Search Results (1,175)

Background/Objectives: Neuromodulation is under investigation as a possibly effective add-on therapy in Alzheimer’s disease (AD). While transcranial pulse stimulation (TPS) has shown positive short-term effects, long-term effects have not yet been fully explored. This study aims to evaluate the long-term feasibility, safety, and potential cognitive benefits of TPS over one year in patients with Alzheimer’s disease, focusing on domains such as memory, speech, orientation, visuo-construction, and depressive symptoms. Methods: We analyzed preliminary data from the first ten out of thirty-five patients enrolled in a prospective TPS study who completed one year of follow-up and were included in a dedicated long-term database. The protocol consisted of six initial TPS sessions over two weeks, followed by monthly booster sessions delivering 6000 pulses each for twelve months. Patients underwent regular neuropsychological assessments using the Alzheimer Disease Assessment Scale (ADAS), Mini-Mental Status Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Beck Depression Inventory (BDI-II). All adverse events (AEs) were documented and monitored throughout the study. Results: Adverse events occurred in less than 1% of stimulation sessions and mainly included mild focal pain or transient unpleasant sensations, as well as some systemic behavioral or vigilance changes, particularly in patients with underlying medical conditions, with some potentially related to the device’s stimulation as adverse device reactions (ADRs). Cognitive test results showed significant improvement after the initial stimulation cycle (ADAS total improved significantly after the first stimulation cycle (M_pre = 28.44, M_post = 18.56; p = 0.001, d = 0.80, 95% CI (0.36, 1.25)), with stable scores across all domains over one year. Improvements were most notable in memory, speech, and mood. Conclusions: TPS appears to be a generally safe and feasible add-on treatment for AD, although careful patient selection and monitoring are advised. While a considerable number of participants were lost to follow-up for various reasons, adverse events and lack of treatment effect were unlikely primary causes. A multifocal stimulation approach (F-TOP2) is proposed to enhance effects across more cognitive domains. Full article

Background/Objectives: This study aimed to compare the effects of low- and medium-frequency NMES, combined with a standard physical therapy (SPT) program, on functional capacity in critically ill patients. Methods: Fifty-four critically ill patients admitted into Intensive Care Unit (ICU) and on mechanical ventilation participated in this randomized, single-blinded, experimental study. Participants were randomly assigned to a Control group, who received a lower limb SPT program; the Low-frequency NMES group received lower limb SPT + NMES at 100 Hz; and the Medium-frequency NMES group received lower limb SPT + NMES at 100 Hz with a carrier frequency of 2500 Hz. The outcomes, encompassing functional capacity in the hospital, included muscle strength, handgrip strength, functional status, degree of independence for activities of daily living, functional and dynamic mobility, quality of life, and total days hospitalized. Results: Both NMES protocols combined with SPT improved functional capacity compared to the control group. Medium-frequency NMES provided additional benefits on dynamic balance, in the degree of independence to perform activities of daily living and quality of life (all p < 0.001) prior to hospital discharge. It also promoted larger gains on functional status prior to ICU discharge and on knee extension strength (both p < 0.05) prior to intermediate care unit discharge. Medium-frequency NMES also enhanced handgrip strength earlier than low-frequency NMES when compared to the control group. Notably, medium-frequency NMES was the only intervention associated with a significant reduction in total hospital stay duration (p < 0.05). Conclusions: Medium-frequency NMES, along with an SPT program in critically ill patients, showed greater benefits on functional capacity during recovery than low-frequency NMES. (Trial registration: This trial is registered on ClinicalTrials.gov: NCT05287919). Implications for rehabilitation: 1. Medium-frequency NMES may enhance physical functionality and quality of life in critically ill patients with ICU-acquired weakness. 2. Medium-frequency NMES can reduce the number of hospitalization days. 3. NMES combined with SPT represents a feasible and effective option for patients unable to engage in active rehabilitation during critical illness. Full article

Self-medication is a subject of global importance. If practiced responsibly, self-medication represents a part of self-care or positive care of an individual or a community in promoting their own health. However, today’s practices of self-medication are often inappropriate and irresponsible, and as such appear all over the world. Inappropriate self-medication can be connected with possible serious health risks and consequences. Therefore, it represents a global health issue. It can even generate additional health problems, which will eventually become a burden to healthcare systems and can induce significant costs, which also raises socioeconomic concerns. Hence, self-medication attracts the attention of researchers and practitioners globally in efforts to clarify the current status and define feasible measures that should be implemented to address this issue. This narrative review aims to give an overview of the situation in the field of self-medication globally, including current practices and attitudes, as well as implications for actions needed to improve this problem. A PubMed/MEDLINE search was conducted for articles published in the period from 1995 up to March 2025 using keywords “self-medication” or “selfmedication” alone or in combinations with terms related to specific subthemes related to self-medication, such as COVID-19, antimicrobials, healthcare professionals, and storing habits of medicines at home. Studies were included if self-medication was their main focus. Publications that only mentioned self-medication in different contexts, but not as their main focus, were excluded. Considering the outcomes of research on self-medication in various contexts, increasing awareness of responsible self-medication through education and informing, together with surveillance of particular medicines and populations, could lead to more appropriate and beneficial self-medication in the future. Full article

Tricuspid regurgitation (TR) is a well-recognized factor contributing to adverse outcomes and mortality. Recent developments in transcatheter valve repair techniques, with the emergence of tricuspid transcatheter edge-to-edge repair (TEER) devices, have altered the treatment algorithm of TR and now offer a safe and feasible alternative for the effective management of the disease and an improvement in patient symptoms. Evidence from large studies and registries showcases the benefit of tricuspid interventions in terms of heart failure hospitalization and quality of life; however, most studies do not report a significant benefit in terms of hard outcomes. Even though longer-term follow-up may be needed to identify such differences, it is important to also identify distinct patient phenotypes that would benefit the most from such interventions, moving from pure anatomical criteria to an overall assessment of the patient’s clinical status. Therefore, the aim of this review is to provide updates on potential moderators of the effect of tricuspid TEER, focusing on novel anatomical criteria, right cardiac function, and renal physiology, in order to guide patient selection and provide an insightful discussion on the optimal patient phenotype for future trial design. Full article

Background/Objectives: Psychosocial (PS) factors and cognitive dysfunction (CD) in patients with atrial fibrillation (AF) may negatively impact treatment compliance. The PS profile covers multiple psychological and socio-economic factors, although research is mostly limited to depression, anxiety, and work stress. This study assessed the prevalence of a broad range of PS factors in patients with AF and their relationship with cognitive decline. Methods: We retrospectively analyzed data from patients referred to a cardiovascular rehabilitation clinic between March 2017 and April 2023 who underwent standardized assessments of PS factors, cognition, and quality of life. Results: Of the 798 included patients, 230 (28.8%) had AF, with a mean age of 68.07 years (SD 9.60 years). Six of nine PS factors were present in more than half of the overall sample. Compared to non-AF patients, those with AF showed significantly higher levels of social isolation, depression, and hostility, whereas low socioeconomic status, family and work-related stress, and other mental disorders were more frequent in the non-AF group. CD was present in 67.4% of the total cohort and was more prevalent in AF patients with a higher PS burden. Patients with permanent AF reported the poorest health status. Conclusions: Integrating assessments of PS factors and cognition in cardiac rehabilitation is feasible and supports a more comprehensive, patient-centred model of care in AF. Full article

Background/Objective: This study examines the composite influence of frailty, malnutrition, and anemia on postoperative outcomes for patients with adult spinal deformity (ASD). Methods: In this retrospective cohort study using the 2011–2022 NSQIP database, we utilized CPT and ICD codes to identify ASD patients who underwent PSF. Subjects were stratified based on frailty status. Frail patients were then classified according to malnutrition and anemia status. Frailty was determined using the revised risk analysis index (RAI-rev). Our primary outcomes were extended length of stay (LOS), non-routine discharge (NRD), 30-day adverse events (AE), and 30-day mortality. For each outcome, we fitted four nested multivariable logistic regression models (RAI-rev + anemia + malnutrition, RAI-rev + anemia, RAI-rev + malnutrition, and RAI-rev alone) and compared the incremental discrimination of each model using receiver operating characteristic (ROC) analysis. Results: Of 3639 patients, 460 were frail alone, 266 were frail + anemic, 37 were frail + malnourished, 121 were frail + anemic + malnourished, and 2755 were not frail. RAI-rev (aOR: 1.84, 95% CI: 1.45–2.35), anemia (aOR: 1.84, 95% CI: 1.45–2.35), and malnourishment (aOR: 2.34, 95% CI: 1.69–3.24) were independent predictors of extended LOS. RAI-rev (aOR: 1.07, 95% CI: 1.04–1.11) and anemia (aOR: 2.09, 95% CI: 1.66–2.61) were associated with an increased risk of 30-day AEs. RAI-rev and malnutrition were independent predictors of NRD (RAI-rev: aOR: 1.11, 95% CI: 1.06–1.16; Malnutrition: aOR: 1.57, 95% CI: 1.08–2.29) and 30-day mortality (RAI-rev: aOR: 1.10, 95% CI: 1.04–1.17; Malnutrition: aOR: 3.79, 95% CI: 1.24–11.60). Based on ROC analysis, RAI-rev + anemic + malnourished was a superior predictor of LOS and 30-day AEs (both p < 0.001). Compared to RAI-rev, RAI-rev + anemic superiorly predicted LOS and 30-day AEs, and RAI-rev + malnutrition superiorly predicted LOS (all p < 0.001). Conclusions: Our results reveal RAI-rev combined with malnutrition and anemia superiorly predicts 30-day AEs and LOS in postoperative ASD patients. Future studies should investigate the feasibility and efficacy of these models for perioperative risk stratification and optimized recovery planning to improve outcomes for ASD patients. Full article

This study proposed an online early lameness detection method for dairy cow health management to overcome the inability of wearable sensor-based methods for online detection and low sensitivity to early lameness. Wearable IMU sensors collected acceleration data in stationary and moving states; a threshold discrimination module using variance of motion-direction acceleration was designed to distinguish states within 2 s, enabling rapid data screening. For moving-state windowed data, the InceptionTime network was modified with YOLOConv1D and SeparableConv1D modules plus Dropout, which significantly reduced model parameters and helped mitigate overfitting risk, enhancing generalization on the test set. Typical gait features were fused with deep features automatically learned by the network, enabling accurate discrimination among healthy, mild (early) lameness, and severe lameness. Results showed that the online detection model achieved 80.6% dairy cow health status detection accuracy with 0.8 ms single-decision latency. The recall and F1 score for lameness, including early and severe cases, reached 89.11% and 88.93%, demonstrating potential for early and progressive lameness detection. This study improves lameness detection efficiency and validates the feasibility and practical value of wearable sensor-based gait analysis for dairy cow health management, providing new approaches and technical support for monitoring and early intervention on large-scale farms. Full article

Accurate ship berthing behavior prediction (BBP) is essential for enabling collision warnings and support decision-making. Existing methods based on Automatic Identification System (AIS) data perform well in the task of ship trajectory prediction over long time-series and large scales, but struggle with addressing the fine-grained and highly dynamic changes in berthing scenarios. Therefore, the accuracy of BBP remains a crucial challenge. In this paper, a novel BBP method based on Light Detection and Ranging (LiDAR) data is proposed. To test its feasibility, a comprehensive dataset is established by conducting on-site collection of berthing data at Dalian Port (China) using a shore-based LiDAR system. This dataset comprises equal-interval data from 77 berthing activities involving three large ships. In order to find a straightforward architecture to provide good performance on our dataset, a cascading network model combining convolutional neural network (CNN), a bi-directional gated recurrent unit (BiGRU) and bi-directional long short-term memory (BiLSTM) are developed to serve as the baseline. Experimental results demonstrate that the baseline outperformed other commonly used prediction models and their combinations in terms of prediction accuracy. In summary, our research findings help overcome the limitations of AIS data in berthing scenarios and provide a foundation for predicting complete berthing status, therefore offering practical insights for safer, more efficient, and automated management in smart port systems. Full article

China’s Loess Plateau is characterized by dense and widely distributed check dams. However, there has been a lack of large-scale and high-temporal-resolution monitoring for the water-filled status of check dams, which is strongly related to their safe operation. In this study, a deep learning-based remote sensing image interpretation technique was developed, which enables long-term, large-scale, and high-frequency monitoring of the water-filled status of check dams. Using object detection algorithms based on deep learning and YOLOv3, an object-detection model was constructed and optimized. Leveraging high spatial resolution optical remote sensing images, the water-filled status of check dams can be identified. The model prediction indicates that the average precision for the check dam and water-filled check dam detection models reached 90.27% and 91.89%, respectively. Case studies were conducted on the check dams in the Jiuyuangou and Xiwuselang small watersheds. The monitoring result based on remote sensing images in the year 2021 shows a good agreement with the actual number of check dams. The proposed monitoring method for the water-filled status of check dams was proven feasible. This provides a reliable and efficient technical approach for monitoring the water-filled status of check dams, which is promising for their daily management and safe operation. Full article

Pseudomonas aeruginosa is a highly adaptable opportunistic pathogen with significant clinical relevance in both human and veterinary medicine. Despite its well-documented role in hospital-acquired infections in human healthcare settings, its persistence and transmission within veterinary clinics remain underexplored. This review highlights the overlooked status of veterinary facilities as environmental reservoirs and amplification points for multidrug-resistant (MDR) P. aeruginosa, emphasizing their relevance to One Health surveillance. We examine the bacterium’s environmental survival strategies, including biofilm formation, resistance to disinfectants, and tolerance to nutrient-poor conditions that facilitate the long-term colonization of moist surfaces, drains, medical equipment, and plumbing systems. Common transmission vectors are identified, including asymptomatic animal carriers, contaminated instruments, and the hands of veterinary staff. The review synthesizes current data on antimicrobial resistance in environmental isolates, revealing frequent expression of efflux pumps and mobile resistance genes, and documents the potential for zoonotic transmission to staff and pet owners. Key gaps in environmental monitoring, infection control protocols, and genomic surveillance are identified, with a call for standardized approaches tailored to the veterinary context. Control strategies, including mechanical biofilm disruption, disinfectant cycling, effluent monitoring, and staff hygiene training, are evaluated for feasibility and impact. The article concludes with a One Health framework outlining cross-species and environmental transmission pathways. It advocates for harmonized surveillance, infrastructure improvements, and intersectoral collaboration to reduce the risk posed by MDR P. aeruginosa within veterinary clinical environments and beyond. By addressing these blind spots, veterinary facilities can become proactive partners in antimicrobial stewardship and global resistance mitigation. Full article

Transpiration is the dominant process driving water loss in crops, significantly influencing their growth, development, and yield. Efficient monitoring of transpiration rate (Tr) is crucial for evaluating crop physiological status and optimizing water management strategies. The three-temperature (3T) model has potential for rapid estimation of transpiration rates, but its application to low-altitude remote sensing has not yet been further investigated. To evaluate the performance of 3T model based on land surface temperature (LST) and canopy temperature (T_C) in estimating transpiration rate, this study utilized an unmanned aerial vehicle (UAV) equipped with a thermal infrared (TIR) camera to capture TIR images of summer maize during the nodulation-irrigation stage under four different moisture treatments, from which LST was extracted. The Gaussian Hidden Markov Random Field (GHMRF) model was applied to segment the TIR images, facilitating the extraction of T_C. Finally, an improved 3T model incorporating fractional vegetation coverage (FVC) was proposed. The findings of the study demonstrate that: (1) The GHMRF model offers an effective approach for TIR image segmentation. The mechanism of thermal TIR segmentation implemented by the GHMRF model is explored. The results indicate that when the potential energy function parameter β value is 0.1, the optimal performance is provided. (2) The feasibility of utilizing UAV-based TIR remote sensing in conjunction with the 3T model for estimating Tr has been demonstrated, showing a significant correlation between the measured and the estimated transpiration rate (T_r-3T_C), derived from T_C data obtained through the segmentation and processing of TIR imagery. The correlation coefficients (r) were 0.946 in 2022 and 0.872 in 2023. (3) The improved 3T model has demonstrated its ability to enhance the estimation accuracy of crop Tr rapidly and effectively, exhibiting a robust correlation with T_r-3T_C. The correlation coefficients for the two observed years are 0.991 and 0.989, respectively, while the model maintains low RMSE of 0.756 mmol H₂O m⁻² s⁻¹ and 0.555 mmol H₂O m⁻² s⁻¹ for the respective years, indicating strong interannual stability. Full article

In recent years, passive acoustic monitoring (PAM) technology has significantly contributed to advancements in aquaculture techniques, system iterations, and increased production yields within intelligent feeding systems for Penaeus vannamei. However, current PAM-based intelligent feeding systems do not incorporate environmental factors into the decision process, limiting the improvement of monitoring accuracy in complex environments such as ponds. To establish a connection between environmental factors and the feeding acoustics of P. vannamei, this study utilized PAM technology combined with video analysis to investigate the effects of three key environmental factors—temperature, ammonia nitrogen, and nitrite nitrogen—on the feeding behavioral characteristics of shrimp, with a specific focus on acoustic signals “clicks”. The results demonstrated a significant correlation between the number of clicks and feed consumption in shrimp across different treatments, establishing this stable relationship as a reliable indicator for assessing shrimp feeding status. When water temperature increased from 20 °C to 32 °C, shrimp feed consumption showed an elevation from 0.46 g to 0.95 g per 30 min, with the average number of clicks increasing from 388 to 2947.58 and sound pressure levels rising accordingly. Conversely, ammonia nitrogen at 12 mg/L reduced feed consumption by 0.15 g and decreased click counts by 911.75 pulses compared to controls, while nitrite nitrogen at 40 mg/L similarly suppressed feed consumption by 0.15 g and the average number of clicks by 304.75. A rise in water temperature stimulated shrimp behaviors such as feeding, swimming, and foraging, while elevated concentrations of ammonia nitrogen and nitrite nitrogen significantly inhibited shrimp activity. Redundancy analysis revealed that temperature was the most prominent factor among the three environmental factors influencing shrimp feeding. This study is the first to quantify the specific effects of common environmental factors on the acoustic feeding signals and feeding behavior of P. vannamei using PAM technology. It confirms the feasibility of using PAM technology to assess shrimp feeding conditions under diverse environmental conditions and the necessity of integrating environmental monitoring modules into future feeding systems. This study provides behavioral evidence for the development of precise feeding technologies and the upgrade of intelligent feeding systems for P. vannamei. Full article

Objective: This study aimed to assess the feasibility and acceptability of a Culinary Medicine and Wellness (CMW) class among undergraduate college students attending a U.S. Minority-Serving Institution (MSI), as well as their food security, mental health status, and eating behaviors. Methods: This pre- and post-intervention study was conducted at an MSI in a Southeastern U.S. University, where students enrolled in a 15-week, three-credit CMW class equivalent to 2.5 h per week and received instruction on cooking and preparing healthy meals on a budget. The primary outcomes were acceptability and feasibility of the CMW class. Participants’ food security status, mental health status, and fruit and vegetable intake were also assessed. Program evaluation utilized thematic analysis and descriptive statistics, and trend analyses of outcomes were performed. Results: Eleven participants completed both surveys. The average age was 24 years, with 73% identifying as Black/African American. All participants were female and experienced low or very low food insecurity, and most reported moderate stress levels. All participants reported they would recommend the CMW class to others, with 73% rating it as excellent. Additionally, 82% felt they had learned valuable cooking and budgeting skills. Conclusions: The acceptability and feasibility of a CMW class among college students at an MSI suggests a promising approach to improving cooking skills, enhancing nutrition knowledge, increasing fruit and vegetable intake, and reducing stress. Full article

Tuberculosis (TB) and undernutrition are intricately linked, significantly impacting health outcomes. However, nutritional support for TB patients is not systematically implemented in Lao People’s Democratic Republic (Lao PDR). This study evaluated the effects of nutritional counselling and support on nutritional recovery and TB treatment outcomes. A longitudinal study involved 297 individuals with drug-susceptible TB, 39.4% of whom had a body mass index (BMI) below 18.5 kg/m². Participants were divided into an observation group and an intervention group, the latter receiving nutritional support. Nutritional support included ready-to-use therapeutic food and therapeutic milk products, tailored to patients’ nutritional status. Data collection was conducted at four intervals during treatment. By the end of treatment, 84.3% of participants improved their nutritional status to a BMI of 18.5 kg/m² or higher. The intervention group showed early nutritional recovery, particularly during the intensive phase of TB treatment, although the p-value (p = 0.067) should be interpreted with caution. The overall treatment success rate was high at 90.6%, with no significant difference between groups. Factors associated with treatment success included age under 45, HIV-negative status, a BMI of 18.5 kg/m² or higher, and clinically diagnosed pulmonary TB. Further assessment is required for the operational feasibility to provide systematic nutritional assessment and counselling for people with TB in Lao PDR. Full article

Circulating current control is a critical part of the Modular Multilevel Converter (MMC) control system. Existing control methods rely on arm current information obtained from complex current measurement devices. However, these devices are susceptible to failures, which can lead to distorted arm currents, increased peak arm current values, and higher losses. In extreme cases, this can result in system instability. This paper first analyzes four typical arm current measurement faults, i.e., constant gain faults, amplitude deviation faults, phase shift faults, and stuck faults. Then, a Kalman Filter (KF)-based fault detection method is proposed, which allows for the simultaneous monitoring status of all six arm current measurements. Moreover, to facilitate fault detection, the Moving Root Mean Square (MRMS) value of the observation residual is defined, which effectively detects faults while suppressing noise. The entire fault detection process takes less than 20 ms. Finally, the feasibility and effectiveness of the proposed method are validated through MATLAB/Simulink simulations and experimental results. Full article