In situ sprayed NIR-responsive, analgesic black phosphorus-based gel for diabetic ulcer treatment.

The treatment of diabetic ulcer (DU) remains a major clinical challenge due to the complex wound-healing milieu that features chronic wounds, impaired angiogenesis, persistent pain, bacterial infection, and exacerbated inflammation. A strategy that effectively targets all these issues has proven elusive. Herein, we use a smart black phosphorus (BP)-based gel with the characteristics of rapid formation and near-infrared light (NIR) responsiveness to address these problems. The in situ sprayed BP-based gel could act as 1) a temporary, biomimetic "skin" to temporarily shield the tissue from the external environment and accelerate chronic wound healing by promoting the proliferation of endothelial cells, vascularization, and angiogenesis and 2) a drug "reservoir" to store therapeutic BP and pain-relieving lidocaine hydrochloride (Lid). Within several minutes of NIR laser irradiation, the BP-based gel generates local heat to accelerate microcirculatory blood flow, mediate the release of loaded Lid for "on-demand" pain relief, eliminate bacteria, and reduce inflammation. Therefore, our study not only introduces a concept of in situ sprayed, NIR-responsive pain relief gel targeting the challenging wound-healing milieu in diabetes but also provides a proof-of-concept application of BP-based materials in DU treatment.

Minimally invasive nanomedicine: nanotechnology in photo-/ultrasound-/radiation-/magnetism-mediated therapy and imaging.

Traditional treatments such as chemotherapy and surgery usually cause severe side effects and excruciating pain. The emergence of nanomedicines and minimally invasive therapies (MITs) has brought hope to patients with malignant diseases. Especially, minimally invasive nanomedicines (MINs), which combine the advantages of nanomedicines and MITs, can effectively target pathological cells/tissues/organs to improve the bioavailability of drugs, minimize side effects and achieve painless treatment with a small incision or no incision, thereby acquiring good therapeutic effects. In this review, we provide a comprehensive review of the research status and challenges of MINs, which generally refers to the medical applications of nanotechnology in photo-/ultrasound-/radiation-/magnetism-mediated therapy and imaging. Additionally, we also discuss their combined application in various fields including cancers, cardiovascular diseases, tissue engineering, neuro-functional diseases, and infectious diseases. The prospects, and potential bench-to-bedside translation of MINs are also presented in this review. We expect that this review can inspire the broad interest for a wide range of readers working in the fields of interdisciplinary subjects including (but not limited to) chemistry, nanomedicine, bioengineering, nanotechnology, materials science, pharmacology, and biomedicine.

Automatic Detection of Twitter Users Who Express Chronic Stress Experiences via Supervised Machine Learning and Natural Language Processing.

Americans bear a high chronic stress burden, particularly during the COVID-19 pandemic. Although social media have many strengths to complement the weaknesses of conventional stress measures, including surveys, they have been rarely utilized to detect individuals self-reporting chronic stress. Thus, this study aimed to develop and evaluate an automatic system on Twitter to identify users who have self-reported chronic stress experiences. Using the Twitter public streaming application programming interface, we collected tweets containing certain stress-related keywords (eg, "chronic," "constant," "stress") and then filtered the data using pre-defined text patterns. We manually annotated tweets with (without) self-report of chronic stress as positive (negative). We trained multiple classifiers and tested them via accuracy and F1 score. We annotated 4195 tweets (1560 positives, 2635 negatives), achieving an inter-annotator agreement of 0.83 (Cohen's kappa). The classifier based on Bidirectional Encoder Representation from Transformers performed the best (accuracy of 83.6% [81.0-86.1]), outperforming the second best-performing classifier (support vector machines: 76.4% [73.5-79.3]). The past tweets from the authors of positive tweets contained useful information, including sources and health impacts of chronic stress. Our study demonstrates that users' self-reported chronic stress experiences can be automatically identified on Twitter, which has a high potential for surveillance and large-scale intervention.

2D Monoelemental Germanene Quantum Dots: Synthesis as Robust Photothermal Agents for Photonic Cancer Nanomedicine.

As a new family member of the emerging two-dimensional (2D) monoelemental materials (Xenes), germanene has shown promising advantages over the prototypical 2D Xenes, such as black phosphorus (BP) and graphene. However, efficient manufacture of novel germanene nanostructures is still a challenge. Herein, a simple top-down approach for the liquid-exfoliation of ultra-small germanene quantum dots (GeQDs) is presented. The prepared GeQDs possess an average lateral size of about 4.5 nm and thickness of about 2.2 nm. The functionalized GeQDs were demonstrated to be robust photothermal agents (PTAs) with outstanding photothermal conversion efficacy (higher than those of graphene and BPQDs), superior stability, and excellent biocompatibility. As a proof-of-principle, 2D GeQDs-based PTAs were used in fluorescence/photoacoustic/photothermal-imaging-guided hyperpyrexia ablation of tumors. This work could expand the application of 2D germanene to the field of photonic cancer nanomedicine.

Stimuli-responsive prodrug-based cancer nanomedicine.

The rapid development of nanotechnology results in the emergence of nanomedicines, but the effective delivery of drugs to tumor sites remains a great challenge. Prodrug-based cancer nanomedicines thus emerged due to their unique advantages, including high drug load efficiency, reduced side effects, efficient targeting, and real-time controllability. A distinctive characteristic of prodrug-based nanomedicines is that they need to be activated by a stimulus or multi-stimulus to produce an anti-tumor effect. A better understanding of various responsive approaches could allow researchers to perceive the mechanism of prodrug-based nanomedicines effectively and further optimize their design strategy. In this review, we highlight the stimuli-responsive pathway of prodrug-based nanomedicines and their anticancer applications. Furthermore, various types of prodrug-based nanomedicines, recent progress and prospects of stimuli-responsive prodrug-based nanomedicines and patient data in the clinical application are also summarized. Additionally, the current development and future challenges of prodrug-based nanomedicines are discussed. We expect that this review will be valuable for readers to gain a deeper understanding of the structure and development of prodrug-based cancer nanomedicines to design rational and effective drugs for clinical use.

Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource.

OBJECTIVE: To mine Twitter and quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions across studies, and create a symptom lexicon for future research. MATERIALS AND METHODS: We retrieved tweets using COVID-19-related keywords, and performed semiautomatic filtering to curate self-reports of positive-tested users. We extracted COVID-19-related symptoms mentioned by the users, mapped them to standard concept IDs in the Unified Medical Language System, and compared the distributions to those reported in early studies from clinical settings. RESULTS: We identified 203 positive-tested users who reported 1002 symptoms using 668 unique expressions. The most frequently-reported symptoms were fever/pyrexia (66.1%), cough (57.9%), body ache/pain (42.7%), fatigue (42.1%), headache (37.4%), and dyspnea (36.3%) amongst users who reported at least 1 symptom. Mild symptoms, such as anosmia (28.7%) and ageusia (28.1%), were frequently reported on Twitter, but not in clinical studies. CONCLUSION: The spectrum of COVID-19 symptoms identified from Twitter may complement those identified in clinical settings.