In silico optimization of RNA-protein interactions for CRISPR-Cas13-based antimicrobials.

peer reviewedRNA-protein interactions are crucial for diverse biological processes. In prokaryotes, RNA-protein interactions enable adaptive immunity through CRISPR-Cas systems. These defence systems utilize CRISPR RNA (crRNA) templates acquired from past infections to destroy foreign genetic elements through crRNA-mediated nuclease activities of Cas proteins. Thanks to the programmability and specificity of CRISPR-Cas systems, CRISPR-based antimicrobials have the potential to be repurposed as new types of antibiotics. Unlike traditional antibiotics, these CRISPR-based antimicrobials can be designed to target specific bacteria and minimize detrimental effects on the human microbiome during antibacterial therapy. In this study, we explore the potential of CRISPR-based antimicrobials by optimizing the RNA-protein interactions of crRNAs and Cas13 proteins. CRISPR-Cas13 systems are unique as they degrade specific foreign RNAs using the crRNA template, which leads to non-specific RNase activities and cell cycle arrest. We show that a high proportion of the Cas13 systems have no colocalized CRISPR arrays, and the lack of direct association between crRNAs and Cas proteins may result in suboptimal RNA-protein interactions in the current tools. Here, we investigate the RNA-protein interactions of the Cas13-based systems by curating the validation dataset of Cas13 protein and CRISPR repeat pairs that are experimentally validated to interact, and the candidate dataset of CRISPR repeats that reside on the same genome as the currently known Cas13 proteins. To find optimal CRISPR-Cas13 interactions, we first validate the 3-D structure prediction of crRNAs based on their experimental structures. Next, we test a number of RNA-protein interaction programs to optimize the in silico docking of crRNAs with the Cas13 proteins. From this optimized pipeline, we find a number of candidate crRNAs that have comparable or better in silico docking with the Cas13 proteins of the current tools. This study fully automatizes the in silico optimization of RNA-protein interactions as an efficient preliminary step for designing effective CRISPR-Cas13-based antimicrobials

A pharmacokinetic study on red ginseng with furosemide in equine

Red ginseng (RG) is a popular ingredient in traditional Korean medicine that has various health benefits. It is commonly taken orally as a dietary supplement; however, its potential interactions with concomitantly administered drugs are unclear. In this study, we examined the pharmacokinetic interaction between furosemide and RG in equine plasma. Liquid chromatography with tandem mass spectrometry analysis was performed to evaluate ginsenosides in the plasma of horses after feeding them RG and furosemide and validate the results. A single bolus of furosemide (0.5 mg/kg) was administered intravenously to female horses that had consumed RG (600 mg/kg/day) every morning for 3 weeks (experimental group), and blood samples were collected from 0 to 24 h, analyzed, and compared with those from female horses that did not consume RG (control group). Four (20s)-protopanaxadiol ginsenosides (Rb1, Rb2, Rc, and Rd) were detected in the plasma. Rb1 and Rc individually showed a high concentration distribution in the plasma. The Cmax, AUC0−t, and AUC0−∞ of furosemide was significantly increased in the experimental group (p < 0.05), while the CL, Vz, and Vss was decreased (p < 0.05, p < 0.01). These changes indicate the potential for pharmacokinetic interactions between furosemide and RG

Detecting Symptoms of Depression in Social Media Data using Machine Learning

Based on the sentence, you are what you post , there have been continuous studies conducted to identify depression by leveraging social media data. Depression detection traditionally is done through a face-to-face meeting with a clinical professional. However, only 52% of patients come in seeking help early enough for effective intervention (Boerema AM, 2016). Factors such as lack of knowledge, ignorance, prejudice and social stigma against people with mental illness and expectation of discrimination of people who have mental illness cause these delays in treatment (Henderson, 2013). Nowadays, social media is a place in which people post their feelings more often than talking to a clinician about their emotions. Therefore, much research has been conducted to detect depressive symptoms in social media data. This research completes three different tasks with some novel approaches. First, we apply word cloud analysis to understand different word usages between depressed and nondepressed users. Second, we train a classification model for detecting depressed users by utilizing a different python-library called Fasttext. In addition, implementing topic modeling to yield insight into how depressed and non-depressed individuals use language differently on social media

Modified bolster dressing with continuous suction improves skin graft survival for an oral cavity wound

Abstract Background Skin engraftment of intraoral defects is known to be inconsistent due to mobility of the oral structure, uneven wounds, and accumulation of saliva under the skin graft. To improve the success rate of oral skin graft, we proposed a novel and simple dressing technique for intraoral skin graft to control saliva accumulation, in comparison with the conventional bolster dressing. Methods We retrospectively reviewed 31 patients reconstructed with skin graft in their intraoral defect. The patients were divided into two groups; conventional bolster group (n = 21) and modified bolster group (n = 10). In the modified bolster group, a polyvinyl alcohol sponge was designed to fit the skin graft and a suction drain was inserted with tagging suture to apply continuous suction. We analyzed the success rate, the size of the skin grafts and clinical variables of each method. Results The overall success rate of oral skin graft was not different between the two groups (90.0 and 90.5%). However, partial necrosis in the engrafted skin was observed frequently in the control group (57.1% versus 20.0%). The relative engrafted area was significantly higher in the modified bolster group (55.0 ± 11.6% versus 23.0 ± 18.7%, p = 0.015). The duration of bolster dressing and the time to start an oral diet were shorter in the modified bolster group. Conclusions Our modified method could be easily applied for removing saliva accumulation under a skin graft and for enhancing skin engraftment of an oral cavity wound

Analysis of the Factors Influencing Body Weight Variation in Hanwoo Steers Using an Automated Weighing System

This study aimed to determine the factors affecting the body weight (BW) of Hanwoo steers by collecting a large number of BW measurements using an automated weighing system (AWS). The BW of 12 Hanwoo steers was measured automatically using an AWS for seven days each month over three months. On the fourth day of the BW measurement each month, an additional BW measurement was conducted manually. After removing the outliers of BW records, the deviations between the AWS records (a) and manual weighing records (b) were analyzed. BW measurement deviations (a − b) were significantly (p < 0.05) affected by month, day and the time within a day as well as the individual animal factor; however, unexplained random variations had the greatest impact (70.4%). Excluding unexplained random variations, the difference between individual steers was the most influential (80.1%). During the day, the BW of Hanwoo steers increased before feed offerings and significantly decreased immediately after (p < 0.05), despite the constant availability of feeds in the feed bunk. These results suggest that there is a need to develop pattern recognition algorithms that consider variations in individual animals and their feeding patterns for the analysis of BW changes in animals

Additional file 1 of In silico optimization of RNA–protein interactions for CRISPR-Cas13-based antimicrobials

Additional file 1. Supplementary Figures S1–S15 and Supplementary Tables S1–S17

Long‐term impact of angiotensin receptor‐neprilysin inhibitor based on short‐term treatment response in heart failure

Abstract Aims The long‐term effect of angiotensin receptor–neprilysin inhibitor (ARNI) remains uncertain in patients who have experienced improvements in left ventricular (LV) systolic function or significant LV reverse remodelling following a certain period of treatment. It is also unclear how ARNI performs in patients who have not shown these improvements. This study aimed to assess the impact of prolonged ARNI use compared with angiotensin‐converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs) in patients with and without significant treatment response after 1 year of heart failure (HF) treatment. Methods and results The present study enrolled patients with HF with reduced ejection fraction (HFrEF) who were treated with either ARNI or ACEIs/ARBs within 1 year of undergoing index echocardiography. After 1 year of treatment, patients were reclassified into the following groups: (i) patients with HF with improved ejection fraction and persistent HFrEF and (ii) patients with and without LV reverse remodelling based on the follow‐up echocardiography. The effect of ARNI versus that of ACEIs/ARBs in each group was assessed from the time of categorizing into new groups using the composite event of all‐cause mortality and HF hospitalization. A total of 671 patients with HFrEF (age, 66.4 ± 14.1 years; males, 66.8%) were included, and 133 (19.8%) composite events of death and rehospitalization for HF were observed during the follow‐up (median follow‐up, 44 [interquartile range, 34–51] months). ARNI had a significantly lower event rate than ACEIs/ARBs in patients with HF with improved ejection fraction (7.0% vs. 30.4%, P = 0.020) and those with persistent HFrEF (17.6% vs. 49.7%, P < 0.001). Irrespective of whether patients exhibited LV reverse remodelling (15.8% vs. 31.1%, P = 0.001) or not (15.0% vs. 54.9%, P < 0.001), ARNIs were associated with a significantly lower event rate than ACEIs/ARBs. Conclusions Regardless of significant treatment response measured by either LVEF or LV reverse remodelling after 1 year of treatment, the extended utilization of ARNI demonstrated a more favourable prognosis than that of ACEIs/ARBs in patients with HFrEF

Predictors of stroke or systemic embolism in patients with non‐valvular atrial fibrillation with CHA2DS2‐VASc score of 0

Abstract Background Anticoagulant therapy has been important for stroke prevention in patients with atrial fibrillation (AF). However, it was not recommended due to its relatively higher risk of bleeding than its lower risk of stroke in patients with a CHA2DS2‐VASc score of 0. Hypothesis This study aimed to evaluate the predictors of stroke in AF patients with very low risk of stroke. Methods Between 1990 and 2020, 542 patients with non‐valvular AF (NVAF) with a CHA2DS2‐VASc score of 0 followed up for at least 6 months were enrolled. Patients with only being woman as a risk factor were included as a CHA2DS2‐VASc score of 0 in this study. The primary outcome was stroke or systemic embolism. Results The primary outcome rate was 0.78%/year. In Cox hazard model, age of ≥50 years at diagnosis (hazard ratio [HR] 6.710, 95% confidence interval [CI] 1.811–24.860, p = .004), LVEDD of ≥46 mm (HR 4.513, 95% CI 1.038–19.626, p = .045), and non‐paroxysmal AF (HR 5.575, 95% CI 1.621–19.175, p = .006) were identified as independent predictors of stroke or systemic embolism. Patients with all three independent predictors had a higher risk of stroke or systemic embolism (4.21%/year), whereas those without did not have a stroke or systemic embolism. Conclusion The annual stroke or systemic embolism rate in NVAF patients with CHA2DS2‐VASc score of 0 was 0.78%/year, and age at AF diagnosis, LVEDD, and non‐paroxysmal AF were independent predictors of stroke or systemic embolism in patients considered to have a very low risk of stroke