Engineering a cell-free biosensor signal amplification circuit with polymerase strand recycling.

Cell-free systems are powerful synthetic biology technologies because of their ability to recapitulate sensing and gene expression without the complications of living cells. Cell-free systems can perform even more advanced functions when genetic circuits are incorporated as information processing components. Here we expand cell-free biosensing by engineering a highly specific isothermal signal amplification circuit called polymerase strand recycling (PSR) that leverages T7 RNA polymerase off-target transcription to recycle nucleic acid inputs within DNA strand displacement circuits. We develop design rules for PSR circuit components and use these rules to construct modular biosensors that can directly sense different RNA targets with limits of detection in the nM range and high specificity. We then use PSR for signal amplification within allosteric transcription factor-based biosensors for small molecule detection. We use a double equilibrium model of transcription factor:DNA and transcription factor:ligand binding interactions to predict biosensor sensitivity enhancement by PSR, and then demonstrate this approach experimentally by achieving 3.6-4.6-fold decreases in biosensor EC50 to sub micromolar ranges. We believe this work expands the current capabilities of cell-free circuits by incorporating PSR, which we anticipate will have a wide range of uses within biotechnology.

Mild and Efficient Preparation of N-Heterocyclic Organic Molecules by Catalyst-free and Solvent-free Methods.

AIMS: The small organic molecular compounds with biological activity containing C-C and C-N or C-O bonding were efficiently prepared without catalyst and solvent in the hydrothermal synthesis reactor. OBJECTIVES: Our goal was to explore new applications for the more environmentally friendly and efficient synthesis of bis(indolyl)methyl, xanthene, quinazolinone, and N-heterocyclic derivatives in hydrothermal synthesis reactors under solvent-free and catalyst-free conditions. METHODS: A greener and more efficient method was successfully developed for the synthesis of bis(indolyl)methyl, heteroanthracene, quinazolinone, and N-heterocyclic derivatives using a hydrothermal synthesis reactor in a solvent- and catalyst-free manner. RESULTS: In a hydrothermal synthesis reactor, bis(indoyl)methyl, xanthene, quinazolinone, and N-heterocyclic derivatives were synthesized without catalysts and solvents. CONCLUSION: Overall, it is proved once again that the catalyst-free and solvent-free synthesis method has universal value and is a more ideal and environmentally friendly new method, especially the hydrothermal reactor for synthesis.

In-depth analysis of the treatment effect and synergistic mechanism of TanReQing injection on clinical multi-drug resistant Pseudomonas aeruginosa.

Antibiotic resistance is a recognized and concerning public health issue. Gram-negative bacilli, such as Pseudomonas aeruginosa (P. aeruginosa), are notorious for their rapid development of drug resistance, leading to treatment failures. TanReQing injection (TRQ) was chosen to explore its pharmacological mechanisms against clinical multidrug-resistant P. aeruginosa (MDR-PA), given its antibacterial and anti-inflammatory properties. We revealed the expression of proteins and genes in P. aeruginosa after co-culture with TRQ. This study developed an assessment method to evaluate clinical resistance of P. aeruginosa using MALDI-TOF MS identification and Biotyper database searching techniques. Additionally, it combined MIC determination to investigate changes in MDR-PA treated by TRQ. TRQ effectively reduced the MICs of ceftazidime and cefoperazone and enhanced the confidence scores of MDR-PA as identified by mass spectrometry. Using this evaluation method, the fingerprints of standard P. aeruginosa and MDR-PA were compared, and the characteristic peptide sequence (Seq-PA No. 1) associated with flagellum was found. The phenotypic experiments were conducted to confirm the effect of TRQ on the motility and adhesion of P. aeruginosa. A combination of co-immunoprecipitation and proteome analysis was employed, and 16 proteins were significantly differentially expressed and identified as potential candidates for investigating the mechanism of inhibiting resistance in P. aeruginosa treated by TRQ. The candidates were verified by quantitative real-time PCR analysis, and TRQ may affect these core proteins (MexA, MexB, OprM, OprF, OTCase, IDH, and ASL) that influence resistance of P. aeruginosa. The combination of multiple methods helps elucidate the synergistic mechanism of TRQ in overcoming resistance of P. aeruginosa.IMPORTANCEPseudomonas aeruginosa is an opportunistic pathogen closely associated with various life-threatening acute and chronic infections. The presence of antimicrobial resistance and multidrug resistance in P. aeruginosa infections significantly complicates antibiotic treatment. The expression of ß-lactamase, efflux systems such as MexAB-OprM, and outer membrane permeability are considered to have the greatest impact on the sensitivity of P. aeruginosa. The study used a method to assess the clinical resistance of P. aeruginosa using matrix-assisted laser desorption ionization time of flight mass spectrometry identification and Biotyper database search techniques. TanReQing injection (TRQ) effectively reduced the MICs of ceftazidime and cefoperazone in multidrug-resistant P. aeruginosa (MDR-PA) and improved the confidence scores for co-cultured MDR-PA. The study found a characteristic peptide sequence for distinguishing whether P. aeruginosa is resistant. Through co-immunoprecipitation and proteome analysis, we explored the mechanism of TRQ overcoming resistance of P. aeruginosa.

Acid protonation promoted different crystal phase structure silicon carbide-based carbon nitride composites to enhance the photocatalytic degradation of dye wastewater.

Acid-protonated crystalline silicon carbide-supported carbon nitride photocatalytic composites were successfully prepared by the impregnation-heat treatment method (P-g-C3N4/ß-SiC and P-g-C3N4/α-SiC). The samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FT-IR), UV-vis diffuse reflectance spectra (UV-vis-DRS) photoluminescence (PL), etc. The results of SEM showed that the P-g-C3N4/ß-SiC and P-g-C3N4/α-SiC materials were transformed from large-area lamellar structures to uniform and dispersed lamellar particles. The UV-vis-DRS and PL showed that the recombination probability of photogenerated electron-hole pairs of P-g-C3N4/ß-SiC and P-g-C3N4/α-SiC samples decreased and the band gap increased. The results of photocatalytic degradation of alizarin red S (ARS), acid fuchsin (AF), and basic fuchsin (BF) showed that the samples P-g-C3N4/ß-SiC and P-g-C3N4/α-SiC had excellent photocatalytic degradation performance. It is worth noting that the degradation performance of the sample P-g-C3N4/ß-SiC on the three dyes is better than that of P-g-C3N4/α-SiC. The electron spin resonance spectra (ESR) results showed that the ˙O2- and ˙OH produced by the two catalysts during the dye degradation process played a leading role in the degradation reaction. Fortunately, the catalyst maintains an excellent cycle life and can be reused more than seven times while degrading all three dyes.

Dynamic RNA synthetic biology: new principles, practices and potential.

An increased appreciation of the role of RNA dynamics in governing RNA function is ushering in a new wave of dynamic RNA synthetic biology. Here, we review recent advances in engineering dynamic RNA systems across the molecular, circuit and cellular scales for important societal-scale applications in environmental and human health, and bioproduction. For each scale, we introduce the core concepts of dynamic RNA folding and function at that scale, and then discuss technologies incorporating these concepts, covering new approaches to engineering riboswitches, ribozymes, RNA origami, RNA strand displacement circuits, biomaterials, biomolecular condensates, extracellular vesicles and synthetic cells. Considering the dynamic nature of RNA within the engineering design process promises to spark the next wave of innovation that will expand the scope and impact of RNA biotechnologies.

LMP2-mRNA lipid nanoparticle sensitizes EBV-related tumors to anti-PD-1 therapy by reversing T cell exhaustion.

BACKGROUND: Targeting EBV-proteins with mRNA vaccines is a promising way to treat EBV-related tumors like nasopharyngeal carcinoma (NPC). We assume that it may sensitize tumors to immune checkpoint inhibitors. RESULTS: We developed an LMP2-mRNA lipid nanoparticle (C2@mLMP2) that can be delivered to tumor-draining lymph nodes. C2@mLMP2 exhibited high transfection efficiency and lysosomal escape ability and induced an increased proportion of CD8 + central memory T cells and CD8 + effective memory T cells in the spleen of the mice model. A strong synergistic anti-tumor effect of C2@mLMP2 in combination with αPD-1 was observed in tumor-bearing mice. The mechanism was identified to be associated with a reverse of CD8 + T cell exhaustion in the tumor microenvironment. The pathological analysis further proved the safety of the vaccine and the combined therapy. CONCLUSIONS: This is the first study proving the synergistic effect of the EBV-mRNA vaccine and PD-1 inhibitors for EBV-related tumors. This study provides theoretical evidence for further clinical trials that may expand the application scenario and efficacy of immunotherapy in NPC.

Integrative models of histopathological images and multi-omics data predict prognosis in endometrial carcinoma.

Objective: This study aimed to predict the molecular features of endometrial carcinoma (EC) and the overall survival (OS) of EC patients using histopathological imaging. Methods: The patients from The Cancer Genome Atlas (TCGA) were separated into the training set (n = 215) and test set (n = 214) in proportion of 1:1. By analyzing quantitative histological image features and setting up random forest model verified by cross-validation, we constructed prognostic models for OS. The model performance is evaluated with the time-dependent receiver operating characteristics (AUC) over the test set. Results: Prognostic models based on histopathological imaging features (HIF) predicted OS in the test set (5-year AUC = 0.803). The performance of combining histopathology and omics transcends that of genomics, transcriptomics, or proteomics alone. Additionally, multi-dimensional omics data, including HIF, genomics, transcriptomics, and proteomics, attained the largest AUCs of 0.866, 0.869, and 0.856 at years 1, 3, and 5, respectively, showcasing the highest discrepancy in survival (HR = 18.347, 95% CI [11.09-25.65], p < 0.001). Conclusions: The results of this experiment indicated that the complementary features of HIF could improve the prognostic performance of EC patients. Moreover, the integration of HIF and multi-dimensional omics data might ameliorate survival prediction and risk stratification in clinical practice.

Targeting lymph node delivery with nanovaccines for cancer immunotherapy: recent advances and future directions.

Although cancer immunotherapy is a compelling approach against cancer, its effectiveness is hindered by the challenge of generating a robust and durable immune response against metastatic cancer cells. Nanovaccines, specifically engineered to transport cancer antigens and immune-stimulating agents to the lymph nodes, hold promise in overcoming these limitations and eliciting a potent and sustained immune response against metastatic cancer cells. This manuscript provides an in-depth exploration of the lymphatic system's background, emphasizing its role in immune surveillance and tumor metastasis. Furthermore, it delves into the design principles of nanovaccines and their unique capability to target lymph node metastasis. The primary objective of this review is to provide a comprehensive overview of the current advancements in nanovaccine design for targeting lymph node metastasis, while also discussing their potential to enhance cancer immunotherapy. By summarizing the state-of-the-art in nanovaccine development, this review aims to shed light on the promising prospects of harnessing nanotechnology to potentiate cancer immunotherapy and ultimately improve patient outcomes.

An Overview of the Therapeutic Strategies for the Treatment of Spinal Muscular Atrophy.

Spinal muscular atrophy (SMA) is a recessive, neurodegenerative disorder. It is one of the most common genetic causes of infant mortality and is characterized by muscle weakness, loss of ambulation, and respiratory failure. SMA is primarily caused by a homozygous deletion or mutation of the survival motor neuron 1 (SMN1) gene. Humans possess a second, nearly identical copy of SMN, known as the SMN2 gene. Although the disease severity correlates inversely with the number of SMN2 copies present, it can never completely compensate for the loss of SMN1 in patients with SMA; SMN2 expresses only a fraction of the functional SMN transcript. The SMN protein is ubiquitous in human cells and plays several roles, ranging from assembling the spliceosome machinery to autophagy, RNA metabolism, signal transduction, cellular homeostasis, DNA repair, and recombination. Although the underlying mechanism remains unclear, anterior horn cells of the spinal cord gray matter are highly vulnerable to decreased SMN protein levels. To harness SMN2's ability to provide SMN function, two treatment strategies have been approved by the Food and Drug Administration (FDA), including an antisense oligonucleotide, nusinersen (Spinraza), and a small molecule, risdiplam (Evrysdi). Onasemnogene abeparvovec (Zolgensma) is an FDA-approved adeno-associated virus 9-mediated gene replacement therapy that creates a copy of the human SMN1 gene. In this review, we summarize the SMA etiology and FDA-approved therapies, and discuss the development of SMA therapeutic strategies and the challenges we faced.

Computer-aided diagnostic models to classify lymph node metastasis and lymphoma involvement in enlarged cervical lymph nodes using PET/CT.

BACKGROUND: It is a clinical problem to identify histological component in enlarged cervical lymph nodes, particularly in differentiation between lymph node metastasis and lymphoma involvement. PURPOSE: To construct two kinds of deep learning (DL)-based computer-aided diagnosis (CAD) systems including DL-convolutional neural networks (DL-CNN) and DL-machine learning for pathological diagnosis of cervical lymph nodes by positron emission tomography (PET)/computed tomography (CT) images. METHODS: We collected CT, PET, and PET/CT images series from 165 patients with enlarged cervical lymph nodes receiving examinations from January 2014 to June 2018. Six CNNs pretrained on ImageNet as DL architectures were used for two kinds of DL-based CAD models, including DL-CNN and DL-machine learning models. The DL-CNN models were constructed via transfer learning for classification of lymphomatous and metastatic lymph nodes. The DL-machine learning models were developed by DL-based features extractors and support vector machine (SVM) classifier. As for DL-SVM models, we also evaluate the effect of handcrafted radiomics features in combination of DL-based features. RESULTS: The DL-CNN model with ResNet50 architecture on PET/CT images had the best diagnostic performance among all six algorithms with an area under the receiver operating characteristic curve (AUC) of 0.845 and accuracy of 78.13% in the testing cohort. The DL-SVM model on ResNet50 extractor showed great performance for the testing cohort with an AUC of 0.901, accuracy of 86.96%, sensitivity of 76.09%, and specificity of 94.20%. The combination of DL-based and handcrafted features yielded the improvement of diagnostic performance. CONCLUSIONS: Our DL-based CAD systems on PET/CT images were developed for classifying metastatic and lymphomatous involvement with favorable diagnostic performance in enlarged cervical lymph nodes. Further clinical practice of our systems may improve quality of the following therapeutic interventions and optimize patients' outcomes.

Degradation of COD in antibiotic wastewater by a combination process of electrochemistry, hydroxyl-functionalized ball-milled zero-valent iron/Fe3O4 and Oxone.

In this study, the significant iron-based material, hydroxyl-functionalized ball-milled zero-valent iron/Fe3O4 (HFB-ZVI/Fe3O4) was employed for the experiments. The performance of the Electro + HFB-ZVI/Fe3O4 + Oxone system for the degradation of chemical oxygen demand (COD) in antibiotic wastewater was investigated. A direct current was applied between a graphite plate anode and two iron plate cathodes, and a series of operational parameters, such as applied electric current, the dosage of HFB-ZVI/Fe3O4 composite, the dosage of Oxone, and initial solution pH, were explored to evaluate the oxidation process. The application of electric current enhanced the gradual degradation of COD and the increase of current intensity accelerated COD degradation. The neutral condition was favourable for the rapid degradation of COD in a short reaction time by the Electro + HFB-ZVI/Fe3O4 + Oxone process and promoted the degradation efficiency of COD. An increase of electric current gradually decreased the reaction solution pH, the larger the electric current applied in the reaction process, the lower the final pH of the reaction solution. Under the optimal experimental conditions (1 g/L HFB-ZVI/Fe3O4 composite, 0.3 g/L Oxone, current intensity = 500 mA, initial solution pH = 7.85), Electro + HFB-ZVI/Fe3O4 + Oxone achieved 99% COD degradation in antibiotic wastewater. Radicals quenching experiments indicated the contribution to COD degradation by hydroxyl radicals (HO•), sulphate radicals (SO4•-) and other oxidants were 66.03%, 24.014% and 9.756%, respectively. The possible mechanism of COD degradation in the Electro + HFB-ZVI/Fe3O4 + Oxone system was also discussed in this study. The findings in this work provided useful information for the treatment of wastewater.

The Immune Subtype Contributes to Distinct Overall Survival for Ovarian Cancer Patients With Platinum-Based Adjuvant Therapy.

Objective: Nowadays, platinum-based therapy has been widely used as the first-line therapy of ovarian cancer. However, the effect of the tumor microenvironment on platinum-based therapy remains unclear. In this study, we aim to investigate the relationship between immune microenvironment subtypes and the prognosis of platinum-based therapy in ovarian cancer. Methods: We integrated 565 ovarian cancer samples from two datasets and obtained the immune subtypes (ISs) by consistent clustering of 1190 immune-related gene expressions. The proportional hazards regression model was used to assess the relationship between ISs and the prognosis of platinum-based adjuvant therapy including progression-free survival (PFS) and overall survival (OS). The prognostic contribution of ISs was validated in three additional cohorts. Non-parametric tests were used to assess genomic characteristics, the proportion of immune cells, and immune-related signature differences among ISs. Results: We identified and validated five ISs associated with different clinical outcomes of the platinum-based adjuvant therapy in ovarian cancer patients. These differences were only found in OS rather than PFS. An immune subtype had the worst OS. Those patients mainly derived from the mesenchymal subtype had the lowest tumor purity with a high leukocyte fraction as well as stromal fraction and had the highest TGF-ß response signaling. By contrast, an immune subtype characterized by immunoreactive status with the highest CD8+T cell infiltration and elevated IFN-γ response signaling had the best prognosis. Other subtypes with more diverse immunologic features such as lowest macrophage regulation signaling showed intermediate prognoses. Notably, the contribution of ISs to OS was independent of the clinical response to platinum-based drugs. Conclusion: Our analysis revealed the association between different immune characteristics and platinum-based adjuvant therapy, indicating the combination of ISs and chemotherapy could optimize the treatment strategy of OC patients.

Small cell lung cancer transformation: From pathogenesis to treatment.

Small cell lung cancer (SCLC) is a type of neuroendocrine tumor with high malignancy and poor prognosis. Besides the de novo SCLC, there is transformed SCLC, which has similar characteristics of pathological morphology, molecular characteristics, clinical manifestations and drug sensitivity. However, de novo SCLC and transformed SCLC have different pathogenesis and tumor microenvironment. SCLC transformation is one of the mechanisms of resistance to chemotherapy, immunotherapy, and targeted therapy in NSCLC. Two hypotheses have been used to explain the pathogenesis of SCLC transformation. Although SCLC transformation is not common in clinical practice, it has been repeatedly identified in many small patient series and case reports. It usually occurs in epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma after treatment with tyrosine kinase inhibitors (TKIs). SCLC transformation can also occur in anaplastic lymphoma kinase (ALK)-positive lung cancer after treatment with ALK inhibitors and in wild-type EGFR or ALK NSCLC treated with immunotherapy. Chemotherapy was previously used to treat transformed SCLC, yet it is associated with an unsatisfactory prognosis. We comprehensively review the advancements in transformed SCLC, including clinical and pathological characteristics, and the potential effective treatment after SCLC transformation, aiming to give a better understanding of transformed SCLC and provide support for clinical uses.

Therapeutic progress and challenges for triple negative breast cancer: targeted therapy and immunotherapy.

Triple negative breast cancer (TNBC) is a subtype of breast cancer, with estrogen receptor, human epidermal growth factor receptor 2 and progesterone receptor negative. TNBC is characterized by high heterogeneity, high rates of metastasis, poor prognosis, and lack of therapeutic targets. Now the treatment of TNBC is still based on surgery and chemotherapy, which is effective only in initial stage but almost useless in advanced stage. And due to the lack of hormone target, hormonal therapies have little beneficial effects. In recent years, signaling pathways and receptor-specific targets have been reported to be effective in TNBC patients under specific clinical conditions. Now targeted therapies have been approved for many other cancers and even other subtypes of breast cancer, but treatment options for TNBC are still limited. Most of TNBC patients showed no response, which may be related to the heterogeneity of TNBC, therefore more effective treatments and predictive biomarkers are needed. In the present review, we summarize potential treatment opinions for TNBC based on the dysregulated receptors and signaling pathways, which play a significant role in multiple stages of TNBC development. We also focus on the application of immunotherapy in TNBC, and summarize the preclinical and clinical trials of therapy for patients with TNBC. We hope to accelerate the research and development of new drugs for TNBC by understanding the relevant mechanisms, and to improve survival.

Criteria for judging the immune markers of COVID-19 disease vaccines.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sweeping the world, effective and affordable vaccines are in urgent need. A reliable system for the assessment of SARS-CoV-2 vaccines would boost the development of vaccines and reduce the research cost. We constructed a logistic regression model and analyzed the relationship between antibody (Ab) level and efficacy of different vaccine types. The relationship between assessment dates and Ab levels was depicted by plotting the mean of Ab levels evolved over time and a fitted cubic polynomial model. Anti-spike immunoglobulin G (IgG) could best estimate the vaccine efficacy (VE) (adjusted R 2  = 0.731) and neutralizing Ab to live SARS-CoV-2 also explained a fine relationship (adjusted R 2 = 0.577). Neutralizing Abs to live SARS-CoV-2 in inactivated virus vaccines reached a peak during days 40-60, and their receptor-binding domain (RBD)-IgG peaked during days 40-50. For messenger RNA (mRNA) and viral vector vaccines, their neutralizing Ab to live SARS-CoV-2 peaked later than day 40, and for RBD-IgG during days 30-50. For mRNA and viral vector vaccines, their peak time of Abs was later than that in inactivated virus vaccines. RBD-IgG peaked earlier than Ab to live SARS-CoV-2. Anti-spike IgG and Ab to live SARS-CoV-2 may be good immune markers for VE assessment.

China's inter-regional embodied carbon emissions: An industrial transfer perspective.

In the context of internal circulation, domestic trade is widely encouraged in China. However, the growth of inter-provincial trade may aggravate inter-regional embodied carbon emissions transfer. The knowledge about the causes of changes in embodied carbon emissions from an industry transfer perspective is limited, which is significant for achieving the regional carbon emission reduction fairly and reasonably. Therefore, this paper utilizes the provincial energy consumption data and the multi-region input-output tables in 2002 and 2012 to calculate the embodied carbon transfer among different regions. Furthermore, the inter-regional embodied carbon emissions transfer trends are analyzed and discussed by the quantitative measurement of industries transfer. The results indicated that nearly 58% of carbon emissions were transferred out from the southeast coastal areas to the central and western areas by importing carbon-intensive productions, reaching 516 million tons. In addition, the carbon intensity in the eastern areas decreased by about 30%, while that increased by 11% in the central and western areas. Energy inequality among regions was getting worse. To promote inter-regional development equity, the emission reduction targets of different regions should be heterogeneous. Specifically, the southeast coastal areas are suggeted to compensate for the transfer-out emissions. The central and western areas are suggested to develop markets for renewable energy topromote the economy and adjust energy structure.

Embodied energy in China: drivers and inequality at a regional level.

China is a large economy with unbalanced economic growth throughout different regions, posing a great challenge to allocating energy saving and carbon emissions reduction responsibilities. This paper applies the multi-regional input-output tables of China in 2007 and 2012 to evaluate the status of embodied energy consumption. The embodied energy transfer of eight regions in China is analyzed based on a demand-side perspective. Furthermore, the driving factors of embodied energy changes and the inequality at a regional level are explored via a structural decomposition analysis, which provides references for promoting regional energy development and adjusting the industrial layout. The results indicate that China's total embodied energy consumption increased from 2.06 billion tons of standard coal equivalent (tce) in 2007 to 3.46 billion tce in 2012. Specifically, embodied energy consumption is concentrated in the Central regions, consuming 710 million tce in 2012. In addition, a large proportion of energy produced in all regions is consumed locally, while the amount of transferred embodied energy is widespread across different regions. The economic scale is the primary driving factor of embodied energy consumption changes, and technological development has a noticeable effect on restraining energy consumption. Regarding the structural effect, significant differences exist in different regions and end-use sectors. In conclusion, the regional development policies aiming to optimize the industrial structure and strengthen energy technology improvement in dual-circulation development patterns are proposed.

Effects of Exogenous Biliverdin Treatment on Neurobehaviors in Mice.

The neuroprotective effects of heme oxygenase (HO) have been well investigated. The potential effects of exogenous supplementation of biliverdin (BVD), one of the main products catalyzed by HO, on neurobehaviors are still largely unknown. The present study aimed to investigate the effects of BVD treatment on depression, anxiety, and memory in adult mice. Mice were injected with BVD through tail vein daily for a total 5 d, and depression- and anxiety-like behaviors were conducted by using open field test (OFT), novelty suppressed feeding (NSF), forced swimming test (FST) and tail suspension test (TST) since the third day of BVD administration. Novel object recognition (NOR) paradigm was used for memory formation test. After the final test, serum and hippocampal levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) of mice were analyzed by enzyme-linked immunosorbent assay (ELISA). The results showed that BVD treatment at low dose (2 mg/kg) induced depression-like behaviors, and high dose (8 mg/kg) BVD injection increased anxiety-like behaviors and impaired memory formation in mice. ELISA data showed that BVD treatment significantly increased hippocampal IL-6 and TNF-α level while only decreasing serum IL-6 level of mice. The present data suggest that exogenous BVD treatment induced depression- and anxiety-like phenotypes, which may be related to inflammatory factors, providing BVD may be a potential target for the prevention of mental disorders.

Graphical-model framework for automated annotation of cell identities in dense cellular images.

Although identifying cell names in dense image stacks is critical in analyzing functional whole-brain data enabling comparison across experiments, unbiased identification is very difficult, and relies heavily on researchers' experiences. Here, we present a probabilistic-graphical-model framework, CRF_ID, based on Conditional Random Fields, for unbiased and automated cell identification. CRF_ID focuses on maximizing intrinsic similarity between shapes. Compared to existing methods, CRF_ID achieves higher accuracy on simulated and ground-truth experimental datasets, and better robustness against challenging noise conditions common in experimental data. CRF_ID can further boost accuracy by building atlases from annotated data in highly computationally efficient manner, and by easily adding new features (e.g. from new strains). We demonstrate cell annotation in Caenorhabditis elegans images across strains, animal orientations, and tasks including gene-expression localization, multi-cellular and whole-brain functional imaging experiments. Together, these successes demonstrate that unbiased cell annotation can facilitate biological discovery, and this approach may be valuable to annotation tasks for other systems.