The safety of human papillomavirus (HPV) vaccines has been evaluated continuously in pre-licensure clinical trials, post-marketing surveillance systems, and observational studies. Most studies have ...found no significant association between serious adverse events and HPV vaccination. However, these studies have focused on Western populations; similar studies focusing on Asian populations are insufficient. Our retrospective cohort study used the HPV-vaccination records of junior high-school adolescent girls aged 12–15 years between 2013 and 2018 in Taiwan’s National Immunization Information System and linked them to a registry for beneficiaries in Taiwan’s National Health Insurance Database (NHID) to establish the vaccinated group. We selected 19 serious diseases as serious adverse events. We compared the incidence rates of these serious adverse events between the vaccinated group and girls in the same age group population, and we calculated the standardized incidence ratio (SIR) to evaluate the risk of serious adverse events after HPV vaccination. Because of the onset of different types of diseases, we set three periods after the subjects received HPV vaccination: within 3 months, within 1 year, and during the study period (2013–2018). The results showed the incidence rates and the SIRs of 19 selected adverse events. Among the 19 selected serious adverse events, the disease with the highest incidence rate during the study period was fibromyalgia (73.23 cases per million population), and the disease with the lowest incidence rate during the study period was Crohn’s disease (0.15 cases per million population). The results showed no statistically significant increases in the risk of 19 selected serious adverse events and indicated no association between HPV vaccination and serious adverse events. Given the benefits and safety of HPV vaccination, our research can reduce concerns about vaccine side effects, inform health policies and improve public and clinician’s acceptance of HPV vaccine policy.
Abstract
Sequence-based analysis and prediction are fundamental bioinformatic tasks that facilitate understanding of the sequence(-structure)-function paradigm for DNAs, RNAs and proteins. Rapid ...accumulation of sequences requires equally pervasive development of new predictive models, which depends on the availability of effective tools that support these efforts. We introduce iLearnPlus, the first machine-learning platform with graphical- and web-based interfaces for the construction of machine-learning pipelines for analysis and predictions using nucleic acid and protein sequences. iLearnPlus provides a comprehensive set of algorithms and automates sequence-based feature extraction and analysis, construction and deployment of models, assessment of predictive performance, statistical analysis, and data visualization; all without programming. iLearnPlus includes a wide range of feature sets which encode information from the input sequences and over twenty machine-learning algorithms that cover several deep-learning approaches, outnumbering the current solutions by a wide margin. Our solution caters to experienced bioinformaticians, given the broad range of options, and biologists with no programming background, given the point-and-click interface and easy-to-follow design process. We showcase iLearnPlus with two case studies concerning prediction of long noncoding RNAs (lncRNAs) from RNA transcripts and prediction of crotonylation sites in protein chains. iLearnPlus is an open-source platform available at https://github.com/Superzchen/iLearnPlus/ with the webserver at http://ilearnplus.erc.monash.edu/.
Background & Aims
Patatin‐like phospholipase domain‐containing protein 3 (PNPLA3) rs738409 polymorphism is associated with NAFLD severity and the PNPLA3 gene is expressed in the kidneys, but whether ...PNPLA3 rs738409 polymorphism is also associated with renal tubular injury (RTI) is uncertain. We assessed the effect of PNPLA3 genotypes on biomarkers of RTI and glomerular function in subjects with NAFLD who had either normal (nALT) or abnormal (abnALT) alanine aminotransaminase levels.
Methods
Two hundred and seventeen patients with histologically proven NAFLD of which 75 had persistently nALT (below upper limit of normal for 3 months) were included. Multivariable regression analyses were undertaken to test associations between PNPLA3 genotype and biomarkers of kidney dysfunction.
Results
The nALT patient group had higher urinary neutrophil gelatinase‐associated lipocalin levels (u‐NGAL, a biomarker of RTI) (P < .001), higher albuminuria (P = .039) and greater prevalence of chronic kidney disease (CKD; P = .046) than the abnALT group. The association between PNPLA3 GG genotype and risk of CKD and abnormal albuminuria remained significant after adjustment for kidney risk factors and severity of NAFLD histology, mostly in the nALT group. Similarly, PNPLA3 GG genotype was associated with higher u‐NGAL levels in the nALT group, even after adjustment for the aforementioned risk factors and glomerular filtration‐based markers (β‐coefficient: 22.29, 95% CI: 0.99‐43.60, P = .041).
Conclusion
Patients with NAFLD and persistently nALT, who carry the PNPLA3 rs738409 G allele, are at higher risk of early glomerular and tubular damage. We suggest PNPLA3 genotyping may help identify patients with NAFLD at higher risk of RTI.
Background
The presence of significant liver fibrosis is a key determinant of long‐term prognosis in non‐alcoholic fatty liver disease (NAFLD). We aimed to develop a novel machine learning algorithm ...(MLA) to predict fibrosis severity in NAFLD and compared it with the most widely used non‐invasive fibrosis biomarkers.
Methods
We used a cohort of 553 adults with biopsy‐proven NAFLD, who were randomly divided into a training cohort (n = 278) for the development of both logistic regression model (LRM) and MLA, and a validation cohort (n = 275). Significant fibrosis was defined as fibrosis stage F ≥ 2. MLA and LRM were derived from variables that were selected using a least absolute shrinkage and selection operator (LASSO) logistic regression algorithm.
Results
In the training cohort, the variables selected by LASSO algorithm were body mass index, pro‐collagen type III, collagen type IV, aspartate aminotransferase and albumin‐to‐globulin ratio. The diagnostic accuracy of MLA showed the highest values of area under the receiver operator characteristic curve (AUROC: 0.902, 95% CI 0.869‐0.904) for identifying fibrosis F ≥ 2. The LRM AUROC was 0.764, 95% CI 0.710‐0.816 and significantly better than the AST‐to‐Platelet ratio (AUROC 0.684, 95% CI 0.605‐0.762), FIB‐4 score (AUROC 0.594, 95% CI 0.503‐0.685) and NAFLD Fibrosis Score (AUROC 0.557, 95% CI 0.470‐0.644). In the validation cohort, MLA also showed the highest AUROC (0.893, 95% CI 0.864‐0.901). The diagnostic accuracy of MLA outperformed that of LRM in all subgroups considered.
Conclusions
Our newly developed MLA algorithm has excellent diagnostic performance for predicting fibrosis F ≥ 2 in patients with biopsy‐confirmed NAFLD.
Highlight
A cohort of patients with biopsy‐proven non‐alcoholic fatty liver disease were randomly divided into a training cohort for the development of a machine learning algorithm and a validation cohort. The machine learning algorithm newly developed by Feng and colleagues had excellent diagnostic accuracy in predicting fibrosis of F³2.
This article proposes a multiple self-sensing gripper (MssGripper) driven by the shape memory alloy (SMA) and empowered by machine learning algorithms. The MssGripper can identify objects without ...external sensors. A single SMA wire can drive the gripper for self-sensing accurately. This article confirms the resistance of the SMA can reflect the phase transition and can be used for displacement and force prediction, as well as for object stiffness prediction. Through machine learning, a backpropagation neural network and long-short-term-memory (LSTM) are used to establish multiple self-sensing models for prediction. The robustness experimental results show that the self-sensing models based on LSTM have higher prediction accuracy. The average root-mean-square errors of displacement prediction and force prediction are 0.063 mm and 0.236 N, respectively, and the stiffness prediction error is less than 9.4%. Moreover, the accuracy of the classifier in stiffness identification is 97.2%. The MssGripper can accurately predict the displacement, force, and stiffness and identify objects such as springs, rubber bars and steel bars. The establishment of the models expands the novel idea of gripper sensing, which is beneficial to promoting miniaturization and compactness.
In Taiwan, the age-standardized incidence of EC, especially esophageal squamous cell carcinoma (ESCC), has increased substantially during the past thirty years. We described the incidence trends of ...EC from 1985−2019 by an average annual percentage change (AAPC) and age-period-cohort model by using Taiwan Cancer Registry data. Age-period-cohort modeling was used to estimate the period and cohort effects of ESCC and esophageal adenocarcinoma (EAC). The Spearman’s correlation coefficient was used to analyze the correlation between age-adjusted incidence rates of EC and the prevalence of risk factors from national surveys. The results showed the incidence rate of ESCC in men (AAPC = 4.2, 95% CI = 3.1−5.4, p < 0.001) increased prominently from 1985−1989 to 2015−2019 while that of EAC in men (AAPC = 1.2, 95% CI = 0.9−1.5, p < 0.001) and ESCC in women (AAPC = 1.7, 95% CI = 1.4−2.1, p < 0.001) increased to a lesser degree. Increased period effects were observed in ESCC in men, ESCC in women, and EAC in men. High correlations were found between the risk factors and the increased birth-cohort effects of ESCC (p < 0.05). To conclude, the incidence of ESCC in both sex and EAC in men increased with statistical significance in recent decades. The increased prevalence of risk factors from approximately 1970−1995 could explain the increased cohort effects of ESCC.
•A thermal stress stiffening method for rotating disk vibration suppression.•Dynamics of rotating flexible disk system heated at disk inner boundary.•Thermal deformation of flexible disk system with ...initial transverse runout.•Experiment verification of the proposed method for vibration suppression.
A thermal stress stiffening method for the vibration suppression of a rotating flexible disk with initial transverse runout is investigated via theoretical and experimental methods in this paper. This method generates in-plane thermal stress by heating the disk inner boundary, thereby enhancing the transversal bending stiffness of the disk and suppressing the transverse vibration. The thermal stress stiffening's influence on the natural frequency, dynamic stability and steady-state response of the disk with and without a mass-spring-damper system loaded is analyzed by theoretical computation. Via a finite element method software, it is found that thermal expansion could change the non-flat disk's shape. A specialized testing set is designed, and the content of the theoretical analysis is tested through experiments. The experimental results show that this method is not only suitable for a freely rotating disk, but also for the vibration suppression of a flexible disk loaded with a transversely symmetrical mass-spring-damper system, and even for that of a flexible disk loaded with a single-sided one. Moreover, this method is easy-to-use and cost-effective in practical applications as a simple and effective way for the vibration suppression of rotating disks.
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Sensor networks play an important role in structural health monitoring and tactile sensors. General sensor networks require different types and a large number of sensors. This article proposes a ...shape memory alloy (SMA) sensor interwoven network. Without the need for additional force or displacement sensors, the position of one external force acting on the sensor network can be estimated, and the magnitude of the force and the corresponding deformation of the sensor network can be determined, only by measuring the resistance of the SMA wires. This article not only proposes a theoretical analytical model to solve the force position and its magnitude, and even the entire deformation of the SMA sensor network, but also designs a sensor network and its test bench for loading experiments. The experimental results confirm the feasibility of the theoretical model. The SMA sensor interwoven network has important application value under the condition that it is not convenient to directly observe the position of the external force and monitor the force size, such as an intelligent self-sensing badminton racket at least.
Bidirectional shape memory alloy (SMA) wire actuators play a critical role in driving applications thanks to their characteristics in memory shaping and good overall performance. SMA wire actuators ...were often studied at a single load type, and there is no comprehensive comparison investigation of different SMA wire actuators in the literature. In this paper, the driving characteristics of four available types of SMA wire actuators, namely, dead-load, biased spring, differential type, and biased superelastic SMA wire actuators are modelled mathematically and then tested in laboratory settings. The characteristics of SMA wire actuators are quantitatively measured and then compared under a range of application scenarios. The output displacement and thermal-electric models of NiTi SMA wires are derived based on the Brinson constitutive model with stress effects in consideration. A customized SMA wire actuator test device is developed to evaluate the theocratical models and benchmark testing four types of SMA wires and their driving characteristics, including structure, design, displacement, response and recovery time, energy efficiency and hysteresis properties. The SMA wire phase transformation characteristics of the four actuators are tested under different activation currents, and then quantitatively compared. In conclusion, this paper adds theoretical and experimental significance to the literature on SMA wire actuators. The reference value on the phase transformation characteristics of SMA wires can be used to guide SMA application in industrial designs and enable theoretical studies in complementary research areas.
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•Displacement and thermo-electric models are built for the variable stress SMA.•A new type of SMA wire actuator with superelastic SMA is innovatively proposed.•SMA wire phase transformation characteristics are tested for 4 types of actuators.•The driving characteristics of four SMA wire actuators are studied and compared.•Application suggestions for these four types of SMA wire actuators are provided.
CCDC88C gene, which encodes coiled‐coil domain containing 88C, is essential for cell communication during neural development. Variants in the CCDC88C caused congenital hydrocephalus, some accompanied ...by seizures. In patients with epilepsy without acquired etiologies, we performed whole‐exome sequencing (trio‐based). Two de novo and two biallelic CCDC88C variants were identified in four cases with focal (partial) epilepsy. These variants did not present or had low frequencies in the gnomAD populations and were predicted to be damaging by multiple computational algorithms. Patients with de novo variants presented with adult‐onset epilepsy, whereas patients with biallelic variants displayed infant‐onset epilepsy. They all responded well to anti‐seizure medications and were seizure‐free. Further analysis showed that de novo variants were located at crucial domains, whereas one paired biallelic variants were located outside the crucial domains, and the other paired variant had a non‐classical splicing and a variant located at crucial domain, suggesting a sub‐molecular effect. CCDC88C variants associated with congenital hydrocephalus were all truncated, whereas epilepsy‐associated variants were mainly missense, the proportion of which was significantly higher than that of congenital hydrocephalus‐associated variants. CCDC88C is potentially associated with focal epilepsy with favorable outcome. The underlying mechanisms of phenotypic variation may correlation between genotype and phenotype.
Two de novo and two biallelic CCDC88C variants were identified in four cases with focal epilepsy without neurodevelopmental disorders. CCDC88C variants associated with congenital hydrocephalus were all truncated, whereas epilepsy‐associated variants were mainly missense, the proportion of which was significantly higher than that of patients with congenital hydrocephalus.
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