A portable solid sampling visualization nano-sensor for soil Cd based on "three-phase transforming" technique.

Direct analysis of solid samples is always challenging for ionic sensors due to solidified elemental presence and matrix interference. In this work, a "three-phase transforming" technique was first established to make solid sampling elemental sensors and visual detection possible in the future. For Cd transforming from soil samples, a metal ceramic heater (MCH) electrothermal vaporizer (ETV) coupled with a dielectric barrier discharge quartz trap (DBD-QT) was first utilized to fulfill the solid sampling and preconcentration of Cd in soil; for on-site analysis, a colorimetric sensor based on the trithiocyanuric acid (TMT) functionalized gold nanoparticles (AuNPs) was chosen as a chromogenic analysis model. The portable and miniature ETV-DBD apparatus directly introduced Cd from soil and then captured Cd, consuming only <130 W and 4.5 kg weight; finally, only 200 µL water was injected as eluent to dissolve Cd for the following colorimetric detection. Herein, the Cd analyte underwent a "three-phase transforming" from solid (Cd compounds in soil), to aerosol (vaporization and transportation), to solid (Cd oxides trapped on quartz surface) and to liquid (Cd2+ in eluate). Under optimized conditions, the method limit of detection (LOD) reached 0.04 mg/kg Cd (50 mg sample), fulfilling fast monitoring of Cd contamination in soil, with <20 % relative standard deviations (RSDs). The analysis time was <10 min excluding sample digestion and acid application, as well as the interference of Pb2+ on the AuNPs sensor can be eliminated via the "three-phase transforming" process, proving an excellent anti-interference for solid analysis. This "three-phase transforming" processing technique coupled with colorimetric sensor holds a great potential for direct and on-site analysis in solid samples without complicated handling, providing a fantastic methodology for the application of ionic sensors and making solid sampling elemental sensor and visual detection possible.

Individual differences of white matter characteristic along the anterior insula-based fiber tract circuit for pain empathy in healthy women and women with primary dysmenorrhea.

Pain empathy, defined as the ability of one person to understand another person's pain, shows large individual variations. The anterior insula is the core region of the pain empathy network. However, the relationship between white matter (WM) properties of the fiber tracts connecting the anterior insula with other cortical regions and an individual's ability to modulate pain empathy remains largely unclear. In this study, we outline an automatic seed-based fiber streamline (sFS) analysis method and multivariate pattern analysis (MVPA) to predict the levels of pain empathy in healthy women and women with primary dysmenorrhoea (PDM). Using the sFS method, the anterior insula-based fiber tract network was divided into five fiber cluster groups. In healthy women, interindividual differences in pain empathy were predicted only by the WM properties of the five fiber cluster groups, suggesting that interindividual differences in pain empathy may rely on the connectivity of the anterior insula-based fiber tract network. In women with PDM, pain empathy could be predicted by a single cluster group. The mean WM properties along the anterior insular-rostroventral area of the inferior parietal lobule further mediated the effect of pain on empathy in patients with PDM. Our results suggest that chronic periodic pain may lead to maladaptive plastic changes, which could further impair empathy by making women with PDM feel more pain when they see other people experiencing pain. Our study also addresses an important gap in the analysis of the microstructural characteristics of seed-based fiber tract network.

Graph Fourier transform for spatial omics representation and analyses of complex organs.

Spatial omics technologies are capable of deciphering detailed components of complex organs or tissue in cellular and subcellular resolution. A robust, interpretable, and unbiased representation method for spatial omics is necessary to illuminate novel investigations into biological functions, whereas a mathematical theory deficiency still exists. We present SpaGFT (Spatial Graph Fourier Transform), which provides a unique analytical feature representation of spatial omics data and elucidates molecular signatures linked to critical biological processes within tissues and cells. It outperformed existing tools in spatially variable gene prediction and gene expression imputation across human/mouse Visium data. Integrating SpaGFT representation into existing machine learning frameworks can enhance up to 40% accuracy of spatial domain identification, cell type annotation, cell-to-spot alignment, and subcellular hallmark inference. SpaGFT identified immunological regions for B cell maturation in human lymph node Visium data, characterized secondary follicle variations from in-house human tonsil CODEX data, and detected extremely rare subcellular organelles such as Cajal body and Set1/COMPASS. This new method lays the groundwork for a new theoretical model in explainable AI, advancing our understanding of tissue organization and function.

Relationship between individual differences in pain empathy and task- and resting-state EEG.

Pain empathy is a complex form of psychological inference that enables us to understand how others feel in the context of pain. Since pain empathy may be grounded in our own pain experiences, it exhibits huge inter-individual variability. However, the neural mechanisms behind the individual differences in pain empathy and its association with pain perception are still poorly understood. In this study, we aimed to characterize brain mechanisms associated with individual differences in pain empathy in adult participants (n = 24). The 32-channel electroencephalography (EEG) was recorded at rest and during a pain empathy task, and participants viewed static visual stimuli of the limbs submitted to painful and nonpainful stimulation to solicit empathy. The pain sensitivity of each participant was measured using a series of direct current stimulations. In our results, the N2 of Fz and the LPP of P3 and P4 were affected by painful pictures. We found that both delta and alpha bands in the frontal and parietal cortex were involved in the regulation of pain empathy. For the delta band, a close relationship was found between average power, either in the resting or task state, and individual differences in pain empathy. It suggested that the spectral power in Fz's delta band may reflect subjective pain empathy across individuals. For the alpha band, the functional connectivity between Fz and P3 under painful picture stimulation was correlated to individuals' pain sensitivity. It indicated that the alpha band may reflect individual differences in pain sensitivity and be involved in pain empathy processing. Our results suggested the distinct role of the delta and alpha bands of EEG signals in pain empathy processing and may deepen our understanding of the neural mechanisms underpinning pain empathy.

Preoperative prediction of lymphovascular space invasion in endometrioid adenocarcinoma: an MRI-based radiomics nomogram with consideration of the peritumoral region.

BACKGROUND: Lymphovascular space invasion (LVSI) of endometrial cancer (EC) is a postoperative histological index, which is associated with lymph node metastases. A preoperative acknowledgement of LVSI status might aid in treatment decision-making. PURPOSE: To explore the utility of multiparameter magnetic resonance imaging (MRI) and radiomic features obtained from intratumoral and peritumoral regions for predicting LVSI in endometrioid adenocarcinoma (EEA). MATERIAL AND METHODS: A total of 334 EEA tumors were retrospectively analyzed. Axial T2-weighted (T2W) imaging and apparent diffusion coefficient (ADC) mapping were conducted. Intratumoral and peritumoral regions were manually annotated as the volumes of interest (VOIs). A support vector machine was applied to train the prediction models. Multivariate logistic regression analysis was used to develop a nomogram based on clinical and tumor morphological parameters and the radiomics score (RadScore). The predictive performance of the nomogram was assessed by the area under the receiver operator characteristic curve (AUC) in the training and validation cohorts. RESULTS: Among the features obtained from different imaging modalities (T2W imaging and ADC mapping) and VOIs, the RadScore had the best performance in predicting LVSI classification (AUCtrain = 0.919, and AUCvalidation = 0.902). The nomogram based on age, CA125, maximum anteroposterior tumor diameter on sagittal T2W images, tumor area ratio, and RadScore was established to predict LVSI had AUC values in the training and validation cohorts of 0.962 (sensitivity 94.0%, specificity 86.0%) and 0.965 (sensitivity 90.0%, specificity 85.3%), respectively. CONCLUSION: The intratumoral and peritumoral imaging features were complementary, and the MRI-based radiomics nomogram might serve as a non-invasive biomarker to preoperatively predict LVSI in patients with EEA.

Evaluation of a Clustering Approach to Define Distinct Subgroups of Patients With Migraine to Select Electroacupuncture Treatments.

BACKGROUND AND OBJECTIVES: The objective of this study was to propose a clustering approach to identify migraine subgroups and test the clinical usefulness of the approach by providing prognostic information for electroacupuncture treatment selection. METHODS: Participants with migraine without aura (MWoA) were asked to complete a daily headache diary, self-rating depression and anxiety, and quality-of-life questionnaires. Whole-brain functional connectivities (FCs) were assessed on resting-state functional MRI (fMRI). By integrating clinical measurements and fMRI data, partial least squares correlation and hierarchical clustering analysis were used to cluster participants with MWoA. Multivariate pattern analysis was applied to validate the proposed subgrouping strategy. Some participants had an 8-week electroacupuncture treatment, and the response rate was compared between different MWoA subgroups. RESULTS: In study 1, a total of 97 participants (age of 28.2 ± 1.0 years, 70 female participants) with MWoA and 77 healthy controls (HCs) (age of 26.8 ± 0.1 years, 61 female participants) were enrolled (dataset 1), and 2 MWoA subgroups were defined. The participants in subgroup 1 had a significantly lower headache frequency (times/month of 4.4 ± 1.1) and significantly higher self-ratings of depression (depression score of 49.5 ± 2.3) when compared with participants in subgroup 2 (times/month of 7.0 ± 0.6 and depression score of 43.4 ± 1.2). The between-group differences of FCs were predominantly related to the amygdala, thalamus, hippocampus, and parahippocampal area. In study 2, 33 participants with MWoA (age of 30.9 ± 2.0 years, 28 female participants) and 23 HCs (age of 29.8 ± 1.1 years, 13 female participants) were enrolled as an independent dataset (dataset 2). The classification analysis validated the effectiveness of the 2-cluster solution of participants with MWoA in datasets 1 and 2. In study 3, 58 participants with MWoA were willing to receive electroacupuncture treatment and were assigned to different subgroups. Participants in different subgroups exhibited different response rates (p = 0.03, OR CI 0.086-0.93) to electroacupuncture treatment (18% and 44% for subgroups 1 and 2, respectively). DISCUSSION: Our study proposed a novel clustering approach to define distinct MWoA subgroups, which could be useful for refining the diagnosis of participants with MWoA and guiding individualized strategies for pain prophylaxis and analgesia.

Rapid and Portable Detection of Hg and Cd in Grain Samples Based on Novel Catalytic Pyrolysis Composite Trap Coupled with Miniature Atomic Absorption Spectrometry.

As toxic metals, Hg and Cd are a concern for food safety and human health; their rapid and portable analysis is still a challenge. A portable and rapid Hg-Cd analyzer constructed from a metal-ceramic heater (MCH)-based electrothermal vaporizer (ETV), an on-line catalytic pyrolysis furnace (CPF), a composite Pt/Ni trap, and a homemade miniature atomic absorption spectrometer (AAS) was proposed for grain analysis in this work. To enhance sensitivity, a new folded light path was designed for simultaneous Hg and Cd analysis using charge coupled device (CCD) in AAS. To eliminate the grain matrix interference, a catalytic pyrolysis furnace with aluminum oxide fillers was utilized to couple with a composite Pt/Ni trap. The method limits of detection (LODs) were 1.1 µg/kg and 0.3 µg/kg for Hg and Cd using a 20 mg grain sample, fulfilling the real sample analysis to monitor the grain contamination quickly; linearity R2 > 0.995 was reached only using standard solution calibration, indicating the sample was free of grain matrix interference. The favorable analytical accuracy and precision were validated by analyzing real and certified reference material (CRM) grains with recoveries of 97-103% and 96-111% for Hg and Cd, respectively. The total analysis time was less than 5 min without sample digestion or use of any chemicals, and the instrumental size and power consumption were <14 kg and 270 W, respectively. Compared with other rapid methods, this newly designed Hg-Cd analyzer is proven to be simple, portable, and robust and is, thus, suitable to quickly monitor Hg and Cd contamination in the field to protect grain and food safety.

Progress in Bioengineering of Myotropic Adeno-Associated Viral Gene Therapy Vectors.

The ability to specifically, safely, and efficiently transfer therapeutic payloads to the striated musculature via a minimally invasive delivery route remains one of the most important but also most ambitious aims in human gene therapy. Over the past two decades, a flurry of groups have harnessed recombinant adeno-associated viruses (AAVs) for this purpose, carrying cargoes that were packaged either in one of the various wild-type capsids or in a synthetic protein shell derived by molecular bioengineering. In this study, we provide an overview over the most commonly used techniques for the enrichment of muscle-specific (myotropic) AAV capsids, typically starting off with the genetic diversification of one or more extant wild-type sequences, followed by the stratification of the ensuing capsid libraries in different muscle types in small or large animals. These techniques include the shuffling of multiple parental capsid genes, peptide display in exposed capsid loops, mutagenesis of individual capsid residues, creation of chimeras between two viral parents, or combinations thereof. Moreover, we highlight alternative experimental or bioinformatic strategies such as ancestral reconstruction or rational design, all of which have already been employed successfully to derive synthetic AAV capsids or vectors with unprecedented in vivo efficiency and/or specificity in the musculature. Most recently, these efforts have culminated in the isolation of unique clades of myotropic vectors called AAVMYO or MyoAAV that have in common the display of the amino acid motif RGD (arginine-glycine-aspartate) on the capsid surface and that exhibit the highest transduction rate in striated muscles of mice or nonhuman primates reported to date. Finally, we note essential looming improvements that will facilitate and accelerate clinical translation of these latest generations of myotropic AAVs, including the identification and utilization of capsid selection or validation schemes that promise optimal translation in humans, and continued efforts to enhance patient safety by minimizing hepatic off-targeting.

CsHscB Derived from a Liver Fluke Clonorchis Sinensis Ameliorates Cholestatic Hepatic Fibrosis in a Mouse Model of Sclerosing Cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by inflammatory fibrosis usually involving the whole biliary tree. However, there are very limited treatment options to treat this disease. Our previous study found a lipid-protein rCsHscB from a liver fluke - Clonorchis sinensis, which had full capacities of immune regulation. Therefore, we investigated the role of rCsHscB in a mouse model of sclerosing cholangitis induced by xenobiotic 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) to explore whether this protein had potential therapeutic value for PSC. METHODS: Mice were fed 0.1% DDC for 4 weeks and treated with CsHscB (30 µg/mouse, intraperitoneal injection, once every 3 days); the control group was given an equal amount of PBS or CsHscB under normal diet conditions. All the mice were sacrificed at 4 weeks for the evaluation of biliary proliferation, fibrosis, and inflammation. RESULTS: rCsHscB treatment attenuated DDC-induced liver congestion and enlargement and significantly decreased the upregulation of serum AST and ALT levels. The administration of rCsHscB to DDC-fed mice significantly decreased cholangiocyte proliferation and pro-inflammatory cytokine production compared to mice fed with DDC alone. Also, rCsHscB treatment showed a decreased expression of α-SMA in the liver and other markers of liver fibrosis (Masson staining, Hydroxyproline content, and collagen deposit). More interestingly, DDC-fed mice treated with rCsHscB showed a significant up-regulation of PPAR-γ expression, which was similar to control mice, indicating the involvement of PPAR-γ signaling in the protective action of rCsHscB. CONCLUSION: Overall, our data show that rCsHscB attenuates the progression of cholestatic fibrosis induced by DDC and supports the potential for manipulating the parasite-derived molecule to treat certain immune-mediated disorders.

Rapid detection of ultratrace urinary arsenic by direct sampling microplasma vaporization based on silicon nitride.

At present, immediate monitoring urinary arsenic is still a challenge for treating arsenic poisoning patients. Thus, a fast, reliable and accurate analytical approach is indispensable to monitor ultratrace arsenic in urine sample for health warning. In this work, a silicon nitride (SN) rod was first integrally utilized as a sample carrier for ≤50 µL urinary aliquot, an electric heater for removing water and ashing sample as well as a high voltage electrode for dielectric barrier discharge vaporization (DBDV). The direct analytical method of arsenic in urine without sample digestion was thus developed using atomic fluorescence spectrometer (AFS) as a model detector. After 4 V electrically heating the SN rod for 60 s, urine sample was dehydrated and ashed outside; then, DBD was exerted under 0.8 A with 0.8 L/min H2 + Ar (1:9, v:v) for 20 s to vaporize arsenic analyte from the SN rod. After optimization, 0.014 µg/L arsenic detection limit (LOD) was reached with favorable analytical precision (RSD <5%) and accuracy (91-110% recoveries) for real sample analysis. As a result, the whole analysis process only consumes <3 min to exclude complicated sample preparation; furthermore, the designed DBDV system only occupies 25 W and <2 kg, which renders a miniature sampling component to hyphenate with a miniature detector to detect arsenic. Thus, this direct sampling DBDV method extremely fulfills the fast, sensitive and precise detection of ultratrace arsenic in urine sample.

Effects on resting-state EEG phase-amplitude coupling in insomnia disorder patients following 1 Hz left dorsolateral prefrontal cortex rTMS.

Despite burgeoning evidence for cortical hyperarousal in insomnia disorder, the existing results on electroencephalography spectral features are highly heterogeneous. Phase-amplitude coupling, which refers to the modulation of the low-frequency phase to a high-frequency amplitude, is probably a more sensitive quantitative measure for characterizing abnormal neural oscillations and explaining the therapeutic effect of repetitive transcranial magnetic stimulation in the treatment of patients with insomnia disorder. Sixty insomnia disorder patients were randomly divided into the active and sham treatment groups to receive 4 weeks of repetitive transcranial magnetic stimulation treatment. Behavioral assessments, resting-state electroencephalography recordings, and sleep polysomnography recordings were performed before and after repetitive transcranial magnetic stimulation treatment. Forty good sleeper controls underwent the same assessment. We demonstrated that phase-amplitude coupling values in the frontal and temporal lobes were weaker in Insomnia disorder patients than in those with good sleeper controls at baseline and that phase-amplitude coupling values near the intervention area were significantly enhanced after active repetitive transcranial magnetic stimulation treatment. Furthermore, the enhancement of phase-amplitude coupling values was significantly correlated with the improvement of sleep quality. This study revealed the potential of phase-amplitude coupling in assessing the severity of insomnia disorder and the efficacy of repetitive transcranial magnetic stimulation treatment, providing new insights on the abnormal physiological mechanisms and future treatments for insomnia disorder.

The potential of electroencephalography coherence to predict the outcome of repetitive transcranial magnetic stimulation in insomnia disorder.

BACKGROUND: It is unknown whether repetitive Transcranial Magnetic Stimulation (rTMS) could improve sleep quality by modulating electroencephalography (EEG) connectivity of insomnia disorder (ID) patients. Great heterogeneity had been found in the clinical outcomes of rTMS for ID. The study aimed to investigate the potential mechanisms of rTMS therapy for ID and develop models to predict clinical outcomes. METHODS: In Study 1, 50 ID patients were randomly divided into active and sham groups, and subjected to 20 sessions of treatment with 1 Hz rTMS over the left dorsolateral prefrontal cortex. EEG during awake, Polysomnography, and clinical assessment were collected and analyzed before and after rTMS. In Study 2, 120 ID patients were subjected to active rTMS stimulation and were then separated into optimal and sub-optimal groups due to the median of Pittsburgh Sleep Quality Index reduction rate. Machine learning models were developed based on baseline EEG coherence to predict rTMS treatment effects. RESULTS: In Study 1, decreased EEG coherence in theta and alpha bands were observed after rTMS treatment, and changes in theta band (F7-O1) coherence were correlated with changes in sleep efficiency. In Study 2, baseline EEG coherence in theta, alpha, and beta bands showed the potential to predict the treatment effects of rTMS for ID. CONCLUSION: rTMS improved sleep quality of ID patients by modulating the abnormal EEG coherence. Baseline EEG coherence between certain channels in theta, alpha, and beta bands could act as potential biomarkers to predict the therapeutic effects.

Novel Platinum-Nickel Composite Trap for Simultaneous and Direct Determination of Mercury and Cadmium in Soil and Its Mechanism Study.

In this work, following a metal-ceramic heater (MCH) as an electrothermal vaporizer (ETV), a novel composite Pt/Ni trap based on platinizing the foamed nickel was first fabricated to trap Hg and Cd simultaneously. So, a solid sampling Hg-Cd analyzer was developed to simultaneously detect trace Hg and Cd in soil samples, mainly consisting of an MCH, a composite Pt/Ni trap, and an atomic fluorescence spectrometer (AFS). This small-size MCH-ETV system only consumes 100 W for the complete vaporization of Hg and Cd in soil matrices. The Pt/Ni trap fulfills the complete trapping of Hg and Cd following the solid sampling MCH-ETV system and then fast releases them by heating. It was proved that trapped and released Hg and Cd by the Pt/Ni trap are atomic species using X-ray photoelectron spectroscopy (XPS) and other approaches; specially, the effective cotrapping of Hg and Cd might be due to forming alloys of Hg + Pt and Cd + Ni on the Pt/Ni trap. Under the optimized conditions, the method detection limits (LODs) of Hg and Cd reached 0.4 µg/kg and 0.04 µg/kg for a 20 mg sample size, the relative standard deviations (RSDs) were within 12% and 8% for soil samples, respectively, and the recoveries ranged from 96% to 105%, indicating favorable analytical sensitivity, precision, and accuracy. The whole analysis time can be controlled within 5 min without the soil digestion process. The proposed Hg-Cd analyzer is thus suitable for rapid detection of Hg and Cd in soil samples with advantages such as simplicity, green, and safety. Further, the proposed solid sampling ETV-composite trap method has a promising application potential in the field and rapid detection for multielements.

Brain recovery of the NAc fibers and prediction of craving changes in person with heroin addiction: A longitudinal study.

BACKGROUND: Progress have been made in brain function recovery after long-term abstinence in person with heroin addiction (PHA). However, less is known about whether the nucleus accumbens (NAc) white matter pathways can recover in PHA by prolonged abstinence. METHODS: Forty-two PHA and Thirty-nine age- and gender- matched healthy controls (HCs) were recruited. Two MRI scans were obtained at baseline (PHA1) and 8-month follow-up (PHA2). We employed tractography atlas-based analysis (TABS) method to investigate fractional anisotropy (FA) changes in NAc fiber tracts (i.e., Insula-NAc, ventral tegmental area (VTA)-NAc, medial prefrontal cortex (MPFC)-NAc) in PHA. A partial least square regression (PLSR) analysis was carried to explore whether FA of NAc fiber tracts can predict longitudinal craving changes. RESULTS: Relative to HCs, lower FA was found in the right Insula-NAc and VTA-NAc fiber tracts in PHA1, and PHA2 showed increased FA values in these tracts compared with PHA1. Furthermore, changes of FA of NAc fiber tracts can predict longitudinal craving changes (r = 0.51). Additionally, craving changes can also be predicted from FA changes in the left Insula-NAc (r = 0.601) and VTA-NAc (r = 0.384) fiber alone. CONCLUSIONS: Results indicated that the right Insula-NAc and VTA-NAc fiber tracts are potential biomarkers for brain recovery. Prediction of craving changes highlighted the utility of structural markers to inform clinical decision-making of treatment for PHA.

Reversal of neurovascular decoupling and cognitive impairment in patients with end-stage renal disease during a hemodialysis session: Evidence from a comprehensive fMRI analysis.

Neurovascular (NV) decoupling is a potential neuropathologic mechanism of cognitive impairment in patients with end-stage renal disease (ESRD). Hemodialysis improves cognitive impairment at 24 h post-dialysis, which suggests a potential neuroprotective effect of hemodialysis treatment on the brain. We investigated the effects of hemodialysis treatment on the reversal of NV decoupling associated with cognitive improvement. A total of 39 patients with ESRD and 39 healthy controls were enrolled. All patients were imaged twice during a dialysis session: before hemodialysis (T1pre-dialysis ) and at 24 h after dialysis (T2post-dialysis ). The healthy controls were imaged once. NV coupling was characterized based on correlation coefficients between four types of blood oxygen level-dependent signals and cerebral blood flow (CBF). A battery of neuropsychological and blood tests was performed before the imaging. Patients with ESRD showed improvements in memory and executive function at T2post-dialysis compared with that at T1pre-dialysis . At both T1pre-dialysis and T2post-dialysis , patients with ESRD had lower amplitude of low-frequency fluctuation (ALFF)-CBF coupling than healthy controls. Additionally, patients with ESRD had higher ALFF-CBF coupling at T2post-dialysis than at T1pre-dialysis . Higher memory scores, higher hemoglobin level, lower total plasma homocysteine level, lower systolic blood pressure variance, and lower ultrafiltration volume were associated with higher ALFF-CBF coupling in patients with ESRD after a hemodialysis session. These findings indicate that partial correction of anemia and hyperhomocysteinemia, stable systolic blood pressure, and fluid restriction may be closely linked to the reversal of NV decoupling and improvement in cognition in patients with ESRD.

Clinical study of the combined use of dexmedetomidine and remifentanil in patients with coronary heart disease undergoing 3D laparoscopic surgery with EEG bispectral index monitoring.

OBJECTIVE: This study sought to investigate the safety and clinical outcomes associated with the combined administration of dexmedetomidine (Dex) and remifentanil (Rem) in patients with coronary heart disease undergoing three-dimensional (3D) laparoscopic surgery, with concurrent monitoring of the electroencephalography (EEG) bispectral index. METHODS: This study is of a retrospective nature and involved a total of 60 patients with coronary heart disease who underwent 3D laparoscopic surgery at our hospital between June 2020 and September 2021. In a double-blind manner, these patients were randomly assigned to two groups: the control group (Group I), which consisted of 30 patients, and the treatment group (Group II) receiving a combination of Dex and Rem, also comprising 30 patients. The study's primary objective was to compare and assess the treatment outcomes in these two patient groups. RESULTS: Patients in Group II who developed postoperative coronary heart disease experienced a significant reduction in blood pressure, heart rate, and electrocardiogram values (P<0.05). Additionally, Group II exhibited lower bispectral index (BIS) and visual analog scale (VAS) values (P<0.05). CONCLUSION: In patients with coronary heart disease undergoing 3D laparoscopic surgery, the intraoperative use of Dex combined with Rem anesthesia offers several advantages. It helps stabilize hemodynamics, reducing the risk of myocardial ischemia, and significantly alleviates postoperative pain, all without increasing the likelihood of adverse postoperative reactions. Furthermore, this approach effectively dampens the intraoperative and postoperative stress response, facilitating enhanced recovery after surgery (ERAS). Overall, the clinical impact is positive, safe, and reliable.

Research on UAV Swarm Network Modeling and Resilience Assessment Methods.

The traditional UAV swarm assessment indicator lacks the whole process description of the performance change after the system is attacked. To meet the realistic demand of increasing resilience requirements for UAV swarm systems, in this paper, we study the modeling and resilience assessment methods of UAV swarm self-organized networks. First, based on complex network theory, a double layer coupled UAV swarm network model considering the communication layer and the structure layer is constructed. Then, three network topological indicators, namely, the average node degree, the average clustering factor, and the average network efficiency, are used to characterize the UAV swarm resilience indicators. Finally, the UAV swarm resilience assessment method, considering dynamic evolution, is designed to realize the resilience assessment of the UAV swarm under different strategies in multiple scenarios. The simulation experiments show that the UAV swarm resilience assessment, considering dynamic reconfiguration, has a strong correlation with the network structure design.

Reconfigurations of Dynamic Functional Network Connectivity in Large-scale Brain Network after Prolonged Abstinence in Heroin Users.

BACKGROUND: Brain recovery phenomenon after long-term abstinence had been reported in substance use disorders. Yet, few longitudinal studies have been conducted to observe the abnormal dynamic functional connectivity (dFNC) of large-scale brain networks and recovery after prolonged abstinence in heroin users. OBJECTIVE: The current study will explore the brain network dynamic connection reconfigurations after prolonged abstinence in heroin users (HUs). METHODS: The 10-month longitudinal design was carried out for 40 HUs. The 40 healthy controls (HCs) were also enrolled. Group independent component analysis (GICA) and dFNC analysis were employed to detect the different dFNC patterns of addiction-related ICNs between HUs and HCs. The temporal properties and the graph-theoretical properties were calculated. Whether the abnormalities would be reconfigured in HUs after prolonged abstinence was then investigated. RESULTS: Based on eight functional networks extracted from GICA, four states were identified by the dFNC analysis. Lower mean dwell time and fraction rate in state4 were found for HUs, which were increased toward HCs after prolonged abstinence. In this state, HUs at baseline showed higher dFNC of RECN-aSN, aSN- aSN and dDMN-pSN, which decreased after protracted abstinence. A similar recovery phenomenon was found for the global efficiency and path length in abstinence HUs. Mean while, the abnormal dFNC strength was correlated with craving both at baseline and after abstinence. CONCLUSION: Our longitudinal study observed the large-scale brain network reconfiguration from the dynamic perspective in HUs after prolonged abstinence and improved the understanding of the neurobiology of prolonged abstinence in HUs.