Correlations between growth differentiation factor 15 (GDF-15) serum levels and gene polymorphism with type 2 diabetes mellitus.

Purpose: To date, the relationship between Growth Differentiation Factor 15 (GDF-15) gene polymorphism and the risk of type 2 diabetes mellitus (T2DM) has not been clarified. Our study aims to explore the association between serum GDF-15 levels and related gene polymorphism with the risk of T2DM in a Chinese rural Yao population. Methods: This was a 1:1 case-control study with 179 T2DM patients and 179 age- and sex-matched control participants. Serum GDF-15 levels were measured by enzyme-linked immunosorbent assay, and polymorphisms (rs1059519, rs1059369, rs1804826 and rs1054564) were genotyped by MassArray mass spectrometry. Results: Serum GDF-15 (sGDF-15) levels were higher in patients with T2DM and glycosylated hemoglobin (HbA1c) ≥ 6.5 % compared to that in controls (p < 0.001). The area under the curve (AUC) corresponding to sGDF-15 levels was 0.626. Serum GDF-15 was positively correlated with fasting plasma glucose (FPG) (rs = 0.150, p < 0.001) and HbA1c (rs = 0.160, p < 0.001). The frequency of GDF-15 gene rs1054564 GC + CC genotype was significantly associated with increased risk of T2DM compared to GG genotype (OR = 1.724, 95CI: 1.046-2.841, p = 0.033). Frequencies of rs1804826 T allele (ß additive = 113.318, p = 0.026) and rs1054564 C allele (ß additive = 247.282, p = 0.001, ß dominant = 286.109, p = 0.001) was significantly correlated with higher sGDF-15. The rs1059519 C allele was negatively correlated with FPG (ß recessive = -0.607, p = 0.047) and HbA1c (ß recessive = -0.456, p = 0.020). Conclusion: Serum GDF-15 levels were positively correlated with FPG and HbA1c. The GDF-15 rs1054564 GC + CC genotype was associated with a significantly higher T2DM risk. The rs1059519 C allele was negatively correlated with FPG and HbA1c.

Association between multiple-heavy-metal exposures and systemic immune inflammation in a middle-aged and elderly Chinese general population.

BACKGROUND: Exposure to heavy metals alone or in combination can promote systemic inflammation. The aim of this study was to investigate potential associations between multiple plasma heavy metals and markers of systemic immune inflammation. METHODS: Using a cross-sectional study, routine blood tests were performed on 3355 participants in Guangxi, China. Eight heavy metal elements in plasma were determined by inductively coupled plasma mass spectrometry. Immunoinflammatory markers were calculated based on peripheral blood WBC and its subtype counts. A generalised linear regression model was used to analyse the association of each metal with the immunoinflammatory markers, and the association of the metal mixtures with the immunoinflammatory markers was further assessed using weighted quantile sum (WQS) regression. RESULTS: In the single-metal model, plasma metal Fe (log10) was significantly negatively correlated with the levels of immune-inflammatory markers SII, NLR and PLR, and plasma metal Cu (log10) was significantly positively correlated with the levels of immune-inflammatory markers SII and PLR. In addition, plasma metal Mn (log10 conversion) was positively correlated with the levels of immune inflammatory markers NLR and PLR. The above associations remained after multiple corrections. In the mixed-metal model, after WQS regression analysis, plasma metal Cu was found to have the greatest weight in the positive effects of metal mixtures on SII and PLR, while plasma metals Mn and Fe had the greatest weight in the positive effects of metal mixtures on NLR and LMR, respectively. In addition, blood Fe had the greatest weight in the negative effects of the metal mixtures for SII, PLR and NLR. CONCLUSION: Plasma metals Cu and Mn were positively correlated with immunoinflammatory markers SII, NLR and PLR. While plasma metal Fe was negatively correlated with immunoinflammatory markers SII, NLR, and PLR.

Closed-Loop Polymer-to-Polymer Upcycling of Waste Poly (Ethylene Terephthalate) into Biodegradable and Programmable Materials.

Poly(ethylene terephthalate) (PET), extensively employed in bottles, film, and fiber manufacture, has generated persistent environmental contamination due to its non-degradable nature. The resolution of this issue requires the conversion of waste PET into valuable products, often achieved through depolymerization into monomers. However, the laborious purification procedures involved in the extraction of monomers pose challenges and constraints on the complete utilization of PET. Herein, a strategy is demonstrated for the polymer-to-polymer upcycling of waste PET into high-value biodegradable and programmable materials named PEXT. This process involves reversible transesterifications dependent on ester bonds, wherein commercially available X-monomers from aliphatic diacids and diols are introduced, utilizing existing industrial equipment for complete PET utilization. PEXT features a programmable molecular structure, delivering tailored mechanical, thermal, and biodegradation performance. Notably, PEXT exhibits superior mechanical performance, with a maximal elongation at break of 3419.2 % and a toughness of 270.79 MJ m-3. These characteristics make PEXT suitable for numerous applications, including shape-memory materials, transparent films, and fracture-resistant stretchable components. Significantly, PEXT allows closed-loop recycling within specific biodegradable analogs by reprograming PET or X-monomers. This strategy not only offers cost-effective advantages in large-scale upcycling of waste PET into advanced materials but also demonstrates its enormous prospect in environmental conservation.

Association between the dietary antioxidant index and relative telomere length of leucocytes in the Chinese population.

Dietary antioxidant indices (DAI) may be potentially associated with relative telomere length (RTL) of leucocytes. This study aimed to investigate the relationship between DAI and RTL. A cross-sectional study involving 1656 participants was conducted. A generalised linear regression model and a restricted cubic spline model were used to assess the correlation of DAI and its components with RTL. Generalised linear regression analysis revealed that DAI (ß = 0·005, P = 0·002) and the intake of its constituents vitamin C (ß = 0·043, P = 0·027), vitamin E (ß = 0·088, P < 0·001), Se (ß = 0·075, P = 0·003), and Zn (ß = 0·075, P = 0·023) were significantly and positively correlated with RTL. Sex-stratified analysis showed that DAI (ß = 0·006, P = 0·005) and its constituents vitamin E (ß = 0·083, P = 0·012), Se (ß = 0·093, P = 0·006), and Zn (ß = 0·092, P = 0·034) were significantly and positively correlated with RTL among females. Meanwhile, among males, only vitamin E intake (ß = 0·089, P = 0·013) was significantly and positively associated with RTL. Restricted cubic spline analysis revealed linear positive associations between DAI and its constituents' (vitamin E, Se and Zn) intake and RTL in the total population. Sex-stratified analysis revealed a linear positive correlation between DAI and its constituents' (vitamin E, Se and Zn) intake and RTL in females. Our study found a significant positive correlation between DAI and RTL, with sex differences.

Association Between Combined Polymetallic Exposure and Osteoporosis.

Combined polymetallic exposure may be an influential factor in osteoporosis. This study aimed to explore the association between polymetallic combined exposure and osteoporosis. A total of 2115 participants were included. Plasma concentrations of 22 metals were determined by inductively coupled plasma mass spectrometry. Osteoporosis was defined as a T ≤ - 2.5. The least absolute shrinkage and selection operator (LASSO) regression, binary logistics regression, and Bayesian kernel machine regression (BKMR) model were used to explore the association between plasma metals and osteoporosis. LASSO regression showed that 10 metals were associated with osteoporosis in the total population (magnesium, calcium, manganese, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum) and women (magnesium, calcium, molybdenum, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum), and four metals associated with men (magnesium, cobalt, aluminum, iron). Logistics regression showed that in total population, magnesium (ORQ3 = 0.653, 95% CI = 0.446-0.954) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.569, 95% CI = 1.095-2.248, ORQ4 = 1.616, 95% CI = 1.109-2.354) and cadmium (ORQ4 = 1.989, 95% CI = 1.379-2.870) were positively correlated; in women, magnesium (ORQ3 = 0.579, 95% CI = 0.379-0.883) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.563, 95% CI = 1.051-2.326, ORQ4 = 1.543, 95% CI = 1.024-2.326) and cadmium (ORQ3 = 1.482, 95% CI = 1.003-2.191, ORQ4 = 1.740, 95% CI = 1.167-2.596) were positively correlated. BKMR model showed that combined polymetallic exposure had an overall positive effect on osteoporosis, magnesium was negatively associated with osteoporosis, and cadmium, selenium, and aluminum were positively associated with osteoporosis. Metal mixtures in plasma were associated with osteoporosis risk. Magnesium may reduce the risk of osteoporosis, while cadmium, selenium, and aluminum may increase the risk of osteoporosis. Future studies needed to explore correlations and mechanisms.

Association between barium exposed, CYP19A1 and central obesity: A cross-sectional study in rural China.

BACKGROUND: obesity is a major risk factor for many metabolic diseases such as diabetes and cardiometabolic diseases. This study aimed to evaluate the association of plasma and urinary barium concentrations, CYP19A1 gene polymorphisms, and their interaction with central obesity in a rural Chinese population. METHODS: restricted cubic spline model was used to explore the dose-response relationship between barium and the risk of developing central obesity and waist circumference; logistic regression model was used to assess the association between barium, CYP19A1 gene polymorphisms and their interaction with central obesity. RESULTS: the results of the restricted cubic spline model showed that plasma barium concentration was linearly associated with the risk of developing central obesity and non-linearly associated with waist circumference. Logistic regression analysis showed that participants with Q4 plasma barium concentration exhibited a higher risk of central obesity compared to participants with Q1 barium concentration; participants carrying the rs10046-AA gene exhibited a lower risk of central obesity than those carrying the rs10046-G(GG+GA) gene; participants carrying the rs10046-GA genotype showed 1.754 times higher risk of central obesity than those carrying rs10046-GG+AA genotype. There was a significant interaction between plasma barium and CYP19A1 gene polymorphism on central obesity. CONCLUSION: the development of central obesity was associated with plasma barium and CYP19A1.

Structural evolution of iminopyridine support for nickel/palladium catalysts in ethylene (oligo)polymerization.

The interest in the late transition metal catalyst based design of new architectures of polyethylene (PE) has continuously been increasing over the last few years. The structure of these catalysts is predominantly important in controlling the morphological and architectural properties of the resulting polyethylene. Particularly, iminopyridine is a versatile bidentate support for Ni and Pd catalysts in ethylene (oligo)polymerization providing a wide variety of products ranging from volatile oligomers to ultra-high molecular weight polyethylene. Extensive structural modifications have been induced in the iminopyridine ligand through steric and electronic substitution, tuning the catalyst behavior in terms of activity and properties of the resulting polymer. Carbocyclic-fused iminopyridine and N-oxide iminopyridine are the new state of the art iminopyridine ligand designs. In this review, we aim to summarize all the developments in mononuclear iminopyridine-nickel and -palladium catalysts for ethylene (oligo)polymerization since the first report published in 1999 to present, focusing on the correlation among the pre-catalyst, co-catalyst type, thermal stability and polymer/oligomer structure. For comparison, the structural variations in the binuclear iminopyridine-nickel catalysts are also described. The detailed comparison of the structural variations in these catalysts with respect to their polymerization performance will give deep understanding in the development of new efficient catalyst designs.

Recent Advances in Microfluidic Platforms for Programming Cell-Based Living Materials.

Cell-based living materials, including single cells, cell-laden fibers, cell sheets, organoids, and organs, have attracted intensive interests owing to their widespread applications in cancer therapy, regenerative medicine, drug development, and so on. Significant progress in materials, microfabrication, and cell biology have promoted the development of numerous promising microfluidic platforms for programming these cell-based living materials with a high-throughput, scalable, and efficient manner. In this review, the recent progress of novel microfluidic platforms for programming cell-based living materials is presented. First, the unique features, categories, and materials and related fabrication methods of microfluidic platforms are briefly introduced. From the viewpoint of the design principles of the microfluidic platforms, the recent significant advances of programming single cells, cell-laden fibers, cell sheets, organoids, and organs in turns are then highlighted. Last, by providing personal perspectives on challenges and future trends, this review aims to motivate researchers from the fields of materials and engineering to work together with biologists and physicians to promote the development of cell-based living materials for human healthcare-related applications.

Inactivating histone deacetylase HDA promotes longevity by mobilizing trehalose metabolism.

Histone acetylations are important epigenetic markers for transcriptional activation in response to metabolic changes and various stresses. Using the high-throughput SEquencing-Based Yeast replicative Lifespan screen method and the yeast knockout collection, we demonstrate that the HDA complex, a class-II histone deacetylase (HDAC), regulates aging through its target of acetylated H3K18 at storage carbohydrate genes. We find that, in addition to longer lifespan, disruption of HDA results in resistance to DNA damage and osmotic stresses. We show that these effects are due to increased promoter H3K18 acetylation and transcriptional activation in the trehalose metabolic pathway in the absence of HDA. Furthermore, we determine that the longevity effect of HDA is independent of the Cyc8-Tup1 repressor complex known to interact with HDA and coordinate transcriptional repression. Silencing the HDA homologs in C. elegans and Drosophila increases their lifespan and delays aging-associated physical declines in adult flies. Hence, we demonstrate that this HDAC controls an evolutionarily conserved longevity pathway.

Evaluation of Single-Cell Cytokine Secretion and Cell-Cell Interactions with a Hierarchical Loading Microwell Chip.

Comprehensive evaluation of single T cell functions such as cytokine secretion and cytolysis of target cells is greatly needed in adoptive cell therapy (ACT) but has never been fully fulfilled by current approaches. Herein, we develop a hierarchical loading microwell chip (HL-Chip) that aligns multiple cells and functionalized beads in a high-throughput microwell array with single-cell/bead precision based on size differences. We demonstrate the potential of the HL-Chip in evaluating single T cell functions by three applications: high-throughput longitudinal secretory profiling of single T cells, large-scale evaluation of cytolytic activity of single T cells, and integrated T cell-tumor cell interactions. The HL-Chip is a simple and robust technology that constructs arrays of defined cell/object combinations for multiple measurements and material retrieval.

Microfluidics-Based Single-Cell Protrusion Analysis for Screening Drugs Targeting Subcellular Mitochondrial Trafficking in Cancer Progression.

Cancer cell migration is often guided by cell protrusions, whose formation and activity involve subcellular localization of mitochondria. However, the role of subcellular mitochondrial trafficking during cell protrusion generation is not well-understood amidst a lack of quantitative data. Here, we present a high-throughput microfluidic platform that enables the quantitative, single-cell precision analysis of cell protrusion formation during cell migration that is regulated by subcellular mitochondrial trafficking. Gene expression profiling of the isolated cell protrusions suggested that mitochondria were found in high numbers within cell protrusions, a finding validated by mitochondrial staining. Quantitative analysis revealed that the formation of cell protrusions could be effectively suppressed by inhibiting subcellular mitochondrial trafficking. We further demonstrated that rapid screening of mitochondria-specific therapeutic drugs to evaluate their effects on cell protrusion formation with single-cell precision could be achieved in the microfluidic platform, which could have clinical utility in the development of new anticancer agents.

Microfluidic Cell Trap Arrays for Single Hematopoietic Stem/Progenitor Cell Behavior Analysis.

Hematopoietic stem/progenitor cell (HSPC) mobilization from the bone marrow to the bloodstream is a required step for blood cell renewal, and HSPC motility is a clinically relevant standard for peripheral blood stem cell transplantation. Individual HSPCs exhibit considerable heterogeneity in motility behaviors, which are subject to complex intrinsic and extrinsic regulatory mechanisms. Motility-based cell sorting is then demanded to fulfill the study of such mechanism complexity. However, due to the HSPC heterogeneity and difficulty in monitoring cell motility, such a platform is still not available. With the recent development of microfluidics technology, motility-based monitoring, sorting, collecting, and analysis of HSPC behaviors are highly possible and achievable if fluid channels and structures are correctly engineered. Here, a new design of microfluidic arrays for single-cell trapping is presented, enabling high-throughput analysis of individual HSPC motility and behavior. Using these arrays, it is observed that HSPC motility is positively correlated with CD34 asymmetric inheritance and cell differentiation. Transcriptomic analysis of HSPCs sorted according to motility reveals changes in expression of genes associated with the regulation of stem-cell maintenance. Ultimately, this novel, physical cell-sorting system can facilitate the screening of HSPC mobilization compounds and the analysis of signals driving HSPC fate decisions.

CRISPR-Cas12a Coupled with Platinum Nanoreporter for Visual Quantification of SNVs on a Volumetric Bar-Chart Chip.

Methods that can detect and quantify single nucleotide variations (SNVs)/single nucleotide polymorphisms (SNPs) are greatly needed in the bioanalytical measurement of gene mutations and polymorphisms. Herein a visual and instrument-free SNV quantification platform is developed. Platinum nanoparticles tethered to magnetic beads by single-stranded DNAs are designed as quantitative readout reporters for a CRISPR-Cas12a nucleic acid detection system. The integration of platinum nanoreporter and CRISPR-Cas system with a volumetric bar-chart chip realizes the volumetric quantification of nucleic acids. This platform enables quantification of multiple cancer mutations in pure DNA samples and mock cell-free DNA samples in serum, with allelic fractions as low as 0.01%. This platform could have great potential in the quantification of SNVs/SNPs as well as other types of nucleic acid targets at the point of care.

High-Throughput Yeast Aging Analysis for Cryptococcus (HYAAC) microfluidic device streamlines aging studies in Cryptococcus neoformans.

Cryptococcus neoformans (Cn) is a deadly fungal pathogen responsible for ~ 180,000 deaths per year and despite effective antifungals, treatment failure and resistance to antifungals are increasingly problematic. Aging and age-related phenotypes are prominent virulence traits that contribute to the resilience of Cn to host responses and antifungals. Traditional methods to study aging in Cn are expensive, inefficient and in need of improvement. Here, we demonstrate the development and use of a High-Throughput Yeast Aging Analysis for Cryptococcus (HYAAC) microfluidic device to better study aging and age-associated genes in Cn. Compared to traditional methods, the HYAAC is superior in its efficiency to isolate, manipulate and observe old cells for analysis. It allows for the trapping and tracking of individual cells over the course of their lifespan, allowing for more precise measurements of lifespan, tracking of age-related phenotypes with age, and a more high-throughput ability to investigate genes associated with aging.

Cellular response to moderate chromatin architectural defects promotes longevity.

Changes in chromatin organization occur during aging. Overexpression of histones partially alleviates these changes and promotes longevity. We report that deletion of the histone H3-H4 minor locus HHT1-HHF1 extended the replicative life span of Saccharomyces cerevisiae. This longevity effect was mediated through TOR signaling inhibition. We present evidence for evolutionarily conserved transcriptional and phenotypic responses to defects in chromatin structure, collectively termed the chromatin architectural defect (CAD) response. Promoters of the CAD response genes were sensitive to histone dosage, with HHT1-HHF1 deletion, nucleosome occupancy was reduced at these promoters allowing transcriptional activation induced by stress response transcription factors Msn2 and Gis1, both of which were required for the life-span extension of hht1-hhf1Δ. Therefore, we conclude that the CAD response induced by moderate chromatin defects promotes longevity.

High-Throughput Isolation of Cell Protrusions with Single-Cell Precision for Profiling Subcellular Gene Expression.

Invading cancer cells extend cell protrusions, which guide cancer-cell migration and invasion, eventually leading to metastasis. The formation and activity of cell protrusions involve the localization of molecules and organelles at the cell front; however, it is challenging to precisely isolate these subcellular structures at the single-cell level for molecular analysis. Here, we describe a newly developed microfluidic platform capable of high-throughput isolation of cell protrusions at single-cell precision for profiling subcellular gene expression. Using this microfluidic platform, we demonstrate the efficient generation of uniform cell-protrusion arrays (more than 5000 cells with protrusions) for a series of cell types. We show precise isolation of cell protrusions with high purity at single-cell precision for subsequent RNA-Seq analysis, which was further validated by RT-qPCR and RNA FISH. Our highly controlled protrusion isolation method opens a new avenue for the study of subcellular functional mechanisms and signaling pathways in metastasis.

Analysis of the bystander effect in cone photoreceptors via a guided neural network platform.

The mammalian retina system consists of a complicated photoreceptor structure, which exhibits extensive random synaptic connections. To study retinal development and degeneration, various experimental models have been used previously, but these models are often uncontrollable, are difficult to manipulate, and do not provide sufficient similarity or precision. Therefore, the mechanisms in many retinal diseases remain unclear because of the limited capability in observing the progression and molecular driving forces. For example, photoreceptor degeneration can spread to surrounding healthy photoreceptors via a phenomenon known as the bystander effect; however, no in-depth observations can be made to decipher the molecular mechanisms or the pathways that contribute to the spreading. It is then necessary to build dissociated neural networks to investigate the communications with controllability of cells and their treatment. We developed a neural network chip (NN-Chip) to load single neurons into highly ordered microwells connected by microchannels for synapse formation to build the neural network. By observing the distribution of apoptosis spreading from light-induced apoptotic cones to the surrounding cones, we demonstrated convincing evidence of the existence of a cone-to-cone bystander killing effect. Combining the NN-Chip with microinjection technology, we also found that the gap junction protein connexin 36 (Cx36) is critical for apoptosis spreading and the bystander effect in cones. In addition, our unique NN-Chip platform provides a quantitative, high-throughput tool for investigating signaling mechanisms and behaviors in neurons and opens a new avenue for screening potential drug targets to cure retinal diseases.