Ultrasound pretreatment enhances moisture migration and drying quality of mulberry via microstructure and cell-wall polysaccharides nanostructure modification.

The effects of ultrasound pretreatment (20 kHz, 30 W/L) on mulberries' texture, microstructure, characteristics of cell-wall polysaccharides, moisture migration, and drying quality were investigated over exposure times ranging from 15 to 45 min. Ultrasound induced softening of mulberry tissue, accompanied by an increase in water-soluble pectin and a decrease in chelate-soluble pectin and Na2CO3-soluble pectin concentrations. Noticeable depolymerization of the pectin nanostructure was observed in the pretreated mulberries, along with a decrease in molecular weight, attributed to side-chain structure cleavage. Ultrasound loosened the cell wall structure, increased free water content and freedom, thereby reducing water diffusion resistance. Ultrasound pretreatment reduced drying time by 11.2 % to 23.3 % at various processing times compared to controls. Due to significantly enhanced drying efficiency, the optimal pretreatment time (30 min) yielded dried mulberries with higher levels of total phenolics and total anthocyanins, along with an increased antioxidant capacity. The results of this study provide insights into the mechanisms by which ultrasound pretreatment can effectively enhance the mulberry drying process.

Effect of various different pretreatment methods on infrared combined hot air impingement drying behavior and physicochemical properties of strawberry slices.

In current work, the effect of freezing (F), ultrasound (U), and freeze- ultrasound (FU) pretreatment on infrared combined with hot air impingement drying kinetics, cell ultrastructure, enzyme activity, and physicochemical properties of strawberry slices were explored. Results showed that FU pretreatment enhanced cell membrane permeability via forming micropores, altered water status by transforming bound water into free water and thus promoted moisture diffusivity and decreased drying time by 50% compared to the control group. FU pretreatment also extensively decreased pectin methylesterase enzyme activity and maintained quality. The contents of total phenols, anthocyanins, vitamin C, antioxidant activity, and a* value of dried strawberries pretreated by FU were extensively increased compared to the control group. U and FU pretreatments were beneficial for retaining aromatic components and organic sulfides according to e-nose analyses. The findings indicate that FU is a promising pretreatment technique as it enhances drying process and quality of strawberry slices.

A direct electrochemical sensor based on covalent organic frameworks/platinum nanoparticles for the detection of ofloxacin in water.

A direct electrochemical sensor based on covalent organic frameworks (COFs)/platinum nanoparticles (PtNPs) composite was fabricated for the detection of ofloxacin (OFX) in water. Firstly, the COF material was synthesized via the condensation reaction of 1,3,5-tris(4-aminophenyl)benzene (TAPB) with terephthalaldehyde (TPA) and integrated with PtNPs by in situ reduction. Then, TAPB-TPA-COFs/PtNPs composite was loaded onto the surface of the glassy carbon electrode (GCE) by drip coating to construct the working electrode (TAPB-TPA-COFs/PtNPs/GCE). The electrochemical performance of TAPB-TPA-COFs/PtNPs/GCE showed a significant improvement compared with that of TAPB-TPA-COFs/GCE, leading to a 3.2-fold increase in the electrochemical signal for 0.01 mM OFX. Under optimal conditions, the TAPB-TPA-COFs/PtNPs/GCE exhibited a wide linear range of 9.901 × 10-3-1.406 µM and 2.024-15.19 µM with a detection limit of 2.184 × 10-3 µM. The TAPB-TPA-COFs/PtNPs/GCE-based electrochemical sensor with excellent performance provides great potential for the rapid and trace detection of residual OFX.

Gait classification for early detection and severity rating of Parkinson's disease based on hybrid signal processing and machine learning methods.

Parkinson's disease (PD) is one of the cognitive degenerative disorders of the central nervous system that affects the motor system. Gait dysfunction represents the pathology of motor symptom while gait analysis provides clinicians with subclinical information reflecting subtle differences between PD patients and healthy controls (HCs). Currently neurologists usually assess several clinical manifestations of the PD patients and rate the severity level according to some established criteria. This is highly dependent on clinician's expertise which is subjective and ineffective. In the present study we address these issues by proposing a hybrid signal processing and machine learning based gait classification system for gait anomaly detection and severity rating of PD patients. Time series of vertical ground reaction force (VGRF) data are utilized to represent discriminant gait information. First, phase space of the VGRF is reconstructed, in which the properties associated with the nonlinear gait system dynamics are preserved. Then Shannon energy is used to extract the characteristic envelope of the phase space signal. Third, Shannon energy envelope is decomposed into high and low resonance components using dual Q-factor signal decomposition derived from tunable Q-factor wavelet transform. Note that the high Q-factor component consists largely of sustained oscillatory behavior, while the low Q-factor component consists largely of transients and oscillations that are not sustained. Fourth, variational mode decomposition is employed to decompose high and low resonance components into different intrinsic modes and provide representative features. Finally features are fed to five different types of machine learning based classifiers for the anomaly detection and severity rating of PD patients based on Hohen and Yahr (HY) scale. The effectiveness of this strategy is verified using a Physionet gait database consisting of 93 idiopathic PD patients and 73 age-matched asymptomatic HCs. When evaluated with 10-fold cross-validation method for early PD detection and severity rating, the highest classification accuracy is reported to be 98.20% and 96.69%, respectively, by using the support vector machine classifier. Compared with other state-of-the-art methods, the results demonstrate superior performance and support the validity of the proposed method.

Novel serum biomarker of Golgi protein 73 for the diagnosis of clinically significant portal hypertension in patients with compensated cirrhosis.

Hepatic venous pressure gradient (HVPG) is the gold standard for evaluating clinically significant portal hypertension (CSPH). However, reliable noninvasive methods are limited. Our study aims to investigate the diagnostic value of serum Golgi protein 73 (GP73) for CSPH in patients with compensated cirrhosis. The study enrolled 262 consecutive patients with compensated cirrhosis from three centers in China from February 2021 to September 2023, who underwent both serum GP73 tests and HVPG measurements. CSPH was defined as HVPG ≥ 10 mmHg. Diagnostic accuracy was evaluated using the areas under the receiver operating characteristic curve (AUC). The prevalence of CSPH was 56.9% (n = 149). There were significant differences between the CSPH and non-CSPH groups in the median serum GP73 level (126.8 vs. 73.1 ng/mL, p < 0.001). GP73 level showed a significant positive linear correlation with HVPG (r = 0.459, p < 0.001). The AUC for the diagnosis of CSPH using serum GP73 alone was 0.75 (95% confidence interval [CI] 0.68-0.81). Multivariate logistic regression analysis determined that the levels of GP73, platelets and international normalized ratio were independently associated with CSPH. The combination of these three markers was termed "IP73" score with an AUC value of 0.85 (95% CI 0.80-0.89) for CSPH. Using 0 as a cut-off value, the specificity and sensitivity of IP73 score were 77.9% and 81.9%, respectively. The IP73 score offers a novel, simple and noninvasive method of assessing CSPH in patients with compensated cirrhosis. A cut-off value of the IP73 score at 0 can distinguish patients with or without CSPH.

Effect of the ripening stage on the pulsed vacuum drying behavior of goji berry (Lycium barbarum L.): Ultrastructure, drying characteristics, and browning mechanism.

In current work, the effect of ripening stages (I, II, and III) on pulsed vacuum drying (PVD) behavior of goji berry was explored. The shortest drying time of goji berry was observed at stage I (6.99 h) which was 13.95 %, and 28.85 % shorter than those at stages II, and III, respectively. This phenomenon was closely associated with the ripening stage, as contributed by the initial physiochemical differences, ultrastructure alterations, and moisture distribution. In addition, lower maturity suffered more severe browning, primarily due to the enzymatic and non-enzymatic reactions of phenolics, followed by pigment degradation and the Maillard reaction. Additionally, the PVD process promoted the rupture and transformation of the pectin fractions, also causing browning either directly or indirectly through participation in other chemical reactions. These findings suggest that the appropriate ripening stage of goji berry should be considered as having a significant impact on drying behaviors and quality attributes.

Vacuum-steam pulsed blanching: An emerging method to enhance texture softening, drying behavior and physicochemical properties of Cornus officinalis.

Vacuum steam pulsed blanching (VSPB) was employed as a novel blanching technology on Cornus officinalis to soften the tissue for subsequent coring and dehydration. The current work aims to explore its effect on mass transfer behavior, PPO inactivation, drying characteristics, physicochemical properties, antioxidant capacity, and microstructure of C. officinalis. Results showed that VSPB increased water loss, decreased solid gain, and increased weight reduction with increased blanching cycles. Besides, VSPB significantly changed physical properties and extensively reduced drying time which was attributed to the cell wall components dissolving and cell turgor pressure decreasing, also verified by observing microstructure alteration. PPO was completely denatured after blanching in 6 cycles, but phenolic compounds were still diffused or degraded. Notably, the content of flavonoids and antioxidant capacity significantly increased compared to fresh samples probably due to increased extractability caused by the disrupting cell structure. Besides, the carotenoids and ascorbic acid could be well preserved.

Abnormal white and gray matter functional connectivity is associated with cognitive dysfunction in presbycusis.

Presbycusis is characterized by high-frequency hearing loss and is closely associated with cognitive decline. Previous studies have observed functional reorganization of gray matter in presbycusis, but the information transmission between gray matter and white matter remains ill-defined. Using resting-state functional magnetic resonance imaging, we investigated differences in functional connectivity (GM-GM, WM-WM, and GM-WM) between 60 patients with presbycusis and 57 healthy controls. Subsequently, we examined the correlation between these connectivity differences with high-frequency hearing loss as well as cognitive impairment. Our results revealed significant alterations in functional connectivity involving the body of the corpus callosum, posterior limbs of the internal capsule, retrolenticular region of the internal capsule, and the gray matter regions in presbycusis. Notably, disrupted functional connectivity was observed between the body of the corpus callosum and ventral anterior cingulate cortex in presbycusis, which was associated with impaired attention. Additionally, enhanced functional connectivity was found in presbycusis between the internal capsule and the ventral auditory processing stream, which was related to impaired cognition in multiple domains. These two patterns of altered functional connectivity between gray matter and white matter may involve both bottom-up and top-down regulation of cognitive function. These findings provide novel insights into understanding cognitive compensation and resource redistribution mechanisms in presbycusis.

A Heart Image Segmentation Method Based on Position Attention Mechanism and Inverted Pyramid.

In the realm of modern medicine, medical imaging stands as an irreplaceable pillar for accurate diagnostics. The significance of precise segmentation in medical images cannot be overstated, especially considering the variability introduced by different practitioners. With the escalating volume of medical imaging data, the demand for automated and efficient segmentation methods has become imperative. This study introduces an innovative approach to heart image segmentation, embedding a multi-scale feature and attention mechanism within an inverted pyramid framework. Recognizing the intricacies of extracting contextual information from low-resolution medical images, our method adopts an inverted pyramid architecture. Through training with multi-scale images and integrating prediction outcomes, we enhance the network's contextual understanding. Acknowledging the consistent patterns in the relative positions of organs, we introduce an attention module enriched with positional encoding information. This module empowers the network to capture essential positional cues, thereby elevating segmentation accuracy. Our research resides at the intersection of medical imaging and sensor technology, emphasizing the foundational role of sensors in medical image analysis. The integration of sensor-generated data showcases the symbiotic relationship between sensor technology and advanced machine learning techniques. Evaluation on two heart datasets substantiates the superior performance of our approach. Metrics such as the Dice coefficient, Jaccard coefficient, recall, and F-measure demonstrate the method's efficacy compared to state-of-the-art techniques. In conclusion, our proposed heart image segmentation method addresses the challenges posed by diverse medical images, offering a promising solution for efficiently processing 2D/3D sensor data in contemporary medical imaging.

Peeling mechanism of tomato induced by HHAIB: Microscopic, ultrastructure, chemical, physical and mechanical properties perspectives.

In order to better manage the peeling degree and avoid unnecessary losses, the current work aimed to explore the peeling mechanism of a novel peeling technology, high-humidity hot air impingement blanching (HHAIB). The relationships between HHAIB peeling performance and the changes in skin temperature, skin structure, water state, pectin fractions content, and skin mechanical properties of tomatoes were analyzed. Results showed, after HHAIB treatment, the epicuticular wax was disrupted, the skin exhibited more and longer random cracks, the degradation of inner skin tissue was observed by transmission electron microscopy, the free water percentage increased resulting in water loss in the whole tomato, the water-soluble pectin contents decreased in tomato fleshes, while the contents of chelate-soluble pectin and sodium-carbonate-soluble pectin increased. HHAIB heating reduced the elongation at break, and increased Young's Modulus of tomato peel. This study revealed the HHAIB peeling mechanism and provided new insights for developing HHAIB peeling technology.

Complement receptor 3-mediated neurotoxic glial activation contributes to rotenone-induced cognitive decline in mice.

Microglia-mediated chronic neuroinflammation has been associated with cognitive decline induced by rotenone, a well-known neurotoxic pesticide used in agriculture. However, the mechanisms remain unclear. This work aimed to elucidate the role of complement receptor 3 (CR3), a highly expressed receptor in microglia, in cognitive deficits induced by rotenone. Rotenone up-regulated the expression of CR3 in the hippocampus and cortex area of mice. CR3 deficiency markedly ameliorated rotenone-induced cognitive impairments, neurodegeneration and phosphorylation (Ser129) of α-synuclein in mice. CR3 deficiency also attenuated rotenone-stimulated microglial M1 activation. In microglial cells, siRNA-mediated knockdown of CR3 impeded, while CR3 activation induced by LL-37 exacerbated, rotenone-induced microglial M1 activation. Mechanistically, CR3 deficiency blocked rotenone-induced activation of nuclear factor κB (NF-κB), signal transducer and activator of transcription 1 (STAT1) and STAT3 signaling pathways. Pharmacological inhibition of NF-κB or STAT3 but not STAT1 was confirmed to suppress microglial M1 activation elicited by rotenone. Further study revealed that CR3 deficiency or knockdown also reduced rotenone-induced expression of C3, an A1 astrocyte marker, and production of microglial C1q, TNFα and IL-1α, a cocktail for activated microglia to induce neurotoxic A1 astrocytes, via NF-κB and STAT3 pathways. Finally, a small molecule modulator of CR3 efficiently mitigated rotenone-elicited cognitive deficits in mice even administered after the establishment of cognitive dysfunction. Taken together, our findings demonstrated that CR3 is a key factor in mediating neurotoxic glial activation and subsequent cognitive impairments in rotenone-treated mice, giving novel insights into the immunopathogenesis of cognitive impairments in pesticide-related Parkinsonism.

Pediatric hypertension caused by congenital abdominal aortic stenosis: A case image report.

We confirm that the cause of hypertension in this pediatric patient is congenital abdominal aortic stenosis. This case serves as a reminder to be vigilant for the possibility of congenital vascular abnormalities leading to hypertension in children.

Pediatric restrictive cardiomyopathy: a case report.

Restrictive cardiomyopathy (RCM) is a rare childhood cardiomyopathy that is a challenging diagnostic problem for clinicians. We describe a case of an 8-year-old girl with a 2-year history of shortness of breath on exertion. Electrocardiogram and echocardiography showed biatrial enlargement, while cardiac magnetic resonance showed biatrial dilation and normal pericardial thickness. Left and right heart catheterization revealed a left ventricular (LV) end-diastolic pressure (EDP) of 20 mmHg, right ventricular (RV) EDP of 13 mmHg, and pulmonary arterial systolic pressure of 51 mmHg. LV and RV pressure traces showed that LV and RV pressures moved concordantly with respiration, and that the systolic area index was 0.98. Cardiac catheterization data were therefore supportive of RCM. Next-generation sequencing identified a heterozygous variant of the troponin I gene (TNNI3; c.574C>T). Combining these findings led to a diagnosis of RCM. The patient's parents chose conservative treatment, but at the 12-month follow-up she died of worsening heart failure and cerebral infarction. This case emphasizes the need for cardiac catheterization and genetic testing in RCM, and suggests that anticoagulants should be recommended to reduce the risk of thromboembolic events.

A Salient Object Detection Method Based on Boundary Enhancement.

Visual saliency refers to the human's ability to quickly focus on important parts of their visual field, which is a crucial aspect of image processing, particularly in fields like medical imaging and robotics. Understanding and simulating this mechanism is crucial for solving complex visual problems. In this paper, we propose a salient object detection method based on boundary enhancement, which is applicable to both 2D and 3D sensors data. To address the problem of large-scale variation of salient objects, our method introduces a multi-level feature aggregation module that enhances the expressive ability of fixed-resolution features by utilizing adjacent features to complement each other. Additionally, we propose a multi-scale information extraction module to capture local contextual information at different scales for back-propagated level-by-level features, which allows for better measurement of the composition of the feature map after back-fusion. To tackle the low confidence issue of boundary pixels, we also introduce a boundary extraction module to extract the boundary information of salient regions. This information is then fused with salient target information to further refine the saliency prediction results. During the training process, our method uses a mixed loss function to constrain the model training from two levels: pixels and images. The experimental results demonstrate that our salient target detection method based on boundary enhancement shows good detection effects on targets of different scales, multi-targets, linear targets, and targets in complex scenes. We compare our method with the best method in four conventional datasets and achieve an average improvement of 6.2% on the mean absolute error (MAE) indicators. Overall, our approach shows promise for improving the accuracy and efficiency of salient object detection in a variety of settings, including those involving 2D/3D semantic analysis and reconstruction/inpainting of image/video/point cloud data.

Triple-Isotope Tracing for Pathway Discernment of NMN-Induced NAD+ Biosynthesis in Whole Mice.

Numerous efforts in basic and clinical studies have explored the potential anti-aging and health-promoting effects of NAD+-boosting compounds such as nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN). Despite these extensive efforts, our understanding and characterization of their whole-body pharmacodynamics, impact on NAD+ tissue distribution, and mechanism of action in various tissues remain incomplete. In this study, we administered NMN via intraperitoneal injection or oral gavage and conducted a rigorous evaluation of NMN's pharmacodynamic effects on whole-body NAD+ homeostasis in mice. To provide more confident insights into NMN metabolism and NAD+ biosynthesis across different tissues and organs, we employed a novel approach using triple-isotopically labeled [18O-phosphoryl-18O-carbonyl-13C-1-ribosyl] NMN. Our results provide a more comprehensive characterization of the NMN impact on NAD+ concentrations and absolute amounts in various tissues and the whole body. We also demonstrate that mice primarily rely on the nicotinamide and NR salvage pathways to generate NAD+ from NMN, while the uptake of intact NMN plays a minimal role. Overall, the tissue-specific pharmacodynamic effects of NMN administration through different routes offer novel insights into whole-body NAD+ homeostasis, laying a crucial foundation for the development of NMN as a therapeutic supplement in humans.

An Interactive Image Segmentation Method Based on Multi-Level Semantic Fusion.

Understanding and analyzing 2D/3D sensor data is crucial for a wide range of machine learning-based applications, including object detection, scene segmentation, and salient object detection. In this context, interactive object segmentation is a vital task in image editing and medical diagnosis, involving the accurate separation of the target object from its background based on user annotation information. However, existing interactive object segmentation methods struggle to effectively leverage such information to guide object-segmentation models. To address these challenges, this paper proposes an interactive image-segmentation technique for static images based on multi-level semantic fusion. Our method utilizes user-guidance information both inside and outside the target object to segment it from the static image, making it applicable to both 2D and 3D sensor data. The proposed method introduces a cross-stage feature aggregation module, enabling the effective propagation of multi-scale features from previous stages to the current stage. This mechanism prevents the loss of semantic information caused by multiple upsampling and downsampling of the network, allowing the current stage to make better use of semantic information from the previous stage. Additionally, we incorporate a feature channel attention mechanism to address the issue of rough network segmentation edges. This mechanism captures richer feature details from the feature channel level, leading to finer segmentation edges. In the experimental evaluation conducted on the PASCAL Visual Object Classes (VOC) 2012 dataset, our proposed interactive image segmentation method based on multi-level semantic fusion demonstrates an intersection over union (IOU) accuracy approximately 2.1% higher than the currently popular interactive image segmentation method in static images. The comparative analysis highlights the improved performance and effectiveness of our method. Furthermore, our method exhibits potential applications in various fields, including medical imaging and robotics. Its compatibility with other machine learning methods for visual semantic analysis allows for integration into existing workflows. These aspects emphasize the significance of our contributions in advancing interactive image-segmentation techniques and their practical utility in real-world applications.

Clinical efficacy and safety of rimegepant in the treatment of migraine: a meta-analysis of randomized controlled trials.

Background: This study aims to evaluate the clinical efficacy and safety of rimegepant for the treatment of migraine in adult patients using a meta-analysis. Methods: The PubMed, EMBASE, and Cochrane Library were searched up to March 2022. Only randomized controlled trials (RCTs) that evaluated migraine and other comparator treatments in adult patients were included. The clinical response at the post-treatment evaluation, including acute pain free and relief effect, whereas the secondary outcomes were the risk of adverse events (AEs). Results: A total of 4 RCTs involving 4,230 patients with episodic migraine were included. Outcome indicators for the number of pain free and relief patients at 2 h, 2-24 h, 2-48 h post-dose showed that rimegepant had better effects relative to the placebo [free at 2 h: OR = 1.84, 95% CI (1.55, 2.18), P < 0.00001; relief at 2 h: OR = 1.80, 95% CI (1.59, 2.04), P < 0.00001]. And there was no significant difference between the occurrence of adverse events in the experimental and control groups [OR = 1.29, 95% CI (0.99, 1.67), P = 0.06]. Conclusion: Rimegepant has better therapeutic effects compared to placebo and no significant difference in adverse events.

Eco-friendly fabrication of multifunctional magnetic plasmonic photocatalyst for adsorption, SERS monitoring and photodegradation of residual fluoroquinolone antibiotics in water.

In this work, a kind of multifunctional magnetic plasmonic photocatalyst was prepared by a green and efficient process. Magnetic mesoporous anatase titanium dioxide (Fe3O4@mTiO2) was synthesized by microwave-assisted hydrothermal, and Ag NPs were simultaneously in-situ grown on Fe3O4@mTiO2 (Fe3O4@mTiO2@Ag), graphene oxide (GO) was then wrapped on Fe3O4@mTiO2@Ag (Fe3O4@mTiO2@Ag@GO) to increase its adsorption capacity for fluoroquinolone antibiotics (FQs). Owing to the localized surface plasmon resonance (LSPR) effect of Ag, as well as the photocatalytic capacity of TiO2, a multifunctional platform based on Fe3O4@mTiO2@Ag@GO was constructed for adsorption, surface-enhanced Raman spectroscopy (SERS) monitoring and photodegradation of FQs in water. The quantitative SERS detection of norfloxacin (NOR), ciprofloxacin (CIP), and enrofloxacin (ENR) was demonstrated with LOD of 0.1 µg mL-1, and the qualitative analysis was confirmed by density functional theory (DFT) calculation. The photocatalytic degradation rate of NOR over Fe3O4@mTiO2@Ag@GO was about 4.6 and 1.4 times faster than that of Fe3O4@mTiO2 and Fe3O4@mTiO2@Ag, indicating the synergetic effects of Ag NPs and GO, the used Fe3O4@mTiO2@Ag@GO can be easily recovered and recycled for at least 5 times. Thus, the eco-friendly magnetic plasmonic photocatalyst provided a potential solution for the removal and monitoring of residual FQs in environmental water.

An accuracy improved ratiometric SERS sensor for rhodamine 6G in chili powder using a metal-organic framework support.

Internal standard molecule 4-mercaptobenzoic acid (4-MBA) embedded Au core-Ag shell nanorods (Au-MBA@Ag NRs) were prepared by a seed-mediated growth method, then loaded on octahedral MIL-88B-NH2 to obtain a novel ratiometric SERS substrate of Au-MBA@Ag NRs/PSS/MIL-88B-NH2 (AMAPM) for detecting rhodamine 6G (R6G) in chili powder. The porous structure and excellent adsorption ability of MIL-88B-NH2, allowed for increased loading of Au-MBA@Ag NRs, thereby shortening the distance between adsorbed R6G and the "hot spot" resulting from local surface plasmon resonance (LSPR) of Au-MBA@Ag NRs. Based on the SERS characteristic peak ratio of R6G to 4-MBA, the ratiometric SERS substrate displayed improved accuracy and excellent performance for R6G detection, with a wide linear range of 5-320 nM and a low detection limit of 2.29 nM as well as fine stability, reproducibility and specificity. The proposed ratiometric SERS substrate offered a simple, fast and sensitive sensing strategy for R6G detection in chili powder, which demonstrated potential applications in food safety and the analysis of trace analytes in complex matrices.

Optimized M24B Aminopeptidase Inhibitors for CARD8 Inflammasome Activation.

Inflammasomes are innate immune signaling platforms that trigger pyroptotic cell death. NLRP1 and CARD8 are related human inflammasomes that detect similar danger signals, but NLRP1 has a higher activation threshold and triggers a more inflammatory form of pyroptosis. Both sense the accumulation of intracellular peptides with Xaa-Pro N-termini, but Xaa-Pro peptides on their own without a second danger signal only activate the CARD8 inflammasome. We recently reported that a dual inhibitor of the Xaa-Pro-cleaving M24B aminopeptidases PEPD and XPNPEP1 called CQ31 selectively activates the CARD8 inflammasome by inducing the build-up of Xaa-Pro peptides. Here, we performed structure-activity relationship studies on CQ31 to develop the optimized dual PEPD/XPNPEP1 inhibitor CQ80 that more effectively induces CARD8 inflammasome activation. We anticipate that CQ80 will become a valuable tool to study the basic biology and therapeutic potential of selective CARD8 inflammasome activation.