Mechanisms of cuproptosis and its relevance to distinct diseases.

Copper is a trace element required by the organism, but once the level of copper exceeds the threshold, it becomes toxic and even causes death. The underlying mechanisms of copper-induced death are inconclusive, with different studies showing different opinions on the mechanism of copper-induced death. Multiple investigations have shown that copper induces oxidative stress, endoplasmic reticulum stress, nucleolar stress, and proteasome inhibition, all of which can result in cell death. The latest research elucidates a copper-dependent death and denominates it as cuproptosis. Cuproptosis takes place through the combination of copper and lipoylated proteins of the tricarboxylic acid cycle, triggering agglomeration of lipoylated proteins and loss of iron-sulfur cluster proteins, leading to proteotoxic stress and ultimately death. Given the toxicity and necessity of copper, abnormal levels of copper lead to diseases such as neurological diseases and cancer. The development of cancer has a high demand for copper, neurological diseases involve the change of copper contents and the binding of copper to proteins. There is a close relationship between these two kinds of diseases and copper. Here, we summarize the mechanisms of copper-related death, and the association between copper and diseases, to better figure out the influence of copper in cell death and diseases, thus advancing the clinical remedy of these diseases.

Overexpression of zinc-finger protein 418 inhibits pathological cardiac remodelling after acute myocardial infarction.

AIMS: Zinc-finger protein 418 (ZNF418) has been confirmed to be expressed in myocardial tissue. However, the role and mechanism of ZNF418 in pathological myocardial remodelling after myocardial infarction (MI) have not been reported. This study was to elucidate the effect and mechanism of ZNF418 on ventricular remodelling after MI in mice. METHODS AND RESULTS: MI mice and H9c2 cardiomyocytes were used to conduct in vivo and in vitro experiments, respectively. ZNF418 expression was regulated by adeno-associated virus 9 and adenovirus vectors. Pathological analysis, echocardiography, and molecular analysis were performed. ZNF418 was down-regulated in the left ventricular tissues of post-MI mice. In contrast, ZNF418 overexpression decreased mortality and improved cardiac function in MI mice. The MI mice exhibited a significantly increased cross-sectional area of myocardial cells and elevated protein expression levels of myocardial hypertrophy markers ANP, BNP, and ß-MHC (all P < 0.05). Moreover, a significantly increased area of myocardial fibrosis and protein expression levels of myocardial fibrosis markers collagen I, collagen III, and CTGF were observed in MI mice (all P < 0.05) in MI mice. All of the above negative effects in MI mice were ameliorated in ZNF418 overexpressed mice (all P < 0.05). Mechanistically, ZNF418 overexpression inhibited the activation of the MAPK signalling pathway, as evidenced by the in vivo and in vitro experiments. CONCLUSIONS: Overexpression of ZNF418 could improve cardiac function and inhibit pathological cardiac remodelling by inhibiting the MAPK signalling pathway in post-MI mice.

Nurses' perspectives on child-friendly care needs in emergency departments: A qualitative study.

BACKGROUND: Children can become anxious when undergoing emergency medical treatment. Therefore, emergency departments should be child friendly. This study explored emergency nurses' perspectives on children's needs during emergency care. METHOD: This qualitative study employed purposive sampling to recruit 17 emergency nurses from 3 medical centers in northern and central Taiwan. Individual interviews were conducted between January and August 2021. Data were analyzed through qualitative content analysis. RESULTS: The participants had 2-23 years of experience in caring for children in emergency departments. We identified 208 unique meaning units in the interview data, 79 of which were related to child-friendly emergency care. These were classified into 42 codes across 6 categories and 27 subcategories. The six categories were timely comfort, emotional care, frontline safety, emergency response, human resources support, and treatment efficiency. CONCLUSION: Emergency nurses have professional competencies, play a crucial role as care providers for children in the emergency department, and ensure the comfort and safety of children seeking treatment. The categories related to child-friendly emergency care identified in this study can serve as a basis for developing child-friendly care emergency guidelines.

Machine learning models to evaluate mortality in pediatric patients with pneumonia in the intensive care unit.

OBJECTIVES: This study aimed to predict mortality in children with pneumonia who were admitted to the intensive care unit (ICU) to aid decision-making. STUDY DESIGN: Retrospective cohort study conducted at a single tertiary hospital. PATIENTS: This study included children who were admitted to the pediatric ICU at the National Taiwan University Hospital between 2010 and 2019 due to pneumonia. METHODOLOGY: Two prediction models were developed using tree-structured machine learning algorithms. The primary outcomes were ICU mortality and 24-h ICU mortality. A total of 33 features, including demographics, underlying diseases, vital signs, and laboratory data, were collected from the electronic health records. The machine learning models were constructed using the development data set, and performance matrices were computed using the holdout test data set. RESULTS: A total of 1231 ICU admissions of children with pneumonia were included in the final cohort. The area under the receiver operating characteristic curves (AUROCs) of the ICU mortality model and 24-h ICU mortality models was 0.80 (95% confidence interval [CI], 0.69-0.91) and 0.92 (95% CI, 0.86-0.92), respectively. Based on feature importance, the model developed in this study tended to predict increased mortality for the subsequent 24 h if a reduction in the blood pressure, peripheral capillary oxygen saturation (SpO2), or higher partial pressure of carbon dioxide (PCO2) were observed. CONCLUSIONS: This study demonstrated that the machine learning models for predicting ICU mortality and 24-h ICU mortality in children with pneumonia have the potential to support decision-making, especially in resource-limited settings.

Unveiling human origins of replication using deep learning: accurate prediction and comprehensive analysis.

Accurate identification of replication origins (ORIs) is crucial for a comprehensive investigation into the progression of human cell growth and cancer therapy. Here, we proposed a computational approach Ori-FinderH, which can efficiently and precisely predict the human ORIs of various lengths by combining the Z-curve method with deep learning approach. Compared with existing methods, Ori-FinderH exhibits superior performance, achieving an area under the receiver operating characteristic curve (AUC) of 0.9616 for K562 cell line in 10-fold cross-validation. In addition, we also established a cross-cell-line predictive model, which yielded a further improved AUC of 0.9706. The model was subsequently employed as a fitness function to support genetic algorithm for generating artificial ORIs. Sequence analysis through iORI-Euk revealed that a vast majority of the created sequences, specifically 98% or more, incorporate at least one ORI for three cell lines (Hela, MCF7 and K562). This innovative approach could provide more efficient, accurate and comprehensive information for experimental investigation, thereby further advancing the development of this field.

Feasibility of apalutamide combined with androgen deprivation therapy and short-course low-dose prednisone in treating metastatic hormone-sensitive prostate cancer: a pilot randomized controlled trial.

Introduction: The role of prednisone in the prevention of androgen receptor antagonist-related rash and treatment for metastatic hormone-sensitive prostate cancer (mHSPC) is unclear. This pilot trial (ChiCTR2200060388) aimed to investigate the feasibility of apalutamide combined with androgen deprivation therapy (ADT) and short-course low-dose prednisone in the treatment of mHSPC. Methods: All patients received apalutamide and ADT and were randomly divided into two groups based on the administration of oral prednisone or not (control group). The primary endpoint was the incidence of rash. The secondary endpoint included the proportions of patients with a decline in PSA ≥50% from baseline, PSA ≥90% from baseline, and decreased to PSA ≤0.2 ng/mL. Results: Between June 2021 and March 2022, a total of 83 patients were enrolled (41 in the prednisone group and 42 in the control group). During the 6-month follow-up, the incidence of rash was significantly lower in the prednisone group compared with the control group (17.1% vs. 38.1%, P=0.049). There were no significant differences in the incidence of other adverse events, the number of patients who required dose adjustment (reduction, interruption, or discontinuation) of apalutamide due to rash, the number of patients with prostate-specific antigen (PSA) decreased by ≥50%, the number of patients with PSA decrease ≥90%, and the number of patients with PSA ≤0.2 ng/mL between the two groups. All patients with diabetes had stable glycemic control with no glucose-related adverse events. Discussion: In patients with mHSPC, the addition of short-course low-dose prednisolone to apalutamide plus ADT can reduce the incidence of rash without risk of other adverse events.

Acanthosis Nigricans in a Patient with Urothelial Carcinoma Treated with PD-L1 Inhibitor Avelumab, and Secondary Adrenal Insufficiency.

Acanthosis nigricans (AN) describes hyperkeratotic and hyperpigmented skin changes and its pathophysiology is linked to the activation of epidermal growth factor receptors. Current literature shows that AN is most commonly diagnosed at the time of the underlying pathology, which may occur under benign or malignant conditions. This case presentation demonstrates the occurrence of AN in a patient following the diagnosis of urothelial carcinoma and ongoing treatment with PD-L1 inhibitor immunotherapy. Subsequent investigations ruled out a secondary malignancy or disease progression; however, metabolic screening identified secondary glucocorticoid induced adrenal insufficiency. AN was persistent in this patient despite adequate treatment, which highlights its co-occurrence in both benign and paraneoplastic conditions.

Case Series: Cemiplimab and Nivolumab Immunotherapy as Promising Treatment in Advanced or Metastatic Cutaneous Squamous Cell Carcinoma.

Cutaneous squamous cell carcinoma (CSCC) is the second most common skin cancer. Surgery is usually curative; however, some locally advanced or metastatic CSCC may be unresectable. Current novel therapeutic options with immune checkpoint inhibition (ICI) of programmed-death receptor 1 (PD-1) such as cemiplimab and nivolumab have demonstrated promising and sustained results with good tolerability in patients with CSCC. This study looks at 2 cases of CSCC treated with cemiplimab and nivolumab, respectively, demonstrating dramatic response within 2 cycles with significant reduction in tumour size and minimal toxicities or adverse outcomes reported. Immunotherapy has shown positive results as an effective treatment option for unresectable, recurrent, or metastatic CSCC. It is currently approved for use in the USA and Europe.

LSA-ac4C: A hybrid neural network incorporating double-layer LSTM and self-attention mechanism for the prediction of N4-acetylcytidine sites in human mRNA.

N4-acetylcytidine (ac4C) is a vital constituent of the epitranscriptome and plays a crucial role in the regulation of mRNA expression. Numerous studies have established correlations between ac4C and the incidence, progression and prognosis of various cancers. Therefore, accurately predicting ac4C sites is an important step towards comprehending the biological functions of this modification and devising effective therapeutic interventions. Wet experiments are primary methods for studying ac4C, but computational methods have emerged as a promising supplement due to their cost-effectiveness and shorter research cycles. However, current models still have inherent limitations in terms of predictive performance and generalization ability. Here, we utilized automated machine learning technology to establish a reliable baseline and constructed a deep hybrid neural network, LSA-ac4C, which combines double-layer Long Short-Term Memory (LSTM) and self-attention mechanism for accurate ac4C sites prediction. Benchmarking comparisons demonstrate that LSA-ac4C exhibits superior performance compared to the current state-of-the-art method, with ACC, MCC and AUROC improving by 2.89 %, 5.96 % and 1.53 %, respectively, on an independent test set. Overall, LSA-ac4C serves as a powerful tool for predicting ac4C sites in human mRNA, thus benefiting research on RNA modification. For the convenience of the research community, a web server has been established at http://tubic.org/ac4C.

Genotyping in patients with congenital adrenal hyperplasia by sequencing of newborn bloodspot samples.

OBJECTIVES: Genotype-phenotype correlation in congenital adrenal hyperplasia (CAH) caused by 21-hydroxylase deficiency ranges from 45 to 97 %. We performed massively parallel sequencing of CYP21A2 on stored newborn bloodspot samples to catalogue the genotypes present in our patients with CAH and enable genotype-phenotype comparison. METHODS: Participants ≤15 years old with clinically diagnosed CAH were recruited from The Sydney Children's Hospitals Network. Phenotype was classified from clinical and biochemical details in the medical record as salt wasting (SW), simple virilising (SV), non-classic (NC) or an intermediate phenotype (SW/SV; SV/NC). Amplicon-based sequencing for CYP21A2 was performed on stored newborn bloodspot samples by the New South Wales Newborn Bloodspot Screening Laboratory on MiSeq™Dx (Illumina, California). Available genetic test results were also obtained from the medical records. RESULTS: Samples from 67 participants (43 % female, age 0.3-15 years) were sequenced, including 9 sibships. SW phenotype was present in 33/67 participants (49 %), SV in 9 (13 %) and NC in 16 (24 %). Intermediate phenotypes included SW/SV in seven participants (10 %) and SV/NC in two (3 %). Variants were identified in 90/116 alleles (78 %). A complete genotype was available in 47/67 participants (70 %). The most common genotype was homozygous c.293-13A/C>G (I2G) in 7/47 participants (15 %). Genotype correlated with the most commonly reported phenotype in 36/44 cases (82 %). Correlation was higher in SW and NC phenotypes. CONCLUSIONS: This study uses genetic testing of newborn bloodspots to identify and characterise the genotypes present in an ethnically diverse Australian population with CAH. It further strengthens our knowledge of genotype-phenotype correlations in CAH.

Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission.

BACKGROUND: Acute respiratory infections (ARIs) are common in children. We developed machine learning models to predict pediatric ARI pathogens at admission. METHODS: We included hospitalized children with respiratory infections between 2010 and 2018. Clinical features were collected within 24 h of admission to construct models. The outcome of interest was the prediction of 6 common respiratory pathogens, including adenovirus, influenza virus types A and B, parainfluenza virus (PIV), respiratory syncytial virus (RSV), and Mycoplasma pneumoniae (MP). Model performance was estimated using area under the receiver operating characteristic curve (AUROC). Feature importance was measured using Shapley Additive exPlanation (SHAP) values. RESULTS: A total of 12,694 admissions were included. Models trained with 9 features (age, event pattern, fever, C-reactive protein, white blood cell count, platelet count, lymphocyte ratio, peak temperature, peak heart rate) achieved the best performance (AUROC: MP 0.87, 95% CI 0.83-0.90; RSV 0.84, 95% CI 0.82-0.86; adenovirus 0.81, 95% CI 0.77-0.84; influenza A 0.77, 95% CI 0.73-0.80; influenza B 0.70, 95% CI 0.65-0.75; PIV 0.73, 95% CI 0.69-0.77). Age was the most important feature to predict MP, RSV and PIV infections. Event patterns were useful for influenza virus prediction, and C-reactive protein had the highest SHAP value for adenovirus infections. CONCLUSION: We demonstrate how artificial intelligence can assist clinicians identify potential pathogens associated with pediatric ARIs upon admission. Our models provide explainable results that could help optimize the use of diagnostic testing. Integrating our models into clinical workflows may lead to improved patient outcomes and reduce unnecessary medical costs.

Auto-Kla: a novel web server to discriminate lysine lactylation sites using automated machine learning.

Recently, lysine lactylation (Kla), a novel post-translational modification (PTM), which can be stimulated by lactate, has been found to regulate gene expression and life activities. Therefore, it is imperative to accurately identify Kla sites. Currently, mass spectrometry is the fundamental method for identifying PTM sites. However, it is expensive and time-consuming to achieve this through experiments alone. Herein, we proposed a novel computational model, Auto-Kla, to quickly and accurately predict Kla sites in gastric cancer cells based on automated machine learning (AutoML). With stable and reliable performance, our model outperforms the recently published model in the 10-fold cross-validation. To investigate the generalizability and transferability of our approach, we evaluated the performance of our models trained on two other widely studied types of PTM, including phosphorylation sites in host cells infected with SARS-CoV-2 and lysine crotonylation sites in HeLa cells. The results show that our models achieve comparable or better performance than current outstanding models. We believe that this method will become a useful analytical tool for PTM prediction and provide a reference for the future development of related models. The web server and source code are available at http://tubic.org/Kla and https://github.com/tubic/Auto-Kla, respectively.

Nasal pillow vs. standard nasal mask for treatment of OSA: a systematic review and meta-analysis.

PURPOSE: The purpose of this study was to compare the effectiveness of nasal pillows with standard nasal masks in the treatment of patients with obstructive sleep apnea (OSA). METHODS: A digitalized search was carried out in four different databases including PubMed, Scopus, EMBASE, and CENTRAL using relevant keywords along with a manual search in relevant journals. All comparative studies comparing outcomes of using a nasal pillow with the use of standard nasal masks for continuous positive airway pressure (CPAP) treatment in patients with OSA were included. The qualitative analysis was carried out by tabulating the demographic data. The quantitative data were subjected to meta-analysis. The quality of comparative studies (both retrospective and prospective cohorts) was evaluated using New-castle Ottawa scale (NOS). RESULTS: A total of 14 studies (eight prospective and six retrospective) were included in the review. Of them, five studies were randomized and were of cross-over study design. No significant differences were observed in achieved CPAP and residual apnea-hypopnea index (AHI) levels between the nasal pillow and nasal mask with SMD - 0.05 95% CI [- 0.18, 0.09], p = 0.50 and SMD - 0.13 95% CI [- 0.28, 0.03], p = 0.12, respectively. However, nasal pillow usage was associated with better CPAP adherence with a difference of only + 0.29 min/night as compared to a standard nasal mask, with SMD 0.29 95% CI [0.07, 0.50], p = 0.009. CONCLUSION: Nasal pillow and standard nasal mask were equally effective in terms of residual AHI level and achieved similar therapeutic CPAP pressures. However, the difference in CPAP adherence between groups, though statistically significant, is of questionable clinical significance.

Tunable hydrogen enhancement of Ce3+ doped CdS with different Poisson's ratio support.

In this article, a 3D photocatalytic support with different Poisson's ratio was used for the first time to control the photocatalytic production rate of hydrogen. It was created by a stereo-lithography method, and the support with the most negative Poisson's ratio got the best result. The Poisson's ratio of the 3D structure influences the rate of hydrogen production, and it is important for the photocatalyst supports to be porous for light to penetrate into them. A series of Ce doped CdS photocatalysts were produced and immobilized on 3D multicellular Al2O3 supports. By changing the proportion of Ce3+ doped into the CdS photocatalysts 1 % of Ce3+ exhibited optimal hydrogen production, which was 222.9 % compared to that of the pure CdS. Using the 3D photocatalytic support with different Poisson's ratio, the photocatalytic production rate of hydrogen increased by 128 %.

Developing the Chinese version problem areas in diabetes-teen for measuring diabetes distress in adolescents with type 1 diabetes.

PURPOSE: To translate the 26-item English version Problem Areas in Diabetes-Teen (PAID-T) into a Chinese version and then to examine its psychometrical properties for measuring diabetes distress in adolescents with type 1 diabetes (T1D). DESIGN AND METHODS: The 26-item English version PAID-T was translated into a Chinese version guided by the translation model for cross-cultural research. A cross-sectional design was used and 203 adolescents with T1D were recruited from four hospitals in Taiwan. Content validity, exploratory factor analysis, and item analysis were used to ensure the item quality and build the factor structure of the Chinese version PAID-T. Confirmatory factor analysis, concurrent validity, and reliability testing were also used to examine its psychometric properties. RESULTS: The three second-order factors of the 18-item Chinese version PAID-T were developed. The correlation coefficients of the three-factor Chinese version PAID-T with self-management and glycosylated hemoglobin levels were all significant and ranged from -0.32 to -0.45 and 0.18 to 0.33 respectively. Cronbach's α and the test-retest reliability of the three-factor Chinese version PAID-T ranged from 0.85 to 0.93 and from 0.89 to 0.94 respectively. CONCLUSIONS: The Chinese version PAID-T with good translation quality was a reliable and valid scale to screen and assess diabetes distress for adolescents with T1D. PRACTICE IMPLICATIONS: Nurses could use the Chinese version PAID-T to track diabetes distress and tailor interventions for adolescents with T1D; also, the Chinese version PAID-T could facilitate the conducting of research on diabetes distress for adolescents with T1D.

Effectiveness of Virtual Reality Interactive Play for Children During Intravenous Placement: A Randomized Controlled Trial.

PURPOSE: This study aimed to evaluate the effectiveness of an interactive virtual reality (VR) play intervention including instructional play and emotional catharsis play sessions in reducing children's pain and fear during intravenous placement. METHODS: A randomized controlled trial with parallel groups was conducted. The sample consisted of 134 hospitalized children aged 6-12 years (intervention group: n = 69; comparison group: n = 65). The intervention involved one immersive intravenous scene in VR before the actual intravenous placement and one emotional catharsis VR play after injection. The comparison group received an educational photo book about intravenous placement before receiving intravenous placement. The children and their caregivers rated their pain and fear by using the Wong-Baker FACES Pain Rating Scale and the Children's Fear Scale. The time required for successful intravenous insertion was also compared between the two groups. RESULTS: Children's pain (p = .028) and fear scores (p = .004) were significantly lower in the intervention group than in the comparison group. Their caregivers' pain and fear scores (both p < .001) were significantly lower in the intervention group. The time required for successful intravenous insertion did not differ significantly between the intervention and comparison groups. CONCLUSIONS: The interactive play intervention with VR effectively reduced children's levels of pain and fear during the intravenous placement procedure. The results of this study can serve as a reference for the implementation of a feasible, child-friendly care practice for clinical intravenous placement in school-aged children.

Using Text Content From Coronary Catheterization Reports to Predict 5-Year Mortality Among Patients Undergoing Coronary Angiography: A Deep Learning Approach.

Background: Current predictive models for patients undergoing coronary angiography have complex parameters which limit their clinical application. Coronary catheterization reports that describe coronary lesions and the corresponding interventions provide information of the severity of the coronary artery disease and the completeness of the revascularization. This information is relevant for predicting patient prognosis. However, no predictive model has been constructed using the text content from coronary catheterization reports before. Objective: To develop a deep learning model using text content from coronary catheterization reports to predict 5-year all-cause mortality and 5-year cardiovascular mortality for patients undergoing coronary angiography and to compare the performance of the model to the established clinical scores. Method: This retrospective cohort study was conducted between January 1, 2006, and December 31, 2015. Patients admitted for coronary angiography were enrolled and followed up until August 2019. The main outcomes were 5-year all-cause mortality and 5-year cardiovascular mortality. In total, 11,576 coronary catheterization reports were collected. BioBERT (bidirectional encoder representations from transformers for biomedical text mining), which is a BERT-based model in the biomedical domain, was utilized to construct the model. The area under the receiver operating characteristic curve (AUC) was used to assess model performance. We also compared our results to the residual SYNTAX (SYNergy between PCI with TAXUS and Cardiac Surgery) score. Results: The dataset was divided into the training (60%), validation (20%), and test (20%) sets. The mean age of the patients in each dataset was 65.5 ± 12.1, 65.4 ± 11.2, and 65.6 ± 11.2 years, respectively. A total of 1,411 (12.2%) patients died, and 664 (5.8%) patients died of cardiovascular causes within 5 years after coronary angiography. The best of our models had an AUC of 0.822 (95% CI, 0.790-0.855) for 5-year all-cause mortality, and an AUC of 0.858 (95% CI, 0.816-0.900) for 5-year cardiovascular mortality. We randomly selected 300 patients who underwent percutaneous coronary intervention (PCI), and our model outperformed the residual SYNTAX score in predicting 5-year all-cause mortality (AUC, 0.867 [95% CI, 0.813-0.921] vs. 0.590 [95% CI, 0.503-0.684]) and 5-year cardiovascular mortality (AUC, 0.880 [95% CI, 0.873-0.925] vs. 0.649 [95% CI, 0.535-0.764]), respectively, after PCI among these patients. Conclusions: We developed a predictive model using text content from coronary catheterization reports to predict the 5-year mortality in patients undergoing coronary angiography. Since interventional cardiologists routinely write reports after procedures, our model can be easily implemented into the clinical setting.

Rare complication of ureteral double-J stenting after ureteroscopy: pelvic ectopic renal parenchymal perforation.

Scarce data are available on pelvic ectopic renal parenchymal perforation. However, this complication might lead to serious consequences. Clinicians should pay attention to the early identification and treatment of this complication. We herein report the first case of pelvic ectopic renal parenchymal perforation caused by a double-J stent after ureteroscopy. Compared with previously reported cases of renal parenchymal perforation not involving an ectopic kidney, our case involved no renal capsule hematoma and no other serious complications. Our primary management strategy was to review relevant examinations and tests, perform close monitoring, and instruct the patient to stay in bed. The patient recovered smoothly after the ureteral stent was removed 1 month postoperatively.