bluuebunny/crossref_metadata_2025_split huggingface dataset:
The positive impact of journaling on adolescents with cystic fibrosis
Authors: Kow Sean , Rieger Brenda , Morse Kimberly , Keens Thomas , Wu Susan 
Published: September 2023

AbstractBackgroundIndividuals with cystic fibrosis (CF) often have psychological difficulties on top of their medically complex care, such as anxiety, depression, and medical mistrust. These have been shown to be associated with worse adherence, pulmonary function test results, and other health outcomes. In this pilot trial, we implemented a journaling program based on narrative therapy methodology to improve mental and physical health outcomes for individuals with CF.MethodsEight adolescents aged 12–17 with a confirmed diagnosis of CF followed in a single center CF clinic were emailed weekly journaling prompts that explored topics like treatment adherence, feeling different with CF, anxiety, depression, and interpersonal relationships. Subjects completed surveys about their experience with the writing assignment and measures of wellness including the Pediatric Symptom Checklist (PSC‐17) and baseline health data was collected from the electronic medical records.ResultsThe average score for the PSC‐17 decreased by 5.5 points, and fell to less than 28 (mean 23.5, SD 12.2), which is the cutoff for screening positive for behavioral or emotional problems. Participants reported the study was enjoyable and had improvement in feelings of anxiety/depression. 100% of participants responded “Strongly Agree” to the statement “I recommend other people with CF to write about the topics from this study.”ConclusionsThe journaling intervention for individuals with CF was feasible and well received. Initial results show improvement in PSC‐17 and other well‐being measures. Further studies are needed to evaluate the impact of journaling on mental health and disease outcomes.
A spectrophotometric trimethylamine monooxygenase assay
Authors: Maurya Shiwangi , Singh Abhishek , Ramanathan Gurunath 
Published: September 2023

AbstractTrimethylamine monooxygenase (Tmm, EC‐1.14.13.148) belongs to the family of flavin‐containing monooxygenases that oxidize trimethylamine into trimethylamine‐N‐oxide (TMAO). Conventional methods for assaying Tmm are accurate over a narrow range of substrate/product concentrations. Here we report a TMAO‐specific enzymatic assay for Tmm using polyallylamine hydrochloride (PAHCl)‐capped MnO2 nanoparticles (PAHCl@MnO2). We achieved TMAO specificity using iodoacetonitrile to remove interfering trimethylamine. The change in the concentration of TMAO is measured by observing the difference in the absorbance of 3,3′,5,5′‐tetramethylbenzidine (TMB) at 650 nm. The assay is tolerant to several interfering metal ions and other compounds. This method is more accessible and reliable than currently known methods. The limit of detection (LOD) and limit of quantitation (LOQ) are 1 μM and 10 μM, respectively, for direct TMAO measurement.
Fast forward? Time compression attempts and post‐IPO performance
Authors: Henderson Andrew D. , Graebner Melissa E. 
Published: September 2023

AbstractResearch SummaryAn initial public offering (IPO) expands a firm's access to funding and enables future‐oriented strategic investments. Though aggressive investments can open new opportunities and speed the construction of relative advantage, this aggression risks time compression diseconomies and maladaptive learning from rushed experiences. We propose a firm's investment tempo and industry velocity combine to affect the trajectory of a firm's post‐IPO performance. Agent‐based simulation modeling suggested that aggressive, up‐tempo investment sped the construction of relative advantage in low‐velocity industries. Empirical analyses of multiyear post‐IPO windows in real firms supported this. In contrast, simulations and analyses of real firms suggested up‐tempo investment was maladaptive in high‐velocity industries as the combination of fast investment and fast industry change was often more than boundedly rational agents could cognitively handle.Managerial SummaryCongratulations! By taking your firm public, you can now finance strategic investments in R&D and CAPX that would have been impossible when your company was private. Rapid investment can open new opportunities, sharpen your firm's skills, and build competitive advantage. However, rapid investment is risky because you can waste time recovering from hastily made mistakes and learn bad habits when new experiences arrive too quickly for managers to assimilate. We found the relationship between investment speed and firm profitability depended on industry velocity. Counterintuitively, rapid investment was ill advised in high‐velocity industries because the combination of fast investment and fast industry change was often more than managers could cognitively handle. In contrast, rapid investment worked well in low‐velocity industries, which placed fewer strains on decision makers.
Machine Learning Reinforced Genetic Algorithm for Massive Targeted Discovery of Selectively Cytotoxic Inorganic Nanoparticles
Authors: Jyakhwo Susan , Serov Nikita , Dmitrenko Andrei , Vinogradov Vladimir V. 
Published: September 2023

AbstractNanoparticles (NPs) have been employed as drug delivery systems (DDSs) for several decades, primarily as passive carriers, with limited selectivity. However, recent publications have shed light on the emerging phenomenon of NPs exhibiting selective cytotoxicity against cancer cell lines, attributable to distinct metabolic disparities between healthy and pathological cells. This study revisits the concept of NPs selective cytotoxicity, and for the first time proposes a high‐throughput in silico screening approach to massive targeted discovery of selectively cytotoxic inorganic NPs. In the first step, this work trains a gradient boosting regression model to predict viability of NP‐treated cell lines. The model achieves mean cross‐validation (CV) Q2 = 0.80 and root mean square error (RMSE) of 13.6. In the second step, this work develops a machine learning (ML) reinforced genetic algorithm (GA), capable of screening >14 900 candidates/min, to identify the best‐performing selectively cytotoxic NPs. As proof‐of‐concept, DDS candidates for the treatment of liver cancer are screened on HepG2 and hepatocytes cell lines resulting in Ag NPs with selective toxicity score of 42%. This approach opens the door for clinical translation of NPs, expanding their therapeutic application to a wider range of chemical space of NPs and living organisms such as bacteria and fungi.
Anisotropic Amorphization and Phase Transition in Na2Ti3O7 Anode Caused by Electron Beam Irradiation
Authors: Cheng Lixun , Shen Yaoling , Nan Pengfei , Wu Chuanqiang , Tai Yilin , Luo Xiaonan , Zhang YongSheng , Ge Binghui 
Published: September 2023

AbstractNa2Ti3O7 is considered one of the most promising anode materials for sodium ion batteries due to its superior safety, environmental friendliness, and low manufacturing cost. However, its structural stability and reaction mechanism still have not been fully explored. As the electron beam irradiation introduces a similar impact on the Na2Ti3O7 anode as the extraction of Na+ ions during the battery discharge process, the microstructure evolution of the materials is investigated by advanced electron microscopy techniques at the atomic scale. Anisotropic amorphization is successfully observed. Through the integrated differential phase contrast‐scanning transmission electron microscopy technique and density functional theory calculation, a phase transition pathway involving a new phase, Na2Ti24O49, is proposed with the reduction of Na atoms. Additionally, it is found that the amorphization is dominated by the surface energy and electron dose rate. These findings will deepen the understanding of structural stability and deintercalation mechanism of the Na2Ti3O7 anode, providing new insight into exploring the failure mechanism of electrode materials.
Engineering the Physical Microenvironment into Neural Organoids for Neurogenesis and Neurodevelopment
Authors: Li Minghui , Sun Heng , Hou Zongkun , Hao Shilei , Jin Liang , Wang Bochu 
Published: September 2023

AbstractUnderstanding the signals from the physical microenvironment is critical for deciphering the processes of neurogenesis and neurodevelopment. The discovery of how surrounding physical signals shape human developing neurons is hindered by the bottleneck of conventional cell culture and animal models. Notwithstanding neural organoids provide a promising platform for recapitulating human neurogenesis and neurodevelopment, building neuronal physical microenvironment that accurately mimics the native neurophysical features is largely ignored in current organoid technologies. Here, it is discussed how the physical microenvironment modulates critical events during the periods of neurogenesis and neurodevelopment, such as neural stem cell fates, neural tube closure, neuronal migration, axonal guidance, optic cup formation, and cortical folding. Although animal models are widely used to investigate the impacts of physical factors on neurodevelopment and neuropathy, the important roles of human stem cell‐derived neural organoids in this field are particularly highlighted. Considering the great promise of human organoids, building neural organoid microenvironments with mechanical forces, electrophysiological microsystems, and light manipulation will help to fully understand the physical cues in neurodevelopmental processes. Neural organoids combined with cutting‐edge techniques, such as advanced atomic force microscopes, microrobots, and structural color biomaterials might promote the development of neural organoid‐based research and neuroscience.
The Importance of Dean Flow in Microfluidic Nanoparticle Synthesis: A ZIF‐8 Case Study
Authors: Yu Xiangjiang , Andreo Jacopo , Walden Madeline , del Campo Javier F. , Basabe‐Desmonts Lourdes , Benito‐Lopez Fernando , Burg Thomas P. , Wuttke Stefan 
Published: September 2023

AbstractThe Dean Flow, a physics phenomenon that accounts for the impact of channel curvature on fluid dynamics, has great potential to be used in microfluidic synthesis of nanoparticles. This study explores the impact of the Dean Flow on the synthesis of ZIF‐8 particles. Several variables that influence the Dean Equation (the mathematical expression of Dean Flow) are tested to validate the applicability of this expression in microfluidic synthesis, including the flow rate, radius of curvature, channel cross sectional area, and reagent concentration. It is demonstrated that the current standard of reporting, providing only the flow rate and crucially not the radius of curvature, is an incomplete description that will invariably lead to irreproducible syntheses across different laboratories. An alternative standard of reporting is presented and it is demonstrated how the sleek and simple math of the Dean Equation can be used to precisely tune the final dimensions of high quality, monodisperse ZIF‐8 nanoparticles between 40 and 700 nm.
IMDAC: A robust intelligent software defect prediction model via multi‐objective optimization and end‐to‐end hybrid deep learning networks
Authors: Zhu Kun , Zhang Nana , Jiang Changjun , Zhu Dandan 
Published: September 2023

AbstractSoftware defect prediction (SDP) aims to build an effective prediction model for historical defect data from software repositories by some specialized techniques or algorithms, and predict the defect proneness of new software modules. Nevertheless, the complex internal intrinsic structure hidden behind the defect data makes it challenging for the built prediction model to capture the most expressive defect feature representations, and largely limits the SDP performance. Fortunately, artificial intelligence is interacting closely with humans and provides powerful intelligent technical support for addressing these SDP issues. In this article, we propose a robust intelligent SDP model called IMDAC based on deep learning and soft computing techniques. This model has three main advantages: (1) an effective deep generative network—InfoGAN (information maximizing GANs) is employed to conduct data augmentation, namely generating sufficient defect instances and achieving defect class balance simultaneously. (2) Select the fewest representative feature subset for the minimum error via an advanced multi‐objective optimization approach—MSEA (multi‐stage evolutionary algorithm). (3) Build a powerful end‐to‐end deep defect predictor by hybrid deep learning techniques—DAE (Denoising AutoEncoder) and CNN (convolutional neural network), which can not only reconstruct a clean “repaired” input with strong robustness and generalization capabilities via DAE, but also learn the abstract deep semantic features with strong discriminating capability via CNN. Experimental results verify the superiority and robustness of the IMDAC model across 15 software projects.
Appreciating systems changes via multiparadigm inquiry: Architectural design, ecological anthropology, Classical Chinese Medicine and systems rhythms
Authors: Ing David 
Published: September 2023

AbstractIn which ways is the subject of systems change(s), as a first‐class concept, distinct from a reduction into (i) systems and (ii) changes? For practice, theory and methods to be authentically rigourous, the philosophy underlying an approach to systems changes can be explicated. Through an appreciative systems framework, presumptions are surfaced as to (i) what are and are not systems changes; (ii) when, where and for whom, systems changes are prioritized for attention; and (iii) how systems changes should be addressed. Philosophies of (i) architectural design, (ii) ecological anthropology, (iii) Classical Chinese Medicine and (iv) rhythms are explored through multiparadigm inquiry and open theorizing. The resulting influence of these four philosophies is considered, leading to a philosophy of systems rhythms more explicitly proposed as a foundation on which to approach systems changes.
Ecological characterization of 175 low‐pathogenicity avian influenza viruses isolated from wild birds in Mongolia, 2009–2013 and 2016–2018
Authors: Barkhasbaatar Ariunbaatar , Gilbert Martin , Fine Amanda E. , Shiilegdamba Enkhtuvshin , Damdinjav Batchuluun , Buuveibaatar Bayarbaatar , Khishgee Bodisaikhan , Johnson Christine K. , Leung Connie Y. H. , Ankhanbaatar Ulaankhuu , Purevtseren Dulam , Tuttle James M. , Mazet Jonna A. K. , Peiris Joseph S. Malik , Jambal Losolmaa , Shatar Munkhduuren , Sukhbaatar Tuvshintugs , Olson Sarah H. 
Published: September 2023

AbstractBackgroundSince 2005, highly pathogenic avian influenza A H5N1 viruses have spread from Asia worldwide, infecting poultry, humans and wild birds. Subsequently, global interest in avian influenza (AI) surveillance increased.ObjectivesMongolia presents an opportunity to study viruses in wild birds because the country has very low densities of domestic poultry and supports large concentrations of migratory water birds.MethodsWe conducted AI surveillance in Mongolia over two time periods, 2009–2013 and 2016–2018, utilizing environmental fecal sampling. Fresh fecal samples were collected from water bird congregation sites. Hemagglutinin (HA) and neuraminidase (NA) subtypes of positive samples were identified through viral isolation or molecular assays, with pathogenicity determined by HA subtype or sequencing the HA cleavage site.ResultsA total of 10,222 samples were collected. Of these, 7,025 fecal samples were collected from 2009 to 2013, and 3,197 fecal samples were collected from 2016 to 2018. Testing revealed 175 (1.7%) positive samples for low‐pathogenicity influenza A, including 118 samples from 2009 to 2013 (1.7%) and 57 samples from 2016 to 2018 (1.8%). HA and NA subtyping of all positives identified 11 subtypes of HA and nine subtypes of NA in 29 different combinations. Within periods, viruses were detected more frequently during the fall season than in the early summer.ConclusionMongolia's critical wild bird habitat is positioned as a crossroad of multiple migratory flyways. Our work demonstrates the feasibility of using an affordable environmental fecal sampling approach for AI surveillance and contributes to understanding the prevalence and ecology of low‐pathogenicity avian influenza viruses in this important location, where birds from multiple flyways mix.
Cross‐cultural adaptation and validation of the KOOS, JR questionnaire for assessing knee osteoarthritis in Spanish‐speaking patients
Authors: Guiloff Rodrigo , Iñiguez Magaly , Prado Tomás , Figueroa Francisco , Olavarría Nicolás , Carrasco Eduardo , Ergas Enrique , Salgado Martín , Lyman Stephen 
Published: September 2023

AbstractPurposeThe present study aims to translate, adapt and validate a Spanish version of the Knee Injury and Osteoarthritis Outcome Score, Joint Replacement (KOOS, JR), including a reliability and validity analysis in patients with knee osteoarthritis (OA).MethodsThis study conducted a prospective validation study following the six stages of the “Guidelines for the Process of Cross‐Cultural Adaptation of Self‐Report Measures”. Psychometric testing was conducted in patients with knee osteoarthritis. Subjects answered the Spanish KOOS, JR (S‐KOOS, JR) and a validated Spanish Oxford Knee Score (S‐OKS). Retest was conducted at 10 days. Acceptability, floor and ceiling effect, internal consistency (Cronbach’s α), reproducibility (mixed‐effect model coefficient [MEMC]) and construct validity (Spearman’s correlation; p = 0.05) were assessed.ResultsForty‐one patients (mean age: 65.6 ± 5.39; 48.8% female) participated in the study. All patients (100%) answered both scores during the first assessment and 38 (92.7%) during the second assessment. All patient‐reported outcomes measures were answered completely (100%). The S‐KOOS, JR resulted in 100% acceptability when answered. There were no ceiling or floor effects detected. The Cronbach’s α for the S‐KOOS, JR was 0.927 and its MEMC was 0.852 (CI 95% 0.636–1.078). The Spearman’s correlation between the S‐KOOS, JR and the S‐OKS was 0.711 (CI 0.345–0.608; p < 0.001) and 0.870 (CI 0.444–0.651; p < 0.001) for the first and second assessments, respectively.ConclusionThe S‐KOOS, JR has very high internal consistency and reproducibility, with a high correlation with the S‐OKS; it is a reliable and valid instrument for characterising Spanish‐speaking patients suffering from knee OA.Level of evidenceIV.
Flavobacterium okayamense sp. nov. isolated from surface seawater
Authors: Kitahara Kei , Muzembo Basilua Andre , Morohoshi Sho , Kunihiro Tadao , Tazato Nozomi , Ohno Ayumu , Uesaka Kazuma , Taniguchi Makoto , Miyoshi Shin-ichi 
Published: September 2023

AbstractStrain KK2020170T, a Gram-stain negative, yellow colony-forming bacterium, was isolated from surface seawater sampled in Kojima Bay, Okayama, Japan. Phylogenetic analysis based on the 16S rRNA gene revealed that strain KK2020170T belongs to the genus Flavobacterium, with Flavobacterium haoranii LQY-7T (98.1% similarity) being its closest relative, followed by Flavobacterium sediminis MEBiC07310T (96.9%) and Flavobacterium urocaniciphilum YIT 12746T (96.0%). Whole-genome shotgun sequencing showed that strain KK2020170T, when paralleled with F. haoranii LQY-7 T, had 81.3% average nucleotide identity, and 24.6% in silico DNA–DNA hybridization values, respectively. The DNA G + C content of strain KK2020170T was 31.1 mol%. The most abundant fatty acids (> 10%) of strain KK2020170T were iso-C15: 0, iso-C17: 0 3-OH and iso-C15: 1 G. The dominant respiratory quinone of the strain was menaquinone MK-6. Based on the phylogenetic and phenotypic analysis results, we propose that strain KK2020170T represents a novel species, for which the name Flavobacterium okayamense sp. nov. has been proposed. The type strain is KK2020170T (= ATCC TSD-280 T = NBRC 115344 T).
Disparities in paediatric radiology research publications from low- and lower middle-income countries: a time for change
Authors: Offiah Amaka C. , Atalabi Omolola M. , Epelman Monica , Khanna Geetika 
Published: September 2023

AbstractThe positive impact of diversity on health research and outcomes is well-recognised and widely published. Despite this, published evidence shows that at every step of the research pathway, issues of equity, diversity and inclusion (EDI) arise. There is evidence of a lack of diversity within research teams, in the research questions asked/research participants recruited, on grant review/funding panels, amongst funded researchers and on the editorial boards and reviewer pools of the journals to which results are submitted for peer-reviewed publication. Considering the journal PediatricRadiology, while its editorial board of 92 members has at least one member affiliated to a country in every region of the world, the majority are in North America (n=52, 57%) and Europe (n=30, 33%) and only two (2%) are affiliated to institutions in a lower middle-income country (LMIC) (India, Nigeria), with one (1%) affiliated to an institution in an upper middle-income country (UMIC) (Peru) and none in a low-income country (LIC). Pediatric Radiology is “…the official journal of the European Society of Paediatric Radiology, the Society for Pediatric Radiology, the Asian and Oceanic Society for Pediatric Radiology and the Latin American Society of Pediatric Radiology”. However, of the total number of manuscripts submitted for potential publication in the four years 2019 through 2022, only 0.03% were from a LIC and only 7.9% were from a LMIC. Further, the frequency of acceptance of manuscripts from UMIC was seven times higher than that from LMIC (no manuscripts were published from LIC). Increased collaboration is required between researchers across the globe to better understand the barriers to equity in the funding, conduct and publication of research from LIC and LMIC and to identify ways in which we can overcome them together.
Graphical abstract