bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-cell metabolome profiling for phenotyping parasitic diseases in phytoplankton
Authors: Vallet Marine , Kaftan Filip , Buaya Anthony , Thines Marco , Guillou Laure , Svatoš Aleš , Pohnert Georg
Published: January 2023

Bloom-forming phytoplankton are key players in aquatic ecosystems, fixing carbon dioxide and forming the base of the marine food web. Diverse stresses, such as nutrient depletion, temperature increase, and pathogen emergence can influence the health and dynamics of algal populations. While population responses to these stressors are well-documented in the aquatic ecosystems, little is known about the individual cellular adaptations. These are however the key to an in-depth physiological understanding of microbiome dynamics in the plankton. Finding solutions to disease control in aquaculture also depends on knowledge of infection dynamics and physiology in algae. Single-cell metabolomics can give insight into infection processes by providing a snapshot of small molecules within a biological system. We used a single-cell metabolome profiling workflow to track metabolic changes of diatoms and dinoflagellates subjected to parasite infection caused by the oomycete Lagenisma coscinodisci and the alveolate Parvilucifera spp. We accurately classified the healthy phenotype of bloom-forming phytoplankton, including the diatoms Coscinodiscus granii and Coscinodiscus radiatus, and the toxic dinoflagellate Alexandrium minutum. We discriminated the infection of the toxic dinoflagellate A. minutum with the alveolate parasitoids Parvilucifera infectans and P. rostrata down to the single-cell resolution. Strain and species-specific responses of the diatom hosts Coscinodiscus spp. Infected with the oomycete pathogen Lagenisma coscinodisci could be recognized. LC-HRMS and fragmentation pattern analysis enabled the structure elucidation of metabolic predictors of infection (guanine, xanthine, DMSP, and pheophorbide). The purine salvage pathway and DMSP lysis could be assigned as regulated processes during host invasion. The findings establish single-cell metabolome profiling with LDI-HRMS coupled with classification analysis as a reliable diagnostic tool to track metabolic changes in algae.
Towards attractive texture modified foods with increased fiber content for dysphagia via 3D printing and 3D scanning
Authors: Ahlinder Astrid , Höglund Evelina , Öhgren Camilla , Miljkovic Ana , Stading Mats
Published: January 2023

As life expectancy increases so do age related problems such as swallowing disorders, dysphagia, which affects 10%–30% of people over 65 years old. For dysphagia patients the texture and rheological properties of the food, and the bolus, is critical to avoid choking and pneumonia. Texture modified foods, timbals, are often served to these patients due to their ease of swallowing. The main concern with these foods is that they do not look visually alike the food they replace, which can decrease the patient’s appetite and lead to reduced food intake and frailty. This study aims to improve both the visual appearance of texturized food as well as the energy density and fiber content of the timbal formulation. 3D scanning and additive manufacturing (3D Printing) were used to produce meals more reminiscent of original food items, increasing their visual appeal. Rheology was used to ensure the original flow profile was maintained as the timbal was reformulated by reducing starch contents and partially replacing with dietary fibers. The amount of starch was reduced from 8.7 wt% in the original formulation to 3.5 wt% and partially replaced with 3 wt% citrus fiber, while maintaining properties suitable for both swallowing and 3D printing. The resulting formulation has improved nutritional properties, while remaining suitable for constructing visually appealing meals, as demonstrated by 3Dprinting a chicken drumstick from a model generated with 3D scanning.
Coproduced urban water services: When technical and governance hybridisation go hand in hand
Authors: Moretto Luisa , Faldi Giuseppe , Rosati Federica Natalia , Teller Jacques
Published: January 2023

This study questions the processes of technical and governance hybridisation in the coproduction of water services in cities of the Global South. The existing literature addresses the compensatory role that water services coproduction plays in urban and peri-urban areas, where access to centralised and reliable water resources is often lacking. However, less research focuses on the evolution of coproduced practices in relation to wider transitions of urban spaces, water resources, centralised infrastructure, and service delivery strategies. Still, the resulting technical and governance configurations stemming from these situations are largely unexplored. This study considers four cities, namely, Hanoi (Vietnam), Dar es Salaam (Tanzania), Cochabamba (Bolivia), and Addis Ababa (Ethiopia). All our case studies are somewhat characterised by rapid land-use changes, juxtaposition of rural and urban activities, varying urban typologies, and increasing poverty, sociospatial inequality, and exclusionary service provision. We draw on data collected from field surveys and participatory workshops with inhabitants and institutional actors between 2017 and 2020 as part of a recent research project. We explore the evolution of water coproduction from technological and governance perspectives. The cases analysed in the research highlight that the time and social development of water coproduction do not follow a linear path. It is rather characterised by cycles of emergence, maturation, and decline. It may build upon pre-existing forms of community-based water management that were established in rural areas (for irrigation or water harvesting, for instance). The results show that water coproduction may have different evolutions, entailing different hybridisation processes. Water coproduction can be characterised by either complementary or concurrent service configurations, by blurring actor categories, and by different drivers in the hybridisation process. Ultimately, evolution in urban coproduced practices appears as a process of technical and governance hybridisation, rather than as final and fixed hybrid systems.
Altering regional development for sustainability: Lessons learned from strategic communications of RCE Saskatchewan (Canada) with government
Authors: Petry Roger Auguste
Published: January 2023

An important part of successful strategies for sustainable development involves altering (or, in some cases, preventing) proposals for development that are unsustainable or have significant opportunity costs relative to more sustainable alternatives. In modern democracies, development proposals normally require formal public approvals (whether at the municipal, provincial/state, or national level) with opportunities for public and specialist input and oversight as well as legal remedies where due processes are not followed. This creates an important locus for ESD, specifically educational interventions by Regional Centers of Expertise on education for sustainable development (RCEs). RCEs are able to rapidly mobilize local, regional, and global expertise to engage such processes, frequently where there are narrow time frames and complex mechanisms for public input. The paper will use a case studies approach examining strategic communications of RCE Saskatchewan with various levels of government in proposed developments within its region in Western Canada. Despite a primary commitment of governments in the RCE Saskatchewan region to economic growth with a more limited role for sustainable development, the RCE has successfully contributed to substantially altering unsustainable development proposals in a range of areas since its acknowledgment in 2007. These proposals have included forest clear-cutting, large-scale water diversions, agricultural drainage, nuclear power, road construction, and potash mining. The RCE's interventions have been modest, involving letters and formal submissions through existing government channels aimed at public officials or elected representatives involved in key stages of decision making. This paper will document some of the main elements of the formal RCE correspondence that has lead to its strategic effectiveness including the RCE's ability to draw upon independent scholarly knowledge (including expertise about governmental processes) and legitimization of local sustainability expertise. These interventions have enabled local learning, modifications of specific development proposals, and, in some cases, system-wide transformations. Importantly, however, it highlights how an older form of university scholarship associated with the rise of the humanities, namely the art of formal correspondence or letter writing, can be customized to the goal of regional education for sustainable development.
Plerixafor and granulocyte colony stimulating factor for poor mobilizers in patients undergoing autologous peripheral hematopoietic stem cell transplantation: Single institution study
Authors: El Cheikh Jean , Terro Khodr , El Warrak Samantha , Ghaoui Nohra , Sharrouf Layal , Timonian Michael Anthony , Ismail Fatima , Zahreddine Ammar , Kreidieh Nabila , Moukalled Nour , Abou Dalle Iman , Bazarbachi Ali
Published: January 2023

Background

Autologous hematopoietic stem cell transplantation (ASCT) has become the mainstay treatment for many hematological malignancies and solid tumors. An adequate number of stem cells must be collected for better ASCT outcomes, which is challenging in 5%–30% of patients. To improve mobilization, plerixafor is used along with granulocyte colony-stimulating factor (G-CSF).

Patients and methods

We conducted a retrospective single center study involving patients who received plerixafor pre-ASCTs between January 2013 and December 2020 at a tertiary care center in Lebanon. We identified a total of 84 consecutive adult patients. All patients identified were poor mobilizers and have eventually received plerixafor either as pre-emptive use before first apheresis in those with peripheral CD34 + of less than 20 cells/ul, or after failure of first apheresis in those with peripheral stem cells (PSC) >2.0 × 106 cells/Kg.

Results

The median age at ASCT was 52.7 years (22–74) with 61% male predominance. Multiple myeloma was the most prevalent disease 64% followed by Lymphoma 32%. The majority of patients were in complete remission 64% at the time of ASCT. Most patients received proteasome inhibitor-based induction therapy 67% and Melphalan-based conditioning therapy 68%. The median follow-up from ASCT was 9 months (1–59). It was noted that greater body mass index (BMI) is a significant factor for better PSC collection whether premobilization (P = 0.003), or post plerixafor mobilization (P = 0.024). Moreover, Multiple Myeloma patients showed better mobilization using Plerixafor (P = 0.049). Using Plerixafor along with G-CSF in poor mobilizers post G-CSF alone showed a statistically significant increase in the collected PSC mean from 0.67 × 106 cells/Kg to 4.90 × 106 cells/Kg (P < 0.001) with a failure rate only for 12 patients (15%). The infusion of PSC > 2.5 × 106 cells/Kg has shown 3 days decrease in time to platelet engraftment (P = 0.021) and a 36% decrease in progression/relapse rate (P = 0.025).

Conclusion

Plerixafor is effective in increasing the PSC yield in poor mobilizers. Low BMI and hematologic malignancies other than Multiple Myeloma are risk factors for poor mobilization. More studies should be performed to establish more risk factors, helping us to identify poor mobilizers more accurately and initiate plerixafor mobilization early on.
Effect of acute ankle experimental pain on lower limb motor control assessed by the modified star excursion balance test
Authors: Bertrand-Charette Michaël , Roy Jean-Sébastien , Bouyer Laurent J.
Published: January 2023

Introduction

Following most musculoskeletal injuries, motor control is often altered. Acute pain has been identified as a potential contributing factor. However, there is little evidence of this interaction for acute pain following ankle sprains. As pain is generally present following this type of injury, it would be important to study the impact of acute pain on ankle motor control. To do so, a valid and reliable motor control test frequently used in clinical settings should be used. Therefore, the objective of this study was therefore to assess the effect of acute ankle pain on the modified Star Excursion Balance Test reach distance.

Methods

Using a cross-sectional design, 48 healthy participants completed the modified Star Excursion Balance Test twice (mSEBT1 and mSEBT2). Following the first assessment, they were randomly assigned to one of three experimental groups: Control (no stimulation), Painless (non-nociceptive stimulation) and Painful (nociceptive stimulation). Electrodes were placed on the right lateral malleolus to deliver an electrical stimulation during the second assessment for the Painful and Painless groups. A generalized estimating equations model was used to compare the reach distance between the groups/conditions and assessments.

Results

Post-hoc test results: anterior (7.06 ± 1.54%; p < 0.0001) and posteromedial (6.53 ± 1.66%; p < 0.001) directions showed a significant reach distance reduction when compared to baseline values only for the Painful group. Regarding the anterior direction, this reduction was larger than the minimal detectable change (5.87%).

Conclusion

The presence of acute pain during the modified Star Excursion Balance Test can affect performance and thus might interfere with the participant's lower limb motor control. As none of the participants had actual musculoskeletal injury, this suggests that pain and not only musculoskeletal impairments could contribute to the acute alteration in motor control.
Advances in PET imaging of ischemic stroke
Authors: Orhii Paulette D. , Haque Muhammad E. , Fujita Masahiro , Selvaraj Sudhakar
Published: January 2023

Ischemic strokes make up 87% of all cerebrovascular events. Intravenous tissue plasminogen activator (tPA), a thrombolytic agent, has been recognized as the only viable option for patients with ischemic stroke if administered within 3.5 h of onset and increases the risk of hemorrhagic transformation if administered beyond the treatment window. Acute treatment strategies are centered around rescuing salvageable penumbra. Molecular imaging using positron emission tomography (PET) has shown higher sensitivity and specificity than CT and MRI in delineating penumbral tissues. In addition, PET imaging has identified the role of key inflammatory mediators in atherosclerosis, cellular damage, and recovery. Recently, a novel PET imaging study has shown the feasibility of investigating synaptic density in subacute stroke. Lastly, novel PET radiotracers have been developed to further explore biochemical mechanisms implicated in stroke pathophysiology. Further investigation with PET is needed to understand stroke mechanisms and advance pharmacologic treatment.
A typology of sustainable circular business models with applications in the bioeconomy
Authors: De Keyser Erika , Mathijs Erik
Published: January 2023

As an approach to sustainable development, circular business models are increasingly being developed. However, many circular business models focus on environmental or technological contributions to sustainability rather than considering all dimensions of sustainability simultaneously. Based on existing sustainable business model archetypes, a hierarchical business model typology is developed that allows a stepwise exploration of sustainable business model innovation opportunities incorporating an environmental, social and economic dimension. An analysis of business model components generates a closer look on the six newly defined Sustainable Circular Business Models. Finally, a conceptual application for organic waste valorization technologies, supported by examples from literature, allows a practical view on the implementation of the business models in the bio-economy. The typology offers a guide toward sustainable business model design or innovation opportunities centered around technologies creating value from waste.
Case Report: A papillary thyroid microcarcinoma patient with skip lymph node metastasis and multiple distant metastasis
Authors: Jiang Qin , Zhai Mimi , Lin Xiang , Ren Chutong , Li Yunxia , Ye Fei , Gong Yi , Liu Sushun
Published: January 2023

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Papillary thyroid microcarcinoma (PTMC) is defined as PTC with a diameter less than 1 centimeter. Most lymph nodes of PTC patients have metastasized to the central neck, and a few lymph nodes have metastasized to the lateral neck. Skip lymph node metastasis, that is, lateral cervical lymph node metastasis without central lymph node metastasis, is even less common. Additionally, distant metastasis of PTMC is also rare, mainly occurring in the lung and bone. Here, we reported a case of PTMC patient with skip lymph node metastasis and multiple distant metastasis. The patient presented with a huge shoulder mass and the primary tumor was found to originate from the thyroid. However, the patient only suffered with PTMC via postoperative pathological results, and interestingly, the patient only had skip lymph node metastasis. Thus, we should focus on PTMC patients with lateral cervical lymph nodes metastasis, especially those with skip metastasis. In addition, this case provides a new perspective for us to understand of skip lymph metastasis and distant metastasis of PTMC.
Case report of retroperitoneal ectopic pancreas with adrenal adenoma
Authors: Sun Zhaochen , Chen Tao , Zhu Xuefeng , Geng Jie , Sui Chaofan , Zhang Nan , Guo Lingfei
Published: January 2023

Background

Ectopic pancreas is a congenital anomaly in which pancreatic tissue is anatomically separated from the main gland and without vascular or ductal continuity. A case of retroperitoneal ectopic pancreas with adrenal adenoma has never yet been reported.

Case Presentation

A 54-year-old man presented three masses in the left retroperitoneum, and two of them were resected. The pathologic findings were a retroperitoneal ectopic pancreas with adrenal adenoma.

Conclusion

We report an extremely rare case of a retroperitoneal ectopic pancreas and its characterization with dynamic gadolinium-enhanced magnetic resonance imaging (MRI).
Specificities of Meningitis and Meningo-Encephalitis After Kidney Transplantation: A French Retrospective Cohort Study
Authors: Tamzali Y. , Scemla A. , Bonduelle T. , Garandeau C. , Gilbert M. , Randhawa S. , De Nattes T. , Hachad H. , Pourcher V. , Taupin P. , Kaminski H. , Hazzan M. , Moal V. , Matignon M. , Fihman V. , Levi C. , Le Quintrec M. , Chemouny J. M. , Rondeau E. , Bertrand D. , Thervet E. , Tezenas Du Montcel S. , Savoye E. , Barrou B. , Kamar N. , Tourret J.
Published: January 2023

Kidney transplant recipients develop atypical infections in their epidemiology, presentation and outcome. Among these, meningitis and meningoencephalitis require urgent and adapted anti-infectious therapy, but published data is scarce in KTRs. The aim of this study was to describe their epidemiology, presentation and outcome, in order to improve their diagnostic and management. We performed a retrospective, multicentric cohort study in 15 French hospitals that included all 199 cases of M/ME in KTRs between 2007 and 2018 (0.9 case per 1,000 KTRs annually). Epidemiology was different from that in the general population: 20% were due to Cryptococcus neoformans, 13.5% to varicella-zoster virus, 5.5% to Mycobacterium tuberculosis, and 4.5% to Enterobacteria (half of which produced extended spectrum beta-lactamases), and 5% were Post Transplant Lymphoproliferative Disorders. Microorganisms causing M/ME in the general population were infrequent (2%, for Streptococcus pneumoniae) or absent (Neisseria meningitidis). M/ME caused by Enterobacteria, Staphylococci or filamentous fungi were associated with high and early mortality (50%–70% at 1 year). Graft survival was not associated with the etiology of M/ME, nor was impacted by immunosuppression reduction. Based on these results, we suggest international studies to adapt guidelines in order to improve the diagnosis and the probabilistic treatment of M/ME in SOTRs.
Towards Multi-Satellite Collaborative Computing via Task Scheduling Based on Genetic Algorithm
Authors: Fei Hongxiao , Zhang Xi , Long Jun , Liu Limin , Wang Yunbo
Published: January 2023

With satellite systems rapidly developing in multiple satellites, multiple tasks, and high-speed response speed requirements, existing computing techniques face the following challenges: insufficient computing power, limited computing resources, and weaker coordination ability. Meanwhile, most methods have more significant response speed and resource utilization limitations. To solve the above problem, we propose a distributed collaborative computing framework with a genetic algorithm-based task scheduling model (DCCF-GA), which can realize the collaborative computing between multiple satellites through genetic algorithm. Specifically, it contains two aspects of work. First, a distributed architecture of satellites is constructed where the main satellite is responsible for distribution and scheduling, and the computing satellite is accountable for completing the task. Then, we presented a genetic algorithm-based task scheduling model that enables multiple satellites to collaborate for completing the tasks. Experiments show that the proposed algorithm has apparent advantages in completion time and outperforms other algorithms in resource efficiency.
Classification of Pear Leaf Diseases Based on Ensemble Convolutional Neural Networks
Authors: Fenu Gianni , Malloci Francesca Maridina
Published: January 2023

Over the last few years, the impact of climate change has increased rapidly. It is influencing all steps of plant production and forcing farmers to change and adapt their crop management practices using new technologies based on data analytics. This study aims to classify plant diseases based on images collected directly in the field using deep learning. To this end, an ensemble learning paradigm is investigated to build a robust network in order to predict four different pear leaf diseases. Several convolutional neural network architectures, named EfficientNetB0, InceptionV3, MobileNetV2 and VGG19, were compared and ensembled to improve the predictive performance by adopting the bagging strategy and weighted averaging. Quantitative experiments were conducted to evaluate the model on the DiaMOS Plant dataset, a self-collected dataset in the field. Data augmentation was adopted to improve the generalization of the model. The results, evaluated with a range of metrics, including accuracy, recall, precison and f1-score, showed that the proposed ensemble convolutional neural network outperformed the single convolutional neural network in classifying diseases in real field-condition with variation in brightness, disease similarity, complex background, and multiple leaves.
Evaluation of Monitoring Data in Foods
Authors: Ambrus Árpád , Szenczi-Cseh Júlia , Doan Vy Vy N. , Vásárhelyi Adrienn
Published: January 2023

Pesticide residue monitoring data reflect the actual residues in foods as traded and are suitable for estimating consumers’ exposure, evaluating compliance with maximum residue limits, MRLs, and refining future risk-based sampling programmes. The long-term exposure (daily intake) is calculated from the national or regional food consumption data and average residues in the edible portions of food. The non-detected residues may be counted as LOQ, 0.5 LOQ, or 0. The short-term intake is calculated from the large portion consumption of individual foods multiplied by the highest residue concentration found in them and the relevant variability factor. Dietary exposure to a pesticide residue may be characterised by the hazard quotient (HQ) and the hazard index (HI). Cumulative exposure should only be assessed for those compounds having the common mechanism of toxicity (cumulative assessment group, CAG). The number of residue data required for these assessments should be calculated with distribution-free statistics at the targeted confidence level. The proper evaluation of the numerous results can only be completed if they are electronically recorded and can be retrieved in specific formats. Our objectives are to present methods for consumer risk assessment, testing compliance with MRLs, and ranking commodities for risk-based sampling and to give examples of electronic processing of residue data.
Reinforcement Learning-Based Adaptive Position Control Scheme for Uncertain Robotic Manipulators with Constrained Angular Position and Angular Velocity
Authors: Xie Zhihang , Lin Qiquan
Published: January 2023

Aiming at robotic manipulators subject to system uncertainty and external disturbance, this paper presents a novel adaptive control scheme that uses the time delay estimation (TED) technique and reinforcement learning (RL) technique to achieve a good tracking performance for each joint of a manipulator. Compared to conventional controllers, the proposed control scheme can not only handle the system parametric uncertainty and external disturbance but also guarantee both the angular positions and angular velocities of each joint without exceeding their preset constraints. Moreover, it has been proved by using Lyapunov theory that the tracking errors are uniformly ultimately bounded (UUB) with a small bound related to the parameters of the controller. Additionally, an innovative RL-based auxiliary term in the proposed controller further minimizes the steady state tracking errors, and thereby the tracking accuracy is not compromised by the lack of asymptotic convergence of tracking errors. Finally, the simulation results validate the effectiveness of the proposed control scheme.
Tooth Diversity Underpins Future Biomimetic Replications
Authors: Wang Di , Han Shuangxia , Yang Ming
Published: January 2023

Although the evolution of tooth structure seems highly conserved, remarkable diversity exists among species due to different living environments and survival requirements. Along with the conservation, this diversity of evolution allows for the optimized structures and functions of teeth under various service conditions, providing valuable resources for the rational design of biomimetic materials. In this review, we survey the current knowledge about teeth from representative mammals and aquatic animals, including human teeth, herbivore and carnivore teeth, shark teeth, calcite teeth in sea urchins, magnetite teeth in chitons, and transparent teeth in dragonfish, to name a few. The highlight of tooth diversity in terms of compositions, structures, properties, and functions may stimulate further efforts in the synthesis of tooth-inspired materials with enhanced mechanical performance and broader property sets. The state-of-the-art syntheses of enamel mimetics and their properties are briefly covered. We envision that future development in this field will need to take the advantage of both conservation and diversity of teeth. Our own view on the opportunities and key challenges in this pathway is presented with a focus on the hierarchical and gradient structures, multifunctional design, and precise and scalable synthesis.
Machine Learning-Based Mortality Prediction Model for Critically Ill Cancer Patients Admitted to the Intensive Care Unit (CanICU)
Authors: Ko Ryoung-Eun , Cho Jaehyeong , Shin Min-Kyue , Oh Sung Woo , Seong Yeonchan , Jeon Jeongseok , Jeon Kyeongman , Paik Soonmyung , Lim Joon Seok , Shin Sang Joon , Ahn Joong Bae , Park Jong Hyuck , You Seng Chan , Kim Han Sang
Published: January 2023

Background: Although cancer patients are increasingly admitted to the intensive care unit (ICU) for cancer- or treatment-related complications, improved mortality prediction remains a big challenge. This study describes a new ML-based mortality prediction model for critically ill cancer patients admitted to ICU. Patients and Methods: We developed CanICU, a machine learning-based 28-day mortality prediction model for adult cancer patients admitted to ICU from Medical Information Mart for Intensive Care (MIMIC) database in the USA (n = 766), Yonsei Cancer Center (YCC, n = 3571), and Samsung Medical Center in Korea (SMC, n = 2563) from 2 January 2008 to 31 December 2017. The accuracy of CanICU was measured using sensitivity, specificity, and area under the receiver operating curve (AUROC). Results: A total of 6900 patients were included, with a 28-day mortality of 10.2%/12.7%/36.6% and a 1-year mortality of 30.0%/36.6%/58.5% in the YCC, SMC, and MIMIC-III cohort. Nine clinical and laboratory factors were used to construct the classifier using a random forest machine-learning algorithm. CanICU had 96% sensitivity/73% specificity with the area under the receiver operating characteristic (AUROC) of 0.94 for 28-day, showing better performance than current prognostic models, including the Acute Physiology and Chronic Health Evaluation (APACHE) or Sequential Organ Failure Assessment (SOFA) score. Application of CanICU in two external data sets across the countries yielded 79–89% sensitivity, 58–59% specificity, and 0.75–0.78 AUROC for 28-day mortality. The CanICU score was also correlated with one-year mortality with 88–93% specificity. Conclusion: CanICU offers improved performance for predicting mortality in critically ill cancer patients admitted to ICU. A user-friendly online implementation is available and should be valuable for better mortality risk stratification to allocate ICU care for cancer patients.
Doxycycline-Induced Changes in Circulating MMP or TIMP2 Levels Are Not Associated with Skeletal-Related Event-Free or Overall Survival in Patients with Bone Metastases from Breast Cancer
Authors: Zhao Huijun , Pond Gregory , Simos Demetrios , Wang Zhou , Robertson Susan , Singh Gurmit , Vandermeer Lisa , Clemons Mark , Addison Christina Lynn
Published: January 2023

Doxycycline is often used as a promoter of inducible gene expression in preclinical models; however, it can also have direct effects on tumor growth and survival. This is due in part to its ability to inhibit cell invasion and regulate matrix metalloproteinase (MMP) expression. Given that doxycycline is also osteotropic, a clinical study to assess its effects on modulation of tumor progression or prevention of skeletal-related events (SRE) in patients with bone metastases from breast cancer (the Achilles trial) was undertaken. Patients received 100 mg of oral doxycycline twice daily for 12 weeks, with serum obtained at baseline and 4, 8 and 12 weeks post-initiation of doxycycline treatment. Exploratory analysis of the effects of doxycycline on circulating levels of MMP or tissue inhibitor of matrix metalloproteinase 2 (TIMP2) was performed in enrolled patients. Statistically significant associations were observed between MMP2, MMP9 and TIMP2 at baseline with significant associations maintained between absolute levels and changes in levels of MMP2 and TIMP2 at weeks 4–12 post initiation of doxycycline. Treatment with doxycycline generally resulted in decreases in MMP2 and MMP9 levels with concurrent upregulation of TIMP2 at 12 weeks post-initiation of doxycycline treatment. Despite this, we observed no association with the levels of any of these factors with either SRE-free or overall survival in this patient cohort. In summary, despite observing hypothesized effects of doxycycline administration on surrogate markers of its anti-tumor activity, measures of circulating levels of these biomarkers were not prognostic in this patient population.
The Influence of the Normal Mammary Microenvironment on Breast Cancer Cells
Authors: Campbell Caroline J. , Booth Brian W.
Published: January 2023

The tumor microenvironment is recognized as performing a critical role in tumor initiation, progression, and metastasis of many cancers, including breast cancer. The breast cancer microenvironment is a complex mixture of cells consisting of tumor cells, immune cells, fibroblasts, and vascular cells, as well as noncellular components, such as extracellular matrix and soluble products. The interactions between the tumor cells and the tumor microenvironment modulate tumor behavior and affect the responses of cancer patients to therapies. The interactions between tumor cells and the surrounding environment can include direct cell-to-cell contact or through intercellular signals over short and long distances. The intricate functions of the tumor microenvironment in breast cancer have led to increased research into the tumor microenvironment as a possible therapeutic target of breast cancer. Though expanded research has shown the clear importance of the tumor microenvironment, there is little focus on how normal mammary epithelial cells can affect breast cancer cells. Previous studies have shown the normal breast microenvironment can manipulate non-mammary stem cells and tumor-derived cancer stem cells to participate in normal mammary gland development. The tumorigenic cells lose their tumor-forming capacity and are “redirected” to divide into “normal”, non-tumorigenic cells. This cellular behavior is “cancer cell redirection”. This review will summarize the current literature on cancer cell redirection and the normal mammary microenvironment’s influence on breast cancer cells.
The Impact of a Family-Centred Intervention for Parents of Children with Developmental Disabilities: A Model Project in Rural Ireland
Authors: McConkey Roy , O’Hagan Pauline , Corcoran Joanne
Published: January 2023

The greater risk of poor mental health and social isolation, experienced by parents of children with developmental disabilities, is compounded by family circumstances and living in rural settings. Often parents receive little personal support. Family-centred interventions have been recommended internationally for promoting children’s development, as well as boosting parental wellbeing. Yet, in many countries, current service provision is predominately child-focused and clinic-centred. An innovative, family-centred support service was designed and evaluated in a rural county of Ireland. Support staff visit the family home every month for around one year with regular check-ins by phone. The service aims included setting developmental goals for the child that were agreed with parents, alongside actions to address the personal needs of parents and siblings. In addition, community activities are identified or created to promote the social inclusion of the child and family in local communities, as well as locating opportunities for social activities for mothers. To date, 96 families with 110 children have been involved and three monthly reviews have been undertaken of each child’s progress. Baseline measures on parents’ mental health and social isolation were gathered and repeated when parents had completed their involvement with the project, along with qualitative information regarding the parents’ experiences. Most children attained their learning targets, alongside those selected as personal goals by parents; in particular, parents reported their child’s greater involvement in community activities, increased knowledge and skills, and with more confidence and resilience. Significant increases in parental well-being scores were reported, but there was a limited impact on their social participation and that of their child. This evidence-based model of provision is an example of how current social care provision for families who have a child with developmental disabilities could be cost-effectively re-envisioned even in rural areas.
A Method for the Dynamics of Vortices in a Bose-Einstein Condensate: Analytical Equations of the Trajectories of Phase Singularities
Authors: De María-García Sergi , Ferrando Albert , Conejero J. Alberto , De Córdoba Pedro Fernández , García-March Miguel Ángel
Published: January 2023

We present a method to study the dynamics of a quasi-two dimensional Bose-Einstein condensate which initially contains several vortices at arbitrary locations. The method allows one to find the analytical solution for the dynamics of the Bose-Einstein condensate in a homogeneous medium and in a parabolic trap, for the ideal non-interacting case. Secondly, the method allows one to obtain algebraic equations for the trajectories of the position of phase singularities present in the initial condensate along with time (the vortex lines). With these equations, one can predict quantities of interest, such as the time at which a vortex and an antivortex contained in the initial condensate will merge. For the homogeneous case, this method was introduced in the context of photonics. Here, we adapt it to the context of Bose-Einstein condensates, and we extend it to the trapped case for the first time. Also, we offer numerical simulations in the non-linear case, for repulsive and attractive interactions. We use a numerical split-step simulation of the non-linear Gross-Pitaevskii equation to determine how these trajectories and quantities of interest are changed by the interactions. We illustrate the method with several simple cases of interest, both in the homogeneous and parabolically trapped systems.
X or Y Cancer: An Extensive Analysis of Sex Differences in Lung Adenocarcinoma
Authors: Hammouz Raneem Yaseen , Orzechowska Magdalena , Anusewicz Dorota , Bednarek Andrzej K.
Published: January 2023

Background: Cellular metabolism is a tightly controlled process during which cell growth and survival are maintained. Lung cancer is a disease with clear sex differences, where female patients have better survival rates than males. Evidence of sex differences is demonstrated in cancer risk, prognosis and response to different therapies, yet a sex-specific approach to cancer studies is not widely considered. These different tumour characteristics attributed to sex that impact disease outcome, including constitutional genetic and somatic molecular differences, make it essential to assess viral and hormonal influences. Methods: In silico analysis of lung adenocarcinoma (LUAD) TCGA data, including K-means clustering algorithm, dimensional reduction with principal component analysis and differential expression analysis using EdgeR (p < 0.05), were used to explore some robust sex differences in LUAD that exist in core signalling pathways and metabolic processes between males and females. The correlation of differentially expressed genes (DEGs) expression with immune abundance in the LUAD cohort was analysed on TIMER2.0 and adjusted by tumour purity utilising Cox proportional hazard. Multiple factorial analysis heatmap visualisation was used to examine endogenous steroid hormonal effects on LUAD patients with different smoking status and age groups. Results: We found 161 DEGs showing key differences in regulation of immune system and cellular homeostasis, key elements of divergent cancer progression, between the two sexes. We also found male and female LUAD patients to favour different metabolic intermediates for energy production to support tumourigenesis. Additionally, high levels of Tregs accompanied by DEGs correlated with better LUAD prognosis, and circulating hormonal transcriptional targets affect proliferation and progression in males and females differently. Finally, we examined the role of oestrogen protection in men and pre-/postmenopausal women. Conclusions: Further studies should focus on sex-specific changes and investigate sex-specific gene regulatory networks of these DEGs. Several lifestyle factors, including tobacco smoking and diet, differ between males and females. These factors might affect metabolic pathways and can influence the activity of epigenetic regulators, resulting in significant global epigenetic changes.
Resistance of Lichens and Mosses of Regenerated Alpine Communities to Repeated Experimental Trampling in the Belianske Tatras, Northern Slovakia
Authors: Piscová Veronika , Ševčík Michal , Sedlák Andrej , Hreško Juraj , Petrovič František , Slobodová Terézia
Published: January 2023

Due to the destruction of alpine ecosystems by extreme human trampling, some alpine areas are closed to tourists. After years of regeneration, a tendency toward reopening these areas for tourism is envisaged. Although numerous studies have documented vegetative responses to trampling disturbance, research that thoroughly examines the trampling impacts on the vegetation at different organizational levels is often limited. Most of the previous studies on the human disturbance of vegetation focused on the impacts on vascular plants, while the impacts on lichens or mosses are less well-documented. To understand how regenerated communities respond to further trampling disturbance, we repeated the experimental research on short-term trampling after 14 years in three high-altitude communities in the Tatras in northern Slovakia. According to Cole and Bayfield’s protocol, we evaluated the resistance of communities trampled in 2008 and 2022, with a focus on groups of lichens and mosses and their individual species. This research brings new knowledge regarding the different behaviors of regenerated vegetation, especially lichens and mosses, to trampling disturbance. The results show that human trampling in alpine communities has a large negative impact and, therefore, management plans should discourage off-trail hiking and limit recreational activities in sensitive or reopened alpine areas.
Transcriptome Dataset of Strawberry (Fragaria × ananassa Duch.) Leaves Using Oxford Nanopore Sequencing under LED Irradiation and Application of Methyl Jasmonate and Methyl Salicylate Hormones Treatment
Authors: Adrian M , Poerwanto Roedhy , Inoue Eiichi , Matra Deden Derajat
Published: January 2023

This data descriptor introduces a transcriptome dataset of strawberry plant left exposed to an LED light treatment and plant hormones of Methyl Jasmonate (MeJA) and Methyl Salicylate (MeSA). These data consist of a transcriptome dataset (four libraries) obtained from the leaves of strawberry plants treated with LEDs of blue and red spectrums and the hormones of Methyl Jasmonate (MeJA) and Methyl Salicylate (MeSA), which allowed us to conduct a further analysis of the growth and development processes of strawberry plants. In addition, we describe detailed procedures on how the plants were prepared and treated and how the data were generated and processed beforehand. Further analysis of these data will significantly help to improve our understanding of the molecular mechanisms of LED light and MeJA-MeSA in strawberry plants.
Impact of Investments and R&D Costs in Renewable Energy Technologies on Companies’ Profitability Indicators: Assessment and Forecast
Authors: Prokopenko Olha , Kurbatova Tetiana , Khalilova Marina , Zerkal Anastasiia , Prause Gunnar , Binda Jacek , Berdiyorov Temur , Klapkiv Yuriy , Sanetra-Półgrabi Sabina , Komarnitskyi Igor
Published: January 2023

Renewable energy technologies play a crucial role in solving global energy and environmental issues, and the pace of the energy transition directly depends on improving their efficiency. Presently, the development and implementation of renewable energy systems are ensured mainly through state funding, the possibilities of which are limited. The potential of attracting private investments depends directly on their impact on companies’ profitability indicators, and the uncertainty regarding the return on investments is one of the main barriers affecting investors’ decision-making. Based on a vector autoregressive model for analysing the stationary time series, the paper explores the impact of long-term investments and research and development costs in renewable energy technologies on the financial performance of ten of the largest companies operating in this field. The study’s results showed that investments and spending on research and development positively affect such companies’ profitability indicators as earnings before interest, taxes, depreciation and amortisation, earnings before interest and tax, net income, and return on investment. The obtained results can be used to substantiate the economic effectiveness of investments in developing and improving renewable energy technologies when forming the companies’ financial policies to support them.
A Novel Approach for Optimizing Building Energy Models Using Machine Learning Algorithms
Authors: Kubwimana Benjamin , Najafi Hamidreza
Published: January 2023

The current practice with building energy simulation software tools requires the manual entry of a large list of detailed inputs pertaining to the building characteristics, geographical region, schedule of operation, end users, occupancy, control aspects, and more. While these software tools allow the evaluation of the energy consumption of a building with various combinations of building parameters, with the manual information entry and considering the large number of parameters related to building design and operation, global optimization is extremely challenging. In the present paper, a novel approach is developed for the global optimization of building energy models (BEMs) using Python EnergyPlus. A Python-based script is developed to automate the data entry into the building energy modeling tool (EnergyPlus) and numerous possible designs that cover the desired ranges of multiple variables are simulated. The resulting datasets are then used to establish a surrogate BEM using an artificial neural network (ANN) which is optimized through two different approaches, including Bayesian optimization and a genetic algorithm. To demonstrate the proposed approach, a case study is performed for a building on the campus of the Florida Institute of Technology, located in Melbourne, FL, USA. Eight parameters are selected and 200 variations of them are supplied to EnergyPlus, and the produced results from the simulations are used to train an ANN-based surrogate model. The surrogate model achieved a maximum of 90% R2 through hyperparameter tuning. The two optimization approaches, including the genetic algorithm and the Bayesian method, were applied to the surrogate model, and the optimal designs achieved annual energy consumptions of 11.3 MWh and 12.7 MWh, respectively. It was shown that the approach presented bridges between the physics-based building energy models and the strong optimization tools available in Python, which can allow the achievement of global optimization in a computationally efficient fashion.
CO2 Emissions from Renewable and Non-Renewable Electricity Generation Sources in the G7 Countries: Static and Dynamic Panel Assessment
Authors: Voumik Liton Chandra , Islam Md. Azharul , Ray Samrat , Mohamed Yusop Nora Yusma , Ridzuan Abdul Rahim
Published: January 2023

The threat of global warming has increased due to industrialization, urbanization, population expansion, and changes in lifestyle among the Group of Seven(G7) Carbon dioxide emissions (CO2) directly affect how much electricity can be generated from various sources. This research aims to identify environmental hazards associated with various energy sources. Analyzing the impact of various energy sources on CO2 emissions from electricity and heat production using data from the G7. The data is analyzed using quantile regression (QR), generalized method of moments (GMM), random effects (RE), and fixed effects (FE). Our results indicate a substantial positive impact on CO2 emissions regardless of the technology used to generate coal and gas power. Coal-fired power plants have a larger impact on the environment than other sources of emissions. Also, all coal and gas coefficients are significant in FE, RE, GMM, and QR. Oil coefficients have a negative impact on environmental degradation and are significant for FE, RE, and D-GMM regressions. Hydroelectric and renewable energy production can reduce CO2 emissions in all regression models. Nuclear energy has a beneficial impact on the environment, but the coefficients are only significant for S-GMM and the last quantile. However, the most significant result of this study is the identification of a cause-and-effect relationship between CO2 emissions and energy production. Carbon dioxide (CO2) emissions can be lowered by shifting away from fossil fuels and toward renewable and hydroelectric sources. The research also suggests several renewable and alternative electricity production policies for sustainable energy.