Unlocking the full potential of mesenchymal stromal cell therapy for osteoarthritis through machine learning-based in silico trials.

Despite the potential of mesenchymal stromal cells (MSCs) in osteoarthritis (OA) treatment, the challenge lies in addressing their therapeutic inconsistency. Clinical trials revealed significantly varied therapeutic outcomes among patients receiving the same allogenic MSCs but different treatment regimens. Therefore, optimizing personalized treatment strategies is crucial to fully unlock MSCs' potential and enhance therapeutic consistency. We employed the XGBoost algorithm to train a self-collected database comprising 37 published clinical reports to create a model capable of predicting the probability of effective pain relief and Western Ontario and McMaster Universities (WOMAC) index improvement in OA patients undergoing MSC therapy. Leveraging this model, extensive in silico simulations were conducted to identify optimal personalized treatment strategies and ideal patient profiles. Our in silico trials predicted that the individually optimized MSC treatment strategies would substantially increase patients' chances of recovery compared to the strategies used in reported clinical trials, thereby potentially benefiting 78.1%, 47.8%, 94.4% and 36.4% of the patients with ineffective short-term pain relief, short-term WOMAC index improvement, long-term pain relief and long-term WOMAC index improvement, respectively. We further recommended guidelines on MSC number, concentration, and the patients' appropriate physical (body mass index, age, etc.) and disease states (Kellgren-Lawrence grade, etc.) for OA treatment. Additionally, we revealed the superior efficacy of MSC in providing short-term pain relief compared to platelet-rich plasma therapy for most OA patients. This study represents the pioneering effort to enhance the efficacy and consistency of MSC therapy through machine learning applied to clinical data. The in silico trial approach holds immense potential for diverse clinical applications.

Prognostic significance of collagen signatures in pancreatic ductal adenocarcinoma obtained from second-harmonic generation imaging.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) ranks among the deadliest types of cancer, and it will be meaningful to search for new biomarkers with prognostic value to help clinicians tailor therapeutic strategies. METHODS: Here we tried to use an advanced optical imaging technique, multiphoton microscopy (MPM) combining second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) imaging, for the label-free detection of PDAC tissues from a cohort of 149 patients. An automated image processing method was used to extract collagen features from SHG images and the Kaplan-Meier survival analysis and Cox proportional hazards regression were used to assess the prognostic value of collagen signatures. RESULTS: SHG images clearly show the different characteristics of collagen fibers in tumor microenvironment. We gained eight collagen morphological features, and a Feature-score was derived for each patient by the combination of these features using ridge regression. Statistical analyses reveal that Feature-score is an independent factor, and can predict the overall survival of PDAC patients as well as provide well risk stratification. CONCLUSIONS: SHG imaging technique can potentially be a tool for the accurate diagnosis of PDAC, and this optical biomarker (Feature-score) may help clinicians make more approximate treatment decisions.

Rapid and label-free detection of gastrointestinal stromal tumor via a combination of two-photon microscopy and imaging analysis.

BACKGROUND: Gastrointestinal stromal tumor (GIST) is currently regarded as a potentially malignant tumor, and early diagnosis is the best way to improve its prognosis. Therefore, it will be meaningful to develop a new method for auxiliary diagnosis of this disease. METHODS: Here we try out a new means to detect GIST by combining two-photon imaging with automatic image processing strategy. RESULTS: Experimental results show that two-photon microscopy has the ability to label-freely identify the structural characteristics of GIST such as tumor cells, desmoplastic reaction, which are entirely different from those from gastric adenocarcinoma. Moreover, an image processing approach is used to extract eight collagen morphological features from tumor microenvironment and normal muscularis, and statistical analysis demonstrates that there are significant differences in three features-fiber area, density and cross-link density. The three morphological characteristics may be considered as optical imaging biomarkers to differentiate between normal and abnormal tissues. CONCLUSION: With continued improvement and refinement of this technology, we believe that two-photon microscopy will be an efficient surveillance tool for GIST and lead to better management of this disease.

Association of the collagen signature with pathological complete response in rectal cancer patients.

Collagen in the tumor microenvironment is recognized as a potential biomarker for predicting treatment response. This study investigated whether the collagen features are associated with pathological complete response (pCR) in locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (nCRT) and develop and validate a prediction model for individualized prediction of pCR. The prediction model was developed in a primary cohort (353 consecutive patients). In total, 142 collagen features were extracted from the multiphoton image of pretreatment biopsy, and the least absolute shrinkage and selection operator (Lasso) regression was applied for feature selection and collagen signature building. A nomogram was developed using multivariable analysis. The performance of the nomogram was assessed with respect to its discrimination, calibration, and clinical utility. An independent cohort (163 consecutive patients) was used to validate the model. The collagen signature comprised four collagen features significantly associated with pCR both in the primary and validation cohorts (p < 0.001). Predictors in the individualized prediction nomogram included the collagen signature and clinicopathological predictors. The nomogram showed good discrimination with area under the ROC curve (AUC) of 0.891 in the primary cohort and good calibration. Application of the nomogram in the validation cohort still gave good discrimination (AUC = 0.908) and good calibration. Decision curve analysis demonstrated that the nomogram was clinically useful. In conclusion, the collagen signature in the tumor microenvironment of pretreatment biopsy is significantly associated with pCR. The nomogram based on the collagen signature and clinicopathological predictors could be used for individualized prediction of pCR in LARC patients before nCRT.

Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer.

BACKGROUND: Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients. METHODS: In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS). RESULTS: TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts). CONCLUSION: These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients.

BACKGROUND: The relationship between collagen features (CFs) in the tumor microenvironment and the treatment response to neoadjuvant chemoradiotherapy (nCRT) is still unknown. This study aimed to develop and validate a perdition model based on the CFs and clinicopathological characteristics to predict the treatment response to nCRT among locally advanced rectal cancer (LARC) patients. METHODS: In this multicenter, retrospective analysis, 428 patients were included and randomly divided into a training cohort (299 patients) and validation cohort (129 patients) [7:3 ratio]. A total of 11 CFs were extracted from a multiphoton image of pretreatment biopsy, and a support vector machine (SVM) was then used to construct a CFs-SVM classifier. A prediction model was developed and presented with a nomogram using multivariable analysis. Further validation of the nomogram was performed in the validation cohort. RESULTS: The CFs-SVM classifier, which integrated collagen area, straightness, and crosslink density, was significantly associated with treatment response. Predictors contained in the nomogram included the CFs-SVM classifier and clinicopathological characteristics by multivariable analysis. The CFs nomogram demonstrated good discrimination, with area under the receiver operating characteristic curves (AUROCs) of 0.834 in the training cohort and 0.854 in the validation cohort. Decision curve analysis indicated that the CFs nomogram was clinically useful. Moreover, compared with the traditional clinicopathological model, the CFs nomogram showed more powerful discrimination in determining the response to nCRT. CONCLUSIONS: The CFs-SVM classifier based on CFs in the tumor microenvironment is associated with treatment response, and the CFs nomogram integrating the CFs-SVM classifier and clinicopathological characteristics is useful for individualized prediction of the treatment response to nCRT among LARC patients.

Association of the Collagen Signature in the Tumor Microenvironment With Recurrence and Survival of Patients With T4N0M0 Colon Cancer.

BACKGROUND: The current clinicopathological risk factors do not accurately predict disease recurrence in patients with T4N0M0 colon cancer. We hypothesized that the collagen signature combined with clinicopathological risk factors (new model) had a better prognostic value than clinicopathological risk factors alone (clinicopathological model). OBJECTIVE: This study aimed to establish a collagen signature in the tumor microenvironment and to validate its role in predicting the recurrence of T4N0M0 colon cancer. DESIGN: This was a retrospective study. SETTINGS: This study took place at a tertiary medical center. PATIENTS: Patients with T4N0M0 colon cancer who underwent surgery at our center between 2009 and 2015 (n = 416) were included. INTERVENTION: A total of 142 collagen features were analyzed in the tumor microenvironment in specimens of colon cancer by using second-harmonic generation imaging. A collagen signature was constructed using a least-absolute shrinkage and selection operator Cox regression model. MAIN OUTCOME MEASURES: The primary outcomes measured were disease-free survival and overall survival. RESULTS: The training and testing cohorts consisted of 291 and 125 randomly assigned samples, with recurrence rates of 19.9% and 22.4%. A 3-feature-based collagen signature predicted the recurrence risk at 1, 3, and 5 years, with the area under the receiver-operating characteristic curves of 0.808, 0.832, and 0.791 in the training cohort and 0.836, 0.807, and 0.794 in the testing cohort. Multivariate analysis revealed that the collagen signature could independently predict the disease-free survival (HR = 7.17, p < 0.001) and overall survival rates (HR = 5.03, p < 0.001). The new model had a better prognostic value than the clinicopathological model, which included 4 clinicopathological risk factors: obstruction or perforation, lymphovascular invasion, tumor budding, and no chemotherapy. LIMITATIONS: This study was limited by its retrospective design. CONCLUSIONS: The collagen signature in the tumor microenvironment may be a new prognostic marker that can effectively predict the recurrence and survival of patients with T4N0M0 colon cancer. See Video Abstract at http://links.lww.com/DCR/B503. ASOCIACIÓN DE LA RÚBRICA DE COLÁGENO EN EL MICROAMBIENTE TUMORAL CON LA RECIDIVA Y LA SOBREVIDA DE PACIENTES CON CÁNCER DE COLON T4N0M0: Los factores de riesgo clínico-patológicos actuales no predicen con precisión la recurrencia de la enfermedad en pacientes con cáncer de colon estadío T4N0M0. Presumimos que la rúbrica de colágeno combinada con factores de riesgo clínico-patológicos (nuevo modelo) tendrían un mejor valor pronóstico que los factores de riesgo clínico-patológicos solos (modelo clínico-patológico).El establecer una rúbrica de colágeno en el microambiente tumoral y validar su papel en la predicción de la recidiva del cáncer de colon T4N0M0.Estudio retrospectivo.Investigación llevada a cabo en un centro médico terciario.Se incluyeron pacientes con cáncer de colon T4N0M0 operados en nuestro centro entre 2009 y 2015 (n = 416).Se analizaron un total de 142 características de colágeno en el microambiente tumoral en muestras de cáncer de colon utilizando imágenes de segunda generación armónica. Se construyó una rúbrica de colágeno utilizando un modelo de regresión LASSO Cox.Sobrevida libre de enfermedad y sobrevida global.Las cohortes de entrenamiento y prueba consistieron en 291 y 125 muestras asignadas al azar, con tasas de recurrencia del 19,9% y 22,4%, respectivamente. La rúbrica del colágeno basada en 3 características predijo el riesgo de recurrencia a 1, 3 y 5 años, con el área bajo las curvas características operativas del receptor de 0,808, 0,832 y 0,791 en la cohorte de entrenamiento y 0,836, 0,807 y 0,794 en la cohorte de prueba, respectivamente. El análisis multivariado reveló que la firma de colágeno podría predecir de forma independiente la supervivencia libre de enfermedad (HR = 7,17, p <0,001) y las tasas de sobrevida general (HR = 5,03, p <0,001). El nuevo modelo tuvo un mejor valor pronóstico que el modelo clínico-patológico, que incluyó cuatro factores de riesgo clínico-patológicos: obstrucción o perforación, invasión linfovascular, gemación tumoral y ausencia de quimioterapia.Este estudio estuvo limitado por su diseño retrospectivo.La rúbrica de colágeno en el microambiente tumoral puede ser un nuevo marcador pronóstico para predecir eficazmente la recurrencia y la subrevida de los pacientes con cáncer de colon T4N0M0. Consulte Video Resumen en http://links.lww.com/DCR/B503. (Traducción-Dr. Xavier Delgadillo).

Computer-aided assessment of the chemokine receptors CXCR3, CXCR4 and CXCR7 expression in gallbladder carcinoma.

Gallbladder carcinoma (GBC) is a vicious and invasive disease. The major challenge in the clinical treatment of GBC is the lack of a suitable prognosis method. Chemokine receptors such as CXCR3, CXCR4 and CXCR7 play vital roles in the process of tumour progression and metastasis. Their expression levels and distribution are proven to be indicative of the progression of GBC, but are hard to be decoded by conventional pathological methods, and therefore, not commonly used in the prognosis of GBC. In this study, we developed a computer-aided image analysis method, which we used to quantitatively measure the expression levels of CXCR3, CXCR4 and CXCR7 in the nuclei and cytoplasm of glandular and interstitial cells from a cohort of 55 GBC patients. We found that CXCR3, CXCR4 and CXCR7 expressions are associated with the clinicopathological variables of GBC. Cytoplasmic CXCR3, nuclear CXCR7 and cytoplasmic CXCR7 were significant predictive factors of histology invasion, whereas cytoplasmic CXCR4 and nuclear CXCR4 were significantly correlated with T and N stage and were associated with the overall survival and disease-free survival. These results suggest that the quantification and localisation of CXCR3, CXCR4 and CXCR7 expressions in different cell types should be considered using computer-aided assessment to improve the accuracy of prognosis in GBC.

Nodal grouping in nasopharyngeal carcinoma: prognostic significance, N classification, and a marker for the identification of candidates for induction chemotherapy.

OBJECTIVES: This study aimed to evaluate the value of nodal grouping (NG), defined as the presence of at least three contiguous lymph nodes (LNs) within one LN region, in staging and management of patients with non-metastatic nasopharyngeal carcinoma (NPC). METHODS: MR images were reviewed to evaluate LN variables, including NG. The Kaplan-Meier method and multivariate Cox regression models evaluated the association between the variables and survival. Harrell's concordance index (C-index) was used to measure the performance of prognostic models. The outcome of induction chemotherapy (IC) in patients with and without NG was compared using matched-pair analysis. RESULTS: In 1224 patients enrolled, NG was found to be an independent prognostic factor for overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and regional recurrence-free survival. The hazard ratio and 95% confidence interval (CI) of NG for OS (3.86, 2.09-7.12) were higher than those of stage N2 (3.54, 1.89-6.70). On upgrading patients with NG from stages N1 to N2, the revised N staging yielded a higher C-index compared to the American Joint Committee on Cancer system in predicting PFS (0.664 vs. 0.658, p = 0.022) and DMFS (0.699 vs. 0.690, p = 0.005). Results of the matched-pair analysis revealed that for patients with NG in stages N1 and N2, IC was correlated with improved OS (p = 0.022), PFS (p = 0.007), and DMFS (p = 0.021). CONCLUSIONS: NG is a significant prognostic factor for patients with NPC. Patients with NG may be upgraded from stages N1 to N2. NG was also a marker for identifying patients who would benefit from IC. KEY POINTS: • Nodal grouping, defined as the presence of at least three contiguous LNs within one LN region on MRI, was identified as a significant prognostic factor. • In patients with nasopharyngeal carcinoma, nodal grouping may influence lymph node staging. • Nodal grouping was a marker for identifying patients who may benefit from induction chemotherapy.

qFibrosis: a fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients.

BACKGROUND & AIMS: There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients. METHODS: qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison. RESULTS: qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93-0.99 for animal samples: 1-16 mm(2); AUC: 0.84-0.97 for biopsies: 10-44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts. CONCLUSIONS: qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice.

Correlation of MR elastography with morphometric quantification of liver fibrosis (Fibro-C-Index) in chronic hepatitis B.

PURPOSE: We evaluated the correlation of MR Elastography (MRE) with morphometric assessment of liver fibrosis in chronic hepatitis B (CHB). METHODS: Thirty-two patients with CHB underwent both MRE and a liver biopsy within a 6-month interval. MRE was performed using standard MRE sequence on a 1.5 Tesla clinical scanner. The liver stiffness (LS) was measured on automatically generated stiffness maps. Morphometric quantification of fibrosis of liver biopsies was performed using a semi-automated image analysis program and expressed as percentage area (Fibro-C-Index). Correlations between MRE, Fibro-C-Index, and histologic fibrosis stages were evaluated. Receiver operating curve (ROC) analysis of MRE and Fibro-C-index for differentiating fibrosis (≥F1), significant fibrosis (≥F2), advanced fibrosis (≥F3), and cirrhosis (F4) was performed. RESULTS: MRE showed excellent correlation with both Fibro-C-Index (r = 0.78, 95% confidence interval [CI], 0.59-0.88, P < 0.001) and histologic staging (rho = 0.87, 95% CI, 0.72-0.94, P < 0.0001). Significant differences in MRE (P = 0.0001) and Fibro-C-Index (P = 0.003) among different stages of liver fibrosis was found. MRE and Fibro-C-Index had similar accuracies for differentiating fibrosis stages: ≥F1 (0.87 versus 0.81, P = 0.6), ≥F2 (0.95 versus 0.94, P = 0.78), ≥F3 (0.98 versus 0.96, P = 0.76), and F4 (1.00 versus 0.92, P = 0.10). CONCLUSION: MRE is an excellent noninvasive indicator of liver fibrosis burden in CHB.

Aging exacerbates damage and delays repair of alveolar epithelia following influenza viral pneumonia.

BACKGROUND: Influenza virus infection causes significantly higher levels of morbidity and mortality in the elderly. Studies have shown that impaired immunity in the elderly contributes to the increased susceptibility to influenza virus infection, however, how aging affects the lung tissue damage and repair has not been completely elucidated. METHODS: Aged (16-18 months old) and young (2-3 months old) mice were infected with influenza virus intratracheally. Body weight and mortality were monitored. Different days after infection, lung sections were stained to estimate the overall lung tissue damage and for club cells, pro-SPC+ bronchiolar epithelial cells, alveolar type I and II cells to quantify their frequencies using automated image analysis algorithms. RESULTS: Following influenza infection, aged mice lose more weight and die from otherwise sub-lethal influenza infection in young mice. Although there is no difference in damage and regeneration of club cells between the young and the aged mice, damage to alveolar type I and II cells (AT1s and AT2s) is exacerbated, and regeneration of AT2s and their precursors (pro-SPC-positive bronchiolar epithelial cells) is significantly delayed in the aged mice. We further show that oseltamivir treatment reduces virus load and lung damage, and promotes pulmonary recovery from infection in the aged mice. CONCLUSIONS: These findings show that aging increases susceptibility of the distal lung epithelium to influenza infection and delays the emergence of pro-SPC positive progenitor cells during the repair process. Our findings also shed light on possible approaches to enhance the clinical management of severe influenza pneumonia in the elderly.

Synthesis of thioesters using an electrochemical three-component reaction involving elemental sulfur.

An electrochemical three-component reaction involving elemental sulfur is disclosed for achieving a metal-free, oxidant-free synthesis of thioesters in a high atom-economical, step-economical and chemoselective manner. A mechanistic investigation indicates that the use of elemental sulfur to trap acyl radical derived from radical umpolung of α-keto acid with an electrochemical design can efficiently generate a carbonyl thiyl radical, which can further be captured by diazoalkane to afford various thioesters.

Nomograms integrating the collagen signature and systemic immune-inflammation index for predicting prognosis in rectal cancer patients.

BACKGROUND: This study aimed to develop and validate a model based on the collagen signature and systemic immune-inflammation index to predict prognosis in rectal cancer patients who underwent neoadjuvant treatment. METHODS: Patients with rectal cancer who had residual disease after neoadjuvant treatment at two Chinese institutions between 2010 and 2018 were selected, one used as a training cohort and the other as a validation cohort. In total, 142 fully quantitative collagen features were extracted using multiphoton imaging, and a collagen signature was generated by least absolute shrinkage and selection operator Cox regression. Nomograms were developed by multivariable Cox regression. The performance of the nomograms was assessed via calibration, discrimination and clinical usefulness. The outcomes of interest were overall survival and disease-free survival calculated at 1, 2 and 3 years. RESULTS: Of 559 eligible patients, 421 were selected (238 for the training cohort and 183 for the validation cohort). The eight-collagen-features collagen signature was built and multivariable Cox analysis demonstrated that it was an independent prognostic factor of prognosis along with the systemic immune-inflammation index, lymph node status after neoadjuvant treatment stage and tumour regression grade. Then, two nomograms that included the four predictors were computed for disease-free survival and overall survival. The nomograms showed satisfactory discrimination and calibration with a C-index of 0.792 for disease-free survival and 0.788 for overall survival in the training cohort and 0.793 for disease-free survival and 0.802 for overall survival in the validation cohort. Decision curve analysis revealed that the nomograms could add more net benefit than the traditional clinical-pathological variables. CONCLUSIONS: The study found that the collagen signature, systemic immune-inflammation index and nomograms were significantly associated with prognosis.

Evaluation of the Agreement Between a New Pyramid Wavefront Sensor Aberrometer and Scheiner-Smirnov Aberrometers.

PURPOSE: To assess agreement between a new aberrometer (Osiris-T; CSO) employing pyramid wavefront sensor technique and Scheiner-Smirnov aberrometer (OPD-Scan III; Nidek) on measuring ocular, corneal, and internal aberrations in healthy participants. METHODS: The measurements were conducted three times consecutively by an experienced examiner. The total root mean square (RMS) aberrations, higher order aberration RMS, coma Z3±1, trefoil Z3±3, spherical aberration Z40, and astigmatism II Z4±2 up to 7th order were exported in both 4-and 6-mm pupil zones. The parameters between the two devices were statistically compared using the paired t-test, and the differences assessed with Bland-Altman plots and 95% limits of agreement. RESULTS: This prospective study included 70 right eyes of 70 healthy participants with an average age of 25.94 ± 6.59 years (range: 18 to 47 years). The mean difference in the two devices ranged from 0.01 µm for astigmatism II Z4±2 to 0.63 µm for total RMS in 4 mm and from 0.01 to 1.41 µm in 6-mm pupil size. The Bland-Altman analysis of ocular, corneal, and internal aberrations indicated high agreement between the two devices and the maximum absolute values for 95% limits of agreement ranged from 0.03 to 1.06 µm for 4-mm pupil diameters and 0.12 to 1.13 µm for 6-mm pupil diameters. CONCLUSIONS: The newly developed pyramid wavefront sensor technique aberrometer demonstrated a high agreement with a Scheiner-Smirnov aberrometer when measuring ocular, corneal, and internal aberrations in healthy participants. Thus, the two aberrometers may be considered interchangeable for clinical applications. [J Refract Surg. 2024;40(4):e218-e228.].

CD20highCD138low tumor-infiltrating lymphocytes predominantly related to cytokine‒cytokine receptor interactions are associated with favorable outcomes in neuroblastoma patients.

Recent advances have revealed that the role of the immune system is prominent in the antitumor response. In the present study, it is aimed to provide an expression profile of tumor-infiltrating lymphocytes (TILs), including mature B cells, plasma cells, and their clinical relevance in neuroblastoma. The expression of CD20 and CD138 was analyzed in the Cangelosi786 dataset (n = 769) as a training dataset and in our cohort (n = 120) as a validation cohort. CD20 high expression was positively associated with favorable overall survival (OS) and event-free survival (EFS) (OS: P < 0.001; EFS: P < 0.001) in the training dataset, whereas CD138 high expression was associated with poor OS and EFS (OS: P < 0.001; EFS: P < 0.001) in both the training and validation datasets. Accordingly, a combined pattern of CD20 and CD138 expression was developed, whereby neuroblastoma patients with CD20highCD138low expression had a consistently favorable OS and EFS compared with those with CD20lowCD138high expression in both the training and validation cohorts (P < 0.0001 and P < 0.01, respectively). Examination of potential molecular functions revealed that signaling pathways, including cytokine‒cytokine receptor interactions, chemokine, and the NF-kappa B signaling pathways, were involved. Differentially expressed genes, such as BMP7, IL7R, BIRC3, CCR7, CXCR5, CCL21, and CCL19, predominantly play important roles in predicting the survival of neuroblastoma patients. Our study proposes that a new combination of CD20 and CD138 signatures is associated with neuroblastoma patient survival. The related signaling pathways reflect the close associations among the number of TILs, cytokine abundance and patient outcomes and provide therapeutic insights into neuroblastoma.

Label-free detection of invasive micropapillary carcinoma of the breast using multiphoton microscopy.

Invasive micropapillary carcinoma of the breast (IMPC) is a rare form of breast cancer with unique histological features, and is associated with high axillary lymph node metastasis and poor clinical prognosis. Thus, IMPC should be diagnosed in time to improve the treatment and management of patients. In this study, multiphoton microscopy (MPM) is used to label-free visualize the morphological features of IMPC. Our results demonstrate that MPM images are well in agreement with hematoxylin and eosin staining and epithelial membrane antigen staining, indicating MPM is comparable to traditional histological analysis in identifying the tissue structure and cell morphology. Statistical analysis shows significant differences in the circumference and area of the glandular lumen and cancer nest between the different IMPC cell clusters with complete glandular lumen morphology, and also shows difference in collagen length, width, and orientation, indicating the invasive ability of different morphologies of IMPC may be different.

A nomogram based on collagen signature for predicting the immunoscore in colorectal cancer.

Objectives: The Immunoscore can categorize patients into high- and low-risk groups for prognostication in colorectal cancer (CRC). Collagen plays an important role in immunomodulatory functions in the tumor microenvironment (TME). However, the correlation between collagen and the Immunoscore in the TME is unclear. This study aimed to construct a collagen signature to illuminate the relationship between collagen structure and Immunoscore. Methods: A total of 327 consecutive patients with stage I-III stage CRC were included in a training cohort. The fully quantitative collagen features were extracted at the tumor center and invasive margin of the specimens using multiphoton imaging. LASSO regression was applied to construct the collagen signature. The association of the collagen signature with Immunoscore was assessed. A collagen nomogram was developed by incorporating the collagen signature and clinicopathological predictors after multivariable logistic regression. The performance of the collagen nomogram was evaluated via calibration, discrimination, and clinical usefulness and then tested in an independent validation cohort. The prognostic values of the collagen nomogram were assessed using Cox regression and the Kaplan-Meier method. Results: The collagen signature was constructed based on 16 collagen features, which included 6 collagen features from the tumor center and 10 collagen features from the invasive margin. Patients with a high collagen signature were more likely to show a low Immunoscore (Lo IS) in both cohorts (P<0.001). A collagen nomogram integrating the collagen signature and clinicopathological predictors was developed. The collagen nomogram yielded satisfactory discrimination and calibration, with an AUC of 0.925 (95% CI: 0.895-0.956) in the training cohort and 0.911 (95% CI: 0.872-0.949) in the validation cohort. Decision curve analysis confirmed that the collagen nomogram was clinically useful. Furthermore, the collagen nomogram-predicted subgroup was significantly associated with prognosis. Moreover, patients with a low-probability Lo IS, rather than a high-probability Lo IS, could benefit from chemotherapy in high-risk stage II and stage III CRC patients. Conclusions: The collagen signature is significantly associated with the Immunoscore in the TME, and the collagen nomogram has the potential to individualize the prediction of the Immunoscore and identify CRC patients who could benefit from adjuvant chemotherapy.

Corneal Higher-Order Aberrations Measurements: Precision of SD-OCT/Placido Topography and Comparison with a Scheimpflug/Placido Topography in Eyes After Small-Incision Lenticule Extraction.

INTRODUCTION: The aim of this study was to evaluate the measurements of corneal higher-order aberrations (HOAs) obtained by a new anterior segment optical coherence tomography (OCT) technique combined with a Placido topographer (the MS-39 device) in eyes with prior small-incision lenticule extraction (SMILE) and compare them to the measurements obtained by a Scheimpflug camera combined with a Placido topographer (the Sirius device). METHODS: A total of 56 eyes (56 patients) were included in this prospective study. Corneal aberrations were analyzed for the anterior, posterior, and total cornea surfaces. Within-subject standard deviation (Sw), test-retest repeatability (TRT), and intraclass correlation coefficient (ICC) were used to assess the intraobserver repeatability and interobserver reproducibility. The differences were evaluated by paired t-test. Bland-Altman plots and 95% limits of agreement (95% LoA) were used to evaluate the agreement. RESULTS: High repeatability was observed for anterior and total corneal parameters, with Sw value < 0.07, TRT ≤ 0.16, and ICCs > 0.893, but not trefoil. For the posterior corneal parameters, ICCs varied from 0.088 to 0.966. Regarding interobserver reproducibility, all Sw values were ≤ 0.04 and TRT ≤ 0.11. ICCs ranged from 0.846 to 0.989, from 0.432 to 0.972, and from 0.798 to 0.985 for the anterior, total, and posterior corneal aberrations parameters, respectively. The mean difference in all aberrations was ≤ 0.05 µm. All parameters showed a narrow 95% LoA. CONCLUSION: The MS-39 device achieved high precision in both anterior and total corneal measurements; the precision of posterior corneal higher-order RMS, astigmatism II, coma, and trefoil was lower. The two technologies used by the MS-39 and Sirius devices can be used interchangeably for measuring corneal HOAs after SMILE.

Detection of fibrotic changes in the progression of liver diseases by label-free multiphoton imaging.

Collagen fibers play an important role in the progression of liver diseases. The formation and progression of liver fibrosis is a dynamic pathological process accompanied by morphological changes in collagen fibers. In this study, we used multiphoton microscopy for label-free imaging of liver tissues, allowing direct detection of various components including collagen fibers, tumors, blood vessels, and lymphocytes. Then, we developed a deep learning classification model to automatically identify tumor regions, and the accuracy reaches 0.998. We introduced an automated image processing method to extract eight collagen morphological features from various stages of liver diseases. Statistical analysis showed significant differences between them, indicating the potential use of these quantitative features for monitoring fibrotic changes during the progression of liver diseases. Therefore, multiphoton imaging combined with automatic image processing method would hold a promising future in rapid and label-free diagnosis of liver diseases.