Hydroxyapatite Film with Distinctive Roughness for Simulating the Bone Microenvironment and Revealing the Behavior of Metastatic Mammary Cancer.

Breast cancer is a common malignant tumor arising in normal mammary epithelial tissues. Nearly 75% of the patients with advanced mammary cancer develop bone metastases, resulting in secondary tumor growth, osteolytic bone degradation, and poor prognosis. The bone matrix comprises a highly hierarchical architecture and is composed of a nonmineral organic part, a predominantly type-I collagen, and a mineral inorganic part composed of hydroxyapatite (HA) nanocrystals (Ca10(PO4)6(OH)2). Although there has been extensive research indicating that the material properties of bone minerals affect metastatic breast cancer, it remains unclear how the microenvironment of the bone matrix, such as the roughness, which changes as a result of osteolytic bone remodeling, affects this disease. In this study, we created HA coatings in situ on polyelectrolyte multilayers (PEMs) by incubating PEMs in a mixture of phosphate and calcium ions. The HA films with distinctive roughness were successfully collected by controlling the incubation time, which served as the simulated microenvironment of the bone matrix. MDA-MB231 breast cancer cells were cultured on HA films, and an optimal roughness was observed in the adhesion, proliferation, and expression of two cytokines closely related to bone metastasis. This study contributed to the understanding of the effect of the microenvironment of the bone matrix, such as the roughness, on the metastasis behavior of breast cancer.

Genomic prediction for sugarcane diseases including hybrid Bayesian-machine learning approaches.

Sugarcane smut and Pachymetra root rots are two serious diseases of sugarcane, with susceptible infected crops losing over 30% of yield. A heritable component to both diseases has been demonstrated, suggesting selection could improve disease resistance. Genomic selection could accelerate gains even further, enabling early selection of resistant seedlings for breeding and clonal propagation. In this study we evaluated four types of algorithms for genomic predictions of clonal performance for disease resistance. These algorithms were: Genomic best linear unbiased prediction (GBLUP), including extensions to model dominance and epistasis, Bayesian methods including BayesC and BayesR, Machine learning methods including random forest, multilayer perceptron (MLP), modified convolutional neural network (CNN) and attention networks designed to capture epistasis across the genome-wide markers. Simple hybrid methods, that first used BayesR/GWAS to identify a subset of 1000 markers with moderate to large marginal additive effects, then used attention networks to derive predictions from these effects and their interactions, were also developed and evaluated. The hypothesis for this approach was that using a subset of markers more likely to have an effect would enable better estimation of interaction effects than when there were an extremely large number of possible interactions, especially with our limited data set size. To evaluate the methods, we applied both random five-fold cross-validation and a structured PCA based cross-validation that separated 4702 sugarcane clones (that had disease phenotypes and genotyped for 26k genome wide SNP markers) by genomic relationship. The Bayesian methods (BayesR and BayesC) gave the highest accuracy of prediction, followed closely by hybrid methods with attention networks. The hybrid methods with attention networks gave the lowest variation in accuracy of prediction across validation folds (and lowest MSE), which may be a criteria worth considering in practical breeding programs. This suggests that hybrid methods incorporating the attention mechanism could be useful for genomic prediction of clonal performance, particularly where non-additive effects may be important.

Temporal patterns of organ dysfunction in COVID-19 patients hospitalized in the intensive care unit: A group-based multitrajectory modeling analysis.

BACKGROUND: The course of organ dysfunction (OD) in Corona Virus Disease 2019 (COVID-19) patients is unknown. Herein, we analyze the temporal patterns of OD in intensive care unit-admitted COVID-19 patients. METHODS: Sequential organ failure assessment scores were evaluated daily within 2 weeks of admission to determine the temporal trajectory of OD using group-based multitrajectory modeling (GBMTM). RESULTS: A total of 392 patients were enrolled with a 28-day mortality rate of 53.6%. GBMTM identified four distinct trajectories. Group 1 (mild OD, n = 64), with a median APACHE II score of 13 (IQR 9-21), had an early resolution of OD and a low mortality rate. Group 2 (moderate OD, n = 140), with a median APACHE II score of 18 (IQR 13-22), had a 28-day mortality rate of 30.0%. Group 3 (severe OD, n = 117), with a median APACHR II score of 20 (IQR 13-27), had a deterioration trend of respiratory dysfunction and a 28-day mortality rate of 69.2%. Group 4 (extremely severe OD, n = 71), with a median APACHE II score of 20 (IQR 17-27), had a significant and sustained OD affecting all organ systems and a 28-day mortality rate of 97.2%. CONCLUSIONS: Four distinct trajectories of OD were identified, and respiratory dysfunction trajectory could predict nonpulmonary OD trajectories and patient prognosis.

Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non-additive variation for key traits.

Sugarcane has a complex, highly polyploid genome with multi-species ancestry. Additive models for genomic prediction of clonal performance might not capture interactions between genes and alleles from different ploidies and ancestral species. As such, genomic prediction in sugarcane presents an interesting case for machine learning (ML) methods, which are purportedly able to deal with high levels of complexity in prediction. Here, we investigated deep learning (DL) neural networks, including multilayer networks (MLP) and convolution neural networks (CNN), and an ensemble machine learning approach, random forest (RF), for genomic prediction in sugarcane. The data set used was 2912 sugarcane clones, scored for 26,086 genome wide single nucleotide polymorphism markers, with final assessment trial data for total cane harvested (TCH), commercial cane sugar (CCS), and fiber content (Fiber). The clones in the latest trial (2017) were used as a validation set. We compared prediction accuracy of these methods to genomic best linear unbiased prediction (GBLUP) extended to include dominance and epistatic effects. The prediction accuracies from GBLUP models were up to 0.37 for TCH, 0.43 for CCS, and 0.48 for Fiber, while the optimized ML models had prediction accuracies of 0.35 for TCH, 0.38 for CCS, and 0.48 for Fiber. Both RF and DL neural network models have comparable predictive ability with the additive GBLUP model but are less accurate than the extended GBLUP model.

Acetamiprid and pyridaben poisoning: A case report.

Background: The agricultural industry has experienced beneficial outcomes by implementing contemporary synthetic pesticides, specifically, the mixture of acetamiprid and pyridaben. However, concerns regarding public health have arisen due to the increased number of suicides caused by insecticide poisoning. Nevertheless, limited reports of human exposure to these pesticides have reported various adverse clinical effects. In this study, we present the case of an individual who consumed the acetamiprid and pyridaben mixture for suicidal purposes, and subsequently developed central nervous system depression, hyperlactacidemia, and metabolic acid poisoning, which thus required clinical management. Case report: A 74-year-old woman was transported to our hospital after ingesting a combination of 30 mL of acetamiprid 5 % and pyridaben 5 %. The patient displayed nausea and vomiting symptoms, followed by confusion. An arterial blood gas analysis revealed metabolic acidosis and hyperlactacidemia. The patient was carefully monitored for vital signs and treated with gastric lavage, purgation, and proton pump inhibitors to reduce gastric acid, blood volume, and electrolyte resuscitation. In addition, the patient received 24 h of hemoperfusion (HP) and continuous renal replacement therapy (CRRT). As a result of these interventions, the patient had a speedy recovery and was discharged 10 days later. Conclusion: This case report provided the details of a rare instance of acute poisoning in humans resulting from exposure to newer synthetic pesticides, specifically acetamiprid and pyridaben. The report described the clinical manifestations and effective supportive therapy management. Future clinicians may find the results of this report valuable for identifying clinical symptoms and treating acute poisoning caused by newer synthetic pesticides.

Clinical characteristics, risk factors and outcomes of Klebsiella pneumoniae pneumonia developing secondary Klebsiella pneumoniae bloodstream infection.

PURPOSE: The clinical characteristics of Klebsiella pneumoniae (KP) pneumonia and KP bloodstream infection (KP-BSI) are often reported, while the risk factors for KP pneumonia developing into secondary KP-BSI (KP-pneumonia/KP-BSI) are largely unknown. Therefore, this study attempted to investigate the clinical characteristics, risk factors and outcomes of KP-pneumonia/KP-BSI. METHODS: A retrospective observational study was conducted at a tertiary hospital between January 1, 2018, and December 31, 2020. The patients were divided into groups of KP pneumonia alone and KP pneumonia/KP-BSI, and the clinical information were collected from medical records electronic system. RESULTS: A total of 409 patients were finally recruited. According to the multivariate logistic regression analysis, male sex (adjusted odds ratio [aOR] 3.7; 95% CI, 1.44-9.5), immunosuppression (aOR, 13.52; 95% CI, 2.53,72.22), APACHE II score higher than 21 (aOR, 3.39; 95% CI, 1.41-8.12), serum procalcitonin (PCT) levels above 1.8 ng/ml (aOR, 6.37; 95% CI, 2.67-15.27), ICU stay of more than 2.5 days before pneumonia onset (aOR, 1.09; 95% CI, 1.02,1.17), mechanical ventilation (aOR, 4.96; 95% CI, 1.2,20.5), Klebsiella pneumoniae isolates producing extended spectrum ß-lactamase (ESBL-positive KP) (aOR, 12.93; 95% CI, 5.26-31.76), and inappropriate antibacterial therapy (aOR, 12.38; 95% CI, 5.36-28.58) were independent factors of KP pneumonia/KP BSI. In comparison with the patients with KP pneumonia alone, the patients with KP pneumonia/KP BSI showed an almost 3 times higher incidence of septic shock (64.4% vs. 20.1%, p < 0.01), a longer duration of mechanical ventilation, and longer lengths of ICU stay and total hospital stay (median days, 15 vs. 4,19 vs. 6, 34 vs. 17, respectively, both p < 0.01). Additionally, the overall in-hospital crude mortality rate in the patients with KP-pneumonia/KP-BSI was more than two times higher than that in those with KP pneumonia alone (61.5% vs. 27.4%, p < 0.01). CONCLUSION: Factors including male sex, immunosuppression, APACHE II score higher than 21, serum PCT levels above 1.8 ng/ml, ICU stay of more than 2.5 days before pneumonia onset, mechanical ventilation, ESBL-positive KP, and inappropriate antibacterial therapy are independent risk factors for KP pneumonia/KP-BSI. Of note, the outcomes in patients with KP pneumonia worsen once they develop secondary KP-BSI, which merits more attention.

Relationship between the microRNAs and PI3K/AKT/mTOR axis: Focus on non-small cell lung cancer.

Lung cancer (LC) is one of the significant causes of mortality worldwide. It has been reported that several factors, including late diagnosis, cancer recurrence, lack of access to effective treatments, and especially chemo-resistance, negatively impact the clinical outcome of the available therapeutic regimens. MicroRNAs (miRNAs) are a class of endogenous non-coding small RNAs, which have been demonstrated to be involved in different aspects of cancer pathogenesis, some of which are known as tumor suppressors, and others may have a role in cancer development or progression. One of the most prominent targets of miRNAs in cancer is the phosphoinositide 3-kinases (PI3Ks)/AKT serine/threonine kinase pathway, which is well-known for regulating the cell cycle and several biological phenomena such as cell proliferation, locomotion, survival, metabolism, and protein synthesis. One group activates the PI3K/AKT pathway axis targeting miRNAs, and the other inhibits this axis. Evidence demonstrated that miRNAs could be employed for diagnosis, treatment monitoring and survival evaluation. Moreover, miRNA-based therapeutic approaches can be helpful in clinical settings of cancer therapy. Therefore, this review summarized the functions of different miRNAs associated with the PI3K/AKT pathway, focusing on non-small cell lung cancer (NSCLC) according to their anti-tumor or oncogenic roles, as well as available and possible therapeutic approaches.

Circulating galectin-3 on admission and prognosis in acute heart failure patients: a meta-analysis.

Changes of serum galectin-3 have been associated with the pathogenesis of many cardiovascular diseases. The aim of the study was to evaluate the prognostic role of serum galectin-3 in patients with acute heart failure (AHF) in a meta-analysis. Follow-up studies evaluating the association between serum galectin-3 on admission and clinical outcomes in AHF patients were identified via search of PubMed and Embase databases. A random effects or a fixed effects model was applied to pool the results depending on the heterogeneity. Subgroup analysis was used to evaluate the influences of study characteristics on the outcomes. Overall, 7057 AHF patients from eighteen follow-up studies were included. Higher serum galectin-3 was associated with higher risks of all-cause mortality (adjusted risk ratio [RR], 1.58; p < 0.001), mortality/HF rehospitalization (RR, 1.68; p < 0.001), and cardiovascular mortality (RR, 1.29; p = 0.04), but not HF rehospitalization (RR, 1.24; p = 0.25) in AHF patients. Subgroup analyses showed that study characteristics including study design, sample size, age, gender, left ventricular ejection fraction, galectin-3 variable type, follow-up duration, and adjustment of type B natriuretic peptide did not significantly impact the results. Significant heterogeneities were detected for the outcomes of all-cause mortality and mortality/HF rehospitalization. However, trim-and-fill analyses by including the imputed studies to generate symmetrical funnel plots showed similar significant meta-analysis results. These results suggested that higher serum galectin-3 may be associated with poor prognosis in AHF patients. Further studies are needed to determine the mechanisms underlying the potential prognostic role of galectin-3 in AHF.

The treatment efficacy of galcanezumab for migraine: A meta-analysis of randomized controlled trials.

The treatment efficacy of galcanezumab for migraine remained controversial. We conducted a systematic review and meta-analysis to explore the influence of galcanezumab versus placebo on the treatment of migraine. We searched PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases through October 2018 for randomized controlled trials (RCTs) assessing the effect of galcanezumab versus placebo for patients with migraine. This meta-analysis was performed using the random-effect model. Six RCTs were included in the meta-analysis. Overall, compared with control group for migraine patients, galcanezumab resulted in greater overall mean reduction in the number of monthly migraine headache day (MHD) (P < 0.05). In contrast, galcanezumab was associated with increased adverse events (risk ratio (RR) = 1.08; 95% CI = 1.01-1.15; P = 0.02), but with no significant impact on serious adverse events between two groups (RR = 2.0; 95% CI = 0.95-4.21; P = 0.07).Galcanezumab showed favorable promotion for the preventive treatment of migraine patients.

Efficacy and Safety of Antiplatelet Therapy Plus Xa Factor Inhibitors in Patients with Coronary Heart Disease: A Meta-Analysis.

BACKGROUND The aim of this study was to systematically evaluate the effect of oral Xa inhibitors plus antiplatelet therapy in the treatment of coronary artery disease. MATERIAL AND METHODS All randomized controlled trials (RCTs) about antiplatelet therapy plus Xa factor inhibitors for coronary artery disease from database inception to January 2019 were searched for and collected from PubMed, Embase, and the Cochrane Library. Two reviewers extracted and analyzed the data independently. Additionally, RevMan 5.0 software was applied for meta-analysis. RESULTS Seven RCTs with 50 044 patients were included. The meta-analysis results showed that treatment with antiplatelet therapy plus Xa factor inhibitors in patients with coronary artery disease could significantly reduce the risk of ischemic events (P<0.00001). Besides, risk of all-cause mortality (P=0.003), myocardial infarction (P=0.02) and ischemic stroke (P<0.0001) were also significantly reduced. However, risk of massive hemorrhage after TIMI (P<0.00001), minor hemorrhage after TIMI (P<0.00001), and intracranial hemorrhage (P=0.006) were significantly increased, respectively. Xa inhibition drugs also intended to increase risk of fatal bleeding, but there was no significant difference (P=0.08). CONCLUSIONS Antiplatelet therapy plus Xa factor inhibitors in patients with coronary artery disease was effective, which could reduce the risk of ischemic composite endpoints, all-cause mortality, myocardial infarction, and ischemic stroke. However, it could significantly increase risk of bleeding in terms of safety.

Effect of paracetamol (acetaminophen) on body temperature in acute stroke: A meta-analysis.

PURPOSE: The objective of this study was to assess the efficacy of paracetamol (acetaminophen) on body temperature in acute stroke. METHODS: Medline, Cochrane Central Register of Controlled Trials, EMBASE, Chinese BioMedical Literature Database, China National Knowledge Infrastructure, and the World Health Organization (WHO) International Clinical Trials Registry Platform were searched electronically. Relevant journals and references of studies included were hand-searched for randomized controlled trials (RCT) and controlled clinical trials (CCT) regarding the efficacy of paracetamol (acetaminophen) on body temperature in acute stroke. Two reviewers independently performed data extraction and quality assessment. Data were analyzed using RevMan 5.3 software by the Cochrane Collaboration. RESULTS: Five studies were included. To compare the efficacy of paracetamol (acetaminophen) in acute stroke, the pooled RR (Risk Ratio) and its 95% CI of body temperature reduction at 24h from the start of treatment were -0.3 (95% CI: -0.52 to -0.08), with statistical significance (P=0.007). Consistently, the pooled RR (Risk Ratio) and its 95% CI of body temperature at 24h from the start of treatment were -0.22 (-0.29, -0.15), with statistical significance (P<0.00001). When analyzing the body temperature reduction after 5days from the start of treatment, the pooled RR (Risk Ratio) and its 95% CI were 0.04 (95% CI: -0.20 to 0.29), with no statistical significance (P=0.73). For functional outcome (mRS≤2) analysis, the pooled RR and its 95% CI were 1.08 (0.88, 1.32), with no statistical significance (P=0.45). In addition, the difference of serious adverse events between acetaminophen and placebo was 0.86 (95% CI: 0.62 to 1.2), with no statistical significance (P=0.27). CONCLUSION: Acetaminophen was revealed to have some favorable influence in body temperature reduction in acute stroke, but showed no important effect on improving functional outcome and reducing adverse events of patients. WHAT THIS PAPER ADDS: What is already known on this subject? Paracetamol (acetaminophen) is one of the most commonly used antipyretic drugs and has some capability to reduce body temperature through acting on central nervous system. WHAT THIS STUDY ADDS: Acetaminophen showed some capability to decrease body temperature for acute stroke. Acetaminophen could not improve functional outcome and reduce adverse events of patients with acute stroke.