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OBJECTIVE: Carpal Tunnel Syndrome (CTS) is a prevalent neuropathy where accurate diagnosis is crucial for effective treatment planning. This study introduces a novel approach for CTS grading using ultrasound, specifically through the analysis of the cross-sectional area (CSA) and shear wave elastography (SWE) of the median nerve in various wrist positions. METHODS: Our research involved subjects from outpatient clinics, diagnosed with CTS through Nerve Conduction Studies (NCS), and a control group of healthy individuals. High-frequency ultrasound and SWE measurements were conducted in three wrist positions: straight, 45° extension, and 45° flexion. RESULTS: The key findings revealed significant differences in median nerve CSA and SWE values between the CTS and control groups across all wrist positions, with notable variances in SWE values correlating with wrist positioning. SWE demonstrated enhanced sensitivity and specificity in distinguishing between mild, moderate, and severe CTS, especially at 45° wrist flexion. In contrast, CSA measurements were limited in differentiating between the varying severity stages of CTS. CONCLUSIONS: The study concludes that SWE, particularly at 45° wrist flexion, provides a more precise diagnostic benchmark for CTS severity grading than CSA. This advancement in non-invasive diagnostic methodology not only aids in accurate CTS grading but also has significant implications in formulating tailored treatment strategies, potentially reducing the reliance on more invasive diagnostic methods like NCS. ADVANCEMENT IN KNOWLEDGE: This study marks a significant advancement in the ultrasound diagnosis of CTS. It particularly highlights the importance of applying SWE technology across various wrist joint angles, offering a new diagnostic benchmark. This discovery provides data support and additional insights for achieving an early consensus on ultrasound-based grading diagnosis of CTS.

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It is widely predicted that climate change's adverse effects will intensify in the future, and along with inadequate agricultural practices, settlement development, and other anthropic activities, could contribute to rapid wetland degradation and thus exert significant negative effects on local communities. This study sought to develop an approach based on the Integrated Water Resource Management (IWRM) in the Ruzizi Plain, eastern Democratic Republic of Congo (DRC), where adverse effects of the climate change are increasingly recurrent. Initially, we analyzed the trends of climate data for the last three decades (1990-2022). Subsequently, the Water Evaluation and Planning (WEAP) approach was employed on two contrasting watersheds to estimate current and future water demands in the region and how local wetlands could serve as reservoirs to meeting water demands. Results indicate that the Ruzizi Plain is facing escalating water challenges owing to climate change, rapid population growth, and evolving land-use patterns. These factors are expected to affect water quality and quantity, and thus, increase pressure on wetland ecosystems. The analysis of past data shows recurrence of dry years (SPI ≤ - 1.5), reduced daily low-intensity rainfall (Pmm < 10 mm), and a significant increase in extreme rainfall events (Pmm ≥ 25 mm). The WEAP outcomes revealed significant variations in future water availability, demand, and potential stressors across watersheds. Cropland and livestock are the main water consumers in rural wetlands, while households, cropland (at a lesser extent), and other urban uses exert significant water demands on wetlands located in urban environments. Of three test scenarios, the one presenting wetlands as water reservoirs seemed promising than those considered optimal (based on policies regulating water use) and rational (stationary inputs but with a decrease in daily allocation). These findings highlight the impact of climate change in the Ruzizi plain, emphasizing the urgency of implementing adaptive measures. This study advocates for the necessity of the IWRM approach to enhance water resilience, fostering sustainable development and wetland preservation under changing climate.

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Socio-cultural contexts are formative to how teachers understand, conceptualize, and act when contending with child sexual abuse (CSA) cases among their students. The purpose of the present study was to investigate the experiences of Druze Arab teachers in Israel coping with cases of CSA among their students and the meaning they attribute to CSA in the context of socio-cultural change. Semi-structured interviews were conducted with 12 female Druze elementary school teachers. All of the participants taught in schools located in Druze villages, where the children of Druze families comprise the majority of the student body. The analysis used a thematic approach. The analysis revealed that a transition between tradition and modernity in the Druze socio-cultural group was the central conceptual framework through which the teachers' narratives regarding CSA emerged. As an emblem of modernity, increasing openness around sexual topics was perceived as simultaneously favorable and threatening to both the welfare of children and the well-being of the community. Coping with CSA was viewed as a negotiation between closed (traditional) and open (modern) society, as well as silence and dialogue regarding CSA. This study highlights the importance of preventing teachers' cultural biases from affecting their contributions to CSA interventions, as well as how religion can be a source of strength when confronting CSA. Implications for policy and developing bottom-up, culturally sensitive training, practice, and interventions are discussed.

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BACKGROUND: The aim of this study was to evaluate the interobserver reliability of measurements of the Acromiohumeral Distance (AHD) first described by Golding et al., the Critical Shoulder Angle (CSA), the Acromion Index with Glenoid Humeral (GH) and Glenoid Acromial (GA) distances, following the measuring method by Nyffeler et al., the Lateral Acromion Angle (LAA), as well as the morphology of the acromion according to Bigliani and the humeral head position according to Maloney in X-rays and MRI. Furthermore, the study assessed the correlation of measurement results in X-ray with those in MRI for AHD, CSA, GA, GH, AI, and LAA. METHODS: A total of 187 patients who underwent shoulder joint X-ray and MRI examinations from 09/2016 to 05/2023 were included in the study. Patients with poor imaging quality, arthrosis or radical prior surgeries, like shoulder prosthetic surgery, status post humerus fractures, that have undergone surgery and therefore changed the anatomical features were excluded, what lead to a total study population of 78. X-ray measurements were performed by two observers in the true anteroposterior view, so that the humeral head and the glenoid are shown without overlap, providing a clear view into the joint space. MRI measurements were performed in oblique coronal MRI slices, using the most accurately depicted glenoid surface as a landmark. RESULTS: Interobserver measurement results showed a significance with p < 0.001 for the assessment of acromion type according to Bigliani, humeral head offset assessment according to Maloney, and AHD. No significance was found for interobserver reliability in measuring LAA. Additionally, there was a high correlation of measurement results in X-ray with measurements in MRI for, CSA, GH/GA, and consequently AI, a good correlation for AHD but no correlation could be shown for LAA. CONCLUSIONS: These findings provide valuable insights into the robustness of radiological parameters for evaluating shoulder pathology, offering promising prospects for clinical applications and further research. Nevertheless, the specific methodological considerations and patient characteristics should be taken into account when interpreting the results to ensure their accurate application in clinical practice.

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Background: Climate change poses a significant threat to agricultural production worldwide, with developing countries being particularly vulnerable to its negative impacts. Agriculture, which is a crucial factor in ensuring food security and livelihoods, is particularly vulnerable to changes in climate patterns, such as increased temperatures, drought, and extreme weather events. One approach to addressing these challenges is by promoting the adoption of climate-smart agriculture (CSA) practices among farmers. CSA combines traditional agricultural practices with innovative techniques and technologies to adapt to and mitigate the impacts of climate change. infrastructure. By adopting CSA practices, farmers can enhance their resilience to climate variability and improve their productivity. Objectives: This review examines the effectiveness of interventions promoting CSA to enhance farmers' knowledge of the benefits of CSA approaches, subsequent adoption of CSA, and disadoption of harmful agricultural practices in low- and middle-income countries (LMICs). Search Methods: We searched 39 academic and online databases, websites, and repositories and screened over 19,000 experimental and quasi-experimental publications to identify studies promoting CSA practices to women farmers. We conducted a citation tracking process on included studies and contacted experts to ensure a thorough search. Selection Criteria: The review focused on studies that included interventions promoting climate-smart agricultural approaches. Using EPPI Reviewer 4, two review authors independently screened the impact evaluation using a standardized screening tool. Data Collection and Analysis: Information about participant characteristics, intervention characteristics, control conditions, research design, sample size, bias risk, outcomes, and results were gathered. Data collection and quantitative analysis were conducted using standard Campbell Collaboration methods. Main Results: Eight impact evaluations were found (two randomized controlled trials) evaluating the effects of CSA practices on farmer's knowledge gains of the benefits of CSA practices and subsequent adoption. Knowledge dissemination approaches such as Farmer Field Schools and weather and climate information services were found to positively impact farmers' knowledge and adoption of specific CSA practices. However, the evidence supporting this claim is uncertain as a high risk of bias was assessed for five of the eight included studies. However, we found no effects on the disadoption of harmful practices such as pesticide overuse. Authors' Conclusions: The evidence base for studies promoting climate-smart agricultural approaches (CSA) to farmers in LMICs is small, and there is a lack of studies reporting sex-disaggregated data and studies explicitly targeting women farmers. The review suggests that knowledge dissemination techniques are significantly effective in improving CSA knowledge and adoption, including integrated pest management techniques and their benefits, adoption of climate-resilient rice seed varieties (STRVs), and use of botanical pesticides by farmers. More and better confidence studies are needed to inform policy and programming, including those that look at a wider range of interventions, including changing norms, values, and institutional arrangements.

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A Model mesogen and its symmetrical Dimer made up of phenyl benzoate core unit are investigated by 13C NMR spectroscopy. The existence of layer order in smectic A and smectic C phases of Dimer mesogen is established by powder X-ray diffraction. The chemical shift anisotropy (CSA) tensors of Model mesogen are determined by 2D separation of undistorted powder patterns by effortless recoupling (SUPER) experiment and are utilized for calculating the order parameters employing the alignment-induced chemical shifts (AIS). Additionally, 2D separated local field (SLF) NMR is availed for extracting 13C-1H dipolar couplings for both mesogens and used for computing the order parameters. A good agreement in the order parameters calculated from 13C-1H dipolar couplings and AIS is observed. Accordingly, the main order parameter (Szz) for the phenyl rings of the Model mesogen is found to be in the range 0.54 - 0.82, and for the Dimer mesogen, the values span 0.64 - 0.82 across mesophases. Since the phenyl benzoate core unit is frequently employed structural moiety for constructing the main chain as well as side chain liquid crystalline polymers and liquid crystalline elastomers, the CSA tensors reported here will be of immense utility for the structural characterization of these materials.

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The objective of this work was to investigate myonuclear permanence and transcriptional regulation as mechanisms for cellular muscle memory after strength training in humans. Twelve untrained men and women performed 10 weeks of unilateral elbow-flexor strength training followed by 16 weeks of de-training. Thereafter, 10 weeks' re-training was conducted with both arms: the previously trained arm and the contralateral untrained control arm. Muscle biopsies were taken from the trained arm before and after both training periods and from the control arm before and after re-training. Muscle biopsies were analysed for fibre cross-sectional area (fCSA), myonuclei and global transcriptomics (RNA sequencing). During the first training period, myonuclei increased in type 1 (13 ± 17%) and type 2 (33 ± 23%) fibres together with a 30 ± 43% non-significant increase in mixed fibre fCSA (P = 0.069). Following de-training, fCSA decreased in both fibre types, whereas myonuclei were maintained, resulting in 33% higher myonuclear number in previously trained vs. control muscle in type 2 fibres. Furthermore, in the previously trained muscle, three differentially expressed genes (DEGs; EGR1, MYL5 and COL1A1) were observed. Following re-training, the previously trained muscle showed larger type 2 fCSA compared to the control (P = 0.035). However, delta change in type 2 fCSA was not different between muscles. Gene expression was more dramatically changed in the control arm (1338 DEGs) than in the previously trained arm (822 DEGs). The sustained higher number of myonuclei in the previously trained muscle confirms myonuclear accretion and permanence in humans. Nevertheless, because of the unclear effect on the subsequent hypertrophy with re-training, the physiological benefit remains to be determined. KEY POINTS: Muscle memory is a cellular mechanism that describes the capacity of skeletal muscle fibres to respond differently to training stimuli if the stimuli have been previously encountered. This study overcomes past methodological limitations related to the choice of muscles and analytical procedures. We show that myonuclear number is increased after strength training and maintained during de-training. Increased myonuclear number and differentially expressed genes related to muscle performance and development in the previously trained muscle did not translate into a clearly superior responses during re-training. Because of the unclear effect on the subsequent hypertrophy and muscle strength gain with re-training, the physiological benefit remains to be determined.

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BACKGROUND: Different prophylactic protocols are available for preventing graft-versus-host disease (GVHD) after matched sibling donor (MSD) allogeneic hematopoietic cell transplantation (allo-HCT). This study aimed to compare the effectiveness of post-transplantation cyclophosphamide plus cyclosporine A (PT-CY/CSA) versus methotrexate plus CSA (MTX/CSA) as GVHD prophylaxis protocols in adult acute myeloid leukemia (AML) patients who received peripheral blood stem cells (PBSC) from fully matched donors. METHODS: The 1-year outcomes of 89 patients treated with PT-CY/CSA and 90 patients treated with MTX/CSA who had MSD allo-HCT for AML using unmanipulated mobilized PBSC were examined and compared. RESULTS: The cumulative incidence of acute GVHD at 100 days was considerably lower in the PT-CY/CSA group (4% vs 19.3%, p = 0.002), however there were no statistically significant difference in the cumulative incidence of chronic GVHD at 1-year (19.6% vs 37.4%, p = 0.053). Significant delays in neutrophil and platelet engraftments were reported in the PT-CY/CSA group (17 vs 12 days) and (13 vs 12 days), respectively (p < 0.001). The cumulative incidences of relapse (19.1% vs 13.7%, p = 0.470), overall survival (79.1% vs 77.3%, p = 0.986), non-relapse mortality (16.5% vs 16.8%, p = 0.837), and the GVHD and relapse-free survival (GRFS) (53.7% vs 46.6%, p = 0.478) did not differ statistically at 1-year. CONCLUSION: PT-CY/CSA demonstrated a significant decrease in the rate of acute GVHD. However, it was associated with engraftment delay.

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The dynamics of the backbone and side-chains of protein are routinely studied by interpreting experimentally determined 15N spin relaxation rates. R1(15N), the longitudinal relaxation rate, reports on fast motions and encodes, together with the transverse relaxation R2, structural information about the shape of the molecule and the orientation of the amide bond vectors in the internal diffusion frame. Determining error-free 15N longitudinal relaxation rates remains a challenge for small, disordered, and medium-sized proteins. Here, we show that mono-exponential fitting is sufficient, with no statistical preference for bi-exponential fitting up to 800 MHz. A detailed comparison of the TROSY and HSQC techniques at medium and high fields showed no statistically significant differences. The least error-prone DD/CSA interference removal technique is the selective inversion of amide signals while avoiding water resonance. The exchange of amide with solvent deuterons appears to affect the rate R1 of solvent-exposed amides in all fields tested and in each DD/CSA interference removal technique in a statistically significant manner. In summary, the most accurate R1(15N) rates in proteins are achieved by selective amide inversion, without the addition of D2O. Importantly, at high magnetic fields stronger than 800 MHz, when non-mono-exponential decay is involved, it is advisable to consider elimination of the shortest delays (typically up to 0.32 s) or bi-exponential fitting.

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Radar signal intra-pulse modulation recognition can be addressed with convolutional neural networks (CNNs) and time-frequency images (TFIs). However, current CNNs have high computational complexity and do not perform well in low-signal-to-noise ratio (SNR) scenarios. In this paper, we propose a lightweight CNN known as the cross-scale aware network (CSANet) to recognize intra-pulse modulation based on three types of TFIs. The cross-scale aware (CSA) module, designed as a residual and parallel architecture, comprises a depthwise dilated convolution group (DDConv Group), a cross-channel interaction (CCI) mechanism, and spatial information focus (SIF). DDConv Group produces multiple-scale features with a dynamic receptive field, CCI fuses the features and mitigates noise in multiple channels, and SIF is aware of the cross-scale details of TFI structures. Furthermore, we develop a novel time-frequency fusion (TFF) feature based on three types of TFIs by employing image preprocessing techniques, i.e., adaptive binarization, morphological processing, and feature fusion. Experiments demonstrate that CSANet achieves higher accuracy with our TFF compared to other TFIs. Meanwhile, CSANet outperforms cutting-edge networks across twelve radar signal datasets, providing an efficient solution for high-precision recognition in low-SNR scenarios.

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Background: Low back pain (LBP) is the most frequent indication to magnetic resonance imaging (MRI) examinations of the lumbosacral spine. The individual role of soft tissues, including muscles, on LBP is not fully understood and the contribution of each MRI-derived parameter of soft tissues status on the intensity of LBP has not been investigated in detail. Methods: The study design was observational retrospective, single center carried out at a University Hospital. Images were acquired using a using a 1.5 Tesla scanner. Patients completed a symptom questionnaire and rated their pain intensity using the Visual Analogue Scale (VAS). The VAS scores ​​were categorized as mild, moderate, and severe using cutoff values of 3.8 and 5.7, based on the literature. Biometric data, including weight and height, were also recorded to calculate the body mass index (BMI). The ratios between intramuscular fat infiltration and net muscle area were also calculated. Patient sample included 94 patients with LBP underwent MRI of the lumbosacral spine. Results: The stepwise analysis revealed that increasing psoas net area was associated with lower VAS levels (odds ratio [OR]: 0.94: 95% confidence interval [CI]: 0.90-0.98; p=.005), and an increase of one square centimeter of total psoas area resulted in a greater probability of reporting a mild (+1.21%; 95% CI: 0.37, 2.05%) or a moderate VAS (+0.40%; 95% CI: -0.02, 0.82%), Furthermore, a more severe VAS was associated with a higher BMI (OR: 1.13; 95% CI: 1.00-1.27). Conclusion: Our study demonstrates a relationship between LBP and MRI parameters of paravertebral and psoas muscles status. The psoas muscle is extremely important for spine stabilization and is linked to clinical symptoms of patients affected by LBP. These findings could contribute to future studies and improve treatment options in patients with LBP, possibly reducing the impact on disability, quality of life and socioeconomical burden.

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In North Bihar (NB), the conventional rice-wheat cropping system has led to soil, water, and environmental degradation, alongside low profitability, threatening sustainability. To address these concerns, a thorough field research was conducted over the course of three years to assess different methods of tillage and crop establishment in a rice, wheat, and greengram cycle. The experiment involved five scenarios with different combinations of crop rotation, tillage techniques, seeding procedures, fertilizer use, and irrigation strategies. Uncertainty analysis showed no significant change in mean and variance estimation among seven scenario replications at 5% significance level. Compared to traditional farming (SN-1), managing DSR-rice (SN-5) increased profitability by 17.56%, improved energy use efficiency (EUE) by 32.16%, and reduced irrigation by 24.76% and global warming potential (GWP) by 23.46%. Similarly, substituting zero tillage wheat (ZTW) SN-5 resulted in comparable profitability gains (18.25%) and significant improvements in irrigation (10 %), EUE (+48.65%), and GWP (-20 %) compared to SN-1. Green gram ZT also showed increased profitability (17.35%), with notable improvements in EUE (+38.31%) and GWP (-12.92%) compared to SN-1. Principal component and correlation analyses revealed relationships between total energy inputs, yields, economic returns, and sustainability indices, highlighting the benefits of crop rotation and tillage practices in optimizing resource use. The study suggests that compared to conventional systems, significant improvements in productivity, profitability, energy-use efficiency, and environmental mitigation can be achieved with Crop Rotation and Tillage Operations techniques.

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Background: In low- and middle-income nations, a significant proportion of maternal and infant deaths are caused by a short birth interval (SBI). In Ethiopia, it is the main factor contributing to maternal and infant mortality. Understanding the spatial distribution of SBIs, i.e., birth intervals of less than 33 months, and the factors that influence them is important for categorizing and promoting targeted interventions. This study used a geographically weighted regression model to evaluate the factors associated with SBIs in hot areas of Ethiopia. Methods: The 2019 Ethiopian Mini Demographic and Health Survey, which is nationally representative, provided the data for this study. The first step in the two-stage cluster design used to collect the data was enumeration areas, and the second stage was households. The survey was conducted between 21 March 2019 and 28 June 2019. A hot spot analysis (local Getis-Ord Gi* statistics) was initially used to investigate spatial variation in SBIs. Geographically weighted regression was used to examine the regional variation in the relationship between SBIs and the factors that cause them. Result: The study indicated that the overall proportion of SBIs among women in Ethiopia was 43.2%. The values for Global Moran's I (Moran's I = 0.773 and p < 0.001) showed the presence of significant SBIs clustering in Ethiopian administrative zones in Ethiopia. High-risk areas of the SBIs include Jarar, Doolo, Shabelle, Afder, Liben, Korahe, Nogob, West Harerge, Guji, Sidama, and Assosa zones. Conclusion: Living in a geographic region with a high proportion of uneducated women, women lacking breastfeeding practices, and followers of Orthodox religions increased the proportion of SBIs. Our full map of hot spots for short birth spacing and the factors that affect them helps in the implementation of precise public health measures for decision-makers.

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Using waste materials as replacements for sand in building materials helps reduce waste and improve the properties and sustainability of the construction materials. Authors proved the possibility of using imperial smelting furnace (ISF) slag granules as a 100% substitute for natural sand in self-compacting (SCC) cement-based mortars of calcium sulfoaluminates (CSA). The study proved that ISF slag's radioactive properties meet this area's requirements. CSA cement eliminates the noted problem in the case of concrete with Portland cement, which is the extended setting of the cement binder. The research findings indicate that using slag to replace sand up to 100% in mortars without grains smaller than 0.125 mm allows high flowability, compaction, low porosity and mechanical parameters. The compressive strength of the CSA cement mortars was about 110 MPa, and more than 140 MPa for geopolymer mortar. Unfortunately, the alkaline pH of a geopolymer causes high leachability of barium and sodium. Thus, the CSA cement is in a more favourable binder to achieve high strength, is environmentally friendly, and is a self-compacting mortar or concrete.

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Cyclophilin A (CypA), the cellular receptor of the immunosuppressant cyclosporin A (CsA), is an abundant cytosolic protein and is involved in a variety of diseases. For example, CypA supports cancer proliferation and mediates viral infections, such as the human immunodeficiency virus 1 (HIV-1). Here, we present the design of PROTAC (proteolysis targeting chimera) compounds against CypA to induce its intracellular proteolysis and to investigate their effect on immune cells. Interestingly, upon connecting to E3 ligase ligands, both peptide-based low-affinity binders and CsA-based high-affinity binders can degrade CypA at nM concentration in HeLa cells and fibroblast cells. As the immunosuppressive effect of CsA is not directly associated with the binding of CsA to CypA but the inhibition of phosphatase calcineurin by the CypA:CsA complex, we investigated whether a CsA-based PROTAC compound could induce CypA degradation without affecting the activation of immune cells. P3, the most efficient PROTAC compound discovered from this study, could deplete CypA in lymphocytes without affecting cell proliferation and cytokine production. This work demonstrates the feasibility of the PROTAC approach in depleting the abundant cellular protein CypA at low drug dosage without affecting immune cells, allowing us to investigate the potential therapeutic effects associated with the endogenous protein in the future.

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To enhance fault detection in slewing bearing vibration signals, an advanced noise-reduction model, HRCSA-VMD-WT, is designed for effective signal noise elimination. This model innovates by refining the Chameleon Swarm Algorithm (CSA) into a more potent Hybrid Reinforcement CSA (HRCSA), incorporating strategies from Chaotic Reverse Learning (CRL), the Whale Optimization Algorithm's (WOA) bubble-net hunting, and the greedy strategy with the Cauchy mutation to diversify the initial population, accelerate convergence, and prevent local optimum entrapment. Furthermore, by optimizing Variate Mode Decomposition (VMD) input parameters with HRCSA, Intrinsic Mode Function (IMF) components are extracted and categorized into noisy and pure signals using cosine similarity. Subsequently, the Wavelet Threshold (WT) denoising targets the noisy IMFs before reconstructing the vibration signal from purified IMFs, achieving significant noise reduction. Comparative experiments demonstrate HRCSA's superiority over Particle Swarm Optimization (PSO), WOA, and Gray Wolf Optimization (GWO) regarding convergence speed and precision. Notably, HRCSA-VMD-WT increases the Signal-to-Noise Ratio (SNR) by a minimum of 74.9% and reduces the Root Mean Square Error (RMSE) by at least 41.2% when compared to both CSA-VMD-WT and Empirical Mode Decomposition with Wavelet Transform (EMD-WT). This study improves fault detection accuracy and efficiency in vibration signals and offers a dependable and effective diagnostic solution for slewing bearing maintenance.

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OBJECTIVE: Pulmonary cavity lesion is one of the commonly seen lesions in lung caused by a variety of malignant and non-malignant diseases. Diagnosis of a cavity lesion is commonly based on accurate recognition of the typical morphological characteristics. A deep learning-based model to automatically detect, segment, and quantify the region of cavity lesion on CT scans has potential in clinical diagnosis, monitoring, and treatment efficacy assessment. METHODS: A weakly-supervised deep learning-based method named CSA2-ResNet was proposed to quantitatively characterize cavity lesions in this paper. The lung parenchyma was firstly segmented using a pretrained 2D segmentation model, and then the output with or without cavity lesions was fed into the developed deep neural network containing hybrid attention modules. Next, the visualized lesion was generated from the activation region of the classification network using gradient-weighted class activation mapping, and image processing was applied for post-processing to obtain the expected segmentation results of cavity lesions. Finally, the automatic characteristic measurement of cavity lesions (e.g., area and thickness) was developed and verified. RESULTS: the proposed weakly-supervised segmentation method achieved an accuracy, precision, specificity, recall, and F1-score of 98.48%, 96.80%, 97.20%, 100%, and 98.36%, respectively. There is a significant improvement (P < 0.05) compared to other methods. Quantitative characterization of morphology also obtained good analysis effects. CONCLUSIONS: The proposed easily-trained and high-performance deep learning model provides a fast and effective way for the diagnosis and dynamic monitoring of pulmonary cavity lesions in clinic. Clinical and Translational Impact Statement: This model used artificial intelligence to achieve the detection and quantitative analysis of pulmonary cavity lesions in CT scans. The morphological features revealed in experiments can be utilized as potential indicators for diagnosis and dynamic monitoring of patients with cavity lesions.

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Developing countries with predominantly agricultural economies are particularly vulnerable to short-term climate variability and long-term climate change adversities. This provides the context for adopting climate-smart agricultural (CSA) practices to ensure consistent agricultural product supply and food security. Although concepts of CSA tools and strategies are well-established, their adoption trends in developing regions are still undesirable, with little to no empirical understanding of factors contributing to these trends. The current research aims to address this gap of knowledge by assessing the nature of climate change impacts, adaptation strategies, and socio-economic characteristics of the farmers influencing the adoption of CSA techniques in a rural cohort in Southwestern Bangladesh. Systematically designed interview schedules revealed that the most common and devastating consequences of climate change in the study area were increased infestation of pests and diseases. Other overlooked hazards including water-logging, cyclones and cold waves, are posing new threats to regional agriculture by changing conventional patterns. Contrary to the status quo, many CSA technologies, especially indigenous approaches, are widely and effectively adopted by farmers in the studied area to cope with climate change. These adoption tendencies and innovations in CSA were found to be significantly driven by factors such as extension and training programs, education of farmers, and dependence on on-farming income. The findings of the current study provide a preliminary analysis of the attitude, knowledge and trends of CSA technology adoption by farmers in a less-saline floodplain niche of a predominantly salinity-impacted coastal region. The study acts as a model for future relevant investigations and implementations for stakeholders with supply of inputs, technologies and expertise in finding sustainable solutions and appropriate extension for communities around the world confronted with similar challenges.

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Chondroitin sulfate (CS) is a linear polysaccharide chain of alternating residues of glucuronic acid (GlcA) and N-acetylgalactosamine (GalNAc), modified with sulfate groups. Based on the structure, CS chains bind to bioactive molecules specifically and regulate their functions. For example, CS whose GalNAc is sulfated at the C4 position, termed CSA, and CS whose GalNAc is sulfated at both C4 and C6 positions, termed CSE, bind to a malaria protein VAR2CSA and receptor type of protein tyrosine phosphatase sigma (RPTPσ), respectively, in a specific manner. Here, we modified CSA and CSE chains with phosphatidylethanolamine (PE) at a reducing end, attached them to liposomes containing phospholipids and generated CSA and CSE liposomes. The CS-PE was incorporated into the liposome particles efficiently. Inhibition ELISA revealed specific interaction of CSA and CSE with recombinant VAR2CSA and RPTPσ, respectively, more efficiently than CS chains alone. Furthermore, CSE liposome was specifically incorporated into RPTPσ-expressing HEK293T cells. These results indicate CS liposome as a novel and efficient drug delivery system, especially for CS-binding molecules.

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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.