Sub-bundle based analysis reveals the role of human optic radiation in visual working memory.

White matter (WM) functional activity has been reliably detected through functional magnetic resonance imaging (fMRI). Previous studies have primarily examined WM bundles as unified entities, thereby obscuring the functional heterogeneity inherent within these bundles. Here, for the first time, we investigate the function of sub-bundles of a prototypical visual WM tract-the optic radiation (OR). We use the 7T retinotopy dataset from the Human Connectome Project (HCP) to reconstruct OR and further subdivide the OR into sub-bundles based on the fiber's termination in the primary visual cortex (V1). The population receptive field (pRF) model is then applied to evaluate the retinotopic properties of these sub-bundles, and the consistency of the pRF properties of sub-bundles with those of V1 subfields is evaluated. Furthermore, we utilize the HCP working memory dataset to evaluate the activations of the foveal and peripheral OR sub-bundles, along with LGN and V1 subfields, during 0-back and 2-back tasks. We then evaluate differences in 2bk-0bk contrast between foveal and peripheral sub-bundles (or subfields), and further examine potential relationships between 2bk-0bk contrast and 2-back task d-prime. The results show that the pRF properties of OR sub-bundles exhibit standard retinotopic properties and are typically similar to the properties of V1 subfields. Notably, activations during the 2-back task consistently surpass those under the 0-back task across foveal and peripheral OR sub-bundles, as well as LGN and V1 subfields. The foveal V1 displays significantly higher 2bk-0bk contrast than peripheral V1. The 2-back task d-prime shows strong correlations with 2bk-0bk contrast for foveal and peripheral OR fibers. These findings demonstrate that the blood oxygen level-dependent (BOLD) signals of OR sub-bundles encode high-fidelity visual information, underscoring the feasibility of assessing WM functional activity at the sub-bundle level. Additionally, the study highlights the role of OR in the top-down processes of visual working memory beyond the bottom-up processes for visual information transmission. Conclusively, this study innovatively proposes a novel paradigm for analyzing WM fiber tracts at the individual sub-bundle level and expands understanding of OR function.

A novel histone deacetylase inhibitor Se-SAHA attenuates isoproterenol-induced heart failure via antioxidative stress and autophagy inhibition.

Heart failure is associated with histone deacetylase (HDAC) regulation of gene expression, the inhibition of which is thought to be beneficial for heart failure therapy. Here, we explored the cardioprotective effects and underlying mechanism of a novel selenium-containing HDAC inhibitor, Se-SAHA, on isoproterenol (ISO)-induced heart failure. We found that pretreatment with Se-SAHA attenuated ISO-induced cardiac hypertrophy and fibrosis in neonatal rat ventricular myocytes (NRVMs). Se-SAHA significantly attenuated the generation of ISO-induced reactive oxygen species (ROS) and restored the expression levels of superoxide dismutase 2 (SOD2) and heme oxygenase-1 (HO-1) in vitro. Furthermore, Se-SAHA pretreatment prevented the accumulation of autophagosomes. Se-SAHA reversed the high expression of HDAC1 and HDAC6 induced by ISO incubation. However, after the addition of the HDAC agonist, the effect of Se-SAHA on blocking autophagy was inhibited. Using ISO-induced mouse models, cardiac ventricular contractile dysfunction, hypertrophy, and fibrosis was reduced treated by Se-SAHA. In addition, Se-SAHA inhibited HDAC1 and HDAC6 overexpression in ISO-treated mice. Se-SAHA treatment significantly increased the activity of SOD2 and improved the ability to eliminate free radicals. Se-SAHA hindered the excessive levels of the microtubule-associated protein 1 light chain 3 (LC3)-II and Beclin-1 in heart failure mice. Collectively, our results indicate that Se-SAHA exerts cardio-protection against ISO-induced heart failure via antioxidative stress and autophagy inhibition.

Novel antibody-antibiotic conjugate using KRM-1657 as payload eliminates intracellular MRSA in vitro and in vivo.

Staphylococcus aureus is considered to be an extracellular pathogen. However, survival of S.aureus within host cells may cause long-term colonization and clinical failure. Current treatments have poor efficacy in clearing intracellular bacteria. Antibody-antibiotic conjugates (AACs) is a novel strategy for eliminating intracellular bacteria. Herein, we use KRM-1657 as payload of AAC for the first time, and we conjugate it with anti S. aureus antibody via a dipeptide linker (Valine-Alanine) to obtain a novel AAC (ASAK-22). The ASAK-22 exhibits good in vitro pharmacokinetic properties and inhibitory activity against intracellular MRSA, with 100 µg/mL of ASAK-22 capable of eliminating intracellular MRSA to the detection limit. Furthermore, the in vivo results demonstrate that a single administration of ASAK-22 significantly reduces the bacterial burden in the bacteremia model, which is superior to the vancomycin treatment.

Inflammatory burden index: associations between osteoarthritis and all-cause mortality among individuals with osteoarthritis.

BACKGROUND: The newly described inflammatory burden index (IBI) reflects a patient's inflammatory burden. This study aimed to estimate the association between IBI, osteoarthritis (OA), and all-cause mortality in patients with OA. METHODS: We extracted the data of adults from the National Health and Nutrition Examination Survey database between 1999 and 2018. After using appropriate survey weights to correct for sample bias, we conducted multivariate logistic regression analyses to explore the association between IBI and OA across three models: in the unadjusted model, partially adjusted model (adjusting age, sex, race, education level, marital status, PIR, BMI, smoking status, drinking status, stroke, CVD, DM, and hypertension) and fully adjusted model (which included additional variables: HBA1C, ALT, AST, BUN, TC, and HDL). And the odds ratios (OR) and 95% confidence intervals (CI) were calculated. Similarly, using comparable survey weights and covariates adjustments, we employed Cox proportional hazards regression analysis to investigate the association between IBI and all-cause mortality in the other 3 models. The Cox proportional hazards regression models were fitted to calculate the hazard ratios (HR) and 95% CI of the association between IBI and all-cause mortality. A restricted cubic spline (RCS) was used to explore the nonlinear relationships between association effects. Subgroup analysis was performed to validate the reliability of their effects. RESULTS: In total, 22,343 eligible participants were included. Multiple logistic regression models revealed that participants with the highest IBI had 2.54 times (95%CI, 2.23, 2.90)) higher risk of OA than those with the lowest IBI in Model 1, whereas the OR was 1.21 (95%CI, 1.03, 1.42) in Model 2 and 1.23 (95%CI,1.05, 1.45) in Model 3. Multiple Cox regression models showed participants with the highest IBI had 186% (95%CI, 1.50, 2.31) times risk of developing all-cause death than those with the lowest IBI in Model 1. This trend remained stable in Models 2 (HR,1.54; 95%CI,1.22, 1.95) and 3 (HR, 1.41; 95%CI, 1.10, 1.80). The RCS revealed a significant positive association between IBI and OA risk. With respect to the association between IBI and all-cause mortality, a slight decrease in mortality was observed from the lowest quartile to the second quartile of IBI, and the mortality risk increased with increasing IBI. Subgroup analyses showed that age, cardiovascular disease, and hypertension were pivotal in the association of IBI with all-cause mortality, whereas the association of IBI with OA remained stable after stratification by other factors such as sex, race, education level, marital, smoking, and drinking status, hypertension, and most serological indices. CONCLUSIONS: This study provides evidence of a positive association between IBI, OA, and all-cause mortality. IBI may be a promising signature for assessing the inflammatory burden in patients with OA, which, in turn, is conducive to precise references for high-risk population recognition, anti-inflammatory guidance, and reducing mortality intervention.

Machine Learning Models Reliably Predict Clinical Outcomes in Medial Patellofemoral Ligament Reconstruction.

PURPOSE: To develop the machine learning model to predict clinical outcomes following MPFLR and identify the important predictive indicators. METHODS: This study included patients who underwent MPFLR from January 2018 to December 2022. The exclusion criteria were as follows: 1) concurrent bony procedures, 2) history of other knee surgeries, and 3) follow-up period of less than 12 months. Forty-two predictive models were constructed for seven clinical outcomes (failure to achieve MCID of clinical scores, return to pre-injury sports, pivoting sports, and recurrent instability) using six machine learning algorithms (Random Forest, Logistic Regression, Support Vector Machine, Decision Tree, implemented multilayer perceptron, and K-nearest neighbor). The performance of the model was evaluated using metrics such as the area under the receiver operating characteristic curve (AUC), accuracy, specificity, and sensitivity. Additionally, Shapley Additive Explanation summary plot was employed to identify the important predictive factors of the best-performing model. RESULTS: A total of 218 patients met criteria. For the best-performing models in predicting failure to achieve the MCID for Lysholm, IKDC, Kujala, and Tegner scores, the AUCs and accuracies were 0.884 (good) and 87.3%, 0.859 (good) and 86.2%, 0.969 (excellent) and 97.0%, and 0.760 (fair) and 76.8%, respectively; 0.952 (excellent) and 95.2% for return to pre-injury sports; 0.756 (fair) and 75.4% for return to pivoting sports; and 0.943 (excellent) and 94.9% for recurrent instability. Low preoperative Tegner score, shorter time to surgery, and absence of severe trochlear dysplasia were significant predictors for return to pre-injury sports, while absence of severe trochlear dysplasia and patellar alta were significant predictors for return to pivoting sports. Older age, female sex, and low preoperative Lysholm score were highly predictive of recurrent instability. CONCLUSION: The predictive models developed using machine learning algorithms can reliably forecast the clinical outcomes of MPFLR, particularly demonstrating excellent performance in predicting recurrent instability. LEVEL OF EVIDENCE: Level III, case-control study.

Comparison of Different Ultrasonic Screening Methods and Analysis of High Risk Factors for Fetal Cardiac Malformation in Second Trimester of Pregnancy.

Current study aims to compare the application of two-dimensional (2D) color doppler ultrasound (CDU) and four-dimensional (4D) ultrasound spatiotemporal image correlation (STIC) in fetal congenital heart disease in the second trimester of pregnancy and to analyze the high risk factors of the disease. From August 2019 to July 2021, 135 second-trimester patients with highly suspected congenital heart malformations were selected who underwent prenatal screening at South Taihu Hospital Affiliated to Huzhou University. 2D-CDU, 4D STIC, and postnatal examination were completed in all patients. 2D-CDU, 4D STIC and 2D-CDU combined with 4D STIC were used to detect fetal cardiac malformations and classify cardiac malformations. The sensitivity, specificity, positive predictive value, negative predictive value and coincidence rate of 2D-CDU, 4D STIC and 2D-CDU combined with 4D STIC were compared. The results of 2D-CDU, 4D STIC and 2D-CDU combined with 4D STIC screening were analyzed for consistency using the results of postpartum diagnosis as the gold standard. Moreover, effects of maternal gestational factors on fetal cardiac malformations by univariate and multivariate analysis. 2D-CDU combined with 4D STIC showed significantly higher section display number than 2D-CDU or 4D STIC in the view of ductal arch, aortic arch, and aortic short-axis. A total of 45 cases of fetal congenital heart malformation were detected in 135 patients in the second trimester, 40, 38 or 42 cases were detected by 2D-CDU, 4D STIC or 2D-CDU combined with 4D STIC, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and coincidence rate of 2D-CDU combined with 4D ultrasound in congenital heart malformation screening were higher than those of 2D-CDU or 4D STIC. Kappa agreement analysis showed that the diagnostic results of 4D STIC and 2D-CDU combined with 4D ultrasound in fetuses with suspected congenital heart malformation were in excellent agreement (κ > 0.75), while 2D-CDU was in good agreement with postpartum diagnosis (κ < 0.75). Univariate and multivariate regression analysis revealed that maternal age ≥ 35, drinking during pregnancy, and history of adverse pregnancy and childbirth were all independent risk factors for fetal cardiac malformations, while folic acid supplementation was an independent protective factor for fetal cardiac malformations. 2D-CDU combined with 4D echocardiography may be superior to single 2D-CDU or 4D STIC in the screening of fetal congenital heart malformation in the second trimester. In order to reduce the incidence of fetal heart anomalies, we should strengthen the screening of pregnancy anomalies in high-risk pregnant women and control the risk factors.

Highly Conductive Imidazolate Covalent Organic Frameworks with Ether Chains as Solid Electrolytes for Lithium Metal Batteries.

Poly(ethylene oxide) (PEO)-based electrolytes are often used for Li+ conduction as they can dissociate the Li salts efficiently. However, high entanglement of the chains and lack of pathways for rapid ion diffusion limit their applications in advanced batteries. Recent developments in ionic covalent organic frameworks (iCOFs) showed that their highly ordered structures provide efficient pathways for Li+ transport, solving the limitations of traditional PEO-based electrolytes. Here, we present imidazolate COFs, PI-TMEFB-COFs, having methoxyethoxy chains, synthesized by Debus-Radziszewski multicomponent reactions and their ionized form, Li+@PI-TMEFB-COFs, showing a high Li+ conductivity of 8.81 mS cm-1 and a transference number of 0.974. The mechanism for such excellent electrochemical properties is that methoxyethoxy chains dissociate LiClO4, making free Li+, then those Li+ are transported through the imidazolate COFs' pores. The synthesized Li+@PI-TMEFB-COFs formed a stable interface with Li metal. Thus, employing Li+@PI-TMEFB-COFs as the solid electrolyte to assemble LiFePO4 batteries showed an initial discharge capacity of 119.2 mAh g-1 at 0.5 C, and 82.0 % capacity and 99.9 % Coulombic efficiency were maintained after 400 cycles. These results show that iCOFs with ether chains synthesized via multicomponent reactions can create a new chapter for making solid electrolytes for advanced rechargeable batteries.

Azobenzene-Based Linker Strategy for Selective Activation of Antibody-Drug Conjugates.

Existing antibody-drug conjugate (ADC) linkers, whether cleavable or non-cleavable, are designed to release highly toxic payloads or payload derivatives upon internalisation of the ADCs into cells. However, clinical studies have shown that only <1 % of the dosed ADCs accumulate in tumour cells. The remaining >99 % of ADCs are nonspecifically distributed in healthy tissue cells, thus inevitably leading to off-target toxicity. Herein, we describe an intelligent tumour-specific linker strategy to address these limitations. A tumour-specific linker is constructed by introducing a hypoxia-activated azobenzene group as a toxicity controller. We show that this azobenzene-based linker is non-cleavable in healthy tissues (O2 >10 %), and the corresponding payload derivative, cysteine-appended azobenzene-linker-monomethyl auristatin E (MMAE), can serve as a safe prodrug to mask the toxicity of MMAE (switched off). Upon exposure to the hypoxic tumour microenvironment (O2<1 %), this linker is cleaved to release MMAE and fully restores the high cytotoxicity of the ADC (switched on). Notably, the azobenzene linker-containing ADC exhibits satisfactory antitumour efficacy in vivo and a larger therapeutic window compared with ADCs containing traditional cleavable or non-cleavable linkers. Thus, our azobenzene-based linker sheds new light on the development of next-generation ADC linkers.

White matter BOLD signals at 7 Tesla reveal visual field maps in optic radiation and vertical occipital fasciculus.

There is growing evidence that blood-oxygen-level-dependent (BOLD) activity in the white matter (WM) can be detected by functional magnetic resonance imaging (fMRI). However, the functional relevance and significance of WM BOLD signals remain controversial. Here we investigated whether 7T BOLD fMRI can reveal fine-scale functional organizations of a WM bundle. Population receptive field (pRF) analyses of the 7T retinotopy dataset from the Human Connectome Project revealed clear contralateral retinotopic organizations of two visual WM bundles: the optic radiation (OR) and the vertical occipital fasciculus (VOF). The retinotopic maps of OR are highly consistent with post-mortem dissections and diffusion tractographies, while the VOF maps are compatible with the dorsal and ventral visual areas connected by the WM. Similar to the grey matter (GM) visual areas, both WM bundles show over-representations of the central visual field and increasing pRF size with eccentricity. Hemodynamic response functions of visual WM were slower and wider compared with those of GM areas. These findings clearly demonstrate that WM BOLD at 7 Tesla is closely coupled with neural activity related to axons, encoding highly specific information that can be used to characterize fine-scale functional organizations of a WM bundle.

Anthraquinone-Based Silicate Covalent Organic Frameworks as Solid Electrolyte Interphase for High-Performance Lithium-Metal Batteries.

Lithium (Li)-metal batteries (LMBs) possess the highest theoretical energy density among current battery designs and thus have enormous potential for use in energy storage. However, the development of LMBs has been severely hindered by safety concerns arising from dendrite growth and unstable interphases on the Li anode. Covalent organic frameworks (COFs) incorporating either redox-active or anionic moieties on their backbones have high Li-ion (Li+) conductivities and mechanical/chemical stabilities, so are promising for solid electrolyte interphases (SEIs) in LMBs. Here, we synthesized anthraquinone-based silicate COFs (AQ-Si-COFs) that contained both redox-active and anionic sites via condensation of tetrahydroxyanthraquinone with silicon dioxide. The nine Li+-mediated charge/discharge processes enabled the AQ-Si-COF to demonstrate an ionic conductivity of 9.8 mS cm-1 at room temperature and a single-ion-conductive transference number of 0.92. Computational studies also supported the nine Li+ mechanism. We used AQ-Si-COF as the solid electrolyte interphase on the Li anode. The LMB cells with a LiCoO2 cathode attained a maximum reversible capacity of 188 mAh g-1 at 0.25 C during high-voltage operation. Moreover, this LMB cell demonstrated suppressed dendrite growth and stable cyclability, with its capacity decreasing by less than 3% up to 100 cycles. These findings demonstrate the effectiveness of our redox-active and anionic COFs and their practical utility as SEI in LMB.

Combination with vorinostat enhances the antitumor activity of cisplatin in castration-resistant prostate cancer by inhibiting DNA damage repair pathway and detoxification of GSH.

BACKGROUND: Like DNA methylation, histone modifications are considered important processes for epigenetic alterations in gene function, and abnormally high expression of histone deacetylases (HDACs) plays a key role in many human diseases. In addition to regulating the acetylation levels of histone and non-histone proteins and gene transcription, HDAC inhibitors as antitumor drugs can also affect the DNA damage repair (DDR) pathway in tumor cells. Prostate cancer (PCa) is one of the most heritable malignancies in which DDR pathway defects can be detected in a considerable proportion of cases. Such defects are more prevalent in castration-resistant prostate cancer (CRPC) and are highly enriched in metastatic lesions. There is currently evidence that DDR pathway-deficient PCa is associated with high-risk biological behaviors and response sensitivity to platinum-based chemotherapy. Platinum-based drugs have been used in multiple clinical trials as monotherapy or in combination with other chemotherapeutic agents for the treatment of CRPC. METHODS: This study evaluated the combined anticancer effect of (cisplatin) CDDP and the HDAC inhibitors vorinostat (SAHA) on three androgen-dependent cell lines PC-3, DU-145, and C4-2B in vitro. The efficacy and safety of SAHA combined with CDDP in the treatment of CRPC were further verified through animal experiments. RESULTS: The combination of the two drugs increases cytotoxic effects by increasing DNA damage. Our results showed that the SAHA could not only reduce the expression of homologous recombinant repair proteins BRCA2, BRCA1, PARP1, and RAD51, but also decrease enzymes that Reduce the key enzymes of GSH biosynthesis, GSS and GCLC, and GSTP1 which can catalyze the binding of GSH to cisplatin. The intracellular GSH level also decreased with the increase of SAHA concentration, at the same time, the content of intracellular Pt element. CONCLUSION: The combination of CDDP and SAHA can produce synergistic anticancer effects in androgen-independent PCa cells in vitro and in vivo. Our results open up a new avenue for the effective treatment of CRPC. To optimize the chemotherapy regimen for patients with advanced PCa, it is necessary to further study the molecular mechanism of platinum drugs, HDAC inhibitors, and their combined action.

Activation of endoplasmic reticulum stress by harmine suppresses the growth of esophageal squamous cell carcinoma.

The worldwide overall 5-year survival rate of esophageal squamous cell carcinoma (ESCC) patients is less than 20%, and novel therapeutic strategies for these patients are urgently needed. Harmine is a natural ß-carboline alkaloid, which received great interest in cancer research because of its biological and anti-tumor activities. The aim of this study is to examine the effects of harmine on ESCC and its mechanism. We investigated the effects of harmine on proliferation, cell cycle, apoptosis, and tumor growth in vivo. RNA sequencing (RNA-seq), real-time PCR, and western blotting were used to detect the mechanism. Harmine inhibited ESCC cell growth in vitro and tumor growth in vivo. Differentially expressed genes in harmine-treated ESCC cells were mainly involved in protein processing in the endoplasmic reticulum (ER). Real-time PCR and western blotting confirmed harmine-induced cellular ER stress. CRISPR-Cas9 knockout of C/EBP homologous protein (CHOP) abolished harmine-induced expression of death receptor 5 and apoptosis. Harmine also induced the expression of CHOP-mediated sestrin-2, which in turn contributes to autophagosome formation via suppressing the AMP-activated protein kinase-protein kinase B-mammalian target of rapamycin signaling pathway. In conclusion, our results demonstrate that harmine inhibits the growth of ESCC through its regulation of ER stress, suggesting that it is a promising candidate for ESCC treatment.

In vivo and in vitro evaluation of pulmonary administration of itraconazole nanostructured lipid carriers for pulmonary aspergillosis.

OBJECTIVE: Pulmonary aspergillosis, which is a secondary complication of fungal pneumonia, is widely considered to have an increasing incidence and high mortality. Itraconazole (Itz) can inhibit ergosterol biosynthesis to treat pulmonary aspergillosis. Nevereless, Itz's clinical application is limited because of its poor water solubility, low oral bioavailability, and systemic hepatotoxicity. In this study, Itz-loaded nanostructured lipid carriers (Itz-NLCs) were developed to improve the in vitro permeability and bioavailability of Itz via pulmonary administration. METHODS: Itz-NLCs were prepared by the emulsification-evaporation method using oleic acid and glycerol monostearate as liquid and solid lipids, respectively. RESULTS: The Itz-NLCs were optimized with tiny particle size, uniform distribution, and excellent entrapment efficiency (EE, 97.57% ± 0.45%). A Xenopus alveolar membrane was used in the permeation study, and the cumulative permeation percentage of Itz was 10% for Itz-NLCs at 8 h, which was 2.50-fold higher than that for Itz suspensions (4%, p < .001). A rabbit pharmacokinetic investigation revealed that Itz-NLCs have an 83.05% absolute bioavailability after intratracheal instillation. CONCLUSIONS: The purpose of Itz-NLCs is to enhance the bioavailability and permeability of Itz in vitro for administration via the lungs.

4-1BB-Based CAR T Cells Effectively Reverse Exhaustion and Enhance the Anti-Tumor Immune Response through Autocrine PD-L1 scFv Antibody.

Exhaustion of chimeric antigen receptor (CAR) T cells is one of the limitations for CAR T efficacy in solid tumors and for tumor recurrence after initial CAR T treatment. Tumor treatment with a combination of programmed cell death receptor-1 (PD-1)/programmed cell death ligand-1 (PD-L1) blockage and CD28-based CAR T cells has been intensively studied. However, it remains largely unclear whether autocrine single-chain variable fragments (scFv) PD-L1 antibody can improve 4-1BB-based CAR T cell anti-tumor activity and revert CAR T cell exhaustion. Here, we studied T cells engineered with autocrine PD-L1 scFv and 4-1BB-containing CAR. The antitumor activity and exhaustion of CAR T cells were investigated in vitro and in a xenograft cancer model using NCG mice. CAR T cells with autocrine PD-L1 scFv antibody demonstrate enhanced anti-tumor activity in solid tumors and hematologic malignancies by blocking the PD-1/PD-L1 signaling. Importantly, we found that CAR T exhaustion was largely diminished by autocrine PD-L1 scFv antibody in vivo. As such, 4-1BB CAR T with autocrine PD-L1 scFv antibody combined the power of CAR T cells and the immune checkpoint inhibitor, thereby increasing the anti-tumor immune function and CAR T persistence, providing a cell therapy solution for a better clinical outcome.

Investigation of image-derived input functions for non-invasive quantification of myelin density using [11C]MeDAS PET.

Multiple sclerosis (MS) is an inflammatory demyelinating disease. Current treatments are focussed on immune suppression to modulate pathogenic activity that causes myelin damage. New treatment strategies are needed to prevent demyelination and promote remyelination. Development of such myelin repair therapies require a sensitive and specific biomarker for efficacy evaluation. Recently, it has been shown that quantification of myelin density is possible using [11C]MeDAS PET. This method, however, requires arterial blood sampling to generate an arterial input function (AIF). As the invasive nature of arterial sampling will reduce clinical applicability, the purpose of this study was to assess whether an image-derived input function (IDIF) can be used as an alternative way to facilitate its routine clinical use. Six healthy controls and 11 MS patients underwent MRI and [11C]MeDAS PET with arterial blood sampling. The application of both population-based whole blood-to-plasma conversion and metabolite corrections were assessed for the AIF. Next, summed images of the early time frames (0-70 s) and the frame with the highest blood-brain contrast were used to generate IDIFs. IDIFs were created using either the hottest 2, 4, 6 or 12 voxels, or an isocontour of the hottest 10% voxels of the carotid artery. This was followed by blood-to-plasma conversion and metabolite correction of the IDIF. The application of a population-based metabolite correction of the AIF resulted in high correlations of tracer binding (Ki) within subjects, but variable bias across subjects. All IDIFs had a sharper and higher peak in the blood curves than the AIF, most likely due to dispersion during blood sampling. All IDIF methods resulted in similar high correlations within subjects (r = 0.95-0.98), but highly variable bias across subjects (mean slope=0.90-1.09). Therefore, both the use of population based blood-plasma and metabolite corrections and the generation of the image-derived whole-blood curve resulted in substantial bias in [11C]MeDAS PET quantification, due to high inter-subject variability. Consequently, when unbiased quantification of [11C]MeDAS PET data is required, individual AIF needs to be used.

Attention module improves both performance and interpretability of four-dimensional functional magnetic resonance imaging decoding neural network.

Decoding brain cognitive states from neuroimaging signals is an important topic in neuroscience. In recent years, deep neural networks (DNNs) have been recruited for multiple brain state decoding and achieved good performance. However, the open question of how to interpret the DNN black box remains unanswered. Capitalizing on advances in machine learning, we integrated attention modules into brain decoders to facilitate an in-depth interpretation of DNN channels. A four-dimensional (4D) convolution operation was also included to extract temporo-spatial interaction within the fMRI signal. The experiments showed that the proposed model obtains a very high accuracy (97.4%) and outperforms previous researches on the seven different task benchmarks from the Human Connectome Project (HCP) dataset. The visualization analysis further illustrated the hierarchical emergence of task-specific masks with depth. Finally, the model was retrained to regress individual traits within the HCP and to classify viewing images from the BOLD5000 dataset, respectively. Transfer learning also achieves good performance. Further visualization analysis shows that, after transfer learning, low-level attention masks remained similar to the source domain, whereas high-level attention masks changed adaptively. In conclusion, the proposed 4D model with attention module performed well and facilitated interpretation of DNNs, which is helpful for subsequent research.

Quantitative assessment of myelin density using [11C]MeDAS PET in patients with multiple sclerosis: a first-in-human study.

PURPOSE: Multiple sclerosis (MS) is a disease characterized by inflammatory demyelinated lesions. New treatment strategies are being developed to stimulate myelin repair. Quantitative myelin imaging could facilitate these developments. This first-in-man study aimed to evaluate [11C]MeDAS as a PET tracer for myelin imaging in humans. METHODS: Six healthy controls and 11 MS patients underwent MRI and dynamic [11C]MeDAS PET scanning with arterial sampling. Lesion detection and classification were performed on MRI. [11C]MeDAS time-activity curves of brain regions and MS lesions were fitted with various compartment models for the identification of the best model to describe [11C]MeDAS kinetics. Several simplified methods were compared to the optimal compartment model. RESULTS: Visual analysis of the fits of [11C]MeDAS time-activity curves showed no preference for irreversible (2T3k) or reversible (2T4k) two-tissue compartment model. Both volume of distribution and binding potential estimates showed a high degree of variability. As this was not the case for 2T3k-derived net influx rate (Ki), the 2T3k model was selected as the model of choice. Simplified methods, such as SUV and MLAIR2 correlated well with 2T3k-derived Ki, but SUV showed subject-dependent bias when compared to 2T3k. Both the 2T3k model and the simplified methods were able to differentiate not only between gray and white matter, but also between lesions with different myelin densities. CONCLUSION: [11C]MeDAS PET can be used for quantification of myelin density in MS patients and is able to distinguish differences in myelin density within MS lesions. The 2T3k model is the optimal compartment model and MLAIR2 is the best simplified method for quantification. TRIAL REGISTRATION: NL7262. Registered 18 September 2018.

PEGylated Poly-HDACi: A Designer Polyprodrug from Optimized Drug Units.

We designed, synthesized, and characterized a tri-block copolymer. Its hydrophobic part, a chain of histone deacetylase inhibitor (HDACi) prodrug, was symmetrically flanked by two identical PEG blocks, whereas the built-in HDACi was a linear molecule, terminated with a thiol at one end, and a hydroxyl group at the other. Such a feature facilitated end-to-end linkage of prodrugs through alternatively aligned disulfides and carbonates. The disulfides served dual roles: redox sensors of smart nanomedicine, and warheads of masked HDACi drugs. This approach, carefully designed to benefit both control-release and efficacy, is conceptually novel for optimizing drug units in nanomedicine. Micelles from this designer polyprodrug released only PEG, CO2 and HDACi, and synergized with DOX against HCT116 cells, demonstrating its widespread potential in combination therapy. Our work highlights, for the first time, the unique advantage of thiol-based drug molecules in nanomedicine design.

Frustration and folding of a TIM barrel protein.

Triosephosphate isomerase (TIM) barrel proteins have not only a conserved architecture that supports a myriad of enzymatic functions, but also a conserved folding mechanism that involves on- and off-pathway intermediates. Although experiments have proven to be invaluable in defining the folding free-energy surface, they provide only a limited understanding of the structures of the partially folded states that appear during folding. Coarse-grained simulations employing native centric models are capable of sampling the entire energy landscape of TIM barrels and offer the possibility of a molecular-level understanding of the readout from sequence to structure. We have combined sequence-sensitive native centric simulations with small-angle X-ray scattering and time-resolved Förster resonance energy transfer to monitor the formation of structure in an intermediate in the Sulfolobus solfataricus indole-3-glycerol phosphate synthase TIM barrel that appears within 50 µs and must at least partially unfold to achieve productive folding. Simulations reveal the presence of a major and 2 minor folding channels not detected in experiments. Frustration in folding, i.e., backtracking in native contacts, is observed in the major channel at the initial stage of folding, as well as late in folding in a minor channel before the appearance of the native conformation. Similarities in global and pairwise dimensions of the early intermediate, the formation of structure in the central region that spreads progressively toward each terminus, and a similar rate-limiting step in the closing of the ß-barrel underscore the value of combining simulation and experiment to unravel complex folding mechanisms at the molecular level.

Inhibition of Netosis with PAD Inhibitor Attenuates Endotoxin Shock Induced Systemic Inflammation.

Neutrophils play a pivotal role in innate immunity by releasing neutrophils extracellular traps (NETs). Excessive NETs are detrimental to the local tissue and further exacerbate inflammation. Protein arginine deiminases (PAD) mediate histone citrullination and NET formation that, in turn, exacerbate endotoxin shock damages. In this study, we further investigated the molecular mechanism underlying PAD and NETs in endotoxic stress in mice. The control group mice were injected with solvent, the LPS endotoxic shock group mice were intraperitoneally injected with LPS at 35 mg/kg only, while the LPS and PAD inhibitor YW3-56 treatment group mice were injected with YW3-56 at 10 mg/kg prior to the LPS injection. YW3-56 significantly prolonged the survival time of the LPS-treated mice. NETs, cfDNA, and inflammatory factors were detected by ELISA in serum, paitoneal cavity, and lung at 24 h after LPS administration. Lung injuries were detected by immunostaining, and lung tissue transcriptomes were analyzed by RNA-seq at 24 h after LPS administration. We found that YW3-56 altered neutrophil tissue homeostasis, inhibited NET formation, and significantly decreased cytokines (IL-6, TNFα and IL-1ß) levels, cytokines gene expression, and lung tissue injury. In summary, NET formation inhibition offers a new avenue to manage inflammatory damages under endotoxic stress.