bluuebunny/crossref_metadata_2025 huggingface dataset:
Rasch-Built Overall Amyotrophic Lateral Sclerosis Disability Scale as a Novel Tool to Measure Disease Progression
Authors: Sun Can , Chen Yong , Xu Lu , Wang Wenjing , Zhang Nan , Fournier Christina N. , Li Nan , Fan Dongsheng
Published: January 2025

Background: A valuable outcome measure to monitor amyotrophic lateral sclerosis (ALS) disease progression is crucial in clinical trials. Rasch-Built Overall Amyotrophic Lateral Sclerosis Disability Scale (ROADS) is a novel questionnaire assessing ALS disability. Currently, there are no studies on the relationship between ROADS and ALS survival. This study explored the value of Chinese ROADS as a novel tool for measuring disease progression and the correlation between ROADS and ALS survival. Methods: A total of 170 ALS participants were included in this study. Clinical characteristics and baseline ROADS, ΔROADS, ALSFRS-R, and ΔFRS of patients were collected. Participants were followed for 18 months to assess time to tracheostomy and survival. Scales were collected every 3 to 6 months. We evaluated the association of baseline ROADS and ΔROADS with survival using Cox regression analyses. Linear mixed effects models were used to assess changes over time in ROADS and ALSFRS-R. Results: Multivariate Cox models confirmed that baseline ROADS positively correlated with ALS survival (HR = 0.95, p < 0.001), while baseline ΔROADS negatively correlated with survival (HR = 1.26, p < 0.001). Additionally, linear mixed effects models suggested that ROADS, similar to ALSFRS-R, declined significantly over time, but there was no significant difference between these two. Conclusions: Our study indicates that Chinese ROADS is strongly related to ALS survival. Changes in ROADS with disease progression are similar to those in ALSFRS-R. These findings support Chinese ROADS as a reliable outcome measure for clinical trials, potentially enhancing the dimension of evaluating treatment effectiveness in ALS trials.
Malnutrition and Its Influence on Gut sIgA–Microbiota Dynamics
Authors: Profir Monica , Enache Robert Mihai , Roşu Oana Alexandra , Pavelescu Luciana Alexandra , Creţoiu Sanda Maria , Gaspar Bogdan Severus
Published: January 2025

In the current era, malnutrition is seen as both undernutrition and overweight and obesity; both conditions are caused by nutrient deficiency or excess and improper use or imbalance in the intake of macro and micronutrients. Recent evidence suggests that malnutrition alters the intestinal microbiota, known as dysbiosis. Secretory immunoglobulin A (sIgA) plays an important role in maintaining and increasing beneficial intestinal microbiota populations and protecting against pathogenic species. Depletion of beneficial bacterial populations throughout life is also conditioned by malnutrition. This review aims to synthesize the evidence that establishes an interrelationship between diet, malnutrition, changes in the intestinal flora, and sIgA levels. Targeted nutritional therapies combined with prebiotic, probiotic, and postbiotic administration can restore the immune response in the intestine and the host’s homeostasis.
To Hemoadsorb or Not to Hemoadsorb—Do We Have the Answer Yet? An Updated Meta-Analysis on the Use of CytoSorb in Sepsis and Septic Shock
Authors: Orban Carmen , Bratu Angelica , Agapie Mihaela , Borjog Tudor , Jafal Mugurel , Sima Romina-Marina , Dumitrașcu Oana Clementina , Popescu Mihai
Published: January 2025

Severe inflammation leading to organ dysfunction is the cornerstone of the pathophysiology of sepsis. Thus, from a theoretical point of view, rebalancing inflammation has the potential to improve patient outcomes. Methods: To better understand the clinical effectiveness of hemoadsorption in managing inflammation, we conducted an updated meta-analysis on the effects of CytoSorb in critically ill septic patients. Ten studies containing 715 patients (355 in the interventional group and 360 in the control group) have been included in the final analysis. Results: Statistical analysis demonstrated that the use of CytoSorb did not influence overall mortality (OR 0.95, 95% CI [0.58, 1.56], p = 0.85), but we observed a decreased mortality when comparing CytoSorb-treated patients with patients in the control group treated with continuous renal replacement therapy (CRRT) (OR 0.97, 95% CI [0.46, 0.98], p = 0.04). We also observed an increased mortality in patients in whom hemoadsorption was initiated earlier in the treatment course (OR 0.97, 95% CI [0.46, 0.98], p = 0.04). We did not observe any significant difference in either intensive care unit length of stay (p = 0.93) or between end-of-treatment severity scores in the two groups (p = 0.24). Conclusions: Although it has a high risk of bias, current evidence does not support the routine use of CytoSorb in critically ill septic patients. The addition of CytoSorb to CRRT may be associated with decreased survival as compared to CRRT alone, but future studies are needed to draw a definitive conclusion.
Extend Plastron Longevity on Superhydrophobic Surface Using Gas Soluble and Gas Permeable Polydimethylsiloxane (PDMS)
Authors: Gupta Ankit , Ling Hangjian
Published: January 2025

The gas (or plastron) trapped between micro/nano-scale surface textures, such as that on superhydrophobic surfaces, is crucial for many engineering applications, including drag reduction, heat and mass transfer enhancement, anti-biofouling, anti-icing, and self-cleaning. However, the longevity of the plastron is significantly affected by gas diffusion, a process where gas molecules slowly diffuse into the ambient liquid. In this work, we demonstrated that plastron longevity could be extended using a gas-soluble and gas-permeable polydimethylsiloxane (PDMS) surface. We performed experiments for PDMS surfaces consisting of micro-posts and micro-holes. We measured the plastron longevity in undersaturated liquids by an optical method. Our results showed that the plastron longevity increased with increasing the thickness of the PDMS surface, suggesting that gas initially dissolved between polymer chains was transferred to the liquid, delaying the wetting transition. Numerical simulations confirmed that a thicker PDMS material released more gas across the PDMS–liquid interface, resulting in a higher gas concentration near the plastron. Furthermore, we found that plastron longevity increased with increasing pressure differences across the PDMS material, indicating that the plastron was replenished by the gas injected through the PDMS. With increasing pressure, the mass flux caused by gas injection surpassed the mass flux caused by the diffusion of gas from plastron to liquid. Overall, our results provide new solutions for extending plastron longevity and will have significant impacts on engineering applications where a stable plastron is desired.
Improving the Long-Term Mechanical Properties of Thermoplastic Short Natural Fiber Compounds by Using Alternative Matrices
Authors: Cosse Renato Lemos , van der Most Tobias , Voet Vincent S. D. , Folkersma Rudy , Loos Katja
Published: January 2025

Wood plastic composites (WPCs) offer a means to reduce the carbon footprint by incorporating natural fibers to enhance the mechanical properties. However, there is limited information on the mechanical properties of these materials under hostile conditions. This study evaluated composites of polypropylene (PP), polystyrene (PS), and polylactic acid (PLA) processed via extrusion and injection molding. Tests were conducted on tensile and flexural strength and modulus, heat deflection temperature (HDT), and creep analysis under varying relative humidity conditions (10% and 90%) and water immersion, followed by freeze—thaw cycles. The addition of fibers generally improved the mechanical properties but increased water absorption. HDT and creep were dependent on the crystallinity of the composites. PLA and PS demonstrated a superior overall performance, except for their impact properties, where PP was slightly better than PLA.
Developing a Label-Free Infrared Spectroscopic Analysis with Chemometrics and Computational Enhancement for Assessing Lupus Nephritis Activity
Authors: Yu Mei-Ching , Huang Xiang-Di , Kuo Chin-Wei , Zhang Kai-Fu , Liang Ping-Chung , Jeng U-Ser , Huang Pei-Yu , Tam Frederick Wai Keung , Lee Yao-Chang
Published: January 2025

Patterns of disease and therapeutic responses vary widely among patients with autoimmune glomerulonephritis. This study introduces groundbreaking personalized infrared (IR)-based diagnostics for real-time monitoring of disease status and treatment responses in lupus nephritis (LN). We have established a relative absorption difference (RAD) equation to assess characteristic spectral indices based on the temporal peak heights (PHs) of two characteristic serum absorption bands: ν1 as the target signal and ν2 as the PH reference for the ν1 absorption band, measured at each dehydration time (t) during dehydration. The RAD gap (Ψ), defined as the difference in the RAD values between the initial and final stages of serum dehydration, enables the measurement of serum levels of IgG glycosylation (ν1 (1030 cm−1), ν2 (1171 cm−1)), serum lactate (ν1 (1021 cm−1), ν2 (1171 cm−1)), serum hydrophobicity (ν1 (2930 cm−1), ν2 (2960 cm−1)), serum hydrophilicity (ν1 (1550 cm−1), ν2 (1650 cm−1)), and albumin (ν1 (1400 cm−1), ν2 (1450 cm−1)). Furthermore, this IR-based assay incorporates an innovative algorithm and our proprietary iPath software (ver. 1.0), which calculates the prognosis prediction function (PPF, Φ) from the RAD gaps of five spectral markers and correlates these with conventional clinical renal biomarkers. We propose that this algorithm-assisted, IR-based approach can augment the patient-centric care of LN patients, particularly by focusing on changes in serum IgG glycosylation.
MicroVi: A Cost-Effective Microscopy Solution for Yeast Cell Detection and Count in Wine Value Chain
Authors: Benito-Altamirano Ismael , Moreno Sergio , Vaz-Romero David M. , Puig-Pujol Anna , Roca-Domènech Gemma , Canals Joan , Vilà Anna , Prades Joan Daniel , Diéguez Ángel
Published: January 2025

In recent years, the wine industry has been researching how to improve wine quality along the production value chain. In this scenario, we present here a new tool, MicroVi, a cost-effective chip-sized microscopy solution to detect and count yeast cells in wine samples. We demonstrate that this novel microscopy setup is able to measure the same type of samples as an optical microscopy system, but with smaller size equipment and with automated cell count configuration. The technology relies on the top of state-of-the-art computer vision pipelines to post-process the images and count the cells. A typical pipeline consists of normalization, feature extraction (i.e., SIFT), image composition (to increase both resolution and scanning area), holographic reconstruction and particle count (i.e., Hough transform). MicroVi achieved a 2.19 µm resolution by properly resolving the G7.6 features from the USAF Resolving Power Test Target 1951. Additionally, we aimed for a successful calibration of cell counts for Saccharomyces cerevisiae. We compared our direct results with our current optical setup, achieving a linear calibration for measurements ranging from 0.5 to 50 million cells per milliliter. Furthermore, other yeast cells were qualitatively resolved with our MicroVi microscope, such as, Brettanomyces bruxellensis, or bacteria, like, Lactobacillus plantarum, thus confirming the system’s reliability for consistent microbial assessment.
Exploring Innovative Approaches for the Analysis of Micro- and Nanoplastics: Breakthroughs in (Bio)Sensing Techniques
Authors: Rivera-Rivera Denise Margarita , Quintanilla-Villanueva Gabriela Elizabeth , Luna-Moreno Donato , Sánchez-Álvarez Araceli , Rodríguez-Delgado José Manuel , Cedillo-González Erika Iveth , Kaushik Garima , Villarreal-Chiu Juan Francisco , Rodríguez-Delgado Melissa Marlene
Published: January 2025

Plastic pollution, particularly from microplastics (MPs) and nanoplastics (NPs), has become a critical environmental and health concern due to their widespread distribution, persistence, and potential toxicity. MPs and NPs originate from primary sources, such as cosmetic microspheres or synthetic fibers, and secondary fragmentation of larger plastics through environmental degradation. These particles, typically less than 5 mm, are found globally, from deep seabeds to human tissues, and are known to adsorb and release harmful pollutants, exacerbating ecological and health risks. Effective detection and quantification of MPs and NPs are essential for understanding and mitigating their impacts. Current analytical methods include physical and chemical techniques. Physical methods, such as optical and electron microscopy, provide morphological details but often lack specificity and are time-intensive. Chemical analyses, such as Fourier transform infrared (FTIR) and Raman spectroscopy, offer molecular specificity but face challenges with smaller particle sizes and complex matrices. Thermal analytical methods, including pyrolysis gas chromatography–mass spectrometry (Py-GC-MS), provide compositional insights but are destructive and limited in morphological analysis. Emerging (bio)sensing technologies show promise in addressing these challenges. Electrochemical biosensors offer cost-effective, portable, and sensitive platforms, leveraging principles such as voltammetry and impedance to detect MPs and their adsorbed pollutants. Plasmonic techniques, including surface plasmon resonance (SPR) and surface-enhanced Raman spectroscopy (SERS), provide high sensitivity and specificity through nanostructure-enhanced detection. Fluorescent biosensors utilizing microbial or enzymatic elements enable the real-time monitoring of plastic degradation products, such as terephthalic acid from polyethylene terephthalate (PET). Advancements in these innovative approaches pave the way for more accurate, scalable, and environmentally compatible detection solutions, contributing to improved monitoring and remediation strategies. This review highlights the potential of biosensors as advanced analytical methods, including a section on prospects that address the challenges that could lead to significant advancements in environmental monitoring, highlighting the necessity of testing the new sensing developments under real conditions (composition/matrix of the samples), which are often overlooked, as well as the study of peptides as a novel recognition element in microplastic sensing.
Explainable Self-Supervised Dynamic Neuroimaging Using Time Reversal
Authors: Iqbal Zafar , Rahman Md. Mahfuzur , Mahmood Usman , Zia Qasim , Fu Zening , Calhoun Vince D. , Plis Sergey
Published: January 2025

Objective: Functional magnetic resonance imaging data pose significant challenges due to their inherently noisy and complex nature, making traditional statistical models less effective in capturing predictive features. While deep learning models offer superior performance through their non-linear capabilities, they often lack transparency, reducing trust in their predictions. This study introduces the Time Reversal (TR) pretraining method to address these challenges. TR aims to learn temporal dependencies in data, leveraging large datasets for pretraining and applying this knowledge to improve schizophrenia classification on smaller datasets. Methods: We pretrained an LSTM-based model with attention using the TR approach, focusing on learning the direction of time in fMRI data, achieving over 98 % accuracy on HCP and UK Biobank datasets. For downstream schizophrenia classification, TR-pretrained weights were transferred to models evaluated on FBIRN, COBRE, and B-SNIP datasets. Saliency maps were generated using Integrated Gradients (IG) to provide post hoc explanations for pretraining, while Earth Mover’s Distance (EMD) quantified the temporal dynamics of salient features in the downstream tasks. Results: TR pretraining significantly improved schizophrenia classification performance across all datasets: median AUC scores increased from 0.7958 to 0.8359 (FBIRN), 0.6825 to 0.7778 (COBRE), and 0.6341 to 0.7224 (B-SNIP). The saliency maps revealed more concentrated and biologically meaningful salient features along the time axis, aligning with the episodic nature of schizophrenia. TR consistently outperformed baseline pretraining methods, including OCP and PCL, in terms of AUC, balanced accuracy, and robustness. Conclusions: This study demonstrates the dual benefits of the TR method: enhanced predictive performance and improved interpretability. By aligning model predictions with meaningful temporal patterns in brain activity, TR bridges the gap between deep learning and clinical relevance. These findings emphasize the potential of explainable AI tools for aiding clinicians in diagnostics and treatment planning, especially in conditions characterized by disrupted temporal dynamics.
Correction: Cooper et al. A Retrospective Study Reviewing Timing to Onset of Habitual Psychogenic Non-Epileptic Seizures in a Home Video Telemetry Cohort. Brain Sci. 2024, 14, 1187
Authors: Cooper Jade , Chester Helen , Fozzato Arianna , Sokolov Elisaveta
Published: January 2025

In the original publication [...]
Mental Health, Emotional Regulation, and Psychosocial Work Factors Among Scientific Researchers: A Cross-Sectional Study from Paraguay
Authors: Torales Julio , Torres-Romero Anthon , Barrios Iván , O’Higgins Marcelo , Caycho-Rodríguez Tomás , Castaldelli-Maia João Mauricio , Ventriglio Antonio
Published: January 2025

Background: This study examined the prevalence of mental health issues among Paraguayan researchers and their relationships with emotional regulation and psychosocial factors. Methods: A cross-sectional survey of 235 researchers was conducted using validated instruments: the Depression, Anxiety, and Stress Scale (DASS-21); the Job Content Questionnaire (JCQ); and the Difficulties in Emotion Regulation Scale (DERS). Sociodemographic, academic, and behavioral variables were also analyzed. Results: Findings revealed significant rates of depression (26.4%), anxiety (30.6%), and stress (32.3%), with female researchers reporting nearly twice the rates of anxiety and stress compared to males. Researchers with doctoral degrees exhibited lower anxiety levels, emphasizing the protective role of advanced academic qualifications. Conversely, younger and early-career researchers were more vulnerable to psychological distress. High job demands and emotional dysregulation were strongly associated with poorer mental health outcomes, while hazardous alcohol consumption and low physical activity further exacerbated risks. Conclusions: These findings highlight the urgent need for institutional reforms to prioritize mental health and well-being in academic environments. By advancing the understanding of occupational health in resource-limited settings, this study provides actionable recommendations to improve the working conditions and mental health of researchers in Paraguay and beyond.
Examining the Role of Psychological Symptoms and Safety Climate in Shaping Safety Behaviors Among Construction Workers
Authors: Guo Na , Liu Yong , Yu Shiwang , Xia Bo , Cong Weiyi
Published: January 2025

Construction workers are often subjected to strenuous manual labor, poor working conditions, and prolonged separation from family, leading to psychological symptoms such as stress, depression, and anxiety. These psychological factors, combined with safety climate elements like risk perception and safety attitude, significantly influence workers’ safety behaviors, including risk-taking, safety compliance, and safety participation. To address these issues, this study investigates the interplay between psychological symptoms, safety climate, and safety behaviors among construction workers in Mainland China. Data were collected through a survey of 160 construction workers, with results analyzed using correlation and regression techniques. The findings reveal that: (1) risky behavior is primarily driven by anxiety and risk perception; (2) safety participation is influenced by safety attitudes and levels of depression; and (3) safety compliance is affected by risk perception, safety attitude, stress, and depression. Interestingly, an inverse relationship is observed between depression and both risky behavior and safety compliance. These results underscore the importance of addressing psychological well-being to improve safety outcomes. Practical implications include providing psychological counseling, stress management training, and improving social connections for workers, such as facilitating regular video calls with family members or offering travel reimbursements.
The Role of Cytoreductive Surgery in Platinum-Resistant Ovarian Cancer (PROC): A Systematic Review
Authors: Sideris Michail , Jamdade Kshitij , Essangri Hajar , Zalawadia Shruti , Oxley Samuel George , Selek Kagan , Phadnis Saurabh
Published: January 2025

Background/Objective: Platinum-resistant ovarian cancer (PROC) has limited therapeutic options, and the role of cytoreductive surgery (CRS) in improving survival outcomes remains uncertain. We performed a systematic review to evaluate the oncological benefit of CRS on PROC patients and the associated surgical morbidity and mortality. Methods: We followed a prospective protocol according to PRISMA guidelines. We searched PubMed, Medline, and Embase till October 2024. We used a “Population Intervention Comparator Outcomes (PICO)” framework. Our population included women with epithelial PROC who underwent CRS with/without chemotherapy. Our outcomes included overall survival (OS), progression-free-survival (PFS), post-operative morbidity and mortality and Quality of Life. Results: Our search yielded 6590 citations; six studies (N = 155 patients) were included. There is limited evidence available on the role of CRS in PROC, with notable variation in reported outcomes and outcomes’ measures; therefore, we were unable to perform quantitative synthesis. CRS demonstrated survival benefits in well-selected PROC patients, particularly those with limited, isolated recurrences, low tumour burden, and good performance status. Complete resection (R0) was associated with significantly longer OS/PFS compared to those who had suboptimal surgeries (R1/R2). Conclusions: CRS seems to extend survival in carefully selected PROC patients, especially those with limited disease spread and favourable surgical profiles. Nevertheless, CRS carries substantial surgical risks, and its benefits appear contingent upon achieving R0. Further prospective trials with standardised patient selection criteria are needed to define CRS’s role in PROC. At present, CRS in PROC should be considered within a multidisciplinary approach in specialised gynaecological oncology centres, with the careful assessment of patient-specific risk factors and potential for R0 resection.
Incidence and Prevalence of Bone Metastases in Different Solid Tumors Determined by Natural Language Processing of CT Reports
Authors: Long Niamh , Woodlock David , D’Agostino Robert , Nguyen Gary , Gangai Natalie , Sevilimedu Varadan , Do Richard Kinh Gian
Published: January 2025

Background/Objectives: Improved survival due to advances in medical therapy has resulted in increasing numbers of cancer patients living with bone metastases; however, our understanding of the prognostic implications of bone metastases requires larger population-based studies outlining their incidence and prevalence in different primary cancer types, including those with lower incidence. This study aimed to evaluate the incidence and prevalence of bone metastases in solid organ tumors by analyzing reports of staging CT studies with natural language processing (NLP). Methods: In this retrospective study, 639,470 reports representing 129,326 unique patients were analyzed; 6279 randomly selected reports were manually annotated and labeled for the presence or absence of bone metastases. From these data, a BERT-based NLP model was developed and applied to the patient database. The cumulative incidence at 5 years and prevalence of bone metastases in each cancer type were calculated. Results: The accuracy of the NLP model on a validation set was 97.1%, with a positive predictive value (precision) of 88.0% and a sensitivity (recall) of 86.3%. The 5-year incidence rate of bone metastases was highest in prostate, breast, head and neck, and lung cancer (52%, 41%, 36%, 33%). Incidence was lowest in central nervous system cancer and testicular cancer (8%, 5%). Prevalence was highest in prostate, breast, and lung cancer (32%, 25% and 23%), and lowest in central nervous system cancer and testicular cancer (4%, 4%). Conclusions: NLP was utilized to demonstrate patterns of bone metastases in a broad range of cancer types and is a valuable tool in population-based assessment of bone metastases.
Prognostic Significance of Lymph Node Ratio in Intrahepatic and Extrahepatic Cholangiocarcinomas
Authors: Khomiak Andrii , Ghaffar Sumaya Abdul , Rodriguez Franco Salvador , Ziogas Ioannis Asterios , Cumbler Ethan , Gleisner Ana Luiza , Del Chiaro Marco , Schulick Richard David , Mungo Benedetto
Published: January 2025

Background/Objectives. Lymph Node Ratio (LNR) is increasingly recognized as an important prognostic factor in various cancer types, with the potential to enhance patient stratification for intrahepatic (ICC) and extrahepatic (ECC) cholangiocarcinoma. The study aimed to assess the impact of LNR on survival in surgically resected patients with ICC and ECC. Methods. This was a retrospective analysis of National Cancer Database (2004–2020) included ICC and ECC (excluding distal bile duct) patients who underwent primary site resection with adequate lymphadenectomy (≥4 LNs excised). Exclusions comprised age < 18 years, distant metastasis, or incomplete key data. LNR was calculated as the ratio of positive LNs to total examined LNs. Survival probabilities were estimated using Kaplan–Meier analysis and Cox regression. Results. The inclusion criteria were met by 954 patients with ICC and 1607 patients with ECC. In patients with ICC, the median OS time was 62.7 months in LNR0 group, 40.8 months in LNR < 30%, and 25.2 months in LNR ≥ 30% (p < 0.001). In ICC, 3-year OS was 69.3%, 54.6%, and 34% for LNR 0, LNR < 30%, and LNR ≥ 30%, respectively (p < 0.05). When adjusted for age, sex, Charlson–Deyo score, histology, surgical margins, chemo- and radiotherapy using Cox regression, LNR < 30% and LNR ≥ 30% were associated with worse OS in patients with ICC (HR 2.1 (95% CI 1.6–2.7) and HR 2.94 (95% CI 2.3–3.8)) and ECC (HR 2.1 (95% CI 1.8–2.5) and HR 3 (95% CI 2.4–3.7)). Conclusions. It is well-known that LN-negative patients have significantly better survival than LN-positive patients with ICC and ECC. This study strongly demonstrates that survival prognosis can be further stratified based on LNR for ICC and ECC patients and that it is not simply a binary factor.
Patient Acceptability of the First Integrative Pediatric Oncology Unit in Spain—The Pediatric Cancer Center Barcelona Experience: A Retrospective Study
Authors: Martínez García Esther , López de San Roman Fernández Cristina , Nishishinya Aquino M. Betina , Pérez-Jaume Sara , Fernández-Jané Carles , Cruz Martínez Ofelia , Morales La Madrid Andrés
Published: January 2025

Background/Objectives: Pediatric cancer patients and their families are increasingly combining conventional treatment with complementary therapies. These therapies are not covered by most public healthcare systems, and Spain is not an exception. To address this need, the Pediatric Cancer Center Barcelona, at the Hospital Sant Joan de Déu (Spain), established the first integrative pediatric oncology unit in 2019. The objective of this study is to describe the feasibility of implementing a pediatric integrative oncology unit, in terms of the acceptance of the interventions, as well as to present initial data on the care activities; Methods: This is a retrospective single-center study, conducted in the Pediatric Cancer Center Barcelona, at the Hospital Sant Joan de Déu. Data from patients during a two-year period were collected by reviewing medical records in a pseudonymous manner; Results: From 1 September 2019 to 30 September 2021, the unit was visited by 433 patients. The median age of patients was 9 years [range 0–34 years], with 266 boys (61.4%) and 167 girls (38.6%). Of these patients, 90.1% were in active treatment, 7.6% were survivors, and 2.3% were at the end of life. Acupuncture was recommended to 227 patients, with a 94.7% acceptance rate. Aromatherapy was recommended to 114 patients, with a 100% acceptance. The reflexology team visited 129 patients, delivering a total of 414 sessions, with a 96.1% acceptance.; Conclusions: The findings of our study support the feasibility of implementing an Integrative Pediatric Oncology Unit within a patient-centered care model in a comprehensive pediatric cancer center. The high acceptance rates of various complementary therapies highlight their potential role in enhancing supportive care for pediatric oncology patients.
Direct Prediction of 48 Month Survival Status in Patients with Uveal Melanoma Using Deep Learning and Digital Cytopathology Images
Authors: Liu T. Y. Alvin , Chen Haomin , Koseoglu Neslihan Dilruba , Kolchinski Anna , Unberath Mathias , Correa Zelia M.
Published: January 2025

Background: Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. The median overall survival time for patients who develop metastasis is approximately one year. In this study, we aim to leverage deep learning (DL) techniques to analyze digital cytopathology images and directly predict the 48 month survival status on a patient level. Methods: Fine-needle aspiration biopsy (FNAB) of the tumor was performed in each patient diagnosed with UM. The cell aspirate was smeared on a glass slide and stained with H&E. Each slide then underwent whole-slide scanning. Within each whole-slide image, regions of interest (ROIs) with UM cells were automatically extracted. Each ROI was converted into super pixels, and the super pixels were automatically detected, segmented and annotated as “tumor cell” or “background” using DL. Cell-level features were extracted from the segmented tumor cells. The cell-level features were aggregated into slide-level features which were learned by a fully connected layer in an artificial neural network, and the patient survival status was predicted directly from the slide-level features. The data were partitioned at the patient level (78% training and 22% testing). Our DL model was trained to perform the binary prediction of yes-versus-no survival by Month 48. The ground truth for patient survival was established via a retrospective chart review. Results: A total of 74 patients were included in this study (43% female; mean age at the time of diagnosis: 61.8 ± 11.6 years), and 207,260 unique ROIs were generated for model training and testing. By Month 48 after diagnosis, 18 patients (24%) died from UM metastasis. Our hold-out test set contained 16 patients, where 6 patients had passed away and 10 patients were alive at Month 48. When using a sensitivity threshold of 80% in predicting UM-specific death by Month 48, our model achieved an overall accuracy of 75%. Within the subgroup of patients who died by Month 48, our model achieved a prediction accuracy of 83%. Of note, one patient in our test set was a clinical surprise, namely death by Month 48 despite having a GEP class 1A tumor, which typically portends a good prognosis. Our model correctly predicted this clinical surprise as well. Conclusions: Our DL model was able to predict the Month 48 survival status directly from digital cytopathology images obtained from FNABs of UM tumors with reasonably robust performance. This approach, if validated prospectively, could serve as an alternative survival prediction tool for patients with UM to whom GEP is not available.
The Role of [18F]FDG PET and Clinicopathologic Factors in Detecting and Predicting Bone Marrow Involvement in Non-Hodgkin Lymphoma
Authors: Al-Ibraheem Akram , Abdlkadir Ahmad Saad , Hasasna Nabil , Alalawi Hasan , Mohamedkhair Ali , Al-Yazjeen Salem , Obeidat Shahed , Rabei Obayda , Al-Jarrah Dua’a , Shahin Omar , Al-Rabi Kamal , Makoseh Mohammad , Almasri Nidal
Published: January 2025

Background/Objectives: This study evaluates the diagnostic accuracy of [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) using bone marrow biopsy (BMB) and clinical follow-up as reference standards. It further identifies predictive factors for bone marrow involvement (BMI) in non-Hodgkin lymphoma (NHL) patients. Methods: NHL patients who underwent [18F]FDG PET and BMB at diagnosis in a tertiary cancer center were included in this study. Diagnostic accuracy was analyzed, and logistic regression was performed to identify BMI predictors using Stata software version 17. A retrospective analysis of 262 NHL patients was conducted. Results: Concordance rates between [18F]FDG PET and BMB and between [18F]FDG PET and clinical follow-up were 75.6% and 88.1%, respectively. The primary cause of discordance between [18F]FDG PET and BMB was the detection of extra-iliac focal hypermetabolic bone marrow lesions by [18F]FDG PET, which were negative on BMB. The sensitivity, specificity, and accuracy of [18F]FDG PET were 62.9%, 80%, and 75.6%, respectively, with BMB as a reference, and 74.1%, 97.5%, and 88.2%, respectively, with clinical follow-up as a reference. The focal bone marrow [18F]FDG pattern was the most reliable indicator of BMI. Univariate logistic regression showed that advanced NHL stage, elevated alkaline phosphatase, thrombocytopenia, leukopenia, and elevated lactate dehydrogenase were significant predictors of BMI. Multivariate analysis revealed advanced NHL stage and thrombocytopenia as clinical predictors. Conclusions: [18F]FDG PET is a reliable tool for assessing BMI, providing comprehensive total-body evaluation and identifying extra-iliac involvement beyond the scope of BMB. The collective interpretation of molecular imaging, clinical, and biochemical factors is crucial for predicting BMI.
Enhancing Treatment Decisions for Advanced Non-Small Cell Lung Cancer with Epidermal Growth Factor Receptor Mutations: A Reinforcement Learning Approach
Authors: Bozcuk Hakan Şat , Sert Leyla , Kaplan Muhammet Ali , Tatlı Ali Murat , Karaca Mustafa , Muğlu Harun , Bilici Ahmet , Kılıçtaş Bilge Şah , Artaç Mehmet , Erel Pınar , Yumuk Perran Fulden , Bilgin Burak , Şendur Mehmet Ali Nahit , Kılıçkap Saadettin , Taban Hakan , Ballı Sevinç , Demirkazık Ahmet , Akdağ Fatma , Hacıbekiroğlu İlhan , Güzel Halil Göksel , Koçer Murat , Gürsoy Pınar , Köylü Bahadır , Selçukbiricik Fatih , Karakaya Gökhan , Alemdar Mustafa Serkan
Published: January 2025

Background: Although higher-generation TKIs are associated with improved progression-free survival in advanced NSCLC patients with EGFR mutations, the optimal selection of TKI treatment remains uncertain. To address this gap, we developed a web application powered by a reinforcement learning (RL) algorithm to assist in guiding initial TKI treatment decisions. Methods: Clinical and mutational data from advanced NSCLC patients were retrospectively collected from 14 medical centers. Only patients with complete data and sufficient follow-up were included. Multiple supervised machine learning models were tested, with the Extra Trees Classifier (ETC) identified as the most effective for predicting progression-free survival. Feature importance scores were calculated by the ETC, and features were then integrated into a Deep Q-Network (DQN) RL algorithm. The RL model was designed to select optimal TKI generation and a treatment line for each patient and was embedded into an open-source web application for experimental clinical use. Results: In total, 318 cases of EGFR-mutant advanced NSCLC were analyzed, with a median patient age of 63. A total of 52.2% of patients were female, and 83.3% had ECOG scores of 0 or 1. The top three most influential features identified were neutrophil-to-lymphocyte ratio (log-transformed), age (log-transformed), and the treatment line of TKI administration, as tested by the ETC algorithm, with an area under curve (AUC) value of 0.73, whereas the DQN RL algorithm achieved a higher AUC value of 0.80, assigning distinct Q-values across four TKI treatment categories. This supports the decision-making process in the web-based ‘EGFR Mutant NSCLC Treatment Advisory System’, where clinicians can input patient-specific data to receive tailored recommendations. Conclusions: The RL-based web application shows promise in assisting TKI treatment selection for EGFR-mutant advanced NSCLC patients, underscoring the potential for reinforcement learning to enhance decision-making in oncology care.
Molecular Insights on Signaling Cascades in Breast Cancer: A Comprehensive Review
Authors: Panda Venketesh K. , Mishra Barnalee , Mahapatra Samikshya , Swain Biswajit , Malhotra Diksha , Saha Suryendu , Khanra Sinjan , Mishra Priyanka , Majhi Sambhunath , Kumari Kavita , Nath Angitha N. , Saha Swarnali , Jena Sarmistha , Kundu Gopal C.
Published: January 2025

The complex signaling network within the breast tumor microenvironment is crucial for its growth, metastasis, angiogenesis, therapy escape, stem cell maintenance, and immunomodulation. An array of secretory factors and their receptors activate downstream signaling cascades regulating breast cancer progression and metastasis. Among various signaling pathways, the EGFR, ER, Notch, and Hedgehog signaling pathways have recently been identified as crucial in terms of breast cancer proliferation, survival, differentiation, maintenance of CSCs, and therapy failure. These receptors mediate various downstream signaling pathways such as MAPK, including MEK/ERK signaling pathways that promote common pro-oncogenic signaling, whereas dysregulation of PI3K/Akt, Wnt/β-catenin, and JAK/STAT activates key oncogenic events such as drug resistance, CSC enrichment, and metabolic reprogramming. Additionally, these cascades orchestrate an intricate interplay between stromal cells, immune cells, and tumor cells. Metabolic reprogramming and adaptations contribute to aggressive breast cancer and are unresponsive to therapy. Herein, recent insights into the novel signaling pathways operating within the breast TME that aid in their advancement are emphasized and current developments in practices targeting the breast TME to enhance treatment efficacy are reviewed.
Association of Increased CT-Attenuation of Visceral Adipose Tissue After Surgery with Poor Survival Outcomes in Patients with Stage II–III Gastric Cancer: A Retrospective Cohort Study
Authors: Lee Sang Mi , Song Geum Jong , Son Myoung Won , Yun Jong Hyuk , Lee Moon-Soo , Lee Jeong Won
Published: January 2025

Background/Objectives: This study aimed to investigate whether post-operative changes in the computed tomography (CT)-attenuation of subcutaneous (SAT) and visceral (VAT) adipose tissues were significantly associated with recurrence-free survival (RFS), peritoneal RFS, and overall survival (OS) in patients with stage II–III gastric cancer. Methods: This retrospective study analyzed 243 patients with stage II–III gastric cancer who underwent curative surgery. CT-attenuation values of SAT (SAT HU) and VAT (VAT HU) were measured from non-contrast-enhanced abdominopelvic CT images taken pre-operatively and 6 months post-operatively. Changes in SAT HU (ΔSAT HU) and VAT HU (ΔVAT HU) between the two CT scans were calculated. The prognostic value of these variables for predicting survival outcomes was assessed. Results: Correlation analyses showed that both ΔSAT HU and ΔVAT HU were significantly positively correlated with T stage, TNM stage, and tumor size (p < 0.05). In the multivariate survival analysis, ΔVAT HU emerged as an independent significant predictor for RFS (p = 0.002, hazard ratio, 2.437), peritoneal RFS (p = 0.023, hazard ratio, 2.457), and OS (p = 0.043, hazard ratio, 2.204) after adjusting for age, sex, histopathological classification, T stage, and N stage. Patients with high ΔVAT HU had worse RFS, peritoneal RFS, and OS compared to those with low ΔVAT HU. Conclusions: Change in CT-attenuation of VAT following surgery was significantly correlated with tumor characteristics and was a significant predictor of RFS, peritoneal RFS, and OS in patients with stage II–III gastric cancer.
Imaging of Peripheral Intraneural Tumors: A Comprehensive Review for Radiologists
Authors: Shirodkar Kapil , Hussein Mohsin , Reddy Pellakuru Saavi , Shah Ankit B. , Raniga Sameer , Pal Devpriyo , Iyengar Karthikeyan P. , Botchu Rajesh
Published: January 2025

Background/Objectives: Intraneural tumors (INTs) pose a diagnostic challenge, owing to their varied origins within nerve fascicles and their wide spectrum, which includes both benign and malignant forms. Accurate diagnosis and management of these tumors depends upon the skills of the radiologist in identifying key imaging features and correlating them with the patient’s clinical symptoms and examination findings. Methods: This comprehensive review systematically analyzes the various imaging features in the diagnosis of intraneural tumors, ranging from basic MR to advanced MR imaging techniques such as MR neurography (MRN), diffusion tensor imaging (DTI), and dynamic contrast-enhanced (DCE) MRI. Results: The article emphasizes the differentiation of benign from malignant lesions using characteristic MRI features, such as the “target sign” and “split-fat sign” for tumor characterization. The role of advanced multiparametric MRI in improving biopsy planning, guiding surgical mapping, and enhancing post-treatment monitoring is also highlighted. The review also underlines the importance of common diagnostic pitfalls and highlights the need for a multi-disciplinary approach to achieve an accurate diagnosis, appropriate treatment strategy, and post-therapy surveillance planning. Conclusions: In this review, we illustrate the main imaging findings of intraneural tumors, focusing on specific MR imaging features that are crucial for an accurate diagnosis and the differentiation between benign and malignant lesions.
Carbon Dioxide-Assisted Gasification of Fresh and Pyrolysis Residues of Macadamia F.Muell Nutshells: The Catalytic Properties of Na, K, and Co
Authors: Medvedev Artem A. , Beldova Daria A. , Nizameev Irek R. , Polikarpova Svetlana B. , Mashkin Mikhail Yu. , Bayburskiy Vladimir L. , Sokolovskiy Pavel V. , Kustov Alexander L. , Kustov Leonid M.
Published: January 2025

Residual Macadamia F.Muell nutshell gasification assisted by CO2 was studied in this work. Monometallic Co, Na, and K and bimetallic CoNa and CoK catalysts were prepared and tested in the catalytic process. The idea of this research was to try to find any synergism between already known catalytically active components and to investigate possible ways to use mixed materials. All the materials under investigation were examined by SEM-EDX and XRD. The DTA-TG of the initial fresh macadamia nutshell was presented in this work. The synergism between the Co and K components was revealed in the CO2-assisted gasification process. The found optimal catalyst was 1.5 wt%K-1.5 wt% Co/PMNS.
Cobalt(II)-Catalyzed C−H Deuteriomethoxylation of Benzamides with CD3OD
Authors: Tan Yu-Yan , Huang Mao-Gui , Feng Wei , Niu Mengyuan , Li Jia-Wei , Liu Yue-Jin
Published: January 2025

Herein, we report a practical example of salicylaldehyde-based cobalt-catalyzed C−H deuteriomethoxylation of benzamides using deuterated methanol, facilitated by 8-aminoquinoline as a directing group. The salicylaldehyde-based cobalt catalyst is user-friendly, and the reaction exhibits broad functional group tolerance, accommodating benzene, heterocycles, and naphthalene rings. The synthetic utility of this methodology was demonstrated through a gram-scale reaction and the subsequent removal of the 8-aminoquinoline directing group to yield deuteriomethoxylated benzoic acid. Preliminary mechanistic studies suggest that C−H activation is not the rate-determining step of the reaction.
Microemulsion-Based Synthesis of Highly Efficient Ag-Doped Fibrous SiO2-TiO2 Photoanodes for Photoelectrochemical Water Splitting
Authors: Arain Samia , Usman Muhammad , Saeed Faiq , Feng Shouzhong , Rehman Waheed , Liu Xianhua , Dai Haitao
Published: January 2025

Fibrous SiO2-TiO2 (FST) is one of the most promising materials for advancing photoelectrochemical water-splitting technology due to its cost-effectiveness and environmental friendliness. However, FST faces intrinsic limitations, including its low conductivity and wide bandgap. In this study, significant progress was made in modifying FST to overcome some of these limitations. This work involved synthesizing a new photoanode made of Ag-doped FST utilizing the microemulsion process. The Ag-doped FST was characterized using XRD, FTIR, UV–Vis, DRS, N2 adsorption–desorption, FESEM, TEM, and XPS. The results confirmed the formation of a continuous concentric lamellar structure with a large surface area. The addition of Ag species into the FST matrix caused interactions that reduced the bandgap. The Ag-doped FST photoanode exhibited an impressive photocurrent density of 13.98 mA/cm2 at 1.2 V (vs. RHE). This photocurrent density was notably higher than that of FST photoanodes, which was 11.65 mA/cm2 at 1.2 V (vs. RHE). Furthermore, the conduction band of Ag-doped FST is positioned closer to the reduction potential of hydrogen compared to that of FST, SiO2, and TiO2, facilitating rapid charge transfer and enabling the spontaneous generation of H2. The fabrication of Ag-doped FST provides valuable insights into the development of high-performance photoanodes for PEC water splitting.
Risk Factors and Clinical Predictors of Suicidal Behaviors and Non-Suicidal Self-Injury Among Pediatric Psychiatry Emergency Admissions Pre- and Post-Pandemic: A Retrospective Cohort Study
Authors: Șipoș Roxana , Văidean Tudor , Predescu Elena
Published: January 2025

Background: Suicidal behavior (SB) and non-suicidal self-injury (NSSI) are significant public health concerns among adolescents. The COVID-19 pandemic may have exacerbated these issues. Methods: This retrospective cohort study analyzed data from 341 adolescents (aged 6–18 years) presenting to a Romanian pediatric psychiatry emergency department during the years 2019 (pre-pandemic) and 2022 (post-pandemic). All participants underwent a thorough psychiatric assessment, and, together with their caregivers, were questioned on a wide range of potentially relevant issues, such as family, social, school, and life history factors. Logistic regression and random forest models were used to identify predictors of SB and NSSI. Results: SB was significantly predicted in regression models based on a prior suicidal ideation (OR = 68.410; p < 0.001), having a parent living abroad (OR = 11.438; p = 0.020), depression (OR = 6.803; p < 0.001), and conflicts with peers (OR = 0.325, p = 0.042), teachers (OR = 0.119, p = 0.024), or both (OR = 0.166, p = 0.012). The random forest model featured a slightly different order of the main predictors and highlighted the importance of additional predictors, such as prior suicide attempts, gender, and past non-suicidal self-injury. NSSI was mainly predicted by a history of self-harm (OR = 52.437; p < 0.001), the number of comorbid psychiatric disorders (OR = 1.709; p = 0.003), and conduct disorder (OR = 0.184; p < 0.001), to which are added, according to random forest models, new predictors, such as borderline personality disorder, suicidal ideation, and school performance. Post-pandemic increases were observed in depression, suicidal ideation, and possible psycho-traumatic negative life event exposure. Conclusions: This study underscores the complex interplay of individual, familial, and societal factors influencing adolescent self-harm. Comprehensive interventions are needed, with early intervention crucial for those with a history of self-harm. Further research using prospective designs is recommended.