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Background Patients with polycystic ovary syndrome (PCOS) face a greater risk of miscarriage during pregnancy. However, the relationship between PCOS and missed abortion (MA) has not been comprehensively studied. Method This retrospective study included 194 pregnant women with PCOS, diagnosed using the 2004 Rotterdam criteria. Participants were categorized into the MA group ( n  = 100) or the control group (term live births, n  = 94) based on pregnancy outcomes. Baseline characteristics and clinical features were collected, and statistical analyses were performed to identify MA risk factors. Results At baseline, the MA group had a lower BMI ( p  = 0.000) and higher educational level ( p  = 0.026) compared to the control group, with no significant differences in other baseline characteristics. Regarding clinical features, significant differences were observed in conception method, menstrual period duration, menstrual patterns, total testosterone, fasting insulin, and anti-Müllerian hormone (AMH) levels. After adjusting for BMI and educational level, univariate analysis identified oligomenorrhea (OR = 10.502, p  = 0.000), menstrual period duration (OR = 1.888, p  = 0.002), total testosterone (OR = 1.047, p  = 0.009), and AMH (OR = 1.286, p  = 0.044) as significant risk factors. Multivariate logistic regression confirmed that menstrual period duration (OR = 2.074, p  = 0.003), oligomenorrhea (OR = 12.487, p  < 0.001), and total testosterone (OR = 1.067, p  = 0.003) were independently associated with MA risk in PCOS patients. Conclusion This study identifies menstrual period duration, oligomenorrhea, and total testosterone as independent risk factors for MA in women with PCOS. These findings highlight the importance of monitoring menstrual irregularities and hormonal profiles to optimize pregnancy outcomes in PCOS patients.

In December 2019, coronavirus disease 2019 (COVID-19), which is caused by the new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in Wuhan (Hubei province, China) 1 ; it soon spread across the world. In this ongoing pandemic, public health concerns and the urgent need for effective therapeutic measures require a deep understanding of the epidemiology, transmissibility and pathogenesis of COVID-19. Here we analysed clinical, molecular and immunological data from 326 patients with confirmed SARS-CoV-2 infection in Shanghai. The genomic sequences of SARS-CoV-2, assembled from 112 high-quality samples together with sequences in the Global Initiative on Sharing All Influenza Data (GISAID) dataset, showed a stable evolution and suggested that there were two major lineages with differential exposure history during the early phase of the outbreak in Wuhan. Nevertheless, they exhibited similar virulence and clinical outcomes. Lymphocytopenia, especially reduced CD4 + and CD8 + T cell counts upon hospital admission, was predictive of disease progression. High levels of interleukin (IL)-6 and IL-8 during treatment were observed in patients with severe or critical disease and correlated with decreased lymphocyte count. The determinants of disease severity seemed to stem mostly from host factors such as age and lymphocytopenia (and its associated cytokine storm), whereas viral genetic variation did not significantly affect outcomes. Genome sequences from 112 patients with confirmed SARS-CoV-2 infection showed two clades of SARS-CoV-2 virus with similar virulence and clinical outcome, and clinical data from 326 cases suggest that T cell depletion and cytokine bursts are associated with a worse prognosis.

Osteosarcoma (OS) is a primary malignant bone tumor that most commonly affects children, adolescents, and young adults. Here, we comprehensively analyze genomic, epigenomic and transcriptomic data from 121 OS patients. Somatic mutations are diverse within the cohort, and only TP53 is significantly mutated. Through unsupervised integrative clustering of the multi-omics data, we classify OS into four subtypes with distinct molecular features and clinical prognosis: (1) Immune activated (S-IA), (2) Immune suppressed (S-IS), (3) Homologous recombination deficiency dominant (S-HRD), and (4) MYC driven (S-MD). MYC amplification with HR proficiency tumors is identified with a high oxidative phosphorylation signature resulting in resistance to neoadjuvant chemotherapy. Potential therapeutic targets are identified for each subtype, including platinum-based chemotherapy, immune checkpoint inhibitors, anti- VEGFR , anti- MYC and PARPi-based synthetic lethal strategies. Our comprehensive integrated characterization provides a valuable resource that deepens our understanding of the disease, and may guide future clinical strategies for the precision treatment of OS. Osteosarcoma survival rates have been largely unchanged for several decades, and treatment response is variable. Here, the authors analyzed genomic, transcriptomic and epigenomic data from 121 osteosarcoma patients and identify subtypes related to treatment outcome.

Lymph node (LN) metastasis is a key prognostic factor in laryngeal squamous cell carcinoma (LSCC). Emerging evidence implicates the role of the microbiome in cancer progression. This study aimed to investigate the microbial features associated with lymph node metastasis in LSCC and their potential for patient stratification. Using 16 S rRNA gene sequencing, we characterized the microbiome of tumor tissues, adjacent normal tissues, lymph nodes, and oral rinses from 108 LSCC patients, including 36 with (LN+) and 72 without (LN-) cervical LN metastasis. Microbial functional potential was predicted using PICRUSt2. Based on repeated stratified 3 cross-validation, random forest models were used to identify metastasis-associated genera. Significant microbial differences were observed between LN + and LN- tumor tissues, with Ralstonia enriched in LN + tumors and Fusobacterium more abundant in LN- cases. All genera detected in lymph nodes were also found in tumor tissues. Functional predictions revealed enrichment of lipid biosynthesis, energy metabolism, and cell wall synthesis pathways in LN + patients, particularly in tumor and oral rinse samples, with low intra-group variability. Classifiers based on tumor, lymph node, and oral microbiota demonstrated the ability to distinguish LN + from LN- patients. The lymph node-derived classifier achieved an accuracy of 84.31% (95% confidence interval [CI]: 81.76% − 86.85%), followed by the tumor-based model (AUC = 84.11%, 95% CI: 81.75% − 86.46%) and oral rinse classifier (AUC = 79.88%, 95% CI: 77.09% − 83.11%). A tumor-specific 17 genera panel showed a discriminative efficacy of 84.11% (95% CI: 81.75% − 86.46%) in tumor tissues. These findings suggest that microbiome alterations may be associated with lymph node metastasis in LSCC. In addition, the oral microbiome showed potential as a non-invasive tool for occult lymph node metastasis detection. However, these results are preliminary and require validation in larger, independent cohorts.

Mild cognitive impairment (MCI) is an intermediate condition between normal aging and dementia. Drug intervention is an important way to prevent MCI from developing into dementia. GuiLingJi (GLJ) is a traditional Chinese medicine formulae and it has the effect of enhancing memory. In view of the absence of special effective drugs for MCI, GLJ warrants investigation as a potential therapeutic agent. This study uses a rat model of MCI, induced by D-galactose injections and a semi-high-fat diet, to explore the therapeutic efficacy of GLJ in MCI and elucidate the potential underlying pharmacological mechanisms by behavioral experiments and biochemical indexes, combined with serum and hippocampal metabolomics. GLJ treatment mitigated D-galactose combined with semi-high-fat diet induced impairments, including abnormal blood lipids, oxidative stress, inflammation, cholinergic dysfunction, apoptosis, and reduced brain-derived neurotrophic factors, along with hippocampal damage. LC-MS metabolomics indicated that these effects involved unsaturated fatty acid and amino acid metabolism. By normalizing linoleic acid and α-linolenic acid levels and activating GPR120, GLJ inhibited the NF-κB/TNF-α pathway. These findings demonstrate that GLJ alleviates MCI symptoms, at least in part, by modulating fatty acid metabolism and suppressing neuroinflammation the GPR120/NF-κB pathway. This study supports GLJ as a promising proprietary TCM formulation for MCI treatment.

Background Recent studies have uncovered that the microbiota in patients with head and neck cancers is significantly altered and may drive cancer development. However, there is limited data to explore the unique microbiota of laryngeal squamous cell carcinoma (LSCC), and little is known regarding whether the oral microbiota can be utilized as an early diagnostic biomarker. Methods Using 16S rRNA gene sequencing, we characterized the microbiome of oral rinse and tissue samples from 77 patients with LSCC and 76 control patients with vocal polyps, and then performed bioinformatic analyses to identify taxonomic groups associated with clinicopathologic features. Results Multiple bacterial genera exhibited significant differences in relative abundance when stratifying by histologic and tissue type. By exploiting the distinct microbial abundance and identifying the tumor-associated microbiota taxa between patients of LSCC and vocal polyps, we developed a predictive classifier by using rinse microbiota as key features for the diagnosis of LSCC with 85.7% accuracy. Conclusion This is the first evidence of taxonomical features based on the oral rinse microbiome that could diagnose LSCC. Our results revealed the oral rinse microbiome is an understudied source of clinical variation and represents a potential non-evasive biomarker of LSCC.

Continuous long-term eddy covariance (EC) measurements of CO2 fluxes (NEE) in a variety of terrestrial ecosystems are critical for investigating the impacts of climate change on ecosystem carbon cycling. However, due to a number of issues, approximately 30–60% of annual flux data obtained at EC flux sites around the world are reported as gaps. Given that the annual total NEE is mostly determined by variations in the NEE data with time scales longer than one day, we propose a novel framework to perform gap filling in NEE data based on machine learning (ML) and time series decomposition (TSD). The novel framework combines the advantages of ML models in predicting NEE with meteorological and environmental inputs and TSD methods in extracting the dominant varying trends in NEE time series. Using the NEE data from 25 AmeriFlux sites, the performance of the proposed framework is evaluated under four different artificial scenarios with gap lengths ranging in length from one hour to two months. The combined approach incorporating random forest and moving average (MA-RF) is observed to exhibit better performance than other approaches at filling NEE gaps in scenarios with different gap lengths. For the scenario with a gap length of seven days, the MA-RF improves the R2 by 34% and reduces the root mean square error (RMSE) by 55%, respectively, compared to a traditional RF-based model. The improved performance of MA-RF is most likely due to the reduction in data variability and complexity of the variations in the extracted low-frequency NEE data. Our results indicate that the proposed MA-RF framework can provide improved gap filling for NEE time series. Such improved continuous NEE data can enhance the accuracy of estimations regarding the ecosystem carbon budget.

β2-agonists are a group of synthetic phenylethanolamine compounds which are traditionally used for treating bronchospasm. These compounds can also increase skeletal muscle mass and decrease body fat. The illegal use of β2-agonists in food-producing animals results in residue of β2-agonists in edible tissues and causes adverse health effects in humans. Thus, the detection of β2-agonists at trace level in complex sample matrices is of great importance for monitoring the abuse of β2-agonists. Many methods have been developed to detect β2-agonists. Among them, a variety of antigen–antibody interaction-based techniques have been established to detect β2-agonists in various samples, including animal feed, urine, serum, milk, tissues and hair. In this review, we summarized current achievement in the extraction of β2-agonists from testing samples and detection of β2-agonists using immunological techniques. Future perspectives were briefly discussed.

Phages provide a potential therapy for multi-drug-resistant (MDR) bacteria. However, a significant portion of viral genes often remains unknown, posing potential dangers. The identification of non-essential genes helps dissect and simplify phage genomes, but current methods have various limitations. In this study, we present an in vivo two-plasmid transposon insertion system to assess the importance of phage genes, which is based on the V. cholerae transposon Tn6677, encoding a nuclease-deficient type I-F CRISPR–Cas system. We first validated the system in Pseudomonas aeruginosa PAO1 and its phage S1. We then used the selection marker AcrVA1 to protect transposon-inserted phages from CRISPR-Cas12a and enriched the transposon-inserted phages. For a pool of selected 10 open-reading frames (2 known functional protein genes and 8 hypothetical protein genes) of phage S1, we identified 5 (2 known functional protein genes and 3 hypothetical protein genes) as indispensable genes and the remaining 5 (all hypothetical protein genes) as dispensable genes. This approach offers a convenient, site-specific method that does not depend on homologous arms and double-strand breaks (DSBs), holding promise for future applications across a broader range of phages and facilitating the identification of the importance of phage genes and the insertion of genetic cargos.

Heart failure (HF) patients in general have a higher risk of developing cancer. Several animal studies have indicated that cardiac remodeling and HF remarkably accelerate tumor progression, highlighting a cause-and-effect relationship between these two disease entities. Targeting ferroptosis, a prevailing form of non-apoptotic cell death, has been considered a promising therapeutic strategy for human cancers. Exosomes critically contribute to proximal and distant organ-organ communications and play crucial roles in regulating diseases in a paracrine manner. However, whether exosomes control the sensitivity of cancer to ferroptosis via regulating the cardiomyocyte-tumor cell crosstalk in ischemic HF has not yet been explored. Here, we demonstrate that myocardial infarction (MI) decreased the sensitivity of cancer cells to the canonical ferroptosis activator erastin or imidazole ketone erastin in a mouse model of xenograft tumor. Post-MI plasma exosomes potently blunted the sensitivity of tumor cells to ferroptosis inducers both in vitro in mouse Lewis lung carcinoma cell line LLC and osteosarcoma cell line K7M2 and in vivo with xenograft tumorigenesis model. The expression of miR-22-3p in cardiomyocytes and plasma-exosomes was significantly upregulated in the failing hearts of mice with chronic MI and of HF patients as well. Incubation of tumor cells with the exosomes isolated from post-MI mouse plasma or overexpression of miR-22-3p alone abrogated erastin-induced ferroptotic cell death in vitro. Cardiomyocyte-enriched miR-22-3p was packaged in exosomes and transferred into tumor cells. Inhibition of cardiomyocyte-specific miR-22-3p by AAV9 sponge increased the sensitivity of cancer cells to ferroptosis. ACSL4, a pro-ferroptotic gene, was experimentally established as a target of miR-22-3p in tumor cells. Taken together, our findings uncovered for the first time that MI suppresses erastin-induced ferroptosis through releasing miR-22-3p-enriched exosomes derived from cardiomyocytes. Therefore, targeting exosome-mediated cardiomyocyte/tumor pathological communication may offer a novel approach for the ferroptosis-based antitumor therapy.