Bone is comprised of mineral, collagenous organic matrix, and water. X-ray-based techniques are the standard approach for bone evaluation in clinics, but they are unable to detect the organic matrix and water components in bone. Magnetic resonance imaging (MRI) is being used increasingly for bone evaluation. While MRI can non-invasively assess the proton pools in soft tissues, cortical bone typically appears as a signal void with clinical MR techniques because of its short T2*. New MRI techniques have been recently developed to image bone while avoiding the ionizing radiation present in x-ray-based methods. Qualitative bone imaging can be achieved using ultrashort echo time (UTE), single inversion recovery UTE (IR-UTE), dual-inversion recovery UTE , double-inversion recovery UTE (Double-IR-UTE), and zero echo time (ZTE) sequences. The contrast mechanisms as well as the advantages and disadvantages of each technique are discussed. Osteoporosis (OP) is a bone disease which affects millions of people around the world  and can Bone is a highly complex hierarchical structure  of organWater in cortical and trabecular bone exist in different states and at various locations , 9. In hBone mineral density (BMD) measurement has been the standard bone evaluation method in clinics performed using x-ray-based techniques including dual-energy x-ray absorptiometry (DEXA) and quantitative computed tomography (QCT) , 16, 17.via indirect visualization of the dark regions (bone) in high-resolution conventional acquisitions, however, this approach is limited to distal bone sites and is very motion-sensitive (Employing magnetic resonance imaging (MRI) for bone evaluation has been increasingly reported in the literature. MRI-based techniques for bone evaluation avoid the potential harm associated with x-ray-based imaging techniques , 16, 22.ensitive , 26. RecQualitative bone imaging can be achieved using conventional, ultrashort echo time (UTE), adiabatic inversion recovery UTE (IR-UTE), dual-inversion recovery UTE , double-inversion recovery UTE (Double-IR-UTE), UTE with rescaled echo subtraction (UTE-RS), Fat suppression UTE, Water- and fat-suppressed proton projection imaging (WASPI), and zero echo time (ZTE) sequences. The contrast mechanisms as well as the advantages and disadvantages of each technique are discussed in detail. A brief comparison between discussed MRI techniques is presented in * cannot be inverted, but can be largely saturated, by the adiabatic IR pulse due to major relaxation of bound water magnetization during the adiabatic inversion pulse. The UTE acquisition is initiated to selectively detect signal from bound water only after an inversion time (TI) when the inverted pore water magnetization approaches the null point  0 ms 10,–15. Ther. Ther15.in vivo signal of bone, but it is still lower than the signal from surrounding soft tissues, which in turn leads to relatively low contrast as demonstrated in UTE MRI sequences with nominal TEs around tens of microseconds or less can detect signals from both bound water (T2* ≈ 300 µs) and pore water  pools in cortical bone, as demonstrated in Adiabatic inversion recovery (IR) preparation pulses have been suggested in different studies to suppress long T2 tissue components and increase the contrast in UTE MR imaging of cortical bone , 32–34. Adiabatic inversion recovery (AIR) UTE (AIR-UTE) , 36 is ain vivo such as tibia and fibula  pulses can also be employed to invert and null signals from long T2 water and fat, respectively . Dual-IRDouble inversion recovery (Double-IR) UTE sequence also employs two adiabatic inversion pulses to invert and null signals from long T2 tissues . DespiteAll the IR-UTE-based techniques  appear to provide a uniform suppression of long T2 water and fat signals, which in turn provides a good qualitative image of the targeted bone. This is because adiabatic IR pulses are relatively insensitive to B1 and B0 inhomogeneities , 62.To the best of our knowledge, there is no detailed comparison study for these techniques. Based on our experience, IR-UTE sequence is more time-efficient than both Dual- and Double-IR UTE sequences. IR- and Double-IR UTE sequences are much less sensitive to the B0 inhomogeneity than Dual-IR UTE sequence. Dual-IR sequence provides a better SNR compared with Double-IR UTE sequence. It would be interesting to perform a future study to compare all these techniques regarding the performance of SNR, CNR, and the corresponding scan efficiency. The comparisons presented in via utilizing a low power soft-pulse for fat excitation in the opposite direction of the following hard pulse  can provide qualitative imaging of the cortical bone , 47. In Water- and fat-suppressed proton projection MRI (WASPI) is another MRI sequence developed for selective imaging of bone water bound to the organic matrix –50. In tvia oversampled acquisition and mathematical reconstruction  sequence, which employs a short rectangular excitation pulse during the fully ramped up readout gradient, followed by fast radial sampling , 53. Alttruction . Figure truction . The quatruction . To imprtruction .in vivo for both cortical and trabecular bone  sequence has been proposed for direct volumetric imaging of bone by simultaneous water and fat signal suppression  which laMRI-based qualitative imaging of different water compartments in bone has drawn great interest among musculoskeletal radiologists and orthopedic researchers. These techniques provide simultaneous assessment of bone and the surrounding soft tissues, while avoiding patient exposure to ionizing radiation. Since conventional clinical MRI techniques fail to detect signal from bone, here are several qualitative MR techniques currently being developed for assessment of cortical bone. Such techniques include UTE MRI, which detects signal from both bound water and pore water in bone, but with low contrast due to much higher signals from the surrounding soft tissues such as muscle and bone marrow fat. IR-UTE-based sequences provide efficient suppression of long T2 tissues, allowing bound water imaging with CT-like bone contrast. Other techniques, such as UTE-RS, WASPI, ZTE and SWIFT also have potential for qualitative bone imaging. Some of the described techniques can be used for quantitative bone imaging and for microstructural evaluations.This study would be greatly improved if the presented MRI images would be acquired from subjects with bone diseases or injuries resulting in a better comparison between presented techniques. However, most published results in the literature only have covered healthy bone images. Comparison between the presented techniques in All authors contributed to the article and approved the submitted version.The authors acknowledge grant support from NIH  and VA Clinical Science and Rehabilitation R&D Awards (I01CX001388 and I01RX002604).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.


To evaluate three fully automated serological assays in terms of reactivity to SARS-CoV-2 immunoglobulin G (IgG) and perform SARS-CoV-2 IgG antibody testing among asymptomatic health care workers (HCW) at the University Hospital Center Zagreb.Three IgG serological assays  were initially evaluated by analyzing 42 samples from confirmed COVID-19-recovered patients and 48 negative individuals. A total of 1678 HCW  were screened for SARS-CoV-2 IgG with the Abbott assay, run on Abbott Architect i2000SR. The samples exceeding the predefined cut-off (1.4 S/C) were reanalyzed with the Elecsys, MAGLUMI, and VIDAS SARS-COV-2 IgG assays.Initially, the MAGLUMI 2019-nCoV IgG produced 26.2% false negatives and the Elecsys Anti-SARS-CoV-2 produced one false positive. Among 1678 HCW, the Abbott assay showed only 10 (0.6%) positive results, with mostly mildly elevated signals. Nine of these samples were non-reactive when they were retested with the Elecsys, MAGLUMI, and VIDAS assays. As for the one remaining sample, it was positive when tested with the Elecsys assay, while the other two assays yielded negative results.SARS-CoV-2 IgG seroprevalence among asymptomatic HCW in our hospital setting was low, with different assays indicating a different number of positive samples. One of the assays yielded a large false negative rate. These findings can be attributed to differences in assay formulation but also to heterogeneity and diverse reactivity of antibodies against SARS-CoV-2 antigens. At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, health care institutions needed to quickly establish organizational changes in order to be able to diagnose and treat COVID-19, and suppress the virus spread , even ifSince HCW are at the frontline of the COVID-19 pandemic, it is necessary to assess the true extent of viral contagion in this group of professionals. The gold standard for the diagnosis of acute COVID-19 infection is viral identification in nasopharingeal and/or oropharyngeal swab specimens with reverse transcription real-time polymerase chain reaction (rRT-PCR). However, serology testing serves as a complementary, non-invasive diagnostic tool for detecting antibody response to SARS-CoV-2, identifying asymptomatic carriers and tracking seroconversion -8. FolloTherefore, a month after the beginning of the pandemic in Croatia, we conducted a large scale serology testing within our institution with the aim to determine the seroprevalence of SARS-CoV-2 IgG antibodies among HCW and assess the proportion of infected asymptomatic HCW.The study was performed at the Department of Laboratory Diagnostics, University Hospital Center (UHC) Zagreb, Croatia. UHC Zagreb is the largest tertiary academic hospital in Croatia, consisting of 28 medical departments with 1800 beds and employing 5500 people . Although the hospital is not a dedicated COVID-19 hospital, at the beginning of the pandemic it underwent massive organizational changes to adapt to a sharply increasing number of emergency patients who would normally have been distributed between two hospitals. In order to suppress the virus spread, the hospital introduced strict preventive measures, including thorough patient triage, obligatory wearing of face masks, body temperature measurements, and hand disinfection at entrance points. Moreover, all hospital staff strictly adhered to social distancing, wore personal protective equipment, and implemented preventive hygiene measures.The serology testing in this study was performed with four serological assays.1) The SARS-CoV-2 IgG  is a qualitative fully automated chemiluminescent immunoassay run on Abbott Architect i2000SR immunoassay analyzer . It detects the presence of IgG antibodies to the nucleocapside protein of SARS-CoV-2 in the serum or plasma. The result is expressed in relative light units (RLU) and reported as an index calculated by dividing the signal of the tested sample by the calibrator . The cut-off is 1.4 S/C. According to the manufacturer, the assay has a diagnostic sensitivity at ≥14 days after symptom onset of 100% and diagnostic specificity of 99.6% .2) The Elecsys Anti-SARS-CoV-2 is a fully automated qualitative electrochemiluminescent immunoassay run on Cobas 6000 analyzer series . It detects the presence of total antibodies (including IgG) against SARS-CoV-2 using a recombinant protein representing its nucleocapside antigen. The result is expressed as a cut-off index (COI), calculated by dividing the electrochemiluminescence signal of the sample with the signal obtained by calibration. The cut-off is 1.0 COI. According to the manufacturer , the assTM 800 immunoassay analyzer . It uses antibodies directed against both the spike and viral nucleocapside SARS-CoV-2 protein (3) The MAGLUMI 2019-nCoV IgG is a fully automated chemiluminescent immunoassay run on MAGLUMI protein . The cut protein .® SARS-COV-2 IgG assay is a semi-automated qualitative assay run on miniVidas analyzer . It is based on the enzyme-linked immunofluorescent principle and detects IgG specific for SARS-CoV-2 nucleocapside and spike protein. The result obtained in relative fluorescence values (RFV) is divided by the RFV of the provided standard. The cut-off is 1.0 RFV. Assay sensitivity is 96.6% at ≥16 days after positive rRT-PCR confirmation (4) The VIDASirmation .The reactivity of the Abbott, Elecsys, and MAGLUMI assays toward SARS-CoV-2 IgG was preliminary evaluated by analyzing a series of 42 samples obtained from recovered COVID-19 patients, in whom the infection was confirmed by rRT-PCR at least 30 days ago. Additionally, we tested 48 presumably negative, healthy volunteers who strictly followed all preventive measures and were not in contact with either COVID-19 patients or anyone outside their own household. The false negative (FN) and false positive (FP) rates were calculated. This part of the study did not involve the use of the VIDAS SARS-COV-2 IgG assay.Given the different assay formulation and reactivity toward target antigens, we also analyzed non-proprietary control samples, ie, SARS-CoV-2 IgG-positive and negative commercial control samples with the Elecsys and MAGLUMI assay, and MAGLUMI 2019-nCoV IgG-positive and negative control samples with the Abbott and Elecsys assay. At the time of conducting this study, dedicated commercial control materials for Elecsys Anti-SARS-CoV-2 were not available.The study enrolled 1678 asymptomatic HCW  who were actively involved in patient care and associated hospital activities from mid-March to the end of April 2020. All asymptomatic HCW with previously confirmed COVID-19 were excluded from this part of the study.All recruited HCW were initially tested with the Abbott SARS-CoV-2 IgG assay. The positive samples were reanalyzed with three other serological assays.The samples were collected during May 2020. From each participant, one 5-mL serum tube  was obtained. The analyses were performed on fresh samples after centrifugation within 8 hours from blood draw. The study was approved by the University Hospital Center Zagreb Ethics Committee, and all participants gave informed consent before enrollment.The Abbott assay initially yielded no false positives or false negatives, the Elecsys yielded one false-positive result, while the MAGLUMI obtained 11 false negatives (26.2%) .Neither the Abbott nor the Elecsys assay obtained any signal in negative and positive MAGLUMI control material. On the contrary, in negative and positive Abbott control material the MAGLUMI and Elecsys assay obtained signals concordant with their declared reactivity, ie, negative or positive.Abbott SARS-CoV-2 IgG testing was performed in 1678 participants , 1312 (78.2%) of whom were female. The greatest number of positive individuals worked at the Department of Gynecology and Obstetrics (16.4%), followed by the Department of Anesthesiology and Intensive Care Unit (13.2%) and Department of Internal Medicine (10.7%) , while the rest worked in hospital administrative and support, technical support, and cleaning services (Supplementary Table 2The Abbott SARS-CoV-2 IgG assay yielded only 10 (0.6%) positive results. Nine of these samples were non-reactive when reanalyzed with the Elecsys Anti-SARS-CoV-2, MAGLUMI 2019-nCoV IgG, and VIDAS SARS-COV-2 IgG assays. The median S/C value of these nine samples obtained with the Abbott SARS-CoV-2 IgG assay was 1.71 (interquartile range: 1.68-2.73). The remaining one sample was classified as positive when reanalyzed with the Abbott assay  and Elecsys Anti-SARS-CoV-2 (2.06 COI), while the other two assays produced negative results.The present study revealed a low SARS-CoV-2 IgG seroprevalence in a large representative sample of asymptomatic HCW from various hospital departments at the UHC Zagreb. This is a hardly surprising finding since a relatively low prevalence among asymptomatic HCW was observed in even more burdened settings, such as referral hospitals in Germany, Spain and United Kingdom, had  -21. FurtAlthough seroprevalence among HCW in our setting was very low, different seroprevalence rates obtained with different serological assays indicate that at this point the exact number of positive HCW cannot be determined. The currently available serological assays differ significantly in terms of the targeted SARS-CoV-2 antigen, assay format, and signal generation, with diverse reactivity and capture specificity of individually produced antibodies against SARS-CoV-2 antigens -24. ThesOur preliminary evaluation revealed occasional discrepancies in assay reactivity, probably because of differences in assays' formulation or antigen presentation. This was especially evident in the case of the MAGLUMI nCoV-IgG, which yielded a striking FN rate. The MAGLUMI nCoV-IgG and VIDAS SARS-COV-2 IgG also classified one asymptomatic HCW as negative, while the other two assays classified him or her as positive, which raised concerns that this might be another true positive. However, the results obtained were not linear when the sample was serially diluted, which is not the case with true positives. This discordance might be explained by the fact that the Abbott and Elecsys assays detect antibodies directed to the nucleocapside, while the MAGLUMI and VIDAS assays detect antibodies against both the spike protein and nucleocapside. Moreover, different target antigens might at least partly explain the fact that we obtained no signal when the MAGLUMI-negative and -positive controls were analyzed with the Abbott and Elecsys assays but obtained signals concordant with their declared reactivity when Abbott controls were analyzed with the MAGLUMI and Elecsys assay. However, specific control constitution, non-commutability of commercial control samples, and matrix-dependent reactivity of each immunoassay could have also contributed to these findings. It is noteworthy that all available assays, although being declared as qualitative, provide a kind of quantitative signal relative to a fixed calibrator value, with intensities largely dependent on assay composition and reaction kinetics. This makes it difficult to compare the quantitation of results obtained by different serological assays . Given aOur study has some limitations. First, owing to limited resources, all study participants were initially screened only with Abbott SARS-CoV-2 IgG assay. Second, only a short initial assessment of assays' performance was performed, not including the VIDAS SARS-COV-2, due to limited reagent quantity. Finally, the positive results were not tested with a reliably validated confirmation method, such as virus neutralization test. However, in an effort to minimize the number of FP results, a testing algorithm with alternative assays was applied, as recommended by the Center for Disease Control and Prevention .In conclusion, this study points to a negligible SARS-CoV-2 IgG seroprevalence among asymptomatic HCW in our hospital setting, which indicates that similarly low rate of acquired immunity was present among the general population in Croatia in the observed period. Although conducted in a non-COVID-19 designated hospital with only occasionally confirmed COVID-19 infections, our study provides valuable results for epidemiological surveillance that became pivotal during the second pandemic wave. While wide serological testing is nowadays strongly advocated, and the laboratory market is quickly becoming overwhelmed with diverse serological assays, scarce peer-reviewed data are available about their diagnostic performance in clinical settings. Thus, our knowledge stems predominantly from manufacturers' data, which seem to be overly optimistic. These data are derived from studies limited by sample size, variable sampling time in relation to symptoms onset, and different patients' characteristics, which results in possible spectrum bias and overestimated diagnostic accuracy. Low-prevalence settings such as ours are especially challenging and require the use of assays with excellent diagnostic specificity in order to avoid FP results. Thus, the existing antibody assays should be carefully evaluated in different disease prevalence settings and applied with caution ,26,27. O


SARS-CoV-2 pathogenicity in humans leads to increased mortality rates due to alterations of significant pathways, including some resulting in exacerbated inflammatory responses linked to the “cytokine storm” and extensive lung pathology, as well as being linked to a number of comorbidities. Our current study compared five SARS-CoV-2 sequences from different geographical regions to those from SARS, MERS and two cold viruses, OC43 and 229E, to identify the presence of miR-like sequences. We identified seven key miRs, which highlight considerable differences between the SARS-CoV-2 sequences, compared with the other viruses. The level of conservation between the five SARS-CoV-2 sequences was identical but poor compared with the other sequences, with SARS showing the highest degree of conservation. This decrease in similarity could result in reduced levels of transcriptional control, as well as a change in the physiological effect of the virus and associated host-pathogen responses. MERS and the milder symptom viruses showed greater differences and even significant sequence gaps. This divergence away from the SARS-CoV-2 sequences broadly mirrors the phylogenetic relationships obtained from the whole-genome alignments. Therefore, patterns of mutation, occurring during sequence divergence from the longer established human viruses to the more recent ones, may have led to the emergence of sequence motifs that can be related directly to the pathogenicity of SARS-CoV-2. Importantly, we identified 7 key-microRNAs  with significant links to KEGG pathways linked to viral pathogenicity and host responses. According to Bioproject data (PRJNA615032), SARS-CoV-2 mediated transcriptomic alterations were similar to the target pathways of the selected 7 miRs identified in our study. This mechanism could have considerable significance in determining the symptom spectrum of future potential pandemics. KEGG pathway analysis revealed a number of critical pathways linked to the seven identified miRs that may provide insight into the interplay between the virus and comorbidities. Based on our reported findings, miRNAs may constitute potential and effective therapeutic approaches in COVID-19 and its pathological consequences.Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a member of the  The emergence of SARS-coronavirus-2 (SARS-CoV-2), which causes coronavirus-mediated disease 2019, or COVID-19, has now spread pandemically, resulting in a serious global health crisis. Coronaviruses are positive-single stranded RNA (+ssRNA) zoonotic viruses with a ~30 kb genome (approx). The coronavirus subfamily is divided into four genera: α, β, γ, and δ, based on serotype and genome features. The genome of a typical CoV codes for at least 6 different open reading frames (ORFs), which have variations based on the CoV type 4. Some ORFs encode non-structural proteins while others code for structural proteins required for viral replication and pathogenesis. Structural proteins include the spike (S) glycoprotein, which has various roles in SARS-CoV based on sequence analysis and might share similar viral genomic and transcriptomic complexity. Other proteins include matrix (M) protein, small envelope (E) protein, and nucleocapsid (N) protein for virus entrance and spread . . 115]. Tapeutics ,118. MERThis mechanism could have considerable significance in determining the symptom spectrum of future potential pandemics. KEGG pathway analysis revealed a number of critical pathways linked to the seven identified miRs that may provide insight into the interplay between the virus and comorbidities.Based on our reported findings, miRs may constitute a potential and effective therapeutic approach to cure COVID19 infection and its pathological consequences, requiring further validation in large cohort patient-derived samples.


The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future. A tumor grows within a highly complex and dynamic local environment composed of immune cells, stromal cells, endothelial cells, as well as other non-cellular components such as secreted cytokines, chemokines and extracellular matrix (ECM). This complex ecosystem is collectively termed as the tumor microenvironment (TME), characterized by its profound heterogeneity, plasticity, and complex cross-interaction . Our groSingle-cell RNA sequencing has been widely used to profile the intratumoral immune landscape of various types of tumors, including skin, breast, lung, liver, colorectal, head and neck, brain, bladder, renal, and endometrial cancers . Tumor i+ T cells are considered as the primary T cell subtype responsible for direct tumor killing. Multiple scRNA-seq studies have demonstrated that intratumoral cytotoxic CD8+ T cells are predominantly in the dysfunctional and exhausted state, characterized by their lack of classical effector cytokine secretion and cytolytic functions, as well as their sustained expression of T cell exhaustion markers  and squamous cell carcinoma (SCC) after PD-1 blockade did not share TCRs with the pre-existing intratumoral CD8+ T cells, suggesting that the pre-existing intratumoral CD8+ T cells had limited capacity of reinvigoration; instead, a fresh population of tumor-reactive CD8+ T cells, presumably originated outside of the TME, were recruited to the tumor site in response to PD-1 blockade. Similar observation was made on melanoma, suggesting that the CD8+ T cells presented predominately in post-ICB treated tumor samples hardly shared TCRs with the pre-treatment samples  cells, and follicular CXCR5-expressing CD8+ T cells , natural killer cells (NKs), etc.) to promote the priming and recruitment of de novo tumor-reactive T cells to the tumor. Therefore, although CD8+ T cells are the primary tumor-reactive cell type, their infiltration and functionality are largely modulated by other immune cell types, which are also essential for anti-tumor immunity.By applying joint scRNA-seq and scTCR-seq, researchers have generated novel insight into the mechanism underlying PD-1 blockade directly from human specimens.  samples . Moreove T cells . These f+ T cells are further classified into pro-inflammatory CD4+ helper T (TH) cells and immunosuppressive CD4+ regulatory T (TREG) cells. In addition to their well-established role on promoting B cell activation and differentiation, TH cells also promote priming and clonal expansion of antigen-specific CD8+ T cells and modulate CD8+ T cell-intrinsic effector functionality in the TME and secondary lymphoid organs  colorectal tumors, which is associated with significantly higher responsiveness to ICB treatment compared to the microsatellite-stable (MSS) colorectal cancers (+ T follicular helper (TFH) cells were reported to enrich in HPV+ head and neck squamous cell carcinoma (HNSCC) and associate with longer progression-free survival  cells, characterized by the expression of lineage-specific transcription factor FOXP3, are the immunosuppressive T cells correlated with tumor progression and poor clinical outcomes. TREG cells are the key component of immune homeostasis that maintains self-tolerance; and dysfunction in TREG cells often leads to autoimmune diseases  was observed from human breast cancer, and this interaction may be important for the development of an immunosuppressive TME  are also critical mediators of tumor progression and immune evasion. Myeloid cells can modulate T cell functions through their ability to present tumor antigens to T cells and to secrete key cytokines and chemokines for T cell differentiation and recruitment . Thus, Tde novo tumor-specific response. Intratumoral DCs identified from human liver and lung cancers by scRNA-seq consisted of two major subpopulations corresponding to cDC1 and cDC2, a third “activated” cDC subpopulation marked by CCR7 and LAMP3, and a fourth pDC subpopulation derived from a distinct lineage , plasmacytoid DCs (pDCs), and monocytes-derived DCs (mo-DCs). The increased abundance of intratumoral cDCs is generally associated with good prognosis, suggesting an anti-tumor role of cDCs . The pri lineage . cDC1, mgression . This obblockade . More spes tdLN; . The idees tdLN; . The actolecules , 2020. Te FLT3LG . Accordie FLT3LG . Notablye FLT3LG . In addine IL-12 . Additioblockade . In addihiPD-1lo . Altoget+CD16–), inflammatory monocytes (CD14intCD16+), immigrant macrophages (HLA-DRintCD192+), tissue-resident macrophages (HLA-DRintCD206+), TAMs (HLA-DRhiCD68+CD64+), myeloid-derived suppressor cells , and monocyte-derived DCs  the mo-DCs; ; and (3) mo-DCs; . Compare mo-DCs; . TAMs co mo-DCs; . Althoug mo-DCs; . A scRNApulation . A separpulation . A thirdpulation . Althougin tumor . Two stuin tumor . PD-L1 egression . A scRNAand IL-6 . Anothereraction . Intriguotherapy . Lastly,otherapy .de novo priming of tumor-reactive T cells; meanwhile, they secrete a rich array of chemokines, cytokines, and co-stimulatory molecules to modulate T cell functions and their response to ICB therapy  or B2M loss-of-function mutations; (2) selection for neoantigen depletion by DNA copy number loss, transcriptional repression or epigenetic repression; and (3) mutations in IFN and IL-2 signaling components , and whether intratumoral TREG cells derived from different origins exert distinct functions. Another important but unanswered question is the cell origin of the expanded T cell population in response to PD-1 blockade. Two groups have independently observed the “clonotype replacement” phenomenon following responsive anti-PD-1 treatment in skin cancer patients: clonotypes expanded after PD-1 blockade were different from the pre-existing clonotypes identified from the pre-treatment TME, suggesting limited reinvigoration capacity of the majority pre-existing T cells in the TME (The joint single-cell analysis of TCR repertoire and transcriptome has yielded tremendous insight into T cell differentiation process by connecting the genetic lineage of a given T cell reflected by its highly polymorphic TCR sequence to its functional phenotype defined by the transcriptome. A landmark study applied this approach to delineate the complete T cell differentiation roadmap of human, from early progenitors residing in the hematopoietic fetal liver and thymus into fully matured T cell types, via sampling of developing human thymus ranged from the early embryonic stage to the adulthood . In the TH cells . Therefo the TME . Howeverin vitro and animal model systems due to the requirement of genetic manipulation. Instead, retrospective lineage tracing, taking advantage of the naturally occurring somatic mutations during development, has been widely used for analysis of human samples (Prospective lineage tracing enabled by simultaneous profiling of single-cell transcriptome and the unique DNA barcodes introduced by genetic manipulation allows for tracking the clonal dynamics of different cell lineages by coupling the transcriptionally defined cell differentiation states with the perspective clonal identifiers that record the past history of cells . Weinreb samples . A varie samples , copy nu samples , single  samples , retrotr samples , microsa samples , 2015 an samples . Lineage samples . ConceivDespite of its great potential, the current single-cell technologies suffer from their limited scalability, sparse coverage, allelic dropouts, PCR errors, and most importantly, lack of spatial information . For ins+ macrophages impacts T cell infiltration (Recent technological advancements in single-cell genomics have greatly impacted the way immunologist to conduct their research, particularly in the immune-oncology field. Due to the highly heterogeneous nature of the immune system, single-cell based analysis such as FACS has always been the gold standard for immunologists to study the phenotypes of immune cells. However, conventional FACS analysis is limited by the number of markers that can be simultaneously analyzed and is largely restricted to analysis of surface markers. Although the development of CyToF largely increased the number of markers to be assessed in parallel, it remains constrained by the availability of known surface markers, which limits the discovery of previously unknown cell states. The emergence of scRNA-seq has revolutionized the way immunologists to “phenotype” their cellular population of interest: instead of assigning a cell into a particular cell type positive or negative for a set of pre-defined markers, scRNA-seq places a cell into a phenotypic continuum reflecting various aspects of its cellular identity including activation, differentiation, metabolic states and more. This leads to the identification of immune cells with much more functional diversity than previously appreciated. Moreover, scRNA-seq unveiled that immune cells differentiate along a continuous trajectory attributed by intrinsic regulatory network and extrinsic environmental stimuli, instead of differentiating step-wisely into discrete cell types or intermediates defined by selected markers. Additionally, the development of single-cell multimodal sequencing enables simultaneous profiling of genome, epigenome, transcriptome, proteome and spatial localization from the same cell . Combiniltration . Lastly,ltration .XC conceived the project. TG and XC wrote the manuscript with input from WL. 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.


Facing the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), high-volume respiratory testing is demanded in laboratories worldwide. We evaluated the performance of a molecular assay for the detection of SARS-CoV-2 on a high-throughput platform, the cobas 6800, using the ‘open channel’ for integration of a laboratory-developed assay. We observed good analytical performance in clinical specimens. The fully automated workflow enables high-throughput testing with minimal hands-on time, while offering fast and reliable results. In January 2020, a previously unknown coronavirus – now named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) – was identified as causative agent of a cluster of suspicious pneumonia cases in Wuhan, China ,2. The WThe ability to quickly confirm or clear suspected cases is crucial during global outbreak scenarios, especially when clinical manifestations are difficult to distinguish from other respiratory infections such as influenza, molecular diagnostics is key for detection of the emerging virus. A variety of suitable assays were made available early on during the course of the outbreak, notably by Corman et al. and others ,5. HowevIn this study we report the analytical evaluation of a laboratory-developed test for the detection of SARS-CoV-2 using the open channel (utility channel) of the cobas 6800 system.A custom-made primer/probe set based on a previously published assay targeting the E gene  was optiAssay performance was evaluated for swab samples. All clinical specimens used were collected at the University Medical Center Hamburg-Eppendorf (UKE-HH). Samples were mixed 1:1 with Roche cobas PCR media (≤ 40% guanidine hydrochloride in Tris-HCL buffer) and incubated for 30 min before loading onto the cobas 6800 system. Apart from that sample preparation step, no further manual steps are required during the entire workflow of the novel assay.https://www.european-virus-archive.com) [Limit of detection (LoD), inter-run variability and cross-reactivity with other respiratory pathogens were determined. In-vitro transcribed RNA (IVT RNA) of the E gene of SARS-CoV-2 and purified RNA of SARS-CoV (strain Frankfurt-1) were used as positive controls , ive.com) . Limit oBetacoronavirus subgenus Sarbecovirus [Potential interference of the SARS-CoV-2 UCT with other respiratory pathogens (including other human CoV strains) was evaluated by analysing 88 previously determined clinical samples and an external quality control assessment panel  containing lysates of infected cells. None of these organisms were detected by the SARS-CoV-2 UCT assay , confirmecovirus .Outbreaks of novel pathogens, such as the ongoing SARS-CoV-2 situation, represent a challenge for molecular diagnostics. However, identification of the agent, sequencing and publication of specific PCR assays for general use, a process that took several weeks 15 years ago, can now be accomplished in a few days . With thAutomated solutions for molecular diagnostics can help handle large numbers of samples and can be scaled to keep pace with fluctuating demand -12. The The system has passed clinical evaluation for a variety of viral and bacterial targets -17 and iIn this study, we demonstrated good analytical performance of an adapted SARS-CoV-2 assay on swab samples with an LoD of 689.3 copies/mL (e.g. 275.72 copies/process) at 95% detection probability, which is roughly in line with results published by Corman et al. . They reHowever, we believe that our assay designed for high-throughput molecular testing could be useful in the ongoing outbreak situation. It demonstrates how commercial PCR platforms can enhance outbreak readiness for emerging pathogens, allowing for large numbers of patients to be screened in a reasonable timeframe, if necessary. It has to be noted that by its nature as a screening test targeting only a single viral gene, positive results should always be confirmed with an independent PCR as recommended . Finally


Immunosuppressive therapies increase the susceptibility of patients to infections. The current pandemic with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) compels clinicians to develop recommendations for successful clinical management and surveillance of immunocompromised patients at high risk for severe disease progression. With only few case studies published on SARS-CoV-2 infection in patients with rheumatic diseases, we report a 25-year-old male who developed moderate coronavirus disease 2019 (COVID-19) with fever, mild dyspnea, and no major complications despite having received high-dose prednisolone, cyclophosphamide, and rituximab for the treatment of highly active, life-threatening eosinophilic granulomatosis with polyangiitis (EGPA). With a wide range of clinical outcomes in coronavirus disease 2019 (COVID-19), from being asymptomatic to fatal acute respiratory distress syndrome, questions have been raised about the safety of immunosuppressive therapies (2), and a long-term, slowly tapered high-dose prednisolone treatment (up to 1 g/day).We report the case of a 25-year-old male with nosocomial COVID-19 while receiving immunosuppressive treatment for eosinophilic granulomatosis with polyangiitis (EGPA). EGPA was newly diagnosed in early January 2020 when the patient presented at the emergency room with sinusitis, asthma, and a life-threatening myocardial infarction, resulting in a decreased ejection fraction of 30%. Blood eosinophils and serum concentrations of Immunoglobulin E (IgE) and C-reactive protein (CRP) were increased, ANCA-testing was negative, and a pulmonary CT scan unremarkable . Immedia2 85%) required oxygen supplementation for 3 days (low flow 2 L/min). With spiking serum concentrations of CRP , procalcitonin , and interleukin-6 , concomitant with decreasing CD4+ and CD8+ T-cell counts, the patient developed fever (max. 39.1°C) on day 7 , he reported catarrh and a mild cough. A SARS-CoV-2 real-time reverse transcription PCR (rt-PCR) from oropharyngeal swab was positive . On day on day 7 . Anti-IL+ and CD4+ T-cell numbers with declining viral RNA load. Notably, antibodies may often be insufficient for viral clearance , it is remarkable that our patient overcame COVID-19 in a rather timely manner without complications. The effects of potential anti-viral agents hydroxychloroquine and lopinavir/ritonavir on the disease course remain unclear. Despite initially higher than average copies per oropharyngeal swab, which could be explained by the effect of immunosuppression during virus contraction, our patient showed a temporal pattern of viral load peaking within the first week after onset of symptoms and gradually declining over the following three weeks as previously described in COVID-19 patient cohorts , 3. Our learance , 6.While our knowledge of COVID-19 pathogenesis continues to evolve, strategies to avoid unfavorable outcomes of SARS-CoV-2 infection should continue to be mindful of potentially greater adverse outcome caused by tempering existing immunosuppressive or immunomodulatory treatment in autoimmune diseases.The original data generated and analyzed for this study are included in the published article. Further inquiries can be directed to the corresponding author.Written informed consent was obtained from the individual for the publication of any potentially identifiable images or data included in this article.MS and RV wrote the manuscript. All authors were involved in direct patient care or acquisition of clinical data, made important intellectual contributions, revised and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Considerable progress has been made recently in the use of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) to diagnose intra-luminal gastrointestinal lesions and extra-luminal lesions near the gastrointestinal tract. Numerous reports have indicated that EUS-FNA has high diagnostic performance and safety, which has led to the routine use of EUS-FNA and an increasing number of cases. Thus, while EUS-FNA has a low rate of complications, endoscopists may encounter these complications as the number of cases increases. Infrequent reports have also described life-threatening complications. Therefore, endoscopists should possess a comprehensive understanding of the complications of EUS-FNA, which include hemorrhage, perforation, infection, and acute pancreatitis, as well as their management. This review examines the available evidence regarding the complications associated with EUS-FNA, and the findings will be useful for ensuring that endoscopists perform EUS-FNA safely and appropriately. Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) was first reported in 1992 ,5,6,7,8.The major complications associated with EUS-FNA include hemorrhage, perforation, infection, and organ-specific complications, such as acute pancreatitis after puncture for pancreatic lesions. Recent reports have also occasionally described needle tract seeding (NTS) as a complication of EUS-FNA. While the specific rates vary according to lesion and study, the complication rate is approximately 0–2.5% ,29,30,31A previous systematic review of complications and deaths associated with EUS-FNA  revealed a complication rate of 0.98% and a mortality rate of 0.02% . The speThe safety of EUS-FNA for solid lesions has been reported numerous times, based on complication rates of 0–2.5% ,28,29,31The EUS-FNA procedure can be performed using 19-gauge, 22-gauge, or 25-gauge needles, and some studies have compared the complication rates according to needle size. No obvious differences in complication rates were observed when 22-gauge needles (64 patients) and 25-gauge needles (67 patients) were used for pancreatic solid lesions , or whenHemorrhage occurs in ≤2% of patients who undergo EUS-FNA ,21,28,32A few reports have described hemorrhage-related death. In one report, 1 patient  died 3 days after experiencing a hemorrhage from an inferior pancreaticoduodenal artery aneurysm, which developed 12 h after EUS-FNA was performed for a pancreatic lesion . AnotherOther reports have linked EUS-FNA-associated hemorrhages to antiplatelet agents and anticoagulatory agents. One study evaluated the risk of hemorrhage to be associated with EUS-FNA in 26 patients who received nonsteroidal anti-inflammatory drugs , 6 patients who received low-dose prophylactic heparin (hemorrhage rate: 33.3%), and 190 control patients who received no treatment (hemorrhage rate: 3.7%) . Those rThree prospective studies of bacteremia associated with EUS-FNA in the upper gastrointestinal tract ,43,44 reThe ASGE guidelines indicate that the risk of bacteremia due to EUS-FNA is low, and prophylactic antibiotics are not recommended when EUS-FNA is performed for solid lesions . HoweverGastrointestinal perforation caused by the needle is uncommon, and a study into interventional endoscopic ultrasound (EUS), which included 224 punctures in 221 patients could only identify perforation in 1 patient  . GastroiCervical esophageal perforation reportedly occurs in 0.03–0.06% of cases that involve diagnostic EUS in the upper gastrointestinal tract ,54. A prDuodenal perforation has been reported in 0.029–0.86% of cases ,55,56,57There have been no large-scale studies regarding EUS-associated perforation of the lower gastrointestinal tract.Acute pancreatitis occurs in approximately 2% of cases that involve EUS-FNA ,20,23,58There have been several recent reports regarding NTS, which is an uncommon complication of EUS-FNA. Peritoneal dissemination after EUS-FNA for intraductal papillary mucinous carcinoma was first reported in 2003 . Since tThe EUS-FNA puncture targets in the patients who developed NTS were pancreatic cancer in 21 patients, intraperitoneal lymph node metastasis from pancreatic head cancer in 1 patient, intraperitoneal lymph node metastasis from melanoma in 1 patient, mediastinal lymph node metastasis from gastric cancer in 1 patient, intraperitoneal recurrence of unknown primary cancer in 1 patient, solid pseudopapillary neoplasm in 1 patient, and intraductal papillary mucinous carcinoma in 2 patients. The transesophageal route was only used for 1 patient for a puncture, and the transgastric routine was used for the remaining 27 patients .All 21 patients with pancreatic cancer had tumors in the pancreatic body and tail, and the mean interval to the NTS diagnosis after curative resection was 24.8 months (range: 6–42 months) in 16 patients. Two patients had solid tumors that were identified in the posterior wall of the gastric body when surgery was performed after EUS-FNA, and NTS was diagnosed based on the resected specimen. However, the time from EUS-FNA to surgery was markedly different when preoperative chemotherapy was used (113 days), and when it was not used (25 days) . In the Fifteen patients had a recurrence that presented as gastric SMT-like masses, and the NTS diagnosis was performed via biopsy during upper gastrointestinal endoscopy or EUS-FNA. The principal modalities for guiding this diagnosis are computed tomography, 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), and upper gastrointestinal endoscopy. However, the NTS was not identified using computed tomography or FDG-PET in 4 cases and was instead diagnosed based on upper gastrointestinal endoscopy findings. Therefore, if the puncture route is not included in the resected specimen, regular observation using upper gastrointestinal endoscopy is recommended for these patients ,79. It hThe reported complication rates are 0.5–2.5% when EUS-FNA is performed for pancreatic solid lesions ,21,22,24A study of EUS-FNA revealed no complications among patients with pancreatic cystic lesions (approximately 60% of puncture targets for 1034 patients with pancreatic lesions), while acute pancreatitis and duodenal perforation were observed in some patients with solid lesions . Other sThe complication rate is low when EUS-FNA is performed for mediastinal lymph nodes and tumors. A study of EUS-FNA performed in 104 patients with suspected mediastinal lymph node metastasis from lung cancer metastases only identified a complication in 1 patient  . AnotherA systematic review and meta-analysis evaluated transesophageal EUS-FNA performed for intrapulmonary tumors (11 reports and 313 patients) . That stOne study identified EUS-FNA-associated complications in only 1 of 130 patients with intraperitoneal lymph node swelling . SimilarAmong 29 patients with intrapelvic lesions, 2 patients (6.9%) developed abscesses requiring percutaneous drainage after EUS-FNA was performed via the lower gastrointestinal tract . Both paNumerous studies have shown that when EUS-FNA is performed for upper gastrointestinal SMT, the technique is safe, and the complication rate is low . HoweverRecent attempts have been made to perform EUS fine-needle biopsy (EUS-FNB) using the franseen-type needle  and the fork-tip needle . This procedure aims to provide better sample acquisition and diagnostic performance, and the safety is reportedly similar to that of EUS-FNA. A study comparing FNA and FNB revealed complications in only 1 of 229 cases (0.4%), which involved 1 case of hemorrhage (requiring endoscopic hemostasis) among 115 patients in the EUS-FNA group and no complications among the 114 patients in the EUS-FNB group . SimilarThe reported complication rate is 0–3.6% when EUS-FNA is performed for hepatic lesions ,103,104.Two systematic reviews and meta-analyses have evaluated EUS-FNA for bile duct and gallbladder lesions. The first meta-analysis (9 reports and 284 patients) revealed no complications among patients with bile duct strictures and gallbladder tumors, which suggested that EUS-FNA is a safe and useful tool for diagnosing bile duct lesions and gallbladder tumors . The secEndoscopic retrograde cholangiopancreatography (ERCP) and EUS-FNA have been compared as the main techniques for diagnosing biliary diseases. One study identified no complications among 16 patients who underwent EUS-FNA for gallbladder lesions, while mild acute pancreatitis was observed for 5 of 25 patients (20%) who underwent endoscopic transpapillary gallbladder drainage . AnotherPeritoneal dissemination can occur when percutaneous puncture or EUS-FNA is performed for hilar cholangiocarcinoma. Thus, performing FNA via the intraperitoneal route should be avoided when radical resection is feasible . There iA single-center study of EUS-FNA in 121 patients with adrenal lesions revealed no complications that were associated with EUS-FNA, although percutaneous puncture had a complication rate of 4% at the same center . AnotherA multicenter study compared tissue acquisition using EUS-FNA or EUS-FNB  and revealed that only 1 patient 0.5%) developed a fever, with a negative blood culture result % develop, and comFew reports have addressed EUS-FNA for splenic lesions, and these reports generally involved single cases or small sample sizes. One study evaluated 12 patients who underwent EUS-FNA because of lesions that were difficult to puncture  or after a diagnosis could not be achieved via computed tomography or EUS-guided puncture . That stAs a method for tissue collection, EUS-FNA plays an important role for the diagnosis of various lesions with a tolerable complication rate. Although EUS-FNA has a low rate of complications, severe complications are possible. Therefore endoscopists must know the latest information regarding the complications associated with EUS-FNA and be prepared to manage these complications.


Rhipicephalus (Boophilus) annulatus and Rhipicephalus (Boophilus) microplus , collectively known as cattle-fever ticks (CFTs), are vectors of protozoal parasites (Babesia bigemina and Babesia bovis) that cause bovine babesiosis . One traditional strategy for CFT eradication involves the implementation of a “pasture vacation,” which involves removing cattle (Bos taurus) from an infested pasture for an extended period of time. However, vacated pastures are often inhabited by wildlife hosts, such as white-tailed deer , which can serve as alternate hosts for questing CFTs. We hypothesized that the distribution of host-seeking larvae among habitat types post-pasture vacation would reflect habitat use patterns of WTD, and in turn, affect the subsequent rate of pasture infestation by CFT.We adapted a spatially explicit, individual-based model to simulate interactions among SCFT, cattle, and WTD as a tool to investigate the potential effects of WTD habitat use preferences on the efficacy of a pasture vacation. We parameterized the model to represent conditions typical of rangelands in south Texas, USA, simulated a 1-year pasture vacation under different assumptions regarding WTD habitat use preferences, and summarized effects on efficacy through (1) time post-vacation to reach 100% of pre-vacation densities of host-seeking larvae, and (2) the ecological conditions that resulted in the lowest host-seeking larval densities following pasture vacation.Larval densities at the landscape scale varied seasonally in a similar manner over the entire simulation period, regardless of WTD habitat use preferences. Following the removal of cattle, larval densities declined sharply to < 100 larvae/ha. Following the return of cattle, larval densities increased to > 60% of pre-vacation densities ≈ 21 weeks post-vacation, and reached pre-vacation levels in less than a year. Trends in larval densities in different habitat types paralleled those at the landscape scale over the entire simulation period, but differed quantitatively from one another during the pasture vacation. Relative larval densities (highest to lowest) shifted from (1) wood/shrub, (2) grass, (3) mixed-brush during the pre-vacation period to (1) mixed-brush, (2) wood/shrub, (3) grass or (1) wood/shrub, (2) mixed-brush, (3) grass during the post-vacation period, depending on WTD habitat use preferences.By monitoring WTD-driven shifts in distributions of SCFT host-seeking larvae among habitat types during simulated pasture vacation experiments, we were able to identify potential SCFT refugia from which recrudescence of infestations could originate. Such information could inform timely applications of acaricides to specific refugia habitats immediately prior to the termination of pasture vacations. Rhipicephalus (Boophilus) annulatus and Rhipicephalus (Boophilus) microplus , collectively known as cattle-fever ticks (CFTs), are vectors of protozoal parasites (Babesia bigemina and Babesia bovis) that cause bovine babesiosis (cattle fever), which is considered the most economically important livestock disease worldwide  for each habitat type, size of activity range (ha), relative number of larvae they can carry at any given time , and numbers of larval, nymphal, and adult SCFTs in each age-class that hosts currently carry. Spatial scales are defined in terms of the 900, square, 1-ha habitat cells. The temporal scales explored are a weekly time step for a total of 3 years for calculation of SCFT development and survival. However, hosts move about the landscape 30 times per week, acquiring and depositing SCFTs among the habitat cells they visit.processes represented in the model include (1) temperature-dependent and habitat-specific development and survival of off-host SCFTs, (2) host-specific survival of on-host SCFTs and host-specific fecundity of deposited (fed) SCFTs, (3) the movement of hosts based on habitat preferences, and (4) host-specific and habitat-specific acquisition and deposition of SCFTs. Tick development, survival, and reproduction occur at the beginning of each weekly time step. Host movement, tick acquisition, and tick deposition occur 30 times within each weekly time step. .The most important design concept is that the SCFT life cycle is influenced by climatic conditions, landscape structure, and the composition of the host community. Survival and development of off-host stages are dependent on the temperature and relative humidity in habitat types to which they are exposed as a consequence of host-driven dispersal of gravid females. Completion of the SCFT life cycle depends on larvae encountering an appropriate host, which is influenced by species abundance, composition of the host community, and habitat preferences of potential host species. Spatial and temporal patterns of abundance of off-host SCFT larvae emerge as system-level properties as a result of equations describing rates of off-host tick development and survival, and rules governing the movements of hosts within the landscape , which We simulated a 1-year pasture vacation experiment under different assumptions regarding WTD habitat use preferences. We used a 3-year simulation period  in which cattle were removed from the system at the beginning (1st week in January) of the vacation year, and were restocked at the beginning of the 1st year post-vacation. The experimental design consisted of 5 Monte Carlo simulations for each of 11 WTD habitat use preferences for good SCFT habitat . As in Wang et al. , simulatMean weekly host-seeking larval densities at the landscape scale varied seasonally in a similar manner regardless of WTD habitat use preferences Fig. a. LarvalTrends in larval densities in different habitat types paralleled those at the landscape scale during all scenarios Fig. b–d. Not Distribution of larval densities among habitat types at their lowest point, 10 weeks post-vacation, was higher in mixed-brush when WTD habitat use preferences for wood/shrub were ≤ 0.3 and was higher in wood/shrub when preferences were ≥ 0.4; larval densities always were lowest in grass Fig. . Thus, rSpatial distributions of host-seeking larvae immediately pre-vacation and 1-year post-vacation were similar, regardless of WTD habitat use preferences; however, distributions immediately following the vacation period differed depending on preferences Fig. . The ratThe simulated effects of WTD habitat use preferences on the efficacy of pasture vacation can be summarized by shifts in the distribution of host-seeking larvae among habitat types during the pasture vacation. These shifts in larval distributions did not have the hypothesized effect on subsequent rates of pasture infestation. Rather, they provided potential SCFT refugia from which recrudescence of infestations could originate. Pre-vacation distributions of host-seeking larvae primarily reflected habitat use preferences of cattle, superimposed on habitat-specific differences in larval survival, thus masking the role of WTD in the maintenance of larvae. Larval densities were highest in wood/shrub, which was used relatively frequently (≈ 30% of the time) by cattle and in which larval survival was highest, followed by grass, which was used most frequently (≈ 60%) by cattle but in which larval survival was lowest. Larval densities were lowest in mixed-brush, where survival was intermediate and cattle use was lowest ≈ 10%). Post-vacation, before tick population recovery began, relative larval densities primarily reflected habitat use preferences of WTD, again superimposed on habitat-specific differences in larval survival. When WTD preferences were close to those assumed by Wang et al. [%. Post-vThe potential for the existence of tick refugia is inherent in the heterogeneous distribution of favorable tick habitats and varied patterns of landscape use by cattle and WTD . LandscaBoselaphus tragocamelus) have been implicated in potential CFT reinfestations [By monitoring the WTD-driven shifts in distributions of host-seeking larvae among habitat types during our simulated pasture vacation experiments, we were able to identify potential SCFT refugia from which recrudescence of infestations could originate following reintroduction of cattle. The importance of feedback mechanisms at the habitat–wildlife–livestock interface in the control of infectious diseases is recognized globally –47. PéreAlthough cattle are the main hosts of CFT, WTD are also confirmed hosts in and around the permanent CFT quarantine zone along the US-Mexico border. Recent CFT infestations outside the quarantine zone pose a serious threat to the US cattle industry. The effects of interactions among host species composition, habitat heterogeneity, and climatic variability on the efficacy of CFT eradication strategies are virtually impossible to investigate in the field. The effects of habitat use preferences of WTD, as well as other potential wildlife hosts, are poorly understood within the context of CFT management. Spatially explicit, individual-based models such as the present one are useful tools for identifying CFT distribution patterns that emerge from a wide variety of tick-host-habitat-climate interactions. Such models allow preliminary a priori evaluation of alternative eradication strategies, including novel strategies involving new technologies, which might require significant investment before a field trial would be possible.Additional file 1. Summary of model parameters and equations.


Juvenile-onset systemic lupus erythematosus (SLE) is a rare autoimmune rheumatic disease characterised by more severe disease manifestations, earlier damage accrual, and higher mortality than in adult-onset SLE. We aimed to use machine-learning approaches to characterise the immune cell profile of patients with juvenile-onset SLE and investigate links with the disease trajectory over time.This study included patients who attended the University College London Hospital  adolescent rheumatology service, had juvenile-onset SLE according to the 1997 American College of Rheumatology revised classification criteria for lupus or the 2012 Systemic Lupus International Collaborating Clinics criteria, and were diagnosed before 18 years of age. Blood donated by healthy age-matched and sex-matched volunteers who were taking part in educational events in the Centre for Adolescent Rheumatology Versus Arthritis at University College London  was used as a control. Immunophenotyping profiles (28 immune cell subsets) of peripheral blood mononuclear cells from patients with juvenile-onset SLE and healthy controls were determined by flow cytometry. We used balanced random forest (BRF) and sparse partial least squares-discriminant analysis (sPLS-DA) to assess classification and parameter selection, and validation was by ten-fold cross-validation. We used logistic regression to test the association between immune phenotypes and k-means clustering to determine patient stratification. Retrospective longitudinal clinical data, including disease activity and medication, were related to the immunological features identified.Between Sept 5, 2012, and March 7, 2018, peripheral blood was collected from 67 patients with juvenile-onset SLE and 39 healthy controls. The median age was 19 years (IQR 13–25) for patients with juvenile-onset SLE and 18 years (16–25) for healthy controls. The BRF model discriminated patients with juvenile-onset SLE from healthy controls with 90·9% prediction accuracy. The top-ranked immunological features from the BRF model were confirmed using sPLS-DA and logistic regression, and included total CD4, total CD8, CD8 effector memory, and CD8 naive T cells, Bm1, and unswitched memory B cells, total CD14 monocytes, and invariant natural killer T cells. Using these markers patients were clustered into four distinct groups. Notably, CD8 T-cell subsets were important in driving patient stratification, whereas B-cell markers were similarly expressed across the cohort of patients with juvenile-onset SLE. Patients with juvenile-onset SLE and elevated CD8 effector memory T-cell frequencies had more persistently active disease over time, as assessed by the SLE disease activity index 2000, and this was associated with increased treatment with mycophenolate mofetil and an increased prevalence of lupus nephritis. Finally, network analysis confirmed the strong association between immune phenotype and differential clinical features.Machine-learning models can define potential disease-associated and patient-specific immune characteristics in rare disease patient populations. Immunological association studies are warranted to develop data-driven personalised medicine approaches for treatment of patients with juvenile-onset SLE.Lupus UK, The Rosetrees Trust, Versus Arthritis, and UK National Institute for Health Research University College London Hospital Biomedical Research Centre. Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune rheumatic disease with a complex aetiology.Evidence before this studyJuvenile-onset systemic lupus erythematosus (SLE) is a rare autoimmune rheumatic disease characterised by a broad array of clinical manifestations associated with multiple genetic and immunological abnormalities; the condition has a more aggressive disease presentation than adult-onset SLE, emphasising the need for improved understanding of the immunological defects driving disease pathogenesis. We searched PubMed, Web of Science, and Google Scholar for research articles published between Jan 1, 1990, and March 1, 2020, using search terms including “(juvenile-onset) systemic lupus erythematosus”, “machine learning”, “immune signatures”, and “stratification”. We also searched for research articles published in the same time window in rheumatology-specific journals. Published abstracts were excluded from the searches. The earliest referenced article was published in 1993; however, due to the modern computational analytical techniques used in this paper, the majority of articles referenced were more recent (since 2016). We found that in-depth computational analysis of multi-omic datasets has accelerated the understanding of complex heterogeneous diseases such as SLE and juvenile-onset SLE. We also found some studies using machine-learning strategies to explore longitudinal gene expression signatures in peripheral blood from patients with juvenile-onset SLE that have identified unique patient groups.Added value of this studyThis study is the first to report an in-depth analysis of immune cell phenotype in patients with juvenile-onset SLE. Machine-learning methods identified a juvenile-onset SLE immune cell signature that stratified patients according to their disease trajectory.Implications of all the available evidenceThe application of machine-learning approaches to immune cell phenotyping data has identified immunological biomarkers that could help to unravel underlying disease mechanisms in juvenile-onset SLE and explain the differences in long-term outcomes of patients with juvenile-onset SLE. Such immunological signatures could facilitate better stratification of patients for optimal treatment choices and provide information to improve interventional clinical trial design.Machine learning is a subdivision of artificial intelligence that builds analytical models through learning by example and has been used in a wide range of clinical areas, including pharmaceutical target prediction for drug discoveryIn the past 4 years, in-depth computational analysis of multi-omic datasets has accelerated the understanding of complex heterogeneous diseases such as SLE and juvenile-onset SLE.Another study applied three different machine-learning approaches, including k-nearest neighbours, generalised logistic models, and random forest models to predict disease activity in patients with SLE using whole-genome gene expression profiles.In this study, peripheral blood was collected from patients who attended the University College London Hospital  adolescent rheumatology service. Patients were eligible to be included in the study if they had juvenile-onset SLE according to the American College of Rheumatology revised classification criteria for lupus (1997) or the Systemic Lupus International Collaborating Clinics (SLICC) criteria (2012), and were diagnosed before the age of 18 years. Full details of inclusion and exclusion criteria and relevant protocol details are in the This study was approved by the London-Harrow Research Ethics Committee, reference 11/LO/0330. Written informed consent was acquired from patients and healthy controls.6) were stained with fixable blue dead cell stain  and a T-cell or antigen presenting cell antibody panel followed by subsequent washes and fixation in 2% paraformaldehyde. Data acquisition was on a BD LSRFORTESSA X-20 flow cytometer , and FlowJo Analysis Software  was used to assess frequencies of 28 immune cell subsets. Cytometer Setup and Tracking (BD Biosciences) beads were run to assess cytometer performance. Application settings were created and applied to panel templates before fluorochrome compensation to ensure that all immunophenotyping data were comparable over time. The list of antibodies used, markers used to identify cell types by flow cytometry, and gating strategy are included in the Peripheral blood mononuclear cells  and sparse partial least squares-discriminant analysis (sPLS-DA)—for classification and parameter selection. Because juvenile-onset SLE is a rare disease, we used a BRF machine-learning approachGroup averages over time or spaghetti plots for individual patient trajectories were analysed. We compared immunophenotype data between healthy controls and patients with juvenile-onset SLE using an unpaired The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.vs 18 years [16–25]; Between Sept 5, 2012, and March 7, 2018, peripheral blood from 67 patients with juvenile-onset SLE and 39 healthy controls was collected . The medIn-depth immune cell phenotyping of PBMCs showed that patients with juvenile-onset SLE had a disrupted immune cell profile compared with healthy controls  B cells, and CD14 monocytes . HoweverFurthermore, removing CD19 unswitched memory B cells (the top variable from the multivariate BRF model) did not substantially alter the predictive capacity of the model  was applied by modelling the probability of juvenile-onset SLE using the immune profiles of the healthy control and juvenile-onset SLE cohorts . 12 of 2As a secondary validation, sPLS-DA was done to rank and validate the immunological variables by their distribution in patients with juvenile-onset SLE and healthy controls. sPLS-DA is a supervised clustering machine-learning approach that combines parameter selection and classification into one operation. By assessing the overall estimation error rate and balanced error rate in ten-fold cross-validation, models with four components were chosen for optimal model performance; these models gave the lowest overall estimation error rate (0·167) and balanced error rate 0·175; . This anTo assess whether the juvenile-onset SLE signature could be used to stratify patients with juvenile-onset SLE further, k-means clustering, an unsupervised machine-learning algorithm was used. After screening, eight of 28 immune cell subsets were selected: total CD4, total CD8, CD8 effector memory (EM), CD8 naive, and invariant natural killer T cells; Bm1 and unswitched memory B cells; and total CD14 monocytes . Based oClear patterns among T-cell subsets were observed from the patient grouping, with significant differences in total CD4 and CD8, CD8 naive, and CD8 EM T-cell frequencies . PatientComparison of patient demographic, clinical characteristics, treatment, and comorbidities between the groups did not reveal major significant differences except for complement component C3, which was significantly reduced in patients in groups 1 and 3 . LongituFinally, the systemic relationships between immunological parameters and serological or clinical biomarkers associated with juvenile-onset SLE were explored using a correlation network analysis. Extensive immune correlations were identified across clinical features . C3 had These results suggest potential interactions between clinical features and disease-related immune dysregulation, which could help to explain the multifactorial, heterogeneous, and systemic nature of the disease.In this study, machine-learning approaches were applied to analyse immune profiles of patients with juvenile-onset SLE and healthy controls in order to overcome difficulties in obtaining large datasets from cohorts of patients with rare diseases. For the first time, these methodologies have identified and validated an immunological signature associated with juvenile-onset SLE and also distinguished a subgroup of patients with juvenile-onset SLE with more persistently moderate disease activity. Furthermore, network analysis suggested differential relationships between clinical features and specific immune cell subsets in juvenile-onset SLE. Together, these findings improve our understanding of juvenile-onset SLE immunopathology and suggest that immune cell profiles can potentially predict future disease activity.Although the immunological differences between healthy controls and patients with adult-onset SLE have been established in many previous studies,Despite the progress in treatment of juvenile-onset SLE, the long-term outcomes of patients are far from satisfactory. Severity and heterogeneity in presentation, the scarcity of predictive biomarkers for disease activity over time to guide therapeutic decisions, and suboptimal treatment response in selected cases are major obstacles affecting clinical outcomes in patients with juvenile-onset SLE.The machine-learning analysis pinpointed eight of the 28 immune cell subtypes examined to be consistently associated with patients with juvenile-onset SLE compared with healthy controls. Furthermore, the B-cell phenotype was stable across all patients with juvenile-onset SLE, which might explain the increased predictive power of these subsets in the BRF model, whereas the CD8 T-cell phenotype was important in stratifying patients with juvenile-onset SLE. The B-cell signature included reduced frequencies of naive (Bm1) and unswitched memory B cells, suggesting that patients with juvenile-onset SLE had a more mature memory B-cell phenotype. Few studies have specifically examined the B-cell phenotype in patients with juvenile-onset SLE, and although B cells in general are dysregulated in patients with SLE,A striking feature of this study was the differential CD8 T-cell profile, which contributed to both the juvenile-onset SLE signature and stratification of juvenile-onset SLE patient subgroups. In particular, patients with juvenile-onset SLE who had elevated CD8 EM T-cell frequencies were associated with increased disease activity at baseline and tended towards a more active disease trajectory , supporting a role for CD8 T cells in the pathogenesis of juvenile-onset SLE. Expanded CD8 memory T cells have been associated with poor disease outcome measures when combined with transcriptional profiling in adults with SLE.This study has some limitations. As disease in the majority of our patients with juvenile-onset SLE was reasonably well controlled by medication, investigation of severely active juvenile-onset SLE phenotype was not possible. Furthermore, SLEDAI-2K, as all disease activity scores, is an imperfect measure of changes in disease severity; however, despite its limitations, the SLEDAI-2K score is widely used in clinical practice to guide therapeutic decisions and define SLE activity categories and was applied consistently when assessing the patients longitudinally. Notably, mycophenolate mofetil doses were significantly elevated in group 1, and this elevation was probably a reflection of the higher disease activity in group 1 patients than in patients in groups 2–4. Furthermore, although longitudinal clinical data were collected, we cannot account for patient non-compliance to prescribed therapy , which could affect the analysis comparing phenotype with disease outcomes and treatment. In addition, no organ-specific immune analysis was done because of practical reasons. Children and adolescents with juvenile-onset SLE are diagnosed on the basis of expert opinion and classified using adult-tailored classification criteria (the American College of Radiology and SLICC classification criteria). This approach can pose considerable challenges in diagnosing patients with atypical presentations. As a consequence, many patients with juvenile-onset SLE are initially labelled as having arthritis or myositis, which have been identified as manifestations of juvenile-onset SLE. For this reason, we have not excluded patients with a concomitant diagnosis of arthritis or myositis from this study. Another characteristic of this juvenile-onset SLE cohort was the small number of patients with black ethnicity within this cohort and specifically within group 1; ethnicity could play a part in altered immune cell phenotype between the groups, as has been shown previously.In conclusion, the application of machine-learning approaches to immune phenotyping data has identified immunological biomarkers that could potentially help to unravel underlying disease mechanisms in juvenile-onset SLE and explain the differences in long-term outcomes of patients with this disease. Such immunological signatures could facilitate better stratification of patients for optimal treatment choices and provide information to improve interventional clinical trial design.


The COVID-19 pandemic has caused an unequally distributed extra workload to hospital personnel and first reports have indicated that especially front-line health care personnel are psychologically challenged. A majority of the Finnish COVID-19 patients are cared for in the Helsinki University Hospital district. The psychological distress of the Helsinki University Hospital personnel has been followed via an electronic survey monthly since June 2020. We report six-month follow-up results of a prospective 18-month cohort study. Individual variation explained much more of the total variance in psychological distress  and negative changes in sleep  than the study survey wave . Regional COVID-19 incidence rates correlated with the personnel’s psychological distress. In adjusted multilevel generalized linear multiple regression models, potentially traumatic COVID-19 pandemic-related events  and front-line COVID-19 work  was associated with personnel psychological distress but age and gender was not. While vaccinations have been initiated, creating hope, continuous follow-up and psychosocial support is still needed for all hospital personnel.  In Europe, the second wave of the COVID-19 pandemic was rising towards the end of the year 2020. Globally, COVID-19 caused 2,421,075 deaths by 17 February 2021 [During the fall and winter 2020 the Finnish population were encouraged to participate in COVID-19 testing if even a single mild flu-like symptom was present and some asymptomatic at-risk groups were tested, such as close-ones of COVID-19 patients, those exposed and travelers crossing the borders. All hospital personnel have easy access to testing. The number of COVID-19 tested still varies, which affects incidence rates. The Uusimaa region COVID-19 testing capacity has been adequate through fall and winter 2020.During the second wave of the COVID-19 pandemic, a part of the health care and other hospital personnel is again severely challenged, while the pandemic-related workload is unevenly distributed. A prospective cohort study with over 4800 responders (19% of the HUS personnel) began in June 2020 and assessed HUS personnel psychological symptoms and well-being monthly via an electronic survey, which also provides information on psychosocial support services .Front-line, but also other HUS personnel, were psychologically distressed as compared to the general Finnish population in June 2020 . These eAn Israelian cross-sectional study on hospital worker N = 1570) anxiety during the COVID-19 pandemic revealed that pandemic work in itself  was not necessarily associated with anxiety 70 anxiet. Risk peAs the second wave of the COVID-19 pandemic challenges hospital personnel again, a recent Cochrane review concludes that there is a lack of evidence on how to support front-line personnel during and after the pandemic and there is a lack of follow-up studies ,9. The aThis study was approved by the HUS Ethical Committee  and permission to conduct the study was obtained from the Joint Authority of the Helsinki and Uusimaa Hospital District (1.6.2020 HUS/157/2020). Since our earlier report , new res(1)Has your work with suspected or confirmed COVID-19 patients included exceptionally disturbing or distressing assignments?(2)Have you had strong anxiety due to your own or a close one’s risk of contracting serious illness for your work with suspected or confirmed COVID-19 patients?(3)Have you or your close one contracted a hospital care requiring severe COVID-19?(4)Has a close one to you died of COVID-19?The electronic survey consists of a few open questions about work and possible changes due to the pandemic. There were also four separate questions on COVID-19 pandemic-related potentially traumatic events (PTEs during the COVID-19 pandemic) that were coded yes/no.Symptom self-rating scales included Primary Care Post-Traumatic Stress Disorder Scale (PC-PTSD-5), Mental Health Index (MHI-5) and Insomnia Severity Index (ISI). MHI-5 asks the following five questions: how much of the time in the last month the responder had considered himself to be a very nervous person, had felt downhearted, had felt calm and peaceful, had felt so down in the dumps that nothing could cheer him up, or considered himself to be a happy person. Raw scores were transformed to a rating between 0 and 100 points. MHI-5 rates under 53 points refer to clinically significant psychological distress . In a Fihttps://sampo.thl.fi/pivot/prod/en/epirapo/covid19case/ (accessed on 4 January 2021).Besides the HUS employees, we draw from an open data repository the weekly COVID-19 incidence rates in the Uusimaa region that the HUS hospital district serves. These official numbers by Finnish Institute of Health and Welfare are available from r was transformed to log(r + 1) for regression modeling to linearize the generally exponential growth rate of infection transmission. Our modeling strategy used all available data waves per employees despite him/her missing some of the waves [Boxplots and local regression lines were drawn with R version 4.0.2 (22 June 2020) to illustrate the data. Multilevel (mixed-effects) ordinary (Gaussian) and logistic  regression models were fitted with lme4 R package, version 1.1-23. A random intercept was used to model employee specific risks that stay constant over repeated measurements. Effects of time were modeled with polynomials of standardized time , and in a sensitivity analysis, with time-specific local COVID-19 log-incidence per week. More specifically, incidence rate he waves ,19. EachBetween-individual variation explained much more of the total variance in MHI-5 score  and in ISI score  than the study wave explained  in a simple linear multilevel model. This quantifies what we observed, e.g., in p = 0.073).Although nursing staff membership predicted MHI-5 screen for higher distress in the survey wave 0 data , this ashttps://www.stat.fi/tup/htpalvelut/tutkimukset/kansalaispulssi_en.html (accessed on 4 January 2021); please see also We inquired Potentially Traumatic Events (PTEs) and direct COVID-19 patient care at each survey wave, and they predicted the screen for low mental health over the follow up , with a We further verified that the local COVID-19 log-incidence predicted low mental health even when adjusting for directly treating COVID-19 patients and experiencing a traumatic event ). On an individual level, PTEs, other life events, resilience and coping strategies may mediate these changes [In our cohort, individual variation explained much of the psychological distress. Reported increase in COVID-19 incidence rates in the Uusimaa district in Finland is associated with psychological distress and negative changes in sleep. COVID-19 second wave here reflects the reported Uusimaa region COVID-19 incidence. COVID-19 infections are reported to the National Infectious Diseases Register in Finland, and on-line reports are compiled by the National Institute of Health and Welfare  noticed that younger age might predict posttraumatic symptoms among the health care personnel during the COVID-19 pandemic, the effects of gender vary between studies ,5,20,24.20 noticeTemporary insomnia symptoms are common, and often non-pathological responses to environmental, circadian, physiological, and emotional challenges. Instead, chronic insomnia can have adverse effects on health, mental wellbeing and coping with stress. Long-term cardiovascular, neurological, and psychological effects of disrupted sleep are mediated by several mechanisms, for example by low grade inflammation, autonomous hyperarousal, endocrine dysregulation, deficient brain drainage, poor restoration of mitochondrial energy resources, deteriorated memory consolidation and emotion regulation, daytime tiredness, lowered mood, anxiety, and maladaptive behavioral responses ,26. VulnLimitations of the study include the fact that the initial responder group represents 19% of Helsinki University Hospital personnel and some of the initial responders (please see the If there is a selection in our study respondents, we expect that those who work in the health care fields affected by the COVID-19 pandemic choose to continue in this survey. We consider social desirability bias unlikely since participation is voluntary. In line with international position papers on the COVID-19 pandemic, mental health research is needed ,34,35, aRecognition of potentially traumatic events during and after the COVID-19 pandemic might help to direct psychosocial support services effectively to psychologically distressed hospital personnel. All such effects of the COVID-19 pandemic cannot be mitigated by employers and psychological distress varied between individuals and also varied in line with the reported COVID-19 incidence, which affects workloads in healthcare settings.


Introduction Despite the use of unfractionated heparin (UFH) or low molecular weight heparin (LMWH), rates of thromboembolic disease, and subsequent morbidity and mortality remain unacceptably high in patients with severe novel coronavirus disease 2019 (COVID-19) disease. Direct oral anticoagulants (DOACs), such as apixaban, have numerous purported benefits although the safety and efficacy of their use in intensive care unit (ICU) patients with severe COVID-19 has yet to be evaluated.Materials and Methods Single-center, retrospective cohort study of 21 ICU patients with severe COVID-19 respiratory disease treated with apixaban for atrial fibrillation (AFib), venous thromboembolism (VTE), catheter-induced thrombosis, and/or COVID-19-induced coagulopathy. The primary objective was to evaluate the incidence of bleeding events and secondary objectives included thromboembolic events, coagulation parameters, and mortality.Results Ninety percent of patients were non-White, 43% were obese, 90% had acute respiratory distress syndrome, and 76% required mechanical ventilation. Nearly half of (47.6%) also experienced renal dysfunction and required renal replacement therapy. Eighty-six percent of patients received prophylaxis or treatment with UFH or LMWH within the 24-hour period prior to apixaban initiation. Patients were initiated on apixaban for the treatment of suspected or confirmed VTE (67%) or AFib (33%). All coagulation parameters remained abnormal but stable throughout the 10-day monitoring period. No patients experienced any major bleeding events or thrombosis throughout the study period. There were four deaths during the follow-up period, all deemed unrelated to coagulopathy or bleeding.Conclusion Apixaban appeared safe and efficacious in ICU patients with severe COVID-19 disease. These data encourage future trials seeking to optimize anticoagulation strategies in patients with severe COVID-19. The novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and its associated disease novel coronavirus disease 2019 (COVID-19) have now decimated the U.S. healthcare system for more than 8 months causing over 240,000 deathsInfection with COVID-19 has been associated with an increased risk of venous and arterial thromboembolic disease due primarily to virus-induced hyperinflammation and subsequent widespread immunothrombosis. SARS-CoV-2 utilizes the angiotensin converting enzyme 2 (ACE2) receptor to infect its host, which is expressed throughout numerous bodily organs and by endothelial cells. Direct viral infection of the endothelium and diffuse endothelial inflammation result in thrombotic microangiopathies and the recruitment of host immune cells and proinflammatory cytokines, leading to pervasive endothelial dysfunction and apoptosis.p = 0.20).The incidence of thromboembolic complications among critically ill intensive care unit (ICU) patients with COVID-19 has been reported as high as 69%.Given the now undeniable link between COVID-19, coagulopathy, and death, it is critical that data to guide optimal anticoagulation strategies be established. In comparison to traditional anticoagulants like UFH, direct oral anticoagulants (DOACs), like apixaban, have the benefit of decreased bleeding complications, lack of required laboratory monitoring, fewer potential drug interactions, less pharmacokinetic (PK) and pharmacodynamic (PD) variability, and superior efficacy.Despite these numerous purported benefits, to our knowledge, there are no published reports describing the clinical outcomes of apixaban use in critically ill ICU patients with severe COVID-19.M2000 REALTIME SYSTEM, Abbott Laboratories, Abbott Park, Illinois, United States).Apixaban was deemed therapeutic if administrated for atrial fibrillation (AFib), treatment of VTE, heparin-induced thrombocytopenia (HIT), line associated-thrombosis, or COVID-19-induced coagulopathy according to our institutional guideline , a 495-bed tertiary care academic medical center in Chicago, Illinois, United States. The study was approved by the Office for the Protection of Research Subjects Institutional Review Board with a waiver of consent granted. Adult (≥18 years of age) inpatients admitted to the medical ICU with a confirmed diagnosis of COVID-19 between March and June 2020 who received at least two doses of therapeutic apixaban were eligible for inclusion. The diagnosis of COVID-19 was confirmed via compatible clinical signs and symptoms, radiographic imaging, and a positive nasopharyngeal swab for SARS-CoV-2  in nonsurgical patients.Additional definitions for disease severity included the DIC score based on the system developed by the ISTH,n[%]), mean and standard deviation (mean ± standard deviation [SD]) for parametric data, or median and interquartile range (median [IQR]) for nonparametric data.No formal sample size calculations were performed given the descriptive nature of this investigation. As this was a single-arm study, summary statistics are reported as the number of observations and percentage  of these 21 patients had been receiving anticoagulation with UFH or enoxaparin within at least the 24 hours of preceding the switch to apixaban, including 11 patients who were receiving full-dose therapeutic anticoagulation.p = 0.20).Despite the well-established association between COVID-19, coagulopathy, and mortality, limited data are available regarding optimal prevention and/or treatment modalities and no reliable data exist to guide dosing in this population. A recent analysis of 2,773 COVID-19 patients revealed that the use of therapeutic anticoagulation may be associated with decreased mortality, especially for mechanically ventilated patients. Importantly, the rate of bleeding events was similar between patients who received anticoagulation and those who did not (3 vs. 1.9%,Our work adds to the existing data evaluating optimal strategies for anticoagulation in patients with COVID-19-induced coagulopathy and expands on these data by evaluating apixaban in this high-risk ICU population for the first time. This study includes numerous inherent limitations such as the small sample size, retrospective, single-arm nature, and relatively short follow-up period. Despite these limitations, to our knowledge, this is the first set of clinical data evaluating the use of DOACs, specifically apixaban, in ICU patients with severe COVID-19-related disease. Apixaban appeared safe and efficacious in this high-risk patient population and these data encourage future trials attempting to optimize anticoagulation strategies in patients with severe COVID-19.