Mobile health apps (MHAs) and medical apps (MAs) are becoming increasingly popular as digital interventions in a wide range of health-related applications in almost all sectors of healthcare. The surge in demand for digital medical solutions has been accelerated by the need for new diagnostic and therapeutic methods in the current coronavirus disease 2019 pandemic. This also applies to clinical practice in gastroenterology, which has, in many respects, undergone a recent digital transformation with numerous consequences that will impact patients and healthcare professionals in the near future. MHAs and MAs are considered to have great potential, especially for chronic diseases, as they can support the self-management of patients in many ways. Despite the great potential associated with the application of MHAs and MAs in gastroenterology and health care in general, there are numerous challenges to be met in the future, including both the ethical and legal aspects of applying this technology. The aim of this article is to provide an overview of the current status of MHA and MA use in the field of gastroenterology, describe the future perspectives in this field, and point out some of the challenges that need to be addressed.

AI-based monitoring of cold shaking incubators is a growing area of research and development. However, there are currently no specific search results that provide information on AI-based monitoring of cold shaking incubators. Nonetheless, there are various shaking incubators available in the market that offer temperature and shaking control, as well as monitoring features such as temperature sensors and laser tachometers. Some examples of shaking incubators with monitoring features include the Labnet Environmental Shaking Incubator, the TriNEST Microplate Incubator Shaker by PerkinElmer, and the Innova S44i Stackable Incubator Shaker by Eppendorf. The Zhichu shaking incubator is another option that offers accurate temperature control and a double shaking platform. The shaking incubator is an incubator which consists of shaker and heating chamber for incubating and shaking sensitive samples. It replaces two devices, reducing both time and space needed. Both the shaking mechanism and temperature chamber are regulated via microprocessors, which control all sensors for motor speed, temperature and time. It is suitable for biochemistry, microbiology and clinical laboratories in which applications require temperature and shaking treatment. This article presents a novel design of calibration method of shaking incubator by studying the essential metrological parameters of the device. The experimental results show that the calibration method presented in this article can establish the metrological traceability system of shaking incubator in China in order to ensure the accuracy and reliability of the device, which is of great importance for the quality control of the device.

Artificial intelligence (AI) has revolutionized many aspects of the pharmaceutical industry, including drug discovery and development, drug repurposing, improving pharmaceutical productivity, clinical trials, medication management, and drug delivery design. AI algorithms can analyze extensive biological data, including genomics and proteomics, to identify disease-associated targets and predict their interactions with potential drug candidates, enabling a more efficient and targeted approach to drug discovery. AI can also assist in experimental design, predict the pharmacokinetics and toxicity of drug candidates, and optimize research and development processes, reducing the need for extensive and costly animal testing. In pharmacy practice, AI technology has a wide range of applications, enabling pharmacists to make decisions based on current data, improving medication management, streamlining workflow, and enhancing patient safety and outcomes. AI can also assist pharmacies with inventory management, predict drug demand, and optimize inventory management, maintaining adequate stock levels and reducing waste. Despite its potential, the implementation of AI in pharmacies faces several challenges, including data quality, initial expense required for AI integration, and the need for comprehensive education and training.

This review article examines the rapidly evolving topic of radiopharmaceuticals, where novel discoveries are made by mixing pharmaceuticals with radioisotopes, creating intriguing therapeutic opportunities. This comprehensive analysis looks at targeted medication delivery, including active targeting with ligand-receptor methods and passive targeting with increased permeability and retention. Additionally covered in the article are stimulus-responsive release systems, which coordinate regulated release for improved accuracy and efficacy of treatment. The vital role that radiopharmaceuticals play in medical imaging and theranostics is heavily discussed, with particular emphasis on how they improve diagnostic precision and enable image-guided therapeutic therapies. In addition to highlighting safety concerns and methods for reducing side effects, the review offers insightful information on how to overcome obstacles and achieve accurate medication distribution. The essay highlights the potential applications of nanoparticle formulations as state-of-the-art developments in next-generation radiopharmaceuticals. Case studies are used to illustrate real-world applications, such as the complex management of bone metastases, the use of radiolabelled antibodies for solid tumors, and peptide receptor radionuclide therapy for neuroendocrine tumors. The last viewpoint predicts how radiopharmaceuticals will develop in the future and hopes for a seamless union of AI and precision medicine. This vision anticipates a day when scientific progress and therapeutic precision converge to create a new era characterized by the union of visionary progress and therapeutic resonance.