bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does cannabidiol make cannabis safer? A randomised, double-blind, cross-over trial of cannabis with four different CBD:THC ratios
Authors: Englund Amir , Oliver Dominic , Chesney Edward , Chester Lucy , Wilson Jack , Sovi Simina , De Micheli Andrea , Hodsoll John , Fusar-Poli Paolo , Strang John , Murray Robin M. , Freeman Tom P. , McGuire Philip 
Published: November 2022

AbstractAs countries adopt more permissive cannabis policies, it is increasingly important to identify strategies that can reduce the harmful effects of cannabis use. This study aimed to determine if increasing the CBD content of cannabis can reduce its harmful effects. Forty-six healthy, infrequent cannabis users participated in a double-blind, within-subject, randomised trial of cannabis preparations varying in CBD content. There was an initial baseline visit followed by four drug administration visits, in which participants inhaled vaporised cannabis containing 10 mg THC and either 0 mg (0:1 CBD:THC), 10 mg (1:1), 20 mg (2:1), or 30 mg (3:1) CBD, in a randomised, counter-balanced order. The primary outcome was change in delayed verbal recall on the Hopkins Verbal Learning Task. Secondary outcomes included change in severity of psychotic symptoms (e.g., Positive and Negative Syndrome Scale [PANSS] positive subscale), plus further cognitive, subjective, pleasurable, pharmacological and physiological effects. Serial plasma concentrations of THC and CBD were measured. THC (0:1) was associated with impaired delayed verbal recall (t(45) = 3.399, d = 0.50, p = 0.001) and induced positive psychotic symptoms on the PANSS (t(45) = −4.709, d = 0.69, p = 2.41 × 10–5). These effects were not significantly modulated by any dose of CBD. Furthermore, there was no evidence of CBD modulating the effects of THC on other cognitive, psychotic, subjective, pleasurable, and physiological measures. There was a dose-response relationship between CBD dose and plasma CBD concentration, with no effect on plasma THC concentrations. At CBD:THC ratios most common in medicinal and recreational cannabis products, we found no evidence that CBD protects against the acute adverse effects of cannabis. This should be considered in health policy and safety decisions about medicinal and recreational cannabis.
KCNF1 promotes lung cancer by modulating ITGB4 expression
Authors: Chen Ching-Yi , Wu Pei-Ying , Van Scoyk Michelle , Simko Stephanie A. , Chou Chu-Fang , Winn Robert A. 
Published: November 2022

AbstractLung cancer continues to be the leading cause of cancer death in the United States. Despite recent advances, the five-year survival rate for lung cancer compared to other cancers still remains fairly low. The discovery of molecular targets for lung cancer is key to the development of new approaches and therapies. Electrically silent voltage-gated potassium channel (KvS) subfamilies, which are unable to form functional homotetramers, are implicated in cell-cycle progression, cell proliferation and tumorigenesis. Here, we analyzed the expression of KvS subfamilies in human lung tumors and identified that potassium voltage-gated channel subfamily F member 1 (KCNF1) was up-regulated in non-small cell lung cancer (NSCLC). Silencing of KCNF1 in NSCLC cell lines reduced cell proliferation and tumor progression in mouse xenografts, re-established the integrity of the basement membrane, and enhanced cisplatin sensitivity. KCNF1 was predominately localized in the nucleoplasm and likely mediated its functions in an ion-independent manner. We identified integrin β4 subunit (ITGB4) as a downstream target for KCNF1. Our findings suggest that KCNF1 promotes lung cancer by enhancing ITGB4 signaling and implicate KCNF1 as a novel therapeutic target for lung cancer.
Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer
Authors: Galeano Niño Jorge Luis , Wu Hanrui , LaCourse Kaitlyn D. , Kempchinsky Andrew G. , Baryiames Alexander , Barber Brittany , Futran Neal , Houlton Jeffrey , Sather Cassie , Sicinska Ewa , Taylor Alison , Minot Samuel S. , Johnston Christopher D. , Bullman Susan 
Published: November 2022

AbstractThe tumour-associated microbiota is an intrinsic component of the tumour microenvironment across human cancer types1,2. Intratumoral host–microbiota studies have so far largely relied on bulk tissue analysis1–3, which obscures the spatial distribution and localized effect of the microbiota within tumours. Here, by applying in situ spatial-profiling technologies4 and single-cell RNA sequencing5 to oral squamous cell carcinoma and colorectal cancer, we reveal spatial, cellular and molecular host–microbe interactions. We adapted 10x Visium spatial transcriptomics to determine the identity and in situ location of intratumoral microbial communities within patient tissues. Using GeoMx digital spatial profiling6, we show that bacterial communities populate microniches that are less vascularized, highly immuno‑suppressive and associated with malignant cells with lower levels of Ki-67 as compared to bacteria-negative tumour regions. We developed a single-cell RNA-sequencing method that we name INVADEseq (invasion–adhesion-directed expression sequencing) and, by applying this to patient tumours, identify cell-associated bacteria and the host cells with which they interact, as well as uncovering alterations in transcriptional pathways that are involved in inflammation, metastasis, cell dormancy and DNA repair. Through functional studies, we show that cancer cells that are infected with bacteria invade their surrounding environment as single cells and recruit myeloid cells to bacterial regions. Collectively, our data reveal that the distribution of the microbiota within a tumour is not random; instead, it is highly organized in microniches with immune and epithelial cell functions that promote cancer progression.
Arbuscular mycorrhiza alters the nutritional requirements in Salvia miltiorrhiza and low nitrogen enhances the mycorrhizal efficiency
Authors: Pu Chunjuan , Yang Guang , Li Pengying , Ge Yang , Garran Thomas Avery , Zhou Xiuteng , Shen Ye , Zheng Han , Chen Meilan , Huang Luqi 
Published: November 2022

AbstractSalvia miltiorrhiza Bunge (danshen in Chinese) is one of the most important medicinal cash crops in China. Previously, we showed that arbuscular mycorrhizal fungi (AMF) can promote S. miltiorrhiza growth and the accumulation of bioactive compounds. Fertilization may affect mycorrhizal efficiency, and appropriate doses of phosphate (P) and nitrogen (N) fertilizers are key factors for obtaining mycorrhizal benefits. However, the optimal fertilization amount for mycorrhizal S. miltiorrhiza remains unclear. In this study, we studied the effects of AMF on the growth and bioactive compounds of S. miltiorrhiza under different doses (low, medium, and high) of P and N fertilizer. The results showed that the mycorrhizal growth response (MGR) and mycorrhizal response of bioactive compounds (MBC) decreased gradually with increasing P addition. Application of a low (N25) dose of N fertilizer significantly increased the MGR of mycorrhizal S. miltiorrhiza, and a medium (N50) dose of N fertilizer significantly increased the MBC of phenolic acids, but decreased the MBC of tanshinones. Our results also showed that the existence of arbuscular mycorrhiza changes nutrient requirement pattern of S. miltiorrhiza. P is the limiting nutrient of non-mycorrhizal plants whereas N is the limiting nutrient of mycorrhizal plants.
Working memory capacity estimates moderate value learning for outcome-irrelevant features
Authors: Ben-Artzi Ido , Luria Roy , Shahar Nitzan 
Published: November 2022

AbstractTo establish accurate action-outcome associations in the environment, individuals must refrain from assigning value to outcome-irrelevant features. However, studies have largely ignored the role of attentional control processes on action value updating. In the current study, we examined the extent to which working memory—a system that can filter and block the processing of irrelevant information in one’s mind—also filters outcome-irrelevant information during value-based learning. For this aim, 174 individuals completed a well-established working memory capacity measurement and a reinforcement learning task designed to estimate outcome-irrelevant learning. We replicated previous studies showing a group-level tendency to assign value to tasks’ response keys, despite clear instructions and practice suggesting they are irrelevant to the prediction of monetary outcomes. Importantly, individuals with higher working memory capacity were less likely to assign value to the outcome-irrelevant response keys, thus suggesting a significant moderation effect of working memory capacity on outcome-irrelevant learning. We discuss the role of working memory processing on value-based learning through the lens of a cognitive control failure.
Personalized prediction of optimal water intake in adult population by blended use of machine learning and clinical data
Authors: Dolci Alberto , Vanhaecke Tiphaine , Qiu Jiqiong , Ceccato Riccardo , Arboretti Rosa , Salmaso Luigi 
Published: November 2022

AbstractGrowing evidence suggests that sustained concentrated urine contributes to chronic metabolic and kidney diseases. Recent results indicate that a daily urinary concentration of 500 mOsm/kg reflects optimal hydration. This study aims at providing personalized advice for daily water intake considering personal intrinsic (age, sex, height, weight) and extrinsic (food and fluid intakes) characteristics to achieve a target urine osmolality (UOsm) of 500 mOsm/kg using machine learning and optimization algorithms. Data from clinical trials on hydration (four randomized and three non-randomized trials) were analyzed. Several machine learning methods were tested to predict UOsm. The predictive performance of the developed algorithm was evaluated against current dietary guidelines. Features linked to urine production and fluid consumption were listed among the most important features with relative importance values ranging from 0.10 to 0.95. XGBoost appeared the most performing approach (Mean Absolute Error (MAE) = 124.99) to predict UOsm. The developed algorithm exhibited the highest overall correct classification rate (85.5%) versus that of dietary guidelines (77.8%). This machine learning application provides personalized advice for daily water intake to achieve optimal hydration and may be considered as a primary prevention tool to counteract the increased incidence of chronic metabolic and kidney diseases.
Motion estimation for large displacements and deformations
Authors: Chen Qiao , Poullis Charalambos 
Published: November 2022

AbstractLarge displacement optical flow is an integral part of many computer vision tasks. Variational optical flow techniques based on a coarse-to-fine scheme interpolate sparse matches and locally optimize an energy model conditioned on colour, gradient and smoothness, making them sensitive to noise in the sparse matches, deformations, and arbitrarily large displacements. This paper addresses this problem and presents HybridFlow, a variational motion estimation framework for large displacements and deformations. A multi-scale hybrid matching approach is performed on the image pairs. Coarse-scale clusters formed by classifying pixels according to their feature descriptors are matched using the clusters’ context descriptors. We apply a multi-scale graph matching on the finer-scale superpixels contained within each matched pair of coarse-scale clusters. Small clusters that cannot be further subdivided are matched using localized feature matching. Together, these initial matches form the flow, which is propagated by an edge-preserving interpolation and variational refinement. Our approach does not require training and is robust to substantial displacements and rigid and non-rigid transformations due to motion in the scene, making it ideal for large-scale imagery such as aerial imagery. More notably, HybridFlow works on directed graphs of arbitrary topology representing perceptual groups, which improves motion estimation in the presence of significant deformations. We demonstrate HybridFlow’s superior performance to state-of-the-art variational techniques on two benchmark datasets and report comparable results with state-of-the-art deep-learning-based techniques.
Impact of chitosan administration on titanium dioxide nanoparticles induced testicular dysfunction
Authors: Halawa Amal A. , Elshopakey Gehad E. , Elmetwally Mohammed A. , El-Adl Mohamed , Lashen Samah , Shalaby Nancy , Eldomany Ehab , Farghali Ahmed , Sayed-Ahmed Mohamed Z. , Alam Nawazish , Syed Nabeel Kashan , Ahmad Sarfaraz , Rezk Shaymaa 
Published: November 2022

AbstractThe potential reproductive toxic effects of oral TiO2 NPs in adult male rats as well as the possible alleviation of chitosan administration was investigated. Animals were allocated to four groups; the first group received deionized water and was assigned as a control group. In the second group, rats received chitosan at a dose of 5 mg/kg BW/day. The third group was designed for administration of TiO2 NPs at a dose of 150 mg/kg BW/day (1/80 LD50). Rats in the fourth group received both TiO2 NPs and chitosan. After 14 days, TiO2 NPs induced testicular lipid peroxidation as well as oxidative stress. Nano-titanium significantly upregulated genes that encode apoptosis and inflammation in testicular tissue. Moreover, it induced histological alteration in the testicular structure with impairment in spermatogenesis via reduction of PCNA immune-staining. Chitosan administration significantly improved the activities of testicular GPx, SOD, and CAT enzymes. In addition, it significantly down-regulated the relative expressions of pro-apoptotic and pro-inflammatory testicular genes. Chitosan was able to improve the testicular architecture as well as spermatogenesis. The current study revealed the capability of chitosan to ameliorate nano-titanium induced testicular toxicity. Thus, attention should be given to the extensive consumption of nano-titanium particles.
Singlet fission initiating triplet generations of BODIPY derivatives through $$\pi $$-stacking: a theoretical study
Authors: Tsuneda Takao , Taketsugu Tetsuya 
Published: November 2022

AbstractThe role of singlet fission (SF) in the triplet-state generation mechanism of 1,3,5,7-tetramethyl-boron-dipyrromethene derivatives is revealed by exploring the cause for the solvent dependence of the generation rate. Comparing the adsorption energy calculations of solvent molecules, i.e., cyclohexane, chloroform and acetonitrile molecules, to the derivatives with the $$\pi $$
π
-stacking energies of these derivatives surprisingly show that the hierarchy of the solvation energies and $$\pi $$
π
-stacking energies strongly correlates with the experimentally-suggested solvent dependence of the triplet-state generation of these derivatives for five and more adsorbing solvent molecules. Following this finding, the excitation spectra of these derivatives in acetonitrile solvent are explored using the proprietary spin-flip long-range corrected time-dependent density functional theory. It is, consequently, confirmed that the $$\pi $$
π
-stacking activates the second lowest singlet excitation to trigger the spin-allowed transition to the singlet doubly-excited tetraradical (TT)$$_1$$

1

state, which generates the long-lived quintet (TT)$$_1$$

1

state causing the SF. However, it is also found that the $$\pi $$
π
-stacking also get a slow intersystem crossing active around the intersections of the lowest singlet excitations with the lowest triplet T$$_1$$

1

excitations in parallel with the SF due to the charge transfer characters of the lowest singlet excitations. These results suggest that SF initiates the triplet-state generations through near-degenerate low-lying singlet and (TT) excitations with a considerable singlet-triplet energy gap after the $$\pi $$
π
-stacking of chromophores stronger than but not far from the solvation. Since these derivatives are organic photosensitizers, this study proposes that SF should be taken into consideration in developing novel heavy atom-free organic photosensitizers, which will contribute to a variety of research fields such as medical care, photobiology, energy science, and synthetic chemistry.
Carer distress among community living older adults with complex needs in the pre- and post-COVID-19 era: a national population study
Authors: Schluter Philip J. , Abey-Nesbit Rebecca , Ahuriri-Driscoll Annabel , Bergler Hans Ulrich , Broadbent Jacqueline C. , Glanville Michaela , Keeling Sally , Jamieson Hamish A. 
Published: November 2022

AbstractCarer distress is one important negative impact of caregiving and likely exacerbated by the novel coronavirus disease 2019 (COVID-19) pandemic, yet little population-based epidemiological information exists. Using national data from repeated standardized comprehensive geriatric needs assessments, this study aims to: describe the pattern of caregiver distress among those providing informal care to community-living adults aged ≥ 65 years with complex needs in New Zealand over time; estimate the COVID-19 effect on this temporal pattern; and, investigate relationships between participants’ sociodemographic and selected health measures on caregiver distress. Fractional polynomial regression and multivariable multilevel mixed-effects models were employed. Overall, 231,277 assessments from 144,358 participants were analysed. At first assessment, average age was 82.0 years (range 65–107 years), and 85,676 (59.4%) were female. Carer distress prevalence increased from 35.1% on 5 July 2012 to a peak of 48.5% on 21 March 2020, when the New Zealand Government announced a national lock-down. However, the population attributional fraction associated with the COVID-19 period was small, estimated at 0.56% (95% CI 0.35%, 0.77%). Carer distress is common and has rapidly increased in recent years. While significant, the COVID-19 impact has been relatively small. Policies and services providing efficacious on-going strategies to support caregivers deserves specific attention.
Limited transfer and retention of locomotor adaptations from virtual reality obstacle avoidance to the physical world
Authors: Weber Anika , Hartmann Ulrich , Werth Julian , Epro Gaspar , Seeley John , Nickel Peter , Karamanidis Kiros 
Published: November 2022

AbstractLocomotor training based in virtual reality (VR) is promising for motor skill learning, with transfer of VR skills in turn required to benefit daily life locomotion. This study aimed to assess whether VR-adapted obstacle avoidance can be transferred to a physical obstacle and whether such transfer is retained after 1 week. Thirty-two young adults were randomly divided between two groups. A control group (CG) merely walked on a treadmill and an intervention group (IG) trained crossing 50 suddenly-appearing virtual obstacles. Both groups crossed three physical obstacles (transfer task) immediately after training (T1) and 1 week later (T2, transfer retention). Repeated practice in VR led to a decrease in toe clearance along with greater ankle plantarflexion and knee extension. IG participants crossed physical obstacles with a lower toe clearance compared to CG but revealed significantly higher values compared to the VR condition. VR adaptation was fully retained over 1 week. For physical obstacle avoidance there were differences between toe clearance of the third obstacle at T1 and the first obstacle at T2, indicating only partial transfer retention. We suggest that perception–action coupling, and thus sensorimotor coordination, may differ between VR and the physical world, potentially limiting retained transfer between conditions.
First-principles investigation of polytypic defects in InP
Authors: Vedel Christian Dam , Smidstrup Søren , Georgiev Vihar P. 
Published: November 2022

AbstractIn this paper we study polytypic defects in Indium Phosphide (InP) using the complementary first-principles methods of density functional theory and non-equilibrium Greens functions. Specifically we study interfaces between the ground state Zincblende crystal structure and the meta-stable Wurtzite phase, with an emphasis on the rotational twin plane defect, which forms due to the polytypic nature of InP. We found that the transition of the band structure across the interface is anisotropic and lasts 7 nm (3.5 nm). Due to this, a crystal-phase quantum well would require a minimal width of 10 nm, which eliminates rotational twin planes as possible quantum wells. We also found that for conducting current, the interfaces increase conductivity along the defect-plane ([11$$\bar{2}$$

2

¯

]), whereas due to real growth limitations, despite the interfaces reducing conductivity across the defect-plane ([111]), we found that a high degree of polytypic defects are still desirable. This was argued to be the case, due to a higher fraction of Wurtzite segments in a highly phase-intermixed system.
Application of healthcare failure mode and effect analysis in controlling surgical instrument packaging defects
Authors: Yi Liangying , Chen Yanhua , Hu Ruixue , Hu Juan , Pan Wei 
Published: November 2022

AbstractSurgical instrument packaging defects may affect the safety of medical care and patients and waste the hospital workforce, material resources, and financial resources. This study explored the application of healthcare failure mode and effect analysis in controlling surgical instrument packaging defects. We retrospectively evaluated the packaging process of 183,642 surgical instruments packaged in our hospital during January–June 2020 using the healthcare failure mode and effect analysis. Besides, we used a decision tree model to determine the steps requiring improvement and formulate the improvement measures. We applied the improvement measures to 190,231 surgical instrument packs packaged in
our hospital during July–December 2020. Based on the healthcare failure mode and effect analysis, we compared the packaging defect rates before and after adopting the improvement measures. Of the 183,642 packs selected before adopting the improvement measures, 98 defects occurred, with a defect rate of 0.053%. However, of the 190,231 packs selected after adopting the improvement measures, 22 defects occurred, with a defect rate of 0.012%. The defect rate of surgical instrument packaging handled by the central sterile supply department staff was significantly reduced (χ2 = 50.822, P = 0.001) after adopting the improvement measures. Using the medical failure mode and effect analysis method to control the defects in surgical instrument packaging can effectively reduce the packaging defect rate, ensuring patient safety.
Cleavages along {110} in bcc iron emit dislocations from the curved crack fronts
Authors: Suzudo Tomoaki , Ebihara Ken-ichi , Tsuru Tomohito , Mori Hideki 
Published: November 2022

AbstractBody-centered-cubic (bcc) transition metals, such as $$\alpha $$
α
-Fe and W, cleave along the {100} plane, even though the surface energy is the lowest along the {110} plane. To unravel the mechanism of this odd response, large-scale atomistic simulations of curved cleavage cracks of $$\alpha $$
α
-Fe were conducted in association with stress intensity factor analyses of straight crack fronts using an interatomic potential created by an artificial neural network technique. The study provides novel findings: Dislocations are emitted from the crack fronts along the {110} cleavage plane, and this phenomenon explains why the {100} plane can be the cleavage plane. However, the simple straight crack-front analyses did not yield the same conclusion. It is suggested that atomistic modeling, at sufficiently large scales to capture the inherent complexities of materials using highly accurate potentials, is necessary to correctly predict the mechanical strength. The method adopted in this study is generally applicable to the cleavage problem of bcc transition metals and alloys.