Global research trends in regulating gut microbiome to improve type 2 diabetes mellitus: bibliometrics and visual analysis.

Background: Gut microbiome (GM) and type 2 diabetes mellitus (T2DM) have two-way effects. Improving T2DM by modulating GM in various ways, such as diet, exercise, and medication, is gradually becoming popular, and related studies have yielded positive results. However, there is still a lack of high-quality bibliometric analyses of research in this area. This study aims to systematize and comprehensively summarize the knowledge structure, research tropics, and research trends of GM and T2DM through bibliometric analysis. Methods: Publications related to GM and T2DM before January 9, 2024, in the Web of Science Core Collection (WOSCC) were searched in this study. Microsoft Excel 2019 was used to analyze publishing trends and CiteSpace (v.6.1.R6 Advanced) was used to analyze institutions, cited journals, references, and keywords.SCImago Graphica (v.1.0.39) was used to analyze countries/regions, institutions' collaborations, cited authors, and published journals. Results: We finally included 1004 articles published from 2008 to 2023. The number of published articles showed an upward trend and reached its peak in 2022. China is the country with the largest number of articles, Univ Copenhagen is the institution with the largest number of articles, Fukui, Michiaki, Hamaguchi, Masahide are the scholars with the largest number of articles, and Cani and Patrice D. are the scholars with the largest number of citations. NUTRIENTS(Q1/5.9) published the most publications, while Nature (Q1/64.8; Cited 804 times) is the most frequently cited journal. Gut microbiota, Obesity, and insulin resistance are the most frequently used keywords. This study found that current researches focus on the effects of diet, exercise, and pharmacological modification of GM to improve T2DM and explores specific mechanisms. Future researches will focus on three areas: complications of T2DM and specific physiological processes, methods and measures to regulate GM, and new experimental techniques and assays. Conclusion: The current researches confirmed the effects and specific mechanisms of modulating GM to improve T2DM. Further exploration of the effects of modulating GM on T2DM complications and specific physiologic processes is a future trend of research. Exploring specific methods for regulating GM and developing new experimental techniques and assays are important for future research.

The value of serum IL-4 to predict the survival of MDS patients.

BACKGROUND: Immune indicators are routinely used for the detection of myelodysplastic syndrome (MDS), but these are not utilized as a reference indicator to assess prognosis in MDS-related prognostic evaluation systems, such as the World Health Organizational prognostic scoring system, the international prostate symptom score, and the revised international prostate symptom score. METHODS: We examined immune indicators, including cluster of differentiation (CD)3, CD4, CD8, CD56, CD19, interleukin (IL)-2, IL-4, IL-6, IL-10, tumor necrosis factor-a, and interferon-γ in 155 newly diagnosed MDS patients. We also conducted a correlation analysis with clinical indices. RESULTS: IL-4 was found to be a predictor of survival in these 155 patients using the receiver operating characteristic curve, with 5.155 as the cut-off point. Patients with serum IL-4 levels ≥ 5.155 had a lower overall survival (OS) than those with IL-45.155 at diagnosis. Furthermore, multivariate analysis revealed that IL-4 levels > 5.155 were an independent predictor of OS (hazard ratio: 0.237; 95% confidence interval, 0.114-0.779; P = 0.013). In addition, serum IL-4 expression in the three different scoring systems showed significant differences in the survival of medium- to high-risk MDS patients (P = 0.014, P < 0.001, P < 0.001). CONCLUSIONS: According to our study, IL-4 levels at the time of diagnosis can predict MDS prognosis in patients as a simple index reflecting host systemic immunity.

The immunological role of mesenchymal stromal cells in patients with myelodysplastic syndrome.

Myelodysplastic syndrome (MDS) is a common hematological malignant disease, characterized by malignant hematopoietic stem cell proliferation in the bone marrow (BM); clinically, it mainly manifests clinically mainly by as pathological hematopoiesis, hemocytopenia, and high-risk transformation to acute leukemia. Several studies have shown that the BM microenvironment plays a critical role in the progression of MDS. In this study, we specifically evaluated mesenchymal stromal cells (MSCs) that exert immunomodulatory effects in the BM microenvironment. This immunomodulatory effect occurs through direct cell-cell contact and the secretion of soluble cytokines or micro vesicles. Several researchers have compared MSCs derived from healthy donors to low-risk MDS-associated bone mesenchymal stem cells (BM-MSCs) and have found no significant abnormalities in the MDS-MSC phenotype; however, these cells have been observed to exhibit altered function, including a decline in osteoblastic function. This altered function may promote MDS progression. In patients with MDS, especially high-risk patients, MSCs in the BM microenvironment regulate immune cell function, such as that of T cells, B cells, natural killer cells, dendritic cells, neutrophils, myeloid-derived suppressor cells (MDSCs), macrophages, and Treg cells, thereby enabling MDS-associated malignant cells to evade immune cell surveillance. Alterations in MDS-MSC function include genomic instability, microRNA production, histone modification, DNA methylation, and abnormal signal transduction and cytokine secretion.

Effect of Dexmedetomidine on Perioperative Stress Response and Immune Function in Patients With Tumors.

OBJECTIVE: This study aims to investigate the effect of dexmedetomidine on perioperative stress response and immune function in patients with tumors. METHODS: Sixty patients who underwent selective radical gastrectomy for cancer were randomly divided into 3 groups: remifentanil group (group R), dexmedetomidine group (group D), and sufentanil group (group S). Remifentanil, dexmedetomidine, and sufentanil were used as general anesthetics. Endotracheal intubation and mechanical ventilation were performed after the spontaneous respiration disappeared. Then, the data were recorded, and blood samples were collected at all time points. RESULTS: The heart rate significantly increased (P < 0.05) at T1 in group S, and both heart rate and mean arterial pressure significantly increased (P < 0.05) in group R when compared to group D. The heart rate significantly increased (P < 0.05) at T2 in group S and group R. Furthermore, the heart rate significantly increased (P < 0.05) at T3 and T4 in group S and group R. Intra-group comparison: The heart rate at T1-T4 and mean arterial pressure at T1-T4 significantly increased (P < 0.05) in group S, and the heart rate at T1 and T4, and mean arterial pressure at T2-T4 significantly increased (P < 0.05) in group R when compared to T0. The serum IL-6, IFN-γ, and ß-EP significantly increased (P < 0.05) at T0' in group S and group R when compared to group D. Blood glucose, and serum IL-10, IFN-γ, and ß-EP significantly increased (P < 0.05), while IL-18 significantly decreased (P < 0.05) at T1' in group S and group R. CONCLUSION: Continuous infusion of dexmedetomidine in combination with the inhalation of sevoflurane is superior to sevoflurane + remifentanil or sufentanil in patients undergoing tumor surgery.

The Scaffold Proteins Paxillin B and α-Actinin Regulate Septation in Aspergillus nidulans via Control of Actin Ring Contraction.

Cytokinesis, as the final step of cell division, plays an important role in fungal growth and proliferation. In the filamentous fungus Aspergillus nidulans, defective cytokinesis is able to induce abnormal multinuclear or nonnucleated cells and then result in reduced hyphal growth and abolished sporulation. Previous studies have reported that a conserved contractile actin ring (CAR) protein complex and the septation initiation network (SIN) signaling kinase cascade are required for cytokinesis and septation; however, little is known about the role(s) of scaffold proteins involved in these two important cellular processes. In this study, we show that a septum-localized scaffold protein paxillin B (PaxB) is essential for cytokinesis/septation in A. nidulans The septation defects observed in a paxB deletion strain resemble those caused by the absence of another identified scaffold protein, α-actinin (AcnA). Deletion of α-actinin (AcnA) leads to undetectable PaxB at the septation site, whereas deletion of paxB does not affect the localization of α-actinin at septa. However, deletion of either α-actinin (acnA) or paxB causes the actin ring to disappear at septation sites during cytokinesis. Notably, overexpression of α-actinin acnA partially rescues the septum defects of the paxB mutant but not vice versa, suggesting AcnA may play a dominant role over that of PaxB for cytokinesis and septation. In addition, PaxB and α-actinin affect the septal dynamic localization of MobA, a conserved component of the SIN pathway, suggesting they may affect the SIN protein complex function at septa. Protein pull-down assays combined with liquid chromatography-mass spectrometry identification indicate that α-actinin AcnA and PaxB likely do not directly interact, but presumably belong to an actin cytoskeleton protein network that is required for the assembly and contraction of the CAR. Taken together, findings in this study provide novel insights into the roles of conserved scaffold proteins during fungal septation in A. nidulans.

A new identified suppressor of Cdc7p/SepH kinase, PomA, regulates fungal asexual reproduction via affecting phosphorylation of MAPK-HogA.

The septation initiation network (SIN), composed of a conserved SepH (Cdc7p) kinase cascade, plays an essential role in fungal cytokinesis/septation and conidiation for asexual reproduction, while the mitogen-activated protein kinase (MAPK) pathway depends on successive signaling cascade phosphorylation to sense and respond to stress and environmental factors. In this study, a SepH suppressor-PomA in the filamentous fungus A. nidulans is identified as a negative regulator of septation and conidiation such that the pomA mutant is able to cure defects of sepH1 in septation and conidiation and overexpression of pomA remarkably suppresses septation. Under the normal cultural condition, SepH positively regulates the phosphorylation of MAPK-HogA, while PomA reversely affects this process. In the absence of PbsB (MAPKK, a putative upstream member of HogA), PomA and SepH are unable to affect the phosphorylation level of HogA. Under the osmostress condition, the induced phosphorylated HogA is capable of bypassing the requirement of SepH, a key player for early events during cytokinesis but not for MobA/SidB, the last one in the core SIN protein kinase cascade, indicating the osmotic stimuli-induced septation is capable of bypassing requirement of SepH but unable to bypass the whole SIN requirement. Findings demonstrate that crosstalk exists between the SIN and MAPK pathways. PomA and SepH indirectly regulate HogA phosphorylation through affecting HogA-P upstream kinases.

ERDS-exome: a Hybrid Approach for Copy Number Variant Detection from Whole-exome Sequencing Data.

Copy number variants (CNVs) play important roles in human disease and evolution. With the rapid development of next-generation sequencing technologies, many tools have been developed for inferring CNVs based on whole-exome sequencing (WES) data. However, as a result of the sparse distribution of exons in the genome, the limitations of the WES technique, and the nature of high-level signal noises in WES data, the efficacy of these variants remains less than desirable. Thus, there is need for the development of an effective tool to achieve a considerable power in WES CNVs discovery. In the present study, we describe a novel method, Estimation by Read Depth (RD) with Single-nucleotide variants from exome sequencing data (ERDS-exome). ERDS-exome employs a hybrid normalization approach to normalize WES data and to incorporate RD and single-nucleotide variation information together as a hybrid signal into a paired hidden Markov model to infer CNVs from WES data. Based on systematic evaluations of real data from the 1000 Genomes Project using other state-of-the-art tools, we observed that ERDS-exome demonstrates higher sensitivity and provides comparable or even better specificity than other tools. ERDS-exome is publicly available at: https://erds-exome.github.io.

GAB2 rs2373115 variant contributes to Alzheimer's disease risk specifically in European population.

A genome-wide association study identified GAB2 rs2373115 to be associated with Alzheimer's disease (AD) risk in European population. However, inconsistent results are reported in East Asian population. Here, we performed an updated analysis using 65,704 samples including 20,982 AD cases and 44,722 controls. First, we investigated the GAB2 rs2373115 variant in Asian population using 3974 AD cases and 7568 controls. To further evaluate the effect of rs2373115 in different populations, we selected 17,008 AD cases and 37,154 controls in European population. We used three genetic models, and found no significant heterogeneity in Asian population. A fixed effect model analysis showed no significant association between rs2373115 and AD in Asian population. There was no significant heterogeneity in the pooled East Asian and European populations. The fixed effect model analysis again showed no significant association between rs2373115 and AD in these pooled populations. Taken together, these findings suggest that GAB2 rs2373115 may contribute to AD susceptibility only in European population but not in East Asian population.

A hybrid continuous-discrete method for stochastic reaction-diffusion processes.

Stochastic fluctuations in reaction-diffusion processes often have substantial effect on spatial and temporal dynamics of signal transductions in complex biological systems. One popular approach for simulating these processes is to divide the system into small spatial compartments assuming that molecules react only within the same compartment and jump between adjacent compartments driven by the diffusion. While the approach is convenient in terms of its implementation, its computational cost may become prohibitive when diffusive jumps occur significantly more frequently than reactions, as in the case of rapid diffusion. Here, we present a hybrid continuous-discrete method in which diffusion is simulated using continuous approximation while reactions are based on the Gillespie algorithm. Specifically, the diffusive jumps are approximated as continuous Gaussian random vectors with time-dependent means and covariances, allowing use of a large time step, even for rapid diffusion. By considering the correlation among diffusive jumps, the approximation is accurate for the second moment of the diffusion process. In addition, a criterion is obtained for identifying the region in which such diffusion approximation is required to enable adaptive calculations for better accuracy. Applications to a linear diffusion system and two nonlinear systems of morphogens demonstrate the effectiveness and benefits of the new hybrid method.

Noise modulation in retinoic acid signaling sharpens segmental boundaries of gene expression in the embryonic zebrafish hindbrain.

Morphogen gradients induce sharply defined domains of gene expression in a concentration-dependent manner, yet how cells interpret these signals in the face of spatial and temporal noise remains unclear. Using fluorescence lifetime imaging microscopy (FLIM) and phasor analysis to measure endogenous retinoic acid (RA) directly in vivo, we have investigated the amplitude of noise in RA signaling, and how modulation of this noise affects patterning of hindbrain segments (rhombomeres) in the zebrafish embryo. We demonstrate that RA forms a noisy gradient during critical stages of hindbrain patterning and that cells use distinct intracellular binding proteins to attenuate noise in RA levels. Increasing noise disrupts sharpening of rhombomere boundaries and proper patterning of the hindbrain. These findings reveal novel cellular mechanisms of noise regulation, which are likely to play important roles in other aspects of physiology and disease.

Semi-permeable Diffusion Barriers Enhance Patterning Robustness in the C. elegans Germline.

Positional information derived from local morphogen concentration plays an important role in patterning. A key question is how morphogen diffusion and gene expression regulation shape positional information into an appropriate profile with suitably low noise. We address this question using a model system--the C. elegans germline--whose regulatory network has been well characterized genetically but whose spatiotemporal dynamics are poorly understood. We show that diffusion within the germline syncytium is a critical control of stem cell differentiation and that semi-permeable diffusion barriers present at key locations make it possible--in combination with a feedback loop in the germline regulatory network--for mitotic zone size to be robust against spatial noise in Notch signaling. Spatial averaging within compartments defined by diffusion barriers is an advantageous patterning strategy, which attenuates noise while still allowing for sharp transitions between compartments. This strategy could apply to other organs.

External noise control in inherently stochastic biological systems.

Biological systems are often subject to external noise from signal stimuli and environmental perturbations, as well as noises in the intracellular signal transduction pathway. Can different stochastic fluctuations interact to give rise to new emerging behaviors? How can a system reduce noise effects while still being capable of detecting changes in the input signal? Here, we study analytically and computationally the role of nonlinear feedback systems in controlling external noise with the presence of large internal noise. In addition to noise attenuation, we analyze derivatives of Fano factor to study systems' capability of differentiating signal inputs. We find effects of internal noise and external noise may be separated in one slow positive feedback loop system; in particular, the slow loop can decrease external noise and increase robustness of signaling with respect to fluctuations in rate constants, while maintaining the signal output specific to the input. For two feedback loops, we demonstrate that the influence of external noise mainly depends on how the fast loop responds to fluctuations in the input and the slow loop plays a limited role in determining the signal precision. Furthermore, in a dual loop system of one positive feedback and one negative feedback, a slower positive feedback always leads to better noise attenuation; in contrast, a slower negative feedback may not be more beneficial. Our results reveal interesting stochastic effects for systems containing both extrinsic and intrinsic noises, suggesting novel noise filtering strategies in inherently stochastic systems.

Noise drives sharpening of gene expression boundaries in the zebrafish hindbrain.

Morphogens provide positional information for spatial patterns of gene expression during development. However, stochastic effects such as local fluctuations in morphogen concentration and noise in signal transduction make it difficult for cells to respond to their positions accurately enough to generate sharp boundaries between gene expression domains. During development of rhombomeres in the zebrafish hindbrain, the morphogen retinoic acid (RA) induces expression of hoxb1a in rhombomere 4 (r4) and krox20 in r3 and r5. Fluorescent in situ hybridization reveals rough edges around these gene expression domains, in which cells co-express hoxb1a and krox20 on either side of the boundary, and these sharpen within a few hours. Computational analysis of spatial stochastic models shows, surprisingly, that noise in hoxb1a/krox20 expression actually promotes sharpening of boundaries between adjacent segments. In particular, fluctuations in RA initially induce a rough boundary that requires noise in hoxb1a/krox20 expression to sharpen. This finding suggests a novel noise attenuation mechanism that relies on intracellular noise to induce switching and coordinate cellular decisions during developmental patterning.

The effect of the signalling scheme on the robustness of pattern formation in development.

Pattern formation in development is a complex process which involves spatially distributed signals called morphogens that influence gene expression and thus the phenotypic identity of cells. Usually different cell types are spatially segregated, and the boundary between them may be determined by a threshold value of some state variable. The question arises as to how sensitive the location of such a boundary is to variations in properties, such as parameter values, that characterize the system. Here, we analyse both deterministic and stochastic reaction-diffusion models of pattern formation with a view towards understanding how the signalling scheme used for patterning affects the variability of boundary determination between cell types in a developing tissue.

A new method for choosing the computational cell in stochastic reaction-diffusion systems.

How to choose the computational compartment or cell size for the stochastic simulation of a reaction-diffusion system is still an open problem, and a number of criteria have been suggested. A generalized measure of the noise for finite-dimensional systems based on the largest eigenvalue of the covariance matrix of the number of molecules of all species has been suggested as a measure of the overall fluctuations in a multivariate system, and we apply it here to a discretized reaction-diffusion system. We show that for a broad class of first-order reaction networks this measure converges to the square root of the reciprocal of the smallest mean species number in a compartment at the steady state. We show that a suitably re-normalized measure stabilizes as the volume of a cell approaches zero, which leads to a criterion for the maximum volume of the compartments in a computational grid. We then derive a new criterion based on the sensitivity of the entire network, not just of the fastest step, that predicts a grid size that assures that the concentrations of all species converge to a spatially-uniform solution. This criterion applies for all orders of reactions and for reaction rate functions derived from singular perturbation or other reduction methods, and encompasses both diffusing and non-diffusing species. We show that this predicts the maximal allowable volume found in a linear problem, and we illustrate our results with an example motivated by anterior-posterior pattern formation in Drosophila, and with several other examples.