Jpx RNA regulates CTCF anchor site selection and formation of chromosome loops.

Chromosome loops shift dynamically during development, homeostasis, and disease. CCCTC-binding factor (CTCF) is known to anchor loops and construct 3D genomes, but how anchor sites are selected is not yet understood. Here, we unveil Jpx RNA as a determinant of anchor selectivity. Jpx RNA targets thousands of genomic sites, preferentially binding promoters of active genes. Depleting Jpx RNA causes ectopic CTCF binding, massive shifts in chromosome looping, and downregulation of >700 Jpx target genes. Without Jpx, thousands of lost loops are replaced by de novo loops anchored by ectopic CTCF sites. Although Jpx controls CTCF binding on a genome-wide basis, it acts selectively at the subset of developmentally sensitive CTCF sites. Specifically, Jpx targets low-affinity CTCF motifs and displaces CTCF protein through competitive inhibition. We conclude that Jpx acts as a CTCF release factor and shapes the 3D genome by regulating anchor site usage.

SMCHD1 Merges Chromosome Compartments and Assists Formation of Super-Structures on the Inactive X.

Mammalian chromosomes are partitioned into A/B compartments and topologically associated domains (TADs). The inactive X (Xi) chromosome, however, adopts a distinct conformation without evident compartments or TADs. Here, through exploration of an architectural protein, structural-maintenance-of-chromosomes hinge domain containing 1 (SMCHD1), we probe how the Xi is reconfigured during X chromosome inactivation. A/B compartments are first fused into "S1" and "S2" compartments, coinciding with Xist spreading into gene-rich domains. SMCHD1 then binds S1/S2 compartments and merges them to create a compartment-less architecture. Contrary to current views, TADs remain on the Xi but in an attenuated state. Ablating SMCHD1 results in a persistent S1/S2 organization and strengthening of TADs. Furthermore, loss of SMCHD1 causes regional defects in Xist spreading and erosion of heterochromatic silencing. We present a stepwise model for Xi folding, where SMCHD1 attenuates a hidden layer of Xi architecture to facilitate Xist spreading.

TERRA RNA Antagonizes ATRX and Protects Telomeres.

Through an integration of genomic and proteomic approaches to advance understanding of long noncoding RNAs, we investigate the function of the telomeric transcript, TERRA. By identifying thousands of TERRA target sites in the mouse genome, we demonstrate that TERRA can bind both in cis to telomeres and in trans to genic targets. We then define a large network of interacting proteins, including epigenetic factors, telomeric proteins, and the RNA helicase, ATRX. TERRA and ATRX share hundreds of target genes and are functionally antagonistic at these loci: whereas TERRA activates, ATRX represses gene expression. At telomeres, TERRA competes with telomeric DNA for ATRX binding, suppresses ATRX localization, and ensures telomeric stability. Depleting TERRA increases telomerase activity and induces telomeric pathologies, including formation of telomere-induced DNA damage foci and loss or duplication of telomeric sequences. We conclude that TERRA functions as an epigenomic modulator in trans and as an essential regulator of telomeres in cis.

EzBioCloud: a genome-driven database and platform for microbiome identification and discovery.

With the continued evolution of DNA sequencing technologies, the role of genome sequence data has become more integral in the classification and identification of Bacteria and Archaea. Six years after introducing EzBioCloud, an integrated platform representing the taxonomic hierarchy of Bacteria and Archaea through quality-controlled 16S rRNA gene and genome sequences, we present an updated version, that further refines and expands its capabilities. The current update recognizes the growing need for accurate taxonomic information as defining a species increasingly relies on genome sequence comparisons. We also incorporated an advanced strategy for addressing underrepresented or less studied lineages, bolstering the comprehensiveness and accuracy of our database. Our rigorous quality control protocols remain, where whole-genome assemblies from the NCBI Assembly Database undergo stringent screening to remove low-quality sequence data. These are then passed through our enhanced identification bioinformatics pipeline which initiates a 16S rRNA gene similarity search and then calculates the average nucleotide identity (ANI). For genome sequences lacking a 16S rRNA sequence and without a closely related genomic representative for ANI calculation, we apply a different ANI approach using bacterial core genes for improved taxonomic placement (core gene ANI, cgANI). Because of the increase in genome sequences available in NCBI and our newly introduced cgANI method, EzBioCloud now encompasses a total of 109 835 species, of which 21 964 have validly published names. 47 896 are candidate species identified either through 16S rRNA sequence similarity (phylotypes) or through whole genome ANI (genomospecies), and the remaining 39 975 were positioned in the taxonomic tree by cgANI (species clusters). Our EzBioCloud database is accessible at www.ezbiocloud.net/db.

Screening and purification of antimicrobial materials from coelomic fluid of sea urchin, Heliocidaris crassispina.

Marine organisms, such as sea urchins like Heliocidaris crassispina, produce bioactive substances with antimicrobial activity to protect themselves from the high density of microorganisms in their habitats. One such substance, Echinochrome A (Ech A), has been isolated from various sea urchins' shells and spines using strong acidic solutions and organic solvents. Ech A, however, has not been reported from the coelomic fluid of H. crassispina. In this study, we report the antimicrobial activity of H. crassispina coelomic fluid extract against various microbes, evaluating its potential for purifying potent antimicrobial materials. Upon confirming the extract as a promising source of antimicrobial materials, we isolated antimicrobial compounds from the extract. A series of HPLC steps were taken to purify antimicrobial materials from the H. crassispina coelomic fluid extract, resulting in the isolation of two single absorbance peaks showing antimicrobial activity against Staphylococcus aureus. One peak consisted of a single antimicrobial compound with a molecular weight (MW) corresponding to Ech A, while the other peak comprised five MWs inferred to be those of Ech A and its oxidative products. The elution of Ech A in two separate peaks may be attributable to the presence of Ech A's isomer, as reported in several previous studies. The use of the environmentally friendly extraction method in procurement of Ech A from the coelomic fluid would contribute to the implementation of risk-reducing extraction method for researchers studying Ech A from sea urchins.

Gut microbial signatures in clinically stable ulcerative colitis according to the mucosal state and associated symptoms.

BACKGROUND AND AIM: The gut microbiome of patients with clinically stable ulcerative colitis (UC) differs from that of healthy individuals depending on the state of the colonic mucosa, especially with or without advanced scarring; however, the underlying mechanism is unclear. Therefore, this study examined the gut microbiome compositional signatures in patients with significant mucosal scarring and UC-related symptoms. METHODS: Stool samples for gut microbiome analysis were prospectively collected from 57 patients with clinically stable UC between January 1 and December 31, 2022. Data from 57 individuals without inflammatory bowel disease (non-IBD) paired by age and sex were selected from our previous study as the control group. The fecal samples were subjected to 16S rRNA gene sequencing. Associations between gut microbiome profiles and clinical or colonoscopic assessments were examined using diversity and differential abundance analyses. RESULTS: Gut microbiome compositions between the patients with clinically stable UC and non-IBD controls differed significantly. Furthermore, gut microbiome compositions varied between the preserved and altered mucosa groups identified based on mucosal changes in the UC group. Differential abundance test of patients with UC for symptomatic remission based on stool frequency from the two-item patient-reported outcome identified several overlapping taxa specified as gut microbiome signatures, including the Enterobacteriaceae unknown genera (Enterobacteriaceae_g), Klebsiella, and several Lachnospiraceae spp. both in mucosal and symptom change analyses. CONCLUSIONS: The gut microbiome can change with mucosal changes, even in clinically stable UC, and some gut microbial signatures may explain the symptom manifestations in patients with UC showing significant mucosal changes.

A history of stereotactic radiosurgery may predict failure of procedure following percutaneous glycerol rhizotomy for trigeminal neuralgia.

BACKGROUND: Both stereotactic radiosurgery (SRS) and percutaneous glycerol rhizotomy are excellent options to treat TN in patients unable to proceed with microvascular decompression. However, the influence of prior SRS on pain outcomes following rhizotomy is not well understood. METHODS: We retrospectively reviewed all patients undergoing percutaneous rhizotomy at our institution from 2011 to 2022. Only patients undergoing percutaneous glycerol rhizotomy following SRS (SRS-rhizotomy) or those undergoing primary glycerol rhizotomy were considered. We collected basic demographic, clinical, and pain characteristics for each patient. Additionally, we characterized pain presentation and perioperative complications. Immediate failure of procedure was defined as presence of TN pain symptoms within 1-week of surgery, and short-term failure was defined as presence of TN pain symptoms within 3-months of surgery. A multivariate logistic regression model was used to evaluate the relationship of a history SRS and failure of procedure following percutaneous glycerol rhizotomy. RESULTS: Of all patients reviewed, 30 had a history of SRS prior to glycerol rhizotomy whereas 371 underwent primary percutaneous glycerol rhizotomy. Patients with a history of SRS were more likely to endorse V3 pain symptoms, p = 0.01. Additionally, patients with a history of SRS demonstrated higher preoperative BNI pain scores, p = 0.01. Patients with a history of SRS were more likely to endorse preoperative numbness, p < 0.0001. A history of SRS was independently associated with immediate failure [OR = 5.44 (2.06-13.8), p < 0.001] and short-term failure of glycerol rhizotomy [OR = 2.41 (1.07-5.53), p = 0.03]. Additionally, increasing age was found to be associated with lower odds of short-term failure of glycerol rhizotomy [OR = 0.98 (0.97-1.00), p = 0.01] CONCLUSIONS: A history of SRS may increase the risk of immediate and short-term failure following percutaneous glycerol rhizotomy. These results may be of use to patients who are poor surgical candidates and require multiple noninvasive/minimally invasive options to effectively manage their pain.

Does the Sequence of Bimaxillary Orthognathic Surgery Affect Accuracy in Skeletal Class III Patients?

BACKGROUND: It is necessary to determine whether the sequence of maxillary and mandibular surgeries in bimaxillary orthognathic surgery affects the accuracy of surgical outcomes. PURPOSE: The study aimed to measure and compare the accuracy among patients who underwent maxilla-first versus mandible-first bimaxillary surgery to correct a class III skeletal pattern. STUDY DESIGN, SETTING, SAMPLE: This retrospective cohort study included consecutive patients treated by a single surgeon at one center using Le Fort I and bilateral sagittal split osteotomy surgery. Exclusions included patients scheduled for one-jaw or maxilla-segmental surgery and those with craniofacial syndromes, such as clefts. PREDICTOR VARIABLE: The predictor variable was operative sequence for bimaxillary operations, divided into maxilla- or mandible-first groups. OUTCOME VARIABLE: The outcome variable was accuracy, measured using linear discrepancies between landmarks in the virtual plan and actual operative outcomes. The measurement of linear discrepancy that was closer to 0 was considered the more accurate result. COVARIATES: Sex, age, maxilla sagittal rotation degree, amount of posterior maxilla impaction, mandibular autorotation (°), and intermediate splint thickness (mm) were the covariates. ANALYSES: Statistical analysis was performed using Student's t-test and Pearson's correlation, with statistical significance set at P < .05. RESULTS: The sample comprised 60 patients with a mean age of 22.8 ± 3.7 years, of whom 36 (60%) were male. In the maxilla-first group, there were 30 subjects (60% male; mean age: 23.1 ± 4.2 years), with a mean mandibular autorotation of 0.41° (range: 0°-2.5°). The mandible-first group comprised 30 patients (60% male; mean age: 22.6 ± 3.3 years), with a mean mandibular autorotation of 5.46° (range: 1.9°-9.2°). The linear discrepancies for all landmarks did not significantly differ between mandible- and maxilla-first groups (P > .18). The mean three-dimensional discrepancies for all landmarks in maxilla-first group was 1.23 ± 0.5 mm and 1.23 ± 0.33 mm in mandible-first group, with no significant difference observed between the groups (P > .98). The amount of mandibular autorotation for intermediate splint application showed no significant correlation with the linear discrepancies (P > .58). CONCLUSION AND RELEVANCE: In patients with skeletal class III malocclusion, mandible-first surgery in bimaxillary orthognathic surgery demonstrates accurate outcomes comparable to maxilla-first surgery.

Association between endocrine-disrupting chemical mixtures and non-alcoholic fatty liver disease with metabolic syndrome as a mediator among adults: A population-based study in Korea.

Endocrine-disrupting chemicals (EDCs) may play a role in non-alcoholic fatty liver disease (NAFLD); however, studies on the combined effects of EDC mixtures on NAFLD development are limited. Here, we explored the association between exposure to EDC mixtures and NAFLD and investigated the potential mediating role of metabolic syndrome (MetS). We included participants from the Korean National Environmental Health Survey Cycle 4 (2018-2020) and quantified the urinary concentrations of various EDCs-eight phthalate metabolites, three phenols, one antibacterial compound, four parabens, four polycyclic aromatic hydrocarbons, and one pyrethroid pesticide metabolite-as well as serum concentrations of five perfluorinated compounds (PFCs). NAFLD was defined as a hepatic steatosis index (HSI) ≥36 or a fatty liver index (FLI) ≥60. Weighted quantile sum (WQS) regression was employed to evaluate the associations between EDC mixtures and the risk of MetS or NAFLD. Causal mediation analysis was conducted to explore the potential mediating effect of MetS on the association between mixtures of EDCs and NAFLD risk. All estimates were adjusted for age, sex, educational level, physical activity, smoking status, involuntary smoking, and drinking habits. A total of 2942 adults were included in the analysis. Moderate-to-high positive correlations were identified between phthalate metabolites and PFCs. Higher WQS scores were associated with an elevated risk of MetS and NAFLD. The sex-stratified WQS regression model showed that the interactions between the WQS index and sex were significant for MetS and NAFLD. According to the causal mediation analysis, both the direct and indirect effects of EDC mixtures on NAFLD, with MetS as a mediator, were significant in females. Collectively, these findings highlight the need for interventions that could address both EDC mixture exposure and metabolic status to effectively reduce the risks associated with NAFLD and its related complications.

Differential effects of digital media platforms on climate change risk information-sharing intention: A moderated mediation model.

This study analyzes the mechanisms through which risk messages about climate change lead to people's risk information-sharing intention, and how digital media platform type serves as a context that moderates those mechanisms. Our analysis is informed by the influence of presumed influence (IPI) model, and we adapt and expand that model in three ways. First, we apply the concept of perceived media reach to the context of digital media platforms, specifically news aggregators and social networking sites. Second, we integrate the two mediators of risk perception and presumed influence. Third, we examine potential moderating roles of digital media platforms in the IPI model. An online survey was conducted among 1000 South Korean adults, and a moderated mediation model (PROCESS Macro Model 59) generated the following results. (1) Perceived media reach was positively related to both mediators-risk perception and presumed influence. (2) By way of those two mediators, perceived reach significantly led to information-sharing intention. (3) Presumed influence, but not risk perception, was significantly related to information-sharing intention. (4) Digital media platforms moderated the relation between perceived reach and risk perception: the role of content-related risk perception was more pronounced in news aggregators, while the role of context-related presumed influence was greater in social networking sites. Theoretical and practical implications for risk communication are discussed.

Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems.

In the autonomous driving industry, there is a growing trend to employ long-wave infrared (LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even in extreme environments. Consequently, both industry and academia are actively researching contrast-enhancement techniques to improve the quality of LWIR-based thermal-imaging cameras. However, most research results only showcase experimental outcomes using mass-produced products that already incorporate contrast-enhancement techniques. Put differently, there is a lack of experimental data on contrast enhancement post-non-uniformity (NUC) and temperature compensation (TC) processes, which generate the images seen in the final products. To bridge this gap, we propose a histogram equalization (HE)-based contrast enhancement method that incorporates a region-based clipping technique. Furthermore, we present experimental results on the images obtained after applying NUC and TC processes. We simultaneously conducted visual and qualitative performance evaluations on images acquired after NUC and TC processes. In the visual evaluation, it was confirmed that the proposed method improves image clarity and contrast ratio compared to conventional HE-based methods, even in challenging driving scenarios such as tunnels. In the qualitative evaluation, the proposed method demonstrated upper-middle-class rankings in both image quality and processing speed metrics. Therefore, our proposed method proves to be effective for the essential contrast enhancement process in LWIR-based uncooled thermal-imaging cameras intended for autonomous driving platforms.

Anti-Obesity Effects of GABA in C57BL/6J Mice with High-Fat Diet-Induced Obesity and 3T3-L1 Adipocytes.

Obesity is the excessive accumulation of body fat resulting from impairment in energy balance mechanisms. In this study, we aimed to investigate the mechanism whereby GABA (γ-aminobutyric acid) prevents high-fat diet-induced obesity, and whether it induces lipolysis and browning in white adipose tissue (WAT), using high-fat diet (HFD)-fed obese mice and 3T3-L1 adipocytes. We demonstrated that GABA substantially inhibits the body mass gain of mice by suppressing adipogenesis and lipogenesis. Consistent with this result, histological analysis of WAT demonstrated that GABA decreases adipocyte size. Moreover, we show that GABA administration decreases fasting blood glucose and improves serum lipid profiles and hepatic lipogenesis in HFD-fed obese mice. Furthermore, Western blot and immunofluorescence analyses showed that GABA activates protein kinase A (PKA) signaling pathways that increase lipolysis and promote uncoupling protein 1 (UCP1)-mediated WAT browning. Overall, these results suggest that GABA exerts an anti-obesity effect via the regulation of lipid metabolism.

Molecular Self-Assembly and Adsorption Structure of 2,2'-Dipyrimidyl Disulfides on Au(111) Surfaces.

The effects of solution concentration and pH on the formation and surface structure of 2-pyrimidinethiolate (2PymS) self-assembled monolayers (SAMs) on Au(111) via the adsorption of 2,2'-dipyrimidyl disulfide (DPymDS) were examined using scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS). STM observations revealed that the formation and structural order of 2PymS SAMs were markedly influenced by the solution concentration and pH. 2PymS SAMs formed in a 0.01 mM ethanol solution were mainly composed of a more uniform and ordered phase compared with those formed in 0.001 mM or 1 mM solutions. SAMs formed in a 0.01 mM solution at pH 2 were composed of a fully disordered phase with many irregular and bright aggregates, whereas SAMs formed at pH 7 had small ordered domains and many bright islands. As the solution pH increased from pH 7 to pH 12, the surface morphology of 2PymS SAMs remarkably changed from small ordered domains to large ordered domains, which can be described as a (4√2 × 3)R51° packing structure. XPS measurements clearly showed that the adsorption of DPymDS on Au(111) resulted in the formation of 2PymS (thiolate) SAMs via the cleavage of the disulfide (S-S) bond in DPymDS, and most N atoms in the pyrimidine rings existed in the deprotonated form. The results herein will provide a new insight into the molecular self-assembly behaviors and adsorption structures of DPymDS molecules on Au(111) depending on solution concentration and pH.

Assessment of phthalate exposure at a fire site in Korean firefighters.

To determine phthalate exposure in 32 firefighters, the concentrations of urinary phthalate metabolites, immediately (exposure day) and three weeks (control day) after fire suppression, were compared. Mono-(2-ethyl-5-carboxypentyl) phthalate, mono-(2-ethyl-5-hydroxyhexyl) phthalate, mono-(2-ethyl-5-oxohexyl) phthalate, mono-n-butyl phthalate (MBP), mono-n-benzyl phthalate (MBzP), and total phthalates (∑phthalates) levels, and creatinine-adjusted levels of MBP, MBzP, and ∑phthalates were significantly higher on exposure day than on control day. Phthalate concentration was significantly higher in firefighters who performed the fire extinguishing tasks (geometric mean [GM], 149.9 µg/L) than in those who performed other tasks (GM 70.8 µg/L) (p = .012). The GM concentration of firefighters who were active ≤ 50 m from the fire was 119.0 µg/L, and 37.6 µg/L for those who were > 50 m away (p = .012). The GM concentration was significantly different (p = .039) in firefighters with subjective symptoms after fire suppression (151.9 µg/L) compared to those without symptoms (81.6 µg/L). This study showed that firefighters were exposed to phthalate.

Enhancing deep learning classification performance of tongue lesions in imbalanced data: mosaic-based soft labeling with curriculum learning.

BACKGROUND: Oral potentially malignant disorders (OPMDs) are associated with an increased risk of cancer of the oral cavity including the tongue. The early detection of oral cavity cancers and OPMDs is critical for reducing cancer-specific morbidity and mortality. Recently, there have been studies to apply the rapidly advancing technology of deep learning for diagnosing oral cavity cancer and OPMDs. However, several challenging issues such as class imbalance must be resolved to effectively train a deep learning model for medical imaging classification tasks. The aim of this study is to evaluate a new technique of artificial intelligence to improve the classification performance in an imbalanced tongue lesion dataset. METHODS: A total of 1,810 tongue images were used for the classification. The class-imbalanced dataset consisted of 372 instances of cancer, 141 instances of OPMDs, and 1,297 instances of noncancerous lesions. The EfficientNet model was used as the feature extraction model for classification. Mosaic data augmentation, soft labeling, and curriculum learning (CL) were employed to improve the classification performance of the convolutional neural network. RESULTS: Utilizing a mosaic-augmented dataset in conjunction with CL, the final model achieved an accuracy rate of 0.9444, surpassing conventional oversampling and weight balancing methods. The relative precision improvement rate for the minority class OPMD was 21.2%, while the relative [Formula: see text] score improvement rate of OPMD was 4.9%. CONCLUSIONS: The present study demonstrates that the integration of mosaic-based soft labeling and curriculum learning improves the classification performance of tongue lesions compared to previous methods, establishing a foundation for future research on effectively learning from imbalanced data.

NADP+ or CO2 reduction by frhAGB-encoded hydrogenase through interaction with formate dehydrogenase 3 in the hyperthermophilic archaeon Thermococcus onnurineus NA1.

IMPORTANCE: The strategy using structural homology with the help of structure prediction by AlphaFold was very successful in finding potential targets for the frhAGB-encoded hydrogenase of Thermococcus onnurineus NA1. The finding that the hydrogenase can interact with FdhB to reduce the cofactor NAD(P)+ is significant in that the enzyme can function to supply reducing equivalents, just as F420-reducing hydrogenases in methanogens use coenzyme F420 as an electron carrier. Additionally, it was identified that T. onnurineus NA1 could produce formate from H2 and CO2 by the concerted action of frhAGB-encoded hydrogenase and formate dehydrogenase Fdh3.

Glial cell proteome using targeted quantitative methods for potential multi-diagnostic biomarkers.

Glioblastoma is one of the most malignant primary brain cancer. Despite surgical resection with modern technology followed by chemo-radiation therapy with temozolomide, resistance to the treatment and recurrence is common due to its aggressive and infiltrating nature of the tumor with high proliferation index. The median survival time of the patients with glioblastomas is less than 15 months. Till now there has been no report of molecular target specific for glioblastomas. Early diagnosis and development of molecular target specific for glioblastomas are essential for longer survival of the patients with glioblastomas. Development of biomarkers specific for glioblastomas is most important for early diagnosis, estimation of the prognosis, and molecular target therapy of glioblastomas. To that end, in this study, we have conducted a comprehensive proteome study using primary cells and tissues from patients with glioblastoma. In the discovery stage, we have identified 7429 glioblastoma-specific proteins, where 476 proteins were quantitated using Tandem Mass Tag (TMT) method; 228 and 248 proteins showed up and down-regulated pattern, respectively. In the validation stage (20 selected target proteins), we developed quantitative targeted method (MRM: Multiple reaction monitoring) using stable isotope standards (SIS) peptide. In this study, five proteins (CCT3, PCMT1, TKT, TOMM34, UBA1) showed the significantly different protein levels (t-test: p value ≤ 0.05, AUC ≥ 0.7) between control and cancer groups and the result of multiplex assay using logistic regression showed the 5-marker panel showed better sensitivity (0.80 and 0.90), specificity (0.92 and 1.00), error rate (10 and 2%), and AUC value (0.94 and 0.98) than the best single marker (TOMM34) in primary cells and tissues, respectively. Although we acknowledge that the model requires further validation in a large sample size, the 5 protein marker panel can be used as baseline data for the discovery of novel biomarkers of the glioblastoma.

Extreme UV Resist Exhibiting Synergism between Chemical and Physical Crosslinking Mechanisms.

Carbon-fluorine bonds in fluorinated molecules can undergo homolytic cleavage reactions when electrons are injected, and the resulting radicals combine to form network structures characterized by reduced solubility. This crosslinking chemistry suggests a new category of patterning materials that function under electron beam (e-beam) and extreme ultraviolet (EUV) lithographic conditions. Although this chemistry enables the production of 50 nm or smaller-sized features of simple fluoroalkylated polymers, it is limited by the need for relatively large amounts of irradiation energy to achieve required solubility changes. Therefore, this study was undertaken to devise a sensitivity-enhancing strategy based on a synergistic combination of radical crosslinking and hydrogen-bonding interactions between highly fluoroalkylated copolymers. An alternating copolymer was synthesized using tert-butoxystyrene and a fluoroalkylated maleimide, the former of which produces active hydrogens through catalytic acidolysis reactions. When the polymer was blended with a catalytic amount of a photoacid generator and subjected to lithographic patterning tests under e-beam and EUV irradiation, the deprotection reactions of tert-butoxy moieties proceeded at room temperature and led to a solubility decrease. We presume the small number of hydroxyl moieties produced formed an intermolecular hydrogen-bonding network, which acted synergistically with the covalent crosslinks generated by C-F bonds. When 30 nm features of copolymer thin films were fabricated by EUV lithography, sensitivity was improved by 25-34% without significant deterioration of pattern quality, especially line-edge roughness. These results demonstrate that EUV resists with improved patterning capabilities can be achieved by combining catalytic acidolysis reactions and noncatalytic crosslinking chemistry.

Development and validation of an automatic classification algorithm for the diagnosis of Alzheimer's disease using a high-performance interpretable deep learning network.

OBJECTIVES: To develop and validate an automatic classification algorithm for diagnosing Alzheimer's disease (AD) or mild cognitive impairment (MCI). METHODS AND MATERIALS: This study evaluated a high-performance interpretable network algorithm (TabNet) and compared its performance with that of XGBoost, a widely used classifier. Brain segmentation was performed using a commercially approved software. TabNet and XGBoost were trained on the volumes or radiomics features of 102 segmented regions for classifying subjects into AD, MCI, or cognitively normal (CN) groups. The diagnostic performances of the two algorithms were compared using areas under the curves (AUCs). Additionally, 20 deep learning-based AD signature areas were investigated. RESULTS: Between December 2014 and March 2017, 161 AD, 153 MCI, and 306 CN cases were enrolled. Another 120 AD, 90 MCI, and 141 CN cases were included for the internal validation. Public datasets were used for external validation. TabNet with volume features had an AUC of 0.951 (95% confidence interval [CI], 0.947-0.955) for AD vs CN, which was similar to that of XGBoost (0.953 [95% CI, 0.951-0.955], p = 0.41). External validation revealed the similar performances of two classifiers using volume features (0.871 vs. 0.871, p = 0.86). Likewise, two algorithms showed similar performances with one another in classifying MCI. The addition of radiomics data did not improve the performance of TabNet. TabNet and XGBoost focused on the same 13/20 regions of interest, including the hippocampus, inferior lateral ventricle, and entorhinal cortex. CONCLUSIONS: TabNet shows high performance in AD classification and detailed interpretation of the selected regions. CLINICAL RELEVANCE STATEMENT: Using a high-performance interpretable deep learning network, the automatic classification algorithm assisted in accurate Alzheimer's disease detection using 3D T1-weighted brain MRI and detailed interpretation of the selected regions. KEY POINTS: • MR volumetry data revealed that TabNet had a high diagnostic performance in differentiating Alzheimer's disease (AD) from cognitive normal cases, which was comparable with that of XGBoost. • The addition of radiomics data to the volume data did not improve the diagnostic performance of TabNet. • Both TabNet and XGBoost selected the clinically meaningful regions of interest in AD, including the hippocampus, inferior lateral ventricle, and entorhinal cortex.

Role of quorum sensing and quorum quenching in anaerobic digestion: A scoping review.

Anaerobic digestion (AD) is a biological process that employs anaerobic microorganisms to degrade organic material, yielding biogas and biofertilizers. Understanding quorum sensing (QS) signaling in mixed microbial systems provides valuable insights into microbial behavior and functions. This review aims to examine recent studies on the roles of QS and QQ in the AD processes. A QS signal molecule, N-acyl homoserine lactone (AHL), induce the production of extraceluller polymers, promoting biofilm formation and bacterial aggregation, thereby the efficiency of AD process. QS-assisted granule formation fosters syntrophy between acetogens and methanogens, leading to increased organic removal and methane production. Specific AHLs were shown to be correlated with the abundance of hydrolytic bacteria and acidogens, further benefiting methane production. QQ was shown to effectively control membrane fouling in anaerobic membrane bioreactors, yet its impact on methane productivity remains unclear. This review shed lights on the existing literature gaps regarding the mechanisms of QS and QQ in AD systems, which will play a vital role in advancing AD applications in the future.