Chemoproteomic profiling of O-GlcNAcylated proteins and identification of O-GlcNAc transferases in rice.

O-linked ß-N-acetylglucosaminylation (O-GlcNAcylation) is a ubiquitous post-translation modification occurring in both animals and plants. Thousands of proteins along with their O-GlcNAcylation sites have been identified in various animal systems, yet the O-GlcNAcylated proteomes in plants remain poorly understood. Here, we report a large-scale profiling of protein O-GlcNAcylation in a site-specific manner in rice. We first established the metabolic glycan labelling (MGL) strategy with N-azidoacetylgalactosamine (GalNAz) in rice seedlings, which enabled incorporation of azides as a bioorthogonal handle into O-GlcNAc. By conjugation of the azide-incorporated O-GlcNAc with alkyne-biotin containing a cleavable linker via click chemistry, O-GlcNAcylated proteins were selectively enriched for mass spectrometry (MS) analysis. A total of 1591 unambiguous O-GlcNAcylation sites distributed on 709 O-GlcNAcylated proteins were identified. Additionally, 102 O-GlcNAcylated proteins were identified with their O-GlcNAcylation sites located within serine/threonine-enriched peptides, causing ambiguous site assignment. The identified O-GlcNAcylated proteins are involved in multiple biological processes, such as transcription, translation and plant hormone signalling. Furthermore, we discovered two O-GlcNAc transferases (OsOGTs) in rice. By expressing OsOGTs in Escherichia coli and Nicotiana benthamiana leaves, we confirmed their OGT enzymatic activities and used them to validate the identified rice O-GlcNAcylated proteins. Our dataset provides a valuable resource for studying O-GlcNAc biology in rice, and the MGL method should facilitate the identification of O-GlcNAcylated proteins in various plants.

Young and undamaged recombinant albumin alleviates T2DM by improving hepatic glycolysis through EGFR and protecting islet ß cells in mice.

BACKGROUND: Albumin is the most abundant protein in serum and serves as a transporter of free fatty acids (FFA) in blood vessels. In type 2 diabetes mellitus (T2DM) patients, the reduced serum albumin level is a risk factor for T2DM development and progression, although this conclusion is controversial. Moreover, there is no study on the effects and mechanisms of albumin administration to relieve T2DM. We examined whether the administration of young and undamaged recombinant albumin can alleviate T2DM in mice. METHODS: The serum albumin levels and metabolic phenotypes including fasting blood glucose, glucose tolerance tests, and glucose-stimulated insulin secretion were studied in db/db mice or diet-induced obesity mice treated with saline or young, undamaged, and ultrapure rMSA. Apoptosis assays were performed at tissue and cell levels to determine the function of rMSA on islet ß cell protection. Metabolic flux and glucose uptake assays were employed to investigate metabolic changes in saline-treated or rMSA-treated mouse hepatocytes and compared their sensitivity to insulin treatments. RESULTS: In this study, treatment of T2DM mice with young, undamaged, and ultrapure recombinant mouse serum albumin (rMSA) increased their serum albumin levels, which resulted in a reversal of the disease including reduced fasting blood glucose levels, improved glucose tolerance, increased glucose-stimulated insulin secretion, and alleviated islet atrophy. At the cellular level, rMSA improved glucose uptake and glycolysis in hepatocytes. Mechanistically, rMSA reduced the binding between CAV1 and EGFR to increase EGFR activation leading to PI3K-AKT activation. Furthermore, rMSA extracellularly reduced the rate of fatty acid uptake by islet ß-cells, which relieved the accumulation of intracellular ceramide, endoplasmic reticulum stress, and apoptosis. This study provided the first clear demonstration that injections of rMSA can alleviate T2DM in mice. CONCLUSION: Our study demonstrates that increasing serum albumin levels can promote glucose homeostasis and protect islet ß cells, which alleviates T2DM.

Reconfigurable microwave photonic mixer for hybrid macro-micro cellular systems.

Microwave photonic mixing can realize the frequency conversion of microwave signals in the optical domain, breaking through the bandwidth bottleneck and electromagnetic interference problems of traditional microwave mixing methods. In the background of the hybrid macro-micro cellular system, a wideband, large dynamic range and reconfigurable microwave photonic mixer is proposed, theoretically analyzed and experimentally demonstrated in this paper. By adjusting the modulator bias voltages and matching the proper digital domain operations, a microwave photonic mixer with reconfigurable functions including single-ended dispersion immune mixing, I/Q frequency down-conversion, image rejection mixing, and double-balanced mixing are realized, respectively. Meanwhile, optimizing the electrical attenuator using convex optimization can suppress the third-order intermodulation distortion (IMD3), maximize the conversion gain, and finally improve the spur-free dynamic range (SFDR). Experimental results show that the proposed scheme can be operated with a frequency from 5 to 20 GHz, and the SFDR can achieve 118.3 dB·Hz4/5. Over the whole frequency range, I/Q frequency down-conversion can be well conducted with an amplitude imbalance below 0.7 dB and a phase imbalance below ±0.7°. After an I/Q imbalance compensation algorithm, the image rejection ratio of over 60 dB is produced. The power fading caused by fiber dispersion is also compensated successfully. For a vector signal with 16 quadrature amplitude modulation, the best error vector magnitude (EVM) reaches 3.4%.

Deep learning based object tracking for 3D microstructure reconstruction.

In medical and material science, 3D reconstruction is of great importance for quantitative analysis of microstructures. After the image segmentation process of serial slices, in order to reconstruct each local structure in volume data, it needs to use precise object tracking algorithm to recognize the same object region in adjacent slice. Suffering from weak representative hand-crafted features, traditional object tracking methods always draw out under-segmentation results. In this work, we have proposed an adjacent similarity based deep learning tracking method (ASDLTrack) to reconstruct 3D microstructure. By transferring object tracking problem to classification problem, it can utilize powerful representative ability of convolutional neural network in pattern recognition. Experiments in three datasets with three metrics demonstrate that our algorithm achieves the promising performance compared to traditional methods.

Characteristics of paraspinal muscle degeneration in patients with adult degenerative scoliosis.

INTRODUCTION: Adult degenerative scoliosis (ADS) is a 3D deformity that greatly affects the quality of life of patients and is closely related to the quality of paraspinal muscles (PSMs), but the specific degenerative characteristics have not been described. METHODS: This study included ADS patients who were first diagnosed in our hospital from 2018 to 2022. Muscle volume (MV) and fat infiltration (FI) of PSM were measured by 3D reconstruction, and spinal parameters were assessed by X-ray. The values of convex side (CV) and concave side (CC) were compared. RESULTS: Fifty patients were enrolled with a mean age of 64.1 ± 5.8 years old. There were significant differences in MV, FI, and Cobb angle between male and female groups. The MV of MF and PS on the CC was significantly larger than that on the CV. In the apex and the segments above the apex, the FI of the MF on the CC is greater than the CV, and in the CV of the segment below the apex, the FI of the MF is greater than the CC. Besides, there was a significant positive correlation between the FI and Cobb angle in the MF of the CC-CV. CONCLUSION: There were significant differences in the MV and FI of PSM on both sides of the spine in ADS patients. It was determined that the PSM of ADS showed different degrees of degeneration in different levels of the lumbar spine and were positively correlated with Cobb angle.

Han's technique: a new reduction technique for acute anterior shoulder dislocation.

INTRODUCTION: Acute anterior shoulder dislocation (AASD) is the most common joint dislocation. Here, we introduced a new reduction technique for AASD, named "Han's technique" (or "Touch overhead technique"). METHODS: Patients diagnosed with AASD were treated with "Han's technique" in the orthopaedic department of our hospital from October 2018 to November 2020. An orthopedic surgeon performed the reduction maneuver without any anesthesia or sedation throughout the reduction process. The fundamental information and related data were recorded, including patients' age, sex, dislocation side, previous dislocations history, reduction time, number of attempts at reduction, success rate of the reduction, intensity of pain during reduction using the 10-point visual analogue scale score (VAS), any complications, with or without the fracture and neurovascular examination results. RESULTS: Forty-one patients with AASD were involved in our study. Thirty-nine cases (95%) were primary dislocation. Eleven patients (27%) were complicated with large tubercle fracture and one patient (2%) complicated with inferior glenoid fractures. All patients were successfully reduced by Han's technique with mean reduction time was 138 s. The pain score during the reduction operation is only1.83 ± 0.83 points. No neurovascular injury or iatrogenic fracture was found after reduction in all patients. CONCLUSIONS: Han's technique (or Touch overhead technique) is a simple, safe, effective, mild and easy to master which can be operated by one surgeon without anesthesia or sedation for AASD.

The effects of cardiolipin on the structural dynamics of the mitochondrial ADP/ATP carrier in its cytosol-open state.

Cardiolipin (CL) has been shown to play a crucial role in regulating the function of proteins in the inner mitochondrial membrane. As the most abundant protein of the inner mitochondrial membrane, the ADP/ATP carrier (AAC) has long been the model of choice to study CL-protein interactions, and specifically bound CLs have been identified in a variety of crystal structures of AAC. However, how CL binding affects the structural dynamics of AAC in atomic detail remains largely elusive. Here we compared all-atom molecular dynamics simulations on bovine AAC1 in lipid bilayers with and without CLs. Our results show that on the current microsecond simulation time scale: 1) CL binding does not significantly affect overall stability of the carrier or structural symmetry at the matrix-gate level; 2) pocket volumes of the carrier and interactions involved in the matrix-gate network become more heterogeneous in parallel simulations with membranes containing CLs; 3) CL binding consistently strengthens backbone hydrogen bonds within helix H2 near the matrix side; and 4) CLs play a consistent stabilizing role on the domain 1-2 interface through binding with the R30:R71:R151 stacking structure and fixing the M2 loop in a defined conformation. CL is necessary for the formation of this stacking structure, and this structure in turn forms a very stable CL binding site. Such a delicate equilibrium suggests the strictly conserved R30:R71:R151stacking structure of AACs could function as a switch under regulation of CLs. Taken together, these results shed new light on the CL-mediated modulation of AAC function.

Function-Related Asymmetry of the Interactions between Matrix Loops and Conserved Sequence Motifs in the Mitochondrial ADP/ATP Carrier.

The ADP/ATP carrier (AAC) plays a central role in oxidative metabolism by exchanging ATP and ADP across the inner mitochondrial membrane. Previous experiments have shown the involvement of the matrix loops of AAC in its function, yet potential mechanisms remain largely elusive. One obstacle is the limited information on the structural dynamics of the matrix loops. In the current work, unbiased all-atom molecular dynamics (MD) simulations were carried out on c-state wild-type AAC and mutants. Our results reveal that: (1) two ends of a matrix loop are tethered through interactions between the residue of triplet 38 (Q38, D143 and Q240) located at the C-end of the odd-numbered helix and residues of the [YF]xG motif located before the N-end of the short matrix helix in the same domain; (2) the initial progression direction of a matrix loop is determined by interactions between the negatively charged residue of the [DE]G motif located at the C-end of the short matrix helix and the capping arginine (R30, R139 and R236) in the previous domain; (3) the two chemically similar residues D and E in the highly conserved [DE]G motif are actually quite different; (4) the N-end of the M3 loop is clamped by the [DE]G motif and the capping arginine of domain 2 from the two sides, which strengthens interactions between domain 2 and domain 3; and (5) a highly asymmetric stable core exists within domains 2 and 3 at the m-gate level. Moreover, our results help explain almost all extremely conserved residues within the matrix loops of the ADP/ATP carriers from a structural point of view. Taken together, the current work highlights asymmetry in the three matrix loops and implies a close relationship between asymmetry and ADP/ATP transport.

Investigating the Broad Matrix-Gate Network in the Mitochondrial ADP/ATP Carrier through Molecular Dynamics Simulations.

The mitochondrial ADP/ATP carrier (AAC) exports ATP and imports ADP through alternating between cytosol-open (c-) and matrix-open (m-) states. The salt bridge networks near the matrix side (m-gate) and cytosol side (c-gate) are thought to be crucial for state transitions, yet our knowledge on these networks is still limited. In the current work, we focus on more conserved m-gate network in the c-state AAC. All-atom molecular dynamics (MD) simulations on a variety of mutants and the CATR-AAC complex have revealed that: (1) without involvement of other positive residues, the charged residues from the three Px[DE]xx[KR] motifs only are prone to form symmetrical inter-helical network; (2) R235 plays a determinant role for the asymmetry in m-gate network of AAC; (3) R235 significantly strengthens the interactions between H3 and H5; (4) R79 exhibits more significant impact on m-gate than R279; (5) CATR promotes symmetry in m-gate mainly through separating R234 from D231 and fixing R79; (6) vulnerability of the H2-H3 interface near matrix side could be functionally important. Our results provide new insights into the highly conserved yet variable m-gate network in the big mitochondrial carrier family.

Deep learning-based automatic inpainting for material microscopic images.

The microscopic image is important data for recording the microstructure information of materials. Researchers usually use image-processing algorithms to extract material features from that and then characterise the material microstructure. However, the microscopic images obtained by a microscope often have random damaged regions, which will cause the loss of information and thus inevitably influence the accuracy of microstructural characterisation, even lead to a wrong result. To handle this problem, we provide a deep learning-based fully automatic method for detecting and inpainting damaged regions in material microscopic images, which can automatically inpaint damaged regions with different positions and shapes, as well as we also use a data augmentation method to improve the performance of inpainting model. We evaluate our method on Al-La alloy microscopic images, which indicates that our method can achieve promising performance on inpainted and material microstructure characterisation results compared to other image inpainting software for both accuracy and time consumption. LAY DESCRIPTION: A basic goal of materials data analysis is to extract useful information from materials datasets that can in turn be used to establish connections along the composition-processing-structure-properties chain. The microscopic images obtained by a microscope is the key carrier of material microstructural information. Researchers usually use image analysis algorithms to extract regions of interest or useful features from microscopic images, aiming to analyse material microstructure, organ tissues or device quality etc. Therefore, the integrity and clarity of the microscopic image are the most important attributes for image feature extraction. Scientists and engineers have been trying to develop various technologies to obtain perfect microscopic images. However, in practice, some extrinsic defects are often introduced during the preparation and/or shooting processes, and the elimination of these defects often requires mass efforts and cost, or even is impossible at present. Take the microstructure image of metallic material for example, samples prepared to microstructure characterisation often need to go through several steps such as cutting, grinding with sandpaper, polishing, etching, and cleaning. During the grinding and polishing process, defects such as scratches could be introduced. During the etching and cleaning process, some defects such as rust caused by substandard etching, stains etc. may arise and be persisted. These defects can be treated as damaged regions with nonfixed positions, different sizes, and random shapes, resulting in the loss of information, which seriously affects subsequent visual observation and microstructural feature extraction. To handle this problem, we provide a deep learning-based fully automatic method for detecting and inpainting damaged regions in material microscopic images, which can automatically inpaint damaged regions with different positions and shapes, as well as we also use a data augmentation method to improve the performance of inpainting model. We evaluate our method on Al-La alloy microscopic images, which indicates that our method can achieve promising performance on inpainted and material microstructure characterisation results compared to other image inpainting software for both accuracy and time consumption.

Targeted mutagenesis of BnTT8 homologs controls yellow seed coat development for effective oil production in Brassica napus L.

Yellow seed is a desirable trait with great potential for improving seed quality in Brassica crops. Unfortunately, no natural or induced yellow seed germplasms have been found in Brassica napus, an important oil crop, which likely reflects its genome complexity and the difficulty of the simultaneous random mutagenesis of multiple gene copies with functional redundancy. Here, we demonstrate the first application of CRISPR/Cas9 for creating yellow-seeded mutants in rapeseed. The targeted mutations of the BnTT8 gene were stably transmitted to successive generations, and a range of homozygous mutants with loss-of-function alleles of the target genes were obtained for phenotyping. The yellow-seeded phenotype could be recovered only in targeted mutants of both BnTT8 functional copies, indicating that the redundant roles of BnA09.TT8 and BnC09.TT8b are vital for seed colour. The BnTT8 double mutants produced seeds with elevated seed oil and protein content and altered fatty acid (FA) composition without any serious defects in the yield-related traits, making it a valuable resource for rapeseed breeding programmes. Chemical staining and histological analysis showed that the targeted mutations of BnTT8 completely blocked the proanthocyanidin (PA)-specific deposition in the seed coat. Further, transcriptomic profiling revealed that the targeted mutations of BnTT8 resulted in the broad suppression of phenylpropanoid/flavonoid biosynthesis genes, which indicated a much more complex molecular mechanism underlying seed colour formation in rapeseed than in Arabidopsis and other Brassica species. In addition, gene expression analysis revealed the possible mechanism through which BnTT8 altered the oil content and fatty acid composition in seeds.

Analytic and Unambiguous Phase-Based Algorithm for 3-D Localization of a Single Source with Uniform Circular Array.

This paper presents an analytic algorithm for estimating three-dimensional (3-D) localization of a single source with uniform circular array (UCA) interferometers. Fourier transforms are exploited to expand the phase distribution of a single source and the localization problem is reformulated as an equivalent spectrum manipulation problem. The 3-D parameters are decoupled to different spectrums in the Fourier domain. Algebraic relations are established between the 3-D localization parameters and the Fourier spectrums. Fourier sampling theorem ensures that the minimum element number for 3-D localization of a single source with a UCA is five. Accuracy analysis provides mathematical insights into the 3-D localization algorithm that larger number of elements gives higher estimation accuracy. In addition, the phase-based high-order difference invariance (HODI) property of a UCA is found and exploited to realize phase range compression. Following phase range compression, ambiguity resolution is addressed by the HODI of a UCA. A major advantage of the algorithm is that the ambiguity resolution and 3-D localization estimation are both analytic and are processed simultaneously, hence computationally efficient. Numerical simulations and experimental results are provided to verify the effectiveness of the proposed 3-D localization algorithm.

Parameter Estimation of Multiple Frequency-Hopping Signals with Two Sensors.

This paper essentially focuses on parameter estimation of multiple wideband emitting sources with time-varying frequencies, such as two-dimensional (2-D) direction of arrival (DOA) and signal sorting, with a low-cost circular synthetic array (CSA) consisting of only two rotating sensors. Our basic idea is to decompose the received data, which is a superimposition of phase measurements from multiple sources into separated groups and separately estimate the DOA associated with each source. Motivated by joint parameter estimation, we propose to adopt the expectation maximization (EM) algorithm in this paper; our method involves two steps, namely, the expectation-step (E-step) and the maximization (M-step). In the E-step, the correspondence of each signal with its emitting source is found. Then, in the M-step, the maximum-likelihood (ML) estimates of the DOA parameters are obtained. These two steps are iteratively and alternatively executed to jointly determine the DOAs and sort multiple signals. Closed-form DOA estimation formulae are developed by ML estimation based on phase data, which also realize an optimal estimation. Directional ambiguity is also addressed by another ML estimation method based on received complex responses. The Cramer-Rao lower bound is derived for understanding the estimation accuracy and performance comparison. The verification of the proposed method is demonstrated with simulations.

Disulfidptosis decoded: a journey through cell death mysteries, regulatory networks, disease paradigms and future directions.

Cell death is an important part of the life cycle, serving as a foundation for both the orderly development and the maintenance of physiological equilibrium within organisms. This process is fundamental, as it eliminates senescent, impaired, or aberrant cells while also promoting tissue regeneration and immunological responses. A novel paradigm of programmed cell death, known as disulfidptosis, has recently emerged in the scientific circle. Disulfidptosis is defined as the accumulation of cystine by cancer cells with high expression of the solute carrier family 7 member 11 (SLC7A11) during glucose starvation. This accumulation causes extensive disulfide linkages between F-actins, resulting in their contraction and subsequent detachment from the cellular membrane, triggering cellular death. The RAC1-WRC axis is involved in this phenomenon. Disulfidptosis sparked growing interest due to its potential applications in a variety of pathologies, particularly oncology, neurodegenerative disorders, and metabolic anomalies. Nonetheless, the complexities of its regulatory pathways remain elusive, and its precise molecular targets have yet to be definitively identified. This manuscript aims to meticulously dissect the historical evolution, molecular underpinnings, regulatory frameworks, and potential implications of disulfidptosis in various disease contexts, illuminating its promise as a groundbreaking therapeutic pathway and target.

Artificial intelligence in skeletal metastasis imaging.

In the field of metastatic skeletal oncology imaging, the role of artificial intelligence (AI) is becoming more prominent. Bone metastasis typically indicates the terminal stage of various malignant neoplasms. Once identified, it necessitates a comprehensive revision of the initial treatment regime, and palliative care is often the only resort. Given the gravity of the condition, the diagnosis of bone metastasis should be approached with utmost caution. AI techniques are being evaluated for their efficacy in a range of tasks within medical imaging, including object detection, disease classification, region segmentation, and prognosis prediction in medical imaging. These methods offer a standardized solution to the frequently subjective challenge of image interpretation.This subjectivity is most desirable in bone metastasis imaging. This review describes the basic imaging modalities of bone metastasis imaging, along with the recent developments and current applications of AI in the respective imaging studies. These concrete examples emphasize the importance of using computer-aided systems in the clinical setting. The review culminates with an examination of the current limitations and prospects of AI in the realm of bone metastasis imaging. To establish the credibility of AI in this domain, further research efforts are required to enhance the reproducibility and attain robust level of empirical support.

Epigenetic regulation and factors that influence the effect of iPSCs-derived neural stem/progenitor cells (NS/PCs) in the treatment of spinal cord injury.

Spinal cord injury (SCI) is a severe neurological disorder that causes neurological impairment and disability. Neural stem/progenitor cells (NS/PCs) derived from induced pluripotent stem cells (iPSCs) represent a promising cell therapy strategy for spinal cord regeneration and repair. However, iPSC-derived NS/PCs face many challenges and issues in SCI therapy; one of the most significant challenges is epigenetic regulation and that factors that influence this mechanism. Epigenetics refers to the regulation of gene expression and function by DNA methylation, histone modification, and chromatin structure without changing the DNA sequence. Previous research has shown that epigenetics plays a crucial role in the generation, differentiation, and transplantation of iPSCs, and can influence the quality, safety, and outcome of transplanted cells. In this study, we review the effects of epigenetic regulation and various influencing factors on the role of iPSC-derived NS/PCs in SCI therapy at multiple levels, including epigenetic reprogramming, regulation, and the adaptation of iPSCs during generation, differentiation, and transplantation, as well as the impact of other therapeutic tools (e.g., drugs, electrical stimulation, and scaffolds) on the epigenetic status of transplanted cells. We summarize our main findings and insights in this field and identify future challenges and directions that need to be addressed and explored.

Syringaresinol promotes the recovery of spinal cord injury by inhibiting neuron apoptosis via activating the ubiquitination factor E4B/AKT Serine/Threonine kinase signal pathway.

Spinal cord injury (SCI) is a serious traumatic disease with no effective treatment. This study aimed to explore the therapeutic effect of syringaresinol on SCI. First, the potential targets and associated signaling pathways of syringaresinol were predicted by bioinformatics analysis and molecular docking. Second, MTT was employed to evaluate cell proliferation rate, Western blot was performed to detect protein expression, RT-qPCR was conducted to detect mRNA expression levels, flow cytometry and 5-ethynyl-2'-deoxyuridine (EDU) staining were used to determine cell apoptosis, and immunofluorescence and immunohistochemistry were used to estimate the expression of RNA binding fox-1 homolog 3 and clipped caspase 3. Basso-Beattie-Bresnahan scores and inclined plate tests were conducted to analyze hindlimb locomotor function. Results showed that syringaresinol could inhibit the apoptosis of glutamate-treated SHSY5Y cells by upregulating the expression of ubiquitination factor E4B (UBE4B) and activating the AKT serine/threonine kinase (AKT) signaling pathway. This effect can be rescued by UBE4B knockdown or AKT pathway inhibition. Syringaresinol remarkably improved locomotor function and increased neuronal survival in SCI rats. Our results suggested that syringaresinol could promote locomotor functional recovery by reducing neuronal apoptosis by activating the UBE4B/AKT signaling pathway.

Single-cell and genome-wide Mendelian randomization identifies causative genes for gout.

BACKGROUND: Gout is a prevalent manifestation of metabolic osteoarthritis induced by elevated blood uric acid levels. The purpose of this study was to investigate the mechanisms of gene expression regulation in gout disease and elucidate its pathogenesis. METHODS: The study integrated gout genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and methylation quantitative trait loci (mQTL) data for analysis, and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and gout. RESULTS: We identified 17 association signals for gout at unique genetic loci, including four genes related by protein-protein interaction network (PPI) analysis: TRIM46, THBS3, MTX1, and KRTCAP2. Additionally, we discerned 22 methylation sites in relation to gout. The study also found that genes such as TRIM46, MAP3K11, KRTCAP2, and TM7SF2 could potentially elevate the risk of gout. Through a Mendelian randomization (MR) analysis, we identified three proteins causally associated with gout: ADH1B, BMP1, and HIST1H3A. CONCLUSION: According to our findings, gout is linked with the expression and function of particular genes and proteins. These genes and proteins have the potential to function as novel diagnostic and therapeutic targets for gout. These discoveries shed new light on the pathological mechanisms of gout and clear the way for future research on this condition.

Albumosomes formed by cytoplasmic pre-folding albumin maintain mitochondrial homeostasis and inhibit nonalcoholic fatty liver disease.

Hepatic mitochondrial dysfunction contributes to the progression of nonalcoholic fatty liver disease (NAFLD). However, the factors that maintain mitochondrial homeostasis, especially in hepatocytes, are largely unknown. Hepatocytes synthesize various high-level plasma proteins, among which albumin is most abundant. In this study, we found that pre-folding albumin in the cytoplasm is completely different from folded albumin in the serum. Mechanistically, endogenous pre-folding albumin undergoes phase transition in the cytoplasm to form a shell-like spherical structure, which we call the "albumosome". Albumosomes interact with and trap pre-folding carnitine palmitoyltransferase 2 (CPT2) in the cytoplasm. Albumosomes control the excessive sorting of CPT2 to the mitochondria under high-fat-diet-induced stress conditions; in this way, albumosomes maintain mitochondrial homeostasis from exhaustion. Physiologically, albumosomes accumulate in hepatocytes during murine aging and protect the livers of aged mice from mitochondrial damage and fat deposition. Morphologically, mature albumosomes have a mean diameter of 4µm and are surrounded by heat shock protein Hsp90 and Hsp70 family proteins, forming a larger shell. The Hsp90 inhibitor 17-AAG promotes hepatic albumosomal accumulation in vitro and in vivo, through which suppressing the progression of NAFLD in mice.

Effects of low-intensity ultrasound opening the blood-brain barrier on Alzheimer's disease-a mini review.

Due to the complex pathological mechanisms of Alzheimer's disease (AD), its treatment remains a challenge. One of the major difficulties in treating AD is the difficulty for drugs to cross the blood-brain barrier (BBB). Low-intensity ultrasound (LIUS) is a novel type of ultrasound with neuromodulation function. It has been widely reported that LIUS combined with intravenous injection of microbubbles (MB) can effectively, safely, and reversibly open the BBB to achieve non-invasive targeted drug delivery. However, many studies have reported that LIUS combined with MB-mediated BBB opening (LIUS + MB-BBBO) can improve pathological deposition and cognitive impairment in AD patients and mice without delivering additional drugs. This article reviews the relevant research studies on LIUS + MB-BBBO in the treatment of AD, analyzes its potential mechanisms, and summarizes relevant ultrasound parameters.