bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of criteria for choosing drug treatment strategies in allergic rhinitis
Authors: Grzegorzewski Damian , Sobczak Marharyta , Tołkacz Michał , Pawliczak Rafał
Published: October 2024

Background

Allergic rhinitis (AR) is the most common type of rhinitis, the treatment of which relies on relieving symptoms. Therefore, we aimed to assess the criteria that influence doctors’ decision-making in the process of drug selection for the treatment of allergic rhinitis based on quantitative, qualitative, and cost analyses.

Methods

We conducted a survey study with the participation of 300 allergologists. A self-developed questionnaire was presented during a computer-assisted telephone interview (CATI) according to

standard procedures. The contingency table underwent statistical analysis using the chi-square test with Cramer’s V. Results were considered statistically significant at p < 0.05.

Results

Our analyses showed that doctors most often prescribe intranasal glucocorticoids and oral antihistamines to treat allergic rhinitis in patients of all ages. The most common factor that affects the decision-making related to AR treatment was the efficiency of the drug. We found a significant relationship between factors and the main workplace (X-squared = 122.81, df = 90, p-value = 0.0123, Cramer’s V = 0.1787216), as well as voivodeship of the main workplace (X-squared = 440.75, df = 270, p-value = 2.378e-10, Cramer’s V = 0.1954731). In our study, respondents claimed that patients are willing to pay 31–50 PLN (∼€7- €11) monthly for the treatment of mild and moderate forms of AR, while they were willing to pay 51–100 PLN (∼€11–€22) for treatment of the severe AR form.

Conclusion

Our study confirms that the management of AR should be focused on the patient. One of the most important factors in choosing a drug is its effectiveness. Moreover, an important factor in the effective treatment of AR is the financial issue; as shown in our analysis, AR treatment costs can be a significant burden, especially for less wealthy citizens in Poland.
PBPK-based translation from preclinical species to humans for the full-size IgG therapeutic efalizumab
Authors: Franz Maria , Jairam Ravi Kumar , Kuepfer Lars , Hanke Nina
Published: October 2024

Introduction

Animal models play a vital role in pharmaceutical research and development by supporting the planning and design of later clinical studies. To improve confidence and reliability of first in human dose estimates it is essential to assess the comparability of animal studies with the human situation. In the context of large molecules, it is particularly important to evaluate the cross-species-translatability of parameters related to neonatal fragment crystallizable receptor (FcRn) binding and target mediated drug disposition (TMDD), as they greatly influence distribution and disposition of proteins in the body of an organism.

Methods

Plasma pharmacokinetic data of the therapeutic protein efalizumab were obtained from literature. Physiologically based pharmacokinetic (PBPK) models were built for three different species (rabbit, non-human primate (NHP), human). Target binding was included in the NHP and human models. The assumption of similar target turnover and target-binding in NHP and human was explored, to gain insights into how these parameters might be translated between species.

Results

Efalizumab PBPK models were successfully developed for three species and concentration-time-profiles could be described appropriately across different intravenously administered doses. The final NHP and human models feature a common set of parameters for target turnover and drug-target-complex internalization, as well as comparable target-binding parameters. Our analyses show that different parameter values for FcRn affinity are crucial to accurately describe the concentration-time profiles.

Discussion

Based on the available data in rabbits, NHP and humans, parameters for FcRn affinity cannot be translated between species, but parameters related to target mediated drug disposition can be translated from NHP to human. The inclusion of additional pharmacokinetic (PK) data including different efalizumab doses would further support and confirm our findings on identifying TMDD and, thus, binding kinetics of efalizumab in NHPs. Furthermore, we suggest that information on target expression and internalization rates could make it possible to develop comprehensive human PBPK models with minimal animal testing. In this project, we compared the pharmacokinetics of a therapeutic protein in rabbit, NHP and human using an open PBPK modeling platform (Open Systems Pharmacology Suite, http://www.open-systems-pharmacology.org). Our findings could support similar translatory studies for first in human dose predictions in the future.
Assessment of ferroptosis as a promising candidate for metastatic uveal melanoma treatment and prognostication
Authors: Swords Ellie , Kennedy Breandán N. , Tonelotto Valentina
Published: October 2024

Uveal melanoma (UM) is the most common primary intraocular tumour in adults. Local resection, radiation therapy, and enucleation are the current first-line, primary UM treatments. However, regardless of the treatment received, around 50% of UM patients will develop metastatic disease within five to 7 years. In the largest published series of unselected patients with metastatic UM (mUM), the median survival time after diagnosis of metastasis was 3.6 months, with less than 1% of patients surviving beyond 5 years. Approved drugs for treatment of mUM include systemic treatment with tebentafusp-tebn or isolated hepatic perfusion (IHP) with melphalan. However, these drugs are only available to a subset of patients and improve survival by only a few months, highlighting the urgent need for new mUM treatments. Accurately predicting which patients are at high risk for metastases is also crucial. Researchers are developing gene expression signatures in primary UM to create reliable prognostic models aimed at improving patient follow-up and treatment strategies. In this review we discuss the evidence supporting ferroptosis, a non-apoptotic form of cell death, as a potential novel treatment target and prognosticator for UM.
ASC speck serum concentrations, a component of sterile cellular inflammation, are associated with individual cardiopulmonary capacity
Authors: Kogel Alexander , Voßhage Nell , Behzadi Amirhossein , Laufs Ulrich , Fikenzer Sven
Published: October 2024

Aims

Exercise-induced cellular stress and sterile inflammation are of increasing interest. ASC specks are a component of the intracellular NLRP3-inflammasome and can be released into the blood. For example, serum ASC specks are increased after marathon running. We therefore tested whether ASC specks are potentially associated with the individual response to physical training and cardiopulmonary capacity.

Methods

We performed a prospective study in 45 healthy athletes. Blood samples were taken before and after cardiopulmonary exercise testing (CPET). ASC speck concentrations were quantitated using flow cytometry.

Results

Baseline ASC speck levels correlated with clinical parameters of body composition (height, weight, BMI) and parameters of cardiopulmonary performance (peak VO2, peak oxygen pulse, heart rate after exercise). Athletes with lowest baseline ASC speck concentrations have a significantly lower BMI (22.0 ± 1.8 vs. 24.9 ± 1.6 kg/m2), higher heart rate at rest (72 ± 10 vs. 58 ± 10 beats/min), lower peak VO2 (2692 ± 629 vs. 3404 ± 747 mL/min) and lower peak oxygen pulse (15.6 ± 3.4 vs. 20.7 ± 3.5 mL/heart rate). Overall, ASC speck concentrations showed no significant change after CPET (7.0 ± 4.5 vs. 8.0 ± 5.4 ASC specks/µL, p = 0.3). However, subgroup analysis revealed a significant increase in circulating ASC specks in athletes with the lowest baseline values (2.37 ± 0.84 vs. 8.43 ± 7.52 ASC specks/µL, p < 0.05). Athletes with an increase in ASC speck concentrations in response to CPET had a lower peak oxygen pulse compared to those with a decrease (17.1 ± 4.2 vs. 19.8 ± 4.1, p < 0.05).

Conclusion

Low ASC speck baseline values as well as an increase in response to exercise are associated with lower peak oxygen pulse in healthy athletes.
Transcriptional and genetic characteristic of chimera pea generation via double ethyl methanesulfonate-induced mutation revealed by transcription analysis
Authors: Hu Jinglei , Liu Mingxia , Wang Dongxia , Liang Yunlong , Zong Yuan , Li Yun , Cao Dong , Liu Baolong
Published: October 2024

Ethyl methanesulfonate (EMS)-induced mutagenesis is a prominent method for generating plant mutants, often resulting in chimera plants; however, their transcriptional and genetic characteristic remain elusive. In this investigation, chimera pea (Pisum sativum L.) specimens, labeled GY1 and GY2, exhibiting a distinctive phenotype with yellow and green leaves were meticulously cultivated via sequential double EMS mutagenesis. The observed color disparity between the yellow and green leaves was attributed to a significant reduction in chlorophyll content coupled with heightened lutein levels in both chimeric variants. Transcriptome profiling revealed the enrichment of differentially expressed genes in both GY1 and GY2, specifically implicating Kyoto Encyclopedia of Genes and Genomes pathways linked to amino acid biosynthesis and ribosome development, alongside Gene Ontology (GO) biological processes linked with stress response mechanisms. Few structural genes associated with chlorophyll and lutein biosynthesis exhibited discernible differential expression. Despite these functional similarities, distinctive nuances were evident between specimens, with GY1 exhibiting enrichment in GO pathways related to chloroplast development and GY2 showing enrichment for ribosome development pathways. Single-nucleotide polymorphism (SNP) analysis uncovered a shared pool of 599 and 598 polymorphisms in the yellow and green leaves of GY1 and GY2, respectively, likely stemming from the initial EMS mutagenesis step. Further investigation revealed an increased number of unique SNPs in the yellow leaves following the second EMS application, whereas the green leaves exhibited sparse and unique SNP occurrences, suggestive of potential evasion from secondary mutagenesis. This inherent genetic variability underpins the mechanism underlying the formation of chimera plants. Predominant base mutations induced by EMS were characterized by G/A and C/T transitions, constituting 74.1% of the total mutations, aligning with established EMS mutation induction paradigms. Notably, genes encoding the eukaryotic translation initiation factor eIIso4G and the ubiquitin ligase RKP, known to modulate leaf color in model plants, harbored two SNPs in the yellow leaves of both GY1 and GY2, implicating their putative role in the yellow leaf phenotype. Collectively, this study provides novel insights into the transcriptional and genetic characteristics of chimera plants via EMS-induced mutagenesis.
YOLO-ACT: an adaptive cross-layer integration method for apple leaf disease detection
Authors: Zhang Silu , Wang Jingzhe , Yang Kai , Guan Minglei
Published: October 2024

Apple is a significant economic crop in China, and leaf diseases represent a major challenge to its growth and yield. To enhance the efficiency of disease detection, this paper proposes an Adaptive Cross-layer Integration Method for apple leaf disease detection. This approach, built upon the YOLOv8s architecture, incorporates three novel modules specifically designed to improve detection accuracy and mitigate the impact of environmental factors. Furthermore, the proposed method addresses challenges arising from large feature discrepancies and similar disease characteristics, ultimately improving the model's overall detection performance. Experimental results show that the proposed method achieves a mean Average Precision (mAP) of 85.1% for apple leaf disease detection, outperforming the latest state-of-the-art YOLOv10s model by 2.2%. Compared to the baseline, the method yields a 2.8% increase in mAP, with improvements of 5.1%, 3.3%, and 2% in Average Precision, Recall, and mAP50-95, respectively. This method demonstrates superiority over other classic detection algorithms. Notably, the model exhibits optimal performance in detecting Alternaria leaf spot, frog eye leaf spot, gray spot, powdery mildew, and rust, achieving mAPs of 84.3%, 90.4%, 80.8%, 75.7%, and 92.0%, respectively. These results highlight the model’s ability to significantly reduce false negatives and false positives, thereby enhancing both detection and localization of diseases. This research offers a new theoretical foundation and direction for future advancements in apple leaf disease detection.
Genome-wide association study reveals the genetic basis of rice resistance to three herbicides
Authors: Xu Peizhou , Qin Yuhe , Ma Maosen , Liu Tengfei , Ruan Fenhua , Xue Le , Cao Jiying , Xiao Guizong , Chen Yun , Fu Hongyan , Zhou Gege , Xie Yonghua , Xia Duo
Published: October 2024

Crop resistance to herbicides is crucial for agricultural productivity and sustainability amidst escalating challenges of weed resistance. Uncovering herbicide resistant genes is particularly important for rice production. In this study, we tested the resistance to three commonly used herbicides: glufosinate, glyphosate and mesotrione of 421 diverse rice cultivars and employed genome-wide association studies (GWAS) to unravel the genetic underpinnings of resistance to these three herbicides in rice. We discovered that cultivated rice exhibited rich variation in resistance to the three herbicides, and the differences among subpopulations were significant. Six identified associations harboring candidate genes for resistance to these herbicides were significant. Among them, RGlu6 and RGly8 were the major QTL for resistance to glufosinate and glyphosate, respectively. The favorable alleles of RGlu6 and RGly8 were primarily present in japonica cultivars that originated from Europe, highlighting the geographic and genetic diversity of herbicide resistance and emphasizing the localized selection pressures in European rice varieties. Moreover, our findings might suggest that traditional target genes may not contain tolerant alleles in nature, and alternative mechanisms with novel loci associated with resistance may work. By mapping the genes for herbicide resistance, our results may help develop new strategies to combat the dual challenges on effective weed management and herbicide sustainability.
Theory of affective pragmatics under biolinguistics
Authors: Zhuo Li
Published: October 2024

This paper introduces a pioneering investigation into affective pragmatics through the perspective of Darwinian Biolinguistics, an interdisciplinary field at the nexus of biological and linguistic principles. Anchored in Darwin’s theory of evolution and the latest developments in neurobiology, this study delves into the influence of biological factors---especially those pertaining to the brain’s emotional processing on pragmatic communication. The research posits that human emotional responses, inherent in our biological constitution, profoundly influence the usage and interpretation of language in social interactions.
Mobile phone dependence among Chinese university students: the contribution of irrational beliefs and solitude
Authors: Kuang Xiaoxue , Kennedy Kerry John , Li Hui
Published: October 2024

This research aimed to explore the impact of selected psychological variables on mobile phone dependence among Chinese university students. Specifically, the study focused on the relationship between solitude and irrational beliefs on mobile phone dependence. The study included 2,888 university students from Guangdong, Southern China, and found that both irrational beliefs and solitude had significant direct effects on mobile phone dependence. The study also revealed that solitude mediated the relationship between irrational beliefs and mobile phone dependence. The results of this study indicate that psychosocial environments, including feelings of solitude and irrational beliefs, can influence mobile phone dependence among undergraduate students. Therefore, it is important to pay attention to these factors and their potential impact on student behavior, particularly when it comes to academic growth and development. Further research in this area may help identify effective strategies to address mobile phone dependence among university students and promote healthier psychosocial environments.
On dementia, duties, and daughters. An ethical analysis of healthcare professionals being confronted with conflicts regarding filial duties in informal dementia care
Authors: Dogan Vildan , Taneska Marija , Novotni Gabriela , Iloski Svetlana , Novotni Antoni , Dimitrova Vesna , Milutinović Miloš , Novotni Ljubisha , Weber Anne , Joksimoski Boban , Chorbev Ivan , Hasani Shpresa , Ivanovska Andrea , Grimmer Timo , Fischer Julia
Published: October 2024

Background

Existing literature on moral conflicts that healthcare professionals encounter in dementia care has explored, amongst others, issues related to autonomy, decision-making capacity, privacy, and more. Notably, conflicts related to healthcare professionals who support informal dementia caregiving and who are confronted with family members being overburdened with their care responsibly remains an underexplored topic in the current literature, particularly in the context of Low-and Middle-Income Countries. The present paper introduces such an encounter, presenting an ethical case analysis of a conflict that occurred during a larger research project conducted in North Macedonia.

Case to be studied

Due to the absence of formal care services that could have relieved an overburdened family caregiver, healthcare professionals felt compelled to reach out to the uninvolved adult daughters, requesting them to participate in their parents’ care. Wondering about whether their reaching out to the daughters might count as an attempt of pressure and undue interference, professionals conflicted over the appropriateness of their action. This paper follows up on their concern, ethically assessing the professionals’ action. To answer the question on whether the healthcare professionals acted appropriately or not, and to what extent, theories of filial duties are applied, embedding their action in the larger context of dementia care in North Macedonia.

Results and conclusion

It is argued that the lack of formal care services in North Macedonia is of utmost relevance to the conflict. Thus, the conclusion is that the ethical inappropriateness of the case is to be located not so much with the action of the healthcare professionals but with the state because of its failure to provide professional care services that allow healthcare professionals to take ethically sound actions to counteract overarching burdens that family members face when providing informal dementia care
Suicide deaths and substance use in Spain between 2010 and 2022
Authors: Flórez Gerardo , Espandian Ashkan , Seoane-Pillado Teresa , Llorens Noelia , Gerpe José Manuel , Saiz Pilar
Published: October 2024

Background

Suicide is a serious public health problem that affects our entire country. The aim of this research was to study the variation in completed suicide rates between 2010 and 2022 in Spain and their relationship with the consumption of addictive substances.

Methods

Completed suicide data from the Spanish Statistical Office (INE) were analyzed with a joinpoint regression model to determine time trends. The relationship between the variation in completed suicide rates with sociodemographic variables, including depression rates, obtained from the Spanish Statistical Office and variables related to the consumption of substances obtained from the survey on alcohol and other drugs in Spain (EDADES) of the Government Delegation for the National Plan on Drugs (DGPNSD) was also studied using an exploratory analysis and also performing a Generalized Additive Model.

Results

The joinpoint regression model did reveal a point of significant change in the period studied for Spain showing a trend of increased suicide death rates for the studied period. The following variables correlated positively with the variation in completed suicide rates in the Generalized Additive Model: alcohol use in the past 12 months, alcohol use in the last 30 days, daily alcohol use in the last 30 days, binge drinking in the last 12 months, binge drinking in the last month, positive Alcohol Use Disorder Test for risky alcohol use, benzodiazepine use in the last 12 months, benzodiazepine use in the last month, daily benzodiazepine use in the last month, use of illegal substances in the last 12 months, use of illegal substances in the last month, mean age and depression rates.

Conclusion

Applying preventive strategies on the risky consumption of alcohol, benzodiazepines and illegal substances would help reduce the rates of completed suicide in Spain.
Epidemiological overlaps in COVID-19 and malaria within healthcare and community settings of Southern Ghana
Authors: Amegatcher Gloria , Acquah Maame E. , Tetteh Deborah K. , Obeng Rachael , Debrah Ethel , Quist Bridget , Acquah-Jackson Priscilla , Boateng Kyerewaa A. , Twieku Gideon , Armoo Samuel , Awandare Gordon A. , Mosi Lydia , Narh Charles A.
Published: October 2024

Background

COVID-19 disruptions including lockdowns and prioritization of COVID-19 control programs in Africa in 2020–2022 contributed to reductions in malaria control activities including malaria diagnosis, treatment and resistance monitoring. This study investigated the malaria burden and distribution on the background of active transmission of SARS-CoV-2 in Southern Ghana; utilizing community health education and medical screening (CHEMS) approach to determine epidemiological overlaps in COVID-19 and malaria.

Methods

Between October–December 2022, prospective cross-sectional surveys, with CHEMS were conducted in Greater Accra and Central regions, where 994 participants enrolled either at a hospital or community setting provided demographic and clinical data including history of clinical malaria infection and antimalarial treatment in the past 2 weeks. Of this study population, 953 provided nasal/throat swabs for COVID-19 RT-PCR testing, with a subset of 136 participants also providing finger-prick blood for malaria RDT testing.

Results

The study population comprised of 73.6% adults, with 54.6% COVID-19 vaccination rate. Overall, 18.1% of participants had a history of clinical malaria, which was associated (adjusted odds ratio > 1.50, p-value ≤0.022) with COVID-19 symptoms and positivity, study area and hospital setting, suggestive of overlaps in the epidemiological risk for malaria. On a background of widespread SARS-CoV-2 infections (12–37%), malaria parasitaemia was detected in 6%, with 2% being co-infections with SARS-CoV-2. Among the malaria positives, 9.5% had a history of antimalarial treatment, which suggested that their infections were recrudescent parasitaemia.

Conclusion

The epidemiological and clinical overlap between malaria and COVID-19 within the hospital and community settings underscores the need for accurate case diagnosis to inform effective clinical treatments. Innovative surveillance programs, with community engagement are needed to maximize control interventions including treatment of asymptomatic malaria infections.
Evaluation of a massive open online course for just-in-time training of healthcare workers
Authors: Strehlow Matthew Charles , Johnston Jamie Sewan , Aluri Kelly Zhang , Prober Charles G. , Acker Peter Corrigan , Patil Avinash S. , Mahadevan Aditya , Mahadevan Swaminatha V.
Published: October 2024

Introduction

COVID-19 created a global need for healthcare worker (HCW) training. Initially, mass trainings focused on public health workers and physicians working in intensive care units. However, in resource-constrained settings, nurses and general practitioners provide most patient care, typically lacking the training and equipment to manage critically ill patients. We developed a massive open online course (MOOC) for HCWs in resource-constrained settings aimed at training bedside providers caring for COVID-19 patients. We describe the development, implementation and analysis of this MOOC.

Methods

From May through June 2020, the course was developed by a multi-disciplinary team and launched on two online platforms in July. The 4-hour course comprises 6 video-based modules. Student knowledge was assessed using pre- and post-module quizzes and final exam, while demographics and user experience were evaluated by pre- and post-course surveys and learning platform data.

Results

From July 17th to September 24th, 30,859 students enrolled, 18,818 started, and 7,101 completed the course. Most participants worked in healthcare (78%) and resided in lower middle- (38%) or upper middle- (20%) income countries. Learners from upper middle-income and lower middle-income countries had higher completion rates. Knowledge gains were observed from pre-module to post-module quizzes and a final exam. Afterward, participants reported increased self-efficacy regarding course objectives, a 0.63 mean increase on a 4-point scale (95% CI [0.60,0.66]). Most participants (93%) would recommend the course to others.

Conclusion

This article demonstrates the potential of MOOCs to rapidly provide access to emerging medical knowledge during a public health crisis, particularly for HCWs in high- and middle-income countries.
Subjective learning gain from a simulation-based health management course: a mixed methods study
Authors: Gu Ren-Ping , Zhao Fang , Bai Jie , Sun Shan-Shan , Zhu Ai-Yong
Published: October 2024

Objectives

Simulations are increasingly being offered as part of the educational experience of healthcare students. We used a Health Management Scenario Simulation system to create a course. This study aimed to evaluate learning gains before and after the course.

Methods

Based on the learning strategies of framing, simulation, and debriefing, the Health Management Scenario Simulation course lasted 4 weeks and was conducted online. Learning gain was assessed using a comparative self-assessment questionnaire administered electronically at the beginning and end of the course. We organized focus group interviews and collected quantitative data after students completed the simulations and the questionnaire. These data were subjected to descriptive statistical analysis and thematic grouping using frequency counting.

Results

There were 195 health management students enrolled in the course. In total, 265 anonymously completed questionnaires were received, 141 (72.31%) on the pre-simulation and 124 (63.59%) on the post-simulation. All questionnaire item gain values were positive, except the item “I can identify common health risk factors,” which showed no change. The skills domain showed the highest learning gain, ranging from 16 to 22%. Six students participated in the focus-group study. The main themes that emerged from students’ reflections were learner-centeredness, competencies, and career development.

Conclusion

Students acquired health management skills through the simulation, which contributed to the development of basic attitudes and skills in their professional careers. Students’ comments highlighted the value of practicing health management skills in a simulated environment.
Seven-tesla magnetic resonance imaging of the nervus terminalis, olfactory tracts, and olfactory bulbs in COVID-19 patients with anosmia and hypogeusia
Authors: Kirsch Claudia F. E. , Khurram Syed Ali , Lambert Daniel , Belani Puneet , Pawha Puneet S. , Alipour Akbar , Rashid Shams , Herb Mackenzie T. , Saju Sera , Zhu Yijuan , Delman Bradley N. , Lin Hung-Mo , Balchandani Priti
Published: October 2024

Introduction

Linking olfactory epithelium to the central nervous system are cranial nerve 1, the olfactory nerve, and cranial nerve “0,” and the nervus terminalis (NT). Since there is minimal expression of angiotensin-converting enzyme-2 (ACE-2) in the olfactory nerve, it is unclear how SARS-CoV-2 causes anosmia (loss of smell) and hypogeusia (reduction of taste). In animal models, NT expresses ACE-2 receptors, suggesting a possible SARS-CoV-2 viral entry site in humans. The purpose of this study was to determine whether ultra-high-field 7 T magnetic resonance imaging (MRI) could visualize the NT, olfactory bulbs (OB), and olfactory tract (OT) in healthy controls and COVID-19 anosmia or hypogeusia and to qualitatively assess for volume loss and T2 alterations.

Methods

In this study, 7 T MRI was used to evaluate the brain and olfactory regions in 45 COVID-19 patients and 29 healthy controls. Neuroimaging was qualitatively assessed by four board-certified neuroradiologists who were blinded to outcome assignments: for the presence or absence of NT; for OB, OT, and brain volume loss; and altered T2 signal, white matter T2 hyperintensities, microhemorrhages, enlarged perivascular spaces, and brainstem involvement.

Results

NT was identifiable in all COVID-19 patients and controls. T2 hyperintensity in the NT, OB, and OT in COVID-19 patients with anosmia or hypogeusia was statistically significant compared to controls and COVID-19 patients without anosmia or hypogeusia.

Discussion

On 7 T MRI, NT was radiographically identifiable, adjacent to OB and OT. In COVID-19 anosmia and hypogeusia, T2 hyperintensity of NT, OB, and OT was statistically significant compared to COVID-19 patients without anosmia or hypogeusia and controls. The NT may be a potential entry site for SARs-CoV-2 and may play a role in the pathophysiology of COVID-19 anosmia.
CheekAge, a next-generation epigenetic buccal clock, is predictive of mortality in human blood
Authors: Shokhirev Maxim N. , Kramer Daniel J. , Corley Janie , Cox Simon R. , Cuellar Trinna L. , Johnson Adiv A.
Published: October 2024

While earlier first-generation epigenetic aging clocks were trained to estimate chronological age as accurately as possible, more recent next-generation clocks incorporate DNA methylation information more pertinent to health, lifestyle, and/or outcomes. Recently, we produced a non-invasive next-generation epigenetic clock trained using Infinium MethylationEPIC data from more than 8,000 diverse adult buccal samples. While this clock correlated with various health, lifestyle, and disease factors, we did not assess its ability to capture mortality. To address this gap, we applied CheekAge to the longitudinal Lothian Birth Cohorts of 1921 and 1936. Despite missing nearly half of its CpG inputs, CheekAge was significantly associated with mortality in this longitudinal blood dataset. Specifically, a change in one standard deviation corresponded to a hazard ratio (HR) of 1.21 (FDR q = 1.66e-6). CheekAge performed better than all first-generation clocks tested and displayed a comparable HR to the next-generation, blood-trained DNAm PhenoAge clock (HR = 1.23, q = 2.45e-9). To better understand the relative importance of each CheekAge input in blood, we iteratively removed each clock CpG and re-calculated the overall mortality association. The most significant effect came from omitting the CpG cg14386193, which is annotated to the gene ALPK2. Excluding this DNA methylation site increased the FDR value by nearly threefold (to 4.92e-06). We additionally performed enrichment analyses of the top annotated CpGs that impact mortality to better understand their associated biology. Taken together, we provide important validation for CheekAge and highlight novel CpGs that underlie a newly identified mortality association.
Predicting conserved functional interactions for long noncoding RNAs via deep learning
Authors: Kratz Megan B. , Smith Keriayn N.
Published: October 2024

Long noncoding RNA (lncRNA) genes outnumber protein coding genes in the human genome and the majority remain uncharacterized. A major difficulty in generalizing understanding of lncRNA function is the dearth of gross sequence conservation, both for lncRNAs across species and for lncRNAs that perform similar functions within a species. Machine learning based methods which harness vast amounts of information on RNAs are increasingly used to impute certain biological characteristics. This includes interactions with proteins that are important mediators of RNA function, thus enabling the generation of knowledge in contexts for which experimental data are lacking. Here, we applied a natural language-based machine learning approach that enabled us to identify RNA binding protein interactions in lncRNA transcripts, using only RNA sequence as an input. We found that this predictive method is a powerful approach to infer conserved binding across species as distant as human and opossum, even in the absence of sequence conservation, thus informing on sequence-function relationships for these poorly understood RNAs.
Earth’s Interconnected Climate: Understanding Our Changing World
Authors: Collins Matthew , Thompson Vikki , Hegerl Gabriele C.
Published: October 2024

Have you ever thought about what causes the weather conditions that you experience where you live? Maybe you are thinking, “Sure, when there are storm clouds overhead it rains or snows, and when the sun shines strongly in the summer, we have hot weather”. This is true, but the “big” story is more complicated: the conditions you experience in your area can actually be caused by weather and climate events that occur thousands of kilometers away. These long-distance effects are called teleconnections, and they are a natural part of Earth’s climate system. In this article, we provide examples of teleconnections and describe how scientists study them using powerful computer programs. We also explain how climate change might affect these invisible forces that stretch across the Earth, and how resulting changes in teleconnections could cause extreme weather events, like powerful rainstorms or droughts, in certain areas. The more scientists understand about teleconnections, the better we can protect areas that are vulnerable to the dangerous effects of climate change.
Emerging signals of climate change from the equator to the poles: new insights into a warming world
Authors: Collins Matthew , Beverley Jonathan D. , Bracegirdle Thomas J. , Catto Jennifer , McCrystall Michelle , Dittus Andrea , Freychet Nicolas , Grist Jeremy , Hegerl Gabriele C. , Holland Paul R. , Holmes Caroline , Josey Simon A. , Joshi Manoj , Hawkins Ed , Lo Eunice , Lord Natalie , Mitchell Dann , Monerie Paul-Arthur , Priestley Matthew D. K. , Scaife Adam , Screen James , Senior Natasha , Sexton David , Shuckburgh Emily , Siegert Stefan , Simpson Charles , Stephenson David B. , Sutton Rowan , Thompson Vikki , Wilcox Laura J. , Woollings Tim
Published: October 2024

The reality of human-induced climate change is unequivocal and exerts an ever-increasing global impact. Access to the latest scientific information on current climate change and projection of future trends is important for planning adaptation measures and for informing international efforts to reduce emissions of greenhouse gases (GHGs). Identification of hazards and risks may be used to assess vulnerability, determine limits to adaptation, and enhance resilience to climate change. This article highlights how recent research programs are continuing to elucidate current processes and advance projections across major climate systems and identifies remaining knowledge gaps. Key findings include projected future increases in monsoon rainfall, resulting from a changing balance between the rainfall-reducing effect of aerosols and rainfall-increasing GHGs; a strengthening of the storm track in the North Atlantic; an increase in the fraction of precipitation that falls as rain at both poles; an increase in the frequency and severity of El Niño Southern Oscillation (ENSO) events, along with changes in ENSO teleconnections to North America and Europe; and an increase in the frequency of hazardous hot-humid extremes. These changes have the potential to increase risks to both human and natural systems. Nevertheless, these risks may be reduced via urgent, science-led adaptation and resilience measures and by reductions in GHGs.
Workflow for predictive risk assessments of UVCBs: cheminformatics library design, QSAR, and read-across approaches applied to complex mixtures of metal naphthenates
Authors: Prussia A. J. , Welsh C. , Somers T. S. , Ruiz P.
Published: October 2024

Substances of unknown or variable composition, complex reaction products, and biological materials (UVCBs) are commonly found in the environment. However, assessing their human toxicological risk is challenging due to their variable composition and many constituents. Metal naphthenate salts are one such category of UVCBs that are the reaction products of naphthenic acids with metals to form complex mixtures. Metal naphthenates are often found or used in household and industrial materials with potential for human exposure, but very few of these materials have been evaluated for causing human health hazards. Herein, we evaluate metal naphthenates using predictions derived from read-across and quantitative structure–activity/property relationship (QSAR/QSPR) models. Accordingly, we first built a computational chemistry library by enumerating the structures of naphthenic acids and derived 11,850 QSAR-acceptable structures; then, we used open and commercial in silico tools on these structures to predict a set of physicochemical properties and toxicity endpoints. We then compared the QSAR/QSPR predictions with available experimental data on naphthenic acids to provide a more complete picture of the contributions of the components to the toxicity profiles of metal naphthenate mixtures. The available systematic acute oral toxicity values (LD50) and QSAR LD50 predictions of all the naphthenic acid components indicated low concern for toxicity. The point of departure predictions for chronic repeated dose toxicity for the naphthenic acid components using QSAR models developed from studies on rats ranged from 25 to 50 mg/kg/day. These values are in good agreement with findings from studies on copper and zinc naphthenates, which had no observed adverse effect levels of 30 and 118 mg/kg/day, respectively. Hence, this study demonstrates how published in silico approaches can be used to identify the potential components of metal naphthenates for further testing, inform groupings of UVCBs such as naphthenates, as well as fill the data gaps using read-across and QSAR models to inform risk assessment.
Methods for Corrosion Detection in Pipes Using Thermography: A Case Study on Synthetic Datasets
Authors: Rezayiye Reza Khoshkbary , Ibarra-Castanedo Clemente , Maldague Xavier
Published: October 2024

This study reviews advanced methods for corrosion detection and characterization in pipes using thermography, with a focus on addressing the limitations posed by small datasets. Thermography captures temperature distributions on the surface of pipes to identify subsurface defects. The challenges of sequential data processing, neural network performance, feature extraction, and dataset size are discussed, with proposed solutions such as advanced algorithms, feature selection techniques, and data augmentation. Given the significant gap in the current literature, there is a need for larger, more diverse datasets to train more robust and accurate machine learning models. A case study combining experimental data with Finite Element Method (FEM) simulations demonstrates that augmenting datasets with synthetic data significantly improves defect detection accuracy. These findings highlight the potential of integrating thermography with machine learning to enhance defect detection, providing insights for future research and practical applications.
Legal and Economic Conditions for Running a Care Farm: A Polish Case Study
Authors: Wojcieszak-Zbierska Monika Małgorzata , Wojcieszak-John Agnieszka
Published: October 2024

The purpose of this paper is to present the situation of Polish care farms in the context of legal and economic conditions. The need to analyze this topic arises from the current lack of literature that has synthetically addressed the challenges posed by the ageing population in the European Union, including in Poland. The research gap revealed by the authors is especially prominent when it comes to aspects related to the setting up and running of care farms in Poland. Therefore, this paper analyzes the legal forms of establishing a care farm. Next, it discusses the economic aspects of how care farms operate. Based on research materials, especially including those retrieved through the use of the formal dogmatic approach, the authors determined the formal conditions for the setting up and successive running of care farms. The authors have analyzed with the help of formal dogma the forms of running care farms in Poland referring to the current legislation, as well as the position presented in the literature. Also, due to the method used in analyzing the materials collected in this study, the authors have presented their views on how to finance such facilities. Findings from this research confirm that Polish care farms have promising outlooks as they respond to the changing needs of an ageing society. Moreover, as a result of the formal dogmatics method used, it was found that in Poland the most common form of running a care farm is an association. This is because the establishment of an association does not require the fulfillment of many legal criteria as is the case with a sole proprietorship. For this reason, those interested in starting a care farm may opt for the association form.
Transcriptome Analysis Revealed the Response Mechanism of Pomegranate to Salt Stress
Authors: Tang Haixia , Wang Chuanzeng , Mei Jian , Feng Lijuan , Wu Qikui , Yin Yanlei
Published: October 2024

Pomegranate (Punica granatum) is a well-known fruit tree species and a significant pioneer ecological species on saline–alkali land with moderate resistance to salt stress. To explore its response mechanism to salt stress could provide valuable insights into the molecular and physiological strategies plants employ to adapt and survive in high-salt environments. In this study, changes in physiological parameters and gene expressions were examined following salt treatment. After 72 h of salt treatment, change patterns of SOD and POD differed between high and low salt concentrations. Similar changes were found in the contents of proline and total soluble sugar. RNA-Seq analysis of fifteen samples detected 32,630 genes from the pomegranate genome data. A total of 6571 DEGs, including 374 TFs, were identified across different treatments. Six special modules and 180 hub genes were obtained by WGCNA analysis. Functional annotation highlighted signaling pathways and the accumulation of primary and secondary metabolites as significant pathways. These findings could reveal the salt tolerance mechanism in pomegranate leaves, offering a theoretical foundation for enhancing plant salt tolerance through genetic engineering.
Progress in Research on Deep Learning-Based Crop Yield Prediction
Authors: Wang Yuhan , Zhang Qian , Yu Feng , Zhang Na , Zhang Xining , Li Yuchen , Wang Ming , Zhang Jinmeng
Published: October 2024

In recent years, crop yield prediction has become a research hotspot in the field of agricultural science, playing a decisive role in the economic development of every country. Therefore, accurate and timely prediction of crop yields is of great significance for the national formulation of relevant economic policies and provides a reasonable basis for agricultural decision-making. The results obtained through prediction can selectively observe the impact of factors such as crop growth cycles, soil changes, and rainfall distribution on crop yields, which is crucial for predicting crop yields. Although traditional machine learning methods can obtain an estimated crop yield value and to some extent reflect the current growth status of crops, their prediction accuracy is relatively low, with significant deviations from actual yields, and they fail to achieve satisfactory results. To address these issues, after in-depth research on the development and current status of crop yield prediction, and a comparative analysis of the advantages and problems of domestic and foreign yield prediction algorithms, this paper summarizes the methods of crop yield prediction based on deep learning. This includes analyzing and summarizing existing major prediction models, analyzing prediction methods for different crops, and finally providing relevant views and suggestions on the future development direction of applying deep learning to crop yield prediction research.
Mechanical Harvesting of Marginal Land and Agroforestry Field: New Insights from Safflower for Bio-Product Production
Authors: Pari Luigi , Bergonzoli Simone , Cozzolino Luca , Baldi Gian Maria , Falce Michele , Alexopoulou Efthymia
Published: October 2024

Considering the increase in market requests for bio-products, it is necessary to study the possibility of cultivating industrial crops in areas still untapped to extend the total cultivation surface, reducing land competition with food crops. With this aim in mind, we studied the harvesting performance and cost, and seed losses of Safflower (Carthamus tinctorius L.) cultivation during two growing seasons and in three different locations: (A) an agroforestry field, (B) a marginal field and (C) a dedicated field utilized as a control. The overall efficiency of the cultivation system was higher in location C in respect to the other two fields. The yield was 12–22% and 21–26% higher in location C compared to locations B and A, respectively, while seed losses were 40–33% and 28–50% lower in C compared to locations A and B, as well as the total harvesting costs, which were 45% and 31–35% lower in location C compared to locations A and B, respectively. Despite this, the results highlighted how the reduction in cultivation efficiency given by limiting factors was lower compared to that of other crops, highlighting the possibility of cultivating Safflower for bio-products’ production on alternative lands.
Diet of Three Cryptobenthic Clingfish Species and the Factors Influencing It
Authors: Trkov Domen , Ivajnšič Danijel , Kovačić Marcelo , Lipej Lovrenc
Published: October 2024

Cryptobenthic fish are small benthic fish species that normally live in various hiding places. Due to their large numbers, they are very important for energy transfer to higher trophic levels. However, due to their small size and hidden lifestyle, knowledge about them and their ecology, including their diet, is still limited. Using a non-destructive method based on faecal pellets, we investigated the diet of three clingfish species, Lepadogaster lepadogaster, L. candolii, and Apletodon incognitus, in the shallow northern Adriatic Sea. To better understand the results, we studied the fauna of potential prey in the habitats of the fish studied and also took fish specimens to observe their behaviour in the laboratory. The three species feed predominantly on crustaceans, particularly amphipods, copepods, and decapods. The proportion of the different taxa in the diet depends on the species of clingfish, the size of the specimens, and the size of the prey. In addition, the behaviour of the fish, the home range of the specimens, and the availability of food played an important role. The presence of certain crustacean groups in the environment also determines the occurrence of clingfish of different species and sizes.