Two neurosubtypes of ADHD different from the clinical phenotypes

Clinical and etiological variability of attention deficit hyperactivity disorder (ADHD) presents an obstacle to understand the disorder. The aim of this study was to disentangle the heterogeneity of ADHD using neuroimaging and a semi-supervised machine learning algorithm. We collected brain structural and functional magnetic resonance imaging (MRI) data and clinical profiles of 183 children with ADHD and 396 neurotypical controls from 7 independent sites. We also used an external validation set with 750 subjects. We adopted a semi-supervised clustering method to subtype ADHD by regional volumetric measures of gray matter, white matter, and fractional amplitude of low frequency fluctuation (fALFF). In addition, split sample test, leave-one-site-out test and external validation were applied to evaluate the reproducibility and stability of ADHD subtypes. Two stable and reproducible neurosubtypes of ADHD were disclosed, which were proved by the split-sample test and leave-one-site-out validation. The structural and functional patterns of ADHD subtypes were also stable in the external validation set. The current two neurosubtypes differed in clinical manifestations and volumetric gray matter, white matter volume and fALFF patterns. The current neurosubtypes of ADHD which were different from clinical phenotypes could facilitate understanding the underlying neuropathological and neurobiological mechanism of the disorder.

CT-based radiomics for predicting radio-chemotherapy response and overall survival in nonsurgical esophageal carcinoma

Background

To predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images.

Methods

This study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS.

Results

To predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively.

Conclusions

This study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival.

A review of multi-modal magnetic resonance imaging studies on perimenopausal brain: a hint towards neural heterogeneity

The population ageing process worldwide is leading to an increasing number of women in the perimenopausal phase. Many of the perimenopausal symptoms, such as headache, depression, insomnia, and cognitive decline, are neurological in nature. Therefore, the study of the perimenopausal brain is of great importance. In addition, relevant studies can also provide an imaging basis for multiple therapies to treat perimenopausal symptoms. Because of its non-invasive nature, magnetic resonance imaging (MRI) has now been widely applied to the study of perimenopausal brains, revealing alterations in the brain associated with symptoms during the menopause transition. In this review, we collected papers and works of literature on the perimenopausal brain using MRI techniques in the Web of Science database. We firstly described the general principles and analysis methods of different MRI modalities briefly and then reviewed the structural, functional, perfusion, and metabolic compounds changes in the brain of perimenopausal women respectively, and described the latest advances in probing the perimenopausal brain using MRI, resulting in summary diagrams and figures. Based on the summary of existing works of the literature, this review further provided a perspective on multi-modal MRI studies in the perimenopausal brain, suggesting that population-based, multi-center, and longitudinal studies will be beneficial to the comprehensive understanding of changes in the perimenopausal brain. In addition, we found a hint towards neural heterogeneity in the perimenopausal brain, which should be addressed by future MRI studies to provide more help for the precise diagnosis and personalized treatment of perimenopausal symptoms. KEY POINTS: • Perimenopause is not only a physiological transition but also a period of neurological transition. • Multi-modal MRI studies have revealed that perimenopause is accompanied by alterations in the brain, which is implicated in many perimenopausal symptoms. • The diversity in the multi-modal MRI findings may give a hint to neural heterogeneity in the perimenopausal brain.

Immediate visual reproduction negatively correlates with brain entropy of parahippocampal gyrus and inferior occipital gyrus in bipolar II disorder adolescents

BACKGROUND

Brain entropy reveals complexity and irregularity of brain, and it has been proven to reflect brain complexity alteration in disease states. Previous studies found that bipolar disorder adolescents showed cognitive impairment. The relationship between complexity of brain neural activity and cognition of bipolar II disorder (BD-II) adolescents remains unclear.

METHODS

Nineteen BD-II patients (14.63 ±1.57 years old) and seventeen age-gender matched healthy controls (HCs) (14.18 ± 1.51 years old) were enlisted. Entropy values of all voxels of the brain in resting-state functional MRI data were calculated and differences of them between BD-II and HC groups were evaluated. After that, correlation analyses were performed between entropy values of brain regions showing significant entropy differences and clinical indices in BD-II adolescents.

RESULTS

Significant differences were found in scores of immediate visual reproduction subtest (VR-I, p = 0.003) and Stroop color-word test (SCWT-1, p = 0.015; SCWT-2, p = 0.004; SCWT-3, p = 0.003) between the two groups. Compared with HCs, BD-II adolescents showed significant increased brain entropy in right parahippocampal gyrus and right inferior occipital gyrus. Besides, significant negative correlations between brain entropy values of right parahippocampal gyrus, right inferior occipital gyrus and immediate visual reproduction subtest scores were observed in BD-II adolescents.

CONCLUSIONS

The findings of the present study suggested that the disrupted function of corticolimbic system is related with cognitive abnormality of BD-II adolescents. And from the perspective temporal dynamics of brain system, the current study, brain entropy may provide available evidences for understanding the underlying neural mechanism in BD-II adolescents.

Glucose uptake and distribution across the human skeleton using state-of-the-art total-body PET/CT

A growing number of studies have demonstrated that the skeleton is an endocrine organ that is involved in glucose metabolism and plays a significant role in human glucose homeostasis. However, there is still a limited understanding of the in vivo glucose uptake and distribution across the human skeleton. To address this issue, we aimed to elucidate the detailed profile of glucose uptake across the skeleton using a total-body positron emission tomography (PET) scanner. A total of 41 healthy participants were recruited. Two of them received a 1-hour dynamic total-body ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET scan, and all of them received a 10-minute static total-body ¹⁸F-FDG PET scan. The net influx rate (K_i) and standardized uptake value normalized by lean body mass (SUL) were calculated as indicators of glucose uptake from the dynamic and static PET data, respectively. The results showed that the vertebrae, hip bone and skull had relatively high K_i and SUL values compared with metabolic organs such as the liver. Both the K_i and SUL were higher in the epiphyseal, metaphyseal and cortical regions of long bones. Moreover, trends associated with age and overweight with glucose uptake (SUL_max and SUL_mean) in bones were uncovered. Overall, these results indicate that the skeleton is a site with significant glucose uptake, and skeletal glucose uptake can be affected by age and dysregulated metabolism.

[Analysis of the direct economic burden of measles cases and its influencing factors in Shanghai from 2017 to 2019]

Objective: To analyze the direct economic burden caused by measles cases in Shanghai from 2017 to 2019 and its influencing factors. Methods: A total of 161 laboratory-confirmed measles cases reported from January 1, 2017, to December 31, 2019, in Shanghai were included in the study through the "Measles Surveillance Information Reporting and Management System" of the "China Disease Surveillance Information Reporting and Management System". Through telephone follow-up and consulting hospital data, the basic information of population, medical treatment situation, medical treatment costs and other information were collected, and the direct economic burden of cases was calculated, including registration fees, examination fees, hospitalization fees, medical fees and other disease treatment expenses, as well as transportation and other expenses of cases. The multiple linear regression model was used to analyze the main influencing factors of the direct economic burden. Results: The age of 161 measles cases M (Q₁, Q₃) was 28.21 (13.33, 37.00) years. Male cases (56.52%) were more than female cases (43.48%). The largest number of cases was≥18 years old (70.81%). The total direct economic burden of 161 measles cases was 540 851.14 yuan, and the per capita direct economic burden was 3 359.32 yuan. The direct economic burden M (Q₁, Q₃) was 873.00 (245.01, 4 014.79) yuan per person. The results of multiple linear regression model analysis showed that compared with other and unknown occupations, central areas and non-hospitalized cases, the direct economic burden of measles cases was higher in scattered children, childcare children, students, and cadre staff in the occupational distribution, suburban areas and hospitalized, with the coefficient of β (95%CI) values of 0.388 (0.150-0.627), 0.297 (0.025-0.569), 0.327 (0.148-0.506) and 1.031 (0.853-1.209), respectively (all P values<0.05). Conclusion: The direct economic burden of some measles cases in Shanghai is relatively high. Occupation, area of residence and hospitalization are the main factors influencing the direct economic burden of measles cases.

Whole slide imaging-based deep learning to predict the treatment response of patients with non-small cell lung cancer

Background

This study developed and validated a deep learning (DL) model based on whole slide imaging (WSI) for predicting the treatment response to chemotherapy and radiotherapy (CRT) among patients with non-small cell lung cancer (NSCLC).

Methods

We collected the WSI of 120 nonsurgical patients with NSCLC treated with CRT from three hospitals in China. Based on the processed WSI, two DL models were established: a tissue classification model which was used to select tumor-tiles, and another model which predicted the treatment response of the patients based on the tumor-tiles (predicting the treatment response of each tile). A voting method was employed, by which the label of tiles with the greatest quantity from 1 patient would be used as the label of the patient.

Results

The tissue classification model had a great performance (accuracy in the training set/internal validation set =0.966/0.956). Based on 181,875 tumor-tiles selected by the tissue classification model, the model for predicting the treatment response demonstrated strong predictive ability (accuracy of patient-level prediction in the internal validation set/external validation set 1/external validation set 2 =0.786/0.742/0.737).

Conclusions

A DL model was constructed based on WSI to predict the treatment response of patients with NSCLC. This model can help doctors to formulate personalized CRT plans and improve treatment outcomes.

Sex differences in structural covariance network based on MRI cortical morphometry: effects on episodic memory

Sex differences in episodic memory (EM), remembering past events based on when and where they occurred, have been reported, but the neural mechanisms are unclear. T1-weighted images of 111 females and 61 males were acquired from the Dallas Lifespan Brain Study. Using surface-based morphometry and structural covariance (SC) analysis, we constructed structural covariance networks (SCN) based on cortical volume, and the global efficiency (Eglob) was computed to characterize network integration. The relationship between SCN and EM was examined by SC analysis among the top-n brain regions that were most relevant to EM performance. The number of SC connections (females: 3306; males: 437, P = 0.0212) and Eglob (females: 0.1845; males: 0.0417, P = 0.0408) of SCN in females were higher than those in males. The top-n brain regions with the strongest SC in females were located in auditory network, cingulo-opercular network (CON), and default mode network (DMN), and in males, they were located in frontoparietal network, CON, and DMN. These results confirmed that the Eglob of SCN in females was higher than males, sex differences in EM performance might be related to the differences in network-level integration. Our study highlights the importance of sex as a research variable in brain science.

[A preliminary report of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis to prevent parastomal hernia]

Objective: To examine the preliminary effect of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis for the prevention of parastomal hernia after abdominoperineal resection for rectal cancer. Methods: This study is a prospective case series study. From June 2021 to June 2022, patients with low rectal cancer underwent laparoscopic abdominoperineal resection combined with extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis at the First Department of General Surgery, Shaanxi Provincial People's Hospital were enrolled. The clinical data and postoperative CT images of patients were collected to analyze the incidence of surgical complication and parastomal hernia. Results: Totally 6 cases of patient were enrolled, including 3 males and 3 females, aging 72.5 (19.5) years (M(IQR)) (range: 55 to 79 years). The operation time was 250 (48) minutes (range: 190 to 275 minutes), the stoma operation time was 27.5 (10.7) minutes (range: 21 to 37 minutes), the bleeding volume was 30 (35) ml (range: 15 to 80 ml). All patients were cured and discharged without surgery-related complications. The follow-up time was 136 (105) days (range: 98 to 279 days). After physical examination and abdominal CT follow-up, no parastomal hernia occurred in the 6 patients up to this article. Conclusions: A method of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis is established. Permanent stoma can be completed with this method safely. It may have a preventive effect on the occurrence of parastomal hernia, which is worthy of further study.

Responsive manganese-based nanoplatform amplifying cGAS-STING activation for immunotherapy

BACKGROUND

The activation of the cyclic guanosine monophosphate-adenosine monophosphate synthase-stimulator of interferon genes (cGAS-STING) signaling pathway has attracted great attention for its ability to up-regulate innate immune response and thus enhance cancer immunotherapy. However, many STING agonists limit the further advancement of immunotherapy due to weak tumor responsiveness or low activation efficiency. The responsive and effective activation of cGAS-STING signaling in tumors is a highly challenging process.

METHODS

In this study, a manganese-based nanoplatform (MPCZ NPs) was constructed that could responsively and efficiently generate more manganese ions (Mn²⁺) and reactive oxygen species (ROS) to activate cGAS-STING signaling pathway. Briefly, manganese dioxide (MnO₂) was loaded with zinc protoporphyrin IX (ZPP) molecule and coated by polydopamine (PDA) embedded with NH₄HCO₃ to obtain MPCZ NPs. Additionally, MPCZ NPs were evaluated in vitro and in vivo for their antitumor effects by methyl thiazolyl tetrazolium (MTT) assay and TUNEL assays, respectively.

RESULTS

In this system, tumor responsiveness was achieved by exogenous (laser irradiation) and endogenous (high levels GSH) stimulation, which triggered the collapse or degradation of PDA and MnO₂. Moreover, the release of Mn²⁺ augmented the cGAS-STING signaling pathway and enhanced the conversion of hydrogen peroxide (H₂O₂) to hydroxyl radical (·OH) under NIR laser irradiation. Furthermore, the release of ZPP and the elimination of GSH by MPCZ NPs inhibited HO-1 activity and prevented ROS consumption, respectively.

CONCLUSIONS

This adopted open source and reduce expenditure strategy to effectively generate more ROS and Mn²⁺ to responsively activate cGAS-STING signaling pathway, providing a new strategy for improving immunotherapy.

Identifying individuals with attention‐deficit/hyperactivity disorder based on multisite resting‐state functional magnetic resonance imaging: A radiomics analysis

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, characterized by symptoms of age-inappropriate inattention, hyperactivity, and impulsivity. Apart from behavioral symptoms investigated by psychiatric methods, there is no standard biological test to diagnose ADHD. This study aimed to explore whether the radiomics features based on resting-state functional magnetic resonance (rs-fMRI) have more discriminative power for the diagnosis of ADHD. The rs-fMRI of 187 subjects with ADHD and 187 healthy controls were collected from 5 sites of ADHD-200 Consortium. A total of four preprocessed rs-fMRI images including regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), voxel-mirrored homotopic connectivity (VMHC) and network degree centrality (DC) were used in this study. From each of the four images, we extracted 93 radiomics features within each of 116 automated anatomical labeling brain areas, resulting in a total of 43,152 features for each subject. After dimension reduction and feature selection, 19 radiomics features were retained (5 from ALFF, 9 from ReHo, 3 from VMHC and 2 from DC). By training and optimizing a support vector machine model using the retained features of training dataset, we achieved the accuracy of 76.3% and 77.0% (areas under curve = 0.811 and 0.797) in the training and testing datasets, respectively. Our findings demonstrate that radiomics can be a novel strategy for fully utilizing rs-fMRI information to distinguish ADHD from healthy controls. The rs-fMRI-based radiomics features have the potential to be neuroimaging biomarkers for ADHD.

Cortical thickness alterations are associated with astrocytes and excitatory neuron-specific transcriptome signatures in pediatric bipolar disorder

Bipolar disorder (BD) is a heritable psychiatric disorder with a complex etiology that is often associated with cortical alterations. Morphometric studies in adults with BD are well established; however, few have examined cortical changes in pediatric BD (PBD). Additionally, the correlation between cortical thickness (CT) changes in PBD and gene expression remains elusive. Here, we performed an integrative analysis using neuroimaging data from 58 PBD individuals and the Allen human brain transcriptomic dataset. We applied partial least squares (PLS) regression analysis on structural MRI data and cortical gene expression, enrichment and specific cell type analysis to investigate the genetic correlates of CT alterations in PBD. We found the expression levels of PBD-related genes showed significant spatial correlations with CT differences. Further enrichment and specific cell type analysis revealed that transcriptome signatures associated with cortical thinning were enriched in synaptic signaling, ion channels, astrocytes, and excitatory neurons. Neurodevelopmental patterns of these genes showed significantly increased expression in the cerebellum, cortex, and subcortical regions during the adolescence period. These results highlight neurodevelopmental transcriptional changes could account for most of the observed correlations with CT differences in PBD, which offers a novel perspective to understand biological conceptualization mechanisms for the genetic correlates of CT alterations.

Application of photoacoustic computed tomography in biomedical imaging: A literature review

Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high-resolution deep-tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real-time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice.

Circadian clock regulates developmental time through ecdysone and juvenile hormones in Bombyx mori

The circadian clock plays an integral role in hormone biosynthesis and secretion. However, how the circadian clock precisely coordinates hormonal homeostasis to maintain normal animal development remains unclear. Here, we show that knocking out the core clock gene Cryptochrome 1 (Cry1) significantly delays the developmental time in Bombyx mori. This study focuses on the ecdysone and juvenile hormone signalling pathways of fifth instar larvae with the longest developmental time delay. We found that the mutant reduced prothoracicotropic hormone synthesis in the brain, and could not produce sufficient ecdysone in the prothoracic gland, resulting in a delayed peak of 20-hydroxyecdysone titre in the hemolymph of fifth instar larvae, prolonging developmental time. Moreover, further investigation revealed that the mutant enhanced juvenile hormone biosynthesis and signalling pathway and that this higher juvenile hormone titre also resulted in prolonged developmental time in fifth instar larvae. Our results provide insights into the molecular mechanisms by which the circadian clock regulates animal development by maintaining hormonal homeostasis.

Ultrasound Image-Based Deep Features and Radiomics for the Discrimination of Small Fat-Poor Angiomyolipoma and Small Renal Cell Carcinoma

We evaluated the performance of ultrasound image-based deep features and radiomics for differentiating small fat-poor angiomyolipoma (sfp-AML) from small renal cell carcinoma (SRCC). This retrospective study included 194 patients with pathologically proven small renal masses (diameter ≤4 cm; 67 in the sfp-AML group and 127 in the SRCC group). We obtained 206 and 364 images from the sfp-AML and SRCC groups with experienced radiologist identification, respectively. We extracted 4024 deep features from the autoencoder neural network and 1497 radiomics features from the Pyradiomics toolbox; the latter included first-order, shape, high-order, Laplacian of Gaussian and Wavelet features. All subjects were allocated to the training and testing sets with a ratio of 3:1 using stratified sampling. The least absolute shrinkage and selection operator (LASSO) regression model was applied to select the most diagnostic features. Support vector machine (SVM) was adopted as the discriminative classifier. An optimal feature subset including 45 deep and 7 radiomics features was screened by the LASSO model. The SVM classifier achieved good performance in discriminating between sfp-AMLs and SRCCs, with areas under the curve (AUCs) of 0.96 and 0.85 in the training and testing sets, respectively. The classifier built using deep and radiomics features can accurately differentiate sfp-AMLs from SRCCs on ultrasound imaging.

The LIM Domain Protein BmFHL2 Inhibits Egg Production in Female Silkworm, Bombyx mori

The female Bombyx mori accumulates a large amount of egg proteins, mainly Vg and 30K, during egg formation to provide nutrition for embryo development. The synthesis and transport of Vg have been extensively studied, particularly the regulation of Vg transcription induced by 20E; however, the mechanism of 30K protein synthesis is poorly studied. As a model organism of the order Lepidoptera, B. mori has high reproduction potential. In the present study, we found that the FHL2 homologous gene (BmFhl2) in B. mori is involved in inhibiting female egg formation by influencing the synthesis of 30K protein. Interference of BmFhl2 expression in silkworm females increased 30K protein synthesis, accelerated ovarian development, and significantly increased the number of eggs produced and laid; however, the 20E pathway was inhibited. The transcription levels of Vg and 30Kc19 were significantly downregulated following BmFhl2 overexpression in the silkworm ovarian cell line BmN. The Co-IP assay showed that the potential binding protein of BmFHL2 included three types of 30K proteins (30Kc12, 30Kc19, and 30Kc21). These results indicate that BmFHL2 participates in egg formation by affecting 30K protein in female B. mori.

[Application of the "virtual-real combination" experimental teaching model in Human Parasitology teaching: a case study of comprehensive schistosome experiments]

Information technology has become an important driver to facilitate higher education developments in the context of new medical sciences. A new "virtual-real combination" experimental teaching model was designed and created through integrating information technology with experimental teaching by Experimental Teaching Center of Basic Medical Sciences and Department of Pathogen Biology, Nanjing Medical University and was applied in Human Parasitology teaching, which achieved satisfactory teaching effectiveness. This new model showed effective to deepen the understanding of the basic human parasitology knowledge, improve the operative skills, and cultivate the moral literacy and comprehensive capability among medical students. This report presents the teaching protocols and implementation, teaching effectiveness and evaluation, and experiences of comprehensive schistosome experiments.

The evolution of marsupial social organization

It is generally believed that marsupials are more primitive than placentals mammals and mainly solitary living, representing the ancestral form of social organization of all mammals. However, field studies have observed pair and group-living in marsupial species, but no comparative study about their social evolution was ever done. Here, we describe the results of primary literature research on marsupial social organization which indicates that most species can live in pairs or groups and many show intra-specific variation in social organization. Using Bayesian phylogenetic mixed-effects models with a weak phylogenetic signal of 0.18, we found that solitary living was the most likely ancestral form (35% posterior probability), but had high uncertainty, and the combined probability of a partly sociable marsupial ancestor (65%) should not be overlooked. For Australian marsupials, group-living species were less likely to be found in tropical rainforest, and species with a variable social organization were associated with low and unpredictable precipitation representing deserts. Our results suggest that modern marsupials are more sociable than previously believed and that there is no strong support that their ancestral state was strictly solitary living, such that the assumption of a solitary ancestral state of all mammals may also need reconsideration.

Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan

An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18–87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p &lt; 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p &lt; 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.

Insights into AIE materials: A focus on biomedical applications of fluorescence

Aggregation-induced emission (AIE) molecules have garnered considerable interest since its first appearance in 2001. Recent studies on AIE materials in biological and medical areas have demonstrated that they show their promise as biomaterials for bioimaging and other biomedical applications. Benefiting from significant advantages of their high sensitivity, excellent photostability, and good biocompatibility, AIE-based materials provide dramatically improved analytical capacities for in vivo detection and demonstration of vital biological processes. Herein, we introduce the development history of AIE molecules and recent progress in areas of biotesting and bioimaging. Additionally, this review also offers an outlook for the potential applications of versatile AIE materials for tracing and treating pathological tissues, including overcoming challenges and feasible solutions.

Treatment planning computed tomography radiomics for predicting treatment outcomes and haematological toxicities in locally advanced cervical cancer treated with radiotherapy: A retrospective cohort study

OBJECTIVE

We evaluated whether radiomic features extracted from planning computed tomography (CT) scans predict clinical end points in patients with locally advanced cervical cancer (LACC) undergoing intensity-modulated radiation therapy and brachytherapy.

DESIGN

A retrospective cohort study.

SETTING

Xiangya Hospital of Central South University, Changsha, Hunan, China.

POPULATION

Two hundred and fifty-seven LACC patients who were treated with intensity-modulated radiotherapy from 2014 to 2017.

METHODS

Patients were allocated into the training/validation sets (3:1 ratio) using proportional random sampling, resulting in the same proportion of groups in the two sets. We extracted 254 radiomic features from each of the gross target volume, pelvis and sacral vertebrae. The sequentially backward elimination support vector machine algorithm was used for feature selection and end point prediction.

MAIN OUTCOMES AND MEASURES

Clinical end points include tumour complete response (CR), 5-year overall survival (OS), anaemia, and leucopenia.

RESULTS

A combination of ten clinicopathological parameters and 34 radiomic features performed best for predicting CR (validation balanced accuracy: 80.8%). The validation balanced accuracy of 54 radiomic features was 85.8% for OS, and their scores can stratify patients into the low-risk and high-risk groups (5-year OS: 95.5% versus 36.4%, p < 0.001). The clinical and radiomic models were also predictive of anaemia and leucopenia (validation balanced accuracies: 71.0% and 69.9%).

CONCLUSION

This study demonstrated that combining clinicopathological parameters with CT-based radiomics may have value for predicting clinical end points in LACC. If validated, this model may guide therapeutic strategy to optimise the effectiveness and minimise toxicity or treatment for LACC.

Perfusion heterogeneity of cerebral small vessel disease revealed via arterial spin labeling MRI and machine learning

Cerebral small vessel disease (CSVD) is associated with altered cerebral perfusion. However, global and regional cerebral blood flow (CBF) are highly heterogeneous across CSVD patients. The aim of this study was to identify subtypes of CSVD with different CBF patterns using an advanced machine learning approach. 121 CSVD patients and 53 healthy controls received arterial spin label MRI, T1 structural MRI and clinical measurements. Regional CBF were used to identify distinct perfusion subtypes of CSVD via a semi-supervised machine learning algorithm. Statistical analyses were used to explore alterations in CBF, clinical measures, gray and white matter volume between healthy controls and different subtypes of CSVD. Correlation analysis was used to assess the association between clinical measures and altered CBF in each CSVD subtype. Three subtypes of CSVD with distinct CBF patterns were found. Subtype 1 showed decreased CBF in the temporal lobe and increased CBF in the parietal and occipital lobe. Subtype 2 exhibited decreased CBF in the right hemisphere of the brain, and increased CBF in the left cerebrum. Subtype 3 demonstrated decreased CBF in the posterior part of the brain, and increased CBF in anterior part of the brain. The three subtypes also differed significantly in gender (p = 0.005), the proportion of subjects with lacune (p = 0.002), with periventricular white matter hyperintensity (p = 0.043), and CSVD burden score (p = 0.048). In subtype 3, it was found that widespread decreased CBF was correlated with total CSVD burden score (r = -0.324, p = 0.029). Compared with healthy controls, the three CSVD subtypes also showed distinct volumetric patterns of white matter. The current results associate different subtypes with different clinical and imaging phenotypes, which can improve the understanding of brain perfusion alterations of CSVD and can facilitate precision diagnosis of CSVD.