[18F]FDG PET integrated with structural MRI for accurate brain age prediction.

PURPOSE: Brain aging is a complex and heterogeneous process characterized by both structural and functional decline. This study aimed to establish a novel deep learning (DL) method for predicting brain age by utilizing structural and metabolic imaging data. METHODS: The dataset comprised participants from both the Universal Medical Imaging Diagnostic Center (UMIDC) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The former recruited 395 normal control (NC) subjects, while the latter included 438 NC subjects, 51 mild cognitive impairment (MCI) subjects, and 56 Alzheimer's disease (AD) subjects. We developed a novel dual-pathway, 3D simple fully convolutional network (Dual-SFCNeXt) to estimate brain age using [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) and structural magnetic resonance imaging (sMRI) images of NC subjects as input. Several prevailing DL models were trained and tested using either MRI or PET data for comparison. Model accuracies were evaluated using mean absolute error (MAE) and Pearson's correlation coefficient (r). Brain age gap (BAG), deviations of brain age from chronologic age, was correlated with cognitive assessments in MCI and AD subjects. RESULTS: Both PET- and MRI-based models achieved high prediction accuracy. The leading model was the SFCNeXt (the single-pathway version) for PET (MAE = 2.92, r = 0.96) and MRI (MAE = 3.23, r = 0.95) on all samples. By integrating both PET and MRI images, the Dual-SFCNeXt demonstrated significantly improved accuracy (MAE = 2.37, r = 0.97) compared to all single-modality models. Significantly higher BAG was observed in both the AD (P < 0.0001) and MCI (P < 0.0001) groups compared to the NC group. BAG correlated significantly with Mini-Mental State Examination (MMSE) scores (r=-0.390 for AD, r=-0.436 for MCI) and the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) scores (r = 0.333 for AD, r = 0.372 for MCI). CONCLUSION: The integration of [18F]FDG PET with structural MRI enhances the accuracy of brain age prediction, potentially introducing a new avenue for related multimodal brain age prediction studies.

A novel spatiotemporal graph convolutional network framework for functional connectivity biomarkers identification of Alzheimer's disease.

BACKGROUND: Functional connectivity (FC) biomarkers play a crucial role in the early diagnosis and mechanistic study of Alzheimer's disease (AD). However, the identification of effective FC biomarkers remains challenging. In this study, we introduce a novel approach, the spatiotemporal graph convolutional network (ST-GCN) combined with the gradient-based class activation mapping (Grad-CAM) model (STGC-GCAM), to effectively identify FC biomarkers for AD. METHODS: This multi-center cross-racial retrospective study involved 2,272 participants, including 1,105 cognitively normal (CN) subjects, 790 mild cognitive impairment (MCI) individuals, and 377 AD patients. All participants underwent functional magnetic resonance imaging (fMRI) and T1-weighted MRI scans. In this study, firstly, we optimized the STGC-GCAM model to enhance classification accuracy. Secondly, we identified novel AD-associated biomarkers using the optimized model. Thirdly, we validated the imaging biomarkers using Kaplan-Meier analysis. Lastly, we performed correlation analysis and causal mediation analysis to confirm the physiological significance of the identified biomarkers. RESULTS: The STGC-GCAM model demonstrated great classification performance (The average area under the curve (AUC) values for different categories were: CN vs MCI = 0.98, CN vs AD = 0.95, MCI vs AD = 0.96, stable MCI vs progressive MCI = 0.79). Notably, the model identified specific brain regions, including the sensorimotor network (SMN), visual network (VN), and default mode network (DMN), as key differentiators between patients and CN individuals. These brain regions exhibited significant associations with the severity of cognitive impairment (p < 0.05). Moreover, the topological features of important brain regions demonstrated excellent predictive capability for the conversion from MCI to AD (Hazard ratio = 3.885, p < 0.001). Additionally, our findings revealed that the topological features of these brain regions mediated the impact of amyloid beta (Aß) deposition (bootstrapped average causal mediation effect: ß = -0.01 [-0.025, 0.00], p < 0.001) and brain glucose metabolism (bootstrapped average causal mediation effect: ß = -0.02 [-0.04, -0.001], p < 0.001) on cognitive status. CONCLUSIONS: This study presents the STGC-GCAM framework, which identifies FC biomarkers using a large multi-site fMRI dataset.

Positron Emission Tomography Imaging of Synaptic Dysfunction in Parkinson's Disease.

Parkinson's disease (PD) is one of the most common neurodegenerative diseases with a complex pathogenesis. Aggregations formed by abnormal deposition of alpha-synuclein (αSyn) lead to synapse dysfunction of the dopamine and non-dopamine systems. The loss of dopaminergic neurons and concomitant alterations in non-dopaminergic function in PD constitute its primary pathological manifestation. Positron emission tomography (PET), as a representative molecular imaging technique, enables the non-invasive visualization, characterization, and quantification of biological processes at cellular and molecular levels. Imaging synaptic function with PET would provide insights into the mechanisms underlying PD and facilitate the optimization of clinical management. In this review, we focus on the synaptic dysfunction associated with the αSyn pathology of PD, summarize various related targets and radiopharmaceuticals, and discuss applications and perspectives of PET imaging of synaptic dysfunction in PD.

Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis.

Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest: area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI: 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI: 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI: 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI: 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI: 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.

In vivo cerebral metabolic and dopaminergic characteristics in multiple system atrophy with orthostatic hypotension.

PURPOSE: Multiple system atrophy (MSA) is a rare neurodegenerative disease, often presented with orthostatic hypotension (OH), which is a disabling symptom but has not been very explored. Here, we investigated MSA patients with OH by using positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) and 11C-N-2-carbomethoxy-3-(4-fluorophenyl)-tropane (11C-CFT) for in vivo evaluation of the glucose metabolism and dopaminergic function of the brain. METHODS: Totally, 51 patients with MSA and 20 healthy controls (HC) who underwent 18F-FDG PET/CT were retrospectively enrolled, among which 24 patients also underwent 11C-CFT PET/CT. All patients were divided into MSA-OH(+) and MSA-OH(-) groups. Then, statistical parametric mapping (SPM) method was used to reveal the regional metabolic and dopaminergic characteristics of MSA-OH(+) compared with MSA-OH(-). Moreover, the metabolic networks of MSA-OH(+), MSA-OH(-) and HC groups were also constructed and analyzed based on graph theory to find possible network-level changes in MSA patients with OH. RESULTS: The SPM results showed significant hypometabolism in the pons and right cerebellar tonsil, as well as hypermetabolism in the left parahippocampal gyrus and left superior temporal gyrus in MSA-OH(+) compared with MSA-OH(-). A reduced 11C-CFT uptake in the left caudate was also shown in MSA-OH(+) compared with MSA-OH(-). In the network analysis, significantly reduced local efficiency and clustering coefficient were shown in MSA-OH(+) compared with HC, and decreased nodal centrality in the frontal gyrus was found in MSA-OH(+) compared with MSA-OH(-). CONCLUSION: In this study, the changes in glucose metabolism in the pons, right cerebellar tonsil, left parahippocampal gyrus and left superior temporal gyrus were found closely related to OH in MSA patients. And the decreased presynaptic dopaminergic function in the left caudate may contribute to OH in MSA. Taken together, this study provided in vivo pathophysiologic information on MSA with OH from neuroimaging approach, which is essential for a better understanding of MSA with OH.

Expression of clMagR/clCry4 protein in mBMSCs provides T2-contrast enhancement of MRI.

Here, we propose for the first time the evaluation of magnetosensitive clMagR/clCry4 as a magnetic resonance imaging (MRI) reporter gene that imparts sensitivity to endogenous contrast in eukaryotic organisms. Using a lentiviral vector, we introduced clMagR/clCry4 into C57BL/6 mice-derived bone marrow mesenchymal stem cells (mBMSCs), which could specifically bind with iron, significantly affected MRI transverse relaxation, and generated readily detectable contrast without adverse effects in vivo. Specifically, clMagR/clCry4 makes mBMSCs beneficial for enhancing the sensitivity of MRI-R2 for iron-bearing granules, in which cells recruit exogenous iron and convert these stores into an MRI-detectable contrast; this is not achievable with control cells. Additionally, Prussian blue staining was performed together with ultrathin cell slices to provide direct evidence of natural iron-bearing granules being detectable on MRI. Hence, it was inferred that the sensitivity of MRI detection should be correlated with clMagR/clCry4 and exogenous iron. Taken together, the clMagR/clCry4 has great potential as an MRI reporter gene. STATEMENT OF SIGNIFICANCE: In this study, we propose the evaluation of magnetosensitive clMagR/clCry4 as an MRI reporter gene, imparting detection sensitivity to eukaryotic mBMSCs for endogenous contrast. At this point, the clMagR and clCry4 were located within the cytoplasm and possibly influence each other. The clMagR/clCry4 makes mBMSCs beneficial for enhancing the sensitivity of MRI-R2 for iron-bearing granules, in which protein could specifically bind with iron and convert these stores into MRI-detectable contrast; this is not achieved by control cells. The viewpoint was speculated that the clMagR/clCry4 and exogenous iron were complementary to each other. Additionally, Prussian blue staining was performed together with TEM observations to provide direct evidence that the iron-bearing granules were sensitive to MRI.

A key O-demethylase in the degradation of guaiacol by Rhodococcus opacus PD630.

Rhodococcus opacus PD630 is a high oil-producing strain with the ability to convert lignin-derived aromatics to high values, but limited research has been done to elucidate its conversion pathway, especially the upper pathways. In this study, we focused on the upper pathways and demethylation mechanism of lignin-derived aromatics metabolism by R. opacus PD630. The results of the aromatic carbon resource utilization screening showed that R. opacus PD630 had a strong degradation capacity to the lignin-derived methoxy-containing aromatics, such as guaiacol, 3,4-veratric acid, anisic acid, isovanillic acid, and vanillic acid. The gene of gcoAR, which encodes cytochrome P450, showed significant up-regulation when R. opacus PD630 grew on diverse aromatics. Deletion mutants of gcoAR and its partner protein gcoBR resulted in the strain losing the ability to grow on guaiacol, but no significant difference to the other aromatics. Only co-complementation alone of gcoAR and gcoBR restored the strain's ability to utilize guaiacol, demonstrating that both genes were equally important in the utilization of guaiacol. In vitro assays further revealed that GcoAR could convert guaiacol and anisole to catechol and phenol, respectively, with the production of formaldehyde as a by-product. The study provided robust evidence to reveal the molecular mechanism of R. opacus PD630 on guaiacol metabolism and offered a promising study model for dissecting the demethylation process of lignin-derived aromatics in microbes.IMPORTANCEAryl-O-demethylation is believed to be the key rate-limiting step in the catabolism of heterogeneous lignin-derived aromatics in both native and engineered microbes. However, the mechanisms of O-demethylation in lignin-derived aromatic catabolism remain unclear. Notably, guaiacol, the primary component unit of lignin, lacks in situ demonstration and illustration of the molecular mechanism of guaiacol O-demethylation in lignin-degrading bacteria. This is the first study to illustrate the mechanism of guaiacol metabolism by R. opacus PD630 in situ as well as characterize the purified key O-demethylase in vitro. This study provided further insight into the lignin metabolic pathway of R. opacus PD630 and could guide the design of an efficient biocatalytic system for lignin valorization.

[18F]FDG PET/MRI combined with chest HRCT in early cancer detection: a retrospective study of 3020 asymptomatic subjects.

PURPOSE: PET/MRI has become an important medical imaging approach in clinical practice. In this study, we retrospectively investigated the detectability of fluorine-18 (18F)-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ([18F]FDG PET/MRI) combined with chest computerized tomography (CT) for early cancer in a large cohort of asymptomatic subjects. METHODS: This study included a total of 3020 asymptomatic subjects who underwent whole-body [18F]FDG PET/MRI and chest HRCT examinations. All subjects received a 2-4-year follow-up for cancer development. Cancer detection rate, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the [18F]FDG PET/MRI with or without chest HRCT were calculated and analyzed. RESULTS: Sixty-one subjects were pathologically diagnosed with cancers, among which 59 were correctly detected by [18F]FDG PET/MRI combined with chest HRCT. Of the 59 patients (32 with lung cancer, 9 with breast cancer, 6 with thyroid cancer, 5 with colon cancer, 3 with renal cancer, 1 with prostate cancer, 1 with gastric cancer, 1 with endometrial cancer, and 1 with lymphoma), 54 (91.5%) were at stage 0 or stage I (according to the 8th edition of the tumor-node-metastasis [TNM] staging system), 33 (55.9%) were detected by PET/MRI alone (27 with non-lung cancers and 6 with lung cancer). Cancer detection rate, sensitivity, specificity, PPV, and NPV for PET/MRI combined with chest CT were 2.0%, 96.7%, 99.6%, 83.1%, and 99.9%, respectively. For PET/MRI alone, the metrics were 1.1%, 54.1%, 99.6%, 73.3%, and 99.1%, respectively, and for PET/MRI in non-lung cancers, the metrics were 0.9%, 93.1%, 99.6%, 69.2%, and 99.9%, respectively. CONCLUSIONS: [18F]FDG PET/MRI holds great promise for the early detection of non-lung cancers, while it seems insufficient for detecting early-stage lung cancers. Chest HRCT can be complementary to whole-body PET/MRI for early cancer detection. TRIAL REGISTRATION: ChiCTR2200060041. Registered 16 May 2022. Public site: https://www.chictr.org.cn/index.html.

Transfection of clMagR/clCry4 imparts MR-T2 imaging contrast properties to living organisms (E. coli) in the presence of Fe3+ by endogenous formation of iron oxide nanoparticles.

Rapid development of medical imaging, such as cellular tracking, has increased the demand for "live" contrast agents. This study provides the first experimental evidence demonstrating that transfection of the clMagR/clCry4 gene can impart magnetic resonance imaging (MRI) T2-contrast properties to living prokaryotic Escherichia coli (E. coli) in the presence of Fe3+ through the endogenous formation of iron oxide nanoparticles. The transfected clMagR/clCry4 gene markedly promoted uptake of exogenous iron by E. coli, achieving an intracellular co-precipitation condition and formation of iron oxide nanoparticles. This study will stimulate further exploration of the biological applications of clMagR/clCry4 in imaging studies.

AIGAN: Attention-encoding Integrated Generative Adversarial Network for the reconstruction of low-dose CT and low-dose PET images.

X-ray computed tomography (CT) and positron emission tomography (PET) are two of the most commonly used medical imaging technologies for the evaluation of many diseases. Full-dose imaging for CT and PET ensures the image quality but usually raises concerns about the potential health risks of radiation exposure. The contradiction between reducing the radiation exposure and remaining diagnostic performance can be addressed effectively by reconstructing the low-dose CT (L-CT) and low-dose PET (L-PET) images to the same high-quality ones as full-dose (F-CT and F-PET). In this paper, we propose an Attention-encoding Integrated Generative Adversarial Network (AIGAN) to achieve efficient and universal full-dose reconstruction for L-CT and L-PET images. AIGAN consists of three modules: the cascade generator, the dual-scale discriminator and the multi-scale spatial fusion module (MSFM). A sequence of consecutive L-CT (L-PET) slices is first fed into the cascade generator that integrates with a generation-encoding-generation pipeline. The generator plays the zero-sum game with the dual-scale discriminator for two stages: the coarse and fine stages. In both stages, the generator generates the estimated F-CT (F-PET) images as like the original F-CT (F-PET) images as possible. After the fine stage, the estimated fine full-dose images are then fed into the MSFM, which fully explores the inter- and intra-slice structural information, to output the final generated full-dose images. Experimental results show that the proposed AIGAN achieves the state-of-the-art performances on commonly used metrics and satisfies the reconstruction needs for clinical standards.

Characterization of neuroinflammation pattern in anti-LGI1 encephalitis based on TSPO PET and symptom clustering analysis.

PURPOSE: TSPO PET with radioligand [18F]DPA-714 is an emerging molecular imaging technique that reflects cerebral inflammation and microglial activation, and it has been recently used in central nervous system diseases. In this study, we aimed to investigate the neuroinflammation pattern of anti-leucine-rich glioma-inactivated 1 (LGI1) protein autoimmune encephalitis (AIE) and to evaluate its possible correlation with clinical phenotypes. METHODS: Twenty patients with anti-LGI1 encephalitis from the autoimmune encephalitis cohort in Huashan Hospital and ten with other AIE and non-inflammatory diseases that underwent TSPO PET imaging were included in the current study. Increased regional [18F]DPA-714 retention in anti-LGI1 encephalitis was detected on a voxel basis using statistic parametric mapping analysis. Multiple correspondence analysis and hierarchical clustering were conducted for discriminate subgroups in anti-LGI1 encephalitis. Standardized uptake value ratios normalized to the cerebellum (SUVRc) were calculated for semiquantitative analysis of TSPO PET features between different LGI1-AIE subgroups. RESULTS: Increased regional retention of [18F]DPA-714 was identified in the bilateral hippocampus, caudate nucleus, and frontal cortex in LGI1-AIE patients. Two subgroups of LGI1-AIE patients were distinguished based on the top seven common symptoms. Patients in cluster 1 had a high frequency of facio-brachial dystonic seizures than those in cluster 2 (p = 0.004), whereas patients in cluster 2 had a higher frequency of general tonic-clonic (GTC) seizures than those in cluster 1 (p < 0.001). Supplementary motor area and superior frontal gyrus showed higher [18F]DPA-714 retention in cluster 2 patients compared with those in cluster 1 (p = 0.024; p = 0.04, respectively). CONCLUSIONS: Anti-LGI1 encephalitis had a distinctive molecular imaging pattern presented by TSPO PET scan. LGI1-AIE patients with higher retention of [18F]DPA-714 in the frontal cortex were more prone to present with GTC seizures. Further studies are required for verifying its value in clinical application.

Biological Scaffolds Assembled with Magnetic Nanoparticles for Bone Tissue Engineering: A Review.

Superparamagnetic iron oxide nanoparticles (SPION) are widely used in bone tissue engineering because of their unique physical and chemical properties and their excellent biocompatibility. Under the action of a magnetic field, SPIONs loaded in a biological scaffold can effectively promote osteoblast proliferation, differentiation, angiogenesis, and so on. SPIONs have very broad application prospects in bone repair, bone reconstruction, bone regeneration, and other fields. In this paper, several methods for forming biological scaffolds via the biological assembly of SPIONs are reviewed, and the specific applications of these biological scaffolds in bone tissue engineering are discussed.

Bionic Magnetic Sensor Based on the MagR/Cry4 Complex-Configured Graphene Transistor with an Integrated On-Chip Gate.

Magnetic-sensitive proteins are regarded as key factors in animals' precise perception of the geomagnetic field. Accurate feedback on the response of these tiny proteins to magnetic fields remains a challenge. Here, we first propose a real-time accurate magnetic sensor based on the MagR/Cry4 complex-configured graphene transistor with an integrated on-chip gate. A nanometer-thick denatured bovine serum albumin film was used as the bio-interface of graphene electrolyte-gated transistors (EGTs) to immobilize the MagR/Cry4 complex. With the optimization and characterization of this bionic graphene EGT, it could detect magnetic fields in real time with a sensitivity of 1 mT, which is far lower than in earlier research. It was concluded that our MagR/Cry4 complex-configured graphene EGTs with a side-gate held great promise in terms of geomagnetic field detection. Furthermore, the constructed approach in this paper could also be utilized as a general solution for recording the response of magnetically sensitive biomolecules to magnetic fields in real time.

Rapid improvement of heart repair in rats after myocardial infarction by precise magnetic stimulation on the vagus nerve with an injectable magnetic hydrogel.

The imbalance between the sympathetic and the parasympathetic nervous system is one of the main pathogeneses of myocardial infarction (MI). Vagus nerve stimulation (VNS), which restores autonomic nervous balance by enhancing the parasympathetic drive, is shown to have benefits for patients with MI. As a clinically safe and effective remote neuromodulation method, magnetic stimulation is expected to overcome the problems of infection and nerve injury caused by electrode implantation. However, it is difficult to achieve precise stimulation on a single vagus nerve due to the poor focus of the magnetic field. Here, we described a novel magnetic vagus nerve stimulation (mVNS) system, which consisted of an injectable chitosan/ß-glycerophosphate (CS/GP) hydrogel loaded with superparamagnetic iron oxide (SPIO) nanoparticles and a mild magnetic pulse sequence. The injectable hydrogel prepared from clinically safe materials ensured minimally invasive implantation, and the SPIO nanoparticles in the hydrogel mediated the precise magnetic stimulation of a single vagus nerve. Under a mild magnetic field (∼100 mT), a decrease in heart rate and a change in vagus nerve potential were found in rats under in situ injection of a magnetic CS/GP hydrogel. Magnetic stimulation on the vagus nerve for 4 weeks (20 Hz, three times daily, 5 minutes each time) significantly improved the cardiac function and reduced the infarct size of the rats subjected to myocardial infarction, accompanied by suppression of inflammatory cell infiltration and inflammation factor expression. Taken together, these results demonstrated that the mVNS exhibited promising potential for treating myocardial infarction in the clinic.

Phenomic Imaging.

Human phenomics is defined as the comprehensive collection of observable phenotypes and characteristics influenced by a complex interplay among factors at multiple scales. These factors include genes, epigenetics at the microscopic level, organs, microbiome at the mesoscopic level, and diet and environmental exposures at the macroscopic level. "Phenomic imaging" utilizes various imaging techniques to visualize and measure anatomical structures, biological functions, metabolic processes, and biochemical activities across different scales, both in vivo and ex vivo. Unlike conventional medical imaging focused on disease diagnosis, phenomic imaging captures both normal and abnormal traits, facilitating detailed correlations between macro- and micro-phenotypes. This approach plays a crucial role in deciphering phenomes. This review provides an overview of different phenomic imaging modalities and their applications in human phenomics. Additionally, it explores the associations between phenomic imaging and other omics disciplines, including genomics, transcriptomics, proteomics, immunomics, and metabolomics. By integrating phenomic imaging with other omics data, such as genomics and metabolomics, a comprehensive understanding of biological systems can be achieved. This integration paves the way for the development of new therapeutic approaches and diagnostic tools.

Protocol for Brain Magnetic Resonance Imaging and Extraction of Imaging-Derived Phenotypes from the China Phenobank Project.

Imaging-derived phenotypes (IDPs) have been increasingly used in population-based cohort studies in recent years. As widely reported, magnetic resonance imaging (MRI) is an important imaging modality for assessing the anatomical structure and function of the brain with high resolution and excellent soft-tissue contrast. The purpose of this article was to describe the imaging protocol of the brain MRI in the China Phenobank Project (CHPP). Each participant underwent a 30-min brain MRI scan as part of a 2-h whole-body imaging protocol in CHPP. The brain imaging sequences included T1-magnetization that prepared rapid gradient echo, T2 fluid-attenuated inversion-recovery, magnetic resonance angiography, diffusion MRI, and resting-state functional MRI. The detailed descriptions of image acquisition, interpretation, and post-processing were provided in this article. The measured IDPs included volumes of brain subregions, cerebral vessel geometrical parameters, microstructural tracts, and function connectivity metrics.

Magnetic hydrogels with ordered structure for biomedical applications.

Magnetic hydrogels composed of hydrogel matrices and magnetic nanomaterials have attracted widespread interests. Thereinto, magnetic hydrogels with ordered structure possessing enhanced functionalities and unique architectures, show tremendous advantages in biomedical fields. The ordered structure brought unique anisotropic properties and excellent physical properties. Furthermore, the anisotropic properties of magnetic ordered hydrogels are more analogous to biological tissues in morphology and mechanical property, showing better biocompatibility and bioinducibility. Thus, we aim to systematically describe the latest advances of magnetic hydrogels with ordered structure. Firstly, this review introduced the synthetic methods of magnetic hydrogels focus on constructing ordered structure. Then, their functionalities and biomedical applications are also summarized. Finally, the current challenges and a compelling perspective outlook of magnetic ordered hydrogel are present.

Microbial lignin valorization through depolymerization to aromatics conversion.

Lignin is the most abundant source of renewable aromatic biopolymers and its valorization presents significant value for biorefinery sustainability, which promotes the utilization of renewable resources. However, it is challenging to fully convert the structurally complex, heterogeneous, and recalcitrant lignin into high-value products. The in-depth research on the lignin degradation mechanism, microbial metabolic pathways, and rational design of new systems using synthetic biology have significantly accelerated the development of lignin valorization. This review summarizes the key enzymes involved in lignin depolymerization, the mechanisms of microbial lignin conversion, and the lignin valorization application with integrated systems and synthetic biology. Current challenges and future strategies to further study lignin biodegradation and the trends of lignin valorization are also discussed.

Visualization of Mitochondria During Embryogenesis in Zebrafish by Aggregation-Induced Emission Molecules.

PURPOSE: Aggregation-induced emission (AIE) molecules have been widely utilized for fluorescence imaging in many biomedical applications, benefited from large Stokes shift, high quantum yield, good biocompatibility, and resistance to photobleaching. And visualization of mitochondria is almost investigated in vitro and ex vivo, but in vivo study of mitochondria is more essential for systematic biological research, especially during embryogenesis. Therefore, suitable and time-saving alternatives with simple operation based on AIE molecules are urgently needed compared with traditional transgenic approach. PROCEDURES: Five tetraphenylethylene isoquinolinium (TPE-IQ)-based molecules with AIE characteristics and their ability of mitochondrial visualization in vitro and in vivo and mitochondrial tracking during embryogenesis on zebrafish model were investigated. The biosafety of these AIE molecules was also evaluated systematically in vitro and in vivo. RESULTS: All these five AIE molecules could image mitochondria in vitro with good biocompatibility. In them, TPE-IQ1 exhibited excellent imaging quality for in vivo visualization and tracking of mitochondria during the 4-day embryogenesis in zebrafish, in comparison with the conventional transgenic fluorescent protein. Furthermore, TPE-IQ1 could visualize mitochondrial damage induced by chemicals in real time on 24-h post fertilization (hpf) embryos. CONCLUSIONS: This study indicated TPE-IQ-based AIE molecules had the potential for mitochondrial imaging and tracking during embryogenesis and mitochondrial damage visualization in vivo.