bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patent landscape analysis for materials based on fungal mycelium: a guidance report on how to interpret the current patent situation
Authors: Meyer Vera , Mengel Sabine 
Published: August 2024

Abstract
Background
Recent advancements in the collaboration between two scientific disciplines—fungal biotechnology and materials sciences—underscore the potential of fungal mycelium as renewable resource for sustainable biomaterials that can be harnessed in different industries. As fungal mycelium can be biotechnologically obtained from different filamentous fungi and is as a material very versatile, respective research and commercial application should be thriving. However, some granted patents in the field of fungal mycelium-based materials have caused uncertainty in the community as to which subject matter is patent-protected and for how long the protection is expected to last.

Results
This opinion paper therefore maps the patent landscape of fungal mycelium-based materials with a specific focus on technical applications including building construction, insulation, packaging, and the like. We provide an overview of granted patents (73) and pending applications (34) related to granted patents, the dominant patent portfolios (five, with the number of patents and/or applications per owner between six and 44), the patent owners, and highlight the key claims formulated to protect the inventions. Additionally, we outline various options towards an increased activity in the field.

Conclusion
Patent developments in the field leave the impression that fungal materials, despite their high potential as renewable and biodegradable materials, have been held back due to patent over-protection. Considering the need for replacing current petroleum-based materials with renewable biomaterials, coordinated efforts may be called for to intensify efforts in the field.
Poor sleep quality and associated factors among people attending antiretroviral treatment clinics in Ethiopia: a systematic review and meta-analysis
Authors: Ferede Yeshiwas Ayale , Zeleke Agerie Mengistie , Assefa Getaw Wubie , Getahun Assaye Birhan , Tassew Worku Chekol 
Published: August 2024

Abstract
Background
Sleep disturbances are frequently reported among people living with HIV infection. In Ethiopia, approximately half of people living with HIV/AIDS experience mental health issues, which further degrade sleep quality. This systematic review and meta-analysis aims to assess the national prevalence of poor sleep quality and identify key determinants.

Methods
A systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, focusing on English-published studies. The search spanned Google Scholar, HINARI, Scopus, PubMed, EMBASE, Web of Science, and AJOL from April 4, 2023, to May 15, 2023. Three reviewers independently extracted data and evaluated study quality using a modified Newcastle‒Ottawa scale for cross-sectional studies. Stata version 11 was used for the meta-analysis, employing a random-effects model to estimate poor sleep quality. Study heterogeneity was assessed using I2 and Cochran's Q test.

Results
A total of 6,070 articles regarding poor sleep quality and/or associated factors among people attending antiretroviral treatment clinics in Ethiopia were retrieved. The pooled estimate of poor sleep quality among people living with HIV in Ethiopia was 52.64 (95% CI: 44.08, 61.20). Depression (AOR = 4.61; 95% CI: 1.15, 18.51), a CD4 count < 200 cells/mm3 (AOR = 1.83; 95% CI: 0.33, 10.18), a viral load > 1000 copies (AOR = 1.42; 95% CI: 0.19, 10.61), and anxiety (AOR = 17.16; 95% CI: 4.47, 65.91) were identified as factors associated with poor sleep quality.

Conclusion
A systematic review and meta-analysis found that about half of people living with HIV/AIDS in Ethiopia experience poor sleep quality. Key factors contributing to poor sleep quality include CD4 count, viral load, depression, and anxiety. Policymakers and relevant organizations should address these issues to improve sleep quality and manage the factors affecting it.
Basic nutrients and UPLC- ZenoTOF-MS/MS based lipomics analysis of Chenopodium quinoa Willd. varieties
Authors: Wang Shufang , Wang Mian , Zhou You , Yang Runqiang , Chen Huimin , Wu Jirong , Xu Jianhong , Tu Kang , Shi Jianrong , Sun Xiaofeng 
Published: August 2024

AbstractThis study conducted a comparison of the nutritional content and lipid composition of five different varieties of quinoa (QL-1, SJ-1, SJ-2, KL-1, and KL-2) from Qinghai Province, China. Each of the five varieties exhibited varying levels of essential nutrients, including crude protein, dietary fiber, and crude fat. The QL-1 variety has the highest concentration of phytic acid, measuring 1.66 g/100 g. A non-targeted lipomics analysis discovered a total of 16 lipid categories and 383 individual lipids in quinoa. Out of the several substances, glyceride had the highest concentration, exceeding 70%, with phospholipids coming next. The percentage of fatty acids and fatty acid esters was between 5 and 11%. The glycerides in all five kinds exhibited a similar composition, with unsaturated glycerides constituting over 99% of the total glycerides. Phospholipids constituted over 11% of the overall lipid content, with lecithin comprising more than 80% and cephalin ranging from 16.70 to 18.61%. The results establish a solid basis for the utilization of quinoa in processing, particularly in lipid processing.
Graphical Abstract
Construction control of rigid frame-continuous girder bridge based on grey theory
Authors: Wan Lijun , Qiao Jiaqi , Sun Quansheng , Liu Jingyang 
Published: August 2024

AbstractTo address the issue of excessive mid-span deflection in rigid frame-continuous girder bridges during the later stages of normal use and to provide a basis for setting the pre-camber of this bridge type. This study focused on a specific rigid frame-continuous girder bridge. Based on the outcomes of finite element analysis, a GM(1,1) model developed using grey theory was utilized to forecast the vertical deflection of the primary girder in the construction phase of a rigid frame-continuous girder bridge, resulting in notable outcomes. The results suggest that the GM(1,1) model grounded in grey theory offers precise estimations of the vertical deflection of the primary girder during the prestressing tendon tensioning stage, displaying a minimal deviation of merely 1.73 mm compared to actual measurements. Consequently, applying the GM(1,1) model based on grey theory for projecting the vertical deflection of the primary girder in the construction process of rigid frame-continuous girder bridges can advance the accuracy of construction management. Through comparative analysis of measured values estimated values and theoretical values at the construction site, it is evident that the predictive model effectively controls the displacement, thus serving as a reference for construction control in similar projects.
Evaluation of prognostic factors for oral tongue squamous cell carcinoma: Significance of intratumoral tumor-infiltrating lymphocytes, lymph node ratio, and depth of invasion.
Authors: Lee Jongwon 
Published: August 2024

132 Background: Oral tongue squamous cell carcinoma (SCC) is an aggressive malignancy with a variable prognosis. Identifying reliable prognostic factors is crucial for developing personalized treatment strategies and improving patient outcomes. This study examined the prognostic significance of clinicopathological factors in oral tongue SCC. Methods: A retrospective cohort study was conducted on 192 patients who underwent surgical resection at Asan Medical Center between 2010 and 2017. Clinicopathological data, including age at diagnosis, American Joint Committee of Cancer (AJCC) 8th edition stages, depth of invasion (DOI), extranodal extension (ENE), intratumoral and stromal (invasive front) tumor-infiltrating lymphocytes (TILs), lymphovascular invasion (LVI), margin status, metastatic-to-examined lymph nodes ratio (LNR), number of metastatic lymph nodes, perineural invasion (PNI), sex, size, tumor budding, tumor differentiation, tumor-to-stromal ratio (TSR), and worst pattern of invasion (WPOI) were analyzed. The total cohort, early-stage group, and late-stage group were analyzed separately. Results: Most variables showed significant associations with the survival rate. The multivariate Cox proportional hazard models for the total cohort showed significant results for intratumoral TILs, DOI grade, and LNR. However, other factors failed to show statistical significance. Intratumoral TIL was the only consistently potent factor for survival in all study groups. Conclusions: Our findings highlight the need for increased focus on the prognostic significance of intratumoral TILs. The DOI grade and LNR were also powerful prognostic factors, especially in late-stage tongue SCCs. Our data suggest that the prognostic significance of certain variables, such as the WPOI, may have been overestimated in the literature, thereby warranting a reassessment of the currently utilized prognostic markers in oral tongue SCC.
Characterization of estrogen receptor mutant breast cancer in 3D cell culture.
Authors: Mayer Olivia , Wright Jordan , Rinderle Caroline , Bunnell Bruce 
Published: August 2024

14 Background: Breast cancer is a leading cancer in women worldwide. Many primary breast cancers are estrogen receptor positive (ER+) and responsive to anti-estrogenic therapies. These tumors can mutate estrogen receptors to survive, allowing the tumors to become more triple-negative-like and therefore more dangerous. Triple-negative breast cancer (TNBC) has been particularly challenging to treat due to its lack of estrogen (ER), progesterone (PR), and human epidermal growth factor (HER2) receptors. Due to the lack of treatment options, TNBC has a poor prognosis and contributes to a significant percentage of breast cancer mortalities. These ER mutants act more like TNBC, resulting in worse clinical outcomes. Current research on these ER mutants has been conducted using two-dimensional (2D), monolayer cell culture, which does not translate effectively in animal models, and ultimately, humans. Three-dimensional (3D) cell culture, which allows for the formation of spheroids, mimics actual tumors and provides results more consistent with tumor treatment in vitro. Due to the lack of research on these ER mutants in 3D culture, they must be characterized to determine baseline gene expression and behavior. After characterization, identifying changes resulting from drug treatment will be possible. Methods: Parental, ER+ MCF7-Luc cells, and daughter D538G and Y537S mutants were seeded at a density of 3000 cells/well in a low-attachment, round-bottomed 96-well plate. 48 hours and 7 days post-seeding, newly-formed spheroids were imaged. Using ImageJ analysis software, diameter, area, perimeter, circularity, aspect ratio, roundness, and solidity were determined. After 7 days in culture, spheres were collected for RNA extraction. Next, cDNA was synthesized, and qRT-PCR was performed to assess gene expression differences. Results: The wild-type ER+ spheres have smaller diameters, spherocity values closer to one, and are more compact. They express different levels of EMT markers from the controls, indicating alterations to signaling pathways. These 3D cultures vary in expression from the 2D cultures of the same cell lines. Conclusions: MCF-7 ER+ breast cancer cells aggregate more readily than ER+ mutants. The ER must be involved in signaling that promotes aggregation, as reduced ER signaling decreases the ability for spheroid formation. This phenomenon and the differences in gene expression may explain why mutants tend to behave in a more triple-negative manner. Cells cultured in 3D express some genes to different extents, confirming the importance of 3D culture for identifying future therapies – cells behave differently in different culturing contexts, 3D being more consistent with tumor behavior. Therefore, characterizing ER+ mutants prior to drug treatment studies is crucial to understanding how compounds affect cancer cells, as well as for identifying differences in various ER+ mutants for better treatment outcomes.
In-training and private physicians' knowledge, attitudes, practices and perceived barriers on the utilization of low dose chest CT scan as lung cancer screening for high-risk patients in a tertiary hospital: Single center experience.
Authors: Palec Jesilyn , de Dios Ivy Dimayuga 
Published: August 2024

150 Background: Lung cancer is the leading cause of cancer-related deaths worldwide. Aside from smoking cessation efforts and guidelines from all proficient panels, utilizing Low dose CT scan (LDCT) of the chest as lung cancer screening (LCS) has been poorly adopted. Methods: This was conducted after institutional review board approval. The respondents were handed hard copy or electronic consent forms and survey questionnaire depending on the platform of their choice. Results: Majority of the respondents were in-training female physicians with median age of 31 years old who specialized in Internal Medicine practicing between 1-5 years who catered to more than 10 patients per week in outpatient clinics. Nearly half of the respondents answered that the recommended frequency for lung cancer screening (LCS) for high-risk individuals is done bi-annually. Majority agreed that lung cancer screening is effective in decreasing lung cancer mortality and morbidity. Most respondents have initiated discussion about the risks and benefits of low dose chest CT scan (LDCT) as lung cancer screening among eligible high-risk patients. However, most of the respondents disagreed that lung cancer screening is cost effective. The top three perceived barriers on the utilization of Low dose chest CT scan as lung cancer screening reported in descending order revealed that it is not cost-effective, some forgets to screen patients and lung cancer screening has the potential to cause mental anguish or anxiety to patients. Conclusions: This study recommends conducting further studies exploring the socio-economic burden and impact assessment of lung cancer in the Philippines to enable translation of more meaningful strategies for local and national lung cancer screening access, health policies and financing. Promoting continuous lung cancer screening forums, lectures and information dissemination of annual LDCT of the chest among high risk patients will encourage and strengthen interdepartmental and multidisciplinary referral and collaboration in increasing earlier detection of lung cancer and decreasing related morbidity and mortality.
Disparities in self-reported pain control among cancer survivors.
Authors: Santos Teles Marco , Modugu Ganesh , Silva Isabel C. , Malhotra Raj , Rahbe Munir , Eskander Mariam F. 
Published: August 2024

151 Background: Cancer survivors often suffer from chronic pain. However, not all patients have access to medication and other pain management strategies, making pain control challenging. We aim to determine the association of sociodemographic factors with self-reported pain control in cancer survivors with cancer-related chronic pain. Methods: A cross-sectional analysis was conducted using data from the 2022 Behavioral Risk Factor Surveillance System survey. Cancer survivors who self-reported physical pain from cancer or treatment were included. Non-melanoma skin cancer survivors were excluded. The outcome of interest was pain control. Univariate analysis with chi-square and multivariable logistic regression were used to determine the sociodemographic characteristics associated with pain control. Models were adjusted for age, sex, marital status, income, insurance coverage, BMI, smoking status, and cancer site. Results: 1,670 cancer survivors with self-reported cancer-related chronic pain were identified. 9.2% were aged < 40, 61.5% were female, and 71.6% were non-Hispanic white. 97.2% were insured, 50.5% earned ≥ $50,000, and 27.6% were college graduates. 29.8% of survivors reported a history of breast cancer, followed by melanoma (6.3%), and lung cancer (6.1%). Young adults (age 18-39) reported significantly lower pain control compared to older survivors (52% vs. 77.7%, p <0.001). Non-Hispanic Black survivors reported the highest rates of pain control, followed by non-Hispanic white, and Hispanic survivors (87.7% vs. 77.5% vs. 60.6%, respectively, p= 0.013). Employed survivors reported significantly higher pain control than those out of the workforce (83.2% vs. 73.7%, p= 0.008, respectively). College graduates reported better pain control than those without a college degree (82.9% vs. 74.7%, p=0.009, respectively). There was no significant association between pain control and insurance coverage or income. On multivariate analysis, young adults had lower pain control than older adults (OR: 0.454; 95% CI: 0.219-0.942). Compared to non-Hispanic white survivors, being Hispanic was associated with worse pain control (OR: 0.324; 95% CI: 0.142-0.737); no significant association was found for non-Hispanic Black survivors (OR: 1.964; 95% CI: 0.851-4.631). Employment was associated with better pain control (OR: 1.997; 95% CI: 1.235-3.231). College degree attainment was not significantly associated with pain control on multivariate analysis (OR: 1.414; 95% CI: 0.934-2.142). Conclusions: Age, race/ethnicity and employment were associated with pain control among cancer survivors. Young adults, Hispanic and unemployed survivors were most likely to have poor pain control. Further research should elucidate the factors driving these relationships in order to achieve more equitable pain management in this population.
Utilizing an automated cloud-based platform, Palantine Foundry, to generate and build large databases for clinical research applications.
Authors: Nguyen Quynh , Weng Julius , Edelkamp Paul , Knafl Mark , Roy Paul , Qian David C , Liao Zhongxing X. , Woodman Scott Eric 
Published: August 2024

165 Background: Academic institutions are adopting automated tools to help develop and maintain large databases. Leveraging advances in clinical data warehouses and artificial intelligence can potentially decrease resource utilization and the time required to conduct research by reducing intensive manual human curation of data. Methods: This research was performed as part of the institutional Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE), IRB-approved protocol 2020-0348. Data were obtained from both structured and unstructured data sources within the MD Anderson electronic health record to validate a retrospective analysis for COVID-19 positive patients undergoing radiation treatments. Multiple data sources were identified, integrated and analyzed using the Syntropy Foundry platform, part of the Context Engine Data Management System at M.D. Anderson Cancer Center (MDACC) to include patient demographics, clinical notes, laboratory values, radiology reports, and oncology treatments. The platform allows real-time updating of these data-sources with integrated statistical packages to streamline rapid statistical analyses. We conducted a retrospective review of patients treated within 3 weeks of COVID infection between March 2020 and November 2022. Patient data was obtained using Foundry. Patients who tested positive for COVID-19 and had their treatment postponed were categorized as having a treatment delay. Patients who started radiation therapy and subsequently had an interruption in treatment due to contracting COVID-19 were categorized as having a treatment break. The Kaplan-Meier method was used to compare survival outcomes and was conducted within Foundry. Results: Syntropy Foundry helped develop a database comprising of 380 COVID-19 positive patients treated with radiation therapy between March 2020 through November 2022. It validated patient demographic information and research variables including patient age, histology, cancer stage, treatment plans, radiographic scans, recurrences, and follow up time that were separately performed manually. It reduced the time and human resources required to retrospectively collect and review these patient charts. Conclusions: Syntropy Foundry and ongoing efforts to leverage machine learning models to facilitate the interpretation of the large amount of accessible clinical data can potentially improve quality and reduce resources needed to generate large research databases. Future applications using artificial intelligence with Foundry to identify clinical recurrence and report patient outcome are under development.
Validating process mining in pediatric oncology: Demonstrating protocol adherence and variability in neuroblastoma treatment.
Authors: van Barneveld Astrid , Berkhout Matthijs , Van Noesel Max , Kemmeren Patrick , Tytgat Lieve 
Published: August 2024

166 Background: Neuroblastoma is the most common extracranial tumor in children. The mortality rate for patients with metastatic disease is over 50%. In the Netherlands, 30 new patients are diagnosed annually. Current clinical treatment guidelines are complex and include multiple treatment arms consisting of chemotherapy, surgery, radiotherapy, and immunotherapy (IT). Although poor patient health and complications are known to cause adaptations to the otherwise standardized treatment regimen, the extent to which these variations occur is unknown. This study aimed to validate the use of process mining, a data-driven technique, to retrospectively examine protocol adherence and variability within current clinical guidelines based upon the GPOH-DCOG NBL2009 neuroblastoma treatment protocol. Methods: Data was extracted from electronic health records, as well as laboratory, pathology, and pharmaceutical databases, to create individual event logs for each patient. Process mining was performed using a fuzzy mining algorithm. The treatment courses for all neuroblastoma patients were mapped. Commonalities and variations were highlighted, and the throughput time for key treatment phases was calculated. Subsequently, conformance with protocol was determined. Results: Analysis of 70 patients treated between 2018-2022 showed 62 distinct treatment processes, revealing significant variations in patient care. Patients with high-risk disease showed the least variation (n=47, 42 variants). Notably, 17 variants were identified among 18 patients who died, indicating a highly personalized approach in the advanced stages of the disease. Subgroup analysis of 17 high-risk patients who received IT consisting of alternating cycles of anti-GD2 antibody and retinoic acid showed 6 variants. 12/17 patients (70.6%) completed the full IT regimen. Other treatment adjustments included shortened anti-GD2 infusions for two patients (5 and 8 days versus the prescribed 10 days, respectively), potentially indicating treatment toxicity. One patient received a 15-day infusion, exceeding the prescribed limit of 11 days. The recorded interval between the administration of anti-GD2 and retinoic acid was a median 5.5 hours (range: 60 seconds – 6.4 days), deviating from the prescribed interval of 24 hours and warranting further investigation. Conclusions: Process mining is a valuable tool for analyzing protocol performance and adherence in neuroblastoma treatment. Despite standardized treatment protocols, significant heterogeneity was observed in the treatment of neuroblastoma patients, especially those with poor prognosis. Throughput time analysis revealed variabilities in the IT regimen that warrant further investigation. This study underscores the potential of data-driven approaches to optimize treatment protocols and support evidence-based practices in clinical oncology.