Molecular and Functional Heterogeneity of Primary Pancreatic Neuroendocrine Tumors and Metastases.

INTRODUCTION: Treatment response to the standard therapy is low for metastatic pancreatic neuroendocrine tumors (PanNETs) mainly due to the tumor heterogeneity. We investigated the heterogeneity between primary PanNETs and metastases to improve the precise treatment. METHODS: The genomic and transcriptomic data of PanNETs were retrieved from the Genomics, Evidence, Neoplasia, Information, Exchange (GENIE), and Gene Expression Omnibus (GEO) database, respectively. Potential prognostic effects of gene mutations enriched in metastases were investigated. Gene set enrichment analysis was performed to investigate the functional difference. Oncology Knowledge Base was interrogated for identifying the targetable gene alterations. RESULTS: Twenty-one genes had significantly higher mutation rates in metastases which included TP53 (10.3% vs. 16.9%, p = 0.035) and KRAS (3.7% vs. 9.1%, p = 0.016). Signaling pathways related to cell proliferation and metabolism were enriched in metastases, whereas epithelial-mesenchymal transition (EMT) and TGF-ß signaling were enriched in primaries. Gene mutations were highly enriched in metastases that had significant unfavorable prognostic effects included mutation of TP53 (p < 0.001), KRAS (p = 0.001), ATM (p = 0.032), KMT2D (p = 0.001), RB1 (p < 0.001), and FAT1 (p < 0.001). Targetable alterations enriched in metastases included mutation of TSC2 (15.5%), ARID1A (9.7%), KRAS (9.1%), PTEN (8.7%), ATM (6.4%), amplification of EGFR (6.0%), MET (5.5%), CDK4 (5.5%), MDM2 (5.0%), and deletion of SMARCB1 (5.0%). CONCLUSION: Metastases exhibited a certain extent of genomic and transcriptomic diversity from primary PanNETs. TP53 and KRAS mutation in primary samples might associate with metastasis and contribute to a poorer prognosis. A high fraction of novel targetable alterations enriched in metastases deserves to be validated in advanced PanNETs.

Combination of QSAR Modeling and Hybrid-Based Consensus Scoring to Identify Dual-Targeting Inhibitors of PLK1 and p38γ.

Polo-like kinase 1 (PLK1) and p38γ mitogen-activated protein kinase (p38γ) play important roles in cancer pathogenesis by controlling cell cycle progression and are therefore attractive cancer targets. The design of multitarget inhibitors may offer synergistic inhibition of distinct targets and reduce the risk of drug-drug interactions to improve the balance between therapeutic efficacy and safety. We combined deep-learning-based quantitative structure-activity relationship (QSAR) modeling and hybrid-based consensus scoring to screen for inhibitors with potential activity against the targeted proteins. Using this combination strategy, we identified a potent PLK1 inhibitor (compound 4) that inhibited PLK1 activity and liver cancer cell growth in the nanomolar range. Next, we deployed both our QSAR models for PLK1 and p38γ on the Enamine compound library to identify dual-targeting inhibitors against PLK1 and p38γ. Likewise, the identified hits were subsequently subjected to hybrid-based consensus scoring. Using this method, we identified a promising compound (compound 14) that could inhibit both PLK1 and p38γ activities. At nanomolar concentrations, compound 14 inhibited the growth of human hepatocellular carcinoma and hepatoblastoma cells in vitro. This study demonstrates the combined screening strategy to identify novel potential inhibitors for existing targets.

The effect of different angle kappa on higher-order aberrations after small incision lenticule extraction.

This study aimed to compare higher-order aberrations (HOAs) after small incision lenticule extraction (SMILE) in patients with different angle kappa. This is a retrospective report in which 341 right eyes of 341 patients who were subjected to SMILE, which used coaxially sighted corneal light reflex (CSCLR) as the treatment zone centered, treated by the same experienced surgeon (LHB) for correction of myopia and myopic astigmatism, preoperative and postoperative spherical equivalent (SE), angle kappa, total higher-order aberrations (total HOA), spherical aberration (SA), vertical coma (VC), horizontal coma (HC), oblique trefoil (OT), and horizontal trefoil (HT), were compared. SMILE showed outstanding performance in terms of safety, efficacy, and predictability. In addition, a comparison of preoperative and postoperative HOAs exhibited the difference of total HOA (P < 0.01), SA (P < 0.01), VC (P < 0.01), and HC (P < 0.01), which was statistically significant; however, for OT and HT with the longer follow-up time, the statistical difference gradually decreased. For stratification of angle kappa into groups based on decantation, angle kappa was divided into three major groups: r < 0.1 mm, 0.1 ≤ r < 0.2 mm, and r ≥ 0.2 mm; the changes of SA (F = 4.127, P = 0.021) and OT (F = 3.687, P = 0.031) exhibited significant difference after 1 year of SMILE. We performed a correlation analysis of all preoperative and postoperative parameters, and the results indicated that the preoperative total HOA was negatively correlated with preoperative cylindrical diopter (DC), and postoperative total HOA, SA, and coma were affected by spherical diopter (DS) and SE. Moreover, we also found a significant difference of SA and VC in the early postoperative with preoperative. SA was positively correlated with Y values and r of 1 year after SMILE. All of the analyzed parameters in the three groups, except for the trefoil, gradually increased over time; however, the trefoil could gradually stabilize over time. We also divided angle kappa into four groups by quadrants; the result showed that the effects of higher-order aberrations were markedly different from the various quadrants. Patients with large angle kappa were able to increase VC and SA postoperatively, and higher HOAs were more significant in patients with high myopia. The differences in quadrants exhibited a diversity of HOAs; this could be attributed to the corneal surface reestablishment and the alteration of angle kappa, but the trend was not apparent. Although all patients displayed increased HOAs after SMILE, the potential application of CSCLR as the treatment zone centered still showed excellent safety, efficacy, and predictability.

Identification of Potential p38γ Inhibitors via In Silico Screening, In Vitro Bioassay and Molecular Dynamics Simulation Studies.

Protein kinase p38γ is an attractive target against cancer because it plays a pivotal role in cancer cell proliferation by phosphorylating the retinoblastoma tumour suppressor protein. Therefore, inhibition of p38γ with active small molecules represents an attractive alternative for developing anti-cancer drugs. In this work, we present a rigorous and systematic virtual screening framework to identify potential p38γ inhibitors against cancer. We combined the use of machine learning-based quantitative structure activity relationship modelling with conventional computer-aided drug discovery techniques, namely molecular docking and ligand-based methods, to identify potential p38γ inhibitors. The hit compounds were filtered using negative design techniques and then assessed for their binding stability with p38γ through molecular dynamics simulations. To this end, we identified a promising compound that inhibits p38γ activity at nanomolar concentrations and hepatocellular carcinoma cell growth in vitro in the low micromolar range. This hit compound could serve as a potential scaffold for further development of a potent p38γ inhibitor against cancer.

Is automatic cephalometric software using artificial intelligence better than orthodontist experts in landmark identification?

BACKGROUND: To evaluate the techniques used for the automatic digitization of cephalograms using artificial intelligence algorithms, highlighting the strengths and weaknesses of each one and reviewing the percentage of success in localizing each cephalometric point. METHODS: Lateral cephalograms were digitized and traced by three calibrated senior orthodontic residents with or without artificial intelligence (AI) assistance. The same radiographs of 43 patients were uploaded to AI-based machine learning programs MyOrthoX, Angelalign, and Digident. Image J was used to extract x- and y-coordinates for 32 cephalometric points: 11 soft tissue landmarks and 21 hard tissue landmarks. The mean radical errors (MRE) were assessed radical to the threshold of 1.0 mm,1.5 mm, and 2 mm to compare the successful detection rate (SDR). One-way ANOVA analysis at a significance level of P < .05 was used to compare MRE and SDR. The SPSS (IBM-vs. 27.0) and PRISM (GraphPad-vs.8.0.2) software were used for the data analysis. RESULTS: Experimental results showed that three methods were able to achieve detection rates greater than 85% using the 2 mm precision threshold, which is the acceptable range in clinical practice. The Angelalign group even achieved a detection rate greater than 78.08% using the 1.0 mm threshold. A marked difference in time was found between the AI-assisted group and the manual group due to heterogeneity in the performance of techniques to detect the same landmark. CONCLUSIONS: AI assistance may increase efficiency without compromising accuracy with cephalometric tracings in routine clinical practice and research settings.

Performance of radiomics models for tumour-infiltrating lymphocyte (TIL) prediction in breast cancer: the role of the dynamic contrast-enhanced (DCE) MRI phase.

OBJECTIVE: To systematically investigate the effect of imaging features at different DCE-MRI phases to optimise a radiomics model based on DCE-MRI for the prediction of tumour-infiltrating lymphocyte (TIL) levels in breast cancer. MATERIALS AND METHODS: This study retrospectively collected 133 patients with pathologically proven breast cancer, including 73 patients with low TIL levels and 60 patients with high TIL levels. The volumes of breast cancer lesions were manually delineated on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and each phase of DCE-MRI, followed by 6250 quantitative feature extractions. The least absolute shrinkage and selection operator (LASSO) method was used to select predictive feature sets for the classifiers. Four models were developed for predicting TILs: (1) single enhanced phase radiomics models; (2) fusion enhanced multi-phase radiomics models; (3) fusion multi-sequence radiomics models; and (4) a combined radiomics-based clinical model. RESULTS: Image features extracted from the delayed phase MRI, especially DCE_Phase 6 (DCE_P6), demonstrated dominant predictive performances over features from other phases. The fusion multi-sequence radiomics model and combined radiomics-based clinical model achieved the highest predictive performances with areas under the curve (AUCs) of 0.934 and 0.950, respectively; however, the differences were not statistically significant. CONCLUSION: The DCE-MRI radiomics model, especially image features extracted from the delayed phases, can help improve the performance in predicting TILs. The radiomics nomogram is effective in predicting TILs in breast cancer. KEY POINTS: • Radiomics features extracted from DCE-MRI, especially delayed phase images, help predict TIL levels in breast cancer. • We developed a nomogram based on MRI to predict TILs in breast cancer that achieved the highest AUC of 0.950.

A CT-based radiomics nomogram for prediction of human epidermal growth factor receptor 2 status in patients with gastric cancer.

OBJECTIVE: To develop and validate a computed tomography (CT)-based radiomics nomogram for predicting human epidermal growth factor receptor 2 (HER2) status in patients with gastric cancer. METHODS: This retrospective study included 134 patients with gastric cancer (HER2-negative: n=87; HER2-positive: n=47) from April 2013 to March 2018, who were then randomly divided into training (n=94) and validation (n=40) cohorts. Radiomics features were obtained from the CT images showing gastric cancer. Least absolute shrinkage and selection operator (LASSO) regression analysis was utilized for building the radiomics signature. A multivariable logistic regression method was applied to develop a prediction model incorporating the radiomics signature and independent clinicopathologic risk predictors, which were then visualized as a radiomics nomogram. The predictive performance of the nomogram was assessed in the training and validation cohorts. RESULTS: The radiomics signature was significantly associated with HER2 status in both training (P<0.001) and validation (P=0.023) cohorts. The prediction model that incorporated the radiomics signature and carcinoembryonic antigen (CEA) level demonstrated good discriminative performance for HER2 status prediction, with an area under the curve (AUC) of 0.799 [95% confidence interval (95% CI): 0.704-0.894] in the training cohort and 0.771 (95% CI: 0.607-0.934) in the validation cohort. The calibration curve of the radiomics nomogram also showed good calibration. Decision curve analysis showed that the radiomics nomogram was useful. CONCLUSIONS: We built and validated a radiomics nomogram with good performance for HER2 status prediction in gastric cancer. This radiomics nomogram could serve as a non-invasive tool to predict HER2 status and guide clinical treatment.

Inhibitory effects of ursolic acid from Bushen Yijing Formula on TGF-ß1-induced human umbilical vein endothelial cell fibrosis via AKT/mTOR signaling and Snail gene.

The present study aimed to investigate the functional components from Bushen Yijing Formula and their inhibition of endothelial-mesenchymal transition (EndMT) and fibrosis in human umbilical vascular endothelial cells (HUVECs). HUVEC fibrosis was induced by treatment of transforming growth factor ß (TGF-ß) as the cellular model. Expression of EndMT biomarker gene and cofactors were determined by quantitative real-time-PCR, western blotting, and immunofluorescence. Angiogenesis capacity of vein endothelial cells was evaluated using tube formation assay. Ursolic acid and drug-contained serum ameliorated EndMT biomarker gene expression changes and angiogenesis capacity suppression induced by TGF-ß treatment. Slug, Snail, and Twist gene expression and phosphorylation of mammalian target of rapamycin (mTOR) and AKT altered by TGF-ß in HUVECs were suppressed by ursolic acid and drug-contained serum. Treatment with the mTOR signaling pathway inhibitor, rapamycin, inhibited the phosphorylation of mTOR and AKT, decreased Snail and Vimentin protein levels, and increased VE-cad protein levels. Overexpression of Snail gene promoted expression of EndMT-related genes and suppressed angiogenesis in HUVECs, which were attenuated by application of ursolic acid and drug-contained serum. Ursolic acid from Bushen Yijing Formula inhibits human umbilical vein endothelial cell EndMT and fibrosis, mediated by AKT/mTOR signaling and Snail gene expression.

[Effects of different wavelet filters on correlation and diagnostic performance of radiomics features].

OBJECTIVE: To investigate the effects of different wavelet filters on correlation and diagnostic performance of radiomics features.
 Methods: A total of 143 colorectal cancer (CRC) patients (64 positive in lymph node metastasis and 79 negative) with contrast-enhanced CT examination were recruited. After labeling the tumor area by experienced radiologists, radiomics wavelets features based on 48 different wavelets were extracted using in-house software coded by Matlab. The correlation coefficients of the features with same names between different wavelets were calculated and got the distribution of high-correlation features between each wavelet. The least absolute shrinkage and selection operator (LASSO) was used to build signatures between lymph node metastasis and wavelet features data set based on different wavelets. The numbers of features in signatures and diagnostic performance were compared using Delong's test.
 Results: With the difference of wavelet order increased, the number of high-correlation features between two wavelets decreased. Some features were prone to high correlation between different wavelets. When building radiomics signature based on single wavelet, signatures built from 'rbio2.2', 'sym7' and 'db7' did well in predicting lymph node metastasis. The signature based on Daubechies wavelet feature set had the highest performance in predicting lymph node metastasis, while the signature from Biorthogonal wavelet features was worst. Improvement was significant in diagnostic performance after excluding the high-correlation features in the whole features set (P=0.004).
 Conclusion: In order to reduce the data redundancy of features, it is recommended to select wavelets with large differences in wavelet orders when calculating radiomics wavelet features. It is necessary to remove high correlation features for improving the diagnostic performance of radiomics signature.

[Preoperative evaluation of histologic grade in invasive breast cancer with T2W-MRI based radiomics signature].

OBJECTIVE: To develop and validate a fat-suppressed (T2 weighted-magnetic resonance imaging, T2W-MRI) based radiomics signature to preoperatively evaluate the histologic grade (grade I/II VS. grade III) of invasive breast cancer.
 Methods: A total of 202 patients with MRI examination and pathologically confirmed invasive breast cancer from June 2011 to February 2017 were retrospectively enrolled. After retrieving fat-suppressed T2W images and tumor segmentation, radiomics features were extracted and valuable features were selected to build a radiomic signature with the least absolute shrinkage and selection operator (LASSO) method. Mann-Whitney U test was used to explore the correlation between radiomics signature and histologic grade. Receiver operating characteristics (ROC) curve was applied to determine the discriminative performance of the radiomics signature [area under curre (AUC), sensitivity, specificity, and accuracy]. An independent validation dataset was used to confirm the discriminatory power of radiomics signature. 
 Results: Eight radiomics features were selected to build a radiomics signature, which showed good performance for preoperatively evaluating histologic grade of invasive breast cancer, with an AUC of 0.802 (95% CI 0.729 to 0.875), sensitivity of 78.7%, specificity of 70.3% and accuracy of 73.7% in training dataset and AUC of 0.812 (95% CI 0.686 to 0.938), sensitivity of 80.0%, specificity of 73.3% and accuracy of 76.0% in the validation dataset.
 Conclusion: The fat-suppressed T2W-MRI based radiomics signature can be used to preoperatively evaluate the histologic grade of invasive breast cancer, which may assist clinical decision-maker.

Radiomics approach for preoperative identification of stages I-II and III-IV of esophageal cancer.

OBJECTIVE: To predict preoperative staging using a radiomics approach based on computed tomography (CT) images of patients with esophageal squamous cell carcinoma (ESCC). METHODS: This retrospective study included 154 patients (primary cohort: n=114; validation cohort: n=40) with pathologically confirmed ESCC. All patients underwent a preoperative CT scan from the neck to abdomen. High throughput and quantitative radiomics features were extracted from the CT images for each patient. A radiomics signature was constructed using the least absolute shrinkage and selection operator (Lasso). Associations between radiomics signature, tumor volume and ESCC staging were explored. Diagnostic performance of radiomics approach and tumor volume for discriminating between stages I-II and III-IV was evaluated and compared using the receiver operating characteristics (ROC) curves and net reclassification improvement (NRI). RESULTS: A total of 9,790 radiomics features were extracted. Ten features were selected to build a radiomics signature after feature dimension reduction. The radiomics signature was significantly associated with ESCC staging (P<0.001), and yielded a better performance for discrimination of early and advanced stage ESCC compared to tumor volume in both the primary [area under the receiver operating characteristic curve (AUC): 0.795vs. 0.694, P=0.003; NRI=0.424)] and validation cohorts (AUC: 0.762 vs. 0.624, P=0.035; NRI=0.834). CONCLUSIONS: The quantitative approach has the potential to identify stage I-II and III-IV ESCC before treatment.

Computed tomography-based radiomics for prediction of neoadjuvant chemotherapy outcomes in locally advanced gastric cancer: A pilot study.

OBJECTIVE: The standard treatment for patients with locally advanced gastric cancer has relied on perioperative radio-chemotherapy or chemotherapy and surgery. The aim of this study was to investigate the wealth of radiomics for pre-treatment computed tomography (CT) in the prediction of the pathological response of locally advanced gastric cancer with preoperative chemotherapy. METHODS: Thirty consecutive patients with CT-staged II/III gastric cancer receiving neoadjuvant chemotherapy were enrolled in this study between December 2014 and March 2017. All patients underwent upper abdominal CT during the unenhanced, late arterial phase (AP) and portal venous phase (PP) before the administration of neoadjuvant chemotherapy. In total, 19,985 radiomics features were extracted in the AP and PP for each patient. Four methods were adopted during feature selection and eight methods were used in the process of building the classifier model. Thirty-two combinations of feature selection and classification methods were examined. Receiver operating characteristic (ROC) curves were used to evaluate the capability of each combination of feature selection and classification method to predict a non-good response (non-GR) based on tumor regression grade (TRG). RESULTS: The mean area under the curve (AUC) ranged from 0.194 to 0.621 in the AP, and from 0.455 to 0.722 in the PP, according to different combinations of feature selection and the classification methods. There was only one cross-combination machine-learning method indicating a relatively higher AUC (>0.600) in the AP, while 12 cross-combination machine-learning methods presented relatively higher AUCs (all >0.600) in the PP. The feature selection method adopted by a filter based on linear discriminant analysis + classifier of random forest achieved a significantly prognostic performance in the PP (AUC, 0.722±0.108; accuracy, 0.793; sensitivity, 0.636; specificity, 0.889; Z=2.039; P=0.041). CONCLUSIONS: It is possible to predict non-GR after neoadjuvant chemotherapy in locally advanced gastric cancers based on the radiomics of CT.

Exploring the Role of Gut-Lung Interactions in COPD Pathogenesis: A Comprehensive Review on Microbiota Characteristics and Inflammation Modulation.

Chronic obstructive pulmonary disease (COPD) is a paramount contributor to global morbidity and mortality. Over the past decade, the concept of the "gut-lung axis" has emerged, offering a lens through which to examine the intricate interplay between the host, microbiome, and respiratory diseases, including COPD. An expanding body of evidence underscores that the composition of both the gastrointestinal and respiratory microbiome deviates in COPD patients compared to healthy individuals, leading to distinct host immune responses and clinical manifestations. The objective of this review is to provide a concise overview of the role both gut and respiratory microbiome play in the development of COPD. This was accomplished by compiling current literature on the microbiome profile in stable and exacerbated cases of COPD, as well as exploring the biological mechanisms through a discussion of relevant experiments conducted on murine models. Hallmark characteristics of the microbial profile in COPD encompass reduced Prevotella species in the respiratory microbiome, culminating in a loss of anti-inflammatory protection, and diminished Bacteroidetes in the gut microbiome, leading to a decrease in protective short-chain fatty acids. The proliferation of Proteobacteria, particularly the Haemophilus species, Moraxellaspecies, and Pseudomonas species contribute to COPD pathologies via recognition of proinflammatory lipopolysaccharide via Toll-like receptors. As a consequence, deteriorated pulmonary function, enhanced severity, increased onset of exacerbations, and elevated mortality were observed.

Treatment of Bone Metastases of Breast Cancer With 177 Lu-DOTA-IBA.

ABSTRACT: Bone metastasis of breast cancer often presents as osteolytic. 177 Lu-DOTA-ibandronic acid ( 177 Lu-DOTA-IBA) is a new radioactive drug for bone metastasis lesion. We report a case of recurrent intermittent pain due to bone metastasis, who demonstrated a satisfactory therapy response after 2 cycles of 177 Lu-DOTA-IBA. In addition, the patient did not have any observable adverse effects.

Effects of visual neuroplasticity training on visual perception, visual quality, and macular blood flow in patients with strabismus.

PURPOSE: To observe the effects of visual neuroplasticity training on visual perception, visual quality, and macular blood flow in patients with concomitant strabismus postoperatively. METHODS: In total, 108 patients underwent binocular strabismus correction operation, and some patients underwent neuroplasticity training. All patients underwent clinical ophthalmic examination, including measurement of best-corrected visual acuity, spherical equivalent, axis length, optical coherence tomography angiography, optical quality analysis system, and visual perception examinations. RESULTS: A total of 78 patients received neuroplasticity training for 1 month postoperatively, and 30 patients did not receive training. All patients underwent a visual perception examination preoperatively and at 1 day, 1 week, and 1 month postoperatively. Macular blood flow and visual quality were examined preoperatively and at 1 month postoperatively. Postoperative visual perception was better than preoperative visual perception (P < 0.05). After neuroplasticity training, the visual perception of the trained subjects was better than that of the untrained subjects (P < 0.05), and the blood flow in the macular area of the trained patients was lower than that of the untrained subjects (P < 0.05). The visual quality of the untrained subjects was lower than that of the trained patients (P < 0.05). CONCLUSIONS: Visual inspection system could accurately evaluate binocular visual perception in patients with concomitant strabismus. After surgical alignment of the strabismus patient, training can stimulate and integrate the formation of stereovision in a short period of time, maintain the visual quality of patients after surgery, and provide conditions for the formation of binocular visual signals and binocular stereovision, but in the short term, it will lead to the decrease of macular blood vessel density and perfusion density. However, the long-term effects of training have not been proven.

Prognostic value of inflammation-related biomarkers in patients with gastroenteropancreatic neuroendocrine neoplasms: A systematic review and meta-analysis.

Hematological indicators of chronic systemic inflammation are significant biomarkers for gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). We performed a systematic review and meta-analysis to assess the impact of certain factors on the overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of patients with GEP-NENs. These factors include the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), and C-reactive protein (CRP) levels. After searching the Medline, Embase, and Cochrane Library databases from January 1, 2000 to October 20, 2022 and the American Society of Clinical Oncology conference proceedings from January 1, 2017, hazard ratios (HRs) and 95% confidence intervals (CIs) were extracted. Subgroup analyses were conducted to identify the origins of heterogeneity and examine the impact of factor grouping. The effects of the cut-off values and sample size were assessed by meta-regression. The results revealed that higher NLRs, PLRs, and CRP levels were associated with shorter OS (HR = 2.09, 95% CI = 1.55-2.8; HR = 1.79, 95% CI = 1.40-2.28; and HR = 2.88, 95% CI = 2.09-3.95, respectively; all p < 0.001). Higher NLRs and lower LMRs were associated with shorter DFS (HR = 3.34, 95% CI = 2.11-5.29 and HR = 2.71, 95% CI = 2.27-3.24, respectively; both p < 0.001). Higher PLRs and CRP levels were correlated with shorter PFS (HR = 3.48, 95% CI = 1.34-9.03, p = 0.01 and HR = 3.14, 95% CI = 1.63-6.08, p = 0.001). As demonstrated in the research, hematological indicators of systemic inflammation are promising biomarkers for GEP-NEN assessment.

The evolution and impact of sarcopenia in severe aplastic anaemia survivors following allogeneic haematopoietic cell transplantation.

BACKGROUND: Sarcopenia is a potential risk factor for adverse outcomes in haematopoietic cell transplantation (HSCT) recipients. We aimed to explore longitudinal body changes in muscle and adipose mass and their prognostic value in allogeneic HSCT-treated severe aplastic anaemia (SAA) patients. METHODS: We retrospectively analysed consecutive SAA patients who underwent allogeneic HSCT between January 2017 and March 2022. Measurements of pectoral muscle and corresponding subcutaneous fat mass were obtained via chest computed tomography at baseline and at 1 month, 3 months, 6 months, and 12 months following HSCT. Sarcopenia was defined as pectoral muscle index (PMI) lower than the sex-specific median at baseline. Changes in body composition over time were evaluated by generalized estimating equations. Cox regression models were used to investigate prognostic factors affecting overall survival (OS) and failure-free survival (FFS). A nomogram was constructed from the Cox regression model for OS. RESULTS: We included 298 adult SAA patients (including 129 females and 169 males) with a median age of 31 years [interquartile range (IQR), 24-39 years] at baseline. Sarcopenia was present in 148 (148/298, 50%) patients at baseline, 218 (218/285, 76%) patients post-1 month, 209 (209/262, 80%) patients post-3 month, 169 (169/218, 78%) patients post-6 month, and 129 (129/181, 71%) patients post-12 month. A significant decrease in pectoral muscle mass was observed in SAA patients from the time of transplant to 1 year after HSCT, and the greatest reduction occurred in post 1-3 months (P < 0.001). The sarcopenia group exhibited significantly lower 5-year OS (90.6% vs. 100%, log-rank P = 0.039) and 5-year FFS (89.2% vs. 100%, log-rank P = 0.021) than the nonsarcopenia group at baseline. Sarcopenia at baseline (hazard ratio, HR, 6.344; 95% confidence interval, CI: 1.570-25.538; P = 0.01; and HR, 3.275; 95% CI: 1.159-9.252; P = 0.025, respectively) and the delta value of the PMI at 6 months post-transplantation (ΔPMI6) (HR, 0.531; 95% CI: 0.374-0.756; P < 0.001; and HR, 0.666; 95% CI: 0.505-0.879; P = 0.004, respectively) were demonstrated to be independent prognostic factors for OS and FFS in SAA patients undergoing HSCT, and were used to construct the nomogram. The C-index of the nomogram was 0.75, and the calibration plot showed good agreement between the predictions made by the nomogram and actual observations. CONCLUSIONS: Sarcopenia persists in SAA patients from the time of transplant to the 1-year follow-up after HSCT. Both sarcopenia at baseline and at 6 months following HSCT are associated with poor clinical outcomes, especially in patients with persistent muscle mass loss up to 6 months after transplantation.

Genetic Insights into the Gut-Lung Axis: Mendelian Randomization Analysis on Gut Microbiota, Lung Function, and COPD.

Background: Chronic obstructive pulmonary disease (COPD) is a respiratory disorder with a complex etiology involving genetic and environmental factors. The dysbiosis of gut microbiota has been implicated in COPD. Mendelian Randomization (MR) provides a tool to investigate causal links using genetic variants as instrumental variables. This study aims to employ MR analysis to explore the causal relationship between gut microbiota, lung function, and COPD. Methods: We utilized genome-wide association study (GWAS) data from MiBioGen, UK Biobank and FinnGen, which were related to gut microbial taxa, lung function parameters including forced vital capacity in one second (FEV1), forced vital capacity (FVC), and percentage of predicted FEV1 (FEV1%pred), as well as GWAS data for COPD. MR analysis was conducted to assess the causal effects of gut microbiota on lung function and the risk of COPD. Sensitivity analysis was utilized to examine the stability of the causal relationships. Multiple testing and reverse analysis were employed to evaluate the robustness of these relationships. Results: Using the IVW method, 64 causal correlations were identified. Through conducting sensitivity analysis, multiple testing, and reverse analysis, we identified 14 robust and stable causal relationships. The bacterial taxa that showed a positive association with lung function included Desulfovibrionaceae, Erysipelotrichales, Desulfovibrionales, Clostridiales, Clostridia, Deltaproteobacteria and Erysipelotrichia, while Selenomonadales and Negativicutes showed a negative association with lung function. The abundance of Holdemanella were positively correlated with the risk of COPD, while FamilyXIII exhibited a negative correlation with the risk of COPD. Conclusion: Several microbial taxa were discovered to have a positive causal correlation with lung function, offering potential insights into the development of probiotics. The presence of microbial taxa negatively correlated with lung function and positively correlated with COPD emphasized the potential impact of gut microbiota dysbiosis on respiratory health.

Therapeutic potential of iron chelators in retinal vascular diseases.

Iron is one of the necessary metal elements in the human body. There are numerous factors that control the balance of iron metabolism, and its storage and transportation mechanisms are intricate. As one of the most energy-intensive tissues in the body, the retina is susceptible to iron imbalance. The occurrence of iron overload in the retina leads to the generation of a significant quantity of reactive oxygen species. This will aggravate local oxidative stress and inflammatory reactions and even lead to ferroptosis, eventually resulting in retinal dysfunction. The blood-retina-retinal barrier is eventually harmed by oxidative stress and elevated inflammation, which are characteristics of retinal vascular disorders. The pathophysiology of retinal vascular disorders may be significantly influenced by iron. Recently, iron-chelating agents have been found to have antioxidative and anti-inflammatory actions in addition to iron chelating. Therefore, iron neutralization is considered to be a new and potentially useful therapeutic strategy. This article reviews the iron overload in retinal vascular diseases and discusses the therapeutic potential of iron-chelating agents.

Effects of the CDC10 (Septin 7) Gene on the Proliferation and Differentiation of Bovine Intramuscular Preadipocyte and 3T3-L1 Cells.

Intramuscular fat content and marbling affecting meat quality are important economic traits in beef cattle. CDC10 (cell division cycle 10 or Septin 7), a member of the septin family involved in cellular proliferation, was considered as a functional and positional candidate gene for beef marbling. In a previous study, we revealed that the expression levels of CDC10 were also positively correlated with marbling scores in Japanese Black cattle. However, the regulatory mechanism of the CDC10 gene on IMF deposition in cattle remains unclear. In the present study, flow cytometry, EdU proliferation assays, and Oil Red O staining results showed that overexpression of CDC10 could promote the differentiation of bovine intramuscular preadipocyte (BIMP) and 3T3-L1 cells, whereas knockdown of CDC10 resulted in the opposite consequences. Furthermore, quantitative PCR and Western blotting results showed that overexpression of CDC10 could promote the expression levels of adipogenic marker genes PPARγ and C/EBPα at both mRNA and protein levels in BIMP and 3T3-L1 cells, whereas knockdown of CDC10 resulted in the opposite consequences. Our results provide new insights into the regulatory roles of CDC10 in adipocytes in animals.