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Abstract Low body mass index is closely related to a high risk of Alzheimer’s disease (AD) and related biomarkers including amyloid-β (Aβ) deposition. However, the association between sarcopenia and Aβ-confirmed AD remains controversial. Therefore, we investigated the relationship between sarcopenia and the AD continuum. We explored sarcopenia’s association with clinical implications of participants on the AD continuum. We prospectively enrolled 142 participants on the AD continuum (19 with preclinical AD, 96 with mild cognitive impairment due to AD, and 28 with AD dementia) and 58 Aβ-negative cognitively unimpaired participants. Sarcopenia, assessed using dual-energy X-ray absorptiometry and hand grip measurements, was considered a predictor. AD continuum, defined by Aβ deposition on positron emission tomography served as an outcome. Clinical severity in participants on the AD continuum assessed using hippocampal volume, Mini-Mental State Examination (MMSE), Seoul Verbal Learning Test (SVLT), and Clinical Dementia Rating Scale Sum of Boxes Scores (CDR-SOB) were also considered an outcome. Sarcopenia (odds ratio = 4.99, p = 0.004) was associated independently with the AD continuum after controlling for potential confounders. Moreover, sarcopenia was associated with poor downstream imaging markers (decreased hippocampal volume, β = − 0.206, p = 0.020) and clinical outcomes (low MMSE, β = − 1.364, p = 0.025; low SVLT, β = − 1.077, p = 0.025; and high CDR-SOB scores, β = 0.783, p = 0.022) in participants on the AD continuum. Sarcopenia was associated with the AD continuum and poor clinical outcome in individuals with AD continuum. Therefore, our results provide evidence for future studies to confirm whether proper management of sarcopenia can effective strategies are required for sarcopenia management to prevent the AD continuum and its clinical implications.

Abstract Knowledge of the factors affecting the difference in kinetics and longevity of the neutralizing antibody (nAb) response to SARS-CoV-2 is necessary to properly prioritize vaccination. In the present study, from March to December 2020, of the 143 patients who recovered from COVID-19, 87 underwent study visits scheduled every 3 months. Patient demographics and blood samples were collected followed by a plaque reduction neutralization test to analyze nAb titers. A linear mixed model was used to compare the effects of sex, age, and disease severity over time. Results demonstrated a gradual reduction in nAb titers over time with a significant decrease from 6 to 9 months post-COVID-19 infection (p

Abstract Cortical atrophy is measured clinically according to established visual rating scales based on magnetic resonance imaging (MRI). Although brain MRI is the primary imaging marker for neurodegeneration, computed tomography (CT) is also widely used for the early detection and diagnosis of dementia. However, they are seldom investigated. Therefore, we developed a machine learning algorithm for the automatic estimation of cortical atrophy on brain CT. Brain CT images (259 Alzheimer’s dementia and 55 cognitively normal subjects) were visually rated by three neurologists and used for training. We constructed an algorithm by combining the convolutional neural network and regularized logistic regression (RLR). Model performance was then compared with that of neurologists, and feature importance was measured. RLR provided fast and reliable automatic estimations of frontal atrophy (75.2% accuracy, 93.6% sensitivity, 67.2% specificity, and 0.87 area under the curve [AUC]), posterior atrophy (79.6% accuracy, 87.2% sensitivity, 75.9% specificity, and 0.88 AUC), right medial temporal atrophy (81.2% accuracy, 84.7% sensitivity, 79.6% specificity, and 0.88 AUC), and left medial temporal atrophy (77.7% accuracy, 91.1% sensitivity, 72.3% specificity, and 0.90 AUC). We concluded that RLR-based automatic estimation of brain CT provided a comprehensive rating of atrophy that can potentially support physicians in real clinical settings.

Abstract Due to the continuously mutating nature of the H3N2 virus, two aspects were considered when preparing the H3N2 microneedle vaccines: (1) rapid preparation and (2) cross-protection against multiple antigenic variants. Previous methods of measuring hemagglutinin (HA) content required the standard antibody, thus rapid preparation of H3N2 microneedle vaccines targeting the mutant H3N2 was delayed as a result of lacking a standard antibody. In this study, H3N2 microneedle vaccines were prepared by high performance liquid chromatography (HPLC) without the use of an antibody, and the cross-protection of the vaccines against several antigenic variants was observed. The HA content measured by HPLC was compared with that measured by ELISA to observe the accuracy of the HPLC analysis of HA content. The cross-protection afforded by the H3N2 microneedle vaccines was evaluated against several antigenic variants in mice. Microneedle vaccines for the 2019–20 seasonal H3N2 influenza virus (19–20 A/KS/17) were prepared using a dip-coating process. The cross-protection of 19–20 A/KS/17 H3N2 microneedle vaccines against the 2015–16 seasonal H3N2 influenza virus in mice was investigated by monitoring body weight changes and survival rate. The neutralizing antibody against several H3N2 antigenic variants was evaluated using the plaque reduction neutralization test (PRNT). HA content in the solid microneedle vaccine formulation with trehalose post-exposure at 40℃ for 24 h was 48% and 43% from the initial HA content by HPLC and ELISA, respectively. The vaccine was administered to two groups of mice, one by microneedles and the other by intramuscular injection (IM). In vivo efficacies in the two groups were found to be similar, and cross-protection efficacy was also similar in both groups. HPLC exhibited good diagnostic performance with H3N2 microneedle vaccines and good agreement with ELISA. The H3N2 microneedle vaccines elicited a cross-protective immune response against the H3N2 antigenic variants. Here, we propose the use of HPLC for a more rapid approach in preparing H3N2 microneedle vaccines targeting H3N2 virus variants.

Porous carbon materials are suitable as highly efficient adsorbents for the treatment of organic pollutants in wastewater. In this study, we developed multiscale porous and heteroatom (O, N)-doped activated carbon aerogels (CAs) based on mesoporous zeolitic imidazolate framework-8 (ZIF-8) nanocrystals and wood using 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) oxidation, in situ synthesis, and carbonization/activation. The surface carboxyl groups in a TEMPO-oxidized wood (TW) can provide considerably large nucleation sites for ZIF-8. Consequently, ZIF-8, with excellent porosity, was successfully loaded into the TW via in situ growth to enhance the specific surface area and enable heteroatom doping. Thereafter, the ZIF-8-loaded TW was subjected to a direct carbonization/activation process, and the obtained activated CA, denoted as ZIF-8/TW-CA, exhibited a highly interconnected porous structure containing multiscale (micro, meso, and macro) pores. Additionally, the resultant ZIF-8/TW-CA exhibited a low density, high specific surface area, and excellent organic dye adsorption capacity of 56.0 mg cm−3, 785.8 m2 g−1, and 169.4 mg g−1, respectively. Given its sustainable, scalable, and low-cost wood platform, the proposed high-performance CA is expected to enable the substantial expansion of strategies for environmental protection, energy storage, and catalysis.

Despite numerous studies on cancer treatment, cancer remains a challenging disease to cure, even after decades of research. In recent years, the cancer vaccine has emerged as a promising approach for cancer treatment, offering few unexpected side effects compared to existing therapies. However, the cancer vaccine faces obstacles to commercialization due to its low efficacy. Particularly, the Toll-like receptor (TLR) adjuvant system, specifically the TLR 7/8 agonist, has shown potential for activating Th1 immunity, which stimulates both innate and adaptive immune responses through T cells. In this study, we developed ProLNG-S, a cholesterol-conjugated form of resiquimod (R848), to enhance immune efficacy by stimulating the immune system and reducing toxicity. ProLNG-S was formulated as ProLNG-001, a positively charged liposome, and co-administered with ovalbumin (OVA) protein in the B16-OVA model. ProLNG-001 effectively targeted secondary lymphoid organs, resulting in a robust systemic anti-tumor immune response and tumor-specific T cell activation. Consequently, ProLNG-001 demonstrated potential for preventing tumor progression and improving survival compared to AS01 by enhancing anti-tumor immunity.

The Korean military's defense research and development (R&D) policy was often shortsighted because of environmental changes, such as the Korea–U.S. alliance, security policies under the regime, and limited budgets. In addition, there was a lack of prior research focusing on identifying the determinants of defense R&D policy, making it difficult for stakeholders in defense R&D policies to determine the appropriateness or validity of decision making. To this end, the purpose of the present study was to suggest a basic reference for defense R&D decision making through the conceptualization of determinants in defense R&D policy and development of measurement items. For this, we developed operational definitions of influencing factors and preliminary items related to defense R&D policy decisions, considering the Republic of Korea Armed Forces. To test reliability and validity, we performed exploratory and confirmatory factor analyses based on discussions with experts. The results show a six-factor structure (security policy, defense posture, technological ambition, dominant and shifting paradigm, science and technology, industry knowledge base, and resources) and 24 items. It is concluded that the use of questionnaire results might better reflect multiple aspects of decision making in defense R&D policy. Future studies need to elaborate on the measurement indicators for defense R&D policy determinants and theorize on policy directions according to changes in future defense and private technology development.

BackgroundIsolation of COVID-19 patients is a crucial infection control measure to prevent further SARS-CoV-2 transmission, but determining an appropriate timing to end the COVID-19 isolation is a challenging. We evaluated the performance of the self-test rapid antigen test (RAT) as a potential proxy to terminate the isolation of COVID-19 patients.Materials and methodsSymptomatic COVID-19 patients were enrolled who were admitted to a regional community treatment center (CTC) in Seoul (South Korea). Self-test RAT and the collection of saliva samples were performed by the patients, on a daily basis, until patient discharge. Cell culture and subgenomic RNA detection were performed on saliva samples.ResultsA total of 138 pairs of saliva samples and corresponding RAT results were collected from 34 COVID-19 patients. Positivity of RAT and cell culture was 27% (37/138) and 12% (16/138), respectively. Of the 16 culture-positive saliva samples, seven (43.8%) corresponding RAT results were positive. Using cell culture as the reference standard, the overall percent agreement, percent positive agreement, and percent negative agreement of RAT were 71% (95% CI, 63–78), 26% (95% CI, 12–42), and 82% (95% CI, 76–87), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the RAT for predicting culture results were 44% (95% CI, 20–70), 75% (95% CI, 66–82), 18% (95% CI, 8–34), and 91% (95% CI, 84–96), respectively.ConclusionAbout half of the patients who were SARS-CoV-2 positive based upon cell culture results gave negative RAT results. However, the remaining positive culture cases were detected by RAT, and RAT showed relatively high negative predictive value for viable viral shedding.

Here, Kim et al. apply various sequencing techniques (RPF-seq, QTI-seq, mRNA-seq, sRNA-seq) to unravel the high-resolution, longitudinal translatome and transcriptome of SARS-CoV-2. They identify a translation initiation site in the leader sequence of all genomic and subgenomic RNAs and show its relevance for the SARS-CoV-2 translatome.

With the increasing importance of environmental protection, high-performance biopolymer films have received considerable attention as effective alternatives to petroleum-based polymer films. In this study, we developed hydrophobic regenerated cellulose (RC) films with good barrier properties through a simple gas–solid reaction via the chemical vapor deposition of alkyltrichlorosilane. RC films were employed to construct a biodegradable, free-standing substrate matrix, and methyltrichlorosilane (MTS) was used as a hydrophobic coating material to control the wettability and improve the barrier properties of the final films. MTS readily coupled with hydroxyl groups on the RC surface through a condensation reaction. We demonstrated that the MTS-modified RC (MTS/RC) films were optically transparent, mechanically strong, and hydrophobic. In particular, the obtained MTS/RC films exhibited a low oxygen transmission rate of 3 cm3/m2 per day and a low water vapor transmission rate of 41 g/m2 per day, which are superior to those of other hydrophobic biopolymer films.

Abstract Gold particles have been widely used in the treatment of prostate cancer due to their unique optical properties, such as their light-heat conversion in response to near-infrared radiation. Due to well-defined synthesis mechanisms and simple manufacturing methods, gold particles have been fabricated in various sizes and shapes. However, the low photothermal transduction efficiency in their present form is a major obstacle to practical and therapeutic uses of these particles. In the current work, we present a silica-coated gold nanoparticle cluster to address the therapeutic limit of single gold nanoparticles (AuNPs) and use its photothermal effect for treatment against PC-3, a typical prostate cancer. Due to its specific nanostructure, this gold nanocluster showed three times higher photothermal transduction efficiency than free single AuNPs. Moreover, while free single particles easily clump and lose optical properties, this silica-coated cluster form remained stable for a longer time in a given medium. In photothermal tests under near-infrared radiation, the excellent therapeutic efficacy of gold nanoclusters, referred to as AuNC@SiO2, was observed in a preclinical sample. Only the samples with both injected nanoclusters followed by photothermal treatment showed completely degraded tumors after 15 days. Due to the unique intrinsic biocompatibility and higher therapeutic effect of these silica-coated gold nanoclusters, they may contribute to enhancement of therapeutic efficacy against prostate cancer.

Yttria-stabilized zirconia (YSZ) nanospheres were synthesized by calcination at 900 °C after the adsorption of Y3+ ions into the pores of a zirconium-based metal–organic framework (MOF). The synthesized 3YSZ (zirconia doped with 3 mol% Y2O3), 8YSZ (8 mol% Y2O3), and 30YSZ (30 mol% Y2O3) nanospheres were found to exhibit uniform sizes and shapes. Complex permittivity and complex permeability were carried out in K-band (i.e., 18–26.5 GHz) to determine their suitability for use as low-k materials in 5G communications. The real and imaginary parts of the permittivity of the sintered 3YSZ were determined to be 21.24 and 0.12, respectively, while those of 8YSZ were 22.80 and 0.16, and those of 30YSZ were 7.16 and 0.38. Control of the real part of the permittivity in the sintered YSZ was facilitated by modifying the Y2O3 content, thereby rendering this material an electronic ceramic with potential for use in high-frequency 5G communications due to its excellent mechanical properties, high chemical resistance, and good thermal stability. In particular, it could be employed as an exterior material for electronic communication products requiring the minimization of information loss.

Since the coronavirus disease outbreak in 2019, several antibody therapeutics have been developed to treat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Antibody therapeutics are effective in neutralizing the virus and reducing hospitalization in patients with mild and moderate infections. These therapeutics target the spike protein of SARS-CoV-2; however, emerging mutations in this protein reduce their efficiency. In this study, we developed a universal SARS-CoV-2 neutralizing antibody. We generated a humanized monoclonal antibody, MG1141A, against the receptor-binding domain of the spike protein through traditional mouse immunization. We confirmed that MG1141A could effectively neutralize live viruses, with an EC50 of 92 pM, and that it exhibited effective Fc-mediated functions. Additionally, it retained its neutralizing activity against the alpha (UK), beta (South Africa), and gamma (Brazil) variants of SARS-CoV-2. Taken together, our study contributes to the development of a novel antibody therapeutic approach, which can effectively combat emerging SARS-CoV-2 mutations.

The wide range of oxygen-containing functional groups on the basal planes and edges of graphene oxide (GO) facilitate the anchoring of active metal ions on its surface. Previously, we have shown that these active centers allow the in situ crystallization of cyano-bridged Ni-based coordination polymers (Ni-CP) as nanoflakes on the surface of GO sheets (Angew. Chem. Int. Ed., 2016, 55, 8426). Here, in this work, by extending our previous concept, we demonstrate that Ni-CP-coated GO sheets can be made to self-assemble to form various multi-layered hybrid structures (Ni-CP/GO) by controlling the composition ratios. Ni3C/rGO with the original morphology was successfully prepared by converting the Ni-CP to Ni3C in the space between the graphene sheets by thermal treatment in an inert atmosphere. The electrochemical analyses reveal that the optimized Ni3C/rGO hybrid exhibits superior electrocatalytic performance for the oxygen reduction reaction (ORR) with good durability and stability. Keywords: Graphene oxide, Ni3C, Self-assembly, Hybrids, Electrocatalysts

Neural networks trained using images with a certain type of distortion should be better at classifying test images with the same type of distortion than generally-trained neural networks, given other factors being equal. Based on this observation, an ensemble of convolutional neural networks (CNNs) trained with different types and degrees of distortions is used. However, instead of simply classifying test images of unknown distortion types with the entire ensemble of CNNs, an extra tiny CNN is specifically trained to distinguish between the different types and degrees of distortions. Then, only the dedicated CNN for that specific type and degree of distortion, as determined by the tiny CNN, is activated and used to classify a possibly distorted test image. This proposed architecture, referred to as a selective deep convolutional neural network (DCNN), is implemented and found to result in high accuracy with low hardware costs. Detailed simulations with realistic image distortion scenarios using three popular datasets show that memory, MAC operations, and energy savings of up to 93.68%, 93.61%, and 91.92%, respectively, can be achieved with almost no reduction in image classification accuracy. The proposed selective DCNN scores up to $2.18\times $ higher than the state-of-the-art DCNN model when evaluated using NetScore, a comprehensive metric that considers both CNN performance and hardware cost. In addition, it is shown that even higher hardware cost reduction can be achieved when selective DCNN is combined with previously proposed model compression techniques. Finally, experiments conducted with extended types and degrees of image distortion show that selective DCNN is highly scalable.

Zoonotic avian influenza viruses pose severe health threats to humans. Of several viral subtypes reported, the low pathogenic avian influenza H7N9 virus has since February 2013 caused more than 1,500 cases of human infection with an almost 40% case-fatality rate. Vaccination of poultry appears to reduce human infections. However, the emergence of highly pathogenic strains has increased concerns about H7N9 pandemics. To develop an efficacious H7N9 human vaccine, we designed vaccine viruses by changing the patterns of N-linked glycosylation (NLG) on the viral hemagglutinin (HA) protein based on evolutionary patterns of H7 HA NLG changes. Notably, a virus in which 2 NLG modifications were added to HA showed higher growth rates in cell culture and elicited more cross-reactive antibodies than did other vaccine viruses with no change in the viral antigenicity. Developed into an inactivated vaccine formulation, the vaccine virus with 2 HA NLG additions exhibited much better protective efficacy against lethal viral challenge in mice than did a vaccine candidate with wild-type (WT) HA by reducing viral replication in the lungs. In a ferret model, the 2 NLG-added vaccine viruses also induced hemagglutination-inhibiting antibodies and significantly suppressed viral replication in the upper and lower respiratory tracts compared with the WT HA vaccines. In a mode of action study, the HA NLG modification appeared to increase HA protein contents incorporated into viral particles, which would be successfully translated to improve vaccine efficacy. These results suggest the strong potential of HA NLG modifications in designing avian influenza vaccines.

In recent years, conjugated microporous polymers (CMPs) have become important precursors for environmental and energy applications, compared with inorganic electrode materials, due to their ease of preparation, facile charge storage process, π-conjugated structures, relatively high thermal and chemical stability, abundance in nature, and high surface areas. Therefore, in this study, we designed and prepared new benzobisthiadiazole (BBT)-linked CMPs (BBT–CMPs) using a simple Sonogashira couplings reaction by reaction of 4,8-dibromobenzo(1,2-c;4,5-c′)bis(1,2,5)thiadiazole (BBT–Br2) with ethynyl derivatives of triphenylamine (TPA-T), pyrene (Py-T), and tetraphenylethene (TPE-T), respectively, to afford TPA–BBT–CMP, Py–BBT–CMP, and TPE–BBT–CMP. The chemical structure and properties of BBT–CMPs such as surface areas, pore size, surface morphologies, and thermal stability using different measurements were discussed in detail. Among the studied BBT–CMPs, we revealed that TPE–BBT–CMP displayed high degradation temperature, up to 340 °C, with high char yield and regular, aggregated sphere based on thermogravimetric analysis (TGA) and scanning electron microscopy (SEM), respectively. Furthermore, the Py–BBT–CMP as organic electrode showed an outstanding specific capacitance of 228 F g−1 and superior capacitance stability of 93.2% (over 2000 cycles). Based on theoretical results, an important role of BBT–CMPs, due to their electronic structure, was revealed to be enhancing the charge storage. Furthermore, all three CMP polymers featured a high conjugation system, leading to improved electron conduction and small bandgaps.

Abstract 2D materials, specifically MoS2 semiconductors, have received tremendous attention for photo‐sensing applications due to their tunable bandgap and low noise levels. A unique photodetector using multilayer MoS2 as the semiconductor channel, in which the gate electrode of the device is permanently connected to the grounded source electrode to introduce rectification, is reported. The proposed grounded‐gate photodiode exhibits high photoresponsivity of 1.031 A W−1, excellent photodetectivity (>6 × 1010 jones), and highly stable rise/fall time response (100–200 ms) under illumination of visible light (at the wavelengths of 405, 532, and 638 nm). Numerical device simulations using quantum transport methods and photoconductive effects are used to explain the device operation. It is also suggested that the gate metal work function can be carefully chosen to increase the sensitivity of the grounded‐gate photodetector by suppressing the dark current. The grounded‐gate device proposed, owing to the properties of rectifying behavior, low contact resistance, consistent photoresponsivity, and linear sensitivity, provides a new platform for next‐generation applications in the field of electronics and optoelectronics.

Synthesis of the polycrystalline Ba2-xSrxNi2(Fe1-yAly)12O22 (x = 0.0, 1.5, y = 0.00, 0.01, and 0.03) was accomplished by employing the polymerizable complex method. The samples were investigated for the crystallographic and magnetic properties by x-ray diffraction (XRD), vibrating sample magnetometer (VSM), and Mössbauer spectrometer. Based on the results of the refined XRD patterns, all samples were confirmed to have a rhombohedral structure with space group R-3m. Moreover, six distinguished sublattices were identified, which were four octahedral sites (18hVI, 3bVI, 6cVI, and 3aVI) and two tetrahedral sites (6cIV*, 6cIV). The lattice constant of a0 and c0 decrease via Sr, Al substitution because the ionic radius of Sr2+ (1.12 Å) is smaller than that of Ba2+ (1.34 Å), and the ionic radius of Al3+ (0.535 Å) is smaller than that of Fe3+ (0.645 Å). The zero-field-cooled (ZFC) measurement was applied at 100 Oe between 4.2 and 295 K and it revealed the spin transition temperature (TS). Substitution of Sr ions increased TS. Al ions were further substituted after the substitution of Sr ions, and TS increased above room temperature. The Mössbauer spectra fit six distinguish sublattices: 18hVI, 3bVI, 6cIV, 6cIV*, 6cVI, and 3aVI. The isomer shift of all samples indicated that the charge state of Fe ions is Fe3+. The Mössbauer spectra obtained with respect to temperature change confirmed the changes in the magnetic hyperfine field curves at Ts.

Fe1-xMgxPO4 (x = 0.01, 0.05, and 0.1) cathode materials are synthesized by a two-step method, which combines the solid-state reaction method and the chemical lithium deintercalation method. A study was conducted to investigate the structural and the magnetic properties of Fe1-xMgxPO4. The crystalline structure of the samples was analyzed by X-ray diffractometer (XRD) using the Rietveld refinement. The magnetic properties of the samples were determined from vibrating sample magnetometer (VSM) and Mösssbauer spectroscopy, including their magnetic interactions, Fe ion states, and structural ordering. The Néel temperature (TN) of Fe1-xMgxPO4 decreases with the increase of the Mg content due to the weakening of the antiferromagnetic exchange. Furthermore, for Fe1-xMgxPO4, the effective moment value decreases as expected with increasing Mg content. Mössbauer spectroscopy measurements at different temperatures were made. The spectrum at 295 K was fitted with a doublet, which has an isomer shift of δ = 0.32 – 0.43 mm/s (Fe3+). The large value of the electric quadrupole splitting (∆EQ = 0.95 – 1.87 mm/s) is explained by the asymmetric local environment of the Fe ions. Below the TN, the spectra of Fe1-xMgxPO4 in the eight resonance absorption lines (including two relatively small intensities) were analyzed. We can obtain a spin value for Fe ions (S = 5/2) of Fe0.9Mg0.1PO4 from the Brillouin functional analysis.

Rapid and accurate measurement of SARS-CoV-2 neutralizing antibodies (nAbs) can aid in understanding the development of immunity against COVID-19. This study evaluated the diagnostic performance of a rapid SARS-CoV-2 nAb detection test called the BZ COVID-19 nAb test BZ-nAb (BZ-nAb; BioZentech). Using the 90% plaque-reduction neutralization test (PRNT-90) as a reference, 104 serum specimens collected from COVID-19-positive and -negative patients were grouped into 40 PRNT-90-positive and 64 PRNT-90-negative specimens. The performance of the BZ-nAb was compared with that of the cPass surrogate virus neutralization test (cPass sVNT; Genscript). The BZ-nAb showed a sensitivity ranging from 92.5%–95.0% and specificity ranging from 96.9%–100%, whereas cPass sVNT showed a sensitivity of 100% (95% confidence interval (CI) 90.5%–100%) and specificity of 98.4% (95% CI, 91.6%–100%). The dilution factor obtained with PRNT-90 showed a stronger correlation with the percent inhibition of cPass sVNT (r = 0.8660, p < 0.001) compared with the test and control line ratio (T/C ratio) of the BZ-nAb (r = −0.7089, p < 0.001). An almost perfect agreement was seen between the BZ-nAb and cPass sVNT results, with a strong negative correlation between the BZ-nAb T/C ratio and cPass sVNT percent inhibition (r = −0.8022, p < 0.001). In conclusion, the diagnostic performance of the BZ-nAb was comparable to that of the cPass sVNT, although the BZ-nAb had a slightly lower sensitivity.

A variety of nanostructured diagnostic tools have been developed for the precise detection of known genetic variants. Molecular beacon systems are very promising tools due to their specific selectivity coupled with relatively lower cost and time requirements than existing molecular detection tools such as next generation sequencing or real-time PCR (polymerase chain reaction). However, they are prone to errors induced by secondary structure responses to environmental fluctuations, such as temperature and pH. Herein, we report a temperature-insensitive, bead-immobilized, molecular beacon-equipped novel DNA nanostructure for detection of cancer miRNA variants with the consideration of thermodynamics. This system consists of three parts: a molecular beacon for cancer-specific RNA capture, a stem body as a core template, and a single bead for solid-support. This DNA system was selectively bound to nanosized beads using avidin–biotin chemistry. Synthetic DNA nanostructures, designed based on the principle of fluorescence-resonance enhanced transfer, were effectively applied for in vitro cancer-specific RNA detection. Several parameters were optimized for higher performance, with a focus on thermodynamic stability. Theoretical issues regarding the secondary structure of a single molecular beacon and its combinatory forms were also studied. This study provides design guidelines for new sensing systems of miRNA variation for next-generation biotechnological applications.

Abstract Background A robotic exoskeleton device is an intelligent system designed to improve gait performance and quality of life for the wearer. Robotic technology has developed rapidly in recent years, and several robot-assisted gait devices were developed to enhance gait function and activities of daily living in elderly adults and patients with gait disorders. In this study, we investigated the effects of the Gait-enhancing Mechatronic System (GEMS), a new wearable robotic hip-assist device developed by Samsung Electronics Co, Ltd., Korea, on gait performance and foot pressure distribution in elderly adults. Methods Thirty elderly adults who had no neurological or musculoskeletal abnormalities affecting gait participated in this study. A three-dimensional (3D) motion capture system, surface electromyography and the F-Scan system were used to collect data on spatiotemporal gait parameters, muscle activity and foot pressure distribution under three conditions: free gait without robot assistance (FG), robot-assisted gait with zero torque (RAG-Z) and robot-assisted gait (RAG). Results We found increased gait speed, cadence, stride length and single support time in the RAG condition. Reduced rectus femoris and medial gastrocnemius muscle activity throughout the terminal stance phase and reduced effort of the medial gastrocnemius muscle throughout the pre-swing phase were also observed in the RAG condition. In addition, walking with the assistance of GEMS resulted in a significant increase in foot pressure distribution, specifically in maximum force and peak pressure of the total foot, medial masks, anterior masks and posterior masks. Conclusion The results of the present study reveal that GEMS may present an alternative way of restoring age-related changes in gait such as gait instability with muscle weakness, reduced step force and lower foot pressure in elderly adults. In addition, GEMS improved gait performance by improving push-off power and walking speed and reducing muscle activity in the lower extremities. Trial registration NCT02843828 .

Abstract Hydrogel-based flexible microelectrodes have garnered considerable attention recently for soft bioelectronic applications. We constructed silver nanowire (AgNW) micropatterns on various substrates, via a simple, cost-effective, and eco-friendly method without aggressive etching or lift-off processes. Polyethylene glycol (PEG) photolithography was employed to construct AgNW patterns with various shapes and sizes on the glass substrate. Based on a second hydrogel gelation process, AgNW patterns on glass substrate were directly transferred to the synthetic/natural hydrogel substrates. The resultant AgNW micropatterns on the hydrogel exhibited high conductivity (ca. 8.40 × 103 S cm−1) with low sheet resistance (7.51 ± 1.11 Ω/sq), excellent bending durability (increases in resistance of only ~3 and ~13% after 40 and 160 bending cycles, respectively), and good stability in wet conditions (an increase in resistance of only ~6% after 4 h). Considering both biocompatibility of hydrogel and high conductivity of AgNWs, we anticipate that the AgNW micropatterned hydrogels described here will be particularly valuable as highly efficient and mechanically stable microelectrodes for the development of next-generation bioelectronic devices, especially for implantable biomedical devices.

Electron-doped SrTiO3 is a well-known n-type thermoelectric material, although the figure of merit of SrTiO3 is still inferior compared with p-type metal oxide-based thermoelectric materials due to its high lattice thermal conductivity. In this study, we have used a different amount of the non-ionic surfactant F127 during sample preparation to introduce nanoscale porosities into bulk samples of La-doped SrTiO3. It has been observed that the porosities introduced into the bulk sample significantly improve the Seebeck coefficient and reduce the thermal conductivity by the charge carrier and phonon scattering respectively. Therefore, there is an overall enhancement in the power factor (PF) followed by a dimensionless figure of merit (zT) over a wide scale of temperature. The sample 20 at% La-doped SrTiO3 with 600 mg of F127 surfactant (SLTO 600F127) shows the maximum PF of 1.14 mW m−1 K−2 at 647 K which is 35% higher than the sample without porosity (SLTO 0F127), and the same sample (SLTO 600F127) shows the maximum value of zT is 0.32 at 968 K with an average enhancement of 62% in zT in comparison with the sample without porosity (SLTO 0F127).

Abstract To sustainably satisfy the growing demand for energy, organic carbonyl compounds (OCCs) are being widely studied as electrode active materials for batteries owing to their high capacity, flexible structure, low cost, environmental friendliness, renewability, and universal applicability. However, their high solubility in electrolytes, limited active sites, and low conductivity are obstacles in increasing their usage. Here, the nucleophilic addition reaction of aromatic carbonyl compounds (ACCs) is first used to explain the electrochemical behavior of carbonyl compounds during charge–discharge, and the relationship of the molecular structure and electrochemical properties of ACCs are discussed. Strategies for molecular structure modifications to improve the performance of ACCs, i.e., the capacity density, cycle life, rate performance, and voltage of the discharge platform, are also elaborated. ACCs, as electrode active materials in aqueous solutions, will become a future research hotspot. ACCs will inevitably become sustainable green materials for batteries with high capacity density and high power density.

Background: In a clinical setting, an individual subject classification model rather than a group analysis would be more informative. Specifically, the subtlety of cortical atrophy in some frontotemporal dementia (FTD) patients and overlapping patterns of atrophy among three FTD clinical syndromes including behavioral variant FTD (bvFTD), non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA) give rise to the need for classification models at the individual level. In this study, we aimed to classify each individual subject into one of the diagnostic categories in a hierarchical manner by employing a machine learning-based classification method. Methods: We recruited 143 patients with FTD, 50 patients with Alzheimer's disease (AD) dementia, and 146 cognitively normal subjects. All subjects underwent a three-dimensional volumetric brain magnetic resonance imaging (MRI) scan, and cortical thickness was measured using FreeSurfer. We applied the Laplace Beltrami operator to reduce noise in the cortical thickness data and to reduce the dimension of the feature vector. Classifiers were constructed by applying both principal component analysis and linear discriminant analysis to the cortical thickness data. For the hierarchical classification, we trained four classifiers using different pairs of groups: Step 1 - CN vs. FTD + AD, Step 2 - FTD vs. AD, Step 3 - bvFTD vs. PPA, Step 4 - svPPA vs. nfvPPA. To evaluate the classification performance for each step, we used a10-fold cross-validation approach, performed 1000 times for reliability. Results: The classification accuracy of the entire hierarchical classification tree was 75.8%, which was higher than that of the non-hierarchical classifier (73.0%). The classification accuracies of steps 1–4 were 86.1%, 90.8%, 86.9%, and 92.1%, respectively. Changes in the right frontotemporal area were critical for discriminating behavioral variant FTD from PPA. The left frontal lobe discriminated nfvPPA from svPPA, while the bilateral anterior temporal regions were critical for identifying svPPA. Conclusions: In the present study, our automated classifier successfully classified FTD clinical subtypes with good to excellent accuracy. Our classifier may help clinicians diagnose FTD subtypes with subtle cortical atrophy and facilitate appropriate specific interventions. Keywords: Frontotemporal dementia, Classification model, Machine learning

Cellulose nanofiber (CNF) and hybrid zeolite imidazole framework (HZ) are an emerging biomaterial and a porous carbonous material, respectively. The composite of these two materials could have versatile physiochemical characteristics. A cellulose nanofiber and cobalt-containing zeolite framework-based composite was prepared using an in-situ and eco-friendly chemical method followed by pyrolysis. The composite was comprised of cobalt nanoparticles decorated on highly graphitized N-doped nanoporous carbons (NPC) wrapped with carbon nanotubes (CNTs) produced from the direct carbonization of HZ. By varying the ratio of CNF in the composite, we determined the optimal concentration and characterized the derived samples using sophisticated techniques. Scanning electron microscopy (SEM), X-ray diffraction analysis (XRD), and X-ray photoelectron spectroscopy (XPS) confirmed the functionalization of CNF in the metallic cobalt-covered N-doped NPC wrapped with CNTs. The CNF–HZNPC composite electrodes show superior electrochemical performance, which is suitable for supercapacitor applications; its specific capacitance is 146 F/g at 1 A/g. Furthermore, the composite electrodes retain a cycling stability of about 90% over 2000 charge–discharge cycles at 10 A/g. The superior electrochemical properties of the cellulose make it a promising candidate for developing electrodes for energy storage applications.

A binder-free process for the electrode preparation for supercapacitor application was suggested by drop casting graphene nanoplatelets on a carbon fiber (GnP@CF) followed by electrodeposition of Ni nanoparticles (NPs). The microstructure of the electrode showed that Ni was homogeneously distributed over the surface of the GnP@CF. XRD analysis confirmed the cubic structure of metallic Ni NPs. The Ni-GnP@CF electrode showed excellent pseudocapacitive behavior in alkaline solution by exhibiting a specific capacitance of 480 F/g at 1.0 A/g, while it was 375 F/g for Ni@CF. The low value of series resistance of Ni-GnP@CF (1 Ω) was attributed to the high capacitance. The enhanced capacitance of the electrode could be correlated to the highly nanoporous structure of the composite material, synergetic effect of the electrical double layer charge-storage properties of graphene, and the pseudocapacitive nature of Ni NPs.

Molybdenum disulfide (MoS2) has attracted considerable attention as a promising electrocatalyst for the hydrogen evolution reaction (HER). However, the catalytic HER performance of MoS2 is significantly limited by the few active sites and low electrical conductivity. In this study, the growth of multiorientated polycrystalline MoS2 using plasma-enhanced chemical vapor deposition (PECVD) for the HER is achieved. The MoS2 is synthesized by sulfurizing a sputtered pillar-shaped Mo film. The relatively low growth temperature during the PECVD process results in multiorientated MoS2 with an expanded interlayer spacing of ~0.75 nm, which provides abundant active sites, a reduced Gibbs free energy of H adsorption, and enhanced intralayer conductivity. In HER applications, the PECVD-grown MoS2 exhibits an overpotential value of 0.45 V, a Tafel slope of 76 mV dec−1, and excellent stability in strong acidic media for 10 h. The high HER performance achieved in this study indicates that two-dimensional MoS2 has potential as an electrocatalyst for next-generation energy technologies.

The past decade has been especially creative for nanogenerators as energy harvesting devices utilizing both piezoelectric and triboelectric properties. Most recently, self-charging power units using both nanogenerators and energy storage systems have begun to be investigated for portable and wearable electronics to be used in our daily lives. This review focuses on these hybrid devices with self-charging combined with energy harvesting storage systems based on the most recent reports. In this research update, we will describe the materials, device structures, integration, applications, and research progress up to the present on hybrid devices.

ObjectivesMobile healthcare applications are becoming a growing trend. Also, the prevalence of dementia in modern society is showing a steady growing trend. Among degenerative brain diseases that cause dementia, Alzheimer disease (AD) is the most common. The purpose of this study was to identify AD patients using magnetic resonance imaging in the mobile environment.MethodsWe propose an incremental classification for mobile healthcare systems. Our classification method is based on incremental learning for AD diagnosis and AD prediction using the cortical thickness data and hippocampus shape. We constructed a classifier based on principal component analysis and linear discriminant analysis. We performed initial learning and mobile subject classification. Initial learning is the group learning part in our server. Our smartphone agent implements the mobile classification and shows various results.ResultsWith use of cortical thickness data analysis alone, the discrimination accuracy was 87.33% (sensitivity 96.49% and specificity 64.33%). When cortical thickness data and hippocampal shape were analyzed together, the achieved accuracy was 87.52% (sensitivity 96.79% and specificity 63.24%).ConclusionsIn this paper, we presented a classification method based on online learning for AD diagnosis by employing both cortical thickness data and hippocampal shape analysis data. Our method was implemented on smartphone devices and discriminated AD patients for normal group.

Mesoporous TiO2 is attracting increasing interest due to properties suiting a broad range of photocatalytic applications. Here we report the facile synthesis of mesoporous crystalline TiO2-B nanobelts possessing a surface area as high as 80.9 m2 g−1 and uniformly-sized pores of 6−8 nm. Firstly, P25 powders are dissolved in NaOH solution under hydrothermal conditions, forming sodium titanate (Na2Ti3O7) intermediate precursor phase. Then, H2Ti3O7 is successfully obtained by ion exchange through acid washing from Na2Ti3O7 via an alkaline hydrothermal treatment. After calcination at 450 °C, the H2Ti3O7 is converted to a TiO2-B phase. At 600 °C, another anatase phase coexists with TiO2-B, which completely converts into anatase when annealed at 750 °C. Mesoporous TiO2-B nanobelts obtained after annealing at 450 °C are uniform with up to a few micrometers in length, 50−120 nm in width, and 5−15 nm in thickness. The resulting mesoporous TiO2-B nanobelts exhibit efficient H2 evolution capability, which is almost three times that of anatase TiO2 nanobelts.

In this paper, we report the fabrication of highly conductive poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS)/cellulose nanofiber (CNF) nanocomposite paper with excellent flexibility through post-treatment with an organic solvent. The post-treated PEDOT:PSS/CNF porous nanocomposite papers showed a lower sulfur content, indicating the removal of residual PSS. The electrical conductivity of PEDOT:PSS/CNF porous nanocomposite paper was increased from 1.05 S/cm to 123.37 S/cm and 106.6 S/cm by post-treatment with dimethyl sulfoxide (DMSO) and ethylene glycol (EG), respectively. These values are outstanding in the development of electrically conductive CNF composites. Additionally, the highly conductive nanocomposite papers showed excellent bending stability during bending tests. Cyclic voltammetry (CV) showed a Faradaic redox reaction and non-Faradaic capacitance due to the redox activity of PEDOT:PSS and large surface area, respectively. Electrochemical energy storage ability was evaluated and results showed that capacitance improved after post-treatment. We believe that the highly conductive PEDOT:PSS/CNF porous nanocomposite papers with excellent flexibility described here are potential candidates for application in porous paper electrodes, flexible energy storage devices, and bioengineering sensors.

Herein, we demonstrate the bottom-up synthesis of 2D cyano-bridged Cu-Ni coordination polymer (CP) nanoflakes through a controlled crystallization process and their conversion to Cu-Ni mixed oxides via a thermal treatment in air. The chelating effect of citrate anions effectively prevents the rapid coordination reaction between Cu2+ and K2[Ni(CN)4], resulting in the deceleration of the crystallization process of CPs. Specifically, with addition of trisodium citrate dehydrate, the number of nuclei formed at the early stage of the reaction is decreased. Less nuclei undergo a crystal growth by interacting with [Ni(CN)4]2−, leading to the formation of larger Cu-Ni CP nanoflakes. Following heat treatment in air, the -CN- groups present within the CP nanoflakes are removed and nanoporous Cu-Ni mixed oxide nanoflakes are generated. When tested as an electrode material for supercapacitors using a three-electrode system, the optimum Cu-Ni mixed oxide sample shows a maximum specific capacitance of 158 F g−1 at a current density of 1 A g−1. It is expected that the proposed method will be useful for the preparation of other types of 2D and 3D CPs as precursors for the creation of various nanoporous metal oxides.

Stable polymeric micelles have been demonstrated to serve as suitable templates for creating mesoporous metals. Herein, we report the utilization of a core-shell-corona type triblock copolymer of poly(styrene-b-2-vinylpyridine-b-ethylene oxide) and H2PtCl6·H2O to synthesize large-sized mesoporous Pt particles. After formation of micelles with metal ions, the reduction process has been carried out by vapor infiltration of a reducing agent, 4-(Dimethylamino)benzaldehyde. Following the removal of the pore-directing agent under the optimized temperature, mesoporous Pt particles with an average pore size of 15 nm and surface area of 12.6 m2·g−1 are achieved. More importantly, the resulting mesoporous Pt particles exhibit superior electrocatalytic activity compared to commercially available Pt black.

Subcortical vascular dementia (SVaD), one of common causes of dementia, has concomitant Alzheimer's disease (AD) pathology in over 30%, termed "mixed dementia". Identifying mixed dementia from SVaD is important because potential amyloid-targeted therapies may be effective for treatment in mixed dementia. The purpose of this study was to discriminate mixed dementia from pure SVaD using magnetic resonance imaging (MRI). We measured brain amyloid deposition using the 11C-Pittsburgh compound B positron emission tomography (PiB-PET) in 68 patients with SVaD. A PiB retention ratio greater than 1.5 was considered PiB(+). Hippocampal and amygdalar shape were used in the incremental learning method to discriminate mixed dementia from pure SVaD because these structures are known to be prominently involved by AD pathologies. Among 68 patients, 23 (33.8%) patients were positive for PiB binding. With use of hippocampal shape analysis alone, PiB(+) SVaD could be discriminated from PiB(-) SVaD with 77.9% accuracy (95.7% sensitivity and 68.9% specificity). With use of amygdalar shape, the discrimination accuracy was 75.0% (87.0% sensitivity and 68.9% specificity). When hippocampal and amygdalar shape were analyzed together, accuracy increased to 82.4% (95.7% sensitivity and 75.6% specificity). An incremental learning method using hippocampal and amygdalar shape distinguishes mixed dementia from pure SVaD. Furthermore, our results suggest that amyloid pathology and vascular pathology have different effects on the shape of the hippocampus and amygdala.