Exploring the neuroprotective role of artesunate in mouse models of anti-NMDAR encephalitis: insights from molecular mechanisms and transmission electron microscopy.

BACKGROUND: The pathway involving PTEN-induced putative kinase 1 (PINK1) and PARKIN plays a crucial role in mitophagy, a process activated by artesunate (ART). We propose that patients with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis exhibit insufficient mitophagy, and ART enhances mitophagy via the PINK1/PARKIN pathway, thereby providing neuroprotection. METHODS: Adult female mice aged 8-10 weeks were selected to create a passive transfer model of anti-NMDAR encephalitis. We conducted behavioral tests on these mice within a set timeframe. Techniques such as immunohistochemistry, immunofluorescence, and western blotting were employed to assess markers including PINK1, PARKIN, LC3B, p62, caspase3, and cleaved caspase3. The TUNEL assay was utilized to detect neuronal apoptosis, while transmission electron microscopy (TEM) was used to examine mitochondrial autophagosomes. Primary hippocampal neurons were cultured, treated, and then analyzed through immunofluorescence for mtDNA, mtROS, TMRM. RESULTS: In comparison to the control group, mitophagy levels in the experimental group were not significantly altered, yet there was a notable increase in apoptotic neurons. Furthermore, markers indicative of mitochondrial leakage and damage were found to be elevated in the experimental group compared to the control group, but these markers showed improvement following ART treatment. ART was effective in activating the PINK1/PARKIN pathway, enhancing mitophagy, and diminishing neuronal apoptosis. Behavioral assessments revealed that ART ameliorated symptoms in mice with anti-NMDAR encephalitis in the passive transfer model (PTM). The knockdown of PINK1 led to a reduction in mitophagy levels, and subsequent ART intervention did not alleviate symptoms in the anti-NMDAR encephalitis PTM mice, indicating that ART's therapeutic efficacy is mediated through the activation of the PINK1/PARKIN pathway. CONCLUSIONS: At the onset of anti-NMDAR encephalitis, mitochondrial damage is observed; however, this damage is mitigated by the activation of mitophagy via the PINK1/PARKIN pathway. This regulatory feedback mechanism facilitates the removal of damaged mitochondria, prevents neuronal apoptosis, and consequently safeguards neural tissue. ART activates the PINK1/PARKIN pathway to enhance mitophagy, thereby exerting neuroprotective effects and may achieve therapeutic goals in treating anti-NMDAR encephalitis.

IRAK-M Plays A Role in the Pathology of Amyotrophic Lateral Sclerosis Through Suppressing the Activation of Microglia.

Microglial activation plays a crucial role in the disease progression in amyotrophic lateral sclerosis (ALS). Interleukin receptor-associated kinases-M (IRAK-M) is an important negative regulatory factor in the Toll-like receptor 4 (TLR4) pathway during microglia activation, and its mechanism in this process is still unclear. In the present study, we aimed to investigate the dynamic changes of IRAK-M and its protective effects for motor neurons in SOD1-G93A mouse model of ALS. qPCR (Real-time Quantitative PCR Detecting System) were used to examine the mRNA levels of IRAK-M in the spinal cord in both SOD1-G93A mice and their age-matched wild type (WT) littermates at 60, 100 and 140 days of age. We established an adeno-associated virus 9 (AAV9)-based platform by which IRAK-M was targeted mostly to microglial cells to investigate whether this approach could provide a protection in the SOD1-G93A mouse. Compared with age-matched WT mice, IRAK-M mRNA level was elevated at 100 and 140 days in the anterior horn region of spinal cords in the SOD1-G93A mouse. AAV9-IRAK-M treated SOD1-G93A mice showed reduction of IL-1ß mRNA levels and significant improvements in the numbers of spinal motor neurons in spinal cord. Mice also showed previously reduction of muscle atrophy. Our data revealed the dynamic changes of IRAK-M during ALS pathological progression and demonstrated that an AAV9-IRAK-M delivery was an effective and translatable therapeutic approach for ALS. These findings may help identify potential molecular targets for ALS therapy.

AI-assisted compressed sensing and parallel imaging sequences for MRI of patients with nasopharyngeal carcinoma: comparison of their capabilities in terms of examination time and image quality.

OBJECTIVE: To compare examination time and image quality between artificial intelligence (AI)-assisted compressed sensing (ACS) technique and parallel imaging (PI) technique in MRI of patients with nasopharyngeal carcinoma (NPC). METHODS: Sixty-six patients with pathologically confirmed NPC underwent nasopharynx and neck examination using a 3.0-T MRI system. Transverse T2-weighted fast spin-echo (FSE) sequence, transverse T1-weighted FSE sequence, post-contrast transverse T1-weighted FSE sequence, and post-contrast coronal T1-weighted FSE were obtained by both ACS and PI techniques, respectively. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and duration of scanning of both sets of images analyzed by ACS and PI techniques were compared. The images from the ACS and PI techniques were scored for lesion detection, margin sharpness of lesions, artifacts, and overall image quality using the 5-point Likert scale. RESULTS: The examination time with ACS technique was significantly shorter than that with PI technique (p < 0.0001). The comparison of SNR and CNR showed that ACS technique was significantly superior with PI technique (p < 0.005). Qualitative image analysis showed that the scores of lesion detection, margin sharpness of lesions, artifacts, and overall image quality were higher in the ACS sequences than those in the PI sequences (p < 0.0001). Inter-observer agreement was evaluated for all qualitative indicators for each method, in which the results showed satisfactory-to-excellent agreement (p < 0.0001). CONCLUSION: Compared with the PI technique, the ACS technique for MR examination of NPC can not only shorten scanning time but also improve image quality. CLINICAL RELEVANCE STATEMENT: The artificial intelligence (AI)-assisted compressed sensing (ACS) technique shortens examination time for patients with nasopharyngeal carcinoma, while improving the image quality and examination success rate, which will benefit more patients. KEY POINTS: • Compared with the parallel imaging (PI) technique, the artificial intelligence (AI)-assisted compressed sensing (ACS) technique not only reduced examination time, but also improved image quality. • Artificial intelligence (AI)-assisted compressed sensing (ACS) pulls the state-of-the-art deep learning technique into the reconstruction procedure and helps find an optimal balance of imaging speed and image quality.

Short-term prognosis for hepatocellular carcinoma patients with lung metastasis: A retrospective cohort study based on the SEER database.

Our study aimed to develop a prediction model to predict the short-term mortality of hepatocellular carcinoma (HCC) patients with lung metastasis. The retrospective data of HCC patients with lung metastasis was from the Surveillance, Epidemiology, and End Results registration database between 2010 and 2015. 1905 patients were randomly divided into training set (n = 1333) and validation set (n = 572). There were 1092 patients extracted from the Surveillance, Epidemiology, and End Results database 2015 to 2019 as the validation set. The variable importance was calculated to screen predictors. The constructed prediction models of logistic regression, random forest, broad learning system, deep neural network, support vector machine, and naïve Bayes were compared through the predictive performance. The mortality of HCC patients with lung metastasis was 51.65% within 1 month. The screened prognostic factors (age, N stage, T stage, tumor size, surgery, grade, radiation, and chemotherapy) and gender were used to construct prediction models. The area under curve (0.853 vs. 0.771) of random forest model was more optimized than that of logistic regression model in the training set. But, there were no significant differences in testing and validation sets between random forest and logistic regression models. The value of area under curve in the logistic regression model was significantly higher than that of the broad learning system model (0.763 vs. 0.745), support vector machine model (0.763 vs. 0.689) in the validation set, and higher than that of the naïve Bayes model (0.775 vs. 0.744) in the testing model. We further chose the logistic regression prediction model and built the prognostic nomogram. We have developed a prediction model for predicting short-term mortality with 9 easily acquired predictors of HCC patients with lung metastasis, which performed well in the internal and external validation. It could assist clinicians to adjust treatment strategies in time to improve the prognosis.

Characteristics of immune cells and cytokines in patients with coronavirus disease 2019 in Guangzhou, China.

To discover immune factors that can predict the progression of COVID-19, we evaluated circulating immune cells and plasma cytokines in COVID-19 patients. We found that T cells, including CD4+ T cells and CD8+ T cells, were significantly decreased in severe COVID-19 symptoms but not in mild symptoms, in comparison with healthy people. T cells remained at a low level after recovery from severe COVID-19. CD4+CD25+CD127low Treg-enriched cells were significantly increased in either mild or severe COVID-19 patients, regardless of recovery or not. Moreover, in either mild or severe COVID-19 patients, Treg-enriched cells up-regulated CD25 and down-regulated CD127. After recovery, CD25 was partially down-regulated but still higher than the normal level, while CD127 returned to the normal level in mild patients but not severe patients. B cells were decreased in mild patients and further decreased in severe patients, and remained low after recovery. NK cells were decreased only in severe COVID-19, with a tendency to return to the normal level after recovery. Plasma IL-6 and IL-10 were both elevated in severe patients but not in mild patients. After recovery, IL-6 remained higher than its normal level, while IL-10 returned to the normal level. Binary logistic regression analysis indicated that CD4+ T cells, B cells, IL-6, and IL-10 were significantly associated with COVID-19 severity. Therefore, these parameters are indicators of COVID-19 severity. Dynamic monitoring of these parameters would benefit therapy planning and prognosis evaluation.

Scalable Majorana vortex modes in iron-based superconductors.

The iron-based superconductor FeTe x Se1-x is one of the material candidates hosting Majorana vortex modes residing in the vortex cores. It has been observed by recent scanning tunneling spectroscopy measurement that the fraction of vortex cores having zero-bias peaks decreases with increasing magnetic field on the surface of FeTe x Se1-x . The hybridization of two Majorana vortex modes cannot simply explain this phenomenon. We construct a three-dimensional tight-binding model simulating the physics of over a hundred Majorana vortex modes in FeTe x Se1-x . Our simulation shows that the Majorana hybridization and disordered vortex distribution can explain the decreasing fraction of the zero-bias peaks observed in the experiment; the statistics of the energy peaks off zero energy in our Majorana simulation are in agreement with the experiment. These agreements lead to an important indication of scalable Majorana vortex modes in FeTe x Se1-x . Thus, FeTe x Se1-x can be one promising platform having scalable Majorana qubits for quantum computing.

Differentiation between nasopharyngeal carcinoma and lymphoma at the primary site using whole-tumor histogram analysis of apparent diffusion coefficient maps.

INTRODUCTION: To determine the value of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating nasopharyngeal carcinoma (NPC) from lymphoma (NPL) at the primary site METHOD AND MATERIALS: One hundred forty-seven patients with nasopharyngeal tumors (89 NPCs and 38 NPLs) who had undergone magnetic resonance imaging (MRI) and diffusion-weighted imaging were retrospectively analyzed. ADC histogram-derived parameters were compared between the NPC and NPL groups by using the Mann-Whitney U test. Receiver operating characteristic (ROC) curves of the histogram parameters were plotted for diagnostic accuracy. Sensitivity and specificity were calculated for each histogram parameter. RESULTS: In whole-tumor histogram analysis, the mean, median, and 10th and 25th percentiles of ADC were all significantly higher in NPC than NPL (P = 0.045, P = 0.035, P = 0.005, and P = 0.016, respectively). Uniformity was significantly higher in NPC than NPL (P = 0.001). Skewness was significantly lower in NPC than NPL (P = 0.039). For the conventional ROI-based method, ADCmean values were significantly higher in NPC than in NPL (P = 0.009). The ROC curve analysis showed that uniformity yielded the largest area under the curve (AUC = 0.768) for differentiating NPC from NPL among all ADC metrics, followed by 10th percentiles of ADC (AUC = 0.725); sensitivity and specificity were 76.5% and 71.4%, respectively. CONCLUSION: Whole-tumor histogram analysis of ADC maps could be helpful for differentiating NPC from NPL.