Loss of function variant in CIP2A associated with female infertility with early embryonic arrest and fragmentation.

BACKGROUND: Early embryonic arrest and fragmentation (EEAF) is a common cause of female infertility, but the genetic causes remain to be largely unknown. CIP2A encodes the cellular inhibitor of PP2A, playing a crucial role in mitosis and mouse oocyte meiosis. METHODS: Exome sequencing and Sanger sequencing were performed to identify candidate causative genes in patients with EEAF. The pathogenicity of the CIP2A variant was assessed and confirmed in cultured cell lines and human oocytes through Western blotting, semi-quantitative RT-PCR, TUNEL staining, and fluorescence localization analysis. FINDINGS: We identified CIP2A (c.1510C > T, p.L504F) as a novel candidate disease-causing gene in human EEAF from a consanguineous family. L504 is highly conserved throughout evolution. The CIP2A variant (c.1510C > T, p.L504F) reduced the expression level of the mutant CIP2A protein, leading to the abnormal aggregation of mutant CIP2A protein and cell apoptosis. Abnormal aggregation of CIP2A protein and chromosomal dispersion occurred in the patient's oocytes and early embryos. We further replicated the patient phenotype by knockdown CIP2A in human oocytes. Additionally, CIP2A deficiency resulted in decreased levels of phosphorylated ERK1/2. INTERPRETATION: We first found that the CIP2A loss-of-function variant associate with female infertility characterized by EEAF. Our findings suggest the uniqueness and importance of CIP2A gene in human oocyte and early embryo development. FUNDING: This work was supported by National Key Research and Development Program of China (2023YFC2706302), the National Natural Science Foundation of China (81000079, 81170165, and 81870959), the HUST Academic Frontier Youth Team (2016QYTD02), and the Key Research of Huazhong University of Science and Technology, Tongji Hospital (2022A20).

Effect of heart rate on poor outcome in stroke patients treated with intra-arterial thrombectomy.

BACKGROUND AND PURPOSE: The relationship between heart rate and the prognosis of patients with large vessel occlusion strokes treated with mechanical thrombectomy (MT) is not well established. This study aimed to evaluate the association of mean heart rate and heart rate variability (HRV) with the clinical outcomes after MT therapy. METHODS: Acute ischemic stroke patients undergoing MT therapy were prospectively recruited from March 2020 to November 2022. Their heart rate was collected every hour for the initial 72 h after MT procedure, and the variability of heart rate was measured by standard deviation (SD) and coefficient of variation (CV). All-cause mortality and worsening of functional outcome (change in modified Rankin Scale (mRS) score) at 3-month were captured. Binary logistic regression was used to evaluate the association between heart rate indicators and all-cause mortality. Ordinal logistic regression was used to evaluate the association between heart rate indicators and worsening of functional outcome. RESULTS: Among 191 MT-treated patients, 51(26.7%) patients died at 3-month after stroke. Increased mean heart rate per 10-bpm, heart rate SD and CV per 5-unit were all associated with the increased risk of mortality (adjusted hazard ratio [aHR] with 95% CI: 1.29 [1.09-1.51], 1.19 [1.07-1.32], 1.14 [1.03-1.27]; respectively). Patients in the highest tertile of heart rate SD had an increased risk of mortality (4.62, 1.70-12.52). After using mRS as a continuous variable, we found increased mean heart rate per 10-bpm, heart rate SD and CV per 5-unit were associated with the worsening of functional outcome (adjusted odds ratio [aOR] with 95% CI: 1.35 [1.11-1.64], 1.27 [1.05-1.53], 1.19 [1.02-1.40]; respectively). A linear relationship was observed between mean heart rate or heart rate SD and mortality; while all of the heart rate measures in this study showed a linear relationship with the worsening of functional outcome. CONCLUSIONS: Higher mean heart rate and HRV were associated with the increased risk of 3-month all-cause mortality and worse functional outcome after MT therapy for AIS patients.

Effective cryopreservation of human brain tissue and neural organoids.

Human brain tissue models and organoids are vital for studying and modeling human neurological disease. However, the high cost of long-term cultured organoids inhibits their wide-ranging application. It is therefore urgent to develop methods for the cryopreservation of brain tissue and organoids. Here, we establish a method using methylcellulose, ethylene glycol, DMSO, and Y27632 (termed MEDY) for the cryopreservation of cortical organoids without disrupting the neural cytoarchitecture or functional activity. MEDY can be applied to multiple brain-region-specific organoids, including the dorsal/ventral forebrain, spinal cord, optic vesicle brain, and epilepsy patient-derived brain organoids. Additionally, MEDY enables the cryopreservation of human brain tissue samples, and pathological features are retained after thawing. Transcriptomic analysis shows that MEDY can protect synaptic function and inhibit the endoplasmic reticulum-mediated apoptosis pathway. MEDY will enable the large-scale and reliable storage of diverse neural organoids and living brain tissue and will facilitate wide-ranging research, medical applications, and drug screening.

Association of Triglyceride Glucose-Derived Indexes with Recurrent Events Following Atherosclerotic Cardiovascular Disease.

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indexes of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indexes shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion: This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Comparative analysis of dynamic transcriptomes reveals specific COVID-19 features and pathogenesis of immunocompromised populations.

A dysfunction of human host genes and proteins in coronavirus infectious disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a key factor impacting clinical symptoms and outcomes. Yet, a detailed understanding of human host immune responses is still incomplete. Here, we applied RNA sequencing to 94 samples of COVID-19 patients with and without hematological tumors as well as COVID-19 uninfected non-tumor individuals to obtain a comprehensive transcriptome landscape of both hematological tumor patients and non-tumor individuals. In our analysis, we further accounted for the human-SARS-CoV-2 protein interactome, human protein interactome, and human protein complex subnetworks to understand the mechanisms of SARS-CoV-2 infection and host immune responses. Our data sets enabled us to identify important SARS-CoV-2 (non-)targeted differentially expressed genes and complexes post-SARS-CoV-2 infection in both hematological tumor and non-tumor individuals. We found several unique differentially expressed genes, complexes, and functions/pathways such as blood coagulation (APOE, SERPINE1, SERPINE2, and TFPI), lipoprotein particle remodeling (APOC2, APOE, and CETP), and pro-B cell differentiation (IGHM, VPREB1, and IGLL1) during COVID-19 infection in patients with hematological tumors. In particular, APOE, a gene that is associated with both blood coagulation and lipoprotein particle remodeling, is not only upregulated in hematological tumor patients post-SARS-CoV-2 infection but also significantly expressed in acute dead patients with hematological tumors, providing clues for the design of future therapeutic strategies specifically targeting COVID-19 in patients with hematological tumors. Our data provide a rich resource for understanding the specific pathogenesis of COVID-19 in immunocompromised patients, such as those with hematological malignancies, and developing effective therapeutics for COVID-19. IMPORTANCE: A majority of previous studies focused on the characterization of coronavirus infectious disease 2019 (COVID-19) disease severity in people with normal immunity, while the characterization of COVID-19 in immunocompromised populations is still limited. Our study profiles changes in the transcriptome landscape post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hematological tumor patients and non-tumor individuals. Furthermore, our integrative and comparative systems biology analysis of the interactome, complexome, and transcriptome provides new insights into the tumor-specific pathogenesis of COVID-19. Our findings confirm that SARS-CoV-2 potentially tends to target more non-functional host proteins to indirectly affect host immune responses in hematological tumor patients. The identified unique genes, complexes, functions/pathways, and expression patterns post-SARS-CoV-2 infection in patients with hematological tumors increase our understanding of how SARS-CoV-2 manipulates the host molecular mechanism. Our observed differential genes/complexes and clinical indicators of normal/long infection and deceased COVID-19 patients provide clues for understanding the mechanism of COVID-19 progression in hematological tumors. Finally, our study provides an important data resource that supports the increasing value of the application of publicly accessible data sets to public health.

Recognizing high-priority disinfection byproducts based on experimental and predicted endocrine disrupting data: Virtual screening and in vitro study.

So far, about 130 disinfection by-products (DBPs) and several DBPs-groups have had their potential endocrine-disrupting effects tested on some endocrine endpoints. However, it is still not clear which specific DBPs, DBPs-groups/subgroups may be the most toxic substances or groups/subgroups for any given endocrine endpoint. In this study, we attempt to address this issue. First, a list of relevant DBPs was updated, and 1187 DBPs belonging to 4 main-groups (aliphatic, aromatic, alicyclic, heterocyclic) and 84 subgroups were described. Then, the high-priority endocrine endpoints, DBPs-groups/subgroups, and specific DBPs were determined from 18 endpoints, 4 main-groups, 84 subgroups, and 1187 specific DBPs by a virtual-screening method. The results demonstrate that most of DBPs could not disturb the endocrine endpoints in question because the proportion of active compounds associated with the endocrine endpoints ranged from 0 (human thyroid receptor beta) to 32% (human transthyretin (hTTR)). All the endpoints with a proportion of active compounds greater than 10% belonged to the thyroid system, highlighting that the potential disrupting effects of DBPs on the thyroid system should be given more attention. The aromatic and alicyclic DBPs may have higher priority than that of aliphatic and heterocyclic DBPs by considering the activity rate and potential for disrupting effects. There were 2 (halophenols and estrogen DBPs), 12, and 24 subgroups that belonged to high, moderate, and low priority classes, respectively. For individual DBPs, there were 23 (2%), 193 (16%), and 971 (82%) DBPs belonging to the high, moderate, and low priority groups, respectively. Lastly, the hTTR binding affinity of 4 DBPs was determined by an in vitro assay and all the tested DBPs exhibited dose-dependent binding potency with hTTR, which was consistent with the predicted result. Thus, more efforts should be performed to reveal the potential endocrine disruption of those high research-priority main-groups, subgroups, and individual DBPs.

Joint Association of Lipoprotein(a) and a Family History of Coronary Artery Disease with the Cardiovascular Outcomes in Patients with Chronic Coronary Syndrome.

AIM: No data are currently available regarding the association between Lp(a) and the cardiovascular outcomes in patients with coronary artery disease (CAD) according to their family history (FHx) of CAD. This study aimed to evaluate the significance of Lp(a) in predicting major adverse cardiovascular events (MACEs) in patients with chronic coronary syndrome (CCS) with or without FHx. METHODS: A total of 6056 patients with CCS were enrolled. Information on FHx was collected, and the plasma Lp(a) levels were measured. All patients were followed up regularly. The independent and joint associations of Lp(a) and FHx with the risk of MACEs, including cardiovascular death, nonfatal myocardial infarction, and stroke, were analyzed. RESULTS: With over an average of 50.35±18.58 months follow-up, 378 MACEs were recorded. A Cox regression analysis showed an elevated Lp(a) level to be an independent predictor for MACEs in patients with [hazard ratio (HR): 2.77, 95% confidence interval (CI): 1.38-5.54] or without FHx (HR: 1.35, 95% CI: 1.02-1.77). In comparison to subjects with non-elevated Lp(a) and negative FHx, patients with elevated Lp(a) alone were at a nominally higher risk of MACEs (HR: 1.26, 95% CI: 0.96-1.67), while those with both had the highest risk (HR: 1.93, 95% CI: 1.14-3.28). Moreover, adding Lp(a) to the original model increased the C-statistic by 0.048 in subjects with FHx (p=0.004) and by 0.004 in those without FHx (p=0.391). CONCLUSIONS: The present study is the first to suggest that Lp(a) could be used to predict MACEs in CCS patients with or without FHx; however, its prognostic significance was more noteworthy in patients with FHx.

Management of hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy is an important cause of heart failure and arrhythmias, including sudden death, with a major impact on the healthcare system. Genetic causes and different phenotypes are now increasingly being identified for this condition. In addition, specific medications, such as myosin inhibitors, have been recently shown as potentially able to modify its symptoms, hemodynamic abnormalities and clinical course. Our article aims to provide a comprehensive outline of the epidemiology, diagnosis and treatment of hypertrophic cardiomyopathy in the current era.

Association of acute glycemic parameters at admission with cardiovascular mortality in the oldest old with acute myocardial infarction.

OBJECTIVES: Stress-related glycemic indicators, including admission blood glucose (ABG), stress-hyperglycemia ratio (SHR), and glycemic gap (GG), have been associated with worse outcomes after acute myocardial infarction (AMI). However, data regarding their prognostic value in the oldest old with AMI are unavailable. Therefore, this study aimed to investigate the association of stress-related glycemic indicators with short- and long-term cardiovascular mortality (CVM) in the oldest old (≥ 80 years) with AMI. METHODS: In this prospective study, a total of 933 consecutive old patients with AMI admitted to FuWai hospital (Beijing, China) were enrolled. On admission, ABG, SHR, and GG were assessed and all participants were classified according to their quartiles. Kaplan-Meier, restricted cubic splines (RCS), and multivariate Cox regression analyses were performed to evaluate the association between these glycemic indicators and CVM within 30 days and long-term follow-up. RESULTS: During an average of 1954 patient-years of follow-up, a total of 250 cardiovascular deaths were recorded. Kaplan-Meier analyses showed the lowest CVM in quartile 1 of ABG and in quartile 2 of SHR and GG. After adjusting for potential covariates, patients in quartile 4 of ABG, SHR, and GG had a respective 1.67-fold (95% CI: 1.03-2.69; P = 0.036), 1.80-fold (95% CI: 1.16-2.79; P = 0.009), and 1.78-fold (95% CI: 1.14-2.79; P = 0.011) higher risk of long-term CVM risk compared to those in the reference groups (quartile 1 of ABG and quartile 2 of SHR and GG). Furthermore, RCS suggested a J-shaped relationship of ABG and a U-shaped association of SHR and GG with long-term CVM. Additionally, we observed similar associations of these acute glycemic parameters with 30-day CVM. CONCLUSIONS: Our data first indicated that SHR and GG consistently had a U-shaped association with both 30-day and long-term CVM among the oldest old with AMI, suggesting that they may be useful for risk stratification in this special population.

Rapid screening of infertility-associated gynecological conditions via ambient glow discharge mass spectrometry utilizing urine metabolic fingerprints.

Infertility presents a widespread challenge for many families worldwide, often arising from various gynecological diseases (GDs) that hinder successful pregnancies. Current diagnostic methods for GDs have disadvantages such as low efficiency, high cost, misdiagnose, invasive injury and etc. This paper introduces a rapid, non-invasive, efficient, and straightforward analytical method that utilizes desorption, separation, and ionization mass spectrometry (DSI-MS) platform in conjunction with machine learning (ML) to detect urine metabolite fingerprints in patients with different GDs. We analyzed 257 samples from patients diagnosed with polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), endometriosis (EMS), recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), and 87 samples from healthy control (HC) individuals. We identified metabolite differences and dysregulated pathways through dimensionality reduction methods, with the result of the discovery of 7 potential biomarkers for GDs diagnosis. The ML method effectively distinguished subtle differences in urine metabolite fingerprints. We anticipate that this innovative approach will offer a patient-friendly, rapid screening, and differentiation method for infertility-related GDs patients.

131I Induced In Vivo Proteolysis by Photoswitchable azoPROTAC Reinforces Internal Radiotherapy.

Photopharmacology, incorporating photoswitches such as azobenezes into drugs, is an emerging therapeutic method to realize spatiotemporal control of pharmacological activity by light. However, most photoswitchable molecules are triggered by UV light with limited tissue penetration, which greatly restricts the in vivo application. Here, this study proves that 131I can trigger the trans-cis photoisomerization of a reported azobenezen incorporating PROTACs (azoPROTAC). With the presence of 50 µCi mL-1 131I, the azoPROTAC can effectively down-regulate BRD4 and c-Myc levels in 4T1 cells at a similar level as it does under light irradiation (405 nm, 60 mW cm-2). What's more, the degradation of BRD4 can further benefit the 131I-based radiotherapy. The in vivo experiment proves that intratumoral co-adminstration of 131I (300 µCi) and azoPROTC (25 mg kg-1) via hydrogel not only successfully induce protein degradation in 4T1 tumor bearing-mice but also efficiently inhibit tumor growth with enhanced radiotherapeutic effect and anti-tumor immunological effect. This is the first time that a radioisotope is successfully used as a trigger in photopharmacology in a mouse model. It believes that this study will benefit photopharmacology in deep tissue.

Comprehensive mapping of saliva by multiomics in children with idiopathic nephrotic syndrome.

AIM: Saliva can reflect an individual's physiological status or susceptibility to systemic disease. However, little attention has been given to salivary analysis in children with idiopathic nephrotic syndrome (INS). We aimed to perform a comprehensive analysis of saliva from INS children. METHODS: A total of 18 children (9 children with INS and 9 normal controls) were recruited. Saliva was collected from each INS patient in the acute and remission phases. 16S rRNA gene sequencing, widely targeted metabolomics, and 4D-DIA proteomics were performed. RESULTS: Actinobacteria and Firmicutes were significantly enriched in the pretreatment group compared with the normal control group, while Bacteroidota and Proteobacteria were significantly decreased. A total of 146 metabolites were identified as significantly different between INS children before treatment and normal controls, which covers 17 of 23 categories. KEGG enrichment analysis revealed three significantly enriched pathways, including ascorbate and aldarate metabolism, pentose and glucuronate interconversions, and terpenoid backbone biosynthesis (P < 0.05). A total of 389 differentially expressed proteins were selected between INS children before treatment and normal controls. According to the KEGG and GO enrichment analyses of the KOGs, abnormal ribosome structure and function and humoral immune disorders were the most prominent differences between INS patients and normal controls in the proteomic analysis. CONCLUSION: Oral microbiota dysbiosis may modulate the metabolic profile of saliva in children with INS. It is hypothesized that children with INS might have "abnormal ribosome structure and function" and "humoral immune disorders".

A cheaper substitute for HRP: ultra-small Cu-Au bimetallic enzyme mimics with infinitesimal steric hindrance to promote catalytic lateral flow immunodetection of clenbuterol.

A highly sensitive lateral flow immunoassay (LFIA) is developed for the enzyme-catalyzed and double-reading determination of clenbuterol (CLE), in which a new type of probe was adopted through the direct electrostatic adsorption of ultra-small copper-gold bimetallic enzyme mimics (USCGs) and monoclonal antibodies. In the assay, based on the peroxidase activity of USCG, the chromogenic substrate TMB-H2O2 was introduced to trigger its color development, and the results were compared with those before catalysis. The detection sensitivity after catalysis is 0.03 ng mL-1 under optimal circumstances, which is 6-fold better than that of the traditional Au NPs-based LFIA and 2-fold greater than that before catalysis. This approach was successfully applied to the detection of CLE in milk, pork and mutton samples with an optimum assay time of 7 min and best catalytic time of 80 s, after which satisfactory recoveries of 98.53-117.79% were obtained. Cu-Au nanoparticles as a signal tag and the use of their nanozyme properties are the first applications in the field of LFIA. This work can be a promising exhibition for the application of a cheaper substitute for HRP, ultra-small bimetallic enzyme mimics, in LFIAs.

Rapid analysis and authentication of Chinese propolis using nanoelectrospray ionization mass spectrometry combined with machine learning.

In this study, we established a simple, rapid, and high-throughput method for the analysis and classification of propolis samples. We utilized nanoESI-MS to analyze 37 samples of propolis from China for the first time, obtaining characteristic fingerprint spectra in negative ion mode, which were then integrated with multivariate analysis to explore variations between water extract of propolis (WEP) and ethanol extract of propolis (EEP). Furthermore, we categorized propolis samples based on different climate zones and colors, screening 10 differential metabolites among propolis from various climate zones, and 11 differential metabolites among propolis samples of different color. By employing machine learning models, we achieved high-precision discrimination and prediction between samples from different climate zones and colors, achieving predictive accuracies of 95.6% and 85.6%, respectively. These results highlight the significant potential of the nanoESI-MS coupled with machine learning methodology for precise classification within the realm of food products.

Inhibitory effects and mechanisms of phenolic compounds in rapeseed oil on advanced glycation end product formation in chemical and cellular models in vitro.

Sinapic acid (SA), canolol (CAO) and canolol dimer (CAO dimer) are the main phenolic compounds in rapeseed oil. However, their possible efficacy against glycation remains unclear. This study aims to explore the impacts of these substances on the formation of advanced glycation end products (AGEs) based on chemical and cellular models in vitro. Based on fluorescence spectroscopy results, three chemical models of BSA-fructose, BSA-methylglyoxal (MGO), and arginine (Arg)-MGO showed that SA/CAO/CAO dimer could effectively reduce AGE formation but with different abilities. After SA/CAO/CAO dimer incubation, effective protection against BSA protein glycation was observed and three different MGO adducts were formed. In MGO-induced HUVEC cell models, only CAO and CAO dimer significantly inhibited oxidative stress and cell apoptosis, accompanied by the regulation of the Nrf2-HO-1 pathway. During the inhibition, 20 and 12 lipid mediators were reversed in the CAO and CAO dimer groups compared to the MGO group.

Modeling the precise interaction of glioblastoma with human brain region-specific organoids.

Glioblastoma is a highly aggressive malignant tumor of the central nervous system, but the interaction between glioblastoma and different types of neurons remains unclear. Here, we established a co-culture model in vitro using 3D printed molds with microchannels, in which glioblastoma organoids (GB), dorsal forebrain organoids (DO, mainly composed of excitatory neurons), and ventral forebrain organoids (VO, mainly composed of inhibitory neurons) were assembled. Our results indicate that DO has a greater impact on altered gene expression profiles of GB, resulting in increased invasive potential. GB cells preferentially invaded DO along axons, whereas this phenomenon was not observed in VO. Furthermore, GB cells selectively inhibited neurite outgrowth in DOs and reduced the expression of the vesicular GABA transporter (VGAT), leading to neuronal hyperexcitability. By revealing how glioblastoma interacts with brain cells, our study provides a more comprehensive understanding of this disease.

Association of Sex With Cardiovascular Outcomes in Heart Failure Patients With Obstructive or Central Sleep Apnea.

BACKGROUND: This study investigated the association of sex with cardiovascular outcomes in a prospective cohort of patients with heart failure (HF) with obstructive sleep apnea or central sleep apnea. METHODS AND RESULTS: Patients were screened for sleep apnea on admission using multichannel cardiopulmonary monitoring from May 2015 to July 2018. The primary outcome was a composite of cardiovascular death or unplanned hospitalization for worsening HF. Ultimately, 453 patients with HF with obstructive sleep apnea or central sleep apnea were included; 71 (15.7%) and 382 (84.3%) were women and men, respectively. During a median follow-up of 2.33 years, 248 (54.7%) patients experienced the primary outcome. In the overall population, after adjusting for potential confounders, women had an increased risk of the primary outcome (66.2% versus 52.6%; hazard ratio [HR], 1.47 [95% CI, 1.05-2.04]; P=0.024) and HF rehospitalization (62.0% versus 46.6%; HR, 1.55 [95% CI, 1.10-2.19]; P=0.013) compared with men but a comparable risk of cardiovascular death (21.1% versus 23.3%; HR, 0.78 [95% CI, 0.44-1.37]; P=0.383). Likewise, in patients with HF with obstructive sleep apnea, women had a higher risk of the primary outcome (81.8% versus 46.3%, HR, 2.37 [95% CI, 1.28-4.38]; P=0.006) and HF rehospitalization (81.8% versus 44.7%, HR, 2.46 [95% CI, 1.32-4.56], P=0.004). However, in patients with HF with central sleep apnea, there was no statistically significant difference between women and men. CONCLUSIONS: In hospitalized patients with HF, female sex was associated with an increased risk of the primary outcome and HF rehospitalization, especially in those with obstructive sleep apnea. Screening for sleep apnea should be emphasized to improve the prognosis. REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02664818.

Urine Metabolic Profiling for Rapid Lung Cancer Screening: A Strategy Combining Rh-Doped SrTiO3-Assisted Laser Desorption/Ionization Mass Spectrometry and Machine Learning.

Lung cancer ranks among the cancers with the highest global incidence rates and mortality. Swift and extensive screening is crucial for the early-stage diagnosis of lung cancer. Laser desorption/ionization mass spectrometry (LDI-MS) possesses clear advantages over traditional analytical methods for large-scale analysis due to its unique features, such as simple sample processing, rapid speed, and high-throughput performance. As n-type semiconductors, titanate-based perovskite materials can generate charge carriers under ultraviolet light irradiation, providing the capability for use as an LDI-MS substrate. In this study, we employ Rh-doped SrTiO3 (STO/Rh)-assisted LDI-MS combined with machine learning to establish a method for urine-based lung cancer screening. We directly analyzed urine metabolites from lung cancer patients (LCs), pneumonia patients (PNs), and healthy controls (HCs) without employing any pretreatment. Through the integration of machine learning, LCs are successfully distinguished from HCs and PNs, achieving impressive area under the curve (AUC) values of 0.940 for LCs vs HCs and 0.864 for LCs vs PNs. Furthermore, we identified 10 metabolites with significantly altered levels in LCs, leading to the discovery of related pathways through metabolic enrichment analysis. These results suggest the potential of this method for rapidly distinguishing LCs in clinical applications and promoting precision medicine.

Changes in properties of human milk under different conditions of frozen storage.

Human milk is the best source of nutrition for infants. Lower freezing temperatures and faster freezing rates allow for better preservation of human milk. However, research on the freezing conditions of human milk is limited. This study investigated the effectiveness of quick freezing and suitable freezing conditions for home preservation. Human milk was stored under different freezing conditions (-18 °C, -18 °C quick freezing, -30 °C, -40 °C, -60 °C, and - 80 °C) for 30, 60, and 90 days and then evaluated for changes in the microbial counts, bioactive protein, and lipid. The results showed that the total aerobic bacterial and Bifidobacteria counts in human milk after storage at freezing temperatures of - 30 °C and lower were closer to those of fresh human milk compared to - 18 °C. Furthermore, the lysozyme loss, lipid hydrolysis degree, and volatile organic compound production were lower. However, -18 °C quick freezing storage was not markedly different from -18 °C in maintaining human milk quality. Based on the results, for household and environmental reasons, the recommended temperature for storing human milk is suggested as -30 °C.