In the AMI model, miR-146a-overexpressing MSCs increased infarct size and fibrosis.
 
  The miR-146a/CXCR4 signaling pathway contributes to MSCs migration and homing induced by ATV pretreatment. miR-146a may be a novel therapeutic target for stimulating MSCs migration to the ischemic tissue for improved repair.
 The miR-146a/CXCR4 signaling pathway contributes to MSCs migration and homing induced by ATV pretreatment. miR-146a may be a novel therapeutic target for stimulating MSCs migration to the ischemic tissue for improved repair.Exosomes are cell-secreted nano-sized vesicles which deliver diverse biological molecules for intercellular communication. Due to their therapeutic potential, exosomes have been engineered in numerous ways for efficient delivery of active pharmaceutical ingredients to various target organs, tissues, and cells. In vivo administered exosomes are normally delivered to the liver, spleen, kidney, lung, and gastrointestinal tract and show rapid clearance from the blood circulation after systemic injection. The biodistribution and pharmacokinetics (PK) of exosomes can be modulated by engineering various factors such as cellular origin and membrane protein composition of exosomes. Recent advances accentuate the potential of targeted delivery of engineered exosomes even to the most challenging organs including the central nervous system. Major breakthroughs have been made related to various imaging techniques for monitoring in vivo biodistribution and PK of exosomes, as well as exosomal surface engineering technologies for inducing targetability. For inducing targeted delivery, therapeutic exosomes can be engineered to express various targeting moieties via direct modification methods such as chemically modifying exosomal surfaces with covalent/non-covalent bonds, or via indirect modification methods by genetically engineering exosome-producing cells. In this review, we describe the current knowledge of biodistribution and PK of exosomes, factors determining the targetability and organotropism of exosomes, and imaging technologies to monitor in vivo administered exosomes. In addition, we highlight recent advances in strategies for inducing targeted delivery of exosomes to specific organs and cells.Foot-and-mouth disease virus (FMDV) A/ASIA/Sea-97 is a predominant lineage in Southeast Asia and East Asia.  https://www.selleckchem.com/products/msc2530818.html  However, Sea-97 lineage has not been well studied since its first outbreak in Thailand in 1997. Thus, we conducted phylogenetic and evolutionary analysis of Sea-97 using 224 VP1 sequences of FMDV A/ASIA during 1960 and 2018. Phylogenetic analysis revealed that Sea-97 lineage can be classified into five groups (G1-G5). After the emergence of G2 from G1, the genetic diversity of Sea-97 increased sharply, causing divergence into G3, G4 and G5. During this evolutionary process, Sea-97 lineage, which was initially found only in some countries in Southeast Asia, gradually spread to East Asia. The evolution rate of this lineage was estimated to be 1.2 × 10-2 substitutions/site/year and there were many differences in amino acid residues compared to vaccine strain. Substitutions at antigenically important sites may affect the efficacy of the vaccine, suggesting the need for appropriate vaccine strains. Our results could provide meaningful information to understand comprehensive characteristic of Sea-97 lineage.
  Plaque psoriasis can significantly impact patients' quality of life. We assessed psychometric properties of the Psoriasis Symptoms and Impacts Measure (P-SIM), developed to capture patients' experiences of signs, symptoms and impacts of psoriasis.
 
  Pooled, blinded, 16-week data from 1002 patients in the BEVIVID and BEREADY bimekizumab phase3 trials were analysed. The suitability of the P-SIM missing score rule (weekly scores considered missing if ≥ 4 daily scores were missing) was assessed. Test-retest reliability was evaluated using intraclass correlation coefficients (ICCs). Convergent validity was assessed between P-SIM and relevant patient-reported outcome (PRO) (Dermatology Life Quality Index [DLQI], DLQI item1 [skin symptoms], Patient Global Assessment of Psoriasis) and clinician-reported outcome (ClinRO) scores (Psoriasis Area and Severity Index [PASI], Investigator's Global Assessment [IGA]) at baseline and week16. Known-groups validity was assessed, comparing P-SIM scores between patient subgroups
 
  P-SIM scores demonstrated good reliability, validity and sensitivity to change. A four-point RD threshold could be used to assess 16-week treatment effects.
 
  BEVIVID NCT03370133; BEREADY NCT03410992.
 BE VIVID NCT03370133; BE READY NCT03410992.
  Safety underreporting is a recurrent issue in clinical trials that can impact patient safety and data integrity. Clinical quality assurance (QA) practices used to detect underreporting rely on on-site audits; however, adverse events (AEs) underreporting remains a recurrent issue. In a recent project, we developed a predictive model that enables oversight of AE reporting for clinical quality program leads (QPLs). However, there were limitations to using solely a machine learning model.
 
  Our primary objective was to propose a robust method to compute the probability of AE underreporting that could complement our machine learning model. Our model was developed to enhance patients' safety while reducing the need for on-site and manual QA activities in clinical trials.
 
  We used a Bayesian hierarchical model to estimate the site reporting rates and assess the risk of underreporting. We designed the model with Project Data Sphere clinical trial data that are public and anonymized.
 
  We built a model that infers the site reporting behavior from patient-level observations and compares them across a study to enable a robust detection of outliers between clinical sites.
 
  The new model will be integrated into the current dashboard designed for clinical QPLs. This approach reduces the need for on-site audits, shifting focus from source data verification to pre-identified, higher risk areas. It will enhance further QA activities for safety reporting from clinical trials and generate quality evidence during pre-approval inspections.
 The new model will be integrated into the current dashboard designed for clinical QPLs. This approach reduces the need for on-site audits, shifting focus from source data verification to pre-identified, higher risk areas. It will enhance further QA activities for safety reporting from clinical trials and generate quality evidence during pre-approval inspections.