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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.

Background Policing, corrections, and other carceral institutions are under scrutiny for driving health harms, while receiving disproportionate resources at the expense of prevention and other services. Amidst renewed interest in structural determinants of health, roles of race and class in shaping government investment priorities are poorly understood. Methods Based on the Social Conflict Model, we assessed relationships between city racial/ economic profiles measured by the Index of Concentration at the Extremes (ICE) and budgetary priorities measured by the novel Carceral Resource Index (CRI), contrasting investments in carceral systems with funding for health and social support across the 50 most populous cities in the United States (U.S.). Bivariate correlations, and unadjusted and adjusted polynomial regression models were used to assess the relationship between budgetary investments and population concentration at extremes in terms of income, racial/ethnic composition, and education, controlling for other demographic characteristics. Results In our sample, median CRI was -0.59 (IQR -0.64, -0.45), with only seven cities exhibiting positive CRI values. This indicates that most large U.S. cities spend more on carceral systems than on health and supportive services, combined. Adjusted polynomial models showed a convex relationship between the CRI and ICE-Education, and ICE-Race(White vs. Black)+Income, with quadratic terms that were positive and significant at pConclusions Municipal prioritization of carceral investments over health and social support is pervasive in the U.S and exacerbated by racial and economic disparities. The CRI offers new opportunities to understand the role of government investments as a structural determinant of health and safety. Longitudinal research is warranted to examine the relationship between budget priorities, structural racism, and health outcomes.

Severinia buxifolia (Rutaceae) is a promising source of bioactive compounds since it has been traditionally used for the treatment of various diseases. The present study aimed at evaluating the impact of different solvents on extraction yields, phytochemical constituents and antioxidants, and in vitro anti-inflammatory activities of S. buxifolia. The results showed that the used solvents took an important role in the yield of extraction, the content of chemical components, and the tested biological activities. Methanol was identified as the most effective solvent for the extraction, resulting in the highest extraction yield (33.2%) as well as the highest content of phenolic (13.36 mg GAE/g DW), flavonoid (1.92 mg QE/g DW), alkaloid (1.40 mg AE/g DW), and terpenoids (1.25%, w/w). The extract obtained from methanol exhibited high capacity of antioxidant (IC50 value of 16.99 μg/mL) and in vitro anti-inflammatory activity (i.e., albumin denaturation: IC50 = 28.86 μg/mL; antiproteinase activity: IC50 = 414.29 μg/mL; and membrane stabilization: IC50 = 319 μg/mL). The antioxidant activity of the S. buxifolia extract was found to be 3-fold higher than ascorbic acid, and the anti-inflammatory activity of S. buxifolia extract was comparable to aspirin. Therefore, methanol is recommended as the optimal solvent to obtain high content of phytochemical constituents as well as high antioxidants and in vitro anti-inflammatory constituents from the branches of S. buxifolia for utilization in pharmacognosy.

This study examined the tar characteristic of wood pellet using a downdraft gasifier system. The wood pellet was used as a feedstock with a variation of moisture content between 2 to 6 wt. %. Tar sample was taken using the JP 2009-40885 method. Gas chromatography mass spectrometry and gravimetric analysis were used to identify and to analyze the tar sample, respectively. The results show that an increase in moisture content slightly decreased the total concentration of tar formation on the nine tar compounds of the biomass. Additionally, the lowest moisture content produced the highest amount of light tar on tar classification. The amount of light tar indicates the ease of ignition in the gasifier. Therefore, this condition will minimize the failure-of-equipment problem because of no clogs in the gasifier equipment. The lowest moisture content had the lowest tar density, and this minimized the deposit of tar in the gasifier. Therefore, the lowest moisture content had low tar production in the biomass gasification process using wood pellets.

Introduction. Subjects with asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) share common features of patients with asthma and COPD. Our study was planned to describe the clinical and functional features of subjects with ACO compared to asthma and COPD patients. Subjects and Methods. Study subjects who met the inclusion criteria were classified into three different groups: asthma, COPD, and ACO groups. All study subjects underwent clinical examination and biological and functional testing. They were then followed for 6 months to evaluate the response to conventional treatment. Results. From March 2015 to March 2017, 76 asthmatic (mean age: 41 ± 22 years), 74 COPD (59 ± 13 years), and 59 ACO (52 ± 14 years) subjects were included. The percentage of subjects with dyspnea on excretion in the ACO group was higher than that in asthma and COPD groups (P 15/hour had a significant probability of risk for ACO (OR = 33.2, P

Abstract Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

Abstract Background Shigellosis remains considerable public health problem in some developing countries. The nature of Shigellae suggests that they are highly adaptable when placed under selective pressure in a human population. This is demonstrated by variation and fluctuations in serotypes and antimicrobial resistance profile of organisms circulating in differing setting in endemic locations. Antimicrobial resistance in the genus Shigella is a constant threat, with reports of organisms in Asia being resistant to multiple antimicrobials and new generation therapies. Methods Here we compare microbiological, clinical and epidemiological data from patients with shigellosis over three different periods in southern Vietnam spanning14 years. Results Our data demonstrates a shift in dominant infecting species (S. flexneri to S. sonnei) and resistance profile of the organisms circulating in southern Vietnam. We find that there was no significant variation in the syndromes associated with either S. sonnei or S. flexneri, yet the clinical features of the disease are more severe in later observations. Conclusions Our findings show a change in clinical presentation of shigellosis in this setting, as the disease may be now more pronounced, this is concurrent with a change in antimicrobial resistance profile. These data highlight the socio-economic development of southern Vietnam and should guide future vaccine development and deployment strategies. Trial Registration Current Controlled Trials ISRCTN55945881

Abstract Background Promoter region plays an important role in determining where the transcription of a particular gene should be initiated. Computational prediction of eukaryotic Pol II promoter sequences is one of the most significant problems in sequence analysis. Existing promoter prediction methods are still far from being satisfactory. Results We attempt to recognize the human Pol II promoter sequences from the non-promoter sequences which are made up of exon and intron sequences. Four methods are used: two kinds of multifractal analysis performed on the numeric sequences obtained from the dinucleotide free energy, Z curve analysis and global descriptor of the promoter/non-promoter primary sequences. A total of 141 parameters are extracted from these methods and categorized into seven groups (methods). They are used to generate certain spaces and then each promoter/non-promoter sequence is represented by a point in the corresponding space. All the 120 possible combinations of the seven methods are tested. Based on Fisher's linear discriminant algorithm, with a relatively smaller number of parameters (96 and 117), we get satisfactory discriminant accuracies. Particularly, in the case of 117 parameters, the accuracies for the training and test sets reach 90.43% and 89.79%, respectively. A comparison with five other existing methods indicates that our methods have a better performance. Using the global descriptor method (36 parameters), 17 of the 18 experimentally verified promoter sequences of human chromosome 22 are correctly identified. Conclusion The high accuracies achieved suggest that the methods of this paper are useful for understanding the difficult problem of promoter prediction.