A Bacterial Effector Reveals the V-ATPase-ATG16L1 Axis that Initiates Xenophagy.

Antibacterial autophagy (xenophagy) is an important host defense, but how it is initiated is unclear. Here, we performed a bacterial transposon screen and identified a T3SS effector SopF that potently blocked Salmonella autophagy. SopF was a general xenophagy inhibitor without affecting canonical autophagy. S. Typhimurium ΔsopF resembled S. flexneri ΔvirAΔicsB with the majority of intracellular bacteria targeted by autophagy, permitting a CRISPR screen that identified host V-ATPase as an essential factor. Upon bacteria-caused vacuolar damage, the V-ATPase recruited ATG16L1 onto bacteria-containing vacuole, which was blocked by SopF. Mammalian ATG16L1 bears a WD40 domain required for interacting with the V-ATPase. Inhibiting autophagy by SopF promoted S. Typhimurium proliferation in vivo. SopF targeted Gln124 of ATP6V0C in the V-ATPase for ADP-ribosylation. Mutation of Gln124 also blocked xenophagy, but not canonical autophagy. Thus, the discovery of SopF reveals the V-ATPase-ATG16L1 axis that critically mediates autophagic recognition of intracellular pathogen.

Will cellular immunotherapies end neurodegenerative diseases?

Neurodegenerative disorders present major challenges to global health, exacerbated by an aging population and the absence of therapies. Despite diverse pathological manifestations, they share a common hallmark, loosely termed 'neuroinflammation'. The prevailing dogma is that the immune system is an active contributor to neurodegeneration; however, recent evidence challenges this. By analogy with road construction, which causes temporary closures and disruptions, the immune system's actions in the central nervous system (CNS) might initially appear destructive, and might even cause harm, while aiming to combat neurodegeneration. We propose that the application of cellular immunotherapies to coordinate the immune response towards remodeling might pave the way for new modes of tackling the roadblocks of neurodegenerative diseases.

A bioorthogonal system reveals antitumour immune function of pyroptosis.

Bioorthogonal chemistry capable of operating in live animals is needed to investigate biological processes such as cell death and immunity. Recent studies have identified a gasdermin family of pore-forming proteins that executes inflammasome-dependent and -independent pyroptosis1-5. Pyroptosis is proinflammatory, but its effect on antitumour immunity is unknown. Here we establish a bioorthogonal chemical system, in which a cancer-imaging probe phenylalanine trifluoroborate (Phe-BF3) that can enter cells desilylates and 'cleaves' a designed linker that contains a silyl ether. This system enabled the controlled release of a drug from an antibody-drug conjugate in mice. When combined with nanoparticle-mediated delivery, desilylation catalysed by Phe-BF3 could release a client protein-including an active gasdermin-from a nanoparticle conjugate, selectively into tumour cells in mice. We applied this bioorthogonal system to gasdermin, which revealed that pyroptosis of less than 15% of tumour cells was sufficient to clear the entire 4T1 mammary tumour graft. The tumour regression was absent in immune-deficient mice or upon T cell depletion, and was correlated with augmented antitumour immune responses. The injection of a reduced, ineffective dose of nanoparticle-conjugated gasdermin along with Phe-BF3 sensitized 4T1 tumours to anti-PD1 therapy. Our bioorthogonal system based on Phe-BF3 desilylation is therefore a powerful tool for chemical biology; our application of this system suggests that pyroptosis-induced inflammation triggers robust antitumour immunity and can synergize with checkpoint blockade.

A Fully Automated Online Enrichment and Separation System for Highly Reproducible and In-Depth Analysis of Intact Glycopeptide.

A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-µg sample amount, while a 10-µg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.

CCR2 inhibitor strengthens the adiponectin effects against myocardial injury after infarction.

Little evidence demonstrated the effects of nitric oxide (NO) hydrogel with adipocytes in vivo. We aimed to investigate the effects of adiponectin (ADPN) and CCR2 antagonist on cardiac functions and macrophage phenotypes after myocardial infarction (MI) using chitosan caged nitric oxide donor (CSNO) patch with adipocytes. 3T3-L1 cell line was induced to adipocytes and ADPN expression was knocked down. CSNO was synthesized and patch was constructed. MI model was constructed and patch was placed on the infarcted area. ADPN knockdown adipocytes or control was incubated with CSNO patch, and CCR2 antagonist was also used to investigate the ADPN effects on myocardial injury after infarction. On day 7 after operation, cardiac functions of the mice using CSNO with adipocytes or ADPN knockdown adipocytes improved more than in mice only using CSNO for treatment. Lymphangiogenesis increased much more in the MI mice using CSNO with adipocytes. After treating with CCR2 antagonist, Connexin43+ CD206+ cells and ZO-1+ CD206+ cells increased, suggesting that CCR2 antagonist promoted M2 polarization after MI. Besides, CCR2 antagonist promoted ADPN expression in adipocytes and cardiomyocytes. ELISA was also used and CKMB expression was much lower than other groups at 3 days after operation. On day 7 after operation, the VEGF and TGFß expressions were high in the adipocytes CSNO group, illustrating that higher ADPN led to better treatment. In all, CCR2 antagonist enhanced the ADPN effects on macrophage M2 polarization and cardiac functions. The combination used in border zone and infarcted areas may help improve patients' prognosis in surgery, such as CABG.

Axin2 depletion in macrophages alleviated senescence and increased immune response after myocardial infarction.

OBJECTIVE AND DESIGN: This study aimed to investigate Axin2 effects on myocardial infarction (MI) using a macrophage Axin2 conditional knockout (cKO) mouse model, RAW264.7 cell line, and human subepicardial tissues from patients with coronary artery bypass graft (CABG). MATERIAL OR SUBJECTS: Axin2 cKO mice showed decreased cardiac function, reduced edema, increased lymphangiogenesis, and improved repair in MI Few studies border zones. Hypoxic macrophages with Axin2 depletion exhibited decreased senescence, elevated IL6 expression, and increased LYVE1 transcription. Senescent macrophages decreased in patients with CABG and low Axin2 expression. TREATMENT: Treatment options included in this study were MI induction in Axin2 cKO mice, in vitro experiments with RAW264.7 cells, and analysis of human subepicardial tissues. METHODS: Assays included MI induction, in vitro experiments, and tissue analysis with statistical tests applied. RESULTS: Axin2 cKO improved cardiac function, reduced edema, enhanced lymphangiogenesis, and decreased senescence. Hypoxic macrophages with Axin2 depletion showed reduced senescence, increased IL6 expression, and elevated LYVE1 transcription. Senescent macrophages decreased in patients with CABG and low Axin2 expression. CONCLUSION: Targeting Axin2 emerges as a novel therapeutic strategy for regulating cardiac lymphatics and mitigating cell senescence post-MI, evidenced by improved outcomes in Axin2-deficient conditions.

Radial basis function neural network optimization algorithm based on dynamic inertial weight particle swarm optimization for separating overlapping peaks in ion mobility spectrometry.

RATIONALE: Ion mobility spectrometry (IMS), as a promising analytical tool, has been widely employed in the structural characterization of biomolecules. Nevertheless, the inherent limitation in the structural resolution of IMS frequently results in peak overlap during the analysis of isomers exhibiting comparable structures. METHODS: The radial basis function (RBF) neural network optimization algorithm based on dynamic inertial weight particle swarm optimization (DIWPSO) was proposed for separating overlapping peaks in IMS. The RBF network structure and parameters were optimized using the DIWPSO algorithm. By extensively training using a large dataset, an adaptive model was developed to effectively separate overlapping peaks in IMS data. This approach successfully overcomes issues related to local optima, ensuring efficient and precise separation of overlapping peaks. RESULTS: The method's performance was evaluated using experimental validation and analysis of overlapping peaks in the IMS spectra of two sets of isomers: 3'/6'-sialyllactose; fructose-6-phosphate, glucose-1-phosphate, and glucose-6-phosphate. A comparative analysis was conducted using other algorithms, including the sparrow search algorithm, DIWPSO algorithm, and multi-objective dynamic teaching-learning-based optimization algorithm. The comparison results show that the DIWPSO-RBF algorithm achieved remarkably low maximum relative errors of only 0.42%, 0.092%, and 0.41% for ion height, mobility, and half peak width, respectively. These error rates are significantly lower than those obtained using the other three algorithms. CONCLUSIONS: The experimental results convincingly demonstrate that this method can adaptively, rapidly, and accurately separate overlapping peaks of multiple components, improving the structural resolution of IMS.

An efficient strategy with a synergistic effect of hydrophilic and electrostatic interactions for simultaneous enrichment of N- and O-glycopeptides.

N- and O-glycosylation modifications of proteins are closely linked to the onset and development of many diseases and have gained widespread attention as potential targets for therapy and diagnosis. However, the low abundance and low ionization efficiency of glycopeptides as well as the high heterogeneity make glycosylation analysis challenging. Here, an enrichment strategy, using Knoevenagel copolymers modified with polydopamine-adenosine (denoted as PDA-ADE@KCP), was firstly proposed for simultaneous enrichment of N- and O-glycopeptides through the synergistic effects of hydrophilic and electrostatic interactions. The adjustable charged surface and hydrophilic properties endow the material with the capability to achieve effective enrichment of intact N- and O-glycopeptides. The experimental results exhibited excellent selectivity (1 : 5000) and sensitivity (0.1 fmol µL-1) of the prepared material for N-glycopeptides from standard protein digest samples. Moreover, it was further applied to simultaneous capturing of N- and O-glycopeptides from mouse liver protein digests. Compared to the commercially available zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) material, the number of glycoproteins corresponding to all N- and O-glycopeptides enriched with PDA-ADE@KCP was much more than that with ZIC-HILIC. Furthermore, PDA-ADE@KCP captured more O-glycopeptides than ZIC-HILIC, revealing its superior performance in O-glycopeptide enrichment. All these results indicated that the strategy holds immense potential in characterizing N- and O-intact glycopeptides in the field of proteomics.

Alpha-kinase 1 is a cytosolic innate immune receptor for bacterial ADP-heptose.

Immune recognition of pathogen-associated molecular patterns (PAMPs) by pattern recognition receptors often activates proinflammatory NF-κB signalling1. Recent studies indicate that the bacterial metabolite D-glycero-ß-D-manno-heptose 1,7-bisphosphate (HBP) can activate NF-κB signalling in host cytosol2-4, but it is unclear whether HBP is a genuine PAMP and the cognate pattern recognition receptor has not been identified. Here we combined a transposon screen in Yersinia pseudotuberculosis with biochemical analyses and identified ADP-ß-D-manno-heptose (ADP-Hep), which mediates type III secretion system-dependent NF-κB activation and cytokine expression. ADP-Hep, but not other heptose metabolites, could enter host cytosol to activate NF-κB. A CRISPR-Cas9 screen showed that activation of NF-κB by ADP-Hep involves an ALPK1 (alpha-kinase 1)-TIFA (TRAF-interacting protein with forkhead-associated domain) axis. ADP-Hep directly binds the N-terminal domain of ALPK1, stimulating its kinase domain to phosphorylate and activate TIFA. The crystal structure of the N-terminal domain of ALPK1 and ADP-Hep in complex revealed the atomic mechanism of this ligand-receptor recognition process. HBP was transformed by host adenylyltransferases into ADP-heptose 7-P, which could activate ALPK1 to a lesser extent than ADP-Hep. ADP-Hep (but not HBP) alone or during bacterial infection induced Alpk1-dependent inflammation in mice. Our findings identify ALPK1 and ADP-Hep as a pattern recognition receptor and an effective immunomodulator, respectively.

Wheat yellow mosaic virus NIb targets TaVTC2 to elicit broad-spectrum pathogen resistance in wheat.

GDP-L-galactose phosphorylase (VTC2) catalyses the conversion of GDP-L-galactose to L-galactose-1-P, a vital step of ascorbic acid (AsA) biosynthesis in plants. AsA is well known for its function in the amelioration of oxidative stress caused by most pathogen infection, but its function against viral infection remains unclear. Here, we have identified a VTC2 gene in wheat named as TaVTC2 and investigated its function in association with the wheat yellow mosaic virus (WYMV) infection. Our results showed that overexpression of TaVTC2 significantly increased viral accumulation, whereas knocking down TaVTC2 inhibited the viral infection in wheat, suggesting a positive regulation on viral infection by TaVTC2. Moreover, less AsA was produced in TaVTC2 knocking down plants (TaVTC2-RNAi) which due to the reduction in TaVTC2 expression and subsequently in TaVTC2 activity, resulting in a reactive oxygen species (ROS) burst in leaves. Furthermore, the enhanced WYMV resistance in TaVTC2-RNAi plants was diminished by exogenously applied AsA. We further demonstrated that WYMV NIb directly bound to TaVTC2 and inhibited TaVTC2 enzymatic activity in vitro. The effect of TaVTC2 on ROS scavenge was suppressed by NIb in a dosage-dependent manner, indicating the ROS scavenging was highly regulated by the interaction of TaVTC2 with NIb. Furthermore, TaVTC2 RNAi plants conferred broad-spectrum disease resistance. Therefore, the data indicate that TaVTC2 recruits WYMV NIb to down-regulate its own enzymatic activity, reducing AsA accumulation to elicit a burst of ROS which confers the resistance to WYMV infection. Thus, a new mechanism of the formation of plant innate immunity was proposed.

Identification and clinical validation of key genes as the potential biomarkers in colorectal adenoma.

BACKGROUND: Colorectal cancer (CRC), ranking third in cancer prevalence and second in mortality worldwide, is mainly derived from colorectal adenoma (CRA). CRA is a common benign disease in the intestine with rapidly increasing incidence and malignant potential. Therefore, this study aimed to recognize significant biomarkers and original pathogenesis in CRA. METHODS: Transcriptome data of GSE8671, GSE37364, and GSE15960 were downloaded from the Gene Expression Omnibus (GEO) datasets, and differentially expressed genes (DEGs) were screened. Functional pathways enrichment, protein-protein interaction (PPI) network, stem-correlation analysis, CIBERSORT, risk score and survival analyses were performed. RT-qPCR and immunohistochemical staining were applied to verify our results.  RESULTS: Screening for significant DEGs in each dataset, we identified 230 robust DEGs, including 127 upregulated and 103 downregulated genes. Functional pathways enrichment showed that these DEGs were distinctly enriched in various tumor-associated pathways, such as growth factor activity, extracellular structure organization, neutrophil activation, and inflammatory response. We filtered out two hub genes via STRING and Modules analysis, including CA2 and HSD11B2. Stem-correlation analysis displayed that hub genes were negatively associated with stem-related genes (Olfm4, CD44, CCND1 and MYC). The CIBERSORT algorithm indicated that Macrophage2, activated mast cells, and Neutrophils promoted CRA progression through inflammation. Survival analysis showed that CA2 and HSD11B2 were positively associated with survival outcomes in CRC. CONCLUSION: Our study has successfully identified the critical role of two core genes in the development and oncogenesis of CRA, which provides novel insight into the underlying pathogenesis, potential biomarkers and therapeutic targets.

Two-step particle swarm optimization algorithm for effective deconvolution and resolution enhancement of various overlapping peaks.

RATIONALE: The existing particle swarm optimization (PSO) algorithms are only effective in deconvoluting the overlapping peaks in ion mobility spectra with fewer than four component peaks, which limits the applicability of these algorithms. METHODS: A high-performance two-step particle swarm optimization (TSPSO) algorithm was developed. Compared to the existing PSO algorithms, TSPSO can narrow the search ranges of all coefficients for the overlapping peaks through Gaussian model calculation, and thus can deconvolute various overlapping peaks with high accuracy, even for 30-component overlapping peaks. In addition, the TSPSO could be further applied to enhance the resolution of the spectra by narrowing the peak widths after the peak deconvolution. RESULTS: Simulated overlapping peaks were first used to evaluate the performance of TSPSO as compared to the dynamic inertia weight particle swarm optimization (DIWPSO) algorithm. The results showed that the profiles of the peaks deconvoluted by using TSPSO were more consistent with the original ones. The fitness values and the standard deviations of the fitness values from TSPSO were also at least an order of magnitude less than those from DIWPSO. By applying TSPSO, the overlapping peaks from both mass spectrometry (MS) and field asymmetric waveform ion mobility spectrometry (FAIMS) spectra can also be well deconvoluted. In addition, the resolutions of the MS and FAIMS spectra can be effectively enhanced after peak deconvolution. The enhanced spectra matched excellently with the experimental ones acquired at high-resolution modes. CONCLUSIONS: The experiment results convincingly demonstrate that the TSPSO algorithm is capable of both deconvoluting complex overlapping peaks and enhancing the spectrum resolution with high accuracy.

Overlapping peak separation algorithm for ion mobility spectra based on multistrategy JAYA.

RATIONALE: In the field of separation science, ion mobility spectrometry (IMS) plays an important role as an analytical tool. However, the lack of sufficient structural resolution is a common problem in qualitative and quantitative analysis using IMS. A method is needed to solve the problem of overlapping peaks caused by insufficient resolution. METHODS: The method uses multiple strategies to more effectively use population information to balance exploration and exploitation capabilities, prevent local optimization, accurately resolve overlapping peaks, quickly obtain optimal spectral peak model coefficients, and accurately identify compounds. RESULTS: Multistrategy JAYA algorithm's (MSJAYA) performance is compared with improved particle swarm optimization (IPSO), dynamic inertia weight particle swarm optimization (DIWPSO), and multiobjective dynamic teaching-learning-based optimization (MDTLBO). The analysis shows that MSJAYA's maximum separation error is within 0.6%, a level of accuracy not guaranteed by the other algorithms. In addition, the separation error fluctuates within a much smaller range, demonstrating MSJAYA's superior robustness. CONCLUSIONS: Compared with other overlapping peak separation algorithms, MSJAYA is more applicable because no special parameters are used. The method allows fast deconvolution analysis of strong overlapping peaks with multiple components, which greatly improves the resolution of IMS.

An improved algorithm for resolving overlapping peaks in ion mobility spectrometry and its application to the separation of glycan isomers.

Despite the popularity of ion mobility spectrometry (IMS) for glycan analysis, its limited structural resolution hinders the effective separation of many glycan isomers. This leads to the overlap of IMS peaks, consequently impacting the accurate identification of glycan compositions. To this end, an improved algorithm, namely second-order differentiation combined with a simulated annealing particle swarm optimization algorithm based on sine adaptive weights (DWSA-PSO), was proposed for the separation of overlapping IMS peaks formed by glycan isomers. DWSA-PSO first performed second-order differentiation to automatically determine the number of components in overlapping peaks and exclude impossible single-peak combinations. It then introduced sinusoidal adaptive weights and a simulated annealing mechanism to improve the algorithm's search capability and global optimization performance, thereby enabling accurate and efficient separation of individual peaks. To evaluate the performance of DWSA-PSO and its application to the separation of glycan isomers, multiple sets of overlapping peaks with different degrees of overlap were simulated, and various types of multi-component overlapping peaks were formed using six disaccharide and four trisaccharide isomers. The experimental results consistently demonstrated that the DWSA-PSO algorithm outperformed both the improved particle swarm optimization (IPSO) algorithm and the dynamic inertia weight particle swarm optimization (DIWPSO) algorithm in terms of separation accuracy, running time, and fitness values. In addition, the DWSA-PSO algorithm was successfully applied to the separation of glycan isomers in malt milk beverage. All these results reveal the capability of the DWSA-PSO algorithm to facilitate the accurate identification of glycan isomers.

In situ growth of a cobalt porphyrin-based covalent organic framework on multi-walled carbon nanotubes for ultrasensitive real-time monitoring of living cell-released nitric oxide.

Nitric oxide (NO), as a critical transcellular messenger, participates in a variety of physiological and pathological processes. However, its real-time detection still faces challenges due to its short half-life and trace amounts. Here, MWCNTs@COF-366-Co was prepared by in situ growth of a cobalt porphyrin-based covalent organic framework (COF-366-Co) on multi-walled carbon nanotubes (MWCNTs), and a unique biosensing platform for ultrasensitive real-time NO determination was established. Remarkably, MWCNTs@COF-366-Co contains plenty of atomically arranged M-N4 active sites for electrocatalysis, which provides more efficient electron transfer pathways and resolves the random arrangement issue of active sites. COF-366-Co with a high surface area contains a large number of exposed active M-N4 sites, providing faster NO transport/diffusion and more efficient electron transfer pathways. Due to the synergy of atomic-level periodic structural features of COF-366-Co and high conductivity of MWCNTs, the MWCNTs@COF-366-Co electrochemical biosensor exhibited excellent NO determination performance in a wide range from 0.09 to 400 µM, with high sensitivity (8.9 µA µM-1 cm-2) and a low limit of detection (16 nM). Moreover, the biosensor has been successfully used to sensitively monitor NO molecules released from human umbilical vein endothelial cells (HUVECs). This research not only designed a multifunctional intelligent biosensor platform, but also provided a broad prospect for continuous dynamic monitoring of the activity of living cells and their released metabolites.

Association of hyperglycemia ratio and ventricular arrhythmia in critically ill patients admitted to the intensive care unit.

INTRODUCTION: The relationship between relative hyperglycemia and ventricular arrhythmia (VA) in critically ill patients admitted to intensive care units (ICU) remains unclear. This study aims to investigate the association between stress hyperglycemia ratio (SHR) and VA in this population. METHODS: This retrospective and observational study analyzed data from 4324 critically ill patients admitted to the ICU, obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The SHR was calculated as the highest blood glucose level during the first 24 h of ICU admission divided by the admission blood glucose level. Based on the optimal cut-off values under the receiver operating characteristic curve, patients were stratified into high SHR (≥ 1.31) and low SHR (< 1.31) group. To investigate the impact of diabetes mellitus (DM) on the outcome, patients were stratified as low SHR/DM; low SHR/non-DM; high SHR/DM, and high SHR/non-DM. Restricted cubic spline (RCS) and logistic regression analysis were performed to analyze the relationship between SHR and VA. RESULTS: A total of 4,324 critically ill patients were included in this retrospective and observational study. The incidence of VA was higher in the high SHR group. Multiple-adjusted RCS revealed a "J-shaped" correlation between SHR and VA morbidity. The logistic regression model demonstrated that high SHR was associated with VA. The high SHR/non-DM group had a higher risk of VA than other groups stratified based on SHR and DM. Subgroup analysis showed that high SHR was associated with an increased risk of VA in patients with coronary artery disease. CONCLUSION: High SHR is an independent risk factor and has potential as a biomarker of higher VT/VF risk in ICU-admitted patients.

Chemotherapy drugs induce pyroptosis through caspase-3 cleavage of a gasdermin.

Pyroptosis is a form of cell death that is critical for immunity. It can be induced by the canonical caspase-1 inflammasomes or by activation of caspase-4, -5 and -11 by cytosolic lipopolysaccharide. The caspases cleave gasdermin D (GSDMD) in its middle linker to release autoinhibition on its gasdermin-N domain, which executes pyroptosis via its pore-forming activity. GSDMD belongs to a gasdermin family that shares the pore-forming domain. The functions and mechanisms of activation of other gasdermins are unknown. Here we show that GSDME, which was originally identified as DFNA5 (deafness, autosomal dominant 5), can switch caspase-3-mediated apoptosis induced by TNF or chemotherapy drugs to pyroptosis. GSDME was specifically cleaved by caspase-3 in its linker, generating a GSDME-N fragment that perforates membranes and thereby induces pyroptosis. After chemotherapy, cleavage of GSDME by caspase-3 induced pyroptosis in certain GSDME-expressing cancer cells. GSDME was silenced in most cancer cells but expressed in many normal tissues. Human primary cells exhibited GSDME-dependent pyroptosis upon activation of caspase-3 by chemotherapy drugs. Gsdme-/- (also known as Dfna5-/-) mice were protected from chemotherapy-induced tissue damage and weight loss. These findings suggest that caspase-3 activation can trigger necrosis by cleaving GSDME and offer new insights into cancer chemotherapy.

[Comparison of Disease Burden Factors of Thyroid Cancer Between China and the World From 1990 to 2019].

Objective To compare the prevalence and disease burden of thyroid cancer and their trends between China and the globe from 1990 to 2019.Methods With the global disease burden data in 2019,Joinpoint was used to predict the trends of the disease burden of thyroid cancer in China and the globe from 1990 to 2019,and logarithmic linear model was used to test the predicted trends.The R language was used for predictive analysis and graphic plotting of the disease burden from 2020 to 2035.Results From 1990 to 2019,the standardized incidence rate and the standardized mortality rate of thyroid cancer in China were lower than those in the globe.The standardized incidence rate in China and the globe showed an increasing trend(with the increases of 102.65% and 40.65%,respectively),while the standardized mortality rate showed a decreasing trend(with the decreases of 7.63% and 4.91%,respectively).Compared with those of the female population,the standardized incidence and mortality rates of the Chinese male population increased significantly from 1990 to 2019(the rates of change in the male population were 48.65% and 214.60%,respectively;and the rates of change in the female population were -39.01% and 60.44%,respectively).China's overall standardized years of life lost(YLL),years lived with disability(YLD),and disability-adjusted life years(DALY)rates during the 30-year period were lower than the global average.The Chinese and global populations showed the standardized YLL rate decreasing by 16.61% and 6.88% and the standardized DALY rate decreasing by 10.77% and 3.65%,respectively,while the rates of standardized YLD increased by 128.91% and 46.89%,respectively.The magnitude of DALY in China and the world was mainly influenced by YLL.The standardized incidence,mortality,and DALY rates of the Chinese male population were gradually approaching the global levels.From 1990 and 2019,thyroid cancer showed a higher mortality rate in the population with the age ≥ 75 years and a higher incidence rate in the population with the age <75 years.It is projected that from 2020 to 2035,the standardized incidence rates in China and the world will increase by 36.66% and 21.15%,respectively;the standardized mortality rates will decrease by 20.19% and 3.46%,respectively;and the standardized DALY rate is expected to decrease by 7.08% in China and increase by 4.35% in the world.Conclusions From 1990 to 2019,China's standardized incidence rate of thyroid cancer increased and had a higher increase than the global level,and the standardized mortality rate decreased,with a slightly higher decrease than the global level.However,the increases in the standardized incidence rate and mortality rate of this disease in China's ≥75 years male population were severe.Although China's disease burden of thyroid cancer showed a decreasing trend in line with the global trend as a whole,the disease burden in the Chinese males was higher than that in the females.Specifically,the disease burden due to premature death was predominant,and the burden in specific populations requires policy attention.

Two-Dimensional FAIMS-IMS Characterization of Peptide Conformers with Resolution Exceeding 1000.

A high-performance field asymmetric waveform ion mobility spectrometry (FAIMS)-IMS-MS platform was developed and applied to explore the conformational diversity of the singly and doubly charged bradykinin (BK + H+)+ and (BK + 2H+)2+ ions. With pure N2 as the FAIMS carrier gas, more than ten conformers of (BK + H+)+ can be resolved using FAIMS-IMS, as compared to only four conformers resolved using either FAIMS or IMS alone. Interestingly, multiple conformers of (BK + H+)+ were found to have completely different values of FAIMS compensation voltage (CV), while their IMS drift times were essentially the same, which were also proven experimentally to not result from the structural annealing by the collisional heating in the ion funnel. The separations in the FAIMS and IMS dimensions are substantially orthogonal, and the overall resolving power of two-dimensional FAIMS-IMS separation is largely proportional to the product of the separation resolving powers of FAIMS and IMS. Using a gas mixture of N2/He to further improve the resolving power of the FAIMS separation, the total resolving powers of the combined FAIMS and IMS separation were estimated to be about 1020 and 1400 for (BK + H+)+ and (BK + 2H+)2+ ions, respectively, which are significantly higher than the resolving power of any ion mobility-based separation techniques demonstrated so far. The combined FAIMS-IMS can thus be a much more powerful technique to explore the structural diversity of biomolecules.

Combination of continuous wavelet transform and genetic algorithm-based Otsu for efficient mass spectrometry peak detection.

Mass spectrometry (MS) data is susceptible to random noises and alternating baseline, posing great challenges to spectral peak detection, especially for weak peaks and overlapping peaks. Herein, an efficient peak detection algorithm combining continuous wavelet transform (CWT) and genetic algorithm-based threshold segmentation (denoted as WSTGA) for mass spectrometry was proposed. Firstly, Mexican Hat wavelet was selected as the mother wavelet by comparing the matching degree between the difference of Gaussian (DOG) and different wavelets. Subsequently, the ridges and valleys were identified from 2D wavelet coefficient matrix. Afterward, an improved threshold segmentation method, Otsu method based on genetic algorithm, was introduced to find optimal segmentation threshold and achieve better image segmentation, overcoming the deficiency of traditional Otsu method that cannot handle long-tailed unimodal histograms. Finally, the characteristic peaks were successfully identified by utilizing the ridge-valley lines in wavelet space and original spectrum. Receiver operating characteristic (ROC) curve, area under curve (AUC) and F1 measure are used as criterions to evaluate performance of peak detection algorithms. Compared with multi-scale peak detection (MSPD) and CWT and image segmentation (CWT-IS) methods, all the results showed that WSTGA can achieve better peak detection. More importantly, the experimental results from MALDI-TOF spectra demonstrated that WSTGA can effectively detect more weak peaks and overlapping peaks while maintaining a lower false peak detection rate than MSPD and CWT-IS methods, indicating its great advantages in characteristic peak identification.