Diabetic nephropathy (DN) is one of the lethal manifestations of diabetic systemic microvascular disease. Elucidation of characteristic metabolic alterations during diabetic progression is critical to understand its pathogenesis and identify potential biomarkers and drug targets involved in the disease. In this study, (1)H nuclear magnetic resonance ((1)H NMR)-based metabonomics with correlative analysis was performed to study the characteristic metabolites, as well as the related pathways in urine and kidney samples of db/db diabetic mice, compared with age-matched wildtype mice. The time trajectory plot of db/db mice revealed alterations, in an age-dependent manner, in urinary metabolic profiles along with progression of renal damage and dysfunction. Age-dependent and correlated metabolite analysis identified that cis-aconitate and allantoin could serve as biomarkers for the diagnosis of DN. Further correlative analysis revealed that the enzymes dimethylarginine dimethylaminohydrolase (DDAH), guanosine triphosphate cyclohydrolase I (GTPCH I), and 3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase) were involved in dimethylamine metabolism, ketogenesis and GTP metabolism pathways, respectively, and could be potential therapeutic targets for DN. Our results highlight that metabonomic analysis can be used as a tool to identify potential biomarkers and novel therapeutic targets to gain a better understanding of the mechanisms underlying the initiation and progression of diseases.

Accurately predicting essential genes is important in many aspects of biology, medicine and bioengineering. In previous research, we have developed a machine learning based integrative algorithm to predict essential genes in bacterial species. This algorithm lends itself to two approaches for predicting essential genes: learning the traits from known essential genes in the target organism, or transferring essential gene annotations from a closely related model organism. However, for an understudied microbe, each approach has its potential limitations. The first is constricted by the often small number of known essential genes. The second is limited by the availability of model organisms and by evolutionary distance. In this study, we aim to determine the optimal strategy for predicting essential genes by examining four microbes with well-characterized essential genes. Our results suggest that, unless the known essential genes are few, learning from the known essential genes in the target organism usually outperforms transferring essential gene annotations from a related model organism. In fact, the required number of known essential genes is surprisingly small to make accurate predictions. In prokaryotes, when the number of known essential genes is greater than 2% of total genes, this approach already comes close to its optimal performance. In eukaryotes, achieving the same best performance requires over 4% of total genes, reflecting the increased complexity of eukaryotic organisms. Combining the two approaches resulted in an increased performance when the known essential genes are few. Our investigation thus provides key information on accurately predicting essential genes and will greatly facilitate annotations of microbial genomes.

Alzheimer's disease (AD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. Identifying altered neuronal gene expression in AD may provide diagnostic or therapeutic targets for AD. The present study aimed to identify differentially expressed genes (DEGs) and their further association with other biological processes that regulate causative factors for AD. The present study performed an integrated analysis of publicly available gene expression omnibus datasets of AD hippocampi. Gene ontology (GO) enrichment analyses, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein‑Protein interaction (PPI) network analysis were performed. The present study detected 295 DEGs (109 upregulated and 186 downregulated genes) in hippocampi between AD and control samples by integrating four datasets of gene expression profiles of hippocampi of patients with AD. Respiratory electron transport chain (GO: 0022904; P=1.64x10‑11) was the most significantly enriched GO term among biological processes, while for molecular functions, the most significantly enriched GO term was that of protein binding (GO: 0005515; P=3.03x10‑29), and for cellular components, the most significantly enriched GO term was that of the cytoplasm (GO: 0005737; P=8.67x10‑33). The most significant pathway in the KEGG analysis was oxidative phosphorylation (P=1.61x10‑13). PPI network analysis showed that the significant hub proteins contained β-actin (degree, 268), hepatoma-derived growth factor (degree, 218) and WD repeat‑containing protein 82 (degree, 87). The integrated analysis performed in the present study serves as a basis for identifying novel drug targets to develop improved therapies and interventions for common and devastating neurological diseases such as AD.

Schizophrenia patients often experience auditory hallucinations (AHs) and visual hallucinations (VHs). However, the degree and type of brain and retinal alterations associated with combined AHs and VHs in schizophrenia patients remain unknown. There is an urgent need for a study that investigates the trajectory of brain and retinal alterations in patients with first-episode untreated schizophrenia accompanied by combined AHs and VHs (FUSCHAV).

New methods for using ketamine in patients with propofol-electroconvulsive therapy-resistant depression (ECT-RD) are needed in the clinic. This study aimed to investigate the therapeutic efficacy of ketamine plus ECT in ECT-RD patients, along with the treatment-induced brain alterations. A total of 28 ECT-RD patients were intravenously injected with ketamine six times and treated with propofol-ECT six times alternately within two weeks. The Hamilton Depression Scale was used to assess the treatment effect. Global functional connectivity density (gFCD) and functional connectivity strength (FCS) were used to evaluate functional brain alterations. As compared with the propofol-ECT treatment group, the addition of ketamine could improve the therapeutic outcomes in patients with ECT-RD. The treatment increased gFCD in the left temporal and subgenual anterior cingulated cortex. Simultaneously, the treatment decreased FCS within the default mode network. Although increased functional connectivity could be sustained for 10 days, the clinical effect was only sustained 7 days, indicating that the clinical effect and functional brain alterations were disjointed. Ketamine plus propofol-ECT can obviously improve the effects of propofol-ECT in ECT-RD patients. However, the effect is limited in 7 days, suggesting the benefit is short-term.

In the present pilot study, we aimed to characterize the brain surface differences between 42 sporadic healthy individuals with AVHs (Hi-AVHs) and 50 healthy individuals without AVHs. The Auditory Hallucinations Rating Scale (AHRS) was used to assess the severity of AVHs, while the gyrification index and fractal dimensions were used to evaluate cerebral cortex complexity. We observed a significant increase of the gyrification index was located in the left superior temporal gyrus, the left temporoparietal junction, the left superior frontal gyrus, and the left parietal lobe. The fractal dimensions had significantly increased in the left Wernicke's area, the left Broca's areas and the left parietal lobe. Our pilot findings indicated gyrification index and fractal dimensions differences were only located in the left hemisphere between the groups of Hi-with and without AVHs. However, these differences did not correlate with the AVHs symptoms, and the non-hallucinating healthy individuals did not demonstrate corresponding reverse changes; hence we cannot postulate that cerebral cortex complexity alterations are related to AVHs. Our pilot study provides a clue for further studies aimed at investigating the brain features of Hi-AVHs.

Depression is a highly prevalent risk factor for both the onset of cardiovascular disease (CVD) and the mortality of CVD patients, and people suffering from CVD are more likely to develop depression than healthy individuals. The aim of this review is to summarize recent findings regarding the underlying relationship between CVD and depression. Literature search and review were conducted using PubMed, Google Scholar, Wanfang Med Online, and Baidu Scholar databases. CVD and depression are intimately related and researchers from around the world have proposed and validated various mechanisms that may potentially explain the comorbidity of CVD and depression. Recent studies have suggested that depression and CVD may manifest as two distinct clinical conditions in two different organs, the brain and the heart, respectively, but may also be linked by shared mechanisms. Of these, inflammation involving the immune system is thought to be a common mechanism of depression and heart disease, with specific inflammatory cytokines or pathways being potential targets for the prevention and treatment of the concurrent diseases. Therefore, inflammation may play an important role in bridging the link between depression and CVD, a finding that can have important clinical implications for the prevention and early intervention of these conditions.

Objective: To investigate whether APOE ε4 affects the association of verbal memory with neurodegeneration presented by the hippocampal volume/intracranial volume ratio (HpVR). Methods: The study sample included 371 individuals with normal cognition (NC), 725 subjects with amnestic mild cognitive impairment (aMCI), and 251 patients with mild Alzheimer's disease (AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who underwent the rey auditory verbal learning test (RAVLT). Multiple linear regression models were conducted to assess the effect of the APOE ε4∗HpVR interaction on RAVLT in all subjects and in each diagnostic group adjusting for age, gender and educational attainment, and global cognition. Results: In all subjects, there was no significant APOE ε4 × HpVR interaction for immediate recall or delayed recall (p > 0.05). However, in aMCI subjects, there was a significant APOE ε4 × HpVR interaction for delayed recall (p = 0.008), but not immediate recall (p = 0.15). More specifically, the detrimental effect of APOE ε4 on delayed recall altered by HpVR such that this effect was most evident among subjects with small to moderate HpVR, but this disadvantage was absent or even reversed among subjects with larger HpVR. No significant interaction was observed in the NC or AD group. Conclusion: These findings highlight a potential role of APOE ε4 status in affecting the association of hippocampus size with delayed recall memory in the early stage of AD.

Secondary KIT gene amplification leads to tyrosine kinase inhibitor resistance in anaplastic lymphoma kinase (ALK) fusion-positive advanced non-small cell lung cancer (NSCLC). The presence of the 4q12 amplicon causes the activation of downstream mast/stem cell growth factor receptor Kit (c-Kit) or platelet-derived growth factor receptor α (PDGFRA) signaling pathways. Therefore, in the present study, the association between the functional proteins phosphorylated c-Kit (p-c-Kit) and phosphorylated PDGFRA (p-PDGFRA) and the prognosis of ALK fusion NSCLC was investigated. Advanced stage NSCLC samples with ALK fusion were tested for their p-c-Kit and p-PDGFRA content by immunohistochemical staining, and for its association with crizotinib efficacy and the survival of the patients. Of 64 eligible ALK-positive patients with NSCLC, 30 (46.9%) were p-c-Kit-positive and 10 (15.7%) were p-PDGFRA-positive. Brain metastases were more common in ALK-positive cases that were p-PDGFRA-positive compared with those who were p-PDGFRA-negative. ALK-positive patients treated with crizotinib, who exhibited high levels of p-c-Kit had significantly lower progression-free survival times than those with low levels. In addition, the patients with high levels of p-c-Kit exhibited lower overall survival times than those with low levels. Furthermore, multivariate analysis indicated that high levels of p-c-Kit in patients with ALK fusion was the only significant predictive factor for crizotinib efficacy and was a prognostic factor for poor overall survival time. However, no statistically significant difference was observed in the survival of patients with different p-PDGFRA levels. p-PDGFRA was more frequently expressed in the ALK-positive cases with brain metastasis. c-Kit signaling activation may be associated with poor efficacy of crizotinib and poor prognosis in advanced ALK fusion NSCLC.

BACKGROUND ABCA2 has been genetically linked to Alzheimer's disease (AD) risk, but its mRNA expression and epigenetics in AD have not been investigated. MATERIAL AND METHODS To explore the diagnosis value of ABCA2 mRNA expression in AD, 2 datasets GES15222 and GSE33000 containing expression profile of brain cortex tissues and 2 datasets GSE63063 (Cohort 1) and GSE63063 (Cohort 2) containing expression profile of blood were downloaded from the NCBI GEO database and analyzed by receiver operating characteristic curve (ROC) analyses and logistic regression. The ABCA2 co-expressed genes were also analyzed by GO annotation to investigate the potential molecular mechanisms. RESULTS The analyses results suggested ABCA2 mRNA expression was upregulated significantly in AD compared with controls in all datasets. ROC analysis suggested that ABCA2 was associated with AD in all datasets, which were also proved by univariate and multivariate analyses. Next, the dataset GSE80970 containing methylation profiles of prefrontal cortex tissues from AD patients were downloaded and analyzed. Methylation of 2 of 36 CpG islands in ABCA2 gene with high diagnostic accuracy of AD from controls in ROC analyses were found to be negatively associated with AD risk in univariate analysis. One was still associated with AD risk after adjustment of confounding factors. Additional analyses indicated that ACBA2 mRNA expression could be used to diagnose mild cognitive impairment (MCI) and Huntington's disease (HD) from controls and to distinguish HD from AD, but not AD from MCI. Furthermore, the genes involved in AD during ABCA2 alteration were analyzed by GO analysis. CONCLUSIONS ABCA2 mRNA expression and methylation is associated AD risk. ABCA2 may be used as a biomarker for AD diagnosis and may be a potential therapeutic target of AD.

Rapid and accurate identification of new essential genes in under-studied microorganisms will significantly improve our understanding of how a cell works and the ability to re-engineer microorganisms. However, predicting essential genes across distantly related organisms remains a challenge. Here, we present a machine learning-based integrative approach that reliably transfers essential gene annotations between distantly related bacteria. We focused on four bacterial species that have well-characterized essential genes, and tested the transferability between three pairs among them. For each pair, we trained our classifier to learn traits associated with essential genes in one organism, and applied it to make predictions in the other. The predictions were then evaluated by examining the agreements with the known essential genes in the target organism. Ten-fold cross-validation in the same organism yielded AUC scores between 0.86 and 0.93. Cross-organism predictions yielded AUC scores between 0.69 and 0.89. The transferability is likely affected by growth conditions, quality of the training data set and the evolutionary distance. We are thus the first to report that gene essentiality can be reliably predicted using features trained and tested in a distantly related organism. Our approach proves more robust and portable than existing approaches, significantly extending our ability to predict essential genes beyond orthologs.

To investigate the effects of adjunct ketamine treatment on chronic treatment-resistant schizophrenia patients with treatment-resistant depressive symptoms (CTRS-TRD patients), including alterations in brain function.

A marker for distinguishing patients with obsessive-compulsive disorder (OCD) spectrum has not yet been identified. Whole-brain resting-state effective and functional connectivity (rsEC and rsFC, respectively) networks were constructed for 50 unmedicated OCD (U-OCD) patients, 45 OCD patients in clinical remission (COCD), 47 treatment-resistant OCD (T-OCD) patients, 42 chronic schizophrenia patients who exhibit OCD symptoms (SCHOCD), and 50 healthy controls (HCs). Multivariate pattern analysis (MVPA) was performed to investigate the accuracy of using connectivity alterations to distinguished among the aforementioned groups. Compared to HCs, rsEC connections were significantly disrupted in the U-OCD (n = 15), COCD (n = 8), and T-OCD (n = 19) groups. Additionally, 21 rsEC connections were significantly disrupted in the T-OCD group compared to the SCHOCD group. The disrupted rsEC networks were associated mainly with the frontal-parietal cortex, basal ganglia, limbic regions, and the cerebellum. Classification accuracies for distinguishing OCD patients from HCs and SCHOCD patients ranged from 66.6% to 98.0%. In conclusion, disrupted communication from the frontal-parietal cortices to subcortical basal nuclei and the cerebellum may represent a functional pathological feature of the OCD spectrum. MVPA based on both abnormal rsEC and rsFC patterns may aid in early differential diagnosis of OCD.

Although visual deficits can be observed at any stage of schizophrenia, few studies have focused on visual cortex alterations in individuals at high risk of schizophrenia. This study aimed to investigate the pathological changes of the primary visual cortex in a prenatal mouse model of MK801-induced high-risk schizophrenia.

This study aimed to investigate the effect of aerobic exercise combined with glucosamine (OTL) on the apoptosis of chondrocytes of rabbit knee osteoarthritis (KOA) by affecting the expression of TRPV5.

Background: In the treatment of patients with bipolar disorder (BP), antidepressant-induced mania is usually observed. The rate of phase switching (from depressive to manic) in these patients exceeds 22%. The exploration of brain activity patterns during an antidepressant-induced manic phase may aid the development of strategies to reduce the phase-switching rate. The use of a murine model to explore brain activity patterns in depressive and manic phases can help us to understandthe pathological features of BP. The novel object recognition preference ratio is used to assess cognitive ability in such models. Objective: To investigate brain Ca2+ activity and behavioral expression in the depressive and manic phases in the same murine model, to aid understanding of brain activity patterns in phase switching in BP. Methods: In vivo two-photon imaging was used to observe brain activity alterations in a murine model in which induce depressive-like and manic-like behaviors were induced sequentially. The immobility time was used to assess depressive-like symptoms and the total distance traveled was used to assess manic-like symptoms. Results: In vivo two-photon imaging revealed significantly reduced brain Ca2+ activity in temporal cortex pyramidal neurons in the depressive phase in mice exposed to chronic unpredictable mild stress compared with naïve controls. The brain Ca2+ activity correlated negatively with the novel object recognition preference ratio within the immobility time. Significantly increased brain Ca2+ activity was observed in the ketamine-induced manic phase. However, this activity did not correlate with the total distance traveled. The novel object recognition preference ratio correlated negatively with the total distance traveled in the manic phase.

We hypothesized that MAP kinase-interacting serine/threonine kinase 2 (MNK2) may contribute to non-small cell lung cancer (NSCLC) development, and serve as a new therapeutic target. Immunohistochemical staining evaluated the correlation between MNK2 expression and clinicopathological features in 367 NSCLC cancer tissues. We determined the effects of MNK2 silencing in NSCLC cell lines in vitro and in vivo. RT-PCR and western blotting was used to examine the impact of MNK2 on ERK and AKT pathways. MNK2 was overexpressed in NSCLC cell lines and tumor tissues. Patients with MNK2 overexpression had lower OS rates (P < 0.001). High expression of MNK2 was correlated with lymph node metastasis (P = 0.008). MNK2 functioned as an independent prognostic factor for poor survival in patients with NSCLC (P = 0.003). MNK2 down-regulation inhibited proliferation, migration and invasion in vitro (P < 0.001), and reduced tumor growth and invasion in nude mice (P < 0.05). MNK2 enhanced phosphorylation of eIF4E, a downstream target of ERK and AKT pathways, which promoted NSCLC proliferation and invasion. We conclude that MNK2 overexpression in NSCLC is associated with proliferation, migration, invasion, and lower survival rates in patients via the phosphorylated eIF4E-mediated signaling pathway.

Functional connectivity (FC) is altered in patients with obsessive-compulsive disorder (OCD). Most previous studies have focused on the strength of FC in patients with OCD; few have examined the number of functional connections in these patients. The number of functional connections is an important index for assessing aberrant FC. In the present study, we used FC density (FCD) mapping to explore alterations in the number of functional connections in patients with treatment-refractory OCD (TROCD) using the FCD index.

To explore the unified and disease specific structural features of the brain in patients spanning six mental disorders who experience own-thought auditory verbal hallucinations (OTAVH).

Schizophrenia is a genetically related mental illness, in which the majority of genetic alterations occur in the non-coding regions of the human genome. In the past decade, a growing number of regulatory non-coding RNAs (ncRNAs) including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have been identified to be strongly associated with schizophrenia. However, the studies of these ncRNAs in the pathophysiology of schizophrenia and the reverting of their genetic defects in restoration of the normal phenotype have been hampered by insufficient technology to manipulate these ncRNA genes effectively as well as a lack of appropriate animal models. Most recently, a revolutionary gene editing technology known as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated nuclease 9 (Cas9; CRISPR/Cas9) has been developed that enable researchers to overcome these challenges. In this review article, we mainly focus on the schizophrenia-related ncRNAs and the use of CRISPR/Cas9-mediated editing on the non-coding regions of the genomic DNA in proving causal relationship between the genetic defects and the pathophysiology of schizophrenia. We subsequently discuss the potential of translating this advanced technology into a clinical therapy for schizophrenia, although the CRISPR/Cas9 technology is currently still in its infancy and immature to put into use in the treatment of diseases. Furthermore, we suggest strategies to accelerate the pace from the bench to the bedside. This review describes the application of the powerful and feasible CRISPR/Cas9 technology to manipulate schizophrenia-associated ncRNA genes. This technology could help researchers tackle this complex health problem and perhaps other genetically related mental disorders due to the overlapping genetic alterations of schizophrenia with other mental illnesses.