Tracing the origin of alveolar stem cells in lung repair and regeneration.

Alveolar type 2 (AT2) cells are stem cells of the alveolar epithelia. Previous genetic lineage tracing studies reported multiple cellular origins for AT2 cells after injury. However, conventional lineage tracing based on Cre-loxP has the limitation of non-specific labeling. Here, we introduced a dual recombinase-mediated intersectional genetic lineage tracing approach, enabling precise investigation of AT2 cellular origins during lung homeostasis, injury, and repair. We found AT1 cells, being terminally differentiated, did not contribute to AT2 cells after lung injury and repair. Distinctive yet simultaneous labeling of club cells, bronchioalveolar stem cells (BASCs), and existing AT2 cells revealed the exact contribution of each to AT2 cells post-injury. Mechanistically, Notch signaling inhibition promotes BASCs but impairs club cells' ability to generate AT2 cells during lung repair. This intersectional genetic lineage tracing strategy with enhanced precision allowed us to elucidate the physiological role of various epithelial cell types in alveolar regeneration following injury.

Dynamics of Endothelial Cell Generation and Turnover in Arteries During Homeostasis and Diseases.

BACKGROUND: Endothelial cell (EC) generation and turnover by self-proliferation contributes to vascular repair and regeneration. The ability to accurately measure the dynamics of EC generation would advance our understanding of cellular mechanisms of vascular homeostasis and diseases. However, it is currently challenging to evaluate the dynamics of EC generation in large vessels such as arteries because of their infrequent proliferation. METHODS: By using dual recombination systems based on Cre-loxP and Dre-rox, we developed a genetic system for temporally seamless recording of EC proliferation in vivo. We combined genetic recording of EC proliferation with single-cell RNA sequencing and gene knockout to uncover cellular and molecular mechanisms underlying EC generation in arteries during homeostasis and disease. RESULTS: Genetic proliferation tracing reveals that ≈3% of aortic ECs undergo proliferation per month in adult mice during homeostasis. The orientation of aortic EC division is generally parallel to blood flow in the aorta, which is regulated by the mechanosensing protein Piezo1. Single-cell RNA sequencing analysis reveals 4 heterogeneous aortic EC subpopulations with distinct proliferative activity. EC cluster 1 exhibits transit-amplifying cell features with preferential proliferative capacity and enriched expression of stem cell markers such as Sca1 and Sox18. EC proliferation increases in hypertension but decreases in type 2 diabetes, coinciding with changes in the extent of EC cluster 1 proliferation. Combined gene knockout and proliferation tracing reveals that Hippo/vascular endothelial growth factor receptor 2 signaling pathways regulate EC proliferation in large vessels. CONCLUSIONS: Genetic proliferation tracing quantitatively delineates the dynamics of EC generation and turnover, as well as EC division orientation, in large vessels during homeostasis and disease. An EC subpopulation in the aorta exhibits more robust cell proliferation during homeostasis and type 2 diabetes, identifying it as a potential therapeutic target for vascular repair and regeneration.

CD4+CD57+ senescent T cells as promoters of systemic lupus erythematosus pathogenesis and the therapeutic potential of senolytic BCL-2 inhibitor.

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by persistent activation of immune cells and overproduction of autoantibodies. The accumulation of senescent T and B cells has been observed in SLE and other immune-mediated diseases. However, the exact mechanistic pathways contributing to this process in SLE remain incompletely understood. In this study, we found that in SLE patients: (1) the frequency of CD4+CD57+ senescent T cells was significantly elevated and positively correlated with disease activity; (2) the expression levels of B-lymphoma-2 (BCL-2) family and interferon-induced genes (ISGs) were significantly upregulated; and (3) in vitro, the cytokine IL-15 stimulation increased the frequency of senescent CD4+ T cells and upregulated the expression of BCL-2 family and ISGs. Further, treatment with ABT-263 (a senolytic BCL-2 inhibitor) in MRL/lpr mice resulted in decreased: (1) frequency of CD4+CD44hiCD62L-PD-1+CD153+ senescent CD4+ T cells; (2) frequency of CD19+CD11c+T-bet+ age-related B cells; (3) level of serum antinuclear antibody; (4) proteinuria; (5) frequency of Tfh cells; and (6) renal histopathological abnormalities. Collectively, these results indicated a dominant role for CD4+CD57+ senescent CD4+ T cells in the pathogenesis of SLE and senolytic BCL-2 inhibitor ABT-263 may be the potential treatment in ameliorating lupus phenotypes.

The doublesex gene regulates dimorphic sexual and aggressive behaviors in Drosophila.

Most animal species display dimorphic sexual behaviors and male-biased aggressiveness. Current models have focused on the male-specific product from the fruitless (fruM) gene, which controls male courtship and male-specific aggression patterns in fruit flies, and describe a male-specific mechanism underlying sexually dimorphic behaviors. Here we show that the doublesex (dsx) gene, which expresses male-specific DsxM and female-specific DsxF transcription factors, functions in the nervous system to control both male and female sexual and aggressive behaviors. We find that Dsx is not only required in central brain neurons for male and female sexual behaviors, but also functions in approximately eight pairs of male-specific neurons to promote male aggressiveness and approximately two pairs of female-specific neurons to inhibit female aggressiveness. DsxF knockdown females fight more frequently, even with males. Our findings reveal crucial roles of dsx, which is broadly conserved from worms to humans, in a small number of neurons in both sexes to establish dimorphic sexual and aggressive behaviors.

Identification of microbe-disease signed associations via multi-scale variational graph autoencoder based on signed message propagation.

BACKGROUND: Plenty of clinical and biomedical research has unequivocally highlighted the tremendous significance of the human microbiome in relation to human health. Identifying microbes associated with diseases is crucial for early disease diagnosis and advancing precision medicine. RESULTS: Considering that the information about changes in microbial quantities under fine-grained disease states helps to enhance a comprehensive understanding of the overall data distribution, this study introduces MSignVGAE, a framework for predicting microbe-disease sign associations using signed message propagation. MSignVGAE employs a graph variational autoencoder to model noisy signed association data and extends the multi-scale concept to enhance representation capabilities. A novel strategy for propagating signed message in signed networks addresses heterogeneity and consistency among nodes connected by signed edges. Additionally, we utilize the idea of denoising autoencoder to handle the noise in similarity feature information, which helps overcome biases in the fused similarity data. MSignVGAE represents microbe-disease associations as a heterogeneous graph using similarity information as node features. The multi-class classifier XGBoost is utilized to predict sign associations between diseases and microbes. CONCLUSIONS: MSignVGAE achieves AUROC and AUPR values of 0.9742 and 0.9601, respectively. Case studies on three diseases demonstrate that MSignVGAE can effectively capture a comprehensive distribution of associations by leveraging signed information.

LncRNA CTBP1-AS inhibits TP63-mediated activation of S100A14 during prostate cancer progression.

Long noncoding RNAs (lncRNAs) have emerged as important molecules and potential new targets for human cancers. This study investigates the function of lncRNA CTBP1 antisense RNA (CTBP1-AS) in prostate cancer (PCa) and explores the entailed molecular mechanism. Aberrantly expressed genes potentially correlated with PCa progression were probed using integrated bioinformatics analyses. A cohort of 68 patients with PCa was included, and their tumor and para-cancerous tissues were collected. CTBP1-AS was highly expressed in PCa tissues and cells and associated with poor patient prognosis. By contrast, tumor protein p63 (TP63) and S100 calcium binding protein A14 (S100A14) were poorly expressed in the PCa tissues and cells. CTBP1-AS did not affect TP63 expression; however it blocked the TP63-mediated transcriptional activation of S100A14, thereby reducing its expression. CTBP1-AS silencing suppressed proliferation, apoptosis resistance, migration, invasion, and tumorigenicity of PCa cell lines, while its overexpression led to inverse results. The malignant phenotype of cells was further weakened by TP63 overexpression but restored following artificial S100A14 silencing. In conclusion, this study demonstrates that CTBP1-AS plays an oncogenic role in PCa by blocking TP63-mediated transcriptional activation of S100A14. This may provide insight into the management of PCa.

The enhanced neutral process with decreasing cell size: a study on phytoplankton metacommunities from the glacier-fed river of Qinghai-Xizang Plateau.

The cell size of phytoplankton is an important defining functional trait that can serve as a driver and sentinel of phytoplankton community structure and function. However, the study of the assembly patterns and drivers of phytoplankton metacommunities with different cell sizes has not been widely carried out. In this study, we systematically investigated the biodiversity patterns, drivers, and assembly processes of the three phytoplankton cell sizes (micro: 20-200 µm; nano: 2-20 µm; pico: 0.2-2 µm) in the Za'gya Zangbo River from the source to the estuary using 18S rDNA amplicon sequencing. The results demonstrated that the alpha diversity and co-occurrence network complexity for all three sizes of phytoplankton increased to a peak downstream of the glacier sources and then decreased to the estuary. The nanophytoplankton subcommunity consistently had the highest alpha diversity and co-occurrence network complexity. On the other hand, total beta diversity followed a unimodal trend of decreasing and then increasing from source to estuary, and was dominated by species replacement components. In addition, deterministic processes driven mainly by physiochemical indices (PCIs) and biogenic elements (BGEs) dominated the assembly of micro- and nanophytoplankton subcommunities, whereas stochastic processes driven by geographical factors (GGFs) dominated the assembly of picophytoplankton subcommunities. The results explained the contradictions in previous studies of phytoplankton community assembly processes in highland aquatic ecosystems, elucidating the different contributions of deterministic and stochastic processes, and the complexity of compositional mechanisms in shaping the assembly of micro-, nano-, and picophytoplankton in this highland glacial river. IMPORTANCE: The cell size of phytoplankton is a key life-history trait and key determinant, and phytoplankton of different cell sizes are differentially affected by ecological processes. However, the study of the assembly patterns and drivers of phytoplankton metacommunities with different cell sizes has not been widely carried out. We provide an in-depth analysis of phytoplankton community diversity across three cell sizes in the glacier-fed river, describing how the pattern of phytoplankton communities differs across cell sizes in response to geochemical gradients. The results show that the smaller phytoplankton (picophytoplankton) are relatively more influenced by dispersal-based stochastic processes, whereas larger ones (microphytoplankton and nanophytoplankton) are more structured by selection-based deterministic processes.

Extension of Endocardium-Derived Vessels Generate Coronary Arteries in Neonates.

BACKGROUND: Unraveling how new coronary arteries develop may provide critical information for establishing novel therapeutic approaches to treating ischemic cardiac diseases. There are 2 distinct coronary vascular populations derived from different origins in the developing heart. Understanding the formation of coronary arteries may provide insights into new ways of promoting coronary artery formation after myocardial infarction. METHODS: To understand how intramyocardial coronary arteries are generated to connect these 2 coronary vascular populations, we combined genetic lineage tracing, light sheet microscopy, fluorescence micro-optical sectioning tomography, and tissue-specific gene knockout approaches to understand their cellular and molecular mechanisms. RESULTS: We show that a subset of intramyocardial coronary arteries form by angiogenic extension of endocardium-derived vascular tunnels in the neonatal heart. Three-dimensional whole-mount fluorescence imaging showed that these endocardium-derived vascular tunnels or tubes adopt an arterial fate in neonates. Mechanistically, we implicate Mettl3 (methyltransferase-like protein 3) and Notch signaling in regulating endocardium-derived intramyocardial coronary artery formation. Functionally, these intramyocardial arteries persist into adulthood and play a protective role after myocardial infarction. CONCLUSIONS: A subset of intramyocardial coronary arteries form by extension of endocardium-derived vascular tunnels in the neonatal heart.

Diversity Patterns of Eukaryotic Phytoplankton in the Medog Section of the Yarlung Zangbo River.

As one of the important biodiversity conservation areas in China, the ecosystem in the lower reaches of the Yarlung Zangbo River is fragile, and is particularly sensitive to global changes. To reveal the diversity pattern of phytoplankton, the metabarcode sequencing was employed in the Medog section of the lower reaches of the Yarlung Zangbo River during autumn 2019 in present study. The phytoplankton assemblies can be significantly divided into the main stem and the tributaries; there are significant differences in the phytoplankton biomass, alpha and beta diversity between the main stem and the tributaries. While both the main stem and the tributaries are affected by dispersal limitation, the phytoplankton assemblages in the entire lower reaches are primarily influenced by heterogeneous selection. Community dissimilarity and assembly process were significantly correlated with turbidity, electrical conductivity, and nitrogen nutrition. The tributaries were the main source of the increase in phytoplankton diversity in the lower reaches of the Yarlung Zangbo River. Such diversity pattern of phytoplankton in the lower reach may be caused by the special habitat in Medog, that is, the excessive flow velocity, and the significant spatial heterogeneity in physical and chemical factors between stem and tributaries. Based on the results and conclusions obtained in present study, continuous long-term monitoring is essential to assess and quantify the impact of global changes on phytoplankton.

Historical and dispersal processes drive community assembly of multiple aquatic taxa in glacierized catchments in the Qinghai-Tibet plateau.

Understanding the relative role of dispersal dynamics and niche constraints is not only a core task in community ecology, but also becomes an important prerequisite for bioassessment. Despite the recent progress in our knowledge of community assembly in space and time, patterns and processes underlying biotic communities in alpine glacierized catchments remain mostly ignored. To fill this knowledge gap, we combined the recently proposed dispersal-niche continuum index (DNCI) with traditional constrained ordinations and idealized patterns of species distributions to unravel community assembly mechanisms of different key groups of primary producers and consumers (i.e., phytoplankton, epiphytic algae, zooplankton, macroinvertebrates, and fishes) in rivers in the Qinghai-Tibet Plateau, the World's Third Pole. We tested whether organismal groups with contrasting body sizes differed in their assembly processes, and discussed their applicability in bioassessment in alpine zones. We found that community structure of alpine river biotas was always predominantly explained in terms of dispersal dynamics and historical biogeography. These patterns are most likely the result of differences in species-specific functional attributes, the stochastic colonization-extinction dynamics driven by multi-year glacier disturbances and the repeated hydrodynamic separation among alpine catchments after the rising of the Qilian mountains. Additionally, we found that the strength of dispersal dynamics and niche constraints was partially mediated by organismal body sizes, with dispersal processes being more influential for microscopic primary producers. Finding that zooplankton and macroinvertebrate communities followed clumped species replacement structures (i.e., Clementsian gradients) supports the notion that environmental filtering also contributes to the structure of high-altitude animal communities in glacierized catchments. In terms of the applied fields, we argue that freshwater bioassessment in glacierized catchments can benefit from incorporating the metacommunity perspective and applying novel approaches to (i) detect the optimal spatial scale for species sorting and (ii) identify and eliminate the species that are sensitive to dispersal-related processes.

Human-multimodal deep learning collaboration in 'precise' diagnosis of lupus erythematosus subtypes and similar skin diseases.

BACKGROUND: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE. OBJECTIVES: We aim to develop a multimodal deep learning system (MMDLS) for human-AI collaboration in diagnosis of LE subtypes. METHODS: This is a multi-centre study based on 25 institutions across China to assist in diagnosis of LE subtypes, other eight similar skin diseases and healthy subjects. In total, 446 cases with 800 clinical skin images, 3786 multicolor-immunohistochemistry (multi-IHC) images and clinical data were collected, and EfficientNet-B3 and ResNet-18 were utilized in this study. RESULTS: In the multi-classification task, the overall performance of MMDLS on 13 skin conditions is much higher than single or dual modals (Sen = 0.8288, Spe = 0.9852, Pre = 0.8518, AUC = 0.9844). Further, the MMDLS-based diagnostic-support help improves the accuracy of dermatologists from 66.88% ± 6.94% to 81.25% ± 4.23% (p = 0.0004). CONCLUSIONS: These results highlight the benefit of human-MMDLS collaborated framework in telemedicine by assisting dermatologists and rheumatologists in the differential diagnosis of LE subtypes and similar skin diseases.

Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance.

BACKGROUND: Enormous clinical and biomedical researches have demonstrated that microbes are crucial to human health. Identifying associations between microbes and diseases can not only reveal potential disease mechanisms, but also facilitate early diagnosis and promote precision medicine. Due to the data perturbation and unsatisfactory latent representation, there is a significant room for improvement. RESULTS: In this work, we proposed a novel framework, Multi-scale Variational Graph AutoEncoder embedding Wasserstein distance (MVGAEW) to predict disease-related microbes, which had the ability to resist data perturbation and effectively generate latent representations for both microbes and diseases from the perspective of distribution. First, we calculated multiple similarities and integrated them through similarity network confusion. Subsequently, we obtained node latent representations by improved variational graph autoencoder. Ultimately, XGBoost classifier was employed to predict potential disease-related microbes. We also introduced multi-order node embedding reconstruction to enhance the representation capacity. We also performed ablation studies to evaluate the contribution of each section of our model. Moreover, we conducted experiments on common drugs and case studies, including Alzheimer's disease, Crohn's disease, and colorectal neoplasms, to validate the effectiveness of our framework. CONCLUSIONS: Significantly, our model exceeded other currently state-of-the-art methods, exhibiting a great improvement on the HMDAD database.

Which productivity can promote clean energy transition -total factor productivity or green total factor productivity?

Developing clean energy is a key pathway and an inevitable choice for achieving the goals of carbon peak and carbon neutrality. From a global perspective, technology is increasingly affecting the trajectory of energy transition, driving clean energy into a stage of rapid development. Therefore, this paper focuses on exploring the dynamic evolutionary characteristics of clean energy transitions driven by different productivity. Using panel data from 171 economies from 1990 to 2019, this paper systematically examines the impact of Total Factor Productivity (TFP) and Green Total Factor Productivity (GTFP) on clean energy transitions. The empirical results indicate that both TFP and GTFP positively impact clean energy transition. Specifically, clean energy consumption increases by 3.35% and 6.03%with a one standard deviation change in TFP and GTFP respectively. Upon decomposing TFP and GTFP, it was found that Green Efficiency Change (GECH) and Green Technical Change (GHCH), especially GECH, are the main factors driving the clean energy transition. Heterogeneity analysis shows that, in developed economies, GTFP has a larger positive impact on clean energy transition than TFP. Furthermore, GTFP demonstrates a significant positive impact on the clean energy transition both before and after the 2008 financial crisis, whereas TFP's positive impact is only evident before the crisis. Our findings emphasize the social benefits of further investments in GTFP.

Applications of Nanozymes in Chiral-Molecule Recognition through Electrochemical and Ultraviolet-Visible Analysis.

Chiral molecules have similar physicochemical properties, which are different in terms of physiological activities and toxicities, rendering their differentiation and recognition highly significant. Nanozymes, which are nanomaterials with inherent enzyme-like activities, have garnered significant interest owing to their high cost-effectiveness, enhanced stability, and straightforward synthesis. However, constructing nanozymes with high activity and enantioselectivity remains a significant challenge. This review briefly introduces the synthesis methods of chiral nanozymes and systematically summarizes the latest research progress in enantioselective recognition of chiral molecules based on electrochemical methods and ultraviolet-visible absorption spectroscopy. Moreover, the challenges and development trends in developing enantioselective nanozymes are discussed. It is expected that this review will provide new ideas for the design of multifunctional chiral nanozymes and broaden the application field of nanozymes.

Decreased propionyl-CoA metabolism facilitates metabolic reprogramming and promotes hepatocellular carcinoma.

BACKGROUND & AIMS: Alterations of multiple metabolites characterize distinct features of metabolic reprograming in hepatocellular carcinoma (HCC). However, the role of most metabolites, including propionyl-CoA (Pro-CoA), in metabolic reprogramming and hepatocarcinogenesis remains elusive. In this study, we aimed to dissect how Pro-CoA metabolism affects these processes. METHODS: TCGA data and HCC samples were used to analyze ALDH6A1-mediated Pro-CoA metabolism and its correlation with HCC. Multiple metabolites were assayed by targeted mass spectrometry. The role of ALDH6A1-generated Pro-CoA in HCC was evaluated in HCC cell lines as well as xenograft nude mouse models and primary liver cancer mouse models. Non-targeted metabolomic and targeted energy metabolomic analyses, as well as multiple biochemical assays, were performed. RESULTS: Decreases in Pro-CoA and its derivative propionyl-L-carnitine due to ALDH6A1 downregulation were tightly associated with HCC. Functionally, ALDH6A1-mediated Pro-CoA metabolism suppressed HCC proliferation in vitro and impaired hepatocarcinogenesis in mice. The aldehyde dehydrogenase activity was indispensable for this function of ALDH6A1, while Pro-CoA carboxylases antagonized ALDH6A1 function by eliminating Pro-CoA. Mechanistically, ALDH6A1 caused a signature enrichment of central carbon metabolism in cancer and impaired energy metabolism: ALDH6A1-generated Pro-CoA suppressed citrate synthase activity, which subsequently reduced tricarboxylic acid cycle flux, impaired mitochondrial respiration and membrane potential, and decreased ATP production. Moreover, Pro-CoA metabolism generated 2-methylcitric acid, which mimicked the inhibitory effect of Pro-CoA on citrate synthase and dampened mitochondrial respiration and HCC proliferation. CONCLUSIONS: The decline of ALDH6A1-mediated Pro-CoA metabolism contributes to metabolic remodeling and facilitates hepatocarcinogenesis. Pro-CoA, propionyl-L-carnitine and 2-methylcitric acid may serve as novel metabolic biomarkers for the diagnosis and treatment of HCC. Pro-CoA metabolism may provide potential targets for development of novel strategies against HCC. IMPACT AND IMPLICATIONS: Our study presents new insights on the role of propionyl-CoA metabolism in metabolic reprogramming and hepatocarcinogenesis. This work has uncovered potential diagnostic and predictive biomarkers, which could be used by physicians to improve clinical practice and may also serve as targets for the development of therapeutic strategies against HCC.

m6A methyltransferase METTL3 programs CD4+ T-cell activation and effector T-cell differentiation in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disorder in which excessive CD4+ T-cell activation and imbalanced effector T-cell differentiation play critical roles. Recent studies have implied a potential association between posttranscriptional N6-methyladenosine (m6A) modification and CD4+ T-cell-mediated humoral immunity. However, how this biological process contributes to lupus is not well understood. In this work, we investigated the role of the m6A methyltransferase like 3 (METTL3) in CD4+ T-cell activation, differentiation, and SLE pathogenesis both in vitro and in vivo. METHODS: The expression of METTL3 was knocked down and METTL3 enzyme activity was inhibited using siRNA and catalytic inhibitor, respectively. In vivo evaluation of METTL3 inhibition on CD4+ T-cell activation, effector T-cell differentiation, and SLE pathogenesis was achieved using a sheep red blood cell (SRBC)-immunized mouse model and a chronic graft versus host disease (cGVHD) mouse model. RNA-seq was performed to identify pathways and gene signatures targeted by METTL3. m6A RNA-immunoprecipitation qPCR was applied to confirm the m6A modification of METTL3 targets. RESULTS: METTL3 was defective in the CD4+ T cells of SLE patients. METTL3 expression varied following CD4+ T-cell activation and effector T-cell differentiation in vitro. Pharmacological inhibition of METTL3 promoted the activation of CD4+ T cells and influenced the differentiation of effector T cells, predominantly Treg cells, in vivo. Moreover, METTL3 inhibition increased antibody production and aggravated the lupus-like phenotype in cGVHD mice. Further investigation revealed that catalytic inhibition of METTL3 reduced Foxp3 expression by enhancing Foxp3 mRNA decay in a m6A-dependent manner, hence suppressing Treg cell differentiation. CONCLUSION: In summary, our findings demonstrated that METTL3 was required for stabilizing Foxp3 mRNA via m6A modification to maintain the Treg differentiation program. METTL3 inhibition contributed to the pathogenesis of SLE by participating in the activation of CD4+ T cells and imbalance of effector T-cell differentiation, which could serve as a potential target for therapeutic intervention in SLE.

Miniature-swine iPSC-derived GABA progenitor cells function in a rat Parkinson's disease model.

Induced pluripotent stem cells (iPS cells) are considered a promising source of cell-based therapy for the treatment of Parkinson's disease (PD). Recent studies have shown forebrain GABA interneurons have crucial roles in many psychiatric disorders, and secondary changes in the GABA system play a directly effect on the pathogenesis of PD. Here, we first describe an efficient differentiation procedure of GABA progenitors (MiPSC-iGABAPs) from miniature-swine iPSCs through two major developmental stages. Then, the MiPSC-iGABAPs were stereotactically transplanted into the right medial forebrain bundle (MFB) of 6-hydroxydopamine (OHDA)-lesioned PD model rats to confirm their feasibility for the neural transplantation as a donor material. Furthermore, the grafted MiPSC-iGABAPs could survive and migrate from the graft site into the surrounding brain tissue including striatum (ST) and substantia nigra (SN) for at least 32 weeks, and significantly improved functional recovery of PD rats from their parkinsonian behavioral defects. Histological studies showed that the grafted cells could migrate and differentiate into various neurocytes, including GABAergic, dopaminergic neurons, and glial cells in vivo, and many induced dopaminergic neurons extended dense neurites into the host striatum. Moreover, over 50% of the grafted MiPSC-iGABAPs could express GABA, and these GABAergic neurons might be responsible for modifying the balance of excitatory and inhibitory signals in the striatum to promote behavioral recovery. Thus, the present study confirmed that the MiPSC-iGABAPs can be used as an attractive donor material for the neural grafting to remodel basal ganglia circuitry in neurodegenerative diseases, avoiding tumorigenicity of iPSCs and the nonproliferative and nondifferentiated potential of mature neurons.

Vision-Based Contact Adhesion Measurement Method on Soft Matter Surfaces.

Adhesion property measurements contribute to a comprehensive understanding of the mechanical properties of soft matters. Indentation tests are a common method for measuring the adhesion force. However, indenters generally have a large volume and a small sensing angle and, thus, are not conducive to local detection in high-precision environments. Here, we propose a vision-based contact adhesion measurement (VisCAM) method to achieve the contact image and adhesion force on soft matter surfaces from the perspective of indentation direction. The coupling of the 7.6 mm diameter probe and a flexible fiber makes the system similar to a miniaturized endoscope. Classical contact theories and finite element models are used for the contact mechanics analysis of silicone rubber. The image grayscale-load mathematical model is constructed based on the change in contact light spot. Finally, the uncertainty of the system is less than 4%, and the measurement error is 0.04 N. In-vitro kidney indentation experiments showed that the local adhesion force measurement of soft tissues can be completed. Our method provides better solutions for understanding the adhesion properties of soft matters.

A novel rat model of sarcopenic obesity based on aging and high-fat diet consumption.

Sarcopenic obesity (SO) is defined as a combination of obesity and sarcopenia, leading to serious health consequences. However, a lack of suitable animal models has hampered research into this disorder. 12-month-old Sprague-Dawley rats were given a high fat content (HFD, SO group) or standard diet (DC groups) for 28 weeks (until 20 months of age). In addition, 2-month-old rats were fed a standard diet as an age control (YC group) until they reached 10 months of age. At the end of the intervention, quadriceps development in the rats was monitored using magnetic resonance examinations and MR spectroscopy. Age-related changes in muscle mass and strength, histopathology, HFD-induced adiposity, and metabolic disturbances were compared between the three groups. Comparing with DC group, rats of SO (20 months, and fed by high-fat diet) exhibited a more prominent loss of muscle mass and strength, a more pronounced decline in myofibre number, IFM, increase in myocyte apoptosis accompanied with increased visceral fat, remarkable glycolipid metabolic disorders, and insulin resistance. However, DC group rats (20 months with standard diet) only showed a decline in quadriceps cross-sectional area/body weight, forelimb grip strength, myofibre cross-sectional area and number, and intermyofibrillar mitochondria number (IFM), increased myocyte apoptosis, without significant metabolic disorder compared with YC group rats. After verifying, SO animal model was successfully set up by HFD induced obesity concomitant with aging-related sarcopenia.

Identification and Validation of Signature Genes and Their Correlations with Infiltrated Immune Cells in Neonatal Sepsis.

Background and Objective: There is increasing demand to identify accurate and reliable molecular biomarkers for early diagnosis of neonatal sepsis. We aimed to identify and verify signature genes in neonatal sepsis through comprehensive bioinformatics analysis. Methods: A Gene Expression Omnibus data set was used to identify differentially expressed genes (DEGs) in patients with neonatal sepsis and healthy controls by functional and disease enrichment analysis. Gene set enrichment analysis, screening of DEGs using 2 machine algorithms, analysis of receiver operating characteristic curves, and correlation analysis with infiltrating immune cells was performed. Results: We identified 433 DEGs: 144 downregulated and 289 upregulated. Gene Ontology analysis identified DEGs for T cell activation, positive regulation of cytokine production, secretory granule cavity, cytoplasmic vesicle cavity, immune receptor activity, and antioxidant activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified DEGs for hematopoietic cell lineage, cytokine-cytokine receptor interaction, and coronavirus disease (COVID-19). Disease Ontology analysis identified DEGs for hematopoietic system diseases, skin system diseases, and bacterial infectious diseases. We also gained understanding of the enrichment of various functions and pathways by gene set enrichment analysis. In the neonatal sepsis group, Gene Ontology analysis results were significant for coagulation, endocytosis, white cell migration, myeloid leukocyte-mediated immunity, and phagocytosis; KEGG analysis results were significant for chemokine signaling pathway, complement and coagulation cascade, leukocyte migration across endothelium, regulation of actin cytoskeleton, and toll-like receptor signaling pathway. We screened 2 signature DEGs (GSN and SEMA4B) using the least absolute shrinkage and selection operator and support vector machine recursive feature elimination algorithms and verified their diagnostic accuracy by receiver operating characteristic curves. We correlated GSN and SEMA4B expression levels with the infiltration levels of 22 types of immune cell. Conclusion: GSN and SEMA4B expression accurately predicted early-stage neonatal sepsis, which is beneficial for early clinical diagnosis and treatment.