Rapid ABO genotyping method using loop-mediated isothermal amplification (LAMP) and real-time PCR

Analyzing all biological evidence at a crime scene presents serious time, budget, and labor constraints. Therefore, selecting valid evidence is crucial for efficient screening. The ABO blood group is a marker that can serve as valid evidence for identifying investigative leads in criminal case. Conventional identification of ABO blood groups using serological methods has only been for blood and is difficult to apply to other body fluids. ABO genotyping was conducted by analyzing single nucleotide polymorphisms (SNP) representative of each blood group. However, this method is time-consuming, expensive, and requires sophisticated instruments. In this study, we developed rapid ABO genotyping method using loop-mediated isothermal amplification (LAMP) and multiplex real-time polymerase chain reaction (PCR). Three SNP sites in the ABO gene (nt 261, 526, and 803) were selected to classify the ABO genotypes. For the specificity test, we performed sequencing of 60 saliva samples to confirm that the genotyping. We conducted experiments to apply ABO genotyping using two amplification methods to mock forensic sample using cotton swab and filter paper. As a result, using LAMP, we successfully identified six ABO genotypes within 30 min at a constant temperature (65 ℃). Moreover, by using multiple real-time PCR, it was possible to detect not only the major group but also the subgroup of the ABO genotype (ex. cis-AB). The amplification results using the new methods were in concordance with the sequencing results. Therefore, these ABO genotyping methods are expected to select valid evidence successfully and efficiently at the crime scene.

Optimizing Lane Departure Warning System towards AI-Centered Autonomous Vehicles

The operational efficacy of lane departure warning systems (LDWS) in autonomous vehicles is critically influenced by the retro-reflectivity of road markings, which varies with environmental wear and weather conditions. This study investigated how changes in road marking retro-reflectivity, due to factors such as weather and physical wear, impact the performance of LDWS. The study was conducted at the Yeoncheon SOC Demonstration Research Center, where various weather scenarios, including rainfall and transitions between day and night lighting, were simulated. We applied controlled wear to white, yellow, and blue road markings and measured their retro-reflectivity at multiple stages of degradation. Our methods included rigorous testing of the LDWS's recognition rates under these diverse environmental conditions. Our results showed that higher retro-reflectivity levels significantly improve the detection capability of LDWS, particularly in adverse weather conditions. Additionally, the study led to the development of a simulation framework for analyzing the cost-effectiveness of road marking maintenance strategies. This framework aims to align maintenance costs with the safety requirements of autonomous vehicles. The findings highlight the need for revising current road marking guidelines to accommodate the advanced sensor-based needs of autonomous driving systems. By enhancing retro-reflectivity standards, the study suggests a path towards optimizing road safety in the age of autonomous vehicles.

Structurally Aligned Multifunctional Neural Probe (SAMP) Using Forest-Drawn CNT Sheet onto Thermally Drawn Polymer Fiber for Long-Term In Vivo Operation

Neural probe engineering is a dynamic field, driving innovation in neuroscience and addressing scientific and medical demands. Recent advancements involve integrating nanomaterials to improve performance, aiming for sustained in vivo functionality. However, challenges persist due to size, stiffness, complexity, and manufacturing intricacies. To address these issues, a neural interface utilizing freestanding CNT-sheets drawn from CNT-forests integrated onto thermally drawn functional polymer fibers is proposed. This approach yields a device with structural alignment, resulting in exceptional electrical, mechanical, and electrochemical properties while retaining biocompatibility for prolonged periods of implantation. This Structurally Aligned Multifunctional neural Probe (SAMP) employing forest-drawn CNT sheets demonstrates in vivo capabilities in neural recording, neurotransmitter detection, and brain/spinal cord circuit manipulation via optogenetics, maintaining functionality for over a year post-implantation. The straightforward fabrication method's versatility, coupled with the device's functional reliability, underscores the significance of this technique in the next-generation carbon-based implants. Moreover, the device's longevity and multifunctionality position it as a promising platform for long-term neuroscience research.

Enhanced Nuclei Segmentation and Classification via Category Descriptors in the SAM Model

Segmenting and classifying nuclei in H&E histopathology images is often limited by the long-tailed distribution of nuclei types. However, the strong generalization ability of image segmentation foundation models like the Segment Anything Model (SAM) can help improve the detection quality of rare types of nuclei. In this work, we introduce category descriptors to perform nuclei segmentation and classification by prompting the SAM model. We close the domain gap between histopathology and natural scene images by aligning features in low-level space while preserving the high-level representations of SAM. We performed extensive experiments on the Lizard dataset, validating the ability of our model to perform automatic nuclei segmentation and classification, especially for rare nuclei types, where achieved a significant detection improvement in the F1 score of up to 12%. Our model also maintains compatibility with manual point prompts for interactive refinement during inference without requiring any additional training.

Epigenetic age prediction using costal cartilage for the investigation of disaster victims and missing persons

The DNA intelligence tool, DNA methylation-based age prediction, can help identify disaster victims and suspects in criminal investigations. In this study, we developed a costal cartilage-based age prediction tool that uses massive parallel sequencing (MPS) of age-associated DNA methylation markers. Costal cartilage samples were obtained from 85 deceased Koreans, aged between 26 and 89 years. An MPS library was prepared using two rounds of multiplex polymerase chain reaction of nine genes (TMEM51, MIR29B2CHG, EDARADD, FHL2, TRIM59, ELOVL2, KLF14, ASPA, and PDE4C). The DNA methylation status of 45 CpG sites was determined and used to train an age prediction model via stepwise regression analysis. Nine CpGs in MIR29B2CHG, FHL2, TRIM59, ELOVL2, KLF14, and ASPA were selected for regression model construction. A leave-one-out cross-validation analysis revealed the high performance of the age prediction model, with a mean absolute error (MAE) and root mean square error of 4.97 and 6.43 years, respectively. Additionally, our model showed good performance with a MAE of 6.06 years in the analysis of data of 181 costal cartilage samples collected from Europeans. Our model effectively estimates the age of deceased individuals using costal cartilage samples; therefore, it can be a valuable forensic tool for disaster victim and missing person investigation.

Quantitative analysis of pulse arrival time and PPG morphological features based cuffless blood pressure estimation: a comparative study between diabetic and non-diabetic groups

Pulse arrival time (PAT) and PPG morphological features have attracted much interest in cuffless blood pressure (BP) estimation, but their effects are not clearly understood when vascular characteristics are affected by diseases such as diabetes. This work quantitatively analyzes the effect of diabetic disease on the PAT and PPG morphological features-based BP estimation. We selected 112 diabetic patients and 308 non-diabetic subjects from VitalDB, and extracted 16 features including PAT, PPG morphological features, and heart rate. BP estimation performance was statistically compared between groups using linear regression models with several feature sets, and the relative importance of each feature in the optimal feature set was extracted. As a result, the standard deviation of the error and mean absolute error of PAT-based BP estimation were significantly higher in the diabetic group than in the non-diabetic group (p < 0.01). A feature set containing PAT and PPG morphological features achieved the best performance in both groups. However, the relative importance of each feature for BP estimation differed notably between groups. The results indicate that different features are important depending on the vascular characteristics, which could help to construct different models to accommodate specific diseases.

DNA methylome profiling of blood to identify individuals in a pair of monozygotic twins

BACKGROUND

Short tandem repeat (STR) markers cannot be used to distinguish between genetically identical monozygotic (MZ) twins, causing problems in a case with an MZ twin as a suspect. Many studies have shown that in older MZ twins, there are significant differences in overall content and genomic distribution of methylation.

OBJECTIVE

In this study, we analyzed the DNA methylome profile of blood to identify recurrent differentially methylated CpG sites (DMCs) to discriminate between MZ twins.

METHODS

Blood samples were collected from 47 paired MZ twins. We performed the DNA methylation profiling using the HumanMethylation EPIC BeadChip platform and identified recurrent DMCs between MZ twins. Then, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and motif enrichment analyses were performed to reveal the biological functions of recurrent DMCs. We collected DNA methylome data from the Gene Expression Omnibus (GEO) public database to verify the recurrent DMCs between MZ twins.

RESULTS

We identified recurrent DMCs between MZ twin samples and observed that they were enriched in immune-related genes. In addition, we verified our DMCs in a public dataset.

CONCLUSION

Our results suggest that the methylation level at recurrent DMCs between MZ twins may serve as a valuable biomarker for identification of individuals in a pair of MZ twins.

Controlling the Surface Morphology of Two-Dimensional Nano-Materials upon Molecule-Mediated Crystal Growth

The surface morphology of Mg-Al-layered double hydroxide (LDH) was successfully controlled by reconstruction during systematic phase transformation from calcined LDH, which is referred to as layered double oxide (LDO). The LDH reconstructed its original phase by the hydration of LDO with expanded basal spacing when reacted with water, including carbonate or methyl orange molecules. During the reaction, the degree of crystal growth along the ab-plane and stacking along the c-axis was significantly influenced by the molecular size and the reaction conditions. The lower concentration of carbonate gave smaller particles on the surface of larger LDO (2000 nm), while the higher concentration induced a sand-rose structure. The reconstruction of smaller-sized LDH (350 nm) did not depend on the concentration of carbonate due to effective adsorption, and it gave a sand-rose structure and exfoliated the LDH layers. The higher the concentration of methyl orange and the longer the reaction time applied, the rougher the surface was obtained with a certain threshold point of the methyl orange concentration. The surface roughness generally increased with the loading mount of methyl orange. However, the degree of the surface roughness even increased after the methyl orange loading reached equilibrium. The result suggested that the surface roughening was mediated by not only the incorporation of guest molecules into the LDH but also a crystal arrangement after a sufficient amount of methyl orange was accommodated.

Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis

BACKGROUND

Cancer subtype identification is important for the early diagnosis of cancer and the provision of adequate treatment. Prior to identifying the subtype of cancer in a patient, feature selection is also crucial for reducing the dimensionality of the data by detecting genes that contain important information about the cancer subtype. Numerous cancer subtyping methods have been developed, and their performance has been compared. However, combinations of feature selection and subtype identification methods have rarely been considered. This study aimed to identify the best combination of variable selection and subtype identification methods in single omics data analysis.

RESULTS

Combinations of six filter-based methods and six unsupervised subtype identification methods were investigated using The Cancer Genome Atlas (TCGA) datasets for four cancers. The number of features selected varied, and several evaluation metrics were used. Although no single combination was found to have a distinctively good performance, Consensus Clustering (CC) and Neighborhood-Based Multi-omics Clustering (NEMO) used with variance-based feature selection had a tendency to show lower p-values, and nonnegative matrix factorization (NMF) stably showed good performance in many cases unless the Dip test was used for feature selection. In terms of accuracy, the combination of NMF and similarity network fusion (SNF) with Monte Carlo Feature Selection (MCFS) and Minimum-Redundancy Maximum Relevance (mRMR) showed good overall performance. NMF always showed among the worst performances without feature selection in all datasets, but performed much better when used with various feature selection methods. iClusterBayes (ICB) had decent performance when used without feature selection.

CONCLUSIONS

Rather than a single method clearly emerging as optimal, the best methodology was different depending on the data used, the number of features selected, and the evaluation method. A guideline for choosing the best combination method under various situations is provided.

Research Progress and Prospects of Nanozyme-Based Glucose Biofuel Cells

The appearance and evolution of biofuel cells can be categorized into three groups: microbial biofuel cells (MBFCs), enzymatic biofuel cells (EBFCs), and enzyme-like nanomaterial (nanozyme)-based biofuel cells (NBFCs). MBFCs can produce electricity from waste; however, they have significantly low power output as well as difficulty in controlling electron transfer and microbial growth. EBFCs are more productive in generating electricity with the assistance of natural enzymes, but their vulnerability under diverse environmental conditions has critically hindered practical applications. In contrast, because of the intrinsic advantages of nanozymes, such as high stability and robustness even in harsh conditions, low synthesis cost through facile scale-up, and tunable catalytic activity, NBFCs have attracted attention, particularly for developing wearable and implantable devices to generate electricity from glucose in the physiological fluids of plants, animals, and humans. In this review, recent studies on NBFCs, including the synthetic strategies and catalytic activities of metal and metal oxide-based nanozymes, the mechanism of electricity generation from glucose, and representative studies are reviewed and discussed. Current challenges and prospects for the utilization of nanozymes in glucose biofuel cells are also discussed.

A Convenient Colorimetric Bacteria Detection Method Utilizing Chitosan-Coated Magnetic Nanoparticles

An effective novel strategy to detect bacteria is promising because it may improve human health by allowing early diagnosis and timely treatment of bacterial infections. Here, we report a simple, reliable, and economical colorimetric assay using the peroxidase-like activity of chitosan-coated iron oxide magnetic nanoparticles (CS-MNPs). When CS-MNPs are incubated with a sample containing bacterial cells such as the gram-negative Escherichia coli or the gram-positive Staphylococcus aureus, the negatively-charged bacterial membrane interacts with positively-charged chitosan on the surface of CS-MNPs, thus resulting in significant reduction of their peroxidase-like activity presumably by a hindrance in the accessibility of the negatively charged substrate, 2-2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) to the positively-charged CS-MNPs. This simple colorimetric strategy allowed the rapid detection of bacterial cells down to 104 CFU mL-1 by the naked eye and 102 CFU mL-1 by spectrophotometry within 10 min. Based on the results, we anticipate that the CS-MNPs-based assay has great potential for the on-site diagnosis of bacterial infections in facility-limited or point-of-care testing (POCT) environments.

Do police officers and firefighters have a higher risk of disease than other public officers? A 13-year nationwide cohort study in South Korea

OBJECTIVES

The work of public officers involves repeated and long-term exposure to heavy workloads, high job strain and workplace violence, all of which negatively impact physical and mental health. This study aimed to evaluate and compare the incidences of diseases among different categories of public officers in Korea, in order to further understand the health risks associated with these occupations.

DESIGN

A cohort study using the National Health Insurance data.

PARTICIPANTS

We collated claims data between 2002 and 2014 for 860 221 public officers.

PRIMARY AND SECONDARY OUTCOME MEASURES

Age-standardised rates were calculated using the direct standardisation method, and HRs were calculated using the Cox proportional hazard regression models.

RESULTS

Overall, we found that police officers and firefighters had a higher incidence of a range of diseases when compared with national and regional government officers (NRG). The most prominent HRs were observed among police officers for angina pectoris (HR: 1.52, 95% CI 1.49 to 1.54), acute myocardial infarction (HR: 1.84, 95% CI 1.77 to 1.92) and cerebrovascular disease (HR: 1.36, 95% CI 1.31 to 1.40). Firefighters were more susceptible to physical ailments and were at a significantly higher risk for traumatic stress disorders (HR: 1.40, 95% CI 1.26 to 1.56) than NRGs.

CONCLUSION

Compared withNRGs, police officers had higher HRs for all measured diseases, except for traumatic stress disorders. While firefighters had higher HRs for almost all diseases examined, public education officers had a higher HR for traumatic stress disorders, when compared with NRGs.

Oligomeric Procyanidins (OPCs) Inhibit Procollagen Type I Secretion of Fibroblasts

Wound healing is composed of a complex process that requires harmonies of various cell populations where fibroblasts play the main role. Oligomeric procyanidins (OPC) are main components of grape (Vitis vinifera) seed extracts, and recent studies showed OPC's effects on inflammation, cell migration, and proliferation. We investigated the effect of OPC on fibroblasts to regulate wound healing process. Human dermal fibroblast known as Hs27 cells were treated with various concentrations of OPC (0, 2.5, 5, 10, and 20 μg/μl). Cell cytotoxicity was evaluated by the Cell Counting Kit assay, and the expression levels of secreted procollagen were analyzed. Procollagen levels in OPC treated cells exposed to transforming growth factor beta 1 (TGF-β1) or ascorbic acid were evaluated using Western blot and immunocytochemistry. Relative mRNA expressions of procollagen, molecular chaperone such as HSP47, P4H were determined by real-time PCR in OPC treated cells. OPC showed no cytotoxicity on Hs27 cells at every concentration but inhibited procollagen secretion in a dose-dependent manner. The inhibitory effect also appeared under TGF-β1 induced collagen overproduction. Immunocytochemistry showed that higher levels of intracytoplasmic procollagen were accumulated in TGF-β1 treatment group, whereas ascorbic acid induced a release of accumulated procollagen under OPC treatment. The mRNA expressions of procollagen, molecular chaperone were not affected by OPC, but procollagen level was increased when exposed to TGF-β1. OPC inhibits procollagen secretion from fibroblasts with no effects on cell proliferations even under the environment of TGF-β1-induced collagen overproduction. OPC could regulate the diseases and symptoms of abnormal overabundant collagen production.

Progression of Hip Displacement during Radiographic Surveillance in Patients with Cerebral Palsy

Progression of hip displacement is common in patients with cerebral palsy (CP). We aimed to investigate the rate of progression of hip displacement in patients with CP by assessing changes in radiographic indices according to Gross Motor Function Classification System (GMFCS) level during hip surveillance. We analyzed the medical records of patients with CP aged < 20 years who underwent at least 6 months interval of serial hip radiographs before any surgical hip intervention, including reconstructive surgery. After panel consensus and reliability testing, radiographic measurements of migration percentage (MP), neck-shaft angle (NSA), acetabular index (AI), and pelvic obliquity (PO) were obtained during hip surveillance. For each GMFCS level, annual changes in radiographic indices were analyzed and adjusted for affecting factors, such as sex, laterality, and type of CP. A total of 197 patients were included in this study, and 1,097 radiographs were evaluated. GMFCS classifications were as follows: 100 patients were level I-III, 48 were level IV, and 49 were level V. MP increased significantly over the duration of hip surveillance in patients with GMFCS levels I-III, IV, and V by 0.3%/year (P < 0.001), 1.9%/year (P < 0.001), and 6.2%/year (P < 0.001), respectively. In patients with GMFCS level IV, NSA increased significantly by 3.4°/year (P < 0.001). Our results suggest that periodic monitoring and radiographic hip surveillance is warranted for patients with CP, especially those with GMFCS level IV or V. Furthermore, physicians can predict and inform parents or caregivers regarding the progression of hip displacement in patients with CP.