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Artificial intelligence (AI) broadly describes a branch of computer science focused on developing machines capable of performing tasks typically associated with human intelligence. Those who connect AI with the world of science fiction may meet its growing rise with hesitancy or outright skepticism. However, AI is becoming increasingly pervasive in our society, from algorithms helping to sift through airline fares to substituting words in emails and SMS text messages based on user choices. Data collection is ongoing and is being leveraged by software platforms to analyze patterns and make predictions across multiple industries. Health care is gradually becoming part of this technological transformation, as advancements in computational power and storage converge with the rapid expansion of digitized medical information. Given the growing and inevitable integration of AI into health care systems, it is our viewpoint that pediatricians urgently require training and orientation to the uses, promises, and pitfalls of AI in medicine. AI is unlikely to solve the full array of complex challenges confronting pediatricians today; however, if used responsibly, it holds great potential to improve many aspects of care for providers, children, and families. Our aim in this viewpoint is to provide clinicians with a targeted introduction to the field of AI in pediatrics, including key promises, pitfalls, and clinical applications, so they can play a more active role in shaping the future impact of AI in medicine.

Stem cell exosomes are nanoscale membrane vesicles released from stem cells of various origins that can regulate signal transduction pathways between liver cells, and their functions in intercellular communication have been recognized. Due to their natural substance transport properties and excellent biocompatibility, exosomes can also be used as drug carriers to release a variety of substances, which has great prospects in the treatment of critical and incurable diseases. Different types of stem cell exosomes have been used to study liver diseases. Due to current difficulties in the treatment of acute liver failure (ALF), this review will outline the potential of stem cell exosomes for ALF treatment. Specifically, we reviewed the pathogenesis of acute liver failure and the latest progress in the use of stem cell exosomes in the treatment of ALF, including the role of exosomes in inhibiting the ALF inflammatory response and regulating signal transduction pathways, the advantages of stem cell exosomes and their use as a drug‐loading system, and their pre‐clinical application in the treatment of ALF. Finally, the clinical research status of stem cell therapy for ALF and the current challenges of exosome clinical transformation are summarized. Mesenchymal stem cell‐derived exosomes from different sources and their use as drug‐loading systems to repair acute liver failure induced by inflammation, autophagy, apoptosis, various cytokines and signaling pathways,etc.

Mesenchymal stromal cells (MSCs), also known as mesenchymal stem cells, have been intensely investigated for clinical applications within the last decades. However, the majority of registered clinical trials applying MSC therapy for diverse human diseases have fallen short of expectations, despite the encouraging pre-clinical outcomes in varied animal disease models. This can be attributable to inconsistent criteria for MSCs identity across studies and their inherited heterogeneity. Nowadays, with the emergence of advanced biological techniques and substantial improvements in bio-engineered materials, strategies have been developed to overcome clinical challenges in MSC application. Here in this review, we will discuss the major challenges of MSC therapies in clinical application, the factors impacting the diversity of MSCs, the potential approaches that modify MSC products with the highest therapeutic potential, and finally the usage of MSCs for COVID-19 pandemic disease.

Animal and clinical studies have confirmed the therapeutic effect of bone marrow mesenchymal stem cells on cerebral ischemia, but their mechanisms of action remain poorly understood. Here, we summarize the transplantation approaches, directional migration, differentiation, replacement, neural circuit reconstruction,angiogenesis, neurotrophic factor secretion, apoptosis, immunomodulation, multiple mechanisms of action,and optimization strategies for bone marrow mesenchymal stem cells in the treatment of ischemic stroke.We also explore the safety of bone marrow mesenchymal stem cell transplantation and conclude that bone marrow mesenchymal stem cell transplantation is an important direction for future treatment of cerebral ischemia. Determining the optimal timing and dose for the transplantation are important directions for future research.

In situ carmustine wafers containing 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) are commonly used for the treatment of recurrent glioblastoma to overcome the brain-blood barrier. In theory, this chemotherapy diffuses into the adjacent parenchyma and the excipient degrades in maximum 8 weeks but no clinical data confirms this evolution, because patients are rarely operated again. A 75-year-old patient was operated twice for recurrent glioblastoma, and a carmustine wafer was implanted during the second surgery. Eleven months later, a third surgery was performed, revealing unexpected incomplete degradation of the wafer. 1H-Nuclear Magnetic Resonance was performed to compare this wafer to pure BCNU and to an unused copolymer wafer. In the used wafer, peaks corresponding to hydrophobic units of the excipient were no longer noticeable, whereas peaks of the hydrophilic units and traces of BCNU were still present. These surprising results could be related to the formation of a hydrophobic membrane around the wafer, thus interfering with the expected diffusion and degradation processes. The clinical benefit of carmustine wafers in addition to the standard radio-chemotherapy remains limited, and in vivo behavior of this treatment is not completely elucidated yet. We found that the wafer may remain after several months. Alternative strategies to deal with the blood–brain barrier, such as drug-loaded liposomes or ultrasound-opening, must be explored to offer larger drug diffusion or allow repetitive delivery.

Programmed cell death protein-1 (PD-1) is a checkpoint receptor expressed on the surface of various immune cells. PD-L1, the natural receptor for PD-1, is mainly expressed in tumor cells. Studies have indicated that PD-1 and PD-L1 are closely associated with the progression of human cancers and are promising biomarkers for cancer therapy. Moreover, the interaction of PD-1 and PD-L1 is one of the important mechanism by which human tumors generate immune escape. This article provides a review on the role of PD-L1/PD-1, mechanisms of immune response and resistance, as well as immune-related adverse events in the treatment of anti-PD-1/PD-L1 immunotherapy in human cancers. Moreover, we summarized a large number of clinical trials to successfully reveal that PD-1/PD-L1 Immune-checkpoint inhibitors have manifested promising therapeutic effects, which have been evaluated from different perspectives, including overall survival, objective effective rate and medium progression-free survival. Finally, we pointed out the current problems faced by PD-1/PD-L1 Immune-checkpoint inhibitors and its future prospects. Although PD-1/PD-L1 immune checkpoint inhibitors have been widely used in the treatment of human cancers, tough challenges still remain. Combination therapy and predictive models based on integrated biomarker determination theory may be the future directions for the application of PD-1/PD-L1 Immune-checkpoint inhibitors in treating human cancers.

It is believed that artificial intelligence (AI) will be an integral part of health care services in the near future and will be incorporated into several aspects of clinical care such as prognosis, diagnostics, and care planning. Thus, many technology companies have invested in producing AI clinical applications. Patients are one of the most important beneficiaries who potentially interact with these technologies and applications; thus, patients' perceptions may affect the widespread use of clinical AI. Patients should be ensured that AI clinical applications will not harm them, and that they will instead benefit from using AI technology for health care purposes. Although human-AI interaction can enhance health care outcomes, possible dimensions of concerns and risks should be addressed before its integration with routine clinical care. The main objective of this study was to examine how potential users (patients) perceive the benefits, risks, and use of AI clinical applications for their health care purposes and how their perceptions may be different if faced with three health care service encounter scenarios. We designed a 2×3 experiment that crossed a type of health condition (ie, acute or chronic) with three different types of clinical encounters between patients and physicians (ie, AI clinical applications as substituting technology, AI clinical applications as augmenting technology, and no AI as a traditional in-person visit). We used an online survey to collect data from 634 individuals in the United States. The interactions between the types of health care service encounters and health conditions significantly influenced individuals' perceptions of privacy concerns, trust issues, communication barriers, concerns about transparency in regulatory standards, liability risks, benefits, and intention to use across the six scenarios. We found no significant differences among scenarios regarding perceptions of performance risk and social biases. The results imply that incompatibility with instrumental, technical, ethical, or regulatory values can be a reason for rejecting AI applications in health care. Thus, there are still various risks associated with implementing AI applications in diagnostics and treatment recommendations for patients with both acute and chronic illnesses. The concerns are also evident if the AI applications are used as a recommendation system under physician experience, wisdom, and control. Prior to the widespread rollout of AI, more studies are needed to identify the challenges that may raise concerns for implementing and using AI applications. This study could provide researchers and managers with critical insights into the determinants of individuals' intention to use AI clinical applications. Regulatory agencies should establish normative standards and evaluation guidelines for implementing AI in health care in cooperation with health care institutions. Regular audits and ongoing monitoring and reporting systems can be used to continuously evaluate the safety, quality, transparency, and ethical factors of AI clinical applications.

Sepsis is now defined as a life-threatening syndrome of organ dysfunction triggered by a dysregulated host response to infection, posing significant challenges in critical care. The main objective of this review is to evaluate the potential of emerging biomarkers for early diagnosis and accurate prognosis in sepsis management, which are pivotal for enhancing patient outcomes. Despite advances in supportive care, traditional biomarkers like C-reactive protein and procalcitonin have limitations, and recent studies have identified novel biomarkers with increased sensitivity and specificity, including circular RNAs, HOXA distal transcript antisense RNA, microRNA-486-5p, protein C, triiodothyronine, and prokineticin 2. These emerging biomarkers hold promising potential for the early detection and prognostication of sepsis. They play a crucial role not only in diagnosis but also in guiding antibiotic therapy and evaluating treatment effectiveness. The introduction of point-of-care testing technologies has brought about a paradigm shift in biomarker application, enabling swift and real-time patient evaluation. Despite these advancements, challenges persist, notably concerning biomarker variability and the lack of standardized thresholds. This review summarizes the latest advancements in sepsis biomarker research, spotlighting the progress and clinical implications. It emphasizes the significance of multi-biomarker strategies and the feasibility of personalized medicine in sepsis management. Further verification of biomarkers on a large scale and their integration into clinical practice are advocated to maximize their efficacy in future sepsis treatment.

As the most abundant and conserved internal modification in eukaryote RNAs, N6-methyladenosine (m 6 A) is involved in a wide range of physiological and pathological processes. The YT521-B homology (YTH) domain-containing family proteins (YTHDFs), including YTHDF1, YTHDF2, and YTHDF3, are a class of cytoplasmic m 6 A-binding proteins defined by the vertebrate YTH domain, and exert extensive functions in regulating RNA destiny. Distinct expression patterns of the YTHDF family in specific cell types or developmental stages result in prominent differences in multiple biological processes, such as embryonic development, stem cell fate, fat metabolism, neuromodulation, cardiovascular effect, infection, immunity, and tumorigenesis. The YTHDF family mediates tumor proliferation, metastasis, metabolism, drug resistance, and immunity, and possesses the potential of predictive and therapeutic biomarkers. Here, we mainly summary the structures, roles, and mechanisms of the YTHDF family in physiological and pathological processes, especially in multiple cancers, as well as their current limitations and future considerations. This will provide novel angles for deciphering m 6 A regulation in a biological system.