Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders.

Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (ß = -4.36, P < 0.001) and neuropsychological function (ß = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (ß = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.

Transcriptome-wide N6-methyladenosine (m6A) methylation profiling of long non-coding RNAs in ovarian endometriosis.

N6-methyladenosine (m6A) methylation is the most prevalent internal epigenetic posttranscriptional mechanism for regulating mammalian RNA. Despite recent advances in determining the biological functions of m6A methylation, its association with the pathology of ovarian endometriosis remains uncertain. Herein, we performed m6A transcriptome-wide profiling to identify key lncRNAs with m6A modification involved in ovarian endometriosis development by bioinformatics analysis. We found the total m6A level was lower in ovarian endometriosis than in normal endometrium samples, with 9663 m6A peaks associated with 8989 lncRNAs detected in ovarian endometriosis and 9902 m6A peaks associated with 9210 lncRNAs detected in normal endometrium samples. These m6A peaks were primarily enriched within AAACU motifs. Functional enrichment analysis indicated that pathways involving the regulation of adhesion and development were significantly enriched in these differentially methylated lncRNAs. The regulatory relationships among lncRNAs, microRNAs (miRNAs), and mRNAs were identified by competing endogenous RNA (ceRNA) analysis and determination of the network regulating lncRNA-mRNA expression. Several specific lncRNA, including LINC00665, LINC00937, FZD10-AS1, DIO3OS and GATA2-AS1 which were differently expressed and modified by m6A, were validated using qRT-PCR and its interaction with infiltrating immune cells was explored. Furthermore, we found LncRNA DIO3OS promotes the invasion and migration of Human endometrial stromal cells (THESCs) and ALKBH5 regulates the expression of the lncRNA DIO3OS through m6A modification in vitro. Our study firstly revealed the transcriptome-wide map of m6A modification in lncRNAs of ovarian endometriosis. These findings may enable the determination of the underlying mechanism governing the pathogenesis of ovarian endometriosis and provide theoretical basis for further deeper research on the role of m6A in the development of ovarian endometriosis.

Evolutionary rewiring of the wheat transcriptional regulatory network by lineage-specific transposable elements.

More than 80% of the wheat genome consists of transposable elements (TEs), which act as major drivers of wheat genome evolution. However, their contributions to the regulatory evolution of wheat adaptations remain largely unclear. Here, we created genome-binding maps for 53 transcription factors (TFs) underlying environmental responses by leveraging DAP-seq in Triticum urartu, together with epigenomic profiles. Most TF binding sites (TFBSs) located distally from genes are embedded in TEs, whose functional relevance is supported by purifying selection and active epigenomic features. About 24% of the non-TE TFBSs share significantly high sequence similarity with TE-embedded TFBSs. These non-TE TFBSs have almost no homologous sequences in non-Triticeae species and are potentially derived from Triticeae-specific TEs. The expansion of TE-derived TFBS linked to wheat-specific gene responses, suggesting TEs are an important driving force for regulatory innovations. Altogether, TEs have been significantly and continuously shaping regulatory networks related to wheat genome evolution and adaptation.

Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3.

Great advances have been made in mass spectrometric data interpretation for intact glycopeptide analysis. However, accurate identification of intact glycopeptides and modified saccharide units at the site-specific level and with fast speed remains challenging. Here, we present a glycan-first glycopeptide search engine, pGlyco3, to comprehensively analyze intact N- and O-glycopeptides, including glycopeptides with modified saccharide units. A glycan ion-indexing algorithm developed for glycan-first search makes pGlyco3 5-40 times faster than other glycoproteomic search engines without decreasing accuracy or sensitivity. By combining electron-based dissociation spectra, pGlyco3 integrates a dynamic programming-based algorithm termed pGlycoSite for site-specific glycan localization. Our evaluation shows that the site-specific glycan localization probabilities estimated by pGlycoSite are suitable to localize site-specific glycans. With pGlyco3, we confidently identified N-glycopeptides and O-mannose glycopeptides that were extensively modified by ammonia adducts in yeast samples. The freely available pGlyco3 is an accurate and flexible tool that can be used to identify glycopeptides and modified saccharide units.

Construction of programmed time-released multifunctional hydrogel with antibacterial and anti-inflammatory properties for impaired wound healing.

The successful reprogramming of impaired wound healing presents ongoing challenges due to the impaired tissue microenvironment caused by severe bacterial infection, excessive oxidative stress, as well as the inappropriate dosage timing during different stages of the healing process. Herein, a dual-layer hydrogel with sodium alginate (SA)-loaded zinc oxide (ZnO) nanoparticles and poly(N-isopropylacrylamide) (PNIPAM)-loaded Cu5.4O ultrasmall nanozymes (named programmed time-released multifunctional hydrogel, PTMH) was designed to dynamically regulate the wound inflammatory microenvironment based on different phases of wound repairing. PTMH combated bacteria at the early phase of infection by generating reactive oxygen species through ZnO under visible-light irradiation with gradual degradation of the lower layer. Subsequently, when the upper layer was in direct contact with the wound tissue, Cu5.4O ultrasmall nanozymes were released to scavenge excessive reactive oxygen species. This neutralized a range of inflammatory factors and facilitated the transition from the inflammatory phase to the proliferative phase. Furthermore, the utilization of Cu5.4O ultrasmall nanozymes enhanced angiogenesis, thereby facilitating the delivery of oxygen and nutrients to the impaired tissue. Our experimental findings indicate that PTMHs promote the healing process of diabetic wounds with bacterial infection in mice, exhibiting notable antibacterial and anti-inflammatory properties over a specific period of time.

Synergistic dual cell therapy for atherosclerosis regression: ROS-responsive Bio-liposomes co-loaded with Geniposide and Emodin.

The development of nanomaterials for delivering natural compounds has emerged as a promising approach for atherosclerosis therapy. However, premature drug release remains a challenge. Here, we present a ROS-responsive biomimetic nanocomplex co-loaded with Geniposide (GP) and Emodin (EM) in nanoliposome particles (LP NPs) for targeted atherosclerosis therapy. The nanocomplex, hybridized with the macrophage membrane (Møm), effectively evades immune system clearance and targets atherosclerotic plaques. A modified thioketal (TK) system responds to ROS-rich plaque regions, triggering controlled drug release. In vitro, the nanocomplex inhibits endothelial cell apoptosis and macrophage lipid accumulation, restores endothelial cell function, and promotes cholesterol effluxion. In vivo, it targets ROS-rich atherosclerotic plaques, reducing plaque area ROS levels and restoring endothelial cell function, consequently promoting cholesterol outflow. Our study demonstrates that ROS-responsive biomimetic nanocomplexes co-delivering GP and EM exert a synergistic effect against endothelial cell apoptosis and lipid deposition in macrophages, offering a promising dual-cell therapy modality for atherosclerosis regression.

Influence of Cry1Ab protein on growth and development of a predatory spider, Pardosa pseudoannulata, from protective perspectives.

The expression of Cry proteins in genetically modified rice varieties safeguards the crop from lepidopteran pests. These proteins have the potential to be transferred through the food chain to arthropods like planthoppers and predatory spiders, triggering defensive responses in these unintended organisms. Hence, we hypothesized that Cry protein might influence the growth and development of spiders by altering protective enzyme activities. The results showed that Cry1Ab protein could accumulate in tissues and subcellular organelles of Pardosa pseudoannulata from Nilaparvata lugens. Cry1Ab protein exposure prolonged the developmental duration in the 5th and 7th instar spiderlings but induced no alterations of other growth indicators, such as body length, median ocular area, and survival rate. In addition, Cry1Ab protein exerted no adverse impacts on several detoxifying enzymes (i.e., superoxide dismutase, catalase, glutathione peroxidase, and acetylcholine esterase) in muscle, midgut, ganglia, and hemolymph at subcellular components (i.e., microsome and cytoplasm). To further explore the effects of Cry1Ab protein on the spiderlings, we performed an integrated transcriptome analysis on spiderlings exposed to Cry1Ab protein. The results showed that Cry1Ab protein might prolong the development duration of P. pseudoannulata via the altered cuticle metabolism (e.g., chitin metabolic process and structural constituent of cuticle). In addition, the gene expression profile associated with detoxifying enzymes and three stress-responsive pathways (JAK/STAT, JNK/SAPK, and Hippo pathways) also displayed no significant alterations under Cry1Ab exposure. Collectively, this integrated analysis generates multidimensional insights to assess the effects of Cry1Ab protein on non-target spiders and demonstrates that Cry1Ab protein exerts no toxicity in P. pseudoannulata.

Conceptual design of a generic data harmonization process for OMOP common data model.

BACKGROUND: To gain insight into the real-life care of patients in the healthcare system, data from hospital information systems and insurance systems are required. Consequently, linking clinical data with claims data is necessary. To ensure their syntactic and semantic interoperability, the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) from the Observational Health Data Sciences and Informatics (OHDSI) community was chosen. However, there is no detailed guide that would allow researchers to follow a generic process for data harmonization, i.e. the transformation of local source data into the standardized OMOP CDM format. Thus, the aim of this paper is to conceptualize a generic data harmonization process for OMOP CDM. METHODS: For this purpose, we conducted a literature review focusing on publications that address the harmonization of clinical or claims data in OMOP CDM. Subsequently, the process steps used and their chronological order as well as applied OHDSI tools were extracted for each included publication. The results were then compared to derive a generic sequence of the process steps. RESULTS: From 23 publications included, a generic data harmonization process for OMOP CDM was conceptualized, consisting of nine process steps: dataset specification, data profiling, vocabulary identification, coverage analysis of vocabularies, semantic mapping, structural mapping, extract-transform-load-process, qualitative and quantitative data quality analysis. Furthermore, we identified seven OHDSI tools which supported five of the process steps. CONCLUSIONS: The generic data harmonization process can be used as a step-by-step guide to assist other researchers in harmonizing source data in OMOP CDM.

Unveiling the potential of machine learning in schizophrenia diagnosis: A meta-analytic study of task-based neuroimaging data.

The emergence of machine learning (ML) techniques has opened up new avenues for identifying biomarkers associated with schizophrenia (SCZ) using task-related fMRI (t-fMRI) designs. To evaluate the effectiveness of this approach, we conducted a comprehensive meta-analysis of 31 t-fMRI studies using a bivariate model. Our findings revealed a high overall sensitivity of 0.83 and specificity of 0.82 for t-fMRI studies. Notably, neuropsychological domains modulated the classification performance, with selective attention demonstrating a significantly higher specificity than working memory (ß = 0.98, z = 2.11, P = 0.04). Studies involving older, chronic patients with SCZ reported higher sensitivity (P <0.015) and specificity (P <0.001) than those involving younger, first-episode patients or high-risk individuals for psychosis. Additionally, we found that the severity of negative symptoms was positively associated with the specificity of the classification model (ß = 7.19, z = 2.20, P = 0.03). Taken together, these results support the potential of using task-based fMRI data in combination with machine learning techniques to identify biomarkers related to symptom outcomes in SCZ, providing a promising avenue for improving diagnostic accuracy and treatment efficacy. Future attempts to deploy ML classification should consider the factors of algorithm choice, data quality and quantity, as well as issues related to generalization.

Assessment of urine CCL2 as a potential diagnostic biomarker for acute kidney injury and septic acute kidney injury in intensive care unit patients.

Acute kidney injury (AKI) is a prevalent and serious condition in the intensive care unit (ICU), associated with significant morbidity and mortality. Septic acute kidney injury (SAKI) contributes substantially to AKI cases in the ICU. However, current diagnostic methods have limitations, necessitating the exploration of novel biomarkers. In this study, we investigated the potential of plasma and urine CCL2 levels as diagnostic markers for AKI and SAKI in 216 ICU patients. Our findings revealed significant differences in plasma (p < 0.01) and urine CCL2 (p < 0.0001) levels between AKI and non-AKI patients in the ICU. Notably, urine CCL2 demonstrated promising predictive value for AKI, exhibiting high specificity and sensitivity (AUC = 0.8976; p < 0.0001). Furthermore, we observed higher urine CCL2 levels in SAKI compared to non-septic AKI (p < 0.001) and urine CCL2 could also differentiate SAKI from non-septic AKI (AUC = 0.7597; p < 0.0001). These results suggest that urine CCL2 levels hold promise as early biomarkers for AKI and SAKI, offering valuable insights for timely intervention and improved management of ICU patients.

BDNF is a prognostic biomarker involved in immune infiltration of lung adenocarcinoma and is associated with brain metastasis.

Non-small cell lung cancer (NSCLC) is one of the leading causes of death worldwide. Brain metastases are a common complication of a wide range of human malignancies, particularly lung adenocarcinoma (LUAD). Brain-derived neurotrophic factor (BDNF), a member of the neurotrophin family, has been linked to several human malignancies and has been shown to promote LUAD tumorigenesis. However, its function in the tumour immune microenvironment (TIME) remains largely unexplored, especially in complex brain tissue environments. In this study, BDNF was found to be particularly increased in patients with advanced tumour stage, lymphatic metastasis, and distant metastasis, indicating a correlation with LUAD progression. We characterized the prognostic value of BDNF and defined BDNF as an unfavourable prognostic indicator through a common driver gene-independent mechanism in LUAD. Furthermore, patients with increased BDNF levels in primary LUAD might have a higher risk of developing brain metastasis (BM), and central nervous system (CNS) metastasis showed an elevated expression of BDNF compared to their matched primary lesions. Additionally, we investigated the interaction between BDNF and infiltrating immune cells in both primary lesions and paired BM using multiplex immunostaining. The results showed that BDNF might drive an immunosuppressive tumour microenvironment (TME) by re-education of tumour-associated macrophages (TAMs) toward a pro-tumorigenic M2 phenotype, particularly in BM. Our findings demonstrate that BDNF serves as an independent potential prognostic marker and correlates with BM in LUAD. As it is closely related to TAM polarization, BDNF may be a promising immune-related biomarker and molecular target in patients with LUAD.

A single-cell transcriptome atlas of the adult human retina.

The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Müller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.

Disruption of Iron Homeostasis to Induce Ferroptosis with Albumin-Encapsulated Pt(IV) Nanodrug for the Treatment of Non-Small Cell Lung Cancer.

Non-small cell lung cancer (NSCLC) is the most common pathological type of lung cancer , accounting for approximately 85% of lung cancers. For more than 40 years, platinum (Pt)-based drugs are still one of the most widely used anticancer drugs even in the era of precision medicine and immunotherapy. However, the clinical limitations of Pt-based drugs, such as serious side effects and drug resistance, have not been well solved. This study constructs a new albumin-encapsulated Pt(IV) nanodrug (HSA@Pt(IV)) based on the Pt(IV) drug and nanodelivery system. The characterization of nanodrug and biological experiments demonstrate its excellent drug delivery and antitumor effects. The multi-omics analysis of the transcriptome and the ionome reveals that nanodrug can activate ferroptosis by affecting intracellular iron homeostasis in NSCLC. This study provides experimental evidence to suggest the potential of HSA@Pt(IV) as a nanodrug with clinical application.

A novel mechanism regulating pyroptosis-induced fibrosis in endometriosis via lnc-MALAT1/miR-141-3p/NLRP3 pathway†.

Endometriosis is a chronic inflammatory disease distinguished by ectopic endometrium and fibrosis. NLRP3 inflammasome and pyroptosis are present in endometriosis. Aberrant increase of Long noncoding (Lnc)-metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) plays a vital role in endometriosis. However, the relationship between lnc-MALAT1, pyroptosis, and fibrosis is not completely known. In the present study, we found that the pyroptosis levels in ectopic endometrium of patients with endometriosis were significantly increased, consistent with fibrosis levels. Lipopolysaccharide (LPS) + ATP could induce pyroptosis of primary endometrial stromal cells (ESCs), thereby releasing interleukin (IL)-1ß and stimulating transforming growth factor (TGF)-ß1-mediated fibrosis. NLRP3 inhibitor MCC950 had the same effect as TGF-ß1 inhibitor SB-431542 in suppressing the fibrosis-inducing effect of LPS + ATP in vivo and in vitro. The abnormal increase of lnc-MALAT1 in ectopic endometrium was connected with NLRP3-mediated pyroptosis and fibrosis. Leveraging bioinformatic prediction and luciferase assays combined with western blotting and quantitative reverse transcriptase-polymerase chain reaction, we validated that lnc-MALAT1 sponges miR-141-3p to promote NLRP3 expression. Silencing lnc-MALAT1 in HESCs ameliorated NLRP3-mediated pyroptosis and IL-1ß release, thereby relieving TGF-ß1-mediated fibrosis. Consequently, our findings suggest that lnc-MALAT1 is critical for NLRP3-induced pyroptosis and fibrosis in endometriosis through sponging miR-141-3p, which may indicate a new therapeutic target of endometriosis treatment.

Toxicity spectrum and risk factors for chemo-immunotherapy in locally advanced or metastatic lung cancer.

Chemo-immunotherapy has become the best first-line treatment for advanced lung cancer patients without oncogenic drivers. However, it may also lead to an increased incidence and severity of treatment-related adverse events. In this retrospective study, lung cancer patients administrated with either anti-PD-1 or anti-PD-L1 treatment plus chemotherapy were included. Data on demographic characteristics, disease characteristics, treatment strategies, laboratory results, and clinical outcomes were collected from the Electronic Medical Records System and evaluation scales. Chi-square, univariate, and multivariate logistic regression analyses were used to identify the risk factors for immune-related adverse events (irAEs). A total of 116 patients were included in the study, and the majority experienced treatment-related adverse events. Adverse events of any grade were reported in 114 (98.3%) patients, with 73 (62.9%) experiencing Grade 3 or higher events. The most frequent adverse events were anemia (67.2%), decreased appetite (62.9%), and alopecia (53.4%). Fifty-four (46.6%) patients were diagnosed with irAEs, with hypothyroidism (28.4%) being the most commonly reported. Multivariable analysis demonstrated a significant correlation between the number of treatment cycles, elevated baseline levels of thyroid stimulating hormone (TSH) and interleukin-6 (IL-6) with irAEs (OR = 1.222, P = 0.009, OR = 1.945, P = 0.016, OR = 1.176, P = 0.004), and IL-6 was identified as a strong predictor of severe irAEs (OR = 1.084, P = 0.014). Our study demonstrated the safety of chemo-immunotherapy in lung cancer patients without additional toxicity. The number of treatment cycles, higher baseline levels of TSH and IL-6 were identified as potential clinical biomarkers for irAEs.

Investigation of dynamic wind speed impacts on radiative transmittance and reflectance in the ocean-sea fog system.

Frequent fog and dynamic wind speeds in the ocean significantly impact the radiation transmittance and reflectance on the sea surface, substantially challenging remote sensing and target detection in marine environments. Establishing a model to study the radiative transfer more accurately in ocean-sea fog systems under dynamic wind speed conditions is crucial. Here, a multichannel Monte Carlo (Mc-MC) model is introduced to investigate radiative transfer in ocean-fog systems, which is more realistic and has greater potential than the traditional MC (Tra-MC) approach. Addressing the challenges of dynamic wind speed, this paper introduces two specialized dynamic wind speed models. One prioritized the accurate simulation of changing sea surface wind speeds, and we investigated the transmittance and reflectance of six regions in the Pacific and Atlantic Oceans under this model. The other is proposed for investigating the effect of dynamic wind speed on radiative transfer. The experimental results indicate that an increase in the wind speed dynamic factor accelerates the rate of wind speed changes, thereby intensifying the instability of the radiative transfer transmittance and reflectance. In addition, the light around both the 1 µm and 2 µm wavelengths exhibit high transmittance, but the light surrounding 1 µm has relatively weaker stability compared to that surrounding 2 µm. These investigations provide valuable insights for infrared remote sensing, target detection, and the development of light sources suitable for marine applications.

Stimulation of lipopolysaccharide from Pseudomonas aeruginosa following H9N2 IAV infection exacerbates inflammatory responses of alveolar macrophages and decreases virus replication.

H9N2 IAV infection contributed to P. aeruginosa coinfection, causing severe hemorrhagic pneumonia in mink. In this study, the in vitro alveolar macrophage models were developed to investigate the innate immune responses to P. aeruginosa LPS stimulation following H9N2 IAV infection, using MH-S cells. The cytokine levels, apoptosis levels and the viral nucleic acid levels were detected and analyzed. As a result, the levels of IFN-α, IL-1ß, TNF-α, and IL-10 in MH-S cells with P. aeruginosa LPS stimulation following H9N2 IAV infection were significantly higher than those in MH-S cells with single H9N2 IAV infection and single LPS stimulation (P < 0.05), exacerbating inflammatory responses. LPS stimulation aggravated the apoptosis of MH-S cells with H9N2 IAV infection. Interestingly, LPS stimulation influences H9N2 IAV replication and indirectly reduced H9N2 IAV replications in in vitro AMs. It implied that LPS should play an important role in the pathogenesis of H9N2 IAV and P. aeruginosa coinfection.

Tunable Fluorescence and Morphology of Aggregates Built from a Mechanically Bonded Amphiphilic Bistable [2]Rotaxane.

Advanced Organic Chemical Materials Co-constructed Mechanically bonded amphiphiles (MBAs), also known as mechanically interlocked molecules (MIMs), have emerged as an important kind of functional building block for the construction of artificial molecular machines and soft materials. Herein, a novel MBA, i. e., bistable [2]rotaxane H2 was designed and synthesized. In the solution state, H2 demonstrated pH and metal ion-responsive emissions due to the presence of a distance-dependent photoinduced electron transfer (PET) process and the fluorescence resonance energy transfer (FRET) process, respectively. Importantly, the amphiphilic feature of H2 has endowed it with unique self-assembly capability, and nanospheres were obtained in a mixed H2 O/CH3 CN solvent. Moreover, the morphology of H2 aggregates can be tuned from nanospheres to vesicles due to the pH-controlled shuttling motion-induced alternation of H2 amphiphilicity. Interestingly, larger spheres with novel pearl-chain-like structures from H2 were observed after adding stoichiometric Zn2+ . In particular, H2 shows pH-responsive emissions in its aggregation state, allowing the visualization of the shuttling movement by just naked eyes. It is assumed that the well-designed [2]rotaxane, and particularly the proposed concept of MBA shown here, will further enrich the families of MIMs, offering prospects for synthesizing more MIMs with novel assembly capabilities and bottom-up building dynamic smart materials with unprecedented functions.

A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI.

BACKGROUND: Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning. PURPOSE: To develop an unenhanced radiomics model with using non-gadolinium based sequences for detecting breast cancer based on T2-weighted (T2W) and diffusion-weighted (DW) MRI. STUDY TYPE: Retrospective analysis followed by retrospective and prospective cohorts study. POPULATION: 1760 patients: Of these, 1293 for model construction (n = 775 for training and 518 for validation). The remaining patients for model testing in internal retrospective (n = 167), internal prospective (n = 188), and external retrospective (n = 112) cohorts. FIELD STRENGTH/SEQUENCE: 3.0T MR scanners from two institution. T2WI, DWI, and first contrast-enhanced T1-weighted sequence. ASSESSMENT: AUCs in distinguishing breast cancer were compared between combined model with gadolinium agent sequence and unenhanced model. Subsequently, the AUCs in testing cohorts of unenhanced model was compared with two radiologists' diagnosis for this research. Finally, patient subgroup analysis in testing cohorts was performed based on clinical subgroups and different types of malignancies. STATISTICAL TESTS: Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, weighted kappa test, and DeLong's test. RESULTS: The unenhanced radiomics model performed best under Gaussian process (GP) classifiers (AUC: training, 0.893; validation, 0.848) compared to support vector machine (SVM) and logistic, showing favorable prediction in testing cohorts (AUCs, 0.818-0.840). The AUCs for the unenhanced radiomics model were not statistically different in five cohorts from those of the combined radiomics model (P, 0.317-0.816), as well as the two radiologists (P, 0.181-0.918). The unenhanced radiomics model was least successful in identifying ductal carcinoma in situ, whereas did not show statistical significance in other subgroups. DATA CONCLUSION: An unenhanced radiomics model based on T2WI and DWI has comparable diagnostic accuracy to the combined model using the gadolinium agent. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

TAK1 blockade as a therapy for retinal neovascularization.

Retinal neovascularization, or pathological angiogenesis in the retina, is a leading cause of blindness in developed countries. Transforming growth factor-ß-activated kinase 1 (TAK1) is a mitogen-activated protein kinase kinase kinase (MAPKKK) activated by TGF-ß1 and other proinflammatory cytokines. TAK1 is also a key mediator of proinflammatory signals and plays an important role in maintaining vascular integrity upon proinflammatory cytokine stimulation such as TNFα. However, its role in pathological angiogenesis, particularly in retinal neovascularization, remains unclear. Here, we investigate the regulatory role of TAK1 in human endothelial cells responding to inflammatory stimuli and in a rat model of oxygen-induced retinopathy (OIR) featured retinal neovascularization. Using TAK1 knockout human endothelial cells that subjected to inflammatory stimuli, transcriptome analysis revealed that TAK1 is required for activation of NFκB signaling and mediates its downstream gene expression related to endothelial activation and angiogenesis. Moreover, pharmacological inhibition of TAK1 by 5Z-7-oxozeaenol attenuated angiogenic activities of endothelial cells. Transcriptome analysis also revealed enrichment of TAK1-mediated NFκB signaling pathway in the retina of OIR rats and retinal neovascular membrane from patients with proliferative diabetic retinopathy. Intravitreal injection of 5Z-7-oxozeaenol significantly reduced hypoxia-induced inflammation and microglial activation, thus attenuating aberrant retinal angiogenesis in OIR rats. Our data suggest that inhibition of TAK1 may have therapeutic potential for the treatment of retinal neovascular pathologies.