Breast cancer therapy: from the perspective of glucose metabolism and glycosylation.

Breast cancer is a leading cause of mortality and the most prevalent form of malignant tumor among women worldwide. Breast cancer cells exhibit an elevated glycolysis and altered glucose metabolism. Moreover, these cells display abnormal glycosylation patterns, influencing invasion, proliferation, metastasis, and drug resistance. Consequently, targeting glycolysis and mitigating abnormal glycosylation represent key therapeutic strategies for breast cancer. This review underscores the importance of protein glycosylation and glucose metabolism alterations in breast cancer. The current research efforts in developing effective interventions targeting glycolysis and glycosylation are further discussed.

Liability, risks, and recommendations for ultrasound use in the diagnosis of obstetrics diseases.

This literature review will summarize the liability issues, risks, and ultrasound recommendations for diagnosing obstetrics diseases. One liability issue is related to misdiagnosis or failure to detect abnormalities during an ultrasound examination. Ultrasound images can be subjective interpretations, and errors may occur due to factors such as operator skill, equipment limitations, or fetal positioning. Another liability concern is related to the potential adverse effects of ultrasound exposure on both the mother and fetus. While extensive research has shown that diagnostic ultrasound is generally safe when used appropriately, there are still uncertainties regarding long-term effects. Some studies suggest a possible association between prolonged or excessive exposure to ultrasound waves and adverse outcomes such as low birth weight, developmental delays, or hearing impairment. Additionally, obtaining informed consent from patients is crucial in mitigating liability risks. Patients should be informed about the purpose of the ultrasound examination, its benefits, limitations, potential risks (even if minimal), and any alternative diagnostic options available. This ensures that patients know the procedure and can make informed decisions about their healthcare. Proper documentation helps establish a clear record of the care provided and can serve as evidence in any legal disputes.

Circ_0002476 regulates cell growth, invasion, and mtDNA damage in non-small cell lung cancer by targeting miR-1182/TFAM axis.

BACKGROUND: Many circular RNAs (circRNAs) have been identified as potential targets for cancer therapy. However, the role of circ_0002476 in non-small cell lung cancer (NSCLC) progression has not been explored. METHODS: The expression levels of circ_0002476, microRNA (miR)-1182, and mitochondrial transcription factor A (TFAM) were detected by quantitative real-time polymerase chain reaction. Cell functions were measured by cell counting kit 8 assay, EdU assay, colony formation assay, flow cytometry and transwell assay. Mitochondrial DNA (mtDNA) damage was assessed by measuring mtDNA copy number and transcript levels of ND1 and ATP6. Protein expression was examined by western blot. The interaction between miR-1182 and circ_0002476 or TFAM was detected by dual-luciferase reporter assay and RNA pull-down assay. Animal experiments were performed to explore circ_0002476 role in vivo. Exosomes (Exs) were extracted and identified by transmission electron microscopy and nanoparticle tracking analysis. RESULTS: Circ_0002476 was overexpressed in NSCLC tissues and cells. Circ_0002476 knockdown suppressed NSCLC cell proliferation and invasion, while promoted apoptosis and mtDNA damage. Circ_0002476 could sponge miR-1182, and miR-1182 inhibitor reversed the influence induced by circ_0002476 knockdown. Moreover, TFAM was targeted by miR-1182, and miR-1182 hindered NSCLC cell progression by regulating TFAM. Additionally, circ_0002476 silencing could reduce NSCLC tumor growth by miR-1182/TFAM. Further analyzed showed that Exs were involved in the transport of circ_0002476 between cells. CONCLUSION: Taken together, our findings suggested that circ_0002476 might be a potential molecular target for NSCLC treatment.

Gut metagenomic characteristics of ADHD reveal low Bacteroides ovatus-associated host cognitive impairment.

Attention-deficit/hyperactivity disorder (ADHD) is a highly heterogeneous psychiatric disorder that can have three phenotypical presentations: inattentive (I-ADHD), hyperactive-impulsive (HI-ADHD), and combined (C-ADHD). Environmental factors correlated with the gut microbiota community have been implicated in the development of ADHD. However, whether different ADHD symptomatic presentations are associated with distinct microbiota compositions and whether patients could benefit from the correction of aberrant bacterial colonization are still largely unclear. We carried out metagenomic shotgun analysis with 207 human fecal samples to characterize the gut microbial profiles of patients with ADHD grouped according to their phenotypical presentation. Then, we transplanted the candidate low-abundance bacteria identified in patient subgroups into ADHD rats and evaluated ADHD-associated behaviors and neuronal activation in these rats. Patients with C-ADHD had a different gut microbial composition from that of healthy controls (HCs) (p = .02), but not from that of I-ADHD patients. Eight species became progressively attenuated or enriched when comparing the compositions of HCs to those of I-ADHD and C-ADHD; in particular, the abundance of Bacteroides ovatus was depleted in patients with C-ADHD. In turn, Bacteroides ovatus supplementation ameliorated spatial working memory deficits and reversed θ electroencephalogram rhythm alterations in ADHD rats. In addition, Bacteroides ovatus induced enhanced neuronal activation in the hippocampal CA1 subregion. These findings indicate that gut microbial characteristics that are unique to patients with C-ADHD may be masked when considering a more heterogeneous group of patients. We link the gut microbiota to brain function in an ADHD animal model, suggesting the relevance of testing a potential bacteria-based intervention for some aspects of ADHD.

Structural and Functional Disruption of Salience Network in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment.

Salience network (SN), playing a vital role in advanced cognitive function, is regarded to be impaired in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The purpose of the study was to explore the importance of structural and functional features of SN in the diagnosis of SCD and aMCI. Structural and resting-state functional magnetic resonance imaging were collected from SCD, aMCI, and healthy control (HC). Cortex thickness, gray matter (GM) volume, spontaneous brain activity, functional connectivity (FC) within SN, and its relationship with cognitive function were analyzed. Moreover, the receiver operating characteristic analysis was performed to assess diagnostic efficacy of altered indictors for SCD and aMCI. Compared to HC, both SCD and aMCI showed decreased GM volume, decreased spontaneous brain activity, and increased FC within SN, while aMCI showed additional decreased cortex thickness. Furthermore, the altered FC in SCD and aMCI was significantly correlated with cognitive function. Particularly, the best-fitting classification models of SCD and aMCI were based on the combined multiple indicators. In conclusion, structure and function of SN were disrupted in SCD and aMCI, which involved in cognitive decline. The combined multiple indicators of SN provided powerful biomarkers for the diagnosis of SCD and aMCI.

Altered Insular Subregional Connectivity Associated With Cognitions for Distinguishing the Spectrum of Pre-clinical Alzheimer's Disease.

Background: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are regarded as part of the pre-clinical Alzheimer's disease (AD) spectrum. The insular subregional networks are thought to have diverse intrinsic connectivity patterns that are involved in cognitive and emotional processing. We set out to investigate convergent and divergent altered connectivity patterns of the insular subregions across the spectrum of pre-clinical AD and evaluated how well these patterns can differentiate the pre-clinical AD spectrum. Method: Functional connectivity (FC) analyses in insular subnetworks were carried out among 38 patients with SCD, 56 patients with aMCI, and 55 normal controls (CNs). Logistic regression analyses were used to construct models for aMCI and CN, as well as SCD and CN classification. Finally, we conducted correlation analyses to measure the relationship between FCs of altered insular subnetworks and cognition. Results: Patients with SCD presented with reduced FC in the bilateral cerebellum posterior lobe and increased FC in the medial frontal gyrus and the middle temporal gyrus. On the other hand, patients with aMCI largely presented with decreased FC in the bilateral inferior parietal lobule, the cerebellum posterior lobe, and the anterior cingulate cortex, as well as increased FC in the medial and inferior frontal gyrus, and the middle and superior temporal gyrus. Logistic regression analyses indicated that a model composed of FCs among altered insular subnetworks in patients with SCD was able to appropriately classify 83.9% of patients with SCD and CN, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.876, 81.6% sensitivity, and 81.8% specificity. A model consisting of altered insular subnetwork FCs in patients with aMCI was able to appropriately classify 86.5% of the patients with aMCI and CNs, with an AUC of 0.887, 80.4% sensitivity, and 83.6% specificity. Furthermore, some of the FCs among altered insular subnetworks were significantly correlated with episodic memory and executive function. Conclusions: Patients with SCD and aMCI are likely to share similar convergent and divergent altered intrinsic FC patterns of insular subnetworks as the pre-clinical AD spectrum, and presented with abnormalities among subnetworks. Based on these abnormalities, individuals can be correctly differentiated in the pre-clinical AD spectrum. These results suggest that alterations in insular subnetworks can be utilized as a potential biomarker to aid in conducting a clinical diagnosis of the spectrum of pre-clinical AD.

Disrupted Patterns of Rich-Club and Diverse-Club Organizations in Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment.

BACKGROUND: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) were considered to be a continuum of Alzheimer's disease (AD) spectrum. The abnormal topological architecture and rich-club organization in the brain functional network can reveal the pathology of the AD spectrum. However, few studies have explored the disrupted patterns of diverse club organizations and the combination of rich- and diverse-club organizations in SCD and aMCI. METHODS: We collected resting-state functional magnetic resonance imaging data of 19 SCDs, 29 aMCIs, and 28 healthy controls (HCs) from the Alzheimer's Disease Neuroimaging Initiative. Graph theory analysis was used to analyze the network metrics and rich- and diverse-club organizations simultaneously. RESULTS: Compared with HC, the aMCI group showed altered small-world and network efficiency, whereas the SCD group remained relatively stable. The aMCI group showed reduced rich-club connectivity compared with the HC. In addition, the aMCI group showed significantly increased feeder connectivity and decreased local connectivity of the diverse club compared with the SCD group. The overlapping nodes of the rich club and diverse club showed a significant difference in nodal efficiency and shortest path length (L p) between groups. Notably, the L p values of overlapping nodes in the SCD and aMCI groups were significantly associated with episodic memory. CONCLUSION: The present study demonstrates that the network properties of SCD and aMCI have varying degrees of damage. The combination of the rich club and the diverse club can provide a novel insight into the pathological mechanism of the AD spectrum. The altered patterns in overlapping nodes might be potential biomarkers in the diagnosis of the AD spectrum.