Digital health and mobile health: a bibliometric analysis of the 100 most cited papers and their contributing authors

Aim: This study aimed to identify and analyze the top 100 most cited digital health and mobile health (m-health) publications. It could aid researchers in the identification of promising new research avenues, additionally supporting the establishment of international scientific collaboration between interdisciplinary research groups with demonstrated achievements in the area of interest. Methods: On 30th August, 2023, the Web of Science Core Collection (WOSCC) electronic database was queried to identify the top 100 most cited digital health papers with a comprehensive search string. From the initial search, 106 papers were identified. After screening for relevance, six papers were excluded, resulting in the final list of the top 100 papers. The basic bibliographic data was directly extracted from WOSCC using its “Analyze” and “Create Citation Report” functions. The complete records of the top 100 papers were downloaded and imported into a bibliometric software called VOSviewer (version 1.6.19) to generate an author keyword map and author collaboration map. Results: The top 100 papers on digital health received a total of 49,653 citations. Over half of them (n = 55) were published during 2013–2017. Among these 100 papers, 59 were original articles, 36 were reviews, 4 were editorial materials, and 1 was a proceeding paper. All papers were written in English. The University of London and the University of California system were the most represented affiliations. The USA and the UK were the most represented countries. The Journal of Medical Internet Research was the most represented journal. Several diseases and health conditions were identified as a focus of these works, including anxiety, depression, diabetes mellitus, cardiovascular diseases, and coronavirus disease 2019 (COVID-19). Conclusions: The findings underscore key areas of focus in the field and prominent contributors, providing a roadmap for future research in digital and m-health

microbeMASST: A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms’ role in ecology and human health

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms’ role in ecology and human health

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

Abstract Background During the COVID-19 pandemic, a variety of clinical decision support systems (CDSS) were developed to aid patient triage. However, research focusing on the interaction between decision support systems and human experts is lacking. Methods Thirty-two physicians were recruited to rate the survival probability of 59 critically ill patients by means of chart review. Subsequently, one of two artificial intelligence systems advised the physician of a computed survival probability. However, only one of these systems explained the reasons behind its decision-making. In the third step, physicians reviewed the chart once again to determine the final survival probability rating. We hypothesized that an explaining system would exhibit a higher impact on the physicians’ second rating (i.e., higher weight-on-advice). Results The survival probability rating given by the physician after receiving advice from the clinical decision support system was a median of 4 percentage points closer to the advice than the initial rating. Weight-on-advice was not significantly different (p = 0.115) between the two systems (with vs without explanation for its decision). Additionally, weight-on-advice showed no difference according to time of day or between board-qualified and not yet board-qualified physicians. Self-reported post-experiment overall trust was awarded a median of 4 out of 10 points. When asked after the conclusion of the experiment, overall trust was 5.5/10 (non-explaining median 4 (IQR 3.5–5.5), explaining median 7 (IQR 5.5–7.5), p = 0.007). Conclusions Although overall trust in the models was low, the median (IQR) weight-on-advice was high (0.33 (0.0–0.56)) and in line with published literature on expert advice. In contrast to the hypothesis, weight-on-advice was comparable between the explaining and non-explaining systems. In 30% of cases, weight-on-advice was 0, meaning the physician did not change their rating. The median of the remaining weight-on-advice values was 50%, suggesting that physicians either dismissed the recommendation or employed a “meeting halfway” approach. Newer technologies, such as clinical reasoning systems, may be able to augment the decision process rather than simply presenting unexplained bias

UV-absorbing mycosporine-like amino acids in the eyes of temperate marine and freshwater fish species

Ultraviolet radiation (UVR) is the photochemically most reactive waveband of incident solar irradiation. Despite high absorption in aquatic environments, UVR causes numerous biochemical, genetic, and cytotoxic effects in aquatic organisms. To counteract UVR stress, many of those species are able to synthesize, accumulate, or acquire UV-sunscreen compounds for photoprotection from their diet. The most abundant UV sunscreens in marine and freshwater organisms are mycosporine-like amino acids (MAAs), which exhibit high molar extinction coefficients in the UVR range along with a strong photo- and heat stability. In this study, we investigated the qualitative and quantitative MAA distribution patterns in the eyes of 39 fish species, mainly from the temperate northern hemisphere (Baltic Sea, Northern Atlantic), using state-of-the-art analytical methods. The fish eyes of the most investigated species (33 taxa) contained MAAs, between one and seven different compounds. The MAAs palythine, asterina-330, palythene, and usujirene were present (as previously reported), and three new compounds, aplysiapalythine A, porphyra-334, and shinorine, were identified. Total MAA concentrations covered a wide range from trace amounts to > 4.2 mg g−1 dry weight, thereby providing the first quantitative data on MAAs in fish eyes. The highest MAA contents were measured in Sprattus sprattus, which are comparable to those of intertidal red seaweeds. The trophic transfer of MAAs from primary producers via zooplankton to the fish is discussed, along with the localization in the fish eye as well as possible additional functions

Feature-Based Molecular Networking—An Exciting Tool to Spot Species of the Genus Cortinarius with Hidden Photosensitizers

Fungi have developed a wide array of defense strategies to overcome mechanical injuries and pathogen infections. Recently, photoactivity has been discovered by showing that pigments isolated from Cortinarius uliginosus produce singlet oxygen under irradiation. To test if this phenomenon is limited to dermocyboid Cortinarii, six colourful Cortinarius species belonging to different classical subgenera (i.e., Dermocybe, Leprocybe, Myxacium, Phlegmacium, and Telamonia) were investigated. Fungal extracts were explored by the combination of in vitro photobiological methods, UHPLC coupled to high-resolution tandem mass spectrometry (UHPLC-HRMS2), feature-based molecular networking (FBMN), and metabolite dereplication techniques. The fungi C. rubrophyllus (Dermocybe) and C. xanthophyllus (Phlegmacium) exhibited promising photobiological activity in a low concentration range (1–7 µg/mL). Using UHPLC-HRMS2-based metabolomic tools, the underlying photoactive principle was investigated. Several monomeric and dimeric anthraquinones were annotated as compounds responsible for the photoactivity. Furthermore, the results showed that light-induced activity is not restricted to a single subgenus, but rather is a trait of Cortinarius species of different phylogenetic lineages and is linked to the presence of fungal anthraquinones. This study highlights the genus Cortinarius as a promising source for novel photopharmaceuticals. Additionally, we showed that putative dereplication of natural photosensitizers can be done by FBMN

Fungal Anthraquinone Photoantimicrobials Challenge the Dogma of Cationic Photosensitizers

The photoantimicrobial potential of four mushroom species (i.e., Cortinarius cinnabarinus, C. sanguineus, C. rubrophyllus, and C. holoxanthus) was explored based on a light modified EUCAST protocol. The extracts were tested against Candida albicans, Escherichia coli, and Staphylococcus aureus under blue (λ = 428 nm and λ = 478 nm, H = 30 J cm-2) and green light (λ = 528 nm, H = 30 J cm-2) irradiation. Three extracts showed significant photoantimicrobial effects at concentrations below 25 µg/mL. Targeted isolation of the major pigments from C. sanguineus led to the identification of two new potent photoantimicrobials, one of them (i.e., dermocybin) being active against S. aureus and C. albicans under green light irradiation (PhotoMIC523 = 39.5 µM and 2.3 µM, respectively) and the other one (i.e., emodin) being active against E. coli in a low micromolar range (PhotoMIC428 = 11.1 µM). Intriguingly, dermocybin was not (photo)cytotoxic against three tested cell lines adding an additional level of selectivity. Since both photoantimicrobials are not charged, this discovery shifts the paradigm of cationic photosensitizers

Accuracy of a Dual-Sensor Heat-Flux (DHF) Non-Invasive Core Temperature Sensor in Pediatric Patients Undergoing Surgery

Accurate temperature measurement is crucial for the perioperative management of pediatric patients, and non-invasive thermometry is necessary when invasive methods are infeasible. A prospective observational study was conducted on 57 patients undergoing elective surgery. Temperatures were measured using a dual-sensor heat-flux (DHF) thermometer (Tcore™) and a rectal temperature probe (TRec), and the agreement between the two measurements was assessed. The DHF measurements showed a bias of +0.413 °C compared with those of the TRec. The limits of agreement were broader than the pre-defined ±0.5 °C range (−0.741 °C and +1.567 °C). Although the DHF sensors tended to overestimate the core temperature compared to the rectal measurements, an error grid analysis demonstrated that 95.81% of the DHF measurements would not have led to a wrong clinical decision, e.g., warming or cooling when not necessary. In conclusion, the low number of measurements that would have led to incorrect decisions suggests that the DHF sensor can be considered an option for continuous temperature measurement when more invasive methods are infeasible

Targeted Isolation of Photoactive Pigments from Mushrooms Yielded a Highly Potent New Photosensitizer: 7,7’-Biphyscion

Pigments of mushrooms are a fertile ground of inspiration: they spread across various chemical backbones, absorption ranges, and bioactivities. While looking from a photochemical perspective, we discovered a new bioactivity, i.e., photoactivity. We revealed that singlet oxygen production is a common theme in one group of webcaps (i.e., dermocyboid Cortinarii, formerly called Dermocybe). This photoactivity was explored by bioactivity-based molecular networking and photo-activity guided isolation. As a result, three photosensitizers based on anthraquinone structures were isolated. All three were photochemically characterized and (photo)cytotoxically tested. For one of the three, i.e. (-)-7,7’-biphyscion (1), a promising photoyield of fD= 20 % (lexc = 455 nm) and an excellent photocytotoxicity of approx. 64 nM against A549 lung cancer cell lines (lexc = 468 nm, 9.3 J/cm²) was found, while no effect was observed in the dark. Several molecular biological methods proved the harmlessness of 1 in the dark while showing that apoptosis is dose-dependent induced by 1 under irradiation. Therewith, 1 is a promising candidate for photodynamic therapy, while the photoactivity theme in the subgenus hints towards a yet unthought bioactivity in fungi: photoactivated defense.</p

Digital Technology Applications in the Management of Adverse Drug Reactions: Bibliometric Analysis

Adverse drug reactions continue to be not only one of the most urgent problems in clinical medicine, but also a social problem. The aim of this study was a bibliometric analysis of the use of digital technologies to prevent adverse drug reactions and an overview of their main applications to improve the safety of pharmacotherapy. The search was conducted using the Web of Science database for the period 1991–2023. A positive trend in publications in the field of using digital technologies in the management of adverse drug reactions was revealed. A total of 72% of all relevant publications come from the following countries: the USA, China, England, India, and Germany. Among the organizations most active in the field of drug side effect management using digital technologies, American and Chinese universities dominate. Visualization of publication keywords using VOSviewer software 1.6.18 revealed four clusters: “preclinical studies”, “clinical trials”, “pharmacovigilance”, and “reduction of adverse drug reactions in order to improve the patient’s quality of life”. Molecular design technologies, virtual models for toxicity modeling, data integration, and drug repurposing are among the key digital tools used in the preclinical research phase. Integrating the application of machine learning algorithms for data analysis, monitoring of electronic databases of spontaneous messages, electronic medical records, scientific databases, social networks, and analysis of digital device data into clinical trials and pharmacovigilance systems, can significantly improve the efficiency and safety of drug development, implementation, and monitoring processes. The result of combining all these technologies is a huge synergistic provision of up-to-date and valuable information to healthcare professionals, patients, and health authorities