Midwest Orthopaedic Research Foundation

There is a significant need for trials that evaluate the treatment of University of Texas (UT) grade 2 and 3 diabetic foot ulcers (bone, joint, or tendon exposed wounds). We undertook a trial looking at the effect of intact fish skin graft (IFSG) on these deep and difficult-to-heal ulcers. 262 patients Intent to Treat (ITT) patients with UT grade 2 and 3 DFUs were randomised to receive intact fish skin graft (IFSG) or a standardised treatment (SOC) that adhered to the International Working Group on the Diabetic Foot (IWGDF) guidelines. The secondary endpoints that were measured included wound area reduction (WAR), healing rates at 20 and 24 weeks; closure rates by UT grade, perfusion, quality of life, pain reduction and IFSG safety. We report ITT (all randomised) (mITT previosly reported) The (WAR) at 12 weeks was 65.53% for IFSG versus 30.82% for SOC (p = 0.007). UT 2 wounds (60% of total) exhibited a closure rate of 47% versus 23% at 16 weeks for IFSG versus SOC (p = 0.0033). Target wound infections were comparable (39 vs. 37) and major outcomes were comparable during the 24 week period (target-limb amputations 8% vs. 7%). Time-to-heal favoured IFSG (restricted mean to 24 weeks 17.31 vs. 19.37 weeks; KM/log-rank significant; Cox HR 1.59). The in the treatment of deep complex diabetic foot wounds the addition of IFSG significantly improved the number of patients with total wound closure as well as the time to wound closure without increased risk of complications. This improvement in total wound closure and time to wound closure was noted across prior amputation status, quality of perfusion, and UT grade.

Abstract Background: The estrogen receptor (ER), cyclin-dependent kinase (CDK), and PI3K-AKT-mTOR (PAM) pathways are interconnected and drive hormone receptor (HR)+/HER2- advanced breast cancer (ABC). In the first line setting, endocrine therapy (ET) combined with a CDK4/6 inhibitor is the standard of care regimen for most patients with HR+/HER2- ABC. For patients in the second line setting, several inhibitors targeting components of the PAM pathway (e.g. PI3Kα, AKT, mTORC1) are approved in combination with ET. By only addressing a single target of the PAM pathway, the currently approved PI3Kα, AKT, mTORC1 inhibitors do not prevent adaptive resistance induced by the other uninhibited PAM targets. In a phase 1b clinical trial, gedatolisib, a multi-target PAM inhibitor, combined with ET and palbociclib showed promising efficacy and safety in patients with HR+/HER2- ABC, regardless of PIK3CA mutation status. Here we investigated the effects of gedatolisib and single-target PI3Kα and AKT inhibitors in combination with fulvestrant and/or palbociclib in breast cancer (BC) cell models with and without PAM pathway mutations and with varying levels of sensitivity to fulvestrant and palbociclib. Methods: Gedatolisib (pan-PI3K, mTORC1/2 inhibitor), inavolisib (PI3Kα inhibitor), capivasertib (AKT inhibitor) were tested as single agents or in combination with fulvestrant and/or palbociclib in treatment-naïve BC cell lines with or without PIK3CA mutations as well as in BC cell lines adapted to long-term treatment with fulvestrant and/or palbociclib. Cell viability, growth rate, cell cycle, DNA replication, apoptosis, and cell death were evaluated by luciferase-based and flow cytometry-based functional assays. Results: Gedatolisib reduced growth rates of treatment-naïve or fulvestrant/palbociclib-adapted BC cell lines, regardless of PIK3CA mutational status, and the addition of fulvestrant and/or palbociclib increased growth-inhibitory effects. From a functional standpoint, the gedatolisib/palbociclib/fulvestrant triplet inhibited DNA replication and/or induced apoptotic cell death more effectively than treatment with single drugs or drug doublets. The gedatolisib/palbociclib/fulvestrant triplet was more effective than PI3Kα and AKT inhibitors (inavolisib, capivasertib) combined with palbociclib and/or fulvestrant in the BC cell lines tested, regardless of PIK3CA mutational status or previous adaptation to palbociclib and/or fulvestrant. Conclusions: These results indicate that gedatolisib plus fulvestrant, with and without palbociclib, effectively controls the growth of treatment-naïve BC cells as well as BC cells adapted to palbociclib/fulvestrant treatment. Moreover, in contrast to the currently approved PI3Kα and AKT inhibitors, the gedatolisib/palbociclib/fulvestrant triplet is effective in BC cells with or without PIK3CA mutations. The combination of gedatolisib with ET and a CDK4/6 inhibitor is being evaluated in two ongoing Phase 3 clinical trials as first-line (VIKTORIA-2) or second-line (VIKTORIA-1) treatment of HR+/HER2- ABC with or without PIK3CA mutations. The non-clinical results presented here provide a strong mechanistic rationale for these clinical studies. Citation Format: S. Rossetti, A. Broege, L. Davis, M. Seibel, S. Stokke, J. Molden, I. Gorbatchevsky, B. Sullivan, L. Laing. Functional analysis of gedatolisib combined with fulvestrant and/or palbociclib in breast cancer cell models adapted to estrogen receptor and/or CDK4/6 inhibitors [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-11-30.

Distinguishing AI-generated text from human writing is crucial for academic integrity, authorship verification, and trustworthy AI. We present a lightweight, reproducible pipeline that detects AI-generated essays using classical NLP features and linear classification, and we complement the supervised detector with structure-revealing unsupervised analysis. Using a balanced corpus of human and AI essays (CSV; text, label), we apply a transparent preprocessing stack— lowercasing, non-alphabetic stripping, stop-word removal, and WordNet lemmatization—followed by TF-IDF vectorization with 1–2-gram features (5k max). A logistic-regression classifier (class_weight=balanced, max_iter=1000) trained on an 80/20 split attains 99.64% accuracy (test n = 550), with classwise F<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> ≈ 1.00 for both human and AI categories. To probe latent structure and dataset artifacts, we perform DBSCAN clustering (cosine metric) on a compact TF-IDF (1k features) and visualize with t-SNE. Clusters segregate strongly by label (e.g., a large AI-dominant cluster of 1,296 samples; human-dominant clusters of 659 and 646), and coefficient analysis highlights interpretable markers (e.g., context, exploration, persuasive for AI; car, vote, electoral college for human). We discuss why near-perfect accuracy is plausible here (prompt/style regularities) and outline stress tests to evaluate robustness (cross-prompt generalization, paraphrase attacks, topic-held-out splits, and calibration). The resulting system is compact, fast, and transparent, offering a practical baseline or production-ready component where explainability and low latency matter.

The rapid rise of natural and anthropogenic disasters can now be translated into the need for the development and implementation of effective and sustainable disaster waste management practices. The waste produced when a disaster occurs is highly heterogeneous, comprising cement, ceramics, plastic, metal, glass, organic matter, and electronic waste. The recovery of these materials through waste sorting can be time-consuming and labour-intensive in disaster situations, often due to inadequate planning. This research presents the disaster waste classification proposed automation using Vision Transformer (ViT-B16). This is built on a well-balanced dataset comprising 4,547 images across seven primary categories. The dataset contained enough real-world complexity and diversity to test the models as expected in deep learning applications. Following data preprocessing, augmentation, and stratified partitioning, the base and frozen convolutional layers of the pretrained ViT-B16 model were fine-tuned with a custom classification head. The model achieved a test balanced accuracy of 85.63%, outperforming traditional convolutional models, with a remarkable ability to generalise and gain strong recognition across heterogeneous sets. The model's performance presents a strong case for real-world implementation. The proposed automation shows interesting possibilities toward deployment on edge devices for real-time inference in highly constrained computing environments with low power. This is particularly valuable in disaster-stricken areas.

Public health leadership plays a crucial role in shaping effective health policies and practices. The National Board of Public Health Examiners (NBPHE) conducts a job task analysis (JTA) survey every 5-7 years to update the Certified in Public Health (CPH) examination. The objective of this study is to examine the JTA findings on leadership tasks in public health practice. In April 2022, through the collaboration of expert panels and a validation survey, 103 tasks organized into ten domains were established for the JTA survey. The JTA survey was distributed online to current public health professionals. Across the tasks in the ten domains, respondents were asked about frequency (Scale of 1-6; how often they performed this task) and criticality (Scale of 1-5; how important this task was to their job). A total of 2,091 public health professionals responded to at least 82 of the 103 tasks (80%) and were included in the analysis. Approximately 86% of respondents worked in the United States and 41% had earned their CPH credential. Average frequency ratings ranged from 2.38 to 5.58, indicating that task ratings ranged from being performed never performed, every few years to daily. Average criticality ratings ranged from 2.46 to 4.64, indicating that task ratings ranged from not important to critically important. Specific to leadership, it was found that the 'leadership' domain ranked 2nd highest for both frequency and criticality. Our findings suggest that leadership-focused development as part of academic public health programs and continuing education for the workforce is essential. Future research may examine how individuals perform on the leadership domain of the CPH exam across multiple characteristics to better inform additional workforce development strategies.