A Multiview Brain Network Transformer Fusing Individualized Information for Autism Spectrum Disorder Diagnosis.

Functional connectivity (FC) networks, built from analyses of resting-state magnetic resonance imaging (rs-fMRI), serve as efficacious biomarkers for identifying Autism Spectrum Disorders (ASD) patients. Given the neurobiological heterogeneity across individuals and the unique presentation of ASD symptoms, the fusion of individualized information into diagnosis becomes essential. However, this aspect is overlooked in most methods. Furthermore, the existing methods typically focus on studying direct pairwise connections between brain ROIs, while disregarding interactions between indirectly connected neighbors. To overcome above challenges, we build common FC and individualized FC by tangent pearson embedding (TP) and common orthogonal basis extraction (COBE) respectively, and present a novel multiview brain transformer (MBT) aimed at effectively fusing common and individualized information of subjects. MBT is mainly constructed by transformer layers with diffusion kernel (DK), fusion quality-inspired weighting module (FQW), similarity loss and orthonormal clustering fusion readout module (OCFRead). DK transformer can incorporate higher-order random walk methods to capture wider interactions among indirectly connected brain regions. FQW promotes adaptive fusion of features between views, and similarity loss and OCFRead are placed on the last layer to accomplish the ultimate integration of information. In our method, TP, DK and FQW modules all help to model wider connectivity in the brain that make up for the shortcomings of traditional methods. We conducted experiments on the public ABIDE dataset based on AAL and CC200 respectively. Our framework has shown promising results, outperforming state-of-the-art methods on both templates. This suggests its potential as a valuable approach for clinical ASD diagnosis.

Visualization of Microcirculation at Acupoints in vivo of Alzheimer's Disease Animal Model with Photoacoustic Microscope: A Pilot Study.

Background: Alzheimer's disease may be effectively treated with acupoint-based acupuncture, which is acknowledged globally. However, more research is needed to understand the alterations in acupoints that occur throughout the illness and acupuncture treatment. Objective: This research investigated the differences in acupoint microcirculation between normal mice and AD animals in vivo. This research also examined how acupuncture affected AD animal models and acupoint microcirculation. Methods: 6-month-old SAMP8 mice were divided into two groups: the AD group and the acupuncture group. Additionally, SAMR1 mice of the same month were included as the normal group. The study involved subjecting a group of mice to 28 consecutive days of acupuncture at the ST36 (Zusanli) and CV12 (Zhongwan) acupoints. Following this treatment, the Morris water maze test was conducted to assess the mice's learning and memory abilities; the acoustic-resolution photoacoustic microscope (AR-PAM) imaging system was utilized to observe the microcirculation in CV12 acupoint region and head-specific region of each group of mice. Results: In comparison to the control group, the mice in the AD group exhibited a considerable decline in their learning and memory capabilities (p < 0.01). In comparison to the control group, the vascular in the CV12 region and head-specific region in mice from the AD group exhibited a considerable reduction in length, distance, and diameter r (p < 0.01). The implementation of acupuncture treatment had the potential to enhance the aforementioned condition to a certain degree. Conclusions: These findings offered tangible visual evidence that supports the ongoing investigation into the underlying mechanisms of acupuncture's therapeutic effects.

Genetic Landscape and Its Prognostic Impact in Children With Langerhans Cell Histiocytosis.

CONTEXT.­: Langerhans cell histiocytosis (LCH) is a rare myeloid neoplasm that predominantly affects young children. OBJECTIVE.­: To investigate genetic alterations and their correlation with clinical characteristics and prognosis in pediatric LCH. DESIGN.­: We performed targeted sequencing to detect mutations in LCH lesions from pediatric patients. RESULTS.­: A total of 30 genomic alterations in 5 genes of the MAPK pathway were identified in 187 of 223 patients (83.9%). BRAF V600E (B-Raf proto-oncogene, serine/threonine kinase) was the most common mutation (51.6%), followed by MAP2K1 (mitogen-activated protein kinase kinase 1) alterations (17.0%) and other BRAF mutations (13.0%). ARAF (A-Raf proto-oncogene, serine/threonine kinase) and KRAS (KRAS proto-oncogene, GTPase) mutations were relatively rare (2.2% and 0.9%, respectively). Additionally, FNBP1 (formin-binding protein 1)::BRAF fusion and MAP3K10 (mitogen-activated protein kinase kinase 10) mutations A17T and R823C were identified in 1 case each, with possible constitutive activation of ERK1/2 phosphorylation. BRAF V600E was more frequent in patients with risk organ involvement, while MAP2K1 mutation was more prevalent in patients with single-system LCH (P = .001). BRAF V600E was associated with craniofacial bone, skin, liver, spleen, and ear involvement (all P < .05). Patients with other BRAF mutations had a higher proportion of spinal column involvement (P = .006). Univariate analysis showed a significant difference in progression-free survival among the 4 molecular subgroups for patients treated with first-line therapy (P = .02). According to multivariate analysis, risk organ involvement was the strongest independent adverse prognostic factor (hazard ratio, 8.854; P < .001); BRAF or MAP2K1 mutation was not an independent prognostic factor. CONCLUSIONS.­: Most pediatric patients with LCH carry somatic mutations involving the MAPK pathway, correlating with clinical characteristics and outcomes for first-line chemotherapy.

Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features.

BACKGROUND AND HYPOTHESIS: Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (MRI) as a tool to enhance SZ diagnosis and provide objective references and biomarkers. Using deep learning with graph convolution, we represent MRI data as graphs, aligning with brain structure, and improving feature extraction, and classification. Integration of multiple modalities is expected to enhance classification. STUDY DESIGN: Our study enrolled 683 SZ patients and 606 healthy controls from 7 hospitals, collecting structural MRI and functional MRI data. Both data types were represented as graphs, processed by 2 graph attention networks, and fused for classification. Grad-CAM with graph convolution ensured interpretability, and partial least squares analyzed gene expression in brain regions. STUDY RESULTS: Our method excelled in the classification task, achieving 83.32% accuracy, 83.41% sensitivity, and 83.20% specificity in 10-fold cross-validation, surpassing traditional methods. And our multimodal approach outperformed unimodal methods. Grad-CAM identified potential brain biomarkers consistent with gene analysis and prior research. CONCLUSIONS: Our study demonstrates the effectiveness of deep learning with graph attention networks, surpassing previous SZ diagnostic methods. Multimodal MRI's superiority over unimodal MRI confirms our initial hypothesis. Identifying potential brain biomarkers alongside gene biomarkers holds promise for advancing objective SZ diagnosis and research in SZ.

Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions.

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

A Fast Feedforward Small-World Neural Network for Nonlinear System Modeling.

It is well-documented that cross-layer connections in feedforward small-world neural networks (FSWNNs) enhance the efficient transmission for gradients, thus improving its generalization ability with a fast learning. However, the merits of long-distance cross-layer connections are not fully utilized due to the random rewiring. In this study, aiming to further improve the learning efficiency, a fast FSWNN (FFSWNN) is proposed by taking into account the positive effects of long-distance cross-layer connections, and applied to nonlinear system modeling. First, a novel rewiring rule by giving priority to long-distance cross-layer connections is proposed to increase the gradient transmission efficiency when constructing FFSWNN. Second, an improved ridge regression method is put forward to determine the initial weights with high activation for the sigmoidal neurons in FFSWNN. Finally, to further improve the learning efficiency, an asynchronous learning algorithm is designed to train FFSWNN, with the weights connected to the output layer updated by the ridge regression method and other weights by the gradient descent method. Several experiments are conducted on four benchmark datasets from the University of California Irvine (UCI) machine learning repository and two datasets from real-life problems to evaluate the performance of FFSWNN on nonlinear system modeling. The results show that FFSWNN has significantly faster convergence speed and higher modeling accuracy than the comparative models, and the positive effects of the novel rewiring rule, the improved weight initialization, and the asynchronous learning algorithm on learning efficiency are demonstrated.

Acupuncture as Add-on Therapy to SSRIs Can Improve Outcomes of Treatment for Anxious Depression: Subgroup Analysis of the AcuSDep Trial.

Purpose: Anxious depression (AD) is a common, distinct depression subtype. This exploratory subgroup analysis aimed to explore the effects of acupuncture as an add-on therapy of selective serotonin reuptake inhibitors (SSRIs) for patients with AD or non-anxious depression (NAD). Patients and Methods: Four hundred and sixty-five patients with moderate-to-severe depression from the AcuSDep pragmatic trial were included in analysis. Patients were randomly assigned to receive MA+SSRIs, EA+SSRIs, or SSRIs alone (1:1:1) for six weeks. AD was defined by using dimensional criteria. The measurement instruments included 17-items Hamilton Depression Scale (HAMD-17), Self-Rating Depression Scale (SDS), Clinical Global Impression (CGI), Rating Scale for Side Effects (SERS), and WHO Quality of Life-BREF (WHOQOL-BREF). Comparison between AD and NAD subgroups and comparisons between groups within either AD or NAD subgroups were conducted. Results: Eighty percent of the patients met the criteria for AD. The AD subgroup had poorer clinical manifestations and treatment outcomes compared to those of the NAD subgroup. For AD patients, the HAMD response rate, remission rate, early onset rate, and the score changes on each scale at most measurement points on the two acupuncture groups were significantly better than the SSRIs group. For NAD patients, the HAMD early onset rates of the two acupuncture groups were significantly better than the SSRIs group. Conclusion: For AD subtype patients, either MA or EA add-on SSRIs showed comprehensive improvements, with small-to-medium effect sizes. For NAD subtype patients, both the add-on acupuncture could accelerate the response to SSRIs treatment. The study contributed to the existing literature by providing insights into the potential benefits of acupuncture in combination with SSRIs, especially for patients with AD subtypes. Due to its limited nature as a post hoc subgroup analysis, prospectively designed, high-quality trials are warranted. Clinical Trials Registration: ChiCTR-TRC-08000297.

Extracellular vesicles containing MFGE8 from colorectal cancer facilitate macrophage efferocytosis.

BACKGROUND: Colorectal cancer (CRC) commonly exhibits tolerance to cisplatin treatment, but the underlying mechanisms remain unclear. Within the tumor microenvironment, macrophages play a role in resisting the cytotoxic effects of chemotherapy by engaging in efferocytosis to clear apoptotic cells induced by chemotherapeutic agents. The involvement of extracellular vesicles (EVs), an intercellular communicator within the tumor microenvironment, in regulating the efferocytosis for the promotion of drug resistance has not been thoroughly investigated. METHODS: We constructed GFP fluorescent-expressing CRC cell lines (including GFP-CT26 and GFP-MC38) to detect macrophage efferocytosis through flow cytometric analysis. We isolated and purified CRC-secreted EVs using a multi-step ultracentrifugation method and identified them through electron microscopy and nanoflow cytometry. Proteomic analysis was conducted to identify the protein molecules carried by CRC-EVs. MFGE8 knockout CRC cell lines were constructed using CRISPR-Cas9, and their effects were validated through in vitro and in vivo experiments using Western blotting, immunofluorescence, and flow cytometric analysis, confirming that these EVs activate the macrophage αvß3-Src-FAK-STAT3 signaling pathway, thereby promoting efferocytosis. RESULTS: In this study, we found that CRC-derived EVs (CRC-EVs) enhanced macrophage efferocytosis of cisplatin-induced apoptotic CRC cells. Analysis of The Cancer Genome Atlas (TCGA) database revealed a high expression of the efferocytosis-associated gene MFGE8 in CRC patients, suggesting a poorer prognosis. Additionally, mass spectrometry-based proteomic analysis identified a high abundance of MFGE8 protein in CRC-EVs. Utilizing CRISPR-Cas9 gene edition system, we generated MFGE8-knockout CRC cells, demonstrating that their EVs fail to upregulate macrophage efferocytosis in vitro and in vivo. Furthermore, we demonstrated that MFGE8 in CRC-EVs stimulated macrophage efferocytosis by increasing the expression of αvß3 on the cell surface, thereby activating the intracellular Src-FAK-STAT3 signaling pathway. CONCLUSIONS: Therefore, this study highlighted a mechanism in CRC-EVs carrying MFGE8 activated the macrophage efferocytosis. This activation promoted the clearance of cisplatin-induced apoptotic CRC cells, contributing to CRC resistance against cisplatin. These findings provide novel insights into the potential synergistic application of chemotherapy drugs, EVs inhibitors, and efferocytosis antagonists for CRC treatment.

Health-related quality-of-life analysis from KEYNOTE-590: pembrolizumab plus chemotherapy versus chemotherapy for advanced esophageal cancer.

BACKGROUND: In the KEYNOTE-590 study, first-line pembrolizumab plus chemotherapy provided statistically significant improvement in overall survival, progression-free survival, and objective response rate compared with chemotherapy, with a manageable safety profile in patients with advanced esophageal cancer. Prespecified health-related quality-of-life (HRQoL) outcomes are reported. MATERIALS AND METHODS: Change from baseline to week 18 in the EORTC Quality of Life Questionnaire Core 30 (QLQ-C30) global health status/QoL (GHS/QoL) and QLQ-Esophageal cancer module (OES18) dysphagia, pain, and reflux scales were evaluated. RESULTS: The HRQoL analysis included 730 patients who received treatment and completed ≥1 HRQoL assessment. Least squares mean (LSM) change from baseline to week 18 was similar between treatment groups for QLQ-C30 GHS/QoL and physical functioning and QLQ-OES18 reflux scales. The QLQ-OES18 dysphagia (LSM difference, -5.54; 95% CI, -10.93 to -0.16) and pain (LSM difference, -2.94; 95% CI, -5.86 to -0.02) scales favored pembrolizumab plus chemotherapy over placebo plus chemotherapy. Median time to confirmed deterioration (TTD) was similar between treatment groups for QLQ-C30 GHS/QoL and physical functioning and QLQ-OES18 dysphagia and reflux scales. Compared with chemotherapy, pembrolizumab plus chemotherapy prolonged median TTD, as seen on the QLQ-OES18 pain scale (HR, 0.69; 95% CI, 0.51 to 0.95). CONCLUSION: The use of pembrolizumab plus chemotherapy maintained HRQoL at week 18 relative to baseline and was comparable with placebo plus chemotherapy. These HRQoL results together with published reports of efficacy, support the use of pembrolizumab plus chemotherapy as first-line therapy for advanced/metastatic esophageal cancer. CLINICALTRIALS.GOV ID: NCT03189719.

Genome resources for three modern cotton lines guide future breeding efforts.

Cotton (Gossypium hirsutum L.) is the key renewable fibre crop worldwide, yet its yield and fibre quality show high variability due to genotype-specific traits and complex interactions among cultivars, management practices and environmental factors. Modern breeding practices may limit future yield gains due to a narrow founding gene pool. Precision breeding and biotechnological approaches offer potential solutions, contingent on accurate cultivar-specific data. Here we address this need by generating high-quality reference genomes for three modern cotton cultivars ('UGA230', 'UA48' and 'CSX8308') and updating the 'TM-1' cotton genetic standard reference. Despite hypothesized genetic uniformity, considerable sequence and structural variation was observed among the four genomes, which overlap with ancient and ongoing genomic introgressions from 'Pima' cotton, gene regulatory mechanisms and phenotypic trait divergence. Differentially expressed genes across fibre development correlate with fibre production, potentially contributing to the distinctive fibre quality traits observed in modern cotton cultivars. These genomes and comparative analyses provide a valuable foundation for future genetic endeavours to enhance global cotton yield and sustainability.

Surface-Grafted Single-Atomic Pt-Nx Complex with a Precisely Regulating Coordination Sphere for Efficient Electron Acceptor-Inducing Interfacial Electron Transfer.

Based on the electron-withdrawing effect of the Pt(bpy)Cl2 molecule, a simple post-modification amide reaction was firstly used to graft it onto the surface of NH2-MIL-125, which formed a highly efficient electron acceptor that induced the conversion of the photoinduced charge migration pathway from internal BDC→TiOx migration to external BDC→PtNx migration, significantly improving the efficiency of photoinduced electron transfer and separation. Furthermore, precise control over the first coordination sphere of Pt single atoms was achieved using further post-modification with additional bipyridine to investigate the effect of Pt-Nx coordination numbers on reaction activity. The as-synthesized NML-PtN2 exhibited superior photocatalytic hydrogen evolution activity of 7.608 mmol g-1 h-1, a remarkable improvement of 225 and 2.26 times compared to pristine NH2-MIL-125 and NML-PtN4, respectively. In addition, the superior apparent quantum yield of 4.01% (390 nm) and turnover frequency of 190.3 h-1 (0.78 wt% Pt SA; 129 times compared to Pt nanoparticles/NML) revealed the high solar utilization efficiency and hydrogen evolution activity of the material. And macroscopic color changes caused by the transition of carrier migration paths was first observed. It holds profound significance for the design of MOF-Molecule catalysts with efficient charge carrier separation and precise regulation of single-atom coordination sphere.

Experimental investigation of brain contusion characteristics and dynamic response in low-age children using an animal model.

INTRODUCTION: Brain contusion is a prevalent traumatic brain injury (TBI) in low-age children, bearing the potential for coma and fatality. Hence, it is imperative to undertake comprehensive research in this field. METHODS: This study employed 4-week-old piglets as surrogates for children and introduced self-designed devices for both free-fall drop impact tests and drop-hammer impact tests. The study explored the characteristics of brain contusion and dynamic responses of brain under these distinct testing conditions. RESULTS: Brain contusions induced by free-fall and drop-hammer conditions both were categorized as the coup injury, except that slight difference in the contusion location was observed, with contusion occurring mainly in the surrounding regions beneath the impact location under free-fall condition and the region just right beneath the impact location under drop-hammer condition. Analysis of impact force and intracranial pressure (ICP) curves indicated similar trends in impact forces under both conditions, yet different trends in ICPs. Further examination of the peak impact forces and ICPs elucidated that, with increasing impact energy, the former followed a combined power and first-order polynomial function, while the latter adhered to a power function. The brain contusion was induced at the height (energy) of 2 m (17.2 J), but not at the heights of 0.4, 0.7, 1, 1.35 and 1.7 m, when the vertex of the piglet head collided with a rigid plate. In the case of a cylindrical rigid hammer (cross-sectional area constituting 40 % of the parietal bone) striking the head, the brain contusion was observed under the energy of 21.9 J, but not under energies of 8.1 J, 12.7 J and 20.3 J. Notably, the incidence of brain contusion was more pronounced under the free-fall condition. CONCLUSIONS: These findings not only facilitate a comprehensive understanding of brain contusion dynamics in pediatric TBIs, but also contribute to the validation of theories and finite element models for piglet heads, which are commonly employed as surrogates for children.

Impact of operative time on textbook outcome after minimally invasive esophagectomy, a risk-adjusted analysis from a high-volume center.

BACKGROUND: We aimed to study the impact of operative time on textbook outcome (TO), especially postoperative complications and length of postoperative stay in minimally invasive esophagectomy. METHODS: Patients undergoing esophagectomy for curative intent within a prospectively maintained database from 2016 to 2022 were retrieved. Relationships between operative time and outcomes were quantified using multivariable mixed-effects models with medical teams random effects. A restricted cubic spline (RCS) plotting was used to characterize correlation between operative time and the odds for achieving TO. RESULTS: Data of 2210 patients were examined. Median operative time was 270 mins (interquartile range, 233-313) for all cases. Overall, 902 patients (40.8%) achieved TO. Among non-TO patients, 226 patients (10.2%) had a major complication (grade ≥ III), 433 patients (19.6%) stayed postoperatively longer than 14 days. Multivariable analysis revealed operative time was associated with higher odds of major complications (odds ratio 1.005, P < 0.001) and prolonged postoperative stay (≥ 14 days) (odds ratio 1.003, P = 0.006). The relationship between operative time and TO exhibited an inverse-U shape, with 298 mins identified as the tipping point for the highest odds of achieving TO. CONCLUSIONS: Longer operative time displayed an adverse influence on postoperative morbidity and increased lengths of postoperative stay. In the present study, the TO displayed an inverse U-shaped correlation with operative time, with a significant peak at 298 mins. Potential factors contributing to prolonged operative time may potentiate targets for quality metrics and risk-adjustment process.

Tuning Thermal Conductivity of Hybrid Perovskites through Halide Alloying.

Tuning the thermal transport properties of hybrid halide perovskites is critical for their applications in optoelectronics, thermoelectrics, and photovoltaics. Here, an effective strategy is demonstrated to modulate the thermal transport property of hybrid perovskites by halide alloying. A highly tunable thermal conductivity of mixed-halide hybrid perovskites is achieved due to halide-alloying and structural distortion. The experimental measurements show that the room temperature thermal conductivity of MAPb(BrxI1- x)3 (x = 0─1) can be largely modulated from 0.27 ± 0.07 W m-1 K-1 (x = 0.5) to 0.47 ± 0.09 W m-1 K-1 (x = 1). Molecular dynamics simulations further demonstrate that the thermal conductivity reduction of hybrid halide perovskites results from the suppression of the mean free paths of the low-frequency acoustic and optical phonons. It is found that halide alloying and the induced structural distortion can largely increase the scatterings of optical and acoustic phonons, respectively. The confined diffusion of MA+ cations in the octahedra cage is found to act as an additional thermal transport channel in hybrid perovskites and can contribute around 10-20% of the total thermal conductivity. The findings provide a strategy for tailoring the thermal transport in hybrid halide perovskites, which may largely benefit their related applications.

Broadband Emission Induced by Band-Edge Carrier Reconfiguration in 2D Hybrid Lead Halide Perovskites.

Broadband emission in hybrid lead halide perovskites (LHPs) has gained significant attention due to its potential applications in optoelectronic devices. The origin of this broadband emission is primarily attributed to the interactions between electrons and phonons. Most investigations have focused on the impact of structural characteristics of LHPs on broadband emission, while neglecting the role of electronic mobility. In this work, the study investigates the electronic origins of broadband emission in a family of 2D LHPs. Through spectroscopic experiments and density functional theory calculations, the study unveils that the electronic states of the organic ligands with conjugate effect in LHPs can extend to the band edges. These band-edge carriers are no longer localized only within the inorganic layers, leading to electronic coupling with molecular states in the barrier and giving rise to additional interactions with phonon modes, thereby resulting in broadband emission. The high-pressure photoluminescence measurements and theoretical calculations reveal that hydrostatic pressure can induce the reconfiguration of band-edge states of charge carriers, leading to different types of band alignment and achieving macroscopic control of carrier dynamics. The findings can provide valuable guidance for targeted synthesis of LHPs with broadband emission and corresponding design of state-of-the-art optoelectronic devices.

MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants.

Massively parallel reporter assay (MPRA) is an important technology to evaluate the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server, for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs and various genomic features, resulting in a total of 242,818 variants tested across more than 30 cell lines and 30 human diseases or traits. MPRAVarDB empowers the query of MPRA variants by genomic region, disease and cell line or by any combination of these query terms. Notably, MPRAVarDB offers a suite of pretrained machine learning models tailored to the specific disease and cell line, facilitating the genome-wide prediction of regulatory variants. MPRAVarDB is friendly to use, and users only need a few clicks to receive query and prediction results.

Caregiver Experiences and Burden in Moderate-Advanced Dementia With Lewy Bodies.

Background and Objectives: Dementia with Lewy bodies (DLB) is a common degenerative dementia, but research on caregiver experiences in late stages is lacking. This study aimed to investigate the caregiving experience in moderate-advanced DLB to identify opportunities for improving care and support. Methods: Dyads of individuals with moderate-advanced DLB and their primary informal caregivers were recruited from specialty clinics, advocacy organizations, and research registries. The study collected demographics, disease-related measures, and measures of the caregiver experience relating to caregiver support, burden, grief, self-efficacy, depression, quality of life, and coping. Spearman correlation coefficients and Wilcoxon rank-sum tests evaluated the relationships of caregiver measures with patient and caregiver variables with adjustments for multiple testing. Results: Caregivers (n = 143) were mostly women (83.5%) and spouses (84.7%) (mean age 68 years; range 37-85). Almost 40% reported high burden and/or depression. Caregiver measures correlated with fluctuation and behavioral symptom severity, sleepiness, and autonomic symptoms of the person with DLB. Higher burden correlated with worse caregiver quality of life, higher depression, and grief. Greater self-efficacy, social support, and resilience correlated with lower caregiver burden. The most frequently reported caregiver concerns were being unable to plan for the future, having to put the needs of the person with DLB ahead of the caregiver's own needs, and worry that the person with DLB would become too dependent on the caregiver, but many additional concerns were endorsed. Caregivers were generally satisfied with medical team support. The lowest reported satisfaction related to information regarding disease progression and how well medical teams shared information with each other. Discussion: Various patient-related and caregiver-related factors influence caregiver experiences in moderate-advanced DLB. Clinicians can target caregiver needs by providing support resources and DLB education and treating bothersome patient symptoms. Future research should investigate what interventions can modify and improve caregiver experiences in advanced DLB and identify therapeutics for patient symptoms currently without adequate treatments (e.g., fluctuations, daytime sleepiness). Trial Registration Information: NCT04829656.

A new dressing system for accelerating wound recovery after primary total knee arthroplasty: a feasibility study.

PURPOSE: Currently, postoperative wound infection and poor healing of total knee arthroplasty have been perplexing both doctors and patients. We hereby innovatively invented a new dressing system to reduce the incidence of postoperative wound complications. METHODS: We enrolled 100 patients who received primary unilateral total knee arthroplasty and then applied the new dressing system. The data collected included the number of dressing changes, postoperative hospital stay, Visual Analogue Scale score (VAS), the Knee Society Score (KSS), the Knee Injury and Osteoarthritis Outcome Score (KOOS), ASEPSIS scores, The Stony Brook Scar Evaluation Scale (SBSES), wound complications, dressing cost, the frequency of shower and satisfaction. Subsequently, a statistical analysis of the data was performed. RESULTS: Our findings demonstrated the average number of postoperative dressing changes was 1.09 ± 0.38, and the average postoperative hospital stay was 3.72 ± 0.98 days. The average cost throughout a treatment cycle was 68.97 ± 12.54 US dollars. Collectively, the results of VAS, KSS, and KOOS revealed that the pain and function of patients were continuously improved. The results of the four indexes of the ASEPSIS score were 0, whereas the SBSES score was 3.58 ± 0.52 and 4.69 ± 0.46 at two weeks and one month after the operation, respectively. We observed no wound complications until one month after the operation. Remarkably, the satisfaction rate of the patients was 91.85 ± 4.99% one month after the operation. CONCLUSION: In this study, we invented a new dressing system for surgical wounds after total knee arthroplasty and further confirmed its clinical feasibility and safety. CHINESE CLINICAL TRIAL REGISTRY: ChiCTR2000033814, Registered 13/ June/2020.

Disruption of Ca2+/calmodulin:KSR1 interaction lowers ERK activation.

KSR1, a key scaffold protein for the MAPK pathway, facilitates ERK activation upon growth factor stimulation. We recently demonstrated that KSR1 binds the Ca2+-binding protein calmodulin (CaM), thereby providing an intersection between KSR1-mediated and Ca2+ signaling. In this study, we set out to generate a KSR1 point mutant with reduced Ca2+/CaM binding in order to unravel the functional implications of their interaction. To do so, we solved the structural determinants of complex formation. Using purified fragments of KSR1, we showed that Ca2+/CaM binds to the CA3 domain of KSR1. We then used in silico molecular modeling to predict contact residues for binding. This approach identified two possible modes of interaction: (1) binding of extended Ca2+/CaM to a globular conformation of KSR1-CA3 via electrostatic interactions or (2) binding of collapsed Ca2+/CaM to α-helical KSR1-CA3 via hydrophobic interactions. Experimentally, site-directed mutagenesis of the predicted contact residues for the two binding models favored that where collapsed Ca2+/CaM binds to the α-helical conformation of KSR1-CA3. Importantly, replacing KSR1-Phe355 with Asp reduces Ca2+/CaM binding by 76%. The KSR1-F355D mutation also significantly impairs the ability of EGF to activate ERK, which reveals that Ca2+/CaM binding promotes KSR1-mediated MAPK signaling. This work, by uncovering structural insight into the binding of KSR1 to Ca2+/CaM, identifies a KSR1 single-point mutant as a bioreagent to selectively study the crosstalk between Ca2+ and KSR1-mediated signaling.

BS-SCRM: a novel approach to secure wireless sensor networks via blockchain and swarm intelligence techniques.

In this paper, we present a novel Secure Clustering Routing Method based on Blockchain and Swarm Intelligence (BS-SCRM) for Wireless Sensor Networks (WSNs), which serves as a cornerstone in the Internet of Things (IoT) infrastructure. Recognizing the limitations of existing clustering routing methods in addressing security threats, our approach integrates blockchain technology to fortify WSNs against vulnerabilities such as man-in-the-middle attacks. The proposed BS-SCRM method is structured in two phases: (1) an enhanced cluster head (CH) election utilizing an elite strategy-enhanced Whale Optimization Algorithm (WOA) that considers node energy and proximity to the base station, and (2) a secure data on-chain phase where blockchain comes into play, encrypting and validating cluster data to safeguard integrity and prevent tampering. We further tackle the challenge of implementing blockchain in resource-constrained WSNs by assigning distinct roles to devices, i.e., ordinary nodes with data viewing permissions and accounting nodes entrusted with both data viewing and consensus algorithm execution. Extensive simulations confirm that BS-SCRM not only improves clustering quality but also provides a more secure and energy-efficient routing solution compared to contemporary methods. More specifically, simulation results in different scenarios demonstrate that BS-SCRM enhances network lifetime by 24-73% compared to other clustering methods when facing attacks.