Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program.

BACKGROUND/AIMS: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1-3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. METHODS: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. RESULTS: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. CONCLUSION: Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

High-sensitivity flip chip blue Mini-LEDs miniaturized optical instrument for non-invasive glucose detection.

The colorimetric detection of glucose typically involves a peroxidase reaction producing a color, which is then recorded and analyzed. However, enzyme detection has difficulties with purification and storage. In addition, replacing enzyme detection with chemical methods involves time-consuming steps such as centrifugation and purification and the optical instruments used for colorimetric detection are often bulky and not portable. In this study, ammonium metavanadate and sulfuric acid were used to prepare the detection solution instead of peroxidase to produce color. We also analyzed the effect of different concentrations of detection solution on absorbance sensitivity. Finally, a flip chip blue Mini-LEDs miniaturized optical instrument (FC blue Mini-LEDs MOI) was designed for glucose detection using optics fiber, collimating lenses, a miniaturized spectrometer, and an FC Blue Mini-LEDs with a center wavelength of 459 nm. While detecting glucose solutions in the concentration range of 0.1-10 mM by the developed MOI, the regression equation of y = 0.0941x + 0.1341, R2 of 0.9744, the limit of detection was 2.15 mM, and the limit of quantification was 7.163 mM. Furthermore, the preparation of the detection solution only takes 10 min, and the absorbance sensitivity of the optimized detection solution could be increased by 2.3 times. The detection solution remained stable with only a 0.6% decrease in absorbance compared to the original after storing it in a refrigerated environment at 3 °C for 14 days. The method proposed in this study for detecting glucose using FC blue light Mini-LEDs MOI reduces the use of peroxidase. In addition, it has a wide detection range that includes blood as well as non-invasive saliva and tear fluids, providing patients with a miniaturized, highly sensitive, and quantifiable glucose detection system.

Spectral analysis with highly collimated mini-LEDs as light sources for quantitative detection of direct bilirubin.

Because the human eye cannot visually detect the results of direct bilirubin test papers accurately and quantitatively, this study proposes four different highly collimated mini light-emitting diodes (HC mini-LEDs) as light sources for detection. First, different concentrations of bilirubin were oxidized to biliverdin by FeCl3 on the test paper, and pictures were obtained with a smartphone. Next, the red, green, and blue (RGB) channels of the pictures were separated to average grayscale values, and their linear relationship with the direct bilirubin concentration was analyzed to detect bilirubin on the test paper noninvasively and quantitatively. The experimental results showed that when green HC mini-LEDs were used as the light sources and image analysis was performed using the G channel, for a direct bilirubin concentration range of 0.1-2 mg/dL, the G channel determination coefficient (R2) reached 0.9523 and limit of detection was 0.459 mg/dL. The detection method proposed herein has advantages such as rapid analysis, noninvasive detection, and digitization according to RGB grayscale changes in the images of the detection test paper.

Noninvasive direct bilirubin detection by spectral analysis of color images using a Mini-LED light source.

Urine test paper is a standard, noninvasive detection method for direct bilirubin, but this method can only achieve qualitative analysis and cannot achieve quantitative analysis. This study used Mini-LEDs as the light source, and direct bilirubin was oxidized to biliverdin by an enzymatic method with ferric chloride (FeCl3) for labeling. Images were captured with a smartphone and evaluated for red (R), green (G), and blue (B) colors to analyze the linear relationship between the spectral change of the test paper image and the direct bilirubin concentration. This method achieved noninvasive detection of bilirubin. The experimental results demonstrated that Mini-LEDs can be used as the light source to analyze the grayscale value of the image RGB. For the direct bilirubin concentration range of 0.1-2 mg/dL, the green channel had the highest coefficient of determination coefficient (R2) of 0.9313 and a limit of detection of 0.56 mg/dL. With this method, direct bilirubin concentrations higher than 1.86 mg/dL can be quantitatively analyzed with the advantage of rapid and noninvasive detection.

Wide-Angle Mini-Light-Emitting Diodes without Optical Lens for an Ultrathin Flexible Light Source.

This report outlines a proposed method of packaging wide-angle (WA) mini-light-emitting diode (mini-LED) devices without optical lenses to create a highly efficient, ultrathin, flexible planar backlight for portable quantum dot light-emitting diode (QLED) displays. Since the luminous intensity curve for mini-LEDs generally recommends a beam angle of 120°, numerous LEDs are necessary to achieve a uniform surface light source for a QLED backlight. The light-guide layer and diffusion layer were packaged together on a chip surface to create WA mini-LEDs with a viewing angle of 180°. These chips were then combined with a quantum dot (QD) film and an optical film to create a high-efficiency, ultrathin, flexible planar light source with excellent color purity that can be used as a QLED display backlight. A 6 in (14.4 cm) light source was used as an experimental sample. When 1.44 W was supplied to the sample, the 3200-piece WA mini-LED with a flexible planar QLED display had a beam angle of 180° on the luminous intensity curve, a planar backlight thickness of 0.98 mm, a luminance of 10,322 nits, and a luminance uniformity of 92%.

Electrothermally-Actuated Micromirrors with Bimorph Actuators--Bending-Type and Torsion-Type.

Three different electrothermally-actuated MEMS micromirrors with Cr/Au-Si bimorph actuators are proposed. The devices are fabricated with the SOIMUMPs process developed by MEMSCAP, Inc. (Durham, NC, USA). A silicon-on-insulator MEMS process has been employed for the fabrication of these micromirrors. Electrothermal actuation has achieved a large angular movement in the micromirrors. Application of an external electric current 0.04 A to the bending-type, restricted-torsion-type, and free-torsion-type mirrors achieved rotation angles of 1.69°, 3.28°, and 3.64°, respectively.

A high performance load balance strategy for real-time multicore systems.

Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper.

A high-performance genetic algorithm: using traveling salesman problem as a case.

This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA.

A high performance cloud-based protein-ligand docking prediction algorithm.

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result.

Evaluation of the DNA stability of forensic markers used in betel-quid chewers' oral swab samples and oral cancerous specimens: implications for forensic application.

Chewed betel-quid (BQ) residues are often considered vital biological evidence at crime scenes, since the human DNA extracted from the residues is actually from buccal epithelial cells and can be associated with suspects. BQ-chewing is also a risk factor for oral diseases and/or cancers. Archived medical oral-specimens can be used to identify specific individuals under adverse conditions, although STR markers are known to be unstable in various tumor tissues. This study evaluates the DNA stability of forensic marker systems in BQ-chewers' oral epithelial cells, and in archived clinical specimens of oral cancer patients. The genotypes of oral and paired peripheral blood samples in 200 subjects were compared, using the commercialized typing systems of HLA-DQA1, PM (including LDLR, GYPA, HBGG, D7S8, and GC loci), and AmpFlSTR markers (including 9 STR loci and the Amelogenin gene). The 100 healthy BQ-chewers had consistent oral swab and paired blood sample genotypes analyzed withboth DQA1/PM and STR marker systems. In the 100 oral cancer patients, one discordant result at D7S8 was found in the 600DQA1/PM-marker loci, and 25 allelic alterations with expansion or contraction were detected in the 900 STR loci. The findings herein suggest that when cancerous specimens were tested, the HLA-DQA1/PM system with point polymorphism appears more reliable than the STR system with length polymorphism. Our results also indicate that healthy BQ-chewers' oral cotton swabs containing buccal epithelial cells are useful for forensic purposes using the HLA-DQA1, PM, and STR marker systems.

Allelic alterations at the STR markers in the buccal tissue cells of oral cancer patients and the oral epithelial cells of healthy betel quid-chewers: an evaluation of forensic applicability.

Although cancerous specimens are usually not used in forensic DNA typing, they might be forcibly employed under certain instances. On the other hand, though the oral epithelial samples have been applied to forensic identification, the great popularity of betel quid (BQ)-chewing in Taiwan, which is known to be a risk factor leading to an oral cancer, makes this application questionable. The DNA stability of nine short tandem repeat (STR) markers (the AmpFlSTR kit) was first investigated and then used to evaluate the forensic appropriateness of the oral samples of both healthy BQ-chewers and the archived clinical specimens from oral cancer patients. The analyses were performed on buccal samples from 100 BQ-chewers and 100 oral cancer patients, as well as their paired peripheral blood samples, and a group of 100 non-BQ-chewers were used for the control. In the group of 100 oral cancer patients, two types of DNA instability were found. They were major allelic imbalance, and allelic alterations including the expansion, the contraction and the un-classified type (i.e. can not be confirmed as the expansion or the contraction). The overall percentage of the cancerous subjects demonstrating DNA instability was 33% (five patients possessing both types of DNA instability). Both types of DNA instability showed a tendency of increasing with the severity of the pathological stage of oral cancer. Forty-four occurrences of major allelic imbalance were found from 21 cancer patients. The statistical result revealed that there was no significant difference in the allelic imbalanced occurrence among the nine STR loci. Allelic alterations were found in 17 patients, within which 12 individuals had the expansion, five had the contraction, and three were the un-classified type. Further, among these 17 patients, three were found to acquire multiple allelic alterations at multiple loci. In the group of 100 unrelated healthy BQ-chewers, two loci with major allelic imbalance were detected. However, the two imbalanced alleles were virtually half lost, and could still be recognized as heterozygous alleles. The statistical results of ANOVA, chi(2), and Scheffe tests indicated that the means of allelic imbalance at the nine STR loci of the oral cancerous group revealed a significant difference from those in the control group. Our results suggest that oral cancer tissues cannot be used as references for forensic purposes using the PCR-based STR systems, whereas the oral swabs from healthy BQ-chewers can be employed, but should be done with caution.