Evaluate test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants, and sensitivity to change over 6 months, of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) biomarkers in knee OA.Ktrans and IAUC60. Median DCE-MRI biomarker values were extracted for each participant at each study visit. Synovial segmentation was performed using both manual and semiautomatic methods with calculation of an additional biomarker, the volume of enhancing pannus (VEP). Test-retest repeatability was assessed using intraclass correlation coefficients (ICC). Smallest detectable differences (SDDs) were calculated from test-retest data. Discrimination between OA and HV was assessed via calculation of between-group standardised mean differences (SMD). Responsiveness was assessed via the number of OA participants with changes greater than the SDD at 6 months.Fourteen individuals aged 40–60 with mild-moderate knee OA and 6 age-matched healthy volunteers (HV) underwent DCE-MRI at 3 T at baseline, 1 month and 6 months. Voxelwise pharmacokinetic modelling of dynamic data was used to calculate DCE-MRI biomarkers including Ktrans demonstrated the best test-retest repeatability , discrimination between OA and HV (SMDs 0.94/0.54/0.50) and responsiveness (5/1/1 out of 12 OA participants with 6-month change > SDD) when compared to IAUC60 and VEP. Biomarkers derived from semiautomatic segmentation outperformed those derived from manual segmentation across all domains.Ktrans demonstrated the best repeatability, discrimination and sensitivity to change suggesting that it is the optimal DCE-MRI biomarker for use in experimental medicine studies.• Dynamic contrast-enhanced MRI (DCE-MRI) provides quantitative measures of synovitis in knee osteoarthritis which may permit early assessment of efficacy in experimental medicine studies.• This prospective observational study compared DCE-MRI biomarkers across domains relevant to experimental medicine: test-retest repeatability, discriminative validity and sensitivity to change.The DCE-MRI biomarker Ktransdemonstrated the best performance across all three domains, suggesting that it is the optimal biomarker for use in future interventional studies.• The online version contains supplementary material available at 10.1007/s00330-021-07698-z. Inflammation of the synovial membrane (synovitis) is common in OA, with MRI-detected synovitis occurring in up to 90% of OA knees , 2. It cDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) aims to characterise the uptake and washout of gadolinium-based contrast agents (GBCA) in tissues of interest, providing biomarkers of tissue perfusion, capillary permeability and blood and interstitial volume. These parameters are known to change in the synovium in OA . DCE-MRIDCE-MRI biomarkers are of particular interest in early-phase experimental medicine studies which aim to establish early proof-of-concept evidence of efficacy of novel treatments, streamline the treatment development process and reduce late-stage failure rates. They could improve outcome assessment in studies of synovitis-targeted therapies by quantifying response to treatment and are likely to be more robust than relying on qualitative or semiquantitative assessment. There may also be a role in selecting which patients are suitable for entry into studies of synovitis-targeted treatments.However, to increase confidence in the utility of DCE-MRI biomarkers in these settings, technical and clinical validation is essential . This inTherefore, the purpose of this study was to evaluate the test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants and sensitivity to change over 6 months, of DCE-MRI biomarkers in knee OA.The study was approved by the local research ethics committee, and written informed consent was given by all participants. This was a single-centre, prospective experimental feasibility study where DCE-MRI was the intervention.2, (iii) clinical diagnosis of knee OA per the American College of Rheumatology criteria and (iv) mild-moderate radiographic OA defined as Kellgren-Lawrence grade 2 or 3 on a postero-anterior fixed flexion knee radiograph taken using a positioning device  with medial compartment predominant disease ) on a 3 T platform  using an 8-channel transmit/receive knee coil (InVivo). Imaging was performed at baseline and 6-month follow-up. A subset of participants  was asked to return for imaging at 1-month post baseline for assessment of test-retest repeatability. Participants were supine and their knee was positioned in the coil with padding and foot support to minimise subject motion.Participants underwent MRI of a single knee , the volume transfer constant for contrast agent between blood plasma and extravascular extracellular space; vp, fractional volume of blood plasma; ve, the fractional volume of extravascular extracellular space; and IAUC60 (mM.s), the initial area under the contrast agent concentration time curve 60-s post contrast agent arrival in the tissue.Voxelwise pharmacokinetic modelling of DCE-MRI data was performed on registered images  using thmol-1.s-1. Native njection . The bioTwo alternative methods of region of interest (ROI) definition were evaluated involving manual and semiautomatic approaches. Manual segmentation of the synovium was performed on the post-contrast 3D fat-suppressed spoiled gradient echo (FS SPGR) sequence by a musculoskeletal radiologist with 6 years’ experience (J.M.), with definition of seven synovial ROIs: suprapatellar, Hoffa’s fat pad, medial and lateral perimeniscal, intercondylar notch, medial and lateral posterior femoral condyles Fig. . AnatomiFor semiautomatic segmentation, enhancing voxels were defined by subtracting the pre-contrast 3D FS SPGR sequence from the matching post-contrast sequence using a shuffle transform . For a gSegmentation was repeated by the original observer with an interval of > 6 months between analyses and an independent second observer  for all baseline visits to enable assessment of intra and inter-observer reproducibility of DCE-MRI biomarkers.Semiquantitative grading of synovitis was performed using the MRI Osteoarthritis Knee Score (MOAKS) by a musculoskeletal radiologist with 6 years’ experience (J.M.) . MOAKS gTest-retest repeatability was assessed using baseline and 1-month whole joint data with calculation of the intraclass correlation coefficient (ICC). Intra- and inter-observer reproducibility was assessed using the root-mean-square coefficient of variation (RMSCV) and the concordance correlation coefficient (CCC). We also calculated the smallest detectable difference (SDD), representing the magnitude of change that would give 95% confidence of a change being genuine rather than due to measurement noise, assuming identical measurement conditions. This is defined as 2.77 (ent (RC) .Discrimination between OA and HV participants was assessed using baseline data. Descriptive statistics were calculated for each group, and the standardised mean difference (SMD) was estimated for each DCE-MRI biomarker by dividing the difference in mean between the two groups by the pooled standard deviation.Six-month changes in each biomarker were assessed using descriptive statistics. The number of participants with changes in each biomarker greater than the SDD was calculated.No formal sample size calculation was performed for this feasibility study. All statistical analyses were performed in R version 3.6.1 .n = 2) and participant withdrawal (n = 1).Fourteen OA and six HV participants were recruited. Baseline characteristics are provided in Table Ktrans, IAUC60 and VEP were not significantly correlated with the value of the biomarker, so wSD and absolute SDD values are presented. Variabilities of vp and ve were significantly correlated with biomarker value, so wCV and percentage SDD values are presented. Kendall’s τ correlation coefficients for baseline and 1-month biomarker values are provided in Supplementary Table vp and ve and the presence of physiologically implausible values (e.g. ve greater than 1), these biomarkers were not used for further analyses. Repeatability of biomarker measurements from semiautomatic segmentation (VEP mask) was better than those derived from manual segmentation for Ktrans and IAUC60. Measurements derived from semiautomatic segmentation were therefore preferred for all subsequent analyses.Repeatability metrics values for each parameter are provided in Table Ktrans derived from semiautomatic segmentation . Ktrans and IAUC60 derived from semiautomatic segmentation demonstrated improved reproducibility compared to manual segmentation. All intra- and inter-observer reproducibility data are provided in Table Intra and inter-observer reproducibility was best for Ktrans and IAUC60 than other HV participants  across all ROIs. On further investigation, it was determined that this HV had taken part in karate practice the night before each of the three study visits and also had an undisclosed history of gout (never having affected the knee). Possible explanations considered for this value were that this represented part of the normal range of healthy values, or that the presence of gout or recent intense physical activity had confounded measurement. This participant’s data were not excluded because the participant met the pre-specified inclusion criteria, but, where appropriate, additional exploratory analyses excluding this participant’s data are reported.Baseline between-group differences for the whole joint are illustrated in Fig. Ktrans, IAUC60 and VEP respectively. Excluding the outlier HV case, SMDs were 1.34 for Ktrans and 1.12 for IAUC60. Visual analysis of plots for individual synovial ROIs  is provided in Fig. Ktrans exceeding the SDD and participants with changes in MOAKS synovitis score.A comparison of 6-month changes in Ktrans is the optimum of the evaluated DCE-MRI biomarkers for use in experimental medicine studies, with the best test-retest repeatability, best discrimination between OA and HV participants and greatest sensitivity to change as judged by the number of participants showing detectable changes over a 6-month period.This study suggests that Several previous studies have used DCE-MRI to evaluate synovitis in knee OA, including describing cross-sectional associations with symptoms and longitudinal association with response to treatment , 27. NovKtrans and IAUC60) performed better than VEP, which reflects the extent of synovitis, across all assessment domains. This finding agrees with a previous knee OA study which suggested improved sensitivity to change of ‘intensive’ vs ‘extensive’ biomarkers of synovitis [Biomarkers that assess the intensity of synovitis  is more likely to undergo biological variation during the test-retest interval. Intra-observer reproducibility was similar for the two methods, but with superior inter-observer reproducibility for semiautomatic segmentation.The design of our study assumes a natural history of OA with negligible change over one month (repeatability), but with the possibility of disease progression over 6 months. This is a short interval relative to the conventional concept of OA as a slowly progressive condition developing and progressing over years. However, experimental medicine studies are typically of short duration and so to be useful in this setting, an imaging biomarker has to be sensitive enough to detect changes over short intervals. We therefore chose a 6-month interval as a reasonable trade-off between the requirements of experimental medicine studies against the expected relatively slow change in disease.-month changes greater than the SDD (particularly for Ktrans) suggesting that sensitivity to change is adequate for experimental medicine studies performed over this interval. A possible counter-argument is that this sensitivity to change indicates that the background variability is too high to expect to be able to detect additive effects of therapy. Moreover, more participants demonstrated significant decreases rather than significant increases in Ktrans, likely related to regression to the mean. However, it should be noted that the majority of participants did not demonstrate significant reductions in DCE-MRI biomarkers and typically had higher values than age-matched controls suggesting that there is potential for improvement in these biomarkers with treatment. Moreover, the group mean 6-month changes in DCE-MRI biomarkers for OA participants was close to 0, after adjustment for baseline values (data not shown). This suggests that the effects of treatment may also be detectable at a group as well as at an individual level.There was a wide range of 6-month changes in DCE-MRI biomarkers in both positive and negative directions in OA participants. This may reflect the fluctuating nature of synovitis in OA, which is well recognised clinically . SeveralKtrans in this study (~ 0.015 min-1), a group-averaged reduction of 50% of the difference between OA and HV mean values (~ 0.01 min-1) could be detected with 80% power and a type 1 error rate of 5% (one-sided) with a sample size of 24 participants per group, assuming an active treatment vs placebo repeated-measures study design. This is a clinically feasible reduction relative to a previous study of change in Ktrans following intra-articular steroid administration [Our results suggest that DCE-MRI biomarkers are likely to be of use in experimental medicine studies featuring putative anti-inflammatory and immunomodulatory disease-modifying treatments. The data presented can be used to inform sample size calculation for further interventional studies. For example, using the observed standard deviation of 6-month change in stration .Limitations of this study include the long test-retest interval (1 month) relative to the time over which clinical fluctuations in synovitis occur in OA. Therefore, the measured variability is likely to include contributions from both methodological and biological sources, and true methodological variability is likely to be lower. A second limitation is that the results presented are from a single centre and obtained with meticulous quality control; therefore, extrapolation to multi-centre studies should be done with caution. However, previous work suggests that DCE-MRI biomarkers can be used in such a setting with appropriate training, calibration and quality control . In partKtrans demonstrates the best performance across these domains and is therefore the most likely to be useful in experimental medicine studies and other future therapeutic trials.In conclusion, this study has assessed the test-retest repeatability, discrimination between OA and ‘normal’ tissue characteristics and sensitivity to change of DCE-MRI biomarkers. ESM 1(DOCX 2 mb)


Objective: Articular cartilage injury is common and difficult to treat clinically because of the characteristics of the cartilage. Bone marrow-derived mesenchymal stem cell (BMSC)-mediated cartilage regeneration is a promising therapy for treating articular cartilage injury. BMSC differentiation is controlled by numerous molecules and signaling pathways in the microenvironment at both the transcriptional and post-transcriptional levels. However, the possible function of super enhancer long non-coding RNAs (SE-lncRNAs) in the chondrogenic differentiation of BMSCs is still unclear. Our intention was to explore the expression profile of SE-lncRNAs and potential target genes regulated by SE-lncRNAs during chondrogenic differentiation in BMSCs.Materials and Methods: In this study, we conducted a human Super-Enhancer LncRNA Microarray to investigate the differential expression profile of SE-lncRNAs and mRNAs during chondrogenic differentiation of BMSCs. Subsequent bioinformatic analysis was performed to clarify the important signaling pathways, SE-lncRNAs, and mRNAs associated with SE-lncRNAs regulating the chondrogenic differentiation of BMSCs.Results: A total of 77 SE-lncRNAs were identified, of which 47 were upregulated and 30 were downregulated during chondrogenic differentiation. A total of 308 mRNAs were identified, of which 245 were upregulated and 63 were downregulated. Some pathways, such as focal adhesion, extracellular matrix (ECM)–receptor interaction, transforming growth factor-β (TGF-β) signaling pathway, and PI3K–Akt signaling pathway, were identified as the key pathways that may be implicated in the chondrogenic differentiation of BMSCs. Moreover, five potentially core regulatory mRNAs  and 37 SE-lncRNAs in chondrogenic differentiation were identified by bioinformatic analysis.Conclusion: We assessed the differential expression levels of SE-lncRNAs and mRNAs, along with the chondrogenic differentiation of BMSCs. By analyzing the interactions and co-expression, we identified the core SE-lncRNAs and mRNAs acting as regulators of the chondrogenic differentiation potential of BMSCs. Our study also provided novel insights into the mechanism of BMSC chondrogenic and cartilage regeneration. Articular cartilage injury is a common and serious condition accompanied by degeneration or loss of cartilage, which can cause swelling, pain, and even disability . Many reAlong with technological developments, super enhancers (SEs), which are associated with pluripotency genes, were described for the first time in mouse embryonic stem cells in 2013 . SEs areIt has been found by many studies that SE-lncRNAs participate in the regulation of varieties of biological processes and many diseases by regulating target genes, including muscle, cardiac and red blood cell development, or cancer and myocardial infarction. The expression of Hand2, an important regulator of differentiation from fibroblasts to cardiomyocytes, is controlled by upstream SE-lncRNA Uph . SE-lncRIn this study, we aimed to explore the expression profile of SE-lncRNAs and potential target genes regulated by SE-lncRNAs during chondrogenic differentiation of BMSCs. Thus, the expression profiles of differentially expressed SE-lncRNAs and mRNAs were identified between uninduced and chondrogenic differentiation of human BMSCs for 7 days by performing microarray analysis. We further conducted bioinformatic analysis to analyze SE-lncRNAs–mRNAs interactions and identified potential core regulatory factors.n = 3) and a group of chondrogenic induction BMSCs (n = 3). Each pair of the uninduced and chondrogenic induction BMSCs were from the same donors. The uninduced group was cultured using MSCM. Chondrogenic induction BMSCs were cultured with a StemPro chondrogenesis differentiation kit  for 7 days. The induction medium was renewed every 3 days.Bone marrow-derived mesenchymal stem cells (three donors) were purchased from ScienCell Research Laboratories Inc. . The culture medium was mesenchymal stem cell medium (MSCM)  supplemented with 5% fetal bovine serum and 1% penicillin/streptomycin. The culture conditions were as described . At threTotal RNA from three samples from the two groups was extracted using the TRIzol reagent (Invitrogen). NanoDrop ND-1000 was used to determine RNA quantity and quality. Standard denaturing agarose gel electrophoresis was used to assess RNA integrity. Arraystar Human Super-Enhancer LncRNA Microarray including 7,753 lncRNAs and 7,040 genes was selected to acquire a comprehensive global profile of human lncRNAs and mRNAs. Recognized public transcriptome databases, such as RefSeq, UCSC knowledge genes, Ensemble, and important publications were used to build the lncRNA data. SE data were arranged from the database of dbSUPER. Samples were labeled and arrays were hybridized according to the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technology). The Agilent DNA Microarray Scanner (part number G2505C) was used to scan after the array was washed and fixed. The acquired images were analyzed using the Agilent Feature Extraction software (version 11.0.1.1). The GeneSpring GX v12.1 software package (Agilent Technologies) was used for quantile normalization of raw data. Next, we selected eligible SE-lncRNAs and mRNAs for further analysis.–ΔΔCT method. The PCR signals were normalized by GAPDH.The levels of genes that were differentially expressed in the microarray analysis were validated by real-time polymerase chain reaction (RT-PCR). Total RNA from the two groups was extracted as described above. RNA (1 μg) was combined with reverse transcriptase to synthesize cDNA according to the protocol of the manufacturer. QuantiTect SYBR Green PCR kits  and an iCycler iQ multicolor real-time PCR detection system  were used to perform real-time RT-PCR. The primers used are listed in p ≤ 0.05 were considered as differentially expressed SE-lncRNAs and mRNAs between uninduced and chondrogenic induction BMSCs. We performed pathway and gene ontology (GO) analyses to determine the functions of important mRNAs in pathways or GO terms involved in chondrogenic differentiation. In-house scripts were used for hierarchical clustering and combined analyses. We built the pathway network (Path-Net) of the significant pathways associated with differentially expressed genes, which can reflect the association among these pathways according to the KEGG database. Based on the differentially expressed genes, the gene signal transduction network  was constructed to determine the relationships between genes. To build a coding-non-coding co-expression (CNC) network, we calculated the correlation coefficient based on the normalized signal value between each pair of mRNAs and SE-lncRNAs.Fold change ≥ 2.0 and t-test using SPSS17 statistical software . Statistical significance was set at p ≤ 0.05.Data were analyzed by Student’s To verify the chondrogenic differentiation of BMSCs, real-time RT-PCR was used to measure the expression levels of the chondrogenic differentiation markers . As shown in t-test was used to present the differentially expressed SE-lncRNAs and mRNAs. Based on the p-value threshold false discovery rate (FDR), we filtered out SE-lncRNAs and mRNAs that changed at least two-fold during chondrogenic differentiation of BMSCs for further analysis. In total, we found 77 differentially expressed SE-lncRNAs  between 7-day chondrogenic induction BMSCs and uninduced BMSCs of which 47 were upregulated and 30 were downregulated  when comparing 7-day chondrogenic induction BMSCs with uninduced BMSCs. There were 245 upregulated genes, including EGR1, RUNX1, and ADAM12, and 63 downregulated genes, including SFRP1, IGFBP6, and ADRB2  were selected, and real-time RT-PCR was used to measure their expression levels. Compared to the uninduced BMSCs, the induced BMSCs displayed increased expression levels of PMEPA1, CDK6, ENC1, and TES and decreased expression levels of ADIRF . The expp < 0.05, FDR < 0.05) were identified between 7-day chondrogenic induction BMSCs and uninduced BMSCs, of which 178 were upregulated and 39 were downregulated .To clarify the critical regulators governing chondrogenic differentiation of BMSCs, GO and pathway analyses were conducted. The significantly altered functions of differentially expressed genes during chondrogenic differentiation of BMSCs were identified by GO analysis. In total, 217 differential GO functions , were identified, with 55 upregulated and 4 downregulated pathways  were identified as possible core regulatory genes of BMSCs  can be found below: YJ conducted the experiments, analyzed the data, and wrote the manuscript. CZ and LL participated in data analysis. LG and JG prepared the figures. ZF participated in the study design. GY reviewed and edited the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


High and CD4+Foxp3+ T cells. No beneficial effects for treatment with empagliflozin alone could be shown. While no effect of dulaglutide or its combination with empaglifozin on hepatic steatosis was evident, these data demonstrate distinct anti-inflammatory effects of dulaglutide and their combination with empagliflozin in a non-diabetic background, which could have important implications for further treatment of NASH.Dysregulation of glucose homeostasis plays a major role in the pathogenesis of non-alcoholic steatohepatitis (NASH) as it activates proinflammatory and profibrotic processes. Beneficial effects of antiglycemic treatments such as GLP-1 agonist or SGLT-2 inhibitor on NASH in patients with diabetes have already been investigated. However, their effect on NASH in a non-diabetic setting remains unclear. With this aim, we investigated the effect of long-acting GLP1-agonist dulaglutide and SGLT-2 inhibitor empagliflozin and their combination in a non-diabetic mouse model of NASH. C57BL/6 mice received a high-fat-high-fructose (HFHC) diet with a surplus of cholesterol for 16 weeks. After 12 weeks of diet, mice were treated with either dulaglutide, empagliflozin or their combination. Dulaglutide alone and in combination with empagliflozin led to significant weight loss, improved glucose homeostasis and diminished anti-inflammatory and anti-fibrotic pathways. Combination of dulaglutide and empagliflozin further decreased MoMFLy6C Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide, which affects nearly 25% of the global adult population, and the incidence is even further increasing . NAFLD iThe main risk factors for NASH are central obesity, dyslipidemia, insulin resistance and type 2 diabetes mellitus (T2DM). Therefore, it was recently proposed to change the nomenclature into “metabolic associated fatty liver disease” (MAFLD) .Therapeutic options in patients with NASH are still rare, but urgently needed. Currently, loss of weight and physical activity are the only established therapeutic strategies . As glucAnimal care and all animal experiments were executed according to protocols approved by the animal welfare commission of the Hannover Medical School, local ethics Animal Review Board  and in accordance with the ARRIVE guidelines.We used 6–8-week-old C57BL/6HanJ Ztm mice. Animals were fed a high-fat-high-carbohydrate (HFHC) diet with a surplus of cholesterol  with 45 g/L 55% Fructose/45% Sucrose  in the drinking water for 16 weeks. After 12 weeks of the diet, pharmacological treatment was started with either dulaglutide  , empagliAfter 16 weeks of HFHC diet, an intraperitoneal glucose-tolerance test (IPGTT) was performed. Further details are provided in the g. Supernatant was aliquoted for triglyceride and protein quantification. Colorimetric detection and quantitation of total protein was performed using the Pierce™ BCA Protein Assay Kit . Triglyceride in supernatant was detected via the Cobas® 8000 modular analyzer .Frozen liver was minced into pieces and homogenized in standard diluent  with 20 µg/mL Leupeptin  via a rod-homogenizer for 10–15 s. Homogenates were centrifuged at 4 °C for 10 min at 10,000× Murine liver was fixed in formalin and embedded in paraffin. Paraffin-embedded sections (2 µm) were stained with haematoxylin and eosin (H&E) for assessment of liver histology, with periodic-acid Schiff reaction (PAS) for assessment of glycogen accumulation and with silver for evaluation of fibrosis. Afterwards, they were graded with the NAFLD-activity score (NAS). In short, sections were graded for lobular inflammation, hepatocyte ballooning and steatosis . GradingLivers and spleens were perfused with PBS and dissected from mice. Organs were then minced using a nylon cell strainer  and washed with phosphate-buffered saline supplemented with 2% fetal calf serum. Afterwards, spleens were lysed in red blood cell lysis buffer . Intrahepatic leucocytes and monocytes were isolated by using 40/70%- percoll density gradients . Subsequently, cells were stained with fluorochrome-conjugated antibodies for multicolor fluorescence-activated cell sorting (FACS) analysis. Detailed information about the antibodies used are provided in the For real-time PCR, the TaqMan Gene Expression Assay was used. Please see the Fresh stool was collected from every animal after 16 weeks of HFHC diet. For stool collection, mice were set into a clean plastic cage and fresh stool was collected and immediately put on dry ice. Afterwards, stool was stored at −80 °C until further preparation. DNA preparation and bioinformatic analyses were performed according to the methods described before . Furthert-test with Welsh-correction was applied for comparisons of differences between the means of two groups. Non-parametric Mann–Whitney test was applied for comparing the NAS-Score. The trapezoidal rule was used to determine the area under the curve (AUC). p-values <0.05 were considered as significant. All results are presented as mean with standard error of the mean (SEM). Graphs were created using the GraphPad Prism v5.0 program and Power Point v2010.Statistical analysis was performed with GraphPad Prism v5.0. The unpaired Student 2-tailed p-values were set to ≤0.049 for two group comparisons (t-test) and for multigroup comparisons (F-test) (ANOVA) (p < 0.05 and q < 0.2). *, difference significant with p < 0.05. **, difference significant with p < 0.01 ***, difference highly significant with p < 0.001. A p-value > 0.05 was considered to be not significant (ns).For analysis of the RT-PCR, the Fluidigm Real-Time PCR Analysis Software V.3.0.2 was used. Data were normalized by the mean values of the housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (Gapdh) and actin β (actb) from the genes of interest. Heat map and principal component analysis (PCA) of the –delta Ct values were performed via the using Qlucore Omics Explorer v3.3 . For analysis Weight loss is the most important treatment option for NASH so far and therefore an important aim of potential therapeutical treatments. After 16 weeks of HFHC diet and 4 weeks of treatment a, we anaAlthough there were no differences in the basal fasting glucose levels, dulaglutide accelerated glucose reduction after injection, so that these mice reached basal fasting glucose levels at the end of the test compared to saline vehicle-treated mice a. Also, We further analyzed the treatment effect on transaminases levels as a marker for hepatocyte damage. Here, treatment with dulaglutide alone significantly reduced the aspartate-aminotransferase (AST). Neither the treatment with empagliflozin nor the combined treatment influenced AST levels. No significant changes in the alanine-aminotransferase (ALT) levels were detected B.After 16 weeks of HFHC diet, the histological development of NASH was analyzed by an experienced pathologist. Paraffin-embedded liver sections were stained with haematoxylin and eosin (H&E) for assessment of liver histology, periodic-acid Schiff reaction (PAS) for assessment of glycogen accumulation and silver staining for evaluation of fibrosis . All ani+ regulatory T (Treg) cells compared to single treatment with empagliflozin as well as control mice  towards reduced CD4+IFNgamma+ after combined treatment compared to empagliflozin  is influenced by various stimuli such as fatty acids or signals from the gut–liver axis [high compared to empagliflozin and control group. Conversely, the amount of MoMFLy6Cneg cells were significantly increased after combined treatment (Macrophages are important drivers of chronic inflammation in the liver and contribute to the progression from simple steatosis to steatohepatitis. Polarization of monocyte-derived macrophages (MoMF) into the pro-inflammatory macrophages  and anti-inflammatory monocytes (MoMF Ly6Clow). In NASH, proinflammatory MoMF strongly promote chronic inflammation and therefore play a critical role in pathogenesis of NASH. In line with the decrease of Kupffer cells, we observed a decrease of CCL2-gene expression in the liver as a marker for decreased inflammation. In addition, the expressions of TNF alpha and IL1beta were significantly decreased after dulaglutide treatment. Previously it was shown that GLP-1 agonist liraglutide modulated the Kupffer cell M2-polarization and inhibits inflammasome activation, which might contribute to the anti-inflammatory effect of dulaglutide [In our study, the anti-inflammatory effects are mediated by various pathways. Kupffer cells, the resident macrophages of the liver, play a critical role in the onset of NASH, as their activation results in the release of various inflammatory mediators, such as chemokine (C-C motif) ligand (CCL2) and TNF alpha . CCL-2 maglutide . Additioaglutide .high) and Kupffer cells in a combined treatment group. Although our data did not show any significant effect of empagliflozin on innate immunity, a previous study in a diabetic mouse model showed improvement of inflammation and insulin resistance by reduction of pro-inflammatory macrophages [Importantly, we could show an even stronger attenuation of pro-inflammatory activation of innate and adaptive immune system marked by decreased Treg population as well as decreased pro-inflammatory macrophages (MoMF Ly6Crophages . TherefoFirmicutes phylum as well as decreased of Bacteriodetes seem to be associated with NASH [Firmicutes:Bacteriodetes ratio, which is mostly pronounced in the saline vehicle group of our study, might be associated with NAFLD development. In the current study, Firmicutes are the very dominant phylum and are even more dominant compared to other studies [Bacteriodetes. In particular, lack of Bacteriodetes in the saline group is surprising. As other studies demonstrated microbiome dysbiosis after high-salt diet [Bacteriodetes, but also after combined treatment. Previous studies showed a correlation between weight loss and increase of abundance of Bacteriodetes as well as an association between improvement of metabolic situation and increase of Bacteriodetes after GLP-1 treatment [Akkermansia spp. after dulaglutide treatment might be in correlation to improvement of the metabolic situation as Akkermansia spp., which is a mucin-degrading short fatty acid-producing species, is decreased in obesity and showed negative correlation to markers of gut permeability and inflammation [Previous animal and human studies already suggested that the gut microbiome plays an important role in the pathogenesis of NASH as the flux of microbial endotoxins to the liver further promotes pro-inflammatory and pro-fibrotic processes . Most imith NASH . Therefo studies , with a alt diet , the appreatment . Furtherammation . Howeverammation , which sammation . Howeverammation , althougammation  and mighammation . FurtherAs insulin resistance promotes dysregulation of peripheral lipolysis and de novo lipogenesis, which then leads to accumulation of free fatty acids in the liver , the effA shortcoming of the study might be the moderate histological manifestation of NASH in this mice model. It is well known from other forms of hepatitis, e.g., autoimmune hepatitis, that histological changes follow biochemical improvements, but months later. Therefore, a prolonged duration of diet as well as a prolonged duration of treatment might be required to determine the histological effects.The pathogenesis of NASH is a complex interaction between environmental factors and genetic determinants. On the one hand, this complex interplay could not be completely represented by a single animal model . HoweverBeyond weight loss and improvement of insulin resistance, the positive effects of GLP-1 agonists also seem to be multifactorial-mediated with additional pleiotropic effects, especially on improvement of cardiovascular disease. As our mouse model replicates only moderate features of the metabolic syndrome in a non-diabetic setting, some pleotropic effects of GLP-1 agonist might not be present in our model.Previous meta-analysis of human studies investigating the impact of GLP-1 agonist in NASH showed promising results with improvement of hepatic steatosis, histological resolution of NASH and decrease of transaminases ,39. HowePrevious studies with a lesser amount of diabetic patients ,41 couldWe could not detect any effect of empagliflozin treatment, neither on the metabolic situation nor on the histological outcome of NASH. Instead, empagliflozin significantly increased expression of pro-inflammatory and pro-fibrotic genes. These data are partly unexpected, as previous data from human and animal studies with SGLT-2 inhibitors showed improvement of NASH . To ruleNevertheless, the additive effect was less pronounced in using lower dosing and more pronounced in severe diabetic situations in these studies. Therefore, the lack of treatment effects by empagliflozin might explain the limited effect of combined treatment compared to dulaglutide-mono treatment with only slightly additional effects on the one hand. On the other hand, one study could show that the SGLT-2-inhibitors induced increase of endogenous glucose production could not be suppressed by combination with GLP-1 agonist , which mFurthermore, in the studies mentioned above, no additional effects on lipid level were detected. As dyslipidemia is an important risk factor for development of steatohepatitis, in particular in the absence of diabetes, this might also contribute to the marginal benefit on NASH.Further limitation of the study might be the lack of an equal control group for the combined treatment. However, comparing both control groups for the individual treatments, we could not see any significant differences. Therefore, we might expect a similar outcome after a combined treatment with saline and Natrosol compared to single treatment.In conclusion, our results did demonstrate no beneficial effects of empagliflozin on the development of NASH in a non-diabetic setting. Furthermore, these data suggest that GLP-1 agonists and SGLT-2 inhibitors are less effective for the prevention of hepatic steatosis in a non-diabetic background compared to previous studies. Nevertheless, the study demonstrates important anti-inflammatory effects of dulaglutide and the combination of dulaglutide and empagliflozine by modulating pro-inflammatory immune response and microbiome dysbiosis. As development of hepatic fibrosis is strongly triggered by inflammation, this might have important implications for the treatment of NASH, e.g., in combination with anti-steatotic treatment. Therefore, further studies are needed to investigate the long-term impact of both agents on NASH and hepatic fibrosis in a non-diabetic background.


This case-control study examined the association of sociodemographic factors and blood group type with risk of SARS-CoV-2 infection and severity of COVID-19. These reports motivated widespread interest in examining ABO blood groups as potential COVID-19 risk factors. Subsequent studies from Italy and Spain2 reported that blood group A was associated with an increased risk of severe COVID-19 and blood group O was associated with a reduced risk. In contrast, a large Danish study3 implicated disease susceptibility but not severity. However, observations from Boston, Massachussets,4 and New York, New York,5 did not confirm any specific associations between ABO blood group and disease. The controversy raised by these contrasting reports led to this case-control study.The observed variability in susceptibility to SARS-CoV-2 and severity of the ensuing COVID-19 have raised intense interest in their environmental and genetic risk factors. An early report from ChinaSTROBE) reporting guideline.Our objective in this case-control study was to independently test whether blood type is associated with SARS-CoV-2 susceptibility and COVID-19 severity. The study was approved by the Intermountain Medical Center institutional review board with a waiver of consent because the study represented no more than minimal privacy risk to individuals. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology  vs non-ICU patients. Infectivity was determined by SARS-CoV-2–specific polymerase chain reaction testing of nasal swabs or saliva samples. Analysis of variance assessed associations across ABO groups. Odds ratios (ORs) between ABO groups were assessed by logistic regression adjusted for age, sex, and Rh factor. P = .11), hospitalization , or ICU admission   who had been tested for SARS-CoV-2 infection were included in the study. Further demographic characteristics of the studied population and ABO blood group associations are shown in P = .08) . SimilarP = .08) .1 Europe,3 Boston,4 New York,5 and elsewhere,6 we embarked on a large, prospective case-control study that included more than 11 000 individuals who were newly infected with SARS-CoV-2, and we found no ABO associations with either disease susceptibility or severity. The smaller sample sizes and retrospective, observational nature of many prior studies, in addition to their striking heterogeneity of ABO associations with disease susceptibility and severity, could be due to chance variations, publication bias, differences in genetic background, geography and environment, and viral strains. The ABO gene is highly polymorphic, and ABO blood groups are distributed differently across ancestries and geographies. Differing disease susceptibilities could be due to natural antibodies or prothrombotic effects with nongroup O.6 The Utah population is dominated by Northern European ancestry, with a minority contribution of Hispanic/Latinx and other ethnicities. However, our results are similar among individuals of White race alone.With contrasting reports from China,Given the large and prospective nature of our study and its strongly null results, we believe that important associations of SARS-CoV-2 and COVID-19 with ABO groups are unlikely and will not be useful factors associated with disease susceptibility or severity on either an individual or population level for similar environments and ancestries. Additional studies, closely controlled for genetics, geography, and viral strain, are required before accepting blood group as a determinant of predisposition to or severity of COVID-19.


We explored the associations of actigraphy-derived rest-activity patterns and circadian phase parameters with clinical symptoms and level 1 polysomnography (PSG) results in patients with chronic insomnia to evaluate the clinical implications of actigraphy-derived parameters for PSG interpretation. Seventy-five participants underwent actigraphy assessments and level 1 PSG. Exploratory correlation analyses between parameters derived from actigraphy, PSG, and clinical assessments were performed. First, participants were classified into two groups based on rest-activity pattern variables; group differences were investigated following covariate adjustment. Participants with poorer rest-activity patterns on actigraphy (low inter-day stability and high intra-daily variability) exhibited higher insomnia severity index scores than participants with better rest-activity patterns. No between-group differences in PSG parameters were observed. Second, participants were classified into two groups based on circadian phase variables. Late-phase participants (least active 5-h and most active 10-h onset times) exhibited higher insomnia severity scores, longer sleep and rapid eye movement latency, and lower apnea–hypopnea index than early-phase participants. These associations remained significant even after adjusting for potential covariates. Some actigraphy-derived rest-activity patterns and circadian phase parameters were significantly associated with clinical symptoms and PSG results, suggesting their possible adjunctive role in deriving plans for PSG lights-off time and assessing the possible insomnia pathophysiology. Growing evidence suggests that homeostatic sleep drive (Process S) and the circadian pacemaker (Process C) reciprocally interact to regulate the sleep–wake cycle2. For example, animals lacking core clock machinery, such as Bmal1 or Clock genes, exhibit impairments in the circadian pacemaker and changes in sleep and quality, such as altered EEG delta power5. Alterations in rest-activity patterns and circadian phase have also been reported in patients with bipolar disorder, Parkinson’s disease, and Alzheimer's disease10. Indeed, circadian rhythm disruptions and sleep difficulties are frequently observed in patients with these conditions, suggesting pathophysiological roles for sleep and circadian alterations in disease initiation and progression11. We thus consider that although circadian rhythm and sleep are two different aspects of sleep–wake cycle biology, these two factors are not independent and could be correlated with each other. Nevertheless, rest-activity pattern changes, circadian phase alterations, and their possible associations with subjective and objective sleep characteristics in patients with insomnia remain poorly characterized. In 2014, Natale et al. assessed the rest-activity patterns in 151 patients with insomnia and 342 normal sleepers12. In this study, there were no significant differences in the rest-activity pattern parameters’ inter-day stability (IS) and intra-daily variability (IV) between patients with insomnia and normal sleepers. However, the absence of these differences does not eliminate the possibility of associations between rest-activity patterns and sleep characteristics in patients with insomnia. For example, the subset of patients with insomnia could have combined rest-activity pattern disruption (low IS and high IV), and this combined difficulty can exacerbate patients’ subjective suffering from insomnia. In a similar way, the circadian phase of patients with insomnia could also have a possible impact on sleep disturbance in each individual.The circadian clock is a system that enables organisms to adapt to external changes in the environment over a 24-h period and is a major determinant of rest-activity patterns, sleepiness, and alertness in humans13. PSG provides an accurate measure of wake and sleep times, as well as respiratory function, muscle activity, heart physiology, and sleep stages. However, level 1 PSG is typically performed for one night in a specialized setting, regardless of patients’ lifestyle, such as sleep environment, which may contribute to poor ecological validity14. Sleep diaries and/or questionnaires are commonly used to identify patients’ lifestyle and circadian phase16. Actigraphy has emerged as a major assessment tool in sleep research and sleep medicine over the last two decades18. In this context, patients’ rest-activity patterns and circadian phase derived from several days of actigraphy assessment may be helpful for performing and/or interpreting level 1 PSG in clinical practice. Several studies have compared PSG-derived sleep parameters with actigraphy-derived parameters such as total sleep time and wakefulness after sleep onset21. However, to the best of our knowledge, no study to date has evaluated the clinical significance of actigraphy-derived rest-activity patterns and circadian phase parameters for the preparation and interpretation of level 1 PSG.Polysomnography (PSG) is considered the gold standard for objectively evaluating sleep quality and quantityIn this study, we investigated the possible associations of actigraphy-derived rest-activity patterns and circadian phase parameters with clinical symptoms and PSG results in 75 patients with insomnia in order to assess the possible associations of the rest-activity pattern or circadian phase deviation with clinical symptoms or PSG results. In addition, we also tried to assess the clinical implications of actigraphy-derived parameters for the preparation and interpretation of PSG in patients with insomnia.22. PSG results indicated that total sleep time and wake after sleep onset were approximately 361.9 min and 14.4%, respectively.Demographic characteristics, rest-activity patterns, and circadian phase according to actigraphy, PSG results, and clinical symptom scores of the study participants are listed in Table To explore the associations among rest-activity patterns, circadian phase, PSG parameters, and clinical symptom scores, Pearson or Spearman correlation analyses were performed based on the distribution of variables Table . As expeHierarchical clustering analyses were performed for the actigraphy data-driven group classification of the participants for the following reasons. First, rest-activity patterns and circadian phase alterations may only occur in a subset of patients with chronic insomnia in sleep clinics. Second, the cut-off values for actigraphy-derived rest-activity patterns or circadian phase parameters have not been suggested to date. Third, using a data-driven clustering approach, two rest-activity pattern variables, IS and IV, or two circadian phase variables, L5 and M10, can be simultaneously considered.First, the study participants were classified into two groups based on rest-activity pattern variables, IS and IV Fig. A. Group To investigate between-group differences and their clinical implications according to rest-activity pattern variables (IS and IV), PSG parameters and clinical symptom scores were compared between groups. Participants with poorer rest-activity patterns  had significantly higher ISI scores in the clinical assessment , late-phase participants (Group L) had adjusted odds ratios (ORs) of 5.8  for long sleep latency, 4.0  for long REM latency, and 0.26  for abnormal AHI.To investigate between-group differences and their clinical implications according to circadian phase variables (L5 and M10 onset times), PSG parameters and clinical symptom scores were compared between groups. Late-phase participants (Group L) had significantly higher ISI scores in the clinical assessment  with insomnia severity and level 1 PSG parameters such as AHI or REM latency. The 75 subjects were further categorized into two groups based on rest-activity patterns or circadian phase using data-driven hierarchical clustering analysis. The analysis revealed that participants with poorer rest-activity patterns (low IS and high IV) exhibited higher insomnia severity scores compared to participants with better rest-activity patterns (high IS and low IV). In addition, late-phase participants (late L5 and M10 onset times) exhibited higher insomnia severity scores, longer sleep latency, longer REM latency, and lower AHI compared to early-phase participants (early L5 and M10 onset times). These associations remained significant even after adjusting for potential covariates including age, sex, BMI, and lights-off time.9. Changes in rest-activity patterns and circadian rhythm disruptions have been suggested to play pathophysiological roles in these conditions27 as well as in the initiation and progression of insomnia disorder29. In the present study, we only identified a weak nonparametric positive association between IV and REM latency. However, following categorization of participants into two groups based on IS and IV (Group 1 and Group 2), no significant difference in REM latency was observed between the two groups . In addition, other major level 1 PSG parameters such as total sleep time (TST), SL, wakefulness after sleep onset (WASO), N1/N2/N3/REM proportion, and AHI were not significantly associated with IS or IV. These findings are not entirely unexpected given the multifactorial pathophysiology of insomnia disorder31. Although there is currently no consensus on the proportion of patients with insomnia with circadian rhythm disruptions, the normal distribution of IS and IV parameters in our study suggests that only a subset of patients with chronic insomnia have abnormal rest-activity patterns and circadian rhythms. Another possibility is that actigraphy-derived rest-activity pattern parameters (IS and IV) are factors independent of insomnia severity, regardless of PSG parameters. Indeed, there is a discrepancy between objective measurements of sleep and subjective insomnia32. This common misperception of sleep in patients with insomnia is problematic because patients perceive that they are getting insufficient sleep. Therefore, patients with insomnia that have sleep misperception might tend to spend more time on sleep than necessary, even during the daytime, which could result in inappropriate and irregular rest-activity patterns.There are several implications that arise from the present study. We did not identify strong relationships between actigraphy-derived rest-activity pattern parameters (IS and IV) and level 1 PSG results in patients with chronic insomnia. IS and IV are the most well-described rest-activity pattern parameters that measure the similarity of one 24-h period to the next and the strength of consolidation of the rest-activity rhythm within a 24-h period, respectively. Several studies have reported possible associations of IS and IV with the differential diagnosis, severity, and pathophysiology of diseases such as Alzheimer’s disease, Parkinson’s disease, bipolar disorder, and posttraumatic stress disorder33. For these cases, reassessing circadian rest-activity phase in daily life and applying chronotherapy, melatonin, and/or timed light exposure are potential options for addressing sleep difficulties36.Participants with late circadian phase on actigraphy (Group L) presented with more complaints regarding insomnia symptoms and longer sleep and REM latency in PSG. Although this association may seem obvious, our findings have important clinical implications for the performance and interpretation of PSG in sleep clinics. The ecological validity of PSG has been questioned due to the disparity between the specialized environment required for level 1 PSG and patients’ home setting. For example, longer sleep or REM latency on PSG is typically considered to indicate difficulties with sleep initiation in the daily lives of patients. However, it could also be due to delayed circadian phase or discomfort induced by the numerous devices required for level 1 PSG on the day of assessment. Differentiating these factors in clinical practice is critical, but may be challenging due to limited information about the patients’ circadian phase or degree of discomfort in PSG. In the present study, actigraphy-derived circadian phase was calculated, revealing that patients with delayed circadian phase had more abnormal sleep and REM latency based on conventional cut-off scores. Thus, our findings imply a possible adjunctive role of actigraphy-derived circadian phase information for the performance and interpretation of PSG. For instance, patients with early circadian phase on actigraphy but abnormal sleep and REM latency on PSG may have more severe sleep initiation difficulties in daily life or feel more uncomfortable during PSG. In contrast, for patients with delayed circadian phase on actigraphy, our findings suggest that sleep physicians should assess patients’ PSG lights-off time based on patients’ routine sleep schedule reports and actigraphy-measured circadian phase before PSG. Theoretically, PSG lights-off time should be consistent with patients’ routine sleep schedule. However, in clinical practice, there may be discrepancies between PSG lights-off time and patients’ routine sleep schedule or circadian phase due to limited and imprecise information reported by patients. We conjecture that actigraphy-measured circadian phase may provide additional adjunctive information to sleep physicians for deriving plans for PSG lights-off time. In addition, sleep difficulties of patients with delayed circadian phase on actigraphy and abnormal sleep and REM latency on PSG may be due to initiation of sleep that is too early for patients’ circadian phase. Indeed, Flynn-Evans et al. analyzed dim light melatonin onset with sleep logs in 79 patients with insomnia and reported that a substantial proportion (10–22%) of patients with insomnia initiated sleep too early for their circadian phase37. The association between higher AHI values and early circadian phase observed in our study may reflect the protective role of a normal circadian phase in obstructive sleep apnea severity.Finally, participants with early circadian phase on actigraphy (Group E) exhibited a slightly higher AHI on PSG. This group difference could be caused by confounding factors. Indeed, participants in Group E were older than subjects in Group L , but no differences in sex or BMI were noted. However, after adjusting for possible covariates including age, subjects in Group E were still significantly more prone to have abnormal AHI on PSG. One large epidemiologic sleep study reported increased AHI values in morning- and evening-type individuals after stratifying the sample by BMI and ageThis study has several limitations. Considering that all participants had insomnia disorder, associations of rest-activity patterns and circadian phase parameters with clinical symptoms and PSG results concerning control participants may have been missed in our study. We thus could not assess whether the obtained results in our study are specific for patients with insomnia or not. Future studies that include control participants with clinical evaluation and PSG results are warranted. In addition, this study was conducted using a relatively small sample size. It should also be noted that participants in our study were predominantly middle-aged to older adults. These points may limit the generalizability of our results at a population level. Furthermore, our study was cross-sectional; hence, causal relationships could not be conclusively demonstrated.In conclusion, this study investigated the associations of actigraphy-derived rest-activity patterns and circadian phase with level 1 PSG results in patients with chronic insomnia. Our analysis revealed that participants with poorer rest-activity patterns (low IS and high IV) on actigraphy assessment exhibited higher insomnia severity scores compared to subjects with better rest-activity patterns (high IS and low IV). In addition, late-phase participants (late L5 and M10 onset times) exhibited higher insomnia severity scores, longer sleep latency, longer REM latency, and lower AHI compared to early-phase participants. Notably, these associations remained significant even after adjusting for covariates. We highlight the clinical implications and the possible adjunctive role of actigraphy-derived rest-activity patterns and circadian phase parameters for the performance and interpretation of PSG in patients with insomnia. Future studies using a larger sample size and repeated assessments of actigraphy and PSG are warranted.This retrospective cross-sectional study used data from the database of a single university-affiliated hospital located in Seoul, South Korea, from May 2016 to January 2020. All patients in the database underwent overnight PSG and monitoring of actigraphy for at least 7 days from the night of PSG. In total, 124 participants diagnosed with chronic insomnia based on clinical symptoms and criteria of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) and International Classification of Sleep Disorders, Third Edition (ICSD-2) were consecutively selected. Inclusion criteria were individuals aged over 20 years with subjective sleep complaints. Exclusion criteria were as follows: non-Korean-speaking foreigners; shift workers; abnormal sleep–wake disorders; other sleep disorders, such as restless legs syndrome, narcolepsy, REM sleep behavior disorder, or periodic limb movement disorder, severe medical, neurological , or psychiatric diseases , and alcohol or illicit drug abuse or current intake of psychoactive medications. A total of 49 participants were excluded due to insufficient actigraphy data , shift worker or irregular sleep–wake rhythm (n = 13), and insomnia due to restless leg syndrome with or without definite periodic limb movement disorder (n = 4). Since we intended to assess the possible associations of actigraphy-derived rest-activity patterns and circadian phase parameters with PSG derived obstructive sleep apnea severity, we did not exclude participants with high AHI. Therefore, participants with combined insomnia with obstructive sleep apnea were included in our analysis. A final total of 75 participants were enrolled in this study.This study was approved by the Institutional Review Board of Samsung Medical Center (SMC IRB No. 2021-04-021). The need for patient informed consent was waived by Institutional Review Board of Samsung Medical Center due to the retrospective nature of the study. This study was performed in accordance with relevant guidelines and regulations of the IRB.Participants were instructed to wear a research-grade triaxial accelerometer Actiwatch 2  on their non-dominant wrist for at least 7 days prior to the night of PSG while performing their usual daily activities in a home setting. Activity counts in 1-min epochs from the first 7 consecutive days of data, commencing at midnight, were processed to calculate rest-activity patterns and circadian phase variables.38. The following parameters were calculated from the non-parametric analysis: (1) IS, which generally represents the strength of coupling of a rhythm to environmental zeitgebers; (2) IV, which generally represents activity fragmentation in a day; (3) L5 onset time; and (4) M10 onset time. Actigraphy data was handled using Actiware version 5.7 software and ‘nparACT’ package for R Statistical Software40. The distributions and correlations of four rest-activity patterns and circadian phase variables are presented in Fig. Rest-activity patterns and circadian phase parameters were extracted using nonparametric analysis of actigraphy data. Nonparametric analysis does not adopt a priori assumptions about the waveform of daily activity; rather, it calculates variables based on raw activity counts42.PSG measurements were recorded during one night of observation with standard electrodes and sensors using Embla N7000 . The following PSG parameters were measured and collected: TST, sleep latency, REM latency, WASO, percent time in each sleep stage , and AHI. Participants completed the ISI and ESS questionnaires to measure the severity of subjectively reported insomnia symptoms and daytime sleepiness, respectivelyContinuous variable data were reported as mean and standard deviation (SD) or median and IQR after verifying the normality of the data distribution using the Shapiro–Wilk test. To explore possible associations between rest-activity patterns, circadian phase, PSG parameters, and clinical symptom scores, Pearson correlation analysis was performed for two normally distributed continuous variables. If one or both variables did not have a normal distribution, nonparametric Spearman correlation analysis was performed. Hierarchical clustering analyses were performed using Ward’s linkage algorithm with Euclidean distances for the actigraphy data-driven group classification of participants. For group comparisons, the Student’s t-test or Mann–Whitney U test was used for variables exhibiting a normal or non-normal distribution, respectively. ANCOVA was performed to examine the significance of observed associations after adjusting for potential covariates including age, sex, BMI, and lights-off time. Considering the skewed distribution and clinical implications of sleep latency, REM latency, and AHI on PSG, logistic regression analysis was performed using conventional cut-off scores after adjusting for age, sex, BMI, and lights-off time.


Immunotherapy with immune checkpoint inhibitors  became a standard of care in non-small cell lung cancer (NSCLC) patients. Most of the clinical trials excluded patients with hepatitis B (HBV), hepatis C (HCV), and human immunodeficiency virus (HIV) active infection . Despite The landscape of advanced non-small cell lung cancer (NSCLC) with no epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) genomic tumor aberrations treatment has evolved substantially during the past few years –10. ImmuThe incorporation of immune checkpoint inhibitors (ICIs) started when nivolumab showed superiority over docetaxel in second-line treatment in the CA 209-017 and CA 209-057 trials , 4. ThenThen, KEYNOTE trials showed that pembrolizumab gives further benefit in first-line treatment in NSCLC patients. First, pembrolizumab in monotherapy showed survival benefit over platinum doublet chemotherapy in treatment-naive patients with programmed death receptor type 1 (PD-L1) expression of at least 50% in the KEYNOTE-024 trial . KEYNOTEThe year 2020 brought a new Food and Drug Administration (FDA) registration based on CA 209-227 trial—nivolumab combined with ipilimumab was found superior to chemotherapy alone in an untreated NSCLC patient in whom PD-L1 expression was ≥1%. The most common adverse events (AEs) observed in ≥20% of patients receiving the combination of nivolumab plus ipilimumab, as in other studies using this combination, were the following: (1) general: fatigue, rash, decreased appetite, and musculoskeletal pain; (2) gastrointestinal: diarrhea/colitis, nausea, and hepatitis; (3) respiratory: dyspnea and cough; and (4) dermatological: pruritus .In January 2021, the results of the CheckMate 209-9LA trial were published, showing that in untreated NSCLC patients, nivolumab plus ipilimumab combined with two cycles of platinum-based chemotherapy improve OS versus standard arm. The study demonstrated that addition of ICI therapy shortens chemotherapy duration with no unexpected safety signs . During In the vast majority of trials evaluating ICI in NSCLC patients, the infection with hepatitis B (HBV), hepatis C (HCV), or human immunodeficiency virus (HIV) was an exclusion criterion and none of them included patients with SARS-Cov-2 , 10, 12.On the other hand, HCV-, HBV-, and HIV-infected patients are at increased risk of developing malignancies, and this population should not be omitted if the most effective treatment option is based on ICI. Precise knowledge of potential risk and specific approach is necessary if such a therapy is to be initiated.Since 2020, the oncologists have to face the problem of SARS-Cov-2 infection among lung cancer patients. A basic knowledge about clinical presentation, susceptibility, and outcome are substantial to take proper clinical decisions.This manuscript provides a literature review in these special populations of NSCLC patients treated with ICI. The presented manuscripts are summarized in As previously mentioned, the infection with HIV, HBV, or HCV is one of the most common exclusion criterion for clinical trials incorporating ICI in the treatment plan.In patients infected with HBV and HCV treated with ICI, the most common concern is potential HBV reactivation and immune hepatitis induced by ICI. Patients infected with HIV are additionally at risk of infectious complications of cancer therapy. Our experience with this patient population started based on case reports, but every year brings new larger evidence in these groups of patients.In one of the published series, seven patients treated with PD-1 inhibitors nivolumab and pembrolizumab for either metastatic melanoma or metastatic NSCLC with medical history of chronic or past HBV/HCV infection treatment were analyzed retrospectively. One patient showed an increase in alanine transaminase (ALT) grade 2 severity that returned to the normal range after treatment of his HCV infection. In four other patients, ALT elevation grade 1 was noted, with no intervention needed, and in the two remaining patients, no toxicity was seen. Treatment outcome was similar as in the noninfected population. Based on these observations, the authors conclude that patients with NSCLC and metastatic melanoma can be effectively and safely treated with PD-1 inhibitors despite HBV/HCV infection, but a close cooperation with hepatologist is required if eventual antiviral therapy is indicated .In a retrospective analysis from five centers, Shah et al. summarized the treatment course in 50 patients with advanced stage cancer and HBV, HCV, or HIV infection treated with ICI. In the HIV cohort of 21 patients, the rate of immune-related adverse events (irAE) was 24% with 14% if grade ≥3 irAE and no significant changes in viral load and CD4+ T-cell counts. In the HCV/HBV cohort of 34 patients, irAE rate was 44% with 29% grade ≥3. In the HBV/HCV patients with pre- or post-treatment viral load, reactivation was not observed  for at least 4 weeks, an open-label, phase 1 study was conducted in 33 patients . In the cohort, 12 irAE occurred, namely, hypothyroidism (6), pneumonitis (3), rash (2), and aminotransferase elevation (1)—thus typical toxicity profile. All patients were on ART, and uncontrolled HIV infection was not noted in any subject. CD 4 T-cell counts increased during the study, but this finding was not statistically significant. The obtained response rates confirm that pembrolizumab is an effective and feasible therapy in HIV-positive cancer patients .Important analysis results were recently published by Lee et al.  The retrp = 0.004). The authors concluded that HBsAg-positive patients are at risk of HBV reactivation during ICI therapy and should be monitored for HBV DNA and given reactivation prophylaxis  or chronic HCV infection (5 cases), who received an anti-PD-1 monoclonal antibody. An overall response rate was 35%. The liver function test elevation from baseline was mild and quite rare with no irAE of grade 3–4 requiring ICI discontinuation or steroids to treat hepatic toxicity. No cases of HBV reactivation or HCV flare were observed on ICI therapy, and no changes in viral load occurred. Thus, treatment of NSCLC patients with ICI appears quite safe in the population of HCV- or/and HBV-infected patients with efficacy measures consistent with those in the noninfected population of NSCLC patients  for advanced stage cancer.There were no treatment-related deaths, but some hepatic events occurred: In 3.4% of HBV-infected patients, and 17.3% of HCV-infected patients, grade 3 or 4 transaminase elevation was seen. Moreover, 2.8% without antiviral treatment experienced a virus load increase, and in 1.9%, virus-related hepatitis was diagnosed. In 18.6% with hepatocellular cancer, 32.4% with melanoma, and 16.7% of NSCLC patients, objective response was achieved. The authors conclude that ICIs are safe and effective in advanced cancer patients with HBV or HCV infection, but still reactivation of viral hepatitis are possible in an unclear mechanism. They recommend to initiate and continue antiviral therapy during ICI treatment if indicated .An important review was published in 2021 with a recommendation to screen all the patients before ICI administration for serologic tests of HBV infection, including HbsAg, anti-Hbc, total IgG, and anti-HBs in order to identify all patients at risk of HBV reactivation to whom antiviral prophylaxis is strongly advised .Further important data for HIV-infected patients with malignancies were provided in the phase 2, open label, non-randomized DURAVAST trial. The trial included 20 patients with malignancies in which ICI therapy was approved or data proving anti-PD1 or anti-PD-L1 activity were published, with no available standard therapy at study enrollment. All the patients were on combination antiretroviral therapy and had no detectable viral load. The CD4+ and CD8+ lymphocyte count and viral load were monitored during durvalumab therapy (at a dose of 1500 mg every 28 days), and no significant changes in these HIV infection activity parameters were observed. Moreover, the study showed a disease control rate of 50%, with 25% of partial responses with no new safety signals in this specific population. The authors conclude that, if indicated, the durvalumab monotherapy should be available to patients with controlled HIV infection .To summarize, HBV, HCV, and HIV infection in NSCLC patients can be treated with ICI if indicated in most of the cases , 25. As In the authors’ opinion, the modification of HBV/HCV/HIV-infected patients requiring ICI therapy should include:a. HBV-infected patients- Reactivation prophylaxis in every patient at risk at least 7 days before ICI initiation- AST, ALT, and total bilirubin concentration assessment before each ICI administration—if any of them increases, viral load should be monitored- If reactivation is diagnosed, ICI therapy should be delayed until liver tests return to normal and ICI rechallenge should be discussed with hepatologistb. HCV-infected patients- Anti-HCV therapy initiation should be considered in every case, with assessment of viral load at day 15. If decreased, ICI can be safely initiated , 21. If - AST, ALT, and total bilirubin concentration assessment before each ICI administration—if any of them increases, viral load should be monitored- If reactivation is diagnosed, ICI therapy should be delayed until liver tests return to normal and ICI rechallenge should be discussed with a hepatologistc. HIV-infected patients- Every patient should receive anti-HIV treatment- CD4+ lymphocyte count and viral load should be assessed before ICI initiation- Monitoring of CD4+ lymphocyte count and viral load should be monitored by an infectious disease specialist as in standard practice- Organ-specific anti-HIV drug toxicity should be monitored before each ICI administration in order to avoid cumulation of toxicity mechanismsAccording to published data, there is no need to assess ICI efficacy more frequently than in the rest of the population.The landscape of lung cancer immunotherapy AEs and clinical course of SARS-Cov-2 infection in lung cancer patients has substantially influenced oncologists’ approach to treatment since January 2020. Theoretically, immunotherapy in lung cancer patients could potentially enhance immunologic control and improve COVID-19 and other infection outcome, but it could also lead to increase the risk of COVID-19 complications, especially in the hyperactive immune phase.Since the pandemic started in China, the first reports originated from Wuhan. In March 2020, a group of Chinese researchers published a retrospective analysis of three hospitals’ database in Wuhan; clinical data were collected from medical records from patients with confirmed COVID-19 .The experience from 14 hospitals included 105 cancer patients (20.95% with lung cancer) and a matched control group, all with COVID-19. The authors demonstrated higher rates of death, intensive care unit (ICU) admission, having at least one severe or critical symptom, and higher risk of the need of mechanical ventilation in the cancer patients’ group, especially in the metastatic setting. It was observed that patients who received immunotherapy tended to have high rates of death [two (33.33%) of six patients] and high chances of developing critical symptoms [four (66.67%) of six patients]—the numbers were very small and a significant difference could not be shown .The data from the systematic review of 31 studies show 181,323 patients with COVID-19, of whom 23,736 patients with cancer confirmed that they are at increased risk of mortality and morbidity. The mortality was highest in hematological malignancies (OR 2.43) followed by lung cancer (OR 1.8) with no association between a particular type of oncologic therapy .Luo et al. were the first authors to address the question whether PD-1 blockade therapy affects COVID-19 severity in lung cancer patients. In the analyzed population, 41 (59%) patients previously received PD-1 blockade in four categories: ever received PD-1 blockade, most recent dose within 6 months, most recent dose within 6 weeks, and first dose within 3 months. Overall, there was no significant difference in severity regardless of PD-1 blockade exposure. Peak IL-6 level among hospitalized patients was similar based on receipt of PD-1 blockade. In this single-institution cohort, over half of our patients with lung cancers and COVID-19 required hospitalization and almost a quarter died, which is consistent with findings from Hubei province , 29.One of the latest published reports used a global database (TERAVOLT) in order to establish what are the effects of SARS-Cov-2 infection in thoracic malignancies patients . Data weThe most recent manuscript was dedicated to identify the patient-specific and cancer-specific features that impact severity of COVID-19, as clinical decisions should be driven by this knowledge. The study was based on a single-institution experience, the Memorial Sloan Kettering Cancer Center in New York, and included 102 consecutive lung cancer patients with COVID-19 diagnosis and analyzed the severity of COVID-19 outcome. The authors found that COVID-19 in lung cancer patients is associated with severe clinical course, with 62% requiring hospitalization and a 25% rate of fatal outcome. As in the general population, patient-specific risk factors including smoking status and chronic obstructive pulmonary disease  correlated with severe outcome . What is encouraging in taking decisions to refer lung cancer patients to ICUs is the fact that 25% of patients initially requiring intubation recovered from COVID-19, as well as the majority of the studied population. The examined impact of cancer therapy on the COVID-19 clinical course and outcome remains a critical question that should drive real-life clinical decisions during the pandemic. In the studied population, recent PD-1 blockade with or without chemotherapy was not linked with increased severity of COVID-19 as well as the comparison of chemotherapy or TKI. The authors did not find an improvement in severity of clinical course of hydroxychloroquine in the studied population .A single-institution retrospective analysis included 820 cancer patients in whom SARS-Cov-2 infection was diagnosed. The observed rates of respiratory failure or death were 36% and 32% for metastatic lung cancer patients who did and did not receive immunotherapy, respectively. The authors admit that immunotherapy use, thoracic cancer, smoking history, and metastatic solid cancer are highly associated; it is difficult to understand which factors are responsible for worse COVID-19 outcomes and need larger analyses in cancer-specific cohorts (p < 0.001), male gender  and presence of comorbidities with an important role of hypertension  and cardiovascular disease (OR 2.32) but not with chemotherapy (even administered up to 4 weeks before COVID-19 diagnosis), immunotherapy, radiotherapy, hormone, or targeted therapy. Thus, the impact of cancer diagnosis and/or treatment itself on COVID-19 clinical course and especially the risk of death was not confirmed  and (2) immunotherapy associated with the risk of exacerbation   were not at higher risk of COVID-19 exacerbation or death. The cancer treatment-related factors with a negative impact on COVID-19 clinical course were as follows: (1) chemotherapy administered within 28 days before infection—associated with increased risk of death  .Thus, as reported above, we have different signals concerning the impact of chemotherapy or immunotherapy on COVID-19 endpoints, and in each case, decisions have to be made in a personalized manner in non-vaccinated patients. As the COVID-19 pandemic is still ongoing, clinicians have to consider the potential risk in patients initiating ICI therapy. Important expert opinions support ICI initiation in a metastatic setting in patients without COVID-19. The adjuvant setting prolonging progression-free survival only in ICI therapy is not equally justified in the authors’ opinion due to increased risk of healthcare resources—an important risk factor of SARS-Cov-2 infection transmission. Treatment delay can also be advised in low volume indolent malignancy . We do nMid-2020 supported the oncological community with the first recommendations concerning lung cancer diagnosis and treatment in the COVID-19 era. Authors are consistent and bring a similar approach to advanced-stage NSCLC patients. It is clearly emphasized that oncologists “should still follow the principles of providing the best possible care and palliative management of our patients to improve overall survival and maintain quality of life”. As we all agree that it is expected to reduce the oncology centers’ visit frequency, patients can benefit from trials results that have shown that less frequent anti-PD-1 antibody administration does not influence their efficacy and safety , 38. TheCOVID-19 brought a new challenge for oncologists—the differential diagnosis of COVID-19 and immune-related adverse events in the course of immunotherapy. As shown in the literature, both immune-related pneumonitis and SARS-Cov-2-related pneumonia have similar clinical manifestations, with the most frequent symptoms occurring in both populations being cough, dyspnea, fever, hypoxia, and weakness. Moreover, the occurrence of gastrointestinal symptoms is also likely a symptom of both COVID-19 and irAE in the course of ICI treatment –41. RadiSince the late 2020, anti-SARS-Cov-2 vaccines have become available. As a sufficient number of doses and healthcare resources were not sufficient, governments all over the world had to establish which populations should be vaccinated as a priority. Thus, the populations in which COVID-19 has an unfavorable clinical course compared to the general population had to be determined. Based on important literature review, it was confirmed that cancer patients should be vaccinated as early as possible due to the high risk of COVID-19 complications and mortality, especially higher in patients with hematological malignancies and lung cancer in advanced stages or those undergoing oncological treatment as frequent contact with healthcare workers is an additional risk factor for SARS-Cov-2 infection .In May 2021, the first results showing the safety of the two doses of the BNT162b2 mRNA vaccine in 134 ICI-treated cancer patients were compared to the control group. Similar rates of side effects were noted in both groups . The study did not show new irAE or exacerbation of the previously noted side effects. Moreover, in patients with irAE, the vaccine side effects were not more frequent and had a mild clinical presentation . These dAs SARS-Cov-2 infection is a new phenomenon, it is strongly advised to follow updated recommendations available, for example, on American Society of Clinical Oncology or European Society of Medical Oncology websites , 47.To summarize the data we have at the end of 2020, lung cancer patients are more susceptible to SARS-Cov-2 infection and they are at higher risk of developing COVID-19 complications such as pneumonia/pneumonitis and ARDS, of being admitted to the ICU, of using mechanical ventilation, and, unfortunately in about one-third of cases, of dying. We do not have clear indications that patients undergoing ICI, subjected to systemic therapy, are at a different risk of contracting COVID-19 or have a different prognosis than patients treated with other systemic therapies. In 2021, when SARS-Cov-2 vaccines are becoming more and more accessible for cancer patients, it is strongly advised to perform the vaccination in order to avoid COVID-19 in cancer patients. In the non-vaccinated patients, national or local policies concerning SARS-Cov-2 molecular screening before immunotherapy initiation differ substantially between countries and even institutions. Despite that, it seems justified to screen every lung cancer patient for SARS-Cov-2 infection before therapy initiation and every subsequent dose, especially in the non-vaccinated population. If the patient is SARS-Cov-2-positive (even if asymptomatic), the delay of any cancer therapy initiation until full recovery (at least 2 weeks following resolution of symptoms) is the only known reasonable approach . The queEK was responsible for literature search and review, publications choice, data assembly, proper language corrections, manuscript writing and final approval. IC was responsible for manuscript writing, proper language corrections and final approval. KW-K was responsible for literature search and review, publications choice, data assembly, proper language corrections, manuscript writing and final approval. All authors contributed to the article and approved the submitted version.EK: honoraria from Roche, Merck, Sharp and Dohme, Bristol-Myers Squibb, AstraZeneca. KW-K: honoraria from Roche, Merck, Sharp and Dohme, Bristol-Myers Squibb, AstraZeneca.The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance—multi-modal feature fusion and imbalanced data modeling. In this study, to improve classification performance for equine activities while tackling these two challenges, we developed a cross-modality interaction network (CMI-Net) involving a dual convolution neural network architecture and a cross-modality interaction module (CMIM). The CMIM adaptively recalibrated the temporal- and axis-wise features in each modality by leveraging multi-modal information to achieve deep intermodality interaction. A class-balanced (CB) focal loss was adopted to supervise the training of CMI-Net to alleviate the class imbalance problem. Motion data was acquired from six neck-attached inertial measurement units from six horses. The CMI-Net was trained and verified with leave-one-out cross-validation. The results demonstrated that our CMI-Net outperformed the existing algorithms with high precision (79.74%), recall (79.57%), F1-score (79.02%), and accuracy (93.37%). The adoption of CB focal loss improved the performance of CMI-Net, with increases of 2.76%, 4.16%, and 3.92% in precision, recall, and F1-score, respectively. In conclusion, CMI-Net and CB focal loss effectively enhanced the equine activity classification performance using imbalanced multi-modal sensor data. The behavior of horses provides rich insight into their mental and physical status and is one of the most important indicators of their health, welfare, and subjective state . HoweverOver recent decades, automated animal activity recognition has been studied widely with the aid of various sensors  and the use of machine learning techniques. For instance, a naïve Bayes (NB) classifier was applied to recognize horse activities  using triaxial acceleration and obtained 90% classification accuracy . Four clAlong with the recent advances in internet technology and fast graphics processing units, various deep learning approaches have been increasingly and successfully adopted in animal activity recognition with wearable sensors. Classification models based on deep learning achieve automatic feature learning through data driving and subsequent animal activity recognition. For example, feed-forward neural networks (FNNs) and long short-term memory (LSTM) models were applied to automatically recognize cattle behaviors  using data collected from inertial measurement units (IMUs) ,13. ConvHowever, multi-modal data fusion has not been well handled when different sensors are used simultaneously in existing studies. Multi-modal data with different characteristics are often simply processed using common fusion strategies such as early fusion, feature fusion, and result fusion . The earIn addition, the collected sensor datasets often present class imbalance problems due to the inconsistent frequency and duration of each activity resulting from specific animal physiology. Deep learning methods trained on imbalanced datasets tend to be biased toward majority classes and away from minority classes, which easily causes poor modal generalization ability and high classification error rates for rare categories . CommonlWe proposed a CMI-Net involving a dual CNN trunk architecture and a joint CMIM to improve equine activity recognition performance using accelerometer and gyroscope data. The dual CNN trunk architecture comprised a residual-like convolution block (Res-LCB) which effectively promoted the representation ability and robustness of the model . The CMIWe devised a novel attention module, i.e., CMIM, to achieve deep intermodality interaction. The CMIM combined spatial information from two-stream feature maps using basic CNN to produce two spatial attention maps with respect to their importance, which could adaptively recalibrate temporal- and axis-wise features in each modality. To the best of our knowledge, the attention mechanism was employed for the first time in animal activity recognition based on multi-modal data yielded by multiple wearable sensors.We adopted a CB focal loss to supervise the training of CMI-Net to mitigate the influence of imbalanced datasets on overall classification performance. The CB focal loss can pay more attention not only to samples of minority classes, diminishing their influence from being overwhelmed during optimization, but also to samples that are hard to distinguish. As far as we know, this is the first time the CB focal loss has been utilized in animal activity recognition based on imbalanced datasets.Experiments performed verified the effectiveness of our proposed CMI-Net and CB focal loss. In particular, the experimental results demonstrated that our CMI-Net outperformed the existing algorithms in equine activity recognition with the precision of 79.74%, recall of 79.57%, F1-score of 79.02%, and accuracy of 93.37%, respectively.To improve the recognition performance for equine activities while tackling the abovementioned challenges, we have developed a cross-modality interaction network (CMI-Net) which achieved a good classification performance in our previous work , and a CThe dataset used in this study was a public dataset created by Kamminga et al. . In thisacc and CNNgyr) separately, is shown in Our proposed CMI-Net, where accelerometer and gyroscope data were fed into two CNN branches –(14). Each indicator value was multiplied by 100 as the result to reflect the difference in indicator values more clearly.-average .−4 was employed, and the learning rate decreased by 0.1 times every 20 epochs. The number of epochs and batch size were set to 100 and 256, respectively. The best model with the highest validation accuracy was saved and verified using test data. To evaluate the classification performance of our CMI-Net, we compared it against various existing methods, including three machine learning methods  and two deep learning methods used in equine activity recognition  [https://github.com/Max-1234-hub/CMI-Net from 1 September 2021.To attain subject-dependent results, the LOOCV method was used, in which four subjects were chosen for training, one for validation, and one for testing each time and rotated in a circular manner. During training, the loss function was added by an L2 regularization term with a weight decay of 0.1 to avoid overfitting. An Adam optimizer with an initial learning rate of 1 × 10onvNet7) ,15, baseOverall, experiments conducted on the public dataset demonstrated that our proposed CMI-Net outperformed the existing algorithms. Ablation studies were then carried out to verify the effectiveness of CMIM and that applying the CMIM in the upper layer of CMI-Net could obtain better performance. Different loss functions were adopted to validate that CB focal loss performed better than any class-level or sample-level reweighted loss used alone, and it effectively improved the overall precision, recall, and F1-score, although the overall accuracy decreased due to the imbalanced dataset used. Furthermore, recognition performance analysis was presented to help us probe the predicted performance on each activity using our CMI-Net with CB focal loss. The details are described as follows.γ = 0.5) enabled the values of precision, recall, and F1-score to increase by 2.76%, 4.16%, and 3.92%, respectively, compared with CMI-Net with softmax CE loss. This revealed that the adoption of CB focal loss effectively improved the overall classification performance.The comparison results of our CMI-Net with three machine learning methods  and two deep learning methods  ,15 are iTo explore the effectiveness of CMIM and the impact of its position in the network on classification performance, the results corresponding to four different variants are shown in The results above have proven that the inclusion of the CMIM in the network provided quantifiable improvements in identification performance. This was also reflected in the qualitative visualization of the embeddings and the corresponding clusters in γ. CMI-Net with CB focal loss (γ = 0.5) achieved the best precision of 82.50%, recall of 83.73%, and F1-score of 82.94%. This indicated that CB focal loss was beneficial to the improvement of classification performance when the modulation strength was controlled appropriately, whereas negative effects occurred if the value of γ was too large or too small.To study the effect of CB focal loss on the optimization of CMI-Net, we show the quantitative performance in γ = 0.5) on the classification performance, we present the classification results of each activity under CMI-Net with CB focal loss and softmax CE loss, respectively, in To provide further insight into the influence of CB focal loss . Both precision and recall values of all activities had more than 90% accuracy , except for the walking-natural activity, which only obtained low precision and recall (In d recall . This lod recall . It alsoThe first limitation of our proposed method is that our model was trained on a public dataset that contained only six labeled activities, i.e., eating, standing, trotting, galloping, walking-rider, and walking-natural. Indeed, there are some other activities such as head shaking, scratch biting, rubbing, and rolling, all of which, although infrequent, are physiologically critical to equine health and welfare, and should have been labeled and included in the dataset. Due to the missing of these infrequent activities in the dataset, inevitably, as a typical open-set recognition problem , these uThe second limitation is that the algorithms we developed and adopted in this study were based on supervised learning, which relied on a large number of annotated samples. Data annotation is a labor-intensive and time-consuming task, and well-annotated data is often limited as reflected by the fact that we can only find one public dataset for equine activities. With regard to the found dataset , in factIn this study, we developed a CMI-Net involving a dual CNN trunk architecture and a joint CMIM to improve equine activity classification performance. The CMI-Net effectively captured complementary information and suppressed unrelated information from multiple modalities. Specifically, the dual CNN architecture extracted modality-specific features, and the CMIM recalibrated temporal- and axis-wise features in each modality by utilizing multi-modal knowledge and achieved deep intermodality interaction. To alleviate the class imbalance problem, a CB focal loss was leveraged for the first time to supervise the training of CMI-Net, which focused more on the difficult samples and samples of minority classes during optimization. The results revealed that our CMI-Net with softmax CE loss outperformed the existing methods, and the adoption of CB focal loss effectively improved the precision, recall, and F1-score while slightly decreasing the accuracy. In addition, ablation studies demonstrated that applying the CMIM in the upper layer of CMI-Net could obtain better performance since high-level features contained more general patterns. CB focal loss also performed better than any class-level or sample-level reweighted losses used alone. In short, the favorable classification performance indicated the effectiveness of our proposed CMI-Net and CB focal loss.