Graph Attention-Based Curriculum Learning for Mental Healthcare Classification

Current research has examined the use of user-generated data from online media to identify and diagnose depression as a serious mental health issue that can significantly impact an individual's daily life. To this end, many studies examined words in personal statements to identify depression. In addition to aiding in the diagnosis and treatment of depression, this study uses and utilizes a Graph Attention Network (GAT) model for the classification of depression from online media. The model is based on masked self-attention layers, that assigns different weight to each node in a neighborhood without costly matrix operations. In addition, an emotion lexicon was extended using hypernyms to improve the model performance. Furthermore, embedding of the model was used to illustrate the contribution of the activated words to each symptom and to obtain qualitative agreement from psychiatrists. This technique uses previously learned embedding to illustrate the contribution of activated words to depressive symptoms in online forums. A significant improvement was observed in the model's performance through the use of the lexicon extension method, resulting in an increase in the ROC performance. The performance was also enhanced by an increase in vocabulary and the adoption of a graph-based curriculum. The lexicon expansion method involves the generation of additional words with similar semantic attributes, utilizing similarity metrics to reinforce lexical features. The graph-based curriculum learning also utilized to handle more challenging training samples, allowing the model to develop increasing expertise in learning complex correlations between input data and output labels.

Long-term clinical outcomes of intravascular imaging-guided percutaneous coronary intervention versus angiography-guided percutaneous coronary intervention in complex coronary lesions: a systematic review and meta-analysis

Background: In this study, we aim to discuss the long-term clinical outcomes of intravascular ultrasound imaging-guided percutaneous intervention (IVUS-PCI) versus angiography-guided percutaneous coronary intervention (PCI) in complex coronary lesions over a mean period of 2 years. Methods: A systematic search and meta-analysis were conducted to assess the efficacy of using intravascular ultrasound or optical coherence tomography guidance in coronary artery stenting compared to angiography. Results: A total of 11 randomized controlled trials with 6740 patients were included. For the primary outcome, a pooled analysis (3.2 vs 5.6%). For secondary outcomes, the risk was significantly low in image-guided percutaneous intervention compared with angiography. Conclusion: Intravascular imaging-guided PCI is significantly more effective than angiography-guided PCI in reducing the risk of target lesion revascularization, target vessel revascularization, cardiac death, major adverse cardiovascular events and stent thrombosis.

Nanoparticle-Terpene Fusion: A Game-Changer in Combating Primary Amoebic Meningoencephalitis Caused by Naegleria fowleri

Pathogenic Naegleria fowleri (N. fowleri) are opportunistic free-living amoebae and are the causative agents of a very rare but severe brain infection called primary amoebic meningoencephalitis (PAM). The fatality rate of PAM in reported cases is more than 95%. Most of the drugs used againstN. fowleri infections are repurposed drugs. Therefore, a large number of compounds have been tested againstN. fowleri in vitro, but most of the tested compounds showed high toxicity and an inability to cross the blood-brain barrier. Andrographolide, forskolin, and borneol are important natural compounds that have shown various valuable biological properties. In the present study, the nanoconjugates (AND-AgNPs, BOR-AgNPs, and FOR-AgNPs) of these compounds were synthesized and assessed against both stages (trophozoite and cyst) ofN. fowleri for their antiamoebic and cysticidal potential in vitro. In addition, cytotoxicity and host cell pathogenicity were also evaluated in vitro. FOR-AgNPs were the most potent nanoconjugate and showed potent antiamoebic activity againstN. fowleriwith an IC50 of 26.35 μM. Nanoconjugates FOR-AgNPs, BOR-AgNPs, and AND-AgNPs also significantly inhibit the viability of N. fowleri cysts. Cytotoxicity assessment showed that these nanoconjugates caused minimum damage to human keratinocyte cells (HaCaT cells) at 100 μg/mL, while also effectively reducing the cytopathogenicity of N. fowleri trophozoites to the HaCaT cells. The outcomes of our experiments have unveiled substantial potential for AND-AgNPs, BOR-AgNPs, and FOR-AgNPs in the realm of developing innovative alternative therapeutic agents to combat infections caused by N. fowleri. This study represents a significant step forward in the pursuit of advanced strategies for managing such amoebic infections, laying the foundation for the development of novel and more effective therapeutic modalities in the fight against free-living amoebae.

Self-assembled micelles loaded with itraconazole as anti-Acanthamoeba nano-formulation

Acanthamoeba castellanii are opportunistic pathogens known to cause infection of the central nervous system termed: granulomatous amoebic encephalitis, that mostly effects immunocompromised individuals, and a sight threatening keratitis, known as Acanthamoeba keratitis, which mostly affects contact lens wearers. The current treatment available is problematic, and is toxic. Herein, an amphiphilic star polymer with AB2 miktoarms [A = hydrophobic poly(ℇ-Caprolacton) and B = hydrophilic poly (ethylene glycol)] was synthesized by ring opening polymerization and CuI catalyzed azide-alkyne cycloaddition. Characterization by 1H and 13C NMR spectroscopy, size-exclusion chromatography and fluorescence spectroscopy was accomplished. The hydrophobic drug itraconazole (ITZ) was incorporated in self-assembled micellar structure of AB2 miktoarms through co-solvent evaporation. The properties of ITZ loaded (ITZ-PCL-PEG2) and blank micelles (PCL-PEG2) were investigated through zeta sizer, scanning electron microscopy and Fourier-transform infrared spectroscopy. Itraconazole alone (ITZ), polymer (DPB-PCL), empty polymeric micelles (PCL-PEG2) alone, and itraconazole loaded in polymeric micelles (ITZ-PCL-PEG2) were tested for anti-amoebic potential against Acanthamoeba, and the cytotoxicity on human cells were determined. The polymer was able to self-assemble in aqueous conditions and exhibited low value for critical micelle concentration (CMC) 0.05-0.06 µg/mL. The maximum entrapment efficiency of ITZ was 68%. Of note, ITZ, DPB, PCL-PEG2 and ITZ-PCL-PEG2 inhibited amoebae trophozoites by 37.34%, 36.30%, 35.77%, and 68.24%, respectively, as compared to controls. Moreover, ITZ-PCL-PEG2 revealed limited cytotoxicity against human keratinocyte cells. These results are indicative that ITZ-PCL-PEG2 micelle show significantly better anti-amoebic effects as compared to ITZ alone and thus should be investigated further in vivo to determine its clinical potential.

No clinical advantage with customized individually made implants over conventional off-the-shelf implants in total knee arthroplasty: a systematic review and meta-analysis

INTRODUCTION

Total knee arthroplasty (TKA) can be performed with either conventional off-the-shelf (OTS) or customized individually-made (CIM) implants. The evidence for CIM implants is limited and variable, and the aim of this review was to compare clinical and radiological outcomes between CIM and OTS implants.

METHODS

A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. Studies reporting on clinical, radiological, or alignment outcomes for CIM and OTS implants were selected. The studies were appraised using the Methodical index for non-randomized studies tool.

RESULTS

Twenty-three studies fulfilled the inclusion criteria. The studies comprised 2856 CIM and 1877 OTS TKAs. Revision rate was higher with CIM (5.9%) compared to OTS (3.7%) implants [OR 1.23(95% CI 0.69-2.18)]. Manipulation under anesthesia (MUA) was higher in CIM (2.2%) compared to OTS (1.1%) group [OR 2.95(95% CI 0.95-9.13)] and complications rate was higher in CIM (5%) vs. OTS (4.5%) [OR 1.45(95% CI 0.53-3.96)] but neither reached statistical significance. Length of stay was significantly shorter in CIM group 2.9 days vs. 3.5 days [MD - 0.51(95% CI - 0.82 to - 0.20)]. Knee Society Score showed no difference between CIM and OTS groups for Knee 90.5 vs. 90.6 [MD - 0.27(95% CI - 4.27 to 3.73)] and Function 86.1 vs. 83.1 [MD 1.51(95% CI - 3.69 to 6.70)].

CONCLUSION

CIM implants in TKA have theoretical benefits over OTS prostheses. However, in this present review, CIM implants were associated with higher revisions, MUA, and overall complication rates. There was no difference in outcome score and CIM implants did not improve overall target alignment; however, more CIM TKAs were found to be in the HKA target zone compared to OTS TKAs. The findings of this review do not support the general utilization of CIM over OTS implants in TKA.

The characteristics and predictors of mortality in periprosthetic fractures around the knee

Aims

Periprosthetic fractures (PPFs) around the knee are challenging injuries. This study aims to describe the characteristics of knee PPFs and the impact of patient demographics, fracture types, and management modalities on in-hospital mortality.

Methods

Using a multicentre study design, independent of registry data, we included adult patients sustaining a PPF around a knee arthroplasty between 1 January 2010 and 31 December 2019. Univariate, then multivariable, logistic regression analyses were performed to study the impact of patient, fracture, and treatment on mortality.

Results

Out of a total of 1,667 patients in the PPF study database, 420 patients were included. The in-hospital mortality rate was 6.4%. Multivariable analyses suggested that American Society of Anesthesiologists (ASA) grade, history of peripheral vascular disease (PVD), history of rheumatic disease, fracture around a loose implant, and cerebrovascular accident (CVA) during hospital stay were each independently associated with mortality. Each point increase in ASA grade independently correlated with a four-fold greater mortality risk (odds ratio (OR) 4.1 (95% confidence interval (CI) 1.19 to 14.06); p = 0.026). Patients with PVD have a nine-fold increase in mortality risk (OR 9.1 (95% CI 1.25 to 66.47); p = 0.030) and patients with rheumatic disease have a 6.8-fold increase in mortality risk (OR 6.8 (95% CI 1.32 to 34.68); p = 0.022). Patients with a fracture around a loose implant (Unified Classification System (UCS) B2) have a 20-fold increase in mortality, compared to UCS A1 (OR 20.9 (95% CI 1.61 to 271.38); p = 0.020). Mode of management was not a significant predictor of mortality. Patients managed with revision arthroplasty had a significantly longer length of stay (median 16 days; p = 0.029) and higher rates of return to theatre, compared to patients treated nonoperatively or with fixation.

Conclusion

The mortality rate in PPFs around the knee is similar to that for native distal femur and neck of femur fragility fractures. Patients with certain modifiable risk factors should be optimized. A national PPF database and standardized management guidelines are currently required to understand these complex injuries and to improve patient outcomes.

Lactase can target cellular differentiation of Acanthamoeba castellanii belonging to the T4 genotype

The free living Acanthamoeba spp. are ubiquitous amoebae associated with potentially blinding disease known as Acanthamoeba keratitis (AK) and a fatal central nervous system infection granulomatous amoebic encephalitis (GAE). With the inherent ability of cellular differentiation, it can phenotypically transform to a dormant cyst form from an active trophozoite form. Acanthamoeba cysts are highly resistant to therapeutic agents as well as contact lens cleaning solutions. One way to tackle drug resistance against Acanthamoeba is by inhibiting the formation of cysts from trophozoites. The biochemical analysis showed that the major component of Acanthamoeba cyst wall is composed of carbohydrate moieties such as galactose and glucose. The disaccharide of galactose and glucose is lactose. In this study, we analyzed the potential of lactase enzyme to target carbohydrate moieties of cyst walls. Amoebicidal assessment showed that lactase was ineffective against trophozoite of A. castellanii but enhanced amoebicidal effects of chlorhexidine. The lactase enzyme did not show any toxicity against normal human keratinocyte cells (HaCaT) at the tested range. Hence, lactase can be used for further assessment for development of potential therapeutic agents in the management of Acanthamoeba infection as well as formulation of effective contact lens disinfectants.

Potential anti-amoebic effects of synthetic 1,4-benzothiazine derivatives against Acanthamoeba castellanii

A rare but lethal central nervous system disease known as granulomatous amoebic encephalitis (GAE) and potentially blinding Acanthamoeba keratitis are diseases caused by free-living Acanthamoeba. Currently, no therapeutic agent can completely eradicate or prevent GAE. Synthetic compounds are a likely source of bioactive compounds for developing new drugs. This study synthesized seventeen 1,4-benzothiazine derivatives (I -XVII) by a base-catalyzed one-pot reaction of 2-amino thiophenol with substituted bromo acetophenones. Different spectroscopic techniques, such as EI-MS, 1H-, and 13C NMR (only for the new compounds), were used for the structural characterization and conformation of compounds. These compounds were assessed for the first time against Acanthamoeba castellanii. All compounds showed anti-amoebic potential in vitro against A. castellanii, reducing its ability to encyst and excyst at 100 μM. Compounds IX, X, and XVI showed the most potent activities among all derivatives and significantly reduced the viability to 5.3 × 104 (p < 0.0003), 2 × 105 (p < 0.006), and 2.4 × 105 (p < 0.002) cells/mL, respectively. The cytotoxicity profile revealed that these molecules showed lower to moderate cytotoxicity, i.e., 36 %, 2 %, and 21 %, respectively, against human keratinocytes in vitro. These results indicate that 1,4-benzothiazines showed potent in vitro activity against trophozoites and cysts of A. castellanii. Hence, these 1,4-benzothiazine derivatives should be considered to develop new potential therapeutic agents against Acanthamoeba infections.

Natural Terpenes Inhibit the Cytopathogenicity of Naegleria fowleri Causing Primary Amoebic Meningoencephalitis in the Human Cell Line Model

Naegleria fowleri is one of the free-living amoebae and is a causative agent of a lethal and rare central nervous system infection called primary amoebic meningoencephalitis. Despite the advancement in antimicrobial chemotherapy, the fatality rate in the reported cases is more than 95%. Most of the treatment drugs used against N. fowleri infection are repurposed drugs. Therefore, a large number of compounds have been tested against N. fowleri in vitro, but most of the compounds showed high toxicity. To overcome this, we evaluated the effectiveness of naturally occurring terpene compounds against N. fowleri. In this study, we evaluated the antiamoebic potential of natural compounds including Thymol, Borneol, Andrographolide, and Forskolin againstN. fowleri. Thymol showed the highest amoebicidal activity with IC50/24 h at 153.601 ± 19.6 μM. Two combinations of compounds Forskolin + Thymol and Forskolin + Borneol showed a higher effect on the viability of trophozoites as compared to compounds alone and hence showed a synergistic effect. The IC50 reported for Forskolin + Thymol was 81.30 ± 6.86 μM. Borneol showed maximum cysticidal activity with IC50/24 h at 192.605 ± 3.01 μM. Importantly, lactate dehydrogenase release testing revealed that all compounds displayed minimal cytotoxicity to human HaCaT, HeLa, and SH-SY5Y cell lines. The cytopathogenicity assay showed that Thymol and Borneol also significantly reduced the host cell cytotoxicity of pretreated amoeba toward the human HaCaT cell line. So, these terpene compounds hold potential as therapeutic agents against infections caused by N. fowleri and are potentially a step forward in drug development against this deadly pathogen as these compounds have also been reported to cross the blood-brain barrier. Therefore, an in vivo study using animal models is necessary to assess the efficacy of these compounds and the need for further research into the intranasal route of delivery for the treatment of these life-threatening infections.

Malabaricones from the fruit of Myristica cinnamomea King as potential agents against Acanthamoeba castellanii

Acanthamoeba castellanii is an opportunistic free-living amoeba (FLA) pathogen which can cause fatal central nervous system (CNS) infection, granulomatous amoebic encephalitis (GAE) and potentially blinding ocular infection, Acanthamoeba keratitis (AK). Acanthamoeba species remain a challenging protist to treat due to the unavailability of safe and effective therapeutic drugs and their ability to protect themselves in the cyst stage. Natural products and their secondary metabolites play a pivotal role in drug discovery against various pathogenic microorganisms. In the present study, the ethyl acetate extract of Myristica cinnamomea King fruit was evaluated against A. castellanii (ATCC 50492), showing an IC50 of 45.102 ± 4.62 µg/mL. Previously, the bio-guided fractionation of the extract resulted in the identification of three active compounds, namely Malabaricones (A-C). The isolated and thoroughly characterized acylphenols were evaluated for their anti-amoebic activity against A. castellanii for the first time. Among tested compounds, Malabaricone B (IC50 of 101.31 ± 17.41 µM) and Malabaricone C (IC50 of 49.95 ± 6.33 µM) showed potent anti-amoebic activity against A. castellanii trophozoites and reduced their viability up-to 75 and 80 %, respectively. Moreover, both extract and Malabaricones also significantly (p < 0.05) inhibit the encystation and excystation of A. castellanii, while showed minimal toxicity against human keratinocyte cells (HaCaT cells) at lower tested concentrations. Following that, the explanation of the possible mechanism of action of purified compounds were assessed by detection of the state of chromatin. Hoechst/PI 33342 double staining showed that necrotic cell death occurred in A. castellanii trophozoites after 8 h treatment of Malabaricones (A-C). These findings demonstrate that Malabaricones B and C could serve as promising therapeutic options against A. castellanii infections.

Predictors of mortality in periprosthetic fractures of the hip: Results from the national PPF study

INTRODUCTION

Periprosthetic fractures (PPFs) around the hip joint are increasing in prevalence. In this collaborative study, we aimed to investigate the impact of patient demographics, fracture characteristics, and modes of management on in-hospital mortality of PPFs involving the hip.

METHODS

Using a multi-centre cohort study design, we retrospectively identified adults presenting with a PPF around the hip over a 10-year period. Univariate and multivariable logistic regression analyses were performed to study the independent correlation between patient, fracture, and treatment factors on mortality.

RESULTS

A total of 1,109 patients were included. The in-hospital mortality rate was 5.3%. Multivariable analyses suggested that age, male sex, abbreviated mental test score (AMTS), pneumonia, renal failure, history of peripheral vascular disease (PVD) and deep surgical site infection were each independently associated with mortality. Each yearly increase in age independently correlates with a 7% increase in mortality (OR 1.07, p=0.019). The odds of mortality was 2.99 times higher for patients diagnosed with pneumonia during their hospital stay [OR 2.99 (95% CI 1.07-8.37) p=0.037], and 7.25 times higher for patients that developed renal failure during their stay [OR 7.25 (95% CI 1.85-28.47) p=0.005]. Patients with history of PVD have a six-fold greater mortality risk (OR 6.06, p=0.003). Mode of treatment was not a significant predictor of mortality.

CONCLUSION

The in-hospital mortality rate of PPFs around the hip exceeds 5%. The fracture subtype and mode of management are not independent predictors of mortality, while patient factors such as age, AMTS, history of PVD, pneumonia, and renal failure can independently predict mortality. Peri-operative optimisation of modifiable risk factors such as lung and kidney function in patients with PPFs around the hip during their hospital stay is of utmost importance.

Alpha-Mangostin and its nano-conjugates induced programmed cell death in Acanthamoeba castellanii belonging to the T4 genotype

Acanthamoeba are free living amoebae that are the causative agent of keratitis and granulomatous amoebic encephalitis. Alpha-Mangostin (AMS) is a significant xanthone; that demonstrates a wide range of biological activities. Here, the anti-amoebic activity of α-Mangostin and its silver nano conjugates (AMS-AgNPs) were evaluated against pathogenic A. castellanii trophozoites and cysts in vitro. Amoebicidal assays showed that both AMS and AMS-AgNPs inhibited the viability of A. castellanii dose-dependently, with an IC50 of 88.5 ± 2.04 and 20.2 ± 2.17 μM, respectively. Both formulations inhibited A. castellanii-mediated human keratinocyte cell cytopathogenicity. Functional assays showed that both samples caused apoptosis through the mitochondrial pathway and reduced mitochondrial membrane potential and ATP production, while increasing reactive oxygen species (ROS) and nicotinamide adenine dinucleotide phosphate (NADPH) cytochrome-c reductase in the cytosol. Whole transcriptome sequencing of A. castellanii showed the expression of 826 genes, with 447 genes being up-regulated and 379 genes being down-regulated post treatment. The Kyoto Encyclopedia of Genes and Genomes analysis showed that the majority of genes were linked to apoptosis, autophagy, RAP1, AGE-RAGE and oxytocin signalling pathways. Seven genes (PTEN, H3, ARIH1, SDR16C5, PFN, glnA GLUL, and SRX1) were identified as the most significant (Log2 (FC) value 4) for molecular mode of action in vitro. Future in vivo studies with AMS and nanoconjugates are needed to realize the clinical potential of this work.

Effect of embelin on inhibition of cell growth and induction of apoptosis in Acanthamoeba castellanii

Acanthamoeba castellanii is the causative agent of fatal encephalitis and blinding keratitis. Current therapies remain a challenge, hence there is a need to search for new therapeutics. Here, we tested embelin (EMB) and silver nanoparticles doped with embelin (EMB-AgNPs) against A. castellanii. Using amoebicidal assays, the results revealed that both compounds inhibited the viability of Acanthamoeba, having an IC50 of 27.16 ± 0.63 and 13.63 ± 1.08 μM, respectively, while causing minimal cytotoxicity against HaCaT cells in vitro. The findings suggest that both samples induced apoptosis through the mitochondria-mediated pathway. Differentially expressed genes analysis showed that 652 genes were uniquely expressed in treated versus untreated cells, out of which 191 were significantly regulated in the negative control vs. conjugate. Combining the analysis, seven genes (ARIH1, RAP1, H3, SDR16C5, GST, SRX1, and PFN) were highlighted as the most significant (Log2 (FC) value ± 4) for the molecular mode of action in vitro. The KEGG analysis linked most of the genes to apoptosis, the oxidative stress signaling pathway, cytochrome P450, Rap1, and the oxytocin signaling pathways. In summary, this study provides a thorough framework for developing therapeutic agents against microbial infections using EMB and EMB-AgNPs.

Significance of CMV reactivation in non-allogeneic stem cell transplant patients with cancers: experience of single tertiary care cancer institute

CMV reactivation is rare in hematological as well as solid organ malignancies in non-allogeneic stem cell transplant settings. An increasing number of patients undergoing active treatment or follow-up and diagnosed with CMV reactivation in recent years prompted us to investigate the risk factors and outcomes of CMV reactivation or disease. This was a hospital-based retrospective study that included 174 cancer patients suspected of CMV reactivation. Among them, forty-one tested positive for CMV viremia. The risk factors for CMV reactivation included the use of steroids in 78% of patients, active cancer in 43.9%, use of a monoclonal antibody rituximab in 31.7%, a history of radiation in 26.8%, and autologous stem cell transplant in 12% of patients. The median age was 36 years, and the most common clinical feature was fever (58.5%; n = 24), followed by GI symptoms (12.1%; n = 5), respiratory symptoms (14.6%; n = 6), cytopenia (7.3%; n = 3), and visual/neurological symptoms (4.8%; n = 2). The mean CMV viral load was 37,332 copies/ml (range: 75.00-633,000.00 copies/ml). Nineteen patients received CMV treatment with an average treatment duration of 81.5 days. The median overall survival was 2 months, with 12.0% of patients alive at 5 years. CMV reactivation is associated with significant morbidity and mortality. We recommend vigilant monitoring of CMV-related symptoms, with a low threshold for testing and treatment, for patients with multiple risk factors for CMV reactivation.

Safety and Efficacy of Zavegepant in Treating Migraine: A Systematic Review

Drugs that act on the calcitonin gene-related peptide (CGRP) pathway herald the dawn of a new era in the management of migraine headaches. The blockade of CGRP alleviates neural inflammation and has been associated with reduced pain sensitization. Zavegepant is a third-generation drug and is the first intranasal CGRP antagonist to be developed. This systematic review aims to assess the safety, efficacy, pharmacokinetics, and tolerability of Zavegepant as an abortive treatment for migraine. Studies that assessed the safety, tolerability, and efficacy of Zavegepant for migraine were identified through a systematic literature review of PubMed, Clinicaltrials.gov, and Cochrane databases in April 2023. Our systematic review yielded a total of six studies that fit our inclusion criteria. Of these, data from only two randomized control trials (RCTs) was homogenous; hence, forest plots of results pooled from the included studies were not reported. The included studies showed that Zavegepant is an efficacious and well-tolerated abortive treatment modality for episodic migraine in adult patients. Zavegepant showed safety and efficacy in migraine treatment according to various parameters throughout the six included studies. These parameters include adverse events, pharmacokinetic properties, CGRP inhibition, effect on blood pressure/electrocardiogram, pain freedom, and freedom from most bothersome symptoms.

The relationship between exposure to noise and hearing loss in orthopaedics

Aims

In the UK, the agricultural, military, and construction sectors have stringent rules about the use of hearing protection due to the risk of noise-induced hearing loss. Orthopaedic staff may also be at risk due to the use of power tools. The UK Health and Safety Executive (HSE) have clear standards as to what are deemed acceptable occupational levels of noise on A-weighted and C-weighted scales. The aims of this review were to assess the current evidence on the testing of exposure to noise in orthopaedic operating theatres to see if it exceeds these regulations.

Methods

A search of PubMed and EMBASE databases was conducted using PRISMA guidelines. The review was registered prospectively in PROSPERO. Studies which assessed the exposure to noise for orthopaedic staff in operating theatres were included. Data about the exposure to noise were extracted from these studies and compared with the A-weighted and C-weighted acceptable levels described in the HSE regulations.

Results

A total of 15 studies were deemed eligible. These included a total of 386 orthopaedic operations and the use of 64 orthopaedic instruments. A total of 294 operations (76%) and 45 instruments (70%) exceeded the regulations on an A-weighted scale, and 22% (10 of 46) of operations exceeded the maximum C-weighted peak acceptable level of noise. Noise-induced hearing loss was reported in 28 of 55 orthopaedic staff members (50.9%).

Conclusion

Safe levels of noise can be exceeded in orthopaedic operations, and when using orthopaedic instruments. Employers have clear policies about exposure to noise in the workplace but have yet to identify orthopaedic theatres as a potential at-risk area. Orthopaedic staff need education, monitoring, and protection, while employers should consider regular assessments of staff in orthopaedic theatres and offer methods to prevent noise-induced hearing loss.

Towards Early Diagnosis and Intervention: An Ensemble Voting Model for Precise Vital Sign Prediction in Respiratory Disease

Worldwide, cardiovascular and chronic respiratory diseases account for approximately 19 million deaths annually. Evidence indicates that the ongoing COVID-19 pandemic directly contributes to increased blood pressure, cholesterol, as well as blood glucose levels. Timely screening of critical physiological vital signs benefits both healthcare providers and individuals by detecting potential health issues. This study aims to implement a machine learning-based prediction and classification system to forecast vital signs associated with cardiovascular and chronic respiratory diseases. The system predicts patients' health status and notifies caregivers and medical professionals when necessary. Utilizing real-world data, a linear regression model inspired by the Facebook Prophet model was developed to predict vital signs for the upcoming 180 seconds. With 180 seconds of lead time, caregivers can potentially save patients' lives through early diagnosis of their health conditions. For this purpose, a Naïve Bayes classification model, a Support Vector Machine model, a Random Forest model, and genetic programming-based hyper tunning were employed. The proposed model outdoes previous attempts at vital sign prediction. Compared with alternative methods, the Facebook Prophet model has the best mean square in predicting vital signs. A hyperparameter-tuning is utilized to refine the model, yielding improved short- and long-term outcomes for each and every vital sign. Furthermore, the F-measure for the proposed classification model is 0.98 with an increase of 0.21. The incorporation of additional elements, such as momentum indicators, could increase the model's flexibility with calibration. The findings of this study demonstrate that the proposed model is more accurate in predicting vital signs and trends.

The rise in trauma & orthopaedic trainee-led research and audit collaborative projects in the United Kingdom since the start of the COVID-19 pandemic

Background and Objective

A significant increase has been observed globally in multi-centre trainee-led trauma & orthopaedic (T&O) research collaborative projects with more emphasis have been on tackling important research questions since the start of the COCID-19 pandemic. The objective of our analysis was to determine the number of trainee-led research collaborative projects in T&O in the United Kingdom that were started during the COVID-19 pandemic.

Methods

A retrospective analysis was conducted to determine how many trainee-led national collaborative projects in T&O were conducted since the start of the COVID-19 pandemic lockdown (March 2020 to June 2021) and the number of projects identified were compared to the previous year (2019). Any regional collaborative projects, projects that were started before the onset of COVID and projects of other surgical specialities were not included in the study.

Results

There were no projects identified in 2019 while in the Covid pandemic lockdown we identified 10 trainee-led collaborative trauma & orthopaedic projects with six of them being published with level of evidence from three to four.

Conclusion

Covid was unprecedented and has placed considerable trials across healthcare. Our study highlights an increase in multi-centre trainee-led collaborative projects within the UK and it underlines the feasibility of such projects especially with the advent of social media and Redcap® which facilitate recruitment of new studies and data.

Open Latarjet with Metal-Free Cerclage Fixation

Despite multiple modifications, the Latarjet is still the most popular procedure for recurrent anterior shoulder instability with glenoid bone loss. Partial or subtotal resorption of the graft is common, potentially leading to hardware prominence and risk of anterior soft-tissue impingement. To minimize the technical difficulties and morbidity associated with metallic implants, a coracoid and conjoint tendon transfer with a mini-open approach using Cerclage tape suture is described, as an alternative for the Latarjet procedure typically performed with metal screws and plates.

Multivariate time-series sensor vital sign forecasting of cardiovascular and chronic respiratory diseases

Approximately 19 million people die each year from cardiovascular and chronic respiratory diseases. As a result of the recent Covid-19 epidemic, blood pressure, cholesterol, and blood sugar levels have risen. Not only do healthcare institutions benefit from studying physiological vital signs, but individuals also benefit from being alerted to health problems in a timely manner. This study uses machine learning to categorize and predict cardiovascular and chronic respiratory diseases. By predicting a patient's health status, caregivers and medical professionals can be alerted when needed. We predicted vital signs for 180 seconds using real-world vital sign data. A person's life can be saved if caregivers react quickly and anticipate emergencies. The tree-based pipeline optimization method (TPOT) is used instead of manually adjusting machine learning classifiers. This paper focuses on optimizing classification accuracy by combining feature pre-processors and machine learning models with TPOT genetic programming making use of linear and Prophet models to predict important indicators. The TPOT tuning parameter combines predicted values with classical classification models such as Naïve Bayes, Support Vector Machines, and Random Forests. As a result of this study, we show the importance of categorizing and increasing the accuracy of predictions. The proposed model achieves its adaptive behavior by conceptually incorporating different machine learning classifiers. We compare the proposed model with several state-of-the-art algorithms using a large amount of training data. Test results at the University of Queensland using 32 patient's data showed that the proposed model outperformed existing algorithms, improving the classification of cardiovascular disease from 0.58 to 0.71 and chronic respiratory disease from 0.49 to 0.70, respectively, while minimizing the mean percent error in vital signs. Our results suggest that the Facebook Prophet prediction model in conjunction with the TPOT classification model can correctly diagnose a patient's health status based on abnormal vital signs and enables patients to receive prompt medical attention.

Anti-amoebic effects of synthetic acridine-9(10H)-one against brain-eating amoebae

Pathogenic A. castellanii and N. fowleri are opportunistic free-living amoebae. Acanthamoeba spp. are the causative agents of granulomatous amebic encephalitis (GAE) and amebic keratitis (AK), whereas Naegleria fowleri causes a very rare but severe brain infection called primary amebic meningoencephalitis (PAM). Acridinone is an important heterocyclic scaffold and both synthetic and naturally occurring derivatives have shown various valuable biological properties. In the present study, ten synthetic Acridinone derivatives (I-X) were synthesized and assessed against both amoebae for anti-amoebic and cysticidal activities in vitro. In addition, excystation, encystation, cytotoxicity, host cell pathogenicity was also performed in-vitro. Furthermore, molecular docking studies of these compounds with three cathepsin B paralogous enzymes of N. fowleri were performed in order to predict the possible docking mode with pathogen. Compound VII showed potent anti-amoebic activity against A. castellanii with IC₅₀ 53.46 µg/mL, while compound IX showed strong activity against N. fowleri in vitro with IC₅₀ 72.41 µg/mL. Compounds II and VII showed a significant inhibition of phenotypic alteration of A. castellanii, while compound VIII significantly inhibited N. fowleri cysts. Cytotoxicity assessment showed that these compounds caused minimum damage to human keratinocyte cells (HaCaT cells) at 100 µg/mL, while also effectively reduced the cytopathogenicity of Acanthamoeba to HaCaT cells. Moreover, Cathepsin B protease was investigated in-silico as a new molecular therapeutic target for these compounds. All compounds showed potential interactions with the catalytic residues. These results showed that acridine-9(10H)-one derivatives, in particular compounds II, VII, VIII and IX hold promise in the development of therapeutic agents against these free-living amoebae.

Emotional Intelligence Attention Unsupervised Learning Using Lexicon Analysis for Irony Based Advertising

Social media platforms have made increasing use of irony in recent years. Users can express their ironic thoughts with audio, video, and images attached to text content. When you use irony, you are making fun of a situation or trying to make a point. It can also express frustration or highlight the absurdity of a situation. The use of irony in social media is likely to continue to increase, no matter the reason. By using syntactic information in conjunction with semantic exploration, we show that attention networks can be enhanced. Using learned embedding, unsupervised learning encodes word order into a joint space. By evaluating the entropy of an example class and adding instances, the active learning method uses the shared representation as a query to retrieve semantically similar sentences from a knowledge base. In this way, the algorithm can identify the instance with the maximum uncertainty and extract the most informative example from the training set. An ironic network trained for each labelled record is used to train a classifier (model). The partial training model and the original labelled data generate pseudo-labels for the unlabeled data. To correctly predict the label of a dataset, a classifier (attention network) updates the pseudo-labels for the remaining datasets. After the experimental evaluation of the 1,021 annotated texts, the proposed model performed better than the baseline models, achieving an F1 score of 0.63 on ironic tasks and 0.59 on non-ironic tasks. We also found that the proposed model generalized well to new instances of datasets.

Cell surface GRP78 regulates TGFβ1-mediated profibrotic responses via TSP1 in diabetic kidney disease

Introduction: Diabetic kidney disease (DKD) is the leading cause of kidney failure in North America, characterized by glomerular accumulation of extracellular matrix (ECM) proteins. High glucose (HG) induction of glomerular mesangial cell (MC) profibrotic responses plays a central role in its pathogenesis. We previously showed that the endoplasmic reticulum resident GRP78 translocates to the cell surface in response to HG, where it mediates Akt activation and downstream profibrotic responses in MC. Transforming growth factor β1 (TGFβ1) is recognized as a central mediator of HG-induced profibrotic responses, but whether its activation is regulated by cell surface GRP78 (csGRP78) is unknown. TGFβ1 is stored in the ECM in a latent form, requiring release for biological activity. The matrix glycoprotein thrombospondin 1 (TSP1), known to be increased in DKD and by HG in MC, is an important factor in TGFβ1 activation. Here we determined whether csGRP78 regulates TSP1 expression and thereby TGFβ1 activation by HG. Methods: Primary mouse MC were used. TSP1 and TGFβ1 were assessed using standard molecular biology techniques. Inhibitors of csGRP78 were: 1) vaspin, 2) the C-terminal targeting antibody C38, 3) siRNA downregulation of its transport co-chaperone MTJ-1 to prevent GRP78 translocation to the cell surface, and 4) prevention of csGRP78 activation by its ligand, active α2-macroglobulin (α2M*), with the neutralizing antibody Fα2M or an inhibitory peptide. Results: TSP1 transcript and promoter activity were increased by HG, as were cellular and ECM TSP1, and these required PI3K/Akt activity. Inhibition of csGRP78 prevented HG-induced TSP1 upregulation and deposition into the ECM. The HG-induced increase in active TGFβ1 in the medium was also inhibited, which was associated with reduced intracellular Smad3 activation and signaling. Overexpression of csGRP78 increased TSP-1, and this was further augmented in HG. Discussion: These data support an important role for csGRP78 in regulating HG-induced TSP1 transcriptional induction via PI3K/Akt signaling. Functionally, this enables TGFβ1 activation in response to HG, with consequent increase in ECM proteins. Means of inhibiting csGRP78 signaling represent a novel approach to preventing fibrosis in DKD.

Presentation, management, and outcomes of cauda equina syndrome up to one year after surgery, using clinician and participant reporting: A multi-centre prospective cohort study

Background

Cauda equina syndrome (CES) results from nerve root compression in the lumbosacral spine, usually due to a prolapsed intervertebral disc. Evidence for management of CES is limited by its infrequent occurrence and lack of standardised clinical definitions and outcome measures.

Methods

This is a prospective multi-centre observational cohort study of adults with CES in the UK. We assessed presentation, investigation, management, and all Core Outcome Set domains up to one year post-operatively using clinician and participant reporting. Univariable and multivariable associations with the Oswestry Disability Index (ODI) and urinary outcomes were investigated.

Findings

In 621 participants with CES, catheterisation for urinary retention was required pre-operatively in 31% (191/615). At discharge, only 13% (78/616) required a catheter. Median time to surgery from symptom onset was 3 days (IQR:1–8) with 32% (175/545) undergoing surgery within 48 h. Earlier surgery was associated with catheterisation (OR:2.2, 95%CI:1.5–3.3) but not with admission ODI or radiological compression. In multivariable analyses catheter requirement at discharge was associated with pre-operative catheterisation (OR:10.6, 95%CI:5.8–20.4) and one-year ODI was associated with presentation ODI (r = 0.3, 95%CI:0.2–0.4), but neither outcome was associated with time to surgery or radiological compression. Additional healthcare services were required by 65% (320/490) during one year follow up.

Interpretation

Post-operative functional improvement occurred even in those presenting with urinary retention. There was no association between outcomes and time to surgery in this observational study. Significant healthcare needs remained post-operatively.

Funding

DCN Endowment Fund funded study administration. Castor EDC provided database use. No other study funding was received.

Automatically Temporal Labeled Data Generation Using Positional Lexicon Expansion for Focus Time Estimation of News Articles

Many facts change over time, which is a fundamental aspect of our physical environment. In the case of pandemic articles, the user is not interested in the creation date of the document, but in the facts and the cause of the last pandemic. Fake news can be better combated by having a document with a temporal focus. Currently, neither the sequence of events nor the temporal focus is considered when obtaining news documents. Despite the limited number of temporal aspects in the available datasets, it is difficult to test and evaluate the temporal conclusions of the model. The goal of this work is to develop a temporal focus news article retrieval model based on co-training to advance research in semi-supervised learning. A mapping of the dataset is performed using 1) the evolving focus time of news articles, 2) the semi-supervised method based on coincidence contexts for learning low-dimensional continuous vectors for learning neural contrast embedding models generating focus time-based query in sequential news articles to facilitate temporal understanding by learning low-dimensional continuous vectors. A diverse dataset of news articles is used to evaluate the effectiveness of the proposed method. With semi-supervised learning and lexicon expansion, the result of the developed model can achieve 89%. The method performed better than previous baselines and traditional machine learning models with improvements of 12.65% and 4.7%, respectively.

Focused ultrasound stimulation of the inflammatory reflex at the spleen ameliorates pulmonary arterial hypertension in rodents

Background

Inflammation is a major contributor in pulmonary arterial hypertension (PAH) pathogenesis. Non-invasive, focused ultrasound stimulation (FUS) of the spleen activates the neuroimmune inflammatory reflex (IR) and suppresses systemic inflammation [1].

Purpose

We aimed to explore whether daily FUS of the spleen improves haemodynamics and biomarkers by modulating the IR, in a rat model of PAH.

Methods

Sprague-Dawley rats (n=12) were injected s.c. with Sugen5416 (VEGF receptor inhibitor) and then, were placed in a hypoxic chamber (FiO2=10%) for 21 days, followed by 14 days of re-exposure to normoxia (FiO2=10%). At day 21, rats were randomized to either FUS (n=6) or sham-stimulation of the spleen (n=6). Each FUS- or sham-stimulation session consisted of 12 minutes. After 14 days of treatment, in a terminal experiment, right ventricular systolic pressure (RVSP) and arterial pressure were measured invasively, as well as biomarkers, in each animal (Figure 1A).

Results

FUS significantly reduced RVSP compared with the sham-stimulation (Mean±SEM, 50.83±3.57 mmHg vs 72.50±5.81; p=0.009), resulting in a 30% relative reduction (Figure 1B). Mean systemic arterial pressure was similar in the 2 groups (Mean±SEM, 79.83±3.73 mmHg vs. 87.00±2.95; p=0.137) (Figure 1C), as was the change in heart rate between day 1 and day 14 of treatment period (−19.53±5.36% vs. −16.79±3.1, p=0.61) (Figure 1D). Consistently, plasma brain natriuretic peptide (BNP) levels are reduced in the FUS group (119.45±19.93 ng/μl vs. 319.39±91.85; p=0.019), indicative of reduced myocardial wall stress in the FUS group (Figure 1E).

Conclusion

Non-invasive FUS of the spleen reduced RVSP by ∼30% and BNP without significantly affecting systemic pressure or heart rate, in rats with severe PAH. Non-invasive FUS, by modulating the IR, may exert an anti-inflammatory effect in PAH. FUS of the spleen is noninvasive, safe, widely available and easy to perform, and should be further explored as a possible therapeutic option in PAH.

Funding Acknowledgement

Type of funding sources: Private hospital(s). Main funding source(s): Northwell Health

Multi-Aspect Deep Active Attention Network for Healthcare Explainable Adoption

Depression is a serious illness that significantly affects the lives of those affected. Recent studies have looked at the possibility of detecting and diagnosing this mental disorder using user-generated data from various forms of online media. Therefore, we addressed the issue of detecting sadness in social media by focusing on terms in personal remarks. To overcome the limitations in classifying depression texts, this study aims to develop attention networks that use covert levels of self-attention. Since nodes/words can express the properties/emotions of their neighbors, this paper naturally assigns each node in a neighborhood its weight without performing costly matrix operations such as similarity or network architecture knowledge. The paper extended the emotion lexicon by using hypernyms. For this reason, our method is superior to the performance of the other designs. According to the results of our experiments, the emotion lexicon combined with an attention network achieves a ROC of 0.87 while maintaining its interpretability and transparency level. Subsequently, the learned embedding is used to display the contribution of each symptom to the activated word, and the psychiatrist is polled to obtain his qualitative agreement with this representation. By using unlabeled forum language, the method increases the rate at which depression symptoms can be identified from information in Internet forums.

Explainable Deep Attention Active Learning for Sentimental Analytics of Mental Disorder

With the increasing use of online mediums, Internet-delivered psychological treatments (IDPs) are becoming an essential tool for improving mental disorders. Online-based health therapies can help a large segment of the population with little resource investment. The task is greatly complicated by the overlapping emotions for specific mental health. Early adoption of a deep learning system presented severe difficulties, including ethical and legal considerations that contributed to a lack of trust. Modern models required highly interpretable, intuitive explanations that humans could understand. To achieve this, we present a deep attention model based on fuzzy classification that uses the linguistic features of patient texts to build emotional lexicons. In medical applications, a diversified dataset generates work. Active learning techniques are used to extend fuzzy rules and the learned dataset gradually. From this, the model can gain a reduction in labeling efforts in mental health applications. In this way, difficulties such as the amount of vocabulary per class, method of generation, the source of data, and the baseline for human performance level can be solved. Moreover, this work illustrates fuzzy explainability by using weighted terms. The proposed method incorporates a subset of unstructured data into the set for training and uses a similarity-based approach. The approach then updates the model training using the new training points in the subsequent cycle of the active learning mechanism. The cycle is repeated until the optimal solution is found. At this point, all unlabeled text is converted into the set for training. The experimental results show that the emotion-based enhancement improves test accuracy and helps develop quality criteria. In the blind test, the bidirectional LSTM architecture with an attention mechanism and fuzzy classification achieved an F1 score of 0.89.

How much does a Medical and Healthcare Products Regulatory Agency medical device alert for metal-on-metal hip arthroplasty patients really cost?

BACKGROUND

Many worldwide regulatory authorities recommend regular surveillance of metal-on-metal hip arthroplasty patients given high failure rates. However, concerns have been raised about whether such regular surveillance, which includes asymptomatic patients, is evidence-based and cost-effective. We determined: (1) the cost of implementing the 2015 MHRA surveillance in "at-risk" Birmingham Hip Resurfacing (BHR) patients; and (2) how many asymptomatic hips with adverse reactions to metal debris (ARMD) would have been missed without patient recall.

METHODS

All BHR patients eligible for the 2015 MHRA recall (all females, and males with head sizes ⩽46 mm, regardless of symptoms) at one centre were invited for review (hips = 707; patients = 593). All patients were investigated (Oxford Hip Score, radiographs, blood metal ions, and targeted cross-sectional imaging) and managed accordingly. Surveillance costs were calculated using finance department data.

RESULTS

The surveillance cost £105,921.79 (range £147.76-£257.50/patient). Radiographs (£39,598) and nurse practitioner time/assistance (£23,618) accounted for 60% of overall costs. 31 hips had ARMD on imaging (12 revised; 19 under surveillance). All revisions were symptomatic. 7 hips with ARMD under surveillance were asymptomatic and remain under regular review. The number needed to treat to avoid missing one asymptomatic ARMD case was 101 patients, representing a cost of £18,041 to avoid one asymptomatic case.

CONCLUSIONS

Implementing MHRA surveillance for "at-risk" BHR patients was extremely costly. The risk of asymptomatic ARMD was low with the BHR (1%), suggesting recommended follow-up in asymptomatic patients is not cost efficient. This raises concerns about the increasingly intensive surveillance recommended in the 2017 MHRA guidance for metal-on-metal hip patients.

Potential anti-acanthamoebic effects through inhibition of CYP51 by novel quinazolinones

Acanthamoeba spp. are free living amoebae which can give rise to Acanthamoeba keratitis and granulomatous amoebic encephalitis. The surface of Acanthamoeba contains ergosterol which is an important target for drug development against eukaryotic microorganisms. A library of ten functionally diverse quinazolinone derivatives (Q1-Q10) were synthesised to assess their activity against Acanthamoeba castellanii T4. The in-vitro effectiveness of these quinazolinones were investigated against Acanthamoeba castellanii by amoebicidal, excystation, host cell cytopathogenicity, and NADPH-cytochrome c reductase assays. Furthermore, wound healing capability was assessed at different time durations. Maximum inhibition at 50 μg/mL was recorded for compounds Q5, Q6 and Q8, while the compound Q3 did not exhibit amoebicidal effects at tested concentrations. Moreover, LDH assay was conducted to assess the cytotoxicity of quinazolinones against HaCaT cell line. The results of wound healing assay revealed that all compounds are not cytotoxic and are likely to promote wound healing at 10 μg/mL. The excystation assays revealed that these compounds significantly inhibit the morphological transformation of A. castellanii. Compound Q3, Q7 and Q8 elevated the level of NADPH-cytochrome c reductase up to five folds. Sterol 14alpha-demethylase (CYP51) a reference enzyme in ergosterol pathway was used as a potential target for anti-amoebic drugs. In this study using i-Tasser, the protein structure of Acanthamoeba castellanii (AcCYP51) was developed in comparison with Naegleria fowleri protein (NfCYP51) structure. The sequence alignment of both proteins has shown 42.72% identity. Compounds Q1-Q10 were then molecularly docked with the predicted AcCYP51. Out of ten quinazolinones, three compounds (Q3, Q7 and Q8) showed good binding activity within 3 Å of TYR 114. The in-silico study confirmed that these compounds are the inhibitor of CYP51 target site. This report presents several potential lead compounds belonging to quinazolinone derivatives for drug discovery against Acanthamoeba infections.

New synthetic phenylquinazoline derivatives induce apoptosis by targeting the pro-survival members of the BCL-2 family

Chemo-resistant cancer cells acquire robust growth potential through cell signaling mechanisms such as the down-regulation of tumor suppressors and the up-regulation of pro-survival proteins, respectively. To overcome chemo-resistance of cancer, small molecule drugs that interact with the cell signaling proteins to enhance sensitization of cancer cells toward cancer therapies are likely to be effective for the treatment of chemo-drug resistant cancer. To identify high potency small molecules, a series of ten novel phenylquinazoline derivatives were synthesized to determine their cellular effects in MCF-7 and MCF-7- cisplatin-resistant (CR) human breast cancer cells which led to the identification of two bioactive compounds, SMS-IV-20 and SMS-IV-40, that exhibited an elevated level of cytotoxicity against the human breast cancer cells and spheroid cells. In addition, both compounds enhanced chemo-sensitization of the human breast cancer cells that were genetically engineered to express the tumor suppressor and pro-apoptotic proteins, MOAP-1, Bax, and RASSF1a (MBR), suggesting that the compounds interact with the MBR signaling pathway. Furthermore, when MCF-7-CR cells were treated with SMS-IV-20 and SMS-IV-40 in the presence of ABT-737, a BCL-XL and BCL-2 inhibitor, enhanced chemo-sensitization was observed, suggesting SMS-IV-20 and SMS-IV-40 exert antagonistic activity to regulate the functional activity of BCL-2 and BCL-XL. Western blot analysis showed that both SMS-IV-20 and SMS-IV-40 induced down-regulation of BCL-2 or both BCl-2 and BCL-XL expression, respectively while promoting the release of mitochondrial Cytochrome C. Taken together, the data showed that SMS-IV-20 and SMS-IV-40 are potent activators of apoptosis that enhance chemo-sensitization through their antagonistic actions on the pro-survival activity of the BCl-2 family in human cancer cells.

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

With the improvement of global infrastructure, Cyber-Physical Systems (CPS) have become an important component of Industry 4.0. Both the application as well as the machine work together to improve the task of interdependencies. Machine learning methods in CPS require the monitoring of computational algorithms, including adopting optimizations, fine-tuning cyber systems, improving resource utilization, as well as reducing vulnerability as well as computation time. By leveraging the tremendous parallelism provided by General-Purpose Graphics Processing Units (GPGPU) as well as OpenCL, it is possible to dramatically reduce the execution time of data-parallel programs. However, when running an application with tiny amounts of data on a GPU, GPU resources are wasted because the program may not be able to fully utilize the GPU cores. This is because there is no mechanism for kernels to share a GPU due to the lack of OS support for GPUs. Optimal device selection is required to reduce the high power of the GPU. In this paper, we propose an energy reduction method for heterogeneous clustering. This study focuses on load balancing; resource-aware processor selection based on machine learning is performed using code features. The proposed method identifies energy-efficient kernel candidates (from the employment pool). Then, it selects a pair of kernel candidates from all possibilities that lead to a reduction in both energy consumption as well as execution time. Experimental results show that the proposed kernel approach reduces execution time by 2.23 times compared to a baseline scheduling system. Experiments have also shown that the execution time is 1.2 times faster than state-of-the-art approaches.

Hyper-Graph Attention Based Federated Learning Method For Mental Health Detection

Internet-Delivered Psychological Treatment (IDPT) has become necessary in the medical field. Deep neural networks (DNNs) require large, diverse patient populations to train models that achieve clinician-level performance. However, DNN models trained on limited datasets have poor clinical performance when used in a new location with different data. Thus, increasing the availability of diverse as well as distinct training data is vital. This study proposes a structural hypergraph as well as an emotional lexicon for word representation. An embedding model based on federated learning was developed for mental health symptom detection. The model treats text data as a collection of consecutive words. The model then learns a low-dimensional continuous vector while maintaining contextual linkage. The generated models with attention-based mechanisms as well as federated learning are then tested experimentally. Our strategy is suitable for vocabulary diversification, grammatical word representation, as well as dynamic lexicon analysis. The goal is to create semantic word representations using an attention network model. Later, clinical processes are used to mark the text by embedding it. Experimental results show the encoding of emotional words using the structural hypergraph. The 0.86 ROC was achieved using the bidirectional LSTM architecture with an attention mechanism.

Deep active reinforcement learning for privacy preserve data mining in 5G environments

Frequent pattern mining (FIM) identifies the most important patterns in data sets. However, due to the huge and high-dimensional nature of transactional data, classical pattern mining techniques suffer from the limitations of dimensions and data annotations. Recently, data mining while preserving privacy is considered as an important research area. Information privacy is a tradeoff that must be considered when using data. Through many years, privacy-preserving data mining (PPDM) made use of methods that are mostly based on heuristics. The operation of deletion was used to hide the sensitive information in PPDM. In this study, we used deep active learning to protect private and sensitive information. This paper combines entropy-based active learning with an attention-based approach to effectively hide sensitive patterns. The constructed models are then validated using high-dimensional transactional data with attention-based and active learning methods in a reinforcement environment. The results show that the proposed model can support and improve the effectiveness of decision-making by increasing the number of training instances through the use of a pooling technique and an entropy uncertainty measure. The proposed paradigm can achieve data sanitization by the hiding sensitive items and avoiding to hide the non-sensitive items. The model outperforms greedy, genetic, and particle swarm optimization approaches.

Ensemble-based deep meta learning for medical image segmentation

Deep learning methods have led to the state-of-the-art medical applications, such as image classification and segmentation. The data-driven deep learning application can help stakeholders for further collaboration. However, limited labeled data set limits the deep learning algorithms to be generalized for one domain into another. To handle the problem, meta-learning helps to solve this issue especially it can learn from a small set of data. We proposed a meta-learning-based image segmentation model that combines the learning of the state-of-the-art models and then used it to achieve domain adoption and high accuracy. Also, we proposed a prepossessing algorithm to increase the usability of the segment part and remove noise from the new test images. The proposed model can achieve 0.94 precision and 0.92 recall. The ability is to increase 3.3% among the state-of-the-art algorithms.

17 Establishment of Virtual Fracture Clinic in Princess Royal Hospital Telford: Experience and Recommendations During the First 9 Months

Introduction

Virtual fracture clinics (VFC) have been shown to be a safe and cost-effective way of managing outpatient referrals to the orthopaedic department. During the coronavirus pandemic there has been a push to reduce unnecessary patient contact whilst maintaining patient safety.

Method

A protocol was developed by the clinical team on how to manage common musculoskeletal presentations to A&E prior to COVID as part of routine service development. Patients broadly triaged into 4 categories; discharge with advice, referral to VFC, referral to face to face clinic or discussion with on call team. The first 9 months of data were analysed to assess types of injury seen and outcomes.

Results

In total 2489 patients were referred to VFC from internal and external sources. 734 patients were discharged without follow-up and 182 patients were discharged for physiotherapy review. Only 3 patients required admission. Regarding follow-ups, 431 patients had a virtual follow-up while 1036 of patients required further face to face follow up. 87 patients were triaged into subspecialty clinics. 37 patients were felt to have been referred inappropriately.

Conclusions

BOA guidelines state all patients must be reviewed within 72 hours of their orthopaedic injury. Implementation of a VFC allows this target to be achieved and at the same time reduce patient contact. Almost half the patients were discharged following VFC review, the remaining patients were followed up. This is especially relevant in the current pandemic where reducing unnecessary trips to hospital will benefit the patient and make the most of the resources available.

18 The Rise in Trauma & Orthopaedic Trainee-Led Research and Audit Collaborative Projects in the United Kingdom Since the Start of the COVID-19 Pandemic

Introduction

There has been a significant rise in trainee-led trauma & orthopaedic (T&O) multi-centre research collaborative projects globally. Since the start of the COVID-19 pandemic, more emphasis has been on global collaborative research efforts to tackle important research questions. The aim was to evaluate the number of T&O trainee-led research collaborative projects that took part since the start of the COVID-19 pandemic in the UK.

Method

A retrospective study that evaluated T&O trainee-led national collaborative projects within the UK since the start of the COVID-19 pandemic lockdown (March 2020 to June 2021). Our exclusion criteria included any regional collaborative projects, projects that were started pre-COVID and projects of other surgical specialities. The number of projects identified was compared to that in 2019.

Results

In 2019, 0 trainee-led collaborative projects were commenced nationally in the UK. Since the COVID-19 pandemic, we identified 10 trainee-led collaborative trauma & orthopaedic projects with 3 being published so far. The level of evidence ranged between 3 and 4.

Conclusions

Covid has placed significant challenges across healthcare. One positive aspect that has been noted is the increase in multi-centre trainee-led collaborative projects within the UK. Our study highlights the feasibility of a trainee-led high quality collaborative research projects in the UK, emphasising the growing contribution of trainees towards research. Wide-spread availability of new technological tools such as social media and Redcap® facilitates such projects in terms of recruitment and data collection. We would, therefore, recommend expanding this trainee-led collaborative platform across in Europe and Worldwide.

Fuzzy Contrast Set Based Deep Attention Network for Lexical Analysis and Mental Health Treatment

Internet-Delivered Psychological Treatments (IDPT) consider the mental problems based on Internet interaction. As the increases of the pandemic, more online tools are then widely used to result in evidence-based mental health serves. This increase helps to cover more population by using fewer resources for mental health treatments. Adaptivity and customization for the remedy routine can help to solve mental health issues speedily. In this research, we propose a fuzzy contrast-based model that uses the attention network for positional weighted words, classifies mental patient authored text into distinct symptoms. After that, the trained embedding is then used to label the mental data. Then attention network expands its lexicons to adapt to the usage of transfer learning techniques. The proposed model uses similarity and contrast sets to classify the weighted attention words. The fuzzy model then uses the sets to classify the mental health data into distinct classes. The method is compared with non-embedding and traditional techniques to demonstrate the proposed model. From the experiments, the feature vector can achieve a high ROC-Curve of 0.82 with nine symptoms problems.

Potent antibacterial activity of MXene–functionalized graphene nanocomposites

(A) SEM and (B) HRTEM images of 75% F graphene:25% Ti3C2Tx nanocomposite.

A Machine-Learning-Based System for Prediction of Cardiovascular and Chronic Respiratory Diseases

Cardiovascular and chronic respiratory diseases are global threats to public health and cause approximately 19 million deaths worldwide annually. This high mortality rate can be reduced with the use of technological advancements in medical science that can facilitate continuous monitoring of physiological parameters-blood pressure, cholesterol levels, blood glucose, etc. The futuristic values of these critical physiological or vital sign parameters not only enable in-time assistance from medical experts and caregivers but also help patients manage their health status by receiving relevant regular alerts/advice from healthcare practitioners. In this study, we propose a machine-learning-based prediction and classification system to determine futuristic values of related vital signs for both cardiovascular and chronic respiratory diseases. Based on the prediction of futuristic values, the proposed system can classify patients' health status to alarm the caregivers and medical experts. In this machine-learning-based prediction and classification model, we have used a real vital sign dataset. To predict the next 1-3 minutes of vital sign values, several regression techniques (i.e., linear regression and polynomial regression of degrees 2, 3, and 4) have been tested. For caregivers, a 60-second prediction and to facilitate emergency medical assistance, a 3-minute prediction of vital signs is used. Based on the predicted vital signs values, the patient's overall health is assessed using three machine learning classifiers, i.e., Support Vector Machine (SVM), Naive Bayes, and Decision Tree. Our results show that the Decision Tree can correctly classify a patient's health status based on abnormal vital sign values and is helpful in timely medical care to the patients.

TP8.2.7 The Post Graduate Virtual Learning Environment: an effective platform for the delivery of a surgical teaching programme in the West Midlands

Aim

The Postgraduate Virtual Learning Environment (PGVLE) is a digital platform developed by HEEWM in response to the COVID-19 pandemic to deliver a virtual teaching programme to surgical trainees. The programme is delivered through the BigBlueButton; an integrated virtual classroom. All teaching sessions are recorded and archived to allow trainees to review content at their convenience. We performed a contemporaneous study to review the effectiveness and quality of the platform in delivering teaching and suggest its future role in the surgical curriculum.

Method

Anonymised feedback was gathered of trainee’s perspective of the platform experience, the quality of teaching and the archived content. All trainees were General Surgery higher trainees (HST) (ST3-ST8). The data from sequential teaching days was analysed.

Results

Of 90 HST, on average 40 attended each monthly training day (consistent with pre-COVID attendance). 122 trainee responses were completed. 68% of respondents were between ST3-ST5. 91% rated the administration and delivery of the teaching sessions as excellent or very good. 16% of trainees watched the archived sessions after the teaching day of which 46% felt it met their educational expectations.

Conclusions

The PGVLE is an effective platform for the delivery of a virtual surgical teaching programme. It met with high levels of trainee satisfaction in the context of the pandemic. The archived content provides advantages to consolidation of learning. It is thought that the PGVLE platform will become a key feature of the surgical training programme in a hybrid learning model, related to relevant curricula, in the future.

511 Organising A Surgical Conference During The COVID-19 Pandemic – Is It ‘Virtually’ The Same?

Introduction

Surgical conferences are invaluable events for healthcare professionals; they provide opportunities to engage with upcoming scientific discoveries, network professionally with peers as well as expand learning through lectures and workshops. For medical students, conferences provide an opportunity to expand understanding beyond the undergraduate curriculum in an interactive manner. COVID-19 has caused disruption to the organisation and attendance of in-person conferences (IPCs). Virtual conferences (VCs) offer a viable solution, allowing delegates to attend from the comfort of their own homes.

Method

The aim of our study was to evaluate an organised VC and explore the perceived benefits and limitations of VCs compared to IPCs. A virtual one-day trauma & orthopaedics (T&O) conference was organised involving lectures, workshops, poster, and oral presentations. Anonymous questionnaire forms were distributed to delegates following the conference to assess the aims of our paper.

Results

From 106 responses, 96.2% rated the conference as ‘Excellent’ or ‘Good’ with 92.5% stating that it increased their passion for T&O surgery. Based on a five-point Likert scale (5= strongly agree, 1= strongly disagree), mean score of agreement for preferring VCs to IPCs was 3.30(± 1.24). Key advantages of the VC were a lower cost (70.8%) and not having to travel (77.4%), whereas the main limitation was the inability to participate in hands-on workshops (84.9%).

Conclusions

Despite the success of our VC, delegate feedback indicates a mixed response comparing VCs to IPCs. We share our findings to encourage similar events to be organised and for other specialties.

483 A Quality Improvement Project: Novel Electronic Operative Note Templates to Improve the Continuity of Post-Operative Patient Care

Introduction

Good Surgical Practice from RCS England encourages the use of e-health records and detailed typed operative notes. The Covid-19 pandemic has led to multi-site operating. ENT operations in our trust were split over three sites including the private sector leading to potential disruption in continuity of patient care. Physical operation notes are difficult to access in emergencies, telephonic clinics or for audit purposes. We aim to have operative notes available on patients’ e-records which adhere to RCSEng guidelines.

Method

In this QIP, we reviewed all ENT operations over a retrospective one-month period recording percentage of notes uploaded to patient e-record and the number of surgeons in theatre. We created two novel RCSEng compliant e-operative notes with a user guide, generic and tonsillectomy-specific, and prospectively collected data to complete the cycle.

Results

261 patients were included in both study periods. Only 36/134(27%) had e-operative pre-intervention improving to 71/127(56%) post-intervention. In the latter period, 76% of operations included a registrar and were more likely to have e-operative notes(72%) compared to when a consultant was operating alone(6%). There was low uptake of our tonsillectomy e-proforma(33%).

Conclusions

Our QIP has already proved effective with our templates increasing operative documentation on e-records. Increased use of e-template was more likely with the presence of a registrar in theatre. Room for improvement remains and we will re-audit after the introduction of further user-friendly operative templates and IT training. This QIP has also revealed additional operative training opportunities of which registrars can take advantage.

1434 An Audit of Surgical Consent Standards in Patients Undergoing Elective ENT Surgery

Aim

Good Surgical Practice (RCS England) and GMC guidelines inform a surgeon’s practice in the consent process for an operation. Since the Covid-19 pandemic, many surgical departments have converted from face-to-face to telephonic consultations. The clinic letter is of increased importance given that it forms a key part of the medical record which the patient should receive to ensure sufficient time and information to make an informed decision.

Method

Clinic letters of patients undergoing elective ENT surgery at our trust over a four-week period were examined in this retrospective audit of compliance with RCSEng and GMC guidelines. Additional data was collected on clinician grade and proportion of letters sent to patients. Patients rated satisfaction with consultation on a five-point Likert scale.

Results

135 eligible patients were included in our audit and the majority were listed by a consultant (57%). In all domains, consultant letters were more likely to be comprehensive as compared to registrars. Overall quality of clinic letters was highly variable regarding documentation of diagnosis (52%), surgical risks (50%), discussion of alternative or no treatment (30%) and registrar discussion with consultant (31%). There was also a stark difference between registrars and consultants sending patients copies of clinic letters (10% vs 47%). Only 10% of patients received a leaflet on their condition. 90% of patients were either satisfied or very satisfied with their clinic consultation.

Conclusions

Refresher sessions on consent, updated template letters and increased provision of patient information leaflets will be introduced to the ENT department, and improvements monitored with further re-audit.

Applications of medicinal chemistry for drug discovery against Acanthamoeba infections

Acanthamoeba is a genus of free-living amoebae, pervasively found in the environment. Most of its pathogenic species are the causative agent of sight-threatening Acanthamoeba keratitis and fatal granulomatous amoebic encephalitis. Despite the advancements in the field of chemotherapy, treating Acanthamoeba infections is still challenging due to incomplete knowledge of the complicated pathophysiology. In case of infection, the treatment regimen for the patients is often ineffective due to delayed diagnosis, poor specificity, and side-effects. Besides the resistance of Acanthamoeba cysts to most of the drugs, the recurrence of infection further complicates the recovery. Thus, it is necessary to develop an effective treatment which can eradicate these rare, but serious infections. Based on various computational and in vitro studies, it has been established that the synthetic scaffolds such as heterocyclic compounds may act as potential drug leads for the development of antiamoebic drugs. In this review, we report different classes of synthetic compounds especially heterocyclic compounds which have shown promising results against Acanthamoeba. Moreover, the antiamoebic activities of synthetic compounds with their possible mode of actions against Acanthamoeba, have been summarized and discussed in this review.