Incidence, Etiology and Prognosis of Initial Liver Injury After Allogeneic Hematopoietic Stem Cell Transplantation: A Multi-Center Retrospective Study.

BACKGROUND: Liver injury post allogeneic hematopoietic stem cell transplantation (Allo-HSCT), particularly first-time occurrences, is a prevalent and severe complication. METHODS: Clinical data from 262 patients treated at 3 medical centers in Shenzhen, China, between January 2018 and December 2021 were retrospectively collected. Risk factors and outcomes of initial liver injury post allo-HSCT were analyzed. RESULTS: Liver injury occurred in 70.8% of patients, with drug-induced liver injury (DILI) being the most common cause. Other causes included graft-versus-host disease (GVHD) and veno-occlusive disease (VOD). Pre-transplant HBsAg positivity was a significant risk factor. Differences in the timing and survival outcomes were observed among patients with different causes and types of liver injury. Patients with VOD or hepatic aGVHD had lower overall survival compared to those with DILI or hepatic cGVHD. Patients with isolated enzyme elevation had a more favorable prognosis than those with isolated bilirubin elevation or simultaneous enzyme and bilirubin elevation. CONCLUSION: Findings of our study serve as a crucial resource for clinicians, assisting in the challenging task of diagnosing and managing liver injuries after allo-HSCT, especially when it occurs for the first time, which may ultimately help to reduce early treatment-related mortality and enhance the long-term survival of transplant recipients.

A machine-learning approach to model risk and protective factors of vulnerability to depression.

There are multiple risk and protective factors for depression. The association between these factors with vulnerability to depression is unclear. Such knowledge is an important insight into assessing risk for developing depression for precision interventions. Based on the behavioral data of 496 participants (all unmarried and not cohabiting, with a college education level or above), we applied machine-learning approaches to model risk and protective factors in estimating depression and its symptoms. Then, we employed Random Forest to identify important factors which were then used to differentiate participants who had high risk of depression from those who had low risk. Results revealed that risk and protective factors could significantly estimate depression and depressive symptoms. Feature selection revealed four key factors including three risk factors (brooding, perceived loneliness, and perceived stress) and one protective factor (resilience). The classification model built by the four factors achieved an ROC-AUC score of 75.50% to classify the high- and low-risk groups, which was comparable to the classification performance based on all risk and protective factors (ROC-AUC = 77.83%). Based on the selected four factors, we generated a mood vulnerability index useful for identifying people's risk for depression. Our findings provide potential clinical insights for developing quick screening tools for mood disorders and potential targets for intervention programs designed to improve depressive symptoms.

Changes in the antioxidant and anti-inflammatory activities of Rosa rugosa 'Mohong' during fermentation.

Fermented rose petals are a traditional delicacy of the Dali Bai community in Yunnan, China. Fermentation enhances the quality and nutritional value of roses, as well as their efficacy, by increasing the levels of phenolic compounds. This study aimed to investigate the significant variations in four active compounds throughout the traditional fermentation process. Four compounds in Rosa rugosa 'Mohong' were examined, and significant variations among polyphenols and antioxidant and anti-inflammatory activities were observed. These variations were studied during fermentation by Saccharomyces rouxii at varying temperatures and durations. Moreover, the results showed that gallic acid and syringic acid content significantly increased (P < 0.05) with a rise in temperature from 20°C-35 °C during fermentation. Simultaneously, rutin and quercetin levels significantly decreased (P < 0.05) at all four temperatures throughout the five periods. The antioxidant and anti-inflammatory activities of fermented R. rugosa 'Mohong' methanol extracts were dose-dependent. Our results provide valuable insights into optimizing the processing scale and quality control of fermented rose products.

Brain network hierarchy reorganization in subthreshold depression.

BACKGROUND: Hierarchy is the organizing principle of human brain network. How network hierarchy changes in subthreshold depression (StD) is unclear. The aim of this study was to investigate the altered brain network hierarchy and its clinical significance in patients with StD. METHODS: A total of 43 patients with StD and 43 healthy controls matched for age, gender and years of education participated in this study. Alterations in the hierarchy of StD brain networks were depicted by connectome gradient analysis. We assessed changes in network hierarchy by comparing gradient scores in each network in patients with StD and healthy controls. The study compared different brain subdivisions if there was a different network. Finally, we analysed the relationship between the altered gradient scores and clinical characteristics. RESULTS: Patients with StD had contracted network hierarchy and suppressed cortical range gradients. In the principal gradient, the gradient scores of default mode network were significantly reduced in patients with StD compared to controls. In the default network, the subdivisions of reduced gradient scores were mainly located in the precuneus, superior temporal gyrus, and anterior and posterior cingulate gyrus. Reduced gradient scores in the default mode network, the anterior and posterior cingulate gyrus were correlated with severity of depression. CONCLUSIONS: The network hierarchy of the StD changed and was significantly correlated with depressive symptoms and severity. These results provided new insights into further understanding of the neural mechanisms of StD.

Value of the virtual monoenergetic image from dual-layer dual-energy computed tomography enterography in the preoperative assessment of the internal penetrating complication of Crohn's disease.

BACKGROUND: To determine the utility of virtual-monoenergetic imaging (VMI) at low energy levels from contrast-enhanced dual-layer dual-energy (DLDE) computed tomography enterography (CTE) in the preoperative assessment of internal penetrating lesions of Crohn's disease (CD). MATERIALS AND METHODS: Thirty-eight patients with penetrating lesions of CD by surgery undergoing contrast-enhanced DLDE CTE were retrospectively included. Polyenergetic imaging (PEI) and VMIs at low energy levels [40-70 kiloelectron volts (keV)] with 10 keV intervals were reconstructed. The objective parameters of image quality [noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR)] and the subjective parameter of image quality [diagnostic performance of lesions (DPL), overall image quality(OIQ)] of PEI and all VMIs at the low energy level were compared to determine the VMI on the optimal energy level. The lesion detection capability between PEI and the optimal VMI was compared. RESULTS: VMI40 was determined to be the optimal VMI among all VMIs at the low energy level for owning the best image quality. No significant difference was found in the detecting capability in penetrating lesions between VMI40 and PEI (p = 1.0), whereas a significant difference was found in the detecting capability in the bowel origin of the penetrating lesions (p = 0.004), the involved organ or structure by the fistula (p = 0.016) and the orifice of the fistula connected to the involved organ or structure ( p = 0.031) between them. CONCLUSIONS: Compared to conventional PEI, VMI40 improves the detection capability in anatomical details of penetrating lesions of CD, helping colorectal surgeons rationalizing preoperative plans of internal penetrating lesions of CD.

Feasibility, safety, and efficacy of task-oriented mirrored robotic training on upper-limb functions and activities of daily living in subacute poststroke patients: a pilot study.

BACKGROUND: Robotic training with high repetitions facilitates upper-limb movements but provides fewer benefits for activities of daily living. Integrating activities of daily living training tasks and mirror therapy into a robot may enhance the functional gains of robotic training. AIM: The aim of this study was to investigate the feasibility, safety, and efficacy of the task-oriented mirrored upper-limb robotic training on the upper-limb functions and activities of daily living of subacute poststroke patients. DESIGN: This study is a single-blinded, active-controlled pilot study. SETTING: The study was carried out at rehabilitation outpatient clinic and ward. POPULATION: A total of 32 subacute poststroke patients were enrolled in the study. METHODS: The enrolled patients were allocated into two groups in a ratio of 1:1. The experimental group received 4 weeks of task-oriented mirrored upper-limb robotic training, consisting of five sessions of 30-minute duration, along with 30 minutes of conventional training. The control group only received 60 minutes of conventional training. The outcome measures were the Fugl-Meyer Assessment Scale for Upper Extremity, Modified Barthel Index, Stroke Self-Efficacy Scale, System Usability Scale, and Quebec User Evaluation with Assistive Technology. RESULTS: All patients completed the full training sessions without significant adverse events related to robotic training. The task-oriented mirrored upper-limb robotic training led to increased Fugl-Meyer Assessment Scale for Upper Extremity (difference: 10.38 points, P<0.001) and Modified Barthel Index (difference: 18.38 points, P<0.001) scores, both of which exceeded the minimal clinically important difference. Intergroup analysis showed significantly higher improvements in the Fugl-Meyer Assessment Scale for Upper Extremity total scores, shoulder, wrist, and hand scores; and Modified Barthel Index scores in the experimental group than in conventional training (all P<0.05). Both groups showed significant improvements in Stroke Self-Efficacy Scale scores after the intervention (both P<0.001), but without a statistically significant intergroup difference (P>0.05). Participants in the experimental group scored an average usability perception score of 74.74 (good) and an average satisfaction score of four or more out of five. CONCLUSIONS: In general, task-oriented mirrored upper-limb robotic training appears feasible and safe for subacute poststroke rehabilitation, facilitating the recovery of upper-limb functions and activities of daily living. CLINICAL REHABILITATION IMPACT: Task-oriented mirrored upper-limb robotic training shows promise for future clinical rehabilitation and clinical trials involving subacute poststroke patients.

Effects of computerized cognitive training on structure‒function coupling and topology of multiple brain networks in people with mild cognitive impairment: a randomized controlled trial.

BACKGROUND: People with mild cognitive impairment (MCI) experience a loss of cognitive functions, whose mechanism is characterized by aberrant structure‒function (SC-FC) coupling and topological attributes of multiple networks. This study aimed to reveal the network-level SC-FC coupling and internal topological changes triggered by computerized cognitive training (CCT) to explain the therapeutic effects of this training in individuals with MCI. METHODS: In this randomized block experiment, we recruited 60 MCI individuals and randomly divided them into an 8-week multidomain CCT group and a health education control group. The neuropsychological outcome measures were the Montreal Cognitive Assessment (MoCA), Chinese Auditory Verbal Learning Test (CAVLT), Chinese Stroop Color-Word Test (SCWT), and Rey-Osterrieth Complex Figure Test (Rey CFT). The brain imaging outcome measures were SC-FC coupling and topological attributes using functional MRI and diffusion tensor imaging methods. We applied linear model analysis to assess the differences in the outcome measures and identify the correspondence between the changes in the brain networks and cognitive functions before and after the CCT. RESULTS: Fifty participants were included in the analyses after the exclusion of three dropouts and seven participants with low-quality MRI scans. Significant group × time effects were found on the changes in the MoCA, CAVLT, and Rey CFT recall scores. The changes in the SC-FC coupling values of the default mode network (DMN) and somatomotor network (SOM) were higher in the CCT group than in the control group (P(unc.) = 0.033, P(unc.) = 0.019), but opposite effects were found on the coupling values of the visual network (VIS) (P(unc.) = 0.039). Increasing clustering coefficients in the functional DMN and SOM and subtle changes in the nodal degree centrality and nodal efficiency of the right dorsal medial prefrontal cortex, posterior cingulate cortex, left parietal lobe, somatomotor area, and visual cortex were observed in the CCT group (P < 0.05, Bonferroni correction). Significant correspondences were found between global cognitive function and DMN coupling values (P(unc.) = 0.007), between immediate memory and SOM as well as FPC coupling values (P(unc.) = 0.037, P(unc.) = 0.030), between delayed memory and SOM coupling values (P(unc.) = 0.030), and between visual memory and VIS coupling values (P(unc.) = 0.007). CONCLUSIONS: Eight weeks of CCT effectively improved global cognitive and memory functions; these changes were correlated with increases in SC-FC coupling and changes in the topography of the DMN and SOM in individuals with MCI. The CCT regimen also modulated the clustering coefficient and the capacity for information transformation in functional networks; these effects appeared to underlie the cognitive improvement associated with CCT. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2000034012. Registered on 21 June 2020.

Effect of Tai Chi on Young Adults with Subthreshold Depression via a Stress-Reward Complex: A Randomized Controlled Trial.

BACKGROUND: Subthreshold depression is a highly prevalent mood disorder in young adults. Mind-body exercises, such as Tai Chi, have been adopted as interventions for clinical depressive symptoms. However, the possible effect and underlying mechanism of Tai Chi on subthreshold depression of young individuals remain unclear. This randomized controlled study aimed to evaluate the effects of Tai Chi training and tested the combined stress and reward circuitry model for subthreshold depression. RESULTS: A total of 103 participants completed this trial, with 49 in the 12-week 24-style Tai Chi group and 54 participants in control group. Our results showed significantly lower scores on depressive symptoms (P = 0.002) and anxiety symptoms (P = 0.009) and higher scores on quality of life (P = 0.002) after Tai Chi training. There were significant reductions in salivary cortisol levels (P = 0.007) and putamen gray matter volume (P < 0.001) in the Tai Chi group. The changes in cortisol levels and putamen gray matter volume had direct (bootstrapping confidence interval [- 0.91, - 0.11]) and indirect effects (bootstrapping confidence interval [- 0.65, - 0.19]) on the changes induced by Tai Chi training on depressive symptoms, respectively. CONCLUSION: The stress-reward complex results indicated an interaction between lowering stress levels and increasing reward circuitry activity associated with the alleviation of depressive symptoms among participants. The 12-week Tai Chi training was effective in improving the symptoms and quality of life of young adults with subthreshold depression. Trial Registration Chinese Registry of Clinical Trials (Registration Number: ChiCTR1900028289, Registered December 12, 2019).

Effects of Tai Chi combined with tDCS on cognitive function in patients with MCI: a randomized controlled trial.

Background: Mild cognitive impairment (MCI) is a critical stage of dementia. Previous reviews have suggested that physical exercise combined with non-invasive brain stimulation is more beneficial for improving cognitive function. However, no targeted studies have confirmed the effect of Tai Chi combined with transcranial direct current stimulation (tDCS) on the improvement of cognitive function in patients with MCI. Thus, this randomized trial was conducted to assess the effect of Tai Chi combined with tDCS on the cognitive performance of patients with MCI. Methods: From April 2018 to February 2020, a randomized, single-blind clinical trial was conducted, involving 180 participants with MCI who were divided into four intervention groups: Tai Chi combined with tDCS (TCT), Tai Chi combined with sham tDCS (TCS), walking combined with tDCS (WAT), and walking combined with sham tDCS (WAS). All participants were assessed at baseline and 12 weeks for global cognitive function, memory, attention, and executive function. Results: At baseline, there were no significant differences in age, gender, education duration, body mass index, or the Baker Depression Inventory among the four groups (P ≥ 0.05). After 12 weeks of intervention, the TCT group showed greater improvements in MOCA scores, memory quotient scores, and digit-symbol coding task reaction time compared to the TCS, WAS, and WAT groups (P < 0.05). The TCT group also had a shorter Stroop test color reaction time compared to the WAS and WAT groups (P < 0.05), a higher increase in Auditory Verbal Learning Test-immediate recall than the TCS and WAT groups (P < 0.05), a shorter visual reaction time than the TCS group (P < 0.05), and a shorter sustained attention time compared to the WAT group (P < 0.05). Conclusion: Tai Chi combined with tDCS effectively improves global cognitive performance, memory, execution function, and attention in patients with MCI. These findings suggest the potential clinical use of Tai Chi combined with tDCS as a physical exercise combined with a non-invasive brain stimulation intervention to improve cognitive function in older adults with MCI. Clinical trial registration: ChiCTR1800015629.

Effects of dorsolateral prefrontal cortex stimulation on network topological attributes in young individuals with high-level perceived stress: A randomized controlled trial.

Individuals with high-level perceived stress are at higher risk of developing a psychiatric disorder. While repetitive transcranial magnetic stimulation (rTMS) is effective for improving emotional symptoms, there is little evidence of its effect on perceived stress. This randomized sham-controlled trial investigated the effect of rTMS on ameliorating high-level stress and explored the associated changes in brain network activity. Fifty participants with high-level perceived stress were randomly assigned to either the active or sham rTMS group and received 12 active/sham rTMS sessions over four weeks (three per week). Perceived stress score (PSS), Chinese affective scale (CAS) normal and now statuses, and functional network topology were measured. Our results showed greater improvements in PSS and CAS_Normal scores, and reduced path length in the default mode network after active rTMS. Functional activations of the angular gyrus, posterior insula, and prefrontal cortex were also modulated in the active group. There were significant associations between posterior insula efficiency and PSS scores, and between angular efficiency and CAS_Now scores in the active group. These cumulative findings suggest rTMS as a promising intervention for recovery from high-level perceived stress.

Abiotrophia defectiva causing infective endocarditis with brain infarction and subarachnoid hemorrhage: a case report.

Introduction: A rare pathogen of Infective Endocarditis (IE), the Abiotrophia defectiva, has been known to trigger life-threatening complications. The case discussed here is of a teenager with brain infarction and subarachnoid hemorrhage caused by IE due to A. defectiva. Case report: A 15-year-old girl with movement disorders involving the left limbs and intermittent fevers was admitted to the hospital. A head CT scan revealed cerebral infarction in the right basal ganglia and subarachnoid hemorrhage. Moreover, vegetation on the mitral valve were confirmed by echocardiography. The blood cultures were found to be positive for Gram-positive streptococcus and identified by Vitek mass spectrometry as A. defectiva. She was prescribed vancomycin antibacterial therapy and underwent a surgical mitral valve replacement. Conclusion: This case is suggestive of the fact that A. defectiva is a rare but crucial pathogen of IE-associated stroke. Obtaining early blood cultures and using microbial mass spectrometry could help achieve an accurate diagnosis. Moreover, reasonable anti-infective medications and surgical interventions need to be combined to avoid and/or manage severe complications.

Global trends and hotspots in the digital therapeutics of autism spectrum disorders: a bibliometric analysis from 2002 to 2022.

Introduction: Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that has become a major cause of disability in children. Digital therapeutics (DTx) delivers evidence-based therapeutic interventions to patients that are driven by software to prevent, manage, or treat a medical disorder or disease. This study objectively analyzed the current research status of global DTx in ASD from 2002 to 2022, aiming to explore the current global research status and trends in the field. Methods: The Web of Science database was searched for articles about DTx in ASD from January 2002 to October 2022. CiteSpace was used to analyze the co-occurrence of keywords in literature, partnerships between authors, institutions, and countries, the sudden occurrence of keywords, clustering of keywords over time, and analysis of references, cited authors, and cited journals. Results: A total of 509 articles were included. The most productive country and institution were the United States and Vanderbilt University. The largest contributing authors were Warren, Zachary, and Sarkar, Nilanjan. The most-cited journal was the Journal of Autism and Developmental Disorders. The most-cited and co-cited articles were Brian Scarselati (Robots for Use in Autism Research, 2012) and Ralph Adolphs (Abnormal processing of social information from faces in autism, 2001). "Artificial Intelligence," "machine learning," "Virtual Reality," and "eye tracking" were common new and cutting-edge trends in research on DTx in ASD. Discussion: The use of DTx in ASD is developing rapidly and gaining the attention of researchers worldwide. The publications in this field have increased year by year, mainly concentrated in the developed countries, especially in the United States. Both Vanderbilt University and Yale University are very important institutions in the field. The researcher from Vanderbilt University, Warren and Zachary, his dynamics or achievements in the field is also more worth our attention. The application of new technologies such as virtual reality, machine learning, and eye-tracking in this field has driven the development of DTx on ASD and is currently a popular research topic. More cross-regional and cross-disciplinary collaborations are recommended to advance the development and availability of DTx.

Computerized Cognitive Training Enhances Episodic Memory by Down-Modulating Posterior Cingulate-Precuneus Connectivity in Older Persons With Mild Cognitive Impairment: A Randomized Controlled Trial.

OBJECTIVE: The neural mechanisms underlying the beneficial effects of a computerized cognitive training (CCT) program for improving episodic memory in older persons with mild cognitive impairment (MCI) remain unclear. This study aimed to use both functional and structural brain changes to elucidate the treatment effects of CCT on enhancing episodic memory. DESIGN, SETTING, AND PARTICIPANTS: Single-blinded, multicenter randomized controlled trial on 60 older adults with MCI in Fuzhou, China. INTERVENTION: Participants were randomly assigned to either an 8-week 24-hour CCT program or a health education program as the control. MEASUREMENTS: Clinical outcomes included changes in scores on the immediate and/or delayed recall subtests of the Chinese auditory verbal learning test (CAVLT) and rey complex figure test (CFT), and changes in gray matter volume and the functional connectivity of the posterior cingulate cortex (PCC) and hippocampus in the Papez circuit on magnetic resonance imaging. RESULTS: Significant group-by-time effects showed greater improvements in both immediate and delayed recall scores of CAVLT and delayed recall scores of Rey CFT in participants receiving the CCT program compared to those in the health education program. Among the CCT participants, seed-based analyses revealed decreases in functional connectivity of the PCC and hippocampus with neural substrates in the parietal and occipital regions. The decreased PCC and precuneus connectivity were found to mediate patients' improvements in immediate recall function. CONCLUSION: An 8-week CCT program was effective for improving episodic memory in older individuals with MCI. The decrease in connectivity originating from the PCC and hippocampus is suggestive of potential plastic changes in the Papez circuit, which could have alleviated the age-related compensatory mechanism. The findings of this study also shed light on expanding the content and extending the frequency and duration of the CCT program in future studies.

Systematic bibliometric and visualized analysis of research hotspots and trends in attention-deficit hyperactivity disorder neuroimaging.

Introduction: This study focused on the research hotspots and development trends of the neuroimaging of attention deficit hyperactivity disorder (ADHD) in the past thirty years. Methods: The Web of Science database was searched for articles about ADHD neuroimaging from January 1992 to September 2022. CiteSpace was used to analyze the co-occurrence of keywords in literature, partnerships between authors, institutions, and countries, the sudden occurrence of keywords, clustering of keywords over time, and analysis of references, cited authors, and cited journals. Results: 2,621 articles were included. More and more articles have been published every year in the last years. These articles mainly come from 435 institutions and 65 countries/regions led by the United States. King's College London had the highest number of publications. The study identified 634 authors, among which Buitelaar, J. K. published the largest number of articles and Castellanos, F. X. was co-cited most often. The most productive and cited journal was Biological psychiatry. In recent years, burst keywords were resting-state fMRI, machine learning, functional connectivity, and networks. And a timeline chart of the cluster of keywords showed that "children" had the longest time span. Conclusions: Increased attention has been paid to ADHD neuroimaging. This work might assist researchers to identify new insight on potential collaborators and cooperative institutions, hot topics, and research directions.

An Effective Test (EOmciSS) for Screening Older Adults With Mild Cognitive Impairment in a Community Setting: Development and Validation Study.

BACKGROUND: Early detection of mild cognitive impairment (MCI) symptoms is an important step to its diagnosis and intervention. We developed a new screening test called "Efficient Online MCI Screening System" (EOmciSS) for use in community-dwelling older adults. It is a self-paced cognitive test to be completed within 10 minutes on tablets or smartphones in homes or care centers for older adults. OBJECTIVE: This study aims to test the validity of EOmciSS for identifying community-dwelling older adults with MCI risks. METHODS: Participants (N=827) completed EOmciSS and other screening tests for MCI. The psychometric properties tested were "subscale item difficulty," "discriminative index," "internal consistency," and "construct validity." We also tested between-group discrimination using the cross-validation method in an MCI group and a normal cognitive function (NCF) group. RESULTS: A total of 3 accuracy factors and 1 reaction time factor explained the structure of the 20 item factors. The difficulty level of accuracy factors (ie, "trail making," "clock drawing," "cube copying," "delayed recall") was 0.63-0.99, whereas that of the reaction time factor was 0.77-0.95. The discriminative index of the medium-to-high-difficulty item factors was 0.39-0.97. The internal consistency (Cronbach α) ranged from .41 (for few item factors) to .96. The training data set contained 9 item factors (CC-Acc1, P<.001; CD-Acc1, P=.07; CD-Acc2, P=.06; CD-Acc3, P<.001; TM-Acc4, P=.07; DR-Acc1, P=.03; RS, P=.06; DR-RT1, P=.02; and DR-RT2, P=.05) that were significant predictors for an MCI classification versus NCF classification. Depressive symptoms were identified as significant factors (P<.001) influencing the performance of participants, and were an integral part of our test system. Age (P=.15), number of years of education (P=.18), and proficiency in using an electronic device (P=.39) did not significantly influence the scores nor classification of participants. Application of the MCI/NCF cutoff score (7.90 out of 9.67) to the validation data set yielded an area under the curve of 0.912 (P<.001; 95% CI 0.868-0.955). The sensitivity was 84.9%, specificity was 85.1%, and the Youden index was 0.70. CONCLUSIONS: EOmciSS was valid and reliable for identifying older adults with significant risks of MCI. Our results indicate that EOmciSS has higher sensitivity and specificity than those of the Computer-Administered Neuropsychological Screen for Mild Cognitive Impairment and the Computerized Cognitive Screen. The user interface, online operation, and self-paced format allowed the test system to be operated by older adults or their caregivers in different settings (eg, home or care centers for older adults). Depressive symptoms should be an integral part in future MCI screening systems because they influence the test performance and, hence, MCI risk. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000039411; http://www.chictr.org.cn/showprojen.aspx?proj=62903.

Cremastra appendiculata polysaccharides improve stress resistance and prolong the lifespan of Caenorhabditis elegans via daf-16 in the insulin signaling pathway.

Cremastra appendiculata polysaccharide (CAP) exhibits potential anti-aging and stress resistance effects. In this study, we investigated the structure, antioxidant properties, and mechanism of action of CAP in Caenorhabditis elegans. The results showed that CAP primarily comprises mannose and glucose and exerts antioxidant activity in vitro. In vivo, CAP prolonged the lifespan of C. elegans in a concentration-dependent manner, with 2.0 mg/mL CAP prolonging the lifespan by 39.97 %. Compared with the control, the activities of superoxide dismutase (SOD) and catalase (CAT) antioxidant enzymes increased by 46 % and 57 %, respectively. However, the reactive oxygen species (ROS) and malondialdehyde (MDA) contents decreased by 38 % and 19.92 %, respectively, at the same CAP concentration, oxidative and heat stress resistance increased. The target genes of the insulin/insulin-like growth factor (IGF) signaling pathway, daf-16, sod-3, ctl-1, and hsp-16.2, were activated by CAP; their mRNA expression levels were upregulated by 7.23 %, 69.78 %, 43.62 %, and 58.62 %, respectively. A transgenic worm assay indicated that CAP regulates the lifespan of C. elegans through daf-16. These results suggest that CAP improves stress resistance and prolongs the lifespan of C. elegans through daf-16 in the insulin/IGF signaling pathway.

Tuning Mass Transport in Electrocatalysis Down to Sub-5†nm through Nanoscale Grade Separation.

Nano and single-atom catalysis open new possibilities of producing green hydrogen (H2 ) by water electrolysis. However, for the hydrogen evolution reaction (HER) which occurs at a characteristic reaction rate proportional to the potential, the fast generation of H2 nanobubbles at atomic-scale interfaces often leads to the blockage of active sites. Herein, a nanoscale grade-separation strategy is proposed to tackle mass-transport problem by utilizing ordered three-dimensional (3d) interconnected sub-5 nm pores. The results reveal that 3d criss-crossing mesopores with grade separation allow efficient diffusion of H2 bubbles along the interconnected channels. After the support of ultrafine ruthenium (Ru), the 3d mesopores are on a superior level to two-dimensional system at maximizing the catalyst performance and the obtained Ru catalyst outperforms most of the other HER catalysts. This work provides a potential route to fine-tuning few-nanometer mass transport during water electrolysis.

Machine learning-based classification of circadian rhythm characteristics for mild cognitive impairment in the elderly.

Introduction: Using wrist-wearable sensors to ecological transient assessment may provide a more valid assessment of physical activity, sedentary time, sleep and circadian rhythm than self-reported questionnaires, but has not been used widely to study the association with mild cognitive impairment and their characteristics. Methods: 31 normal cognitive ability participants and 68 MCI participants were monitored with tri-axial accelerometer and nocturnal photo volumetric pulse wave signals for 14 days. Two machine learning algorithms: gradient boosting decision tree and eXtreme gradient boosting were constructed using data on daytime physical activity, sedentary time and nighttime physiological functions, including heart rate, heart rate variability, respiratory rate and oxygen saturation, combined with subjective scale features. The accuracy, precision, recall, F1 value, and AUC of the different models are compared, and the training and model effectiveness are validated by the subject-based leave-one-out method. Results: The low physical activity state was higher in the MCI group than in the cognitively normal group between 8:00 and 11:00 (P < 0.05), the daily rhythm trend of the high physical activity state was generally lower in the MCI group than in the cognitively normal group (P < 0.05). The peak rhythms in the sedentary state appeared at 12:00-15:00 and 20:00. The peak rhythms of rMSSD, HRV high frequency output power, and HRV low frequency output power in the 6h HRV parameters at night in the MCI group disappeared at 3:00 a.m., and the amplitude of fluctuations decreased; the amplitude of fluctuations of LHratio nocturnal rhythm increased and the phase was disturbed; the oxygen saturation was between 90 and 95% and less than 90% were increased in all time periods (P < 0.05). The F1 value of the two machine learning algorithms for MCI classification of multi-feature data combined with subjective scales were XGBoost (78.02) and GBDT (84.04). Conclusion: By collecting PSQI Scale data combined with circadian rhythm characteristics monitored by wrist-wearable sensors, we are able to construct XGBoost and GBDT machine learning models with good discrimination, thus providing an early warning solution for identifying family and community members with high risk of MCI.

Automated assessment of balance: A neural network approach based on large-scale balance function data.

Balance impairment (BI) is an important cause of falls in the elderly. However, the existing balance estimation system needs to measure a large number of items to obtain the balance score and balance level, which is less efficient and redundant. In this context, we aim at building a model to automatically predict the balance ability, so that the early screening of large-scale physical examination data can be carried out quickly and accurately. We collected and sorted out 17,541 samples, each with 61-dimensional features and two labels. Moreover, using this data a lightweight artificial neural network model was trained to accurately predict the balance score and balance level. On the premise of ensuring high prediction accuracy, we reduced the input feature dimension of the model from 61 to 13 dimensions through the recursive feature elimination (RFE) algorithm, which makes the evaluation process more streamlined with fewer measurement items. The proposed balance prediction method was evaluated on the test set, in which the determination coefficient (R2) of balance score reaches 92.2%. In the classification task of balance level, the metrics of accuracy, area under the curve (AUC), and F1 score reached 90.5, 97.0, and 90.6%, respectively. Compared with other competitive machine learning models, our method performed best in predicting balance capabilities, which is especially suitable for large-scale physical examination.