USP5 facilitates diabetic retinopathy development by stabilizing ROBO4 via deubiquitination.

Ubiquitin-specific proteases (USPs) have been proved to play important roles in the progression of diabetic retinopathy. In this study, we explored the role of USP5 and its possible mechanisms in diabetic retinopathy development. Cell proliferation, apoptosis, inflammation and oxidative stress were determined using CCK-8 assay, EdU staining assay, flow cytometry, and ELISA, respectively. The mRNA and protein expression of ROBO4 and USP5 were measured through RT-qPCR and western blot, respectively. Co-IP and deubiquitination assay were conducted to evaluate the interaction between ROBO4 and USP5. The results showed that high glucose (HG) stimulation significantly led to HRPE cell damage as described by suppressing proliferation, and promoting oxidative stress, inflammation and apoptosis. ROBO4 was markedly increased in diabetic retinopathy plasma samples and HG-triggered HRPE cells. Depletion of ROBO4 could alleviate HG-caused HRPE cell damage. USP5 was also significantly elevated in diabetic retinopathy plasma samples and HG-triggered HRPE cells. USP5 overexpression aggravated HG-induced HRPE cell damage. USP5 stabilized ROBO4 through deubiquitination. Moreover, USP5 knockdown decreased ROBO4 expression to mitigate HG-triggered cell damage in HRPE cells. USP5 stabilized ROBO4 via deubiquitination to repress cell proliferation, and facilitate inflammation, cell apoptosis and oxidative stress in HG-treated HRPE cells, thereby promoting the development of diabetic retinopathy.

Inter-module gap filling method for photon counting detectors based on dual acquisition.

The use of photon counting detectors in X-ray imaging missions can effectively improve the signal-to-noise ratio and image resolution. However, the stitching of photon counting detector modules leads to large-size localized information loss in the acquired projected image, which seriously affects the regional observation. In this paper, we propose a method to fill the inter-module gap based on dual acquisition, referred to as the GFDA algorithm, which is divided into three main steps: (i) acquire the main projection by short-exposure scanning, and then scan again by vertically moving the carrier table to acquire the reference projection; (ii) use the alignment method to locate the projected region of interest; (iii) use image stitching and image fusion to recover the missing information. We analyzed the gray value of the region of interest of the Siemens star projection and the reconstructed conch slice data, and proved that the proposed method can recover the information more smoothly and perfectly. The GFDA algorithm is able to achieve a better image restoration effect without additional scanning time and better retain image details. In addition, the GFDA algorithm is scalable, which is demonstrated in the task of filling the stitching of multiple types of photonic technology detectors.

THz spectrum processing method based on optimal wavelet selection.

Terahertz spectrum is easily interfered by system noise and water-vapor absorption. In order to obtain high quality spectrum and better prediction accuracy in qualitative and quantitative analysis model, different wavelet basis functions and levels of decompositions are employed to perform denoising processing. In this study, the terahertz spectra of wheat samples are denoised using wavelet transform. The compound evaluation indicators (T) are used for systematically analyzing the quality effect of wavelet transform in terahertz spectrum preprocessing. By comparing the optimal denoising effects of different wavelet families, the wavelets of coiflets and symlets are more suitable for terahertz spectrum denoising processing than the wavelets of fejer-korovkin and daubechies, and the performance of symlets 8 wavelet basis function with 4-level decomposition is the optimum. The results show that the proposed method can select the optimal wavelet basis function and decomposition level of wavelet denoising processing in the field of terahertz spectrum analysis.

Intestinal Morphology and Glucose Transporter Gene Expression under a Chronic Intake of High Sucrose.

Sucrose is a disaccharide that is degraded into fructose and glucose in the small intestine. High-sucrose and high-fructose diets have been reported, using two-dimensional imaging, to alter the intestinal morphology and the expression of genes associated with sugar transport, such as sodium glucose co-transporter 1 (SGLT1), glucose transporter 2 (GLUT2), and glucose transporter 5 (GLUT5). However, it remains unclear how high-fructose and high-sucrose diets affect the expression of sugar transporters and the intestinal morphology in the whole intestine. We investigate the influence of a chronic high-sucrose diet on the expression of the genes associated with sugar transport as well as its effects on the intestinal morphology using 3D imaging. High sucrose was found to increase GLUT2 and GLUT5 mRNA levels without significant changes in the intestinal morphology using 3D imaging. On the other hand, the delay in sucrose absorption by an α-glucosidase inhibitor significantly improved the intestinal morphology and the expression levels of SGLT1, GLUT2, and GLUT5 mRNA in the distal small intestine to levels similar to those in the proximal small intestine, thereby improving glycemic control after both glucose and sucrose loading. These results reveal the effects of chronic high-sugar exposure on glucose absorption and changes in the intestinal morphology.

Multimodal covarying brain patterns mediate genetic and psychological contributions to individual differences in pain sensitivity.

ABSTRACT: Individuals vary significantly in their pain sensitivity, with contributions from the brain, genes, and psychological factors. However, a multidimensional model integrating these factors is lacking due to their complex interactions. To address this, we measured pain sensitivity (ie, pain threshold and pain tolerance) using the cold pressor test, collected magnetic resonance imaging (MRI) data and genetic data, and evaluated psychological factors (ie, pain catastrophizing, pain-related fear, and pain-related anxiety) from 450 healthy participants with both sexes (160 male, 290 female). Using multimodal MRI fusion methods, we identified 2 pairs of covarying structural and functional brain patterns associated with pain threshold and tolerance, respectively. These patterns primarily involved regions related to self-awareness, sensory-discriminative, cognitive-evaluative, motion preparation and execution, and emotional aspects of pain. Notably, pain catastrophizing was negatively correlated with pain tolerance, and this relationship was mediated by the multimodal covarying brain patterns in male participants only. Furthermore, we identified an association between the single-nucleotide polymorphism rs4141964 within the fatty acid amide hydrolase gene and pain threshold, mediated by the identified multimodal covarying brain patterns across all participants. In summary, we suggested a model that integrates the brain, genes, and psychological factors to elucidate their role in shaping interindividual variations in pain sensitivity, highlighting the important contribution of the multimodal covarying brain patterns as important biological mediators in the associations between genes/psychological factors and pain sensitivity.

Role of APOE in glaucoma.

Glaucoma is a chronic blinding eye disease caused by the progressive loss of retinal ganglion cells (RGCs). Currently, no clinically approved treatment can directly improve the survival rate of RGCs. The Apolipoprotein E (APOE) gene is closely related to the genetic risk of numerous neurodegenerative diseases and has become a hot topic in the field of neurodegenerative disease research in recent years. The optic nerve and retina are extensions of the brain's nervous system. The pathogenesis of retinal degenerative diseases is closely related to the degenerative diseases of the nerves in the brain. APOE consists of three alleles, ε4, ε3, and ε2, in a single locus. They have varying degrees of risk for glaucoma. APOE4 and the APOE gene deletion (APOE-/-) can reduce RGC loss. By contrast, APOE3 and the overall presence of APOE genes (APOE+/+) result in significant loss of RGC bodies and axons, increasing the risk of glaucoma RGCs death. Currently, there is no clear literature indicating that APOE2 is beneficial or harmful to glaucoma. This study summarises the mechanism of different APOE genes in glaucoma and speculates that APOE targeted intervention may be a promising method for protecting against RGCs loss in glaucoma.

Modulatory effects of transcutaneous auricular vagus nerve stimulation (taVNS) on attentional processes.

Background: The modulatory effect of transcutaneous auricular vagus nerve stimulation (taVNS) on attention has varied in previous studies. This inconsistency might be attributed to the combined influence of the modulation effect on the different attentional functions, including alerting, orienting and executive control. Aims: We aimed to preliminarily examine the modulatory effects of taVNS on different attentional functions. Methods: Fifty-nine healthy participants were recruited and were randomly assigned to taVNS (receiving taVNS for 20 minutes) or control (receiving taVNS for 30 seconds) groups. All participants underwent a dot-probe task before and after the taVNS/control intervention. Their behavioural performance and electroencephalographic signals during pre- and post-tests were recorded, and different observed variables were extracted and analysed to characterise different attentional systems. Results: We observed that active taVNS applied at the left ear significantly improved the overall behavioural performance, that is, shorter reaction time (RT) and lower intra-individual reaction time variability (IIRTV) for right-hand responses when compared with the control condition. In addition, active taVNS resulted in larger P3 and movement-related cortical potential (MRCP) amplitudes associated with right-hand reactions than the control condition. Active taVNS also decreased the difference between the pre- and post-tests in the power spectral density of spontaneous high-α band oscillations at C4 electrode. Importantly, parallel mediation models for right-hand responses showed that the change of P3 amplitude mediated the effects of taVNS on RT and IIRTV. In contrast, the change of MRCP amplitude suppressed the effect of taVNS on the IIRTV. Conclusions: Our results provided behavioural and brain evidence supporting the effects of taVNS on different attentional systems, and their interaction further shaped behavioural performance, suggesting a promising role of taVNS in cognitive enhancement.

Machine learning regression algorithms to predict short-term efficacy after anti-VEGF treatment in diabetic macular edema based on real-world data.

The objective of this retrospective study was to predict short-term efficacy of anti-vascular endothelial growth factor (VEGF) treatment in diabetic macular edema (DME) using machine learning regression models. Real-world data from 279 DME patients who received anti-VEGF treatment at Ineye Hospital of Chengdu University of TCM between April 2017 and November 2022 were analyzed. Eight machine learning regression models were established to predict four clinical efficacy indicators. The accuracy of the models was evaluated using mean absolute error (MAE), mean square error (MSE) and coefficient of determination score (R2). Multilayer perceptron had the highest R2 and lowest MAE among all models. Regression tree and lasso regression had similar R2, with lasso having lower MAE and MSE. Ridge regression, linear regression, support vector machines and polynomial regression had lower R2 and higher MAE. Support vector machine had the lowest MSE, while polynomial regression had the highest MSE. Stochastic gradient descent had the lowest R2 and high MAE and MSE. The results indicate that machine learning regression algorithms are valuable and effective in predicting short-term efficacy in DME patients through anti-VEGF treatment, and the lasso regression is the most effective ML algorithm for developing predictive regression models.

The analgesic effects and neural oscillatory mechanisms of virtual reality scenes based on distraction and mindfulness strategies in human volunteers.

BACKGROUND: Virtual reality (VR) has been widely used as a non-pharmacological adjunct to pain management. However, there is no consensus on what type of VR content is the best for pain alleviation and by what means VR modulates pain perception. We used three experiments to explore the analgesic effect of VR scenes in healthy adult volunteers. METHODS: We first compared the effect of immersive VR on pain perception with active (i.e. non-immersive, two-dimensional video) and passive (i.e. no VR or audiovisual input) controls at both subjective perceptual (Experiment 1) and electrophysiological (electroencephalography) levels (Experiment 2), and then explored possible analgesic mechanisms responsible for VR scenes conveying different strategies (e.g. exploration or mindfulness; Experiment 3). RESULTS: The multisensory experience of the VR environment lowered pain intensity and unpleasantness induced by contact heat stimuli when compared with two control conditions (P=0.001 and P<0.001, respectively). The reduced pain intensity rating correlated with decreased P2 amplitude (r=0.433, P<0.001) and increased pre-stimulus spontaneous gamma oscillations (r=-0.339, P=0.004) by 32-channel electroencephalography. A VR exploration scene induced a strong sense of immersion that was associated with increased pre-stimulus gamma oscillations (r=0.529, P<0.001), whereas a VR mindfulness meditation scene had a minor effect on immersive feelings but induced strong pre-stimulus alpha oscillations (r=-0.550, P<0.001), which led to a comparable analgesic effect. CONCLUSIONS: Distinct neural mechanisms are responsible for VR-induced analgesia, deepening our understanding of the analgesic benefits of VR and its neural electrophysiological correlates. These findings support further development of digital healthcare.

Identification of heavy metal pollutants in wheat by THz spectroscopy and deep support vector machine.

This paper proposes to detect heavy metal pollutants in wheat using terahertz spectroscopy and deep support vector machine (DSVM). Five heavy metal pollutants, arsenic, lead, mercury, chromium, and cadmium, were considered for detection in wheat samples. THz spectral data were pre-processed by wavelet denoising. DSVM was introduced to further enhance the accuracy of the SVM classification model. According to the relationship between the accuracy and the training time with the number of hidden layers ranging from 1 to 4, the model performs the best when the hidden layer network has three layers. Besides, using the back-propagation algorithm to optimize the entire DSVM network. Compared with Deep neural network (DNN) and SVM models, the comprehensive evaluation index of the proposed model optimized by DSVM has the highest accuracy of 91.3 %. It realized the exploration enhanced the classification accuracy of the heavy metal pollutants in wheat.

Enhanced neural synchrony associated with long-term ballroom dance training.

Long-term dance training offers numerous benefits, including improvements in physical health, posture, body coordination, and mental health and well-being. Since dance is an art form of body-to-body communication, professional dancers may share feelings and thoughts on dance with their partners, owing to their shared training experiences. Considering this perspective, one may expect that professional dancers would demonstrate pronounced neural similarities when viewing dancing videos, which could be associated with their training duration. To test these hypotheses, we collected functional magnetic resonance imaging (fMRI) data while presenting ballroom dancing and neutral video clips with long durations (∼100 s each) to 41 professional ballroom dancers (19 pairs of dance partners) and 39 age- and sex-matched nondancers. Our findings revealed that dancers exhibited broader and stronger neural similarities across the whole brain when watching dancing video clips, as compared to the control group. These increased neural similarities could be interpreted in at least two distinct ways. First, neural similarities in certain brain regions within the motor control circuit (i.e., frontal cortical-basal ganglia-thalamic circuit) were significantly correlated with dance-related information (e.g., dance partners' cooperation duration), which reinforced the impact of long-term dance training on neural synchronization. Second, neural similarities in other brain regions (e.g., memory-related brain regions) were significantly correlated with subjects' impression of the viewed videos (i.e., whether they have watched before, familiarity, and liking), which may not necessarily be directly linked to long-term dance training. Altogether, our study provided solid evidence for synchronized neural mechanisms in professional dancers due to long-term dance training.

Deep learning for detection of age-related macular degeneration: A systematic review and meta-analysis of diagnostic test accuracy studies.

OBJECTIVE: To evaluate the diagnostic accuracy of deep learning algorithms to identify age-related macular degeneration and to explore factors impacting the results for future model training. METHODS: Diagnostic accuracy studies published in PubMed, EMBASE, the Cochrane Library, and ClinicalTrails.gov before 11 August 2022 which employed deep learning for age-related macular degeneration detection were identified and extracted by two independent researchers. Sensitivity analysis, subgroup, and meta-regression were performed by Review Manager 5.4.1, Meta-disc 1.4, and Stata 16.0. The risk of bias was assessed using QUADAS-2. The review was registered (PROSPERO CRD42022352753). RESULTS: The pooled sensitivity and specificity in this meta-analysis were 94% (P = 0, 95% CI 0.94-0.94, I2 = 99.7%) and 97% (P = 0, 95% CI 0.97-0.97, I2 = 99.6%), respectively. The pooled positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the area under the curve value were 21.77(95% CI 15.49-30.59), 0.06 (95% CI 0.04-0.09), 342.41 (95% CI 210.31-557.49), and 0.9925, respectively. Meta-regression indicated that types of AMD (P = 0.1882, RDOR = 36.03) and layers of the network (P = 0.4878, RDOR = 0.74) contributed to the heterogeneity. CONCLUSIONS: Convolutional neural networks are mostly adopted deep learning algorithms in age-related macular degeneration detection. Convolutional neural networks, especially ResNets, are effective in detecting age-related macular degeneration with high diagnostic accuracy. Types of age-related macular degeneration and layers of the network are the two essential factors that impact the model training process. Proper layers of the network will make the model more reliable. More datasets established by new diagnostic methods will be used to train deep learning models in the future, which will benefit for fundus application screening, long-range medical treatment, and reducing the workload of physicians.

The effect of background liked music on acute pain perception and its neural correlates.

Music shows tremendous promise in pain relief, especially when considering its non-pharmacological nature. However, our understanding of the precise mechanisms behind music-induced analgesia (MIA) remains poor. The positive emotional state induced by music is one of the key components explaining MIA. To test this possibility and reveal its neural correlates, the present study applied nociceptive laser stimuli to 28 healthy participants when their liked or disliked songs were played as background music, or when they were resting in silence. Differences among conditions were quantified by self-reports of pain intensity and unpleasantness, as well as brain activations in response to acute laser stimuli. As expected, liked music significantly lowered pain ratings to acute painful stimuli compared to disliked music and no music. Consistent with this observation, brain activations in response to acute painful stimuli were deceased within brain areas encoding sensory components of pain, such as the right precentral and postcentral gyri (PreCG/PoCG), brain areas related to affective components of pain, such as the anterior cingulate cortex and bilateral putamen, and brain areas associated with motor control and avoidance reactions to pain, such as the left cerebellum, when liked music was played in the background in comparison to disliked music. Importantly, the relationship between music listening and differences in pain ratings of two music conditions was mediated by the magnitude of right PreCG/PoCG and left cerebellum activations. These findings deepened our understanding of the analgesic benefits of background liked music, a property relevant to clinical applications.

Elevated dementia risk, cognitive decline, and hippocampal atrophy in multisite chronic pain.

Numerous studies have investigated the impacts of common types of chronic pain (CP) on patients' cognitive function and observed that CP was associated with later dementia. More recently, there is a growing recognition that CP conditions frequently coexist at multiple body sites and may bring more burdens on patients' overall health. However, whether and how multisite CP (MCP) contributes to an increased risk of dementia, compared to single-site CP (SCP) and pain-free (PF), is largely unclear. In the current study, utilizing the UK Biobank cohort, we first investigated dementia risk in individuals (n = 354,943) with different numbers of coexisting CP sites using Cox proportional hazards regression models. We then applied generalized additive models to investigate whether MCP leads to excessive deterioration of participants' (n = 19,116) cognition and brain structure. We found that individuals with MCP were associated with significantly higher dementia risk, broader and faster cognitive impairment, and greater hippocampal atrophy than both PF individuals and those with SCP. Moreover, the detrimental effects of MCP on dementia risk and hippocampal volume aggravated along with the number of coexisting CP sites. Mediation analyses further revealed that the decline of fluid intelligence in MCP individuals was partially mediated by hippocampal atrophy. Our results suggested that cognitive decline and hippocampal atrophy interact biologically and may underlie the increased risk of dementia associated with MCP.

Transcutaneous Auricular Vagus Nerve Stimulation Facilitates Cortical Arousal and Alertness.

Transcutaneous auricular vagus nerve stimulation (taVNS) is a promising noninvasive technique with potential beneficial effects on human emotion and cognition, including cortical arousal and alertness. However, it remains unclear how taVNS could improve cortical arousal and alertness, which are crucial for consciousness and daily task performance. Here, we aimed to estimate the modulatory effect of taVNS on cortical arousal and alertness and to reveal its underlying neural mechanisms. Sixty subjects were recruited and randomly assigned to either the taVNS group (receiving taVNS for 20 min) or the control group (receiving taVNS for 30 s). The effects of taVNS were evaluated behaviorally using a cue-target pattern task, and neurologically using a resting-state electroencephalogram (EEG). We found that taVNS facilitated the reaction time for the targets requiring right-hand responses and attenuated high-frequency alpha oscillations under the close-eye resting state. Importantly, taVNS-modulated alpha oscillations were positively correlated with the facilitated target detection performance, i.e., reduced reaction time. Furthermore, microstate analysis of the resting-state EEG when the eyes were closed illustrated that taVNS reduced the mean duration of microstate C, which has been proven to be associated with alertness. Altogether, this work provided novel evidence suggesting that taVNS could be an enhancer of both cortical arousal and alertness.

Neural processes responsible for the translation of sustained nociceptive inputs into subjective pain experience.

Tracking and predicting the temporal structure of nociceptive inputs is crucial to promote survival, as proper and immediate reactions are necessary to avoid actual or potential bodily injury. Neural activities elicited by nociceptive stimuli with different temporal structures have been described, but the neural processes responsible for translating nociception into pain perception are not fully elucidated. To tap into this issue, we recorded electroencephalographic signals from 48 healthy participants receiving thermo-nociceptive stimuli with 3 different durations and 2 different intensities. We observed that pain perception and several brain responses are modulated by stimulus duration and intensity. Crucially, we identified 2 sustained brain responses that were related to the emergence of painful percepts: a low-frequency component (LFC, < 1 Hz) originated from the insula and anterior cingulate cortex, and an alpha-band event-related desynchronization (α-ERD, 8-13 Hz) generated from the sensorimotor cortex. These 2 sustained brain responses were highly coupled, with the α-oscillation amplitude that fluctuated with the LFC phase. Furthermore, the translation of stimulus duration into pain perception was serially mediated by α-ERD and LFC. The present study reveals how brain responses elicited by nociceptive stimulation reflect the complex processes occurring during the translation of nociceptive information into pain perception.

Culture-sex interaction in self-report empathy: The theory and meta-analyses.

Empathy is sharing and understanding others' emotions. Recently, researchers identified larger Western-Asian cultural differences in self-report empathy with females relative to males (i.e., the culture-sex interaction theory). Neglecting this phenomenon, previous researchers focused on identifying the cultural impact on empathy per se and reported divergent results. This meta-analysis aims to reveal the heterogeneity of the earlier publications and decode the heterogeneity as per the culture-sex interaction. The current results suggested the following: First, the cultural impact on empathy increased along with three sex stratification categories (male-only, mixed-sex, and female-only, in that order). Second, the effect size statistically differed between the binary classifications of sex (female-only > male-only). Third, the mixed-sex samples' effect size was positively regressed on the samples' sex ratio (i.e., percentage of females). The current results revealed the heterogeneity of previous publications and highlighted the significance of the culture-sex interaction effect on empathy for future investigations.

The association between ballroom dance training and empathic concern: Behavioral and brain evidence.

Dance is unique in that it is a sport and an art simultaneously. Beyond improving sensorimotor functions, dance training could benefit high-level emotional and cognitive functions. Duo dances also confer the possibility for dancers to develop the abilities to recognize, understand, and share the thoughts and feelings of their dance partners during the long-term dance training. To test this possibility, we collected high-resolution structural and resting-state functional magnetic resonance imaging (MRI) data from 43 expert-level ballroom dancers (a model of long-term exposure to duo dance training) and 40 age-matched and sex-matched nondancers, and measured their empathic ability using a self-report trait empathy scale. We found that ballroom dancers showed higher scores of empathic concern (EC) than controls. The EC scores were positively correlated with years with dance partners but negatively correlated with the number of dance partners for ballroom dancers. These behavioral results were supported by the structural and functional MRI data. Structurally, we observed that the gray matter volumes in the subgenual anterior cingulate cortex (ACC) and EC scores were positively correlated. Functionally, the connectivity between ACC and occipital gyrus was positively correlated with both EC scores and years with dance partners. In addition, the relationship between years with dance partners and EC scores was indirect-only mediated by the ACC-occipital gyrus functional connectivity. Therefore, our findings provided solid evidence for the close link between long-term ballroom dance training and empathy, which deepens our understanding of the neural mechanisms underlying this phenomenon.

Sex difference in trait empathy is encoded in the human anterior insula.

Females are considered the more empathic sex. This conventional view, however, has been challenged in the past few decades with mixed findings. These heterogeneous findings could be caused by the fact that empathy is a complex and multifaceted construct. To clarify whether sex differences exist in certain dimensions of empathy and whether they are associated with specific neural bases, this study measured trait empathy using the interpersonal reactivity index (IRI) and collected brain structural and functional magnetic resonance imaging data in a large sample of healthy participants (206 males vs. 302 females). We found that females scored higher in the personal distress (PD) subscale than males, but they were comparable to males in other IRI subscales. Sex difference in PD was encoded by brain structural (e.g. gray matter volume in left anterior insula [AI]) and functional (e.g. resting-state functional connectivity between left AI and temporoparietal junction/inferior frontal gyrus) characteristics. Notably, the relationship between sex and PD was indirect-only and serially mediated by AI-associated structural and functional characteristics. Altogether, our results suggested that sex difference existed in self-oriented affective empathy (i.e. PD) and highlighted the importance of the AI, both structurally and functionally, in mediating the sex difference in trait empathy.