As these three GVHD prevention/treatment modalities continue their path toward clinical application, it is imperative the field understand both the biological advantages and disadvantages of each approach.The development of graft versus host disease (GVHD) represents a long-standing complication of allogeneic hematopoietic cell transplantation . Different approaches have been used to control the development of GVHD with most relying on variations of chemotherapy drugs to eliminate allo-reactive T cells. While these approaches have proven effective, it is generally accepted that safer, and less toxic GVHD prophylaxis drugs are required to reduce the health burden placed on allo-HCT recipients. In this review, we will summarize the emerging concepts revolving around three biologic-based therapies for GVHD using T regulatory cells (Tregs), myeloid-derived-suppressor-cells (MDSCs) and mesenchymal stromal cell (MSC) exosomes. This review will highlight how each specific modality is unique in its mechanism of action, but also share a common theme in their ability to preferentially activate and expand Treg populations  Graft versus-host disease (GVHD) remains a significant problem following an allogeneic hematopoietic cell transplantation  with GVHD patients experiencing a lower quality of life and a higher risk of death. Our understanding of the cellular and molecular mechanisms of GVHD has provided researchers additional clarity on the etiology of its pathogenesis. This has allowed for a growing number of non-biologic and biologic-based GVHD prophylaxis/treatment therapeutics to be investigated as safer modalities for allo-HCT patients. Specifically, the investigation into the use of biologics for GVHD therapies is still in its infancy but there are several exciting possibilities in the pipeline. In this mini-review, we will highlight three emerging biologic-based therapies that are at different stages of conceptualization and development which include T regulatory cells (Tregs), myeloid-derived-suppressor cells (MDSCs) and mesenchymal stromal cell (MSC) exosomes. We will also emphasize the similarities and differences of each modality in terms of biologic activity and possible clinical use.via CD39/CD73 activity (T regulatory cells (Tregs) represent a T cell polarization state with potent immunosuppressive activity –4. Classactivity Figure 1While the activity of Tregs is predicated on the recognition of self-peptides presented by antigen-presenting-cells (APCs) to prevent the development of an autoimmune disease, Tregs can also develop against non-self-peptides in the periphery . Moreovehigh characteristic of all Treg populations  develop during T cell development and are characterized in mice by the expression of neuropilin-1, the transcription factor Helios and in the expression of CD3, CD4, FOXP3 and CD25ulations –13. Mostulations . This Tr17 polarization. Studies have shown that iTregs can be polarized into TH17 cells and vice versa, highlighting the plasticity of this population and how the balance of iTreg/TH17 polarization can influence immune responses  exit the thymus as conventional T cells but are polarized to iTregs in environments with high levels of TGFβ, retinoic acid, IDO, and other mediators , 14, 15.esponses –20.In both pre-clinical mouse models and clinical studies, it has been established that elevated Tregs frequencies in the graft is correlated with lower rates of GVHD –26. AnotThe TCR repertoire of tTregs and iTregs do not overlap, highlighting the different antigens they recognize (germline self-antigens vs microbiota-derived antigens) , 28, 29.in vitro  may be equally important –35. mTORrization , 37. Add17 cells –37.The polarization of naïve CD4 T cells to iTregs by sirolimus makes it an effective therapeutic candidate that is currently used in the clinic. One multicenter study (BMT-CTN-1501) revealed that sirolimus was equivalent to prednisone for initial GVHD treatment and resulted in a shorter time to immune suppression discontinuation . Anotherin vivo should continue to be prioritized.With so many current GVHD drugs connected with an expansion of the iTreg population, it is logical for a growing number of clinical trials to investigate the direct treatment of Tregs. Unfortunately, iTreg adoptive therapies are hindered by high production costs, the inability to generate/store multiple doses and the need for a patient specific product. Thus, the investigation into new therapies preferentially expand/polarize iTregs Myeloid-derived-suppressor-cells (MDSCs) represent a heterogeneous population of cell types with the general function of dampening immune responses –50. MDSC+, CD33high) but also express several M2 markers  and are CD16-/HLA-DR- while both classical and inflammatory monocytes are all HLA-DR+  but also express the same immunosuppressive markers listed above  but maintain expression of CD33 and the immunosuppressive markers ; however, they have also been shown to prevent GVHD –58. One MDSCs populations have been shown to use a variety of molecular pathways to control T cell responses including indoleamine-pyrrole 2,3-dioxygenase (IDO), cyclooxygenases, arginase, TGF-β, IL-10 and PD-L1 Figure 12 by the receptors EP2 or EP4 have been shown to prevent the polarization of T cells into TH1 cells and directly promote the expression of FOXP3 similar to TGF-β , mRNA and possibly even DNA , 82, 83.As an ever-growing number of studies support the role of exosomes in generating MDSC populations, the mechanism(s) utilized by exosomes to generate these MDSC populations remains largely unexplored Figure 1Compared to standard cellular therapies, exosomes have several fundamental advantages including i) long-term storage, ii) low-immunogenicity, iii) no requirement for HLA-matching and iv) the ability to be mass-produced , 81, 89.Despite the lack of approved exosome-based therapies, there are a growing number of pre-clinical studies using exosomes to treat a variety of diseases. Most of these studies have utilized MSC-based exosomes, which builds upon the growing field of MSC-based cellular therapies, as they contain similar immunosuppressive properties. A series of studies by one team of investigators have sequentially shown that the treatment with human MSCs, or exosomes “educated” myeloid cells were able to prevent lethal acute radiation syndrome (ARS) , 82, 90.The use of MSCs for GVHD prevention and treatment has been explored in a large number of trials with most reporting that MSCs are safe and well tolerated. Unfortunately, the response rates among trials varied considerably and FDA approval is still elusive . RecentlThe field of GVHD research is at an exciting inflection point where the investigation into biologics as novel prophylaxis/treatment modalities may soon become standard. While the three modalities discussed in this review are all poised to make significant advances toward clinical use, these biologic modalities are not without their limitations. Similar to the experiences of CAR manufacturing, the use of Tregs or MDSCs as a cellular therapy will always be challenged with their production times, the manufacturing process and capacity to be used in the allogeneic setting. For these reasons, MSC-exosome treatment represents an exciting and promising modality. Exosome treatments have the potential to be used in the allogeneic setting, mass-produced for repeated injections, and stored for immediate use. Their eventual use in the clinic will ultimately be decided by their ease of use and long-term efficacy compared to direct cellular therapies which boast strong short term activity but are limited to a single infusion and long-term activity.Promoting the expansion and activation of Tregs after allo-HCT remains the most validated method of suppressing GVHD though the optimal approach to achieve this remains under investigation. Exploring the use of MDSCs and MSC-exosomes as novel approaches to activate Tregs should be a focus of investigation in the next decade. The development of these and other biologic-based prophylaxis/treatment modalities will offer allo-HCT recipients an improved quality of life by reducing off-target toxicity and improving overall efficacy by directing their new immune system to control the development of GVHD.NH drafted and performed the literature search. NH, JK and PH revised and edited the manuscript. All authors approved the final version of this manuscript. All authors contributed to the article and approved the submitted version.


The COVID-19 pandemic has posed a significant global threat, leading to several initiatives for its control and management. One such initiative involves wastewater-based epidemiology, which has gained attention for its potential to provide early warning of virus outbreaks and real-time information on its spread. In this study, wastewater samples from two wastewater treatment plants (WWTPs) located in the southeast of Spain (region of Murcia), namely Murcia, and Cartagena, were analyzed using RT-qPCR and high-throughput sequencing techniques to describe the evolution of SARS-CoV-2 in the South-East of Spain. Additionally, phylogenetic analysis and machine learning approaches were applied to develop a pre-screening tool for the identification of differences among the variant composition of different wastewater samples. The results confirmed that the levels of SARS-CoV-2 in these wastewater samples changed concerning the number of SARS-CoV-2 cases detected in the population, and variant occurrences were in line with clinical reported data. The sequence analyses helped to describe how the different SARS-CoV-2 variants have been replaced over time. Additionally, the phylogenetic analysis showed that samples obtained at close sampling times exhibited a higher similarity than those obtained more distantly in time. A second analysis using a machine learning approach based on the mutations found in the SARS-CoV-2 spike protein was also conducted. Hierarchical clustering (HC) was used as an efficient unsupervised approach for data analysis. Results indicated that samples obtained in October 2022 in Murcia and Cartagena were significantly different, which corresponded well with the different virus variants circulating in the two locations. The proposed methods in this study are adequate for comparing consensus sequence types of the SARS-CoV-2 sequences as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point. On 11 March 2020, the WHO declared the current coronavirus disease (COVID-19) situation a global pandemic on the basis of “alarming levels of spread and severity, and by the alarming levels of inaction” . The strThe topics linked to SARS-CoV-2 are numerous, ranging from the epidemiology of the disease to treatments and impacts on different aspects of society. One of the main topics since the beginning of the COVID-19 pandemic has been wastewater-based epidemiology (WBE). Wastewater monitoring has been used as a successful, non-invasive, and early warning tool for monitoring the status and trend of COVID-19 infection and as an instrument for tuning public health responses . The infThe usefulness of WBE is not only associated with the detection of the virus in the wastewater associated with a specific population, but also with an early warning alert for the detection of new variants of clinical concern for public health. Since March 2021, the European Commission adopted a recommendation on a common approach to establish and make greater use of systematic wastewater surveillance of SARS-CoV-2 as a new source of independent information on the spread of the virus and its variants in the European Union .In the South-East of Spain, systematic surveillance of SARS-CoV-2 in wastewater started in March 2020 and continues to date, which resulted in a historical inventory of the SARS-CoV-2 concentration throughout the duration of the pandemic . HoweverThe aim of the current study is to use wastewater monitoring and clinical data to provide an overview of the historical data for SARS-CoV-2 levels obtained in the South-East of Spain. This information will be combined with the results obtained using high-throughput sequencing techniques to describe the evolution of SARS-CoV-2. With the sequencing data provided by WGS, phylogenetic trees and machine learning approaches are used as a pre-screening for the identification of differences among the variant composition of different wastewater samples. The aim of this study is not to use phylogeny to describe the evolution of SARS-CoV-2.g for 30 min, and the resulting pellet was resuspended in 1 mL of PBS, pH 7.4. Influent grab water samples were taken monthly from two wastewater treatment plants (WWTPs) located in the two main cities (Murcia and Cartagena) of the Region of Murcia (Spain) from March 2020 to March 2023. Concentration (200 mL) was performed using an aluminum-based adsorption–precipitation method, as previously described . A finalRecovery controls were prepared by spiking PEDV . For each sample, the percentage recovery was calculated by dividing the viral titer of concentrated sample by the titer of the recovery control. g. Next, the resulting supernatant was transferred to the loading cartridge, and 300 μL of lysis buffer was added. The cartridge was then loaded in the Maxwell® RSC Instrument  using the “Maxwell RSC Viral total Nucleic Acid” running program for the nucleic acid extraction. The obtained RNA was eluted in 100 μL nuclease-free water. Negative controls were included by using nuclease-free water instead of a concentrated sample. SARS-CoV-2 nucleic acid detection was performed via RT-qPCR using One Step PrimeScriptTM RT-PCR Kit   targeting a genomic region of the nucleocapsid gene (N1 region) using primers, probes, and conditions previously described in CDC panel [Nucleic acid extraction of SARS-CoV-2 from wastewater concentrates was performed using an automated method with the Maxwell RSC Pure Food GMO and authentication kit (Promega) with slight modifications . FirstlyDC panel . All RT-The prevalence of SARS-CoV-2 variants was assessed using five different duplex gene allelic discrimination TaqMan RT-qPCR procedures using primers, probes, and conditions previously described ,21. AlphEach RT-qPCR analysis included duplicate wells with undiluted RNA and a 10-fold dilution to check for inhibition, as well as corresponding negative controls (amplification and extraction). Standard curves for genome quantitation of different variants were prepared using commercially available Twist Synthetic SARS-CoV-2 RNA Controls , control 17 (EPI_ISL_7926), and control 23 (EPI_ISL_15440143). The percentage of SARS-CoV-2 genomes containing each variant-specific mutation in the S gene was calculated using the formula: TM RT SuperMix  and amplification via multiplex PCR. Sequencing libraries were built using the Native Barcoding Kit . The last purified product was eluted in 15 μL of elution buffer. Finally, the library was loaded on an R9.4.1 flow cell (FLO-MIN106) and placed onto a MinION Mk1C sequencer for a 36–48 h run.Samples with RT-qPCR cycle threshold (Ct) values below 32-34 and a high recuperation percentage (≥25%), based on the recovery control (PEDV CV777 strain), were selected for sequencing analysis. Genomic sequencing of SARS-CoV-2 present in selected wastewater samples was carried out following the ARTIC protocol version 4 for retrotranscription using LunaScripthttps://data-dataref.ifremer.fr/bioinfo/ifremer/obepine/lsem/data/dna-sequence-raw/ (accessed on 27 April 2023)). Successfully base-called reads were further analyzed following the ARTIC nCoV-2019 pipeline version 1.2.1.2 (ARTIC nCoV-2019 novel coronavirus bioinformatics protocol), which included demultiplexing, read filtering, primers, and barcode trimming. The resulting alignment file was used for single nucleotide variants (SNVs) calling using LoFreq version 2.1.5, with a minimum base quality of 20 and 20× coverage, relative to the Wuhan-Hu-1/2019 reference genome (GenBank: MN908947.3). Short indel calling was also performed using Lofreq after a preprocessing step to insert indel qualities. Samtools were used to read alignment files and to extract genome coverage percentages at different depths . Samtools also allowed the extraction of mean genome coverage across the distinct amplicons trimmed for primer and overlapping sequences for each sample. For VOC analysis, we excluded samples with depth 30 coverage < 70%. Based on previous studies, single nucleotide variants (SNVs) and indels with coverage < 30, average quality < 30, frequency < 5%, and homopolymer run > 4 (for indels only) were excluded [After the sequencing runs, fast5 data files were base-called using Guppy  to generate fastq files ).Epidemiological data on COVID-19 in the Murcia Region were retrieved from the publicly available repository of the “Servicio de epidemiologia” of the “Consejería de Salud de la Región de Murcia” (Sixteen consensus SARS-CoV-2 sequences (in format .fasta) associated with the selected WWTPs (Murcia and Cartagena) from March to October 2022 were used for the phylogenetic analysis. These consensus sequences were generated using ARTIC bioinformatic pipeline for SARS-CoV-2 (ARTIC nCoV-2019 novel coronavirus bioinformatics protocol) specifically designed for Nanopore data.The phylogenetic tree of the 16 consensus sequence types was generated using an alignment-free method with feature-frequency profile methodology .N is the length of the SARS-CoV-2 reference genome (GenBank: MN908947.3). In this study, the selected optimum k value corresponds to the positive integer value that verifies k > k_(H_max).The phylogenetic tree of the 16 consensus sequences was generated using an alignment-free method with feature-frequency profile methodology . The proN = 29.903 bp hence k_(H_max) = 7.43, which gives the value of optimum k = 8.Then, Phylogenic tree: seqinr, Biostrings, ape, textmineR.Clustering: openxlsx, dplyr, pheatmap, ggplot2.From the results obtained with the previous methodology based on 8-mer, the pairwise distance between each two genomes was estimated using the Jensen–Shannon divergence measure. As a result of this computation, we obtained a distance matrix that applied neighbor-joining (NJ) is a frequently used algorithm for constructing phylogenetic trees. The obtained distance matrix was used to generate the phylogenetic tree based on the NJ algorithm, to illustrate the relatedness between the consensus sequences. All analyses were conducted using R version 4.2.2. The specific R packages use for the analysis were:The machine learning (ML) analysis was applied to the data corresponding to the 16 SARS-CoV-2 spike protein mutation profiles associated with the selected WWTPs (Murcia and Cartagena), covering the period from March to October 2022. The different WWTP profiles were classified by means of the Hierarchical Clustering ML technique . In thisSince the beginning of the pandemic in March 2020, multiple waves of SARS-CoV-2 were recorded in Murcia (Spain). Three different situations can be identified between the WBE data and the clinical cases in the historical profile. The first of them A is charNumerous international efforts have arisen to identify SARS-CoV-2 in sewage systems during the pandemic. These efforts employ various analytical procedures that rely on RT-qPCR, genetic material preparation, and enrichment . ThroughFor all wastewater samples collected weekly from Cartagena and Murcia WWTPs, RT-qPCR was performed to identify and analyze the prevalence of UK/Alpha (Del 69/70), Beta (Del241/243), Delta (Del 157/158), Omicron (Del. 31/33), Omicron BA.1. (Ins 214), Omicron BA.2.  variants of concern . RT-qPCR results show a 100% prevalence of the Omicron variant all through the studied period of 2022. Notably, between weeks 11 and 13 of 2022, a shift from the Omicron BA.1. variant to the Omicron BA.2. (presence of deletion 25/27 together with no presence of deletion 69/70) variant was observed. The 69/70 deletion, associated with the Alpha VOC at the first stages of the pandemic, was detected shortly after starting the studied period, as both Alpha and Omicron (BA.4 and BA.5) share this mutation. Thus, the concurrence of deletion 69/70 with deletion 25/27 from week 22 indicates a shift from Omicron BA.2 to Omicron BA.4 and BA.5. As other studies report, in mid-December 2021, the Omicron variant overtook the Delta variant, which had been the majority during the months of October and November 2021. The transition from Delta to Omicron occurred rapidly in 2-3 weeks in the month of December (weeks 49 to 51 of 2021) ,30; thusThe aim of this study is to apply phylogenetic analysis to compare the SARS-CoV-2 variants that are present in a population at a specific time point with other populations or other time points within the same population. The idea is to develop a pre-screening strategy to identify significant changes that can be derived from the introduction of a new variant. When a significant change is initially identified a deeper evaluation of the sequence analyses would be necessary. To compare different sequences, there are several approaches. The selection of one or another will depend on whether the genomes that will be compared, shared or not, have an alignable set of common genes. In cases where there is an alignable set of genes, two methods can be used, including: (1) multiple sequence alignment (MSA), where the identification a common subset of genes shared by all of the species is compared to build a MSA for each gene; and (2) the use of the gene profiling method, where the occurrence of each gene in a dictionary of genes is counted, forming a gene presence/absence profile . On the As explained in the materials and method section, the NJ algorithm was used for constructing phylogenetic trees because of its fast operation and high accuracy, and is based on their similarity. In this case, the NJ algorithm was used to infer evolutionary relationships between different isolates obtained at different time intervals from the WWTPs of Murcia and Cartagena. The phylogenic tree was based on the complete genome sequences found in the wastewater at the different sampling times and locations (Cartagena and Murcia). In this case, the approach presented by Dong et al. , which rThe aim was to determine if the consensus sequence types obtained from a specific sampling showed similarities or differences with other samples. Establishing a consensus sequence from wastewater samples to determine which is the SARS-CoV-2 variant affecting a population is not the most recommended methodology because sequences assembled from wastewater are a mix of many strains. However, in this study, the consensus sequence type was generated in a homogeneous way, which allowed them to be comparable. Each of the generated consensus sequence types is valuable as an overall view of all the SARS mutations that are present in a specific population at a specific time. It is the absolute comparison which gives relevant information regarding relevant changes over time in a specific population. Thus, this methodology could be used as a preliminary screening to determine if a drastic change in the variants that are present in a population occurs between one sampling time and another, or among different populations. If changes between two samples are observed, a more in-depth study could be needed to determine if this is due to the introduction of new variants. Similar approaches have been already used to determine if multiple lineages are present and circulating in a given population ,31. In tThe classification obtained based on the phylogenetic analysis shows that in most of the cases, samples obtained at close sampling times show a higher similarity than those samples more separated in time . Even thA second analysis based on machine learning analysis was performed using the information obtained from the mutations found in the SARS-CoV-2 spike protein for each location and sampling times. Hierarchical clustering (HC) has been defined as an efficient unsupervised approach to unlabeled data analysis . These data bring supplementary information on the similarities of the sequences that are circulating in a specific sample. The heatmap represented in It is important to understand that the clustering was based on the probability percentages of each of the mutations in the different WWTPs in the different sampled months, while the phylogenetic analysis was carried out based on the consensus sequences of each WWTP at all times. Therefore, the information provided by the clustering is based on a different concept than that used for the phylogenetic analysis. The information obtained in the two analyses can be considered complementary, but since they are based on different data, direct comparison is not correct. However, some general correlations can be found between the two analyses. Based on The methods proposed in this study seem to be adequate to compare consensus sequence types as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point.


Reprocessing and disinfecting endoscopes is a routine practice in otolaryngology. An effective, safe, and rapid disinfection technique is essential during the COVID-19 pandemicTo validate the efficacy of chlorine dioxide wipes in disinfecting three types of airway endoscopes contaminated with COVID-19-positive patient secretions.Chlorine dioxide wipes were tested on rigid nasal endoscopes, laryngoscope blades, and flexible bronchoscopes. The endoscopes were disinfected using the wipes after exposure to COVID-19-positive patients. The tested scope was included in the study if the post procedure pre disinfection swab was positive for COVID-19 virus using RT-PCR. We analyzed 38 samples for 19 subjects (scopes) pre and post disinfection with chlorine dioxide wipes from July 2021 to February 2022.A total of four rigid endoscopes, four flexible bronchoscopes, and four laryngoscopes were included in the study which represent 24 pre and post disinfection swabs. The others were excluded because of negative pre disinfection swab. All the post disinfection PCR swab results were negative.Chlorine dioxide is a convenient, fast, and effective disinfection technique for COVID-19-contaminated airway endoscopes. The authority of the Republic of China had reported pneumonia cases of unknown cause in Wuhan in the province of Hubei (China) between 8 December 2019 and 2 January 2020. However, on 11 and 12 January, they declared the first cases of what is now called SARS-CoV-2, caused by the novel Coronavirus-19 . On 11 FThe wide spread of the disease and strict isolation and social distancing protocols strongly affect all aspects of financial and social as well as medical fields . Airway Many issues have been raised to address the situation after opening the service. Reprocessing and disinfecting endoscopes are essential after each airway procedure . Many obThis study aimed to validate the efficacy of chlorine dioxide wipes system in disinfecting three types of airway endoscopes contaminated with COVID-19-positive patient secretions.This study tested the efficacy of using the chlorine dioxide wipes system. The wipes were tested on three groups of airway endoscopes. The first group was rigid nasal endoscopes after passing them through the nasopharynges of positive patients. Laryngoscope blades in the second group were tested after being used for intubation. Finally, flexible bronchoscopes were tested after bronchoscopic guidance endotracheal intubation. For each group, two swabs were taken from every tested device. The first was immediately after the procedure and the second after disinfection using chlorine dioxide wipes. The swabs were sent for real-time polymerase chain reaction (RT-PCR) tests for COVID-19. A pre disinfection swab was performed to avoid false positive cases. All cleaning episodes were performed by a single person fully trained in the disinfection practice according to the manufacturer’s instructions. After each use, the devices were sent to the central sterile services department CSSD for standard sterilization.The currently recommended modality for diagnosing acute or current SARS-CoV-2 infection is a nucleic acid amplification test (NAAT) detecting one or more RNA gene targets specific to the virus. The most common is RT-PCR, which employs fluorescence to detect the amount of amplified DNA in real time . Some ofAll recommended controls were used: A negative (no template) control was used to exclude sample contamination during the assay run. A positive template (COVID-19_N_P) control was used to verify that the assay run performed as intended and was used on every assay plate.An internal control was used to detect nucleic acid present in the sample. This also served as an extraction control to ensure that samples tested as negative contained nucleic acid for testing. A negative extraction control  served as both a NEC to monitor for any cross-contamination occurring during the extraction process and an extraction control to validate extraction reagents and successful RNA extraction.This study analyzed 38 samples for 19 subjects  from July 2021 to February 2022. We used an Applied Biosystems 7500, Real-Time PCR Instrument System and LightCycler 480 , targeting the genes RdRp, N, RdRp/E, ORF lab, and E.Guidelines suggested by Julious were followed to estimate the sample size. A minimum sample size of 12 subjects per treatment arm for a main study sample size of 95 participants corresponds to standardized effect sizes of 0.5  . The samAll cases were recruited from hospitalized patients at Qatif Central Hospital. Patients were included if confirmed to be COVID-19-positive by RT-PCR. Additionally, the swab from the instrument used on a patient before disinfection needed to be positive. Conversely, the case was excluded from the study if the swab taken from the instrument after examining the patient and before disinfection was negative for COVID-19.Data was entered and analyzed using SPSS . The mean and standard deviation were calculated for numerical variables and counts and percentages for categorical variables.Informed written consent was obtained from each patient. The study was approved by Qatif Central Hospital Scientific Research Ethics Committee (ID: QCH-SRECO 271/2021). Tests were performed with appropriate personal protective equipment to ensure the examiner’s safety. The study protocol was performed in accordance with the relevant guidelines.Of all the tested subjects (19 scopes), 7  were excluded due to negative pre disinfection PCR swab results. A total of 24 swabs (63.2%) from four rigid endoscopes, four flexible bronchoscopes, and four laryngoscopes were included in this study as the pre disinfection PCR swab results were positive. All the post disinfection PCR swab results were negative.The time consumed during disinfection was between 4 and 5 minutes; the average time required for disinfection was approximately 4:33 minutes. The time between scope infection and starting disinfection ranged from 1 to 2 minutes; we found no difference in the post disinfection results. The disinfection technique between the three different instruments, metal instruments  and rubber or silicon material fiberoptic nasopharyngoscopy, ran with the same steps, and no post disinfection results were obtained. After each disinfection procedure, the instrument was checked for any damage related to the use of disinfectant including the surface and the lens of the endoscopes. There was no damage documented in all the procedures.In this study, precise copy-number quantitation of COVID-19 RNA for collected swabs was unnecessary. However, analytical sensitivity and limit of detection (LoD) studies established that the lowest concentration of SARS-CoV-2 (genome copies [cp]/μL) that could be detected by the assays used was Cycle threshold (CT:38). We used CT values of SARS-CoV-2 to detect the sample positivity rather than set clinical cutoffs.The average CT of all (12) positive swabs ranged from 15 to 34, much lower than 38, which is generally considered an upper borderline for reliable positive results, regardless of the type of commercial RT-PCR test used in SARS-CoV-2 diagnostics. The mean CT value for the positive swabs (pre disinfected) was CT:26 for the RT-PCR results of all tested swabs. All post disinfected swabs showed negative results with no CT detected. Table 1.COVID-19 remains a pandemic worldwide. With insufficient vaccination in some parts of the world and the emergence of several new mutations of the virus, conditions are expected to be serious for some time.This situation raised concerns about sterilization, disinfection, and cleaning in health care environments. These three reprocessing techniques differ in their degree of killing microorganisms. While sterilization eliminates all organisms, disinfection does not eradicate bacterial spores, and cleaning only reduces the burden by removing physical matter. This study tested the efficacy of using chlorine dioxide wipes to disinfect different types of instruments contaminated by secretions from the airways of COVID-19 patients.Choosing the type of reprocessing technique depends on two factors: the category of hospital instruments required and the manufacturers’ recommendations. Critical items are used on sterile tissue, so sterilization is the ideal reprocessing technique for these instruments. Different airway instruments, such as nasal endoscopes, laryngeal blades, and fiberoptic bronchoscopes, are semi critical items requiring a high level of disinfection . ChoosinChlorine dioxide wipes system is a convenient, fast disinfection technique for COVID-19-contaminated airway endoscopes. This study showed its high efficacy. It is very helpful to be used with many advantages especially in the pandemic situation. Further larger studies should be conducted to support this result.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Qatif Central Hospital research and ethical committee. The patients/participants provided their written informed consent to participate in this study.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


High-throughput RNA proximity ligation assays are molecular methods that areused to simultaneously analyze the spatial proximity of many RNAs in livingcells. Their principle is based on cross-linking, fragmentation, and subsequentreligation of RNAs, followed by high-throughput sequencing. The generatedfragments have two different types of splits, one resulting from pre-mRNAsplicing and the other formed by the ligation of spatially close RNA strands.Here, we present RNAcontacts, a universal pipeline for detecting RNA–RNAcontacts in high-throughput RNA proximity ligation assays. RNAcontactscircumvents the inherent problem of mapping sequences with two distinct typesof splits using a two-pass alignment, in which splice junctions are inferredfrom a control RNA-seq experiment on the first pass and then provided to thealigner as bona fide introns on the second pass. Compared to previouslydeveloped methods, our approach allows for a more sensitive detection of RNAcontacts and has a higher specificity with respect to splice junctions that arepresent in the biological sample. RNAcontacts automatically extracts contacts,clusters their ligation points, computes the read support, and generates tracksfor visualizing through the UCSC Genome Browser. The pipeline is implemented inSnakemake, a reproducible and scalable workflow management system for rapid anduniform processing of multiple datasets. RNAcontacts is a generic pipeline forthe detection of RNA contacts that can be used with any proximity ligationmethod as long as one of the interacting partners is RNA. RNAcontacts isavailable via the GitHub repository https://github.com/smargasyuk/ RNAcontacts/ The rapid evolution of high-throughput sequencing technology enabled the invivo identification of spatial contacts between nucleic acids, including theDNA contacts in the 3D chromatin structure , 2, 3, fA number of recently developed methods employ RNA proximity ligation to traceback RNA–RNA interactions in vivo and in vitro  and GENCODE transcriptannotation v34lift37 were downloaded from the Genome Reference Consortium and GENCHigh-throughput sequencing data Two bioreplicates of rRNA-depleted RIC-seq data (GSM3629915 and GSM3629916) inthe HeLa cell line  were dow--runMode alignReads --outSAMtype BAM SortedByCoordinate --chimOutTypeJunctions.On the second pass, the RIC-seq data were mapped to the human genome using thesame version of STAR aligner with the following additional settings:--chimSegmentMin 15 --chimJunctionOverhangMin 15 --chimScoreJunctionNonGTAG -1--scoreGapNoncan -1 --scoreGapATAC -1 --scoreGapGCAG -1 --chimSegmentReadGapMax3 --outFilterMatchNminOverLread 0.5 --outFilterScoreMinOverLread 0.5.The parameter --chimSegmentReadGapMax 3 is introduced to account for themappability of the additional biotinylated cytosine residue in RIC-seq [14].The penalty score is reduced to -1 for all non-canonical splice junctions onthe second pass.Pipeline implementation RIC-contacts is implemented in the popular workflow management system Snakemake and is aVisualization To visualize the contact maps, we converted the contact lists to the‘cool’ format using the cooler package v0.8.11 with 100-bpresolution and visualized the maps with the pygenometracks package v3.7. Splitread visualization was performed with IGV v2.11.2 and the UCSC Genome Browser. By defaThe RNAcontacts pipeline We have developed RNAcontacts, a computational pipeline for the analysis of RNAproximity ligation data, which circumvents the problem of multiple split typesby aligning short reads in a two-pass mode. The worSpliced alignment programs usually generate two separate output filescorresponding to co-linear and non-co-linear splits. In particular, the STARaligner reports co-linear splits  within the standard SAM/BAM output, while non-co-linearsplits are placed in the chimeric output file, since the BAM format does notallow their representation with a single CIGAR string . RNAcontIn application to the RIC-seq experiment in the HeLa cell line , RNAcontIndeed, the distribution of distances between two consecutive ligation pointshas a rapidly decaying tail, with approximately 50% of distances below 9 ntsand 90% of distances below 21 nts . We chose to cluster the ligationpoints using single linkage clustering with distance cutoffs (δ) of 10 ntsand 20 nts . A contact was defined as a pair of clusters, with thenumber of supporting reads equal to the sum of read counts corresponding toligation junctions.For each δ, we subdivided the contacts into three groups: intrageniccontacts (both ends of a contact belong to an annotated gene), contacts in cis, and contacts in trans (ondifferent chromosomes). The number of contacts (n), the cluster length (s), thedistance between contacting clusters , and the number of supporting reads (r) were only marginallydifferent for the two values of δ. On averThe distances between contacting clusters were distributed differently forneo-junctions and chimeric splits, both in terms of the number of contacts andwhen weighted by the number of supporting reads . Remarkably, thedistributions have two modes, with the first mode at d-~1000 corresponding tothe intragenic contacts encoded by both neo-junctions and chimeric splits.Chimeric reads may encode intragenic contacts if the split is in backwardorientation, as in circular RNAs .The secRNAcontacts has higher sensitivity than RICpipe To compare the performance of RNAcontacts with that of RICpipe, a pipelineoriginally designed to analyze RIC-seq data, we first analyzed ligationjunctions of 50 nts or longer located on the same chromosome and then matchedtheir exact genomic positions obtained by the two pipelines. We excludedjunctions in reads mapped to rRNA from RNAcontacts results for this analysis,because RICpipe removes rRNA reads .Only 40Additionally, we checked the performance of RNAcontacts on the RIC-seq data inthe HeLa cell line with and without the first mapping pass. For this purpose,we ran the second pass of RNAcontacts by supplying only the splice junctionsannotated in GENCODE , withoutIn this work, we have presented a conceptual solution to the problem of mappingshort reads with two distinct split types, which are characteristic of RNAproximity ligation assays, using the STAR aligner. However, the approach is notlimited to STAR, and any other spliced aligner program can be used instead. We haveThe nature of RNA proximity ligation data is similar to that of Hi-C. Yet ithas important distinctions related to the resolution. While it is a commonpractice for Hi-C to average chromatin contacts at kilobase or megabase scale,the assessment of RNA–RNA contacts using proximity ligation intrinsicallytargets single-nucleotide levels. Meanwhile, the read support by RIC-seq in themost naturally occurring contacts, for example, mediated by the RNA structurein the human SF1 gene , is veryTo summarize, RNAcontacts implements a generic RNA–RNA contact analysispipeline that accounts for multiple split types specific to RNA proximityligation methods. Initially designed for the RIC-seq protocol, the scope of thesoftware can be extended to any method involving proximity ligation in whichone of the interacting partners is RNA.The data set supporting the results of this study is available in the Zenodorepository (https://zenodo.org/ record/7027475) [


P < .001). Overall, we have developed a multimodal deep learning algorithm, MultiCOVID, that discriminates among COVID-19, heart failure, non-COVID pneumonia and healthy patients using both CXR and blood test with a significantly better performance than experienced thoracic radiologists.The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood test have been demonstrated to have predictive value on Coronavirus Disease 2019 (COVID-19) diagnosis on different prevalence scenarios. With the objective of improving and accelerating the diagnosis of COVID-19, a multi modal prediction algorithm (MultiCOVID) based on CXR and blood test was developed, to discriminate between COVID-19, Heart Failure and Non-COVID Pneumonia and healthy (Control) patients. This retrospective single-center study includes CXR and blood test obtained between January 2017 and May 2020. Multi modal prediction models were generated using opensource DL algorithms. Performance of the MultiCOVID algorithm was compared with interpretations from five experienced thoracic radiologists on 300 random test images using the McNemar–Bowker test. A total of 8578 samples from 6123 patients  were evaluated across datasets. For the entire test set, the overall accuracy of MultiCOVID was 84%, with a mean AUC of 0.92 (0.89–0.94). For 300 random test images, overall accuracy of MultiCOVID was significantly higher (69.6%) compared with individual radiologists  and the consensus of all five radiologists (59.3%,  The outbreak of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), stroke the worldwide population with more than 200 million cases and 4.5 million deaths by August 2021. The rapid spread of the pandemic led to a global overexertion of health care and research facilities in order to counteract the growing rate of infection. However, a collapse of the sanitary system was imminent and inevitable worldwide, and new technologies were needed to speed up the diagnostic process.The reference for COVID-19 diagnosis is the detection of SARS-CoV-2 viral RNA by real-time polymerase chain reaction (RT-PCR). However, the massive requests for sample processing at the beginning of the pandemic caused serious delays to obtain results.As lung involvement is one of the main causes of morbidity and mortality in SARS-CoV-2 infection, a quick identification of characteristic findings in chest imaging can support the diagnosis and speed up the identification of COVID-19 positive patients at the emergency units.1. In addition, one of the main hurdles to overcome when training an algorithm to detect Sars-CoV-2 infection in CXR is the similarity of findings with other entities like bacterial pneumonias or heart failure2. On the other hand, models based on laboratory results of peripheral blood also give predictive results on diagnosis3 and prognosis4.Several studies have shown that implementation of deep learning (DL) tools to detect chest X-rays (CXR) findings typically associated with SARS-CoV-2 infection, deliver comparable results to those acquired by interpretation of radiologists. However, most of the trained models have a drop in their prediction performance when tested over external datasets5. A multicategory approach that takes into account differential diagnoses that are more stable in their prevalence could reduce this variability.A key fact to highlight is how the incursion of COVID-19 caused a dramatic drop in the emergency room consultations of other pathologies. Later on, after the initial peak, the decline of the COVID-19 prevalence made the non-COVID diseases emerge once again at the hospitals. This is relevant due to the challenge of performing an efficient differential diagnosis with selected pathologies during a pandemic. It is well known that the predictive value of a diagnostic test is conditioned by the prevalence of the disease and that of COVID varies widely throughout the different waves of the pandemicWith the objective of improving and accelerating the diagnosis of COVID-19, we developed a tool to assist physicians in reaching a diagnosis. This tool is a multi-modal prediction algorithm (MultiCOVID) based on CXR and blood test with the ability to discriminate between COVID-19, Heart Failure (HF), Non-COVID Pneumonia (NCP) and healthy (Control) samples.We retrospectively collected CXR images and hemogram values from 8578 samples from 6123 patients and healthy subjects  from Parc Salut Mar (PSMAR) Consortium, Barcelona, Spain. Four cohorts were designed: (i) 1171 samples from patients diagnosed with COVID-19 by RT-PCR from March to May 2020; (ii) 1008 samples of patients who suffered an episode of heart failure between 2012 to 2019; (iii) 490 samples of patients diagnosed with non-COVID pneumonia (NCP) from 2018 to 2019; (iv) 5909 samples of standard preoperatory studies of healthy subjects from 2017 to 2019 , and hold-out test (10%) set. For training/validation split, we divided the dataset in training (80%) and validation (20%) sets with 5 different random seeds. We ensured that there were no cross-over patients between groups.6. The CXR-only classification model consists of a validated Convolutional neural network (CNN) resnet-34 architecture7. Tabular only-model is an Attention-based network (TabNet)8. Joint model is a multi-modal deep learning algorithm which merges the CXR-only and the Blood-only models and uses both CXR image and blood tests as input values. It uses Gradient Blending in order to prevent overfitting and improve generalization9. MultiCOVID model is an ensemble predictor of 5 different Joint models that would classify independently between the different classes. Then it uses majority vote to assign a final classification. The whole pipeline development and training was performed using fastai deep learning API10.Detailed description of the models, training policy and image preprocessing are provided in Hold-out test dataset consisting of 300 samples  was used for expert interpretation. Each sample consisted of a CXR with matched blood results. Expert interpretations were independently provided by five board-certified thoracic radiologists  with 2–30 years post-residency training experience. Radiologists were able to check both non segmented images and blood test results without any other additional information in a platform created ad-hoc for prediction. They provided a classification for each image in one of the four categories . A consensus interpretation for the radiologist was obtained by the majority vote for each paired CHX-blood test analyzed.A two-tailed t-test P value was reported when clinical and population blood test differences were assessed. McNemar–Bowker test was used to compare model performance against radiologist majority vote using FDR correction. Plotting and statistical analyses were performed using the packages ggplot, ggpubr and rcompanion in R, version 3.6 .The study was designed to use radiology images and associated clinical/demographic/ laboratory patient information already collected for the purpose of performing clinical COVID-19 research by Hospital del Mar. The study was conducted in accordance with the relevant institutional guidelines and regulations. The experimental protocols, data acquisition and analysis were approved by the Parc de Salut Mar Clinical Research Ethics Committee (2020/9199/I). Informed consent was obtained, when possible, from patients or legal representatives or waived by the local Parc de Salut Mar Clinical Research Ethics Committee (2020/9199/I) if informed consent was not available due to the pandemic situation.P < 0.001 for each comparison) and was not considered as a valid variable for further classification.A total of 8578 samples were evaluated across datasets. Patient characteristics and blood test parameters are shown in Table 1. For this reason, we first developed a segmentation algorithm able to segment lung parenchyma at a 95%-pixel accuracy. Then, after segmentation, we evaluated the accuracy of the algorithms for three complementary datasets: non-segmented images, segmented regions and excluded regions. After a few training epochs the three different models achieved nonrandom accuracies between 67 and 74% -based algorithms should be rigorously evaluated due to their ability to learn non relevant features in order to increase its prediction accuracy74% Fig. A. Howeve74% Fig. B.Figure These observations showed that, although there are important features outside the lung parenchyma that may help the model to classify between the different entities (eg. heart size), there are other elements  catheters) that might confound the model. Thus, we decided to first segment all the CXR before training our models for prediction of diagnosis. In order to accomplish this task, we generated a 785-radiology level lung segmentation dataset and trained a U-net model to regenerate the whole CXR dataset keeping only the lung parenchyma.In order to evaluate the prediction capacity of both segmented CXR and blood sample data, we built different DL models using both sources alone or in combination. Metrics comparison of all the single vision (CXR-only) and tabular (Blood-only) models are detailed in 12 showed that patient classification was related to two different axes: the immune compartment and the red blood cell (RBC) compartment, respectively  models alone (Supplementary Table P < 0.001). In addition, for COVID-19 prediction individually, MultiCOVID showed similar sensitivity to the radiologists’ consensus but with a much higher specificity, leading to significantly better performance when discerning between COVID-19 versus Control and COVID-19 vs HF patients  when the consensus interpretation of all 5 radiologists based on the majority vote was considered. Of note, the overall accuracy achieved by MultiCOVID was 69.6% (209/300) that was significantly higher than consensus interpretation . The integration of these results allows the team to diagnose a patient accurately. However, this process is time consuming and sometimes findings are difficult to interpret, leading to misdiagnosis.13.To improve this diagnostic process, we have developed and trained a multimodal deep learning algorithm based in a multiple input approach combining CXR images together with blood sample data to identify COVID-19 diagnosis with high sensitivity. This way we were able to manage the increased complexity of the dataset. These data from multiple sources are somehow correlated and complementary to each other and could reflect patterns that are not present in single models aloneHence, MultiCOVID is fed by two of the most common and fast clinical tests requested in the emergency room (CXR and Blood test) and can predict the presence of three different diseases  with similar CXR characteristics.9, Blood-only models could point to interesting population of cells that are differently represented in COVID-19 patients, leveraging its prediction capacity. In this context, the immune compartment plays an important role in the COVID-19 response, and it has been already published that COVID-19 patients present fewer overall leukocytes counts and, more concretely, eosinophil counts15. Furthermore, oxygen transport seems to be somehow affected, modulating the red cell population. In this regard, in our work we found significant differences in the erythrocyte count and the hemoglobin concentration. Although most of the studies correlate the reduction of this values to severe COVID-19 patients16, this is the first dataset to compare them in these four different categories at the time of diagnosis.Analysis of single models shows the importance of model interpretation. While CXR-only models could identify patterns outside the lung parenchyma that could diminish its generalization capacity20 or CXR28 this is the first study that combines both parameters and compares its prediction capacity at diagnosis. Of note, only one previously published study integrates both blood test and CXR severity scores in order to determine in-hospital death of COVID-19 patients29. Hence, it is clear that merging both sources of data leads to a better prediction performance when compared with the two single models alone and that this difference is more pronounced where the number of cases is scarce. It is important to stress that this combination of data sources addresses the variable prevalence of COVID-19 cases during the pandemic, which is an issue that could not be solved in previous studies24.Moreover, although a huge amount of literature about COVID-19 diagnosis and prognosis has been published using only blood testsOur study has several limitations. First, the algorithm was evaluated on a single center; thus, there was likely some degree of bias. Additionally, the sample collection was performed in different time periods for each group of patients, which could present some kind of differences in the CXR image acquisition although this was partially solved using the lung segmentation model which removes the noise signal present outside the lung parenchyma. And finally, model performance could be influenced by potential shifts in the disease landscape due to COVID-19 variants and vaccination efforts, which could influence the generalizability and interpretation of our findings.We have developed a multimodal deep learning algorithm, MultiCOVID, that discriminates among COVID-19, heart failure, non-COVID pneumonia and healthy patients using both CXR and blood test with a significantly better performance than experienced thoracic radiologists.Our approach and results suggest an innovative scenario where COVID-19 prediction could be identified from other similar diseases and facilitate triage within the emergency room in a COVID-19 low prevalence situation.Supplementary Information 1.Supplementary Table 1.


Compression therapy based on multilayer compression bandaging and compression garment use remains the most efficient component of complex physical therapy (CPT) in lymphedema treatment. The proper self-application of compression bandages is generally considered as problematic. Adjustable compression wraps (ACW) have been proposed as an alternative to the commonly used short-stretch bandages for lymphedema. These systems allow easy application and removal for patients. They have been tested in patients with vascular disorders of the lower limbs and can be considered in breast cancer survivors with upper-limb lymphedema.p < 0.001). A further decrease in the affected limb volume within the second week was noted only in the CB-Group (p = 0.02). A parallel trend was found in the percentage reduction in the excess volume after one and two weeks of compression therapy. Within two weeks, both groups achieved a significant improvement in decreasing lymphedema-related symptoms, but women from the ACW-Group reported complications related to carrying out compression more frequently (p = 0.002). ACW can reduce lymphedema and disease-related symptoms, but based on the results it is difficult to recommend this method as an alternative option in the acute phase of CPT among women with advanced arm lymphedema.The objective of this study is to compare the effectiveness, comfort and possibilities of the self-application of adjustable compression wraps (ACW) with compression bandaging (CB) in the acute phase of treatment in advanced upper-limb lymphedema. In total, 36 patients who fulfilled the admission criteria were randomly assigned into ACW-Group (18 patients), or CB-Group (18 patients). Treatment in both groups lasted for two weeks. In the first, all patients were educated in applying adjustable compression wraps (ACW-Group) or self-bandaging (CB-Group) and treated by experienced physiotherapists. In the second week, the use of ACW and CB was continued by the patients themselves at home. In both groups, a clinically significant reduction in the affected limb volume was found after the first week ( Breast cancer-related lymphedema (BCRL) as a result of lymphatic system insufficiency and impaired lymph transport remains one of major long-term complications among breast cancer survivors . The firDespite compression not being curative because it cannot modulate the pathophysiology of lymphedema , the posBecause lymph is propelled from the extremities to the blood stream not only by intrinsic contraction but also extrinsic forces such as contractions of the skeletal muscles adjacent to the lymphatic vessels, the effectiveness of compression in terms of improving muscle pumping via the veins and lymphatics may also help lymph propulsion by enhancing the extrinsic force. Short-stretch compression characterized with a high level stiffness is more beneficial for the augmentation of muscle pumping than long-stretch compression due to poorer tolerance and the risk of traumatizing soft tissues . In compShort-stretch compression bandaging effectively reduces limb volume during the acute, intensive phase of CPT ,6, whileTeaching the self-application of CPT is effective in maintaining or improving its benefits and can be used as a self-care tool in management ,17,18. HOne option to improve the self-management of patients is innovative adjustable compression wraps (ACW), as an alternative to the commonly used short-stretch bandages ,21, but Preliminary clinical trials confirm a similar or even higher effectiveness of ACW in reducing primary lower-limb lymphedema and better comfort at the initial phase of treatment compared to short-stretch bandages ,23, in mIn only one randomized clinical trial was the effectiveness of ACW in the treatment of upper-limb lymphedema assessed . There aThe objective of this study is to compare the effectiveness, comfort and possibilities regarding the self-application of adjustable compression wraps with multi-layer compression bandaging at the intensive phase of treatment in advanced upper-limb lymphedema among breast cancer survivors.During the recruitment period (between January and November 2022), among 65 women after breast cancer treatment admitted to the Lymphedema Clinic, 36 patients fulfilled the admission criteria-stage-II (according to ISL) lymphedema, ≥20% excess limb volumes, positive pitting skin sign, and absent signs of active cancer, venous thrombosis or previous compression. These participants were randomly assigned  into the experimental group with the adjustable compression wrap, ACW-Group (18 patients), or the control with compression bandaging, CB-Group (18 patients). The two groups were comparable concerning baseline characteristics, including BMI, type of surgery, additional onco-therapeutic modalities, limb volume and excess volume. They differed only in age. Women in the CB group were older compared to the ACW group .In the ACW group, adjustable compression garments  were fitted based on individual limb measurements and they were used for 24 h . The kitIn the CB group, multi-layer bandaging of the limb was performed using short-stretch bandages with pads . At the beginning of bandaging, a cotton tube stockinet was placed on the arm, and a layer of gauze was applied to the fingers and hand. A layer of foam padding (Lymphset: Lohmann & Raucher) was placed on the hand and wrapped around the arm. Three bandages of different sizes  were placed around the limb with the first starting at the hand, the second at the wrist and the third beginning below the elbow .Sub-bandage pressure was measured via the Kikushime device  on the dorsal part of the forearm, as well as on the arm, to ensure a pressure value within the range of 20–30 mmHg, comparable to the pressure used in the compression system among the ACW Group. Bandages were removed for a short time before the therapeutic session the next day, as in the ACW-Group, and put on the next day. The exercise program, including aerobic exercises of the upper limbs combined with deep breathing, was performed in adjustable compression wraps or bandaging for 15 min in 1 session per day. Treatment in both groups lasted 10 days . In the first week, all patients were treated by 2 experienced physiotherapists and educated in applying adjustable compression wraps (ACW group) or self-bandaging (CB group). During the 2nd week, the use of ACW and CB was continued by the patients themselves at home. Patients were asked to maintain the adjustable compression wraps or compression bandaging even over the weekend (Saturday and Sunday). After 2 weeks, all patients were fitted with made-to-measure compression sleeves in the range 23–32 mmHg .A2BMI1/BMI2A1) − 1, where A1 and A2 are arm volumes of the treated arm at baseline and after 2 weeks, and BMI1 and BMI2 are Body Mass Indexes at the corresponding time points).Measurements, including physical functioning, limb volumes and disease-related symptoms, were taken before the intervention, as well as after 1 and 2 weeks of treatment in both groups. Circumferential upper-limb measurements were taken with the arm abducted at 30°, starting at the level of the ulnar styloid, every 4 cm proximal to this point along both limbs. The calculation of limb segment volumes was carried out using a simplified frustum formula (summed truncated cone). The excess volume was the difference between the affected and unaffected limbs expressed in liters. The percentage reduction in the excess volume was obtained as follows: (excess volume before treatment–excess volume after treatment) × 100/excess volume before treatment. To quantify lymphedema, which functions independently of the opposite arm and accounts for fluctuations in patient weight, we additionally used the WAC formula  based on the International Compression Club (ICC) Questionnaire-Part for Patients . Firstlyp-value of <0.05 was chosen as the level of statistical significance. Data were analyzed using the R program (version 4.2.2), a language and environment for statistical computing  [We summarized the baseline demographics using descriptive statistics and means with standard deviations (SD) or medians with interquartile ranges (IQR) in non-normally (according to Shapiro–Wilk test) distributed ordinal quantitative data. To calculate the differences between the two groups with a non-normal data distribution, the Mann–Whitney test was used. Quantitative non-normally distributed variables in one group evaluated twice were analyzed using the Mann–Whitney test. Data measured within one group more than twice were checked by the Friedman test and Wilcoxon test with Bonferroni post hoc correction. A Austria) .Sample size calculations were performed based on the previous study with an evaluation of adjustable compression wrap effectiveness . A totalp < 0.001). A further decrease in the affected limb volume within the second week of the treatment was noted only in the CB group. No further improvement was observed in the AWC group after the second week. A statistically significant difference in the affected limb volume  was observed between the groups after 2 weeks of therapy. A parallel trend was observed in the percentage reduction in excess volume  after 1 week and  after 2 weeks of compression therapy, without statistically significant differences. The percentage reduction in WAC  was comparable in both groups  significantly decreased in both groups only after 1 week .The level of physical functioning that was comparable before the treatment , while in the CB group, significant changes were observed both after the first and second weeks . A better improvement in decreasing disease-related symptoms was noted in the CB group (p = 0.001)  .p = 0.049). Moreover, women from the ACW group more frequently reported complications related to compression . The level of compliance regarding the application of compression over 2 weeks in both groups was high.ACW, as a part of CPT, can reduce lymphedema and disease-related symptoms but based on the results it is difficult to recommend this method as an alternative option in the acute phase of CPT among women with advanced arm lymphedema. Rigorously designed high-quality randomized trials with larger sample sizes are needed to verify the effectiveness of ACW in BCRL. This management with ACW could be more effective when performed by an experienced physiotherapist. Education on self-management related to adjustable compression wrap application and compression bandaging is still needed.


These findings inform our understanding of the distribution and intersection of responses to public health lockdown orders in the U.S. and build further evidence of the importance of social connectedness on psychological distress. Lockdown measures enacted in 2020 to control the spread of COVID-19 led to increases in the prevalence of mental health problems. Due to their high-risk status, individuals with chronic diseases may be at increased risk and disproportionately adversely affected by the COVID-19 pandemic. The investigators examined associations between having a high-risk chronic condition, social connectedness, and general distress and COVID-19-specific distress among U.S. adults during the COVID-19 lockdown. Baseline measures of a longitudinal survey collected at the beginning of the pandemic (April to June 2020) were analyzed to identify factors associated with loss of social connectedness from pre- to post-lockdown. The associations between social connectedness and both general and COVID-19-specific psychological distress were adjusted for certain high-risk chronic illnesses and interaction effects. The sample available for analysis included 1354 subjects (262 high-risk chronic diseases and 1092 without chronic illness). Those reporting the loss of social connectedness were younger (median = 39 vs. 42) and more likely to be unemployed because of the pandemic (19.4% vs. 11.0%). Adjustment for interaction demonstrated a stronger negative association between social connectedness change and the psychosocial impact of COVID-19 for those with high-risk illness(es) (change in connectedness*chronic illness OR = 0.88, 95%CI: 0.79–0.98,  Coronavirus disease 2019 (COVID-19) caused by the SARS-COV-2 (severe acute respiratory syndrome coronavirus 2) virus was an unprecedented public health crisis. Governments across the globe initially responded by instituting social distancing guidelines and strict lockdowns involving mandatory stay-at-home orders and the temporary closure of non-essential businesses and schools ,5,6,7,8.Humans are social beings by nature, and the loss of positive social connections and relationships can have profound effects on mental health outcomes . When loEven though the COVID-19 pandemic and associated lockdown affected the entire population, it did not affect all individuals equally. For example, the odds of experiencing depression and anxiety symptoms during the COVID-19 lockdown were 2.5 times higher for low-income individuals compared with high-income individuals . IndividDuring the early stages of the pandemic, there was limited investigation into the incipient and unfolding mental health impacts of COVID-19 lockdown policies, particularly on individuals with chronic diseases ; howeverFor several reasons, individuals with chronic diseases may be at increased risk for decrements in social connectedness, and their mental health may be disproportionately adversely affected by the COVID-19 pandemic. First, given the ongoing social and emotional challenges of chronic diseases and their treatment ,30, thesGiven the above, this case–control study examined associations between having a high-risk chronic condition, social connectedness, and general and COVID-19-specific distress among U.S. adults during the COVID-19 lockdown. Specifically, we examined (1) the characteristics associated with loss of social connectedness, (2) the strength of associations between mental health and changes in social connectedness, and (3) whether the pandemic differentially affected those associations between mental health and social connectedness in individuals with high-risk chronic diseases. These findings will hopefully provide useful information for intervention developers on whether greater social connectedness may help to buffer these individuals from the adverse effects on their distress and mental health from this and any future public health lockdowns.This study reports on baseline data obtained from the initial survey of a longitudinal study on the psychosocial and health-behavioral impacts of the COVID-19 pandemic . EligiblSociodemographic variables included reports of respondents’ age, gender, race/ethnicity, education, marital status, household income, number of household residents, whether they lived with someone over 65 (yes/no) or under 18 (yes/no), employment status, and residence zip code and nearest cross streets. Based on the latter, we used the 2010 Rural-Urban Commuting Area (RUCA) codes to define urban and rural areas of residence ,41. RUCAHealth-related variables included chronic illness status and adherence to COVID-19 social distancing and lockdown measures. Concerning the former, individuals reported whether they had a chronic or serious health condition that required medication or management at home (yes/no) and, if so, were asked to specify the condition. To assess adherence with stay-at-home orders, we first asked, “Is the area where you live currently under a ‘Stay-at-Home,’ ‘Safer-at-Home,’ or ‘Shelter-at-Home’ order? (yes/no)”. The sample was restricted to respondents who replied “yes” to this question. We then asked, “To what extent do you currently follow the stay-at-home order?” With regard to social distancing, we asked, “What amount of social distancing do you currently practice?” With regard to other public health behaviors, we asked, “Do you currently practice protective measures?” Response options to all three behavior questions were on an 11-point Likert-type scale from 0 to 10, with higher scores indicating greater endorsement or frequency.The survey asked, “Before/Since the COVID-19 pandemic, how many individuals did you feel close to who live outside your household?” Response options were on an 11-point Likert-type scale from 0 (none) to 11 (10 or more). Change in social connectedness  was computed by subtracting the score prior to the pandemic from the score since the pandemic (range of −10 to 10). This range was then dichotomized to indicate a loss of social connectedness related to the pandemic .General distress was assessed using the 4-item short-form Patient-Reported Outcome Measure Information System (PROMIS) depression and anxiety measures ,43. The COVID-19-specific distress was assessed using the 4-item short form PROMIS Psychosocial Impact of Illness—Negative (PII-N) scale ,47. InstDescriptive statistics were calculated to characterize the sample, including the mean, standard deviation (S.D.), median, range (for continuous variables), and relative frequency . Subsequent analyses focused on bivariate and multivariate associations between changes in social connectedness due to the pandemic and either general or COVID-19-specific psychological distress.This process entailed two steps. In Step 1, we identified factors associated with losses in social connectedness for the overall sample using bivariate tests of statistical significance  and effect size . In Step 2, multivariate logistic regression analysis was conducted to estimate the association between each of the psychological distress outcome variables  and chronic illness status, change in social connectedness, and the interaction between chronic illness status and social connectedness change. All analysis was conducted using STATA v16.1 .Of the 2435 adults who consented to participate, 213 were excluded because they did not pass our survey quality control  and data quality checks . Of the 2222 survey respondents who provided usable data, 1825 responded to the stay-at-home question and 1671 (91.5%) indicated that they were currently under Stay-at-Home orders at the time of the survey. Of those, 262 indicated that they had one of the high-risk chronic diseases of interest  and 1092 reported that they did not have a chronic illness. Thus, the study sample comprised 1354 respondents.Overall, 40.1% of the sample reported a loss of social connectedness, 52.9% reported no change, and 7.9% reported increases in social connectedness . Median p < 0.001) and anxiety ; and an 81% greater odds of reaching the case threshold for COVID-19 specific distress .Consistent, strong associations between a loss of social connectedness and depression and anxiety were found . Individp < 0.001) and anxiety .As p = 0.020; p = 0.49).Adjustment for chronic illness status did not alter the significance of the association between close social connectedness and PII-N . However, the lone instance of interaction between chronic illness and social connectedness demonstrated a stronger negative  association between social connectedness change and psychosocial impact of COVID-19 for those with a chronic condition  which became the focus for this analysis. In addition, the levels of psychosocial distress one standard deviation above a population-standardized mean  in this sample indicates a high level of need for psychosocial support during the time this survey was collected. Finally, survey respondents demonstrated a strong, consistent association between poorer general and COVID-19-specific psychological distress and reduced social connectedness.The lone statistical interaction effect showed a larger tradeoff between loss of close social connectedness and a measure of the emotional and psychological toll (PII-N) specifically related to the pandemic . While pThese findings are notable for providing hindsight into the experiences felt in the early weeks and months of the pandemic. Perhaps more importantly, they also provide useful information for programs responding to future public health crises or addressing the more generalized, ongoing problems of social connectedness and psychological distress. These findings also emphasize the importance of developing treatment plans to improve the community’s response to future public health crises. While the SARS-CoV-2 pandemic was a generational public health disaster, there is also reason to believe that the globe will face more such events in coming years . Such plWhile no effect was identified between loss of contacts and gender or race in this survey, the study indicated that those with a loss of connectedness were less likely to be married, less likely to have a college education, and less overall and COVID-19 specific unemployment. This result suggests there may be other underlying social and economic supports which predict changes to individuals’ social connectedness during the pandemic and perhaps influence the exacerbation or mitigation of general and disease-specific psychological distress responses.Based on these findings, the specific impact of distress from the pandemic, lockdowns, and resulting loss of social connectedness on the needs of those with chronic diseases and what interventions are needed most should be further investigated . EmphasiThe long-term effects of COVID-19 are still unknown, but these findings and previous evidence ,5,6,7,8 As an analysis of a baseline survey, temporality is difficult to establish with this sample and the reported findings represent correlations, not causal relationships. While some items specifically focus on changes due to the onset of the pandemic or community lockdowns, others, such as the general distress measures of depression and anxiety, do not necessarily account for the timing of symptom onset or exacerbation from the pandemic. The self-reported chronic illnesses may be presumed to identify diagnoses that predate the pandemic; however, this is not specifically documented. Both the change in social connectedness assessed pre- and post-lockdown, albeit via recall, and the PII-N measure were worded to assess the impact of COVID-19 specifically.In addition, the entire survey is based on self-reported answers that pose a threat of response bias. For example, those respondents reporting chronic diseases may also present a threat of biased recall if they devoted greater consideration to their social interactions, exposures, or psychological distress effects than other participants.While the study reports findings collected from respondents across the U.S., the participants do not necessarily reflect a representative sample. Demographics, living conditions, and family sizes all differ to varying degrees from national averages. This naturally impacts the generalizability of the findings, which should be interpreted in the context of this sample. Bivariate and multivariate testing also reflect an available case analysis, with listwise deletion of cases with missing values. For this reason, the sample sizes for individual tests are reported in the tables to document the sample size included in each instance appropriately.The chronic illness group is smaller than the healthier comparison group and not a monolith itself. Diabetes and heart and lung diseases are very different conditions with different management needs. They are collapsed in this analysis to reflect the elevated risk of severe illness posed by these conditions, but larger samples of those living with these chronic diseases should be collected to understand better the heterogeneity of any effects reported here. Finally, the analysis also involves multiple tests for statistical significance with a standard type I error rate of 5%, indicating some degree of risk for false positive results without adjustment. However, the principal findings of the dynamic relationships between social connectedness, distress, and chronic illness within this study are shown to be consistent through multiple testing approaches .The loss of connectedness in one’s social network was heavily associated with poorer psychological distress and mental health during the early months of the 2020 pandemic. The association between the loss of close contacts since lockdowns and COVID-19-specific distress (PII-N) was stronger for those respondents living with and managing chronic illnesses that put them at higher risk for severe COVID-19. A loss of contacts was also associated with living situation and unemployment during the pandemic, among other things. These findings inform our understanding of the distribution and intersection of responses to public health lockdown orders in the U.S. They also build further evidence of the importance of social connectedness on psychological distress more generally. In the event of ongoing or new public health crises, psychosocial interventions targeting individuals identified as high-risk for disease and death should be developed and rapidly implemented.


While compliance with preventive measures remains central to limit the spread of COVID-19, these measures critically affected mental health of young adults. We therefore investigated the association between the level of compliance with COVID-19 preventive measures and depressive symptoms among young adults in Canada and France.From October to December 2020, we conducted a cross-sectional online survey of young adults ages 18–29 years in Canada (n = 3246) and France (n = 2680) to collect demographic data, experiences with COVID-19 preventive measures, and mental health. Depressive symptoms were assessed by the Patient Health Questionnaire-9 (PHQ-9). Compliance profiles were built using cluster analysis. Weighted multivariable logistic regression was used to estimate associations between compliance level and major depressive symptoms (PHQ-9 score≥15) in each country.One third of respondents reported major depressive symptoms . Four compliance profiles were identified: high (42.5%), medium-high (21.7%), medium-low (18.1%), and low (17.7%), with high levels more frequently observed in Canada compared to France. In both countries, participants in low compliance profile (Canada: Adjusted Odds Ratio (AOR) [95% Confidence Interval] 0.75 , France: AOR 0.60 ), in the medium-low , and medium-high compliance profiles  were less likely to report major depressive symptoms compared to the high compliance profile. Ethno-racial minorities, sexual and gender minority, and unemployed young adults had higher odds of reporting such symptoms.Major depressive symptoms were associated with high compliance with COVID-19 preventive measures among young adults. The implementation of socially-isolating measures should be coupled with mental health interventions to address mental health needs of young adults, with enhanced supports for sub-groups who are structurally disadvantaged . Since the beginning of the COVID-19 pandemic, various jurisdictions around the world implemented public health preventive measures to prevent the spread of the virus –4. ThrouPreliminary evidence collected in the first months of the COVID-19 pandemic (March-August 2020) highlights that young adults (<30 years) had lower levels of engagement in some preventive behaviors, including physical distancing and hygiene measures, than older adults –11. PrevTo date, research examining the association between depression and compliance with COVID-19 preventive measures has been mainly conducted among adults, and these results are equivocal. For example, several studies showed that adherence to distancing behaviors and staying at home was associated with increased risk for depression –23 whileThe objective of this study was therefore to investigate the association between the level of compliance with multiple COVID-19 preventive measures and depressive symptoms among young adults living in Canada and France. We hypothesized that we would observe a significant association between the levels of compliance with COVID-19 preventive measures and depressive symptoms, such that those who report lower levels of compliance will experience lower levels of depressive symptoms. Our hypothesis is based on the assumptions that young adults who were highly compliant to socially restrictive COVID-19 measures would report fewer opportunities to connect with family/friends. As such, they would be less likely to receive and benefit from social supports, which would lead to an increased risk of experiencing depressive symptoms.France-Canada Observatory on COVID-19, Youth health and Social well-being (FOCUS) study, a cross-sectional, online anonymous survey exploring the impact of the pandemic on social and health outcomes among young adults ages 18–29 years in Canada and France. The survey was conducted from the 8th of October to the 23rd of December 2020.Data were collected through the Canada and France are two high-income countries that have been particularly affected by the COVID-19 pandemic, respectively with 3.8 and 28.8 million total number of cases since March 2020 . In bothIn Canada, the first peak of COVID-19 cases started in mid-March 2020 with a major outbreak in the province of Quebec . BetweenIn France, the COVID-19 pandemic spiked dramatically in March-April 2020, mainly in the northeast and the region of Paris. Between March and May 2020, a national lockdown was implemented to control the spread of the pandemic before a gradual reopening of activities and businesses over the summer . The peaQualtrics. On the first page of the online survey, all participants were provided with the study’s objective and details about how to participate. Prior to accessing the online questionnaire, all participants were informed that the completion of the questionnaire implied informed consent. Participants were also informed that they could stop the survey questionnaire at any time. All participants were also provided with an option to enter a draw to win one of three cash prizes . Ethical approval was granted by the University of British Columbia Behavioural Research Ethics Board (H20-02053).Survey participants were recruited through non-probability sampling using online posts and advertisements on social media platforms  and university websites, and word of mouth. Additional efforts were made to reach underrepresented populations and geographic areas by using targeted ads from demographic criteria available on social media platforms . Participants were eligible if they were: (1) between the age of majority  and 29 years; resided in Canada or France; and (2) able to complete the survey in English (Canada) or French (either country). The questionnaire comprised four major sections: sociodemographic, social life and experiences during the pandemic (including questions about COVID-19 preventive measures), access to social and health services, and health outcomes . In order to ascertain the acceptability of the questionnaire, we invited 10 youth (n = 5 in each country) to pre-test the questionnaires and provide insights about the format, content and sequencing of the questionnaire, including whether questions were clear and the responses available for each question were appropriate. Survey data were collected using Qualtrics to access our online questionnaire , screening time and duration of survey completion, and checking for inconsistencies across each new submission [To ensure survey security and protect our online survey from fraudulent submissions (including duplicate submissions and “bot” attacks), we used several preventive methods including setting up security survey options in our survey tool bmission . Furtherbmission .The population for the present study included participants of the FOCUS study who had complete data on socio-demographics, COVID-19 preventive measures, and mental health questions. Therefore, participants who had missing information on socio-demographics, the questions about the COVID-19 preventive measures or did not complete the depression scale were excluded.Depressive symptoms within the past two weeks were measured using the Patient Health Questionnaire-9 (PHQ-9) , a valida priori determined that these measures were not conceptually linked to mental health in the same manner as the socially-isolating measures and therefore were not included in the construction of compliance profiles.Our primary exposure was the level of compliance with COVID-19 preventive measures. Using a multiple-choice question with ten response options, we asked participants whether they took any actions to decrease their risk of getting or transmitting COVID-19 in the past 6 months. The following five socially-isolating preventive measures were used to build a COVID-19 compliance profiles variable : staying home from work or school, only taking essential trips, avoiding social gatherings of over 10 people, avoiding meeting friends, and maintaining a social bubble at home. Five other preventive measures were collected including health behaviors , and hygiene practices ; however, we The covariates included the following socio-demographic characteristics: age, gender identity, sexual orientation, province/region of residence, area of residence , highest degree of education, employment status, and living arrangements. In Canada, ethno-racial identity was collected using the Canadian Institute for Health Information standards . In Franetc.) due to the COVID-19 pandemic. Given the limited number of participants who reported a positive test for COVID-19 , we did not include the results of the tests in our analysis.To best capture the climate of uncertainty regarding the evolution of the COVID-19 pandemic and the economic downturn that young adults experienced at the time of the survey , we included four other covariates in our analysis. Level of concern for COVID-19’s impact was assessed by asking the following questions: “How concerned are you about the impact of COVID-19 on: (1) the economy and businesses; and (2) the uncertainty of the future”. Response options were classified in low (not or a bit concerned) and high level of concern (quite or very concerned). We also asked participants if they have: (3) been tested for COVID-19 in the past 6 months (yes versus no), and (4) lost any individual income  they are empirically demonstrated explanatory factors  associated with depression –49, and Using data from both countries, we conducted a cluster analysis to identify COVID-19 compliance profiles. The K-means method of cluster analysis was applied to classify participants into mutually exclusive groups, using Euclidean distances with cluster centers based on least squares estimation (SAS PROC FASTCLUS procedure) . The numUnadjusted and adjusted associations between major depressive symptoms (PHQ-9 score ≥15) and level of compliance were estimated using multivariable logistic regression, adjusted for all covariates listed above. In our models, participants with high compliance were considered as the reference group because both Canadian and French health authorities recommended at the time of the survey to comply with the COVID-19 preventive measures included in our profile construction . In our multivariate logistic regression models see , we use Of the 8424 participants of the FOCUS survey, 89.6% completed the initial sociodemographic information. Of these, we excluded those who did not respond to the COVID-19 preventive measures (n = 383), and mental health questions (n = 1286), resulting in a final study sample of 5926 . Participants excluded  were more likely to come from France (61.1% vs. 38.9%), be younger , identify as men (38.4% vs. 29.5%) and as straight/heterosexual (65.5% vs. 59.5%), live in medium or small cities (53.5% vs. 46.5%), report a lower education level  compared to the participants included in this analysis see . ParticiFour COVID-19 compliance profiles were identified . In the In multivariable analyses , compareIn both countries, young adults who identified as non-binary or with a gender identity other than man or woman , and those who identified as bisexual  or as a sexual minority  had higher odds of reporting major depressive symptoms. Young adults who self-identified as Indigenous in Canada , and descendants of immigrants in France  had higher odds of reporting major depressive symptoms. Furthermore, being unemployed  was associated with higher odds of reporting major depressive symptoms than those who were employed. Similar associations were found with having a high concern about the uncertainty of the future .One third of young adults who participated in our study reported major depressive symptoms. In both countries, participants with lower levels of compliance with COVID-19 preventive measures were less likely to experience major depressive symptoms. Similar high prevalence trends of moderate-to-severe depressive symptoms (PHQ-9 score≥10) were observed elsewhere among young adults in Canada (67%)  and amonOur study also identifies an association between the level of COVID-19 preventive measure compliance and depressive symptoms. During the first year of the pandemic (March-December 2020), young adults who were highly compliant with socially-isolating preventive measures had less opportunities to engage with peers and to reduce time in isolation. These experiences may have been particularly challenging for young people ages 18–29, a period of the life course in which key social and professional developments are occurring. For example, several studies in the US identified multiple COVID-19-related stressors that may have contributed to the increased levels of depressive thoughts among students, such as decreased social interactions, disruptions to sleeping patterns, decline in physical activity, or spending more time on screens –65. In pFurthermore, this association between compliance to COVID-19 preventive measures and depressive symptoms may partly be explained due to the differences in prevalence of depression between Canada and France, given that a higher proportion of participants with low levels of compliance were found in the French sample. This may be related to a higher prevalence of attitudes of distrust in the government actions and communication toward preventive measures in France compared to Canada, two contextual factors which are known to be critical determinants when designing and implementing campaign of prevention that requires a large-scale behavioral change . In FranOur findings also highlight that specific sub-groups of young adults reported higher rates of depressive symptoms. In both countries, sexual and gender minority youth were more likely to report major depressive symptoms compared to their heterosexual counterparts. Previous studies showed that sexual and gender minority youth experienced financial difficulties, limited access to gender-affirming resources, and increased experiences of discrimination, which therefore may increase the risk for depression –75. Our Our study was conducted among a large and diverse sample of young adults, which allowed us to compare some population characteristics  that have been rarely explored in previous COVID-19 studies among young adults. Our findings enabled us to further discuss the contextual and social-cultural factors that may have influenced the prevalence of depressive symptoms and the level of compliance in two high-income countries significantly impacted by the pandemic.There are also several limitations. First, we used a non-probability sampling design and most participants were recruited via advertisements on social media. To reduce this bias, we then conducted analyses in each country on a sample that was weighted by age, gender, and province/region of residence. While this weighting procedure enables us to present greater extrapolation of our findings to the Canadian and French young adults’ population, our weighted samples are still not fully representative of the young adult population in Canada and France, which limits our ability to generalize these findings to all young adults living in both countries. Furthermore, our recruitment process might have led to the self-selection of respondents more concerned with COVID-19 than the general population. Second, our cross-sectional design does not allow us to clarify underlying causal mechanisms onto the association between compliance and depression. Third, we did not assess the participants’ history of mental health diagnostics.These findings provide critical insights into the association of socially-isolating public health measures and depressive symptoms among young adults. The implementation of such measures should be coupled with mental health support interventions to address the timely mental health needs of young adults, with recognition that those who are highly compliant with these measures may be more likely to experience depression. These kinds of interventions should be designed in a way to support the mental health needs of young adults who are structurally disadvantaged , as these are the mostly likely to be negatively impacted by public health restrictions.Our findings showed that young adults were engaged in COVID-19 preventive behaviors and also experienced high levels of depressive symptoms in Canada and France. Those who were more likely to be compliant with COVID-19 preventive measures reported higher prevalence of depressive symptoms. As such, this study provides new evidence in favour of the development and promotion of strategies that enhance access of young adults to equitable and non-judgemental mental health services. This is especially important for young adults who experienced various forms of social exclusion  during the COVID-19 pandemic.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.