Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a clinically critical pathogen that causes severe infection. Due to improper antibiotic administration, the prevalence of CRKP infection has been ...increasing considerably. In recent years, the utilization of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has enabled the identification of bacterial isolates at the families and species level. Moreover, machine learning (ML) classifiers based on MALDI-TOF MS have been recently considered a novel method to detect clinical antimicrobial-resistant pathogens.
A total of 2683 isolates (369 CRKP cases and 2314 carbapenem-susceptible Klebsiella pneumoniae CSKP) collected in the clinical laboratories of Taipei Medical University Hospital (TMUH) were included in this study, and 80% of data was split into the training data set that were submitted for the ML model. The remaining 20% of data was used as the independent data set for external validation. In this study, we established an artificial neural network (ANN) model to analyze all potential peaks on mass spectrum simultaneously.
Our artificial neural network model for detecting CRKP isolates showed the best performance of area under the receiver operating characteristic curve (AUROC = 0.91) and of area under precision-recall curve (AUPRC = 0.90). Furthermore, we proposed the top 15 potential biomarkers in probable CRKP isolates at 2480, 4967, 12,362, 12,506, 12,855, 14,790, 15,730, 16,176, 16,218, 16,758, 16,919, 17,091, 18,142, 18,998, and 19,095 Da.
Compared with the prior MALDI-TOF and machine learning studies of CRKP, the amount of data in our study was more sufficient and allowing us to conduct external validation. With better generalization abilities, our artificial neural network model can serve as a reliable screening tool for CRKP isolates in clinical practice. Integrating our model into the current workflow of clinical laboratories can assist the rapid identification of CRKP before the completion of traditional antimicrobial susceptibility testing. The combination of MADLI-TOF MS and machine learning techniques can support physicians in selecting suitable antibiotics, which has the potential to enhance the patients' outcomes and lower the prevalence of antimicrobial resistance.
This paper proposes a Kullback‐Leibler information (KLI) control chart for monitoring the occurrence rate of a process that follows an exponential distribution. The chart is designed for detecting a ...decrease, an increase, or both in the occurrence rate. Due to the skewness of the plotted statistic, the performance of the chart is investigated separately when the occurrence rate is estimated by the maximum likelihood estimator, the uniformly minimum variance unbiased estimator, and the minimum mean squared error estimator. The KLI chart is effective for a wide range of shifts of the occurrence rate. Its performance is slightly behind cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) charts around sizes of shift where these two charts are optimized. It outperforms these two charts elsewhere. The relative mean index (RMI) values show that the KLI chart has better overall performance. A backward empirical sequential test is used for the plotted statistic of the chart. It is shown equivalent to the cumulative sum scheme and the change point method for the generalized likelihood ratio chart in terms of run length. The use of KLI chart does not require any design parameter other than the control limit.
Profile monitoring is referred to as monitoring the functional relationship between the response and explanatory variables. Traditionally, process control charts monitor the mean and/or the variance ...of a univariate quality characteristic. For several correlated quality characteristics, multivariate process control charts monitor the mean vector and/or the covariance matrix. However, monitoring the functional relationship between variables is sometimes more beneficial. One example is the power output of a Diesel engine and the amount of fuel injected should be related. In this paper, we propose a Kullback‐Leibler information (KLI) control chart for linear profiles monitoring in Phase II. The plotted statistics of the KLI chart are calculated based on a backward procedure. The functional relationship is described by linear regression. The performance of the proposed KLI control chart is compared with those of other existing control charts, especially the Generalized Likelihood Ratio (GLR) chart for both KLI and GLR charts do not require design parameters. The results show that (1) the KLI control chart is better than the GLR control chart in detecting the shift of variance in terms of Average Time to Signal, and (2) if the shift of the regression coefficient is small, the GLR chart outperforms the KLI chart, but if the size of shift is large, the KLI chart outperforms the GLR chart. The plotted statistics of KLI are compared to that of GLR. Their similarity is discussed.
•Prediction of activities of daily living (ADL) is crucial for post-stroke patients.•No robust prediction models are currently available.•A machine learning-based approach to predict ADL is proposed ...based on the assessments from rehabilitation ward of a reference hospital.•ADL of post-stroke patients could be accurately predicted by the approach.
Prediction of activities of daily living (ADL) is crucial for optimized care of post-stroke patients. However, no suitably-validated and practical models are currently available in clinical practice.
Participants of a Post-acute Care-Cerebrovascular Diseases (PAC-CVD) program from a reference hospital in Taiwan between 2014 and 2016 were enrolled in this study. Based on 15 rehabilitation assessments, machine learning (ML) methods, namely logistic regression (LR), support vector machine (SVM), and random forest (RF), were used to predict the Barthel index (BI) status at discharge. Furthermore, SVM and linear regression were used to predict the actual BI scores at discharge.
A total of 313 individuals (men: 208; women: 105) were enrolled in the study. All the classification models outperformed single assessments in predicting the BI statuses of the patients at discharge. The performance of the LR and RF algorithms was higher (area under ROC curve (AUC): 0.79) than that of SVM algorithm (AUC: 0.77). In addition, the mean absolute errors of both SVM and linear regression models in predicting the actual BI score at discharge were 9.86 and 9.95, respectively.
The proposed ML-based method provides a promising and practical computer-assisted decision making tool for predicting ADL in clinical practice.
, a medicinal fungus that is abundant in bioactive compounds such as N6-(2-hydroxyethyl)-adenosine (HEA) and polysaccharides, possesses remarkable anti-inflammatory, antioxidant, and nerve damage ...recovery properties. Deep ocean water (DOW) contains minerals that can be absorbed and transformed into organic forms by fungi fermentation. Recent studies have shown that culturing
in DOW can enhance its therapeutic benefits by increasing the levels of bioactive compounds and minerals' bioavailibility. In this study, we investigated the effects of DOW-cultured
(DCC) on brain damage and memory impairment induced by D-galactose in rats. Our results indicate that DCC and its metabolite HEA can improve memory ability and exhibit potent antioxidant activity and free radical scavenging in D-galactose-induced aging rats (
< 0.05). Additionally, DCC can mitigate the expression of inflammatory factors, such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1β (IL-1β), cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS), thereby preventing brain aging. Furthermore, DCC showed a significant decrease in the expression of the aging-related proteins glial fibrillary acidic protein (GFAP) and presenilin 1 (PS1). By reducing brain oxidation and aging-related factors, DOW-cultured
demonstrate enhanced anti-inflammatory, antioxidant, and neuroprotective effects, making it a promising therapeutic agent for preventing and treating age-related brain damage and cognitive impairment.
This paper proposes a parameter‐free Kullback‐Leibler information control chart for monitoring sustained shifts in the process mean of a normally distributed process in phase II. Two plotted ...statistics are provided. One is based on our backward empirical sequential test, the other is based on the maximum log‐likelihood ratio change point method. These two achieve similar performances for the control chart. The performance of the proposed chart is compared with those of the cumulative sum chart, the exponentially weighted moving average chart, and the generalized likelihood ratio (GLR) chart. The results show that our proposed chart and the GLR chart have similar performances. Both can detect a wide range of shifts in the process mean, and neither requires design parameters other than the control limits. The proposed chart outperforms GLR when the size of the shift is below 1.24 standard deviations, while GLR outperforms the proposed chart when the size of the shift is above 1.24 standard deviations.
Obesity and excess adiposity are leading causes of metabolic and cardiovascular morbidity and mortality. Early identification of individuals at risk is key for preventive strategies. We examined the ...relationship between infant body composition (0-2 years of age) and later (>2 years) health outcomes using a systematic review.
We preregistered the study on PROSPERO (ID 288013) and searched Embase, PubMed and Cochrane databases for English language publications using the Medical Subject Headings (MeSH) terms 'infant' and 'body composition' and 'risk' between January 1946 and February 2022. We included studies which assessed infant body composition using predetermined in vivo methods other than body mass index (BMI).
We identified 6015 articles. After abstract screening to assess eligibility, we reviewed 130 full text publications. 30 were included in the final assessment and narrative synthesis. Meta-analysis was not possible due to heterogeneity of results. All 30 studies were of high quality and reported associations between infant body composition and 19 different health outcomes after 2 years of age. Outcome measurements ranged from 2 years to 16 years. The strongest associations were found between infant fat mass and later fat mass (7 studies), and later BMI (5 studies). For 11 of the outcomes assessed, there was no relationship to infant adiposity detected.
Current evidence, from a small number of studies, suggests a positive association between infant adiposity and future adiposity or BMI, but the validity of infant body composition as a biomarker of future health remains inconclusive. Carefully designed, standardised studies are required to identify the value of infant body composition for predicting later health.
PROSPERO: 288013.
Taiwan's National Health Insurance (NHI) program forced discontinuation of biologic use in Crohn's disease (CD) after a limited treatment duration, regardless of disease activity. This study ...investigated the retreatment rate and suboptimal outcomes (i.e., CD‐related surgeries, hospitalizations, emergency room visits, and oral steroid flare‐ups) after forced discontinuation. This retrospective cohort study was conducted using data from the NHI Database. Patients who received ≥40 weeks of biologic treatment followed by a forced discontinuation were included. The time of biologic retreatment and the cumulative incidence of suboptimal outcomes after the forced discontinuation as well as related risk factors were analyzed. Included were 215 patients (68% male). At the beginning of biologic therapy, the mean age (±SD) was 35.7 (±13.5) years, and the disease duration was 4.46 (±3.52) years. The median (interquartile range) biologic treatment duration was 57.86 (50.3–83.3) weeks. Within the first year after forced discontinuation, 67% of patients (n = 144) were retreated with a second course of biologics, and 53% of patients (n = 114) experienced at least one suboptimal outcome. The independent risk factors associated with the occurrence of suboptimal outcomes were CD‐related emergency room visits and hospitalizations during biologic therapy (hazard ratio: 2.49; 95% confidence interval: 1.59–3.89). More than two‐thirds of patients with CD required biological retreatment within 1 year after a forced discontinuation. The substantial proportion of patients with poor disease outcomes highlights the need to continue the biologic.
Main Findings of the Study.
During tumorigenesis, urokinase (uPA) and uPA receptor (uPAR) play essential roles in mediating pathological progression in many cancers. To understand the crosstalk between the uPA/uPAR signaling ...and cancer, as well as to decipher their cellular pathways, we proposed to use cancer driver genes to map out the uPAR signaling. In the study, an integrated pharmaceutical bioinformatics approach that combined modulator identification, driver gene ontology networking, protein targets prediction and networking, pathway analysis and uPAR modulator screening platform construction was employed to uncover druggable targets in uPAR signaling for developing a novel anti-cancer modality. Through these works, we found that uPAR signaling interacted with 10 of 21 KEGG cancer pathways, indicating the important role of uPAR in mediating intracellular cancerous signaling. Furthermore, we verified that receptor tyrosine kinases (RTKs) and ribosomal S6 kinases (RSKs) could serve as signal hubs to relay uPAR-mediated cellular functions on cancer hallmarks such as angiogenesis, proliferation, migration and metastasis. Moreover, we established an in silico virtual screening platform and a uPAR–driver gene pair rule for identifying potential uPAR modulators to combat cancer. Altogether, our results not only elucidated the complex networking between uPAR modulation and cancer but also provided a paved way for developing new chemical entities and/or re-positioning clinically used drugs against cancer.
Surface properties are essential for substrates exhibiting high sensitivity in surface‐enhanced Raman scattering (SERS) applications. In this work, novel SERS hybrid substrates using ...polystyrene‐block‐poly(methyl methacrylate) and anodic aluminum oxide templates is presented. The hybrid substrates not only possess hierarchical porous nanostructures but also exhibit superhydrophilic surface properties with the water contact angle ≈0°. Such surfaces play an important role in providing uniform enhanced intensities over large areas (relative standard deviation ≈10%); moreover, these substrates are found to be highly sensitive (limit of detection ≈10−12 m for rhodamine 6G (R6G)). The results show that the hybrid SERS substrates can achieve the simultaneous detection of multicomponent mixtures of different target molecules, such as R6G, crystal violet, and methylene blue. Furthermore, the bending experiments show that about 70% of the SERS intensities are maintained after bending from ≈30° to 150°.
Novel surface‐enhanced Raman scattering hybrid substrates using polystyrene‐block‐poly(methyl methacrylate) and anodic aluminum oxide templates is presented. The hybrid substrates exhibit superhydrophilic surface properties with the water contact angle ≈0°, providing uniform enhanced intensities over large areas; moreover, these substrates are found to be highly sensitive (limit of detection ≈10−12 m for rhodamine 6G).
