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Abstract Traumatic brain injury (TBI) is a key contributor to global morbidity that lacks effective treatments. Microbial infections are common in TBI patients, and their presence could modify the physiological response to TBI. It is estimated that one-third of the human population is incurably infected with the feline-borne parasite, Toxoplasma gondii, which can invade the central nervous system and result in chronic low-grade neuroinflammation, oxidative stress, and excitotoxicity—all of which are also important pathophysiological processes in TBI. Considering the large number of TBI patients that have a pre-existing T. gondii infection prior to injury, and the potential mechanistic synergies between the conditions, this study investigated how a pre-existing T. gondii infection modified TBI outcomes across acute, sub-acute and chronic recovery in male and female mice. Gene expression analysis of brain tissue found that neuroinflammation and immune cell markers were amplified in the combined T. gondii + TBI setting in both males and females as early as 2-h post-injury. Glutamatergic, neurotoxic, and oxidative stress markers were altered in a sex-specific manner in T. gondii + TBI mice. Structural MRI found that male, but not female, T. gondii + TBI mice had a significantly larger lesion size compared to their uninfected counterparts at 18-weeks post-injury. Similarly, diffusion MRI revealed that T. gondii + TBI mice had exacerbated white matter tract abnormalities, particularly in male mice. These novel findings indicate that a pre-existing T. gondii infection affects the pathophysiological aftermath of TBI in a sex-dependent manner, and may be an important modifier to consider in the care and prognostication of TBI patients.

Abstract Federated Learning (FL) is a recent Machine Learning method for training with private data locally stored in distributed machines without gathering them into one place for central learning. Because FL depends on a central server for repeated aggregation of local training models, this server is prone to become a performance bottleneck. Therefore, one can combine FL with Edge Computing: introduce a layer of edge servers to each serve as a regional aggregator to offload the main server. The scalability is thus improved, however at the cost of learning accuracy. We show that this cost can be alleviated with a proper choice of edge server assignment: which edge servers should aggregate the training models from which local machines. In this paper, we propose an assignment solution for this purpose. Our solution is especially useful for the case of non-IID training data which is well-known to hinder today’s FL performance. Our findings are substantiated with an evaluation study using real-world datasets.

Abstract Post-vaccination adverse reactions have been reported with varying symptoms and severity owing to research and production time pressures during the coronavirus disease 2019 (COVID-19) pandemic. In this article, we report a rare case of Guillain–Barré syndrome (GBS) in a patient with COVID-19 with acute respiratory distress syndrome (ARDS) after receiving Sinopharm's Vero Cell vaccine (China). The patient who was initially negative for COVID-19 was diagnosed with GBS based on paralysis that developed from the lower extremities to the upper extremities, as confirmed by cytoalbuminologic dissociation in the cerebrospinal fluid. The patient's condition worsened with ARDS caused by COVID-19 infection during the hospital stay, and SpO2 decreased to 83% while receiving oxygen through a non-rebreather mask (15 l/min) on day 6. The patient was treated with standard therapy for severe COVID-19, invasive mechanical ventilation, and five cycles of therapeutic plasma exchange (TPE) with 5% albumin replacement on day 11 due to severe progression. The patient was weaned off the ventilator on day 28, discharged on day 42, and was completely healthy after 6 months without any neurological sequelae until now. Our report showed the potential of TPE for GBS treatment in critically ill patients with COVID-19 after COVID-19 vaccination.

Nanofluids have been widely used as a class of promising working fluids with excellent heat transfer properties. However, the theoretical research on the thermal enhancement mechanism of nanofluids is still in the preliminary stage. Fractional constitutive models provide a new powerful tool to investigate the superior mechanical and thermal properties of nanofluids owing to their advantages in depicting the memory and genetic properties of the system. Fractional nanofluid models have become one of the hot research topics in recent years as better control of flow behavior and heat transfer can be achieved by considering fractional derivatives. The existing studies have indicated that the results obtained by the fractional-order nanofluid model are more consistent with the experimental results than traditional integer-order models. The purpose of this review is to identify the advantages and applications of fractional nanofluid models. First, various definitions of fractional derivatives and correlations of flux utilized in nanofluid modeling are presented. Then, the recent researches on nanofluids with fractional derivatives are sorted and analyzed. The impacts of fractional parameters on flow behaviors and heat transfer enhancement are also highlighted according to the Buongiorno model as well as the Tiwari and Das nanofluid model with fractional operators. Finally, applications of fractional nanofluids in many emerging fields such as solar energy, seawater desalination, cancer therapy, and microfluidic devices are addressed in detail.

IntroductionPost-traumatic epilepsy (PTE) is a debilitating chronic outcome of traumatic brain injury (TBI), and neuroinflammation is implicated in increased seizure susceptibility and epileptogenesis. However, how common clinical factors, such as infection, may modify neuroinflammation and PTE development has been understudied. The neurotropic parasite, Toxoplasma gondii (T. gondii) incurably infects one-third of the world’s population. Thus, many TBI patients have a pre-existing T. gondii infection at the time of injury. T. gondii infection results in chronic low-grade inflammation and altered signaling pathways within the brain, and preliminary clinical evidence suggest that it may be a risk factor for epilepsy. Despite this, no studies have considered how a pre-existing T. gondii infection may alter the development of PTE.MethodsThis study aimed to provide insight into this knowledge gap by assessing how a pre-existing T. gondii infection alters susceptibility to, and severity of, pentylenetetrazol (PTZ)-induced seizures (i.e., a surrogate marker of epileptogenesis/PTE) at a chronic stage of TBI recovery. We hypothesized that T. gondii will increase the likelihood and severity of seizures following PTZ administration, and that this would occur in the presence of intensified neuroinflammation. To test this, 6-week old male and female C57BL/6 Jax mice were intraperitoneally injected with 50,000 T. gondii tachyzoites or with the PBS vehicle only. At 12-weeks old, mice either received a severe TBI via controlled cortical impact or sham injury. At 18-weeks post-injury, mice were administered 40 mg/kg PTZ and video-recorded for evaluation of seizure susceptibility. Fresh cortical tissue was then collected for gene expression analyses.ResultsAlthough no synergistic effects were evident between infection and TBI, chronic T. gondii infection alone had robust effects on the PTZ-seizure response and gene expression of markers related to inflammatory, oxidative stress, and glutamatergic pathways. In addition to this, females were more susceptible to PTZ-induced seizures than males. While TBI did not impact PTZ responses, injury effects were evident at the molecular level.DiscussionOur data suggests that a pre-existing T. gondii infection is an important modifier of seizure susceptibility independent of brain injury, and considerable attention should be directed toward delineating the mechanisms underlying this pro-epileptogenic factor.

Mild traumatic brain injury (mTBI) is a common and unmet clinical issue, with limited treatments available to improve recovery. The cerebrovascular system is vital to provide oxygen and nutrition to the brain, and a growing body of research indicates that cerebrovascular injury contributes to mTBI symptomatology. Vascular endothelial growth factor-A (VEGF-A) is a potent promoter of angiogenesis and an important modulator of vascular health. While indirect evidence suggests that increased bioavailability of VEGF-A may be beneficial after mTBI, the direct therapeutic effects of VEGF-A in this context remains unknown. This study therefore aimed to determine whether intracerebroventricular administration of recombinant VEGF-A could improve recovery from mTBI in a rat model. Male and female Sprague–Dawley rats were assigned to four groups: sham + vehicle (VEH), sham + VEGF-A, mTBI + VEH, mTBI + VEGF-A. The mTBI was induced using the lateral impact model, and treatment began at the time of the injury and continued until the end of the study. Rats underwent behavioral testing between days 1 and 10 post-injury, and were euthanized on day 11 for post-mortem analysis. In males, the mTBI + VEGF-A group had significantly worse cognitive recovery in the water maze than all other groups. In females, the VEGF treatment worsened cognitive performance in the water maze regardless of mTBI or sham injury. Analysis of hippocampal tissue found that these cognitive deficits occurred in the presence of gene expression changes related to neuroinflammation and hypoxia in both male and female rats. These findings indicate that the VEGF-A treatment paradigm tested in this study failed to improve mTBI outcomes in either male or female rats.

From a linguistic perspective it seems intuitive that a strong link would exist between the study of linguistics and critical thinking (CT). After all, linguistics is about making sense of language analysis, which contributes to the enhancement of CT while CT, in reciprocation, enables meaningful analysis. Yet this link has virtually never been clearly defined or made explicit either in studies on linguistics teaching and learning or in those on CT development. This paper explores the relationship between linguistics study and CT in the Vietnamese context from the perspectives of undergraduate English Linguistics students and their lecturers, with a view to improving both students' linguistics study and their CT. Drawing on data collected in questionnaires and interviews at a public university in Vietnam, the findings of the study reveal a variety of aspects of linguistics tasks and classroom activities where the link is significant as well as a range of specific CT skills and dispositions that are related to linguistics teaching and learning. In general, the students and the lecturers showed a positive attitude towards the integration of CT into linguistics teaching and learning, but challenges and barriers to this integration were identified. The study suggests the use of problem-solving tasks and open-ended questions for fostering the reciprocal relationship between linguistics study and CT.

Recently, hybrid capacitive deionization (HCDI) has been a promising desalination technology because of its low cost and effective ion removal ability. The electrode material is an important factor to affect to desalination capacity of HCDI technology. In this study, the nanocomposite electrodes were fabricated successfully based on activated carbon and reduced-graphene oxide/cobalt oxide (rGO-Co3O4) and polymeric binders which were used as cathode electrodes for Hybrid capacitive deionization (HCDI) technology. The effect of polyvinyl alcohol (PVA) and polyvinylidene fluoride (PVDF) polymeric binders and the amount of rGO-Co3O4 on characteristic as well as specific capacitance of the nanocomposite electrodes were investigated. The nanocomposite electrode combined hydrophilic binder of PVA-based and 50 % rGO-Co3O4 has a specific capacitance of 15.3 mg/g in 200 ppm NaCl solution after 25 min at 1.2 V, which is 1.67 times higher than that of the AC-based electrode. [ABSTRACT FROM AUTHOR]

The study conducted in the centre of Vietnam in 2023 aims to explore English-majored students’ perceptions towards the application of ChatGPT in developing students’ English language. The research was grounded on the Technology Acceptance Model developed by Davis (1998) and further revised by Shoufan (2023). The quantitative approach was selected for the study with the questionnaire as the instrument. 369 English-majored students who have experienced using ChatGPT in language learning were selected for the study. The findings reveal that although students found it easy to use ChatGPT as well as perceived it as a useful tool for their language learning, they had neutral opinions on its usefulness. Furthermore, students had a high level of attitudes towards the use of ChatGPT in language learning while the negative attitudes towards it were found to be at a low level. While genders were recognised not to have impacts on students’ perceptions, class levels had significant effects on those of students It is highly recommended that teaching strategies, careful monitoring, and a balance between the use of ChatGPT and human interaction should be under consideration for an effective adoption of ChatGPT in language learning and teaching. [ABSTRACT FROM AUTHOR]

In this work, the unsteady magnetohydrodynamics boundary layer flow and heat transfer of novel generalized Kelvin–Voigt viscoelastic nanofluids over a moving plate are investigated. The classical Kelvin–Voigt constitutive relation is generalized to incorporate a time-fractional derivative to characterize the fluid behavior, which is proved to be of significance and physically justified. The newly developed fractional Kelvin–Voigt constitutive correlation and a dual-phase-lagging constitutive equation are applied to the momentum and energy equations, respectively, for a nanofluid model over a moving plate. The formulated integrodifferential velocity and thermal boundary layer equations are solved using the finite difference method together with a fast algorithm, which reduces the consumed central processing unit time significantly. Several numerical examples are presented to illustrate the influence of the critical parameters on the nanofluid motion and thermal characteristics. Compared to the fractional Maxwell nanofluid model, the velocity boundary layer for the fractional Kelvin–Voigt nanofluid model is thinner. Although the fractional indexes show similar effects on the velocity boundary layer, the impacts of the relaxation parameters are in contrast. This work provides valuable insights into the feasibility of using the fractional Kelvin–Voigt viscoelastic model to depict the fluid flow and heat transfer characteristics of nanofluids. [ABSTRACT FROM AUTHOR]