Enhanced stability of boron modified NiFe hydroxide for oxygen evolution reaction.

The introduction of non-metal elements including boron has been identified as a significant means to enhance oxygen evolution reaction (OER) performance in NiFe-based catalysts. To understand the catalytic activity and stability, recent attention has widened toward the Fe species as a potential contributor, prompting exploration from various perspectives. Here, boron incorporation in NiFe hydroxide achieves significantly enhanced activity and stability compared to the boron-free NiFe hydroxide. The boron inclusion in NiFe hydroxide is found to show exceptionally improved stability from 12 to 100 hours at a high current density (200 mA cm-2). It facilitates the production and redeposition of OER-active, high-valent Fe species in NiFe hydroxide based on the operando Raman, UV-vis, and X-ray absorption spectroscopy analysis. It is proposed that preserving a homogenous distribution of Fe across the boron-containing catalyst surface enhances OER stability, unlike the bare NiFe hydroxide electrocatalyst, which exhibits uneven Fe dissolution, confirmed through elementary mapping analysis. These findings shed light on the potential of anionic regulation to augment the activity of iron, an aspect not previously explored in depth, and thus are expected to aid in designing practical OER electrocatalysts.

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.

Probing Cation Effects on *CO Intermediates from Electroreduction of CO2 through Operando Raman Spectroscopy.

Cations in an electrolyte modulate microenvironments near the catalyst surface and affect product distribution from an electrochemical CO2 reduction reaction, and thus, their interaction with intermediate states has been tried to be probed. Herein, we directly observed the cation effect on *CO intermediates on the Cu(OH)2-derived catalyst in real time through operando surface-enhanced Raman spectroscopy at high overpotentials (-1.0 VRHE). Atop *CO peaks are composed of low-frequency binding *CO (*COLFB) and high-frequency binding *CO (*COHFB) because of their adsorption sites. These two *CO intermediates are found to have different sensitivities to the cation-induced field, and each *CO is proposed to be suitably stabilized for efficient C-C coupling. The proportions between *COHFB and *COLFB are dependent on the type of alkali cations, and the increases in the *COHFB ratio have a high correlation with selective C2H4 production under K+ and Cs+, indicating that *COHFB is the dominant and fast active species. In addition, as the hydrated cation size decreases, *COLFB is more sensitively red-shifted than *COHFB, which promotes C-C coupling and suppresses C1 products. Through time-resolved operando measurements, dynamic changes between the two *CO species are observed, showing the rapid initial adsorption of *COHFB and subsequently reaching a steady ratio between *COLFB and *COHFB.

Electro-assisted methane oxidation to formic acid via in-situ cathodically generated H2O2 under ambient conditions.

Direct partial oxidation of methane to liquid oxygenates has been regarded as a potential route to valorize methane. However, CH4 activation usually requires a high temperature and pressure, which lowers the feasibility of the reaction. Here, we propose an electro-assisted approach for the partial oxidation of methane, using in-situ cathodically generated reactive oxygen species, at ambient temperature and pressure. Upon using acid-treated carbon as the electrocatalyst, the electro-assisted system enables the partial oxidation of methane in an acidic electrolyte to produce oxygenated liquid products. We also demonstrate a high production rate of oxygenates (18.9 µmol h-1) with selective HCOOH production. Mechanistic analysis reveals that reactive oxygen species such as ∙OH and ∙OOH radicals are produced and activate CH4 and CH3OH. In addition, unstable CH3OOH generated from methane partial oxidation can be additionally reduced to CH3OH on the cathode, and so-produced CH3OH is further oxidized to HCOOH, allowing selective methane partial oxidation.

Vorinostat-induced acetylation of RUNX3 reshapes transcriptional profile through long-range enhancer-promoter interactions in natural killer cells.

Natural killer (NK) cells are an essential part of the innate immune system that helps control infections and tumors. Recent studies have shown that Vorinostat, a histone deacetylase (HDAC) inhibitor, can cause significant changes in gene expression and signaling pathways in NK cells. Since gene expression in eukaryotic cells is closely linked to the complex three-dimensional (3D) chromatin architecture, an integrative analysis of the transcriptome, histone profiling, chromatin accessibility, and 3D genome organization is needed to gain a more comprehensive understanding of how Vorinostat impacts transcription regulation of NK cells from a chromatin-based perspective. The results demonstrate that Vorinostat treatment reprograms the enhancer landscapes of the human NK-92 NK cell line while overall 3D genome organization remains largely stable. Moreover, we identified that the Vorinostat-induced RUNX3 acetylation is linked to the increased enhancer activity, leading to elevated expression of immune response-related genes via long-range enhancerpromoter chromatin interactions. In summary, these findings have important implications in the development of new therapies for cancer and immune-related diseases by shedding light on the mechanisms underlying Vorinostat's impact on transcriptional regulation in NK cells within the context of 3D enhancer network. [BMB Reports 2023; 56(7): 398-403].

Deep Learning Accelerators' Configuration Space Exploration Effect on Performance and Resource Utilization: A Gemmini Case Study.

Though custom deep learning (DL) hardware accelerators are attractive for making inferences in edge computing devices, their design and implementation remain a challenge. Open-source frameworks exist for exploring DL hardware accelerators. Gemmini is an open-source systolic array generator for agile DL accelerator exploration. This paper details the hardware/software components generated using Gemmini. The general matrix-to-matrix multiplication (GEMM) of different dataflow options, including output/weight stationary (OS/WS), was explored in Gemmini to estimate the performance relative to a CPU implementation. The Gemmini hardware was implemented on an FPGA device to explore the effect of several accelerator parameters, including array size, memory capacity, and the CPU/hardware image-to-column (im2col) module, on metrics such as the area, frequency, and power. This work revealed that regarding the performance, the WS dataflow offered a speedup of 3× relative to the OS dataflow, and the hardware im2col operation offered a speedup of 1.1× relative to the operation on the CPU. For hardware resources, an increase in the array size by a factor of 2 led to an increase in both the area and power by a factor of 3.3, and the im2col module led to an increase in area and power by factors of 1.01 and 1.06, respectively.

CTCF controls three-dimensional enhancer network underlying the inflammatory response of bone marrow-derived dendritic cells.

Dendritic cells are antigen-presenting cells orchestrating innate and adaptive immunity. The crucial role of transcription factors and histone modifications in the transcriptional regulation of dendritic cells has been extensively studied. However, it is not been well understood whether and how three-dimensional chromatin folding controls gene expression in dendritic cells. Here we demonstrate that activation of bone marrow-derived dendritic cells induces extensive reprogramming of chromatin looping as well as enhancer activity, both of which are implicated in the dynamic changes in gene expression. Interestingly, depletion of CTCF attenuates GM-CSF-mediated JAK2/STAT5 signaling, resulting in defective NF-κB activation. Moreover, CTCF is necessary for establishing NF-κB-dependent chromatin interactions and maximal expression of pro-inflammatory cytokines, which prime Th1 and Th17 cell differentiation. Collectively, our study provides mechanistic insights into how three-dimensional enhancer networks control gene expression during bone marrow-derived dendritic cells activation, and offers an integrative view of the complex activities of CTCF in the inflammatory response of bone marrow-derived dendritic cells.

Lightweight and Energy-Efficient Deep Learning Accelerator for Real-Time Object Detection on Edge Devices.

Tiny machine learning (TinyML) has become an emerging field according to the rapid growth in the area of the internet of things (IoT). However, most deep learning algorithms are too complex, require a lot of memory to store data, and consume an enormous amount of energy for calculation/data movement; therefore, the algorithms are not suitable for IoT devices such as various sensors and imaging systems. Furthermore, typical hardware accelerators cannot be embedded in these resource-constrained edge devices, and they are difficult to drive real-time inference processing as well. To perform the real-time processing on these battery-operated devices, deep learning models should be compact and hardware-optimized, and hardware accelerator designs also have to be lightweight and consume extremely low energy. Therefore, we present an optimized network model through model simplification and compression for the hardware to be implemented, and propose a hardware architecture for a lightweight and energy-efficient deep learning accelerator. The experimental results demonstrate that our optimized model successfully performs object detection, and the proposed hardware design achieves 1.25× and 4.27× smaller logic and BRAM size, respectively, and its energy consumption is approximately 10.37× lower than previous similar works with 43.95 fps as a real-time process under an operating frequency of 100 MHz on a Xilinx ZC702 FPGA.

Local striatal volume and motor reserve in drug-naïve Parkinson's disease.

Motor reserve (MR) may explain why individuals with similar pathological changes show marked differences in motor deficits in Parkinson's disease (PD). In this study, we investigated whether estimated individual MR was linked to local striatal volume (LSV) in PD. We analyzed data obtained from 333 patients with drug naïve PD who underwent dopamine transporter scans and high-resolution 3-tesla T1-weighted structural magnetic resonance images. Using a residual model, we estimated individual MRs on the basis of initial UPDRS-III score and striatal dopamine depletion. We performed a correlation analysis between MR estimates and LSV. Furthermore, we assessed the effect of LSV, which is correlated with MR estimates, on the longitudinal increase in the levodopa-equivalent dose (LED) during the 4-year follow-up period using a linear mixed model. After controlling for intracranial volume, there was a significant positive correlation between LSV and MR estimates in the bilateral caudate, anterior putamen, and ventro-posterior putamen. The linear mixed model showed that the large local volume of anterior and ventro-posterior putamen was associated with the low requirement of LED initially and accelerated LED increment thereafter. The present study demonstrated that LSV is crucial to MR in early-stage PD, suggesting LSV as a neural correlate of MR in PD.

Contracted thalamic shape is associated with early development of levodopa-induced dyskinesia in Parkinson's disease.

Levodopa-induced dyskinesia (LID), a long-term motor complication in Parkinson's disease (PD), is attributable to both presynaptic and postsynaptic mechanisms. However, no studies have evaluated the baseline structural changes associated with LID at a subcortical level in PD. A total of 116 right-handed PD patients were recruited and based on the LID latency of 5 years, we classified patients into those vulnerable to LID (PD-vLID, n = 49) and those resistant to LID (PD-rLID, n = 67). After adjusting for covariates including dopamine transporter (DAT) availability of the posterior putamen, we compared the subcortical shape between the groups and investigated its association with the onset of LID. The PD-vLID group had lower DAT availability in the posterior putamen, higher parkinsonian motor deficits, and faster increment in levodopa equivalent dose than the PD-rLID group. The PD-vLID group had significant inward deformation in the right thalamus compared to the PD-rLID group. Inward deformation in the thalamus was associated with an earlier onset of LID at baseline. This study suggests that independent of presynaptic dopamine depletion, the thalamus is a major neural substrate for LID and that a contracted thalamic shape at baseline is closely associated with an early development of LID.

CTCF-mediated chromatin looping provides a topological framework for the formation of phase-separated transcriptional condensates.

CTCF is crucial to the organization of mammalian genomes into loop structures. According to recent studies, the transcription apparatus is compartmentalized and concentrated at super-enhancers to form phase-separated condensates and drive the expression of cell-identity genes. However, it remains unclear whether and how transcriptional condensates are coupled to higher-order chromatin organization. Here, we show that CTCF is essential for RNA polymerase II (Pol II)-mediated chromatin interactions, which occur as hyperconnected spatial clusters at super-enhancers. We also demonstrate that CTCF clustering, unlike Pol II clustering, is independent of liquid-liquid phase-separation and resistant to perturbation of transcription. Interestingly, clusters of Pol II, BRD4, and MED1 were found to dissolve upon CTCF depletion, but were reinstated upon restoration of CTCF, suggesting a potent instructive function for CTCF in the formation of transcriptional condensates. Overall, we provide evidence suggesting that CTCF-mediated chromatin looping acts as an architectural prerequisite for the assembly of phase-separated transcriptional condensates.

Liver-Specific Deletion of Mouse CTCF Leads to Hepatic Steatosis via Augmented PPARγ Signaling.

BACKGROUND & AIMS: The liver is the major organ for metabolizing lipids, and malfunction of the liver leads to various diseases. Nonalcoholic fatty liver disease is rapidly becoming a major health concern worldwide and is characterized by abnormal retention of excess lipids in the liver. CCCTC-binding factor (CTCF) is a highly conserved zinc finger protein that regulates higher-order chromatin organization and is involved in various gene regulation processes. Here, we sought to determine the physiological role of CTCF in hepatic lipid metabolism. METHODS: We generated liver-specific, CTCF-ablated and/or CD36 whole-body knockout mice. Overexpression or knockdown of peroxisome proliferator-activated receptor (PPAR)γ in the liver was achieved using adenovirus. Mice were examined for development of hepatic steatosis and inflammation. RNA sequencing was performed to identify genes affected by CTCF depletion. Genome-wide occupancy of H3K27 acetylation, PPARγ, and CTCF were analyzed by chromatin immunoprecipitation sequencing. Genome-wide chromatin interactions were analyzed by in situ Hi-C. RESULTS: Liver-specific, CTCF-deficient mice developed hepatic steatosis and inflammation when fed a standard chow diet. Global analysis of the transcriptome and enhancer landscape revealed that CTCF-depleted liver showed enhanced accumulation of PPARγ in the nucleus, which leads to increased expression of its downstream target genes, including fat storage-related gene CD36, which is involved in the lipid metabolic process. Hepatic steatosis developed in liver-specific, CTCF-deficient mice was ameliorated by repression of PPARγ via pharmacologic blockade or adenovirus-mediated knockdown, but hardly rescued by additional knockout of CD36. CONCLUSIONS: Our data indicate that liver-specific deletion of CTCF leads to hepatosteatosis through augmented PPARγ DNA-binding activity, which up-regulates its downstream target genes associated with the lipid metabolic process.

Comprehensive impedance investigation of low-cost anion exchange membrane electrolysis for large-scale hydrogen production.

Anion exchange membrane (AEM) electrolysis is a promising solution for large-scale hydrogen production from renewable energy resources. However, the performance of AEM electrolysis is still lower than what can be achieved with conventional technologies. The performance of AEM electrolysis is limited by integral components of the membrane electrode assembly and the reaction kinetics, which can be measured by ohmic and charge transfer resistances. We here investigate and then quantify the contributions of the ohmic and charge transfer resistances, and the rate-determining steps, involved in AEM electrolysis by using electrochemical impedance spectroscopy analysis. The factors that have an effect on the performance, such as voltage, flow rate, temperature and concentration, were studied at 1.5 and 1.9 V. Increased voltage, flow rate, temperature and concentration of the electrolyte strongly enhanced the anodic activity. We observed that here the anodic reaction offered a greater contribution to the overpotential than the cathode did.

Association of Subcortical Structural Shapes With Tau, Amyloid, and Cortical Atrophy in Early-Onset and Late-Onset Alzheimer's Disease.

The objectives of this study were to compare the topographical subcortical shape and to investigate the effects of tau or amyloid burden on atrophic patterns in early onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). One hundred and sixty-one participants (53 EOAD, 44 LOAD, 33 young controls, and 31 older controls) underwent [18F]THK5351 positron emission tomography (PET), [18F]flutemetamol (FLUTE) PET, and 3T MRI scans. We used surface-based analysis to evaluate subcortical structural shape, permutation-based statistics for group comparisons, and Spearman's correlations to determine associations with THK, FLUTE, cortical thickness, and neuropsychological test results. When compared to their age-matched controls, EOAD patients exhibited shape reduction in the bilateral amygdala, hippocampus, caudate, and putamen, while in LOAD patients, the bilateral amygdala and hippocampus showed decreased shapes. In EOAD, widespread subcortical shrinkage, with less association of the hippocampus, correlated with THK retention and cortical thinning, while in LOAD patients, subcortical structures were limited which had significant correlation with THK or mean cortical thickness. Subcortical structural shape showed less correlation with FLUTE global retention in both EOAD and LOAD. Multiple cognitive domains, except memory function, correlated with the bilateral amygdala, caudate, and putamen in EOAD patients, while more restricted regions in the subcortical structures were correlated with neuropsychological test results in LOAD patients. Subcortical structures were associated with AD hallmarks in EOAD. However, the correlation was limited in LOAD. Moreover, relationship between subcortical structural atrophy and cognitive decline were quite different between EOAD and LOAD. These findings suggest that the effects of Alzheimer's pathologies on subcortical structural changes in EOAD and LOAD and they may have different courses of pathomechanism.

Identification of Heterogeneous Subtypes of Mild Cognitive Impairment Using Cluster Analyses Based on PET Imaging of Tau and Astrogliosis.

Background: Mild cognitive impairment (MCI) is a condition with diverse causes and clinical outcomes that can be categorized into subtypes. [18F]THK5351 has been known to detect reactive astrogliosis as well as tau which is accompanied by neurodegenerative changes. Here, we identified heterogeneous groups of MCI patients using THK retention patterns and a graph theory approach, allowing for the comparison of risk of progression to dementia in these MCI subgroups. Methods: Ninety-seven participants including 60 MCI patients and individuals with normal cognition (NC, n = 37) were included and undertook 3T MRI, [18F]THK5351 PET, and detailed neuropsychological tests. [18F]Flutemetamol PET was also performed in 62 participants. We calculated similarities between MCI patients using their regional standardized uptake value ratio of THK retention in 75 ROIs, and clustered subjects with similar retention patterns using the Louvain method based on the modularity of the graph. The clusters of patients identified were compared with an age-matched control group using a general linear model. Dementia conversion was evaluated after a median follow-up duration of 34.6 months. Results: MCI patients were categorized into four groups according to their THK retention patterns: (1) limbic type; (2) diffuse type; (3) sparse type; and (4) AD type (retention pattern as in AD). Subjects of the limbic type were characterized by older age, small hippocampal volumes, and reduced verbal memory and frontal/executive functions. Patients of the diffuse type had relatively large vascular burden, reduced memory capacity and some frontal/executive functions. Co-morbidity and mortality were more frequent in this subgroup. Subjects of the sparse type were younger and declined only in terms of visual memory and attention. No individuals in this subgroup converted to dementia. Patients in the AD type group exhibited the poorest cognitive function. They also had the smallest hippocampal volumes and the highest risk of progression to dementia (90.9%). Conclusion: Using cluster analyses with [18F]THK5351 retention patterns, it is possible to identify clinically-distinct subgroups of MCI patients and those at greater risk of progression to dementia.

Highly cost-effective platinum-free anion exchange membrane electrolysis for large scale energy storage and hydrogen production.

Anion exchange membrane (AEM) electrolysis eradicates platinum group metal electrocatalysts and diaphragms and is used in conventional proton exchange membrane (PEM) electrolysis and alkaline electrolysis. It can produce pressurised hydrogen by using low cost non-noble metal catalysts. However, the performances are still lower than that of the conventional PEM electrolysis technology. In this study, we addressed the performance issue by using a novel combination of Ni-Fe-O x for oxygen evolution reaction (OER) and Ni-Fe-Co hydrogen evolution reaction (HER) electrodes with a PBI anion exchange membrane. The Ni-Fe-O x and Ni-Fe-Co electrodes exhibit exceptionally high catalytic activity, requiring over potentials that are as low as 236 and 84 mV dec-1, respectively, for OER and HER to occur. These electrocatalysts exhibits excellent durability which can be used as oxygen evolution and hydrogen evolution catalysts for long term electrolysis. The high rate capability of 1000 mA cm-2 at 1.9 V and 60 °C demonstrates the potential of the combined membrane electrode assembly. The best performance, which is comparable to those of commercial PEM electrolysis systems, is thus an affordable alternative to this technology. In addition to that, the AEM electrolysis is promising on a multi-scale level for long-term hydrogen production.

Solutions to the water flooding problem for unitized regenerative fuel cells: status and perspectives.

Unitized regenerative fuel cells (URFC) are capable of generating, storing, and releasing energy on demand in a sustainable manner. Water management is of vital importance to achieve maximum performance, durability, and round-trip efficiency in URFCs. However, URFCs suffer from critical issues related to their mode-switching process, water flooding, and membrane dehydration. The essential problem of water management is maintaining a subtle equilibrium between membrane drying and liquid water flooding to prevent membrane dehydration and ensure high URFC performance. This paper provides an overview of the operating principle of URFCs and describes the underlying phenomena related to water management issues. It also summarizes state-of-the-art studies of water management with a focus on recent developments and discusses the technical challenges of water management strategies. In addition, we propose a novel system design to address these critical water management issues. Overall, this review identifies the gaps in the research and development of URFC water management and identifies several essential future developments and research directions for future investigation.