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Metasurfaces are a topic of significant research and are used in various applications due to their unique ability to manipulate electromagnetic waves in microwave and optical frequencies. These artificial sheet materials, which are usually composed of metallic patches or dielectric etchings in planar or multi-layer configurations with subwavelength thickness, have the advantages of light weight, ease of fabrication, and ability to control wave propagation both on the surface and in the surrounding free space. Recent progress in the field has been classified by application and reviewed in this article. Starting with the development of frequency-selective surfaces and metamaterials, the unique capabilities of different kinds of metasurfaces have been highlighted. Surface impedance can be varied and manipulated by patterning the metasurface unit cells, which has broad applications in surface wave absorbers and surface waveguides. They also enable beam shaping in both transmission and reflection. Another important application is to radiate in a leaky wave mode as an antenna. Other applications of metasurfaces include cloaking, polarizers, and modulators. The controllable surface refractive index provided by metasurfaces can also be applied to lenses. When active and non-linear components are added to traditional metasurfaces, exceptional tunability and switching ability are enabled. Finally, metasurfaces allow applications in new forms of imaging.

Colistin resistance, driven by chromosomal mutations and the spread of plasmid-mediated MCR genes, has emerged as a critical challenge in combating multidrug-resistant Gram-negative bacteria. This resistance compromises the efficacy of colistin, leading to higher treatment failure rates, prolonged hospitalizations, and increased mortality. Recent studies have highlighted key mechanisms, including lipid A modifications, that enable bacteria to evade colistin’s effects. The global spread of MCR genes exacerbates the issue, underlining the need for improved diagnostics and rapid detection of resistant strains to prevent adverse patient outcomes. To combat this growing threat, a multifaceted approach is essential, involving enhanced antimicrobial stewardship, stricter infection control measures, and continued research into alternative therapies and diagnostic methods. Collaborative efforts from researchers, healthcare providers, policymakers, and the pharmaceutical industry are crucial to preserving colistin’s effectiveness and mitigating the broader impact on public health.

Background Body donation remains crucial for medical education and research, yet donor shortages persist worldwide, often due to limited awareness and cultural barriers. The Theory of Planned Behavior (TPB) offers a robust framework to understand and influence donation intentions. This study evaluates the efficacy of a culturally sensitive, TPB-based educational intervention aimed at enhancing behavioral determinants related to body donation among adults in India. Methods A quasi-experimental pre-post design was employed with 163 adult participants. The multi-component intervention included multimedia educational materials, peer discussions, motivational media, and practical guidance on registration. Participants completed a validated, bilingual TPB questionnaire assessing knowledge, attitudes, subjective norms, perceived behavioral control, and behavioral intentions immediately before and after the intervention. Statistical analyses involved paired-sample t-tests to compare pre- and post-intervention scores, multiple linear regression to identify predictors of behavioral intention, and subgroup analyses examining sociodemographic influences. Results Post-intervention assessments revealed statistically significant improvements across all TPB constructs (all p  < 0.001). Knowledge increased markedly from a mean score of 2.7 to 3.8 (on a 0–4 scale), corresponding to a large effect size (Cohen’s d = 1.25). Attitude, subjective norms, and perceived behavioral control all showed medium effect sizes (d = 0.65–0.70). Multiple regression indicated that attitude (β = 0.40, p  < 0.001), subjective norms (β = 0.32, p  < 0.01), and perceived behavioral control (β = 0.26, p  < 0.01) were independent predictors of post-intervention intention, jointly explaining 52% of the variance (R² = 0.52). Notably, willingness or intention to donate increased to 66% post-intervention, with higher readiness observed among participants with prior knowledge, urban residence, male gender, higher education, and older age. Conclusion The TPB-based, culturally tailored educational intervention effectively enhanced knowledge and psychosocial determinants of body donation intention among Indian adults. These findings underscore the potential of theory-driven, culturally adapted programs to increase readiness for body donation, offering scalable strategies to address donor shortages in diverse cultural contexts globally.

The integration of telehealth into palliative care has garnered significant attention due to its potential to enhance both access and quality of care, particularly for patients in rural and underserved areas. This interest stems from the need to address geographical and logistical barriers that traditionally hinder palliative care delivery. Despite its potential benefits, the effectiveness of telehealth and the challenges associated with its implementation remain underexplored, necessitating further investigation. This study aims to critically evaluate the effectiveness of telehealth in palliative care by focusing on several key areas: its impact on access to care, symptom management, patient satisfaction, and cost-effectiveness. To achieve this, a systematic review was conducted, synthesizing data from various studies that investigated telehealth interventions within palliative care settings. The review employed a comprehensive search strategy across electronic databases, concentrating on randomized controlled trials (RTCs) published between 2014 and 2024. To ensure the reliability of the findings, low-quality and unrelated studies were excluded, and the remaining studies were meticulously analyzed for bias and methodological quality. The review's findings indicate that telehealth significantly enhances access to palliative care, allowing patients to receive timely and appropriate care without the need for extensive travel. It also improves symptom management and patient satisfaction, aligning to provide patient-centered care. Additionally, telehealth is cost-effective by reducing expenses associated with travel and in-person visits. These benefits highlight telehealth's potential to address some of the critical challenges in palliative care delivery. Despite its advantages, implementing telehealth in palliative care is not without challenges. Technological barriers, such as inadequate infrastructure and device limitations, pose significant hurdles. Integration issues, including the need for seamless incorporation into existing care systems, and varying levels of digital literacy among patients and caregivers, also impact the effectiveness of telehealth. Addressing these challenges is crucial for optimizing telehealth's implementation. Ensuring that telehealth solutions are accessible, user-friendly, and well-integrated into care practices is essential for fully leveraging its potential benefits.

Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high incidences and mortality rates, which raised the need for effective diagnostic strategies for the early detection and management of CRC. While there are several conventional cancer diagnostics available, they have certain limitations that hinder their effectiveness. Significant research efforts are currently being dedicated to elucidating novel methodologies that aim at comprehending the intricate molecular mechanism that underlies CRC. Recently, microfluidic diagnostics have emerged as a pivotal solution, offering non-invasive approaches to real-time monitoring of disease progression and treatment response. Microfluidic devices enable the integration of multiple sample preparation steps into a single platform, which speeds up processing and improves sensitivity. Such advancements in diagnostic technologies hold immense promise for revolutionizing the field of CRC diagnosis and enabling efficient detection and monitoring strategies. This article elucidates several of the latest developments in microfluidic technology for CRC diagnostics. In addition to the advancements in microfluidic technology for CRC diagnostics, the integration of artificial intelligence (AI) holds great promise for further enhancing diagnostic capabilities. Advancements in microfluidic systems and AI-driven approaches can revolutionize colorectal cancer diagnostics, offering accurate, efficient, and personalized strategies to improve patient outcomes and transform cancer management.

This study was designed to understand the molecular mechanisms of azole resistance in Candida tropicalis using genetic and bioinformatics approaches. Thirty-two azole-resistant and 10 azole-susceptible (S) clinical isolates of C . tropicalis were subjected to mutation analysis of the azole target genes including ERG11 . Inducible expression analysis of 17 other genes potentially associated with azole resistance was also evaluated. Homology modeling and molecular docking analysis were performed to study the effect of amino acid alterations in mediating azole resistance. Of the 32 resistant isolates, 12 (37.5%) showed A395T and C461T mutations in the ERG11 gene. The mean overexpression of CDR1 , CDR3 , TAC1 , ERG1 , ERG2 , ERG3 , ERG11 , UPC2 , and MKC1 in resistant isolates without mutation (R-WTM) was significantly higher (p<0.05) than those with mutation (R-WM) and the sensitive isolates (3.2–11 vs. 0.2–2.5 and 0.3–2.2 folds, respectively). Although the R-WTM and R-WM had higher (p<0.05) CDR2 and MRR1 expression compared to S isolates, noticeable variation was not seen among the other genes. Protein homology modelling and molecular docking revealed that the mutations in the ERG11 gene were responsible for structural alteration and low binding efficiency between ERG11p and ligands. Isolates with ERG11 mutations also presented A220C in ERG1 and together T503C, G751A mutations in UPC2 . Nonsynonymous mutations in the ERG11 gene and coordinated overexpression of various genes including different transporters, ergosterol biosynthesis pathway, transcription factors, and stress-responsive genes are associated with azole resistance in clinical isolates of C . tropicalis .

Head-fixed behavioral experiments in rodents permit unparalleled experimental control, precise measurement of behavior, and concurrent modulation and measurement of neural activity. Here, we present OHRBETS (Open-Source Head-fixed Rodent Behavioral Experimental Training System; pronounced ‘Orbitz’), a low-cost, open-source platform of hardware and software to flexibly pursue the neural basis of a variety of motivated behaviors. Head-fixed mice tested with OHRBETS displayed operant conditioning for caloric reward that replicates core behavioral phenotypes observed during freely moving conditions. OHRBETS also permits optogenetic intracranial self-stimulation under positive or negative operant conditioning procedures and real-time place preference behavior, like that observed in freely moving assays. In a multi-spout brief-access consumption task, mice displayed licking as a function of concentration of sucrose, quinine, and sodium chloride, with licking modulated by homeostatic or circadian influences. Finally, to highlight the functionality of OHRBETS, we measured mesolimbic dopamine signals during the multi-spout brief-access task that display strong correlations with relative solution value and magnitude of consumption. All designs, programs, and instructions are provided freely online. This customizable platform enables replicable operant and consummatory behaviors and can be incorporated with methods to perturb and record neural dynamics in vivo.

The opioid epidemic in the United States remains a major public health concern, with opioid-related deaths increasing more than 8-fold since 1999. Chronic pain, affecting 1 in 5 US adults, is a key contributor to opioid use and misuse. While previous research has explored clinical and behavioral predictors of opioid risk, less attention has been given to large-scale linguistic patterns in public discussions of pain. Social media platforms such as X (formerly Twitter) offer real-time, population-level insights into how individuals express pain, distress, and coping strategies. Understanding these linguistic markers matters because they can reveal underlying psychological states, perceptions of health care access, and community-level opioid risk factors, offering new opportunities for early detection and targeted public health response. This study aimed to examine linguistic markers of pain communication on the social media platform X and assess whether language patterns differ among US states with high and low opioid mortality rates. We also evaluated the predictive power of these linguistic features using machine learning and identified key thematic structures through semantic network analysis. We collected 1,438,644 pain-related tweets posted between January and December 2021 using tweepy and snscrape. Tweets from 2 high-opioid mortality states (Ohio and Florida) and 2 low opioid mortality states (South and North Dakota) were selected, resulting in 31,994 tweets from high-death states (HDS) and 750 tweets from low-death states (LDS). Six machine learning algorithms (random forest, k-nearest neighbor, decision tree, naive Bayes, logistic regression, and support vector machine) were applied to predict state-level opioid mortality risk based on linguistic features derived from Linguistic Inquiry and Word Count. Synthetic Minority Oversampling Technique was used to address class imbalance. Semantic network analysis was conducted to visualize co-occurrence patterns and conceptual clustering. The random forest model demonstrated the strongest predictive performance, with an accuracy of 94.69%, balanced accuracy of 94.69%, κ of 0.89, and an area under the curve of 0.95 (P<.001). Tweets from HDS contained significantly more affective pain words (t =10.84; P<.001; Cohen d=0.12), health care access references, and expressions of distress. LDS tweets showed greater use of authenticity markers (t =-10.04; P<.001) and proactive health-seeking language. Semantic network analysis revealed denser discourse in HDS (density=0.28) focused on distress and barriers to care, while LDS discourse emphasized recovery and optimism. Our findings demonstrated that linguistic markers in publicly shared pain-related discourse show distinct and predictable differences across regions with varying opioid mortality risks. These linguistic patterns reflect underlying psychological, social, and structural factors that contribute to opioid vulnerability. Importantly, they offer a scalable, real-time resource for identifying at-risk communities. Harnessing social media language analytics can strengthen early detection systems, guide geographically targeted public health messaging, and inform policy efforts aimed at reducing opioid-related harm and improving pain management equity.

Soil-transmitted helminth (STH) infections (hookworms, Trichuris, Ascaris) and Strongyloides spp. are associated with a substantial global burden and high morbidity. Sensitive and specific methods for diagnosis of these infections are essential for mapping the burden in communities, accurate assessment of infection levels, to guide interventions and monitoring the success of STH control programs. Despite considerable progress to control STH over several decades, we are still far from identifying a fully adequate diagnostic test. Conventional microscopy-based methods such as direct Kato-Katz smear or mounts after stool centrifugation/ flotation-based concentration techniques have been the mainstay of diagnosis, especially in resource-poor countries where these infections abound. However, recently, these are being adapted to closed, easy to perform, digital formats, thereby improving the sensitivity as well as applicability in a remote, resource-limited setting. The use of image analysis systems to identify and quantify helminth eggs, with potential adaptation to smartphones, is also promising. Antibody detection tests have a limited role mostly in the case of Strongyloides hyperinfection. Coproantigen detection tests have been developed and used in veterinary practice for detection of STH, but these have not been evaluated for use in humans. More sensitive molecular diagnostics, including assays developed with new bioinformatic tools and techniques such as polymerase chain reaction (PCR), quantitative PCR (qPCR) and loop-mediated amplification assay, can help in the clear and precise assessment of STH burden during elimination phase and are of immense value for diagnosis in areas with low endemicity and in travelers to endemic regions. Moreover, the molecular techniques will help detect new species that may emerge. Sample preservation and efficient DNA extraction are critical and significantly affect the efficiency of molecular diagnostic tests. In addition to the diagnosis of clinical or asymptomatic infection in humans, detection of STH eggs in environmental samples is imperative to boost STH control efforts. Overall the diagnostic performance, cost-effectiveness, ease of performance, rapidity and in-field applicability of any test should be considered when choosing from the various diagnostic assays in areas with different endemicity, in addition to striving towards the development of novel technologies and optimization of existing methods. Keywords: soil-transmitted helminths, diagnosis, microscopy, molecular

This comprehensive review explores the complexities surrounding pancreatic head cancer, a highly fatal and challenging-to-treat illness with a survival rate of less than five years. Despite being a major contributor to cancer-related deaths, pancreatic head malignancy often eludes early detection due to its posterior location and high metastatic potential. The review delves into the associated symptoms, including gastric outlet obstruction and obstructive jaundice, highlighting the impact on the patient's eligibility for surgery. Examining recent advancements, the article discusses fast-track surgery recovery programs and emerging immunotherapeutic approaches, acknowledging the unique challenges posed by the immunosuppressive environment of pancreatic head cancer. Additionally, the review elucidates the intricate relationship between pancreatic cancer and glucose levels, emphasizing the role of islets of Langerhans in insulin production. The pathogenesis section explores lifestyle and genetic factors contributing to pancreatic head carcinoma, shedding light on risk factors such as smoking, obesity, diabetes, and hereditary predispositions. The extensive analysis of pancreatic cancer diagnosis methods encompasses imaging techniques, biopsies, and biomarkers, emphasizing the challenges posed by late-stage diagnoses. Addressing treatment modalities, the review emphasizes the significance of surgery, chemotherapy, radiotherapy, and targeted therapy. The intricate details of neoadjuvant, immunotherapy, and microbial therapy provide a comprehensive understanding of evolving treatment strategies. The review concludes by highlighting promising areas of research, including oncolytic viral therapy and gene editing technology, aiming to enhance the limited treatment options for this devastating disease.