The Renoprotective and Anti-Inflammatory Effects of Human Urine-Derived Stem Cells on Acute Kidney Injury Animals.

BACKGROUND: Acute Kidney Injury (AKI) is defined as a sudden loss of kidney function, which is often caused by drugs, toxins, and infections. The large spectrum of AKI implies diverse pathophysiological mechanisms. In many cases, AKI can be lethal, and kidney replacement therapy is frequently needed. However, current treatments are not satisfying. Developing novel therapies for AKI is essential. Adult stem cells possess regenerative ability and play an important role in medical research and disease treatment. METHODS: In this study, we isolated and characterized a distinct human urine-derived stem cell, which expressed both proximal tubular cell and mesenchymal stem cell genes as well as certain unique genes. RESULTS: It was found that these cells exhibited robust protective effects on tubular cells and anti- inflammatory effects on macrophages in vitro. In an ischemia-reperfusion-induced acute kidney injury NOD-SCID mouse model, transplantation of USCs significantly protected the kidney morphology and functions in vivo. CONCLUSION: In summary, our results highlighted the effectiveness of USCs in protecting from PTC injury and impeding macrophage polarization, as well as the secretion of pro-inflammatory interleukins, suggesting the potential of USCs as a novel cell therapy in AKI.

Trait anxiety and corresponding neuromarkers predict internet addiction: A longitudinal study.

Background and Aims: The high prevalence of internet addiction (IA) has become a worldwide problem that profoundly affects people's mental health and executive function. Empirical studies have suggested trait anxiety (TA) as one of the most robust predictors of addictive behaviors. The present study investigated the neural and socio-psychological mechanisms underlying the association between TA and IA. Methods: Firstly, we tested the correlation between TA and IA. Then we investigated the longitudinal influence of TA on IA using a linear mixed effect (LME) model. Secondly, connectome-based predictive modeling (CPM) was employed to explore neuromarkers of TA, and we tested whether the identified neuromarkers of TA can predict IA. Lastly, stressful life events and default mode network (DMN) were considered as mediating variables to explore the relationship between TA and IA. Findings: A significant positive correlation between TA and IA was found and the high TA group demonstrated higher IA across time. CPM results revealed that the functional connectivity of cognitive control and emotion-regulation circuits and DMN were significantly correlated with TA. Furthermore, a significant association was found between the neuromarkers of TA and IA. Notably, the CPM results were all validated in an independent sample. The results of mediation demonstrated that stressful life events and correlated functional connectivity mediated the association between TA and IA. Conclusions: Findings of the present study facilitate a deeper understanding of the neural and socio-psychological mechanisms linking TA and IA and provide new directions for developing neural and psychological interventions.

Neural basis underlying the association between thought control ability and happiness: The moderating role of the amygdala.

Thought control ability (TCA) plays an important role in individuals' health and happiness. Previous studies demonstrated that TCA was closely conceptually associated with happiness. However, empirical research supporting this relationship was limited. In addition, the neural basis underlying TCA and how this neural basis influences the relationship between TCA and happiness remain unexplored. In the present study, the voxel-based morphometry (VBM) method was adopted to investigate the neuroanatomical basis of TCA in 314 healthy subjects. The behavioral results revealed a significant positive association between TCA and happiness. On the neural level, there was a significant negative correlation between TCA and the gray matter density (GMD) of the bilateral amygdala. Split-half validation analysis revealed similar results, further confirming the stability of the VBM analysis findings. Furthermore, gray matter covariance network and graph theoretical analyses showed positive association between TCA and both the node degree and node strength of the amygdala. Moderation analysis revealed that the GMD of the amygdala moderated the relationship between TCA and happiness. Specifically, the positive association between TCA and self-perceived happiness was stronger in subjects with a lower GMD of the amygdala. The present study indicated the neural basis underlying the association between TCA and happiness and offered a method of improving individual well-being.

Concurrent JCPyV-DNAemia Is Correlated With Poor Graft Outcome in Kidney Transplant Recipients with Polyomavirus-associated Nephropathy.

BACKGROUND: Co-infection of JC polyomavirus (JCPyV) and BK polyomavirus (BKPyV) is uncommon in kidney transplant recipients, and the prognosis is unclear. This study aimed to investigate the effect of concurrent JCPyV-DNAemia on graft outcomes in BKPyV-infected kidney transplant recipients with polyomavirus-associated nephropathy (PyVAN). METHODS: A total of 140 kidney transplant recipients with BKPyV replication and PyVAN, 122 without concurrent JCPyV-DNAemia and 18 with JCPyV-DNAemia were included in the analysis. Least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to identify prognostic factors for graft survival. A nomogram for predicting graft survival was created and evaluated. RESULTS: The median tubulitis score in the JCPyV-DNAemia-positive group was higher than in JCPyV-DNAemia-negative group (P = 0.048). At last follow-up, the graft loss rate in the JCPyV-DNAemia-positive group was higher than in the JCPyV-DNAemia-negative group (50% versus 25.4%; P = 0.031). Kaplan-Meier analysis showed that the graft survival rate in the JCPyV-DNAemia-positive group was lower than in the JCPyV-DNAemia-negative group (P = 0.003). Least absolute shrinkage and selection operator regression and multivariate Cox regression analysis demonstrated that concurrent JCPyV-DNAemia was an independent risk factor for graft survival (hazard ratio = 4.808; 95% confidence interval: 2.096-11.03; P < 0.001). The nomogram displayed favorable discrimination (C-index = 0.839), concordance, and clinical applicability in predicting graft survival. CONCLUSIONS: Concurrent JCPyV-DNAemia is associated with a worse graft outcome in BKPyV-infected kidney transplant recipients with PyVAN.

Multiple sources of unconscious-information processing affect a single response: independent unconscious priming effects.

At present there is little knowledge on whether and how multiple pieces of unconscious information can simultaneously affect a single conscious response. In the present study, we manipulated the congruency relation between a masked prime arrow and the target arrow, as well as that between masked flankers and the target arrow. The results demonstrated that the masked prime and flankers produced independent unconscious priming effects on the response to the target. In the process of studying the above phenomenon, two secondary findings were made. First, although the prime congruency effect was obtained, the flanker congruency effect was smaller when the flankers were displayed simultaneously with the target than when they were displayed sequentially before the target. This suggested that priming stimulation required enough time to be processed to a sufficient extent to produce an unconscious priming effect. Second, when the prime stimulus was removed, leaving only the flankers, the flanker priming effect increased, suggesting that the attention attracted to the prime and its conscious mask could also reduce the flanker congruency effect. These results observed across several experiments were replicated in one within-subjects experiment. We proposed an "independent unconscious influence hypothesis" for the phenomenon. This hypothesis was further integrated into a more comprehensive unconscious information processing model. The possible causes of the observed phenomena were discussed.

Connectome-based predictive modeling of Internet addiction symptomatology.

Internet addiction symptomatology (IAS) is characterized by persistent and involuntary patterns of compulsive Internet use, leading to significant impairments in both physical and mental well-being. Here, a connectome-based predictive modeling approach was applied to decode IAS from whole-brain resting-state functional connectivity in healthy population. The findings showed that IAS could be predicted by the functional connectivity between prefrontal cortex with the cerebellum and limbic lobe and connections of the occipital lobe with the limbic lobe and insula lobe. The identified edges associated with IAS exhibit generalizability in predicting IAS within an independent sample. Furthermore, we found that the unique contributing network, which predicted IAS in contrast to the prediction networks of alcohol use disorder symptomatology (the range of symptoms and behaviors associated with alcohol use disorder), prominently comprised connections involving the occipital lobe and other lobes. The current data-driven approach provides the first evidence of the predictive brain features of IAS based on the organization of intrinsic brain networks, thus advancing our understanding of the neurobiological basis of Internet addiction disorder (IAD) susceptibility, and may have implications for the timely intervention of people potentially at risk of IAD.

Neural specialization with generalizable representations underlies children's cognitive development of attention.

From childhood to adulthood, the human brain develops highly specialized yet interacting neural modules that give rise to nuanced attention and other cognitive functions. Each module can specialize over development to support specific functions, yet also coexist in multiple neurobiological modes to support distinct processes. Advances in cognitive neuroscience have conceptualized human attention as a set of cognitive processes anchored in highly specialized yet interacting neural systems. The underlying mechanisms of how these systems interplay to support children's cognitive development of multiple attention processes remain unknown. Leveraging developmental functional magnetic resonance imaging with attention network test paradigm, we demonstrate differential neurocognitive development of three core attentional processes from childhood to adulthood, with alerting reaching adult-like level earlier, followed by orienting and executive attention with more protracted development throughout middle and late childhood. Relative to adults, young children exhibit immature specialization with less pronounced dissociation of neural systems specific to each attentional process. Children manifest adult-like distributed representations in the ventral attention and cingulo-opercular networks, but less stable and weaker generalizable representations across multiple processes in the dorsal attention network. Our findings provide insights into the functional specialization and generalization of neural representations scaffolding cognitive development of core attentional processes from childhood to adulthood. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Spontaneous brain activity associated with individual differences in decisional and emotional forgiveness.

Previous studies have explored the neural bases of forgiveness, however, the neural associations of decisional and emotional forgiveness remain unclear. Regional homogeneity (ReHo) and functional connectivity (FC) measured by resting-state functional magnetic resonance imaging (fMRI) were used to investigate the neural associations of individual differences in decisional and emotional forgiveness among healthy volunteers (256 participants, 85 males). The results of the ReHo analysis showed that decisional forgiveness was positively correlated with the left inferior parietal lobule (IPL). Furthermore, emotional forgiveness was positively correlated with the dorsal anterior cingulate cortex (dACC) and left supramarginal gyrus (SMG). The results of the FC analysis showed that decisional forgiveness was positively associated with the FC strength between the left IPL and left middle frontal gyrus (MFG) and negatively correlated with the FC strength among the left IPL, right superior temporal gyrus (STG), and left SMG. Furthermore, there was a significant positive correlation between emotional forgiveness and FC strength between the left SMG and right IPL. These findings suggest an association between decisional and emotional forgiveness and spontaneous brain activity in brain regions related to empathy, emotion regulation, and cognitive control.

Basolateral Amygdala Functional Connectivity in Alexithymia: Linking Interoceptive Sensibility and Cognitive Empathy.

Emotions rely on bodily states, and perceiving the emotions of others depends on awareness of one's own emotional state. However, the intercorrelations among interoception, alexithymia, and empathy are not well understood, and the neural mechanisms behind this connection are also largely unknown. To address these issues, 297 college students participated in this study, completing measures of interoceptive sensibility (IS), empathy and alexithymia and undergoing resting-state fMRI scans. The functional connectivity of the amygdala was analysed to identify the neural substrates of alexithymia, and mediation analyses were conducted to examine the mediation effect of alexithymia and alexithymia-specific amygdala functional connectivity on the relationship between IS and empathy. The results showed that higher levels of IS were associated with increased cognitive empathy through weakened alexithymia. Functional connectivity analysis indicated that right basolateral amygdala (BLA)-left precuneus connectivity was negatively related to alexithymia, while right BLA-left precentral gyrus connectivity was positively related to alexithymia. Furthermore, right BLA-left precuneus connectivity was found to mediate the impact of interoception on cognitive empathy. In conclusion, this study provides valuable insights into the relationships among IS, alexithymia, and empathy. The right BLA-left precuneus connectivity may serve as a shared neural substrate between interoception and cognitive empathy.

Validation of the Appearance-Related Social Media Consciousness Scale with Chinese adolescents and young adults.

Research has revealed a negative association between appearance-related social media consciousness (ASMC) and mental health, but the impact of this association in the Chinese population remains understudied. This study examined the psychometric properties of the ASMC scale among Chinese adolescents and young adults and to further investigate the scale's measurement invariance and differences in ASMC across gender and age groups. Exploratory and confirmatory factor analyses were conducted to examine the ASMC scale's factorial structure among Chinese adolescents and young adults, including 1109 adolescents (50.0% boys) aged 12-18 (mean, 14.89) years and 457 young adults (42.5% men) aged 18-25 (mean, 20.75) years. The measurement invariance across gender and age groups, internal consistency and convergent validity were examined. ASMC scale was found to have a unidimensional structure and to be invariant across gender and age groups. It exhibited excellent internal consistency and strong construct validity. Moderate gender differences and pronounced age differences in ASMC scale scores were observed. Our findings support the validity of the ASMC scale as an effective instrument for the measurement of appearance-related social media consciousness experience among Chinese young adults and adolescents. Further study is required to evaluate the status of ASMC as a risk factor for disordered eating and target for preventive interventions within Chinese samples.

Elevated BMI impacts brain-state dynamics within the sensorimotor-to-transmodal hierarchy.

OBJECTIVE: Overweight and obesity, as commonly indicated by a higher BMI, are associated with functional alterations in the brain, which may potentially result in cognitive decline and emotional illness. However, the manner in which these detrimental impacts manifest in the brain's dynamic characteristics remains largely unknown. METHODS: Based on two independent resting-state functional magnetic resonance imaging data sets (Behavioral-Brain Research Project of Chinese Personality, n = 1923; Human Connectome Project, n = 998), the current study employed a Hidden Markov model to identify the spatiotemporal features of brain activity states. Subsequently, the study examined the changes in brain-state dynamics and the corresponding functional outcomes that arise with an increase in BMI. RESULTS: Elevated BMI tends to shift the brain's activity states toward a greater emphasis on a specific set of states, i.e., the metastate, that are relevant to the joint activities of sensorimotor systems, making it harder to transfer to the metastate of transmodal systems. These findings were reconfirmed in a longitudinal sample (Behavioral-Brain Research Project of Chinese Personality, n = 34) that exhibited a significant increase in BMI at follow-up. Importantly, the alternation of brain-state dynamics specifically mediated the relationships between BMI and adverse functional outcomes, including cognitive decline and symptoms of mental illness. CONCLUSIONS: The altered brain-state dynamics within the sensorimotor-to-transmodal hierarchy provide new insights into obesity-related brain dysfunctions and mental health issues.

Volume of the Dentate Gyrus/CA4 Hippocampal subfield mediates the interplay between sleep quality and depressive symptoms.

Background: Emerging evidence increasingly suggests that poor sleep quality is associated with depressive symptoms. The hippocampus might play a crucial role in the interplay between sleep disturbance and depressive symptomatology, e.g., hippocampal atrophy is typically seen in both insomnia disorder and depression. Thus, examining the role of hippocampal volume in the interplay between poor sleep quality and depressive symptoms in large healthy populations is vital. Methods: We investigated the association between self-reported sleep quality, depressive symptoms, and hippocampal total and subfields' volumes in 1603 healthy young adults from the Behavioral Brain Research Project. Mediation analysis explored the mediating role of hippocampal volumes between sleep quality and depressive symptoms. Results: Self-reported sleep quality and depressive symptoms were positively correlated. In addition, it negatively related to three hippocampal subfields but not total hippocampal volume. In particular, hippocampal subfield DG and CA4 volumes mediated the interrelationship between poor sleep quality and depressive symptoms. Conclusions: Our findings improved the current understanding of the relationship between sleep disturbance, depressive symptomatology, and hippocampal subfields in healthy populations. Considering the crucial role of DG in hippocampal neurogenesis, our results suggest that poor sleep quality may contribute to depression through a reduction of DG volume leading to impaired neurogenesis which is crucial for the regulation of mood.

Transcriptomic Similarity Informs Neuromorphic Deviations in Depression Biotypes.

BACKGROUND: Major depressive disorder (MDD) is complicated by population heterogeneity, motivating the investigation of biotypes through imaging-derived phenotypes. However, neuromorphic heterogeneity in MDD remains unclear, and how the correlated gene expression (CGE) connectome constrains these neuromorphic anomalies in MDD biotypes has not yet been studied. METHODS: Here, we related cortical thickness deviations in MDD biotypes to a pattern of CGE connectome. Cortical thickness was estimated from 3-dimensional T1-weighted magnetic resonance images in 2 independent cohorts (discovery cohort: N = 425; replication cohort: N = 217). The transcriptional activity was measured according to Allen Human Brain Atlas. A density peak-based clustering algorithm was used to identify MDD biotypes. RESULTS: We found that patients with MDD were clustered into 2 replicated biotypes based on single-patient regional deviations from healthy control participants across 2 datasets. Biotype 1 mainly exhibited cortical thinning across the brain, whereas biotype 2 mainly showed cortical thickening in the brain. Using brainwide gene expression data, we found that deviations of transcriptionally connected neighbors predicted regional deviation for both biotypes. Furthermore, putative CGE-informed epicenters of biotype 1 were concentrated on the cognitive control circuit, whereas biotype 2 epicenters were located in the social perception circuit. The patterns of epicenter likelihood were separately associated with depression- and anxiety-response maps, suggesting that epicenters of MDD biotypes may be associated with clinical efficacies. CONCLUSIONS: Our findings linked the CGE connectome and neuromorphic deviations to identify distinct epicenters in MDD biotypes, providing insight into how microscale gene expressions informed MDD biotypes.

Copper-Catalyzed Radical Allene C(sp2 )-H Cyanation.

While the hydrogen atom abstraction (HAA) from C(sp3 )-H bond has been well explored, the radical-mediated chemo- and regio-selective functionalization of allenic C(sp2 )-H bond via direct HAA from C(sp2 )-H bond of allene remains an unsolved challenge in synthetic chemistry. This is primarily due to inherent challenges with addition of radical intermediates to allenes, regioselectivity of HAA process, instability of allenyl radical toward propargyl radical et al. Herein, we report a copper catalyzed allenic C(sp2 )-H cyanation of an array of tri- and di-substituted allenes with exceptional site-selectivity, while mono-substituted allene was successfully cyanated, albeit with a low yield. In the developed strategy, steric N-fluoro-N-alkylsulfonamide, serving as precursor of hydrogen atom abstractor, plays a crucial role in achieving the desired regioselectivity and avoiding addition of N-centered radical to allene.

Psychological resilience-related functional connectomes predict creative personality.

Both psychological resilience and creativity are complex concepts that have positive effects on individual adaptation. Previous studies have shown overlaps between the key brain regions or brain functional networks related to psychological resilience and creativity. However, no direct experimental evidence has been provided to support the assumption that psychological resilience and creativity share a common brain basis. Therefore, the present study investigated the relationship between psychological resilience and creativity using neural imaging method with a machine learning approach. At the behavioral level, we found that psychological resilience was positively related to creative personality. Predictive analysis based on static functional connectivity (FC) and dynamic FC demonstrated that FCs related to psychological resilience could effectively predict an individual's creative personality score. Both the static FC and dynamic FC were mainly located in the default mode network. These results prove that psychological resilience and creativity share a common brain functional basis. These findings also provide insights into the possibility of promoting individual positive adaptation from negative events or situations in a creative way.

Mechanistic insights into the effects of diuron exposure on Alexandrium pacificum.

Diuron (N-(3,4-dichlorophenyl)-N,N­dimethylurea, DCMU), a ureic herbicide, is extensively used in agriculture to boost crop productivity; however, its extensive application culminates in notable environmental pollution, especially in aquatic habitats. Therefore, the present study investigated the effect of diuron on the dinoflagellate Alexandrium pacificum, which is known to induce harmful algal blooms (HAB), and its potential to biodegrade DCMU. Following a four-day DCMU exposure, our results revealed that A. pacificum proficiently assimilated DCMU at concentrations of 0.05 mg/L and 0.1 mg/L in seawater, attaining a complete reduction (100 % efficiency) after 96 h for both concentrations. Moreover, evaluations of paralytic shellfish toxins content indicated that cells subjected to higher DCMU concentrations (0.1 mg/L) exhibited reductions of 73.4 %, 86.7 %, and 75 % in GTX1, GTX4, and NEO, respectively. Exposure to DCMU led to a notable decrease in A. pacificum's photosynthetic efficacy, accompanied by increased levels of reactive oxygen species (ROS) and suppressed cell growth, with a growth inhibition rate of 41.1 % at 72 h. Proteomic investigations pinpointed the diminished expression levels of specific proteins like SxtV and SxtW, linked to paralytic shellfish toxins (PSTs) synthesis, as well as key proteins associated with Photosystem II, namely PsbA, PsbD, PsbO, and PsbU. Conversely, proteins central to the cysteine biosynthesis pathways exhibited enhanced expression. In summary, our results preliminarily resolved the molecular mechanisms underlying the response of A. pacificum to DCMU and revealed that DCMU affected the synthesis of PSTs. Meanwhile, our data suggested that A. pacificum has great potential in scavenging DCMU.

Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI.

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future.

Shen Qi Wan ameliorates nephritis in chronic kidney disease via AQP1 and DEFB1 regulation.

Shen Qi Wan (SQW) has been proven to exert anti-inflammatory effects in the kidneys of CKD models accompanied by unclear therapeutic mechanisms. This study aims to evaluate the kidney-protective and anti-inflammatory effects of SQW and to elucidate its fundamental mechanisms for CKD treatment. Firstly, the main active components of SQW were identified by UPLC-Q-TOF/MS technique. Subsequently, we evaluated inflammatory factors, renal function and renal pathology changes following SQW treatment utilizing adenine-induced CKD mice and aquaporin 1 knockout (AQP1-/-) mice. Additionally, we conducted RNA-seq analysis and bioinformatics analysis to predict the SQW potential therapeutic targets and anti-nephritis pathways. Simultaneously, WGCNA analysis method and machine learning algorithms were used to perform a clinical prognostic analysis of potential biomarkers in CKD patients from the GEO database and validated through clinical samples. Lipopolysaccharide-induced HK-2 cells were further used to explore the mechanism. We found that renal collagen deposition was reduced, serum inflammatory cytokine levels decreased, and renal function was improved after SQW intervention. It can be inferred that ß-defensin 1 (DEFB1) may be a pivotal target, as confirmed by serum and renal tissue samples from CKD patients. Furthermore, SQW assuages inflammatory responses by fostering AQP1-mediated DEFB1 expression was confirmed in in vitro and in vivo studies. Significantly, the renal-protective effect of SQW is to some extent attenuated after AQP1 gene knockout. SQW could reduce inflammatory responses by modulating AQP1 and DEFB1. These findings underscore the potential of SQW as a promising contender for novel prevention and treatment strategies within the ambit of CKD management.

An amygdala-centered effective connectivity network in trait anxiety.

Previous studies have established that the amygdala plays an important role in trait anxiety. However, there remains limited knowledge regarding the changes in amygdala-centered effective connectivity network associated with this trait. The current study employed the Granger Causal analysis to investigate the directional connectivity patterns involving the amygdala in relation to trait anxiety in a large cohort of young adults (N = 424). The results revealed a negative association between trait anxiety scores and the Granger causality from the left middle frontal gyrus and right superior frontal gyrus to the right amygdala. Conversely, higher trait anxiety levels were found to be associated with increased effective connectivity from the left amygdala to the left hippocampus. These results demonstrated the significance of the prefrontal cortex-amygdala-hippocampus neural circuitry in the neurobiological mechanisms underlying trait anxiety. Our findings advance the comprehension of this characteristic, holding promise for informing strategies in the prevention and treatment of related mental disorders.