Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes.

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Breast segmentation in infrared thermography from characteristical inframammary shape.

Infrared thermography is gaining relevance in breast cancer assessment. For this purpose, breast segmentation in thermograms is an important task for performing automatic image analysis and detecting possible temperature changes that indicate the presence of malignancy. However, it is not a simple task since the breast limit borders, especially the top borders, often have low contrast, making it difficult to isolate the breast area. Several algorithms have been proposed for breast segmentation, but these highly depend on the contrast at the lower breast borders and on filtering algorithms to remove false edges. This work focuses on taking advantage of the distinctive inframammary shape to simplify the definition of the lower breast border, regardless of the contrast level, which indeed also provides a strong anatomical reference to support the definition of the poorly marked upper boundary of the breasts, which has been one of the major challenges in the literature. In order to demonstrate viability of the proposed technique for an automatic breast segmentation, we applied it to a database with 180 thermograms and compared their results with those reported by others in the literature. We found that our approach achieved a high performance, in terms of Intersection over Union of 0.934, even higher than that reported by artificial intelligence algorithms. The performance is invariant to breast sizes and thermal contrast of the images.

Foliar-applied melatonin and titanium nanoparticles modulate cadmium (Cd) toxicity through minimizing Cd accumulation and optimizing physiological and biochemical properties in sage (Salvia officinalis L.).

Notwithstanding the fact that melatonin (MT) and titanium nanoparticles (Ti NPs) alone have been widely used recently to modulate cadmium (Cd) stress in plants, there is a gap in the comparative impacts of these materials on lowering Cd toxicity in sage plants. The objective of this study was to determine how foliar application of MT and Ti NPs affected the growth, Cd accumulation, photosynthesis, water content, lipid peroxidation, and essential oil (EO) quality and quantity of sage plants in Cd-contaminated soils. A factorial experiment was conducted using MT at 100 and 200 µM and Ti NPs at 50 and 100 mg L-1 topically, together with Cd toxicity at 10 and 20 mg Cd kg-1 soil. The results showed that Cd toxicity decreased plant growth and enhanced lipid peroxidation. The Cd stress at 20 mg kg-1 soil resulted in increases in Cd root (693%), Cd shoot (429%), electrolyte leakage (EL, 29%), malondialdehyde (MDA, 72%), shoot weight (31%), root weight (27%), chlorophyll (Chl) a + b (26%), relative water content (RWC, 23%), and EO yield (30%). The application of MT and Ti NPs controlled drought stress by reducing MDA and EL, enhancing plant weight, Chl, RWC, and EO production, and minimizing Cd accumulation in plant tissues. The predominant compounds in the EO were α-thujone, 1,8-cineole, ß-thujone, camphor, and α-humulene. MT and Ti NPs caused α-thujone to rise, whereas Cd stress caused it to fall. Based on heat map analysis, MDA was the trait that was most sensitive to treatments. In summary, the research emphasizes the possibility of MT and Ti NPs, particularly MT at 200 µM, to mitigate Cd toxicity in sage plants and enhance their biochemical reactions.

Testing the feasibility and preliminary efficacy of Meaningful Activity for Managing Behavioral Symptoms of Distress (MAC-4-BSD) intervention for residents with dementia in assisted living: Protocol description.

The purpose of this manuscript is to describe the protocol for an Alzheimer's Association-funded cluster randomized trial that focuses on engaging assisted living residents with dementia in meaningful activity to help address their behavioral symptoms of distress using a theoretically based approach, Meaningful Activity for Managing Behavioral Symptoms of Distress (MAC-4-BSD). The development of MAC-4-BSD was based on the Social Ecological Model and Social Cognitive Theory. The MAC-4-BSD intervention includes the following four steps: (1) Assessment of the assisted living physical environment and policies to facilitate meaningful activity; (2) Education of staff about implementation of meaningful activity; (3) Assessment of resident preferences and goals for meaningful activity; (4) Mentoring and motivating staff and residents to facilitate engagement in meaningful activity. The overall aim of this study will be to determine the feasibility and preliminary efficacy of implementing the MAC-4-BSD intervention and test whether it will improve residents' engagement in meaningful activity, behavioral symptoms of distress, and quality of life as well as the environment and policies to promote meaningful activity in assisted living.

Unveiling the efficacy of Bacillus faecalis and composted biochar in alleviating arsenic toxicity in maize.

Arsenic (As) contamination is a major environmental pollutant that adversely affects plant physiological processes and can hinder nutrients and water availability. Such conditions ultimately resulted in stunted growth, low yield, and poor plant health. Using rhizobacteria and composted biochar (ECB) can effectively overcome this problem. Rhizobacteria have the potential to enhance plant growth by promoting nutrient uptake, producing growth hormones, and suppressing diseases. Composted biochar can enhance plant growth by improving aeration, water retention, and nutrient cycling. Its porous structure supports beneficial microorganisms, increasing nutrient uptake and resilience to stressors, ultimately boosting yields while sequestering carbon. Therefore, the current study was conducted to investigate the combined effect of previously isolated Bacillus faecalis (B. faecalis) and ECB as amendments on maize cultivated under different As levels (0, 300, 600 mg As/kg soil). Four treatments (control, 0.5% composted biochar (0.5ECB), B. faecalis, and 0.5ECB + B. faecalis) were applied in four replications following a completely randomized design. Results showed that the 0.5ECB + B. faecalis treatment led to a significant rise in maize plant height (~ 99%), shoot length (~ 55%), root length (~ 82%), shoot fresh (~ 87%), and shoot dry weight (~ 96%), root fresh (~ 97%), and dry weight (~ 91%) over the control under 600As stress. There was a notable increase in maize chlorophyll a (~ 99%), chlorophyll b (~ 81%), total chlorophyll (~ 94%), and shoot N, P, and K concentration compared to control under As stress, also showing the potential of 0.5ECB + B. faecalis treatment. Consequently, the findings suggest that applying 0.5ECB + B. faecalis is a strategy for alleviating As stress in maize plants.

Ensuring People Living with HIV Inform the Future of HIV Treatment in Low- and Middle-Income Countries: A Scoping Review and Recommendations for a Community-Led Research Agenda.

The HIV treatment landscape in low- and middle-income countries (LMICs) is rapidly evolving, exemplified by the expansion of differentiated service delivery (DSD) during the coronavirus disease (COVID-19) pandemic. Long-acting products represent a new frontier that will require a significant redesign of health systems. It is critical to understand service delivery and product preferences of people living with HIV (PLHIV) and ensure evidence generation is guided by community priorities. We conducted a scoping review to identify gaps among preference studies and inform future research. Peer-reviewed articles published from January 2014-May 2022 reporting acceptability or preference data from PLHIV or caregivers for one or more service delivery or product attribute were eligible. Service delivery studies were restricted to LMIC populations while product studies had no geographical restrictions. Based on gaps identified, we consulted advocates to develop community-led research agenda recommendations. Of 6,493 studies identified, 225 studies on service delivery attributes and 47 studies on product preferences were eligible. The most frequently studied delivery models were integration (n = 59) and technology-based interventions (n = 55). Among product literature, only 15 studies included LMIC populations. Consultation with advocates highlighted the need for research on long-acting products, including among pediatric, pregnant, and breastfeeding PLHIV, PLHIV on second-line regimens, and key populations. Consultation also emphasized the need to understand preferences on clinic visit frequency, side effects, and choice. While the preference literature has expanded, gaps remain around long-acting regimens and their delivery. To fill these gaps, the research agenda must be guided by the priorities of communities of PLHIV.

Considerations for the development of iPSC-derived cell therapies: a review of key challenges by the JSRM-ISCT iPSC Committee.

Since their first production in 2007, human induced pluripotent stem cells (iPSCs) have provided a novel platform for the development of various cell therapies targeting a spectrum of diseases, ranging from rare genetic eye disorders to cancer treatment. However, several challenges must be tackled for iPSC-based cell therapy to enter the market and achieve broader global adoption. This white paper, authored by the Japanese Society for Regenerative Medicine (JSRM) - International Society for Cell Therapy (ISCT) iPSC Committee delves into the hurdles encountered in the pursuit of safe and economically viable iPSC-based therapies, particularly from the standpoint of the cell therapy industry. It discusses differences in global guidelines and regulatory frameworks, outlines a series of quality control tests required to ensure the safety of the cell therapy, and provides details and important considerations around cost of goods (COGs), including the impact of automated advanced manufacturing.

Unearthing the power of microbes as plant microbiome for sustainable agriculture.

In recent years, research into the complex interactions and crosstalk between plants and their associated microbiota, collectively known as the plant microbiome has revealed the pivotal role of microbial communities for promoting plant growth and health. Plants have evolved intricate relationships with a diverse array of microorganisms inhabiting their roots, leaves, and other plant tissues. This microbiota mainly includes bacteria, archaea, fungi, protozoans, and viruses, forming a dynamic and interconnected network within and around the plant. Through mutualistic or cooperative interactions, these microbes contribute to various aspects of plant health and development. The direct mechanisms of the plant microbiome include the enhancement of plant growth and development through nutrient acquisition. Microbes have the ability to solubilize essential minerals, fix atmospheric nitrogen, and convert organic matter into accessible forms, thereby augmenting the nutrient pool available to the plant. Additionally, the microbiome helps plants to withstand biotic and abiotic stresses, such as pathogen attacks and adverse environmental conditions, by priming the plant's immune responses, antagonizing phytopathogens, and improving stress tolerance. Furthermore, the plant microbiome plays a vital role in phytohormone regulation, facilitating hormonal balance within the plant. This regulation influences various growth processes, including root development, flowering, and fruiting. Microbial communities can also produce secondary metabolites, which directly or indirectly promote plant growth, development, and health. Understanding the functional potential of the plant microbiome has led to innovative agricultural practices, such as microbiome-based biofertilizers and biopesticides, which harness the power of beneficial microorganisms to enhance crop yields while reducing the dependency on chemical inputs. In the present review, we discuss and highlight research gaps regarding the plant microbiome and how the plant microbiome can be used as a source of single and synthetic bioinoculants for plant growth and health.

Exogenous melatonin delays oxidative browning in litchi during cold storage by regulating biochemical attributes and gene expression.

Oxidative damage leading to loss of nutritional quality and pericarp discoloration of harvested litchi fruits drastically limits consumer acceptance and marketability. In the present investigation, the impact of postharvest melatonin application at different concentrations, i.e., 0.1 mM, 0.25 mM, and 0.5 mM, on fruit quality and shelf life of litchi fruits under cold storage conditions was studied. The results revealed the positive effect of melatonin application at all concentrations on fruit quality and shelf life. However, treatment with 0.5 mM concentration of melatonin resulted in minimum weight loss, decay loss, pericarp discoloration, and also retained higher levels of TSS, acidity, total sugar, ascorbic acid, anthocyanin, antioxidant, and phenolics content during cold storage. Melatonin administration also restricted the enzymatic activity of the polyphenol oxidase (PPO) and peroxidase (POD) enzymes in the fruit pericarp and maintained freshness of the fruits up to 30 days in cold storage. At the molecular level, a similar reduction in the expression of browning-associated genes, LcPPO, LcPOD, and Laccase, was detected in preserved litchi fruits treated with melatonin. Anthocyanin biosynthetic genes, LcUFGT and LcDFR, on the other hand showed enhanced expression in melatonin treated fruits compared to untreated fruits. Melatonin, owing to its antioxidant properties, when applied to harvested litchi fruits retained taste, nutritional quality and red color pericarp up till 30 days in cold storage.

Determining the number of attributes in the GDINA model.

Exploratory cognitive diagnosis models have been widely used in psychology, education and other fields. This paper focuses on determining the number of attributes in a widely used cognitive diagnosis model, the GDINA model. Under some conditions of cognitive diagnosis models, we prove that there exists a special structure for the covariance matrix of observed data. Due to the special structure of the covariance matrix, an estimator based on eigen-decomposition is proposed for the number of attributes for the GDINA model. The performance of the proposed estimator is verified by simulation studies. Finally, the proposed estimator is applied to two real data sets Examination for the Certificate of Proficiency in English (ECPE) and Big Five Personality (BFP).

Microfluidic capillary electrophoresis - mass spectrometry for rapid charge-variant and glycoform assessment of monoclonal antibody biosimilar candidates.

Early-stage cell line screening is a vital step in developing biosimilars of therapeutic monoclonal antibodies (mAbs). While the quality of the manufactured antibodies is commonly assessed by charge-based separation methods employing UV absorbance detection, these methods lack the ability to identify resolved mAb variants. We evaluated the performance of microfluidic capillary electrophoresis coupled to mass spectrometry (MCE-MS) as a rapid tool for profiling mAb biosimilar candidates from clonal cell lines. A representative originator sample was used to develop the MCE-MS method. The addition of dimethylsulfoxide (DMSO) to the background electrolyte yielded up to 60-fold enhancement of the protein MS signal. The resulting electropherograms consistently provided resolution of mAb charge variants within 10 min. Deconvoluted mass spectra facilitated the identification of basic variants such as C-terminal lysine and proline amidation, while the acidic variants could be assigned to deamidated forms. The MCE-MS method also allowed the identification of 18 different glycoforms in biosimilar samples. To mimic early-stage cell line selection, samples from five clonal cell lines that all expressed the same biosimilar candidate mAb were compared to their originator mAb. Based on the similarity observed in charge variants and glycoform profiles acquired by MCE-MS, the most promising candidate could be selected. The MCE-MS method demonstrated good overall reproducibility, as confirmed by a transferability study involving two separate laboratories. This study highlights the efficacy of the MCE-MS method for rapid proteoform screening of clonal cell line samples, underscoring its potential significance as an analytical tool in biosimilar process development.

Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction.

BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis. METHODS: All adult discharges for STEMI in the National Inpatient Sample (October 2015 to December 2019) were included, excluding patients with prior myocardial infarction. Machine-learning clustering analysis was used to define clusters based on 21 clinical attributes of interest. Main outcomes of the study were cluster-based comparison of risk profile, in-hospital clinical outcomes and utilization of invasive management. Binomial hierarchical multivariable logistic regression with adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) was used to detect the between-cluster differences. RESULTS: Out of overall 470,960 STEMI cases, the machine-learning analysis revealed 4 different clusters with 205,640 (cluster 0: 'behavioural risk cluster'), 146,400 (cluster 1: 'least comorbidity cluster'), 45,100 (cluster 2: 'diabetes with end-organ damage cluster') and 73,820 (cluster 3: 'cardiometabolic cluster') cases. Attributes with the highest importance for clustering were hypertension and diabetes. After multivariable adjustment, patients from 'diabetes with end-organ damage cluster' exhibited the worst mortality, MACCE and ischemic stroke (p < 0.001 for all), as well as the lowest utilization of invasive management (p < 0.001 for all), in comparison to other clusters. Patients from 'behavioural risk cluster' exhibited the best in-hospital prognosis and the highest utilization of invasive management, compared to other clusters (p < 0.001 for all). CONCLUSIONS: Machine learning driven clustering of inpatients with STEMI reveals important population subgroups with distinct prevalence, risk profile, prognosis and management. Data driven approaches may identify high risk phenogroups and warrants further study.

Enhancing germination and growth of canola (Brassica napus L.) through hydropriming and NaCl priming.

The excessive accumulation of sodium chloride (NaCl) in soil can result in soil salinity, which poses a significant challenge to plant growth and crop production due to impaired water and nutrient uptake. On the other hand, hydropriming (WP) and low level of NaCl priming can improve the germination of seeds, chlorophyll contents, oil and seed yield in plants. That's why this study investigates the impact of hydro and different levels of NaCl (0.5, 1.0, 1.5 and 2.0%) priming, as pre-treatment techniques on canola seeds germination, growth and yield of two varieties Punjab and Faisal Canola. Results showed that, WP performed significant best for increase in germination (~ 20 and ~ 22%) and shoot length (~ 6 and ~ 10%) over non-priming (NP) in Punjab Canola and Faisal Canola respectively. A significant increase in plant height (~ 6 and ~ 7%), root length (~ 1 and ~ 7%), shoot fresh weight (~ 5 and ~ 7%), root fresh weight (~ 6 and ~ 7%) in Punjab Canola and Faisal Canola respectively. It was also observed that plants under WP and 0.5%NaCl priming were also better in production of seed yield per plant, oil contents, silique per plant, seeds per silique, and branches per plant chlorophyll contents and leaf relative water contents over NP. In conclusion, WP and 0.5%NaCl has potential to improve the germination, growth, yield and oil attributes of canola compared to non-priming, 1.0%NaCl priming, 1.5%NaCl priming and 2.0%NaCl priming.

Exploring consumer responses to official endorsement: roles of credibility and attractiveness attributes in live streaming.

Introduction: Official endorsement, distinct from celebrity, expertise, and peer endorsement, introduces a new paradigm where local government officials use online platforms, particularly live streaming, to promote local products and brands. Methods: This study examines the influence of official endorsement on consumer responses using the source credibility and source attractiveness models. We developed a framework that considers official credibility and attractiveness attributes as antecedents, and consumer perceived security and enjoyment as mediators, affecting purchase intention and local brand awareness. The study also incorporates variables such as consumer region and power distance belief. Results: Data from 594 responses obtained through an online survey were analyzed using structural equation modeling. The results indicate that official credibility attributes (expertise, trustworthiness, government credibility) enhances consumer perceived security, while official attractiveness attributes (physical attractiveness, interaction friendliness, and similarity with consumers) increases consumer enjoyment. Both perceived security and enjoyment positively influence purchase intention and local brand awareness. These relationships are partially moderated by consumer region and power distance belief. Discussion: This research pioneers the study of official endorsements, expanding the endorsement literature. It also provides practical insights for marketing professionals and government officials on leveraging official endorsements to enhance the value of local products and brands..

Combined effect of gallic acid and zinc ferrite nanoparticles on wheat growth and yield under salinity stress.

Salinity stress significantly impacts crops, disrupting their water balance and nutrient uptake, reducing growth, yield, and overall plant health. High salinity in soil can adversely affect plants by disrupting their water balance. Excessive salt levels can lead to dehydration, hinder nutrient absorption, and damage plant cells, ultimately impairing growth and reducing crop yields. Gallic acid (GA) and zinc ferrite (ZnFNP) can effectively overcome this problem. GA can promote root growth, boost photosynthesis, and help plants absorb nutrients efficiently. However, their combined application as an amendment against drought still needs scientific justification. Zinc ferrite nanoparticles possess many beneficial properties for soil remediation and medical applications. That's why the current study used a combination of GA and ZnFNP as amendments to wheat. There were 4 treatments, i.e., 0, 10 µM GA, 15 µM GA, and 20 µM GA, without and with 5 µM ZnFNP applied in 4 replications following a completely randomized design. Results exhibited that 20 µM GA + 5 µM ZnFNP caused significant improvement in wheat shoot length (28.62%), shoot fresh weight (16.52%), shoot dry weight (11.38%), root length (3.64%), root fresh weight (14.72%), and root dry weight (9.71%) in contrast to the control. Significant enrichment in wheat chlorophyll a (19.76%), chlorophyll b (25.16%), total chlorophyll (21.35%), photosynthetic rate (12.72%), transpiration rate (10.09%), and stomatal conductance (15.25%) over the control validate the potential of 20 µM GA + 5 µM ZnFNP. Furthermore, improvement in N, P, and K concentration in grain and shoot verified the effective functioning of 20 µM GA + 5 µM ZnFNP compared to control. In conclusion, 20 µM GA + 5 µM ZnFNP can potentially improve the growth, chlorophyll contents and gas exchange attributes of wheat cultivated in salinity stress. More investigations are suggested to declare 20 µM GA + 5 µM ZnFNP as the best amendment for alleviating salinity stress in different cereal crops.

Effect of selective fermentation on nutritional parameters and techno-functional characteristics of fermented millet-based probiotic dairy product.

The primary goal of this study was to assess the effect of selective fermentation on the nutritional and techno-functional characteristics of fermented millet-skim milk-based product. The product was made with HHB-311 biofortified pearl millet (PM) flour, skim milk powder, and isolated cultures (either alone or in combination) of Limosilactobacillus fermentum MS005 (LF) and Lactobacillus rhamnosus GG 347 (LGG). To optimize fermentation time, time intervals 8, 16, and 24 h were explored, while the temperature was kept 37 °C. Results of protein digestibility showed that LF (16 h) and LGG (24 h) fermented samples had significantly higher (P < 0.05) protein digestibility of 90.75 ± 1.6% and 93.76 ± 3.4%, respectively, than that of control (62.60 ± 2.6%). Further, 16 h fermentation with LF showed enhanced iron (39%) and zinc (14%) bioavailability. The results suggested that LF with 16 h fermentation is most suitable for making millet-based fermented products with superior techno-functional attributes and micronutrient bioavailability.

Preparation and evaluation of functional cocoa-free spread alternatives from different sources.

Spread products have an important market share as they have high nutritional value and they are increasingly consumed, especially by children as a source of energy. The purpose of this work was to evaluate the potential use of powdered chickpea, black rice, carob, doum, date seeds, and beetroot to produce novel functional spreadable products as cocoa-free alternatives. Additionally, to avoid the side effects of cocoa-based products and to assess the cocoa replacement effects on the sensory properties, chemical composition, texture analysis, viscosity, antioxidant, peroxide stability, and microbial quality during storage periods were compared to the ones of cocoa spread. Sensory evaluation revealed that most formulated spreads were accepted as chocolate spread alternatives since there was no significant difference in overall acceptability among cocoa, chickpea, black rice, carob, and doum, while date seeds and beetroot spreads were significantly less acceptable. A variation was observed in the proximate chemical analysis of the produced functional spreads, as the alternative spreads had different characteristics to each other in their physicochemical, texture, and rheological properties. Results indicated a wide variation in the total phenolic content (TPC) of the different spread extracts. The highest amount of TPC was obtained for beetroot spread (455.84 mg GAE/100 g) followed by black rice spread (436.08 mg GAE/100 g). The obtained results indicated that the antioxidant activity of different spreads was significantly different (p < .05) while based on their microbiological analysis, they could have a shelf life of up to 9 months. According to the results, chickpea, carob, doum, black rice, date seeds, and beetroot powders could be used for the production of cocoa-free alternatives as they were highly acceptable and they showed antioxidant and antimicrobial activity.

Patient Acceptability and Preferences for Solid Oral Dosage Form Drug Product Attributes: A Scoping Review.

Background: There is no consistent framework for patient-centric drug product design, despite the common understanding that drug product acceptability and preferences influence adherence and, therefore, drug product effectiveness. The aim of this review was to assess current understanding of patient acceptability and preferences for solid oral dosage form (SODF) drug product attributes, and the potential impact of these attributes on patient behaviors and outcomes. Patients and Methods: A scoping review was conducted. Embase, Ovid MEDLINE®, and PubMed® were searched for full-text articles published between January 2013 and May 2023. Following screening and assessment against predefined inclusion criteria, data were analyzed thematically. Results: Nineteen studies were included. Four overarching domains of drug product attributes were identified and summarized in a framework: appearance, swallowability, palatability, and handling. Each domain was informed by specific drug product attributes: texture, form, size, shape, color, marking, taste, mouthfeel, and smell. The most frequently studied domains were swallowability and appearance, while the most studied attributes were size, shape, and texture. Smell, marking, and mouthfeel were the least studied attributes. Texture intersected all domains, while form, shape, and size intersected appearance, swallowability, and handling. Swallowability and size appeared to be the key domain and attribute, respectively, to consider when designing drug products. Few studies explored the impact of drug product attributes on behaviors and outcomes. Conclusion: While existing studies of drug product attributes have focused on appearance and swallowability, this review highlighted the importance of two less well-understood domains-palatability and handling-in understanding patients' acceptability and preferences for SODF drug products. The framework provides a tool to facilitate patient-centric design of drug products, organizing and categorizing physical drug product attributes into four overarching domains (appearance, swallowability, palatability, and handling), encouraging researchers to comprehensively assess the impact of drug product attributes on patient acceptability, preferences, and outcomes.

Medicines come in a variety of types and forms. These include tablets and capsules. Factors, such as the size and shape of tablets, can affect how people take medicines. However, patients are rarely involved in designing the medicines that they take. In this study, researchers summarized 19 studies published between 2013 and 2023. They wanted to understand how different factors, like size and shape, affect patients' preferences, ability, and willingness to take medicines. Researchers focused on the "physical" aspects of medicines and found 4 common themes: 1) what they look like (appearance), 2) how easy they are to swallow (swallowability), 3) how they taste and feel in the mouth (palatability), and 4) how easy they are to handle (handling). Eight factors were also found: color, markings, shape, size, smell, taste, texture, and how a medicine feels in the mouth (mouthfeel). Most studies focused on what medicines look like and how easy they are to swallow. The factors that researchers mostly looked at were the size, shape, and texture of medicines. The design of medicines can impact patients of different ages, though there may be specific needs for certain groups of patients, including children, older adults, and people with certain diseases. Patient input should become a part of future medicines design to ensure their acceptability.

Multi-view attribute learning and context relationship encoding enhanced segmentation of lung tumors from CT images.

Graph convolutional neural networks (GCN) have shown the promise in medical image segmentation due to the flexibility of representing diverse range of image regions using graph nodes and propagating knowledge via graph edges. However, existing methods did not fully exploit the various attributes of image nodes and the context relationship among their attributes. We propose a new segmentation method with multi-similarity view enhancement and node attribute context learning (MNSeg). First, multiple views were formed by measuring the similarities among the image nodes, and MNSeg has a GCN based multi-view image node attribute learning (MAL) module to integrate various node attributes learnt from multiple similarity views. Each similarity view contains the specific similarities among all the image nodes, and it was integrated with the node attributes from all the channels to form the enhanced attributes of image nodes. Second, the context relationships among the attributes of image nodes are formulated by a transformer-based context relationship encoding (CRE) strategy to propagate these relationships across all the image nodes. During the transformer-based learning, the relationships were estimated based on the self-attention on all the image nodes, and then they were encoded into the learned node features. Finally, we design an attention at attribute category level (ACA) to discriminate and fuse the learnt diverse information from MAL, CRE, and the original node attributes. ACA identifies the more informative attribute categories by adaptively learn their importance. We validate the performance of MNSeg on a public lung tumor CT dataset and an in-house non-small cell lung cancer (NSCLC) dataset collected from the hospital. The segmentation results show that MNSeg outperformed the compared segmentation methods in terms of spatial overlap and the shape similarities. The ablation studies demonstrated the effectiveness of MAL, CRE, and ACA. The generalization ability of MNSeg was proved by the consistent improved segmentation performances using different 3D segmentation backbones.

Chemical Profile and Aroma Effects of Major Volatile Compounds in New Mulberry Leaf Fu Brick Tea and Traditional Fu Brick Tea.

This study aimed to investigate the aroma effects of key volatile compounds in a new type of mulberry leaf Fu brick teas (MTs) and traditional Fu brick teas (FTs). Headspace solid-phase microextraction (HS-SPME), gas chromatography-mass spectrometry (GC-MS), sensory evaluation, and chemometrics were used to determine the differences in key flavour qualities between the two. The results showed that a total of 139 volatile components were identified, with aldehydes, ketones, and alcohols dominating. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) combined with the odour activity value (OAV) showed that seven aroma compounds had an OAV > 10, including 2-(4-methylcyclohex-3-en-1-yl) propan-2-ol with floral and fruity aroma and green attributes, 6-methylhept-5-en-2-one, (E)-6,10-dimethyl-5,9-Undecadien-2-one, (3E,5E)-octa-3,5-dien-2-one, Benzaldehyde, and (E)-3,7,11,15-tetramethylhexadec-2-en-1-ol, which were more abundant in MTs than FTs; Cedrol with sweet aroma attributes was more consistent in MTs than FTs, and we suggest that these odour compounds are important aroma contributors to MTs. Taken together, these findings will provide new insights into the mechanism of formation of the characteristic attributes of aroma in MTs.