Stem cells from human exfoliated deciduous teeth rejuvenate the liver in naturally aged mice by improving ribosomal and mitochondrial proteins.

BACKGROUND AIMS: Aging is accompanied by a decline in cellular proteome homeostasis, mitochondrial, and metabolic function. Mesenchymal stromal cell (MSC) therapies have been reported to extend lifespan and delay some age-related pathologies, yet the anti-aging rate and mechanisms remain unclear. Here, we investigated the effects and mechanism by transplantation of stem cells from human exfoliated deciduous teeth (SHED) into the naturally aged mice model. METHODS: SHED were cultured in vitro and injected into mice by caudal vein. The in vivo imaging uncovered that SHED labeled by DiR dye mainly migrated to the liver, spleen, and lung organs of wild-type mice. As the main metabolic organ and SHED homing place, the liver was selected for proteomics and aging clock algorithm (LiverClock) analysis, which was constructed to estimate the proteomic pattern related to liver age state. RESULTS: After 6 months of continuous SHED injections, the liver proteomic pattern was reversed from senescent (∼30 months) to a youthful state (∼3 months), accompanied with upregulation of hepatocytes marker genes, anti-aging protein Klotho, a global improvement of liver functional pathways proteins, and a dramatic regulation of ribosomal and mitochondrial proteins, including upregulation of translation elongation and ribosome-sparing proteins Rpsa and Rplp0; elongation factors Eif4a1, Eef1b2, Eif5a; protein-folding chaperones Hsp90aa and Hspe1; ATP synthesis proteins Atp5b, Atp5o, Atp5j; and downregulation of most ribosomal proteins, suggesting that the proteome homeostasis destruction and mitochondria dysfunction in the aged mice liver might be relieved after SHED treatment. CONCLUSIONS: SHED treatment could dramatically relieve the senescent state of the aged liver, affect ribosome component proteins and upregulate the ribosomal biogenesis proteins in the aged mice liver. These results may help understand the improvements and mechanisms of SHED treatment in anti-aging.

Stem cells from human exfoliated deciduous teeth affect mitochondria and reverse cognitive decline in a senescence-accelerated mouse prone 8 model.

BACKGROUND AIMS: Stem cell therapy is a novel therapy being explored for AD. The molecular mechanism of its effect is still unclear. The authors investigated the effects and mechanism by injection of SHEDs into an AD mouse model. METHODS: SHEDs were cultured in vitro and injected into AD SAMP8 mice by caudal vein, and SHEDs labeled via synthetic dye showed in vivo migration to the head. The cognitive ability of SAMP8 mice was evaluated via Barnes maze and new object recognition. The pathological indicators of AD, including Tau, amyloid plaques and inflammatory factors, were examined at the protein or RNA level. Next, macro-proteomics analysis and weighted gene co-expression network analysis (WGCNA) based on protein groups and behavioral data were applied to discover the important gene cluster involved in the improvement of AD by SHEDs, which was further confirmed in an AD model in both mouse and cell lines. RESULTS: SHED treatment improved the cognitive ability and pathological symptoms of SAMP8 mice. Proteomics analysis indicated that these improvements were tightly related to the mitochondria, which was proved through examination of the shape and function of mitochondria both in vivo (SAMP8 brain) and in vitro (SH-SY5Y cells). Finally, the core targets of SHEDs in the mitochondrial pathway, Hook3, Mic13 and MIF, were screened out and confirmed in vivo. CONCLUSIONS: SHED treatment significantly relieved AD symptoms, improved cognitive ability and reversed memory loss in an AD mouse model, possibly through the recovery of dysfunctional mitochondria. These results raise the possibility that SHED may ease the symptoms of AD by targeting the mitochondria.

Establishment and validation of a drug-target microarray for SARS-CoV-2.

COVID-19 has become one of the worst epidemic in the world, currently already more than four million people have been infected, which probably co-exist with human beings, and has a significant impact on the global economy and political order. In the process of fighting against the epidemic in China, the clinical value of a variety of herbal medicines has been recognized and written into the clinical application guide. However, their effective molecular mechanism and potential targets are still not clear. Pathology and pharmacology research will gradually attract attention in the post-epidemic outbreak term. Here, we constructed a COVID-19 protein microarray of potential therapy targets, which contains the main drug targets to the SARS-CoV-2 virus and the anti-virus, anti-inflammatory cellar targets of the host. Series of quality controls test has been carried out, which showed that it could be applied for drug target screening of bio-active natural products. The establishment of this microarray will provide a useful tool for the study of the molecular pharmacology of natural products.

Tuning of Persulfate Activation from a Free Radical to a Nonradical Pathway through the Incorporation of Non-Redox Magnesium Oxide.

Nonradical-based advanced oxidation processes for pollutant removal have attracted much attention due to their inherent advantages. Herein we report that magnesium oxides (MgO) in CuOMgO/Fe3O4 not only enhanced the catalytic properties but also switched the free radical peroxymonosulfate (PMS)-activated process into the 1O2 based nonradical process. CuOMgO/Fe3O4 catalyst exhibited consistent performance in a wide pH range from 5.0 to 10.0, and the degradation kinetics were not inhibited by the common free radical scavengers, anions, or natural organic matter. Quantitative structure-activity relationships (QSARs) revealed the relationship between the degradation rate constant of 14 substituted phenols and their conventional descriptor variables (i.e., Hammett constants σ, σ-, σ+), half-wave oxidation potential (E1/2), and pKa values. QSARs together with the kinetic isotopic effect (KIE) recognized the electron transfer as the dominant oxidation process. Characterizations and DFT calculation indicated that the incorporated MgO alters the copper sites to highly oxidized metal centers, offering a more suitable platform for PMS to generate metastable copper intermediates. These highly oxidized metals centers of copper played the key role in producing O2•- after accepting an electron from another PMS molecule, and finally 1O2 as sole reactive species was generated from the direct oxidation of O2•- through thermodynamically feasible reactions.

Zeta potential-assisted sorption of uranyl tricarbonate complex from aqueous solution by polyamidoxime-functionalized colloidal particles.

Uranium(vi) is one of the main sources in nuclear energy but can cause severe effects to human health and the environment, therefore it is important to develop a new method and materials for uranium capture. A novel approach is reported here for efficient uranium sorption by polyamidoxime-functionalized colloids with zeta potential-assistance. Specifically, colloidal particles were prepared via emulsion polymerization with (3-acrylamidopropyl)trimethyl-ammonium chloride (MAPTAC). The zeta potential of the colloids could be controlled by the concentration of MAPTAC. The effects of pH, the sorbent dose and competing ions on uranium(vi) sorption were investigated. The sorption process followed a pseudo-second-order kinetics and could reach equilibrium within 3.5 h at pH 7.8. The colloidal particles with high zeta potentials showed higher selectivity, faster kinetics and larger capacity for the sorption of uranium(vi) in comparison with that of negative zeta potential particles. This work may provide a new method for efficient uranium(vi) capture from aqueous solution through zeta potential-assisted sorption.

Network-based pharmacology and UHPLC-Q-Exactive-Orbitrap-MS reveal Jinhua Qinggan granule's mechanism in reducing cellular inflammation in COVID-19.

Introduction: The outbreak of SARS-CoV-2, leading to COVID-19, poses a major global health threat. While specific treatments and vaccines are under development, Traditional Chinese Medicine (TCM) has historically been effective against pandemics, including viral pneumonias. Our study explores the efficacy and mechanisms of Jinhua Qinggan Granules (JHQG) in treating COVID-19. Methods: We analyzed JHQG's components using UHPLC-Q-Exactive-Orbitrap-MS, identifying 73 compounds. Network pharmacology and single-cell RNA sequencing (scRNA-seq) were used to assess JHQG's effects on immune cells from peripheral blood mononuclear cells (PBMCs). Literature review supported the antiviral and anti-inflammatory effects of JHQG. Results: JHQG targets were found to interact with immune cells, including neutrophils, monocytes, plasmablasts, and effector T cells, reducing their overactivation in severe COVID-19. JHQG's modulation of these cells' activity likely contributes to reduced inflammation and improved clinical outcomes. Discussion: Our findings provide insights into JHQG's mechanism of action, highlighting its potential in controlling the inflammatory response in COVID-19 patients. The study supports the use of JHQG as a safe and effective treatment for COVID-19 and similar viral infections, leveraging its ability to modulate immune cell activity and reduce inflammation.

A Network Pharmacology-based Study on the Anti-aging Properties of Traditional Chinese Medicine Sisheng Bulao Elixir.

BACKGROUND: Traditional Chinese Medicine (TCM) has a rich history of use in preventing senescence for millennia in China. Nonetheless, a systematic method to study the antiaging properties and the underlying molecular mechanism of TCM remains absent. OBJECTIVE: The objective of this study is to decipher the anti-aging targets and mechanisms of Sisheng Bulao Elixir (SBE) using a systematic approach based on a novel aging database and network pharmacology. METHODS: Bioactive compounds and target proteins in SBE were identified via the Traditional Chinese Medicine System Pharmacology (TCMSP) database. Aging-related proteins were uncovered through alignment with the Ageing Alta database. A compound-target (CT) protein network analysis highlighted key flavonoids targeting aging. Core aging-related proteins were extracted through protein-protein interaction (PPI) network analysis. Molecular docking validated binding activities between core compounds and aging-related proteins. The antioxidant activity of SBE was confirmed using an in vitro senescent cells model. RESULTS: A total of 39 active compounds were extracted from a pool of 639 compounds in SBE. Through a matching process with the Aging Alta, 88 target proteins associated with the aging process were identified. Impressively, 80 out of these 88 proteins were found to be targeted by flavonoids. Subsequently, an analysis using CT methodology highlighted 11 top bioactive flavonoids. Notably, core aging-related proteins, including AKT1, MAPK3, TP53, VEGFA, IL6, and HSP90AA1, emerged through the PPI network analysis. Moreover, three flavonoids, namely quercetin, kaempferol, and luteolin, exhibited interactions with over 100 aging-related proteins. Molecular docking studies were conducted on these flavonoids with their shared three target proteins, namely AKT1, HSP90AA1, and IL6, to assess their binding activities. Finally, the antioxidant properties of SBE were validated using an in vitro model of senescent cells. CONCLUSION: This study offers novel insights into SBE's anti-aging attributes, providing evidence of its molecular mechanisms. It enhances our understanding of traditional remedies in anti-aging research.

OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing.

Single-cell sequencing is frequently affected by "omission" due to limitations in sequencing throughput, yet bulk RNA-seq may contain these ostensibly "omitted" cells. Here, we introduce the single cell trajectory blending from Bulk RNA-seq (BulkTrajBlend) algorithm, a component of the OmicVerse suite that leverages a Beta-Variational AutoEncoder for data deconvolution and graph neural networks for the discovery of overlapping communities. This approach effectively interpolates and restores the continuity of "omitted" cells within single-cell RNA sequencing datasets. Furthermore, OmicVerse provides an extensive toolkit for both bulk and single cell RNA-seq analysis, offering seamless access to diverse methodologies, streamlining computational processes, fostering exquisite data visualization, and facilitating the extraction of significant biological insights to advance scientific research.

Too Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco.

Findings from graphical perception can guide visualization recommendation algorithms in identifying effective visualization designs. However, existing algorithms use knowledge from, at best, a few studies, limiting our understanding of how complementary (or contradictory) graphical perception results influence generated recommendations. In this paper, we present a pipeline of applying a large body of graphical perception results to develop new visualization recommendation algorithms and conduct an exploratory study to investigate how results from graphical perception can alter the behavior of downstream algorithms. Specifically, we model graphical perception results from 30 papers in Draco-a framework to model visualization knowledge-to develop new recommendation algorithms. By analyzing Draco-generated algorithms, we showcase the feasibility of our method to (1) identify gaps in existing graphical perception literature informing recommendation algorithms, (2) cluster papers by their preferred design rules and constraints, and (3) investigate why certain studies can dominate Draco's recommendations, whereas others may have little influence. Given our findings, we discuss the potential for mutually reinforcing advancements in graphical perception and visualization recommendation research.

Composition of intestinal flora affects the risk relationship between Alzheimer's disease/Parkinson's disease and cancer.

An increasing number of epidemiological studies have shown that there is a significant inverse relationship between the onset of Alzheimer's disease/Parkinson's disease (AD/PD) and cancer, but the mechanism is still unclear. Considering that intestinal flora can connect them, we tried to explain this phenomenon from the intestinal flora. This review briefly introduced the relationship among AD/PD, cancer, and intestinal flora, studied metabolites or components of the intestinal flora and the role of intestinal barriers and intestinal hormones in AD/PD and cancer. After screening, a part of the flora capable of participating in the occurrence processes of the three diseases at the same time was obtained, the abundance changes of the special flora in AD/PD and various types of cancers were summarized, and they were classified according to the flora function and abundance, which in turn innovatively and reasonably explained the fact that AD/PD and cancer showed certain antagonism in epidemiological statistics from the perspective of intestinal flora. This review also proposed that viewing the risk relationship between diseases from the perspective of intestinal flora may provide new research ideas for the treatment of fecal microbiota transplantation (FMT) and related diseases.

Phosphate sequestration by lanthanum-layered rare earth hydroxides through multiple mechanisms while avoiding the attenuation effect from sediment particles in lake water.

Lanthanum-based adsorbents have been used extensively to capture phosphate from wastewater. However, the attenuation effect that arises from the coexistence of sediment and humic acid is the major drawback in practical applications. The Lanthanum-layered rare earth hydroxides (LRHs)-Cl (La-LRH-Cl) was synthesized and achieved high elemental phosphorus (P) adsorption capacity (138.9 mg-P g-1) along with a fast adsorption rate (k2 = 0.0031 g mg-1·min-1) over a wide pH range while avoiding the attenuation effect that arises from the coexistence of sediment and humic acid in lake water. The La-LRH-Cl effectively captured phosphate through multiple interactions, such as the ion exchange of Cl- and phosphate, the memory effect of LRH and the inner-sphere complexation of La-P. Moreover, physical models demonstrated that the adsorption of phosphate onto La-LRH-Cl was a monolayer endothermic process, during which PO43- interacted by multi-docking via parallel orientation at 293 K and multi-ionic interactions through pure non-parallel orientation at 303 K. Hence, 1000 L of 11.08 mg-P L-1 of the acquired lake water was decontaminated by 30 g of La-LRH-Cl to 0.09 mg-P L-1 within 7 days. In addition, over ~12,125 BV of an industrial effluent containing 3.26 mg-P L-1 was treated to below USEPA's discharge limit in fixed-bed tests. It was found that the memory effect of LRH was responsible for the stable performance and reusability. Therefore, more focus should be placed on the collective role of La and LRH layered structure as a means of preventing the attenuation effect in the real water matrix.

An Evaluation-Focused Framework for Visualization Recommendation Algorithms.

Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualization recommendation algorithms are inadequately specified from an evaluation perspective. In this paper, we propose an evaluation-focused framework to contextualize and compare a broad range of visualization recommendation algorithms. We present the structure of our framework, where algorithms are specified using three components: (1) a graph representing the full space of possible visualization designs, (2) the method used to traverse the graph for potential candidates for recommendation, and (3) an oracle used to rank candidate designs. To demonstrate how our framework guides the formal comparison of algorithmic performance, we not only theoretically compare five existing representative recommendation algorithms, but also empirically compare four new algorithms generated based on our findings from the theoretical comparison. Our results show that these algorithms behave similarly in terms of user performance, highlighting the need for more rigorous formal comparisons of recommendation algorithms to further clarify their benefits in various analysis scenarios.

Regulatory factor identification for nodal genes in zebrafish by causal inference.

Activation of nodal genes is critical for mesoderm and endoderm induction. Our previous study reported that zebrafish nodal genes ndr1/squint and ndr2/cyclops are coordinately regulated by maternal Eomesa, Hwa-activated ß-catenin (Hwa/ß-catenin) signaling, and Nodal autoregulation (Nodal/Smad2) signaling. However, the exact contribution and underlying mechanisms are still elusive. Here, we applied "causal inference" to evaluate the causal between the independent and dependent variables, and we found that Hwa/ß-catenin and Smad2 are the cause of ndr1 activation, while Eomesa is the cause of ndr2 activation. Mechanistically, the different cis-regulatory regions of ndr1 and ndr2 bound by Eomesa, ß-catenin, and Smad2 were screened out via ChIP-qPCR and verified by the transgene constructs. The marginal GFP expression driven by ndr1 transgenesis could be diminished without both maternal Eomesa and Hwa/ß-catenin, while Eomesa, not ß-catenin, could bind and activate ndr2 demonstrated by ndr2 transgenesis. Thus, the distinct regulation of ndr1/ndr2 relies on different cis-regulatory regions.

ERgene: Python library for screening endogenous reference genes.

In gene expression analysis, sample differences and experimental operation differences are common, but sometimes, these differences will cause serious errors to the results or even make the results meaningless. Finding suitable internal reference genes efficiently to eliminate errors is a challenge. Aside from the need for high efficiency, there is no package for screening endogenous genes available in Python. Here, we introduce ERgene, a Python library for screening endogenous reference genes. It has extremely high computational efficiency and simple operation steps. The principle is based on the inverse process of the internal reference method, and the robust matrix block operation makes the selection of internal reference genes faster than any other method.

High-throughput screening suggests glutathione synthetase as an anti-tumor target of polydatin using human proteome chip.

Polydatin (PD) is a bio-active ingredient with known anti-tumor effects. However, its specific protein targets yet have not been systematically screened, and the molecular anti-tumor mechanism is still unclear. Here, proteomic-chip was efficiently used to screen potential targets of PD. First, we investigated through animal experiment and proteomics studies, and found that polydatin play an important role in tumor cells. Then, the red-green fluorescent of polydatin was compared comprehensively to screen its targets on chip, followed by bioinformatics analysis. Glutathione synthetase (GSS) was selected as candidate research target. After a series of molecular biological experiments GSS was confirmed a target protein for PD in vitro. Moreover, we also found that PD can significantly inhibit the activity of GSS in vitro and live cells. Our findings reveal that PD could be a selective small-molecule GSS enzyme activity inhibitor and GSS could be a potential therapeutic target in cancer.