analyses must consider: the permanent environmental effects and genetic and residual covariance among harvests. Thus, for quantitative traits, genetic selection must consider several harvests to maximize the selective accuracy .Jatropha curcas breeding because they consider the genetic and residual covariance among harvests and allows fitting the genetic and non-genetic trajectories (plot and permanent environment) over time [Jatropha curcas breeding.In this context, random regression models (RRM) can be a very efficient alternative for repeated measures analyses in ver time ,12. Besiver time –15. ThusJatropha curcas were evaluated for grain yield (GY) trait (kg plant-1), in six harvests (2010 to 2015) ; and, hmax is time of the last harvest (2015).The time of the harvests must be scaled to range from -1 to +1 in order to use Legendre polynomials. The scaling formula is given below :tx=−1+2Yijkl is the ith individual  on the jth harvest  on the kth replication  on the lth plot ; Rk is the fixed effect of replication;. bM is the fixed regression coefficient fitted through the fifth degree of Legendre polynomials to the common average trajectory of progenies. The random effects, gim, pikm, and sik are the random regression coefficients for the Legendre polynomials of degree m for the genetic, permanent environment, and plot effects, respectively. ϕijm is the mth Legendre polynomial for the jth harvest from the ith individual; m is the fit degree, ranging from M = 0 to M = 5, of the Legendre polynomial for the genetic, permanent environment, and plot effects, respectively; and εijkl is the residual random effect associated with Yijkl.Variance components were estimated by restricted maximum likelihood , and geny is the phenotypic data vector; b is the vector of the effects of measurement-replication combinations (assumed to be fixed) added to the overall mean; g is the vector of the individual genetic effects (assumed as random); p is the vector of the permanent environmental effects (assumed as random); s is the vector of the plot effects (assumed as random); and e is the vector of residuals (random). X, Z, W and Q refer to the incidence matrices for these effects.In the matrix notation, the above model is described as follows:g~N, p~N, s~N, and e~N; where Kg, Kp, and Ks are the covariance matrices for genetic, permanent environment, and plot effects, respectively; ⊗ denotes the Kronecker product; I is an identity matrix with appropriate order to the respective random effect; and R refers to the matrix of residual covariances. Different residual covariance structures  were tested.In this model, LogL is the logarithm of the maximum (L) of the residual likelihood function, p is the number of estimated parameters, n is the number of observations, and r(x) is the rank of the incidence matrix of fixed effect.The polynomial order in random regression models was selected using the Bayesian information criterion (BIC) , as follLogLR is the logarithm of the maximum (LR) of the residual likelihood function of the reduced model .The significance of the genetic, permanent environment and plot effects was tested using the likelihood ratio test (LRT) , as follx refers to the genetic or permanent environmental or plot covariance matrices.Variance components estimates  of the genetic coefficient covariance matrix, aiming to evaluated the genotype x measurement interaction, was calculated by the following expression [mth element of the fth eigenvector of Kg, and Φm is the normalized value of the mth Legendre polynomial.The eigenfunction  between each pair of harvests were obtained by the following expression:i and j; i and j, respectively.The areas under the genetic trajectories (A), aiming to rank the clones, were obtained by the following expression ,25:A=μ+Statistical analyses were performed using the ASReml 4.1  and R 2 softwareAccording to the BIC, the best RRM was the one of order two for the genetic effects, order five for the plot effects, and order one for the permanent environment effects; with diagonal residual variance structure . Thus, tThe genetic variance was not constant through the harvests . The estJatropha curcas progenies  . The secJatropha curcas progenies. They ranged from -0.5879 to 2.0520, and the top ten families  were: 6, 70, 48, 16, 10, 1, 34, 39, 15, 29, and 54. The complete rank are presented in the supplementary material (ρg < 0.66) in the 2010–2012, 2010–2013, 2010–2014, 2010–2015; high magnitudes (0.67 < ρg < 0.89) in the 2010–2011, 2011–2014, and 2011–2015; and very high magnitudes (ρg > 0.90) in the remaining pairs of harvests . Considering the other random effects of the model , a total of 36 covariance components were estimated. The RRM are equivalent to the covariance functions and can be considered a reduced and simplified multiple-trait model, which allows the same parameters of interest  to be obtained, but with lower parameterization and with less computational effort [Among the various criteria for selection of models, the BIC is prominent, because it is a consistent criterion. The selected model fit diagonal residual variance structure  and the projection of these genetic values for a common age, for ordering and selection purposes. Besides that, Legendre polynomials have been used to model growth curves in perennial plant breeding ,28.Jatropha curcas families. Besides that, the plot and permanent environmental effects are statistically significant , i.e., they differ from zero. The significance of genetic effects shows the potential of this population and allow the selection of superior families, even with a restricted genetic basis explored in Jatropha curcas breeding in Brazil [According to the LRT, there was genetic variability among the n Brazil ,29. It in Brazil .The RRM is mainly focused on visualizing trajectories and covariance functions over time. Therefore, the variance components and genetic parameters can vary over the harvests. In this study, it is generally observed an increasing trend in the variance components and genetic parameters over time. Such pattern was also observed by ,10,30.Jatropha curcas [The individual heritability estimates decreased from the first to the third harvest. Then, there was an upward trend until the sixth harvest, which indicates that the third harvest is more affected by the environmental conditions. According to , the hera curcas ,30. BesiJatropha curcas genotypes are more sensitive to environmental variations in the early stages of growth [Upward trend in genetic variances and heritabilities along the time, are biologically consistent. Such trends can be related to the fact that f growth ,30, due f growth , which lf growth  for an aAccording to , the seld higher . This isd higher .Jatropha curcas.The genetic trajectories describe the genetic values of each family over time and encompass the six harvests evaluated in this study. The RRM can predict the genetic value for any family in any time (between the first and sixth harvest). The trajectories demonstrated that the families presented similar performance in the first harvests, which reveals that a precocious selection tends to be less efficient. The genetic correlations reinforce the inefficiency in earlier selection. The genetic correlations between the pairs of harvest presented very high values > 0.90) only between the last harvests. In addition [0 only beJatropha curcas [The RRM fitted through Legendre polynomials allows obtain the eigenfunctions and eigenvalues . Accordia curcas .Jatropha curcas progenies reinforced the presence of genotype × measurement interaction, once their trajectories are non-linear and intersect each other, which implies a different ranking in each harvest. In addition, the trajectories could also be interpreted as genetic variability. The more distant the genetic trajectories from each other, the more genetically distinct are the progenies [The genetic trajectories of the 73 rogenies .In this study, genotype ranking was performed based on the areas under the genetic trajectories. Therefore, genetic selection was based on the higher area under the genetic trajectories. The advantage of this strategy is that selection response can be predicted not only in the genotypic expression in any harvest but also in quantifying the environmental sensitivity of the trait through the genetic trajectories (robustness or responsiveness to changes in the environment). Besides that, it can be used for any number of harvests .Jatropha curcas breeding programs.The RRM can be used to help describing the observed phenotypic over time efficiently and allows genetic selection based on adaptability, stability and yield performance ,36–38. TS1 TableP.D. Gen: polynomial degree for the genetic effect; P.D. Plot: polynomial degree for the plot effect; P.D. Perm: polynomial degree for the permanent environment effect; DF: degrees of freedom; LogL: logarithm of the maximum of the restricted likelihood function; Gen. P.: total number of genetic covariances estimated; Plot P.: total number of plot covariances estimated; Perm. P.: total number of permanent environment covariance estimated; Res. P: total number of residual covariances estimated; and BIC: Bayesian information criterion. The selected model by BIC was indicated in bold.(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


The frequency of BPSD  and the living conditions  were related to their use of care resources. Particular BPSDs, such as anxiety or restlessness, throwaway food, aggressive behavior, tearing of clothes, and sexual harassment of patients were related to the caregivers’ use of care resources (p < 0.01). Health professionals have to evaluate the patients’ BPSD and identify the caregivers’ essential needs. Individualized medical care and BPSD-related care resources should be provided for patients and caregivers for taking off their care burden and improving patient care.This study was to evaluate the utilization of long-term care service resources by caregivers of patients with dementia (PWD) and to determine affecting factors. In this cross-sectional study, a total of 100 dyads were enrolled and caregivers responded to the questionnaires. We found 40% of caregivers not using any care resources. Between those caregivers using and not-using care resources, we found differences ( The world’s population is rapidly aging. Aging-related decline in physical and cognitive functions, especially dementia, creates a growing healthcare burden. The 2019 report of Alzheimer’s Disease International (ADI) estimated 50 million people in 2018 have dementia worldwide. By 2050, the number likely will rise to 152 million. A new case of dementia occurs in the world every three seconds. The global cost of the disease is about USD one trillion a year, and the cost is estimated to double by 2030 [The main problem of dementia is cognitive dysfunction and the resulting deterioration in memory, orientation, judgment, calculation, abstract thinking, attention, and language. With reference to Behavior and Psychological Syndrome Dementia (BPSD), the functional disorders include agitation, personality change, delusions or hallucinations, aggression, wandering, sleep disturbance, and repetitive behaviors. The progression of these symptoms requires not only economic and social impacts in caring people with dementia (PWD), but also has detrimental effects on the well-being of caregivers ,2,3,4. RThe average time duration for caring PWD ranges from 8 to 12 years . Home isp = 0.89) or care burdens (p = 0.47) did not reach statistical significance [However, a number of studies reported that these services do not translate into practical benefits as much as expected ,26,27. Aificance . In shorMost studies have evaluated the severity of dementia patients based on the number and frequency of occurrences with BPSD. In addition to the frequency of BPSD, our present study further investigated which symptoms of BPSD are related to caregivers’ viewing of required care service resources. The aims of the study were three-folds: (a) to evaluate the utilization of long-term care service resources for caregivers of PWD; (b) to identify the relationship between the characteristics of patients and caregivers, the BPSD of care-recipients, caregivers’ burden, social support and the use of long-term care service resources; and (c) to explore the factors affecting caregivers in using long-term care service resources.This is a cross-sectional study. Purposive sampling was applied, based on clinical diagnoses, to those patients with mild to moderate dementia. Clinical Dementia Rating (CDR) scores were between 1 and 2, and their family caregivers were serving at the neurologic and psychiatric outpatient departments of a medical center located at Xitum district (urban/moderate income) in central Taiwan. Based on physicians’ referrals, we distributed questionnaires to a total of 100 dyads . The inclusion criteria were: main caregivers caring patients daily for more than 4 h, or were family decision-makers; caregivers were blood relatives or in-laws, aged 20 years or over; able to communicate in Mandarin or Taiwanese; and agreed to be interviewed. We excluded those in employment relationships. During the outpatient appointment, two trained researchers explained the study aim and contents of the questionnaire to both the patient and caregiver after the clinical examination. Data were collected by structured questionnaires and interviews of ~30 min.To evaluate behavior and psychological symptoms of patients, participants were asked to complete the Dementia Behavior Disturbance Scale (DBD). To understand their care burden, social support network and the use of service resources, they were also asked to complete three additional questionnaires: Caregiver Burden Inventory (CBI), Functional Social Support Scale (FSS), and the Use of Long-Term Care Service Resources Scale. Questionnaires were translated from English to Chinese, with reliability and validity verified.The scale was designed by Baumgarten et al. in 1990 , consistHere we adopted the “Chinese Caregiver Burden Inventory, CCBI” from Kuo et al. (2014) , based oThis is based on the social support concept of Thoits (1982)  and tranTailored to the aim of this study, a total of 19 care service resource items were listed according to the service resources of the long-term care policy announced by the Ministry of Health and Welfare . They inWe recorded demographics data of PWD patients including gender, age, marital status, education level, religions, current living conditions, and other diseases if applicable. The demographic data of caregivers included gender, age, marital status, religion, education level, employment status, relationship with patients, living conditions (live or not with patient), number of years caring patients, co-caregivers, financial status, and self-rated health status.The study was approved by the Institutional Review Board (IRB) I and II of TVGH . Participants all signed the informed consent.p < 0.05 was considered statistically significant. Data were analyzed with IBM SPSS software version 22.0.Descriptive statistics were applied to demographic data as well as the number, percentage, average, and standard deviation (SD) for each scale. The same wording as appeared in the open-ended questions was summarized and displayed with frequency and percentage. Inferential statistics including t-tests, chi-square tests, and ANOVA analyses were applied to assess differences between the demographic data/score of each questionnaire and the use of long-term care service resources. A Pearson’s correlation coefficient was used to determine the correlation between continuous variables and the frequency of use of long-term care resources. Logistic regressions on the use of long-term care resources and respective variables were interpreted using the odds ratio (OR). All statistical tests were two-tailed, and We collected a total of 100 questionnaires fully completed without missing information. For PWD patients, 52% were women vs 48% men, with an average age of 81.0 ± 9.8 years, mostly married (59%); the main education level was elementary school (55%) and 17% were illiterate, 45% of patients were Buddhist/Taoist, 83% were living with spouses and/or children or grandchildren, and 38% had other chronic diseases such as diabetes and hypertension (details shown in The average care burden on the caregivers was 57.0 (SD = 12.4), with the highest score in time burden , and the lowest score in emotional burden . The social support score for caregivers was averaged at 41.3 (SD = 9.7), with the lowest score in the information support  .Regarding the use of long-term care service resources, 40% of caregivers had never used them. Reasons for not using the resources were as follows: “not sure whether they fulfill the criteria to use those service resources” (38.2%), “never heard of the resources” (20.8%), and “not required” (19.4%). Regarding “the best way to care for dementia patients”, 62.5% caregivers responded, “care at home by family or others”, and only 17.3% caregivers responded “24-h care nursing home”.p < 0.05), anxious or restless, throwaway food, aggressive behavior, tearing up clothes, sexual harassment (p < 0.01) . The top five behaviors responded in the questionnaire were: repeating the same theme; losing and misplacing things; sleeping a lot during the day; repeating the same action; and waking up at night for no reason. Analysis of variance showed that the use of long-term care service resources was significantly related with BPSD symptoms. These symptoms were hoarding for no reason, urinary incontinence, verbal or physical aggression, refusing others’ help with their hygiene, fecal incontinence, breaking out and getting lost, screaming for no reason ( < 0.01) .p < 0.05) between caregivers using and not using long-term care service resources , and BPSD of the PWD both showed statistically significant differences (esources .p < 0.05) between the age of the caregivers and BPSD of patients. That is, the younger the caregiver (Pearson correlation coefficient of −0.253), and the more frequent the BPSD (Pearson correlation coefficient 0.245), the higher was the frequency of using long-term care services resources (p < 0.01) with caregivers’ burden with a Pearson correlation coefficient of −0.464. That is, the more frequent the BPSD, the greater the caregivers’ burden. Burden on caregivers and social support of them were not related to the frequency of using long-term care service resources (p > 0.05).Taking into account the frequency of using long-term care services resources, we found significant correlations , and 3.519 times the increase in the probability of using long-term care service resources while caregivers were not living with patients compared to living with patients .Logistic regression analyses showed that long-term care service utilization was significantly affected by the frequency of patients’ BPSD and the living conditions of caregivers . On averWe studied PWD caregivers in their use of long-term care service resources and their affecting factors. We found 40% of them not using care service resources. Particular care-recipients’ BPSD , caregivers’ health status, and living with patients or not, affected significantly the caregivers‘ use of the care service resources. Furthermore, we found the frequency of BPSD and caregivers not living with patients increased the caregivers’ use of such care service resources.Most caregivers are known to be unpaid women staying at home, typically spouses and daughters-in-law of the patients ,6,10. ThOur current study showed that caregivers not living with patients had a greater probability of using long-term care service resources than those living with patients. “The younger the caregiver, the higher the frequency of care resource utilization” indicated that younger caregivers are better able to search for information , and to Caregivers of PWD are basically in a full-time engagement ,2. Not oPrevious studies have reported that BPSD is one of the most critical factors contributing to the care burden ,9,10,15,We found that the low utilization of long-term care service resources by caregivers of PWD (particularly the long-term care services related to dementia) is likely due to the poverty of information available on related services. The caregivers were “not sure whether they fulfill the criteria” and “never heard of the resources,” demonstrating the importance of service information acquisition by the caregivers. The availability of resources affects the willingness of caregivers to utilize care resources . Long-teWe found two important factors including patients’ BPSD and caregivers not living with the patient influence the long-term care service resources used, especially regarding certain problem behaviors and psychologic symptoms that could embarrass caregivers more and increase their burden. A larger/nationwide study for generalizability, and a stratified sampling database will be needed to strengthen our present results. This is a cross-sectional study, and caregivers had to recall the BPSD occurred in the past before filling out the questionnaire. Memory bias was unavoidable. A longitudinal research study in the future could help with data accuracy.The study found BPSD, especially certain problem behaviors and psychologic symptoms, could more embarrass caregivers and increase their burden. Health professionals have to evaluate the patients’ problem symptoms and identify caregivers’ essential needs exactly. Appropriate individualized medical care should be provided and BPSD related long-term care service resources need to be referred to PWD and caregivers to take off their burden and improve the quality of care for patients with dementia.


Fatigue is a kind of non-specific symptom, which occurs widely in sub-health and various diseases. It is closely related to people's physical and mental health. Due to the lack of objective diagnostic criteria, it is often neglected in clinical diagnosis, especially in the early stage of disease. Many clinical practices and researches have shown that tongue and pulse conditions reflect the body's overall state. Establishing an objective evaluation method for diagnosing disease fatigue and non-disease fatigue by combining clinical symptom, index, and tongue and pulse data is of great significance for clinical treatment timely and effectively.In this study, 2632 physical examination population were divided into healthy controls, sub-health fatigue group, and disease fatigue group. Complex network technology was used to screen out core symptoms and Western medicine indexes of sub-health fatigue and disease fatigue population. Pajek software was used to construct core symptom/index network and core symptom-index combined network. Simultaneously, canonical correlation analysis was used to analyze the objective tongue and pulse data between the two groups of fatigue population and analyze the distribution of tongue and pulse data.P < 0.05), on the contrast, correlation analysis of tongue and pulse in the sub-health fatigue group showed no statistical significance.Some similarities were found in the core symptoms of sub-health fatigue and disease fatigue population, but with different node importance. The node-importance difference indicated that the diagnostic contribution rate of the same symptom to the two groups was different. The canonical correlation coefficient of tongue and pulse data in the disease fatigue group was 0.42 (The complex network technology was suitable for correlation analysis of symptoms and indexes in fatigue population, and tongue and pulse data had a certain diagnostic contribution to the classification of fatigue population. Fatigue is a state in which the body cannot initiate or maintain a certain intensity of activity, or manifest a pathological dysfunction during the initiation or maintenance of voluntary activity. It is a physiological manifestation of body's self-regulation, and a pathological result of certain diseases . FatigueSub-health status is defined as the decline in vitality, physiological function, and adaptation capacity, but in general not meeting the diagnostic criteria for clinical or sub-clinical diseases , 8. It hIn the diagnosis methods of Traditional Chinese Medicine (TCM), tongue and pulse diagnoses always play an important role in clinical diagnosis and treatment. Tongue and pulse diagnoses are comprehensive diagnostic methods based on body's overall state, suitable for comprehensive evaluation of body's functional state, and have become an important objective basis for health status evaluation and syndrome diagnosis . HoweverComplex network is a basic framework with high topological abstraction. Further analysis of the network through classification, screening, and other analytical methods can mine the potential rules of many clinical data. Complex network is used in the analysis of basic rules of TCM , networkDespite the progress made in current research on fatigue, there are still many problems that need to be solved. For example, studies on fatigue are relatively simple. It is essential to study the correlation of fatigue symptoms and do the combined analysis of fatigue symptoms and indexes. Besides, analysis on objective tongue and pulse data of fatigue is mostly independent. To address the above problems, in this study, 2362 physical examination population were divided into healthy controls, sub-health fatigue group, and disease fatigue group. Complex network technology was used to screen out core symptoms and Western medicine indexes. Through constructing the core symptom and index network and the core symptom-index combined network, analyzing the network structure to establish the distribution of fatigue symptoms and indexes. Simultaneously, canonical correlation analysis method was used to get the associated relationship between tongue and pulse data of disease fatigue and sub-health fatigue population. Based on symptom, Western medicine index, and tongue and pulse data, this study tried to explore the characteristics of different fatigue population from different dimensions.All the 7025 people were selected in the Medical Examination Center of Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine from Jul. 2015 to Dec.2018. The most common diseases in fatigue population mainly include hypertension, diabetes, hyperlipidemia, and fatty liver, other diseases, such as coronary heart disease and cancer due to the lack of patients, they were not included. A total of 361 sub-health fatigue and 1529 disease fatigue population were further selected.Four well-trained clinicians completed the diagnosis according to the diagnostic criteria of the disease. The Health Status Assessment Questionnaire  and Information Record Form of Four Diagnosis of Traditional Chinese Medicine (Copyright No.: 2016Z11L025702) designed by the sub-health research group of the "863 Plan" was used to investigate fatigue syndrome. Patients with fatigue symptom were defined as disease fatigue population, those who had no obvious positive indexes in Western medicine, H20 score was between 60 and 79, and with fatigue symptom were defined as sub-health fatigue population, and those who had no obvious positive indexes in Western medicine, H20 score was between 80 and 100, and without fatigue symptom were defined as healthy controls.The overall flow diagram of this study was shown in Fig. The four-diagnostic scale of TCM included 25 categories and 256 subitems. The symptoms and signs were classified as none, mild, and severe with 0, 1, and 2 points. We used Tongue and Face Diagnosis Analysis-1 instrument (TFDA-1) (software copyright registration No.: 2018SR033451) and Pulse Diagnosis Analysis-1 instrument (PDA-1) (Patent No.: ZL201620157027.6), which independent developed by the National Key Research and Development Program to collect the clinical tongue and pulse data. Besides, clinical Western medicine indexes mainly include 191 items such as blood routine, urine routine, liver and kidney function, tumor markers, electrocardiogram, and imaging examination. Considering fatigue had no specific indexes, the existing Western medicine indexes were auxiliary. For example, anemia fatigue patients were often associated with decreased hemoglobin, cancer fatigue patients were often associated with abnormal tumor markers. It was necessary to combine specific symptoms in specific diseases for comprehensive analysis and judgment. The tongue and face diagnosis equipment and the analysis interface were shown in Figs. The color parameters of tongue image in Fig. 1 was the main amplitude, h3 was the heavy wave front wave amplitude, h4 was the dicrotic notch amplitude, h5 was the gravity wave amplitude, t1 was the time value from the start point to the crest point of the main wave, t4 was the time value from the start point to the dicrotic notch, t5 was the time value from the dicrotic notch to the endpoint, t was one pulsating period, and w was divided into w1 and w2, w1 was 1/3 height of the main wave, w2 was 1/5 height of the main wave.The parameters of sphygmogram in Fig. Using Python3.7 to make data arrangement, and established the symptom and Western medicine index data sets, respectively. A total of 494 symptoms and indexes were collected, including 254 symptoms of TCM and 240 Western medicine indexes. The data sets were binarized. The positive TCM syndromes were recorded as "1", and negative TCM syndromes were recorded as "0". Negative qualitative data of Western medicine index were recorded as "0", positive data including weak positive (+) and strong positive (++ or +++) were recorded as "1", quantitative data in the normal range were recorded as "0", higher than or lower than normal range were recorded as "1".According to the data characteristics in this study, the improved node contraction method was used to analyze the network nodes quantitatively. Node contraction was the integration of k nodes connected to the node with this node, replace the k + 1 nodes with a new node, and the edges that were previously associated with k + 1 nodes were now associated with the new node. After nodes with high importance were shrunk and fused, the whole network's connection would be closer, and the aggregation degree would increase. This method's basic idea was to shrink the nodes in the network one by one and then compare the network aggregation degree changes to rank the importance of nodes. The improved node contraction method  comprehedij was the shortest distance between node Vi and node Vj in the network. Wij was the weight between node Vi and node Vj. The node importance was expressed by IMC(Vi), which was defined as in formula (i) was the aggregation degree of the weighted network after contraction of node Vi.In the above formula, entclass1pt{minimaVi, Vj, Wij], indicating the existence of an edge with a weight of W from node Vi to node Vj. To better demonstrate the interaction between nodes, the symptom and index pairs were divided by the triad's maximum weight to obtain the normalized weight value.In this study, the improved node contraction method took the degree, betweenness, and edge weight of nodes, which was basically consistent with the purpose and requirement of each node's importance. In this paper, the sum of edge weight was used as the point weight to obtain an undirected weighted network. Triple was an improved form of adjacency list, and many network data were represented in the form of triples. A triple could be thought of as a three-column matrix, with each row in the format of [MATLAB (R2016a) software was used to process the binary data, and the core symptom and index data were selected according to the importance of node. Selected the top 10 data to construct the network and do analysis by Pajek (Pajek 64 5.08) software. The networks were output after editing each node's color and label and adjusting the node position manually.P value < 0.05 was considered statistically significant.SPSS (Version 25.0) software was used for statistical analysis. Continuous data with normal distribution were presented as the mean and standard deviation, and those with abnormal distribution were presented as median and upper and lower quartiles. The categorical variables were expressed as counts and percentages. Analysis of Variance (ANOVA) was performed for data that normal distribution and homogeneity of variance among groups, Kruskal–Wallis H test was performed for non-normal distribution data. All the tests were two-tailed, and a In this study, researchers from Shanghai University of Traditional Chinese Medicine completed all scales and tongue and pulse collection. All researchers were medical professionals in TCM or integrated TCM and Western medicine. Moreover, all researchers have been trained in standard operating procedures to ensure consistency and accuracy in interpreting data collection results. Each study participant was interviewed by at least two professional researchers and supervised by at least two senior physicians to ensure data collection consistency and authenticity and reduce the measurement bias.There were 742 people in the healthy controls, 361 people in the sub-health fatigue group, and 1529 people in the disease fatigue group. The patients in the disease fatigue group were mainly hypertension, diabetes, hyperlipidemia, and fatty liver. The statistical analysis of baseline characteristics of the healthy controls, sub-health fatigue, and disease fatigue groups were shown in Table P < 0.01), and age was statistically significant in the disease fatigue group compared with the sub-health fatigue group (P < 0.01).From the result, we could see that there were many more males than females in the three groups, actually the total number of people who participated in medical examinations, males were higher than females, the reason might be that there were more males than females in routine physical examinations in the area where the hospital was located, and males might pay more attention to routine physical examinations. Age and BMI were statistically significant in the sub-health fatigue group and disease fatigue group subjects compared with healthy controls , and then used Pajek software to draw the core symptoms network. The network was shown in Fig. As the total network had many nodes and complex network relationships, its core nodes' relationships could not be well described. Therefore, it was necessary to select core nodes according to the importance of nodes IMC software to detect outliers or extreme values. Individuals with outliers or extreme values in tongue or pulse data of the three groups were excluded, although this reduced the sample size to some extent, it ensured the accuracy of the results. Finally, 551 people were included in the healthy controls, 252 in the sub-health fatigue group, and 1160 in the disease fatigue group.P < 0.05), tongue characteristic parameters were mainly affected by TB-Cb, TB-b, TB-H, and TC-Cb, the canonical correlation coefficients were − 0.435, 0.431, 0.429, and − 0.374, respectively, P < 0.05. Pulse characteristic parameters were mainly affected by h1 and h1/t1, the canonical correlation coefficients were 0.388 and 0.378, respectively, P < 0.05, as shown in Fig. P < 0.05), tongue characteristic parameters were mainly affected by perAll, TC-Cr, TB-Cr, TB-Cb, TB-b, and the canonical correlation coefficients were − 0.723, 0.697, 0.649, − 0.603 and 0.590, respectively, P < 0.05. Pulse characteristic parameters were mainly affected by h4, h4/h1, h3/h1, h3 and w2/t, the canonical correlation coefficients were − 0.621, − 0.609, − 0.507, − 0.480 and − 0.446, respectively, P < 0.05, as shown in Fig. Canonical Correlation Analysis verified the overall correlation between one set of variables and another. The results showed a certain correlation between the tongue and pulse data in healthy controls and the disease fatigue group. The correlation coefficient of tongue and pulse data in healthy controls was 0.475 (Fatigue is an important early warning signal of abnormal health status. It should be treated in time to prevent it from further developing into more serious diseases. At present, there are two main reasons for the difficulties in fatigue research. Firstly, the mechanism of fatigue is complex, and there is still a lack of diagnostic criteria for fatigue. Secondly, there is a lack of effective fatigue evaluation models . Modern In this study, complex network technology was used to screen out the main symptoms and indexes of fatigue patients and the interaction between symptoms and indexes. Studying the interrelationship between fatigue-related symptoms contributed to further determine the direction of diagnosis of fatigue-related diseases. Headache, chest distress, and xerophthalmia were more significant in sub-health fatigue population. Headache and chest distress were generally manifested as qi stagnation syndrome, and xerophthalmia was the common clinical manifestation of jinye deficiency syndrome. Wiry pulse, greasy coating, and dizziness were more significant in disease fatigue group. The clinical significance of wiry pulse is mainly about liver and gallbladder disease, pain, phlegm and retained fluid, consumptive disease, and stomach gas decline. The clinical significance of greasy coating was phlegm-damp, phlegm and retained fluid, and dyspepsia. These two symptoms were consistent with common pathological manifestations of the disease. Furthermore, dizziness was the concomitant symptom of hypertension, hypoglycemia, anemia, and cancer. Basophil, platelet distribution width, percentage of monocyte, hemoglobin, hematocrit were blood routine item, the value of PH of urine and uric acid are routine items of urine examination, abnormal of these two indexes mostly indicate the abnormal renal function, and BMI mostly reflects human metabolism, so it can be seen that abnormal blood routine, renal function, blood pressure, and basic metabolism are more common in patients with fatigue.Associated analysis of symptoms and indexes can better explore the nature of diseases , 44. In Fatigue as a comprehensive performance of the whole body, it was necessary to analyze the relationship of indexes. The canonical correlation analysis was used for the combined analysis of tongue and pulse data. Canonical correlation analysis of tongue and pulse data showed that the healthy controls' correlation was stronger than that in the disease fatigue group. In contrast, the correlation coefficient between canonical variables and all tongue and pulse variables in the disease fatigue group was greater than that in the healthy controls. The reason might be that there are many kinds of diseases in disease fatigue group while the healthy controls were relatively single. The tongue and pulse in the healthy controls tended to be more stable, and its characteristics were relatively stable. For example, the healthy controls' tongue was generally reddish tongue, thin white tongue coating, and the pulse was usually normal pulse. The tongue and pulse in the disease fatigue group might be diversified due to different diseases. Patients' tongue could present as purple-red tongue, bluish-purple tongue, yellow greasy tongue coating, white greasy tongue coating, etc. Their pulse could be different forms of wiry pulse, tight pulse, slippery pulse, uneven pulse, etc. The tongue and pulse abnormalities of disease fatigue population destroyed a certain stable correlation of the health state and tended to a certain partial correlation.This study still has some limitations. Firstly, there are many kinds of diseases in this study, which did not conducive to interpreting the results. In the future, specific diseases will can be refined to analyze the relationship of symptom-index and the tongue-pulse data. Secondly, complexion spectral data can be added based on tongue and pulse data. Integrating more objective indexes that can objectively evaluate fatigue will be more productive to analyze its phenomenon and mechanism. Besides, this study still lacks treatment guidance and intervention for fatigue population, which will be improved in the future.In summary, this study constructed the fatigue-related symptom networks and symptom-index networks, analyzed the data relationship of tongue and pulse in fatigue population, and revealed the distribution rule of symptom and index, the tongue and pulse data in different fatigue population. It provided an objective basis for establishing the data evaluation of fatigue state, and we are looking forward to establishing a fatigue evaluation method based on objective data of tongue and pulse in the future.