Activation of neurotoxic A1-reactive astrocytes by SFTS virus infection accelerates fatal brain damage in IFNAR1-/- mice.

Severe fever with thrombocytopenia syndrome (SFTS) has a high mortality rate compared to other infectious diseases. SFTS is particularly associated with a high risk of mortality in immunocompromised individuals, while most patients who die of SFTS exhibit symptoms of severe encephalitis before death. However, the region of brain damage and mechanisms by which the SFTS virus (SFTSV) causes encephalitis remains unknown. Here, we revealed that SFTSV infects the brainstem and spinal cord, which are regions of the brain associated with respiratory function, and motor nerves in IFNAR1-/- mice. Further, we show that A1-reactive astrocytes are activated, causing nerve cell death, in infected mice. Primary astrocytes of SFTSV-infected IFNAR1-/- mice also induced neuronal cell death through the activation of A1-reactive astrocytes. Herein, we showed that SFTSV induces fatal neuroinflammation in the brain regions important for respiratory function and motor nerve, which may underlie mortality in SFTS patients. This study provides new insights for the treatment of SFTS, for which there is currently no therapeutic approach.

3D airway geometry analysis of factors in airway navigation failure for lung nodules.

BACKGROUND: This study aimed to quantitatively reveal contributing factors to airway navigation failure during radial probe endobronchial ultrasound (R-EBUS) by using geometric analysis in a three-dimensional (3D) space and to investigate the clinical feasibility of prediction models for airway navigation failure. METHODS: We retrospectively reviewed patients who underwent R-EBUS between January 2017 and December 2018. Geometric quantification was analyzed using in-house software built with open-source python libraries including the Vascular Modeling Toolkit ( http://www.vmtk.org ), simple insight toolkit ( https://sitk.org ), and sci-kit image ( https://scikit-image.org ). We used a machine learning-based approach to explore the utility of these significant factors. RESULTS: Of the 491 patients who were eligible for analysis (mean age, 65 years +/- 11 [standard deviation]; 274 men), the target lesion was reached in 434 and was not reached in 57. Twenty-seven patients in the failure group were matched with 27 patients in the success group based on propensity scores. Bifurcation angle at the target branch, the least diameter of the last section, and the curvature of the last section are the most significant and stable factors for airway navigation failure. The support vector machine can predict airway navigation failure with an average area under the curve of 0.803. CONCLUSIONS: Geometric analysis in 3D space revealed that a large bifurcation angle and a narrow and tortuous structure of the closest bronchus from the lesion are associated with airway navigation failure during R-EBUS. The models developed using quantitative computer tomography scan imaging show the potential to predict airway navigation failure.

Predicting cerebrovascular age and its clinical relevance: Modeling using 3D morphological features of brain vessels.

Aging manifests as many phenotypes, among which age-related changes in brain vessels are important, but underexplored. Thus, in the present study, we constructed a model to predict age using cerebrovascular morphological features, further assessing their clinical relevance using a novel pipeline. Age prediction models were first developed using data from a normal cohort (n = 1181), after which their relevance was tested in two stroke cohorts (n = 564 and n = 455). Our novel pipeline adapted an existing framework to compute generic vessel features for brain vessels, resulting in 126 morphological features. We further built various machine learning models to predict age using only clinical factors, only brain vessel features, and a combination of both. We further assessed deviation from healthy aging using the age gap and explored its clinical relevance by correlating the predicted age and age gap with various risk factors. The models constructed using only brain vessel features and those combining clinical factors with vessel features were better predictors of age than the clinical factor-only model (r = 0.37, 0.48, and 0.26, respectively). Predicted age was associated with many known clinical factors, and the associations were stronger for the age gap in the normal cohort. The age gap was also associated with important factors in the pooled cohort atherosclerotic cardiovascular disease risk score and white matter hyperintensity measurements. Cerebrovascular age, computed using the morphological features of brain vessels, could serve as a potential individualized marker for the early detection of various cerebrovascular diseases.

Oven-Roasting Effects the Fatty Acid Composition, Antioxidant Properties, and Oxidative Stability of Pomegranate (Punica granatum L.) Seed Oil.

In this study, we investigated the effect of roasting conditions and time on the physicochemical properties of pomegranate seed oil. We analyzed the fatty acid, total phenolic, flavonoid, tocopherol, and phytosterol contents of pomegranate seed oil extracted under four conditions: raw, heated at 160°C for 15 min, heated at 160°C for 20 min, and heated at 180°C for 10 min, which included three that were well-established to enhance nutritional and flavor properties. Furthermore, the oxidative stability was evaluated based on the acid value, peroxide value, and induction period. Roasting significantly decreased the contents of punicic acid, polyunsaturated fatty acids, tocopherol, and phytosterol and the 2,2-diphenyl-1-picrylhydrazyl radical scavenging capacity (P<0.05) of the oil. Conversely, saturated fatty acids, monounsaturated fatty acids, acid value, peroxide value, total phenolic and flavonoid contents, and induction period were significantly increased (P<0.05). Our results suggest that the roasting conditions were nutritionally and oxidatively stable, thereby enhancing the roasting process and providing a database for essential roasting treatments for pomegranate seed oil.

Comparison of biportal endoscopic and microscopic tubular paraspinal approach for foraminal and extraforaminal lumbar disc herniation.

OBJECTIVE: Foraminal and extraforaminal lumbar disc herniation (FELDH) is an important pathological condition that can lead to lumbar radiculopathy. The paraspinal muscle-splitting approach introduced by Reulen and Wiltse is a reasonable surgical technique. Minimally invasive procedures using a tubular retractor system have also been introduced. However, surgical treatment is considered more challenging for FELDH than for central or subarticular lumbar disc herniations (LDHs). Some researchers have proposed uniportal extraforaminal endoscopic lumbar discectomy through a posterolateral approach as an alternative for FELDH, but heterogeneous clinical results have been reported. Recently, the biportal endoscopic (BE) paraspinal approach has been suggested as an alternative. The aim of this study was to compare the clinical outcomes of BE and microscopic tubular (MT) paraspinal approaches for decompressive foraminotomy and lumbar discectomy (paraLD) in patients with FELDH. METHODS: Ninety-one consecutive patients with unilateral lumbar radiculopathy and FELDH underwent paraLD. Demographic and perioperative data were collected. Clinical outcomes were evaluated using the visual analog scale (VAS) for back and leg pain, the Oswestry Disability Index (ODI) for spinal disability, and the modified Macnab criteria for patient satisfaction. Postoperative complications and reoperation rates were also evaluated. RESULTS: In total, 76 patients were included in the final analysis. Among them, 43 underwent BE paraLD (group A) and the remaining 33 underwent MT paraLD (group B). The demographic and preoperative data were not statistically different between the groups. All patients showed significant improvements in VAS back, VAS leg, and ODI scores compared with baseline values (p < 0.05). The improvement in VAS back scores was significantly better in group A than in group B on postoperative day 2 (p < 0.001). However, all clinical parameters were comparable between the two groups after postoperative year 1 (p > 0.05). According to the modified Macnab criteria, 86.1% and 72.7% of the patients had excellent or good outcomes in groups A and B, respectively. No intergroup differences were observed (p = 0.367). In addition, there were no differences in the total operation time or amount of surgical drainage. Postoperative complications were not significantly different between the two groups (p = 0.301); however, reoperation rates were significantly higher in group B (p = 0.035). CONCLUSIONS: BE paraLD is an effective treatment for FELDH and is an alternative to MT paraLD. In particular, BE paraLD has advantages of early improvement in postoperative back pain and low reoperation rates.

Evolution of RNA Viruses: Reasons for the Existence of Separate Plus, Minus, and Double-Strand Replication Strategies.

Plus, minus, and double-strand RNA viruses are all found in nature. We use computational models to study the relative success of these strategies. We consider translation, replication, and virion assembly inside one cell, and transmission of virions between cells. For viruses which do not incorporate a polymerase in the capsid, transmission of only plus strands is the default strategy because virions containing minus strands are not infectious. Packaging only plus strands has a significant advantage if the number of RNA strands produced per cell is larger than the number of capsids. In this case, by not packaging minus strands, the virus produces more plus-strand virions. Therefore, plus-strand viruses are selected at low multiplicity of infection. However, at high multiplicity of infection, it is preferable to package both strands because the additional minus virions produced are helpful when there are multiple infections per cell. The fact that plus-strand viruses are widespread while viruses that package both strands are not seen in nature suggests that RNA strands are indeed produced in excess over capsids, and that the multiplicity of infection is not sufficiently high to favor the production of both kinds of virions. For double-strand viruses, we show that it is advantageous to produce only plus strands from the double strand within the cell, as is observed in real viruses. The reason for the success of minus-strand viruses is more puzzling initially. For viruses that incorporate a polymerase in the virion, minus virions are infectious. However, this is not sufficient to explain the success of minus-strand viruses, because in this case, viruses that package both strands outcompete those that package only minus or only plus. Real minus-strand viruses make use of replicable strands that are coated by a nucleoprotein, and separate translatable plus strands that are uncoated. Here we show that when there are distinct replicable and translatable strands, minus-strand viruses are selected.

Leveraging segmentation-guided spatial feature embedding for overall survival prediction in glioblastoma with multimodal magnetic resonance imaging.

BACKGROUND AND OBJECTIVE: Patients with glioblastoma have a five-year relative survival rate of less than 5 %. Thus, accurately predicting the overall survival (OS) of patients with glioblastoma is crucial for effective treatment planning. METHODS: To fully leverage the imaging characteristics of glioblastomas, we propose a segmentation-guided regression method for predicting OS of patients with brain tumors using multimodal magnetic resonance imaging. Specifically, a brain tumor segmentation network was first pre-trained without leveraging survival information. Subsequently, the survival regression network was jointly trained with the guidance of brain tumor segmentation, focusing on tumor voxels and suppressing irrelevant backgrounds. RESULTS: Our proposed framework, based on the well-known backbone of UNETR++, achieved a Dice score of 0.7910, Spearman correlation of 0.4112, and Harrell's concordance index of 0.6488. The model consistently showed promising results compared with baseline methods on two different datasets (BraTS and UCSF-PDGM). Furthermore, ablation studies on our training configurations demonstrated that both the pre-training segmentation network and contrastive loss significantly improved all metrics for OS prediction. CONCLUSIONS: In this study, we propose a joint learning framework based on a pre-trained segmentation backbone for OS prediction by leveraging a brain tumor segmentation map. By utilizing a spatial feature map, our model can operate using a sliding-window approach, which can be adopted by varying the matrix sizes and resolutions of the input images.

Development and psychometric testing of a questionnaire for the Korea Youth risk behavior survey to assess physical activity behaviors.

BACKGROUND: Physical activity is essential for physical, mental, and cognitive health. Providing evidence to develop better public health policies to encourage increased physical activity is crucial. Therefore, we developed an in-depth survey as part of the Korea Youth Risk Behavior Survey to assess the current status and determinants of physical activity among Korean adolescents. METHODS: We developed an initial version of the questionnaire based on a review of validated questionnaires, recent trends and emerging issues related to adolescent physical activity, and the national public health agenda pertaining to health promotion. Content validity was confirmed by a panel of 10 experts. Face validity was confirmed through focus group interviews with 12 first-year middle school students. The test-retest reliability of the questionnaire was evaluated by administering it twice, approximately two weeks apart, to a sample of 360 middle and high school students. Additionally, the frequency or average number of responses was analyzed in a sample of 600 students who participated in the initial test-retest reliability evaluation of the questionnaire developed in this study. RESULTS: Through item pool generation and content and face validity test, the final 15 questionnaire items were developed across five themes: levels of physical activity, school sports club activities, transportation-related physical activity, physical activity-promoting environments, and factors mediating physical activity. The test-retest reliability ranged from fair to substantial. Results from the newly developed survey reveal that only a minority of adolescents engage in sufficient physical activity, with only 17.2% and 21.5% participating in vigorous and moderate-intensity activities, respectively, for at least five days per week. Among school-based activities, 44.3% of students do not participate in school sports clubs due to reasons including absence of clubs and disinterest in exercise. The major motivators for physical activity are personal enjoyment and health benefits, whereas preferences for other leisure activities and academic pressures are the predominant barriers. CONCLUSIONS: This study developed valid and reliable in-depth survey items to assess physical activity among Korean youths. It will hopefully enhance our understanding of adolescent physical activity, offering essential preliminary evidence to inform the development of public health strategies aimed at promoting adolescent health.

The Combined Effects of Alcohol Consumption and Smoking on Cancer Risk by Exposure Level: A Systematic Review and Meta-Analysis.

BACKGROUND: Alcohol consumption is a major risk factor for cancer, and when combined with smoking, the risk increases. Nevertheless, few studies have comprehensively evaluated the combined effects of alcohol consumption and smoking on the risk of various cancer types. Therefore, to assess these effects, we conducted a systematic review and meta-analysis. METHODS: We performed a systematic search of five literature databases, focusing on cohort and case-control studies. Considering exposure levels, we quantified the combined effects of alcohol consumption and smoking on cancer risk and assessed multiplicative interaction effects. RESULTS: Of 4,452 studies identified, 24 (4 cohort studies and 20 case-control studies) were included in the meta-analysis. We detected interaction effect of light alcohol and moderate smoking on head and neck cancer risk (relative risk [RR], 4.26; 95% confidence interval [CI], 2.50-7.26; I² = 65%). A synergistic interaction was observed in heavy alcohol and heavy smoking group (RR, 35.24; 95% CI, 23.17-53.58; I² = 69%). In more detailed cancer types, the interaction effect of heavy alcohol and heavy smoking was noticeable on oral (RR, 36.42; 95% CI, 24.62-53.87; I² = 46%) and laryngeal (RR, 38.75; 95% CI, 19.25-78.01; I² = 69%) cancer risk. CONCLUSION: Our study provided a comprehensive summary of the combined effects of alcohol consumption and smoking on cancers. As their consumption increased, the synergy effect became more pronounced, and the synergy effect was evident especially for head and neck cancer. These findings provide additional evidence for the combined effect of alcohol and smoking in alcohol guidelines for cancer prevention.

Global intracranial arterial tortuosity is associated with intracranial atherosclerotic burden.

The effect of arterial tortuosity on intracranial atherosclerosis (ICAS) is not well understood. This study aimed to evaluate the effect of global intracranial arterial tortuosity on intracranial atherosclerotic burden in patients with ischemic stroke. We included patients with acute ischemic stroke who underwent magnetic resonance angiography (MRA) and classified them into three groups according to the ICAS burden. Global tortuosity index (GTI) was defined as the standardized mean curvature of the entire intracranial arteries, measured by in-house vessel analysis software. Of the 516 patients included, 274 patients had no ICAS, 140 patients had a low ICAS burden, and 102 patients had a high ICAS burden. GTI increased with higher ICAS burden. After adjustment for age, sex, vascular risk factors, and standardized mean arterial area, GTI was independently associated with ICAS burden (adjusted odds ratio [adjusted OR] 1.33; 95% confidence interval [CI] 1.09-1.62). The degree of association increased when the arterial tortuosity was analyzed limited to the basal arteries (adjusted OR 1.48; 95% CI 1.22-1.81). We demonstrated that GTI is associated with ICAS burden in patients with ischemic stroke, suggesting a role for global arterial tortuosity in ICAS.

Histopathologic image-based deep learning classifier for predicting platinum-based treatment responses in high-grade serous ovarian cancer.

Platinum-based chemotherapy is the cornerstone treatment for female high-grade serous ovarian carcinoma (HGSOC), but choosing an appropriate treatment for patients hinges on their responsiveness to it. Currently, no available biomarkers can promptly predict responses to platinum-based treatment. Therefore, we developed the Pathologic Risk Classifier for HGSOC (PathoRiCH), a histopathologic image-based classifier. PathoRiCH was trained on an in-house cohort (n = 394) and validated on two independent external cohorts (n = 284 and n = 136). The PathoRiCH-predicted favorable and poor response groups show significantly different platinum-free intervals in all three cohorts. Combining PathoRiCH with molecular biomarkers provides an even more powerful tool for the risk stratification of patients. The decisions of PathoRiCH are explained through visualization and a transcriptomic analysis, which bolster the reliability of our model's decisions. PathoRiCH exhibits better predictive performance than current molecular biomarkers. PathoRiCH will provide a solid foundation for developing an innovative tool to transform the current diagnostic pipeline for HGSOC.

Controlling Fluorination Density of Soluble Polyimide Gate Dielectrics and its Influence on Organic Crystal Growth and Device Operational Stability.

Fluorinated polyimides (PIs) are among the most promising candidates for gate dielectric materials in organic electronic devices because of their solution processability and outstanding chemical, mechanical, and thermal stabilities. Additionally, fluorine (F) substitution improves the electrical properties of PI thin films, such as enhanced dielectric properties and reduced surface trap densities. However, the relationship between the fluorination density of PIs and crystal growth modes of vacuum-deposited conjugated molecules on PI thin films, which is directly related to the lateral charge transport along the PI-organic semiconductor interface, has not been systematically studied. Herein, five different soluble PIs with different F densities were synthesized, and the correlation between fluorination and thin-film properties was systematically investigated. Not only were their dielectric properties modulated, but the growth modes of the organic molecules deposited on the PI thin films also changed with increasing surface F density. This phenomenon was observed by both surface and crystallographic analyses, which resulted in extremely high operational stability of field-effect transistors and the successful fabrication of organic complementary circuits. We believe that the correlation between PI backbone fluorination and its thin-film properties will provide practical insights into the material design based on controlled molecular directed surface assembly on fluorinated polymer dielectrics.

GAN-MAT: Generative adversarial network-based microstructural profile covariance analysis toolbox.

Multimodal magnetic resonance imaging (MRI) provides complementary information for investigating brain structure and function; for example, an in vivo microstructure-sensitive proxy can be estimated using the ratio between T1- and T2-weighted structural MRI. However, acquiring multiple imaging modalities is challenging in patients with inattentive disorders. In this study, we proposed a comprehensive framework to provide multiple imaging features related to the brain microstructure using only T1-weighted MRI. Our toolbox consists of (i) synthesizing T2-weighted MRI from T1-weighted MRI using a conditional generative adversarial network; (ii) estimating microstructural features, including intracortical covariance and moment features of cortical layer-wise microstructural profiles; and (iii) generating a microstructural gradient, which is a low-dimensional representation of the intracortical microstructure profile. We trained and tested our toolbox using T1- and T2-weighted MRI scans of 1,104 healthy young adults obtained from the Human Connectome Project database. We found that the synthesized T2-weighted MRI was very similar to the actual image and that the synthesized data successfully reproduced the microstructural features. The toolbox was validated using an independent dataset containing healthy controls and patients with episodic migraine as well as the atypical developmental condition of autism spectrum disorder. Our toolbox may provide a new paradigm for analyzing multimodal structural MRI in the neuroscience community and is openly accessible at https://github.com/CAMIN-neuro/GAN-MAT.

Comparative analysis of malt quality and starch characteristics of three South Korean barley cultivars.

In this study, malt was produced in pilot-scale facilities and conditioned using three barley (Hordeum vulgare L.) cultivars in South Korea (Heugho, Hopum, and Kwangmaeg). Quality and starch characteristics were compared. The starch content was considerably reduced in all malts. Coleoptile elongation was higher in Heugho (HHM; 85.7% ± 12.6%) and Hopum (HPM; 83.9% ± 10.7%) than in Kwangmaeg (KMM; 78.1% ± 9.9%) malt. Malt yield ranged from 81.8 to 84.9%, with no significant difference. All samples presented type A crystallinity, and granules showed discoid shapes. After malting, the mono- and di-saccharide contents (not including sucrose) were increased. The fermentable sugar level was the highest in HHM, whereas non-fermentable sugar was the highest in KMM. These results suggest that HPM enables efficient scarification based on the rapid degradation of starch, while Heugho barley and HHM have a high potential for beer and malt production, respectively. Supplementary Information: The online version contains supplementary material available at 10.1007/s10068-023-01419-6.

Implantation of hUCB-MSCs generates greater hyaline-type cartilage than microdrilling combined with high tibial osteotomy.

PURPOSE: To compare the outcomes of treating large cartilage defects in knee osteoarthritis using human allogeneic umbilical cord blood-derived mesenchymal stem cell (hUCB-MSC) implantation or arthroscopic microdrilling as a supplementary cartilage regenerative procedure combined with high tibial osteotomy (HTO). METHODS: This 1-year prospective comparative study included 25 patients with large, near full-thickness cartilage defects (International Cartilage Repair Society grade ≥ IIIB) in the medial femoral condyles and varus malalignment. Defects were treated with hUCB-MSC implantation or arthroscopic microdrilling combined with HTO. The primary outcomes were pain visual analogue scale and International Knee Documentation Committee subjective scores at 12, 24 and 48 weeks. Secondary outcomes included arthroscopic, histological and magnetic resonance imaging assessments at 1 year. RESULTS: Fifteen and 10 patients were treated via hUCB-MSC implantation and microdrilling, respectively. Baseline demographics, limb alignment and clinical outcomes did not significantly differ between the groups. Cartilage defects and total restored areas were significantly larger in the hUCB-MSC group (7.2 ± 1.9 vs. 5.2 ± 2.1 cm2, p = 0.023; 4.5 ± 1.4 vs. 3.0 ± 1.6 cm2, p = 0.035). The proportion of moderate-to-strong positive type II collagen staining was significantly higher in the hUCB-MSC group compared to that in the microdrilled group (93.3% vs. 60%, respectively). Rigidity upon probing resembled that of normal cartilage tissue more in the hUCB-MSC group (86.7% vs. 50.0%, p = 0.075). Histological findings revealed a higher proportion of hyaline cartilage in the group with implanted hUCB-MSC (p = 0.041). CONCLUSION: hUCB-MSC implantation showed comparable clinical outcomes to those of microdrilling as supplementary cartilage procedures combined with HTO in the short term, despite the significantly larger cartilage defect in the hUCB-MSC group. The repaired cartilage after hUCB-MSC implantation showed greater hyaline-type cartilage with rigidity than that after microdrilling. LEVEL OF EVIDENCE: Level II, Prospective Comparative Cohort Study.

Distinct spatiotemporal patterns of cortical thinning in Alzheimer's disease-type cognitive impairment and subcortical vascular cognitive impairment.

Previous studies on Alzheimer's disease-type cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI) has rarely explored spatiotemporal heterogeneity. This study aims to identify distinct spatiotemporal cortical atrophy patterns in ADCI and SVCI. 1,338 participants (713 ADCI, 208 SVCI, and 417 cognitively unimpaired elders) underwent brain magnetic resonance imaging (MRI), amyloid positron emission tomography, and neuropsychological tests. Using MRI, this study measures cortical thickness in five brain regions (medial temporal, inferior temporal, posterior medial parietal, lateral parietal, and frontal areas) and utilizes the Subtype and Stage Inference (SuStaIn) model to predict the most probable subtype and stage for each participant. SuStaIn identifies two distinct cortical thinning patterns in ADCI (medial temporal: 65.8%, diffuse: 34.2%) and SVCI (frontotemporal: 47.1%, parietal: 52.9%) patients. The medial temporal subtype of ADCI shows a faster decline in attention, visuospatial, visual memory, and frontal/executive domains than the diffuse subtype (p-value < 0.01). However, there are no significant differences in longitudinal cognitive outcomes between the two subtypes of SVCI. Our study provides valuable insights into the distinct spatiotemporal patterns of cortical thinning in patients with ADCI and SVCI, suggesting the potential for individualized therapeutic and preventive strategies to improve clinical outcomes.

Whole-brain structural connectome asymmetry in autism.

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

Br doping-induced evolution of the electronic band structure in dimorphic and hexagonal SnSe2 thermoelectric materials.

SnSe2 with its layered structure is a promising thermoelectric material with intrinsically low lattice thermal conductivity. However, its poor electronic transport properties have motivated extensive doping studies. Br doping effectively improves the power factor and converts the dimorphic SnSe2 to a fully hexagonal structure. To understand the mechanisms underlying the power factor improvement of Br-doped SnSe2, the electronic band parameters of Br-doped dimorphic and hexagonal SnSe2 should be evaluated separately. Using the single parabolic band model, we estimate the intrinsic mobility and effective mass of the Br-doped dimorphic and hexagonal SnSe2. While Br doping significantly improves the mobility of dimorphic SnSe2 (with the dominant hexagonal phase), it results in a combination of band convergence and band flattening in fully hexagonal SnSe2. Br-doped dimorphic SnSe2 is predicted to exhibit higher thermoelectric performance (zT ∼0.23 at 300 K) than Br-doped fully hexagonal SnSe2 (zT ∼0.19 at 300 K). Characterisation of the other, currently unidentified, structural phases of dimorphic SnSe2 will enable us to tailor the thermoelectric properties of Br-doped SnSe2.

Density Functional Theory-Based Approach For Dielectric Constant Estimation of Soluble Polyimide Insulators.

Evaluation of the insulating properties of polymers, such as the dielectric constant and dissipation factor, is crucial in electronic devices, including field-effect transistors and wireless communication applications. This study applies density functional theory (DFT) to predict the dielectric constant of soluble polyimides (SPIs). Various SPIs containing trifluoromethyl groups in the backbone with different pendant types, numbers, and symmetries are successfully synthesized, and their dielectric constants are evaluated and compared with the DFT-estimated values. Two types of DFT-optimized SPIs, single-chain and stacked-chain models, are used to describe the local geometries of the SPIs. In addition, to reveal the relationship between the molecular structure and dielectric constant, further investigations are conducted by considering the dielectric constant of composing ionic and electronic components. The DFT-estimated static dielectric constant of the single-chain model accurately reproduces the corresponding experimental value with at least 80% accuracy. Our approach provides a rational and accelerated strategy to evaluate polymer insulators for electronic devices based on cost-effective DFT calculations.