Viral infections and implications for male reproductive health

Viral infections have haunted humankind since times immemorial.Overpopulation,globalization,and extensive deforestation have created an ideal environment for a ...     

Tracheal and laryngotracheal resections and reconstructions—a single-centre experience

BackgroundSurgical resection has proven to be the most effective long-term treatment in managing airway stenoses and has shown to decrease the risk of tumor recurrence and mortality in patients with tumor infiltration to the airways. However, there are only a few Nordic reports on the results of a tracheal resection (TR) and cricotracheal resection (CTR). This study aimed to evaluate the volume and short-term outcome of TR and CTR at our institution.MethodsRetrospective review of patients who underwent TR or CTR between 2004 and 2019 at the Helsinki University Hospital (Helsinki, Finland).ResultsForty-four patients were included, of which 21 (47.7%) underwent surgery for a tumor, whereas 23 (52.3%) were operated for a benign stenosis. The most common tumor type was thyroid carcinoma with tracheal invasion (15.9%). The distance between the upper margin of the stenosis or tumor infiltration and the vocal cords was in median 3 [interquartile range (IQR), 2–5] cm and the median length of resection 2.5 (IQR, 2–3.5) cm. Overall success rate was 75% (no need for reoperation or postoperative intervention). Complications occurred in 20 (45.5%) patients, of which 10 patients were operated for a tumor, and 10 for a benign stenosis.ConclusionsTracheal and CTRs were effective in treating tracheal and subglottic stenoses with variable etiology. However, complications were common especially following cricotracheal tumor resections. These procedures show a clear need for further centralization due to their complex nature and should therefore be performed primarily at institutes with highly experienced multi-professional teams.     

Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19

To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations.A published convolutional Siamese neural network-based model previously trained on hospitalized patients with COVID-19 was tuned using 250 outpatient CXRs. This model produces a quantitative measure of COVID-19 lung disease severity (pulmonary x-ray severity (PXS) score). The model was evaluated on CXRs from 4 test sets, including 3 from the United States (patients hospitalized at an academic medical center (N = 154), patients hospitalized at a community hospital (N = 113), and outpatients (N = 108)) and 1 from Brazil (patients at an academic medical center emergency department (N = 303)). Radiologists from both countries independently assigned reference standard CXR severity scores, which were correlated with the PXS scores as a measure of model performance (Pearson R). The Uniform Manifold Approximation and Projection (UMAP) technique was used to visualize the neural network results.Tuning the deep learning model with outpatient data showed high model performance in 2 United States hospitalized patient datasets (R = 0.88 and R = 0.90, compared to baseline R = 0.86). Model performance was similar, though slightly lower, when tested on the United States outpatient and Brazil emergency department datasets (R = 0.86 and R = 0.85, respectively). UMAP showed that the model learned disease severity information that generalized across test sets.A deep learning model that extracts a COVID-19 severity score on CXRs showed generalizable performance across multiple populations from 2 continents, including outpatients and hospitalized patients.     

Histological evaluation of Curcuma longa-ghee formulation and hyaluronic acid on gingival healing in dog

Ethnopharmacological relevance

The experimental finding of Asian traditional medicine revealed the pharmacological effect of the local application of ghee which was taken from cow butterfat and the rhizomes of Curcuma longa. These materials significantly improved the healing process of the wound. In addition, ancient physicians of Middle East discovered that the powdered rhizomes of Curcuma longa (common turmeric) also had impressive medicinal qualities. Over the centuries, this spice has been used as a pain relieving, anti-inflammatory agent to relieve pain and inflammation in the skin and muscles.

Aim of the study

We decided to mix ghee which was taken from sheep butterfat with the powdered rhizomes of Curcuma longa to formulate a novel cost-benefit material and then, evaluate its potential therapeutic effect on acceleration of surgical wound healing; moreover, this present study was performed to compare the effects of Curcuma longa–ghee formulation and hyaluronic acid on gingival wound healing following surgery.

Materials and methods

Five healthy 3-year-old male beagle dogs were used in this study. They had intact teeth and the clinical and radiographic examination revealed no periodontal disease. Ghee was obtained from the refined sheep butterfat heated to 70 °C mixed with the powdered rhizomes of Curcuma longa and was applied with two different ratios including materials A and B. Randomly, these three materials including hyaluronic acid, materials A and B were applied topically in test regions and then covered with periodontal pack. Histological changes were monitored in days 4 and 7 after operation to evaluate the inflammatory and repair stage of healing process.

Results

We observed significant difference in the inflammatory and repair parameters of the healing process between cases treated with this new formulation and cases of hyaluronic acid application.

Conclusion

The results suggested a positive potential therapeutic effect on surgical wound healing particularly improvement of periodontal treatment consequences after surgery.