On-Chip Metamaterial-Enhanced Mid-Infrared Photodetectors with Built-In Encryption Features.

The integration of mid-infrared (MIR) photodetectors with built-in encryption capabilities holds immense promise for advancing secure communications in decentralized networks and compact sensing systems. However, achieving high sensitivity, self-powered operation, and reliable performance at room temperature within a miniaturized form factor remains a formidable challenge, largely due to constraints in MIR light absorption and the intricacies of embedding encryption at the device level. Here, a novel on-chip metamaterial-enhanced, 2D tantalum nickel selenide (Ta₂NiSe₅)-based photodetector, meticulously designed with a custom-engineered plasmonic resonance microstructure to achieve self-powered photodetection in the nanoampere range is unveiled.

Vital sign measurements demonstrate terminal digit bias and boundary effects.

Objective: The measurement and recording of vital signs may be impacted by biases, including preferences for even and round numbers. However, other biases, such as variation due to defined numerical boundaries (also known as boundary effects), may be present in vital signs data and have not yet been investigated in a medical setting. We aimed to assess vital signs data for such biases.

Knowledge-Driven Experimental Discovery of Ce-Based Metal Oxide Composites for Selective Catalytic Reduction of NO with NH through Interpretable Machine Learning.

Mining the scientific literature, combined with data-driven methods, may assist in the identification of optimized catalysts. In this paper, we employed interpretable machine learning to discover ternary metal oxides capable of selective catalytic reduction of nitrogen oxides with ammonia (NH-SCR). Specifically, we devised a machine learning framework utilizing extreme gradient boosting (XGB), identified for its optimal performance, and SHapley Additive exPlanations (SHAP) to evaluate a curated database of 5654 distinct metal oxide composite catalytic systems containing cerium (Ce) element, with records of catalyst composition and preparation and reaction conditions.

Ophthalmology Operation Note Encoding with Open-Source Machine Learning and Natural Language Processing.

Introduction: Accurate assignment of procedural codes has important medico-legal, academic, and economic purposes for healthcare providers. Procedural coding requires accurate documentation and exhaustive manual labour to interpret complex operation notes. Ophthalmology operation notes are highly specialised making the process time-consuming and challenging to implement.

Immune Checkpoint Inhibitors and Optic Neuropathy: A Systematic Review.

Introduction: Immune checkpoint inhibitors are a class of monoclonal antibodies that are used as a mainstay of immunotherapy for multiple solid organ malignancies. With the recent increase in popularity of these agents, immune-related adverse events including optic neuropathy are becoming more frequently reported. This review aims to explore the association between immune checkpoint inhibitors and optic neuropathy through analysis of incidence, clinical features, investigations, treatment, and patient outcomes.

Professionalism and clinical short answer question marking with machine learning.

Machine learning may assist in medical student evaluation. This study involved scoring short answer questions administered at three centres. Bidirectional encoder representations from transformers were particularly effective for professionalism question scoring (accuracy ranging from 41.

[Experimental investigation of vincristine on chemosensitivity through Stathmin regulation in oral squamous cell carcinoma].

Purpose: Our previous studies have found that Stathmin, a microtubule depolymerizing protein, is a potential biomarker to guide locally advanced oral squamous cell carcinoma (OSCC) induction chemotherapy. This study further explored the regulatory effect of vincristine on Stathmin and its potention as an alternative chemotherapy drug.

Methods: Stathmin overexpressed and knockdown stable cell lines were constructed.

Prevalence and risk factors for cataracts in the Lao People's Democratic Republic: The Vientiane Eye Study.

Purpose: To determine the prevalence and risk factors for cataracts in the Vientiane Province.

Methods: We conducted a population-based study of 1264 participants aged ≥40 years of age from urban and rural areas of Vientiane Province. Data collection included demographic information, smoking history, body mass index, blood pressure, history of trauma and dilated lens examination using the World Health Organization WHO Simplified Cataract Grading System.

Prevalence and causes of visual impairment and blindness in Lao People's Democratic Republic: the Vientiane Eye Study.

Aims: To determine the prevalence and causes of visual impairment and blindness in Vientiane Province, the Lao People's Democratic Republic (Lao PDR).

Methods: We conducted a population-based, cross-sectional study of 1264 participants aged 40 years and older from urban and rural areas of Vientiane Province. The ophthalmic examination included presenting and pinhole Snellen visual acuity (VA) with an illiterate E chart, slit-lamp examination of the anterior segment and dilated stereoscopic fundus examination.

Prevalence of Refractive Error in Vientiane Province, Lao People's Democratic Republic.

Purpose: To determine the prevalence of adult refractive error and associated risk factors in the Vientiane Province of the Lao People's Democratic Republic.

Methods: Population-based, cross-sectional ophthalmic survey of individuals ≥ 40 years of age in Vientiane Province. Suitable refractive data was available in 1058 individuals.

Medical student knowledge and critical appraisal of machine learning: a multicentre international cross-sectional study.

To utilise effectively tools that employ machine learning (ML) in clinical practice medical students and doctors will require a degree of understanding of ML models. To evaluate current levels of understanding, a formative examination and survey was conducted across three centres in Australia, New Zealand and the United States. Of the 245 individuals who participated in the study (response rate = 45.

Daily estimates of individual discharge likelihood with deep learning natural language processing in general medicine: a prospective and external validation study.

Machine learning, in particular deep learning, may be able to assist in the prediction of the length of stay and timing of discharge for individual patients. Artificial neural networks applied to medical text have previously shown promise in this area. In this study, a previously derived artificial neural network was applied to prospective and external validation datasets.

Anti-tumor effect of carrimycin on oral squamous cell carcinoma cells in vitro and in vivo.

Purpose: Carrimycin is a newly synthesized macrolide antibiotic with good antibacterial effect. Exploratory experiments found its function in regulating cell physiology, proliferation and immunity, suggesting its potential anti-tumor capacity. The aim of this study is to investigate the anti-tumor effect of carrimycin against human oral squamous cell carcinoma cells in vitro and in vivo.

Prevalence of glaucoma in the Lao People's Democratic Republic: the Vientiane Eye Study.

Aims: To determine the prevalence and subtypes of glaucoma in Vientiane Province.

Methods: We conducted a population-based study of 1264 participants aged ≥40 years of age from urban and rural areas of Vientiane Province. Data collection included Snellen visual acuity, slip lamp examination, tonometry, gonioscopy, dilated stereoscopic disc examination and perimetry.

Mixed-data deep learning in repeated predictions of general medicine length of stay: a derivation study.

The accurate prediction of likely discharges and estimates of length of stay (LOS) aid in effective hospital administration and help to prevent access block. Machine learning (ML) may be able to help with these tasks. For consecutive patients admitted under General Medicine at the Royal Adelaide Hospital over an 8-month period, daily ward round notes and relevant discrete data fields were collected from the electronic medical record.

Anti-VEGF crunch syndrome in proliferative diabetic retinopathy: A review.

Anti-vascular endothelial growth factor (anti-VEGF) crunch syndrome describes the progression to tractional retinal detachment following intravitreal anti-VEGF therapy in an eye with proliferative diabetic retinopathy . We reviewed the literature on the anti-VEGF crunch using the PubMed and Cochrane databases. Anti-VEGF crunch typically manifests as sudden vision loss in the affected eye between 1 and 6 weeks following intravitreal anti-VEGF injection, with a mean onset of 13 days.

Optic neuropathy secondary to perhexiline and amiodarone.

Bilateral optic disc swelling is an important clinical sign for potentially life-threatening and sight-threatening conditions, with the most common being raised intracranial pressure and pseudopapillitis. Perhexiline-related and amiodarone-related optic disc swellings are diagnoses of exclusion. This report describes the diagnosis of a man with perhexiline-induced and amiodarone-induced optic neuropathy after extensive investigation consisting of full ophthalmic examination, biochemical screen, temporal artery biopsy, CT, MRI, positron emission tomography and lumbar puncture.

The use of frontalis sling in the management of variable ptosis secondary to congenital myasthenic syndrome.

Congenital myasthenic syndrome (CMS) describes a group of rare inherited disorders caused by impaired neuromuscular transmission at the motor endplate. Common ophthalmic manifestations associated with CMS include ptosis and ophthalmoplegia. A 19-year-old female presented with variable day-to-day ptosis secondary to CMS that was refractory to medical therapy.