bluuebunny/crossref_metadata_2025 huggingface dataset:
Short- and long-term mortality of subarachnoid hemorrhage according to hospital volume and severity using a nationwide multicenter registry study
Authors: Park Sang-Won , Lee Ji Young , Heo Nam Hun , Han James Jisu , Lee Eun Chae , Hong Dong-Yong , Lee Dong-Hun , Lee Man Ryul , Oh Jae Sang
Published: August 2022

Introduction

Recent improvements in treatment for subarachnoid hemorrhage (SAH) have decreased the mortality rates; however, the outcomes of SAH management are dependent on many other factors. In this study, we used nationwide, large-scale, observational data to investigate short- and long-term mortality rates after SAH treatment and the influence of patient severity and hospital volume.

Patients and methods

We selected patients with SAH treated with clipping and coiling from the South Korean Acute Stroke Assessment Registry. High- and low-volume hospitals performed ≥20 clipping and coiling procedures and <20 clipping and coiling procedures per year, respectively. Short- and long-term mortality were tracked using data from the Health Insurance Review and Assessment Service.

Results

Among 2,634 patients treated using clipping and coiling, 1,544 (58.6%) and 1,090 (41.4%) were hospitalized in high- and low-volume hospitals, respectively, and 910 (34.5%) and 1,724 (65.5%) were treated with clipping and coiling, respectively. Mortality rates were 13.5, 14.4, 15.2, and 16.1% at 3 months, 1, 2, and 4 years, respectively. High-volume hospitals had a significantly lower 3-month mortality rate. Patients with mild clinical status had a significantly lower 3-month mortality rate in high-volume hospitals than in low-volume hospitals. Patients with severe clinical status had significantly lower 1- and 2-year mortality rates in high-volume hospitals than in low-volume hospitals.

Conclusion

Short- and long-term mortality in patients with SAH differed according to hospital volume. In the modern endovascular era, clipping and coiling can lead to better outcomes in facilities with high stroke-care capabilities.
High-frequency repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex may reduce impulsivity in patients with methamphetamine use disorders: A pilot study
Authors: Liu Qingming , Xu Xingjun , Cui Huimin , Zhang Lei , Zhao Zhiyong , Dong Da , Shen Ying
Published: August 2022

Background

Individuals who use methamphetamine (MA) for a long period of time may experience decreased inhibition and increased impulsivity. In order to reduce impulsivity or improve inhibitory control ability, high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) has attracted much attention of researchers. Recent studies on addiction have shown that rTMS can stimulate different brain regions to produce different therapeutic effects. Recent work also suggests that HF-rTMS over right dorsolateral prefrontal cortex (DLPFC) does not affect the impulsivity of patients with alcohol use disorder; while HF-rTMS over left DLPFC could improve the impulsivity of patients with alcohol use disorder and cigarette smokers. However, it should be noted that empirical studies applying HF-rTMS over left DLPFC of patients with MA use disorders (MAUD) (to evaluate its effect on impulsivity) are still lacking.

Methods

Twenty-nine patients with MAUD underwent five sessions of HF-rTMS on the left DLPFC per week for 4 consecutive weeks. The cue-induced craving and stop-signal and NoGo task were assessed pre-rTMS and post-rTMS (at the end of the 4-week rTMS treatment). In addition, 29 healthy controls were recruited. There was no rTMS intervention for the controls, the performance of the stop-signal and NoGo task was evaluated on them.

Results

In total, HF-rTMS of the left DLPFC significantly decreased MA-dependent patients’ cue-induced craving and stop-signal reaction time (SSRT). For SSRT, the pre-test of experimental group was significantly higher than the score of control group. In the experimental group, the pre-test score was significantly higher than the post-test score. For Go and stop-signal delay (SSD), the pre-test scores of the experimental group was significantly lower than the scores of the control group. No significant difference was found between the pre-test and the post-test scores of the experimental group.

Conclusion

Add-on HF-rTMS of left DLPFC may be an effective intervention for reducing impulsivity and cue-induced craving of patients with MAUD. Future research with a control group of MAUD that does not undergo the treatment is needed to confirm the effectiveness.
Widespread cortical thinning, excessive glutamate and impaired linguistic functioning in schizophrenia: A cluster analytic approach
Authors: Liang Liangbing , Silva Angélica M. , Jeon Peter , Ford Sabrina D. , MacKinley Michael , Théberge Jean , Palaniyappan Lena
Published: August 2022

Introduction

Symptoms of schizophrenia are closely related to aberrant language comprehension and production. Macroscopic brain changes seen in some patients with schizophrenia are suspected to relate to impaired language production, but this is yet to be reliably characterized. Since heterogeneity in language dysfunctions, as well as brain structure, is suspected in schizophrenia, we aimed to first seek patient subgroups with different neurobiological signatures and then quantify linguistic indices that capture the symptoms of “negative formal thought disorder” (i.e., fluency, cohesion, and complexity of language production).

Methods

Atlas-based cortical thickness values (obtained with a 7T MRI scanner) of 66 patients with first-episode psychosis and 36 healthy controls were analyzed with hierarchical clustering algorithms to produce neuroanatomical subtypes. We then examined the generated subtypes and investigated the quantitative differences in MRS-based glutamate levels [in the dorsal anterior cingulate cortex (dACC)] as well as in three aspects of language production features: fluency, syntactic complexity, and lexical cohesion.

Results

Two neuroanatomical subtypes among patients were observed, one with near-normal cortical thickness patterns while the other with widespread cortical thinning. Compared to the subgroup of patients with relatively normal cortical thickness patterns, the subgroup with widespread cortical thinning was older, with higher glutamate concentration in dACC and produced speech with reduced mean length of T-units (complexity) and lower repeats of content words (lexical cohesion), despite being equally fluent (number of words).

Conclusion

We characterized a patient subgroup with thinner cortex in first-episode psychosis. This subgroup, identifiable through macroscopic changes, is also distinguishable in terms of neurochemistry (frontal glutamate) and language behavior (complexity and cohesion of speech). This study supports the hypothesis that glutamate-mediated cortical thinning may contribute to a phenotype that is detectable using the tools of computational linguistics in schizophrenia.
A generalized deep learning network for fractional anisotropy reconstruction: Application to epilepsy and multiple sclerosis
Authors: Gaviraghi Marta , Ricciardi Antonio , Palesi Fulvia , Brownlee Wallace , Vitali Paolo , Prados Ferran , Kanber Baris , Gandini Wheeler-Kingshott Claudia A. M.
Published: August 2022

Fractional anisotropy (FA) is a quantitative map sensitive to microstructural properties of tissues in vivo and it is extensively used to study the healthy and pathological brain. This map is classically calculated by model fitting (standard method) and requires many diffusion weighted (DW) images for data quality and unbiased readings, hence needing the acquisition time of several minutes. Here, we adapted the U-net architecture to be generalized and to obtain good quality FA from DW volumes acquired in 1 minute. Our network requires 10 input DW volumes (hence fast acquisition), is robust to the direction of application of the diffusion gradients (hence generalized), and preserves/improves map quality (hence good quality maps). We trained the network on the human connectome project (HCP) data using the standard model-fitting method on the entire set of DW directions to extract FA (ground truth). We addressed the generalization problem, i.e., we trained the network to be applicable, without retraining, to clinical datasets acquired on different scanners with different DW imaging protocols. The network was applied to two different clinical datasets to assess FA quality and sensitivity to pathology in temporal lobe epilepsy and multiple sclerosis, respectively. For HCP data, when compared to the ground truth FA, the FA obtained from 10 DW volumes using the network was significantly better (p <10−4) than the FA obtained using the standard pipeline. For the clinical datasets, the network FA retained the same microstructural characteristics as the FA calculated with all DW volumes using the standard method. At the subject level, the comparison between white matter (WM) ground truth FA values and network FA showed the same distribution; at the group level, statistical differences of WM values detected in the clinical datasets with the ground truth FA were reproduced when using values from the network FA, i.e., the network retained sensitivity to pathology. In conclusion, the proposed network provides a clinically available method to obtain FA from a generic set of 10 DW volumes acquirable in 1 minute, augmenting data quality compared to direct model fitting, reducing the possibility of bias from sub-sampled data, and retaining FA pathological sensitivity, which is very attractive for clinical applications.
Predicting and mitigating fatigue effects due to sleep deprivation: A review
Authors: Kayser Kylie C. , Puig Vannia A. , Estepp Justin R.
Published: August 2022

The deleterious effects of insufficient sleep have been well-established in the literature and can lead to a wide range of adverse health outcomes. Some of the most replicated findings demonstrate significant declines in cognitive functions such as vigilance and executive attention, psychomotor and cognitive speed, and working memory. Consequently, these decrements often lead individuals who are in a fatigued state to engage in substandard performance on everyday tasks. In the interest of curtailing these effects, prior work has attempted to identify mechanisms that predict fatigue onset and develop techniques to mitigate its negative consequences. Nonetheless, these results are often confounded by variables such as an individual’s resistance to fatigue, sleep history, and unclear distinctions about whether certain performance decrements are present due to fatigue or due to other confounding factors. Similar areas of research have provided approaches to produce models for the prediction of cognitive performance decrements due to fatigue through the use of multi-modal recording and analysis of fatigue-related responses. Namely, gathering and combining response information from multiple sources (i.e., physiological and behavioral) at multiple timescales may provide a more comprehensive representation of what constitutes fatigue onset in the individual. Therefore, the purpose of this review is to discuss the relevant literature on the topic of fatigue-related performance effects with a special emphasis on a variety of physiological and behavioral response variables that have shown to be sensitive to changes in fatigue. Furthermore, an increasing reliance on sleep loss, meant to assist in meeting the demands of modern society, has led to an upsurge in the relevance of identifying dependable countermeasures for fatigued states. As such, we will also review methods for the mitigation of performance effects due to fatigue and discuss their usefulness in regulating these effects. In sum, this review aims to inspire future work that will create opportunities to detect fatigue and mitigate its effects prior to the onset of cognitive impairments.
Amyloid pathology induces dysfunction of systemic neurotransmission in aged APPswe/PS2 mice
Authors: Oh Se Jong , Lee Namhun , Nam Kyung Rok , Kang Kyung Jun , Han Sang Jin , Lee Kyo Chul , Lee Yong Jin , Choi Jae Yong
Published: August 2022

This study aimed to investigate how amyloid pathology affects the functional aspects of neurotransmitter systems in Alzheimer’s disease. APPswe/PS2 mice (21 months of age) and wild-type (WT) mice underwent positron emission tomography (PET) and magnetic resonance spectroscopy (MRS). First, we obtained 18F-FDG and 18F-florbetaben PET scans to evaluate neuronal integrity and amyloid pathology. Second, 18F-FPEB and 18F-FMZ PET data were acquired to assess the excitatory-inhibitory neurotransmission. Third, to monitor the dopamine system, 18F-fallypride PET was performed. Amyloid PET imaging revealed that radioactivity was higher in the AD group than that in the WT group, which was validated by immunohistochemistry. In the cortical and limbic areas, the AD group showed a 25–27% decrease and 14–35% increase in the glutamatergic and GABAergic systems, respectively. The dopaminergic system in the AD group exhibited a 29% decrease in brain uptake compared with that in the WT group. A reduction in glutamate, N-acetylaspartate, and taurine levels was observed in the AD group using MRS. Our results suggest that dysfunction of the neurotransmitter system is associated with AD pathology. Among the systems, the GABAergic system was prominent, implying that the inhibitory neurotransmission system may be the most vulnerable to AD pathology.
Imaging and spectroscopic methods to investigate adult neurogenesis in vivo: New models and new avenues
Authors: Just Nathalie , Chevillard Pierre-Marie , Migaud Martine
Published: August 2022

Adult neurogenesis (AN) can be defined as the birth and development of new neurons in adulthood. Until the 1990s, AN was deemed not to happen after birth. Gradually, several groups demonstrated that specific zones of the brain of various species had a neurogenic potential. AN could be the key to treating a large range of neurodegenerative, neuropsychiatric, and metabolic diseases, with a better understanding of the mechanisms allowing for regeneration of new neurons. Despite this promising prospect, the existence of AN has not been validated in vivo in humans and therefore remains controversial. Moreover, the weight of AN-induced plasticity against other mechanisms of brain plasticity is not known, adding to the controversy. In this review, we would like to show that recent technical advances in brain MR imaging methods combined with improved models can resolve the debate.
Relationships between educational attainment, hypertension, and amyloid negative subcortical vascular dementia: The brain-battering hypothesis
Authors: Hwangbo Song , Kim Young Ju , Park Yu Hyun , Kim Hee Jin , Na Duk L. , Jang Hyemin , Seo Sang Won
Published: August 2022

Purpose

Many epidemiological studies suggest that lower education levels and vascular risk factors increase the likelihood of developing Alzheimer's disease dementia (ADD) and subcortical vascular dementia (SVaD). However, whether the brain-battering hypothesis can explain the relationship between education levels and the clinical diagnosis of dementia remains controversial. The objective of this study was to investigate whether vascular risk factors mediate the association between education level and the diagnosis of amyloid-beta positive (Aβ+) ADD and amyloid-beta negative (Aβ-) SVaD.

Methods

We analyzed 376 participants with Aβ normal cognition (Aβ- NC), 481 with Aβ+ ADD, and 102 with Aβ- SVaD. To investigate the association of education level and vascular risk factors with these diagnoses, multivariable logistic regression analysis was used, with age, sex, and APOE ε4 carrier status used as covariates. Path analysis was performed to investigate the mediation effects of hypertension on the diagnosis of Aβ- SVaD.

Results

The Aβ- SVaD group (7.9 ± 5.1 years) had lower education levels than did the Aβ- NC (11.8 ± 4.8 years) and Aβ+ ADD (11.2 ± 4.9 years) groups. The frequencies of hypertension and diabetes mellitus were higher in the Aβ- SVaD group (78.4 and 32.4%, respectively) than in the Aβ- NC (44.4 and 20.8%) and Aβ+ ADD (41.8 and 15.8%, respectively) groups. Increased education level was associated with a lower risk of Aβ- SVaD [odds ratio (OR) 0.866, 95% confidence interval (CI), 0.824–0.911], but not Aβ+ ADD (OR 0.971, 95% CI 0.940–1.003). The frequency of hypertension was associated with a higher risk of developing Aβ- SVaD (OR 3.373, 95% CI, 1.908–5.961), but not Aβ+ ADD (OR 0.884, 95% CI, 0.653–1.196). In the path analysis, the presence of hypertension partially mediated the association between education level and the diagnosis of Aβ- SVaD.

Conclusion

Our findings revealed that education level might influence the development of Aβ- SVaD through the brain-battering hypothesis. Furthermore, our findings suggest that suitable strategies, such as educational attainment and prevention of hypertension, are needed for the prevention of Aβ- SVaD.
Development and assessment of a risk prediction model for moderate-to-severe obstructive sleep apnea
Authors: Yan Xiangru , Wang Liying , Liang Chunguang , Zhang Huiying , Zhao Ying , Zhang Hui , Yu Haitao , Di Jinna
Published: August 2022

Background

OSA is an independent risk factor for several systemic diseases. Compared with mild OSA, patients with moderate-to-severe OSA have more severe impairment in the function of all organs of the body. Due to the current limited medical condition, not every patient can be diagnosed and treated in time. To enable timely screening of patients with moderate-to-severe OSA, we selected easily accessible variables to establish a risk prediction model.

Method

We collected 492 patients who had polysomnography (PSG), and divided them into the disease-free mild OSA group (control group), and the moderate-to-severe OSA group according to the PSG results. Variables entering the model were identified by random forest plots, univariate analysis, multicollinearity test, and binary logistic regression method. Nomogram were created based on the binary logistic results, and the area under the ROC curve was used to evaluate the discriminative properties of the nomogram model. Bootstrap method was used to internally validate the nomogram model, and calibration curves were plotted after 1,000 replicate sampling of the original data, and the accuracy of the model was evaluated using the Hosmer-Lemeshow goodness-of-fit test. Finally, we performed decision curve analysis (DCA) of nomogram model, STOP-Bang questionnaire (SBQ), and NoSAS score to assess clinical utility.

Results

There are 6 variables entering the final prediction model, namely BMI, Hypertension, Morning dry mouth, Suffocating awake at night, Witnessed apnea, and ESS total score. The AUC of this prediction model was 0.976 (95% CI: 0.962–0.990). Hosmer-Lemeshow goodness-of-fit test χ2 = 3.3222 (P = 0.1899 > 0.05), and the calibration curve was in general agreement with the ideal curve. The model has good consistency in predicting the actual occurrence of moderate-to-severe risk, and has good prediction accuracy. The DCA shows that the net benefit of the nomogram model is higher than that of SBQ and NoSAS, with has good clinical utility.

Conclusion

The prediction model obtained in this study has good predictive power for moderate-to-severe OSA and is superior to other prediction models and questionnaires. It can be applied to the community population for screening and to the clinic for prioritization of treatment.
Quantitative susceptibility mapping as an imaging biomarker for Alzheimer’s disease: The expectations and limitations
Authors: Uchida Yuto , Kan Hirohito , Sakurai Keita , Oishi Kenichi , Matsukawa Noriyuki
Published: August 2022

Alzheimer’s disease (AD) is the most common type of dementia and a distressing diagnosis for individuals and caregivers. Researchers and clinical trials have mainly focused on β-amyloid plaques, which are hypothesized to be one of the most important factors for neurodegeneration in AD. Meanwhile, recent clinicopathological and radiological studies have shown closer associations of tau pathology rather than β-amyloid pathology with the onset and progression of Alzheimer’s symptoms. Toward a biological definition of biomarker-based research framework for AD, the 2018 National Institute on Aging–Alzheimer’s Association working group has updated the ATN classification system for stratifying disease status in accordance with relevant pathological biomarker profiles, such as cerebral β-amyloid deposition, hyperphosphorylated tau, and neurodegeneration. In addition, altered iron metabolism has been considered to interact with abnormal proteins related to AD pathology thorough generating oxidative stress, as some prior histochemical and histopathological studies supported this iron-mediated pathomechanism. Quantitative susceptibility mapping (QSM) has recently become more popular as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. The association of cerebral susceptibility values with other pathological biomarkers for AD has been investigated using various QSM techniques; however, direct evidence of these associations remains elusive. In this review, we first briefly describe the principles of QSM. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood– brain barrier function in clinical settings for AD. Third, we mention the relationships among QSM, established biomarkers, and cognitive performance in AD. Finally, we discuss the role of QSM as an imaging biomarker as well as the expectations and limitations of clinically useful diagnostic and therapeutic implications for AD.
Real-time mental stress detection using multimodality expressions with a deep learning framework
Authors: Zhang Jing , Yin Hang , Zhang Jiayu , Yang Gang , Qin Jing , He Ling
Published: August 2022

Mental stress is becoming increasingly widespread and gradually severe in modern society, threatening people’s physical and mental health. To avoid the adverse effects of stress on people, it is imperative to detect stress in time. Many studies have demonstrated the effectiveness of using objective indicators to detect stress. Over the past few years, a growing number of researchers have been trying to use deep learning technology to detect stress. However, these works usually use single-modality for stress detection and rarely combine stress-related information from multimodality. In this paper, a real-time deep learning framework is proposed to fuse ECG, voice, and facial expressions for acute stress detection. The framework extracts the stress-related information of the corresponding input through ResNet50 and I3D with the temporal attention module (TAM), where TAM can highlight the distinguishing temporal representation for facial expressions about stress. The matrix eigenvector-based approach is then used to fuse the multimodality information about stress. To validate the effectiveness of the framework, a well-established psychological experiment, the Montreal imaging stress task (MIST), was applied in this work. We collected multimodality data from 20 participants during MIST. The results demonstrate that the framework can combine stress-related information from multimodality to achieve 85.1% accuracy in distinguishing acute stress. It can serve as a tool for computer-aided stress detection.
Peak frequency of the sensorimotor mu rhythm varies with autism-spectrum traits
Authors: Strang Caroline C. , Harris Alison , Moody Eric J. , Reed Catherine L.
Published: August 2022

Autism spectrum disorder (ASD) is a neurodevelopmental syndrome characterized by impairments in social perception and communication. Growing evidence suggests that the relationship between deficits in social perception and ASD may extend into the neurotypical population. In electroencephalography (EEG), high autism-spectrum traits in both ASD and neurotypical samples are associated with changes to the mu rhythm, an alpha-band (8–12 Hz) oscillation measured over sensorimotor cortex which typically shows reductions in spectral power during both one’s own movements and observation of others’ actions. This mu suppression is thought to reflect integration of perceptual and motor representations for understanding of others’ mental states, which may be disrupted in individuals with autism-spectrum traits. However, because spectral power is usually quantified at the group level, it has limited usefulness for characterizing individual variation in the mu rhythm, particularly with respect to autism-spectrum traits. Instead, individual peak frequency may provide a better measure of mu rhythm variability across participants. Previous developmental studies have linked ASD to slowing of individual peak frequency in the alpha band, or peak alpha frequency (PAF), predominantly associated with selective attention. Yet individual variability in the peak mu frequency (PMF) remains largely unexplored, particularly with respect to autism-spectrum traits. Here we quantified peak frequency of occipitoparietal alpha and sensorimotor mu rhythms across neurotypical individuals as a function of autism-spectrum traits. High-density 128-channel EEG data were collected from 60 participants while they completed two tasks previously reported to reliably index the sensorimotor mu rhythm: motor execution (bimanual finger tapping) and action observation (viewing of whole-body human movements). We found that individual measurement in the peak oscillatory frequency of the mu rhythm was highly reliable within participants, was not driven by resting vs. task states, and showed good correlation across action execution and observation tasks. Within our neurotypical sample, higher autism-spectrum traits were associated with slowing of the PMF, as predicted. This effect was not likely explained by volume conduction of the occipitoparietal PAF associated with attention. Together, these data support individual peak oscillatory alpha-band frequency as a correlate of autism-spectrum traits, warranting further research with larger samples and clinical populations.
Combinations of scalp acupuncture location for the treatment of post-stroke hemiparesis: A systematic review and Apriori algorithm-based association rule analysis
Authors: Wang Yu-Fang , Chen Wei-Yi , Lee Chang-Ti , Shen Yi-Ying , Lan Chou-Chin , Liu Guan-Ting , Kuo Chan-Yen , Chen Mao-Liang , Hsieh Po-Chun
Published: August 2022

Background

Post-stroke hemiparesis strongly affects stroke patients’ activities of daily living and health-related quality of life. Scalp acupuncture (SA) is reportedly beneficial for post-stroke hemiparesis. However, there is still no standard of SA for the treatment of post-stroke hemiparesis. Apriori algorithm-based association rule analysis is a kind of “if-then” rule-based machine learning method suitable for investigating the underlying rules of acupuncture point/location selections. This study aimed to investigate the core SA combinations for the treatment of post-stroke hemiparesis by using a systematic review and Apriori algorithm-based association rule analysis.

Methods

We conducted a systematic review to include relevant randomized controlled trial (RCT) studies investigating the effects of SA treatment in treating patients with post-stroke hemiparesis, assessed by the Fugl-Meyer Assessment (FMA) score. We excluded studies using herbal medicine or manual acupuncture.

Results

We extracted 33 SA locations from the 35 included RCT studies. The following SA styles were noted: International Standard Scalp Acupuncture (ISSA), WHO Standard Acupuncture Point Locations (SAPL), Zhu’s style SA, Jiao’s style SA, and Lin’s style SA. Sixty-one association rules were investigated based on the integrated SA location data.

Conclusions

SAPL_GV20 (Baihui), SAPL_GV24 (Shenting), ISSA_MS6_i (ISSA Anterior Oblique Line of Vertex-Temporal, lesion-ipsilateral), ISSA_MS7_i (ISSA Posterior Oblique Line of Vertex-Temporal, lesion-ipsilateral), ISSA_PR (ISSA Parietal region, comprised of ISSA_MS5, ISSA_MS6, ISSA_MS7, ISSA_MS8, and ISSA_MS9), and SAPL_Ex.HN3 (Yintang) can be considered the core SA location combination for the treatment of post-stroke hemiparesis. We recommend a core SA combination for further animal studies, clinical trials, and treatment strategies.
Stretch stress propels glutamine dependency and glycolysis in optic nerve head astrocytes
Authors: Pappenhagen Nathaniel , Yin Eric , Morgan Autumn B. , Kiehlbauch Charles C. , Inman Denise M.
Published: August 2022

Glaucoma is an optic neuropathy that leads to irreversible blindness, the most common subtype of which is typified by a chronic increase in intraocular pressure that promotes a stretch injury to the optic nerve head. In rodents, the predominant glial cell in this region is the optic nerve head astrocyte that provides axons with metabolic support, likely by releasing lactate produced through astrocytic glycolysis. Our primary hypothesis is that stretching of the optic nerve head astrocytes alters their metabolic activity, thereby advancing glaucoma-associated degeneration by compromising the metabolic support that the astrocytes provide to the axons in the optic nerve head. Metabolic changes in optic nerve head astrocytes were investigated by subjecting them to 24 h of 12% biaxial stretch at 1 Hz then measuring the cells’ bioenergetics using a Seahorse XFe24 Analyzer. We observed significant glycolytic and respiratory activity differences between control and stretched cells, including greater extracellular acidification and lower ATP-linked respiration, yet higher maximal respiration and spare capacity in stretched optic nerve head astrocytes. We also determined that both control and stretched optic nerve head astrocytes displayed a dependency for glutamine over pyruvate or long-chain fatty acids for fuel. The increased use of glycolysis as indicated by the extracellular acidification rate, concomitant with a dependency on glutamine, suggests the need to replenish NAD + for continued glycolysis and provision of carbon for TCA cycle intermediates. Stretch alters optic nerve astrocyte bioenergetics to support an increased demand for internal and external energy.
Prediction of pre-eclampsia by using radiomics nomogram from gestational hypertension patients
Authors: Liu Xue-Fei , Lu Jing-Jing , Li Meng-Die , Li Ying , Zeng An-Rong , Qiang Jin-Wei
Published: August 2022

Background

Pre-eclampsia (PE) is the main cause of death in maternal and prenatal morbidity. No effective clinical tools could be used for the prediction of PE. A radiomics nomogram based on diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps was established to predict PE from gestational hypertension (GH).

Materials and methods

A total of 138 patients with hypertensive disorders of pregnancy were continuously enrolled in the study prospectively, namely, 58 patients with PE and 80 patients with GH. The patients were randomly divided into a training cohort (n = 97) and a test cohort (n = 41). Radiomics features were extracted from DWI and ADC maps. The radiomics signature was constructed using a least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort. A radiomics nomogram was developed by combining the radiomics signature with the selected clinical risk factors. The area under the receiver operating characteristic (ROC) curves (AUC), specificity, sensitivity, accuracy, positive predictive value, and negative predictive values of the radiomics signature, clinical risk factors, and radiomics nomogram were calculated. Decision curve analysis (DCA) was performed to determine the clinical usefulness of the radiomics nomogram.

Results

The LASSO analysis finally included 11 radiomics features, which were defined as the radiomics signature. The individualized prediction nomogram was constructed by integrating the radiomics signature, maternal age, and body mass index (BMI). The nomogram exhibited a good performance both in the training cohort [AUC of 0.89 (95% CI, 0.82–0.95)] and test cohort [AUC of 0.85 (95% CI, 0.73–0.97)] for predicting PE from GH. The DCA indicated that clinicians and patients could benefit from the use of radiomics nomogram.

Conclusion

The radiomics nomogram could individually predict PE from GH. The nomogram could be conveniently used to facilitate the treatment decision for clinicians and patients.
Identification and characterization of N6-methyladenosine circular RNAs in the spinal cord of morphine-tolerant rats
Authors: Xing Manyu , Deng Meiling , Shi Yufei , Dai Jiajia , Ding Tong , Song Zongbin , Zou Wangyuan
Published: August 2022

Morphine tolerance (MT) is a tricky problem, the mechanism of it is currently unknown. Circular RNAs (circRNAs) serve significant functions in the biological processes (BPs) of the central nervous system. N6-methyladenosine (m6A), as a key post-transcriptional modification of RNA, can regulate the metabolism and functions of circRNAs. Here we explore the patterns of m6A-methylation of circRNAs in the spinal cord of morphine-tolerant rats. In brief, we constructed a morphine-tolerant rat model, performed m6A epitranscriptomic microarray using RNA samples collected from the spinal cords of morphine-tolerant rats and normal saline rats, and implemented the bioinformatics analysis. In the spinal cord of morphine-tolerant rats, 120 circRNAs with different m6A modifications were identified, 54 of which were hypermethylated and 66 of which were hypomethylated. Functional analysis of these m6A circRNAs found some important pathways involved in the pathogenesis of MT, such as the calcium signaling pathway. In the m6A circRNA-miRNA networks, several critical miRNAs that participated in the occurrence and development of MT were discovered to bind to these m6A circRNAs, such as miR-873a-5p, miR-103-1-5p, miR-107-5p. M6A modification of circRNAs may be involved in the pathogenesis of MT. These findings may lead to new insights into the epigenetic etiology and pathology of MT.
A retinal contribution to opioid-induced sleep disorders?
Authors: Bergum Nikolas , Berezin Casey-Tyler , Vigh Jozsef
Published: August 2022

Chronic opioid use is linked to persistent and severe sleep/wake disturbances in patients. These opioid-related sleep problems increase risk for developing opioid dependence, mood disorders and in turn overdose in chronic pain patients receiving opioid therapy. Despite the well-established link between long-term opioid use and sleep disorders, the mechanism by which opioids perturb sleep remains unclear. Interestingly, animal studies indicate that opioids disrupt sleep/wake behaviors by altering an animal’s ability to synchronize their circadian rhythms to environmental light cycles (i.e., photoentrainment). A specific subset of retinal cells known as intrinsically photosensitive retinal ganglion cells (ipRGCs) that express μ-opioid receptors are exclusively responsible for transmitting environmental light information to sleep/circadian centers in the brain. Thus, this review will focus on the effect of opioids on ipRGCs and their projection regions that are involved in the photoentrainment of sleep/wake behaviors. Lastly, we discuss the viability of ipRGCs as a potential therapeutic target for treating opioid-related sleep/wake problems.
Disrupting interaction between miR-132 and Mmp9 3′UTR improves synaptic plasticity and memory in mice
Authors: Kuzniewska Bozena , Rejmak Karolina , Nowacka Agata , Ziółkowska Magdalena , Milek Jacek , Magnowska Marta , Gruchota Jakub , Gewartowska Olga , Borsuk Ewa , Salamian Ahmad , Dziembowski Andrzej , Radwanska Kasia , Dziembowska Magdalena
Published: August 2022

As microRNAs have emerged to be important regulators of molecular events occurring at the synapses, the new questions about their regulatory effect on the behavior have araised. In the present study, we show for the first time that the dysregulated specific targeting of miR132 to Mmp9 mRNA in the mouse brain results in the increased level of Mmp9 protein, which affects synaptic plasticity and has an effect on memory formation. Our data points at the importance of complex and precise regulation of the Mmp9 level by miR132 in the brain.
The role of enkephalinergic systems in substance use disorders
Authors: Rysztak Lauren G. , Jutkiewicz Emily M.
Published: August 2022

Enkephalin, an endogenous opioid peptide, is highly expressed in the reward pathway and may modulate neurotransmission to regulate reward-related behaviors, such as drug-taking and drug-seeking behaviors. Drugs of abuse also directly increase enkephalin in this pathway, yet it is unknown whether or not changes in the enkephalinergic system after drug administration mediate any specific behaviors. The use of animal models of substance use disorders (SUDs) concurrently with pharmacological, genetic, and molecular tools has allowed researchers to directly investigate the role of enkephalin in promoting these behaviors. In this review, we explore neurochemical mechanisms by which enkephalin levels and enkephalin-mediated signaling are altered by drug administration and interrogate the contribution of enkephalin systems to SUDs. Studies manipulating the receptors that enkephalin targets (e.g., mu and delta opioid receptors mainly) implicate the endogenous opioid peptide in drug-induced neuroadaptations and reward-related behaviors; however, further studies will need to confirm the role of enkephalin directly. Overall, these findings suggest that the enkephalinergic system is involved in multiple aspects of SUDs, such as the primary reinforcing properties of drugs, conditioned reinforcing effects, and sensitization. The idea of dopaminergic-opioidergic interactions in these behaviors remains relatively novel and warrants further research. Continuing work to elucidate the role of enkephalin in mediating neurotransmission in reward circuitry driving behaviors related to SUDs remains crucial.
Comparison of two front-of-pack nutrition labels for Brazilian consumers using a smartphone app in a real-world grocery store: A pilot randomized controlled study
Authors: Silva Alessandro Rangel Carolino Sales , Ni Mhurchu Cliona , Anastácio Lucilene Rezende
Published: August 2022

One of the suggestions for improving the understanding of food labels is implementing front-of-pack nutrition labeling (FoPNL), where nutritional information is objectively made available to consumers. Scientific data on the best FoPNL model to be adopted for the Brazilian population is still emerging, especially in real-world purchase situations. This study aims to evaluate/compare the proposed Brazilian and Mexican FoPNL systems, on different outcome measures, using an application, in dairy foods available in a supermarket aisle. This pilot randomized controlled trial in a real-world purchase situation was conducted in June/July 2021. A total of 230 participants were randomly allocated to one of the three study arms (Mexican and Brazilian FoPNL systems or control—nutritional information table and ingredients list). Using a smartphone, the participants scanned a product barcode and received the allocated FoPNL (with information about excessive added sugars, sodium, and/or saturated fat content) or the control. After, they answered questions related to our primary outcome (decision to buy or not to buy a product) and secondary outcomes (perceived healthiness, facilitation of a quick purchase decision, and identification of excess nutrients). The Mexican FoPNL system performed better in the primary outcome (3.74 ± 1.34) and “facilitation of a quick purchase decision” (3.59 ± 1.31), compared to the control (3.28 ± 1.45;p = 0.043 and 3.11 ± 1.42; p = 0.029). The Mexican FoPNL system performed better in supporting consumers to identify dairy foods, among the selected sample in this study, high in added sugars than the control (82.2% and 63.5% of correct answers, respectively; p = 0.009). For saturated fats, the Brazilian FoPNL resulted in 93.1% of correct answers against 48.2% for the control and 58.9% for the Mexican system (p ≤ 0.001). The Mexican FoPNL system facilitated consumer decision-making on when to buy or not to buy a selected dairy product and in helping to quickly decide which dairy products to buy, among the selected sample in this study, compared to the control. Considering the right answers of critical nutrients in excess or not, both models of FoPNL, delivered by a smartphone app, performed well.
Construction and experimental verification of user-friendly molecular subtypes mediated by immune-associated genes in hepatocellular carcinoma
Authors: Yuan Juzheng , Wang Yang , Wang Xudan , Zhang Wenjie , Ding Rui , Yue Shuqiang , Li Xiao
Published: August 2022

Hepatocellular carcinoma (HCC) accounts for third most cancer death globally, and its prognosis continues to be poor even with many novel therapeutic approaches emerging. The advent of immunotherapy seems to offer new hope, but low response rates are an unresolved problem. To gain further knoeledge of the effect of immune-related genes in HCC, we examined the connection between immune-related genes and the immune microenvironment in HCC through the HCC transcriptome dataset. The study also aimed to construct and experimentally validate user-friendly molecular subtypes mediated by immune-related genes in HCC. The immune cell infiltration patterns differs in HCC adjacent non-disease tissues and cancerous tissues. Patients with HCC could be classified into 2 subtypes: subtype A and subtype B. Specifically, subtype A shows characteristics of a hot tumor, in which the infiltration of cells exhibiting antigens and the expression of other crucial factors associated with immune function are higher than in a cold tumor. In addition, we identified Hub genes for the different subtypes and constructed a prognostic prediction model based on six genes (KLRB1, KLF2, S100A9, MSC, ANXA5, and IMPDH1). Further experimental analysis of HCC samples exhibited that the expression levels of KLF2 and ANXA5 were associated with immune cell infiltration and expression of PD-L1 in cancer tissues. Our work suggests that the expression of immune-related genes has crucial effect on the tumor microenvironment and prognosis of HCC patients and may be associated with immunotherapeutic response, which provides new clues for the widespread and effective application of immunotherapy in HCC.
Prognostic value of 12 m7G methylation-related miRNA markers and their correlation with immune infiltration in breast cancer
Authors: Zhang Wenchuan , Zhang Shuwan , Wang Zhe
Published: August 2022

RNA guanine-7 methyltransferase (RNMT), in complex with FAM103A1, plays an important role in tumorigenesis and development. The aim of this study was to establish a prognostic model of RNMT and FAM103A1-based upstream microRNAs and explore its correlation with immune cell infiltration in breast cancer (BC) while investigating its potential prognostic value and verify the model by quantitative real-time polymerase chain reaction (qRT-PCR). The miRNA expression data upstream of the m7G methyltransferase complex RNMT/FAM103A1 in BC was obtained from The Cancer Genome Atlas and TargetScan databases. We performed univariate Cox regression, LASSO regression, Kaplan-Meier survival, and principal component analyses, along with risk prognostic modelling. Based on multivariate Cox regression analysis, a total of 12 m7G methyltransferase-related miRNAs were found. The model showed good accuracy for predicting the 1-, 3-,5-, and 10-year survival rates, and the areas under the curve were almost >0.7. To characterize the risk-level model constructed from 12 miRNAs, 12 differentially expressed mRNAs related to prognosis and immune infiltration were obtained. The prognosis of BC patients is well predicted by the risk model we constructed. This model is also closely related to immune infiltration, and new immunotherapy targets can be explored from this field.
Percutaneous ultrasound-guided core needle biopsy for the diagnosis of cardiac tumors: Optimizing the treatment strategy for patients with intermural and pericardial cardiac tumors
Authors: Xie Ying , Hong Zhi-liang , Zhao Yan-chun , Chen Sheng , Lin Yu-cheng , Wu Song-song
Published: August 2022

Objective

The aims of this study are to investigate the clinical value and practical safety of ultrasound-guided percutaneous core needle biopsy on diagnosing cardiac tumor and to discuss the treatment strategy for cardiac intermural and pericardial tumors.

Methods

The clinical data were retrospectively collected for patients with intermural and pericardial cardiac tumors. The patients were divided into groups of surgical resection, surgical resection after obtaining pathological tissue by PUS-CNB, and/or radiotherapy according to the treatment modality. Ultrasound-guided aspiration biopsy was divided into cardiac tumor biopsy and extracardiac lesion biopsy according to patient conditions. The surgical time was recorded, and the safety and clinical application value of PUS-CNB for the diagnosis of cardiac tumors were evaluated in terms of complications and satisfaction with pathological sampling.

Results

A total of 18 patient cases were collected, and PUS-CNB of cardiac tumors was performed in 8 cases, with sampling times averaging 15.6 ± 3.0 min. Four cases of cardiac tumors combined with extracardiac tumors were biopsied, with puncture times averaging 13.0 ± 2.9 min. All 12 biopsied patients had no postoperative complications. Except for 1 failed biopsy, the biopsies were successful and the pathological results were consistent with the clinical diagnosis with a satisfaction rate of 91.7%. Except for two cases of surgical resection, the rest were considered for conservative treatment. Surgical resection and/or biopsy were performed in six cases, and two cases were aggravated after surgery. The final pathology of all 17 cardiac tumors was malignant.

Conclusion

PUS-CNB is safe and effective, providing a simple and undemanding method for accurate diagnosis of cardiac intermural and pericardial tumors while avoiding unnecessary open-heart surgery.