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Abstract Background Homologous recombination deficiency (HRD) stands as a clinical indicator for discerning responsive outcomes to platinum-based chemotherapy and poly ADP-ribose polymerase (PARP) inhibitors. One of the conventional approaches to HRD prognostication has generally centered on identifying deleterious mutations within the BRCA1/2 genes, along with quantifying the genomic scars, such as Genomic Instability Score (GIS) estimation with scarHRD. However, the scarHRD method has limitations in scenarios involving tumors bereft of corresponding germline data. Although several RNA-seq-based HRD prediction algorithms have been developed, they mainly support cohort-wise classification, thereby yielding HRD status without furnishing an analogous quantitative metric akin to scarHRD. This study introduces the expHRD method, which operates as a novel transcriptome-based framework tailored to n-of-1-style HRD scoring. Results The prediction model has been established using the elastic net regression method in the Cancer Genome Atlas (TCGA) pan-cancer training set. The bootstrap technique derived the HRD geneset for applying the expHRD calculation. The expHRD demonstrated a notable correlation with scarHRD and superior performance in predicting HRD-high samples. We also performed intra- and extra-cohort evaluations for clinical feasibility in the TCGA-OV and the Genomic Data Commons (GDC) ovarian cancer cohort, respectively. The innovative web service designed for ease of use is poised to extend the realms of HRD prediction across diverse malignancies, with ovarian cancer standing as an emblematic example. Conclusions Our novel approach leverages the transcriptome data, enabling the prediction of HRD status with remarkable precision. This innovative method addresses the challenges associated with limited available data, opening new avenues for utilizing transcriptomics to inform clinical decisions.

Summary: Histone H3K9 methylated heterochromatin silences repetitive non-coding sequences and lineage-specific genes during development, but how tissue-specific genes escape from heterochromatin in differentiated cells is unclear. Here, we examine age-dependent transcriptomic profiling of terminally differentiated mouse retina to identify epigenetic regulators involved in heterochromatin reorganization. The single-cell RNA sequencing analysis reveals a gradual downregulation of Kdm3b in cone photoreceptors during aging. Disruption of Kdm3b (Kdm3b+/−) of 12-month-old mouse retina leads to the decreasing number of cones via apoptosis, and it changes the morphology of cone ribbon synapses. Integration of the transcriptome with epigenomic analysis in Kdm3b+/− retinas demonstrates gains of heterochromatin features in synapse assembly and vesicle transport genes that are downregulated via the accumulation of H3K9me1/2. Contrarily, losses of heterochromatin in apoptotic genes exacerbated retinal neurodegeneration. We propose that the KDM3B-centered epigenomic network is crucial for balancing of cone photoreceptor homeostasis via the modulation of gene set-specific heterochromatin features during aging.

Abstract This study discloses a dataset of electric vehicles’ (EVs’) charging transactions at a scale for multi-faceted analysis from both EV charger and user perspectives. The data comprises whole sessions that occurred during a charging operation company’s annual commercial operation period, specifically including identifiers and charger location categories. For data acquisition, machine-to-machine wireless communication system with proper retransmission for interruption is utilised. The entire dataset is newly collected and is available with 72,856 sessions from 2,337 EV users and 2,119 chargers. The dataset can be used in a variety of ways for the functioning of power systems and markets, including EV charging service businesses, charger installation siting, demand transaction market design, and long-term investment planning of EV-related infrastructure.

Abstract For the accurate and continuous control of soft actuators in dynamic environments, the movements of the soft actuators must be monitored in real-time. To this end, various soft actuators capable of self-monitoring have been developed by separately integrating sensing devices into actuators. However, integrating such heterogeneous sensing components into soft actuators results in structural complexity, high manufacturing costs, and poor interfacial stability. Here, we report on intelligent pneumatic fiber-reinforced soft actuators with an inherent flexible proprioceptive sensor that uses only the essential components of typical fiber-reinforced soft actuators. The inherent flexible proprioceptive sensor is achieved by leveraging two parallel conductive microfibers around an elastomeric chamber of the soft actuator, which simultaneously acts as both a capacitive bending sensor and radial expansion limiting fibers of typical fiber-reinforced soft actuators. The proprioceptive soft actuator exhibits excellent mechanical actuation up to 240° bending motion and proprioceptive sensing performance with high sensitivity of 1.2 pF rad−1. Mathematical analysis and simulations of the soft actuator can effectively predict the bending actuation and capacitive responses against input pressures. We demonstrate that proprioceptive soft actuators can be used to construct a soft gripping system and prosthetic hand which express various hand gestures and perform dexterous manipulation with real-time proprioceptive sensing capability.

Abstract Salts play a crucial role in maintaining human health by regulating fluid levels and supporting various physiological processes. However, conventional seawater-derived salts are associated with microplastic pollution and pose potential health risks. Jeju lava seawater (JLS), sourced exclusively from Jeju Island, has emerged as a unique alternative, free of microplastics and enriched with essential minerals such as magnesium, calcium, zinc, and iron. In this study, we investigated the effects of JLS on osteoarthritis (OA) pathogenesis, focusing on chondrocyte metabolism and OA development. We performed surgical destabilization of the medial meniscus to establish a murine model of OA. We examined the expression of catabolic and anabolic factors in JLS-treated chondrocytes. Our cell viability assay revealed that JLS treatment was not cytotoxic to chondrocytes at concentrations ≤ 0.5%. Additionally, JLS treatment resulted in a concentration-dependent increase in the expression of anabolic factors like aggrecan, SOX9, and COL2A1 while decreasing the expression of catabolic factors such as MMP3, MMP13, ADAMTS4, and ADAMTS5 in the chondrocytes stimulated with pro-inflammatory cytokines. Although not statistically significant compared to the control group, JLS intake slightly attenuated the OARSI score, osteophyte score, synovitis score, subchondral bone thickness, and osteophyte size in the mouse model of OA. Conclusively, these results suggest that JLS ameliorates OA by positively influencing chondrocyte metabolism, making it a promising therapeutic candidate for OA management.

To develop in vitro respiratory models, it is crucial to identify the factors involved in epithelial cell differentiation. In this study, we comprehensively analyzed the effects of air–liquid interface (ALI) culture on epithelial cell differentiation using single-cell RNA sequencing (scRNA-seq). ALI culture induced a pronounced shift in cell composition, marked by a fivefold increase in ciliated cells and a reduction of more than half in basal cells. Transcriptional signatures associated with epithelial cell differentiation, analyzed using iPathwayGuide software, revealed the downregulation of VEGFA and upregulation of CDKN1A as key signals for epithelial differentiation. Our findings highlight the efficacy of the ALI culture for replicating the human lung airway epithelium and provide valuable insights into the crucial factors that influence human ciliated cell differentiation.

Herein, the challenge of accurately classifying the manufacturing origin of printing paper, including continent, country, and specific product, was addressed. One-dimensional convolutional neural network (1D CNN) models trained on infrared (IR) spectrum data acquired from printing paper samples were used for the task. The preprocessing of the IR spectra through a second-derivative transformation and the restriction of the spectral range to 1800 to 1200 cm-1 improved the classification performance of the model. The outcomes were highly promising. Models trained on second-derivative IR spectra in the 1800 to 1200-cm-1 range exhibited perfect classification for the manufacturing continent and country, with an impressive F1 score of 0.980 for product classification. Notably, the developed 1D CNN model outperformed traditional machine learning classifiers, such as support vector machines and feed-forward neural networks. In addition, the application of data point attribution enhanced the transparency of the decision-making process of the model, offering insights into the spectral patterns that affect classification. This study makes a considerable contribution to printing paper classification, with potential implications for accurate origin identification in various fields.

Graph neural networks (GNNs) are powerful tools for handling graph-structured data. However, their design often limits them to learning only higher-order feature interactions, leaving low-order feature interactions overlooked. To address this problem, we introduce a novel GNN method called explicit feature interaction-aware graph neural network (EFI-GNN). Unlike conventional GNNs, EFI-GNN is a multilayer linear network designed to model arbitrary-order feature interactions explicitly within graphs. To validate the efficacy of EFI-GNN, we conduct experiments using various datasets. The experimental results demonstrate that EFI-GNN has competitive performance with existing GNNs, and when a GNN is jointly trained with EFI-GNN, predictive performance sees an improvement. Furthermore, the predictions made by EFI-GNN are interpretable, owing to its linear construction. The source code of EFI-GNN is available at https://github.com/gim4855744/EFI-GNN.

The Paris Agreement, which is carried out in a bottom-up manner, is giving great vitality to the transition to low-carbon energy system. Accordingly, as the spread of renewable energy increases, securing flexibility resources is emerging as a keyword in the power system and power market, and many studies on demand response (DR) and energy storage system (ESS) classified as demand-side flexible resources are being conducted. However, most of the studies on DR are on voluntary DR programs that participate through bidding among incentive-based DR or price-based DR programs, and ESS faced difficulties in its distribution due to low economic feasibility. Therefore, in this work, we propose a feasible process for participating in a reliability DR program that guarantees high profitability but involves high uncertainty, and non-cooperative game model is suggested to mitigate the uncertainty through surplus electricity-trading model of ESS. In addition, a subjective decision-making based on prospect theory is proposed to reflect the impact of the uncertainty about the incentive-based program’s engagement. Case study results performed in an environment formed based on actual operation data of the Korean DR market prove that participants’ uncertainty is mitigated when participating in the DR market through power trading of ESS through the proposed model. In addition, a small-scale ESS with an average benefit–cost ratio of 0.78 improves by up to 1.08 (1.04 with a standard scenario).

Abstract Objectives We performed comprehensive association analyses of common high-confidence gnomAD-reported copy number deletions (CNDs) with 60 quantitative traits from UK10K consortium WGS data. Methods The study made use of data generated by the UK10K Consortium. UK10K consortium WGS data consist of TwinsUK (n = 1754, middle-aged females) and ALSPAC (n = 1867, birth to adolescence) cohorts. UK10K consortium called 18,739 CNDs (hg19) with GenomeSTRiP software. After filtering out variants with minor allele frequency

This study shows a case of neoadjuvant chemotherapy application for the management of a 34-year-old male patient diagnosed with invasive intraductal papillary mucinous neoplasm (IPMN), for which curative margin-negative resection initially seemed challenging. Five cycles of the FOLFIRINOX regimen (5-fluorouracil, leucovorin, irinotecan, and oxaliplatin) were administered preoperatively, resulting in a significant reduction of the intraductal mass size and deformity of the main vessels. The patient subsequently underwent a successful robotic pylorus-preserving pancreatoduodenectomy. Postoperatively, the patient received adjuvant chemotherapy with FOLFIRINOX, and after 5 months, showed no signs of tumor recurrence or specific complications. These findings suggest that neoadjuvant therapy can be a potentially effective strategy even in advanced invasive IPMN. Further research is necessary to establish guidelines for its application.

Pleuronectidae is a well-studied familyin the order Pleuronectiformes. In contrast, genetic research on the flatfish Acanthopsetta nadeshnyi of the Pleuronectidae family is limited. This study reports the complete mitogenome of A. nadeshnyi. The mitogenome was 17,206 bases long and included 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes, and a putative control region. Phylogenetic analysis based on the nucleotide sequences of the 13 PCGs confirmed that A. nadeshnyi belongs to the Pleuronectidae family.

Abstract In response to the growing demand for wearable devices designed for seamless integration with 3D bio‐surfaces, fiber‐based devices have gained prominence in textile‐based wearable electronics due to their flexibility and unique structure. In particular, though diodes with rectifying properties are crucial for a range of electronic systems, there has been scant reporting on diodes with a fiber structure. This study introduces a fiber‐based flexible ionic diode that exhibits a rectification ratio of 2773 and an output current of 28.2 mA at 3 V. The diode is composed of a double helical Zn‐based fiber anode, a Ti‐based fiber cathode on Au nanoparticle‐based flexible fiber electrodes, and a LiCl hydrogel electrolyte. By modulating the double helical design and the ionic conductivity of the hydrogel, the electrical performance of the diode to achieve varying rectification ratios and output currents can be tailored. Owing to the remarkable flexibility and stability of the fiber electrodes, the fiber‐based ionic diode consistently upholds its rectifying capabilities, even under washing procedures and significant bending deformation. Furthermore, this diode seamlessly integrates into various electronic circuits, including half‐wave rectifiers, capacitor–diode filters, and logic gate systems.

Background: DNA methylation markers are considered robust diagnostic features in various cancer types, as epigenetic marks are commonly altered during cancer progression. Differentiation between benign prostatic hyperplasia (BPH) and early-stage prostate cancer (PCa) is clinically difficult, relying on the information of the patient's symptoms or levels of prostate-specific antigen. Methods: A total of 42 PCa patients and 11 BPH patients were recruited. Genomic DNA was purified from tissues and used for the library preparation of the target-enriched methylome with enzymatic conversion and a Twist 85 Mbp EM-seq panel. Paired-end sequencing (150 bp) was performed using NovaSeq 6000 or NextSeq 550. After quality control, including adapter trimming and de-duplication of raw sequencing data, differential methylation patterns were analyzed between the BPH and PCa groups. Results: We report DNA methylation patterns existing between BPH and PCa. The major finding is that broad hypermethylation occurred at genic loci in PCa tissues as compared to the BPH. Gene ontology analysis suggested that hypermethylation of genic loci involved in chromatin and transcriptional regulation is involved in cancer progression. We also compared PCa tissues with high Gleason scores to tissues with low Gleason scores. The high-Gleason PCa tissues showed hundreds of focal differentially methylated CpG sites corresponding to genes functioning in cancer cell proliferation or metastasis. This suggests that dissecting early-to-advanced-grade cancer stages requires an in-depth analysis of differential methylation at the single CpG site level. Conclusions: Our study reports that enzymatic methylome sequencing data can be used to distinguish PCa from BPH and advanced PCa from early-stage PCa. The stage-specific methylation patterns in this study will be valuable resources for diagnostic purposes as well as further development of liquid biopsy approaches for the early detection of PCa.

Abstract Natural killer (NK) cells are promising tool for cancer treatment. Methods have been developed for large-scale NK cell expansion, including feeder cell-based methods or methods involving stimulation with NK cell activating signals, such as anti-CD16 antibodies. Different clones of anti-CD16 antibodies are available; however, a comprehensive comparison of their differential effects on inducing NK cell activation and expansion has not been conducted among these various clones under the same experimental conditions. Herein, we found that the NK cell expansion rate differed depending on the various anti-CD16 antibodies (CB16, 3G8, B73.1, and MEM-154) coated on microbeads when stimulated with genetically engineered feeder cells, K562‑membrane-bound IL‑18, and mbIL‑21 (K562‑mbIL‑18/-21). Only the CB16 clone combination caused enhanced NK cell expansion over K562‑mbIL‑18/-21 stimulation alone with similar NK cell functionality. Treatment with the CB16 clone once on the initial day of NK cell expansion was sufficient to maximize the combination effect. Overall, we developed a more enhanced NK expansion system by merging a feeder to effectively stimulate CD16 with the CB16 clone.

Abstract Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Regulation of metabolic gene expression is crucial for maximizing bioproduction titers. Recent engineering tools including CRISPR/Cas9, CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) have enabled effective knock-out, knock-down, and overexpression of endogenous pathway genes, respectively, for advanced strain engineering. CRISPRi in particular has emerged as a powerful tool for gene repression through the use of a deactivated Cas9 (dCas9) protein and target guide RNA (gRNA). By constructing gRNA arrays, CRISPRi has the capacity for multiplexed gene downregulation across multiple orthogonal pathways for enhanced bioproduction titers. In this study, we harnessed CRISPRi to downregulate 32 essential and non-essential genes in E. coli strains heterologously expressing either the original mevalonate pathway or isopentenyl diphosphate (IPP) bypass pathway for isoprenol biosynthesis. Isoprenol remains a candidate bioproduct both as a drop-in blend additive and as a precursor for the high-performance sustainable aviation fuel, 1,4-dimethylcyclooctane (DMCO). Of the 32 gRNAs targeting genes associated with isoprenol biosynthesis, a subset was found to vastly improve product titers. Construction of a multiplexed gRNA library based on single guide RNA (sgRNA) performance enabled simultaneous gene repression, yielding a 3 to 4.5-fold increase in isoprenol titer (1.82 ± 0.19 g/L) on M9-MOPS minimal medium. We then scaled the best performing CRISPRi strain to 2-L fed-batch cultivation and demonstrated translatable titer improvements, ultimately obtaining 12.4 ± 1.3 g/L isoprenol. Our strategy further establishes CRISPRi as a powerful tool for tuning metabolic flux in production hosts and that titer improvements are readily scalable with potential for applications in industrial bioproduction.

Hematoxylin and eosin (H&E) staining has been widely used as a fundamental and essential tool for diagnosing diseases and understanding biological phenomena by observing cellular arrangements and tissue morphological changes. However, conventional staining methods commonly involve solution-based, complex, multistep processes that are susceptible to user-handling errors. Moreover, inconsistent staining results owing to staining artifacts pose real challenges for accurate diagnosis. This study introduces a solution-free H&E staining method based on agarose hydrogel patches that is expected to represent a valuable tool to overcome the limitations of the solution-based approach. Using two agarose gel-based hydrogel patches containing hematoxylin and eosin dyes, H&E staining can be performed through serial stamping processes, minimizing color variation from handling errors. This method allows easy adjustments of the staining color by controlling the stamping time, effectively addressing variations in staining results caused by various artifacts, such as tissue processing and thickness. Moreover, the solution-free approach eliminates the need for water, making it applicable even in environmentally limited middle- and low-income countries, while still achieving a staining quality equivalent to that of the conventional method. In summary, this hydrogel-based H&E staining method can be used by researchers and medical professionals in resource-limited settings as a powerful tool to diagnose and understand biological phenomena.

Abstract Background Advanced spark ignition engines require high performance fuels with improved resistance to autoignition. Biologically derived olefinic alcohols have arisen as promising blendstock candidates due to favorable octane numbers and synergistic blending characteristics. However, production and downstream separation of these alcohols are limited by their intrinsic toxicity and high aqueous solubility, respectively. Bioproduction of carboxylate esters of alcohols can improve partitioning and reduce toxicity, but in practice has been limited to saturated esters with characteristically low octane sensitivity. If olefinic esters retain the synergistic blending characteristics of their alcohol counterparts, they could improve the bioblendstock combustion performance while also retaining the production advantages of the ester moiety. Results Optimization of Escherichia coli isoprenoid pathways has led to high titers of isoprenol and prenol, which are not only excellent standalone biofuel and blend candidates, but also novel targets for esterification. Here, a selection of olefinic esters enhanced blendstock performance according to their degree of unsaturation and branching. E. coli strains harboring optimized mevalonate pathways, thioester pathways, and heterologous alcohol acyltransferases (ATF1, ATF2, and SAAT) were engineered for the bioproduction of four novel olefinic esters. Although prenyl and isoprenyl lactate titers were limited to 1.48 ± 0.41 mg/L and 5.57 ± 1.36 mg/L, strains engineered for prenyl and isoprenyl acetate attained titers of 176.3 ± 16.0 mg/L and 3.08 ± 0.27 g/L, respectively. Furthermore, prenyl acetate (20% bRON = 125.8) and isoprenyl acetate (20% bRON = 108.4) exhibited blend properties comparable to ethanol and significantly better than any saturated ester. By further scaling cultures to a 2-L bioreactor under fed-batch conditions, 15.0 ± 0.9 g/L isoprenyl acetate was achieved on minimal medium. Metabolic engineering of acetate pathway flux further improved titer to attain an unprecedented 28.0 ± 1.0 g/L isoprenyl acetate, accounting for 75.7% theoretical yield from glucose. Conclusion Our study demonstrated novel bioproduction of four isoprenoid oxygenates for fuel blending. Our optimized E. coli production strain generated an unprecedented titer of isoprenyl acetate and when paired with its favorable blend properties, may enable rapid scale-up of olefinic alcohol esters for use as a fuel blend additive or as a precursor for longer-chain biofuels and biochemicals.

Abstract Microplastics (MPs) are now a global issue due to increased plastic production and use. Recently, various studies have been performed in response to the human health risk assessment. However, these studies have focused on spherical MPs, which have smooth edges and a spherical shape and account for less than 1% of MPs in nature. Unfortunately, studies on fragment-type MPs are very limited and remain in the initial stages. In this study, we studied the effect that 16.4 µm fragment type polypropylene (PP) MPs, which have an irregular shape and sharp edges and form naturally in the environment, had on breast cancer. The detrimental effects of PPMPs on breast cancer metastasis were examined. Here, 1.6 mg/ml of PPMP, which does not induce cytotoxicity in MDA-MB-231, was used, and at this concentration, PPMP did not induce morphological changes or cellular migrating in the MDA-MB-231 and MCF-7 cells. However, PPMP incubation for 24 hours in the MDA-MB-231 cells significantly altered the level of cell cycle-related transcripts in an RNA-seq analysis. When confirmed by qRT-PCR, the gene expression of TMBIM6, AP2M1, and PTP4A2 was increased, while the transcript level of FTH1 was decreased. Further, secretion of the pro-inflammatory cytokine IL-6 from cancer cells was elevated with the incubation of PPMP for 12 hours. These results suggest that PPMP enhances metastasis-related gene expression and cytokines in breast cancer cells, exacerbating breast cancer metastasis.

Abstract Background Previous investigations of transcriptomic signatures of cancer patient survival and post-therapy relapse have focused on tumor tissue. In contrast, here we show that in colorectal cancer (CRC) transcriptomes derived from normal tissues adjacent to tumors (NATs) are better predictors of relapse. Results Using the transcriptomes of paired tumor and NAT specimens from 80 Korean CRC patients retrospectively determined to be in recurrence or nonrecurrence states, we found that, when comparing recurrent with nonrecurrent samples, NATs exhibit a greater number of differentially expressed genes (DEGs) than tumors. Training two prognostic elastic net-based machine learning models—NAT-based and tumor-based in our Samsung Medical Center (SMC) cohort, we found that NAT-based model performed better in predicting the survival when the model was applied to the tumor-derived transcriptomes of an independent cohort of 450 COAD patients in TCGA. Furthermore, compositions of tumor-infiltrating immune cells in NATs were found to have better prognostic capability than in tumors. We also confirmed through Cox regression analysis that in both SMC-CRC as well as in TCGA-COAD cohorts, a greater proportion of genes exhibited significant hazard ratio when NAT-derived transcriptome was used compared to when tumor-derived transcriptome was used. Conclusions Taken together, our results strongly suggest that NAT-derived transcriptomes and immune cell composition of CRC are better predictors of patient survival and tumor recurrence than the primary tumor.

Microstomus achne (Jordan and Starks, 1904) is an economically valuable flatfish belonging to the family Pleuronectidae and the only flatfish that inhabits Korea. Here, we report on the complete mitochondrial genome of M. achne and the phylogenetic relationship between close species. The mitogenome is 16,971 bp long and encodes 13 protein-coding genes (PCGs), 22 transfer RNAs, and two ribosomal RNAs. The phylogenetic analysis showed that M. achne clustered with Glyptocephalus stelleri, which supports the conclusion that M. achne belongs to the family Pleuronectidae. The results of this study provide a better understanding of M. achne.

Harmful algal blooms (HABs) pose a potential risk to human and ecosystem health. HAB occurrences are influenced by numerous environmental factors; thus, accurate predictions of HABs and explanations about the predictions are required to implement preventive water quality management. In this study, machine learning (ML) algorithms, i.e., random forest (RF) and extreme gradient boosting (XGB), were employed to predict HABs in eight water supply reservoirs in South Korea. The use of synthetic minority oversampling technique for addressing imbalanced HAB occurrences improved classification performance of the ML algorithms. Although RF and XGB resulted in marginal performance differences, XGB exhibited more stable performance in the presence of data imbalance. Furthermore, a post hoc explanation technique, Shapley additive explanation was employed to estimate relative feature importance. Among the input features, water temperature and concentrations of total nitrogen and total phosphorus appeared important in predicting HAB occurrences. The results suggest that the use of ML algorithms along with explanation methods increase the usefulness of predictive models as a decision-making tool for water quality management. HIGHLIGHTS Machine learning (ML) algorithms were used to predict HAB occurrences in water supply reservoirs.; Synthetic minority oversampling technique (SMOTE) was applied to address the class imbalance problem.; The performance of extreme gradient boosting (XGB) with SMOTE was more stable under class imbalance compared to random forest.; Shapley additive explanation (SHAP) was used to estimate relative feature importance.; Water temperature and nutrients were generally important features.;

Intimate partner violence (IPV) substantially harms women's overall health worldwide. The intergenerational cycle of IPV among women remains underexplored from the perspective of victimization and perpetration, and by types of subsequent IPV. The 2017 Philippines National Demographic and Health Survey dataset of 12,248 currently in-union (married or cohabiting) women aged 15 to 49 were utilized in this study. The main exposure variable was measured by the question: “as far as you know, did your father ever beat your mother?“. Multivariate logistic regression was performed to investigate the association between being ever exposed to parental IPV and (1) women's IPV victimization (by types: any, physical, sexual, and emotional) and (2) IPV perpetration (physical) by women against their husbands or male partners. Further, multinomial logistic regression examined the association between exposure to parental IPV and the experience of being an IPV victim only, perpetrator only, or both. We have found that women who were exposed to parental IPV were more likely to experience IPV victimization (OR: 2.1, 95% CI: 1.9, 2.4 for any IPV; OR: 2.3, 95% CI: 2.0, 2. for physical IPV; OR: 2.0, 95% CI: 1.6, 2.4 for sexual IPV; and OR: 2.0, 95% CI: 1.8, 2.2 for emotional IPV), and also perpetrate physical IPV themselves (OR: 2.1, 95% CI: 1.9, 2.4) compared to those unexposed to parental IPV. Moreover, women exposed to parental IPV were three times more likely to be both a perpetrator and a victim of IPV (OR: 3.1, 95% CI: 2.7, 3.7), much higher than the odds of being a victim only (OR: 1.9, 95% CI: 1.8, 2.2) or a perpetrator only (OR: 1.9, 95% CI: 1.6, 2.). In summary, exposure to parental IPV was associated with Filipino women being victims and perpetrators of IPV themselves. The integration of violence prevention within parenting and community programs can be considered to prevent the perpetuation of the intergenerational cycle of IPV.

The glutamine–histidine–glycine–valine (QHGV), a peptide derived from oysters, exhibits antioxidant activity and is being actively researched as a potential pharmaceutical and functional cosmetic ingredient. In this study, we synthesized the QHGV peptide and explored the hitherto unknown anti-inflammatory effects of QHGV. The antioxidant property was also characterized by conjugating with various naturally derived phenolic acids, such as caffeic, gallic, ferulic, sinapinic, and vanillic acids. Conjugation with phenolic acids not only enhanced the antioxidant activity of QHGV but also diminished the lipopolysaccharide-induced generation of reactive oxygen species (ROS) in the murine macrophage cell line, RAW 264.7. The reduction in the levels of reactive oxygen species led to the reduced mRNA expression of inducible nitric oxide synthase (iNos) and cyclooxygenase 2 (Cox-2), resulting in an anti-inflammatory effect through the inhibition of the phosphorylation of mitogen-activated protein kinase, including extracellular signal-activated protein kinase, c-Jun NH2-terminal kinase, and p38. Furthermore, the phenolic acid-conjugated peptides increased the mRNA and protein levels of collagen type I, indicative of a wrinkle-improvement effect. The phenolic acid conjugates of the peptide were not cytotoxic to human keratinocytes such as HaCaT cells. These results suggest that phenolic acid conjugation can enhance the potential of peptides as drug and cosmetic resources.

Fibrous dysplasia (FD) is a rare bone disorder characterized by the replacement of normal bone with benign fibro-osseous tissue. Developments in our understanding of the pathophysiology and treatment options are impeded by the lack of suitable research models. In this study, we developed an in vitro organotypic model capable of recapitulating key intrinsic and phenotypic properties of FD. Initially, transcriptomic profiling of individual cells isolated from patient lesional tissues unveiled intralesional molecular and cellular heterogeneity. Leveraging these insights, we established patient-derived organoids (PDOs) using primary cells obtained from patient FD lesions. Evaluation of PDOs demonstrated preservation of fibrosis-associated constituent cell types and transcriptional signatures observed in FD lesions. Additionally, PDOs retained distinct constellations of genomic and metabolic alterations characteristic of FD. Histological evaluation further corroborated the fidelity of PDOs in recapitulating important phenotypic features of FD that underscore their pathophysiological relevance. Our findings represent meaningful progress in the field, as they open up the possibility for in vitro modeling of rare bone lesions in a three-dimensional context and may signify the first step towards creating a personalized platform for research and therapeutic studies.

The inevitable gap between in vitro and in vivo degradation rate of biomaterials has been a challenging factor in the optimal designing of scaffold's degradation to be balanced with new tissue formation. To enable non-/minimum-invasive tracking of in vivo scaffold degradation, chemical modifications have been applied to label polymers with fluorescent dyes. However, the previous approaches may have limited expandability due to complicated synthesis processes. Here, we introduce a simple and efficient method to fluorescence labeling of polymeric scaffolds via blending with near-infrared (NIR) quantum dots (QDs), semiconductor nanocrystals with superior optical properties. QDs-labeled, 3D-printed PCL scaffolds showed promising efficiency and reliability in quantitative measurement of degradation using a custom-built fiber-optic imaging modality. Furthermore, QDs-PCL scaffolds showed neither cytotoxicity nor secondary labeling of adjacent cells. QDs-PCL scaffolds also supported the engineering of fibrous, cartilaginous, and osteogenic tissues from mesenchymal stem/progenitor cells (MSCs). In addition, QDs-PCL enabled a distinction between newly forming tissue and the remaining mass of scaffolds through multi-channel imaging. Thus, our findings suggest a simple and efficient QDs-labeling of PCL scaffolds and minimally invasive imaging modality that shows significant potential to enable in vivo tracking of scaffold degradation as well as new tissue formation.

Summary: Predicting cancer recurrence is essential to improving the clinical outcomes of patients with colorectal cancer (CRC). Although tumor stage information has been used as a guideline to predict CRC recurrence, patients with the same stage show different clinical outcomes. Therefore, there is a need to develop a method to identify additional features for CRC recurrence prediction. Here, we developed a network-integrated multiomics (NIMO) approach to select appropriate transcriptome signatures for better CRC recurrence prediction by comparing the methylation signatures of immune cells. We validated the performance of the CRC recurrence prediction based on two independent retrospective cohorts of 114 and 110 patients. Moreover, to confirm that the prediction was improved, we used both NIMO-based immune cell proportions and TNM (tumor, node, metastasis) stage data. This work demonstrates the importance of (1) using both immune cell composition and TNM stage data and (2) identifying robust immune cell marker genes to improve CRC recurrence prediction. The bigger picture: Colorectal cancer is a significant global public health issue, and accurately predicting its recurrence remains a challenge despite advances in screening and treatment. Accurate recurrence prediction is crucial for clinicians to make informed decisions about treatment and follow-up care, leading to timely interventions that may improve outcomes and potentially prolong survival. In this study, we present a method that combines immune cell information with clinical data to enhance the accuracy of recurrence risk prediction. The predictive performance of the method was validated using two independent cohorts of patients with colorectal cancer of different races. Our approach has implications for both clinical practice and research, as it helps to suggest treatment strategies by predicting recurrence risk and identifying potential therapeutic targets based on immune cell information.

Abstract Fiber‐based implantable electronics are one of promising candidates for in vivo biomedical applications thanks to their unique structural advantages. However, development of fiber‐based implantable electronic devices with biodegradable capability remains a challenge due to the lack of biodegradable fiber electrodes with high electrical and mechanical properties. Here, a biocompatible and biodegradable fiber electrode which simultaneously exhibits high electrical conductivity and mechanical robustness is presented. The fiber electrode is fabricated through a facile approach that incorporates a large amount of Mo microparticles into outermost volume of a biodegradable polycaprolactone (PCL) fiber scaffold in a concentrated manner. The biodegradable fiber electrode simultaneously exhibits a remarkable electrical performance (≈43.5 Ω cm−1), mechanical robustness, bending stability, and durability for more than 4000 bending cycles based on the Mo/PCL conductive layer and intact PCL core in the fiber electrode. The electrical behavior of the biodegradable fiber electrode under the bending deformation is analyzed by an analytical prediction and a numerical simulation. In addition, the biocompatible properties and degradation behavior of the fiber electrode are systematically investigated. The potential of biodegradable fiber electrode is demonstrated in various applications such as an interconnect, a suturable temperature sensor, and an in vivo electrical stimulator.

Measurement(s) electricity consumption Technology Type(s) advanced metering infrastructure

The airway epithelium lining the luminal surface of the respiratory tract creates a protective barrier that ensures maintenance of tissue homeostasis and prevention of respiratory diseases. The airway epithelium, unfortunately, is frequently injured by inhaled toxic materials, trauma, or medical procedures. Substantial or repeated airway epithelial injury can lead to dysregulated intrinsic repair pathways and aberrant tissue remodeling that can lead to dysfunctional airway epithelium. While disruption in the epithelial integrity is directly linked to degraded epithelial barrier function, the correlation between the structure and function of the airway epithelium remains elusive. In this study, we quantified the impact of acutely induced airway epithelium injury on disruption of the epithelial barrier functions. By monitoring alternation of the flow motions and tissue bioimpedance at local injury site, degradation of the epithelial functions, including mucociliary clearance and tight/adherens junction formation, were accurately determined with a high spatiotemporal resolution. Computational models that can simulate and predict the disruption of the mucociliary flow and airway tissue bioimpedance have been generated to assist interpretation of the experimental results. Collectively, findings of this study advance our knowledge of the structure–function relationships of the airway epithelium that can promote development of efficient and accurate diagnosis of airway tissue injury.

The importance of resources for balancing electricity supply and demand is increasing with the decentralization of power systems; the role of demand response is being emphasized to effectively deal with the volatility of renewable energy. In this study, a model to participate in the electricity market, especially energy and demand response, utilizing demand response resources by compensating for the uncertainty of renewable energy products is proposed. The probabilistic distribution of photovoltaic generation, derived based on stochastic programming, was used as a framework for solving the optimization problem by reflecting the uncertainty of photovoltaic generation. Moreover, a demand response modelling approach to enhance flexibility was developed by estimating the maximum potential demand response capacity in an industrial load. The output of these models was used to derive an optimal operational strategy to participate in the day-ahead market. The simulated Korean electricity market results confirmed that the virtual power plant aggregator’s profits increased when using the suggested strategy to utilizing demand response resources.

Under the carbon-neutral environment, the number of renewable power sources needs to be drastically increased. To respond to the large variability derived from renewable power sources, potential flexible resources have been established and researched. Among these, securing flexibility by using demand is achieved through demand response. For this purpose, it is helpful to identify flexumers—consumers with flexibility—for each player involved in the demand response. To identify the characteristics of flexumers among the demand consumers, we propose a method to classify the characteristics of flexumers into four groups based on power consumption data: price responsivity score, consistency score, flexible amount, and response time score. To verify the effectiveness of the proposed classification, the test system was evaluated with the power-consumption data from 19 companies in 11 industries. One company in the steel industry scored remarkably high in terms of a flexible amount. Overall, companies in the energy, chemical, material, filter and cement industries relatively showed characteristics suitable to flexumers. The suitability for flexumer application was quantitatively compared between industries, and other implications included the scope of criteria application and the direction of formula improvement. With the electrification of other industries, sector coupling, and the digitization of the power industry, the identification of flexumers in demand will significantly alter the plans for securing power-system flexibility. Therefore, the proposed flexumer characteristic formulas can contribute to the advancement of empirical data-based power-industry modeling by classifying resources with flexumer characteristics among the demand agents in the power system model.

In this study, the thermodynamic performance of a ventilated brake disc was improved by securing structural stability and verified through bench experiments. A brake disc is a braking device that decelerates a vehicle or stops it, and the disc should maintain a reliable braking force. The temperature rise on the disc surface has the greatest effect on the braking force. In recent years, many studies have been conducted on the shape of the disc in order to secure stable braking force and heat dissipation at the same time. However, as the disc surface is processed further, it becomes more difficult to have stable braking force, although the heat dissipation property is improved. Therefore, in this study, disc shapes were designed to improve heat dissipation performance while maintaining structural performance. The stress and temperature distribution were analyzed using ANSYS and optimal design of disc shapes was performed through PIAnO. In addition, to compare and verify the initial model and the optimized model, a prototype was fabricated to judge the feasibility of the optimization using a dynamometer. It can be expected that the heat dissipation performance and driving safety can be improved by using new brake discs.

Abstract Pulmonary air leak is the most common complication of lung surgery, with air leaks that persist longer than 5 days representing a major source of post‐surgery morbidity. Clinical management of air leaks is challenging due to limited methods to precisely locate and assess leaks. Here, we present a sound‐guided methodology that enables rapid quantitative assessment and precise localization of air leaks by analyzing the distinct sounds generated as the air escapes through defective lung tissue. Air leaks often present after lung surgery due to loss of tissue integrity at or near a staple line. Accordingly, we investigated air leak sounds from a focal pleural defect in a rat model and from a staple line failure in a clinically relevant swine model to demonstrate the high sensitivity and translational potential of this approach. In rat and swine models of free‐flowing air leak under positive pressure ventilation with intrapleural microphone 1 cm from the lung surface, we identified that: (a) pulmonary air leaks generate sounds that contain distinct harmonic series, (b) acoustic characteristics of air leak sounds can be used to classify leak severity, and (c) precise location of the air leak can be determined with high resolution (within 1 cm) by mapping the sound loudness level across the lung surface. Our findings suggest that sound‐guided assessment and localization of pulmonary air leaks could serve as a diagnostic tool to inform air leak detection and treatment strategies during video‐assisted thoracoscopic surgery (VATS) or thoracotomy procedures.

Summary: Predicting colorectal cancer recurrence after tumor resection is crucial because it promotes the administration of proper subsequent treatment or management to improve the clinical outcomes of patients. Several clinical or molecular factors, including tumor stage, metastasis, and microsatellite instability status, have been used to assess the risk of recurrence, although their predictive ability is limited. Here, we predicted colorectal cancer recurrence based on cellular deconvolution of bulk tumors into two distinct immune cell states: cancer-associated (tumor-infiltrating immune cell-like) and noncancer-associated (peripheral blood mononuclear cell-like). Prediction model performed significantly better when immune cells were deconvoluted into two states rather than a single state, suggesting that the difference in cancer recurrence was better explained by distinct states of immune cells. It indicates the importance of distinguishing immune cell states using cellular deconvolution to improve the prediction of colorectal cancer recurrence.

Pseudopleuronectes herzensteini belonging to Pleuronectiformes (family Pleuronectidae) is important in the fishery industry. However, the molecular biology of this valuable fish has hardly been reported. Thus, here we report the complete mitochondrial genome of P. herzensteini. The mitochondrial DNA (mtDNA) of P. herzensteini is 16,719 bp long and contains 13 mitochondrial protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes, and a putative control region between tRNA-P and tRNA-F distinguished by a single short noncoding region. Phylogenetic analysis using PCGs confirmed that this mtDNA sequence belongs to the family Pleuronectidae. This is the first study reporting the complete mitochondrial genome sequence of P. herzensteini.

Providing personalized product recommendations in offline retail stores, especially small-format offline retail businesses such as convenience stores, poses a great challenge. To address this issue, this study aimed to find a solution by shifting the perspective on recommendation methods and altering the target of recommendations. In this study, recommending products was defined as suggesting products that should be introduced and displayed within the store. This recommendation system proposes products that individual stores have not yet introduced but are anticipated to be purchased by customers. Building upon this, we developed a store-based collaborative filtering recommendation system. Furthermore, various rules and logic pertinent to store operations and business considerations for convenience stores were integrated to implement this recommendation system. The accuracy and effectiveness of the system were demonstrated through its application in actual convenience stores. Results from the pilot implementation of the system showed that 88% of the newly recommended products in individual stores were sold within a week, and the sales revenue was 1.75 times higher than the average sales of those products across the entire stores. Survey results on business owners’ satisfaction yielded a score of 4.2 out of 5, indicating a high level of contentment. This research holds significance in extending the scope of personalized recommendation studies from primarily online platforms to offline retail businesses such as convenience stores. The study also suggests avenues for future research to address some of the identified limitations.

Abstract Previous studies suggested that genetic, environmental factors and their interactions could affect body fat mass (BFM). However, studies describing these effects were performed at a single time point in a population. In this study, we investigated the interaction between genetic and environmental factors in affecting BFM and implicate the healthcare utilization of lifestyle modifications from a personalized and genomic perspective. We examined how nutritional intake or physical activity changes in the individuals affect BFM concerning the genetic composition. We conducted an observational study including 259 adult participants with single nucleotide polymorphism (SNP) genotyping and longitudinal lifestyle monitoring, including food consumption and physical activities, by following lifestyle modification guidance. The participants’ lifelog data on exercise and diet were collected through a wearable device for 3 months. Moreover, we measured anthropometric and serologic markers to monitor their potential changes through lifestyle modification. We examined the influence of genetic composition on body fat reduction induced by lifestyle changes using genetic risk scores (GRSs) of three phenotypes: GRS-carbohydrate (GRS-C), GRS-fat (GRS-F), and GRS-exercise (GRS-E). Our results showed that lifestyle modifications affected BFM more significantly in the high GRS class compared to the low GRS class, indicating the role of genetic factors affecting the efficiency of the lifestyle modification-induced BFM changes. Interestingly, the influence of exercise modification in the low GRS class with active lifestyle change was lower than that in the high GRS class with inactive lifestyle change (P = 0.022), suggesting the implication of genetic factors for efficient body fat control.

The great interest in developing emerging zinc-ion capacitors (ZIC) for energy storage applications is due to their inexpensiveness and the future necessity for hybrid electrical energy storage devices. The Zn-ion hybrid capacitor device was assembled using boron (B)-doped reduced graphene oxide (B-RGO) material, which acts as the cathode, and pure zinc metal as an anode. This research work aims to study the influence of B-doped reduced graphene oxide (B-RGO) with Aloe vera gel as an electrolyte. The reduced graphene oxide (RGO) and B-RGO electrode active materials were confirmed through X-ray diffraction (XRD), RAMAN, Fourier transformation infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM) and field emission-transmission electron microscopy (FE-TEM) analysis. The surface morphological images reveal that a few-layered nanostructure B-RGO was used in the Zn-ion hybrid capacitor device. The electrochemical performance of the Zn-ion hybrid capacitor was evaluated through cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) measurements, with a wide active potential range of 0–2 V versus Zn/Zn+. The mixture composition of Aloe vera extract and 1M ZnSO4 electrolyte generated a stable voltage and exhibited good capacitive behavior. The fabricated ZIC coin cell device with the Aloe vera gel semi-gel electrolyte containing ZnSO4 demonstrated improved Zn+ ionic exchange and storage efficiency. Moreover, the B-RGO electrode active material exhibited excellent cycle stability. The simple one-step electrochemical technique is the most suitable process for boron doping into graphene nanosheets for future energy storage applications.

A monopost seat is a novel, lightweight seat developed to utilize most of the interior space of vehicles. The space under the seat can be utilized by inserting a monopost columnar structure between a monopost seat rail and the floorboard. This design increases the perceived spaciousness of the vehicle and imparts passengers with a higher degree of freedom, because the seats can be adjusted more easily than standard seats. Meeting these requirements will require the seats to be sufficiently strong and sturdy in order to maintain passenger safety. Compared to traditional seats, it is more likely that a monopost seat will shift under the mass of the passenger, and these seats are more vulnerable to external vehicle collisions. Passenger safety is further compromised if an operational function is added. Therefore, further research on monopost seats is required. This study performed quasi-static and dynamic simulations to determine if the attachment of monopost seats to a vehicle meets international safety requirements in collision events. With a focus on clarifying the dynamic simulation process, the outcomes of quasi-static simulations were compared with the results obtained from dynamic simulations.

Abstract Background Biliary tract infection with the carcinogenic human liver fluke, Clonorchis sinensis, provokes chronic inflammation, epithelial hyperplasia, periductal fibrosis, and even cholangiocarcinoma. Complications are proportional to the intensity and duration of the infection. In addition to mechanical irritation of the biliary epithelia from worms, their excretory-secretory products (ESPs) cause chemical irritation, which leads to inflammation, proliferation, and free radical generation. Methods A three-dimensional in vitro cholangiocyte spheroid culture model was established, followed by ESP treatment. This allowed us to examine the intrinsic pathological mechanisms of clonorchiasis via the imitation of prolonged and repetitive in vivo infection. Results Microarray and RNA-Seq analysis revealed that ESP-treated cholangiocyte H69 spheroids displayed global changes in gene expression compared to untreated spheroids. In ESP-treated H69 spheroids, 185 and 63 probes were found to be significantly upregulated and downregulated, respectively, corresponding to 209 genes (p 2). RNA-Seq was performed for the validation of the microarray results, and the gene expression patterns in both transcriptome platforms were well matched for 209 significant genes. Gene ontology analysis demonstrated that differentially expressed genes were mainly classified into immune system processes, the extracellular region, and the extracellular matrix. Among the upregulated genes, four genes (XAF1, TRIM22, CXCL10, and BST2) were selected for confirmation using quantitative RT-PCR, resulting in 100% similar expression patterns in microarray and RNA-Seq. Conclusions These findings broaden our understanding of the pathological pathways of liver fluke-associated hepatobiliary disorders and suggest a novel therapeutic strategy for this infectious cancer. Graphic abstract

The vehicle front-end module (FEM) is an integrated system in which major modules are assembled in the front of the vehicle. Among the FEM components, a carrier occupies the largest volume and weight. In recent years, the requirements of a carrier are increasing due to the diversification of vehicle size, enlargement of headlight, and so on. So, recent requirements are difficult to satisfy with the existing design. Therefore, this study was attempted to solve the current problems by applying only plastic, not the existing hybrid type, to the most important Member-radiator Support Upper (MRSU) of the carrier. As a process, topology optimization was performed using Altair’s Optistruct, thereby implementing a new concept of MRSU. In addition, the strength analysis was conducted using ABAQUS of Simulia. An initial model and an optimized model were compared and verified to determine the validity of optimization. After that, a prototype of carrier was manufactured and the final verification was conducted through HLR test. As a result, the strength and weight of the carrier were improved by about 24% and 15% respectively. In addition, the waste-generating process was improved, resulting in a development time reduction of approximately 32%.

Abstract Alzheimer’s disease (AD) is mainly characterized by the deposition of extracellular amyloid plaques and intracellular accumulation of neurofibrillary tangles (NFTs). While the recent 5xFAD AD mouse model exhibits many AD-related phenotypes and a relatively early and aggressive amyloid β production, it does not show NFTs. Here, we developed and evaluated a novel AD mouse model (6xTg-AD, 6xTg) by crossbreeding 5xFAD mice with mice expressing mutant (P301L) tau protein (MAPT). Through behavioral and histopathological tests, we analyzed cognitive changes and neuropathology in 6xTg mice compared to their respective parental strains according to age. Spatial memory deficits occurred in 6xTg mice at 2 months of age, earlier than they occurred in 5xFAD mice. Histopathological data revealed aggressive Aβ42 and p-tau accumulation in 6xTg mice. Microglial activation occurred in the cortex and hippocampus of 6xTg mice beginning at 2 months. In 6xTg model mice, the synaptic loss was observed in the cortex from 4 months of age and in the hippocampus from 6 months of age, and neuronal loss appeared in the cortex from 4 months of age and in the hippocampus 6 months of age, earlier than it is observed in the 5xFAD and JNPL3 models. These results showed that each pathological symptom appeared much faster than in their parental animal models. In conclusion, these novel 6xTg-AD mice might be an advanced animal model for studying AD, representing a promising approach to developing effective therapy.

Abstract The number of young adult patients with major depression, one of the most common mental disorders, is gradually increasing in modern society. Stressful experiences in early life are considered one of the risk factors for chronic depressive symptoms, along with an abnormal inflammatory response in later life. Although increased inflammatory activity has been identified in patients with depression, the cause of long-lasting depressive states is still unclear. To identify the effects of cumulative mild stress in brain development periods, we generated a young adult depression mouse model exposed to cumulative mild stress (CPMS; cumulative mild prenatal stress, mild maternal separation, and mild social defeat) to mimic early life adversities. CPMS mice exhibited more long-lasting anxiety and depression-like behaviors than groups exposed to single or double combinations of mild stress in young adult age. Using the molecular works, we found that inflammatory cytokines, especially interleukin (IL)-17, upregulated microglial activation in the hippocampus, amygdala, and prefrontal cortex of CPMS mice. In the brains of CPMS mice, we also identified changes in the T helper (Th)-17 cell population as well as differentiation. Finally, anti-IL-17 treatment rescued anxiety and depression-like behavior in CPMS mice. In conclusion, we found that cumulative mild stress promoted long-lasting depressive symptoms in CPMS mice through the upregulation of IL-17. We suggest that the CPMS model may be useful to study young adult depression and expect that IL-17 may be an important therapeutic target for depression in young adults.

Neoadjuvant chemotherapy is a therapeutic option for the treatment of breast cancer. Here, the authors characterize changes in the gene expression profiles and immune microenvironment in serial breast cancer biopsies taken before, during and after neoadjuvant chemotherapy.

Abstract Background To analyze mean corneal powers and astigmatisms on anterior, posterior, and total cornea in patients with keratoconus as calculated according to various keratometric measurements using a Scheimpflug camera. Methods We examined the left eyes of 64 patients (41 males and 23 females; mean age 29.94 ± 6.63 years) with keratoconus. We measured simulated K (Sim-K), posterior K, true net power (TNP) and four types of total corneal refractive powers (TCRP). We then used the obtained values to analyze mean K, and corneal astigmatism. TCRP were measured at 2.0 ~ 5.0 mm. Results Mean corneal powers from Sim K, posterior K, and TNP were 49.12 ± 3.99, − 7.39 ± 0.79, and 47.78 ± 4.09 diopters, respectively. For TCRP centered on the pupil, mean K tended to decrease with measurement area (all p

Background A single institution retrospective analysis of 124 non‐small cell lung carcinoma (NSCLC) patients was performed to identify whether disease‐free survival (DFS) achieves incremental values when radiomic and genomic data are combined with clinical information. Methods Using the least absolute shrinkage and selection operator (LASSO) Cox regression method, radiomic and genetic features were reduced in number for selection of the most useful prognostic feature. We created four models using only baseline clinical data, clinical data with selected genetic features, clinical data with selected radiomic features, and clinical data with selected genetic and radiomic features together. Multivariate Cox proportional hazards analysis was performed to determine predictors of DFS. Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for DFS prediction by four constructed models at the five‐year time point. Results On precontrast scan, improved discrimination performance was obtained in a merging of selected radiomics and genetics (AUC = 0.8638), compared with clinical data only (AUC = 0.7990), selected genetic features (AUC = 0.8497), and selected radiomic features (AUC = 0.8355). On post‐contrast scan, discrimination performance was improved (AUC = 0.8672) compared with the clinical variables (AUC = 0.7913), and selected genetic features (AUC = 0.8376) and selected radiomic features (AUC = 0.8399) were considered. Conclusions The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating clinicopathologic model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone. Key points Significant findings of the study Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for disease‐free survival (DFS). The discriminative performance for DFS was better when combining radiomic and genetic features compared to clinical data only, selected genetic features, and selected radiomic features. What this study adds The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating a clinicopathological model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.