In Situ Polymerization Bi-Functional Gel Polymer Electrolyte for High Performance Quasi-Solid-State Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries are expected to be the next-generation energy storage system due to the ultrahigh theoretical energy density and low cost. However, the notorious shuttle effect of higher-order polysulfides and the uncontrollable lithium dendrite growth are the two biggest challenges for commercially viable Li-S batteries. Herein, these two main challenges are solved by in situ polymerization of bi-functional gel polymer electrolyte (GPE). The initiator (SiCl4) not only drives the polymerization of 1,3-dioxolane (DOL) but also induces the construction of a hybrid solid electrolyte interphase (SEI) with inorganic-rich compositions on the Li anode. In addition, diatomaceous earth (DE) is added and anchored in the GPE to obtain PDOL-SiCl4-DE electrolyte through in situ polymerization. Combined with density functional theory (DFT) calculations, the hybrid SEI provides abundant adsorption sites for the deposition of Li+, inhibiting the growth of lithium dendrites. Meanwhile, the shuttle effect is greatly alleviated due to the strong adsorption capacity of DE toward lithium polysulfides. Therefore, the Li/Li symmetric cell and Li-S full cell assembled with PDOL-SiCl4-DE exhibit excellent cycling stability. This study offers a valuable reference for the development of high performance and safe Li-S batteries.

Huntington's Disease: Complex Pathogenesis and Therapeutic Strategies.

Huntington's disease (HD) arises from the abnormal expansion of CAG repeats in the huntingtin gene (HTT), resulting in the production of the mutant huntingtin protein (mHTT) with a polyglutamine stretch in its N-terminus. The pathogenic mechanisms underlying HD are complex and not yet fully elucidated. However, mHTT forms aggregates and accumulates abnormally in neuronal nuclei and processes, leading to disruptions in multiple cellular functions. Although there is currently no effective curative treatment for HD, significant progress has been made in developing various therapeutic strategies to treat HD. In addition to drugs targeting the neuronal toxicity of mHTT, gene therapy approaches that aim to reduce the expression of the mutant HTT gene hold great promise for effective HD therapy. This review provides an overview of current HD treatments, discusses different therapeutic strategies, and aims to facilitate future therapeutic advancements in the field.

Aberrant splicing of mutant huntingtin in Huntington's disease knock-in pigs.

Huntington's disease (HD) is an autosomal-dominant inherited neurodegenerative disease caused by a CAG repeat expansion in exon1 of the huntingtin gene (HTT). This expansion leads to the production of N-terminal mutant huntingtin protein (mHtt) that contains an expanded polyglutamine tract, which is toxic to neurons and causes neurodegeneration. While the production of N-terminal mHtt can be mediated by proteolytic cleavage of full-length mHtt, abnormal splicing of exon1-intron1 of mHtt has also been identified in the brains of HD mice and patients. However, the proportion of aberrantly spliced exon1 mHTT in relation to normal mHTT exon remains to be defined. In this study, HTT exon1 production was examined in the HD knock-in (KI) pig model, which more closely recapitulates neuropathology seen in HD patient brains than HD mouse models. The study revealed that aberrant spliced HTT exon1 is also present in the brains of HD pigs, but it is expressed at a much lower level than the normally spliced HTT exon products. These findings suggest that careful consideration is needed when assessing the contribution of aberrantly spliced mHTT exon1 to HD pathogenesis, and further rigorous investigation is required.

High-Performance Solid Lithium Metal Batteries Enabled by LiF/LiCl/LiIn Hybrid SEI via InCl3 -Driven In Situ Polymerization of 1,3-Dioxolane.

The use of poly(1,3-dioxolane) (PDOL) electrolyte for lithium batteries has gained attention due to its high ionic conductivity, low cost, and potential for large-scale applications. However, its compatibility with Li metal needs improvement to build a stable solid electrolyte interface (SEI) toward metallic Li anode for practical lithium batteries. To address this concern, this study utilized a simple InCl3 -driven strategy for polymerizing DOL and building a stable LiF/LiCl/LiIn hybrid SEI, confirmed through X-ray photoelectron spectroscopy (XPS) and cryogenic-transmission electron microscopy (Cryo-TEM). Furthermore, density functional theory (DFT) calculations and finite element simulation (FES) verify that the hybrid SEI exhibits not only excellent electron insulating properties but also fast transport properties of Li+ . Moreover, the interfacial electric field shows an even potential distribution and larger Li+ flux, resulting in uniform dendrite-free Li deposition. The use of the LiF/LiCl/LiIn hybrid SEI in Li/Li symmetric batteries shows steady cycling for 2000 h, without experiencing a short circuit. The hybrid SEI also provided excellent rate performance and outstanding cycling stability in LiFePO4 /Li batteries, with a high specific capacity of 123.5 mAh g-1 at 10 C rate. This study contributes to the design of high-performance solid lithium metal batteries utilizing PDOL electrolytes.

Stable LiF-Rich Electrode-Electrolyte Interface toward High-Voltage and High-Energy-Density Lithium Metal Solid Batteries.

Lithium-rich layered oxide (LRLO) materials have attracted significant attention due to their high specific capacity, low cost, and environmental friendliness. However, owing to its unique capacity activation mechanism, the release of lattice oxygen during the first charge process leads to a series of problems, such as severe voltage decay, poor cycle stability, and poor rate performance. Herein, a fluorinated quasi-solid-state electrolyte (QSSE) via a simple thermal polymerization method toward lithium metal batteries with LRLO materials is reported. The well-designed QSSE exhibits an ionic conductivity of 6.4 × 10-4 S cm-1 at 30 °C and a wide electrochemical stable window up to 5.6 V. Most importantly, XPS spectra demonstrate the generation of a LiF-rich electrode-electrolyte interface (EEI), where the in situ generated LiF provides strong protection against the structural degradation of LRLO materials and directs the uniform plating/stripping behaviors of lithium-ions to inhibit the formation of lithium dendrites. As a result, LRLO/QSSE/Li batteries exhibit excellent rate performance and demonstrate a large initial capacity for 209.7 mA h g-1 with a capacity retention of 80.8% after 200 cycles at 0.5C. This work provides a new insight for the LiF-rich EEI design of safe, high-performance quasi-solid-state lithium metal batteries.

Highly CEP-stable optical parametric amplifier at 2†µm with a few-cycle duration and 100 kHz repetition rate.

We develop a BiB3O6 (BiBO)-based optical parametric amplifier in the spectral region around 2 µm using a Yb:KGW amplifier operating at 100 kHz. The two-stage degenerate optical parametric amplification results in a typical output energy of 30 µJ after compression, spectrum covering 1.7-2.5 µm range, and a pulse duration fully compressible down to 16.4 fs, corresponding to 2.3 cycles. Due to the inline difference frequency generation of the seed pulses, the carrier envelope phase (CEP) is passively stabilized without feedback over 11 hours at the level below 100 mrad including a long-term drift. Short-term statistical analysis in the spectral domain further shows a behavior qualitatively different from that of parametric fluorescence, indicating high degree of suppression of optical parametric fluorescence. The high phase stability together with the few-cycle pulse duration is promising for the investigation of high-field phenomena such as subcycle spectroscopy in solids or high harmonics generation.

TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile.

Determining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular mechanisms regulating gene expression in different biological conditions. Biological assays designed to directly mapping TFBSs require large sample size and intensive resources. As an alternative, ATAC-seq assay is simple to conduct and provides genomic cleavage profiles that contain rich information for imputing TFBSs indirectly. Previous footprint-based tools are inheritably limited by the accuracy of their bias correction algorithms and the efficiency of their feature extraction models. Here we introduce TAMC (Transcriptional factor binding prediction from ATAC-seq profile at Motif-predicted binding sites using Convolutional neural networks), a deep-learning approach for predicting motif-centric TF binding activity from paired-end ATAC-seq data. TAMC does not require bias correction during signal processing. By leveraging a one-dimensional convolutional neural network (1D-CNN) model, TAMC make predictions based on both footprint and non-footprint features at binding sites for each TF and outperforms existing footprinting tools in TFBS prediction particularly for ATAC-seq data with limited sequencing depth.

Characteristics and influencing factors of social isolation in patients with breast cancer: a latent profile analysis.

PURPOSE: The goal of this study is to investigate the social isolation (SI) subtypes of patients with breast cancer (BC) and to explore its influencing factors. METHODS: A sample of 303 BC patients participated in the study from September to December, 2021. Latent profile analysis (LPA) was performed to identify SI clusters based on the three sub-scales of the Chinese version of the Social Anxiety Scale, the Chinese version of the Social Avoidance and Distress Scale, and the Chinese version of the Loneliness Scale. RESULTS: We found that SI can be divided into three categories: high-level (Class 1), middle-level (Class 2), and low-level (Class 3), accounting for 20.46%, 33.00%, and 46.54%, respectively. Compared to Class 3, Class 1, which had the lower average monthly income per family member (RMB) (< 3000: OR = 5.298, P = .021; 3000 ~ 5000: OR = 5.320, P = .018), was more likely to suffer from SI due to occupation (Laborer: OR = 12.023, P = .009). Surgery (OR = 14.138, P < .001; OR = 2.777, P = .020), chemotherapy (OR = 10.224, P = .001; OR = 3.545, P = .001); poorer family functioning (OR = .671, P < .001; OR = .801, P = .002), and lower levels of self-transcendence (OR = .806, P < .001; OR = .911, P < .001) were important influencing factors for SI in Class 1 and Class 2 compared to Class 3. CONCLUSION: SI is classifiably heterogeneous among patients with BC. Strategies that identify characteristics of SI and give targeted intervention focusing on family functioning and improving self-transcendence levels contribute to the prevention of SI among patients with BC.

Relationship of sleep-quality and social-anxiety in patients with breast cancer: a network analysis.

BACKGROUND: There is a complex relationship between social anxiety and sleep quality. However, network analysis studies of associations between social anxiety and sleep quality are lacking, particularly among patients with breast cancer. The current study aimed to extend this research to a sample of patients with breast cancer and to examine symptom-level associations between social anxiety and sleep quality using network analysis. METHODS: Network analysis was conducted to explore their associations and identify bridge items of social anxiety and sleep quality. RESULTS: The network structure revealed 9 important edges between social anxiety and sleep quality. "Subjective sleep quality" had the highest EI value in the network. "Working difficulty under watching" and "Sleep disorders" had the highest BEI values in their own communities. CONCLUSION: There are complex pathological correlation pathways between social anxiety and sleep quality in breast cancer patients. "Subjective sleep quality", "Working difficulty under watching" and "Sleep disorders" have the potential to be intervention targets for sleep disorder-social anxiety comorbidity. Medical staff can take corresponding interventions according to the the centrality indices and bridge centrality indicators identified in this study, which is likely to effectively reduce the comorbidity of sleep disorders and social anxiety.

Pterygium combined with corneal perforation: a case report.

BACKGROUND: Pterygium is a common ocular surface disease. Pterygium combined with corneal perforation is rare. CASE PRESENTATION: A 28-year-old female patient visited our outpatient clinic due to sudden onset of blurred vision and increased tearing in her left eye. The visual acuity was 1.0 OD and intraocular pressure (IOP) of 19.5 mmHg for the right eye with no significant abnormalities found in the anterior and posterior segments. The visual acuity of her left eye was 0.06, and IOP was 6.2 mmHg. A triangular vascular membranous tissue was seen in her left eye below the nose growing into the cornea and the pupil area was not touched. Slit-lamp examination revealed a tiny round corneal perforation in 8 o'clock position of the lesion area. Hospital diagnosis was given as pterygium combined with corneal perforation. The patient was treated with levofloxacin eye drops and autologous serum-based eye drops. CONCLUSIONS: We report a rare case of pterygium combined with corneal perforation. Perforation is a very rare complication of pterygium. This patient received proper treatment and good result was seen. This article aimed to improve clinicians' understanding of pterygium.

Huntingtin Interacting Proteins and Pathological Implications.

Huntington's disease (HD) is caused by an expansion of a CAG repeat in the gene that encodes the huntingtin protein (HTT). The exact function of HTT is still not fully understood, and previous studies have mainly focused on identifying proteins that interact with HTT to gain insights into its function. Numerous HTT-interacting proteins have been discovered, shedding light on the functions and structure of HTT. Most of these proteins interact with the N-terminal region of HTT. Among the various HTT-interacting proteins, huntingtin-associated protein 1 (HAP1) and HTT-interacting protein 1 (HIP1) have been extensively studied. Recent research has uncovered differences in the distribution of HAP1 in monkey and human brains compared with mice. This finding suggests that there may be species-specific variations in the regulation and function of HTT-interacting proteins. Understanding these differences could provide crucial insights into the development of HD. In this review, we will focus on the recent advancements in the study of HTT-interacting proteins, with particular attention to the differential distributions of HTT and HAP1 in larger animal models.

Increasing astrogenesis in the developing hippocampus induces autistic-like behavior in mice via enhancing inhibitory synaptic transmission.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized primarily by impaired social communication and rigid, repetitive, and stereotyped behaviors. Many studies implicate abnormal synapse development and the resultant abnormalities in synaptic excitatory-inhibitory (E/I) balance may underlie many features of the disease, suggesting aberrant neuronal connections and networks are prone to occur in the developing autistic brain. Astrocytes are crucial for synaptic formation and function, and defects in astrocytic activation and function during a critical developmental period may also contribute to the pathogenesis of ASD. Here, we report that increasing hippocampal astrogenesis during development induces autistic-like behavior in mice and a concurrent decreased E/I ratio in the hippocampus that results from enhanced GABAergic transmission in CA1 pyramidal neurons. Suppressing the aberrantly elevated GABAergic synaptic transmission in hippocampal CA1 area rescues autistic-like behavior and restores the E/I balance. Thus, we provide direct evidence for a developmental role of astrocytes in driving the behavioral phenotypes of ASD, and our results support that targeting the altered GABAergic neurotransmission may represent a promising therapeutic strategy for ASD.

Sequelae of COVID-19 among previously hospitalized patients up to 1 year after discharge: a systematic review and meta-analysis.

OBJECTIVE: Although complications and clinical symptoms of COVID-19 have been elucidated, the prevalence of long-term sequelae of COVID-19 is less clear in previously hospitalized COVID-19 patients. This review and meta-analysis present the occurrence of different symptoms up to 1 year of follow-up for previously hospitalized patients. METHODS: We performed a systematic review from PubMed and Web of Science using keywords such as "COVID-19", "SARS-CoV-2", "sequelae", "long-term effect" and included studies with at least 3-month of follow-up. Meta-analyses using random-effects models were performed to estimate the pooled prevalence for different sequelae. Subgroup analyses were conducted by different follow-up time, regions, age and ICU admission. RESULTS: 72 articles were included in the meta-analyses after screening 11,620 articles, identifying a total of 167 sequelae related to COVID-19 from 88,769 patients. Commonly reported sequelae included fatigue (27.5%, 95% CI 22.4-33.3%, range 1.5-84.9%), somnipathy (20.1%, 95% CI 14.7-26.9%, range 1.2-64.8%), anxiety (18.0%, 95% CI 13.8-23.1%, range 0.6-47.8%), dyspnea (15.5%, 95% CI 11.3-20.9%, range 0.8-58.4%), PTSD (14.6%, 95% CI 11.3-18.7%, range 1.2-32.0%), hypomnesia (13.4%, 95% CI 8.4-20.7%, range 0.6-53.8%), arthralgia (12.9%, 95% CI 8.4-19.2%, range 0.0-47.8%), depression (12.7%, 95% CI 9.3-17.2%, range 0.6-37.5%), alopecia (11.2%, 95% CI 6.9-17.6%, range 0.0-47.0%) over 3-13.2 months of follow-up. The prevalence of most symptoms reduced after > 9 months of follow-up, but fatigue and somnipathy persisted in 26.2% and 15.1%, respectively, of the patients over a year. COVID-19 patients from Asia reported a lower prevalence than those from other regions. CONCLUSIONS: This review identified a wide spectrum of COVID-19 sequelae in previously hospitalized COVID-19 patients, with some symptoms persisting up to 1 year. Management and rehabilitation strategies targeting these symptoms may improve quality of life of recovered patients.

Association Between Platelet Glycoprotein IIb/IIIa Inhibition and In-Hospital Outcomes in ST-Elevation Myocardial Infarction Patients Treated with Coronary Thrombus Aspiration: Findings from the CCC-ACS Project.

PURPOSE: Thrombus aspiration in ST-elevation myocardial infarction (STEMI) with high thrombus burden did not improve clinical outcomes. The clinical efficacy of the bailout use of platelet glycoprotein IIb/IIIa inhibitors (GPIs) in this clinical scenario remains unknown. METHODS: We assessed associations between GPI use and in-hospital major bleeds, ischemic events, and mortality among STEMI patients treated with percutaneous coronary intervention (PCI) and thrombus aspiration in a nationwide acute coronary syndrome registry (the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome project). RESULTS: A total of 5896 STEMI patients who received thrombus aspiration were identified, among which 56.3% received GPI therapy. In a 1-to-1 propensity-score-matched cohort, compared with STEMI patients not treated with GPI, GPI use was associated with a 69% increase in major in-hospital bleeds, with an odds ratio (OR) of 1.69, a 95% confidence interval (CI) of 1.08 to 2.65, and a nonsignificant reduction in ischemic events (OR: 0.61, 95% CI: 0.36 to 1.06), as well as a neutral effect on mortality (OR: 0.93, 95% CI: 0.55 to 1.58). However, among patients aged < 60 years, GPI use was associated with a reduction in ischemic events (OR: 0.27, 95% CI: 0.08 to 0.98), and no significant increase in major bleeds was observed. CONCLUSION: In a nationwide registry, routine use of GPI following thrombus aspiration was not associated with reduced in-hospital ischemic events and mortality but at the cost of increased major bleeding. However, for patients aged < 60 years, there may be a potential net benefit.

Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories.

BACKGROUND: No consensus has been reached on an optimal blood lactate evaluation system although several approaches have been reported in the literature in recent years. A group-based trajectory modeling (GBTM) method could better stratify patients with acute respiratory distress syndrome (ARDS) complicated with sepsis in the intensive care unit (ICU). PATIENTS AND METHODS: 760 patients from the comprehensive ICU of Tianjin Medical University General Hospital with ARDS complicated with sepsis were eligible for analysis. Serial serum lactate levels were measured within 48 h of admission. In addition to the GBTM lactate groups, the initial lactate, peak lactate level, the area under the curve of serial lactate (lactate AUC), and lactate clearance were also considered for comparison. The short- and long-term outcomes were the 30- and 90-day mortality, respectively. RESULTS: Three lactate groups were identified based on GBTM, with group 3 exhibiting the worse short- [hazard ratio (HR) for 30-day mortality: 2.96, 95% confidence interval (CI) 1.79-4.87, P < 0.001] and long term (HR for 90-day mortality: 3.49, 95% CI 2.06-5.89, P < 0.001) outcomes followed by group 2 (HR for 30-day mortality: 2.05, 95% CI 1.48-2.84, P < 0.001 and HR for 90-day mortality: 1.99, 95% CI 1.48-2.67, P < 0.001). GBTM lactate groups exhibited significantly improved diagnostic performance of initial lactate + SOFA scores/APACHE II scores models. Based on the multivariable fractional polynomial interaction (MFPI) approach, GBTM lactate groups could better differentiate high-risk patients than the initial lactate groups in short- and long-term outcomes. CONCLUSIONS: To the best of our knowledge, this is the first report that GBTM-based serial blood lactate evaluations significantly improve the diagnostic capacity of traditional critical care evaluation systems and bring many advantages over previously documented lactate evaluation systems.

Design framework for metasurface optics-based convolutional neural networks.

Deep learning using convolutional neural networks (CNNs) has been shown to significantly outperform many conventional vision algorithms. Despite efforts to increase the CNN efficiency both algorithmically and with specialized hardware, deep learning remains difficult to deploy in resource-constrained environments. In this paper, we propose an end-to-end framework to explore how to optically compute the CNNs in free-space, much like a computational camera. Compared to existing free-space optics-based approaches that are limited to processing single-channel (i.e., gray scale) inputs, we propose the first general approach, based on nanoscale metasurface optics, that can process RGB input data. Our system achieves up to an order of magnitude energy savings and simplifies the sensor design, all the while sacrificing little network accuracy.

Excitation mechanism of A1g mode and origin of nonlinear temperature dependence of Raman shift of CVD-grown mono- and few-layer MoS2 films.

MoS2 films are grown on SiO2/Si substrates by chemical vapor deposition. The vibrational properties of optical phonons of mono-, bi- and multilayer MoS2 are studied by Raman scattering spectroscopy over temperature range from 90 to 540 K with 514.5 nm and 785 nm lasers. The Raman peaks of E2g1 and A1g modes are observed simultaneously for mono-, bi- and multilayer MoS2 with 514.5 nm laser, but only the Raman peak of E2g1 mode is seen for monolayer MoS2 as 785 nm laser is used, revealing electron-phonon exchange excitation mechanism of A1g mode for the first time. The Raman shifts of E2g1 and A1g modes present obvious nonlinear temperature dependence. A semi-quantitative model is used to fit the nonlinear temperature dependence of Raman shifts which matches well to experimental data. Meanwhile, the fitting results reveal that the nonlinear temperature dependence of Raman shifts of E2g1 mode mainly originates from three-phonon anharmonic effect, while one of A1g mode is contributed by stronger three- and weaker four-phonon anharmonic effects cooperatively but two contributions are comparable in intensity.

Study on the Water Absorption Characteristics of Anthracite Particles after Immersion in Water.

Reducing pollution caused by coal dust has always been a hot issue in the coal mining industry, and the water absorption of coal particles plays an important role in dust reduction. To study the relationship between different immersion time and the water absorption of coal particles, the substance content of coal particles after immersion was analyzed and water absorption characterization of coal particles was carried out by X-ray diffraction (XRD), water absorption calculations, and water absorption measurements. The results indicate that immersion can alter the material content of coal particles, leading to a decrease in the content of soluble mineral kaolinite, thereby affecting the wettability of coal particles. Notably, the longer the immersion time, the higher the water absorption rate of the particles, indicating a more significant water absorption effect. Furthermore, there is a negative correlation between particle sizes and water absorption of coal particles. The research results provide a theoretical reference for reducing coal dust pollution and improving the efficiency of dust suppression through spray.

The association of impulsivity with depression and anxiety symptoms: A transdiagnostic network analysis and replication.

BACKGROUND: Impulsivity increases the risk for depression and anxiety. However, the granular pathways among them remain unknown. A network approach that moves from disorder-level analysis to symptom-level analysis can provide further understanding of psychopathological mechanisms. In this study, we examined the network structure of impulsivity and separate and comorbid symptoms of depression and anxiety. METHODS: Regularized partial-correlation networks were estimated using cross-sectional data from 1047 Chinese participants aged 18-26 years (main dataset, mean age = 21.45 ± 2.01 years) and 325 Chinese participants aged 18-36 years (an independent replication dataset, mean age = 21.49 ± 3.73 years), including impulsivity-depression, impulsivity-anxiety, and impulsivity-depression-anxiety networks. The datasets were collected from 1 June 2023 to 4 August 2023 and from 27 April 2022 to 16 May 2022, respectively. Impulsivity, depression, and anxiety were assessed using Barratt Impulsiveness Scale Version 11, Patient Health Questionnaire-9, and Generalized Anxiety Disorder-7, respectively. Bridge centrality was analyzed, and a network comparison test (NCT) was conducted to investigate the differences between the main dataset and replication dataset. RESULTS: The motor impulsivity dimension was revealed to be closely connected with individual symptoms of depression and anxiety regardless of whether they were in separate disorder forms or comorbid forms. In all the networks, motor impulsivity was the most important bridge node. The NCT showed comparable network connectivity and network structure between the main and replication datasets. LIMITATIONS: The use of cross-sectional data limited the inferences about the direction of causality between variables. CONCLUSIONS: These findings elucidate the psychopathological mechanisms underlying how impulsivity functions within depression, anxiety, and comorbidity and support that motor impulsivity is an important risk factor across different mental disorders and is responsible for comorbidity. The implications of these findings are discussed.