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Abstract The Claustrum/dorsal endopiriform cortex complex (CLA) is an enigmatic brain region with extensive glutamatergic projections to multiple cortical areas. The transcription factor Nurr1 is highly expressed in the CLA, but its role in this region is not understood. By using conditional gene-targeted mice, we show that Nurr1 is a crucial regulator of CLA neuron identity. Although CLA neurons remain intact in the absence of Nurr1, the distinctive gene expression pattern in the CLA is abolished. CLA has been hypothesized to control hallucinations, but little is known of how the CLA responds to hallucinogens. After the deletion of Nurr1 in the CLA, both hallucinogen receptor expression and signaling are lost. Furthermore, functional ultrasound and Neuropixel electrophysiological recordings revealed that the hallucinogenic-receptor agonists’ effects on functional connectivity between prefrontal and sensorimotor cortices are altered in Nurr1-ablated mice. Our findings suggest that Nurr1-targeted strategies provide additional avenues for functional studies of the CLA.

Abstract Mutations in the α-Synuclein (αS) gene promote αS monomer aggregation that causes neurodegeneration in familial Parkinson’s disease (fPD). However, most mouse models expressing single-mutant αS transgenes develop neuronal aggregates very slowly, and few have dopaminergic cell loss, both key characteristics of PD. To accelerate neurotoxic aggregation, we previously generated fPD αS E46K mutant mice with rationally designed triple mutations based on the α-helical repeat motif structure of αS (fPD E46K→3 K). The 3 K variant increased αS membrane association and decreased the physiological tetramer:monomer ratio, causing lipid- and vesicle-rich inclusions and robust tremor-predominant, L-DOPA responsive PD-like phenotypes. Here, we applied an analogous approach to the G51D fPD mutation and its rational amplification (G51D → 3D) to generate mutant mice. In contrast to 3 K mice, G51D and 3D mice accumulate monomers almost exclusively in the cytosol while also showing decreased αS tetramer:monomer ratios. Both 1D and 3D mutant mice gradually accumulate insoluble, higher-molecular weight αS oligomers. Round αS neuronal deposits at 12 mos immunolabel for ubiquitin and pSer129 αS, with limited proteinase K resistance. Both 1D and 3D mice undergo loss of striatal TH+ fibers and midbrain dopaminergic neurons by 12 mos and a bradykinesia responsive to L-DOPA. The 3D αS mice have decreased tetramer:monomer equilibria and recapitulate major features of PD. These fPD G51D and 3D mutant mice should be useful models to study neuronal αS-toxicity associated with bradykinetic motor phenotypes.

Abstract Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time interventional MRI (i-MRI). Here, we proposed a deep unrolled neural network, dubbed as LSFP-Net, for real-time i-MRI reconstruction. By integrating LSFP-Net and a custom-designed, MR-compatible interventional device into a 3 T MRI scanner, a real-time MRI-guided brain intervention system is proposed. The performance of the system was evaluated using phantom and cadaver studies. 2D/3D real-time i-MRI was achieved with temporal resolutions of 80/732.8 ms, latencies of 0.4/3.66 s including data communication, processing and reconstruction time, and in-plane spatial resolution of 1 × 1 mm2. The results demonstrated that the proposed method enables real-time monitoring of the remote-controlled brain intervention, and showed the potential to be readily integrated into diagnostic scanners for image-guided neurosurgery.

Abstract Prosaposin (PSAP) modulates glycosphingolipid metabolism and variants have been linked to Parkinson’s disease (PD). Here, we find altered PSAP levels in the plasma, CSF and post-mortem brain of PD patients. Altered plasma and CSF PSAP levels correlate with PD-related motor impairments. Dopaminergic PSAP-deficient (cPSAPDAT) mice display hypolocomotion and depression/anxiety-like symptoms with mildly impaired dopaminergic neurotransmission, while serotonergic PSAP-deficient (cPSAPSERT) mice behave normally. Spatial lipidomics revealed an accumulation of highly unsaturated and shortened lipids and reduction of sphingolipids throughout the brains of cPSAPDAT mice. The overexpression of α-synuclein via AAV lead to more severe dopaminergic degeneration and higher p-Ser129 α-synuclein levels in cPSAPDAT mice compared to WT mice. Overexpression of PSAP via AAV and encapsulated cell biodelivery protected against 6-OHDA and α-synuclein toxicity in wild-type rodents. Thus, these findings suggest PSAP may maintain dopaminergic lipid homeostasis, which is dysregulated in PD, and counteract experimental parkinsonism.

Background: Early screening of prostate cancer (PCa) is pivotal but challenging in the clinical scenario due to the phenomena of false positivity or false negativity of some serological evaluations, e.g. PSA testing. Decline of serum Zn2+ levels in PCa patients reportedly plays a crucial role in early screening of PCa. Accordingly, we combined 4 indices comprising the serum levels of total PSA (tPSA), free PSA (fPSA), Zn2+ and demographic information (especially age) in order to ameliorate the efficacies of PCa screening with support vector machine (SVM) algorithms. Methods: A total of 858 male patients with prostate disorders and 345 healthy male controls were enrolled. Patients’ data included 4 variables and serum Zn2+ was quantified via a self-invented Zn2+ responsive AIE-based fluorescent probe as previously published. tPSA and fPSA were routinely determined by a chemiluminescent method. Mathematical simulations were conducted to establish a SVM model for the combined diagnostics with the four variables. Moreover, ROC and its characteristic AUC were also employed to evaluate the classification efficacy of the model. Sigmoid function was utilized to estimate corresponding probabilities of classifying the clinical subjects as per 5 grades, which were incorporated into our established prostate index (PI) stratification system. Results: In SVM model, the mean AUC of the ROC with the quartet of variables was approximately 84% for PCa diagnosis, whereas the mean AUC of the ROCs with tPSA, fPSA, [Zn2+] or age alone was 64%, 62%, 55% and 59%, respectively. We further established an integrated prostate index (PI) stratification system with 5 grades and a software package to support clinicians in predicting PCa, with the accuracy of our risk stratification system being 83.3%, 91.6% and 83.3% in predicting normal, benign and PCa cases in corresponding groups. Follow-up findings especially MRI results and PI-RADS scores supported the reliability of this stratification platform as well. Conclusion: Findings from our present study demonstrated that index combination via SVM algorithms may well facilitate clinicians in early differential screening of PCa. Meanwhile, our established PI stratification system based on SVM model and Sigmoid function provided substantial accuracy in preclinical risk prediction of developing prostate cancer.

Abstract In Parkinson’s disease (PD), axons of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNc) degenerate before their cell bodies. Calcium influx during pacemaker firing might contribute to neuronal loss, but it is not known if dysfunctions of voltage-gated calcium channels (VGCCs) occur in DA neurons somata and axon terminals. We investigated T-type and L-type VGCCs in SNc-DA neurons of two mouse models of PD: mice with a deletion of the Nurr1 gene in DA neurons from an adult age (cNurr1 mice), and mice bearing the G2019S mutation in the gene coding for LRRK2 (G2019S mice). Adult cNurr1 mice displayed motor and DA deficits, while middle-aged G2019S mice did not. The number and morphology of SNc-DA neurons, most of their intrinsic membrane properties and pacemaker firing were unaltered in cNurr1 and G2019S mice compared to their control and wild-type littermates. L-type VGCCs contributed to the pacemaker firing of SNc-DA neurons in G2019S mice, but not in control, wild-type, and cNurr1 mice. In cNurr1 mice, but not G2019S mice, the contribution of T-type VGCCs to the pacemaker firing of SNc-DA neurons was reduced, and somatic dopamine-D2 autoreceptors desensitized more. Altered contribution of L-type and T-type VGCCs to the pacemaker firing was not observed in the presence of a LRRK2 kinase inhibitor in G2019S mice, and in the presence of a flavonoid with antioxidant activity in G2019S and cNurr1 mice. The role of L-type and T-type VGCCs in controlling dopamine release from axon terminals in the striatum was unaltered in cNurr1 and G2019S mice. Our findings uncover opposite changes, linked to oxidative stress, in the function of two VGCCs in DA neurons somata, but not axon terminals, in two different experimental PD models.

The escalating prevalence of microplastics and nanoplastics in aquatic environments is a major challenge affecting the behavior and reproductive health of aquatic organisms while posing potential risks to human health and ecosystems. This review focuses on the neurobehavioral changes and reproductive toxicity of MNPs in zebrafish and their relationships. At the same time, the neurobehavioral changes caused by MNPs were studied, and the synergistic effects of the interaction of these pollutants with other environmental contaminants were explored. In addition, zebrafish, as a model organism, provide valuable insights into the subtle but important effects of MNPs on reproductive behavior, which is critical for understanding reproductive success, suggesting that behavioral changes can serve as an early biomarker of reproductive toxicity. In addition, based on classical endocrine disruptor models and behavioral research methods, the current status of the research on the reproductive toxicity of MNPs in zebrafish was reviewed, which further indicated that the behavioral parameters of zebrafish can be used as an effective and rapid tool to evaluate the reproductive toxicity of MNPs. However, behavioral methods for rapidly assessing the toxicity of MNPs are still an area of exploration. To address limitations and challenges in the current scope of research, this review outlines future research directions with the aim of improving our understanding of the environmental and health impacts of MNPs. This work aims to inform targeted environmental policies and advance public health strategies to address the growing challenge of MNPs pollution.

Mutations in the GBA1 gene increase the risk of developing Parkinson’s disease (PD). However, most carriers of GBA1 mutations do not develop PD throughout their lives. The mechanisms of how GBA1 mutations contribute to PD pathogenesis remain unclear. Cerebrospinal fluid (CSF) is used for detecting pathological conditions of diseases, providing insights into the molecular mechanisms underlying neurodegenerative disorders. In this study, we utilized the proximity extension assay to examine the levels of metabolism-linked protein in the CSF from 17 PD patients carrying GBA1 mutations (GBA1-PD) and 17 idiopathic PD (iPD). The analysis of CSF secretome in GBA1-PD identified 11 significantly altered proteins, namely FKBP4, THOP1, GLRX, TXNDC5, GAL, SEMA3F, CRKL, APLP1, LRP11, CD164, and NPTXR. To investigate GBA1-associated CSF changes attributed to specific neuronal subtypes responsible for PD, we analyzed the cell culture supernatant from GBA1-PD-induced pluripotent stem cell (iPSC)-derived midbrain dopaminergic (mDA) neurons. The secretome analysis of GBA1-PD iPSC-derived mDA neurons revealed that five differently regulated proteins overlapped with those identified in the CSF analysis: FKBP4, THOP1, GLRX, GAL, and CRKL. Reduced intracellular level of the top hit, FKPB4, was confirmed via Western Blot. In conclusion, our findings identify significantly altered CSF GBA1-PD-associated proteins with FKPB4 being firmly attributed to mDA neurons.

GPR37L1 is an orphan G-protein-coupled receptor, which is implicated in neurological disorders, but its normal physiological role is poorly understood. Its close homologue, GPR37, is implicated in Parkinson’s disease and affective disorders. In this study, we set out to characterize adult and middle-aged global GPR37L1 knock-out (KO) mice regarding emotional behaviors. Our results showed that GPR37L1KO animals, except adult GPR37L1KO males, exhibited impaired retention of aversive memory formation as assessed by the shorter retention latency in a passive avoidance task. Interestingly, the viral-mediated deletion of GPR37L1 in conditional knockout mice in the hippocampus of middle-aged mice also showed impaired retention in passive avoidance tasks, similar to what was observed in global GPR37L1KO mice, suggesting that hippocampal GPR37L1 is involved in aversive learning processes. We also observed that middle-aged GPR37L1KO male and female mice exhibited a higher body weight than their wild-type counterparts. Adult and middle-aged GPR37L1KO female mice exhibited a reduced level of serum corticosterone and middle-aged GPR37L1KO females showed a reduced level of epinephrine in the dorsal hippocampus in the aftermath of passive avoidance task, with no such effects observed in GPR37L1KO male mice, suggesting that lack of GPR37L1 influences behavior and biochemical readouts in age- and sex-specific manners.

Prosaposin (PSAP) and progranulin (PGRN) are two lysosomal proteins that interact and modulate the metabolism of lipids, particularly sphingolipids. Alterations in sphingolipid metabolism have been found in schizophrenia. Genetic associations of PSAP and PGRN with schizophrenia have been reported. To further clarify the role of PSAP and PGRN in schizophrenia, we examined PSAP and PGRN levels in postmortem cingulate cortex tissue from healthy controls along with patients who had suffered from schizophrenia, bipolar disorder, or major depressive disorder. We found that PSAP and PGRN levels are reduced specifically in schizophrenia patients. To understand the role of PSAP in the cingulate cortex, we used an AAV strategy to knock down PSAP in neurons located in this region. Neuronal PSAP knockdown led to the downregulation of neuronal PGRN levels and behavioral abnormalities. Cingulate-PSAP-deficient mice exhibited increased anxiety-like behavior and impaired prepulse inhibition, as well as intact locomotion, working memory, and a depression-like state. The behavioral changes were accompanied by increased early growth response protein 1 (EGR-1) and activity-dependent cytoskeleton-associated protein (ARC) levels in the sensorimotor cortex and hippocampus, regions implicated in circuitry dysfunction in schizophrenia. In conclusion, PSAP and PGRN downregulation in the cingulate cortex is associated with schizophrenia pathophysiology.

In order to understand the difference in muscle nutritional quality between yellow catfish (Pelteobagrus fulvidraco) cultured in in-pond raceway systems (IPR) and traditional ponds (TRP), two modes were used to culture the yellow catfish with the same initial body weight [average body weight (15.69 1 ± 2.28) g] for 60 days. The growth index, muscle texture characteristics, muscle nutritional components, amino acids and fatty acids of the fish were measured after the culture experiment. The results showed that the weight gain rate, specific growth rate and survival rate of IPR were significantly higher than TRP (p < 0.05). The hardness, elasticity, chewiness and resilience of the yellow catfish cultured in IPR were significantly higher than those cultured in TRP (p < 0.05). The crude protein content in the muscle of the yellow catfish cultured in IPR was significantly higher than that cultured in TRP (p < 0.01), while the content of crude fat and water was significantly lower (p < 0.01). The total amount of amino acids, essential amino acids and flavor amino acids of IPR were significantly higher than TRP (p < 0.01). The percentages of saturated fatty acids in muscle of the yellow catfish cultured in IPR and TRP were 3.59% and 3.83%, respectively, and the percentages of unsaturated fatty acids were 96.41% and 96.17%, respectively. It was concluded that the nutritional quality of yellow catfish cultured in IPR was better than that of fish cultured in TRP.

GPR37 is an orphan G-protein-coupled receptor, a substrate of parkin which is linked to Parkinson’s disease (PD) and affective disorders. In this study, we sought to address the effects of early life stress (ELS) by employing the paradigm of limited nesting material on emotional behaviors in adult GPR37 knockout (KO) mice. Our results showed that, while there was an adverse effect of ELS on various domains of emotional behaviors in wild type (WT) mice in a sex specific manner (anxiety in females, depression and context-dependent fear memory in males), GPR37KO mice subjected to ELS exhibited less deteriorated emotional behaviors. GPR37KO female mice under ELS conditions displayed reduced anxiety compared to WT mice. This was paralleled by lower plasma corticosterone in GPR37KO females and a lower increase in P-T286-CaMKII by ELS in the amygdala. GPR37KO male mice, under ELS conditions, showed better retention of hippocampal-dependent emotional processing in the passive avoidance behavioral task. GPR37KO male mice showed increased immobility in the forced swim task and increased P-T286-CaMKII in the ventral hippocampus under baseline conditions. Taken together, our data showed overall long-term effects of ELS—deleterious or beneficial depending on the genotype, sex of the mice and the emotional context.

Bayesian methods for solving inverse problems are a powerful alternative to classical methods since the Bayesian approach offers the ability to quantify the uncertainty in the solution. In recent years, data-driven techniques for solving inverse problems have also been remarkably successful, due to their superior representation ability. In this work, we incorporate data-based models into a class of Langevin-based sampling algorithms for Bayesian inference in imaging inverse problems. In particular, we introduce NF-ULA (normalizing flow-based unadjusted Langevin algorithm), which involves learning a normalizing flow (NF) as the image prior. We use NF to learn the prior because a tractable closed-form expression for the log prior enables the differentiation of it using autograd libraries. Our algorithm only requires a normalizing flow-based generative network, which can be pretrained independently of the considered inverse problem and the forward operator. We perform theoretical analysis by investigating the well-posedness and nonasymptotic convergence of the resulting NF-ULA algorithm. The efficacy of the proposed NF-ULA algorithm is demonstrated in various image restoration problems such as image deblurring, image inpainting, and limited-angle X-ray computed tomography reconstruction. NF-ULA is found to perform better than competing methods for severely ill-posed inverse problems. [ABSTRACT FROM AUTHOR]

We consider a Beckmann formulation of an unbalanced optimal transport (UOT) problem. The\Gamma -convergence of this formulation of UOT to the corresponding optimal transport (OT) problem is established as the balancing parameter\alpha goes to infinity. The discretization of the problem is further shown to be asymptotic preserving regarding the same limit, which ensures that a numerical method can be applied uniformly and the solutions converge to the one of the OT problem automatically. Particularly, there exists a critical value, which is independent of the mesh size, such that the discrete problem reduces to the discrete OT problem for\alpha being larger than this critical value. The discrete problem is solved by a convergent primal-dual hybrid algorithm and the iterates for UOT are also shown to converge to that for OT. Finally, numerical experiments on shape deformation and partial color transfer are implemented to validate the theoretical convergence and the proposed numerical algorithm. [ABSTRACT FROM AUTHOR]

Deep neural network (DNN) has been attracting a great attention in various applications. Network training algorithms play essential roles for the effectiveness of DNN. Although stochastic gradient descent (SGD) and other explicit gradient-based methods are the most popular algorithms, there are still many challenges such as gradient vanishing and explosion occurring in training a complex and deep neural networks. Motivated by the idea of error back propagation (BP) and proximal point methods (PPM), we propose a semi-implicit back propagation method for neural network training. Similar to the BP, the update on the neurons are propagated in a backward fashion and the parameters are optimized with proximal mapping. The implicit update for both hidden neurons and parameters allows to choose large step size in the training algorithm. Theoretically, we demonstrate the convergence of the proposed method under some standard assumptions. The experiments on illustrative examples, and two real data sets: MNIST and CIFAR-10, demonstrate that the proposed semi-implicit BP algorithm leads to better performance in terms of both loss decreasing and training/test accuracy, with a detail comparison to SGD/Adam and a similar algorithm proximal back propagation (ProxBP). [ABSTRACT FROM AUTHOR]