bluuebunny/crossref_metadata_2025_split huggingface dataset:
A pharmacophore-guided deep learning approach for bioactive molecular generation
Authors: Zhu Huimin , Zhou Renyi , Cao Dongsheng , Tang Jing , Li Min 
Published: October 2023

AbstractThe rational design of novel molecules with the desired bioactivity is a critical but challenging task in drug discovery, especially when treating a novel target family or understudied targets. We propose a Pharmacophore-Guided deep learning approach for bioactive Molecule Generation (PGMG). Through the guidance of pharmacophore, PGMG provides a flexible strategy for generating bioactive molecules. PGMG uses a graph neural network to encode spatially distributed chemical features and a transformer decoder to generate molecules. A latent variable is introduced to solve the many-to-many mapping between pharmacophores and molecules to improve the diversity of the generated molecules. Compared to existing methods, PGMG generates molecules with strong docking affinities and high scores of validity, uniqueness, and novelty. In the case studies, we use PGMG in a ligand-based and structure-based drug de novo design. Overall, the flexibility and effectiveness make PGMG a useful tool to accelerate the drug discovery process.
Morphogenetic metasurfaces: unlocking the potential of Turing patterns
Authors: Fromenteze Thomas , Yurduseven Okan , Uche Chidinma , Arnaud Eric , Smith David R. , Decroze Cyril 
Published: October 2023

AbstractThe reaction-diffusion principle imagined by Alan Turing in an attempt to explain the structuring of living organisms is leveraged in this work for the procedural synthesis of radiating metasurfaces. The adaptation of this morphogenesis technique ensures the growth of anisotropic cellular patterns automatically arranged to satisfy local electromagnetic constraints, facilitating the radiation of waves controlled in frequency, space, and polarization. Experimental validations of this method are presented, designing morphogenetic metasurfaces radiating far-field circularly polarized beams and generating a polarization-multiplexed hologram in the radiative near-field zone. The exploitation of morphogenesis-inspired models proves particularly well suited for solving generative design problems, converting global physical constraints into local interactions of simulated chemical reactants ensuring the emergence of self-organizing meta-atoms.
Microrobots powered by concentration polarization electrophoresis (CPEP)
Authors: Katzmeier Florian , Simmel Friedrich C. 
Published: October 2023

AbstractSecond-order electrokinetic flow around colloidal particles caused by concentration polarization electro-osmosis (CPEO) can result in a phoretic motion of asymmetric particle dimers in a homogeneous AC electrical field, which we refer to as concentration polarization electro-phoresis (CPEP). To demonstrate this actuation mechanism, we created particle dimers from micron-sized silica spheres with sizes 1.0 μm and 2.1 μm by connecting them with DNA linker molecules. The dimers can be steered along arbitrarily chosen paths within a 2D plane by controlling the orientation of the AC electric field in a fluidic chamber with the joystick of a gamepad. Further utilizing induced dipole-dipole interactions, we demonstrate that particle dimers can be used to controllably pick up monomeric particles and release them at any desired position, and also to assemble several particles into groups. Systematic experiments exploring the dependence of the dimer migration speed on the electric field strength, frequency, and buffer composition align with the theoretical framework of CPEO and provide parameter ranges for the operation of our microrobots. Furthermore, experiments with a variety of asymmetric particles, such as fragmented ceramic, borosilicate glass, acrylic glass, agarose gel, and ground coffee particles, as well as yeast cells, demonstrate that CPEP is a generic phenomenon that can be expected for all charged dielectric particles.
Decreased liver B vitamin-related enzymes as a metabolic hallmark of cancer cachexia
Authors: Kojima Yasushi , Mishiro-Sato Emi , Fujishita Teruaki , Satoh Kiyotoshi , Kajino-Sakamoto Rie , Oze Isao , Nozawa Kazuki , Narita Yukiya , Ogata Takatsugu , Matsuo Keitaro , Muro Kei , Taketo Makoto Mark , Soga Tomoyoshi , Aoki Masahiro 
Published: October 2023

AbstractCancer cachexia is a complex metabolic disorder accounting for ~20% of cancer-related deaths, yet its metabolic landscape remains unexplored. Here, we report a decrease in B vitamin-related liver enzymes as a hallmark of systemic metabolic changes occurring in cancer cachexia. Metabolomics of multiple mouse models highlights cachexia-associated reductions of niacin, vitamin B6, and a glycine-related subset of one-carbon (C1) metabolites in the liver. Integration of proteomics and metabolomics reveals that liver enzymes related to niacin, vitamin B6, and glycine-related C1 enzymes dependent on B vitamins decrease linearly with their associated metabolites, likely reflecting stoichiometric cofactor-enzyme interactions. The decrease of B vitamin-related enzymes is also found to depend on protein abundance and cofactor subtype. These metabolic/proteomic changes and decreased protein malonylation, another cachexia feature identified by protein post-translational modification analysis, are reflected in blood samples from mouse models and gastric cancer patients with cachexia, underscoring the clinical relevance of our findings.
Human cellular model systems of β-thalassemia enable in-depth analysis of disease phenotype
Authors: Daniels Deborah E. , Ferrer-Vicens Ivan , Hawksworth Joseph , Andrienko Tatyana N. , Finnie Elizabeth M. , Bretherton Natalie S. , Ferguson Daniel C. J. , Oliveira A. Sofia. F. , Szeto Jenn-Yeu A. , Wilson Marieangela C. , Brewin John N. , Frayne Jan 
Published: October 2023

Abstractβ-thalassemia is a prevalent genetic disorder causing severe anemia due to defective erythropoiesis, with few treatment options. Studying the underlying molecular defects is impeded by paucity of suitable patient material. In this study we create human disease cellular model systems for β-thalassemia by gene editing the erythroid line BEL-A, which accurately recapitulate the phenotype of patient erythroid cells. We also develop a high throughput compatible fluorometric-based assay for evaluating severity of disease phenotype and utilize the assay to demonstrate that the lines respond appropriately to verified reagents. We next use the lines to perform extensive analysis of the altered molecular mechanisms in β-thalassemia erythroid cells, revealing upregulation of a wide range of biological pathways and processes along with potential novel targets for therapeutic investigation. Overall, the lines provide a sustainable supply of disease cells as research tools for identifying therapeutic targets and as screening platforms for new drugs and reagents.
Rebound effects undermine carbon footprint reduction potential of autonomous electric vehicles
Authors: Onat Nuri C. , Mandouri Jafar , Kucukvar Murat , Sen Burak , Abbasi Saddam A. , Alhajyaseen Wael , Kutty Adeeb A. , Jabbar Rateb , Contestabile Marcello , Hamouda Abdel Magid 
Published: October 2023

AbstractAutonomous vehicles offer greater passenger convenience and improved fuel efficiency. However, they are likely to increase road transport activity and life cycle greenhouse emissions, due to several rebound effects. In this study, we investigate tradeoffs between improved fuel economy and rebound effects from a life-cycle perspective. Our results show that autonomy introduces an average 21.2% decrease in operation phase emissions due to improved fuel economy while manufacturing phase emissions can surge up to 40%. Recycling efforts can offset this increase, cutting emissions by 6.65 tons of Carbon dioxide equivalent per vehicle. However, when examining the entire life cycle, autonomous electric vehicles might emit 8% more greenhouse gas emissions on average compared to nonautonomous electric vehicles. To address this, we suggest; (1) cleaner and more efficient manufacturing technologies, (2) ongoing fuel efficiency improvements in autonomous driving; (3) renewable energy adoption for charging, and (4) circular economy initiatives targeting the complete life cycle.
Rab41-mediated ESCRT machinery repairs membrane rupture by a bacterial toxin in xenophagy
Authors: Nozawa Takashi , Toh Hirotaka , Iibushi Junpei , Kogai Kohei , Minowa-Nozawa Atsuko , Satoh Junko , Ito Shinji , Murase Kazunori , Nakagawa Ichiro 
Published: October 2023

AbstractXenophagy, a type of selective autophagy, is a bactericidal membrane trafficking that targets cytosolic bacterial pathogens, but the membrane homeostatic system to cope with bacterial infection in xenophagy is not known. Here, we show that the endosomal sorting complexes required for transport (ESCRT) machinery is needed to maintain homeostasis of xenophagolysosomes damaged by a bacterial toxin, which is regulated through the TOM1L2–Rab41 pathway that recruits AAA-ATPase VPS4. We screened Rab GTPases and identified Rab41 as critical for maintaining the acidification of xenophagolysosomes. Confocal microscopy revealed that ESCRT components were recruited to the entire xenophagolysosome, and this recruitment was inhibited by intrabody expression against bacterial cytolysin, indicating that ESCRT targets xenophagolysosomes in response to a bacterial toxin. Rab41 translocates to damaged autophagic membranes via adaptor protein TOM1L2 and recruits VPS4 to complete ESCRT-mediated membrane repair in a unique GTPase-independent manner. Finally, we demonstrate that the TOM1L2–Rab41 pathway-mediated ESCRT is critical for the efficient clearance of bacteria through xenophagy.
Generalization of procedural motor sequence learning after a single practice trial
Authors: Johnson B. P. , Iturrate I. , Fakhreddine R. Y. , Bönstrup M. , Buch E. R. , Robertson E. M. , Cohen L. G. 
Published: October 2023

AbstractWhen humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments (N = 2095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0–30 s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill.
Eliminating the interference of water for direct sensing of submerged plastics using hyperspectral near-infrared imager
Authors: Zhu Chunmao , Kanaya Yugo 
Published: October 2023

AbstractInterference from water in the reflectance spectra of plastics is a major obstacle to optical sensing of plastics in aquatic environments. Here we present evidence of the feasibility of sensing plastics in water using hyperspectral near-infrared to shortwave-infrared imaging techniques. We captured hyperspectral images of nine polymers submerged to four depths (2.5–15 mm) in water using a hyperspectral imaging system that utilizes near-infrared to shortwave-infrared light sources. We also developed algorithms to predict the reflectance spectra of each polymer in water using the spectra of the dry plastics and water as independent variables in a multiple linear regression model after a logarithmic transformation. A narrow 1100–1300 nm wavelength range was advantageous for detection of polyethylene, polystyrene, and polyvinyl chloride in water down to the 160–320 µm size range, while a wider 970–1670 nm wavelength range was beneficial for polypropylene reflectance spectrum prediction in water. Furthermore, we found that the spectra of the other five polymers, comprising polycarbonate, acrylonitrile butadiene styrene, phenol formaldehyde, polyacetal, and polymethyl methacrylate, could also be predicted within their respective optimized wavelength ranges. Our findings provide fundamental information for direct sensing of plastics in water on both benchtop and airborne platforms.
Deep learning and clustering approaches for dental implant size classification based on periapical radiographs
Authors: Park Ji-Hyun , Moon Hong Seok , Jung Hoi-In , Hwang JaeJoon , Choi Yoon-Ho , Kim Jong-Eun 
Published: October 2023

AbstractThis study investigated two artificial intelligence (AI) methods for automatically classifying dental implant diameter and length based on periapical radiographs. The first method, deep learning (DL), involved utilizing the pre-trained VGG16 model and adjusting the fine-tuning degree to analyze image data obtained from periapical radiographs. The second method, clustering analysis, was accomplished by analyzing the implant-specific feature vector derived from three key points coordinates of the dental implant using the k-means++ algorithm and adjusting the weight of the feature vector. DL and clustering model classified dental implant size into nine groups. The performance metrics of AI models were accuracy, sensitivity, specificity, F1-score, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC-ROC). The final DL model yielded performances above 0.994, 0.950, 0.994, 0.974, 0.952, 0.994, and 0.975, respectively, and the final clustering model yielded performances above 0.983, 0.900, 0.988, 0.923, 0.909, 0.988, and 0.947, respectively. When comparing the AI model before tuning and the final AI model, statistically significant performance improvements were observed in six out of nine groups for DL models and four out of nine groups for clustering models based on AUC-ROC. Two AI models showed reliable classification performances. For clinical applications, AI models require validation on various multicenter data.
Phase transformations and vibrational properties of hybrid organic–inorganic perovskite MAPbI3 bulk at high pressure
Authors: Ardimas  , Pakornchote Teerachote , Sukmas Wiwittawin , Chatraphorn Sojiphong , Clark Stewart J. , Bovornratanaraks Thiti 
Published: October 2023

AbstractThe structural stability and internal properties of hybrid organic–inorganic perovskites (HOIPs) have been widely investigated over the past few years. The interplay between organic cations and inorganic framework is one of the prominent features. Herein we report the evolution of Raman modes under pressure in the hybrid organic–inorganic perovskite MAPbI$$_3$$

3

by combining the experimental approach with the first-principles calculations. A bulk MAPbI$$_3$$

3

single crystal was synthesized via inverse temperature crystallization (ITC) technique and characterized by Raman spectroscopy, while the diamond anvil cells (DACs) was employed to compress the sample. The classification and behaviours of their Raman modes are presented. At ambient pressure, the vibrations of inorganic PbI$$_6$$

6

octahedra and organic MA dominate at a low-frequency range (60–760 cm$$^{-1}$$

-
1

) and a fingerprint range (900–1500 cm$$^{-1}$$

-
1

), respectively. The applied pressure exhibits two significant changes in the Raman spectrum and indicates of phase transition. The results obtained from both experiment and calculations of the second phase at 3.26 GPa reveal that the internal vibration intensity of the PbI$$_6$$

6

octahedra (< 110 cm$$^{-1}$$

-
1

) reduces as absences of MA libration (150–270 cm$$^{-1}$$

-
1

) and internal vibration of MA (450–750 cm$$^{-1}$$

-
1

). Furthermore, the hydrogen interactions around 1300 cm$$^{-1}$$

-
1

remain strong high pressure up to 5.34 GPa.
Load-sharing characteristics of stenting and post-dilation in heavily calcified coronary artery
Authors: Dong Pengfei , Colmenarez Jose , Lee Juhwan , Hassani Neda Shafiabadi , Wilson David L. , Bezerra Hiram G. , Gu Linxia 
Published: October 2023

AbstractIn this work, stenting in non-calcified and heavily calcified coronary arteries was quantified in terms of diameter-pressure relationships and load transfer from the balloon to the artery. The efficacy of post-dilation in non-calcified and heavily calcified coronary arteries was also characterized in terms of load sharing and the changes in tissue mechanics. Our results have shown that stent expansion exhibits a cylindrical shape in non-calcified lesions, while it exhibits a dog bone shape in heavily calcified lesions. Load-sharing analysis has shown that only a small portion of the pressure load (1.4 N, 0.8% of total pressure load) was transferred to the non-calcified lesion, while a large amount of the pressure load (19 N, 12%) was transferred to the heavily calcified lesion. In addition, the increasing inflation pressure (from 10 to 20 atm) can effectively increase the minimal lumen diameter (from 1.48 to 2.82 mm) of the heavily calcified lesion, the stress (from 1.5 to 8.4 MPa) and the strain energy in the calcification (1.77 mJ to 26.5 mJ), which are associated with the potential of calcification fracture. Results indicated that increasing inflation pressure can be an effective way to improve the stent expansion if a dog bone shape of the stenting profile is observed. Considering the risk of a balloon burst, our results support the design and application of the high-pressure balloon for post-dilation. This work also sheds some light on the stent design and choice of stent materials for improving the stent expansion at the dog bone region and mitigating stresses on arterial tissues.
Rollator usage lets young individuals switch movement strategies in sit-to-stand and stand-to-sit tasks
Authors: Herzog Michael , Krafft Frieder C. , Stetter Bernd J. , d’Avella Andrea , Sloot Lizeth H. , Stein Thorsten 
Published: October 2023

AbstractThe transitions between sitting and standing have a high physical and coordination demand, frequently causing falls in older individuals. Rollators, or four-wheeled walkers, are often prescribed to reduce lower-limb load and to improve balance but have been found a fall risk. This study investigated how rollator support affects sit-to-stand and stand-to-sit movements. Twenty young participants stood up and sat down under three handle support conditions (unassisted, light touch, and full support). As increasing task demands may affect coordination, a challenging floor condition (balance pads) was included. Full-body kinematics and ground reaction forces were recorded, reduced in dimensionality by principal component analyses, and clustered by k-means into movement strategies. Rollator support caused the participants to switch strategies, especially when their balance was challenged, but did not lead to support-specific strategies, i.e., clusters that only comprise light touch or full support trials. Three strategies for sit-to-stand were found: forward leaning, hybrid, and vertical rise; two in the challenging condition (exaggerated forward and forward leaning). For stand-to-sit, three strategies were found: backward lowering, hybrid, and vertical lowering; two in the challenging condition (exaggerated forward and forward leaning). Hence, young individuals adjust their strategy selection to different conditions. Future studies may apply this methodology to older individuals to recommend safe strategies and ultimately reduce falls.
Local monitoring of photosensitizer transient states provides feedback for enhanced efficiency and targeting selectivity in photodynamic therapy
Authors: Sandberg Elin , Srambickal Chinmaya V. , Piguet Joachim , Liu Haichun , Widengren Jerker 
Published: October 2023

AbstractPhotodynamic therapy (PDT) fundamentally relies on local generation of PDT precursor states in added photosensitizers (PS), particularly triplet and photo-radical states. Monitoring these states in situ can provide important feedback but is difficult in practice. The states are strongly influenced by local oxygenation, pH and redox conditions, often varying significantly at PDT treatment sites. To overcome this problem, we followed local PDT precursor state populations of PS compounds, via their fluorescence intensity response to systematically varied excitation light modulation. Thereby, we could demonstrate local monitoring of PDT precursor states of methylene blue (MB) and IRdye700DX (IR700), and determined their transitions rates under different oxygenation, pH and redox conditions. By fiber-optics, using one fiber for both excitation and fluorescence detection, the triplet and photo-radical state kinetics of locally applied MB and IR700 could then be monitored in a tissue sample. Finally, potassium iodide and ascorbate were added as possible PDT adjuvants, enhancing intersystem crossing and photoreduction, respectively, and their effects on the PDT precursor states of MB and IR700 could be locally monitored. Taken together, the presented procedure overcomes current methodological limitations and can offer feedback, guiding both excitation and PDT adjuvant application, and thereby more efficient and targeted PDT treatments.
Automation at the service of the study of executive functions in preclinical models
Authors: Zoratto Francesca , Pisa Edoardo , Soldati Claudia , Barezzi Caterina , Ottomana Angela Maria , Presta Martina , Santangelo Valerio , Macrì Simone 
Published: October 2023

AbstractCognitive flexibility involves the capability to switch between different perspectives and implement novel strategies upon changed circumstances. The Wisconsin Card Sorting Test (in humans) and the Attentional Set-Shifting Task (ASST, in rodents) evaluate individual capability to acquire a reward-associated rule and subsequently disregard it in favour of a new one. Both tasks entail consecutive stages wherein subjects discriminate between: two stimuli of a given category (simple discrimination, SD); the stimuli of SD confounded by an irrelevant stimulus of a different category (compound discrimination, CD); different stimuli belonging to the SD category (intradimensional shift, IDS); and two stimuli of the confounding category (extradimensional shift, EDS). The ASST is labour intensive, not sufficiently standardised, and prone to experimental error. Here, we tested the validity of a new, commercially available, automated version of ASST (OPERON) in two independent experiments conducted in: different mouse strains (C57BL/6 and CD1 mice) to confirm their differential cognitive capabilities (Experiment 1); and an experimental model of chronic stress (administration of corticosterone in the drinking water; Experiment 2). In both experiments, OPERON confirmed the findings obtained through the manual version. Just as in Experiment 1 both versions captured the deficit of C57BL/6 mice on the reversal of the CD (CDR), so also in Experiment 2 they provided analogous evidence that corticosterone treated mice have a remarkable impairment in the IDS. Thus, OPERON capitalises upon automated phenotyping to overcome the limitation of the manual version of the ASST while providing comparable results.