Non-centrosymmetric topological phase probed by non-linear Hall effect.

Non-centrosymmetric topological material has attracted intense attention due to its superior characteristics as compared with the centrosymmetric one, although probing the local quantum geometry in non-centrosymmetric topological material remains challenging. The non-linear Hall (NLH) effect provides an ideal tool to investigate the local quantum geometry. Here, we report a non-centrosymmetric topological phase in ZrTe5, probed by using the NLH effect. The angle-resolved and temperature-dependent NLH measurement reveals the inversion and ab-plane mirror symmetries breaking at <30 K, consistently with our theoretical calculation. Our findings identify a new non-centrosymmetric phase of ZrTe5 and provide a platform to probe and control local quantum geometry via crystal symmetries.

Ganoderic acid A ameliorates depressive-like behaviors in CSDS mice: Insights from proteomic profiling and molecular mechanisms.

OBJECTIVE: Ganoderic Acid A (GAA), a primary bioactive component in Ganoderma, has demonstrated ameliorative effects on depressive-like behaviors in a Chronic Social Defeat Stress (CSDS) mouse model. This study aims to elucidate the underlying molecular mechanisms through proteomic analysis. METHODS: C57BL/6 J mice were allocated into control (CON), chronic social defeat stress (CSDS), GAA, and imipramine (IMI) groups. Post-depression induction via CSDS, the GAA and IMI groups received respective treatments of GAA (2.5 mg/kg) and imipramine (10 mg/kg) for five days. Behavioral assessments utilized standardized tests. Proteins from the prefrontal cortex were analyzed using LC-MS, with further examination via bioinformatics and PRM for differential expression. Western blot analysis confirmed protein expression levels. RESULTS: Chronic social defeat stress (CSDS) induced depressive-like behaviors in mice, which were significantly alleviated by GAA treatment, comparably to imipramine (IMI). Proteomic analysis identified distinct proteins in control (305), GAA-treated (949), and IMI-treated (289) groups. Enrichment in mitochondrial and synaptic proteins was evident from GO and PPI analyses. PRM analysis revealed significant expression changes in proteins crucial for mitochondrial and synaptic functions (namely, Naa30, Bnip1, Tubgcp4, Atxn3, Carmil1, Nup37, Apoh, Mrpl42, Tprkb, Acbd5, Dcx, Erbb4, Ppp1r2, Fam3c, Rnf112, and Cep41). Western blot validation in the prefrontal cortex showed increased levels of Mrpl42, Dcx, Fam3c, Ppp1r2, Rnf112, and Naa30 following GAA treatment. CONCLUSION: GAA exhibits potential antidepressant properties, with its action potentially tied to the modulation of synaptic functions and mitochondrial activities.

Highly controlled synthesis of symmetrically branched tripod and pentapod nanocrystals with enhanced photocatalytic performance.

Anisotropic nanostructures with tunable optical properties induced by controllable size and symmetry have attracted much attention in many applications. Herein, we report a controlled synthesis of symmetrically branched AuCu alloyed nanocrystals. By varying Au:Cu atom ratio in precursor, Y-shaped tripods with three-fold symmetry and star-shaped pentapods with five-fold symmetry are synthesized, respectively. The growth mechanism of AuCu tripods from icosahedral seeds and AuCu pentapods from decahedral seeds is revealed. Aiming to excellent photocatalytic performance, CdS nanocrystals are controlled grown onto the sharp tips of AuCu tripods and pentapods. In addition, a carrier-selective blocking layer of Ag2S is introduced between AuCu and CdS, for achieving effective charge separation in AuCu-Ag2S-CdS nanohybrids. Through evaluating the photocatalytic performance by hydrogen generation experiments, the AuCu-Ag2S-CdS tripod nanocrystals exhibit an optimized hydrogen evolution rate of 2182 µmol·g-1·h-1. These findings will contribute greatly to the understanding of complex nanoparticle growth mechanism and provide a strategy for the design of anisotropic nanoalloys for widely photocatalytic applications.

Transcatheter tricuspid valve replacement with LuX-valve device: Overview of key echocardiographic considerations.

Tricuspid regurgitation is a common valve disease with high incidence and poor prognosis. For elderly patients and those with a history of open heart surgery, second thoracotomy and valve replacement carry a high risk. Transcatheter tricuspid valve replacement (TTVR) has become an alternative treatment for patients with high surgical risk. LuX-Valve is a novel self-expandable valve that does not rely on radial force to anchor the valve annulus. The preliminary results have been satisfactory, and this technology is gradually being adopted in China and around the world. Successful implementation of this technique depends on echocardiographic preoperative screening, intraoperative guidance, and postoperative follow-up. The purpose of this article is to provide a state-of-the-art review of the key points and technical considerations for preoperative screening, intraoperative guidance, and postoperative follow-up for TTVR.

Melanin-Targeting Radiotracers and Their Preclinical, Translational, and Clinical Status: From Past to Future.

Melanin is one of the representative biomarkers of malignant melanoma and a potential target for diagnosis and therapy. With advancements in chemistry and radiolabeling technologies, promising strides have been made to synthesize radiolabeled melanin-binding molecules for various applications. We present an overview of melanin-targeted radiolabeled molecules and compare their features reported in preclinical studies. Clinical practice and trials are also discussed to elaborate on the safety and validity of the probes, and expanded applications beyond melanoma are reviewed. Melanin-targeted imaging holds potential value in the diagnosis, staging, and prognostic assessment of melanoma and other applications. Melanin-targeted radionuclide therapy possesses immense potential but requires more clinical validation. Furthermore, an intriguing avenue for future research involves expanding the application scope of melanin-targeted probes and exploring their value.

Automatic planning of maxillary anterior dental implant based on prosthetically guided and pose evaluation indicator.

PURPOSE: Preoperative planning of maxillary anterior dental implant is a prerequisite to ensuring that the implant achieves the proper three-dimensional (3D) pose, which is essential for its long-term stability. However, the current planning process is labor-intensive and subjective, relying heavily on the surgeon's experience. Consequently, this paper proposes an automatic method for computing the optimal pose of the dental implant. METHODS: The method adopts the principle of prosthetically guided dental implant placement. Initially, the prosthesis coordinate system is established to determine the implant candidate orientations. Subsequently, virtual slices of the maxilla in the buccal-palatal direction are generated according to the prosthesis position. By extracting feature points from the virtual slices, the implant candidate starting points are acquired. Then, a candidate pose set is obtained by combining these candidate starting points and orientations. Finally, a pose evaluation indicator is introduced to determine the optimal implant pose from this set. RESULTS: Twenty-two cases were utilized to validate the method. The results show that the method could determine an ideal pose for the dental implant, with the average minimum distance between the implant and the left tooth root, the right tooth root, the palatal side, and the buccal side being 2.57 ± 0.53 mm, 2.59 ± 0.65 mm, 0.74 ± 0.19 mm, 1.83 ± 0.16 mm, respectively. The planning time was less than 9 s. CONCLUSION: Unlike manual planning, the proposed method can efficiently and accurately complete maxillary anterior dental implant planning, providing a theoretical analysis of the success rate of the implant. Thus, it has great potential for future clinical application.

Inter-relationships of depression and insomnia symptoms with life satisfaction in stroke and stroke-free older adults: Findings from the Health and Retirement Study based on network analysis and propensity score matching.

BACKGROUND: Depression and insomnia are common co-occurring psychiatric problems among older adults who have had strokes. Nevertheless, symptom-level relationships between these disorders remain unclear. OBJECTIVES: In this study, we compared inter-relationships of depression and insomnia symptoms with life satisfaction among older stroke patients and stroke-free peers in the United States. METHODS: The study included 1026 older adults with a history of stroke and 3074 matched controls. Data were derived from the US Health and Retirement Study. Depression, insomnia and life satisfaction were assessed. Propensity score matching was employed to identify demographically-similar groups of stroke patients and controls. Central and bridge symptoms were assessed using Expected influence (EI) and bridge EI, respectively. RESULTS: The prevalence of depression in the stroke group (25.0 %) was higher than that of controls (14.3 %, P < 0.001). In stroke group, "Feeling depressed" (CESD1; EI: 5.80), "Feeling sad" (CESD7; EI: 4.67) and "Not enjoying life" (CESD6; EI: 4.51) were the most central symptoms, while "Feeling tired in the morning" (JSS4; BEI: 1.60), "Everything was an effort" (CESD2; BEI: 1.21) and "Waking up during the night" (JSS2; BEI: 0.98) were key bridge symptoms. In controls, the most central symptoms were "Lack of happiness" (CESD4; EI: 6.45), "Feeling depressed" (CESD1; EI: 6.17), and "Feeling sad" (CESD7; EI: 6.12). Furthermore, "Feeling tired in the morning" (JSS4; BEI: 1.93), "Everything was an effort" (CESD2; BEI: 1.30), and "Waking up too early" (JSS3; BEI: 1.12) were key bridge symptoms. Life satisfaction had the most direct associations with "Not enjoying life" (CESD6) and "Feeling lonely" (CESD5) in the two groups, respectively. CONCLUSION: Older adults with stroke exhibited more severe depression and insomnia symptoms. Interventions targeting central and bridge symptoms may help to mitigate the co-occurrence of these symptoms.

Aspirin treatment for unruptured intracranial aneurysms: Focusing on its anti-inflammatory role.

Intracranial aneurysms (IAs), as a common cerebrovascular disease, claims a worldwide morbidity rate of 3.2%. Inflammation, pivotal in the pathogenesis of IAs, influences their formation, growth, and rupture. This review investigates aspirin's modulation of inflammatory pathways within this context. With IAs carrying significant morbidity and mortality upon IAs rupture and current interventions limited to surgical clipping and endovascular coiling, the quest for pharmacological options is imperative. Aspirin's role in cardiovascular prevention, due to its anti-inflammatory effects, presents a potential therapeutic avenue for IAs. In this review, we examine aspirin's efficacy in experimental models and clinical settings, highlighting its impact on the progression and rupture risks of unruptured IAs. The underlying mechanisms of aspirin's impact on IAs are explored, with its ability examined to attenuate endothelial dysfunction and vascular injury. This review may provide a theoretical basis for the use of aspirin, suggesting a promising strategy for IAs management. However, the optimal dosing, safety, and long-term efficacy remain to be established. The implications of aspirin therapy are significant in light of current surgical and endovascular treatments. Further research is encouraged to refine aspirin's clinical application in the management of unruptured IAs, with the ultimate aim of reducing the incidence of aneurysms rupture.

Applicability of the generalized wind profile model over mountainous forests.

The analytical equation based on Monin-Obukhov (M-O) similarity theory (i.e., wind profile equation) has been adopted since 1970s for using in the prediction of wind vertical profile over flat terrains, which is mature and accurate. However, its applicability over complex terrains remains unknown. This applicability signifies the accuracy of the estimations of aerodynamic parameters for the boundary layer of non-flat terrain, such as zero-displacement height (d) and aerodynamic roughness length (z0), which will determine the accuracy of frequency correction and source area analysis in calculating carbon, water, and trace gas fluxes based on vorticity covariance method. Therefore, the validation of wind profile model in non-flat terrain is the first step to test whether the flux model needs improvement. We measured three-dimensional wind speed data by using the Ker Towers (three towers in a watershed) at Qingyuan Forest CERN in the Mountainous Region of east Liaoning Province, and compared them with data from Panjin Agricultural Station in the Liaohe Plain, to evaluate the applicability of a generalized wind profile model based on the Monin-Obukhov similarity theory on non-flat terrain. The results showed that the generalized wind profile model could not predict wind speeds accurately of three flux towers separately located in different sites, indicating that wind profile model was not suitable for predicting wind speeds in complex terrains. In the leaf-off and leaf-on periods, the coefficient of determination (R2) between observed and predicted wind speeds ranged from 0.12 to 0.30. Compared to measured values, the standard error of the predicted wind speeds was high up to 2 m·s-1. The predicted wind speeds were high as twice as field-measured wind speed, indicating substantial overestimation. Nevertheless, this model correctly predicted wind speeds in flat agricultural landscape in Panjin Agricultural Station. The R2 between observed wind speeds and predicted wind speed ranged from 0.90 to 0.93. The standard error between observed and predicted values was only 0.5 m·s-1. Results of the F-test showed that the root-mean-square error of the observed and predicted wind speeds in each secondary forest complex terrain was much greater than that in flat agricultural landscape. Terrain was the primary factor affecting the applicability of wind profile model, followed by seasonality (leaf or leafless canopy). The wind profile model was not applicable to the boundary-layer flows over forest canopies in complex terrains, because the d was underestimated or both the d and z0 were underestimated, resulting in inaccurate estimation of aerodynamic height.

Analysis of brain structural covariance network in Cushing disease.

Background: Cushing disease (CD) is a rare clinical neuroendocrine disease. CD is characterized by abnormal hypercortisolism induced by a pituitary adenoma with the secretion of adrenocorticotropic hormone. Individuals with CD usually exhibit atrophy of gray matter volume. However, little is known about the alterations in topographical organization of individuals with CD. This study aimed to investigate the structural covariance networks of individuals with CD based on the gray matter volume using graph theory analysis. Methods: High-resolution T1-weighted images of 61 individuals with CD and 53 healthy controls were obtained. Gray matter volume was estimated and the structural covariance network was analyzed using graph theory. Network properties such as hubs of all participants were calculated based on degree centrality. Results: No significant differences were observed between individuals with CD and healthy controls in terms of age, gender, and education level. The small-world features were conserved in individuals with CD but were higher than those in healthy controls. The individuals with CD showed higher global efficiency and modularity, suggesting higher integration and segregation as compared to healthy controls. The hub nodes of the individuals with CD were Short insular gyri (G_insular_short_L), Anterior part of the cingulate gyrus and sulcus (G_and_S_cingul-Ant_R), and Superior frontal gyrus (G_front_sup_R). Conclusions: Significant differences in the structural covariance network of patients with CD were found based on graph theory. These findings might help understanding the pathogenesis of individuals with CD and provide insight into the pathogenesis of this CD.

Learning to Sketch: A Neural Approach to Item Frequency Estimation in Streaming Data.

Recently, there has been a trend of designing neural data structures to go beyond handcrafted data structures by leveraging patterns of data distributions for better accuracy and adaptivity. Sketches are widely used data structures in real-time web analysis, network monitoring, and self-driving to estimate item frequencies of data streams within limited space. However, existing sketches have not fully exploited the patterns of the data stream distributions, making it challenging to tightly couple them with neural networks that excel at memorizing pattern information. Starting from the premise, we envision a pure neural data structure as a base sketch, which we term the meta-sketch, to reinvent the base structure of conventional sketches. The meta-sketch learns basic sketching abilities from meta-tasks constituted with synthetic datasets following Zipf distributions in the pre-training phase and can be quickly adapted to real (skewed) distributions in the adaption phase. The meta-sketch not only surpasses its competitors in sketching conventional data streams but also holds good potential in supporting more complex streaming data, such as multimedia and graph stream scenarios. Extensive experiments demonstrate the superiority of the meta-sketch and offer insights into its working mechanism.

Pathological high intraocular pressure induces glial cell reactive proliferation contributing to neuroinflammation of the blood-retinal barrier via the NOX2/ET-1 axis-controlled ERK1/2 pathway.

BACKGROUND: NADPH oxidase (NOX), a primary source of endothelial reactive oxygen species (ROS), is considered a key event in disrupting the integrity of the blood-retinal barrier. Abnormalities in neurovascular-coupled immune signaling herald the loss of ganglion cells in glaucoma. Persistent microglia-driven inflammation and cellular innate immune system dysregulation often lead to deteriorating retinal degeneration. However, the crosstalk between NOX and the retinal immune environment remains unresolved. Here, we investigate the interaction between oxidative stress and neuroinflammation in glaucoma by genetic defects of NOX2 or its regulation via gp91ds-tat. METHODS: Ex vivo cultures of retinal explants from wildtype C57BL/6J and Nox2 -/- mice were subjected to normal and high hydrostatic pressure (Pressure 60 mmHg) for 24 h. In vivo, high intraocular pressure (H-IOP) was induced in C57BL/6J mice for two weeks. Both Pressure 60 mmHg retinas and H-IOP mice were treated with either gp91ds-tat (a NOX2-specific inhibitor). Proteomic analysis was performed on control, H-IOP, and treatment with gp91ds-tat retinas to identify differentially expressed proteins (DEPs). The study also evaluated various glaucoma phenotypes, including IOP, retinal ganglion cell (RGC) functionality, and optic nerve (ON) degeneration. The superoxide (O2-) levels assay, blood-retinal barrier degradation, gliosis, neuroinflammation, enzyme-linked immunosorbent assay (ELISA), western blotting, and quantitative PCR were performed in this study. RESULTS: We found that NOX2-specific deletion or activity inhibition effectively attenuated retinal oxidative stress, immune dysregulation, the internal blood-retinal barrier (iBRB) injury, neurovascular unit (NVU) dysfunction, RGC loss, and ON axonal degeneration following H-IOP. Mechanistically, we unveiled for the first time that NOX2-dependent ROS-driven pro-inflammatory signaling, where NOX2/ROS induces endothelium-derived endothelin-1 (ET-1) overexpression, which activates the ERK1/2 signaling pathway and mediates the shift of microglia activation to a pro-inflammatory M1 phenotype, thereby triggering a neuroinflammatory outburst. CONCLUSIONS: Collectively, we demonstrate for the first time that NOX2 deletion or gp91ds-tat inhibition attenuates iBRB injury and NVU dysfunction to rescue glaucomatous RGC loss and ON axon degeneration, which is associated with inhibition of the ET-1/ERK1/2-transduced shift of microglial cell activation toward a pro-inflammatory M1 phenotype, highlighting NOX2 as a potential target for novel neuroprotective therapies in glaucoma management.

LncRNA XIST modulates miR-328-3p ectopic expression in lung injury induced by tobacco-specific lung carcinogen NNK both in vitro and in vivo.

BACKGROUND AND PURPOSE: It is well acknowledged that tobacco-derived lung carcinogens can induce lung injury and even lung cancer through a complex mechanism. MicroRNAs (MiRNAs) are differentially expressed in tobacco-derived carcinogen nicotine-derived nitrosamine ketone (NNK)-treated A/J mice. EXPERIMENTAL APPROACH: RNA sequencing was used to detect the level of long non-coding RNAs (lncRNAs). Murine and human lung normal and cancer cells were used to evaluate the function of lncRNA XIST and miR-328-3p in vitro, and NNK-treated A/J mice were used to test their function in vivo. In vivo levels of miR-328-3p and lncRNA XIST were analysed, using in situ hybridization. miR-328-3p agomir and lncRNA XIST-specific siRNA were used to manipulate in vivo levels of miR-328-3p and lncRNA XIST in A/J mice. KEY RESULTS: LncRNA XIST was up-regulated in NNK-induced lung injury and dominated the NNK-induced ectopic miRNA expression in NNK-induced lung injury both in vitro and in vivo. Either lncRNA XIST silencing or miR-328-3p overexpression exerted opposing effects in lung normal and cancer cells regarding cell migration. LncRNA XIST down-regulated miR-328-3p levels as a miRNA sponge, and miR-328-3p targeted the 3'-UTR of FZD7 mRNA, which is ectopically overexpressed in lung cancer patients. Both in vivo lncRNA XIST silencing and miR-328 overexpression could rescue NNK-induced lung injury and aberrant overexpression of the lung cancer biomarker CK19 in NNK-treated A/J mice. CONCLUSIONS AND IMPLICATIONS: Our results highlight the promotive effect of lncRNA XIST in NNK-induced lung injury and elucidate its post-transcriptional mechanisms, indicating that targeting lncRNA XIST/miR-328-3p could be a potential therapeutic strategy to prevent tobacco carcinogen-induced lung injury in vivo.

Preclinical efficacy of a PSMA-targeted actinium-225 conjugate (225Ac-macropa-pelgifatamab) - a targeted alpha therapy for prostate cancer.

PURPOSE: Initially, prostate cancer responds to hormone therapy but eventually resistance develops. Beta emitter-based PSMA (prostate-specific membrane antigen)-targeted radionuclide therapy is approved for the treatment of metastatic castration-resistant prostate cancer. Here we introduce a targeted alpha therapy (TAT) consisting of the PSMA antibody pelgifatamab covalently linked to a macropa chelator and labeled with actinium-225 and compare its efficacy and tolerability with other TATs. EXPERIMENTAL DESIGN: The in vitro characteristics and in vivo biodistribution, antitumor efficacy, and tolerability of 225Ac-macropa-pelgifatamab (225Ac-pelgi) and other TATs were investigated in cell line- and patient-derived prostate cancer xenograft models. The antitumor efficacy of 225Ac-pelgi was also investigated in combination with the androgen receptor inhibitor darolutamide. RESULTS: Actinium-225-labeling of 225Ac-pelgi was efficient already at room temperature. Potent in vitro cytotoxicity was seen in PSMA-expressing (LNCaP, MDA-PCa-2b, and C4-2) but not in PSMA-negative (PC-3 and DU-145) cell lines. High tumor accumulation was seen for both 225Ac-pelgi and 225Ac-DOTA-pelgi in the MDA-PCa-2b xenograft model. In the C4-2 xenograft model, 225Ac-pelgi showed enhanced antitumor efficacy with a T/Cvolume (treatment/control) ratio of 0.10 compared with 225Ac-DOTA-pelgi, 225Ac-DOTA-J591, and 227Th-HOPO-pelgifatamab (227Th-pelgi) (all at 300 kBq/kg) with T/Cvolume ratios of 0.37, 0.39, and 0.33, respectively. 225Ac-pelgi was less myelosuppressive than 227Th-pelgi. 225Ac-pelgi showed dose-dependent treatment efficacy in the patient-derived KuCaP-1 model and strong combination potential with darolutamide in both cell line- (22Rv1) and patient-derived (ST1273) xenograft models. CONCLUSIONS: These results provide a strong rationale to investigate 225Ac-pelgi in patients with prostate cancer. A clinical phase 1 study has been initiated (NCT06052306).

Multi-modal molecular determinants of clinically relevant osteoporosis subtypes.

Due to a rapidly aging global population, osteoporosis and the associated risk of bone fractures have become a wide-spread public health problem. However, osteoporosis is very heterogeneous, and the existing standard diagnostic measure is not sufficient to accurately identify all patients at risk of osteoporotic fractures and to guide therapy. Here, we constructed the first prospective multi-omics atlas of the largest osteoporosis cohort to date (longitudinal data from 366 participants at three time points), and also implemented an explainable data-intensive analysis framework (DLSF: Deep Latent Space Fusion) for an omnigenic model based on a multi-modal approach that can capture the multi-modal molecular signatures (M3S) as explicit functional representations of hidden genotypes. Accordingly, through DLSF, we identified two subtypes of the osteoporosis population in Chinese individuals with corresponding molecular phenotypes, i.e., clinical intervention relevant subtypes (CISs), in which bone mineral density benefits response to calcium supplements in 2-year follow-up samples. Many snpGenes associated with these molecular phenotypes reveal diverse candidate biological mechanisms underlying osteoporosis, with xQTL preferences of osteoporosis and its subtypes indicating an omnigenic effect on different biological domains. Finally, these two subtypes were found to have different relevance to prior fracture and different fracture risk according to 4-year follow-up data. Thus, in clinical application, M3S could help us further develop improved diagnostic and treatment strategies for osteoporosis and identify a new composite index for fracture prediction, which were remarkably validated in an independent cohort (166 participants).

Indirect Shear Wave Excitation for Brain Magnetic Resonance Elastography with Minimal Cerebral Blood Flow Alteration.

Magnetic resonance elastography (MRE) of brain relies on inducing and measuring shear waves in the brain. However, studies have shown vibration could induce changes in cerebral blood flow (CBF), which has a modulation effect and can affect the biomechanical properties measured. OBJECTIVE: This work demonstrates the initial prototype of the indirect excitation method, which can generate shear waves in the brain with minimal changes in CBF. METHODS: A simple system was designed to produce stable vibrations underneath the neck. Instead of directly stimulating the skull, shear waves were indirectly transmitted to the brain through the spine and brainstem. RESULTS: Phantom results showed that the proposed actuator did not interfere with the routine imaging sequence and successfully generated multifrequency shear waves. When compared with the conventional direct head stimulation method, brain MRE results from the proposed actuator showed no significant differences in terms of intraclass correlation coefficients (ICC) and coefficients of variation (CV). Moreover, the octahedral shear strain (OSS) generated by the indirect excitation in the frontal and parietal lobes decreased by 25.96% and 16.73% respectively. Evaluation of CBF in healthy volunteers revealed no significant changes for the indirect excitation method, whereas significant decreases in CBF were observed in four subregions when employing direct excitation. CONCLUSION: The proposed actuator offers a more accurate and comfortable approach to MRE measurements while causing minimal CBF alterations. SIGNIFICANCE: This work presents the first demonstration of an indirect excitation brain MRE system that minimizes CBF changes, thus holding potential for future applications of brain MRE.

Acetyl-CoA synthetase 2 induces pyroptosis and inflammation of renal epithelial tubular cells in sepsis-induced acute kidney injury by upregulating the KLF5/NF-κB pathway.

BACKGROUND: Pyroptosis of the renal tubular epithelial cells (RTECs) and interstitial inflammation are central pathological characteristics of acute kidney injury (AKI). Pyroptosis acts as a pro-inflammatory form of programmed cell death and is mainly dependent on activation of the NLRP3 inflammasome. Previous studies revealed that acetyl-CoA synthetase 2 (ACSS2) promotes inflammation during metabolic stress suggesting that ACSS2 might regulate pyroptosis and inflammatory responses of RTECs in AKI. METHODS AND RESULTS: The expression of ACSS2 was found to be significantly increased in the renal epithelial cells of mice with lipopolysaccharide (LPS)-induced AKI. Pharmacological and genetic strategies demonstrated that ACSS2 regulated NLRP3-mediated caspase-1 activation and pyroptosis through the stimulation of the KLF5/NF-κB pathway in RTECs. The deletion of ACSS2 attenuated renal tubular pathological injury and inflammatory cell infiltration in an LPS-induced mouse model, and ACSS2-deficient mice displayed impaired NLRP3 activation-mediated pyroptosis and decreased IL-1ß production in response to the LPS challenge. In HK-2 cells, ACSS2 deficiency suppressed NLRP3-mediated caspase-1 activation and pyroptosis through the downregulation of the KLF5/NF-κB pathway. The KLF5 inhibitor ML264 suppressed NF-κB activity and NLRP3-mediated caspase-1 activation, thus protecting HK-2 cells from LPS-induced pyroptosis. CONCLUSION: Our results suggested that ACSS2 regulates activation of the NLRP3 inflammasome and pyroptosis by inducing the KLF5/NF-κB pathway in RTECs. These results identified ACSS2 as a potential therapeutic target in AKI.

Constructing CoNi-LDH/Fe MOF/NF Heterostructure Catalyst for Energy-Efficient OER and UOR at High Current Density.

The sluggish kinetics of the oxygen evolution reaction (OER) always results in a high overpotential at the anode of water electrolysis and an excessive electric energy consumption, which has been a major obstacle for hydrogen production through water electrolysis. In this study, we present a CoNi-LDH/Fe MOF/NF heterostructure catalyst with nanoneedle array morphology for the OER. In 1.0 M KOH solution, the heterostructure catalyst only required overpotentials of 275 and 305 mV to achieve high current densities of 500 and 1000 mA/cm2 for OER, respectively. The catalytic activities are much higher than those of the reference single-component CoNi-LDH/NF and Fe MOF/NF catalysts. The improved catalytic performance of the heterostructure catalyst can be ascribed to the synergistic effect of CoNi-LDH and Fe MOF. In particular, when the anodic OER is replaced with the urea oxidation reaction (UOR), which has a relatively lower thermodynamic equilibrium potential and is expected to reduce the cell voltage, the overpotentials required to achieve the same current densities can be reduced by 80 and 40 mV, respectively. The cell voltage required to drive overall urea splitting (OUS) is only 1.55 V at 100 mA/cm2 in the Pt/C/NF||CoNi-LDH/Fe MOF/NF two-electrode electrolytic cell. This value is 60 mV lower compared with that required for overall water splitting (OWS). Our results indicate that a reasonable construction of a heterostructure catalyst can significantly give rise to higher electrocatalytic performance, and using UOR to replace the anodic OER of the OWS can greatly reduce the electrolytic energy consumption.

Tinnitus classification based on resting-state functional connectivity using a convolutional neural network architecture.

OBJECTIVES: Many studies have investigated aberrant functional connectivity (FC) using resting-state functional MRI (rs-fMRI) in subjective tinnitus patients. However, no studies have verified the efficacy of resting-state FC as a diagnostic imaging marker. We established a convolutional neural network (CNN) model based on rs-fMRI FC to distinguish tinnitus patients from healthy controls, providing guidance and fast diagnostic tools for the clinical diagnosis of subjective tinnitus. METHODS: A CNN architecture was trained on rs-fMRI data from 100 tinnitus patients and 100 healthy controls using an asymmetric convolutional layer. Additionally, a traditional machine learning model and a transfer learning model were included for comparison with the CNN, and each of the three models was tested on three different brain atlases. RESULTS: Of the three models, the CNN model outperformed the other two models with the highest area under the curve, especially on the Dos_160 atlas (AUC = 0.944). Meanwhile, the model with the best classification performance highlights the crucial role of the default mode network, salience network, and sensorimotor network in distinguishing between normal controls and patients with subjective tinnitus. CONCLUSION: Our CNN model could appropriately tackle the diagnosis of tinnitus patients using rs-fMRI and confirmed the diagnostic value of FC as measured by rs-fMRI.