bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feasibility of intraoperative neuromonitoring and cortical/subcortical mapping in patients with cerebral lesions of highly functional localizations—pathway to case adapted monitoring and mapping procedures
Authors: Staub-Bartelt Franziska , Rapp Marion , Sabel Michael 
Published: November 2023

BackgroundIntraoperative neuromonitoring (IONM) and mapping procedures via direct cortical stimulation (DCS) are required for resection of eloquently located cerebral lesions. In our neurooncological department, mapping and monitoring are used either combined or separately for surgery of functional lesions. The study aims to provide a practical insight into strengths and pitfalls of intraoperative neuromonitoring and mapping in supratentorial functionally located infiltrating lesions.MethodsIONM and mapping techniques performed in eloquent located brain tumors were analyzed with a focus on neurological outcome and resection results obtained via MRI. Additionally, the surgeons’ view on obligatory techniques was explored retrospectively immediately after surgery. To evaluate the impact of the described items, we correlated intraoperative techniques in various issues.ResultsMajority of the 437 procedures were performed as awake surgery (53%). Monopolar stimulation was used in 348 procedures and correlated with a postoperative temporary neurological deficit. Bipolar stimulation was performed in 127 procedures, particularly on tumors in the left hemisphere for language mapping. Overall permanent deficit was seen in 2% of the patients; neither different mapping or monitoring modes nor stimulation intensity, localization, or histopathological findings correlated significantly with permanent deficits. Evaluation of post-OP MRI revealed total resection (TR) in 209 out of 417 cases. Marginal residual volume in cases where total resection was assumed but MRI failed to proof TR was found (0.4 ml). Surgeons’ post-OP evaluation of obligatory techniques matched in 73% with the techniques actually used.ConclusionWe report 437 surgical procedures on highly functional located brain lesions. Resection without permanent deficit was adequately achievable in 98% of the procedures. Chosen mapping or monitoring techniques mostly depended on localization and vascular conflicts but also in some procedures on availability of resources, which was emphasized by the post-OP surgeons’ evaluation. With the present study, we aimed to pave the way to á la carte choice of monitoring and or mapping techniques, reflecting the possibilities of even supratotal resection in eloquent brain tumor lesions and the herewith increased need for monitoring and limiting resources.
Intensity modulated radiation therapy with stereotactic body radiation therapy boost for unfavorable prostate cancer: five-year outcomes
Authors: Carrasquilla Michael , Sholklapper Tamir , Pepin Abigail N. , Hodgins Nicole , Lei Siyuan , Rashid Abdul , Danner Malika , Zwart Alan , Bolanos Grecia , Ayoob Marilyn , Yung Thomas , Aghdam Nima , Collins Brian , Suy Simeng , Kumar Deepak , Hankins Ryan , Kowalczyk Keith , Dawson Nancy , Collins Sean 
Published: November 2023

PurposeIntensity-modulated radiation therapy (IMRT) with brachytherapy boost for unfavorable prostate cancer has been shown to improve biochemical relapse-free survival compared to IMRT alone. Stereotactic body radiation therapy (SBRT) is a less-invasive alternative to brachytherapy. Early outcomes utilizing SBRT boost suggest low rates of high-grade toxicity with a maintained patient-reported quality of life. Here, we report the 5-year progression-free survival (PFS) and prostate cancer-specific survival (PCSS) of patients treated with IMRT plus SBRT boost.Materials and methodsBetween 2008 and 2020, 255 patients with unfavorable prostate cancer were treated with robotic SBRT (19.5 Gy in three fractions) followed by fiducial-guided IMRT (45–50.4 Gy) according to an institutional protocol. For the first year, the patient’s PSA level was monitored every 3 months, biannually for 2 years, and annually thereafter. Failure was defined as nadir + 2 ng/mL or a rising PSA with imaging suggestive of recurrence. Detection of recurrence also included digital rectal examination and imaging studies, such as MRI, CT, PET/CT, and/or bone scans. PFS and PCSS were calculated using the Kaplan–Meier method.ResultsThe median follow-up period was 71 months. According to the NCCN risk classification, 5% (13/255) of the patients had favorable intermediate-risk disease, 23% (57/255) had unfavorable intermediate-risk disease, 40% (102/255) had high-risk disease, and 32% (83/255) had very high-risk disease. Androgen deprivation therapy was administered to 80% (204/255) of the patients. Elective pelvic lymph node IMRT was performed in 28 (10%) patients. The PFS for all patients at 5 years was 81% (favorable intermediate risk, 91%; unfavorable intermediate risk, 89%; high-risk, 78%; and very-high risk, 72%). The PCSS for all patients at 5 years was 97% (favorable intermediate risk, 100%; unfavorable intermediate risk, 100%; high risk, 100%; and very high risk, 89%).ConclusionThe incidence of failure following IMRT plus SBRT for unfavorable prostate cancer remains low at 5 years.
Magnetic resonance imaging radiomics-based prediction of clinically significant prostate cancer in equivocal PI-RADS 3 lesions in the transitional zone
Authors: Zhao Ying-Ying , Xiong Mei-Lian , Liu Yue-Feng , Duan Li-Juan , Chen Jia-Li , Xing Zhen , Lin Yan-Shun , Chen Tan-Hui 
Published: November 2023

PurposeThis bi-institutional study aimed to establish a robust model for predicting clinically significant prostate cancer (csPCa) (pathological grade group ≥ 2) in PI-RADS 3 lesions in the transition zone by comparing the performance of combination models.Materials and methodsThis study included 243 consecutive men who underwent 3-Tesla magnetic resonance imaging (MRI) and ultrasound-guided transrectal biopsy from January 2020 and April 2022 which is divided into a training cohort of 170 patients and a separate testing cohort of 73 patients. T2WI and DWI images were manually segmented for PI-RADS 3 lesions for the mean ADC and radiomic analysis. Predictive clinical factors were identified using both univariate and multivariate logistic models. The least absolute shrinkage and selection operator (LASSO) regression models were deployed for feature selection and for constructing radiomic signatures. We developed nine models utilizing clinical factors, radiological features, and radiomics, leveraging logistic and XGboost methods. The performances of these models was subsequently compared using Receiver Operating Characteristic (ROC) analysis and the Delong test.ResultsOut of the 243 participants with a median age of 70 years, 30 were diagnosed with csPCa, leaving 213 without a csPCa diagnosis. Prostate-specific antigen density (PSAD) stood out as the only significant clinical factor (odds ratio [OR], 1.068; 95% confidence interval [CI], 1.029–1.115), discovered through the univariate and multivariate logistic models. Seven radiomic features correlated with csPCa prediction. Notably, the XGboost model outperformed eight other models (AUC of the training cohort: 0.949, and validation cohort: 0.913). However, it did not surpass the PSAD+MADC model (P &gt; 0.05) in the training and testing cohorts (AUC, 0.949 vs. 0.888 and 0.913 vs. 0.854, respectively).ConclusionThe machine learning XGboost model presented the best performance in predicting csPCa in PI-RADS 3 lesions within the transitional zone. However, the addition of radiomic classifiers did not display any significant enhancement over the compound model of clinical and radiological findings. The most exemplary and generalized option for quantitative prostate evaluation was Mean ADC+PSAD.
Pragmatic physiologically-based pharmacokinetic modeling to support clinical implementation of optimized gentamicin dosing in term neonates and infants: proof-of-concept
Authors: de Hoop-Sommen Marika A. , van der Heijden Joyce E. M. , Freriksen Jolien J. M. , Greupink Rick , de Wildt Saskia N. 
Published: November 2023

IntroductionModeling and simulation can support dosing recommendations for clinical practice, but a simple framework is missing. In this proof-of-concept study, we aimed to develop neonatal and infant gentamicin dosing guidelines, supported by a pragmatic physiologically-based pharmacokinetic (PBPK) modeling approach and a decision framework for implementation.MethodsAn already existing PBPK model was verified with data of 87 adults, 485 children and 912 neonates, based on visual predictive checks and predicted-to-observed pharmacokinetic (PK) parameter ratios. After acceptance of the model, dosages now recommended by the Dutch Pediatric Formulary (DPF) were simulated, along with several alternative dosing scenarios, aiming for recommended peak (i.e., 8–12 mg/L for neonates and 15–20 mg/L for infants) and trough (i.e., &lt;1 mg/L) levels. We then used a decision framework to weigh benefits and risks for implementation.ResultsThe PBPK model adequately described gentamicin PK. Simulations of current DPF dosages showed that the dosing interval for term neonates up to 6 weeks of age should be extended to 36–48 h to reach trough levels &lt;1 mg/L. For infants, a 7.5 mg/kg/24 h dose will reach adequate peak levels. The benefits of these dose adaptations outweigh remaining uncertainties which can be minimized by routine drug monitoring.ConclusionWe used a PBPK model to show that current DPF dosages for gentamicin in term neonates and infants needed to be optimized. In the context of potential uncertainties, the risk-benefit analysis proved positive; the model-informed dose is ready for clinical implementation.
Computed tomography-based imaging biomarker identifies coal workers’ pneumoconiosis
Authors: Pyo Jaehun , Chau Ngan-Khanh , Park Eun-Kee , Choi Sanghun 
Published: November 2023

Rationale: The increase in the incidence and the diagnostic limitations of pneumoconiosis have emerged as a public health concern. This study aimed to conduct a computed tomography (CT)- based quantitative analysis to understand differences in imaging results of pneumoconiosis according to disease severity.Methods: According to the International Labor Organization (ILO) guidelines, coal workers’ pneumoconiosis (CWP) are classified into five categories. CT images were obtained only at full inspiration and were quantitatively evaluated for airway structural variables such as bifurcation angle (θ), hydraulic diameter (Dh), wall thickness (WT), and circularity (Cr). Parenchymal functional variables include abnormal regions (emphysema, ground–glass opacities, consolidation, semi consolidation, and fibrosis) and blood vessel volume. Through the propensity score matching method, the confounding effects were decreased.Results: Category 4 demonstrated a reduced θ in TriLUL, a thicker airway wall in both the Trachea and Bronint compared to Category 0, and a decreased Cr in Bronint. Category 4 presented with higher abnormal regions except for ground–glass opacity and a narrower pulmonary blood vessel volume. A negative correlation was found between abnormal areas with lower Hounsfield units (HU) than the normal lung and the ratio of forced expiratory volume in 1 s/forced vital capacity, with narrowed pulmonary blood vessel volume which is positively correlated with abnormal areas with upper HU than the normal lung.Conclusion: This study provided valuable insight into pneumoconiosis progression through a comparison of quantitative CT images based on severity. Furthermore, as there has been paucity of studies on the pulmonary blood vessel volume of the CWP, in this study, a correlation between reduced pulmonary blood vessel volume and regions with low HU values holds significant importance.
A simulation-free constrained regression approach for flux estimation in isotopically nonstationary metabolic flux analysis with applications in microalgae
Authors: Küken Anika , Treves Haim , Nikoloski Zoran 
Published: November 2023

IntroductionFlux phenotypes from different organisms and growth conditions allow better understanding of differential metabolic networks functions. Fluxes of metabolic reactions represent the integrated outcome of transcription, translation, and post-translational modifications, and directly affect growth and fitness. However, fluxes of intracellular metabolic reactions cannot be directly measured, but are estimated via metabolic flux analysis (MFA) that integrates data on isotope labeling patterns of metabolites with metabolic models. While the application of metabolomics technologies in photosynthetic organisms have resulted in unprecedented data from 13CO2-labeling experiments, the bottleneck in flux estimation remains the application of isotopically nonstationary MFA (INST-MFA). INST-MFA entails fitting a (large) system of coupled ordinary differential equations, with metabolite pools and reaction fluxes as parameters. Here, we focus on the Calvin-Benson cycle (CBC) as a key pathway for carbon fixation in photosynthesizing organisms and ask if approaches other than classical INST-MFA can provide reliable estimation of fluxes for reactions comprising this pathway.MethodsFirst, we show that flux estimation with the labeling patterns of all CBC intermediates can be formulated as a single constrained regression problem, avoiding the need for repeated simulation of time-resolved labeling patterns.ResultsWe then compare the flux estimates of the simulation-free constrained regression approach with those obtained from the classical INST-MFA based on labeling patterns of metabolites from the microalgae Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii under different growth conditions.DiscussionOur findings indicate that, in data-rich scenarios, simulation-free regression-based approaches provide a suitable alternative for flux estimation from classical INST-MFA since we observe a high qualitative agreement (rs=0.89) to predictions obtained from INCA, a state-of-the-art tool for INST-MFA.
A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms
Authors: Vignapiano Annarita , Monaco Francesco , Pagano Claudio , Piacente Martina , Farina Federica , Petrillo Gianvito , Sica Raffaella , Marenna Alessandra , Shin Jae Il , Solmi Marco , Corrivetti Giulio 
Published: November 2023

IntroductionDepression is the leading cause of worldwide disability, until now only 3% of patients with major depressive disorder (MDD) experiences full recovery or remission. Different studies have tried to better understand MDD pathophysiology and its resistant forms (TRD), focusing on the identification of candidate biomarkers that would be able to reflect the patients’ state and the effects of therapy. Development of digital technologies can generate useful digital biomarkers in a real-world setting. This review aims to focus on the use of digital technologies measuring symptom severity and predicting treatment outcomes for individuals with mood disorders.MethodsTwo databases (PubMed and APA PsycINFO) were searched to retrieve papers published from January 1, 2013, to July 30, 2023, on the use of digital devices in persons with MDD. All papers had to meet specific inclusion criteria, which resulted in the inclusion of 12 articles.ResultsResearch on digital biomarkers confronts four core aspects: (I) predicting diagnostic status, (II) assessing symptom severity and progression, (III) identifying treatment response and (IV) monitoring real-word and ecological validity. Different wearable technologies have been applied to collect physiological, activity/sleep, or subjective data to explore their relationships with depression.DiscussionDepression’s stable rates and high relapse risk necessitate innovative approaches. Wearable devices hold promise for continuous monitoring and data collection in real world setting.ConclusionMore studies are needed to translate these digital biomarkers into actionable interventions to improve depression diagnosis, monitoring and management. Future challenges will be the applications of wearable devices routinely in personalized medicine.
Promoting Latinx health equity through community-engaged policy and practice reforms in North Carolina
Authors: Thoumi Andrea , Plasencia Gabriela , Madanay Farrah , Ho Ethan Shih-An , Palmer Caroline , Kaalund Kamaria , Chaudhry Nikhil , Labrador Amy , Rigsby Kristen , Onunkwo Adaobi , Almonte Ivan , Gonzalez-Guarda Rosa , Martinez-Bianchi Viviana , Cholera Rushina 
Published: November 2023

IntroductionThe Latinx Advocacy Team &amp; Interdisciplinary Network for COVID-19 (LATIN-19) is a unique multi-sector coalition formed early in the COVID-19 pandemic to address the multi-level health inequities faced by Latinx communities in North Carolina.MethodsWe utilized the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework to conduct a directed content analysis of 58 LATIN-19 meeting minutes from April 2020 through October 2021. Application of the NIMHD Research Framework facilitated a comprehensive assessment of complex and multidimensional barriers and interventions contributing to Latinx health while centering on community voices and perspectives.ResultsCommunity interventions focused on reducing language barriers and increasing community-level access to social supports while policy interventions focused on increasing services to slow the spread of COVID-19.DiscussionOur study adds to the literature by identifying community-based strategies to ensure the power of communities is accounted for in policy reforms that affect Latinx health outcomes across the U.S. Multisector coalitions, such as LATIN-19, can enable the improved understanding of underlying barriers and embed community priorities into policy solutions to address health inequities.
Risk factors for household food insecurity in the Eastern Caribbean Health Outcomes Research Network cohort study
Authors: Martinez-Brockman Josefa L. , Hromi-Fiedler Amber , Galusha Deron , Oladele Carol , Acosta Lisbette , Adams O. Peter , Maharaj Rohan G. , Nazario Cruz M. , Nunez Maxine , Nunez-Smith Marcella , Pérez-Escamilla Rafael ,   on behalf of the ECHORN Writing Group
Published: November 2023

BackgroundGlobally, 1.3 billion people were considered food insecure as of 2022. In the Caribbean region, the prevalence of moderate or severe food insecurity was 71.3% as of 2020, the highest of all subregions in Latin America. Experienced based measurement scales, like the Latin American and Caribbean Food Security Scale, are efficient measurement tools of food insecurity used globally. The Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study is a population-based longitudinal cohort study in the two Caribbean U.S. territories of Puerto Rico and the U.S. Virgin Islands, as well as in Barbados and Trinidad &amp; Tobago. The purpose of this research was to examine the demographic, psychosocial, behavioral, and environmental risk factors associated with household food insecurity (HFI) among adults ≥40 years of age in the ECHORN cohort.MethodsA cross-sectional analysis of baseline ECHORN cohort study data was conducted. The primary outcome was household food insecurity (none, mild, moderate/severe). A total of 16 known and potential risk factors were examined for their association with HFI. The ANOVA and chi-square statistics were used in bivariate analysis. Ordinal logistic regression was used for the multivariable and sex stratified analyses.ResultsMore than one-quarter of the sample (27.3%) experienced HFI. In bivariate analyses, all risk factors examined except for sex, were significantly associated with HFI status. In the multivariable analysis, all variables except sex, education, marital status, smoking status, and residing in Puerto Rico were significant predictors of HFI in the adjusted model. In sex stratified analysis, depression, food availability, self-rated physical health, and island site were significantly associated with increased odds of worsening HFI for women, but not for men. Source of potable water was an important risk factor for both men and women.DiscussionThe prevalence of HFI in the ECHORN cohort study is comparable to other studies conducted in the region. While women did not have an increased risk of HFI compared to men, a different set of risk factors affected their vulnerability to HFI. More research is needed to understand how water and food security are interrelated in the ECHORN cohort.
Knowledge, attitudes and behaviors on antimicrobial resistance among general public across 14 member states in the WHO European region: results from a cross-sectional survey
Authors: Singh-Phulgenda Sauman , Antoniou Pantelis , Wong Danilo Lo Fo , Iwamoto Kotoji , Kandelaki Ketevan 
Published: November 2023

BackgroundAntimicrobial resistance (AMR) is a major global public health threat requiring urgent action. Pan-European data on knowledge, attitudes and behaviors among the general public regarding antibiotic use and AMR is limited.MethodsA multicentric, cross-sectional survey of the general public was conducted in the capital cities of 14 Member States of the WHO European Region. A validated questionnaire from the AMR Eurobarometer survey was used to collect data on antibiotic use and knowledge, access to antibiotics, and understanding of policy responses through face-to-face exit interviews.ResultsOut of 8,221 respondents from 14 Member States, 50% took antibiotics in the past 12 months and the majority (53%) obtained their most recent course from a medical practitioner. The most reported reasons for taking antibiotics orally in the past 12 months were cold (24%), sore throat (21%), cough (18%), and flu (16%). Overall, 84% of participants showed a lack of knowledge about appropriate antibiotic use. However, only 37% of respondents reported receiving any information in the past year about the importance of avoiding unnecessary antibiotic use. Doctors were the most cited (50%) and most trusted (80%) source of information. Among respondents who experienced COVID-19, 28% took antibiotics with a prescription, while 8% took antibiotics without a prescription.ConclusionThis study highlights the urgent need for targeted awareness campaigns and educational initiatives to address knowledge gaps and promote responsible antibiotic use. The findings emphasize the role of the general population in combating AMR. The data serve as baseline information for future evaluations and interventions in the Region.
A linguistic analysis of dehumanization toward substance use across three decades of news articles
Authors: Giorgi Salvatore , Habib Daniel Roy Sadek , Bellew Douglas , Sherman Garrick , Curtis Brenda 
Published: November 2023

IntroductionSubstances and the people who use them have been dehumanized for decades. As a result, lawmakers and healthcare providers have implemented policies that subjected millions to criminalization, incarceration, and inadequate resources to support health and wellbeing. While there have been recent shifts in public opinion on issues such as legalization, in the case of marijuana in the U.S., or addiction as a disease, dehumanization and stigma are still leading barriers for individuals seeking treatment. Integral to the narrative of “substance users” as thoughtless zombies or violent criminals is their portrayal in popular media, such as films and news.MethodsThis study attempts to quantify the dehumanization of people who use substances (PWUS) across time using a large corpus of over 3 million news articles. We apply a computational linguistic framework for measuring dehumanization across three decades of New York Times articles.ResultsWe show that (1) levels of dehumanization remain high and (2) while marijuana has become less dehumanized over time, attitudes toward other substances such as heroin and cocaine remain stable.DiscussionThis work highlights the importance of a holistic view of substance use that places all substances within the context of addiction as a disease, prioritizes the humanization of PWUS, and centers around harm reduction.