Miracle-dz/UniFAR-FTUs huggingface dataset:
Peptidomic analysis of follicular fluid in patients with polycystic ovarian syndrome

Objective: The aim of this study was to analyze and compare the differential expression of peptides within the follicular fluid of polycystic ovary syndrome (PCOS) patients versus normal women by using peptidomics techniques. The underlying mechanisms involved in PCOS pathogenesis will be explored, together with screening and identification of potential functional peptides via bioinformatics analysis. Materials and methods: A total of 12 patients who underwent in vitro fertilization and embryo transfer (IVF-ET) at the Reproductive Medicine Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from 1 September 2022 to 1 November 2022 were included in this study. The follicular fluid of PCOS patients (n = 6) and normal women (n = 6) were collected. The presence and concentration differences of various peptides were detected by the LC-MS/MS method. GO and KEGG analysis were performed on the precursor proteins of the differentially-expressed peptides, and protein network interaction analysis was carried out to identify functionally-relevant peptides among the various peptides. Results: A variety of peptides within the follicular fluid of PCOS versus normal patients were detected by peptidomics techniques. Altogether, 843 upregulated peptides and 236 downregulated peptides were detected (absolute fold change ≥2 and p < 0.05). Of these, 718 (718 = 488 + 230) peptides were only detected in the PCOS group, while 205 (205 = 174 + 31) were only detected in the control group. Gene Ontology enrichment and pathway analysis were performed to characterize peptides through their precursor proteins. We identified 18 peptides from 7 precursor proteins associated with PCOS, and 4 peptide sequences were located in the functional domains of their corresponding precursor proteins. Conclusion: In this study, differences in the follicular development of PCOS versus normal patients were revealed from the polypeptidomics of follicular development, which thus provided new insights for future studies on the pathological mechanisms of PCOS development.
In-silico study of antisense oligonucleotide antibiotics

Background The rapid emergence of antibiotic-resistant bacteria directly contributes to a wave of untreatable infections. The lack of new drug development is an important driver of this crisis. Most antibiotics today are small molecules that block vital processes in bacteria. To optimize such effects, the three-dimensional structure of targeted bacterial proteins is imperative, although such a task is time-consuming and tedious, impeding the development of antibiotics. The development of RNA-based therapeutics has catalyzed a new platform of antibiotics—antisense oligonucleotides (ASOs). These molecules hybridize with their target mRNAs with high specificity, knocking down or interfering with protein translation. This study aims to develop a bioinformatics pipeline to identify potent ASO targets in essential bacterial genes. Methods Three bacterial species (P. gingivalis, H. influenzae, and S. aureus) were used to demonstrate the utility of the pipeline. Open reading frames of bacterial essential genes were downloaded from the Database of Essential Genes (DEG). After filtering for specificity and accessibility, ASO candidates were ranked based on their self-hybridization score, predicted melting temperature, and the position on the gene in an operon. Enrichment analysis was conducted on genes associated with putative potent ASOs. Results A total of 45,628 ASOs were generated from 348 unique essential genes in P. gingivalis. A total of 1,117 of them were considered putative. A total of 27,273 ASOs were generated from 191 unique essential genes in H. influenzae. A total of 847 of them were considered putative. A total of 175,606 ASOs were generated from 346 essential genes in S. aureus. A total of 7,061 of them were considered putative. Critical biological processes associated with these genes include translation, regulation of cell shape, cell division, and peptidoglycan biosynthetic process. Putative ASO targets generated for each bacterial species are publicly available here: https://github.com/EricSHo/AOA. The results demonstrate that our bioinformatics pipeline is useful in identifying unique and accessible ASO targets in bacterial species that post major public health issues.
Developing Capabilities for Sustainable Business Models –Exploring Project Maturity for Innovation Processes

Companies must cultivate new dynamic capabilities to meet the demands for sustainable solutions in an uncertain and dynamic world. This longitudinal case study explores the significance of project maturity as a critical capability within complex innovation processes for developing sustainable business models. The purpose of the study is to gain a better understanding of the central factors companies encounter when making efforts to build sustainable business models through innovation projects. Tracking a market-leading company's journey from ideation to implementation over an extended period, this study focuses on creating a sustainable business emphasising waste reduction, heightened customer satisfaction, and profitability. Key insights emerge through qualitative methods, including interviews, observations, and document analysis. The findings highlight the pivotal role of project maturity in innovation projects centred around sustainable value propositions. Project maturity is salient in creating an autonomous unit, fostering agility, and promoting open collaboration. It encompasses organisational ambidexterity and collaborative engagement with vital stakeholders. Furthermore, proficient project managers well-versed in agile project management and innovation processes and contextual resolution emerge as crucial drivers in innovation projects aimed at developing capabilities for sustainable business models. By tailoring project maturity to the specific needs of each project and integrating agile methodologies, organisations can forge the necessary capabilities for crafting sustainable business models. Additionally, dynamic capabilities can be cultivated by aligning projects with the overall business strategy and implementing practices that facilitate continuous learning and improvement. This study underscores the importance of project maturity within innovation processes and its role in creating profitable and sustainable business models by developing new dynamic capabilities. The research findings offer valuable insights for businesses seeking to design effective innovation processes supporting sustainable business model realization.
A method for detecting parallelism and flatness of truss tracks

As a large structure, the truss track will inevitably wear and deform during long-term operation, which can negatively impact construction safety and quality. Therefore, it is necessary to safely, quickly and accurately detect the parallelism and flatness of the truss track. This paper proposes a new method for detecting parallelism and flatness of truss track based on point cloud data of 3D laser scanner. A corresponding data post-processing system is developed based on the method proposed above. Finally, the proposed method and system have been successfully applied to an actual detecting project of truss track in a large-scale iron and steel enterprise. The results show that the new method proposed in this paper is effective and feasible.
Transcriptome Profiling Provides Insights into the Early Development of Tiller Buds in High- and Low-Tillering Orchardgrass Genotypes

Orchardgrass (Dactylis glomerata L.) is among the most economically important perennial cool-season grasses, and is considered an excellent hay, pasture, and silage crop in temperate regions worldwide. Tillering is a vital feature that dominates orchardgrass regeneration and biomass yield. However, transcriptional dynamics underlying early-stage bud development in high- and low-tillering orchardgrass genotypes are unclear. Thus, this study assessed the photosynthetic parameters, the partially essential intermediate biomolecular substances, and the transcriptome to elaborate the early-stage profiles of tiller development. Photosynthetic efficiency and morphological development significantly differed between high- (AKZ-NRGR667) and low-tillering genotypes (D20170203) at the early stage after tiller formation. The 206.41 Gb of high-quality reads revealed stage-specific differentially expressed genes (DEGs), demonstrating that signal transduction and energy-related metabolism pathways, especially photosynthetic-related processes, influence tiller induction and development. Moreover, weighted correlation network analysis (WGCNA) and functional enrichment identified distinctively co-expressed gene clusters and four main regulatory pathways, including chlorophyll, lutein, nitrogen, and gibberellic acid (GA) metabolism pathways. Therefore, photosynthesis, carbohydrate synthesis, nitrogen efficient utilization, and phytohormone signaling pathways are closely and intrinsically linked at the transcriptional level. These findings enhance our understanding of tillering in orchardgrass and perennial grasses, providing a new breeding strategy for improving forage biomass yield.
FORMULATION, AND CHARACTERIZATION OF NANOSTRUCTURED LIPID CARRIER (NLC) CONTAINING QUERCETIN

Quercetin, like triterpenoids, decreases blood glucose levels. Quercetin has several limitations including low solubility, low percutaneous permeability, and low bioavailability. The formulation of quercetin preparations in a Nanostructured Lipid Carrier (NLC) system is one solution to increase its solubility. The quercetin NLC system was successfully formulated by the high shear homogenization method at a speed of 6000 rpm. The solid lipid glyceryl monostearate and sunflower oil play important roles in the formation of NLC. The physicochemical characteristics examined in this study included the particle size, dispersion, viscosity, pH, and entrapment efficiency. The particle size of NLC quercetin ranges from 22.98 ± 0.008 nm to 41.04 ± 0.082 nm, with p-values < 0.05. The dispersion power of quercetin NLC ranges from 5.12 ± 0.11 cm to 7.01 ± 0.28 cm, p values < 0.05. The resulting pH range is 7.3 ± 0.01 to 7.4 ± 0.01, and the resulting viscosity is 223.7 ± 9.8 cps to 492.0 ± 0.0 cps. Entrapment efficiency range of (62.20 ± 0.245)% to (86.17 ± 0.287)% ( p < 0.05). The ratio of solid lipid concentration to liquid lipid concentration in NLC quercetin has a significant effect on particle size, dispersion, and entrapment efficiency. Keywords: Nanostructured Lipid Carrier, Quercetin, Lipid, Glyceryl Monosterate, Sunflower Oil
Quantum interferometric power versus quantum correlations in a graphene layer system with a scattering process under thermal noise

Cutting-edge quantum processing technology is currently exploring the remarkable electronic properties of graphene layers, such as their high mobility and thermal conductivity. Our research is dedicated to investigating the behavior of quantum resources within a graphene layer system with a scattering process, specifically focusing on quantum interferometric power (QIP) and quantum correlations, while taking into account the influence of thermal noise. To quantify these correlations, we employ measures like local quantum uncertainty (LQU) and logarithmic negativity (LN). We examine how factors like temperature, inter-valley scattering processes strength, and other system parameters affect both QIP and quantum correlations. Our results reveal that higher temperatures lead to a reduction in QIP and non-classical correlations within graphene layers. Moreover, it is noteworthy that QIP and LQU respond similarly to changes in temperature, whereas LN is more sensitive to these variations. By optimizing system parameters such as band parameter, wavenumber operators and scattering processes strength, we can mitigate the impact of thermal noise and enhance the quantum advantages of graphene-based quantum processing
Low‐cost air quality monitoring networks for long‐term field campaigns: A review

The application of low‐cost air quality monitoring networks has substantially grown over the last few years, following the technological advances in the production of cheap and portable air pollution sensors, thus potentially greatly increasing the limited spatial information on air quality conditions provided by traditional stations. However, the use of low‐cost air quality sensors still presents many limitations, mostly related to the reliability of their measurements. Despite the increasing number of papers focusing on these issues, some of the challenges connected to the use of low‐cost air quality sensors are still poorly investigated and understood, considering in particular those related to long‐term applications of low‐cost air quality networks and their integration within the reference air quality monitoring system. The present review aims at filling this gap, by analysing the characteristics of low‐cost air quality monitoring networks that were run across long‐term field campaigns, including their geographical location, the pollutants monitored, the type and number of stations employed, and the length of the field campaign, with a particular attention on assessing the aims for their deployment and on the evaluation of their integration within official air quality monitoring networks. Moreover, a critical analysis of the most insightful suggestions and recommendations delivered in the literature, as well as of the relevant critical issues, is presented, highlighting still open research areas and outlining future challenges.
Advisor compensation

Using the 2015 National Financial Capability Study Investor Survey, this study uses agency theory to inform an exploration of characteristics associated with knowing how one’s financial advisor/broker is compensated. This study further examines how individuals who do know the compensation method choose between financial advisors with different compensation models. Proposed changes in the financial advising regulatory landscape, as well as the pending changes to the CFP Board Standards of Professional Conduct, brings greater emphasis on understanding consumers’ advisor compensation preferences. Primary results indicate that clients who place importance on fees, that are more knowledgeable about diversification, and that perform background checks are more likely to know compensation methods. A follow-up analysis reveals distinct differences between individuals that used each model, but also provide some mixed results, indicating that clients may not fully understand the compensation paid to their advisors. Discussion and implications related to these results are provided.
Preclinical Models and Technologies in Glioblastoma Research: Evolution, Current State, and Future Avenues

Glioblastoma is the most common malignant primary central nervous system tumor and one of the most debilitating cancers. The prognosis of patients with glioblastoma remains poor, and the management of this tumor, both in its primary and recurrent forms, remains suboptimal. Despite the tremendous efforts that are being put forward by the research community to discover novel efficacious therapeutic agents and modalities, no major paradigm shifts have been established in the field in the last decade. However, this does not mirror the abundance of relevant findings and discoveries made in preclinical glioblastoma research. Hence, developing and utilizing appropriate preclinical models that faithfully recapitulate the characteristics and behavior of human glioblastoma is of utmost importance. Herein, we offer a holistic picture of the evolution of preclinical models of glioblastoma. We further elaborate on the commonly used in vitro and vivo models, delving into their development, favorable characteristics, shortcomings, and areas of potential improvement, which aids researchers in designing future experiments and utilizing the most suitable models. Additionally, this review explores progress in the fields of humanized and immunotolerant mouse models, genetically engineered animal models, 3D in vitro models, and microfluidics and highlights promising avenues for the future of preclinical glioblastoma research.
A Framework of Moving Behavior Modeling in the Maritime Surveillance

Due to requirements of homeland security, maritime traffic surveillance becomes an important research area. An automated solution to analyze the collected data and summarize them into a model is helpful for objects’ movement behavior analysis in maritime domain. However, it is a challenging problem to develop a model that can precisely capture the objects’ movement behavior due to objects would seldom exactly repeat the same moving path in the maritime space, a free moving space. In this paper, based on multiple vessels’ trajectories from Automatic Identification System (AIS), we aim to mine trajectory patterns and profile them into a model, called TMP model (Trajectory Pattern Mining and Profiling model). We conduct experiments on real data and experimental results demonstrate that TMP model can effectively and precisely reflect the movement behaviors in the maritime surveillance.
Large Divergence of Satellite Monitoring of Diffuse Radiation Effect on Ecosystem Water‐Use Efficiency

Water‐use efficiency (WUE), defined as the ratio of gross primary productivity (GPP) and evapotranspiration (ET), is a key indicator of the coupling of carbon and water cycles in terrestrial ecosystems. Diffuse radiation significantly affects WUE as diffuse radiation has stronger fertilization effects on GPP than ET. Remote sensing data‐driven (RS) models were widely used to estimate WUE. However, the performance of RS models in simulating diffuse radiation effect on WUE is poorly understood. We used GPP and ET products from MODIS, PML, BESS, and GLASS to explore the response of WUE to diffuse radiation across different vegetation types. We found that there was a large divergence among the RS models in estimating the response of WUE to FDP. PML model performed better than other RS models in simulating diffuse radiation effect on WUE. This research has significant implications for improving model simulations and understanding global carbon and water cycles.
SIRT1 Prevents R-Loops during Chronological Aging by Modulating DNA Replication at rDNA Loci

In metazoans, the largest sirtuin, SIRT1, is a nuclear protein implicated in epigenetic modifications, circadian signaling, DNA recombination, replication, and repair. Our previous studies have demonstrated that SIRT1 binds replication origins and inhibits replication initiation from a group of potential initiation sites (dormant origins). We studied the effects of aging and SIRT1 activity on replication origin usage and the incidence of transcription–replication collisions (creating R-loop structures) in adult human cells obtained at different time points during chronological aging and in cancer cells. In primary, untransformed cells, SIRT1 activity declined and the prevalence of R-loops rose with chronological aging. Both the reduction in SIRT1 activity and the increased abundance of R-loops were also observed during the passage of primary cells in culture. All cells, regardless of donor age or transformation status, reacted to the short-term, acute chemical inhibition of SIRT1 with the activation of excessive replication initiation events coincident with an increased prevalence of R-loops. However, cancer cells activated dormant replication origins, genome-wide, during long-term proliferation with mutated or depleted SIRT1, whereas, in primary cells, the aging-associated SIRT1-mediated activation of dormant origins was restricted to rDNA loci. These observations suggest that chronological aging and the associated decline in SIRT1 activity relax the regulatory networks that protect cells against excess replication and that the mechanisms protecting from replication–transcription collisions at the rDNA loci manifest as differentially enhanced sensitivities to SIRT1 decline and chronological aging.
Cities as Solitons: Analytic Solutions to Models of Agglomeration and Related Numerical Approaches

Economic geography equilibria that represent spontaneous agglomeration in a featureless underlying geographic space have been solved only numerically, and the resulting spatial configurations were symmetric. This paper introduces a method of obtaining analytic solutions to similar models. In the case of continuum space, the multi-city equilibria are again symmetric. However, by working in discrete space it is possible to generate stable equilibria with multiple cities of various population levels and spatial extent, asymmetrically distributed across space. The properties of these equilibria may be understood in terms of deterministic chaos theory. The analytic approach makes it possible to find all equilibria, stable and unstable. There are two qualitative predictions that may be empirically tested: (1) the stability of an isolated city does not depend on its precise position, and (2) if two cities are too close to each other, the configuration becomes unstable and the space between the cities is filled with newcomers, turning the two cities into a megalopolis. In addition, the stable equilibria of the model are compared to population density in northern Chile. It is possible to find equilibria that match the real-world population density profile with correlation of 0.9 or more.
ANALYSIS OF STRESS AMONG THE FEMALE EMPLOYEES WITH CHILDREN IN THE UNIVERSITY OF CAPE COAST: IMPLICATIONS FOR MANAGEMENT PRACTICES

The study investigated the sources, effects and coping strategies of stress adopted by female employees with children in the University of Cape Coast. A descriptive study design was employed in carrying out the study. Two hundred and four (204) respondents were sampled out of the 431 female employees with children. The instrument used was a constructed questionnaire. The results revealed that demands from husbands, children and thinking of promotional issues were some of the stressors that confronted the respondents. The major effects of stress among the respondents were their inability to plan well and lack of concentration on household chores. The result showed that the most prevailing coping strategy adopted by the respondents was engaging in conversation with friends and family members as well as getting assistance from colleagues and house helps. It was concluded that female employees with children in the University of Cape Coast go through stress which emanates from different sources. Some of the recommendations were that management of the University should educate employees on appropriate strategies to cope with their stress and could be done through seminars, conferences and workshops on coping strategies of stress. Key Words: work stress, coping strategies, female employees, university of cape coast