Increased FGF-21 Improves Ectopic Lipid Deposition in the Liver and Skeletal Muscle.

Obesity can lead to excessive lipid accumulation in non-adipose tissues, such as the liver and skeletal muscles, leading to ectopic lipid deposition and damaging target organ function through lipotoxicity. FGF-21 is a key factor in regulating lipid metabolism, so we aim to explore whether FGF-21 is involved in improving ectopic lipid deposition. We observed the characteristics of ectopic lipid deposition in the liver and skeletal muscles of obesity-resistant mice, detected the expression of FGF-21 and perilipin, and found that obesity-resistant mice showed a decrease in ectopic lipid deposition in the liver and skeletal muscles and increased expression of FGF-21. After inhibiting the expression of FGF-21, a more severe lipid deposition in liver cells and skeletal muscle cells was found. The results indicate that inhibiting FGF-21 can exacerbate ectopic lipid deposition via regulating lipid droplet synthesis and decomposition, as well as free fatty acid translocation and oxidation. In conclusion, FGF-21 is involved in improving ectopic lipid deposition caused by obesity in the liver and skeletal muscles.

Sustainable biochar application in anammox process: Unveiling novel pathways for enhanced nitrogen removal and efficient start-up at low temperature.

This study explored the use of biochar to accelerate the establishment of anaerobic ammonium oxidation (anammox) reactors operating at 15 ± 1℃. Incorporating 10 g/L bamboo charcoal in S1 accelerated the start-up of anammox in 87 days, which was significantly shorter than 103 days in S0 (without biochar). After 140 days, S1 exhibited a 10.9 % increase in nitrogen removal efficiency due to a 28.9 % elevation in extracellular polymeric substances, bolstering anammox bacterial resilience. Predominant anammox bacteria (Cadidatus Brocadia and Cadidatus Jettenia) showed relative abundances of 3.19 % and 0.38 % in S1, respectively, which were significantly higher than 0.40 % and 0.05 % in S0. Biochar provides favorable habitats for the enrichment of anammox bacteria and accelerates the establishment of anammox at low temperatures. This finding holds promise for enhancing the efficiency of anammox in cold climates and advancing sustainable wastewater nitrogen removal.

Airway hillocks are injury-resistant reservoirs of unique plastic stem cells.

Airway hillocks are stratified epithelial structures of unknown function1. Hillocks persist for months and have a unique population of basal stem cells that express genes associated with barrier function and cell adhesion. Hillock basal stem cells continually replenish overlying squamous barrier cells. They exhibit dramatically higher turnover than the abundant, largely quiescent classic pseudostratified airway epithelium. Hillocks resist a remarkably broad spectrum of injuries, including toxins, infection, acid and physical injury because hillock squamous cells shield underlying hillock basal stem cells from injury. Hillock basal stem cells are capable of massive clonal expansion that is sufficient to resurface denuded airway, and eventually regenerate normal airway epithelium with each of its six component cell types. Hillock basal stem cells preferentially stratify and keratinize in the setting of retinoic acid signalling inhibition, a known cause of squamous metaplasia2,3. Here we show that mouse hillock expansion is the cause of vitamin A deficiency-induced squamous metaplasia. Finally, we identify human hillocks whose basal stem cells generate functional squamous barrier structures in culture. The existence of hillocks reframes our understanding of airway epithelial regeneration. Furthermore, we show that hillocks are one origin of 'squamous metaplasia', which is long thought to be a precursor of lung cancer.

Light-Sheet Microscopic Imaging of Whole-Mouse Vascular Network with Fluorescent Microsphere Perfusion.

Visualizing the whole vascular network system is crucial for understanding the pathogenesis of specific diseases and devising targeted therapeutic interventions. Although the combination of light sheet microscopy and tissue-clearing methods has emerged as a promising approach for investigating the blood vascular network, leveraging the spatial resolution down to the capillary level and the ability to image centimeter-scale samples remains difficult. Especially, as the resolution improves, the issue of photobleaching outside the field of view poses a challenge to image the whole vascular network of adult mice at capillary resolution. Here, we devise a fluorescent microsphere vascular perfusion method to enable labeling of the whole vascular network in adult mice, which overcomes the photobleaching limit during the imaging of large samples. Moreover, by combining the utilization of a large-scale light-sheet microscope and tissue clearing protocols for whole-mouse samples, we achieve the capillary-level imaging resolution (3.2 × 3.2 × 6.5 µm) of the whole vascular network with dimensions of 45 × 15 × 82 mm in adult mice. This method thus holds great potential to deliver mesoscopic resolution images of various tissue organs for whole-animal imaging.

Enhanced reduction of graphene oxide via laser-dispersion coupling: Towards large-scale, low-defect graphene for crease-free heat-dissipating membranes in advanced flexible electronics.

The advancement of flexible electronics demands improved components, necessitating heat dissipation membranes (HDMs) to exhibit high thermal conductivity while maintaining structural integrity and performance stability even after extensive deformation. Herein, we have devised a laser-modulated reduction technique for graphene oxide (GO), enabling the fabrication of high-quality, large-scale, low-defect graphene, which yields high-performance HDMs after orderly deposition. The work underscores the crucial role of the laser wavelength and dispersion liquid's coupling intensity in influencing the morphology and properties of graphene. Optimal coupling effect and energy conversion are realized when a laser of 1064 nm wavelength irradiates a triethylene glycol (TEG)/N,N-Dimethylformamide (DMF) dispersion. This unique synergy generates high transient energy, which facilitates the deprotonation process and ensures a swift, comprehensive GO reduction. In contrast to conventional water-based laser reduction methods, the accelerated reaction magnifies the size of the graphene sheets by mitigating the ablation effect. After membrane construction with an ordered structure, the corresponding membrane exhibits a high thermal conductivity of 1632 W m-1 K-1, requiring only ∼1/10 of the total preparation time required by other reported methods. Remarkably, the resulting HDM demonstrates superior resilience against creasing and folding, maintaining excellent smoothness and negligible reduction in thermal conductivity after violent rubbing. The combination of exceptional flexibility and thermal conductivity in HDMs paves the way for long-term practical use in the flexible electronics industry.

[Research on Position Verification of Multi-Leaf Collimator (MLC) and Dose Verification Based on Electronic Portal Imaging Device].

Objective: A quality control (QC) system based on the electronic portal imaging device (EPID) system was used to realize the Multi-Leaf Collimator (MLC) position verification and dose verification functions on Primus and VenusX accelerators. Methods: The MLC positions were calculated by the maximum gradient method of gray values to evaluate the deviation. The dose of images acquired by EPID were reconstructed using the algorithm combining dose calibration and dose calculation. The dose data obtained by EPID and two-dimensional matrix (MapCheck/PTW) were compared with the dose calculated by Pinnacle/TiGRT TPS for γ passing rate analysis. Results: The position error of VenusX MLC was less than 1 mm. The position error of Primus MLC was significantly reduced after being recalibrated under the instructions of EPID. For the dose reconstructed by EPID, the average γ passing rates of Primus were 98.86% and 91.39% under the criteria of 3%/3 mm, 10% threshold and 2%/2 mm, 10% threshold, respectively. The average γ passing rates of VenusX were 98.49% and 91.11%, respectively. Conclusion: The EPID-based accelerator quality control system can improve the efficiency of accelerator quality control and reduce the workload of physicists.

Design, synthesis, and evaluation of novel quindoline derivatives with fork-shaped side chains as RNA G-quadruplex stabilizers for repressing oncogene NRAS translation.

NRAS mutation is the second most common oncogenic factor in cutaneous melanoma. Inhibiting NRAS translation by stabilizing the G-quadruplex (G4) structure with small molecules seems to be a potential strategy for cancer therapy due to the NRAS protein's lack of a druggable pocket. To enhance the effects of previously reported G4 stabilizers quindoline derivatives, we designed and synthesized a novel series of quindoline derivatives with fork-shaped side chains by introducing (alkylamino)alkoxy side chains. Panels of experimental results showed that introducing a fork-shaped (alkylamino)alkoxy side chain could enhance the stabilizing abilities of the ligands against NRAS RNA G-quadruplexes and their anti-melanoma activities. One of them, 10b, exhibited good antitumor activity in the NRAS-mutant melanoma xenograft mouse model, showing the therapeutic potential of this kind of compounds.

High Manganese Content of Lipid NanoMn (LNM) by Microfluidic Technology for Enhancing Anti-Tumor Immunity.

Immunotherapy is a clinically effective method for treating tumors. Manganese can activate the cGAS-STING signaling pathway and induce an anti-tumor immune response. However, its efficacy is hindered by non-specific distribution and low uptake rates. In this study, we employed microfluidic technology to design and develop an innovative preparation process, resulting in the creation of a novel manganese lipid nanoparticle (LNM). The lipid manganese nanoparticle produced in this process boasts a high manganese payload, excellent stability, the capacity for large-scale production, and high batch repeatability. LNM has effectively demonstrated the ability to activate the cGAS-STING signaling pathway, induce the production of pro-inflammatory cytokines, and inhibit tumor development. Notably, LNM does not require combination chemotherapy drugs or other immune activators. Therefore, LNM presents a safe, straightforward, and efficient strategy for anti-tumor immune activation, with the potential for scalable production.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis.

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

Prognosis Prediction of Diffuse Large B-cell Lymphoma in 18F-FDG PET images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

Rubisco and sucrose synthesis and translocation are involved in the regulation of photosynthesis in wheat with different source-sink relationships.

Source-sink relationships influence photosynthesis. So far, the limiting factors for photosynthesis of wheat cultivars with different source-sink relationships have not been determined. We aimed to determine the variation patterns of photosynthetic characteristics of wheat cultivars with different source-sink relationships. In this study, two wheat cultivars with different source-sink relationships were selected for photosynthetic physiological analyses. The results showed that YM25 (source-limited cultivar) had higher photosynthetic efficiency compared to YM1 (sink-limited cultivar). This is mainly due to a stronger photochemical efficiency, electron transfer capacity, and Rubisco carboxylation capacity of YM25. YM25 accumulated less soluble carbohydrates in flag leaves than YM1. This is mainly due to the stronger sucrose synthesis and transport capacity of YM25 by presenting higher sucrose-related enzyme activities and gene expression. A PCA analysis showed that Rubisco was the main factor limiting the photosynthetic capacity of YM25. The soluble sugar accumulation in flag leaves and sink limitation decreased the photosynthetic activity of YM1. Increased N application improved source-sink relationships and increased grain yield and source leaf photosynthetic capacity in both two wheat cultivars. Taken together, our findings suggest that Rubisco and sucrose synthesis and translocation are involved in the regulation of photosynthesis of wheat cultivars with different source-sink relationships and that source and sink limitation effects should be considered in photosynthesis.

Hypoxia Reversion by Low-Immunogenic Ultra-Acid-Sensitive Comicelles of Protein-Polymer Conjugates Sensitizes Tumors to Photodynamic Therapy.

Hypoxia is characteristic of the tumor microenvironment, which is correlated with resistance to photodynamic therapy (PDT), radiotherapy, chemotherapy, and immunotherapy. Catalase is potentially useful to catalyze the conversion of endogenous H2O2 to O2 for hypoxia reversion. However, the efficient delivery of catalase into the hypoxia regions of tumors is a huge challenge. Here, we report the self-assembly of ultra-acid-sensitive polymer conjugates of catalase and albumin into nanomicelles that are responsive to the acidic tumor microenvironment. The immunogenicity of catalase is mitigated by the presence of albumin, which reduces the cross-linking of catalase with B cell receptors, resulting in improved pharmacokinetics. The ultra acid sensitivity of the nanomicelles makes it possible to efficiently escape the lysosomal degradation after endocytosis and permeate into the interior of tumors to reverse hypoxia in vitro and in vivo. In mice bearing triple-negative breast cancer, the nanomicelles loaded with a photosensitizer effectively accumulate and penetrate into the whole tumors to generate a sufficient amount of O2 to reverse hypoxia, leading to enhanced efficacy of PDT without detectable side effects. These findings provide a general strategy of self-assembly to design low-immunogenic ultra-acid-sensitive comicelles of protein-polymer conjugates to reverse tumor hypoxia, which sensitizes tumors to PDT.

Diagnosis of benign and malignant peripheral lung lesions based on a feature model constructed by the random forest algorithm for grayscale and contrast-enhanced ultrasound.

Rationale and objectives: To construct a predictive model for benign and malignant peripheral pulmonary lesions (PPLs) using a random forest algorithm based on grayscale ultrasound and ultrasound contrast, and to evaluate its diagnostic value. Materials and methods: We selected 254 patients with PPLs detected using chest lung computed tomography between October 2021 and July 2023, including 161 malignant and 93 benign lesions. Relevant variables for judging benign and malignant PPLs were screened using logistic regression analysis. A model was constructed using the random forest algorithm, and the test set was verified. Correlations between these relevant variables and the diagnosis of benign and malignant PPLs were evaluated. Results: Age, lesion shape, size, angle between the lesion border and chest wall, boundary clarity, edge regularity, air bronchogram, vascular signs, enhancement patterns, enhancement intensity, homogeneity of enhancement, number of non-enhancing regions, non-enhancing region type, arrival time (AT) of the lesion, lesion-lung AT difference, AT difference ratio, and time to peak were the relevant variables for judging benign and malignant PPLs. Consequently, a model and receiver operating characteristic curve were constructed with an AUC of 0.92 and an accuracy of 88.2%. The test set results showed that the model had good predictive ability. The index with the highest correlation for judging benign and malignant PPLs was the AT difference ratio. Other important factors were lesion size, patient age, and lesion morphology. Conclusion: The random forest algorithm model constructed based on clinical data and ultrasound imaging features has clinical application value for predicting benign and malignant PPLs.

A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer.

OBJECTIVE: This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients. METHODS: 4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT. RESULTS: The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT. CONCLUSIONS: Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.

Electroenzymatic tandem catalysis for the conversion of nitrate into ammonia.

A porous silver nanostructure-supported ionic liquid-modified chloroperoxidase nanohybrid was successfully used in electroenzymatic tandem catalysis to achieve an efficient, mild, and stable approach for the conversion of nitrate into ammonia.

A web-based tool for real-time adequacy assessment of kidney biopsies.

The escalating incidence of kidney biopsies providing insufficient tissue for diagnosis poses a dual challenge, straining the healthcare system and jeopardizing patients who may require rebiopsy or face the prospect of an inaccurate diagnosis due to an unsampled disease. Here, we introduce a web-based tool that can provide real-time, quantitative assessment of kidney biopsy adequacy directly from photographs taken with a smartphone camera. The software tool was developed using a deep learning-driven automated segmentation technique, trained on a dataset comprising nephropathologist-confirmed annotations of the kidney cortex on digital biopsy images. Our framework demonstrated favorable performance in segmenting the cortex via 5-fold cross-validation (Dice coefficient: 0.788±0.130) (n=100). Offering a bedside tool for kidney biopsy adequacy assessment has the potential to provide real-time guidance to the physicians performing medical kidney biopsies, reducing the necessity for re-biopsies. Our tool can be accessed through our web-based platform: http://www.biopsyadequacy.org.

Simplified Modular Access to Enantiopure 1,2-Aminoalcohols via Ni-Electrocatalytic Decarboxylative Arylation.

Chiral aminoalcohols are omnipresent in bioactive compounds. Conventional strategies to access this motif involve multiple-step reactions to install the requisite functionalities stereoselectively using conventional polar bond analysis. This study reveals that a simple chiral oxazolidine-based carboxylic acid can be readily transformed to substituted chiral aminoalcohols with high stereochemical control by Ni-electrocatalytic decarboxylative arylation. This general, robust, and scalable coupling can be used to synthesize a variety of medicinally important compounds, avoiding protecting and functional group manipulations, thereby dramatically simplifying their preparation.

Brain functional connectivity alterations of Wernicke's area in individuals with autism spectrum conditions in multi-frequency bands: A mega-analysis.

Characterized by severe deficits in communication, most individuals with autism spectrum conditions (ASC) experience significant language dysfunctions, thereby impacting their overall quality of life. Wernicke's area, a classical and traditional brain region associated with language processing, plays a substantial role in the manifestation of language impairments. The current study carried out a mega-analysis to attain a comprehensive understanding of the neural mechanisms underpinning ASC, particularly in the context of language processing. The study employed the Autism Brain Image Data Exchange (ABIDE) dataset, which encompasses data from 443 typically developing (TD) individuals and 362 individuals with ASC. The objective was to detect abnormal functional connectivity (FC) between Wernicke's area and other language-related functional regions, and identify frequency-specific altered FC using Wernicke's area as the seed region in ASC. The findings revealed that increased FC in individuals with ASC has frequency-specific characteristics. Further, in the conventional frequency band (0.01-0.08 Hz), individuals with ASC exhibited increased FC between Wernicke's area and the right thalamus compared with TD individuals. In the slow-5 frequency band (0.01-0.027 Hz), increased FC values were observed in the left cerebellum Crus II and the right lenticular nucleus, pallidum. These results provide novel insights into the potential neural mechanisms underlying communication deficits in ASC from the perspective of language impairments.

Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning.

Quantitative phase imaging (QPI) through multi-core fibers (MCFs) has been an emerging in vivo label-free endoscopic imaging modality with minimal invasiveness. However, the computational demands of conventional iterative phase retrieval algorithms have limited their real-time imaging potential. We demonstrate a learning-based MCF phase imaging method that significantly reduced the phase reconstruction time to 5.5 ms, enabling video-rate imaging at 181 fps. Moreover, we introduce an innovative optical system that automatically generated the first, to the best of our knowledge, open-source dataset tailored for MCF phase imaging, comprising 50,176 paired speckles and phase images. Our trained deep neural network (DNN) demonstrates a robust phase reconstruction performance in experiments with a mean fidelity of up to 99.8%. Such an efficient fiber phase imaging approach can broaden the applications of QPI in hard-to-reach areas.

Exploring the Mechanism of Immediate Analgesia Induced by Tuina Intervention on Minor Chronic Constriction Injury in Rats Using LC-MS.

Purpose: This study aimed to investigate changes in metabolomic expression in the spinal dorsal horn (SDH) and thalamus during a Tuina session, aiming to elucidate the mechanism of immediate analgesia. Methods: The rats were randomly divided into three groups: the Sham group, the Model group, and the Tuina group. A minor chronic constriction injury (minor CCI) model was established in both the Model group and the Tuina group. The therapeutic effect of Tuina was determined using the mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) tests. Differential metabolites of the SDH and thalamus were detected using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Bioinformatic analysis was performed using CV, PCA, Venn, and KEGG. Results: The therapeutic effect of MWT and TWL after instant Tuina intervention was significant. The therapeutic effect of Tuina instant was significantly better compared to the Model group. In the Veen analysis, it was found that Tuina instantly regulates 10 differential metabolites in the SDH and 5 differential metabolites in the thalamus. In the KEGG enrichment analysis, we found that differential metabolites were enriched in 43 pathways in the thalamus and 70 pathways in the SDH. Conclusion: Tuina therapy may have analgesic effects by metabolizing neurotransmitters such as 2-Picolinic Acid, 5-Hydroxy-Tryptophan Glutathione Betaine-aldehyde-chloride Leucine Lysine Methionine Sarcosine Succinic Acid Histidine Acetylcholine and 5-Hydroxyindoleacetic Acid through the cAMP pathway. It also affects pathways of neurodegeneration-multiple diseases, butanoate metabolism, tyrosine metabolism.