A review on associated factors and management measures for sarcopenia in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease characterized by hyperglycemia, insulin resistance, and insufficient insulin secretion. Sarcopenia, as a new complication of diabetes, is characterized by the loss of muscle mass and the progressive decline of muscle strength and function in T2DM patients, which has a serious impact on the physical and mental health of patients. Insulin resistance, mitochondrial dysfunction, and chronic inflammation are common mechanisms of diabetes and sarcopenia. Reasonable exercise training, nutrition supplement, and drug intervention may improve the quality of life of patients with diabetes combined with sarcopenia. This article reviews the relevant factors and management measures of sarcopenia in T2DM patients, in order to achieve early detection, diagnosis, and intervention.

A framework towards digital twins for type 2 diabetes.

Introduction: A digital twin is a virtual representation of a patient's disease, facilitating real-time monitoring, analysis, and simulation. This enables the prediction of disease progression, optimization of care delivery, and improvement of outcomes. Methods: Here, we introduce a digital twin framework for type 2 diabetes (T2D) that integrates machine learning with multiomic data, knowledge graphs, and mechanistic models. By analyzing a substantial multiomic and clinical dataset, we constructed predictive machine learning models to forecast disease progression. Furthermore, knowledge graphs were employed to elucidate and contextualize multiomic-disease relationships. Results and discussion: Our findings not only reaffirm known targetable disease components but also spotlight novel ones, unveiled through this integrated approach. The versatile components presented in this study can be incorporated into a digital twin system, enhancing our grasp of diseases and propelling the advancement of precision medicine.

Imaging and Histopathological Features Of Primary Thymic Neuroendocrine Tumor.

OBJECTIVES: To investigate CT, MRI, and PET/CT features with histopathological findings of primary thymic neuroendocrine tumor. MATERIALS AND METHODS: All 9 cases with pathologically proven primary thymic neuroendocrine tumors were reviewed retrospectively. Among them, 7 underwent enhanced CT, 1 with MRI (enhanced) and another with PET/CT scan. Multiple characters were examined, including tumor location, contour, CT attenuation, enhancement pattern, involvement of surrounding structure and lymphadenopathy. RESULTS: Among 9 patients studied, 7 (77%) masses were located in the anterior superior mediastinum, 1 in the anterior superior-middle mediastinum, and 1 in the anterior and middle mediastinum. The maximum diameter (longitudinal) ranged from 4.2 to 23 cm (mean ± standard deviation, 9.5 cm ± 2.8). Four masses had irregular, 3 had lobulated, and 2 had smooth contours, while 8 masses had clear margins and 1 had an ill-defined margin. Six masses showed heterogeneous attenuation with necrotic/cystic component (n=5), calcification (n=2) and hemorrhage(n=1), and 3 showed homogeneous attenuation on the non-enhanced image. After contrast administration, 8 masses showed heterogeneous attenuation, and 1 showed homogeneous attenuation with tumor vessels visible in 4 masses. Among all, 8 masses showed strong enhancement, and 1 showed moderate enhancement in comparison to muscles in the anterior thoracic wall on enhanced images. Involvement of adjacent mediastinal structures was observed in 5 cases. Immunohistochemical analysis showed that the tumor cells were positive for CgA, Syn, CK, CD56 and EMA. CONCLUSION: Primary NETs are large masses located anterior superior mediastinum, irregular in contour, showing heterogeneous attenuation with necrotic/cystic component and strong heterogeneous enhancement with tumor vessels, compressing local mediastinal structures. In addition, immunohistochemical examination is required in such a diagnosis.

Enhancing cancer immunotherapy via inhibition of soluble epoxide hydrolase.

Cancer therapy, including immunotherapy, is inherently limited by chronic inflammation-induced tumorigenesis and toxicity within the tumor microenvironment. Thus, stimulating the resolution of inflammation may enhance immunotherapy and improve the toxicity of immune checkpoint inhibition (ICI). As epoxy-fatty acids (EpFAs) are degraded by the enzyme soluble epoxide hydrolase (sEH), the inhibition of sEH increases endogenous EpFA levels to promote the resolution of cancer-associated inflammation. Here, we demonstrate that systemic treatment with ICI induces sEH expression in multiple murine cancer models. Dietary omega-3 polyunsaturated fatty acid supplementation and pharmacologic sEH inhibition, both alone and in combination, significantly enhance anti-tumor activity of ICI in these models. Notably, pharmacological abrogation of the sEH pathway alone or in combination with ICI counter-regulates an ICI-induced pro-inflammatory and pro-tumorigenic cytokine storm. Thus, modulating endogenous EpFA levels through dietary supplementation or sEH inhibition may represent a unique strategy to enhance the anti-tumor activity of paradigm cancer therapies.

Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells.

Poor prognosis and drug resistance in glioblastoma (GBM) can result from cellular heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation into glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation resists temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how the topology of transcription factor interaction networks drives distinct trajectories of cell state transitions in PD-GSCs resistant or susceptible to cytotoxic drug treatment. By experimentally testing predictions based on TRN simulations, we show that drug treatment drives surviving PD-GSCs along a trajectory of intermediate states, exposing vulnerability to potentiated killing by siRNA or a second drug targeting treatment-induced transcriptional programs governing non-genetic cell plasticity. Our findings demonstrate an approach to uncover TRN topology and use it to rationally predict combinatorial treatments that disrupts acquired resistance in GBM.

The perinucleolar compartment: structure, function, and utility in anti-cancer drug development.

The perinucleolar compartment (PNC) was initially identified as a nuclear structure enriched for the polypyrimidine tract-binding protein. Since then, the PNC has been implicated in carcinogenesis. The prevalence of this compartment is positively correlated with disease progression in various types of cancer, and its expression in primary tumors is linked to worse patient outcomes. Using the PNC as a surrogate marker for anti-cancer drug efficacy has led to the development of a clinical candidate for anti-metastasis therapies. The PNC is a multicomponent nuclear body situated at the periphery of the nucleolus. Thus far, several non-coding RNAs and RNA-binding proteins have been identified as the PNC components. Here, we summarize the current understanding of the structure and function of the PNC, as well as its recurrent links to cancer progression and metastasis.

Monoallelically expressed noncoding RNAs form nucleolar territories on NOR-containing chromosomes and regulate rRNA expression.

Out of the several hundred copies of rRNA genes arranged in the nucleolar organizing regions (NOR) of the five human acrocentric chromosomes, ~50% remain transcriptionally inactive. NOR-associated sequences and epigenetic modifications contribute to the differential expression of rRNAs. However, the mechanism(s) controlling the dosage of active versus inactive rRNA genes within each NOR in mammals is yet to be determined. We have discovered a family of ncRNAs, SNULs (Single NUcleolus Localized RNA), which form constrained sub-nucleolar territories on individual NORs and influence rRNA expression. Individual members of the SNULs monoallelically associate with specific NOR-containing chromosomes. SNULs share sequence similarity to pre-rRNA and localize in the sub-nucleolar compartment with pre-rRNA. Finally, SNULs control rRNA expression by influencing pre-rRNA sorting to the DFC compartment and pre-rRNA processing. Our study discovered a novel class of ncRNAs influencing rRNA expression by forming constrained nucleolar territories on individual NORs.

Cell Population Growth Kinetics in the Presence of Stochastic Heterogeneity of Cell Phenotype.

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized uniform exponential growth of the cell population. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture a departure from the uniform exponential growth model for the initial growth ("take-off"). Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth dynamics, which could be explained by the presence of inter-converting subpopulations with different growth rates, and which could last for many generations. Based on the hypothesis of existence of multiple subpopulations, we developed a branching process model that was consistent with the experimental observations.

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

Single-cell gene set scoring with nearest neighbor graph smoothed data (gssnng).

Summary: Gene set scoring (or enrichment) is a common dimension reduction task in bioinformatics that can be focused on the differences between groups or at the single sample level. Gene sets can represent biological functions, molecular pathways, cell identities, and more. Gene set scores are context dependent values that are useful for interpreting biological changes following experiments or perturbations. Single sample scoring produces a set of scores, one for each member of a group, which can be analyzed with statistical models that can include additional clinically important factors such as gender or age. However, the sparsity and technical noise of single-cell expression measures create difficulties for these methods, which were originally designed for bulk expression profiling (microarrays, RNAseq). This can be greatly remedied by first applying a smoothing transformation that shares gene measure information within transcriptomic neighborhoods. In this work, we use the nearest neighbor graph of cells for matrix smoothing to produce high quality gene set scores on a per-cell, per-group, level which is useful for visualization and statistical analysis. Availability and implementation: The gssnng software is available using the python package index (PyPI) and works with Scanpy AnnData objects. It can be installed using "pip install gssnng." More information and demo notebooks: see https://github.com/IlyaLab/gssnng.

Cell population growth kinetics in the presence of stochastic heterogeneity of cell phenotype.

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized uniform exponential growth of the cell population. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture a departure from the uniform exponential growth model for the initial growth ("take-off"). Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth dynamics, which could be explained by the presence of inter-converting subpopulations with different growth rates, and which could last for many generations. Based on the hypothesis of existence of multiple subpopulations, we developed a branching process model that was consistent with the experimental observations.

Gut Microbiota-Derived Tryptophan Metabolite Indole-3-aldehyde Ameliorates Aortic Dissection.

Tryptophan, an essential dietary amino acid, is metabolized into various metabolites within both gut microbiota and tissue cells. These metabolites have demonstrated potential associations with panvascular diseases. However, the specific relationship between tryptophan metabolism, particularly Indole-3-aldehyde (3-IAId), and the occurrence of aortic dissection (AD) remains unclear. 3-IAId showed an inverse association with advanced atherosclerosis, a risk factor for AD. In this study, we employed a well-established ß-aminopropionitrile monofumarate (BAPN)-induced AD murine model to investigate the impact of 3-IAId treatment on the progression of AD. Our results reveal compelling evidence that the administration of 3-IAId significantly mitigated aortic dissection and rupture rates (BAPN + 3-IAId vs. BAPN, 45% vs. 90%) and led to a notable reduction in mortality rates (BAPN + 3-IAId vs. BAPN, 20% vs. 55%). Furthermore, our study elucidates that 3-IAId exerts its beneficial effects by inhibiting the phenotype transition of vascular smooth muscle cells (VSMCs) from a contractile to a synthetic state. It also mitigates extracellular matrix degradation, attenuates macrophage infiltration, and suppresses the expression of inflammatory cytokines, collectively contributing to the attenuation of AD development. Our findings underscore the potential of 3-IAId as a promising intervention strategy for the prevention of thoracic aortic dissection, thus providing valuable insights into the realm of vascular disease management.

Nucleolar structure connects with global nuclear organization.

The nucleolus is a multifunctional nuclear body. To tease out the roles of nucleolar structure without resorting to the use of multi-action drugs, we knocked down the RNA polymerase I subunit RPA194 in HeLa cells by siRNA. Loss of RPA194 resulted in nucleolar-structural segregation and effects on both nucleolus-proximal and distal-nuclear components. The perinucleolar compartment was disrupted, centromere clustering around nucleoli was significantly reduced, and the intranuclear locations of specific genomic loci were altered. Moreover, Cajal bodies, distal from nucleoli, underwent morphological and some compositional changes. In comparison, when the preribosomal RNA-processing factor, UTP4, was knocked down, neither nucleolar segregation nor the intranuclear effects were observed, demonstrating that the changes of nucleolar proximal and distal nuclear domains in RPA194 knockdown cells unlikely arise from a cessation of ribosome synthesis, rather from the consequence of nucleolar-structure alteration. These findings point to a commutative system that links nucleolar structure to the maintenance and spatial organization of certain nuclear domains and genomic loci.

Concerted epithelial and stromal changes during progression of Barrett's Esophagus to invasive adenocarcinoma exposed by multi-scale, multi-omics analysis.

Esophageal adenocarcinoma arises from Barrett's esophagus, a precancerous metaplastic replacement of squamous by columnar epithelium in response to chronic inflammation. Multi-omics profiling, integrating single-cell transcriptomics, extracellular matrix proteomics, tissue-mechanics and spatial proteomics of 64 samples from 12 patients' paths of progression from squamous epithelium through metaplasia, dysplasia to adenocarcinoma, revealed shared and patient-specific progression characteristics. The classic metaplastic replacement of epithelial cells was paralleled by metaplastic changes in stromal cells, ECM and tissue stiffness. Strikingly, this change in tissue state at metaplasia was already accompanied by appearance of fibroblasts with characteristics of carcinoma-associated fibroblasts and of an NK cell-associated immunosuppressive microenvironment. Thus, Barrett's esophagus progresses as a coordinated multi-component system, supporting treatment paradigms that go beyond targeting cancerous cells to incorporating stromal reprogramming.

PAF49: An RNA Polymerase I subunit essential for rDNA transcription and stabilization of PAF53.

The application of genetic and biochemical techniques in yeast has informed our knowledge of transcription in mammalian cells. Such systems have allowed investigators to determine whether a gene was essential and to determine its function in rDNA transcription. However, there are significant differences in the nature of the transcription factors essential for transcription by Pol I in yeast and mammalian cells, and yeast RNA polymerase I contains 14 subunits while mammalian polymerase contains 13 subunits. We previously reported the adaptation of the auxin-dependent degron that enabled a combination of a "genetics-like" approach and biochemistry to study mammalian rDNA transcription. Using this system, we studied the mammalian orthologue of yeast RPA34.5, PAF49, and found that it is essential for rDNA transcription and cell division. The auxin-induced degradation of PAF49 induced nucleolar stress and the accumulation of P53. Interestingly, the auxin-induced degradation of AID-tagged PAF49 led to the degradation of its binding partner, PAF53, but not vice versa. A similar pattern of co-dependent expression was also found when we studied the non-essential, yeast orthologues. An analysis of the domains of PAF49 that are essential for rDNA transcription demonstrated a requirement for both the dimerization domain and an "arm" of PAF49 that interacts with PolR1B. Further, we demonstrate this interaction can be disrupted to inhibit Pol I transcription in normal and cancer cells which leads to the arrest of normal cells and cancer cell death. In summary, we have shown that both PAF53 and PAF49 are necessary for rDNA transcription and cell growth.

Apposition of Fibroblasts With Metaplastic Gastric Cells Promotes Dysplastic Transition.

BACKGROUND & AIMS: Elements of field cancerization, including atrophic gastritis, metaplasia, and dysplasia, promote gastric cancer development in association with chronic inflammation. However, it remains unclear how stroma changes during carcinogenesis and how the stroma contributes to progression of gastric preneoplasia. Here we investigated heterogeneity of fibroblasts, one of the most important elements in the stroma, and their roles in neoplastic transformation of metaplasia. METHODS: We used single-cell transcriptomics to evaluate the cellular heterogeneity of mucosal cells from patients with gastric cancer. Tissue sections from the same cohort and tissue microarrays were used to identify the geographical distribution of distinct fibroblast subsets. We further evaluated the role of fibroblasts from pathologic mucosa in dysplastic progression of metaplastic cells using patient-derived metaplastic gastroids and fibroblasts. RESULTS: We identified 4 subsets of fibroblasts within stromal cells defined by the differential expression of PDGFRA, FBLN2, ACTA2, or PDGFRB. Each subset was distributed distinctively throughout stomach tissues with different proportions at each pathologic stage. The PDGFRα+ subset expanded in metaplasia and cancer compared with normal, maintaining a close proximity with the epithelial compartment. Co-culture of metaplasia- or cancer-derived fibroblasts with gastroids showing the characteristics of spasmolytic polypeptide-expressing metaplasia-induced disordered growth, loss of metaplastic markers, and increases in markers of dysplasia. Culture of metaplastic gastroids with conditioned media from metaplasia- or cancer-derived fibroblasts also promoted dysplastic transition. CONCLUSIONS: These findings indicate that fibroblast associations with metaplastic epithelial cells can facilitate direct transition of metaplastic spasmolytic polypeptide-expressing metaplasia cell lineages into dysplastic lineages.

Nucleolar structure connects with global nuclear organization.

The nucleolus is a multi-functional nuclear body. To tease out the roles of nucleolar structure without resorting to multi-action drugs, we knocked down RNA polymerase I subunit RPA194 in HeLa cells by siRNA. Loss of RPA194 resulted in nucleolar structural segregation and effects on both nucleolus-proximal and distal nuclear components. The perinucleolar compartment was disrupted, centromere-nucleolus interactions were significantly reduced, and the intranuclear locations of specific genomic loci were altered. Moreover, Cajal bodies, distal from nucleoli, underwent morphological and compositional changes. To distinguish whether these global reorganizations are the results of nucleolar structural disruption or inhibition of ribosome synthesis, the pre-ribosomal RNA processing factor, UTP4, was also knocked down, which did not lead to nucleolar segregation, nor the intranuclear effects seen with RPA195A knockdown, demonstrating that they do not arise from a cessation of ribosome synthesis. These findings point to a commutative system that links nucleolar structure to the maintenance and spatial organization of certain nuclear bodies and genomic loci.

Nucleoli and the nucleoli-centromere association are dynamic during normal development and in cancer.

Centromeres are known to cluster around nucleoli in Drosophila and mammalian cells, but the significance of the nucleoli-centromere interaction remains underexplored. To determine whether the interaction is dynamic under different physiological and pathological conditions, we examined nucleolar structure and centromeres at various differentiation stages using cell culture models and the results showed dynamic changes in nucleolar characteristics and nucleoli-centromere interactions through differentiation and in cancer cells. Embryonic stem cells usually have a single large nucleolus, which is clustered with a high percentage of centromeres. As cells differentiate into intermediate states, the nucleolar number increases and the centromere association decreases. In terminally differentiated cells, including myotubes, neurons, and keratinocytes, the number of nucleoli and their association with centromeres are at the lowest. Cancer cells demonstrate the pattern of nucleoli number and nucleoli-centromere association that is akin to proliferative cell types, suggesting that nucleolar reorganization and changes in nucleoli-centromere interactions may play a role in facilitating malignant transformation. This idea is supported in a case of pediatric rhabdomyosarcoma, in which induced differentiation reduces the nucleolar number and centromere association. These findings suggest active roles of nucleolar structure in centromere function and genome organization critical for cellular function in both normal development and cancer.

Cell Population Growth Kinetics in the Presence of Stochastic Heterogeneity of Cell Phenotype.

Recent studies at individual cell resolution have revealed phenotypic heterogeneity in nominally clonal tumor cell populations. The heterogeneity affects cell growth behaviors, which can result in departure from the idealized exponential growth. Here we measured the stochastic time courses of growth of an ensemble of populations of HL60 leukemia cells in cultures, starting with distinct initial cell numbers to capture the departure from the exponential growth model in the initial growth phase. Despite being derived from the same cell clone, we observed significant variations in the early growth patterns of individual cultures with statistically significant differences in growth kinetics and the presence of subpopulations with different growth rates that endured for many generations. Based on the hypothesis of existence of multiple inter-converting subpopulations, we developed a branching process model that captures the experimental observations.