bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rates, characteristics and toxicology of cocaine‐related deaths in Australia, 2000–2021
Authors: Darke Shane , Duflou Johan , Peacock Amy , Chrzanowska Agata , Farrell Michael , Lappin Julia 
Published: September 2022

AbstractAimsTo (i) assess the population mortality rates of cocaine‐related deaths in Australia, 2000 to 2021; (ii) determine the circumstances of death and case characteristics; and (iii) determine their toxicological profile.DesignRetrospective study of cocaine‐related deaths in Australia, 2000 to 2021, retrieved from the National Coronial Information System.SettingAustralia‐wide.CasesA total of 884 cases, mean age = 33.8 (SD, 10.0) years and 86.5% (n = 765) male.MeasurementsInformation was collected on characteristics, manner of death and toxicology. Only cases in which the presence of blood cocaine and/or metabolites were included.FindingsPopulation rates did not significantly increase during 2001–2011 (annual percentage change [APC] = 1.5; CI, −3.2, 6.5), but from 2012, there was a marked acceleration (APC = 20.0, 95% CI, 15.5, 25.3). Circumstances of death were unintentional drug toxicity (70.7%, n = 625), intentional self‐harm (17.8%, n = 157), traumatic accident (11.5%, n = 102). The proportion of cases constituted by unintentional toxicity declined across the study period (APC = −2.6; CI, −3.1, −2.1). There was a substantial decline in the proportion of cases with a history of injecting drug use (APC = −5.7; CI, −6.5, −4.9) and with a history of substance use problems (APC = −3.2; CI, −3.9, −2.5). Both cocaine (0.100 vs 0.050 mg/L, P < 0.001) and benzoylecgonine (0.590 vs 0.240 mg/L, P < 0.001) concentrations were higher amongst toxicity cases than in cases of death from traumatic injury. Cocaethylene was present in 26.4% (n = 233), levamisole in 18.6% (n = 164) and lignocaine in 11.5% (n = 102). Psychoactive drugs in addition to cocaine were present in 92.9% (n = 821), most commonly opioids (50.5%, n = 446), alcohol (47.1%, n = 416), hypnosedatives (43.2%, n = 382) and psychostimulants (30.3%, n = 268). There was a steady decline in the proportion of opioid positive cases (APC = −5.4; CI, −6.3, −4.5).ConclusionsThere was a large increase in cocaine‐related deaths across Australia from 2000 to 2021. This was accompanied by changes in case profiles, with histories of injecting drug use and substance use problems, as well as recent opioid use, becoming less prominent.
Predictors of histologic response to dietary therapy in eosinophilic oesophagitis
Authors: Wang Lillian , Mara Kristin C. , Ravi Karthik , Wu Tsung‐Teh , Smyrk Thomas C. , Katzka David A. , Alexander Jeffrey A. 
Published: September 2022

SummaryBackgroundDietary therapy successfully treats eosinophilic oesophagitis (EoE), but limited data exist on predictors of patient response.AimsTo determine response rates and to identify predictors of histologic response to elimination diets in adults with EoEMethodsThis was a retrospective, single‐centre study of adults with PPI‐refractory EoE undergoing dietary therapy with six food elimination diet (SFED) or extended six food elimination diet (ExSFED) in an outpatient setting from January 2012 to January 2019. Patient demographics, radiologic and endoscopic findings, endoscopic reference (EREF) scores, histology and symptoms were evaluated before and after food elimination. Histologic response was assessed via tissue obtained from endoscopically‐guided biopsy or Cytosponge. Dietary therapy adherence was assessed via structured phone interview. Multivariable logistic regression analysis was performed to identify predictors of dietary response.ResultsWe included 68 patients, of whom 62% had a histologic response to dietary therapy (81% to SFED, 19% to ExSFED). Median duration of follow‐up was 45 months (IQR, 34–53 months). On multivariable analysis, higher pre‐SFED EREF score was the only variable associated with dietary non‐response (OR 0.07, 95% CI 0.49, 0.98; p = 0.04).ConclusionsIn adults with EoE, histologic dietary non‐response to SFED was associated with a higher pre‐SFED EREF score, suggesting that fixed structural disease may predict dietary non‐response. Our additional observations of poor correlation between symptomatic and histologic flares, and identification of ExSFED responders, suggest that histologic confirmation should be sought before committing patients to lifelong dietary changes. We also recommend the consideration of restricting legumes and corn in SFED non‐responders as ExSFED detected additional dietary responders.
GABAA receptors as targets for anaesthetics and analgesics and promising candidates to help treat coronavirus infections: A mini‐review
Authors: Luo Yujia , Balle Thomas 
Published: September 2022

AbstractGABA is a major inhibitory neurotransmitter that regulates the balance between excitatory and inhibitory circuits in the human nervous system. The GABA receptors are divided into three main subtypes, GABAA, GABAB, and GABAC (also termed GABAA rho) receptors. GABAA receptors are pentameric ligand‐gated ion channels widely expressed throughout the central and peripheral nervous system. The activation of GABAA receptors results in opening of an anion‐selective channel that mainly gates chloride ions and allows them to flow into the neuron, causing hyperpolarization of the cell membrane that dampens neural excitability. This makes GABAA receptors critical anaesthetic and analgesic targets for existing as well as for the development of novel drugs. In this review, we first summarize the biochemical properties of GABAA receptors and the clinical anaesthetics and analgesics targeting the receptors. In a forward‐looking section, we summarize the emerging role of GABAergic signalling in treatment of COVID‐19 related infections. Finally, we discuss the opportunities arising from targeting specific and unique subunit interfaces for the development of novel anaesthetics and analgesics leading to more efficient therapies.
An fMRI examination of the neural basis of suicide attempts: The role of mentalizing in the context of mood
Authors: Malhi Gin S. , Das Pritha , Outhred Tim , Bryant Richard A. , Calhoun Vince D. 
Published: September 2022

AbstractObjectivesFacial emotion recognition (FER) deficits in depressed mood disorder patients contribute to suicidality. Prior research shows that intrinsic brain activity patterns are altered by attempting suicide. Therefore, we investigated in depressed patients whether differences in FER contribute to their clinical symptoms of suicide.MethodsNeural activity in response to an FER task was compared across three groups: healthy controls (HCs, N = 66), suicide non‐attempter (SNA, N = 50), suicide attempter (SA, N = 25). Modulation of brain networks by the task and functional connectivity (FC) within (using spatial map, spectral power) and between (using functional network connectivity; FNC) were examined. The contribution of these differences to suicidal symptoms in each group was also examined.ResultsPatient groups displayed impaired FC both within and between networks but differed in nature and networks involved. They also showed differential modulation of networks by task, such that compared with both HC and SNA, SA displayed impaired FC within the default‐mode network (DMN) and also its task modulation. In the SA group, FC within the DMN and FNC between two lateral prefrontal networks, and its interaction with the basal ganglia network contributed significantly to the clinical symptoms of suicide.ConclusionsThis study affirms differences between SA and SNA brain activity patterns and suggests that suicidal activity probably emanates via different mechanisms in these patient groups. Perhaps, over‐attribution of emotion impairs one's self‐referential thought processes and coupled with diminished emotional control this makes depressed individuals vulnerable to suicide.
The inhibition of MDM2 slows cell proliferation and activates apoptosis in ADPKD cell lines
Authors: Patergnani Simone , Giattino Antonino , Bianchi Nicoletta , Giorgi Carlotta , Pinton Paolo , Aguiari Gianluca 
Published: September 2022

AbstractIntroductionAutosomal dominant polycystic kidney disease (ADPKD) is characterised by progressive cysts formation and renal enlargement that in most of cases leads to end stage of renal disease (ESRD). This pathology is caused by mutations of either PKD1 or PKD2 genes that encode for polycystin‐1 (PC1) and polycystin‐2 (PC2), respectively. These proteins function as receptor‐channel complex able to regulate calcium homeostasis. PKD1/2 loss of function impairs different signalling pathways including cAMP and mTOR that are considered therapeutic targets for this disease. In fact, Tolvaptan, a vasopressin‐2 antagonist that reduces cAMP levels, is the only drug approved for ADPKD treatment. Nevertheless, some ADPKD patients developed side effects in response to Tolvaptan including liver damage. Conversely, mTOR inhibitors that induced disease regression in ADPKD animal models failed the clinical trials.ResultsHere, we show that the inhibition of mTOR causes the activation of autophagy in ADPKD cells that could reduce therapy effectiveness by drug degradation through the autophagic vesicles. Consistently, the combined treatment with rapamycin and chloroquine, an autophagy inhibitor, potentiates the decrease of cell proliferation induced by rapamycin. To overcome the dangerous activation of autophagy by mTOR inhibition, we targeted MDM2 (a downstream effector of mTOR signalling) that is involved in TP53 degradation by using RG7112, a small‐molecule MDM2 inhibitor used for the treatment of haematologic malignancies. The inhibition of MDM2 by RG7112 prevents TP53 degradation and increases p21 expression leading to the decrease of cell proliferation and the activation of apoptosis.ConclusionThe targeting of MDM2 by RG7112 might represent a new therapeutic option for the treatment of ADPKD.
The prevalence of acromegaly is higher than previously reported: Changes over a three‐decade period
Authors: Aagaard Charlotte , Christophersen Amanda S. , Finnerup Susanne , Rosendal Christian , Gulisano Helga A. , Ettrup Kåre S. , Vestergaard Peter , Karmisholt Jesper , Nielsen Eigil Husted , Dal Jakob 
Published: September 2022

AbstractObjectiveTo study time‐related changes in the prevalence and patient characteristics of acromegaly, as well as to assess the impact of changes in treatment on disease control.MethodsA total of 107 patients with acromegaly were identified by healthcare registries and subsequently validated by patient chart review over a three‐decade period (1992–2021). A systematic literature review focusing on the incidence and prevalence of acromegaly was performed identifying 31 studies.ResultsThe prevalence of acromegaly significantly increased throughout the study period (R2 = 0.94, p < .001) and was 122 cases/106 persons in 2021 whereas the annual incidence remained constant at 4.6 cases/106 persons. The age at the first sign of acromegaly and the age at diagnosis significantly increased during the study period, whereas growth hormone and insulin‐like growth factor I decreased. Incidentalomas constituted 32% of all cases diagnosed with acromegaly in the last decade. Primary surgery was used in 93% of all cases, and repeated surgery decreased from 24% to 10% during the three decades. The use of first‐generation somatostatin analogues (21%–48%) and second‐line medical treatment (4%–20%) increased with a concomitant improvement of biochemical disease control (58%–91%).ConclusionThe prevalence of acromegaly is higher than previously reported and the clinical presentation has shifted towards a milder phenotype. Modern treatment of acromegaly enables individualized treatment and disease control in the majority of patients.
Effects of writers, erasers and readers within miRNA‐related m6A modification in cancers
Authors: Feng Huiru , Yuan Xiaofei , Wu Shuting , Yuan Yue , Cui Linchong , Lin Danfan , Peng Xiaohong , Liu Xiong , Wang Fan 
Published: September 2022

AbstractBackgroundAs one of the most abundant post‐transcriptional mRNA modifications, N6‐methyladenosine (m6A) has attracted extensive attention from scientists. Emerging evidence indicates that m6A modification plays a significant role in cancer‐related signalling pathways. Existing research demonstrates that m6A modifications were also identified in miRNAs and contribute to cancer‐related signalling pathways.MethodsA literature retrieval has been performed to collect m6A‐miRNA‐related original articles published in recent years. Later, a systematic analysis has been conducted to abstract and classify the relationships between m6A modification and miRNAs, and their contributions to tumorigenesis and cancer development.ResultsAccumulating literature provides important insights into multiple relationships between m6A modifications and miRNAs. Mechanically, m6A writer and eraser alter pri‐miRNAs m6A levels, and m6A readers could dually modulate pri‐miRNAs processing and pri‐miRNAs degradation. It is also been demonstrated that miRNAs impair m6A regulators' translation to influence m6A medication function in return. Aberrant expressions of m6A regulators and miRNAs could dysregulate proliferative, apoptosis, cell adhesion‐related, and malignant transformation signalling pathways, and contribute to tumour occurrence and development.ConclusionThis review summarizes the interrelationship between m6A modification and miRNAs; highlights the combined effects of each type of m6A regulator and miRNAs in cancers. These findings enhance our understanding of m6A‐miRNAs' multiple interactions and significant modulatory role in tumorigenesis and progression.
Analysis of individual components of frailty: Pre‐transplant grip strength is the strongest predictor of post kidney transplant outcomes
Authors: Parajuli Sandesh , Astor Brad C. , Lorden Heather M. , O'Toole Kristan A. , Wallschlaeger Rebecca E. , Breyer Isabel C. , Dodin Ban , Aziz Fahad , Garonzik‐Wang Jacqueline , Mandelbrot Didier A. 
Published: September 2022

AbstractFrailty is commonly assessed during kidney transplant recipient (KTR) evaluation. However, individual frailty components may have varying impact on post‐transplant outcomes. In this single‐center study of 825 KTRs, we determined the association between the individual components of a modified Fried frailty score and delayed graft function (DGF), early hospital readmission (EHR), cardiovascular (CV) events, acute rejection (AR), death censored graft failure (DCGF), and death. Sum frailty ≥3 was significantly associated with EHR (aOR = 3.62; 95% CI: 1.21–10.80). Among individual components, only grip strength was significantly associated with EHR (aOR = 1.54; 95% CI: 1.03–2.31). The addition of grip strength to a model with the other four components resulted in Net Reclassification Improvement (NRI) of 20.51% (p = .01). Similarly, only grip strength was significantly associated with CV events (aOR = 1.79; 95% CI: 1.12–2.86). The addition of grip strength to a model with the other four components resulted in NRI of 27.37% (p = .006). No other frailty components were associated with the outcomes of interest. Based on our findings, handgrip strength may be an important tool while assessing frailty, mainly predicting early readmission and cardiovascular events post‐transplant.
Population pharmacokinetic and pharmacodynamic modeling of evobrutinib in healthy adult participants
Authors: Papasouliotis Orestis , Mitchell David , Girard Pascal , Dyroff Martin 
Published: September 2022

AbstractEvobrutinib, a Bruton's tyrosine kinase (BTK) inhibitor, has shown therapeutic potential in relapsing multiple sclerosis. This analysis aimed to develop pharmacokinetic (PK) and pharmacodynamic (PD; BTK occupancy [BTKO]) models of evobrutinib and simulate PK and BTKO profiles under alternative dosing regimens. Data were obtained from two phase I evobrutinib studies in healthy adult participants (Japanese and non‐Japanese). Overall, 2326 observations were available from 76 participants; n = 42 from Study MS200527_0017 Part A received evobrutinib 25, 75, or 200 mg once‐daily oral doses for 6 days while fasted; n = 18 from Study MS200527_0019 and n = 16 from Study MS200527_0017 Part B received single evobrutinib 75 mg oral doses with food (low‐fat meal) and while fasted. Population PK/PD modeling for evobrutinib concentrations and BTKO (fraction unbound) were performed using nonlinear mixed‐effects modeling. The effect of once‐daily/twice‐daily regimens and doses of 10–200 mg on BTKO were simulated. A two‐compartment model with sequential zero‐first order absorption and first‐order elimination adequately described the data. Bioavailability increased by 49% with food compared with when fasted. There was no difference in PK parameters between Japanese and non‐Japanese participants. The BTKO profile of evobrutinib was described by the irreversible binding population model. The simulated percentage of participants with minimum BTKO increased in a dose‐dependent manner across the BTKO thresholds of interest (70%, 80%, 90%, and 95% occupancy). Evobrutinib doses of 25 mg once‐daily, 50 mg twice‐daily, or 75 mg twice‐daily while fasted are possible choices for further development, assuming BTKO ≥70% at trough is needed to achieve efficacy.
Helicobacter pylori infection and PD‐L1 expression in gastric cancer: A meta‐analysis
Authors: Zhu Yaodong , Zhu Fangyuan , Ba He , Chen Jie , Bian Xiuliang 
Published: September 2022

AbstractBackgroundHigh expression of programmed death ligand‐1 (PD‐L1) has been related to good response to immunotherapy patients with gastric cancer (GC). However, the influence of Helicobacter pylori (HP) infection on PD‐L1 expression in GC remains unknown. A meta‐analysis was performed to evaluate the association between HP infection and PD‐L1 expression in GC.MethodsObservational studies that investigated the relationship between HP infection and PD‐L1 expression in patients with GC were obtained by search electronic databases, including PubMed, Embase, Cochrane's Library and Web of Science. A random‐effect model incorporating the possible influence of between‐study heterogeneity was used to pool the results.ResultsTen studies with 1870 patients with GC contributed to the meta‐analysis. Pooled results showed that HP infection was significantly associated with the tumour expression of PD‐L1 (odds ratio [OR]: 1.90, 95% confidence interval: 1.33–2.72, p < .001; I2 = 53%). Subgroup analyses showed that the association between HP infection and PD‐L1 expression in GC was not significantly affected by sample size, methods for PD‐L1 evaluation and quality score (p for subgroup analyses all >.05). However, a stronger association was observed in studies with higher prevalence of HP infection (≥35%, OR: 2.58) as compared with those with lower prevalence (<35%, OR: 1.45, p for subgroup difference = .04).ConclusionHelicobacter pylori infection in GC patients is associated with tumour expression of PD‐L1, suggesting HP infection may be a predictor of good response to immunotherapy in GC.
RETRACTED: Cyber security for federated learning environment using AI technique
Authors: J. Alyamani Hasan 
Published: September 2022

AbstractA cyber‐security threat in the Android environment is seen as malicious code. Due to the rapid development of Android malware deployments, manually detecting malicious apps inside the Android environment is almost impossible. In the end of an outcome, machine learning has emerged as a promising method for detecting malware. Because the increasing accessibility and appropriate attributes have a significant impact on machine learning performance, selecting features becomes more critical in malware detection using the machine learning. In the existing system, a filter‐based feature selection method was used. The filter‐based feature subset selection strategies are mathematically efficient for computation. But they refuse to address concerns including such multicollinearity, which impacts the filter methods' accuracy. To overcome this issue, this research develops a hybrid method that combines the findings of both static and dynamic malware examination. This method tackles the issue of more effectively analysing, identifying, and classifying Android malware. Many feature selection approaches are compared and contrasted based on a variety of parameters, such as the composition of important extracted features. By using extracted features, whilst completing static and dynamic malware examinations, several machine learning methods are used to identify and characterize malware. The experimental result shows the evaluation of the feature selection method which is varied from other algorithms. It enhances the accuracy and minimizes the run time of the learning models.
Metaheuristics with federated learning enabled intrusion detection system in Internet of Things environment
Authors: Vaiyapuri Thavavel , Algamdi Shabbab , John Rajan , Sbai Zohra , Al‐Helal Munira , alkhayyat Ahmed , Gupta Deepak 
Published: September 2022

AbstractBecause of increased applications of Internet of Things (IoT) environment in real‐time environment, confidential data gathered by the IoT devices are being communicated to the cloud environment to train the machine learning (ML) models in understanding the patterns that exist in the data. At the same time, the sensitive nature of the IoT data attracts malicious users into hacking efforts. An intrusion detection system (IDS) can be applied to ensure security in the IoT environment. In order to improve security, the ML models can be executed at the data source instead of centralized cloud server. Federated learning (FL) is a recent progression of ML model which enables the ML models to move into the data source rather than moving the data to centralized cloud and thereby resolves cybersecurity problems in the IoT environment. In this view, this study introduces an FL based IDS using bird swarm algorithm based feature selection with classification (FLIDS‐BSAFSC) model in IoT environment. The presented FLIDS‐BSAFSC model undergoes training on multiple aspects of IoT dataset in a decentralized format to classify, detect, and defend against attacks. The proposed FLIDS‐BSAFSC model initially applies min–max normalization technique to pre‐process the IoT data. Besides, BSA based feature selection (BSA‐FS) technique is designed to elect feature subsets. Finally, social group optimization algorithm with kernel extreme learning machine model is employed for identifying various kinds of classes. In the view of FL where the IoT dataset is not distributed to the server carries out profile aggregation competently with the advantage of peer learning. The experimental validation of the FLIDS‐BSAFSC model is tested using benchmark datasets and the results are inspected under several aspects. The experimental values highlighted the better performance of the FLIDS‐BSAFSC model over recent approaches.