Metabolic reprogramming: a new option for the treatment of spinal cord injury.

Spinal cord injuries impose a notably economic burden on society, mainly because of the severe after-effects they cause. Despite the ongoing development of various therapies for spinal cord injuries, their effectiveness remains unsatisfactory. However, a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming. In this review, we explore the metabolic changes that occur during spinal cord injuries, their consequences, and the therapeutic tools available for metabolic reprogramming. Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling. However, spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism, lipid metabolism, and mitochondrial dysfunction. These metabolic disturbances lead to corresponding pathological changes, including the failure of axonal regeneration, the accumulation of scarring, and the activation of microglia. To rescue spinal cord injury at the metabolic level, potential metabolic reprogramming approaches have emerged, including replenishing metabolic substrates, reconstituting metabolic couplings, and targeting mitochondrial therapies to alter cell fate. The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury. To further advance the metabolic treatment of the spinal cord injury, future efforts should focus on a deeper understanding of neurometabolism, the development of more advanced metabolomics technologies, and the design of highly effective metabolic interventions.

Cluster headache: understandings of current knowledge and directions for whole process management.

Cluster headache (CH) is a common primary headache that severely impacts patients' quality of life, characterized by recurrent, severe, unilateral headaches often centered around the eyes, temples, or forehead. Distinguishing CH from other headache disorders is challenging, and its pathogenesis remains unclear. Notably, patients with CH often experience high levels of depression and suicidal tendencies, necessitating increased clinical attention. This comprehensive assessment combines various reports and the latest scientific literature to evaluate the current state of CH research. It covers epidemiology, population characteristics, predisposing factors, and treatment strategies. Additionally, we provide strategic insights into the holistic management of CH, which involves continuous, individualized care throughout the prevention, treatment, and rehabilitation stages. Recent advances in the field have revealed new insights into the pathophysiology of CH. While these findings are still evolving, they offer a more detailed understanding of the neurobiological mechanisms underlying this disorder. This growing body of knowledge, alongside ongoing research efforts, promises to lead to the development of more targeted and effective treatments in the future.

Fondaparinux Sodium for Anticoagulant Therapy After Primary Percutaneous Coronary Intervention: A Single-Center Randomized Trial in China.

ABSTRACT: In this study, we investigated the safety and efficacy of fondaparinux sodium in postpercutaneous coronary intervention (PCI) anticoagulation therapy for patients with ST-segment elevation myocardial infarction. There are a total of 200 patients with ST segment elevation myocardial infarction underwent PCI and anticoagulation therapy. They were randomly split into experimental (n = 108) and control groups (n = 92). The experimental group received postoperative fondaparinux sodium (2.5 mg q.d), while the control group received enoxaparin (4000 IU q12 h). We did not use a loading dose for enoxaparin. Bleeding incidence and major adverse cardiovascular/cerebrovascular events were monitored during hospitalization, and at 1, 3, and 6 months postsurgery. The primary end points, including bleeding, mortality, and myocardial infarction during hospitalization, were not significantly different between the 2 groups. For secondary end points, the incidence of combined end point events at 1 month, 3 months, and 6 months after surgery in the experimental group was lower than in the control group (P < 0.05). According to Cox regression analysis, the risk of bleeding in the experimental group was significantly lower than that in the control group [hazard ratios: 0.506, 95% confidence interval (CI): 0.284-0.900] (P = 0.020). The risk of mortality in the experimental group was significantly lower than in the control group (hazard ratio: 0.188, 95% CI: 0.040-0.889) (P = 0.035). In summary, perioperative use of fondaparinux sodium during PCI in patients with STEMI in this study was associated with a lower risk of bleeding and death compared with enoxaparin use in the absence of loading dose.

Evidence that beneficial microbial inoculation enhances heavy metal-contaminated soil remediation: Variations in plant endophyte communities.

Microbial remediation of heavy metal (HM)-contaminated soil is a sustainable approach; however, the impact of microbial inoculation on the internal environment of plants remains understudied. Thus, Enterobacter sp. FM-1 (Enterobacter sp.) and the hyperaccumulator Bidens pilosa L. (B. pilosa L.) were used to study these effects. Through analyses of plant physiological and biochemical characteristics, the endophytic microbial community composition, microbial co-occurrence networks and functional predictions, the potential mechanisms by which Enterobacter sp. benefits the phytoremediation of HM-contaminated soil by B. pilosa L. were elucidated. Inoculation with Enterobacter sp. promoted the growth of B. pilosa L. and influenced the endophytic microbial community diversity in B. pilosa L. Interactions among endophytes facilitated the formation of microbial networks, with endophytic fungi playing a more prominent role than endophytic bacteria as the level of HM contamination increased. Functional predictions via PICRUSt2 revealed that endophytic bacteria are involved primarily in processes related to carbohydrate metabolism, ABC transporters, and amino acid metabolism. In conclusion, this study provides evidence for the beneficial role of microbes in improving the plant endosphere environment.

Emerging roles of the C-to-U RNA editing in plant stress responses.

RNA editing is an important post-transcriptional event in all living cells. Within chloroplasts and mitochondria of higher plants, RNA editing involves the deamination of specific cytosine (C) residues in precursor RNAs to uracil (U). An increasing number of recent studies detail specificity of C-to-U RNA editing as an essential prerequisite for several plant stress-related responses. In this review, we summarize the current understanding of responses and functions of C-to-U RNA editing in plants under various stress conditions to provide theoretical reference for future research.

Decimeter-depth and polarization addressable color 3D meta-holography.

Fueled by the rapid advancement of nanofabrication, metasurface has provided unprecedented opportunities for 3D holography. Large depth 3D meta-holography not only greatly increases information storage capacity, but also enables distinguishing of the relative spatial relationship of 3D objects, which has important applications in fields like optical information storage and medical diagnosis. Although the methods based on Fresnel diffraction theory can reconstruct the real depth information of 3D objects, the maximum depth is only 2 mm. Here, we develop a 3D meta-holography based on angular spectrum diffraction theory to break through the depth limit. By developing the angular spectrum diffraction theory into meta-holography, the metasurface structure with independent polarization control is used to create a polarization multiplexing 3D meta-hologram. The fabricated amorphous silicon metasurface increases the depth range by 47.5 times and realizes 0.95 dm depth reconstruction for polarization independent and different color 3D meta-hologram in visible. Such polarization controlled large-depth color meta-holography is expected to open avenue for data storage, display, information security and virtual reality.

Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using 18F-FDG PET-CT parameters.

PURPOSE: The objective of this study is to assess the prognostic efficacy of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (ML) prognostic model for NPC patients based on these 18F-FDG PET/CT parameters and clinical variables. METHOD: A cohort of 678 patients diagnosed with NPC between 2016 and 2020 was analyzed in this study. The model was constructed using four advanced ML algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Least Absolute Shrinkage and Selection Operator (LASSO), and multifactor COX step-up regression. Statistical significance of the models was assessed using Kaplan-Meier (K-M) curves, with a significance level established at P < 0.05. The prognostic efficacy of the models was evaluated through the analysis of receiver operating characteristic (ROC) curves, with the area under the ROC curve (AUC) serving as a criterion for model selection. The decision curve analysis (DCA) and concordance index (C-index) were employed to assess the precision of the optimal model. RESULTS: Multivariate analysis revealed age, T stage, and metabolic tumor volume (MTV) for the primary nasopharyngeal tumor (MTVT) as significant independent prognostic factors for overall survival (OS) in NPC patients. Additionally, the LASSO model identified six key variables, including peak standardized uptake value (SUV-peak) for the primary nasopharyngeal tumor (SUV-peak(T)), MTVT, heterogeneity index for neck lymph nodes (HIN), age, pathological type, and T stage. Remarkably, the LASSO model demonstrated superior performance with a 5-year AUC of 0.849 compared to other models. Further assessment using the C-index and DCA confirmed the accuracy of the LASSO model. Subgroup analysis revealed notable risk factors, such as a high heterogeneity index (HI) for the primary nasopharyngeal tumor (HIT), MTV values for neck lymph nodes (MTVN), and HIN. CONCLUSIONS: We developed a novel prognostic machine learning model that integrates 18F-FDG PET-CT parameters and clinical characteristics, significantly enhancing prognosis prediction in NPC.

Pain, Function and Quality of Life in Temporomandibular Disorder Patients With Different Disc Positions.

BACKGROUND: Whether pain, jaw function and quality of life are correlated with disc positions is controversial, and similar studies evaluating disc positions by magnetic resonance imaging (MRI) are very limited. OBJECTIVE: This study evaluated the pain, mandibular function and quality of life of the temporomandibular disorders (TMDs) patients with different disc positions according to MRI, and the relationship among them. METHODS: Three hundred and thirty-five participants were included. Patients completed questionnaires included the Numeric Rating Scale (NRS), Jaw Functional Limitation Scale 8-item (JFLS-8), the Generalised Anxiety Disorder 7-item (GAD-7), Patient Health Questionnaire 9-item (PHQ-9) and Oral Health Impact Profile for TMD (OHIP-TMD). MRI was conducted to evaluate these diagnoses, resulting in the identification of three distinct categories: normal positioning (NP), disc displacement with reduction (DDwR) and disc displacement without reduction (DDwoR). RESULTS: Participants had the mean age of 28.55 ± 11.10 years (80.90% women). DDwR and DDwoR had a higher percentage of females compared with NP. Significant differences existed among patients in all questionnaires. The DDwoR group had significantly the highest pain, functional limitation and the worst quality of life. Moreover, they experienced the most difficulties in chewing tough foods, yawning, experiencing pain and psychological discomfort. Moreover, the multivariate regression showed that age, female gender, diagnosis as DDwoR, GAD-7 and PHQ-9 were significantly linked to higher functional limitation. Worse quality of life was associated with age, diagnosis as DDwoR, GAD-7 and PHQ-9. CONCLUSIONS: Among patients with different disc positions, DDwoR showed the highest pain, functional limitation and the worst quality of life. Also, NP showed a proportion of chronic pain. Physical pain, psychological discomfort and chewing tough food were regarded as the most impaired. Women who experience anxiety and depression tended to have a higher propotion of dysfunction and a lower quality of life.

Acupuncture Therapy on Dysphagia in Patients with Parkinson's Disease: A Randomized Controlled Study.

OBJECTIVE: To explore the effect of acupuncture therapy on dysphagia in patients with Parkinson's disease. METHODS: This randomized controlled study lasted 42 days and included 112 patients with Parkinson's disease and dysphagia. Participants were randomly assigned to the experimental and control groups (56 cases each group) using the completely randomized design, all under routine treatment. The experimental group was given acupuncture therapy. The primary outcome was Penetration-Aspiration Scale (PAS). The secondary outcomes were (1) Standardized Swallowing Assessment (SSA), and (2) nutritional status including body mass index (BMI), serum albumin, prealbumin, and hemoglobin. Adverse events were recorded as safety indicators. RESULTS: One participant quitted the study midway. There were no significant differences in baseline assessment (P>0.05). After treatment, both groups showed significant improvement in PAS, SSA and nutritional status except for BMI of the control group. There were significant differences between the two groups in the PAS for both paste and liquid, SSA (25.18±8.25 vs. 20.84±6.92), BMI (19.97±3.34 kg/m2vs. 21.26 ±2.38 kg/m2), serum albumin (35.16 ±5.29 g/L vs. 37.24 ±3.98 g/L), prealbumin (248.33 ±27.72 mg/L vs. 261.39 ±22.10 mg/L), hemoglobin (119.09±12.53 g/L vs. 126.67±13.97 g/L) (P<0.05). There were no severe adverse events during the study. CONCLUSION: The combination of routine treatment and acupuncture therapy can better improve dysphagia and nutritional status in patients with Parkinson's disease, than routine treatment solely. (registration No. CLINICALTRIAL: gov NCT06199323).

A 12-year retrospective analysis of non-operative management for paediatric duodenal hematomas caused by trauma at a single center.

BACKGROUND: Paediatric traumatic duodenal hematoma is a rare type of blunt abdominal injury for which treatment strategies are controversial. This study aimed to evaluate the application value of nonoperative management of paediatric duodenal hematoma caused by trauma. METHODS: A retrospective analysis was conducted on patients with duodenal hematoma with a confirmed history of abdominal trauma admitted to our hospital between January 2010 and December 2022. General patient information, including age, sex, cause of injury, clinical manifestations, and treatment outcomes, was recorded. RESULTS: A total of 11 cases were included in this study, with 6 males and 5 females. School-age children (≥6 years) accounted for 72.7% (8/11) of the cases. Bicycle handlebar injuries accounted for 63.6% (7/11) of cases. Among these cases, 5 (45.5%) were classified as American Association for the Surgery of Trauma grade I, while the remaining were classified as grade II. The median history time was 1 day (range: 2 h-12 days). All patients were successfully treated using non-operative methods. The median time to oral feeding after injury was 17 days (range: 9-32 days). Oral feeding was initiated within 2 weeks in 2 patients (18.2%), within 3 weeks in 6 patients (54.5%), and within 4 weeks in 10 patients (90.9%). CONCLUSION: Paediatric traumatic duodenal hematoma is more common in school-aged children, mainly due to bicycle handlebar injuries. Nonoperative treatment is proven to be safe and effective, with duodenal obstruction symptoms typically resolving within 4 weeks.

Noble metal-free plasmonic Cu/WO3-x@ZNC bi-functional composite for ciprofloxacin photocatalytic degradation and photothermal water evaporation via visible-infrared exposure.

Herein, coupling of noble metal-free plasmonic copper nanoparticles with tungsten suboxide and supporting on zeolite nanoclay (Cu/WO3-x@ZNC) composite will be introduced for bi-functional photocatalytic ciprofloxacin (CIP) degradation and water photothermal evaporation under visible/infrared (Vis/IR) exposure. Reduced band-gap of WO3-x via oxygen vacancies creation and localized surface plasmon resonance (LSPR) formation by Cu nanoparticles contributed significantly the extension and intensification of composite's photo-absorption range. Furthermore, small mesoporous structure of ZNC enhanced CIP adsorption and charge carriers separation where the reported photocatalytic efficiencies were 88.3 and 81.7% upon IR and Vis light exposure respectively. It was evidenced that plasmonic hot electrons (e-.s) and hydroxyl radicals (OH•-) performed the basic functions of the photocatalytic process. At the other side, oxygen vacancies existence, plasmonic effect, and confining thermal characteristics of WO3-x, Cu, and ZNC correspondingly induced water photothermal evaporation with efficiencies up to 97.5 and 72.8% under IR and Vis illumination respectively. This work introduces synthesis of a novel bi-functional photocatalytic-photothermal composite by metal sub-oxide and non-noble metal plasmonic coupling and supporting on naturally-derived carrier for water restoration under broad spectral exposure.

Automated Interstitial Lung Abnormality Probability Prediction at CT: A Stepwise Machine Learning Approach in the Boston Lung Cancer Study.

Background It is increasingly recognized that interstitial lung abnormalities (ILAs) detected at CT have potential clinical implications, but automated identification of ILAs has not yet been fully established. Purpose To develop and test automated ILA probability prediction models using machine learning techniques on CT images. Materials and Methods This secondary analysis of a retrospective study included CT scans from patients in the Boston Lung Cancer Study collected between February 2004 and June 2017. Visual assessment of ILAs by two radiologists and a pulmonologist served as the ground truth. Automated ILA probability prediction models were developed that used a stepwise approach involving section inference and case inference models. The section inference model produced an ILA probability for each CT section, and the case inference model integrated these probabilities to generate the case-level ILA probability. For indeterminate sections and cases, both two- and three-label methods were evaluated. For the case inference model, we tested three machine learning classifiers (support vector machine [SVM], random forest [RF], and convolutional neural network [CNN]). Receiver operating characteristic analysis was performed to calculate the area under the receiver operating characteristic curve (AUC). Results A total of 1382 CT scans (mean patient age, 67 years ± 11 [SD]; 759 women) were included. Of the 1382 CT scans, 104 (8%) were assessed as having ILA, 492 (36%) as indeterminate for ILA, and 786 (57%) as without ILA according to ground-truth labeling. The cohort was divided into a training set (n = 96; ILA, n = 48), a validation set (n = 24; ILA, n = 12), and a test set (n = 1262; ILA, n = 44). Among the models evaluated (two- and three-label section inference models; two- and three-label SVM, RF, and CNN case inference models), the model using the three-label method in the section inference model and the two-label method and RF in the case inference model achieved the highest AUC, at 0.87. Conclusion The model demonstrated substantial performance in estimating ILA probability, indicating its potential utility in clinical settings. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zagurovskaya in this issue.

Pogostemon cablin essential oil as feed additive promotes the repair of the rumen epithelial barrier in heat-stressed beef cattle.

Pogostemon cablin essential oil (PEO), extracted from P. cablin, has anti-oxidant, anti-inflammatory, and anti-stress properties, as well as the ability to improve gastrointestinal digestion. This study aims to evaluate the effects of PEO on the performance, rumen epithelial morphology, and barrier function in heat-stressed beef cattle. Thirty-six male Jingjiang cattle at 18 months old were randomly assigned into four groups and fed a diet containing PEO at 0 (control), 50, 100, or 150 mg/kg in the feed concentrate (n = 9). All experimental cattle were fed under high temperature and humidity in summer for 60 days. The results indicated that 50 mg/kg of PEO treatment enhanced the average daily gain of beef cattle compared with the control group (P = 0.032). All PEO treatments reduced the diamine oxidase activity (P = 0.004) and malondialdehyde content (P = 0.008) in serum. In addition, the content of 70 kDa heat shock protein in the 100 mg/kg group was increased, and the activity of glutathione peroxidase and total antioxidant capacity in both 100 mg/kg and 150 mg/kg groups were enhanced compared to the control group (P < 0.05). More importantly, PEO treatment with 50 mg/kg enhanced the mRNA relative expressions of occludin in ruminal epithelia but decreased the mRNA relative expressions of c-Jun N-terminal kinase, P38 mitogen-activated protein kinases, caspase-3, Beclin1 (P < 0.05), and extremely significant declined the mRNA relative expressions of extracellular regulated protein kinases and ubiquitin-binding protein in contrast to the control group (P < 0.01). These findings indicated that dietary PEO supplementation might be favorable to improve growth performance and repairing damaged rumen epithelium of heat-stressed cattle by down-regulating the mitogen-activated protein kinase signaling pathway.

Higher Platelet Count Mostly in Normal Range is Associated with First Episode of Peritonitis Risk in Incident Peritoneal Dialysis Patients.

BACKGROUND: Platelets play parts in infection and immune processes. However, the association between platelet count and the risk of peritoneal dialysis-associated peritonitis is unclear. METHODS: This was a retrospective, observational, single-center cohort study. A Cox regression analysis was used to evaluate the independent association of platelet count with the occurrence of first PD-associated peritonitis. Models were adjusted for gender, age, BMI, cardiovascular disease, diabetes mellitus, white blood cell count, neutrophil-lymphocyte ratio, hemoglobin level, albumin level, potassium level, and anti-platelet medication usage. RESULTS: A total of 2374 patients were enrolled in this study (59% men; mean age 47.40 ± 12.12). The average platelet count was 229.30±82.12 x 109/L. 467 (20%) patients suffered from PD-associated peritonitis at least once. In the multivariable model, the adjusted hazard ratios (HRs) for quartiles 2, 3 and 4 versus quartile 1 were 1.428 (95% CI 1.060-1.924, P=0.019), 1.663 (95% CI 1.240-2.229, P<0.001) and 1.843 (95% CI 1.363-2.492, P<0.001) with baseline data. A nonlinear relationship between platelet count and first PD-associated peritonitis was observed. Further, the association between platelet and first PD-associated peritonitis was significant in the patients with hypokalemia (P for interaction=0.040). CONCLUSION: In PD patients, elevated platelet counts were significantly associated with an increased risk of the first onset of PD-associated peritonitis.

Single-cell sequencing of the vermiform appendix during development identifies transcriptional relationships with appendicitis in preschool children.

BACKGROUND: The development of the human vermiform appendix at the cellular level, as well as its function, is not well understood. Appendicitis in preschool children, although uncommon, is associated with a high perforation rate and increased morbidity. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on the human appendix during fetal and pediatric stages as well as preschool-age inflammatory appendices. Transcriptional features of each cell compartment were discussed in the developing appendix. Cellular interactions and differentiation trajectories were also investigated. We compared scRNA-seq profiles from preschool appendicitis to those of matched healthy controls to reveal disease-associated changes. Bulk transcriptomic data, immunohistochemistry, and real-time quantitative PCR were used to validate the findings. RESULTS: Our analysis identified 76 cell types in total and described the cellular atlas of the developing appendix. We discovered the potential role of the BMP signaling pathway in appendiceal epithelium development and identified HOXC8 and PITX2 as the specific regulons of appendix goblet cells. Higher pericyte coverage, endothelial angiogenesis, and goblet mucus scores together with lower epithelial and endothelial tight junction scores were found in the preschool appendix, which possibly contribute to the clinical features of preschool appendicitis. Preschool appendicitis scRNA-seq profiles revealed that the interleukin-17 signaling pathway may participate in the inflammation process. CONCLUSIONS: Our study provides new insights into the development of the appendix and deepens the understanding of appendicitis in preschool children.

Pyridine-Catalyzed Chemoselective Four-Component Cascade Reaction of Aromatic Aldehydes, Malononitrile/Cyanoacetates, MBH Carbonates, and Alcohols.

An efficient pyridine-catalyzed chemoselective four-component cascade reaction of aromatic aldehydes, malononitrile/cyanoacetates, Morita-Baylis-Hillman (MBH) carbonates, and alcohols has been established. This one-pot reaction progressed in an unusual reaction with solvent participation via a Knoevenagel condensation/oxa-Michael addition/SN2' substitution sequence. This method allowed for facile access to an array of functionalized chain alkylbenzenes and dihydroquinolinones bearing one all-carbon quaternary center in moderate to excellent yields. It is worth noting that the configuration of the all-carbon quaternary center could be modulated by changing only the electron-withdrawing groups via a tandem reduction/cyclization reaction.

Naphthalimide-Modified Clusters for Red-Emitting Devices with High Color Purity.

Conventional fluorescent materials frequently exhibit narrow-band emissions with a small full width at half-maximum (fwhm) due to localized-state characteristics, but electroluminescence is less efficient owing to the utilization of only singlet excitons. In this work, taking advantage of naphthalimide (NAI)-acetylide derivatives with a rigid planar structure and localized transition characteristics, we elaborately designed two mononuclear Pt(II) complexes with weak double emissions of fluorescence and phosphorescence. Taking them as synthetic precursors, we prepared three PtAu2 heteronuclear clusters and successfully attained highly efficient narrow-band red phosphorescence with the fwhm below 30 nm. Both theoretical and experimental results suggest that the phosphorescence of PtAu2 clusters mainly originates from the naphthalimide-localized 3IL (intraligand) triplet state. Solution-processed organic light-emitting diodes (OLEDs) achieved highly efficient narrow-band red electroluminescence with an external quantum efficiency (EQE) of 16.7%. The CIE coordinates of the electroluminescence (0.69, 0.31) closely match the standard red emission for ultrahigh-definition display.

An explainable graph neural network approach for integrating multi-omics data with prior knowledge to identify biomarkers from interacting biological domains.

The rapid growth of multi-omics datasets, in addition to the wealth of existing biological prior knowledge, necessitates the development of effective methods for their integration. Such methods are essential for building predictive models and identifying disease-related molecular markers. We propose a framework for supervised integration of multi-omics data with biological priors represented as knowledge graphs. Our framework is based on the use of graph neural networks (GNNs) to model the relationships among features from high-dimensional 'omics data and set transformers to integrate low dimensional representations of 'omics features. Furthermore, our framework incorporates explainability methods to elucidate important biomarkers and extract interaction relationships between biological quantities of interest. We demonstrate the effectiveness of our approach by applying it to Alzheimer's disease (AD) multi-omics data from the ROSMAP cohort, showing that the integration of transcriptomics and proteomics data with AD biological domain network priors improves the prediction accuracy of AD status and highlights robust AD biomarkers.