bluuebunny/crossref_metadata_2025 huggingface dataset:
Unraveling neurovascular mysteries: the role of endothelial glycocalyx dysfunction in Alzheimer’s disease pathogenesis
Authors: O’Hare Nicholas , Millican Karina , Ebong Eno E.
Published: July 2024

While cardiovascular disease, cancer, and human immunodeficiency virus (HIV) mortality rates have decreased over the past 20 years, Alzheimer’s Disease (AD) deaths have risen by 145% since 2010. Despite significant research efforts, effective AD treatments remain elusive due to a poorly defined etiology and difficulty in targeting events that occur too downstream of disease onset. In hopes of elucidating alternative treatment pathways, now, AD is commonly being more broadly defined not only as a neurological disorder but also as a progression of a variety of cerebrovascular pathologies highlighted by the breakdown of the blood-brain barrier. The endothelial glycocalyx (GCX), which is an essential regulator of vascular physiology, plays a crucial role in the function of the neurovascular system, acting as an essential vascular mechanotransducer to facilitate ultimate blood-brain homeostasis. Shedding of the cerebrovascular GCX could be an early indication of neurovascular dysfunction and may subsequently progress neurodegenerative diseases like AD. Recent advances in in vitro modeling, gene/protein silencing, and imaging techniques offer new avenues of scrutinizing the GCX’s effects on AD-related neurovascular pathology. Initial studies indicate GCX degradation in AD and other neurodegenerative diseases and have begun to demonstrate a possible link to GCX loss and cerebrovascular dysfunction. This review will scrutinize the GCX’s contribution to known vascular etiologies of AD and propose future work aimed at continuing to uncover the relationship between GCX dysfunction and eventual AD-associated neurological deterioration.
The fusion of vegetation indices increases the accuracy of cotton leaf area prediction
Authors: Fan Xianglong , Gao Pan , Zhang Mengli , Cang Hao , Zhang Lifu , Zhang Ze , Wang Jin , Lv Xin , Zhang Qiang , Ma Lulu
Published: July 2024

Introduction

Rapid and accurate estimation of leaf area index (LAI) is of great significance for the precision agriculture because LAI is an important parameter to evaluate crop canopy structure and growth status.

Methods

In this study, 20 vegetation indices were constructed by using cotton canopy spectra. Then, cotton LAI estimation models were constructed based on multiple machine learning (ML) methods extreme learning machine (ELM), random forest (RF), back propagation (BP), multivariable linear regression (MLR), support vector machine (SVM)], and the optimal modeling strategy (RF) was selected. Finally, the vegetation indices with a high correlation with LAI were fused to construct the VI-fusion RF model, to explore the potential of multi-vegetation index fusion in the estimation of cotton LAI.

Results

The RF model had the highest estimation accuracy among the LAI estimation models, and the estimation accuracy of models constructed by fusing multiple VIs was higher than that of models constructed based on single VIs. Among the multi-VI fusion models, the RF model constructed based on the fusion of seven vegetation indices (MNDSI, SRI, GRVI, REP, CIred-edge, MSR, and NVI) had the highest estimation accuracy, with coefficient of determination (R2), rootmean square error (RMSE), normalized rootmean square error (NRMSE), and mean absolute error (MAE) of 0.90, 0.50, 0.14, and 0.26, respectively.

Discussion

Appropriate fusion of vegetation indices can include more spectral features in modeling and significantly improve the cotton LAI estimation accuracy. This study will provide a technical reference for improving the cotton LAI estimation accuracy, and the proposed method has great potential for crop growth monitoring applications.
Development of highly discriminatory SCoT- and CBDP-based SCAR fingerprint for authentication of Indian senna (Senna alexandrina Mill.) formerly Cassia angustifolia Vahl.)
Authors: Chouksey Sarika , Ashfaq Mohd Ashraf , Kaira Pushkar , Farhat Sabnam , Pandey Maneesha , Kumar Ch. Anil , Nagaraja Reddy Rama Reddy
Published: July 2024

Introduction

Indian senna (Senna alexandrina Mill.) (formerly Cassia angustifolia Vahl.) is an important medicinal plant of the family Fabaceae. The leaves and pods of Indian senna yield sennosides and rhein-based laxative. Adulteration of Indian senna is a serious issue as with most of the medicinal plants used in the Indian systems of traditional medicine. The bulk of dried leaves and pods of morphologically related species, such as Cassia fistula, Senna occidentalis, Senna sophera, and Senna tora, is usually mixed with those of the Indian senna, and the admixture is used in laxative-based formulations. The present investigation is a modest attempt at developing species-specific start codon targeted (SCoT) polymorphism- and CAAT-box-derived polymorphism (CBDP)-based sequence-characterized amplified region (SCAR) markers for the identification and authentication of Indian senna and four adulterant species (C. fistula, S. occidentalis, S. sophera, and S. tora species).

Methods

In this study, genomic DNA extracted from 44 accessions of Indian senna and four adulterant species was subjected to SCoT and CBDP PCR. The polymorphic amplicons were identified, eluted, ligated, and transformed into Escherichia coli DH5 α strain. PCR, restriction analysis, and DNA sequencing confirmed the transformed recombinant plasmid clones.

Results

Post-sequencing, the sequence of the primary SCoT and CBDP primers was analyzed and extended into the unique signature sequence of the concerned accessions. This resulted in development of one SCoT-44- and two CBDP-25-based SCARs. SCoT-44 SCAR produced a signature amplicon of 287 bp for accession DCA120, and CBDP-25 SCAR yielded signature amplicons of 575 and 345 bp for accessions DCA13 and DCA119, respectively. The developed SCAR markers were validated across 48 samples (44 accessions of Indian senna and 4 adulterant species) and produced distinct amplicons in Indian senna only, while no such amplicon was observed in the other four adulterant species.

Discussion

The information generated using these markers have been faithfully converted to single-locus, unequivocal, highly reproducible, and informative sequence-based SCAR markers. These markers will enable discrimination of individual plants on the basis of unique sequence-specific amplicons, which could be used as diagnostic markers to settle issues pertaining to the true identity of Indian senna.
The relationship between time anxiety and college students’ sleep quality: the mediating role of irrational procrastination and the moderating effect of physical activity
Authors: Sun Zhe , Gao Xinchao , Ren Penghui
Published: July 2024

Background

Poor sleep quality has become one of the most pressing public issues among Chinese college students, with an increasing incidence rate in recent years. Although some studies showed that anxiety is related to sleep quality, the relationship between time anxiety (which is a more concrete manifestation of anxiety in the temporal dimension) and sleep quality, as well as its potential mechanisms, still requires further investigation and analysis. This study aimed to explore the relationship between time anxiety and sleep quality among college students, and to examine the mediating role of irrational procrastination and the moderating effect of physical activity.

Methodology

A cross-sectional study was conducted with 1,137 participants recruited from four universities in eastern, western, and central China. They completed a questionnaire survey on time anxiety, irrational procrastination, physical activity, and sleep quality. Data analysis was performed using SPSS 26.0 and PROCESS 3.3.

Results

Time anxiety had a significant positive impact on sleep quality (β = 0.28, t = 9.95, p < 0.001). Irrational procrastination played a mediating role between time anxiety and college students’ sleep quality, the effect value was 0.05, and the intermediary effect accounted for 19.26%. Physical activity moderated the direct effect of time anxiety on college students’ sleep quality (β = −0.08, t = −2.98, p < 0.01), and moderated the second half path of irrational procrastination mediation model (β = −0.06, t = −2.12, p < 0.05).

Conclusion

Higher levels of time anxiety are associated with poorer sleep quality among college students. Time anxiety not only directly affects college students’ sleep quality, but also indirectly affects it through irrational procrastination. Conducting physical activities can mitigate the impact of time anxiety and irrational procrastination on college students’ sleep quality.
Incidence of effort-reward imbalance among nurses: a systematic review and meta-analysis
Authors: Zhang Yujie , Lei Shanyan , Yang Fang
Published: July 2024

Introduction

To systematically evaluate the incidence of effort-reward imbalance among nurses.

Method

PubMed, Web of Science, Embase, CNKI, WanFang Data, and VIP databases were searched to collect studies on the incidence of effort-reward imbalance among nurses. The search timeframe was from database construction to December 2023. Two researchers independently screened the literature, extracted the data, and evaluated the risk of bias in the included studies. The meta-analysis was performed using Stata 17.1 software.

Results

A total of 60 studies, including 79,644 participants, were included. The prevalence of effort-reward imbalance among nurses was 52.3% (95% CI: 44.9–59.7%). In terms of time, the incidence of effort-reward imbalance among nurses before 2010 (26.6, 95%CI: 6.8–46.4%) and in 2010–2015 (42.4, 95%CI: 32.1–52.8%), 2016–2020 (60.2, 95%CI: 49.6–70.7%), and 2021–2023 (65.0, 95%CI: 51.5–78.4%) continued to increase. Geographically, Asia (57.4, 95%CI: 51.8–63.1%) nurses had a relatively higher prevalence of effort-reward imbalance. In terms of department, the incidence of effort-reward imbalance among nurses was relatively higher in operating rooms (71.8, 95%CI: 64.5–79.0%), ICU (64.6, 95%CI: 27.7–100.0%), emergency (68.7, 95%CI: 62.9–74.5%), and pediatrics (65.8, 95%CI: 32.2–99.3%).

Discussion

The prevalence of nurse effort-reward imbalance is high, and there are differences in its prevalence across time, geography, department. Hospital administrators should actively take measures to effectively prevent and reduce the effort-reward imbalance for nurses, especially for nurses in Asia, operating rooms, emergency pediatrics and ICU departments.

Systematic review registration

PROSPERO (CRD42023452428).
Aberrant brain language network in schizophrenia spectrum disorder: a systematic review of its relation to language signs beyond symptoms
Authors: Alonso-Sanchez María F. , Z-Rivera Lucía , Otero Mónica , Portal Jorge , Cavieres Álvaro , Alfaro-Faccio Pedro
Published: July 2024

Background

Language disturbances are a core feature of schizophrenia, often studied as a formal thought disorder. The neurobiology of language in schizophrenia has been addressed within the same framework, that language and thought are equivalents considering symptoms and not signs. This review aims to systematically examine published peer-reviewed studies that employed neuroimaging techniques to investigate aberrant brain-language networks in individuals with schizophrenia in relation to linguistic signs.

Methods

We employed a language model for automatic data extraction. We selected our studies according to the PRISMA recommendations, and we conducted the quality assessment of the selected studies according to the STROBE guidance.

Results

We analyzed the findings from 37 studies, categorizing them based on patient characteristics, brain measures, and language task types. The inferior frontal gyrus (IFG) and superior temporal gyrus (STG) exhibited the most significant differences among these studies and paradigms.

Conclusions

We propose guidelines for future research in this field based on our analysis. It is crucial to investigate larger networks involved in language processing, and language models with brain metrics must be integrated to enhance our understanding of the relationship between language and brain abnormalities in schizophrenia
Sustainability initiatives in inpatient psychiatry: tackling food waste
Authors: Liwinski Timur , Bocek Iona , Schmidt Andreas , Kowalinski Eva , Dechent Frieder , Rabenschlag Franziska , Moeller Julian , Sarlon Jan , Brühl Annette B. , Nienaber André , Lang Undine E. , Huber Christian G.
Published: July 2024

Background

Food plays a dual role in promoting human health and environmental sustainability. Yet, current food systems jeopardize both. Food waste poses a major global challenge due to its significant economic, social, and environmental impacts. Healthcare facilities generate the largest amounts of food waste compared to other forms of catering provision. Food waste correlates with environmental unsustainability and diminished patient satisfaction, compounding the prevalent challenge of hospital malnutrition and contributing to suboptimal patient outcomes.

Materials and methods

In a three-year interventional study (2020-2022) at a psychiatric tertiary care center, we assessed and mitigated food waste using evidence-based measures. We conducted systematic food wastage audits over three years (2020-2022) in May and June, each lasting four weeks. Costs were analyzed comprehensively, covering food, staff, infrastructure, and disposal. Environmental impact was assessed using Umweltbelastungspunkte (UBP) and CO2e/kg emissions, alongside water usage (H2O - l/kg).

Results

Economic losses due to food wastage were substantial, primarily from untouched plates and partially consumed dinners, prompting meal planning adjustments. Despite a >3% increase in meals served, both food waste mass and costs decreased by nearly 6%. Environmental impact indicators showed a reduction >20%. Vegetables, salad, and fruits constituted a significant portion of waste. Overproduction minimally contributed to waste, validating portion control efficacy.

Conclusion

Our study highlights significant economic and environmental losses due to hospital food waste, emphasizing the importance of resource efficiency. The strategies outlined offer promising avenues for enhanced efficiency. The decrease in food waste observed over the three-year period underscores the potential for improvement.
Trajectories and influencing factors of cognitive function and physical disability in Chinese older people
Authors: Cheng Shuyuan , Yin Rong , Wu Kunpeng , Wang Qiong , Zhang Hui , Ling Li , Chen Wen , Shi Leiyu
Published: July 2024

Introduction

Dementia and physical disability are serious problems faced by the aging population, and their occurrence and development interact.

Methods

Based on data from a national cohort of Chinese people aged 60 years and above from the China Health and Retirement Longitudinal Survey from 2011 to 2018, we applied the group-based trajectory model to identify the heterogeneous trajectories of cognitive function and physical disability in participants with different physical disability levels. Next, multinomial logistic regression models were used to explore the factors affecting these trajectories.

Results

The cognitive function trajectories of the Chinese older people could be divided into three characteristic groups: those who maintained the highest baseline level of cognitive function, those with a moderate baseline cognitive function and dramatic progression, and those with the worst baseline cognitive function and rapid–slow–rapid progression. The disability trajectories also fell into three characteristic groups: a consistently low baseline disability level, a low initial disability level with rapid development, and a high baseline disability level with rapid development. Compared with those free of physical disability at baseline, a greater proportion of participants who had physical disability at baseline experienced rapid cognitive deterioration. Education, income, type of medical insurance, gender, and marital status were instrumental in the progression of disability and cognitive decline in the participants.

Discussion

We suggest that the Chinese government, focusing on the central and western regions and rural areas, should develop education for the older people and increase their level of economic security to slow the rate of cognitive decline and disability among this age group. These could become important measures to cope with population aging.
“This can certainly work…”: stakeholder perspectives of the feasibility of a caregiver-led training program for caregivers of children with cerebral palsy in a rural setting in Malawi
Authors: Bakuwa Takondwa Connis , Saloojee Gillian , Slemming Wiedaad
Published: July 2024

Introduction

Caregiver training is a key component of rehabilitation for children with complex lifelong disabilities such as cerebral palsy. However critical shortages of therapists in low- and middle-income countries like Malawi, reduce access to therapy. Introducing expert caregivers to assist with the provision of basic training on the condition for fellow caregivers offers a potential solution. However, there is a paucity of evidence regarding the implementation of such strategies in low-resource settings. The aim of this study was to explore perspectives of stakeholders regarding the feasibility of implementing a caregiver-led and delivered training program for caregivers of children with cerebral palsy in Malawi.

Methods

Over 5 days in January 2023, a caregiver-led training program, the “Malamulele Onward Carer-to-Carer Training Program,” was conducted in Blantyre, Malawi. A South African master trainer traveled to Malawi and delivered the program to potential stakeholders including caregivers of children with cerebral palsy; physiotherapists; and community-based organization representatives. Stakeholder perspectives regarding the acceptability, demand, practicality and adaptation of the program were obtained through a combination of focus group discussions, in-depth interviews, and daily field notes. Data from the focus group discussions and in-depth interviews were analyzed using thematic analysis.

Results

The caregiver-led training program was deemed acceptable despite two areas identified as potential areas of concern; that the expert caregivers may cross practice boundaries and that their fellow caregivers may look down upon them. A demand for this program was expressed because of perceived relative advantages and relevance to caregiver needs. Participants indicated that the intervention could be easily delivered using local materials, absorbed and supported by existing community structures.

Conclusion

A caregiver-led training program offers an innovative way of supporting caregivers of children with complex disabilities such as cerebral palsy in low-resource settings. The stakeholder engagement demonstrated the positive perspectives of all stakeholders. The areas for modification and adaptation highlighted by the stakeholders will be useful in strengthening the implementation of the program in Malawi.
Heat therapy for different knee diseases: expert opinion
Authors: Rossi Roberto
Published: July 2024

Musculoskeletal pain is a major burden in our society. Management of musculoskeletal pain or injuries includes both pharmacological and non-pharmacological approaches, including heat therapy (HT). HT is a well-established treatment option due to its ability to promote muscle relaxation, enhance blood circulation, and modulate nociceptors with a good safety profile. The main focus of this paper is to review the available literature about HT in knee pathologies (i.e., arthrosis, arthritis, traumatic pathologies in the subacute phase, muscle and tendon pathologies linked to fatigue, muscle tension and distractions) and to provide an expert opinion in case of lack of data.
Moving together—benefits of a 12-week online dance training intervention on static and dynamic postural stability and gait speed in older women: an exploratory pre-post study
Authors: Hansen Rasmus Kopp , Jochum Elizabeth , Egholm Ditte , Villumsen Morten , Hirata Rogerio Pessoto
Published: July 2024

Background

Physical inactivity negatively affects gait performance and postural stability in older adults resulting in a higher risk of fall accidents. Previous research has shown that in-person dance training improves various aspects of balance and lower-extremity function, however, little is known about the potential benefits of dance training delivered online on variables used for fall risk stratification in older adults. We aimed to explore the benefits of a 12-week online dance training intervention on static and dynamic postural stability and gait speed in older women.

Methods

Forty-five older adults (44 women) were included in this exploratory pre-post study. The 12-week dance intervention consisted of two weekly 60-min classes in contemporary (improvisation) and salsa dance delivered online through Zoom video calls. Static and dynamic postural stability was assessed using the center of pressure (CoP) area and velocity (force platform), and the Mini Balance Evaluation Systems Test (Mini-BESTest), respectively. 10-m gait speed was measured using photo gates. Before and after comparisons were performed using paired sample t-tests.

Results

Thirty-two older women completed the study. There were no significant changes for static postural stability assessed by CoP area or velocity (P ≥ 0.218, Cohen d ≤ 0.234). The Mini-BESTest total score was significantly improved at post-intervention (23.88 ± 3.01) compared to baseline (22.56 ± 1.41, P = 0.007, d = 0.52). 10-m gait speed was significantly faster at post-intervention (1.68 ± 0.25 m/s) compared to baseline (1.57 ± 0.22 m/s, P < 0.001, d = 0.737).

Discussion

Although some caution is needed due to the uncontrolled study design, the results indicate that online dance training has a small effect on static postural stability but may be beneficial for gait speed and in particular dynamic postural control among older women. While the absolute increase in gait speed suggests limited clinical relevance, the change in Mini-BESTest score may reflect a clinically meaningful enhancement of dynamic postural control.
Assessment of the nociceptive response to the use of cannabidiol alone and in combination with meloxicam through infrared pupillometry in female dogs undergoing elective ovariohysterectomy
Authors: Casas-Alvarado Alejandro , Martínez-Burnes Julio , Hernández-Ávalos Ismael , Mora-Medina Patricia , Miranda-Cortés Agatha , Domínguez-Oliva Adriana , Mota-Rojas Daniel
Published: July 2024

The negative effects of pain are a constant concern in the surgical management of animals, leading to the search for new drugs or more effective analgesic protocols to control this negative emotion. This study aimed to evaluate the nociceptive response of cannabidiol (CBD) alone and in combination with meloxicam using infrared pupillometry in female dogs undergoing elective ovariohysterectomy (OVH) under isoflurane anesthesia. A total of 60 female dogs of different breeds were included. These dogs were randomly assigned to four study groups according to the treatment: Control Group (G0: n = 15) receiving saline solution; group premedicated with meloxicam at a dose of 0.2 mg Kg−1 IV (GMelox: n = 15). Postoperatively this drug was used at 0.1 mg Kg−1 IV every 24 h; the CBD-treated Group (GCBD: n = 15) at a dose of 2 mg Kg−1 orally in the preoperative. Postoperatively was administrated every 12 h; and the Group premedicated with the combination of meloxicam and CBD (GMelox/CBD: n = 15) Meloxicam at a dose of 0.2 mg Kg−1 IV preoperatively, and 0.1 mg Kg−1 IV during the postoperative. CBD at a dose of 2 mg Kg−1 orally in the preoperative, and every 12 h in the postoperative. Treatments were administered for 48 postoperative hours. After OVH, the pupillary neurologic index, pupillary size, minimum diameter (MIN), percentage change, constriction latency (Lat), constriction velocity, and maximum constriction velocity were recorded as pupillometric variables in both eyes during events (E): Baseline (30 min before drug administration), E30 min, E1h, E2h, E3h, E4h, E8h, E12h, E24h, and E48h. The Short-Form of the Glasgow Composite Measure Pain Scale (GCMPS-SF) was used to assess pain during the same events. Overall, it was observed that the pupillometric variables Size, MIN., and Lat. were significantly higher in G0 compared to the other groups during E30 min, E1h, and E2h (p = 0.03), indicating greater pupil dilation in G0 animals. Additionally, no statistically significant differences were observed in GCMPS-SF between GMelox, GCBD, and GMelox/CBD during the postoperative period (p > 0.05). In contrast, the scores were statistically different compared to G0 (p = 0.00001), where all animals in this group received rescue analgesia at 2 h post-surgery. According to pupillometry and scores on the GCMPS-SF scale, it was observed that monotherapy with cannabidiol provides a similar analgesic effect to meloxicam alone or in combination with cannabidiol to manage acute pain in dogs. Similarly, these findings suggest that infrared pupillometry could be a tool for recognizing acute pain in dogs.
Surgical management of primary and idiopathic internal hydrocephalus in dogs and cats
Authors: Schmidt Martin J. , Farke Daniela
Published: July 2024

Ventriculoperitoneal shunt placement is an effective method to treat internal hydrocephalus in dogs and cats. Although it has a long history in veterinary medicine, the technique continues to evolve. Despite continuing attempts to reduce the incidence of associated complications, shunt failure remains a major problem, and often leads to multiple hospital admissions. This review gives an overview about current knowledge of ventriculoperitoneal shunting techniques in animals, applicable shunt hardware as well as shunt-associated complications and their prevention and treatment.
Advancing Cassava Age Estimation in Precision Agriculture: Strategic Application of the BRAH Algorithm
Authors: Boonprong Sornkitja , Satapanajaru Tunlawit , Piolueang Ngamlamai
Published: July 2024

Cassava crop age estimation is crucial for optimizing irrigation, fertilization, and pest management, which are key components of precision agriculture. Accurate knowledge of crop age allows for effective resource application, minimizing environmental impact and enhancing yield predictions. The Bare Land Referenced Algorithm from Hyper-Temporal Data (BRAH) is used for bare land classification and cassava crop age estimation, but it traditionally requires manual NDVI thresholding, which is challenging with large datasets. To address this limitation, we propose automating the thresholding process using Otsu’s method and enhancing the image contrast with histogram equalization. This study applies these enhancements to the BRAH algorithm for bare land classification and cassava crop age estimation in Ratchaburi, Thailand, utilizing a dataset of 604 Landsat satellite images from 1987 to 2024. Our research demonstrates the accuracy and practicality of the BRAH algorithm, with Otsu’s method providing 94% accuracy in detecting the bare land validation locations with an average deviation of 8.78 days between the acquisition date and the validated date. This approach facilitates precise agricultural planning and management, promoting sustainable farming practices and supporting several Sustainable Development Goals (SDGs).
Transcriptomic Analysis Reveals the Mechanism of MtLOX24 in Response to Methyl Jasmonate Stress in Medicago truncatula
Authors: Xu Lei , Xu Yanchao , Lv Huanhuan , Xu Yanran , Wen Jiangqi , Li Mingna , Kang Junmei , Liu Zhipeng , Yang Qingchuan , Long Ruicai
Published: July 2024

Lipoxygenase (LOX) is associated with responses to plant hormones, environmental stresses, and signaling substances. Methyl jasmonate (MeJA) treatment triggers the production of LOX, polyphenol oxidase, and protease inhibitors in various plants, producing resistance to herbivory. To examine the response of MtLOX24 to MeJA, the phenotypic and physiological changes in Medicago truncatula MtLOX24 overexpression and lox mutant plants were investigated. Additionally, wild-type R108, the MtLOX24-overexpressing line L4, and the mutant lox-1 were utilized as experimental materials to characterize the differentially expressed genes (DEGs) and metabolic pathways in response to MeJA. The results indicate that after treatment with 200 µM of MeJA, the damage in the mutants lox-1 and lox-2 was more serious than in the overexpressing lines L4 and L6, with more significant leaf wilting, yellowing, and oxidative damage in lox-1 and lox-2. Exogenous application of MeJA induced H2O2 production and POD activity but reduced CAT activity in the lox mutants. Transcriptome analysis revealed 10,238 DEGs in six libraries of normal-growing groups (cR108, cL4, and clox1) and MeJA-treated groups (R108, L4, and lox1). GO and KEGG functional enrichment analysis demonstrated that under normal growth conditions, the DEGs between the cL4 vs. cR108 and the clox-1 vs. cR108 groups were primarily enriched in signaling pathways such as plant–pathogen interactions, flavonoid biosynthesis, plant hormone signal transduction, the MAPK signaling pathway, and glutathione metabolism. The DEGs of the R108 vs. cR108 and L4 vs. cL4 groups after MeJA treatment were mainly enriched in glutathione metabolism, phenylpropanoid biosynthesis, the MAPK signaling pathway, circadian rhythm, and α-linolenic acid metabolism. Among them, under normal growth conditions, genes like PTI5, PR1, HSPs, PALs, CAD, CCoAOMT, and CYPs showed significant differences between L4 and the wild type, suggesting that the expression of these genes is impacted by MtLOX24 overexpression. CDPKs, CaMCMLs, IFS, JAZ, and other genes were also significantly different between L4 and the wild type upon MeJA treatment, suggesting that they might be important genes involved in JA signaling. This study provides a reference for the study of the response mechanism of MtLOX24 under MeJA signaling.
FTY720 Reduces the Biomass of Biofilms in Pseudomonas aeruginosa in a Dose-Dependent Manner
Authors: Niazy Abdurahman A. , Lambarte Rhodanne Nicole A. , Sumague Terrence S. , Vigilla Mary Grace B. , Bin Shwish Najla M. , Kamalan Ranan , Daeab Eid Khulaif , Aljehani Nami M.
Published: July 2024

Pseudomonas aeruginosa, a nosocomial pathogen, has strong biofilm capabilities, representing the main source of infection in the human body. Repurposing existing drugs has been explored as an alternative strategy to combat emerging antibiotic-resistant pathogens. Fingolimod hydrochloride (FTY720), an immunomodulatory drug for multiple sclerosis, has shown promising antimicrobial effects against some ESKAPE pathogens. Therefore, the effects of FTY720 on the biofilm capabilities of Pseudomonas aeruginosa were investigated in this study. It was determined that FTY720 inhibited the growth of P. aeruginosa PAO1 at 100 µM. The significant reduction in PAO1 cell viability was observed to be dose-dependent. Additional cytotoxicity analysis on human cell lines showed that FTY720 significantly reduced viabilities at sub-inhibitory concentrations of 25–50 µM. Microtiter assays and confocal analysis confirmed reductions in biofilm mass and thickness and the cell survivability ratio in the presence of FTY720. Similarly, virulence production and biofilm-related gene expression (rhlA, rhlB, pilA, pilI, fliC, fliD and algR) were determined. The results demonstrate that pigment production was affected and quantitative real-time PCR analysis showed a variable degree of reduced gene expression in response to FTY720 at 12.5–50 µM. These findings suggest that FTY720 could be repurposed as an alternative antibiofilm agent against Pseudomonas aeruginosa.
Overlapping Image-Set Determination Method Based on Hybrid BoVW-NoM Approach for UAV Image Localization
Authors: Lee Juyeon , Choi Kanghyeok
Published: July 2024

With the increasing use of unmanned aerial vehicles (UAVs) in various fields, achieving the precise localization of UAV images is crucial for enhancing their utility. Photogrammetry-based techniques, particularly bundle adjustment, serve as foundational methods for accurately determining the spatial coordinates of UAV images. The effectiveness of bundle adjustment is significantly influenced by the selection of input data, particularly the composition of overlapping image sets. The selection process of overlapping images significantly impacts both the accuracy of spatial coordinate determination and the computational efficiency of UAV image localization. Therefore, a strategic approach to this selection is crucial for optimizing the performance of bundle adjustment in UAV image processing. In this context, we propose an efficient methodology for determining overlapping image sets. The proposed method selects overlapping images based on image similarity, leveraging the complementary strengths of the bag of visual words and number of matches techniques. Essentially, our method achieves both high accuracy and high speed by utilizing a Bag of Visual Words for candidate selection and the number of matches for additional similarity assessment for overlapping image-set determination. We compared the performance of our proposed methodology with the conventional number of matches and bag-of-visual word-based methods for overlapping image-set determination. In the comparative evaluation, the proposed method demonstrated an average precision of 96%, comparable to that of the number of matches-based approach, while surpassing the 62% precision achieved by both bag-of-visual-word methods. Moreover, the processing time decreased by approximately 0.11 times compared with the number of matches-based methods, demonstrating relatively high efficiency. Furthermore, in the bundle adjustment results using image sets, the proposed method, along with the number of matches-based methods, showed reprojection error values of less than 1, indicating relatively high accuracy and contributing to the improvement in accuracy in estimating image positions.
A Hybrid Group-Based Food Recommender Framework for Handling Overlapping Memberships
Authors: Rais Rao Naveed Bin , Noman Muhammad , Khalid Osman , Khan Imran A.
Published: July 2024

Recommender systems (RSs) play a pivotal role in mitigating information overload by aiding individuals or groups in discovering relevant and personalized information. An individual’s food preferences may vary when dining with friends compared to dining with family. Most of the existing group RSs generally assume users to be associated with a single group. However, in real-world scenarios, a user can be part of multiple groups due to overlapping/diverse preferences. This raises several challenges for traditional RSs due to the inherent complexity of group memberships, degrading the effectiveness and accuracy of the recommendations. Computing user to group membership degrees is a complex task, and conventional methods often fall short in accurately capturing the varied preferences of individuals. To address these challenges, we propose an integrated two-stage group recommendation (ITGR) framework that considers users’ simultaneous memberships in multiple groups with conflicting preferences. We employ fuzzy C-means clustering along with collaborative filtering to provide a more flexible and precise approach to membership assignment. Group formation is carried out using similarity thresholds followed by deep neural collaborative filtering (DNCF) to generate the top-k items for each group. Experiments are conducted using a large-scale recipes’ dataset, and the results demonstrate that the proposed model outperforms traditional approaches in terms of group satisfaction, normalized discounted cumulative gain (NDCG), precision, recall, and F1-measure.
Data-Centric Solutions for Addressing Big Data Veracity with Class Imbalance, High Dimensionality, and Class Overlapping
Authors: Bolívar Armando , García Vicente , Alejo Roberto , Florencia-Juárez Rogelio , Sánchez J. Salvador
Published: July 2024

An innovative strategy for organizations to obtain value from their large datasets, allowing them to guide future strategic actions and improve their initiatives, is the use of machine learning algorithms. This has led to a growing and rapid application of various machine learning algorithms with a predominant focus on building and improving the performance of these models. However, this data-centric approach ignores the fact that data quality is crucial for building robust and accurate models. Several dataset issues, such as class imbalance, high dimensionality, and class overlapping, affect data quality, introducing bias to machine learning models. Therefore, adopting a data-centric approach is essential to constructing better datasets and producing effective models. Besides data issues, Big Data imposes new challenges, such as the scalability of algorithms. This paper proposes a scalable hybrid approach to jointly addressing class imbalance, high dimensionality, and class overlapping in Big Data domains. The proposal is based on well-known data-level solutions whose main operation is calculating the nearest neighbor using the Euclidean distance as a similarity metric. However, these strategies may lose their effectiveness on datasets with high dimensionality. Hence, the data quality is achieved by combining a data transformation approach using fractional norms and SMOTE to obtain a balanced and reduced dataset. Experiments carried out on nine two-class imbalanced and high-dimensional large datasets showed that our scalable methodology implemented in Spark outperforms the traditional approach.
Statistical Comparison of Time Series Models for Forecasting Brazilian Monthly Energy Demand Using Economic, Industrial, and Climatic Exogenous Variables
Authors: Serrano André Luiz Marques , Rodrigues Gabriel Arquelau Pimenta , Martins Patricia Helena dos Santos , Saiki Gabriela Mayumi , Filho Geraldo Pereira Rocha , Gonçalves Vinícius Pereira , Albuquerque Robson de Oliveira
Published: July 2024

Energy demand forecasting is crucial for effective resource management within the energy sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This study undertakes a comparative analysis of different forecasting models to predict future energy demand trends in Brazil, improve forecasting methodologies, and achieve sustainable development goals. The evaluation encompasses the following models: Seasonal Autoregressive Integrated Moving Average (SARIMA), Exogenous SARIMA (SARIMAX), Facebook Prophet (FB Prophet), Holt–Winters, Trigonometric Seasonality Box–Cox transformation, ARMA errors, Trend, and Seasonal components (TBATS), and draws attention to their respective strengths and limitations. Its findings reveal unique capabilities among the models, with SARIMA excelling in tracing seasonal patterns, FB Prophet demonstrating its potential applicability across various sectors, Holt–Winters adept at managing seasonal fluctuations, and TBATS offering flexibility albeit requiring significant data inputs. Additionally, the investigation explores the effect of external factors on energy consumption, by establishing connections through the Granger causality test and conducting correlation analyses. The accuracy of these models is assessed with and without exogenous variables, categorized as economical, industrial, and climatic. Ultimately, this investigation seeks to add to the body of knowledge on energy demand prediction, as well as to allow informed decision-making in sustainable energy planning and policymaking and, thus, make rapid progress toward SDG7 and its associated targets. This paper concludes that, although FB Prophet achieves the best accuracy, SARIMA is the most fit model, considering the residual autocorrelation, and it predicts that Brazil will demand approximately 70,000 GWh in 2033.
Bimatoprost Can Increase Growth and Density of Eyebrow Hair: A Prospective Study on a Group of Young Women
Authors: Załęcki Piotr , Skakowska Justyna , Nowicka Danuta
Published: July 2024

Bimatoprost is a prostaglandin analog used in cosmetic products designed to stimulate hair growth, including eyebrows. However, limited study-based evidence confirming its efficacy, safety, and patient satisfaction is available. The aim of this study was to investigate whether, and to what extent, bimatoprost affects the density and length of eyebrow hair in young women in comparison to sweet almond oil. The study group included 27 healthy women who used bimatoprost cosmetic preparation once daily for 5 weeks and then crossed over to use sweet almond oil once daily for 5 weeks. Bimatoprost preparation, in comparison to sweet almond oil, improved eyebrow density (70% vs. 30%; p = 0.003) and eyebrow hair elongation (59% vs. 26%; p = 0.014), but not eyebrow hair hydration (59% vs. 89%; p = 0.001) and hair darkness (22% vs. 11%; p = 0.278). The comfort of use was comparable for both preparations (63% vs. 67%; p = 0.996), but treatment satisfaction was significantly higher with bimatoprost (66% vs. 22%; p < 0.001). All reported adverse events were minor, transient, and resolved spontaneously. We conclude that the bimatoprost preparation was significantly more effective than sweet almond oil in improving the density and length of eyebrow hair, with a similar level of safety. Therefore, bimatoprost can be considered an ingredient in cosmetics designed to enhance eyebrow growth; however, further larger studies with extended follow-ups are needed.
An Automated Geographical Information System-Based Spatial Machine Learning Method for Leak Detection in Water Distribution Networks (WDNs) Using Monitoring Sensors
Authors: Elshazly Doha , Gawai Rahul , Ali Tarig , Mortula Md Maruf , Atabay Serter , Khalil Lujain
Published: July 2024

Pipe leakage in water distribution networks (WDNs) has been an emerging concern for water utilities worldwide due to its public health and economic significance. Not only does it cause significant water losses, but it also deteriorates the quality of the treated water in WDNs. Hence, a prompt response is required to avoid or minimize the eventual consequences. This raises the necessity of exploring the possible approaches for detecting and locating leaks in WDNs promptly. Currently, various leak detection methods exist, but they are not accurate and reliable in detecting leaks. This paper presents a novel GIS-based spatial machine learning technique that utilizes currently installed pressure, flow, and water quality monitoring sensors in WDNs, specifically employing the Geographically Weighted Regression (GWR) and Local Outlier Factor (LOF) models, based on a WDN dataset provided by our partner utility authority. In addition to its ability as a regression model for predicting a dependent variable based on input variables, GWR was selected to help identify locations on the WDN where coefficients deviate the most from the overall coefficients. To corroborate the GWR results, the Local Outlier Factor (LOF) is used as an unsupervised machine learning model to predict leak locations based on spatial local density, where locality is given by k-nearest neighbours. The sample WDN dataset provided by our utility partner was split into 70:30 for training and testing of the GWR model. The GWR model was able to predict leaks (detection and location) with a coefficient of determination (R2) of 0.909. The LOF model was able to predict the leaks with a matching of 80% with the GWR results. Then, a customized GIS interface was developed to automate the detection process in real-time as the sensor’s readings were recorded and spatial machine learning was used to process the readings. The results obtained demonstrate the ability of the proposed method to robustly detect and locate leaks in WDNs.
Concerning Transformations of Bases Associated with Unimodular diag(1, −1, −1)-Matrices
Authors: Shilin I. A. , Choi Junesang
Published: July 2024

Considering a representation space for a group of unimodular diag(1, −1, −1)-matrices, we construct several bases whose elements are eigenfunctions of Casimir infinitesimal operators related to a reduction in the group to some one-parameter subgroups. Finding the kernels of base transformation integral operators in terms of special functions, we consider the compositions of some of these transformations. Since composition is a ‘closed’ operation on the set of base transformations, we obtain some integral relations for the special functions involved in the above kernels.
Human Hepatobiliary Organoids: Recent Advances in Drug Toxicity Verification and Drug Screening
Authors: Fang Haoyu , Xu Haoying , Yu Jiong , Cao Hongcui , Li Lanjuan
Published: July 2024

Many drug and therapeutic modalities have emerged over the past few years. However, successful commercialization is dependent on their safety and efficacy evaluations. Several preclinical models are available for drug-screening and safety evaluations, including cellular- and molecular-level models, tissue and organoid models, and animal models. Organoids are three-dimensional cell cultures derived from primary tissues or stem cells that are structurally and functionally similar to the original organs and can self-renew, and they are used to establish various disease models. Human hepatobiliary organoids have been used to study the pathogenesis of diseases, such as hepatitis, liver fibrosis, hepatocellular carcinoma, primary sclerosing cholangitis and biliary tract cancer, as they retain the physiological and histological characteristics of the liver and bile ducts. Here, we review recent research progress in validating drug toxicity, drug screening and personalized therapy for hepatobiliary-related diseases using human hepatobiliary organoid models, discuss the challenges encountered in current research and evaluate the possible solutions.
A Shared Receptor Suggests a Common Ancestry between an Insecticidal Bacillus thuringiensis Cry Protein and an Anti-Cancer Parasporin
Authors: Bryce-Sharron Nicole , Nasiri Mojtaba , Powell Tom , West Michelle J. , Crickmore Neil
Published: July 2024

Cry toxins, produced by the bacterium Bacillus thuringiensis, are of significant agronomic value worldwide due to their potent and highly specific activity against various insect orders. However, some of these pore-forming toxins display specific activity against a range of human cancer cells whilst possessing no known insecticidal activity; Cry41Aa is one such toxin. Cry41Aa has similarities to its insecticidal counterparts in both its 3-domain toxic core structure and pore-forming abilities, but how it has evolved to target human cells is a mystery. This work shows that some insecticidal Cry toxins can enhance the toxicity of Cry41Aa against hepatocellular carcinoma cells, despite possessing no intrinsic toxicity themselves. This interesting crossover is not limited to human cancer cells, as Cry41Aa was found to inhibit some Aedes-active Cry toxins in mosquito larval assays. Here, we present findings that suggest that Cry41Aa shares a receptor with several insecticidal toxins, indicating a stronger evolutionary relationship than their divergent activities might suggest.
Importance of Circadian Rhythms in the Ocular Surface
Authors: Zhang Xiaozhao , Jie Ying
Published: July 2024

Circadian rhythms are a ubiquitous feature throughout the organism. Accumulating evidence suggests that the dysfunction of circadian rhythms due to genetic mutations or environmental factors contributes to the genesis and progress of multiple diseases. The physiological homeostasis of the ocular surface, like any other tissue or organ, is also orchestrated by circadian rhythms. In this review, we summarize the molecular clocks and the expression of clock-controlled genes in the mammalian ocular surface. Based on the circadian expression of these genes, we conclude the diurnal oscillations of cellular biological activities in the mammalian ocular surface. Moreover, we evaluate the factors entraining circadian oscillators in the ocular surface. Finally, we further discuss the latest development of the close correlation between circadian rhythms and ocular health. Briefly, this review aimed to synthesize the previous studies to aid in understanding the importance of circadian rhythms in the ocular surface and the possible opportunities for circadian rhythm-based interventional strategies to restore the homeostasis of the ocular surface.