bluuebunny/crossref_metadata_2025_split huggingface dataset:
FNIP1 abrogation promotes functional revascularization of ischemic skeletal muscle by driving macrophage recruitment
Authors: Sun Zongchao , Yang Likun , Kiram Abdukahar , Yang Jing , Yang Zhuangzhuang , Xiao Liwei , Yin Yujing , Liu Jing , Mao Yan , Zhou Danxia , Yu Hao , Zhou Zheng , Xu Dengqiu , Jia Yuhuan , Ding Chenyun , Guo Qiqi , Wang Hongwei , Li Yan , Wang Li , Fu Tingting , Hu Shijun , Gan Zhenji 
Published: November 2023

AbstractIschaemia of the heart and limbs attributable to compromised blood supply is a major cause of mortality and morbidity. The mechanisms of functional angiogenesis remain poorly understood, however. Here we show that FNIP1 plays a critical role in controlling skeletal muscle functional angiogenesis, a process pivotal for muscle revascularization during ischemia. Muscle FNIP1 expression is down-regulated by exercise. Genetic overexpression of FNIP1 in myofiber causes limited angiogenesis in mice, whereas its myofiber-specific ablation markedly promotes the formation of functional blood vessels. Interestingly, the increased muscle angiogenesis is independent of AMPK but due to enhanced macrophage recruitment in FNIP1-depleted muscles. Mechanistically, myofiber FNIP1 deficiency induces PGC-1α to activate chemokine gene transcription, thereby driving macrophage recruitment and muscle angiogenesis program. Furthermore, in a mouse hindlimb ischemia model of peripheral artery disease, the loss of myofiber FNIP1 significantly improved the recovery of blood flow. Thus, these results reveal a pivotal role of FNIP1 as a negative regulator of functional angiogenesis in muscle, offering insight into potential therapeutic strategies for ischemic diseases.
Structural basis for ligand recognition and signaling of hydroxy-carboxylic acid receptor 2
Authors: Park Jae-Hyun , Kawakami Kouki , Ishimoto Naito , Ikuta Tatsuya , Ohki Mio , Ekimoto Toru , Ikeguchi Mitsunori , Lee Dong-Sun , Lee Young-Ho , Tame Jeremy R. H. , Inoue Asuka , Park Sam-Yong 
Published: November 2023

AbstractHydroxycarboxylic acid receptors (HCAR1, HCAR2, and HCAR3) transduce Gi/o signaling upon biding to molecules such as lactic acid, butyric acid and 3-hydroxyoctanoic acid, which are associated with lipolytic and atherogenic activity, and neuroinflammation. Although many reports have elucidated the function of HCAR2 and its potential as a therapeutic target for treating not only dyslipidemia but also neuroimmune disorders such as multiple sclerosis and Parkinson’s disease, the structural basis of ligand recognition and ligand-induced Gi-coupling remains unclear. Here we report three cryo-EM structures of the human HCAR2–Gi signaling complex, each bound with different ligands: niacin, acipimox or GSK256073. All three agonists are held in a deep pocket lined by residues that are not conserved in HCAR1 and HCAR3. A distinct hairpin loop at the HCAR2 N-terminus and extra-cellular loop 2 (ECL2) completely enclose the ligand. These structures also reveal the agonist-induced conformational changes propagated to the G-protein-coupling interface during activation. Collectively, the structures presented here are expected to help in the design of ligands specific for HCAR2, leading to new drugs for the treatment of various diseases such as dyslipidemia and inflammation.
Developing Ni single-atom sites in carbon nitride for efficient photocatalytic H2O2 production
Authors: Zhang Xu , Su Hui , Cui Peixin , Cao Yongyong , Teng Zhenyuan , Zhang Qitao , Wang Yang , Feng Yibo , Feng Ran , Hou Jixiang , Zhou Xiyuan , Ma Peijie , Hu Hanwen , Wang Kaiwen , Wang Cong , Gan Liyong , Zhao Yunxuan , Liu Qinghua , Zhang Tierui , Zheng Kun 
Published: November 2023

AbstractPhotocatalytic two-electron oxygen reduction to produce high-value hydrogen peroxide (H2O2) is gaining popularity as a promising avenue of research. However, structural evolution mechanisms of catalytically active sites in the entire photosynthetic H2O2 system remains unclear and seriously hinders the development of highly-active and stable H2O2 photocatalysts. Herein, we report a high-loading Ni single-atom photocatalyst for efficient H2O2 synthesis in pure water, achieving an apparent quantum yield of 10.9% at 420 nm and a solar-to-chemical conversion efficiency of 0.82%. Importantly, using in situ synchrotron X-ray absorption spectroscopy and Raman spectroscopy we directly observe that initial Ni-N3 sites dynamically transform into high-valent O1-Ni-N2 sites after O2 adsorption and further evolve to form a key *OOH intermediate before finally forming HOO-Ni-N2. Theoretical calculations and experiments further reveal that the evolution of the active sites structure reduces the formation energy barrier of *OOH and suppresses the O=O bond dissociation, leading to improved H2O2 production activity and selectivity.
Floquet-tailored Rydberg interactions
Authors: Zhao Luheng , Lee Michael Dao Kang , Aliyu Mohammad Mujahid , Loh Huanqian 
Published: November 2023

AbstractThe Rydberg blockade is a key ingredient for entangling atoms in arrays. However, it requires atoms to be spaced well within the blockade radius, which limits the range of local quantum gates. Here we break this constraint using Floquet frequency modulation, with which we demonstrate Rydberg-blockade entanglement beyond the traditional blockade radius and show how the enlarged entanglement range improves qubit connectivity in a neutral atom array. Further, we find that the coherence of entangled states can be extended under Floquet frequency modulation. Finally, we realize Rydberg anti-blockade states for two sodium Rydberg atoms within the blockade radius. Such Rydberg anti-blockade states for atoms at close range enables the robust preparation of strongly-interacting, long-lived Rydberg states, yet their steady-state population cannot be achieved with only the conventional static drive. Our work transforms between the paradigmatic regimes of Rydberg blockade versus anti-blockade and paves the way for realizing more connected, coherent, and tunable neutral atom quantum processors with a single approach.
Avoiding inferior clusterings with misspecified Gaussian mixture models
Authors: Kasa Siva Rajesh , Rajan Vaibhav 
Published: November 2023

AbstractClustering is a fundamental tool for exploratory data analysis, and is ubiquitous across scientific disciplines. Gaussian Mixture Model (GMM) is a popular probabilistic and interpretable model for clustering. In many practical settings, the true data distribution, which is unknown, may be non-Gaussian and may be contaminated by noise or outliers. In such cases, clustering may still be done with a misspecified GMM. However, this may lead to incorrect classification of the underlying subpopulations. In this paper, we identify and characterize the problem of inferior clustering solutions. Similar to well-known spurious solutions, these inferior solutions have high likelihood and poor cluster interpretation; however, they differ from spurious solutions in other characteristics, such as asymmetry in the fitted components. We theoretically analyze this asymmetry and its relation to misspecification. We propose a new penalty term that is designed to avoid both inferior and spurious solutions. Using this penalty term, we develop a new model selection criterion and a new GMM-based clustering algorithm, SIA. We empirically demonstrate that, in cases of misspecification, SIA avoids inferior solutions and outperforms previous GMM-based clustering methods.
Entropy analysis on EMHD 3D micropolar tri-hybrid nanofluid flow of solar radiative slendering sheet by a machine learning algorithm
Authors: Jakeer Shaik , Basha H. Thameem , Reddy Seethi Reddy Reddisekhar , Abbas Mohamed , Alqahtani Mohammed S. , Loganathan K. , Anand A. Vivek 
Published: November 2023

AbstractThe purpose of this paper is to analyze the heat transfer behavior of the electromagnetic 3D micropolar tri-hybrid nanofluid flow of a solar radiative slendering sheet with non-Fourier heat flux model. The conversion of solar radiation into thermal energy is an area of significant interest as the demand for renewable heat and power continues to grow. Due to their enhanced ability to promote heat transmission, nanofluids can significantly contribute to enhancing the efficiency of solar-thermal systems. The combination of silicon oil-based silicon (Si), magnesium oxide (MgO), and titanium (Ti) nanofluids has attracted attention for their ability to improve the performance of solar-thermal systems. The present study discloses a new approach for intelligent numerical computing solving, which utilizes an MLP feed-forward back-propagation ANN and the Levenberg-Marquard algorithm. The collection of data was conducted for the purpose of testing, certifying, and training the ANN model. The Bvp4c solver in MATLAB is utilized to solve the nonlinear equations governing the momentum, temperature, skin-friction coefficient, and Nusselt number. The characteristics of numerous dimensionless parameters such as porosity parameter $$\left(K={0.0,2.0,4.0}\right)$$

K
=

0.0
,
2.0
,
4.0

, vortex viscosity parameter $$\left({R}_{1}={0.5,1.0,1.5}\right)$$

R
1

=

0.5
,
1.0
,
1.5

, electric field parameter $$\left(E={0.0,0.1,0.2}\right)$$

E
=

0.0
,
0.1
,
0.2

, thermal relaxation time $$\left(\Lambda ={0.01,0.10,0.20}\right)$$

Λ
=

0.01
,
0.10
,
0.20

, heat source/sink parameter, $$\left(Q=-{0.3,0.0,0.3}\right)$$

Q
=
-

0.3
,
0.0
,
0.3

thermal radiation parameter $$\left(R={0.5,1}.{0,1.5}\right)$$

R
=

0.5
,
1

.

0
,
1.5

, temperature ratio parameter $$\left({\theta }_{w}={0.5,1.0,1.5}\right)$$

θ
w

=

0.5
,
1.0
,
1.5

,nanoparticle volume fraction $$\left(\phi ={0.00,0.02,0.04}\right)$$

ϕ
=

0.00
,
0.02
,
0.04

on Si + MgO + Ti/silicon oil micropolar tri-hybrid nanofluida are analyzed. The ANN model engages in a process of data selection, network construction, training, and evaluation of its effectiveness through the utilization of mean square error. Tables and graphs are used to show how essential parameters affect fluid transport properties. The velocity profile is decreased by higher values of the porosity parameter, whereas the temperature profile is increased. The temperature profile is inversely proportional to higher values of the electric field parameter. The micro-rotation profiles reduced by expanding values vortex viscosity parameter. It has been determined that entropy generation and Bejan number intensifications for enlarged nanoparticle volume fraction.
Neuroanatomy of the late Cretaceous Thescelosaurus neglectus (Neornithischia: Thescelosauridae) reveals novel ecological specialisations within Dinosauria
Authors: Button David J. , Zanno Lindsay E. 
Published: November 2023

AbstractOrnithischian dinosaurs exhibited a diversity of ecologies, locomotory modes, and social structures, making them an ideal clade in which to study the evolution of neuroanatomy and behaviour. Here, we present a 3D digital reconstruction of the endocranial spaces of the latest Cretaceous neornithischian Thescelosaurus neglectus, in order to interpret the neuroanatomy and paleobiology of one of the last surviving non-avian dinosaurs. Results demonstrate that the brain of Thescelosaurus was relatively small compared to most other neornithischians, instead suggesting cognitive capabilities within the range of extant reptiles. Other traits include a narrow hearing range, with limited ability to distinguish high frequencies, paired with unusually well-developed olfactory lobes and anterior semicircular canals, indicating acute olfaction and vestibular sensitivity. This character combination, in conjunction with features of the postcranial anatomy, is consistent with specializations for burrowing behaviours in the clade, as evidenced by trace and skeletal fossil evidence in earlier-diverging thescelosaurids, although whether they reflect ecological adaptations or phylogenetic inheritance in T. neglectus itself is unclear. Nonetheless, our results provide the first evidence of neurological specializations to burrowing identified within Ornithischia, and non-avian dinosaurs more generally, expanding the range of ecological adaptations recognized within this major clade.
High-resolution surface electromyographic activities of facial muscles during the six basic emotional expressions in healthy adults: a prospective observational study
Authors: Guntinas-Lichius Orlando , Trentzsch Vanessa , Mueller Nadiya , Heinrich Martin , Kuttenreich Anna-Maria , Dobel Christian , Volk Gerd Fabian , Graßme Roland , Anders Christoph 
Published: November 2023

AbstractHigh-resolution facial surface electromyography (HR-sEMG) is suited to discriminate between different facial movements. Whether HR-sEMG also allows a discrimination among the six basic emotions of facial expression is unclear. 36 healthy participants (53% female, 18–67 years) were included for four sessions. Electromyograms were recorded from both sides of the face using a muscle-position oriented electrode application (Fridlund scheme) and by a landmark-oriented, muscle unrelated symmetrical electrode arrangement (Kuramoto scheme) simultaneously on the face. In each session, participants expressed the six basic emotions in response to standardized facial images expressing the corresponding emotions. This was repeated once on the same day. Both sessions were repeated two weeks later to assess repetition effects. HR-sEMG characteristics showed systematic regional distribution patterns of emotional muscle activation for both schemes with very low interindividual variability. Statistical discrimination between the different HR-sEMG patterns was good for both schemes for most but not all basic emotions (ranging from p > 0.05 to mostly p < 0.001) when using HR-sEMG of the entire face. When using information only from the lower face, the Kuramoto scheme allowed a more reliable discrimination of all six emotions (all p < 0.001). A landmark-oriented HR-sEMG recording allows specific discrimination of facial muscle activity patterns during basic emotional expressions.
Immune inhibitory receptor-mediated immune response, metabolic adaptation, and clinical characterization in patients with COVID-19
Authors: An Huaying , Yan Congrui , Ma Jun , Gong Jiayuan , Gao Fenghua , Ning Changwen , Wang Fei , Zhang Meng , Li Baoyi , Su Yunqi , Liu Pengyu , Wei Hanqi , Jiang Xingwei , Yu Qun 
Published: November 2023

AbstractImmune inhibitory receptors (IRs) play a critical role in the regulation of immune responses to various respiratory viral infections. However, in coronavirus disease 2019 (COVID-19), the roles of these IRs in immune modulation, metabolic reprogramming, and clinical characterization remain to be determined. Through consensus clustering analysis of IR transcription in the peripheral blood of patients with COVID-19, we identified two distinct IR patterns in patients with COVID-19, which were named IR_cluster1 and IR_cluster2. Compared to IR_cluster1 patients, IR_cluster2 patients with lower expressions of immune inhibitory receptors presented with a suppressed immune response, lower nutrient metabolism, and worse clinical manifestations or prognosis. Considering the critical influence of the integrated regulation of multiple IRs on disease severity, we established a scoring system named IRscore, which was based on principal component analysis, to evaluate the combined effect of multiple IRs on the disease status of individual patients with COVID-19. Similar to IR_cluster2 patients, patients with high IRscores had longer hospital-free days at day 45, required ICU admission and mechanical ventilatory support, and presented higher Charlson comorbidity index and SOFA scores. A high IRscore was also linked to acute infection phase and absence of drug intervention. Our investigation comprehensively elucidates the potential role of IR patterns in regulating the immune response, modulating metabolic processes, and shaping clinical manifestations of COVID-19. All of this evidence suggests the essential role of prognostic stratification and biomarker screening based on IR patterns in the clinical management and drug development of future emerging infectious diseases such as COVID-19.
Rapid evolution of phenotypic plasticity in patchy habitats
Authors: Promy Nawsheen T. , Newberry Mitchell , Gulisija Davorka 
Published: November 2023

AbstractPhenotypic plasticity may evolve rapidly, enabling a population’s persistence in the face of sudden environmental change. Rapid evolution can occur when there is considerable genetic polymorphism at selected loci. We propose that balancing selection could be one of the mechanisms that sustain such polymorphism for plasticity. We use stochastic Monte Carlo simulations and deterministic analysis to investigate the evolution of a plasticity modifier locus in structured populations inhabiting favorable and adverse environments, i.e. patchy habitats. We survey a wide range of parameters including selective pressures on a target (structural) locus, plasticity effects, population sizes, and migration patterns between demes including periodic or continuous bidirectional and source-sink dynamics. We find that polymorphism in phenotypic plasticity can be maintained under a wide range of environmental scenarios in both favorable and adverse environments due to the balancing effect of population structure in patchy habitats. This effect offers a new plausible explanation for the rapid evolution of plasticity in nature: Phenotypic plasticity may rapidly evolve from genetic variation maintained by balancing selection if the population has experienced immigration from populations under different selection regimes.
X-ray reflectivity study of the heat shock protein Hsp70 interaction with an artificial cell membrane model
Authors: Makky Ali , Czajor Julian , Konovalov Oleg , Zhakhov Alexander , Ischenko Alexander , Behl Ankita , Singh Shailja , Abuillan Wasim , Shevtsov Maxim 
Published: November 2023

AbstractMembrane-bound heat shock protein 70 (Hsp70) apart from its intracellular localization was shown to be specifically expressed on the plasma membrane surface of tumor but not normal cells. Although the association of Hsp70 with lipid membranes is well documented the exact mechanisms for chaperone membrane anchoring have not been fully elucidated. Herein, we addressed the question of how Hsp70 interacts with negatively charged phospholipids in artificial lipid compositions employing the X-ray reflectivity (XRR) studies. In a first step, the interactions between dioleoylphosphatidylcholine (DOPC) in the presence or absence of dioleoylphosphatidylserine (DOPS) and Hsp70 had been assessed using Quartz crystal microbalance measurements, suggesting that Hsp70 adsorbs to the surface of DOPC/DOPS bilayer. Atomic force microscopy (AFM) imaging demonstrated that the presence of DOPS is required for stabilization of the lipid bilayer. The interaction of Hsp70 with DOPC/DOPS lipid compositions was further quantitatively determined by high energy X-ray reflectivity. A systematic characterization of the chaperone-lipid membrane interactions by various techniques revealed that artificial membranes can be stabilized by the electrostatic interaction of anionic DOPS lipids with Hsp70.
Heart failure patients monitoring using IoT-based remote monitoring system
Authors: Umer Muhammad , Aljrees Turki , Karamti Hanen , Ishaq Abid , Alsubai Shtwai , Omar Marwan , Bashir Ali Kashif , Ashraf Imran 
Published: November 2023

AbstractIntelligent health monitoring systems are becoming more important and popular as technology advances. Nowadays, online services are replacing physical infrastructure in several domains including medical services as well. The COVID-19 pandemic has also changed the way medical services are delivered. Intelligent appliances, smart homes, and smart medical systems are some of the emerging concepts. The Internet of Things (IoT) has changed the way communication occurs alongside data collection sources aided by smart sensors. It also has deployed artificial intelligence (AI) methods for better decision-making provided by efficient data collection, storage, retrieval, and data management. This research employs health monitoring systems for heart patients using IoT and AI-based solutions. Activities of heart patients are monitored and reported using the IoT system. For heart disease prediction, an ensemble model ET-CNN is presented which provides an accuracy score of 0.9524. The investigative data related to this system is very encouraging in real-time reporting and classifying heart patients with great accuracy.
Comparison of the prognostic impact of IPI and PIT in peripheral T-cell lymphoma in real-world practice with a large elderly population
Authors: Nakamura Nobuhiko , Kanemura Nobuhiro , Matsumoto Takuro , Nakamura Hiroshi , Ikoma Yoshikazu , Shibata Yuhei , Kitagawa Junnichi , Kasahara Senji , Yamada Toshiki , Sawada Michio , Kaneda Yuto , Fukuno Kenji , Takada Eri , Goto Hideko , Lee Shin , Fujita Kei , Morishita Tetsuji , Hara Takeshi , Tsurumi Hisashi , Shimizu Masahito 
Published: November 2023

AbstractWe compared the predictive ability of the International Prognostic Index (IPI), a frequently used prognostic model for peripheral T-cell lymphoma (PTCL), with that of a type-specific prognostic model, the Prognostic Index for PTCL-U (PIT). We retrospectively analyzed 113 patients diagnosed with PTCL. The median age was 67 years (range, 16–88 years), 75 patients (66%) were male, and the most common disease type was PTCL, not otherwise specified (69%). With a median follow-up of 6.8 years (interquartile range, 2.7–9.9 years), 5-year survival rates for the four groups in IPI were 85%, 62%, 49%, and 13%, respectively. Similarly, 5-year survival rates for the four groups in PIT were 83%, 64%, 49%, and 19%, respectively. The area under the receiving operating characteristic curve for predicting mortality from PIT (0.725) was not significantly different from that from the IPI (0.685, P = 0.134). Multivariable analysis showed that performance status ≥ 2 (P < 0.0001) and extranodal lesions ≥ 2 (P = 0.029) were significantly associated with lower overall survival. The present study found no significant difference in prognostic ability between the IPI and PIT for PTCL, and both models appear useful as predictive models.
Toxicity effects of zinc supply on growth revealed by physiological and transcriptomic evidences in sweet potato (Ipomoea batatas (L.) Lam)
Authors: Meng Yusha , Xiang Chao , Huo Jinxi , Shen Shengfa , Tang Yong , Wu Liehong 
Published: November 2023

AbstractZinc toxicity affects crop productivity and threatens food security and human health worldwide. Unfortunately, the accumulation patterns of zinc and the harmful effects of excessive zinc on sweet potato have not been well explored. In the present research, two genotypes of sweet potato varieties with different accumulation patterns of zinc were selected to analyze the effects of excessive zinc on sweet potato via hydroponic and field cultivation experiments. The results indicated that the transfer coefficient was closely related to the zinc concentration in the storage roots of sweet potato. Excessive zinc inhibited the growth of sweet potato plants by causing imbalanced mineral concentrations, destroying the cellular structure and reducing photosynthesis. Furthermore, a total of 17,945 differentially expressed genes were identified in the two genotypes under zinc stress by transcriptomic analysis. Differentially expressed genes involved in the absorption and transport of zinc, defense networks and transcription factors played important roles in the response to zinc stress. In conclusion, this study provides a reference for the selection of sweet potato varieties in zinc contaminated soil and lays a foundation for investigating the tolerance of sweet potato to excessive zinc, which is meaningful for environmental safety and human health.