Military Medical Research最新文献

Background: Acute liver injury (ALI) requires rapid hepatic regeneration to avert fatal liver failure. As key mechanisms, systemic metabolic remodeling and inter-organ crosstalk are critical for this regenerative process. Skeletal muscle, as a major metabolic organ system, undergoes significant remodeling during ALI. However, its specific regulatory contributions remain largely uncharacterized.

Methods: Partial (2/3) hepatectomy and acetaminophen were used to induce ALI in male mice. RNA-sequencing (RNA-seq), assay for transposase-accessible chromatin by sequencing (ATAC-seq), chromatin immunoprecipitation, luciferase assay, Western blotting, TUNEL assay, immunohistochemistry, and phase separation assays were performed to reveal the transcriptional axis involved. Serum fibroblast growth factor binding protein 1 (FGFBP1) protein levels in ALI patients were assessed via enzyme-linked immunosorbent assay.

Results: Integrated analysis of RNA-seq and ATAC-seq following ALI identifies glucocorticoid (GC) signaling-mediated regulation of fibroblast growth factor 6 (FGF6) in skeletal muscle metabolism. Muscle-specific knockdown of GC receptor (GR) exacerbates ALI and suppresses liver regeneration. Fgf6-knockout mice exhibited improved ALI and enhanced liver regeneration, with intramuscular injection of FGF6-neutralizing antibody rescuing the detrimental effects induced by GR knockdown. Further analysis of the FGF6 downstream target revealed that FGF6 regulates FGFBP1 expression through extracellular signal regulated kinase-activating transcription factor 3 signaling. Moreover, FGF6 regulates the heparin-dependent release kinetics of FGFBP1 by perturbing its liquid-liquid phase separation (LLPS)-driven condensate dynamics at the plasma membrane. Circulating FGFBP1 subsequently interacts with hepatic fibroblast growth factor 5 (FGF5) through LLPS mechanisms to regulate liver regeneration.

Conclusion: Our results demonstrate a molecular mechanism by which muscle-liver crosstalk can initiate and sustain liver regeneration via the FGF6-FGFBP1/FGF5 axis, providing a potential therapeutic target and treatment strategy for ALI.

Background: Epilepsy is a neurological disorder characterized by recurrent seizures due to hyperexcitable neuronal network activity. The manifestations vary widely, ranging from subtle sensory disturbances to profound alterations of consciousness, depending on which brain regions are affected and their underlying etiology. Exploring the biophysical mechanisms of epileptic seizures holds significant for predicting and controlling the disease.

Methods: We analyzed 45 spontaneous seizures recorded from 24 patients with focal epilepsy, as well as stimulation-induced seizures from 2 additional patients. A second-order Butterworth low-pass filter isolated the slow-varying direct current (Sv DC) component (0.01-0.5 Hz), a frequency range often overlooked in electroencephalography. The energy ratio of the Sv DC component was calculated by dividing its total energy by the total signal energy during seizures and over a 1-hour period including the seizure, enabling comparison between ictal and interictal states.

Results: The Sv DC component exhibited spatially dynamic changes during both ictal and interictal periods and showed a moderate correlation with high-frequency activity. Moreover, it accounted for a high energy proportion in both periods, with seizure data showing that 80.82% of leads had ≥ 60% Sv DC energy. Notably, interictal Sv DC fluctuations were more pronounced in electrodes located within the epileptogenic zone, suggesting its potential as a marker for epileptogenic localization. Furthermore, the temporal variability of the Sv DC signal, reflected in its dispersion, demonstrates potential as an early indicator of seizure development.

Conclusions: The Sv DC component may reflect local voltage differences likely linked to ion channel activity, potentially contributing to seizure initiation. Combined analysis of Sv DC with low- and high-frequency components offers a comprehensive framework for understanding epileptic networks and guiding diagnosis and therapy.

Background: Multiparametric magnetic resonance imaging (mpMRI) has significantly advanced prostate cancer (PCa) detection, yet decisions on invasive biopsy with moderate prostate imaging reporting and data system (PI-RADS) scores remain ambiguous.

Methods: To explore the decision-making capacity of Generative Pretrained Transformer-4 (GPT-4) for automated prostate biopsy recommendations, we included 2299 individuals who underwent prostate biopsy from 2018 to 2023 in 3 large medical centers, with available mpMRI before biopsy and documented clinical-histopathological records. GPT-4 generated structured reports with given prompts. The performance of GPT-4 was quantified using confusion matrices, and sensitivity, specificity, as well as area under the curve were calculated. Multiple artificial evaluation procedures were conducted. Wilcoxon's rank sum test, Fisher's exact test, and Kruskal-Wallis tests were used for comparisons.

Results: Utilizing the largest sample size in the Chinese population, patients with moderate PI-RADS scores (scores 3 and 4) accounted for 39.7% (912/2299), defined as the subset-of-interest (SOI). The detection rates of clinically significant PCa corresponding to PI-RADS scores 2-5 were 9.4, 27.3, 49.2, and 80.1%, respectively. Nearly 47.5% (433/912) of SOI patients were histopathologically proven to have undergone unnecessary prostate biopsies. With the assistance of GPT-4, 20.8% (190/912) of the SOI population could avoid unnecessary biopsies, and it performed even better [28.8% (118/410)] in the most heterogeneous subgroup of PI-RADS score 3. More than 90.0% of GPT-4 -generated reports were comprehensive and easy to understand, but less satisfied with the accuracy (82.8%). GPT-4 also demonstrated cognitive potential for handling complex problems. Additionally, the Chain of Thought method enabled us to better understand the decision-making logic behind GPT-4. Eventually, we developed a ProstAIGuide platform to facilitate accessibility for both doctors and patients.

Conclusions: This multi-center study highlights the clinical utility of GPT-4 for prostate biopsy decision-making and advances our understanding of the latest artificial intelligence implementation in various medical scenarios.

γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric disorders, particularly in regulating executive and cognitive functions. This review explores the latest neuromodulation techniques, focusing on the critical role of γ oscillations in various brain disorders. Direct γ neuromodulation induces γ-frequency oscillations to synchronize disrupted brain networks, while indirect methods influence γ oscillations by modulating cortical excitability. We investigate how monitoring dynamic features of γ oscillations allows for detailed evaluations of neuromodulation effectiveness. By targeting γ oscillatory patterns and restoring healthy cross-frequency coupling, interventions may alleviate cognitive and behavioral symptoms linked to disrupted communication. This review examines clinical applications of γ neuromodulations, including enhancing cognitive function through 40 Hz multisensory stimulation in Alzheimer's disease, improving motor function in Parkinson's disease, controlling seizures in epilepsy, and modulating emotional dysfunctions in depression. Additionally, these neuromodulation strategies aim to regulate excitatory-inhibitory imbalances and restore γ synchrony across neurological and psychiatric disorders. The review highlights the potential of γ oscillations as biomarkers to boost restorative results in clinical applications of neuromodulation. Future studies might focus on integrating multimodal personalized protocols, artificial intelligence (AI) driven frameworks for neural decoding, and global multicenter collaborations to standardize and scale precision treatments across diverse disorders.

Background: More efficacious, noninvasive screening methods are needed for advanced colorectal neoplasia. miR-92a is a reliable and reproducible biomarker for early colorectal cancer detection in stool samples. We compared the diagnostic efficacies of miR-92a, immunochemical fecal occult blood testing (FIT), and their combination (FIT + miR-92a) in a prospective multicenter screening trial.

Methods: Overall, 16,240 participants aged 30-75 years were enrolled between April 1, 2021, and December 31, 2023. A total of 15,586 participants returned samples available for both FIT and miR-92a tests. All those with positive, and a random selection of those with negative screening tests were recommended to undergo colonoscopy. Follow-ups were performed until participants completed the colonoscopic examination. A total of 1401 screen-positive and 2079 randomly selected screen-negative individuals completed colonoscopies. Primary outcomes included sensitivity, number needed to screen (NNS), Youden index and receiver operating characteristic area under the curve (AUC) for advanced adenomas and colorectal cancer [advanced neoplasia (AN)] for each screening modality in the diagnostic performance analysis.

Results: Colonoscopy was performed in 3480 individuals. The colonoscopy compliance rate was 47.8% for screen-positive individuals. The sensitivity of miR-92a versus FIT for AN was 70.9% versus 54.3% (P < 0.001), NNS was 24.7 versus 32.2 (P = 0.001), Youden index was 47.9% versus 35.0% (P < 0.001), AUC was 0.74 versus 0.67 (P = 0.010). FIT + miR-92a had a sensitivity of 85.4%, an NNS of 20.5, a Youden index of 47.9% and an AUC of 0.74 for AN.

Conclusions: For AN screening, miR-92a demonstrated better sensitivity, NNS, Youden index and AUC as compared with FIT. Compared with FIT, using miR-92a appears to be more efficient for population-based screening programs. Screening sensitivity for AN can be further enhanced if conditionally used in combination with FIT.

Trial registration: Chinese Clinical Trial Registration Number: ChiCTR2200065415.

Background: The prevalence of circadian misalignment, particularly social jetlag (SJL), contributes significantly to the epidemic of metabolic disorders. However, the precise impact of SJL on the liver has remained poorly elucidated.

Methods: The rhythmicity of circulating prolactin (PRL) was evaluated in subjects with SJL and mice under SJL. The causative mechanism of SJL on fatty liver was explored using jetlag model in wild-type and Prl^-/- mice. Luciferase reporter assay, electrophoretic mobility shift assay, and chromatin immunoprecipitation analysis were used to study the transcriptional mechanism of retinoic acid receptor-related orphan receptor α on PRL. RNA-seq on human and mice liver as well as circadian analysis were used to study the mechanism of SJL-associated desynchronized PRL on hepatic lipid metabolism. The therapeutic effect of PRL intervention on SJL-induced mice at different time points was compared.

Results: SJL increases the risk of metabolic dysfunction-associated steatotic liver disease (MASLD), mediated by the disruption of the rhythmicity of serum PRL. In particular, SJL inhibits the rhythmic transcription of PRL in the pituitary, leading to desynchronized PRL levels in circulation. Under jetlag conditions, the rhythmicity of the hepatic PRL signaling pathway was significantly dampened, which resulted in increased lipogenesis via inhibited hepatic mitogen-activated protein kinase/cyclin D1 expressions. Notably, PRL treatment at PRL nadir in jetlagged mice decreased hepatic lipid content and liver injury markers to a greater extent compared with conventional PRL administration.

Conclusions: Reprogrammed hepatic PRL signaling pathway with concomitant dysregulated lipid metabolism homeostasis was the causative mechanism of fatty liver under SJL, which was mediated through derailed serum PRL rhythm. Restoration of PRL rhythm could effectively alleviate SJL-induced fatty liver, providing new insight into treating MASLD.

Background: China accounts for one-quarter of the world's diabetes population, with significant subnational disparities. However, none of the available data have provided comprehensive estimates and projections at both regional and national levels in diabetes prevention and management. This study aimed to explore the temporal trends and geographical variations in the prevalence and non-fatal burden of diabetes by age and sex across China from 2005 to 2023, and to forecast diabetes prevalence through 2050.

Methods: We conducted a population-based study based on the nationally representative surveys, and literature reviews. Using the DisMod-MR model and Chinese-specific disease disability weights, we estimated the non-fatal burdens of diabetes, including prevalence and years lived with disability (YLDs), across sexes, age groups, and locations. The temporal trend change was measured as the average annual percent change. The effect of the Human Development Index on burdens was assessed by applying Spearman's rank correlation analysis. We further projected diabetes prevalence to 2050 under two scenarios, the natural trend and the effective intervention on body mass index (BMI).

Results: In 2023, an estimated 233 million individuals in China were living with diabetes. Compared to 2005, the age-standardized rate (ASR) of prevalence has increased by nearly 50%, from 7.53% (95% CI 7.00-8.10%) to 13.7% (95% CI 12.6-14.8%) in 2023. The ASR of YLDs was estimated at 19.1 per 1000 population (95% CI 18.6-19.5) in 2023, compared to 10.5 per 1000 population in 2005. The ASR of prevalence and YLDs was consistently higher in males than in females. The provinces with the highest diabetes prevalence and disease burden were Beijing, Tianjin, and Shanghai. Our forecast results suggest that if existing trends continue, the prevalence of obesity will reach 29.1% (95% CI 22.2-38.2%) nationally by 2050, with some provinces in the northern region observing a prevalence of over 40%. Conversely, if effective obesity interventions were implemented, the growth in diabetes prevalence could potentially be suppressed by nearly 50%.

Conclusions: The health burden and economic cost associated with diabetes are profound. There is an urgent need to scale up preventive efforts and improve population awareness to enhance disease management and achieve optimal treatment outcomes.

The treatment of chronic wounds presents significant challenges due to the necessity of accelerating healing within complex microenvironments characterized by persistent inflammation and biochemical imbalances. Factors such as bacterial infections, hyperglycemia, and oxidative stress disrupt cellular functions and impair angiogenesis, substantially delaying wound repair. Nanozymes, which are engineered nanoscale materials with enzyme-like activities, offer distinct advantages over conventional enzymes and traditional nanomaterials, making them promising candidates for chronic wound treatment. To enhance their clinical potential, nanozyme-based catalytic systems are currently being optimized through formulation advancements and preclinical studies assessing their biocompatibility, anti-oxidant activity, antibacterial efficacy, and tissue repair capabilities, ensuring their safety and clinical applicability. When integrated into multifunctional wound dressings, nanozymes modulate reactive oxygen species levels, promote tissue regeneration, and simultaneously combat infections and oxidative damage, extending beyond conventional enzyme-like catalysis in chronic wound treatment. The customizable architectures of nanozymes enable precise therapeutic applications, enhancing their effectiveness in managing complex wound conditions. This review provides a comprehensive analysis of the incorporation of nanozymes into wound dressings, detailing fabrication methods and emphasizing their transformative potential in chronic wound management. By identifying and addressing key limitations, we introduce strategic advancements to drive the development of nanozyme-driven dressings, paving the way for next-generation chronic wound treatments.