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Breast-conserving surgery accompanied by adjuvant radiotherapy is the standard of care for patients with early-stage breast cancer. However, re-excision is reported in 20–30 % of cases, largely because of close or involved tumor margins in the specimen. Several intraoperative tumor margin assessment techniques have been proposed to overcome this issue, however, none have been widely adopted. Furthermore, tumor margin assessment of the excised specimen provides only an indirect indication of residual cancer in the patient following excision of the primary tumor. Handheld optical coherence tomography (OCT) probes and their functional extensions have the potential to detect residual cancer in vivo in the surgical cavity. Until now, validation of in vivo OCT has been achieved through correlation with ex vivo histology performed on the specimen removed during surgery that is adjacent to the tissue scanned in vivo. However, this indirect approach cannot accurately validate in vivo imaging performance. To address this, we present a method for robust co-registration of in vivo OCT scans with histology performed, not on the main specimen, but on cavity shavings corresponding directly to the tissue scanned in vivo. In this approach, we use ex vivo OCT scans as an intermediary, surgical sutures as fiducial markers, and extend the in vivo field-of-view to 15 × 15 mm2 by acquiring partially overlapping scans. We achieved successful co-registration of 78 % of 139 in vivo OCT scans from 16 patients. We present a detailed analysis of three cases, including a case where a functional extension of OCT, quantitative micro-elastography, was performed.

BackgroundMexico has one of the highest global incidences of paediatric overweight and obesity. Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analysis methods.PurposeTo explore if multimodal machine learning can enhance identifying predictive features from obesogenic environments and investigating complex disease or social patterns, using the Mexican National Health and Nutrition Survey.MethodsWe grouped features into five data modalities corresponding to paediatric population exogenous factors, in two multimodal machine learning pipelines, against a unimodal early fusion baseline. The supervised pipeline employed four methods: Linear classifier with Elastic Net regularisation, k-Nearest Neighbour, Decision Tree, and Random Forest. The unsupervised pipeline used traditional methods with k-Means and hierarchical clustering, with the optimal number of clusters calculated to be k = 2.ResultsThe decision tree classifier in the supervised early fusion approach produced the best quantitative results. The top five most important features for classifying child or adolescent health were measures of an adult in the household, selected at random: BMI, obesity diagnosis, being single, seeking care at private healthcare, and having paid TV in the home. Unsupervised learning approaches varied in the optimal number of clusters but agreed on the importance of home environment features when analysing inter-cluster patterns. Main findings from this study differed from previous studies using only traditional statistical methods on the same database. Notably, the BMI of a randomised adult within the household emerged as the most important feature, rather than maternal BMI, as reported in previous literature where unwanted cultural bias went undetected.ConclusionOur general conclusion is that multimodal machine learning is a promising approach for comprehensively analysing obesogenic environments. The modalities allowed for a multimodal approach designed to critically analyse data signal strength and reveal sources of unwanted bias. In particular, it may aid in developing more effective public health policies to address the ongoing paediatric obesity epidemic in Mexico.

Charitable organizations are increasingly soliciting donors to engage in word of mouth (WOM) as a strategy to foster future contributions. While some organizations encourage donors to share WOM that focuses on their own donations (donor-focused WOM; e.g., "I just donated to the kids of @StJude. Join me in saving children's lives."), others prompt donors to share WOM that focuses on the organization itself (charity-focused WOM; e.g., "Smile Train gives children with clefts the #PowerOfASmile."). Contrary to the common belief that people mostly want to talk about themselves, the current research demonstrates that donor-focused WOM backfires, such that donors are less likely to share donor- than charity-focused WOM. This effect is driven by their belief that donor-focused WOM is less altruistic and is therefore less efficacious in persuading others to contribute to the same cause. In addition to sharing, the type of WOM solicited exerts far-reaching impact, with donor-focused WOM attracting fewer new donors than charity-focused WOM. The current research improves the understanding of WOM type, its effect, and the underlying processes. [ABSTRACT FROM AUTHOR]

Simple Summary: Fibroblast growth factors (FGFs) and their receptors (FGFRs) play a crucial role in cancer development. However, due to their diverse cellular functions, the mechanisms by which they drive cancer are complex. In this review, we discuss the mechanisms of action of FGFs and FGFRs, as well as how the dysregulation of FGF signaling contributes to cancer in various tumor types. The complexity of FGF signaling is partly explained by the large number of FGF isoforms and FGFR receptor types. We provide a classification of FGF ligands based on their signaling modes and binding specificity to FGFRs. Additionally, we explore promising therapeutic strategies being developed to target FGF signaling in oncology, including small molecules, ligand traps, and monoclonal antibody-based inhibitors. Fibroblast growth factors (FGFs) have diverse functions in the regulation of cell proliferation and differentiation in development, tissue maintenance, wound repair, and angiogenesis. The goal of this review paper is to (i) deliberate on the role of FGFs and FGF receptors (FGFRs) in different cancers, (ii) present advances in FGF-targeted cancer therapies, and (iii) explore cell signaling mechanisms that explain how FGF expression becomes dysregulated during cancer development. FGF is often mutated and overexpressed in cancer and the different FGF and FGFR isoforms have unique expression patterns and distinct roles in different cancers. Among the FGF members, the FGF 15/19 subfamily is particularly interesting because of its unique protein structure and role in endocrine function. The abnormal expression of FGFs in different cancer types (breast, colorectal, hepatobiliary, bronchogenic, and others) is examined and correlated with patient prognosis. The classification of FGF ligands based on their mode of action, whether autocrine, paracrine, endocrine, or intracrine, is illustrated, and an analysis of the binding specificity of FGFs to FGFRs is also provided. Moreover, the latest advances in cancer therapeutic strategies involving small molecules, ligand traps, and monoclonal antibody-based FGF inhibitors are presented. Lastly, we discuss how the dysregulation of FGF and FGFR expression affects FGF signaling and its role in cancer development. [ABSTRACT FROM AUTHOR]

The goal of this paper is to discuss the role of ALDH isozymes in different cancers, review advances in ALDH1-targeting cancer therapies, and explore a mechanism that explains how ALDH expression becomes elevated during cancer development. ALDH is often overexpressed in cancer, and each isoform has a unique expression pattern and a distinct role in different cancers. The abnormal expression of ALDHs in different cancer types (breast, colorectal, lung, gastric, cervical, melanoma, prostate, and renal) is presented and correlated with patient prognosis. ALDH plays a significant role in various cellular functions, such as metabolism, oxidative stress response, detoxification, and cellular differentiation. Among the ALDH families, ALDH1 has gained considerable attention as a cancer stem cell (CSC) marker due to its significant role in the maintenance of stemness and the differentiation of stem cells (SCs), along with its involvement in tumorigenesis. A description of the cellular mechanisms and physiology of ALDH1 that underlies cancer development is provided. Moreover, current advances in ALDH1-targeting cancer therapies are discussed. [ABSTRACT FROM AUTHOR]