Ultrathin and Deformable Graphene Etch Mask for Fabrication of 3D Microstructures.

Three-dimensional (3D) microfabrication techniques play a crucial role across various research fields. These techniques enable the creation of functional 3D structures on the microscale, unlocking possibilities for diverse applications. However, conventional fabrication methods have limits in producing complex 3D structures, which require numerous fabrication steps that increase the costs. Graphene is an atomically thin material known for its deformability and impermeability to small gases and molecules, including reactive gases like XeF2. These features make graphene a potential candidate as an etch mask for 3D microfabrication. Here, we report the fabrication of various 3D microstructures using graphene etch masks directly grown and patterned on a Si substrate. The patterned graphene deforms and wraps the etched structures, allowing for the fabrication of complicated 3D microstructures, such as mushroom-like and step-like microstructures. As a practical demonstration of the graphene etch mask, we fabricate an omniphobic surface of reentrant 3D structures on a Si substrate. Our work provides a method for fabricating complex 3D microstructures using a graphene etch mask, contributing to advancements in etching and fabrication processes.

Real-Time Signal Analysis with Wider Dynamic Range and Enhanced Sensitivity in Multiplex Colorimetric Immunoassays Using Encoded Hydrogel Microparticles.

The simultaneous quantification of multiple proteins is crucial for accurate medical diagnostics. A promising technology, the multiplex colorimetric immunoassay using encoded hydrogel microparticles, has garnered attention, due to its simplicity and multiplex capabilities. However, it encounters challenges related to its dynamic range, as it relies solely on the colorimetric signal analysis of encoded hydrogel microparticles at the specific time point (i.e., end-point analysis). This necessitates the precise determination of the optimal time point for the termination of the colorimetric reaction. In this study, we introduce real-time signal analysis to quantify proteins by observing the continuous colorimetric signal change within the encoded hydrogel microparticles. Real-time signal analysis measures the "slope", the rate of the colorimetric signal generation, by focusing on the kinetics of the accumulation of colorimetric products instead of the colorimetric signal that appears at the end point. By developing a deep learning-based automatic analysis program that automatically reads the code of the graphically encoded hydrogel microparticles and obtains the slope by continuously tracking the colorimetric signal, we achieved high accuracy and high throughput analysis. This technology has secured a dynamic range more than twice as wide as that of the conventional end-point signal analysis, simultaneously achieving a sensitivity that is 4-10 times higher. Finally, as a demonstration of application, we performed multiplex colorimetric immunoassays using real-time signal analysis covering a wide concentration range of protein targets associated with pre-eclampsia.

Glycerol 3-phosphate dehydrogenases (1 and 2) in cancer and other diseases.

The glycerol 3-phosphate shuttle (GPS) is composed of two different enzymes: cytosolic NAD+-linked glycerol 3-phosphate dehydrogenase 1 (GPD1) and mitochondrial FAD-linked glycerol 3-phosphate dehydrogenase 2 (GPD2). These two enzymes work together to act as an NADH shuttle for mitochondrial bioenergetics and function as an important bridge between glucose and lipid metabolism. Since these genes were discovered in the 1960s, their abnormal expression has been described in various metabolic diseases and tumors. Nevertheless, it took a long time until scientists could investigate the causal relationship of these enzymes in those pathophysiological conditions. To date, numerous studies have explored the involvement and mechanisms of GPD1 and GPD2 in cancer and other diseases, encompassing reports of controversial and non-conventional mechanisms. In this review, we summarize and update current knowledge regarding the functions and effects of GPS to provide an overview of how the enzymes influence disease conditions. The potential and challenges of developing therapeutic strategies targeting these enzymes are also discussed.

Evaluating Linkage Quality of Population-Based Administrative Data for Health Service Research.

BACKGROUND: To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors. METHODS: This study analyzed claims data submitted to the Health Insurance Review and Assessment Service (HIRA DATA). The linkage errors of the two deterministic linkage methods were evaluated based on the use of the match key. The first deterministic linkage uses a unique identification number, and the second deterministic linkage uses the name, gender, and date of birth as a set of partial identifiers. The linkage error included in this deterministic linkage method was compared with the absolute standardized difference (ASD) of Cohen's according to the baseline characteristics, and the linkage quality was evaluated through the following indicators: linked rate, false match rate, missed match rate, positive predictive value, sensitivity, specificity, and F1-score. RESULTS: For the deterministic linkage method that used the name, gender, and date of birth as a set of partial identifiers, the true match rate was 83.5 and the missed match rate was 16.5. Although there was bias in some characteristics of the data, most of the ASD values were less than 0.1, with no case greater than 0.5. Therefore, it is difficult to determine whether linked data constructed with deterministic linkages have substantial differences. CONCLUSION: This study confirms the possibility of building health and medical data at the national level as the first data linkage quality verification study using big data from the HIRA. Analyzing the quality of linkages is crucial for comprehending linkage errors and generating reliable analytical outcomes. Linkers should increase the reliability of linked data by providing linkage error-related information to researchers. The results of this study will serve as reference data to increase the reliability of multicenter data linkage studies.

Review of Image-Processing-Based Technology for Structural Health Monitoring of Civil Infrastructures.

The continuous monitoring of civil infrastructures is crucial for ensuring public safety and extending the lifespan of structures. In recent years, image-processing-based technologies have emerged as powerful tools for the structural health monitoring (SHM) of civil infrastructures. This review provides a comprehensive overview of the advancements, applications, and challenges associated with image processing in the field of SHM. The discussion encompasses various imaging techniques such as satellite imagery, Light Detection and Ranging (LiDAR), optical cameras, and other non-destructive testing methods. Key topics include the use of image processing for damage detection, crack identification, deformation monitoring, and overall structural assessment. This review explores the integration of artificial intelligence and machine learning techniques with image processing for enhanced automation and accuracy in SHM. By consolidating the current state of image-processing-based technology for SHM, this review aims to show the full potential of image-based approaches for researchers, engineers, and professionals involved in civil engineering, SHM, image processing, and related fields.

The impact of statin treatment duration on the risk of new-onset diabetes mellitus and recurrent vascular events in ischemic stroke patients: a linked data analysis.

INTRODUCTION: Although statin therapy reduces cardiovascular events, statin use is associated with the risk of new-onset diabetes mellitus (NODM). Using a linked dataset, we evaluated the effect of statin treatment on vascular outcomes and NODM development in patients with ischemic stroke. METHODS: From the dataset, we identified 20,250 patients with acute ischemic stroke who had neither a prior history of DM nor a previous history of statin use before the index stroke. Patients were divided into statin users and non-users. The outcomes were NODM and vascular outcomes, including recurrent ischemic stroke and acute myocardial infarction (AMI). RESULTS: Of the 20,250 patients, 13,706 (67.7%) received statin treatment after the index stroke. For the risk of NODM, a time-response relationship was observed between the use of statins and NODM; a longer post-stroke follow-up duration substantially increased the risk of NODM. Among those with ischemic stroke exceeding 3 years, statin users had an approximately 1.7-fold greater risk of NODM than statin non-users. Statin therapy significantly reduced the risk of recurrent ischemic stroke by 54% (HR 0.46, 95% CI, 0.43-0.50, P < 0.001) across all stroke subtypes. CONCLUSION: Statin therapy following ischemic stroke increased the occurrence of NODM in patients over a period of 3 years. Despite the increased risk of NODM, statin therapy shows a beneficial effect in reducing major cardiovascular events such as recurrent ischemic stroke and AMI in patients with ischemic stroke.

Comparative estimation of the effects of antihypertensive medications on schizophrenia occurrence: a multinational observational cohort study.

BACKGROUND: The association between antihypertensive medication and schizophrenia has received increasing attention; however, evidence of the impact of antihypertensive medication on subsequent schizophrenia based on large-scale observational studies is limited. We aimed to compare the schizophrenia risk in large claims-based US and Korea cohort of patients with hypertension using angiotensin-converting enzyme (ACE) inhibitors versus those using angiotensin receptor blockers (ARBs) or thiazide diuretics. METHODS: Adults aged 18 years who were newly diagnosed with hypertension and received ACE inhibitors, ARBs, or thiazide diuretics as first-line antihypertensive medications were included. The study population was sub-grouped based on age (> 45 years). The comparison groups were matched using a large-scale propensity score (PS)-matching algorithm. The primary endpoint was incidence of schizophrenia. RESULTS: 5,907,522; 2,923,423; and 1,971,549 patients used ACE inhibitors, ARBs, and thiazide diuretics, respectively. After PS matching, the risk of schizophrenia was not significantly different among the groups (ACE inhibitor vs. ARB: summary hazard ratio [HR] 1.15 [95% confidence interval, CI, 0.99-1.33]; ACE inhibitor vs. thiazide diuretics: summary HR 0.91 [95% CI, 0.78-1.07]). In the older subgroup, there was no significant difference between ACE inhibitors and thiazide diuretics (summary HR, 0.91 [95% CI, 0.71-1.16]). The risk for schizophrenia was significantly higher in the ACE inhibitor group than in the ARB group (summary HR, 1.23 [95% CI, 1.05-1.43]). CONCLUSIONS: The risk of schizophrenia was not significantly different between the ACE inhibitor vs. ARB and ACE inhibitor vs. thiazide diuretic groups. Further investigations are needed to determine the risk of schizophrenia associated with antihypertensive drugs, especially in people aged > 45 years.

Role of Brassica rapa SWEET genes in the defense response to Plasmodiophora brassicae.

BACKGROUND: Interactions of plants with biotic stress factors including bacteria, fungi, and viruses have been extensively investigated to date. Plasmodiophora brassicae, a protist pathogen, causes clubroot disease in Cruciferae plants. Infection of Chinese cabbage (Brassica rapa) plants with P. brassica results in the formation of root galls, which inhibits the roots from absorbing soil nutrients and water. Sugar, the major source of carbon for all living organisms including pathogens and host plants, plays an important role in plant growth and development. OBJECTIVE: To explore the roles of BrSWEET2, BrSWEET13, and BrSWEET14 in P. brassicae resistance, Arabidopsis thaliana T-DNA knockout mutants sweet2, sweet13, and sweet14 were employed. METHODS: To isolate total RNA from the collected root nodules, the root tissues washed several times with running water and frozen tissues with liquid nitrogen. Total RNA was extracted using the Spectrum™ Plant Total RNA Kit (SIGMA) and cDNA was synthesized in a 20 µl reaction volume using the ReverTra Ace-α-® kit (TOYOBO). Real-time PCR was performed in a 10 µl reaction volume containing 1 µl of template DNA, 1 µl of forward primer, 1 µl of reverse primer, 5 µl of 2× iQTM SYBR® Green Supermix (BioRad), and 2 µl of sterile distilled water. The SWEET genes were genotyped using BioFACT™ 2× TaqBasic PCR Master Mix 2. RESULTS: Both sweet2 and sweet14 showed strong resistance to P. brassicae compared with wild-type Arabidopsis and Chinese cabbage plants and sweet13 mutant plants. Pathogenicity assays indicated that the SWEET2 gene plays an important role in clubroot disease resistance in higher plants.

Using Methyl Bromide for Interspecies Cell-Cell Signaling and As a Reporter in a Model Soil Consortium.

Soil microbial communities with reduced complexity are emerging as model systems for studying consortia-scale phenotypes. To establish synthetic biology tools for studying these communities in hard-to-image environmental materials, we evaluated whether a single member of a model soil consortium (MSC) can be programmed to report on gene expression without requiring matrix disruption. For these studies, we targeted a five-membered MSC that includes Dyadobacter fermentans, Ensifer adhaerens, Rhodococcus sp003130705, Streptomyces sp001905665, and Variovorax beijingensis. By coupling the expression of a methyl halide transferase to a constitutive promoter, we show that V. beijingensis can be programmed to synthesize methyl halides that accumulate in the soil headspace at levels that are ≥24-fold higher than all other MSC members across a range of environmentally relevant hydration conditions. We find that methyl halide production can report on an MSC promoter that is activated by changes in water potential, and we demonstrate that a synthetic gas signal can be read out directly using gas chromatography and indirectly using a soil-derived Methylorubrum that is programmed to produce a visual output in response to methyl halides. These tools will be useful for future studies that investigate how MSC responds to dynamic hydration conditions, such as drought and flood events induced by climate change, which can alter soil water potential and induce the release of stored carbon.

Galvanic Bipolar Electrode Arrays with Self-Driven Optical Readouts.

In this work, we report a bipolar electrode (BPE) array system with self-driven optical readouts of the faradic current flowing through the BPEs. The BPE array system is based on the spontaneous redox reactions that are respectively occurring at opposite poles of the BPEs with appropriate electrocatalysts on the poles; this system is analogous to one consisting of galvanic electrochemical cells. The galvanic BPE array system operates in a self-powered mode that requires there to be neither a direct electrical connection nor external electrical polarization to each BPE. Importantly, the appropriate electrocatalysts on the poles play a critical role in the galvanic BPE array system to induce the spontaneous redox reactions occurring at the poles of BPEs. Moreover, the galvanic BPE array system provides self-driven optical readouts, including fluorometric and colorimetric ones, to report the faradaic current resulting from the spontaneous redox reactions on the BPE poles. Based on the unique benefits that the galvanic BPE array system has over conventional BPEs, we demonstrated the promising potential of galvanic BPE arrays for the simple yet rapid and quantitative screening of electrocatalysts for the oxygen reduction reaction as well as sensitive sensing of H2O2 in parallel.

Electrochemiluminescence of dimethylaminonaphthalene-oxazaborine donor-acceptor luminophores.

Donor-acceptor (D-A) type molecules with a skeleton consisting of a dimethylaminonaphthalene donor and an oxazaborine acceptor were designed as efficient electrochemiluminescence (ECL) luminophores with tunable intramolecular charge transfer (ICT). The D-A ECL luminophores demonstrated that the ICT characteristics play a critical role in the electrochemistry and ECL of luminophores in the presence of tri-n-propylamine, which was rationalised experimentally and computationally. Furthemore, dual-peaked ECL-potential behaviours of the luminophores were rationalised using two competitive pathway ECL mechanisms, elucidated through the use of spooling ECL spectroscopy.

Sargassum horneri Extract Attenuates Depressive-like Behaviors in Mice Treated with Stress Hormone.

Sargassum horneri, a brown seaweed, is known for its various health benefits; however, there are no reports on its effects on depression. This study aimed to investigate the antidepressant effects of S. horneri ethanol extract (SHE) in mice injected with corticosterone (CORT) and to elucidate the underlying molecular mechanisms. Behavioral tests were conducted, and corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH), and CORT levels were measured. A fluorometric monoamine oxidase (MAO) enzyme inhibition assay was performed. Neurotransmitters like serotonin, dopamine, and norepinephrine levels were determined. Moreover, the ERK-CREB-BDNF signaling pathway in the prefrontal cortex and hippocampus was evaluated. Behavioral tests revealed that SHE has antidepressant effects by reducing immobility time and increasing time spent in open arms. Serum CRH, ACTH, and CORT levels decreased in the mice treated with SHE, as did the glucocorticoid-receptor expression in their brain tissues. SHE inhibited MAO-A and MAO-B activities. In addition, SHE increased levels of neurotransmitters. Furthermore, SHE activated the ERK-CREB-BDNF pathway in the prefrontal cortex and hippocampus. These findings suggest that SHE has antidepressant effects in CORT-injected mice, via the regulation of the hypothalamic-pituitary-adrenal axis and monoaminergic pathway, and through activation of the ERK-CREB-BDNF signaling pathway. Thus, our study suggests that SHE may act as a natural antidepressant.

Scalable Infrastructure Supporting Reproducible Nationwide Healthcare Data Analysis toward FAIR Stewardship.

Transparent and FAIR disclosure of meta-information about healthcare data and infrastructure is essential but has not been well publicized. In this paper, we provide a transparent disclosure of the process of standardizing a common data model and developing a national data infrastructure using national claims data. We established an Observational Medical Outcome Partnership (OMOP) common data model database for national claims data of the Health Insurance Review and Assessment Service of South Korea. To introduce a data openness policy, we built a distributed data analysis environment and released metadata based on the FAIR principle. A total of 10,098,730,241 claims and 56,579,726 patients' data were converted as OMOP common data model. We also built an analytics environment for distributed research and made the metadata publicly available. Disclosure of this infrastructure to researchers will help to eliminate information inequality and contribute to the generation of high-quality medical evidence.

The lipoprotein-associated phospholipase A2 inhibitor Darapladib sensitises cancer cells to ferroptosis by remodelling lipid metabolism.

Arachidonic and adrenic acids in the membrane play key roles in ferroptosis. Here, we reveal that lipoprotein-associated phospholipase A2 (Lp-PLA2) controls intracellular phospholipid metabolism and contributes to ferroptosis resistance. A metabolic drug screen reveals that darapladib, an inhibitor of Lp-PLA2, synergistically induces ferroptosis in the presence of GPX4 inhibitors. We show that darapladib is able to enhance ferroptosis under lipoprotein-deficient or serum-free conditions. Furthermore, we find that Lp-PLA2 is located in the membrane and cytoplasm and suppresses ferroptosis, suggesting a critical role for intracellular Lp-PLA2. Lipidomic analyses show that darapladib treatment or deletion of PLA2G7, which encodes Lp-PLA2, generally enriches phosphatidylethanolamine species and reduces lysophosphatidylethanolamine species. Moreover, combination treatment of darapladib with the GPX4 inhibitor PACMA31 efficiently inhibits tumour growth in a xenograft model. Our study suggests that inhibition of Lp-PLA2 is a potential therapeutic strategy to enhance ferroptosis in cancer treatment.

Estimation of Mastectomy Volume Using Preoperative Mastectomy Simulation Images Acquired by the Vectra H2 System.

Preoperative prediction of breast volume is very important in planning breast reconstruction. In this study, we assessed the usefulness of a novel method for preoperative estimation of mastectomy volume by comparing the weight of actual mastectomy specimens with the values predicted by the developed method using the Vectra H2. Methods: All patients underwent skin-sparing mastectomy and immediate autologous breast reconstruction. Preoperatively, the patient's breast was scanned using the Vectra H2 and a postmastectomy simulation image was constructed on a personal computer. The estimated mastectomy volume was calculated by comparing the preoperative and postmastectomy three-dimensional simulation images. Correlation coefficients with the estimated mastectomy volume were calculated for the actual mastectomy weight and the transplanted flap weight. Results: Forty-five breasts of 42 patients were prospectively analyzed. The correlations with the estimated mastectomy volume were r = 0.95 (P < 0.0001) for actual mastectomy weight and r = 0.84 (P < 0.0001) for transplanted free-flap weight. The mastectomy weight estimation formula obtained by linear regression analysis using the estimated mastectomy volume was 0.98 × estimated mastectomy volume + 5.4 (coefficient of determination R2 = 0.90, P < 0.0001). The root-mean-square error for the mastectomy weight estimation formula was 38 g. Conclusions: We used the Vectra H2 system to predict mastectomy volume. The predictions provided by this method were highly accurate. Three-dimensional imaging is a noncontact, noninvasive measurement method that is both accurate and simple to perform. Use of this effective tool for volume prediction is expected to increase in the future.

Deep Learning-Based Image Noise Quantification Framework for Computed Tomography.

OBJECTIVE: Noise quantification is fundamental to computed tomography (CT) image quality assessment and protocol optimization. This study proposes a deep learning-based framework, Single-scan Image Local Variance EstimatoR (SILVER), for estimating the local noise level within each region of a CT image. The local noise level will be referred to as a pixel-wise noise map. METHODS: The SILVER architecture resembled a U-Net convolutional neural network with mean-square-error loss. To generate training data, 100 replicate scans were acquired of 3 anthropomorphic phantoms (chest, head, and pelvis) using a sequential scan mode; 120,000 phantom images were allocated into training, validation, and testing data sets. Pixel-wise noise maps were calculated for the phantom data by taking the per-pixel SD from the 100 replicate scans. For training, the convolutional neural network inputs consisted of phantom CT image patches, and the training targets consisted of the corresponding calculated pixel-wise noise maps. Following training, SILVER noise maps were evaluated using phantom and patient images. For evaluation on patient images, SILVER noise maps were compared with manual noise measurements at the heart, aorta, liver, spleen, and fat. RESULTS: When tested on phantom images, the SILVER noise map prediction closely matched the calculated noise map target (root mean square error <8 Hounsfield units). Within 10 patient examinations, SILVER noise map had an average percent error of 5% relative to manual region-of-interest measurements. CONCLUSION: The SILVER framework enabled accurate pixel-wise noise level estimation directly from patient images. This method is widely accessible because it operates in the image domain and requires only phantom data for training.

Genomic analyses in Cornelia de Lange Syndrome and related diagnoses: Novel candidate genes, genotype-phenotype correlations and common mechanisms.

Cornelia de Lange Syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder characterized by highly variable manifestations of growth and developmental delays, upper limb involvement, hypertrichosis, cardiac, gastrointestinal, craniofacial, and other systemic features. Pathogenic variants in genes encoding cohesin complex structural subunits and regulatory proteins (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the major pathogenic contributors to CdLS. Heterozygous or hemizygous variants in the genes encoding these five proteins have been found to be contributory to CdLS, with variants in NIPBL accounting for the majority (>60%) of cases, and the only gene identified to date that results in the severe or classic form of CdLS when mutated. Pathogenic variants in cohesin genes other than NIPBL tend to result in a less severe phenotype. Causative variants in additional genes, such as ANKRD11, EP300, AFF4, TAF1, and BRD4, can cause a CdLS-like phenotype. The common role that these genes, and others, play as critical regulators of developmental transcriptional control has led to the conditions they cause being referred to as disorders of transcriptional regulation (or "DTRs"). Here, we report the results of a comprehensive molecular analysis in a cohort of 716 probands with typical and atypical CdLS in order to delineate the genetic contribution of causative variants in cohesin complex genes as well as novel candidate genes, genotype-phenotype correlations, and the utility of genome sequencing in understanding the mutational landscape in this population.

Proteasome-Associated Proteins, PA200 and ECPAS, Are Essential for Murine Spermatogenesis.

Proteasomes are highly sophisticated protease complexes that degrade non-lysosomal proteins, and their proper regulation ensures various biological functions such as spermatogenesis. The proteasome-associated proteins, PA200 and ECPAS, are predicted to function during spermatogenesis; however, male mice lacking each of these genes sustain fertility, raising the possibility that these proteins complement each other. To address this issue, we explored these possible roles during spermatogenesis by producing mice lacking these genes (double-knockout mice; dKO mice). Expression patterns and quantities were similar throughout spermatogenesis in the testes. In epididymal sperm, PA200 and ECPAS were expressed but were differentially localized to the midpiece and acrosome, respectively. Proteasome activity was considerably reduced in both the testes and epididymides of dKO male mice, resulting in infertility. Mass spectrometric analysis revealed LPIN1 as a target protein for PA200 and ECPAS, which was confirmed via immunoblotting and immunostaining. Furthermore, ultrastructural and microscopic analyses demonstrated that the dKO sperm displayed disorganization of the mitochondrial sheath. Our results indicate that PA200 and ECPAS work cooperatively during spermatogenesis and are essential for male fertility.

Generation of a PDGFRB-mCherry knock-in reporter human induced pluripotent stem cell line (KITi001-A-1), using CRISPR/Cas9 nuclease.

PDGFRB encodes platelet-derived growth factor receptor beta (PDGFR-ß), a cell surface tyrosine kinase receptor for members of the platelet-derived growth factor family. It is required for the normal development of the vascular and nervous systems and rearrangement of the actin cytoskeleton. PDGFR-ß plays an essential role in early liver diseases, including liver fibrosis. Here, we generated a human induced pluripotent stem cell (iPSC) line, KITi001-A-1, using CRISPR/Cas9. This reporter iPSC line and its derivatives are useful for tracing PDGFR-ß-expressing cells and for screening for liver fibrosis-inducing compounds.