10-day Period Research Articles

Changes in glucose variability and diabetes control in children and young adults with type 1 diabetes on routine continuous glucose monitoring and continuous subcutaneous insulin therapy following a switch to hybrid closed-loop therapy (MiniMed 780G) – retrospective study

IntroductionAdvanced hybrid closed loop (AHCL) insulin delivery systems offer considerable benefits to individuals with type 1 diabetes (T1D) in terms of glucose control and quality of life. With increasing numbers of regular users, real-life long-term data on long-term AHCL effectiveness become available.Material and methodsThis was a single-centre retrospective study. We included children and young adults (age 5–25 years ) with established T1D (≥ 3 m) who started MiniMed780G therapy between January 2021 and April 2022. We excluded those naïve to continuous glucose monitoring (CGM) or insulin pumps, as well as those without good-quality baseline CGM data. Included patients were followed for 12 months, with CGM and pump data retrieved from 14-day periods before transition and 3, 6, 9, and 12 months following the start of automode. Clinical data (body weight, height, glycated haemoglobin concentration) were recorded from the most recent outpatient visits.ResultsAmong 81 patients who started AHCL therapy, 46 met the criteria for analysis (mean age 11.5 ±4.4 years, diabetes duration 4.4 ±3.6 years, mean glycated haemoglobin 7.0 ±1.0%). Over the year following transition, we noted a significant improvement in time in target range 70–180 mg/dl (TIR, baseline: 69.1 ±12.0% to 12 m: 76.9 ±8.5%, <i>p</i> < 0.0001) and time in tight range 70–140 mg/dl (baseline: 45.3 ±14.2% to 12 m: 53.3 ±10.4%, <i>p</i> < 0.0001). Time below target range 70 mg/dl (TBR70 mg/dl) decreased significantly for 24-hour records (<i>p</i> = 0.0020). Importantly, those improvements were not accompanied by an increase in daily dose of insulin or body mass index.ConclusionsA prolonged 12-month-long observation in a routine care setting demonstrates that for young CGM- and pump users with T1D, switch AHCL offers sustained benefits in glucose variability.

Associations of seasonally available global positioning systems-derived walkability and objectively measured sleep in the Nurses' Health Study 3 Mobile Health Substudy.

Sleep is influenced by the environments that we experience while awake and while asleep. Neighborhood walkability has been linked with chronic disease and lifestyle factors, such as physical activity; however, evidence for the association between walkability and sleep is mixed. Extant studies assign walkability based on residential addresses, which does not account for mobility. We examined the association between walkability and sleep in the Nurses' Health Study 3 (NHS3) Mobile Health Substudy (MHS). From 2018 to 2020, individuals in the United States-based NHS3 prospective cohort participated in the MHS, in which minute-level global positioning systems (GPS) data and objective sleep duration and efficiency measures were collected via a custom smartphone application and Fitbit, respectively, for four 7-day periods across a year to capture seasonal variability. Census tract walkability was calculated by summing z-scores of population density (2015-2019 American Community Survey), business density (2018 Infogroup), and intersection density (2018 TIGER/Line road shapefiles). We ran generalized additive mixed models with penalized splines to estimate the association between walkability and sleep, adjusting for individual-level covariates as well as GPS-based exposure to environmental and contextual factors. The average main sleep period duration was 7.9 hours and the mean sleep efficiency was 93%. For both sleep duration and sleep efficiency, we did not observe an association with daily average walkability exposure. In this study of women across the United States, we found that daily GPS-based neighborhood walkability exposure during wake time was not associated with objective wearable-derived sleep duration or sleep efficiency.

Reliability of Regression Based Hybrid Machine Learning Models for the Prediction of Solar Photovoltaics Power Generation

Solar Photovoltaics (PVs) have become widespread as micro-distributed electric power generators in urban residential and commercial areas due to their affordability and minimal maintenance requirements. Despite these advantages, PV generation is intermittent, necessitating the implementation of robust predictive algorithms to capture power generation trends effectively. Accurate PV generation prediction is crucial for balancing energy demand and supply. Precise predictions help utilities use other grid resources efficiently, enhance market participation, and make informed planning decisions. Therefore, ensuring the precise performance of predictive models is imperative in the power generation industry. However, the performance of the predictive models typically fluctuates over time, necessitating a reliability assessment of their performance. This paper develops a hybrid machine learning model by integrating the support vector machine (SVM), random forest (RF), and gradient boosting machine (GBM) with multivariate adaptive regression spline (MARS) to predict the hourly PV power generation for 3-day and 7-day periods in three urban areas of North Dakota. The performance of the models has been recorded over a year, and a probability distribution model is proposed to demonstrate the hybrid algorithm’s reliability and effectiveness. Results show the proposed prediction model is more reliable for shorter prediction periods. The hybrid-MARS models significantly improve prediction reliability compared to the stand-alone MARS model. Among these models, MARS-SVM exhibits the highest reliability and consistently better accuracy than other hybrid models.

Lichens of Niue: a preliminary checklist

ABSTRACT A first checklist is provided for the lichenised fungi of Niue. Based on field-work undertaken during May 2024, when 130 collections were made over a 10-day period, 55 species are recognised, representing 33 genera and 22 families. Six genera include three or more species: Coccocarpia (5 species), Graphis (3), Lepidocollema (3), Physcia (6), Pyrenula (5), and Ramalina (3). In addition, nineteen collections referable to the genera Bacidia, Coccocarpia, Herpothallon, Leptogium, Megalaria, Pertusaria and Toninia could not be identified to species level due to infertile, immature, or depauperate specimens. This checklist is undoubtedly incomplete, and it is hoped that future studies will expand the island’s known lichen diversity. A number of the new records reported here for Niue are also first reports for islands of the wider Pacific Ocean or southwestern Polynesia.

Detection of miR-133a-5p Using a Molecular Beacon Probe for Investigating Postmortem Intervals

Background: When a body is discovered at a crime or murder scene, it is crucial to examine the body and estimate its postmortem interval (PMI). Accurate estimation of PMI is vital for identifying suspects and providing clues to resolve the case. MicroRNAs (miRNAs or miRs) are small non-coding RNAs that remain relatively stable in the cell nucleus even after death-related changes occur. Objective: This study developed a molecular beacon probe for mmu-miR-133a-5p and assessed its use in mouse muscle tissue at temperatures of 4 °C and 21 °C to estimate the PMI. Methods: A total of 36 healthy adult male BALB/c mice were divided into 9 PMI time points (0, 2, 6, 8, and 10 days) with 3 mice per time point, and they were exposed to 4 °C and 21 °C. Next, the expression pattern of mmu-miR-133a in the skeletal muscle tissue over a 10-day PMI period was analyzed using the developed molecular beacon probe. Results: The molecular beacon (MB) probe was designed for optimal thermodynamic stability with a hairpin structure that opened in the presence of mmu-miR-133a-5p, thus separating the fluorophore from the quencher and resulting in a strong fluorescence signal at 495 nm. Fluorescence intensity increased with mmu-miR-133a-5p concentration from 1 ng/μL to 1000 ng/μL and exhibited a strong correlation (R2 = 0.9966) and a detection limit of 1 ng/μL. Subsequently, the expression level of mmu-miR-133a-5p was observed to be stable in mouse skeletal muscle tissue at both 4 °C and 21 °C. Conclusions: This user-friendly assay can complete measurements in just 30 min after RNA extraction and is suitable for point-of-care testing, and it possesses the potential to improve existing complex and time-consuming methods for PMI estimation.

Changes in heart rate variability during an eHealth behavior change intervention program in patients with cardiovascular disease

BackgroundCardiovascular disease (CVD) risk is associated with health behaviors such as physical inactivity, dietary habits, and smoking. The autonomic nervous system plays a key role in this association. The present longitudinal study examines whether ECG-based indices of autonomic nervous system activity change during an eHealth-based behavior intervention program and assesses whether improvements in health behaviors are associated with increases in parasympathetic autonomic nervous system activity. MethodsData from the DoCHANGE-2 (https://clinicaltrials.gov/study/NCT03178305) eHealth-based behavior intervention study in patients with CVD were analyzed for participants with valid ECG recordings (N = 58, mean age = 58.9 [SD = 12.7] years, 21 % women). Heart rate variability (indexed as RMSSD) was calculated from home-recorded (40 s) ECGs over 5-day periods at baseline, 3, and 6 months. Health behaviors, clinical, and psychosocial information was obtained from questionnaires and medical records. Data were analyzed using linear mixed models and general linear models. ResultsOver the 6-month period, RMSSD decreased significantly, with the lowest values at six months (B = -19.336 [95 %CI −36.291; 2.381], p = 0.026). Health behaviors improved significantly during the active (0–3 months) intervention period (B = 13.360 [95 %CI 6.931 19.789], p < 0.001). Higher BMI (B = −0.369 [−0.739; 0.000]; p = 0.05) and older age (B = −0.404 [95 % CI −0.597; − 0.211]; p < 0.001) were associated with lower RMSSD across the three timepoints. No consistent associations were found between changes in health behaviors and changes in RMSSD. ConclusionThis study shows that changes in HRV during an eHealth-based behavioral intervention were not associated with the observed improvements in health behaviors. These findings require replication in larger well-controlled investigations.

Effect of phenylbutazone administration on the enteroinsular axis in horses with insulin dysregulation.

Phenylbutazone is prescribed for laminitis-associated pain and decreases glucose and insulin responses to an oral glucose test (OGT) in horses with insulin dysregulation (ID). Investigate the effect of phenylbutazone administration on the enteroinsular axis in horses. Sixteen horses, including 7 with ID. Randomized cross-over study design, with horses assigned to treatment with phenylbutazone (4.4 mg/kg IV q24h) or placebo (5 mL 0.9% saline). On Day 9 of treatment, an OGT was conducted, followed by a 10-day washout period, administration of the alternative treatment, and repetition of the OGT. Glucose-dependent insulinotropic polypeptide (GIP), and active glucagon-like peptide 1 and 2 (aGLP-1 and GLP-2) concentrations were determined by ELISA. The effects of ID status and treatment on peptide concentrations were assessed using t tests and analyses of variance. Horses with ID had significantly higher maximum GIP concentrations (Cmax) than controls (median, 279.1; interquartile range [IQR], 117.5-319.4 pg/mL vs median, 90.12; IQR, 74.62-116.5 pg/mL; P = .01), but no significant effect of ID was detected on aGLP-1 and GLP-2 concentrations. In horses with ID, phenylbutazone treatment significantly decreased GIP Cmax compared with placebo (168.1 ± 59.26 pg/mL vs 242.8 ± 121.8 pg/mL; P = .04), but no significant effect of phenylbutazone was detected on aGLP-1 and GLP-2 concentrations. Glucose-dependent insulinotropic polypeptide, aGLP-1 and GLP-2 do not mediate the decrease in glucose and insulin concentrations observed after phenylbutazone administration. Only GIP was repeatedly associated with ID status, calling into question the role of the enteroinsular axis in ID.

Effects of Liquid Vermicompost Utilization on Water Quality Parameters in Aquaponic Systems

Effects of Liquid Vermicompost Utilization on Water Quality Parameters in Aquaponic Systems

Evaluating the Efficacy of Inhaled Colistin via Two Nebulizer Types in Ventilator-Associated Pneumonia: Prospective Randomized Trial.

Backgroud: This prospective randomized trial evaluated the clinical efficacy of inhaled colistin administered through two distinct nebulizer types, a vibrating mesh nebulizer (VMN) and a jet nebulizer (JN), in the treatment of ventilator-associated pneumonia caused by multidrug-resistant bacteria. In addition, an in vitro model was used to determine the optimal delivery of colistin. Method: Thirty-two patients prescribed intravenous (IV) colistin inhalation were randomized to receive either a VMN (n = 17) or a JN (n = 15), then compared to the control group (IV alone) over a 7-to 10-day period. The primary endpoint was the clinical pulmonary infection score (CPIS), and the secondary endpoints were the Sequential Organ Failure Assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation (APACE) score, and duration of ventilator use. Results: Results from in vitro testing demonstrated that VMN delivered a significantly higher colistin dose than JN (35.68 ± 3.55% vs. 23.56 ± 3.31%; p < 0.001) when positioned at the humidifier inlet. Compared to the IV alone group, the IV with inhalation group yielded significant improvements in CPIS, SOFA score, and APACHE score on day 7; nevertheless, clinical outcomes between the two nebulizers were statistically indistinguishable. Conclusions: In conclusion, although VMN delivers a higher dose in vitro, both nebulizers yielded comparable clinical outcomes. This study was registered at US Clinical Trial Registration (NCT04633317).

Enhanced industrial wastewater monitoring: method development for non-target screening of highly polar substances using ZIC-HILIC-HRMS.

Non-target screening (NTS) plays a major role in the monitoring and management of water bodies. While the NTS of moderate to non-polar substances is well-established, the screening of highly polar chemicals remains challenging. In this study, a robust separation method for highly polar substances using zwitterionic hydrophilic interaction liquid chromatography coupled with high-resolution mass spectrometry (ZIC-HILIC-HRMS) was developed. This method was specifically designed for the NTS of industrial wastewater, with the objective of capturing a wide range of polar contaminants in each acquisition run. Method validation included assessing key parameters such as repeatability, reproducibility, linearity, and limit of detection (LOD). For repeatability and reproducibility, the average %RSD of intensity and retention time across all substances in different matrices-solvent, influent, and effluent-remained below 6% and 1%, respectively (n = 10). The method demonstrated good linearity (R2 > 0.99) for 75% of the substances, while LODs varied between 0.1 and 40µg/L depending on the compound tested. The method was then applied for NTS analysis of untreated wastewater at various locations within a chemical industrial park. Additionally, the overall influent and effluent of an industrial wastewater treatment plant (WWTP) were monitored over a 10-day period. Principal component analysis (PCA) was performed to interpret the data, identifying irregularities in the wastewater content. Moreover, the method demonstrated the WWTP's ability to achieve an average removal efficiency of approximately 90% for this category of substances in this period, while also detecting their degradation products in the effluent. Finally, the method was successfully integrated into the daily monitoring routine of the WWTP, ensuring continuous surveillance and improved management of wastewater treatment processes.

Variation in adherence measures as a function of calculation methods.

We aim to compare different operational definitions of medication adherence as well as examine the within-patient variability among these measures among patients treated for multiple comorbid conditions. Electronically monitored adherence data from a study on comorbid conditions were examined using three different calculation methods. DAILY adherence calculated the number of administrations divided by the number prescribed, without considering inter-dose interval. TIMING used predefined inter-dose intervals. Measures were aggregated to six 30-day periods. A PILLCOUNT approach counted the total administrations divided by the expected number in each 30-day period. Within-patient variability was computed based on DAILY and TIMING results for each 30-day period. Results varied by adherence calculation method. PILLCOUNT demonstrated the largest adherence rates (89%-92%); DAILY rates were lower (79%-85%); and TIMING was the lowest (62%-68%) over the 6-month period. TIMING within-patient variability (29%-35%) was larger than DAILY (20%-25%). Differences among the three methods confirm the importance of the adherence definition. TIMING may underestimate medicinal effects because patients may take medication as instructed (e.g., with meals) rather than at fixed intervals. PILLCOUNT may overestimate adherence by not accounting for inconsistent use. DAILY may best provide daily estimates of correct administration. Higher variability for TIMING may indicate patients are more likely to vary time between doses. Adherence calculation methods are important in interpreting results. Variability measures provide a more complete picture of adherence and may raise the likelihood of effects on biological outcomes. We propose studies of adherence include calculation method in the definition of adherence.

Effects of fasting on the interplay between temperature and Trypanosoma cruzi infection on the life cycle of the Chagas disease vector Rhodnius prolixus.

Rhodnius prolixus, a triatomine insect, is one of the most important vectors of Chagas disease in South America. Its interaction with the parasite Trypanosoma cruzi, the causative agent of this disease, is known to be deeply affected by ambient temperature and the nutritional status of the insect vector. In this study, we investigated how starvation affects the life cycle of R. prolixus and the population dynamics of the parasite inside the intestine of the vector at four temperatures ranging from 24°C to 30°C. The weights and molting times of chronically infected and uninfected insects were monitored through repeated 30-day fasting periods from first instar to adult stage, assessing their capacity to retain blood meal weight between developmental stages and tracking parasite concentrations in their urine. Our results demonstrate that ambient temperature is a crucial factor affecting the resistance of R. prolixus to starvation, as survival, body weight, and weight retention greatly decreased in high temperature treatments. Furthermore, we showed that temperature significantly influenced whether T. cruzi established an infection in early instars, with few insects developing infections at the lowest and highest temperature treatments. Additionally, we discovered that a fasting period of 30 days induces a steady decrease in parasite populations in the vector over its lifetime. Infection by T. cruzi had no effect on the survival, molting time, and nutritional factors monitored in our protocol. Our results highlight the importance of nutrition as a determining factor for the development of the vector and the parasite, providing valuable insights for elucidating the complex interplay between temperature and nutrition in shaping the epidemiology of Chagas disease in a changing climate.

An evaluative project of a ward-based pharmacist working within an MDT as part of a ‘Reablement &amp; Frailty’ speciality unit

Abstract Introduction Reablement care aims to prevent hospital re-admissions, costly institutional placements, and increase quality of life for frail patients, as well as preventing long-term decisions being made prematurely based on the patient’s current state of health1. Pharmacist involvement in multi-disciplinary teams (MDT) across other specialities has been demonstrated extensively worldwide as effective in reducing medication errors and providing significant improvements to patient care. However, little research has been conducted specifically within a reablement &amp; frailty setting, and the subsequent impact on the scale and quality of care provided to patients2. Aim To identify the responsibilities of a singular ward-based pharmacist working within a ‘reablement &amp; frailty’ MDT and evaluate the subsequent impact on patient care by categorising and quantifying the significance of pharmacist interventions and contributions. Methods A three-stage, quantitative service evaluation project: 1. Pharmacist development of two data collection tools to capture responsibilities: one for clinical interventions/recommendations and one for structured medication reviews; 2. Collection of daily interventions on 18-bed reablement unit over 13 days (3-day pilot + 10-day data collection period) by ward pharmacist using above data collection tools; 3. Scoring of each intervention based on two adapted, previously validated scales3: I. Severity score –potential severity of harm to the patient if contribution was missed (clinically insignificant, significant, serious, or life-threatening) II. Intervention score –likelihood of contribution preventing hospital re-admission - scale of 1-3 (1 - no likelihood, 2 - possible likelihood, and 3 - high likelihood) Ethical approval was obtained through the Robert Gordon University university ethics committee in addition to local approval via the Epsom &amp; St Helier hospital’s research &amp; development department. Results A total of 88 clinical contributions were made and collected over the 3-day pilot and 10-day data collection period, averaging just under seven contributions per day. Two ‘life-threatening’ interventions were made, both with a high likelihood of preventing a hospital re-admission. Based on potential severity of harm, most entries were scored as ‘significant’ (67%, n=59), followed by ‘serious’ (16%, n=14). Just over half of all clinical interventions (52%, n=46) scored as having either a possible OR high likelihood to prevent a hospital re-admission. The ward doctor actioned 94% (n = 73) of the pharmacist’s recommendations. Discussion / Conclusion With an average of just under 7 clinical contributions made daily, it is clear that pharmacist involvement in the ‘reablement &amp; frailty’ MDT can reduce medication error incidence through prompt identification and resolution, optimise medication regimens, and contribute to reducing patient risk of future re-admissions through effective interventions and medicines optimisation. Due to the different uses of the term ‘reablement’ globally, the findings from this study may not be applicable to all areas of reablement, such as home-based rehabilitation or bed-based respite. However, with this study forming foundation research into a novel reablement unit within secondary care, a promising argument has been made to promote pharmacist inclusion within MDTs across all specialities and the benefit that pharmacist contributions can bring to ensuring holistic care and effective patient reablement.

Application of LSTM recurrent neural networks for bitcoin price prediction

The growing interest in cryptocurrencies such as Bitcoin highlights the need for effective predictive models in this volatile market. This study developed and trained a model based on the Long Short-Term Memory (LSTM) Recurrent Neural Network architecture to forecast Bitcoin values with a low error percentage. The results confirmed the effectiveness of the LSTM model in predicting Bitcoin prices, demonstrating its ability to handle the high volatility characteristics of this market. Hypotheses regarding the efficiency of shorter versus longer lookback periods and the influence of data volume on model performance were tested. The experiments showed that increasing the volume of data used in training significantly increases the accuracy of predictions, evidenced by the lower error rates (MAPE and RMSE) obtained with larger data volumes. However, a saturation point was observed, after which further increases in data volume did not result in significant improvements. Regarding the lookback period, the results indicated that 30-day periods presented with the best performance, with lower forecast errors. Very short or very long lookback periods tend to increase the error, which highlights the importance of proper window selection for this type of model. Statistical analysis confirmed the significant influence of data volume and lookback period on model performance, although the interaction between these factors did not show statistical significance.

Analysis of the impact of environmental enrichment on the behaviors of bioterium rats

Rats are often used in experimental research due to their intelligence and ease of handling. However, traditional housing conditions can limit their natural behaviors, potentially leading to discomfort. Environmental enrichment aims to increase behavioral diversity, promote healthy behaviors, encourage positive use of the environment, enhance the animal's ability to cope with stressors, and reduce stereotypic behaviors. This study primarily aimed to assess the impact of environmental enrichment on laboratory rat behaviors. A group of 18 rats was selected and divided into three groups (n=6): control, physical enrichment, and feeding enrichment. The enrichment groups were provided with specific objects (a plastic tube for physical enrichment and a seed-filled cardboard roll for feeding enrichment) over a 10-day period, with open field tests conducted on days 1, 5, and 10 to evaluate time spent in central and peripheral zones. Statistical analyses were conducted in RStudio using t-test (p&lt;0.05) to compare open field activity, water intake, and food consumption across groups. Results showed that animals exposed to environmental enrichment displayed fewer stereotypic behaviors and increased feeding frequency. Thus, assessing the impact of physical and feeding enrichment in rats of laboratory demonstrates that enrichment strategies provide positive impacts on animal welfare.

Does high hepatic bioavailability enhance the effect of oral compared to subcutaneous glucocorticoids?

Glucocorticoids (GC) are important in the treatment of autoinflammatory disorders. Oral prednisolone ≤5 mg/day can be effective, but such doses are at or even below physiological daily endogenous GC production. We hypothesised that their immunosuppressive effect might be explained by high hepatic bioavailability of oral GC, exposing the liver to supraphysiological GC via the portal circulation. We tested this by comparing the effect of oral versus subcutaneous low-dose prednisolone, on erythrocyte sedimentation rate (ESR). Patients with rheumatoid arthritis or psoriatic arthritis, elevated ESR (≥30 mm/h) and no current or recent GC therapy were eligible. In a pilot study (n=5), 5 mg/day oral prednisolone decreased ESR significantly, suggesting a sample size of 10 patients for a randomised, non-blinded crossover trial. Patients received 5 mg/day prednisolone for 2 periods of 4 days: one treatment period orally and one subcutaneously with a 10-day washout period between treatments. ESR was measured before (day 1 and 15) and after (day 5 and 19) each treatment course. 10 patients were included. ESR decreased after both oral and subcutaneous prednisolone, by -5.6 (20.9) and -5.8 (3.0) mm/h, respectively (p=0.98). The treatment order had no effect on the outcome. . Short-term oral low-dose GC therapy is not more effective than parental GC in decreasing ESR, arguing against therapeutic high hepatic bioavailability effects. More likely, systemic concentration peaks following administration explain why oral physiological steroid doses are clinically effective.

Waiting to Exhale: The Feasibility and Appropriateness of Home Blood Oxygen Monitoring in Oncology Patients Post-Hospital Discharge.

Pulse oximetry remote patient monitoring (RPM) post-hospital discharge increased during the COVID-19 pandemic as patients and providers sought to limit in-person encounters and provide more care in the home. However, there is limited evidence on the feasibility and appropriateness of pulse oximetry RPM in patients with cancer after hospital discharge. This feasibility study enrolled oncology patients discharged after an unexpected admission at the Memorial Sloan Kettering Cancer Center from October 2020 to July 2021. Patients were asked to measure their blood oxygen (O2) level daily during the hours of 9 am-5 pm during a 10-day monitoring period posthospitalization. An automated system alerted clinicians to blood O2 levels below 93.0%. We evaluated the feasibility (>50.0% of patients providing at least one measurement from home) and appropriateness (>50.0% of alerts leading to a clinically meaningful patient interaction) of pulse oximetry RPM. Sixty-two patients were enrolled in the study, with 53.2% female patients and a median age of 68 years. The most prevalent malignancy was thoracic (62.9%). The feasibility metric was met, with 45 patients (72.6%, 45 of 62) providing blood O2 levels at least once during the 10-day monitoring program. The appropriateness threshold was not met; of the 121 alerts, only 39.7% (48 alerts) was linked to a clinically meaningful interaction. This feasibility study showed that while patients with cancer were willing to measure blood O2 levels at home, most alerts did not result in meaningful clinical interactions. There is a need for improved patient support systems and logistical infrastructure to support appropriate use of RPM at home.

The effects of compound probiotics on production performance, rumen fermentation and microbiota of Hu sheep.

Fungal probiotics have the potential as feed additives, but less has been explored in ruminant feed up to date. This study aimed to determine the effect of compound probiotics (CPs) with Aspergillus oryzae 1, Aspergillus oryzae 2 and Candida utilis on Hu sheep's growth performance, rumen fermentation and microbiota. A total of 120 male Hu sheep, aged 2 months and with the body weight of 16.95 ± 0.65 kg were divided into 4 groups. Each group consisted of 5 replicates, with 6 sheep per replicate. Group A was the control group fed with the basal diet. Group B, C and D was supplemented with the basal diet by adding 400, 800 and 1,200 grams per ton (g/t) CPs, respectively. The feeding trial lasted for 60 days after a 10-day adaptation period. The results showed that the average daily gain (ADG) of sheep in the CPs groups were significantly higher, the feed/gain were significantly lower than those in group A in the later stage and the overall period. The addition of CPs increased the economic benefit. The levels of CD4+ and the CD4+/CD8+ ratio in the CPs groups were higher than those in Group A. The levels of GSH, IgG, IL-2, IL-6, and IFN-γ in group C were significantly elevated compared with group A. Group B showed a significant increase in rumen NH3-N and cellulase activity. There was no difference in VFAs content between group A and group B, however, with the increasing addition of CPs, the butyric acid and isobutyric acid content tended to decrease. The rumen microbiota analysis indicated that the CPs addition increased the Firmicutes and Proteobacteria abundances, decreased the Bacteroidetes abundance. The correlation analysis showed that Prevotella was negatively correlated with ADG, and the addition of 400 CPs in group B reduced Prevotella's relative abundance, indicating CPs increased sheep growth by decreasing Prevotella abundance. The CPs addition reduced caspase-3, NF-κB and TNF-α expression in liver, jejunum and rumen tissues. In conclusion, the addition of CPs increased the sheep production performance, reduced inflammation, improved rumen and intestinal health. Considering the above points and economic benefits, the optimal addition of CPs as an additive for Hu sheep is 800 g/t.

Rapid remote volcanic ashfall impact assessment for the 2022 eruption of Hunga volcano, Tonga: a bespoke approach and lessons identified

When disasters occur, rapid impact assessments are required to prioritise response actions, support in-country efforts and inform the mobilisation of aid. The 15 January 2022 eruption of Hunga volcano, Tonga, and the resulting atmospheric shockwave, ashfall, underwater mass disturbance and tsunami, caused substantial impacts across the Kingdom of Tonga. Volcanic impacts on the scale observed after the eruption are rare, necessitating a reliance on international advice and assistance. The situation was complicated by the loss of Tonga’s international submarine fibreoptic cable (causing a complete loss of communications for approximately 20 days) along with border closures due to the COVID-19 pandemic. A need emerged for a rapid remote volcanic impact assessment and provision of specialist advice to help inform the response of international partners. Here we present a novel methodology for conducting rapid remote volcanic ashfall impact assessments, conducted over a 10-day period following the eruption. We used three different hazard models for ashfall thickness across the main island of Tongatapu and available asset information and vulnerability functions for buildings, agriculture, electricity networks, water supply and roads, to provide initial estimates of losses due to ashfall from the 15 January eruption. For buildings, we estimated losses both as total losses and as percentages of the total replacement cost of buildings on Tongatapu. For agriculture, we made probabilistic estimates of production losses for three different crop classes. For ashfall clean-up, we estimated ranges of ashfall volumes requiring clean-up from road surfaces and roofs. For water supply, electricity networks and roads, our analysis was limited to assessing the exposure of important assets to ashfall, as we had insufficient information on system configurations to take the analysis further. Key constraints on our analysis were the limited nature of critical infrastructure asset inventories and the lack of volcanic vulnerability models for tropical regions including Pacific Island nations. Key steps towards iteratively improving rapid remote impact assessments will include developing vulnerability functions for tropical environments as well as ground-truthing estimated losses from remote approaches against in-person impact assessment campaigns.

A coordination attention residual U-Net model for enhanced short and mid-term sea surface temperature prediction

Sea surface temperature (SST) is crucial for studying global oceans and evaluating ecosystems. Accurately predicting short and mid-term daily SST has been a significant challenge in oceanography. Traditional deep learning methods can handle temporal data and spatial features but often struggle with long-range spatiotemporal dependencies. To address this, we propose a coordination attention residual U-Net(CResU-Net) model designed to better capture the dynamic spatiotemporal correlations of high-resolution SST. The model integrates coordinate attention mechanisms, multiple residual modules, and depthwise separable convolutions to enhance prediction capabilities. The spatiotemporal variations of SST across different areas of the South China Sea are complex, making accurate predictions challenging. Experiments across various regions of the South China Sea show the model’s effectiveness and robust generalization in predicting high-resolution daily SST. For a 10-day forecast period, the model achieves approximately 0.3 °C in RMSE, outperforming several advanced models.