Improving classification performance of motor imagery BCI through EEG data augmentation with conditional generative adversarial networks.

In brain-computer interface (BCI), building accurate electroencephalogram (EEG) classifiers for specific mental tasks is critical for BCI performance. The classifiers are developed by machine learning (ML) and deep learning (DL) techniques, requiring a large dataset for training to build reliable and accurate models. However, collecting large enough EEG datasets is difficult due to intra-/inter-subject variabilities and experimental costs. This leads to the data scarcity problem, which causes overfitting issues to training samples, resulting in reducing generalization performance. To solve the EEG data scarcity problem and improve the performance of the EEG classifiers, we propose a novel EEG data augmentation (DA) framework using conditional generative adversarial networks (cGANs). An experimental study is implemented with two public EEG datasets, including motor imagery (MI) tasks (BCI competition IV IIa and III IVa), to validate the effectiveness of the proposed EEG DA method for the EEG classifiers. To evaluate the proposed cGAN-based DA method, we tested eight EEG classifiers for the experiment, including traditional MLs and state-of-the-art DLs with three existing EEG DA methods. Experimental results showed that most DA methods with proper DA proportion in the training dataset had higher classification performances than without DA. Moreover, applying the proposed DA method showed superior classification performance improvement than the other DA methods. This shows that the proposed method is a promising EEG DA method for enhancing the performances of the EEG classifiers in MI-based BCIs.

Detecting pulmonary malignancy against benign nodules using noninvasive cell-free DNA fragmentomics assay.

BACKGROUND: Early screening using low-dose computed tomography (LDCT) can reduce mortality caused by non-small-cell lung cancer. However, ∼25% of the 'suspicious' pulmonary nodules identified by LDCT are later confirmed benign through resection surgery, adding to patients' discomfort and the burden on the healthcare system. In this study, we aim to develop a noninvasive liquid biopsy assay for distinguishing pulmonary malignancy from benign yet 'suspicious' lung nodules using cell-free DNA (cfDNA) fragmentomics profiling. METHODS: An independent training cohort consisting of 193 patients with malignant nodules and 44 patients with benign nodules was used to construct a machine learning model. Base models using four different fragmentomics profiles were optimized using an automated machine learning approach before being stacked into the final predictive model. An independent validation cohort, including 96 malignant nodules and 22 benign nodules, and an external test cohort, including 58 malignant nodules and 41 benign nodules, were used to assess the performance of the stacked ensemble model. RESULTS: Our machine learning models demonstrated excellent performance in detecting patients with malignant nodules. The area under the curves reached 0.857 and 0.860 in the independent validation cohort and the external test cohort, respectively. The validation cohort achieved an excellent specificity (68.2%) at the targeted 90% sensitivity (89.6%). An equivalently good performance was observed while applying the cut-off to the external cohort, which reached a specificity of 63.4% at 89.7% sensitivity. A subgroup analysis for the independent validation cohort showed that the sensitivities for detecting various subgroups of nodule size (<1 cm: 91.7%; 1-3 cm: 88.1%; >3 cm: 100%; unknown: 100%) and smoking history (yes: 88.2%; no: 89.9%) all remained high among the lung cancer group. CONCLUSIONS: Our cfDNA fragmentomics assay can provide a noninvasive approach to distinguishing malignant nodules from radiographically suspicious but pathologically benign ones, amending LDCT false positives.

Sources, environmental fate, and impacts of microplastic contamination in agricultural soils: A comprehensive review.

The pervasive presence of microplastics has emerged as a pressing global environmental concern, posing threats to food security and human health upon infiltrating agricultural soils. These microplastics primarily originate from agricultural activities, including fertilizer inputs, compost-based soil remediation, irrigation, and atmospheric deposition. Their remarkable durability and resistance to biodegradation contribute to their persistent presence in the environment. Microplastics within agricultural soils have prompted concerns regarding their potential impacts on agricultural practices. Functioning as significant pollutants and carriers of microcontaminants within agricultural ecosystems, microplastics and their accompanying contaminants represent ongoing challenges. Within these soil ecosystems, the fate and transportation of microplastics can detrimentally affect plant growth, microbial communities, and, subsequently, human health via the food chain. Specifically, microplastics interact with soil factors, impacting soil health and functionality. Their high adsorption capacity for hazardous microcontaminants exacerbates soil contamination, leading to increased adverse effects on organisms and human health. Due to their tiny size, microplastic debris is easily ingested by soil organisms and can transfer through the food chain, causing physiological and/or mechanical damage. Additionally, microplastics can affect plant growth and have the potential to accumulate and be transported within plants. Efforts to mitigate these impacts are crucial to safeguarding agricultural sustainability and environmental health. Future research should delve into the long-term impacts of environmental aging processes on microplastic debris within agricultural soil ecosystems from various sources, primarily focusing on food security and human beings.

Medulloblastomas Initiated by Homologous Recombination Defects in Mice.

Germline mutations of homologous-recombination (HR) genes are among the top contributors to medulloblastomas. A significant portion of human medulloblastomas exhibit genomic signatures of HR defects. We queried whether ablation of Brca2 and Palb2, and their related Brca1 and Bccip genes, in the mouse brain can differentially initiate medulloblastomas. Conditional knockout mouse models of these HR genes and a conditional knockdown of Bccip (shBccip-KD) were established. Deletion of any of these genes led to microcephaly and neurologic defects, with Brca1- and Bccip- producing the worst. Trp53 co-deletion significantly rescued the microcephaly with Brca1, Palb2, and Brca2 deficiency but exhibited limited impact on Bccip- mice. For the first time, inactivation of either Brca1 or Palb2 with Trp53 was found to induce medulloblastomas. Despite shBccip-CKD being highly penetrative, Bccip/Trp53 deletions failed to induce medulloblastomas. The tumors displayed diverse immunohistochemical features and chromosome copy number variation. Although there were widespread up-regulations of cell proliferative pathways, most of the tumors expressed biomarkers of the sonic hedgehog subgroup. The medulloblastomas developed from Brca1-, Palb2-, and Brca2- mice were highly sensitive to a poly (ADP-ribose) polymerase inhibitor but not the ones from shBccip-CKD mice. These models recapitulate the spontaneous medulloblastoma development with high penetrance and a narrow time window, providing ideal platforms to test therapeutic agents with the ability to differentiate HR-defective and HR-proficient tumors.

Periodontitis and Chronic Obstructive Pulmonary Disease: A bidirectional Mendelian randomization study.

OBJECTIVE: Observational studies have suggested an association between chronic periodontitis (CP) and chronic obstructive pulmonary disease (COPD). This study aimed to determine whether there is a causal relationship between CP and COPD incidence. DESIGN: Two­sample Mendelian Randomization (MR) analysis using summary statistics from two genome­wide association studies (GWASs) of European ancestry. Single nucleotide polymorphisms (SNPs) associated with COPD were obtained from the FinnGen database, which included 16,380,382 SNPs. The diagnosis of COPD was based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD 2023). We also obtained SNPs associated with CP from the FinnGen database, which included 16,380,378 SNPs. RESULTS: Sixteen eligible SNPs were extracted to analyze the causal effect of CP on COPD incidence. There was no causal correlation between CP and COPD using the inverse variance-weighted method (IVW) (OR=0.97, 95%CI= 0.91-1.05; p=0.482). Seven eligible SNPs were extracted to analyze the causal effect of COPD on CP incidence. Again, there was also no causal correlation between using IVW (OR=1.09, 95%CI=0.93-1.28; p=0.279). CONCLUSION: We did not demonstrate a causal relationship between genetically predicted CP and COPD, or between genetically predicted COPD and CP.

Immune Checkpoint Blockade Delays Cancer and Extends Survival in Murine DNA Polymerase Mutator Syndromes.

Mutations in polymerases Pold1 and Pole exonuclease domains in humans are associated with increased cancer incidence, elevated tumor mutation burden (TMB) and response to immune checkpoint blockade (ICB). Although ICB is approved for treatment of several cancers, not all tumors with elevated TMB respond. Here we generated Pold1 and Pole proofreading mutator mice and show that ICB treatment of mice with high TMB tumors did not improve survival as only a subset of tumors responded. Similarly, introducing the mutator alleles into mice with Kras/p53 lung cancer did not improve survival, however, passaging mutator tumor cells in vitro without immune editing caused rejection in immune-competent hosts, demonstrating the efficiency by which cells with antigenic mutations are eliminated. Finally, ICB treatment of mutator mice earlier, before observable tumors delayed cancer onset, improved survival, and selected for tumors without aneuploidy, suggesting the use of ICB in individuals at high risk for cancer prevention. Highlights: Germline somatic and conditional Pold1 and Pole exonuclease domain mutations in mice produce a mutator phenotype. Spontaneous cancers arise in mutator mice that have genomic features comparable to human tumors with these mutations.ICB treatment of mutator mice with tumors did not improve survival as only a subset of tumors respond. Introduction of the mutator alleles into an autochthonous mouse lung cancer model also did not produce immunogenic tumors, whereas passaging mutator tumor cells in vitro caused immune rejection indicating efficient selection against antigenic mutations in vivo . Prophylactic ICB treatment delayed cancer onset, improved survival, and selected for tumors with no aneuploidy.

Transcriptomic landscape of mammalian ventral pallidum at single-cell resolution.

The ventral pallidum (VP) is critical for motivated behaviors. While contemporary work has begun to elucidate the functional diversity of VP neurons, the molecular heterogeneity underlying this functional diversity remains incompletely understood. We used snRNA-seq and in situ hybridization to define the transcriptional taxonomy of VP cell types in mice, macaques, and baboons. We found transcriptional conservation between all three species, within the broader neurochemical cell types. Unique dopaminoceptive and cholinergic subclusters were identified and conserved across both primate species but had no homolog in mice. This harmonized consensus VP cellular atlas will pave the way for understanding the structure and function of the VP and identified key neuropeptides, neurotransmitters, and neuro receptors that could be targeted within specific VP cell types for functional investigations.

RESPIRATION DEFECTS LIMIT SERINE SYNTHESIS REQUIRED FOR LUNG CANCER GROWTH AND SURVIVAL.

Mitochondrial function is important for both energetic and anabolic metabolism. Pathogenic mitochondrial DNA (mtDNA) mutations directly impact these functions, resulting in the detrimental consequences seen in human mitochondrial diseases. The role of pathogenic mtDNA mutations in human cancers is less clear; while pathogenic mtDNA mutations are observed in some cancer types, they are almost absent in others. We report here that the proofreading mutant DNA polymerase gamma ( PolG D256A ) induced a high mtDNA mutation burden in non-small-cell lung cancer (NSCLC), and promoted the accumulation of defective mitochondria, which is responsible for decreased tumor cell proliferation and viability and increased cancer survival. In NSCLC cells, pathogenic mtDNA mutations increased glycolysis and caused dependence on glucose. The glucose dependency sustained mitochondrial energetics but at the cost of a decreased NAD+/NADH ratio that inhibited de novo serine synthesis. Insufficient serine synthesis, in turn, impaired the downstream synthesis of GSH and nucleotides, leading to impaired tumor growth that increased cancer survival. Unlike tumors with intact mitochondrial function, NSCLC with pathogenic mtDNA mutations were sensitive to dietary serine and glycine deprivation. Thus, mitochondrial function in NSCLC is required specifically to sustain sufficient serine synthesis for nucleotide production and redox homeostasis to support tumor growth, explaining why these cancers preserve functional mtDNA. In brief: High mtDNA mutation burden in non-small-cell lung cancer (NSCLC) leads to the accumulation of respiration-defective mitochondria and dependency on glucose and glycolytic metabolism. Defective respiratory metabolism causes a massive accumulation of cytosolic nicotinamide adenine dinucleotide + hydrogen (NADH), which impedes serine synthesis and, thereby, glutathione (GSH) and nucleotide synthesis, leading to impaired tumor growth and increased survival. Highlights: Proofreading mutations in Polymerase gamma led to a high burden of mitochondrial DNA mutations, promoting the accumulation of mitochondria with respiratory defects in NSCLC.Defective respiration led to reduced proliferation and viability of NSCLC cells increasing survival to cancer.Defective respiration caused glucose dependency to fuel elevated glycolysis.Altered glucose metabolism is associated with high NADH that limits serine synthesis, leading to impaired GSH and nucleotide production.Mitochondrial respiration defects sensitize NSCLC to dietary serine/glycine starvation, further increasing survival.

Effects of looming audio on transcranial magnetic stimulation-induced phosphene perception.

Looming sounds are known to influence visual function in the brain, even as early as the primary visual cortex. However, despite evidence that looming sounds have a larger impact on cortical excitability than stationary sounds, the influence of varying looming strengths on visual ability remains unclear. Here, we aim to understand how these signals influence low-level visual function. Fourteen healthy undergraduate students participated. They were blindfolded and received transcranial magnetic stimulation (TMS) to the primary visual cortex following auditory stimulation with different strength looming sounds. Participants reported whether they perceived a phosphene, or an illusory visual percept, following TMS stimulation. We hypothesized that rates of phosphene activity would increase with increasing levels of looming strength. A linear mixed-effect model showed that phosphene activity was significantly higher at higher strength of looming (F(1, 69) = 5.33, p = .024) and at higher TMS pulse strength (F(1, 18) = 4.71, p = .043). However, there was also a significant interaction between looming strength and pulse strength (F(1, 69) = 4.33, p = .041). At lower levels of TMS strength, phosphene rate increased with looming strength, while at higher levels of TMS strength the effect was reversed. These results suggest a complex relationship between looming strength and cortical activity, potentially reflecting the mixed contribution of total auditory energy and the rate of changes. This work will enhance our ability to predict audiovisual interactions and may help improve auditory warning systems designed to capture visual attention.

Topographic analysis of pancreatic cancer by TMA and digital spatial profiling reveals biological complexity with potential therapeutic implications.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies. Tissue microarrays (TMA) are an established method of high throughput biomarker interrogation in tissues but may not capture histological features of cancer with potential biological relevance. Topographic TMAs (T-TMAs) representing pathophysiological hallmarks of cancer were constructed from representative, retrospective PDAC diagnostic material, including 72 individual core tissue samples. The T-TMA was interrogated with tissue hybridization-based experiments to confirm the accuracy of the topographic sampling, expression of pro-tumourigenic and immune mediators of cancer, totalling more than 750 individual biomarker analyses. A custom designed Next Generation Sequencing (NGS) panel and a spatial distribution-specific transcriptomic evaluation were also employed. The morphological choice of the pathophysiological hallmarks of cancer was confirmed by protein-specific expression. Quantitative analysis identified topography-specific patterns of expression in the IDO/TGF-ß axis; with a heterogeneous relationship of inflammation and desmoplasia across hallmark areas and a general but variable protein and gene expression of c-MET. NGS results highlighted underlying genetic heterogeneity within samples, which may have a confounding influence on the expression of a particular biomarker. T-TMAs, integrated with quantitative biomarker digital scoring, are useful tools to identify hallmark specific expression of biomarkers in pancreatic cancer.

[Analysis of the change in human resources of centers for disease control and prevention in different regions of China from 2010 to 2020].

Objective: To analyze the change in human resources within China's Centers for Disease Control and Prevention (CDC) from 2010 to 2020. Methods: The self-reported information from provincial, prefectural (city), and county (district) levels of China's CDC, covering employee counts, staff composition, professional qualifications, educational backgrounds, technical titles, and tenure, were extracted from the China Disease Prevention and Control Information System. The demographic context was provided by the annual population figures from the China Statistical Yearbook (2010-2020). The profile of CDC personnel was described, and the average annual percentage rate change (AAPC), average annual percentage rate change (APC), human resource agglomeration degree (HRAD) and the difference between HRAD and population agglomeration degree (PAD) were calculated. The Joinpoint regression model was used to analyze the time trend. Results: The decade under review witnessed a net increase of 17 300 active and 18 300 enrolled personnel in the CDC, surpassing the national population growth rate with AAPCs of 0.93% and 1.03%, respectively. This upward trajectory was statistically significant (P<0.05). The ratio of disease control personnel per 10 000 population escalated from 1.14 to 1.21. An initial decline in active CDC workforce density (from 1.31 to 1.27 per 10 000 population between 2010 and 2017) was followed by an increase (from 1.28 to 1.37 between 2018 and 2020), with APCs of -0.40% and 3.73%, respectively. The proportion of professional and technical staff in 2019 was highest in the eastern region (86.01%), followed by the western (83.75%) and central regions (79.54%). The period also saw an enhancement in the average academic degree (from 1.91 to 2.43 points) and professional title scores (from 1.39 to 1.53 points) of CDC personnel. While the average tenure in the eastern and western regions showed a slight decline, the central region experienced an increase, with HRAD values indicating a higher concentration in the eastern and central regions compared to the western region. The HRAD-PAD discrepancy revealed a negative value in the eastern region, nearing zero in the central and western regions. Conclusion: Between 2010 and 2020, China's CDC experienced notable growth in human resources and underwent structural optimization, albeit with significant regional disparities in concentration.

Mild liver dysfunction in Klinefelter syndrome is associated with abdominal obesity and elevated lipids but not testosterone treatment.

CONTEXT: Klinefelter syndrome (KS) is associated with hypergonadotropic hypogonadism, which contributes to characteristic phenotypical manifestations including metabolic alterations. Extensive research has demonstrated important associations between androgens and liver function. OBJECTIVES: Investigation of the association between metabolic parameters, sex hormones and liver function in males with KS, both treated (T-KS) and untreated (U-KS) and healthy control males. METHODS: A total of 65 KS males were recruited, of which 32 received testosterone replacement therapy (TRT). Also, 69 healthy controls were recruited. We used alanine aminotransferase (ALAT), alkaline phosphatase and PP (prothrombin-proconvertin time ratio) as the main liver markers. Multivariable regression was performed within the three groups. All statistics were calculated using STATA. Principal component analysis was utilized to demonstrate the interconnected patterns among all measured biomarkers, and to elucidate how the different groups were linked to these patterns. RESULTS: Higher levels of main liver markers were observed in U-KS compared to controls, with no significant differences between U-KS and T-KS. T-KS had lower abdominal fat, total cholesterol, and LDL cholesterol than U-KS. Using multivariable models, variation in ALAT in U-KS was explained by HOMA2%S; in T-KS by BMI and SHBG; and in controls by hip circumference and estradiol. We found no multivariable models explaining variation in PP in U-KS; in T-KS, PP was explained by BMI and LDL cholesterol, and in controls by total cholesterol. Using principal component analysis U-KS was positively associated to D1 (an obese profile, which also included ALAT) and controls negatively associated with D1 (non-obese profile). CONCLUSION: KS males have mild liver dysfunction reflected by a significant increase in the main liver markers and decrease in albumin. The presented data underscore a primary role of metabolic conditions including obesity, insulin resistance and unfavourable lipid profile, in the elevated liver function markers seen in males with KS. Whether TRT can improve liver function in KS warrants further studies. Our findings, highlight that an evaluation of the liver function should be part of the clinical care in males with KS.

Applications of engineered biochar in remediation of heavy metal(loid)s pollution from wastewater: Current perspectives toward sustainable development goals.

Environmental pollution of heavy metal(loid)s (HMs) caused adverse impacts, has become one of the emerging concerns and challenges worldwide. Metal(loid)s can pose significant threats to living organisms even when present in trace levels within environmental matrices. Extended exposure to these substances can lead to adverse health consequences in humans. Removing HM-contaminated water and moving toward sustainable development goals (SDGs) is critical. In this mission, biochar has recently gained attention in the environmental sector as a green and alternative material for wastewater removal. This work provides a comprehensive analysis of the remediation of typical HMs by biochars, associated with an understanding of remediation mechanisms, and gives practical solutions for ecologically sustainable. Applying engineered biochar in various fields, especially with nanoscale biochar-aided wastewater treatment approaches, can eliminate hazardous metal(loid) contaminants, highlighting an environmentally friendly and low-cost method. Surface modification of engineered biochar with nanomaterials is a potential strategy that positively influences its sorption capacity to remove contaminants. The research findings highlighted the biochars' ability to adsorb HM ions based on increased specific surface area (SSA), heightened porosity, and forming inner-sphere complexes with oxygen-rich groups. Utilizing biochar modification emerged as a viable approach for addressing lead (Pb), cadmium (Cd), arsenic (As), mercury (Hg), and chromium (Cr) pollution in aqueous environments. Most biochars investigated demonstrated a removal efficiency >90 % (Cd, As, Hg) and can reach an impressive 99 % (Pb and Cr). Furthermore, biochar and advanced engineered applications are also considered alternative solutions based on the circular economy.

The mental health of Australians bereaved during the first two years of the COVID-19 pandemic: a latent class analysis.

BACKGROUND: The COVID-19 pandemic disrupted many areas of life, including culturally accepted practices at end-of-life care, funeral rites, and access to social, community, and professional support. This survey investigated the mental health outcomes of Australians bereaved during this time to determine how these factors might have impacted bereavement outcomes. METHODS: An online survey indexing pandemic and bereavement experiences, levels of grief, depression, anxiety, and health, work, and social impairment. Latent class analysis (LCA) was used to identify groups of individuals who shared similar symptom patterns. Multinomial regressions identified pandemic-related, loss-related, and sociodemographic correlates of class membership. RESULTS: 1911 Australian adults completed the survey. The LCA identified four classes: low symptoms (46.8%), grief (17.3%), depression/anxiety (17.7%), and grief/depression/anxiety (18.2%). The latter group reported the highest levels of health, work, and social impairment. The death of a child or partner and an inability to care for the deceased due to COVID-19 public health measures were correlated with grief symptoms (with or without depression and anxiety). Preparedness for the person's death and levels of pandemic-related loneliness and social isolation differentiated all four classes. Unemployment was associated with depression/anxiety (with or without grief). CONCLUSIONS: COVID-19 had profound impacts for the way we lived and died, with effects that are likely to ricochet through society into the foreseeable future. These lessons learned must inform policymakers and healthcare professionals to improve bereavement care and ensure preparedness during and following future predicted pandemics to prevent negative impacts.

[Automated cephalometric landmark identification and location based on convolutional neural network].

Objective: To develop an automated landmark location system applicable to the case of landmark missing. Methods: Four and eighty-one lateral cephalograms, which contained 240 males and 241 females, with an average age of (24.5±5.6) years, taken from January 2015 to January 2021 in the Department of Orthodontics, Capital Medical University School of Stomatology, and met the inclusion criteria were collected. Five postgraduate orthodontic students were the annotators to manually locate 61 possible landmarks in 481 lateral cephalograms. Two assistant professors in the department as reviewers performed calibration. Two professors as arbitrators, made final decision. Data sets were established (341 were used as training set, 40 as validation set, and 100 as test set). In this paper, an automatic landmarks identification and location model based on convolutional neural networks (CNN), CephaNET, was developed. The model was trained by feeding the original image into the feature extraction module and convolutional pose machine (CPM) module to locate landmarks with high accuracy using deep supervision. Training set was enhanced to 1 684 images by histogram equalization, cropping, and adjustment of brightness. The model was trained to compare the Gaussian heat maps output from the network with the set threshold to identify landmark missing cases. Test set of 100 lateral cephalograms was used to test the accuracy of the model. The evaluation criteria used were success detection rate of missing landmark, mean radial error (MRE) and success detection rate (SDR) in the range of 2.0, 2.5, 3.0, 3.5 and 4.0 mm. Results: The model identified and located 61 commonly used landmarks in 0.13 seconds on average. It had an average accuracy of 93.5% in identifying missing landmarks. The MRE of our testing set was (1.19±0.91) mm. SDR of 2.0, 2.5, 3.0, 3.5 and 4.0 mm were 85.4%, 90.2%, 93.5%, 95.4%, 97.0% respectively. Conclusions: The model proposed in this paper could adapt to the absence of landmark in lateral cephalograms and locate 61 commonly used landmarks with high accuracy to meet the requirements of different cephalometric analysis methods.

Evaluation of a national clinical programme for the management of self-harm in hospital emergency departments: impact on patient outcomes and the provision of care.

BACKGROUND: Emergency departments are important points of intervention, to reduce the risk of further self-harm and suicide. A national programme to standardise the management of people presenting to the emergency department with self-harm and suicidal ideation (NCPSHI) was introduced in Ireland in 2014. The aim of this study was to evaluate the impact of the NCPSHI on patient outcomes and provision of care. METHODS: Data on self-harm presentations were obtained from the National Self-Harm Registry Ireland from 2012 to 2017. The impacts of the NCPSHI on study outcomes (3-month self-harm repetition, biopsychosocial assessment provision, admission, post-discharge referral, and self-discharge) were examined at an individual and aggregate (hospital) level, using a before and after study design and interrupted time series analyses, respectively. The 15 hospitals that implemented the programme by January 2015 (of a total of 24 between 2015 and 2017) were included in the analyses. RESULTS: There were 31,970 self-harm presentations during the study period. In hospitals with no service for self-harm (n = 4), risk of patients not being assessed reduced from 31.8 to 24.7% following the introduction of the NCPSHI. Mental health referral in this hospital group increased from 42.2 to 59.0% and medical admission decreased from 27.5 to 24.3%. Signs of a reduction in self-harm repetition were observed for this hospital group, from 35.1 to 30.4% among individuals with a history of self-harm, but statistical evidence was weak. In hospitals with a pre-existing liaison psychiatry service (n = 7), risk of self-discharge was lower post-NCPSHI (17.8% vs. 14.8%). In hospitals with liaison nurse(s) pre-NCPSHI (n = 4), medical admission reduced (27.5% vs. 24.3%) and there was an increase in self-harm repetition (from 5.2 to 7.8%. for those without a self-harm history). CONCLUSION: The NCPSHI was associated with improvements in the provision of care across hospital groups, particularly those with no prior service for self-harm, highlighting the need to consider pre-existing context in implementation planning. Our evaluation emphasises the need for proper resourcing to support the implementation of clinical guidelines on the provision of care for people presenting to hospital with self-harm.

Epithelial-mesenchymal transition profiles in triple negative breast carcinoma may explain its aggressive nature.

Epithelial-mesenchymal transition (EMT) is increasingly explored in cancer progression. Considering that triple negative (TN) breast cancer has the poorest survival among molecular subtypes, we investigated 49 TN, 45 luminal and 25 HER2-enriched female breast carcinomas for EMT expression (using E-cadherin and vimentin immunohistochemistry) against lymphovascular and/or lymph node invasion. E-cadherin and vimentin expressions were semi-quantitated for positive- cancer cells (0=0-<1%, 1=1-10%, 2 =11-50%, 3=>50%) and staining intensity (0=negative, 1=weak, 2=moderate, 3=strong), with final score (low=0-4 and high=6-9) derived by multiplying percentage and intensity scores for each marker. Low E-cadherin and/or high vimentin scores defined EMT positivity. Low E-cadherin co-existing with high vimentin defined "complete" (EMT-CV), while low E-cadherin (EMT-C) or high vimentin (EMT-V) occurring independently defined "partial" subsets. 38 (31.9%) cancers expressed EMT, while 59.2 % TN, 13.3% luminal and 12% HER2-enriched cancers expressed EMT (p<0.05). Among the cancers with lymphovascular and/or lymph node invasion, EMT positivity by molecular types were 66.7% TN, 7.4% luminal and 11.8% HER2-enriched (p<0.05). Although EMT-V, associated with stem-cell properties was the dominant TN EMT profile, EMT-CV, a profile linked to vascular metastases, was encountered only in TN. EMT appears important in TN cancer and different EMT profiles may be associated with its aggressive nature.

Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.

Recently, convolutional neural network (CNN)-based classification models have shown good performance for motor imagery (MI) brain-computer interfaces (BCI) using electroencephalogram (EEG) in end-to-end learning. Although a few explainable artificial intelligence (XAI) techniques have been developed, it is still challenging to interpret the CNN models for EEG-based BCI classification effectively. In this research, we propose 3D-EEGNet as a 3D CNN model to improve both the explainability and performance of MI EEG classification. The proposed approach exhibited better performances on two MI EEG datasets than the existing EEGNet, which uses a 2D input shape. The MI classification accuracies are improved around 1.8% and 6.1% point in average on the datasets, respectively. The permutation-based XAI method is first applied for the reliable explanation of the 3D-EEGNet. Next, to find a faster XAI method for spatio-temporal explanation, we design a novel technique based on the normalized discounted cumulative gain (NDCG) for selecting the best among a few saliency-based methods due to their higher time complexity than the permutation-based method. Among the saliency-based methods, DeepLIFT was selected because the NDCG scores indicated its results are the most similar to the permutation-based results. Finally, the fast spatio-temporal explanation using DeepLIFT provides deeper understanding for the classification results of the 3D-EEGNet and the important properties in the MI EEG experiments.