Search

Due to the development of next-generation sequencing technology and an increased appreciation of their role in modulating host immunity and their potential as therapeutic agents, the human microbiome has emerged as a key area of interest in various biological investigations of human health and disease. However, microbiome data present a number of statistical challenges not addressed by existing methods, such as the varying sequencing depth, the compositionality, and zero inflation. Solutions like scaling and transformation methods help to mitigate heterogeneity and release constraints, but often introduce biases and yield inconsistent results on the same data. To address these issues, we conduct a systematic review of compositional data transformation, with a particular focus on the connection and distinction of existing techniques. Additionally, we create a new framework that enables the development of new transformations by combining proportion conversion with contrast transformations. This framework includes well-known methods such as Additive Log Ratio (ALR) and Centered Log Ratio (CLR) as special cases. Using this framework, we develop two novel transformations—Centered Arcsine Contrast (CAC) and Additive Arcsine Contrast (AAC)—which show enhanced performance in scenarios with high zero-inflation. Moreover, our findings suggest that ALR and CLR transformations are more effective when zero values are less prevalent. This comprehensive review and the innovative framework provide microbiome researchers with a significant direction to enhance data transformation procedures and improve analytical outcomes.

Rechargeable magnesium-ion (Mg-ion) batteries have attracted wide attention for energy storage. However, magnesium anode is still limited by the irreversible Mg plating/stripping procedure. Herein, a well-designed binary Bi2O3-Bi2S3 (BO-BS) heterostructure is fulfilled by virtue of the cooperative interface and energy band engineering targeted fast Mg-ion storage. The built-in electronic field resulting from the asymmetrical electron distribution at the interface of electron-rich S center at Bi2S3 side and electron-poor O center at Bi2O3 side effectively accelerates the electrochemical reaction kinetics in the Mg-ion battery system. Moreover, the as-designed heterogenous interface also benefits to maintaining the electrode integrity. With these advantages, the BO-BS electrode displays a remarkable capacity of 150.36 mAh g−1 at 0.67 A g–1 and a superior cycling stability. This investigation would offer novel insights into the rational design of functional heterogenous electrode materials targeted the fast reaction kinetics for energy storage systems.

Purpose: Idiopathic granulomatous mastitis (IGM) poses diagnostic challenges due to its diverse clinical and radiological presentations, often mimicking malignancies. This study aimed to assess the diagnostic efficacy of multimodal ultrasound for mass and non-mass enhancements in Dynamic Contrast-Enhanced MRI (DCE-MRI) of IGM and breast cancer. Methods: A retrospective analysis involved patients confirmed histopathologically with IGM and BC. All patients underwent conventional ultrasound (C-US), ultrasound elastography (UE), contrast-enhanced ultrasound (CEUS), and DCE-MRI examinations. Blinded experienced radiologists assessed imaging findings. Diagnostic accuracy, sensitivity, and specificity were calculated for mass and non-mass enhancements. Results: For mass enhancements (ME), multimodal ultrasound demonstrated strong efficacy (AUC = 0.8651, 95 % CI: 0.7431 to 0.9871), exhibiting high sensitivity (83.3 %) and specificity (92.4 %) in differentiating IGM from breast cancer. However, for non-mass enhancements (NME), multimodal ultrasound showed limited accuracy (AUC = 0.6306) with lower sensitivity (65.6 %) and specificity (81.2 %) in distinguishing between IGM and breast cancer. Conclusion: Multimodal ultrasound displayed good diagnostic efficacy for mass enhancements in DCE-MRI for IGM and breast cancer, while for non-mass enhancement patterns, DCE-MRI remains the most valuable radiological modality for comprehensively assessing this condition's complexities.

Abstract Background Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. Methods This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. Results The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. Conclusions Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival.

Abstract This research delves into the nuances, origins, and societal effects of irrational religious orientations within China’s Generation Z, employing grounded theory methodology for a comprehensive analysis. The focus is on those born between 1995 and 2010, a demographic raised amidst rapid information technology growth and significantly influenced by digitalization and globalization. The study identifies three primary dimensions of irrational religious orientations in Generation Z: religious spiritual dependence, religious instrumental tendency, and religious uniqueness identity. These are shaped by factors such as the overwhelming influx of information via digital media, societal pressures and psychological dilemmas, conflicts in values and identity crises, as well as feelings of social isolation and the need for group belonging. To address these trends, the study suggests several interventions: enhancing multicultural and values education, implementing stricter online information regulation and literacy programs, boosting mental health awareness and support, and fostering engagement in social and cultural activities. These recommendations are essential for comprehensively understanding and effectively responding to the irrational religious orientations of Generation Z, ultimately contributing to their overall well-being and healthy development.

AIMMild cognitive impairment (MCI) includes two distinct subtypes, namely progressive MCI (pMCI) and stable MCI (sMCI). The objective of this study was to identify the topological reorganization of brain functional networks in patients with pMCI and sMCI.MethodsResting-state functional magnetic resonance imaging (rs-fMRI) was applied to patients with pMCI, sMCI and healthy controls. Graph theory was applied to study the topological characteristics of the brain’s functional networks, examining global and nodal metrics, modularity, and rich-club organization. Analysis of covariance and two sample t-tests were applied to assess differences in topological attributes between patient groups, alongside correlation analysis, which examined the value of changing topological attributes in predicting various clinical outcomes.ResultsSignificant differences between each group with regard to network metrics were observed. These included clustering coefficients and small-worldness. At the nodal level, several nodes with an abnormal degree centrality and nodal efficiency were detected. In rich club, pMCI and sMCI patients showed declined connectivity compared with HC. Significant differences were observed in the intra- and inter-module connections among the three groups. Particularly noteworthy was the irreplaceable role of the cerebellar module in network interactions.ConclusionOur study revealed significant differences in network topological properties among sMCI, pMCI and HC patients, which were significantly correlated with cognitive function. Most notably, the cerebellar module played a crucial role in the overall network interactions. In conclusion, these findings could aid in the development of imaging markers used to expedite diagnosis and intervention prior to Alzheimer’s disease onset.

Dissolved organic carbon refers to soluble carbon substances in water bodies and can be used as an important indicator for water pollution. Spectroscopic detection is commonly used to detect dissolved organic carbon in seawater. However, independent spectral methods are susceptible to interference, and insufficient extraction of the data features can occur. Accordingly, this study introduces a multisource spectral fusion method that relies on a combination of principal component analysis and convolutional neural networks to construct the detection model. The Bayesian correction method is used for calibration, and the dissolved organic carbon content of 10 groups of unfiltered seawater samples is analyzed. Correcting the spectral data acquired from samples containing impurities significantly improved the linear correlation coefficient R2 of dissolved organic carbon from 0.8891 to 0.9838. Similarly, the mean absolute error was significantly reduced from 15.33% to 3.24%, while the individual absolute error was effectively controlled, remaining within 9%. The obtained results show that the developed method effectively integrates the ultraviolet absorption and fluorescence spectral data and overcomes interference from other substances using the Bayesian correction method. Overall, this provides a highly accurate detection system with potential applications in monitoring the marine environment.

Background Mastectomy (MT) and breast conservation surgery (BCS) are two common surgical options for the treatment of locally advanced breast cancer (LABC). Neoadjuvant chemotherapy (NACT) is frequently administered before surgery to shrink tumors and improve surgical outcomes. However, there is a lack of consensus on the optimal surgical approach after NACT and its impact on survival outcomes. Objective This meta-analysis aims to compare the survival outcomes between MT and BCS in patients treated with NACT. Method A PRISMA selection was used to identify studies across electronic database such as PubMed, and Cochrane Library from inception until 11 th July, 2023. A total of 10 comparative studies involving a total of 5018 patients were included. Among them, 2898 patients underwent MT while 2120 underwent BCS after receiving NACT. The outcomes assessed were the 5-year overall survival (OS) and 5-year disease-free survival (DFS). The data from the included studies were pooled, and odds ratios (OR) with 95% confidence intervals (CI) were calculated to evaluate the differences between MT and BCS in terms of survival outcomes. Prospero: CRD42024496831. Result The meta-analysis revealed that patients who underwent MT after NACT had a higher 5-year OS compared to those who underwent BCS (OR 2.68, 95% CI [2.19-3.28; p

Abstract The flavonoid xanthohumol is an important flavor substance in the brewing industry that has a wide variety of bioactivities. However, its unstable structure results in its low content in beer. Microbial biosynthesis is considered a sustainable and economically viable alternative. Here, we harness the yeast Saccharomyces cerevisiae for the de novo biosynthesis of xanthohumol from glucose by balancing the three parallel biosynthetic pathways, prenyltransferase engineering, enhancing precursor supply, constructing enzyme fusion, and peroxisomal engineering. These strategies improve the production of the key xanthohumol precursor demethylxanthohumol (DMX) by 83-fold and achieve the de novo biosynthesis of xanthohumol in yeast. We also reveal that prenylation is the key limiting step in DMX biosynthesis and develop tailored metabolic regulation strategies to enhance the DMAPP availability and prenylation efficiency. Our work provides feasible approaches for systematically engineering yeast cell factories for the de novo biosynthesis of complex natural products.

Abstract Pancreatic cancer is highly lethal, of which 90% is pancreatic ductal adenocarcinoma (PDAC), with a 5-year survival rate of less than 12%, lacking effective treatment options and late diagnosis. Furthermore, the tumors show an intense resistance to cytotoxic chemotherapies. As autophagy is elevated in PDAC, targeting the autophagic pathway is regarded as a promising strategy for cancer treatment. Immunofluorescence and transmission electron microscopy were utilized to assess the autophagic flux. Label-free quantitative phosphoproteomics was used to figure out critically altered tyrosine phosphorylation of the proteins. Tumor-bearing mice were used to validate that SH2 TrM-(Arg)9 restrained the growth of tumor cells. SH2 TrM-(Arg)9 inhibited collagen-induced autophagy via blocking the DDR1/PYK2/ERK signaling cascades. SH2 TrM-(Arg)9 improved the sensitivity of PANC-1/GEM cells to gemcitabine (GEM). Inhibition of autophagy by SH2 TrM-(Arg)9 may synergized with chemotherapy and robusted tumor suppression in pancreatic cancer xenografts. SH2 TrM-(Arg)9 could enter into PDAC cells and blockade autophagy through inhibiting DDR1/PYK2/ERK signaling and may be a new treatment strategy for targeted therapy of PDAC.

Structured illumination microscopy (SIM) is a popular and powerful super-resolution (SR) technique in biomedical research. However, the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio (SNR) of raw images. To obtain high-quality SR images, several raw images need to be captured under high fluorescence level, which further restricts SIM’s temporal resolution and its applications. Deep learning (DL) is a data-driven technology that has been used to expand the limits of optical microscopy. In this study, we propose a deep neural network based on multi-level wavelet and attention mechanism (MWAM) for SIM. Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image, resulting in superior SR images compared to those generated using wide-field images as input data. We also demonstrate that the number of SIM raw images can be reduced to three, with one image in each illumination orientation, to achieve the optimal tradeoff between temporal and spatial resolution. Furthermore, our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms. We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

Abstract Background Cerebral small vessel disease (CSVD) is considered an age‐related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD‐M) or without (CSVD‐W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration. Methods Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization‐prepared rapid gradient‐echo (MPRAGE) sequence to obtain structural T1‐weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting‐state functional MRI (rs‐fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two‐sample t‐test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p

Abstract Background The failure of novel therapies effective in preclinical animal models largely reflects the fact that current models do not really mimic the pathological/therapeutic features of glioblastoma (GBM), in which the most effective temozolomide chemoradiotherapy (RT/TMZ) regimen can only slightly extend survival. How to improve RT/TMZ efficacy remains a major challenge in clinic. Methods Syngeneic G422TN-GBM model mice were subject to RT/TMZ, surgery, piperlongumine (PL), αPD1, glutathione. Metabolomics or transcriptomics data from G422TN-GBM and human GBM were used for gene enrichment analysis and estimation of ROS generation/scavenging balance, oxidative stress damage, inflammation and immune cell infiltration. Overall survival, bioluminescent imaging, immunohistochemistry, and immunofluorescence staining were used to examine therapeutic efficacy and mechanisms of action. Results Here we identified that glutathione metabolism was most significantly altered in metabolomics analysis upon RT/TMZ therapies in a truly refractory and reliable mouse triple-negative GBM (G422TN) preclinical model. Consistently, ROS generators/scavengers were highly dysregulated in both G422TN-tumor and human GBM. The ROS-inducer PL synergized surgery/TMZ, surgery/RT/TMZ or RT/TMZ to achieve long-term survival (LTS) in G422TN-mice, but only one LTS-mouse from RT/TMZ/PL therapy passed the rechallenging phase (immune cure). Furthermore, the immunotherapy of RT/TMZ/PL plus anti-PD-1 antibody (αPD1) doubled LTS (50%) and immune-cured (25%) mice. Glutathione completely abolished PL-synergistic effects. Mechanistically, ROS reduction was associated with RT/TMZ-resistance. PL restored ROS level (mainly via reversing Duox2/Gpx2), activated oxidative stress/inflammation/immune responses signature genes, reduced cancer cell proliferation/invasion, increased apoptosis and CD3+/CD4+/CD8+ T-lymphocytes in G422TN-tumor on the basis of RT/TMZ regimen. Conclusion Our findings demonstrate that PL reverses RT/TMZ-reduced ROS and synergistically resets tumor microenvironment to cure GBM. RT/TMZ/PL or RT/TMZ/PL/αPD1 exacts effective immune cure in refractory GBM, deserving a priority for clinical trials.

Abstract Speech emotion recognition (SER) is a hot topic in speech signal processing. When the training data and the test data come from different corpus, their feature distributions are different, which leads to the degradation of the recognition performance. Therefore, in order to solve this problem, a cross-corpus speech emotion recognition method is proposed based on subspace learning and domain adaptation in this paper. Specifically, training set data and the test set data are used to form the source domain and target domain, respectively. Then, the Hessian matrix is introduced to obtain the subspace for the extracted features in both source and target domains. In addition, an information entropy-based domain adaption method is introduced to construct the common space. In the common space, the difference between the feature distributions in the source domain and target domain is reduced as much as possible. To evaluate the performance of the proposed method, extensive experiments are conducted on cross-corpus speech emotion recognition. Experimental results show that the proposed method achieves better performance compared with some existing subspace learning and domain adaptation methods.

With the improvement in the level of science and technology and the improvement of people’s living standards, the functions of traditional manual wheelchairs have been unable to meet people’s living needs. Therefore, traditional wheelchairs have been gradually replaced by smart wheelchairs. Compared with traditional wheelchairs, smart wheelchairs have the characteristics of light operation and faster speed. However, when driving on some complex road surfaces, the vibration generated by the bumps of the motorcycle will cause damage to the human body, so wheelchairs with good electric power and stability can better meet the needs of people and make up for their travel needs. Based on the traditional vehicle stability analysis method, the mathematical theory of roll stability and pitch stability of the wheelchair–human system was established. We built a multi-body dynamics model with human skeleton and joint stiffness based on the multi-body dynamics method. The functioning of the wheelchair–human system was simulated and analyzed on the ditch, step, and combined road. The acceleration and Euler angle changes of the human head, chest, and wheelchair truss position were obtained, and the data results were analyzed to evaluate the stability and comfort of the system. Finally, a wheelchair test platform was built, and the road driving test was carried out according to the simulation conditions to obtain the system acceleration and angle data during the driving process. The simulation analysis was compared to verify the accuracy of the multi-body dynamics method, and the stability and comfort of the system were evaluated.

Nickle-copper ferrite (Ni0.5Cu0.5Fe2O4) supported on activated carbon (AC) (AC@Ni0.5Cu0.5Fe2O4) was synthesized and used as adsorbent, photocatalyst, and activator of peroxydisulfate (PDS) to realize the removal of ciprofloxacin (CIP). AC@Ni0.5Cu0.5Fe2O4 properties were characterized by scanning electron microscope equipped with energy-dispersive X-ray (SEM-EDX), X-ray diffraction (XRD), N2 adsorption-desorption isotherm plot of Brunauer-Emmett-Teller (BET) and Barrett-Joyner-Halenda (BJH), vibrating sample magnetometer (VSM). A rapid removal rate (94.30%) of CIP was achieved on AC@Ni0.5Cu0.5Fe2O4/PDS/UV system with the condition of catalyst dosage 0.30 g/L, initial pH 7.3, PDS addition 0.20 mM, CIP concentration 10 mg/L (200 mL), UV 28 W, in 30 min. Free radical quenching experiments indicate that reactive species of superoxide (·O2−), holes (h+), sulfate radicals (SO4−·) and hydroxyl radicals (·OH) were produced and all worked. The reusability test demonstrated that AC@Ni0.5Cu0.5Fe2O4 could be recycled five times with minimal performance reduction for the removal of CIP. The XRD and SEM of the after used AC@Ni0.5Cu0.5Fe2O4 did not change significantly, which further showed its stability and recyclability. This work might provide new insight into the application of AC@Ni0.5Cu0.5Fe2O4 in photocatalysis coupled with adsorption in peroxydisulfate assisted system and has high potential in CIP removal. HIGHLIGHTS AC@Ni0.5Cu0.5Fe2O4 was synthesized by a simple co-precipitation method.; AC@Ni0.5Cu0.5Fe2O4 has a large specific surface area and thus can provide more reaction sites.; AC@Ni0.5Cu0.5Fe2O4 can be used as adsorbent, photocatalyst, and activator of peroxydisulfate.; AC@Ni0.5Cu0.5Fe2O4 displayed an excellent recyclability.;

In this article, we present a rare case of breast metastasis of lung cancer. Chest computed tomography (CT) for a woman in her early 50s indicated right lung malignancy, multiple bone metastases, and an irregular mass in her right breast. Further inquiry into the case history revealed that the patient had been aware of the breast mass for 3 years, without respiratory symptoms. Biopsy of the breast mass suggested estrogen receptor (ER) (+), progesterone receptor (PR) (−), and human epidermal growth factor receptor 2 (HER2) (+ +) breast cancer. The patient was initially diagnosed with breast cancer with lung and bone metastasis. However, comprehensive breast cancer treatment was ineffective, and thyroid transcription factor-1 (TTF-1), napsin A, and cytokeratin 7 (CK7) were evaluated to better understand the origin of the cancer. To the best of our knowledge, this patient had the longest reported disease course from presentation with a breast lump as the first symptom to the final diagnosis of breast metastasis of lung cancer. To provide a better reference for differential diagnosis of ambiguous tumors, we also performed a systematic literature review.

Abstract Recent progress in RNA sequencing (RNA-seq) allows us to explore whole-genome gene expression profiles and to develop predictive model for disease risk. The objective of this study was to develop and validate an RNA-seq-based transcriptomic risk score (RSRS) for disease risk prediction that can simultaneously accommodate demographic information. We analyzed RNA-seq gene expression data from 441 asthmatic and 254 non-asthmatic samples. Logistic least absolute shrinkage and selection operator (Lasso) regression analysis in the training set identified 73 differentially expressed genes (DEG) to form a weighted RSRS that discriminated asthmatics from healthy subjects with area under the curve (AUC) of 0.80 in the testing set after adjustment for age and gender. The 73-gene RSRS was validated in three independent RNA-seq datasets and achieved AUCs of 0.70, 0.77 and 0.60, respectively. To explore their biological and molecular functions in asthma phenotype, we examined the 73 genes by enrichment pathway analysis and found that these genes were significantly (p

ABSTRACT The three-dimensional (3D) genome structure of human malaria parasite Plasmodium falciparum is highly organized and plays important roles in regulating coordinated expression patterns of specific genes such as virulence genes which are involved in antigenic variation and immune escape. However, the molecular mechanisms that control 3D genome of the parasite remain elusive. Here, by analyzing genome organization of P. falciparum, we identify high-interacting regions (HIRs) with strong chromatin interactions at telomeres and virulence genes loci. Specifically, HIRs are highly enriched with repressive histone marks (H3K36me3 and H3K9me3) and form the transcriptional repressive center. Deletion of PfSET2, which controls H3K36me3 level, results in marked reduction of both intrachromosomal and interchromosomal interactions for HIRs. Importantly, such chromatin reorganization coordinates with dynamic changes in epigenetic feature in HIRs and transcriptional activation of var genes. Additionally, different cluster of var genes based on the pattern of chromatin interactions show distinct transcriptional activation potential after deletion of PfSET2. Our results uncover a fundamental mechanism that the epigenetic factor PfSET2 controls the 3D organization of heterochromatin to regulate the transcription activities of var genes family in P. falciparum. IMPORTANCE PfSET2 has been reported to play key role in silencing var genes in Plasmodium falciparum, while the underlying molecular mechanisms remain unclear. Here, we provide evidence that PfSET2 is essential to maintain 3D genome organization of heterochromatin region to keep var genes in transcription repressive state. These findings can contribute better understanding of the regulation of high-order chromatin structure in P. falciparum.

BACKGROUND Studies assessing the efficacy of therapies for neovascular age-related macular degeneration (nvAMD) have demonstrated that aflibercept may have a longer treatment interval than its less-expensive alternative, bevacizumab. However, whether this benefit justifies the additional cost of aflibercept remains under debate. We have recently reported that a treat-and-extend-pause/monitor approach can be used to successfully wean 31% of patients with nvAMD off anti-VEGF therapy. Here, we examined whether the choice of therapy influences the outcomes of this approach.METHODS In this retrospective analysis, 122 eyes of 106 patients with nvAMD underwent 3 consecutive monthly injections with either aflibercept (n = 70) or bevacizumab (n = 52), followed by a treat-and-extend protocol, in which the decision to extend the interval between treatments was based on visual acuity, clinical exam, and the presence or absence of fluid on optical coherence tomography. Eyes that remained stable 12 weeks from their prior treatment were given a 6-week trial of holding further treatment, followed by quarterly monitoring. Treatment was resumed for worsening vision, clinical exam, or optical coherence tomography findings.RESULTS At the end of 1 year, eyes receiving bevacizumab had similar vision but required more injections (8.7 ± 0.3 treatments vs. 7.2 ± 0.3 treatments) compared with eyes receiving aflibercept. However, eyes treated with aflibercept were almost 3 times more likely to be weaned off treatment (43% vs. 15%) compared with eyes treated with bevacizumab at the end of 1 year.CONCLUSION These observations expose an advantage of aflibercept over bevacizumab and have important clinical implications for the selection of therapy for patients with nvAMD.FUNDING This work was supported by the National Eye Institute, NIH grants R01EY029750 and R01EY025705, Research to Prevent Blindness, the Alcon Young Investigator Award from the Alcon Research Institute, and the Branna and Irving Sisenwein Professorship in Ophthalmology.

Abstract Studies have shown that matrine has antitumor activity against many types of cancers. However, the direct target in cancer cells of its anticancer effect has not been identified. The purpose of this study was to find the molecular target of matrine to inhibit the proliferation of cancer cells and explore its mechanism of action. Herein we showed that matrine inhibited the proliferation of cancer in vitro and in vivo. Pull-down assay with matrine-amino coupling resins and liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) identified Src as the target of matrine. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) provided solid evidences that matrine directly bound to Src. Bioinformatics prediction and pull-down experiment demonstrated that Src kinase domain was required for its interaction with matrine and Ala392 in the kinase domain participated in matrine–Src interaction. Intriguingly, matrine was proven to inhibit Src kinase activity in a non-ATP-competitive manner by blocking the autophosphorylation of Tyr419 in Src kinase domain. Matrine down-regulated the phosphorylation levels of MAPK/ERK, JAK2/STAT3, and PI3K/Akt signaling pathways via targeting Src. Collectively, matrine targeted Src, inhibited its kinase activity, and down-regulated its downstream MAPK/ERK, JAK2/STAT3, and PI3K/Akt phosphorylation signaling pathways to inhibit the proliferation of cancer cells.

We consider sparsity selection for the Cholesky factor L of the inverse covariance matrix in high-dimensional Gaussian DAG models. The sparsity is induced over the space of L via non-local priors, namely the product moment (pMOM) prior [Johnson, V., & Rossell, D. (2012). Bayesian model selection in high-dimensional settings. Journal of the American Statistical Association, 107(498), 649–660. https://doi.org/10.1080/01621459.2012.682536] and the hierarchical hyper-pMOM prior [Cao, X., Khare, K., & Ghosh, M. (2020). High-dimensional posterior consistency for hierarchical non-local priors in regression. Bayesian Analysis, 15(1), 241–262. https://doi.org/10.1214/19-BA1154]. We establish model selection consistency for Cholesky factor under more relaxed conditions compared to those in the literature and implement an efficient MCMC algorithm for parallel selecting the sparsity pattern for each column of L. We demonstrate the validity of our theoretical results via numerical simulations, and also use further simulations to demonstrate that our sparsity selection approach is competitive with existing methods.

Abstract The viability of lithium‐sulfur (Li–S) batteries toward real implementation directly correlates with unlocking lithium polysulfide (LiPS) evolution reactions. Along this line, designing promotors with the function of synchronously relieving LiPS shuttle and promoting sulfur conversion is critical. Herein, the nitrogen evolution on hierarchical and atomistic Ni–N–C electrocatalyst, mainly pertaining to the essential subtraction, reservation and coordination of nitrogen atoms, is manipulated to attain favorable Li–S pouch cell performances. Such rational evolution behavior realizes the “nitrogen balance” in simultaneously regulating the Ni–N coordination environment, Ni single atom loading, abundant vacancy defects, active nitrogen and electron conductivity, and maximizing the electrocatalytic activity elevation of Ni–N–C system. With such merit, the cathode harvests favorable performances in a soft‐packaged pouch cell prototype even under high sulfur mass loading and lean electrolyte usage. A specific energy density up to 405.1 Wh kg−1 is harvested by the 0.5‐Ah‐level pouch cell.

ObjectiveThis study aimed to assess Chinese public pandemic fatigue and potential influencing factors using an appropriate tool and provide suggestions to relieve this fatigue.MethodsThis study used a stratified sampling method by age and region and conducted a cross-sectional questionnaire survey of citizens in Xi'an, China, from January to February 2022. A total of 1500 participants completed the questionnaire, which collected data on demographics, health status, coronavirus disease 2019 (COVID-19) stressors, pandemic fatigue, COVID-19 fear, COVID-19 anxiety, personal resiliency, social support, community resilience, and knowledge, attitude, and practice toward COVID-19. Ultimately, 1354 valid questionnaires were collected, with a response rate of 90.0%. A binary logistic regression model was used to examine associations between pandemic fatigue and various factors.ResultNearly half of the participants reported pandemic fatigue, the major manifestation of which was “being sick of hearing about COVID-19” (3.353 ± 1.954). The logistic regression model indicated that COVID-19 fear (OR = 2.392, 95% CI = 1.804–3.172), sex (OR = 1.377, 95% CI = 1.077–1.761), the pandemic's impact on employment (OR = 1.161, 95% CI = 1.016–1.327), and COVID-19 anxiety (OR = 1.030, 95% CI = 1.010–1.051) were positively associated with pandemic fatigue. Conversely, COVID-19 knowledge (OR = 0.894, 95% CI = 0.837–0.956), COVID-19 attitude (OR = 0.866, 95% CI = 0.827–0.907), COVID-19 practice (OR = 0.943, 95% CI = 0.914–0.972), community resiliency (OR = 0.978, 95% CI = 0.958–0.999), and health status (OR = 0.982, 95% CI = 0.971–0.992) were negatively associated with pandemic fatigue.ConclusionThe prevalence of pandemic fatigue among the Chinese public was prominent. COVID-19 fear and COVID-19 attitude were the strongest risk factors and protective factors, respectively. These results indicated that the government should carefully utilize multi-channel promotion of anti-pandemic policies and knowledge.

Abstract Alcohol-related liver disease (ALD), a condition caused by alcohol overconsumption, occurs in three stages of liver injury including steatosis, hepatitis, and cirrhosis. DEP domain-containing protein 5 (DEPDC5), a component of GAP activities towards Rags 1 (GATOR1) complex, is a repressor of amino acid-sensing branch of the mammalian target of rapamycin complex 1 (mTORC1) pathway. In the current study, we found that aberrant activation of mTORC1 was likely attributed to the reduction of DEPDC5 in the livers of ethanol-fed mice or ALD patients. To further define the in vivo role of DEPDC5 in ALD development, we generated Depdc5 hepatocyte-specific knockout mouse model (Depdc5-LKO) in which mTORC1 pathway was constitutively activated through loss of the inhibitory effect of GATOR1. Hepatic Depdc5 ablation leads to mild hepatomegaly and liver injury and protects against diet-induced liver steatosis. In contrast, ethanol-fed Depdc5-LKO mice developed severe hepatic steatosis and inflammation. Pharmacological intervention with Torin 1 suppressed mTORC1 activity and remarkably ameliorated ethanol-induced hepatic steatosis and inflammation in both control and Depdc5-LKO mice. The pathological effect of sustained mTORC1 activity in ALD may be attributed to the suppression of peroxisome proliferator activated receptor α (PPARα), the master regulator of fatty acid oxidation in hepatocytes, because fenofibrate (PPARα agonist) treatment reverses ethanol-induced liver steatosis and inflammation in Depdc5-LKO mice. These findings provide novel insights into the in vivo role of hepatic DEPDC5 in the development of ALD.

The green preparation of metal oxide nanoparticles is an environmentally friendly method, which could reduce the use of toxic solvents and their impact on the environment. The purpose of this study is to investigate the green synthesis of zinc oxide (ZnO) nanoparticles using extracts of Hibiscus cannabinus leaves and to evaluate their potential applications in environmental remediation. In this work, ZnO nanoparticles were successfully prepared and thoroughly characterized using UV–vis, Fourier transform infrared analysis (FTIR), X-ray diffraction (XRD), transmission electron microscope (TEM) analysis, and scanning electron microscope (SEM) with energy dispersive x-ray analysis (EDAX). As a result, the synthesized ZnO nanoparticles showed a good adsorption capacity for Congo red (CR), and satisfactory antioxidant and antibacterial activities. They exhibited good adsorption and removal abilities for CR in aqueous solutions. With the conditions optimized, the adsorption kinetics and isotherms were fitted to the pseudo-second-order model and the Langmuir model. The ZnO nanoparticles could also effectively scavenge 2-2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-di(3-ethylbenzthiazoline sulphonate) (ABTS) radicals, and appeared to inhibit the growth of Escherichia coli and Staphylococcus aureus bacteria. Based on the identified adsorption capacity, the green synthesized ZnO nanoparticles demonstrated their potential to be used in the removal of dyeing wastewater and in the further purification of water due to their antioxidant activity and antibacterial activity.

Abstract Objective To explore the influences of digital media use on the core symptoms, emotional state, life events, learning motivation, executive function (EF) and family environment of children and adolescents diagnosed with attention deficit hyperactivity disorder (ADHD) during the novel coronavirus disease 2019 (COVID-19) pandemic. Method A total of 192 participants aged 8–16 years who met the diagnostic criteria for ADHD were included in the study. Children scoring higher than predetermined cut-off point in self-rating questionnaires for problematic mobile phone use (SQPMPU) or Young’s internet addiction test (IAT), were defined as ADHD with problematic digital media use (PDMU), otherwise were defined as ADHD without PDMU. The differences between the two groups in ADHD symptoms, EF, anxiety and depression, stress from life events, learning motivation and family environment were compared respectively. Results When compared with ADHD group without PDMU, the group with PDMU showed significant worse symptoms of inattention, oppositional defiant, behavior and emotional problems by Swanson, Nolan, and Pelham Rating Scale (SNAP), more self-reported anxiety by screening child anxiety-related emotional disorders (SCARED) and depression by depression self-rating scale for children (DSRSC), more severe EF deficits by behavior rating scale of executive function (BRIEF), more stress from life events by adolescent self-rating life events checklist (ASLEC), lower learning motivation by students learning motivation scale (SLMS), and more impairment on cohesion by Chinese version of family environment scale (FES-CV). The ADHD with PDMU group spent significantly more time on both video game and social media with significantly less time spend on physical exercise as compared to the ADHD without PDMU group. Conclusion The ADHD children with PDMU suffered from more severe core symptoms, negative emotions, EF deficits, damage on family environment, pressure from life events, and a lower motivation to learn. Supervision of digital media usage, especially video game and social media, along with increased physical exercise, is essential to the management of core symptoms and associated problems encountered with ADHD.

Most patients with neovascular age-related macular degeneration (nvAMD), the leading cause of severe vision loss in elderly US citizens, respond inadequately to current therapies targeting a single angiogenic mediator, vascular endothelial growth factor (VEGF). Here, we report that aqueous fluid levels of a second vasoactive mediator, angiopoietin-like 4 (ANGPTL4), can help predict the response of patients with nvAMD to anti-VEGF therapies. ANGPTL4 expression was higher in patients who required monthly treatment with anti-VEGF therapies compared with patients who could be effectively treated with less-frequent injections. We further demonstrate that ANGPTL4 acts synergistically with VEGF to promote the growth and leakage of choroidal neovascular (CNV) lesions in mice. Targeting ANGPTL4 expression was as effective as targeting VEGF expression for treating CNV in mice, while simultaneously targeting both was more effective than targeting either factor alone. To help translate these findings to patients, we used a soluble receptor that binds to both VEGF and ANGPTL4 and effectively inhibited the development of CNV lesions in mice. Our findings provide an assay that can help predict the response of patients with nvAMD to anti-VEGF monotherapy and suggest that therapies targeting both ANGPTL4 and VEGF will be a more effective approach for the treatment of this blinding disease.

Current yeast metabolic engineering in isoprenoids production mainly focuses on rewiring of cytosolic metabolic pathway. However, the precursors, cofactors and the enzymes are distributed in various sub-cellular compartments, which may hamper isoprenoid biosynthesis. On the other side, pathway compartmentalization provides several advantages for improving metabolic flux toward target products. We here summarize the recent advances on harnessing sub-organelle for isoprenoids biosynthesis in yeast, and analyze the knowledge about the localization of enzymes, cofactors and metabolites for guiding the rewiring of the sub-organelle metabolism. This review may provide some insights for constructing efficient yeast cell factories for production of isoprenoids and even other natural products.

Cancer stem-like cells are the culprits of tumour recurrence and metastasis, but their regulatory mechanisms are not fully understood. Here, the authors show that the scaffold protein SH3RF3 enhances the stem-like properties of breast cancer by facilitating activation of the JNK-JUN pathway and PTX3 expression.

Abstract The lithium polysulfides (LiPS) dissolution into electrolyte as well as consequent shuttle behavior seriously exacerbate the electrochemical performance of lithium–sulfur batteries. Herein, the intrinsic defect of graphene has been tailored by using plasma irradiation. The topological defective carbon structure is demystified into monovacancy and divacancy which effectively promote Li–S redox kinetics by selectively decelerating the generation of soluble high‐order LiPSs and passingly promoting the conversion to final solid products. Theoretical prediction uncovers the selective manipulation of Li–S redox kinetics by defective graphene, facilitating the reduced overpotential effect and uniform deposition of Li2S. Moreover, the divacancy presents a higher activity for Li–S chemistry in contrast with monovacancy. Therefore, the battery achieves superior cyclability with a capacity retention of 88.6% at 1.0 C over 300 cycles. Furthermore, it yields an areal capacity up to 8.5 mAh cm−2 with a sulfur loading of 13.3 mg cm−2.

This study aimed to address the problems of low detection accuracy and inaccurate positioning of small-object detection in remote sensing images. An improved architecture based on the Swin Transformer and YOLOv5 is proposed. First, Complete-IOU (CIOU) was introduced to improve the K-means clustering algorithm, and then an anchor of appropriate size for the dataset was generated. Second, a modified CSPDarknet53 structure combined with Swin Transformer was proposed to retain sufficient global context information and extract more differentiated features through multi-head self-attention. Regarding the path-aggregation neck, a simple and efficient weighted bidirectional feature pyramid network was proposed for effective cross-scale feature fusion. In addition, extra prediction head and new feature fusion layers were added for small objects. Finally, Coordinate Attention (CA) was introduced to the YOLOv5 network to improve the accuracy of small-object features in remote sensing images. Moreover, the effectiveness of the proposed method was demonstrated by several kinds of experiments on the DOTA (Dataset for Object detection in Aerial images). The mean average precision on the DOTA dataset reached 74.7%. Compared with YOLOv5, the proposed method improved the mean average precision (mAP) by 8.9%, which can achieve a higher accuracy of small-object detection in remote sensing images.

Background To reduce the treatment burden for patients with neovascular age-related macular degeneration (nvAMD), emerging therapies targeting vascular endothelial growth factor (VEGF) are being designed to extend the interval between treatments, thereby minimizing the number of intraocular injections. However, which patients will benefit from longer-acting agents is not clear.Methods Eyes with nvAMD (n = 122) underwent 3 consecutive monthly injections with currently available anti-VEGF therapies, followed by a treat-and-extend protocol. Patients who remained quiescent 12 weeks from their prior treatment entered a treatment pause and were switched to pro re nata (PRN) treatment (based on vision, clinical exam, and/or imaging studies). Proteomic analysis was performed on aqueous fluid to identify proteins that correlate with patients’ response to treatment.Results At the end of 1 year, 38 of 122 eyes (31%) entered a treatment pause (≥30 weeks). Conversely, 21 of 122 eyes (17%) failed extension and required monthly treatment at the end of year 1. Proteomic analysis of aqueous fluid identified proteins that correlated with patients’ response to treatment, including proteins previously implicated in AMD pathogenesis. Interestingly, apolipoprotein-B100 (ApoB100), a principal component of drusen implicated in the progression of nonneovascular AMD, was increased in treated patients who required less frequent injections. ApoB100 expression was higher in AMD eyes compared with controls but was lower in eyes that develop choroidal neovascularization (CNV), consistent with a protective role. Accordingly, mice overexpressing ApoB100 were partially protected from laser-induced CNV.Funding This work was supported by the National Eye Institute, National Institutes of Health grants R01EY029750, R01EY025705, and R01 EY27961; the Research to Prevent Blindness, Inc.; the Alcon Research Institute; and Johns Hopkins University through the Robert Bond Welch and Branna and Irving Sisenwein professorships in ophthalmology.Conclusion Aqueous biomarkers could help identify patients with nvAMD who may not require or benefit from long-term treatment with anti-VEGF therapy.

Sit-to-stand transfer is a very common and critical movement of daily life in elderly individuals, especially independent elderly individuals. However, most assistive robots do not have a sit-to-stand transfer function. In this article, a multi-fuzzy Sarsa learning-based sit-to-stand motion control method for walking-support assistive robot was proposed. First, the mechanical design of walking-support assistive and sit-to-stand transfer motion control problems were introduced. Then, the fuzzy Sarsa learning method, which is a model-free algorithm, was used to design the motion control algorithm for the human–robot system. To realize natural and intuitive sit-to-stand transfer movement for a human–robot system, the interactive force between the robot and human and the error position between the real-time center of mass and reference center of mass were state variables of the proposed fuzzy Sarsa learning-based sit-to-stand motion control algorithm. Considering the computing efficiency of the controller, a multi-fuzzy Sarsa learning -based motion control algorithm was developed to realize natural sit-to-stand transfer motion. Finally, the experimental results verify the effectiveness of the proposed algorithm.

To investigate attention deficit hyperactivity disorder (ADHD) core symptoms that impair executive function (EF), emotional state, learning motivation, and the family and parenting environment of children and adolescents with ADHD, both with and without severe difficulties. This will be explored within an online learning environment during the period of COVID-19 pandemic. A total of 183 ADHD children diagnosed using DSM-V criteria were selected and divided into 2 groups high difficulties during online learning (HDOL) and low difficulties during online learning (LDOL) according to the answer of Home Quarantine Investigation of the Pandemic (HQIP). The participants filled out a set of questionnaires to assess their emotional state and learning motivation, and their parents also filled out the questionnaires about ADHD core symptoms, EF, and family and parenting environment. Compared with ADHD children in the LDOL group, the children in the HDOL group had significant symptoms of inattention, hyperactivity, oppositional defiant, behavioral and emotional problems according to the Swanson, Nolan, and Pelham Rating Scale (SNAP). They also had more severely impaired EF according to the Behavior Rating Inventory of Executive Function (BRIEF), more difficulties and disturbances in the family by the Chinese version of Family Environment Scale (FES-CV), and lower parenting efficacy and satisfaction by Parenting Sense of Competence (PSOC). With regard to the self-rating questionnaires of children and adolescents, the HDOL group reported lower learning motivation according to the Students Learning Motivation Scale (SLMS). By Screening for Child Anxiety-Related Emotional Disorders and Depression Self-Rating Scale for Children (DSRSC), those in HDOL presented more negative emotions. The HDOL group spent significantly more time on both video games and social software per day and significantly less time on multiple activities per week, when compared to those in the LDOL group. This study demonstrated that ADHD children and adolescents with HDOL had more inattention-related behaviors, more severe emotional problems and EF impairment, weaker learning motivation, and poorer family and parenting environment. Meanwhile, digital media use should be supervised and appropriate extracurricular activities should be encouraged by parents and schools.

Current control is of utmost importance for grid-connected converters to achieve a high level of performance. The complex proportional integral controller is usually employed for its excellent performance in terms of cross-coupling decoupling and stability. The pole/zero cancellation characteristic of the complex proportional integral controller, which is always valid in the continues-time domain, fails in the discrete-time domain, resulting in an oscillatory or even unstable response. The discrete complex proportional integral controller has thus been addressed in this work, which cancels the complex plant pole with a matching zero provided by the controller in the discrete-time domain. It has been proved that pole/zero cancellation of the discrete complex proportional integral controller is always valid, regardless of the variation of the excitation frequency. An important feature of performance independence from the pulse ratio is thus achieved. Also, to achieve the possible highest performance, a tuning method based on critical damping is developed in the discrete-time domain, which addresses the one-sample delay directly in the tuning process. In this manner, the minimum settling time and negligible overshoot for transient response can be achieved, along with the most enhanced stability and avoidance of closed-loop anomalous peaks. Experimental results have verified the effectiveness of the developed method.

Background: Changes in the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF) have provided stronger evidence for the pathophysiology of cognitive impairment. Whether the altered patterns of ALFF and fALFF differ in amnestic cognitive impairment (aMCI) and vascular mild cognitive impairment (vMCI) is largely unknown. The purpose of this study was to explore the ALFF/fALFF changes in the two diseases and to further explore whether they contribute to the diagnosis and differentiation of these diseases.Methods: We searched PubMed, Ovid, and Web of Science databases for articles on studies using the ALFF/fALFF method in patients with aMCI and vMCI. Based on the activation likelihood estimation (ALE) method, connectivity modeling based on coordinate meta-analysis and functional meta-analysis was carried out.Results: Compared with healthy controls (HCs), patients with aMCI showed increased ALFF/fALFF in the bilateral parahippocampal gyrus/hippocampus (PHG/HG), right amygdala, right cerebellum anterior lobe (CAL), left middle temporal gyrus (MTG), left cerebrum temporal lobe sub-gyral, left inferior temporal gyrus (ITG), and left cerebrum limbic lobe uncus. Meanwhile, decreased ALFF/fALFF values were also revealed in the bilateral precuneus (PCUN), bilateral cuneus (CUN), and bilateral posterior cingulate (PC) in patients with aMCI. Compared with HCs, patients with vMCI predominantly showed decreased ALFF/fALFF in the bilateral CUN, left PCUN, left PC, and right cingulate gyrus (CG).Conclusions: The present findings suggest that ALFF and fALFF displayed remarkable altered patterns between aMCI and vMCI when compared with HCs. Thus, the findings of this study may serve as a reliable tool for distinguishing aMCI from vMCI, which may help understand the pathophysiological mechanisms of these diseases.

Abstract Introduction The current diagnosis of Parkinson's disease (PD) comorbidity with depression (DPD) largely depends on clinical evaluation. However, the modality may tend to lack precision in detecting PD with depression. A radiomic approach that combines functional connectivity and activity with clinical scores has the potential to achieve accurate and differential diagnosis between PD and DPD. Methods In this study, we aimed to employ the radiomic approach to extract large‐scale features of functional connectivity and activity for differentiating among DPD, PD with no depression (NDPD), and healthy controls (HC). We extracted 6,557 features of five types from all subjects including clinical characteristics, resting‐state functional connectivity (RSFC), amplitude of low‐frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel‐mirrored homotopic connectivity (VMHC). Lasso, random forest, and support vector machine (SVM) were implemented for feature selection and dimension reduction based on the training sets, and the prediction performance for different methods in the testing sets was compared. Results The results showed that nineteen features were selected for the group of DPD versus HC, 34 features were selected for the group of NDPD versus HC, and 17 features were retained for the group of DPD versus NDPD. In the testing sets, Lasso prediction achieved the accuracies of 0.95, 0.96, and 0.85 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Random forest achieved the accuracies of 0.90, 0.82, and 0.90 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively, while SVM yielded the accuracies of 1, 0.86 and 0.65 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Conclusions By identifying aberrant functional connectivity and activity as potential biomarkers, the radiomic approach facilitates a deeper understanding and provides new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) exhibits the poorest prognosis of all solid tumors with a 5‐year survival rate of less than 10% and a median survival of 6 months after diagnosis. Numerous targeted agents have been developed and evaluated to improve the survival benefit in patients with PDAC. Unfortunately, most agents have been proven futile mainly owing to the dense stroma and the sophisticated signaling pathways of PDAC. Here, we show the potent effectiveness of Aptamer‐SH2 superbinder‐(Arg)9 conjugate on the treatment of PDAC. In this conjugate, DNA aptamer selected against PDAC cell line confers the function of specifically recognizing and binding to the PDAC cells and activated pancreatic stellate cells (PSCs) in stroma; cell penetrating peptide (Arg)9 facilitates the intracellular delivery of fused proteins; SH2 superbinder conducts the drastic blockade of multiple phosphotyrosines (pY)‐based signaling pathways in tumor cells. Methods PDAC‐associated pY were reanalyzed by bioinformatics screen. XQ‐2d and SH2 superbinder‐(Arg)9 were crosslinked with BMH to form XQ‐2d‐SH2 CM‐(Arg)9 conjugate. Immunofluorescence was utilized to assess the potency of the conjugate entering cells. MTT and wound healing assays were performed to evaluate the proliferation or migration of PANC‐1 and BxPC‐3 cells, respectively. Western blot and Pulldown assays revealed that conjugate influenced several pY‐based signaling pathways. Tumor‐bearing mice were used to validate XQ‐2d‐SH2 CM‐(Arg)9, which restrained the growth and metastasis of cancer cells. Results XQ‐2d‐His‐SH2 CM‐(Arg)9 conjugate restrained proliferation, invasion, and metastasis of PDAC cells with potent efficacy via blocking the activity of several pY‐related signaling cascades. XQ‐2d‐His‐SH2 CM‐(Arg)9 could eliminate the dense stroma of PDAC and then arrive at tumor tissues. Conclusions XQ‐2d‐SH2 CM‐(Arg)9 conjugate may efficiently destroy the pancreatic stroma and show potent antitumor efficacy with minimal toxic effect by regulating tumor cell proliferation and metastasis in vitro and in vivo, which makes it to be a promising targeted therapy of PDAC.

The outbreak of COVID-19, caused by the SARS-CoV-2 coronavirus, has been declared a pandemic by the World Health Organization (WHO) in March, 2020 and rapidly spread to over 210 countries and territories around the world. By December 24, there are over 77M cumulative confirmed cases with more than 1.72M deaths worldwide. To mathematically describe the dynamic of the COVID-19 pandemic, we propose a time-dependent SEIR model considering the incubation period. Furthermore, we take immunity, reinfection, and vaccination into account and propose the SEVIS model. Unlike the classic SIR based models with constant parameters, our dynamic models not only predicts the number of cases, but also monitors the trajectories of changing parameters, such as transmission rate, recovery rate, and the basic reproduction number. Tracking these parameters, we observe the significant decrease in the transmission rate in the U.S. after the authority announced a series of orders aiming to prevent the spread of the virus, such as closing non-essential businesses and lockdown restrictions. Months later, as restrictions being gradually lifted, we notice a new surge of infection emerges as the transmission rates show increasing trends in some states. Using our epidemiology models, people can track, timely monitor, and predict the COVID-19 pandemic with precision. To illustrate and validate our model, we use the national level data (the U.S.) and the state level data (New York and North Dakota), and the resulting relative prediction errors for the infected group and recovered group are mostly lower than 0.5%. We also simulate the long-term development of the pandemic based on our proposed models to explore when the crisis will end under certain conditions.

In this experiment, response surface methodology was used to study the preparation of malic acid calcium salt from bovine bones assisted by ultrasonication. The results showed that the optimum conditions for ultrasound-assisted preparation of calcium malate from bovine bone were as follows: solid-liquid ratio 1:15, solid-acid ratio 1:1.5, ultrasonic power 200 W, ultrasonic temperature 35°C, and ultrasonication time 17 min. The efficiency of calcium recovery was 66.16%, and the purity was 92.54%. After three ultrasonic treatments of 17 min each, the calcium malate conversion rate of bovine bone reached 95.73%. Animal experiments showed that feeding bovine bone-derived calcium malate significantly increased alkaline phosphatase (ALP) activity and bone calcium content, reduced tartrate-resistant acid phosphatase (TRAP) activity, and maintained the balance of serum calcium and phosphorus. These results indicated that the ultrasonic method effectively ionized calcium in bovine bone, which provides a reference point for the industrial production of calcium products with bovine bone as the raw material.

Parkinson’s disease (PD) is a progressive, chronic, and neurodegenerative disorder that is primarily diagnosed by clinical examinations and magnetic resonance imaging (MRI). In this study, we proposed a machine learning based radiomics method to predict PD. Fifty healthy controls (HC) along with 70 PD patients underwent resting-state magnetic resonance imaging (rs-fMRI). For all subjects, we extracted five types of 6664 features, including mean amplitude of low-frequency fluctuation (mALFF), mean regional homogeneity (mReHo), resting-state functional connectivity (RSFC), voxel-mirrored homotopic connectivity (VMHC) and gray matter (GM) volume. After conducting dimension reduction utilizing Least absolute shrinkage and selection operator (LASSO), fifty-three radiomic features including 46 RSFCs, 1 mALFF, 3 mReHos, 1 VMHC, 2 GM volumes and 1 clinical factor were retained. The selected features also indicated the most discriminative regions for PD. We further conducted model fitting procedure for classifying subjects in the training set employing random forest and support volume machine (SVM) to evaluate the performance of the two methods. After cross-validation, both methods achieved 100% accuracy and area under curve (AUC) for distinguishing between PD and HC in the training set. In the testing set, SVM performed better than random forest with the accuracy, true positive rate (TPR) and AUC being 85%, 1 and 0.97, respectively. These findings demonstrate the radiomics technique has the potential to support radiological diagnosis and to achieve high classification accuracy for clinical diagnostic systems for patients with PD.

Abstract Background Glioblastomas multiforme (GBM) is the most devastating primary intracranial malignancy lacking effective clinical treatments. Notch2 has been established to be a prognostic marker and probably involved in GBM malignant progression. N-acetylcysteine (NAC), a precursor of intracellular glutathione (GSH), has been widely implicated in prevention and therapy of several cancers. However, the role of NAC in GBM remains unclear and the property of NAC independent of its antioxidation is largely unknown. Methods The mRNA and protein levels of Notch family and other related factors were detected by RT-PCR and western blot, respectively. In addition, intracellular reactive oxygen species (ROS) was measured by flow cytometry-based DCFH-DA. Moreover, cell viability was assessed by CCK8 and cell cycle was analyzed by flow cytometry-based PI staining. The level of apoptosis was checked by flow cytometry-based Annexin V/PI. Cell migration and invasion were evaluated by wound healing and transwell invasion assays. At last, U87 Xenograft model was established to confirm whether NAC could restrain the growth of tumor. Results Our data showed that NAC could decrease the protein level of Notch2. Meanwhile, NAC had a decreasing effect on the mRNA and protein levels of its downstream targets Hes1 and Hey1. These effects caused by NAC were independent of cellular GSH and ROS levels. The mechanism of NAC-mediated Notch2 reduction was elucidated by promoting Notch2 degradation through Itch-dependent lysosome pathway. Furthermore, NAC could prevent proliferation, migration, and invasion and might induce apoptosis in GBM cells via targeting Notch2. Significantly, NAC could suppress the growth of tumor in vivo. Conclusions NAC could facilitate Notch2 degradation through lysosomal pathway in an antioxidant-independent manner, thus attenuating Notch2 malignant signaling in GBM cells. The remarkable ability of NAC to inhibit cancer cell proliferation and tumor growth may implicate a novel application of NAC on GBM therapy.

Abstract Background Melanoma is a malignant tumor with high misdiagnosis rate and poor prognosis. The bio-targeted therapy is a prevailing method in the treatment of melanoma; however, the accompanying drug resistance is inevitable. SH2 superbinder, a triple-mutant of the Src Homology 2 (SH2) domain, shows potent antitumor ability by replacing natural SH2-containing proteins and blocking multiple pY-based signaling pathways. Polyarginine (Arg)9, a powerful vector for intracellular delivery of large molecules, could transport therapeutic agents across cell membrane. The purpose of this study is to construct (Arg)9-SH2 superbinder and investigate its effects on melanoma cells, expecting to provide potential new approaches for anti-cancer therapy and overcoming the unavoidable drug resistance of single-targeted antitumor agents. Methods (Arg)9 and SH2 superbinder were fused to form (Arg)9-SH2 superbinder via genetic engineering. Pull down assay was performed to identify that (Arg)9-SH2 superbinder could capture a wide variety of pY proteins. Immunofluorescence was used to detect the efficiency of (Arg)9-SH2 superbinder entering cells. The proliferation ability was assessed by MTT and colony formation assay. In addition, wound healing and transwell assay were performed to evaluate migration of B16F10, A375 and A375/DDP cells. Moreover, apoptosis caused by (Arg)9-SH2 superbinder was analyzed by flow cytometry-based Annexin V/PI. Furthermore, western blot revealed that (Arg)9-SH2 superbinder influenced some pY-related signaling pathways. Finally, B16F10 xenograft model was established to confirm whether (Arg)9-SH2 superbinder could restrain the growth of tumor. Results Our data showed that (Arg)9-SH2 superbinder had the ability to enter melanoma cells effectively and displayed strong affinities for various pY proteins. Furthermore, (Arg)9-SH2 superbinder could repress proliferation, migration and induce apoptosis of melanoma cells by regulating PI3K/AKT, MAPK/ERK and JAK/STAT signaling pathways. Importantly, (Arg)9-SH2 superbinder could significantly inhibit the growth of tumor in mice. Conclusions (Arg)9-SH2 superbinder exhibited high affinities for pY proteins, which showed effective anticancer ability by replacing SH2-containing proteins and blocking diverse pY-based pathways. The remarkable ability of (Arg)9-SH2 superbinder to inhibit cancer cell proliferation and tumor growth might open the door to explore the SH2 superbinder as a therapeutic agent for cancer treatment.

An ionic porous aromatic framework is developed as a self-degraded template to synthesize the magnetic heterostructure of γ-Fe2O3/WO3·0.5H2O. The Fe3O4 polyhedron was obtained with the two-phase method first and then reacted with sodium tungstate to form the γ-Fe2O3/WO3·0.5H2O hybrid nanostructure. Under the induction effect of the ionic porous network, the Fe3O4 phase transformed to the γ-Fe2O3 state and complexed with WO3·0.5H2O to form the n-n heterostructure with the n-type WO3·0.5H2O on the surface of n-type γ-Fe2O3. Based on a UV-Visible analysis, the magnetic photocatalyst was shown to have a suitable band gap for the catalytic degradation of organic pollutants. Under irradiation, the resulting γ-Fe2O3/WO3·0.5H2O sample exhibited a removal efficiency of 95% for RhB in 100 min. The charge transfer mechanism was also studied. After the degradation process, the dispersed powder can be easily separated from the suspension by applying an external magnetic field. The catalytic activity displayed no significant decrease after five recycles. The results present new insights for preparing a hybrid nanostructure photocatalyst and its potential application in harmful pollutant degradation.

Objective: This study compared survival of prostate cancer patients with low prostate specific antigen level (PSA ≤ 10 ng/ml) and high-grades of Gleason score (GS) of 8–10 with different treatment options (i.e., radical prostatectomy [RP], external beam radiotherapy [EBRT], or external beam radiotherapy with brachytherapy [EBRT+BT]).Materials and Methods: The Surveillance, Epidemiology and End Results (SEER) database data (2004–2013), and overall survival (OS) and prostate cancer-specific mortality (PCSM), were evaluated using the Cox proportional hazards regression model and Fine and Gray competing risk model.Results: The SEER data contained 9,114 patients, 4,175 of whom received RP, 4,114 received EBRT, and 825 received EBRT+BT with a median follow-up duration of 47 months. RP patients had significantly better OS than patients with EBRT and EBRT+BT (adjusted HR [AHR]: 3.36, 95% CI: 2.43–4.64, P < 0.001; AHR: 2.15, 95% CI: 1.32–3.48, P = 0.002; respectively). There was no statistical difference in PCSM between RP and EBRT+BT (AHR: 1.31, 95% CI: 0.61–2.80, P = 0.485), while EBRT had worse OS (P < 0.05). The subgroup analysis revealed that there was no statistical difference in prognosis of patients with age of >70 years old, or PSA levels of ≤ 2.5 ng/ml between RP and EBRT+BT (P > 0.05).Conclusion: RP patients with low PSA levels and high GS had better OS compared to either EBRT or EBRT+BT, while RP and EBRT+BT resulted in significantly lower PCSM, compared to EBRT. Moreover, EBRT+BT and RP were associated with similar survival of patients with age of > 70 years old, or PSA levels of ≤ 2.5 ng/ml.

The formation of gaps in the endothelium is a crucial process underlying both cancer and immune cell extravasation, contributing to the functioning of the immune system during infection, the unfavorable development of chronic inflammation and tumor metastasis. Here, we present a stochastic-mechanical multiscale model of an endothelial cell monolayer and show that the dynamic nature of the endothelium leads to spontaneous gap formation, even without intervention from the transmigrating cells. These gaps preferentially appear at the vertices between three endothelial cells, as opposed to the border between two cells. We quantify the frequency and lifetime of these gaps, and validate our predictions experimentally. Interestingly, we find experimentally that cancer cells also preferentially extravasate at vertices, even when they first arrest on borders. This suggests that extravasating cells, rather than initially signaling to the endothelium, might exploit the autonomously forming gaps in the endothelium to initiate transmigration.

High-dimensional variable selection is an important research topic in modern statistics. While methods using nonlocal priors have been thoroughly studied for variable selection in linear regression, the crucial high-dimensional model selection properties for nonlocal priors in generalized linear models have not been investigated. In this paper, we consider a hierarchical generalized linear regression model with the product moment nonlocal prior over coefficients and examine its properties. Under standard regularity assumptions, we establish strong model selection consistency in a high-dimensional setting, where the number of covariates is allowed to increase at a sub-exponential rate with the sample size. The Laplace approximation is implemented for computing the posterior probabilities and the shotgun stochastic search procedure is suggested for exploring the posterior space. The proposed method is validated through simulation studies and illustrated by a real data example on functional activity analysis in fMRI study for predicting Parkinson’s disease.