Identification of a novel heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) ligand that disrupts HnRNPA2B1/nucleic acid interactions to inhibit the MDMX-p53 axis in gastric cancer.

Gastric carcinoma is a highly malignant tumor that still lacks effective molecular targets. Heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) is an essential oncogenic driver overexpressed in various cancers. The potential role of hnRNPA2B1 in oncotherapy has not been revealed because of the absence of active chemical molecules. In this study, we identified the pseudourea derivative XI-011 as a novel hnRNPA2B1 ligand using chemical proteomics. An interaction study indicated that XI-011 could bind the nucleotide-binding domain to disrupt the recruitment of hnRNPA2B1 to the promoter and untranslated region of the murine double minute X (MDMX) gene, thereby inhibiting its transcription. In addition, chemical targeting of hnRNPA2B1 recovered inactivated p53 and enhanced the therapeutic efficacy of apatinib in vivo. This work presented a novel strategy to restore p53 activity for the treatment of gastric cancers via chemically targeting hnRNPA2B1.

Metabolomics and transcriptomics provide insights into the flavonoid biosynthesis pathway in the roots of developing Aster tataricus.

Aster tataricus (L.) is an important medicinal plant in China. Its roots are rich in flavonoids, the main medicinal components. However, the molecular basis of flavonoid biosynthesis in the roots of A. tataricus remains unclear. In this study, the content of total flavonoid of A. tataricus roots at different developmental stages was measured first, and the results showed that the content of total flavonoid gradually decreased from September to November, which may be caused by the stagnation of A. tataricus growth due to the decrease in temperature after September. Then, an integrated analysis of transcriptome and metabolome was conducted on five developing stages of A. tataricus roots to identify flavonoid compositions and potential genes involved in flavonoid biosynthesis. A total of 80 flavonoid metabolites, of which 75% were flavonols and flavonoids, were identified in metabolomic analyses, among which isorhamnetin, kaempferol, quercetin, and myricetin were the main skeletons of these flavonoids. Cluster analysis divided these 80 flavonoids into 3 clusters. The compounds in cluster I mainly accumulated in S1, S3, and S5. In cluster II, the relative content of the flavonoid metabolites showed an upward trend from S2 to S4. In cluster III, the flavonoids decreased from S1 to S5. A total of 129 structural genes, including 43 PAL, 23 4CL, 9 C4H, 4 CHS, 18 CHI, 3 F3H, 5 F3'H, 1 F3'5'H, 21 FLS, and 2 FSII, and 65 transcription factors, including 22 AP2/ERF, 7 bHLH, 5 bZIP, 8 MYB, 11 NAC, and 12 WRKY, showed significant correlation with total flavonoid content. Eighteen genes (7 4CL, 5 C4H, 2 CHI, 1 F3H, and 3 FLS) and 30 genes (5 PAL, 9 4CL, 1 C4H, 2 CHI, 1 F3H, 1 DFR, 7 3AT, 1 BZ1, and 3 UGT79B1) were identified as key structural genes for kaempferol and anthocyanins biosynthesis, respectively. Our study provides valuable information for understanding the mechanism of flavonoid biosynthesis in A. tataricus root.

Enhancing vacuum squeezing via magnetic field optimization.

In this paper, we report on -3.5±0.2 dB vacuum squeezing (corresponding to -4.2±0.2 dB with loss correction) at 795 nm via the polarization self-rotation (PSR) effect in rubidium vapor by applying a magnetic field, whose direction is perpendicular to the propagation and polarization of the pump light. Compared with the case without the magnetic field, whose optimal squeezing degree is about -1.5 dB, this weak magnetic field can enhance the PSR effect and ultimately increase the squeezing degree. This compact squeezed light source can be potentially utilized in quantum protocols in which atomic ensembles are involved, such as in quantum memory, atomic magnetometers and quantum interferometers.

Microplastics impacts in seven flagellate microalgae: Role of size and cell wall.

The toxicity of microplastic particles (MPs) on aquatic environments has been widely reported; however, their effects on protists are still contradictory. For example, it is unclear if cell size and cell wall have a role in shaping the response of flagellates to MPs. In this study, seven marine flagellated microalgae (six Dinoflagellates and one Raphidophyceae) were incubated with 10 mg L-1 MPs (polystyrene plastic micro-spheres, 1 µm diameter) to address the above question by measuring different response variables, i.e., growth, optimal photochemical efficiency (Fv/Fm), chlorophyll-a (Chl-a) content, superoxide dismutase (SOD) activity, and cell morphology. The effect of MPs on growth and Fv/Fm showed species-specificity effects. Maximum and minimum MPs-induced inhibitions were detected in Karenia mikimotoi (76.43%) and Akashiwo sanguinea (10.16%), respectively, while the rest of the species showed intermediate responses. The presence of MPs was associated with an average reduction of Chl-a content in most cases and with a higher superoxide dismutase activity in all cases. Seven species were classified into two groups by the variation of Chl-a under MPs treatment. One group (Prorocentrum minimum and Karenia mikimotoi) showed increased Chl-a, while the other (P. donghaiense, P. micans, Alexandrium tamarense, Akashiwo sanguinea, Heterosigma akashiwo) showed decreased Chl-a content. The MPs-induced growth inhibition was negatively correlated with cell size in the latter group. SEM images further indicated that MPs-induced malformation in the smaller cells (e.g., P. donghaiense and K. mikimotoi) was more severe than the bigger cells (e.g., A. sanguinea and P. micans), probably due to a relatively higher ratio of the cell surface to cell volume in the former. These results implicate that the effect of MPs on marine flagellated microalgae was related to the cell size among most species but not cell wall. Thus plastic pollution may have size-dependent effects on phytoplankton in future scenarios.

Real-time batch inspection system for surface defects on circular optical filters.

Optical filters, one of the essential parts of many optical instruments, are used to select a specific radiation band of optical devices. There are specifications for the surface quality of the optical filter in order to ensure the instrument's regular operation. The traditional machine learning techniques for examining the optical filter surface quality mentioned in the current studies primarily rely on the manual extraction of feature data, which restricts their ability to detect optical filter surfaces with multiple defects. In order to solve the problems of low detection efficiency and poor detection accuracy caused by defects too minor and too numerous types of defects, this paper proposes a real-time batch optical filter surface quality inspection method based on deep learning and image processing techniques. The first part proposes an optical filter surface defect detection and identification method for seven typical defects. A deep learning model is trained for defect detection and recognition by constructing a dataset. The second part uses image processing techniques to locate the accurate position of the defect, determine whether the defect is located within the effective aperture, and analyze the critical eigenvalue data of the defect. The experimental results show that the method improves productivity and product quality and reduces the manual workload by 90%. The proposed model and method also compare the results of surface defect detection with the actual measurement data in the field, verifying that the method has good recognition accuracy while improving efficiency.

Quantum enhanced electro-optic sensor for E-field measurement.

The measurement of intense E-field is a fundamental need in various research areas. An electro-optic (EO) sensor based on common path interferometer (CPI) is widely used due to its better temperature stability and controllability of optical bias. However, the small EO coefficient leads to poor sensitivity. In this paper, a quantum enhanced EO sensor is proposed by replacing the vacuum state in classical one with a squeezed-vacuum state. Theoretical analysis shows that the performance of the quantum enhanced EO sensor, including signal to noise ratio (SNR) and sensitivity, can always beat the classical one due to the noise suppression caused by the squeezed-vacuum state. Experimental results demonstrate that, there is still a 1.12dB quantum enhancement compared with the classical one when the degree of the squeezed-vacuum is 1.60dB. More importantly, except the increase of the EO coefficient or the optical power, the performance of the EO sensor can also be enhanced via quantum light source. Such a quantum enhanced EO sensor could be practically applied for the measurement of intense E-field.

Preparation of boronic acid-modified polymer dots under mild conditions and their applications in pH and glucose detection.

For the first time, boronic acid-modified polymer dots (B-PDs) were fabricated by a "synthesis-modification integration" route using polyethylenimine (PEI) and phenylboronic acid as precursors. Under optimized preparation conditions, the B-PDs exhibited an average size of 2.2 nm, good water solubility, and high fluorescence quantum yield of 8.69%. The B-PDs showed reversible fluorescence response in acid solutions (blue emissions) and alkaline solutions (green emissions). The fluorescence emissions of B-PDs demonstrated an obvious red shift with varying the pH value from 1 - 13. Moreover, glucose could assemble on the surface of B-PDs due to the reversible reaction between boronic acid and cis-diols, which resulted in a blue shift of emission wavelength and an obvious increase of FL intensity at λex = 380 nm based on the aggregation-induced enhancement effect. The glucose sensing method was thus developed in the range 0.0001 - 1.0 mol L-1. Applications to real human blood and glucose injection samples demonstrated satisfactory results. The B-PDs based on the analytical method display good selectivity, wide detection range, and simplicity in preparation and detection, implying promising applications as a practical platform for biosensing.

TGF-ß1 sustains germ cell cyst reservoir via restraining follicle formation in the chicken.

The transforming growth factor ß (TGF-ß) superfamily members are important molecules that regulate many ovarian functions under normal physiological and pathological conditions. TGF-ß1 and its receptors are highly expressed in the ovarian cells of many species. However, the effect of TGF-ß1 on the capacity of the avian germ cell reservoir remains unknown. In this study, 5-day-old chicks were injected with TGF-ß1 (2.5, 12.5, and 62.5 µg/kg body weight) for 3 days to assess the effect of TGF-ß1 on early follicle development. Morphological analysis showed that treatment with TGF-ß1 (12.5 µg/kg) increased the number of germ cell cysts and reduced the number of primordial and growing follicles. The diameter and area of oocytes and follicles were decreased after TGF-ß1 treatment. Immunohistochemical staining of the proliferating cell nuclear antigen revealed that the ratios of the positive somatic and granulosa cells were decreased by 16.2% and 2.48%, respectively. Furthermore, more apoptotic cells were observed in the TGF-ß1 group than those of the control by terminal deoxynucleotidyl transferase dUTP nick end labeling assay. In addition, we cultured the 5d chicken ovaries for 3 days in vitro and found that treatment with TGF-ß1 (10 ng/mL) manifested similar results as the in vivo experiment. However, the negative effect of TGF-ß1 on early ovary development was rescued by treatment with a TGF-ßR1 inhibitor SD208, resulting in increased expression of steroidogenic enzymes and cell cycle-regulating proteins. In conclusion, TGF-ß1 could maintain the germ cell reservoir by restraining follicle activation involving reduced cell proliferation and steroidogenic enzymes gene expression at the early stage of ovarian development.

Sensor Fusion-Based Cooperative Trail Following for Autonomous Multi-Robot System.

Autonomously following a man-made trail in the wild is a challenging problem for robotic systems. Recently, deep learning-based approaches have cast the trail following problem as an image classification task and have achieved great success in the vision-based trail-following problem. However, the existing research only focuses on the trail-following task with a single-robot system. In contrast, many robotic tasks in reality, such as search and rescue, are conducted by a group of robots. While these robots are grouped to move in the wild, they can cooperate to lead to a more robust performance and perform the trail-following task in a better manner. Concretely, each robot can periodically exchange the vision data with other robots and make decisions based both on its local view and the information from others. This paper proposes a sensor fusion-based cooperative trail-following method, which enables a group of robots to implement the trail-following task by fusing the sensor data of each robot. Our method allows each robot to face the same direction from different altitudes to fuse the vision data feature on the collective level and then take action respectively. Besides, considering the quality of service requirement of the robotic software, our method limits the condition to implementing the sensor data fusion process by using the "threshold" mechanism. Qualitative and quantitative experiments on the real-world dataset have shown that our method can significantly promote the recognition accuracy and lead to a more robust performance compared with the single-robot system.

[Spatiotemporal Interaction Characteristics and Transition Mechanism of Carbon Intensity in China's Transportation Industry].

This research was conducted using many spatial analysis approaches to dissect the spatiotemporal interactive characteristics of carbon emission intensity within the transportation sector from 2002 to 2020. An in-depth exploration of their transition mechanisms was conducted by nesting the obtained timewarp types with the panel quantile model. Finally, the geodetector model aligned with different transition mechanisms was employed to investigate and analyze the interaction effects among various factors influencing carbon intensity in the transportation sector. The results indicated that:① The carbon emission intensity of the transportation sector in 30 provinces and regions of China showed an overall downward trend with fluctuations, and the spatial clustering level was relatively stable. ② The spatiotemporal interactive features of ESTDA revealed that the relationship between the northwest region and its adjacent spatial units was unstable, with significant variations and fluctuations. In contrast, economically developed areas such as coastal cities in the eastern part had established mature transportation networks, resulting in a relatively stable local spatial pattern, though a few areas still exhibited spatiotemporal competitiveness. ③ The spatiotemporal transition of carbon intensity in the transportation sector could be categorized into four driving or constraining modes(the population economy urbanization constraint model, population economy urbanization facility constraint model, technology consumption industry-driven model, and technology industry regulation-driven model). Most provinces were influenced by the low quantile constraint and high quantile drive modes, with only a few affected by the high quantile constraint and low quantile drive modes, the majority of which were located in the northwest or southwest regions. ④ Further, we introduced the geographical detector model based on the identified mechanism of carbon emission intensity transition in the transportation sector, emphasizing the coordinated development of multiple factors and strengthening inter-regional collaborative governance.

Investigation into the fabrication of plant-based simulant connective tissue utilizing algae polysaccharide-derived hydrogel.

Connective tissue is an important component of meat products that provides support to animal muscles. Hydrogels are considered a promising alternative to connective tissues and simulate actual products by adjusting the gel texture and mouthfeel. This study used soybean protein isolate (SPI), corn starch (CS), konjac glucomannan (KGM), and seaweed powder (SP) as raw materials to examine the effect of different added SP and KGM concentrations on the gel texture. The G' of the gel increased five-fold when the SP and KGM concentration was increased from 1 % to 3 %. The results of mechanical property tests showed that with the addition of SP, the gel hardness increased from 316.00 g to 1827.23 g and the tensile strength increased from 0.027 MPa to 0.089 MPa. Sensory evaluation showed that the samples with 2 % SP and KGM presented the highest overall acceptability score and the most significant similarity to real connective tissue. The connective tissue simulants exhibited excellent water-holding capacity (>90 %), significantly increasing their juiciness. SEM indicated that 2 % KGM addition improved gel network structure stability. The results demonstrate the potential of seaweed polysaccharide-derived hydrogels as connective tissue mimics. This provides a new strategy for the preparation of high mechanical strength hydrogels and lays the foundation for structural diversification of plant-based meat.

Salt ions improve soybean protein isolate/curdlan complex fat substitutes: Effect of molecular interactions on freeze-thaw stability.

Although emulsion gels show significant potential as fat substitutes, they are vulnerable to degreasing, delamination, and other undesirable processes during freezing, storage, and thawing, leading to commercial value loss in terms of juiciness, flavor, and texture. This study investigated the gel strength and freeze-thaw stability of soybean protein isolate (SPI)/curdlan (CL) composite emulsion gels after adding sodium chloride (NaCl). Analysis revealed that adding low salt ion concentrations promoted the hardness and water-holding capacity (WHC) of fat substitutes, while high levels displayed an inhibitory effect. With 40 mM NaCl as the optimum concentration, the hardness increased from 259.33 g (0 mM) to 418.67 g, the WHC increased from 90.59 % to 93.18 %, exhibiting good freeze-thaw stability. Confocal laser scanning microscopy (CLSM) and particle size distribution were used to examine the impact of salt ion concentrations on protein particle aggregation and the damaging effect of freezing and thawing on the proteoglycan complex network structure. Fourier-transform infrared spectroscopy (FTIR) and protein solubility evaluation indicated that the composite gel network structure consisted of covalent contacts between the proteoglycan molecules and hydrogen bonds, playing a predominant role in non-covalent interaction. This study showed that the salt ion concentration in the emulsion gel affected its molecular interactions.

Solution-Processed One-Dimensional Photonic Crystals Based on Hollow Silica Exhibiting High Refractive Index Contrast.

Poor interfacial quality and low refractive index contrast (Δn) are critical challenges for the development of high-performance one-dimensional photonic crystals (1DPhCs) via solution methods that impede their optical efficiency. Herein, we introduce an innovative approach by hybridizing hollow SiO2 with poly(vinyl alcohol), referred to as PHS, followed by alternate assembly with TiO2 via spin-coating, achieving a 1DPhC with Δn = 0.76 at the wavelength of 550 nm. This method circumvents the need for high-temperature treatment and complex curing conditions, resulting in a 1DPhC with superior interfacial and optical characteristics. By adjusting the thickness of the PHS layers, we can finely tune the reflectance spectrum, attaining over 99% reflectance at the photonic band gap. Furthermore, 1DPhC demonstrates excellent adhesion to polycarbonate substrates and retains its optimal optical performance even after rigorous environmental testing, including hygrothermal cycles, exposure to hot water, friction, and solvent sonication. This research paves the way for the facile fabrication of high-performance 1DPhCs under mild conditions, offering new perspectives for photonic material processing.

Effects of Nonimmersive Virtual Reality Intervention on Children With Spastic Cerebral Palsy: A Meta-analysis and Systematic Review.

ABSTRACT: This review aimed to assess the effectiveness of nonimmersive virtual reality intervention compared with traditional rehabilitation in improving the functions of the upper and lower limbs, balance, and social participation among children with spastic cerebral palsy. We used librarian-designed searches of 10 databases to identify research articles on randomized controlled trials that assessed the effectiveness of nonimmersive virtual reality in intervening spastic cerebral palsy patients up to April 15, 2023. Independent evaluation was conducted by two trained investigators using the evaluation criteria of randomized controlled trial quality indicated in the Cochrane Manual of Assessment "risk-of-bias tool." The Physical Therapy Evidence Database scale was used to evaluate the method and quality of the literature. Twenty-one research articles involving 779 patients with spastic cerebral palsy were included. Significant differences between the nonimmersive virtual reality rehabilitation and traditional rehabilitation groups were observed in all indicators, except for the Jebsen-Taylor Hand Function Test. Nonimmersive virtual reality intervention is effective in improving the function of the lower extremity, balance, and social participation in children with spastic cerebral palsy, but its effect on upper limb function is still controversial.

Yellow emissive nitrogen-doped carbon dots as a fluorescence probe for the sensitive and selective detection of silver ions.

In this work, yellow emissive carbon dots (Y-CDs) were prepared via a simple hydrothermal method using catechol and hydrazine hydrate as the carbon and nitrogen sources, respectively. The average particle size was 2.99 nm. The Y-CDs demonstrate excitation-dependent emission properties, and the maximum emission wavelength is 570 nm at E x = 420 nm. The fluorescence quantum yield is calculated to be 28.2%. Ag+ could quench the fluorescence of Y-CDs with high selectivity. The quenching mechanism was further explored by various characterization techniques. A sensitive fluorescent probe for Ag+ detection was established based on Y-CDs with a linear range of 3-300 µM. The detection limit was calculated to be 1.1 µM. The proposed method shows satisfactory results in real water samples without interference by coexistence.

Influence of Surface Discharge on Resin Degradation in Decay-like Fracture of Composite Insulators.

Composite insulators have gradually become the preferred approach for electrical insulation in power systems, especially in polluted areas. Composite insulators consist of three main components: the shed, rod, and end fitting. Insulators withstand mechanical stresses via rods that are composed of glass-fiber-reinforced epoxy (GFRE). However, regardless of the high tensile strength of GFRE rods, in real-life operation, abnormal fractures have frequently been reported all over the world, which substantially increase the risk of major accidents in power systems. Fractural accidents mainly consist of brittle and decay-like fractures, which exhibit rather different morphologies at the cross sections. Brittle fracture has been effectively eliminated, while the mechanism of decay-like fracture has still not been clearly revealed. In this study, surface discharge tests were applied to investigate the discharge influence on the degradation of GFRE. The test successfully simulated the composition variation of the rods in real-life composite insulators with decay-like fractures. Moreover, it confirmed that the distinction between the characteristics of brittle fracture and decay-like fracture stems from epoxy degradation due to hydrolysis and carbonization. In addition, the respective influences of the resin type, glass fiber type, and acid liquid immersion on the degradation process were probed, and the degradation mechanism proposed in this research was verified. Based on the results, measures for preventing the development of decay-like fractures in real-life operations were determined.

Ferric Chloride Controls Citrus Anthracnose by Inducing the Autophagy Activity of Colletotrichum gloeosporioides.

Colletotrichum gloeosporioides causes citrus anthracnose, which seriously endangers the pre-harvest production and post-harvest storage of citrus due to its devastating effects on fruit quality, shelf life, and profits. However, although some chemical agents have been proven to effectively control this plant disease, little to no efforts have been made to identify effective and safe anti-anthracnose alternatives. Therefore, this study assessed and verified the inhibitory effect of ferric chloride (FeCl3) against C. gloeosporioides. Our findings demonstrated that FeCl3 could effectively inhibit C. gloeosporioides spore germination. After FeCl3 treatment, the germination rate of the spores in the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) groups decreased by 84.04% and 89.0%, respectively. Additionally, FeCl3 could effectively inhibit the pathogenicity of C. gloeosporioides in vivo. Optical microscopy (OM) and scanning electron microscopy (SEM) analyses demonstrated the occurrence of wrinkled and atrophic mycelia. Moreover, FeCl3 induced autophagosome formation in the test pathogen, as confirmed by transmission electron microscopy (TEM) and monodansylcadaverine (MDC) staining. Additionally, a positive correlation was identified between the FeCl3 concentration and the damage rate of the fungal sporophyte cell membrane, as the staining rates of the control (untreated), 1/2 MIC, and MIC FeCl3 treatment groups were 1.87%, 6.52%, and 18.15%, respectively. Furthermore, the ROS content in sporophyte cells increased by 3.6%, 29.27%, and 52.33% in the control, 1/2 MIC, and MIC FeCl3 groups, respectively. Therefore, FeCl3 could reduce the virulence and pathogenicity of C. gloeosporioides. Finally, FeCl3-handled citrus fruit exhibited similar physiological qualities to water-handled fruit. The results show that FeCl3 may prove to be a good substitute for the treatment of citrus anthracnose in the future.

The GRAS Salts of Na2SiO3 and EDTA-Na2 Control Citrus Postharvest Pathogens by Disrupting the Cell Membrane.

Sodium silicate (Na2SiO3) and ethylenediaminetetraacetic acid disodium salt (EDTA-Na2) are inorganic salts classified as 'Generally Recognized as Safe' (GRAS) compounds with great advantages in controlling various pathogens of postharvest fruits and vegetables. Here, we determined the median effective concentration (EC50) of Na2SiO3 (0.06%, 0.05%, 0.07% and 0.08%) and EDTA-Na2 (0.11%, 0.08%, 0.5%, and 0.07%) against common pathogens affecting postharvest citrus fruit, including Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii, and Colletotrichum gloeosporioides. Na2SiO3 and EDTA-Na2 treatments at the EC50 decreased the spore germination rate, visibly disrupted the spore cell membrane integrity, and significantly increased the lipid droplets (LDs) of the four postharvest pathogens. Moreover, both treatments at EC50 significantly reduced the disease incidence of P. italicum (by 60% and 93.335, respectively) and G. citri-aurantii (by 50% and 76.67%, respectively) relative to the control. Furthermore, Na2SiO3 and EDTA-Na2 treatment resulted in dramatically lower disease severity of the four pathogens, while also demonstrating no significant change in citrus fruit quality compared with the control. Therefore, Na2SiO3 and EDTA-Na2 present a promising approach to control the postharvest diseases of citrus fruit.

Novel automaticity index reveals a cognitive ability-related decline in gait automaticity during dual-task walking.

Gait automaticity refers to the ability to walk with minimal recruitment of attentional networks typically mediated through the prefrontal cortex (PFC). Reduced gait automaticity is common with aging, contributing to an increased risk of falls and reduced quality of life. A common assessment of gait automaticity involves examining PFC activation using near-infrared spectroscopy (fNIRS) during dual-task (DT) paradigms, such as walking while performing a cognitive task. However, neither PFC activity nor task performance in isolation measures automaticity accurately. For example, greater PFC activation could be interpreted as worse gait automaticity when accompanied by poorer DT performance, but when accompanied by better DT performance, it could be seen as successful compensation. Thus, there is a need to incorporate behavioral performance and PFC measurements for a more comprehensive evaluation of gait automaticity. To address this need, we propose a novel automaticity index as an analytical approach that combines changes in PFC activity with changes in DT performance to quantify gait automaticity. We validated the index in 173 participants (≥65 y/o) who completed DTs with two levels of difficulty while PFC activation was recorded with fNIRS. The two DTs consisted of reciting every other letter of the alphabet while walking over either an even or uneven surface. We found that as DT difficulty increases, more participants showed the anticipated decrease in automaticity as measured by the novel index compared to PFC activation. Furthermore, when comparing across individuals, lower cognitive function related to worse automaticity index, but not PFC activation or DT performance. In sum, the proposed index better quantified the differences in automaticity between tasks and individuals by providing a unified measure of gait automaticity that includes both brain activation and performance. This new approach opens exciting possibilities to assess participant-specific deficits and compare rehabilitation outcomes from gait automaticity interventions.

Novel attentional gait index reveals a cognitive ability-related decline in gait automaticity during dual-task walking.

Introduction: Gait automaticity refers to the ability to walk with minimal recruitment of attentional networks typically mediated through the prefrontal cortex (PFC). Reduced gait automaticity (i.e., greater use of attentional resources during walking) is common with aging, contributing to an increased risk of falls and reduced quality of life. A common assessment of gait automaticity involves examining PFC activation using near-infrared spectroscopy (fNIRS) during dual-task (DT) paradigms, such as walking while performing a cognitive task. However, neither PFC activity nor task performance in isolation measures automaticity accurately. For example, greater PFC activation could be interpreted as worse gait automaticity when accompanied by poorer DT performance, but when accompanied by better DT performance, it could be seen as successful compensation. Thus, there is a need to incorporate behavioral performance and PFC measurements for a more comprehensive evaluation of gait automaticity. To address this need, we propose a novel attentional gait index as an analytical approach that combines changes in PFC activity with changes in DT performance to quantify automaticity, where a reduction in automaticity will be reflected as an increased need for attentional gait control (i.e., larger index). Methods: The index was validated in 173 participants (≥65 y/o) who completed DTs with two levels of difficulty while PFC activation was recorded with fNIRS. The two DTs consisted of reciting every other letter of the alphabet while walking over either an even or uneven surface. Results: As DT difficulty increases, more participants showed the anticipated increase in the attentional control of gait (i.e., less automaticity) as measured by the novel index compared to PFC activation. Furthermore, when comparing across individuals, lower cognitive function was related to higher attentional gait index, but not PFC activation or DT performance. Conclusion: The proposed index better quantified the differences in attentional control of gait between tasks and individuals by providing a unified measure that includes both brain activation and performance. This new approach opens exciting possibilities to assess participant-specific deficits and compare rehabilitation outcomes from gait automaticity interventions.