Biomedicines最新文献

Purpose: Murine models of pancreatic cancer with damp-heat syndrome were established based on two methods to explore the differences in the composition of intestinal flora and to seek characteristic genera with potential for model evaluation.

Methods: In our study, thirty-four C57BL/6J male mice were randomly divided into a control group (Con), a model group (Mod), a classic damp-heat syndrome group (CDHS), and a climate-chamber group (CC). CDHS and CC groups were fed with a high-fat diet and glucose water, while the CDHS group was given 2.4 g/kg alcohol by gavage for 10 days, and the CC group was placed in a climatic chamber with a set temperature of (32 ± 1) °C and humidity of (92 ± 2)% for 10 days. The Mod group, CDHS group, and CC group underwent tumor-building experiments on day 11. Tumorigenicity was then assessed twice a week. After 4 weeks, feces, colon tissue, and tumor tissue were taken from the mice and were tested, and the mice were euthanized afterwards.

Results: Mice in the CDHS and CC groups showed symptoms similar to the clinical damp-heat syndrome observed in traditional Chinese medicine (TCM), and exhibited a worse general condition and more rapid tumor growth trend than those in the Mod group. The pathological examination indicated that inflammation was prevalent in the CDHS and CC groups. Both groups had a disrupted intestinal barrier and an overgrowth of pathogenic bacteria such as c_Gammaproteobacteria, o_Enterobacteriales, and g_Bacteroides. Their microbiota composition showed greater diversity.

Conclusions: Intestinal flora may have a promising future in the discovery of indicators for evaluating a model of damp-heat syndrome in pancreatic cancer.

Background: His bundle pacing (HBP) and left bundle branch pacing (LBBP) are emerging therapies for patients with heart failure and conduction disorders, offering potential advantages over traditional pacing methods. These approaches aim to restore physiological conduction and improve cardiac function more effectively.

Objective: This study aims to evaluate the efficacy and safety of HBP and LBBP in patients with heart failure and conduction disturbances, comparing these techniques to conventional pacing.

Methods: A comprehensive review of recent studies and clinical trials was conducted, focusing on the performance of HBP and LBBP in improving cardiac function, reducing QRS duration, and enhancing overall patient outcomes. The analysis includes data on clinical efficacy, procedural safety, and long-term benefits associated with these pacing modalities.

Results: Both HBP and LBBP have demonstrated significant improvements in cardiac function and clinical outcomes compared to conventional pacing. HBP effectively restores physiological conduction with improved synchronization and a reduction in QRS duration. LBBP has shown enhanced left ventricular activation, leading to better overall cardiac performance. Both techniques have been associated with a lower incidence of complications and a higher success rate in achieving optimal pacing thresholds.

Conclusions: HBP and LBBP offer promising alternatives to traditional pacing for patients with heart failure and conduction disorders. These advanced pacing strategies provide superior clinical outcomes and improved cardiac function with reduced risk of complications. Further research and clinical trials are needed to fully establish the long-term benefits and safety profiles of these techniques in diverse patient populations.

Objectives: Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) has gained a primary role in prostate cancer (PCa) imaging, overcoming conventional imaging and prostate-specific antigen (PSA) serum levels, and has recently emerged as a promising technique for monitoring therapy response in metastatic castration-resistant prostate cancer (mCRPC) patients treated with novel hormonal therapy, taxanes, and radioligand therapy (RLT). In this review, we aim to provide an overview of the most relevant aspects under study and future prospects related to the prognostic role of PSMA PET/CT in mCRPC.

Methods: A systematic literature search was performed in the following databases: MEDLINE, PubMed, and EMBASE databases. The study focused exclusively on English-language studies, excluding papers not pertinent to the topic.

Results: PSMA PET imaging offers a higher sensitivity and specificity than conventional imaging and provides accurate staging and efficient diagnosis of distant metastases. The data presented herein highlight the usefulness of PET in risk stratification, with a prognostic potential that can have a significant impact on clinical practice. Several prospective trials are ongoing and will shortly provide more evidence supporting the prognostic potential of PET PSMA data in this clinical scenario.

Conclusions: Current evidence proves the prognostic role of PSMA PET/CT in different settings, with raising relevance also in the context of mCRPC.

Background: Neurosurgery demands exceptional precision due to the brain's complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon's ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as a promising innovation, offering real-time, in vivo non-invasive biochemical tissue characterization. This literature review evaluates the current research on RS applications in intraoperative neurosurgery, emphasizing its potential to enhance surgical precision and patient outcomes.

Methods: Following PRISMA guidelines, a comprehensive systematic review was conducted using PubMed to extract relevant peer-reviewed articles. The inclusion criteria focused on original research discussing real-time RS applications with human tissue samples in or near the operating room, excluding retrospective studies, reviews, non-human research, and other non-relevant publications.

Results: Our findings demonstrate that RS significantly improves tumor margin delineation, with handheld devices achieving high sensitivity and specificity. Stimulated Raman Histology (SRH) provides rapid, high-resolution tissue images comparable to traditional histopathology but with reduced time to diagnosis. Additionally, RS shows promise in identifying tumor types and grades, aiding precise surgical decision-making. RS techniques have been particularly beneficial in enhancing the accuracy of glioma surgeries, where distinguishing between tumor and healthy tissue is critical. By providing real-time molecular data, RS aids neurosurgeons in maximizing the extent of resection (EOR) while minimizing damage to normal brain tissue, potentially improving patient outcomes and reducing recurrence rates.

Conclusions: This review underscores the transformative potential of RS in neurosurgery, advocating for continued innovation and research to fully realize its benefits. Despite its substantial potential, further research is needed to validate RS's clinical utility and cost-effectiveness.

Background. Currently, it is known that the gut microbiota plays an important role in the functioning of the immune system, and a rebalancing of the bacterial community can arouse complex immune reactions and lead to immune-mediated responses in an organism, in particular, the development of atopic dermatitis (AD). Cytokines and chemokines are regulators of the innate and adaptive immune response and represent the most important biomarkers of the immune system. It is known that changes in cytokine profiles are a hallmark of many diseases, including atopy. However, it remains unclear how the bacterial imbalance disrupts the function of the immune response in AD. Objectives. We attempted to determine the role of gut bacteria in modulating cytokine pathways and their role in atopic inflammation. Methods. We sequenced the 16S rRNA gene from 50 stool samples of children aged 3-12 years who had confirmed atopic dermatitis, and 50 samples from healthy children to serve as a control group. To evaluate the immune status, we conducted a multiplex immunofluorescence assay and measured the levels of 41 cytokines and chemokines in the serum of all participants. Results. To find out whether changes in the composition of the gut microbiota were significantly associated with changes in the level of inflammatory cytokines, a correlation was calculated between each pair of bacterial family and cytokine. In the AD group, 191 correlations were significant (Spearman's correlation coefficient, p ≤ 0.05), 85 of which were positive and 106 which were negative. Conclusions. It has been demonstrated that intestinal dysbiosis is associated with alterations in cytokine profiles, specifically an increase in proinflammatory cytokine concentrations. This may indicate a systemic impact of these conditions, leading to an imbalance in the immune system's response to the Th2 type. As a result, atopic conditions may develop. Additionally, a correlation between known AD biomarkers (IL-5, IL-8, IL-13, CCL22, IFN-γ, TNF-α) and alterations in the abundance of bacterial families (Pasteurellaceae, Barnesiellaceae, Eubacteriaceae) was observed.

Background/objectives: Type 1 diabetes affects cytokines as potential inducers of NFκB signalling involved in inflammation and neuronal survival. Our goal was to assess the expression of NFκB p65 and its negative regulator, Nrf2, in myenteric neurons and adjacent smooth muscle of different gut segments after chronic hyperglycaemia and immediate insulin treatment.

Methods: After ten weeks of hyperglycaemia, intestinal samples of control, streptozotocin-induced diabetic and insulin-treated diabetic rats were prepared for fluorescent immunohistochemistry, immunogold electron microscopy, ELISA and qPCR.

Results: In the diabetic rats, the proportion of NFκB p65-immunoreactive myenteric neurons decreased significantly in the duodenum and increased in the ileum. The density of NFκB p65-labelling gold particles increased in the ileal but remained unchanged in the duodenal ganglia. Meanwhile, both total and nuclear Nrf2 density increased in the myenteric neurons of the diabetic duodenum. In smooth muscle, NFκB p65 and Nrf2 density increased in the small intestine of diabetic rats. While on the mRNA level, NFκB p65 and Nrf2 were induced, on the protein level, NFκB p65 increased and Nrf2 decreased in muscle/myenteric plexus homogenates. Insulin treatment had protective effects.

Conclusions: Our findings reveal a segment-specific NFκB and Nrf expression in myenteric neurons and ganglionic muscular environments, which may contribute to regional neuronal survival and motility disturbances in diabetes.

Background: To date, there have been numerous metataxonomic studies on gut microbiota (GM) profiling based on the analyses of data from public repositories. However, differences in study population and wet and dry pipelines have produced discordant results. Herein, we propose a biostatistical approach to remove these batch effects for the GM characterization in the case of autism spectrum disorders (ASDs).

Methods: An original dataset of GM profiles from patients with ASD was ecologically characterized and compared with GM public digital profiles of age-matched neurotypical controls (NCs). Also, GM data from seven case-control studies on ASD were retrieved from the NCBI platform and exploited for analysis. Hence, on each dataset, conditional quantile regression (CQR) was performed to reduce the batch effects originating from both technical and geographical confounders affecting the GM-related data. This method was further applied to the whole dataset matrix, obtained by merging all datasets. The ASD GM markers were identified by the random forest (RF) model.

Results: We observed a different GM profile in patients with ASD compared with NC subjects. Moreover, a significant reduction of technical- and geographical-dependent batch effects in all datasets was achieved. We identified Bacteroides_H, Faecalibacterium, Gemmiger_A_73129, Blautia_A_141781, Bifidobacterium_388775, and Phocaeicola_A_858004 as robust GM bacterial biomarkers of ASD. Finally, our validation approach provided evidence of the validity of the QCR method, showing high values of accuracy, specificity, sensitivity, and AUC-ROC.

Conclusions: Herein, we proposed an updated biostatistical approach to reduce the technical and geographical batch effects that may negatively affect the description of bacterial composition in microbiota studies.

Background: Schizophrenia (SZ) is a multifactorial chronic psychiatric disorder with a worldwide prevalence of 1%. Altered expression of PLCβ occurs in SZ patients, suggesting alterations in the PLCβ/IP₃/Ca²⁺ signaling pathway. This cascade regulates critical cellular processes in all cell types, including the neuronal lineage; however, there is scarce evidence regarding the functionality of this transduction signaling in neuronal cells derived from SZ patients. Objective: We evaluated the functionality of the PLCβ/IP₃/Ca²⁺ pathway in olfactory neuronal precursor cells (hONPCs) obtained from SZ patients. Methods: Cryopreserved hONPCs isolated from SZ patients and healthy subjects (HS) were thawed. The cellular types in subcultures were corroborated by immunodetection of the multipotency and lineage markers SOX-2, Musashi-1, nestin, and β-III tubulin. The PLCβ/IP₃/Ca²⁺ pathway was activated by GPCR (G_q) ligands (ATP, UTP, serotonin, and epinephrine). In addition, PLCβ and IP₃R were directly stimulated by perfusing cells with the activators m-3M3FBS and ADA, respectively. Cytosolic Ca²⁺ was measured by microfluorometry and by Ca²⁺ imaging. The amount and subcellular distribution of the PLCβ1 and PLCβ3 isoforms were evaluated by confocal immunofluorescence. IP₃ concentration was measured by ELISA. Results: The results show that the increase of cytosolic Ca²⁺ triggered by GPCR ligands or directly through either PLCβ or IP₃R activation was significantly lower in SZ-derived hONPCs, regarding HS-derived cells. Moreover, the relative amount of the PLCβ1 and PLCβ3 isoforms and IP₃ production stimulated with m-3M3FBS were reduced in SZ-derived cells. Conclusions: Our results suggest an overall functional impairment in the PLCβ/IP₃/Ca²⁺ signaling pathway in SZ-derived hONPCs.

Background: Prostate cancer is the second most common new cancer diagnosis in the United States. It is usually slow-growing, and when it is low-grade and confined to the prostate gland, it can be treated either conservatively (through active surveillance) or with surgery. However, if the cancer has spread beyond the prostate, such as to the lymph nodes, then that indicates a more aggressive cancer, and surgery may not be adequate. Methods: The challenge is that it is often difficult for radiologists reading prostate-specific imaging such as magnetic resonance images (MRIs) to differentiate malignant lymph nodes from non-malignant ones. An emerging field is the development of artificial intelligence (AI) models, including machine learning and deep learning, for medical imaging to assist in diagnostic tasks. Earlier research focused on implementing texture algorithms to extract imaging features used in classification models. More recently, researchers began studying the use of deep learning for both stand-alone feature extraction and end-to-end classification tasks. In order to tackle the challenges inherent in small datasets, this study was designed as a scalable hybrid framework utilizing pre-trained ResNet-18, a deep learning model, to extract features that were subsequently fed into a machine learning classifier to automatically identify malignant lymph nodes in patients with prostate cancer. For comparison, two texture algorithms were implemented, namely the gray-level co-occurrence matrix (GLCM) and Gabor. Results: Using an institutional prostate lymph node dataset (42 positives, 84 negatives), the proposed framework achieved an accuracy of 76.19%, a sensitivity of 79.76%, and a specificity of 69.05%. Using GLCM features, the classification achieved an accuracy of 61.90%, a sensitivity of 74.07%, and a specificity of 42.86%. Using Gabor features, the classification achieved an accuracy of 65.08%, a sensitivity of 73.47%, and a specificity of 52.50%. Conclusions: Our results demonstrate that a hybrid approach, i.e., using a pre-trainined deep learning model for feature extraction, followed by a machine learning classifier, is a viable solution. This hybrid approach is especially useful in medical-imaging-based applications with small datasets.

Over the past decade, there has been a rapid increase in the incidence of inflammatory bowel disease. It has been suggested that multifactorial interactions of environmental factors, genetic factors, immune response and intestinal microbiota are involved in the pathogenesis of inflammatory bowel disease. It is widely recognized that the intestinal microbiota are essential for human metabolism, the immune system and pathogen resistance, and are integral to human health. Therefore, the dysbiosis of the microbiota is a critical step leading to intestinal mucosal damage and a key factor in the pathogenesis of inflammatory bowel disease. Regulating the microbiota through interventions such as enteral nutrition, fecal microbiota transplantation, and probiotic supplementation has the potential to prevent or even reverse intestinal dysbiosis, opening up new perspectives for the treatment of inflammatory bowel disease.