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Can technology-based gait training result in relevant changes of ambulatory function in people with chronic, neurological diagnoses? A longitudinal, cohort study

Objectives To determine whether a six-months technology-based gait training results in relevant changes of ambulatory function in a chronic stage after a neurological event. Further, changes in quality of life will be assessed as well as the willingness to pay for technology-based gait training. Design Single-center, longitudinal cohort study. Setting One outpatient center specialized in neurological rehabilitation. Participants Adults with a chronic neurological diagnosis resulting in residual gait impairments. Intervention Six month of technology-based gait training (with Lokomat, Andago, or C-Mill) with a minimal number of trainings of 10 per month. Primary & secondary outcome measures Walking performance assessed with the 10-meter walk test, 6-minute walk test and functional ambulation category; quality of life assessed with the EQ-5D-3L and WHODAS 2.0; predicted market share and willingness to pay assessed with a choice-based conjoint analysis survey and direct question. Results 27 participants completed three months while 20 completed six months of training. Comparing variables at baseline (BL) and after three (M3) and six (M6) months of training, both the walking speed in the 10-meter walk test (BL: 0.46m/s, M3: 0.54 m/s M6: 0.57 m/s) and the distance covered in the 6-minute walk test (BL: 149m, M3: 155m, M6: 159m) showed improvements that were below the clinically relevant change. The quality of life did not indicate a change. The direct willingness to pay was at CHF 80 which resulted in an estimated market share of 55% based on the conjoint analysis. Conclusion The observed, small changes in ambulatory function in patients with chronic, neurological impairments and the willingness to pay indicates the need to provide technology-based gait training in an outpatient setting.

Berberine treatment inhibits ferroptosis in NIT-1 murine pancreatic cell line via inhibiting OGT expression levels

Near-infrared II cyanine fluorophores with large stokes shift engineered by regulating respective absorption and emission

Perceived challenges and enablers to evaluating a whole systems approach initiative: Reflections of embedded researchers

Physical inactivity remains a substantial public health concern, with complex socio-environmental factors contributing to increasing inactivity. Whole systems approaches to physical activity seek to address these complexities by promoting multi-component, place-based interventions. This study reflects on the experiences of three embedded researchers working within a whole systems approach initiative aimed at reducing physical inactivity in the United Kingdom. Researchers were embedded within a local authority and affiliated to a university whilst responsible for evaluating the effectiveness and efficacy of the whole systems approach initiative. Using a reflective journaling method, followed by inductive thematic analysis, the findings identified key challenges and enablers to evaluating the initiative. Key challenges included the perceived value of research and evaluation within the local authority, a lack of capacity to conduct evaluative activity, and the presence of confirmation and reporting bias within the wider delivery team. Key enablers included relationship-building, skill development, and protected time for evaluation and research activity. The findings suggest that institutions supporting embedded researchers should establish regular contact with the local authority, help to establish realistic expectations, and support researchers to overcome emerging challenges. Recommendations for researchers include developing robust relationships, setting out clear expectations, and ensure they have protected time at key points during the evaluation. Through these recommendations, researchers may be better prepared to overcome implementation challenges and improve the efficiency of the evaluation process.

Dynamic task allocation in fog computing using enhanced fuzzy logic approaches

Cell-guiding microporous hydrogels by photopolymerization-induced phase separation

Abstract Microporous scaffolds facilitate solute transport and cell-material interactions, but materials allowing for spatiotemporally controlled pore formation in aqueous solutions are lacking. Here, we propose cell-guiding microporous hydrogels by photopolymerization-induced phase separation (PIPS) as instructive scaffolding materials for 3D cell culture. We formulate a series of PIPS resins consisting of two ionic polymers (norbornene-functionalized polyvinyl alcohol, dextran sulfate), di-thiol linker and water-soluble photoinitiator. Before PIPS, the polymers are miscible. Upon photocrosslinking, they demix due to the increasing molecular weight and form a microporous hydrogel. The pore size is tunable in the range of 2-40 μm as a function of light intensity, polymer composition and molecular charge. Unlike conventional methods to fabricate porous hydrogels, our PIPS approach allows for in situ light-controlled pore formation in the presence of living cells. We demonstrate that RGD-functionalized microporous hydrogels support high cell viability (>95%), fast cell spreading and 3D morphogenesis. As a proof-of-concept, these hydrogels also enhance the osteogenic differentiation of human mesenchymal stromal cells, matrix mineralization and collagen secretion. Collectively, this study presents a class of cell-guiding microporous hydrogels by PIPS which may find applications in complex tissue engineering.

Identification of a novel chemotherapy benefit index for patients with advanced ovarian cancer based on Bayesian network analysis

Background This study aims to evaluate the efficacy of chemotherapy and optimize treatment strategies for patients with advanced ovarian cancer. Methods Based on The Cancer Genome Atlas (TCGA) transcriptome data, we conducted correlation and Bayesian network analyses to identify key genes strongly associated with chemotherapy prognosis. Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) was used to verify the expression of these key genes. The Chemotherapy Benefit Index (CBI) was developed using these genes via multivariable Cox regression analysis, and validated using both internal and external validation sets (GSE32062 and GSE30161) with a random forest model. Subsequently, we analyzed distinct molecular characteristics and explored additional immunotherapy in CBI-high and CBI-low subgroups. Results Based on the network and machine learning analyses, CBI was developed from the following ten genes: COL6A3, SPI1, HSF1, CD3E, PIK3R4, MZB1, FERMT3, GZMA, PSMB9 and RSF1. Significant differences in overall survival were observed among the CBI-high, medium, and low subgroups (P < 0.001), which were consistent with the two external validation sets (P < 0.001 and P = 0.003). The AUC of internal validation and two external validation cohorts were 0.87, 0.71 and 0.70, respectively. Molecular function analysis indicated that the CBI-low subgroup is characterized by the activation of cancer-related signaling pathways, immune-related biological processes, higher TP53 mutation rate, particularly with a better response to immune checkpoint blockade (ICB) treatment, while the CBI-high subgroup is characterized by inhibition of cell cycle, less response to ICB treatment, and potential therapeutic targets. Conclusions This study provided a novel CBI for patients with advanced ovarian cancer through network analyses and machine learning. CBI could serve as a prognostic prediction tool for patients with advanced ovarian cancer, and also as a potential indicator for immunotherapy.

Modeling energy consumption indexes of an industrial cement ball mill for sustainable production

Abstract The total cement energy consumption is around 5% of global industrial energy usage. In cement plants, mills consume half of this energy for dry grinding particles. However, grinding in tumbling mills is a random process, and a maximum of 5% of this energy would be directly devoted to particle size reduction. Thus, understanding interactions between operation variables and the mill energy consumption factors would be essential for sustainable cement production and green transition. Surprisingly, few investigations were conducted to study the energy consumption indexes of cement mills. Using a conscious lab “CL” as an advanced AI structure for industrial-scale problems could facilitate such an understanding of interactions within cement mill variables and promote controlling energy consumption for sustainable production. To fill the gap, this study developed a CL by examining different AI models (Random Forest, Support Vector Regression, Convolutional Neural Network, extreme gradient boosting, CatBoost, and SHapley Additive exPlanations) for modeling energy consumption indexes of a close ball mill circuit in a cement plant to address the effectiveness of operating variables. Explainable AI modeling highlighted interactions and measured the effectiveness of operating variables on mill energy consumption indexes. The airlift current and separator variables ranked the most effective operating factors on the mill energy consumption indexes. CatBoost, as an advanced AI model, showed the highest prediction accuracy for modeling (R2: 0.90). Such a CL model for a cement mill can be used for training operators, controlling the process, saving time and energy, reducing laboratory work, and scaling issues, and finally enhancing sustainability.

Restoring calcium crosstalk between ER and mitochondria promotes intestinal stem cell rejuvenation through autophagy in aged Drosophila

Binding of transmissible gastroenteritis virus and porcine respiratory coronavirus to human and porcine aminopeptidase N receptors as an indicator of cross-species transmission

Coronaviruses have the ability to overcome interspecies barriers and adapt to new hosts, posing significant epidemic risks in cases of zoonotic transmission to humans. A critical factor in this process is the interaction between coronavirus spike proteins and host cell surface receptors, which plays an important role in infection and disease progression. This study focused on two representatives of coronaviruses: transmissible gastroenteritis virus (TGEV) and its mutant, porcine respiratory coronavirus (PRCV), both of which naturally cause disease in pigs. A phylogenetic analysis of previously identified strains of these viruses was performed, and the conservation of receptor-binding domain (RBD) sequences within their spike proteins was evaluated. In silico modeling was performed for complexes of the RBDs from 16 virus strains with porcine aminopeptidase N (APN), as well as for putative complexes with the human APN receptor. The binding free energy of these modeled complexes was evaluated, along with the impact of more than 500 theoretical mutations in the RBD. The computational results suggest that the TGEV 133 strain exhibits the highest affinity for both porcine and human receptors, with only two additional mutations required to further enhance this affinity. Molecular dynamics simulations were conducted for porcine and human APN complexes with known TGEV strains (Purdue and 133) as well as a theoretical mutated strain. These simulations reveal differences in the dynamic behavior of complexes with porcine and human receptors and support the hypothesis that mutagenesis at a few key amino acid residues in the RBD could enable TGEV to achieve affinity for human APN comparable to that of its natural host receptor. The findings underscore a theoretical risk of zoonotic transmission of these coronaviruses to humans, emphasizing the importance of further monitoring these pathogens.

Scutellarin suppresses ovarian cancer progression by targeting METTL5

A reconfigurable arbitrary retarder array as complex structured matter

Abstract Tuneable retarder arrays, such as spatially patterned liquid crystal devices, have given rise to impressive photonic functionality, fuelling diverse applications ranging from microscopy and holography to encryption and communications. Presently these solutions are limited by the controllable degrees of freedom of structured matter, hindering applications that demand photonic systems with high flexibility and reconfigurable topologies. Here we demonstrate a compound modulator that implements a synthetic tuneable arbitrary retarder array as virtual pixels derived by cascading low functionality tuneable devices, realising full dynamic control of its arbitrary elliptical axis geometry, retardance value, and induced phase. Our approach offers unprecedented functionality that is user-defined and possesses high flexibility, allowing our modulator to act as a new beam generator, analyser, and corrector, opening an exciting path to tuneable topologies of light and matter.

Testing policies during an epidemic: An economic analysis

I build a stochastic epidemiological model with production and endogenous responses to the epidemic to compare different testing policies to isolate and quarantine the infectious: voluntary tests, random screenings and contact tracing. To increase the number of screened individuals at given testing capacity, I also allow for the use of group testing. Contact tracing with group testing is the best testing policy unless in case of: very contagious diseases, socially dense countries, high test costs and limited testing capacity. The gains include a lower mortality, a smaller output loss, and lower peaks of infections and hospitalizations. I show that sophisticated tracing technologies are not needed to achieve these gains.

Spatial neglect after subcortical stroke may reflect cortico-cortical disconnection

Abstract Spatial neglect is commonly attributed to lesions of a predominantly right-hemispheric cortical network. Although spatial neglect was also repeatedly observed after lesions to the basal ganglia and the thalamus, many anatomical network models omit these structures. We investigated if disruption of functional or structural connectivity can explain spatial neglect in subcortical stroke. We retrospectively investigated data of first-ever, acute stroke patients with right-sided lesions of the basal ganglia (n = 27) or the thalamus (n = 16). Based on lesion location, we estimated (i) functional connectivity via lesion-network mapping with normative resting state fMRI data, (ii) structural white matter disconnection using a white matter atlas and (iii) tract-wise disconnection of association fibres based on normative tractography data to investigate the association of spatial neglect and disconnection measures. Apart from very small clusters of functional disconnection observed in inferior/middle frontal regions in lesion-network symptom mapping for basal ganglia lesions, our analyses found no evidence of functional or structural subcortico-cortical disconnection. Instead, the multivariate consideration of lesion load to several association fibres predicted the occurrence of spatial neglect (p = 0.0048; AUC = 0.76), which were the superior longitudinal fasciculus, inferior occipitofrontal fasciculus, superior occipitofrontal fasciculus, and the uncinate fasciculus. Disconnection of long (cortico-cortical) association fibres can explain spatial neglect in subcortical stroke. Like the competing theory of remote cortical hypoperfusion, our finding does not support a genuine role for subcortical grey matter structures in spatial neglect.

Characteristics of the first confirmed case of human infection with mpox virus clade Ib in China

Single cell level analysis of ATP release kinetics and cell fate following ultrasound targeted microbubble cavitation using microscopy techniques

It is known that ultrasound-targeted microbubble cavitation (UTMC) can induce vasodilation. This image-guided spatially targeted approach is called provascular therapy when used as a radiotherapy sensitizer in radiation oncology. Extracellular adenosine-5’-triphosphate (eATP), which plays an important role in vascular tone regulation, is released by cells following UTMC, possibly through sonoporation (formation of temporary and non-deadly pores in the cell membrane) and/or cell death. Herein, we were interested in quantifying UTMC-mediated ATP released in vitro using a microfluidics-based model and study its relationship with cell fate to better understand and improve bioeffects induced by UTMC. Lipid microbubbles (MB, Definity®), luciferin-luciferase (LL – for eATP quantification), and propidium iodide (PI – poration tracer) were flowed over HUVEC cells cultured in a microfluidic device. Ultrasound at 1 MHz, varying in pressure (peak negative pressure: 300, 400 kPa) and length (10, 100, 1000 cycles) were applied to the chip. The LL chemiluminescent signal after the ultrasound pulse was acquired with an EMCCD camera to characterize ATP release kinetics. Then, a viability assay was performed with calcein-AM. An in-house MATLAB program pairing eATP kinetics with PI/calcein data was used to classify cells into three categories (sonoporated, dead, and untreated). Within the testing conditions, a single UTMC pulse caused between 4% and 55% PI-positive (PI+) cells in the ultrasound-treated area. Amongst PI+ cells, we generally found more dead cells than sonoporated cells, except for milder pulses (300 kPa; 10 and 100 cycles). The analysis of individual responses of ATP release demonstrated that dead cells released more ATP (up to 22.4 ± 12.2 fmol/cell) than sonoporated cells (6.8 ± 3.4 fmol/cell) and at a faster release rate which peaked at 4s. This study showed that sonoporation plays a significant role in UTMC-mediated ATP release, advancing our understanding of UTMC’s potential use as a radiosensitizer in solid tumors.

Characterization of the complete mitochondrial genome of Monticola rufiventris and phylogenetic implications

A self-sufficient system for fog-to-water conversion and nitrogen fertilizer production to enhance crop growth

Language and economic behaviour: Future tense use causes less not more temporal discounting

Previous studies have found cross-cultural correlations between linguistic obligations for talking about future events and economic decisions like saving money. The hypothesis is that a grammatical obligation to use the future tense (e.g. will) causes speakers to perceive future rewards as temporally distal and therefore less valuable (“temporal discounting”). However, no studies have tested whether speakers actually temporally discount as a function of the extent to which they use the future tense. We present two studies which use a novel language-elicitation paradigm to do this, involving speakers of English (which obliges the future tense) and Dutch (which does not). We used mediation analysis to test how language-level differences in the grammatical obligation to use the future tense impact economic decisions via individual language use habits. However, we found that English speakers who habitually make greater use of the future tense actually discount less, not more. These results suggest obligatory future tense use is not responsible for previously-reported cross-cultural correlations. Instead, we suggest that a better explanation involves modal notions of certainty (the probability of an event occurring) rather than temporal distance (when an event will occur). Future tenses express high certainty, which makes the correct prediction that obligatory tense marking should cause less discounting. In contrast, the cross-cultural differences may be driven by variation in other aspects of future time reference, such as low-certainty modal terminology (e.g. may, might).

Sediment accumulation by coastal biogenic structures sustains intertidal flats facing sea level rise in the German Wadden sea

Abstract Biogenic structures such as oyster reefs and mussel beds can enhance sedimentation and promote the expansion of intertidal flats in the German Wadden Sea. This study presents large-scale measurements of sedimentation at biogenic structures that depend on biological activities, the hydrodynamic environment and surface roughness. As the surface roughness of intertidal flats has changed with the bioinvasion of the Pacific oyster and the resulting transformation of mussel beds into oyster reefs, we hypothesised that sedimentation rates vary between these structures. To quantify the extent of sedimentation over time, we surveyed bivalve-covered intertidal flats in 2020 and 2022 and generated digital models of the structures and surrounding terrain. The sediment accumulation rates for the mussel bed and oyster reefs reached 3.9 cm³/(cm²*y), with higher rates observed within the mussel bed than within the oyster reefs. Generally, biogenic structures at lower elevations experienced higher sediment accumulation rates. All accumulation rates exceeded previously reported rates for intertidal flats and the current rate of sea level rise in the Wadden Sea. Our findings suggest that oyster reefs and mussel beds have comparable effects on sediment accumulation, supporting the persistence of intertidal flats and thus helping to stabilise the Wadden Sea.