A multi-patch-based deep learning model with VGG19 for breast cancer classifications in the pathology images.

Purpose: Breast cancer encompasses various subtypes with distinct prognoses, necessitating accurate stratification methods. Current techniques rely on quantifying gene expression in limited subsets. Given the complexity of breast tissues, effective detection and classification of breast cancer is crucial in medical imaging.

Challenges and opportunities of artificial intelligence in African health space.

The application of artificial intelligence (AI) to healthcare in Africa has the potential to transform productivity, diagnosis, disease surveillance, and resource allocation by improving accuracy and efficiency. However, to fully realize its benefits, it is necessary to consider issues concerning data privacy, equity, infrastructure integration, and ethical policy development. The use of these tools may improve the detection of diseases, the distribution of resources, and the continuity of care.

"Longing is good": proof-of-concept for a novel psychological intervention to tackle self-blaming emotions.

Background: Many people with depression, for which self-blame plays a key role, are not amenable to current standard psychological treatments. This calls for novel self-guided interventions, which require less attention and motivation. The present study sought to establish proof-of-concept for a novel self-guided intervention in a non-clinical sample, which prompts people to transform self-blaming feelings into "longing," as a related unpleasant, but presumably more adaptive and approach-related emotion, which plays a key role in many musical and literary genres but has been largely overlooked in clinical research.

Noise-agnostic quantum error mitigation with data augmented neural models.

Quantum error mitigation, a data processing technique for recovering the statistics of target processes from their noisy version, is a crucial task for near-term quantum technologies. Most existing methods require prior knowledge of the noise model or the noise parameters. Deep neural networks have the potential to lift this requirement, but current models require training data produced by ideal processes in the absence of noise.

Electroresponsive Thiol-Yne Click-Hydrogels for Insulin Smart Delivery: Tackling Sustained Release and Leakage Control.

Diabetes is a metabolic disorder caused by the body's inability to produce or use insulin. Considering the figures projected by the World Health Organization, research on insulin therapy is crucial. Hence, we present a soft biointerface based on a thiol-yne poly(ethylene glycol) (PEG) click-hydrogel as an advanced treatment option to administrate insulin.

Thrombolytic therapy for patients with acute ischemic stroke: systematic review and network meta-analysis of randomized trials.

Objective: To systematically compare the benefits and risks of all thrombolytic agents (tenecteplase, reteplase, and alteplase) at different doses for thrombolytic therapy in patients with acute ischemic stroke (AIS).

Background: Alteplase is the cornerstone treatment for AIS, but alternative thrombolytic agents are needed. The efficacy and safety of tenecteplase and reteplase, compared to alteplase, remain unclear, as does the optimal dosing for these treatments.

The efficacy of hypothermia combined with thrombolysis or mechanical thrombectomy on acute ischemic stroke: a systematic review and meta-analysis.

Background: Therapeutic hypothermia improves outcomes in experimental stroke models, especially after ischemia-reperfusion injury. In recent years, the safety and efficacy of hypothermia combining thrombolysis or mechanical thrombectomy have attracted widespread attention. The primary objective of the study was to evaluate the effectiveness and safety of hypothermia by combining reperfusion therapy in acute ischemic stroke patients.

Efficacy and safety of intravenous ferric carboxymaltose in the treatment of Restless Legs Syndrome: a systematic review and meta-analysis.

Introduction: Restless Legs Syndrome (RLS), also known as Willis-Ekbom Disease (WED), is a sensorimotor disorder characterized by an uncontrollable urge to move the legs, typically accompanied by discomfort. Low iron levels, pregnancy, and age are some identified risk factors. RLS is treated using various pharmacological options, including dopamine agonists, benzodiazepines, anticonvulsants, opioids, and bupropion.

Association between hypertension and hearing loss: a systemic review and meta-analysis.

Objective: To systematically evaluate the association between hypertension and hearing loss.

Methods: A standardized search for studies on hypertension and hearing loss in PubMed, Embase, Scopus, and Web of Science was performed using subject terms, free terms, and keyword combinations for the period of library construction to March 2024. Meta-analysis was performed using RevMan 5.

A dynamic variant of Takotsubo cardiomyopathy mimicking apical hypertrophic cardiomyopathy: a case report.

Background: Takotsubo cardiomyopathy usually presents with acute reversible left ventricular apical hypokinesia and apical ballooning with basal hyperdynamic function. We describe an underreported case of Takotsubo cardiomyopathy (TCM), misinterpreted as apical hypertrophic cardiomyopathy (HCM) due to transient apical oedema in the recovery phase of the condition.

Case Summary: A 74-year-old Caucasian woman, presented to the emergency department complaining of retrosternal chest pain following, emotional stress.

Polygenic risk scores for atrial fibrillation and heart failure and the risk of stroke and dementia.

Atrial fibrillation and heart failure have both been suggested to increase stroke and dementia risk. However, in observational studies, reversed causation and unmeasured confounding may occur. To mitigate these issues, this study aims to investigate if higher genetic risk for atrial fibrillation and heart failure increases dementia and stroke risk.

Current practices in prevention, screening, and treatment of diabetes in kidney transplant recipients: European survey highlights from the ERA DESCARTES Working Group.

Background: Although post-transplant diabetes mellitus (PTDM) is a common complication after kidney transplantation, there are few data on prevention, optimal screening, and treatment strategies.

Methods: The European Renal Association's DESCARTES working group distributed a web-based survey to European transplant centres to gather information on risk assessment, screening procedures, and management practices for preventing and treating PTDM in kidney transplant recipients.

Results: Answers were obtained from 121/241 transplant centres (50%) across 15 European countries.

Baseline Clinical Factors Associated with Cessation of Growth Hormone Therapy in Patients with Severe Growth Hormone Deficiency - Real World Evidence.

Background: Growth hormone replacement is indicated in adults with severe growth hormone (GH) deficiency, adult growth hormone deficiency assessment (AGHDA) score of at least 11 and are receiving treatment for other pituitary hormone deficiencies. There are no data looking at the cessation of GH replacement in adult patients with severe GH deficiency and the factors that predict the likelihood of patients continuing or stopping growth hormone replacement.

Methods: We audited patients on the GH register between January 2006 and January 2023 in Hull University Teaching Hospitals NHS foundation Trust, a UK tertiary hospital.

Meta-analysis of the clinicopathologic features of endometrial cancer molecular staging.

Objective: The 2013 TCGA identified four molecular subgroups of endometrial cancer; however, the data results for most of the pathological features were varied and of low value for clinical application. Therefore, a meta-analysis of articles related to the clinicopathological features of molecular typing was performed to observe how the prevalence of the four subgroups varied across different pathological features and whether they were associated with certain specific pathological features and to understand how molecular typing may influence current pathological assessments.

Methods: PubMed, Embase, Web of Science, CNKI, Wanfang, and VIP were searched from the time of library construction until May 2024, and the following data were extracted: histological type, FIGO grade, FIGO stage, LVSI, depth of muscularis propria infiltration, and lymph node status of each TCGA group.

Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis.

Background: Breast cancer (BC), as a leading cause of cancer mortality in women, demands robust prediction models for early diagnosis and personalized treatment. Artificial Intelligence (AI) and Machine Learning (ML) algorithms offer promising solutions for automated survival prediction, driving this study's systematic review and meta-analysis.

Methods: Three online databases (Web of Science, PubMed, and Scopus) were comprehensively searched (January 2016-August 2023) using key terms ("Breast Cancer", "Survival Prediction", and "Machine Learning") and their synonyms.

Machine learning-based identification of proteomic markers in colorectal cancer using UK Biobank data.

Colorectal cancer is one of the leading causes of cancer-related mortality in the world. Incidence and mortality are predicted to rise globally during the next several decades. When detected early, colorectal cancer is treatable with surgery and medications.

Efficacy and safety of nivolumab plus ipilimumab in gastrointestinal cancers: a systematic review and meta-analysis.

Introduction: Gastrointestinal (GI) cancers represent a significant global health burden, and the need for more effective treatment options is exceptionally pressing. The present meta-analysis aimed to explore the efficacy and safety of the combination of nivolumab and ipilimumab in treating GI cancers.

Methods: A systematic search of four databases (PubMed, Embase, Web of Science, and Cochrane Library) was conducted for articles on the treatment of GI cancers with nivolumab combined with ipilimumab, published from 2014 up to 30 August 2024.

Prioritizing Patients from the Most Deprived Areas on Elective Waiting Lists in the NHS in England: Estimating the Health and Health Inequality Impact.

Unlabelled: Reducing hospital waiting lists for elective procedures is a policy concern in the National Health Service (NHS) in England. Following growth in waiting lists after COVID-19, the NHS published an elective recovery plan that includes an aim to prioritize patients from deprived areas. We use a previously developed model to estimate the health and health inequality impact under hypothetical targeted versus universal policies to reduce waiting time.

Efficacy of traditional Chinese medicine as an adjunctive treatment in patients with renal dysfunction: a systematic-review and meta-analysis.

Objective: The effectiveness of using as an adjuvant therapy for patients with renal dysfunction (RD), especially acute kidney injury (AKI), is still a topic of debate. In response to the current conflicting data, the present meta-analysis was conducted to assess the clinical effectiveness of in the treatment of RD and to provide evidence for clinical practice.

Methods: Several databases, including PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI) and Wanfang, were systematically searched updated to March 25, 2024.

Incidence of HTLV-1-associated myelopathy in the UK from 1991 to 2024: a longitudinal observational cohort study.

Introduction: Human T-cell lymphotropic virus type 1 (HTLV-1) may cause spinal cord inflammation, leading to HTLV-1-associated myelopathy (HAM). HAM is a chronic and progressive neurological disorder that is associated with increased mortality and impaired quality of life. There are limited data on the incidence of HAM, with higher rates seen in Latin America and the Caribbean compared to Japan.

ADHD and ASD are Normal Biological Variations as part of Human Evolution and are not "Disorders".

Recent developments driven by people with attention-deficit hyperactivity disorder (ADHD) and/or autism spectrum disorder (ASD) have highlighted that far from being disorders, ADHD and/or ASD can be seen as natural variations in neurodevelopment. The neurodiversity movement acknowledges that people with ADHD and/or ASD have specific strengths, that can help them outperform neurotypical individuals in certain situations and that these conditions should therefore not be seen as disorders. This view is supported by evolutionary science, which can be used as a framework to understand ADHD and/or ASD as natural variations that were not eliminated by natural selection due to their benefit to the individual and group in certain situations.

Through each other's eyes: initial results and protocol for the co-design of an observational measure of adolescent-parent interaction using first-person perspective.

Background: Current observational methods to understand adolescent-parent interaction are limited in terms of ecological and content validity. We outline initial results and a protocol for future work from a programme of work to: (1) establish a new method for data capture of adolescent-parent interaction at home using wearable cameras and; (2) develop a new relevant and comprehensive observational micro-coding scheme. In Part 1, we report our completed preliminary work, comprised of an initial scoping review, and public engagement work.

Understanding recurrent groin pain following periacetabular osteotomy: assessment of psoas tendon mechanics using discrete element analysis.

Recurrent groin pain following periacetabular osteotomy (PAO) is a challenging problem. The purpose of our study was to evaluate the position and dynamics of the psoas tendon as a potential cause for recurrent groin pain following PAO. A total of 386 PAO procedures, performed between January 2013 and January 2020, were identified from a single surgeon series.

Scale-Up of Continuous Metallaphotoredox Catalyzed C-O Coupling to a 10 kg-Scale Using Small Footprint Photochemical Taylor Vortex Flow Reactors.

We report the development and optimization of a scalable flow process for metallaphotoredox (Ir/Ni) C-O coupling, a mild and efficient approach for forming alkyl-aryl ethers, a common motif in medicinal and process chemistry settings. Time-resolved infrared spectroscopy (TRIR) highlighted the amine as the major quencher of the photocatalyst triplet excited state, along with the formation of an Ir(II) species that, in the presence of the Ni cocatalyst, has its lifetime shortened, suggesting reductive quenching of Ir(III)*, followed by reoxidation facilitated by the Ni cocatalyst. TRIR and batch reaction screening was used to develop conditions transferrable to flow, and many processing benefits of performing the reaction in flow were then demonstrated using a simple to construct/operate, small-footprint FEP coil flow reactor, including short (<10 min) space times and reduced catalyst loadings (down to 0.