Cancer screening in hospitalized ischemic stroke patients: a multicenter study focused on multiparametric analysis to improve management of occult cancers.

Background/aims: The reciprocal promotion of cancer and stroke occurs due to changes in shared risk factors, such as metabolic pathways and molecular targets, creating a "vicious cycle." Cancer plays a direct or indirect role in the pathogenesis of ischemic stroke (IS), along with the reactive medical approach used in the treatment and clinical management of IS patients, resulting in clinical challenges associated with occult cancer in these patients. The lack of reliable and simple tools hinders the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) approach. Therefore, we conducted a multicenter study that focused on multiparametric analysis to facilitate early diagnosis of occult cancer and personalized treatment for stroke associated with cancer. Methods: Admission routine clinical examination indicators of IS patients were retrospectively collated from the electronic medical records. The training dataset comprised 136 IS patients with concurrent cancer, matched at a 1:1 ratio with a control group. The risk of occult cancer in IS patients was assessed through logistic regression and five alternative machine-learning models. Subsequently, select the model with the highest predictive efficacy to create a nomogram, which is a quantitative tool for predicting diagnosis in clinical practice. Internal validation employed a ten-fold cross-validation, while external validation involved 239 IS patients from six centers. Validation encompassed receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and comparison with models from prior research. Results: The ultimate prediction model was based on logistic regression and incorporated the following variables: regions of ischemic lesions, multiple vascular territories, hypertension, D-dimer, fibrinogen (FIB), and hemoglobin (Hb). The area under the ROC curve (AUC) for the nomogram was 0.871 in the training dataset and 0.834 in the external test dataset. Both calibration curves and DCA underscored the nomogram's strong performance. Conclusions: The nomogram enables early occult cancer diagnosis in hospitalized IS patients and helps to accurately identify the cause of IS, while the promotion of IS stratification makes personalized treatment feasible. The online nomogram based on routine clinical examination indicators of IS patients offered a cost-effective platform for secondary care in the framework of PPPM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00354-8.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review.

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

Generative Listener EEG for Speech Emotion Recognition Using Generative Adversarial Networks with Compressed Sensing.

Currently, emotional features in speech emotion recognition are typically extracted from the speeches, However, recognition accuracy can be influenced by factors such as semantics, language, and cross-speech datasets. Achieving consistent emotional judgment with human listeners is a key challenge for AI to address. Electroencephalography (EEG) signals prove to be an effective means of capturing authentic and meaningful emotional information in humans. This positions EEG as a promising tool for detecting emotional cues conveyed in speech. In this study, we proposed a novel approach named CS-GAN that generates listener EEGs in response to a speaker's speech, specifically aimed at enhancing cross-subject emotion recognition. We utilized generative adversarial networks (GANs) to establish a mapping relationship between speech and EEGs to generate stimulus-induced EEGs. Furthermore, we integrated compressive sensing theory (CS) into the GAN-based EEG generation method, thereby enhancing the fidelity and diversity of the generated EEGs. The generated EEGs were then processed using a CNN-LSTM model to identify the emotional categories conveyed in the speech. By averaging these EEGs, we obtained the event-related potentials (ERPs) to improve the cross-subject capability of the method. The experimental results demonstrate that the generated EEGs by this method outperform real listener EEGs by 9.31% in cross-subject emotion recognition tasks. Furthermore, the ERPs show an improvement of 43.59%, providing evidence for the effectiveness of this method in cross-subject emotion recognition.

Clinicopathological features of kidney injury in patients receiving immune checkpoint inhibitors (ICPi) combined with anti-vascular endothelial growth factor (anti-VEGF) therapy.

BACKGROUND: Immune checkpoint inhibitor (ICPi) combined with anti-vascular endothelial growth factor (VEGF) therapy has increasingly become a promising strategy in various malignancies. However, the combination might be associated with increased risk of nephrotoxicity. METHODS: We retrospectively recruited patients who suffered kidney injury and received renal biopsy after anti-VEGF/ICPi mono- or combination therapy and divided them into three groups: anti-VEGF monotherapy, ICPi monotherapy and combination therapy. Clinical and histopathological features of three groups were analysed. All patients were followed-up for 3 months after biopsy, with or without glucocorticoid treatment, and renal outcome were compared. RESULTS: A total of 46 patients were enrolled. Eighteen patients received anti-VEGF monotherapy, 12 received ICPi monotherapy and 16 received combined treatment of anti-VEGF and ICPi. Proteinuria level of anti-VEGF group, ICPi group and combination group were 4.07±3.17 g/day, 0.60±0.61 g/day and 2.05±2.50 g/day, respectively (p=0.002). The peak serum creatinine level of combination group (1.75±0.77 mg/dL) was also in between ICPi group (2.79±0.90 mg/dL) and anti-VEGF group (1.34±0.60 mg/dL) (p<0.001). Multiple histopathological patterns involving glomerulus, tubulointerstitium and vessel existed in the majority of cases in combination group (68.8%). Renal complete and partial recovery rate of combination therapy were also in between monotherapy (57.1% vs 40.0% in anti-VEGF group, 100.0% in ICPi group, respectively). CONCLUSIONS: Kidney injury in patients treated with combination therapy of ICPi and anti-VEGF shows hybrid pathological patterns and intermediate clinical features compared with monotherapy. Cohorts with larger sample and better design, as well as basic research, are needed to elucidate the mechanism of 'protection' effect of combination anti-cancer therapy to renal function.

A case report on multiple acyl-CoA dehydrogenase deficiency with severe myopathy and osteoporosis.

A 35-year-old male patient presented fluctuating bilateral lower extremity weakness for 3 years. Physical examination showed grade 4 proximal muscle weakness in both lower extremities and grade 5 distal muscle weakness. Laboratory data revealed elevated creatine kinase, triglycerides, and cholesterol. Muscle pathology showed deposition of lipid droplet under the sarcolemma. Bone densitometry indicated severe osteoporosis. Next-generation sequencing revealed a pathogenic mutation in the ETFDH gene. The patient was diagnosed with late-onset multiple acyl-CoA dehydrogenase deficiency. After riboflavin treatment, symptoms of the patient were relieved, physical endurance was restored, and bone mineral density was improved.

Development and validation of a nomogram model for central venous access device-related thrombosis in hospitalized children.

This study aimed to develop and validate a nomogram model of central venous access device-related thrombosis (CRT) for hospitalized children. A total of 503 consecutive cases from a hospital in Changsha City, Hunan Province were stochastically classified into the training set and internal validation set at a ratio of 7:3, and 85 consecutive cases in two hospitals in Urumqi City, Xinjiang Uygur Autonomous Region were collected as an external validation set. Univariate analysis and multivariate analysis on CRT-related risk factors of hospitalized children were conducted, a logistic regression model was employed to establish the nomogram, and the discrimination, calibration, and decision curve analysis was performed to assess the proposed nomogram model. The nomogram model involved seven independent risk factors, including blind catheterization, abnormal liver function, central line-associated bloodstream infection, infection, number of catheter lines, leukemia, and bed rest > 72 h. The discrimination results showed that the area under the receiver operating characteristic curve of the training set, internal validation set, and external validation set was 0.74, 0.71, and 0.76 respectively, and the accuracy rates of the proposed nomogram model were 79%, 72%, and 71% in the training set, internal validation set, and external validation set. The calibration results also showed that the calibration curve had great fitness for each dataset. More importantly, the decision curve suggested that the proposed nomogram model had a prominent clinical significance. CONCLUSION: The nomogram model can be used as a risk assessment tool to reduce the missed diagnosis rate and the incidence of CRT in hospitalized children. WHAT IS KNOWN: • Central venous access device-related thrombosis is generally asymptomatic for hospitalized children, causing the missed diagnosis of central venous access device-related thrombosis easily. • No risk prediction nomogram model for central venous access device-related thrombosis in hospitalized children has been established. WHAT IS NEW: • A visual and personalized nomogram model was built by seven accessible variables (blind catheterization, abnormal liver function, central line-associated bloodstream infection, infection, number of catheter lines, leukemia, and bed rest > 72 h). • The model can effectively predict the risk of central venous access device-related thrombosis for hospitalized children.

Baicalin promotes antiviral IFNs production and alleviates type I IFN-induced neutrophil inflammation.

Type I and III interferons (IFNs) both serve as pivotal components of the host antiviral innate immune system. Although they exert similar antiviral effects, type I IFNs can also activate neutrophil inflammation, a function not born by type III IFNs. Baicalin, the main bioactive component of Scutellariae radix, has been shown to exert therapeutic effects on viral diseases due to its anti-viral, anti-inflammatory and immunomulatory activities. There is uncertainty, however, on the association between the antiviral effects of baicalin and the modulation of anti-viral IFNs production and the immunological effects of type I IFNs. Here, a Poly (I:C)-stimulated A549 cell line was established to mimic a viral infection model. Our results demonstrated that baicalin could elevate the expression of type I and III IFNs and their receptors in Poly (I:C)-stimulated A549 cells. Moreover, the potential regulation effects of baicalin for type I IFN-induced neutrophil inflammation was further explored. Results showed that baicalin diminished the production of the pro-inflammatory cytokines (IL-1ß, IL-6, IL-17 and TNF-α), ROS, and neutrophil extracellular traps and suppressed chemotaxis. Collectively, all these data indicated that baicalin had a dual role on IFNs production and effects: (1) Baicalin was able to elevate the expression of type I and III IFNs and their receptors, (2) and it alleviated type I IFN-mediated neutrophil inflammatory response. This meant that baicalin has the potential to act as an eximious immunomodulator, exerting antiviral effects and reducing inflammation.

Block Distributed Joint Temporal-Frequency-Phase Modulation for Steady-State Visual Evoked Potential Based Brain-Computer Interface With a Limited Number of Frequencies.

How to encode as many targets as possible with limited frequency resources is a grave problem that restricts the application of steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs). In the current study, we propose a novel block-distributed joint temporal-frequency-phase modulation method for a virtual speller based on SSVEP-based BCI. A 48-target speller keyboard array is virtually divided into eight blocks and each block contains six targets. The coding cycle consists of two sessions: in the first session, each block flashes at different frequencies while all the targets in the same block flicker at the same frequency; in the second session, all the targets in the same block flash at different frequencies. Using this method, 48 targets can be coded with only eight frequencies, which greatly reduces the frequency resources required, and average accuracies of 86.81  ± 9.41% and 91.36  ± 6.41% were obtained for both the offline and online experiments. This study provides a new coding approach for a large number of targets with a small number of frequencies, which can further expand the application potential of SSVEP-based BCI.

Theoretical study of the tuning role of ß-methylthio or ß-methylselenyl on the charge-transport properties of acenedithiophenes derivatives.

To date, the manipulation of intermolecular nonconjugation interactions in organic crystals is still a great challenge due to the complexity of weak intermolecular interactions. Here we designed molecules substituted by ß-methylselenyl on naphtho[1,2-b:5,6-b']dithiophene and anthra[2,3-b:6,7-b']dithiophene, respectively (anti-ß-MS-NDT, anti-ß-MS-ADT), which together with anti-ß-MS-BDT synthesized experimentally all exhibited 2D brickwork π-stacking. Moreover, their maximum molecular carrier mobilities reached 3.30 and 16.46 cm2 V-1 s-1. These results indicated that the substitution of ß-methylselenyl could be a strategy to directionally adjust the parent herringbone stacking into 2D brickwork π-stacking. Hirshfeld surface analysis and symmetry-adapted perturbation theory (SAPT) were used to investigate the nonconjugated interactions in the pitched π-stacking formed by the ß-methylthio-substituted acenedithiophene derivatives and the 2D brickwork π-stacking of the ß-methylselenyl-substituted ones; wherein, the steric hindrance caused by the introduction of the substituents promoted Csp2-Csp2⋯π interactions to replace Csp2-H⋯π to stabilize the face-to-face stacking. Moreover, by calculating the decomposition energy of the intermediate state model of the molecular stacking mode that may exist in the replacement conversion process, it was found that the energy of this intermediate state was larger than that of the actual ones, finally confirming the inevitability of the actual existence in this stacking. In addition, because of the reduction in intensity of the special vibration modes, it could be found that the ß-methylselenyl substitution showed better phonon assistance than ß-methylthio substitution in terms of dynamic disorder. This study is a further step toward fully understanding the relationship between intermolecular interactions and regulation of the molecular stacking.

Low awareness of venous thromboembolism among neurosurgical hospitalized patients: a cross-sectional study.

BACKGROUND: Venous thromboembolism (VTE) including Deep Venous Thrombosis (DVT) and Pulmonary Embolism (PE), is a serious cause of patient morbidity and mortality in hospitals. Neurosurgical hospitalized patients have higher rates of immobility and bed rest, thus increasing their risk of developing VTE. This highlights the need for their thromboprophylaxis regimens. Patients' awareness of VTE is essential for promoting strategies such as early ambulation and encouraging self-assessment and self-reporting of VTE signs and symptoms. This study evaluated neurosurgical hospitalized patients' awareness of VTE and explored the influencing factors to provide a theoretical basis for nursing intervention. METHODS: We selected one tertiary level hospital in Hunan Province and randomly sampled eligible patients from each five neurosurgical units. We conducted a cross-sectional survey of the hospitalized patients of neurosurgery using the self-designed and validated VTE knowledge questionnaire, and the influencing factors were analyzed using SPSS 26.0. RESULTS: A total of 386 neurosurgical hospitalized patients completed the survey. The score of VTE knowledge in neurosurgical hospitalized patients was 13.22 (SD = 11.52). 36.0% and 21.2% of participants reported they had heard of DVT and PE, respectively. 38.9% of participants were unable to correctly identify any symptoms of VTE. The most frequently identified risk factor was 'immobility or bed rest for more than three days' (50.0% of participants), and 38.1% of patients agreed that PE could cause death. 29.5% of participants were unable to identify any prophylactic measures of VTE. The results of Negative Binomial Regression showed that the influencing factors of VTE knowledge in neurosurgical hospitalized patients were education level (P < 0.004) and sources of information related to VTE, including nurses (95% CI = 2.201-4.374, P < 0.001), and family member/friend (95% CI = 2.038-4.331, P < 0.001), Internet/TV (95% CI = 1.382-2.834, P < 0.001). Other sources included patient /pamphlet/poster /professional books (95% CI = 1.492-3.350, P < 0.001). CONCLUSIONS: This study demonstrates the lack of awareness of VTE among neurosurgical hospitalized patients. More attention must be paid to carrying out training on VTE knowledge according to different characteristics of neurosurgical hospitalized patients, so as to ensure safe and high-quality patient care.

Effective Connectivity Analysis and Classification of Action Observation From Different Perspectives: An fMRI Study.

OBJECTIVE: Analyzing the effective connectivity characteristics of brain networks in the process of action observation is helpful for understanding the neurodynamic mechanisms during action observation. METHOD: In this study, functional magnetic resonance imaging (fMRI) images were obtained from 20 participants who performed hand-object interaction observation tasks from the first-person perspective (1PP) and third-person perspective (3PP). On the basis of a meta-analysis, 11 key brain regions were extracted as nodes to build an action observation network. The weighted and directional connections between all of the nodes were investigated using partial directional coherence (PDC) analysis in five narrow frequency bands. RESULTS: The statistical analysis indicated that the ultra-low frequency band ( ≤ 0.04 Hz) exhibited significant activation compared with other frequency bands for both 1PP and 3PP. In addition, it was found that 3PP induced significantly stronger brain activation than 1PP in the ultra-low frequency band. Moreover, this study attempted to classify fMRI data corresponding to different perspectives using brain network features. A comparative analysis revealed that the weighted and binary PDC matrix methods achieved classification accuracies of 86.3% and 80.8%, respectively. SIGNIFICANCE: The weighted PDC analysis exhibits a more comprehensive understanding of neural mechanisms during action observation in different visual perspectives. It also has potential applications value in human-computer interaction in the future.

Segregation, integration and balance in resting-state brain functional networks associated with bipolar disorder symptoms.

Bipolar disorder (BD) is a serious mental disorder involving widespread abnormal interactions between brain regions, and it is believed to be associated with imbalanced functions in the brain. However, how this brain imbalance underlies distinct BD symptoms remains poorly understood. Here, we used a nested-spectral partition (NSP) method to study the segregation, integration, and balance in resting-state brain functional networks in BD patients and healthy controls (HCs). We first confirmed that there was a high deviation in the brain functional network toward more segregation in BD patients than in HCs and that the limbic system had the largest alteration. Second, we demonstrated a network balance of segregation and integration that corresponded to lower anxiety in BD patients but was not related to other symptoms. Subsequently, based on a machine-learning approach, we identified different system-level mechanisms underlying distinct BD symptoms and found that the features related to the brain network balance could predict BD symptoms better than graph theory analyses. Finally, we studied attention-deficit/hyperactivity disorder (ADHD) symptoms in BD patients and identified specific patterns that distinctly predicted ADHD and BD scores, as well as their shared common domains. Our findings supported an association of brain imbalance with anxiety symptom in BD patients and provided a potential network signature for diagnosing BD. These results contribute to further understanding the neuropathology of BD and to screening ADHD in BD patients.

Magnesium Lithospermate B Protects Against Cisplatin-Induced Acute Kidney Injury via Alleviating Mitochondrial Dysfunction.

Purpose: Apoptosis plays a critical role in cisplatin-induced acute kidney injury (AKI) and is related to mitochondrial dysfunction. Magnesium lithospermate B (Mlb), one of the most important components of Salvia miltiorrhiza Bunge, is mainly used to treat cardiovascular diseases because of its anti-apoptotic effects. The mechanism underlying the protective effect of Mlb against cisplatin-induced AKI remains unclear. In this study, we investigated the protective effect of Mlb on mitochondrial function against apoptosis caused by cisplatin-induced renal injury. Methods: Renal injury induced by cisplatin in mouse renal tubular epithelial cells (mTECs) was measured by quantifying serum creatinine levels, mitochondrial morphology, cell viability, apoptosis, Dynamin-related protein 1(Drp1) expression, etc. The cells were then administered Mlb to determine its protective effects against cisplatin-induced AKI. Results: Mlb treatment significantly reduced serum creatinine levels and pathological injury of renal, inhibited the production of malondialdehyde, and reduced the depletion of superoxide dismutase. In addition, Mlb reduced Bax/Bcl2, cleaved caspase-3/caspase-3, and maintained mitochondrial integrity after AKI. Mlb administration also improved cell viability and reduced the percentage of apoptotic cells in vitro. Furthermore, Mlb reduced mitochondrial reactive oxygen species, improved mitochondrial membrane potential, and ameliorated mitochondrial morphological abnormalities by downregulating Drp1 expression. Conclusion: These results indicated that Mlb could protect the kidneys against cisplatin-induced apoptosis by alleviating mitochondrial dysfunction.

State-independent and -dependent behavioral and neuroelectrophysiological characteristics during dynamic decision-making in patients with current and remitted depression.

BACKGROUND: It is unclear whether the altered decision-making (DM) observed in patients with major depressive disorder (MDD) is neurophysiological and whether it improves with remission of depressive symptoms. The aim of this study was to identify developmental patterns of DM behavior, related cognitive characteristics, and electrophysiological abnormalities in patients with MDD across clinical stages. METHODS: A sample of 48 first-episode MDD patients (FD group), 41 remitted MDD patients (RD group), and 43 healthy controls (HCs) completed psychometric assessments and performed the balloon analogue risk task (BART) while event-related potentials (ERPs) were recorded. RESULTS: The RD group had lower depressiveness, self-blame, rumination, and catastrophizing tendencies, and higher mental resilience scores than the FD group, but retained significant differences from HCs. MDD patients showed a more conservative DM strategy than HCs, with no significant difference between the FD and RD groups. Compared to the FD group, the RD group had a smaller FRN for negative feedback and a trend toward a smaller P3 for positive feedback. Compared with HCs, the RD group had a smaller P3 during the positive feedback phase. FRN amplitude correlated positively with depression level and negatively with mental resilience. LIMITATIONS: Because a comparative cross-section design was employed, longitudinal studies are needed to make causal inferences. CONCLUSION: MDD patients presented a stable risk-avoidance bias in actively depressed and remission periods, consistent with a state-independent impairment pattern. Significantly reduced FRN amplitudes during remission indicated a state-dependent impairment pattern, and FRN amplitudes correlated with depression level. An abnormal feedback P3 component may be a state-independent characteristic that may become more pronounced with MDD progression.

Ononin ameliorates inflammation and cartilage degradation in rat chondrocytes with IL-1ß-induced osteoarthritis by downregulating the MAPK and NF-κB pathways.

BACKGROUND: Osteoarthritis (OA) treatment aims to improve inflammation and delay cartilage degeneration. However, there is no effective strategy presently available. Ononin, a representative isoflavone glycoside component extracted from natural Chinese herbs, exerts anti-inflammatory and proliferative effects. However, the therapeutic effect of ononin on chondrocyte inflammation remains unclear. METHODS: In this study, we explored the therapeutic effect and potential mechanism of ononin in OA by establishing an interleukin-1 beta (IL-1ß)-induced chondrocyte inflammation model. RESULTS: Our results verified that ononin alleviated the IL-1ß-induced decrease in chondrocyte viability, attenuated the overexpression of the inflammatory factors tumour necrosis factor α (TNF-α) and interleukin 6 (IL-6), and simultaneously inhibited the expression of cartilage extracellular matrix (ECM)-degrading enzymes such as matrix metalloproteinase-13 (MMP-13). Furthermore, the decomposition of Collagen II protein could be alleviated in the OA model by ononin. Finally, ononin improved chondrocyte inflammation by downregulating the mitogen-activated protein kinase (MAPK) and nuclear factor kappa-B (NF-κB) signalling pathways. CONCLUSION: Our findings suggested that ononin could inhibit the IL-1ß-induced proinflammatory response and ECM degradation in chondrocytes by interfering with the abnormal activation of the MAPK and NF-κB pathways, indicating its protective effect against OA.

Flexible Brain Transitions Between Hierarchical Network Segregation and Integration Associated With Cognitive Performance During a Multisource Interference Task.

Cognition involves locally segregated and globally integrated processing. This process is hierarchically organized and linked to evidence from hierarchical modules in brain networks. However, researchers have not clearly determined how flexible transitions between these hierarchical processes are associated with cognitive performance. Here, we designed a multisource interference task (MSIT) and introduced the nested-spectral partition (NSP) method to detect hierarchical modules in brain functional networks. By defining hierarchical segregation and integration across multiple levels, we showed that the MSIT requires higher network segregation in the whole brain and most functional systems but generates higher integration in the control system. Meanwhile, brain networks have more flexible transitions between segregated and integrated configurations in the task state. Crucially, higher functional flexibility in the resting state, less flexibility in the task state and more efficient switching of the brain from resting to task states were associated with better task performance. Our hierarchical modular analysis was more effective at detecting alterations in functional organization and the phenotype of cognitive performance than graph-based network measures at a single level.

Highlighting psychological pain avoidance and decision-making bias as key predictors of suicide attempt in major depressive disorder-A novel investigative approach using machine learning.

OBJECTIVE: Predicting suicide is notoriously difficult and complex, but a serious public health issue. An innovative approach utilizing machine learning (ML) that incorporates features of psychological mechanisms and decision-making characteristics related to suicidality could create an improved model for identifying suicide risk in patients with major depressive disorder (MDD). METHOD: Forty-four patients with MDD and past suicide attempts (MDD_SA, N = 44); 48 patients with MDD but without past suicide attempts (MDD_NS, N = 48-42 of whom with suicide ideation [MDD_SI, N = 42]), and healthy controls (HCs, N = 51) completed seven psychometric assessments including the Three-dimensional Psychological Pain Scale (TDPPS), and one behavioral assessment, the Balloon Analogue Risk Task (BART). Descriptive statistics, group comparisons, logistic regressions, and ML were used to explore and compare the groups and generate predictors of suicidal acts. RESULTS: MDD_SA and MDD_NS differed in TDPPS total score, pain arousal and avoidance subscale scores, suicidal ideation scores, and relevant decision-making indicators in BART. Logistic regression tests linked suicide attempts to psychological pain avoidance and a risk decision-making indicator. The resultant key ML model distinguished MDD_SA/MDD_NS with 88.2% accuracy. The model could also distinguish MDD_SA/MDD_SI with 81.25% accuracy. The ML model using hopelessness could classify MDD_SI/HC with 94.4% accuracy. CONCLUSION: ML analyses showed that motivation to avoid intolerable psychological pain, coupled with impaired decision-making bias toward under-valuing life's worth are highly predictive of suicide attempts. Analyses also demonstrated that suicidal ideation and attempts differed in potential mechanisms, as suicidal ideation was more related to hopelessness. ML algorithms show useful promises as a predictive instrument.

Brain Fingerprinting and Lie Detection: A Study of Dynamic Functional Connectivity Patterns of Deception Using EEG Phase Synchrony Analysis.

This study investigated the brain functional connectivity (FC) patterns related to lie detection (LD) tasks with the purpose of analyzing the underlying cognitive processes and mechanisms in deception. Using the guilty knowledge test protocol, 30 subjects were divided randomly into guilty and innocent groups, and their electroencephalogram (EEG) signals were recorded on 32 electrodes. Phase synchrony of EEG was analyzed between different brain regions. A few-trials-based relative phase synchrony (FTRPS) measure was proposed to avoid the false synchronization that occurs due to volume conduction. FTRPS values with a significantly statistical difference between two groups were employed to construct FC patterns of deception, and the FTRPS values from the FC networks were extracted as the features for the training and testing of the support vector machine. Finally, four more intuitive brain fingerprinting graphs (BFG) on delta, theta, alpha and beta bands were respectively proposed. The experimental results reveal that deceptive responses elicited greater oscillatory synchronization than truthful responses between different brain regions, which plays an important role in executing lying tasks. The functional connectivity in the BFG is mainly implicated in the visuo-spatial imagery, bottom-top attention and memory systems, work memory and episodic encoding, and top-down attention and inhibition processing. These may, in part, underlie the mechanism of communication between different brain cortices during lying. High classification accuracy demonstrates the validation of BFG to identify deception behavior, and suggests that the proposed FTRPS could be a sensitive measure for LD in the real application.

Omega-3 fatty acids and blood-based biomarkers in Alzheimer's disease and mild cognitive impairment: A randomized placebo-controlled trial.

BACKGROUND: Increased serum levels of pro-inflammatory biomarkers are consistently associated with cognitive decline. The omega-3 unsaturated fatty acids (n-3 PUFAs) had been linked to slowing cognitive decline due to their potential anti-inflammatory effects. To our knowledge, the different regiments of pure DHA, pure EPA, and their combination on various associated symptoms of dementia, including a mild form of cognitive impairment (MCI) and Alzheimer's disease (AD), have never been studied. METHODS: This multisite, randomized, double-blind, placebo-controlled trial was conducted at two veteran's retirement centers and one medical center in central Taiwan between 2013 and 2015. 163 MCI or AD patients were randomly assigned to placebo (n = 40), docosahexaenoic acid (DHA, 0.7 g/day, n = 41), eicosapentaenoic acid (EPA, 1.6 g/day, n = 40), or EPA (0.8 g/day) + DHA (0.35 g/day) (n = 42) group for 24 months. The results were measured as the cognitive and functional abilities, biochemical, and inflammatory cytokines profiles. Chi-square tests, two-sample t-test, ANOVA, and linear mixedeffects models were conducted with p < 0.05. RESULTS: 131 (80%) participants had completed the trial with all cognitive, functional, and mood status assessments. The statistically significant difference between the placebo and treatment groups was not determined, concerning the changes in cognitive, functional, and mood status scores, the biochemical profiles, and inflammatory cytokines levels. However, EPA was found to reduce the C-C motif ligands 4 (CCL4) level (p < 0.001). Additionally, EPA could reduce the constructional praxis (p < 0.05) and spoken language ability scores (p < 0.01), and DHA also reduced the spoken language ability score (p < 0.05). CONCLUSION: Overall, n-3 PUFAs supplements did not reduce cognitive, functional, and depressive symptom outcomes, but spoken language ability and constructional praxis subitems of ADAS-cog. These findings show that attention to clinical heterogeneity in dementia is crucial when studying nutrients interventions, such as n-3 PUFAs. In addition, with small effect size CCL4 is a better indicator than other inflammatory cytokines for EPA treatment response.