AI-MARRVEL - A Knowledge-Driven AI System for Diagnosing Mendelian Disorders.

BACKGROUND: Diagnosing genetic disorders requires extensive manual curation and interpretation of candidate variants, a labor-intensive task even for trained geneticists. Although artificial intelligence (AI) shows promise in aiding these diagnoses, existing AI tools have only achieved moderate success for primary diagnosis. METHODS: AI-MARRVEL (AIM) uses a random-forest machine-learning classifier trained on over 3.5 million variants from thousands of diagnosed cases. AIM additionally incorporates expert-engineered features into training to recapitulate the intricate decision-making processes in molecular diagnosis. The online version of AIM is available at https://ai.marrvel.org. To evaluate AIM, we benchmarked it with diagnosed patients from three independent cohorts. RESULTS: AIM improved the rate of accurate genetic diagnosis, doubling the number of solved cases as compared with benchmarked methods, across three distinct real-world cohorts. To better identify diagnosable cases from the unsolved pools accumulated over time, we designed a confidence metric on which AIM achieved a precision rate of 98% and identified 57% of diagnosable cases out of a collection of 871 cases. Furthermore, AIM's performance improved after being fine-tuned for targeted settings including recessive disorders and trio analysis. Finally, AIM demonstrated potential for novel disease gene discovery by correctly predicting two newly reported disease genes from the Undiagnosed Diseases Network. CONCLUSIONS: AIM achieved superior accuracy compared with existing methods for genetic diagnosis. We anticipate that this tool may aid in primary diagnosis, reanalysis of unsolved cases, and the discovery of novel disease genes. (Funded by the NIH Common Fund and others.).

Spatiotemporal patterns and co-occurrence patterns of dissimilatory nitrate reduction to ammonium community in sediments of the Lancang River cascade reservoirs.

Dissimilatory nitrate reduction to ammonium (DNRA) is an important nitrate reduction pathway in freshwater sediments. Many studies have focused on the DNRA process in various natural habitats. However, the joint operation of cascade reservoirs will affect the physical and chemical properties of sediments, which may change the DNRA process and bacterial community pattern in the surface sediments of cascade reservoirs. Our study was the first to investigate the spatiotemporal distribution patterns of potential DNRA rate, nrfA gene abundances, and DNRA bacterial community diversity in surface sediments of the Lancang River cascade reservoirs. The results of slurry incubation experiments combined with the 15N isotope tracer experiment ascertained that the potential rates of DNRA were 0.01-0.15 nmol-N cm-3 h-1, and qPCR results indicated that the abundance range of nrfA was 1.08 × 105-2.51 × 106 copies g-1 dry weight. High throughput sequencing of the nrfA gene revealed that the relative abundance of Anaeromyxobacter (4.52% on average), Polyangium (4.09%), Archangium (1.86%), Geobacter (1.34%), and Lacunisphaera (1.32%) were high. Pearson and RDA correlation analysis exhibited that nrfA gene abundance was positively correlated with altitude, pH, OC, and sand concentration. Anaeromyxobacter was positively correlated with reservoir age and DNRA potential rate. The deterministic environmental selection process plays a crucial role in the formation of the DNRA bacterial community. Network analysis displayed that the dominant DNRA genus was the key population of the DNRA microbial community in the sediments of Lancang River cascade reservoirs. This study reveals that the variation of DNRA bacterial activity and community structure is largely driven by the construction of cascade reservoirs, and provides a new idea for further understanding the characteristics of the DNRA community in the cascade reservoir ecosystem.

Microplastics emerge as a hotspot for dibutyl phthalate sources in rivers and oceans: Leaching behavior and potential risks.

Dibutyl phthalate (DBP) as a plasticizer has been widely used in the processing of plastic products. Nevertheless, these DBP additives have the potential to be released into the environment throughout the entire life cycle of plastic products. Herein, the leaching behavior of DBP from PVC microplastics (MPs) in freshwater and seawater and its potential risks were investigated. The results show that the plasticizer content, UV irradiation, and hydrochemical conditions have a great influence on the leaching of DBP from the MPs. The release of DBP into the environment increases proportionally with higher concentrations of additive DBP in MPs, particularly when it exceeds 15 %. The surface of MPs undergoes accelerated oxidation and increased hydrophilicity under UV radiation, thereby facilitating the leaching of DBP. Through 30 continuous leaching experiments, the leaching of DBP from MPs in freshwater and seawater can reach up to 12.28 and 5.42 mg g-1, respectively, indicating that MPs are a continuous source of DBP pollution in the aquatic environment. Moreover, phthalate pollution index (PPI) indicates that MPs can significantly increase DBP pollution in marine environment through land and sea transport processes. Therefore, we advocate that the management of MPs waste containing DBP be prioritized in coastal sustainable development.

The Role of Oxygen Vacancies in Phase Transition and the Optical Absorption Properties within Nanocrystalline ZrO2.

Zirconia (ZrO2) nanoparticles were synthesized using a solvothermal method under varying synthesis conditions, namely acidic, neutral, and alkaline. X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) were leveraged to investigate the phase evolution and topographical features in detail. The resulting crystal phase structures and grain sizes exhibited substantial variation based on these conditions. Notably, the acidic condition fostered a monoclinic phase in ZrO2, while the alkaline condition yielded a combination of tetragonal and monoclinic phases. In contrast, ZrO2 obtained under neutral conditions demonstrated a refinement in grain sizes, constrained within a 1 nm scale upon an 800 °C thermal treatment. This was accompanied by an important transformation from a monoclinic phase to tetragonal phase in the ZrO2. Furthermore, a rigorous examination of XPS data and a UV-visible spectrometer (UV-vis) analysis revealed the significant role of oxygen vacancies in phase stabilization. The notable emergence of new energy bands in ZrO2, in stark contrast to the intrinsic bands observed in a pure monoclinic sample, are attributed to these oxygen vacancies. This research offers valuable insights into the novel energy bands, phase stability, and optical absorption properties influenced by oxygen vacancies in ZrO2. Moreover, it proposes an innovative energy level model for zirconia, underpinning its applicability in diverse technological areas.

Large-Scale Multiobjective Evolutionary Algorithm Guided by Low-Dimensional Surrogates of Scalarization Functions.

Recently, computationally intensive multiobjective optimization problems have been efficiently solved by surrogate-assisted multiobjective evolutionary algorithms. However, most of those algorithms can only handle no more than 200 decision variables. As the number of decision variables increases further, unreliable surrogate models will result in a dramatic deterioration of their performance, which makes large-scale expensive multiobjective optimization challenging. To address this challenge, we develop a large-scale multiobjective evolutionary algorithm guided by low-dimensional surrogate models of scalarization functions. The proposed algorithm (termed LDS-AF) reduces the dimension of the original decision space based on principal component analysis, and then directly approximates the scalarization functions in a decompositionbased multiobjective evolutionary algorithm. With the help of a two-stage modeling strategy and convergence control strategy, LDS-AF can keep a good balance between convergence and diversity, and achieve a promising performance without being trapped in a local optimum prematurely. The experimental results on a set of test instances have demonstrated its superiority over eight state-of-the-art algorithms on multiobjective optimization problems with up to 1000 decision variables using only 500 real function evaluations.

Risk factors influencing postoperative outcome of arthroscopic rotator cuff repair and construction of a nomogram prediction model.

OBJECTIVE: To investigate the risk factors influencing the postoperative outcome of arthroscopic rotator cuff repair (ARCR) and develop a nomogram prediction model. METHODS: A retrospective study was conducted on 302 patients who underwent ARCR from January 2019 to August 2023. Patients were categorized into two groups: a control group with 150 patients showing good recovery and an observation group with 152 patients exhibiting poor recovery. Relevant clinical data were collected and statistically analyzed. A nomogram model was constructed based on the results of multivariate logistic regression analysis. The model's accuracy, discrimination, and clinical utility were evaluated using calibration charts, AUC, c-index, and decision curve analysis. Internal validation was performed through self-random sampling. RESULTS: Univariate and multivariate regression analysis identified having a frozen shoulder, large rotator cuff tear, increased intraoperative rivet use, diabetes, and traumatic tear as predictive risk factors for poor postoperative outcomes. These factors were utilized to develop a clinical predictive nomogram. The nomogram model demonstrated excellent predictive accuracy for poor postoperative outcomes, both internally and externally. The unadjusted concordance index (C-index) was 0.793 [95% confidence interval (CI), 0.825-0.995]. The AUC for the nomogram was 0.788. Decision curve analysis revealed that the predictive model was clinically useful when the threshold probability ranged from 20 to 60%. CONCLUSION: The presence of a frozen shoulder, large rotator cuff tear, increased intraoperative rivet use, diabetes, and traumatic tear elevate the risk of suboptimal outcomes following ARCR. Conversely, having a higher preoperative University of California at Los Angeles Shoulder Rating Scale score mitigates this risk. This study introduces a novel nomogram model, exhibiting relatively high accuracy, which enables clinicians to precisely assess the postoperative adverse risk among patients with rotator cuff injuries requiring arthroscopic repair at the outset of treatment.

Efficient biodegradation of chlorobenzene via monooxygenation pathways by Pandoraea sp. XJJ-1 with high potential for groundwater bioremediation.

Chlorobenzene (CB), extensively used in industrial processes, has emerged as a significant contaminant in soil and groundwater. The eco-friendly and cost-effective microbial remediation has been increasingly favored to address this environmental challenge. In this study, a degrading bacterium was isolated from CB-contaminated soil at a pesticide plant, identified as Pandoraea sp. XJJ-1 (CCTCC M 2021057). This strain completely degraded 100 mg·L-1 CB and showed extensive degradability across a range of pH (5.0-9.0), temperature (10-37 °C), and CB concentrations (100-600 mg·L-1). Notably, the degradation efficiency was 85.2% at 15 °C, and the strain could also degrade six other aromatic hydrocarbons, including benzene, toluene, ethylbenzene, and xylene (o-, m-, p-). The metabolic pathway of CB was inferred using ultraperformance liquid chromatography, gas chromatography-mass spectrometry, and genomic analysis. In strain XJJ-1, CB was metabolized to o-chlorophenol and 3-chloroxychol by CB monooxygenase, followed by ortho-cleavage by the action of 3-chlorocatechol 1,2-dioxygenase. Moreover, the presence of the chlorobenzene monooxygenation pathway metabolism in strain XJJ-1 is reported for the first time in Pandoraea. As a bacterium with low-temperature resistance and composite pollutant degradation capacity, strain XJJ-1 has the potential application prospects in the in-situ bioremediation of CB-contaminated sites.

Error-Reduced Digital Elevation Model of the Qinghai-Tibet Plateau using ICESat-2 and Fusion Model.

The Qinghai-Tibet Plateau (QTP) holds significance for investigating Earth's surface processes. However, due to rugged terrain, forest canopy, and snow accumulation, open-access Digital Elevation Models (DEMs) exhibit considerable noise, resulting in low accuracy and pronounced data inconsistency. Furthermore, the glacier regions within the QTP undergo substantial changes, necessitating updates. This study employs a fusion of open-access DEMs and high-accuracy photons from the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2). Additionally, snow cover and canopy heights are considered, and an ensemble learning fusion model is presented to harness the complementary information in the multi-sensor elevation observations. This innovative approach results in the creation of HQTP30, the most accurate representation of the 2021 QTP terrain. Comparative analysis with high-resolution imagery, UAV-derived DEMs, control points, and ICESat-2 highlights the advantages of HQTP30. Notably, in non-glacier regions, HQTP30 achieved a Mean Absolute Error (MAE) of 0.71 m, while in glacier regions, it reduced the MAE by 4.35 m compared to the state-of-the-art Copernicus DEM (COPDEM), demonstrating its versatile applicability.

Circulating Small Extracellular Vesicles Involved in Systemic Regulation Respond to RGC Degeneration in Glaucoma.

Glaucoma is a leading cause of irreversible blindness worldwide and is characterized by progressive retinal ganglion cell (RGC) degeneration and vision loss. Since irreversible neurodegeneration occurs before diagnosable, early diagnosis and effective neuroprotection are critical for glaucoma management. Small extracellular vesicles (sEVs) are demonstrated to be potential novel biomarkers and therapeutics for a variety of diseases. In this study, it is found that intravitreal injection of circulating plasma-derived sEVs (PDEV) from glaucoma patients ameliorated retinal degeneration in chronic ocular hypertension (COH) mice. Moreover, it is found that PDEV-miR-29s are significantly upregulated in glaucoma patients and are associated with visual field defects in progressed glaucoma. Subsequently, in vivo and in vitro experiments are conducted to investigate the possible function of miR-29s in RGC pathophysiology. It is showed that the overexpression of miR-29b-3p effectively prevents RGC degeneration in COH mice and promotes the neuronal differentiation of human induced pluripotent stem cells (hiPSCs). Interestingly, engineered sEVs with sufficient miR-29b-3p delivery exhibit more effective RGC protection and neuronal differentiation efficiency. Thus, elevated PDEV-miR-29s may imply systemic regulation to prevent RGC degeneration in glaucoma patients. This study provides new insights into PDEV-based glaucoma diagnosis and therapeutic strategies for neurodegenerative diseases.

Progress of researches on mechanisms of acupuncture for secondary prevention of ischemic stroke. / é’ˆåˆºå‚ä¸Žç¼ºè¡€æ€§è„‘å’ä¸­äºŒçº§é¢„é˜²çš„ç ”ç©¶è¿›å±•.

Ischemic stroke (IS) is one of the main causes inducing death and disability in adults. Because of the high recurrence rate of IS, prevention of recurrence is of great significance to this population, for which the evidence-based and effective secondary prevention strategy is an important means, and acupuncture intervention has a positive effect on its risk factors. In the present article, we reviewed the progress of researches on the mechanisms of acupuncture underlying prevention of IS relapse from the perspective of its main risk factors, namely 1) hypertension (preventing and controlling the adverse effects caused by the imbalance of blood pressure level, vascular and other tissue structures, endocrine factors and central nervous system activities in patients with hypertension after IS), 2) hypercholesterolemia (lowering serum total cholesterol, triglyceride, low-density lipoprotein-cholesterol (LDL-C) and raising high-density lipoprotein cholesterol), 3) diabetes (regulating the secretion function of adipose tissue, activating the insulin signal transduction pathway, protecting the function of pancreatic ß cells, and regulating the central nervous system functions to participate in the secondary prevention of IS), 4) smoking (relieving the symptoms of smoking cessation and reducing the smoker's dependence on smoking by changing the internal environment, lowering the level of blood endorphin and regulating the excitability of central nervous system), 5) sleep apnea syndrome (regulating local muscle function and the excitability of the nervous system, but also affecting some organic changes as reducing tonsil swelling) and 6) obesity (lowering blood glucose and lipid, increasing the ratio of brown/white fat, reducing leptin resistance, and suppressing appetite to induce body weight loss, or directly regulate the changes of fat tissue, etc). Results shows that the acupuncture's regulatory mechanism for IS risk factors is closely related to the neuroendocrine system, and simultaneously involves multiple targets of multiple risk factors. Due to its good efficacy and safety, acupuncture therapy is of great value for clinical promotion as an important intervention for secondary prevention.

Co-Exploring Structured Sparsification and Low-Rank Tensor Decomposition for Compact DNNs.

Sparsification and low-rank decomposition are two important techniques to compress deep neural network (DNN) models. To date, these two popular yet distinct approaches are typically used in separate ways; while their efficient integration for better compression performance is little explored, especially for structured sparsification and decomposition. In this article, we perform systematic co-exploration on structured sparsification and decomposition toward compact DNN models. We first investigate and analyze several important design factors for joint structured sparsification and decomposition, including operational sequence, decomposition format, and optimization procedure. Based on the observations from our analysis, we then propose CEPD, a unified DNN compression framework that can co-explore the benefits of structured sparsification and tensor decomposition in an efficient way. Empirical experiments demonstrate the promising performance of our proposed solution. Notably, on the CIFAR-10 dataset, CEPD brings 0.72%-0.45% accuracy increase over the baseline ResNet-56 and MobileNetV2 models, respectively, and meanwhile, the computational costs are reduced by 43.0%-44.2%, respectively. On the ImageNet dataset, our approach can enable 0.10%-1.39% accuracy increase over the baseline ResNet-18 and ResNet-50 models with 59.4%-54.6% fewer parameters, respectively.

Combining metabolomics with network pharmacology to reveal the therapeutic mechanism of Dingchuan Decoction in rats with OVA-induced allergic asthma.

Dingchuan Decoction (DCD) is a traditional Chinese medicine prescription commonly used in the treatment of asthma, but the mechanism of DCD in treating asthma has not yet been determined. In this study, we employed a combination of metabolomics and network pharmacology to investigate the mechanism of DCD in treating asthma. An allergic asthma rat model was induced by ovalbumin (OVA). Metabolomics based on 1H NMR and UHPLC-MS was used to identify differential metabolites and obtain the major metabolic pathways and potential targets. Network pharmacology was utilized to explore potential targets of DCD for asthma treatment. Finally, the results of metabolomics and network pharmacology were integrated to obtain the key targets and metabolic pathways of DCD for the therapy of asthma, and molecular docking was utilized to validate the key targets. A total of 76 important metabolites and 231 potential targets were identified through metabolomics. Using network pharmacology, 184 potential therapeutic targets were obtained. These 184 targets were overlaid with the 231 potential targets obtained through metabolomics and were analyzed in conjunction with metabolic pathways. Ultimately, the key targets were identified as aldehyde dehydrogenase 2 (ALDH2) and amine oxidase copper-containing 3 (AOC3), and the relevant metabolic pathways affected were glycolysis and gluconeogenesis as well as arginine and proline metabolism. Molecular docking showed that the key targets had high affinity with the relevant active ingredients in DCD, which further demonstrated that DCD may exert therapeutic effects by acting on the key targets. The present study demonstrated that DCD can alleviate OVA-induced allergic asthma and that DCD may have a therapeutic effect by regulating intestinal flora and polyamine metabolism through its effects on ALDH2 and AOC3.

Engineering of a Baeyer-Villiger monooxygenase to Improve Substrate Scope, Stereoselectivity and Regioselectivity.

Baeyer-Villiger monooxygenases belong to a family of flavin-binding proteins that catalyze the Baeyer-Villiger (BV) oxidation of ketones to produce lactones or esters, which are important intermediates in pharmaceuticals or sustainable materials. Phenylacetone monooxygenase (PAMO) from Thermobifida fusca with moderate thermostability catalyzes the oxidation of aryl ketone substrates, but is limited by high specificity and narrow substrate scope. In the present study, we applied loop optimization by loop swapping followed by focused saturation mutagenesis in order to evolve PAMO mutants capable of catalyzing the regioselective BV oxidation of cyclohexanone and cyclobutanone derivatives with formation of either normal or abnormal esters or lactones. We further modulated PAMO to increase enantioselectivity. Crystal structure studies indicate that rotation occurs in the NADP-binding domain and that the high B-factor region is predominantly distributed in the catalytic pocket residues. Computational analyses further revealed dynamic character in the catalytic pocket and reshaped hydrogen bond interaction networks, which is more favorable for substrate binding. Our study provides useful insights for studying enzyme-substrate adaptations.

The C2 isthmus screw provided sufficient biomechanical stability in the setting of atlantoaxial dislocation-a finite element study.

BACKGROUND: The emerging of the C2 isthmus screw fixation technique is gaining popularity in the setting of atlantoaxial dislocation or other conditions requiring fixation of C2. However, the biomechanical stability of this fixation is poorly understood. PURPOSE: To compare and elucidate the biomechanical stability of C2 pedicle screw (C2PS), C2 isthmus screw (C2IS) and C2 short isthmus screw (C2SIS) fixation techniques in atlantoaxial dislocation (AAD). METHOD: A three-dimensional finite element model (FEM) from occiput to C3 was established and validated from a healthy male volunteer. Three FEMs, C1 pedicle screw (PS)-C2PS, C1PS-C2IS, C1PS-C2SIS were also constructed. The range of motion (ROM) and the maximum von Mises stress under flexion, extension, lateral bending and axial rotation loading were analyzed and compared. The pullout strength of the three fixations for C2 was also evaluated. RESULT: C1PS-C2IS model showed the greatest decrease in ROM with flexion, extension, lateral bending and axial rotation. C1PS-C2PS model showed the least ROM reduction under all loading conditions than both C2IS and C2SIS. The C1PS-C2PS model had the largest von Mises stress on the screw under all directions followed by C1PS-C2SIS, and lastly the C1PS-C2IS. Under axial rotation and lateral bending loading, the three models showed the maximum and minimum von Mises stress on the screw respectively. The stress of the three models was mainly located in the connection of the screw and rod. Overall, the maximum screw pullout strength for C2PS, C2IS and C2SIS were 729.41N, 816.62N, 640.54N respectively. CONCLUSION: In patients with atlantoaxial dislocations, the C2IS fixation provided comparable stability, with no significant stress concentration. Furthermore, the C2IS had sufficient pullout strength when compared with C2PS and C2SIS. C2 isthmus screw fixation may be a biomechanically favourable option in cases with AAD. However, future clinical trials are necessary for the evaluation of the clinical outcomes of this technique.

Electro-scalp acupuncture regulates the expression of CYP27a1/b1, CYP24a and related inflammatory cytokines in ischemic cortex of rats with middle cerebral artery occlusion. / ç”µå¤´é’ˆè°ƒæŽ§å¤§è„‘ä¸­åŠ¨è„‰æ “å¡žå¤§é¼ ç¼ºè¡€å¤§è„‘çš®å±‚åŒºCYP27a1/b1、CYP24aåŠç›¸å ³ç‚Žæ€§ç»†èƒžå› å­è¡¨è¾¾çš„ç ”ç©¶.

OBJECTIVES: To observe the effect of electro-scalp acupuncture (ESA) on the expression of cytochrome P450a1/b1 (CYP27a1/b1), cytochrome P45024a (CYP24a), signal transducer and activator of transcription (STAT)4, STAT6, tumor necrosis factor-α (TNF-α), interleukin (IL)-1ß and IL-4 in ischemic cerebral cortex of rats with acute ischemic stroke, so as to explore its mechanism in alleviating inflammatory reaction of ischemic stroke. METHODS: Sixty SD rats were randomly divided into sham-operation, model, vitamin D3 and ESA groups, with 15 rats in each group. The middle cerebral artery occlusion rat model was established with thread ligation according to Zea-Longa's method. Rats in the vitamin D3 group were given 1, 25-VitD3 solution (3 ng·100 g-1·d-1) by gavage, once daily for 7 days. Rats in the ESA group were treated at bilateral anterior parietotemporal slash (MS6) with ESA (2 Hz/100 Hz, 1 mA), 30 min a day for 7 days. Before and after interventions, the neurological deficit score and neurobehavioral score were evaluated. TTC staining was used to detect the volume of cerebral infarction in rats. The positive expressions of CYP24a, CYP27a1 and CYP27b1 in the cerebral cortex of ischemic area were detected by immunofluorescence. The mRNA expressions of STAT4 and STAT6 in the cerebral cortex of ischemic area were detected by quantitative real-time PCR. The protein expression levels of TNF-α, IL-1ß and IL-4 in the cerebral cortex of ischemic area were detected by Western blot. RESULTS: Compared with the sham-operation group, the neurological deficit score, neurobehavioral score, the percentage of cerebral infarction volume, the positive expression level of CYP24a and mRNA expression level of STAT4, protein expression levels of TNF-α and IL-1ß in cerebral cortex were increased (P<0.01), while the positive expression levels of CYP27a1/b1 and STAT6 mRNA, protein expression level of IL-4 were decreased (P<0.01) in the model group. After the treatment and compared with the model group, the neurological deficit score, neurobehavioral score, the percentage of cerebral infarction volume, the positive expression level of CYP24a and mRNA expression level of STAT4, protein expression levels of TNF-α and IL-1ß in cerebral cortex were decreased (P<0.01), while the positive expression levels of CYP27a1/b1 and STAT6 mRNA expression level, protein expression level of IL-4 were increased (P<0.01) in the ESA and vitamin D3 groups. CONCLUSIONS: ESA can alleviate the inflammatory response in ischemic stroke, which maybe related to its function in regulating the balance between CYP27a1/b1 and CYP24a, converting vitamin D into active vitamin D3, inhibiting vitamin D3 degradation, and regulating Th1/Th2 balance.

Implications of the Propagation Method for the Phytochemistry of Nepeta cataria L. throughout a Growing Season.

Catnip (Nepeta cataria L.) plants produce a wide array of specialized metabolites with multiple applications for human health. The productivity of such metabolites, including nepetalactones, and natural insect repellents is influenced by the conditions under which the plants are cultivated. In this study, we assessed how field-grown catnip plants, transplanted after being propagated via either single-node stem cuttings or seeds, varied regarding their phytochemical composition throughout a growing season in two distinct environmental conditions (Pittstown and Upper Deerfield) in the state of New Jersey, United States. Iridoid terpenes were quantified in plant tissues via ultra-high-performance liquid chromatography with triple quadrupole mass spectrometry (UHPLC-QqQ-MS), and phenolic compounds (phenolic acids and flavonoids) were analyzed via UHPLC with diode-array detection (UHPLC-DAD). The highest contents of total nepetalactones in Pittstown were found at 6 weeks after transplanting (WAT) for both seedlings and cuttings (1305.4 and 1223.3 mg/100 g, respectively), while in Upper Deerfield, the highest contents for both propagules were at 11 WAT (1247.7 and 997.1 mg/100 g, respectively) for seed-propagated and stem cuttings). The highest concentration of nepetalactones was associated with floral-bud to partial-flowering stages. Because plants in Pittstown accumulated considerably more biomass than plants grown in Upper Deerfield, the difference in nepetalactone production per plant was striking, with peak productivity reaching only 598.9 mg per plant in Upper Deerfield and 1833.1 mg per plant in Pittstown. Phenolic acids accumulated in higher contents towards the end of the season in both locations, after a period of low precipitation, and flavone glycosides had similar accumulation patterns to nepetalactones. In both locations, rooted stem cuttings reached their maximum nepetalactone productivity, on average, four weeks later than seed-propagated plants, suggesting that seedlings have, overall, better agronomic performance.

C-176 reduces inflammation-induced pain by blocking the cGAS-STING pathway in microglia.

OBJECTIVE: Inflammatory pain, is caused by lesions or diseases of the somatosensory tissue, is a prevalent chronic condition that profoundly impacts the quality of life. However, clinical treatment for this type of pain remains limited. Traditionally, the stimulation of microglia and subsequent inflammatory reactions are considered crucial elements to promote the worsening of inflammatory pain. Recent research has shown the crucial importance of the cGAS-STING pathway in promoting inflammation. It is still uncertain if the cGAS-STING pathway plays the role in the fundamental cause of inflammatory pain. We aim to explore the treatment of inflammatory pain by interfering with cGAS-STING signaling pathway. METHODS: In this study, we established an inflammatory pain model by CFA into the plantar of mice. Activation of microglia, various inflammatory factors and cGAS-STING protein in the spinal dorsal horn were evaluated. Immunofluorescence staining was used to observe the cellular localization of cGAS and STING. The cGAS-STING pathway proteins expression and mRNA expression of indicated microglial M1/M2 phenotypic markers in the BV2 microglia were detected. STING inhibitor C-176 was intrathecal injected into mice with inflammatory pain, and the pain behavior and microglia were observed. RESULTS: This research showed that injecting CFA into the left hind paw of mice caused mechanical allodynia and increased inflammation in the spine. Our research results suggested that the cGAS-STING pathway had a function in the inflammation mediated by microglia in the spinal cord dorsal horn. Blocking the cGAS-STING pathway using STING antagonists (C-176) led to reduced release of inflammatory factors and prevented M1 polarization of BV2 microglia in a laboratory setting. Additionally, intrathecal administration of C-176 reduced the allodynia in CFA treated mice. CONCLUSION: Our results suggest that inhibiting microglial polarization through the cGAS-STING pathway represents a potential novel therapeutic strategy for inflammatory pain.

Learning At a Glance: Towards Interpretable Data-Limited Continual Semantic Segmentation Via Semantic-Invariance Modelling.

Continual semantic segmentation (CSS) based on incremental learning (IL) is a great endeavour in developing human- like segmentation models. However, current CSS approaches encounter challenges in the trade-off between preserving old knowledge and learning new ones, where they still need large-scale annotated data for incremental training and lack interpretability. In this paper, we present Learning at a Glance (LAG), an efficient, robust, human- like and interpretable approach for CSS. Specifically, LAG is a simple and model-agnostic architecture, yet it achieves competitive CSS efficiency with limited incremental data. Inspired by human- like recognition patterns, we propose a semantic-invariance modelling approach via semantic features decoupling that simultaneously reconciles solid knowledge inheritance and new-term learning. Concretely, the proposed decoupling manner includes two ways, i.e., channel- wise decoupling and spatial-level neuron-relevant semantic consistency. Our approach preserves semantic-invariant knowledge as solid prototypes to alleviate catastrophic forgetting, while also constraining sample-specific contents through an asymmetric contrastive learning method to enhance model robustness during IL steps. Experimental results in multiple datasets validate the effectiveness of the proposed method. Furthermore, we introduce a novel CSS protocol that better reflects realistic data-limited CSS settings, and LAG achieves superior performance under multiple data-limited conditions.

Amygdala neuronal dyshomeostasis via 5-HT receptors mediates mood and cognitive defects in Alzheimer's disease.

Behavioral changes or neuropsychiatric symptoms (NPSs) are common features in dementia and are associated with accelerated cognitive impairment and earlier deaths. However, how NPSs are intertwined with cognitive decline remains elusive. In this study, we identify that the basolateral amygdala (BLA) is a key brain region that is associated with mood disorders and memory decline in the AD course. During the process from pre- to post-onset in AD, the dysfunction of parvalbumin (PV) interneurons and pyramidal neurons in the amygdala leads to hyperactivity of pyramidal neurons in the basal state and insensitivity to external stimuli. We further demonstrate that serotonin (5-HT) receptors in distinct neurons synergistically regulate the BLA microcircuit of AD rather than 5-HT levels, in which both restrained inhibitory inputs by excessive 5-HT1AR signaling in PV interneurons and depolarized pyramidal neurons via upregulated 5-HT2AR contribute to aberrant neuronal hyperactivity. Downregulation of these two 5-HT receptors simultaneously enables neurons to resist ß-amyloid peptides (Aß) neurotoxicity and ameliorates the mood and cognitive defects. Therefore, our study reveals a crucial role of 5-HT receptors for regulating neuronal homeostasis in AD pathogenesis, and this would provide early intervention and potential targets for AD cognitive decline.