The design, fabrication, and use of a hotspot-producing and temperature-sensing resistance thermometer for evaluating the thermal properties of low-dimensional materials are described in this paper. The materials that are characterized include one-dimensional (1D) carbon nanotubes, and two-dimensional (2D) graphene and boron nitride films. The excellent thermal performance of these materials shows great potential for cooling electronic devices and systems such as in three-dimensional (3D) integrated chip-stacks, power amplifiers, and light-emitting diodes. The thermometers are designed to be serpentine-shaped platinum resistors serving both as hotspots and temperature sensors. By using these thermometers, the thermal performance of the abovementioned emerging low-dimensional materials was evaluated with high accuracy. The semiconductor industry is pursuing electronic systems with higher integration density, more functions, higher power and frequency, and smaller footprint and volume, with lower cost. When the performance increases, the power density in electronics systems becomes higher and higher; thus, heat dissipation becomes a critical issue. In addition, the increase of hotspots and packaging complexity, such as in three-dimensional 3D) stacking of processor and memory chips, makes thermal management an even more difficult task in microsystems. Various advanced materials and technologies were proposed and demonstrated to improve thermal management in electronics, for instance, nanoparticles and graphene-enhanced thermal interface materials (TIMs) , carbon D stackinVarious methods were developed to characterize the thermal performance of nanomaterials. For instance, the thermal bridge method can be used to measure the in-plane thermal conductivity of extremely small structures down to a single atom layer ; the e-bThe principle of a resistance thermometer is to use temperature-sensitive materials to detect temperature by monitoring the change in electrical resistance of the material. Among all the materials, platinum (Pt) is one of the most used due to its highly linear temperature–resistance relationship. Fu et al. fabricated a resistance thermometer using e-beam evaporated Pt thin films on silicon chips , as show2. The thickness of the platinum thermometers is 40 nm. Prior to the deposition of the platinum resistors, a 20-nm-thick titanium layer was deposited as an adhesion layer. The thickness of the insulating silicon dioxide (SiO2) layer on the silicon substrate was 300 nm. Balandin et al. used a similar structure to model the heat spreading from metal–oxide–semiconductor (MOS) field-effect transistors on silicon-on-insulator (SOI) substrates with and without graphene heat spreaders [The thermal test chip fabricated by Fu et al.  shown inpreaders . In this paper, the thermal test chip shown in 2sp hybridized C–C bonding, CNTs exhibit excellent thermal properties. Therefore, they were proposed as a candidate for thermal interface material development and many results were reported [2 insulating layer on the hotspot circuit. More details about the transfer process can be found elsewhere [Owing to the very strong reported ,17,18,19reported ,21 and creported . They grreported , as showlsewhere ,24. PrioAfter transfer, the on-chip CNT-based micro heat sink was mounted onto a supporting circuit board as shown in In order to examine the cooling performance of the CNT-based micro heat sink, air and water were used as coolant, and they were pumped to flow through the micro channels between the CNT fins. Some results of the experiments are shown in 2, the hotspot temperature decreased by almost 50 °C (from 116 to 68 °C) upon using water at a flow rate of 0.32 m/s, compared to when air was used as the coolant, even though the air flow rate was ten times larger (3.2 m/s). However, more interesting is the unfortunate fact that the CNT cooling fins seemed to have a minimal influence when air was used as coolant. This is believed to be a combination of the thermal contact resistance to the hotspot being too high due to the interface layers, and that macro-scale cooling may not be directly scalable to a micro-scale environment.As expected, water is a much more effective coolant than air. For a heat flux of 3000 W/cmThe experiments showed that, when the chip was cooled by water at a flow rate of 0.32 m/s, the hotspot temperature on the chip with the CNT cooling fin structure was about 8–10 °C lower than on the test chip without the CNT fins. Interestingly enough, beyond a certain flow rate of the water coolant, the cooling effect seems to be more or less independent of the flow rate, as shown in Finally, Similar to CNTs, graphene also possesses excellent thermal and mechanical properties due to its special crystalline structure . In elecBalandin et al. showed that a few-layer graphene-based heat spreader connected to the drain of gallium nitride (GaN) high-power field-effect transistors considerably reduced the device temperature . Using mTo evaluate the graphene-based heat spreaders, a new version of the resistance thermometer was designed and fabricated. Based on the lessons learnt from the CNT-based micro heat sink, the wires connecting the hotspot resistor and the I/O pads were redesigned to minimize the power dissipation via interconnect circuit. Two examples of such redesigned resistance thermometers are shown in 2, and its resistance was about 80 Ω at room temperature. monolayer graphene grown by chemical vapor deposition (CVD) was placed on the thermal test chip as heat spreader via the transfer method [2 protective layer. 2. Thick graphene-based films fabricated from the liquid-phase exfoliation method [2 layer was reduced to one-tenth of the thickness that was used in the CNT cooling fin experiments. The detailed process of transferring and placing the monolayer and multilayer graphene heat spreader onto the hotspot structure is described elsewhere [These hotspot test structures were used in a series of experiments to investigate the thermal performance of 2D materials with high thermal conductivity, such as monolayer and multilayer graphene, and BN-based heat spreaders. By using such 2D materials as heat spreaders to dissipate the Joule heat generated from the hotspot laterally across the chip surface, both the hotspot temperature and the average temperature across the chip can be lowered. The area of the hotspot resistor used in these experiments was 390 × 400 μmr method ,35. The n method ,37 were lsewhere . In another investigation, an infrared camera was used to monitor the temperature on the thermal test chip to evaluate the cooling performance of a graphene-based heat spreader . The theA recent study showed that the cooling performance of a graphene-based heat spreader (fabricated via the vacuum filtration method) can be further improved by interfacial functionalization . In a se2. By placing a graphene film without functionalization on the surface of the test structure and repeating the measurements, the hotspot temperature was found to decrease to 140 °C (∆T = 6 °C). The estimated accuracy was ±0.5 °C. If, instead, the functionalized graphene-based heat spreader was used, where the thermal contact resistance between the graphene-based film and the test structure was reduced by the addition of a functionalized graphene oxide (FGO) interfacial layer, the hotspot temperature was found to decrease to 134 °C (∆T = 12 °C). The resulting thermal performance of the graphene-based heat spreader before and after functionalization is shown in In this paper, we also summarize the use of hotspot test structures for the evaluation of the performance of 2D hexagonal boron nitride (hBN) films as heat spreaders. The advantage of BN films over graphene is that they are electrically insulating and yet good thermal conductors . In scen2) insulators. For hBN monolayers, the thermal conductivity value can be even higher [2 layers, which will significantly decrease the total thermal resistance along the heat conduction path and, therefore, greatly improve the cooling performance. For thermal management applications, 2D hBN was used to develop both thermal composites [Bulk hBN has a typical thermal conductivity of 390 W/mK, which is 280 times higher than the thermal conductivity of silicon dioxide  . In thisIt should be noted that there is larger variation in thermal performance between different hBN films (multilayer hBN films) as compared to variations between different monolayer hBN films. This is explained by the difficulties in maintaining the same properties between samples obtained by drop-coating of LPE hBN solutions. As shown in Reference , studies2).A few emerging low-dimensional materials exhibit excellent thermal properties that could be used for thermal management of high-power electronics. In this paper, we reviewed a number of serpentine hotspot-producing and temperature-sensing test structures that can be used to evaluate the thermal performance of these 1D and 2D materials. The performances of both CNT-based micro heat sinks and two-dimensional films of graphene and hBN-based heat spreaders were summarized. For the CNT-based heat sink, air did not show much cooling effect, while water cooling could lower the hotspot temperature by 50 °C at high heat flux densities. Furthermore, several studies using monolayer graphene and hBN as a heat spreader were summarized. The monolayer graphene heat spreader was shown to be much more efficient in spreading the heat, thereby lowering the hotspot temperature, than the monolayer hBN heat spreader. Concerning few-layer graphene heat spreaders, it was shown that their performance could be improved considerably by functionalization using APTES, which can minimize the thermal contact resistance between the chip and the heat spreader. Few-layer hBN heat spreaders were shown to have similar heat spreading performance to few-layer graphene without functionalization (~5°C at 1000 W/cmThese 1D and 2D materials show great potential as heat dissipation materials in electronics. However, challenges need to be addressed before the low-dimensional materials can be pushed onto the market. For the CNT-based micro heat sink, a CNT transfer process which can be upscaled to industry level and be compatible with the current semiconductor processes needs to be approved. For graphene-based heat spreaders, the thick graphene films are more favorable than the CVD-grown mono- to few-layer graphene films from the processability perspective. Lastly, hBN-based heat spreaders are easier to integrate into electronic systems than graphene-based heat spreaders because hBN films are electrically insulating; however, the mechanical strength of the hBN films needs to be improved.


We investigated the relationship of plasma amyloid beta (Aβ) with cerebral deposition of Aβ and tau on positron emission tomography (PET).18F]flortaucipir scan. Scans were preprocessed by standard techniques, and mean global and regional amyloid and tau values were extracted. Free Aβ42/Aβ40 (Aβ F42:F40) and total Aβ42/Aβ40 (Aβ T42:T40) were evaluated for differences by diagnosis and relation to PET Aβ positivity. Relationships between these measures and cerebral Aβ and tau on both regional and voxel-wise basis were also evaluated.Forty-four participants  underwent amyloid PET and a blood draw. Free and total plasma Aβ40 and Aβ42 were assessed using a validated assay. Thirty-seven participants  also underwent a [Lower Aβ T42:T40 was associated with diagnosis and PET Aβ positivity. Lower plasma Aβ T42:T40 ratios predicted cerebral Aβ positivity, both across the full sample and in CN only. Finally, lower plasma Aβ T42:T40 ratios were associated with increased cortical Aβ and tau in AD-related regions on both regional and voxel-wise analyses.Plasma Aβ measures may be useful biomarkers for predicting cerebral Aβ and tau. Additional studies in larger samples are warranted. AD affects 5.7 million individuals in the United States, a number that is expected to rise to nearly 14 million by 2050 APOE) Recent advances in blood-based assays have suggested that levels of amyloid beta (Aβ) can be precisely measured and are associated with levels of Aβ in the brain, making them good potential biomarkers for AD-risk screening and early detection. Specifically, previous studies have suggested that plasma levels of Aβ, tau, and other target proteins, such as neurofilament light, amyloid precursor protein, and others, are altered in patients with AD and those in the prodromal stage of AD, mild cognitive impairment (MCI). A number of studies have suggested that plasma Aβ42 and Aβ40 measures, as well as the ratio of Aβ42/Aβ40 are reduced in patients with AD and MCI and that these plasma biomarkers can predict the presence of AD and MCI and progression from normal to impaired cognition The goal of the present study was to investigate a measure of plasma Aβ42 and Aβ40 in a cohort of participants who are CN or are diagnosed with MCI or AD. Our initial goal is to replicate previous studies showing that plasma Aβ measures are linked to the presence of cerebral Aβ on PET. Furthermore, we extend these analyses to also investigate whether plasma Aβ42 and Aβ40 are associated with cerebral tau deposition on PET. The overall purpose of this study is to establish whether this plasma Aβ measure represents a promising biomarker for potential screening and early diagnosis of those at risk for AD.22.118F]florbetapir or [18F]florbetaben, cognitive and clinical assessment, and a blood sample. Thirty-seven participants also were studied with tau PET using [18F]flortaucipir. Diagnoses were made by clinician consensus using standard criteria. Briefly, participants with MCI had a significant complaint about their cognition from themselves and/or an informant or clinician, as well as a significant deficit  in either memory or another cognitive domain, but with no significant decline in daily functioning. Patients with AD showed significant impairment on cognitive measures and a decline in daily functioning and met criteria for an AD diagnosis according to the updated National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association criteria Forty-four participants  from the Indiana Memory and Aging Study (IMAS) at the Indiana Alzheimer Disease Center were included in this study. All participants underwent an amyloid PET scan with either Florbetapir  or [18F]florbetaben  were acquired on all participants. Briefly, [18F]florbetapir scans were initiated by an intravenous injection of approximately 10 mCi of [18F]florbetapir. After a 50-minute uptake period, participants were imaged on a Siemens mCT for 20 minutes (50–70 minutes) using continuous list mode data acquisition. [18F]Florbetaben scans involved the intravenous administration of approximately 8 mCi of [18F]florbetaben. After a 90-minute uptake period, PET data were acquired for 20 minutes (90–110 minutes) using continuous list mode acquisition on a Siemens mCT. A computed tomography scan was acquired for both scans for scatter and attenuation correction. List mode data were subsequently rebinned into four 5-minute frames for both types of amyloid PET scans and reconstructed using parameters from the Alzheimer's Disease Neuroimaging Initiative protocol (http://adni.loni.usc.edu), with corrections for scatter and random coincidence events, attenuation, and radionuclide decay. The four 5-minute frames for each type of amyloid PET scan were spatially aligned to each subject's T1-weighted structural magnetic resonance imaging, motion corrected, and normalized to Montreal Neurologic Institute space, using Statistical Parametric Mapping 8 (SPM8). For [18F]florbetapir, the frames were averaged to create a 50-70 minute static image, while for [18F]florbetaben, the frames were averaged to create a 90–110 minute static image. Finally, static images were intensity normalized to the whole cerebellum to create standardized uptake value ratio (SUVR) images and smoothed with an 8-mm full-width half maximum Gaussian kernel. The whole cerebellum region of interest (ROI) was taken from the Centiloid project  were extracted from target ROIs, including the global cortex, lateral parietal lobe, and precuneus, generated using FreeSurfer version 5.1  and extracted using MarsBaR [2.418F]flortaucipir PET was initiated by intravenous injection of approximately 10 mCi of [18F]flortaucipir. After a 75-minute uptake, participants are imaged for 30 minutes by continuous list mode data acquisition on a Siemens mCT, which is subsequently rebinned into six 5-minute frames. Scans were again reconstructed using a standard scanner software program  and according to the Alzheimer's Disease Neuroimaging Initiative protocol (http://adni.loni.usc.edu). Using SPM8, the middle four 5-minute frames (80–100 minutes) were motion corrected, normalized to Montreal Neurologic Institute space using the subject-specific T1-weighted structural magnetic resonance imaging, averaged to create an 80–100 minute static image, intensity normalized to the cerebellar crus to create SUVR images, and smoothed with an 8-mm full-width half-maximum Gaussian kernel.The ). A larger area of amyloid deposition encompassing nearly the entire cortex was significantly associated with plasma Aβ T42:T40 (P < .05 [FWE]).Plasma Aβ F42:F40 was significantly associated with amyloid deposition in the left frontal lobe on voxel-wise analysis (P < .05 [FWE]). Plasma Aβ T42:T40 was significantly associated with tau deposition in the temporal and parietal lobes (P < .05 [FWE]).Cerebral tau deposition in the bilateral medial and lateral temporal lobes was significantly associated with plasma Aβ F42:F40 on voxel-wise analysis  that may alter the relationship between plasma Aβ and cortical amyloid and tau. Additional studies to investigate the impact of comorbidities on this relationship are crucial for ultimately establishing this assay as a clinical tool. In addition, the CN group in this study had a high prevalence of APOE ε4 positivity, suggesting that they represent a higher risk group. Thus, the findings in this study may not accurately generalize to the normal older adult population as a whole. Future epidemiologic studies in community-based samples are needed to explore plasma amyloid measures in the general older adult population. Finally, this is a cross-sectional study, and thus, we could not assess outcome data or whether the assay predicted future cognitive decline. Future studies will allow us to fully assess the outcome of these participants. In addition, future studies should investigate genetic associations and potential genetic modulators of plasma amyloid levels.1.Systematic review: To investigate associations between plasma amyloid biomarkers and neuroimaging measures of cerebral amyloid and tau, we searched for combinations of “plasma,” “blood,” “amyloid,” “PET,” and “Alzheimer's.” We then combined the returned articles to generate a summary of the current literature evaluating blood-based biomarkers of AD in predicting diagnosis and abnormal neuroimaging and cerebrospinal fluid biomarkers.2.Interpretation: Our results provide new evidence that plasma amyloid measures accurately reflect cerebral amyloid deposition and can predict the presence of amyloid in cognitively normal older adults with high accuracy. Furthermore, these results suggest a relationship of plasma amyloid with cerebral tau, which is mediated by cerebral amyloid.3.Future directions: To confirm the current findings, additional analyses with larger samples would be beneficial. In addition, longitudinal follow-up studies with repeated plasma samples, neuroimaging, and cognitive testing would help determine whether the plasma amyloid measure can predict and monitor clinical decline over time.In sum, plasma Aβ measures were reduced in patients with MCI and AD, predicted cerebral Aβ positivity on PET, even in CN individuals, and were associated with cerebral amyloid and tau load. These preliminary findings suggest that these plasma measures of Aβ may be a potential screening tool for detecting AD-related neuropathology in at-risk individuals in clinical settings or pharmaceutical trials. As AD therapeutics are developed, these assays may be helpful in providing an initial determination of which individuals may benefit from follow-on cerebrospinal fluid and/or PET investigations before treatment.


Phenomics provides new technologies and platforms as a systematic phenome-genome approach. However, few studies have reported on the systematic mining of shared genetics among clinical biochemical indices based on phenomics methods, especially in China. This study aimed to apply phenomics to systematically explore shared genetics among 29 biochemical indices based on the Fangchenggang Area Male Health and Examination Survey cohort.P < 10− 4) were associated with three or more traits. After integrating the SNPs related to two or more traits with the GWAS catalogue, 31 SNPs were found to be associated with several diseases (P < 10− 8). Using ALDH2 as an example to preliminarily explore its biological function, we also confirmed that the rs671 (ALDH2) polymorphism affected multiple traits of osteogenesis and adipogenesis differentiation in 3 T3-L1 preadipocytes.A total of 1999 subjects with 29 biochemical indices and 709,211 single nucleotide polymorphisms (SNPs) were subjected to phenomics analysis. Three bioinformatics methods, namely, Pearson’s test, Jaccard’s index, and linkage disequilibrium score regression, were used. The results showed that 29 biochemical indices were from a network. IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Key genes and loci associated with metabolism traits were further identified, and shared genetics analysis showed that 29 SNPs (All these findings indicated a network of shared genetics and 29 biochemical indices, which will help fully understand the genetics participating in biochemical metabolism. Complex traits are the product of various biological signals and some intermediate traits may be affected either directly or indirectly by these signals . A phenoPleiotropy, which is a DNA variant or mutation that can affect multiple traits, is a common phenomenon in genetics . For exathe ALDH2 rs671 polymorphism affected serum TG levels [The Fangchenggang Area Male Health and Examination (FAMHES) cohort was initiated in 2009 in Fangchenggang City, Guangxi, China. It is a comprehensive demographic and health survey that focuses on investigating the interaction between the environment and genetic factors on men’s health. In a previous study, we reported that biochemical indices are closely associated with disease. For example, higher complement 3 (C3) and complement 4 (C4) were associated with an increase in metabolic syndrome (MetS) . Low serG levels . AlthougThe aim of this study was to identify the shared genetics responsible for 29 biochemical indices in the FAMHES cohort using a phenomics approach. Our findings shed light on the relationships between these 29 biochemical indices, including their shared genetic basis and genetic risk loci.P value was less than 0.01) , suggesting that the stratification correlation worked well  associated with all 29 biochemical indices were obtained and then annotated using the SNP function database with default parameters and the south Asian population option [For each trait, we used a linear mixed model estimate fixed value, adjusted with PC1 and PC2 of population stratification and age, respectively, to perform a GWAS. A total of 86,556 SNPs  were found  were the first top factors in the network of these 29 traits and were related to more than 20 traits. Additionally, IgM, CRP, C4, BUN, TG, creatinine and FSH were the second top factors and connected with more than 15–20 traits, and OSTEOC, oestradiol, glucose, FOL, TE, SHBG, FERR, BMI, ALT and HDL were the third top traits, which correlated with more than 10 traits  were correlated with more than 5 traits. After filtering the genes with SNPs (P < 10− 4), there were 71 genes correlated with more than or equal to 3 traits, especially aldehyde dehydrogenase 2 family member (ALDH2), BRCA1 associated protein (BRAP), cadherin 13 (CDH13) and CUB and Sushi multiple domains 1 (CSMD1), which was related to more than 5 traits. In these 71 genes, 38 genes were found to connect more than 5 other genes in the interactional network annotated from the BioGRID database [We selected SNPs with  central . After idatabase  (AdditioP < 1✕10− 3) were associated with three or more clinical biochemical quantitative traits, and 13 of these 481 SNPs were related to more than 5 traits. In these SNPs, rs12229654 (near cut like homeobox 2 (CUX2)), rs2188380 (located in CUX2), rs3809297 (located in CUX2) and rs3782886 (located in BRAP) were related to more than 10 traits. Six SNPs in CUX2 were correlated with more than 5 traits, which indicates that CUX2 should play an important role on this net. In addition, for all the SNPs with P < 1 × 10− 4, 29 SNPs were related to three or more biochemical indices  with the GWAS catalogue [ALDH2 was related to 21 traits, six SNPs  in or near CYP19A1 were mainly associated with hormone measurements. This finding supports the idea that shared genetics for traits can produce correlations among these traits.After integrating the SNPs associated with more than 2 traits, osteocalcin, RUNX family transcription factor 2 (Runx2), and collagen type I (Col1), was significantly higher in ALDH2-WT cells than in ALDH2-G504 L-mut or control cells , C/EBPβ, adipocyte fatty acid-binding protein (Fabp4), and Pparγ (peroxisome proliferator-activated receptor), were much higher in ALDH2-WT cells than in ALDH2-G504 L-mut or control cells  in  studies , 25; howA network of shared genetics and 29 biochemical indices were found in this research study. Not only did one intermediate phenotype have multiple associated SNPs, interestingly, one SNP associating with multiple intermediate phenotypes was also common. The phenomenon of some genes or loci having the ability to affect multiple distinct phenotypic traits is called pleiotropy. Increasing attention has been paid to pleiotropy. In 2011, according to the data of the NIH GWAS website, Sivakumaran found that nearly 5% of SNPS and 17% of genes or gene regions were related to two or more diseases or traits . In 2018Immunoglobulin is produced by plasma cells and lymphocytes and is characteristic of these types of cells and plays an essential role in the body’s immune system. In this study, we found that IgG, IgA, IgE and IgM were the central traits in the biochemical indices network, and these traits could be linked to 19 or more traits. HCY, a naturally occurring amino acid found in blood plasma, plays a central role in biochemical indices by connecting with 23 traits. High levels of HCY have been associated with several body dysfunctions, such as vasculature  and endoALDH2 and BRAP can be related to 9 traits and are connected with 19 and 13 genes, respectively. ALDH2 belongs to the aldehyde dehydrogenase family of proteins, which is the second enzyme of the major oxidative pathway of alcohol metabolism. ALDH2 dysfunction will lead to several diseases, such as cancer [BRAP is a cytoplasmic protein, which can bind to the nuclear localization signal of BRCA1 and other proteins [CSMD1 was related to 8 traits. CSMD1 is a large (~ 390 kDa) membrane-bound complement inhibitor [Pleiotropy refers that some genes or loci that have the ability to affect multiple distinct phenotypic traits. After integrating all the related genes among 29 biochemical indices, surprisingly, s cancer , 37, alcs cancer , and cars cancer . BRAP isproteins . The polproteins  and metaproteins . Additionhibitor . Mutationhibitor . These tP < 10–4) were associated with three or more traits and correlated with each other. These results revealed that the shared regulatory genetics are most likely to drive association signals and play important roles in clinical biological function. This phenomenon may provide important “scaffolding” to support a framework to explore the basic mechanism of biochemical indices.If the SNPs located in sites related to promoter DNase binding, enhancer histone binding and transcript binding, the marginally significant SNPs play regulatory roles affecting protein binding or the presence of eQTL , 46. In Shared genetics are commonly used to build disease-diseased relationship and mine the common disorder of diseases , 48. An P value of correlation analysis, a great deal of potential information was lost while significant loci were obtained. Some loci did not achieve a P cut-off value but itself, but if these loci were located in a short range or were involved in similar functions, these lower p value loci may also affect biological function [P < 1 × 10− 3, and three gene regions in CD28, PRDM1 and CD2/CD58 were identified that were closely related to rheumatoid arthritis [− 8 to 10− 3, and performed a meta-analysis on genetic variation and blood indexes and environmental exposure histories [With the emergence of GWAS, a large number of loci and disease-related information were elucidated. However, due to its strict restriction on the function . Furtherrthritis . To asseistories . Kostem istories .Because there are no mature methods of research on the genetic relationship between traits at the level of genome-wide summary statistics, we set a lower threshold value for obtaining more SNPs for analysis, and then analysed the association of these candidate SNPs by three different methods: Pearson correlation coefficient, LDSC or Jaccard correlation. As we show, even with three different calculation methods, most of the top important traits are similar. Of these, IgA, IgG, HCY, AFP, IgE and B12 were the first top factors in the network. Our research is an experimental attempt to assess the network of shared genetics and 29 biochemical indices.P < 10− 4) were associated with more than 3 traits. Thirty-one SNPs were associated with several diseases (P < 10− 8) by integrating the SNPs related with 2 or more traits with the GWAS catalogue. Third, using ALDH2 as an example to preliminarily explore its biological function, we found that the rs671 (ALDH2) polymorphism could affect the osteogenic and adipogenic differentiation of 3 T3-L1 preadipocytes. We clarified that 29 biochemical indices were from a network and that hub variations/genes played a vital role in biological processes. These findings highlight a network of shared genetics and 29 biochemical indices.We investigated the correlations among 29 biochemical indices through three biological information methods. First, we found that IgA, IgG, IgE, IgM, HCY, AFP and B12 were in the central community of 29 biochemical indices. Second, the shared genetics analysis showed that 29 SNPs  fasting venous blood specimens were obtained between 7:00 am and 10:00 am, and serum samples were extracted and stored at − 80 °C. Triglyceride, cholesterol, HDL-C, LDL-C, glucose, ALT, BUN, uric acid and creatinine were measured enzymatically on a Dimension-RxL Chemistry Analyzer  in the Department of Clinical Laboratory Science at the Fangchenggang First People’s Hospital. CRP, C3, C4, IgA, IgE, IgG, IgM, and ASO were measured with immunoturbidimetric methods on a HITACHI 7600 Biochemistry Analyzer . Ferritin, folate and vitamin B12, TE, oestradiol, FSH, SHBG, insulin, AFP and OSTEOC were measured with the same batch of reagents by electrochemiluminescence immunoassay and HCY assayed by enzyme cycle method using a COBAS 6000 system E601 (Elecsys module) Immunoassay Analyzer .P value for the Hardy-Weinberg equilibrium (HWE) test was greater than 1 × 10− 3, the minor allele frequency (MAF) was greater than 0.01, and the genotype call rate was greater than 95%. The inferred genotypes of SNPs in the genome that were not directly genotyped were computed by the IMPUTE program [Genome-wide SNP genotyping was performed with an Illumina Omni 1 M chip . Among 2012 genotyped subjects, 1999 passed the QC call rate of 95% and were included in the final data analysis. A total of 709,211 SNPs in these subjects passed the QC criteria as follows: the  program   tool to identify the genes containing all of the SNPs for which the P value for the GWAS was less than 1 × 10− 3. The human interactome was obtained by combining protein-protein interaction (PPI) information from the BioGRID database [Phenotypes are linked if they share alterations in genetics. The pathobiology of human diseases might be understood by creating molecular and phenotypic networks , 66. We database .We built correlations among 29 clinical phenomes based on the common genes/proteins between two traits. To minimize the bias in estimating the correlation between two given traits, we calculated the molecular comorbidity index (MCI) by adapting the formula from Grosdidier S  to furthproteinstrait1 and proteinstrait2 are the proteins related to clinical traits 1 and 2, respectively. proteinstrait1 → trait2 are those proteins related to trait 1 that interact with the proteins associated with trait 2 (and vice versa proteinstrait2 → trait1). The two operators ∩ and ∪ denote the intersection and union between the two sets of elements .Where The genetic correlations derived from the summary statistics were evaluated by the GWAS effect size for a given SNP and integrated the effects of all SNPs that were in linkage disequilibrium (LD) with that SNP. The LDSC (which targets genetic correlation) uses variants across the whole genome and is a symmetrical  analysis for the risk factor and the outcomes . In shor2. The osteoblast-inducing medium used was α-MEM (α-minimum Eagle’s medium) containing 10% FBS , 100 nM dexamethasone, 5 mM β-phosphoglyceride and 5 μg/mL vitamin C. The adipogenesis-inducing medium included A and B medium. The A medium was DMEM containing 10% FBS, 100 nM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine and 5 μg/mL insulin. The B medium was DMEM containing 10% FBS and 5 μg/mL insulin. For adipocyte induction, cells were cultured for two cycles of A medium for 2 days and then B medium for 1 day. Cell proliferation was measured by a CCK-8 assay according to the manufacturer’s instructions . Cell apoptosis was examined by Annexin V-APC/7-AAD staining followed by flow cytometry detection. For Oil Red O or Alizarin Red S staining, cells were fixed with 4% paraformaldehyde for 30 min and stained with 4% Oil Red O solution or 0.4% Alizarin Red S. Lipid droplets and calcium nodules were quantified using ImageJ software. Cellular RNA was extracted using an RNA extraction kit . Reverse transcription was performed with the Transcriptor Reverse Transcriptase Kit . Quantitative reverse transcriptase-PCR was performed using a Roche Light Cycler 480 and KANGWEI qPCR Kit . Per-primer sequences are listed in Additional file Full-length ALDH2-WT and ALDH2-G504 L-mut cDNA were cloned into the pTSBOE-CMV-MSC-3flag-EF1-tRFP-F2A-Puro lentivirus vector . The 3 T3-L1 preadipocytes were cultured in Dulbecco’s modified Eagle’s medium (DMEM) with 10% foetal bovine serum (FBS) at 37 °C in a humidified atmosphere with 5% COThe correlations among the 29 biochemical indices were computed by the CORR procedure using SAS 9.0 and defined as the Pearson correlation coefficient between the rank variables. With the exception of BUN, HCY, B12, FERR, OSTEOC, creatinine, uric acid, cholesterol, HDL, LDL, TE and C3, 17 traits without normal distribution were logarithmically transformed to normalize the distribution. The association of the SNPs with 29 clinical quantitative traits was evaluated using a linear regression adjusted for population stratification factors (PC1 and PC2) and age. Population stratification was evaluated by a principal component approach with EIGENSTRAT software .The datasets generated and analysed during the current study are available in the Genome variation Map (GVM) of National Genomics Data Center (NGDC) (Accession Number: GVM000052).Additional file 1: Fig. S1. The cluster dendrogram for the 29 biochemical indices from the FAMHES cohort created with the hclust win R package. In this analysis, two main clusters were produced among these 29 traits. FERR (ferritin), CRP (C-reactive protein), C3 (complement 3), C4 (complement 4), AFP , TG (triglycerides), LDL (low density lipoprotein), ALT , BMI (body mass index), ASO (anti streptolysin) (anti-streptolysin “O”), IgG (immunoglobulin G), IgA (immunoglobulin A), IgM (immunoglobulin M), BUN (blood urea nitrogen), FSH (follicle-stimulating hormone), HDL (high-density lipoprotein), TE (testosterone), SHBG (sex hormone binding globulin), IgE (immunoglobulin E), B12 (vitamin B12), HCY (homocysteine).Additional file 2: Fig. S2. Network characteristics of 5313 associated genes for 29 biochemical indices in individuals from the FAMHES cohort were analysed by Cytoscape. (A) Topological coefficient, (B) degree, (C) clustering coefficient, and (D) closeness centrality.Additional file 3: Fig. S3. The integration of correlated traits from three methods. (A) Venn diagram of the integration of correlated traits from three methods. (B) The related traits were integrated if they fulfilled the following conditions: the Pearson coefficient was greater than 0.3, the P value was less than 0.01, the Jaccard coefficient was greater than 0.6, or the LDSC p value was less than 0.05. Each testing method was denoted by a specific colour: green for Jaccard, and blue for LDSC.Additional file 4: Fig. S4. A lentiviral vector was used to overexpress ALDH2-WT or ALDH2-G504 L-mut in 3 T3-L1 preadipocytes. (A) Localization of the Glu504Lys substitution mutation in ALDH2. Ex: exon. (B) The plasmid used to express the ALDH2-Gluc504Lys mutant protein in 3 T3-L1, ALDH2-WT was expressed using the same plasmid backbone. (C) Sequencing analysis of the ALDH2 gene exogenously expressed in 3 T3-L1 cells infected with ALDH2-WT (top) or ALDH2-G504 L-mut (bottom). (D) Expression of the transfected ALDH2 protein in 3 T3-L1 cells was indirectly assessed by the detection of RFP expression from the lentiviral vector. An RFP signal was detected by fluorescence microscopy at 48 h after infection in both 3 T3-L1 cells infected with ALDH2-WT and ALDH2-G504 L-mut. RFP control means 3 T3-L1 cells infected with plasmid backbone.Additional file 5: Table S1. Information on the 27 clinical quantitative traits from 1999 populations.Additional file 6: Table S2. Genetic correlation estimates, standard errors and P values for selected pairs of traits.Additional file 7: Table S3. The information on essential genes correlated with more than 3 traits.Additional file 8: Table S4. Twenty-nine SNPs (P < 1 × 10− 4) related to more than 3 traits were annotated in the HaploReg database.Additional file 9: Table S5. The annotation of 31 (P < 1 × 10− 4) SNPs was associated with more than 1 trait.Additional file 10: Table S6. The primer sequences of osteogenic and adipogenic differentiation in 3 T3-L1 cells.


Within the mitotic spindle, kinesin motors cross-link and slide overlapping microtubules. Some of these motors exhibit off-axis power strokes, but their impact on motility and force generation in microtubule overlaps has not been investigated. Here, we develop and utilize a three-dimensional in vitro motility assay to explore kinesin-14, Ncd, driven sliding of cross-linked microtubules. We observe that free microtubules, sliding on suspended microtubules, not only rotate around their own axis but also move around the suspended microtubules with right-handed helical trajectories. Importantly, the associated torque is large enough to cause microtubule twisting and coiling. Further, our technique allows us to measure the in situ spatial extension of the motors between cross-linked microtubules to be about 20 nm. We argue that the capability of microtubule-crosslinking kinesins to cause helical motion of overlapping microtubules around each other allows for flexible filament organization, roadblock circumvention and torque generation in the mitotic spindle. Some kinesins exhibit off-axis power strokes but their impact on motility and force generation in microtubule overlaps has not been investigated so far. Here authors use a 3D in vitro motility assay and find that Ndc’s off-axis motor forces generate torque in antiparallel microtubules which causes microtubule twisting and coiling. However, the spindle is a three-dimensional (3D) structure and interesting mechanical details may emerge in the third dimension, which are not just intuitive extensions of the 2D model. For instance, previous studies have shown that the mitotic spindle is twisted with a distinct left-handed chirality6.The mitotic spindle is a complex subcellular machinery that segregates chromosomes during eukaryotic cell division. Several in vivo and in vitro studies provide us with a consolidated two-dimensional (2D) model, detailing the mechanisms employed by dynamic microtubules, kinesins and microtubule-associated proteins (MAPs) to assemble, maintain and disassemble the spindle in order to coordinate chromosome segregation7, kinesin-89 and kinesin-1411, have been shown to exhibit off-axis components in their stepping behavior, i.e., they do not move strictly parallel to the longitudinal microtubule axis. These mitotic kinesins are microtubule cross-linkers involved in connecting and sliding microtubules14. To address if their off-axis  motion translates to cross-linked microtubules, we explore the 3D motion of microtubules propelled along each other by the kinesin-14. Kinesin-14 is a non-processive, minus-end directed motor with an additional diffusive microtubule-interaction site in its N-terminal tail domain that enables the motor to cross-link and slide antiparallel microtubules12. Specifically, we suspend long microtubules on nano-fabricated ridges15 and track the motion of cross-linked, shorter microtubules along the long ones. Besides being able to measure the in situ spatial extension of the motors between the cross-linked microtubules, we discover that antiparallel microtubules both rotate around their own axis and helically move around each other in a right-handed manner. Importantly, the torque resulting from the underlying off-axis motor forces is large enough to cause microtubule twisting and coiling.Interestingly several mitotic kinesins, like kinesin-5Drosophila melanogaster kinesin-14 motors, Ncd, we suspended parts of long “template” microtubules such that short cross-linked “transport” microtubules could access the entire lattice of the suspended template microtubules. As illustrated in Fig. 15. Atto647n-labeled transport microtubules were cross-linked to the template microtubules via full length GFP-Ncd (4 nM if not otherwise noted), hereafter referred to as Ncd, in ADP. After the addition of ATP, antiparallel transport microtubules started to slide along the template microtubules while parallel transport microtubules remained locked in their position. To observe the position of the transport microtubules with respect to the template microtubules, the microtubule positions were tracked in 2D individually in the rhodamine and Atto647n fluorescence channels using FIESTA16 and the distance of the center points of the transport microtubules from the tracked center line of the template microtubules, referred to as the sideways distance, were obtained  of the template microtubules and zero when the transport microtubules are on top (or bottom) of the template microtubules.To study the uninhibited sliding motion of cross-linked microtubules driven by ned Fig. . Since tN = 7 complete rotations). When the transport microtubule encountered the ridge, its helical motion was blocked without significant impediment to the longitudinal motion, and it stayed at the right-hand side of the template microtubule. The transport microtubule only resumed its helical motion after the entire microtubule (1.8 μm long) had left the ridge. This indicates that surface immobilization of the template microtubule on the ridge hindered the helical motion of the transport microtubule. Since the helical motion of the transport microtubule on the ridge was locked on the right-hand side of the template microtubule, we infer that the helical motion is right-handed (or clockwise in the direction of motion).To interpret the 3D motion of antiparallel transport microtubules, the sideways distance was plotted with respect to the distance traveled in the longitudinal direction of the template microtubules. Figure N = 63). This clearly indicates that the helical motion induced by Ncd is right-handed. Only in a couple of events the transport microtubules moved around the surface-immobilized template microtubules, presumably at locations of statistically low densities of anti-rhodamine antibodies. These observations are consistent with 2D sliding motility assays performed on unstructured glass coverslips  and upon removing the flip events became −45.5 ± 0.1 nm (N = 83). At low Ncd concentration (0.02 nM), the sideways motion of transport microtubules became erratic. However, there was still a bias to the right-hand side with a mean sideways distance of −26.8 ± 0.7 nm (N = 24). Parallel transport microtubules (31 events) were found to be locked, both in their longitudinal and axial direction, and did not exhibit any preference for which side of the template microtubule they were bound to  exhibited robust helical trajectories in the valley regions along suspended template microtubules  for all 3D sliding events with at least two complete helical turns. We obtained a mean value of 86.2 ± 4.4 nm  is high enough to twist and coil microtubules.Having shown that transport microtubules rotate around their own axis and move helically around the suspended template microtubules, we asked if the underlying off-axis motor forces would generate a torque that was high enough to cause twisting deformations of microtubules. Towards this end, we performed 2D sliding motility assays (Ncd concentration of 4 nM) on unstructured glass surfaces with long transport microtubules and short, surface-immobilized template microtubules. We focused on events, where the leading end of a transport microtubule was locked in a parallel configuration on one template microtubule and the trailing end of the same transport microtubule was sliding in an antiparallel configuration on another template microtubule Fig. . We foun20. This also became evident in our experiments where individual transport microtubules could helically move around the suspended parts of template microtubules, but were held on the right-hand side of the surface-immobilized parts of the template microtubules . The vast majority (about 96%21) of these microtubules are expected to comprise 14 protofilaments, which provide a left-handed supertwist of about 8 µm23. Conceivably, the origin of the right-handed helical motion is related to the off-axis component in the power stroke of Ncd , elucidated in previous studies exploring the rotational motion of microtubules gliding on surface-bound Ncd motors11. However, the geometry in which the motors perform their power strokes is crucially different. In previous studies, motors were bound rigidly to a planar surface . In our current study, microtubules are linked to each other by motors diffusively coupled to one microtubule via their tail domains and interacting with the other microtubule via their motor domains (microtubule–microtubule sliding geometry). Strikingly, in this geometry (where motor force in the forward direction goes down significantly18), transport microtubules still rotate around their own longitudinal axis but additionally also move helically around the template microtubules. For parallel transport microtubules, the motors facing opposite directions between the cross-linked microtubules antagonize each other, locking the microtubules longitudinally as well as axially  where a similar decrease in the sliding velocity was attributed to steric  hindrance between the motors24. At the same time, we observed that the rotational frequency stayed constant upon variation of the motor density  on the total number and length of template microtubules bound to the surfaces, (ii) on the total number and length of transport microtubules in solution, as well as (iii) on the history of events .The sizeable variation in the observed helical pitches and velocities of transport microtubules in the 3D sliding assays cannot be entirely attributed to motor stochasticity as microtubule sliding involves multiple motors. In addition, we did not observe any correlation of the helical pitches and velocities with the lengths of the transport microtubules, suggesting that the absolute number of motors in the overlaps between template and transport microtubules alone does not influence helical pitch or velocity. Because it was difficult to systematically investigate the influence of the motor density in 3D sliding motility assays with suspended microtubules, we employed FLIC-based 2D gliding and sliding motility assays. We found that an increase in the Ncd motor density decreased the microtubule velocity . This may be achieved by numerically analyzing the dynamics of the microtubule shapes in assays similar to the experiments presented here or by extending our assay to enable direct torque measurements, for example by using 3D optical tweezers15. Most importantly, based on our observations we conjecture that Ncd can generate torques, likely high enough to be relevant in vivo, for example in the mitotic spindle.While we showed that Ncd motors in the sliding geometry cause an intricate axial motion of short transport microtubules, it is not evident that the torque generated by the motors is large enough to be important for intracellular, mechanical events. Both on structured and unstructured glass surfaces  while the other one is free  one microtubules is fixed at some point  of different cross-linking motors and MAPs in their active states—in correlation with their functional behavior as generators of longitudinal as well as axial motility and force.In addition to resolving the 3D trajectories of microtubules sliding around each other, our experimental approach provides a compelling means to measure the extension of motors in their active state while cross-linking and sliding microtubules. For Ncd, we find an in situ extension of 18–21 nm which is in the same range as estimated in earlier electron-microscopy studies for microtubule cross-linker mixtures in yeast cells, including the homolog kinesin-14, klp27. In microtubule overlaps where kinesin-5 and kinesin-14 co-exist, the two motors antagonize each other in the longitudinal direction25 but the torques generated by them are expected to add up  of the evolutionarily conserved motor domains of kinesin motors or if there is any particular function associated with it.In summary, this study elucidates that Ncd motors induce a helical motion of antiparallelly cross-linked microtubules around each other as well as a rotational motion around their own axis. In vivo, such motion (as opposed to a strict linear motion) might be useful to circumnavigate obstacles on microtubule lattices or in the surrounding environment. While minus-end directed kinesin-14 induces a right-handed rotational motion, other plus-end directed cross-linking kinesins, like kinesin-5, have been shown to induce left-handed rotational motion up Fig. . Therefo6-tagged D. melanogaster full length GFP-Ncd expressed in SF9 insect cells (cell line IPLB-Sf-21-AE) using a baculovirus expression system36. Cells were lysed in 25 mM Tris, 300 mM NaCl, 5 mM imidazole, 5 mM MgCl2, 0.2% (v/v) Tween-20, 10% (v/v) glycerol, 1× protease inhibitor cocktail, 10 mM dithiothreitol (DTT), 1 mM ATP, pH 7.4 and proteins were bound to Ni-NTA resin. Proteins were eluted by cleavage of the His6-tag with His-tagged PreScission protease18. For FLIC-based sliding motility assays, a different batch of full length GFP-Ncd expressed in Escherichia coli a was used12. Cells were lysed  Tween-20, 300 mM NaCl, 20 mM imidazole, 1× protease inhibitor cocktail, pH 7.2 and proteins were bound to a Talon cobalt-affinity resin. After elution with 300 mM imidazole, proteins were further purified with size exclusion chromatography.Most experiments were performed with recombinant His2 glass coverslips  were imprinted with a UV curable resin, EVG NIL UV/A 200 nm (EV Group) using UV nanoimprint lithography (UV-NIL) as described in Mitra et al.9. The structure imprinted on the glass coverslips was characterized by repeated pattern of relief lines (that form the ridges) with a height of 370 nm  and a width of 2 μm (or 5 μm), separated by 10 μm wide valleys between the ridges.Cleaned 22 × 22 mmα,β)-methylene-diphosphonate (GMP-CPP) grown, taxol-stabilized (referred to as double stabilized). Template microtubules were long (average length > 15 μm) and rhodamine-labeled, while transport microtubules were short (average length 1–2 μm) and Atto647n-labeled. Totally, 4.6 μM rhodamine-labeled porcine tubulin was added to a polymerization solution, comprising of BRB80  supplemented with 1 mM GMP-CPP  and 4 mM MgCl2, incubated on ice for 5 min followed by 30 min at 37 °C, to grow short microtubule seeds. The solution was centrifuged at 17,000×g for 15 min at 25 °C to remove free tubulin and the pellet was resuspended in a new polymerization solution supplemented with 0.4 μM of rhodamine-labeled tubulin. This solution was incubated overnight at 37 °C with low tubulin concentration allowing microtubule seeds to anneal and form long microtubules. The solution was then centrifuged at 17,000×g for 15 min at 25 °C and the pellet was resuspended in BRB80T solution (BRB80 supplemented with 10 μM taxol). Transport microtubules were grown as short Atto647n-labeled microtubule seeds in the same way as described for the first cycle of polymerization for template microtubules.Both, template and transport microtubules, were guanylyl-(17) were used. For the FLIC-based gliding motility assays, rhodamine-speckled microtubules were used.For the FLIC-based sliding motility assays, Cy5-labeled template microtubules (grown as described above) and rhodamine-speckled transport microtubule . Microtubules were sedimented as described above, resuspended in BRB80T and allowed to anneal for 48 h.For the microtubule coiling assays, taxol-stabilized Atto647n-labeled transport microtubules were grown at 37 °C for 2.5 h in BRB80 supplemented with 30 µM Atto647n-labeled tubulin, 4.8% (v/v) dimethyl sulfoxide, 4 mM MgCl2, 75 mM KCl, 10 µM taxol, 200 µg mL−1 casein, 10 mM DTT, 0.1% (v/v) Tween-20, 20 mM d-glucose, 100 µg mL−1 glucose oxidase, 10 µg mL−1 catalase and either 1 mM ATP (MB-ATP) or 1 mM ADP (MB-ADP). 3D sliding motility assays on suspended template microtubule were performed in microfluidic flow cells constructed on 22 × 22 mm2 glass coverslips patterned with UV-NIL polymer resin and 18 × 18 mm2 unpatterned glass coverslips, both dichlorodimethylsilane (DDS)-coated to make the surface hydrophobic37. Before silanization, the patterned coverslips were cleaned mildly (using 5% mucasol and then 70% ethanol) to avoid corrosion of the structure. 2D sliding motility assays on surface-immobilized microtubules were performed on unpatterned silanized coverslips or silicon wafers (10 × 10 mm2) with a 30 nm thermally grown oxide layer . In both, 2D and 3D sliding assays, flow cells were flushed with the following sequence of solutions: (i) Bead solution consisting of 2% (v/v) 200 nm Tetraspeck beads . (ii) Antibody solution consisting of 20–200 µg mL−1 anti-rhodamine antibody  in phosphate-buffered saline (PBS) for unspecific binding of antibodies to the surface (incubation time 5 min). (iii) 1% pluronic F-127 in PBS (Sigma) in order to block the surface from unspecific protein adsorption (incubation time >60 min). (iv) BRB80 washing step to remove unbound F-127 and exchange buffers. (v) Rhodamine-labeled template microtubule solution in BRB80T, followed by an immediate washing step with MB, in order to immobilize microtubules perpendicular to the ridges. (vi) MB-ADP solution containing Ncd (concentration ranging between 0.02 and 40 nM) for the motors to bind to the template microtubules. (vii) MB-ADP solution containing Atto647n-labeled transport microtubules, followed by immediate washing step with MB-ADP, in order to cross-link few transport microtubules to the template microtubules and wash away the unbound ones. (viii) MB-ATP solution at the microscope after finding a suitable field of view. For FLIC-based sliding motility assays, Cy5-labeled template microtubules were immobilized on the surface using anti-Cy5 antibodies  and rhodamine-speckled transport microtubules were used.Motility buffer (MB), used in all motility assays, consisted of 20 mM Hepes at pH 7.2, 1 mM EGTA, 2 mM MgCl17 with replacement of BRB80 based motility buffer with MB-ATP.For 2D FLIC-based gliding motility assays on Fab-fragment  and mouse anti-GFP antibody-coated surfaces , the assay was performed in flow cells constructed from DDS-coated silicon wafers and glass coverslips as described in Mitra et al.38. For sliding motility assays, a field of view was selected when there were three (or more) Tetraspeck beads bound to the surface and several trackable template microtubules suspended between ridges. Template microtubules were imaged in the TRITC channel (for 50–100 frames at 3–10 fps with exposure time 100–300 ms) before and after imaging the transport microtubules in the Atto647n channel (for 5–15 min at 3–10 fps with exposure time 100–300 ms) to confirm that the template microtubules do not move while imaging the transport microtubules. For FLIC-based motility assays, a 63× water immersion 1.2NA objective (Zeiss) was used (higher working distance) in order to image rhodamine-speckled microtubule (for 5–15 min at 1 fps in the TRITC channel with exposure time 400 ms) on the silicon wafer surfaces on the far side of the flow cells.Optical imaging was performed using an inverted fluorescence microscope  with a 63× oil immersion 1.46NA objective (Zeiss) in combination with an EMCDD camera  controlled by Metamorph (Molecular Devices Corporation). A LED white light lamp  in combination with a TRITC filterset  and an Atto647n filterset , corresponding to rhodamine-labeled microtubules and Atto647n/Cy5-labeled microtubules, respectively, were used for epifluorescence imaging. The imaging temperature was maintained at 24 °C by fitting a custom-made hollow brass ring around the body of the objective and connecting it to a water bath with a cooling/heating unit 16 (version 1.6.0). First, the Tetraspeck beads, that serve as fiducial markers, were tracked in both channels to obtain the color offset correction  between the two channels as well as the image drift correction in the corresponding channels. Template microtubules with relevant sliding events were tracked. Since template microtubules were immobilized, the filament position (tracked over 50–100 frames) was averaged to obtain the filament position. Sliding transport microtubules  and locked transport microtubules  on template microtubules with sliding events (to know the microtubule orientation) were tracked. After color and drift correction, the sideways distance was obtained as the perpendicular distance of the center point of the tracked transport microtubule from the averaged center line (tracked over the recorded 50–100 frames) corresponding to the template microtubule  and sliding transport microtubules (Atto647n channel) were analyzed using FIESTARotational pitch, end-to-end velocity and the diameter of the helical path corresponding to each rotation of a helical sliding event was determined by manual computer-aided measurement of the sideways distance versus forward distance plots. For a given sliding event, measurements from individual rotations were averaged to obtain the mean pitch, velocity and diameter of helical path. Accounting for the helicity of the path traversed by the sliding microtubule, the actual velocity along the path . The kymographs were then analyzed with MATLAB  using the speckle analysis method17.The rotational pitch of the gliding or sliding microtubules in the FLIC-based motility assays was obtained from their kymographs, which were generated in Fiji41. Here, the distribution (N number of measurements) was resampled by randomly picking N measurements from the measured distribution (with replacement) and calculating the median of the resampled distribution. This was repeated 1000 times. The resulting bootstrapping distribution was used to estimate the parameter (mean of the bootstrapping distribution μ) and its error (standard deviation of the bootstrapping distribution σ). All values and errors as well as error bars in this paper use μ ± 3σ , unless otherwise noted.For estimating parameters from any given distribution  we used a bootstrapping approachData for the microtubule coiling experiments were acquired from five independent experiments. Data for all other experiments were acquired during at least three independent experimental days, performed over several months.In boxplots Fig.  midline Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2Supplementary Movie 3Supplementary Movie 4Reporting Summary


In view of the deficiency of the split grouting theory for the filling area, a 3D simulated grouting test system was designed to explore the slurry diffusion law, reinforcement mechanism of split grouting in a filling soil, and effect of grouting reinforcement. The test system included an experiment bench system, grouting system, and information monitoring system, using which experimental research on split grouting in a filling soil was conducted. The grouting model experiment procedure was introduced first, following which the diffusion rule of slurry in the filling medium and the reinforcement mechanism of split grouting were analyzed according to the properties and distribution characteristics of grouting veins after grouting reinforcement. Finally, a uniaxial compression test, light dynamic contact test, permeability test, and laboratory geotechnical test were conducted on the soil before and after grouting. The relationship between the zoning characteristics of different properties of veins and the mechanical properties of filling soil were discussed. The results showed that there were three types of grouting veins: trunk grouting, branch grouting, and permeable grouting. The injected soil body was strengthened by the three-stage grouting vein network of the mentioned vein types and the compaction between soils. After the grouting, the uniaxial compressive strength of the filling soil increased by an average of 186%, and the permeability coefficient decreased by an average of 47 times. The cohesion and internal friction angle increased by 45.3% and 44.9%, respectively. Additionally, density, water content, and other indicators of filling were improved. The bearing characteristics reflected by a dynamic contact test were consistent with the distribution of grouting veins. The research results offer significant guidance for the reinforcement mechanism of split grouting and the evaluation of the grouting effect. Grouting reinforcement technology manipulates slurry penetration, compaction, and splitting into rock cracks or soil layers. Soil with cracks and a loose structure is consolidated, forming a certain strength or impermeability of the “stone body” . GroutinAt present, many scholars have done substantial research on grouting reinforcement mechanisms . In termIn terms of experimental research, Li et al.  carried However, in the above studies, other scholars have only studied the slurry diffusion rules from the theoretical perspective or carried out laboratory model tests on sand or clay. Owing to the particularity of grouting engineering, the randomness and uncertainty of the grouting process was ignored when only theoretical derivation and numerical simulation were used. In addition, many assumptions were needed, so it was difficult to truly reflect the grout diffusion law and reinforcement mechanism of compaction grouting and splitting grouting ,17. FurtIn addition, inaccurate evaluation of the grouting effect can lead to serious safety accidents, making reasonable evaluation of the grouting effect a major problem after the grouting . At presIn summary, to investigate the slurry diffusion law and reinforcement mechanism under the condition of split grouting in the filling area and to better evaluate the effect of grouting reinforcement, a 3D grouting model test system was developed. A model test was conducted with excavated filling under the surface of the construction site of a project in Changsha, Hunan Province, China. The distribution characteristics of slurry veins were obtained, and the diffusion law and reinforcement mechanism of grouting in filling soil were studied. Through a uniaxial compression test, light dynamic penetration test, and indoor penetration test of the reinforcement bodies in different reinforcement areas after grouting, the grouting effect of the filling soil was tested. On the basis of the weighted average method, the overall improvement of filling soil performance was obtained. This study can truly reflect the process of the split grouting of the filling medium and summarize its reinforcement mechanism and performance improvement. This study offers inspiration and reference to practitioners who wish to conduct similar experiments related to the design and construction of split grouting in the fill area.In view of the weak bearing capacity of the foundation and the poor effect of grouting reinforcement in the filling area, a 3D grouting model test system was designed to explore the slurry diffusion law and reinforcement characteristics under the condition of the split grouting of filling soil. The system can simulate the compaction grouting and splitting grouting of various soils. After the grouting, the injected medium was excavated to obtain the distribution characteristics of grouting veins, and then the slurry diffusion law and reinforcement mechanism were revealed. As the grouting process is unable to be viewed to completion in engineering applications, it is difficult to directly judge whether the grouting effect meets the needs of the project. The indoor model test can not only reflect the splitting grouting process of the filling medium, but also facilitate the sampling of the filling soil after the grouting. The in situ and indoor tests of the filled soil before and after grouting were carried out, and the test results were compared and analyzed. Combined with the characteristics of the exposed pulping veins, the improvement effect of split grouting on soil filling performance can be analyzed qualitatively and quantitatively. The structure diagram of the test system is shown in To facilitate installation, disassembly, observation, and sampling, a layered combination method was used to design the model test bench. Its structural diagram and schematic diagram are shown in The grouting system mainly included the grouting pump and grouting material. The grouting pump consisted of a ZB-HG-60/8 double-fluid grouting machine with a rated flow of 60 L/min and a rated pressure of 8 MPa. The rate of grouting could be controlled by adjusting the expansion and contraction frequency of the cylinder piston. The grouting material was cement–sodium silicate (C–S) slurry commonly used in engineering. The cement was P.O42.5 ordinary Portland cement purchased from Hunan Kangda company, and the sodium silicate was ordinary sodium silicate solution from Hunan Hetang chemical company, with a modulus of 3.2 and a concentration of 25°Be. Before grouting, the cement slurry and sodium silicate solution were stored in the slurry storage bucket. In addition, the grouting system also included a mud mixer, sieve , transparent pulp suction pipe, high-pressure pipe, and grouting steel pipe , among others. Under the grouting pressure, the slurry was injected into the soil layer through the bottom of the grouting pipe, as shown in The monitoring system included both image acquisition and data acquisition. The data acquisition portion was composed of a CJ-G3P grouting recorder, supporting a PCM400 pressure sensor, JDK-300 electromagnetic flowmeter, and computer. The experimental results were recorded via an HD camera to provide a guarantee for the smooth progress of the test. In the experiment, the electromagnetic flowmeter was connected to the grouting line after the grouting pump in series. Both ends of the flowmeter were connected to the grouting line with matching flanges and steel pipes. The direction of the arrow on the electromagnetic flowmeter must be consistent with the direction of the slurry flow. When grouting, the grouting recorder was connected to the interface corresponding to the electromagnetic flowmeter, and the power line was connected to intervene the 220 V alternating current. During the grouting process, the grouting recorder’s pressure sensor automatically acquired the grouting pressure, flow, as well as process parameters such as density, grouting quantity, and the electrical signal. The collected data were displayed on the recorder and eventually routed to an external computer and printed out. The element of the pressure transmitter was a resistance strain gauge. The detection system was composed of a light dynamic penetrator , soil sampler, standard ring cutter, universal testing machine, and TST-55 penetrator. They were used to detect the differences in the physical and mechanical properties of the soil before and after grouting. The information monitoring equipment is shown in (1)The spatial distribution characteristics of grouting veins along the direction of slurry migration under the condition of split grouting in filling medium were obtained, and the reinforcement mechanism of split grouting was discussed.(2)The physical and mechanical parameters, bearing capacity, and permeability coefficient of the injected medium before and after grouting were tested, and the improvement effect of splitting grouting on the filling strength was comprehensively evaluated.The grouting material adopted the C–S double slurry commonly used in engineering. The cement is P.O42.5 ordinary Portland cement. The cement slurry water–cement ratio was m(W)/m(C) = 1:1. The sodium silicate solution used was of module 3.2 and concentration 25°Be. The volume ratio of the double slurry is V(C)/V(S) = 2:1.The soil used in the experiment was plain fill with a uniform texture, which was located 1–3 m below the construction site surface in the town of Datuo, Changsha city, Hunan province, China. The basic parameters of the soil are listed in The nonuniform coefficient of soil Carry out simple sieving of the filling soil retrieved from the construction site. Remove the large particles of stones, plants, and garbage; then, mix the soil to make it uniform in texture, and take soil samples at random to determine its particle size distribution.Connect the pieces of equipment into a whole system as shown in The filling process is carried out in layers, with the filling height of each layer not exceeding 0.3 m. After reserving a gap in the grouting pipe, the soil is shoveled into the model cavity, and the soil is evenly tamped from the center outwards with the tamping machine. Then, the soil samples of each layer are collected randomly at four locations with a standard ring cutter to test their compactness. Ensure a soil sample density difference of less than 10%. At the same time, the average density error of the soil samples in different layers should be less than 10%. If it fails to meet the requirements, the soil should be rammed again. After meeting the requirements, the next layer of soil should be filled and rammed until the four layers of soil with a total height of 1.2 m are filled.Carry out light dynamic preliminary tests on the soil before grouting; the test points should be evenly and randomly distributed. Record the times that the hammer falls when the penetration instrument enters 300 mm into the soil . After the light dynamic penetration test is completed, the orifices generated during the test should be backfilled and compacted.Prepare the cement slurry and sodium silicate solution. The water–cement ratio of the cement slurry should be 1:1; the same quality of water and cement should be mixed evenly through a 5 mm sieve into the slurry bucket. The sodium silicate solution is to be prepared as 25°Be and stored in another slurry bucket.Conduct pre-grouting. A hole with a diameter of 70 mm and a depth of 1 m is drilled using a hydro-electric drill on the flat ground near the testbed. Lower the 1 m long grouting pipe for pre-grouting to ensure the normal use of the pressure gauge, flow meter, and grouting system. Clean the grouting pipe after the completion of pre-grouting. A 61.8 mm diameter sampler is used to sample in the center of the model barrel with a total sampling depth of 1050 mm. Then laboratory tests are carried out on the soil samples to determine their density, water content, permeability coefficient, shear strength, and compressive strength.Conduct grouting. Before the grouting, drain the water from the pipeline. When thick slurry appears at the pressure relief hole, close the pressure relief hole, and then start grouting and observe the changes of the injected soil surface, slurry flow, grouting pressure, and other parameters.Seven days after the grouting, a light dynamic preliminary test should be conducted again at the corresponding position.Remove the shell of the test cavity, excavate the reinforced soil layer by layer from top to bottom, and observe the properties and distribution of grouting veins. Soil samples should be collected in different grouting areas, with no less than six samples in each area; then, the soil density test, water content test, permeability test, direct shear test, and uniaxial compression test should be carried out.The experiment flow chart is shown in A single-pipe/single-hole grouting method was adopted in the experiment. The grouting pressure range was 0–0.5 MPa, and the grouting rate was 0–10 L/min. Take the grouting volume of 100 kg as the control standard for the end of the experiment. During the grouting process, the grouting should be stopped when the slurry appears on the top surface of the injected soil or the pressure exceeds 1 MPa.The experimental results were analyzed from two aspects: the properties and the distribution characteristics of grouting veins and the reinforcement effect of split grouting. After the excavation of the injected soil, it was found that the slurry was mainly retained and distributed in the form of veins and slurry soil combination. The diffusion rule and reinforcement mechanism of split grouting slurry in the filling medium were studied by analyzing the properties and distribution characteristics of the slurry veins. In the evaluation of the grouting reinforcement effect, the uniaxial compression test, light dynamic touchdown test, indoor geotechnical test, and permeability test were carried out to compare and analyze the physical and mechanical properties of the injected soil before and after grouting. The improvement of the filling performance of the split grouting was obtained, and the experimental results were systematically analyzed from both qualitative and quantitative perspectives.The distribution of exposed veins is shown in The trunk grouting veins were generally distributed in a horizontal plate-shape, with the grouting hole as the center. The grouting veins continued to expand further along the direction of slurry migration, forming a planar plate-shaped structure with varying thickness. The thickness of the grouting veins near the grouting hole was larger, and the thickness of the grouting veins decreased gradually as they expand further outward. In general, the trunk grouting veins of the first layer did not run through the entire filling layer, while the second and third slurry veins did run through the entire filling layer, which extended to the lateral wall of the model cavity. The planar distribution of trunk grouting veins is shown in Between the trunk grouting veins, the intersecting branch grouting veins extend to form an intersecting network. After the trunk splitting cracks were formed, the slurry was injected into the cracks and the surrounding soil was compressed. As a result, the soil around the trunk veins was continuously compressed and its strength increased. As the pressure continued to increase, splitting would occur again on the surface of least resistance. In general, the second split plane would be perpendicular to the first split plane. With the grouting, the subsequent split plane would continue to be generated on the weak surface in the soil, and would eventually form crisscrossed branch veins that would envelop the filling structure. The branch grouting veins embedded in the filling played the role of anchorage, which was mainly distributed near the grouting hole. As shown in For the permeable filling areas, the slurry penetrated the filling pores and continuously compacted the pores, so the physical and mechanical properties of the soil body were improved. The slurry appeared as irregular and discontinuous fine grouting veins, which were mainly positioned away from the grouting hole and the trunk grouting veins, near the top and bottom of the model cavity. These tiny grouting veins were less dense and lighter in color. Compared with branch grouting veins, their size and width were smaller, in the range of 0.5–2 mm, as shown in From the characteristics and distribution of the grouting veins, the reinforcement effect of split grouting on the filling was mainly reflected in two aspects. On one hand, the trunk grouting veins replaced the filling in corresponding parts, playing the role of a supporting skeleton of the injected medium. The cross of the branch grouting veins formed a network structure, which acted as a type of reinforcement for the soil, and the branch grouting veins were embedded into the filling to play the role of anchoring. On the other hand, the slurry had significant compaction and permeation effects on the filling. The expansion of the slurry splitting channel forced the pore water pressure in the surrounding soil to rise. After grouting, the pore pressure would gradually dissipate, effective stress would increase, soil would be consolidated and compacted, and shear strength of the soil would increase accordingly.According to the distribution of grouting veins after the grouting, in order to simplify the calculation, the thickness of the trunk grouting veins was assumed to be unchanged along the expansion direction, and the areas between the trunk grouting veins were all assumed to be branch grouting veins, while the other areas were considered to be the permeable filling areas. The distribution law of the filled soil slurry veins after excavation was observed, and the map of the filled soil partition was created with the same scale, as shown in The compressive strength test of the filling samples was carried out, and the grouting stone body was cured for seven days at room temperature. A uniaxial compression test of the samples in each partition was conducted with the CB-WAW-1000 universal testing machine. Then, the equivalent elastic modulus of the injected soil was determined by the coefficient weighted average of the volume of each grouting reinforcement area in the whole fill volume. The uniaxial compressive strength test results of the filling samples are listed in The average compression modulus of the grouting reinforcement range is as follows:According to Equations (3) and (4), the average compressive strength of the filling before grouting reinforcement was 6.65 MPa, and the average compressive strength of the trunk grouting vein area after grouting was 35.58 MPa; this indicates an increase of 431% after grouting reinforcement. The average compressive strength of the branch grouting vein reinforcement area was 23.18 MPa, which was 248% higher than that of the area before reinforcement. The average compressive strength of the permeable filling area was 10.7 MPa and the equivalent elastic modulus of the injected soil was 19.02 MPa, which were 61% and 186% higher than that of the area before grouting, respectively. This indicated that the three-stage grouting vein network of trunk vein-branch, vein-permeable filling veins could significantly improve the strength of the injected soil.The in situ test could well reflect the true stress–strain state of the soil under undisturbed conditions. The research used a light dynamic preliminary test to quantitatively understand the change of mechanical properties of the soil before grouting. Before and after grouting, six points were selected for the dynamic penetration test. The arrangement of penetration points is shown in The physical and mechanical parameters of soil samples from different areas before and after grouting were measured via indoor geotechnical tests, as shown in The permeability coefficient of soil samples was measured by a TST-55 permeameter. To avoid disturbance, a large block was cut out first during sampling; then, a cutting tool was used to cut along the edge of the ring knife. After the ring knife was embedded in the sample, the sample was truncated and leveled with the top and bottom of the ring tool as the boundary. The sample was put into the sleeve of the permeameter, and molten wax was poured into the gap between the sample and the sleeve. After the wax liquid condensed, the sample and sleeve were placed on the base for the penetration test. As the grouting veins of different characters were distributed roughly in layers in the filling after grouting, the permeability coefficient of the filling was also expected to show obvious stratification characteristics. When Darcy’s law was used to calculate the permeability coefficient of the injected soil within the grouting range, the permeability coefficient in the horizontal direction and vertical direction was calculated separately. The calculation model is shown in According to the principle of seepage mechanics, the equivalent permeability coefficient of a layered foundation along the direction of parallel planes The equivalent permeability coefficients in the horizontal and vertical directions of the injected soil were calculated according to Equations (5) and (6), respectively. The results showed that A model experiment system for simulating split grouting in filling soil was developed. The equipment could also meet the splitting grouting process of other soils and can be easily disassembled to support the observation and sampling analysis of the excavation of the grouting reinforcement body.In the experiment, three types of grouting veins were formed by the split grouting of filling soil, namely, trunk grouting veins, branch grouting veins, and permeable filling grouting veins. The trunk grouting veins were centered on the grouting holes and distributed in a roughly horizontal plate shape. The intersecting branch grouting veins extended between the trunk grouting veins, and the penetration filling phenomenon occurred in the area away from the grouting hole and trunk grouting vein. The thickness of grouting veins near the grouting hole was larger and gradually decreased as it expanded further.The filling soil was strengthened by the three-stage grouting vein network of trunk vein-branch, vein-permeation filling veins, and the compaction between soils, in which the trunk grouting veins contribute significantly towards strength improvement.The results of the uniaxial compression test, dynamic preliminary test, and indoor geotechnical test showed that the equivalent compressive strength of filling increased by 186%; equivalent cohesion and internal friction angle increased by 45.3% and 44.9%, respectively; and equivalent permeability coefficient decreased by 47 times. The bearing capacity of the foundation was increased by 2–3 times.The filling medium in this study was filling soil below the construction site. Owing to the split grouting in different types of media, the characteristics of the veins, reinforcement effect, and reinforcement mechanism were quite different. Thus, the conclusions obtained in this study could provide a solid reference for the design and theoretical research of grouting reinforcement in the filled soil layer and the detection of grouting effect. The applicability of other types of soil is still uncertain, and relevant research on other types of soil will be carried out in the future.Grouting technology is a changing and complex process, and model tests are an effective means to study the grouting reinforcement law and mechanism. This study introduced in detail the experimental process of simulated filling splitting grouting in the laboratory, and the grouting effect detection and evaluation methods were also provided. Tests of the soil filling performance after grouting were conducted. The following conclusions were drawn:


This study aimed to identify factors associated with health-related quality of life (HRQoL) and the burden on the relatives of older people with multi-morbidity.A secondary analysis of baseline data from 296 dyads, including older patients with multimorbidity and their relatives, which were previously collected in a randomized study.The analysis was conducted to select correlated independent variables to enter a final linear regression analysis of two models with different endpoints: the relatives’ HRQoL (EQ5D index) and burden .Sixteen variables correlated with the relatives’ HRQoL, and 15 with the relatives’ burden. Both the HRQoL and burden correlated with both patient and relative variables. A high HRQoL was associated with relatives’ working/studying. A high burden was associated with caring for an older person with changed behaviour. A low burden was associated with the relatives’ high scores on positive values of caring, quality of support and HRQoL.Older persons and their relatives should be considered as a unit in the development of support of older people in order to increase the health and quality of life of both groups. To support and protect relatives from a high burden, potential measures could include improving the relative’s HRQoL and strengthening their ability to find positive values in care and strengthening reliable and good support from others. The relatives’ HRQoL explained the variation in the burden. However, the burden did not explain the variation in the HRQoL, which suggests that the relatives’ HRQoL is not so readily affected by their burden, whereas the relatives’ HRQoL can influence their burden. The variables used in the regression analyses where chosen to reflect important aspects of the relatives’ and older persons’ situations. The final models explained 38% of the variation in the relatives’ burden but only 10% of the variation in their HRQoL. This could be important to consider when choosing outcome assessments in future studies. Relatives play an important role in the caring of older people. A consequence of the increase in the proportion of older people in the global population –3 is thaThe question of how to properly assess the situation of the informal carer and the person being cared for concerns not only the design but also the choice of outcome variables that can reveal vital information about the dyadic situation. Burden is a frequently used outcome variable in studies on the relatives of older people. Although burden is an important aspect of caring, it only assesses the situation of relatives and we do not know how it refers to an older person’s situation. However, generic assessments of HRQoL, which are also frequently used, allow comparisons between different groups and interventions despite their different characteristics, and can also be used in cost-effective analyses. Thus, HRQoL has also been suggested as an outcome measure for informal carers in order to aggregate the effect on the HRQoL of both patients and relatives. However, these types of HRQoL assessments are constructed for evaluating interventions for patients. Thus, more research is required on generic HRQoL assessments when used on relatives . We therOur aim was to identify factors associated with HRQoL and with the burden of relatives of older people with multi-morbidity.This study is based on a secondary analysis of existing dyadic baseline data on older patients with multimorbidity and their relatives, previously collected in a randomized controlled study designed to evaluate an ambulatory geriatric unit. Two statistical regression models were developed to examine the explanatory factors for relatives’ perceived A) HRQoL and B) burden.Data were collected in a municipality in South-Eastern Sweden with a combined rural and urban population of approximately 130,000. Most health care was provided at 10 primary centres and one hospital with a total of around 300 beds, 12 specialist departments and 24-h admittance for surgical and medical emergencies. The municipality provided home health and social care when needed. In Sweden, county councils and municipalities are responsible for providing health and social care, funded mainly by income taxes.Inclusion criteria for older people with multi-morbidity were age ≥ 75 years, living in their regular home in a city in South-Eastern Sweden, having at least three concomitant medical diagnoses and having received inpatient hospital care at least three times in the previous 12 months. Out of a random sample of 844 eligible older people, 325 declined to participate, 79 had moved to an institution, 26 had died and 32 were unavailable. The remaining 382 older persons and 296 of their relatives took part in a baseline assessment. There were no additional inclusion or exclusion criteria for the relatives. Thus, the present analysis includes dyadic data from 296 older people with multi-morbidity and 296 relatives who were their closest caring relatives  or took part in a structured telephone interview (50%). The data collectors were trained care professionals but were not engaged in caring for the older participants. Both the older people and their participating relatives were informed of their right to withdraw from the study and were assured that their confidentiality would be maintained.To ensure coverage of important aspects of the caring situation, we consulted previous research to choose appropriate questions, instruments and scales. All the selected instruments and set of questions have been used in other studies of older people and relatives, in both Sweden and in other countries, and have demonstrated proper validity and reliability. Age, sex, civil status, educational level, occupation.-EQ-5D index (Dependent variable in regression model A): Self-reported health status in five domains  and transformed into an index based on the public’s valuation of quality of life related to different health states  .-Negative impact scale in COPE index (Dependent variable in regression model B): A summary of seven questions on: emotional well-being, physical health, overly demanding caring, difficulties in relationships with family, with friends, feeling trapped, financial difficulties  .-Hours of care per week provided by the relative of the older person.-Positive value in caring: Positive value scale (4 item) in COPE index: questions on coping with caring, finding caring worthwhile, experiencing a good relationship with the person, cared for, and being appreciated for providing care  .-Attachment security profile: Experiences in close relationships (ECR-16) contains two subscales: Anxiety scale, a measure of fear of rejection and abandonment (8 item) and Avoidance scale, a measure of discomfort with closeness and dependence on close others (8 item),  .-Sense of security in care – Relatives’ evaluation (SEC-R) contains threes subscales: Care interaction scale (7 item), Mastery scale (5 item), Patient situation scale (5 item)  .-Quality of support scale (4 item) in COPE index: questions on support received from friends and neighbours, from family, and from health and social services, and perceived overall support  .-Relatives’ perceptions of weather the older person has changed behaviour that affects the interaction with the relatives and make them sad or upset: a single question from the EUROFAMCARE Comprehensive Assessment Tool  , based o-Relatives’ expectation of the older person’s future health development over the next year: a single question from the Patient Perspective on Care and Rehabilitation Process instrument (POCR)  .Geriatric Depression Scale 15-item (GDS)  .-Sense of security in care – Patient’ evaluation (SEC-P) contains threes subscales: Care interaction scale (8 item); Identity scale (4 item), Mastery scale (3 item),  .-Quality of support scale (4 item) in COPE index: questions on support received from friends and neighbours, from family, and from health and social services, and perceived overall support  .We conducted uni-, bi- and multivariate analyses, including a commonality analysis, to select unique impacts of correlated independent variables to enter in a final linear regression analysis of two models. The EQ5D index was the dependent variable in model A (HRQoL) and the negative impact scale of the COPE index was the dependent variable in model B (burden). We used a Pearson’s correlation in the parametric bivariate analysis for the continuous variables with normal distribution and a non-parametric Spearman’s Rho correlation analysis for the categorical data. Independent variables were selected for use in an initial forward stepwise regression Table . VariablAges ranged from 31 to 91 years in the relatives and from 75 to 96 years in the older people. Table p < 0.05) between the two concepts under investigation and other variables. The HRQoL correlated with 16 out of 19 variables and burden with 15 out of 19 variables  by 0.139 on the scale. This variable had a direct influence of 28% on the variance of HRQoL and the whole model explained 10% of the variance in HRQoL when adjusted for multiple variables , positive value in caring (31%), quality of support (17%) and relatives’ HRQoL (11%). When adjusted for multiple variables, the whole model explained 38% of the variance in the burden  and B (burden). Most of the examined variables have significant bivariate associations with HRQoL (16 out of 19) and burden (15 out of 19), and some of them demonstrate the dyadic aspect of caring, such as the older people’s sense of security, perceived quality of support, and mental health. Of the four selected variables in model A, only one – working/studying – explained the variation in relatives’ HRQoL, whereas, all four of the four selected variables in model B explained variations in the relatives’ burden: relatives’ perceptions of changed behaviour in the older person, positive value in caring, quality of support and the relatives’ HRQoL.The results indicate that the relatives’ involvement in work or study is associated with a higher HRQoL. Other researchers have found that relatives who can balance work and family life with a caring situation also report higher levels of life satisfaction and well-being . Having The four explanatory factors of burden demonstrate that the relatives’ caring situation is embedded in their total life situation, which also embraces the older persons’ situation. The relatives’ HRQoL is one of the explanatory factors of burden and it shows an association pattern of higher burden – lower HRQoL, and vice versa. This is a pattern that has been described in other studies on relatives of older people , 5, 30. In our results, caring for an older person with changed behaviour is related to higher burden. This result is in line with other studies on the relatives of persons with cognitive impairment, for example, from dementia or stroke , 32–34. When considering ways of improving a relative’s situation, there are important findings to consider, such as the relationship between a lower burden and higher scores on relatives’ positive value in caring and on quality of support. Strengthening family carers’ perceptions of positive values as a coping strategy to decrease their burden and strain has been suggested in other studies , 19, 36.There are some circumstances that may have implications for the interpretations of the results. This study drew on a randomized sample of older people. In order to obtain paired data, only those who were dyads, i.e. older persons who had a participating relative, could be included. However, the relatives in our sample were demographically similar to those in other Swedish studies of the relatives of older people  and, likThe results indicate that older persons and relatives should be considered as a unit in the development of support of older people in order to increase health and quality of life for both, as well as in evaluations. In particular, relatives of older people with multi-morbidity and a deteriorating mental state (depression and changed behaviour) and relatives with a lower HRQoL are at risk of a high burden. In order to support and protect relatives from a high burden, potential measures could be improving relatives’ HRQoL and strengthening their ability to find positive values in care, strengthening reliable and good support from others, as well as strengthening support for the older person. The results call for further investigation of the interplay between the situation of elderly persons and their caring relatives, through dyadic studies.The regression models explained more of the variation in the burden (38%) than in the HRQoL (10%). Consequently, there are aspects other than the variables that were selected in the present analysis that influence a relatives’ situation, particularly their HRQoL. Furthermore, the relatives’ HRQoL explained the variation in the burden, although the burden did not explain the variation in the HRQoL. These findings suggest that the relatives’ HRQoL is not so easily affected by their burden, whereas the relatives’ HRQoL can influence their perceived burden. Our study also highlights the risk that assessments of HRQoL (EQ5D index) can underestimate the effect of the caring situation, particularly on younger carers (who are working), because young people generally have better health that can mask the effects more readily seen in older carers. This highlights the need for HRQoL instruments that also capture social interaction as this has shown to be an important aspect of being a relative caring for a family member, as well as being an older person in need of support from others. These results should be considered when deciding on interventions and choosing outcome assessments in future studies on the relatives’ of older people with multi-morbidity.