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Recent efforts in the area of photothermal therapy (PTT) follow two important aims: (i) selective targeting of plasmonic nanoparticles to the tumor and (ii) real-time guidance of PTT operation through employing multimodal imaging modalities. In the present study, we utilized a multifunctional theranostic nanoplatform constructed from iron (III) oxide–gold (Fe2O3@Au) core–shell nanoparticles to fulfill these aims. The Au shell exhibits surface plasmon resonance, a property that is exploited to realize PTT. The magnetic core enables Fe2O3@Au to be employed as a magnetic resonance imaging (MRI) contrast agent. Furthermore, the magnetic core has the potential to establish a magnetic drug targeting strategy through which Fe2O3@Au can be directed to the tumor site by means of magnetic field. To test these potentials, Balb/c mice bearing CT26 colorectal tumor model were intravenously injected with Fe2O3@Au. Immediately after injection, a magnet was placed on the tumor site for 3 h to concentrate nanoparticles, followed by the near infrared (NIR) laser irradiation. MRI study confirmed the accumulation of nanoparticles within the tumor due to T2 enhancement capability of Fe2O3@Au. The in vivo thermometry results demonstrated that the tumors in magnetic targeting group had a significantly higher temperature elevation rate upon NIR irradiation than non-targeted group (~ 12 °C vs. 8.5 °C). The in vivo antitumor assessment revealed that systemic injection of Fe2O3@Au in combination with magnetic targeting and NIR irradiation resulted in complete remission of tumor growth. Therefore, Fe2O3@Au can establish a targeted PTT strategy for efficient eradication of tumor cells under the guidance of MRI.

Bone marrow (BM) from human and rodent species contains a population of multipotential cells referred to as mesenchymal stem cells (MSCs). Currently, MSCs are isolated indirectly by using a culture step and then the generation of fibroblast colony-forming units (CFU-fs). Unprocessed or native BM MSCs have not yet been fully characterised. We have previously developed a direct enrichment method for the isolation of MSCs from human BM by using the CD49a protein (alpha1-integrin subunit). As the CD49a gene is highly conserved in mammals, we have evaluated whether this direct enrichment can be employed for BM cells from rodent strains (rat and mouse). We have also studied the native phenotype by using both immunodetection and immunomagnetic methods and have compared MSCs from mouse, rat and human BM. As is the case for human BM, we have demonstrated that all rodent multipotential CFU-fs are contained within the CD49a-positive cell population. However, in the mouse, the number of CFU-fs is strain-dependent. Interestingly, all rat and mouse Sca-1-positive cells are concentrated within the CD49a-positive fraction and also contain all CFU-fs. In human, the colonies have been detected in the CD49a/CD133 double-positive population. Thus, the CD49a protein is a conserved marker that permits the direct enrichment of BM MSCs from various mammalian species; these cells have been phenotyped as true BM stem cells.

Low-level laser therapy (LLLT) is a form of light therapy that triggers biochemical changes within cells. Photons are absorbed by cellular photoreceptors, triggering chemical alterations and potential biochemical benefits to the human body. LLLT has been used in pain management for years and is also known as cold laser therapy, which uses low-frequency continuous laser of typically 600 to 1000 nm wavelength for pain reduction and healing stimulation. Many studies have demonstrated analgesic and anti-inflammatory effects provided by photobiomodulation in both experimental and clinical trials. The purpose of this research article was to present a summary of the possible pain management benefits of LLLT. In cold laser therapy, coherent light of wavelength 600 to 1000 nm is applied to an area of concern with hope for photo-stimulating the tissues in a way that promotes and accelerates healing. This is evidenced by the similarity in absorption spectra between oxidized cytochrome c oxidase and action spectra from biological responses to light. LLLT, using the properties of coherent light, has been seen to produce pain relief and fibroblastic regeneration in clinical trials and laboratory experiments. LLLT has also been seen to significantly reduce pain in the acute setting; it is proposed that LLLT is able to reduce pain by lowering the level of biochemical markers and oxidative stress, and the formation of edema and hemorrhage. Many studies have demonstrated analgesic and anti-inflammatory effects provided by photobiomodulation in both experimental and clinical trials. Based on current research, the utilization of LLLT for pain management and osteoarthritic conditions may be a complementary strategy used in clinical practice to provide symptom management for patients suffering from osteoarthritis and chronic pain.

A 34-year-old man with a history of gunshot wound (GSW) to the right upper chest developed secondary aortic valve endocarditis (AVE) and was treated with an artificial valve placement (AVP). Three months after, he presented to an outpatient pain management clinic right arm pain and was diagnosed with complex regional pain syndrome type II (CRPS II). The patient underwent a diagnostic sympathetic ganglion block, before undergoing endoscopic thoracic sympathectomy surgery. Successful outcomes revealed decreased pain, opioid utilisation and improved tolerance to therapy and activities of daily living. To our knowledge, this is the first case reporting CRPS II arising from a GSW complicated by AVE followed by AVP, which emphasises how unforeseen syndromes can arise from the management of seemingly unrelated pathology. This case demonstrates the importance of timely and proper diagnosis of uncharacterised residual pain status post-trauma and differential diagnosis and management of chronic pain syndromes.

Comment Selecting an appropriate pharmacological intervention for a patient with OH can reduce IOP by decreasing aqueous humour production by the ciliary processes-for example, carbonic anhydrase (CA) inhibitors. Because of its efficacy, the β adrenergic blocker-for example, timolol, is the gold standard compared with the other treatment. The mechanism of choroidal detachment with dorzolamide is probably due to hypotony caused by the reduction of intraocular pressure by the combination of timolol and dorzolamide. 1, 5 This mechanism has been mentioned in cases of choroidal detachment caused by latanoprost, a prostaglandin analogue used topically to reduce IOP, reported by Marques after filtration surgery. 6 Another case of choroidal detachment has been reported in a patient who underwent left extracapsular cataract extraction with topically latanoprost prescribed immediately postoperatively. 7 Ocular surgery, even if there is a history, seems to increase the risk of choroidal detachment when used as a pharmacological aqueous humour suppressant therapy-for example, dorzolamide or the combination of timolol and dorzolamide.

Majority voting and averaging are common approaches used to resolve annotator disagreements and derive single ground truth labels from multiple annotations. However, annotators may systematically disagree with one another, often reflecting their individual biases and values, especially in the case of subjective tasks such as detecting affect, aggression, and hate speech. Annotator disagreements may capture important nuances in such tasks that are often ignored while aggregating annotations to a single ground truth. In order to address this, we investigate the efficacy of multi-annotator models. In particular, our multi-task based approach treats predicting each annotators’ judgements as separate subtasks, while sharing a common learned representation of the task. We show that this approach yields same or better performance than aggregating labels in the data prior to training across seven different binary classification tasks. Our approach also provides a way to estimate uncertainty in predictions, which we demonstrate better correlate with annotation disagreements than traditional methods. Being able to model uncertainty is especially useful in deployment scenarios where knowing when not to make a prediction is important.

Urban flooding poses risks to the safety of drivers and pedestrians, and damages infrastructures and lifelines. It is important to accommodate cities and local agencies with enhanced rapid flood detection skills and tools to better understand how much flooding a region may experience at a certain period of time. This results in flood management orders being announced in a timely manner, allowing residents and drivers to preemptively avoid flooded areas. This research combines information received from ground observed data derived from road closure reports from the police department, with remotely sensed satellite imagery to develop and train machine-learning models for flood detection for the City of San Diego, CA, USA. For this purpose, flooding information are extracted from Sentinel 1 satellite imagery and fed into various supervised and unsupervised machine learning models, including Random Forest (RF), Support Vector Machine (SVM), and Maximum Likelihood Classifier (MLC), to detect flooded pixels in images and evaluate the performance of these ML models. Moreover, a new unsupervised machine learning framework is developed which works based on the change detection (CD) approach and combines the Otsu algorithm, fuzzy rules, and iso-clustering methods for urban flood detection. Results from the performance evaluation of RF, SVM, MLC and CD models show 0.53, 0.85, 0.75 and 0.81 precision measures, 0.9, 0.85, 0.85 and 0.9 for recall values, 0.67, 0.85, 0.79 and 0.85 for the F1-score, and 0.69, 0.87, 0.83 and 0.87 for the accuracy measure, respectively, for each model. In conclusion, the new unsupervised flood image classification and detection method offers better performance with the least required data and computational time for enhanced rapid flood mapping. This systematic approach will be potentially useful for other cities at risk of urban flooding, and hopefully for detecting nuisance floods, by using satellite images and reducing the flood risk of transportation design and urban infrastructure planning.

Understanding motivations underlying acts of hatred are essential for developing strategies to prevent such extreme behavioral expressions of prejudice (EBEPs) against marginalized groups. In this work, we investigate the motivations underlying EBEPs as a function of moral values. Specifically, we propose EBEPs may often be best understood as morally motivated behaviors grounded in people’s moral values and perceptions of moral violations. As evidence, we report five studies that integrate spatial modeling and experimental methods to investigate the relationship between moral values and EBEPs. Our results, from these U.S. based studies, suggest that moral values oriented around group preservation are predictive of the county-level prevalence of hate groups and associated with the belief that extreme behavioral expressions of prejudice against marginalized groups are justified. Additional analyses suggest that the association between group-based moral values and EBEPs against outgroups can be partly explained by the belief that these groups have done something morally wrong. Understanding motivations underlying acts of hatred are essential for developing strategies to prevent such acts against marginalized groups. Here the authors show that group-based moral values are associated with tendency to justify extreme behavioural expressions of prejudice.

Designed to assist both recent graduates, as well as experienced chemists or scientists with limited regulatory, compendial or pharmaceutical analysis background, make that transition, this book is a concise, yet comprehensive introduction to the drug development process and analysis of chemically synthesized, small molecule drugs. It features contributions by distinguished experts in the field, including editor and author an analytical chemist with decades of technical management and teaching experience in compendial, regulatory, and industry. This book provides an introduction to pharmaceutical analysis for small molecules (non-biologics) using commonly used techniques for drug characterization and performance tests. The driving force for industry to perform pharmaceutical analyses is submission of such data and supporting documents to regulatory bodies for drug approval in order to market their products. In addition, related required supporting studies including good laboratory/documentation practices including analytical instrument qualification are highlighted in this book.

Prebiotics are a group of nutrients that are degraded by gut microbiota. Their relationship with human overall health has been an area of increasing interest in recent years. They can feed the intestinal microbiota, and their degradation products are short-chain fatty acids that are released into blood circulation, consequently, affecting not only the gastrointestinal tracts but also other distant organs. Fructo-oligosaccharides and galacto-oligosaccharides are the two important groups of prebiotics with beneficial effects on human health. Since low quantities of fructo-oligosaccharides and galacto-oligosaccharides naturally exist in foods, scientists are attempting to produce prebiotics on an industrial scale. Considering the health benefits of prebiotics and their safety, as well as their production and storage advantages compared to probiotics, they seem to be fascinating candidates for promoting human health condition as a replacement or in association with probiotics. This review discusses different aspects of prebiotics, including their crucial role in human well-being.