Reproducibility study of intravoxel incoherent motion and apparent diffusion coefficient parameters in normal pancreas.

BACKGROUND: The consistency of pancreatic apparent diffusion coefficient (ADC) values and intravoxel incoherent motion (IVIM) parameter values across different magnetic resonance imaging (MRI) devices significantly impacts the patient's diagnosis and treatment. AIM: To explore consistency in image quality, ADC values, and IVIM parameter values among different MRI devices in pancreatic examinations. METHODS: This retrospective study was approved by the local ethics committee, and informed consent was obtained from all participants. In total, 22 healthy volunteers (10 males and 12 females) aged 24-61 years (mean, 28.9 ± 2.3 years) underwent pancreatic diffusion-weighted imaging using 3.0T MRI equipment from three vendors. Two independent observers subjectively scored image quality and measured the pancreas's overall ADC values and signal-to-noise ratios (SNRs). Subsequently, regions of interest (ROIs) were delineated for the IVIM parameters (true diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction) using post-processing software. These ROIs were on the head, body, and tail of the pancrease. The subjective image ratings were assessed using the kappa consistency test. Intraclass correlation coefficients (ICCs) and mixed linear models were used to evaluate each device's quantitative parameter values. Finally, a pairwise analysis of IVIM parameter values across each device was performed using Bland-Altman plots. RESULTS: The Kappa value for the subjective ratings of the different observers was 0.776 (P < 0.05). The ICC values for inter-observer and intra-observer agreements for the quantitative parameters were 0.803 [95% confidence interval (CI): 0.684-0.880] and 0.883 (95%CI: 0.760-0.945), respectively (P < 0.05). The ICCs for the SNR between different devices was comparable (P > 0.05), and the ICCs for the ADC values from different devices were 0.870, 0.707, and 0.808, respectively (P < 0.05). Notably, only a few statistically significant inter-device agreements were observed for different IVIM parameters, and among those, the ICC values were generally low. The mixed linear model results indicated differences (P < 0.05) in the f-value for the pancreas head, D-value for the pancreas body, and D-value for the pancreas tail obtained using different MRI machines. The Bland-Altman plots showed significant variability at some data points. CONCLUSION: ADC values are consistent among different devices, but the IVIM parameters' repeatability is moderate. Therefore, the variability in the IVIM parameter values may be associated with using different MRI machines. Thus, caution should be exercised when using IVIM parameter values to assess the pancreas.

Application of the clearance rate of inflammatory markers for evaluation of the therapeutic effect in adult bacterial bloodstream infection.

BACKGROUND: Bloodstream infection (BSI) is a serious systemic infectious disease. This study aimed to investigate the application of the clearance rate of interleukin-6, procalcitonin, and C-reactive protein for the evaluation of antimicrobial efficacy in adult bacterial BSI without other inflammatory factors. METHODS: Patients with positive blood culture and without other inflammatory factors in The First Hospital of Hebei Medical University from January 2017 to December 2019, who received continuous detection interleukin-6, procalcitonin, and C-reactive protein, were selected. The clearance rate of these inflammatory markers was calculated, and the consistency test (kappa test) was performed to analyze the clinical outcomes (cure, improvement, delay, deterioration, or death). RESULTS: For adult patients with bacterial BSI without other inflammatory factors, the testing speculation based on the clearance rate of interleukin-6 and C-reactive protein was consistent with the clinical outcome of the patients, with kappa values of 0.784 and 0.714, respectively (P=0.000). The testing speculation based on the procalcitonin clearance rate was generally consistent with the clinical outcome, with a kappa value of 0.685 (P=0.000). The testing speculation based on the procalcitonin clearance rate showed good consistency with the clinical outcome of patients with Gram-positive cocci infection, kappa =0.813 (P=0.000); for patients with gram-negative bacilli infection, the consistency of clinical outcomes was general, kappa =0.649 (P=0.000). CONCLUSIONS: In adult patients with bacterial BSI without other inflammatory factors, the clearance rate of interleukin-6, procalcitonin, and C-reactive protein can predict the clinical outcome within 24 hours, among which the procalcitonin clearance rate can better predict the clinical outcome of patients with Gram-negative bacilli infection. This approach can be used to evaluate the effectiveness of anti-infection treatment in early-stage BSI.

Evaluation of deep learning techniques for identification of sarcoma-causing carcinogenic mutations.

The abnormal growth of human healthy cells is called cancer. One of the major types of cancer is sarcoma, mostly found in human bones and soft tissue cells. It commonly occurs in children. According to a survey of the United States of America, there are more than 17,000 sarcoma patients registered each year which is 15% of all cancer cases. Recognition of cancer at its early stage saves many lives. The proposed study developed a framework for the early detection of human sarcoma cancer using deep learning Recurrent Neural Network (RNN) algorithms. The DNA of a human cell is made up of 25,000 to 30,000 genes. Each gene is represented by sequences of nucleotides. The nucleotides in a sequence of a driver gene can change which is termed as mutations. Some mutations can cause cancer. There are seven types of a gene whose mutation causes sarcoma cancer. The study uses the dataset which has been taken from more than 134 samples and includes 141 mutations in 8 driver genes. On these gene sequences RNN algorithms Long and Short-Term Memory (LSTM), Gated Recurrent Units and Bi-directional LSTM (Bi-LSTM) are used for training. Rigorous testing techniques such as Self-consistency testing, independent set testing, 10-fold cross-validation test are applied for the validation of results. These validation techniques yield several metrics such as Area Under the Curve (AUC), sensitivity, specificity, Mathew's correlation coefficient, loss, and accuracy. The proposed algorithm exhibits an accuracy of 99.6% with an AUC value of 1.00.

Analysis of Factors Influencing Multidrug-Resistant Tuberculosis and Validation of Whole-Genome Sequencing in Children with Drug-Resistant Tuberculosis.

OBJECTIVE: Pediatric tuberculosis (TB) is one of the top ten causes of death in children. Our study was to analyze influencing factors of multidrug-resistant tuberculosis (MDR-TB) and validation of whole-genome sequencing (WGS) used in children with drug-resistant TB (DR-TB). METHODS: All Mycobacterium tuberculosis (Mtb) strains were isolated from patients aged below 18 years old of Children's Hospital of Chongqing Medical University, China. A total of 208 Mtb isolates were tested for eight anti-TB drugs with phenotypic drug susceptibility test (DST) and for genetic prediction of the susceptible profile with WGS. The patients corresponding to each strain were grouped according to drug resistance and genotype. Influencing factors of MDR-TB and DR-TB were analyzed. RESULTS: According to the phenotypic DST and WGS, 82.2% of Mtb strains were susceptible to all eight drugs, and 6.3% were MDR-TB. Using the phenotypic DSTs as the gold standard, the kappa value of WGS to predict isoniazid, rifampin, ethambutol, rifapentine, prothionamide, levofloxacin, moxifloxacin and amikacin was 0.84, 0.89, 0.59, 0.86, 0.89, 0.82, 0.88 and 1.00, respectively. There was significant difference in the distribution of severe TB, diagnosis, treatment and outcome between MDR and drug-susceptible group (P<0.05). The distribution of severe TB and treatment between DR and drug-susceptible group was statistically different (P<0.05). The results of binary logistic regression showed that Calmette-Guérin bacillus (BCG) vaccine is the protective factor for MDR-TB (OR=0.19), and MDR-TB is the risk factor for PTB and EPTB (OR=17.98). CONCLUSION: The BCG vaccine is a protective factor for MDR-TB, and MDR-TB might not be confined to pulmonary infection, spreading to extrapulmonary organs in children. MDR-TB had more severe cases and a lower recovery rate than drug-susceptible TB. WGS could provide an accurate prediction of drug susceptibility test results for anti-TB drugs, which are needed for the diagnosis and precise treatment of TB in children.

Estimating the Influence of Physicochemical and Biochemical Property Indexes on Selection for Amino Acids Usage in Eukaryotic Cells.

Proteins can evolve by accumulating changes on amino acid sequences. These changes are mainly caused by missense mutations on its DNA coding sequences. Mutations with neutral or positive effects on fitness can be maintained while deleterious mutations tend to be eliminated by natural selection. Amino acid changes are influenced by the biophysical, chemical, and biological properties of amino acids. There is a multiplicity of amino acid properties that can influence the function and expression of proteins. Amino acid properties can be expressed into numerical indexes, which can help to predict functional and structural aspects of proteins and allow statistical inferences of selection pressure on amino acid usage. The accuracy of these analyses may be compromised by the existence of several numerical indexes that measure the same amino acid property, and the lack of objective parameters to determine the most accurate and biologically relevant index. In the present study, the gradient consistency test was used in order to estimate the magnitude of directional selection imparted by amino acid biochemical and biophysical properties on protein evolution.

Assessing consistency in clinical trials with two subgroups and binary endpoints: A new test within the logistic regression model.

In late stage drug development, the experimental drug is tested in a diverse study population within the relevant indication. In order to receive marketing authorization, robust evidence for the therapeutic efficacy is crucial requiring investigation of treatment effects in well-defined subgroups. Conventionally, consistency analyses in subgroups have been performed by means of interaction tests. However, the interaction test can only reject the null hypothesis of equivalence and not confirm consistency. Simulation studies suggest that the interaction test has low power but can also be oversensitive depending on sample size-leading in combination with the actually ill-posed null hypothesis to findings regardless of clinical relevance. In order to overcome these disadvantages in the setup of binary endpoints, we propose to use a consistency test based on the interval inclusion principle, which is able to reject heterogeneity and confirm consistency of subgroup-specific treatment effects while controlling the type I error. This homogeneity test is based upon the deviation between overall treatment effect and subgroup-specific effects on the odds ratio scale and is compared with an equivalence test based on the ratio of both subgroup-specific effects. Performance of these consistency tests is assessed in a simulation study. In addition, the consistency tests are outlined for the relative risk regression. The proposed homogeneity test reaches sufficient power in realistic scenarios with small interactions. As expected, power decreases for unbalanced subgroups, lower sample sizes, and narrower margins. Severe interactions are covered by the null hypothesis and are more likely to be rejected the stronger they are.

Consistency test of coincidence-summing calculation methods for extended sources.

An internal consistency test of the calculation of coincidence-summing correction factors FC for volume sources is presented. The test is based on exact equations relating the values of FC calculated for three ideal measurement configurations. The test is applied to a number of 33 sets of FC values sent by 21 teams. Most sets passed the test, but not the results obtained using the quasi-point source approximation; in the latter case the test qualitatively indicated the magnitude of the bias of FC.

The MULTISENSE Test of Lexical-Gustatory Synaesthesia: An automated online diagnostic.

Lexical-gustatory (LG) synesthesia is an intriguing neurological condition in which individuals experience phantom tastes when hearing, speaking, reading, or thinking about words. For example, the word "society" might flood the mouth of an LG synesthete with the flavor of fried onion. The condition is usually verified in individuals by obtaining verbal descriptions of their word-flavor associations on more than one occasion, separated by several months. Their flavor associations are significantly more consistent over time than are those of controls (who are asked to invent associations by intuition and to recall them from memory). Although this test reliably dissociates synesthetes from nonsynesthetes, it suffers from practical and methodological limitations. Here we present a novel, automated, online consistency test, which can be administered in just 30 min in order to instantly and objectively verify LG synesthesia. We present data from two versions of our diagnostic test, in which synesthetes report their synesthetic flavors either from a hierarchical set of food categories (Exp. 1) or by specifying their basic component tastes (sweet, salty, bitter, etc.). We tested the largest sample of self-declared LG synesthetes studied to date and used receiver operating characteristic analysis to assess the discriminant power of our tests. Although both our methods discriminated synesthetes from controls, our second test (Exp. 2) has greater discriminatory power with a threshold cutoff. We suggest that our novel diagnostic for LG synesthesia has unprecedented benefits in its automated and objective scoring, its ease of use for participants and researchers, its short testing time, and its online platform.

Application of different patella height indices in patients undergoing total knee arthroplasty.

BACKGROUND: One complication of total knee arthroplasty (TKA) is patella baja (PB). Patellar tendon shortening and joint line elevation are two main causes of PB. The purpose of this study was to determine the incidence of PB before and after TKA by measuring the patellar height and provide evidence for choosing a suitable index. METHODS: In total, 256 consecutive patients who underwent primary TKA were included in this study. Radiographic measurements were performed; the Insall-Salvati (IS) index, modified IS (MIS) index, Blackburne-Peel (BP) index, and Caton-Deschamps (CD) index were computed; and the incidence of PB was calculated before and after the operation. The consistency between the IS and MIS indices and between the BP and CD indices was analyzed. RESULTS: The preoperative incidence of true PB (TPB) and pseudo-PB (PPB) was 9.4 and 0.8%, respectively. The postoperative incidence of TPB and PPB was 10.2 and 9.0%, respectively. The consistency between the IS and MIS indices was moderate preoperatively (pre-kappa = 0.602) and postoperatively (post-kappa = 0.742). The consistency between the BP and CD indices was moderate preoperatively (pre-kappa = 0.742) and good postoperatively (post-kappa = 0.797). CONCLUSION: The incidence of PB, especially PPB, increased after TKA. The CD and BP indices are of greater importance for the diagnosis of PB after TKA. The MIS index is a better choice than the IS index to measure the length of the patellar tendon. To measure the height of the joint line, the BP index is better postoperatively and the CD index is better preoperatively.

On clinical trials with a high placebo response rate.

The basic problem that causes the frequent failure of a standard randomized parallel placebo-controlled clinical trial with a high placebo response rate is the underestimation of the treatment effect by the observed relative treatment difference. A two-period sequential parallel enrichment design has been proposed where the first period is a standard parallel design and at the end of the first period, the placebo non-responders are identified and re-randomized in the second period. Based on such a design, available methods have primarily focused on testing either the first period treatment null hypothesis or the global null hypothesis defined as the joint period 1 and period 2 treatment effect null hypothesis by a test statistic which is either derived from a combined statistic or defined directly as a weighted z-score where the weights are functions of some population and design parameters satisfying certain power optimality criterion. However, in some cases, it is not clear what their combined statistics are estimating and in others, the combined statistics are estimating the apparent treatment effect; but generally, there is no discussion of the need to provide a proper assessment of the treatment effect for the intended study population. It should be clear that an appropriate assessment of the treatment effect for the intended study population is critical for the benefit/risk analysis as well as the proper dosage recommendation. Any benefit/risk analysis and dosage recommendation that are based on an apparent treatment effect from a standard parallel design such as the first period of a sequential parallel enrichment design tend to underestimate the benefit/risk ratio which in turn may lead to overdosing recommendation. It is the purpose of this paper to introduce the concept of an adjusted treatment effect which is derived by adjusting the apparent treatment effect from the first period of a sequential parallel enrichment design with information from the second period subject to a consistency condition. The adjustment properly compensates for the high placebo response rate. It is proposed that this adjusted treatment effect should be used to assess the treatment effect for the intended study population and should be the basis for the benefit/risk analysis and the dosage recommendation.