Effects of environmental concentrations of sulfamethoxazole on Skeletonema costatum and Phaeodactylum tricornutum: Insights into growth, oxidative stress, biochemical components, ultrastructure, and transcriptome.

This study aimed to assess the ecological risks posed by sulfamethoxazole (SMX) at environmentally relevant concentrations. Specifically, its effects on the growth and biochemical components (total protein, total lipid, and total carbohydrate) of two marine microalgae species, namely Skeletonema costatum (S. costatum) and Phaeodactylum tricornutum (P. tricornutum), were investigated. Our findings revealed that concentrations of SMX below 150 ng/L stimulated the growth of both microalgae. Conversely, at higher concentrations, SMX inhibited their growth while promoting the synthesis of photosynthetic pigments, total protein, total lipid, and total carbohydrate (P < 0.05). Transmission electron microscope (TEM) observations demonstrated significant alterations in the ultrastructure of algal cells exposed to SMX, including nuclear marginalization, increased chloroplast volume, and heightened vacuolation. In addition, when SMX was lower than 250 ng/L, there was no oxidative damage in two microalgae cells. However, when SMX was higher than 250 ng/L, the antioxidant defense system of algal cells was activated to varying degrees, and the level of malondialdehyde (MDA) increased, indicating that algae cells were damaged by oxidation. From the molecular level, environmental concentration of SMX can induce microalgae cells to produce more energy substances, but there are almost no other adverse effects, indicating that the low level of SMX at the actual exposure level was unlikely to threaten P. tricornutum, but a higher concentration can significantly reduce its genetic products, which can affect the changes of its cell structure and damage P. tricornutum to some extent. Therefore, environmental concentration of SMX still has certain potential risks to microalgae. These outcomes improved current understanding of the potential ecological risks associated with SMX in marine environments.

A novel nomogram to predict psoriatic arthritis in patients with plaque psoriasis.

OBJECTIVE: To construct a predictive model for Psoriatic Arthritis (PsA) based on clinical and ultrasonic characteristics in patients with plaque psoriasis (PsP). PATIENTS AND METHODS: Demographic, clinical, and ultrasound data were collected from patients with PsP and PsA between May 2019 and December 2022. RESULTS: A total of 212 patients with PsP and 123 with PsA in the training cohort, whereas the validation cohort comprised 91 patients with PsP and 49 with PsA. The multivariate logistic regression identified nail psoriasis (odds ratio [OR] 1.88, 95% CI: 1.07-3.29), synovitis (OR 18.23, 95% CI: 4.04-82.33), enthesitis (OR 3.71, 95% CI: 1.05-13.14), and bone erosion (OR 11.39, 95% CI: 3.05-42.63) as effective predictors for PsA. The area under the curve was 0.750 (95% CI, 0.691-0.806) and 0.804 (95% CI, 0.723-0.886) for the training and validation cohorts, respectively. The Hosmer-Lemeshow goodness-of-fit test showed good consistency for both the training cohort (p  =  0.970) and the validation cohort (p  =  0.967). Calibration curves also indicated good calibration for both cohorts. The DCA revealed that the predictive model had good clinical utility. CONCLUSIONS: We have developed a quantitative, intuitive, and convenient predictive model based on nail psoriasis, synovitis, enthesitis, and bone erosion to assess the risk of PsA in patients with plaque psoriasis.

GeoDTR+: Toward Generic Cross-View Geolocalization via Geometric Disentanglement.

Cross-View Geo-Localization (CVGL) estimates the location of a ground image by matching it to a geo-tagged aerial image in a database. Recent works achieve outstanding progress on CVGL benchmarks. However, existing methods still suffer from poor performance in cross-area evaluation, in which the training and testing data are captured from completely distinct areas. We attribute this deficiency to the lack of ability to extract the geometric layout of visual features and models' overfitting to low-level details. Our preliminary work [1] introduced a Geometric Layout Extractor (GLE) to capture the geometric layout from input features. However, the previous GLE does not fully exploit information in the input feature. In this work, we propose GeoDTR+ with an enhanced GLE module that better models the correlations among visual features. To fully explore the LS techniques from our preliminary work, we further propose Contrastive Hard Samples Generation (CHSG) to facilitate model training. Extensive experiments show that GeoDTR+ achieves state-of-the-art (SOTA) results in cross-area evaluation on CVUSA [2], CVACT [3], and VIGOR [4] by a large margin ( 16.44%, 22.71%, and 13.66% without polar transformation) while keeping the same-area performance comparable to existing SOTA. Moreover, we provide detailed analyses of GeoDTR+. Our code will be available at https://gitlab.com/vail-uvm/geodtr_plus.

HSP70 contributes to pathogenesis of fulminant hepatitis induced by coronavirus.

Fulminant viral hepatitis (FH) represents a significant clinical challenge, with its pathogenesis not yet fully elucidated. Heat shock protein (HSP)70, a molecular chaperone protein with a broad range of cytoprotective functions, is upregulated in response to stress. However, the role of HSP70 in FH remains to be investigated. Notably, HSP70 expression is upregulated in the livers of coronavirus-infected mice and patients. Therefore, we investigated the mechanistic role of HSP70 in coronavirus-associated FH pathogenesis. FH was induced in HSP70-deficient (HSP70 KO) mice or in WT mice treated with the HSP70 inhibitor VER155008 when infected with the mouse hepatitis virus strain A59 (MHV-A59). MHV-A59-infected HSP70 KO mice exhibited significantly reduced liver damage and mortality. This effect was attributed to decreased infiltration of monocyte-macrophages and neutrophils in the liver of HSP70 KO mice, resulting in lower levels of inflammatory cytokines such as IL-1ß, TNFα, and IL-6, and a reduced viral load. Moreover, treatment with the HSP70 inhibitor VER155008 protected mice from MHV-A59-induced liver damage and FH mortality. In summary, HSP70 promotes coronavirus-induced FH pathogenesis by enhancing the infiltration of monocyte-macrophages and neutrophils and promoting the secretion of inflammatory cytokines. Therefore, HSP70 is a potential therapeutic target in viral FH intervention.

Challenging the N-Heuristic: Effect size, not sample size, predicts the replicability of psychological science.

Large sample size (N) is seen as a key criterion in judging the replicability of psychological research, a phenomenon we refer to as the N-Heuristic. This heuristic has led to the incentivization of fast, online, non-behavioral studies-to the potential detriment of psychological science. While large N should in principle increase statistical power and thus the replicability of effects, in practice it may not. Large-N studies may have other attributes that undercut their power or validity. Consolidating data from all systematic, large-scale attempts at replication (N = 307 original-replication study pairs), we find that the original study's sample size did not predict its likelihood of being replicated (rs = -0.02, p = 0.741), even with study design and research area controlled. By contrast, effect size emerged as a substantial predictor (rs = 0.21, p < 0.001), which held regardless of the study's sample size. N may be a poor predictor of replicability because studies with larger N investigated smaller effects (rs = -0.49, p < 0.001). Contrary to these results, a survey of 215 professional psychologists, presenting them with a comprehensive list of methodological criteria, found sample size to be rated as the most important criterion in judging a study's replicability. Our findings strike a cautionary note with respect to the prioritization of large N in judging the replicability of psychological science.

Bridging Histopathology and Radiomics Toward Prognosis of Metastasis in Early Breast Cancer.

Tumor histomorphology is crucial for the prognostication of breast cancer outcomes because it contains histological, cellular, and molecular tumor heterogeneity related to metastatic potential. To enhance breast cancer prognosis, we aimed to apply radiomics analysis-traditionally used in 3D scans-to 2D histopathology slides. This study tested radiomics analysis in a cohort of 92 breast tumor specimens for outcome prognosis, addressing -omics dimensionality by comparing models with moderate and high feature counts, using least absolute shrinkage and selection operator for feature selection and machine learning for prognostic modeling. In the test folds, models with radiomics features [area under the curves (AUCs) range 0.799-0.823] significantly outperformed the benchmark model, which only included clinicopathological (CP) parameters (AUC = 0.584). The moderate-dimensionality model with 11 CP + 93 radiomics features matched the performance of the highly dimensional models with 1,208 radiomics or 11 CP + 1,208 radiomics features, showing average AUCs of 0.823, 0.799, and 0.807 and accuracies of 79.8, 79.3, and 76.6%, respectively. In conclusion, our application of deep texture radiomics analysis to 2D histopathology showed strong prognostic performance with a moderate-dimensionality model, surpassing a benchmark based on standard CP parameters, indicating that this deep texture histomics approach could potentially become a valuable prognostic tool.

Epilepsy lesion localization method based on brain function network.

Objective: In the past, the localization of seizure onset zone (SOZ) primarily relied on traditional EEG signal analysis methods. However, due to their limited spatial and temporal resolution, accurately pinpointing neural activity was challenging, thereby restricting their clinical applicability. Compared with traditional EEG signals, SEEG signals have superior spatial and temporal resolution, and can more accurately record neural activity near epileptic foci, making them better suited for studying SOZ. In addition, the traditional EEG signal analysis methods still have limitations, mainly focusing on the analysis of local signal features, while ignoring the complexity and interconnection of the overall brain network. How to more accurately locate SOZ is still not well resolved. The purpose of this study is to develop an effective positioning method for more accurate positioning. Method: To overcome these limitations, this study proposed a model integrating brain functional network analysis with nonlinear dynamics. We utilized weighted phase lag index (WPLI) to construct brain functional network, epilepic network connectivity strength (ENCS) as the feature, and introduced persistence entropy (PE) for feature fusion, subsequently employing support vector machine (SVM) classification. Results: The proposed method was verified on the HUP-iEEG dataset, our solution identified the SOZ with 0.9440 accuracy, 0.9848 precision, 0.8974 recall rate, 0.9340 F1 score and 0.9697 area under the ROC curve across patients, which outperforms the existing approaches. It exhibits a 2.30 percentage point enhancement in localisation accuracy along with a 2.97 percentage points in AUC compared to others. Conclusion: Our method consider the interactions between nodes in brain network connections, as well as the inherent nonlinear and non-stationary properties of neural signals, to be more robust.

A vagal-brainstem interoceptive circuit for cough-like defensive behaviors in mice.

Coughing is a respiratory behavior that plays a crucial role in protecting the respiratory system. Here we show that the nucleus of the solitary tract (NTS) in mice contains heterogenous neuronal populations that differentially control breathing. Within these subtypes, activation of tachykinin 1 (Tac1)-expressing neurons triggers specific respiratory behaviors that, as revealed by our detailed characterization, are cough-like behaviors. Chemogenetic silencing or genetic ablation of Tac1 neurons inhibits cough-like behaviors induced by tussive challenges. These Tac1 neurons receive synaptic inputs from the bronchopulmonary chemosensory and mechanosensory neurons in the vagal ganglion and coordinate medullary regions to control distinct aspects of cough-like defensive behaviors. We propose that these Tac1 neurons in the NTS are a key component of the airway-vagal-brain neural circuit that controls cough-like defensive behaviors in mice and that they coordinate the downstream modular circuits to elicit the sequential motor pattern of forceful expiratory responses.

Research on the mechanism of sea buckthorn leaf Fu tea in the treatment of hyperlipidemia.

Background: Hyperlipidemia (HLP) presents a significant challenge to global public health. Mounting evidence suggests that statins, the recommended first-line lipid-lowering agents, have significant adverse effects. Consequently, the quest for natural and efficacious alternative therapies is steadily emerging as a research priority for HLP prevention and treatment. Consumption of tea, which is rich in diverse biologically active compounds with the capacity to regulate lipid metabolism and combat obesity, has emerged as a promising alternative therapy. Sea buckthorn leaves are rich in a multitude of biologically active substances, have a hypolipidemic effect, and can be used as a raw material for tea because of their unique flavor. There is a suggestion that combining Aspergillus cristatus with tea could modify or boost the lipid-lowering active compounds present in tea, thereby increasing its efficacy in regulating lipid metabolism. Results: Sea Buckthorn Leaf Fu Tea (SBLFT) was obtained by fermentation when sea buckthorn leaves contained 42 % moisture, inoculated with Aspergillus cristatus 0.2 mL/g, and incubated for 8 d at constant temperature. Animal experiments demonstrated that SBLFT significantly inhibited body weight gain in HLP rats and reduced lipid content and serum oxidative stress. In addition, liver tissue sections and functional indices showed that SBLFT can improve liver morphology and function abnormalities. Reverse transcription-polymerase chain reaction results indicated that the expression of Liver kinase B1 (LKB1), adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK), acetyl CoA carboxylase 1 (ACC1), and sterol-regulatory element binding protein-1 (SREBP1c) gene related to lipid metabolism was altered. Conclusion: SBLFT improved HLP, specifically via promoting the expression of LKB1 in the liver of HLP rats, activating AMPK, and inhibiting ACC1 and SREBP1c expression, resulting in the inhibition of fatty acid and triglyceride synthesis-related enzymes at the transcriptional level.

SH2B1 Defends Against Energy Imbalance, Obesity, and Metabolic Disease via a Paraventricular Hypothalamus→Dorsal Raphe Nucleus Neurocircuit.

SH2B1 mutations are associated with obesity, type 2 diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD) in humans. Global deletion of Sh2b1 results in severe obesity, type 2 diabetes, and MASLD in mice. Neuron-specific restoration of SH2B1 rescues the obesity phenotype of Sh2b1-null mice, indicating that the brain is a main SH2B1 target. However, SH2B1 neurocircuits remain elusive. SH2B1-expressing neurons in the paraventricular hypothalamus (PVHSH2B1) and a PVHSH2B1→dorsal raphe nucleus (DRN) neurocircuit are identified here. PVHSH2B1 axons monosynaptically innervate DRN neurons. Optogenetic stimulation of PVHSH2B1 axonal fibers in the DRN suppresses food intake. Chronic inhibition of PVHSH2B1 neurons causes obesity. In male and female mice, either embryonic-onset or adult-onset deletion of Sh2b1 in PVH neurons causes energy imbalance, obesity, insulin resistance, glucose intolerance, and MASLD. Ablation of Sh2b1 in the DRN-projecting PVHSH2B1 subpopulation also causes energy imbalance, obesity, and metabolic disorders. Conversely, SH2B1 overexpression in either total or DRN-projecting PVHSH2B1 neurons protects against diet-induced obesity. SH2B1 binds to TrkB and enhances brain-derived neurotrophic factor (BDNF) signaling. Ablation of Sh2b1 in PVHSH2B1 neurons induces BDNF resistance in the PVH, contributing to obesity. In conclusion, these results unveil a previously unrecognized PVHSH2B1→DRN neurocircuit through which SH2B1 defends against obesity by enhancing BDNF/TrkB signaling.

Comprehensive review of emerging contaminants: Detection technologies, environmental impact, and management strategies.

Emerging contaminants (ECs) are a diverse group of unregulated pollutants increasingly present in the environment. These contaminants, including pharmaceuticals, personal care products, endocrine disruptors, and industrial chemicals, can enter the environment through various pathways and persist, accumulating in the food chain and posing risks to ecosystems and human health. This comprehensive review examines the chemical characteristics, sources, and varieties of ECs. It critically evaluates the current understanding of their environmental and health impacts, highlighting recent advancements and challenges in detection and analysis. The review also assesses existing regulations and policies, identifying shortcomings and proposing potential enhancements. ECs pose significant risks to wildlife and ecosystems by disrupting animal hormones, causing genetic alterations that diminish diversity and resilience, and altering soil nutrient dynamics and the physical environment. Furthermore, ECs present increasing risks to human health, including hormonal disruptions, antibiotic resistance, endocrine disruption, neurological effects, carcinogenic effects, and other long-term impacts. To address these critical issues, the review offers recommendations for future research, emphasizing areas requiring further investigation to comprehend the full implications of these contaminants. It also suggests increased funding and support for research, development of advanced detection technologies, establishment of standardized methods, adoption of precautionary regulations, enhanced public awareness and education, cross-sectoral collaboration, and integration of scientific research into policy-making. By implementing these solutions, we can improve our ability to detect, monitor, and manage ECs, reducing environmental and public health risks.

Quantifying instantaneous nitrogen oxides emissions from power plants based on space observations.

Thermal power plants are significant contributors to nitrogen oxides (NOx), impacting global atmospheric conditions and human health. Satellite observations, known for their continuity and global coverage, have become an effective means of quantifying power plant emissions. Previous studies, often accumulating long temporal data into integrated plumes, resulted in substantial errors in annual emissions at the individual power plant level due to neglecting variations in emissions and diffusion conditions. This study presents, for the first time, the quantification of instantaneous NOx emissions based on single overpass observations from the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite. By addressing the temporal variability of power plant emissions, it effectively reduces annual estimation errors. Comparative analysis between the Exponentially-Modified Gaussian (EMG) and Gaussian Plume Model (GPM) simulations demonstrates the capability of EMG to provide instantaneous emission estimates based on actual plumes, exhibiting closer proximity to actual monitoring values than GPM. Applying the EMG method, we quantify the instantaneous emission rates of six power plants in the United States. Comparing annual emission estimations at individual power plants with traditional integrated plume results, our method demonstrates a 63.7 % improvement in annual emission estimations. This study offers more detailed data on power plant emissions, providing a new avenue for better understanding the emission behavior of thermal power plants.

Neglected Spleen Transcriptional Profile Reveals Inflammatory Disorder Conferred by Rabbit Hemorrhagic Disease Virus 2 Infection.

Rabbit hemorrhagic disease (RHD) is an acute fatal disease caused by the rabbit hemorrhagic disease virus (RHDV). Since the first outbreaks of type 2 RHDV (RHDV2) in April 2020 in China, the persistence of this virus in the rabbit population has caused substantial economic losses in rabbit husbandry. Previous failures in preventing RHDV2 prompted us to further investigate the immune mechanisms underlying the virus's pathogenicity, particularly concerning the spleen, a vital component of the mononuclear phagocyte system (MPS). For this, a previous RHDV2 isolate, CHN/SC2020, was utilized to challenge naive adult rabbits. Then, the splenic transcriptome was determined by RNA-Seq. This study showed that the infected adult rabbits had 3148 differentially expressed genes (DEGs), which were associated with disease, signal transduction, cellular processes, and cytokine signaling categories. Of these, 100 upregulated DEGs were involved in inflammatory factors such as IL1α, IL-6, and IL-8. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEGs were significantly enriched in the cytokine-cytokine receptor interaction signaling pathway, which may play a vital role in CHN/SC2020 infection. At the same time, proinflammatory cytokines and chemokines were significantly increased in the spleen at the late stages of infection. These findings suggested that RHDV2 (CHN/SC2020) might induce dysregulation of the cytokine network and compromise splenic immunity against viral infection, which expanded our understanding of RHDV2 pathogenicity.

Research Note: Rapid generation of a novel fowl adenovirus serotype 11 reverse genetic platform.

Fowl adenovirus serotype 11 (FAdV-11) is one of the main causative agents of inclusion body hepatitis (IBH) in broilers. Outbreaks of FAdV-11-related IBH have been increasingly reported in China and many other geographical areas worldwide. However, the critical virulence factors of FAdV-11 remain uncertain due to the lack of technical platforms for efficient manipulation of FAdV-11 genome. Here, we reported the establishment of a FAdV-11 reverse genetic system based on a novel FAdV-11 Chinese isolate FJSW/2021 using the exonuclease combined with RecET (ExoCET), Redαß recombineering and ccdB counter-selection techniques for the first time. A recombinant FAdV-11 was rescued efficiently by using the established reverse genetic platform through swapping the ORF11 gene of the FAdV-11 FJSW/2021 with the ZsGreen fluorescent protein expression cassette. This study provides an effective technical platform for identifying virulence factors of FAdV-11 and developing recombinant FAdV-11-vectored vaccine candidates.

A Metastructure Based on Amorphous Carbon for High Efficiency and Selective Solar Absorption.

Efficient solar thermal conversion is crucial for renewable clean energy technologies such as solar thermal power generation, solar thermophotovoltaic and seawater desalination. To maximize solar energy conversion efficiency, a solar selective absorber with tailored absorption properties designed for solar applications is indispensable. In this study, we propose a broadband selective absorber based on amorphous carbon (a-C) metamaterials that achieves high absorption in the ultraviolet (UV), visible (Vis) and near-infrared (NIR) spectral ranges. Additionally, through metal doping, the optical properties of carbon matrix materials can be modulated. We introduce Ti@a-C thin film into the nanostructure to enhance light absorption across most of the solar spectrum, particularly in the NIR wavelength band, which is essential for improving energy utilization. The impressive solar absorptivity and photothermal conversion efficiency reach 97.8% and 95.6%, respectively. Notably, these superior performances are well-maintained even at large incident angles with different polarized states. These findings open new avenues for the application of a-C matrix materials, especially in fields related to solar energy harvesting.

Discovery of a Novel Chromone Enantiomer and the Precursors of Nonactic Acid from the Coral-Reef-Derived Streptomyces sp. SCSIO 66814.

Three pairs of enantiomers (1-3)-the new 12R-aloesol (1a) and two new fatty acids (2 and 3)-and one new natural product (4) together three known compounds (5-7) were isolated from a coral-reef-derived Streptomyces sp. SCSIO 66814. Their structures were determined through extensive spectroscopic analysis, chiral analysis, and single-crystal X-ray diffraction data. Compounds 2 and 3 were presumed to be intermediates for further generating homononactic acid (5) and nonactic acid, and the latter two molecules were able to act as precursors to form macrotetrolides with remarkable biological activity. The isolation of related precursors, compounds 2-5, provided more evidence to support the proposal of a plausible biosynthetic pathway for nonactic acid and its homologs. Additionally, (+)-1 exhibited a weak activity against DPPH radicals.

2,3-Dimethoxycinnamic Acid from a Marine Actinomycete, a Promising Quorum Sensing Inhibitor in Chromobacterium violaceum.

An ethyl acetate extract of a marine actinomycete strain, Nocardiopsis mentallicus SCSIO 53858, isolated from a deep-sea sediment sample in the South China Sea, exhibited anti-quorum-sensing (QS) activity against Chromobacterium violaceum CV026. Guided by the anti-QS activity, a novel active compound was isolated and purified from the extract and was identified as 2,3-dimethoxycinnamic acid (2,3-DCA) through spectral data analysis. At a concentration of 150 µg/mL, 2,3-DCA exhibited robust inhibitory effects on three QS-regulated traits of C. violaceum CV026: violacein production, swarming motility, and biofilm formation, with inhibition rates of 73.9%, 65.9%, and 37.8%, respectively. The quantitative reverse transcription polymerase chain reaction results indicated that 2,3-DCA can disrupt the QS system in C. violaceum CV026 by effectively suppressing the expression of QS-related genes, including cviR, vioA, vioB, and vioE. Molecular docking analysis revealed that 2,3-DCA hinders the QS system by competitively binding to the same binding pocket on the CviR receptor as the natural signal molecule N-hexanoyl-L-homoserine lactone. Collectively, these findings suggest that 2,3-DCA exhibits promising potential as an inhibitor of QS systems, providing a potential solution to the emerging problem of bacterial resistance.

Genome-guided discovery of two undescribed 6,6-spiroketal polyketides and stereochemical correction of bafilomycins P and Q from the marine-derived Streptomyces sp. SCSIO 66814.

Bafilomycins are macrocyclic polyketides with intriguing structures and therapeutic value. Genomic analysis of Streptomyces sp. SCSIO 66814 revealed a type I polyketide synthase biosynthetic gene cluster (BGC), namely blm, which encoded bafilomycins and featured rich post-modification genes. The One strain many compounds (OSMAC) strategy led to the discovery of six compounds related to the blm BGC from the strain, including two previously undescribed 6,6-spiroketal polyketides, streptospirodienoic acids D (1) and E (2), and four known bafilomycins, bafilomycins P (3), Q (4), D (5), and G (6). The structures of 1 and 2 were determined by extensive spectroscopic analysis, quantum calculation, and biosynthetic analysis. Additionally, the absolute configurations of the 6/5/5 tricyclic ring moiety containing six consecutive chiral carbons in the putative structures of 3 and 4 were corrected through NOE analysis, DP4+ calculation, and single-crystal X-ray diffraction data. Bioinformatic analysis uncovered a plausible biosynthetic pathway for compounds 1-6, indicating that both streptospirodienoic acids and bafilomycins were derived from the same blm BGC. Additionally, sequence analysis revealed that the KR domains of module 2 from blm BGC was B1-type, further supporting the configurations of 1-4. Notably, compounds 3 and 4 displayed significant cytotoxic activities against A-549 human non-small cell lung cancer cells and HCT-116 human colon cancer cells.

Single-chain fluorescent integrators for mapping G-protein-coupled receptor agonists.

G protein-coupled receptors (GPCRs) transduce the effects of many neuromodulators including dopamine, serotonin, epinephrine, acetylcholine, and opioids. The localization of synthetic or endogenous GPCR agonists impacts their action on specific neuronal pathways. In this paper, we show a series of single-protein chain integrator sensors that are highly modular and could potentially be used to determine GPCR agonist localization across the brain. We previously engineered integrator sensors for the mu- and kappa-opioid receptor agonists called M- and K-Single-chain Protein-based Opioid Transmission Indicator Tool (SPOTIT), respectively. Here, we engineered red versions of the SPOTIT sensors for multiplexed imaging of GPCR agonists. We also modified SPOTIT to create an integrator sensor design platform called SPOTIT for all GPCRs (SPOTall). We used the SPOTall platform to engineer sensors for the beta 2-adrenergic receptor (B2AR), the dopamine receptor D1, and the cholinergic receptor muscarinic 2 agonists. Finally, we demonstrated the application of M-SPOTIT and B2AR-SPOTall in detecting exogenously administered morphine, isoproterenol, and epinephrine in the mouse brain via locally injected viruses. The SPOTIT and SPOTall sensor design platform has the potential for unbiased agonist detection of many synthetic and endogenous neuromodulators across the brain.

Short-term effectiveness and potential factors of ustekinumab based on real-world data in Chinese psoriasis patients.

BACKGROUND: As one of the most effective biologic treatments for psoriasis, the short-term effectiveness of ustekinumab has yet to be studied extensively. OBJECTIVE: The purpose of this study was to evaluate the short-term effectiveness and potential factors within four weeks after the first-dose ustekinumab treatment based on real-world data. METHODS: The study enrolled 98 patients with moderate-to-severe psoriasis, given ustekinumab 45 mg at week 0, week 4, and then every 12 weeks. Based on clinical data collected at baseline and week 4, we investigated the short-term effectiveness of ustekinumab after the first dose and potential factors associated with the treatment. For evaluation, we collected demographic information, body data, medical history, laboratory examination results, Psoriasis Area and Severity Index (PASI), body surface area (BSA), and dermatology life quality index (DLQI). Response rates were calculated based on the number of patients that achieved a 75/90/100% reduction in PASI (PASI 75/90/100), and the primary treatment goal was to achieve PASI 75. RESULTS: The response rates for PASI 75/90/100 at week 4 were 30.5%, 18.9%, and 16.8%, respectively. For PASI 75, the response rate was higher in patients without metabolic syndrome (MS) (without MS vs. with MS: 36.9% vs. 5.9%, p = 0.013); the serum triglyceride (TG) level was significantly lower in patients achieving PASI 75 (expressed as mean ± standard deviation, achieved vs. unachieved: 1.82 ± 1.79 vs. 3.59 ± 8.89, p = 0.010). For PASI 100, the response rates were higher in female patients (female vs. male: 26.3% vs. 10.5%, p = 0.044) and patients with a family history of psoriasis (with family history vs. without family history: 44.4% vs. 13.9%, p = 0.042). In addition, the possibility of achieving PASI 75/90/100 went up along with the serum high-density lipoprotein cholesterol (HDL-C) level (expressed as adjusted odds ratio < 95% confidence interval>: PASI 75: 28.484 < 2.035-248.419>, p = 0.011; PASI 90: 28.226 < 2.828-281.729>, p = 0.004; PASI 100: 12.175 < 1.876-79.028>, p = 0.009). CONCLUSION: In this study, nearly one-third of patients achieved PASI 75 after only the first-dose ustekinumab treatment. Sex, family history of psoriasis, MS, serum TG level might affect the short-term effectiveness, and serum HDL-C level may be a potential factor. The possibility of achieving treatment goals (PASI 75/90/100) at week 4 increased along with serum HDL-C levels.