Congenital hypothyroidism and risk of subsequent autism spectrum disorder and attention-deficit/hyperactivity disorder in Taiwan.

AIM: Evidence suggests an association between maternal hypothyroidism and risk of attention-deficit/hyperactivity disorder (ADHD) or autism spectrum disorder (ASD) in offspring. We examined the risk of ASD and ADHD in individuals with congenital hypothyroidism (CHT). METHODS: A nationwide population-based cohort study enrolled a total of 1260 children younger than 12 years with a confirmed diagnosis of CHT and no prior diagnosis of any neurodevelopmental disorders, selected from the National Health Insurance Research Database of Taiwan between 1998 to 2013. In addition, 12,600 controls matched for sex, age, and residence were selected. Cox proportional hazards analysis was used to investigate the association among CHT, ASD, and ADHD. RESULTS: Children with CHT were associated with a higher incidence of ASD (7.1‰ vs 1.3‰, P < 0.001) and ADHD (39.7‰ vs 18.7‰, P < 0.001) than the control group. Cox regression analyses demonstrated that children with CHT were associated with elevated risks of ASD (hazard ratio [HR], 4.72 [95% confidence interval (CI), 2.08-10.70]) and ADHD (HR, 2.03 [95% CI, 1.49-2.77]), after adjusting for demographic data and family history of major psychiatric disorders, compared with the control group. CONCLUSION: Children with CHT were associated with approximately a two-fold increased risk of ADHD and a four-fold increased risk of ASD than the control group. Our study highlights the need for future research to elucidate the potential pathophysiology among CHD, ASD, and ADHD.

Distinct Effects of Major Affective Disorder Diagnoses and Suicidal Symptom Severity on Inhibitory Control Function and Proinflammatory Cytokines: Single-Site Analysis of 800 Adolescents and Adults.

BACKGROUND: Inhibitory control function and proinflammatory cytokines play a role in the pathomechanisms underlying major affective disorders and suicidal behavior. However, the distinct or interactive effects of major affective disorders and suicidal symptom severity on inhibitory control function and proinflammatory cytokines remain unclear. METHODS: This study included 287 patients with bipolar disorder, 344 with major depressive disorder, and 169 healthy controls. We categorized the participants into three groups on the basis of Montgomery-Åsberg Depression Rating Scale (MADRS) item 10 (suicidal symptoms) score: 0, 2 or 3, and ≥4. The participants completed the go/no-go task and the measurements for C-reactive protein (CRP) and tumor necrosis factor-α (TNF-α) levels. RESULTS: Errors in the go/no-go task were associated with suicidality (p = .040), regardless of the severity of suicidal symptoms and diagnosis. An elevated CRP level was especially associated with MADRS item 10 score ≥ 4 (p = 0.001). Increased TNF-α level could distinguish bipolar disorder from major depressive disorder (p < .001). DISCUSSION: Our study indicated the distinct effects of major affective disorder diagnosis and suicide symptom severity on inhibitory control function and CRP and TNF-α levels. Importantly, individuals with the poorest inhibitory control function and highest CRP levels had more severe suicidal symptoms.

DisenSemi: Semi-Supervised Graph Classification via Disentangled Representation Learning.

Graph classification is a critical task in numerous multimedia applications, where graphs are employed to represent diverse types of multimedia data, including images, videos, and social networks. Nevertheless, in the real world, labeled graph data are always limited or scarce. To address this issue, we focus on the semi-supervised graph classification task, which involves both supervised and unsupervised models learning from labeled and unlabeled data. In contrast to recent approaches that transfer the entire knowledge from the unsupervised model to the supervised one, we argue that an effective transfer should only retain the relevant semantics that align well with the supervised task. We introduce a novel framework termed in this article, which learns disentangled representation for semi-supervised graph classification. Specifically, a disentangled graph encoder is proposed to generate factorwise graph representations for both supervised and unsupervised models. Then, we train two models via supervised objective and mutual information (MI)-based constraints, respectively. To ensure the meaningful transfer of knowledge from the unsupervised encoder to the supervised one, we further define an MI-based disentangled consistency regularization between two models and identify the corresponding rationale that aligns well with the current graph classification task. Experiments conducted on various publicly available datasets demonstrate the effectiveness of our .

New CDDO Arylboronate Ester Derivatives with High Selectivity and Low Toxicity.

As an oleanolic acid derivative, CDDO-Me lacks selectivity for tumors. Based on the high reactive oxygen species (ROS) level in cancer cells, compound 4 was selected from 17 new CDDO arylboronate ester derivatives. A preliminary study revealed that 4 displayed the highest selectivity for cancer cells. Furthermore, 4 could be transformed to 4H by ROS to increase its covalent binding ability and antiproliferation effect (IC50 of 2.11 vs 0.37 µM) in BGC-823 cells. Interestingly, 4 increased ROS levels to induce apoptosis in BGC-823 cells. Moreover, the LD50 of 4 (91.2 mg/kg) was much greater than that of CDDO-Me (61.7 mg/kg) in ICR mice. A pharmacokinetic study indicated that 4 could be transformed to 4H in vivo. In addition, 4 exhibited a greater tumor inhibition rate (86.2%) than CDDO-Me (51.7%). Overall, the design of 4 provided an effective modification strategy for CDDO to increase the selectivity for cancer cells.

Risk of Periodontitis in Adolescents With Attention Deficit Hyperactivity Disorder: A Cohort Study of 81,055 Participants.

OBJECTIVES: Previous studies have demonstrated poor oral hygiene in children with attention deficit hyperactivity disorder (ADHD). However, the association between ADHD and periodontitis is still unclear. METHODS: In all, 16,211 adolescents with ADHD and 162,110 age- and sex-matched controls participated in the study between 2001 and 2011. To identify the occurrence of periodontitis, the participants were followed up till the end of 2011. Confounding factors, including smoking, diabetes, and depressive disorder, were assessed and adjusted in the Cox regression models. RESULTS: Adolescents with ADHD (HR: 2.29) were more likely to develop periodontitis later in life than controls. We additionally observed the beneficial effect of atomoxetine (HR: 0.42) on the periodontitis risk among adolescents with ADHD. However, this finding should be interpreted cautiously given the small sample (n = 290) of children taking atomoxetine in the present study. CONCLUSIONS: ADHD is an independent risk factor for subsequent periodontitis development. Oral health should be closely monitored in adolescents with ADHD. Future investigation of the shared pathomechanisms between periodontitis and ADHD is warranted.

Species-level understanding of the bacterial community in Daqu based on full-length 16S rRNA gene sequences.

Daqu is used as the fermentation starter of Baijiu and contributes diversified functional microbes for saccharifying grains and converting sugars into ethanol and aroma components in Baijiu products. Daqu is mainly classified into three types, namely low (LTD), medium (MTD) and high (HTD) temperature Daqu, according to the highest temperatures reached in their fermentation processes. In this study, we used the PacBio small-molecule real-time (SMRT) sequencing technology to determine the full-length 16 S rRNA gene sequences from the metagenomes of 296 samples of different types of Daqu collected from ten provinces in China, and revealed the bacterial diversity at the species level in the Daqu samples. We totally identified 310 bacteria species, including 78 highly abundant species (with a relative abundance >0.1% each) which accounted for 91.90% of the reads from all the Daqu samples. We also recognized the differentially enriched bacterial species in different types of Daqu, and in the Daqu samples with the same type but from different provinces. Specifically, Lactobacillales, Enterobacterales and Bacillaceae were significantly enriched in the LTD, MTD and HTD groups, respectively. The potential co-existence and exclusion relationships among the bacteria species involved in all the Daqu samples and in the LTD, MTD and HTD samples from a specific region were also identified. These results provide a better understanding of the bacterial diversity in different types of Daqu at the species level.

Risks of developing major psychiatric disorders among child and adolescent intensive care unit survivors.

BACKGROUND: The mental health of child and adolescent intensive care unit (ICU) survivors is increasingly being researched. However, the literature on how various types of critical illness influence specific psychiatric disorders remains limited. METHODS: This study analyzed the data of 8704 child and adolescent ICU survivors and 87,040 age-, sex-, family income-, and residence-matched controls who were followed from enrollment to the end of 2013; the data covered the period from 1996 to 2013 and were extracted from a nationwide data set. The primary outcomes were the risks of five major psychiatric disorders (MPDs), namely schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), obsessive compulsive disorder (OCD), and posttraumatic stress disorder (PTSD). RESULTS: Relative to the controls, the child and adolescent ICU survivors (mean age = 10.33 years) exhibited higher risks of developing five MPDs. The associated hazard ratios (HRs) and confidence intervals (CIs) are as follows: PTSD, HR = 4.67, 95 % CI = 2.42-9.01; schizophrenia, HR = 3.19, 95 % CI = 2.27-4.47; BD, HR = 2.02, 95 % CI = 1.33-3.05; OCD, HR = 1.96, 95 % CI = 1.21-3.16; and MDD, HR = 1.68, 95 % CI = 1.44-1.95. The risks of developing MPDs varied across multiple types of critical illness related to ICU admission. CONCLUSIONS: The risks of MPDs were significantly higher among the child and adolescent ICU survivors than among the controls. The development of appropriate MPD prevention strategies should be emphasized for this vulnerable population.

A portable affective computing system for identifying mate preference.

Recognizing an individual's preference state for potential romantic partners based on electroencephalogram (EEG) signals holds significant practical value in enhancing matchmaking success rates and preventing romance fraud. Despite some progress has been made in this field, challenges such as high-dimensional feature space and channel redundancy limited the technology's practical application. The aim of this study is to explore the most discriminative EEG features and channels, in order to enhance the recognition performance of the system, while maximizing the portable and practical value of EEG-based systems for recognizing romantic attraction. To achieve this goal, we first conducted an interesting simulated dating experiment to collect the necessary data. Next, EEG features were extracted from various dimensions, including band power and asymmetry index features. Then, we introduced a novel method for EEG feature and channel selection that combines the sequential forward selection (SFS) algorithm with the frequency-based feature subset integration (FFSI) algorithm. Finally, we used the random forest classifier (RFC) to determine a person's preference state for potential romantic partners. Experimental results indicate that the optimal feature subset, selected using the SFS-FFSI method, attained an average classification accuracy of 88.42%. Notably, these features were predominantly sourced from asymmetry index features of electrodes situated in the frontal, parietal, and occipital lobes.

New insights into membrane fouling in coagulation-ultrafiltration by cake characteristics analysis: A case study with PACl-Al13 and PACl.

Membrane fouling is a bottleneck issue that hindered the further application of ultrafiltration technology. To alleviate membrane fouling, coagulation-ultrafiltration (C-UF) process using polyaluminum chloride (PACl) and PACl-Al13 with high proportion of Al13O4(OH)247+ as coagulants, respectively, were investigated at various pH conditions. Results indicated that an increase in solution pH contributed to larger floc size and looser floc structure for both PACl and PACl-Al13. It was conducive to the formation of more porous cake, as evidenced by mean pore area and pore area distribution of cake, leading to lower reversible fouling. Furthermore, humic acid (HA) removal presented a trend of first increasing and then decreasing with the increase of pH. The optimal HA removal was achieved at pH 6 regardless of coagulant type, suggesting that the slightest irreversible fouling should be occurred at this point. Interestingly, the irreversible fouling with PACl coagulant achieved a minimum value at pH 9, while the minimal irreversible fouling with PACl-Al13 was observed at pH 6. We speculated that the cake formed by PACl could further intercept HA prior to UF process at alkaline pH. Furthermore, compared with PACl, PACl-Al13 had a stronger charge neutralization ability, thus contributing to more compact floc structure and higher HA removal at various pH conditions. By UF fractionation measurement, higher HA removal for PACl-Al13 was due to higher removal of HA with molecular weight less than 50 kDa.

GALA: Graph Diffusion-based Alignment with Jigsaw for Source-free Domain Adaptation.

Source-free domain adaptation is a crucial machine learning topic, as it contains numerous applications in the real world, particularly with respect to data privacy. Existing approaches predominantly focus on Euclidean data, such as images and videos, while the exploration of non-Euclidean graph data remains scarce. Recent graph neural network (GNN) approaches could suffer from serious performance decline due to domain shift and label scarcity in source-free adaptation scenarios. In this study, we propose a novel method named Graph Diffusion-based Alignment with Jigsaw (GALA) tailored for source-free graph domain adaptation. To achieve domain alignment, GALA employs a graph diffusion model to reconstruct source-style graphs from target data. Specifically, a score-based graph diffusion model is trained using source graphs to learn the generative source styles. Then, we introduce perturbations to target graphs via a stochastic differential equation instead of sampling from a prior, followed by the reverse process to reconstruct source-style graphs. We feed them into an off-the-shelf GNN and introduce class-specific thresholds with curriculum learning, which can generate accurate and unbiased pseudo-labels for target graphs. Moreover, we develop a simple yet effective graph mixing strategy named graph jigsaw to combine confident graphs and unconfident graphs, which can enhance generalization capabilities and robustness via consistency learning. Extensive experiments on benchmark datasets validate the effectiveness of GALA. The source code is available at https://github.com/luo-junyu/GALA.

A novel insight of degradation ibuprofen in aqueous by catalytic ozonation with supported catalyst: Supports effect on ozone mass transfer.

Catalytic ozonation is an effective wastewater purification process. However, the low ozone mass transfer in packed bubble columns leads to low ozone utilization efficiency (OUE), poor organic degradation performance, and high energy consumption. Therefore, there is an urgent need to develop efficient supported catalysts that can enhance mass transfer and performance. However, the reaction mechanism of the support on ozone mass transfer remains unclear, which hinders the development of catalytic ozonation applications. In this study, lava rocks (LR)-supported catalysts, specifically CuMn2O4@LR and MnO2Co3O4@LR, were proposed for catalytic ozonation of IBP degradation due to their superior catalytic activity, stability, and high OUE. Addition of CuMn2O4@LR or MnO2Co3O4@LR increased IBP removal efficiency from 85% to 91% or 88%, and reduced energy consumption from 2.86 to 2.14 kWh/m3 or 2.60 kWh/m3, respectively. This improvement was attributed to LR-supported catalysts enhancing mass transfer and promoting O3 decomposition to generate •OH and •O2-, leading to IBP degradation. Furthermore, this study investigated the effects of ozone dose, supporter sizes, and catalyst components on ozone-liquid mass transfer. The results revealed that the size of the supporter influenced stacked porosity and consequently affected ozone mass transfer. Larger-sized LR (kLa= 0.172 min-1) exhibited better mass transfer compared to smaller-sized supports. Based on these findings, it was concluded that both CuMn2O4@LR and MnO2Co3O4@LR are potential catalysts for catalytic ozonation in residual IBP degradation of pharmaceutical wastewater, and LR showed good credibility as a catalyst supporter. Understanding the effects of supporters and active components on ozone mass transfer provides a fundamental principle for designing supported catalysts in catalytic ozonation applications.

Sexually transmitted infection and teenage pregnancy in adolescents having parents with schizophrenia: a retrospective cohort study of 64,350 participants.

BACKGROUND: The risks of sexually transmitted infections (STIs) and teenage pregnancy in the offspring of parents with schizophrenia remain unknown. METHODS: From the Taiwan National Health Insurance Research Database, 5,850 individuals born between 1980 and 1999 having any parent with schizophrenia and 58,500 age-, sex-, income- and residence-matched controls without parents with severe mental disorders were enrolled in 1996 or on their birthdate and followed up to the end of 2011. Those who contracted any STI or became pregnant in adolescence during the follow-up period were identified. RESULTS: Cox regression analyses demonstrated that offspring of parents with schizophrenia (hazard ratio [HR]: 1.21, 95% confidence interval [CI]: 1.02-1.44), especially daughters (HR: 1.30, 95% CI: 1.06-1.58), were more likely to contract any STI later in life than the control comparisons. In addition, daughters of parents with schizophrenia had an elevated risk of being pregnant in their adolescence (HR: 1.47, 95% CI: 1.29-1.67) compared with those having no parents with severe mental disorders. DISCUSSION: The positive relationship between parental schizophrenia and offspring STIs and teenage pregnancy necessitates clinicians and public health officers to closely monitor the sexual health in the offspring of parents with schizophrenia so that optimal and prompt preventive measures can be taken in the at-risk group.

Risk of traumatic brain injury among patients with ADHD and their unaffected siblings.

BACKGROUND: As the relationship between attention deficit hyperactivity disorder (ADHD) and traumatic brain injury (TBI) is gaining increasing attention, the TBI risk in patients with ADHD, unaffected siblings of ADHD probands, and non-ADHD controls remains unclear. METHODS: Overall, 18,645 patients with ADHD, 18,880 unaffected siblings of ADHD probands, and 188,800 age-/sex-matched controls were followed up from enrollment to the end of 2011. The cases of TBI and TBI requiring hospitalization were identified during follow-up. RESULTS: Patients with ADHD (hazard ratio [HR]: 1.57) and unaffected siblings (HR: 1.20) had an increased risk of any TBI compared with non-ADHD controls. Surprisingly, the likelihood of developing TBI requiring hospitalization during follow-up was higher in the unaffected siblings group (HR: 1.21) than in the control group, whereas it was lower in the ADHD probands group (HR: 0.86). CONCLUSIONS: Patients with ADHD and unaffected siblings of ADHD probands were more likely to develop any TBI during follow-up than controls. Unaffected siblings of patients with ADHD exhibited the highest risk of subsequent TBI requiring hospitalization compared with patients with ADHD and healthy controls. Therefore, TBI risk in patients with ADHD and their unaffected siblings would require further investigation. IMPACT: ADHD diagnosis and ADHD trait are associated with risk of traumatic brain injury (TBI). Both patients with ADHD and their unaffected siblings were more likely to develop TBI during the follow-up compared with the control group. TBI requiring hospitalization occurred more in the sibling group than in the proband group. TBI risk should be closely monitored among unaffected siblings of patients with ADHD.

Magnetic field-assisted adsorption of phosphate on biochar loading amorphous Zr-Ce (carbonate) oxide composite.

For metal-based phosphate adsorbents, the dispersity and utilization of surface metal active sites are crucial factors in their adsorption performance and synthesis cost. In this study, a biochar material modified with amorphous Zr-Ce (carbonate) oxides (BZCCO-13) was synthesized for the phosphate uptake, and the adsorption process was enhanced by magnetic field. The beside-magnetic field was shown to have a better influence than under-magnetic field on adsorption, with maximum adsorption capacities (123.67 mg P/g) 1.14-fold greater than that without magnetic field. The beside-magnetic field could also accelerate the adsorption rate, and the time to reach 90% maximum adsorption capacity decreased by 83%. BZCCO-13 has a wide range of application pHs from 5.0 to 10.0, with great selectivity and reusability. The results of XPS and ELNES showed that the "magnetophoresis" of Ce3+ under the magnetic field was the main reason for the enhanced adsorption performance. In addition, increased surface roughness, pore size and oxygen vacancies, enhanced mass transfer by Lorentz force under a magnetic field, all beneficially influenced the adsorption process. The mechanism of phosphate adsorption by BZCCO-13 could be attributed to electrostatic attraction and CO32-dominated ligand exchange. This study not only provided an effective strategy for designing highly effective phosphate adsorbents, but also provides a new light on the application of rare earth metal-based adsorbent in magnetic field.

Low-energy shock waves promote the cisplatin chemosensitivity of human osteosarcoma MNNG/HOS cells via the P2X7/Akt/mTOR pathway.

Background: The current dilemma of osteosarcoma treatment is the resistance of chemotherapeutic drugs after long-term usage, which also introduces life-threatening side effects. Methods and results: To minimize chemoresistance in osteosarcoma patients, the authors applied shock waves (SWs) to human osteosarcoma MNNG/HOS cells, then evaluated the cell viability and extracellular ATP levels, and further investigated the effect of SWs on cisplatin (DDP) cytotoxicity in MNNG/HOS cells. The authors' results showed that 400 SW pulses at 0.21 mJ/mm2 exhibited little influence on the MNNG/HOS cell viability. In addition, this SW condition significantly promoted the extracellular ATP release in MNNG/HOS cells. Importantly, low-energy SWs obviously increased Akt and mammalian target of rapamycin (mTOR) phosphorylation and activation in MNNG/HOS cells, which could be partially reversed in the presence of P2X7 siRNA. The authors also found that low-energy SWs strongly increased the DDP sensitivity of MNNG/HOS cells in the absence of P2X7. Conclusions: For the first time, the authors found that SW therapy reduced the DDP resistance of MNNG/HOS osteosarcoma cells when the ATP receptor P2X7 was downregulated. SW therapy may provide a novel treatment strategy for chemoresistant human osteosarcoma.

Epicardial adipose tissue in obesity with heart failure with preserved ejection fraction: Cardiovascular magnetic resonance biomarker study.

BACKGROUND: Obesity has become a serious public health issue, significantly elevating the risk of various complications. It is a well-established contributor to Heart failure with preserved ejection fraction (HFpEF). Evaluating HFpEF in obesity is crucial. Epicardial adipose tissue (EAT) has emerged as a valuable tool for validating prognostic biomarkers and guiding treatment targets. Hence, assessing EAT is of paramount importance. Cardiovascular magnetic resonance (CMR) imaging is acknowledged as the gold standard for analyzing cardiac function and morphology. We hope to use CMR to assess EAT as a bioimaging marker to evaluate HFpEF in obese patients. AIM: To assess the diagnostic utility of CMR for evaluating heart failure with preserved ejection fraction [HFpEF; left ventricular (LV) ejection fraction ≥ 50%] by measuring the epicardial adipose tissue (EAT) volumes and EAT mass in obese patients. METHODS: Sixty-two obese patients were divided into two groups for a case-control study based on whether or not they had heart failure with HFpEF. The two groups were defined as HFpEF+ and HFpEF-. LV geometry, global systolic function, EAT volumes and EAT mass of all subjects were obtained using cine magnetic resonance sequences. RESULTS: Forty-five patients of HFpEF- group and seventeen patients of HFpEF+ group were included. LV mass index (g/m2) of HFpEF+ group was higher than HFpEF- group (P < 0.05). In HFpEF+ group, EAT volumes, EAT volume index, EAT mass, EAT mass index and the ratio of EAT/[left atrial (LA) left-right (LR) diameter] were higher compared to HFpEF- group (P < 0.05). In multivariate analysis, Higher EAT/LA LR diameter ratio was associated with higher odds ratio of HFpEF. CONCLUSION: EAT/LA LR diameter ratio is highly associated with HFpEF in obese patients. It is plausible that there may be utility in CMR for assessing obese patients for HFpEF using EAT/LA LR diameter ratio as a diagnostic biomarker. Further prospective studies, are needed to validate these proof-of-concept findings.

Proinflammatory cytokine levels, cognitive function, and suicidal symptoms of adolescents and young adults with major depressive disorder.

Whether proinflammatory cytokine dysregulation and cognitive dysfunction are associated with suicidal symptoms in adolescents and young adults with major depressive disorder (MDD) remains uncertain. We assessed the cognitive function and proinflammatory cytokine levels of 43 and 51 patients aged 15-29 years with MDD and severe and mild suicidal symptoms, respectively, as well as those of 85 age- and sex-matched healthy controls. Specifically, we measured serum levels of C-reactive protein, tumor necrosis factor-α (TNF-α), interleukin-2, and interleukin-6 and assessed cognitive function by using working memory and go/no-go tasks. The severity of the patients' suicidal symptoms was based on Item 10 of the Montgomery-Åsberg Depression Rating Scale; scores of ≤ 2 and ≥ 4 indicated mild and severe symptoms, respectively. The patients with MDD and severe suicidal symptoms had higher levels of C-reactive protein (p = .019) and TNF-α (p = .002) than did the patients with mild symptoms or the healthy controls. The number of errors committed on the go/no-go by patients with MDD and severe suicidal symptoms (p = .001) was significantly higher than those by patients with MDD and mild symptoms or by controls. After adjusting for nonsuicidal depressive symptoms, we observed suicidal symptoms to be positively associated with TNF-α levels (p = .050) and errors on the go/no-go task (p = .021). Compared with mild suicidal symptoms, severe symptoms are associated with greater serum levels of proinflammatory cytokines and inferior cognitive function in adolescents and young adults with MDD.

A Comprehensive Survey on Deep Graph Representation Learning.

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining. Classic graph embedding methods follow the basic idea that the embedding vectors of interconnected nodes in the graph can still maintain a relatively close distance, thereby preserving the structural information between the nodes in the graph. However, this is sub-optimal due to: (i) traditional methods have limited model capacity which limits the learning performance; (ii) existing techniques typically rely on unsupervised learning strategies and fail to couple with the latest learning paradigms; (iii) representation learning and downstream tasks are dependent on each other which should be jointly enhanced. With the remarkable success of deep learning, deep graph representation learning has shown great potential and advantages over shallow (traditional) methods, there exist a large number of deep graph representation learning techniques have been proposed in the past decade, especially graph neural networks. In this survey, we conduct a comprehensive survey on current deep graph representation learning algorithms by proposing a new taxonomy of existing state-of-the-art literature. Specifically, we systematically summarize the essential components of graph representation learning and categorize existing approaches by the ways of graph neural network architectures and the most recent advanced learning paradigms. Moreover, this survey also provides the practical and promising applications of deep graph representation learning. Last but not least, we state new perspectives and suggest challenging directions which deserve further investigations in the future.

Application of metabolomics in oral squamous cell carcinoma.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is a prevalent malignancy affecting the head and neck region. The prognosis for OSCC patients remains unfavorable due to the absence of precise and efficient early diagnostic techniques. Metabolomics offers a promising approach for identifying distinct metabolites, thereby facilitating early detection and treatment of OSCC. OBJECTIVE: This review aims to provide a comprehensive overview of recent advancements in metabolic marker identification for early OSCC diagnosis. Additionally, the clinical significance and potential applications of metabolic markers for the management of OSCC are discussed. RESULTS: This review summarizes metabolic changes during the occurrence and development of oral squamous cell carcinoma and reviews prospects for the clinical application of characteristic, differential metabolites in saliva, serum, and OSCC tissue. In this review, the application of metabolomic technology in OSCC research was summarized, and future research directions were proposed. CONCLUSION: Metabolomics, detection technology that is the closest to phenotype, can efficiently identify differential metabolites. Combined with statistical data analyses and artificial intelligence technology, it can rapidly screen characteristic biomarkers for early diagnosis, treatment, and prognosis evaluations.

Dysfunction of circulating endothelial progenitor cells in major depressive disorder.

OBJECTIVES: Despite mounting evidence demonstrates circulating endothelial progenitor cells (cEPCs) quantitative changes in depression, no study has investigated cEPC functions in major depressive disorder (MDD). We investigated the role of cEPC adhesive and apoptotic functions in MDD. METHODS: We recruited 68 patients with MDD and 56 healthy controls (HCs). The depression symptoms, anxiety, psychosomatic symptoms, subjective cognitive dysfunction, quality of life, and functional disability were evaluated using the Hamilton Depression Rating Scale and Montgomery-Åsberg Depression Rating Scale, Hamilton Anxiety Rating Scale, Depression and Somatic Symptoms Scale (DSSS), Perceived Deficits Questionnaire-Depression, 12-Item Short Form Health Survey (SF-12), and Sheehan Disability Scale (SDS), respectively. Working memory and executive function were assessed using a 2-back task and Wisconsin Card Sorting Test (WCST). Inflammatory marker (soluble interleukin-6 receptor, C-reactive protein, and tumor necrosis factor-α receptor-1), cEPC adhesive, and apoptotic levels were measured using in vitro assays. RESULTS: The MDD patients showed significantly lower cEPC adhesive levels than the HCs, and this difference in adhesive function remained statistically significant even after adjusting for inflammatory marker levels. The cEPC adhesion levels were in inverse correlations with commission and omission errors in 2-back task, the percent perseverative response and percent perseverative errors in WCST, and the DSSS and SDS scores, but in positive correlations with SF-12 physical and mental component scores. cEPC apoptotic levels did not differ significantly between the groups. CONCLUSION: The findings indicate that cEPC adhesive function is diminished in MDD and impacts various aspects of cognitive and psychosocial functions associated with the disorder.