Newly developed reversible MAO-B inhibitor circumvents the shortcomings of irreversible inhibitors in Alzheimer's disease

Monoamine oxidase-B (MAO-B) has recently emerged as a potential therapeutic target for Alzheimer's disease (AD) because of its association with aberrant γ-aminobutyric acid (GABA) production in reactive astrocytes. Although short-term treatment with irreversible MAO-B inhibitors, such as selegiline, improves cognitive deficits in AD patients, long-term treatments have shown disappointing results. We show that prolonged treatment with selegiline fails to reduce aberrant astrocytic GABA levels and rescue memory impairment in APP/PS1 mice, an animal model of AD, because of increased activity in compensatory genes for a GABA-synthesizing enzyme, diamine oxidase (DAO). We have developed a potent, highly selective, and reversible MAO-B inhibitor, KDS2010 (IC50 = 7.6 nM; 12,500-fold selectivity over MAO-A), which overcomes the disadvantages of the irreversible MAO-B inhibitor. Long-term treatment with KDS2010 does not induce compensatory mechanisms, thereby significantly attenuating increased astrocytic GABA levels and astrogliosis, enhancing synaptic transmission, and rescuing learning and memory impairments in APP/PS1 mice.

Flexible elastomer patch with vertical silicon nanoneedles for intracellular and intratissue nanoinjection of biomolecules

Vertically ordered arrays of silicon nanoneedles (Si NNs), due to their nanoscale dimension and low cytotoxicity, could enable minimally invasive nanoinjection of biomolecules into living biological systems such as cells and tissues. Although production of these Si NNs on a bulk Si wafer has been achieved through standard nanofabrication technology, there exists a large mismatch at the interface between the rigid, flat, and opaque Si wafer and soft, curvilinear, and optically transparent biological systems. Here, we report a unique methodology that is capable of constructing vertically ordered Si NNs on a thin layer of elastomer patch to flexibly and transparently interface with biological systems. The resulting outcome provides important capabilities to form a mechanically elastic interface between Si NNs and biological systems, and simultaneously enables direct imaging of their real-time interactions under the transparent condition. We demonstrate its utility in intracellular, intradermal, and intramuscular nanoinjection of biomolecules into various kinds of biological cells and tissues at their length scales.

Correlations of the Gastric and Duodenal Microbiota with Histological, Endoscopic, and Symptomatic Gastritis

Mucosal inflammation is characterized by neutrophil and mononuclear cell infiltration. This study aimed to determine the gastric and duodenal microbiota associated with histological, endoscopic, and symptomatic gastritis. Dyspeptic adults who presented for evaluation were included. Subjects with either comorbidities or recent drug intake were excluded. Three endoscopic biopsies were obtained from the antrum, body, and duodenum. Next-generation sequencing for 16S ribosomal RNA V1⁻V2 hypervariable regions was performed. The correlation between the composition of microbiota and the degree of inflammatory cell infiltration, endoscopic findings, and Patient Assessment of Gastrointestinal Disorders Symptom Severity Index (PAGI-SYM) score was analyzed. In 98 included subjects, microbial communities in the antrum and body showed Bray⁻Curtis similarity; however, those in the duodenum showed dissimilarity. Histological and endoscopic gastritis was associated with the abundance of Helicobacter pylori and that of commensal bacteria in the stomach. The abundances of Variovorax paradoxus and Porphyromonas gingivalis were correlated with histological gastritis, but not with endoscopic or symptomatic gastritis. The total PAGI-SYM score showed a stronger correlation with the duodenal microbiota (Prevotella nanceiensis and Alloprevotella rava) than with the gastric microbiota (H. pylori, Neisseria elongate, and Corynebacterium segmentosum). Different correlations of the gastric and duodenal microbiota with histological, endoscopic, and symptomatic gastritis were observed for the first time at the species level. H. pylori-negative gastritis is not associated with endoscopic or symptomatic gastritis. Only H. pylori-induced endoscopic gastritis requires gastric cancer surveillance. Owing to the weak correlation with H. pylori, symptomatic gastritis should be assessed separately from histological and endoscopic gastritis.

Ultrahigh strength, modulus, and conductivity of graphitic fibers by macromolecular coalescence

Theoretical considerations suggest that the strength of carbon nanotube (CNT) fibers be exceptional; however, their mechanical performance values are much lower than the theoretical values. To achieve macroscopic fibers with ultrahigh performance, we developed a method to form multidimensional nanostructures by coalescence of individual nanotubes. The highly aligned wet-spun fibers of single- or double-walled nanotube bundles were graphitized to induce nanotube collapse and multi-inner walled structures. These advanced nanostructures formed a network of interconnected, close-packed graphitic domains. Their near-perfect alignment and high longitudinal crystallinity that increased the shear strength between CNTs while retaining notable flexibility. The resulting fibers have an exceptional combination of high tensile strength (6.57 GPa), modulus (629 GPa), thermal conductivity (482 W/m·K), and electrical conductivity (2.2 MS/m), thereby overcoming the limits associated with conventional synthetic fibers.

Ultrahigh-resolution scanning microwave impedance microscopy of moiré lattices and superstructures

Two-dimensional heterostructures composed of layers with slightly different lattice vectors exhibit new periodic structure known as moiré lattices, which, in turn, can support novel correlated and topological phenomena. Moreover, moiré superstructures can emerge from multiple misaligned moiré lattices or inhomogeneous strain distributions, offering additional degrees of freedom in tailoring electronic structure. High-resolution imaging of the moiré lattices and superstructures is critical for understanding the emerging physics. Here, we report the imaging of moiré lattices and superstructures in graphene-based samples under ambient conditions using an ultrahigh-resolution implementation of scanning microwave impedance microscopy. Although the probe tip has a gross radius of ~100 nm, spatial resolution better than 5 nm is achieved, which allows direct visualization of the structural details in moiré lattices and the composite super-moiré. We also demonstrate artificial synthesis of novel superstructures, including the Kagome moiré arising from the interplay between different layers.

Facile Interfacial Engineering of Mesoporous TiO2 for Low-Temperature Processed Perovskite Solar Cells

The mesoporous TiO2 nanoparticle-based scaffold structure is the best electron transport layer (ETL) for perovskite solar cells (PSCs) and is still used in most PSCs with optimal photovoltaic characteristics. However, the high sintering temperature of TiO2 nanoparticles required to remove binders from the TiO2 paste limits PSC application to flexible electronics. In this study, a simple interface modification process involving ethanol rinsing is developed to enhance the photovoltaic characteristics of low-temperature processed PSCs. This easy and fast technique could enable remarkable performance by PSCs by significantly increasing the fill factor and current density, leading to a power conversion efficiency more than four times that of untreated solar cells.

Evolutionary rewiring of regulatory networks contributes to phenotypic differences between human and mouse orthologous genes

Mouse models have been engineered to reveal the biological mechanisms of human diseases based on an assumption. The assumption is that orthologous genes underlie conserved phenotypes across species. However, genetically modified mouse orthologs of human genes do not often recapitulate human disease phenotypes which might be due to the molecular evolution of phenotypic differences across species from the time of the last common ancestor. Here, we systematically investigated the evolutionary divergence of regulatory relationships between transcription factors (TFs) and target genes in functional modules, and found that the rewiring of gene regulatory networks (GRNs) contributes to the phenotypic discrepancies that occur between humans and mice. We confirmed that the rewired regulatory networks of orthologous genes contain a higher proportion of species-specific regulatory elements. Additionally, we verified that the divergence of target gene expression levels, which was triggered by network rewiring, could lead to phenotypic differences. Taken together, a careful consideration of evolutionary divergence in regulatory networks could be a novel strategy to understand the failure or success of mouse models to mimic human diseases. To help interpret mouse phenotypes in human disease studies, we provide quantitative comparisons of gene expression profiles on our website (http://sbi.postech.ac.kr/w/RN).

Lack of early sensitivity and gradual emergence of native phoneme categories: A pattern from underrepresented language learners

Perceptual narrowing of speech perception supposes that young infants can discriminate most speech sounds early in life. During the second half of the first year, infants' phonetic sensitivity is attuned to their native phonology. However, supporting evidence for this pattern comes primarily from learners from a limited number of regions and languages. Very little evidence has accumulated on infants learning languages spoken in Asia, which accounts for most of the world's population. The present study examined the developmental trajectory of Korean-learning infants' sensitivity to a native stop contrast during the first year of life. The Korean language utilizes unusual voiceless three-way stop categories, requiring target categories to be derived from tight phonetic space. Further, two of these categories-lenis and aspirated-have undergone a diachronic change in recent decades as the primary acoustic cue for distinction has shifted among modern speakers. Consequently, the input distributions of these categories are mixed across speakers and speech styles, requiring learners to build flexible representations of target categories along these variations. The results showed that among the three age groups-4-6 months, 7-9 months, and 10-12 months-we tested, only 10-12-month-olds showed weak sensitivity to the two categories, suggesting that robust discrimination is not in place by the end of the first year. The study adds scarcely represented data, lending additional support for the lack of early sensitivity and prolonged emergence of native phonology that are inconsistent with learners of predominant studies and calls for more diverse samples to verify the generality of the typical perceptual narrowing pattern. RESEARCH HIGHLIGHTS: We investigated Korean-learning infants' developmental trajectory of native phoneme categories and whether they show the typical perceptual narrowing pattern. Robust discrimination did not appear until 12 months, suggesting that Korean infants' native phonology is not stabilized by the end of the first year. The prolonged emergence of sensitivity could be due to restricted phonetic space and input variations but suggests the possibility of a different developmental trajectory. The current study contributes scarcely represented Korean-learning infants' phonetic discrimination data to the speech development field.

Development of fricative sound perception in Korean infants: The role of language experience and infants' initial sensitivity

In this paper, we report data on the development of Korean infants' perception of a rare fricative phoneme distinction. Korean fricative consonants have received much interest in the linguistic community due to the language's distinct categorization of sounds. Unlike many fricative contrasts utilized in most of the world's languages, Korean fricatives (/s*/-/s/) are all voiceless. Moreover, compared with other sound categories, fricatives have received very little attention in the speech perception development field and no studies thus far have examined Korean infants' development of native phonology in this domain. Using a visual habituation paradigm, we tested 4‒6-month-old and 7‒9-month-old Korean infants on their abilities to discriminate the Korean fricative pair in the [a] vowel context, /s*a/-/sa/, which can be distinguished based on acoustic cues, such as the durations of aspiration and frication noise. Korean infants older than 7 months were able to reliably discriminate the fricative pair but younger infants did not show clear signs of such discrimination. These results add to the growing evidence that there are native sound contrasts infants cannot discriminate early on without a certain amount of language exposure, providing further data to help delineate the specific nature of early perceptual capacity.

Gold Nanorod Density-Dependent Label-Free Bacteria Sensing on a Flake-like 3D Graphene-Based Device by SERS

Surface-enhanced Raman spectroscopy (SERS) is an effective technique for biosensing, enabling label-free detection of biomolecules with enhanced sensitivity. There is a tremendous probability of signal failure in Raman frequencies because of the scattering of the Raman radiation in liquids, effective SERS improvement is required to reduce this issue when considering liquid specimens. We examined a liquid bacterial sample, investigating the electrostatic interactions of the bacterial samples with gold nanorods (AuNRs) and graphene. We established a voltage-gated 3D graphene functionalized with an AuNR-based device on the silicon substrate for SERS measurements when the applied voltage ranges from 0 to 3 V. Moreover, AuNRs density-susceptible bacterial sample analysis with varied concentrations of bacterial samples has also been described. Using bacterial SERS analysis, the bacterial components amide II (1555-1565 cm-1) and amide III (1250-1350 cm-1) have been discovered for both bacteria, Gram-positive, Listeria monocytogenes and Gram-negative, Salmonella typhi. Our fabricated device affords an interesting label-free, rapid, and reproducible bacterial sample analysis based on the density of the AuNRs when functionalizing flake-like 3D graphene, which can help facilitate label-free bacteria sensing platforms.

The relationship between resource abundance and insect herbivory on islands

We examined the relationship between resource abundance and the feeding activity of phytophagous insects on three common island plants. The aim was to investigate the correlation between phytophagous insects' abundance and availability of food and island geography. We collected 30,835 leaves from three tree species groups (Mallotus japonicus, Prunus species, and Quercus species) on 18 islands in southwest Korea. The number of plant resources for herbivores varied: the number of leaves per shoot was the highest in Mallotus, leaf weight and the water content per leaf was significantly lower in Quercus species. External feeding was higher for Prunus and Quercus species, whereas the internal feeding type was significantly higher for Quercus species. Geography (area and distance), elevation and food resource (elevation, number of plant species, and the forest cover rate) had a variable effect on phytophagous insects feeding activities: distance and the number of plant species were more explainable to the external feeding guild. In contrast, area and forest cover were more to the internal feeding guild.

Biological export production controls upper ocean calcium carbonate dissolution and CO2 buffer capacity

Marine biogenic calcium carbonate (CaCO3) cycles play a key role in ecosystems and in regulating the ocean's ability to absorb atmospheric carbon dioxide (CO2). However, the drivers and magnitude of CaCO3 cycling are not well understood, especially for the upper ocean. Here, we provide global-scale evidence that heterotrophic respiration in settling marine aggregates may produce localized undersaturated microenvironments in which CaCO3 particles rapidly dissolve, producing excess alkalinity in the upper ocean. In the deep ocean, dissolution of CaCO3 is primarily driven by conventional thermodynamics of CaCO3 solubility with reduced fluxes of CaCO3 burial to marine sediments beneath more corrosive North Pacific deep waters. Upper ocean dissolution, shown to be sensitive to ocean export production, can increase the neutralizing capacity for respired CO2 by up to 6% in low-latitude thermocline waters. Without upper ocean dissolution, the ocean might lose 20% more CO2 to the atmosphere through the low-latitude upwelling regions.

Increases of Phosphorylated Tau (Ser202/Thr205) in the Olfactory Regions Are Associated with Impaired EEG and Olfactory Behavior in Traumatic Brain Injury Mice

Traumatic brain injury (TBI) leads to long-term cognitive impairments, with an increased risk for neurodegenerative and psychiatric disorders. Among these various impairments, olfactory dysfunction is one of the most common symptoms in TBI patients. However, there are very few studies that show the association between olfactory dysfunction and repetitive TBI. To investigate the effects of repetitive TBI on olfactory functioning and the related pathological neuronal injuries in mice, we applied a weight-drop model of TBI and performed neuropathological examinations and electroencephalography (EEG) in olfactory-bulb-associated areas. Through neuropathological examinations, we found significant increases of amyloid precursor protein (APP) and phosphorylated Tau (p-Tau) (S202/T205) in olfactory-bulb-associated areas. Neuronal atrophy in the lateral anterior olfactory nucleus (AOL), granule layer olfactory bulb (GrO), and dorsal tenia tecta (DTT) was also found to be correlated with p-Tau levels. However, there was no difference in the total Tau levels in the olfactory-bulb-associated areas of TBI mice. Electroencephalography (EEG) of repetitive TBI mouse models showed impaired spontaneous delta oscillation, as well as altered cross-frequency coupling between delta phase and amplitudes of the fast oscillations in the resting-state olfactory bulb. Furthermore, abnormal alterations in EEG band powers were observed during the olfactory oddball paradigm test. TBI also led to impairments of the olfactory-function-associated behaviors. This study provides evidence of behavioral, neuropathological, and physiological alterations in the mouse olfactory system caused by repetitive TBI. Together, p-Tau alterations and EEG impairments may serve as important biomarkers of olfactory-track-associated dysfunctions in repetitive TBI.

Unraveling membrane protein localization and interactions in nanodiscs

Nanodiscs, consisting of a lipid bilayer surrounded by membrane scaffold proteins (MSPs), are extensively used to study membrane proteins (MPs) because they provide a stable lipid environment. However, the precise mechanism governing MP behavior within the nanodisc remains elusive. Here, we examined the cryo-EM structures of various MPs reconstituted in nanodiscs from EMPIAR. By analyzing the heterogeneity and interactions in the nanodiscs, we discovered that MPs display a distinct spatial preference toward the edges of the nanodisc shells. Furthermore, MPs can establish direct, amphipathic interactions with the MSPs, causing a reduction in local protein dynamics. These interactions may rearrange MSP-MSP interactions into MP-MSP interactions. Collectively, we provide structural insights into how nanodiscs contribute to MP structural behavior and dynamics. Impact statement Nanodiscs are used to study membrane proteins (MPs), but the mechanisms governing the behavior of MPs within nanodiscs remain elusive. Here, we provide structural insights into how nanodiscs contribute to the behavior of MPs, which will aid the interpretation of cryo-EM studies performed using nanodiscs.

Association of serum ferritin and lung function in tobacco-naïve postmenopausal women: Analysis of population-based nationally representative data

INTRODUCTION

Ferritin regulates iron homeostasis, and is involved in the inflammation in the lung, especially in smokers; however, its associations on pulmonary function in nonsmokers remain unclear.

OBJECTIVES

The present study aimed to evaluate the association between serum ferritin and lung function in a tobacco-naïve postmenopausal women.

METHODS

In this study, 25 534 individuals were enrolled, among who 5338 tobacco-naïve individuals were identified; of those, 342 men and 2879 women (742 pre- and 2137 postmenopausal) with data of serum ferritin, lung function and covariates were included. To evaluate the association of ferritin and lung function, multivariable-adjusted linear regression analyses was used including the factors of predicted value of forced expiratory volume in 1 second (FEV1 %) and forced vital capacity (FVC%). Logistic regression analyses were used to measure the relationship between ferritin and restrictive and obstructive lung disease.

RESULTS

In premenopausal women, FEV1 %/FVC was weakly but positively associated with serum ferritin, and after adjusting for covariates, the association was without statistical significance. No significant association between ferritin and obstructive lung disease was observed. In postmenopausal women, predicted FVC% was negatively associated with serum ferritin, and ferritin was dose-dependently related with risk for restrictive lung disease. The odds ratio for restrictive lung disease in postmenopausal women was 2.285 at T3 and 1.560 at T2 relative to that at T1.

CONCLUSIONS

High serum ferritin level was significantly associated with lower FVC% and increased risk of restrictive lung disease in tobacco-naïve postmenopausal women. Further study is needed to determine the mechanism underlying the current findings.

Imputing missing sleep data from wearables with neural networks in real-world settings

Sleep is a critical component of health and well-being but collecting and analyzing accurate longitudinal sleep data can be challenging, especially outside of laboratory settings. We propose a simple neural network model titled SOMNI (Sleep data restOration using Machine learning and Non-negative matrix factorIzation [NMF]) for imputing missing rest-activity data from actigraphy, which can enable clinicians to better handle missing data and monitor sleep-wake cycles of individuals with highly irregular sleep-wake patterns. The model consists of two hidden layers and uses NMF to capture hidden longitudinal sleep-wake patterns of individuals with disturbed sleep-wake cycles. Based on this, we develop two approaches: the individual approach imputes missing data based on the data from only one participant, while the global approach imputes missing data based on the data across multiple participants. Our models are tested with shift and non-shift workers' data from three independent hospitals. Both approaches can accurately impute missing data up to 24 hours of long dataset (>50 days) even for shift workers with extremely irregular sleep-wake patterns (AUC > 0.86). On the other hand, for short dataset (~15 days), only the global model is accurate (AUC > 0.77). Our approach can be used to help clinicians monitor sleep-wake cycles of patients with sleep disorders outside of laboratory settings without relying on sleep diaries, ultimately improving sleep health outcomes.

A differential diagnosis between uterine leiomyoma and leiomyosarcoma using transcriptome analysis

BACKGROUND

The objective of this study was to estimate the accuracy of transcriptome-based classifier in differential diagnosis of uterine leiomyoma and leiomyosarcoma. We manually selected 114 normal uterine tissue and 31 leiomyosarcoma samples from publicly available transcriptome data in UCSC Xena as training/validation sets. We developed pre-processing procedure and gene selection method to sensitively find genes of larger variance in leiomyosarcoma than normal uterine tissues. Through our method, 17 genes were selected to build transcriptome-based classifier. The prediction accuracies of deep feedforward neural network (DNN), support vector machine (SVM), random forest (RF), and gradient boosting (GB) models were examined. We interpret the biological functionality of selected genes via network-based analysis using GeneMANIA. To validate the performance of trained model, we additionally collected 35 clinical samples of leiomyosarcoma and leiomyoma as a test set (18 + 17 as 1st and 2nd test sets).

RESULTS

We discovered genes expressed in a highly variable way in leiomyosarcoma while these genes are expressed in a conserved way in normal uterine samples. These genes were mainly associated with DNA replication. As gene selection and model training were made in leiomyosarcoma and uterine normal tissue, proving discriminant of ability between leiomyosarcoma and leiomyoma is necessary. Thus, further validation of trained model was conducted in newly collected clinical samples of leiomyosarcoma and leiomyoma. The DNN classifier performed sensitivity 0.88, 0.77 (8/9, 7/9) while the specificity 1.0 (8/8, 8/8) in two test data set supporting that the selected genes in conjunction with DNN classifier are well discriminating the difference between leiomyosarcoma and leiomyoma in clinical sample.

CONCLUSION

The transcriptome-based classifier accurately distinguished uterine leiomyosarcoma from leiomyoma. Our method can be helpful in clinical practice through the biopsy of sample in advance of surgery. Identification of leiomyosarcoma let the doctor avoid of laparoscopic surgery, thus it minimizes un-wanted tumor spread.

Active Arm Swing During Running Improves Rotational Stability of the Upper Body and Metabolic Energy Efficiency

PURPOSE

The kinematic benefits of arm swing during running for upper body stability have been previously investigated, while its role in metabolic energy efficiency remains controversial. To address this, this study aimed to test the hypothesis that active arm swing during running reduces both torso angular motion around the longitudinal axis and metabolic energy consumption.

METHODS

We employed forward dynamics musculoskeletal running simulations with different arm conditions to investigate the hypothesis. Full-body musculoskeletal running models, incorporating 150 muscles, were developed using artificial neural network-based running controllers. Three arm conditions were simulated using the running models and controllers: active arm swing, passive arm swing, and fixed arms.

RESULTS

Our results revealed that the active arm swing model demonstrated the lowest total metabolic energy consumption per traveling distance. The costs of transport were 5.52, 5.73, and 5.82 J/kg-m for active, passive, and fixed arm models, respectively. Interestingly, while metabolic energy consumption in the upper limb muscles was higher during active arm swing, the total energy consumption was lower. Additionally, the longitudinal rotation of the torso was minimal in the active arm swing condition.

CONCLUSION

These findings support our hypothesis, demonstrating that active arm swing during running reduces the angular motion of the torso and the metabolic energy consumption. This study provides evidence that arm swing during running is performed actively as an energy-saving mechanism. These results contribute to understanding of running biomechanics and may have implications for performance optimization in sports and rehabilitation settings.

Image quality improvement in bowtie-filter-equipped cone-beam CT using a dual-domain neural network

BACKGROUND

The bowtie-filter in cone-beam CT (CBCT) causes spatially nonuniform x-ray beam often leading to eclipse artifacts in the reconstructed image. The artifacts are further confounded by the patient scatter, which is therefore patient-dependent as well as system-specific.

PURPOSE

In this study, we propose a dual-domain network for reducing the bowtie-filter-induced artifacts in CBCT images.

METHODS

In the projection domain, the network compensates for the filter-induced beam-hardening that are highly related to the eclipse artifacts. The output of the projection-domain network was used for image reconstruction and the reconstructed images were fed into the image-domain network. In the image domain, the network further reduces the remaining cupping artifacts that are associated with the scatter. A single image-domain-only network was also implemented for comparison.

RESULTS

The proposed approach successfully enhanced soft-tissue contrast with much-reduced image artifacts. In the numerical study, the proposed method decreased perceptual loss and root-mean-square-error (RMSE) of the images by 84.5% and 84.9%, respectively, and increased the structure similarity index measure (SSIM) by 0.26 compared to the original input images on average. In the experimental study, the proposed method decreased perceptual loss and RMSE of the images by 87.2% and 92.1%, respectively, and increased SSIM by 0.58 compared to the original input images on average.

CONCLUSIONS

We have proposed a deep-learning-based dual-domain framework to reduce the bowtie-filter artifacts and to increase the soft-tissue contrast in CBCT images. The performance of the proposed method has been successfully demonstrated in both numerical and experimental studies.

Cell-cell communication network-based interpretable machine learning predicts cancer patient response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. However, only some patients respond to ICIs, and current biomarkers for ICI efficacy have limited performance. Here, we devised an interpretable machine learning (ML) model trained using patient-specific cell-cell communication networks (CCNs) decoded from the patient's bulk tumor transcriptome. The model could (i) predict ICI efficacy for patients across four cancer types (median AUROC: 0.79) and (ii) identify key communication pathways with crucial players responsible for patient response or resistance to ICIs by analyzing more than 700 ICI-treated patient samples from 11 cohorts. The model prioritized chemotaxis communication of immune-related cells and growth factor communication of structural cells as the key biological processes underlying response and resistance to ICIs, respectively. We confirmed the key communication pathways and players at the single-cell level in patients with melanoma. Our network-based ML approach can be used to expand ICIs' clinical benefits in cancer patients.

The emergence of remote laboratory courses in an emergency situation: University instructors' agency during the COVID-19 pandemic

This study examines and describes how various online remote laboratory courses, necessitated by the COVID-19 pandemic, were implemented at Hankuk University in Korea in 2020. We compared four general undergraduate laboratory courses, one each for physics, chemistry, biology, and earth science, and two major-level laboratory courses taught during the spring and fall of 2020. Employing a sociocultural perspective, we examined how the changes in structures at the macro-, meso-, and micro-levels shaped the responses of educational authorities and impacted the agency of university instructors. Instructors implemented various remote laboratory courses in each content area dependent upon availability and access to material resources, including access to video of laboratory activities, and also based on the nature of experimental data associated with each content area. Drawing from survey responses and in-depth interviews with instructors and students, we share findings about how instructor practices impacted the interactions of students, the processes for evaluation, and student learning. We discuss how the global pandemic has re-ignited the debate about the role and value of experimental laboratory activities for undergraduate science majors and about the significance of hands-on versus minds-on science learning. Implications for how universities approach laboratory coursework in the post-COVID-19 are discussed, and questions for university science instruction are raised for future research.

Morphological characteristics of facial scars: A retrospective analysis according to scar location, onset, age, and cause

The morphology of facial scars shows a wide variation in terms of texture and colour. To date, there are no reliable predictors of aberrant scarring. We conducted a retrospective analysis to identify factors associated with specific scar features and types. Photographs and medical records of 428 patients with facial scars were retrospectively reviewed. Patients with keloids were excluded. The mean age of the patients was 45.43 ± 23.13 years with a male-to-female ratio of 1:1.36. Atrophic scars were the most common (42.8%), followed by flat scars (38.7%) and hypertrophic scars (18.5%). Scars on the forehead were more likely to be atrophic, whereas scars on the chin/jaw and around the mouth were more likely to be hypertrophic. Hypopigmentation was significantly more common in scars located on the forehead. Redness (erythema) was significantly more common in scars located on the chin/jaw. Old scars were less likely to be erythematous, and hypertrophic. Atrophic scars were more common in younger patients. Scars caused by dermatologic conditions, such as acne, were more likely to be atrophic, whereas surgical scars had the lowest risk of being atrophic or hypertrophic. In conclusion, the location, onset, and cause of facial scars were associated with specific features of scars.

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice

Although mice are social, multiple animals' neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure. The power of lower frequency bands-delta to alpha-were correlated with each other and anti-correlated with gamma power. The high-to-low-power ratio (HLR) provided a useful measure to understand LFP changes along the change of behavioural and locomotive states. The HLR during huddled conditions was lower than that during non-huddled conditions, dividing the social context into two. Multi-brain analyses of HLR indicated that the mice in the group displayed high cross-correlation. The mice in the group often showed unilateral precedence of HLR by Granger causality analysis, possibly comprising a hierarchical social structure. Overall, this study shows the importance of the social environment in brain dynamics and emphasises the simultaneous multi-brain recordings in social neuroscience.

Impact of Indazole Scaffold as Antibacterial and Antifungal Agent

Heterocycles consisting of a nitrogen atom, Indazole, is a pungent, biological, heterocyclic, bicyclic compound possessing electron-rich portions. Indazole is composed of two nitrogen atoms put under the azoles family, further called isoindazolone. It is colorless solid nitrogen- containing heterocyclics with atomic formula-C7H6N2 are extraordinary scaffolds, still identified as isoindazole. Therefore, analogs of Indazole have experienced expert approaches in later times because of its special biological properties, such as anti-microbial, anti-inflammatory, anticancer, anti- HIV and antihypertensive actions. 1H-indazole and 2H-indazole are two toutomeric forms of Indazole. Sometimes, indazole produces three tautomeric forms that are 1H, 2H and 3H tautomers of indazole. 1H-indazole is reliable than 2H-indazole. We should note that a series of derivatives of indazole having 2H toutomers follow hybridization of cyclic systems and act as anti-inflammatory as well as anti-microbial compounds. It formed Indazole itself and derivatives of Indazole in natural products. A sequence of N-methyl-3-aryl inazoles has dominant against bacterial strains like xanthomon as campstris, Baillus cereus, Escherichia coli, Bacillus megaterium and a fungal strain candida albicans found by in-vitro anti-microbial study of indazole derivatives.