Prostaglandin F2α receptor (FP receptor) signaling is a plausible target for promoting hair growth, but clinical data on topical latanoprost acid (the active free-acid FP agonist) in hair loss are lacking. This study aimed to evaluate the clinical efficacy, safety, and mechanistic basis of topical latanoprost acid in women with female androgenetic alopecia. In this investigator-initiated, randomized, double-blind, single-center, dose-ranging pilot trial, 29 adult women with hair loss predominantly consistent with female androgenetic alopecia were randomized to vehicle (n = 2) or topical latanoprost acid 0.01% (n = 8), 0.05% (n = 13), or 0.1% (n = 6), applied once daily for 6 months. The primary endpoint was within-participant change in target-area hair count (TAHC, hairs/cm²) from baseline to month 6; trichoscopic activity markers (yellow dots) and follicular-unit (FU) remodeling were secondary and exploratory outcomes. Human hair dermal papilla cells (HHDPCs) were assessed for FP receptor-linked signaling (intracellular Ca²⁺ flux) and DNA synthesis by 5-ethynyl-2'-deoxyuridine (EdU) incorporation after exposure to latanoprost acid versus equimolar latanoprost. An increase in TAHC was observed across all active treatment arms (mean ± SEM ΔTAHC: 17.8 ± 4.3, 23.5 ± 6.1, and 16.5 ± 6.5 hairs/cm² in the latanoprost acid 0.01%, 0.05%, and 0.1% arms, respectively). No significant between-arm differences were detected. Secondary and exploratory trichoscopic analyses showed reductions in yellow-dot counts, a decrease in single-hair FUs, and an increase in triple-hair FUs. Safety was favorable, with no serious adverse events. In mechanistic assays, latanoprost acid triggered rapid, concentration-dependent Ca²⁺ flux, whereas equimolar latanoprost produced delayed signals; neither compound altered EdU incorporation. In this pilot proof-of-concept trial, topical latanoprost acid showed a coherent clinical-trichoscopic bioactivity signal, supported by FP receptor-linked signaling in HHDPCs. These findings require confirmation in larger randomized pharmacokinetic/pharmacodynamic-integrated trials designed to optimize dose, confirm efficacy, and further characterize long-term safety. ClinicalTrials.gov, NCT07412587; registered on February 2, 2026.
Despite the World Health Organization's recommendation for exclusive breastfeeding, Thailand's rate was only 14% in 2019. Many new mothers experience discomfort and lack confidence during breastfeeding. The novel Ing Oun breastfeeding pillow was developed to support breastfeeding in the side-lying position. This study compared breastfeeding effectiveness between the Ing Oun pillow and the normal side-lying position and evaluated maternal satisfaction. A proof-of-concept randomized controlled trial was conducted in a postpartum unit in Thailand. Ninety-two first-time mothers with vaginal births were randomly assigned to either the Ing Oun breastfeeding pillow in the side-lying position (intervention) or the normal side-lying position (control). Breastfeeding effectiveness was assessed by nurse-midwives and mothers based on infant positioning and attachment. Maternal satisfaction with the pillow was measured using a self-report questionnaire. Compared with the control group, mothers using the Ing Oun breastfeeding pillow demonstrated significant improvements in breastfeeding effectiveness, including reduced nipple pain during suckling [median=3 (IQR: 2-4) vs 3 (IQR: 1-4), p<0.001], observing more areola above the infant's top lip [median=4 (IQR: 3-4) vs 3 (IQR:1-4), p<0.001], and improved support for continued suckling [median=4 (IQR: 2-4) vs 3 (IQR: 1-4), p<0.05]. Mothers in the intervention group reported high levels of satisfaction with the pillow, with 65.2% expressing confidence in breastfeeding. The Ing Oun breastfeeding pillow shows potential as a breastfeeding support aid; however, further research is needed to refine its design and evaluate broader applicability.CLINICAL TRIAL REGISTRATION: The study is registered on the official website of Thai Clinical Trials Registry.IDENTIFIER: TCTR20241016002.
Mental health disorders are leading causes of morbidity worldwide and often co-occur with substance use and other addictive behaviors. However, many individuals in mental health care settings are not screened for addictions. General psychopathology measures, such as the Brief Symptom Inventory (BSI), may offer valuable insights into addiction risk. This study explores whether machine learning models can utilize BSI responses to predict problematic substance use (alcohol, drugs) and addictive behaviors (gambling, gaming, hypersexual behavior, and pornography use). A population sample of Jewish adults in Israel (N=2,451) was assessed for mental health, including the BSI, problematic substance use (alcohol, drugs), and potentially addictive behaviors: gambling, gaming, compulsive sexual behavior, and pornography use. Machine learning models - including decision trees, random forest, boosting, LASSO, subset-selection, and elastic net regression- were employed to predict addiction outcomes based on BSI responses. The BSI demonstrated varying degrees of predictive ability across different addictions and models. Explained variance (R2) ranged from 2.9% to 27.0%, while Area Under the Curve (AUC) values, indicating classification capabilities according to clinical thresholds, ranged from 0.60 to 0.84. Behavioral addictions generally showed descriptively higher predictability than substance use disorders. The BSI contains substantial information on addiction risk, demonstrating its potential to enhance screening for comorbid addictions in mental health settings. These findings, also serve as proof of principle for notion that existing psychopathology measures can be leveraged to inform about potential comorbidity. Being able to efficiently identify which mental health patients must be screened for addictions will help to determine the most appropriate interventions.
Large symptomatic brain metastases require initial surgical resection. However, local control (LC) after Gamma Knife radiosurgery (GKRS) to resection cavities remains variable. Quantitative risk stratification using routinely available treatment-time variables could inform surveillance and multidisciplinary decision-making. We performed a retrospective study of post-resection cavities treated with GKRS at a single institution (2014-2024). The primary endpoint was LC. The cohort comprised of 401 post-resection cavities. A gradient boosting classifier was trained using eight routine treatment-time features: age, sex, pre-treatment Karnofsky Performance Status, primary tumor category, single vs. multiple metastases, lobe/structure, eloquence, and cavity volume. Performance was estimated using five-fold stratified cross-validation with out-of-fold predictions and compared with a prevalence-only baseline. Discrimination and calibration were assessed using the receiver operating characteristic area under the curve (ROC-AUC), and Brier score; operating characteristics were reported at a prespecified probability threshold of 0.50. We compared the performance of two different AI models for predicting LC. The prevalence baseline demonstrated chance-level discrimination (ROC-AUC 0.494). The gradient boosting model improved performance with ROC-AUC 0.735 and PR-AUC 0.802 with acceptable calibration (Brier 0.208). At threshold 0.50, accuracy was 0.701 with sensitivity 0.783 and specificity 0.566. A feedforward neural network trained on the same features performed worse (ROC-AUC 0.672; PR-AUC 0.768; Brier 0.219). A machine learning model using routine treatment-time variables can meaningfully stratify LC after GKRS to post-resection cavities. The gradient boosting model showed the best performance supporting further external validation and prospective evaluation. Not applicable.
Cole-Carpenter syndrome (CCS) is a rare autosomal dominant skeletal disorder characterized by severe bone fragility, recurrent fractures, craniosynostosis, and distinctive craniofacial abnormalities. Pathogenic variants in P4HB, encoding protein disulfide isomerase A1 (PDIA1), represent the most frequent cause of CCS. The recurrent missense mutation p.Tyr393Cys (Y393C) has been identified in unrelated patients, yet the in vivo consequences of this mutation on skeletal biology and its therapeutic implications remain poorly understood. Here, we generated a mouse model carrying the mouse homolog P4hbY393C mutation. Comprehensive skeletal phenotyping revealed pronounced osteopenia and reduced local bone quality in mutant mice across multiple ages. Consistently, CCS mice exhibited reduced circulating levels of procollagen type I N-terminal propeptide (PINP I), indicating decreased type I collagen biosynthesis. At the cellular level, primary osteoblasts isolated from CCS mice showed lower expression and secretion of type I collagen, along with decreased expression of osteocalcin and higher mineralization. On the other hand, osteoclast differentiation was increased. Given the lack of disease-modifying therapies for CCS, we explored different therapeutic strategies. We performed a functional screen of an FDA-approved drug library identifying four compounds that significantly enhanced type I collagen secretion. Finally, we developed an allele-specific RNA interference (siRNAs) approach and identified siRNA sequences capable of selectively silencing the mutant P4hb allele in vitro and ex vivo without cytotoxic effects. Collectively, our study establishes a robust preclinical model for P4hb-related CCS, defines defective type I collagen biosynthesis as a central pathogenic mechanism, and identifies promising therapeutic strategies with translational potential for this currently untreatable skeletal disorder.
To introduce a novel method that explores the relationship between sensory perception during the cosmetic application journey and measurable physical parameters. We establish a three-dimensional, three-interval thixotropy test (3D-3ITT) protocol that maps 'shear dose' (rate × duration) to structural recovery, and test whether this fingerprint associates with sensory and emotional responses during use. Four formulations were prepared as two pairs: serum-like (S1s/S2s) and watery-lotion (S1w/S2w), using two thickeners at higher vs. lower concentrations to reach target viscosities. From 3D-3ITT recovery maps, we computed an equal-weighted early-time thixotropy index (TI3D). In a subsequent consumer study (N = 30), untrained participants completed randomized, contralateral half-face application of each pair and a questionnaire assessing sensory attributes and emotions. 3D-3ITT clearly differentiated the four samples. Formulations primarily thickened with Alcaligenes polysaccharides (S1s/S1w) showed markedly greater sensitivity (higher TI3D) to shear dose than those thickened with Xanthan gum (S2s/S2w), with TI3D values of 46 (S1s), 37 (S1w), and 5.8 for both S2s and S2w. In consumer testing, the high-TI3D formulations were generally rated as more easily absorbed and less sticky or greasy, with the clearest sensory differences concentrated in application phase attributes. In the serum pair, the high-TI3D formulation (S1s) produced significantly more favourable emotional shifts, including lower Anxiety and higher Relax, Comfort and Overall Emotional State. Across both paired studies, larger positive sensory shifts were modestly yet significantly associated with larger positive emotional shifts at the subject level. Overall, thixotropy captured by TI3D provided more insight and separation than conventional rheological metrics. 3D-3ITT provides a compact, usage-relevant recovery landscape and a single actionable index that may help relate laboratory metrics to consumer-relevant sensory and emotional responses. In this four-formula proof-of-concept set, TI3D differentiated textures more sensitively than single-point rheology and was consistent with a cautious interpretation of a TI3D-sensory-emotion pathway. Practically, this supports rapid A/B down-selection, targeted polymer/process tuning, and further exploration of how laboratory metrics relate to perceivable sensory experience. Présenter une nouvelle méthode qui explore la relation entre la perception sensorielle pendant le parcours d’application cosmétique et les paramètres physiques mesurables. Nous établissons un protocole de test de thixotropie tridimensionnel à trois intervalles (3D‑3ITT) qui relie la « dose de cisaillement » (taux × durée) à la récupération structurelle, et nous testons si cette empreinte est associée à des réponses sensorielles et émotionnelles pendant l’utilisation. MÉTHODES: Quatre formulations ont été préparées en deux paires : type sérum (S1s/S2s) et lotion aqueuse (S1w/S2w), en utilisant deux épaississants à des concentrations plus élevées comparées à des concentrations plus faibles pour atteindre les viscosités cibles. À partir des cartes de récupération 3D‐3ITT, nous avons calculé un indice de thixotropie précoce (TI3D) pondéré à parts égales. Dans une étude ultérieure auprès des consommateurs (N = 30), des participants non formés ont réalisé une application randomisée, controlatérale, sur une demi‐face de chaque paire et ont rempli un questionnaire évaluant les caractéristiques sensorielles et les émotions. RÉSULTATS: 3D‐3ITT a clairement différencié les quatre échantillons. Les formulations principalement épaissies avec des polysaccharides d’Alcaligenes (S1s/S1w) ont montré une sensibilité (TI3D) nettement plus élevée à la dose de cisaillement que celles épaissies avec de la gomme xanthane (S2s/S2w), avec des valeurs de TI3D de 46 (S1s), 37 (S1w) et 5,8 pour S2s et S2w. Dans les tests auprès des consommateurs, les formulations à TI3D élevé ont généralement été évaluées comme étant plus facilement absorbées et moins collantes ou grasses, les différences sensorielles les plus nettes étant concentrées sur les attributs de la phase d’application. Dans la paire de sérums, la formulation à TI3D élevé (S1s) a produit des changements émotionnels significativement plus favorables, notamment une anxiété plus faible et davantage de relaxation, de confort et un meilleur état émotionnel global. Dans les deux études appariées, des changements sensoriels positifs plus importants étaient modestement mais significativement associés à des changements émotionnels positifs plus importants au niveau du sujet. Dans l’ensemble, la thixotropie capturée par TI3D a fourni plus d’informations et de séparation que les mesures rhéologiques conventionnelles. 3D‐3ITT fournit un paysage de récupération compact et pertinent pour l’utilisation, ainsi qu’un indice unique exploitable qui peut aider à relier les mesures de laboratoire aux réponses sensorielles et émotionnelles pertinentes pour le consommateur. Dans cet ensemble de preuve de concept à quatre formules, TI3D a différencié les textures plus sensiblement que la rhéologie à un seul point et était cohérent avec une interprétation prudente d’une voie TI3D‐sensorielle‐émotion. En pratique, cela permet une présélection A/B rapide, un ajustement ciblé des polymères/processus et une exploration plus approfondie de la manière dont les mesures de laboratoire sont liées à l’expérience sensorielle perceptible.
No sufficiently sensitive biomarker exists to monitor disease progression to assess treatment efficacy in synucleinopathies such as Parkinson's disease (PD), particularly during the prodromal phase when interventions are likely to be most effective. Existing digital biomarkers often rely on active tasks or clinic-based assessments, limiting their scalability and real-world applicability. In this proof-of-concept study, we evaluated whether linguistic features derived from real-world phone call recordings using large language models can serve as a language-based progression biomarker in isolated rapid eye movement sleep behavior (iRBD). In this two-year study, we enrolled 74 participants, including 21 iRBD (20 men), 26 PD (25 men), and 27 healthy controls (26 men) age-matched to iRBD participants. Speech data collection occurred remotely in participants' natural environments through routine phone calls. Over 34,000 phone calls (<1,400 hours) were recorded over the two-year period. Compared to healthy controls, individuals with iRBD exhibited significant declines in sentence coherence (p = 0.016), semantic-syntactic diversity (p < 0.001), topic diversity (p < 0.001), and sentence probability (p < 0.001) over the two years. Prodromal changes in iRBD were detectable with an area under the curve of 0.82 from as few as 21 calls. For a two-year neuroprotective trial targeting 50% drug efficacy, the estimated sample size was 78 iRBD participants per arm based on a time-to-event analysis. These findings demonstrate that fully automated phone call analysis can detect both prodromal and progressive changes in alpha-synucleinopathy. This approach is scalable, minimizes the effort required from both patients and clinical staff, and enables remote, low-burden monitoring in screening at-risk populations and therapeutic trials.
Coinfection of hepatitis B virus and hepatitis C virus presents great difficulty in treatment procedures, especially in terms of prediction of the response to the direct-acting antiviral therapy. In view of this, developing adequate prediction models would play a vital role in ensuring better personalization and effectiveness in terms of treatment. The objective of this paper is to develop and validate prediction models for the identification of patients' responses to direct-acting antiviral therapy in chronic HBV/HCV coinfected patients following treatment completion. This retrospective clinical prediction study involved the use of medical records of 154 patients with HBV/HCV coinfection treated with the help of direct-acting antiviral therapy in Holy Family Hospital, Rawalpindi, Pakistan. Sixteen predictors were used to develop logistic regression models to predict treatment responses at 4 and 12 weeks. In addition, to counter the problems of class imbalance, the synthetic minority oversampling technique was applied to the datasets, while nested stratified cross-validation was used for hyperparameter tuning and model validation. Performance was evaluated through different performance metrics such as ROC-AUC, accuracy, precision, recall, and F1-score. The performance of the two models was very good at each endpoint. For the endpoint of 4 weeks, the ROC-AUC score was 0.858 (95% CI 0.746-0.942), the accuracy was 0.760, and the F1-score was 0.851. In the case of the 12-week endpoint, the ROC-AUC score was 0.850 (95% CI 0.769-0.916), the accuracy was 0.786, and the F1-score was 0.856. The important predictors were HCV genotypes, age, body mass index, hemoglobin, and liver function test results. Good model calibration was evident from the calibration graphs, which showed slight deviation from the ideal calibration line at both endpoints. The current study developed prediction models for treatment response in HBV/HCV coinfected patients based on clinical and laboratory information from baseline. The models showed very good internal validity, but the 12-week model performed slightly better than the 4-week model in terms of classification balance. Such models represent useful tools for decision-making in case of a personalized approach.
Patient and public involvement (PPI) is increasingly promoted in health services research, yet empirical evidence remains limited on how participatory governance is operationalised in research practices. This qualitative study explored patient partners' experiences of involvement in the PaRole OncO France (PROOF) research project, a multicentre participatory action research (PAR) project aimed at adapting, implementing and evaluating a peer support intervention in oncology. Semi-structured interviews were conducted with patient partners involved in project governance. Data were analysed using inductive thematic analysis, with patient partners involved in validating analytic outputs. Seven of the eight invited patient partners (PPs) were interviewed. Three interrelated themes emerged: (1) personal invitation as recognition: a catalyst of engagement, whereby being personally solicited was experienced as recognition of experiential legitimacy; (2) securing a 'real place': relational trust, dedicated spaces and institutional frictions, capturing both the conditions enabling genuine co-governance (dedicated spaces, recognition of experiential knowledge and responsive research teams) and the administrative and temporal constraints that strained it; and (3) reciprocal transformation: perceived impacts on the research and on personal trajectories. Patient partners perceived meaningful contributions to intervention design and team cohesion, alongside personal benefits such as skills development and network building. Persistent barriers were primarily structural, including administrative constraints, research temporalities and regulatory procedures. PROOF illustrates how intentional participatory governance mechanisms can support sustained PPI in research. Addressing administrative barriers, clarifying roles and nurturing trust and communication are crucial for meaningful participation in oncology research. The qualitative data presented in this manuscript were obtained through interviews with patient partners. Patient partners co-designed governance structures, participated in all committees, co-facilitated co-construction workshops, and contributed to data interpretation and manuscript validation.
The hydrodynamic model of hydrocephalus proposes that ventriculomegaly is driven by exaggerated intraventricular pulsations rather than impaired cerebrospinal fluid (CSF) circulation alone. Under this model, endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) treats hydrocephalus by creating a pulsation absorber and by reducing a primary source of intraventricular pulsation. However, direct intraoperative human evidence supporting this two-step mechanism is lacking. This study aimed to test the hypothesis that ETV followed by CPC would produce measurable, stepwise decreases in mean intraventricular pressure (ICP) and pulsation amplitude in infants with hydrocephalus. This single-institution proof-of-concept study included infants with symptomatic hydrocephalus undergoing ETV/CPC as the first definitive treatment. A fiber-optic ICP sensor was attached to the operative ventriculoscope and passively recorded mean and pulsatile ICP (pulsation amplitude) throughout the procedure. Longitudinal brain parenchymal volume (BPV) and cerebrospinal fluid volume (CSFV) were obtained through segmentation of clinically acquired T2-weighted MRI and converted to age- and sex-matched z-scores. All patients were followed for a minimum of 6 months postoperatively. Five infants (median corrected age at ETV/CPC 8 months) were included. No surgical complications occurred, and no ETV/CPC failures were observed during follow-up. Overall, mean ICP decreased by 56-97% after the combined procedure in four patients. In three patients (Patients 1, 3, and 5), both mean ICP and pulsation amplitude decreased stepwise following ETV and then CPC, consistent with the hypothesized therapeutic mechanism. Patient 4 demonstrated a large reduction in mean ICP after ETV with minimal additional effect from CPC and no significant change in pulsation amplitude. Patient 2 demonstrated neither a reduction in mean ICP nor a meaningful change in pulsation amplitude after either procedure; this patient also had a delayed and atypical clinical response. Intracranial segmentation demonstrated BPV z-score stabilization within normal range and CSFV plateau in all patients after surgery. This proof-of-concept study provides the first direct intraoperative human evidence supporting the hydrodynamic mechanism of ETV/CPC in a subset of infant with hydrocephalus. Our findings suggest that determination of intraoperative ICP parameters is feasible, safe and might ultimately prove helpful in improving patient selection for ETV/CPC, warranting further investigation in larger cohorts.
Atomically precise metal nanoclusters (NCs), as ultrasmall materials with well-defined composition and structure, exceptional biocompatibility, and unique optical properties, position them as strong candidates in the field of electrochemiluminescence (ECL). However, the ECL efficiency of NCs is relatively low, which dramatically constrained their applications due to the demands of detection sensitivity and brightness. In this study, we report the interface self-assembly of Au10 nanoclusters for the first time, and ultimately formed a fibrous structure with a high aspect ratio, Au10-Fiber, which is an innovative approach that significantly enhances the ECL activity of Au10 NCs. By employing time-dependent and in situ spectroscopic techniques, we visually monitored the dynamic assembly process, and elucidated the interface self-assembly mechanism mediated by aurophilic interaction and π-π stacking. The increase in local electronic density, enhanced conductivity of the ordered structure, and accelerated electron transfer within the π-conjugated system collectively contributed to the significant enhancement of the ECL performance, thereby revealing the key structural factors responsible for ECL enhancement. As a proof of concept, we successfully constructed an ECL immunosensor based on Au10-Fiber for the detection of Alzheimer's disease biomarker Aβ1-42, achieving a detection limit below 3.33 fg/mL.
Economically motivated adulteration (EMA) of roasted coffee presents a critical challenge to global market integrity and consumer safety, specifically regarding the surreptitious inclusion of high-risk allergens like barley and soybeans. The detection of such contaminants is historically hindered by the Maillard reaction, a thermal convergence during roasting that renders adulterants visually and spectrally indistinguishable from the coffee matrix. To address this forensic gap, this study presents a targeted hyperspectral imaging (HSI) framework (400-1000 nm) integrated with a two-stage hierarchical Support Vector Machine (SVM) designed to decouple detection from specific biological diagnosis. A core contribution of this methodology is the implementation of Principal Component Analysis (PCA) to resolve spectral redundancy across the 128-band hypercube. By distilling the data into two primary components capturing over 92% of the cumulative variance, the framework establishes a "spectrochemical bridge" that isolates hidden chromatic and biochemical variances invisible to traditional RGB sensors. This high-significance feature space allows the SVM to overcome the "Euclidean trap" inherent in unsupervised clustering, which frequently suffers from "class collapse" in roasted materials. Experimental results demonstrate that the hierarchical pipeline achieves an optimal overall accuracy of 88.6% and a Kappa coefficient of 0.378. The system attained high reliability during the Stage-1 binary screening, achieving an F1-score of 0.922 to protect the primary coffee matrix, while the Stage-2 multi-class model successfully mapped the spatial distribution of the highly camouflaged allergens. By providing pixel-wise, automated risk assessments, this work establishes a data-driven proof-of-concept for 'Smart Food Safety' systems, highlighting the potential for forensic authentication in future industrial quality control environments.
Heavy metal contamination, driven by anthropogenic disruption of natural geochemical cycles, has led to widespread bioaccumulation, posing a serious global health threat. Addressing this crisis demands the development of simple and sensitive strategies capable of monitoring metal pollution in the environment. Leveraging nongenetically modified native organisms, this research offers a promising low-cost, eco-friendly screening approach for detecting heavy metals in contaminated samples. Current study uses post-translational splicing of the Mycobacterium tuberculosis (Mtb) SufB precursor protein to detect metals by linking metal-induced splicing inhibition to viability loss of native mycobacterial cells. Toxic metal ions like Cd2+ and Hg2+ blocked splicing activity of Mtb SufB precursor protein over a concentration range of 25 μM-2 mM, while Pb2+ and Cr3+ failed to do so. An innovative biosensor platform was designed to detect metals by a simple Alamar Blue assay using attenuated Mtb H37Ra as indicator cells. Qualitative metal detection was assessed via colorimetric variation relating to mycobacterial viability, while concurrent spectral absorbance measurement enabled metal ion quantification. Loss of H37Ra cell viability by metal ions over the 25 μM-2 mM concentration range highlighted the sensitivity of the designed biosensor, while the addition of metal-specific chelators reversed the effect. Multiplexing ability was evaluated by including known splicing inhibitors like Cu2+, Zn2+, and Pt4+ over various concentration ranges alongside Cd2+ and Hg2+ in a simple 96-well plate format. The designed intein-based biosensor offers a user-friendly platform, readily standardizable for high-throughput detection using native organisms harboring metal-sensing precursor proteins. As a proof-of-concept, this study demonstrates the applicability of intein-based biosensing for initial heavy metal screening in environmental and industrial effluents, serving as a rapid and accessible tool prior to targeted advanced analysis.
The efficacy of current opioid overdose interventions is fundamentally limited by their reliance on bystander detection and administration, leaving unwitnessed overdoses, a predominant cause of fatalities, unaddressed. Herein, we developed an innovative fentanyl-responsive microneedle (MN) patch (iNal patch) engineered as an autonomous harm reduction tool to dynamically release naloxone on demand in response to fentanyl levels. Specifically, the iNal patch integrates mesoporous silica nanoparticles (MSNs) loaded with naloxone. The nanoparticle surfaces are modified by fentanyl-sensitive aptamers, allowing precise and dose-dependent drug release triggered by fentanyl exposure. The engineered MN matrix composed of swellable maleated poly(vinyl alcohol) facilitates rapid skin penetration and interstitial fluid access, ensuring immediate and sustained naloxone release. From in vitro and in vivo studies, the iNal patch was demonstrated to effectively reverse fentanyl-induced opioid overdose symptoms, rapidly restore normal physiological behaviors in mice, and enable multiple responsive drug-release cycles to prevent renarcotization. This proof-of-concept MN platform establishes a new paradigm for materials-based harm reduction, offering an autonomous safety net for high-risk populations independent of human supervision.
Marine adhesive organisms commonly employ epidermal growth factor (EGF)-like domains for wet attachment, yet the molecular mechanisms guiding their self-assembly remain elusive. Here, we report a disulfide‑sticker strategy in the recombinant scallop adhesive protein Sbp9Δ. Dynamic disulfide bonds, acting synergistically with Ca2+ coordination, orchestrate the multiscale hierarchical self-assembly of Sbp9Δ by modulating its conformational heterogeneity. Spectroscopic and scattering analyses reveal that disulfide formation acts as a covalent sticker, rigidifying Sbp9Δ into β-sheet-rich rod-like nanostructures, which direct orderly aggregation into extensive two-dimensional networks. The resulting coating exhibits robust wet adhesion across diverse substrates, accompanied by intrinsic antioxidant activity. As a proof of concept, the biocompatible Sbp9Δ coating markedly promotes hair regeneration by enhancing angiogenesis, stimulating follicular cell proliferation, and effectively scavenging reactive oxygen species (ROS), exhibiting superior efficacy compared with minoxidil. In a mouse model of androgenetic alopecia, the Sbp9Δ coating activates the follicular niche through the upregulation of Wnt signaling and the downregulation of calcium signaling, leading to robust hair follicle activation. By integrating insights from marine biology, biophysics, and materials science, this work elucidates a disulfide-mediated assembly paradigm in marine adhesives and translates it into a functional strategy for hair regeneration.
Porous liquids (PLs) combine the properties of permanent porosity with fluidity, offering a unique class of materials for selective gas capture and separation in solution. Here, we report a Type II PL formed by dissolving a shape-persistent, purely hydrocarbon molecular cage (1) featuring an intrinsic cavity in a sterically bulky, size-excluded solvent. Structural analysis, molecular dynamics (MD) simulations, and positron annihilation lifetime spectroscopy (PALS) unambiguously demonstrate effective solvent exclusion from the intrinsic cage cavity and preservation of permanent, cage-derived porosity in the liquid state. The hydrocarbon cage exhibits a strong physisorption affinity for CO2 in the solid state (Qst = 30-40 kJ mol-1), arising from quadrupolar interactions under Å-scale confinement. As a proof-of-concept application illustrating how PLs can be tailored toward specific molecular separations, the resulting Type II PL was evaluated for ethylene/ethane separation, one of the most challenging hydrocarbon separations. The design of a purely hydrocarbon cage with a cavity shape and size matched to C2 hydrocarbons, together with the identification of a compatible sterically bulky, size-excluded solvent, affords a molecularly sieving PL that selectively uptakes ethylene over ethane. The PL achieves iterative enrichment to ∼90% ethylene purity from an equimolar ethylene/ethane mixture through sequential adsorption-desorption cycles under mild thermal conditions. The study establishes purely hydrocarbon organic cages as modular building blocks for Type II PLs and demonstrates how intrinsic cage size and shape, and solvent exclusion can be rationally designed to adapt PLs to perform challenging hydrocarbon separations.
Psychotropic medications remain foundational in psychiatric care, yet the neurophysiological mechanisms through which they exert therapeutic and adverse effects are still poorly characterised, limiting the field's ability to optimise treatment selection and monitoring. Electroencephalography (EEG) offers a non-invasive, real-time window into brain function that could support more precise, mechanism-informed prescribing; however, progress has been constrained by the absence of sufficiently large and systematically analysed pharmaco-EEG datasets. In this cross-sectional observational study, we analysed over 24,000 clinical EEG recordings (∼6000 h of data) obtained across a wide range of psychiatric diagnoses and medication regimens. We compared more than 75,000 spectral, connectivity, and nonlinear EEG features across major drug classes, including benzodiazepines, SSRIs, antipsychotics, and anticonvulsants. Dimensionality-reduced analyses revealed robust, class-specific neurophysiological signatures that can be linked to psychotropic drugs' mechanisms of action: benzodiazepines increased beta and decreased theta-alpha power; SSRIs enhanced gamma-band coherence; and antipsychotics and anticonvulsants produced marked slow-wave amplification and reductions in signal complexity. All results are made publicly accessible through an interactive resource (BrainwavesRX), enabling clinicians and researchers to explore medication-specific EEG effects at multiple levels of granularity. By establishing a population-level reference atlas of psychotropic medication effects on human neural dynamics, this study provides an important foundation for future studies leveraging EEG to predict treatment response, detect insufficient or excessive pharmacological effects, and ultimately advance the development of individualised, data-driven psychiatric care. The publication was prepared as part of Foundation of Polish Science's Proof of Concept (FENG.02.01-IP.05-0010/24) and BRAINCITY IRAP (FENG.02.07-IP.05-0179/23) projects.
Finding suitable therapies for treatment-refractory neuropsychiatric disorders constitutes a major goal for translational neuroscience. Deep brain stimulation shows promise for treatment resistant depression, but treatment efficacy varies substantially across patients. Objective, electrophysiologically driven strategies to optimize deep brain stimulation for treatment resistant depression could greatly improve clinical efficacy by minimizing the trial-and-error approach needed to personalize stimulation settings. This may not only reduce the delay between the start of the treatment and symptom improvement, but also enable acute, real-time verification of circuit engagement, advancing our understanding of the mechanism mediating antidepressant effects. Here, we investigate whether cerebro-cerebral evoked potentials elicited through different deep brain stimulation configurations could be used to guide stimulation personalization for treatment resistant depression. Cerebro-cerebral evoked potentials offer a fast, objective way to identify regions engaged by stimulation, revealing the effective connectivity pattern of the stimulated location. Data were collected from eight patients with treatment resistant depression who received dual bilateral deep brain stimulation devices targeting the subcallosal cingulate and ventral capsule/ventral striatum. During an initial in-hospital monitoring period, single-pulse electrical stimulation was delivered through the deep brain stimulation devices and cerebro-cerebral evoked potentials were recorded through temporary stereo-electroencephalography probes across fronto-temporal regions. Patients underwent several outpatient stimulation programming sessions over the course of 9 months to identify the stimulation configurations leading to the greatest improvement in depressive symptoms. We retrospectively analysed cerebro-cerebral evoked potentials obtained in response to stimulation of different stimulation configurations to identify features distinguishing the clinically effective configurations. The deep brain stimulation configurations leading to the greatest improvement in depressive symptoms were associated with significantly larger evoked potentials in the orbitofrontal cortex and showed an increased number of evoked potentials across dorsal and ventral prefrontal regions. Waveform similarity analysis revealed a gradient in therapeutic effects, such that multiple alternative stimulation configurations led to similar symptom improvement. The vast deep brain stimulation parameter space might contain a configuration subspace defined by comparable therapeutic effects. In addition, evoked potentials obtained from single-pulse and from bursts of high-frequency stimulation displayed similar spatial patterns, suggesting that either method might be able to identify the configuration best engaging the circuit mediating the clinical response. Together, these findings provide proof-of-principle evidence that stimulation-evoked prefrontal responses reflect network engagement associated with antidepressant effects. Cerebro-cerebral evoked potentials may offer an objective and acute strategy to guide contact selection in deep brain stimulation for treatment resistant depression.
Complex coacervates (CCs) effectively concentrate biomolecules via liquid-liquid phase separation; however, extracting analytes for detection remains challenging because of the high ionic strength required to dissolve the CC phase. Here, we demonstrate a workflow integrating CC-based pre-concentration with nanopore sensing, which inherently operates under high-salt conditions. We investigated CCs formed by polycations (PLL, PDDA) and nucleotides (ATP, ADP) for the enrichment of microRNAs (miRNAs). While these CC components inhibited reverse-transcription polymerase chain reaction (RT-PCR), the dissolved phase was compatible with lipid bilayer-based α-hemolysin nanopore detection. Optimization of the polymer composition (S-PDDA/ATP) minimized pore clogging and noise. Using specific DNA probes, we successfully detected miRNA enriched in the CCs immediately after salt-induced dissolution. This study establishes a proof of concept for using phase separation as a seamless pre-concentration strategy for nanopore-based biosensing.
Thermogalvanic waste-heat harvesting offers a promising route to the productive utilization of low-grade thermal energy, but current cells remain limited by low thermopower and power output. Here, we report a thermogalvanic electrolyte that inserts the canonical Fe(CN)63-/4- redox cycle within an optimized NH4OH-CH3COOH alkaline environment. Our results show that the optimal mixture establishes differential formation energies between the hexacyanoferrate redox pair, thereby amplifying the configurational entropy difference between redox states and boosting the thermopower from 1.48 to 2.64 mV K-1 in a symmetric graphite cell, with a normalized power density of ∼1.5 mW m-2 K-2 sustained across ΔT = 10-50 K. We show that placing the optimized electrolyte within an asymmetric copper-graphite electrode setup leads to a hybrid mechanism of galvanic-thermogalvanic (gTg), which produces a total output substantially exceeding the sum of isothermal galvanic and electrode-analogous thermogalvanic cell outputs, while also demonstrating significantly extended operational longevity over isothermal discharge. A 50-cell proof-of-concept device mounted on a PC tower produces 42 V and 160 mW total output, of which 7 V and 37.6 mW are derived from the thermal contribution.