Characterizing the concentration of ethanol-water solutions by oblique-incidence reflectivity difference combined with deep learning algorithms.

The detection of ethanol-water solution concentration plays an important role in industries, medical care, food and other aspects, which has attracted much attention. In this paper, a 632.8 nm laser combined with the oblique-incidence reflectivity difference (OIRD) method was used to obtain a signal linearly related to the solution concentration and containing the information of the dielectric constant of the solution. Combined with a variety of deep learning algorithms, ethanol-water solutions with a volume concentration of 0-95 % are detected. Among them, the prediction accuracy of the MLP, CNN, LSTM, CNN + BiLSTM + Attention models were 93.65 %, 96.54 %, 97.12 %, 99.23 %, respectively. The experimental results indicate that the OIRD method can achieve rapid, non-destructive, accurate and reliable detection of ethanol-water solutions.

Case report: Bridging radiation therapy before chimeric antigen receptor T-cell therapy induces sustained remission in patients with relapsed/refractory double-expressor diffuse large B-cell lymphoma with localized compressive symptoms.

Background: High-risk double-expressor diffuse large B-cell lymphoma has an inferior prognosis following standard first-line therapy. After failure of second-line therapy, treatment options are limited if accompanied by localized compressive symptoms. Chimeric Antigen Receptor T cell (CAR-T) therapy preceded by bridging radiotherapy may be an effective emerging therapy. Case presentation: We report a 66-year-old female patient diagnosed with stage IV double-expressor diffuse large B-cell lymphoma. The patient achieved progressive disease after two cycles of rituximab, cyclophosphamide, liposomal doxorubicin, vincristine, and prednisone and continued to develop cervical lymph node recurrence after second-line therapy. The patient was infused with CAR-T cells after receiving focal bridging radiotherapy and remained in complete response more than 9 months after treatment. In addition, the patients did not experience serious adverse reactions related to radiotherapy as well as CAR-T cell therapy. Conclusions: In this article, we describe a patient with double-expressor diffuse large B-cell lymphoma with localized compression symptoms after second-line treatment failure who benefited from CAR-T combined with focal bridging radiotherapy.

Enhanced Poly-γ-Glutamic Acid Production by a Newly Isolated Bacillus halotolerans F29.

Poly-γ-glutamic acid (γ-PGA) is a promising biopolymer for various applications. In this study, we isolated a novel γ-PGA-producing strain, Bacillus halotolerans F29. The one-factor-at-a-time method was used to investigate the influence of carbon sources, nitrogen sources, and culture parameters on γ-PGA production. The optimal carbon and nitrogen sources were sucrose and (NH4)2SO4, respectively. The optimal culture conditions for γ-PGA production were determined to be 37 °C and a pH of 5.5. Response surface methodology was used to determine the optimum medium components: 77.6 g/L sucrose, 43.0 g/L monosodium glutamate, and 2.2 g/L K2HPO4. The γ-PGA titer increased significantly from 8.5 ± 0.3 g/L to 20.7 ± 0.7 g/L when strain F29 was cultivated in the optimized medium. Furthermore, the γ-PGA titer reached 50.9 ± 1.5 g/L with a productivity of 1.33 g/L/h and a yield of 2.23 g of γ-PGA/g of L-glutamic acid with the optimized medium in fed-batch fermentation. The maximum γ-PGA titer reached 45.3 ± 1.1 g/L, with a productivity of 1.06 g/L/h when molasses was used as a carbon source. It should be noted that the γ-PGA yield in this study was the highest of all reported studies, indicating great potential for the industrial production of γ-PGA.

Spatial cell interplay networks of regulatory T cells predict recurrence in patients with operable non-small cell lung cancer.

BACKGROUND: The interplay between regulatory T cells (Tregs) and neighboring cells, which is pivotal for anti-tumor immunity and closely linked to patient prognosis, remains to be fully elucidated. METHODS: Tissue microarrays of 261 operable NSCLC patients were stained by multiplex immunofluorescence (mIF) assay, and the interaction between Tregs and neighboring cells in the tumor microenvironment (TME) was evaluated. Employing various machine learning algorithms, we developed a spatial immune signature to predict the prognosis of NSCLC patients. Additionally, we explored the interplay between programmed death-1/programmed death ligand-1 (PD-1/PD-L1) interactions and their relationship with Tregs. RESULTS: Survival analysis indicated that the interplay between Tregs and neighboring cells in the invasive margin (IM) and tumor center was associated with recurrence in NSCLC patients. We integrated the intersection of the three algorithms to identify four crucial spatial immune features [P(CD8+Treg to CK) in IM, P(CD8+Treg to CD4) in IM, N(CD4+Treg to CK) in IM, N(CD4+Tcon to CK) in IM] and employed these characteristics to establish SIS, an independent prognosticator of recurrence in NSCLC patients [HR = 2.34, 95% CI (1.53, 3.58), P < 0.001]. Furthermore, analysis of cell interactions demonstrated that a higher number of Tregs contributed to higher PD-L1+ cells surrounded by PD-1+ cells (P < 0.001) with shorter distances (P = 0.004). CONCLUSION: We dissected the cell interplay network within the TME, uncovering the spatial architecture and intricate interactions between Tregs and neighboring cells, along with their impact on the prognosis of NSCLC patients.

Optimizing the spatial immune landscape of CD103+CD8+ tissue-resident memory T cells in non-small cell lung cancer by neoadjuvant chemotherapy.

BACKGROUND: Neoadjuvant chemotherapy (NAC) combined with immunotherapy is increasingly used in non-small cell lung cancer (NSCLC). Tissue-resident memory T (TRM) cells are the primary subset responding to anti-cancer immunity. However, the immunomodulatory effects of NAC on TRM cells remain unknown. METHODS: We established two NSCLC cohorts including patients undergoing upfront surgery (US) and NAC followed by surgery. Beyond the unpaired comparison between the US cohort (n = 122) and NAC cohort (n = 141) with resection samples, 58 matched pre-NAC biopsy samples were available for paired comparisons. Using multiplex immunofluorescence, we characterized TRM cells (CD103+CD8+) and four heterogeneous TRM subsets, including naive TRM1 (PD-1-Tim-3-), pre-exhausted TRM2 (PD-1+Tim-3-), TRM3 (PD-1-Tim-3+), and terminally exhausted TRM4 (PD-1+Tim-3+). Cell density, cytotoxicity, and two spatial features were defined to evaluate the effect of NAC on TRM subsets. RESULTS: The cell densities, infiltration scores, and cancer-cell proximity scores of TRM cells, especially TRM1&2 subsets, were significantly increased after NAC and associated with better prognosis of patients. In Contrast, no significant change was observed in the TRM4 subset, which was associated with poor prognosis. Besides, the cytotoxicity of TRM subsets was unaltered after NAC. Compared with patients without major pathologic response (MPRs), patients with MPR had higher densities of TRM1&2 subsets and higher cancer-cell proximity scores of TRM2&3 subsets. Furthermore, increased density of CD31 + cancer microvessels was positively associated with both TRM and Tnon-RM cells after NAC. CONCLUSIONS: NAC may remodel the cell density and spatial distribution of TRM subsets, which is associated with favorable therapeutic effect and prognosis in patients with NSCLC.

Computed tomography-based radiomics and clinical-genetic features for brain metastasis prediction in patients with stage III/IV epidermal growth factor receptor-mutant non-small-cell lung cancer.

PURPOSE: To evaluate the value of computed tomography (CT)-based radiomics combined with clinical-genetic features in predicting brain metastasis in patients with stage III/IV epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancer (NSCLC). METHODS: The study included 147 eligible patients treated at our institution between January 2018 and May 2021. Patients were randomly divided into two cohorts for model training (n = 102) and validation (n = 45). Radiomics features were extracted from the chest CT images before treatment, and a radiomics signature was constructed using the Least Absolute Shrinkage and Selection Operator regression. Kaplan-Meier survival analysis was used to describe the differences in brain metastasis-free survival (BM-FS) risk. A clinical-genetic model was developed using Cox regression analysis. Radiomics, genetic, and combined prediction models were constructed, and their predictive performances were evaluated by the concordance index (C-index). RESULTS: Patients with a low radiomics score had significantly longer BM-FS than those with a high radiomics score in both the training (p < 0.0001) and the validation (p = 0.0016) cohorts. The C-indices of the nomogram, which combined the radiomics signature and N stage, overall stage, third-generation tyrosine kinase inhibitor treatment, and EGFR mutation status, were 0.886 (95% confidence interval [CI] 0.823-0.949) and 0.811 (95% CI 0.719-0.903) in the training and validation cohorts, respectively. The combined model achieved a higher discrimination and clinical utility than the single prediction models. CONCLUSIONS: The combined radiomics-genetic model could be used to predict BM-FS in stage III/IV NSCLC patients with EGFR mutations.

The hybrid operation based on microsurgery assisted by intraoperative spinal angiography in patients with spinal dural arteriovenous fistula: a series of 45 cases from multicenter research.

BACKGROUND: To assess the clinical effects of hybrid surgery, which includes spinal angiography-assisted microsurgery, in the treatment of spinal dural arteriovenous fistulas (SDAVF). METHODS: We retrospectively reviewed 45 patients who underwent hybrid Spinal dural arteriovenous fistula (SDAVF) resection between September 2019 and June 2022. The hybrid surgery involved intraoperative digital subtraction angiography (DSA) of the spinal vessels to determine the source of the blood-supplying artery, location of the fistula and draining vein, indocyanine green fluorescence (ICG)-assisted microsurgical resection of the fistula, and postoperative DSA to verify therapeutic efficacy. The Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Visual Analog Scale (VAS), Barthel score, modified Rankin Scale (mRS) and modified Aminoff-Logue score (key indicator) were used to assess the clinical effects of SDAVF resection. RESULTS: A series of 45 patients with SDAVF were successfully treated with hybrid surgery without fistula recurrence. There were no intraoperative complications related to spinal angiography, and none of the patients died. Postoperatively, two patients experienced clinical deterioration of spinal cord function, which manifested as bilateral lower extremity paralysis and bladder sphincter dysfunction. Postoperatively, improvement in mALS scores was observed in 16 cases (35.6%) within 1-2 days, 12 cases (26.7%) at 1 week, and 7 cases (15.6%) at 6 months. No SDAVF recurrence was detected in the spinal MRA examination 6 months after surgery. When compared with preoperative mALS scores, 35 cases (77.8%) showed significant improvement in symptoms, 8 cases (17.8%), remained unchanged, and 2 cases (4.4%) deteriorated. Compared with the preoperative scores, the postoperative mALS score was significantly decreased [postoperative vs. preoperative: 2(1,3) vs. 3(2,4)], HAMD score [(12.2 ± 5.5) vs. (19.6 ± 6.3)], HAMA score [(15.6 ± 5.5) vs. (20.5 ± 6.5)], and VAS score [3(2,5) vs. 5(4,8)]. Conversely, Barthel scoresshowed significant increase [(74.6 ± 8.7) vs. (67.8 ± 9.2)] (P < 0.05). However, the mRS scores were lower than preoperatively [1(1,2) vs. 2(1,2.5)], but the difference was not statistically significant (P > 0.05). There was a significant increase in "good" neurological outcomes at follow-up compared with preoperative function (62.2% vs. 33.3%) (P = 0.023). CONCLUSION: Hybrid surgery is a safe and effective treatment for patients with SAVF, which is beneficial for improving anxiety, depression, spinal cord, and neurological function, and relieving pain. However, the treatment of patients with SDAVF is a complex, long-term process requiring further multidisciplinary interventions, including clinical care, psychosocial interventions, and neurorehabilitation.

Modified spatial architecture of regulatory T cells after neoadjuvant chemotherapy in non-small cell lung cancer patients.

It is crucial to decipher the modulation of regulatory T cells (Tregs) in tumor microenvironment (TME) induced by chemotherapy, which may contribute to improving the efficacy of neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer (NSCLC). We retrospectively collected specimens from patients with II-III NSCLC, constituting two cohorts: a neoadjuvant chemotherapy (NAC) cohort (N = 141) with biopsy (N = 58) and postoperative specimens (N = 141), and a surgery-only cohort (N = 122) as the control group. Then, the cell density (Dens), infiltration score (InS), and Treg-cell proximity score (TrPS) were conducted using a panel of multiplex fluorescence staining (Foxp3, CD4, CD8, CK, CD31, ɑSMA). Subsequently, the association of Tregs with cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) was analyzed. Patients with NAC treatment have a higher density of Tregs in both paired (P < 0.001) and unpaired analysis (P = 0.022). Additionally, patients with NAC treatment showed higher infiltration score (paired, P < 0.001; unpaired, P = 0.014) and more CD8+T cells around Tregs (paired/unpaired, both P < 0.001). Subgroup analysis indicated that tumors with a diameter of ≤ 5 cm exhibited increase in both Dens(Treg) and InS(Treg), and gemcitabine, pemetrexed and taxel enhanced Dens(Treg) and TrPS(CD8) following NAC. Multivariate analysis identified that the Dens(Tregs), InS(Tregs) and TrPS(CD8) were significantly associated with better chemotherapy response [OR = 8.54, 95%CI (1.69, 43.14), P = 0.009; OR = 7.14, 95%CI (1.70, 30.08), P = 0.024; OR = 5.50, 95%CI (1.09, 27.75), P = 0.039, respectively] and positive recurrence-free survival [HR = 3.23, 95%CI (1.47, 7.10), P = 0.004; HR = 2.70; 95%CI (1.27, 5.72); P = 0.010; HR = 2.55, 95%CI (1.21, 5.39), P = 0.014, respectively]. Moreover, TrPS(CD8) and TrPS(CD4) were negatively correlated with the CMVs and CAFs. These discoveries have deepened our comprehension of the immune-modulating impact of chemotherapy and underscored that the modified spatial landscape of Tregs after chemotherapy should be taken into account for personalized immunotherapy, aiming to ultimately improve clinical outcomes in patients with NSCLC.

Dysfunction of CD8+ T cells around tumor cells leads to occult lymph node metastasis in NSCLC patients.

Occult lymph node metastasis (OLNM) is one of the main causes of regional recurrence in inoperable N0 non-small cell lung cancer (NSCLC) patients following stereotactic ablation body radiotherapy (SABR) treatment. The integration of immunotherapy and SABR (I-SABR) has shown preliminary efficiency in mitigating this recurrence. Therefore, it is necessary to explore the functional dynamics of critical immune effectors, particularly CD8+ T cells in the development of OLNM. In this study, tissue microarrays (TMAs) and multiplex immunofluorescence (mIF) were used to identify CD8+ T cells and functional subsets (cytotoxic CD8+ T cells/predysfunctional CD8+ T cells (CD8+ Tpredys)/dysfunctional CD8+ T cells (CD8+ Tdys)/other CD8+ T cells) among the no lymph node metastasis, OLNM, and clinically evident lymph node metastasis (CLNM) groups. As the degree of lymph node metastasis escalated, the density of total CD8+ T cells and CD8+ Tdys cells, as well as their proximity to tumor cells, increased progressively and remarkably in the invasive margin (IM). In the tumor center (TC), both the density and proximity of CD8+ Tpredys cells to tumor cells notably decreased in the OLNM group compared with the group without metastasis. Furthermore, positive correlations were found between the dysfunction of CD8+ T cells and HIF-1α+CD8 and cancer microvessels (CMVs). In conclusion, the deterioration in CD8+ T cell function and interactive dynamics between CD8+ T cells and tumor cells play a vital role in the development of OLNM in NSCLC. Strategies aimed at improving hypoxia or targeting CMVs could potentially enhance the efficacy of I-SABR.

Characterizing Edible Oils by Oblique-Incidence Reflectivity Difference Combined with Machine Learning Algorithms.

Due to the significant price differences among different types of edible oils, expensive oils like olive oil are often blended with cheaper edible oils. This practice of adulteration in edible oils, aimed at increasing profits for producers, poses a major concern for consumers. Furthermore, adulteration in edible oils can lead to various health issues impacting consumer well-being. In order to meet the requirements of fast, non-destructive, universal, accurate, and reliable quality testing for edible oil, the oblique-incidence reflectivity difference (OIRD) method combined with machine learning algorithms was introduced to detect a variety of edible oils. The prediction accuracy of Gradient Boosting, K-Nearest Neighbor, and Random Forest models all exceeded 95%. Moreover, the contribution rates of the OIRD signal, DC signal, and fundamental frequency signal to the classification results were 45.7%, 34.1%, and 20.2%, respectively. In a quality evaluation experiment on olive oil, the feature importance scores of three signals reached 63.4%, 18.9%, and 17.6%. The results suggested that the feature importance score of the OIRD signal was significantly higher than that of the DC and fundamental frequency signals. The experimental results indicate that the OIRD method can serve as a powerful tool for detecting edible oils.

Cloning, Expression, and Functional Characterization of Two Highly Efficient Flavonoid-di-O-glycosyltransferases ZmUGT84A1 and ZmUGT84A2 from Maize (Zea mays L.).

The maize (Zea mays L.) glycosyltransferase family 1 comprises many uridine diphosphate glycosyltransferase (UGT) members. However, UGT activities and biochemical functions have seldom been revealed. In this study, the genes of two flavonoid di-O-glycosyltransferases ZmUGT84A1 and ZmUGT84A2 were cloned from maize plant and expressed in Escherichia coli. Phylogenetic analysis showed that the two enzymes were homologous to AtUGT84A1 and AtUGT84A3. The two recombinant enzymes showed a high conversion rate of luteolin to its glucosides, mainly 4',7-di-O-glucoside and minorly 3',7-di-O-glucoside in two-step glycosylation reactions in vitro. Moreover, the recombinant ZmUGT84A1 and ZmUGT84A2 had a broad substrate spectrum, converting eriodictyol, naringenin, apigenin, quercetin, and kaempferol to monoglucosides and diglucosides. The highly efficient ZmUGT84A1 and ZmUGT84A2 may be used as a tool for the effective synthesis of various flavonoid O-glycosides and as markers for crop breeding to increase O-glycosyl flavonoid content in food.

Clinical characteristics and MRI based radiomics nomograms can predict iPFS and short-term efficacy of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma with brain metastases.

BACKGROUND: Predicting short-term efficacy and intracranial progression-free survival (iPFS) in epidermal growth factor receptor gene mutated (EGFR-mutated) lung adenocarcinoma patients with brain metastases who receive third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapy was of great significance for individualized treatment. We aimed to construct and validate nomograms based on clinical characteristics and magnetic resonance imaging (MRI) radiomics for predicting short-term efficacy and intracranial progression free survival (iPFS) of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma patients with brain metastases. METHODS: One hundred ninety-four EGFR-mutated lung adenocarcinoma patients with brain metastases who received third-generation EGFR-TKI treatment were included in this study from January 1, 2017 to March 1, 2023. Patients were randomly divided into training cohort and validation cohort in a ratio of 5:3. Radiomics features extracted from brain MRI were screened by least absolute shrinkage and selection operator (LASSO) regression. Logistic regression analysis and Cox proportional hazards regression analysis were used to screen clinical risk factors. Single clinical (C), single radiomics (R), and combined (C + R) nomograms were constructed in short-term efficacy predicting model and iPFS predicting model, respectively. Prediction effectiveness of nomograms were evaluated by calibration curves, Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Kaplan-Meier analysis was used to compare the iPFS of high and low iPFS rad-score patients in the predictive iPFS R model and to compare the iPFS of high-risk and low-risk patients in the predictive iPFS C + R model. RESULTS: Overall response rate (ORR) was 71.1%, disease control rate (DCR) was 91.8% and median iPFS was 12.67 months (7.88-20.26, interquartile range [IQR]). There were significant differences in iPFS between patients with high and low iPFS rad-scores, as well as between high-risk and low-risk patients. In short-term efficacy model, the C-indexes of C + R nomograms in training cohort and validation cohort were 0.867 (0.835-0.900, 95%CI) and 0.803 (0.753-0.854, 95%CI), while in iPFS model, the C-indexes were 0.901 (0.874-0.929, 95%CI) and 0.753 (0.713-0.793, 95%CI). CONCLUSIONS: The third-generation EGFR-TKI showed significant efficacy in EGFR-mutated lung adenocarcinoma patients with brain metastases, and the combined line plot of C + R can be utilized to predict short-term efficacy and iPFS.

Spatial features of specific CD103+CD8+ tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer.

BACKGROUND: Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it. METHODS: Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). RESULTS: The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1-Tim-3-TRM), TRM2 (PD-1+Tim-3-TRM), TRM3 (PD-1-Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63-3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells. CONCLUSIONS: These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.

The analysis of multiple omics and examination of pathological images revealed the prognostic and therapeutic significances of CD93 in lung squamous cell carcinoma.

As a potent pro-angiogenic factor, the role of CD93 in the prognosis and therapeutic outcomes of lung squamous cell carcinoma (LUSC) merits exploration. In this study, we systematically collected transcriptomic, genomic, and clinical data from various public databases, as well as pathological images from hospital-operated patients. Employing statistical analysis software like R (Version 4.2.2) and GraphPad (Version 8.0), we conducted comprehensive analyses of multi-omics data. The results revealed elevated CD93 expression in LUSC tissues, closely associated with various cancer-related pathways. High CD93 expression indicated advanced clinical stage and poorer prognosis. Furthermore, CD93 contributed to resistance against chemotherapy and immunotherapy by enhancing tumor cell stemness, reducing immune cell infiltration, and inducing T cell exhaustion. Patients with low CD93 expression exhibited higher response rates to both chemotherapy and immunotherapy. Immunohistochemistry validated the significance of CD93 in LUSC. CD93 emerges as a biomarker signaling unfavorable prognosis and influencing therapeutic outcomes, suggesting a potential LUSC treatment avenue.

Body Composition and Radiomics From 18 F-FDG PET/CT Together Help Predict Prognosis for Patients With Stage IV Non-Small Cell Lung Cancer.

PURPOSE: To determine whether integration of data on body composition and radiomic features obtained using baseline 18 F-FDG positron emission tomography/computed tomography (PET/CT) images can be used to predict the prognosis of patients with stage IV non-small cell lung cancer (NSCLC). METHODS: A total of 107 patients with stage IV NSCLC were retrospectively enrolled in this study. We used the 3D Slicer (The National Institutes of Health, Bethesda, Maryland) software to extract the features of PET and CT images. Body composition measurements were taken at the L3 level using the Fiji (Curtis Rueden, Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison) software. Independent prognostic factors were defined by performing univariate and multivariate analyses for clinical factors, body composition features, and metabolic parameters. Data on body composition and radiomic features were used to build body composition, radiomics, and integrated (combination of body composition and radiomic features) nomograms. The models were evaluated to determine their prognostic prediction capabilities, calibration, discriminatory abilities, and clinical applicability. RESULTS: Eight radiomic features relevant to progression-free survival (PFS) were selected. Multivariate analysis showed that the visceral fat area/subcutaneous fat area ratio independently predicted PFS ( P = 0.040). Using the data for body composition, radiomic features, and integrated features, nomograms were established for the training (areas under the curve = 0.647, 0.736, and 0.803, respectively) and the validation sets (areas under the receiver operating characteristic = 0.625, 0.723, and 0.866, respectively); the integrated model showed better prediction ability than that of the other 2 models. The calibration curves revealed that the integrated nomogram exhibited a better agreement between the estimation and the actual observation in terms of prediction of the probability of PFS than that of the other 2 models. Decision curve analysis revealed that the integrated nomogram was superior to the body composition and radiomics nomograms for predicting clinical benefit. CONCLUSION: Integration of data on body composition and PET/CT radiomic features can help in prediction of outcomes in patients with stage IV NSCLC.

Open spina bifida characterisation in a dog foetus.

BACKGROUND: Open spina bifida is an uncommon malformation in animals, and there is a lack of imaging, clinical, and pathological characterisation of this condition in dogs. OBJECTIVE: Open spina bifida is rarely observed in animals due to high levels of perinatal mortality and frequent euthanasia. To the best of our knowledge, we present the first case of spina bifida in a dog was diagnosed in-utero and then followed post-partum. METHODS: A 3-year-old Poodle was presented with twin pregnancy. Radiographic and ultrasonographic findings were suggestive of vertebral malformation and open spina bifida with myelomeningocele in one foetus. Conservative treatment was given but the puppy died 3 days after birth. Thereafter, anatomical and histopathological analysis of several organs was performed to characterise the disease. RESULTS: When the twins were born, one puppy had a linear dorsal midline cutaneous defect extending from the level of vertebrae L2-L6. R Radiographic examination showed several congenital vertebral malformations involving the thoracic segment, lumbar segment, sacrum and scapula. Histopathological examinations confirmed the presence of open spina bifida and identified additional abnormalities in several internal organs. CONCLUSIONS: This case presents a complete characterisation of open spina bifida, before birth and after death, using imaging and histopathology techniques.

18F-FDG PET/CT radiomics for prediction of lymphovascular invasion in patients with early stage non-small cell lung cancer.

Objective: To explore a prediction model for lymphovascular invasion (LVI) on cT1-2N0M0 radiologic solid non-small cell lung cancer (NSCLC) based on a 2-deoxy-2[18F]fluoro-D-glucose ([18F]F-FDG) positron emission tomography-computed tomography (PET-CT) radiomics analysis. Methods: The present work retrospectively included 148 patients receiving surgical resection and verified pathologically with cT1-2N0M0 radiologic solid NSCLC. The cases were randomized into training or validation sets in the ratio of 7:3. PET and CT images were used to select optimal radiomics features. Three radiomics predictive models incorporating CT, PET, as well as PET/CT images radiomics features (CT-RS, PET-RS, PET/CT-RS) were developed using logistic analyses. Furthermore, model performance was evaluated by ROC analysis for predicting LVI status. Model performance was evaluated in terms of discrimination, calibration along with clinical utility. Kaplan-Meier curves were employed to analyze the outcome of LVI. Results: The ROC analysis demonstrated that PET/CT-RS (AUCs were 0.773 and 0.774 for training and validation sets) outperformed both CT-RS(AUCs, 0.727 and 0.752) and PET-RS(AUCs, 0.715 and 0.733). A PET/CT radiology nomogram (PET/CT-model) was developed to estimate LVI; the model demonstrated conspicuous prediction performance for training (C-index, 0.766; 95%CI, 0.728-0.805) and validation sets (C-index, 0.774; 95%CI, 0.702-0.846). Besides, decision curve analysis and calibration curve showed that PET/CT-model provided clinically beneficial effects. Disease-free survival and overall survival varied significantly between LVI and non-LVI cases (P<0.001). Conclusions: The PET/CT radiomics models could effectively predict LVI on early stage radiologic solid lung cancer and provide support for clinical treatment decisions.

18F-FDG PET/CT radiomics predicts brain metastasis in I-IIIA resected Non-Small cell lung cancer.

OBJECTIVE: To establish 18F-FDG PET/CT radiomics model for predicting brain metastasis in non-small cell lung cancer (NSCLC) patients. METHODS: This research comprised 203 NSCLC patients who had received surgical therapy at two institutions. To identify independent predictive factors of brain metastasis, metabolic indicators, CT features, and clinical features were investigated. A prediction model was established by incorporating radiomics signature and clinicopathological risk variables. The suggested model's performance was assessed from the perspective of discrimination, calibration, and clinical application. RESULTS: The C-indices of the PET/CT radiomics model in the training, internal validation, and external validation cohorts were 0.911, 0.825 and 0.800, respectively. According to the multivariate analysis, neuron-specific enolase (NSE) and air bronchogram were independent risk factors for brain metastasis (BM). Furthermore, the combined model integrating radiomics and clinicopathological characteristics related to brain metastasis performed better in terms of prediction, with C-indices of 0.927, 0.861, and 0.860 in the training, internal validation, and external validation cohorts, respectively. The decision curve analysis (DCA) suggested that the PET/CT nomogram was clinically beneficial. CONCLUSIONS: A predictive algorithm based on PET/CT imaging information and clinicopathological features may accurately predict the probability of brain metastasis in NSCLC patients following surgery. This presented doctors with a unique technique for screening NSCLC patients at high risk of brain metastasis.

Efficacy and safety of immunoradiotherapy for advanced non-small cell lung cancer: a retrospective comparative cohort study.

Background: Treatment of radiotherapy (RT) combined with immune checkpoint inhibitor (ICI) may remarkably improve the prognosis in patients with metastatic non-small cell lung cancer (NSCLC). However, the treatment time of RT, irradiated lesion and the optimum combined scheme, have not been fully determined. Methods: Data regarding overall survival (OS), progression-free survival (PFS), treatment response, and adverse events of 357 patients with advanced NSCLC treated with ICI alone or in combination with RT prior to/during ICI treatment were retrospectively collected. Additionally, subgroup analyses for radiation dose, time interval between RT and immunotherapy, and number of irradiated lesions were performed. Results: Median PFS of the ICI alone and ICI + RT groups was 6 and 12 months, respectively (P<0.0001). The objective response rate (ORR) and disease control rate (DCR) were significantly higher in the ICI + RT group than in the ICI alone group (P=0.014; P=0.015, respectively). However, OS, the distant response rate (DRR), and the distant control rate (DCRt) did not differ significantly between the groups. Out-of-field DRR and DCRt were defined in unirradiated lesions only. Compared with RT application prior to ICI, its application concomitant with ICI led to higher DRR (P=0.018) and DCRt (P=0.002). Subgroup analyses revealed that single-site, high biologically effective dose (BED) (≥72 Gy), planning target volume (PTV) size (<213.7 mL) RT groups had better PFS. In multivariate analysis, PTV volume [≥213.7 vs. <213.7 mL: hazard ratio (HR), 1.89; 95% confidence interval (CI): 1.04-3.42; P=0.035] was an independent predictor of immunotherapy PFS. Additionally, radio-immunotherapy increased the incidence rate of grade 1-2 immune-related pneumonitis compared with ICI alone. Conclusions: Combination therapy using ICIs and radiation may improve PFS and tumor response rates in advanced NSCLC patients regardless of programmed cell death 1 ligand 1 (PD-L1) level or previous treatments. However, it may increase the incidence of immune-related pneumonitis.

Characterization and clinical verification of immune-related genes in hepatocellular carcinoma to aid prognosis evaluation and immunotherapy.

BACKGROUND: Immune-related genes (IRGs) have been confirmed to play an important role in tumorigenesis and tumor microenvironment formation in hepatocellular carcinoma (HCC). We investigated how IRGs regulates the HCC immunophenotype and thus affects the prognosis and response to immunotherapy. METHODS: We investigated RNA expression of IRGs and developed an immune-related genes-based prognostic index (IRGPI) in HCC samples. Then, the influence of the IRGPI on the immune microenvironment was comprehensively analysed. RESULTS: According to IRGPI, HCC patients are divided into two immune subtypes. A high IRGPI was characterized by an increased tumor mutation burden (TMB) and a poor prognosis. More CD8 + tumor infiltrating cells and expression of PD-L1 were observed in low IRGPI subtypes. Two immunotherapy cohorts confirmed patients with low IRGPI demonstrated significant therapeutic benefits. Multiplex immunofluorescence staining determined that there were more CD8 + T cells infiltrating into tumor microenvironment in IRGPI-low groups, and the survival time of these patients was longer. CONCLUSIONS: This study demonstrated that the IRGPI serve as a predictive prognostic biomarker and potential indicator for immunotherapy.