Category: Statistics

Diseases. 2021 Sep 17;9(3):61. doi: 10.3390/diseases9030061.

ABSTRACT

To examine the association between uric acid levels and liver enzyme functions amongst adults with hyperuricemia and gout in the United States. The National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2016 was used to study the research objective. Data were analyzed for descriptive statistics and for differences using the t test, Chi-square test and ANOVA. A regression analysis was performed to determine association between demographics and liver enzymes. A p value of <0.05 or <0.001 was considered statistically significant. A total of 14,946 adults (≥20 yrs.) were included in this study. Sample mean age was 49 ± 0.15 yrs., and 54% were female. Overall, 15% adults had elevated uric acid levels (≥6.8 mg/dL), men had significantly higher uric acid levels than women (6 mg/dL vs. 4.8 mg/dL). High uric acid levels were associated with more than two times higher odds of elevated ALT, AST and GGT (p < 0.001). Similarly, gender-based target uric acid values were associated with two-fold increased odds of GGT, over one-and-a-half fold higher odds of ALT and AST (p < 0.001). Regression analysis showed significant association between age, gender, race/ethnicity, body mass index, and hypertension and ALT, AST, ALP, total bilirubin and GGT (p < 0.001). Adults with hyperuricemia and gout are most likely to develop liver dysfunctions and suffer associated morbidities. Such patients need to be appropriately monitored and managed for their liver functions and to prevent associated morbidities.

PMID:34562968 | DOI:10.3390/diseases9030061

Dent J (Basel). 2021 Sep 6;9(9):105. doi: 10.3390/dj9090105.

ABSTRACT

BACKGROUND: The treatment of the surface of titanium implants with argon plasma improved its hydrophilicity and cell adhesion, resulting in higher bone apposition on implant and graft surfaces. The spontaneous perforation over time of the sinus mucosa after sinus augmentation has been documented in experimental studies at both implants and graft particles. The aim of the present study was to evaluate the influence of plasma argon treatment of the implant surface on bone apposition and on the rate of sinus mucosa perforations.

METHODS: A sinus lifting procedure was performed bilaterally in sixteen rabbits, and implants, either treated with argon plasma or left without treatment (control), were placed simultaneously without grafts. After 8 weeks, histological analyses were carried out.

RESULTS: A collapse of the sinus mucosa was observed at all implants. Twenty-four out of thirty-two implants presented sinus mucosa perforations at the apex. Several perforations were also found at the threads. Thinned mucosa sites (width < 40 µm) were found around almost all implants. About 2.6-2.9 mm of the apical regions of the implant did not present signs of osseointegration and about 1.3 mm were exposed to the sinus cavity. No statistically significant differences were found between plasma and control sites.

CONCLUSIONS: In conclusion, the sinus mucosa was damaged and perforated by direct contact with treated and non-treated implant surfaces. The treatment of the implant surface with argon plasma did not affect the outcomes.

PMID:34562979 | DOI:10.3390/dj9090105

Audiol Res. 2021 Sep 17;11(3):474-490. doi: 10.3390/audiolres11030044.

ABSTRACT

There is an increasing need for state-of-the-art Central Auditory Processing assessment for Portuguese native speakers, applicable as early as possible. As a contribution to answering this need, this paper presents a new battery for Central Auditory Processing assessment for European Portuguese applicable to children aged 5 and above, named BAPA-PE, providing information regarding test selection and development. The battery consists of six behavioral tests: Staggered Spondaic Words (SSW) for European Portuguese, Filtered Speech, Speech in Noise, Detection Interval in Noise, Duration, and Frequency Pattern. The normative data for children aged 5 to 12 are also reported. A sample was obtained of 217 subjects without ear pathology and with typical development. Each age group was composed of at least 30 children. All children were evaluated using pure tone audiometry, speech audiometry, impedance, and otoacoustic emissions. Normative scores are reported for each of the six auditory processing tests. The assessment is applicable to young children (aged 5 and 6). The statistical analyses showed significant effects in scores of Age for all tests and of Ear for several tests. The main result from the work presented, the Auditory Processing Assessment Battery-European Portuguese (BAPA-PE), is available for clinical use with normative data. This battery is a new tool for behaviorism assessment of European Portuguese speakers with suspected central auditory pathology and for monitoring the results of auditory training.

PMID:34562882 | DOI:10.3390/audiolres11030044

Biosensors (Basel). 2021 Aug 26;11(9):297. doi: 10.3390/bios11090297.

ABSTRACT

Vascular Access (VA) is often referred to as the “Achilles heel” for a Hemodialysis (HD)-dependent patient. Both the patent and sufficient VA provide adequacy for performing dialysis and reducing dialysis-related complications, while on the contrary, insufficient VA is the main reason for recurrent hospitalizations, high morbidity, and high mortality in HD patients. A non-invasive Vascular Wall Motion (VWM) monitoring system, made up of a pulse radar sensor and Support Vector Machine (SVM) classification algorithm, has been developed to detect access flow dysfunction in Arteriovenous Fistula (AVF). The harmonic ratios derived from the Fast Fourier Transform (FFT) spectrum-based signal processing technique were employed as the input features for the SVM classifier. The result of a pilot clinical trial showed that a more accurate prediction of AVF flow dysfunction could be achieved by the VWM monitor as compared with the Ultrasound Dilution (UD) flow monitor. Receiver Operating Characteristic (ROC) curve analysis showed that the SVM classification algorithm achieved a detection specificity of 100% at detection thresholds in the range from 500 to 750 mL/min and a maximum sensitivity of 95.2% at a detection threshold of 750 mL/min.

PMID:34562887 | DOI:10.3390/bios11090297

Adv Med Sci. 2021 Sep 22;67(1):1-9. doi: 10.1016/j.advms.2021.09.001. Online ahead of print.

ABSTRACT

PURPOSE: Antibiotic resistance is widespread throughout the world and represents a serious health concern. There is an urgent need for the development of novel tools for rapidly distinguishing antibiotic resistant bacteria from susceptible strains. Previous work has demonstrated that differences in antimicrobial susceptibility can be reflected in differences in the profile of volatile organic compounds (VOCs) produced by dissimilar strains. The aim of this study was to investigate the effect of the presence of cephalosporin antibiotics on the VOC profile of extended spectrum beta-lactamase (ESBL) and non-ESBL producing strains of Escherichia coli.

MATERIAL AND METHODS: In this study, VOCs from strains of Escherichia coli positive and negative for the most commonly encountered ESBL, CTX-M in the presence of cephalosporin antibiotics were assessed using solid-phase microextraction (SPME) coupled with a combined gas chromatography-mass spectrometry/metal oxide sensor (GC-MS/MOS) system.

RESULTS: Our proof-of-concept study allowed for distinguishing CTX-M positive and negative bacteria within 2 ​h after the addition of antibiotics. One MOS signal (RT: 22.6) showed a statistically significant three-way interaction (p ​= ​0.033) in addition to significant two-way interactions for culture and additive (p ​= ​0.046) plus time and additive (p ​= ​0.020). There were also significant effects observed for time (p ​= ​0.009), culture (p ​= ​0.030) and additive (p ​= ​0.028). No effects were observed in the MS data.

CONCLUSIONS: The results of our study showed the potential of VOC analysis using SPME combined with a GC-MS/MOS system for the early detection of CTX-M-producing, antibiotic-resistant E. coli, responsible for urinary tract infections (UTIs).

PMID:34562855 | DOI:10.1016/j.advms.2021.09.001

Diabetes Metab Syndr. 2021 Sep 11;15(6):102280. doi: 10.1016/j.dsx.2021.102280. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Reproductive-aged women are prone to type 2 diabetes mellitus. This study aims to evaluate the optimal cut off point of Triglyceride/Glucose Index for predicting glucose status conversion among women of reproductive age.

METHODS: This study involved normoglycemic and prediabetes women aged 20-49 years from the Bogor Non-Communicable Diseases Cohort Study (West Java, Indonesia) conducted from 2011 to 2016. Statistical analysis was performed using Receiver Operating Characteristics curve analysis with STATA version 15.

RESULTS: Among prediabetes subjects (n = 371), the cut-off point of TyG index for regression from prediabetes to normoglycemic subjects was <4.51 [sensitivity, specificity, AUC (95%CI) 83.9%, 80.1%, 0.913 (0.875-0.943), respectively] and the cut-off point for progression from prediabetes to diabetes was >4.54 [80.0%, 73.1%, 0.858 (0.807-0.900)]. Among normoglycemic subjects (n = 1300), the cut-off point of TyG index for progression to prediabetes and diabetes were >4.44 [80.1%, 71.1%, 0.834 (0.812-0.854)] and >4.47 [80.6%, 80.8%, 0.909 (0.890-0.926)] respectively.

CONCLUSION: Based on sample of subjects evaluated between 2011 and 2016, TyG index appears to be a promising marker for glucose status conversion among reproductive-aged women in Jakarta, Indonesia.

PMID:34562866 | DOI:10.1016/j.dsx.2021.102280

Clin Imaging. 2021 Sep 21;80:454-458. doi: 10.1016/j.clinimag.2021.09.003. Online ahead of print.

ABSTRACT

PURPOSE: Prostate volume and PSA density (PSAd) are important in the risk stratification of suspected prostate cancer (Pca). PI-RADS v2.1 allows for determining volume via segmentation or ellipsoid calculation. The purpose of our study was to compare ellipsoid and segmentation volume calculation methods and evaluate if PSAd diagnostic performance is altered.

METHODS: We retrospectively assessed 397 patients (mean age/standard deviation: 63.7/7.4 years) who underwent MRI and prostate biopsy or prostatectomy, with Pca classified by Gleason ≥3 + 4 and ≥4 + 4 disease. Prostate total volumes were determined with ellipsoid calculations (TVe) and with semi-automated segmentation (TVs), along with inter-rater reliability with intraclass correlation coefficient (ICC). PSAd was calculated for TVe and TVs and ROC curves were created to compare performance for Gleason ≥3 + 4 and ≥4 + 4 disease.

RESULTS: TVe was significantly higher than TVs (p < 0.0001), with mean TVe = 55.4 mL and TVs = 51.0 mL. ROC area under the curve for PSAd derived with TVe (0.63, 95%CI:0.59-0.68) and TVs (0.64, 95%CI:0.59-0.68) showed no significant difference for Gleason ≥3 + 4 disease (p = 0.45), but PSAd derived with TVs (0.63, 95%CI: 0.58-0.68) significantly outperformed TVe (0.61, 95%CI: 0.57-0.67) for Gleason ≥4 + 4 disease (p = 0.02). Both methods demonstrated excellent inter-rater reliability with TVe with ICC of 0.93(95%CI: 0.92-0.94) and TVs with ICC of 0.98(95%CI: 0.98-0.99).

CONCLUSION: Traditional ellipsoid measurements tend to overestimate total prostate volume compared to segmentation, but both methods demonstrate similar diagnostic performance of derived PSA density for PI-RADS clinically significant disease. For higher grade disease, PSAd derived from segmentation volumes demonstrates statistically significant superior performance. Both methods are viable, but segmentation volume is potentially better.

PMID:34562834 | DOI:10.1016/j.clinimag.2021.09.003

J Mol Graph Model. 2021 Sep 18;109:108022. doi: 10.1016/j.jmgm.2021.108022. Online ahead of print.

ABSTRACT

Targeting Polo-like kinase 1 (Plk1) by molecular inhibitors is being a promising approach for tumor therapy. Nevertheless, insufficient methodical analyses have been done to characterize the interactions inside the Plk1 binding pocket. In this study, an extensive combined ligand and structure-based drug design workflow was conducted to data-mine the structural requirements for Plk1 inhibition. Consequently, the binding modes of 368 previously known Plk1 inhibitors were investigated by pharmacophore generation technique. The resulted pharmacophores were engaged in the context of Genetic function algorithm (GFA) and Multiple linear regression (MLR) analyses to search for a prognostic QSAR model. The most successful QSAR model was with statistical criteria of (r²₂₇₇ = 0.76, r²adj = 0.76, r²pred = 0.75, Q² = 0.73). Our QSAR-selected pharmacophores were validated by Receiver Operating Characteristic (ROC) curve analysis. Later on, the best QSAR model and its associated pharmacophoric hypotheses (HypoB-T4-5, HypoI-T2-7, HypoD-T4-3, and HypoC-T3-3) were used to identify new Plk1 inhibitory hits retrieved from the National Cancer Institute (NCI) database. The most potent hits exhibited experimental anti-Plk1 IC₅₀ of 1.49, 3.79. 5.26 and 6.35 μM. Noticeably, our hits, were found to interact with the Plk1 kinase domain through some important amino acid residues namely, Cys67, Lys82, Cys133, Phe183, and Asp194.

PMID:34562852 | DOI:10.1016/j.jmgm.2021.108022

Schizophr Res. 2021 Sep 22;238:10-19. doi: 10.1016/j.schres.2021.08.026. Online ahead of print.

ABSTRACT

Nonlinear dynamical analysis has been used to quantify the complexity of brain signal at temporal scales. Power law scaling is a well-validated method in physics that has been used to describe the dynamics of a system in the frequency domain, ranging from noisy oscillation to complex fluctuations. In this research, we investigated the power-law characteristics in a large-scale resting-state fMRI data of schizophrenia and healthy participants derived from Taiwan Aging and Mental Illness cohort. We extracted the power spectral density (PSD) of resting signal by Fourier transform. Power law scaling of PSD was estimated by determining the slope of the regression line fitting to the logarithm of PSD. t-Test was used to assess the statistical difference in power law scaling between schizophrenia and healthy participants. The significant differences in power law scaling were found in six brain regions. Schizophrenia patients have significantly more positive power law scaling (i.e., more homogenous frequency components) at four brain regions: left precuneus, left medial dorsal nucleus, right inferior frontal gyrus, and right middle temporal gyrus and less positive power law scaling (i.e., more dominant at lower frequency range) in bilateral putamen compared with healthy participants. Moreover, significant correlations of power law scaling with the severity of psychosis were found. These findings suggest that schizophrenia has abnormal brain signal complexity linked to psychotic symptoms. The power law scaling represents the dynamical properties of resting-state fMRI signal may serve as a novel functional brain imaging marker for evaluating patients with mental illness.

PMID:34562833 | DOI:10.1016/j.schres.2021.08.026

Neural Netw. 2021 Sep 9;144:394-406. doi: 10.1016/j.neunet.2021.09.005. Online ahead of print.

ABSTRACT

Uncertainty evaluation is a core technique when deep neural networks (DNNs) are used in real-world problems. In practical applications, we often encounter unexpected samples that have not seen in the training process. Not only achieving the high-prediction accuracy but also detecting uncertain data is significant for safety-critical systems. In statistics and machine learning, Bayesian inference has been exploited for uncertainty evaluation. The Bayesian neural networks (BNNs) have recently attracted considerable attention in this context, as the DNN trained using dropout is interpreted as a Bayesian method. Based on this interpretation, several methods to calculate the Bayes predictive distribution for DNNs have been developed. Though the Monte-Carlo method called MC dropout is a popular method for uncertainty evaluation, it requires a number of repeated feed-forward calculations of DNNs with randomly sampled weight parameters. To overcome the computational issue, we propose a sampling-free method to evaluate uncertainty. Our method converts a neural network trained using dropout to the corresponding Bayesian neural network with variance propagation. Our method is available not only to feed-forward NNs but also to recurrent NNs such as LSTM. We report the computational efficiency and statistical reliability of our method in numerical experiments of language modeling using RNNs, and the out-of-distribution detection with DNNs.

PMID:34562813 | DOI:10.1016/j.neunet.2021.09.005