[Prognostic Value of DTA Mutations in Patients with Newly Diagnosed Acute Myeloid Leukemia].

OBJECTIVE: To investigate the prognostic significance of DTA (DNMT3A, TET2, ASXL1 ) gene mutations in patients with non-M3 acute myeloid leukemia (AML). METHODS: The clinical data of 180 newly diagnosed AML patients hospitalized in the First People's Hospital of Changzhou from January 2018 to April 2022 were retrospectively analyzed. Next-generation sequencing technology was used to detect 150 gene mutations in the patients, and log-rank tests and Cox regression models were used to analyze the prognostic factors. RESULTS: DTA gene mutations were detected in 83 (46.1%) of 180 AML patients. Compared to patients without DTA mutations, patients with DTA mutations were significantly older (P < 0.001). The median overall survival (OS) time and disease-free survival (DFS) time in the DTA mutation group were significantly shorter than those in the group without DTA mutation (both P < 0.05). Multivariate analysis showed that age ≥ 60 years (P < 0.001), with DTA mutation (P =0.018), and intermediate-risk (relative to favorable-risk) (P =0.005) were independent risk factors for OS in AML patients. CONCLUSION: AML patients with DTA mutations are relatively older, with shorter median OS time and DFS time, and poor prognosis.

Relationships between the gut microbiome and brain functional alterations in first-episode, drug-naïve patients with major depressive disorder.

OBJECTIVE: Increasing evidence has shown that the microbiota-gut-brain axis (MGB) is involved in the mechanism of major depressive disorder (MDD). However, the relationship between the gut microbiome and brain function in MDD patients has not been determined. Here, we intend to identify specific changes in the gut microbiome and brain function in first-episode, drug-naïve MDD patients and then explore the associations between the two omics to elucidate how the MGB axis plays a role in MDD development. METHODS: We recruited 38 first-episode, drug-naïve MDD patients and 37 healthy controls (HC). The composition of the fecal microbiome and neural spontaneous activity alterations were examined using 16S rRNA gene amplicon sequencing analysis and regional homogeneity (ReHo). Spearman correlation analyses were conducted to assess the associations between the gut microbiome and brain function. RESULTS: Compared with HC, MDD patients exhibited distinct alterations in the gut microbiota and elevated ReHo in the frontal regions. In the MDD group, a positive relationship was noted between the relative abundance of Blautia and the HAMD-17 and HAMA scores, as well as between the relative abundance of Oxalobacteraceae and the HAMD-17 score. The relative abundances of Porphyromonadaceae and Parabacteroides were negatively correlated with the ReHo values of frontal regions. LIMITATIONS: Our study utilized a cross-sectional design, and the number of subjects was relatively small. CONCLUSION: We found that some specific gut microbiomes were associated with frontal function, and others were associated with clinical symptoms in MDD patients, which may support the role of the MGB axis underlying MDD.

Gender differences in plasma S100B levels of patients with major depressive disorder.

BACKGROUND: Low concentrations of S100B have neurotrophic effects and can promote nerve growth and repair, which plays an essential role in the pathophysiological and histopathological alterations of major depressive disorder (MDD) during disease development. Studies have shown that plasma S100B levels are altered in patients with MDD. In this study, we investigated whether the plasma S100B levels in MDD differ between genders. METHODS: We studied 235 healthy controls (HCs) (90 males and 145 females) and 185 MDD patients (65 males and 120 females). Plasma S100B levels were detected via multifactor assay. The Mahalanobis distance method was used to detect the outliers of plasma S100B levels in the HC and MDD groups. The Kolmogorov-Smirnov test was used to test the normality of six groups of S100B samples. The Mann-Whitney test and Scheirer-Ray-Hare test were used for the comparison of S100B between diagnoses and genders, and the presence of a relationship between plasma S100B levels and demographic details or clinical traits was assessed using Spearman correlation analysis. RESULTS: All individuals in the HC group had plasma S100B levels that were significantly greater than those in the MDD group. In the MDD group, males presented significantly higher plasma S100B levels than females. In the male group, the plasma S100B levels in the HC group were significantly higher than those in the MDD group, while in the female group, no significant difference was found between the HC and MDD groups. In the male MDD subgroup, there was a positive correlation between plasma S100B levels and years of education. In the female MDD subgroup, there were negative correlations between plasma S100B levels and age and suicidal ideation. CONCLUSIONS: In summary, plasma S100B levels vary with gender and are decreased in MDD patients, which may be related to pathological alterations in glial cells.

Gel polymer electrolytes for rechargeable batteries toward wide-temperature applications.

Rechargeable batteries, typically represented by lithium-ion batteries, have taken a huge leap in energy density over the last two decades. However, they still face material/chemical challenges in ensuring safety and long service life at temperatures beyond the optimum range, primarily due to the chemical/electrochemical instabilities of conventional liquid electrolytes against aggressive electrode reactions and temperature variation. In this regard, a gel polymer electrolyte (GPE) with its liquid components immobilized and stabilized by a solid matrix, capable of retaining almost all the advantageous natures of the liquid electrolytes and circumventing the interfacial issues that exist in the all-solid-state electrolytes, is of great significance to realize rechargeable batteries with extended working temperature range. We begin this review with the main challenges faced in the development of GPEs, based on extensive literature research and our practical experience. Then, a significant section is dedicated to the requirements and design principles of GPEs for wide-temperature applications, with special attention paid to the feasibility, cost, and environmental impact. Next, the research progress of GPEs is thoroughly reviewed according to the strategies applied. In the end, we outline some prospects of GPEs related to innovations in material sciences, advanced characterizations, artificial intelligence, and environmental impact analysis, hoping to spark new research activities that ultimately bring us a step closer to realizing wide-temperature rechargeable batteries.

Alterations in the fecal microbiota of methamphetamine users with bad sleep quality during abstinence.

BACKGROUND: Methamphetamine (MA) abuse has resulted in a plethora of social issues. Sleep disturbance is a prominent issue about MA addiction, which serve as a risk factor for relapse, and the gut microbiota could play an important role in the pathophysiological mechanisms of sleep disturbances. Therefore, improving sleep quality can be beneficial for treating methamphetamine addiction, and interventions addressing the gut microbiota may represent a promising approach. METHOD: We recruited 70 MA users to investigate the associations between sleep quality and fecal microbiota by the Pittsburgh Sleep Quality Index (PSQI), which was divided into MA-GS (PSQI score < 7, MA users with good sleep quality, n = 49) and MA-BS group (PSQI score ≥ 7, MA users with bad sleep quality, n = 21). In addition, we compared the gut microbiota between the MA-GS and healthy control (HC, n = 38) groups. 16S rRNA sequencing was applied to identify the gut bacteria. RESULT: The study revealed that the relative abundances of the Thermoanaerobacterales at the order level differed between the MA-GS and MA-BS groups. Additionally, a positive correlation was found between the relative abundance of the genus Sutterella and daytime dysfunction. Furthermore, comparisons between MA users and HCs revealed differences in beta diversity and relative abundances of various bacterial taxa. CONCLUSION: In conclusion, the study investigated alterations in the gut microbiota among MA users. Furthermore, we demonstrated that the genus Sutterella changes may be associated with daytime dysfunction, suggesting that the genus Sutterella may be a biomarker for bad sleep quality in MA users.

Associations between impulsivity and fecal microbiota in individuals abstaining from methamphetamine.

INTRODUCTION: Methamphetamine (MA) abuse is a major public problem, and impulsivity is both a prominent risk factor and a consequence of addiction. Hence, clarifying the biological mechanism of impulsivity may facilitate the understanding of addiction to MA. The microbiota-gut-brain axis was suggested to underlie a biological mechanism of impulsivity induced by MA. METHODS: We therefore recruited 62 MA addicts and 50 healthy controls (HCs) to investigate the alterations in impulsivity and fecal microbiota and the associations between them in the MA group. Thereafter, 25 MA abusers who abstained from MA for less than 3 months were followed up for 2 months to investigate the relationship between impulsivity and microbiota as abstinence became longer. 16S rRNA sequencing was conducted for microbiota identification. RESULTS: Elevated impulsivity and dysbiosis characterized by an increase in opportunistic pathogens and a decrease in probiotics were identified in MA abusers, and both the increased impulsivity and disrupted microbiota tended to recover after longer abstinence from MA. Impulsivity was related to microbiota, and the effect of MA abuse on impulsivity was mediated by microbiota. CONCLUSION: Our findings potentially highlighted the importance of abstention and implicated the significant role of the microbiota-gut-brain axis in the interrelationship between microbiota and behaviors, as well as the potential of microbiota as a target for intervention of impulsivity.

A Holistic Approach to CT Protocol and Dose Management.

PURPOSE: Challenges from administrative support, scanners' heterogeneity, patient size variation, and protocol mapping hinder CT protocol and dose management. We present a holistic approach to overcome these challenges. METHODS: A dose tracking software was selected with two key requirements: intelligent protocol mapping and customizable dose threshold settings according to the patient size. A multifaceted workflow was carefully implemented. It included patient size-dependent dose thresholds for e-mail alerts, a base protocol archive on a website with a unified format using an in-house developed reformat software upon protocol export, prompt dose alert follow-up, and well-controlled protocol changes. The thresholds were iteratively updated following protocol changes or review of dose statistics. The program outcome was evaluated using 11 protocols from January 2020 to May 2023 (N = 148,678) in comparison to ACR's achievable dose (AD) and dose reference levels (DRLs). RESULTS: The 75th percentile dose data were lower than the ACR's DRL on average, ranging from -4.9% to -36%. The median doses were in a range of -23% to 19% on average in comparison with the ACR's AD. The median value from pulmonary embolism scans initially showed 36% higher than the AD but was gradually reduced to nearly 3% lower than the AD. The percentage of unjustified alerted cases decreased from 80% in first half year of 2020 to 17% in the first 5 months of 2023. CONCLUSIONS: The results showed that our holistic approach to protocol and dose management has been effective. The impact to practice has been prompt and sustainable.

Computed tomography dose index determination in dose modulation prospectively involving the third-generation iterative reconstruction and noise index.

PURPOSE: Optimizing CT protocols is challenging in the presence of automatic dose modulation because the CT dose index (CTDIvol) at different patient sizes is unknown to the operator. The task is more difficult when both the image quality index and iterative reconstruction prospectively affect the dose determination. It is of interest in practice to be informed of the CTDIvol during the protocol initialization and evaluation. It was our objective to obtain a predictive relationship between CTDIvol, the image quality index, and iterative reconstruction strength at various patient sizes. METHODS: Dose modulation data were collected on a GE Revolution 256-slice scanner utilizing a Mercury phantom and selections of the noise index (NI) from 8 to 17, the third generation iterative reconstruction (ASIR-V) from 0% to 80%, and phantom diameters from 16 to 36 cm. The fixed parameters were 120 kVp, a pitch of .984, and a collimation of 40 mm with a primary slice width of 2.5 mm. The CTDIvol per diameter was based on the average tube current over three adjacent slices (same or similar diameter) multiplied by a conversion factor between the average mA of the series and the reported CTDIvol. The relationship between CTDIvol, NI, and ASIR-V for each diameter was fitted with a 2nd order polynomial of ASIR-V multiplied by a power law of NI. RESULTS: The ASIR-V fit parameters versus diameter followed a Lorentz function while the NI exponent versus diameter followed an exponential growth function. The CTDIvol predictions were accurate within 15% compared to phantom results on a separate GE Revolution. For clinical relevance, the phantom diameter was converted to an abdomen or chest equivalent diameter and was well matched to patient data. CONCLUSION: The fitted relationship for CTDIvol. for given values of NI and ASIR-V blending for a range of phantom sizes was a good match to phantom and patient data. The results can be of direct help for selecting adequate parameters in CT protocol development.

Lignocellulose-Based Optical Biofilter with High Near-Infrared Transmittance via Lignin Capturing-Fusing Approach.

Near-infrared (NIR) transparent optical filters show great promise in night vision and receiving windows. However, NIR optical filters are generally prepared by laborious, environmentally unfriendly processes that involve metal oxides or petroleum-based polymers. We propose a lignin capturing-fusing approach to manufacturing optical biofilters based on molecular collaboration between lignin and cellulose from waste agricultural biomass. In this process, lignin is captured via self-assembly in a cellulose network; then, the lignin is fused to fill gaps and hold the cellulose fibers tightly. The resulting optical biofilter featured a dense structure and smooth surface with NIR transmittance of ~90%, ultralow haze of close to 0%, strong ultraviolet-visible light blocking (~100% at 400 nm and 57.58% to 98.59% at 550 nm). Further, the optical biofilter has comprehensive stability, including water stability, solvent stability, thermal stability, and environmental stability. Because of its unique properties, the optical biofilter demonstrates potential applications in the NIR region, such as an NIR-transmitting window, NIR night vision, and privacy protection. These applications represent a promising route to produce NIR transparent optical filters starting from lignocellulose biomass waste.

The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets.

Background: Methamphetamine use disorder (MUD) poses a considerable public health threat, and its identification remains challenging due to the subjective nature of the current diagnostic system that relies on self-reported symptoms. Recent studies have suggested that MUD patients may have gut dysbiosis and that gut microbes may be involved in the pathological process of MUD. We aimed to examine gut dysbiosis among MUD patients and generate a machine-learning model utilizing gut microbiota features to facilitate the identification of MUD patients. Method: Fecal samples from 78 MUD patients and 50 sex- and age-matched healthy controls (HCs) were analyzed by 16S rDNA sequencing to identify gut microbial characteristics that could help differentiate MUD patients from HCs. Based on these microbial features, we developed a machine learning model to help identify MUD patients. We also used public data to verify the model; these data were downloaded from a published study conducted in Wuhan, China (with 16 MUD patients and 14 HCs). Furthermore, we explored the gut microbial features of MUD patients within the first three months of withdrawal to identify the withdrawal period of MUD patients based on microbial features. Results: MUD patients exhibited significant gut dysbiosis, including decreased richness and evenness and changes in the abundance of certain microbes, such as Proteobacteria and Firmicutes. Based on the gut microbiota features of MUD patients, we developed a machine learning model that demonstrated exceptional performance with an AUROC of 0.906 for identifying MUD patients. Additionally, when tested using an external and cross-regional dataset, the model achieved an AUROC of 0.830. Moreover, MUD patients within the first three months of withdrawal exhibited specific gut microbiota features, such as the significant enrichment of Actinobacteria. The machine learning model had an AUROC of 0.930 for identifying the withdrawal period of MUD patients. Conclusion: In conclusion, the gut microbiota is a promising biomarker for identifying MUD and thus represents a potential approach to improving the identification of MUD patients. Future longitudinal studies are needed to validate these findings.

Sex effects on differentiating patients with major depressive disorder from bipolar disorder in depressive state: A fMRI study with follow-up.

BACKGROUND: Bipolar disorder (BD) is difficult to discriminate from major depressive disorder (MDD) before the appearance of mania or hypomania. This study was designed to identify whether patients with MDD and those who converted to BD are distinguishable using dynamic amplitude low-frequency fluctuations (dALFF) and describe the sex effects on the identification of the two disorders. METHODS: We compared the dALFF values of 35 BD patients who converted from MDD during the 2-year follow-up, 99 MDD patients, and 130 healthy controls (HCs) using two-way ANOVA. Pearson's correlation was used to compare dALFF in dysfunctional brain regions and clinical characteristics. RESULTS: A main effect of diagnosis was discovered in the frontal and occipital gyrus. For the main effect of sex, both the left middle occipital gyrus and the medial part of the superior frontal gyrus had higher dALFF values in males compared to females. An interaction of sex and diagnosis effect was observed in the right precentral gyrus. Male MDD patients exhibited a higher dALFF value than male BD patients. Additionally, we discovered a higher dALFF value in females than in males in BD patients. WCST scores were positively associated with dALFF values in the frontal and occipital gyrus in MDD patients. Meanwhile, dALFF values in the occipital gyrus positively correlated with WCST in female MDD patients only. LIMITATION: Most of the participants were on medication and the sample size was small. CONCLUSIONS: Our study is the first to find the non-neglectable role of sex effects in differentiating BD and MDD at an early stage.

Optimal dose determination for coronary artery calcium scoring CT at standard tube voltage.

OBJECTIVES: Coronary artery calcium scoring (CACs) at 120 kVp is the standard practice. It is an important tool for preventative management of asymptomatic patients. However, the current dose delivery, albeit patient-size dependent, does not connect the CACs specific noise requirement to the dose, causing significant dose variations. We propose a new approach for optimal dose determination by incorporating the patient-size dependent noise threshold. METHODS: A polyethylene-based Mercury phantom of various diameters was scanned with a dual-source CT using CACs gating at different volume CT dose index (CTDIvol). The relationship of noise to the diameter and CTDIvol was obtained. The phantom diameter was then converted to the patient chest diameter through a retrospective analysis of a clinical cohort (N = 140). Finally, the patient-size dependent noise threshold was applied, and the optimal dose was derived. The prescribed doses were compared with those from a clinical CACs cohort (N = 262). RESULTS: A power-exponential relationship was found for the noise versus CTDIvol and phantom diameter (R2 = 0.988). The phantom diameter versus the patient effective diameter was found to obey a linear relationship (R2 = 0.998). Two noise threshold settings were made for dose options: one for more dose saving, and another for tighter noise constraint. Retrospective comparisons with clinical CACs studies showed an average dose reduction of 23% in 80.5% of the cases with option 1. The average dose reduction is 23% in 77.9% of the cases with option 2. CONCLUSION: A new optimal dose scheme dictated by the target noise was established for CACs at 120 kVp. The proposed dose modulation can serve as the baseline from which further dose reduction is possible.

Cognitive function and cardiovascular health in the elderly: network analysis based on hypertension, diabetes, cerebrovascular disease, and coronary heart disease.

Introduction: Cognitive decline in the elderly population is a growing concern, and vascular factors, such as hypertension, diabetes, cerebrovascular disease, and coronary heart disease, have been associated with cognitive impairments. This study aims to provide deeper insights into the structure of cognitive function networks under these different vascular factors and explore their potential associations with specific cognitive domains. Methods: Cognitive function was assessed using a modified Chinese version of the mini-mental state examination (MMSE) scale, and intensity centrality and side weights were estimated by network modeling. The network structure of cognitive function was compared across subgroups by including vascular factors as subgroup variables while controlling for comorbidities and confounders. Results: The results revealed that cerebrovascular disease and coronary heart disease had a more significant impact on cognitive function. Cerebrovascular disease was associated with weaker centrality in memory and spatial orientation, and a sparser cognitive network structure. Coronary heart disease was associated with weaker centrality in memory, repetition, executive function, recall, attention, and calculation, as well as a sparser cognitive network structure. The NCT analyses further highlighted significant differences between the cerebrovascular disease and coronary heart disease groups compared to controls in terms of overall network structure and connection strength. Conclusion: Our findings suggest that specific cognitive domains may be more vulnerable to impairments in patients with cerebrovascular disease and coronary heart disease. These insights could be used to improve the accuracy and sensitivity of cognitive screening in these patient populations, inform personalized cognitive intervention strategies, and provide a better understanding of the potential mechanisms underlying cognitive decline in patients with vascular diseases.

Early long-term low-dosage colchicine and major adverse cardiovascular events in patients with acute myocardial infarction: a systematic review and meta-analysis.

Background: Current evidence on the efficacy and safety of colchicine after acute myocardial infarction (AMI) remains controversial. This study aims to clarify early low-dose long-term colchicine's exact efficacy and safety in AMI patients via more studies. Methods: We searched PubMed, Web of Science, Embase, and Cochrane Library databases for randomized controlled trials assessing the efficacy of colchicine on major adverse cardiovascular events (MACE) in recent AMI patients from inception to January 29, 2023, without any restriction. Additionally, we conducted subgroup analyses to assess the impact of early (≤3 days) long-term (≥1 year) low-dosage (0.5 mg/d) colchicine. Summary estimates were computed using Mantel-Haenszel and reported as risk ratios (RRs) or standard mean differences (SMDs), mean differences (MDs) with 95% confidence intervals (CIs). Sensitivity analyses were performed to explore the potential sources of heterogeneity. Review Manager software was used for the meta-analysis. Results: Eight studies identified from 564 screened records were analyzed, with 5,872 patients after AMI. The length of follow-up varied from five days to 22.7 months, and 0.5-1.0 mg colchicine was administered daily. In summary, compared to the control group, colchicine reduced the occurrence of MACE (RR, 0.56; 95% CI, 0.48-0.67) with 2.99-fold gastrointestinal adverse events in patients with recent AMI. Moreover, the relation referred to a gradual decrease in the occurrence of MACE with a longer follow-up duration (≥1 year) and lower dosage (0.5 mg/d) without leading more gastrointestinal adverse events. Colchicine decreased the follow-up levels of C-reactive protein (CRP) (MD -0.66, 95% CI, -0.98- -0.35) and neutrophils (SMD -0.22, 95% CI, -0.39- -0.55) when the follow-up period was 30 days. Conclusion: Early long-term low-dose colchicine decreases the risk of MACE via anti-inflammation without leading more gastrointestinal adverse events in patients with AMI.

Effect of intra-aortic balloon pump with veno-arterial extracorporeal membrane oxygenation in acute myocardial infarction with cardiogenic shock: A meta-analysis.

BACKGROUND: The effectiveness of a concomitant intra-aortic balloon pump (IABP) with veno-arterial extracorporeal membrane oxygenation (VA-ECMO) intervention in acute myocardial infarction with cardiogenic shock (AMICS) patients is contested in the literature. This study sought to compare short-term mortality weaning rate from VA-ECMOin AMICS cases. METHODS: We conducted a literature review and compared the primary and secondary endpoints in the following treatment groups of AMICS patients: (1) VA-ECMO plus IABP vs. IABP alone and (2) VA-ECMO plus IABP vs. VA-ECMO alone. The primary endpoint was in-hospital all-cause mortality; while 30-days mortality, weaning from VA-ECMO, and vascular complications comprised secondary endpoints. RESULTS: VA-ECMO concomitant with IABP was administered to 3,580 (76.4%) patients, while IABP alone and VA-ECMO alone treatments accounted for 1.7% and 21.9% of the patients, respectively. We found that in-hospital mortality was significantly lower in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (odds ratio (OR) = 0.52; 95% Confidence Interval (CI) = 0.21-1.31; I-squared statistic (I2 = 30%) or IABP alone (OR = 0.20; 95% CI = 0.08-0.55; I2 = 0%). Additionally, 30-days mortality was significantly lower in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (OR = 0.31; 95% CI = 0.25-0.40; I2 = 0%) or IABP alone (OR = 0.24; 95% CI = 0.11-0.50; I2 = 0%). A significant difference was observed in weaning from VA-ECMO in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (OR = 1.91; 95% CI = 1.09-3.33; I2 = 0%). CONCLUSION: In-hospital and 30-days mortality were significantly lower in AMICS patients treated with VA-ECMO plus IABP vs. VA-ECMO alone or IABP alone. VA-ECMO with concomitant IABP could increase the proportion of patients weaned from VA-ECMO, significantly reducing in-hospital mortality, without increasing complications.

Altered gray matter volumes and plasma IL-6 level in major depressive disorder patients with suicidal ideation.

BACKGROUNDS: Suicidal ideation (SI) is one of the most serious consequences of major depressive disorder (MDD). Understanding the unique mechanism of MDD with SI (MDD + S) is crucial for treatment development. While abundant research has studied MDD, past studies have not reached a consensus on the mechanism of MDD + S. The study aimed to investigate the abnormalities of the gray matter volumes (GMVs) and plasma IL-6 level in MDD + S to further reveal the mechanism of MDD + S. METHODS: We tested the plasma IL-6 level using Luminex multifactor assays and collected the Structural Magnetic Resonance Imaging (SMRI) data from 34 healthy controls (HCs), 36 MDD patients without SI (MDD - S) and 34 MDD + S patients. We performed a partial correlation between the GMVs of the brain regions with significant differences and plasma IL-6 level with age, sex, medication, scores of HAMD-17 and HAMA as the covariates. RESULTS: Compared with HCs and MDD - S, MDD + S had significantly decreased GMVs in the left cerebellum Crus I/II and significantly increased plasma IL-6 level; compared with HCs, both the MDD + S and MDD - S had significantly decreased GMVs in right precentral and postcentral gyri. No significant correlation was found between the GMVs and the plasma IL-6 level in the MDD + S and MDD - S, respectively. While the GMVs of the right precentral and postcentral gyri negatively correlated with the level of IL-6 in the whole MDD (r = -0.28, P = 0.03). The GMVs of the left cerebellum Crus I/II (r = -0.47, P = 0.02), and the right precentral and postcentral gyri (r = -0.42, P = 0.04) negatively correlated with the level of IL-6 in HCs. CONCLUSION: The altered GMVs and the plasma IL-6 level may provide a scientific basis to understand the pathophysiological mechanisms of MDD + S.

Gray matter volume reduction in orbitofrontal cortex correlated with plasma glial cell line-derived neurotrophic factor (GDNF) levels within major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a severe mental disorder characterized by reduced gray matter volume (GMV). To date, the pathogenesis of MDD remains unclear, but neurotrophic factors play an essential role in the pathophysiological alterations of MDD during disease development. In particular, plasma glial cell line-derived neurotrophic factor (GDNF) has been suggested as a potential biomarker that may be associated with disease activity and neurological progression in MDD. Our study investigated whether plasma GDNF levels in MDD patients and healthy controls (HCs) are correlated with GMV alterations. METHODS: We studied 54 MDD patients and 48 HCs. The effect of different diagnoses on whole-brain GMV was investigated using ANOVA (Analysis of Variance). The threshold of significance was p < 0.05, and Gaussian random-field (GRF) correction for error was used. All analyses were controlled for covariates such as ethnicity, handedness, age, and gender that could affect GMV. RESULT: Compared with the HC group, the GMV in the MDD group was significantly reduced in the right inferior orbitofrontal cortex (OFC), and plasma GDNF levels were significantly higher in the MDD group than in the HC group. In the right inferior OFC, the GDNF levels were positively correlated with GMV reduction in the MDD group, whereas in the HC group, a negative correlation was observed between GDNF levels and GMV reduction. CONCLUSION: Although increased production of GDNF in MDD may help repair neural damage in brain regions associated with brain disease, its repairing effects may be interfered with and hindered by underlying neuroinflammatory processes.

Shared and distinct functional connectivity of hippocampal subregions in schizophrenia, bipolar disorder, and major depressive disorder.

Schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) share etiological and pathophysiological characteristics. Although neuroimaging studies have reported hippocampal alterations in SZ, BD, and MDD, little is known about how different hippocampal subregions are affected in these conditions because such subregions, namely, the cornu ammonis (CA), dentate gyrus (DG), and subiculum (SUB), have different structural foundations and perform different functions. Here, we hypothesize that different hippocampal subregions may reflect some intrinsic features among the major psychiatric disorders, such as SZ, BD, and MDD. By investigating resting functional connectivity (FC) of each hippocampal subregion among 117 SZ, 103 BD, 96 MDD, and 159 healthy controls, we found similarly and distinctly changed FC of hippocampal subregions in the three disorders. The abnormal functions of middle frontal gyrus might be the core feature of the psychopathological mechanisms of SZ, BD, and MDD. Anterior cingulate cortex and inferior orbital frontal gyrus might be the shared abnormalities of SZ and BD, and inferior orbital frontal gyrus is also positively correlated with depression and anxiety symptoms in SZ and BD. Caudate might be the unique feature of SZ and showed a positive correlation with the cognitive function in SZ. Middle temporal gyrus and supplemental motor area are the differentiating features of BD. Our study provides evidence for the different functions of different hippocampal subregions in psychiatric pathology.

Artificial intelligence-driven consensus gene signatures for improving bladder cancer clinical outcomes identified by multi-center integration analysis.

To accurately predict the prognosis and further improve the clinical outcomes of bladder cancer (BLCA), we leveraged large-scale data to develop and validate a robust signature consisting of small gene sets. Ten machine-learning algorithms were enrolled and subsequently transformed into 76 combinations, which were further performed on eight independent cohorts (n = 1218). We ultimately determined a consensus artificial intelligence-derived gene signature (AIGS) with the best performance among 76 model types. In this model, patients with high AIGS showed a higher risk of mortality, recurrence, and disease progression. AIGS is not only independent of traditional clinical traits [(e.g., American Joint Committee on Cancer (AJCC) stage)] and molecular features (e.g., TP53 mutation) but also demonstrated superior performance to these variables. Comparisons with 58 published signatures also indicated that AIGS possessed the best performance. Additionally, the combination of AIGS and AJCC stage could achieve better performance. Patients with low AIGS scores were sensitive to immunotherapy, whereas patients with high AIGS scores might benefit from seven potential therapeutics: BRD-K45681478, 1S,3R-RSL-3, RITA, U-0126, temsirolimus, MRS-1220, and LY2784544. Additionally, some mutations (TP53 and RB1), copy number variations (7p11.2), and a methylation-driven target were characterized by AIGS-related multi-omics alterations. Overall, AIGS provides an attractive platform to optimize decision-making and surveillance protocol for individual BLCA patients.

Distinguishing major depressive disorder from bipolar disorder in remission: A brain structural network analysis.

BACKGROUND: It is challenging to differentiate major depressive disorder (MDD) from bipolar disorder (BD) in depression and remission. To exclude the potential influence of depressive episodes, we compared the white matter (WM) network between MDD and BD patients in remission to find disease-specific alterations in MDD and BD, and then distinguish these two affective disorders. METHODS: We recruited 33 patients with remitted MDD (rMDD), 54 patients with remitted BD (rBD), and 60 healthy controls (HCs). Diffusion tensor imaging and high-resolution 3D T1-weighted image were acquired. Global and nodal topological parameters were used to depict the alterations of the whole-brain WM network. RESULTS: We found that rMDD displayed increased global network efficiency (Eglob) and local network efficiency (Eloc) compared with HCs, whereas we found no significance between rBD and HCs. Compared with rBD and HCs, patients in the rMDD group showed increased nodal degree and nodal efficiency, and decreased nodal shortest path length in the four cerebral regions, including the right calcarine fissure (CAL.R), right cuneus (CUN.R), left lingual gyrus (LING.L), and left middle occipital gyrus (MOG.L). We did not find any rBD specific changes of nodal topological metrics. LIMITATIONS: The main limitation is the possible effects of medication and BD subtypes on the results. CONCLUSIONS: Our findings indicate that rMDD exhibited elevated global properties compared with HCs group, and increased nodal properties in the CAL.R, CUN.R, LING.L, and MOG.L specifically compared with rBD and HCs, which may underlie the distinction of the two affective disorders in remission.