Applicability of the CT Radiomics of Skeletal Muscle and Machine Learning for the Detection of Sarcopenia and Prognostic Assessment of Disease Progression in Patients with Gastric and Esophageal Tumors.

PURPOSE: Sarcopenia is considered a negative prognostic factor in patients with malignant tumors. Among other diagnostic options, computed tomography (CT), which is repeatedly performed on tumor patients, can be of further benefit. The present study aims to establish a framework for classifying the impact of sarcopenia on the prognosis of patients diagnosed with esophageal or gastric cancer. Additionally, it explores the significance of CT radiomics in both diagnostic and prognostic methodologies. MATERIALS AND METHODS: CT scans of 83 patients with esophageal or gastric cancer taken at the time of diagnosis and during a follow-up period of one year were evaluated retrospectively. A total of 330 CT scans were analyzed. Seventy three of these patients received operative tumor resection after neoadjuvant chemotherapy, and 74% of the patients were male. The mean age was 64 years (31-83 years). Three time points (t) were defined as a basis for the statistical analysis in order to structure the course of the disease: t1 = initial diagnosis, t2 = following (neoadjuvant) chemotherapy and t3 = end of the first year after surgery in the "surgery" group or end of the first year after chemotherapy. Sarcopenia was determined using the psoas muscle index (PMI). The additional analysis included the analysis of selected radiomic features of the psoas major, quadratus lumborum, and erector spinae muscles at the L3 level. Disease progression was monitored according to the response evaluation criteria in solid tumors (RECIST 1.1). CT scans and radiomics were used to assess the likelihood of tumor progression and their correlation to sarcopenia. For machine learning, the established algorithms decision tree (DT), K-nearest neighbor (KNN), and random forest (RF) were applied. To evaluate the performance of each model, a 10-fold cross-validation as well as a calculation of Accuracy and Area Under the Curve (AUC) was used. RESULTS: During the observation period of the study, there was a significant decrease in PMI. This was most evident in patients with surgical therapy in the comparison between diagnosis and after both neoadjuvant therapy and surgery (each p < 0.001). Tumor progression (PD) was not observed significantly more often in the patients with sarcopenia compared to those without sarcopenia at any time point (p = 0.277 to p = 0.465). On average, PD occurred after 271.69 ± 104.20 days. The time from initial diagnosis to PD in patients "with sarcopenia" was not significantly shorter than in patients "without sarcopenia" at any of the time points (p = 0.521 to p = 0.817). The CT radiomics of skeletal muscle could predict both sarcopenia and tumor progression, with the best results for the psoas major muscle using the RF algorithm. For the detection of sarcopenia, the Accuracy was 0.90 ± 0.03 and AUC was 0.96 ± 0.02. For the prediction of PD, the Accuracy was 0.88 ± 0.04 and the AUC was 0.93 ± 0.04. CONCLUSIONS: In the present study, the CT radiomics of skeletal muscle together with machine learning correlated with the presence of sarcopenia, and this can additionally assist in predicting disease progression. These features can be classified as promising alternatives to conventional methods, with great potential for further research and future clinical application. However, when sarcopenia was diagnosed with PMI, no significant correlation between sarcopenia and PD could be observed.

Radiomics and Clinicopathological Characteristics for Predicting Lymph Node Metastasis in Testicular Cancer.

Accurate prediction of lymph node metastasis (LNM) in patients with testicular cancer is highly relevant for treatment decision-making and prognostic evaluation. Our study aimed to develop and validate clinical radiomics models for individual preoperative prediction of LNM in patients with testicular cancer. We enrolled 91 patients with clinicopathologically confirmed early-stage testicular cancer, with disease confined to the testes. We included five significant clinical risk factors (age, preoperative serum tumour markers AFP and B-HCG, histotype and BMI) to build the clinical model. After segmenting 273 retroperitoneal lymph nodes, we then combined the clinical risk factors and lymph node radiomics features to establish combined predictive models using Random Forest (RF), Light Gradient Boosting Machine (LGBM), Support Vector Machine Classifier (SVC), and K-Nearest Neighbours (KNN). Model performance was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, the decision curve analysis (DCA) was used to evaluate the clinical usefulness. The Random Forest combined clinical lymph node radiomics model with the highest AUC of 0.95 (±0.03 SD; 95% CI) was considered the candidate model with decision curve analysis, demonstrating its usefulness for preoperative prediction in the clinical setting. Our study has identified reliable and predictive machine learning techniques for predicting lymph node metastasis in early-stage testicular cancer. Identifying the most effective machine learning approaches for predictive analysis based on radiomics integrating clinical risk factors can expand the applicability of radiomics in precision oncology and cancer treatment.

Deep Neural Networks and Machine Learning Radiomics Modelling for Prediction of Relapse in Mantle Cell Lymphoma.

Mantle cell lymphoma (MCL) is a rare lymphoid malignancy with a poor prognosis characterised by frequent relapse and short durations of treatment response. Most patients present with aggressive disease, but there exist indolent subtypes without the need for immediate intervention. The very heterogeneous behaviour of MCL is genetically characterised by the translocation t(11;14)(q13;q32), leading to Cyclin D1 overexpression with distinct clinical and biological characteristics and outcomes. There is still an unfulfilled need for precise MCL prognostication in real-time. Machine learning and deep learning neural networks are rapidly advancing technologies with promising results in numerous fields of application. This study develops and compares the performance of deep learning (DL) algorithms and radiomics-based machine learning (ML) models to predict MCL relapse on baseline CT scans. Five classification algorithms were used, including three deep learning models (3D SEResNet50, 3D DenseNet, and an optimised 3D CNN) and two machine learning models based on K-nearest Neighbor (KNN) and Random Forest (RF). The best performing method, our optimised 3D CNN, predicted MCL relapse with a 70% accuracy, better than the 3D SEResNet50 (62%) and the 3D DenseNet (59%). The second-best performing method was the KNN-based machine learning model (64%) after principal component analysis for improved accuracy. Our optimised CNN developed by ourselves correctly predicted MCL relapse in 70% of the patients on baseline CT imaging. Once prospectively tested in clinical trials with a larger sample size, our proposed 3D deep learning model could facilitate clinical management by precision imaging in MCL.

Community coalition and key stakeholder perceptions of the community opioid epidemic before an intensive community-level intervention.

INTRODUCTION: Opioid overdoses are a major public health emergency in the United States. Despite effective treatments that can save lives, access to and utilization of such treatments are limited. Community context plays an important role in addressing treatment barriers and increasing access. The HEALing Communities Study (HCS) is a multisite community-level cluster-randomized trial that will study implementation and outcomes of a community coalition-based intervention (Communities that HEAL [CTH]) that implements evidence-based practices (EBPs) to reduce opioid overdose deaths in four states. To examine contextual factors critical to understanding implementation, we assessed the perspectives of community members about their communities, current substance use-related services, and other important issues that could impact intervention implementation. METHODS: Researchers conducted 382 semi-structured qualitative interviews in the HCS communities. Interviews were audio-recorded and transcribed; researchers subsequently analyzed data using directed content analysis based on the constructs of the RE-AIM/PRISM implementation science framework to identify key themes within the external community context. RESULTS: Despite the diversity in states and communities, four similar themes related to the external community context emerged across communities: These themes included the importance of understanding: 1) community risk perceptions, 2) levels of stigma, 3) the health services environment and the availability of substance use services, and 4) funding for substance use services. CONCLUSION: Understanding and addressing the external community context in which the CTH intervention and EBPs are implemented are crucial for successful health services-related and community engaged interventions. While implementing EBPs is a challenging undertaking, doing so will help us to understand if and how a community-based intervention can successfully reduce opioid overdose deaths and influence both community beliefs and the community treatment landscape.

Identification of potential modulators of osteosarcoma metastasis by high-throughput cellular screening of natural products.

A high-throughput screening assay was developed and applied to a large library of natural product extract samples, in order to identify compounds which preferentially inhibited the in vitro 2D growth of a highly metastatic osteosarcoma cell line (MG63.3) compared to a cognate parental cell line (MG63) with low metastatic potential. Evaluation of differentially active natural product extracts with bioassay-guided fractionation led to the identification of lovastatin (IC50  = 11 µm) and the limonoid toosendanin (IC50  = 26 nm). Other statins and limonoids were then tested, and cerivastatin was identified as a particularly potent (IC50  < 0.1 µm) and selective agent. These compounds potently and selectively induced apoptosis in MG63.3 cells, but not MG63. Assays with other cell pairs were used to examine the generality of these results. Statins and limonoids may represent unexplored opportunities for development of modulators of osteosarcoma metastasis. As cerivastatin was previously approved for clinical use, it could be considered for repurposing in osteosarcoma, pending validation in further models.

Optimizing multifunctional agroecosystems in irrigated dryland agriculture to restore soil carbon - Experiments and modelling.

Irrigated dryland agroecosystems could become more sustainable if crop and soil management enhanced soil organic carbon (SOC). We hypothesized that combining high inputs from cover crops with no-tillage will increase long-term SOC stocks. Caatinga shrublands had been cleared in 1972 for arable crops and palm plantations before implementing field experiments on Mango and Melon systems (established in 2009 and 2012, respectively). Each of the two experiments were managed with no-till (NT) or conventional till (CT), and three types of cover cropping, either a plant mixture of 75% (PM1) or 25% (PM2) legumes, or spontaneous vegetation (SV). The RothC model was used with a daily timestep to simulate the soil moisture dynamics and C turnover for this dry climate. Carbon inputs were between 2.62 and 5.82 Mg C ha-1 year-1 and increased the depleted SOC stocks by 0.08 to 0.56 Mg C ha-1 year-1. Scenarios of continuous biomass inputs of ca. 5 Mg C ha-1 year-1 for 60 years are likely to increase SOC stocks in the mango NT beyond the original Caatinga SOC by between 19.2 and 20.5 Mg C ha-1. Under CT similar inputs would increase SOC stocks only marginally above depletion (2.75 to 2.47 Mg C ha-1). Under melon, annual carbon inputs are slightly greater (up to 5.5 Mg C ha-1 year-1) and SOC stocks would increase on average by another 8% to 22.3 to 20.6 Mg C ha-1 under NT and by 8 Mg C ha-1 under CT. These long-term simulations show that combining NT with high quality cover crops (PM1, PM2) would exceed SOC stocks of the initial Caatinga within 20 and 25 years under irrigated melon and mango cultivation, respectively. These results present a solution to reverse prior loss of SOC by replacing CT dryland agriculture with irrigated NT plus high input cover crops agroecosystems.

Galtonosides A-E: Antiproliferative and Antiplasmodial Cholestane Glycosides from Galtonia regalis.

An extract of Galtonia regalis from the Natural Products Discovery Institute showed moderate antiplasmodial activity, with an IC50 value less than 1.25 µg/mL. The two known cholestane glycosides 1 and 2 and the five new cholestane glycosides galtonosides A-E (3-7) were isolated after bioassay-directed fractionation. The structures of the new compounds were determined by interpretation of their NMR and mass spectra. Among these compounds, galtonoside B (4) displayed the most potent antiplasmodial activity, with an IC50 value of 0.214 µM against the drug-resistant Dd2 strain of Plasmodium falciparum.

Anibamine and Its Analogues: Potent Antiplasmodial Agents from Aniba citrifolia.

In our continuing search for novel natural products with antiplasmodial activity, an extract of Aniba citrifolia was found to have good activity, with an IC50 value less than 1.25 µg/mL. After bioassay-directed fractionation, the known indolizinium alkaloid anibamine (1) and the new indolizinium alkaloid anibamine B (2) were isolated as the major bioactive constituents, with antiplasmodial IC50 values of 0.170 and 0.244 µM against the drug-resistant Dd2 strain of Plasmodium falciparum. The new coumarin anibomarin A (3), the new norneolignan anibignan A (5), and six known neolignans (7-12) were also obtained. The structures of all the isolated compounds were determined based on analyses of 1D and 2D NMR spectroscopic and mass spectrometric data, and the absolute configuration of anibignan A (5) was assigned from its ECD spectrum. Evaluation of a library of 28 anibamine analogues (13-40) indicated that quaternary charged analogues had IC50 values as low as 58 nM, while uncharged analogues were inactive or significantly less active. Assessment of the potential effects of anibamine and its analogues on the intraerythrocytic stages and morphological development of P. falciparum revealed substantial activity against ring stages for compounds with two C-10 side chains, while those with only one C-10 side chain exhibited substantial activity against trophozoite stages, suggesting different mechanisms of action.

Antiplasmodial flavanones and a stilbene from Carpha glomerata.

Bioassay-guided fractionation of an extract of Carpha glomerata (Cyperaceae) led to the isolation of seven compounds. Compounds 1 (carphorin A), 3 (carphorin C), 4 (carphorin D), and 5 (carphabene) are new compounds, and compound 2 (8-(3″-hydroxyisoamyl)-naringenin) was isolated for the first time as a natural product. All structures were elucidated based on analyses of their HR-ESIMS and 1D and 2D NMR data. Compounds 1, 2, and 6, which have prenyl or hydroxyprenyl side chains, exhibited antiplasmodial activities with IC50 values of 5.2 ±â€¯0.6, 3.4 ±â€¯0.4, and 6.7 ±â€¯0.8 µM against the drug-resistant Dd2 strain of Plasmodium falciparum. In addition the prenylated stilbene 5 also showed good activity, with IC50 5.8 ±â€¯0.7 µM.

Antiplasmodial Diterpenoids and a Benzotropolone from Petradoria pumila.

An extract of Petradoria pumila from the Natural Products Discovery Institute was found to have moderate antiplasmodial activity, with an IC50 value between 5 and 10 µg/mL. The four new diterpenoids petradoriolides A-D (1-4), the new benzotropolone petradoriolone (5), and the two known lignans 6 and 7 were isolated after bioassay-directed fractionation. The structures and stereochemistries of the new compounds were determined by interpretation of NMR spectroscopy, mass spectrometry, and ECD spectra. Among these compounds, petradoriolide C (3) displayed the most potent antiplasmodial activity, with an IC50 value of 7.3 µM.

Antiplasmodial Chromanes and Chromenes from the Monotypic Plant Species Koeberlinia spinosa.

Nine new compounds containing either a chromane or chromene ring moiety were isolated from the monotypic plant Koeberlinia spinosa. Compounds 1-4 are chromanes with all possible E and Z isomers of the isoprenoid side chain, with compound 5 a methylated derivative of 1. Compounds 6 and 7 were assigned as diastereomeric cyclized derivatives of 2 and were probably artifacts formed during the extraction or the isolation processes. Compounds 8 and 9 were characterized as new chromenes. Structure elucidation of 1-9 was conducted via 1D and 2D NMR spectroscopic data interpretation, and absolute configurations were determined by ECD spectroscopic analysis. Compounds 2, 5, 6, and 7 had weak antiplasmodial activity, while none of the compounds exhibited antiproliferative activity. The isolation, structure elucidation, and biological evaluation of these compounds are presented.

Antiplasmodial alkaloids from bulbs of Amaryllis belladonna Steud.

A bioassay-guided fractionation and chemical investigation of Amaryllis belladonna Steud. bulbs resulted in the isolation and identification of the new crinane alkaloid 1,4-dihydroxy-3-methoxy powellan (1), along with the 3 known crinane alkaloids 2-4 and the two lycorane alkaloids 5-6. The structures were elucidated by interpretation of combined HR-ESIMS, CD and 2D NMR spectroscopic data. Among these isolated compounds the lycorane-type alkaloid acetylcaranine (5) exhibited strong antiplasmodial activity, while compounds 3 and 4 were moderately active, and compounds 1 and 6 were inactive.

Bioactive Neolignans and Other Compounds from Magnolia grandiflora L.: Isolation and Antiplasmodial Activity.

Bioassay-guided fractionation of a methanol extract of Magnolia grandiflora against Plasmodium falciparum yielded two new (1 and 2) and six known (3 - 8) bioactive compounds. The structures of the new compounds were assigned by mass spectrometric and 1D- and 2D-NMR data. Known compounds were identified by comparison of 1 H-NMR and MS data with literature data. The two known neolignans 3 and 4 showed moderate antiplasmodial activity with the IC50 values of 2.8 ± 0.1 and 3.4 ± 0.1 µm, respectively. Weak antiplasmodial activity was recorded for compounds 1, 2, 5, 6, 7, and 8, with the IC50 values of 38 ± 2, 23 ± 2, 16.5 ± 0.2, 86 ± 1, 44 ± 4, and 114 ± 9 µm, respectively.

Growth Inhibition of Colon Cancer and Melanoma Cells by Versiol Derivatives from a Paraconiothyrium Species.

Bioassay-guided fractionation of a colon cancer growth inhibitory extract of the fungus Paraconiothyrium sp. led to the isolation of eight new versiol derivatives (1, 3-8, 10) along with two known compounds. The structures were elucidated by interpretation of combined MS and 2D NMR spectroscopic data. Compounds 8, 9, and 10 showed cell growth inhibition against COLO205 and KM12 cells, and both 8 and 9 displayed selectivity in their inhibition of melanoma cell lines in the NCI 60 one-dose test. In addition, compound 8 and the crude Paraconiothyrium sp. extract showed potent dose-dependent inhibitory effects in the five-dose NCI 60 cell line assay.

Antiplasmodial Sesquiterpenoid Lactones from Trichospira verticillata: Structure Elucidation by Spectroscopic Methods and Comparison of Experimental and Calculated ECD Data.

A dichloromethane extract of Trichospira verticillata from the Natural Products Discovery Institute was discovered to have good antiplasmodial activity (IC50 ∼5 µg/mL). After purification by liquid-liquid partition and C18 reversed-phase HPLC, four new germacranolide-type sesquiterpenoid lactones named trichospirolides A-D (1-4) were isolated. The structures of the new compounds were elucidated by analysis of their 1D and 2D NMR and MS data. The relative and absolute configurations were assigned based on a comparison of calculated and experimental ECD and UV spectra, specific rotations, internuclear distances, and coupling constants for all possible diastereomers for each compound. Among these four compounds, the conjugated dienone 1 displayed the most potent antiplasmodial activity, with an IC50 value of 1.5 µM.

New potently bioactive alkaloids from Crinum erubescens.

Antimalarial bioassay-guided fractionation of the swamp lily Crinum erubescens led to the isolation of four compounds with potent antiplasmodial activity. Compounds 1 and 2 were determined from their spectroscopic data to be the known pesticidal compound cripowellin A and the known pesticidal and antiproliferative compound cripowellin B. 1D and 2D-NMR techniques were used to determine the identities of 3 and 4 as the new compounds cripowellin C and D. A fifth compound was identified as the known alkaloid hippadine, which was inactive against Plasmodium falciparum. The antiplasmodial IC50 values of compounds 1-4 were determined to be 30±2, 180±20, 26±2, and 260±20nM, respectively, and their antiproliferative IC50 values against the A2780 human ovarian cancer cell line were 11.1±0.4, 16.4±0.1, 25±2, and 28±1nM.

New Antiplasmodial Diterpenes from Gutierrezia sarothrae.

Bioassay guided fractionation of the MeOH extract of the plant Gutierrezia sarothrae (Asteraceae) using an assay for antiplasmodial activity against the drug-resistant Dd2 strain of Plasmodium falciparum led to the isolation of the two new diterpenes 3α-angeloyloxy-15-hydroxylabda-7,13-dien-16,15-olid-18-oic acid (1) and 3α-angeloyloxy-15-methoxylabda-7,13-dien-16,15-olid-18-oic acid (2). The structures of 1 and 2 were elucidated by interpretation of 1D and 2D NMR spectroscopic data, mass spectrometry, and comparison with the data of related compounds reported in the literature. Compound 1 exhibited moderate antiplasmodial activity with an IC50 values of 10.4 ± 4.3 µM.

Antiplasmodial phloroglucinol derivatives from Syncarpia glomulifera.

Bioassay guided fractionation of a MeOH extract of the stem bark of Syncarpia glomulifera (Myrtaceae) led to the isolation of the two new phloroglucinol derivatives (±)-rhodomyrtosone F (1) and (±)-calliviminone I (2), the three known triterpenes, betulinic acid (3), ursolic acid-3-acetate (4), and ursolic acid (5), and 1-(2,4,6-trihydroxyphenyl)-1-hexanone (6). Compound 1 exhibited strong antiplasmodial activity, while compounds 2-4 were moderately active and 5 and 6 were inactive in this assay. The structures of 1 and 2 were elucidated based on analyses of their mass spectrometric data, 1D and 2D NMR spectra, and comparison with related compounds.