Background/Objectives: We conducted a comprehensive investigation to explore the pathological expression of the CXCR4 receptor in lymphoproliferative disorders (LPDs) using [⁶⁸Ga]Ga-Pentixafor PET/CT or PET/MRI technology. The PICO question was as follows: What is the diagnostic role (outcome) of [⁶⁸Ga]Ga-Pentixafor PET (intervention) in patients with LPDs (problem/population)? Methods: The study was written based on the reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, and it was registered on the prospective register of systematic reviews (PROSPERO) website (CRD42024506866). A comprehensive computer literature search of Scopus, MEDLINE, Scholar, and Embase databases was conducted, including articles indexed up to February 2024. To the methodological evaluation of the studies used the quality assessment of diagnosis accuracy studies-2 (QUADAS-2) tool. Results: Of the 8380 records discovered, 23 were suitable for systematic review. Fifteen studies (on 571 LPD patients) focused on diagnosis and staging, and eight trials (194 LPD patients) assessed treatment response. Conclusions: The main conclusions that can be inferred from the published studies are as follows: (a) [⁶⁸Ga]Ga-Pentixafor PET may have excellent diagnostic performance in the study of several LPDs; (b) [⁶⁸Ga]Ga-Pentixafor PET may be superior to [¹⁸F]FDG or complementary in some LPDs variants and settings; (c) multiple myeloma seems to have a high uptake of [⁶⁸Ga]Ga-Pentixafor. Overall, this technique is probably suitable for imaging, staging, and follow-up on patients with LPD. Due to limited data, further studies are warranted to confirm the promising role of [⁶⁸Ga]Ga-Pantixafor in this context. Full article

Background/Objectives: Obesity is currently considered a public health problem in both developed and developing countries. Gender- and age-specific body mass index (BMI) growth standards or references are particularly effective in monitoring the global obesity pandemic. This study aimed to report disparities in age-, gender- and ethnic-specific statistical estimates of overweight and obesity for 2–18 years aged Pakistani children and adolescents using the World Health Organization (WHO), the Center for Disease Control (CDC) 2000 references, the International Obesity Task Force (IOTF) and Pakistani references for BMI. Methods: The study used secondary data of 10,668 pediatric population, aged 2–18 years. Demographic information like age (years), gender, city and anthropometric examinations, i.e., height (cm) and weight (kg) were used in this study. The recommended age- and gender-specific BMI cut-offs of the WHO, CDC 2000 and the IOTF references were used to classify the children sampled as overweight and obese. For the Pakistani reference, overweight and obesity were defined as BMI-for-age ≥ 85th percentile and BMI-for-age ≥ 95th percentile, respectively. Cohen’s κ statistic was used to assess the agreement between the international references and local study population references in the classification of overweight/obesity. Results: The statistical estimates (%) of the participants for overweight and obesity varied according to the reference used: WHO (7.4% and 2.2%), CDC (4.9% and 2.1%), IOTF (5.2% and 2.0%) and Pakistan (8.8% and 6.0%), respectively; suggesting higher levels of overweight and obesity prevalence when local study references are used. The Kappa statistic shows a moderate to excellent agreement (κ ≥ 0.6) among three international references when classifying child overweight and obesity and poor agreement between local references and the WHO (0.45, 0.52), CDC (0.25, 0.50) and IOTF references (0.16, 0.31), for overweight and obesity, respectively. Conclusions: The results of the study showed a visible difference in the estimates of excess body weight after applying the WHO, CDC, IOTF and local BMI references to the study population. Based on the disparity results and poor agreement between international references and the local study reference, this study recommends using local BMI references in identifying children with overweight and obesity. Full article

Background: Biomarkers development for prognostication or prediction of perioperative myocardial disease is critical for the evolution of treatment options in patients undergoing cardiac surgery. The aim of our prospective monocentric study was to investigate the role of selenoprotein 1 (SEEP 1) as a potential biomarker for assessing the risk of myocardial injury after cardiac surgery. Methods: Circulating SEPP1 was measured in the blood of 45 patients before surgery and at 4 h, 8 h and 12 h after CPB by enzyme-linked immunosorbent assay (ELISA); (3) Results: circulating SEPP-1 levels measured 4 h after surgery were strongly correlated with CK-MB levels measured at 48 h (R = 0.598, p < 0.0001) and at 72 h (R = 0.308, p = 0.05). Close correlations were also found between 4 h SEPP-1 and Hs-c troponin values measured at 24 h (R = 0.532, p < 0.0001), 48 h (R = 0.348, p = 0.01) and 72 h (R = 0.377, p = 0.02), as well as with cardiopulmonary bypass (CPB) (R = 0.389, p = 0.008) and cross-clamp time (R = 0.374, p = 0.001); (4) Conclusions: Early SEPP1 measurement after CPB may hold great potential for identifying cardiac surgery patients at risk of developing perioperative myocardial injury. Full article

Electrocardiogram (ECG) abnormalities are the most common cardiac complications after acute ischemic stroke (AIS) and predict poor outcomes. The arterial baroreflex is an essential determinant of cardiovascular autonomic regulation, with receptors mainly residing in carotid sinuses and aortic arch. The atherosclerosis of these baroreceptor-resident arteries (BRA) is very common in AIS patients and might impair baroreflex function. However, the associations between the atherosclerosis of BRA and ECG abnormalities after AIS are still unknown. In total, 228 AIS patients within 7 days after onset without a pre-existing heart disease were prospectively recruited. With computed tomography angiography, atherosclerosis conditions in 10 segments of the carotid sinuses and aortic arch were scored and summed as the Total Atherosclerosis Burden of BRA (TAB-BRA), and asymptomatic coronary artery stenosis (ACAS) ≥50% was simultaneously assessed. We performed 12-lead ECG to dynamically detect abnormal repolarization, and 24 h Holter ECG to monitor arrhythmias and heart rate variability (HRV) parameters, which are reliable indicators to assess cardiac autonomic function. We found that TAB-BRA was positively associated with abnormal repolarization (OR 1.09; CI% 1.03–1.16; p = 0.003) and serious cardiac arrhythmias (OR 1.08; CI% 1.01–1.15; p = 0.021). In addition, TAB-BRA was an important predictor of abnormal repolarization, persisting over 3 days (OR 1.17; CI% 1.05–1.30; p = 0.003). However, ACAS ≥ 50% did not relate to these ECG abnormalities. TAB-BRA was negatively correlated with parasympathetic-related HRV parameters. Our results indicated that AIS patients with a high TAB-BRA are more likely to have ECG abnormalities and delayed normalization, which may relate to the decreased cardiac parasympathetic activity, but not the accompanied ACAS ≥ 50%. Full article

Wheat is the main grain crop in our country, and the traditional wheat yield estimation method is time-consuming and laborious. By estimating wheat yield efficiently, quickly and non-destructively, agricultural producers can quickly obtain information about wheat yield, manage wheat fields more scientifically and accurately, and ensure national food security. Taking the Xinxiang Experimental Base of the Crop Science Research Institute, Chinese Academy of Agricultural Sciences as an example, hyperspectral data for the critical growth stages of wheat were pre-processed. A total of 27 vegetation indices were calculated from the experimental plots. These indices were then subjected to correlation analysis with measured wheat yield. Vegetation indices with Pearson correlation coefficients greater than 0.5 were selected. Five methods, including multiple linear regression, stepwise regression, principal component regression, neural networks and random forests, were used to construct wheat yield estimation models. Among the methods used, multiple linear regression, stepwise regression and the models developed using principal component analysis showed a lower modelling accuracy and validation precision. However, the neural network and random forest methods both achieved a modelling accuracy R² greater than 0.6, with validation accuracy R² values of 0.729 and 0.946, respectively. In addition, the random forest method had a lower cross-validation RMSE value, with values of 869.8 kg/hm⁻², indicating a higher model accuracy. In summary, the random forest method provided the optimal estimation for wheat yield, enabling the timely and accurate pre-harvest wheat yield prediction, which has significant value for precision agriculture management and decision making. Full article

(1) Background: Since multiple sclerosis (MS) is a neurological pathology known for its disabling effects across many domains, the introduction of virtual reality (VR) usage has been attempted, as it represents a new method of approach to rehabilitation and treatment of chronic neurological pathologies. Encouraging research has explored the use of video game consoles and VR-assisted Robot-Assisted Gait Training (RAGT) to address balance disturbances in this population. (2) Methods: The search involved two databases, Web of Science and PubMed, utilizing a selection of terms including “Virtual reality”, “Multiple sclerosis”, “Balance”, and “Rehabilitation”. Two reviewers initiated and performed the search for articles, subsequently selecting and extracting data from the studies. The PEDro scale was the tool for evaluating the quality of the articles that we introduced in our research. (3) Results: After rigorous scanning, nine articles remained eligible for our study. VR interventions, particularly compared to standard balance training, consistently improved balance in multiple sclerosis. Robotic-assisted technology with 2D VR yielded superior results in balance rehabilitation. VR interventions had varied effects on walking speed. They have shown promise in decreasing the risk of falls and improving patients’ daily lives while reducing fatigue in multiple sclerosis. (4) Conclusions: VR offers comparable or superior benefits to classical exercise and no intervention for balance but does not significantly improve functional mobility. However, it shows the potential to improve quality of life and fatigue in MS patients. Investigation of VR alongside RAGT is important to be performed with larger sample sizes and comprehensive results are needed to fully understand its efficacy in MS rehabilitation. Full article

Transportation has an essential place in societies and importance to people in terms of its social and economic aspects. Innovative rail systems need to be integrated with developing technologies for transportation. Systemic failures, personnel errors, sabotage, and cyber-attacks in the techniques used will cause a damaged corporate reputation and revenue losses. In this study, cybersecurity attack methods in smart rail systems were determined, and cyber events occurring worldwide through these technologies were analyzed. Risk analysis in terms of transportation safety in smart rail systems was determined by considering the opinions of 10 different experts along with the Analytic Hierarchical Process (AHP) performance criteria. Informatics experts were selected from a group of people with at least 5–15 years of experience. According to these risk analysis calculations, cybersecurity stood out as the most critical security risk at 27.74%. Other risky areas included physical security, calculated at 14.59%, operator errors at 16.20%, and environmental security at 10.93%. Full article

This study aimed to develop biocomposite films based on cassava starch and microcrystalline cellulose (MCC) derived from cassava pulp for potential medical packaging applications. MCC was extracted from cassava pulp, and its structure and chemical composition, crystallinity, and thermal properties were characterized. The MCC showed a yield of 14.92% and crystallinity of 46.91%. Different MCC contents (1%, 3%, and 5% w/w of starch) were incorporated into cassava starch films. The effects of MCC contents on film properties, including morphology, thickness, mechanical strength, chemical interactions, moisture content, surface wettability, and water activity index, were studied. The effects of UV-C sterilization on the disinfection of starch/MCC on film properties were determined. Results showed that all starch/MCC films exhibited good transparency and thickness ranging from 127 to 144 µm. As MCC content increased from 1 to 5%, Young’s modulus and tensile strength of the films improved significantly from 112.12 to 488.89 MPa and 3.21 to 11.18 MPa, respectively, while elongation at break decreased from 44.74 to 4.15%. Incorporating MCC also reduced film surface wettability, with the water contact angle increasing from 69.17° to 102.82°. The starch/3%MCC holds promise as a biocomposite film for medical packaging applications, offering advantages in terms of good transparency, mechanical properties, and surface hydrophobicity. Furthermore, the absence of microbial growth in the sterilized gauze pad with sealing in the sterilized starch/3%MCC film confirms that the UV-C sterilization, 30 min for each side at 254 nm effectively eliminated any microorganisms present on the starch/3%MCC film without damaging the film properties. This finding highlights a reliable approach to ensuring the sterility of starch/MCC films for medical packaging applications. Full article

The detection of faults during an operational process constitutes a crucial objective within the framework of developing a control system to monitor the structure of industrial mechanisms. Even minor faults can give rise to significant consequences that require swift resolution. This research investigates the impact of overtension in the tooth belt transmission and heating of the screw transmission worm on the vibration signals in a robotic system. Utilizing FFT techniques, distinct frequency characteristics associated with different faults were identified. Overtension in the tooth belt transmission caused localized oscillations, addressed by adjusting the acceleration and deceleration speeds. Heating of the screw transmission worm led to widespread disturbances affecting servo stress and positioning accuracy. A fuzzy logic algorithm based on spectral analysis was proposed for adaptive control, considering the vibration’s frequency and amplitude. The simulation results demonstrated effective damage mitigation, reducing wear on the mechanical parts. The diagnostic approach, relying on limited data, emphasized the feasibility of identifying transmission damage, thereby minimizing maintenance costs. This research contributes a comprehensive and adaptive solution for robotic system diagnostics and control, with the proposed fuzzy logic algorithm showing promise for efficient signal processing and machine learning applications. Full article

Aiming at the phenomenon that a high-power torque converter is susceptible to cavitation, which leads to performance degradation, first, a transient flow field model of the torque converter is established, and CFD simulation and experimental research on the torque converter are carried out to find out the speed ratio region where cavitation occurs in the torque converter as well as the rule of occurrence of cavitation, and then the cavitation identification method based on the difference between the inlet and outlet flow of the torque converter is proposed. Then, the transient flow process inside the torque converter is analyzed, and it is pointed out that the angle between the inlet angle of the stator and the outlet angle of the turbine of the torque converter, i.e., the fluid inflow injection deviation angle is an important factor affecting the cavitation phenomenon. By adjusting the key parameters of the stator blade bone line, the fluid inflow deviation angle of the torque converter stator is optimized, so that the speed ratio range of cavitation under large load conditions is greatly reduced from the original 0–0.5 (50%) to 0–0.15 (15%). Meanwhile, in terms of test performance, the nominal torque of the torque converter is greatly improved under the premise of ensuring that the performance is basically unchanged, in which the nominal torque of the test zero speed is increased by 28.7%, and the cavitation of the torque converter has been greatly improved. Full article

Technological developments coupled with socioeconomic changes are driving a rapid transformation of the fifth-generation (5G) cellular network landscape. This evolution has led to versatile applications with fast data-transfer capabilities. The integration of 5G with wireless sensor networks (WSNs) has rendered the Internet of Things (IoTs) crucial for measurement and sensing. Although 5G-enabled IoTs are vital, they face challenges in data integrity, such as mixed noise, outliers, and missing values, owing to various transmission issues. Traditional methods such as the tensor robust principal component analysis (TRPCA) have limitations in preserving essential data. This study introduces an enhanced approach, the weighted robust tensor principal component analysis (WRTPCA), combined with weighted tensor completion (WTC). The new method enhances data recovery using tensor singular value decomposition (t-SVD) to separate regular and abnormal data, preserve significant components, and robustly address complex data corruption issues, such as mixed noise, outliers, and missing data, with the globally optimal solution determined through the alternating direction method of multipliers (ADMM). Our study is the first to address complex corruption in multivariate data using the WTRPCA. The proposed approach outperforms current techniques. In all corrupted scenarios, the normalized mean absolute error (NMAE) of the proposed method is typically less than 0.2, demonstrating strong performance even in the most challenging conditions in which other models struggle. This highlights the effectiveness of the proposed approach in real-world 5G-enabled IoTs. Full article

The use of deep convolutional neural networks has significantly improved the performance of super-resolution. Employing deeper networks to enhance the non-linear mapping capability from low-resolution (LR) to high-resolution (HR) images has inadvertently weakened the information flow and disrupted long-term memory. Moreover, overly deep networks are challenging to train, thus failing to exhibit the expressive capability commensurate with their depth. High-frequency and low-frequency features in images play different roles in image super-resolution. Networks based on CNNs, which should focus more on high-frequency features, treat these two types of features equally. This results in redundant computations when processing low-frequency features and causes complex and detailed parts of the reconstructed images to appear as smooth as the background. To maintain long-term memory and focus more on the restoration of image details in networks with strong representational capabilities, we propose the Frequency-Separated Attention Network (FSANet), where dense connections ensure the full utilization of multi-level features. In the Feature Extraction Module (FEM), the use of the Res ASPP Module expands the network’s receptive field without increasing its depth. To differentiate between high-frequency and low-frequency features within the network, we introduce the Feature-Separated Attention Block (FSAB). Furthermore, to enhance the quality of the restored images using heuristic features, we incorporate attention mechanisms into the Low-Frequency Attention Block (LFAB) and the High-Frequency Attention Block (HFAB) for processing low-frequency and high-frequency features, respectively. The proposed network outperforms the current state-of-the-art methods in tests on benchmark datasets. Full article

Adherence to fire safety regulations for wood is one of the most important tasks in its use in structural and architectural applications. This article deals with determining the influence of heat flux on the ignition process of spruce (Picea abies L. Karst.) and beech wood (Fagus sylvatica L.). The heat flux was generated by an electric radiant panel. The analysed parameters included the ignition time of the spruce and beech wood samples, the influence of wood density, and sample moisture, and the course of sample combustion, both with and without flame, was observed. The heat flux was maintained at constant values, depending on the distance of the examined sample from the panel, along with the specific power of the radiation panel. The power of the radiation panel was set to constant values of 5 kW and 10 kW. The samples were placed at distances of 50, 70, 100, 150, and 200 mm from the heat source, and heat fluxes in the range of 13–92 kW·m⁻² were observed. At a power of 5 kW and a heat flux of 64 kW·m⁻², neither the sample of beech nor that of spruce wood, placed at the distance of 100 mm from the radiation panel, exhibited flaming combustion. The ignition time for the beech wood was approximately twice that of the spruce wood, likely due to the higher average wood density. It can be stated that wood density, as one of the main factors, significantly influences the ignition phase of burning. The statistical analysis examined variables including wood type, radiant panel output, distance, and heat flux in relation to ignition time. The analysis revealed a significant difference between ignition time and distance (p-value = 0.0000, H = 37.51583) as well as between ignition time and heat flux (p-value = 0.0000, H = 37.69726). Similarly, the time to ignition for all tested beech wood samples was longer than for spruce wood. Full article

Single-crystal diamond tools occupy an important position in the field of optical processing as the basis and key to advanced optical manufacturing technology, such as grating manufacturing and optical mirror-turning processing. Single-crystal diamond tools have become the cornerstone of the development of related industries. This paper takes a single-crystal diamond arc tool as the research object. Sound signal analysis technology and vibration signal analysis technology are comprehensively applied to the online orientation identification of a single-crystal diamond tool in the indexing grinding process. The online orientation method of the tool is explored, the sound signal and the vibration signal are taken as the characteristic signals, and a wavelet algorithm (WT) is used to reduce the noise of the vibration signal and sound signal. The kurtosis of the sound signal and the kurtosis and skewness of the vibration signal in the high-order statistics strongly related to the grinding direction of a single-crystal diamond are used as the characteristic parameters, and the online direction recognition model of the tool is established using the Hidden Markov Method (HMM). The above characteristic parameters are used as model input for multi-information fusion. The mapping relationship between the characteristic parameters of the characteristic signal and the crystal orientation of the single-crystal diamond crystal face is obtained, and then the online orientation method of the single-crystal diamond arc tool in the process of indexing grinding is formed. The effectiveness of the method is verified by experiments, and effective orientation information is provided for research on the positioning control strategy of the tool grinding process to ensure the efficiency of grinding and improve the manufacturing level of the tool. Full article

 This research, focusing on the environmental impact of tire and brake disc pad wear, constitutes a significant area of transport-related studies. These two key vehicle components are not only the most frequently worn but also generate micro- and nano-pollutants (i.e., rubber, metal oxides) that potentially harm the environment. Over half of the globally produced natural and synthetic rubbers, which amounted to about 30 million tons in 2022, are used for tire production. This work focuses on the study of roadside snow, sand, and standing water deposits from various locations in the urban agglomeration (Poznań, Poland) during the winter season, determining their qualitative composition and the quantitative content of pollutants originating from tire abrasion. In addition, the method of washing nano- and micro-rubber particles and their full characteristics was also presented. Fourier-transform infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopic studies, optical and scanning electron microscopy (SEM-EDS), particle size studies using a dynamic light scattering (DLS) particle analyzer, and thermogravimetric analysis (TGA) were conducted for a detailed characterization of the pollutants in the environment. The conducted particle separation methods allowed for the extraction of a fraction mainly containing gum residues with particle sizes less than 2 µm. The results of these tests make it possible to estimate the level of contamination with rubber and metal residues during the abrasion of tires, pads, and brake discs while driving, which is crucial for understanding the impact of vehicle part exploitation on the environment.  Full article

Efficient magnetic resonance imaging (MRI) segmentation, which is helpful for treatment planning, is essential for identifying brain tumors from detailed images. In recent years, various convolutional neural network (CNN) structures have been introduced for brain tumor segmentation tasks and have performed well. However, the downsampling blocks of most existing methods are typically used only for processing the variation in image sizes and lack sufficient capacity for further extraction features. We, therefore, propose SARFNet, a method based on UNet architecture, which consists of the proposed SL_iRF module and advanced AAM module. The SL_iRF downsampling module can extract feature information and prevent the loss of important information while reducing the image size. The AAM block, incorporated into the bottleneck layer, captures more contextual information. The Channel Attention Module (CAM) is introduced into skip connections to enhance the connections between channel features to improve accuracy and produce better feature expression. Ultimately, deep supervision is utilized in the decoder layer to avoid vanishing gradients and generate better feature representations. Many experiments were performed to validate the effectiveness of our model on the BraTS2018 dataset. SARFNet achieved Dice coefficient scores of 90.40, 85.54, and 82.15 for the whole tumor (WT), tumor core (TC), and enhancing tumor (ET), respectively. The results show that the proposed model achieves state-of-the-art performance compared with twelve or more benchmarks. Full article

The accurate identification of target imagery in the presence of sea fog is essential for the precise detection and comprehension of targets situated at sea. To overcome the issues encountered when applying traditional polarimetric dehazing methods to sea fog imagery, this paper proposes an improved polarimetric dehazing method. Initially, the methodology employs quartile-based selection on polarization difference images to ascertain atmospheric light at an infinite distance. Subsequently, the study describes a segmentation approach for sea–sky background images based on the degree of polarization. The results show that the image information entropy of the segmentation process improves by more than 6% compared to that of alternative methodologies, and the local contrast of the image is increased by more than 30% compared to that of the original foggy image. These outcomes confirm the effectiveness of the proposed dehazing methodology in addressing the challenges associated with sea fog imagery. Full article

This multimethod study investigated an environmental recycling project in a Finnish kindergarten group, tailored for children aged 4 to 6, as part of early childhood environmental education for sustainable development. We aimed to identify the main drivers of sustainable lifestyles in the families of kindergarten children and evaluate the project’s effective practices. We utilized a qualitative approach using interviews with parents and feedback from teachers and employed the Following a Thread approach alongside inductive thematic analysis. The results highlight the crucial role of Finland’s socio-cultural context, including the emphasis on free play in natural settings and the encouragement of exploration under gentle guidance, in fostering sustainable behaviors among children. Additionally, the parents’ strong environmental sensitivity was manifested in their will to engage with their surrounding community to promote sustainability. The results underscore the importance of collaboration between parents and educators in promoting environmental awareness from an early age. The study advocates for policy changes to ensure that children and teachers have access to natural environments during day care, suggesting that integrating free play in nature with hands-on recycling activities can significantly contribute to sustainable education. Moreover, this topic should be further investigated in different living environments. Full article

 Educational institutions and educators are significant in children’s lives, and they have a crucial role in implementing policies, practices, and sexual education to enhance children’s safety. Such policies and practices should be based on the voices of CSA survivors. This study explored child sexual abuse (CSA) survivors’ viewpoints on their past experiences with educators and the educational system. A qualitative thematic approach was used to analyze 61 written testimonies collected in 2020–2021 by the Israeli Independent Public Inquiry on CSA. Two interrelated themes arose: 1) CSA survivors’ retrospective perspectives of educators and the educational system’s responses to signs of their CSA, described as ranging from abusive to life-saving. Specifically, they shared three types of responses: a) harmful and hurtful; b) dismissive and ignoring; and c) accepting and attending. 2) The second theme described the survivors’ messages to educators to promote constructive change. The survivors conveyed expectations that educators should play a central role in CSA prevention, detection, and intervention and, specifically, the need for educators to receive professional training, provide beneficial sexual education, and identify and respond to CSA. The findings promoted moving beyond individual-level interventions to focus on improving educational institutional and organizational cultures related to CSA in both national and international contexts. Full article

BRCA1 mutations predispose women to breast and ovarian cancer. The anticancer effect of zinc is typically linked to its antioxidant abilities and protecting cells against oxidative stress. Zinc regulates key processes in cancer development, including DNA repair, gene expression, and apoptosis. We took a blood sample from 989 female BRCA1 mutation carriers who were initially unaffected by cancer and followed them for a mean of 7.5 years thereafter. There were 172 incident cases of cancer, including 121 cases of breast cancer, 29 cases of ovarian cancers, and 22 cancers at other sites. A zinc level in the lowest tertile was associated with a modestly higher risk of ovarian cancer compared to women with zinc levels in the upper two tertiles (HR = 1.65; 95% CI 0.80 to 3.44; p = 0.18), but this was not significant. Among those women with zinc levels in the lowest tertile, the 10-year cumulative risk of ovarian cancer was 6.1%. Among those in the top two tertiles of zinc level, the ten-year cumulative risk of ovarian cancer was 4.7%. There was no significant association between zinc level and breast cancer risk. Our preliminary study does not support an association between serum zinc level and cancer risk in BRCA1 mutation carriers. Full article

Environmental contamination by heavy metals (HMs) has emerged as a significant global issue in recent decades. Among natural substances, food-deriving polyphenols have found a valuable application in chelating therapy, partially limited by their low water solubility. Thus, three different hydroalcoholic extracts titrated in quercetin (QE), ellagic acid (EA), and curcumin (CUR) were formulated using maltodextrins as carriers, achieving a powder with a valuable water solubility (MQE 91.3 ± 1.2%, MEA 93.4 ± 2.1, and MCUR 89.3 ± 2%). Overcoming the problem of water solubility, such formulations were tested in an in vitro simulated gastrointestinal digestion experiment conducted on a water sample with standardized concentrations of the principal HMs. Our results indicate that regarding the nonessential HMs investigated (Pb, Cd, As, Sb, and Hg), MQE has been shown to be the most effective in increasing the HMs’ non-bioaccessible concentration, resulting in concentration increases in Cd of 68.3%, in As of 51.9%, in Hg of 58.9%, in Pb of 271.4, and in Sb of 111.2% (vs control, p < 0.001) in non-bioaccessible fractions. Regarding the essential HMs, MEA has shown the greatest capability to increase their intestinal bioaccessibility, resulting in +68.5%, +61.1, and +22.3% (vs control, p < 0.001) increases in Cu, Zn, and Fe, respectively. Finally, considering the strong relation between the antiradical and chelating activities, the radical scavenging potentials of the formulations was assayed in DPPH and ABTS assays. Full article

Heat stress is one of the stressors that negatively affect broiler chickens, leading to a reduction in production efficiency and profitability. This reduction affects the economy in general, especially in hot and semi-hot countries. Therefore, improving heat tolerance of broiler chicks is a key to sustained peak performance, especially under adverse environmental heat stress conditions. The present study investigated three early feed withdrawal regimes (FWD) as a potential mitigation for thermal stress exposure. A total of 240 unsexed one-day-old Cobb-500 chicks were randomly recruited to one of four experimental groups using a completely randomized design (10 birds × 6 replicates). The experimental groups included the control group with no feed withdrawal (control), while the other three groups were subjected to early feed withdrawal for either 24 h on the 5th day of age (FWD-24), 12 h on the 3rd and 5th day of age (FWD-12), or 8 h on the 3rd, 4th, and 5th day of age (FWD-8), respectively. Production performance was monitored throughout the experiment. Meanwhile, blood and liver samples were taken at the end of the experimental period to evaluate major physiological dynamic changes. Our findings demonstrated that under chronic heat stress conditions, FWD treatments significantly improved broilers’ production performance and enhanced several physiological parameters compared with the control. Serum levels of thyroid hormones were elevated, whereas leptin hormone was decreased in FWD groups compared with the control. Moreover, serum total protein, globulin, and hemoglobin levels were higher, while total cholesterol and uric acid were lower in the FWD groups. Furthermore, FWD groups showed significantly higher antioxidant marker activity with a significantly lower lipid peroxidation level. Immunoglobulin levels, lysozyme, complement factor C3, and liver heat shock protein 70 (HSP70) concentration were also elevated in FWD compared with the control. Also, serum interleukin-1β (IL-1β) and interferon-gamma (IFN-γ) significantly increased with FWD. Based on our findings, early feed withdrawal can be applied as a promising non-invasive nutritional strategy for broilers reared under chronic heat stress conditions. Such a strategy promotes the alleviation of the deleterious effects of heat stress on broiler performance, immunity, and redox status, owing to the onset of physiological adaptation and the development of thermotolerance ability. Full article