Perovskite CoSn(OH)6 nanocubes with tuned d-band states towards enhanced oxygen evolution reactions.

The CoSn(OH)6 perovskite hydroxide is a structure stable and inexpensive electrocatalyst for the oxygen evolution reaction (OER). However, the OER activity of CoSn(OH)6 is still unfavorable due to its limited active sites. In this work, an Fe3+ doping strategy is used to optimize the d-band state of the CoSn(OH)6 perovskite hydroxide. The CoSn(OH)6 catalyst with slightly Fe3+ doped nanocubes is synthesized by a facile hydrothermal method. Structure characterization shows that Fe3+ ions are incorporated into the crystal structure of CoSn(OH)6. Owing to the regulation of the electronic structure, CoSn(OH)6-Fe1.8% exhibits an OER overpotential of 289 mV at a current density of 10 mA cm-2 in OER electrochemical tests. In situ Raman spectroscopy shows that no obvious re-construction occurred during the OER for both CoSn(OH)6 and CoSn(OH)6-Fe1.8%. DFT calculations show that the introduction of Fe3+ into CoSn(OH)6 can shift the d-band center to a relatively high position, thus promoting the OER intermediates' adsorption ability. Further DFT calculations suggest that incorporation of an appropriate amount of Fe3+ into CoSn(OH)6 significantly reduces the rate-determining Gibbs free energy during the OER. This work offers valuable insights into tuning the d-band center of perovskite hydroxide materials for efficient OER applications.

Intensive Ambulance-Delivered Blood-Pressure Reduction in Hyperacute Stroke.

BACKGROUND: Treatment of acute stroke, before a distinction can be made between ischemic and hemorrhagic types, is challenging. Whether very early blood-pressure control in the ambulance improves outcomes among patients with undifferentiated acute stroke is uncertain. METHODS: We randomly assigned patients with suspected acute stroke that caused a motor deficit and with elevated systolic blood pressure (≥150 mm Hg), who were assessed in the ambulance within 2 hours after the onset of symptoms, to receive immediate treatment to lower the systolic blood pressure (target range, 130 to 140 mm Hg) (intervention group) or usual blood-pressure management (usual-care group). The primary efficacy outcome was functional status as assessed by the score on the modified Rankin scale (range, 0 [no symptoms] to 6 [death]) at 90 days after randomization. The primary safety outcome was any serious adverse event. RESULTS: A total of 2404 patients (mean age, 70 years) in China underwent randomization and provided consent for the trial: 1205 in the intervention group and 1199 in the usual-care group. The median time between symptom onset and randomization was 61 minutes (interquartile range, 41 to 93), and the mean blood pressure at randomization was 178/98 mm Hg. Stroke was subsequently confirmed by imaging in 2240 patients, of whom 1041 (46.5%) had a hemorrhagic stroke. At the time of patients' arrival at the hospital, the mean systolic blood pressure in the intervention group was 158 mm Hg, as compared with 170 mm Hg in the usual-care group. Overall, there was no difference in functional outcome between the two groups (common odds ratio, 1.00; 95% confidence interval [CI], 0.87 to 1.15), and the incidence of serious adverse events was similar in the two groups. Prehospital reduction of blood pressure was associated with a decrease in the odds of a poor functional outcome among patients with hemorrhagic stroke (common odds ratio, 0.75; 95% CI, 0.60 to 0.92) but an increase among patients with cerebral ischemia (common odds ratio, 1.30; 95% CI, 1.06 to 1.60). CONCLUSIONS: In this trial, prehospital blood-pressure reduction did not improve functional outcomes in a cohort of patients with undifferentiated acute stroke, of whom 46.5% subsequently received a diagnosis of hemorrhagic stroke. (Funded by the National Health and Medical Research Council of Australia and others; INTERACT4 ClinicalTrials.gov number, NCT03790800; Chinese Trial Registry number, ChiCTR1900020534.).

Artificial intelligence driven malnutrition diagnostic model for patients with acute abdomen based on GLIM criteria: a cross-sectional research protocol.

BACKGROUND: Patients with acute abdomen often experience reduced voluntary intake and a hypermetabolic process, leading to a high occurrence of malnutrition. The Global Leadership Initiative on Malnutrition (GLIM) criteria have rapidly developed into a principal methodological tool for nutritional diagnosis. Additionally, machine learning is emerging to establish artificial intelligent-enabled diagnostic models, but the accuracy and robustness need to be verified. We aimed to establish an intelligence-enabled malnutrition diagnosis model based on GLIM for patients with acute abdomen. METHOD: This study is a single-centre, cross-sectional observational investigation into the prevalence of malnutrition in patients with acute abdomen using the GLIM criteria. Data collection occurs on the day of admission, at 3 and 7 days post-admission, including biochemical analysis, body composition indicators, disease severity scoring, nutritional risk screening, malnutrition diagnosis and nutritional support information. The occurrence rate of malnutrition in patients with acute abdomen is analysed with the GLIM criteria based on the Nutritional Risk Screening 2002 and the Mini Nutritional Assessment Short-Form to investigate the sensitivity and accuracy of the GLIM criteria. After data cleansing and preprocessing, a machine learning approach is employed to establish a predictive model for malnutrition diagnosis in patients with acute abdomen based on the GLIM criteria. ETHICS AND DISSEMINATION: This study has obtained ethical approval from the Ethics Committee of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital on 28 November 2022 (Yan-2022-442). The results of this study will be disseminated in peer-reviewed journals, at scientific conferences and directly to study participants. TRIAL REGISTRATION NUMBER: ChiCTR2200067044.

Capsaicin Enhanced the Efficacy of Photodynamic Therapy Against Osteosarcoma via a Pro-Death Strategy by Inducing Ferroptosis and Alleviating Hypoxia.

Ferroptosis, a novel form of nonapoptotic cell death, can effectively enhance photodynamic therapy (PDT) performance by disrupting intracellular redox homeostasis and promoting apoptosis. However, the extremely hypoxic tumor microenvironment (TME) together with highly expressed hypoxia-inducible factor-1α (HIF-1α) presents a considerable challenge for clinical PDT against osteosarcoma (OS). Hence, an innovative nanoplatform that enhances antitumor PDT by inducing ferroptosis and alleviating hypoxia is fabricated. Capsaicin (CAP) is widely reported to specifically activate transient receptor potential vanilloid 1 (TRPV1) channel, trigger an increase in intracellular Ca2+ concentration, which is closely linked with ferroptosis, and participate in decreased oxygen consumption by inhibiting HIF-1α in tumor cells, potentiating PDT antitumor efficiency. Thus, CAP and the photosensitizer IR780 are coencapsulated into highly biocompatible human serum albumin (HSA) to construct a nanoplatform (CI@HSA NPs) for synergistic tumor treatment under near-infrared (NIR) irradiation. Furthermore, the potential underlying signaling pathways of the combination therapy are investigated. CI@HSA NPs achieve real-time dynamic distribution monitoring and exhibit excellent antitumor efficacy with superior biosafety in vivo. Overall, this work highlights a promising NIR imaging-guided "pro-death" strategy to overcome the limitations of PDT for OS by promoting ferroptosis and alleviating hypoxia, providing inspiration and support for future innovative tumor therapy approaches.

sTREM2 in the prognostic evaluation of acute lung injury after cardiac surgery in infants.

BACKGROUND: Previous studies have shown that TREM2 plays a protective role in acute lung injury (ALI). This prospective study aimed to investigate the role of sTREM2 as a forecasting factor for ALI in infants after pediatric cardiac surgery undergoing cardiopulmonary bypass (CPB). METHODS: Seventy-five consecutive patients younger than 1 year who underwent cardiac surgery were enrolled in this study. Sixty-one fulfilled the inclusion criteria and had been divided into ALI and non-ALI groups. Children's demographic characteristics and clinical data were collected. Perioperative sTREM2 levels were analyzed at five timepoints. RESULTS: In this study, children in the ALI group were younger, lighter, with higher RACHS-1 scores and underwent significantly longer CPB time. Post-CPB ALI had an impact on clinical outcomes, which contributed to a longer duration of mechanical ventilation, ICU and hospital stay than non-ALI group. Significant differences were manifested off-CPB, 1 h/6 h after CPB, and day 1 after surgery between the two groups. Binary logistic models revealed that off-CPB sTREM2 was significantly associated with the incidence of post-CPB ALI after adjustment. ROC analysis showed that the AUC of off-CPB sTREM2 level was 0.791, and the optimal cutoff value was 788.6 pg/ml. CONCLUSIONS: The off-CPB sTREM2 level was an independent prognostic factor for post-CPB ALI in infants. IMPACT: Plasma sTREM2 works together with downstream TREM2 to regulate inflammation response by binding the receptor to other cells. Previous studies have shown that TREM2 plays a protective role in ischemia-reperfusion and has anti-inflammatory effects on acute lung injury (ALI). This study analyzed the risk factors of post-cardiopulmonary bypass (CPB) ALI. We found that weight and off-CPB sTREM2 level were independent prognostic factors for post-CPB ALI. Plasma sTREM2 may serve as an early biomarker in the prognostic evaluation of acute lung injury after cardiac surgery in infants.

Skeletal muscle-secreted DLPC orchestrates systemic energy homeostasis by enhancing adipose browning.

MyoD is a skeletal muscle-specifically expressed transcription factor and plays a critical role in regulating myogenesis during muscle development and regeneration. However, whether myofibers-expressed MyoD exerts its metabolic function in regulating whole body energy homeostasis in vivo remains largely unknown. Here, we report that genetic deletion of Myod in male mice enhances the oxidative metabolism of muscle and, intriguingly, renders the male mice resistant to high fat diet-induced obesity. By performing lipidomic analysis in muscle-conditioned medium and serum, we identify 1,2-dilinoleoyl-sn-glycero-3-phosphocholine (DLPC) as a muscle-released lipid that is responsible for MyoD-orchestrated body energy homeostasis in male Myod KO mice. Functionally, the administration of DLPC significantly ameliorates HFD-induced obesity in male mice. Mechanistically, DLPC is found to induce white adipose browning via lipid peroxidation-mediated p38 signaling in male mice. Collectively, our findings not only uncover a novel function of MyoD in controlling systemic energy homeostasis through the muscle-derived lipokine DLPC but also suggest that the DLPC might have clinical potential for treating obesity in humans.

EMDL_m6Am: identifying N6,2'-O-dimethyladenosine sites based on stacking ensemble deep learning.

BACKGROUND: N6, 2'-O-dimethyladenosine (m6Am) is an abundant RNA methylation modification on vertebrate mRNAs and is present in the transcription initiation region of mRNAs. It has recently been experimentally shown to be associated with several human disorders, including obesity genes, and stomach cancer, among others. As a result, N6,2'-O-dimethyladenosine (m6Am) site will play a crucial part in the regulation of RNA if it can be correctly identified. RESULTS: This study proposes a novel deep learning-based m6Am prediction model, EMDL_m6Am, which employs one-hot encoding to expressthe feature map of the RNA sequence and recognizes m6Am sites by integrating different CNN models via stacking. Including DenseNet, Inflated Convolutional Network (DCNN) and Deep Multiscale Residual Network (MSRN), the sensitivity (Sn), specificity (Sp), accuracy (ACC), Mathews correlation coefficient (MCC) and area under the curve (AUC) of our model on the training data set reach 86.62%, 88.94%, 87.78%, 0.7590 and 0.8778, respectively, and the prediction results on the independent test set are as high as 82.25%, 79.72%, 80.98%, 0.6199, and 0.8211. CONCLUSIONS: In conclusion, the experimental results demonstrated that EMDL_m6Am greatly improved the predictive performance of the m6Am sites and could provide a valuable reference for the next part of the study. The source code and experimental data are available at: https://github.com/13133989982/EMDL-m6Am .

ACP-BC: A Model for Accurate Identification of Anticancer Peptides Based on Fusion Features of Bidirectional Long Short-Term Memory and Chemically Derived Information.

Anticancer peptides (ACPs) have been proven to possess potent anticancer activities. Although computational methods have emerged for rapid ACPs identification, their accuracy still needs improvement. In this study, we propose a model called ACP-BC, a three-channel end-to-end model that utilizes various combinations of data augmentation techniques. In the first channel, features are extracted from the raw sequence using a bidirectional long short-term memory network. In the second channel, the entire sequence is converted into a chemical molecular formula, which is further simplified using Simplified Molecular Input Line Entry System notation to obtain deep abstract features through a bidirectional encoder representation transformer (BERT). In the third channel, we manually selected four effective features according to dipeptide composition, binary profile feature, k-mer sparse matrix, and pseudo amino acid composition. Notably, the application of chemical BERT in predicting ACPs is novel and successfully integrated into our model. To validate the performance of our model, we selected two benchmark datasets, ACPs740 and ACPs240. ACP-BC achieved prediction accuracy with 87% and 90% on these two datasets, respectively, representing improvements of 1.3% and 7% compared to existing state-of-the-art methods on these datasets. Therefore, systematic comparative experiments have shown that the ACP-BC can effectively identify anticancer peptides.

The Spectrum and Age-Sex Patterns Among Outpatients with Allergic Diseases - Yichang City, Hubei Province, China, 2018-2021.

What is already known about this topic?: Allergic diseases have affected an estimated 40% of the population in China. However, our understanding of the full spectrum of these diseases remains insufficient. What is added by this report?: Between 2018 and 2021, Yichang City documented 625,929 outpatient visits mainly related to skin and mucous membrane allergies (77.90%) and allergic respiratory conditions (19.64%). In 2021, the occurrence of outpatient visits for conditions such as allergic rhinitis, acute atopic conjunctivitis, and atopic dermatitis increased. The demographic analysis revealed that male patients comprised the majority of the under 18 age bracket (56.05%), while female patients were predominantly represented in the 18 to 65 age bracket (61.79%). What are the implications for public health practice?: This constitutes the first analysis of the spectrum of allergic diseases, utilizing regional outpatient data, which has substantial implications for understanding the disease burden.

Area-Based Sociodemographic Factors Associated with Latent Tuberculosis Infection in a Low-Prevalence Setting.

Area-based sociodemographic markers, such as census tract foreign-born population, have been used to identify individuals and communities with a high risk for tuberculosis (TB) infection in the United States. However, these markers have not been evaluated as independent risk factors for TB infection in children. We evaluated associations between census tract poverty, crowding, foreign-born population, and the CDC's Social Vulnerability Index (CDC-SVI) ranking and TB infection in a population of children tested for TB infection in Boston, Massachusetts. After adjustment for age, crowding, and foreign-born percentage, increasing census tract poverty was associated with increased odds of TB infection (adjusted odds ratio [aOR] per 10% increase in population proportion living in poverty: 1.20 [95% CI, 1.04-1.40]; P = 0.01), although this association was attenuated after further adjustment for preferred language. In separate models, increasing CDC-SVI ranking was associated with increased odds of TB infection, including after adjustment for age and language preference (aOR per 10-point increase in CDC-SVI rank: 1.08 [95% CI, 1.02-1.15]; P = 0.01). Our findings suggest area-based sociodemographic factors may be valuable for characterizing TB infection risk and defining the social ecology of pediatric TB infection in low-burden settings.

CRIP1 Reshapes the Gastric Cancer Microenvironment to Facilitate Development of Lymphatic Metastasis.

Lymphangiogenesis in tumors provides an auxiliary route for cancer cell invasion to drainage lymph nodes, facilitating the development of lymphatic metastasis (LM). However, the mechanisms governing tumor lymphangiogenesis and lymphatic permeability in gastric cancer (GC) remain largely unknown. Here, the unprecedented role and mechanism of cysteine-rich intestinal protein-1 (CRIP1) in mediating the development of GC LM is uncovered. A series of assays are performed to identify downstream targets of CRIP1, and rescue experiments are performed to confirm the effects of this regulatory axis on LM. CRIP1 overexpression facilitates LM in GC by promoting lymphangiogenesis and lymphatic vessel permeability. CRIP1 promotes phosphorylation of cAMP responsive element binding protein 1(CREB1), which then mediates vascular endothelial growth factor C (VEGFC) expression necessary for CRIP1-induced lymphangiogenesis and transcriptionally promotes C-C motif chemokine ligand 5 (CCL5) expression. CCL5 recruits macrophages to promote tumor necrosis factor alpha (TNF-α) secretion, eventually enhancing lymphatic permeability. The study highlights CRIP1 regulates the tumor microenvironment to promote lymphangiogenesis and LM in GC. Considering the current limited understanding of LM development in GC, these pathways provide potential targets for future therapeutics.

Serum soluble triggering receptor levels expressed on myeloid cells2 identify early acute kidney injury in infants and young children after pediatric cardiopulmonary bypass.

Background: Acute kidney injury (AKI) is a potential complication after cardiopulmonary bypass (CPB) of pediatric cardiac surgery and contributes to a certain amount of perioperative mortality. Serum soluble triggering receptor expressed on myeloid cells2 (sTREM2) is an inflammation-associated cytokine in circulation. Alterations of sTREM2 level have been reported in Alzheimer's disease, sepsis, and some other pathologic conditions. This study aimed to investigate the role of sTREM2 as a forecasting factor for AKI in infants and young children and other factors associated with early renal injury after pediatric CPB. Methods: A prospective cohort study with consecutive infants and young children ≤ 3 years old undergoing CPB from September 2021 to August 2022 was conducted in an affiliated university children's hospital. These patients were divided into an AKI group (n = 10) and a non-AKI group (n = 60). Children's characteristics and clinical data were measured. Perioperative sTREM2 levels were analyzed with enzyme-linked immunosorbent assay (ELISA). Results: In children developing AKI, the sTREM2 levels significantly decreased at the beginning of CPB compared to the non-AKI group. Based on binary logistic regression analysis and multivariable regression analysis, risk-adjusted classification for congenital heart surgery (RACHS-1), operation time, and the s-TREM2 level at the beginning of CPB (AUC = 0.839, p = 0.001, optimal cut-off value: 716.0 pg/ml) had predictive value for post-CPB AKI. When combining the sTREM2 level at the beginning of CPB and other indicators together, the area under the ROC curve enlarged. Conclusions: Operation time, RACHS-1 score, and sTREM2 level at the beginning of CPB were independent prognosis factors of post-CPB AKI in infants and young children ≤ 3 years old. Decreased sTREM2 identified post-CPB AKI, and ultimately hampered the outcomes. Our findings indicated that sTREM2 may be a protective factor for AKI after CPB in infants and young children ≤ 3 years old.

JNK1 activated pRb/E2F1 and inhibited p53/p21 signaling pathway is involved in hydroquinone-induced pathway malignant transformation of TK6 cells by accelerating the cell cycle progression.

Hydroquinone (HQ) is an important metabolites of benzene in the body, and it has been found to result in cellular DNA damage, mutation, cell cycle imbalance, and malignant transformation. The JNK1 signaling pathway plays an important role in DNA damage repair. In this study, we focused on whether the JNK1 signaling pathway is involved in the HQ-induced cell cycle abnormalities and the underlying mechanism. The results showed that HQ induced abnormal progression of the cell cycle and initiated the JNK1 signaling pathway. We further confirmed that JNK1 suppression decelerated the cell cycle progression through inhibiting pRb/E2F1 signaling pathway and triggering p53/p21 pathway. Therefore, we concluded that JNK1 might be involved in HQ-induced malignant transformation associated with activating pRb/E2F1 and inhibiting p53/p21 signaling pathway which resulting in accelerating the cell cycle progression.

Nucleated Red Blood Cells Are Predictive of In-Hospital Mortality for Pediatric Patients.

PURPOSE: We sought to establish whether nucleated red blood cells (NRBCs) are predictive of disposition, morbidity, and mortality for pediatric patients presenting to the emergency department (ED). METHODS: A single-center retrospective cohort study examining all ED encounters from patients aged younger than 19 years between January 2016 and March 2020, during which a complete blood count was obtained. Univariate analysis and multivariable logistic regression were used to test the presence of NRBCs as an independent predictor of patient-related outcomes. RESULTS: The prevalence of NRBCs was 8.9% (4195/46,991 patient encounters). Patient with NRBCs were younger (median age 4.58 vs 8.23 years; P < 0.001). Those with NRBCs had higher rates of in-hospital mortality (30/2465 [1.22%] vs 65/21,741 [0.30%]; P < 0.001), sepsis (19% vs 12%; P < 0.001), shock (7% vs 4%; P < 0.001), and cardiopulmonary resuscitation (CPR) (0.62% vs 0.09%; P < 0.001). They were more likely to be admitted (59% vs 51%; P < 0.001), have longer median hospital length of stay {1.3 (interquartile range [IQR], 0.22-4.14) vs 0.8 days (IQR, 0.23-2.64); P < 0.001}, and median intensive care unit (ICU) length of stay (3.9 [IQR, 1.87-8.72] vs 2.6 days [IQR, 1.27-5.83]; P < 0.001). Multivariable regression revealed presence of NRBCs as an independent predictor for in-hospital mortality (adjusted odds ratio [aOR], 2.21; 95% confidence interval [CI], 1.38-3.53; P < 0.001), ICU admission (aOR, 1.30; 95% CI, 1.11-1.51; P < 0.001), CPR (aOR, 3.83; 95% CI, 2.33-6.30; P < 0.001), and 30-day return to the ED (aOR, 1.15; 95% CI, 1.15-1.26; P < 0.001). CONCLUSIONS: The presence of NRBCs is an independent predictor for mortality, including in-hospital mortality, ICU admission, CPR, and readmission within 30 days for children presenting to the ED.

A Bond-Based Peridynamic Model with Matrix Plasticity for Impact Damage Analysis of Composite Materials.

The prediction of damage and failure to fiber-reinforced polymer composites in extreme environments, particularly when subjected to impact loading, is a crucial issue for the application and design of protective structures. In this paper, based on the prototype microelastic brittle (PMB) model and the LaRC05 composite materials failure model, we proposed a bond-based peridynamic (BB-PD) model with the introduction of plastic hardening of the resin matrix for fiber-reinforced polymer composites. The PD constitutive relationships of the matrix bond and interlayer bond under compressive loading are considered to include two stages of linear elasticity and plastic hardening, according to the stress-strain relationship of the resin matrix in the LaRC05 failure model. The proposed PD model is employed to simulate the damage behaviors of laminated composites subjected to impact loading. The corresponding ballistic impact tests of composite laminates were carried out to observe their damage behaviors. The PD prediction results are in good agreement with the ballistic experimental results, which can verify the correctness and accuracy of the PD model developed in this study in describing the impact damage behaviors of composite materials. In addition, the characteristics and degree of damage in composite laminates are analyzed and discussed based on this PD model. The difference in the impact resistance of composite laminates with different stacking sequences is also studied using the numerical simulation results.

A New Grey Wolf Optimizer Tuned Extended Generalized Predictive Control for Distillation Process.

The distillation process plays an essential role in the petrochemical industry. However, the high-purity distillation column has complicated dynamic characteristics such as strong coupling and large time delay. To control the distillation column accurately, we proposed an extended generalized predictive control (EGPC) method inspired by the principles of extended state observer and proportional-integral-type generalized predictive control method; the proposed EGPC can adaptively compensate the system for the effects of coupling and model mismatch online and performs well in controlling time-delay systems. The strong coupling of the distillation column needs fast control, and the large time delay requires soft control. To balance the requirement for fast and soft control at the same time, a grey wolf optimizer with reverse learning and adaptive leaders number strategies (RAGWO) was proposed to tune the parameters of EGPC, and these strategies enable RAGWO to have a better initial population and improve its exploitation and exploration ability. The benchmark test results indicate that the RAGWO outperforms the existing optimizers for most of the selected benchmark functions. Extensive simulations show that the proposed method in terms of fluctuation and response time is superior to other methods for controlling the distillation process.

DeepDN_iGlu: prediction of lysine glutarylation sites based on attention residual learning method and DenseNet.

As a key issue in orchestrating various biological processes and functions, protein post-translational modification (PTM) occurs widely in the mechanism of protein's function of animals and plants. Glutarylation is a type of protein-translational modification that occurs at active ε-amino groups of specific lysine residues in proteins, which is associated with various human diseases, including diabetes, cancer, and glutaric aciduria type I. Therefore, the issue of prediction for glutarylation sites is particularly important. This study developed a brand-new deep learning-based prediction model for glutarylation sites named DeepDN_iGlu via adopting attention residual learning method and DenseNet. The focal loss function is utilized in this study in place of the traditional cross-entropy loss function to address the issue of a substantial imbalance in the number of positive and negative samples. It can be noted that DeepDN_iGlu based on the deep learning model offers a greater potential for the glutarylation site prediction after employing the straightforward one hot encoding method, with Sensitivity (Sn), Specificity (Sp), Accuracy (ACC), Mathews Correlation Coefficient (MCC), and Area Under Curve (AUC) of 89.29%, 61.97%, 65.15%, 0.33 and 0.80 accordingly on the independent test set. To the best of the authors' knowledge, this is the first time that DenseNet has been used for the prediction of glutarylation sites. DeepDN_iGlu has been deployed as a web server (https://bioinfo.wugenqiang.top/~smw/DeepDN_iGlu/) that is available to make glutarylation site prediction data more accessible.

Antibody-free approach for ubiquitination profiling by selectively clicking the ubiquitination sites.

Ubiquitination is a reversible post-translational modification that plays a pivotal role in numerous biological processes. Antibody-based approaches, as the most used methods for identifying ubiquitination sites, exist sequence recognition bias, high cost, and ubiquitin-like protein modification interference, limiting their widespread application. Here, we proposed an Antibody-Free approach for Ubiquitination Profiling, termed AFUP, by selectively clicking the ubiquitinated lysine to enrich and profile endogenous ubiquitinated peptides using mass spectrometry. Briefly, protein amines were blocked with formaldehyde, and then the ubiquitin molecules were hydrolyzed from the ubiquitinated proteins by non-specific deubiquitinases USP2 and USP21 to release the free ε-amine of lysine. Peptides containing free ε-amines were selectively enriched with streptavidin beads upon NHS-SS-biotin labeling. Finally, the enriched peptides were eluted by DTT and analyzed by LC-MS/MS, resulting in ubiquitination profiling. Preliminary experiment showed that 349 ± 7 ubiquitination sites were identified in 0.8 mg HeLa lysates with excellent reproducibility (CV = 2%) and high quantitative stability (Pearson, r ≥ 0.91) using our method. With the combination of AFUP and simple basic C18 pre-fractionation, approximately 4000 ubiquitination sites were identified in a single run of 293T cells. In addition, we showed that 209 ubiquitination sites were significantly regulated in UBE2O knockdown cells after normalized to protein abundance. In conclusion, our results demonstrated that AFUP is a robust alternative strategy for ubiquitomics research.

Interferon Gamma Release Assay Results and Testing Trends Among Patients Younger Than 2 Years Old at Two US Health Centers.

BACKGROUND: Interferon-gamma release assays (IGRAs) are approved for children ≥2 years old to aid in diagnosis of Mycobacterium tuberculosis (TB) infection and disease. Tuberculin skin tests (TSTs) continue to be the recommended method for diagnosis of TB infection in children <2 years, in part due to limited data and concern for high rates of uninterpretable results. METHODS: We performed a retrospective cohort study of IGRA use in patients <2 years old in 2 large Boston healthcare systems. The primary outcome was the proportion of valid versus invalid/indeterminate IGRA results. Secondary outcomes included concordance of IGRAs with paired TSTs and trends in IGRA usage over time. RESULTS: A total of 321 IGRA results were analyzed; 308 tests (96%) were valid and 13 (4%) were invalid/indeterminate. Thirty-seven IGRAs were obtained in immunocompromised patients; the proportion of invalid/indeterminate results was significantly higher among immunocompromised (27%) compared with immunocompetent (1%) patients ( P < 0.001). Paired IGRAs and TSTs had a concordance rate of 64%, with most discordant results in bacille Calmette-Guérin-vaccinated patients. The proportion of total TB tests that were IGRAs increased over the study period (Pearson correlation coefficient 0.85, P < 0.001). CONCLUSIONS: The high proportion of valid IGRA test results in patients <2 years of age in a low TB prevalence setting in combination with the known logistical and interpretation challenges associated with TSTs support the adoption of IGRAs for this age group in certain clinical scenarios. Interpretation of IGRAs, particularly in immunocompromised patients, should involve consideration of the broader clinical context.