Target-based deep learning network surveillance of non-contrast computed tomography for small infarct core of acute ischemic stroke.

Purpose: Rapid diagnosis of acute ischemic stroke (AIS) is critical to achieve positive outcomes and prognosis. This study aimed to construct a model to automatically identify the infarct core based on non-contrast-enhanced CT images, especially for small infarcts. Methods: The baseline CT scans of AIS patients, who had DWI scans obtained within less than 2 h apart, were included in this retrospective study. A modified Target-based deep learning model of YOLOv5 was developed to detect infarctions on CT. Randomly selected CT images were used for testing and evaluated by neuroradiologists and the model, using the DWI as a reference standard. Intraclass correlation coefficient (ICC) and weighted kappa were calculated to assess the agreement. The paired chi-square test was used to compare the diagnostic efficacy of physician groups and automated models in subregions. p < 0.05 was considered statistically significant. Results: Five hundred and eighty four AIS patients were enrolled in total, finally 275 cases were eligible. Modified YOLOv5 perform better with increased precision (0.82), recall (0.81) and mean average precision (0.79) than original YOLOv5. Model showed higher consistency to the DWI-ASPECTS scores (ICC = 0.669, κ = 0.447) than neuroradiologists (ICC = 0.452, κ = 0.247). The sensitivity (75.86% vs. 63.79%), specificity (98.87% vs. 95.02%), and accuracy (96.20% vs. 91.40%) were better than neuroradiologists. Automatic model had better diagnostic efficacy than physician diagnosis in the M6 region (p = 0.039). Conclusion: The deep learning model was able to detect small infarct core on CT images more accurately. It provided the infarct portion and extent, which is valuable in assessing the severity of disease and guiding treatment procedures.

Recent Advances in the Application of Natural Products for Postharvest Edible Mushroom Quality Preservation.

Edible mushrooms are favored by consumers for their excellent nutritional value and pharmacological properties. However, fresh mushrooms are highly perishable and undergo rapid quality deterioration induced by a series of intrinsic and extrinsic factors during postharvest storage. In recent years, the application of natural products derived from plants, animals, microorganisms, and other sources in mushroom quality preservation has drawn increasing attention. Compared to chemical preservatives, natural products show similar or higher biological activity and have few side effects on human health. This review summarizes the recent advances in the application of natural products used for quality maintenance of postharvest mushrooms. These natural substances mainly include essential oils, polyphenols, polysaccharides, bacteriocins, and other extracts. They have the potential to inhibit mushroom weight loss, softening, and browning, reduce the count of pathogenic microorganisms, and retain nutrients and flavor, effectively improving the quality of mushrooms and extending their shelf-life. The preservation techniques for natural products and their preservation mechanisms are also discussed here. Overall, this review provides current knowledge about natural products in edible mushroom preservation and aims to inspire more in-depth theoretical research and promote further practical application.

Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT. MATERIALS AND METHODS: This retrospective study included 400 patients with aneurysmal SAH (156 with delayed cerebral ischemia) who underwent NCCT. The study used ATT-Deeplabv3+ for automatically segmenting hemorrhagic regions using semisupervised learning. Principal component analysis was used for reducing the dimensionality of deep learning features extracted from the average pooling layer of ATT-DeepLabv3+. The classification model integrated clinical data, radiomics, and deep learning features to predict delayed cerebral ischemia. Feature selection involved Pearson correlation coefficients, least absolute shrinkage, and selection operator regression. We developed models based on clinical features, clinical-radiomics, and a combination of clinical, radiomics, and deep learning. The study selected logistic regression, Naive Bayes, Adaptive Boosting (AdaBoost), and multilayer perceptron as classifiers. The performance of segmentation and classification models was evaluated on their testing sets using the Dice similarity coefficient for segmentation, and the area under the receiver operating characteristic curve (AUC) and calibration curves for classification. RESULTS: The segmentation process achieved a Dice similarity coefficient of 0.91 and the average time of 0.037 s/image. Seventeen features were selected to calculate the radiomics score. The clinical-radiomics-deep learning model with multilayer perceptron achieved the highest AUC of 0.84 (95% CI, 0.72-0.97), which outperformed the clinical-radiomics model (P = .002) and the clinical features model (P = .001) with multilayer perceptron. The performance of clinical-radiomics-deep learning model using AdaBoost was significantly superior to its clinical-radiomics model (P = .027). The performance of the clinical-radiomics-deep learning model and the clinical-radiomics model with logistic regression notably exceeded that of the model based solely on clinical features (P = .028; P = .046). The AUC of the clinical-radiomics-deep learning model with multilayer perceptron (P < .001) and the clinical-radiomics model with logistic regression (P = .046) were significantly higher than the clinical model with logistic regression. Of all models, the clinical-radiomics-deep learning model with multilayer perceptron showed best calibration. CONCLUSIONS: The proposed 2-stage end-to-end model not only achieves rapid and accurate segmentation but also demonstrates superior diagnostic performance with high AUC values and good calibration in the clinical-radiomics-deep learning model, suggesting its potential to enhance delayed cerebral ischemia detection and treatment strategies.

Comparable cerebral cortex activity and gait performance in elderly hypertensive and healthy individuals during dual-task walking: A fNIRS study.

BACKGROUND: Hypertension increases the risk of cognitive impairment and related dementia, causing impaired executive function and unusual gait parameters. However, the mechanism of neural function illustrating this is unclear. Our research aimed to explore the differences of cerebral cortex activation, gait parameters, and working memory performance between healthy older adults (HA) and older hypertensive (HT) patients when performing cognitive and walking tasks. METHOD: A total of 36 subjects, including 12 healthy older adults and 24 older hypertensive patients were asked to perform series conditions including single cognitive task (SC), single walking task (SW), and dual-task (DT), wearing functional near-infrared spectroscopy (fNIRS) equipment and Intelligent Device for Energy Expenditure and Activity equipment to record cortical hemodynamic reactions and various gait parameters. RESULTS: The left somatosensory cortex (L-S1) and bilateral supplementary motor area (SMA) showed higher cortical activation (p < .05) than HA when HT performed DT. The intragroup comparison showed that HT had higher cortical activation (p < .05) when performing DT as SW. The cognitive performance of HT was significantly worse (p < .05) than HA when executing SC. The activation of the L-S1, L-M1, and bilateral SMA in HT were significantly higher during SW (p < .05). CONCLUSION: Hypertension can lead to cognitive impairment in the elderly, including executive function and walking function decline. As a result of these functional declines, elderly patients with hypertension are unable to efficiently allocate brain resources to support more difficult cognitive interference tasks and need to meet more complex task demands by activating more brain regions.

Observation-Based Diagnostics of Reactive Nitrogen Recycling through HONO Heterogenous Production: Divergent Implications for Ozone Production and Emission Control.

Understanding of nitrous acid (HONO) production is crucial to photochemical studies, especially in polluted environments like eastern China. In-situ measurements of gaseous and particulate compositions were conducted at a rural coastal site during the 2018 spring Ozone Photochemistry and Export from China Experiment (OPECE). This data set was applied to investigate the recycling of reactive nitrogen through daytime heterogeneous HONO production. Although HONO levels increase during agricultural burning, analysis of the observation data does not indicate more efficient HONO production by agricultural burning aerosols than other anthropogenic aerosols. Box and 1-D modeling analyses reveal the intrinsic relationships between nitrogen dioxide (NO2), particulate nitrate (pNO3), and nitric acid (HNO3), resulting in comparable agreement between observed and simulated HONO concentrations with any one of the three heterogeneous HONO production mechanisms, photosensitized NO2 conversion on aerosols, photolysis of pNO3, and conversion from HNO3. This finding underscores the uncertainties in the mechanistic understanding and quantitative parametrizations of daytime heterogeneous HONO production pathways. Furthermore, the implications for reactive nitrogen recycling, ozone (O3) production, and O3 control strategies vary greatly depending on the HONO production mechanism. On a regional scale, the conversion of HONO from pNO3 can drastically enhance O3 production, while the conversion from NO2 can reduce O3 sensitivity to NOx changes in polluted eastern China.

The mediating effect of positive expectations in the relationship between social support and post-traumatic stress disorder symptoms among parents of children with acute lymphoblastic leukemia.

PURPOSE: Parents of children with cancer are exposed to risks of developing post-traumatic stress disorder (PTSD) symptoms, but few studies have explored PTSD symptoms of Chinese parents of children with acute lymphoblastic leukemia (ALL). Our study aimed to examine the association between social support and PTSD symptoms and to examine the mediating effect of positive expectations in this relationship among parents of children with ALL. METHODS: A cross-sectional study was conducted of consecutive parents of children with ALL in the Shengjing Hospital of China Medical University. A total of 177 parents eligible for this study completed questionnaires on PTSD symptoms, perceived social support, optimism and general self-efficacy anonymously. Asymptotic and resampling strategies were used to examine how positive expectations mediated the association between perceived social support and PTSD symptoms. RESULTS: Mean score of PTSD symptoms was 37.64 ± 14.44; 29.4% of the sample scored 44 and above, 19.8% scored 50 and above. After adjusting for covariates, perceived social support was negatively associated with the total score of PTSD symptoms (ß = -0.209, p < 0.01). Positive expectations were found to mediate the relationship between perceived social support and PTSD symptoms, especially for the symptoms of avoidance and hyperarousal. CONCLUSIONS: Optimism and general self-efficacy fully mediated the association between perceived social support and PTSD symptoms. Therefore, social support and positive expectations should be included in PTSD preventions and treatments targeting Chinese parents of children with ALL.

Tilted Bragg grating in a glycerol-infiltrated specialty optical fiber for temperature and strain measurements.

In this Letter, we propose an in-line tilted fiber Bragg grating sensor for temperature and strain measurements. The grating is inscribed in a specialty optical fiber using tightly focused femtosecond laser pulses and the line-by-line direct writing method. Beside the central core in which the grating is produced, a hollow channel filled with glycerol aqueous solution significantly improves the sensitivity of the fiber cladding modes due to its high thermo-optic coefficient. We show that the temperature sensitivity of the core mode is 9.8 pm/°C, while the one of the cladding modes is strongly altered and can reach -24.3 pm/°C, in the investigated range of 20-40°C. For the strain measurement, sensitivities of the core mode and the cladding modes are similar (∼0.60 pm/µÎµ) between 0 and 2400 µÎµ. The significative difference of temperature sensitivity between the two modes facilitates the discrimination of the dual parameters in simultaneous measurements.

Effective Connectivity of Default Mode Network Subsystems in Parkinson's Disease with Mild Cognitive Impairment Based on Spectral Dynamic Causal Modeling.

OBJECTIVE: The objective of this study is to compare the differences in effective connectivity within the default mode network (DMN) subsystems between patients with Parkinson's disease with mild cognitive impairment (PD-MCI) and patients with Parkinson's disease with normal cognition (PD-CN). The mechanisms underlying DMN dysfunction in PD-MCI patients and its association with clinical cognitive function in PD-MCI are aimed to be investigated. METHODS: The spectral dynamic causal model (spDCM) was employed to analyze the effective connectivity of functional magnetic resonance imaging (fMRI) data in the resting state for the DMN subsystems, which include the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), left and right angular gyrus (LAG, RAG) in 23 PD-MCI and 22 PD-CN patients, respectively. The effective connectivity values of DMN subsystems in the two groups were statistically analyzed using a two-sample t-test. The Spearman correlation analysis was used to test the correlation between the effective connectivity values of the subsystems with significant differences between the two groups and the clinical cognitive function (as measured by Montreal Cognitive Assessment Scale (MoCA) score). RESULTS: Statistical analysis revealed significant differences in the effective connections of MPFC-LAG and LAG-PCC between the two patient groups (MPFC-LAG: t = -2.993, p < 0.05; LAG-PCC: t = 2.174, p < 0.05). CONCLUSIONS: The study findings suggest that abnormal strength and direction of effective connections between DMN subsystems are found in PD-MCI patients.

Effect of ultrasound-guided injection of botulinum toxin type A into shoulder joint cavity on shoulder pain in poststroke patients: study protocol for a randomized controlled trial.

BACKGROUND: Hemiplegic shoulder pain (HSP) is a common complication after stroke. It severely affects the recovery of upper limb motor function. Early shoulder pain in hemiplegic patients is mainly neuropathic caused by central nerve injury or neuroplasticity. Commonly used corticosteroid injections in the shoulder joint can reduce shoulder pain; however, the side effects also include soft tissue degeneration or increased tendon fragility, and the long-term effects remain controversial. Botulinum toxin injections are relatively new and are thought to block the transmission of pain receptors in the shoulder joint cavity and inhibit the production of neuropathogenic substances to reduce neurogenic inflammation. Some studies suggest that the shoulder pain of hemiplegia after stroke is caused by changes in the central system related to shoulder joint pain, and persistent pain may induce the reorganization of the cortical sensory center or motor center. However, there is no conclusive evidence as to whether or not the amelioration of pain by botulinum toxin affects brain function. In previous studies of botulinum toxin versus glucocorticoids (triamcinolone acetonide injection) in the treatment of shoulder pain, there is a lack of observation of differences in changes in brain function. As the content of previous assessments of pain improvement was predominantly subjective, objective quantitative assessment indicators were lacking. Functional near-infrared imaging (fNIRS) can remedy this problem. METHODS: This study protocol is designed for a double-blind, randomized controlled clinical trial of patients with post-stroke HSP without biceps longus tenosynovitis or acromion bursitis. Seventy-eight patients will be randomly assigned to either the botulinum toxin type A or glucocorticoid group. At baseline, patients in each group will receive shoulder cavity injections of either botulinum toxin or glucocorticoids and will be followed for 1 and 4 weeks. The primary outcome is change in shoulder pain on the visual analog scale (VAS). The secondary outcome is the assessment of changes in oxyhemoglobin levels in the corresponding brain regions by fNIRS imaging, shoulder flexion, external rotation range of motion, upper extremity Fugl-Meyer, and modified Ashworth score. DISCUSSION: Ultrasound-guided botulinum toxin type A shoulder joint cavity injections may provide evidence of pain improvement in patients with HSP. The results of this trial are also help to analyze the correlation between changes in shoulder pain and changes in cerebral hemodynamics and shoulder joint motor function. TRIAL REGISTRATION: Chinese clinical Trial Registry, ChiCTR2300070132. Registered 03 April 2023, https://www.chictr.org.cn/showproj.html?proj=193722 .

A New Method of Constructing Methyleneindene and Quinoline Frameworks from Methylenecyclopropanes.

In this paper, we have established an operationally convenient protocol for the rapid construction of polysubstituted methyleneindene and quinoline derivatives under mild conditions. This new synthetic method is achieved through the conversion of acetyl-substituted methylenecyclopropanes with TsOH ⋅ H2O and ortho-amino-substituted methylenecyclopropanes with aromatic aldehyde and TsOH ⋅ H2O, respectively. A variety of transformations of the obtained products was demonstrated. The plausible reaction mechanisms were also proposed.

Implications of a Ultrasomics Signature for Predicting Malignancy in Thyroid Nodules with Hashimoto's Thyroiditis.

RATIONALE AND OBJECTIVES: It remains a challenge to determine the nature of thyroid nodules (TNs) with Hashimoto's thyroiditis (HT). We aim to investigate the multiregional ultrasomics signatures obtained from B-mode ultrasound (B-US) and contrast-enhanced ultrasound (CEUS) images for predicting malignancy in TNs of patients with HT. MATERIALS AND METHODS: B-US and CEUS images of 193 nodules (110 malignant and 83 benign nodules) from 110 patients were retrospectively collected in the single-center study, extracting ultrasomics signatures from the intratumoral (In) and peritumoral (Peri) regions of the thyroid. In-B-US, Peri-B-US, In-CEUS, and Peri-CEUS ultrasomics models and a stacking regression model were constructed, and the diagnostic performance of the models was evaluated by comparing the area under the receiver operating characteristic curve (ROC). RESULTS: The In-B-US, Peri-B-US, In-CEUS, Peri-CEUS, and stacking regression model in the training and testing datasets which attained AUC (95% CI) of 0.872(0.812, 0.932), 0.815(0.747, 0.882), 0.739(0.659, 0.819), 0.890(0.836, 0.943), 0.997(0.992, 1.000) and 0.799(0.650, 0.948), 0.851(0.727, 0.974), 0.622(0.440, 0.805), 0.742(0.573, 0.911), 0.867(0.741, 0.992); sensitivity of 82.8%, 89.7%, 71.3%, 74.7%, 96.6% and 69.6%, 78.3%, 43.5%, 78.3%, 91.3%; specificity of 80.6%, 58.2%, 67.2%, 91.0%, 98.5% and 93.8%, 87.5%, 93.3%, 75.0%, 81.2%, respectively. The stacking regression model based on ultrasomics signatures showed favorable calibration and discriminative capabilities. Compared to the stacking regression model, the difference in AUC between the In-B-US and Peri-B-US models was not statistically significant (P > 0.05). However, the difference in AUC between the In-CEUS and Peri-CEUS models was significant (P < 0.05). CONCLUSION: The application of an ultrasomics approach can effectively predict the benign or malignant nature of TNs accompanied by HT. The diagnostic performance of the ultrasomics model was improved by combining the dual-region and dual-mode of thyroid.

2D to 3D Reconstruction of Boron-Linked Covalent-Organic Frameworks.

The transformation of two-dimensional (2D) covalent-organic frameworks (COFs) into three-dimensions (3D) is synthetically challenging, and it is typically addressed through interlayer cross-linking of alkene or alkyne bonds. Here, we report the first example of the chemical reconstruction of a 2D COF to a 3D COF with a complete lattice rearrangement facilitated by base-triggered boron hybridization. This chemical reconstruction involves the conversion of trigonal boronate ester linkages to tetrahedral anionic spiroborate linkages. This transformation reticulates the coplanar, closely stacked square cobalt(II) phthalocyanine (PcCo) units into a 3D perpendicular arrangement. As a result, the pore size of COFs expands from 2.45 nm for the initial 2D square lattice (sql) to 3.02 nm in the 3D noninterpenetrated network (nbo). Mechanistic studies reveal a base-catalyzed boronate ester protodeboronation pathway for the formation of the spiroborate structure.

Effects on brain structural and functional in deaf children after aerobic exercise training: a pilot cluster randomized controlled study.

Purpose: To examine effects of aerobic exercise interventions on brain via the structural Magnetic Resonance Imaging (MRI), as well as functional change during working memory (WM) task using fMRI in deaf children.Method: The study applied a cluster randomized controlled design. Twelve deaf children in the intervention group were required to complete an eleven-week aerobic exercise intervention, while other twelve age and gender matched deaf children in the control group were required to keep their normal daily life. Task fMRI images of each participant were acquired in the baseline and post intervention period. The surface-based morphometry (SBM) analysis and functional activation analysis were employed to probe the effects of 11-week aerobic exercise on cerebral structural and functional in deaf children, respectively.Results: The 11-week aerobic exercise intervention did not change brain structure in deaf children. However, behavior performance (reaction time and mean accuracy rate) presented significant improvements after the 11-week aerobic exercise intervention. Compared to the control group, the intervention group showed decreased reaction time in the 2-back (p < 0.001) and 2-0 back (p < 0.001), and increased mean accuracy rate during 2-back (p = 0.034). Furthermore, enhanced brain activations in the left supplementary motor cortex (p < 0.05, FDR-corrected) and left paracentral lobule (p < 0.05, FDR-corrected) were observed in the intervention group.Conclusion: 11-week aerobic exercise intervention may not be able to modulate brain structure in deaf children, but may have significantly positive effects on behavior performance and brain functional activation during WM task.

Tandem Mass Tag-Based Proteomic Analysis of Normal and Degenerated Human Intervertebral Discs.

Background: Intervertebral disc degeneration (IVDD) is the main cause of low back pain (LBP), but the specific regulatory factors, pathways and specific molecular mechanisms remain unclear. Methods: We identified and quantitatively analyzed Pfirrmann Grade II (n=3) and Pfirrmann Grade IV (n=3) pulposus samples via MRI. The differential abundance of proteins in the samples was determined and quantitatively analyzed by relative and absolute quantitative analysis of the isotope marker levels combined with the liquid chromatography-tandem mass spectrometry (LC‒MSMS/MS). Results: A total of 70 proteins (30 significantly increased proteins (> 1.2-fold change) and 40 significantly decreased proteins (< 0.8-fold change)) showed different levels among the groups. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology (GO) enrichment analyses and Western blot analysis showed that CYCS, RAC1, and PSMD14 may play important roles in IVDD and that Epstein‒Barr virus infection, viral myocarditis, colorectal cancer, nonalcoholic fatty liver disease (NAFLD) and amyotrophic lateral sclerosis (ALS) are the main pathways involved in IVDD. Conclusion: CYCS, RAC1 and PSMD14 may play important roles in IVDD, and Epstein‒Barr virus infection, viral myocarditis, colorectal cancer, NAFLD and ALS may be the main pathways involved in IVDD.

The value of MRI-based radiomics for evaluating early parotid gland injury in primary Sjögren's syndrome.

OBJECTIVE: This study aimed to evaluate the value of machine learning models (ML) based on MRI radiomics in diagnosing early parotid gland injury in primary Sjögren's syndrome (pSS). METHODS: A total of 164 patients (114 in the training cohort and 50 in the testing cohort) with pSS (n=82) or healthy controls (HC) (n=82) were enrolled. Itksnap software was used to perform two-dimensional segmentation of the bilateral parotid glands on T1-weighted (T1WI) and fat-suppressed T2-weighted imaging (fs-T2WI) images. A total of 1548 texture features of the parotid glands were extracted using radiomics software. A radiomics score (Radscore) was constructed and calculated. A t-test was used to compare the Radscore between the two groups. Finally, five machine learning models were trained and tested to identify early pSS parotid injury, and the performance of the machine learning models was evaluated by calculating the acceptance operating curve (ROC) and other parameters. RESULTS: The Radscores between the pSS and HC groups showed significant statistical differences (p<0.001). Among the five machine learning models, the Extra Trees Classifier (ETC) model performed high predictive efficacy in identifying early pSS parotid injury, with an AUC of 0.87 in the testing set. CONCLUSION: MRI radiomics-based machine learning models can effectively diagnose early parotid gland injury in primary Sjögren's syndrome.

Detection of monosodium urate depositions and atherosclerotic plaques in the cardiovascular system by dual-energy computed tomography.

Aim: The study aimed to explore the relationship between urate deposition and surrounding atherosclerotic plaques, and to confirm the contribution of urate deposition to the development of coronary atherosclerosis. Methods and results: The present study employed Dual-energy CT (DECT) material separation technology through calcium score scan to access the presence of MSU crystal deposition in coronary atherosclerotic plaques in patients with clinically suspected coronary heart diseases undergoing DECT. DECT showed that among 872 patients, 441 had plaques in coronary arteries; the incidence of plaque was 50.6 %. The patients were divided in the atherosclerotic plaque vs. non-plaque groups. There were significant differences in age, sex, blood pressure, blood glucose, serum creatinine, and history of gout and hyperuricemia between the plaque and non-plaque groups (all P < 0.05). Among the patients with coronary plaques, there were 348 patients (78.9 %) with simple atherosclerotic plaque (AP), 8 (1.8 %) with simple urate depositions (UD), and 85 (19.3 %) with urate depositions and atherosclerotic plaques (UDAP). The multivariable analysis showed that urate deposition was independently associated with plaques after adjustment for age, sex, blood pressure, blood glucose, serum creatinine, history of gout, and history of hyperuricemia (OR = 13.69, 95%CI: 7.53-22.95, P = 0.035). UPAP patients had significantly higher coronary calcium scores than AP patients [210.1 (625.2) AU vs 58.2 (182.5) AU, P < 0.001] Urate deposition (16.7 mm3) positively correlated with plaque calcification (73.8 mm³) in UPAP patients (r = 0.325, P < 0.001). Conclusion: Patients with gout or a history of hyperuricemia were more likely to exhibit UDAP. Urate deposition was independently associated with plaques.

Molecular Face-Rotating Polyhedra: Chiral Cages Inspired by Mathematics.

ConspectusMolecular polyhedral cages, notable for their enclosed inner cavities, can possess varying degrees of symmetry, spanning from regular Platonic polyhedra to lower symmetry forms that may display chirality. Crafting chiral molecular cages typically involves using building blocks containing stereogenic elements or arranging achiral components in a manner that lacks mirror and inversion symmetries. Achieving precise control over their chirality poses both significance and challenges.In this Account, we present an overview of our research endeavors in the realm of chiral molecular polyhedral cages, drawing inspiration from Buckminster Fuller's "Face-Rotating Polyhedra (FRP)". Mathematically, FRP introduce a unique form of chirality distinguished by a rotating pattern around the center of each face, setting it apart from regular polyhedra.Molecular FRP can be constructed using two types of facial building blocks. The first includes rigid, planar molecules such as truxene and triazatruxene, which exhibit either clockwise or counterclockwise rotations in two dimensions. The second category involves propeller-like molecules, e.g., tetraphenylethylene, 1,2,3,4,5-penta(4-phenylaldehyde)pyrrole, and tridurylborane, displaying dynamic stereochemistry.The synthesis of FRP may potentially yield a diverse array of stereoisomers. Achieving high stereoselectivity becomes feasible through the selection of building blocks with specific substitution patterns and rigidity. Prominent noncovalent repulsive forces within the resulting cages often play a pivotal role in the dynamic covalent assembly process, ultimately leading to the formation of thermodynamically stable FRP products.The capacity to generate a multitude of stereoisomers, combined with the integration of chiral vertices, has facilitated investigations into phenomena such as chiral self-sorting and the "sergeant and soldiers" chiral amplification effect in FRP. Even the inclusion of one chiral vertex significantly impacts the stereochemical configuration of the entire cage. While many facial building blocks establish a stable rotational pattern in FRP, other units, such as tridurylborane, can dynamically transition between P and M configurations within the cage structures. The kinetic characteristics of such stereolabile FRP can be elucidated through physicochemical investigations.Our research extends beyond the FRP concept to encompass mathematical analysis of these structures. Graph theory, particularly the coloring problem, sheds light on the intricate facial patterns exhibited by various FRP stereoisomers and serves as an efficient tool to facilitate the discovery of novel FRP structures. This approach offers a fresh paradigm for designing and analyzing chiral molecular polyhedral cages, showcasing in our work the synergy between mathematics and molecular design.

Center of mass motion and plantar pressure distribution during walking in overweight individuals.

BACKGROUND: Gait imbalance has been reported in overweight individuals and could further impair their mobility and quality of life. As the feet are the most distal part of the body and sensitively interface with external surroundings, evaluating the plantar pressure distribution can provide critical insights into their roles in regulating gait balance control. Therefore, the purpose of this study was to evaluate the effect of body weight and different gait speeds on the plantar pressure distribution and whole-body center of mass (COM) motion during walking. METHODS: Eleven overweight individuals (OB) and 13 non-overweight individuals (NB) walked on a 10-meter walkway at three speed conditions (preferred, 80% and 120% of preferred speed). Gait balance was quantified by the mediolateral COM sway. Plantar pressure data were obtained using wireless pressure-sensing insoles that were inserted into a pair of running shoes. Analysis of variance models were used to examine the effect of body size, gait speeds, or their interactions on peak mediolateral COM and peak plantar pressure during walking. RESULTS: Significant group effects of peak plantar pressure under the lateral forefoot (P = 0.03), lateral midfoot (P = 0.02), and medial heel (P = 0.02) were observed. However, the mediolateral COM motion and spatiotemporal gait parameters only revealed significant speed effects. SIGNIFICANCE: Findings from this study indicated that overweight individuals exhibited increased plantar pressure under the lateral aspect of the foot, particularly during the late stance phase of walking, in an effort to maintain a comparable mediolateral COM motion to that of non-overweight individuals. Such elevated pressure in overweight individuals may potentially increase the risk of musculoskeletal pathology in the long term. The identified patterns are noteworthy as they have practical implications for designing targeted interventions and improving the overall health of individuals with a high BMI.

Self-assembled soft alloy with Frank-Kasper phases beyond metals.

Soft building blocks, such as micelles, cells or soap bubbles, tend to adopt near-spherical geometry when densely packed together. As a result, their packing structures do not extend beyond those discovered in metallic glasses, quasicrystals and crystals. Here we report the emergence of two Frank-Kasper phases from the self-assembly of five-fold symmetric molecular pentagons. The µ phase, an important intermediate in superalloys, is indexed in soft matter, whereas the ϕ phase exhibits a structure distinct from known Frank-Kasper phases in metallic systems. We find a broad size and shape distribution of self-assembled mesoatoms formed by molecular pentagons while approaching equilibrium that contribute to the unique packing structures. This work provides insight into the manipulation of soft building blocks that deviate from the typical spherical geometry and opens avenues for the fabrication of 'soft alloy' structures that were previously unattainable in metal alloys.

What can molecular assembly learn from catalysed assembly in living organisms?

Molecular assembly is the process of organizing individual molecules into larger structures and complex systems. The self-assembly approach is predominantly utilized in creating artificial molecular assemblies, and was believed to be the primary mode of molecular assembly in living organisms as well. However, it has been shown that the assembly of many biological complexes is "catalysed" by other molecules, rather than relying solely on self-assembly. In this review, we summarize these catalysed-assembly (catassembly) phenomena in living organisms and systematically analyse their mechanisms. We then expand on these phenomena and discuss related concepts, including catalysed-disassembly and catalysed-reassembly. Catassembly proves to be an efficient and highly selective strategy for synergistically controlling and manipulating various noncovalent interactions, especially in hierarchical molecular assemblies. Overreliance on self-assembly may, to some extent, hinder the advancement of artificial molecular assembly with powerful features. Furthermore, inspired by the biological catassembly phenomena, we propose guidelines for designing artificial catassembly systems and developing characterization and theoretical methods, and review pioneering works along this new direction. Overall, this approach may broaden and deepen our understanding of molecular assembly, enabling the construction and control of intelligent assembly systems with advanced functionality.