Unity College

Colon-targeted drug delivery as an oral drug delivery technique holds great promise for overcoming the limitations related to the modern medicine. These systems are highly able to protect the drugs from the low pH of the stomach and safely deliver them to the colon as they are pH-responsive. Poly(vinyl alcohol) (PVA) and poly(acrylic acid) (PAA) polymers have been widely used in drug delivery applications due to their excellent hydrophilicity, biocompatibility, and mechanical properties. Moreover, due to the presence of strong acidic functional groups in the PAA matrix, combination of PVA and PAA makes it possible to provide pH-sensitive drug delivery systems for colon-targeted drug delivery applications. Hence, pH-sensitive PVA-PAA-based hydrogels with various forms are suitable candidates for the safe delivery of different drugs such as non-steroidal anti-inflammatory drugs (NSAIDs), anticancer drugs, or even insulin to the colon. Therefore, the present review illustrates various forms of pH-responsive PVA-PAA-based hydrogels for colon-targeted drug delivery applications.

Head and neck squamous cell carcinomas (HNSCCs) are considered the most common histological type of head and neck cancer. This study aims to develop a drug delivery system based on zein protein nanoparticles (Zein NPs) to enhance the therapeutic effect of the anticancer peptide, Pistacia zardin1 (PZ1), for the treatment of maxillofacial cancers. PZ1-Zein NPs were synthesized by the desolvation method. These spherical nanoparticles (size: 162.8 nm, PDI: 0.27) showed high encapsulation efficiency (89%) and pH-responsive release (with higher drug release in the acidic tumor microenvironment). In vitro cytotoxicity assays showed that PZ1-Zein NPs significantly reduced IC50 values in HNSCC cell lines (e.g., SCC-25: 7.5 µM vs. 19.3 µM for free peptide, p < 0.001) while exhibiting improved selectivity for cancer cells over normal HaCaT cells. Mechanistic investigations confirmed that PZ1-Zein NPs significantly increased apoptosis, as shown by increased caspase-3/7 activity (5.8-fold vs. 2.6-fold). These findings highlight PZ1-Zein NPs as a promising nanomedicine strategy and a candidate functional component for future dual-functional scaffolds aimed at targeted hard tissue engineering and surgery in HNSCC management.

Therapeutic anti-diabetic peptides (ADPs) are an emerging class of clinically-relevant biologics with the potential to manage glucose (glycaemic) levels. However, the majority of existing computational pipelines are either narrowly focused or unverified. Here, we present a principled, end-to-end, and provenance-aware framework for the de novo generation, filtering and classification of ADPs. In terms of design, candidate peptides are derived from three complementary strategies: guided modification of functional motifs, recombination of conserved bioactive fragments, and a hybrid generative engine. Candidates are then subjected to biochemical triage (net charge, hydrophobicity, Boman index), homology screening, and APD-style predictors/calculators. For classification, we use a blend of (1) interpretable biochemical descriptors (net charge, hydrophobicity, Boman index), and (2) sequence-derived representations learned by a CNN-with-attention backbone, to parse local motifs and longer-range context. Classifier heads are automatically tuned with an Optimized Tree-structured Parzen Estimator (OptimizedTPE). Training used 238 experimentally validated ADPs with homology-aware splits (Train/Val/Internal-Test positives: 167/24/47) and a curated negative pool at a 2:1 ratio; additionally, Train-only weak-label augmentation added 412 screened positives (and matched negatives) for robustness. We report an evaluation on an independent, external panel of 180 peptides, fully disjoint from the training data in both source and time. On this unseen set, the model achieves ≈ 98.75% accuracy (F1 ≈ 0.985, precision ≈ 0.99, recall ≈ 0.98, specificity ≈ 0.99, ROC AUC ≈ 0.99). This suggests high sensitivity to true ADPs while tightly controlling false positives in the setting of realistic class imbalance. Taken together, these results make the framework a candidate for a reproducible, biologically-grounded, in silico screening layer for metabolic peptide therapeutics.

There is growing support and interest in postsecondary interdisciplinary environmental education, which integrates concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy, and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here is a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise in explaining changing water usage than discussing trade-offs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as a more nuanced understanding of student comprehension of complex interdisciplinary concepts.

Global sea turtle populations are in decline and so a global network of sea turtle nesting conservation programs have been established worldwide with the goal to protect vulnerable nesting mothers, and their clutches of eggs. Yet researchers have recently estimated that sea turtle nesting habitat is likely to suffer as a result of climate change and associated sea level rise. This study examines nest monitoring data from Costa Rica's Osa Peninsula with the aim to identify clutches located in suitable nesting habitat most susceptible to sea level rise and subsequent inundation. We analyze the impacts of six different sea level rise scenarios (from 0.25 m to 2 m) and discuss nesting inclinations and distributions of threatened Olive Ridley (Lepidochelys olivacea) and Green (Chelonia mydas) sea turtles on two beaches of the peninsula—known locally as Piro and Pejeperro. Sea-level rise scenarios on Piro beach indicated that 28.81% of the entire sample were likely to be inundated under a 0.25 m scenario, and 16.52% on Pejeperro beach. Under a more extreme, 2 m scenario, results indicated that 41.74% of nest sites on Piro and 24.55% on Pejeperro would be impacted. Results suggest that Olive Ridley turtles may be more susceptible to sea-level rise, based on their preferred nesting zones, commonly nesting closer to the tide line, as opposed to Green turtles that prefer to nest further from the tide line in vegetation zones where sea-level rise is likely to have less impact. Ultimately, the methodologies used in this study can support sea turtle conservation programs in assessing the potential effects of sea level rise and understanding nesting distributions on their nesting beaches, while also providing important insight in forecasting nest management and implementing monitoring techniques that may reduce the negative impacts associated with climate change and subsequent sea-level rise.

The idea of electronic-learning is based on technology intervene globally, this learning approach has attained greater attention in view of educational perspective and the advantages of e-learning in educational viewpoint. The present study will provide insights of face-to-face teaching as well as e- learning and teaching importance and how it influenced the 21st century teaching learning process. However, the number of diverse e-learning programs available to crutch teaching and learning process which is found to be expanding robustly. The chief concern for educational developers as well as teachers in education sector was selection of e-technology. However, it is well ball parked that whichever teaching need best supports as well as provide optimum learning opportunities is regarded as beneficial and best e-learning technology. Hence, the present study highlights diverse e-technologies utilized in educational sector and which would be better in educational institutes for towards online learning to bridges the gap between a student and a teacher from whichever different geographical location they are present. The educational system around the world is undergoing increasing pressure to use the new information and communication technology to acquaint students with the knowledge and information and require in this techno-savvy Era. To develop a knowledge society, it is essential to integrate ICT at all levels of the education system, e-content is a very powerful tool of education. It is the latest method of instruction that has attracted the attention of learners and teachers of all instruction systems. It is a valuable resource for the development of an information rich society where everyone, irrespective of caste, religion, race, region, gender bias is empowered to create, receive share and utilize information and knowledge for their economic, social, cultural, political, etc. upliftment and development. E-learning and e-teaching systems are involved in teachers’ professional activities and development if e-learning/e-teaching is the technology which supports the process of teachers’ learning of university courses, the teacher is in the position of e-learner, if e-learning/e-teaching is the content of the teachers’ institution curricula to be applied in the teaching process, the teacher switches from the position of 21st century e-Learner to the one of e-teacher in blended/ e-learning systems.

The capacity to capture and broadcast sports events with close to real-time volumetric reconstruction techniques opens exciting perspectives in how audiences can consume and interact with these contents. In this work, we propose the design of an real-time cinematography system that is capable of generating qualitative framing and editing of volumetric-captured content, by mimicking real broadcast footage. To illustrate our approach, we focus on the specific problem of cinematography for ring-based events such as Ultimate Fighting Championships (UFC). We start by extracting statistical features from hours of real footage to understand the specific framing and cutting behaviors of real broadcast directors. We then exploit these features in a real-time editing system, not only to replicate the behaviors in existing broadcasting, but also to generalize to novel camera layouts. We demonstrate our approach on the volumetric reconstruction of UFC fights, compare our results with baseline methods, and report different qualitative and quantitative evaluations.

Captive animals typically develop anticipatory behaviors, actions of increased frequency done in anticipation of an event such as feeding. Anticipatory behaviors can be an indicator of an animal's welfare. However, for rehabilitating animals that are expected to be reintroduced into the wild, these behaviors need to be extinguished to ensure successful release. Scheduled activities such as feeding occur daily and vocalizations could potentially be used to identify anticipatory behavior. Here, we tested the hypothesis that manatee calves modify their vocal production rate as a form of anticipatory behavior. Vocalizations of two Antillean manatee (Trichechus manatus manatus) calves were recorded for 10 min before, during, and after feeding sessions at Wildtracks, a manatee rehabilitation center in Belize. The number of calls were counted across recording sessions and three acoustic parameters were measured from calls including duration, frequency modulation, and center frequency. A repeated measures ANOVA comparing the number of calls across sessions indicated manatees produced significantly more calls before feeding sessions than during and after sessions. In addition, manatees increased the duration and lowered the frequency of calls before feeding sessions. This information can give further insight on ways to improve rehabilitation protocols and manage human interactions to increase the overall survival rate of rehabilitated manatees when released back into the wild.