bluuebunny/crossref_metadata_2025 huggingface dataset:
Arylsulfatases and neuraminidases modulate engagement of CCR5 by chemokines by removing key electrostatic interactions
Authors: Pinheiro Inês , Calo Nicolas , Paolini-Bertrand Marianne , Hartley Oliver
Published: October 2023

The chemokine receptor CCR5 is known to exist in cell surface subpopulations that differ in their capacity to engage ligands. One proposed explanation for this phenomenon is the presence of CCR5 species with different levels of post-translational modifications (PTMs). Tyrosine sulfation and O-glycan sialylation are PTMs that add negative charges to the extracellular domain of CCR5 and make strong contributions to chemokine binding but it is not known whether cellular mechanisms to control their levels exist. In this study we used a combination of sulfation-sensitive and sulfation-insensitive CCR5 ligands to show that the rate of turnover of CCR5 tyrosine sulfation is more rapid than the rate of turnover of the receptor itself. This suggests that the steady state level of CCR5 sulfation is maintained through the combination of tyrosine protein sulfotransferase (TPST), the trans-Golgi network (TGN)-resident ‘source enzyme, and a ‘sink’ activity that removes tyrosine sulfation from CCR5. By measuring the effects on ligand binding of knockdown and overexpression experiments, we provided evidence that non-lysosomal cellular arylsulfatases, particularly ARSG, ARSI and ARSJ, are CCR5 sulfation ‘sink’ enzymes. We also used targeted knockdown and sialylation-sensitive and insensitive chemokines to identify the sialidase NEU3 as a candidate ‘sink’ enzyme for CCR5 O-glycan sialylation. This study provides the first experimental evidence of activity of sulfatase and sialidase ‘sink’ enzymes on CCR5, providing a potential mechanism for cells to control steady-state levels of these PTMs and thereby exert dynamic control over receptor-ligand interactions at the cell surface and during receptor desensitization.
Conditional survival nomogram for dynamic monitoring of long-term survival in non- keratinizing large cell squamous cell carcinoma
Authors: Zhang Jin , Xiang Yang , Chen Jiqiu , Liu Lei , Liu Qingsong , Jin Jian , Zhu Shihui
Published: October 2023

Background:
The incidence of nonkeratinizing large cell squamous cell carcinoma (NKLCSCC) continues to rise. Compared to other squamous cell carcinoma subtypes, the NKLCSCC displays lower differentiation and higher malignancy, necessitating specialized analysis and research of this disease. Therefore, the aim of our study was to develop and evaluate a novel conditional survival (CS)-based prediction model for NKLCSCC patients, with the objective of offering timely and accurate updates on survival rates.
Methods:
The data for patients with NKLCSCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The identified patients were randomized into the training group and the validation group, with a proportion of 7:3. The Kaplan–Meier method was used to estimate overall survival (OS). The CS rate was defined as the likelihood of a patient surviving for a specific period of time following NKLCSCC diagnosis, based on the number of years they have already survived. We firstly described the CS pattern of the NKLCSCC patients. Subsequently, a least absolute shrinkage and selection operator (LASSO) regression method with 10-fold cross-validation was employed to identify prognostic factors. A multivariate Cox regression model was used to demonstrate these predictors’ prognostic value and to develop a CS-based nomogram model. Lastly, the predictive performance of the developed model was evaluated and validated.
Results:
Based on the SEER database, a total of 7,252 elderly patients with NKLCSCC were identified from 2000 to 2019, with 5,076 patients allocated to the training group and 2,176 patients assigned to the validation group. Through CS analysis, we observed that these patients exhibited a remarkable improvement in 10-year survival rate with each additional year of survival. The survival rate increased from initially 56% to 62%, 70%, 74%, 79%, 82%, 86%, 90%, 93% and ultimately reached an impressive 97%. The LASSO regression analysis achieved a 10-fold cross-validation and identified 9 significant predictive factors. Then, the CS-based nomogram was successfully constructed based on these selected predictors and it could effectively stratify risk for these patients. Furthermore, this CS-based survival prediction model was successfully validated in both training and validation groups.
Conclusion:
This study described the CS pattern of patients with NKLCSCC, underscoring the gradual improvement in survival rates among long-term survivors over time. We have also developed the first novel CS-based nomogram model for NKLCSCC patients, which enables real-time prognostic prediction and risk stratification, facilitating personalized treatment decision-making and devising more cost-effective follow-up strategies for clinicians.
Antimicrobial Activity and Phytochemical Analysis of Essential Oil of Carum Carvi, an Important Phytofood of Indian Folk Medicinal Plants
Authors: Pande Kamal K , Pandey Bharat , Pande Lata , Paliwal A.K. , Kumar Tarun
Published: October 2023

The present study was done to investigate the chemical constituents of Carum carvi Linn (Caraway) and to evaluate their antimicrobial activity. The fresh plants and seeds were collected from Himalayan hills of Uttarakhand state of India. Essential oil was obtained via steam distillation followed by chromatographic separation (TLC, GC-MS). Head space GC-MS was also done for quantification of highly volatile compounds. Biological activity of oil was evaluated by determination of minimum inhibitory concentration, which was found active against both bacteria and fungi. The MIC of the samples ranged from 50 µg/ml to 100 µg/ml. The antibacterial activity of Carum carvi essential oil is apparently due to carvone (23.3%), limonene (18.2%), carvacrol (6.7%), and linalool (0.3%), which inhibit the growth of fungi and bacteria.
Hypertension Among Persons Living With HIV/Aids and Its Association With Hiv-Related Health Factors
Authors: Denu Mawulorm KI , Revoori Ritika , Buadu Maame Araba E. , Oladele Oluwakemi , Berko Kofi Poku
Published: October 2023

Background Human Immunodeficiency Virus (HIV) infection remains a public health concern in many countries. The increased life expectancy in the post-Antiretroviral Therapy (ART) era has led to an increased risk of cardiovascular disease and death among Persons Living with HIV (PLHIV). Hypertension remains a significant risk factor for cardiovascular disease among PLHIV. Some studies have suggested associations between hypertension among PLHIV and HIV-related health factors.Objective To determine the prevalence of hypertension among PLHIV on antiretroviral medications and examine its association with HIV-related health factors.Methods A cross-sectional study was conducted among attendants at an adult HIV clinic. 362 study participants were selected by systematic sampling. Data on hypertension diagnosis, HIV-related health factors, sociodemographic and other traditional cardiovascular risk factors were collected using a standardized questionnaire and patient chart review. Multivariate logistic regression model was used to determine the association between hypertension and HIV-related factors, adjusting for other risk factors for hypertension.Results The mean age of participants was 47.9 years and majority of participants were female (77.1%). 42% of study participants had been on antiretroviral medications for > 10 years. The prevalence of hypertension was 17.4%. Age > 50 years was associated with higher odds of hypertension (aOR:3.75, 95%CI:1.68,8.55, p-value:0.002). BMI in overweight and obese categories, and a history of comorbid medical conditions (diabetes, hyperlipidemia) were also associated with higher odds of hypertension (aOR:3.76, 95%CI:1.44,9.81, p-value:0.007), (aOR:3.17, 95%CI:1.21,8.32, p-value:0.019) and (aOR:14.25, 95%CI:7.41,27.41, p-value:<0.001) respectively. No HIV-related health factors were associated with hypertension.Conclusion Hypertension was a common condition among PLHIV on antiretroviral medications. No HIV-related health factors were associated with hypertension. Traditional risk factors associated with hypertension were increased age > 50 years, increased BMI, and a history of comorbid medical conditions.
Implications of the Inflation Reduction Act on Deployment of Low-Carbon Ammonia Technologies
Authors: Chyong Chi Kong , Italiani Eduardo , Kazantzis Nikolaos
Published: October 2023

Building on the stochastic economic analysis of the plant-level ammonia production (AP) model, this study comprehensively considers key low-carbon AP pathways - steam methane reforming with carbon capture and storage (CCS), biomass gasification (BH2S), and electrolysis (AEC) - under multiple policy frameworks – subsidies, carbon pricing, renewable hydrogen rules. CCS and BH2S demonstrate strong economic potential under the Inflation Reduction Act due to cost-effectiveness and limited public support requirements. In contrast, AEC faces economic challenges due to high costs and low efficiency. To efficiently decarbonize AP, policymakers and academia should prioritize (i) adapting Haber-Bosch (HB) processes for variable bioenergy quality, (ii) ensuring safe CO2 transport and storage while mitigating CCS value chain risks, (iii) supporting R&D to reduce costs and enhance efficiency in flexible HB, renewable energy, and storage technologies, and (iv) establishing a technologically neutral policy framework that considers dynamic cost reductions and interactions between policy instruments and technologies.
Characterising Support and Care Assistants in Formal Hospital Settings: A Scoping Review
Authors: Kagonya Vincent A. , Onyango Onesmus , Maina Michuki , Gathara David , English Mike , Imam Abdulazeez
Published: October 2023

Background: A 15 million health workforce shortage is still experienced globally leading to a sub-optimal healthcare worker-to-population ratio in most countries. The use of low-skilled care assistants has been suggested as a cost-saving human resource for health strategy that can significantly reduce the risks of rationed, delayed, or missed care. However, the characterisation, role assignment, regulation, and clinical governance mechanisms for unlicensed assistive workforce remain unclear or inconsistent. The purpose of this study was to map and collate evidence of how care assistants are labelled, utilised, regulated, and managed in formal hospital settings as well as their impact on patient care.
Methods: We conducted a scoping review of literature from PUBMED, CINAHL, PsychINFO, EMBASE, Web of Science, Scopus, and Google Scholar. Searches and eligibility screening were conducted using the Participants-Context-Concepts framework. Thematic content analysis guided the synthesis of the findings.
Results: 73 records from a total of 15 countries were included in the final full-text review and synthesis. A majority (78%) of these sources were from high-income countries. Many titles are used to describe care assistants, and these vary within and across countries. On ascribed roles, care assistants perform direct patient care, housekeeping, clerical and documentation, portering, patient flow management, ordering of laboratory tests, emergency response and first aid duties. Additional extended roles that require higher competency levels exist in the United States, Australia, and Canada. There is a mixture of both positive and negative sentiments on their impact on patient care or nurses’ perception and experiences. Clinical and organisational governance mechanisms vary substantially across the 15 countries. Licensure, regulatory mechanisms, and task-shifting policies are largely absent or not reported in these countries.
Conclusion: The nomenclature used to describe care assistants and the tasks they perform vary substantially within countries and across healthcare systems. There is, therefore, a needto review and update the international and national classification of occupations for clarity and more meaningful nomenclature for care assistants. Also, the association between care assistants and care outcomes or nurses’ experience remains unclear. Further, there is a dearth of empirical evidence on this topic from low and middle-income countries.
A study on the diagnosis of lung cancer using flexible fiberoptic endoscopy
Authors: Alhourani Ali , Salameh Samer , alomari Mohamed nada
Published: October 2023

Objective: Describe the main pathological forms of lung cancer in the large airways and present their endoscopic aspects in a group of patients with lung cancer.
Methods and materials: A cross-sectional study on 38 patients from Al-Mowasat University Hospital. A paper questionnaire was used through which patient information was collected. The data was entered into the AMSL program and analyzed by the researchers in order to reach the goal of the study.
Results: The percentage of males was 38.2% and the percentage of females was 15.8%, and the average age of the patients was 64.21 ± 3.699 years. More than two-thirds of the patients lived in restricted areas, and the percentage of smokers was 55.3%. The average age of patients with non-small cell lung cancer was 65.47 ± 2.623, and the average age of the patients Those with small cell lung cancer: 59.5 ± 3.423, statistical significance = 0.000, and the incidence of SCC is the most common, at 50%.
Conclusion: There are significant differences in the ages of patients depending on the type of lung cancer, there is no statistically significant relationship between gender and the type of lung cancer, there is no significant relationship between the type of lung cancer and smoking, and there is no statistically significant relationship between residence and the type of lung cancer in patients.
Reduced Arctic Ocean CO2 uptake due to coastal permafrost erosion
Authors: Nielsen David Marcolino , Chegini Fatemeh , Maerz Joeran , Brune Sebastian , Dobrynin Mikhail , Baehr Johanna , Brovkin Victor , Ilyina Tatiana
Published: October 2023

Arctic coastal permafrost erosion is projected to increase by a factor of 2-3 by 2100. However, organic matter (OM) fluxes from the coastal permafrost into the ocean have not been considered in Earth system models (ESMs) so far. Here, we represent coastal permafrost erosion in an ESM, and perform simulations with varying permafrost OM properties, such as sinking fraction and nutrient content. We find that coastal erosion reduces the Arctic Ocean CO2 uptake from the atmosphere in all simulations: by 4.6-13.2 TgC/year by 2100, which is about 7-14% of the Inner Arctic uptake. We show that coastal permafrost erosion exerts a positive biogeochemical feedback on climate, increasing atmospheric CO2 by 1-2 TgC/year per degree-C of increase in global surface air temperature. We thereby recommend that coastal permafrost erosion be considered in future climate projections.
Indian Summer Monsoon Simulations In Successive Generations Of The NCAR Community Atmosphere Model
Authors: Kumar Ravi , Pathak Raju , Sahany Sandeep , Mishra Saroj K.
Published: October 2023

Four generations of the NCAR Community Atmosphere Model (CAM-3, 4, 5, and 6) are evaluated for the Indian summer monsoon (ISM) simulations. Total precipitation simulated by successive versions of CAM is overestimated over the western equatorial Indian Ocean (EIO), Arabian Sea, and Western Ghats (WGs), and underestimated over the eastern EIO, Bay of Bengal (BoB), and Indo-Burmese mountains, due to overestimated convective and underestimated large-scale precipitation, respectively. Overestimation of total precipitation over the Himalayan region is increased in successive CAM variants, primarily through enhanced large-scale precipitation. Improvement in total precipitation simulation over BoB is found in successive CAM variants, with the largest improvement in CAM6. The frequency of total precipitation is overestimated for low precipitation rates and underestimated for high precipitation rates in CAM variants, except in CAM4 for high precipitation rates. The subtropical westerly and tropical easterly jets are better simulated in CAM5-6 than CAM3-4 (highly overestimated). The easterly shear of zonal wind during the peak monsoon is highly overestimated in all CAM variants. The monsoon low-level jet over AS and peninsular India is overestimated in all CAM variants with the largest overestimation in CAM6, resulting in increased precipitation over WGs and peninsular India. We find the large underestimation in a tropical easterly jet over peninsular India and EIO in CAM3 to have improved in the successive versions. In addition, overestimation of the strength of the subtropical westerly jet and the Tibetan anticyclone seen in CAM3 has improved in successive variants of CAM. We find improvements in monsoon intra-seasonal oscillation (MISO) and associated internal dynamics and the east-west and north-south heat source in successive variants of CAM. Overall, we find many improvements in the simulation of ISM precipitation and its associated dynamics in successive variants of CAM, however, there still remain some important biases (e.g., eastward component of MISO, monsoon low-level jet, excessive precipitation over Himalayan foothills, early monsoon onset, etc.) that need to be alleviated for more realistic ISM simulations in future versions of CAM.
Ludwig von Alvensleben, 1800–1868
Authors: Schreiber Michael
Published: October 2023

Ludwig von Alvensleben war einer der produktivsten Übersetzer des 19. Jahrhunderts. Er gilt daher heute manchen als Prototyp des nur auf Quantität bedachten "Fabrikübersetzers". Dass die Zeitgenossen seine Übersetzungstätigkeit nicht ganz so negativ einschätzten, lässt sich an seinerzeit veröffentlichten Rezensionen erkennen. Der Blick in die Bibliographie macht allerdings auch deutlich, dass sich seine Übersetzungen im Literaturbetrieb bzw. am Buchmarkt nicht lange halten konnten.
Optimal mass variables for semivisible jets
Authors: Pedro Kevin , Shyamsundar Prasanth
Published: October 2023

Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with standard model hadrons in the form of semivisible jets. Classical mass reconstruction techniques may not be optimal for these unusual topologies, in which the missing transverse momentum comes from massive particles and has a nontrivial relationship to the visible jet momentum. We apply the artificial event variable network, a semisupervised, interpretable machine learning technique that uses an information bottleneck, to derive superior mass reconstruction functions for several cases of resonant semivisible jet production. We demonstrate that the technique can extrapolate to unknown signal model parameter values. We further demonstrate the viability of conducting an actual search for new physics using this method, by applying the learned functions to standard model background events from quantum chromodynamics.
Determinants of Indonesian Gen Z’s purchase behavior on online travel platforms: Extending UTAUT model
Authors: Dian Octaviani Reni , Sucherly  , Prabowo Harjanto , Sari Diana
Published: October 2023

Understanding Gen Z’s purchase behavior in online travel agents is essential to effectively engage and meet the unique preferences of this generation, fostering long-term loyalty and satisfaction. Utilizing the unified theory of acceptance and use of technology (UTAUT) as the theoretical foundation, this study aims to analyze the impact of performance expectancy, effort expectancy, social influence, facilitating condition, and trust on purchase decision of flight tickets through online travel agent platforms. The data were collected through an online survey of 253 Gen Z users of online travel agent applications in Indonesia, such as Traveloka, Tiket.com, Pegipegi.com, Agoda, and Booking.com. The study employed PLS-SEM to test the hypotheses. The results indicate that performance expectancy, effort expectancy, social influence, and facilitating conditions influence trust (t-value 1.645, p-value < 0.05). Further, performance expectancy, effort expectancy, and facilitating conditions influence purchase decisions (t-value 1.645, p-value < 0.05). However, social influence does not significantly affect purchase decisions (t-value 1.041, p-value > 0.05). The analysis also shows that trust fully mediates the relationship between social influence and purchase decisions, while no mediating effect is identified in the relationship between effort expectancy and purchase decisions. By investigating the key factors contributing to Gen Z’s buying behavior in online travel agent platforms, this paper provides valuable insights for online travel businesses to effectively engage and cater to Gen Z’s unique needs and preferences.
Milk ingredients are the future of dairy production
Authors: Melnikova E. , Rudnichenko E. , Kuznetsova S.
Published: October 2023

The new area of milk processing is discussed in the article – the functional technological ingredient obtaining. Much attention is paid to protein components, their composition, physical and chemical properties and fields of application.
Metamorphosis of the Public Administration Paradigm and the New Qualification Profile of Civil Servants
Authors: Gershanok Aleksandr , Lomonosova Iana
Published: October 2023

In conditions of rapidly changing external environment, increasing international tension, and more complicated public policy, the theory of public administration must quickly adapt. Traditional models of public administration based on strict hierarchical subordination are extremely ineffective, which necessitates their radical rethinking and redesign. These changes affect the requirements for the qualification profile of civil servants. The key trend is the rejection of team management methods in favor of methods based on participation, involvement, effective motivation. The purpose of the study is to analyze the theory of public administration basic concepts (models); to establish the functions and tasks of civil servants and arrange them; to identify key trends in the society development that affect the qualification profile of civil servants. The research is based on scientific works, statistical data of national and foreign agencies and institutes, empirical data. Scientific methods: literature analysis, comparative analysis, synthesis, generalization, observation; methods, used in the article are of scientific abstraction and abstract thinking. The novelty of the research lies in the conclusion that the paradigm of public administration shifts towards social partnership and decentralization of public administration, increasing the responsibility of civil servants.
Impact of Municipal Districts’ Budgetary Provision on the Sustainability of the Agro-Industrial Complex Development in Kemerovo region – Kuzbass
Authors: Arzumanyan Misak
Published: October 2023

The article proposes and implements the quantitative assessment method for measuring the connection between sustainability of the agro-industrial complex development and the municipal districts’ budgetary provision in the Kemerovo region – Kuzbass. The goal is to determine the level of budget indicators impact on the sustainability of the agro-industrial complex development. The budget indicators are mathematically compared with the indicators of 4 fundamental components of sustainable development of the agro-industrial complex. The method is intended for researchers solving the problems of regulating socio-economic development at the local level and at the level of the Federation subject; for authorities of the Russian Federation subjects and municipal authorities for making managerial decisions. The results can serve as a foundation for assessing the level of the agro-industrial complex sustainable development in the municipal districts of the region.
Consumer Practice and Population Sentiment in Conditions of 2020–2022 Instability (regional aspect)
Authors: Belehova Galina
Published: October 2023

Various crises are integral for social development. Primarily crises manifest themselves in income and consumption changes, which makes consumer behavior and population sentiment studies necessary in unstable socio-economic conditions. The purpose of the study is to analyze consumer practice and population sentiment trends in the Vologda Oblast during the socio-economic changes of 2020–2022. The author determines that consumer practices of the region’s population hardly change in quantitative and qualitative terms, consumer sentiments also appear stable. Population’s assessment of capability for large purchases, car and housing purchases, savings remains neutral. However, the persistency of neutral consumer practices and sentiments levels suggests that the residents of the region do not expect positive changes in the economic life of their family and the country in the near future.
System of Long-Term Care for the Disabled and Elderly Citizens in the Stavropol Krai: Assessment of the Social Performance
Authors: Samofatova Kseniya
Published: October 2023

The system of long-term care for the disabled and elderly people has to attract investments and produce a social effect. The purpose of the study is to assess the social performance of the of long-term care system for the disabled and elderly citizens in the Stavropol Krai on the basis of the original author’s approach. Methods: description and literature analysis, analytical and statistical methods of data processing, indirect anonymous survey. The author analyzes the scientific literature to form the conceptual and categorical apparatus. The survey uses multi-stage typological sampling. The indirect survey involved 500 respondents; the expert survey – 20 experts in the field of social services and long-term care. The research shows that the system of long-term care for the disabled and elderly people is a priority at the federal and regional levels and has a high social performance. The practical significance of this study lies in the development and implementation of the original methodology for assessing the social performance of the long-term care system.
From digital twin paradigm to digital water services
Authors: Gino Ciliberti Francesco , Berardi Luigi , Laucelli Daniele Biagio , David Ariza Andres , Vanessa Enriquez Laura , Giustolisi Orazio
Published: October 2023

In the context of water distribution networks (WDNs), researchers and technicians are actively working on new ways to transition into the digital era. They are focusing on creating standardized methods that fit the unique characteristics of these systems, with a strong emphasis on developing customized digital twins. This involves combining advanced hydraulic modeling with advanced data-driven techniques like artificial intelligence, machine learning, and deep learning. This paper begins by giving a detailed overview of the important progress that has led to this digital transformation. It highlights the potential to create interconnected digital water services (DWSs) that can support all aspects of managing, planning, and designing WDNs. This approach introduces standardized procedures that allow a continuous improvement of the digital representation of these networks. Additionally, technicians benefit from DWSs developed as QGIS software plugins. These services strategically enhance their understanding of technical decisions, improving logical reasoning, consistency, scalability, integrability, efficiency, effectiveness, and adaptability for both short-term and long-term management tasks. Notably, the framework remains adaptable, ready to embrace upcoming technological advancements and data gathering capabilities, all while keeping end-users central in shaping these technical developments.
Analysis and risk assessment of pharmaceutical residues in fish from three water bodies in Ghana
Authors: Duncan Albert Ebo , Adokoh Christian , Osei-Marfo Martha , Barnie Samuel , Sakyi Aboagye George , Adjei Josephe
Published: October 2023

Illegal mining has overshadowed pharmaceutical pollution even though exposure to pharmaceutical waste is high. Consumption of fish potentially polluted with pharmaceuticals from the rivers continues with little concern or potential threat it poses. In the present study, the residues of one antibiotic (Chloramphenicol), five hormones (progesterone, 17-beta Estradiol, Estrone, 17a-Ethynylestradiol, and one), three environmental contaminants (4-para-nonylphenol, 4-tert-octylphenol, and Bisphenol A), one barbiturate (Primidone) and one analgesic (Diclofenac sodium salt), were investigated from fish samples from the rivers Pra, Narkwa, and the Volta. The results show a high concentration of drugs in River Pra in comparison to those in Rivers Narkwa and Volta. The hazard quotients (HQs) for the environmental contaminants were all above 1, except Bisphenol A. Furthermore, the HQs from this study suggest that consumers of fish from any of the three rivers stand a hazard risk of Chloramphenicol (19), 17a-Ethynylestradiol (4), Estrone (1.366), Diclofenac sodium salt (3.29), Progesterone (4.598), 4-tert-octylphenol (87.2), and 4-para-nonylphenol (7.252), but negligible risk against E2 (0.687), Primidone (0.014), Testosterone (0.16), and Bisphenol A (0.642). Of the fish species studied, the highest concentration of all pharmaceuticals put together is found in Clarias gariepinus, Labeo senegalensis, and Chrysichthys nigrodigitatus in that order.
Model parameter sensitivity and identifiability for urban river water quality: impact of domestic wastewater discharges from on-site treatment facilities
Authors: Inagaki Yoshihiko , Habineza Elias , Dang Hieu Minh , Makwinja Rodgers , Komori Masahito , Sakakibara Yutaka
Published: October 2023

River water quality degradation is a risk to human health. Hence, many water quality models have been developed to predict the future states of water bodies and understand how the current water treatment systems will respond to future pollution loads and climatic drivers. A Japanese river was evaluated with the River Water Quality Model No.1 (RWQM1), and parameter sensitivity and identifiability analyses were executed on the model output using parameter sensitivity ranking, collinearity index, and Fisher Information Matrix-derived criterion. Among RWQM1 kinetic parameters, those related to hydrolysis, growth of aerobicheterotrophs, and first-stage nitrifiers were the most influential. Reactive soluble organic substances included in untreated gray waters, in addition to a prevalence ratio of the most advanced on-site treatment facility, strongly contributed to the model output variability. A remediation analysis revealed that a renewal to the most advanced on-site treatment facility by 20% increment was almost equivalent to the 70% decrease in the effluent concentration from an on-site treatment facility producing the highest pollutant load in terms of a BOD concentration decrease in the stream. This study provided baseline data assisting in policy implementation regarding the management of effluents from on-site treatment facilities.
FINAL REPORT FROM THE FORUM ON NURSING PRACTICE REGULATION IN THE REGION OF THE AMERICAS MARCH 15-16, 2023
Authors: Cassiani Silvia Helena De Bortoli , Dias Bruna Moreno , Durães Mônica Diniz , Almeida Bruno Guimarães de , Palha Pedro Fredemir , Ventura Carla Aparecida Arena , Gir Elucir , Gazotti Juliana , Santos Betânia Maria Pereira dos , Gomes Antônio Marcos Freire , Cunha Isabel Cristina Kowal Olm , Lourenção Luciano Garcia , Freire Neyson Pinheiro
Published: October 2023

There are nearly 7 million nursing professionals in the Region of the Americas, representing more than 56% of human health resources. The regulation of professional practices promotes and protects professional integrity, ensuring professionals are competent and well qualified. The Forum on Nursing Practice Regulation in the Region of the Americas aimed to present the regulatory frameworks for the professional practice of nursing; discuss strategic actions to support professional regulatory bodies; analyze requirements for licensing and renovating licenses; and share successful experiences in nursing regulation. The Forum counted on the participation of 83 guests in-person, with representatives from 17 countries from Latin America and the Caribbean. The COFENplay platform registered the participation of 6,906 spectators. The debates in the event led to the proposal of the following recommendations: promote a national discussion with key-actors, including the Ministries of Health, Education, and Work and Employment, to advance regulation in the countries; recommend an intersectoral articulation with the topic of Human Health Resource regulation; generate a common base for the identification of information on regulation; and broaden the research about these topics, as well as the ability to generate and analyze data.
Report on the 17th International Scientific Conference in the “Humanistic Ecology” Series: “Environmental Philosophy and Ethics in the Face of the Ecological Crisis” (Warsaw, 20-21 September 2023)
Authors: Sadowski Ryszad F.
Published: October 2023

SEeB does not provide abstracts for reports.
Insight to Biofabrication of Liver Microtissues for Disease Modeling: Challenges and Opportunities
Authors: Dortaj Hengameh , Azarpira Negar , Pakbaz Sara
Published: October 2023

:

In the last decade, liver diseases with high mortality rates have become one of the most
important health problems in the world. Organ transplantation is currently considered the most effective
treatment for compensatory liver failure. An increasing number of patients and shortage of
donors has led to the attention of reconstructive medicine methods researchers. The biggest challenge
in the development of drugs effective in chronic liver disease is the lack of a suitable preclinical
model that can mimic the microenvironment of liver problems. Organoid technology is a
rapidly evolving field that enables researchers to reconstruct, evaluate, and manipulate intricate biological
processes in vitro. These systems provide a biomimetic model for studying the intercellular
interactions necessary for proper organ function and architecture in vivo. Liver organoids,
formed by the self-assembly of hepatocytes, are microtissues and can exhibit specific liver characteristics
for a long time in vitro. Hepatic organoids are identified as an impressive tool for evaluating
potential cures and modeling liver diseases. Modeling various liver diseases, including tumors,
fibrosis, non-alcoholic fatty liver, etc., allows the study of the effects of various drugs on these
diseases in personalized medicine. Here, we summarize the literature relating to the hepatic
stem cell microenvironment and the formation of liver Organoids
Three Decades of Valproate: A Current Model for Studying Autism
Spectrum Disorder
Authors: Zarate-Lopez David , Torres-Chávez Ana Laura , Gálvez-Contreras Alma Yadira , Gonzalez-Perez Oscar
Published: October 2023

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increased prevalence
and incidence in recent decades. Its etiology remains largely unclear, but it seems to involve a
strong genetic component and environmental factors that, in turn, induce epigenetic changes during
embryonic and postnatal brain development. In recent decades, clinical studies have shown that inutero
exposure to valproic acid (VPA), a commonly prescribed antiepileptic drug, is an environmental
factor associated with an increased risk of ASD. Subsequently, prenatal VPA exposure in rodents has
been established as a reliable translational model to study the pathophysiology of ASD, which has
helped demonstrate neurobiological changes in rodents, non-human primates, and brain organoids
from human pluripotent stem cells. This evidence supports the notion that prenatal VPA exposure is a
valid and current model to replicate an idiopathic ASD-like disorder in experimental animals. This review
summarizes and describes the current features reported with this animal model of autism and the
main neurobiological findings and correlates that help elucidate the pathophysiology of ASD. Finally,
we discuss the general framework of the VPA model in comparison to other environmental and genetic
ASD models.
Estudio simulación esfuerzos en acero AISI/SAE 1045 por medio modelación en SolidWorks
Authors: García Castellanos Carlos Javier
Published: October 2023

The study of the mechanical properties of materials is important for the selection and implementation of these at the engineering level, which are carried out with destructive tests such as tension testing, topics that are addressed in the subject of Materials Strength. Process that can be simplified using simulation analysis methods carried out using 3D design software such as SolidWorks, to validate the behavior of the materials and thus be able to optimize the design of the components taking into account the parameters of characterization of materials based on the respective technical standards. For which the analysis of the AISI/SAE 1045 steel is proposed, carried out both analytically and by simulation in the software, where through the analysis of the data obtained quantitatively it is possible to demonstrate the equivalence of the results obtained in both cases.
Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study
Authors: Yang Liuyang , Zhang Ting , Han Xuan , Yang Jiao , Sun Yanxia , Ma Libing , Chen Jialong , Li Yanming , Lai Shengjie , Li Wei , Feng Luzhao , Yang Weizhong
Published: October 2023

Background

Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging respiratory infectious diseases like influenza and COVID-19, especially when reported case data may not fully reflect the actual epidemic curve.

Objective

This study aimed to develop a predictive model for influenza outbreaks by combining Baidu search query data with traditional virological surveillance data. The goal was to improve early detection and preparedness for influenza outbreaks in both northern and southern China, providing evidence for supplementing modern intelligence epidemic surveillance methods.

Methods

We collected virological data from the National Influenza Surveillance Network and Baidu search query data from January 2011 to July 2018, totaling 3,691,865 and 1,563,361 respective samples. Relevant search terms related to influenza were identified and analyzed for their correlation with influenza-positive rates using Pearson correlation analysis. A distributed lag nonlinear model was used to assess the lag correlation of the search terms with influenza activity. Subsequently, a predictive model based on the gated recurrent unit and multiple attention mechanisms was developed to forecast the influenza-positive trend.

Results

This study revealed a high correlation between specific Baidu search terms and influenza-positive rates in both northern and southern China, except for 1 term. The search terms were categorized into 4 groups: essential facts on influenza, influenza symptoms, influenza treatment and medicine, and influenza prevention, all of which showed correlation with the influenza-positive rate. The influenza prevention and influenza symptom groups had a lag correlation of 1.4-3.2 and 5.0-8.0 days, respectively. The Baidu search terms could help predict the influenza-positive rate 14-22 days in advance in southern China but interfered with influenza surveillance in northern China.

Conclusions

Complementing traditional disease surveillance systems with information from web-based data sources can aid in detecting warning signs of influenza outbreaks earlier. However, supplementation of modern surveillance with search engine information should be approached cautiously. This approach provides valuable insights for digital epidemiology and has the potential for broader application in respiratory infectious disease surveillance. Further research should explore the optimization and customization of search terms for different regions and languages to improve the accuracy of influenza prediction models.
Psychological Resilience Factors and Their Association With Weekly Stressor Reactivity During the COVID-19 Outbreak in Europe: Prospective Longitudinal Study
Authors: Bögemann Sophie A , Puhlmann Lara M C , Wackerhagen Carolin , Zerban Matthias , Riepenhausen Antje , Köber Göran , Yuen Kenneth S L , Pooseh Shakoor , Marciniak Marta A , Reppmann Zala , Uściƚko Aleksandra , Weermeijer Jeroen , Lenferink Dionne B , Mituniewicz Julian , Robak Natalia , Donner Nina C , Mestdagh Merijn , Verdonck Stijn , van Dick Rolf , Kleim Birgit , Lieb Klaus , van Leeuwen Judith M C , Kobylińska Dorota , Myin-Germeys Inez , Walter Henrik , Tüscher Oliver , Hermans Erno J , Veer Ilya M , Kalisch Raffael
Published: October 2023

Background

Cross-sectional relationships between psychosocial resilience factors (RFs) and resilience, operationalized as the outcome of low mental health reactivity to stressor exposure (low “stressor reactivity” [SR]), were reported during the first wave of the COVID-19 pandemic in 2020.

Objective

Extending these findings, we here examined prospective relationships and weekly dynamics between the same RFs and SR in a longitudinal sample during the aftermath of the first wave in several European countries.

Methods

Over 5 weeks of app-based assessments, participants reported weekly stressor exposure, mental health problems, RFs, and demographic data in 1 of 6 different languages. As (partly) preregistered, hypotheses were tested cross-sectionally at baseline (N=558), and longitudinally (n=200), using mixed effects models and mediation analyses.

Results

RFs at baseline, including positive appraisal style (PAS), optimism (OPT), general self-efficacy (GSE), perceived good stress recovery (REC), and perceived social support (PSS), were negatively associated with SR scores, not only cross-sectionally (baseline SR scores; all P<.001) but also prospectively (average SR scores across subsequent weeks; positive appraisal (PA), P=.008; OPT, P<.001; GSE, P=.01; REC, P<.001; and PSS, P=.002). In both associations, PAS mediated the effects of PSS on SR (cross-sectionally: 95% CI –0.064 to –0.013; prospectively: 95% CI –0.074 to –0.0008). In the analyses of weekly RF-SR dynamics, the RFs PA of stressors generally and specifically related to the COVID-19 pandemic, and GSE were negatively associated with SR in a contemporaneous fashion (PA, P<.001; PAC,P=.03; and GSE, P<.001), but not in a lagged fashion (PA, P=.36; PAC, P=.52; and GSE, P=.06).

Conclusions

We identified psychological RFs that prospectively predict resilience and cofluctuate with weekly SR within individuals. These prospective results endorse that the previously reported RF-SR associations do not exclusively reflect mood congruency or other temporal bias effects. We further confirm the important role of PA in resilience.
Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study (Preprint)
Authors: Yang Liuyang , Zhang Ting , Han Xuan , Yang Jiao , Sun Yanxia , Ma Libing , Chen Jialong , Li Yanming , Lai Shengjie , Li Wei , Feng Luzhao , Yang Weizhong
Published: October 2023

BACKGROUND

Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging respiratory infectious diseases like influenza and COVID-19, especially when reported case data may not fully reflect the actual epidemic curve.

OBJECTIVE

This study aimed to develop a predictive model for influenza outbreaks by combining Baidu search query data with traditional virological surveillance data. The goal was to improve early detection and preparedness for influenza outbreaks in both northern and southern China, providing evidence for supplementing modern intelligence epidemic surveillance methods.

METHODS

We collected virological data from the National Influenza Surveillance Network and Baidu search query data from January 2011 to July 2018, totaling 3,691,865 and 1,563,361 respective samples. Relevant search terms related to influenza were identified and analyzed for their correlation with influenza-positive rates using Pearson correlation analysis. A distributed lag nonlinear model was used to assess the lag correlation of the search terms with influenza activity. Subsequently, a predictive model based on the gated recurrent unit and multiple attention mechanisms was developed to forecast the influenza-positive trend.

RESULTS

This study revealed a high correlation between specific Baidu search terms and influenza-positive rates in both northern and southern China, except for 1 term. The search terms were categorized into 4 groups: essential facts on influenza, influenza symptoms, influenza treatment and medicine, and influenza prevention, all of which showed correlation with the influenza-positive rate. The influenza prevention and influenza symptom groups had a lag correlation of 1.4-3.2 and 5.0-8.0 days, respectively. The Baidu search terms could help predict the influenza-positive rate 14-22 days in advance in southern China but interfered with influenza surveillance in northern China.

CONCLUSIONS

Complementing traditional disease surveillance systems with information from web-based data sources can aid in detecting warning signs of influenza outbreaks earlier. However, supplementation of modern surveillance with search engine information should be approached cautiously. This approach provides valuable insights for digital epidemiology and has the potential for broader application in respiratory infectious disease surveillance. Further research should explore the optimization and customization of search terms for different regions and languages to improve the accuracy of influenza prediction models.