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Abstract Excessive iron accumulation in the brain cortex increases the risk of cognitive deterioration. However, interregional relationships (defined as susceptibility connectivity) of local brain iron have not been explored, which could provide new insights into the underlying mechanisms of cognitive decline. Seventy-six healthy controls (HC), 58 participants with mild cognitive impairment due to probable Alzheimer’s disease (MCI-AD) and 66 participants with white matter hyperintensity (WMH) were included. We proposed a novel approach to construct a brain susceptibility network by using Kullback‒Leibler divergence similarity estimation from quantitative susceptibility mapping and further evaluated its topological organization. Moreover, sparse logistic regression (SLR) was applied to classify MCI-AD from HC and WMH with normal cognition (WMH-NC) from WMH with MCI (WMH-MCI).The altered susceptibility connectivity in the MCI-AD patients indicated that relatively more connectivity was involved in the default mode network (DMN)-related and visual network (VN)-related connectivity, while more altered DMN-related and subcortical network (SN)-related connectivity was found in the WMH-MCI patients. For the HC vs. MCI-AD classification, the features selected by the SLR were primarily distributed throughout the DMN-related and VN-related connectivity (accuracy = 76.12%). For the WMH-NC vs. WMH-MCI classification, the features with high appearance frequency were involved in SN-related and DMN-related connectivity (accuracy = 84.85%). The shared and specific patterns of the susceptibility network identified in both MCI-AD and WMH-MCI may provide a potential diagnostic biomarker for cognitive impairment, which could enhance the understanding of the relationships between brain iron burden and cognitive decline from a network perspective.

Abstract Background Neuro-navigated repetitive transcranial magnetic stimulation (rTMS) is potentially effective in enhancing cognitive performance in the spectrum of Alzheimer’s disease (AD). We explored the effect of rTMS-induced network reorganization and its predictive value for individual treatment response. Methods Sixty-two amnestic mild cognitive impairment (aMCI) and AD patients were recruited. These subjects were assigned to multimodal magnetic resonance imaging scanning before and after a 4-week stimulation. Then, we investigated the neural mechanism underlying rTMS treatment based on static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) analyses. Finally, the support vector regression was used to predict the individual rTMS treatment response through these functional features at baseline. Results We found that rTMS at the left angular gyrus significantly induced cognitive improvement in multiple cognitive domains. Participants after rTMS treatment exhibited significantly the increased sFNC between the right frontoparietal network (rFPN) and left frontoparietal network (lFPN) and decreased sFNC between posterior visual network and medial visual network. We revealed remarkable dFNC characteristics of brain connectivity, which was increased mainly in higher-order cognitive networks and decreased in primary networks or between primary networks and higher-order cognitive networks. dFNC characteristics in state 1 and state 4 could further predict individual higher memory improvement after rTMS treatment (state 1, R = 0.58; state 4, R = 0.54). Conclusion Our findings highlight that neuro-navigated rTMS could suppress primary network connections to compensate for higher-order cognitive networks. Crucially, dynamic regulation of brain networks at baseline may serve as an individualized predictor of rTMS treatment response. Relevance statement Dynamic reorganization of brain networks could predict the efficacy of repetitive transcranial magnetic stimulation in the spectrum of Alzheimer’s disease. Key points • rTMS at the left angular gyrus could induce cognitive improvement. • rTMS could suppress primary network connections to compensate for higher-order networks. • Dynamic reorganization of brain networks could predict individual treatment response to rTMS. Graphical Abstract

Abstract Background Subjective cognitive decline (SCD) is a preclinical, asymptomatic stage of Alzheimer's disease (AD). Early identification and assessment of progressive SCD is crucial for preventing the onset of AD. Methods The study recruited 60 individuals diagnosed with SCD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Participants were divided into two groups: progressive SCD (pSCD, 23 individuals) and stable SCD (sSCD, 37 individuals) based on their progression to mild cognitive impairment (MCI) within 5 years. Cortical thickness, volumes of the hippocampus subfield, and subcortical regions were analyzed using T1‐weighted images and the FreeSurfer software. Network‐based statistics (NBS) were performed to compare structural covariance networks (SCNs) between the two groups. Results Results showed that the pSCD group showed significant atrophy of the hippocampal‐fimbria (p = .018) and cortical thinning in the left transverse temporal (cluster size 71.84 mm2, cluster‐wise corrected p value = .0004) and left middle temporal gyrus (cluster size 45.05 mm2, cluster‐wise corrected p value = .00639). The combination of these MRI features demonstrated high accuracy (AUC of 0.86, sensitivity of 78.3%, and specificity of 89.3%). NBS analysis revealed that pSCD individuals showed an increase in structural networks within the default mode network (DMN) and a decrease in structural connections between the somatomotor network (Motor) and DMN networks. Conclusion Our findings demonstrate that atrophy of the hippocampus and thinning of the cortex may serve as effective biomarkers for early identification of individuals at high risk of cognitive decline. Changes in connectivity within and outside of the DMN may play a crucial role in the pathophysiology of pSCD.

White matter hyperintensities (WMH) are widely observed in older adults and are closely associated with cognitive impairment. However, the underlying neuroimaging mechanisms of WMH-related cognitive dysfunction remain unknown. This study recruited 61 WMH individuals with mild cognitive impairment (WMH-MCI, n = 61), 48 WMH individuals with normal cognition (WMH-NC, n = 48) and 57 healthy control (HC, n = 57) in the final analyses. We constructed morphological networks by applying the Kullback-Leibler divergence to estimate interregional similarity in the distributions of regional gray matter volume. Based on morphological networks, graph theory was applied to explore topological properties, and their relationship to WMH-related cognitive impairment was assessed. There were no differences in small-worldness, global efficiency and local efficiency. The nodal local efficiency, degree centrality and betweenness centrality were altered mainly in the limbic network (LN) and default mode network (DMN). The rich-club analysis revealed that WMH-MCI subjects showed lower average strength of the feeder and local connections than HC (feeder connections: P = 0.034; local connections: P = 0.042). Altered morphological connectivity mediated the relationship between WMH and cognition, including language (total indirect effect: −0.010; 95 % CI: −0.024, −0.002) and executive (total indirect effect: −0.010; 95 % CI: −0.028, −0.002) function. The altered topological organization of morphological networks was mainly located in the DMN and LN and was associated with WMH-related cognitive impairment. The rich-club connection was relatively preserved, while the feeder and local connections declined. The results suggest that single-subject morphological networks may capture neurological dysfunction due to WMH and could be applied to the early imaging diagnostic protocol for WMH-related cognitive impairment.

Understanding the distinct functions of human muscles could not only help professionals obtain insights into the underlying mechanisms that we accommodate compromised neuromuscular system, but also assist engineers in developing rehabilitation devices. This study aims to determine the contribution of major muscle and the energy flow in the human musculoskeletal system at four sub-phases (collision, rebound, preload, push-off) during the stance of walking at different speeds. Gait experiments were performed with three self-selected speeds: slow, normal, and fast. Muscle forces and mechanical work were calculated by using a subject-specified musculoskeletal model. The functions of individual muscles were characterized as four functional behaviors (strut, spring, motor, damper), which were determined based on the mechanical energy. The results showed that during collision, hip flexors (iliacus and psoas major) and ankle dorsiflexors (anterior tibialis) were the most dominant muscles in buffering the stride with energy absorption; during rebound, the posterior muscles (gluteus maximus, gastrocnemius, posterior tibialis, soleus) contributed the most to energy generation; during preload, energy for preparing push-off was mainly absorbed by the muscles surrounding knee (vastus, semimembranosus, semitendinosus); during push-off, ankle plantar flexors (gastrocnemius, soleus, posterior tibialis, peroneus muscles, flexor digitorum, flexor hallucis) mainly behaved to generate energy for forward propulsion. With increased walking speed, additional energy (almost 400%) from harder stride was mainly absorbed by the flexor muscles. Hip extensors and adductors transferred more energy (around 150%) to the distal segments during rebound. Soleus and gastrocnemius muscles generated more energy (about 75%) to the proximal segments for propulsion. Along with our previous study of joint-level energy analysis, these findings could assist better understanding of human musculoskeletal behaviors during locomotion and provide principles for the bio-design of related assistive devices from motors performance enhancement to rehabilitation such as exoskeleton and prosthesis.

BackgroundThe mechanism of gait and balance dysfunction (GBD) in cerebral small vessel disease (CSVD) remains unclear. Evidence supports cognition engages in GBD of CSVD. The cerebellum is important in motor and cognition, while little is known about the influence of the cerebellum on GBD in CSVD.MethodsThis study is a retrospective cohort study. All participants of this study were enrolled from the CSVD individuals in Nanjing Drum Tower Hospital from 2017 to 2021. The GBD of CSVD patients was defined as Tinetti Test score ≤ 23. Cerebral cortical thickness, cerebellar gray matter volume, the amplitude of low-frequency fluctuation, functional connectivity, and modular interaction were calculated to determine the cortical atrophy and activity patterns of CSVD patients with GBD. The effect of cognitive domains during GBD in CSVD patients was explored by correlation analyses.ResultsA total of 25 CSVD patients were recruited in CSVD patients with GBD group (Tinetti Test score ≤ 23, mean age ± standard deviation: 70.000 ± 6.976 years), and 34 CSVD patients were recruited in CSVD patients without GBD group (Tinetti Test score > 23, mean age ± standard deviation: 64.029 ± 9.453 years). CSVD patients with GBD displayed worse cognitive performance and cortical atrophy in the right cerebellum VIIIa and bilateral superior temporal gyrus than those without GBD. The right postcentral gyrus, left inferior temporal gyrus, right angular gyrus, right supramarginal gyrus and right middle frontal gyrus were functionally overactivated and showed decreased modular interaction with the right cerebellum. Tinetti Test scores were negatively related to the volume of the right cerebellum VIIIa in CSVD patients with GBD. Notably, memory, especially visuospatial memory, was greatly associated with GBD in CSVD.ConclusionThe cortical atrophy and altered functional activity in sensorimotor area and ventral attention network in the cerebellum and cerebrum may underlying the GBD in CSVD. Memory might be critically cognitively responsible for GBD in CSVD.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that progressively affects bulbar and limb function. Despite increasing recognition of the disease as a multinetwork disorder characterized by aberrant structural and functional connectivity, its integrity agreement and its predictive value for disease diagnosis remain to be fully elucidated. In this study, we recruited 37 ALS patients and 25 healthy controls (HCs). High-resolution 3D T1-weighted imaging and resting-state functional magnetic resonance imaging were, respectively, applied to construct multimodal connectomes. Following strict neuroimaging selection criteria, 18 ALS and 25 HC patients were included. Network-based statistic (NBS) and the coupling of grey matter structural–functional connectivity (SC–FC coupling) were performed. Finally, the support vector machine (SVM) method was used to distinguish the ALS patients from HCs. Results showed that, compared with HCs, ALS individuals exhibited a significantly increased functional network, predominantly encompassing the connections between the default mode network (DMN) and the frontoparietal network (FPN). The increased structural connections predominantly involved the inter-regional connections between the limbic network (LN) and the DMN, the salience/ventral attention network (SVAN) and FPN, while the decreased structural connections mainly involved connections between the LN and the subcortical network (SN). We also found increased SC–FC coupling in DMN-related brain regions and decoupling in LN-related brain regions in ALS, which could differentiate ALS from HCs with promising capacity based on SVM. Our findings highlight that DMN and LN may play a vital role in the pathophysiological mechanism of ALS. Additionally, SC–FC coupling could be regarded as a promising neuroimaging biomarker for ALS and shows important clinical potential for early recognition of ALS individuals.

Retinal imaging being a potential biomarker for Alzheimer’s disease is gradually attracting the attention of researchers. However, the association between retinal parameters and AD neuroimaging biomarkers, particularly structural changes, is still unclear. In this cross-sectional study, we recruited 25 cognitively impaired (CI) and 21 cognitively normal (CN) individuals. All subjects underwent retinal layer thickness and microvascular measurements with optical coherence tomography angiography (OCTA). Gray matter and white matter (WM) data such as T1-weighted magnetic resonance imaging and diffusion tensor imaging, respectively, were also collected. In addition, hippocampal subfield volumes and WM tract microstructural alterations were investigated as classical AD neuroimaging biomarkers. The microvascular and retinal features and their correlation with brain structural imaging markers were further analyzed. We observed a reduction in vessel density (VD) at the inferior outer (IO) sector (p = 0.049), atrophy in hippocampal subfield volumes, such as the subiculum (p = 0.012), presubiculum (p = 0.015), molecular_layer_HP (p = 0.033), GC-ML-DG (p = 0.043) and whole hippocampus (p = 0.033) in CI patients. Altered microstructural integrity of WM tracts in CI patients was also discovered in the cingulum hippocampal part (CgH). Importantly, we detected significant associations between retinal VD and gray matter volumes of the hippocampal subfield in CI patients. These findings suggested that the retinal microvascular measures acquired by OCTA may be markers for the early prediction of AD-related structural brain changes.

Cortical visual system dysfunction is closely related to the progression of Alzheimer’s Disease (AD), while retinal vascular structures play an important role in the integrity of the function of the visual network and are a potential biomarker of AD. This study explored the association between the cortical visual system and retinal vascular structures in AD-spectrum patients, and it established a screening tool to detect preclinical AD based on these parameters identified in a retinal examination. A total of 42 subjects were enrolled and were distributed into two groups: 22 patients with cognitive impairment and 20 healthy controls. All participants underwent neuropsychological tests, optical coherence tomography angiography and resting-state fMRI imaging. Seed-based functional connectivity analysis was used to construct the cortical visual network. The association of functional connectivity of the cortical visual system and retinal vascular structures was further explored in these subjects. This study found that the cognitive impairment group displayed prominently decreased functional connectivity of the cortical visual system mainly involving the right inferior temporal gyrus, left supramarginal gyrus and right postcentral gyrus. Meanwhile, we observed that retinal vascular structure characteristics deteriorated with the decline in functional connectivity in the cortical visual system. Our study provided novel insights into the aberrant cortical visual system in patients with cognitive impairment that strongly emphasized the critical role of retinal vascular structure characteristics, which could be used as potential biomarkers for diagnosing and monitoring the progression of AD.

Glymphatic dysfunction has been linked to cognitive decline in several neurodegenerative diseases. In cerebral small vessel disease (CSVD), the mechanism of white matter hyperintensities (WMH)-related cognitive impairment (CI) is still under investigation. The diffusion tensor image (DTI) analysis along the perivascular space (ALPS) method has been considered to be a reliable parameter to evaluate glymphatic function. Therefore, we applied the ALPS-index to determine the influence of glymphatic function on CI in CSVD. In total, 137 CSVD patients (normal cognitive group, mild CI group, and dementia group) and 52 normal controls were included in this study. The ALPS-index was calculated based on the DTI. Correlation analyses and mediation analysis were conducted to examine the relationship between glymphatic function and cognition. Remarkable differences in the ALPS-index were observed between subjects with and without CI. The ALPS-index was negatively correlated with age, WMH volume, and general cognitive function in all CSVD patients. In the mild CI group, the ALPS-index was independently positively related to episodic memory, and mediated the relationship between WMH volume and episodic memory. In conclusion, the ALPS-index is a potential marker for early recognition of CI in CSVD. Glymphatic dysfunction mediates the relationship between WMH and CI in CSVD.

During human walking, mechanical energy transfers between segments via joints. Joint mechanics of the human body are coordinated with each other to adapt to speed change. The aim of this study is to analyze the functional behaviors of major joints during walking, and how joints and segments alter walking speed during different periods (collision, rebound, preload, and push-off) of stance phase. In this study, gait experiment was performed with three different self-selected speeds. Mechanical works of joints and segments were determined with collected data. Joint function indices were calculated based on net joint work. The results show that the primary functional behaviors of joints would not change with altering walking speed, but the function indices might be changed slightly (e.g., strut functions decrease with increasing walking speed). Waist acts as strut during stance phase and contributes to keep stability during collision when walking faster. Knee of stance leg does not contribute to altering walking speed. Hip and ankle absorb more mechanical energy to buffer the strike during collision with increasing walking speed. What is more, hip and ankle generate more energy during push-off with greater motion to push distal segments forward with increasing walking speed. Ankle also produces more mechanical energy during push-off to compensate the increased heel-strike collision of contralateral leg during faster walking. Thus, human may utilize the cooperation of hip and ankle during collision and push-off to alter walking speed. These findings indicate that speed change in walking leads to fundamental changes to joint mechanics.

Abstract Background Previous studies have suggested that tea consumption may have a positive impact on oral health. However, the effects of different tea types on oral health remain unclear. Therefore, this study aimed to determine the association between residual teeth and consumption habits of different types of tea (green tea, black tea, oolong tea, and scented tea) in older adults. Methods We conducted a secondary analysis using data from the Chinese Longitudinal Healthy Longevity Survey in 2018. In a sample of 6,387 older adults, we performed logistic regression analysis to examine the relationship between persistent tea consumption and oral health according to sex and brushing frequency. The indices for particularly healthy oral health and relative health were set at more than 20 teeth and more than 10 teeth, respectively. Results The study included 2,725 males and 3,662 females, both aged 65 and older. Among individuals with more than 20 teeth, drinking green tea significantly improved oral health in men (adjusted odds ratio [ORs]: 1.377; 95% confidence interval [CI]: 1.082–1.752) and drinking black tea significantly improved the oral health of women (ORs: 2.349, 95%CI: 1.028–5.366). In the daily brushing group, green tea had a significant beneficial effect on increasing the number of teeth in men and black tea had a significant beneficial effect in women. Among individuals with more than 10 teeth, drinking green tea significantly improved oral health in men (ORs: 1.539; 95% CI: 1.209–1.959) and drinking green tea and scented tea significantly improved the oral health of women (ORs: 1.447, 95%CI: 1.052–1.991; ORs: 1.948, 95%CI: 1.137–3.340). In the daily brushing group, consumption of green tea and black tea had significant beneficial effects on increasing the number of teeth in men, whereas that of green tea, black tea, and scented tea had significant beneficial effects in women. Conclusion Long-term green tea consumption in males and black tea consumption in females were significantly associated with maintaining functional dentition (≥20 teeth). Similarly, long-term green tea consumption in males and green tea and scented tea consumption in females were associated with avoiding severe tooth loss (≥10 teeth). Furthermore, in the daily tooth brushing group, long-term consumption of black tea was associated with avoiding severe tooth loss in both sexes. However, tea consumption alone had no effect on oral health without good brushing habits.

ABSTRACT: Objective: This study aimed to reveal the geographic accessibility of dental clinics for most municipalities in Japan in 2015 and to explore the association between dental accessibility and dental caries status in 3-year-old children. Methods: We computed the accessibility index and accessibility index rate for the population outside a 1-km radius of dental clinics using a geographic information system. We also used spatial autocorrelation analysis (Moran's I statistic) to examine the spatial clustering patterns of dental accessibility in Japanese municipalities. In addition, we adjusted the prevalence of dental caries for most municipalities using empirical Bayesian estimation. Finally, we applied multiple linear regression to scrutinise the associations between dental caries status, including the prevalence of dental caries and decayed and filled teeth (dft), and dental accessibility, with adjustments made for other sociodemographic variables. Results: The distribution of dental accessibility in Japanese municipalities is relatively unequal. Dental accessibility is decent in the 3 metropolitan areas around Tokyo, Osaka, and Nagoya but poor in the Tohoku and Kyushu regions. In addition, dental accessibility is significantly related to the prevalence of dental caries and dft after adjusting for other sociodemographic variables (P < .005). Conclusions: This study suggests that dental accessibility is considerably connected to the dental caries status of 3-year-old children after excluding financial burden. Preschool children in areas with poor dental accessibility are likely to have poor dental caries status. We also verified the inequality of dental accessibility amongst Japanese municipalities. For the future development of primary oral health care, more attention should be paid to people with a disadvantage in terms of dental accessibility.

An efficient iodine-mediated coupling of cyclic amines with sulfonyl hydrazides is reported. This transformation opens a new route to the synthesis of vinyl sulfones derivatives, which is a common structural motif in natural products and pharmaceuticals. Tentative mechanistic studies suggest that this reaction is likely to involve a radical process. [ABSTRACT FROM AUTHOR]