Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing stage flexibility of the SNARC effect: Task relevance or magnitude relevance?

Previous studies have shown that the processing stage of the spatial-numerical association of response codes (SNARC) effect was flexible. Two recent studies by Nan et al. (2021) and Yan et al. (2021) used the same experimental paradigm to check whether the SNARC effect occurred in the semantic-representation stage but reached contradictory conclusions, showing that the SNARC effect was influenced by a magnitude Stroop effect in a magnitude comparison task but not by a parity Stroop effect in a parity judgment task. The two studies had two distinct operational factors: the task type (magnitude comparison task or parity judgment task, with the numerical magnitude information task-relevant or task-irrelevant) and the semantic representation stage-related interference information (magnitude or parity Stroop effect, with the interference information magnitude-relevant or magnitude-irrelevant). To determine which factor influenced the SNARC effect, in the present study, the Stroop effect was switched in the two tasks based on the previous studies. The findings of four experiments consistently showed that the SNARC effect was not influenced by the parity Stroop effect in the magnitude comparison task but was influenced by the magnitude Stroop effect in the parity judgment task. Combined with the results of Nan et al. (2021) and Yan et al. (2021), the findings indicated that regardless of the task type or the task-relevance of numerical magnitude information, magnitude-relevant interference information was the primary factor to affect the SNARC effect. Furthermore, a two-stage processing model that explained the observed flexibility of the SNARC effect was proposed and discussed. Public Significance Statement Previous studies have shown that the spatial-numerical association of response codes (SNARC) effect is flexible in the direction and processing stage. The task type and interference information might be two influential factors for the flexibility of the SNARC effect. The present study reported that magnitude-relevant interference information, regardless of task type, was a crucial role to affect the SNARC effect. Moreover, a two-stage processing model was proposed to reveal the processing pathway of the SNARC effect and provided a possible explanation for the longstanding debate about the processing stage of the SNARC effect.
Towards a bionic IoT: Environmental monitoring using smartphone interrogated plant sensors

The utilisation of plants directly as quantifiable natural sensors is proposed. A case study measuring surface wettability of Aucuba japonica, or Japanese Laurel, plants using a novel smartphone field interrogator is demonstrated. This plant has been naturalised globally from Asia. Top-down contact angle measurements map wettability on-site and characterise a range of properties impacting plant health, such as aging, solar and UV exposure, and pollution. Leaves at an early age or in the shadow of trees are found to be hydrophobic with contact angle θ ~ 99°, while more mature leaves under sunlight are hydrophilic with θ ~ 79°. Direct UVA irradiation at λ = 365 nm is shown to accelerate aging, changing contact angle of one leaf from slightly hydrophobic at θ ~ 91° to be hydrophilic with θ ~ 87 ° after 30 min. Leaves growing beside a road with heavy traffic are observed to be substantially hydrophilic, as low as θ ~ 47°, arising from increased wettability with particulate accumulation on the leaf surface. Away from the road, the contact angle increases as high as θ ~ 96°. The results demonstrate that contact angle measurements using a portable diagnostic IoT edge device can be taken into the field for environmental detection, pollution assessment and more. Using an internet connected smartphone combined with a plant sensor allows multiple measurements at multiple locations together in real-time, potentially enabling tracking of parameter change anywhere where plants are present or introduced. This hybrid integration of widely distributed living organic systems with the internet marks the beginning of a new bionic internet-of-things (b-IoT).
Domain fusion TLR2-4 enhances the autophagy-dependent clearance of Staphylococcus aureus in the genetic engineering goat

Staphylococcus aureus infections pose a potential threat to livestock production and public health. A novel strategy is needed to control S. aureus infections due to its adaptive evolution to antibiotics. Autophagy plays a key role in degrading bacteria for innate immune cells. In order to promote S. aureus clearance via Toll-like receptor (TLR)-induced autophagy pathway, the domain fusion TLR2-4 with the extracellular domain of TLR2, specific recognizing S. aureus, and transmembrane and intracellular domains of TLR4 is assembled, then the goat expressing TLR2-4 is generated. TLR2-4 substantially augments the removal of S. aureus within macrophages by elevating autophagy level. Phosphorylated JNK and ERK1/2 promote LC3-puncta in TLR2-4 macrophages during S. aureus-induced autophagy via MyD88 mediated the TAK1 signaling cascade. Meantime, the TRIF-dependent TBK1-TFEB-OPTN signaling is involved in TLR2-4-triggered autophagy after S. aureus challenge. Moreover, the transcript of ATG5 and ATG12 is significantly increased via cAMP-PKA-NF-κB signaling, which facilitates S. aureus-induced autophagy in TLR2-4 macrophages. Overall, the novel receptor TLR2-4 enhances the autophagy-dependent clearance of S. aureus in macrophages via TAK1/TBK1-JNK/ERK, TBK1-TFEB-OPTN, and cAMP-PKA-NF-κB-ATGs signaling pathways, which provide an alternative approach for resistant against S. aureus infection.
Abnormalities of Electroencephalography Microstates in Drug-Naïve, First-Episode Schizophrenia

Objective Microstate analysis is a powerful tool to probe the brain functions, and changes in microstates under electroencephalography (EEG) have been repeatedly reported in patients with schizophrenia. This study aimed to investigate the dynamics of EEG microstates in drug-naïve, first-episode schizophrenia (FE-SCH) and to test the relationship between EEG microstates and clinical symptoms. Methods Resting-state EEG were recorded for 23 patients with FE-SCH and 23 healthy controls using a 64-channel cap. Three parameters, i.e., contribution, duration, and occurrence, of the four microstate classes were calculated. Group differences in EEG microstates and their clinical symptoms [assessed using the Positive and Negative Syndrome Scale (PANSS)] were analyzed. Results Compared with healthy controls, patients with FE-SCH showed increased duration, occurrence and contribution of microstate class C and decreased contribution and occurrence of microstate class D. In addition, the score of positive symptoms in PANSS was negatively correlated with the occurrence of microstate D. Conclusion Our findings showed abnormal patterns of EEG microstates in drug-naïve, first-episode schizophrenia, which might help distinguish individuals with schizophrenia in the early stage and develop early intervention strategies.
EhVps23, an ESCRT-I Member, Is a Key Factor in Secretion, Motility, Phagocytosis and Tissue Invasion by Entamoeba histolytica

The EhVps23 protein, an orthologue of the yeast Vps23 and the mammalian TSG101 proteins, is the single member of the ESCRT-I complex of Entamoeba histolytica identified and characterized until now. EhVps23 actively participates in vesicular trafficking and phagocytosis, which influence several cellular events. In this paper, we investigated the role of EhVps23 in virulence-related functions, including the invasive capacity of trophozoites, using transfected trophozoites. Trophozoites overexpressing the EhVps23 protein (Neo-EhVps23) presented helical arrangements in the cytoplasm, similar to the ones formed by EhVps32 for scission of vesicles. By confocal and transmission electron microscopy, EhVps23 was detected in multivesicular bodies, vesicles, and the extracellular space. It was secreted in vesicles together with other proteins, including the EhADH adhesin. Probably, these vesicles carry molecules that participate in the prey capture or in cell-cell communication. Mass spectrometry of precipitates obtained using α-EhVps23 antibodies, evidenced the presence of proteins involved in motility, phagocytosis, vesicular trafficking and secretion. The study of cellular functions, revealed that Neo-EhVps23 trophozoites exhibit characteristics similar to those described for mammalian transformed cells: they grew 50% faster than the control; presented a significant higher rate of phagocytosis, and migrated five-fold faster than the control, in concordance with the low rate of migration exhibited by Ehvps23-knocked down trophozoites. In addition, Neo-EhVps23 trophozoites produced dramatic liver abscesses in experimental animals. In conclusion, our results showed that EhVps23 overexpression gave to the trophozoites characteristics that resemble cancer cells, such as increased cell proliferation, migration, and invasion. The mutant that overexpresses EhVps23 can be a good study model to explore different events related to the transformation of malignant cells.
Liquid Metal-Embedded Layered-PDMS Antenna for Flexible and Conformal Applications

This article proposes a dual-band slot IFA antenna using a combined technique of liquid metal (LM) filling and polydimethylsiloxane substrate. The antenna working at 2.4 and 5.8 GHz consists of three liquid metal layers—radiation patch, short circuit stub, and ground plane and can be bent to different radiuses for flexible, conformal, and wearable applications. The vacuum filling method enables realization of a monolithic-integrated substrate. The applicability of this antenna for a wearable wristband is validated through simulation.
Health Policy Development During COVID-19 in Saudi Arabia: Mixed Methods Analysis

Healthcare systems are increasingly required to utilize effective approaches, apply evidence-based practice, and consequently sustain successful strategic management. Document analysis provides insights into the effective management tools applied by agencies to respond to crises. This article provides a practical exploration of how the Saudi health authority applied effective measures to eventually reduce the administrative and clinical consequences while managing the COVID-19 pandemic. The conceptual descriptive framework was based on health policy triangle of Walt and Gilson. Official reports and supporting documents issued by the Saudi government toward COVID-19 were operationally analyzed. Moreover, five healthcare professional experts were invited in a semistructured interview to assess the strategic steps that have been utilized to minimize the health risk by conducting a healthcare risk analysis. Various documents showed that two major entities were responsible for managing regulations and medications of COVID-19 in addition to six other entities that were partially involved. Although each entity was approved to work independently, their efforts were cohesively associated with each other. Most documents were well-applied on personal, social, organizational, and national strata. However, it is unclear how lessons identified became affirmative, while the collaboration remains vague, especially under the emergence of a new entity such as the Public Health Authority. Healthcare professional experts also positively supported the effectiveness of such policies to confront COVID-19 through the following three domains: health guidelines, utilizing simulation (telehealth/telecommunication) services, and ensuring continuity of services.
Stimulating Brand Innovation Strategy via Knowledge Acquisition, Market Orientation, and Strategic Capability Using Social Media Within China’s Online Technology Industry

In the context of China’s online technology business, this study explores the linkages between knowledge acquisition via social media, two modes of market orientation (proactive and responsive), social media strategic capability, and brand innovation strategy. Data were collected from 853 Chinese technology firms with the help of questionnaire. To analyze the collected data structure, equation modeling was applied using smart-PLS 3.3 version. Results indicate that knowledge acquisition from social media, market orientation (proactive and responsive), and strategic capability has significant impact on brand innovation in the context of social media. Furthermore, strategic capability on social media moderates the relationship between knowledge, market orientation (proactive and responsive), and brand innovation in the context of social media. This study offers new perspectives on market orientation and brand innovation strategy by extending the literature and testing key assumptions. Moreover, using social media knowledge in social media marketing and innovation management is a sensible approach for making changes and transforming an organization.
The 14-3-3 Protein Family and Schizophrenia

Schizophrenia is a debilitating mental disorder that affects approximately 1% of the world population, yet the disorder is not very well understood. The genetics of schizophrenia is very heterogenous, making it hard to pinpoint specific alterations that may cause the disorder. However, there is growing evidence from human studies suggesting a link between alterations in the 14-3-3 family and schizophrenia. The 14-3-3 proteins are abundantly expressed in the brain and are involved in many important cellular processes. Knockout of 14-3-3 proteins in mice has been shown to cause molecular, structural, and behavioral alterations associated with schizophrenia. Thus, 14-3-3 animal models allow for further exploration of the relationship between 14-3-3 and schizophrenia as well as the study of schizophrenia pathology. This review considers evidence from both human and animal model studies that implicate the 14-3-3 family in schizophrenia. In addition, possible mechanisms by which alterations in 14-3-3 proteins may contribute to schizophrenia-like phenotypes such as dopaminergic, glutamatergic, and cytoskeletal dysregulations are discussed.
Aneurysm Location Affects Clinical Course and Mortality in Patients With Subarachnoid Hemorrhage

Objective The influence of preexisting factors on the clinical course of patients with subarachnoid hemorrhage (SAH), such as patient age, arterial hypertension, and aneurysm characteristics, is still a matter of debate. However, the specific impact of the exact aneurysm location has not received adequate attention. Therefore, the aim of this study was to investigate the influence of aneurysm location as a preexisting factor on the clinical course and mortality. Methods The data of consecutive patients with aneurysmal SAH who were treated from October 2010 to July 2020 were retrospectively analyzed. We distinguished four aneurysm locations: the anterior complex, internal carotid artery (ICA), middle cerebral artery (MCA), and posterior circulation. Logistic regression analysis and receiver operating characteristics were used to investigate the influence of aneurysm location on the occurrence of acute hydrocephalus, Delayed Cerebral Ischemia (DCI), neurological outcome, and in-hospital mortality. Neurological outcome was assessed 3 months after discharge using the Glasgow Outcome Scale. Results A total of 603 patients were included in this study. Patients with MCA aneurysms were 2.52 times less likely to develop acute hydrocephalus compared to patients with anterior complex aneurysms (p = 0.001). Delayed cerebral ischemia occurred most frequently in patients with an anterior complex aneurysm and least frequently in MCA aneurysms (p = 0.014). In ICA aneurysms, mortality was 2.56-fold higher than in patients with aneurysms of the anterior complex (p = 0.006). An additional ROC analysis showed a good prediction for in-hospital mortality when taking the aneurysm's location into account [AUC.855 (CI.817 −0.893)]. Conclusions The aneurysm's location proved to be a significant predictor of acute hydrocephalus, DCI, and in-hospital mortality, demonstrating the impact of this preexisting biological factor on the course of SAH.
Morphing-Enabled Path Planning for Flying Tensegrity Robots as a Semidefinite Program

The development of deformable drones is of high importance but presents significant challenges. Such drones can be based on tensegrity structures, which leaves open the questions of configuration-space path planning for such robots. In this paper we propose a method that takes advantage of a simplified encoding of the drone’s shape, allowing to turn the path planning into a sequence of semidefinite programs. The mapping from the simplified description and the actual tensegrity configuration is done via a data-driven method, using a pre-computed dataset of statically stable configurations and their outer Löwner-John ellipsoids, as well as eigendecompositions of the ellipsoid matrices. Together it allows rapid containment check, whose computational cost depends linearly on the number of dataset entries. Thus, the proposed method offloads computationally-intensive parts to the offline dataset generation procedure, speeding up the algorithm execution.
Decline in Mental Health in the Beginning of the COVID-19 Outbreak Among European Older Adults—Associations With Social Factors, Infection Rates, and Government Response

Objective Governments across the world have deployed a wide range of non-pharmaceutical interventions (NPI) to mitigate the spread of COVID-19. Certain NPIs, like limiting social contacts or lockdowns, had negative consequences for mental health in the population. Especially elder people are prone to mental illnesses during the current pandemic. This article investigates how social factors, infections rates, and stringency of NPIs are associated with a decline in mental health in different European countries. Methods Data stem from the eighth wave of the SHARE survey. Additional data sources were used to build macro indicators for infection rates and NPIs. Two subsamples of persons with mental health problems were selected (people who reported being depressed, n = 9.240 or nervous/anxious, n = 10.551). Decline in mental health was assessed by asking whether depressive symptoms or nervousness/anxiety have become worse since the beginning of the COVID-19 outbreak. For each outcome, logistic regression models with survey-design were used to estimate odds ratios (OR), using social factors (age, gender, education, living alone, and personal contacts) and macro indicators (stringency of NPIs and infection rates) as predictors. Results Higher age was associated with a lower likelihood of becoming more depressed (OR 0.87) or nervous/anxious (OR 0.88), while female gender increased the odds of a decline in mental health (OR 1.53 for being more depressed; OR 1.57 for being more nervous/anxious). Higher education was only associated with becoming more nervous/anxious (OR 1.59), while living alone or rare personal contacts were not statistically significant. People from countries with higher infection rates were more likely to become more depressed (OR 3.31) or nervous/anxious (OR 4.12), while stringency of NPIs showed inconsistent associations. Conclusion A majority of European older adults showed a decline in mental health since the beginning of the COVID-19 outbreak. This is especially true in countries with high prevalence rates of COVID-19. Among older European adults, age seems to be a protective factor for a decline in mental health while female gender apparently is a risk factor. Moreover, although NPIs are an essential preventative mechanism to reduce the pandemic spread, they might influence the vulnerability for elderly people suffering from mental health problems.
Fibroblast Activation Protein-Alpha is a Prognostic Biomarker Associated With Ferroptosis in Stomach Adenocarcinoma

Background: The potential role of fibroblast activation protein-alpha (FAP) in modulating the progression and invasion of stomach adenocarcinoma (STAD) has not yet been comprehensively investigated. This study aimed to explore the role of FAP in STAD and the underlying association between FAP and the tumor microenvironment (TME) and ferroptosis. Methods: Overall survival was analyzed to evaluate the prognostic value of FAP based on gene expression data and clinical information on STAD. Associations between FAP expression, clinical parameters, and immune characteristics were comprehensively analyzed. The ferroptosis-related patterns of STAD samples were investigated based on 43 ferroptosis-related genes, and the correlations between these clusters and clinical characteristics were evaluated. The possible biological functions and pathways were explored using gene set enrichment analysis (GSEA). Results: FAP was identified as a novel biomarker that significantly contributed to the poor prognosis of STAD (hazard ratio = 1.270, P = 0.013). The elevated level of FAP expression was related to a more advanced tumor stage in STAD. The close relationship between FAP and the TME was validated. Four distinct ferroptosis-related clusters (A–D) were evident. Evaluating ferroptosis-related clusters could illustrate the stages of STAD and patient prognosis. Cluster C displayed the lowest FAP expression and a better prognosis than the other clusters. The different clusters were linked to different biological mechanisms, including epithelial-mesenchymal transition and immune-relevant pathways. Conclusion: FAP is a promising biomarker to distinguish prognosis and is associated with the TME and ferroptosis in STAD.
Spatial Memory Drives Foraging Strategies of Wolves, but in Highly Individual Ways

The ability of wild animals to navigate and survive in complex and dynamic environments depends on their ability to store relevant information and place it in a spatial context. Despite the centrality of spatial memory, and given our increasing ability to observe animal movements in the wild, it is perhaps surprising how difficult it is to demonstrate spatial memory empirically. We present a cognitive analysis of movements of several wolves (Canis lupus) in Finland during a summer period of intensive hunting and den-centered pup-rearing. We tracked several wolves in the field by visiting nearly all GPS locations outside the den, allowing us to identify the species, location and timing of nearly all prey killed. We then developed a model that assigns a spatially explicit value based on memory of predation success and territorial marking. The framework allows for estimation of multiple cognitive parameters, including temporal and spatial scales of memory. For most wolves, fitted memory-based models outperformed null models by 20 to 50% at predicting locations where wolves chose to forage. However, there was a high amount of individual variability among wolves in strength and even direction of responses to experiences. Some wolves tended to return to locations with recent predation success—following a strategy of foraging site fidelity—while others appeared to prefer a site switching strategy. These differences are possibly explained by variability in pack sizes, numbers of pups, and features of the territories. Our analysis points toward concrete strategies for incorporating spatial memory in the study of animal movements while providing nuanced insights into the behavioral strategies of individual predators.