Palliative care needs and utilisation of specialist services for people diagnosed with motor neuron disease: a national population-based study.

INTRODUCTION: There is a growing emphasis on the importance of the availability of specialist palliative care for people with motor neuron disease (MND). However, the palliative care needs of this population and the utilisation of different specialist services remain poorly defined. OBJECTIVES: To (1) describe clinical characteristics, symptom burden and functional levels of patients dying with MND on their admission to palliative care services; (2) determine factors associated with receiving inpatient or community palliative care services. DESIGN: An observational study based on point-of-care assessment data from the Australian Palliative Care Outcomes Collaboration. PARTICIPANTS: A total of 1308 patients who received palliative care principally because of MND between 1 January 2013 and 31 December 2020. MEASURES: Five validated clinical instruments were used to assess each individual's function, distress from symptoms, symptom severity and urgency and acuity of their condition. RESULTS: Most patients with MND had no or mild symptom distress, but experienced a high degree of functional impairment. Patients who required 'two assistants for full care' relative to those who were 'independent' (OR=11.53, 95% CI: 4.87 to 27.26) and those in 'unstable' relative to 'stable' palliative care phases (OR=16.74, 95% CI: 7.73 to 36.24) were more likely to use inpatient versus community-based palliative care. Associations between the use of different palliative care services and levels of symptom distress were not observed in this study. CONCLUSIONS: Patients with MND were more likely to need assistance for decreased function and activities of daily living, rather than symptom management. This population could have potentially been cared for in the palliative phase in a community setting if greater access to supportive services were available in this context.

The haplotype-resolved genome of diploid Chrysanthemum indicum unveils new acacetin synthases genes and their evolutionary history.

Acacetin, a flavonoid compound, possesses a wide range of pharmacological effects, including antimicrobial, immune regulation, and anticancer effects. Some key steps in its biosynthetic pathway were largely unknown in flowering plants. Here, we present the first haplotype-resolved genome of Chrysanthemum indicum, whose dried flowers contain abundant flavonoids and have been utilized as traditional Chinese medicine. Various phylogenetic analyses revealed almost equal proportion of three tree topologies among three Chrysanthemum species (C. indicum, C. nankingense, and C. lavandulifolium), indicating that frequent gene flow among Chrysanthemum species or incomplete lineage sorting due to rapid speciation might contribute to conflict topologies. The expanded gene families in C. indicum were associated with oxidative functions. Through comprehensive candidate gene screening, we identified five flavonoid O-methyltransferase (FOMT) candidates, which were highly expressed in flowers and whose expressional levels were significantly correlated with the content of acacetin. Further experiments validated two FOMTs (CI02A009970 and CI03A006662) were capable of catalyzing the conversion of apigenin into acacetin, and these two genes are possibly responsible acacetin accumulation in disc florets and young leaves, respectively. Furthermore, combined analyses of ancestral chromosome reconstruction and phylogenetic trees revealed the distinct evolutionary fates of the two validated FOMT genes. Our study provides new insights into the biosynthetic pathway of flavonoid compounds in the Asteraceae family and offers a model for tracing the origin and evolutionary routes of single genes. These findings will facilitate in vitro biosynthetic production of flavonoid compounds through cellular and metabolic engineering and expedite molecular breeding of C. indicum cultivars.

Development and Validation of a Nomograph Model for Post-Operative Central Nervous System Infection after Craniocerebral Surgery.

PURPOSE: A nomograph model of predicting the risk of post-operative central nervous system infection (PCNSI) after craniocerebral surgery was established and validated. METHODS: The clinical medical records of patients after cranial surgery in Renmin Hospital of Wuhan University from January 2020 to September 2022 were collected, of whom 998 patients admitted to Shouyi Hospital District were used as the training set and 866 patients admitted to Guanggu Hospital District were used as the validation set. Lasso regression was applied to screen the independent variables in the training set, and the model was externally validated in the validation set. RESULTS: A total of 1864 patients after craniocerebral surgery were included in this study, of whom 219 (11.75%) had PCNSI. Multivariate logistic regression analysis showed that age > 70 years, a previous history of diabetes, emergency operation, an operation time ≥ 4 h, insertion of a lumbar cistern drainage tube ≥ 72 h, insertion of an intracranial drainage tube ≥ 72 h, intraoperative blood loss ≥ 400 mL, complicated with shock, postoperative albumin ≤ 30 g/L, and an ICU length of stay ≥ 3 days were independent risk factors for PCNSI. The area under the curve (AUC) of the training set was 0.816 (95% confidence interval (95%CI), 0.773-0.859, and the AUC of the validation set was 0.760 (95%CI, 0.715-0.805). The calibration curves of the training set and the validation set showed p-values of 0.439 and 0.561, respectively, with the Hosmer-Lemeshow test. The analysis of the clinical decision curve showed that the nomograph model had high clinical application value. CONCLUSION: The nomograph model constructed in this study to predict the risk of PCNSI after craniocerebral surgery has a good predictive ability.

Protein succinylation associated with the progress of hepatocellular carcinoma.

Although post-translational modification is critical to tumorigenesis, how succinylation modification of lysine sites influences hepatocellular carcinoma (HCC) remains obscure. 90 tumours and paired adjacent normal tissue of liver cancer were enrolled for succinylation staining. 423 HCC samples with 20 genes related to succinylation modification from TCGA were downloaded for model construction. Statistical methods were employed to analyse the data, including the Non-Negative Matrix Factorization (NMF) algorithm, t-Distributed Stochastic Neighbour Embedding (t-SNE) algorithm, and Cox regression analysis. The staining pan-succinyllysine antibody staining indicated that tumour tissues had a higher succinyllysine level than adjacent tissues (p < 0.001), which could be associated with a worse prognosis (p = 0.02). The survival was associated with pathological stage, tumour recurrence status and succinyllysine intensity in the univariate or multivariable cox survival analysis model. The risk model from 20 succinyllysine-related genes had the best prognosis prediction. The high expression of succinylation modification in HCC contributed to the worse patient survival prognosis. Model construction of 20 genes related to succinylation modification (MEAF6, OXCT1, SIRT2, CREBBP, KAT5, SIRT4, SIRT6, SIRT7, CPT1A, GLYATL1, SDHA, SDHB, SDHC, SDHD, SIRT1, SIRT3, SIRT5, SUCLA2, SUCLG1 and SUCLG2) could be reliable in predicting prognosis in HCC.

Identification of Prognostic Genes in Hepatocellular Carcinoma.

Background: Previous studies have demonstrated the important role of tumor stem cells (TSCs) in the development of hepatocellular carcinoma (HCC); however, TSC-related genetic markers have not been investigated. Aim: The aim of the present study was to identify stem cell-related signature genes to predict the prognosis of HCC, using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Methods: In total, 423 liver HCC tissue samples, including 373 tumor and 50 adjacent normal tissue samples from TCGA, and 115 primary tumor and 52 adjacent non-tumor tissue samples from the GEO GSE76427 database, were used in the present study. The non-negative matrix factorization (NMF) algorithm, t-distributed stochastic neighbor embedding (t-SNE) algorithm and Cox regression analysis were combined for model construction and validation. Results: Overall, six clusters were identified using the NMF and t-SNE algorithms with 470 stem cell-related genes. The results demonstrated that patients in cluster 5 had the worst prognosis. For multivariate Cox survival analysis, 15 genes with optimal lambda values were chosen and eight genes were incorporated into the final regression model using the optimal Akaike information criterion value. Validation of the risk model using the aforementioned eight signature genes demonstrated the models strong reliability and stable predictive performance. Conclusion: The results of the present study indicated that the eight-gene (Hes family BHLH transcription factor 5, KIT ligand, methyltransferase-like 3, proteasome 26S subunit non-ATPase 1, Ras-related protein Rab-10, treacle ribosome biogenesis factor 1, YTH N6-methyladenosine RNA binding protein 2 and Zinc Finger CCCH-Type Containing 13) signature constructed by the model may be reliable in predicting the prognosis of patients with HCC.

Exosomes Derived From Hypertrophic Cardiomyocytes Induce Inflammation in Macrophages via miR-155 Mediated MAPK Pathway.

The inflammatory immune microenvironment plays an important role in the development of cardiac hypertrophy. Exosomes have emerged as the potent modulators of inflammatory responses. This study aimed to determine how exosomes derived from angiotensin II (Ang II)-induced hypertrophic cardiomyocytes (HCs) interfere with the inflammatory signal pathways in macrophages. Herein, we showed that increased exosome release was observed in HCs when compared to normal cardiomyocytes (NCs). Incubation of the murine macrophage cell line RAW264.7 in the presence of exosomes isolated from the culture media of HCs triggers the secretion of inflammatory cytokines interleukin (IL)-6 and IL-8. Cytokines release induced by HCs-derived exosomes was prevented by down-regulation of Argonaute2 (AGO2), suggesting that the non-coding RNAs were involved in exosome-induced inflammatory responses in RAW 264.7 macrophages. RNA sequencing assays further demonstrated that a total of seven microRNAs were differentially expressed between NCs-derived and HCs-derived exosomes. Importantly, miR-155 played a crucial role in the initiation of inflammation in macrophages. Further analyses demonstrated that HCs-derived exosomes induced the phosphorylation of extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 via miR-155. Our results support the concept that exosomal microRNAs have emerged as important inflammatory response modulators regulating cardiac hypertrophy.

A first look at the effects of long inter-pregnancy interval and advanced maternal age on perinatal outcomes: A retrospective cohort study.

BACKGROUND: After China's One-child Policy was replaced with the Two-child Policy in 2013, the rate of second pregnancies with a longer inter-pregnancy interval (IPI) has suddenly increased in that country; however, the effect of long IPIs (≥49 months) on perinatal outcomes remains unreported. METHODS: This was a retrospective cohort study in China from July 2015 through June 2016. We used univariate and multivariate logistic regression models to test the associations among IPI, maternal age, and perinatal outcome (preterm delivery, term low birthweight, and small-for-gestational age). We included baseline factors and variables with biological plausibility as confounders. RESULTS: Our analytic sample included 3309 second pregnancies. The mean IPI was 75.36 months. Compared with second pregnancies with a short IPI of 7-24 months, those with long IPIs had higher adjusted odds ratios (ORs) of preterm delivery (1.70-2.00 [95% CI 1.20-3.33]) and term low birthweight (2.16-2.68 [1.10-6.17]), but not small-for-gestational age. The mean maternal age at current delivery was 32.0 years. Compared with the reference group (25-29 years), second pregnancies for the oldest maternal age group (≥35 years) showed no statistically significant increased ORs for adverse perinatal outcomes. CONCLUSION: Long IPI is a significant contributor to preterm delivery and term low birthweight. Health care providers need to pay close attention to preterm delivery prevention and fetal growth during prenatal care for second pregnancies where the mothers have long IPIs.

A sandwich dipstick assay for ATP detection based on split aptamer fragments.

Aptamer-based strip assay is an easy, highly efficient and low-cost detection method, which has been developed and easily applied to onsite detection. A new sensitive sandwich dipstick assay for adenosine triphosphate (ATP) detection was successfully developed based on specific recognition between split aptamer fragments and the target. In this method, the thiolated aptamer was first conjugated to the surface of gold nanoparticles (AuNPs), while the biotin-aptamer was immobilized on the surface of a nitrocellulose filter in the test line. In the presence of ATP, the thiol-aptamer/ATP/biotin-aptamer complexes were generated, which led to an obvious increase in optical signals at the test line. Under the optimal determination conditions, an excellent linear logarithmic response to the ATP concentration was obtained within the range of 0.5 µM to 5 mM. The limit of detection (LOD) of 0.5 µM was reached at a signal-to-noise ratio of 3. The dipstick assay showed a good average recovery of 96-108 % with the RSD of less than 20 % in urine samples. The proposed method exhibited high specificity against other nucleotides such as the uridine triphosphate (UTP), cytidine triphosphate (CTP), and guanosine triphosphate (GTP). The results indicated that the dipstick strip may be considered as an inexpensive screening tool for onsite ATP determination. Graphical Abstract A simple split aptamer fragments based sandwich-type dipstick assay was developed for ATP detection.

Lentivirus-Mediated siRNA Targeting ER-α Inhibits Tumorigenesis and Induces Apoptosis in Hepatocarcinoma Cells.

BACKGROUND AND OBJECTIVES: Estrogen receptor-α (ER-α) plays important roles in hepatocarcinogenesis. Recent studies have shown that ER-α could lead to cell cycle progression or inhibition of apoptosis. To better understand the role of ER-α, RNA interference (RNAi) was used to inhibit ER-α expression in the human hepatocellular carcinoma (HCC) cells. METHODS: Lentivirus-mediated ER-α small interfering RNA (siRNA) was transfected into HCC cells Hep3B. ER-α expression was monitored by real-time polymerase chain reaction (PCR) and western blot. Cell proliferation, apoptosis, and invasion were examined by methyl thiazol tetrazolium (MTT), flow cytometry (FCM), and invasion assay, respectively. RESULTS: ER-α siRNA efficiently downregulated the expression of ER-α in Hep3B cells at both mRNA and protein levels in a time-dependent manner. ER-α siRNA also inhibited cell proliferation and reduced cell invasion (compared with other groups, P < 0.05, resp.). Furthermore, knockdown of ER-α slowed down the cell population at S phase and increased the rate of apoptosis (P < 0.05, resp.). CONCLUSION: ER-α knockdown suppressed the growth of HCC cells. Thus, ER-α may play a very important role in carcinogenesis of HCC and its knockdown may offer a new potential gene therapy approach for human liver cancer in the future.

Gold nanoparticle-based colorimetric aptasensor for rapid detection of six organophosphorous pesticides.

Fast immunoassay-based screening methods are unavailable for most small-molecule pesticides because of a lack of immunogenicity and the difficulty in obtaining antibodies by animal immunization. Aptamers are single-stranded DNA molecules selected through an in vitro process, which can bind to any target including nonimmunogenic small molecules with high affinity and specificity. Although various aptamer-based sensing methods have been developed for antibiotics, microorganisms, heavy metal ions, and biotoxins, there are few reports on aptamer-based methods for quick detection of organophosphorous pesticides. The gold (Au) nanoparticle (AuNP) colorimetric assay is a widely utilized rapid detection method because of properties such as easy operation and visualized results. In the present study, organophosphorous pesticide aptamers were adsorbed on the surface of AuNPs to stabilize the AuNP solution against high concentrations of salt to prevent AuNP aggregation. After the addition of targets, the aptamers binding to the targets are detached from the AuNPs, resulting in aggregation of AuNPs and a color change from red to purple-blue. The proposed method can detect 6 organophosphorous pesticides with good recoveries from 72% to 135% in environmental river water samples. The present study provides a new way for simple, rapid, and multiplex detection of organophosphorous pesticides.

Highly sensitive colorimetric detection of 17ß-estradiol using split DNA aptamers immobilized on unmodified gold nanoparticles.

Gold nanoparticle (AuNP) based colorimetric aptasensor have been developed for many analytes recently largely because of the ease of detection, high sensitivity, and potential for high-throughput analysis. Most of the target aptamers for detection have short sequences. However, the approach shows poor performance in terms of detection sensitivity for most of the long-sequence aptamers. To address this problem, for the first time, we split the 76 mer aptamer of 17ß-estradiol into two short pieces to improve the AuNP based colorimetric sensitivity. Our results showed that the split P1 + P2 still retained the original 76 mer aptamer's affinity and specificity but increased the detection limit by 10-fold, demonstrating that as low as 0.1 ng/mL 17ß-estradiol could be detected. The increased sensitivity may be caused by lower aptamer adsorption concentration and a lower affinity to the AuNPs of a short single-strand DNA (ssDNA) sequence. Our study provided a new way to use long-sequence aptamers to develop a highly sensitive AuNP-based colorimetric aptasensor.

Colorimetric aptasensor using unmodified gold nanoparticles for homogeneous multiplex detection.

Colorimetric aptasensors using unmodified gold nanoparticles (AuNPs) have attracted much attention because of their low cost, simplicity, and practicality, and they have been developed for various targets in the past several years. However, previous research has focused on developing single-target assays. Here, we report the development of a homogeneous multiplex aptasensor by using more than one class of aptamers to stabilize AuNPs. Using sulfadimethoxine (SDM), kanamycin (KAN) and adenosine (ADE) as example targets, a KAN aptamer (750 nM), an SDM aptamer (250 nM) and an ADE aptamer (500 nM) were mixed at a 1∶1∶1 volume ratio and adsorbed directly onto the surface of unmodified AuNPs by electrostatic interaction. Upon the addition of any of the three targets, the conformation of the corresponding aptamer changed from a random coil structure to a rigid folded structure, which could not adsorb and stabilize AuNPs. The AuNPs aggregated in a specific reaction buffer (20 mM Tris-HCl containing 20 mM NaCl and 5 mM KCl), which led to a color change from red to purple/blue. These results demonstrate that the multiplex colorimetric aptasensor detected three targets simultaneously while maintaining the same sensitivity as a single-target aptasensor for each individual target. The multiplex aptasensor could be extended to other aptamers for various molecular detection events. Due to its simple design, easy operation, fast response, cost effectiveness and lack of need for sophisticated instrumentation, the proposed strategy provides a powerful tool to examine large numbers of samples to screen for a small number of potentially positive samples containing more than one analyte, which can be further validated using sophisticated instruments.