scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics.

Single-cell RNA sequencing has achieved massive success in biological research fields. Discovering novel cell types from single-cell transcriptomics has been demonstrated to be essential in the field of biomedicine, yet is time-consuming and needs prior knowledge. With the unprecedented boom in cell atlases, auto-annotation tools have become more prevalent due to their speed, accuracy and user-friendly features. However, existing tools have mostly focused on general cell-type annotation and have not adequately addressed the challenge of discovering novel rare cell types. In this work, we introduce scNovel, a powerful deep learning-based neural network that specifically focuses on novel rare cell discovery. By testing our model on diverse datasets with different scales, protocols and degrees of imbalance, we demonstrate that scNovel significantly outperforms previous state-of-the-art novel cell detection models, reaching the most AUROC performance(the only one method whose averaged AUROC results are above 94%, up to 16.26% more comparing to the second-best method). We validate scNovel's performance on a million-scale dataset to illustrate the scalability of scNovel further. Applying scNovel on a clinical COVID-19 dataset, three potential novel subtypes of Macrophages are identified, where the COVID-related differential genes are also detected to have consistent expression patterns through deeper analysis. We believe that our proposed pipeline will be an important tool for high-throughput clinical data in a wide range of applications.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Self-supervised contrastive learning for integrative single cell RNA-seq data analysis.

We present a novel self-supervised Contrastive LEArning framework for single-cell ribonucleic acid (RNA)-sequencing (CLEAR) data representation and the downstream analysis. Compared with current methods, CLEAR overcomes the heterogeneity of the experimental data with a specifically designed representation learning task and thus can handle batch effects and dropout events simultaneously. It achieves superior performance on a broad range of fundamental tasks, including clustering, visualization, dropout correction, batch effect removal, and pseudo-time inference. The proposed method successfully identifies and illustrates inflammatory-related mechanisms in a COVID-19 disease study with 43 695 single cells from peripheral blood mononuclear cells.

Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study.

BACKGROUND: Melancholic depression (MD) is one of the most prevalent and severe subtypes of major depressive disorder (MDD). Previous studies have revealed inconsistent results regarding alterations in grey matter volume (GMV) of the hippocampus and amygdala of MD patients, possibly due to overlooking the complexity of their internal structure. The hippocampus and amygdala consist of multiple and functionally distinct subregions, and these subregions may play different roles in MD. This study aims to investigate the volumetric alterations of each subregion of the hippocampus and amygdala in patients with MD and non-melancholic depression (NMD). METHODS: A total of 146 drug-naïve, first-episode MDD patients (72 with MD and 74 with NMD) and 81 gender-, age-, and education-matched healthy controls (HCs) were included in the study. All participants underwent magnetic resonance imaging (MRI) scans. The subregional segmentation of hippocampus and amygdala was performed using the FreeSurfer 6.0 software. The multivariate analysis of covariance (MANCOVA) was used to detect GMV differences of the hippocampal and amygdala subregions between three groups. Partial correlation analysis was conducted to explore the relationship between hippocampus or amygdala subfields and clinical characteristics in the MD group. Age, gender, years of education and intracranial volume (ICV) were included as covariates in both MANCOVA and partial correlation analyses. RESULTS: Patients with MD exhibited a significantly lower GMV of the right hippocampal tail compared to HCs, which was uncorrelated with clinical characteristics of MD. No significant differences were observed among the three groups in overall and subregional GMV of amygdala. CONCLUSIONS: Our findings suggest that specific hippocampal subregions in MD patients are more susceptible to volumetric alterations than the entire hippocampus. The reduced right hippocampal tail may underlie the unique neuropathology of MD. Future longitudinal studies are required to better investigate the associations between reduced right hippocampal tail and the onset and progression of MD.

Health economics study of paliperidone palmitate in the treatment of schizophrenia: a 12-month cohort study.

BACKGROUND: To analyze the economic benefits of paliperidone palmitate in the treatment of schizophrenia. METHODS: We collected 546 patients who met the diagnostic criteria for schizophrenia according to the 《International Statistical Classification of Diseases and Related Health Problems,10th》(ICD-10). We gathered general population data such as gender, age, marital status, and education level, then initiated treatment with paliperidone palmitate. Then Follow-up evaluations were conducted at 1, 3, 6, 9, and 12 months after the start of treatment to assess clinical efficacy, adverse reactions, and injection doses. We also collected information on the economic burden before and after 12 months of treatment, as well as the number of outpatient visits and hospitalizations in the past year to analyze economic benefits. RESULTS: The baseline patients totaled 546, with 239 still receiving treatment with paliperidone palmitate 12 months later. After 12 months of treatment, the number of outpatient visits per year increased compared to before (4 (2,10) vs. 12 (4,12), Z=-5.949, P < 0.001), while the number of hospitalizations decreased (1 (1,3) vs. 1 (1,2), Z = 5.625, P < 0.001). The inpatient costs in the direct medical expenses of patients after 12 months of treatment decreased compared to before (5000(2000,12000) vs. 3000 (1000,8050), P < 0.05), while there was no significant change in outpatient expenses and direct non-medical expenses (transportation, accommodation, meal, and family accompanying expenses, etc.) (P > 0.05); the indirect costs of patients after 12 months of treatment (lost productivity costs for patients and families, economic costs due to destructive behavior, costs of seeking non-medical assistance) decreased compared to before (300(150,600) vs. 150(100,200), P < 0.05). CONCLUSION: Palmatine palmitate reduces the number of hospitalizations for patients, as well as their direct and indirect economic burdens, and has good economic benefits.

Fabrication of Nitrogen Based Magnetic Conjugated Microporous Polymer for Efficient Extraction of Neonicotinoids in Water Samples.

Facile and sensitive methods for detecting neonicotinoids (NEOs) in aquatic environments are crucial because they are found in extremely low concentrations in complex matrices. Herein, nitrogen-based magnetic conjugated microporous polymers (Fe3O4@N-CMP) with quaternary ammonium groups were synthesized for efficient magnetic solid-phase extraction (MSPE) of NEOs from tap water, rainwater, and lake water. Fe3O4@N-CMP possessed a suitable specific surface area, extended π-conjugated system, and numerous cationic groups. These properties endow Fe3O4@N-CMP with superior extraction efficiency toward NEOs. The excellent adsorption capacity of Fe3O4@N-CMP toward NEOs was attributed to its π-π stacking, Lewis acid-base, and electrostatic interactions. The proposed MSPE-HPLC-DAD approach based on Fe3O4@N-CMP exhibited a wide linear range (0.1-200 µg/L), low detection limits (0.3-0.5 µg/L), satisfactory precision, and acceptable reproducibility under optimal conditions. In addition, the established method was effectively utilized for the analysis of NEOs in tap water, rainwater, and lake water. Excellent recoveries of NEOs at three spiked levels were in the range of 70.4 to 122.7%, with RSDs less than 10%. This study provides a reliable pretreatment method for monitoring NEOs in environmental water samples.

Family-based genetic analysis in schizophrenia by whole-exome sequence to identify rare pathogenic variants.

Schizophrenia (SCZ) is influenced by a combination of genetic and environmental factors. Although several studies have been conducted to identify the causative loci and genes, few of these loci or genes can be repeated due to the high phenotypic and genetic heterogeneity of disease, and their mechanisms are not fully understood. There may be some "missing heritability" that has not yet been found. In order to investigate the deleterious heritable mutations, whole-exome sequencing (WES) in pedigrees with SCZ was used in the current work. Two unrelated pedigrees with SCZ were recruited to perform WES. Genetic analysis was next performed to find potential variants in accordance with the prioritized strategy. Followed by genetic analysis to detect candidate variants according to the prioritized strategy. Next, a series of algorithms was used to predict the pathogenicity of variants. Sanger sequencing was finally conducted to verify the co-segregation. Recessive mutations in six genes (TFEB, SNAI2, TFAP2B, PRKDC, ST18 in Pedigree 1 and PKHD1L1 in Pedigree 2) that co-segregated with SCZ in two families were discovered through genetic analysis by WES. Sanger sequencing verified that all of the mutations in the affected siblings were homozygous. These results corroborated the hypothesis that SCZ exhibits strong heterogeneity and complex inheritance patterns. The newly discovered homozygous variations deepen our understanding of the mutation spectrum and offer more proof for the involvement of TFEB, SNAI2, TFAP2B, PRKDC, ST18, and PKHD1L1 in the development of SCZ.

Altered topology of individual brain structural covariance networks in major depressive disorder.

BACKGROUND: The neurobiological pathogenesis of major depression disorder (MDD) remains largely controversial. Previous literatures with limited sample size utilizing group-level structural covariance networks (SCN) commonly generated mixed findings regarding the topology of brain networks. METHODS: We analyzed T1 images from a high-powered multisite sample including 1173 patients with MDD and 1019 healthy controls (HCs). We used regional gray matter volume to construct individual SCN by utilizing a novel approach based on the interregional effect size difference. We further investigated MDD-related structural connectivity alterations using topological metrics. RESULTS: Compared to HCs, the MDD patients showed a shift toward randomization characterized by increased integration. Further subgroup analysis of patients in different stages revealed this randomization pattern was also observed in patients with recurrent MDD, while the first-episode drug naïve patients exhibited decreased segregation. Altered nodal properties in several brain regions which have a key role in both emotion regulation and executive control were also found in MDD patients compared with HCs. The abnormalities in inferior temporal gyrus were not influenced by any specific site. Moreover, antidepressants increased nodal efficiency in the anterior ventromedial prefrontal cortex. CONCLUSIONS: The MDD patients at different stages exhibit distinct patterns of randomization in their brain networks, with increased integration during illness progression. These findings provide valuable insights into the disruption in structural brain networks that occurs in patients with MDD and might be useful to guide future therapeutic interventions.

The effects of childhood maltreatment on cortical thickness and gray matter volume: a coordinate-based meta-analysis.

Childhood maltreatment has been suggested to have an adverse impact on neurodevelopment, including microstructural brain abnormalities. Existing neuroimaging findings remain inconsistent and heterogeneous. We aim to explore the most prominent and robust cortical thickness (CTh) and gray matter volume (GMV) alterations associated with childhood maltreatment. A systematic search on relevant studies was conducted through September 2022. The whole-brain coordinate-based meta-analysis (CBMA) on CTh and GMV studies were conducted using the seed-based d mapping (SDM) software. Meta-regression analysis was subsequently applied to investigate potential associations between clinical variables and structural changes. A total of 45 studies were eligible for inclusion, including 11 datasets on CTh and 39 datasets on GMV, consisting of 2550 participants exposed to childhood maltreatment and 3739 unexposed comparison subjects. Individuals with childhood maltreatment exhibited overlapped deficits in the median cingulate/paracingulate gyri simultaneously revealed by both CTh and GM studies. Regional cortical thinning in the right anterior cingulate/paracingulate gyri and the left middle frontal gyrus, as well as GMV reductions in the left supplementary motor area (SMA) was also identified. No greater regions were found for either CTh or GMV. In addition, several neural morphology changes were associated with the average age of the maltreated individuals. The median cingulate/paracingulate gyri morphology might serve as the most robust neuroimaging feature of childhood maltreatment. The effects of early-life trauma on the human brain predominantly involved in cognitive functions, socio-affective functioning and stress regulation. This current meta-analysis enhanced the understanding of neuropathological changes induced by childhood maltreatment.

A novel circular RNA, circIgfbp2, links neural plasticity and anxiety through targeting mitochondrial dysfunction and oxidative stress-induced synapse dysfunction after traumatic brain injury.

Traumatic brain injury (TBI) can lead to different neurological and psychiatric disorders. Circular RNAs (circRNAs) are highly expressed in the nervous system and enriched in synapses; yet, the underlying role and mechanisms of circRNAs in neurological impairment and dysfunction are still not fully understood. In this study, we investigated the expression of circRNAs and their relation with neurological dysfunction after TBI. RNA-Seq was used to detect differentially expressed circRNAs in injured brain tissue, revealing that circIgfbp2 was significantly increased. Up-regulated hsa_circ_0058195, which was highly homologous to circIgfbp2, was further confirmed in the cerebral cortex specimens and serum samples of patients after TBI. Moreover, correlation analysis showed a positive correlation between hsa_circ_0058195 levels and the Self-Rating Anxiety Scale scores in these subjects. Furthermore, knockdown of circIgfbp2 in mice relieved anxiety-like behaviors and sleep disturbances induced by TBI. Knockdown of circIgfbp2 in H2O2 treated HT22 cells alleviated mitochondrial dysfunction, while its overexpression reversed the process. Mechanistically, we discovered that circIgfbp2 targets miR-370-3p to regulate BACH1, and down-regulating BACH1 alleviated mitochondrial dysfunction and oxidative stress-induced synapse dysfunction. In conclusion, inhibition of circIgfbp2 alleviated mitochondrial dysfunction and oxidative stress-induced synapse dysfunction after TBI through the miR-370-3p/BACH1/HO-1 axis. Thus, circIgfbp2 might be a novel therapeutic target for anxiety and sleep disorders after TBI.

Connectome gradient dysfunction in major depression and its association with gene expression profiles and treatment outcomes.

Patients with major depressive disorder (MDD) exhibit concurrent deficits in both sensory and higher-order cognitive processing. Connectome studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this gradient structure is disrupted in patients with MDD and how this disruption associates with gene expression profiles and treatment outcome remain unknown. Using a large cohort of resting-state fMRI data from 2227 participants (1148 MDD patients and 1079 healthy controls) recruited at nine sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth, postmortem gene expression, and an 8-week antidepressant treatment (20 MDD patients) data to assess the meta-analytic cognitive functions, transcriptional profiles, and treatment outcomes related to MDD gradient alterations, respectively. Relative to the controls, MDD patients exhibited global topographic alterations in the principal primary-to-transmodal gradient, including reduced explanation ratio, gradient range, and gradient variation (Cohen's d = 0.16-0.21), and focal alterations mainly in the primary and transmodal systems (d = 0.18-0.25). These gradient alterations were significantly correlated with meta-analytic terms involving sensory processing and higher-order cognition. The transcriptional profiles explained 53.9% variance of the altered gradient pattern, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. The baseline gradient maps of patients significantly predicted symptomatic improvement after treatment. These results highlight the connectome gradient dysfunction in MDD and its linkage with gene expression profiles and clinical management, providing insight into the neurobiological underpinnings and potential biomarkers for treatment evaluation in this disorder.

Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium.

Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

Status of TWEAK DNA methylation and mRNA expression in systemic lupus erythematosus.

OBJECTIVE: Draw upon research into the serum concentration, mRNA expression, and DNA methylation of TNF-like weak inducer of apoptosis (TWEAK) in the peripheral blood of systemic lupus erythematosus patients and healthy controls in an attempt to investigate the epigenetics associated with TWEAK in the pathogenesis of systemic lupus erythematosus (SLE). METHODS: A total of 178 SLE patients (SLE group) and 131 sex-age matched healthy controls (HC group) were recruited. Enzyme-linked immunosorbent assays (ELISA) was used to detect serum protein concentration of TWEAK. TWEAK mRNA expression was analyzed by Real-time quantitative reverse transcriptase-polymerase chain reaction (RT-PCR). Methylation levels of the promotor of TWEAK were measured using quantitative DNA methylation analysis on the MassARRAY spectrometry. RESULTS: Serum TWEAK concentrations were not statistically significant in SLE patients and HCs. Nevertheless, serum TWEAK concentrations were significantly lower in patients with renal involvement when compared to those without it. Serum TWEAK concentrations were reduced in clinically active patients (SLEDAI ≥ 10) compared with clinically stable patients (SLEDAI < 10). It was also significantly associated with SLEDAI. Compared with the HC group, the TWEAK mRNA expression in the SLE group was significantly lower. The global DNA methylation levels of TWEAK in the SLE group were observed to be significantly higher than the HC group. SLE patients with renal involvement, and the clinically active patients had higher TWEAK global methylation as well as exhibited variation in certain CpG island methylation. Furthermore, TWEAK methylation negatively correlated with TWEAK mRNA expression. CONCLUSION: This study suggests that TWEAK DNA methylation is a valuable as a focus for epigenetic studies because of it potentially influencing TWEAK gene expression in SLE patients. Aberrant DNA methylation of TWEAK may be involved in the initiation and development of SLE.

Distinct functional brain abnormalities in insomnia disorder and obstructive sleep apnea.

Insomnia disorder (ID) and obstructive sleep apnea (OSA) are the two most prevalent sleep disorders worldwide, but the pathological mechanism has not been fully understood. Functional neuroimaging findings indicated regional abnormal neural activities existed in both diseases, but the results were inconsistent. This meta-analysis aimed to explore concordant regional functional brain changes in ID and OSA, respectively. We conducted a coordinate-based meta-analysis (CBMA) of resting-state functional magnetic resonance imaging (rs-fMRI) studies using the anisotropic effect-size seed-based d mapping (AES-SDM) approach. Studies that applied regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) or fractional ALFF (fALFF) to analyze regional spontaneous brain activities in ID or OSA were included. Meta-regressions were then applied to investigate potential associations between demographic variables and regional neural activity alterations. Significantly increased brain activities in the left superior temporal gyrus (STG.L) and right superior longitudinal fasciculus (SLF.R), as well as decreased brain activities in several right cerebral hemisphere areas were identified in ID patients. As for OSA patients, more distinct and complicated functional activation alterations were identified. Several neuroimaging alterations were functionally correlated with mean age, duration or illness severity in two patients groups revealed by meta-regressions. These functionally altered areas could be served as potential targets for non-invasive brain stimulation methods. This present meta-analysis distinguished distinct brain function changes in ID and OSA, improving our knowledge of the neuropathological mechanism of these two most common sleep disturbances, and also provided potential orientations for future clinical applications.Registration number: CRD42022301938.

A SERS/fluorescence dual-mode immuno-nanoprobe for investigating two anti-diabetic drugs on EGFR expressions.

A surface-enhanced Raman scattering (SERS)/fluorescence dual-mode nanoprobe was proposed to assess anti-diabetic drug actions from the expression level of the epidermal growth factor receptor (EGFR), which is a significant biomarker of breast cancers. The nanoprobe has a raspberry shape, prepared by coating a dye-doped silica nanosphere with a mass of SERS tags, which gives high gains in fluorescence imaging and SERS measurement. The in situ detection of EGFR on the cell membrane surfaces after drug actions was achieved by using this nanoprobe, and the detection results agree with the enzyme-linked immunosorbent assay (ELISA) kit. Our study suggests that rosiglitazone hydrochloride (RH) may be a potential drug for diabetic patients with breast cancer, while the anti-cancer effect of metformin hydrochloride (MH) is debatable since MH slightly promotes the EGFR expression of MCF-7 cells in this study. This sensing platform endows more feasibility for highly sensitive and accurate feedback of pesticide effects at the membrane protein level.

Cryptic diversity and phylogeography of the Rhabdophis nuchalis group (Squamata: Colubridae).

Previous studies, have found that the rapid uplift of the Tibetan plateau accelerated the diversification of species. However, there are few relevant biogeographic data for the Colubridae in this region. We conducted a comprehensive study of the Rhabdophis nuchalis Group, which presently contains four nominal species, R. nuchalis, R. pentasupralabialis, R. leonardi, and R. chiwen. Building upon previous studies with specimens we have recently examined, greater interspecific and intraspecific diversity has been revealed. Here we address three questions: (1) Do the intraspecific differences represent only geographic variation within lineages, or are there cryptic species? (2) What are the interspecific relationships among members of the R. nuchalis Group? (3) What has been the biogeographic history of this species group? To resolve these questions we used four mitochondrial gene sequences and one nuclear sequence to investigate the molecular phylogenetic and geographic relationships among populations. Our molecular analysis reveals cryptic species diversity within the R. nuchalis Group, and seven clades were identified in the analysis. Ancestral area estimation suggests that the R. nuchalis Group originated in the Hengduan Mountains approximately 6.24 Mya and expanded its range northward to the Qinling-Daba Mountains. The Sichuan Basin appears to have been a barrier to migration. Species divergence seems to have been related to the rapid uplift of the Qinghai-Tibet Plateau.

Disrupted intrinsic functional brain topology in patients with major depressive disorder.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Rh-Catalyzed Highly Enantioselective Hydrogenation of Functionalized Olefins with Chiral Ferrocenylphosphine-Spiro Phosphonamidite Ligands.

A highly efficient Rh-catalyzed hydrogenation of functionalized olefins has been realized by a new family of highly rigid chiral ferrocenylphosphine-spiro phosphonamidite ligands. Excellent enantiocontrol (>99% ee in most cases) was achieved with a wide range of α-dehydroamino acid esters and α-enamides. This practicable catalytic system was further applied in the scalable synthesis of highly optically pure key intermediates of cinacalcet and d-phenylalanine.

Electrostimulus-associated PD-L1 expression on cell membrane revealed by immune SERS nanoprobes.

Programmed cell death ligand 1 (PD-L1) is considered a major immune checkpoint protein that mediates antitumor immune suppression and response. Effectively regulating PD-L1 expression and dynamic monitoring has become a significant challenge in immunotherapy. Herein, we adopted smart surface-enhanced Raman scattering (SERS) nanoprobes to discriminate and monitor the dynamic expression of PD-L1 under external electrostimulation (ES). The PD-L1 expression levels in three cell lines (MCF-7 cells, HeLa cells, and H8 cells) were assessed before and after ES. The results reveal that ES could effectively and rapidly mediate a transformation in the PD-L1 content (or activity) on the cell membrane. Moreover, the molecular profiles of the cell membrane before and after ES were revealed by using the label-free SERS method with the help of immune plasmonic nanoparticles. The cell membrane protein information presented identifiable conformation changes after ES, showing a significant inhibitory effect on the bridge of PD-L1 and its antibody. This study indicates that ES is superior to chemical drugs due to lesser side effects because ES-based regulation does not depend on intracellular signalling pathways. This strategy is versatile and robust for discriminating and monitoring PD-L1 on cell membranes, thus providing potential clinical application value to PD-L1-mediated systems. This study also offers a practical way to assess the molecular profiles of cell membrane proteins in the presence of an external stimulus, which may be applicable to many membrane protein-related studies.

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.