Disentangling the effects of metabolic cost and accuracy on movement speed.

On any given day, we make countless reaching movements to objects around us. While such ubiquity may suggest uniformity, each movement's speed is unique-why is this? Reach speed is known to be influenced by accuracy; we slow down to sustain high accuracy. However, in other forms of movement like walking or running, metabolic cost is often the primary determinant of movement speed. Here we bridge this gap and ask: how do metabolic cost and accuracy interact to determine speed of reaching movements? First, we systematically measure the effect of increasing mass on the metabolic cost of reaching across a range of movement speeds. Next, in a sequence of three experiments, we examine how added mass affects preferred reaching speed across changing accuracy requirements. We find that, while added mass consistently increases metabolic cost thereby leading to slower metabolically optimal movement speeds, self-selected reach speeds are slower than those predicted by an optimization of metabolic cost alone. We then demonstrate how a single model that considers both accuracy and metabolic costs can explain preferred movement speeds. Together, our findings provide a unifying framework to illuminate the combined effects of metabolic cost and accuracy on movement speed and highlight the integral role metabolic cost plays in determining reach speed.

Consecutive high-performance removal of Cu2+ metal ions and Deltamethrin using multifunctional pyrolysis cuttlebone/cotton fabric nanocomposite.

A simple technique was developed for the modification of cotton materials that is inexpensive, environmentally friendly, and very effective. Waste Cotton fabrics (WCFs) are loaded with propolis extract (PE) for Cu2+ removal. Then, Cu2+ underwent a pyrolysis process with modified cuttlebone (CB) at 900 °C for 5 h. The surface of the prepared materials was characterized using X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray (SEM-EDX), Fourier transform infrared (FTIR), BET, particle sizes, thermogravimetric analysis (TGA) and zeta potential analysis. The Cu2+ metal ions from an aqueous solution were removed using WCFs/PE, and DLM was subsequently removed using pyro WCFs/PE/Cu/CB. The as-prepared NPs exhibited the face-centered cubic structure of WCFs/PE/Cu/CB with crystallite sizes ranging from 386.70 to 653.10 nm. FTIR spectra revealed that CB was present on the surface of the resulting WCFs/PE/Cu. SEM revealed the dispersion of a uniformly flower-like morphology over a large area. Sorption studies were performed based on parameters that included pH, dose, contact time, and initial concentration. The adsorption isotherm and the kinetic studies of the DLM adsorption process were applied at a pH of 5.0 and a temperature of 25 °C using several isotherms and kinetic models. The results revealed qmax (20.51 mg/g) with R2 = 0.97, the Langmuir isotherm that best matches the experimental data. Hence, the Langmuir isotherm suggests that it is the model that best describes sorption on homogenous surfaces or surface-supporting sites with various affinities. The correlation coefficient R2, χ2, adjusted correlation coefficient, and error functions like root mean square (RMSE), normalized root mean square error (NRMES), and mean absolute error (MAE) were used to evaluate the best-fit models to the experimental adsorption data. Moreover, cost estimation for the prepared adsorbent WCFs/PE/Cu showed that it costs approximately 3 USD/g, which is a cheap adsorbent compared to other similar adsorbents reported in the literature. The examined WCFs/PE have significant applicability potential for Cu2+-laden wastewater treatment due to their superior Cu2+ metal ions adsorption capability and reusability. The cytotoxicity and safety study showed that at higher concentrations, it resulted in much less cell viability. Additionally, the removal efficiency of Cu2+ metal ions from synthetic, realistic industrial wastewater using WCFs/PE reached up to 96.29 %, demonstrating good adsorption capability. Thus, there is a huge possibility of accomplishing this and performing well. This study paves the way for the reuse and valorization of selected adsorbents following circular economy principles. Two green metrics were applied, the Analytical Eco-scale and the Analytical GREEnness Calculator (AGREE).

Geochemical processes, salinity sources and utility characterization of groundwater in a semi-arid region of Iraq through geostatistical and isotopic techniques.

Identifying factors contributing to water salinity is paramount in efficiently managing limited water resources in arid environments. The primary objective of this study is to enhance understanding regarding the hydrochemistry, source, and mechanism of water salinity, as well as to assess the suitability of water for various uses in southern Iraq. The groundwater samples were collected from water wells and springs and analyzed for major cations and anions along with stable isotopes (δ18O and δ2H) to accomplish the objective. The analysis of major ion chemistry, hydrochemical techniques, principal component analysis (PCA), and isotope signatures were adopted to determine the primary factors contributing to water mineralization. The study inferred that evaporation and geological processes encompassing water-rock interactions, such as dissolution precipitation and ion exchange, were key processes. The stable isotope analysis revealed that the water originated from meteoric sources and underwent significant evaporation during or before infiltration. The utility assessment of water samples indicates that most samples are not appropriate for consumption and are significantly below the established standards for potable water. In contrast, a significant portion of the groundwater samples were found to meet the criteria for irrigation suitability by adopting Wilcox and the US Salinity Laboratory criteria. The groundwater could be considered for irrigation with proper salinity control management. Overall, this study has significantly improved the understanding of the hydrogeochemical regimes and acts as a first step toward the sustainable utilization of water resources.

Desert date seed extract-loaded chitosan nanoparticles ameliorate hyperglycemia and insulin deficiency through the reduction in oxidative stress and inflammation.

Plants represents a huge source of bioactive materials that have been used since the old times in the treatment of many diseases. Balanites aegyptiaca, known as desert date, has been used in treatment of fever, diabetes and bacterial infection. Desert dates contains a hard seed that resembles 50-60% of the fruit. The seed extract contains many fatty acids, amino acids and other bioactive materials that gives the extract its antioxidant and anti-inflammatory properties. The study aimed to use Balanites seed extract-loaded chitosan nanoparticles (SeEx-C NPs) for the treatment of streptozotocin (STZ)-induced diabetes in male Sprague Dawley rats. Animals were divided into two main divisions (healthy and diabetic rats). Each division contained seven groups (5 rats/group): control untreated group I, SeEx treated group II and group III (10 and 20 mg/kg b.w., respectively), C NPs treated group IV and group V (10 and 20 mg/kg b.w., respectively) and SeEx-C NPs treated group VI and group VII (10 and 20 mg/kg b.w., respectively). The therapeutical effects of SeEx-C NPs were evaluated through biochemical and immunological assessments in rats' pancreases. The results showed that SeEx-C NPs (10 and 20 mg/kg b.w.) reduced the oxidative stress and inflammation in rats' pancreases allowing the islets neogenesis. The loading of SeEx on C NPs allowed the delivery of fatty acids (oleic, lauric and myristic acid), amino acids (lysine, leucine, phenylalanine and valine) and minerals to pancreatic beta-cells in a sustainable manner. SeEx-C NPs administration successfully increased insulin secretion, allowed pancreatic islets neogenesis and reduced oxidative stress and inflammation.

Slowing of Movements in Healthy Aging as a Rational Economic Response to an Elevated Effort Landscape.

Why do we move slower as we grow older? The reward circuits of the brain, which tend to invigorate movements, decline with aging, raising the possibility that reduced vigor is due to the diminishing value that our brain assigns to movements. However, as we grow older, it also becomes more effortful to make movements. Is age-related slowing principally a consequence of increased effort costs from the muscles, or reduced valuation of reward by the brain? Here, we first quantified the cost of reaching via metabolic energy expenditure in human participants (male and female), and found that older adults consumed more energy than the young at a given speed. Thus, movements are objectively more costly for older adults. Next, we observed that when reward increased, older adults, like the young, responded by initiating their movements earlier. Yet, unlike the young, they were unwilling to increase their movement speed. Was their reluctance to reach quicker for rewards due to the increased effort costs, or because they ascribed less value to the movement? Motivated by a mathematical model, we next made the young experience a component of aging by making their movements more effortful. Now the young responded to reward by reacting faster but chose not to increase their movement speed. This suggests that slower movements in older adults are partly driven by an adaptive response to an elevated effort landscape. Moving slower may be a rational economic response the brain is making to mitigate the elevated effort costs that accompany aging.

Effects of reward and effort history on decision making and movement vigor during foraging.

During foraging, animals explore a site and harvest reward and then abandon that site and travel to the next opportunity. One aspect of this behavior involves decision making, and the other involves movement control. These two aspects of behavior may be linked via an underlying desire to maximize a single normative utility: the sum of all rewards acquired, minus all efforts expended, divided by time. According to this theory, the history of rewards, and not just its immediate availability, should dictate how long one should stay and harvest reward and how vigorously one should travel to the next opportunity. We tested this theory in a series of experiments in which humans used their hand to harvest tokens at a reward patch and then used their arm to reach toward another patch. After a history of high rewards, the subjects not only shortened their harvest duration but also moved more vigorously toward the next reward opportunity. In contrast, after a history of high effort they lengthened their harvest duration but reduced their movement vigor, reaching more slowly to the next reward site. Thus, a history of high reward or low effort biased decisions by promoting early abandonment of the reward site and biased movements by promoting vigor.NEW & NOTEWORTHY Much of life is spent foraging. Whereas previous work has focused on the decision regarding time spent harvesting from a reward patch, here we test the idea that both decision making and movement control are tuned to optimize the net rate of reward in an environment. Our results show that movement patterns reflect not just immediate expectations but also past experiences in the environment, providing fundamental insight into the factors governing volitional control of arm movements.

Multisite Mpox Infection and Viral Dynamics Among Persons With HIV in Metro Atlanta.

The 2022 mpox outbreak primarily involved sexual transmission among men who have sex with men and disproportionately affected persons with human immunodeficiency virus (HIV). We examined viral dynamics and clinical features in a cohort evaluated for mpox infection at a comprehensive HIV clinic in Atlanta, Georgia. Viral DNA was found in 8 oropharyngeal and 5 anorectal specimens among 10 mpox cases confirmed by lesion swab polymerase chain reaction. Within-participant anatomic site of lowest cycle threshold (Ct) value varied, and lower Ct values were found in oropharyngeal and anorectal swabs when corresponding symptoms were present. This provides insight into mpox infection across multiple anatomic sites among people with HIV.

Fear of a new pandemic: perception and prediction of monkeypox among the middle east general population.

Background: Monkeypox is a zoonotic disease caused by the monkeypox virus, an Orthopox virus. The 2022 monkeypox outbreak provoked fear among the public. Public awareness about the disease could be an important factor in its control. The authors conducted this study to assess the perception and prediction of monkeypox among the Middle East public. Methods: This cross-sectional study was conducted in August 2022. Data were conveniently collected from eight Middle Eastern countries using an online self-administered questionnaire distributed through educational and social media platforms. Statistical analysis was conducted using R software. Results: Approximately 11 016 individuals participated in this study. The participants' overall knowledge score indicated poor knowledge about monkeypox. Most of the participants knew the causative organism (66.7%). However, numerous participants were not aware of the disease mode of transmission, symptoms, complications, and vaccination. Participants' awareness was mostly gained from social media (61.8%). The majority predicted acquiring monkeypox when protective measures are not taken (72.7%), progression to a pandemic with economic consequences (50.8 and 52%, respectively), and the ability of the Ministry of Health to control the epidemic (51.5%). Conclusion: In the Middle East, public knowledge about monkeypox is poor. Raising awareness about monkeypox would be of benefit in controlling the epidemic. This study constitutes evidence upon which health education programs could be designed.

Viral and host factors associated with SARS-CoV-2 disease severity in Georgia, USA.

While SARS-CoV-2 vaccines have shown strong efficacy, their suboptimal uptake combined with the continued emergence of new viral variants raises concerns about the ongoing and future public health impact of COVID-19. We investigated viral and host factors, including vaccination status, that were associated with SARS-CoV-2 disease severity in a setting with low vaccination rates. We analyzed clinical and demographic data from 1,957 individuals in the state of Georgia, USA, coupled with viral genome sequencing from 1,185 samples. We found no difference in disease severity between individuals infected with Delta and Omicron variants among the participants in this study, after controlling for other factors, and we found no specific mutations associated with disease severity. Compared to those who were unvaccinated, vaccinated individuals experienced less severe SARS-CoV-2 disease, and the effect was similar for both variants. Vaccination within 270 days before infection was associated with decreased odds of moderate and severe outcomes, with the strongest association observed at 91-270 days post-vaccination. Older age and underlying health conditions, especially immunosuppression and renal disease, were associated with increased disease severity. Overall, this study provides insights into the impact of vaccination status, variants/mutations, and clinical factors on disease severity in SARS-CoV-2 infection when vaccination rates are low. Understanding these associations will help refine and reinforce messaging around the crucial importance of vaccination in mitigating the severity of SARS-CoV-2 disease.

Common Mechanisms of Learning in Motor and Cognitive Systems.

Rapid progress in our understanding of the brain's learning mechanisms has been accomplished over the past decade, particularly with conceptual advances, including representing behavior as a dynamical system, large-scale neural population recordings, and new methods of analysis of neuronal populations. However, motor and cognitive systems have been traditionally studied with different methods and paradigms. Recently, some common principles, evident in both behavior and neural activity, that underlie these different types of learning have become to emerge. Here we review results from motor and cognitive learning, relying on different techniques and studying different systems to understand the mechanisms of learning. Movement is intertwined with cognitive operations, and its dynamics reflect cognitive variables. Training, in either motor or cognitive tasks, involves recruitment of previously unresponsive neurons and reorganization of neural activity in a low dimensional manifold. Mapping of new variables in neural activity can be very rapid, instantiating flexible learning of new tasks. Communication between areas is just as critical a part of learning as are patterns of activity within an area emerging with learning. Common principles across systems provide a map for future research.

Knowledge, attitude, and ethical concepts of Sudanese medical students regarding stem cells and its application.

One of the major challenges that stem cell transplantation faces is a lack of donors due to a lack of knowledge and awareness of the importance of stem cell transplantation, this implies that health care providers should arm themselves with sufficient knowledge to contribute positively to raising awareness. This is an analytical cross-sectional study of 1040 medical students from 10 universities from various Sudanese states, through an online self-administered pre-tested and structured questionnaire formulated by the authors with a particular focus and/or reflection on the knowledge and attitudes of medical students. The median knowledge score among all students was 8.0 (6-9) with the majority of students confirming that stem cells are capable of dividing and can self-renew for a long period (88.6%). Regarding attitude, the median score among the participants was 23 (17-27) with (47.9%) agreeing that competency in stem cell knowledge is important for them as future health care providers. In terms of ethical attitude; the majority of the students (59, 2%) think there's a need to obtain ethical approval before conducting research. Moreover, (45.9%) of students believe that health practitioners have the right to use stem cells in treatments if those treatments have been scientifically proven to be effective on animals and on human cells in the laboratory. It is important to promote educational programs that inform medical students about the full range of possibilities offered by stem cell research. Furthermore, more studies is required to determine how society and religion affect medical students' attitudes toward stem cells.

Effort cost of reaching prompts vigor reduction in older adults.

As people age, they move slower. Is age-related reduction in vigor a reflection of a reduced valuation of reward by the brain, or a consequence of increased effort costs by the muscles? Here, we quantified cost of movements objectively via the metabolic energy that young and old participants consumed during reaching and found that in order reach at a given speed, older adults expended more energy than the young. We next quantified how reward modulated movements in the same populations and found that like the young, older adults responded to increased reward by initiating their movements earlier. Yet, their movements were less sensitive to increased reward, resulting in little or no modulation of reach speed. Lastly, we quantified the effect of increased effort on how reward modulated movements in young adults. Like the effects of aging, when faced with increased effort the young adults responded to reward primarily by reacting faster, with little change in movement speed. Therefore, reaching required greater energetic expenditure in the elderly, suggesting that the slower movements and reactions exhibited in aging are partly driven by an adaptive response to an elevation in the energetic landscape of effort. That is, moving slower appears to be a rational economic consequence of aging. Significance statement: Healthy aging coincides with a reduction in speed, or vigor, of walking, reaching, and eye movements. Here we focused on disentangling two opposing sources of aging-related movement slowing: reduced reward sensitivity due to loss of dopaminergic tone, or increased energy expenditure movements related to mitochondrial or muscular inefficiencies. Through a series of three experiments and construction of a computational model, here we demonstrate that transient changes in reaction time and movement speed together offer a quantifiable metric to differentiate between reward- and effort-based alterations in movement vigor. Further, we suggest that objective increases in the metabolic cost of moving, not reductions in reward valuation, are driving much of the movement slowing occurring alongside healthy aging.

Sudan's armed rivalry: A comment on the vulnerable healthcare system catastrophe.

The Sudan War 2023 is a military conflict that erupted in the heart of a paralyzed state system. A total of 68% of hospitals are presently closed, with the remainder operating just partially owing to a lack of staff, medical supplies, and pharmaceuticals. Furthermore, due to power outages, Sudan's vaccination and insulin stocks are under jeopardy. Additionally, patients with chronic conditions have difficulty receiving their prescriptions. This unaccounted-for conflict is expected to degrade Sudan's already-weak healthcare sector by the recent COVID-19 pandemic and 2018 revolution. Humanitarian emergency care is being offered by numerous non-for-profit organizations and civilians initiatives; but, more measures, notably aimed at preventing political upheaval, are required to save the country's future.

A Residual-Dense-Based Convolutional Neural Network Architecture for Recognition of Cardiac Health Based on ECG Signals.

Cardiovascular disorders are often diagnosed using an electrocardiogram (ECG). It is a painless method that mimics the cyclical contraction and relaxation of the heart's muscles. By monitoring the heart's electrical activity, an ECG can be used to identify irregular heartbeats, heart attacks, cardiac illnesses, or enlarged hearts. Numerous studies and analyses of ECG signals to identify cardiac problems have been conducted during the past few years. Although ECG heartbeat classification methods have been presented in the literature, especially for unbalanced datasets, they have not proven to be successful in recognizing some heartbeat categories with high performance. This study uses a convolutional neural network (CNN) model to combine the benefits of dense and residual blocks. The objective is to leverage the benefits of residual and dense connections to enhance information flow, gradient propagation, and feature reuse, ultimately improving the model's performance. This proposed model consists of a series of residual-dense blocks interleaved with optional pooling layers for downsampling. A linear support vector machine (LSVM) classified heartbeats into five classes. This makes it easier to learn and represent features from ECG signals. We first denoised the gathered ECG data to correct issues such as baseline drift, power line interference, and motion noise. The impacts of the class imbalance are then offset by resampling techniques that denoise ECG signals. An RD-CNN algorithm is then used to categorize the ECG data for the various cardiac illnesses using the retrieved characteristics. On two benchmarked datasets, we conducted extensive simulations and assessed several performance measures. On average, we have achieved an accuracy of 98.5%, a sensitivity of 97.6%, a specificity of 96.8%, and an area under the receiver operating curve (AUC) of 0.99. The effectiveness of our suggested method for detecting heart disease from ECG data was compared with several recently presented algorithms. The results demonstrate that our method is lightweight and practical, qualifying it for continuous monitoring applications in clinical settings for automated ECG interpretation to support cardiologists.

Flood susceptibility mapping utilizing the integration of geospatial and multivariate statistical analysis, Erbil area in Northern Iraq as a case study.

Climate extreme events such as floods and droughts in any area have a significant impact on human life, infrastructure, agriculture, and the economy. In the last two years, flash floods caused by heavy rainstorms have become frequent and destructive in many catchments in Northern Iraq. The present study aims to examine flash floods in the Erbil region, Northern Iraq using Remote sensing (RS), Geographic Information System (GIS), and Principal Component Analysis (PCA) for geomorphic data. PCA results revealed that 12 geomorphic parameters exhibited a significant correlation with two different statistical components. To facilitate practical application, ranks are assigned based on the calculated parameters for flood susceptibility mapping. Out of the 24 basins in the current study, three basins (16, 3, and 14) have the highest geomorphometric values (36-39), indicating the zone most susceptible to flash floods and making up a maximum area of 38.58% of the studied region. Six basins (4, 8, 9, 10, 12, and 15), which have geomorphometric values between 30 and 35 and cover a land area of 27.86%, are the most moderately vulnerable to floods. The remaining basins, which make up 33.47% of the research, are occasionally subject to floods and have geomorphometric scores below 30. The precision of the flood susceptibility mapping was validated using the bifurcation ratio and drainage density relationship as well as past flood damages, such as economic losses and human casualties. Most of the recorded injuries and fatalities took place in areas that were particularly prone to severe past flooding. Additionally, the investigation revealed that 44.56% of all populated areas are located in extremely vulnerable basins. The findings demonstrate a notable correlation between the identified flood-susceptible areas and the occurrence of past flood damage.

Topical caffeine-loaded nanostructured lipid carriers for enhanced treatment of cellulite: A 32 full factorial design optimization and in vivo evaluation in rats.

The goal of this study was the development and evaluation of semisolid caffeine (CAF) loaded nanostructured lipid carriers (NLCs) for topical treatment of cellulite. CAF-loaded NLC formulations were prepared via high-speed homogenization followed by ultrasonication. A 32 full factorial design was employed for formulation optimization. The total lipid content (%) and the liquid lipid content per total lipids (%) were chosen as factors, whereas particle size (PS), polydispersity index (PDI), zeta potential (|ZP|) and viscosity (VIS) were selected as responses. The design suggested CAF-NLC3 as the optimum formulation consisting of a total lipid content of 15% w/w (palmitic acid and soft paraffin/isopropyl myristate, 7:3 w/w) and a surfactant content of 10% w/w (Tween 80/lecithin, 8:1.2 w/w). CAF-NLC3 revealed PS, PDI, ZP, VIS and CAF content values of 318.8 nm, 0.253, -41.1 mV, 18.0 Pa.s and 97.57%, respectively. It showed a pseudoplastic rheological behavior, acceptable pH value (5.25), good spreadability (1.12 mm2/g) and spherical shape employing transmission electron microscopy. Differential scanning calorimetry and X-ray diffraction demonstrated the amorphization of CAF in CAF-NLC3. CAF-NLC3 remained stable for 3 months at room and refrigeration conditions. A single topical application of CAF-NLC3 on shaved abdominal skins of Wistar rats revealed enhanced skin retention of CAF by 2-fold and 1.4-fold after 4 h when compared with plain CAF gel (CAF-P) and marketed CAF gel (CAF-M), respectively. Furthermore, CAF-NLC3 exhibited a superior anti-cellulite activity in comparison with CAF-P and CAF-M through elevating extracellular matrix components (collagen 1, elastin and hyaluronic acid) and stimulating the brown adipose tissue thermogenesis via up-regulating UCP1 and PPAR-γ expression. In addition, CAF-NLC3 prominently increased lipolysis through HSL activity and decreased pro-inflammatory cytokines such as ICAM-1 and VCAM-1 after 30 days of treatment on a high fat diet-induced cellulite rat model. These findings were further confirmed by histopathological examination supported by morphometric analysis. Therefore, incorporation of CAF in a semisolid NLC formulation would be a promising cosmetic approach for the topical treatment of cellulite.

The educational value of ward rounds as a learning and teaching opportunity for house officers, medical officers, and registrars in Sudanese hospitals: a multi-center cross-sectional study.

BACKGROUND: Ward rounds are a cornerstone in the educational experience of junior doctors and an essential part of teaching patient care. Here, we aimed to assess the doctors' perception of ward rounds as an educational opportunity and to identify the obstacles faced in conducting a proper ward round in Sudanese hospitals. METHOD: A cross-sectional study was conducted from the 15th to the 30th of January 2022 among house officers, medical officers, and registrars in about 50 teaching and referral hospitals in Sudan. House officers and medical officers were considered the learners, while specialist registrars were considered the teachers. Doctors' perceptions were assessed using an online questionnaire, with a 5-level Likert scale to answer questions. RESULTS: A total of 2,011 doctors participated in this study (882 house officers, 697 medical officers, and 432 registrars). The participants were aged 26.9 ± 3.2 years, and females constituted about 60% of the sample. An average of 3.1 ± 6.8 ward rounds were conducted per week in our hospitals, with 11.1 ± 20.3 h spent on ward rounds per week. Most doctors agreed that ward rounds are suitable for teaching patient management (91.3%) and diagnostic investigations (89.1%). Almost all the doctors agreed that being interested in teaching (95.1%) and communicating appropriately with the patients (94.7%) make a good teacher in ward rounds. Furthermore, nearly all the doctors agreed that being interested in learning (94.3%) and communicating appropriately with the teacher (94.5%) make a good student on ward rounds. About 92.8% of the doctors stated that the quality of ward rounds could be improved. The most frequently reported obstacles faced during ward rounds were the noise (70%) and lack of privacy (77%) in the ward environment. CONCLUSION: Ward rounds have a special value in teaching patient diagnosis and management. Being interested in teaching/learning and having good communication skills were the two major criteria that make a good teacher/learner. Unfortunately, ward rounds are faced with obstacles related to the ward environment. It is mandatory to ensure the quality of both ward rounds' teaching and environment to optimize the educational value and subsequently improve patient care practice.

Metabolic costs of walking and arm reaching in persons with mild multiple sclerosis.

Movement slowness is a common and disruptive symptom of multiple sclerosis (MS). A potential cause is that individuals with MS slow down to conserve energy as a behavioral adjustment to heightened metabolic costs of movement. To investigate this prospect, we measured the metabolic costs of both walking and seated arm reaching at five speeds in persons with mild MS (pwMS; n = 13; 46.0 ± 7.7 yr) and sex- and age-matched controls (HCs; n = 13; 45.8 ± 7.8 yr). Notably, the cohort of pwMS was highly mobile and no individuals required a cane or aid when walking. We found that the net metabolic power of walking was approximately 20% higher for pwMS across all speeds (P = 0.0185). In contrast, we found no differences in the gross power of reaching between pwMS and HCs (P = 0.492). Collectively, our results suggest that abnormal slowness of movement in MS-particularly reaching-is not the consequence of heightened effort costs and that other sensorimotor mechanisms are playing a considerable role in slowing.NEW & NOTEWORTHY Individuals with multiple sclerosis (MS) often move more slowly than those without the disease. A possible cause is that movements in MS are more energetically expensive and slowing is an adaptation to conserve metabolic resources. Here, we find that while walking is more costly for persons with MS, arm-reaching movements are not. These results bring into question the driving force of movement slowness in MS and implicate other motor-related networks contributing to slowing.

Learning vs. minding: How subjective costs can mask motor learning.

When learning new movements some people make larger kinematic errors than others, interpreted as a reduction in motor-learning ability. Consider a learning task where error-cancelling strategies incur higher effort costs, specifically where subjects reach to targets in a force field. Concluding that those with greater error have learned less has a critical assumption: everyone uses the same error-canceling strategy. Alternatively, it could be that those with greater error may be choosing to sacrifice error reduction in favor of a lower effort movement. Here, we test this hypothesis in a dataset that includes both younger and older adults, where older adults exhibited greater kinematic errors. Utilizing the framework of optimal control theory, we infer subjective costs (i.e., strategies) and internal model accuracy (i.e., proportion of the novel dynamics learned) by fitting a model to each population's trajectory data. Our results demonstrate trajectories are defined by a combination of the amount learned and strategic differences represented by relative cost weights. Based on the model fits, younger adults could have learned between 65-90% of the novel dynamics. Critically, older adults could have learned between 60-85%. Each model fit produces trajectories that match the experimentally observed data, where a lower proportion learned in the model is compensated for by increasing costs on kinematic errors relative to effort. This suggests older and younger adults could be learning to the same extent, but older adults have a higher relative cost on effort compared to younger adults. These results call into question the proposition that older adults learn less than younger adults and provide a potential explanation for the equivocal findings in the literature. Importantly, our findings suggest that the metrics commonly used to probe motor learning paint an incomplete picture, and that to accurately quantify the learning process the subjective costs of movements should be considered.

Light-Dermo: A Lightweight Pretrained Convolution Neural Network for the Diagnosis of Multiclass Skin Lesions.

Skin cancer develops due to the unusual growth of skin cells. Early detection is critical for the recognition of multiclass pigmented skin lesions (PSLs). At an early stage, the manual work by ophthalmologists takes time to recognize the PSLs. Therefore, several "computer-aided diagnosis (CAD)" systems are developed by using image processing, machine learning (ML), and deep learning (DL) techniques. Deep-CNN models outperformed traditional ML approaches in extracting complex features from PSLs. In this study, a special transfer learning (TL)-based CNN model is suggested for the diagnosis of seven classes of PSLs. A novel approach (Light-Dermo) is developed that is based on a lightweight CNN model and applies the channelwise attention (CA) mechanism with a focus on computational efficiency. The ShuffleNet architecture is chosen as the backbone, and squeeze-and-excitation (SE) blocks are incorporated as the technique to enhance the original ShuffleNet architecture. Initially, an accessible dataset with 14,000 images of PSLs from seven classes is used to validate the Light-Dermo model. To increase the size of the dataset and control its imbalance, we have applied data augmentation techniques to seven classes of PSLs. By applying this technique, we collected 28,000 images from the HAM10000, ISIS-2019, and ISIC-2020 datasets. The outcomes of the experiments show that the suggested approach outperforms compared techniques in many cases. The most accurately trained model has an accuracy of 99.14%, a specificity of 98.20%, a sensitivity of 97.45%, and an F1-score of 98.1%, with fewer parameters compared to state-of-the-art DL models. The experimental results show that Light-Dermo assists the dermatologist in the better diagnosis of PSLs. The Light-Dermo code is available to the public on GitHub so that researchers can use it and improve it.