Effect of SlSAHH2 on metabolites in over-expressed and wild-type tomato fruit.

Background: Tomato (Solanum lycopersicum) is an annual or perennial herb that occupies an important position in daily agricultural production. It is an essential food crop for humans and its ripening process is regulated by a number of genes. S-adenosyl-l-homocysteine hydrolase (AdoHcyase, EC 3.3.1.1) is widespread in organisms and plays an important role in regulating biological methylation reactions. Previous studies have revealed that transgenic tomato that over-express SlSAHH2 ripen earlier than the wild-type (WT). However, the differences in metabolites and the mechanisms driving how these differences affect the ripening cycle are unclear. Objective: To investigate the effects of SlSAHH2 on metabolites in over-expressed tomato and WT tomato. Methods: SlSAHH2 over-expressed tomato fruit (OE-5# and OE-6#) and WT tomato fruit at the breaker stage (Br) were selected for non-targeted metabolome analysis. Results: A total of 733 metabolites were identified by mass spectrometry using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the Human Metabolome database (HMDB). The metabolites were divided into 12 categories based on the superclass results and a comparison with the HMDB. The differences between the two databases were analyzed by PLS-DA. Based on a variable important in projection value >1 and P < 0.05, 103 differential metabolites were found between tomato variety OE-5# and WT and 63 differential metabolites were found between OE-6# and WT. These included dehydrotomatine, L-serine, and gallic acid amongst others. Many metabolites are associated with fruit ripening and eight common metabolites were found between the OE-5# vs. WT and OE-6# vs. WT comparison groups. The low L-tryptophan expression in OE-5# and OE-6# is consistent with previous reports that its content decreases with fruit ripening. A KEGG pathway enrichment analysis of the significantly different metabolites revealed that in the OE-5# and WT groups, up-regulated metabolites were enriched in 23 metabolic pathways and down-regulated metabolites were enriched in 11 metabolic pathways. In the OE-6# and WT groups, up-regulated metabolites were enriched in 29 pathways and down-regulated metabolites were enriched in six metabolic pathways. In addition, the differential metabolite changes in the L-serine to flavonoid transformation metabolic pathway also provide evidence that there is a phenotypic explanation for the changes in transgenic tomato. Discussion: The metabolomic mechanism controlling SlSAHH2 promotion of tomato fruit ripening has been further elucidated.

Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study.

BACKGROUND: Early prediction of delayed cerebral ischemia (DCI) is critical to improving the prognosis of aneurysmal subarachnoid hemorrhage (aSAH). Machine learning (ML) algorithms can learn from intricate information unbiasedly and facilitate the early identification of clinical outcomes. This study aimed to construct and compare the ability of different ML models to predict DCI after aSAH. Then, we identified and analyzed the essential risk of DCI occurrence by preoperative clinical scores and postoperative laboratory test results. METHODS: This was a multicenter, retrospective cohort study. A total of 1039 post-operation patients with aSAH were finally included from three hospitals in China. The training group contained 919 patients, and the test group comprised 120 patients. We used five popular machine-learning algorithms to construct the models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and f1 score were used to evaluate and compare the five models. Finally, we performed a Shapley Additive exPlanations analysis for the model with the best performance and significance analysis for each feature. RESULTS: A total of 239 patients with aSAH (23.003%) developed DCI after the operation. Our results showed that in the test cohort, Random Forest (RF) had an AUC of 0.79, which was better than other models. The five most important features for predicting DCI in the RF model were the admitted modified Rankin Scale, D-Dimer, intracranial parenchymal hematoma, neutrophil/lymphocyte ratio, and Fisher score. Interestingly, clamping or embolization for the aneurysm treatment was the fourth button-down risk factor in the ML model. CONCLUSIONS: In this multicenter study, we compared five ML methods, among which RF performed the best in DCI prediction. In addition, the essential risks were identified to help clinicians monitor the patients at high risk for DCI more precisely and facilitate timely intervention.

Efficacy of stem cell therapy in patients with chronic liver disease: an umbrella review of systematic reviews.

BACKGROUND: Stem cell therapy offers promising benefits like modulating immune responses, reducing inflammation, and aiding liver regeneration. This umbrella review seeks to compile evidence from systematic reviews to assess the efficacy of stem cell therapy for improving liver function and survival rates in chronic liver disease patients. METHODS: We searched electronic databases up to February 15, 2024. The selection process focused on systematic reviews comparing stem cell therapy with standard care or a placebo. The primary outcomes evaluated were changes in liver enzymes, the MELD score, and survival rates. Nested Knowledge software was utilized for screening and data extraction. All statistical analyses were performed using R software, version 4.3. RESULTS: Our umbrella review included 28 systematic reviews. The meta-analysis showcased a notable improvement in survival rates with a pooled RR of 1.487 (95% CI: 1.281 to 1.727). In non-randomized studies, albumin levels exhibited an SMD of 0.786 (95% CI: 0.368 to 1.204), indicating positive therapeutic effects. For ALT, the meta-analysis revealed a decrease in levels with an SMD of -0.499 (95% CI: -0.834 to -0.164), and for AST, an overall SMD of -0.362 (95% CI: -0.659 to -0.066) was observed, suggesting hepatoprotective effects. No significant changes were observed in total bilirubin levels and MELD scores in RCTs. CONCLUSION: Stem cell therapy exhibits potential as a novel treatment for chronic liver diseases, as it has demonstrated improvements in survival rates and certain liver function markers. More high-quality RCTs are needed in the future to fully ascertain the efficacy of stem cell therapy in this patient population.

Mapping the neural mechanism that distinguishes between holistic thinking and analytic thinking.

Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

SemiSynBio: A new era for neuromorphic computing.

Neuromorphic computing has the potential to achieve the requirements of the next-generation artificial intelligence (AI) systems, due to its advantages of adaptive learning and parallel computing. Meanwhile, biocomputing has seen ongoing development with the rise of synthetic biology, becoming the driving force for new generation semiconductor synthetic biology (SemiSynBio) technologies. DNA-based biomolecules could potentially perform the functions of Boolean operators as logic gates and be used to construct artificial neural networks (ANNs), providing the possibility of executing neuromorphic computing at the molecular level. Herein, we briefly outline the principles of neuromorphic computing, describe the advances in DNA computing with a focus on synthetic neuromorphic computing, and summarize the major challenges and prospects for synthetic neuromorphic computing. We believe that constructing such synthetic neuromorphic circuits will be an important step toward realizing neuromorphic computing, which would be of widespread use in biocomputing, DNA storage, information security, and national defense.

Prognosis Prediction of Diffuse Large B-cell Lymphoma in 18F-FDG PET images Based on Multi-Deep-Learning Models.

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

Diffusion-Based Generative Network for de Novo Synthetic Promoter Design.

Computer-aided promoter design is a major development trend in synthetic promoter engineering. Various deep learning models have been used to evaluate or screen synthetic promoters, but there have been few works on de novo promoter design. To explore the potential ability of generative models in promoter design, we established a diffusion-based generative model for promoter design in Escherichia coli. The model was completely driven by sequence data and could study the essential characteristics of natural promoters, thus generating synthetic promoters similar to natural promoters in structure and component. We also improved the calculation method of FID indicator, using a convolution layer to extract the feature matrix of the promoter sequence instead. As a result, we got an FID equal to 1.37, which meant synthetic promoters have a distribution similar to that of natural ones. Our work provides a fresh approach to de novo promoter design, indicating that a completely data-driven generative model is feasible for promoter design.

Clinical and ultrasound features of 46 children with suppurative osteoarthritis: experience from two centers.

OBJECTIVE: Diagnosing musculoskeletal infections in children is challenging. In recent years, with the advancement of ultrasound technology, high-resolution ultrasound has unique advantages for musculoskeletal children. The aim of this work is to summarize the ultrasonographic and clinical characteristics of children with pyogenic arthritis and osteomyelitis. This study provides a simpler and more effective diagnostic basis for clinical treatment. METHODS: Fifty children with osteomyelitis or arthritis were diagnosed via ultrasound, and the results of the ultrasound diagnosis were compared with those of magnetic resonance imaging and surgery. Clinical and ultrasound characteristics were also analyzed. RESULTS: Out of 50 patients, 46 were confirmed to have suppurative infection by surgical and microbiological examination. Among these 46 patients, 26 were diagnosed with osteomyelitis and 20 had arthritis. The manifestations of osteomyelitis were subperiosteal abscess (15 patients), bone destruction (17 patients), bone marrow abscess (9 patients), and adjacent joint abscess (13 patients). Osteomyelitis mostly affects the long bones of the limbs, femur and humerus (10 and 9 patients, respectively), followed by the ulna, radius, tibia and fibula (one patient each). The manifestations of arthritis were joint pus (20 patients) and joint capsule thickening (20 patients), and hip dislocation (8 patients). All the patients had arthritis involving the hip joint. CONCLUSION: Subperiosteal abscess, bone destruction, and joint abscess with dislocation are ultrasonographic features of pyogenic osteoarthritis. The findings of this work can improve the early diagnosis and differentiation of pyogenic osteoarthritis and provide a reliable basis for treatment.

Management of pulmonary arterial hypertension：before, during and after pregnancy.

Pregnancy complicated with pulmonary arterial hypertension (PAH) is a severe and dangerous condition for both the mother and the fetus. Pregnancy-specific alterations in the maternal cardiovascular system suggest that PAH in pregnancy may manifest more severe symptoms compared with those in non-pregnant patients. Although most societal guidelines recommend early termination in the case of PAH, some recent data suggests that maternal mortality among patients with PAH is lower than previously observed and suggests if a woman decides to proceed with the pregnancy, she should be counseled about the potential risks of continuing with the pregnancy. This review paper starts with a real clinical case of PAH complicating with pregnancy, then summarizes the clinical features, diagnosis, and risk stratification. Effective treatments were also clarified, including pre-conception counseling and monitoring, general and supportive care, medication and immune therapy, delivery and postpartum care, counseling on contraception and breastfeeding, maternal and fetal outcomes, and cardiac surgery. The article summarizes points of uncertainty in both laboratory and clinical practices, as well as current guidelines and clinical recommendations.

Polygonatum sibiricum Saponin Prevents Immune Dysfunction and Strengthens Intestinal Mucosal Barrier Function in Cyclophosphamide-Induced Immunosuppressed BALB/c Mice.

The aim of this study was to explore the immunomodulatory effect of Polygonatum sibiricum saponin (PS) in a cyclophosphamide-induced (Cy) immunosuppression mice model. Oral administration of PS by gavage effectively alleviated weight loss caused by Cy and increased the index of immune organs. PS promoted the proliferation of splenic lymphocytes and T cell subsets (CD3+, CD355+, CD4+/CD8+) and relieved the xylene-induced inflammatory response and Cy-induced increase of serum hemolysin. Moreover, PS increased serum levels of lactate dehydrogenase and acid phosphatase. PS elevated serum level of cytokines and immunoglobulins (TNF-α, IFN-γ, IL-4, IL-6, IL-ß, SIgA, and IgG) and the expression of mRNA of IL-10, TNF-α, and IL-6 in the spleen. Increased mRNA expression of tight junction protein (ZO-1, Mucin2, Occludin) expression and protein expression of IL-6/MyD88/TLR4 in the small intestine showed that PS exhibited a restorative effect on intestinal mucosal injury caused by cyclophosphamide. Oral PS prevented Cy-induced decline in leukocytes, red blood cells, lymphocytes, hemoglobin concentrations, and neutrophils, providing evidence for alleviating hematopoietic disorders. In addition, PS increased SOD and NO levels, reduced MDA levels, and improved oxidative damage in the liver. These findings demonstrate that PS has the potential to be developed as a supplemental agent for alleviating immunosuppression caused by chemotherapeutic agents.

Underwater image enhancement using Divide-and-Conquer network.

Underwater image enhancement has become the requirement for more people to have a better visual experience or to extract information. However, underwater images often suffer from the mixture of color distortion and blurred quality degradation due to the external environment (light attenuation, background noise and the type of water). To solve the above problem, we design a Divide-and-Conquer network (DC-net) for enhancing underwater image, which mainly consists of a texture network, a color network and a refinement network. Specifically, the multi-axis attention block is presented in the texture network, which combine different region/channel features into a single stream structure. And the color network employs an adaptive 3D look-up table method to obtain the color enhanced results. Meanwhile, the refinement network is presented to focus on image features of ground truth. Compared to state-of-the-art (SOTA) underwater image enhance methods, our proposed method can obtain the better visual quality of underwater images and better qualitative and quantitative performance. The code is publicly available at https://github.com/zhengshijian1993/DC-Net.

Assessment of blood one-carbon metabolism indexes during mid-to-late pregnancy in 397 Chinese pregnant women.

Objectives: One-carbon metabolism (OCM) significantly influences fetal growth and neurodevelopment through transferring methyl group to biomolecules, during which folate, methionine, choline and betaine function as methyl donor nutrients, while vitamin B2, B6, B12 function as enzyme cofactors, and homocysteine (Hcy) and S-adenosyl methionine (SAM) are functional metabolites. This study aimed to assess blood OCM index levels and explore their relationships among Chinese pregnant women. Methods: Data were obtained from the baseline of the Mother-Child Nutrition and Health Cohort Study. Pregnant women, voluntarily recruited from September 2020 to June 2022 during antenatal examinations in five Chinese cities at 24-32 gestational weeks, provided fasting venous blood samples. Measurements included RBC and serum folate, serum vitamin B2, B6, B12, choline, betaine, methionine, total Hcy (tHcy), and plasma SAM. Sociodemographic characteristics and pregnancy-related conditions were collected via a self-designed questionnaire. Results: Of 397 participants, 82.6% were in mid-pregnancy (24-27 gestational weeks) and 17.4% were in late-pregnancy (28-32 gestational weeks). Serum folate, vitamin B6, and B12 deficiencies were 2.5, 1.3, and 8.3%, respectively. Elevated tHcy (≥10 µmol/L) was observed in 1.8% of pregnant women. Elderly pregnant women (aged 35 and above) exhibited significantly lower serum methionine levels (p < 0.05), while multiparous women had lower RBC folate levels (p < 0.05), and lower serum methionine and vitamin B12 levels (p < 0.10, not statistically significant). Partial correlation analysis revealed positive associations between RBC folate and cofactor vitamin B12 (r = 0.244, p < 0.05) in the folate cycle, as well as significant correlations between two methyl donor paths [serum folate was significantly related to serum choline (r = 0.172) and betaine (r = 0.193)]. As functional biomarkers of OCM, serum tHcy exhibited negative associations with RBC folate (ß = -0.330, p < 0.05) and vitamin B6 (ß = -0.317, p < 0.05), and plasma SAM displayed a positive association with serum betaine (ß = 0.610, p < 0.05), while negatively associated with serum vitamin B6 (ß = -0.181, p < 0.05). Conclusion: The blood OCM exhibited imbalances during mid-to-late pregnancy, characterized by lower levels of folate, vitamin B6, and B12, alongside elevated tHcy levels. Adequate folate and vitamin B6 emerged as significant predictors of lower tHcy levels. Additionally, serum betaine showed a positive correlation with plasma SAM. This suggests the importance of not only ensuring sufficient folate but also optimizing other OCM-related nutrients throughout pregnancy.

The cadmium tolerance enhancement through regulating glutathione conferred by vacuolar compartmentalization in Aspergillus sydowii.

Aspergillus was found to be a vital hyperaccumulation species for heavy metal removal with admirable tolerance capacity. But the potential tolerance mechanism has not been completely studied. This study quantified the amounts of total cadmium (Cd), Cd2+, glutathione (GSH), and reactive oxygen species (ROS) in the protoplasts and vacuoles of mycelium. We modulated GSH synthesis using buthionine sulfoximine (BSO) and 2-oxothiazolidine-4-carboxylic acid (OTC) to investigate the subcellular regulatory mechanisms of GSH in the accumulation of Cd. The results confirmed that GSH plays a crucial role in vacuolar compartmentalization under Cd stress. GSH and GSSG as a redox buffer to keep the cellular redox state in balance and GSH as a metal chelating agent to reduce toxicity. When regulating the decreased GSH content with BSO, and increased GSH content with OTC, the system of Cd-GSH-ROS can change accordingly, this also supported that vacuolar compartmentalization is a detoxification strategy that can modulate the transport and storage of substances inside and outside the vacuole reasonably. Interestingly, GSH tended to be distributed in the cytoplasm, the battleground of redox takes place in the cytoplasm but not in the vacuole. These finding potentially has implications for the understanding of tolerance behavior and detoxification mechanisms of cells. In the future bioremediation of Cd in soil, the efficiency of soil remediation can be improved by developing organisms with high GSH production capacity.

CT perfusion imaging of the liver and the spleen can identify severe portal hypertension.

PURPOSE: To determine if hepatic and splenic perfusion parameters are useful in identifying severe portal hypertension (SPH). METHODS: The study enrolled 52 patients who underwent perfusion CT scan within one week before the hepatic venous pressure gradient (HVPG) measurement. A commercial software package was used for post-processing to generate hepatic and splenic perfusion parameters. Correlations were assessed using Pearson and Spearman rank correlation coefficients. Logistic regression was used to screen predictive parameters of SPH. The cut-off values of parameters for severe portal hypertension were calculated, as well as the sensitivity and specificity. RESULTS: There was a significant difference between SPH and non-severe portal hypertension (NSPH) in blood volume of liver (BVLiver), hepatic arterial fraction (HAF), hepatic arterial perfusion (HAP), portal venous perfusion (PVP), mean slope of increase in spleen (MSISpleen), BVSpleen, blood flow of spleen (BFSpleen), BVSpleen/Liver, and BVSpleen/Liver(P) (p < 0.05). The Spearman correlation coefficient was - 0.541 (p < 0.001) between BVSpleen/Live and HVPG and - 0.568 (p < 0.001) between BVSpleen/Liver(P) and HVPG. Using a BVSpleen/Liver value of 0.780 or BVSpleen/Liver(P) value of 1.061 as the cut-off value for the detection of SPH, the sensitivity and specificity were 94.7% and 72.7%, 100%, and 63.6% respectively. CONCLUSION: There was a moderate correlation between CT perfusion parameters BVSpleen/Liver, BVSpleen/Liver(P), and HVPG, which may be used to detect severe portal hypertension.

Prolonged myelin deficits contribute to neuron loss and functional impairments after ischaemic stroke.

Ischaemic stroke causes neuron loss and long-term functional deficits. Unfortunately, effective approaches to preserving neurons and promoting functional recovery remain unavailable. Oligodendrocytes, the myelinating cells in the CNS, are susceptible to oxygen and nutrition deprivation and undergo degeneration after ischaemic stroke. Technically, new oligodendrocytes and myelin can be generated by the differentiation of oligodendrocyte precursor cells (OPCs). However, myelin dynamics and their functional significance after ischaemic stroke remain poorly understood. Here, we report numerous denuded axons accompanied by decreased neuron density in sections from ischaemic stroke lesions in human brain, suggesting that neuron loss correlates with myelin deficits in these lesions. To investigate the longitudinal changes in myelin dynamics after stroke, we labelled and traced pre-existing and newly-formed myelin, respectively, using cell-specific genetic approaches. Our results indicated massive oligodendrocyte death and myelin loss 2 weeks after stroke in the transient middle cerebral artery occlusion (tMCAO) mouse model. In contrast, myelin regeneration remained insufficient 4 and 8 weeks post-stroke. Notably, neuronal loss and functional impairments worsened in aged brains, and new myelin generation was diminished. To analyse the causal relationship between remyelination and neuron survival, we manipulated myelinogenesis by conditional deletion of Olig2 (a positive regulator) or muscarinic receptor 1 (M1R, a negative regulator) in OPCs. Deleting Olig2 inhibited remyelination, reducing neuron survival and functional recovery after tMCAO. Conversely, enhancing remyelination by M1R conditional knockout or treatment with the pro-myelination drug clemastine after tMCAO preserved white matter integrity and neuronal survival, accelerating functional recovery. Together, our findings demonstrate that enhancing myelinogenesis is a promising strategy to preserve neurons and promote functional recovery after ischaemic stroke.

Hypoxia promotes non-small cell lung cancer cell stemness, migration, and invasion via promoting glycolysis by lactylation of SOX9.

BACKGROUND: Lung cancer is the deadliest form of malignancy and the most common subtype is non-small cell lung cancer (NSCLC). Hypoxia is a typical feature of solid tumor microenvironment. In the current study, we clarified the effects of hypoxia on stemness and metastasis and the molecular mechanism. METHODS: The biological functions were assessed using the sphere formation assay, Transwell assay, and XF96 extracellular flux analyzer. The protein levels were detected by western blot. The lactylation modification was assessed by western blot and immunoprecipitation. The role of SOX9 in vivo was explored using a xenografted tumor model. RESULTS: We observed that hypoxia promoted sphere formation, migration, invasion, glucose consumption, lactate production, glycolysis, and global lactylation. Inhibition of glycolysis suppressed cell stemness, migration, invasion, and lactylation. Moreover, hypoxia increased the levels of SOX9 and lactylation of SOX9, whereas inhibition of glycolysis reversed the increase. Additionally, knockdown of SOX9 abrogated the promotion of cell stemness, migration, and invasion. In tumor-bearing mice, overexpression of SOX9 promoted tumor growth, and inhibition of glycolysis suppressed tumor growth. CONCLUSION: Hypoxia induced the lactylation of SOX9 to promote stemness, migration, and invasion via promoting glycolysis. The findings suggested that targeting hypoxia may be an effective way for NSCLC treatment and reveal a new mechanism of hypoxia in NSCLC.

GeneMiner: A tool for extracting phylogenetic markers from next-generation sequencing data.

The advancement of next-generation sequencing (NGS) technologies has been revolutionary for the field of evolutionary biology. This technology has led to an abundance of available genomes and transcriptomes for researchers to mine. Specifically, researchers can mine for various types of molecular markers that are vital for phylogenetic, evolutionary and ecological studies. Numerous tools have been developed to extract these molecular markers from NGS data. However, due to an insufficient number of well-annotated reference genomes for non-model organisms, it remains challenging to obtain these markers accurately and efficiently. Here, we present GeneMiner, an improved and expanded version of our previous tool, Easy353. GeneMiner combines the reference-guided de Bruijn graph assembly with seed self-discovery and greedy extension. Additionally, it includes a verification step using a parameter-bootstrap method to reduce the pitfalls associated with using a relatively distant reference. Our results, using both experimental and simulation data, showed GeneMiner can accurately acquire phylogenetic molecular markers for plants using transcriptomic, genomic and other NGS data. GeneMiner is designed to be user-friendly, fast and memory-efficient. Further, it is compatible with Linux, Windows and macOS. All source codes are publicly available on GitHub (https://github.com/sculab/GeneMiner) and Gitee (https://gitee.com/sculab/GeneMiner) for easy accessibility and transparency.

M3S-Net: multi-modality multi-branch multi-self-attention network with structure-promoting loss for low-dose PET/CT enhancement.

Objective.PET (Positron Emission Tomography) inherently involves radiotracer injections and long scanning time, which raises concerns about the risk of radiation exposure and patient comfort. Reductions in radiotracer dosage and acquisition time can lower the potential risk and improve patient comfort, respectively, but both will also reduce photon counts and hence degrade the image quality. Therefore, it is of interest to improve the quality of low-dose PET images.Approach.A supervised multi-modality deep learning model, named M3S-Net, was proposed to generate standard-dose PET images (60 s per bed position) from low-dose ones (10 s per bed position) and the corresponding CT images. Specifically, we designed a multi-branch convolutional neural network with multi-self-attention mechanisms, which first extracted features from PET and CT images in two separate branches and then fused the features to generate the final generated PET images. Moreover, a novel multi-modality structure-promoting term was proposed in the loss function to learn the anatomical information contained in CT images.Main results.We conducted extensive numerical experiments on real clinical data collected from local hospitals. Compared with state-of-the-art methods, the proposed M3S-Net not only achieved higher objective metrics and better generated tumors, but also performed better in preserving edges and suppressing noise and artifacts.Significance.The experimental results of quantitative metrics and qualitative displays demonstrate that the proposed M3S-Net can generate high-quality PET images from low-dose ones, which are competable to standard-dose PET images. This is valuable in reducing PET acquisition time and has potential applications in dynamic PET imaging.

Ketamine alleviates fear memory and spatial cognition deficits in a PTSD rat model via the BDNF signaling pathway of the hippocampus and amygdala.

BACKGROUND: Post-traumatic stress disorder (PTSD) is associated with traumatic stress experiences. This condition can be accompanied by learning and cognitive deficits. Studies have demonstrated that ketamine can rapidly and significantly alleviate symptoms in patients with chronic PTSD. Nonetheless, the effects of ketamine on neurocognitive impairment and its mechanism of action in PTSD remain unclear. METHODS: In this study, different concentrations of ketamine (5, 10, 15, and 20 mg/kg, i.p.) were evaluated in rat models of single prolonged stress and electrophonic shock (SPS&S). Expression levels of brain-derived neurotrophic factor (BDNF) and post-synaptic density-95 (PSD-95) in the hippocampus (HIP) and amygdala (AMG) were determined by Western blot analysis and immunohistochemistry. RESULTS: The data showed that rats subjected to SPS&S exhibited significant PTSD-like cognitive impairment. The effect of ketamine on SPS&S-induced neurocognitive function showed a U-shaped dose effect in rats. A single administration of ketamine at a dosage of 10-15 mg/kg resulted in significant changes in behavioral outcomes. These manifestations of improvement in cognitive function and molecular changes were reversed at high doses (15-20 mg/kg). CONCLUSION: Overall, ketamine reversed SPS&S-induced fear and spatial memory impairment and the down-regulation of BDNF and BDNF-related PSD-95 signaling in the HIP and AMG. A dose equal to 15 mg/kg rapidly reversed the behavioral and molecular changes and promoted the amelioration of cognitive dysfunction. The enhanced association of BDNF signaling with PSD-95 effects could be involved in the therapeutic efficiency of ketamine for PTSD.

Is nurses' clinical competence associated with their moral identity and injury?

BACKGROUND: The enhancement of nursing care quality is closely related to the clinical competence of nurses, making it a crucial component within health systems. OBJECTIVE: The present study investigated the relationship between nurses' clinical competence, moral identity, and moral injury during the COVID-19 outbreak. RESEARCH DESIGN: This cross-sectional study was carried out among frontline nurses, using the Moral Identity Questionnaire (MIQ), the Moral Injury Symptom Scale-Healthcare Professionals version (MISS-HP), and the Competency Inventory for Registered Nurse (CIRN) as data collection tools. PARTICIPANTS: and research context: The research population for this study consisted of all frontline nurses (n = 251) employed in a hospital in southern Iran. Sampling was conducted between May 1, 2021 and September 30, 2021, during the COVID-19 outbreak. ETHICAL CONSIDERATIONS: The present study received approval from the research ethics committee of Rafsanjan University of Medical Sciences, with project No. 99267 and code of ethics ID No. IR. RUMS.REC.1399.262, dated 15.02.2021. RESULTS: According to the study findings, 42.2% of the nurses demonstrated high clinical competence, while 51.4% exhibited moderate clinical competence. The results indicated a positive correlation between moral identity and clinical competence but a negative correlation between moral injury and clinical competence. Furthermore, the variables of moral identity and moral injury were found to predict 10% of the variance in clinical competence. CONCLUSION: According to the results, moral identity and moral injury had an impact on the clinical competence of nurses. Therefore, implementing a program aimed at enhancing moral identity and providing training strategies to address moral injury during crises like the COVID-19 pandemic can lead to improvements in nurses' clinical competence and the overall quality of care they provide.