bluuebunny/crossref_metadata_2025 huggingface dataset:
A High-Throughput Screening of a Natural Products Library for Mitochondria Modulators
Authors: Makinde Emmanuel , Ma Linlin , Mellick George D. , Feng Yunjiang
Published: April 2024

Mitochondria, the energy hubs of the cell, are progressively becoming attractive targets in the search for potent therapeutics against neurodegenerative diseases. The pivotal role of mitochondrial dysfunction in the pathogenesis of various diseases, including Parkinson’s disease (PD), underscores the urgency of discovering novel therapeutic strategies. Given the limitations associated with available treatments for mitochondrial dysfunction-associated diseases, the search for new potent alternatives has become imperative. In this report, we embarked on an extensive screening of 4224 fractions from 384 Australian marine organisms and plant samples to identify natural products with protective effects on mitochondria. Our initial screening using PD patient-sourced olfactory neurosphere-derived (hONS) cells with rotenone as a mitochondria stressor resulted in 108 promising fractions from 11 different biota. To further assess the potency and efficacy of these hits, the 11 biotas were subjected to a subsequent round of screening on human neuroblastoma (SH-SY5Y) cells, using 6-hydroxydopamine to induce mitochondrial stress, complemented by a mitochondrial membrane potential assay. This rigorous process yielded 35 active fractions from eight biotas. Advanced analysis using an orbit trap mass spectrophotometer facilitated the identification of the molecular constituents of the most active fraction from each of the eight biotas. This meticulous approach led to the discovery of 57 unique compounds, among which 12 were previously recognized for their mitoprotective effects. Our findings highlight the vast potential of natural products derived from Australian marine organisms and plants in the quest for innovative treatments targeting mitochondrial dysfunction in neurodegenerative diseases.
The Impact of Inorganic Systems and Photoactive Metal Compounds on Cytochrome P450 Enzymes and Metabolism: From Induction to Inhibition
Authors: Havrylyuk Dmytro , Heidary David K. , Glazer Edith C.
Published: April 2024

While cytochrome P450 (CYP; P450) enzymes are commonly associated with the metabolism of organic xenobiotics and drugs or the biosynthesis of organic signaling molecules, they are also impacted by a variety of inorganic species. Metallic nanoparticles, clusters, ions, and complexes can alter CYP expression, modify enzyme interactions with reductase partners, and serve as direct inhibitors. This commonly overlooked topic is reviewed here, with an emphasis on understanding the structural and physiochemical basis for these interactions. Intriguingly, while both organometallic and coordination compounds can act as potent CYP inhibitors, there is little evidence for the metabolism of inorganic compounds by CYPs, suggesting a potential alternative approach to evading issues associated with rapid modification and elimination of medically useful compounds.
Study of Compost Based on Sewage Sludge and Different Structural Materials
Authors: Kosobucki Przemysław
Published: April 2024

The characterization of compost compositions on the basis of sewage sludge and structural materials (straw, sawdust, bark) composting is described. A comparison of the methods most often used for composting and characterization of structural materials is also presented. Sewage sludge and structural materials were mixed in different ratios and composted in piles (laboratory scale) for 3 months. During this time, the composting process was controlled using standard methods. The bioavailability of some xenobiotics in an agriculture experiment (using beans) was also investigated.
Neuroendocrine Neoplasia: From Pathophysiology to Novel Therapeutic Approaches
Authors: Carsote Mara , Nistor Claudiu
Published: April 2024

Neuroendocrine neoplasia (NEN) represents a sensational field of modern medicine; immense progress in emerging biochemical, molecular, endocrine, immunohistochemical, and serum tumour markers of disease, respectively, which are part of early diagnosis, genetic testing, and multidisciplinary approaches [...]
Dynamic Random Walk and Dynamic Opposition Learning for Improving Aquila Optimizer: Solving Constrained Engineering Design Problems
Authors: Varshney Megha , Kumar Pravesh , Ali Musrrat , Gulzar Yonis
Published: April 2024

One of the most important tasks in handling real-world global optimization problems is to achieve a balance between exploration and exploitation in any nature-inspired optimization method. As a result, the search agents of an algorithm constantly strive to investigate the unexplored regions of a search space. Aquila Optimizer (AO) is a recent addition to the field of metaheuristics that finds the solution to an optimization problem using the hunting behavior of Aquila. However, in some cases, AO skips the true solutions and is trapped at sub-optimal solutions. These problems lead to premature convergence (stagnation), which is harmful in determining the global optima. Therefore, to solve the above-mentioned problem, the present study aims to establish comparatively better synergy between exploration and exploitation and to escape from local stagnation in AO. In this direction, firstly, the exploration ability of AO is improved by integrating Dynamic Random Walk (DRW), and, secondly, the balance between exploration and exploitation is maintained through Dynamic Oppositional Learning (DOL). Due to its dynamic search space and low complexity, the DOL-inspired DRW technique is more computationally efficient and has higher exploration potential for convergence to the best optimum. This allows the algorithm to be improved even further and prevents premature convergence. The proposed algorithm is named DAO. A well-known set of CEC2017 and CEC2019 benchmark functions as well as three engineering problems are used for the performance evaluation. The superior ability of the proposed DAO is demonstrated by the examination of the numerical data produced and its comparison with existing metaheuristic algorithms.
Gold Nanoprobes for Detection of a Crucial EGFR Deletion for Early Diagnosis of Non-Small-Cell Lung Cancer
Authors: Enea Maria , Nuekaew Anupong , Franco Ricardo , Pereira Eulália
Published: April 2024

Gold nanoparticles (AuNPs) exhibit improved optical and spectral properties compared to bulk materials, making them suitable for the detection of DNA, RNA, antigens, and antibodies. Here, we describe a simple, selective, and rapid non-cross linking detection assay, using approx. 35 nm spherical Au nanoprobes, for a common mutation occurring in exon 19 of the epidermal growth factor receptor (EGFR), associated with non-small-cell lung cancer cells. AuNPs were synthesized based on the seed-mediated growth method and functionalized with a specific 16 bp thiolated oligonucleotide using a pH-assisted method. Both AuNPs and Au nanoprobes proved to be highly stable and monodisperse through ultraviolet-visible spectrophotometry, dynamic light scattering (DLS), and electrophoretic light scattering (ELS). Our results indicate a detection limit of 1.5 µg mL−1 using a 0.15 nmol dm−3 Au nanoprobe concentration. In conclusion, this work presents an effective possibility for a straightforward, fast, and inexpensive alternative for the detection of DNA sequences related to lung cancer, leading to a potential platform for early diagnosis of lung cancer patients.
Detection of NT-proBNP Using Optical Fiber Back-Reflection Plasmonic Biosensors
Authors: Assunção Ana Sofia , Vidal Miguel , Martins Maria João , Girão Ana Violeta , Loyez Médéric , Caucheteur Christophe , Mesquita-Bastos José , Costa Florinda M. , Pereira Sónia O. , Leitão Cátia
Published: April 2024

Heart failure (HF) is a clinical entity included in cardiovascular diseases affecting millions of people worldwide, being a leading cause of hospitalization of older adults, and therefore imposing a substantial economic burden on healthcare systems. HF is characterized by dyspnea, fatigue, and edema associated with elevated blood levels of natriuretic peptides, such as N Terminal pro-B-type Natriuretic Peptide (NT-proBNP), for which there is a high demand for point of care testing (POCT) devices. Optical fiber (OF) biosensors offer a promising solution, capable of real-time detection, quantification, and monitoring of NT-proBNP concentrations in serum, saliva, or urine. In this study, immunosensors based on plasmonic uncladded OF tips were developed using OF with different core diameters (200 and 600 µm). The tips were characterized to bulk refractive index (RI), anddetection tests were conducted with NT-proBNP concentrations varying from 0.01 to 100 ng/mL. The 200 µm sensors showed an average total variation of 3.6 ± 2.5 mRIU, an average sensitivity of 50.5 mRIU/ng·mL−1, and a limit of detection (LOD) of 0.15 ng/mL, while the 600 µm sensors had a response of 6.1 ± 4.2 mRIU, a sensitivity of 102.8 mRIU/ng·mL−1, and an LOD of 0.11 ng/mL. Control tests were performed using interferents such as uric acid, glucose, and creatinine. The results show the potential of these sensors for their use in biological fluids.
Radio, Podcasts, and Music Streaming—An Electroencephalography and Physiological Analysis of Listeners’ Attitude, Attention, Memory, and Engagement
Authors: Bosshard Shannon , Rodero Emma , Rodríguez-de-Dios Isabel , Brickner Jamie
Published: April 2024

Whilst radio, podcasts, and music streaming are considered unique audio formats that offer brands different opportunities, limited research has explored this notion. This current study analyses how the brain responds to these formats and suggests that they offer different branding opportunities. Participants’ engagement, attitude, attention, memory, and physiological arousal were measured while each audio format was consumed. The results revealed that music streaming elicited more positive attitudes, higher attention, greater levels of memory encoding, and increased physiological arousal compared to either radio or podcasts. This study emphasises the importance for brands of utilising diverse audio channels for unique branding and marketing opportunities.
The Interplay between Glioblastoma Cells and Tumor Microenvironment: New Perspectives for Early Diagnosis and Targeted Cancer Therapy
Authors: Virtuoso Assunta , D’Amico Giuseppa , Scalia Federica , De Luca Ciro , Papa Michele , Maugeri Grazia , D’Agata Velia , Caruso Bavisotto Celeste , D’Amico Agata Grazia
Published: April 2024

Glioblastoma multiforme (GBM) stands out as the most tremendous brain tumor, constituting 60% of primary brain cancers, accompanied by dismal survival rates. Despite advancements in research, therapeutic options remain limited to chemotherapy and surgery. GBM molecular heterogeneity, the intricate interaction with the tumor microenvironment (TME), and non-selective treatments contribute to the neoplastic relapse. Diagnostic challenges arise from GBM advanced-stage detection, necessitating the exploration of novel biomarkers for early diagnosis. Using data from the literature and a bioinformatic tool, the current manuscript delineates the molecular interplay between human GBM, astrocytes, and myeloid cells, underscoring selected protein pathways belonging to astroglia and myeloid lineage, which can be considered for targeted therapies. Moreover, the pivotal role of extracellular vesicles (EVs) in orchestrating a favorable microenvironment for cancer progression is highlighted, suggesting their utility in identifying biomarkers for GBM early diagnosis.
How Coparenting Is Linked to Depression among Chinese Young Girls and Boys: Evidence from a Network Analysis
Authors: Zhao Demao , Gao Xin , Chen Wei , Zhou Quan
Published: April 2024

This study aimed to explore the relationship between parental coparenting and depression among Chinese young adolescents and potential gender differences via network analysis. Thus, 793 fourth-grade students (girls: 281 (35.40%), Mage = 9.99 years, SD = 0.59 years) were recruited from three primary schools in Northern China. The young adolescents rated their depression and perceived paternal and maternal coparenting. Network analysis was used to detect the central nodes and bridge mechanisms among coparenting and depressive components. The results indicated that paternal and maternal consistency as well as maternal conflict were the most central components in the coparenting–depression network. Paternal consistency, maternal conflict and paternal disparagement in coparenting, as well as somatic complaints and positive affect in adolescents’ depression, exhibited high bridge strengths, suggesting those constructs served as vital bridges to connect the two subnetworks. Moreover, paternal consistency showed a higher bridge strength in the boys’ network than the girls’ one, whereas the edge linking adolescents’ positive affect to paternal disparagement and integrity was stronger in the girls’ network. This study contributes to the understanding of associations between parental coparenting and young adolescents’ depression and offered insights into targeted interventions for early adolescent depression by enhancing parental coparenting.
Establishment of Safety Management Measures for Major Construction Workers through the Association Rule Mining Analysis of the Data on Construction Accidents in Korea
Authors: Yoon Young-Geun , Ahn Changbum Ryan , Yum Sang-Guk , Oh Tae Keun
Published: April 2024

Despite increasing industrial advancements, fatal and severe accidents, such as “Falls”, “Struck-by”, “Hit by an object”, “Be crushed”, and “Caught-in/between” accidents, persist in developed countries, including Korea. Various methods, including risk assessment, monitoring systems, technology improvements, and safety education, are being implemented to reduce accidents. However, only a few studies have revealed the causes of accidents and their interrelationships; these studies are based on limited data. Korea recently published accident data using national statistical systems, including the construction safety management integrated information (CSI), enabling the analyses of major accident types. Here, we selected various representative accident cases to minimize the duplication of the data published from 2019 to 2023 and applied the Material, Method, Machine, or Man (4M) analysis method, a risk assessment technique, to perform an accident-type-based association rule mining (ARM) analysis of the accident factors. Through the ARM analysis, we quantitatively identified complex correlations for major accidents. Based on the 4M factors derived through this analysis, we improved a 2–4 model for accident causation and proposed safety management measures for each construction entity.
Near-Miss Detection Metrics: An Approach to Enable Sensing Technologies for Proactive Construction Safety Management
Authors: Hashmi Filzah , Hassan Muhammad Usman , Zubair Muhammad Umer , Ahmed Khursheed , Aziz Taha , Choudhry Rafiq M.
Published: April 2024

One in every five occupational deaths occurs in the construction sector. A proactive approach for improving on-site safety is identifying and analyzing accident precursors, such as near-misses, that provide early warnings of accidents. Despite the importance of near-misses, they are frequently left unreported and unrecorded in the construction sector. The adoption of modern technologies can prevent accidents by automated data collection and analysis. This study aims to develop near-miss detection metrics to facilitate the automated detection of near-misses through sensors. The study adopted a mixed method approach including both qualitative and quantitative approaches. First, a quantifiable definition of near-misses was developed from the literature. Hazards, accidents, and the causes of accidents were identified. Through empirical and statistical analyses of accidents from the OSHA repository, combinations of unsafe acts and conditions responsible for a near-miss were identified. The identified factors were analyzed using a frequency analysis, correlation, and a lambda analysis. The results revealed twelve significant near-misses, such as A1—approach to restricted areas and C2—unguarded floor/roof openings, A5—equipment and tool inspection was incomplete and C8—unsafely positioned ladders and scaffolds, A2—no or improper use of PPE and C2—unguarded floor or roof openings, etc. Lastly, measurable data required by sensors for autonomous detection of near-misses were determined. The developed metric set the basis for automating near-miss reporting and documentation using modern sensing technology to improve construction safety. This study contributes to improving construction safety by addressing the underreporting of near-miss events. Overall, the developed metrics lay the groundwork for enhancing construction safety through automated near-miss reporting and documentation. Furthermore, it helps for the establishment of safety management schemes in the construction industry, specifically in identifying near-misses. This research offers valuable insight into developing guidelines for safety managers to improve near-miss reporting and detection on construction sites. In sum, the findings can be valuable for other industries also looking to establish or assess their own safety management systems.
Association of Insomnia and Obstructive Sleep Apnea with Worse Oral Mucositis and Quality of Life in Head and Neck Cancer Patients Undergoing Radiation Therapy
Authors: Iovoli Austin J. , Smith Kelsey , Yu Han , Kluczynski Melissa A. , Jungquist Carla R. , Ray Andrew D. , Farrugia Mark K. , Gu Fangyi , Singh Anurag K.
Published: April 2024

Background: Patients with head and neck cancer (HNC) undergoing radiation therapy (RT) often experience sleep disturbances that may contribute to oral mucositis (OM) and quality of life (QOL). Methods: Patients with HNC treated with RT at a single institution were examined. Sleep questionnaires were given on the first day of RT to assess for insomnia and obstructive sleep apnea (OSA). Patient-reported QOL and oral mucositis were assessed during RT. Associations between insomnia and OSA with QOL were assessed using the Mann–Whitney U test. Linear mixed models assessed associations with OM. Results: Among 87 patients, 34 patients (39%) had subthreshold or greater insomnia and 47 patients (54%) screened positive for OSA. Upon RT completion, patients with subthreshold or greater insomnia had worse physical function (p = 0.005), fatigue (p = 0.01), insomnia (p < 0.001), and sticky saliva (p = 0.002). Patients screening positive for OSA had worse physical function (p = 0.01), sticky saliva (p = 0.02), fatigue (p = 0.007), insomnia (p = 0.009), and pain (p = 0.005). Upon linear mixed model evaluation, subthreshold or greater insomnia (p = 0.01) and positive OSA screen (p = 0.002) were associated with worse OM. Conclusion: Insomnia and OSA are highly prevalent in patients with HNC undergoing RT. These sleep disturbances are associated with worse QOL and OM during treatment.
Reducing State Conflicts between Network Motifs Synergistically Enhances Cancer Drug Effects and Overcomes Adaptive Resistance
Authors: Kim Yunseong , Choi Sea Rom , Cho Kwang-Hyun
Published: April 2024

Inducing apoptosis in cancer cells is a primary goal in anti-cancer therapy, but curing cancer with a single drug is unattainable due to drug resistance. The complex molecular network in cancer cells causes heterogeneous responses to single-target drugs, thereby inducing an adaptive drug response. Here, we showed that targeted drug perturbations can trigger state conflicts between multi-stable motifs within a molecular regulatory network, resulting in heterogeneous drug responses. However, we revealed that properly regulating an interconnecting molecule between these motifs can synergistically minimize the heterogeneous responses and overcome drug resistance. We extracted the essential cellular response dynamics of the Boolean network driven by the target node perturbation and developed an algorithm to identify a synergistic combinatorial target that can reduce heterogeneous drug responses. We validated the proposed approach using exemplary network models and a gastric cancer model from a previous study by showing that the targets identified with our algorithm can better drive the networks to desired states than those with other control theories. Of note, our approach suggests a new synergistic pair of control targets that can increase cancer drug efficacy to overcome adaptive drug resistance.
Prognostic Value of PCSK9 Levels in Premenopausal Women at Risk of Breast Cancer—Evidence from a 17-Year Follow-Up Study
Authors: Ruscica Massimiliano , Macchi Chiara , Gandini Sara , Macis Debora , Guerrieri-Gonzaga Aliana , Aristarco Valentina , Serrano Davide , Lazzeroni Matteo , Rizzuto Alessandra Stefania , Gaeta Aurora , Corsini Alberto , Gulisano Marcella , Johansson Harriet , Bonanni Bernardo
Published: April 2024

Background and aim: The involvement of cholesterol in cancer development remains a topic of debate, and its association with breast cancer has yet to be consistently demonstrated. Considering that circulating cholesterol levels depend on several concomitant processes, we tested the liability of plasma levels of proprotein convertase subtilisin/kexin type 9 (PCSK9), one of the key regulators of cholesterol levels, as a prognostic biomarker in the context of breast neoplastic events. Methods: Within a prospective randomized breast cancer prevention trial we measured baseline plasma levels of PCSK9. A total of 235 at-risk premenopausal women were randomized and followed up for 17 years. Participants enrolled in this placebo-controlled, phase II, double-blind trial were randomly assigned to receive either tamoxifen 5 mg/d or fenretinide 200 mg/d, both agents, or placebo for 2 years. The associations with breast cancer events were evaluated through competing risk and Cox regression survival models, adjusted for randomization strata (5-year Gail risk ≥ 1.3% vs. intraepithelial neoplasia or small invasive breast cancer of favorable prognosis), age, and treatment allocation. PCSK9 associations with biomarkers linked to breast cancer risk were assessed on blood samples collected at baseline. Results: The plasmatic PCSK9 median and interquartile range were 207 ng/mL and 170–252 ng/mL, respectively. Over a median follow-up period of 17 years and 89 breast neoplastic events, disease-free survival curves showed a hazard ratio of 1.002 (95% CI: 0.999–1.005, p = 0.22) for women with PCSK9 plasma levels ≥ 207 ng/mL compared to women with levels below 207 ng/mL. No differences between randomization strata were observed. We found a negative correlation between PCSK9 and estradiol (r = −0.305), maintained even after partial adjustment for BMI and age (r = −0.287). Cholesterol (r = 0.266), LDL-C (r = 0.207), non-HDL-C (r = 0.246), remnant cholesterol (r = 0.233), and triglycerides (r = 0.233) also correlated with PCSK9. Conclusions: In premenopausal women at risk of early-stage breast cancer, PCSK9 did not appear to have a role as a prognostic biomarker of breast neoplastic events. Larger studies are warranted investigating patients in different settings.
Review of the Use of Medicinal Cannabis Products in Palliative Care
Authors: Troyer James , Tanco Kimberson
Published: April 2024

In this review, we discuss the potential role of cannabis and cannabinoids in the management of cancer-related symptoms. There is limited evidence demonstrating the effectiveness of cannabis-based products in treating cancer-related pain and gastrointestinal symptoms such as nausea, vomiting, and loss of appetite. Regarding the role of cannabis-based products in the treatment of insomnia and mood disorders, most studies looked at these symptoms as secondary outcomes with mixed results. Cannabis-based products have adverse effects, ranging from neuropsychiatric to systemic effects to potential drug interactions.
Precision Immuno-Oncology in NSCLC through Gender Equity Lenses
Authors: Marks Jennifer , Sridhar Arthi , Ai Angela , Kiel Lauren , Kaufman Rebekah , Abioye Oyepeju , Mantz Courtney , Florez Narjust
Published: April 2024

Precision immuno-oncology involves the development of personalized cancer treatments that are influenced by the unique nature of an individual’s DNA, immune cells, and their tumor’s molecular characterization. Biological sex influences immunity; females typically mount stronger innate and adaptive immune responses than males. Though more research is warranted, we continue to observe an enhanced benefit for females with lung cancer when treated with combination chemoimmunotherapy in contrast to the preferred approach of utilizing immunotherapy alone in men. Despite the observed sex differences in response to treatments, women remain underrepresented in oncology clinical trials, largely as a result of gender-biased misconceptions. Such exclusion has resulted in the development of less efficacious treatment guidelines and clinical recommendations and has created a knowledge gap in regard to immunotherapy-related survivorship issues such as fertility. To develop a more precise approach to care and overcome the exclusion of women from clinical trials, flexible trial schedules, multilingual communication strategies, financial, and transportation assistance for participants should be adopted. The impact of intersectionality and other determinants of health that affect the diagnosis, treatment, and outcomes in women must also be considered in order to develop a comprehensive understanding of the unique impact of immunotherapy in all women with lung cancer.
Silencing the Mitochondrial Gatekeeper VDAC1 as a Potential Treatment for Bladder Cancer
Authors: Alhozeel Belal , Pandey Swaroop Kumar , Shteinfer-Kuzmine Anna , Santhanam Manikandan , Shoshan-Barmatz Varda
Published: April 2024

The strategy for treating bladder cancer (BC) depends on whether there is muscle invasion or not, with the latter mostly treated with intravesical therapy, such as with bacillus Calmette–Guérin (BCG). However, BCG treatment is unsuccessful in 70% of patients, who are then subjected to radical cystectomy. Although immune-checkpoint inhibitors have been approved as a second-line therapy for a subset of BC patients, these have failed to meet primary endpoints in clinical trials. Thus, it is crucial to find a new treatment. The mitochondrial gatekeeper protein, the voltage-dependent anion channel 1 (VDAC1), mediates metabolic crosstalk between the mitochondria and cytosol and is involved in apoptosis. It is overexpressed in many cancer types, as shown here for BC, pointing to its significance in high-energy-demanding cancer cells. The BC cell lines UM-UC3 and HTB-5 express high VDAC1 levels compared to other cancer cell lines. VDAC1 silencing in these cells using siRNA that recognizes both human and mouse VDAC1 (si-m/hVDAC1-B) reduces cell viability, mitochondria membrane potential, and cellular ATP levels. Here, we used two BC mouse models: subcutaneous UM-UC3 cells and chemically induced BC using the carcinogen N-Butyl-N-(4-hydroxybutyl) nitrosamine (BBN). Subcutaneous UM-UC3-derived tumors treated with si-m/hVDAC1 showed inhibited tumor growth and reprogrammed metabolism, as reflected in the reduced expression of metabolism-related proteins, including Glut1, hexokinase, citrate synthase, complex-IV, and ATP synthase, suggesting reduced metabolic activity. Furthermore, si-m/hVDAC1-B reduced the expression levels of cancer-stem-cell-related proteins (cytokeratin-14, ALDH1a), modifying the tumor microenvironment, including decreased angiogenesis, extracellular matrix, tumor-associated macrophages, and inhibited epithelial–mesenchymal transition. The BBN-induced BC mouse model showed a clear carcinoma, with damaged bladder morphology and muscle-invasive tumors. Treatment with si-m/hVDAC1-B encapsulated in PLGA-PEI nanoparticles that were administered intravesically directly to the bladder showed a decreased tumor area and less bladder morphology destruction and muscle invasion. Overall, the obtained results point to the potential of si-m/hVDAC1-B as a possible therapeutic tool for treating bladder cancer.
A Novel Approach for Glioblastoma Treatment by Combining Apoptosis Inducers (TMZ, MTX, and Cytarabine) with E.V.A. (Eltanexor, Venetoclax, and A1210477) Inhibiting XPO1, Bcl-2, and Mcl-1
Authors: Zhao Kai , Braun Madita , Meyer Leonie , Otte Katharina , Raifer Hartmann , Helmprobst Frederik , Möschl Vincent , Pagenstecher Axel , Urban Hans , Ronellenfitsch Michael W. , Steinbach Joachim P. , Pesek Jelena , Watzer Bernhard , Nockher Wolfgang A. , Taudte R. Verena , Neubauer Andreas , Nimsky Christopher , Bartsch Jörg W. , Rusch Tillmann
Published: April 2024

Adjuvant treatment for Glioblastoma Grade 4 with Temozolomide (TMZ) inevitably fails due to therapeutic resistance, necessitating new approaches. Apoptosis induction in GB cells is inefficient, due to an excess of anti-apoptotic XPO1/Bcl-2-family proteins. We assessed TMZ, Methotrexate (MTX), and Cytarabine (Ara-C) (apoptosis inducers) combined with XPO1/Bcl-2/Mcl-1-inhibitors (apoptosis rescue) in GB cell lines and primary GB stem-like cells (GSCs). Using CellTiter-Glo® and Caspase-3 activity assays, we generated dose–response curves and analyzed the gene and protein regulation of anti-apoptotic proteins via PCR and Western blots. Optimal drug combinations were examined for their impact on the cell cycle and apoptosis induction via FACS analysis, paralleled by the assessment of potential toxicity in healthy mouse brain slices. Ara-C and MTX proved to be 150- to 10,000-fold more potent in inducing apoptosis than TMZ. In response to inhibitors Eltanexor (XPO1; E), Venetoclax (Bcl-2; V), and A1210477 (Mcl-1; A), genes encoding for the corresponding proteins were upregulated in a compensatory manner. TMZ, MTX, and Ara-C combined with E, V, and A evidenced highly lethal effects when combined. As no significant cell death induction in mouse brain slices was observed, we conclude that this drug combination is effective in vitro and expected to have low side effects in vivo.
The Use of PVD Coatings for Anti-Wear Protection of the Press-In Connection Elements
Authors: Kowalski Sławomir
Published: April 2024

Press-in connections are the commonly used methods for connecting machinery components. In relation to that wide use, those connections are liable to various types of damage and wear. Therefore, this article proposes one of the methods which may improve the life of the press-in connection. CrN+OX, TiN, and ZrN coatings made in the PVD technology were used. The coatings were applied on shafts mating with sleeves and subjected to a rotational bending moment. Tests and observations were conducted that enabled the assessment of the influence of those coatings on the development of wear, in particular fretting, in the tribological kinematic pair. The tests showed the development of wear on all the observed shaft surfaces, with a lower intensity of damage recorded on coated shafts compared to uncoated ones. The traces of fretting wear were noted each time at the edges of the connection, which is due to the mechanism of wear development under rotational bending conditions. In the case of uncoated shafts, wear occurs at the entire circumference of the axle seat in the form of a 3–4 mm wide ring; however, that width is different on either side. In the case of coated shafts, wear occurs on the circumference of the axle seat in the form of a thin ring 1–3 mm wide, depending on the coating. In the case of a ZrN coating, fretting wear appears locally. The largest surface area occupied by wear is 0.75 cm2. Fretting wear comprises mainly material build-ups, pits, and surface scratches. In addition to fretting wear, damage resulting from the process of forcing the sleeve onto the shaft was observed on the tested surfaces.
Progression Learning Convolution Neural Model-Based Sign Language Recognition Using Wearable Glove Devices
Authors: Liang Yijuan , Jettanasen Chaiyan , Chiradeja Pathomthat
Published: April 2024

Communication among hard-of-hearing individuals presents challenges, and to facilitate communication, sign language is preferred. Many people in the deaf and hard-of-hearing communities struggle to understand sign language due to their lack of sign-mode knowledge. Contemporary researchers utilize glove and vision-based approaches to capture hand movement and analyze communication; most researchers use vision-based techniques to identify disabled people’s communication because the glove-based approach causes individuals to feel uncomfortable. However, the glove solution successfully identifies motion and hand dexterity, even though it only recognizes the numbers, words, and letters being communicated, failing to identify sentences. Therefore, artificial intelligence (AI) is integrated with the sign language prediction system to identify disabled people’s sentence-based communication. Here, wearable glove-related sign language information is utilized to analyze the recognition system’s efficiency. The collected inputs are processed using progression learning deep convolutional neural networks (PLD-CNNs). The technique known as progression learning processes sentences by dividing them into words, creating a training dataset. The model assists in efforts to understand sign language sentences. A memetic optimization algorithm is used to calibrate network performance, minimizing recognition optimization problems. This process maximizes convergence speed and reduces translation difficulties, enhancing the overall learning process. The created system is developed using the MATLAB (R2021b) tool, and its proficiency is evaluated using performance metrics. The experimental findings illustrate that the proposed system works by recognizing sign language movements with excellent precision, recall, accuracy, and F1 scores, rendering it a powerful tool in the detection of gestures in general and sign-based sentences in particular.
Computational Modelling and Simulation of Scaffolds for Bone Tissue Engineering
Authors: N. Musthafa Haja-Sherief , Walker Jason , Domagala Mariusz
Published: April 2024

Three-dimensional porous scaffolds are substitutes for traditional bone grafts in bone tissue engineering (BTE) applications to restore and treat bone injuries and defects. The use of computational modelling is gaining momentum to predict the parameters involved in tissue healing and cell seeding procedures in perfusion bioreactors to reach the final goal of optimal bone tissue growth. Computational modelling based on finite element method (FEM) and computational fluid dynamics (CFD) are two standard methodologies utilised to investigate the equivalent mechanical properties of tissue scaffolds, as well as the flow characteristics inside the scaffolds, respectively. The success of a computational modelling simulation hinges on the selection of a relevant mathematical model with proper initial and boundary conditions. This review paper aims to provide insights to researchers regarding the selection of appropriate finite element (FE) models for different materials and CFD models for different flow regimes inside perfusion bioreactors. Thus, these FEM/CFD computational models may help to create efficient designs of scaffolds by predicting their structural properties and their haemodynamic responses prior to in vitro and in vivo tissue engineering (TE) applications.
The Explainability of Transformers: Current Status and Directions
Authors: Fantozzi Paolo , Naldi Maurizio
Published: April 2024

An increasing demand for model explainability has accompanied the widespread adoption of transformers in various fields of applications. In this paper, we conduct a survey of the existing literature on the explainability of transformers. We provide a taxonomy of methods based on the combination of transformer components that are leveraged to arrive at the explanation. For each method, we describe its mechanism and survey its applications. We find out that attention-based methods, both alone and in conjunction with activation-based and gradient-based methods, are the most employed ones. A growing attention is also devoted to the deployment of visualization techniques to help the explanation process.
Massive Bird Nest Losses: A Neglected Threat for Passerine Birds in Atlantic Forest Fragments from the Pernambuco Endemism Center
Authors: Lobo-Araújo Lahert William , Costa Mariellen Cristine , Silveira Luís Fábio , Francisco Mercival Roberto
Published: April 2024

Understanding the mechanisms by which tropical forest fragmentation can affect the persistence of species and populations is of scientific and practical interest. However, nest survival has been one the least addressed of the potentially harmful effects associated with habitat fragmentation, and studies involving nest predator’s identification are still underdeveloped. The Pernambuco Endemism Center (PEC) is the part of the Atlantic Forest located north of the São Francisco River, in northeastern Brazil, where large forest tracts no longer exist and a wave of bird extinctions has occurred recently. Here, we investigated the nest survival of forest understory birds from three PEC fragments (690, 979, and 1036 ha), and we used infra-red camera traps for predators’ identification. Overall, the apparent nest survival was 15.5%, and nest-day-based survival probability for the four more representative species (including two endemic and threatened taxa) were 2.6, 4.4, 6.9, and 18.9%, being 2.7 to 8.5 times smaller than populations or related taxa from the Atlantic Forest of southeastern Brazil. Predators were marmosets (25%), opossums (25%), tegu (19.4%), coati (16.7%), snakes (8.3%), and hawks (5.5%). Jackknife2 model-predicted nest predator’s richness was 20.7 (SD = 1.6). We reinforce the evidence that nest predation associated with fragmentation can affect negatively the bird populations from tropical forests.
A Sustainable Approach to Asthma Diagnosis: Classification with Data Augmentation, Feature Selection, and Boosting Algorithm
Authors: Lee Zne-Jung , Yang Ming-Ren , Hwang Bor-Jiunn
Published: April 2024

Asthma is a diverse disease that affects over 300 million individuals globally. The prevalence of asthma has increased by 50% every decade since the 1960s, making it a serious global health issue. In addition to its associated high mortality, asthma generates large economic losses due to the degradation of patients’ quality of life and the impairment of their physical fitness. Asthma research has evolved in recent years to fully analyze why certain diseases develop based on a variety of data and observations of patients’ performance. The advent of new techniques offers good opportunities and application prospects for the development of asthma diagnosis methods. Over the last few decades, techniques like data mining and machine learning have been utilized to diagnose asthma. Nevertheless, these traditional methods are unable to address all of the difficulties associated with improving a small dataset to increase its quantity, quality, and feature space complexity at the same time. In this study, we propose a sustainable approach to asthma diagnosis using advanced machine learning techniques. To be more specific, we use feature selection to find the most important features, data augmentation to improve the dataset’s resilience, and the extreme gradient boosting algorithm for classification. Data augmentation in the proposed method involves generating synthetic samples to increase the size of the training dataset, which is then utilized to enhance the training data initially. This could lessen the phenomenon of imbalanced data related to asthma. Then, to improve diagnosis accuracy and prioritize significant features, the extreme gradient boosting technique is used. The outcomes indicate that the proposed approach performs better in terms of diagnostic accuracy than current techniques. Furthermore, five essential features are extracted to help physicians diagnose asthma.
Effects of Froggy Mouth Appliance in Pediatric Patients with Atypical Swallowing: A Prospective Study
Authors: Scribante Andrea , Pascadopoli Maurizio , Gallo Simone , Gandini Paola , Manzini Pietro , Fadani Giulia , Sfondrini Maria Francesca
Published: April 2024

Atypical swallowing has a high incidence in growing subjects. Orthopedic treatment with orthodontic appliances and speech therapy are the main approaches to this problem. The aim of this prospective study was to evaluate the changes in the dental arches induced by one year of treatment with the Froggy Mouth myofunctional appliance designed to correct atypical swallowing. In total, 16 patients with atypical swallowing were instructed to use the Froggy Mouth appliance. A digital intraoral impression was taken at baseline (T0). The Froggy Mouth appliance had to be used for 15 min/day throughout the treatment period. At the end of the first year of treatment (T1), another impression was taken with the same intraoral scanner. Digital casts of the T0 and T1 impressions were obtained using software and the two casts were superimposed to record the following measurements: upper intercanine distance, upper arch diameter, upper arch width, overbite and overjet. The data were statistically analyzed (significance threshold: p < 0.05). Student’s t-test was used to compare pre- and post-treatment measurements. Linear regressions were performed to assess the influence of arch width on anterior and posterior diameters. A significant increase was found for the upper arch diameters (p < 0.05), whereas no statistically significant difference was found for the incisor relationship (overjet/overbite) (p > 0.05). To date, the efficacy of this appliance has not been extensively studied. According to the present prospective study, the Froggy Mouth protocol could be a valuable method as a myofunctional therapy for atypical swallowing, but further studies are needed to confirm these preliminary results.
Evaluation of Mosaic Image Quality and Analysis of Influencing Factors Based on UAVs
Authors: Du Xiaoyue , Zheng Liyuan , Zhu Jiangpeng , Cen Haiyan , He Yong
Published: April 2024

With the growing prominence of UAV-based low-altitude remote sensing in agriculture, the acquisition and processing of high-quality UAV remote sensing images is paramount. The purpose of this study is to investigate the impact of various parameter settings on image quality and optimize these parameters for UAV operations to enhance efficiency and image quality. The study examined the effects of three parameter settings (exposure time, flight altitudes and forward overlap (OF)) on image quality and assessed images obtained under various conditions using signal-to-noise ratio (SNR) and BRISQUE algorithms. The results indicate that the setting of exposure time during UAV image acquisition directly affects image quality, with shorter exposure times resulting in lower SNR. The optimal exposure times for the RGB and MS cameras have been determined as 0.8 ms to 1.1 ms and 4 ms to 16 ms, respectively. Additionally, the best image quality is observed at flight altitudes between 15 and 35 m. The setting of UAV OF complements exposure time and flight altitude; to ensure the completeness of image acquisition, it is suggested that the flight OF is set to approximately 75% at a flight altitude of 25 m. Finally, the proposed image redundancy removal method has been demonstrated as a feasible approach for reducing image mosaicking time (by 84%) and enhancing the quality of stitched images (by 14%). This research has the potential to reduce flight costs, improve image quality, and significantly enhance agricultural production efficiency.
“The House Is on Fire”: A Critical Analysis of Anti-CRT Bans and Faculty Experiences
Authors: Briscoe Kaleb L. , Jones Veronica A.
Published: April 2024

The anti-critical race theory movement has caused educators strife and fear nationally. In these current socio-political times, faculty are navigating unprecedented experiences of racism as they teach and research critical race theory. Through our work, we examined 40 faculty experiences challenging legislation at a national, state, and institutional level. We present recommendations for practice and policy that resist the surveillance experienced during this socio-political backlash.
Design and Assessment of an Active Learning-Based Seminar
Authors: Roig Pedro Juan , Alcaraz Salvador , Gilly Katja , Bernad Cristina , Juiz Carlos
Published: April 2024

The Internet of Things (IoT) is an emerging paradigm, even though it does not receive enough attention in many academic plans. In order to introduce our students to IoT, in this paper we present the overall results of a seminar dedicated to encourage them to design basic IoT projects on a software application called Packet Tracer v8.2.1. Such projects were carried out in groups, whereas the evaluation process was performed by means of filling in a peer review construct after the presentation was made by each team. This construct was previously validated by a panel of five experts by applying the Aiken’s V test, where an overall value of 0.907 was obtained. There were nine items within that construct, which were grouped into three dimensions, such as the quality of the prototypes presented, the communication skills during the presentations of the prototypes, and the alignment of the prototypes with SDGs. The average results obtained for all dimensions were all above 8 out of 10, whilst the medians were all 9 and the coefficient of variations were around 0.2. Those results showed high ratings with moderate variation among them. Furthermore, the reliability of the data collected in the evaluation process was assessed by applying the Cronbach’s alpha, accounting for values above 0.9 for each dimension and overall, which means an excellent internal consistency of such data. Likewise, the level of engagement during the activity was also measured by the means of the ISA engagement scale, resulting in an overall value around 6.5, with a median of 7, which proved a high engagement among students.
Exploring the Effects of Early Extramural English Exposure on the Vocabulary Size of University Students
Authors: Busby Nicole Louise
Published: April 2024

Research has shown that current informal extramural (out-of-class) activities can be an important predictor of second language (L2) vocabulary knowledge, but less is known about the relationship between language proficiency and activities earlier in life, which could have contributed to L2 acquisition. This exploratory study investigated Norwegian university students’ reported exposure to English through extramural activities at an early age and how this related to their current vocabulary size in L2 English. Participants (N = 40) completed an online survey comprising items from the Vocabulary Size Test (VST) and questions about the earliest extramural activity they felt made an important contribution to their knowledge of L2 English and the age at which they engaged in this activity. Participants’ mean English vocabulary size, as measured by the VST, was 11,246 words, and regression analysis found that the age of reported earliest extramural exposure was a significant predictor for L2 vocabulary size but that the current age of participants was not a significant predictor of VST scores. The results suggest that investigating early exposure to extramural input could be an important avenue for future research.