Fibroblast growth factor 5 protects against spinal cord injury through activating AMPK pathway.

Excessive productions of inflammatory cytokines and free radicals are involved in spinal cord injury (SCI). Fibroblast growth factor 5 (FGF5) is associated with inflammatory response and oxidative damage, and we herein intend to determine its function in SCI. Lentivirus was instilled to overexpress or knockdown FGF5 expression in mice. Compound C or H89 2HCl were used to suppress AMP-activated protein kinase (AMPK) or protein kinase A (PKA), respectively. FGF5 level was significantly decreased during SCI. FGF5 overexpression mitigated, while FGF5 silence further facilitated inflammatory response, oxidative damage and SCI. Mechanically, FGF5 activated AMPK to attenuate SCI in a cAMP/PKA-dependent manner, while inhibiting AMPK or PKA with pharmacological methods significantly abolished the neuroprotective effects of FGF5 against SCI. More importantly, serum FGF5 level was decreased in SCI patients, and elevated serum FGF5 level often indicate better prognosis. Our study identifies FGF5 as an effective therapeutic and prognostic target for SCI.

Sevoflurane Protects against Intestinal Ischemia-Reperfusion Injury by Activating Peroxisome Proliferator-Activated Receptor Gamma/Nuclear Factor-κB Pathway in Rats.

BACKGROUND: Intestinal ischemia/reperfusion (I/R) injury is a clinical challenge with high morbidity and mortality, whereas the effective therapeutic strategy is limited. Inflammatory reaction plays important roles in I/R-induced intestinal damage and multi-organ dysfunction syndrome. Peroxisome proliferator-activated receptor gamma (PPARγ) has been identified as an endogenous anti-inflammatory regulator by inhibiting nuclear factor-κB (NF-κB) activation. Our previous research has shown that the pretreatment with inhaled anesthetic sevoflurane protects intestinal I/R injury. However, whether the protection induced by sevoflurane is mediated by inhibiting intestinal inflammatory reaction via activation of PPARγ/NF-κB pathway is underdetermined. In this study, we investigated the effects of sevoflurane on intestinal inflammatory reaction during intestinal I/R and the role of PPARγ/NF-κB pathway. METHODS: Rat model of intestinal I/R was used in this study. The superior mesenteric artery was clamped for 60 min followed by 120-min reperfusion. Sevoflurane at 0.5 minimum alveolar concentration was inhaled for 30 min before ischemic insult. GW9662, a specific PPARγ antagonist, was injected intraperitoneally before sevoflurane inhalation. RESULTS: Intestinal I/R caused severe intestinal mucosa histopathological injury evaluated by Chiu's scoring, induced epithelial cell apoptosis evaluated by terminal deoxyribonucleotide transferase-mediated dUTP nick end labeling and activation of caspase-3, upregulated serum MOD levels, reduced protein expression of Bcl-2 and PPARγ, increased protein expression of NF-κB P65 and proinflammatory cytokine tumor necrosis factor-α and interleukin-6 in the intestine. Sevoflurane preconditioning significantly ameliorated these changes induced by intestinal I/R. However, GW9662 partly blocked the protective effects induced by sevoflurane. CONCLUSIONS: Our results suggest sevoflurane-induced protection against intestinal I/R injury is partly mediated by inhibiting intestinal inflammatory reaction via activation of PPARγ/NF-κB pathway.

Mapping knowledge of the stem cell in traumatic brain injury: a bibliometric and visualized analysis.

Background: Traumatic brain injury (TBI) is a brain function injury caused by external mechanical injury. Primary and secondary injuries cause neurological deficits that mature brain tissue cannot repair itself. Stem cells can self-renewal and differentiate, the research of stem cells in the pathogenesis and treatment of TBI has made significant progress in recent years. However, numerous articles must be summarized to analyze hot spots and predict trends. This study aims to provide a panorama of knowledge and research hotspots through bibliometrics. Method: We searched in the Web of Science Core Collection (WoSCC) database to identify articles pertaining to TBI and stem cells published between 2000 and 2022. Visualization knowledge maps, including co-authorship, co-citation, and co-occurrence analysis were generated by VOSviewer, CiteSpace, and the R package "bibliometrix." Results: We retrieved a total of 459 articles from 45 countries. The United States and China contributed the majority of publications. The number of publications related to TBI and stem cells is increasing yearly. Tianjin Medical University was the most prolific institution, and Professor Charles S. Cox, Jr. from the University of Texas Health Science Center at Houston was the most influential author. The Journal of Neurotrauma has published the most research articles on TBI and stem cells. Based on the burst references, "immunomodulation," "TBI," and "cellular therapy" have been regarded as research hotspots in the field. The keywords co-occurrence analysis revealed that "exosomes," "neuroinflammation," and "microglia" were essential research directions in the future. Conclusion: Research on TBI and stem cells has shown a rapid growth trend in recent years. Existing studies mainly focus on the activation mechanism of endogenous neural stem cells and how to make exogenous stem cell therapy more effective. The combination with bioengineering technology is the trend in this field. Topics related to exosomes and immune regulation may be the future focus of TBI and stem cell research.

Relative quantification of phenolic compounds in exocarp-mesocarp and endocarp of sumac (Toxicodendron vernicifluum) combined with transcriptome analysis provides insights into glycosylation of flavonoids and biflavonoid biosynthesis.

The pericarp of fruit can be differentiated into endocarp, mesocarp, and exocarp. To explore the differences in gene expression and metabolites in different tissues of the pericarp, the fruits of sumac (Toxicodendron vernicifluum) were separated into endocarp and mesocarp-exocarp. The metabolites and transcriptome of exocarp-mesocarp and endocarp of Toxicodendron vernicifluum were analyzed by HPLC-QTOF-MS/MS and RNA sequencing, respectively. A total of 52 phenolic compounds were identified, including 3 phenylpropane derivatives, 10 urushiol compounds and 39 flavonoids. The exocarp-mesocarp contained more urushiol compounds and flavonoid glycosides while the endocarp contained more biflavonoids, such as rhusflavone and dihydromorelloflavone. The characteristic component of endocarp was rhusflavone and the characteristic component of exocarp-mesocarp was urushiol (triene). Most of the genes involved in flavonoid synthesis pathway were upregulated in endocarp compared with exocarp-mesocarp and positively correlated with the content of flavonoids. The candidate genes related to the synthesis of components of flavonoid glycosides and biflavonoids were screened. Metabolomic and transcriptomic analyses provide new insights into the synthesis and distribution of flavonoid glycosides and biflavonoids in the fruits of Toxicodendron vernicifluum.

Factors Associated With Nonadherence to Lung Cancer Screening Across Multiple Screening Time Points.

Importance: Screening with low-dose computed tomography (CT) has been shown to reduce mortality from lung cancer in randomized clinical trials in which the rate of adherence to follow-up recommendations was over 90%; however, adherence to Lung Computed Tomography Screening Reporting & Data System (Lung-RADS) recommendations has been low in practice. Identifying patients who are at risk of being nonadherent to screening recommendations may enable personalized outreach to improve overall screening adherence. Objective: To identify factors associated with patient nonadherence to Lung-RADS recommendations across multiple screening time points. Design, Setting, and Participants: This cohort study was conducted at a single US academic medical center across 10 geographically distributed sites where lung cancer screening is offered. The study enrolled individuals who underwent low-dose CT screening for lung cancer between July 31, 2013, and November 30, 2021. Exposures: Low-dose CT screening for lung cancer. Main Outcomes and Measures: The main outcome was nonadherence to follow-up recommendations for lung cancer screening, defined as failing to complete a recommended or more invasive follow-up examination (ie, diagnostic dose CT, positron emission tomography-CT, or tissue sampling vs low-dose CT) within 15 months (Lung-RADS score, 1 or 2), 9 months (Lung-RADS score, 3), 5 months (Lung-RADS score, 4A), or 3 months (Lung-RADS score, 4B/X). Multivariable logistic regression was used to identify factors associated with patient nonadherence to baseline Lung-RADS recommendations. A generalized estimating equations model was used to assess whether the pattern of longitudinal Lung-RADS scores was associated with patient nonadherence over time. Results: Among 1979 included patients, 1111 (56.1%) were aged 65 years or older at baseline screening (mean [SD] age, 65.3 [6.6] years), and 1176 (59.4%) were male. The odds of being nonadherent were lower among patients with a baseline Lung-RADS score of 1 or 2 vs 3 (adjusted odds ratio [AOR], 0.35; 95% CI, 0.25-0.50), 4A (AOR, 0.21; 95% CI, 0.13-0.33), or 4B/X, (AOR, 0.10; 95% CI, 0.05-0.19); with a postgraduate vs college degree (AOR, 0.70; 95% CI, 0.53-0.92); with a family history of lung cancer vs no family history (AOR, 0.74; 95% CI, 0.59-0.93); with a high age-adjusted Charlson Comorbidity Index score (≥4) vs a low score (0 or 1) (AOR, 0.67; 95% CI, 0.46-0.98); in the high vs low income category (AOR, 0.79; 95% CI, 0.65-0.98); and referred by physicians from pulmonary or thoracic-related departments vs another department (AOR, 0.56; 95% CI, 0.44-0.73). Among 830 eligible patients who had completed at least 2 screening examinations, the adjusted odds of being nonadherent to Lung-RADS recommendations at the following screening were increased in patients with consecutive Lung-RADS scores of 1 to 2 (AOR, 1.38; 95% CI, 1.12-1.69). Conclusions and Relevance: In this retrospective cohort study, patients with consecutive negative lung cancer screening results were more likely to be nonadherent with follow-up recommendations. These individuals are potential candidates for tailored outreach to improve adherence to recommended annual lung cancer screening.

Tailoring pretext tasks to improve self-supervised learning in histopathologic subtype classification of lung adenocarcinomas.

Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease with five predominant histologic subtypes. Fully supervised convolutional neural networks can improve the accuracy and reduce the subjectivity of LUAD histologic subtyping using hematoxylin and eosin (H&E)-stained whole slide images (WSIs). However, developing supervised models with good prediction accuracy usually requires extensive manual data annotation, which is time-consuming and labor-intensive. This work proposes three self-supervised learning (SSL) pretext tasks to reduce labeling effort. These tasks not only leverage the multi-resolution nature of the H&E WSIs but also explicitly consider the relevance to the downstream task of classifying the LUAD histologic subtypes. Two tasks involve predicting the spatial relationship between tiles cropped from lower and higher magnification WSIs. We hypothesize that these tasks induce the model to learn to distinguish different tissue structures presented in the images, thus benefiting the downstream classification. The third task involves predicting the eosin stain from the hematoxylin stain, inducing the model to learn cytoplasmic features relevant to LUAD subtypes. The effectiveness of the three proposed SSL tasks and their ensemble was demonstrated by comparison with other state-of-the-art pretraining and SSL methods using three publicly available datasets. Our work can be extended to any other cancer type where tissue architectural information is important. The model could be used to expedite and complement the process of routine pathology diagnosis tasks. The code is available at https://github.com/rina-ding/ssl_luad_classification.

Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer.

The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL's advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867).

Capturing Demographic, Health-Related, and Psychosocial Variables in a Standardized Manner: Towards Improving Cancer Screening Adherence.

Determining factors influencing patient participation in and adherence to cancer screening recommendations is key to successful cancer screening programs. However, the collection of variables necessary to anticipate patient behavior in cancer screening has not been systematically examined. Using lung cancer screening as a representative example, we conducted an exploratory analysis to characterize the current representations of 18 demographic, health-related, and psychosocial variables collected as part of a conceptual model to understand factors for lung cancer screening participation and adherence. Our analysis revealed a lack of standardization in controlled terminologies and common data elements for these variables. For example, only eight (44%) demographic and health-related variables were recorded consistently in the electronic health record. Multiple survey instruments could collect the remaining variables but were highly inconsistent in how variables were represented. This analysis suggests opportunities to establish standardized data formats for psychological, cognitive, social, and environmental variables to improve data collection.

Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis.

Lung cancer screening (LCS) is effective in reducing mortality, particularly when patients adhere to follow-up recommendations standardized by the Lung CT Screening Reporting & Data System (Lung-RADS). Nevertheless, patient adherence to recommended intervals varies, potentially diminishing benefit from screening. We conducted a systematic review and meta-analysis of patient adherence to Lung-RADS-recommended screening intervals. We systematically searched MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, and major radiology and oncology conference archives between April 28, 2014, and December 17, 2020. Eligible studies mentioned patient adherence to the recommendations of Lung-RADS. The review protocol was registered with PROSPERO (CRD42020189326). We identified 24 eligible studies for qualitative summary, of which 21 were suitable for meta-analysis. The pooled adherence rate was 57% (95% confidence interval: 46%-69%) for defined adherence (e.g., an annual incidence screen was performed within 15 mo) among 6689 patients and 65% (95% confidence interval: 55%-75%) for anytime adherence among 5085 patients. Large heterogeneity in adherence rates between studies was observed (I2 = 99% for defined adherence, I2 = 98% for anytime adherence). Heterogeneous adherence rates were associated with Lung-RADS scores, with significantly higher adherence rates among Lung-RADS 3 to 4 than Lung-RADS 1 to 2 (p < 0.05). Patient adherence to Lung-RADS-recommended screening intervals is suboptimal across clinical LCS programs in the United States, especially among patients with results of Lung-RADS categories 1 to 2. To improve adherence rates, future research may focus on implementing tailored interventions after identifying barriers to LCS. We also propose a minimum standardized set of data elements for future pooled analyses of LCS adherence on the basis of our findings.

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome.

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

LncRNA NEAT1/miR-128-3p/AQP4 axis regulating spinal cord injury-induced neuropathic pain progression.

BACKGROUND: Neuropathic pain (NP) is the comorbidity in spinal cord injury(SCI), which is the hardest to cure. Non-coding RNA dysregulations are related to the development of NP. NEAT1(nuclear paraspeckle assembly transcript 1) is a new type of lncRNA. This study explores the role and specific mechanism of NEAT1 in SCI-mediated NP. METHODS: Firstly, the NEAT1 expression in SCI rats and the control group was detected with RT-PCR to analyze the relationship between NEAT13 and NP symptoms. Then, SCI rats were intrathecally injected with NEAT13 overexpressing and knocking down lentiviruses. Afterward, ELISA was utilized to assess the expression of IL-6, IL-1ß and TNFα in rats. Subsequently, immunohistochemistry was adopted to verify the activation of microglial cells. After that, bioinformatics analysis was employed to further predict the downstream target genes of NEAT1, while RT-PCR and Western blot were conducted to determine the relative expression of miR-128-3p and aquaporin-4(AQP4). Meanwhile, a dual-luciferase reporter assay was performed to further study the targeting relationship between NEAT1 and miR-128-3p, and miR-128-3p and AQP4. RESULTS: SCI rats showed distinctly higher NEAT1 expression compared with that of the control group. ELISA experiment confirmed that the over-expression of NEAT1 enhanced the expression of IL-6, IL-1ß, and TNFα in SCI rats. Other related mechanism studies revealed that NEAT13 targeted and inhibited miR-128-3p as its competing endogenous RNA (ceRNA), and enhanced AQP4 expression, while miR-128-3p targeted AQP4 to regulate its expression. SUMMARY: NEAT1 affects AQP4 signaling pathway to alleviate the spinal cord injury-induced NP via promoting miR-128-3p expression.

An electronic circular dichroism spectroscopy method for the quantification of L- and D-amino acids in enantiomeric mixtures.

Rapid quantitative analysis of single chiral amino acid (aa) was achieved using circular dichroism (CD) with data analysis by standard calibration curve. The absolute concentrations of D- and L-aas in enantiomeric mixtures were determined by CD and achiral liquid chromatography (LC) method. It is worth noting that CD and LC were used independently, not online LC/CD in this study. The errors of the experimental results were less than 10%. The method is also applicable to the quantification of non-aa chiral molecules, such as chiral nucleoside and chiral quinine. With this study, we provide a new method for the chiral quantitative analysis of enantiomeric aas mixtures.

Cyclic Dipeptides Formation From Linear Dipeptides Under Potentially Prebiotic Earth Conditions.

Cyclic dipeptides (DKPs) are peptide precursors and chiral catalysts in the prebiotic process. This study reports proline-containing DKPs that were spontaneously obtained from linear dipeptides under an aqueous solution. Significantly, the yields of DKPs were affected by the sequence of linear dipeptides and whether the reaction contains trimetaphosphate. These findings provide the possibility that DKPs might play a key role in the origin of life.

Evaluation of different antibiotic prophylaxis strategies for hepatectomy: A network meta-analysis.

BACKGROUND: The application of antibiotic prophylaxis for hepatectomy remains uncertain. This research aims to evaluate different antibiotic prophylaxis strategies for hepatectomy based on network meta-analysis. METHODS: Literature retrieval was conducted in globally recognized databases, namely, MEDLINE, EMBASE and Cochrane Central, to address relative randomized controlled trials (RCTs) investigating antibiotic prophylaxis strategies for hepatectomy. Relative parametric data, including surgical site infection (SSI), remote site infection (RSI) and total infection (TI), were quantitatively pooled and estimated based on the Bayesian theorem. The values of surface under the cumulative ranking curve (SUCRA) probabilities regarding each parameter were calculated and ranked. Node-splitting analysis was performed to test the inconsistency of the main results, and publication bias was assessed by examining the funnel plot symmetry. Additional pairwise meta-analyses were performed to validate the differences between respective strategies at the statistical level. RESULTS: After a detailed review, a total of 5 RCTs containing 4 different strategies were included for the network meta-analysis. The results indicated that the application of no antibiotics possessed the highest possibility of having the best clinical effects on SSI (SUCRA, 0.56), RSI (SUCRA, 0.46) and TI (SUCRA, 0.61). Moreover, node-splitting analysis and funnel plot symmetries illustrated no inconsistencies in the current study. Additional pairwise meta-analyses determined that additional and long-duration applications had no clinical benefit. CONCLUSION: Based on current evidence, we concluded that antibiotic prophylaxis did not reveal clinical benefit in hepatectomy. However, more relative trials and statistical evidence are still needed.