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Large aggregations of wild mammals are declining globally, sometimes before they can be scientifically documented and their ecological value understood, although non-scientists may be aware of these phenomena. Video recording of wildlife by non-academics is becoming more frequent with increasing activities of humans in natural habitats. This opportunistically-collected material can document rare or ecologically important events, such as large aggregations, and thus provide potentially valuable data for ecologists and conservationists. We used footage of a large herd of Cape buffalo recorded by a wildlife film producer in the Mababe Depression, northern Botswana, and applied automated detection and tracking techniques to count individuals as they moved across the video frame. To complement this demographic snapshot, we accessed local ecological knowledge from stakeholders to provide contextual information for a more complete understanding of the ecosystem processes potentially driving population movement and trends. Manual review of the automated count resulted in a minimum verified group size of 3676 buffalo and an extrapolated total estimated herd size of approximately 4128 (range 3676-5041), which matched herd size estimates provided by local stakeholders. To our knowledge, this is the largest documented group of Cape buffalo, which we identify as a mega-herd. We recommend research into the costs, benefits, and ecological consequences of forming such large groups. This study represents an opportunistic collaboration among wildlife filmmakers, computer scientists, lay experts, and ecologists, and highlights the value of combining contributions from different fields to generate information that can be used in conservation practice.

Scientists invest years and decades in research discoveries that may lead to important life-saving technologies that benefit humanity. However, many of these researchers may not be familiar with determining whether their ideas can be turned into a viable product and made sellable. Educational programs such as the National Science Foundation I-Corps Program and I-RED from the National Institute of General Medical Sciences at the NIH support this shift toward faculty gaining greater entrepreneurship knowledge. These programs provide additional preparation for faculty, particularly in specialized business information and entrepreneurial skills. Despite the importance of commercialization training, few post-doctoral and faculty members in life sciences receive formal education in intellectual property, entrepreneurship, and research commercialization. Accordingly, this article aims to provide a guide to help start or facilitate the entrepreneurial journey to support the commercialization of their creative outputs. The article provides a timeline of events from idea discovery to technology commercialization, translating academic skills into entrepreneurial careers, understanding the entrepreneurial ecosystem, and discussing the pros and cons of entrepreneurship for scientists. The article emphasizes the need for academic researchers to gain knowledge in research commercialization and entrepreneurship to impact and benefit humanity beyond the laboratory.

The COVID-19 pandemic demonstrated the potential role of digital health tools in enhancing pandemic preparedness and response. These tools became essential, supporting not only health care delivery but also decision-making, communication, case identification, contact tracing, surveillance, vaccination rollout, and intervention evaluation. The interest in applying digital health tools to pandemic preparedness and response motivated conversations about digital epidemiology-a field of study that aims to provide insight into health and disease determinants by leveraging diverse digital data sources. In a globalized world, effective preparedness and response to pandemics require coordinated global action. This study investigates experts' opinions on strategies for improving global health security through the effective use of digital epidemiology, considering the current landscape of digital determinants of health. Epidemiologists, public health specialists, data scientists, and professionals with expertise in various components of digital health were recruited through convenience and snowball sampling methods. Their opinions were elicited using an electronic questionnaire developed by the authors in Research Electronic Data Capture (REDCap; Vanderbilt University). To ensure a global perspective, participants were recruited from Africa, North America, Oceania, and Europe. Thematic analysis and the strengths, weaknesses, opportunities, and threats (SWOT) analysis framework were used to analyze participants' responses. Most participants were familiar with the concept of digital epidemiology and expressed positive sentiments about its potential in strengthening global health security. Privacy and security, along with ethical and legal considerations, were ranked by most experts as high priority areas that decision-makers and implementers must consider to ensure sustainable integration of digital epidemiology tools in future pandemic preparedness and response. A SWOT analysis of participants' views on the promise of digital epidemiology revealed fewer strengths and more weaknesses compared to other components of the analysis framework. This study highlights the growing recognition of digital epidemiology as a critical tool for enhancing global health security, particularly using nontraditional data sources and emerging technologies, including artificial intelligence. The study affirms the need for a globally coordinated approach to governance, regulation, and investment in digital health infrastructure to ensure the responsible and effective application of digital innovations in epidemiological practice.

The Controlled Release Society (CRS, www.controlledrelease.org) held its fourth iteration of research and development in oral peptide administration on 14 July 2025 in Philadelphia (United States), entitled "Recent advances in oral peptide delivery: from molecule to market." The previous versions were held in 2008, 2014, and 2023 (online), so it is a topic of continuing interest to drug delivery scientists as several oral peptide products have been released in the market over the period despite the enormous technical and commercial challenges involved. The workshop was co-sponsored by Frontiers in Drug Delivery, Novo Nordisk, Johnson and Johnson, Merck, Protagonist Therapeutics, Quotient Sciences, Genentech (Roche), and Bristol-Myers Squibb. It consisted of nine talks and two roundtable sessions. The overall aim of the workshop was to provide an update on the current clinical oral peptide programmes, address mechanistic progress on permeation enhancers, and evaluate the limitations of preclinical bioassays and animal models.

Malappuram district, Kerala, ranked 7th among the most landslide-prone districts in India, according to the Landslide Atlas of India 2023 from the National Remote Sensing Centre (NRSC). The aim of this study is to map landslide susceptibility zones at the district level in Malappuram, Kerala, using GIS-based Weighted Overlay Analysis (WOA). The most commonly used factors for slope failure preparation were slope, elevation, aspect, curvature, land use/land cover, annual rainfall, distance to road, distance to river, soil depth, geology, LS factor, drainage density, Stream Power Index, and Topographic Wetness Index. The AHP technique has been applied to weight the 14 conditioning factors, and Pearson correlation has been used to assess the relation among these variables and between these variables and the landslide points. We have found that most variables are independent, with a maximum correlation coefficient of 0.72. Five respondents ranked 14 conditioning variables using a structured AHP matrix in a paired comparison. The Consistency Ratio obtained is 0.047, which is <&#x2009;0.10. Slope was given the highest weightage (18%), followed by geology (13%) and annual rainfall (10%), which have the highest contributions to slope failures. The 14 conditioning factors were reclassified into five categories with values ranging from 1 to 5. The 14 classified factors were then combined to produce the landslide susceptibility map of the study area. The landslide susceptible maps were classified into low (39%, ~&#x2009;1384 km2), moderate (51%, ~&#x2009;1811 km2), and high landslide susceptibility zones (10%, ~&#x2009;355 km2). The high landslide susceptible areas are distributed over, in, and around the north-east highland of the district and are characterised by a combination of high slopes, charnockite geology, and high rainfall. The model has been validated using historical landslides point and random non-landslide points. The ratio of landslide and non-landslide points is 70:30 for training and testing, respectively. We obtained AUC values of 0.921 and 0.897 for training and testing, respectively. At the village level, the most affected villages due to landslides have been selected based on the percentage of land area falling within the highly landslide susceptible zones among all 135 revenue villages of the district. The most susceptible villages, in descending order, are Kerala Estate, Chokkad, Akampadam, Karulai, and Kurumbalangode. A detailed landslide susceptibility map of Malappuram district will enable scientists and authorities to plan mitigation actions, regulate construction activities in highly affected areas, and implement an early warning system at the local level.

Fleeting public interest in the Viking mission inspired Carl Sagan to devise a new mode of science communication. One result was the Cosmos television series. Carl's global success offended many in the scientific community, and he was punished despite his solid research credentials. Almost 50 years later, the importance of public outreach by scientists seems to have reached greater professional acceptance. Key Words: Science communication-Viking-Cosmos-Mars-Public outreach. Astrobiology 00, 000-000.

Decades before medical definitions of developmental normalcy revolved around statistical averages, nineteenth-century medical scientists identified a non-statistical "normal" that cohered within racial groups but was not generalizable across them. Using early child medicine treatises and anatomical, physiological, and ethnological texts, this article argues that nineteenth-century child development science was a race-making enterprise. The first sections analyze texts on child development and disease, identifying the racial parameters of developmental norms and the developmental events most frequently associated with racial differentiation: cranial suture closure and puberty. The following sections argue that variable rates of development and the degree of synchronicity between mental and physical development produced racial hierarchies and threatened racial degeneration. By examining "ethnic" classifications of idiocy, in which developmental timing considered typical for Black children was pathologized in White children, this article argues that developmental disorder posed a threat to racial order. As Darwinian evolutionism introduced scientific and social concerns about the historical contingency of racial progress, the clinical management of child development acquired newfound importance as a safeguard for White racial purity. Joining histories of nineteenth-century child development science and antebellum medical cultures with disability history, this article offers a pre-history of "developmental disability" as a racial category.

The stochastic model of chromatography mathematically represents the molecular mass transfer that occurs during a separation. Single-molecule microscopy allows for direct visualization of molecular analytes adsorbing within column materials. Experimental single-molecule data and the stochastic model can predict elution profiles using the adjustable variable r&#x304;m, the average number of adsorptions per molecule. Previously, only a single r&#x304;m value was used to match either peak location or shape, while the effects of adjusting np, the number of modeling points, have not been studied. Here, we systematically explore a wide range of these two variables in the stochastic model to determine if it is possible to optimize agreement between modeled single-molecule and high-performance liquid chromatography (HPLC) chromatograms. A metric to quantify chromatogram agreement is introduced by taking the weighted difference in the elution time and shape of the chromatograms. We determine the non-linear effects of r&#x304;m and np on peak height, width, and asymmetry and link the observations to the molecular behavior. Applying our approach to experiments with variable flow rate shows that increased sampling of rare, long time adsorption events affects agreement between simulated and HPLC elution profiles. Finally, we make quantitative recommendations that the single-molecule experiments should sample available binding sites following an exponential association model and that np must be > 1.5 &#xd7; r&#x304;m to achieve accurate results. Overall, we verify that the current form of the stochastic model based solely on mass transfer is unable to simultaneously match both peak location and shape and make recommendations for future improvements to the model by separation scientists.

Prostate cancer is a major cause of disease and mortality among older men (mean age 67.3 years old) in the United States and globally. Given the biological heterogeneity of this cancer in this short- and long-term United States retrospective population-based analysis, the focus is on incidence, mortality, and survival by age, race/ethnicity, stage, and severity in cohort entry time periods (1975-99 and 2000-22), and disease duration. This comparative cohort short- and long-term study is intended to provide age-adjusted epidemiologic and demographic survival and mortality data for convenient reference by all physicians, scientists, insurance underwriters, and others interested in cancer mortality follow-up.

Scientists and laypeople alike have long been inspired by infants' acquisition of skills-from walking to talking to interacting with objects. Indeed, complementary aims of developmental science are to characterize infants' changing skills and identify the experiences that propel learning. Our observations of infants' unconstrained behavior in the ecologically-valid home environment have led to new insights on learning that integrate theory at the intersection of Piaget's writings on embodied action and Vygotsky's writings on the socially embedded nature of learning. These insights formed the basis of my plenary talk at the Jean Piaget Society conference, at which I underscored the need to: (1) surmount soundbites that early learning is rapid and effortless by characterizing the immense amount of practice that infants generate across domains such as playing, walking, and talking; (2) reinforce Piaget's observation that cognition is grounded in sensorimotor action; (3) challenge assumptions that controlling the environment is the only way to identify learning mechanisms; and (4) elucidate the shared and unique developmental contexts that frame infants' learning across cultural communities. Objective documentation of the natural behaviors, cultural niches, and learning opportunities of infants around the world is fundamental to science.

&#xbb; Artificial intelligence (AI) is increasingly integrated across the total hip and knee arthroplasty care continuum, including preoperative risk stratification and templating, intraoperative computer-vision guidance and robotic assistance, and postoperative complication detection and outcome prediction. &#xbb; Machine-learning models often outperform traditional statistical approaches in predicting complications, discharge disposition, operative time, and patient-reported outcomes after total joint arthroplasty. &#xbb; Deep learning and computer vision systems are rapidly improving radiographic interpretation, implant templating, mechanical alignment measurement, and early detection of prosthetic loosening. &#xbb; Despite promising performance, most AI tools remain limited by incomplete external validation, workflow integration challenges, and potential bias from nonrepresentative data sets. &#xbb; Future progress in arthroplasty AI will depend on multimodal data integration, large-scale registries, prospective validation, and careful collaboration between surgeons and data scientists to ensure safe and clinically meaningful implementation.

Clear, consistent language is essential in toxicology and risk assessment because terminology directly affects risk communication and understanding. The original concept of a "No Harm Dose of Reasonable Certainty" (NHDoRC) for an amount of chemical to which people can be exposed without detrimental effects is a plain language expression that clearly describes regulatory intent. However, the subsequent introduction and use of many related technical terms, such as NOAEL, BMD, RP and PoD, with almost the same meaning, can confuse non-experts and even scientists working in different regulatory entities. Similarly, ADI, RfD, TDI, MRL, HBGV and RV are all different abbreviations used in toxicology and risk assessment to describe the "acceptable" human dose in the context of food, water, and environmental chemicals. Likewise, the frequent use of terms such as margin of exposure (MoE) and margin of safety (MoS) interchangeably further complicates communication, as they are mathematically (and toxicologically) quite different. NOAEL and BMD10 are sometimes used interchangeably, but they usually represent two different points on the dose-response curve. Because of the many complications in the terminology used in risk assessment, a committee should be established to harmonize terminology across agencies and the wider risk assessment community, including industry and academia. The recommendations from such a committee would improve clarity, transparency, regulatory efficiency, and public trust in chemical risk assessment.

Earprint biometrics has been proposed as a forensic identification method based on the distinctive morphology of the external human ear and the prints it may leave on surfaces during criminal activity. Since the late twentieth century, earprints have occasionally been introduced as evidence in criminal investigations and court proceedings in several jurisdictions, including the Netherlands, the United Kingdom, Switzerland, and the United States. Despite these applications, the scientific validity of earprint comparison remains contested. This article presents a narrative review of the forensic, anthropological, and legal literature on earprint identification. It examines the development of earprint research from early anthropometric approaches to contemporary digital and automated comparison techniques. Particular attention is given to the anatomical basis of ear morphology, the classification of earprints, and the methodological frameworks used in forensic comparison. The review also evaluates empirical studies addressing variability in earprint deposition, examiner subjectivity, and the absence of validated statistical models for assessing evidential strength. The medico-legal implications of earprint evidence are examined through analysis of forensic casework and appellate decisions in which earprint testimony played a significant role. These cases illustrate the risks associated with the premature adoption of forensic techniques lacking standardized protocols and empirically established error rates. The review concludes that although earprints may provide investigative information and potentially corroborative evidence, current scientific limitations prevent their reliable use as independent identification evidence. Future progress requires standardized international protocols, large-scale validation studies, probabilistic interpretation frameworks, and interdisciplinary collaboration between forensic scientists, statisticians, and legal scholars.