The Spiral of Tillaux: dead on accurate; a cadaveric study.

INTRODUCTION: The Spiral of Tillaux describes the historically accepted insertion distances of the medial rectus, inferior rectus, lateral rectus, and superior rectus from the limbus: 5.5 mm, 6.5 mm, 6.9 mm, and 7.7 mm, respectively. The corneal diameters are historically accepted to be 11.7 mm horizontally and 10.6 mm vertically in adults. We investigated the variability of the insertion distances of the extraocular rectus muscles from the limbus as well as the corneal diameters using eyes from human cadavers and compared our measurements to these historically accepted measurements. METHODS: A sample of 60 eyes were included. For each eye, a 360 peritomy was conducted and the conjunctiva bluntly dissected to view the sclera. Muscle hooks were utilized to isolate the extraocular rectus muscles. Calipers were used to measure the insertion distances of the rectus muscles as well as the corneal diameters. RESULTS: The mean rectus muscle insertions distances from the limbus were medial 5.28 mm, inferior 5.72 mm, lateral 6.40 mm, and superior 6.78 mm. These insertion distances were shorter than the historical benchmarks (p < .01). However, observed maximum distances of the rectus muscles were all greater than the historically accepted benchmarks, with the medial, inferior, lateral, and superior rectus muscles being 6.4 mm, 7.3 mm, 7.4 mm, and 7.8 m from the limbus, respectively. The mean width and height of the cornea were 11.7 mm and 10.7 mm, respectively, and similar to the expected ranges. CONCLUSION: This study concludes that variability does exist from the historically accepted Spiral of Tillaux measurements. In addition, significant variation exists between male and female rectus muscle insertions. However, we did confirm that the rectus muscles followed the same spiral pattern described by the Spiral of Tillaux and concluded that the corneal diameters are consistent with previously accepted values.

Extravasation and infiltration: under-recognised complications of intravenous therapy.

Occasionally, the administration of intravenous (IV) therapies can go wrong. Infiltration or extravasation is a complication when a drug or IV therapy leaks into the tissues surrounding the vascular access device. Extravasation can cause serious and often life-changing injuries. Extravasation is often associated with systemic anti-cancer therapy but non-chemotherapy drugs have been reported as having a greater risk of serious complications. This study outlines the first UK Infusion unit evaluation of the ivWatch infusion monitoring device which was undertaken from August 2023 to January 2024. Out of 2254 infusions monitored with ivWatch, the device prevented 122 cases of infiltration and extravasation from causing any harm to the patient, corresponding to a 5.4% 'check IV' notification rate.

Effects of dispersal and temperature variability on phytoplankton realized temperature niches.

Phytoplankton species exhibit fundamental temperature niches that drive observed species distributions linked to realized temperature niches. A recent analysis of field observations of Prochlorococcus showed that for all ecotypes, the realized niche was, on average, colder and wider than the fundamental niche. Using a simple trait-based metacommunity model that resolves fundamental temperature niches for a range of competing phytoplankton, we ask how dispersal and local temperature variability influence species distributions and diversity, and whether these processes help explain the observed discrepancies between fundamental and realized niches for Prochlorococcus. We find that, independently, both dispersal and temperature variability increase realized temperature niche widths and local diversity. The combined effects result in high diversity and realized temperature niches that are consistently wider than fundamental temperature niches. These results have broad implications for understanding the drivers of phytoplankton biogeography as well as for refining species distribution models used to project how climate change impacts phytoplankton distributions.

Predicting Colonic Neoplasia Surgical Complications: A Machine Learning Approach.

BACKGROUND: A range of statistical approaches have been used to help predict outcomes associated with colectomy. The multifactorial nature of complications suggests that machine learning algorithms may be more accurate in determining postoperative outcomes by detecting nonlinear associations, which are not readily measured by traditional statistics. OBJECTIVE: The aim of this study was to investigate the utility of machine learning algorithms to predict complications in patients undergoing colectomy for colonic neoplasia. DESIGN: Retrospective analysis using decision tree, random forest, and artificial neural network classifiers to predict postoperative outcomes. SETTINGS: National Inpatient Sample database (2003-2017). PATIENTS: Adult patients who underwent elective colectomy with anastomosis for neoplasia. MAIN OUTCOME MEASURES: Performance was quantified using sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve to predict the incidence of anastomotic leak, prolonged length of stay, and inpatient mortality. RESULTS: A total of 14,935 patients (4731 laparoscopic, 10,204 open) were included. They had an average age of 67 ± 12.2 years, and 53% of patients were women. The 3 machine learning models successfully identified patients who developed the measured complications. Although differences between model performances were largely insignificant, the neural network scored highest for most outcomes: predicting anastomotic leak, area under the receiver operating characteristic curve 0.88/0.93 (open/laparoscopic, 95% CI, 0.73-0.92/0.80-0.96); prolonged length of stay, area under the receiver operating characteristic curve 0.84/0.88 (open/laparoscopic, 95% CI, 0.82-0.85/0.85-0.91); and inpatient mortality, area under the receiver operating characteristic curve 0.90/0.92 (open/laparoscopic, 95% CI, 0.85-0.96/0.86-0.98). LIMITATIONS: The patients from the National Inpatient Sample database may not be an accurate sample of the population of all patients undergoing colectomy for colonic neoplasia and does not account for specific institutional and patient factors. CONCLUSIONS: Machine learning predicted postoperative complications in patients with colonic neoplasia undergoing colectomy with good performance. Although validation using external data and optimization of data quality will be required, these machine learning tools show great promise in assisting surgeons with risk-stratification of perioperative care to improve postoperative outcomes. See Video Abstract . PREDICCIN DE LAS COMPLICACIONES QUIRRGICAS DE LA NEOPLASIA DE COLON UN ENFOQUE DE MODELO DE APRENDIZAJE AUTOMTICO: ANTECEDENTES:Se han utilizado una variedad de enfoques estadísticos para ayudar a predecir los resultados asociados con la colectomía. La naturaleza multifactorial de las complicaciones sugiere que los algoritmos de aprendizaje automático pueden ser más precisos en determinar los resultados posoperatorios al detectar asociaciones no lineales, que generalmente no se miden en las estadísticas tradicionales.OBJETIVO:El objetivo de este estudio fue investigar la utilidad de los algoritmos de aprendizaje automático para predecir complicaciones en pacientes sometidos a colectomía por neoplasia de colon.DISEÑO:Análisis retrospectivo utilizando clasificadores de árboles de decisión, bosques aleatorios y redes neuronales artificiales para predecir los resultados posoperatorios.AJUSTE:Base de datos de la Muestra Nacional de Pacientes Hospitalizados (2003-2017).PACIENTES:Pacientes adultos sometidos a colectomía electiva con anastomosis por neoplasia.INTERVENCIONES:N/A.PRINCIPALES MEDIDAS DE RESULTADO:El rendimiento se cuantificó utilizando la sensibilidad, especificidad, precisión y la característica operativa del receptor del área bajo la curva para predecir la incidencia de fuga anastomótica, duración prolongada de la estancia hospitalaria y mortalidad de los pacientes hospitalizados.RESULTADOS:Se incluyeron un total de 14.935 pacientes (4.731 laparoscópicos, 10.204 abiertos). Presentaron una edad promedio de 67 ± 12,2 años y el 53% eran mujeres. Los tres modelos de aprendizaje automático identificaron con éxito a los pacientes que desarrollaron las complicaciones medidas. Aunque las diferencias entre el rendimiento del modelo fueron en gran medida insignificantes, la red neuronal obtuvo la puntuación más alta para la mayoría de los resultados: predicción de fuga anastomótica, característica operativa del receptor del área bajo la curva 0,88/0,93 (abierta/laparoscópica, IC del 95%: 0,73-0,92/0,80-0,96); duración prolongada de la estancia hospitalaria, característica operativa del receptor del área bajo la curva 0,84/0,88 (abierta/laparoscópica, IC del 95%: 0,82-0,85/0,85-0,91); y mortalidad de pacientes hospitalizados, característica operativa del receptor del área bajo la curva 0,90/0,92 (abierto/laparoscópico, IC del 95%: 0,85-0,96/0,86-0,98).LIMITACIONES:Los pacientes de la base de datos de la Muestra Nacional de Pacientes Hospitalizados pueden no ser una muestra precisa de la población de todos los pacientes sometidos a colectomía por neoplasia de colon y no tienen en cuenta factores institucionales y específicos del paciente.CONCLUSIONES:El aprendizaje automático predijo con buen rendimiento las complicaciones postoperatorias en pacientes con neoplasia de colon sometidos a colectomía. Aunque será necesaria la validación mediante datos externos y la optimización de la calidad de los datos, estas herramientas de aprendizaje automático son muy prometedoras para ayudar a los cirujanos con la estratificación de riesgos de la atención perioperatoria para mejorar los resultados posoperatorios. (Traducción-Dr. Fidel Ruiz Healy ).

Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean.

Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (µmax ) and temperature coefficients (Q10 ; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same µmax and the same Q10 (as in to Eppley, 1972), (2) a unique µmax but the same Q10 (similar to Kremer et al., 2017), or (3) a unique µmax and a unique Q10 (following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario. Our results suggest that applying a µmax and Q10 universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q10 between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization. Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.

KiteLock 4%: the next generation of CVAD locking solutions.

Central venous access devices (CVADs), including peripherally inserted central catheters (PICCs) and cuffed tunnelled catheters, play a crucial role in modern medicine by providing reliable access for medication and treatments directly into the bloodstream. However, these vital medical devices also pose a significant risk of catheter-related bloodstream infections (CRBSIs) alongside associated complications such as thrombosis or catheter occlusion. To mitigate these risks, healthcare providers employ various strategies, including the use of locking solutions in combination with meticulous care and maintenance protocols. KiteLock 4% catheter lock is a solution designed to combat the triple threat of infection, occlusion and biofilm. This locking solution is described as the only locking solution to provide cover for all three complications.

Ecological and statistical models to configure flow regime for environment benefit in highly engineered rivers: a case study in the MacKenzie River, Southeast Australia.

Ecological and statistical models were developed using freshwater algal assemblages to assess water quality and ecological health of a regulated river. These models were used to inform configuration of flows to maintain or improve environmental conditions of the waterway whilst meeting consumptive water supply commitments. The flow regime of the MacKenzie River, western Victoria, Australia, has been substantially modified since the construction of a water supply reservoir on its upper reach in 1887. Water is withdrawn at several locations downstream of the reservoir, creating a substantially modified flow regime, impacting key environmental values of the river. To assess the impact of the different flow regimes on river health and ecosystem function, ten sites were repeatedly sampled along the river between February 2012 and April 2014. Physical and chemical characteristics of water, including pH, temperature, turbidity, electrical conductivity, dissolved oxygen, total nitrogen, total phosphorous, cations, and anions, were measured. Biological properties of the algal periphyton communities, including dry mass, ash-free dry mass, chlorophyll-a concentration, and species composition, were also measured. Exploration of the algal assemblage and water chemistry data using the computationally unconstrained ordination technique such as principal component analysis principal component analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA), and canonical correspondence analysis (CCA) indicated two strong gradients in the data sets. Furthermore, the quantitative ecosystem response models have been developed as the prototype tool to assist in the future configuration of flows in this river. The empirical data and models showed the lower reaches of the river to be in poor condition under low flows, but this condition improved under flows of 35 ML/day, as indicated by the reduction in green algae and cyanobacteria and improvement. Finally, the results are presented to tailor discharge and duration of water volume by amalgamation of consumptive and environmental flows to improve the condition of the stream thereby supplementing the flows dedicated to environmental outcomes.

Analysis of Uveal Melanoma 5-Year Survival Rates by Medicaid Status: A Nationwide Analysis.

PURPOSE: The survival outcomes of patients with primary uveal melanomas based on Medicaid status have not been previously discussed in the literature. METHODS: The Surveillance, Epidemiology, and End Results Medicaid database were utilized to identify patients with primary uveal melanomas diagnosed between 2006 and 2013. The Kaplan-Meier method was utilized to construct 5-year survival curves in adult, non-elderly patients. Log-rank testing was used to determine differences in survival rates, and multivariate Cox proportional hazards modeling was utilized to perform adjusted survival analysis. RESULTS: A total of 1,765 patients were included (Medicaid: 81, non-Medicaid: 1684). A total of 1683 (95.4%) were White. The average age was 51.75 years (SD = 9.5 years). Medicaid patients were more likely to be unmarried, live in a high poverty neighborhood, and live in a rural area (all p < .001). We observed no significant difference in 5-year survival rates between those enrolled in Medicaid (86.6%, 95% CI: 79.1%1-94.7%) and those not enrolled in Medicaid (85.5, 95% CI: 83.8%-87.2%) (p = .80). After controlling for socioeconomic and clinical factors, Medicaid enrollment was not associated with an increased risk of mortality compared to non-Medicaid enrollment. Age (aHR: 1.04, 95% CI: 1.02-1.06, p < .001) and tumor size >10 mm (aHR: 3.04, 95% CI: 1.49-6.21, p = .002) were associated with an increased risk of mortality. CONCLUSION: Medicaid enrollment was not associated with worse cancer-specific 5-year survival. Further research needs to be elicited to better understand the role of Medicaid enrollment in patients with primary uveal melanoma.

Dinoflagellate vertical migration fuels an intense red tide.

Harmful algal blooms (HABs) are increasing globally, causing economic, human health, and ecosystem harm. In spite of the frequent occurrence of HABs, the mechanisms responsible for their exceptionally high biomass remain imperfectly understood. A 50-y-old hypothesis posits that some dense blooms derive from dinoflagellate motility: organisms swim upward during the day to photosynthesize and downward at night to access deep nutrients. This allows dinoflagellates to outgrow their nonmotile competitors. We tested this hypothesis with in situ data from an autonomous, ocean-wave-powered vertical profiling system. We showed that the dinoflagellate Lingulodinium polyedra's vertical migration led to depletion of deep nitrate during a 2020 red tide HAB event. Downward migration began at dusk, with the maximum migration depth determined by local nitrate concentrations. Losses of nitrate at depth were balanced by proportional increases in phytoplankton chlorophyll concentrations and suspended particle load, conclusively linking vertical migration to the access and assimilation of deep nitrate in the ocean environment. Vertical migration during the red tide created anomalous biogeochemical conditions compared to 70 y of climatological data, demonstrating the capacity of these events to temporarily reshape the coastal ocean's ecosystem and biogeochemistry. Advances in the understanding of the physiological, behavioral, and metabolic dynamics of HAB-forming organisms from cutting-edge observational techniques will improve our ability to forecast HABs and mitigate their consequences in the future.

Best practice in the use of peripheral venous catheters: A scoping review and expert consensus.

Background: Peripheral intravenous catheters (PIVCs) are the most commonly used invasive medical device in health care with an overall failure rate of 35-50%. Most complications are non-infectious, but local site and bloodstream infections can also occur. Even if PIVC-related infections are rare, the total number of affected patients and the preponderance of Staphylococcus aureus as related pathogen due to the frequent use of these devices are relevant arguments to implement preventive strategies. The aim of this document is to raise awareness that infections caused by PIVCs are a relevant problem that can be reduced by practice change. Methods: A panel of experts discussed this topic based on evidence and proposed practice points by consensus. Discussion: Despite published evidence-based guidelines, current practice concerning aseptic techniques during insertion and care of PIVCs often are substandard. These devices have become commonplace and tend to be perceived as safe. An overall lack of awareness about the true risks associated with the use of PIVCs results in limited surveillance and prevention efforts. Conclusion: Successful insertion and maintenance bundles in central venous lines are a blueprint to the implementation of adapted bundle strategies in the prevention of PIVC-associated infections. There is a need for studies to specifically investigate infection prevention in PIVCs and to agree on effective and implementable bundles.

Detecting patterns of post-fire pine regeneration in a Madrean Sky Island with field surveys and remote sensing.

The American Southwest is experiencing drastic increases in aridity and wildfire incidence, triggering conversion of some frequent surface forests to non-forest. Extensive research has focused on these dynamics in regional ponderosa pine forests, but we know much less about Madrean pine-oak forests, which are broadly distributed from the Sierra Madre in Mexico to the Sky Island mountain ranges in the U.S. Increased fire incidence and drought in these forests are limiting pine regeneration and driving conversion of biodiverse forests to oak shrublands. We investigated regeneration patterns in Pinus engelmannii and P. leiophylla during severe drought 10 years after the Horseshoe Two Megafire in the Chiricahua Mountains, Arizona-a follow-up to an assessment five years post-fire. In long-term plots, we examined changes in pine seedling and resprout recruitment. Past research demonstrated that topography and fire severity influenced pine recruitment across environmental gradients. We investigated here whether Landsat-8 normalized difference vegetation index (NDVI) and evapotranspiration estimated by the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) added explanatory value to our understanding of these patterns. Conversion of Madrean pine-oak forest to oak shrublands continued 6-10 years post-fire. A dense, low oak canopy continued to coalesce in sites subject to severe fire. The importance of resprouts in P. leiophylla regeneration accelerated because these plants outgrew competing oak resprouts. Topography and fire severity (dNBR) were important predictors of 2021 patterns of pine recruitment. NDVI added explanatory value to these models, suggesting its potential in tracking forest dynamics. Evapotranspiration did not add value, likely because ECOSTRESS' larger pixel sizes and moving pixel locations created excessive subpixel heterogeneity in this highly dissected landscape. These models suggest that P. engelmannii is more drought sensitive, was more negatively affected by drought and fire, and is more at risk to shifts in climate and wildfires than P. leiophylla.

Elastomeric, fillable infusion pumps: an overview for clinical practice.

Due to advances in elastomeric pump technology, there are now devices available that can be filled with intravenous (IV) therapy at the bed or chair side. These devices are safe, reliable and enable the patient to be mobile when having their infusion. The Surefuser™+ elastomeric infusion pump is available in multiple configurations and allows patients to remain independent and receive IV therapy infusions in their own homes. The pump can also be used in the acute healthcare setting where traditional electronic infusion pumps may not be available. This article provides an overview of the Surefuser+ elastomeric infusion pump, its features and mode of action and how it can be used in clinical practice.

Exploratory Survey of Australian SMEs: an Investigation into the Barriers and Opportunities Associated with Circular Economy.

Small- and medium-sized enterprises (SMEs) account for 97.4% of all businesses in Australia and, contribute, by revenue, 32% to the country's economy. In the last decade, Australian SMEs have become increasingly aware of the importance of sustainability and need to shift away from a linear to circular economy (CE). Since 2019, there has been considerable growth on CE adoption research in SMEs, but empirical research examining Australian SMEs has yet to be undertaken. This study has used a survey and aims to understand the enablers and barriers of CE adoption in Australian SMEs. The research addresses three specific research questions- What are the barriers that impact CE adoption in Australian SMEs?; What enablers facilitate CE adoption in Australian SMEs?; and What is the effect of industry type, geographic location and job roles on enablers and barriers identification for CE adoption in Australian SMEs? Based on 352 responses from the survey of Australian SMEs, the paper identifies and analyses the enablers and barriers that these organizations face as they transition towards circular economy. The impact that location, industry sector and the role respondents undertake within the organization provides some interesting insights into how Australian SMEs are managing the process of adoption of CE. The research demonstrates that there is an overwhelming need for the development of consistent, sectoral, industry and location-specific policies by the federal and state governments to support internal policy development and the acquisition of new technologies in order to stimulate Australian SME CE adoption. In addition, Australian SMEs need to have a better understanding of how budgetary constraints, the lack of customer awareness and an absence of clearly defined business process impact CE adoption.

How to improve aseptic technique to reduce bloodstream infection during vascular access procedures.

Bloodstream infections associated with vascular access procedures pose a serious risk to patients that can be reduced by better standards of aseptic technique. The objectives of this roundtable of experts were to achieve a consensus on how to improve skin antisepsis in hospital, improve training, competency, compliance and consistency in skin antisepsis, review the role of devices in improving skin antisepsis, identify methods to improve skin antisepsis integrated with the Aseptic Non Touch Technique (ANTT®) approach, and identify challenges to the implementation of the panel's recommendations. Recommendations include using MHRA-licensed 2% chlorhexidine gluconate in 70% isopropyl alcohol solution with bidirectional strokes for up to 30 seconds, then leaving the skin to air dry for 30 seconds; using the ANTT Clinical Practice Framework and terminology as the standard for skin antisepsis training and practice; standardised ANTT and skin antisepsis education with 3-yearly competency assessments for all UK health professionals; and more research to address the evidence gap on transmission of infection after skin antisepsis.