Updated World Health Organization (WHO) treatment guidelines prioritize all-oral drug-resistant tuberculosis (DR-TB) regimens. Several poorly tolerated drugs, such as amikacin and para-aminosalicylic acid (PAS), remain treatment options for DR-TB in WHO-recommended longer regimens as Group C drugs. Incomplete treatment with anti-TB drugs increases the risk of treatment failure, relapse, and death. We determined whether missed doses of individual anti-TB drugs, and reasons for their discontinuation, varied in closely monitored hospital settings prior to the 2020 WHO DR-TB treatment guideline updates.We collected retrospective data on adult patients with microbiologically confirmed DR-TB between 2008 and 2015 who were selected for a study of acquired drug resistance in the Western Cape Province of South Africa. Medical records through mid-2017 were reviewed. Patients received directly observed treatment during hospitalization at specialized DR-TB hospitals. Incomplete treatment with individual anti-TB drugs, defined as the failure to take medication as prescribed, regardless of reason, was determined by comparing percent missed doses, stratified by HIV status and DR-TB regimen. We applied a generalized mixed effects model.Mycobacterium tuberculosis with resistance to rifampicin and isoniazid (multidrug-resistant TB [MDR-TB]) without resistance to ofloxacin or amikacin, and 102 (42%) had resistance to ofloxacin and/or amikacin. Most patients (129 [53%]) had multiple hospitalizations and DST changes occurred in 146 (60%) by the end of their last hospital discharge. Incomplete treatment was significantly higher for amikacin (18%), capreomycin (18%), PAS (17%) and kanamycin (16%) than other DR-TB drugs (P<0.001), including ethionamide (8%), moxifloxacin (7%), terizidone (7%), ethambutol (7%), and pyrazinamide (6%). Among the most frequently prescribed drugs, second-line injectables had the highest rates of discontinuation for adverse events (range 0.56–1.02 events per year follow-up), while amikacin, PAS and ethionamide had the highest rates of discontinuation for patient refusal (range 0.51–0.68 events per year follow-up). Missed doses did not differ according to HIV status or anti-TB drug combinations.Among 242 patients, 131 (54%) were male, 97 (40%) were living with HIV, 175 (72%) received second-line treatment prior to first hospitalization, and 191 (79%) died during the study period. At initial hospitalization, 134 (55%) patients had We found that incomplete treatment for second-line injectables and PAS during hospitalization was higher than for other anti-TB drugs. To maximize treatment success, interventions to improve person-centered care and mitigate adverse events may be necessary in cases when PAS or amikacin (2020 WHO recommended Group C drugs) are needed. After SARS-CoV-2, tuberculosis (TB) is the deadliest infectious disease globally and most TB high-burden countries are not on track to reach World Health Organization (WHO) End TB Strategy targets . Drug-reSouth Africa has among the highest global incidence rates of DS-TB and DR-TB ,6. In 20Mycobacterium tuberculosis transmission ) with most hospitalized twice (83/129 [64%]) or three times (23/129 [18%]) during one treatment period. A higher proportion of patients with multiple hospitalizations was HIV-negative (84/145 [58%]) than HIV-positive (45/97 [40%]).The median duration of monitoring treatment doses during all hospitalizations was 331 days  and did not differ by HIV status. Overall hospital-based percent missed doses of anti-TB drugs was highest for amikacin (18%), capreomycin (18%), PAS (17%), and kanamycin (16%) .A generalized logistic mixed effects model showed that odds of receiving doses (vs. missing doses) of clofazimine, ethambutol, ethionamide, isoniazid, moxifloxacin, ofloxacin, pyrazinamide, and terizidone were significantly higher than odds of receiving doses of capreomycin , but not kanamycin or PAS. The odds of receiving doses (vs. missing doses) of amikacin were significantly lower than odds of receiving doses of capreomycin (P<0.001). The odds of receiving doses did not vary by HIV status . Number of hospitalizations was not significantly associated with received doses of any anti-TB drug  of all reasons for treatment discontinuation, although reasons varied widely per drug .Drug discontinuation due to adverse events was highest for amikacin (1.02 events per year follow-up), kanamycin (0.7 events per year follow-up), and capreomycin (0.56 events per year follow-up). Rifafour and linezolid also had relatively high rates of discontinuation due to adverse events, though these were infrequently prescribed during our study. The highest rates of discontinuation due to patient refusal or absconding, among frequently prescribed drugs, were for amikacin (0.68 events per year follow-up) and PAS (0.57 events per year follow-up). Streptomycin had the highest discontinuation rate (1.65 events per year follow-up) but was only prescribed to 2 study patients.Among the anti-TB drugs with the highest percent missed doses, PAS is the only oral drug included in the most recent WHO MDR-TB treatment recommendations list (Group C) . A cumulTo verify the impact of discrepant health professional documentation on recorded research data and to verify data captured by novice data capturers we did in-depth data quality control for 134/242 (55%) study patients. No errors affecting treatment data reporting or study outcomes were noted in 114/134 (85%) cases. In the 20 cases where treatment data, as recorded by researchers, were revised, two were due to updated study specific standard operating procedures, three due to data capture errors and 15 due to incorrect treatment dose counting by data capturers.In this study we found that hospital-based incomplete treatment with individual anti-TB drugs varied considerably. Overall missed doses of PAS and the second-line injectable drugs  were higher (16–18%) than the other anti-TB drugs commonly included in DR-TB regimens. Doses received of other most commonly used anti-TB drugs exceeded 92%. PAS and second-line injectable drugs were considered core drugs in MDR and XDR regimens during the study period.Efforts to eliminate injectable drugs from DR-TB treatment regimens are supported in the 2020 updated WHO guidelines on DR-TB, with recommendations for all-oral shorter and longer regimens . HoweverBecause PAS is an oral medication that may still be used in some WHO-recommended longer regimens, we assessed factors associated with complete treatment of PAS and found that previous drug-susceptible TB was independently associated with lower completion of PAS. Similarly, Batte and colleagues found that previous TB was associated with overall poor adherence to MDR-TB treatment at a referral hospital in Uganda . The reaThe high percent missed doses of amikacin and PAS may have been related in part to continuation of prescribed doses of these drugs despite repeated patient refusal. If prescriptions for these drugs would have been discontinued earlier, upon patient refusal, duration of recorded amikacin and PAS treatment would have been shorter and the percent missed doses would have been lower. Adjustments to treatment regimens due to patient refusal of drugs may have facilitated a more patient-centered approach to treatment. However, limited availability of viable treatment alternatives during the study period may have contributed to extended treatment periods with PAS despite frequent patient refusal.The higher percent missed doses of PAS and injectable drugs did not differ according to HIV status. We were unable to compare incomplete treatment of ART and anti-TB drugs due to differences in ART medication capture in hospital records. However, adherence to XDR-TB treatment was found to be significantly lower than adherence to ART in a previous study in South Africa .To our knowledge, this is the first study to determine hospital-based incomplete treatment of individual DR-TB drugs in the Africa region. Wang and colleagues assessed treatment interruption in MDR-TB patients in China using hospital records and self-report . ConsistPrior to decentralization of DR-TB care in South Africa, hospital-based DR-TB treatment was routinely done for many reasons, including to control and oversee administration of expensive medications, allow for monitoring of adverse drug events, and increase treatment adherence in general . SeveralAnti-TB drug adherence, particularly hospital-based adherence, relies on multiple interactive factors including patient perceptions and behavior, the extent of multi-disciplinary teamwork, medication supply chain, education and training of staff, and regular quality improvement of adherence support ,41. FurtDuring our medication chart review we at times noted medication record discrepancies such as implausible medication administration  and differences between physician prescription orders and prescription information recorded on prescription charts. Support for accurate prescription chart documentation, as a health systems improvement measure, may assist optimizing assessment of patient completion of treatment. Evidence of incomplete treatment is critical for optimal patient care, since it allows clinical decisions such as change of regimen and support for continuation of care.The definition of adherence is generally limited to completeness of treatment related to active patient choices, though may more broadly include other reasons for missed doses, such as specified lab abnormalities in clinical trials . BecauseThe high overall mortality in our study cohort  is similWhen medications that are frequently refused or poorly tolerated by patients need to be included in treatment regimens , approaches to improve patient completion of treatment and ensure reliable recording of treatment data that are more effective and less restrictive to patients should be considered. For example, implementation of digital technologies that can monitor and remind patients to take medication have the potential to be more patient-centered and successful ,48. The Our study had several limitations. The patients in our cohort were not representative of all DR-TB patients. Patients were selected based on serial drug-susceptibility testing, were more likely to be sicker and to have had previous exposure to first and second-line drugs. Furthermore, after decentralization and deinstitutionalization of DR-TB treatment, patients were mainly admitted to the hospital due to severity of illness. All these factors may have been associated with prior non-completion of treatment and missed doses during hospitalization. Our study patients may have been less likely to complete treatment with anti-TB drugs, even in the hospital setting, than other DR-TB patients. On the other hand, the severity of illness may have prompted patients to be more careful in taking their medication. Further studies, including qualitative assessments of patient and healthcare worker experience of completion of treatment, and evaluation of adherence support mechanisms, may help improve understanding of inpatient incomplete treatment.Our analyses were primarily descriptive, particularly in reporting in-hospital incomplete treatment. The retrospective nature of the dataset prevented more inferential analyses that accounted for treatment after hospital discharge, and our results should be interpreted only in terms of medication completion during hospitalization.Our analysis of drug incomplete treatment was limited by what was recorded on prescription charts. We investigated and corrected errors found during data quality checks but were not able to resolve all apparent prescription chart errors. Since we captured reasons for discontinuation of drugs as recorded in the prescription charts and medical records, we could have misclassified reasons for discontinuation. For example, a drug may have been recorded as having been discontinued due to treatment interruption when it was truly discontinued due to an adverse event. Focused pharmacovigilance studies on hospitalized DR-TB patients may provide additional insight into the relationship between treatment completion, drug tolerability, and adverse events. Healthcare provider education and training on the impact of accurate documentation on patient care and on research is vital .We did not have access to anti-TB drug treatment data from all hospitals where patients received DR-TB treatment, including missing prescription charts during hospitalizations. Excluding periods when patients did not receive a drug for >7 consecutive days from missed dose calculations could have resulted in underestimation of percent missed doses. Prospective hospital and community-based anti-TB drug adherence studies, including the use of improved adherence monitoring technology, is essential given the change to newer anti-TB drugs and shorter duration of DR-TB treatment.Incomplete DR-TB treatment was not uniform during hospitalization, with percent missed doses to amikacin, kanamycin, capreomycin, and PAS higher than other anti-TB drugs. Our study was unable to distinguish whether missed doses occurred due to poor tolerability of anti-TB drugs or patient-driven factors. However, we found that the injectable drugs were discontinued frequently due to adverse effects and both amikacin and PAS were frequently discontinued due to patient refusal. Patient-centered approaches to adherence monitoring and treatment support are particularly warranted when drugs with better completion and tolerability than amikacin and PAS (2020 WHO Group C drugs) are unable to be used.S1 File(PDF)Click here for additional data file.S2 File(CSV)Click here for additional data file.S3 File(CSV)Click here for additional data file.S4 File(CSV)Click here for additional data file.S5 File(CSV)Click here for additional data file.S6 File(CSV)Click here for additional data file.S7 File(CSV)Click here for additional data file.


Previous research has shown that school can be an influential context to promote students' physical activity engagement, physical fitness, and motor competence. The purpose of this study was to investigate the effectiveness of a 5-month-long intervention program that aimed to increase students' motor competence and physical fitness during school days.SD = .33) students from five schools participated in the study. At the beginning of the study, students were divided into experimental and control groups on purpose. The intervention consisted of three components: a) weekly 20 minutes sessions of guided training during a regular PE lesson, b) weekly 20 minutes sessions of guided training during recess and c) daily 5 minutes long activity breaks during academic lessons. Intervention activities aimed to increase different elements of physical fitness and motor competence. One week before and one week after the intervention period students' physical fitness levels were measured by 20-meter shuttle run (cardiorespiratory fitness), curl-up and push-up (muscular fitness) tests, and motor competence by 5-leaps (locomotor skills) and throwing-catching-combination (object control skills) tests.A quasi-experimental intervention design with pre- and post-tests was implemented. Altogether 325 Finnish Grade 5 . Moreover, univariate analysis revealed that students in the experimental group performed significantly better in 20-meter shuttle run test , curl-up , push-up  and throwing-catching-combination . There were no differences between experimental and control groups in 5-leaps test .Repeated measures MANOVA indicated that there was a multivariate interaction effect between experimental and control groups over time (F  = 7.52, p=.000, partial ηThe intervention program appeared to be effective in increasing students' cardiorespiratory fitness, muscular fitness, and object control skills. This indicates that guided school-based physical activity programs can be influential in promoting physical fitness and motor competence among school children.


While recent advances in plant single-cell RNA sequencing (scRNA-seq) have made numerous strides in identifying novel regulatory events, transcriptional profiling of certain cell types, such as phloem poles, has not yet been thoroughly investigated. A recent article by Otero et al. utilized cell-type specific marker lines and a second-generation single-cell approach to uncover transcriptomic landscapes specifying protophloem-adjacent cells, as well as identify a set of important transcription factors (TFs) signifying early phloem development. For instance, Shahan et al. recently constructed an organ-scale single-cell transcriptomic map in Arabidopsis root2. However, such a global approach may not completely capture the intricate gene regulation carried out by cell subpopulations that are spatially adjacent but undergoing distinct differentiation programs, owing to the inadequate sequencing resolution in specific root areas. For instance, phloem poles, structures involved in long-distance transport of sugar and other metabolites, are characterized by four heterogeneous cell types: protophloem sieve elements, metaphloem sieve elements, phloem pole pericycles and companion cells. As most of these cell types play an important role in phloem pole development, they were found underrepresented in previous scRNA-seq studies. To deconvolute this heterogeneity, Otero et al.3 combined cell-type specific marker lines, fluorescence-activated cell sorting and SMRT-sequencing technologies to obtain high-resolution scRNA-seq profiles within protophloem sieve element-neighboring regions across developmental stages3  has established high-resolution cell-type specific atlases that provide insight into both shared and distinctive transcriptome signatures across diverse cell types in developing plantses3 Fig. . The aut3. Developmental trajectories analysis further resolved clusters representing early, undifferentiated stages of cells that were prone to three different cell fates: metaphloem sieve element (cluster 8), phloem pole pericycle (cluster 9), and companion cell (cluster 10). Interestingly, these protophloem sieve element-adjacent cells show similar co-expression patterns even after differentiation, leading to a better understanding of how protophloem sieve elements rely on their surroundings before and after enucleation3. The authors also managed to identify early metaphloem sieve elements in clusters 10 and 1, suggesting the existence of intertwining cell fates during phloem morphogenesis3. Finally, a group of TFs pertaining to the DNA-binding with one finger (DOF) family, PINEAPPLEs (PAPLs), were validated as downstream targets of PHLOEM EARLY DOF (PEAR) genes in early phloem. PAPLs appear to be of critical importance to sugar transport into root, but further study is needed to characterize their precise contributions to nutrient allocation3.Subsequently, the authors developed a high-quality scRNA-seq dataset encompassing 10,204 phloem pole cells, from which they inferred 15 representative clusters with diverse cell identities and developmental statuses3. This study also outlines a technical framework that can potentially be extended to other plant organs to determine spatiotemporal gene regulation both at steady state and under diverse environmental conditions.In summary, this study provides a broad perspective of the developmental trajectories of the phloem poles as well as highlights the critical importance of DOF TFs to phloem development


The cardiovascular event rate decreased significantly from 0.632 events/year to 0.080 events/year (p < 0.001). Conclusions: Pemafibrate therapy might have the potential to lower triglyceride/HDL-cholesterol ratio and decrease cardiovascular events.Background: Pemafibrate is a novel selective peroxisome proliferator-activated receptor-α modulator, which was demonstrated to reduce serum triglyceride level with few drug-related adverse events in phase II and III clinical trials. However, its clinical implication in real-world practice remains unknown. Triglyceride/HDL-cholesterol ratio is a surrogate of small dense LDL-cholesterol, which is a newly proposed cardiovascular risk factor independent of LDL-cholesterol levels. Methods: Consecutive patients who received pemafibrate between April 2020 and September 2021 and continued therapy for at least 3 months were included in this retrospective analysis. The primary outcome was the trend in triglyceride/HDL-cholesterol ratio during the 3-month treatment period. The change in cardiovascular event rate between the one-year pre-treatment period and the on-treatment period was also analyzed. Results: A total of 19 patients  were included and continued pemafibrate therapy for 3 months without any drug-related adverse events. Sixteen were add-on and three were conversions from other fibrates. Triglyceride/HDL-cholesterol ratio decreased significantly from 5.85  to 3.14  ( Low-density lipoprotein (LDL)-cholesterol-lowering therapy with statins can reduce the risk of incident cardiovascular diseases considerably , whereasPemafibrate is a novel selective PPARα activator that was recently introduced with an expected improvement in efficacy and safety compared with traditional fenofibrate in prior cohort studies ,10,11,12Consecutive patients who were initiated on pemafibrate for the first time between April 2020 and September 2021 and continued pemafibrate for at least 3 months to treat hypertriglyceridemia were retrospectively included in this study. Some of them received pemafibrate as a first fibrate and others received pemafibrate as conversion from other fibrates. Those who received pemafibrate previously or those who initiated pemafibrate before the study period were excluded. Written informed consents were obtained from all participants before the listing. The institutional review board approved the study protocol . Laboratory data including lipid parameters were assayed by standard laboratory procedures. All serum and plasma samples were obtained just before the initiation of pemafibrate as baseline data and 3 months later as follow-up data in a fasting condition and frozen at −80 degrees immediately. We defined the change in triglyceride level relative to HDL-cholesterol as the primary outcome. Triglyceride-rich lipoprotein-cholesterol was calculated as follows: total cholesterol−(LDL-cholesterol and HDL-cholesterol) .Demographics, comorbidities, and medication data were obtained just before pemafibrate initiation as baseline characteristics. Cardiovascular events including heart failure, stroke, and ischemic heart disease were counted during the one-year pre-treatment period and during the pemafibrate treatment period. The change in cardiovascular event rate stratified by time of pemafibrate initiation was defined as the secondary outcome. p < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS Statistics 23 .Continuous variables are presented as median  irrespective of their distribution. Categorical variables are presented as numbers and percentages. The trend in continuous variables was assessed by Wilcoxon signed-rank test. Event rates were compared between the pre-treatment period and the treatment period by negative binomial regression analysis. A value of A total of 19 patients were included. Median age was 63  years old and 74% were men . Thirteep < 0.001; p = 0.001). Triglyceride/HDL-cholesterol ratio decreased from 5.85  to 3.14   mg/dL to 156  mg/dL . Following pemafibrate therapy, the ratio decreased significantly irrespective of the existence of diabetes mellitus (p < 0.05 for both).Twelve patients had diabetes mellitus. The baseline triglyceride/HDL-cholesterol ratio was statistically not different between those with and without diabetes mellitus . Hemoglobin, estimated glomerular filtration ratio, and plasma B-type natriuretic peptide levels remained unchanged during the 3-month pemafibrate therapy . During the pemafibrate therapy  days), one cardiovascular event (worsening heart failure) was observed. Event rates decreased from 0.632 events per year to 0.080 events per year  Three-month pemafibrate therapy decreased triglyceride/HDL-cholesterol ratio significantly. (2) Urine protein level decreased following the 3-month pemafibrate therapy. (3) The cardiovascular event rate was lower during the pemafibrate therapy compared to the pre-treatment period. Pemafibrate may be a superior alternative to conventional fibrates, including fenofibrate, in improving hypertriglyceridemia, maintaining relatively lower drug-related adverse event rates . The safWe validated the efficacy and safety of pemafibrate therapy in our real-world clinical practice in patients with a variety of comorbid conditions. All patients who received pemafibrate were included without any strict restrictions. All patients continued pemafibrate therapy without drug-related adverse events that required drug termination. We focused on the impact of pemafibrate on triglyceride/HDL-cholesterol ratio, instead of triglyceride alone. The triglyceride/HDL-cholesterol ratio is a recently-introduced surrogate of small dense LDL-cholesterol , which iAlthough we did not measure small dense LDL-cholesterol directly, three-month pemafibrate therapy may decrease the burden of small dense LDL-cholesterol levels, irrespective of the concomitant lipid-lowering therapy or conversion from other fibrates. Furthermore, we observed in this study that pemafibrate decreased triglyceride-rich lipoprotein-cholesterol, which was very recently introduced and demonstrated to be associated with incremental cardiovascular risk .We observed a decrease in urine protein levels following three months of pemafibrate therapy. A few studies have investigated the impact of pemafibrate on renal function in the clinical setting. In mice with diabetic nephropathy, pemafibrate therapy decreased albuminuria via inhibition of renal lipid content and oxidative stress . In anotUnderstanding that the presence of small dense LDL-cholesterol increases cardiovascular risk independent of LDL-cholesterol level, it is reasonable to hypothesize that pemafibrate would reduce cardiovascular events by lowering small dense LDL-cholesterol. We observed a lower cardiovascular event rate during pemafibrate therapy compared to the pre-treatment period (without pemafibrate). An ongoing PROMINENT study , which iOur study was comprised of a small cohort size with short-term observational period. Given the small sample size, we assumed all variables as non-parametric data irrespective of their distribution. Non-significance in this study does not indicate similarity. This is a proof-of-concept preliminary study, and further larger-scale studies are warranted to validate and expand our findings, although it should take longer clinical experience of pemafibrate therapy in real-world practice. We lack a control group and just compared the clinical variables between baseline and 3 months later. The medications including pemafibrate remained unchanged during the treatment period, but other confounders might have affected the outcomes. Given the retrospective nature of this study and a lack of control group, we observed just a potential association between pemafibrate therapy and clinical variables, but cannot infer causality. Pemafibrate therapy might be associated with a lower triglyceride/HDL-cholesterol ratio and risk of incident cardiovascular events, although definite conclusions cannot be derived from this small sample-sized study. Larger-scale longer-term studies are warranted to validate and strengthen our findings. Of note, further trials are needed to better assess the reduction in the degree of atherosclerosis, lipid parameters including small dense LDL-cholesterol, and cardiovascular risk in patients receiving pemafibrate therapy.


Coronavirus disease 2019 (COVID-19) is identified as the pneumonia and acute respiratory distress syndrome caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). The intravascular thrombotic phenomena related to the COVID-19 are emerging as an important complication that contribute to significant mortality.We present a 62-year-old man with severe COVID-19 and type 2 diabetes. After symptomatic and supportive treatment, the respiratory function was gradually improved. However, the patient suddenly developed abdominal pain, and the enhanced CT scan revealed renal artery thrombosis. Given the risk of surgery and the duration of the disease, clopidogrel and heparin sodium were included in the subsequent treatment. The patient recovered and remained stable upon follow-up.Thrombosis is at a high risk in patients with severe COVID-19 pneumonia because of hypercoagulable state, blood stasis and endothelial injury. Thrombotic events caused by hypercoagulation status secondary to vascular endothelial injury deserves our attention. Because timely anticoagulation can reduce the risk of early complications, as illustrated in this case report. The past research shows that COVID-19 can cause arteriovenous thromboembolism in most organ systems . Among tA 62-year-old man with a history of type 2 diabetes presented with fever that started 5 days ago. Cough, fatigue, or abdominal pain were not present. At admission, the body temperature was 36.7 °C, and the patient was diagnosed with SARS-CoV-2 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) assay. Vital signs on presentation revealed heart rate of 76 beats/minute, respiratory rate of 20 breaths/minute, and blood pressure of 117/65 mmHg. A chest computed tomography scan showed ground glass-like shadows multiple consolidations in the both upper lobes  Infection Treatment Plan Guide , the cor9-nCoV InIn this case, renal artery thrombosis suddenly occurred during the treatment of COVID-19 and subsequently led to left renal threatening ischemia. The laboratory test indicating thrombotic complications was elevated D-dimer. Previous studies have shown that elevated D-dimer was a risk factor for death in patients with SARS-CoV-2 infection, especially in elderly patients , 8. The Thrombotic events caused by hypercoagulation status secondary to vascular endothelial injury deserves our attention. Because timely anticoagulation can reduce the risk of early complications.


KIT, HGF, NT5E, PROM1, CD33, ANPEP, CDH2, IL1B, and CXCL2) among the hubs were further validated as possible diagnostic ETP-ALL markers using another gene expression dataset (GSE78132) with 17 ETP-ALL and 27 non-ETP-ALL samples. Linear dimensionality reduction analysis with the expression levels of the hub genes in ETP-ALL revealed their divergent inclinations towards different hematopoietic lineages, proposing them as novel indicators of lineage specification in the incompletely differentiated ETP-ALL blasts. This further led to the formulation of a personalized lineage score calculation algorithm, which uncovered a considerable B-lineage-bias in a substantial fraction of ETP-ALL subjects from the GSE28703 and GSE78132 cohorts. In addition, STRING-derived physical interactome of the potential biomarkers displayed complete segregation of the B-lineage-skewed markers from other lineage-associated factors, highlighting their distinct functionality and possible druggability in ETP-ALL. A panel of these biomarkers might be useful in pinpointing the dominant lineage specification programmes in the ETP-ALL blasts on a personalized level, urging the development of novel lineage-directed precision therapies as well as repurposing of existing therapies against leukemia of different hematopoietic lineages; which might overcome the drawbacks of conventional chemotherapy.Early T precursor acute lymphoblastic leukemia (ETP-ALL) exhibits poor clinical outcomes and high relapse rates following conventional chemotherapeutic protocols. Extensive developmental flexibility of the multipotent ETP-ALL blasts with considerable intra-population heterogeneity in terms of immunophenotype and prognostic parameters might be a target for novel therapeutic interventions. Using a public gene expression dataset (GSE28703) from NCBI GEO DataSets with 12 ETP-ALL and 40 non-ETP-ALL samples, such heterogeneity was found to be reflected in their transcriptome as well. Hub genes were identified from the STRING-derived functional interaction network of genes showing differential expression between ETP-ALL and non-ETP-ALL as well as variable expression across ETP-ALL. Nine genes ( T cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic neoplasm of the T lymphocytic compartment, accounting for 15 and 25% of total pediatric and adult acute lymphoblastic leukemia (ALL) cases, respectively . The disIn spite of a relatively low rate of incidence among children (11%) as well as adults (7.4%), the clinical outcome for ETP-ALL is often remarkably poor; even worse than other T-ALL subtypes . HoweverSeveral studies have explored the genetic traits of ALL samples and have identified various mutational and transcriptional signatures unique to ETP-ALL . AlthougAgainst such a backdrop, this study explored the ETP-ALL transcriptome available on public databases to pinpoint the hubs from a functional interaction network of genes showing significant difference in expression between ETP-ALL and non-ETP-ALL subjects as well as substantial variance among the ETP-ALL subjects themselves. Transcript levels of the genes, therefore, might not only classify ALL into ETP-ALL and non-ETP-ALL, but might further categorize ETP-ALL into separate subclasses based on their differential lineage inclinations. This may potentiate the invention of novel precision therapies targeting different lineage propensities, which might eliminate the shortcomings of conventional chemotherapy. Besides, the findings might open new avenues for the prospective use of B-cell acute lymphoblastic leukemia (B-ALL) or acute myelogenous leukemia (AML)-directed therapeutic modalities against ETP-ALL in a case-by-case manner.GSE28703 and GSE78132) containing normalized gene expression data from ETP-ALL and non-ETP-ALL leukemic blasts were selected from NCBI Gene Expression Omnibus (GEO) DataSets (GSE13159) was used to evaluate gene expression levels in acute leukemia of mature leukocytes  as well as progenitor/precursor-B-cell acute lymphoblastic leukemia (pro/pre-B-ALL). Detailed information regarding the datasets is provided in The flow of work adopted in this study is depicted in DataSets  after a DataSets . AnotherThe unsupervised, agglomerative hierarchical clustering-based dendrogram, constructed on iDEP.92  with topIdentification of differentially expressed genes (DEG) between sample groups was performed on iDEP.92 using the limma function with fold-change >2 and FDR  <0.1. Genes with standard deviation >2 in expression values within the ETP-ALL group were selected as variably expressed genes within ETP-ALL. Gene expression heatmaps of differentially/variably expressed genes were created on Heatmapper . Venn diKnowledge-based protein-protein interaction maps involving genes of interest were retrieved from STRING  and visup-value <0.01 and overlap >5 genes were mapped onto the pathway network. Edge thicknesses on the networks described the relative overlap in genes between the two gene set nodes. Gene set enrichment analysis (GSEA) against the ‘GO biological process’ (for pathways) and ‘TF.Target.TRRUST’ (for transcription factors) databases for ETP-ALL samples with higher and lower levels of hub gene expression than the corresponding cohort mean was performed on iDEP.92, with FDR <0.2. Pathway enrichment on Cytoscape was carried out using the ‘STRING Enrichment’ function on the ‘StringApp’ plugin  analysis on ROCplot . MagnituThe pairwise correlation matrix of all ETP-ALL and non-ETP-ALL samples, constructed on iDEP.92, was composed of Pearson’s correlation coefficients between each pair of samples, denoting their whole transcriptomic correlation. Linear dimensionality reduction in terms of principal component analysis (PCA) with normalized expression values of selected genes in ETP-ALL was carried out on ClustVis . NormaliFor prediction of personalized scores indicating net lineage skew in leukemic blasts from ETP-ALL patients, expression values of each hub gene were normalized with respect to the population mean expression values of the respective genes. Next, the normalized expression values were transformed to a fold-change value with respect to the stem-like condition by the following formula:Lineage scores were further computed as geometric means of transformed expression scores of all genes displaying skew towards individual lineages . Box plots represented the mean and interquartile range. Whiskers extended till the 5th and 95th percentile, while remaining points were shown as outliers. Violin plots, constructed on BoxPlotR , additioCD5 expression between the two groups  on ROC plots were comprehensively higher (>0.75) than those of the others . Reliability of the classification performances by the genes between ETP-ALL and non-ETP-ALL in terms of true positivity rate and true negativity rate, as observed on the corresponding confusion matrices  were selected as candidate diagnostic biomarkers of ETP-ALL.After requisite quality assessments , a secon dataset , concord dataset . AUC pare others . Three gmatrices , was alsCD7 and HES1 varied in concordance with CDH2 expression (CD19 and EBF1 significantly varied with NT5E levels (IL7R (common lymphoid marker) and CEBPA (myeloid marker) along with CDH2 and NT5E in individual ETP-ALL subjects  inverse correlation with stemness marker CD34  reinforced the proposed biomarkers as indices of lineage bias in ETP-ALL , while IL1B correlated best with pediatric ALL and considerably with AML  and B-lineage (purple) clusters, respectively; while PROM1 existed in the stemness (orange) cluster. Unlike KIT, HGF, and ANPEP belonging exclusively to the myelo-monocytic (red) cluster, CXCL2 was present in the overlapping zone between B-lineage and dendritic cell-lineage (green) clusters. CD33 and IL1B were assigned to a separate cluster of uncertainty (grey) owing to their promiscuity in terms of lympho-myeloid specification. Of note, this grey cluster was located right between the B-lineage and stemness clusters, suggestive of their inclination towards a state in between stem cell-like pluripotency and lineage induction.Understanding the developmental predisposition of the leukemic blasts from ETP-ALL patients might potentiate the use of existing treatment modalities targeting lineage-restricted, mature acute leukemia against ETP-ALL. Considerable consistency was observed in terms of lineage-skewed expression of myeloid-biased ed CXCL2  in ETP-Ar-B-ALLs . Albeit  ETP-ALL , highligwith AML . NT5E, od origin . Agglomed origin . CDH2 anPROM1 was selected as reference standard for transformation of the expression levels of individual hub genes into comparable scores. Furthermore, transformed scores for different lineages for individual patients were calculated by considering the geometric means of the personalized transformed score(s) of all the markers inclined towards individual lineages. For example, normalization and transformation of the hub gene expression levels in the GSM710933 sample from the GSE28703 ETP-ALL cohort revealed a strong myeloid bias within the leukemic blasts . Therefore, mining the symbiosis among the total physical interactome of these genes was of utmost importance, as any mode of therapeutic interventions against them is expected to perturb the functioning of all these interactors together. Although enrichment analyses based on the physical interaction networks of the individual genes unveiled the downstream functions performed by their individual interactomes , this waKIT+HGF+ANPEP+NT5E+CDH2−PROM1+CXCL2+CD33+IL1B+, which might be used in conjunction with the conventional biomarkers , compared to those between CD34 and the corresponding lineage markers proposed in this study . This indicates the ETP-ALL blasts to exist in an intermediate state between absolute stemness and complete lineage fixation, where the expression levels of the proposed markers might act as better indicators of specification than the levels of the mature-stage lineage markers. Close inspection of the physical interactome of the proposed markers, hence, might be profitable in defining the cellular processes associated with the lineage-priming checkpoints within ETP-ALL, which might be ideal therapeutic targets. Since some of the markers are even cell-surface expressed, they might also be exploited for targeted delivery of therapeutics specifically to the ETP-ALL blasts. In fact, CD33-targeted delivery of IMGN779 against ETP-ALL in vitro has already yielded promising results (The incompletely differentiated ETP-ALL blasts are not true mimics of the differentiated leukemic blasts from B-ALL or AML; resonated by their high levels of stem cell-associated gene expression . Therefo results , making The considerable B-lineage inclination in a sizeable fraction of ETP-ALL samples  coupled Multiple studies have uncovered the molecular phenomena behind the lineage plasticity of ETPs, and have designated certain genes as barcodes of particular specification programmes in these multipotent cells . However


Single-cell multi-omics (scMulti-omics) has brought transformative insights into immuno-oncology, demonstrating success in describing novel immune subsets and defining important regulators of antitumor immunity. Here, we give examples of how scMulti-omics has been used in specific tumor studies and discuss how this may develop in the future. The mixture of cell subpopulations in tumors is considered one of the important characteristics for drug resistance, metastasis, and disease relapse. The presence of diverse immune cells in a tumor microenvironment (TME) may profoundly affect clinical outcomes. One significant challenge in immuno-oncology is identifying the heterogeneity of immune cells in tumors and their differentiation process. Traditional profiling approaches, such as flow cytometry or mass cytometry, rely heavily on pre-existing knowledge and cell-type defining markers. Bulk transcriptional analyses dilute the contribution of a small subset of immune cells in the overall gene expression pattern. To overcome these limitations, a scMulti-omics study can offer detailed identification of diverse immune subsets at a higher resolution and provide an opportunity to understand the contribution of immune cells to tumor progression.1. These modalities include DNA, gene expression, chromatin accessibility, chromatin architecture organization, histone modification, protein, T/B cell receptors, and DNA methylation status  define tumor and immune cell identity in different patient groups, (b) infer the heterogeneous nature of diverse immune repertoires, (c) understand the communication between cancer cells and immune cells and the molecular mechanisms underlying cellular heterogeneity within the TME, and (d) accelerate the discovery of novel pathogenesis and therapeutics in many cancer types.More than 30 single-cell sequencing technologies have been established to allow the interrogation of multiple modalities that characterize different genetic and epigenetic sequencing information in a cell simultaneouslytus Fig. . Further4: (a) intra-modality integration where the same modality  are measured from different cells (unmatched data), (b) unmatched inter-modality integration where multiple modalities  are measured from different cells, samples, or experiments, and (c) matched inter-modality integration where multiple modalities are measured from the same cell.The integration of scMulti-omics data can be categorized into three types+ T cells from six cancer types and discovered a previously underappreciated tumor-infiltrating follicular regulatory T cell group. This cell subset can effectively suppress antitumor T cells and is associated with resistance to anti-PD-1 therapy5. The second advantage is to enable the discovery of a wide spectrum of different immune cell types and their gene markers. Zhang et al. profiled and integrated scRNA-seq data of 397,810 T cells from 316 patients of 21 cancer types, and depicted the pan-cancer landscape of T cells (including 17 CD8+ and 24 CD4+ subclusters) in the TME6. Specific markers, such as TNFRSF9 (in regulatory T cells), ZNF683 and CXCR6 (in tissue-resident memory T cells), and GZMK (in effector memory cells), were identified in each subtype. The third advantage is integrating different sequencing technologies and leveraging their unique features7. For example, using one Smart-Seq2 (deep sequencing depth and high sensitivity) scRNA-seq and 10X Genomics (suitable for detecting large cell populations due to its massive throughputs) scRNA-seq data from CD45+ immune cells, Zhang et al. identified LAMP3+ dendritic cells as an important cell type originating from tumors, migrating to hepatic lymph nodes, and shaping the lymphocyte function through antigen-specific priming8. The fourth advantage is the ability to build single-cell atlas, such as the tumor immune atlas9, in order to provide a comprehensive compendium of immune cells and an inspection of gene expression patterns in different immune cell types.Here, we provide four experimental examples to demonstrate the advantages of intra-modality integration of multiple single-cell RNA sequencing (scRNA-seq) data compared to the analysis of individual datasets Fig. . The fir+ cells, which linked these two CD8+ subset populations in one developmental pathway. These results provide crucial evidence to support that early transitional CD8+ cells progressively differentiate into dysfunctional T cell states10. In the second example, scientists used scRNA-seq and single-cell sequencing assay for transposase-accessible chromatin sequencing (scATAC-seq) on KMT2A-rearranged acute lymphocytic leukemia to uncover significantly increased lineage plasticity in younger leukemia patients11. They also identified an immunosuppressive signaling circuit between cytotoxic lymphocytes and leukemic cells, providing clinical implications for molecularly targeted and immunotherapy approaches. In this circuit, natural killer (NK) T cells produce interferon-gamma IFNγ to activate leukemic cells; in turn, these leukemic cells employ inhibitory molecules such as transforming growth factor beta (TGF-β) to suppress cytotoxic T and NK cells. The third example showcased that protein abundance, gene expression, and chromatin accessibility can be integrated to identify biological networks linking cancer/immune-specific relations among genes, such as cis-regulatory elements, TFs, and cancer-related peak-to-gene linkages13. Specifically, Granja et al. used Seurat14 to couple the above three modalities measured in six mixed-phenotype acute leukemia samples13. They observed common malignant signatures across patients and patient-specific regulatory features, and they identified 91,601 putative peak-gene linkages and key TFs  that regulate marker genes in leukemia .Compared with the studies only using an individual single-cell sequencing dataset, the unmatched inter-modality integration has shown advances in detecting tumor intrinsic and extrinsic factors affecting critical subpopulations. Here, we provide three examples to showcase how the integration led to accurate cell subpopulation prediction and characterization by combining unique features from different modalities Fig. . The fir15, where matched gene expression and protein abundances are quantified from the same cell. Leader et al. applied CITE-seq to profile gene expression and 81 antibodies from eight non-small cell lung patients16. Their study showcased that CITE-seq allowed for highly accurate CD4+ and CD8+ T cell clustering and annotation that scRNA-based clustering could not completely resolve . Second, scRNA-seq can be jointly sequenced with spatial transcriptomics to delineate communication between different subsets of immune cells in TME. Pelka et al. profiled the scRNA-seq of 371,223 cells and matched spatial transcriptome data from 45 regions of interest in three colorectal tumor samples with high CXCL13 T cell program activity17. They discovered spatially organized cell-cell interactions that contribute to a coordinated multi-cellular immune response in human colorectal tumors. Specifically, the IFNγ derived from T cells can induce expression of CXCR3 ligand to attract more activated IFNG + and CXCL13 + T cells and CXCL10/CXCL11 + myeloid cells to form spatially organized foci within human tumors. Lastly, the joint profiling of scRNA-seq and scATAC-seq can enable a precise definition of cell types and their differentiation states, offering a unique opportunity to discover novel TFs and epigenetic mechanisms and build dynamic gene regulatory networks18. Unfortunately, no immuno-oncology study has been published using this kind of scMulti-omics technology in the public domain as of today.The matched inter-modality integration takes the power of joint profiling of scMulti-omics with minimum cell-wise and modality-wise biases to build more reliable connections among modalities Fig. . Compare20. Second, multiple computational tools have been developed to integrate scMulti-omics data in a generic style21, but not particularly designed or optimized for data analysis in immuno-oncology. For example, the number of features in dimension reduction and the resolution in Louvain clustering can be tailored higher in immuno-oncological scMulti-omics data than those used for normal tissues or cell lines. Also, acknowledged marker genes and signatures  can be included in the data analyses to auto-correct the cell clustering result. Third, current methods have limited power to understand the cross-talk between cells and different modalities. This limits the application of scMulti-omics data for inferring the underlying biological networks of diverse cell types, elucidating the response of these networks to external stimuli in a specific cell type13, and discovering the molecular programs that drive transitions from one cell type to another in TME. Last, as the data complexity increases , computational efficiency becomes more critical and requires scalability to handle huge amounts of data.There are still several challenges for applying scMulti-omics in immuno-oncology. First, batch effect removal is one of the main obstacles in accurate integrative analyses, which needs to retain the true signals and remove differences between samples, conditions, and experiments. Experimentally, the joint profiling of multiple modalities from the same cell rather than separating sequencing from different cells can greatly minimize the batch effect; and computationally, the selection of appropriate tools to handle the batch effect can be guided by the existing benchmarking methods22). Such databases can create a path towards innovative studies in tool development and optimization, and provide opportunities for the potential integration of different modalities across different cancer types, species, and treatment conditions. With the increased generation of scMulti-omics data, deep learning will revolutionize tool development and single-cell data analysis, as deep learning frameworks are powerful in extracting features from complex data in a hypothesis-free manner23. For example, a deep graph representative learning framework  can be used to extract and learn the appropriate features of different modalities in order to characterize cellular heterogeneity. It has a great potential to identify the joint embeddings of cells and multiple modalities synergistically, with a heterogeneous graph model that includes cells, genes, chromatin peaks, and other epigenetic elements in the same graph (Fig. 24 (Fig. We envisage more scMulti-omics data and computational tools becoming available for integrative analysis in immuno-oncology. As more data is generated, databases that systematically collect processed single-cell data in immuno-oncology are needed (e.g., TISCHaph Fig. . In addi 24 Fig. .Fig. 2De


Background: Povidone-iodine and chlorhexidine gluconate are commonly used antiseptics that have broad antiviral properties, including against SARS-CoV-2. Nasal and oral antisepsis is a possible option to reduce viral transmission; however, effectiveness data are limited. The acceptability of this method for adjunct infection control is also unknown. We are conducting a clinical randomized controlled trial (NCT04478019) to evaluate the effectiveness and feasibility of nasal and oral antisepsis to prevent COVID-19. Methods: Healthcare and other essential workers with in-person job duties were recruited into a 10-week clinical trial. Participation did not require in-person activities: all communication was web- or telephone-based, supplies were shipped directly to the participant, and participants self-collected specimens. Participants completed a 3-week intervention and 3-week control phases and were randomized to the timing of these phases  had enrolled. Moreover, 20 adverse effects have been reported, including skin irritation, epistaxis, and mouth discoloration; 9 participants withdrew due to side effects. Laboratory analyses are ongoing to measure effectiveness in reducing SARS-CoV-2 viral load. We performed an interim analysis of intervention acceptability. Survey responses were given on a Likert scale of 1  to 5 (extremely). Although 36% of respondents (n = 74) reported on the postsurvey that the intervention was less acceptable than they had expected on the presurvey, the overall acceptability measure was still relatively high (3.76) Disclosures: None


Coronavirus (CoV) disease (COVID-19) identified in Wuhan, China, in 2019, is mainly characterized by atypical pneumonia and severe acute respiratory syndrome (SARS) and is caused by SARS CoV-2, which belongs to the Coronaviridae family. Determining the underlying disease mechanisms is central to the identification and development of COVID-19-specific drugs for effective treatment and prevention of human-to-human transmission, disease complications, and deaths.Here, next-generation RNA sequencing (RNA Seq) data were obtained using Illumina Next Seq 500 from SARS CoV-infected A549 cells and mock-treated A549 cells from the Gene Expression Omnibus (GEO) (GSE147507), and quality control (QC) was assessed before RNA Seq analysis using CLC Genomics Workbench 20.0. Differentially expressed genes (DEGs) were imported into BioJupies to decipher COVID-19 induced signaling pathways and small molecules derived from chemical synthesis or natural sources to mimic or reverse COVID -19 specific gene signatures. In addition, iPathwayGuide was used to identify COVID-19-specific signaling pathways, as well as drugs and natural products with anti-COVID-19 potential.Here, we identified the potential activation of upstream regulators such as signal transducer and activator of transcription 2 (STAT2), interferon regulatory factor 9 (IRF9), and interferon beta (IFNβ), interleukin-1 beta (IL-1β), and interferon regulatory factor 3 (IRF3). COVID-19 infection activated key infectious disease-specific immune-related signaling pathways such as influenza A, viral protein interaction with cytokine and cytokine receptors, measles, Epstein-Barr virus infection, and IL-17 signaling pathway. Besides, we identified drugs such as prednisolone, methylprednisolone, diclofenac, compound JQ1, and natural products such as Withaferin-A and JinFuKang as candidates for further experimental validation of COVID-19 therapy.In conclusion, we have used the in silico next-generation knowledge discovery (NGKD) methods to discover COVID-19-associated pathways and specific therapeutics that have the potential to ameliorate the disease pathologies associated with COVID-19. COVID-19 is characterized by symptoms ranging from a mild cold to more severe illnesses, such as SARS, sudden stroke, gastrointestinal complications, and multiple organ failure, even leading to death in some patients.,5,7 COVID-19 is highly transmissible and pathogenic compared with other viral infections, and the exact mortality rate has yet to be determined because the pandemic is not yet under control in several countries, resulting in unprecedented protective measures, partial or complete lockdowns, travel restrictions, etc. As of March 7, 2022, COVID-19 had already infected more than 446 million people in 195 countries and territories around the world and killed approximately 6 million people, according to data from the Johns Hopkins Coronavirus Dashboard. However, the exact mortality rate will not be calculated or determined until the COVID-19 epidemic reaches a plateau. The United States of America and WHO have declared the SARS-CoV-2 outbreak a public health emergency because it is more contagious than the severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV).,8,9 SARS-CoV-2 possesses a nucleocapsid with a positive-sense RNA genome. Host cells express SARS-CoV-2 nucleoproteins and the nucleocapsid protein (N protein), which is the most abundant, highly immunogenic protein, and is required for CoV RNA synthesis. The N protein is a structural protein that binds to the CoV RNA genome and forms a capsid around viral RNA. However, the spike protein (S protein) is critical for binding between SARS CoV-2 and angiotensin-converting enzyme 2 (ACE2) surface receptors on host cells  has renamed this nCoV as SARS-CoV 2, which is the causative agent of COVID-19.,12 deciphering the underlying pathological mechanisms is central to identifying and developing COVID-19 specific drugs to effectively treat and prevent human-to-human transmission, COVID-19 complications, and deaths. In silico methodologies can be successfully used to identify potential drugs and natural products based on high-dimensional RNA-seq datasets derived from various disease pathologies.,14 We have recently shown that the next-generation knowledge discovery (NGKD) platforms can effectively be used to uncover the gene signatures regulated by COVID-19 and the potential therapeutics using RNAseq datasets derived from normal human primary bronchial epithelial (NHBE) cells. However, in the present study, the raw RNA Seq reads (single-end) (FASTQ files) in quadruplicate obtained from SARS CoV-infected A549 cells and mock-treated A549 cells using Illumina Next Seq 500 were obtained from the Gene Expression Omnibus (GEO) (accession number: GSE147507) and quality control (QC) was evaluated before RNA Seq analysis using CLC Genomics Workbench 20.0 . After the initial QC, the RNA Seq reads were imported into the CLC Genomics Workbench 20.0  before RNA Seq analysis and evaluated using NGKD platforms such as BioJupies and iPathwayGuide  to decipher the disease-specific molecular signatures and a series of small molecules derived from either synthetic or natural sources to mimic or reverse the COVID-19 gene signatures.Although COVID-19 vaccines are currently available as preventive measures and many are in the research and development phase,,14Animal models and human subjects were not used in this study. This study was performed using RNA-seq datasets from next-generation sequencing experiments with A549 cells. The raw data were obtained from the Gene Expression Omnibus (GEO), as indicated in the Data Source section below. Therefore, they were exempt from institutional review board (IRB) approval. and were used for subsequent downstream analysis with high-throughput NGKD platforms.Raw RNA Seq reads (single-end) (FASTQ format) in quadruplicate obtained with Illumina Next Seq 500 from A549 cells infected with SARS CoV-2 and mock-treated A549 cells were obtained from the Gene Expression Omnibus (GEO) (accession number: GSE147507) to obtain the differentially expressed genes (DEGs) before RNA Seq analysis.Raw RNA Seq reads (single-end) in quadruplicates (FASTQ files) derived from SARS CoV-infected A549 cells and mock-treated A549 cells using Illumina Next Seq 500 were derived from the GEO, and quality control (QC) was evaluated using CLC Genomics Workbench 20.0 (Qiagen)RNA Seq reads were imported into CLC Genomics Workbench 20.0 (Qiagen) after the QC step. The RNA Seq Analysis Tool in the Biomedical Genomics Analysis plugin of the CLC Genomics Workbench was used to extract all annotated transcripts using both Homo sapiens (hg38) _genes (Gene track) and Homo sapiens (hg38) _mRNA (mRNA track) and mapped to the human reference genome (GRCh38). A gene expression track (GE) was generated for A549 cells infected with SARS CoV-2 and corresponding mock reads (test vs. control). In addition, the differential expression tool was used in the two groups in the CLC Genomics Workbench to perform a statistical test for differential expression for a set of expression tracks (test vs. control). Here, a multifactorial statistic based on a negative binomial generalized linear model (GLM) is used, and the differential expression in the two groups tool deals with one factor and two groups. In this analysis, “Total Exon Read” values were used for GE. Differentially expressed genes (DEGs) were generated for the test compared to the corresponding control and used for further downstream analysis using the NGKD platform. In Biojupies, RNASeq datasets were compressed into an HDF5 data package and uploaded to Google Cloud. Raw data were normalized to log10 counts per million (log CPM) and differentially expressed genes between the control and experimental groups were determined using the R package limma. The principal component analysis function in the Python module of sklearn was used to transform log CPM based on the Z-score method to generate the PCA plot, and Clustergrammer was used to generate interactive heat maps, and the DEGs were then sent to Enrichr. In the volcano plot, DEGs were plotted on the x-axis and P values were corrected using the Benjamini-Hochberg method, transformed (−log10), and plotted on the y-axis.,21 However, average gene expression is shown on the x-axis in the MA plot, and P values were corrected, transformed (−log10), and plotted on the y-axis using the Benjamini-Hochberg method.,21 Gene Ontology (GO) and pathway enrichment analyses were performed with both upregulated and downregulated genes in Enrichr. Significant GO terms and pathways  were calculated using a cut-off value of < 0.1 after applying the Benjamini–Hochberg correction.,21BioJupies was used to analyze the DEGs generated using the CLC Genomics Workbench to identify novel signaling pathways, disease-specific gene networks, and a range of drugs and small molecules derived from natural sources to mimic or reverse disease-specific gene signatures. Similarly, the L1000FWD analysis was performed by submitting the top 2000 DEGs to the L1000FWD signature search API.The L1000CDS2 analysis was performed by submitting the best 2000 DEGs to the L1000CDS2 signature search API. in the iPathwayGuide was used to determine the differentially regulated signaling pathways, gene ontologies, and upstream drugs or natural products, as previously described. Briefly, the pathway score was calculated based on the p-value obtained using Fisher’s method. The P value was corrected using multiple testing corrections for the false discovery rate (FDR) and Bonferroni correction.,26 The FDR has significant power, but it controls only the family-based false-positive rate.,21 Pathways and gene interactions with DEGs were generated using the KEGG database. For each Gene Ontology term (GO), the number of DEGs annotated with the term was compared with the randomly expected DEGs.,29 iPathwayGuide used an overrepresentation approach to calculate the statistical significance of observing at least the specified number of DEGs.–32 The hypergeometric distribution was used to calculate P values in the iPathwayGuide analysis and corrected for multiple comparisons using FDR and Bonferroni.–32The impact analysis method (IAM)–32The prediction of upstream chemicals, drugs, and toxicants (CDTs) was based on two types of information: (i) the enrichment of DEGs from experiments and (ii) a network of interactions from the Advaita Knowledge Base (AKB v2012).–32 For each CDT u, the number of consistent DE genes after u, DTA(u), is compared to the number of measured target genes expected to be both consistent and DE. iPathwayGuide uses an over-representation approach to calculate the statistical significance of observing at least a given number of consistent DE genes. The P value Ppres was calculated using a hypergeometric distribution.–32 The analysis uses Fisher’s standard method to combine the P values into a test statistic.The research hypothesis refers to the presence of CDT. This hypothesis is useful for investigating whether a given phenotype is influenced by the presence of a particular chemical, drug, or toxicant.–32In parallel with the upstream CDTs predicted to be present, Pabs and Pz were used to predict upstream CDTs that were absent. This hypothesis is important when investigating whether a given phenotype is affected by the absence of a particular chemical necessary for the proper functioning of the organism or cell. The research hypothesis states that the upstream CDT is insufficient under the conditions under study. For each upstream CDT u, the number of consistent DE genes downstream of u, DTI(u), was compared to the number of measured target genes expected to be both consistent and DE by chance. Using Fisher’s method, the analysis combines Pabs and Pz, with Pz considered only for significantly negative z-scores (z ≤ −2).,35 Ligand-based target prediction for both prednisolone and withaferin-A was performed as previously described.,36The isomeric simplified molecular-input line-entry system (SMILES) codes of prednisolone and withaferin-A were used in the SwissTarget Prediction tool to identify protein targets.,37,38 The Open Targets Platform uses scientific evidence to assess and rank associations between targets and disease and to help prioritize targets. The query list of approximately 100 candidate molecular targets of prednisolone and withaferin-A was used to discover protein targets significantly (P < .05) associated with COVID-19.The Open Targets Platform web tool was used to uncover the molecular targets of prednisolone and withaferin-A associated with COVID-19 disease pathology  The raw RNA Seq reads (Single-End) (FASTQ files) in quadruplicates derived using Illumina Next Seq 500 from SARS CoV-infectedA549 cells, and mock-treated A549 cells were obtained from the Gene Expression Omnibus (GEO) (GSE147507), and quality control (QC) was evaluated before RNA Seq analysis using the CLC Genomics Workbench 20.0 (Qiagen). The DEGs were further analyzed using BioJupies and iPathwayGuide  to decipher disease-specific signatures and an array of drugs and small molecules derived from natural sources to mimic or reverse disease-specific gene signatures.The present study was done using RNA-seq datasets obtained from next-generation sequencing experiments with mock-treated and SARS CoV-2 infected A549 cells.The global patterns in the high-dimensional RNA-seq datasets were uncovered using PCA analysis Fig. A. The ClWithania somnifera was found to reverse the COVID-19 induced molecular signatures in both L1000CDS2 and L1000FWD analyses along with other small molecule drugs.The bar chart Fig. A shows tP value) for each term, and significant terms enriched in each GO category are highlighted in bold. Similarly, Figure P value) for each term, and the significantly enriched pathways  are highlighted in bold.The GO enrichment analysis for the biological processes, molecular function, and cellular components was generated using Enrichr Fig. . The x-aP value cut-off (.05) and a fold change cut-off of 1.5. The DEGs were analyzed in the context of pathways obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, gene ontologies from the Gene Ontology Consortium database, and iPathwayGuide analysis, which further showed that 34 pathways were significantly affected in the SARS CoV2 infected A549 cells compared to the mock-treated A549 cells. In addition, 557 Gene Ontology (GO) terms, 224 gene upstream regulators, 451 chemical upstream regulators, and 31 diseases were found to be significantly (P < .05) enriched before the correction for multiple comparisons.In this experiment, 141 DEGs were identified from a total of 9665 DEGs obtained from BioJupies analysis of the RNASeq reads of SARS CoV-infected A549 cells and mock-treated A549 cells based on a The top five upstream regulators identified after the Bonferroni correction for signal transducer and activator of transcription 2 (STAT2), interferon regulatory factor 9 (IRF9), interferon-beta (IFNβ), interleukin-1-beta (IL-1β), and interferon regulatory factor 3 (IRF3) were predicted to be activated Table .q value) were identified using iPathwayGuide. The top identified biological processes were innate immune response, response to external biotic stimulus, response to other organisms, response to biotic stimulus, and defense response to other organisms, including chemokine receptor binding, chemokine activity, CXCR chemokine receptor binding, receptor-ligand activity, signaling receptor activator activity. The top cellular components identified included blood microparticles, fibrinogen complexes, nuclear outer membranes, extracellular spaces, and extracellular regions for each pruning type , interleukin-8 (IL-8), tumor necrosis factor-alpha (TNF-α), C-X-C motif chemokine ligand 10 (CXCL-10), and interferon-gamma induced protein-10 (IP-10), and contributes to poor prognosis. In the present study, withaferin-A was predicted to counteract the molecular signatures triggered by COVID-19. Using NGKD platforms, we recently found that withaferin-A reverses the gene signatures induced by COVID-19 in NHBE cells.The COVID-19 pandemic is currently being addressed with vaccines, convalescent plasma, monoclonal antibodies, antiviral drugs such as remdesivir, and preventive measures such as wearing masks, hand hygiene, and social distancing.W. somnifera (Indian ginseng or ashwagandha). Its active constituents include withanolides, saponins, alkaloids, and steroidal lactones. W. somnifera is used in herbal preparations in traditional medicine and has antioxidant, anti-anxiety, anti-inflammatory, antibacterial, and aphrodisiac properties, among others,51 Ashwagandha has neuroprotective, cardioprotective, immunomodulatory, and anticancer properties. In a recent in silico screening study, ashwagandha was also found to contain natural compounds against COVID-19.Analysis of the open-target platform revealed that 36 targets played a role in COVID-19 pathology. Withaferin-A is a constituent of the medicinal plant  The traditional Chinese herbal formula, JinFuKang, consists of 12 medicinal plants, with each dose containing 10 mL. JinFuKang has anticancer properties and numerous medicinal benefits. Antiviral remdesivir reduces mortality only very slightly, the use of corticosteroids increases the possibility of secondary infections, and monoclonal antibody therapies are either expensive or difficult to obtain for COVID-19 therapy. However, oral antiviral drugs such as paxlovid and molnupiravir introduced by Pfizer and Merck, respectively, are authorized by the Food and Drug Administration (FDA), USA, for COVID-19 treatment. Nevertheless, it may also be valuable to explore the gene signatures triggered by COVID-19 and its variants in different experimental model systems to identify potential drugs or natural products for COVID-19 therapy.Traditional Chinese Medicine (TCM) has also been used in the treatment of COVID-19.,2 to determine mechanisms of action before preclinical and clinical trials for the potential treatment of COVID-19 and related pathologies. In conclusion, this study outlines a valuable method for applying NGKD platforms to discover precise drugs and natural products for the potential treatment of COVID-19-related disease pathologies.The present study demonstrated the application of RNA sequencing technologies in conjunction with NGKD platforms to decipher specific compounds, either synthetic or derived from natural products, for the potential amelioration of COVID-19. However, further in-depth studies are needed to validate drugs such as prednisolone, methylprednisolone, diclofenac, and JQ1, and natural products such as Withaferin-A and JinFuKang in COVID-19 infection model systems, such as primary human alveolar epithelial cells and human small intestinal organoids (hSIOs)The authors gratefully acknowledge the technical and financial support from King Abdulaziz University, DSR, Jeddah. Saudi ArabiaPNP, LAD, LD, SB, and MR designed experiments. PNP and MR conducted experiments. PNP, LAD, LD, SB, and MR analyzed the data. PNP and MR prepared the manuscript. PNP and MR revised the manuscript. All authors contributed to the editing of the manuscript and scientific discussions.


The role of molecular imaging in IE diagnostic work-up has been constantly growing due to technical improvements and the increasing evidence supporting its added diagnostic and prognostic value. The various underlying molecular processes of 99mTc-HMPAO-SPECT/CT as well as 18F-FDG PET/CT translate to different imaging properties, which should be considered in clinical practice. Both techniques provide additional diagnostic value in the assessment of patients at risk of IE. Nuclear imaging should be considered in the IE diagnostic algorithm, not only for the insights gained into ongoing infection at a molecular level, but also for the determination of the optimal clinical therapeutic strategies.Infective endocarditis (IE) is a growing epidemiological challenge. Appropriate diagnosis remains difficult due to heterogenous etiopathogenesis and clinical presentation. The disease may be followed by increased mortality and numerous diverse complications. Developing molecular imaging modalities may provide additional insights into ongoing infection and support an accurate diagnosis. We present the current evidence for the diagnostic performance and indications for utilization in current guidelines of the hybrid modalities: single photon emission tomography with technetium99m-hexamethylpropyleneamine oxime–labeled autologous leukocytes ( Infective endocarditis (IE) is considered to be a challenging disease both for initial evaluation and subsequent treatment due to complex etiopathogenesis and the presentation. Rising rates of cardiac implantable electronic devices (CIED) implantation in the elderly with the rising number of co-morbidities has led to an increase in the prevalence of cardiac device-related IE (CDRIE) cases ,2,3,4,5.18F-FDG PET/CT) along with single photon emission tomography/ computed tomography with technetium99m-hexamethylpropyleneamine oxime–labeled autologous leukocytes (99mTc-HMPAO-SPECT/CT) . ,15. 2,1599mTc-HMPAO-SPECT/CT examination has high specificity and sensitivity in suspected PVE, especially in case of inconclusive transthoracic echocardiography (TTE) F-ciprofloxacin ability to mark soft-tissue infections [18F]F-fleroxacin capability to image bronchitis [11C]erythromycin between healthy and pneumonic lung tissue [11C]rifampin in patients with tuberculosis has been shown to be able to discriminate accurately affected pulmonary lesions, which has not been confirmed in terms of brain tissue F-fections , [18F]F-onchitis . Althougg tissue . Imagingn tissue ,66. Alth99mTc-HMPAO-SPECT/CT and 18F-FDG PET/CT yield further diagnostic and prognostic value in the assessment of patients at risk of IE, thus should be considered in the IE diagnostic process, according to current indications based on international guidelines. The inclusion of 99mTc-HMPAO-SPECT/CT and 18F-FDG PET/CT into the IE diagnostic process improves the appropriate classification of patients and helps to avoid unnecessary treatment, as well as provides additional information about extracardiac lesions. Although, there have not been yet published data on antibiotic-derived PET tracers and artificial intelligence potential application in IE diagnostic process, their role in the future may increase and translate into clinical practice.Accurate IE diagnosis and multimodality assessment play a crucial role in choosing the best therapeutic approach, which may be involving prolonged antibiotic treatment, cardiac surgery, and complete hardware removal. Since IE has numerous severe complications as well as remains associated with high in-hospital and long-term mortality, thus evolving diagnostic modalities is pivotal for improving outcomes. Nuclear medicine imaging techniques provide additional insight into ongoing IE on a molecular level. The


To assess whether systemic-pulmonary collaterals are associated with clinical severity and extent of pulmonary perfusion defects in chronic thromboembolic pulmonary hypertension (CTEPH).p < 0.05.This prospective study was approved by a local ethics committee. Twenty-four patients diagnosed with inoperable CTEPH were enrolled between July 2014 and February 2017. Systemic-pulmonary collaterals were detected using pulmonary vascular enhancement on intra-aortic computed tomography (CT) angiography. The pulmonary enhancement parameters were calculated, including (1) Hounsfield unit differences (HUdiff) between pulmonary trunks and pulmonary arteries (PAs) or veins (PVs), namely HUdiff-PA and HUdiff-PV, on the segmental base; (2) the mean HUdiff-PA, mean HUdiff-PV, numbers of significantly enhanced PAs and PVs, on the patient base. Pulmonary perfusion defects were recorded and scored using the lung perfused blood volume (PBV) based on intravenous dual-energy CT (DECT) angiography. Pearson’s or Spearman’s correlation coefficients were used to evaluate correlations between the following: (1) segment-based intra-aortic CT and intravenous DECT parameters (2) patient-based intra-aortic CT parameters and clinical severity parameters or lung PBV scores. Statistical significance was set at r = 0.45, p < 0.01). The mean HUdiff-PV was correlated with the mean pulmonary arterial pressure (PAP) , cardiac output , and lung PBV score . And the number of significantly enhanced PVs was correlated with the mean PAP , pulmonary vascular resistance , and lung PBV score .Segmental HUdiff-PV was correlated with the segmental perfusion defect score (PV enhancement measured by intra-aortic CT angiography reflects clinical severity and pulmonary perfusion defects in CTEPH.Intra-aortic CT angiography demonstrated heterogeneous enhancement within the pulmonary vasculature, showing collaterals from the systemic arteries to the pulmonary circulation in CTEPH.• The degree of systemic-pulmonary collateral development was significantly correlated with the clinical severity of CTEPH and may be used to evaluate disease progression.• The distribution of systemic-pulmonary collaterals is positively correlated with perfusion defects in the lung segments in CTEPH.•  Chronic thromboembolic pulmonary hypertension (CTEPH) is a severe progressive pulmonary disease, classified into the fourth group of pulmonary hypertension (PH) in the 2018 Nice classification , 4.Systemic-pulmonary collaterals, a distinctive feature of CTEPH, may play an important role in its pathophysiology –7. Due tIntra-aortic injection of contrast media prevents contamination of enhancements from the right heart system and can be used to detect and estimate bronchial-pulmonary shunt flow . EnhanceWe aimed to evaluate the degree of shunt formation using intra-aortic CT angiography. We assessed whether the degree of contrast enhancement in the pulmonary vasculature, identified by CT angiography after intra-aortic injection, was associated with the clinical severity of CTEPH and pulmonary perfusion defects reflected in lung PBV images.This prospective study was approved by the local ethics committee; written informed consent was obtained from all patients. Twenty-five consecutive patients  diagnosed with inoperable CTEPH based on the current standard criteria between July 2014 and February 2017 were enrolled [α = 0.05, β = 0.20, r = 0.60) for the correlation.Sample size was calculated as previously reported . The totIntra-aortic CT angiography was performed using one of two multidetector CT scanners . An intra-aortic injection into the ascending aorta was performed using a 4-Fr pigtail catheter. A total of 105 ml of 1:3 diluted iodine contrast media  was injected at a rate of 9 ml/s using a power injector , 28. CT Two radiologists, blinded to patient clinical information, evaluated the CT images through visual observations performed with a window width of 350 Hounsfield units (HU) and a window level of 75 HU. Circular regions of interest (ROIs) were placed by consensus where enhancement appeared in the individual vessels on axial images. Multiple ROIs (3–5) were placed across multiple sections of each vessel. The mean CT values of the two highest-enhanced ROIs for each vessel were selected to represent the degree of vascular enhancement in the corresponding lung segment Figs. . MeasureConsidering the haemodynamics of contrast media injected from the ascending aorta at a 9-s scan delay, we assumed that no contrast medium entered the PT. Therefore, we used the HU-PT value as a reference for the non-enhanced intraluminal blood density. We then defined the degree of contrast enhancement in the target segmental vessel as the Hounsfield unit difference (HUdiff), calculated as HU-PA, HU-PV, minus HU-PT. For each patient, the HUdiff values for PAs and PVs were recorded separately for 18 lung segments as HUdiff-PAs and HUdiff-PVs, to represent the degrees of systemic-pulmonary collateral development observed in the PAs or PVs.We recorded the Hounsfield unit standard deviation (SD) of the ROI on the PT for each patient to evaluate the significant enhancement . SignifiFor patient-based analysis, the mean HUdiff-PA and mean HUdiff-PV were calculated as the average values of 18 segmental HUdiff-PA or HUdiff-PV separately for each patient.The total number of significantly enhanced PAs and PVs were calculated separately for each patient.Intravenous DECT angiography was performed within 3 months of intra-aortic CT angiography Fig.  using a The same two radiologists, blinded to the patients’ demographic and clinical information, scored the extent of pulmonary perfusion defects by consensus using both axial and coronal colour-coded lung PBV images. The scoring standards for lung PBV images suggested by Takagi et al were applied   Fig. 5)5). The pWe compared the laterality between the right and left lung for pulmonary vascular enhancement parameters and pulmonary perfusion defects separately as follows: the mean of HUdiff-PA and HUdiff-PV, the percentage of significantly enhanced PAs and PVs, and the mean perfusion defect scores of the 10-right lung segments versus those of the 8-left lung segments.All patients underwent right heart catheterisation (RHC) during the same session as the intra-aortic CT angiography examination. Pulmonary arterial pressure (PAP) , PVR, right atrial pressure (RAP), pulmonary arterial wedge pressure (PAWP), cardiac index (CI), and cardiac output (CO) values were obtained. Brain natriuretic peptide (BNP) levels and 6-min walking distance (6 MWD) were measured within 3 months of intra-aortic CT angiography. No surgical or endovascular interventions were performed during this period.t-test. The HU-PT values, as the reference, were compared between the two groups imaged with different scanners using an independent t-test. Within-subject laterality was evaluated using paired t-test. Intraobserver agreement of pulmonary vascular enhancement data was determined using the intraclass correlation coefficient (ICC). Correlations between the findings of intra-aortic CT angiography, RHC, other clinical parameters, and lung PBV imaging findings were evaluated using Pearson’s or Spearman’s correlation coefficients. To accommodate the use of multiple variables per patient, the standard errors of the variables were estimated using bootstrapping methods with 10,000 samples. Multivariable linear regression analyses were used to assess whether different scanners were confounding factors in the correlation analysis. Statistical computations were performed using IBM SPSS Statistics for Windows (version 21.0. IBM Corp.). Statistical significance was set at p < 0.05.Descriptive statistics were presented as means with SDs for normally distributed variables, medians with interquartile ranges for non-normally distributed variables, and numbers of cases (and percentages) per group for categorical variables. Sex differences in pulmonary vascular enhancement and pulmonary perfusion defect parameters were assessed separately using an independent One patient was excluded from this study because the interval between the two scans was over three months. Consequently, 24 patients were included in the final analysis . Image data were collected from all 24 patients as a total of 432 HU-PAs , 432 HU-PVs , and 24 HU-PTs ; they were calculated into 432 HUdiff-PAs  and 432 HUdiff-PVs . A total of 176 and 224 PAs and PVs were significantly enhanced, respectively, in 24 patients.r = 0.23, p = 0.28) or mean HUdiff-PV . No sex differences were observed in the aforementioned parameters.We calculated the mean HUdiff-PAs  and mean HUdiff-PVs  on the patient base. We also calculated the total number of significantly enhanced PAs  and PVs  on the patient base. Patients’ heart rates during image acquisition were not correlated with mean HUdiff-PA  and calculated lung PBV scores  for 24 patients. No sex differences were observed in the aforementioned parameters.We compared patient-based pulmonary vascular enhancement parameters with clinical severity parameters by using Pearson’s and Spearman’s correlation coefficients. PV enhancement parameters were correlated with several clinical severity parameters. Significant correlations were found between the mean HUdiff-PV and mean PAP, systolic PAP, and CO; the total number of significantly enhanced PVs and mean PAP, systolic PAP, and PVR Fig. . The totr = 0.45, p < 0.01). No correlation was found between the HUdiff-PA and perfusion defect scores .We performed lung segment-based and patient-based evaluations to study the relationship between pulmonary vascular enhancement parameters and pulmonary perfusion defect parameters using Spearman’s correlation. In the lung segment-based evaluation, a positive correlation was found between the HUdiff-PV and perfusion defect scores . A positive correlation was also found between the total number of significantly enhanced PVs and lung PBV score   Fig. . No corrp = 0.21). In multivariable linear regression analyses, the scanners were not identified as significant confounding factors (p = 0.28 – 0.59) in the assessment of correlations between pulmonary enhancement parameters and clinical severity parameters or perfusion defect scores.The Siemens scanner was used in 16 patients , and the Canon scanner was used in 8 patients . The HU-PT values were not significantly different between the two groups , and the total number of PVs with significant enhancement correlated with important clinical severity parameters, including mean PAP and PVR (patient-based). Second, the degree of enhancement in the PV correlated positively with the degree of pulmonary perfusion defects (lung segment-based), and the overall PV enhancement degree correlated positively with the lung PBV score (patient-based). We also found that pulmonary vascular enhancement and pulmonary perfusion defects showed right-sided dominance in the CTEPH group. The observed enhancement in the pulmonary vasculature reflected the first-pass iodine contrast. The contrast medium coursed through a systemic-pulmonary shunt into the PVs. Therefore, the degree of enhancement reflects the degree of systemic collateral development.Our study is the first to assess the detailed segmental distribution of systemic-pulmonary collaterals and verify their value in reflecting CTEPH severity. The positive correlation between the degree of systemic collateral flow and mean PAP and PVR suggests that shunts may play an important role in CTEPH progression. Exposure to high-pressure systemic circulation may induce small-vessel disease, contributing to increased PH and PVR , 6. StudOur study has several limitations. First is the small sample size. Larger studies are required to validate our results. Second, we only assessed the degree of systemic collateral development before CTEPH treatment. Comparisons between changes in the systemic collaterals and clinical severity of CTEPH and changes in pulmonary perfusion and other treatment outcomes are necessary to confirm the clinical value of our study. Third, the time interval between the two CT examinations was not minimised in all patients. However, only chronic patients were enrolled, and their clinical conditions did not change under close management with anticoagulant drugs and vasodilators. Fourth, intra-aortic CT angiography is a feasible technique for assessing systemic-pulmonary collaterals; however, because of its invasiveness, indications should be carefully evaluated by a multidisciplinary CTEPH team in routine clinical settings. Fifth, our results are based on manual measurements. In the future, an alternative automated quantitative tool may be required to improve the reliability of shunt measurements and reduce bias and time consumption caused by manual measurements.In conclusion, intra-aortic CT angiography demonstrated heterogeneous enhancement, reflecting collateral circulation from the systemic arteries to the pulmonary circulation in CTEPH. The mean HUdiff-PV and number of significantly enhanced PVs may help estimate the clinical severity of CTEPH and reflect the extent of pulmonary perfusion defects in patients. Our findings provide a better understanding of haemodynamic changes in CTEPH and provide insight into the management of patients with CTEPH.


Histochemistry for Alcian Blue performed on the tissue harvested from the cubital site reveals myxoid degeneration of the small nerve collaterals, a clear sign of nerve injury. It still remains unclear why the syndrome occurs in a localized and not generalized form to all osteofibrous tunnels. Today, modified messenger ribonucleic acid vaccines as Spikevax® represent an avantgarde technological platform with a lot of potential, but one which needs careful monitoring in order to identify in advance those patients who may experience adverse events after their administration.Coronavirus disease 2019 (COVID-19) is the most dramatic pandemic of the new millennium. To counter it, specific vaccines have been launched in record time under emergency use authorization or conditional marketing authorization and have been subjected to additional monitoring. The European Medicines Agency recommend reporting any suspected adverse reactions during this additional monitoring phase. For the first time in the available medical literature, we report a left cubital tunnel syndrome in a 28-year-old right-handed healthy male after seven days from the first dose of Spikevax Coronavirus disease 2019 (COVID-19) is the most dramatic pandemic of the new millennium. To counter it, specific vaccines have been launched in record time under emergency use authorization or conditional marketing authorization amino}octanoate (SM-102) lipid nanoparticles, plus 1,2-dimyristoyl-rac-glycero-3-methoxypolyethylene glycol-2000 (PEG2000 DMG), 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), acetic acid, cholesterol, sodium acetate, sucrose, trihydrate, trometamol, trometamol hydrochloride and water for injections ..9].Before decompression surgery, an anti-nucleocapsid SARS-CoV-2 γ-immunoglobulins (IgG) test and an anti-spike receptor binding domain (RBD) SARS-CoV-2 IgG test were performed by chemiluminescent microparticle immunoassay (CMIA). The former resulted negative (0.220 UA/mL), while the latter was positive (5816.30 UA/mL).During surgery, entrapment was confirmed A, and th®, thus not completing the primary vaccination course, nor to receive a booster dose.Subsequently, the patient opted not to receive the second dose of Spikevax® is indicated for active immunization to prevent COVID-19 in individuals 12 years of age and older. It is administered as primary course of two doses at a time distance of 28 days from each other [Spikevaxch other . A boostch other .Among the reported adverse reaction there are: arthralgia ≥1/10) , chills  , chillsPreviously, our research group has described two cases of concomitant cubital and carpal syndrome after severe COVID-19 in the non-dominant limb of as many middle-aged male patients admitted to intensive care . SimilarToday, anti-nucleocapsid SARS-CoV-2 IgG CMIA is the serological test of choice to evaluate long-term SARS-CoV-2 infection , while aWhen compared to Guillain-Barré syndrome, which begins in the hands and feet ascending to the arms, legs and upper body within hours or days, it still remains unclear why these events occur in a localized and not generalized form to all osteofibrous tunnels.Our work attempts to describe in depth a new neurological event to keep in mind during COVID-19 vaccination schedule. It allows to add a piece in the complex spectrum of post-vaccinal neurological events, that vary from paresthesia to more serious conditions such as Guillain-Barré syndrome.Tested on humans starting from 2005 at first to fight cancer and then from 2013 against infectious agents, modRNA vaccines represent today an avantgarde technological platform with a lot of potential, but one which needs careful monitoring in order to identify in advance those subjects who may experience more or less serious adverse events after their administration.