Tag: pubmed

BMC Bioinformatics. 2022 Nov 8;23(1):466. doi: 10.1186/s12859-022-05017-x.

ABSTRACT

BACKGROUND: In most parts of the world, especially in underdeveloped countries, acquired immunodeficiency syndrome (AIDS) still remains a major cause of death, disability, and unfavorable economic outcomes. This has necessitated intensive research to develop effective therapeutic agents for the treatment of human immunodeficiency virus (HIV) infection, which is responsible for AIDS. Peptide cleavage by HIV-1 protease is an essential step in the replication of HIV-1. Thus, correct and timely prediction of the cleavage site of HIV-1 protease can significantly speed up and optimize the drug discovery process of novel HIV-1 protease inhibitors. In this work, we built and compared the performance of selected machine learning models for the prediction of HIV-1 protease cleavage site utilizing a hybrid of octapeptide sequence information comprising bond composition, amino acid binary profile (AABP), and physicochemical properties as numerical descriptors serving as input variables for some selected machine learning algorithms. Our work differs from antecedent studies exploring the same subject in the combination of octapeptide descriptors and method used. Instead of using various subsets of the dataset for training and testing the models, we combined the dataset, applied a 3-way data split, and then used a “stratified” 10-fold cross-validation technique alongside the testing set to evaluate the models.

RESULTS: Among the 8 models evaluated in the “stratified” 10-fold CV experiment, logistic regression, multi-layer perceptron classifier, linear discriminant analysis, gradient boosting classifier, Naive Bayes classifier, and decision tree classifier with AUC, F-score, and B. Acc. scores in the ranges of 0.91-0.96, 0.81-0.88, and 80.1-86.4%, respectively, have the closest predictive performance to the state-of-the-art model (AUC 0.96, F-score 0.80 and B. Acc. ~ 80.0%). Whereas, the perceptron classifier and the K-nearest neighbors had statistically lower performance (AUC 0.77-0.82, F-score 0.53-0.69, and B. Acc. 60.0-68.5%) at p < 0.05. On the other hand, logistic regression, and multi-layer perceptron classifier (AUC of 0.97, F-score > 0.89, and B. Acc. > 90.0%) had the best performance on further evaluation on the testing set, though linear discriminant analysis, gradient boosting classifier, and Naive Bayes classifier equally performed well (AUC > 0.94, F-score > 0.87, and B. Acc. > 86.0%).

CONCLUSIONS: Logistic regression and multi-layer perceptron classifiers have comparable predictive performances to the state-of-the-art model when octapeptide sequence descriptors consisting of AABP, bond composition and standard physicochemical properties are used as input variables. In our future work, we hope to develop a standalone software for HIV-1 protease cleavage site prediction utilizing the linear regression algorithm and the aforementioned octapeptide sequence descriptors.

PMID:36344934 | DOI:10.1186/s12859-022-05017-x

BMC Nephrol. 2022 Nov 7;23(1):359. doi: 10.1186/s12882-022-02996-0.

ABSTRACT

BACKGROUND: Predicting allograft survival is vital for efficient transplant success. With dynamic changes in patient conditions, clinical indicators may change longitudinally, and doctors’ judgments may be highly variable. It is necessary to establish a dynamic model to precisely predict the individual risk/survival of new allografts.

METHODS: The follow-up data of 407 patients were obtained from a renal allograft failure study. We introduced a landmarking-based dynamic Cox model that incorporated baseline values (age at transplantation, sex, weight) and longitudinal changes (glomerular filtration rate, proteinuria, hematocrit). Model performance was evaluated using Harrell’s C-index and the Brier score.

RESULTS: Six predictors were included in our analysis. The Kaplan-Meier estimates of survival at baseline showed an overall 5-year survival rate of 87.2%. The dynamic Cox model showed the individual survival prediction with more accuracy at different time points (for the 5-year survival prediction, the C-index = 0.789 and Brier score = 0.065 for the average of all time points) than the static Cox model at baseline (C-index = 0.558, Brier score = 0.095). Longitudinal covariate prognostic analysis (with time-varying effects) was performed.

CONCLUSIONS: The dynamic Cox model can utilize clinical follow-up data, including longitudinal patient information. Dynamic prediction and prognostic analysis can be used to provide evidence and a reference to better guide clinical decision-making for applying early treatment to patients at high risk.

PMID:36344916 | DOI:10.1186/s12882-022-02996-0

BMC Anesthesiol. 2022 Nov 7;22(1):341. doi: 10.1186/s12871-022-01891-3.

ABSTRACT

BACKGROUND: Thoracic epidural analgesia (TEA) has always been the first choice for postoperative pain treatment, but associated complications and contraindications may limit its use. Our study put forward a new analgesic strategy that combines TEA with patient controlled intravenous analgesia (PCIA) to optimize TEA.

METHODS: Patients undergoing laparotomy were enrolled in this prospective randomized study. Patients were randomized to one of two groups: TEA/PCIA group and TEA group. Patients in TEA/PCIA group received TEA in the day of surgery and the first postoperative day and PCIA continued to use until the third postoperative day. Patients in TEA group received TEA for three days postoperatively. Visual analogue scale (VSA) pain scores at rest and on movement at 6, 24,48,72 h after surgery were recorded. In addition, the incidence of inadequate analgesia, adverse events, time to first mobilization, time to pass first flatus, time of oral intake recovery, time of urinary catheter removal, postoperative length of hospital stay, cumulative opioid consumption, and the overall cost were compared between the two groups. We examined VAS pain scores using repeated measures analysis of variance; P < 0.05 was considered as statistically significant.

RESULTS: Eighty-six patients were analysed (TEA/PCIA = 44, TEA = 42). The mean VAS pain scores at rest and on movement in TEA/PCIA group were lower than TEA group, with a significant difference on movement and 48 h postoperatively (P < 0.05). The time to first mobilization and pass first flatus were shorter in TEA/PCIA group (P < 0.05). Other measurement showed no statistically significant differences.

CONCLUSIONS: The combination of TEA with PCIA for patients undergoing laparotomy, can enhance postoperative pain control and facilitate early recovery without increasing the incidence of adverse effects and overall cost of hospitalization.

TRIAL REGISTRATION: Chinese Clinical Trial Registry( www.chictr.org.cn ), ChiCTR 1,800,020,308, 13 December 2018.

PMID:36344910 | DOI:10.1186/s12871-022-01891-3

Environ Sci Pollut Res Int. 2022 Nov 8. doi: 10.1007/s11356-022-23900-1. Online ahead of print.

ABSTRACT

This research aims to develop an ecological carrying capacity index for the ecological environment under the principle of the pressure-state-response framework model and discusses the coupling coordination of ecological environment pressure, state, and response system of the urban region in china from 2011 to 2020. Furthermore, predicated the degree of security warning for each year while establishing the ecological carrying capacity index and the urban ecological coupling model. Results specify that the coordination degree of urban ecological development in Nanchang, Jiangxi has been improved year by year, the ecological carrying capacity security index shows an upward tendency from the overall view, and the security warning degree rises from comparative insecurity to comparative security. The analysis demonstrates that in the process of national ecological civilization construction demonstration zone construction, the ecological resources and environmental policies adopted by Nanchang city have played a great role in promoting ecological security. However, the ecological security index in Nanchang is still below 0.6, far from the high-security level (0.77), and the government and the public still need to do a lot to improve ecological security.

PMID:36344890 | DOI:10.1007/s11356-022-23900-1

Environ Sci Pollut Res Int. 2022 Nov 7. doi: 10.1007/s11356-022-23893-x. Online ahead of print.

ABSTRACT

Gearbox is an important part of wind turbine. Diagnosing and forecasting gearbox faults of wind turbines can effectively reduce the costs of operation and maintenance and improve the reliability of gearbox operation. Due to high dimensionality and nonlinearity of system parameters, the paper uses the grey relation analysis to select features related to gearbox oil temperature. Features with a relational degree above 0.7 are selected as input data related to oil temperature, including wind speed, ambient temperature, power, and gearbox shaft temperature. Then, a new extreme learning machine with kernel improved by the whale optimization algorithm is established to forecast gearbox oil temperature. Through the residuals between gearbox oil temperature predicted by the proposed model and monitored by the SCADA, whether the gearbox exists faults can be diagnosed. In the case study, the test data was divided into two groups (the test data with and without faults). In the data test without faults, compared with three other models, the proposed model has the smallest false-negative rate (0.211%) and mean absolute percentage error (2.812%). In the data test with faults, the proposed model can diagnose gearbox faults earlier (160 min in advance) than the other three benchmark models. The results show that the proposed hybrid model performs well in the fault diagnosis and prediction of wind turbine gearbox.

PMID:36344885 | DOI:10.1007/s11356-022-23893-x

Ann Intern Med. 2022 Nov 8. doi: 10.7326/M22-1438. Online ahead of print.

ABSTRACT

BACKGROUND: Parkinson disease (PD) is associated with α-synuclein (αS) aggregation within enteric neurons. ENT-01 inhibits the formation of αS aggregates and improved constipation in an open-label study in patients with PD.

OBJECTIVE: To evaluate the safety and efficacy of oral ENT-01 for constipation and neurologic symptoms in patients with PD and constipation.

DESIGN: Randomized, placebo-controlled phase 2b study. (ClinicalTrials.gov: NCT03781791).

SETTING: Outpatient.

PATIENTS: 150 patients with PD and constipation.

INTERVENTION: ENT-01 or placebo daily for up to 25 days. After baseline assessment of constipation severity, daily dosing was escalated to the prokinetic dose, the maximum dose (250 mg), or the tolerability limit, followed by a washout period.

MEASUREMENTS: The primary efficacy end point was the number of complete spontaneous bowel movements (CSBMs) per week. Neurologic end points included dementia (assessed using the Mini-Mental State Examination [MMSE]) and psychosis (assessed using the Scale for the Assessment of Positive Symptoms adapted for PD [SAPS-PD]).

RESULTS: The weekly CSBM rate increased from 0.7 to 3.2 in the ENT-01 group versus 0.7 to 1.2 in the placebo group (P < 0.001). Improvement in secondary end points included SBMs (P = 0.002), stool consistency (P < 0.001), ease of passage (P = 0.006), and laxative use (P = 0.041). In patients with dementia, MMSE scores improved by 3.4 points 6 weeks after treatment in the ENT-01 group (n = 14) versus 2.0 points in the placebo group (n = 14). Among patients with psychosis, SAPS-PD scores improved from 6.5 to 1.7 six weeks after treatment in the ENT-01 group (n = 5) and from 6.3 to 4.4 in the placebo group (n = 6). ENT-01 was well tolerated, with no deaths or drug-related serious adverse events. Adverse events were predominantly gastrointestinal, including nausea (34.4% [ENT-01] vs. 5.3% [placebo]; P < 0.001) and diarrhea (19.4% [ENT-01] vs. 5.3% [placebo]; P = 0.016).

LIMITATION: Longer treatment periods need to be investigated in future studies.

CONCLUSION: ENT-01 was safe and significantly improved constipation.

PRIMARY FUNDING SOURCE: Enterin, Inc.

PMID:36343348 | DOI:10.7326/M22-1438

Ann Intern Med. 2022 Nov 8. doi: 10.7326/M22-1566. Online ahead of print.

ABSTRACT

BACKGROUND: Implantable cardioverter defibrillators (ICDs) improve survival in patients at risk for cardiac arrest, but are associated with intravascular lead-related complications. The subcutaneous ICD (S-ICD), with no intravascular components, was developed to minimize lead-related complications.

OBJECTIVE: To assess key ICD performance measures related to delivery of ICD therapy, including inappropriate ICD shocks (delivered in absence of life-threatening arrhythmia) and failed ICD shocks (which did not terminate ventricular arrhythmia).

DESIGN: Randomized, multicenter trial. (ClinicalTrials.gov: NCT02881255).

SETTING: The ATLAS trial.

PATIENTS: 544 eligible patients (141 female) with a primary or secondary prevention indication for an ICD who were younger than age 60 years, had a cardiogenetic phenotype, or had prespecified risk factors for lead complications were electrocardiographically screened and 503 randomly assigned to S-ICD (251 patients) or transvenous ICD (TV-ICD) (252 patients). Mean follow-up was 2.5 years (SD, 1.1). Mean age was 49.0 years (SD, 11.5).

MEASUREMENTS: The primary outcome was perioperative major lead-related complications.

RESULTS: There was a statistically significant reduction in perioperative, lead-related complications, which occurred in 1 patient (0.4%) with an S-ICD and in 12 patients (4.8%) with TV-ICD (-4.4%; 95% CI, -6.9 to -1.9; P = 0.001). There was a trend for more inappropriate shocks with the S-ICD (hazard ratio [HR], 2.37; 95% CI, 0.98 to 5.77), but no increase in failed appropriate ICD shocks (HR, 0.61 (0.15 to 2.57). Patients in the S-ICD group had more ICD site pain, measured on a 10-point numeric rating scale, on the day of implant (4.2 ± 2.8 vs. 2.9 ± 2.2; P < 0.001) and 1 month later (1.3 ± 1.8 vs. 0.9 ± 1.5; P = 0.035).

LIMITATION: At present, the ATLAS trial is underpowered to detect differences in clinical shock outcomes; however, extended follow-up is ongoing.

CONCLUSION: The S-ICD reduces perioperative, lead-related complications without significantly compromising the effectiveness of ICD shocks, but with more early postoperative pain and a trend for more inappropriate shocks.

PRIMARY FUNDING SOURCE: Boston Scientific.

PMID:36343346 | DOI:10.7326/M22-1566

Health Aff (Millwood). 2022 Nov;41(11):1635-1644. doi: 10.1377/hlthaff.2021.01955.

ABSTRACT

The relationship between immigrant entry and COVID-19 spread in the United States has driven much political discussion and policy, including the implementation of Title 42 by the Centers for Disease Control and Prevention. To examine the relationship between COVID-19 spread and immigrant entry, we compared 2020-21 immigrant flows with local COVID-19 rates, using estimates of border crossings from the Border Patrol and visas issued through the Department of Labor’s seasonal guest worker program. Our analysis capturing seasonal guest worker entry at the national level showed no statistically significant relationship with COVID-19 rates. Our analyses of Southwest border crossings showed a small, statistically significant relationship between immigrant flows and COVID-19 rates in border counties (0.14 percent increase in local cases per 100,000 residents for each additional 100 immigrants). However, this estimate is modest compared with the fact that half of all month-to-month changes in case rates were greater than 59 percent. Furthermore, the modest increase became nonsignificant with increasing local vaccination rates. Estimates also did not maintain their statistical significance when analyzed with some alternative approaches. Our findings support existing evidence that the short-term impacts of immigrant flow on local COVID-19 rates were minimal.

PMID:36343326 | DOI:10.1377/hlthaff.2021.01955

J Chin Med Assoc. 2022 Nov 1;85(11):1044-1050. doi: 10.1097/JCMA.0000000000000783. Epub 2022 Nov 2.

ABSTRACT

BACKGROUND: Overall survival of systemic lupus erythematosus (SLE) patients significantly increased in recent decades, however, the relative risk of mortality is still high. Long-term survival outcome of pediatric SLE remains unclear. This study aims to explore the long-term survival rate and its predictors in patients with systemic lupus erythematosus (SLE).

METHODS: A retrospective, hospital-based cohort study was performed between 2004 and 2018 in a tertiary referral medical center in Taiwan. Data on comorbidities, medications, and causes of admission were collected for risk factor analysis using time-dependent multivariate Cox proportional hazards models.

RESULTS: A total of 2392 adults and 115 pediatric SLE patients were enrolled (female, n = 2157 and 95, respectively). The 10-year survival rates were 93.2%, 90.2%, 98.9%, and 100% in adult women, adult men, girls, and boys with SLE, respectively. The overall mortality rate was 2.09 case/100 patient-years (PY) for male SLE and 1.39 case/100 PY for female SLE patients. Male SLE patients did not have a statistically significantly higher mortality rate than female SLE patients in each age stratification. Infectious disease (n = 119), heart failure (n = 21), and cerebrovascular accident (n = 14) were the leading causes of death in adult SLE patients. Advanced age (hazard ratio [HR]: 1.04, 95% confidence interval [CI]: 1.03-1.05), treatment with mean dosage of systemic glucocorticoid equivalent to >10 mg/d of prednisolone (HR: 1.71, 95% CI: 1.14-2.57), comorbidities with malignancy (HR: 1.94, 95% CI: 1.22-3.09), chronic kidney disease (HR: 1.86, 95% CI: 1.25-2.77), hypertension (HR: 1.42, 95% CI: 1.01-1.98), and admission due to bacterial pneumonia (HR: 1.92, 95% CI: 1.12-3.31) and sepsis (HR: 2.78, 95% CI: 1.51-5.13) were independent risk factors for mortality in SLE patients.

CONCLUSION: SLE patients with advanced age, malignancy, chronic kidney disease, hypertension, treated with a higher average dosage of glucocorticoids, and admission due to bacterial pneumonia and sepsis have an increased risk of mortality.

PMID:36343272 | DOI:10.1097/JCMA.0000000000000783

Proc Natl Acad Sci U S A. 2022 Nov 16;119(46):e2200822119. doi: 10.1073/pnas.2200822119. Epub 2022 Nov 7.

ABSTRACT

Epilepsy is a disorder characterized by paroxysmal transitions between multistable states. Dynamical systems have been useful for modeling the paroxysmal nature of seizures. At the same time, intracranial electroencephalography (EEG) recordings have recently discovered that an electrographic measure of epileptogenicity, interictal epileptiform activity, exhibits cycling patterns ranging from ultradian to multidien rhythmicity, with seizures phase-locked to specific phases of these latent cycles. However, many mechanistic questions about seizure cycles remain unanswered. Here, we provide a principled approach to recast the modeling of seizure chronotypes within a statistical dynamical systems framework by developing a Bayesian switching linear dynamical system (SLDS) with variable selection to estimate latent seizure cycles. We propose a Markov chain Monte Carlo algorithm that employs particle Gibbs with ancestral sampling to estimate latent cycles in epilepsy and apply unsupervised learning on spectral features of latent cycles to uncover clusters in cycling tendency. We analyze the largest database of patient-reported seizures in the world to comprehensively characterize multidien cycling patterns among 1,012 people with epilepsy, spanning from infancy to older adulthood. Our work advances knowledge of cycling in epilepsy by investigating how multidien seizure cycles vary in people with epilepsy, while demonstrating an application of an SLDS to frame seizure cycling within a nonlinear dynamical systems framework. It also lays the groundwork for future studies to pursue data-driven hypothesis generation regarding the mechanistic drivers of seizure cycles.

PMID:36343269 | DOI:10.1073/pnas.2200822119