Diagnosis of Autism Spectrum Disorder by Dynamic Local Graph-Theory Indicators Based on Electroencephalogram.

BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopment disease characterized by impaired social and cognitive abilities. Despite its prevalence, reliable biomarkers for identifying individuals with ASD are lacking. Recent studies have suggested that alterations in the functional connectivity of the brain in ASD patients could serve as potential indicators. However, previous research focused on static functional-connectivity analysis, neglecting temporal dynamics and spatial interactions. To address this gap, our study integrated dynamic functional connectivity, local graph-theory indicators, and a feature-selection and ranking approach to identify biomarkers for ASD diagnosis. METHODS: The demographic information, as well as resting and sleeping electroencephalography (EEG) data, were collected from 20 ASD patients and 25 controls. EEG data were pre-processed and segmented into five sub-bands (Delta, Theta, Alpha-1, Alpha-2, and Beta). Functional-connection matrices were created by calculating coherence, and static-node-strength indicators were determined for each channel. A sliding-window approach, with varying widths and moving steps, was used to scan the EEG series; dynamic local graph-theory indicators were computed, including mean, standard deviation, median, inter-quartile range, kurtosis, and skewness of the node strength. This resulted in 95 features (5 sub-bands × 19 channels) for each indicator. A support-vector-machine recurrence-feature-elimination method was used to identify the most discriminative feature subset. RESULTS: The dynamic graph-theory indicators with a 3-s window width and 50% moving step achieved the highest classification performance, with an average accuracy of 95.2%. Notably, mean, median, and inter-quartile-range indicators in this condition reached 100% accuracy, with the least number of selected features. The distribution of selected features showed a preference for the frontal region and the Beta sub-band. CONCLUSIONS: A window width of 3 s and a 50% moving step emerged as optimal parameters for dynamic graph-theory analysis. Anomalies in dynamic local graph-theory indicators in the frontal lobe and Beta sub-band may serve as valuable biomarkers for diagnosing autism spectrum disorders.

Study of the mandibular canal and its surrounding canals by multi-view cone-beam computed tomography.

OBJECTIVES: To determine the mandibular anatomical structures by observing cone-beam computed tomography (CBCT) from multiple angles. MATERIALS AND METHODS: This retrospective study analyzed 1593 consecutive CBCT images. Ultimately, 95 CBCTs met the inclusion criteria. The mandibular, inferior lingual, and bony canals at the tooth apex were studied by multi-angle observation CBCT. Descriptive statistics were used for statistical analysis. RESULTS: It is beneficial to further observe the anastomosis of the mandibular, lingual, and mandibular canals when the course of the mandibular lingual canal is observed on CBCT cross-section. The frequency of the inferior lingual canal anastomosis with the mandibular canal was 43.2% (95% confidence interval (CI) 33, 53.3) in the sample. The mental foramen was located below the long axis of the tooth in a few samples, with an occurrence rate of 29.5% (95% CI 20.1, 38.8). The occurrence rate of various types of the bony canal at the apex of the tooth in canines, first premolars, second premolars, first molars, and second molars under the root apex was recorded through the multi-angle observation of the dental volume reformat (DVR) and three-dimensional (3D) levels in CBCT. CONCLUSION: This study demonstrates the utility of CBCT imaging in examining mandibular anatomy from multiple angles, providing valuable insights into anatomical variations, and enhancing our understanding of mandibular structures. This research emphasizes the crucial role of meticulous CBCT examination in precisely identifying and understanding key anatomical structures, ultimately reducing the risk of surgical complications. CRITICAL RELEVANCE STATEMENT: By examining cone-beam computed tomography scans from various perspectives, it is possible to determine the precise position of anatomical structures within the jaw. This allows for a more accurate assessment, reducing the risk of harm to these structures during treatment. KEY POINTS: • It is crucial to utilize image data effectively to enhance the comprehension of human anatomy. • We captured detailed images of the mandible from different angles and orientations utilizing cone-beam computed tomography (CBCT). • This study provides essential anatomical information for procedural planning to ensure optimal outcomes and patient safety.

Examining the U-shaped relationship of sleep duration and systolic blood pressure with risk of cardiovascular events using a novel recursive gradient scanning model.

Background: Observational studies have suggested U-shaped relationships between sleep duration and systolic blood pressure (SBP) with risks of many cardiovascular diseases (CVDs), but the cut-points that separate high-risk and low-risk groups have not been confirmed. We aimed to examine the U-shaped relationships between sleep duration, SBP, and risks of CVDs and confirm the optimal cut-points for sleep duration and SBP. Methods: A retrospective analysis was conducted on NHANES 2007-2016 data, which included a nationally representative sample of participants. The maximum equal-odds ratio (OR) method was implemented to obtain optimal cut-points for each continuous independent variable. Then, a novel "recursive gradient scanning method" was introduced for discretizing multiple non-monotonic U-shaped independent variables. Finally, a multivariable logistic regression model was constructed to predict critical risk factors associated with CVDs after adjusting for potential confounders. Results: A total of 26,691 participants (48.66% were male) were eligible for the current study with an average age of 49.43 ± 17.69 years. After adjusting for covariates, compared with an intermediate range of sleep duration (6.5-8.0 h per day) and SBP (95-120 mmHg), upper or lower values were associated with a higher risk of CVDs [adjusted OR (95% confidence interval) was 1.20 (1.04-1.40) for sleep duration and 1.17 (1.01-1.36) for SBP]. Conclusions: This study indicates U-shaped relationships between SBP, sleep duration, and risks of CVDs. Both short and long duration of sleep/higher and lower BP are predictors of cardiovascular outcomes. Estimated total sleep duration of 6.5-8.0 h per day/SBP of 95-120 mmHg is associated with lower risk of CVDs.

An Optimal Prognostic Model Based on Multiparameter Ultrasound for Acute-on-Chronic Liver Failure.

OBJECTIVE: Acute-on-chronic liver failure (ACLF) is associated with a considerably high mortality, and accurate prognosis prediction is critical to navigate intervention decisions and improve clinical outcomes. The objective of this study was to establish a better prognostic model for ACLF based on multiparameter ultrasound in combination with clinical features. METHODS: A total of 149 patients with ACLF were prospectively enrolled and underwent conventional ultrasound, 2-D shear wave elastography (SWE), attenuation imaging, color Doppler sonography, superb microvascular imaging and contrast-enhanced ultrasound (CEUS). Univariate and multivariate analyses were performed to identify independent ultrasound signatures for the prognosis of ACLF, which, when integrated with clinical characteristics, were used to establish a prognostic model. RESULTS: Hepatic perfusion features of CEUS differed significantly between the poor and good prognosis groups, among which the time interval (TI) between peak portal vein (PV) velocity and liver parenchyma (LP) enhancement, TI(PV, LP), was independently associated with the prognosis of ACLF. A prediction model comprising TI(PV, LP) and the international normalized ratio was established, and the area under the curve (AUC) was 0.851, which is greater than those of the Model for End-stage Liver Disease (0.785), fall time of LP model (0.754), 2-D SWE nomogram (0.708) and TI(PV, LP) (0.352). Furthermore, the performance of the model was verified in an independent validation cohort (AUC = 0.920). CONCLUSION: The newly developed model performs better than existing tested models; thus, it has potential as a better non-invasive model for predicting the prognosis of patients with ACLF. A future multicenter, large-sample study is required to validate the performance of this model.

Spatially Confined LiF Nanoparticles in an Aligned Polymer Matrix as the Artificial SEI Layer for Lithium Metal Anodes.

The uncontrollable growth of lithium (Li) dendrites and the instability of the Li/electrolyte interface hinder the development of next-generation rechargeable lithium metal batteries. The combination of inorganic nanoparticles and polymers as the artificial SEI layer shows great potential in regulating lithium-ion flux. Here, we design spatially confined LiF nanoparticles in an aligned polymer matrix as the artificial SEI layer. A high dielectric polymer matrix homogenizes the electric field near the surface of lithium metal. Aligned pores with LiF nanoparticles promote the lithium-ion transport across the artificial SEI layer. The synergistic effect of the highly polar ß-phase PVDF and LiF nanoparticles provides high stability over 900 h for the Li//Li symmetrical cell. Besides, a Li//LFP full battery equipped with this artificial layer shows good performance in the commercial carbonate electrolyte, demonstrating the great potential of this protective film in lithium metal batteries.

Long-term Effects of a Social Media-Based Intervention (Run4Love) on Depressive Symptoms of People Living With HIV: 3-Year Follow-up of a Randomized Controlled Trial.

BACKGROUND: Emerging studies have shown the effectiveness of mobile health (mHealth) interventions in reducing depressive symptoms among people living with HIV. Most of these studies included only short-term follow-up, with limited data on long-term effects. OBJECTIVE: The purpose of this study is to assess the long-term effects of a randomized controlled trial called Run4Love on depressive symptoms among people living with HIV at 1-year and 3-year follow-ups. METHODS: A total of 300 people living with HIV with depressive symptoms were recruited and randomized to an intervention or a control group in Guangzhou, China, from September 2017 to January 2018. The intervention group received a 3-month Run4Love program, including adapted evidence-based cognitive behavioral stress management courses and exercise promotion via WeChat (Tencent), a popular social media app. The control group received usual care and a brochure on nutrition. The primary outcome was reduction in depressive symptoms, measured using the Center for Epidemiological Studies-Depression (CES-D) scale. Data used in this study were collected at baseline and at the 1-year and 3-year follow-ups. Generalized estimating equations were used to examine the group differences at 1-year and 3-year follow-ups. RESULTS: Approximately half of the participants completed the assessment at 1-year (149/300, 49.7%) and 3-year (177/300, 59%) follow-ups. At 1-year follow-up, participants in the intervention group reported significant reduction in depressive symptoms compared with the control group (CES-D: from 23.9 to 18.1 in the intervention group vs from 24.3 to 23.3 in the control group; mean -4.79, SD 13.56; 95% CI -7.78 to -1.81; P=.002). At 3-year follow-up, between-group difference in CES-D remained statistically significant (from 23.9 to 20.5 in the intervention group vs from 24.3 to 24.4 in the control group; mean -3.63, SD 13.35; 95% CI -6.71 to -0.54; P=.02). No adverse events were reported during the 3-year follow-up period. CONCLUSIONS: The mHealth intervention, Run4Love, significantly reduced depressive symptoms among people living with HIV, and the intervention effects were sustained at 1-year and 3-year follow-ups. Further research is needed to explore the mechanisms of the long-term effects of mHealth interventions such as Run4Love and to implement these effective interventions among people living with HIV. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR-IPR-17012606. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/10274.

Toward Highly Stable Anode for Secondary Batteries: Employing TiO2 Shell as Elastic Buffering Marix for FeOx Nanoparticles.

Transition metal oxides are considered promising anode materials for next-generation lithium-ion and sodium-ion batteries (LIBs and SIBs) because of their high theoretical capacities; however, their practical application is limited by the detrimental large volume expansion that occurs upon cycling. In this work, a rationally designed TiO2 @Fe@FeOx nanocomposite encapsulated by a TiO2 shell with unique core-shell structure is synthesized and exhibits outstanding electrochemical performance as an anode in LIBs and SIBs. The nanocomposite exhibits a reversible capacity of 619.2 mAh g-1 at 1 A g-1 with a coulombic efficiency over 99.5% after 1000 cycles when used as a LIB anode. The nanocomposite also exhibits superior sodium storage performance (267 mAh g-1 at 50 mA g-1 , capacity retention of 65.4% after 1000 cycles at 200 mA g-1 ). The TiO2 shell serves as a strong conformal layer and soft matrix that can tolerate the volume expansion and maintain the structural integrity of the anode during discharging and charging. Moreover, the open active diffusion channels of the shell contribute to high ion diffusivity and improved ionic, and electronic diffusion. These findings indicate that adoption of TiO2 coating is an effective strategy to optimize the electrochemical performance of transition metal oxide anode materials.

Anion-Doped Cobalt Selenide with Porous Architecture for High-Rate and Flexible Lithium-Sulfur Batteries.

Emerging catalytic host for sulfur is an effective approach to breaking the limits of lithium-sulfur batteries for practical applications. Herein, the hydrangea-shaped Co0.85 Se electrocatalyst with macroporous architecture is synthesized. Besides, to improve the electronic conductivity of Co0.85 Se, some defects (S-doped) are introduced into the structure of crystals. The S-doped Co0.85 Se exhibited an outstanding electrocatalytic effect on lithium polysulfides conversion and can induce and regulate uniform growth of insoluble Li2 S on its surface due to the synergistic adsorption by Se and S. As a result, the S/C cathode achieved a high initial capacity of 1340.6 mAh g-1 at 0.5 C and a stable cycling capacity of 666.6 mAh g-1 at 1 C after 500 cycles by 5 wt% Co0.85 SeS additions. Moreover, high S loading cathodes are designed through in situ synthesis of Co0.85 SeS on flexible carbon cloth (Co0.85 SeS@CC). The porous and open framework of Co0.85 SeS@CC facilitated electrolyte infiltration and accommodated the volume change of sulfur during the charge/discharge process. Taking by these advantages, a high areal capacity of 9.663 mAh cm-2 is achieved at a high sulfur loading of 9.98 mg cm-2 . Even at a high current density of 15 mA cm-2 , a reversible capacity of 603.7 mAh g-1 is maintained at a sulfur loading of 6.52 mg cm-2 . This proposed work provides a feasible approach to high-rate and flexible Li-S batteries.

Powering lithium-sulfur batteries by ultrathin sulfurized polyacrylonitrile nanosheets.

Sulfurized polyacrylonitrile (SPAN) is a promising cathode material for stable lithium-sulfur (Li-S) batteries due to its shuttle-free redox mechanism. However, the redox kinetics of SPAN needs to be enhanced to improve Li-S batteries. Herein, a salt-templating method is proposed for the fabrication of ultrathin SPAN nanosheets, which can afford a large contact area with the electrolyte and shorten the transport paths of electrons/ions involved in the reaction. In situ Raman analysis confirms the reversible breaking and formation of C-S/S-S bonds in SPAN nanosheets during cycling while ex situ SEM reveals the formation of lithium sulfide particles on the surface of SPAN nanosheets at the end of discharge. At a high current density of 2 A g-1, coin cells based on a SPAN nanosheet cathode can deliver a reversible capacity of 408 mA h g-1composite over 100 cycles with a capacity retention rate of 95%. Meanwhile, pouch cells using a SPAN nanosheet cathode exhibit a capacity retention rate close to 100% after 100 cycles at the same current density. These results herald a new approach for powering Li-S batteries by the nanoscale design of the SPAN cathode.

Advanced Li-S Batteries Enabled by a Biomimetic Polysulfide-Engulfing Net.

Lithium-sulfur batteries are attractive because of their high specific capacity and energy density, but issues with the polysulfide dissolution and shuttling intrinsically hinder their wide application. Here, hydroxylate multiwalled carbon nanotubes (MWCNT-OH) were grafted with a supramolecular polymer (heptakis(6-amino-6-deoxy)-ß-cyclodextrin) to form a polysulfide-engulfing net, which was coated on a separator. Such a molecular microarray structure of a polymer can block the polysulfides and have biomimetic cellular behavior for engulfing polysulfides. The cavity (∼6 Å) and functional groups of the supramolecular polymer can provide a dynamic structure for reversible adsorption of polysulfides while the conductive MWCNT-OH ensure fast electron transfer. The batteries with the modified separator exhibited excellent rate capacities (945.5 and 625.4 mA h g-1 at 2 C and 4 C rates, respectively). Especially, the high areal capacities of 5.86 and 7.2 mA h cm-2 achieved at S loadings of 4.5 and 6.0 mg cm-2 and good cycling stability after 200 cycles at 0.1 C can be obtained. This demonstrates a strategy of supramolecular polymer-grafted carbon for dynamic polysulfide adsorption toward advanced Li-S batteries.

MOF-derived lithiophilic CuO nanorod arrays for stable lithium metal anodes.

Lithium (Li) metal is regarded as the most promising anode material for next-generation high energy density rechargeable batteries. However, the uncontrolled growth of Li dendrites and the infinite volume expansion of Li decrease the coulombic efficiency and cause safety concerns. One of the best strategies to solve these problems is engineering a nanostructured interface on the current collector. Thus, in the present paper, to regulate Li nucleation and suppress the growth of Li dendrites, metal-organic framework (MOF)-derived CuO nanorod arrays with lithiophilic groups were synthesized on a Cu foil current collector (CuO NAs/CF). The CuO nanorod arrays with the N-containing group in CuO NAs/CF not only acted as lithiophilic active sites to reduce the nucleation barrier to Li deposition, but also decreased the current density and homogenized the Li-ion flux distribution. The CuO NAs/CF electrode showed a high coulombic efficiency of 98% for more than 180 cycles at 1 mA cm-2 and excellent cycling stability with a low overpotential of 30 mV for 600 h in symmetric cells. Based on the Li-CuO NAs/CF composite anode, full cells with a LiFePO4 cathode showed improved cycling stability, small polarization, and flat voltage curves compared with the cells using a planar Cu current collector. This work provides a new strategy for designing MOF-derived materials for stable, dendrite-free lithium metal anodes.

Cobalt nanoparticles shielded in N-doped carbon nanotubes for high areal capacity Li-S batteries.

N-Doped carbon nanotubes with embedded cobalt nanoparticles (Co-NCNTs) were prepared by thermally annealing a mixture of ZIF-67 and dicyandiamide precursors. Because of the dual chemical affinity of Co and N to S species, Li-S batteries with a Co-NCNT modified separator revealed enhanced redox kinetics of lithium polysulfide conversion and achieved a high areal capacity of 3.73 mA h cm-2 after 100 cycles at 0.1C at a sulfur loading of 4.3 mg cm-2.

Boosting High-Rate Li-S Batteries by an MOF-Derived Catalytic Electrode with a Layer-by-Layer Structure.

Rechargeable high-energy lithium-sulfur batteries suffer from rapid capacity decay and poor rate capability due to intrinsically intermediate polysulfides' shuttle effect and sluggish redox kinetics. To tackle these problems simultaneously, a layer-by-layer electrode structure is designed, each layer of which consists of ultrafine CoS2-nanoparticle-embedded porous carbon evenly grown on both sides of reduced graphene oxide (rGO). The CoS2 nanoparticles derived from metal-organic frameworks (MOFs) have an average size of ≈10 nm and can facilitate the conversion between Li2S6 and Li2S2/Li2S in the liquid electrolyte by a catalytic effect, leading to improved polysulfide redox kinetics. In addition, the interconnected conductive frameworks with hierarchical pore structure afford fast ion and electron transport and provide sufficient space to confine polysulfides. As a result, the layer-by-layer electrodes exhibit good rate capabilities with 1180.7 and 700 mAh g-1 at 1.0 and 5.0 C, respectively, and maintain an impressive cycling stability with a low capacity decay of 0.033% per cycle within ultralong 1000 cycles at 5.0 C. Even with a high sulfur loading of 3.0 mg cm-2, the electrodes still show high rate performance and stable cycling stability over 300 cycles.

Multifunctional Self-Healing Ionogels from Supramolecular Assembly: Smart Conductive and Remarkable Lubricating Materials.

Self-healing ionogel is a promising smart material because of its high conductivity and reliable stimuli responsiveness upon mechanical damage. However, self-healing ionogels possessing rapid, complete recovery properties and multifunctionality are still limited. Herein, we designed a new d-gluconic acetal-based gelator (PB8) bearing a urea group in the alkyl side chain. Interestingly, the balance between hydrophilicity and hydrophobicity of the molecule is achieved. Thus, PB8 could form transparent ionogels because of its excellent affinity to ionic liquids (ILs), which exhibited appropriate mechanical strength, high viscoelasticity, and efficient self-healing properties. The presence of synergistic effects from hydrogen bonding, π-π stacking, and interactions between the urea-containing side chains was responsible for the self-assembly of gelators in ILs and the self-healing property mainly related to the side chains of PB8. Interestingly, the transparent PB8-IL4 ionogel possessed high conductivity and mechanical strength, moldable and injectable properties, and rapid and complete self-healing characteristics (complete recovery within 14 min), which showed excellent performance as a smart ionic conductor. Furthermore, the self-healing PB8-based ionogels with anticorrosion properties are a remarkable lubricating material in the steel-steel contact and exhibited excellent lubricating performances. Overall, an efficient PB8-based ionogel with self-healing properties has been developed for potential use both as a smart electrical conductor and as a high-performance lubricating material. The unique structure of PB8 bearing a urea group in the side chain is found to be responsible for the multifunctional ionogel formation.

Development of Self-Healing d-Gluconic Acetal-Based Supramolecular Ionogels for Potential Use as Smart Quasisolid Electrochemical Materials.

Formation of supramolecular ionic liquid (IL) gels (ionogels) induced by low-molecular-mass gelators (LMMGs) is an efficient strategy to confine ILs, and the negligible influence of LMMGs on the electrochemical properties of ILs makes ionogels ideal quasisolid electrochemical materials. Furthermore, the stimuli-responsive and self-healing characters of the supramolecular gel can be utilized for the potential development of smart electrochemical materials. However, the poor mechanical properties of supramolecular ionogels reported so far limit their practical applications. Herein, we investigated a series of efficient d-gluconic acetal-based gelators (Gn, PG16, and B8) that can harden a wide variety of ILs at low concentrations. It was shown that both alkyl chain length and the number of hydrogen bonding sites of a certain gelator, as well as the nature of the IL anion, significantly influenced the gelation abilities. The resulting ionogels were thermally reversible, and most of them were stable at room temperature. Interestingly, a PG16-based supramolecular ionogel showed rapid self-healing properties upon mechanical damage. Furthermore, the PG16-based ionogel demonstrated unprecedented performances including the favorable ionic conductivity, excellent mechanical strength, and enhanced viscoelasticity, which make it a great self-healing electrochemical material. The ionogel formation mechanism was proposed based on the analysis of Fourier transform infrared, 1HNMR, and X-ray diffraction, indicating that a combination of hydrogen bonding, π-π stacking, and interactions between alkyl chains was responsible for the self-assembly of gelators in ILs. Overall, our present studies on exploring the structure-property relationship of gelators for the formation of practically useful supramolecular ionogels shed light for future development of more functionalized ionogels.

Flexible and highly transparent two-component organogels with enhanced viscoelasticity for self-healing materials and room-temperature phase-selective gelation.

A novel two-component organogel system based on acid-base interaction showed flexibility, high-transparency and self-healing properties with enhanced viscoelasticity. Meanwhile, the two-component gelator displayed room-temperature phase selective gelation of aromatic solvents from aromatic solvents/water mixtures in powder form and excellent dye removal ability.