bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving primary care access for rural women Veterans: the Boost Team
Authors: Cohen Jenny K. , Monteith Lindsey L. , Stacker Tara , McCarthy Michaela , Bomsztyk Mayan , Wilson Abigail , Childers Jennifer , Hussain Tanvir , Kohlwes Jeffrey
Published: July 2024

Objectives

To improve healthcare access for rural cisgender women and gender diverse Veterans, we created the “Boost Team,” a clinician-driven telehealth outreach service to connect this population to Veterans Health Administration (VHA) services.

Methods

Between 9/2021 and 2/2022, we conducted a needs assessment in the Veterans Integrated Service Network (VISN) 21 and used those data to develop an outreach intervention. We piloted a clinician-led outreach intervention in 3/2022, and formally deployed an outreach team in 9/2022.

Results

The needs assessment uncovered opportunities to educate Veterans, staff, and clinicians about available VHA women's health services, and a need for easily-accessible gender-sensitive services. During the pilot, 58% (7/12) rural cisgender women Veterans were successfully contacted, all reported positive experiences with the intervention. The formal outreach team launched in 9/2022 and consists of a nurse practitioner (NP), scheduler, Peer Support Specialist, and medical director. From 9/2022 to 12/2022 the Boost NP called 110 rural cisgender women and gender diverse Veterans and spoke to 65 (59%) of them. Common care needs identified and addressed included care coordination, new referrals, medication management, and diagnostics.

Discussion

Data from Boost show that clinician-led outreach can engage rural cisgender women and gender diverse Veterans in VHA services, there is a desire for more gender-sensitive services, and there is a need for systems-level improvements to allow for improved care coordination and decreased leakage outside of VHA. Using robust strategies grounded in implementation sciences, we will continue conducting a program evaluation to study the impact of Boost and scale and expand the program.
The therapeutic potential of irisin to mitigate the risk of metabolic syndrome in postmenopausal women
Authors: Parkin Rebecca A. , Murray Andrew J.
Published: July 2024

Oestradiol withdrawal at menopause predisposes women to metabolic syndrome, a cluster of interrelated conditions including obesity, insulin resistance, dyslipidaemia and hypertension that together confer an increased risk of developing type 2 diabetes mellitus and cardiovascular disease. Hormone replacement therapies are commonly used to treat acute symptoms of the perimenopausal period, and whilst they have been associated with metabolic improvements in many studies, long-term use is considered unviable. Novel approaches are required to mitigate the risk of postmenopausal metabolic syndrome. In 2012, the exercise-inducible myokine irisin was isolated from the skeletal muscle of mice and identified to have anti-obesity and antidiabetic effects in vivo. Irisin is now recognised to exert pleiotropic action on cognitive, bone and metabolic health. There is accumulating evidence from in vitro and in vivo rodent studies that irisin can mitigate each component condition of metabolic syndrome. In postmenopausal women, independent associations have been observed between (a) exercise and plasma irisin concentration and (b) plasma irisin concentration and reduced incidence of metabolic syndrome. To date, however, no study has considered the mechanistic basis by which irisin, whether exercise-induced or exogenously administered, could reduce the incidence or severity of metabolic syndrome in postmenopausal women. This review aims to analyse the literature concerning the metabolic actions of irisin, with a focus on its therapeutic potential for metabolic syndrome driven by a state of oestradiol depletion. It evaluates the practicality of exercise as a therapy and discusses other irisin-based therapeutic strategies that may alleviate postmenopausal metabolic syndrome. Finally, it highlights areas where future research is required to advance knowledge of irisin's biological action such that it could be considered a viable candidate for clinical application.
Flow cytometry in the differential diagnosis of myelodysplastic neoplasm with low blasts and cytopenia of other causes
Authors: Plander Márk , Kányási Mária , Szendrei Tamás , Skrapits Judit , Timár Botond
Published: July 2024

Background

Myelodysplastic neoplasms (MDS) are characterized by cytopenia, morphologic dysplasia, and genetic abnormalities. Multiparameter flow cytometry (FCM) is recommended in the diagnostic work-up of suspected MDS, but alone is not sufficient to establish the diagnosis. Our aim was to investigate the diagnostic power of FCM in a heterogeneous population of patients with cytopenia, excluding cases with increased blast count.

Methods

We analyzed bone marrow samples from 179 patients with cytopenia (58 MDS, 121 non-MDS) using a standardized 8-color FCM method. We evaluated the sensitivity, specificity, and accuracy of several simple diagnostic approaches, including Ogata score, extended Ogata score, the WHO and ELN iMDSFlow recommended “3 aberrations in two cell compartments method,” and the combination of the Ogata score and “3 aberrations in two cell compartments method.” The patients were followed until the diagnosis was confirmed, with a median follow-up of 2 months (range 0.2–27).

Results

The combination of Ogata score and “3 aberrations in two cell compartments method” achieved the highest diagnostic accuracy (78%) with sensitivity and specificity 61% and 86%, respectively. When using only the “3 aberrations in two cell compartments method,” the accuracy was 77% with a sensitivity of 72% and a specificity of 79%. The most frequently observed etiologies among the false positive cases were substrate deficiencies, inflammation/infection, or toxic effects. MDS can be excluded in all these cases after a thorough clinical evaluation and a relatively short follow-up.

Conclusion

FCM remains an important but supplementary part in an integrated diagnostic process of MDS with low blasts. The combination of the Ogata score and the “3 aberrations in two cell compartments method” slightly improves accuracy compared to the detection of “3 aberrations in two cell compartments method” alone.
Discrete Element Model of Oil Peony Seeds and the Calibration of Its Parameters
Authors: Zhou Hao , Li Kangtai , Qin Zhiyu , Wang Shengsheng , Wang Xuezhen , Sun Fengyun
Published: July 2024

Oil peony is an important oil crop that is primarily sown by using artificial methods at present. Its seeder encounters the problems of low efficiency of seeding that significantly limits the highly efficient mechanized production of high-quality peony oil. In this study, Fengdan white oil peony seeds were used as the research object and repose angle as the response value to establish a discrete element model (DEM) and parameter calibration. The range of parameters of oil peony seeds was first obtained through an experiment, and their repose angle was obtained by an inclinometer. A three-dimensional DEM of oil peony seeds was then established. The Plackett–Burman (PB) test was utilized to screen the parameters that had a significant influence on the repose angle, and the steepest ascent (SA) test was applied to determine their optimum range of testing. Following this, based on Box–Behnken (BBD) test results, a second-order regression model between the important parameters and the repose angle was constructed. Finally, the absolute minimum difference between simulated and measured repose angles was utilized as the objective of optimization to obtain the following optimum combination of parameters: The values of the seed–steel collision recovery coefficient (CRC), seed–seed static friction coefficient (SFC), seed–steel SFC, and seed–seed rolling friction coefficient (RFC) were 0.704, 0.324, 0.335, and 0.045, respectively. This optimal combination of parameters was confirmed through simulations, and the error between simulated and measured repose angles was only 0.67%, indicating that the calibrated DEM of oil peony seeds was reliable.
Modeling Risk in Fusarium Head Blight and Yield Analysis in Five Winter Wheat Production Regions of Hungary
Authors: Anda Angela , Simon-Gáspár Brigitta , Simon Szabina , Soós Gábor , Menyhárt László
Published: July 2024

The five-year mean yield of five Hungarian wheat production counties was 5.59 t ha−1 with a 7.02% average coefficient of variation. There was a regional effect on yield when progressing from south to north with a 1–2 °C higher mean winter air temperature, meaning that the Ta in southern counties increased the five-season mean yield by 15.9% (p = 0.002) compared to the yield of northern counties. Logistic regression models developed to assess the FHB risk driven by a few meteorological variables (Ta; RH) provided proper predictive performance. The results in the regression model were validated against the measured infection rates (P%) provided by the NÉBIH 30 days before and after heading. The FHB pressure was comparatively higher in Zala County, probably due to its special topological and growing conditions, irrespective of the season. Across all areas studied, two of the five identified counties (Pest and Somogy) provided the best classification for FHB infection. In the remaining three counties, the seasonal mean prediction accuracy (differences) exceeded 10% in only 6 out of 30 model outputs. The modeled five-season P% values averaged 70.4% and 93.2% of the measured infection rates for models 1 and 2, respectively. The coincidence of wet and warm weather around the time of wheat flowering enhanced the risk of FHB.
Improvement in Natural Antioxidant Recovery from Sea Buckthorn Berries Using Predictive Model-Based Optimization
Authors: Kim Seunghee , Lee Jeongho , Son Hyerim , Lee Kang Hyun , Chun Youngsang , Lee Ja Hyun , Lee Taek , Yoo Hah Young
Published: July 2024

Sea buckthorn berries (SBB) are well known for being rich in natural bioactive compounds with high pharmacological activity. In this study, the optimization of extraction parameters was performed to recover phenolic compounds with high antioxidant activity from SBB. This study involved a systematic optimization approach, including screening for a variety of parameters, including temperature, time, ethanol concentration, agitation, and solid loading. On the basis of Plackett–Burman design (PBD) model, the two most significant parameters (agitation and solid loading) were selected, and the correlation model between those parameters and multiple responses was derived via response surface methodology (RSM). As a result, the optimal extraction condition for maximizing phenolic content and antioxidant activity was determined to be agitation at 109.54 rpm and a solid loading of 172.67 g/L. Under optimal conditions, SBB extract showed a total phenolic content of 0.21 mg/mL and ABTS and DPPH activities of 27.27% and 58.16%, respectively. The SBB extract prepared under optimal conditions was found to contain caffeic acid, vanillic acid, rutin, and vitamin B1 (thiamine). This work is the first challenge to design an optimization model for the efficient recovery of antioxidants from SBB and is significant in that the model can be applied simply and economically to conventional extraction processes.
Advancements in Real-Time Monitoring of Enteric Methane Emissions from Ruminants
Authors: O’Connor Seán , Noonan Flannagán , Savage Desmond , Walsh Joseph
Published: July 2024

The agricultural sector is responsible for a significant proportion of global anthropogenic methane (CH4) emissions, with enteric CH4 produced from ruminant livestock representing approximately 28% of the total. The development of effective mitigation strategies necessitates the accurate and actionable monitoring of CH4 emissions. However, a considerable research gap remains concerning real-time monitoring techniques capable of supporting on-farm enteric CH4 mitigation strategies. To bridge this research gap, this study explores the current status of real-time enteric CH4 emission monitoring techniques and technologies for ruminants. The study achieves this by reviewing key biomarkers and proxies for ruminant emissions, examining established animal-based measurement techniques, exploring emerging technologies, and critically assessing technological limitations and opportunities. By shedding light on this research area, this study aims to assist stakeholders in developing a viable pathway for on-farm emission monitoring, with the hope of facilitating a meaningful reduction in GHG emissions from the livestock sector.
Recycling of Agro-Food and Urban Wastes According to the Circular Economy and Sustainable Paradigms
Authors: Vigoroso Lucia , Cavallo Eugenio , Pampuro Niccolò
Published: July 2024

In the era of eco-sustainability, it is crucial to recognize the importance of treating agro-food and urban wastes; by transforming what might be considered waste into valuable resources, we can combat environmental degradation while promoting economic growth, environmental sustainability, and public health [...]
Algorithm for Corn Crop Row Recognition during Different Growth Stages Based on ST-YOLOv8s Network
Authors: Diao Zhihua , Ma Shushuai , Zhang Dongyan , Zhang Jingcheng , Guo Peiliang , He Zhendong , Zhao Suna , Zhang Baohua
Published: July 2024

Corn crop row recognition during different growth stages is a major difficulty faced by the current development of visual navigation technology for agricultural robots. In order to solve this problem, an algorithm for recognizing corn crop rows during different growth stages is presented based on the ST-YOLOv8s network. Firstly, a dataset of corn crop rows during different growth stages, including the seedling stage and mid-growth stage, is constructed in this paper; secondly, an improved YOLOv8s network, in which the backbone network is replaced by the swin transformer (ST), is proposed in this paper for detecting corn crop row segments; after that, an improved supergreen method is introduced in this paper, and the segmentation of crop rows and background within the detection frame is achieved utilizing the enhanced method; finally, the corn crop row lines are identified using the proposed local–global detection method, which detects the local crop rows first, and then detects the global crop rows. The corn crop row segment detection experiments show that the mean average precision (MAP) of the ST-YOLOv8s network during different growth stages increases by 7.34%, 11.92%, and 4.03% on average compared to the MAP of YOLOv5s, YOLOv7, and YOLOv8s networks, respectively, indicating that the ST-YOLOv8s network has a better crop row segment detection effect compared to the comparison networks. Corn crop row line detection experiments show that the accuracy of the local–global detection method proposed in this paper is improved by 17.38%, 10.47%, and 5.99%, respectively, compared with the accuracy of the comparison method; the average angle error is reduced by 3.78°, 1.61°, and 0.7°, respectively, compared with the average angle error of the comparison method; and the average fitting time is reduced by 5.30 ms, 18 ms, and 33.77 ms, respectively, compared with the average fitting time of the comparison method, indicating that the local–global detection method has a better crop row line detection effect compared to the comparison method. In summary, the corn crop row recognition algorithm proposed in this paper can well accomplish the task of corn crop row recognition during different growth stages and contribute to the development of crop row detection technology.
Assessing Effect of Irrigation Frequency on Evaporation and Transpiration in Vineyards Using SIMDualKc Simulation Model with Measured Wet Fraction
Authors: Esteban-Sanchez Gonzalo , Campillo Carlos , Uriarte David , Moral Francisco J.
Published: July 2024

Irrigation efficiency is important for the environment and the economy. SIMDualKc has been effectively used to calculate evaporation and transpiration separately in vineyards for different irrigation strategies, but not to analyze the impact of irrigation frequency. This study was conducted for the in-field adjustment of the soil wetted fraction (wf) with a time domain reflectometry (TDR) sensor as a function of different irrigation frequency treatments (T03, T07, and T15 with irrigation every 3, 7, and 15 days, respectively). Evaporation and transpiration values were estimated separately with the SIMDualKc model for different irrigation frequencies with the adjusted wf, comparing them with vineyard field measurements and analyzing the effect of different irrigation frequencies on vineyard yield. The wf in T15 was higher than that in T07, which in turn was higher than that in T03. SIMDualKc indicates the most unfavorable treatment to be the T07, with higher evaporation and lower transpiration than T15 and T03, while T15 had higher evaporation and lower transpiration than T03. Although stomatic conductance also indicates the most unfavorable case to be T07, no clear differences were found between T03 and T15. No statistically significant differences were obtained in yield. The results indicate that the differences observed between irrigation frequencies are not reflected in yield but do show up in water use efficiency.
Effects of Planting Density and Nitrogen Management on Light and Nitrogen Resource Utilization Efficiency and Yield of Summer Maize in the Sichuan Hilly Region
Authors: Lei Hao , Zhou Fang , Cai Qianyi , Wang Xinglong , Du Lunjing , Lan Tianqiong , Kong Fanlei , Yuan Jichao
Published: July 2024

The low efficiency of light and nitrogen resources, poor yield and profit, and environmental pollution of maize production are main problems in many areas of China. We hypothesized that optimizing nitrogen fertilizer density management strategies could alleviate the above issues. To address this, a 3-year on-site experiment with three planting densities and four nitrogen rates was conducted in the Sichuan Hilly Region. The results indicated that increasing the planting density could increase the extinction coefficient and solar radiation interception of maize populations as well as enhance the utilization efficiency of light and nitrogen resources and yield. For every 100 kg ha−1 increase in nitrogen fertilizer, RUE increased by 0.16%, NUE decreased by 25.0%, and soil apparent nitrogen loss quantity increased by 67.8 kg ha−1. There was a certain interaction between planting density and nitrogen rate. The appropriate planting density and nitrogen rate combination was 67,500 plants ha−1 with 180 kg N ha−1 under the experimental condition. Excessive close planting in weak-light areas and excessive nitrogen reduction after densification are not advisable. This study indicated that nitrogen–density strategies should be matched with the local natural resources such as sunlight. The results provide a theoretical for high-yield and high-quality maize production in these areas.
Response of Blackgram (Vigna mungo L.) Cultivars for Nipping and Graded Levels of Nitrogen for Higher Productivity under Irrigated Conditions
Authors: Marimuthu Subbaiyan , Navamaniraj Koilpitchai Nelson , Kathiravan Muthuselvan , Balasubramanian Palaniyappan , Surendran Udayarpillai , El-Hendawy Salah , Mattar Mohamed A.
Published: July 2024

Blackgram (Vigna mungo L.) holds significant importance among grain legumes, particularly in terms of its production and productivity. Over the years, the decline in the cultivation area of this crop has become increasingly evident due to its persistently low yields. Many technologies are being implemented to improve the yield, and nipping is one of them. The main objective of this paper was to standardize the nipping timing and graded levels of nitrogen (N) application on growth and seed yield in blackgram cultivars under irrigated conditions. A study with three blackgram cultivars (cv.), three levels of N, and three intervals of nipping was taken up during the winter and monsoon seasons of 2018 and 2019, respectively. The study revealed that blackgram cv. VBN8 recorded a higher plant height of 49.52 cm, a higher number of branches (4.08), a higher number of pods per plant (47.75), a higher seed yield of 882 kg.ha−1, and a benefit cost ratio (B:C ratio) of 2.49. Among the graded levels of nutrients, applications of 125% N and 100% phosphorus (P) and potassium (K) recorded the highest growth and yield attributes, with a B:C ratio of 2.33. Nipping at 25 days after sowing (DAS) registered a higher number of branches (4.08), more pods per plant (48.14), and a seed yield of 902 kg.ha−1 with a B:C ratio of 2.36. Higher N, P, and K uptake was observed in blackgram VBN8, with an application of 150% recommended N and 100% P and K and nipping at 25 DAS. To conclude, application of 125% recommended N and 100% P and K and nipping at 25 DAS were found to be significant in enhancing the productivity of blackgram and NPK uptake, and resulted in 14% more profit than no nipping treatments.
The Effect of Subclinical Ketosis on the Peripheral Blood Mononuclear Cell Inflammatory Response and Its Crosstalk with Depot-Specific Preadipocyte Function in Dairy Cows
Authors: Ford Hunter R. , Mitchell Ty M. , Scull Tanner , Benitez Oscar J. , Strieder-Barboza Clarissa
Published: July 2024

During the periparturient period, cows undergo heightened energy demands at lactation onset, paired with reduced dry matter intake, leading to negative energy balance (NEB). Excessive lipolysis-driven adipose tissue remodeling, triggered by NEB, significantly contributes to ketosis in periparturient dairy cows. However, the role of peripheral blood mononuclear cells (PBMCs) in the pathogenesis of ketosis and in modulating adipose tissue function remains poorly understood. Here, we investigated how ketosis affects the transcriptional profile and secretome of PBMCs and its influence on preadipocyte function in visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Twenty-one postpartum Holstein dairy cows were categorized as either subclinical ketosis (SCK; BHB ≥ 1.0 mM) or control (CON; BHB < 0.8 mM) based on blood beta-hydroxybutyrate (BHB) concentration screening. Blood samples were collected intravenously for the isolation of PBMCs and serum metabolic profiling. Ketosis elevated circulating NEFA and BHB levels but reduced total WBC and neutrophil counts. Isolated PBMCs were evaluated for gene expression and used to produce conditioned media (PBMC-CM), during which PBMCs were stimulated with 10 ng/mL LPS. The overall phenotype of PBMCs was largely consistent between SCK and CON cows, with minimal differences detected in immunomodulatory cytokine expression and PBMC-CM composition following stimulation. Preadipocytes isolated from non-ketotic cows were treated with PBMC-CM to assess the effect of PBMC secretomes on adipose cell function. Preadipocytes treated with SCK PBMC-CM showed reduced lipid accumulation compared to those treated with CON PBMC-CM regardless of the depot. SAT preadipocytes had heightened expression of lipid metabolism-related genes, including DGAT1, LIPE, and FASN, compared to VAT when treated with SCK PBMC-CM. Preadipocytes treated with CM from PBMC stimulated by LPS exhibited upregulation in IL1B and IL6 regardless of the depot or source of PBMCs. Together, these results indicate that although PBMC profiles showed minimal differences, preadipocytes treated with PBMC-CM may be influenced by additional factors, leading to altered preadipocyte function and gene expression that may contribute to adipose cellular dysfunction.
Using Thermal Signature to Evaluate Heat Stress Levels in Laying Hens with a Machine-Learning-Based Classifier
Authors: Solis Isaac Lembi , de Oliveira-Boreli Fernanda Paes , de Sousa Rafael Vieira , Martello Luciane Silva , Pereira Danilo Florentino
Published: July 2024

Infrared thermography has been investigated in recent studies to monitor body surface temperature and correlate it with animal welfare and performance factors. In this context, this study proposes the use of the thermal signature method as a feature extractor from the temperature matrix obtained from regions of the body surface of laying hens (face, eye, wattle, comb, leg, and foot) to enable the construction of a computational model for heat stress level classification. In an experiment conducted in climate-controlled chambers, 192 laying hens, 34 weeks old, from two different strains (Dekalb White and Dekalb Brown) were divided into groups and housed under conditions of heat stress (35 °C and 60% humidity) and thermal comfort (26 °C and 60% humidity). Weekly, individual thermal images of the hens were collected using a thermographic camera, along with their respective rectal temperatures. Surface temperatures of the six featherless image areas of the hens’ bodies were cut out. Rectal temperature was used to label each infrared thermography data as “Danger” or “Normal”, and five different classifier models (Random Forest, Random Tree, Multilayer Perceptron, K-Nearest Neighbors, and Logistic Regression) for rectal temperature class were generated using the respective thermal signatures. No differences between the strains were observed in the thermal signature of surface temperature and rectal temperature. It was evidenced that the rectal temperature and the thermal signature express heat stress and comfort conditions. The Random Forest model for the face area of the laying hen achieved the highest performance (89.0%). For the wattle area, a Random Forest model also demonstrated high performance (88.3%), indicating the significance of this area in strains where it is more developed. These findings validate the method of extracting characteristics from infrared thermography. When combined with machine learning, this method has proven promising for generating classifier models of thermal stress levels in laying hen production environments.
Effect of Heat Stress on Lactating and Non-Lactating Blackbelly Ewes under Tropical Conditions during Summer
Authors: Valencia-Franco Edgar , García y González Ethel Caterina , Guevara-Arroyo Aurora Matilde , Torres-Agatón Fernando , Robles-Robles José Manuel , Rodríguez-Castillo José del Carmen , Paredes-Alvarado Marisol , Alaniz-Gutiérrez Luis , Ruiz-Ortega Maricela , Ponce-Covarrubias José Luis
Published: July 2024

Two groups of ewes (10 lactating and 10 non-lactating) were used to evaluate the effect of heat stress during summer under tropical conditions. In this study, a temperature and humidity index (THI) was found that ranged between 65 and 79 (morning and afternoon). Likewise, a heat tolerance coefficient (HTC) of 6 units was observed. The highest breathing frequency (BF; 115.46 ± 35.25 breaths per minute (bpm)) and rectal temperature (RT; 38.95 ± 0.51 °C) were found during the afternoon in the group of lactating ewes. The means were compared by group, time of the day, and interaction, and only significant differences were found between groups for RT and udder temperature (p < 0.001). In the case of time of day, all parameters were higher during the afternoon, regardless of the group of ewes (p < 0.001). Likewise, an interaction was found in the parameters RT, right paralumbar fossa (RPF), rump, leg, and udder (p < 0.001). In conclusion, Blackbelly ewes lactating during the summer in the tropics have higher skin temperatures, and also raise BF and RT to tolerate HS in tropical climates.
Evolution, Diversity, and Conservation of Herpetofauna
Authors: Zhu Wei , Wang Bin , Jiang Jianping
Published: July 2024

Amphibians and reptiles play a critical role in the evolution of Tetrapoda, showcasing significant diversity in terms of their genetics, species, morphology, life history traits, and evolutionary functions [...]
Molecular and Serological Surveillance for Mycobacterium leprae and Mycobacterium lepromatosis in Wild Red Squirrels (Sciurus vulgaris) from Scotland and Northern England
Authors: Zhou Zijie , van Hooij Anouk , Wassenaar Gaby N. , Seed Emma , Verhard-Seymonsbergen Els M. , Corstjens Paul L. A. M. , Meredith Anna L. , Wilson Liam A. , Milne Elspeth M. , Beckmann Katie M. , Geluk Annemieke
Published: July 2024

Leprosy is a poverty-associated infectious disease in humans caused by Mycobacterium leprae or M. lepromatosis, often resulting in skin and peripheral nerve damage, which remains a significant public health concern in isolated areas of low- and middle-income countries. Previous studies reported leprosy in red squirrels in the British Isles, despite the fact that autochthonous human cases have been absent for centuries in this region. To investigate the extent of M. leprae and M. lepromatosis presence in wild red squirrels in the northern UK, we analyzed 220 blood/body cavity fluid samples from opportunistically sampled red squirrels (2004–2023) for specific antibodies against phenolic glycolipid-I, a cell wall component specific for these leprosy bacilli. Additionally, we assessed bacillus-derived DNA by real-time PCR (qPCR) in 250 pinnae from the same cohort. M. lepromatosis and M. leprae DNA were detected by qPCR in 20.4% and 0.8% of the squirrels, respectively. No cases of co-detection were observed. Detectable levels of anti-PGL-I antibodies by UCP-LFA were observed in 52.9% of animals with the presence of M. lepromatosis determined by qPCR, and overall in 15.5% of all animals. In total, 22.6% (n = 296) of this UK cohort had at least some exposure to leprosy bacilli. Our study shows that leprosy bacilli persist in red squirrels in the northern UK, emphasizing the necessity for ongoing molecular and serological monitoring to study leprosy ecology in red squirrels, gain insight into potential zoonotic transmission, and to determine whether the disease has a conservation impact on this endangered species.
Correction: Otgontamir et al. Assessing Changes in the Distribution Patterns of the European Wildcat in Hungary. Animals 2024, 14, 785
Authors: Otgontamir Chimed , Fehér Ádám , Schally Gergely , Heltai Miklós , Szabó László , Lehoczki Róbert , Lkhagvasuren Davaa , Biró Zsolt
Published: July 2024

In the original publication [...]
Relationship between Pelvic Dimensions and Maximum Traction Forces Required during Parturition in Holstein Cows Using a Biomechanical Obstetric Simulator
Authors: Tsaousioti Angeliki , Praxitelous Anastasia , Patsikas Michail , Becker Meik , Bollwein Heinrich , Boscos Constantin M. , Kiossis Evangelos , Tsousis Georgios
Published: July 2024

The primary aim of this study was to investigate the effect of the pelvic dimensions of Holstein cows on the traction forces during parturition. Additionally, the relationship between calf measurements and traction forces was explored. For this purpose, a modified in vitro biomechanical model simulating obstetric tractions was used. For the requirements of the experiment, six bone pelvises of deceased Holstein cows were collected based on their estimated pelvic inlet area (EPA) and prepared. Additionally, six stillborn calves were collected based on their body weight (BW). The parameters of the pelvic inlet and cavity were measured using computed tomography (CT). Using the simulator, every calf was pulled in a random order through all pelvises, realizing a total of 36 obstetrical tractions, and the required forces were documented with appropriate software. In each extraction, three peaks of forces were recorded, with the first peak occurring at the entrance of the elbows into the maternal pelvic cavity, the second peak at the entrance of the thorax, and the third at the entrance of the calf’s pelvis. Logistic regression revealed an exponential relationship between pelvic parameters and traction forces for the entrance of the elbows and the pelvis, with the recorded forces being higher in the two smallest pelvises and stabilizing at a lower level thereafter, while for the entrance of the thorax, the correlations were either exponential or linear. The adjusted coefficients of determination (r2) were generally above the threshold of 0.5 for the entrance of the elbows and pelvis and lower (0.3–0.4) regarding the thorax and were statistically significant (p < 0.05) in all cases. Regarding the relationships between the calf dimensions and the required traction forces, the types of correlations were primarily linear and of lower magnitude. The combination of pelvic and calf parameters in a multivariate model resulted in an r2 of 0.72 for the entrance of the elbows using the pelvic diagonal and calf’s body weight, an r2 of 0.62 using the pelvic area and calf’s thoracic circumference, and an r2 of 0.75 using the pelvic diagonal and calf’s fetlock joint width. In conclusion, under the conditions of the present experimentation, the applied traction forces were mainly influenced by the pelvic dimensions in an exponential manner, whereas the calf body measurements showed a weaker effect. Based on these findings, critical cut-off points exist, different for every pelvic parameter, below which a significant increase in the required traction forces is expected.
Animal Welfare Guidelines for International Development Organisations in the Global South
Authors: Ssuna Paul , Crump Andrew , Siegmund Karin
Published: July 2024

International development organisations have improved billions of human lives in the Global South. However, in both their projects and advice to governments, most of these organisations neglect animal welfare. This blindspot matters. Poor welfare standards risk the organisation’s reputation, particularly with donors; they reduce livestock lifespans and productivity, harming recipients; and they cause animals unnecessary pain and suffering. Here, we set out animal welfare guidelines for international development organisations. They were developed through extensive stakeholder engagement with organisations, donors, and recipients, especially in Africa. To comprehensively cover animal welfare, the guidelines encompass governance structure within the organisation, staff training, standard operating procedures, water, food, housing, social isolation, enrichment, drainage and waste disposal, disease, invasive procedures, transport, slaughter, breeds, record-keeping, and monitoring and evaluation of success. We urge international development organisations to adopt and institutionalise these guidelines, so they promote good animal welfare.
Polish Dairy Farm Transformations and Competitiveness 20 Years after Poland’s Accession to the European Union
Authors: Ziętara Wojciech , Pietrzak Michał , Malak-Rawlikowska Agata
Published: July 2024

Poland is one of the leading milk producers in the EU, being the fifth largest after countries such as Germany, France, Italy, and the Netherlands. From Poland’s accession to the European Union in 2004 up to 2022, Polish milk production experienced dynamic development. In this, there occurred a strong decline in the number of dairy farms (by −78%) and the number of cows (by −21%), an increase in dairy herd size (3.5 times) and increase in milk production (+60%) and milk yield per cow (by +62%). These were among the highest growth dynamics among the analysed countries. As a result of this significant transformation, Poland maintained an important position in milk exports, with a 31% export share in production in 2022. The scale of milk production was the basic factor determining the efficiency and competitiveness of dairy farms in Poland. Milk yield, farmland productivity, labour productivity, milk price, and the Corrected Competitiveness Index (based on labour and land opportunity costs) all showed a positive relationship with cow herd size on the farm. Milk production is highly uncompetitive for smaller farms (<15 cows). Despite substantial public support, the smaller farms, where subsidies equal up to 47% of total production value, could not earn sufficient income to cover the cost of capital, risk, and management in 2008, and even more so in 2021. This is because the farm income is too small to cover the extremely high opportunity cost of labour. The larger farms (with 30 cows and more) are competitive and responsible for the majority (~60–70%) of milk produced and delivered to the market. The most challenging from the sectoral policy point of view are medium farms (10–29 cows), whose share in production and deliveries is still important. To survive as economically viable units, these farms have to increase in scale and improve productivity. Otherwise, they will be gradually supplanted by larger farms.
Effects of Hypoxia on the Antibacterial Activity of Epidermal Mucus from Chilean Meagre (Cilus gilberti)
Authors: Vega Belinda , Toro-Araneda Teresa , Alvarado Juan F. , Cárcamo Claudia B. , Guzmán Fanny , Acosta Félix , Oliva Marcia , Serrano Edison , Galarza Janeth I. , Álvarez Claudio A.
Published: July 2024

Comprehending the immune defense mechanisms of new aquaculture species, such as the Chilean meagre (Cilus gilberti), is essential for sustaining large-scale production. Two bioassays were conducted to assess the impact of acute and intermittent hypoxia on the antibacterial activity of juvenile Chilean meagre epidermal mucus against the potential pathogens Vibrio anguillarum and Vibrio ordalii. Lysozyme and peroxidase activities were also measured. In general, fish exposed to hypoxia showed a 9–30% reduction in mucus antibacterial activity at the end of hypoxic periods and after stimulation with lipopolysaccharide. However, following water reoxygenation, the activity of non-stimulated fish was comparable to that of fish in normoxic conditions, inhibiting bacterial growth by 35–52%. In the case of fish exposed to chronic hypoxia, the response against V. anguillarum increased by an additional 19.8% after 6 days of control inoculation. Lysozyme exhibited a similar pattern, while no modulation of peroxidase activity was detected post-hypoxia. These results highlight the resilience of C. gilberti to dissolved oxygen fluctuations and contribute to understanding the potential of mucus in maintaining the health of cultured fish and the development of future control strategies.
In Vitro Evaluation of Colistin Conjugated with Chitosan-Capped Gold Nanoparticles as a Possible Formulation Applied in a Metered-Dose Inhaler
Authors: Changsan Narumon , Atipairin Apichart , Muenraya Poowadon , Sritharadol Rutthapol , Srichana Teerapol , Balekar Neelam , Sawatdee Somchai
Published: July 2024

Inhaled colistin is used to treat pneumonia and respiratory infections through nebulization or dry powder inhalers. Nevertheless, the development of a metered-dose inhaler (MDI) for colistin, which could enhance patient convenience and treatment efficacy, has not yet been developed. Colistin is known for its ability to induce cellular toxicity. Gold nanoparticles (AuNPs) can potentially mitigate colistin toxicity. Therefore, this study aimed to evaluate the antimicrobial effectiveness of colistin conjugated with chitosan-capped gold nanoparticles (Col-CS-AuNPs) and their potential formulation for use with MDIs to deliver the aerosol directly to the deep lung. Fourier-transform infrared spectroscopy, nuclear magnetic resonance, and elemental analysis were used to characterize the synthesized Col-CS-AuNPs. Drug release profiles fitted with the most suitable release kinetic model were evaluated. An MDI formulation containing 100 µg of colistin per puff was prepared. The aerosol properties used to determine the MDI performance included the fine particle fraction, mass median aerodynamic diameter, and geometric standard deviation, which were evaluated using the Andersen Cascade Impactor. The delivered dose uniformity was also determined. The antimicrobial efficacy of the Col-CS-AuNP formulation in the MDI was assessed. The chitosan-capped gold nanoparticles (CS-AuNPs) and Col-CS-AuNPs had particle sizes of 44.34 ± 1.02 and 174.50 ± 4.46 nm, respectively. CS-AuNPs effectively entrapped 76.4% of colistin. Col-CS-AuNPs exhibited an initial burst release of up to 60% colistin within the first 6 h. The release mechanism was accurately described by the Korsmeyer–Peppas model, with an R2 > 0.95. The aerosol properties of the Col-CS-AuNP formulation in the MDI revealed a high fine particle fraction of 61.08%, mass median aerodynamic diameter of 2.34 µm, and geometric standard deviation of 0.21, with a delivered dose uniformity within 75–125% of the labeled claim. The Col-CS-AuNP MDI formulation completely killed Escherichia coli at 5× and 10× minimum inhibitory concentrations after 6 and 12 h of incubation, respectively. The toxicity of CS-AuNP and Col-CS-AuNP MDI formulations in upper and lower respiratory tract cell lines was lower than that of free colistin. The stability of the Col-CS-AuNP MDI formulation was maintained for at least 3 months. The Col-CS-AuNP MDI formulation effectively eradicated bacteria over a 12-h period, showing promise for advancing lung infection treatments.
New Fe3O4-Based Coatings with Enhanced Anti-Biofilm Activity for Medical Devices
Authors: Pirușcă Ioana Adelina , Balaure Paul Cătălin , Grumezescu Valentina , Irimiciuc Stefan-Andrei , Oprea Ovidiu-Cristian , Bîrcă Alexandra Cătălina , Vasile Bogdan , Holban Alina Maria , Voinea Ionela C. , Stan Miruna S. , Trușcă Roxana , Grumezescu Alexandru Mihai , Croitoru George-Alexandru
Published: July 2024

With the increasing use of invasive, interventional, indwelling, and implanted medical devices, healthcare-associated infections caused by pathogenic biofilms have become a major cause of morbidity and mortality. Herein, we present the fabrication, characterization, and in vitro evaluation of biocompatibility and anti-biofilm properties of new coatings based on Fe3O4 nanoparticles (NPs) loaded with usnic acid (UA) and ceftriaxone (CEF). Sodium lauryl sulfate (SLS) was employed as a stabilizer and modulator of the polarity, dispersibility, shape, and anti-biofilm properties of the magnetite nanoparticles. The resulting Fe3O4 functionalized NPs, namely Fe3O4@SLS, Fe3O4@SLS/UA, and Fe3O4@SLS/CEF, respectively, were prepared by co-precipitation method and fully characterized by XRD, TEM, SAED, SEM, FTIR, and TGA. They were further used to produce nanostructured coatings by matrix-assisted pulsed laser evaporation (MAPLE) technique. The biocompatibility of the coatings was assessed by measuring the cell viability, lactate dehydrogenase release, and nitric oxide level in the culture medium and by evaluating the actin cytoskeleton morphology of murine pre-osteoblasts. All prepared nanostructured coatings exhibited good biocompatibility. Biofilm growth inhibition ability was tested at 24 h and 48 h against Staphylococcus aureus and Pseudomonas aeruginosa as representative models for Gram-positive and Gram-negative bacteria. The coatings demonstrated good biocompatibility, promoting osteoblast adhesion, migration, and growth without significant impact on cell viability or morphology, highlighting their potential for developing safe and effective antibacterial surfaces.
Hospitalized COVID-19 Patients with Urinary Tract Infection in Iran: Candida Species Distribution and Antifungal Susceptibility Patterns
Authors: Shiyadeh Zeinab Soleimani , Farahyar Shirin , Vahedi Larijani Laleh , Beardsley Justin , Nouri Noura , Mahmoudi Shahram , Roudbar Mohammadi Shahla , Rodrigues Célia Fortuna , Roudbary Maryam
Published: July 2024

Candida species, typically part of the human skin and mucous membrane flora, can cause opportunistic fungal infections, notably urinary tract infections (UTIs), which are on the rise among hospitalized COVID-19 patients. The lack of understanding of UTIs in this population, coupled with the emergence of multidrug-resistant strains, poses significant challenges for effective treatment and further investigations. In this study, urine samples were collected from 70 COVID-19 patients with UTIs in sterile containers for microbiology examination. After microscopic observation, the isolates were identified both by phenotypic and molecular techniques such as multiplex PCR. Antifungal susceptibility testing (AFST) against fluconazole (Flu), itraconazole (Itr), and amphotericin B (AMB) was performed according to CLSI M27/S4 standard methods, with the frequency of isolates including Candida albicans (n = 20, 51.3%), Candida tropicalis (n = 15, 38.4%), Nakaseomyces glabrata (previously Candida glabrata) (n = 2, 5.1%), Pichia kudriavzevii (previously Candida krusei), and Candida parapsilosis (n = 1, 2.5%). All isolates of C. albicans, C. tropicalis, C. glabrata, and C. parapsilosis were sensitive to amphotericin B, while C. kruzei was resistant to AMB. Around 70% of C. albicans isolates were sensitive to Flu; 20% of C. tropicalis were resistant to itraconazole, while 33% were resistant to fluconazole. C. albicans and C. tropicalis were the main causes of candiduria in infected cases and both Flu and AMB showed good results in AFST in these species. Performing drug susceptibility testing for clinical isolates of Candida spp. provided guidance for appropriate management and control, and timely antifungal treatment.
Adaptive Cubature Kalman Filter for Inertial/Geomagnetic Integrated Navigation System Based on Long Short-Term Memory Network
Authors: Liu Tianhao , Zhao Tianshang , Zhao Huijun , Wang Chenguang
Published: July 2024

Inertial navigation systems experience error accumulation over time, leading to the use of integrated navigation as a classical solution to mitigate inertial drift. This provides a novel approach to navigation and positioning by using the combined advantages of inertial and geomagnetic navigation systems. However, inertial/geomagnetic navigation is affected by significant magnetic interference in practical scenarios, resulting in reduced navigation accuracy. This research introduces a new neural network-assisted integrated inertial–geomagnetic navigation method (IM-NN), and utilizes the adaptive cubature Kalman filter to integrate attitude information from geomagnetism and inertial sensors. A model was created utilizing a Long Short-Term Memory Network (LSTM) to represent the relationship between specific force, angular velocity, and integrated navigation attitude information. The dynamics were estimated based on current and previous Inertial Measurement Unit (IMU) data using IM-NN. This study demonstrated that the method effectively corrected inertial accumulation errors and mitigated geomagnetic disruption, resulting in a more accurate and dependable navigation solution in environments with geomagnetic rejection compared to conventional single inertial navigation methods.
Comparative Study of Conventional Machine Learning versus Deep Learning-Based Approaches for Tool Condition Assessments in Milling Processes
Authors: Przybyś-Małaczek Agata , Antoniuk Izabella , Szymanowski Karol , Kruk Michał , Sieradzki Alexander , Dohojda Adam , Szopa Przemysław , Kurek Jarosław
Published: July 2024

This evaluation of deep learning and traditional machine learning methods for tool state recognition in milling processes aims to automate furniture manufacturing. It compares the performance of long short-term memory (LSTM) networks, support vector machines (SVMs), and boosting ensemble decision trees, utilizing sensor data from a CNC machining center. These methods focus on the challenges and importance of feature selection, data preprocessing, and the application of tailored machine learning models to specific industrial tasks. Results show that SVM, with an accuracy of 96%, excels in handling high-dimensional data and robust feature extraction. In contrast, LSTM, which is appropriate for sequential data, is constrained by limited training data and the absence of pre-trained networks. Boosting ensemble decision trees also demonstrate efficacy in reducing model bias and variance. Conclusively, selecting an optimal machine learning strategy is crucial, depending on task complexity and data characteristics, highlighting the need for further research into domain-specific models to improve performance in industrial settings.