Aneuploidy, a condition caused by an imbalance between the relative dosages of chromosomes, generally produces a novel phenotype specific to the molecular karyotype. Few techniques are currently available for detecting the molecular karyotypes of aneuploids in plants.Based on this imbalance in chromosome dosage, a new approach (referred to as ‘SSR-qPCR’) combining simple sequence repeat (SSR) markers and quantitative real-time PCR (qPCR) has been developed and utilized to detect some common aneuploids irrespective of heterozygosity. We screened 17 specific SSR markers covering all loquat linkage groups and redesigned 6 pairs of primers for SSR markers that can detect loquat chromosome aneuploidies. The SSR-qPCR detection results obtained for hybrid progeny and open-pollination progeny of triploid loquat showed diagnostic accuracies of 88.9% and 62.5%, respectively, compared with the chromosome preparation results.SSR-qPCR can detect loquat aneuploids and be used to construct the entire molecular karyotypes of aneuploid individuals. Therefore, this method offers a novel alternative for the detection of chromosome aneuploidies. Datura trisomies results in a different phenotype, depending on which type of chromosome has trisomy [Arabidopsis thaliana. Some aneuploids are useful for crop production. Guava, pear and loquat aneuploids have been studied in relation to rootstock selection for dwarfing [Aneuploidy can result in partial genome duplication, which involves the imbalance between the relative dosages of chromosomes . Aneuplo trisomy . Henry e trisomy  demonstrdwarfing –9. Moreodwarfing –12. TherA. thaliana have been detected by measurement of the relative allelic ratios of the heterozygous genotype [Malus, with particular emphasis on aneuploidy, via detection of the types of heterozygous genotypes and the corresponding frequencies of occurrence [Many techniques have been widely used for the detection of chromosome copy number changes in aneuploid individuals. The unquestionable and unique merit of classic cytogenetics and fluorescence in situ hybridization (FISH) is their abilities to produce complete karyotypes and reveal balanced major rearrangements; however, these techniques are time consuming and labour intensive . Flow cygenotype . The detcurrence . Both ofcurrence . Microsacurrence , 22, butEriobotrya japonica (Thunb.) Lindl.) originated in Southwest China, and among the 20 species belonging to the genus Eriobotrya, only loquat is used for commercial fruit production [Loquat  can be used to construct the entire molecular karyotypes of aneuploid individuals of Twenty-three loquat lines with different ploidies were used as the materials in this study Table : 2 SichuGenomic DNA isolation was performed based on the cetyltrimethylammonium bromide method of Roche et al. . After iA total of 209 SSRs derived from loquat (16), pear (42), apple (144), peach (5), apricot (1) and plum (1) were used in this study (Table 2+ free), 1.5 mM MgCl2, 0.0375 mM each dNTP, 0.25 µM each of the forward and reverse primer, 50 ng of genomic DNA and 1 unit of Taq DNA polymerase . The amplification was performed using a C1000 Touch PCR System thermal cycler (Bio-Rad) with the following temperature conditions: 94 °C for 2.5 min, followed by 35 cycles of 94 °C for 30 s, 60 °C for 30 s and 72 °C for 30 s and a final step of 72 °C for 10 min. The PCR products were mixed with 15% loading buffer , and 0.05% bromophenol blue and xylene cyanol). Three microliters of each mixture was loaded into 8% denaturing polyacrylamide gels (7 M urea) in 1× TBE buffer . The gels were run at 220 W for 50 min and silver stained [SSR reactions were performed in a final volume of 20 μL, containing 2.0 μL of 10× PCR buffer  and 0.3% pectinase . After 3 h, the enzyme solution was removed, the apical meristems were soaked in deionized water for 10 min, and placed in Carnoy’s solution. At last, apical meristems were dispersed on slides with tweezers and dried over the alcohol burner flame. Chromosomes were colorized with 5% Giemsa staining, dried in air, and visualized under a microscope .Chromosomes at mitotic metaphase were prepared from root tip materials according to methods reported by Chen et al. . Root tiqPCR was performed using a StepOne real-time PCR instrument (ABI Corporation). The PCR amplifications were performed in a 10 μL reaction system containing genomic DNA (50 ng), 0.2 µM each primer, corresponding ROX Reference Dye I (0.2 μL), and 2 × NovoStart® SYBR qPCR SuperMix Plus (Novoprotein Scientific Inc.) (5 μL). The PCR began at 95 °C for 1 min and then progressed to 40 cycles of 95 °C for 20 s and 60 °C for 1 min. This programme was followed by 95 °C for 15 s and 60 °C for 1 min. The fluorescence was measured at 60 °C for 40 cycles.We first obtained the PCR product amount  ratios of the 17 LGs in known euploid strains as controls. Known aneuploid strains and unknown loquat strains were then examined and compared with the controls. A limited number of ΔRn values were expected according to the following aneuploidy and euploidy ΔRn scale: 1 , 0.5 (2x − 1 karyotype), 1.5 (2x + 1 karyotype), 0.75 (4x − 1 karyotype) and 1.25 (4x + 1 karyotype).StepOne v2.1 software (ABI Corporation) was used to calculate the ΔRn values of each segmental duplication. Each LG had one SSR marker, and the fluorescence intensity of each SSR marker in a single material was calculated. The ΔRn values were calculated based on the method of Zimmermann et al. . To the Our goal was to obtain 17 amplified stable SSR markers covering all loquat LGs. Of all the 209 SSR markers derived from loquat, pear, apple, peach, apricot and plum, 102 SSRs  were applicable to loquat, of which 28  showed polymorphism  karyotype variation. The means and standard deviations of ΔRn of the bottom, middle and top of the exponential phase are shown in Table To verify the method for the detection of aneuploid karyotype variation, 9 hybrid offspring of Q24× ‘Huabai No. 1’, 7 open-pollination progeny of the triploid loquat A313 and 9 open-pollination progeny of the triploid loquat A322 were obtained, and these included a total of 22 aneuploids and 3 euploids. We detected their chromosome numbers using conventional cytological methods   [Fragaria × ananassa) [Actinidia. arguta var. giraldii [Similar to conventional cytological methods, SSR-qPCR has several advantages: reliability, low sample demand, ease of performance, and ability to produce precise data. The PCR analysis can directly generate data for analysis without the need for gel electrophoresis or other processing steps, which saves considerable time. Notably, karyotyping through conventional cytological analysis is difficult for some species, such as omosomes . Kiwifruomosomes –53. Lianry small . These fbadense) , octoplonanassa) , and thegiraldii . In addiSimilar to microarray-based comparative genomic hybridization (array-CGH), SSR-qPCR can be used to detect changes in fluorescence intensity caused by chromosomal abnormalities, and changes in the chromosome copy number in the whole-genome can be detected through just one experiment. Array-CGH detects abnormalities in the initial chromosome copy number of a sample and requires the use of different fluorescent labels. The method is complicated and extremely expensive in terms of chip cost; therefore, array-CGH is not suitable for large-scale experiments . SSR-qPCMoreover, qPCR directly quantifies the fluorescence intensity, which is directly proportional to the amount of PCR product amplified. The examination of ΔRn values might be more accurate than a method that relies solely on CT values . TherefoA. thaliana [Detection using the SSR-qPCR method is based on the amount of the PCR product amplified. Some studies based on QF-PCR have shown that small changes in the length of the sequences do not affect the amount of the PCR product amplified. For example, the sequence of Chr13 differs from that of Chr6 by 3 bp but this difference does not affect the trisomy detection of Chr13 by QF-PCR . In addithaliana . The peathaliana , 16. TheOur method is more suitable for homozygous alleles than heterozygous alleles. The 17 SSR markers used in this study produced single bands and were not polymorphic. We found that these 17 SSR markers were relatively conserved in 23 known loquat strains. However, these 17 SSR markers might not be suitable for some unknown loquat varieties. The genetic heterozygosity of fruit trees is generally high. In this study, the accuracy of SSR-qPCR for 16 open-pollination progeny of triploid loquat strains (A313 and A322) was only 62.5%, whereas the accuracy of SSR-qPCR for 9 hybrid offspring of Q24× ‘Huabai No. 1’ was 88.9%. SSR markers are randomly distributed throughout plant genomes, and the flanking regions of SSR markers are generally relatively conserved single-copy sequences. SSR markers are short tandem repeats. Tandem repeats are usually found in pericentromeres, centromeres or telomeres, and the tandem repeats near centromeres are more conserved than those in other locations . Tandem Prunus mume [We were able to detect the complete molecular karyotypes of aneuploid individuals using the SSR-qPCR method, which requires a high-density genetic linkage map. SSR markers are codominant, polymorphic, and suitable for the construction of high-density genetic maps . At presnus mume , sweet onus mume , jujube nus mume , pineappnus mume , and kiwnus mume , as wellnus mume , have beMalus, aneuploidization of chromosomes mainly occurs in 15 LGs, excluding LG1 and LG8 [The impacts of aneuploidization on speciation and evolution have long been ignored. In humans, trisomy is mainly found on chromosomes 21, 18, 13, 11, X, and Y , 16, 18. and LG8 . We founAneuploidy greatly exceeds euploidy in crosses between a triploid and a diploid parent –109. In Aneuploidy can initiate special gene expression. For example, dwarfing tree systems, male sterility, multiple petals, tolerance of drought or cold or resistance to disease can result from ‘super-dominant expression’ due to chromosomal gain or ‘pseudo-dominant expression’ due to chromosomal loss in aneuploids –12. TherIn summary, SSR-qPCR can be used to construct molecular karyotypes of loquat aneuploids. This study provides the first demonstration that a strategy using SSR markers and qPCR can be used to successfully describe complete molecular karyotypes of aneuploids. This technique provides a novel alternative for the detection of chromosome aneuploidies. Marker-assisted breeding using SSR markers with stable amplification will effectively accelerate the breeding of loquat aneuploids. The influences of aneuploidization on speciation and evolution have previously been ignored. The greater genetic diversity in aneuploids than in euploids might provide a broader basis for natural selection. Aneuploids and euploids should be more accurately and strongly applied in studies of breeding, genetics and evolutionary biology. This is the first study to provide reliable molecular evidence for aneuploidy in triploid progeny. This study provides a reliable strategy for further exploration of aneuploidy and the enhancement of polyploid breeding programmes for other species.Additional file 1: Fig. S1. Seventeen pairs of SSR primers detected in 23 known loquat strains by polyacrylamide gel electrophoresis.Additional file 2: Fig. S2. qPCR melting curves for the 17 pairs of SSR primers.Additional file 3: Table S1. ΔRn values for the 17 pairs of SSR primers in 22 euploid loquat strains. Table S2. ΔRn values for the 17 pairs of SSR primers in 9 hybrid offspring of Q24 × ‘Huabai No. 1’. Table S3. ΔRn values for the 17 pairs of SSR primers in 16 open-pollination progeny of triploid loquat strains (A313 and A322).


Transthoracic echocardiography (TTE) and cardiac magnetic resonance (CMR) are current standard for assessing aortic regurgitation (AR). Regurgitant fraction (RF) can also be estimated by Doppler examination of the left subclavian artery (LSA-Doppler). However, a comparison of AR grading scales using these methods and a TTE multiparametric approach as reference is lacking. We evaluated the severity of AR in 73 patients , with a wide spectrum of AR of the native valve. Using a recommended TTE multiparametric approach the AR was divided in none/trace (n = 12), mild (n = 23), moderate (n = 12), and severe (n = 26). RF was evaluated by LSA-Doppler  and by CMR phase-contrast imaging ; the grading scales were then calculated. There were a good correlation between all methods, but mean RF values were greater with TTE compared with LSA-Doppler and CMR . Mean differences in RF values between methods were significant in the groups with mild and moderate AR. Grading scales that best defined the TTE derived AR severity using CMR were: mild, < 21%; moderate, 22 to 41%; and severe, > 42%; and using LSA-Doppler: mild, < 29%; moderate, 30 to 44%; and severe, > 45%. RF values for AR grading using TTE, LSA-Doppler and CMR correlate well but differ in groups with mild and moderate AR when using a recognized multiparametric echocardiographic approach. Clinical prospective studies should validate these proposed modality adjusted grading scales.The online version of this article (10.1007/s10554-020-01844-2) contains supplementary material, which is available to authorized users. Transthoracic echocardiography (TTE) is widely recognized as non-invasive gold standard for quantification of aortic valve regurgitation (AR). The severity of AR can also be evaluated with the estimation of regurgitant fraction (RF) by flow measurement in ascending aorta using cardiovascular magnetic resonance imaging (CMR). Recently, was also validated the assessment of the RF by examination of the left subclavian artery (LSA) velocity contour by pulsed Doppler as an alternative method , 2.However, there is still no final consensus in which scale should be used with these modalities to define AR severity. Several studies compared AR severity by CMR vs. angiography and/or echocardiography. But the cut-off values reported are variable , reflectintegrative approach using multiple qualitative, semi-quantitative, and quantitative measurements [All proposed echocardiographic qualitative, semi-quantitative, and quantitative methods exhibit significant limitations. They are not feasible in a percentage of patients with AR, principally, due to inappropriate acoustic windows, interposition of valve tissue, and the inherent difficulty in correctly identifying the flow convergence zone. Hence, current echocardiographic guidelines strongly recommend an urements , 11.multiparametric approach has not been evaluated. Consequently, we sought to analyze which grading scale of CMR and LSA-Doppler derived RF best correlates with mild, moderate, and severe grades of AR, using a multiparametric echocardiographic approach as a reference standard.A comparison of the RF measurements of above mentioned methods with a recommended TTE We prospectively enrolled 73 patients , 61 with a wide spectrum of AR of the native valve referred to our center for evaluation of the pathology (AR group), and 12 patients with non or trace AR on TTE with clinical indication for a CMR study other than heart valve disease (control group). Patients were eligible if they had sinus rhythm during the study. Those with an associated cardiac valve lesion more than moderate, with aortic coarctation, or with typical contraindications for CMR imaging were excluded.multiparametric approach the AR was quantified and divided in to 3 groups: mild (n = 23), moderate (n = 12), and severe (n = 26). We evaluated also the RF derived from the Doppler examination of the LSA  and from CMR phase-contrast quantitative flow . RF measurements of all methods were then compared within the groups.Usually, patients underwent CMR imaging, LSA-Doppler, and TTE within 12 h. All baseline characteristics were prospectively collected. Based on a recommended TTE The systolic and diastolic flow profiles of the LSA were evaluated by use of pulsed wave Doppler ultrasound (3.4–9 MHz linear probe). Patients were examined in a supine position with a subclavicular approach. Higher-frequencies (> 7 MHz) were used for assessment of the morphology, and lower-frequency (< 7 MHz) was preferred for Doppler examination. LSA was documented with gray-scale imaging and color Doppler to rule out relevant stenosis. The depiction of the LSA was modified to align the Doppler angle parallel to the vector of blood flow and to avoid the Doppler signal of the adjacent vein. The sample volume was placed just nearby the origin of the LSA. Patients with vascular shunts of the left upper arm were excluded. As previously described , the outAll TTE were performed by experienced echocardiographers using commercially available ultrasound machines  equipped with M5S or 4V1c 2D TTE probes. All recordings were stored digitally for offline analysis. Left-ventricular (LV) volumes and ejection fraction (EF) were calculated using the biplane Simpson disk method. Doppler measurements were evaluated as the average of at least three cycles. An effort was made to perform the flow convergence (PISA) method, from apical views or, in case of eccentric jets, from parasternal long-axis views. The AR severity was graded according to a recommended TTE “multiparametric approach” , 11, con2; the slice thickness was 8.0 mm. The typical temporal resolution of the cine b-SSFP sequences was 30–25 ms depending on the heart rate. The imaging plane for the through-plane phase-contrast flow measurement was placed in the ascending aorta approximately 10 mm above the aortic valve and positioned perpendicular to the flow direction. On a coronal image of the aorta together with the 3-chamber view the CMR operator checked that the image plane was truly perpendicular to the aortic flow direction. To avoid aliasing, velocity encoding was individually adapted, starting at 200 cm/s, and if aliasing occurred, the maximum velocity was increased by 50 cm/s steps until aliasing disappeared. Image data acquisition was gated to the ECG signal with a temporal resolution of 35 phases per cardiac cycle and acquired during a 12–15 s breath-hold. Outlining the region of interest within the aortic lumen for each cardiac phase, the instantaneous flow volume (cm3/s) was calculated and graphically displayed over the entire cardiac cycle.All CMR examinations were performed in our cardiology department on a 1.5-T MRI system  equipped with a 28-element array coil with full in-coil signal digitalization combined with optical transmission. All scans were accomplished without sedation. Image data acquisition and subsequent analysis were carried out according to current guidelines. For cine imaging, a balanced steady-state free precession (b-SSFP) sequence with retrospective gating was used during short-periods of breath-holding. All standard cardiac geometries were acquired . Imaging parameters were chosen as follows: echo time (TE) and repetition time (TR) were set to shortest resulting in an average TR of around 4 ms and a TE of 2 ms, with a reconstructed in-plane resolution of 1.0 × 1.0 mmForward and reversed flow volumes were measured, and the regurgitation fraction was calculated as follows: aortic RF (%) = diastolic reversed flow volume × 100/systolic forward flow volume.Data are presented as mean (SD), median (25th to 75th percentile), or frequency (percent) as appropriate. Statistical differences between groups were assessed using Student’s t-test for continuous variables or Fisher’s exact test for categorical variables. Multigroup comparisons of continuous variables were performed using an analysis of variance (ANOVA). Spearman correlation coefficient was used to assess correlations between methods. Linear regression and c-statistics were used to assess the cut-off values of CMR and LSA-Doppler derived RF that best reflect the three-scale grading of AR by multiparametric TTE approach. Using these cut-offs the rate of agreement for AR grading was evaluated by calculating a κ-statistics. Additionally, the mean difference with the 95% confidence interval was also determined. Two-tailed p-values < 0.05 were considered statistically significant. Analyses were performed using SPSS software . The study was conducted in accordance with the Declaration of Helsinki, and was approved by the local research ethics committee (067/17-ek). All patients received informed consent.Demographic and baseline patient characteristics are presented in Table In the whole cohort the RF measurements assessed by PISA-method, LSA-Doppler, and CMR imaging were strongly correlated Fig. . But theUsing a linear regression and a receiver operating characteristic (ROC) curve analysis the RF values that best defined the multiparametric TTE derived AR severity using CMR were: mild, < 21%; moderate, 22 to 41%; and severe, > 42%; and using LSA-Doppler: mild, < 29%; moderate, 30 to 44%; and severe, > 45% , were recategorized as severe AR when a multiparametric approach was used. Five of these 7 patients were symptomatic; all of them had dilated LV ; and the decision to grade them as severe AR were made based on proposed echocardiographic parameters like a descending aorta end-diastolic flow reversal velocity > 20 cm/s, quantitative Doppler derived RF > 50%, and a vena contracta > 6 mm. Finally, there were comparable feasibility and kappa values for the agreement between all three methods and multiparametric TTE approach  and mild AR. RF cut-offs of < 7% for CMR and < 14% for LSA-Doppler showed a sensitivity and a positive predictive value of 100% for presence of non/trace AR but a poor specificity  due to overlap between non/trace and mild AR  applying CMR imaging, and in 50 of 61 patients (82%) with LSA-Doppler method. The kappa values of 0.748 and 0.726 indicate good agreement. Harmonizing grading schemes between imaging modalities. Indeed, using a unified standard grading scale for all methods as proposed in current recommendations [To the best of our knowledge, this is the first study to analyze which grading scale best defines the ndations  resultedThe feasibility of the PISA method was 85%, in accordance with original publications . But a sLSA-Doppler method also displayed higher RF values in the group with mild AR. The more pronounced the vessel wall elasticity the more expansion in systole and recoil in diastole. This means that the diastolic VTI is recorded from a smaller area than the systolic VTI, implying that the diastolic/systolic VTI ratio should overestimate the RF. A simplified formula has been proposed for correcting for aortic pulsatility  but specDiscrepancies in the group of mild and moderate AR might also be explained with the fact that CMR phase-contrast sequences may underestimate the slower, swirling regurgitant flow. Moreover, blood ejected into the aortic sinuses in systole that has not yet crossed the CMR image slice flows back into the left ventricle and, hence, will not contribute to the AR determination: the smaller RVol and RF, the greater the influence on the diagnostic accuracy. These potential limitations may be overcome by the use of slice tracking flow CMR sequences, which follow the valve and capture this potentially “undetected” regurgitation, with an increase in the RF by 60%, 15%, and 7% in mild, moderate and severe AR, respectively .Interestingly, in the group with severe AR there were no significant differences between all three methods derived RF. Suggesting that the cut-off value for severe AR should be relative similar with all methods. Indeed, by PISA method the cut-off value for severe AR with the best sum of sensitivity and specificity, using a multiparametric TTE approach as reference, was a RF > 46%. This cut-off value slightly lower than the recommended by the guidelines was due to the presence of seven patients with borderline PISA derived RF values that were recategorized as severe AR according to the multiparametric TTE approach. Indeed, a trend toward underestimation of the RVol by PISA was observed  in patieFinally, LSA-Doppler method and CMR were unable to distinguish between none/trace and mild AR in a significant number of patients with a marked overlap. Nevertheless, none of the cases with a non/trace AR had a RF > 14% by LSA-Doppler or > 7% by CMR. For the assessment of RF, an inter-observer coefficient of variation of 12% has been described for the LSA-Doppler . This meAlthough studies were performed on the same day in most patients, they were not performed simultaneously. Thus, differences in hemodynamic conditions might have resulted in different RF, especially in patients with mild or mild to moderate AR, where small changes in hemodynamics may influence the grading of AR. Nevertheless, a uniform tendency of overestimation with TTE derived flow convergence method makes this hypothesis less probable. Moreover, this reflects normal clinical practice during the evaluation of patients with AR, and may not be expected to have a major impact on the results, particularly in patients with moderate and severe AR.The lack of a robust gold standard reference method makes challenge to determine with certainty which method under or overestimate. However, our study used a recommended echocardiographic multiparametric approach , 11 as rWe conducted the study in a moderately sized group of patients with AR of the native valve and may not apply to those patients with prosthetic valve or atrial fibrillation. Moreover, the proposed grading scale showed a good correlation and diagnostic accuracy when compared with an accepted standard multiparametric TTE approach, but were not based on clinical outcomes. It is a hypothesis trigger showing that grading scales are not the same in all modalities and they should be adapted. Thus, future studies with an even larger number of patients will have to validate these grading scales, and appraise its correlation with clinical outcomes in different clinical scenarios.The results of the present study demonstrate that the quantitative RF values for AR grading using PISA-method, LSA-Doppler and CMR correlate well with each other but differ in groups with mild and moderate AR when using a recognized multiparametric echocardiographic approach.Supplementary file1 (PDF 270 kb)Below is the link to the electronic supplementary material.


For total knee replacement (TKR) patients, rehabilitation after the surgery is key to regaining mobility. This study proposes a sensor-based system for effectively monitoring rehabilitation progress after TKR. The system comprises a hardware module consisting of the triaxial accelerometer and gyroscope, a microcontroller, and a Bluetooth module, and a software app for monitoring the motion of the knee joint. Three indices, namely the number of swings, the maximum knee flexion angle, and the duration of practice each time, were used as metrics to measure the knee rehabilitation progress. The proposed sensor device has advantages such as usability without spatiotemporal constraints and accuracy in monitoring the rehabilitation progress. The performance of the proposed system was compared with the measured range of motion of the Cybex isokinetic dynamometer (or Cybex) professional rehabilitation equipment, and the results revealed that the average absolute errors of the measured angles were between 1.65° and 3.27° for the TKR subjects, depending on the swing speed. Experimental results verified that the proposed system is effective and comparable with the professional equipment. A survey revealed that more than 80% of elderly people aged 75 years or older were encumbered by degenerative arthritis . FurtherAccording to a hospital’s tracking report, some patients after TKR had knees that remained swollen or even deteriorated when the patients returned to the hospital for inpatient services . WhetherWith the advancement of electronic technologies and their integration with wearable devices, the underlying systems have been extensively applied in the field of medicine, especially for tracking rehabilitation actions. To assess the evidence of wearable devices supporting their efficacy in assisting rehabilitation after total hip replacement and TKR, a review by Bahadori et al.  found thInertial measurement units (IMUs) have been widely applied to detect human postures and gaits in recent years. As a result of their low cost, ease of use, and low weight, sensors can be easily integrated with wearable devices and the Internet of things for various applications. IMUs can be used in posture identification for applications in sports and healthcare.Van Der Straaten et al.  gave sysEvaluation of gait and body motion disorder is relevant to fall risk assessment after knee-joint surgery . Huang eData analysis and motion classification based on posture detection can help researchers more clearly understand users’ motion behavior. Some well-known methods such as neural networks, fuzzy modeling, and data mining have been proposed for analyzing motion patterns. Milosevic et al.  used selFrom the literature survey, we discovered that there remained problems to be solved in previous studies on rehabilitation monitoring after TKR. Therefore, the developed sensor-based system is aimed to fulfill three objectives: (1) monitoring whether the TKR patients followed the orthopedist’s rehabilitation instructions at home, (2) recording the duration of each rehabilitation session, and (3) determining the extent to which a patient’s knee can flex in each rehabilitation course. To fulfill these objectives, the developed sensor devices had to be reliable, user friendly, and easy to use and had to enable TKR patients to achieve rehabilitation effects at home similar to those achieved using professional equipment in a hospital.This paper is organized as follows. In In the proposed method, after TKR, patients must follow the orthopedist’s or physical therapist’s instructions to strengthen the knee as well as to avoid complications or dislocation of the new joint. Patients may feel uncomfortable while walking or exercising, and their legs and feet may be swollen. Physical therapists will instruct patients to use professional equipment such as the Cybex to restore movement in the knee and leg. The patient’s leg is bound to the arm of the equipment for rehabilitation. On the basis of the wound recovery progress, the arm’s swing speed is adjusted to the optimal speed suitable for the patient’s current knee condition. The equipment automatically records the ROM, indicating the flexion angle of the knee joint, as shown in The structure of the proposed system comprises two parts, rehabilitation devices and user information, as shown in The developed sensor device is shown in When the users are ready for rehabilitation, they simply must turn on the devices and select the app to receive signals transmitted from the devices. The system flowchart is presented in When the swing motion is fast, the measured acceleration from the triaxial accelerometer is influenced by the gravity effect and cannot reflect the actual flexion angle of the leg. To realize the effect of gravity on the measurement, some preliminary experiments were performed to remove the gravity effect. When a user sits on a chair flexing the leg at 90° at different velocities, as shown in xa(t), ya(t), and za(t) represent the acceleration values from the X-, Y-, and Z-axes at time t, respectively. The angles between the SMV and the three axes are denoted by ρ, φ, and θ, respectively, as illustrated in To remove the effect of gravity, we adopted a method used in fall detection that involves applying the SMV , which iA is the sum of vectors G and B, and When the triaxial accelerometer detects an object’s motion, it measures forces exerted by the object as well as by gravity. The total force can be expressed as follows:ρ, ϕ, and θ can be calculated as follows:The angles xB, yB, and zB. The results from another experiment after removing the effect of gravity are shown in From Equations (2) and (3), we can find the desired forces This study used a six-axis IMU, which comprises a triaxial accelerometer and triaxial gyroscope ,30. The Z-axis was perpendicular to the ground, therefore it was used as the reference direction for acceleration, which made the rotation direction parallel to the Z-axis. When the X- and Y-axes are rotating with the Z-axis, the measured acceleration should be . However, this would make determining the yaw angle impossible. To determine the yaw angle, we applied the quaternion calculation.The directions of the rotation angles are expressed as shown on the right side of q = w + xi + yj + zk, where  are the values of the quaternion. When applied to the six-axis inertia module, the quaternion can be calculated from the acceleration and angular velocity. This study used the MPU6050 inertia sensing module, which includes the quaternion in its functional library. We express the function for retrieving the values of the quaternion to calculate the yaw angle as follows:The quaternion can be expressed as The yaw angles calculated using Equation (7) were not smooth. The raw signals needed to be processed by the Kalman filter to obtain the desired signals.During a rehabilitation course, the users’ knee motion angle varies over time. The distribution of the swing angles may range, for example, from 60° to 180°. Even if we were to record all motion angles, there is no simple method to quantitatively measure the effect in each rehabilitation course. To resolve this problem, we applied Fuzzy c-means (FCM) to identify the centroid of the acceleration signals so that an equivalent ROM can be calculated to represent the effect of a rehabilitation course.θ, where θ is the angle between the shank and the ground.FCM is one of the commonly used machine learning methods that can softly partition data into the predetermined number of clusters . A datumThe triaxial accelerometer is highly sensitive, therefore any vibration or other disturbance during the rehabilitation course causes an abnormal reading from the device. Therefore, before determining the equivalent angles, gravity was removed and the Kalman filter was then applied to preprocess the received signals from the sensor devices. Using the Kalman filter to preprocess the raw acceleration signals can suppress disturbances and smooth them for further analysis. The equivalent ROM was calculated from the centroids G1 and G2, as shown in g and Yg were considered.Step 1: Record the signals from both sensors 1 and 2. The swing effects from the left and right directions were discarded, and only the acceleration signals from X1i and fcm2j for i, j = 1, 2, 3.Step 2: Use FCM to cluster the signals from each sensor into three groups, represented by fcmStep 3: Find the centroid from each sensor device and represent the pair as .Step 4: Perform basic operations on inverse trigonometric functions to calculate the equivalent ROM from the centroid pair  as follows:An Android smartphone was used to receive and record signals transmitted from the developed sensor devices. The users needed to input some basic information, such as name, age, gender, and the preferred animation type  at the first time of use. The designs for the animation types were based on the fact that most elderly people living in the vicinity of the hospital were fishermen, farmers, and retirees. After this information was input, the smartphone was paired with the sensor devices via Bluetooth, as shown in the lower part of the start page. Once paired successfully, the smartphone was ready to receive and analyze the signals transmitted from the sensor devices. An orthopedist can simultaneously track and monitor a patient’s rehabilitation status. If a patient does not follow the instructions, the orthopedist can actively contact the patient to determine what the problems are.The maximum swing angle is displayed sequentially in the lower part of the smartphone screen each time, as shown in To monitor the effect of rehabilitation, a line chart is used to display each swing angle on the screen, which represents a considerable improvement over the current rehabilitation system in which patients must wait before receiving an examination report. Furthermore, quantile plots are presented to display the swing angles in ascending order as well as to quantitatively compare whether there is noticeable progress after the designated course.X-axis represents the percentage of swing angles, and the Y-axis represents the corresponding angles. A line drawn perpendicular to 50% (f = 0.5) intersects with the bottom curve at an angle of 60° and with the upper curve at 75°. This implies that the first 50% of the swing angles were lower than 60° in the first rehabilitation course, whereas the leg flexion angle improved to 75° in the second rehabilitation course, indicating progress. By contrast, the swing angle remaining low, the line plots being flat, or the plots not having noticeable differences relative to the previous plots for a long time indicates either that the surgery was not completely successful or that the replaced knee joint gradually hardened. This may require immediate intervention by orthopedists to identify the problems.To quantitatively monitor the long-term progress of rehabilitation, we used a quantile plot to display the swing angles on the app. After the completion of one exercise course, the swing angles were saved in the memory and displayed as a line plot in the app, as shown in From June 2015 to May 2016, 35 subjects (11 without using Cybex and 24 using Cybex) aged 20–85 years were enrolled for the experiments at Chang Gung Memorial Hospital, Chiayi Branch, Taiwan. Written informed consent was obtained from all subjects. This study was approved by the Institutional Review Board of the Chang Gung Foundation (IRB-104-3347B). The research was conducted according to the principles of the Declaration of Helsinki. A detailed personal history review, general health examination, and lifestyle questionnaire were administered for all subjects.Before using the hospital equipment, 11 participants were invited to test the effectiveness of the developed sensor devices in the laboratory. The characteristics of the 11 participants are listed in Cybex is a motorized equipment used in the hospital and its swing speed can be manually adjusted to meet the user’s need. Experiments were then performed using professional rehabilitation equipment, Cybex, as a benchmark. To validate the effectiveness of the proposed system, only one sensor had to be worn at the shank during swings driven by Cybex, as shown in There were 16 healthy control subjects, namely eight men aged 59–66 years, six women aged 20–30 years, one woman aged 53 years, and one woman aged 65 years. Each subject wore one sensor device on the right shank and participated in experiments at angular speeds of 25°/s, 60°/s, and 180°/s for swings driven by Cybex. The three controlled speeds corresponded to normal walking speed, running speed, and athlete speed, respectively. The experiment was repeated five times at each angular speed. Then, the subjects repeated the process for the left leg. Only the maximum angle was saved in the database in each swing. Thus, ten data were collected from each subject on both legs at each angular velocity. The experiments were designed to verify the accuracy of the sensor devices with reference to Cybex as the benchmark.The proposed method was used to calculate the equivalent ROM. The subjects sat on a chair, therefore only the lower limb swung with the equipment. On the basis of the distribution of sensor signals from the accelerometers, where the Y-axis signals were located in the proximity of 0, we could identify that sensor 1 was worn on the thigh and sensor 2 was worn on the ankle. For the example of one experiment course shown in In total, 160 swing angles should have been received for each angular speed from the 16 healthy control subjects. However, in some experiments, sensor data were not received successfully due to some unexpected situations such as the sensor not being worn tightly and sliding during swings. After these abnormal data were removed, 135 swing angles were available at each angular speed. The ROM is plotted in We also calculated the correlation coefficients between the two measurement systems under three angular speeds, 25°/s, 60°/s, and 180°/s shown in Eight TKR subjects aged 60–85 years participated in the experiments. They were instructed to perform the same experiments as the healthy control subjects. For each angular speed, 80 swing angles should have been received from the eight TKR subjects. After the removal of nine abnormal data, 71 swing angles remained available at each angular speed. The ROM is plotted in Correlation coefficients between the two measurement systems under three angular speeds shown in After completing the rehabilitation on Cybex, each TKR subject sat on the chair to flex the leg back and forth approximately 90° 20 times. This was designed to simulate the rehabilitation scenario at home. The results showed no error in counting the swings from all subjects.Monitoring whether TKR patients are rehabilitated after the surgery remains a major concern for orthopedists. Without continuing rehabilitation, full recovery is delayed and the weak knee joint may affect the mobility of the patients, resulting in an urgent need for new devices or methods to overcome these problems. In this paper, an effective method is proposed to resolve the problems using three approaches: (1) monitoring whether the TKR patients follow the rehabilitation instructions at home, (2) automatically recording the duration of the rehabilitation course, and (3) saving the flexion angles and monitoring the progress from each rehabilitation course.The proposed sensor device has social benefits and advantages such as usability without spatiotemporal constraints, reduction of frequency returning to the hospital for inpatient services, saving medical expenses, and accuracy in monitoring the rehabilitation progress. The developed sensor devices can be easily worn on the thigh and ankle, and the proposed method can calculate the number of swings and the equivalent ROM from each rehabilitation course. This fulfills the second and third goals of this study. An app was designed to display the swing angles so that users can track the effect of rehabilitation. The orthopedist can also monitor the progress of rehabilitation, thereby fulfilling the first goal of this study. The experimental results show that the average absolute swing errors from the TKR subjects were between 1.65° and 3.27° and that the accuracies were between 98.09% and 96.16% at different angular speeds.Although the developed sensor devices are small and lightweight, they must be placed into a shell, and Velcro and an elastic belt are required to wear them on the leg. The hardware is proposed to be modified into a chip in the future. Furthermore, the developed devices are under investigation for other medical applications, such as rehabilitation for frozen shoulder, measuring trembling in Parkinson’s disease, identifying gait and joint patterns during walking, evaluating medial/lateral load or possible excessive stress shielding growth, and sport applications such as pitching pattern identification and adjustment.


Background: Early diagnosis of occlusal caries is of paramount importance for a minimally invasive approach in dentistry. The aim of the present in vivo clinical prospective study was to compare the diagnostic outcomes of visual subjective evaluation between the International Caries Detection and Assessment System (ICDAS-II) and an intraoral fluorescence-based camera  for the detection of pits and fissures in early caries lesions of posterior teeth. Methods: The study included 1011 posterior teeth in 255 patients aged 13–20 years (mean age 16 ± 2.2 years). Two blinded operators evaluated all the occlusal surfaces and the first assigned an ICDAS-II code, while the second assessed the VistaCam score: sound enamel (score 0–1.2); initial enamel decay (score 1.2–1.5); dentine caries (score 1.5–3). Results: Some 283 (28%) of the assessed teeth were ICDAS-II code 0; 334 (33%) code 1; 189 (18.7%) code 2; 176 (17.4%) code 3; and 29 (2.9%) code 4. The level of agreement between the two procedures was expressed by using Cohen’s and Fleiss’ kappa statistics and performing McNemar’s test. VistaCam assessed in 513 (50.7%) sound enamel; in 292 (28.9%) initial enamel decay; and in 206 (20.4%) dentine caries. Conclusions: This comparative study showed a poor agreement between the two diagnostic methods, especially between ICDAS-II 0, 1 and 2 codes and fluorescence assessments. One of the most prominent trends in modern dentistry is minimally invasive dentistry (MID), which aims to preserve as much hard tooth tissue as possible and to prevent the future loss of teeth . HoweverThe visual-tactile evaluation is usually carried out in accordance with the International Caries Detection and Assessment System (ICDAS-II), which guarantees standardization and comparability for proper diagnosis, data collection and future re-evaluation . HoweverMany trials have been published on the accuracy and efficacy of each of the above-mentioned diagnostic methods, but scant data are available on the comparative diagnostic outcomes on early occlusal caries assessment ,6,7. Then. 4280). All patients signed informed consent forms. All the procedures were in accordance with the Helsinki Declaration of 1975 [This in vivo prospective study was conducted at the 1st Observation Unit of Oral and Maxillofacial Sciences Department, “Sapienza” University of Rome. The study was approved by the Local Ethics Committee n. 420. All paAll recruited subjects were ASA status 1 . The inclusion criteria were: age > 12 years, permanent dentition, no fixed appliance and no restorations on the occlusal surface of the assessed teeth. A total of 1011 permanent teeth (691 first molars and 320 second molars) in 255 patients, aged 13–20 years (mean age 16 ± 2.2 years), were evaluated. A preliminary 3-day theoretical and practical calibration course was conducted by an experienced dentist (LO), and the weighted kappa values were excellent both for ICDAS-II criteria, kappa = 0.87, and for VistaCam criteria, kappa = 0.92.Two blinded and trained operators inspected the unrestored occlusal surfaces of each tooth with a plane dental mirror, in accordance with generally accepted standards ; the firPrior to each diagnostic evaluation, a professional cleaning was performed with a rotary brush and a polishing paste in order to standardize the visual and fluorescence assessment of the occlusal surfaces. First, a trained dentist (D.C.) conducted a visual inspection to assess the ICDAS-II score. To standardize the conditions, all the diagnostic assessments were performed in the same dental unit, with the same source of light, a dental mirror and the use of compressed air, and in the morning. The ICDAS-II distinguishes six various stages of caries, along with a score of “0”, which means caries-free; from 1–3, which grades the alterations in enamel, to 4–6, which describes the alterations in dentin .The new technology was then presented and explained to the patient and to parents or caregivers. Successively, the second blind operator (M.M.) assessed the VistaCam score.The VistaCam iX Vista Proof Tip  uses ultraviolet light of 405 nm length to locate and assess the severity of dental caries in the hard tissues of the tooth and distinguishes caries, tartar and plaque, displaying the results in a clear histogram applied to the image of the tooth surface on an attached computer screen ,10. The For subsequent evaluation, the Vista Proof values were classified as follows: 0–1.2 = sound tissue; 1.3–1.5 = enamel caries; >1.5 = dentine caries .Some 283 (28%) of the assessed teeth were diagnosed as ICDAS-II code 0; 334 (33%) code 1; 189 (18.7%) code 2; 176 (17.4%) code 3; and 29 (2.9%) code 4. VistaCam assessed in 513 (50.7%) sound enamel (0–1.2); in 292 (28.9%) initial enamel decay (1.2–1.5); and in 206 (20.4%) dentine caries (1.5–3) . n = 283) were classified by fluorescence camera as 244 sound, 32 enamel decay and 7 dentine caries. The teeth assessed as ICDAS-II code 1 were classified by fluorescence camera as 212 sound, 100 enamel caries and 22 dentine caries. Those evaluated as ICDAS-II code 2 were classified by fluorescence camera as 50 sound, 98 enamel caries and 41 dentine caries. A total of 205 occlusal surfaces were assessed as ICDAS-II codes 3 and 4, and were classified by VistaCam as sound in 3.4%, 27.7% enamel caries and 68.9% dentine caries  and with dentine caries in 8.7% (70). In total, 37.2% of the samples showed a false negative when using the ICDAS-II scoring system.p < 0.05) shows that there is evidence of asystematic differences between the proportion of positive responses from the two methods. McNemar’s chi-square value was 142.15, when df = 1 with a p-value of <0.001. The weighted kappa test showed coefficients ranging from 0.553 to 0.641, with an estimate of 0.61. These results showed a poor agreement between the two methods. The adjusted rand index (ARI) was computed to further corroborate this point and an ARI = 0.25 was calculated, which is quite a low value.The first question to be answered was whether there was a systematic difference between the results obtained from each method. For a binary response, the data were assessed by performing McNemar’s test, a modification of the ordinary chi-square test that takes the paired nature of the responses into account. A statistically significant result  , and, asJablonski-Momeni et al. evaluated the performance of ICDAS-II, laser fluorescence, fluorescence-based camera, and radiographic examinations for occlusal caries detection in order to assess their influence on treatment decisions when used as a single diagnostic method or as a combination of two methods. Their results showed that the use of the fluorescence-based camera is the most accurate evaluation method for assessing the condition of the dental surface before the establishment of a treatment plan, followed by ICDAS-II and other methods of evaluation . In addiMoreover, VistaCam showed efficacy in evaluating the residual carious tissue, appearing to be a useful supplementary tool in assessing the endpoint of caries excavation . In addiWhen taking into account the aspect of practical application during epidemiological studies, it is important to remember that ICDAS-II ensures detailed information about lesion severity, but it is considered as a time-consuming and hard to analyze method, also in the conditions of the dental office. Moreover, out of the office, it is even more difficult to keep the mouth dry and to ensure standardized and sufficient lighting conditions, which makes it impossible to carry out epidemiological studies and correct diagnosis of early carious lesions .The use of VistaCam also presents some limitations, as examinations should be carried out under certain conditions. The functioning intra-oral camera should not be disturbed by the presence of saliva on the tested hard tissues, and blood should be removed before the test, because it contains porphyrin derivatives, such as hemoglobin. The presence of these compounds enhances the fluorescence and increases the value of results ,23. In aThe limitations of this study are principally due to the availability of the proposed diagnostic technology. The use of a fluorescence-based camera assumes that it is purchased, and on a global scale there are realities where dentistry has yet to be based on the possibility of finding the basic means of assistance. That is to say that ICDAS-II remains a more democratically available method for caries screening, with unfortunately a low sensitivity for early caries detection. On the other hand, the strengths of the clinical study reported here are mainly based on a new diagnostic, non-invasive and not operator-sensitive technology that permits one to safely and continuously monitor the enamel demineralization at early stages.In conclusion, the data from the current in vivo prospective clinical study suggest that there is poor agreement between the two diagnostic methods, especially in ICDAS-II codes 0, 1 and 2 and fluorescence evaluations. Future randomized studies will better define the role of the operator’s visual inspection and the fluorescence-based camera. Until then, usage of ICDAS-II and fluorescence-based cameras together should continue to be considered the standard of care and begin to be widely used in daily dental routine.


There are three α1-adrenergic receptor subtypes  that are known to play various roles in neurotransmission and cognition. They are related to two other adrenergic receptor families that also bind norepinephrine and epinephrine, the β- and α2-, each with three subtypes . Previous studies assessing the roles of α1-adrenergic receptors in neurotransmission and cognition have been inconsistent. This was due to the use of poorly-selective ligands and many of these studies were published before the characterization of the cloned receptor subtypes and the subsequent development of animal models. With the availability of more-selective ligands and the development of animal models, a clearer picture of their role in cognition and neurotransmission can be assessed. In this review, we highlight the significant role that the α1-adrenergic receptor plays in regulating synaptic efficacy, both short and long-term synaptic plasticity, and its regulation of different types of memory. We will also present evidence that the α1-adrenergic receptors, and particularly the α1A-adrenergic receptor subtype, are a potentially good target to treat a wide variety of neurological conditions with diminished cognition.α Using a series of several ligands in competition binding assays, the α1A-AR subtype was shown to display a 10–100-fold higher binding affinity compared to the α1B-AR subtype for a distinct series of ligands  that display similar binding affinities but evoke different physiological effects for the same endogenous catecholamines. Signaling selectivity is achieved through the coupling to different G-proteins and effector systems in both temporal and spatial settings , and particularly the α1-ARs, have too low of avidity for localization and in vivo studies , endogenous promoter-driven expression of EGFP, or placement of β-galactosidase gene to KO the receptor. Using this transgenic-tagged approach, the α1A- and α1B-ARs was shown to exhibit similar expression patterns in the CNS, though the relative abundance was different , the relative distribution of α1-ARs in the brain has been estimated to be composed of ~55% α1A  mouse models of the αifferent . Both α1em cells . Using the brain . Using t~55% α1A , 35% α1B~55% α1A , and 10%~55% α1A .1A- or α1B-ARs were not found in brain vascular cells or adult astrocytes using these mouse models, despite previous studies using primary and cell culture lines indicating expression of α1-ARs. α1-ARs are highly abundant in vascular smooth muscle in the periphery. This disparity can be explained in two ways. First, while a large fragment of the endogenous promoter (~4kb) was used to drive systemic expression of the α1-ARs in the transgenic mouse models used for localization studies, a limiting factor is that there may have been missing distant promoter regions that are responsible for expression of the subtypes in astrocytes and the brain vasculature. There are also studies which indicate that the α1-AR abundance and receptor subtype switches when tissue is processed into cells in culture or when the cells are immortalized  where NE is synthesized and released. From this area, different and diffuse projections of NE-releasing neurons disperse throughout the CNS to innervate the hippocampus, spinal cord, prefrontal cortex, cerebellum, thalamus, cortex, and amygdala . The disDisruption in the NE system is also involved in a number of neurological diseases including Alzheimer’s disease (AD), epilepsy, attention-deficit disorder, Parkinson’s disease, depression, schizophrenia, and posttraumatic stress disorder . α1-ARs 1-AR subtypes is limited due to the lack of commercially available subtype-selective ligands with at least 100-fold selectivity between the subtypes , and/or calcium  at the mouse CA3 and CA1 synapse  and is considered a major mechanism of learning and memory and has been mostly studied in the hippocampus. αpocampus . α1-AR apocampus  and may pocampus . The actpocampus . α1-AR sbehavior . The α1A synapse . These αognition . These t1-ARs also induce LTP in the neocortex. Using neocortical slices, α1-ARs stimulated on astrocytes caused the exocytosis of ATP which initiated a subsequent burst of ATP-mediated synaptic currents from ATP receptors on the pyramidal neurons inducing LTP  and is associated with increased cognition. Impaired α1-AR function following lesion in the ventral hippocampus decreased glutamatergic synaptic plasticity within the PFC and resulted in PFC-related cognitive dysfunction  is also a form of long-term plasticity. Decreases in synaptic strength contribute to learning and memory functions by increasing flexibility in the synapse to store information . LTD has1-ARs induced LTD at excitatory CA3–CA1 synapses in the rat hippocampus even when β-ARs were inhibited and 85% of the NE innervation was depleted by degeneration with the neurotoxin DSP-4  receptor  are expressed throughout the PFC , which caused the depolarization of the interneuron leading to an increased calcium influx through calcium channels . The disThe medial PFC is also involved in reward-related memories by receiving major dopamine (DA) neurotransmission from the ventral tegmental area (VTA), which then projects back onto the VTA and the nucleus accumbens in the forebrain. These networks play a prominent role in the reward circuitry .1-ARs  on VTA neurons that increased NMDA receptor-mediated glutamatergic plasticity to induce the learning of cocaine-associated behavior  facilitates the neuronal connections and communication between the hippocampus and cortical areas that are required for consolidation and recall of memories . Alterat1-ARs (1A-AR density (1-ARs increased spontaneous inhibitory postsynaptic currents (IPSCs) in both frequency and amplitude when recorded from the principal neurons in the EC  is involved in the consolidation and storage of memory . While t storage , while a storage . Phenyleetention  suggestilidation .1-AR activation reversed cannabinoid-induced amnesia  receives major modulatory input from the locus coeruleus . MOB exh125-HEAT  and spec subtype .1-AR agonist phenylephrine increased evoked activation of mitral cells that were also inhibited by the α1A-AR selective antagonist WB-4101  from membrane phospholipids. It is IP release that increases intracellular calcium that contracts smooth muscle causing increased blood pressure for agonists that activate this receptor (1-AR have the potential to interact with the other subtypes and/or crossover to β-AR or α2-ARs. There are no existing ligands that demonstrate more than 100-fold selectivity between the α1-AR subtypes. Ligands with 50 to 100-fold selectivity are good research tools to dissect functions of the different subtypes, but not selective enough for therapeutics.A major function and limitation of the αreceptor . This si1A-AR positive allosteric modulator will enhance the α1A-AR NE-mediated effects, achieving subtype selective responses.Allosteric modulators are currently being pursued in the pharmaceutical industry as the next wave of therapeutics to treat disease. There are several advantages to using allosteric modulators when compared to current orthosteric agonists . The eff1-ARs. In the early 1980s it was recognized that the way phenethylamine agonists bound and signaled through the α1-AR was different from the way imidazoline agonists interacted (2-ARs (1-AR selective (1A-ARs are preferentially activated by imidazolines (+2 even though they are not allosteric modulators (1A-AR imidazoline partial agonists have been shown to mediate functions that are uncoupled from blood pressure at low doses (1A-AR stimulation would increase cognition, my laboratory developed a series of positive allosteric modulators that are not agonists and do not evoke an IP response on their own, but conformationally potentiate the cAMP response of NE (1A-AR positive allosteric modulators are currently in pre-clinical studies.Conformational changes and signaling-bias, crucial benefits of allosteric modulators were recognized early for the αteracted . While md (2-ARs , key difelective . The α1Aazolines  and imiddulators . α1A-AR ow doses . Based use of NE . It is pse of NE  as well 1-ARs, and all are described as negative allosteric modulators with no known clinically-useful application as of yet (2-AR (2-AR and display cooperative signals with agonists, they are not ligand-selective nor signaling-biased. However, all these studies give hope for the eventual development of allosteric modulators for the ARs that may be used to treat disease and specifically for AD.There are three published reports of allosteric modulation at αs of yet . Positivet (2-AR . While t1-ARs play an important role in synaptic efficacy and plasticity with effects on increasing learning and memory functions. There is no longer any controversy on their roles in cognition that was prevalent in the 1990s and early 2000s due to the use of nonselective ligands or using too high concentrations of ligands that would cross talk with other ARs. α1-ARs are expressed on a wide variety of neurons but also on glia and both contribute to its effects on cognition. α1-AR activation can improve conditioned fear, spatial, reward, olfactory, storage, recall and consolidation of memories. Consolidating and understanding the mechanisms involved in neurotransmission, learning, and memory may lead to new treatments in neurodegenerative diseases and age or disease-mediated cognitive decline. With the advent of allosteric drugs for GPCRs, α1-ARs that may become an effective treatment option in AD and other dementias without the unwanted side effects on blood pressure.There is substantial evidence that αThe author confirms being the sole contributor of this work and has approved it for publication.This work was supported by a grant from NIH RO1AG066627 and The Edward N. & Della L. Thome Memorial Foundation Awards Program in Alzheimer’s Disease Drug Discovery Research.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions. In fNIRS, near-infrared light sources and detectors  are placed over the scalp. In the near infrared spectrum HbO and HbR are the two main optical absorbers in cerebral tissue. Assuming homogeneous hemoglobin concentration changes inside a portion of the illuminated volume, the modified Beer Lambert Law is usually considered to convert changes in Optical Density  is a non-invasive technique that allows measuring oxygenated (HbO) and deoxygenated (HbR) hemoglobin concentration changes 19. Alike fMRI, we generally assume that there is a linear and time invariant relationship between events of a specific task and the impulse response of the neurovascular system called the Hemodynamic Response Function (HRF). Therefore, 20. In common practice, it is usually accepted to adopt an a priori fixed shape for the HRF28. For instance, the canonical BOLD-HRF30 is a standard choice, leaving only magnitude coefficients as free parameters to estimate. This parametrization has the advantage to offer optimal statistical power and interpretability if the HRF shape is specified correctly. However, according to both fMRI and fNIRS literature, there are temporal differences between 31 and there is evidence that the shape of the HRF varies across subjects, brain regions and tasks37. Additionally, the HRF may also be altered in some pathological conditions39. For these reasons, fixed HRFs might not be an accurate a priori to model the dynamics of Despite its limited spatial resolution and penetration depth, fNIRS has emerged as a complement to functional Magnetic Resonance Imaging (fMRI) due to its portability and possibility to perform long-lasting scans at bedside41. One of the most flexible model, a finite impulse response basis set42, contains one free parameter for every time-point of the HRF. It allows to model the whole range of shapes and delays for either 45, but sensitive to physiological confounding factors and noise level40. In the context of DOT reconstruction, which is a complex process also dependent on noise level46, it is still unclear whether deconvolution can be applied in a robust manner after DOT reconstruction.Different approaches have been proposed to attempt estimating the HRF shape through a set of basis functions. Employing the first and second derivatives of the canonical HRF or a combination of gamma functions are the most common ways to capture the variability in the hemodynamic responses18. HRF estimation was obtained using a Maximum Likelihood Estimator (MLE), whereas the temporal autocorrelation of the residuals was modelled using an order 1 autoregressive model AR(1)47. We simulated and added OD changes to real, resting-state data at different SNR levels, then evaluated the efficiency of MLE to deconvolve the shape of different simulated HRFs after reconstruction along the cortical surface. Our deconvolution approach was finally illustrated using fNIRS data acquired from subjects during motor or visual tasks and data from spontaneous epileptic activity in one epilepsy patient.The objective of this study was to evaluate the robustness of the deconvolution analysis when applied to DOT reconstructions on personalized fNIRS montages spatially constrained towards a target brain region15 and further improved in Machado et al.18 consists in estimating the optimal positions of a specific number of sources and detectors along the scalp surface, providing the best sensitivity to a target brain volume identified a priori. The procedure consists of the following steps: (1) Defining the set of possible optode positions along the high density tessellated surface of the scalp (48. (2) Performing Monte Carlo simulations for photon transport into biological tissues50 in order to generate “all” possible sensitivity profiles . To do so, we used the volume-to-surface interpolation method proposed in Grova et al.51, allowing to preserve sulco-gyral morphology. The surfacic sensitivity matrix was then thresholded at 10% of its maximum coefficient value .Reconstruction of K delta functions (56. This model is known as the Finite Impulse Response (FIR) basis set42:The deconvolution problem can be treated within a GLM framework, modelling the unknown HRF n and M cosines functions (< 0.01 Hz) from the discrete cosine transform basis set57 and random additive noise e[n].The GLM can then be expressed as follows:K columns of M last columns represent the set of cosine functions modelling the drifts. L regression coefficients we wish to estimate, and N dimensional multivariate normal distribution Considering all sampling indices together, the matrix formulation of the problem leads to the following equation:58. Assuming In order to estimate own see “” sectionK first values, hence the name partial). We tested the following null hypothesis:A question of interest is whether the estimated HRF coefficients -MLE modeling -MLE and partial F-based inference was evaluated in a separate study, and reported in supplementary material -MLE and 63. Data were acquired at rest with subjects sitting in a comfortable chair according to our fNIRS protocol, approved by the research ethics committee of the Montreal Neurological Institute and the McConnell Brain Imaging Center. Methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants and/or their legal guardians. Runs were acquired for 10 min  with the Brainsight CW fNIRS system (685 and 830 nm). For all selected participants, we also acquired an anatomical T1-weighted MRI acquisitions  with no history of neurological or psychiatric disorders. For every subjects, we applied a personalized optimal montage (maximum 4 sources and 8 detectors) targeting specifically the right motor cortex of every subject. The right hand knob region of every subject was visually identified and marked on the cortical surface by an expert anatomist (GP). This motor region will be further denoted as our target Region of Interest (ROI)  to remove very slow trends. Detrending the data was necessary to define a stable baseline necessary to convert measured intensity signals into After acquisitions, fNIRS runs were reviewed to exclude large movement artefacts. Small movement artefacts were marked manually and corrected using a spline interpolation subtraction technique65  that were delayed by 2 s for HbR, as suggested by Jasdzewski et al., Wolf et al.46.The homogeneous hemoblobin concentration changes in the ROI were then converted into mentclass2pt{minim see Eq.  and addeThe same scaling factor DOT reconstruction of hod see “” sectioni corresponding to the first peak of the estimated HRF . To assess the accuracy of the shape of the reconstructed HRF independently from the quantitative accuracy on its amplitude, we first normalized the reconstructed HRF to a maximum of 1. We estimated the shape error of the estimated HRF as the Mean Squared Error (MSE) between 65, using the true simulated parameters of each HRF as initial conditions  during a left hand finger opposition task using a personalized optimal montage positioned over the right hand knob area for two right handed subjects. Methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants. The event related paradigm consisted of 30 trials followed by 2–60 s of rest. Participants were instructed by an auditory cue to press their thumb and index fingers for 1 s against each other then relax. Data were band pass filtered [0.005 0.6] Hz and converted into We also analyzed fNIRS data  during a visual task using a personalized optimal montage positioned over the right visual cortex (V1) for one right handed subject. The visual task was a left hemi-field black and white checkerboard flashing at 5 Hz. The event related paradigm consisted of 50 trials of 2.4 s duration followed by followed by 5–15 s of rest. Data were analyzed using the same methodology considered for the motor task.16, we selected one run of 15 min from one patient with focal epilepsy who underwent simultaneous EEG/fNIRS acquisitions during 4 h. The selected patient was a 24 years old female diagnosed with right frontal epilepsy. EEG/MEG source localization suggested a right frontal generator for the epileptic discharges. EEG was acquired using 25 scalp electrodes placed according to the 10–20 system. fNIRS montage was tailored using the optimal montage methodology to target a right frontal epileptic focus, identified using MEG source localization. The montage was then completed to cover also the homologous contralateral region to the presumed focus. Epileptiform discharges consisted of 10 bursts of rhythmic fast activity in the beta range (20–25 Hz) lasting 0.5–1 s each. DOT was applied on the From our previous EEG/fNIRS studyFigure Figure Figure Errors in estimation of the first peak of the HRF (TTP1) for all HRF models investigated are reported in Fig. Errors on the estimation of the undershoot peak (TTP2) are reported for all HRF models in Fig. Error in the estimation of the durations of the main peak (FWHM1) and undershoot FWHM2), are reported for all HRF models in Fig. , are repROI targeted by our optimal montage strategy . Quantitatively, the main peaks of both HbO and HbR responses obtained after deconvolution were very close to the ones of a canonical HRF model, peaking around 5 s for HbO and 6 s for HbR. We observed a small undershoot estimated for subject 1 but none for subject 2.Finger opposition results obtained on subjects 1 and 2 are presented in Figs. ROI targeted by our optimal montage strategy . Quantitatively, the main peaks of both HbO and HbR responses obtained after deconvolution were very peaking around 6 s for both HbO and HbR.Visual task experiment on subject 3 is presented in Fig. 16, we observed bilateral frontal significant hemodynamic responses. We report the global response, but individual responses measured in each hemisphere were not significantly different. The underlying mechanisms explaining the occurrence of those bilateral fNIRS responses to unilateral epileptic discharges, also reported in EEG/fMRI studies, are complex and not clearly understood. For HbO, the main peak of the reconstructed HRF (peak around 5–6 s and a duration of 8 s) was close to the canonical form with a very prominent undershoot peaking at 15 s. The small increase in HbO occurring at 30 s might be caused by some physiological contaminations. The SNR, computed retrospectively, was found to be at − 7.4 dB for the best pair. For HbR, we found a decrease in the inferior part of the FOV (peak around 5–6 s and a duration of 5 s). On the superior part of the FOV, we found a reverse pattern consisting in an increase HbR followed by a negative undershoot, which could suggest surround inhibition.fNIRS analysis of transient epileptic discharges  is presented in Fig. 41, it is the first time such a validation is performed after reconstruction along the cortical surface. One of the most important result is that deconvolution after inverse modelling using an AR(1)-MLE estimator seems to be robust, especially at realistic SNR levels .The purpose of this study was to evaluate robustness of HRF deconvolution after reconstruction of 18. Our HRF deconvolution results should remain valid or even improve, when considering spatially extended ultra high density montage14 as these montages have even better properties for reconstructions.Through this study we used personalized optimal montages aiming at maximizing the sensitivity to a target brain region as they offer excellent properties for local reconstructions and provide overall better SNR in the source-detector space than non optimized sparse arrangements of optodesOD changes obtained using cortical activation models. We considered 4 different shapes of HRF with  to investigate the ability of deconvolution techniques to recover a large spectrum of HRF shapes. We also varied the SNR of scalp measured OD changes applying a global scaling factor to real physiological and instrumental noise signals acquired at rest46. Here we are reporting the results obtained using simulations involving a rapid event related paradigm . We obtained similar performances when considering another event-related design or block designs for simulations (results not shown). This is in agreement with Aarabi et al.40 who demonstrated using a vast array of stimulus paradigms that the timing of events had negligible effects effect on the performance of deconvolution.We validated the proposed methodology in a simulation environment with scalp evoked Overall, we obtained quite accurate reconstructions for HRFs for both HbO and HbR signals over a large range of SNR levels, whereas estimating HRF amplitude, delays and durations for HbR required larger SNR to reach similar accuracy than for HBO. Our results are overall suggesting that the HRF main peak can be measured with good accuracy under 1 s for long duration HRF models and excellent accuracy below 0.25 s for canonical, short and large undershoot HRF models. Similarly, we found that the main peak durations (i.e. FWHM) can be measured with good accuracy below 1 s for canonical, short and large undershoot HRF models. Our results are also suggesting that when the amplitude of the undershoot is large, delay and duration of the HRF can be measured with good accuracy below 1 s over a large range of SNR levels.40, for instance, investigated the effect of confounding variables on HRF estimation using deconvolution at the sensor level in a rat model and demonstrated that periodic low-frequency systemic hemodynamic fluctuations as well as phase-locked noise can markedly obscure hemodynamic evoked responses in rapid event-related designs.Long duration HRF models were more difficult to estimate accurately due to the intrinsic smoother variations of the response which may overlap easily with systemic physiological fluctuations. Aarabi et al.18, improved SNR could be achieved through additional filtering techniques including PCA filtering  and superficial signal correction using short separation (< 5 mm) source-detector measurements70.We demonstrated our ability to reconstruct event related responses to a finger opposition task or a flashing checkerboard using deconvolution after local reconstruction along the cortical surface. While we were able to reconstruct the main peak for HbO and HbR with sufficient confidence, the reconstruction of the undershoot was less accurate in agreement with our simulation results. We estimated that the SNR obtained on these real measurements was ranging from − 5 to 2 dB Fig.  and 11. The main advantage of the proposed deconvolution method is to gain insights about neurovascular coupling mechanisms considering the possible underlying variability of the hemodynamic response. While our main objective was first to propose a detailed quantitative evaluation of the method. A detailed analysis of HRF variability at the intra- and inter-subject level is of great interest. We hope to carefully address these important questions in our future investigations on larger populations of patients and additional tasks.71 who suggested that AR(1) models should be sufficient when signals are almost free of motion artefacts, whereas higher order AR models should be considered in presence of motion. In our case, our recordings were almost free from any motion artefacts because we used collodion to maintain optode contacts on the skin. Investigation of different strategies to handle atypical error structures including higher AR orders72, precoloring73 or whitening techniques in the wavelet domain44 was out of the scope of this study but could be considered in the future. Additionally, future studies could include less conservative approaches to handle the multiple comparison problem such as the random field theory28 or the false discovery rate approach74.Incorrect assumptions on the unexplained errors of the deconvolution model applied to fNIRS data containing serial-correlated noise and motion-related artefacts may also have led to inflated F test statistics, false positives activations around the ROI and incorrect estimation of the HRF. However, the lack of significant reconstructions below − 20 dB, which may be considered as a null condition, and our additional validation study using partial F test statistic  should result in similar performances after linear regression along the cortical surface as suggested in fNIRS at the sensor level41. However, low degree-of-freedom models, such as canonical HRF and its derivatives should be preferred only if we can tolerate a degree of mismatch between the underlying HRF shape and the model assumptions41.Comparison of the FIR basis set with other basis sets or statistical formulation of the multiple linear regression problem within a Bayesian formalism53. Errors are still within values reported in Boas et al.11, Tian and Liu27 when using DOT on regular high density montages and within values reported by Machado et al.18 when applying inverse modelling with optimal montages. Better accuracy could be expected from more advanced inverse operators, such as the maximum entropy on the mean method77.Quantitatively, the true amplitude of the simulated activity was systematically misestimated . Indeed, it is generally accepted that the L2-minimum-norm model is tends to favour smeared solutions around locations where the measurements are the most sensitive, especially for EEG/MEG source localizationIn the present study, we investigated the accuracy HRF deconvolution when applied to reconstruction along the cortical surface obtained from personalized optimal montages that can be qualified as a local quantification tool with improved optical coupling and minimal movement sensitivity. While deconvolution is generally considered challenging, we demonstrated that HRF deconvolution, even using a straightforward computationally low cost AR(1)-ML estimator and F based inference, was able to accurately recover a large variability of HRFs along the cortical surface allowing to exploit the richness of the high temporal resolution offered by fNIRS. Our results indicate that particular attention should be placed upon maximizing SNR when designing fNIRS studies especially when the objective is to estimate low amplitude transients such as the undershoot.Supplementary Information.


The transcription factor forkhead box (FOXO) controls important biological responses, including proliferation, apoptosis, differentiation, metabolism, and oxidative stress resistance. The transcriptional activity of FOXO is tightly regulated in a variety of cellular processes. FOXO can convert the external stimuli of insulin, growth factors, nutrients, cytokines, and oxidative stress into cell-specific biological responses by regulating the transcriptional activity of target genes. However, how a single transcription factor regulates a large set of target genes in various tissues in response to a variety of external stimuli remains to be clarified. Evidence indicates that FOXO-binding proteins synergistically function to achieve tightly controlled processes. Here, we review the elaborate mechanism of FOXO-binding proteins, focusing on adipogenesis, glucose homeostasis, and other metabolic regulations in order to deepen our understanding and to identify a novel therapeutic target for the prevention and treatment of metabolic disorders. Forkhead box (FOXO) transcription factors play important roles in apoptosis, the cell cycle, DNA damage repair, oxidative stress, cell differentiation, glucose metabolism, and other cellular functions . FOXO geThe transcriptional activity of FOXO is regulated by post-translational modification, including phosphorylation, acetylation, and ubiquitination, which determine subcellular localization, binding with DNA or other regulatory factors, and degradation, among other features. One of the basic regulatory systems is the growth factor-mediated phosphatidylinositol-3 kinase (PI3K)/Akt pathway, which induces phosphorylation of FOXO transcription factors. The three consensus AKT phosphorylation sites are conserved in all members of the mammalian FOXO families, except FOXO6 ,12,13,14FOXO proteins function primarily as transcription factors in the nucleus and bind to the FOXO binding consensus domain of target genes, regulating the expression of these genes. The highly conserved FOXO binding consensus domain, (G/C)(T/A)AA(C/T)AA, is identified as the FOXO-recognized element (FRE) ,15. Furt14-3-3 proteins are a family of modulator proteins that regulate multiple signaling pathways by binding to Ser/Thr-phosphorylated motifs on target proteins ,17,18. 1In contrast, another protein kinase, the AMP-activated protein kinase (AMPK), is essential to the cellular responses to low energy level and activates FOXO function. AMPK has been shown to phosphorylate FOXO3 at six sites  that are different from the AKT phosphorylation sites . In the Oxidative stress also plays an important role in the regulation of FOXO proteins. Under oxidative stress, FOXO translocates to the nucleus to gain stress resistance by activating genes involved in oxidative detoxification, such as manganese superoxide dismutase (MnSOD) and catalase ,27. The The cAMP response element-binding protein (CREB) binding protein (CBP) and its related protein p300 (p300/CBP) are histone acetyltransferases that act as coactivators of numerous transcription factors ,35. In tCaenorhabditis elegans, sir2 and FOXO ortholog daf-16 have overlapping and distinct functions in regulating life span [Silent information regulator 2 (Sir2) is an evolutionarily conserved histone deacetylase in the sirtuin family of nicotinamide adenine dinucleotide (NAD)-dependent deacetylases and is considered as a longevity regulatory gene. Life span extension by Sir2 was first reported in yeast . In Caenife span ,40. Sir2ife span  and induC. elegans [In mammals, the Sir2 family has seven members. Among them, SIRT1 is the closest homologue of yeast and  elegans . SIRT1 i elegans ,43, and  elegans ,45. Acet elegans . A study elegans . Express elegans .KQ/KQFoxo1) and constitutively deacetylated Foxo1 (KR/KRFoxo1) clearly demonstrated the significance of FOXO acetylation in vivo [KQ/KQFoxo1 is predominantly cytoplasmic with a loss of function phenotype, whereas KR/KRFoxo1 is predominantly nuclear with a gain of function phenotype. KQ/KQFoxo1 is embryonic lethal due to cardiac and angiogenic defects. KR/KRFoxo1 mice present with hyperglycemia and insulin resistance. Increased hepatic gluconeogenic gene expression and decreased glycemic gene expression result in excessive hepatic glucose output. Furthermore, KR/KRFoxo1 mice have decreased free fatty acid (FFA) and triglyceride (TG) levels with a lower respiratory quotient, which is consistent with a state of preferential lipid usage. These findings suggest that, in response to fasting or caloric restriction, deacetylated Foxo1 promotes gluconeogenesis, and with prolonged fasting, the gluconeogenesis shifts to lipolysis  to bind to the target region of DNA, and FOXO1 binding to PPARγ is considered to disrupt this PPARγ/RXR complex, resulting in an incapability of PPARγ to bind DNA . PPARγ, Foxo1 is involved in energy homeostasis in adipose tissue ,67,68,69Ucp1 enhancer region and inhibits Ucp1 expression in adipocytes, suppressing energy expenditure. Under cold exposure and other stimuli, Zfp238 binds to Foxo1 and acts as a corepressor, leading to reactivation of Ucp1 expression and the generation of beige adipocytes in WAT  and/or decreased clearance of TG-rich particles is observed. Adipolipoprotein C-III (apoC-III) inhibits lipoprotein lipase and hepatic lipase, impairing the clearance of TG-rich particles and leading to hypertriglyceridemia . The apo insulin . In insueridemia . PPARα wHepatocyte nuclear factor (HNF)-4, a member of the steroid/thyroid nuclear receptor superfamily, is a transcription factor expressed in liver, kidney, intestine, and pancreatic β-cells ,76. HNF-Gck expression: PPARγ, hypoxia-inducible factor-1(HIF-1), sterol regulatory element-binding protein 1c (SREBP1c), and HNF-4 [Gck promoter, which induces Gck expression. Sirt1 deacetylates Foxo1 and deacetylated Foxo1 binds to the Gck promoter and disrupts the binding of HNF-4 to its binding site in the proximal Gck promoter [Gck expression in hepatocyte is tightly controlled not only by Foxo1–HNF-4 interaction but also by the post-translational modification of Foxo1 acetylation (Glucokinase (GCK) is one of the key enzymes that regulates glucose utilization in the liver. Several transcription factors are known to regulate nd HNF-4 . Acetylapromoter . These ftylation .Pgc1 is increased. PGC1α binds and activates FOXO1, leading to activation of gluconeogenic gene expression, such as glucose-6-phosphatase (G6pc) [PGC1α is a transcription co-activator and regulates adaptive thermogenesis in brown fat, muscle-fiber specification, and hepatic-fasting response. In the liver, PGC1α induces gluconeogenesis during fasting . When gle (G6pc) . Foxo1 aPck1), and activates its expression in a C/EBPα-dependent manner. Insulin inhibits Pck1 expression and other C/EBPα-dependent transcription enhanced by Foxo1. Thus, Foxo1 regulates gluconeogenesis by binding to C/EBPα, and by linking insulin signaling to C/EBPα during liver development [CCAAT/enhancer-binding protein (C/EBP) is a family of basic-leucine zipper transcription factors involved in female fertility, gluconeogenesis, adipogenesis, and hematopoiesis . Foxo1 delopment .Gck) expression and increases glucose production by activating G6pc expression [Gck expression in the liver. Ablation of SIN3A in the liver activates the expression of Gck without affecting other FOXO1 target genes, and reduces glycemia without concurrent steatosis. These findings suggest that FOXO1 selectively controls the expression of Gck by interacting with SIN3a. During insulin-induced Gck expression, clearance of SIN3a is observed, which requires phosphorylation of FOXO1 at two sites, Thr24 and Ser253. In contrast, inhibition of G6pc requires FOXO1 phosphorylation of one site, Ser253. These results are consistent with the previous finding that Thr24 phosphorylation is regulated by insulin and insulin-like growth factor-1 receptors [FOXO1 inhibits glucose utilization by suppressing glucokinase  gene, the α-cell determinant, through methylation of the Arx promoter region. In contrast, Foxo1 induces Arx expression by binding to the Arx promoter region. Foxo1 binding to the promoter region releases the DNA methyl transferase (DNMT)3a from the Arx promoter, and hypomethylation in the CG-rich promoter region is induced, leading to activation of Arx expression. In FcorKO, immunostaining shows an increase in Arx-positive endocrine cells from e15.5 and an increase in glucagon-positive cells from e17.5, suggesting that FCoR is involved in α- and β-cell differentiation from the endocrine progenitor stage. These findings suggest that Arx is a target gene of Foxo1 and its transactivation is suppressed by FCoR via methylation by DNMT3a.Furthermore, recent study showed that FCoR is also expressed in pancreatic α- and β-cells from the embryonic stage . FcorKO FcorKO, most Foxo1 translocates to the nucleus and the intrinsic Foxo1 level decreases. This is probably due to deacetylated Foxo1 being activated in the absence of FCoR, followed by degradation. This result is consistent with the previous findings that activated FOXO is rapidly ubiquitinated and degraded [Arx expression and α-cell mass from the endocrine progenitor stage and is required to maintain α- and β-cell identity (FCoR acetylates Foxo1 and suppresses Foxo1 activity in islet cells . The notdegraded . Furtherdegraded . This stidentity .Smooth muscle cells (SMCs) are unique cells with phenotypic plasticity and present transition between a quiescent contractile phenotype and a proliferative phenotype in response to local environmental cues, including growth factors/inhibitors, mechanical influences, cell–cell and cell–matrix interactions, and various inflammatory mediators . Smooth Hes) gene is a Csl target gene. Hes gene expression is activated by Notch/Foxo1 binding, and Hes1 function as a transcription factor that suppresses myogenic determination gene (MyoD) transcription [FOXO transcription regulates myogenesis not only in SMC, but also in skeletal muscle . Conditicription . Thus, NDiabetic cardiomyopathy is defined by the existence of abnormal myocardial structure in the absence of other cardiac risk factors such as hypertension or coronary diseases. In cardiac muscle, insulin receptor substrates (IRS)-1 or IRS-2 activates the Akt signaling pathway and inactivates Foxo1, leading to promoting cardiac function and survival ,100. UndIn contrast, Foxo1 plays an essential role in response to starvation. As mentioned in Pomc and Agrp. Leptin signaling activates Janus kinase 2 (JAK2) and the signal transducer and activator of transcription 3 (STAT3), leading to nuclear translocation of phosphorylated STAT3. STAT3 then activates the Pomc gene while it suppresses the Agrp gene, resulting in suppression of food intake  neurons and orexigenic agouti-related peptide (AgRP) neurons in the arcuate nucleus (ARC) of hypothalamus are the major neuropeptides involved in this process ,103,104.d intake . InsulinSirt1 is expressed in POMC neuron and AgRP neurons in ARC . For hypC. elegans to mammals. Post-translational modification of FOXO tightly controls the activation and/or repression of target gene expression in response to various external stimuli. In addition to the classical regulation by post-translational modifications, there are various regulatory systems involved in FOXO regulation. To achieve this elegant and complex regulatory mechanism, FOXO does not act alone. The partner proteins synergistically function to cope with versatile physiological changes in different organs. Previous studies have shown that there are a variety of patterns regarding interaction between FOXO and the FOXO-binding protein to regulate target gene transcriptions  analysis showed that FOXO3 is related to an extended life span in humans, while FOXO1 is not [The primary function of FOXO is to support the living organism to survive unfavorable conditions and attain longevity. However, in higher eukaryotes, we see that loss-of-insulin signaling, which causes gain-of-FOXO function, can lead to various metabolic disorders, including type 2 diabetes. This is the result of dysregulation of FOXO activity caused by conditions such as obesity and insulin resistance. FOXO function in “longevity” is featured in 1 is not . Loss ofUnderstanding the multilayer mechanism of the tissue-specific metabolic regulation by FOXO and the fine-tuning mechanism by the FOXO-binding protein will lead us to make a proper approach to prevention and treatment of metabolic disorders.