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Abstract Androgenetic alopecia (AGA) is the most prevalent type of hair loss. Its morbility is mainly psychological although an increased incidence in melanoma has also been observed in affected subjects. Current drug based therapies and physical treatments are either unsuccessful in the long term or have relevant side effects that limit their application. Therefore, a new therapeutic approach is needed to promote regenerative enhancement alternatives. These treatment options, focused on the cellular niche restoration, could be the solution to the impact of dihydrotestosterone in the hair follicle microenvironment. In this context emerging regenerative therapies such as Platelet-rich plasma or Platelet-rich fibrine as well as hair follicle stem cells and mesenchymal stem cell based therapies and their derivatives (conditioned medium CM or exoxomes) are highlighting in the evolving landscape of hair restoration. Nanotechnology is also leading the way in AGA treatment through the design of bioinks and nanobiomaterials whose structures are being configuring in a huge range of cases by means of 3D bioprinting. Due to the increasing number and the rapid creation of new advanced therapies alternatives in the AGA field, an extended review of the current state of art is needed. In addition this review provides a general insight in current and emerging AGA therapies which is intented to be a guidance for researchers highlighting the cutting edge treatments which are recently gaining ground.

A potential underlying mechanism associated with the difficulties in social interactions in Autistic Spectrum Disorders (ASD) concerns the abnormal development of moral reasoning. The present study examined utilitarian and deontological judgments in impersonal and personal moral dilemmas, comparing 66 individuals with ASD and 61 typically developing (TD) individuals between 6 and 18 years. Utilitarian judgments decreased with age. This decline was much more gradual for personal dilemmas in the ASD than in the TD group. ASD individuals rated utilitarian judgments as more appropriate but felt less calm, consistent with the Empathy Imbalance hypothesis. Utilitarian judgments were associated with social interaction difficulties in ASD. These findings identify possible social therapeutic targets for more efficient coping strategies in individuals with ASD.

Methods Four-step process: (1) creation of a governance model, a web platform and reporting forms for a PSRLS in Catalonia (SNiSP Cat); (2) SNiSP Cat roll out; (3) embed SNiSP Cat information in the accreditation model for HCO and the PS scorecard; (4) Development of SNiSP Cat within the QPSS Plan Cat 2023–2027.Results The SNiSP Cat is in use by 63/64 acute care hospital (ACH), 376/376 primary healthcare teams (PCT) and 17/98 long-term care facilities (LTCF). 1335/109 273 professionals were trained. Until 2022, 127 051 incidents have been migrated and reported (2013–2022). The system has generated three comprehensive risk maps for HCO: one for ACH, including patients’ falls, medication, clinical process and procedures; second for PCT, including clinical process and procedures, clinical administration and medication; and a third for LTCF, included patients’ falls, medication, digital/analogical documentation. SNiSP Cat provided information to support 53 standards out of 1312 of the ACH accreditation model and 14 standards out of 379 of PCT one. Regarding the MHC patient safety scorecard, 14 indicators out of 147 of ACH and 4 out of 41 of PCT are supported by SNiSP Cat data.Conclusions The availability of a territorial PSRLS (SNiSP Cat) allows MHC leads the Q&PS policy with direct information, risk maps and data support to the standards for the Catalan accreditation models and PS scorecard linked to incentivisation, turning the SNiSP Cat into a driven tool to implement the Quality and Patient Safety Strategic Plan of Catalonia 2023–2027.

Almond oils extracted from roasted kernels at different roasting times at 150 °C were analyzed to quantify quality parameters such as acidity, peroxide value, K232, K270, antioxidant activity and the oxidative stability index. The roasting process induced oxidation of the chemical compounds in the oil, resulting in increased acidity, peroxide value, K232 and K270. The antioxidant activity exhibited a decreasing trend over time, while the oxidative stability showed only slight changes. Excitation-emission matrices (EEMs) were directly scanned on almond oil samples. The combination of the EEMs with parallel factor analysis (PARAFAC) provided qualitative information about the main fluorophores and their evolution with the roasting time. Quantitative information was obtained using unfolded partial least squares (U-PLS), demonstrating the effectiveness of the fluorescence technique in combination with multivariate analysis to quantify analytical parameters in almond oils. Prediction models were developed, and subjected to external validation. The coefficients of determination in the external validation were higher than 0.94 for all parameters except k270.

Abstract Background In rheumatoid arthritis (RA), the activation of T and B cell clones specific for self-antigens leads to the chronic inflammation of the synovium. Here, we perform an in-depth quantitative analysis of the seven chains that comprise the adaptive immune receptor repertoire (AIRR) in RA. Results In comparison to controls, we show that RA patients have multiple and strong differences in the B cell receptor repertoire including reduced diversity as well as altered isotype, chain, and segment frequencies. We demonstrate that therapeutic tumor necrosis factor inhibition partially restores this alteration but find a profound difference in the underlying biochemical reactivities between responders and non-responders. Combining the AIRR with HLA typing, we identify the specific T cell receptor repertoire associated with disease risk variants. Integrating these features, we further develop a molecular classifier that shows the utility of the AIRR as a diagnostic tool. Conclusions Simultaneous sequencing of the seven chains of the human AIRR reveals novel features associated with the disease and clinically relevant phenotypes, including response to therapy. These findings show the unique potential of AIRR to address precision medicine in immune-related diseases.

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Introduction: This study investigates the comparative efficacy of neuromodulation therapy using the EXOPULSE Mollii Suit and a structured exercise program in pain modulation and muscle oxygenation in Fibromyalgia patients.Methods: A randomized, crossover, longitudinal, and experimental study design was employed, involving 10 female Fibromyalgia patients. Participants were subjected to two distinct treatment modalities: neuromodulation therapy with the EXOPULSE Mollii Suit and a strength-based High-Intensity Interval Training (HIIT) exercise program, each conducted over 16 sessions. Outcome measures included pain severity, assessed using the Numeric Rating Scale (NRS), and muscle oxygenation variables measured via Near-Infrared Spectroscopy (NIRS).Results: Both interventions demonstrated significant reductions in NRS scores and improvements in muscle oxygenation. However, the exercise program yielded more pronounced long term basal adaptations in muscle oxygenation compared to the neuromodulation therapy.Discussion: The findings underscore the potential of integrating non-pharmacological treatments, particularly structured exercise programs, in managing Fibromyalgia. While neuromodulation therapy presents a viable alternative, the exercise regimen’s capacity to induce basal muscle oxygenation adaptations suggests its superiority in addressing the complex symptoms of Fibromyalgia. Furthermore, these therapeutic approaches may enhance patients’ vocational values and employability opportunities by improving their functional capabilities and overall quality of life.

ObjectiveThis work is the result of one of the lines of research opened in the LabinTic group (UCLM) and a stay in the city of Padua, in the Italian Veneto area, in 2022. After observing the side effects in Italy as a result of COVID-19 and the Great Lockdown, we wanted to know in more depth some aspects related to how the people of Veneto used IT as an important weapon to fight against forced isolation and, if possible, compare this with other similar studies performed in Castilla-La Mancha.MethodTo achieve this objective, an ad hoc questionnaire was designed and validated through expert judgment. This questionnaire was administered to a random probabilistic sample by disseminating it through social media and email using the “snowball” method. A total of 338 people who comprised the population sample of the study (n = 338) were obtained. After analyzing the data through SPSS 28, using a mixed methodology considering qualitative and quantitative aspects, the great influence that IT had among the Italian population during the lockdown common aspects of their everyday lives and incorporating some acquired habits (listening to music, for example) into their usual life routines after the return to normality was determined among other features and assessments. In summary, the text highlights how the pandemic influenced music consumption, the popularity of different music genres, the role of social media, and the enduring importance of the music itself in people’s lives. It suggests that music remains a source of comfort and entertainment in challenging times.

BackgroundPoststroke fatigue is a prevalent issue among stroke survivors, significantly impeding functional recovery and diminishing their quality of life.AimThis prospective cohort study aims to investigate the association between poststroke fatigue and the extent of functional recovery in survivors of ischemic and hemorrhagic strokes. Additionally, it seeks to delineate the temporal progression of poststroke fatigue in these two stroke subtypes.MethodsWe assessed a cohort of 79 patients recovering from acute ischemic or hemorrhagic strokes. Poststroke fatigue was quantified using the Fatigue Severity Scale (FSS) and the Numeric Rating Scale (NRSfatigue). Patients’ condition was evaluated using the National Institute of Health Stroke Scale (NIHSS), and functional independence levels were determined using the Barthel Index for Activities of Daily Living (BIADL) and the Modified Rankin Scale (MRS). Depressive mood and pain were measured using the Beck Depression Inventory (BDI) and the Numeric Rating Scale for pain (NRSpain), respectively.ResultsOur primary findings indicate that the early manifestation of clinically significant fatigue (CSF) is predictive of a poorer trajectory in functional independence levels during recovery. Furthermore, we observed differing patterns of fatigue progression between ischemic and hemorrhagic strokes. Fatigue tends to ameliorate over time in hemorrhagic stroke cases, paralleling functional recovery, while it remains stable over time in ischemic stroke cases.ConclusionOur results underscore the detrimental impact of early poststroke fatigue on long-term outcomes. Furthermore, they highlight the imperative of managing poststroke fatigue, particularly during the subacute phase of stroke recovery.

Objective To assess the predictive value of four cardiovascular (CV) risk algorithms for identifying high-risk psoriatic arthritis (PsA) patients.Methods Evaluation of patients with PsA enrolled in the Spanish prospective project CARdiovascular in RheuMAtology. Baseline data of 669 PsA patients with no history of CV events at the baseline visit, who were followed in rheumatology outpatient clinics at tertiary centres for 7.5 years, were retrospectively analysed to test the performance of the Systematic Coronary Risk Assessment (SCORE), the modified version (mSCORE) European Alliance of Rheumatology Associations (EULAR) 2015/2016, the SCORE2 algorithm (the updated and improved version of SCORE) and the QRESEARCH risk estimator version 3 (QRISK3).Results Over 4790 years of follow-up, there were 34 CV events, resulting in a linearised rate of 7.10 per 1000 person-years (95% CI 4.92 to 9.92). The four CV risk scales showed strong correlations and all showed significant associations with CV events (p

The efficient series connection of planar leaky-wave antennas (LWA) to obtain directive frequency beam scanning, is proposed in this paper. Conditions for the proper performance are here derived, showing that the distance between antennas must be minimized while optimizing the phase shift introduced by the interconnection. Consequently, the methodology to design the transition is presented by an example using SMA connectors and a meander coaxial cable. Such series arrangement is useful to overcome the restricted directivity of planar LWAs in the UHF band due to limited PCB standard manufacturing sizes, while optimizing the radiation efficiency. The presented theory is validated with practical design examples of microstrip LWA arrays operating in the 900 MHz UHF band. Also, the frequency-beam scanning behaviour of the series-fed LWA array is analysed, demonstrating good performance when the proposed design conditions are satisfied, compared to a non-optimized design which can lead to destructive interference in the desired scanning directions.

A compact antenna design is proposed to synthesize two-dimensional amplitude monopulse radiation patterns, with application to integrated sensing and communications in the ISM 2.4 GHz band. The antenna makes use of two air-filled leaky waveguides to generate four diagonally scanned beams without the need of complex feeding networks. The design demonstrates the generation of monopulse patterns in the two perpendicular planes of the antenna, covering an angular field of view of 40° X 60° where the Direction of Arrival can be estimated. The simple structure and compactness of this antenna makes it very suitable for low-cost multi-functional joint radar-communications using commercial wireless networks.

In the context of neurorehabilitation, there have been rapid and continuous improvements in sensors-based clinical tools to quantify limb performance. As a result of the increasing integration of technologies in the assessment procedure, the need to integrate evidence-based medicine with benchmarking has emerged in the scientific community. In this work, we present the experimental validation of our previously proposed benchmarking scheme for upper limb capabilities in terms of repeatability, reproducibility, and clinical meaningfulness. We performed a prospective multicenter study on neurologically intact young and elderly subjects and post-stroke patients while recording kinematics and electromyography. 60 subjects (30 young healthy, 15 elderly healthy, and 15 post-stroke) completed the benchmarking protocol. The framework was repeatable among different assessors and instrumentation. Age did not significantly impact the performance indicators of the scheme for healthy subjects. In post-stroke subjects, the movements presented decreased smoothness and speed, the movement amplitude was reduced, and the muscular activation showed lower power and lower intra-limb coordination. We revised the original framework reducing it to three motor skills, and we extracted 14 significant performance indicators with a good correlation with the ARAT clinical scale. The applicability of the scheme is wide, and it may be considered a valuable tool for upper limb functional evaluation in the clinical routine.

Abstract The application of graph theory to metacommunity ecology allows a deeper analysis of the effect of network structure on diversity patterns. Here, we set out to test the role of network centrality metrics and environmental characteristics in diversity patterns of pond macroinvertebrate metacommunities. We tested two approaches to construct the networks: one used the percolation distance, whereas the other was based on a community‐contingent distance. The role of each patch within the network was then analyzed using its centrality value. Later, we analyzed the relationships between the macroinvertebrate diversity and centrality metrics for four study sites. The calculated diversity metrics cover different facets of biodiversity at two scales: pond and pondscape. Environmental characteristics of the studied ponds were also included. All relationships were tested considering the entire macroinvertebrate dataset, but also differentiated by dispersal mode (i.e., active vs. passive) and considering the two types of network approaches analyzed. The results were mostly consistent when comparing the network approaches used. Centrality metrics tended to be positively related to alpha and negatively to beta diversity. Environmental uniqueness showed a positive effect on beta diversity metrics, regardless of the dispersal mode. We only observed a weak negative relationship between eutrophication and species richness of active dispersers. Pond size showed a positive effect on both alpha and beta diversity, but was detected more frequently on alpha diversity metrics. We could not find evidence for a clear negative effect of habitat degradation on diversity. We found a greater importance of environmental characteristics versus the centrality metrics for both alpha and beta diversity of active dispersers, while a combination of their contributions for passive dispersers. An unexpected importance of centrality was observed for alpha diversity of passive dispersers. Using empirical data, we demonstrate that the centrality of a patch in an undirected network affects diversity regardless of the approach used to construct the networks, with a higher influence at local scale regardless of the dispersal mode. This study broadens knowledge of the relationships between environmental features and network centrality, demonstrating the important role of centrality as a determinant of diversity in metacommunities.

Abstract Background and Study Aims Our aim was to determine the impact of the SARS‐CoV‐2 pandemic on the diagnosis and prognosis of colorectal cancer (CRC). Patients and Methods This prospective cohort study included individuals diagnosed with CRC between March 13, 2019 and June 20, 2021 across 21 Spanish hospitals. Two time periods were compared: prepandemic (from March 13, 2019 to March 13, 2020) and pandemic (from March 14, 2020 to June 20, 2021, lockdown period and 1 year after lockdown). Results We observed a 46.9% decrease in the number of CRC diagnoses (95% confidence interval (CI): 45.1%–48.7%) during the lockdown and 29.7% decrease (95% CI: 28.1%–31.4%) in the year after the lockdown. The proportion of patients diagnosed at stage I significantly decreased during the pandemic (21.7% vs. 19.0%; p = 0.025). Centers that applied universal preprocedure SARS‐CoV‐2 PCR testing experienced a higher reduction in the number of colonoscopies performed during the pandemic post‐lockdown (34.0% reduction; 95% CI: 33.6%–34.4% vs. 13.7; 95% CI: 13.4%–13.9%) and in the number of CRCs diagnosed (34.1% reduction; 95% CI: 31.4%–36.8% vs. 26.7%; 95% CI: 24.6%–28.8%). Curative treatment was received by 87.5% of patients diagnosed with rectal cancer prepandemic and 80.7% of patients during the pandemic post‐lockdown period (p = 0.002). Conclusions The COVID‐19 pandemic has led to a decrease in the number of diagnosed CRC cases and in the proportion of stage I CRC. The reduction in the number of colonoscopies and CRC diagnoses was higher in centers that applied universal SARS‐CoV‐2 PCR screening before colonoscopy. In addition, the COVID‐19 pandemic has affected curative treatment of rectal cancers.

IntroductionIn recent years, the decoding of motor imagery (MI) from electroencephalography (EEG) signals has become a focus of research for brain-machine interfaces (BMIs) and neurorehabilitation. However, EEG signals present challenges due to their non-stationarity and the substantial presence of noise commonly found in recordings, making it difficult to design highly effective decoding algorithms. These algorithms are vital for controlling devices in neurorehabilitation tasks, as they activate the patient's motor cortex and contribute to their recovery.MethodsThis study proposes a novel approach for decoding MI during pedalling tasks using EEG signals. A widespread approach is based on feature extraction using Common Spatial Patterns (CSP) followed by a linear discriminant analysis (LDA) as a classifier. The first approach covered in this work aims to investigate the efficacy of a task-discriminative feature extraction method based on CSP filter and LDA classifier. Additionally, the second alternative hypothesis explores the potential of a spectro-spatial Convolutional Neural Network (CNN) to further enhance the performance of the first approach. The proposed CNN architecture combines a preprocessing pipeline based on filter banks in the frequency domain with a convolutional neural network for spectro-temporal and spectro-spatial feature extraction.Results and discussionTo evaluate the approaches and their advantages and disadvantages, EEG data has been recorded from several able-bodied users while pedalling in a cycle ergometer in order to train motor imagery decoding models. The results show levels of accuracy up to 80% in some cases. The CNN approach shows greater accuracy despite higher instability.

Abstract The increasing use of antimicrobial drugs has been linked to the rise of drug-resistant fungus in recent years. Antimicrobial resistance is being studied from a variety of perspectives due to the important clinical implication of resistance. The processes underlying this resistance, enhanced methods for identifying resistance when it emerges, alternate treatment options for infections caused by resistant organisms, and so on are reviewed, along with strategies to prevent and regulate the formation and spread of resistance. This overview will focus on the action mechanism of antifungals and the resistance mechanisms against them. The link between antibacterial and antifungal resistance is also briefly discussed. Based on their mechanism action, antifungals are divided into three distinct categories: azoles, which target the ergosterol synthesis; 5-fluorocytosine, which targets macromolecular synthesis and polyenes, which interact physiochemically with fungal membrane sterols. Antifungal resistance can arise through a wide variety of ways. Overexpression of the target of the antifungal drug, changes to the drug target, changes to sterol biosynthesis, decreased intercellular concentration of the target enzyme, and other processes. A correlation exists between the mechanisms of resistance to antibacterial and antifungals, despite the fact that the comparison between the two is inevitably constrained by various parameters mentioned in the review. Drug extrusion via membrane pumps has been thoroughly documented in both prokaryotic and eukaryotic cells, and development of new antifungal compounds and strategies has also been well characterized.