Advancing cancer treatments: The role of oligonucleotide-based therapies in driving progress.

Although recent advancements in cancer immunology have resulted in the approval of numerous immunotherapies, minimal progress has been observed in addressing hard-to-treat cancers. In this context, therapeutic oligonucleotides, including interfering RNAs, antisense oligonucleotides, aptamers, and DNAzymes, have gained a central role in cancer therapeutic approaches due to their capacity to regulate gene expression and protein function with reduced toxicity compared with conventional chemotherapeutics. Nevertheless, systemic administration of naked oligonucleotides faces many extra- and intracellular challenges that can be overcome by using effective delivery systems. Thus, viral and non-viral carriers can improve oligonucleotide stability and intracellular uptake, enhance tumor accumulation, and increase the probability of endosomal escape while minimizing other adverse effects. Therefore, gaining more insight into fundamental mechanisms of actions of various oligonucleotides and the challenges posed by naked oligonucleotide administration, this article provides a comprehensive review of the recent progress on oligonucleotide delivery systems and an overview of completed and ongoing cancer clinical trials that can shape future oncological treatments.

Circular RNA-based therapy provides sustained and robust neuroprotection for retinal ganglion cells.

Ocular neurodegenerative diseases like glaucoma lead to progressive retinal ganglion cell (RGC) loss, causing irreversible vision impairment. Neuroprotection is needed to preserve RGCs across debilitating conditions. Nerve growth factor (NGF) protein therapy shows efficacy, but struggles with limited bioavailability and a short half-life. Here we explore a novel approach to address this deficiency by utilizing circular RNA (circRNA)-based therapy. We show that circRNAs exhibit an exceptional capacity for prolonged protein expression and circRNA-expressed NGF protects cells from glucose deprivation. In a mouse optic nerve crush model, lipid nanoparticle (LNP)-formulated circNGF administered intravitreally protects RGCs and axons from injury-induced degeneration. It also significantly outperforms NGF protein therapy without detectable retinal toxicity. Furthermore, single-cell transcriptomics revealed LNP-circNGF's multifaceted therapeutic effects, enhancing genes related to visual perception while reducing trauma-associated changes. This study signifies the promise of circRNA-based therapies for treating ocular neurodegenerative diseases and provides an innovative intervention platform for other ocular diseases.

Synthesis and characterization of chromium aluminum carbide MAX phases (CrxAlCx-1) for potential biomedical applications.

MAX phases, characterized as nanolaminates of ternary carbides/nitrides structure, possess a unique combination of ceramic and metallic properties, rendering them pivotal in materials research. In this study, chromium aluminum carbide ternary compounds, Cr2AlC (211), Cr3AlC2 (312), and Cr4AlC3 (413) were successfully synthesized with high purity using a facile and cost-effective sol-gel method. Structural, morphological, and chemical characterization of the synthesized phases was conducted to understand the effects of composition changes and explore potential applications. Comprehensive characterization techniques including XRD for crystalline structure elucidations, SEM for morphological analysis, EDX for chemical composition, Raman spectroscopy for elucidation of vibrational modes, XPS to analyze elemental composition and surface chemistry, and FTIR spectroscopy to ensure the functional groups analysis, were performed. X-ray diffraction analysis indicated the high purity of the synthesized Cr2AlC phase as well as other ternary compounds Cr3AlC2 and Cr4AlC3, suggesting its suitability as a precursor for MXenes production. Additionally, the antimicrobial activity against Candida albicans and biocompatibility assessments against Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and HepG2 cell line were investigated. The results demonstrated significant antifungal activity of the synthesized phases against Candida albicans and negligible impact on the viability of E. coli and S. aureus. Interestingly, lower concentrations of Cr2AlC MAX phase induced cytotoxicity in HepG2 cells by triggering intercellular oxidative stress, while Cr3AlC2 and Cr4AlC3 exhibited lower cytotoxicity compared to Cr2AlC, highlighting their potential in biomedical applications.

A comprehensive review on nutritional, nutraceutical, and industrial perspectives of perilla (Perilla frutscens L.) seeds - An orphan oilseed crop.

There is a growing need to mainstream orphan or underutilized crops to enhance nutritional security and sustainable agriculture. Among these, Perilla frutescens L. is an important crop due to its rich nutritional and phytochemical content which makes it significant in nutrition, medicine, and industrial sector. Perilla seeds are mainly rich in ω-3 fatty acids, dietary fiber, amino acids, vitamins, and minerals, high α-linolenic acid, which contributes to their health benefits. This review explores the nutritional profile of perilla seeds and highlights its unique composition compared to other oilseed crops. It also analyzes the phytochemical components of perilla seeds and their various biological activities, including antioxidant, antidiabetic, antiobesity, cardioprotective, anticancer, antimicrobial, neuroprotective, and anti-inflammatory effects. These activities demonstrate the potential of perilla seeds in both pharmaceutical and food sectors. The review also covers recent advancements in genomics and transgenic research discussing potential areas for crop improvement. Additionally, it explores the use of perilla seeds in functional foods, blending perilla oil with other oils, and their applications in enhancing product formulations. This review offers valuable insights for researchers, students, policymakers, environmentalists, and industry professionals by detailing the potential of perilla seeds across various sectors. The findings support sustainable agriculture, crop diversification, and innovative product development, thus contributing to the integration of perilla into mainstream agriculture.

Exploring the multi-faceted potential: Synthesized ZnO nanostructure - Characterization, photocatalysis, and crucial biomedical applications.

This research describes the methodology for synthesizing zinc oxide nanoparticles (ZnO-NPs). It demonstrates a unique, cost-effective, and non-toxic chemical technique for producing ZnO-NPs using the precipitation method with NaOH as reducing and capping agents. The formed nanoparticles have been characterized and analyzed using numerous techniques such as; Fluorescence emission spectroscopy (FL), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray Spectroscopy (EDX), ultraviolet-visible optical absorption (UV-Vis), Fourier transform infrared spectroscopy (FTIR), and Thermal gravimetric analysis (TGA). Also, the analytical technique X-ray diffraction studies has been used which showed that the ZnO-NPs had a Wurtzite hexagonal crystal structure with an average crystallite size of 34.27 nm. The form and the size of the synthesized ZnO-NPs have been seen in SEM and TEM photographs. Using J-image, particle size has been obtained at 13.33 nm, and the grain boundaries were all approximately spherical. Peaks in the FT-IR spectrum of the NPs indicate the presence of carboxylate (COO) and hydroxyl (O-H) functional groups. According to these findings, Zn interstitial defects are responsible for the 380 nm emission peak. Since EDX could not identify any impurities below the detection threshold, we may be sure that Zn and O are the principal components of the synthesized sample. ZnO-NPs cause an absorption band at 350.34 nm in the UV-Vis spectrum and a band gap of 3.24 eV. The catalytic activity of the synthesized ZnO nanoparticles (NPs) was evaluated by investigating their effectiveness in degrading crystal violet (CV) and methylene blue (MB) dyes, along with assessing the degradation rates. The results demonstrated a high degradation efficiency, with ZnO NPs achieving approximately 96.72 % degradation for CV and 97.169 % for MB dyes, underscoring their remarkable efficacy in the degradation process. As for antimicrobial activity assessment, the results revealed that the ZnO-NPs had negligible impact on Gram-negative bacteria, whereas they exhibited a discernible effect on Gram-positive bacteria. Additionally, it showed anti-cancer potential against colon (SW480), breast (MDA-231), and cervix (HELA) lines cells as seen by (MTT) assay. Hence, due to its simplified processes and cheaper chemicals, our synthesis technique may use in industrial settings for various applications.

Comparing health risks and musculoskeletal issues between professional and casual mobile esports players: a cross-sectional descriptive study in Jakarta.

Mobile gaming poses significant health risks, such as musculoskeletal (MSK) and eye problems, as players maintain the same posture for long periods. The objective of the current study is to describe the prevalence and assess the association of musculoskeletal and eye problems among professional gamers (PG) and casual gamers (CG) with their physical activity level and physical fitness. A total of 94 mobile-gaming athletes (43 PG, 51 CG) were prospectively recruited in this study. Descriptive analysis was performed for BMIs, fatigue scores, musculoskeletal problems profile, and eye problems profile. The associations between physical activity level, BMI, grip strength, flexibility, and MSK injury were tested with a Chi-square test. A total of 65.96% of the players experienced MSK complaints, with the shoulder (26.2%), neck (25.4%), and hand (21.3%) being the top three affected regions. This study also found ocular issues among the players, with eye fatigue (n = 50) as the most frequent complaint. Differential outcomes were observed between the PG and CG groups regarding physical activity (p = 0.001) and flexibility (p = 0.02). Conversely, no statistically significant variances were detected between the PG and CG concerning musculoskeletal (MSK) disorder indicators (p = 1.000), body mass index (BMI) (p = 0.132), body fat (BF) percentage (p = 0.317), grip strength (p = 0.006 for the right side, p = 0.116 for the left side), or waist circumference (p = 0.680). Furthermore, a significant association was observed between physical activity and BMI (p = 0.029). Study results showed that two-thirds of players experienced MSK injury, with the most common complaints being neck, shoulder, hand, and wrist pain. All participants reported at least one eye problem, with the majority reporting multiple complaints. There were significant differences observed in physical activity and flexibility between the PG and CG groups; however, no correlation was found between musculoskeletal injury incidence and the players' physical fitness variables. This lack of correlation may be attributed to the relatively short career span of gamers.

Advances in valorization of sweet potato peels: A comprehensive review on the nutritional compositions, phytochemical profiles, nutraceutical properties, and potential industrial applications.

During food production, food processing, and supply chain, large amounts of food byproducts are generated and thrown away as waste, which to a great extent brings about adverse consequences on the environment and economic development. The sweet potato (Ipomoea batatas L.) is cultivated and consumed in many countries. Sweet potato peels (SPPs) are the main byproducts generated by the tuber processing. These residues contain abundant nutrition elements, bioactive compounds, and other high value-added substances; therefore, the reutilization of SPP holds significance in improving their overall added value. SPPs contain abundant phenolic compounds and carotenoids, which might contribute significantly to their nutraceutical properties, including antioxidant, antimicrobial, anticancer, prebiotic, anti-inflammatory, wound-healing, and lipid-lowering effects. It has been demonstrated that SPP could be promisingly revalorized into food industry, including: (1) applications in diverse food products; (2) applications in food packaging; and (3) applications in the recovery of pectin and cellulose nanocrystals. Furthermore, SPP could be used as promising feedstocks for the bioconversion of diverse value-added bioproducts through biological processing.

E-gaming: An active learning pedagogy for engaging learners in a private university in Karachi, Pakistan.

There is a radical shift in teaching and learning pedagogies to engage the learners in healthcare profession. It was a tough challenge for Pakistani educators of an esteemed university to motivate and assess the learners for concept absorption and critical reasoning using creative approaches. Teaching and learning styles have changed fundamentally from conventional teacher centred to inquiry-based student-centred approach. Classroom teaching in recognised nursing and medical institutes in Pakistan have transformed to blended and entirely online methodologies with the integration of diverse active learning strategies. The educators grapple to engage the millennials and to encounter this, gaming technological platform was used to facilitate the learners for maximum integration, active participation, and create an exciting learning experience. Various e-gaming tools, such as Kahoot, Jamboard, Padlet Wall, Ed-Puzzle, Mentimeter, etc., were used in nursing and medical courses and were highly appreciated by the leaners to retain, review, and self-assess.

A Review: Application of Doped Hydrogenated Nanocrystalline Silicon Oxide in High Efficiency Solar Cell Devices.

Due to the unique microstructure of hydrogenated nanocrystalline silicon oxide (nc-SiOx:H), the optoelectronic properties of this material can be tuned over a wide range, which makes it adaptable to different solar cell applications. In this work, the authors review the material properties of nc-SiOx:H and the versatility of its applications in different types of solar cells. The review starts by introducing the growth principle of doped nc-SiOx:H layers, the effect of oxygen content on the material properties, and the relationship between optoelectronic properties and its microstructure. A theoretical analysis of charge carrier transport mechanisms in silicon heterojunction (SHJ) solar cells with wide band gap layers is then presented. Afterwards, the authors focus on the recent developments in the implementation of nc-SiOx:H and hydrogenated amorphous silicon oxide (a-SiOx:H) films for SHJ, passivating contacts, and perovskite/silicon tandem devices.

Human Factors in AI-Driven Digital Solutions for Increasing Physical Activity: Scoping Review.

BACKGROUND: Artificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. Understanding and optimizing the interaction between individuals and AI-driven mHealth apps is essential for achieving the desired outcomes. OBJECTIVE: This study aims to review and describe the current evidence on the HFs in AI-driven digital solutions for increasing PA. METHODS: We conducted a scoping review by searching for publications containing terms related to PA, HFs, and AI in the titles and abstracts across 3 databases-PubMed, Embase, and IEEE Xplore-and Google Scholar. Studies were included if they were primary studies describing an AI-based solution aimed at increasing PA, and results from testing the solution were reported. Studies that did not meet these criteria were excluded. Additionally, we searched the references in the included articles for relevant research. The following data were extracted from included studies and incorporated into a qualitative synthesis: bibliographic information, study characteristics, population, intervention, comparison, outcomes, and AI-related information. The certainty of the evidence in the included studies was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). RESULTS: A total of 15 studies published between 2015 and 2023 involving 899 participants aged approximately between 19 and 84 years, 60.7% (546/899) of whom were female participants, were included in this review. The interventions lasted between 2 and 26 weeks in the included studies. Recommender systems were the most commonly used AI technology in digital solutions for PA (10/15 studies), followed by conversational agents (4/15 studies). User acceptability and satisfaction were the HFs most frequently evaluated (5/15 studies each), followed by usability (4/15 studies). Regarding automated data collection for personalization and recommendation, most systems involved fitness trackers (5/15 studies). The certainty of the evidence analysis indicates moderate certainty of the effectiveness of AI-driven digital technologies in increasing PA (eg, number of steps, distance walked, or time spent on PA). Furthermore, AI-driven technology, particularly recommender systems, seems to positively influence changes in PA behavior, although with very low certainty evidence. CONCLUSIONS: Current research highlights the potential of AI-driven technologies to enhance PA, though the evidence remains limited. Longer-term studies are necessary to assess the sustained impact of AI-driven technologies on behavior change and habit formation. While AI-driven digital solutions for PA hold significant promise, further exploration into optimizing AI's impact on PA and effectively integrating AI and HFs is crucial for broader benefits. Thus, the implications for innovation management involve conducting long-term studies, prioritizing diversity, ensuring research quality, focusing on user experience, and understanding the evolving role of AI in PA promotion.

Effect of a Smartphone App (S-Check) on Actual and Intended Help-Seeking and Motivation to Change Methamphetamine Use Among Adult Consumers of Methamphetamine in Australia: Randomized Waitlist-Controlled Trial.

BACKGROUND: Interventions are required that address delays in treatment-seeking and low treatment coverage among people consuming methamphetamine. OBJECTIVE: We aim to determine whether a self-administered smartphone-based intervention, the "S-Check app" can increase help-seeking and motivation to change methamphetamine use, and determine factors associated with app engagement. METHODS: This study is a randomized, 28-day waitlist-controlled trial. Consenting adults residing in Australia who reported using methamphetamine at least once in the last month were eligible to download the app for free from Android or iOS app stores. Those randomized to the intervention group had immediate access to the S-Check app, the control group was wait-listed for 28 days before gaining access, and then all had access until day 56. Actual help-seeking and intention to seek help were assessed by the modified Actual Help Seeking Questionnaire (mAHSQ), modified General Help Seeking Questionnaire, and motivation to change methamphetamine use by the modified readiness ruler. χ2 comparisons of the proportion of positive responses to the mAHSQ, modified General Help Seeking Questionnaire, and modified readiness ruler were conducted between the 2 groups. Logistic regression models compared the odds of actual help-seeking, intention to seek help, and motivation to change at day 28 between the 2 groups. Secondary outcomes were the most commonly accessed features of the app, methamphetamine use, feasibility and acceptability of the app, and associations between S-Check app engagement and participant demographic and methamphetamine use characteristics. RESULTS: In total, 560 participants downloaded the app; 259 (46.3%) completed eConsent and baseline; and 84 (32.4%) provided data on day 28. Participants in the immediate access group were more likely to seek professional help (mAHSQ) at day 28 than those in the control group (n=15, 45.5% vs n=12, 23.5%; χ21=4.42, P=.04). There was no significant difference in the odds of actual help-seeking, intention to seek help, or motivation to change methamphetamine use between the 2 groups on the primary logistic regression analyses, while in the ancillary analyses, the imputed data set showed a significant difference in the odds of seeking professional help between participants in the immediate access group compared to the waitlist control group (adjusted odds ratio 2.64, 95% CI 1.19-5.83, P=.02). For participants not seeking help at baseline, each minute in the app increased the likelihood of seeking professional help by day 28 by 8% (ratio 1.08, 95% CI 1.02-1.22, P=.04). Among the intervention group, a 10-minute increase in app engagement time was associated with a decrease in days of methamphetamine use by 0.4 days (regression coefficient [ß] -0.04, P=.02). CONCLUSIONS: The S-Check app is a feasible low-resource self-administered intervention for adults in Australia who consume methamphetamine. Study attrition was high and, while common in mobile health interventions, warrants larger studies of the S-Check app. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12619000534189; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377288&isReview=true.

A Deep Learning-Based Rotten Food Recognition App for Older Adults: Development and Usability Study.

BACKGROUND: Older adults are at greater risk of eating rotten fruits and of getting food poisoning because cognitive function declines as they age, making it difficult to distinguish rotten fruits. To address this problem, researchers have developed and evaluated various tools to detect rotten food items in various ways. Nevertheless, little is known about how to create an app to detect rotten food items to support older adults at a risk of health problems from eating rotten food items. OBJECTIVE: This study aimed to (1) create a smartphone app that enables older adults to take a picture of food items with a camera and classifies the fruit as rotten or not rotten for older adults and (2) evaluate the usability of the app and the perceptions of older adults about the app. METHODS: We developed a smartphone app that supports older adults in determining whether the 3 fruits selected for this study (apple, banana, and orange) were fresh enough to eat. We used several residual deep networks to check whether the fruit photos collected were of fresh fruit. We recruited healthy older adults aged over 65 years (n=15, 57.7%, males and n=11, 42.3%, females) as participants. We evaluated the usability of the app and the participants' perceptions about the app through surveys and interviews. We analyzed the survey responses, including an after-scenario questionnaire, as evaluation indicators of the usability of the app and collected qualitative data from the interviewees for in-depth analysis of the survey responses. RESULTS: The participants were satisfied with using an app to determine whether a fruit is fresh by taking a picture of the fruit but are reluctant to use the paid version of the app. The survey results revealed that the participants tended to use the app efficiently to take pictures of fruits and determine their freshness. The qualitative data analysis on app usability and participants' perceptions about the app revealed that they found the app simple and easy to use, they had no difficulty taking pictures, and they found the app interface visually satisfactory. CONCLUSIONS: This study suggests the possibility of developing an app that supports older adults in identifying rotten food items effectively and efficiently. Future work to make the app distinguish the freshness of various food items other than the 3 fruits selected still remains.

Hydroethanolic extracts from Bauhinia guianensis: a study on acute toxicity in Zebrafish embryos and adults.

CONTEXT: The botanical species Bauhinia guianensis Aublet (Leguminosae-Cercidoideae) is traditionally used in the Amazon for medicinal purposes. OBJECTIVE: The acute toxicity of the hydroethanolic extracts from B. guianensis leaves and stems (HELBg and HESBg) was evaluated in zebrafish (Danio rerio), with emphasis on the embryonic developmental stage and adult alterations. MATERIALS AND METHODS: Extracts were analyzed on LC-DAD-MS/MS. Zebrafish eggs were inoculated individually with concentrations of HELBg and HESBg (0.25, 0.5, 0.75, 1.0, and 1.5 µg/mL), observed for 96 h. Adult zebrafish were treated with a single oral dose (100, 200, 500, 1000, and 2000 mg/kg) of HELBg and HESBg, observed for 48 h. RESULTS: HELBg and HESBg analysis detected 55 compounds. Both extracts exhibited toxicity, including embryo coagulation at higher doses of HELBg and absence of heartbeats in embryos at all doses of HESBg. Behavioral variations were observed; tissue alterations in adult zebrafish were found at the highest doses, primarily in the liver, intestine, and kidneys because of HELBg and HESBg effects. The LD50 of HESBg was 1717 mg/kg, while HELBg exceeded the limit dose of 2000 mg/kg. CONCLUSIONS: The study on acute toxicity of B. guianensis extracts exhibits significant toxic potential, emphasizing effects on embryonic and adult zebrafish. The results suggest relative safety of the species preparations, encouraging further clinical trials on potential biological activities.

Design and application of coal gangue sorting system based on deep learning.

With the advancement of science and technology, coal-washing plants are transitioning to intelligent, information-based, and professional sorting systems. This shift accelerates the construction a modern economic system characterized by green and low-carbon development, thereby promoting the high-quality advancement of the coal industry. Traditional manual gangue picking and multi-axis robotic arm gangue selection currently suffer from low recognition accuracy, slow sorting efficiency, and high worker labor intensity. This paper proposes a deep learning-based, non-contact gangue recognition and pneumatic intelligent sorting system. The system constructs a dynamic database containing key feature information such as the target gangue's contour, quality, and center of mass. The system elucidates the relationships between ejection speed, mass, volume, angle of incidence, and the impact energy matching mechanism. Demonstration experiments using the system prototype for coal gangue sorting reveal that, compared to existing robotic arm sorting methods in coal washing plants, this system achieves a gangue identification accuracy exceeding 97%, a sorting rate above 91%, and a separation time of less than 3 s from identification to separation, thereby effectively enhancing raw coal purity.

Tailor-Made Polysaccharides for Biomedical Applications.

Polysaccharides (PSAs) are carbohydrate-based macromolecules widely used in the biomedical field, either in their pure form or in blends/nanocomposites with other materials. The relationship between structure, properties, and functions has inspired scientists to design multifunctional PSAs for various biomedical applications by incorporating unique molecular structures and targeted bulk properties. Multiple strategies, such as conjugation, grafting, cross-linking, and functionalization, have been explored to control their mechanical properties, electrical conductivity, hydrophilicity, degradability, rheological features, and stimuli-responsiveness. For instance, custom-made PSAs are known for their worldwide biomedical applications in tissue engineering, drug/gene delivery, and regenerative medicine. Furthermore, the remarkable advancements in supramolecular engineering and chemistry have paved the way for mission-oriented biomaterial synthesis and the fabrication of customized biomaterials. These materials can synergistically combine the benefits of biology and chemistry to tackle important biomedical questions. Herein, we categorize and summarize PSAs based on their synthesis methods, and explore the main strategies used to customize their chemical structures. We then highlight various properties of PSAs using practical examples. Lastly, we thoroughly describe the biomedical applications of tailor-made PSAs, along with their current existing challenges and potential future directions.

Eco-Friendly Textile-Based Wearable Humidity Sensor with Multinode Wireless Connectivity for Healthcare Applications.

Textile-based wearable humidity sensors are of great interest for human healthcare monitoring as they can provide critical human-physiology information. The demand for wearable and sustainable sensing technology has significantly promoted the development of eco-friendly sensing solutions for potential real-world applications. Herein, a biodegradable cotton (textile)-based wearable humidity sensor has been developed using fabsil-treated cotton fabric coated with a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) sensing layer. The structural, chemical composition, hygroscopicity, and morphological properties are examined using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), contact angle measurement, and scanning electron microscopy (SEM) analysis. The developed sensor exhibited a nearly linear response (Adj. R-square value observed as 0.95035) over a broad relative humidity (RH) range from 25 to 91.5%RH displaying high sensitivity (26.1%/%RH). The sensor shows excellent reproducibility (on replica sensors with a margin of error ±1.98%) and appreciable stability/aging with time (>4.5 months), high flexibility (studied at bending angles 30°, 70°, 120°, and 150°), substantial response/recovery durations (suitable for multiple applications), and highly repeatable (multicyclic analysis) sensing performance. The prospective relevance of the developed humidity sensor toward healthcare applications is demonstrated via breathing rate monitoring (via a sensor attached to a face mask), distinguishing different breathing patterns (normal, deep, and fast), skin moisture monitoring, and neonatal care (diaper wetting). The multinode wireless connectivity is demonstrated using a Raspberry Pi Pico-based system for demonstrating the potential applicability of the developed sensor as a real-time humidity monitoring system for the healthcare sector. Further, the biodegradability analysis of the used textile is evaluated using the soil burial degradation test. The work suggests the potential applicability of the developed flexible and eco-friendly humidity sensor in wearable healthcare devices and other humidity sensing applications.

Botany, Phytochemistry, pharmacology, and applications of Pandanus amaryllifolius Roxb.: A review.

Pandan (Pandanus amaryllifolius Roxb.), a member of the Pandanaceae family, has been consumed as food and medicine since ancient times. The current paper provides an overview of the botanical profile, phytochemistry, pharmacology, and applications of P. amaryllifolius. Information regarding P. amaryllifolius was collected from online sources (using PubMed, Science Direct, Google Scholar, Web of Science, ACS, and CNKI) as well as traditional textbooks. Over 100 compounds have been identified, including its characteristic components 2-Acetyl-1-pyrroline and Pandanus alkaloids. Several therapeutic uses of P. amaryllifolius, such as antioxidant, hypoglycemic, antimicrobial, and antitumor activities, have been demonstrated in modern pharmacological studies. Additionally, it could be applied in various fields, including food, energy, material, and the environment. Continued research on P. amaryllifolius can contribute to the development of new drugs and therapies for various diseases. And further studies are needed to improve its utilization.

Unbiased plasma profiling using pre-selected RNA aptamer pools predicts mortality in COVID-19 and identifies protein risk factors.

The impact of the COVID-19 pandemic demands effective prognostic tools for precise risk evaluation and timely intervention. This study utilized the APTASHAPE technology to profile plasma proteins in COVID-19 patient samples. Employing a highly diverse 2'-fluoro-protected RNA aptamer pool enriched toward proteins in the plasma samples from COVID-19 patients, we performed a single round of parallel selection on the derivation cohort and identified 93 discriminatory aptamers capable of distinguishing COVID-19 and healthy plasma samples. A subset of these aptamers was then used to predict 30-day mortality with high sensitivity and specificity in a validation cohort of 165 patients. We predicted 30-day mortality with areas under the curve (AUCs) of 0.91 in females and 0.68 in males. Affinity purification coupled with mass spectrometry analysis of the aptamer-targeted proteins identified potential biomarkers associated with disease severity, including complement system components. The study demonstrates the APTASHAPE technology as an unbiased approach that not only aids in predicting disease outcomes but also offers insights into gender-specific differences, shedding light on the nuanced aspects of COVID-19 pathophysiology. In conclusion, the findings highlight the promise of APTASHAPE as a valuable tool for estimating risk factors in COVID-19 patients and enabling stratification for personalized treatment management.

A Decomposition-Based Multi-Objective Flying Foxes Optimization Algorithm and Its Applications.

The flying foxes optimization (FFO) algorithm stimulated by the strategy used by flying foxes for subsistence in heat wave environments has shown good performance in the single-objective domain. Aiming to explore the effectiveness and benefits of the subsistence strategy used by flying foxes in solving optimization challenges involving multiple objectives, this research proposes a decomposition-based multi-objective flying foxes optimization algorithm (MOEA/D-FFO). It exhibits a great population management strategy, which mainly includes the following features. (1) In order to improve the exploration effectiveness of the flying fox population, a new offspring generation mechanism is introduced to improve the efficiency of exploration of peripheral space by flying fox populations. (2) A new population updating approach is proposed to adjust the neighbor matrices to the corresponding flying fox individuals using the new offspring, with the aim of enhancing the rate of convergence in the population. Through comparison experiments with classical algorithms (MOEA/D, NSGA-II, IBEA) and cutting-edge algorithms (MOEA/D-DYTS, MOEA/D-UR), MOEA/D-FFO achieves more than 11 best results. In addition, the experimental results under different population sizes show that the proposed algorithm is highly adaptable and has good application prospects in optimization problems for engineering applications.

Plasmon-enhanced fluorescence for biophotonics and bio-analytical applications.

Fluorescence spectroscopy serves as an ultrasensitive sophisticated tool where background noises which serve as a major impediment to the detection of the desired signals can be safely avoided for detections down to the single-molecule levels. One such way of bypassing background noise is plasmon-enhanced fluorescence (PEF), where the interactions of fluorophores at the surface of metals or plasmonic nanoparticles are probed. The underlying condition is a significant spectral overlap between the localized surface plasmon resonance (LSPR) of the nanoparticle and the absorption or emission spectra of the fluorophore. The rationale being the coupling of the excited state of the fluorophore with the localized surface plasmon leads to an augmented emission, owing to local field enhancement. It is manifested in enhanced quantum yields concurrent with a decrease in fluorescence lifetimes, owing to an increase in radiative rate constants. This improvement in detection provided by PEF allows a significant scope of expansion in the domain of weakly emitting fluorophores which otherwise would have remained unperceivable. The concept of coupling of weak emitters with plasmons can bypass the problems of photobleaching, opening up avenues of imaging with significantly higher sensitivity and improved resolution. Furthermore, amplification of the emission signal by the coupling of free electrons of the metal nanoparticles with the electrons of the fluorophore provides ample opportunities for achieving lower detection limits that are involved in biological imaging and molecular sensing. One avenue that has attracted significant attraction in the last few years is the fast, label-free detection of bio-analytes under physiological conditions using plasmonic nanoparticles for point-of-care analysis. This review focusses on the applications of plasmonic nanomaterials in the field of biosensing, imaging with a brief introduction on the different aspects of LSPR and fabrication techniques.