The digital cushion is linked to the development of claw horn lesions (CHL) in dairy cattle. The objectives of this study were to (1) estimate genetic parameters for digital cushion thickness (DCT), (2) estimate the genetic correlation between DCT and CHL, and (3) identify candidate genes associated with DCT. A cohort of 2,352 Holstein dairy cows were prospectively enrolled on 4 farms and assessed at 4 time points: before calving, immediately after calving, in early lactation, and in late lactation. At each time point, CHL was recorded by veterinary surgeons, and ultrasonographic images of the digital cushion were stored and retrospectively measured at 2 anatomical locations. Animals were genotyped and pedigree details extracted from the national database. Genetic parameters were estimated following a single-step approach implemented in AIREMLF90. Four traits were analyzed: the 2 DCT measurements, sole lesions (sole hemorrhage and sole ulcers), and white line lesions. All traits were analyzed with univariate linear mixed models; bivariate models were fit to estimate the genetic correlation between traits within and between time points. Single-marker and window-based genome-wide association analyses of DCT traits were conducted at each time point; candidate genes were mapped near (<0.2 Mb) or within the genomic markers or windows with the largest effects. Heritability estimates of DCT ranged from 0.14 to 0.44 depending on the location of DCT measurement and assessment time point. The genetic correlation between DCT and sole lesions was generally negative, notably between DCT immediately after calving and sole lesions in early or late lactation, and between DCT in early or late lactation and sole lesion severity in early or late lactation. Digital cushion thickness was not genetically correlated with white line lesions. A polygenic background to DCT was found; genes associated with inflammation, fat metabolism, and bone development were mapped near or within the top markers and windows. The moderate heritability of DCT provides an opportunity to use selective breeding to change DCT in a population. The negative genetic correlation between DCT and sole lesions at different stages of production lends support to current hypotheses of sole lesion pathogenesis. Highlighted candidate genes provide information regarding the complex genetic background of DCT in Holstein cows, but further studies are needed to explore and corroborate these findings. CHL) refers to foot lesions that arise from damaged corium, including sole hemorrhage (SH), sole ulcers (SU), and white line lesions (WL).The digital cushion of the bovine claw is composed of 3 parallel pads of soft fat and loose connective tissue that are thought to play an important role in protecting the corium from mechanical forces in the foot . New horDCT) has since been measured in a succession of studies, with a general agreement that a thin DCT represents an increased risk of subsequent CHL development  studies have used genomic markers to map QTL that may be associated with the genetic variance of DCT. Two recent GWA studies of around 600 Holstein and Jersey cows characterized DCT as a complex trait and identified candidate genes related to inflammation, fat tissue deposition, bone growth, and keratinocyte function  estimate genetic parameters for DCT at different stages during a production cycle; (2) estimate the genetic correlation between DCT and CHL, evaluating sole lesions (SH and SU) and WL separately; and (3) identify QTL associated with DCT.The study was conducted following ethical approval by the University of Liverpool Research Ethics Committee  and procedures regulated by the Animals (Scientific Procedures) Act were conducted under a United Kingdom (UK) Home Office License (P191F589B).A prospective cohort study was designed to measure the DCT in dairy cows and record CHL at 4 time points during a production cycle. Data were collected from 4 dairy herds (A–D) in the northwest of the United Kingdom. These herds were selected for convenience based on the practicalities of frequent visits and assessments. Herds A to C housed lactating cows year round, milked cows 3 times daily, and recorded 305-d milk yields of approximately 11,000 to 11,500 L. Herd D housed lactating cows year round except for lower yielding cows, which were grazed during the summer; cows were milked twice daily, and the 305-d milk yield was approximately 9,000 L. Parous cows in all herds were routinely foot-trimmed twice a year before drying-off and at 60 to 120 d after calving. In all herds, lactating cows were regularly footbathed after milking. Herd A footbathed cows 3 times a week with either copper sulfate or formalin, herd B footbathed cows twice daily with formalin, herd C footbathed cows daily with either copper sulfate or formalin, and herd D footbathed cows 3 times a week with formalin.T1-Precalving), immediately after parturition , in early lactation around the time of peak milk yield (T3-Early), and in late lactation (T4-Late). Sample size was determined by resource constraints; all eligible animals were enrolled until the final assessments (T4-Late) began, at which point further enrollments ended because simultaneous data collection at 4 time points was not feasible.All animals that were registered as Holsteins and expected to calve between April and December 2019 were prospectively enrolled with no additional inclusion or exclusion criteria applied. A total of 2,352 animals were enrolled. Data were collected during weekly or twice weekly visits to each herd from February 2019 to July 2020 (with a break from March to June 2020 due to COVID-19 restrictions). Animals were assessed for foot lesions at 4 time points: before parturition , as previously described . This siThe data collection procedure was the same at all time points with 2 exceptions. At T2-Calving on herd C, only hind feet were assessed to reduce the handling time of cows that had recently calved; this approach was only required in this herd owing to the large numbers of cows calving each week. The other exception was at the T4-Late assessments, which resumed in June 2020 following a break due to COVID-19 restrictions; data collection from this point onwards was more limited owing to social distancing protocols, and digital cushion images were not collected.DCT-MAX); this point corresponds to the interconnecting abaxial and axial pads of the digital cushion  in the midline of the claw (DCT-FT); at this point, the specific part of the digital cushion measured was assumed to be the middle pad in a typical cow . This approach was intended to capture the severity and distribution of sole lesions, while minimizing the diluting effect of healthy claws in animals with sole lesions. We followed the same process for WL  to create a variable called “white line lesion severity” (WL-Severity). Both SL-Severity and WL-Severity were analyzed as continuous traits.The 2 DCT measurements (DCT-MAX and DCT-FT) were analyzed as continuous traits. As per our research objectives, sole lesions (SH and SU) were analyzed separately from WL. It is thought that SH and SU represent different stages of the same disease process . TherefoBos taurus genome (ARS-UCD 1.2) . Genotypes were subsequently imputed to 80K SNP genotypes by Edinburgh Genetic Evaluation Services (EGENES) using an in-house procedure that has been developed for all national genomic evaluations of dairy cattle in the United Kingdom. Briefly, this imputation process uses the Illumina BovineSNP50 BeadChip and Illumina BovineHD BeadChip (Illumina Inc.), in addition to other commercial genotyping arrays, extra gene tests, and large-effect sequence variants. Following imputation, genotypes included 79,051 SNP spanning the entire genome. Chromosomal locations of the imputed 80K SNP panel were drawn from the latest assembly of the UCD 1.2) .Imputed genotypes were available for 2,250 animals. Genotype quality control was implemented using PREGSF90  within tlmerTest package ; b is a vector of the fixed effects including herd (4 levels), parity , season of calving , and days relative to parturition (continuous variable); a is a vector of random additive genetic effects for each animal; e is vector of random residual effects; and X and Z are incidence matrices for b and a, respectively. Random effects were assumed to be normally distributed with a mean of zero and covariance structure ofI is an identity matrix and H is the relationship matrix incorporating pedigree and genomic information in a single-step genomic analyses framework , M is the number of SNP, and ip is the minor allele frequency at locus i.Genetic parameters of each trait  were estimated at each time point separately  with single-trait linear mixed models, resulting in a total of 16 univariate models. Models were fit using the average information restricted maximum likelihood algorithm, implemented in AIREMLF90 . The genramework . The invework (H  is definionships . The genTo explore the genetic relationship between the 2 DCT traits (DCT-MAX and DCT-FT), bivariate models were fit for DCT-MAX and DCT-FT at each of the 4 time points. To estimate the genetic correlation between stages of production for each DCT trait, bivariate models were fit with each pairwise combination of time points , resulting in 6 bivariate models for DCT-MAX and 6 bivariate models for DCT-FT.One of our objectives was to evaluate the genetic relationship between DCT and CHL. Therefore, we fit bivariate models for combinations of DCT and CHL traits, both within the same time point and between time points. Specifically, we fit bivariate models for DCT-MAX and SL-Severity at each of the 4 time points and for every pairwise combination of time points, such as DCT-MAX at T2-Calving and SL-Severity at T3-Early, and so on. This process was repeated for DCT-FT and SL-Severity, DCT-MAX and WL-Severity, and finally for DCT-FT and WL-Severity, resulting in an additional 40 bivariate models.G0 is the genetic covariance matrix between traits due to animal additive genetic effects, R0 is the residual covariance matrix between traits, ⊗ is the Kronecker product, H is the relationship matrix, and I is an identity matrix.Bivariate models had the same parameters as the univariate models , and ranP-values, using POSTGSF90  at each of the 4 time points . The genOSTGSF90 , 2019.P ≤ 0.05, which was corrected for multiple testing to 7.67E-07 (P ≤ 0.05/number of tested markers). Suggestive SNP were defined using a genome-wide threshold equivalent to one false-positive result per genome scan (P ≤ 1/number of tested markers).In each GWA analysis, genomic inflation was assessed by calculating the inflation factor of the test statistic . We adjuome scan , the sugLD) in our study population (A window-based GWA approach was used to further explore the association between genomic regions and DCT traits (DCT-MAX and DCT-FT). The window size was determined by linkage disequilibrium (pulation . The magpulation . On averB. taurus genome (ARS-UCD 1.2) downloaded from the National Center for Biotechnology Information database (https://www.ncbi.nlm.nih.gov/assembly/GCF_002263795.1/). In each GWA analysis, the closest gene to each significant or suggestive SNP was identified, up to a maximum of 0.2 Mb upstream or downstream from the marker. Additionally, genes were explored if they were contained or partially contained within genomic windows that explained >0.5% of the total genetic variance. The UniProt database  were analyzed at 4 assessment time points with single-trait models, and estimates of variance components and heritability are provided in The genetic correlations between DCT traits  and CHL traits , both within each time point and between time points, are provided in B. taurus autosome (BTA)-4. Suggestive SNP were identified on BTA-3, BTA-5, BTA-6, BTA-13, BTA-14, BTA-23, and BTA-26  at each time point. The genomic inflation factor ranged from 0.94 to 1.00 in the 8 single-marker GWA analyses. Single-marker analyses revealed a polygenic background to both DCT-MAX and DCT-FT at each time point . From ald BTA-26 . PositioWindow-based GWA analyses showed a similarly complex genetic background to DCT-MAX and DCT-FT . The samGO) terms: positive regulation of I-kappaB kinase/NF-kappaB signaling (GO: 0043123), positive regulation of CREB transcription factor activity (GO: 0032793), cellular response to mechanical stimulus (GO: 0071260), cell adhesions (GO: 0007155), and positive regulation of phosphatidylinositol 3-kinase signaling (GO: 0014068).The set of positional candidate genes, identified from single-marker and window-based GWA analyses, were enriched in biological processes of 5 Gene Ontology  compared with the DCT measurement taken distal to the flexor tuberosity of distal phalanx . The DCT-FT measurement is arguably more clinically relevant than DCT-MAX for sole lesion development, as this corresponds to the predilection site for these lesions and DCT-FT has been shown to correlate with CHL risk phenotypically . We alsoA key objective of our study was to estimate the genetic correlation between DCT and CHL. The genetic correlation between DCT traits and WL-Severity was not statistically different from zero, except between DCT-MAX at T3-Early and WL-Severity at T4-Late when it was positive (0.29 ± 0.14). This single positive genetic correlation should be interpreted cautiously owing to the large standard errors of this estimate, and because this was the only nonzero genetic correlation between these traits. If a positive genetic correlation truly exists between DCT and WL, it may reflect previous observations of a potentially positive genetic correlation between body condition and DCT , a positOur results indicate that DCT traits were negatively correlated with SL-Severity at several time points, although the magnitude of the genetic correlation in these instances was relatively small. A negative genetic correlation between DCT and CHL incidence was reported by The strength of the genetic correlation between DCT traits and SL-Severity that we observed was generally weak, with large standard errors, and in many cases the 95% confidence interval included zero. Unbiased estimates of genetic correlation are effectively impossible to obtain , therefoWe observed a weak negative genetic correlation between the DCT immediately after calving and the severity of sole lesions later in lactation. The suspensory apparatus of the distal phalanx has been shown to be weaker around parturition, which may result in compression of the underlying soft tissues, including the digital cushion and corium . CompresPeriparturient compression of the digital cushion is an intuitive explanation for our observation that DCT was thinnest immediately after calving, a finding replicated elsewhere . Our resWe recorded the DCT to be thinner at T3-Early than at either T1-Precalving or T4-Late, in agreement with previous research . High-yiRELN gene. In cattle, RELN is primarily expressed in central nervous tissue and is involved in neuron development . This region explained 1.06% and 1.03% of the total genetic variation of DCT-MAX at T2-Calving and T3-Early, respectively, and contained 2 candidate genes, nnotated ; therefonnotated  and withnnotated . TherefoKHDRBS3. This gene has been associated with average daily gain in cattle , so KHDRBS3 may contribute to the genetic correlation between DCT and sole lesions.Other results of interest from GWA analyses include the genomic region on BTA-14 (5.88–6.53 Mb), which explained 0.78% and 0.95% of the total genetic variance for DCT-MAX at T1-Precalving and T3-Early, respectively. This window was also adjacent to a region (6.00–6.62 Mb) that explained 0.51% of the total genetic variance for DCT-MAX at T4-Late. The candidate gene in these windows was n cattle , and it n cattle . TherefoKCNQ3 and EFR3A. The KCNQ3 gene has previously been associated with milk fat percentage and milk yield in Holsteins , which explained 0.72% of the total genetic variation for DCT-FT at T1-Precalving, was also associated with SU development in GWA analysis of CHL using this data set . Candidate genes in this window were olsteins , while Eolsteins . The lipolsteins  and is colsteins . Althougolsteins , so KCNQOSR1 gene on BTA-11 (identified for DCT-MAX at T4-Late) has been linked to multiple conformation traits including feet and leg conformation, rear leg placement, and rump width  has previously been associated with foot angle , and one of the candidate genes for DCT identified by TRIM55. Although TRIM46 and TRIM55 are in different families (We did not identify any QTL or candidate genes that were highlighted by previous GWA studies of DCT ,b. Howevfamilies , TRIM prfamilies , and theOverall, in the context of the limited previous research in this area, our results replicate some of the reported findings as well as providing additional data. Given the number of markers tested in 8 GWA analyses, only a small number of markers were associated with significant or suggestive effects on DCT. Our results did not corroborate any of the specific QTL reported in 2 previous GWA studies of DCT by We have estimated the genetic parameters and characterized the genetic background of DCT using the largest data set currently available. In addition to the size of the study population, the prospective cohort study design and accuracy of phenotype recording are further strengths of this study; however, we acknowledge some important limitations.One of the limitations of this study population was the small number of farms included, which could reduce estimates of environmental variance and inflate the estimated heritability. This limitation also affects previous research, so we have insufficient context for speculating about how much it affects our results. It is also important to note that almost two-thirds of the study population were from a single herd; replication of results in a wider and more diverse population would strengthen interpretation of our findings.A relatively large proportion of animals had missing data for the DCT-FT measurement due to the absence or ambiguity of anatomical landmarks in the stored ultrasound images; we did not record DCT-FT from these images to maintain a high accuracy of this phenotype. We designed our study to collect and store images that were retrospectively blinded and measured. If we had measured images at the same time as data collection, we could have reduced the number of missing measurements; however, subconscious biases can influence this process unless measurements are made with blinding to factors such as stage of lactation, body condition, and presence of lesions . We applIt has recently been shown, albeit in a small cohort of animals, that ultrasound measurements of DCT in weight-bearing and non-weight-bearing feet are only weakly correlated ; therefoIn conclusion, it is reasonable to question whether DCT measured using ultrasonography is the most important property of the digital cushion in terms of force dissipation and CHL development. Previous studies have described the composition of the digital cushion and its relationship with body condition and foot lesions , but theCaution is required to generalize the genetic parameters and QTL reported in this study, particularly given the polygenic nature of DCT and the small number of herds. Our results are from a population of Holstein cows in 4 dairy herds that were all commercially run with operating practices common to many UK dairy farms, but they could not be considered representative of the full spectrum of dairy farms. Within these 4 herds, 3 were operating similar and relatively intensive systems of zero grazing and 3 times a day milking. The overall period prevalence of lame cows , based oKHDRBS3 gene may contribute to the susceptibility of cows to SU in addition to the thickness of the digital cushion. Further work is needed to investigate these candidate genes and establish the precise role of the digital cushion in the pathogenesis of sole lesions.The results from this prospective cohort study indicate that DCT is a heritable trait that has a weak negative genetic correlation with the severity of sole lesions, but not with WL. The strength of the genetic correlation between DCT and sole lesions depends on the stage of lactation at which both the digital cushion and sole lesions are assessed. Digital cushion thickness is a polygenic trait, and few QTL were associated with observable effects. Candidate genes identified for DCT are related to inflammation, fat metabolism, and bone development. Most notably, the


From this, a single-center, observational cohort study has been being conducted by Tianjin Medical University General Hospital since 2021. As a pilot study of this clinical trial, the present research recruited 12 pairs of gender- and age-matched rmTBI patients with healthy subjects. Their blood samples were collected for exosome isolation, and multi-omics screening to explore potential diagnostic biomarkers in blood and its exosomes. The expression level of CHL1 protein, KIF2A mRNA, LIN7C mRNA, miR-297, and miR-1183 in serum and exosomes were found to be differentially expressed between groups. Besides, serum and exosomal CHL1, KIF2A, and miR-1183, as well as exosomal miR-297 were further verified as potential biomarkers for CTE by low-throughput assays. They are expected to contribute to establishing a novel set of CTE diagnostic signatures with classic neurodegenerative indicators in our future study, thereby updating the consensus diagnostic criteria for CTE by incorporating new evidence of the in vivo biomarkers.Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts, which is susceptible in elderly people with declined mobility, athletes of full contact sports, military personnel and victims of domestic violence. It has been pathologically diagnosed in brain donors with a history of repetitive mild traumatic brain injury (rmTBI), but cannot be clinically diagnosed for a long time. By the continuous efforts by neuropathologists, neurologists and neuroscientists in recent 10 years, an expert consensus for the diagnostic framework of CTE was proposed in 2021 funded by the National Institute of Neurological Disorders and Stroke. The new consensus contributes to facilitating research in the field. However, it still needs to incorporate  Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts, typically brain concussion and subconcussive trauma . ElderlyThe diagnosis of CTE can be confirmed only by post-mortem neuropathologic examination demonstrating a unique pattern of perivascular hyperphosphorylated tau deposition in neurons and astrocytes at the depths of cerebral sulci . In ordeAlthough there have been several studies on fluid biomarkers for CTE pathology , most ofRecently, with the development of bioinformatics, the potential value of transcriptomic and proteomics information as disease biomarkers has aroused wide attention. Exosomes are small vesicles secreted by living cells into the extracellular space that function as important carriers of information transferred among cells. They contain a large number of specific proteins and functional nucleic acids, participate in pathophysiological processes, and correlated with the occurrence and progression of various diseases. Because the membrane structure of exosomes can protect their internal ribonucleic acid (RNA) from RNase degradation, exosomal RNA is more stable and has higher concentration than free RNA in serum or plasma. Besides, in view of the maturity of the isolation and purification technique for exosomes, exosomal RNAs and proteins have been regarded as an important source of clinical biomarkers. Therefore, exploring exosomal diagnostic biomarkers for CTE would be a breakthrough point to solve the problem of early and efficient diagnosis of the disease.in vivo biomarkers.In the present study, we developed a population-based matched CTE cohort, and performed multi-omics screening to explore potential diagnostic biomarkers (RNAs and proteins) in blood and its exosomes. The verified biomarkers are expected to contribute to establishing a novel set of CTE diagnostic signatures with classic neurodegenerative indicators, thereby updating the consensus diagnostic criteria for CTE by incorporating new evidence of the The present research was conducted as a pilot study of the clinical trial  we hosted, named observational cohort study of blood transcriptomics and proteomics information as biomarkers of TES, which is aimed at exploring a novel set of diagnostic signatures for CTE or TES by recruiting 120 subjects with the history of rmTBI. The inclusion of human subjects was approved by the Ethics Committees of Tianjin Medical University General Hospital (Grant No. IRB2021-YX-056-01). The work began in June, 2021, and is still open to the public till now.In this research, blood samples were collected from 12 patients with rmTBI  who visited Cadre Physical Examination Center or Department of Neurosurgery in Tianjin Medical University General Hospital from August, 2021 to July, 2022. Blood samples from 12 gender- and age-matched healthy subjects were used as controls. Inclusion criteria for patients with rmTBI are as follows: (1) Age ≥ 18 and ≤ 80 years old with independent behavior ability. (2) Have a clear history of rmTBI. (3) The most recent head injury occurred 3 months ago. Inclusion criteria for healthy controls are as follows: (1) Age ≥ 18 and ≤ 80 years old with independent behavior ability. (2) No history of repetitive mild TBI. (3) Generally healthy with normal basic laboratory tests. Exclusion criteria include pregnant or lactating women, past history of cancer, moderate to severe traumatic brain injury, other neurological or psychiatric disorders, complications of hematological diseases, severe cardiopulmonary diseases, hepatic failure, or renal failure. More detailed information of the trial protocol is specified in the trial registration.All patients underwent an evaluation for determining the certainty of CTE pathology according to the expert consensus, in which 1 of them were diagnosed with probable CTE (high certainty), 3 of them were diagnosed with possible CTE (medium certainty), and other 8 patients were diagnosed with suggestive of CTE (low certainty). The 4 patients with probable or possible CTE and their matched healthy individuals were selected for multi-omics high-throughput assays (RNA microarray and proteomics sequencing). Their baseline characteristics are shown in Twenty milliliter blood samples were collected from all enrolled individuals in the morning after a 12-h fast and were kept in polypropylene tubes containing coagulant. They were centrifuged at 3,000 × g for 5 min at 4°C to obtain the serum (8–12 ml), and then stored at −80°C.2 magnet protocol  at the concentration of 50 mg/ml for 5 min at 4°C on a thermos-shaker to allow sufficient enrichment. Exosomes were lysed from the surface of microspheres by washing three times with PBS, and were identified using electron microscopy, nanoparticle tracking analysis and surface biomarker  detection by Western Blotting.Six to eight milliliter serum samples were proceeded to collect exosomes using a TiOprotocol . BrieflyFree RNA from the serum sample (1–1.5 ml) was extracted using TRIzol reagent  and purified with a RNeasy mini kit . Free protein from another 1–1.5 ml serum sample was extracted by a serum protein extraction kit . Exosomal RNA and protein from the serum sample (6–9 ml) was extracted using the Total Exosome RNA and Protein Isolation Kit (Invitrogen) following the manufacturer’s protocol.RNA concentration of each sample was determined by NanoDrop ND-2000 Spectrophotometer , and the quality was assessed with electrophoresis on 2% agarose gels. Protein concentration of each sample was quantified using spectrophotometry and the BCA  method.p-value of less than 0.05. Hierarchical clustering was performed based on differentially expressed lncRNAs (DElncRNAs), circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) using R package Pheatmap Version 1.0.12 .Before microarray assay, total RNA was first amplified using the GeneChip™ WT PLUS Piko Reagent Kit . Biotinylated cDNA was then prepared from 250 ng total RNA according to the standard GeneChip™ protocol . Following labeling, fragmented cDNA was hybridized for 16 h at 45°C on Clariom™ D Array and GeneChip™ miRNA 4.0 Array. GeneChips were then washed and stained in the GeneChip™ Fluidics Station 450. All arrays were scanned with GeneChip™ Scanner 3000 7G. The raw data was normalized by Transcriptome Analysis Console Software Version 4.0.1 with Robust Multichip Analysis algorithm using Affymetrix default analysis settings, and global scaling as a normalization method. Values presented are log2 RMA signal intensity. The threshold set for up- and down-regulated RNAs was more than 1.2-fold change with a Q-value of 1% for the precursor and protein were used, and protein quantities were reported only in samples that passed the filter. The significantly differentially expressed proteins (DEPs) were screened out if their absolute ratio of fold change > 1.20 with Q-value < 0.05 (OE biotech).The protein sample was digested, prepared for transition library construction, and scanned by mass spectrometry using the data-independent acquisition (DIA) mode by Orbitrap mass spectrometer . The MS data of the single-shot subject samples were used to generate a hybrid library for protein identification and quantitation using Spectronaut software Version 15.7 . All searches were performed against the human UniProt reference proteome of canonical and isoform sequences with 20,373 entries downloaded in March 2022. Searches used carbamidomethylation as fixed modification, and acetylation of the protein N-terminus as well as oxidation of methionines as variable modifications. The trypsin/P proteolytic cleavage rule was applied, permitting a maximum of two miscleavages and a peptide length of 7–52 amino acids. Protein intensities were normalized using the Local Normalization algorithm based on a local regression model . SpectraGenes that were simultaneously differentially expressed in serum and its exosomes with the same trend (both up-regulated or down-regulated) were obtained for subsequent analysis. They were named as co-DEmRNAs, co-DEmiRNAs, co-DElncRNAs, and co-DEcircRNAs.1 Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions, linking the genomic information with higher order functional information. The pathway enrichment analysis was used to find out the significant pathway of a list of genes using the KEGG database.2 According to the obtained miRNA-mRNA interaction, GO and KEGG enrichment analyses for co-DEmRNAs and target genes of co-DEmiRNAs were carried out using the enrichment analysis tool of Metascape.3The Gene Ontology (GO) is a structured and controlled vocabulary of terms, which are subdivided into 3 non-overlapping ontologies, Molecular Function, Biological Process and Cellular Component. GO enrichment analysis was performed to analyze the primary function of a list of genes using the GO database.4 an integrated public miRNA-target prediction database that includes the data from PITA, miRmap, miRanda, PicTar, and TargetScan. The predicted miRNA-mRNA pairs were then integrated with the data of co-DEmiRNAs and co-DEmRNAs to obtain their regulatory relationships.The interaction of miRNA-mRNA was predicted using the miRWalk 3.0,5 a website identified 1.5 million of RNA-RNA interactions through analyzing thousands of CLIP-seq and various high-throughput sequencing data. The screening criteria were number of supporting experiments low stringency R1, and the predicted lncRNA-miRNA and circRNA-miRNA pairs were integrated with the data of co-DElncRNAs and co-DEcircRNAs to obtain their regulatory relationships.The lncRNA-miRNA and circRNA-miRNA interaction prediction was performed using the ENCORI,p < 0.05.Using the matrix data of co-DElncRNAs, co-DEcircRNAs, and co-DEmRNAs, the Pearson correlation coefficients was calculated for each lncRNA-mRNA and circRNA-mRNA pair. A correlated test was then performed to find significant pairs with the threshold of | r| > 0.9 and The ceRNA network was constructed to discover the ceRNA mechanism based on co-DERNAs, including co-DElncRNAs, co-DEcircRNAs, co-DEmiRNAs, and co-DEmRNAs. Briefly, the Pearson Correlation Coefficient between matched miRNA-mRNA, lncRNA-miRNA, circRNA-miRNA, lncRNA-Mrna, and circRNA-mRNA was computed using R function cor.test (Hmisc and corplot) based on their expression data. The significant correlation pair was defined with a correlation value of more than 0.99. For a given lncRNA-mRNA or circRNA-mRNA pair, both of them were targeted by a common miRNA, and co-expressed negatively with it. Such a lncRNA-miRNA-mRNA or circRNA-miRNA-mRNA pair was identified as competing ceRNA triplets. The two complex networks were finally integrated, and the visualization of the ceRNA network was built by software Cytoscape Version 3.6.0.Based on the interactions of proteins in the KEGG database, global signal transduction network was generated to demonstrate the interaction among the DEPs, in order to select the key proteins with powerful ability to modulate others in the network. The visualization of PPI network was built by software Cytoscape Version 3.6.0. Briefly, to get the most closely related interaction pairs, the PPI score was set to 0.99 (high confidence). The CytoHubba plug-in Version 0.1 was used to analyze the network topology properties of the nodes, and obtain the significant ones by score ranking. The MCODE plug-in Version 2.0.2 was then used to analyze the most important clustering modules in the PPI network with a score threshold of more than 10.6 and the RNAdisease database,7 and selected the genes  that associated with neuropathology to ensure the diagnostic specificity. Their expression levels were further determined by low-throughput assays for blood samples from all 24 subjects in the cohort.The results of high-throughput assays on blood samples from the 8 subjects include 4 datasets: serum free RNAs, serum free proteins, exosomal RNAs and exosomal proteins. Multi-omics analysis was performed following the steps as below: (1) Obtained serum and exosomal differentially expressed indicators on both mRNA and protein level. They were analyzed as the first part of candidate CTE biomarkers . (2) Obtained the intersection of serum free DEPs and exosomal DEPs. The indicators in the two intersections were analyzed as the second part of candidate CTE biomarkers (CHL1 and CFB). (3) Screened out hub genes with the highest connectivity in the ceRNA network as the third part of candidate CTE biomarkers . (4) Screened out hub genes with the highest degree of link in the PPI network as the fourth part of candidate CTE biomarkers . (5) Manually search the function of above candidate biomarkers using the GeneCards databaseLow-throughput verification for potential protein biomarkers of CTE were performed using ELISA. The CHL1 concentration was determined by the ELISA kit  following the manufacturer’s instructions.Ct–ΔΔ method on each group. The primers used were as follows: GAPDH, GCCAAGGCTGTGGGCAAGGT (forward) and TCTCCAGGCGGCACGTCAGA (reverse); U6, CTCGCTT CGGCAGCACA (forward) and AACGCTTCACGAATTT GCGT (reverse); KIF2A, ATTTTCTCTCATTGACCTGGCTG (forward) and ACTCCTTGAGTGCTAAAAGGC (reverse); LIN7C, TGCCGCCACAGAAACTTCAG (forward) and TGATGTCCACCGTCTCATAAACA (reverse); hsa-miR-297, GCAGATGTATGTGTGCATGTG (forward) and AGGTCCAGTTTTTTTTTTTTTTTCAT (reverse); hsa-miR-1183, CACTGTAGGTGATGGTGAGA (forward) and AGTTTTTTTTTTTTTTTGCCCACT (reverse).Low-throughput verification for potential RNA biomarkers of CTE were performed using RT-PCR. Briefly, reverse transcription and PCR were performed using the Hairpin-it miRNA/mRNA RT-PCR Quantitation kit  with corresponding primers. GAPDH and U6 were used as the internal control for mRNA and miRNA quantification, respectively. All PCR reactions were performed using standard PCR conditions. The Ct value was detected by CFX Connect™ RT-PCR system , and the data were analyzed by means of 2t-test or Wilcoxon rank sum test as appropriate. Categorical data were expressed as number (percentage) and compared using the chi-square test. Statistical analyses for GO and KEGG enrichment analysis were performed using Fisher’s exact test. Pearson’s correlation test was utilized to calculate the correlation coefficients between hub genes in the PPI network. All statistical analyses were performed using SPSS Statistics Version 27.0 . A two-tailed p-value of less than 0.05 was considered to be statistically significant.The continuous variables were expressed as mean ± standard deviation, and compared using the Student’s Twelve pairs of gender- and age-matched rmTBI patients with healthy subjects were enrolled in this research, and their demographic characteristics are presented in The results of RNA microarray and proteomic sequencing for 4 pairs of gender- and age-matched CTE patients with healthy subjects were comprehensively analyzed, and the original data were uploaded as The co-DEmRNAs and co-DEmiRNAs were defined as mRNAs and miRNAs that were both up-regulated or down-regulated in serum and its exosomes of the 4 CTE patients, compared with healthy subjects. A functional enrichment analysis was performed for co-DEmRNAs and target genes of co-DEmiRNAs, and the top 10 GO and all KEGG pathway terms are shown in In terms of biological progress of GO analysis, the genes were significantly enriched in synaptic vesicle uncoating, protein localized to basolateral plasma membrane, protein depolymerization, synaptic vesicle endocytosis, presynaptic endocytosis, cellular protein complex disassembly, protein-containing complex disassembly, neurotransmitter secretion, cellular component disassembly, and positive regulation of hydrolase activity, most of which are associated with synaptic function. Regarding cellular component of GO analysis, the enriched terms included bicellular tight junction, postsynaptic density, asymmetric synapse, postsynaptic specialization, neuron to neuron synapse, presynapse, anchoring junction, adherens junction, postsynapse, and synapse part. The function of them are related to tight junction (important component of blood-brain barrier) and neurotransmitter. As to molecular function of GO analysis, peptide-aspartate beta-dioxygenase activity, L27 domain binding, structural constituent of muscle, oxidoreductase activity, clathrin binding, PDZ domain binding, dioxygenase activity, protein tyrosine phosphatase activity, electron transfer activity, and protein domain specific binding were enriched. For KEGG analysis, the most significantly enriched pathways were cardiac muscle contraction, transcriptional misregulation in cancer, calcium signaling pathway and endocytosis. Consequently, changes in the expression levels of co-DEmRNAs and target genes of co-DEmiRNAs in serum and exosomes may reflect altered function on synapse-mediated neurotransmitter transmission and blood-brain barrier permeability after rmTBI.Using the matrix data of co-DERNAs and online tools to predict their regulation relationship, 4 DElncRNAs were found to target 2 DEmiRNAs, which are able to bind 3 DEmRNAs. A ceRNA network was thus constructed according to the lncRNA-miRNA-mRNA triplets . Then, tThe PPI network of DEPs in serum and exosomes were constructed individually based on their interaction relationship in the KEGG database. As shown in p-values of less than 0.01) with all the other DEPs. In addition, GO and KEGG Enrichment Analyses were performed, which indicated that the genes were enriched in synapse pruning, cell junction disassembly, integrin binding complement activation, immune effector process, regulation of immune system process, and complement/coagulation cascades.Hub genes with more than 3 links in the PPI network of DEPs in serum, and those with more than 2 links in the PPI network of DEPs in exosomes were selected for the Pearson correlation analysis . We founThe candidate CTE biomarkers  were screened out through multi-omics analysis using Venn map  and funcPatients with CTE are characterized by progressive neurological disorders. Their clinical symptoms mainly include cognitive decline, behavioral change, emotional dysregulation and motor disturbance . The cogIn order to explore novel blood signatures to improve the diagnostic framework of CTE, we started the observational cohort study of blood transcriptomics and proteomics information as biomarkers of TES in 2021. In the present research, we collected blood samples from the first 12 pairs of rmTBI patients with healthy volunteers that had been recruited for the cohort. By high-throughput multi-omics screening, we found that co-DEmRNAs, target genes of co-DEmiRNAs and hub genes of the PPI network in serum and exosomes were significantly enriched in synapse-mediated neurotransmitter transmission and blood-brain barrier permeability. It is worth noting that chronic synaptic adaptation and reorganization, as well as blood-brain barrier breakdown and repair are indeed important neuropathological changes in CTE, and associated with the cognitive dysfunction . On thisCHL1 protein is a member of the L1 gene family of neural cell adhesion molecules. It is a neural recognition molecule that involves in L1CAM interactions, nervous system development and synaptic plasticity. Specifically, it could promote neurite outgrowth of hippocampal neurons, suppress neuronal cell death, and regulate cell migration in nerve regeneration and cortical development. CHL1 also plays a role in positioning of pyramidal neurons, regulating the number of interneurons and the efficacy of GABAergic synapses, and potentiating integrin-dependent cell migration toward extracellular matrix proteins . These fThe verified biomarkers are expected to contribute to CTE diagnosis. However, several limitations, especially the small cohort size should be taken into account when interpreting the results. First, according to the provisional levels of certainty for CTE pathology proposed by the expert consensus, the patients we recruited were classified as 1 probable CTE, 3 possible CTE and 8 suggested of CTE or only with rmTBI history. Due to the low incidence of the disease, we failed to follow the opinions of expert consensus, in which cohorts of patients with probable CTE as primary subjects are recommended for the biomarker study. It may lead to a decrease in the specificity of the biomarkers we found. Second, the small sample size for high-throughput sequencing and low-throughput verification assays may result in the screened differentially expressed RNAs and proteins cannot well reveal characteristics of the whole CTE population due to individual differences. Therefore, we did not depict Receiver-Operating Characteristic curve to show the outcome prediction performance of each potential biomarker, or compare with that of classic neurodegenerative biomarkers, in order to avoid their misuse in future research and clinical diagnosis.ClinicalTrials.gov Identifier: NCT04928534). It provides effective methodologies for managing subsequent large-scale cohort study and analyzing the multi-omics big data. Although the potential biomarkers for CTE we found are not recommended to be directly applied to clinical use, they contribute to further studies on establishing a novel set of CTE diagnostic signatures with classic neurodegenerative indicators. As specified in the trial registration, our research team will continue to develop a CTE cohort including 120 strictly matched rmTBI patients and healthy subjects, aiming to update the consensus diagnostic criteria by incorporating solid evidence of the in vivo biomarkers.In conclusion, this research is a pilot study of our ongoing cohort study  and the ProteomeXchange database (Project ID: PXD037637). The processed matrix data of high-throughput assays can be found in the The RNA microarray and proteomic sequencing datasets for this study can be found in the ArrayExpress database . The patients/participants provided their written informed consent to participate in this study.XG and PL were responsible to conception and design of the study. XG developed the method, performed data visualization, statistical analysis, and wrote the manuscript. ML, MG, and LZ conducted laboratory examinations. SZ, JQ, LC, WL, YW, JY, ZY, and WT contributed to cohort recruitment. FC provided methodological supports. PL reviewed the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.


Introduction: Various biomarkers are used when evaluating the hospitalization needs of patients diagnosed with Coronavirus disease (COVID-19). Ischemia-modified albumin (IMA) is a biomarker that causes blood levels to increase as a result of hypoxia and acidosis. We think that an increase in IMA in the blood may be caused by hypoxia stemming from lung damage. This study aimed to compare the mean/median of the blood IMA value in patients with pneumonia due to COVID-19 infection with a control group.Methods: The case group included patients with COVID-19 pneumonia detected by lung imaging and a positive COVID test. Demographic information of the case group, the severity of pneumonia, and their PCR test results were recorded in the data set.Findings: A total of 150 people, 90 of whom were in the case group and 60 of whom were in the control group, participated in the study. No statistically significant differences were found between the blood IMA levels of the case group and the control group. When the blood IMA levels of the case group were compared according to pneumonia severity, no statistically significant differences were found between the mild-moderate and severe pneumonia groups.Conclusion: Blood IMA levels are not a diagnostic biomarker for patients with COVID-19 pneumonia and are not helpful in predicting the severity of pneumonia. Coronavirus disease COVID-19), which started in Wuhan, China, in 2019, poses a high risk of transmission, has required hospitalization of patients exceeding hospital capacity in many countries, and can result in mortality [9, which Prognostic markers have an important role in determining the hospitalization needs of patients . Many st2) is released from proteins and peptides. Cu2 binds to the N-terminal region of albumin. Free oxygen radicals damage the Cu2 binding site of albumin, and IMA is formed [Ischemia-modified albumin (IMA) is a negatively charged globular protein at physiological pH . Its blos formed . PulmonaThis study began after receiving the approval of the ethics committee . An informed consent form was obtained from the control group individuals, patients, and patients’ first-degree relatives if the participating patients’ level of consciousness was not appropriate to give consent.Clinical evaluationPatient GroupsPatients who had symptoms of COVID-19 pneumonia, who were diagnosed with COVID-19 pneumonia, or who had a positive test for COVID-19 according to a reverse transcription polymerase chain reaction (RT-PCR) test administered through nasal swab samples were admitted to the study. The clinical diagnosis and pneumonia severity staging of the patients were made according to the guidelines of the COVID-19 diagnosis and treatment of the Turkish Ministry of Health [Mild Moderate Pneumonia2 level >90% in room air, and mild to moderate pneumonia findings on chest X-ray or computed tomography (CT).It was defined as patients with symptoms such as fever, muscle/joint pains, cough and sore throat, respiratory rate <30/minute, SpOSevere Pneumonia2 level below 90% in room air.It was defined as patients with symptoms such as muscle/joint pains, fever, sore throat, and cough, and with clinical findings such as bilateral diffuse pneumonia on chest X-ray or tomography, tachypnea (30/minute), and an SpOControl groupHealthy adults in the same sex and age group (±10) as the patients in the case group were included in the control group.Inclusion CriteriaInclusion criteria for the patient group included being diagnosed with COVID-19 pneumonia in the emergency department and being at least 18 years old. As for the control group, the criteria included no history of known disease, no use of any medications, and no recent or present infectious symptoms.Exclusion CriteriaPatients who had a serum albumin level below 3 g/dl and above 5.5 g/dl and who were diagnosed with acute ischemic heart disease/myocardial infarction, trauma, pulmonary embolism, mesenteric ischemia, peripheral vascular disease, acute ischemic cerebravascular disease, muscle diseases, or liver diseases and who did not give written consent were excluded from the study.Blood SamplesThe blood samples taken at the time of admission to the emergency department were centrifuged , their serum was separated, and the serum was stored at −80 °C to be studied.IMA Level MeasurementSerum IMA levels were measured using commercially available ELISA kits  per the manufacturer’s protocols.Statistical analysisThe SPSS 22.0 Windows program was used for the statistical analysis. Kolmogorov-Smirnov test was used for testing normality distribution. Mann Whitney U tests were conducted to compare two non-parametric, independent groups. p<0.05 level was accepted as the alpha significance level.A total of 150 people , participated in the study. Thirty-six (40%) people in the case group and 27 (45%) people in the control group were female. The mean ages of the case group and controls were 66.1±14.7 and 59.1±15.5 years, respectively.The median serum IMA level was 5.1 (3.4-7.9) IU/mL in the COVID-19 patient group, while it was found to be 4.6 (3.32-7.07) IU/mL in the control group. No statistically significant differences were found between the blood IMA levels of the case group and the controls (p=0.446)  Table .The pulmonary involvement of COVID-19 patients has been explained by different mechanisms. Although they share a single etiology (SARS-CoV-2), these severely hypoxemic patients can be quite different from one another . Viral iIn another study examining perfusion changes in patients with COVID-19 pneumonia, three main findings were obtained, including increased perfusion proximal to areas of lung opacity; decreased peripheral perfusion areas corresponding to peripheral lung opacities; and increased perfusion halo consolidation surrounding peripheral areas. These perfusion abnormalities, combined with pulmonary vascular enlargement, suggest intrapulmonary shunting towards areas of impaired gas exchange, resulting in clinical hypoxia and worsening ventilation-perfusion mismatch. Although hypo-perfused peripheral opacities are also seen in pulmonary embolism and pulmonary infarction, as in pulmonary embolism or pulmonary infarction, segmental perfusion increase is not observed in pulmonary opacities in COVID-19 disease. Therefore, opacities seen in COVID-19 disease are stated as atypical .This study found no differences in the blood IMA levels of patients with mild-moderate and severe COVID-19 pneumonia. Blood IMA levels may not have increased in COVID-19 patients due to a number of factors such as pulmonary involvement of COVID-19 patients ranging from mild to severe; complete obstruction due to ischemic process; hypoperfusion and thrombus were not in the foreground; interstitial pulmonary edema as a result of increased lung permeability due to the inflammatory process; worsening of this condition with intrapulmonary shunt, and pulmonary embolism; and different characteristics from perfusion abnormalities were exhibited.A study evaluating oxidative stress biomarkers stated that IMA level predicted severity and intensive care hospitalization in COVID-19 patients . In the In another study, it was stated that IMA levels were higher in the early phase of COVID-19 than in the acute phase . One of In our study, blood IMA levels are not a diagnostic biomarker for patients with COVID-19 pneumonia and are not helpful in predicting the severity of pneumonia. We think that it is important to classify the COVID-19 mild-moderate and severe groups and on which day the serum IMA level is studied after the symptoms of COVID-19.We think that studies with larger samples and comparing COVID-19 subgroups with IMA and other biomarkers are needed. We think that meta-analysis studies can be done by evaluating according to COVID severity groups and whether there is an early phase or not.


The Family Nurse Partnership (FNP) is a specialist home-visiting programme for first-time teenage mothers. Developed in the US, short-term outcomes (by age 2 years) were established in England in the Building Blocks trial. We used routine data  linked to our trial cohort to assess longer-term impact.Mothers recruited to the trial and their first-born children were linked to health , education/social care  data in England up to age 7-years. Analysis of data within in a trusted-research environment assessed programme impact upon child maltreatment, child development/educational and maternal life course outcomes when compared to usually provided health and social care support alone. Our primary outcome was child in need registration. Planned sub-group analysis included differential effects by maternal age, deprivation level, care experience and for child outcomes, sex.Match rates for 1547 children were 97.4% (NPD) and 98.3% (HES). We found no difference between trial arms in proportion of children assessed as in need (adjusted odds ratio (aOR) OR:0.98, 95% confidence interval (CI): 0.74 to 1.31). Aside from a longer duration in care for children in the usual care arm (two months), there were no other differences in maltreatment outcomes. Children in the FNP arm were more likely to achieve a good level of development at reception age at age 4-5 years  and, after adjusting for month of birth, to reach the expected standard in reading at Key Stage 1 at age around 7 years .We found programme improvements for child development/educational achievement but not for child maltreatment outcomes. Additional sub-group analysis revealed some evidence of the programme benefiting mothers with greater baseline vulnerability and boys, consistent with previous trials. The study benefits from the linkage of administrative data to a previously randomised trial cohort.


Chronic liver diseases commonly cause severe scarring of the liver (cirrhosis) and liver cancer. The eventual progression of this scarring process to liver cancer is influenced by a variety of factors, including inflammatory cytokines (soluble mediators of cell communication). In order to increase our understanding of these mediators we studied them in the blood of patients with hepatitis B (HBV), hepatitis C (HCV), alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) patients with liver cirrhosis. We studied more than a 100 cytokines in up to 400 patients. We discovered that patients with cirrhosis had a vast upregulation of a wide variety of immune mediators, which stimulated inflammation and were linked with tumor-promoting roles. In contrast to prevailing assumptions, each type of underlying liver disease exhibited a unique immune mediator profile in blood, which is likely to impact how we will study these markers in the future. Patients with HBV cirrhosis had the largest number of upregulated inflammation-inducing mediators, compared to HCV, ALD and NAFLD. Next, we related blood immune mediator levels with liver cancer. To do so, we studied cytokine profiles in patients with small tumors, thus, those qualified for surgical curative strategies. We observed unique sets of cytokines in serum in each liver cancer group, indicating a role for these mediators in detecting liver cancer. In conclusion, our findings underscore the impact of different liver diseases on circulating immune mediators. Future studies that aim to study them as diagnostic tools will need to correct for this important effect accordingly.p < 0.0001), including those with pro-oncogenic features, when compared to healthy individuals. In contrast to prevailing assumptions, each etiological cause of cirrhosis exhibited a unique cytokine profile in blood. Regardless of antiviral therapy, HBV cirrhosis patients had the largest number of upregulated proinflammatory mediators, compared to HCV, ALD and NAFLD (p < 0.0001). To further evaluate the etiology-dependent modulation of cytokine response in relation to liver cancer, we studied cytokine profiles in early-stage HCC patients strictly stratified by underlying liver disease. We observed unique sets of differentially expressed cytokines in each cohort of early-stage HCC patients of different cirrhosis etiologies. Conclusions: Our findings, therefore, underscore the importance of stratification by the etiological cause of liver cirrhosis in immune-based studies.Background and Aims: Chronic liver disease—from any etiology—can progress to fibrosis, cirrhosis and hepatocellular carcinoma (HCC). The progression of liver cirrhosis to the end stages of disease is influenced by a variety of factors, including inflammatory cytokines. We pursued a study of cytokine-mediated inflammatory responses in hepatitis B (HBV), hepatitis C (HCV), alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) patients with liver cirrhosis. Methods: Immune profiles were determined through the serum multiplex profiling of >100 cytokines in a 188 cirrhotic patients, 35 healthy controls and 196 early-stage HCC patients. Results: Patients with liver cirrhosis exhibited a vast upregulation of proinflammatory cytokines ( Chronic liver disease is a common cause of global mortality. The primary causes of liver injury in patients are alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD) and chronic viral infections with hepatitis C (HCV) or hepatitis B (HBV). These chronic injuries lead to liver fibrosis or cirrhosis and place patients at high risk of developing hepatocellular carcinoma (HCC) . The immA retrospective cohort was established with cirrhosis and HCC patients visiting Erasmus Medical Center between 1 January 2009 and 31 December 2020. Patients were identified using a prospectively maintained pathology database and health care insurance registries.®). Liver cirrhosis patients secondary to chronic infections with HCV or HBV, alcohol consumption and NAFLD, with a WHO performance score of 0, Child–Pugh A or B, and no history of HCC since blood collection, served as our cirrhosis study cohort and served as controls for HCC development. Chronic HBV patients with cirrhosis were serum HBV surface antigen (HBsAg)-positive for more than 6 months, and both nucleoside analog treated and untreated patients were included. Chronic HCV patients were anti-HCV positive and HCV RNA-positive and were not on treatment with direct acting antivirals. Patients with alcoholic liver disease had persistent histopathological steatohepatitis and a daily intake of >40 g ethanol for men and >30 g for women for more than 10 years, in the absence of other triggers of liver damage. Patients with NAFLD had persistent histopathological liver steatosis and lacked any evidence of ongoing or recent consumption of significant quantities of alcohol, medication or other inducers of steatosis. Cases were excluded if they showed evidence of decompensated cirrhosis; infection with a second hepatitis virus, hepatitis D virus, hepatitis E virus or human immunodeficiency virus; presence of auto-immune liver disease, hemochromatosis, Wilson’s disease, antitrypsin alpha-1 deficiency, primary biliary cholangitis, primary sclerosing cholangitis, documented clinical history of immunomodulatory drugs, other malignancies; or with ageing-associated debilitating cardiovascular diseases, autoimmune diseases and hyperplastic syndromes. A complete medical history was obtained for each patient, including antiviral therapy, alcohol consumption, and signs of type II diabetes. Data on smoking history was not consistently documented in the electronic health records and, therefore, not registered in this study.All participants had cirrhosis, confirmed by biopsy (Metavir) or liver transient elastography  staging system was evaluated on all patients in the database, and only patients with early-stage disease, i.e., BCLC stage 0 and stage A and with a serum sample available in our biobank were included. Patients with liver cirrhosis and HCC, secondary to chronic infections with HCV or HBV, alcohol consumption and NAFLD were compared in terms of clinical characteristics and the exploratory analytes.Archived biobank serum of patients was collected during visits at the outpatient and isolation was done under aseptic conditions within clean room facilities, in accordance with Good Manufacturing Practice regulations.All patient samples and data used in this study were collected in the context of routine clinical patient care and the Institutional Review Board of the Erasmus Medical Center in Rotterdam approved of the use of these data and samples (METC-2017-1140 and MEC-2020-0383). The biobanked sera, and the subsequent use of these data for the study of circulating immune profiles was permitted by the board, which also waived the need for informed consent.Circulating cytokines were measured using the Bio-Plex platform, specifically the Bio-Plex human cytokine 47-Plex panel; the Bio-Plex human chemokine 40-Plex panel; and Single-Plex kits for pentraxin-3, MMP-1, MMP-2 and IL-6Rα . In total, 93 experimental analytes were tested in 4 different panels. Since 19 analytes were present in two or more panels, our analysis was conducted with 74 analytes.The multiplex protein assays were performed, as described by the manufacturer. In short, cytokine standards were determined in duplicate. Serum samples were diluted four times with sample diluent. Fifty µL anti-cytokine conjugated beads were plated in a 96-well; washed twice; and 50 µL cytokine standards, kit control or serum samples were added and incubated for 30 min on a shaker. Plates were washed three times with 100 µL Bio-Plex wash buffer, then 25 µL detection antibody was added and plates were incubated for 30 min on a shaker. Next, the wash steps were repeated and 50 µL streptavidin-phycoerythrin was added. Finally, the plates were incubated for 10 min and washed three times, and the beads were suspended in Bio-Plex assay buffer. Data were acquired on a validated and calibrated Bio-Plex 200 system (Bio-Rad) by measuring the fluorescent signal of the fluorescent reporters. The Bio-Plex Manager 6.2 software (Bio-Rad) was used for data analysis. The standard curves were calculated using five parameter logistic regression analysis with default automated weighing. The highest and lowest reliable values of the standard curve of every individual analyte was selected as lower and upper limits of quantification. Undetectable values were substituted by dividing the lower limit by two.To assure reproducibility of the measurements between different batches, sera of healthy controls and HCV patients were pooled, aliquoted, and included at different positions on each assay plate. In addition, a technical replicate provided by the manufacturer was also included on each plate. The coefficient of variation (%CV) was calculated for each as [SD/mean] × 100, and five markers with %CV > 30 were excluded . The limit of detection of the eligible analytes are presented in p < 0.05 was considered statistically significant. R studio (version 1.4.1717) and GraphPad Prism (version 8) were used to perform statistical analyses.Serum biomarker levels across cirrhotic patients, HCC patients and healthy controls were statistically tested. The Mann–Whitney Wilcoxon Test, Kruskall–Wallis test, Chi-square or the Pearson correlation were applied, when appropriate. False discovery rate was determined using the two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli with Q = 1%. Multiple comparisons among the cirrhotic patients, HCC patients and healthy individuals were corrected using the Holm–Bonferroni or Bonferroni method. All statistical tests were two-sided and In order to study the cytokine milieu in cirrhosis, we conducted multiplex protein assays on the sera of 188 patients with compensated cirrhosis secondary to HBV or HCV infections, NAFLD or ALD and compared them to sera from 35 healthy individuals . The anaSince we demonstrated that the serum cytokine levels differed between samples from cirrhotic patient and healthy individuals, we decided to stratify the cirrhotic samples for different etiological causes . Heat map analysis identified highly distinctive profiles in cytokine expression between groups, with 47 significantly expressed cytokines in one of the cirrhosis etiologies, and at least four immunological profiles were evidently observed .Upon detailed assessment, cytokine levels and cirrhosis etiology revealed that HBV-cirrhosis—regardless of antiviral therapy—had a 3-fold increase in IFN-γ, TRAIL and CXCL1 (GRO-α) levels and up to 3-fold decrease in MMP-2, CXCL12, IL2RA, IL-6Rα, CCL2 (MCP1) and CCL21 (6kine) levels B. HCV-ciOurselves and others have previously reported on specific circulating cytokine profiles that may be indicative of the presence of HCC at a very early stage of its development, suggesting a potential role for blood immune mediators as biomarkers ,10,11. HLiver cirrhosis is an inflammation-driven disease and an important cause of global morbidity and mortality. Here, we studied in detail the cytokine-based immune response in patients with HBV-, HCV-, ALD-, and NAFLD-associated liver cirrhosis, as well as the differential variation of these circulating cytokine signatures in patients with early-stage HCC. We found that liver cirrhosis had a profound impact on the circulating immune profile and was associated with a wide repertoire of pro-inflammatory and HCC-promoting cytokines. We observed etiology-specific cytokine responses with up to 47 significantly augmented cytokines in HBV, HCV, ALD or NAFLD. In order to study the impact of these findings, we also studied the cytokine-based immune response in liver cirrhosis patients with early-stage HCC patients. Following strict stratification, we confirmed the important immunologic role of the etiological cause of cirrhosis, as we observed etiology-specific immune profiles that strongly correlated with the presence of early-stage HCC.In recent years, elegant immunological studies found that cirrhosis etiology can influence local tumor immune responses ,12. ThesMore than 90% of HCC cases will develop in a background of liver cirrhosis . TherefoThrough a combination of highly sensitive and quantitative multiplex-based assays, we expose that cytokines are differentially up- or down-regulated in patients with early-stage HCC, as compared to cirrhotic patients, depending on their cause of liver disease being HBV, HCV, ALD or NALFD. The function of these markers in early-stage HCC is currently unclear and our study is not powered or designed to assess them as biomarkers. However, we provide important clues to the potential differential expression of these analytes related to underlying liver disease. Taken together, by studying circulating cytokines strictly stratified by underlying liver disease, our study provides important clues into the immunology of liver cirrhosis and the etiological cause of cirrhosis etiology. This is important in the context of recent advances in immune-based therapies and predictive biomarkers in patients with cirrhosis and HCC, and our data now provide a rationale for stratification of patients with HCC and cirrhosis according to the underlying etiology of liver disease.Liver cirrhosis has a profound impact on the levels of circulating immune mediators and associates with a wide repertoire of pro-inflammatory and HCC-promoting cytokines. Among the patients with liver cirrhosis, we observed significantly enhanced circulating cytokine levels in HBV, HCV, ALD and NAFLD, which underlines the impact of cirrhosis etiology on the circulating immune profile. We also studied the cytokine-based immune response in liver cirrhosis patients with early-stage HCC patients. Following strict stratification, we confirmed the important immunologic consequences of the etiological cause of cirrhosis, as etiology-specific immune profiles were observed that strongly correlated with the presence of early-stage HCC. Future prospective studies will have to unravel whether monitoring the circulating immune response to predict the development of HCC and cirrhosis etiology deserve more attention in studies that aim to unravel the mysteries of the immune system in fibrosis and HCC.


Intraoperative hypotension is associated with postoperative complications. However, in the majority of surgical patients, blood pressure (BP) is measured intermittently with a non-invasive cuff around the upper arm (NIBP-arm). We hypothesized that NIBP-arm, compared with a non-invasive continuous alternative, would result in missed events and in delayed recognition of hypotensive events. This was a sub-study of a previously published cohort study in adult patients undergoing surgery. The detection of hypotension  was compared using two non-invasive methods; intermittent oscillometric NIBP-arm versus continuous NIBP measured with a finger cuff (cNIBP-finger) . cNIBP-finger was used as the reference standard. Out of 350 patients, 268 patients (77%) had one or more hypotensive events during surgery. Out of the 286 patients, 72 (27%) had one or more missed hypotensive events. The majority of hypotensive events (92%) were detected with NIBP-arm, but were recognized at a median of 1.2 (0.6–2.2) minutes later. Intermittent BP monitoring resulted in missed hypotensive events and the hypotensive events that were detected were recognized with a delay. This study highlights the advantage of continuous monitoring. Future studies are needed to understand the effect on patient outcomes. An association between intraoperative hypotension and postoperative renal insufficiency, myocardial injury and increased mortality in non-cardiac surgical patients has been reported in numerous cohort studies ,2,3,4. RIntraoperatively, BP can be monitored continuously or intermittently. The current standard for continuous BP monitoring is invasively via cannulation of the radial artery. Placement of an arterial cannula poses a small risk of developing nerve damage, infection, thrombus formation or a pseudoaneurysm ,9,10. A In the vast majority of surgical patients, however, BP is monitored intermittently using an oscillometric method with a non-invasive cuff around the upper arm (NIBP-arm) . On averOur primary objective was to determine whether use of intermittent (NIBP-arm) compared with continuous (cNIBP-finger) BP monitoring results in missed hypotensive events. This is not a validation study; we purely studied the effect of continuous monitoring. Our second objective was to assess the delay time between continuous and intermittent BP monitoring in the recognition of hypotensive events. We hypothesize that intermittent BP monitoring would result in missed hypotensive events and would result in delayed recognition of hypotensive events. In an exploratory manner, we assessed the effect of NIBP-arm sample interval on the number of missed events and delay time.The present study describes a sub-study from a prior published prospective cohort study . The stuFor this sub-study, those patients receiving NIBP-arm as standard care  and experiencing at least one hypotensive event during surgery were selected see .Prior to induction, a cNIBP finger cuff  was connected to the patient and the heart reference sensor was zeroed at heart level. The Nexfin measured non-invasive finger BP continuously using the volume clamp method. The cuff pressure varied dynamically to keep the volume of the finger arteries under the cuff constant throughout the cardiac cycle ,21. The NIBP-arm was measured with a BP cuff around the upper arm . The NIBP-arm cuff was inflated intermittently and the interval was chosen by the treating anesthesiologist. cNIBP-finger was connected contralateral from NIBP-arm to allow continuous monitoring. Per institutional practice, BP was treated when MAP dropped below 65 mmHg.cNIBP-finger data were extracted from the Nexfin device and NIBP-arm data were extracted from the electronical medical records system . Patient data were collected and de-identified.No sample size analysis was performed as data for the present sub-study were derived from an earlier published prospective cohort study and no inferential statistics were performed . The resFor the analysis of this study, cNIBP-finger arterial waveform data after the start of surgery  were included. Nexfin samples blood pressure at 200 Hz. Data was extracted from the device after internal online beat-detection was completed. Values for MAP were averaged for every 20 s. Data points during a period of poor or noisy signal quality were excluded from further analyses .Hypotension was defined as a cNIBP-finger MAP below 65 mmHg for at least one minute . cNIBP-fNIBP-arm intermittent data points were interpolated to allow time synchronization between cNIBP-finger and NIBP-arm . All patPrimary endpoint: missed hypotensive events were calculated as cNIBP-finger hypotensive events (MAP below 65 mmHg for more than one minute) not recognized by NIBP-arm. A missed hypotensive event based on >5 mmHg offset between cNIBP-finger and NIBP-arm was not counted as a true missed event.Because NIBP-arm provides intermittent data, one NIBP-arm data point of a MAP below 65 mmHg was sufficient to count as a recognized event. For the missed hypotensive events, the lowest cNIBP-finger MAP value reached and the average cNIBP-finger MAP for the hypotensive events were reported. The average cNIBP-finger MAP was calculated by adding all blood pressure values during the hypotensive event divided by the number of data points. For example, for a hypotensive event with MAP 62, 60, 56, 54, 60, 64 mmHg, the average MAP would be 59 mmHg  and the lowest MAP would be 54 mmHg.Secondary endpoint: the time from recognition of a hypotensive event with cNIBP-finger to recognition with NIBP-arm was presented as the delay in detection time.Exploratively, the missed events and delay times per NIBP-arm sample interval subgroup were reported. The NIBP-arm sample interval was the sample interval  most frequently chosen during surgery. As subgroups had different numbers of patients, the missed events per subgroup had to be corrected to allow for comparison. We presented the number of missed hypotensive events as a percentage of the number of patients per subgroup.Data analyses were performed with MATLAB and SPSS. Continuous data were presented as median with interquartile range (IQR), or mean with standard deviation (SD) when normally distributed. Categorical data were given as frequencies with percentages.In the database consisting of 507 patients, a median of 2.3% of the data [IQR 0.6–9.7], which had poor signal quality, was removed. For this sub-study, 404 out of 507 patients receiving NIBP-arm as standard care (and the blinded cNIBP-finger monitoring for study purposes) were selected . The othThe median age was 56 years (IQR 43–66) and 54% of the patients were female. The study group was heterogenous in terms of types of surgeries. The majority of anesthesiologists set the NIBP-arm interval at 3 min (43%), followed by 2 min (28%) and 5 min (20%) see .In 268 patients, 1006 total hypotensive events were recognized with cNIBP-finger, whereas 80 (8%) of these events were missed by NIBP-arm see . The 80 The median delay time between the cNIBP-finger and NIBP-arm was 1.2 min (0.6–2.2).The fraction of missed events, corrected for the number of patients per group, did increase with increasing sample intervals up to five minutes, but paradoxically showed a decrease at a sample interval of five minutes or higher see . The delIntraoperatively, intermittent BP monitoring resulted in one or more missed hypotensive events in 27% of the patients. The majority of hypotensive events were detected with intermittent BP monitoring; however, hypotensive events were recognized with a median delay time exceeding one minute. The majority of anesthesiologists measure NIBP-arm every two, three or five minutes. Notably, it is not common to measure NIBP-arm every four minutes.As expected, the delay time between recognition of a hypotensive event increased when the sample interval increased. Paradoxically, more missed hypotensive events were recognized in patients where NIBP-arm was measured every three minutes compared with those with a five-minute sample interval. Selection bias might be the underlying cause of this finding, as for hemodynamically more stable patients the measurement interval is more often set at 5 min. Moreover, the small subgroups in these exploratory analyses might also explain this observation.This study adds to previous work demonstrating that continuous BP monitoring reduces intraoperative hypotension ,26,27. HThe continuous non-invasive device we used in this study has substantial costs. It requires an extra monitor system in the operating room and, contrary to NIBP-arm, a new finger BP cuff is required for every patient . A studyThis study has some limitations. First, to answer our study question we had to use two different methods to measure BP: the current oscillometric standard (NIBP-arm) and a continuous alternative (NIBP-finger) which utilizes the arterial pressure waveform ,30. AlthSecond, cNIBP-finger was connected contralaterally from NIBP-arm to allow continuous monitoring. A previous study demonstrated no relevant cNIBP measurement differences between contralateral side measurements .Third, the 8% missed events in the present study were in between two intermittent BP measurements. As this was not an intervention trial, we do not know if these hypotensive events resolved with or without treatment. The median minimal missed MAP during those missed episodes was 60 mmHg, which is generally considered mild hypotension. However, evidence that intraoperative hypotension is hazardous is increasing and not detecting those hypotensive events in patients could lead to a false sense of safety .Fourth, we took the cNIBP-finger as the reference standard in this study, and we calculated hypotension endpoints (such as TWA) for the continuous BP monitoring only. Since NIBP-arm measurements are intermittent we were not able to reliably calculate a true TWA for NIBP-arm. An additional disadvantage of the NIBP-arm is that is does not provide an arterial waveform and thus does not allow for pulse wave analysis. Pulse wave analysis can provide hemodynamic variables such as cardiac output (CO) and stroke volume variation (SVV) to assess the underlying cause of hypotension .Fifth, in this study a hypotensive event was defined as a MAP below 65 mmHg for more than one minute in line with our previous studies ,24,25. TSix, the current study is a sub-study of a previously published paper . As suchSeven, although the literature regarding the hazardousness of intraoperative hypotension is increasing, evidence is mostly based on associations reported in cohort studies. Randomized clinical trials demonstrating a causal effect between hypotension and worse postoperative outcome are sparse ,6. FuturIn this single-center intraoperative cohort study, intermittent BP monitoring resulted in one or more missed events in 72 out of 268 patients. The majority of hypotensive events (92%) were detected with intermittent BP monitoring but were recognized at a median of 1.2 min later. As even short durations of hypotension could be hazardous, continuous monitoring might be preferred. Future studies are needed to determine the effect of continuous BP monitoring on patient outcomes and to assess cost-efficiency.


Despite microbiological evidence, the empirical carbapenems were continued for a median (interquartile range (IQR)) of seven (5–8) days. This implies the need for a rapid diagnostic assay on direct specimens, together with comprehensive antimicrobial stewardship (AMS) discourse with intensivists to address this issue.Excessive antibiotic consumption is still common among critically ill patients admitted to intensive care units (ICU), especially during the coronavirus disease 2019 (COVID-19) period. Moreover, information regarding antimicrobial consumption among ICUs in South-East Asia remains scarce and limited. This study aims to determine antibiotics utilization in ICUs by measuring antibiotics consumption over the past six years (2016–2021) and specifically evaluating carbapenems prescribed in a COVID-19 ICU and a general intensive care unit (GICU) during the second year of the COVID-19 pandemic. (2) Methods: This is a retrospective cross-sectional observational analysis of antibiotics consumption and carbapenems prescriptions. Antibiotic utilization data were estimated using the WHO Defined Daily Doses (DDD). Carbapenems prescription information was extracted from the audits conducted by ward pharmacists. Patients who were prescribed carbapenems during their admission to COVID-19 ICU and GICU were included. Patients who passed away before being reviewed by the pharmacists were excluded. (3) Results: In general, antibiotics consumption increased markedly in the year 2021 when compared to previous years. Majority of carbapenems were prescribed empirically (86.8%). Comparing COVID-19 ICU and GICU, the reasons for empirical carbapenems therapy in COVID-19 ICU was predominantly for therapy escalation (64.7% COVID-19 ICU vs. 34% GICU,  Antibiotics have been prescribed in 70% of ICU patients due to the high prevalence of suspected or proven infection . Since tA systematic review of 38 studies consisting of 2715 ICU admissions found a similar frequency of antibiotics prescription at 71%. Yet, incidences of bacterial infections were reported in only 30.8% of the studies reviewed. Furthermore, 69.2% of the antibiotics prescribed were empirical without strong evidence of bacterial infection [Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacterales [Acinetobacter baumannii (58.5%) [Klebsiella pneumoniae [Antimicrobial resistance (AMR) has been a global health threat declared by World Health Organization (WHO) since 2015 . With thcterales ,12,13. T (58.5%) . Howevereumoniae . Hence, The usage of antibiotics was stable from 2016 through 2019. Comparing the year 2019 and year 2021, the total consumption of selected antibiotics  in both Considering the past six years, the total admissions had dropped since 2020 and were the lowest in 2021. However, the average length of stay per patient and total patient days in both ICUs were the longest in 2021 at 8.02 days and 6229 days, respectively . The aveIn 2021, a total of 605 carbapenems prescription requests were retrieved from the preauthorization forms, of which 159 prescriptions for 149 patients in the GICU and the COVID-19 ICU were eligible to be included . Meanwhip < 0.0001) and the median (IQR) length of ICU stay was longer (9 (5–15) days vs. 5 (3–10) days, p < 0.0001) in the COVID-19 ICU compared to the GICU.In 2021, there were 336 admissions to COVID-19 ICU and 231 admissions to GICU. The all-cause in-ICU mortality was higher  and patients’ age (median (IQR): 61 (46–68) years old vs. 60 (37–71) years old, p = 0.806) were comparable between COVID-19 ICU and GICU. Notably, GICU had significantly more patients colonized with resistant organisms who were prescribed carbapenems (p = 0.003)  with a median (IQR) age of 61 (44–69) years old. The male proportion  .p = 0.011). In the GICU, the majority were for healthcare-associated infections in the GICU   (79.9%), followed by healthcare-associated infection (type-2), and six prescriptions were for community-acquired infection (type-1). Most prescriptions were for nosocomial infections in COVID-19 ICU  see . Meropenp < 0.001). Empirical escalation to carbapenems was often prescribed for type-3 patients , and predominantly observed in COVID-19 ICU . The initiation of empirical therapy considering ESBL GNB risk was more frequent  in GICU. No association was found between reasons for empirical therapy with sites of infection. However, empirical therapy was more often intended for respiratory infections in the COVID-19 ICU (p = 0.017).More than half of the carbapenems were prescribed for escalation therapy, followed by the consideration of ESBL GNB risk . ConversOverall, out of 159 prescriptions, 101 (63.5%) had positive growth from cultures and 66 (41.5%) from blood cultures. The remaining 58 (36.5%) prescriptions had no growth, mixed growth, or candida species from respiratory samples or urine samples. Klebsiella pneumoniae and Klebsiella spp.  were frequently isolated, and the majority were ESBL producers. Two Klebsiella isolates were carbapenemases producers . All isolates were from type-2 and type-3 patients. Among 50 patients with rectal colonization, only eight patients (16.0%) had ESBL GNB bacteremia, compared to eight (8.9%) among 90 patients without colonization (p = 0.268). For the empirical prescriptions, the isolated organisms are listed in Acinetobacter spp. were frequently isolated, especially from COVID-19 ICU (p = 0.143), whereas Enterobacterales and Pseudomonas aeruginosa were isolated more often from GICU. Among definitive therapies, roducers . This wap = 0.015). Compared to GICU, a shorter duration of definitive therapy (p = 0.463), but a longer duration of empirical therapy (p = 0.654) was observed in COVID-19 ICU (p = 0.624).During the carbapenems therapy, 55 patients passed away before completing the treatment. Overall, the median (IQR) duration of carbapenems prescriptions was seven (5–8) days. The duration of definitive therapy was significantly longer than that of empirical therapy by one day  isolated from respiratory cultures, although the clinical significance is debatable, especially in COVID-19 infected critically ill patients [Following the CLSI revision in 2020 on the breakpoint and questioning the clinical value of polymyxin(s) ,23, empipatients . In contCarbapenems are broad-spectrum antibiotics belonging to the WATCH group under the WHO AWaRe classification, which should be the focus of stewardship . FurtherEnterobacterales, which were predominantly Klebsiella spp., similar to another tertiary hospital in the same region in Malaysia [To our knowledge, this was the first study to compare the carbapenems prescription pattern between the COVID-19 ICU and the GICU. Meropenem was the preferred agent used, as it had better activities on gram-negative bacteria and central nervous system penetration . This isMalaysia .The reasons for empirical prescription differed between the COVID-19 ICU and the GICU, associated with the distribution of the patient types. Rectal colonization with ESBL/MDR GNB was listed as a risk factor for infection ,35,36. TEmpirical carbapenems prescription was seen to be mainly driven by the intention to escalate therapy in the COVID-19 ICU and expectably more for respiratory infection. Diagnosing hospital or ventilator-acquired pneumonia was challenging in which overdiagnosis and overtreatment were commonly practiced . RespiraAcinetobacter spp. and Stenotrophomonas maltophilia are isolated, carbapenems might be inadequate. Carbapenem-resistant Acinetobacter baumannii (CRAb) was isolated in substantial proportion among positive cultures from the COVID-19 ICU, compared to the GICU. This was consistent with studies by Rangel et al. [During the pandemic period, both the COVID-19 ICU and the GICU experienced a shortage in staffing as they were managed by the same clinician teams. Apart from the uncertainty in COVID-19 management, overwhelming workload and exhaustion could cause clinicians to rely on broad-spectrum antibiotics in the dread of missing possible infecting microbes . Howeverl et al.  and Russl et al. , which nl et al. . A cohorl et al. . Althougl et al. . Referril et al. . It was When ESBL-producing organism(s) is isolated, carbapenem is the preferred choice as there is yet an alternative agent proven non-inferiority as in the case of piperacillin/tazobactam in bacteremia . While tNegative cultures are also common among the critically ill. It usually takes five days of blood culture incubation before confirming negative growth , during Antibiotic prescription is often executed by focusing on the immediate benefit instead of the potential detrimental effect in the distant future, which was described by Langford et al.  as cogniThe findings add to the existing paucity of information on exposure to broad-spectrum antibiotics in critical care areas in the South-East Asia region. We have demonstrated that the excessive antibiotic consumption is likely a result of unwarranted empirical use over a prolonged period and de-escalation is not performed promptly. Furthermore, we report the duration of therapy adjusted to indication, which provides more meaningful feedback to critical care clinicians for engagement in AMS initiatives. The same measurement can be adopted as a benchmarking across institutions and to design a standard tool of appropriateness assessment, which is currently lacking for critical care areas ,73. MDR There were many limitations due to the nature of the retrospective observational study based on a single center. Furthermore, the data were retrieved from datasets focusing on carbapenems prescriptions and might not provide the whole picture of antibiotic prescription practice. There could also be missing data that were likely lost due to limited physical access to the COVID-19 ICU. The indication and prescription duration for COVID-19 ICU was extracted during table round discussion and, therefore, subjected to recall bias though data availability and accuracy became better when documents were made available electronically. This study reflected the practice during the COVID-19 pandemic year, which might be different from the usual practice before that. In addition, therapy was evaluated according to the microbiological reports and did not assess the correlation with infection severity . HoweverThis current study provides a snapshot of the difference in the prescription practice and the microbiological profile among patients prescribed carbapenems between the COVID-19 ICU and the GICU. This is important as AMS strategies should cater to the circumstances under which broad-spectrum antibiotics are used . ICU couThis was a cross-sectional retrospective observational study conducted at the Hospital Canselor Tuanku Muhriz (HCTM), a 1054 bedded tertiary care university hospital located in Kuala Lumpur, Malaysia. This study included antibiotic prescriptions dispensed to ICU(s) during the period from 2016 to 2021. The unit used to be a 17-bedded medical/surgical ICU. In 2020, another ward was repurposed as COVID-19 ICU with only 3 beds initially. Following the worsening of the COVID-19 pandemic, the total ICUs’ capacity was configured as the COVID-19 ICU operated fully and expanded to be 22-bedded, while the GICU was 8-bedded since December 2020.The GICU was a mixed medical and surgical-based intensive care unit and the COVID-19 ICU was designed specifically for patients with confirmed COVID-19 infection. The triaging for admission was based on the admission and discharge protocol of the local institution, which was adapted from Malaysia National Protocol  and critThe GICU and COVID-19 ICU were primarily managed by clinicians of specialty in anesthesiology and intensive care. One ICU pharmacist was assigned to deliver pharmaceutical care service by participating in the daily handover rounds/discussions with a team remotely for COVID-19 ICU and performing bedside reviews for GICU. Medications were prescribed by medical officers on duty in both ICUs. ® 2 system . Antibiotic susceptibility testings (AST) were performed using the Kirby–Bauer disk diffusion method and results were interpreted according to Clinical and Laboratory Standard Institute (CLSI) guidelines [The ICUs practiced a routine infection control measure of collecting nasal and rectal swabs from newly admitted patients. All microbiological investigations were done by an in-house microbiological diagnostic laboratory service. Organisms were identified by automated VITEKidelines .® to initiate the dispensing process based on the unit of use system by the pharmacy. Meanwhile, the administration of antibiotic(s) was manually documented using a paper-based prescription with columns for prescribers to note the indication of the antibiotic as empirical, definitive, or prophylaxis, and columns for administration by nurses for up to 7 days. Both electronic and manual prescriptions were renewed if the duration of antibiotic was beyond 7 days. Antibiotics prescriptions were guided by the national ICU antimicrobial prescribing guide [Antibiotics were electronically prescribed using the hospital electronic prescription system Mediprong guide  and locang guide , as COVIng guide . AntibioData on antibiotics consumption were extracted from the manually recorded dispensing documents from the pharmacy department. The cumulative admissions and patient days data were acquired from the hospital department of health information. Prescriptions of carbapenems were extracted from antibiotics preauthorization forms and carbapenems monitoring datasets in the pharmacy department. Microbiological reports were accessed using the hospital’s online microbiological reports system (OMS). The duration of carbapenems therapy was calculated by subtracting the date of initiation from the date of completion and adjusted by adding one day. All carbapenems prescriptions for patients admitted to COVID-19 ICU and GICU wards during 2021 were included. Carbapenems prescriptions of patient(s) who died or were transferred out before pharmacist review were excluded due to incomplete data. Carbapenems courses during which the patient(s) died before doctors’ order to stop/complete therapy were excluded from the evaluation of therapy duration. With reference to WHO methodology , the DDDAntibiotic usage before the pandemic was estimated for the year 2016 to 2019. The antibiotic usage during the pandemic was estimated for 2021. The utilization during 2020 did not belong to either group due to the transitional operation of the COVID-19 ICU.Enterobacterales were isolated, carbapenem was considered indicated when MIC was less than 8 [Carbapenems prescriptions were considered definitive when it was initiated or continued following the availability of microbiological results, with pathogen or susceptibility requiring coverage with carbapenems’ spectrum, from cultures of relevant sites except those from nasal swab and/or rectal swab for infection control surveillance purposes. If carbapenem-resistant s than 8 . Converss than 8  or the iPatient types were classified according to the risk factors of infection by resistant organisms. Type-1 or community-acquired infection referred to young patients with no or few comorbid conditions who had no contact with the health care system and no prior antibiotic treatment in the last 90 days; Type-2 or healthcare-associated infection referred to patients who had contact with the healthcare system in the past 3 months or less than 1 week in the hospital or less than 48 h in the ICU , had an invasive procedure or recent antibiotic therapy in the last 3 months or were more than 65 years old with few comorbidities ,92; TypeThe risk of infection with ESBL GNB was considered when a patient had received antibiotics in the past 90 days, especially second and third generation cephalosporins; hospitalization for more than 2 days in the past 90 days; was a resident in a nursing home; had chronic dialysis in the past 1 month; had home wound care, immunosuppressive disease, and/or therapy, catheter colonized by ESBL GNB and rectal swab with ESBL GNB. This was adapted from local guidelines ,95.p-value of <0.05 was used as the level of significance.Antibiotic utilization was measured in units of DDD per 1000 patient days in aggregate annual data. All analyses were carried out using Statistical Package for the Social Sciences (SPSS), version 27.0 , categorical, and continuous data variables. Univariable analyses were performed with Chi-Squared test or Fisher Exact test to compare categorical variables where appropriate. The median of continuous variables was compared using the Mann–Whitney test. A Antibiotics’ consumption in ICU increased markedly during the pandemic year, with near to two-fold increments in carbapenems utilization. Most carbapenem therapies were empirical and the reasons for prescribing differed between the two ICUs. Carbapenems were frequently prescribed to escalate therapy in the COVID-19 ICU, while in the GICU, it was for concern of ESBL GNB risk. Both ICUs had a similar duration of empirical carbapenems’ usage.