Identification of Potential Biomarkers for Major Depressive Disorder: Based on Integrated Bioinformatics and Clinical Validation.

Major depressive disorder (MDD) is a severe mental illness characterized by a lack of objective biomarkers. Mounting evidence suggests there are extensive transcriptional molecular changes in the prefrontal cortex (PFC) of individuals with MDD. However, it remains unclear whether there are specific genes that are consistently altered and possess diagnostic power. In this study, we conducted a systematic search of PFC datasets of MDD patients from the Gene Expression Omnibus database. We calculated the differential expression of genes (DEGs) and identified robust DEGs using the RRA and MetaDE methods. Furthermore, we validated the consistently altered genes and assessed their diagnostic power through enzyme-linked immunosorbent assay experiments in our clinical blood cohort. Additionally, we evaluated the diagnostic power of hub DEGs in independent public blood datasets. We obtained eight PFC datasets, comprising 158 MDD patients and 263 healthy controls, and identified a total of 1468 unique DEGs. Through integrated analysis, we identified 290 robustly altered DEGs. Among these, seven hub DEGs (SLC1A3, PON2, AQP1, EFEMP1, GJA1, CENPD, HSD11B1) were significantly down-regulated at the protein level in our clinical blood cohort. Moreover, these hub DEGs exhibited a negative correlation with the Hamilton Depression Scale score (P < 0.05). Furthermore, these hub DEGs formed a panel with promising diagnostic power in three independent public blood datasets (average AUCs of 0.85) and our clinical blood cohort (AUC of 0.92). The biomarker panel composed of these genes demonstrated promising diagnostic efficacy for MDD and serves as a useful tool for its diagnosis.

Correction: A differential-targeting core-shell microneedle patch with coordinated and prolonged release of mangiferin and MSC-derived exosomes for scarless skin regeneration.

Correction for 'A differential-targeting core-shell microneedle patch with coordinated and prolonged release of mangiferin and MSC-derived exosomes for scarless skin regeneration' by Shang Lyu et al., Mater. Horiz., 2024, https://doi.org/10.1039/D3MH01910A.

Connections between the middle frontal gyrus and dorso-ventral attention network associate with the development of attentional symptoms.

BACKGROUND: The right MFG has been proposed as a convergence site for the DAN and VAN, regulating both networks and enabling flexible modulation of attention. However, it is unclear if the connections between the right MFG and these networks can predict changes in ADHD symptoms. METHODS: This study used data from the Children School Functions and Brain Development project (n = 713, 56.2% boys). Resting-state fMRI was employed to analyze the connections of the right MFG with DAN/VAN, connectome-based predictive modeling was applied for longitudinal prediction, and ADHD PRS were used for genetic analysis. RESULTS: The ADHD symptoms were associated with the connections between the right MFG and DAN subregion, including the FEF, as well as the VAN subregions, namely the IPL and IFG. Furthermore, these connections of the right MFG with FEF, IPL, and IFG could significantly predict changes in ADHD symptoms over one year and mediate the prediction of ADHD symptom changes by PRS for ADHD. Finally, the validation samples confirmed that the functional connectivity between the right MFG and FEF/IPL in ADHD patients was significantly weaker than that in the typically developing controls, and this difference disappeared after medication. CONCLUSIONS: The connection of right MFG with DAN and VAN can serve as a predictive indicator for changes in ADHD symptoms over the following year, while also mediating the prediction of ADHD symptom changes by PRS for ADHD. These findings hold promise as potential biomarkers for early identification of children at risk of developing ADHD.

Oxidative stress promotes liver fibrosis by modulating the microRNA-144 and SIN3A-p38 pathways in hepatic stellate cells.

Background & Aims: Reactive oxygen species (ROS) act as modulators triggering cellular dysfunctions and organ damage including liver fibrosis in which hepatic stellate cell (HSC) activation plays a key role. Previous studies suggest that microRNA-144 (miR-144) acts as a pro-oxidant molecule; however, whether and how miR-144 affects HSC activation and liver fibrosis remain unknown. Methods: Carbon tetrachloride (CCl4) and bile duct ligation (BDL)-induced experimental liver fibrosis models were used. Hepatic miR-144 expression was analyzed by miRNA in situ hybridization with RNAscope probe. The in vivo effects of silencing or overexpressing miR-144 were examined with an adeno-associated virus 6 (AAV6) carrying miR-144 inhibitor or mimics in fibrotic mouse experimental models. Results: In this study, we demonstrated that ROS treatment significantly upregulated miR-144 in HSCs, which further promoted HSC activation in vitro. Interestingly, miR-144 was preferentially elevated in HSCs of experimental liver fibrosis in mice and in human liver fibrotic tissues. Furthermore, in vivo loss or gain-of-function experiments via AAV6 carrying miR-144 antagomir or agomir revealed that blockade of miR-144 in HSCs mitigated, while overexpression of miR-144 in HSCs accelerated the development of experimental liver fibrosis. Mechanistically, SIN3 transcription regulator family member A (SIN3A), a transcriptional repressor, was identified to be the target of miR-144 in HSCs. MiR-144 downregulated Sin3A, and in line with this result, specific knockdown of Sin3a in HSCs remarkedly activated p38 MAPK signaling pathway to promote HSC activation, eventually exacerbating liver fibrosis. Conclusions: Oxidative stress-driven miR-144 fuels HSC activation and liver fibrogenesis by limiting the SIN3A-p38 axis. Thus, a specific inhibition of miR-144 in HSCs could be a novel therapeutic strategy for the treatment of liver fibrosis.

Fungal fermentation of Fuzhuan brick tea: A comprehensive evaluation of sensory properties using chemometrics, visible near-infrared spectroscopy, and electronic nose.

Fuzhuan brick tea (FBT) fungal fermentation is a key factor in achieving its unique dark color, aroma, and taste. Therefore, it is essential to develop a rapid and reliable method that could assess its quality during FBT fermentation process. This study focused on using electronic nose (e-nose) and spectroscopy combination with sensory evaluations and physicochemical measurements for building machine learning (ML) models of FBT. The results showed that the fused data achieved 100 % accuracy in classifying the FBT fermentation process. The SPA-MLR method was the best prediction model for FBT quality (R2 = 0.95, RMSEP = 0.07, RPD = 4.23), and the fermentation process was visualized. Where, it was effectively detecting the degree of fermentation relationship with the quality characteristics. In conclusion, the current study's novelty comes from the established real-time method that could sensitively detect the unique post-fermentation quality components based on the integration of spectral, and e-nose and ML approaches.

Niclosamide subacute exposure alters the immune response and microbiota of the gill and gut in black carp larvae, Mylopharyngodon piceus.

Niclosamide (NIC) is a commonly used insecticide and molluscicide in the prevention and treatment of parasitic diseases in fish. The utilization of NIC has the potential to disrupt the microbial community present on the mucosal tissue of fish, leading to localized inflammatory responses. The objective of this study was to evaluate the impact of NIC on the immune system and bacterial populations within the gill and gut of Mylopharyngodon piceus. Fish were subjected to varying concentrations of NIC, including a control group (0 µg/L), a low NIC group (15% 96 h LC50, LNG, 9.8 µg/L), and a high NIC group (80% 96 h LC50, HNG, 52.5 µg/L). Gill and gut samples were collected 28 days post-exposure for analysis. The findings revealed that the 96-h LC50 for NIC was determined to be 65.7 µg/L, and histopathological examination demonstrated that exposure to NIC resulted in gill filament subepithelial edema, exfoliation, degeneration, and a decrease in gill filament length. Furthermore, the gut exhibited apical enterocyte degeneration and leucocyte infiltration following NIC exposure. Additionally, NIC exposure led to a significant elevation in the levels of immunoglobulin M (IgM), complement component 3 (C3), and complement component 4 (C4) in both gill and gut tissues. Moreover, the activity of lysozyme (LYZ) was enhanced in the gill, while the activities of peroxidase (POD) and immunoglobulin T (IgT) were increased in gut tissue. The exposure to NIC resulted in enhanced mRNA expression of c3, c9, tnfα, il6, il8, and il11 in the gill tissue, while decreasing c3 and il8 expression in the gut tissue. Furthermore, the natural resistance-associated macrophage protein (nramp) mRNA increased, and liver-expressed antimicrobial peptide 2 (leap2) mRNA decreased in gill and gut tissues. And hepcidin (hepc) mRNA levels rose in gill but fell in gut tissue. NIC exposure also led to a decrease in gill bacterial richness and diversity, which significantly differed from the control group, although this separation was not significant in the gut tissue. In conclusion, the administration of NIC resulted in alterations in both the immune response and mucosal microbiota of fish. Furthermore, it was noted that gills displayed a heightened vulnerability to sublethal effects of NIC in comparison to gut tissues.

Advanced deep learning algorithm for instant discriminating of tea leave stress symptoms by smartphone-based detection.

The primary challenges in tea production under multiple stress exposures have negatively affected its global market sustainability, so introducing an infield fast technique for monitoring tea leaves' stresses has tremendous urgent needs. Therefore, this study aimed to propose an efficient method for the detection of stress symptoms based on a portable smartphone with deep learning models. Firstly, a database containing over 10,000 images of tea garden canopies in complex natural scenes was developed, which included healthy (no stress) and three types of stress (tea anthracnose (TA), tea blister blight (TB) and sunburn (SB)). Then, YOLOv5m and YOLOv8m algorithms were adapted to discriminate the four types of stress symptoms; where the YOLOv8m algorithm achieved better performance in the identification of healthy leaves (98%), TA (92.0%), TB (68.4%) and SB (75.5%). Furthermore, the YOLOv8m algorithm was used to construct a model for differentiation of disease severity of TA, and a satisfactory result was obtained with the accuracy of mild, moderate, and severe TA infections were 94%, 96%, and 91%, respectively. Besides, we found that CNN kernels of YOLOv8m could efficiently extract the texture characteristics of the images at layer 2, and these characteristics can clearly distinguish different types of stress symptoms. This makes great contributions to the YOLOv8m model to achieve high-precision differentiation of four types of stress symptoms. In conclusion, our study provided an effective system to achieve low-cost, high-precision, fast, and infield diagnosis of tea stress symptoms in complex natural scenes based on smartphone and deep learning algorithms.

Evaluating the diagnostic accuracy of heat shock proteins and their combination with Alpha-Fetoprotein in the detection of hepatocellular carcinoma: a meta-analysis.

BACKGROUND: A growing body of research suggests that heat shock proteins (HSPs) may serve as diagnostic biomarkers for hepatocellular carcinoma (HCC), but their results are still controversial. This meta-analysis endeavors to evaluate the diagnostic accuracy of HSPs both independently and in conjunction with alpha-fetoprotein (AFP) as novel biomarkers for HCC detection. METHODS: Pooled statistical indices, including sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) with 95% confidence intervals (CI), were computed to assess the diagnostic accuracy of HSPs, AFP, and their combinations. Additionally, the area under the summary receiver operating characteristic (SROC) curve (AUC) was determined. RESULTS: A total of 2013 HCC patients and 1031 control subjects from nine studies were included in this meta-analysis. The summary estimates for HSPs and AFP are as follows: sensitivity of 0.78 (95% CI: 0.69-0.85) compared to 0.73 (95% CI: 0.65-0.80); specificity of 0.89 (95% CI: 0.81-0.95) compared to 0.86 (95% CI: 0.77-0.91); PLR of 7.4 (95% CI: 3.7-14.9) compared to 5.1 (95% CI: 3.3-8.1); NLR of 0.24 (95% CI: 0.16-0.37) compared to 0.31 (95% CI: 0.24-0.41); DOR of 30.19 (95% CI: 10.68-85.37) compared to 16.34 (95% CI: 9.69-27.56); and AUC of 0.90 (95% CI: 0.87-0.92) compared to 0.85 (95% CI: 0.82-0.88). The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.90 (95% CI: 0.82-0.95), 0.94 (95% CI: 0.82-0.98), 14.5 (95% CI: 4.6-45.4), 0.11 (95% CI: 0.06-0.20), 133.34 (95% CI: 29.65-599.61), and 0.96 (95% CI: 0.94-0.98) for the combination of HSPs and AFP. CONCLUSION: Our analysis suggests that HSPs have potential as a biomarker for clinical use in the diagnosis of HCC, and the concurrent utilization of HSPs and AFP shows notable diagnostic effectiveness for HCC.

Quantifying the impact of anthropogenic emissions and aquatic environmental impacts on sedimentary mercury variations in a typical urban river.

In urban and industrial regions, sedimentary mercury (Hg) serves as the crucial indicator for Hg pollution, posing potential risks to ecology and human health. The physicochemical processes of Hg in aquatic environments are influenced by various factors such as anthropogenic emissions and aquatic environmental impacts, making it challenging to quantify the drivers of total mercury (THg) variations. Here, we analyzed the spatiotemporal variations, quantified driving factors, and assessed accumulation risks of sedimentary THg from the mainstream of a typical urban river (Haihe River). THg in the urban region (37-3237 ng g-1) was significantly higher (t-test, p < 0.01) than in suburban (71-2317 ng g-1) and developing regions (156-916 ng g-1). The sedimentary THg in suburban and developing regions increased from 2003 to 2018, indicating the elevated atmospheric deposition of Hg. Together with the temperature, grain size of sediments, total organic carbon (TOC), the pH and salinity of water, 40 components of parent and substituted polycyclic aromatic hydrocarbons (PAHs) were first introduced to quantify the driver of sedimentary THg based on generalized additive model. Results showed that anthropogenic emissions, including three PAHs components (31%) and TOC (63%), accounted for 94% of sedimentary THg variations. The aquatic environmental impacts accounted for 5% of sedimentary THg variations. The geo-accumulation index of THg indicated moderate to heavy accumulation in the urban region. This study demonstrates that homologous pollutants such as PAHs can be used to trace sources and variations of Hg pollution, supporting their co-regulation as international conventions regulate pollutants.

CatLet score and clinical CatLet score as predictors of long-term outcomes in patients with acute myocardial infarction presenting later than 12 hours from symptom onset.

BACKGROUND: Our recently developed Coronary Artery Tree description and Lesion EvaluaTion (CatLet) angiographic scoring system is unique in its description of the variability in the coronary anatomy, the degree of stenosis of a diseased coronary artery, and its subtended myocardial territory, and can be utilized to predict clinical outcomes for patients with acute myocardial infarction (AMI) presenting ≤12 h after symptom onset. The current study aimed to assess whether the Clinical CatLet score (CCS), as compared with CatLet score (CS), better predicted clinical outcomes for AMI patients presenting >12 h after symptom onset. METHODS: CS was calculated in 1018 consecutive AMI patients enrolled in a retrospective registry. CCS was calculated by multiplying CS by the ACEF I score (age, creatinine, and left ventricular ejection fraction). Primary endpoint was major adverse cardiac events (MACEs) at 4-year-follow-up, a composite of cardiac death, myocardial infarction, and ischemia-driven revascularization. RESULTS: Over a 4-year follow-up period, both scores were independent predictors of clinical outcomes after adjustment for a broad spectrum of risk factors. Areas-under-the-curve (AUCs) for CS and CCS were 0.72(0.68-0.75) and 0.75(0.71-0.78) for MACEs; 0.68(0.63-0.73) and 0.78(0.74-0.83) for all-cause death; 0.73(0.68-0.79) and 0.83(0.79-0.88) for cardiac death; and 0.69(0.64-0.73) and 0.75(0.7-0.79) for myocardial infarction; and 0.66(0.61-0.7) and 0.63(0.58-0.68) for revascularization, respectively. CCS performed better than CS in terms of the above-mentioned outcome predictions, as confirmed by the net reclassification and integrated discrimination indices. CONCLUSIONS: CCS was better than CS to be able to risk-stratify long-term outcomes in AMI patients presenting >12 h after symptom onset. These findings have indicated that both anatomic and clinical variables should be considered in decision-making on management of patients with AMI presenting later.

Polygenic risk-stratified screening for nasopharyngeal carcinoma in high-risk endemic areas of China: a cost-effectiveness study.

Background: Nasopharyngeal carcinoma (NPC) has an extremely high incidence rate in Southern China, resulting in a severe disease burden for the local population. Current EBV serologic screening is limited by false positives, and there is opportunity to integrate polygenic risk scores for personalized screening which may enhance cost-effectiveness and resource utilization. Methods: A Markov model was developed based on epidemiological and genetic data specific to endemic areas of China, and further compared polygenic risk-stratified screening [subjects with a 10-year absolute risk (AR) greater than a threshold risk underwent EBV serological screening] to age-based screening (EBV serological screening for all subjects). For each initial screening age (30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, and 65-69 years), a modeled cohort of 100,000 participants was screened until age 69, and then followed until age 79. Results: Among subjects aged 30 to 54 years, polygenic risk-stratified screening strategies were more cost-effective than age-based screening strategies, and almost comprised the cost-effectiveness efficiency frontier. For men, screening strategies with a 1-year frequency and a 10-year absolute risk (AR) threshold of 0.7% or higher were cost-effective, with an incremental cost-effectiveness ratio (ICER) below the willingness to pay (¥203,810, twice the local per capita GDP). Specifically, the strategies with a 10-year AR threshold of 0.7% or 0.8% are the most cost-effective strategies, with an ICER ranging from ¥159,752 to ¥201,738 compared to lower-cost non-dominated strategies on the cost-effectiveness frontiers. The optimal strategies have a higher probability (29.4-35.8%) of being cost-effective compared to other strategies on the frontier. Additionally, they reduce the need for nasopharyngoscopies by 5.1-27.7% compared to optimal age-based strategies. Likewise, for women aged 30-54 years, the optimal strategy with a 0.3% threshold showed similar results. Among subjects aged 55 to 69 years, age-based screening strategies were more cost-effective for men, while no screening may be preferred for women. Conclusion: Our economic evaluation found that the polygenic risk-stratified screening could improve the cost-effectiveness among individuals aged 30-54, providing valuable guidance for NPC prevention and control policies in endemic areas of China.

Correction: Assessment of network structure characteristics and factors of corporate flows in Guangdong Province.

[This corrects the article DOI: 10.1371/journal.pone.0293870.].

Advances in Synthesis and Applications of Single-Atom Catalysts for Metal Oxide-Based Gas Sensors.

As a stable, low-cost, environment-friendly, and gas-sensitive material, semiconductor metal oxides have been widely used for gas sensing. In the past few years, single-atom catalysts (SACs) have gained increasing attention in the field of gas sensing with the advantages of maximized atomic utilization and unique electronic and chemical properties and have successfully been applied to enhance the detection sensitivity and selectivity of metal oxide gas sensors. However, the application of SACs in gas sensors is still in its infancy. Herein, we critically review the recent advances and current status of single-atom catalysts in metal oxide gas sensors, providing some suggestions for the development of this field. The synthesis methods and characterization techniques of SAC-modified metal oxides are summarized. The interactions between SACs and metal oxides are crucial for the stable loading of single-atom catalysts and for improving gas-sensitive performance. Then, the current application progress of various SACs (Au, Pt, Cu, Ni, etc.) in metal oxide gas sensors is introduced. Finally, the challenges and perspectives of SACs in metal oxide gas sensors are presented.

Development of segregation and integration of functional connectomes during the first 1,000 days.

The first 1,000 days of human life lay the foundation for brain development and later cognitive growth. However, the developmental rules of the functional connectome during this critical period remain unclear. Using high-resolution, longitudinal, task-free functional magnetic resonance imaging data from 930 scans of 665 infants aged 28 postmenstrual weeks to 3 years, we report the early maturational process of connectome segregation and integration. We show the dominant development of local connections alongside a few global connections, the shift of brain hubs from primary regions to high-order association cortices, the developmental divergence of network segregation and integration along the anterior-posterior axis, the prediction of neurocognitive outcomes, and their associations with gene expression signatures of microstructural development and neuronal metabolic pathways. These findings advance our understanding of the principles of connectome remodeling during early life and its neurobiological underpinnings and have implications for studying typical and atypical development.

Association between Abdominal Aortic Calcification and Coronary Heart Disease in Essential Hypertension: A Cross-Sectional Study from the 2013-2014 National Health and Nutrition Examination Survey.

BACKGROUND: This study aimed to investigate the association between abdominal aortic calcification (AAC) and coronary heart disease (CHD) in essential hypertension (EH). METHODS: This study included patients diagnosed with EH during the 2013-2014 NHANES survey cycle. The study cohort was categorized into the following four groups based on their AAC-24 score: no AAC (0); mild AAC (1-4); moderate AAC (5-15); and severe AAC (16-24). Logistic regression models were used to assess the association between AAC and CHD. Restricted cubic spline curves (RCS) were used to explore possible nonlinear relationships between AAC and CHD. RESULTS: The prevalence of CHD was found to be higher in the moderate AAC and severe AAC groups than in the group without AAC (40.1% versus 30.9%, 47.7% versus 30.9%). On a continuous scale, the fully adjusted model showed a 7% increase in the risk of CHD prevalence per score increase in AAC [OR (95% CI) = 1.07 (1.03-1.11)]. On a categorical scale, the fully adjusted model showed the risk of CHD prevalence in EH patients with moderate AAC and severe AAC was 2.06 (95%CI, 1.23-3.45) and 2.18 (1.09-5.25) times higher than that in patients without AAC, respectively. The RCS curve suggested a dose-response linear relationship between AAC and CHD. CONCLUSION: These findings highlight that in patients with EH, a higher severity of AAC is associated with a higher risk of CHD prevalence.

High-valent metal-oxo species transformation and regulation by co-existing chloride: Reaction pathways and impacts on the generation of chlorinated by-products.

High-valent metal-oxo species (HMOS) have been extensively recognized in advanced oxidation processes (AOPs) owing to their high selectivity and high chemical utilization efficiency. However, the interactions between HMOS and halide ions in sewage wastewater are complicated, leading to ongoing debates on the intrinsic reactive species and impacts on remediation. Herein, we prepared three typical HMOS, including Fe(IV), Mn(V)-nitrilotriacetic acid complex (Mn(V)NTA) and Co(IV) through peroxymonosulfate (PMS) activation and comparatively studied their interactions with Cl- to reveal different reactive chlorine species (RCS) and the effects of HMOS types on RCS generation pathways. Our results show that the presence of Cl- alters the cleavage behavior of the peroxide OO bond in PMS and prohibits the generation of Fe(IV), spontaneously promoting SO4•- production and its subsequent transformation to secondary radicals like Cl• and Cl2•-. The generation and oxidation capacity of Mn(V)NTA was scarcely influenced by Cl-, while Cl- would substantially consume Co(IV) and promote HOCl generation through an oxygen-transfer reaction, evidenced by density functional theory (DFT) and deuterium oxide solvent exchange experiment. The two-electron-transfer standard redox potentials of Fe(IV), Mn(V)NTA and Co(IV) were calculated as 2.43, 2.55 and 2.85 V, respectively. Due to the different reactive species and pathways in the presence of Cl-, the amounts of chlorinated by-products followed the order of Co(II)/PMS > Fe(II)/PMS > Mn(II)NTA/PMS. Thus, this work renovates the knowledge of halide chemistry in HMOS-based systems and sheds light on the impact on the treatment of salinity-containing wastewater.

In Situ Synthesis of Liquid Metal Conductive Fibers toward Smart Cloth.

To meet the diverse needs of humans, smart cloth has become a potential research hotspot to replace traditional cloth. However, it is challenging to manufacture a flexible fabric with multiple functions. Here, we introduce a smart cloth based on liquid metal (LM) conductive fibers. Ga2O3 nanoparticles are obtained through ultrasonic pretreatment. Furthermore, a coordination bond is formed between thiol groups on the surface of protein fibers and Ga2O3 through a scraping method, allowing Ga2O3 particles to be grafted onto the surface of protein fibers in situ. Finally, LM conductive fibers are encapsulated using a photocuring adhesive. In addition, a wearable smart cloth integrated with multiple sensors has been developed based on LM conductive fibers. Users can not only monitor their movement trajectory and the surrounding environment in real time but also have their data supervised by family members through a client, achieving remote and continuous monitoring. The development of this wearable smart cloth provides strong support for future wearable, flexible electronic devices.

Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2.

The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.

Biolimus-coated versus paclitaxel-coated balloons for coronary in-stent restenosis (BIO ASCEND ISR): a randomised, non-inferiority trial.

BACKGROUND: The treatment of in-stent restenosis (ISR) after drug-eluting stent (DES) implantation remains challenging in current clinical practice. AIMS: The study was conducted to investigate a novel biolimus-coated balloon (BCB) for the treatment of coronary DES-ISR compared with the best-investigated paclitaxel-coated balloon (PCB). METHODS: This was a prospective, multicentre, randomised, non-inferiority trial comparing a novel BCB with a clinically proven PCB for coronary DES-ISR. The primary endpoint was in-segment late lumen loss (LLL) at 9 months assessed by an independent core laboratory. Baseline and follow-up optical coherence tomography were performed in a prespecified subgroup of patients. RESULTS: A total of 280 patients at 17 centres were randomised to treatment with a BCB (n=140) versus a PCB (n=140). At 9 months, LLL in the BCB group was 0.23±0.37 mm compared to 0.25±0.35 mm in the PCB group; the mean difference between the groups was -0.02 (95% confidence interval [CI]: -0.12 to 0.07) mm; p-value for non-inferiority<0.0001. Similar clinical outcomes were also observed for both groups at 12 months. In the optical coherence tomography substudy, the neointimal area at 9 months was 2.32±1.04 mm2 in the BCB group compared to 2.37±0.93 mm2 in the PCB group; the mean difference between the groups was -0.09 (95% CI: -0.94 to 0.76) mm2; p=non-significant. CONCLUSIONS: This head-to-head comparison of a novel BCB shows similar angiographic outcomes in the treatment of coronary DES-ISR compared with a clinically proven PCB. (ClinicalTrials.gov: NCT04733443).

Defocus-integration interferometric scattering microscopy for speckle suppression and enhancing nanoparticle detection on a substrate.

Direct optical detection and imaging of single nanoparticles on a substrate in wide field underpin vast applications across different research fields. However, speckles originating from the unavoidable random surface undulations of the substrate ultimately limit the size of the decipherable nanoparticles by the current optical techniques, including the ultrasensitive interferometric scattering microscopy (iSCAT). Here, we report a defocus-integration iSCAT to suppress the speckle noise and to enhance the detection and imaging of single nanoparticles on an ultra-flat glass substrate and a silicon wafer. In particular, we discover distinct symmetry properties of the scattering phase between the nanoparticle and the surface undulations that cause the speckles. Consequently, we develop the defocus-integration technique to suppress the speckles. We experimentally achieve an enhancement of the signal-to-noise ratio by 6.9 dB for the nanoparticle detection. We demonstrate that the technique is generally applicable for nanoparticles of various materials and for both low and high refractive index substrates.