Miracle-dz/UniFAR-FTUs huggingface dataset:
Boosting β-carotene and storage materials productivities by two-stage mixed and monochromatic exposure stresses on Dunaliella salina

Abstract Growth and product formation of Dunaliella salina, a potent β-carotene source, were investigated under single and two-stage monochromic and mixed illuminations using two LEDs, each emitting red (R), blue (B), or white (W) light. Targeting cell growth in single-stage, WW, RR, and BB, as well as RB illumination, were compared and mixed RB illumination was found most supportive showing the highest cell growth of 1.81 ± 0.008 g/L. Subsequently, new two-stage illuminations (RB-BB and RB-RR) were designed to investigate growth and bio-product formation using RB illumination similarly in the 1st stage followed by separate BB and RR illuminations within the 2nd stage. RB-BB strategy resulted in enhanced productivities of lipid (7.6 mg/L/day), starch (20 mg/L/day), and β-carotene (0.4 mg/L/day) which were respectively higher by 80, 70, and 81% compared to single-stage control (WW). RB-RR strategy stimulated cell growth while it resulted in decreased productivities of products (other than chlorophyll). The highest biomass level of 2.2 g/L and nitrate removal of 80% were obtained in RB-RR while RB-BB resulted in the lowest values of 1.2 g/L and 48%, respectively. Appropriate selection of illuminations in two-stage strategies, therefore, functions to enhance the productivity of important metabolites or cell growth which can have generic applications in other microalgae. NOVELTY STATEMENT Although the effects of a variety of stressful conditions on microalgae product lines have been investigated so far, the effects of two-stage mixed and monochromatic exposure as a light management strategy have not yet been considered. This strategy was inspired by the fact that cell mass alongside the cell content of a product contributes to product productivity. Accordingly, the growth of Dunaliella salina was first examined under single-stage mixed and monochromatic exposure where mixed red-blue light led to the highest biomass formation. Shifting from mixed to different monochromatic exposures was then examined as a stress factor to stimulate product formation. Higher cell factories obtained under mixed exposure in the 1st stage escalated product productivities within the 2nd stage when exposed to monochromatic light. Graphical Abstract
Planning under uncertainty in complex structured environments

Many real-world tasks require multiple decision makers (agents) to coordinate their actions in order to achieve common long-term goals. Examples include: manufacturing systems, where managers of a factory coordinate to maximize profit; rescue robots that, after an earthquake, must safely find victims as fast as possible; or sensor networks, where multiple sensors collaborate to perform a large-scale sensing task under strict power constraints. All of these tasks require the solution of complex long-term multiagent planning problems in uncertain dynamic environments. Factored Markov decision processes (MDPs) allow us to represent complex uncertain dynamic systems very compactly by exploiting problem-specific structure. Specifically, the state of the system is described by a set of variables that evolve stochastically over time using a representation, called dynamic Bayesian network, that often allows for an exponential reduction in representation complexity. However, the complexity of exact solution algorithms for such MDPs grows exponentially in the number of variables, and in the number of agents. This thesis builds a formal framework and approximate planning algorithms that exploit structure in factored MDPs to solve problems with many trillions of states and actions very efficiently. The main contributions of this thesis include: Factored linear programs: A novel LP decomposition technique, using ideas from inference in Bayesian networks, that can exploit problem structure to reduce exponentially-large LPs to polynomially-sized ones that are provably equivalent. Factored approximate planning: A suite of algorithms, building on our factored LP decomposition technique, that exploit structure in factored MDPs to obtain exponential reductions in planning time. Distributed coordination: An efficient distributed multiagent decision making algorithm, where the coordination structure arises naturally from the factored representation of the system dynamics. Generalization in relational MDPs: A framework for obtaining general solutions from a small set of environments, allowing agents to act in new environments without replanning. Empirical evaluation: A detailed evaluation on a variety of large-scale tasks, including multiagent coordination in a real strategic computer game, demonstrating that our formal framework yields effective plans, complex agent coordination, and successful generalization in some of the largest planning problems in the literature.
Nano-drug co-delivery system of natural active ingredients and chemotherapy drugs for cancer treatment: a review

Abstract Chemotherapy drugs have been used for a long time in the treatment of cancer, but serious side effects are caused by the inability of the drug to be solely delivered to the tumor when treating cancer with chemotherapy. Natural products have attracted more and more attention due to the antitumor effect in multiple ways, abundant resources and less side effects. Therefore, the combination of natural active ingredients and chemotherapy drugs may be an effective antitumor strategy, which can inhibit the growth of tumor and multidrug resistance, reduce side effects of chemotherapy drugs. Nano-drug co-delivery system (NDCDS) can play an important role in the combination of natural active ingredients and chemotherapy drugs. This review provides a comprehensive summary of the research status and application prospect of nano-delivery strategies for the combination of natural active ingredients and chemotherapy drugs, aiming to provide a basis for the development of anti-tumor drugs.
Psilocybin in neuropsychiatry: a review of its pharmacology, safety, and efficacy

Abstract Psilocybin is a tryptamine alkaloid found in some mushrooms, especially those of the genus Psilocybe. Psilocybin has four metabolites including the pharmacologically active primary metabolite psilocin, which readily enters the systemic circulation. The psychoactive effects of psilocin are believed to arise due to the partial agonist effects at the 5HT2A receptor. Psilocin also binds to various other receptor subtypes although the actions of psilocin at other receptors are not fully explored. Psilocybin administered at doses sufficient to cause hallucinogenic experiences has been trialed for addictive disorders, anxiety and depression. This review investigates studies of psilocybin and psilocin and assesses the potential for use of psilocybin and a treatment agent in neuropsychiatry. The potential for harm is also assessed, which may limit the use of psilocybin as a pharmacotherapy. Careful evaluation of the number needed to harm vs the number needed to treat will ultimately justify the potential clinical use of psilocybin. This field needs a responsible pathway forward.
Implementing polymeric pseudorotaxanes for boosting corneal permeability and antiaspergillus activity of tolnaftate: formulation development, statistical optimization, ex vivo permeation and in vivo assessment

Abstract Fungal keratitis (FK) is a devastating ocular disease that can cause corneal opacity and blindness if not treated effectively. Tolnaftate (TOL) is a selective fungicidal drug against Aspergillus spp. which are among the most common causes of mycotic keratitis. TOL is lipophilic drug with low water solubility and permeation which act as obstacles for its clinical ocular efficacy. Hence, this study aimed to statistically optimize a novel polymeric pseudorotaxanes (PSRs) containing TOL for enhancing its ocular permeability and antifungal effect. For achieving this goal, a full 31.22 factorial design was fashioned for preparing and optimizing TOL-PSRs using film hydration technique. Three formulation variables were studied: drug amount (X1), weight ratio of Pluronics to HPβCD (X2) and Pluronic system (X3). Entrapment efficiency percent (EE%) (Y1), particle size (PS) (Y2) and zeta potential (ZP) (Y3) were set as dependent variables. The selected optimal TOL-PSRs (PSR1) showed EE% of 71.55 ± 2.90%, PS of 237.05 ± 12.80 nm and ZP of −32.65 ± 0.92 mV. In addition, PSR1 was compared to conventional polymeric mixed micelles (PMMs) and both carriers significantly increased the drug flux and resulted in higher amount permeated per unit area in 8 h compared to drug suspension. The histopathological studies assured the safety of PSR1 for ocular use. The in vivo susceptibility testing using Aspergillus niger confirmed that PSR1 displayed sustained antifungal activity up to 24 h. The obtained results revealed the admirable potential of PSR1 to be used as novel nanocarriers for promoting TOL ocular delivery.
Flexible nano-liposomes-based transdermal hydrogel for targeted delivery of dexamethasone for rheumatoid arthritis therapy

Abstract Rheumatoid arthritis (RA) is an inflammatory immune-mediated disease that can lead to synovitis, cartilage destruction, and even joint damage. Dexamethasone (DEX) is a commonly used agent for RA therapy on inflammation manage. However, the traditional administering DEX is hampered by low efficiency and obvious adverse effects. Therefore, in order to efficiently deliver DEX to RA inflamed joints and overcome existing deficiencies, we developed transdermal formation dextran sulfate (DS) modified DEX-loaded flexible liposome hydrogel (DS-FLs/DEX hydrogel), validated their transdermal efficiency, evaluated its ability to target activated macrophages, and its anti-inflammatory effect. The DS-FLs/DEX exhibited excellent biocompatibility, sustainable drug release, and high uptake by lipopolysaccharide (LPS)-activated macrophages. Furthermore, the DS-FLs/DEX hydrogel showed desired skin permeation as compared with regular liposome hydrogel (DS-RLs/DEX hydrogel) due to its good deformability. In vivo, when used the AIA rats as RA model, the DS-FLs/DEX hydrogel can effectively penetrate and accumulate in inflamed joints, significantly improve joint swelling in RA rats, and reduce the destructive effect of RA on bone. Importantly, the expression of inflammatory cytokines in joints was inhibited and the system toxicity did not activate under DS-FLs/DEX hydrogel treatment. Overall, these data revealed that the dextran sulfate (DS) modified DEX-loaded flexible liposome hydrogel (DS-FLs/DEX hydrogel) can prove to be an excellent drug delivery vehicle against RA.
Analysis of the docking property of host variants of hACE2 for SARS-CoV-2 in a large cohort

The recent novel coronavirus disease (COVID-19) outbreak, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is threatening global health. However, an understanding of the interaction of SARS-CoV-2 with human cells, including the physical docking property influenced by the host’s genetic diversity, is still lacking. Here, based on germline variants in the UK Biobank covering 502,543 individuals, we revealed the molecular interactions between human angiotensin-converting enzyme 2 (hACE2), which is the representative receptor for SARS-CoV-2 entry, and COVID-19 infection. We identified six nonsense and missense variants of hACE2 from 2585 subjects in the UK Biobank covering 500000 individuals. Using our molecular dynamics simulations, three hACE2 variants from 2585 individuals we selected showed higher levels of binding free energy for docking in the range of 1.44–3.69 kcal/mol. Although there are diverse contributors to SARS-CoV-2 infections, including the mobility of individuals, we analyzed the diagnosis records of individuals with these three variants of hACE2. Our molecular dynamics simulations combined with population-based genomic data provided an atomistic understanding of the interaction between hACE2 and the spike protein of SARS-CoV-2.
A Multinational Study of Patient Preferences for How Decisions Are Made in Their Care

Inadequate consideration has been given to patient preferences for patient-centered care (PCC) across countries or cultures in our increasingly global society. We examined what 1,698 participants from the United States, Hong Kong, Philippines, and Australia described as important when making health care decisions. Analysis of frequencies following directed content coding of open-ended questions revealed differences in patients’ preferences for doctor behaviors and decision-making considerations across countries. Being well informed by their doctor emerged as most important in decision-making, especially in Hong Kong. Participants in Australia and the United States wanted their doctor to meet their emotional needs. The safety and efficacy of treatments were the most common consideration, especially for Hong Kong. Findings suggest that doctors should focus on information exchange and identifying patient concerns about efficacy, lifestyle impact, cost, and recovery speed. Rather than assuming patients prefer shared decision-making, doctors must assess patient’s decision control preferences.
Usability assessment of interaction management support in LOUISE, an ECA-based user interface for elders with cognitive impairment

Embodied conversational agents (ECA) are possible enablers of assistive technologies, in particular for older adults with cognitive impairment. Yet, dedicated interaction management techniques addressing the specificities of this public are needed. OBJECTIVES: We assess whether the interaction management framework of the LOUISE (Lovely User Interface for Servicing Elders) ECA has the potential to overcome the user interface constraints linked to cognitive impairment. METHODS: LOUISE supports key target-specific features: personalization; attention management; context reminders; image and video displays; a conversation manager for task-oriented interactions; and the foundations for a domain-specific XML-based language for task-oriented assistive scenarios. LOUISE’s usability and acceptance were evaluated at the Broca geriatric hospital in Paris. with a group of 14 older adults with either mild cognitive impairment (MCI) or Alzheimer’s disease (AD) through four simple but realistic assistive scenarios: drinking, taking medicine, measuring blood pressure and choosing the lunch menu. RESULTS: Most of our participants were able to interact with the ECA, succeeded in completing the proposed tasks and enjoyed our design. CONCLUSION: The field usability evaluation of LOUISE’s interaction management framework suggests that this suite of interaction techniques can be effective in enabling interfaces for users with MCI or AD.
Heterogeneity analysis of astrocytes following spinal cord injury at single‐cell resolution

Astrocytes play many important functions in response to spinal cord injury (SCI) in an activated manner, including clearance of necrotic tissue, formation of protective barrier, maintenance of microenvironment balance, interaction with immune cells, and formation of the glial scar. More and more studies have shown that the astrocytes are heterogeneous, such as inflammatory astrocyte 1 (A1) and neuroprotective astrocyte 2 (A2) types. However, the subtypes of astrocyte resulting from SCI have not been clearly defined. In this study, using single‐cell RNA sequencing, we constructed the transcriptomic profile of astrocytes from uninjured spinal cord tissue and injured tissue nearby the lesion epicenter at 0.5, 1, 3, 7, 14, 60, and 90 days after mouse hemisection spinal cord surgery. Our analysis uncovered six transcriptionally distinct astrocyte states, including Atp1b2+, S100a4+, Gpr84+, C3+/G0s2+, GFAP+/Tm4sf1+, and Gss+/Cryab+ astrocytes. We used these new signatures combined with canonical astrocyte markers to determine the distribution of morphologically and physiologically distinct astrocyte population at injured sites by immunofluorescence staining. Then we identified the dynamic evolution process of each astrocyte subtype following SCI. Finally, we also revealed the evolution of highly expressed genes in these astrocyte subtypes at different phases of SCI. Together, we provided six astrocyte subtypes at single‐cell resolution following SCI. These data not only contribute to understand the heterogeneity of astrocytes during SCI but also help to find new astrocyte subtypes as a target for SCI repair.
Deciphering the arrangement of dust in the clumpy tori of active galactic nuclei

OF DISSERTATION DECIPHERING THE ARRANGEMENT OF DUST IN THE CLUMPY TORI OF ACTIVE GALACTIC NUCLEI In the framework of active galactic nuclei (AGNs), a galaxy’s supermassive black hole is surrounded by a dusty torus whose clumpy configuration allows for either direct or obscured views toward the central engine. Viewing AGNs from different angles gives rise to a variety of AGN classifications; for example, the generic Type 1 AGN class requires the detection of optically broad emission lines, which arise from quickly moving material within the torus, whereas Type 2 AGNs lack these observations. While these viewing angles are not directly observable, synthetic torus models generated with CLUMPY provide a means to determine them along with other parameters that describe the nature and characteristics of the torus in general. Employing CLUMPY models with mid-infrared spectroscopic observations of a large sample of both Type 1 and Type 2 AGNs allows us to acquire a further understanding of the clumpy torus structure and its viewing angles.
Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers

The prevalence of patients who are Incapacitated with No Evident Advance Directives or Surrogates (INEADS) remains unknown because such data are not routinely captured in structured electronic health records. This study sought to develop and validate a natural language processing (NLP) algorithm to identify information related to being INEADS from clinical notes. We used a publicly available dataset of critical care patients from 2001 through 2012 at a United States academic medical center, which contained 418,393 relevant clinical notes for 23,904 adult admissions. We developed 17 subcategories indicating reduced or elevated potential for being INEADS, and created a vocabulary of terms and expressions within each. We used an NLP application to create a language model and expand these vocabularies. The NLP algorithm was validated against gold standard manual review of 300 notes and showed good performance overall (F-score = 0.83). More than 80% of admissions had notes containing information in at least one subcategory. Thirty percent (n = 7,134) contained at least one of five social subcategories indicating elevated potential for being INEADS, and <1% (n = 81) contained at least four, which we classified as high likelihood of being INEADS. Among these, n = 8 admissions had no subcategory indicating reduced likelihood of being INEADS, and appeared to meet the definition of INEADS following manual review. Among the remaining n = 73 who had at least one subcategory indicating reduced likelihood of being INEADS, manual review of a 10% sample showed that most did not appear to be INEADS. Compared with the full cohort, the high likelihood group was significantly more likely to die during hospitalization and within four years, to have Medicaid, to have an emergency admission, and to be male. This investigation demonstrates potential for NLP to identify INEADS patients, and may inform interventions to enhance advance care planning for patients who lack social support.
Pollen‐based reconstruction reveals the impact of the onset of agriculture on plant functional trait composition

Abstract The onset of agriculture improved the capacity of ecosystems to produce food, but inadvertently altered other vital ecosystem functions. Plant traits play a central role in determining ecosystem properties, therefore we investigated how the onset of agriculture in Europe changed plant trait composition using 78 pollen records. Using a novel Bayesian approach for reconstructing plant trait composition from pollen records, we provide a robust method that can account for trait variability within pollen types. We estimate an overall four‐fold decrease in plant size through agriculture and associated decreases in leaf and seed size. We show an increase in niche space towards the resource‐acquisitive end of the leaf economic spectrum. Decreases in leaf phosphorus might have been caused by nutrient depletion through grazing and burning. Our results show that agriculture, from its start, has likely been gradually impacting biogeochemical cycles through altered vegetation composition.
Multi‐organs perioperative immune‐related adverse events and postoperative bronchial anastomotic fistula in a patient receiving neoadjuvant immunotherapy with NSCLC

The safety of neoadjuvant chemoimmunotherapy before surgery in patients with non–small cell lung cancer (NSCLC) remains unclear in the perioperative stage. We describe a case of a 63‐year‐old man with IIIC stage NSCLC who received neoadjuvant chemoimmunotherapy and radical lobectomy. After the second cycle of pembrolizumab and chemotherapy (paclitaxel + carboplatin), the patient was diagnosed with immunologic enterocolitis and relieved by glucocorticoid therapy. Radical lobectomy of the right upper lobe was then performed. On postoperative day 4 (POD 4), the patient suddenly suffered suffocated wheezing during sleep. Interstitial lung disease was, therefore, identified by chest computed tomography scan. Glucocorticoids and mechanical ventilation were applied and the symptoms were relieved. On POD 10, the patient developed a bronchial fistula and underwent emergent repair surgery. This is the first case of multi‐organs, multi‐time point immune‐related adverse events (irAE) in perioperative NSCLC patients who received neoadjuvant chemoimmunotherapy. Clinicians should be on high alert for signs of irAEs in neoadjuvant chemoimmunotherapy patients, promptly requiring multidisciplinary management.