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BackgroundPolycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age and is closely associated with chronic low-grade inflammation and insulin resistance. To clarify the contribution of prepubertal weight gain to the development of insulin resistance in PCOS, we investigated the effects of early postnatal overfeeding on inflammatory and energy-sensing pathways as well as on markers of insulin signaling in the liver of the PCOS rat model.MethodsObesity induced by overfeeding was achieved by reducing litter size, while the PCOS-like condition was developed by treatment with 5α-dihydrotestosterone (DHT). Western blot and qPCR were used to analyze the expression of pro-inflammatory transcription factors and cytokines, as well as markers of the energy sensing and insulin signaling pathways.ResultsThe results showed that hepatic insulin sensitivity was impaired only in DHT-treated rats raised in small litters, as evidenced by increased phosphorylation of IRS1 on Ser307 and decreased expression of total IRS1. Postnatal overfeeding stimulated JNK1 activation independent of hyperandrogenemia; nevertheless, the synergistic effect of both factors triggered NLRP3 activation and increased IL1β expression in the small litter DHT-treated group. This pro-inflammatory state was accompanied by decreased activatory phosphorylation of AMPK and reduced levels of its protein targets.ConclusionsOverfeeding in the early postnatal period leads to a decrease in hepatic insulin sensitivity in the rat model of PCOS, which is associated with decreased activation of AMPK and stimulation of the hepatic NLRP3-IL1β signaling pathway. Accordingly, the inhibition of NLRP3 activation could provide a basis for the development of new therapeutic strategies for the treatment of insulin resistance in women with PCOS.

Introduction/Objective. Neurological impairment and immobility in stroke patients can lead to numerous complications. This study aimed to evaluate the effect of cycling exercises with visual feedback combined with conventional rehabilitation on neurological and motor recovery, balance, walking speed and endurance, and activities of daily living (ADL) in patients after acute and subacute stroke. Methods. A randomized prospective controlled trial was applied to this research. One hundred and twenty-seven hemiplegic stroke patients who received in-hospital rehabilitation were randomly assigned into two groups. Both groups received conventional rehabilitation treatment. The experimental group had an extra 30 minutes of cycling exercises for the upper and lower extremities on a stationary ergocycle MOTOmed muvi. Both groups’ neurological status, upper and lower limb function, independence in ADL, balance, walking speed, and endurance were observed before and after the rehabilitation treatment. Outcome measures used were the National Institute of Health Stroke Scale (NIHSS), the modified Ashworth scale (MAS), the Brunnstrom Motor Evaluation Scale (BMES), upper and lower Fugl-Meyer assessment (FMA), the Barthel index (BI), the Berg Balance Scale (BBS), the six-minute walk test (6MWT) and the Timed Up and Go test (TUG). Results. The neurological recovery on the NIHSS scale, spasticity of the knee extensor measured by the MAS, the BMES and FMA-LE subscale for the affected leg, and the 6MWT presented more significant improvement in the experimental group than in the control group after the treatment (p < 0.05 for all three analyses). Conclusion. Cycling exercises with visual feedback combined with conventional rehabilitation could promote neurological recovery and improve the motor function of the affected leg and walking speed in patients recuperating after acute and subacute stroke.

Background/Aim. A very limited amount of data regarding the rehabilitation outcome of surgical patients with COVID-19 is available in the current literature. The aim of this study was to point out the characteristics of early rehabilitation of these patients and determine the predictors of rehabilitation outcomes. Methods. The study was designed as a prospective clinical trial. It included patients who had surgical treatment from April 1, 2022, to March 31, 2023, at the University Clinical Center of Vojvodina, Serbia and either had positive results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) preoperatively or developed coronavirus disease 2019 (COVID-19) within 72 hrs after surgery. The rehabilitation program was planned for each patient according to the type of surgical treatment, age, clinical presentation and severity of the COVID-19, length of immobilization, and comorbidities. Rehabilitation treatment (RT) started with a minimum of one 30-minute daily session, up to three 30-minute sessions daily. Patients were assessed at the beginning of RT and discharge. Outcomes were assessed with the Modified Borg Scale (MBS) for dyspnoea, Barthel index (BI) for activities of daily living, Six-Minute Walk Test (6MWT) for exercise tolerance, and Timed up and Go (TUG) test for balance and lower limb mobility. Results. A total of 81 patients were included in the study. RT was successful for 42 patients (24 female and 18 male) with an average age of 62.10 ± 20.07 years. These patients exhibited significant functional improvement, which was measured by all tests that assessed rehabilitation outcome at discharge: BI (p < 0.001), MBS (p < 0.001), 6MWT (p < 0.001), and TUG test (p < 0.001). The remaining 31 patients had unsuccessful RT. The binary logistic regression analysis has shown that age (p = 0.009), cardiovascular disease (p = 0.017), and malignancy (p = 0.022) were significant predictors of rehabilitation outcome. Conclusion. Results of the present study implicate that individually tailored RT during the acute phase of COVID-19 in surgical patients is very challenging. Advanced age, cardiovascular disease, and malignancy are predictors of unfavorable outcomes, and careful consideration is needed when planning the treatment for these patients.

In order to gain a better understanding of contemporary political realism, as well as of the theories of two classical political philosophers, this paper argues that the methodological roots of a contextualist model of realism can be found, among others, in the writings of Aristotle and Machiavelli. It is argued that the methodological assumptions of contextualist political realism can be formulated through two main notions: 1) the experiential basis - analysis of politics through reliance on experience from political practice; and 2) contextualism - avoiding universal claims as much as possible, i.e., making claims about politics always within a socio-historical context. Using those lenses, the paper points out the methodological elements of Aristotle's and Machiavelli's political theories that are in line with this version of political realism, claiming both of them could be perceived as forerunners to a certain degree.

Hyperspectral imaging has emerged as a pivotal technology in agricultural research, offering a powerful means to non-invasively monitor stress factors, such as drought, in crops like potato plants. In this context, the integration of attention-based deep learning models presents a promising avenue for enhancing the efficiency of stress detection, by enabling the identification of meaningful spectral channels. This study assesses the performance of deep learning models on two potato plant cultivars exposed to water-deficient conditions. It explores how various sampling strategies and biases impact the classification metrics by using a dual-sensor hyperspectral imaging systems (VNIR -Visible and Near-Infrared and SWIR—Short-Wave Infrared). Moreover, it focuses on pinpointing crucial wavelengths within the concatenated images indicative of water-deficient conditions. The proposed deep learning model yields encouraging results. In the context of binary classification, it achieved an area under the receiver operating characteristic curve (AUC-ROC—Area Under the Receiver Operating Characteristic Curve) of 0.74 (95% CI: 0.70, 0.78) and 0.64 (95% CI: 0.56, 0.69) for the KIS Krka and KIS Savinja varieties, respectively. Moreover, the corresponding F1 scores were 0.67 (95% CI: 0.64, 0.71) and 0.63 (95% CI: 0.56, 0.68). An evaluation of the performance of the datasets with deliberately introduced biases consistently demonstrated superior results in comparison to their non-biased equivalents. Notably, the ROC-AUC values exhibited significant improvements, registering a maximum increase of 10.8% for KIS Krka and 18.9% for KIS Savinja. The wavelengths of greatest significance were observed in the ranges of 475–580 nm, 660–730 nm, 940–970 nm, 1420–1510 nm, 1875–2040 nm, and 2350–2480 nm. These findings suggest that discerning between the two treatments is attainable, despite the absence of prominently manifested symptoms of drought stress in either cultivar through visual observation. The research outcomes carry significant implications for both precision agriculture and potato breeding. In precision agriculture, precise water monitoring enhances resource allocation, irrigation, yield, and loss prevention. Hyperspectral imaging holds potential to expedite drought-tolerant cultivar selection, thereby streamlining breeding for resilient potatoes adaptable to shifting climates.

Increased energy consumption and climate change, driven by greenhouse gas emissions, pose significant risks to global sustainability. Concerns about using agricultural land for fuel production and its competition with food production have made feedstocks like corn (Zea mays) highly controversial. This study explores the potential of alternative feedstocks, such as hemp (Cannabis sativa) and cucurbits (family Cucurbitaceae), for biofuel production amidst environmental concerns linked to fossil fuel usage. Hemp is widely acknowledged as a promising feedstock for sustainable biorefinery due to its agricultural adaptability and its ability to produce oil and carbohydrates. Cucurbits seeds are characterized by a high oil content, which can be utilized in the food industry or for energy production as biofuel. As a byproduct of cucurbits processing, a significant number of seeds often remains, which constitutes waste. By examining hemp and cucurbit byproducts and waste, which are suitable for bioenergy production, this research highlights the promise these alternative feedstocks hold for the biofuel industry. Utilizing these resources presents a viable route to diminish dependence on fossil fuels and transition toward a more environmentally sustainable energy future.

Increased fructose consumption and chronic stress, the major characteristics of modern lifestyle, impact human health; however, the consequences of their combination on the uterus remain understudied. In this study, we investigated contractile activity, morphology, and intracellular activity of antioxidant enzymes in uteri from virgin Wistar rats subjected to liquid fructose supplementation and/or unpredictable stress over 9 weeks. Contractile activity and uterine response to oxytocin or adrenaline were examined ex vivo using isolated bath chambers. Fructose supplementation, irrespective of stress, affected uterine morphology by increasing endometrium while decreasing myometrium volume density, attenuated uterine response to increasing doses of oxytocin, and increased glutathione peroxidase activity. Stress, irrespective of fructose, attenuated dose-dependent adrenaline-induced uterine relaxation. Stress, when applied solely, decreased mitochondrial superoxide dismutase activity. In the combined treatment, irregular estrous cycles and both reduced response to oxytocin and to adrenaline (as a consequence of fructose consumption and exposure to stress), along with fructose-related alteration of uterine morphology, were detected. In conclusion, fructose and stress affect uterine contractile activity, irrespective of each other, by inducing completely distinct responses in isolated uteri. In the combined treatment, the effects of both factors were evident, suggesting that the combination exerts more detrimental effects on the uterus than each factor individually.

Palmitoylethanolamide (PEA) is an endocannabinoid-like bioactive lipid mediator belonging to the family of N-acylethanolamines, most abundantly found in peanuts and egg yolk. When the gastrointestinal (GI) effects of PEA are discussed, it must be pointed out that it affects intestinal motility but also modulates gut microbiota. This is due to anti-inflammatory, antioxidant, analgesic, antimicrobial, and immunomodulatory features. Additionally, PEA has shown beneficial effects in several GI diseases, particularly irritable bowel syndrome and inflammatory bowel diseases, as various studies have shown, and it is important to emphasize its relative lack of toxicity, even at high dosages. Unfortunately, there is not enough endogenous PEA to treat disturbed gut homeostasis, even though it is produced in the GI tract in response to inflammatory stimuli, so exogenous intake is mandatory to achieve homeostasis. Intake of PEA could be through animal and/or vegetable food, but bearing in mind that a high dosage is needed to achieve a therapeutic effect, it must be compensated through dietary supplements. There are still open questions pending to be answered, so further studies investigating PEA’s effects and mechanisms of action, especially in humans, are crucial to implementing PEA in everyday clinical practice.

Droughts are more and more often a limiting factor to agricultural production and can have severe negative effects on food security in vulnerable countries. Global agriculture early warning systems monitor agriculture in near real-time by analyzing meteorological data (e.g. precipitation and temperature) and optical remote sensing data as proxy vegetation health to detect possible negative anomalies and trigger warnings. Seasonal climate forecast can add a predictive component and inform about upcoming precipitation deficits, thus allowing anticipation and improved planning of response actions. Here, we propose a scheme to adapt the standard precipitation forecast from the seasonal Copernicus Climate Change Service multi-system to crop and rangeland phenology, making them suitable for agricultural early warning. Precipitation forecasts are first elaborated into tercile maps showing the probability of the most likely tercile (i.e. drier than normal, normal, wetter than normal) and associated skills of all possible monthly periods combinations included in the six months forecasting horizon. Afterwards, agronomically relevant tercile maps are produced for the closest season in time at any location. These maps are obtained by mosaicking the forecasts for the appropriate growing season period at each grid cell. The resulting map shows the tercile probability for the remaining part of the ongoing growing season (if any at time of analysis) or the probability of the next upcoming season (if in between growing season at time of analysis). The proposed methodology offers a precipitation seasonal forecast product ready to use by agricultural analysts and directly ingestible by automatic warning systems.

In Somalia’s drylands, charcoal production is a major driver of forest degradation enabled by civil conflict and institutional weakness. Up to now, the extent and exact location of charcoal production has usually been estimated by visually detecting charcoal kilns on Very High Resolution (VHR) images. Taking advantage of the availability of a dataset of charcoal kilns delineated on VHR images by the Food and Agriculture Organization (FAO) experts, we designed a computer vision (CV) approach to automatically identify charcoal kilns on VHR images. The methodology relies on a curated subset of the expert-labeled dataset and a collection of panchromatic and pan-sharpened multispectral Natural Color (RGB) VHR for the years 2018 and 2019. Kiln delineations paired with the VHR images are visually reviewed and used with a Faster R-CNN model, an object detection deep learning method. A two-stage methodology is used to train the best models for panchromatic and RGB images, respectively. The first stage uses a small number of high quality pairs to define the best parameters of the models while the second stage uses a larger set of pairs to fine tune the previous models. The results indicates that charcoal kilns are detected with a precision of 90% in panchromatic images and of 80% in RGB images. The models are then used to predict the presence of kilns over the available VHR images. Omission errors are prioritized over commission errors to mitigate the difficulty in detecting kilns in some specific situations. Comparison between the FAO expert kiln dataset and objects predicted by the CNN model is giving encouraging results. With a visual screening complementing the proposed workflow, CV can aid charcoal kiln monitoring in Somalia while alleviating manual work.

In the pursuit of maximizing onion (Allium cepa) yield and quality, farmers often face the challenges of unfavorable ecological conditions and inadequate agronomic practices. Therefore, our two-year study investigated the effects of biostimulants (BTs) of plant growth on bulb yield and the bioactive compounds of directly seeded onion. Four treatments were applied: control (C), seaweed extracts (BT1), humic and fulvic acid (BT2), and Trichoderma spp. (BT3). The results demonstrated a significant increase in bulb yield with BT1 (↑ 18.7%), BT2 (↑ 18.0%), and BT3 (↑ 24.3%). Intriguingly, all BTs markedly reduced phenolic content across both years. Additionally, BT1 and BT3 elevated flavonoid levels (↑ 16.8% and ↑ 16.7%, respectively), while BT2 decreased them (↓ 24.2%). Notably, in 2021, DPPH, FRAP, and ABTS tests indicated a significant reduction in antioxidant capacity compared to C. Our study underscores the important role of BTs in enhancing yield, influencing secondary metabolites and contributing to environmental sustainability in onion cultivation.

This paper analyses the spatial layout and possibilities of the antifascism tangible heritage for memorial tourism development in the municipalities and towns of Southern Istria. In the first half of the 20th century, the antifascist struggle in Istria was a crucial part of several political turning points. Those historical turning points had far-reaching consequences and, for the most part, were marked by armed conflicts, individual and mass human casualties and terror over the population. The motive of travel in memorial tourism here is to visit the places where these tragic events occurred and commemorate the victims. The aim of the research was to determine the geographical distribution of the antifascism tangible heritage in Southern Istria and their suitability for the development of memorial tourism. An additional objective was to propose thematic routes of memorial tourism in Southern Istrian municipalities and towns. Methods of analyses of historical research, fieldwork, participant observation, spatial and GIS analysis were used. The survey indicated that six South Istrian municipalities and two towns have 167 well-preserved and marked tangible antifascism monuments. The largest number of monuments are located in the central district of the city of Pula. The main contribution of this article was to provide re-evaluation of antifascism tangible heritage as the potential resource for the memorial tourism development as the innovation in the tourism supply of Istria.

Objectives: The study aimed to determine the relationship between the mandibular asymmetry index according to Kjellberg between patients with painful unilateral anterior disc displacement (DD) and asymptomatic volunteers without disc displacement. Vertical measurements were performed on a panoramic single-image radiograph, and the disc status was confirmed by magnetic resonance imaging (MRI). Material and methods: Two groups of subjects were retrospectively selected, 40 patients (the overall mean age was 35.5 years; 75% female) with temporomandibular disorder symptoms confirmed by RDC/TMD axis I and manual functional analysis. Unilateral DD was determined by MRI. A comparative group of asymptomatic volunteers (20 dental students with a mean age of 23.4 years; 72% female) had the physiological position of the disc determined by MRI. The vertical asymmetry of the condyle was determined by the method of Kjellberg et al. The symmetry of the gonial angle of the mandible was also measured. Results: A comparison of the mean of the asymmetry index between patients (average 90.89±7.08%) and asymptomatic volunteers (mean 95.86±4.44%) showed a statistically significant difference (p=0.0029). There was no difference (p=0.088) in gonial angle symmetry between the patients (mean 96.48±2.96°) and the asymptomatic volunteers (mean 97.52±2.31°). The distribution of the presence of individual DD diagnoses (partial and total displacement with reduction, displacement without reduction) in patients diagnosed with asymmetry of the mandible was without statistical significance (p>0.05). Conclusion: This study actually points to the asymmetry of the mandible as a potential morphological risk of anterior DD.