Miniature three-photon microscopy maximized for scattered fluorescence collection.

In deep-tissue multiphoton microscopy, diffusion and scattering of fluorescent photons, rather than ballistic emanation from the focal point, have been a confounding factor. Here we report on a 2.17-g miniature three-photon microscope (m3PM) with a configuration that maximizes fluorescence collection when imaging in highly scattering regimes. We demonstrate its capability by imaging calcium activity throughout the entire cortex and dorsal hippocampal CA1, up to 1.2 mm depth, at a safe laser power. It also enables the detection of sensorimotor behavior-correlated activities of layer 6 neurons in the posterior parietal cortex in freely moving mice during single-pellet reaching tasks. Thus, m3PM-empowered imaging allows the study of neural mechanisms in deep cortex and subcortical structures, like the dorsal hippocampus and dorsal striatum, in freely behaving animals.

Heparin and calreticulin interact on the surface of early G0/G1 dividing rat mesangial cells to regulate hyperglycemic glucose-induced responses.

Heparin can block pathological responses associated with diabetic nephropathy in animal models and human patients. Our previous studies showed that the interaction of heparin on the surface of rat mesangial cells (RMCs) entering G1 of cell division in hyperglycemic glucose: 1) blocked glucose uptake by glucose transporter 4; 2) inhibited cytosolic uridine diphosphate-glucose elevation that would occur within 6 h from G0/G1; and 3) prevented subsequent activation of hyaluronan synthesis in intracellular compartments and subsequent inflammatory responses. However, specific proteins that interact with heparin are unresolved. Here, we showed by live cell imaging that fluorescent heparin was rapidly internalized into the cytoplasm and then into the endoplasmic reticulum, Golgi, and nuclei compartments. Biotinylated-heparin was applied onto the surface of growth arrested G0/G1 RMCs in order to extract heparin-binding protein(s). SDS-PAGE gels showed two bands at ∼70 kDa in the extract that were absent when unlabeled heparin was used to compete. Trypsin digests of the bands were analyzed by MS and identified as calreticulin and prelamin A/C. Immunostaining with their antibodies identified the presence of calreticulin on the G0/G1 RMC cell surface. Previous studies have shown that calreticulin can be on the cell surface and can interact with the LDL receptor-related protein, which has been implicated in glucose transport by interaction with glucose transporter 4. Thus, cell surface calreticulin can act as a heparin receptor through a mechanism involving LRP1, which prevents the intracellular responses in high glucose and reprograms the cells to synthesize an extracellular hyaluronan matrix after division.

Monocyte adhesive hyaluronan matrix induced by hyperglycemia in diabetic lung injuries.

Infiltrated pre-inflammatory monocytes and macrophages have important roles in the induction of diabetic lung injuries, but the mechanism mediating their infiltration is still unclear. Here, we showed that airway smooth muscle cells (SMCs) activated monocyte adhesion in response to hyperglycemic glucose (25.6 mM) by significantly increasing hyaluronan (HA) in the cell matrix, with concurrent 2- to 4-fold increases in adhesion of U937 monocytic-leukemic cells. The HA-based structures were attributed directly to the high-glucose and not to increased extracellular osmolality, and they required growth stimulation of SMCs by serum. Treatment of SMCs with heparin in high-glucose induces synthesis of a much larger HA matrix, consistent with our observations in the glomerular SMCs. Further, we observed increases in tumor necrosis factor-stimulated gene-6 (TSG-6) expression in high-glucose and high-glucose plus heparin cultures, and the heavy chain (HC)-modified HA structures existed on the monocyte-adhesive cable structures in high-glucose and in high-glucose plus heparin-treated SMC cultures. Interestingly, these HC-modified HA structures were unevenly distributed along the HA cables. Further, the in vitro assay with recombinant human TSG-6 and the HA14 oligo showed that heparin has no inhibitory activity on the TSG-6-induced HC-transfer to HA, consistent with the results from SMC cultures. These results support the hypothesis that hyperglycemia in airway smooth muscle induces the synthesis of a HA matrix that recruits inflammatory cells and establishes a chronic inflammatory process and fibrosis that lead to diabetic lung injuries.

Genome-wide identification and integrated analysis of the FAR1/FHY3 gene family and genes expression analysis under methyl jasmonate treatment in Panax ginseng C. A. Mey.

Ginseng (Panax ginseng C. A. Mey.) is an important and valuable medicinal plant species used in traditional Chinese medicine, and its metabolite ginsenoside is the primary active ingredient. The FAR1/FHY3 gene family members play critical roles in plant growth and development as well as participate in a variety of physiological processes, including plant development and signaling of hormones. Studies have indicated that methyl jasmonate treatment of ginseng adventitious roots resulted in a significant increase in the content of protopanaxadiol ginsenosides. Therefore, it is highly significant to screen the FAR1/FHY3 gene family members in ginseng and preliminarily investigate their expression patterns in response to methyl jasmonic acid signaling. In this study, we screened and identified the FAR1/FHY3 family genes in the ginseng transcriptome databases. And then, we analyzed their gene structure and phylogeny, chromosomal localization and expression patterns, and promoter cis-acting elements, and made GO functional annotations on the members of this family. After that, we treated the ginseng adventitious roots with 200 mM methyl jasmonate and investigated the trend of the expression of four genes containing the largest number of methyl jasmonate cis-acting elements at different treatment times. All four genes were able to respond to methyl jasmonate, the most significant change was in the PgFAR40 gene. This study provides data support for subsequent studies of this family member in ginseng and provides experimental reference for subsequent validation of the function of this family member under methyl jasmonic acid signaling.

Miniature two-photon microscopy for enlarged field-of-view, multi-plane and long-term brain imaging.

We have developed a miniature two-photon microscope equipped with an axial scanning mechanism and a long-working-distance miniature objective to enable multi-plane imaging over a volume of 420 × 420 × 180 µm3 at a lateral resolution of ~1 µm. Together with the detachable design that permits long-term recurring imaging, our miniature two-photon microscope can help decipher neuronal mechanisms in freely behaving animals.

Antibiotic resistance and virulence genes in Helicobacter pylori strains isolated from children in Shanghai, China (2019-2022).

BACKGROUND: The increasing prevalence of antibiotic-resistant Helicobacter pylori strains poses a significant threat to children's health. This study investigated antibiotic resistance rates in Helicobacter pylori strains isolated from children in Shanghai and analyzed the presence of virulence genes in these strains. METHODS: We obtained 201 Helicobacter pylori strains from pediatric patients with upper gastrointestinal symptoms who underwent gastrointestinal endoscopy between 2019 and 2022. Subsequently, we performed antibiotic susceptibility tests and virulence gene PCR assays on these strains. RESULTS: Helicobacter pylori resistance rates of 45.8%, 15.4%, 1.0%, and 2.5% were detected for metronidazole, clarithromycin, amoxicillin, and levofloxacin, respectively. Among all isolates, 64.7% exhibited resistance to at least one antibiotic. Resistance to metronidazole and clarithromycin increased from 2019 to 2022. The predominant vacA gene subtype was vacA s1a/m2. The prevalence of vacA m2 and dupA exhibited an upward trend, while oipA presented a decreasing trend from 2019 to 2022. The prevalence of dupA was significantly higher in gastritis than peptic ulcer disease, and in non-treatment compared to treatment groups. CONCLUSIONS: Helicobacter pylori antibiotic resistance remains high in children and has risen in recent years. Therefore, the increasing use of metronidazole and clarithromycin requires increased monitoring in children. No association was observed between antibiotic resistance and virulence gene phenotypes.

MEMS-based two-photon microscopy with Lissajous scanning and image reconstruction under a feed-forward control strategy.

Two-photon microscopy (TPM) based on two-dimensional micro-electro-mechanical (MEMS) system mirrors shows promising applications in biomedicine and the life sciences. To improve the imaging quality and real-time performance of TPM, this paper proposes Lissajous scanning control and image reconstruction under a feed-forward control strategy, a dual-parameter alternating drive control algorithm and segmented phase synchronization mechanism, and pipe-lined fusion-mean filtering and median filtering to suppress image noise. A 10 fps frame rate (512 × 512 pixels), a 140 µm × 140 µm field of view, and a 0.62 µm lateral resolution were achieved. The imaging capability of MEMS-based Lissajous scanning TPM was verified by ex vivo and in vivo biological tissue imaging.

Effects of replacing fishmeal with soybean meal on the immune and antioxidant capacity, and intestinal metabolic functions of red swamp crayfish Procambarus clarkii.

Excess utilization of plant protein sources in animal feed has been found to adversely affect the antioxidant properties and immunity of animals. While the role of gut microbes in plant protein-induced inflammation has been identified in various models, the specific mechanisms regulating gut microbes in crustaceans remain unclear. Accordingly, this study was designed to investigate the effects of replacing fishmeal with soybean meal (SM) on the hepatopancreas antioxidant and immune capacities, and gut microbial functions of crayfish, as well as the potential microbial regulatory mechanisms. 750 crayfish (4.00 g) were randomly divided into five groups: SS0, SS25, SS50, SS75, and SS100, and fed diets with different levels of soybean meal substituted for fishmeal for six weeks. High SM supplementation proved detrimental to maintaining hepatopancreas health, as indicated by an increase in hemolymph MDA content, GPT, and GOT activities, the observed rupture of hepatopancreas cell basement membranes, along with the decreased number of hepatopancreatic F cells. Moreover, crayfish subjected to high SM diets experienced obvious inflammation in hepatopancreas, together with up-regulated mRNA expression levels of nfkb, alf, and tlr (p<0.05), whereas the lzm mRNA expression level exhibited the highest value in the SS25 group. Furthermore, hepatopancreas antioxidant properties highly attenuated by the level of dietary SM substitution levels, as evidenced by the observed increase in MDA content (p<0.05), decrease in GSH content (p<0.05), and inhabitation of SOD, CAT, GPx, and GST activities (p<0.05), along with down-regulated hepatopancreas cat, gpx, gst, and mmnsod mRNA expression levels via inhibiting nrf2/keap1 pathway. Functional genes contributing to metabolism identified that high SM diets feeding significantly activated lipopolysaccharide biosynthesis, revealing gut dysfunction acted as the cause of inflammation. The global microbial co-occurrence network further indicated that the microbes contributing more to serum indicators and immunity were in module eigengene 17 (ME17). A structural equation model revealed that the genes related to alf directly drove the serum enzyme activities through microbes in ME17, with OTU399 and OTU533 identified as major biomarkers and classified into Proteobacteria that secrete endotoxins. To conclude, SM could replace 25 % of fishmeal in crayfish diets without negatively affecting immunity, and antioxidant capacity. Excessive SM levels contributed to gut dysfunction and weakened the innate immune system of crayfish.

New Insights for Biosensing: Lessons from Microbial Defense Systems.

Microorganisms have gained defense systems during the lengthy process of evolution over millions of years. Such defense systems can protect them from being attacked by invading species (e.g., CRISPR-Cas for establishing adaptive immune systems and nanopore-forming toxins as virulence factors) or enable them to adapt to different conditions (e.g., gas vesicles for achieving buoyancy control). These microorganism defense systems (MDS) have inspired the development of biosensors that have received much attention in a wide range of fields including life science research, food safety, and medical diagnosis. This Review comprehensively analyzes biosensing platforms originating from MDS for sensing and imaging biological analytes. We first describe a basic overview of MDS and MDS-inspired biosensing platforms (e.g., CRISPR-Cas systems, nanopore-forming proteins, and gas vesicles), followed by a critical discussion of their functions and properties. We then discuss several transduction mechanisms (optical, acoustic, magnetic, and electrical) involved in MDS-inspired biosensing. We further detail the applications of the MDS-inspired biosensors to detect a variety of analytes (nucleic acids, peptides, proteins, pathogens, cells, small molecules, and metal ions). In the end, we propose the key challenges and future perspectives in seeking new and improved MDS tools that can potentially lead to breakthrough discoveries in developing a new generation of biosensors with a combination of low cost; high sensitivity, accuracy, and precision; and fast detection. Overall, this Review gives a historical review of MDS, elucidates the principles of emulating MDS to develop biosensors, and analyzes the recent advancements, current challenges, and future trends in this field. It provides a unique critical analysis of emulating MDS to develop robust biosensors and discusses the design of such biosensors using elements found in MDS, showing that emulating MDS is a promising approach to conceptually advancing the design of biosensors.

Integrated spatial metabolomics and network pharmacology to explore the pharmacodynamic substances and mechanism of Radix ginseng-Schisandra chinensis Herb Couple on Alzheimer's disease.

Radix ginseng and Schisandra chinensis have been extensively documented in traditional Chinese medicine (TCM) for their potential efficacy in treating dementia. However, the precise mechanism of their therapeutic effects remains to be fully elucidated. In this study, air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and network pharmacology are used to investigate the pharmacodynamics and mechanism underlying the herbal combination consisting of Radix ginseng-Schisandra chinensis (RS) in a rodent model for Alzheimer's disease (AD). Brain histopathological findings suggested that RS attenuates hippocampal damage in AD mice, making this combination a potential AD treatment. Twenty-eight biomarkers were identified by spatial metabolomics analysis, which are intricately linked to neuroinflammation, neurotransmitter imbalance, energy deficiency, oxidative stress, and aberrant fatty acid metabolism in AD. The total extract of RS (TE) affected 22 of these biomarkers, with the small molecule components of RS (SN) significantly influencing 19 and the large molecule components of RS (PR) impacting 14. Nine small molecule components are likely to dominate the pharmacodynamics of RS. We constructed a target interaction network based on the corresponding bioactivities that revealed relationships amongst 11 key biomarkers, 8 active ingredients and 12 critical targets. This research illustrates the immense potential of spatial metabolomics and network pharmacology in the study of TCM, revealing the targets and mechanisms underlying herbal formulas.

Activated carbon fiber as an efficient co-catalyst toward accelerating Fe2+/Fe3+ cycling for improved removal of antibiotic cefaclor via electro-Fenton process using a gas diffusion electrode.

The electro-Fenton (EF) based on gas-diffusion electrodes (GDEs) reveals promising application prospective towards recalcitrant organics degradation because such GDEs often yields superior H2O2 generation efficiency and selectivity. However, the low efficiency of Fe2+/Fe3+ cycle with GDEs is always considered to be the limiting step for the EF process. In this study, activated carbon fiber (ACF) was firstly employed as co-catalyst to facilitate the performance of antibiotic cefaclor (CEC) decomposition in EF process. It was found that the addition of ACF co-catalyst achieved a rapid Fe2+/Fe3+ cycling, which significantly enhanced Fenton's reaction and hydroxyl radicals (•OH) generation. X-ray photoelectron spectroscopy (XPS) results indicated that the functional groups on ACF surface are related to the conversion of Fe3+ into Fe2+. Moreover, DMSO probing experiment confirmed the enhanced •OH production in EF + ACF system compared to conventional EF system. When inactive BDD and Ti4O7/Ti anodes were paired to EF system, the addition of ACF could significantly improve mineralization degree. However, a large amount of toxic byproducts, including chlorate (ClO3-) and perchlorate (ClO4-), were generated in these EF processes, especially for BDD anode, due to their robust oxidation capacity. Higher mineralization efficiency and less toxic ClO4- generation were obtained in the EF + ACF process with Ti4O7/Ti anode. This presents a novel alternative for efficient chloride-containing organic removal during wastewater remediation.

Insights into the efficient mineralization of antibiotic trimethoprim in aqueous media by Fe2+ catalytically enhanced vacuum-UV irradiation: Kinetics, mechanisms, and toxicity evaluation.

The widespread existence of antibiotics in the environment has attracted growing concerns regarding the potential adverse effects on aquatic organisms, ecosystems, and human health even at low concentrations. Extensive efforts have been devoted to developing new methods for effective elimination of antibiotics from wastewater. Herein, a novel process of Fe2+ catalytically enhanced vacuum ultraviolet (VUV) irradiation was proposed as a promising approach for the removal of antibiotic trimethoprim (TMP) in water. Compared with UVC photolysis, VUV photolysis, and UVC/Fe2+, VUV/Fe2+ could increase the pseudo-first-order reaction rate constant of TMP removal by 6.6-38.4 times and the mineralization rate by 36.5%-59.9%. The excellent performance might originate from the synergistic effect of VUV and Fe2+, i.e., VUV irradiation could effectively split water and largely accelerate the Fe3+/Fe2+ cycle to generate more reactive oxygen species (ROS). EPR results indicated that •OH and O2•- were identified as the main ROS in the UVC/Fe2+ and VUV/Fe2+ processes, while •OH, O2•-, and 1O2 were involved in the VUV process. The operating parameters, such as Fe2+ dosage and initial TMP contents, were evaluated and optimized. Up to 8 aromatic intermediates derived from hydroxylation, demethylation, carbonylation, and methylene group cleavage were identified by UPLC-QTOF-MS/MS technique, the possible pathways of TMP degradation were proposed. Finally, the acute and chronic toxicity of intermediates formed during TMP degradation in the VUV/Fe2+ process were also evaluated.

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD. METHODS: A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model. RESULTS: Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables. CONCLUSIONS: Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

Mortality Study of Patients with Omicron Infection Before and After the Implementation of the New Crown Standard.

Objective: To investigate the mortality rate of patients with Omicron infection before and after the implementation of the new crown standard, and to evaluate the impact of new treatment protocols on the mortality rate of patients with Omicron infection. Methods: Clinical data of 1419 Omicron-infected patients treated in our hospital from April 10, 2022 to June 3, 2022 were collected(Patients diagnosed with Omicron infection who met the diagnostic criteria in the "Diagnosis and treatment protocol for novel coronavirus pneumonia (trial version 9)"15 and whose nasal/pharyngeal swab samples were typed as Omicron variants by laboratory viral genotyping). They were divided into the observation group (April 25 2022 - June 3 2022) and the control group (April 10 2022 - April 24 2022) before and after the implementation criteria. Clinical data of 1419 patients were collected and compared between the two groups on whether to use anticoagulant drugs, whether to use antiplatelet drugs, gender, whether to use new drugs of thymosin/thymus method, age, whether to use herbal medicine, whether to use Fuzheng prescription, blood routine, liver function, kidney function indicators, mortality of patients. Results: A total of 1419 patients were initially selected; 501 patients with incomplete information were excluded, and finally, 918 patients were included. According to the time period before and after the application criteria, they were divided into an observation group (586 cases) and a control group (332 cases). There were no statistically significant differences in gender, age, antiplatelet drug use, and herbal medicine use between the two groups (P < .05). However, there were significant differences in the use of anticoagulant drugs, thymidine/thymidine drugs, and Fu Zhengfang between the two groups. It was statistically significant that the mortality rate in the observation group (2.39)% was significantly lower than that in the control group (5.12)%. P < .05 White blood cell count, red blood cell ratio, lymphocyte count, hemoglobin, neutrophil count, and neutrophil ratio were not significantly different between the two groups (P < .05) .In comparison to the control group (4.92±8.00)10^9/L, the platelet count in the observation group (4.77±3.41)109/L was considerably lower. The difference was statistically significant (P < .05). The comparison of total bilirubin, total protein values and alkaline phosphatase values between the two groups was not significant (P < .05). In the observation group, albumin (38.71±6.39) g/L, glutamate transaminase (23.93±26.03) U/L, glutathione transaminase (26.12±25.53) U/L, gamma-glutamyltransferase (34.28±52.3) U/L, globulin values (28.13±5.55) g/L were significantly lower than those of the control group (36.66±7.08) g/L, (30.36±65.77) U/L, (33.29±49.72) U/L, (43.76±80.23) U/L, (29.85±5.67) g/L, the difference was statistically significant (P < .05). Between the two groups, there were no significant differences in the values of uric acid or creatinine (P > .05). Levels and uric acid readings did not differ significantly, P > .05. The difference between the urea values of the observation group (7.44±6.34 mmol/L) and the control group (8.75±7.51 mmol/L) was statistically significant (P < .05). Conclusion: After the implementation of the treatment protocol for COVID-19 (Trial Version 9), the number of death cases among patients with Omicron variant infection has significantly decreased. The treatment protocol is safe and feasible and can be widely applied in clinical settings..And it will further promote the development and administration of vaccines to prevent and control the spread of the novel coronavirus, reducing the occurrence of patients and death cases.

Machine Tool Wear Prediction Technology Based on Multi-Sensor Information Fusion.

The intelligent monitoring of cutting tools used in the manufacturing industry is steadily becoming more convenient. To accurately predict the state of tools and tool breakages, this study proposes a tool wear prediction technique based on multi-sensor information fusion. First, the vibrational, current, and cutting force signals transmitted during the machining process were collected, and the features were extracted. Next, the Kalman filtering algorithm was used for feature fusion, and a predictive model for tool wear was constructed by combining the ResNet and long short-term memory (LSTM) models (called ResNet-LSTM). Experimental data for thin-walled parts obtained under various machining conditions were utilized to monitor the changes in tool conditions. A comparison between the ResNet and LSTM tool wear prediction models indicated that the proposed ResNet-LSTM model significantly improved the prediction accuracy compared to the individual LSTM and ResNet models. Moreover, ResNet-LSTM exhibited adaptive noise reduction capabilities at the front end of the network for signal feature extraction, thereby enhancing the signal feature extraction capability. The ResNet-LSTM model yielded an average prediction error of 0.0085 mm and a tool wear prediction accuracy of 98.25%. These results validate the feasibility of the tool wear prediction method proposed in this study.

Adaptive Optimization Method for Prediction and Compensation of Thin-Walled Parts Machining Deformation Based on On-Machine Measurement.

Thin-walled aluminum alloy parts are widely used in the aerospace field because of their favorable characteristics that cater to various applications. However, they are easily deformed during milling, leading to a low pass rate of workpieces. On the basis of on-machine measurement (OMM) and surrogate stiffness models (SSMs), we developed an iterative optimization compensation method in this study to overcome the machining deformation of thin-walled parts. In the error compensation process, the time-varying factors of workpiece stiffness and the impact of prediction model errors were considered. First, we performed machining deformation simulation and information extraction on the key nodes of the machined surface, and an SSM containing the stiffness information of discrete nodes of each cutting layer was established. Subsequently, the machining errors were monitored through intermittent OMM to suppress the adverse impact of prediction model errors. Further, an interlayer correction coefficient was introduced in the compensation process to iteratively correct the prediction model error of each node in the SSM along the depth direction, and a correction coefficient between parts was introduced to realize the iterative correction of the prediction model for the same node position between different parts. Finally, the feasibility of the proposed method was verified through multiple sets of actual machining experiments on thin-walled parts with added pads.

Miniature Two-Photon Microscopic Imaging Using Dielectric Metalens.

Miniature two-photon microscopy has emerged as a powerful technique for investigating brain activity in freely moving animals. Ongoing research objectives include reducing probe weight and minimizing animal behavior constraints caused by probe attachment. Employing dielectric metalenses, which enable the use of sizable optical components in flat device structures while maintaining imaging resolution, is a promising solution for addressing these challenges. In this study, we designed and fabricated a titanium dioxide metalens with a wavelength of 920 nm and a high aspect ratio. Furthermore, a meta-optic two-photon microscope weighing 1.36 g was developed. This meta-optic probe has a lateral resolution of 0.92 µm and an axial resolution of 18.08 µm. Experimentally, two-photon imaging of mouse brain structures in vivo was also demonstrated. The flat dielectric metalens technique holds promising opportunities for high-performance integrated miniature nonlinear microscopy and endomicroscopy platforms in the biomedical field.

Screening of key immune-related gene in Parkinson's disease based on WGCNA and machine learning. / 基于WGCNAå’Œæœºå™¨å­¦ä¹ ç­›é€‰å¸•é‡‘æ£®ç— å ç–«ç›¸å ³å ³é”®åŸºå› .

OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning. METHODS: This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. RESULTS: A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation. CONCLUSIONS: This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals.

Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.

Millimeter field-of-view miniature two-photon microscopy for brain imaging in freely moving mice.

Development of miniature two-photon microscopy (m2PM) has made it possible to observe fine structure and activity of neurons in the brain of freely moving animals. However, the imaging field-of-view of existing m2PM is still significantly smaller than that of miniature single-photon microscopy. Here we report that, through the design of low-magnification objective, large field-of-view scan lens and small tilt angle microscanner, a 2.5-g m2PM achieved a field-of-view of 1000 × 788 µm2, comparable to that of a typical single-photon miniscope. We demonstrated its capability by imaging neurons, dendrites and spines in the millimeter field-of-view, and simultaneous recording calcium activities, through a gradient-index lens, of approximately 400 neurons in the dorsal hippocampal CA1 in a freely moving mouse. Integrated with a detachable 1.2-g fast z-scanning module, it enables a 1000 × 788 × 500 µm3 volumetric neuronal imaging in the cerebral cortex. Thus, millimeter FOV m2PM provides a powerful tool for deciphering neuronal population dynamics in experimental paradigms allowing for animal's free movement.