Chemotherapy-induced cognitive impairment or “chemobrain” is a prevalent long-term complication of chemotherapy and one of the more devastating. Most of the studies performed so far to identify the cognitive dysfunctions induced by antineoplastic chemotherapies have been focused on treatment with anthracyclines, frequently administered to breast cancer patients, a population that, after treatment, shows a high possibility of long survival and, consequently, of chemobrain development. In the last few years, different possible strategies have been explored to prevent or reduce chemobrain induced by the anthracycline doxorubicin (DOX), known to promote oxidative stress and inflammation, which have been strongly implicated in the development of this brain dysfunction. Here, we have critically analyzed the results of the preclinical studies from the last few years that have evaluated the potential of phenolic compounds (PheCs), a large class of natural products able to exert powerful antioxidant and anti-inflammatory activities, in inhibiting DOX-induced chemobrain. Several PheCs belonging to different classes have been shown to be able to revert DOX-induced brain morphological damages and deficits associated with learning, memory, and exploratory behavior. We have analyzed the biological and molecular mechanisms implicated and suggested possible future perspectives in this research area. Full article

Respiratory malignancies, encompassing cancers affecting the lungs, the trachea, and the bronchi, pose a significant and dynamic public health challenge. Given that air pollution stands as a significant contributor to the onset of these ailments, discerning the most detrimental agents becomes imperative for crafting policies aimed at mitigating exposure. This study advocates for the utilization of explainable artificial intelligence (XAI) methodologies, leveraging remote sensing data, to ascertain the primary influencers on the prediction of standard mortality rates (SMRs) attributable to respiratory cancer across Italian provinces, utilizing both environmental and socioeconomic data. By scrutinizing thirteen distinct machine learning algorithms, we endeavor to pinpoint the most accurate model for categorizing Italian provinces as either above or below the national average SMR value for respiratory cancer. Furthermore, employing XAI techniques, we delineate the salient factors crucial in predicting the two classes of SMR. Through our machine learning scrutiny, we illuminate the environmental and socioeconomic factors pertinent to mortality in this disease category, thereby offering a roadmap for prioritizing interventions aimed at mitigating risk factors. Full article

Flowability greatly affects the application of ultrafine dry powder fire extinguishing systems, while hydrophobicity and acute inhalation toxicity are concerns for fire extinguishing agents. In the present study, we examined the impact of hydrophobic fumed silica on the hydrophobicity and flow properties of ammonium dihydrogen phosphate as the base. Our findings revealed that incorporating 6 wt.% of hydrophobic fumed silica resulted in optimal flowability, accompanied by a hydrophobicity angle of 126.48°. The excessive inclusion of hydrophobic fumed silica impeded powder flow within the ammonium dihydrogen phosphate particles. Furthermore, the investigations indicated that the incorporation of a small quantity of bentonite (0.5 wt.%) amongst the three functional additives—bentonite, magnesium stearate, and perlite—offered further enhancements in powder flowability. In fire extinguishing experiments’ total flooding conditions (1 m³), the designed UDPA exhibited a minimum required extinguishing concentration of merely 41.5 g/m³, which is better than the publicly reported value. Moreover, observations on the well-being of mice subjected to nearly three times the extinguishing concentration at 60 s, 10 min, and 3 days, respectively, demonstrated the absence of acute inhalation toxicity associated with the designed UDPA. Collectively, the developed ultrafine dry powder fire extinguishing agent displayed promising performance and possesses broad applicability. Full article

Single-chain polymeric nanoparticles (SCPNs) have been extensively explored as a synthetic alternative to enzymes for catalytic applications. However, the inherent structural heterogeneity of SCPNs, arising from the dispersity of the polymer backbone and stochastic incorporation of different monomers as well as catalytic moieties, is expected to lead to variations in catalytic activity between individual particles. To understand the effect of structural heterogeneities on the catalytic performance of SCPNs, techniques are required that permit researchers to directly monitor SCPN activity at the single-polymer level. In this study, we introduce the use of single-molecule fluorescence microscopy to study the kinetics of Cu(I)-containing SCPNs towards depropargylation reactions. We developed Cu(I)-containing SCPNs that exhibit fast kinetics towards depropargylation and Cu-catalyzed azide-alkyne click reactions, making them suitable for single-particle kinetic studies. SCPNs were then immobilized on the surface of glass coverslips and the catalytic reactions were monitored at a single-particle level using total internal reflection fluorescence (TIRF) microscopy. Our studies revealed the interparticle turnover dispersity for Cu(I)-catalyzed depropargylations. In the future, our approach can be extended to different polymer designs which can give insights into the intrinsic heterogeneity of SCPN catalysis and can further aid in the rational development of SCPN-based catalysts. Full article

The present meta-analysis summarizes brain activation for social cognition and emotion-processing tasks in borderline personality disorder (BPD). We carried out two meta-analyses to elaborate on commonalities and potential differences between the two types of tasks. In the first meta-analysis, we implemented a more liberal strategy for task selection (including social and emotional content). The results confirmed previously reported hyperactivations in patients with BPD in the bilateral amygdala and prefrontal cortex and hypoactivations in bilateral inferior frontal gyri. When applying a stricter approach to task selection, focusing narrowly on social cognition tasks, we only found activation in prefrontal areas, particularly in the anterior cingulate and ventromedial prefrontal cortex. We review the role of these areas in social cognition in healthy adults, suggesting that the observed BPD hyperactivations may reflect an overreliance on self-related thought in social cognition. Full article

Unmanned helicopters are always subject to various external disturbances and constraints when performing tasks. In this paper, an extended state observer-based command-filtered safe tracking control scheme is investigated for an unmanned helicopter under time-varying path constraints and disturbances. To restrict the position states within the real-time safe flight boundaries, a safe reference path is regulated using the safe protection algorithm. The ESO is utilized to handle the unknown external disturbances. Moreover, the command filter technique is combined with the backstepping approach and twice inverse solution for the nonlinear unmanned helicopter system. According to the Lyapunov stability analysis, the safety and the tracking performance of the helicopter can be proved, and the availability of the safe tracking controller can also be illustrated by numerical simulations. Full article

Background: It is unclear whether patients with basal ganglia calcifications (BGC) should undergo infectious disease testing as part of their diagnostic work-up. We investigated the occurrence of possibly associated infections in patients with BGC diagnosed with Fahr’s disease or syndrome and consecutively performed a systematic review of published infectious diseases associated with BGC. Methods: In a cross-sectional study, we evaluated infections in non-immunocompromised patients aged ≥ 18 years with BGC in the Netherlands, who were diagnosed with Fahr’s disease or syndrome after an extensive multidisciplinary diagnostic work-up. Pathogens that were assessed included the following: Brucella sp., cytomegalovirus, human herpesvirus type 6/8, human immunodeficiency virus (HIV), Mycobacterium tuberculosis, rubella virus, and Toxoplasma gondii. Next, a systematic review was performed using MEDLINE and Embase (2002–2023). Results: The cross-sectional study included 54 patients (median age 65 years). We did not observe any possible related infections to the BGC in this population. Prior infection with Toxoplasma gondii occurred in 28%, and in 94%, IgG rubella antibodies were present. The positive tests were considered to be incidental findings by the multidisciplinary team since these infections are only associated with BGC when congenitally contracted and all patients presented with adult-onset symptoms. The systematic search yielded 47 articles, including 24 narrative reviews/textbooks and 23 original studies (11 case series, 6 cross-sectional and 4 cohort studies, and 2 systematic reviews). Most studies reported congenital infections associated with BGC (cytomegalovirus, HIV, rubella virus, Zika virus). Only two studies reported acquired pathogens (chronic active Epstein–Barr virus and Mycobacterium tuberculosis). The quality of evidence was low. Conclusions: In our cross-sectional study and systematic review, we found no convincing evidence that acquired infections are causing BGC in adults. Therefore, we argue against routine testing for infections in non-immunocompromised adults with BGC in Western countries. Full article

Background: Mitochondria are the ‘powerhouses of cells’ and progressive mitochondrial dysfunction is a hallmark of aging in skeletal muscle. Although different forms of exercise modality appear to be beneficial to attenuate aging-induced mitochondrial dysfunction, it presupposes that the individual has a requisite level of mobility. Moreover, non-exercise alternatives (i.e., nutraceuticals or pharmacological agents) to improve skeletal muscle bioenergetics require time to be effective in the target tissue and have another limitation in that they act systemically and not locally where needed. Mitochondrial transplantation represents a novel directed therapy designed to enhance energy production of tissues impacted by defective mitochondria. To date, no studies have used mitochondrial transplantation as an intervention to attenuate aging-induced skeletal muscle mitochondrial dysfunction. The purpose of this investigation, therefore, was to determine whether mitochondrial transplantation can enhance skeletal muscle bioenergetics in an aging rodent model. We hypothesized that mitochondrial transplantation would result in sustained skeletal muscle bioenergetics leading to improved functional capacity. Methods: Fifteen female mice (24 months old) were randomized into two groups (placebo or mitochondrial transplantation). Isolated mitochondria from a donor mouse of the same sex and age were transplanted into the hindlimb muscles of recipient mice (quadriceps femoris, tibialis anterior, and gastrocnemius complex). Results: The results indicated significant increases (ranging between ~36% and ~65%) in basal cytochrome c oxidase and citrate synthase activity as well as ATP levels in mice receiving mitochondrial transplantation relative to the placebo. Moreover, there were significant increases (approx. two-fold) in protein expression of mitochondrial markers in both glycolytic and oxidative muscles. These enhancements in the muscle translated to significant improvements in exercise tolerance. Conclusions: This study provides initial evidence showing how mitochondrial transplantation can promote skeletal muscle bioenergetics in an aging rodent model. Full article

Diaspore dispersal is crucial in shaping plant population dynamics, biodiversity, and ecosystem functions. The effect of the vegetation structure on the secondary wind dispersal of diaspores with different appendage types is not well understood. Using a wind tunnel and a high-definition video camera, we accurately measured the lift-off and dispersal velocities of diaspores from sixteen plant species across six wind velocities (2, 4, 6, 8, 10, and 12 m s⁻¹) under six simulated vegetation structures. Vegetation structure and appendage type were pivotal factors, explaining 41.1% and 42.3% of the variance in lift-off velocity and accounting for 12.0% and 25.3% of the variability in diaspore dispersal velocity, respectively. Vegetation coverage was the main factor influencing near-surface wind velocity, and the lift-off and dispersal velocities of diaspores changed significantly when vegetation coverage exceeded 40%. Diaspores with one wing, having high lift-off velocities and low dispersal velocities, adopt the anti-long-distance wind dispersal strategy, whereas diaspores with pappus, having low lift-off velocities and high dispersal velocities, adopt the long-distance wind dispersal strategy. In contrast, diaspores with thorn, discoid, balloon, and four wings adopt the non-long-distance wind dispersal strategy, suitable for environments such as low-coverage deserts and desert steppes but not high-coverage typical steppes. This study could help comprehend the effect of the vegetation structure on the dispersal process of diaspores, which facilitate habitat restoration and biodiversity conservation of grassland and forest ecosystems. Full article

In recent years, there has been rapid advancement in new energy technologies aimed at mitigating greenhouse gas emissions stemming from fossil fuels. Nonetheless, uncertainties persist in both the power output of new energy sources and load. To effectively harness the economic and operational potential of an Integrated Energy System (IES), this paper introduces an enhanced uncertainty set. This set incorporates N-1 contingency considerations and the nuances of source–load distribution. This framework is applied to a robust optimization model for an Electric Vehicle Integrated Energy System (EV-IES), which includes Electric Vehicle Battery Swapping Station (EVBSS). Firstly, this paper establishes an IES model of the EVBSS, and then proceeds to classifies and schedules the large-scale battery groups within these stations. Secondly, this paper proposes an enhanced uncertainty set to account for the operational status of multiple units in the system. It also considers the output characteristics of both new energy sources and loads. Additionally, it takes into consideration the N-1 contingency state and multi-interval distribution characteristics. Subsequently, a multi-time-scale optimal scheduling model is established with the objective of minimizing the total cost of the IES. The day-ahead robust optimization fully considers the multivariate uncertainty of the IES. The solution employs the Nested Column and Constraint Generation (C&CG) algorithm, based on the distribution characteristics of multiple discrete variables in the model. The intraday optimal scheduling reallocates the power of each unit based on the robust optimization results from the day-ahead scheduling. Finally, the simulation results demonstrate that the proposed method effectively reduces the conservatism of the uncertainty set, ensuring economic and stable operation of the EV-IES while meeting the demands of electric vehicle users. Full article

Chilean mining faces challenges associated with the depletion of oxidized copper ore and the environmental complexity of treating concentrates with high arsenic content. Given this, hydrometallurgy emerges as an alternative for the treatment of these concentrates. This research analyzes the interaction of sulfuric acid (0, 70, 140, and 210 kg/t), sodium chloride (0, 25, 50, and 100 kg/t), curing time (1, 5, 10, and 15 days), and temperature (25, 35, 50, and 75 °C) in the pretreatment of a copper concentrate with 35.57% total copper and 5.91% arsenic (enargite, 35.93%). In the pretreatment, a maximum copper extraction of 26.71% is achieved using 210 kg/t sulfuric acid at 50 °C over 15 days of curing. The experimental results are analyzed through an empirical model, where the interaction between sulfuric acid and curing time is identified as beneficial when the sulfuric acid addition is above 70 kg/t, leading to higher moisture content in the sample. In the absence of sulfuric acid, sodium chloride significantly influences the achievement of higher copper extractions. During curing at higher temperatures, the importance of maintaining a moisture level is emphasized to prevent solution evaporation and hinder diffusion through the particles, thereby ensuring reactivity in the sample. Full article

We provide comparative studies of the structural, morphological, microstructural, and magnetic properties of MnFePSi-glass-coated microwires (MnFePSi-GCMWs) and bulk MnFePSi at different temperatures and magnetic fields. The structure of MnFePSi GCMWs prepared by the Taylor–Ulitovsky method consists of the main Fe₂P phase and secondary impurities phases of Mn₅Si₃ and Fe₃Si, as confirmed by XRD analysis. Additionally, a notable reduction in the average grain size from 24 µm for the bulk sample to 36 nm for the glass-coated microwire sample is observed. The analysis of magnetic properties of MnFePSi-glass-coated microwires shows different magnetic behavior as compared to the bulk MnFePSi. High coercivity (450 Oe) and remanence (0.32) are observed for MnFePSi-GCMWs compared to low coercivity and remanent magnetization observed for bulk MnFePSi alloy. In addition, large irreversibility at low temperatures is observed in the thermal dependence of magnetization of microwires. Meanwhile, the bulk sample shows regular ferromagnetic behavior, where the field cooling and field heating magnetic curves show a monotonic increase by decreasing the temperature. The notable separation between field cooling and field heating curves of MnFePSi-GCMWs is seen for the applied field at 1 kOe. Also, the M/M_5K vs. T for MNFePSi-GCMWs shows a notable sensitivity at a low magnetic field compared to a very noisy magnetic signal for bulk alloy. The common features for both MnFePSi samples are high Curie temperatures above 400 K. From the experimental results, we can deduce the substantial effect of drawing and quenching involved in the preparation of glass-coated MnFePSi microwires in modification of the microstructure and magnetic properties as compared to the same bulk alloy. The provided studies prove the suitability of the Taylor–Ulitovsky method for the preparation of MnFePSi-glass-coated microwires. Full article

This paper focuses on returns comovements in global stock portfolios including the US Dollar as a defensive asset. The main contribution is the selection of a large set of macroeconomic and financial variables as potential drivers of these comovements and the emphasis on the predictive accuracy of proposed econometric models. One-year US Expected Inflation stands out as the most important predictor, while models including a larger number of variables yield significant predictive gains. Larger forecast errors, due to parameters instabilities, are documented during major financial crises and the COVID-19 pandemic period. Some research directions to improve the forecasting power of econometric models are discussed in the concluding section. Full article

In current-generation designs of total primary hip joint replacement, the prostheses are fabricated from alloys. The modulus of elasticity of the alloy is substantially higher than that of the surrounding bone. This discrepancy plays a role in a phenomenon known as stress shielding, in which the bone bears a reduced proportion of the applied load. Stress shielding has been implicated in aseptic loosening of the implant which, in turn, results in reduction in the in vivo life of the implant. Rigid implants shield surrounding bone from mechanical loading, and the reduction in skeletal stress necessary to maintain bone mass and density results in accelerated bone loss, the forerunner to implant loosening. Femoral stems of various geometries and surface modifications, materials and material distributions, and porous structures have been investigated to achieve mechanical properties of stems closer to those of bone to mitigate stress shielding. For improved load transfer from implant to femur, the proposed study investigated a strategic debulking effort to impart controlled flexibility while retaining sufficient strength and endurance properties. Using an iterative design process, debulked configurations based on an internal skeletal truss framework were evaluated using finite element analysis. The implant models analyzed were solid; hollow, with a proximal hollowed stem; FB-2A, with thin, curved trusses extending from the central spine; and FB-3B and FB-3C, with thick, flat trusses extending from the central spine in a balanced-truss and a hemi-truss configuration, respectively. As outlined in the International Organization for Standardization (ISO) 7206 standards, implants were offset in natural femur for evaluation of load distribution or potted in testing cylinders for fatigue testing. The commonality across all debulked designs was the minimization of proximal stress shielding compared to conventional solid implants. Stem topography can influence performance, and the truss implants with or without the calcar collar were evaluated. Load sharing was equally effective irrespective of the collar; however, the collar was critical to reducing the stresses in the implant. Whether bonded directly to bone or cemented in the femur, the truss stem was effective at limiting stress shielding. However, a localized increase in maximum principal stress at the proximal lateral junction could adversely affect cement integrity. The controlled accommodation of deformation of the implant wall contributes to the load sharing capability of the truss implant, and for a superior biomechanical performance, the collared stem should be implanted in interference fit. Considering the results of all implant designs, the truss implant model FB-3C was the best model. Full article

The work presents a tool enabling the selection of powder for 3D printing. The project focused on three types of powders, such as steel, nickel- and cobalt-based and aluminum-based. An important aspect during the research was the possibility of obtaining the mechanical parameters. During the work, the possibility of using the selected algorithm based on artificial intelligence like Random Forest, Decision Tree, K-Nearest Neighbors, Fuzzy K-Nearest Neighbors, Gradient Boosting, XGBoost, AdaBoost was also checked. During the work, tests were carried out to check which algorithm would be best for use in the decision support system being developed. Cross-validation was used, as well as hyperparameter tuning using different evaluation sets. In both cases, the best model turned out to be Random Forest, whose F1 metric score is 98.66% for cross-validation and 99.10% after tuning on the test set. This model can be considered the most promising in solving this problem. The first result is a more accurate estimate of how the model will behave for new data, while the second model talks about possible improvement after optimization or possible overtraining to the parameters. Full article

High-flow nasal cannula (HFNC) is becoming the gold standard to treat respiratory distress at any age since it potentially provides several significant clinical advantages. An obstacle to the diffusion of this simple and effective system of oxygen therapy is the impossibility to know the optimal flow rate leading to such advantages that allows the reduction in the respiratory effort without causing hyperinflation. To assist clinicians during HFNC treatment in setting the optimal flow rate and in determining the most relevant parameters related to respiratory mechanics and the effort of the patient, we developed a new programmable data monitoring, acquisition, and elaborating system (Pro_HFNC). The application of Pro_HFNC is fully compatible with HFNC as it is interfaced with patient through a facial mask and two specific catheters. The unavoidable and unpredictable loss of air flow occurring around the contour of the mask is evaluated and compensated by a specific algorithm implemented by Pro_HFNC. Our preliminary clinical trials on pediatric patients treated with HFNC show that Pro_HFNC is actually capable to detect for any specific patient both the lower threshold of the delivered flow beyond which the benefits of HFNC application are reached and all the parameters useful for a complete evaluation of the respiratory profile. Pro_HFNC can really help physicians in setting the optimal flow rate during HFNC treatment, thus allowing for the most effective HFNC performance. Full article

A UAV-assisted space–air–ground integrated network (SAGIN) can provide communication services for remote areas and disaster-stricken regions. However, the increasing types and numbers of ground terminals (GTs) have led to the explosive growth of communication data volume, which is far from meeting the communication needs of ground users. We propose a mobile edge network model that consists of three tiers: satellites, UAVs, and GTs. In this model, UAVs and satellites deploy edge servers to deliver services to GTs. GTs with limited computing capabilities can upload computation tasks to UAVs or satellites for processing. Specifically, we optimize association control, bandwidth allocation, computation task allocation, caching decisions, and the UAV’s position to minimize task latency. However, the proposed joint optimization problem is complex, and it is difficult to solve. Hence, we utilize Block Coordinate Descent (BCD) and introduce auxiliary variables to decompose the original problem into different subproblems. These subproblems are then solved using the McCormick envelope theory, the Successive Convex Approximation (SCA) method, and convex optimization techniques. The simulation results extensively illustrate that the proposed solution dramatically decreases the overall latency when compared with alternative benchmark schemes. Full article

This study aimed to examine the effects of capital structure on the financial performance of Ethiopian commercial banks. The dependent variable, financial performance, is measured by Return on Assets (ROA), while factors such as loan-to-deposit ratio (LDR), asset-to-total equity ratio (ATER), total deposit-to-total asset ratio (TDTAR), capital adequacy ratio (CAD), and asset growth ratio (GA) were used as proxy independent variables to gauge capital structure. Using a quantitative approach and an explanatory research design, this study analyzes 6 years of audited financial reports from 14 commercial banks in Ethiopia. This investigation employs a random effect regression model and Stata 14 software package to explore the relationships among these variables. The result revealed that both the loan-to-deposit ratio and the total deposit-to-total asset ratio have a positive and significant impact on financial performance, while the asset growth ratio showed a negative effect. Based on these findings, this study recommends that bank authorities concentrate on bolstering their deposit base, managing asset growth efficiently, maintaining adequate capital levels, and optimizing leverage levels to improve financial performance and ensure long-term sustainability in the banking sector. Additionally, this research is anticipated to inform policymakers about regulatory frameworks for banks and assist banking managers in formulating effective capital financing strategies within the Ethiopian commercial banking sector, thus enriching the existing literature on the relationship between capital structure and financial performance. Full article

Straw return is one of the main methods for protecting black soil. Efficient and accurate straw return detection is important for the sustainability of conservation tillage. In this study, a rapid straw return detection method is proposed for large areas. An optimized Sh-DeepLabv3+ model based on the aforementioned detection method and the characteristics of straw return in Jilin Province was then used to classify plots into different straw return cover types. The model used Mobilenetv2 as the backbone network to reduce the number of model parameters, and the channel-wise feature pyramid module based on channel attention (CA-CFP) and a low-level feature fusion module (LLFF) were used to enhance the segmentation of the plot details. In addition, a composite loss function was used to solve the problem of class imbalance in the dataset. The results show that the extraction accuracy is optimal when a 2048 × 2048-pixel scale image is used as the model input. The total parameters of the improved model are 3.79 M, and the mean intersection over union (MIoU) is 96.22%, which is better than other comparative models. After conducting a calculation of the form–grade mapping relationship, the error value of the area prediction was found to be less than 8%. The results show that the proposed rapid straw return detection method based on Sh-DeepLabv3+ can provide greater support for straw return detection. Full article

The biosynthesis of silver nanoparticles (AgNPs) using plant extracts has become a safe replacement for conventional chemical synthesis methods to fight plant pathogens. In this study, the antifungal activity of biosynthesized AgNPs was evaluated both in vitro and under greenhouse conditions against root rot fungi of common beans (Phaseolus vulgaris L.), including Macrophomina phaseolina, Pythium graminicola, Rhizoctonia solani, and Sclerotium rolfsii. Among the eleven biosynthesized AgNPs, those synthesized using Alhagi graecorum plant extract displayed the highest efficacy in suppressing those fungi. The findings showed that using AgNPs made with A. graecorum at a concentration of 100 μg/mL greatly slowed down the growth of mycelium for R. solani, P. graminicola, S. rolfsii, and M. phaseolina by 92.60%, 94.44%, 75.93%, and 79.63%, respectively. Additionally, the minimum inhibitory concentration (75 μg/mL) of AgNPs synthesized by A. graecorum was very effective against all of these fungi, lowering the pre-emergence damping-off, post-emergence damping-off, and disease percent and severity in vitro and greenhouse conditions. Additionally, the treatment with AgNPs led to increased root length, shoot length, fresh weight, dry weight, and vigor index of bean seedlings compared to the control group. The synthesis of nanoparticles using A. graecorum was confirmed using various physicochemical techniques, including UV spectroscopy, Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) analysis. Collectively, the findings of this study highlight the potential of AgNPs as an effective and environmentally sustainable approach for controlling root rot fungi in beans. Full article

School violence remains a major concern for scholars, policymakers, and the public in the United States. Despite the implementation of various school violence prevention programs, information regarding their effectiveness in the United States is outdated and limited. This systematic review identified current elementary school programs that effectively reduce school violence in the United States and determined the types of elementary school violence prevention programs implemented, their effectiveness, and the types of tools used to enhance such programs. A qualitative methodological approach was employed, and four databases were searched. English articles published between 2012 and 2023 were selected. Furthermore, data involving elementary school education, school personnel, teachers, and children (5–12-year-old) in the United States were included in the thematic analysis. Results confirmed that the school-wide Positive Behavior Interventions and Supports program effectively decreases violence, suspensions, office referrals, and disruptive behaviors, whereas positive action effectively reduces negative violent behaviors. Social–emotional learning (SEL) implementation also reduced behavioral issues. The findings of this study are relevant for guiding teachers, school administrators, policymakers, teacher education preparation programs, and health professionals in constructing evidence-based violence prevention programs with an added SEL component for elementary schools. Full article

Despite the profession placing great emphasis on oral potentially malignant disorders (OPMDs) as a gateway for early recognition and consequently better outcomes for oral cancer, the death rates for lip and oral cavity cancer have remained stagnant for three decades. Evidence shows that only a small fraction of oral cancers are in fact preceded by OPMDs, and that most OPMDs have an annual transformation rate of less than 1%. As OPMDs encompass a very heterogeneous group of oral conditions, it could be argued that only patients with oral mucosal diseases bearing a substantial risk of malignant transformation warrant close surveillance and treatment, these include proliferative leukoplakia, erythroplakia, non-homogeneous leukoplakia, as well as diseases presenting with severe dysplasia at biopsy. In this narrative review, I discuss the intricate epidemiology of the malignancies that we colloquially refer to as oral cancer, explore the limitations of focusing on OPMDs to reduce the incidence and mortality of oral cavity cancer, and argue that a may-be cancer label represents overdiagnosis for most OPMDs. Full article