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Platelet-rich plasma (PRP) and its derivatives are an emerging biotechnology whereby concentrated platelets provide damaged tissue with growth factors, cytokines, and other mediators to improve healing outcomes. Although there is strong evidence in the benefits of autologous PRP for both acute and chronic wounds, allogeneic PRP has been studied far less in comparison.

In this mini-review, we discuss critical steps of allogenic PRP (and its derivatives) preparation. We performed a non-systematic review of the literature to identify animal and human subject studies testing allogenic PRP for wound treatment. We searched OVID Medline and PubMed for articles using the keywords "wound, ulcer, lesion, skin, and cutaneous" and "PRP, or platelet-rich plasma, or platelet-rich fibrin, or PRF, or platelet releasate" and "homologous, allogeneic or allogenic," which were limited to non-review articles and English language. Two studies in animal models and 8 studies in patients were reviewed. There were inconsistencies rin, or PRF, or platelet releasate" and "homologous, allogeneic or allogenic," which were limited to non-review articles and English language. Two studies in animal models and 8 studies in patients were reviewed. There were inconsistencies in preparation methods, treatment regimens, and some lacked a control group in their studies. Despite these variations, none of the studies identified any major side effects or adverse events. The treatment resulted in a reduced time to heal and/or reduced wound size in most cases. Key Messages In situations where autologous PRP is not available or suitable, allogeneic PRP appears to provide a safe alternative. Its efficacy, however, requires larger-scale studies with appropriate controls. Standardization in PRP preparation and treatment regime are also needed to be able to interpret allogenic PRP efficacy.

Detailed understanding of the immune response to severe acute respiratory syndrome coronavirus (SARS-CoV)-2, the cause of coronavirus disease 2019 (CO-VID-19) has been hampered by a lack of quantitative antibody assays.

The objective was to develop a quantitative assay for IgG to SARS-CoV-2 proteins that could be implemented in clinical and research laboratories.

The biotin-streptavidin technique was used to conjugate SARS-CoV-2 spike receptor-binding domain (RBD) or nucleocapsid protein to the solid phase of the ImmunoCAP. Plasma and serum samples from patients hospitalized with COVID-19 (n = 60) and samples from donors banked before the emergence of COVID-19 (n = 109) were used in the assay. SARS-CoV-2 IgG levels were followed longitudinally in a subset of samples and were related to total IgG and IgG to reference antigens using an ImmunoCAP 250 platform.

At a cutoff of 2.5 μg/mL, the assay demonstrated sensitivity and specificity exceeding 95% for IgG to both SARS-CoV-2 proteins. Among 36 patients units.

Prior studies have suggested that head injury might be a potential risk factor of amyotrophic lateral sclerosis (ALS). However, the association has not been well established. We aimed to provide a synopsis of the current understanding of head injury's role in ALS.

We performed a systematic search in PubMed for observational studies that quantitatively investigated the association between head injury and ALS risk published before April 10, 2020. We used a random-effects model to calculate odds ratios (ORs) and 95% confidence intervals (CIs).

Fourteen eligible articles including 10,703 cases and 2,159,324 controls were selected in current meta-analysis. We found that head injury was associated with an increased risk of ALS (OR = 1.38, 95% CI 1.20-1.60) and the association was slightly stronger concerning severe head injury and ALS risk (OR = 1.69, 95% CI 1.27-2.23). Considering the number of head injuries (N) and ALS risk, the association was weak (OR = 1.23, 95% CI 1.10-1.37, N = 1; OR = 1.29, 95% CI 0.89-1.86, N ≥ 2). In addition, a strong association with ALS risk was found in individuals who suffered head injury <1 year (OR = 4.05, 95% CI 2.79-5.89), and when the time lag was set at 1-5, 5-10, and >10 years, the pooled OR was 1.13, 1.35, and 1.10, respectively.

This meta-analysis indicates that head injury, especially severe head injury, could increase ALS risk. Oxidopamine Although a strong association is found between head injury <1 year and ALS risk in the current study, this result suggests a possibility of reverse causation.

This meta-analysis indicates that head injury, especially severe head injury, could increase ALS risk. Although a strong association is found between head injury less then 1 year and ALS risk in the current study, this result suggests a possibility of reverse causation.

Dysfunctional appraisals about traumatic events and their sequelae are a key mechanism in posttraumatic stress disorder (PTSD). Experimental studies have shown that a computerized cognitive training, cognitive bias modification for appraisals (CBM-APP), can modify dysfunctional appraisals and reduce analogue trauma symptoms amongst healthy and subclinical volunteers.

We aimed to test whether CBM-APP could reduce dysfunctional appraisals related to trauma reactions in PTSD patients, and whether this would lead to improvements in PTSD symptoms.

We compared CBM-APP to sham training in a parallel-arm proof-of-principle double-blind randomized controlled trial amongst 80 PTSD patients admitted to an inpatient clinic. Both arms comprised a training schedule of 8 sessions over a 2-week period and were completed as an adjunct to the standard treatment programme.

In intention-to-treat analyses, participants receiving CBM-APP showed a greater reduction in dysfunctional appraisals on a scenario task from pre- tosent therapeutic approaches.There has been an explosion of use for quantitative image analysis in the setting of lung disease due to advances in acquisition protocols and postprocessing technology, including machine and deep learning. Despite the plethora of published papers, it is important to understand which approach has clinical validation and can be used in clinical practice. This paper provides an introduction to quantitative image analysis techniques being used in the investigation of lung disease and focusses on the techniques that have a reasonable clinical validation for being used in clinical trials and patient care.

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