Browse Articles

Turning Thermal Roll‐Off Into Thermal Boost in Perovskites via Heat‐Activated Interfacial Polarization

ABSTRACT For semiconductor devices operating under elevated temperatures, especially in high‐insolation regions, the intrinsic thermal degradation of optoelectronic performance poses a fundamental challenge. Herein, we report a heat‐activated interfacial polarization strategy that uniquely converts this performance loss into a substantial gain. By incorporating electron‐deficient N‐heteroaromatic cations into lead–iodide perovskites, we induce a thermally driven electron cloud deformation at the organic–inorganic interface. This process establishes a reversible interfacial dipole that reshapes the electrostatic landscape, lowering charge‐transport barriers and effectively screening deep trap states. As a result, carrier mobility increases by ∼100‐fold and trap density reduces by ∼80% upon heating from 300 to 363 K, directly inverting the conventional thermal‐roll‐off trend. The universality of this mechanism is demonstrated across 1D, 2D, and 3D perovskite systems, all exhibiting pronounced photocurrent enhancement with temperature. As a proof‐of‐concept application, fire‐warning detectors based on this strategy achieve 100‐fold and 1000‐fold enhanced responsivity to flame‐signal infrared irradiation and smoke‐marker NO 2 gas, respectively, under identical heating conditions. This work establishes thermal energy as a functional asset rather than a performance liability, opening new avenues for thermally robust and smart optoelectronics.

Deep learning architectures for EEG-based classification of Dravet syndrome: A comparative study of pre-trained and non-pretrained hybrid CNN-LSTM models

Objective This study explores the potential of artificial intelligence (AI) using a hybrid deep learning Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) framework, for EEG-based classification and analysis of Dravet Syndrome (DS). Method The study cohort comprised nine pediatric patients with DS, confirmed through either a heterozygous pathogenic mutation in the SCN1A gene or a clinical diagnosis consistent with established diagnostic criteria. In addition, EEG recordings from age-matched healthy control subjects and pediatric patients with non-Dravet epilepsy (“abnormal” EEG) were included. Data on demographic information, seizure characteristics, developmental skills, cognitive functions, and genetic results were gathered from patient records. EEG recordings were analyzed using a subject-independent leave-one-subject-out validation strategy, spatial and temporal features by employing this model on preprocessed EEG data, effectively differentiating DS patients from Abnormal cases and healthy controls. Result Among the evaluated CNN-LSTM models, the pre-trained architecture achieved superior performance with improved stability across most subjects, with an overall accuracy of 85%, balanced accuracy of 85%, a macro-averaged F1-score of 0.85, and a macro-averaged ROC–AUC of 0.87, demonstrating stable performance for multi-class EEG classification of DS, Abnormal, and control subjects. The non-pretrained model showed reduced sensitivity and increased inter-class confusion, particularly for DS and Abnormal classes. Conclusion This study demonstrates that a pre-trained CNN-LSTM framework can support automated EEG-based classification of DS-related patterns as a proof-of-concept methodological approach, even in the context of limited subject availability. EEG-specific pretraining improves classification consistency and feature separability compared with training from scratch, highlighting the value of representation learning for rare epilepsy syndromes. Larger multi-center datasets and prospective validation will be required to assess robustness, generalizability, and clinical utility.

A hybrid Monte Carlo–LLM framework quantifies model- and architecture-dependent variability in synthetic-patient simulations

Low‐Dimensional Perovskites for Neuromorphic Vision Computing

ABSTRACT Neuromorphic computing offers a promising route to overcome the energy and data‐movement limitations of von Neumann architectures, particularly for in‐sensor and edge‐intelligence applications. Achieving such systems relies on functional materials that intrinsically integrate sensing, memory, and computation. Metal halide perovskites have emerged as a compelling platform due to their outstanding optoelectronic properties, tunable low‐dimensional structures, and pronounced ion‐migration dynamics. This review focuses on low‐dimensional perovskite nanostructures for neuromorphic vision devices. We summarize recent advances in the synthesis and integration of zero‐, one‐, and two‐dimensional perovskites, and analyze ion‐migration‐driven optoelectronic and memristive mechanisms underlying synaptic and neuronal behaviors. By correlating material and device characteristics with neural network algorithms, we discuss pathways toward efficient neuromorphic computing. Finally, representative opportunities for perovskite‐based in‐memory, in‐sensor, and near‐sensor computing are discussed, highlighting key challenges toward monolithic sensing–memory–computing integration.

Global, Regional, and National Burden of chronic kidney disease in older adults from 1990 to 2021: Results from the Global Burden of Disease Study 2021

Background Drawing on data from the Global Burden of Disease (GBD) 2021 study, this research provides the first systematic assessment of the burden and trends of chronic kidney disease (CKD) among the global population aged 75 years and over between 1990 and 2021. Unlike previous studies covering the entire age spectrum, this study focuses on the age group with the highest concentration of disease burden and the greatest health vulnerability, with the aim of revealing the unique epidemiological patterns specific to this population. Methods The study methodology involved extracting data on the prevalence, incidence, mortality and disability-adjusted life years (DALYs) for chronic kidney disease (CKD) among people aged 75 years and over in 204 countries and territories from the GBD 2021 database. All reported rates are age-standardized. We calculated estimated annual percentage changes (EAPCs) to analyze trends and examined the association between the disease burden and the Sociodemographic Index (SDI). Results The study found that in 2021, approximately 127 million people aged 75 years and over worldwide were living with CKD. Between 1990 and 2021, the age-standardized prevalence declined slightly (EAPC = −0.06%; 95% UI: −0.09% – −0.03%), whilst incidence, mortality and DALY rates all rose significantly (EAPCs of 0.50%; 95% UI: 0.47%–0.53%, 1.55%; 95% UI: 1.48%–1.61% and 1.07%; 95% UI: 1.02%–1.12%, respectively), demonstrating the key phenomenon of ‘prevalence–mortality trend divergence’. The relationship between the burden of disease and socio-economic development is complex: regions with low SDI bear the heaviest burden of mortality, whilst regions with high SDI have experienced the fastest growth in mortality rates. The study also revealed significant heterogeneity in the burden across age, gender and geographical regions. Conclusions The burden of chronic kidney disease (CKD) among the global older adult population is rapidly shifting from a pattern of ‘high prevalence’ to one characterised by ‘high incidence, high mortality and high disability’, with the underlying drivers exhibiting fundamental differences across regions at various stages of development. This necessitates that public health strategies move beyond a ‘one-size-fits-all’ approach and instead develop highly age-specific and contextually tailored interventions. This study provides a detailed map for understanding the epidemiology of CKD in the context of extreme population ageing, and offers crucial evidence for the allocation of resources and the formulation of policies.

Efficient mechanical casting defect detection based on state space modeling and multiscale attention

Geometric Artifacts in Time‐of‐Flight Mobility Measurements of Perovskite Single Crystals

ABSTRACT Carrier mobility is an important parameter of metal halide perovskites that determines carrier diffusion length in solar cells, response speed of detectors, and other device characteristics. Time‐of‐flight (ToF) is widely used to evaluate carrier mobilities in thick perovskite crystals and is often regarded as a direct probe of long‐range drift transport. Here we show that extracted ToF mobilities are sensitive to the electrode geometry. The concentration of electric field lines near electrode edges can dramatically shorten the transit time. ToF mobilities can be overestimated by up to 10 times by the distorted electric field in devices with electrode diameters smaller than the crystal thickness. An electrode‐diameter‐to‐crystal‐thickness ratio larger than 8 is required to obtain consistent charge transit time and thus the carrier mobility. Using a guard ring biased at the same potential as the electrode, the minimum electrode‐diameter‐to‐crystal‐thickness ratio can be reduced to 2.5.

Cognitive-behavioral therapy focused on inhibitory learning, for adults with avoidant/restrictive food intake disorder (ARFID): Study protocol of a prospective study

Objective Currently, there are no evidence-based treatments available for adults with avoidant/restrictive food intake disorder (ARFID). The present paper describes the design of a study evaluating a cognitive-behavioral therapy (CBT) protocol for adults with ARFID, with a focus on exposure using inhibitory learning principles. Method This multicenter study uses a prospective, uncontrolled, repeated-measures design. A total of 120 adults (aged ≥ 18 years) with ARFID will be included via 11 participating treatment centers throughout the Netherlands. Participants will receive a manualized treatment of 25 weekly sessions. Assessments will be conducted at baseline, post-treatment, and at 1- and 12-month follow-ups. The primary outcome is ARFID severity, measured by the Pica, ARFID, and Rumination Disorder Interview (PARDI). Session-level measures of fear and expectancies will be collected throughout the treatment to explore potential mechanisms of change. Treatment effects will be examined across ARFID profiles and comorbid disorders. Discussion This is the first large-scale study to investigate an outpatient CBT program for adults with ARFID. By examining outcomes across ARFID profiles and exploring underlying mechanisms of change, the findings are expected to inform treatment refinement and provide a foundation for future controlled trials. The study has been preregistered in AsPredicted (#212,212) and the trial was registered in the Overview of Medical Research in the Netherlands (NL-OMON6121).

Operational feasibility of drone based BVLOS transport for temperature sensitive oncosurgical specimens from a secondary to tertiary hospital corridor in India

Metabolic Reprogramming by Engineered Probiotics Potentiates Tumor Chemodynamic Immunotherapy

ABSTRACT Engineered bacteria hold promise for remodeling immunosuppressive tumor microenvironments through innate immunogenicity and localized therapeutic delivery. While bacterial‐derived metabolites are increasingly recognized as key mediators, their specific roles in interkingdom crosstalk remain underexplored. Here, we develop a programmable probiotic platform leveraging Lactobacillus gasseri (LG)‐tumor metabolic interplay to potentiate bladder cancer therapy. The selected LG strain demonstrates superior tumor‐colonizing ability and intrinsic H 2 O 2 /lactate biosynthesis, creating an optimal tumor microenvironment for hemoglobin‐modified MnOx nanoparticles to enhance chemodynamic therapy efficacy. Mechanistically, microbial metabolites, including L‐leucine, orchestrate neutrophil phenotypic reprogramming by suppressing pro‐angiogenic dcTRAIL‐R1 + neutrophils while activating antigen‐presenting CD74 + neutrophil populations. The engineered system elicites coordinated immunomodulation through multiple mechanisms: (1) promoting dendritic cell maturation, (2) increasing CD74 + neutrophil populations, (3) inducing macrophage polarization from M2 to M1 phenotypes, and (4) enhancing tumor infiltration of CD8 + T cells and natural killer cells. This study reveals that bacteria‐tumor metabolic crosstalk upregulates beneficial metabolites, notably leucine, which promotes phenotypic reprogramming of neutrophils toward the antigen‑presenting CD74 + subset, thereby bridging innate metabolic regulation with adaptive antitumor immunity. This finding goes beyond the material‐centric logic of previous probiotic‐nanomaterial systems and establishes a metabolism‐centric framework for bacteria‑mediated cancer immunotherapy.

Correction: Exploring motor variability in adults with severe athetoid or ataxic cerebral palsy: Impact on error-based and reward-based learning

Characteristics and patterns of sweetener use in ultra-processed food products available in Brazilian supermarkets

Abstract Sweeteners are non-sugar food additives that provide a sweet taste to products and, according to the Nova Classification, they are markers of ultra-processing. This study aimed to characterize the use of sweeteners in ultra-processed food products available for consumption in Brazil, pre-labeling-reform. Based on data from about 10,000 packaged products with lists of ingredients collected in Brazilian supermarkets in 2017, this study identified 910 products (9.2%) whose list of ingredients included sweeteners. The distribution of the number and types of sweeteners in the products was analyzed, and factor analysis was performed to identify the patterns of sweetener use. Sweeteners were used in products such as non-carbonated beverages, sweets in general, and sweetened dairy beverages; sucralose was the most prevalent sweetener (53%), followed by acesulfame potassium (50%) and sodium cyclamate (33%). These additives were mostly used together; that is, several products contained a combination of two or more types of sweeteners, and there were products that alone were formulated with four or more sweeteners. Factor analysis identified four different patterns of additive use, and sweet cookies, tabletop sweeteners, and cakes and sweet pies were the subgroups that stood out when associated with the patterns of sweeteners use.

Stabilizing Lattice Oxygen Redox via Thermally Driven La‐Stratification for Ultra‐Stable Li‐Rich Cathodes

ABSTRACT Lithium‐ and manganese‐rich layered oxides (LMR) are promising cathodes for next‐generation lithium‐ion batteries owing to their high capacity and low cost. However, severe capacity fading and voltage decay caused by irreversible lattice‐oxygen loss remain major obstacles to commercialization. Herein, a thermally driven stratification (TDS) strategy is developed to simultaneously construct a uniform La 2 O 3 surface coating and a concentration‐gradient La distribution in the bulk. Advanced characterization combined with DFT calculations reveals that bulk La stabilizes the chemical states of TMs and lattice oxygen, their local electronic structures and coordination environments, and the overall crystallographic framework, while enhancing Li + diffusion kinetics. Meanwhile, the surface La 2 O 3 layer promotes the formation of a stable cathode‐electrolyte interphase and suppresses microcrack generation, thereby preserving structural integrity during cycling. As a result, the optimized LMR‐TDS cathode delivers a high initial discharge capacity of 287.5 mAh g −1 with an initial Coulombic efficiency of 88.50%, retains 90.37% of its capacity after 500 cycles at 1 C, and exhibits an ultralow voltage decay of only 0.967 mV per cycle. Furthermore, an LMR‐TDS||graphite pouch cell achieves 84.67% capacity retention after 1000 cycles. This work provides an effective surface‐bulk co‐engineering strategy for simultaneously mitigating capacity fading and voltage decay in LMR cathodes.

Personality traits have an effect on pain-related psychological variables in patients with chronic low back pain

Introduction An association between personality factors and pain experience has been investigated. However, the direct contributions of personality traits by the Maudsley Personality Inventory to clinical pain outcomes in patients with chronic pain remain unclear. The Maudsley Personality Inventory is a self-report questionnaire used to assess extroversion, neurotic tendencies, and lying or exhibitionistic tendencies. The present study aimed to investigate whether personality traits influenced with the pain-related psychological variables in patients with chronic secondary low back pain (CLBP). Methods One hundred fifteen consecutive outpatients with CLBP were included. Personality traits were measured by using the Maudsley Personality Inventory to assess extroversion, neurotic tendencies, and lying or exhibitionistic tendencies. The association of Maudsley neurotic tendency score and pain-related variables was analyzed and then performed a path analysis. Eleven patients (9%) were the biased persons with frequent lying. Results The pain-related variables showed no significant differences between the persons with frequent lying and those with normal. The Maudsley neurotic tendency score was significantly associated with Pain Catastrophizing Scale, Hospital Anxiety and Depression Scale, Pain Self-Efficacy Questionnaire, Athens Insomnia Scale, and EuroQol-5 Dimensions-3 level. The unstandardized coefficients for Maudsley neurotic tendency score were small, compared to pain-Numerical Rating Scale in each outcome. Conclusions These results suggest the presence of neurotic tendency could have an impact on the health outcomes in patients with CLBP, but the impact was small.

Screening of the antiproliferative activity of lycopene isomers in a panel of human cancer cell lines: Lycopene Z-isomers exhibit greater activity than the all-E-isomer

Abstract Lycopene occurs as multiple geometrical isomers, whereas most studies on its cancer-related effects have focused on the all- E -isomer or on preparations with an undefined isomer composition. In this study, the antiproliferative activities of all- E -isomer-rich lycopene preparation ( E -LYC) and Z -isomer-rich lycopene preparation ( Z -LYC) were compared using a panel of 102 human cancer cell lines under identical experimental conditions. Z -LYC showed a broader antiproliferative profile than E -LYC, with IC 50 values within the tested concentration range (3.16–31,600 nM) in 91 and 16 cell lines, respectively. Tissue sensitivity analysis indicated that lymphoid malignancies and leukemia were relatively sensitive to Z -LYC, with additional sensitivity observed in bone, soft tissue, ovarian, and testicular germ cell tumors. Phenotypic similarity analysis further showed broader correlations for Z -LYC than E -LYC with reference anticancer agents, suggesting a more distinct biological response profile at the cellular level. Preliminary molecular docking simulations also suggested that lycopene Z -isomers may interact more favorably than the all- E -isomer with selected cancer-related proteins. These findings indicate that lycopene Z -isomers exhibit broader antiproliferative activity than the all- E -isomer in this in vitro screening platform and warrant further mechanistic and in vivo studies.

Multidimensional Symmetry Engineering of Metasurfaces for Circular Dichroism and Advanced Photonics

ABSTRACT Chiral metasurfaces provide a powerful artificial platform for manipulating the spin, phase, and amplitude of light at the subwavelength scale. The ability to generate strong circular dichroism (CD), optical activity, and spin‐selective light‐matter interaction creates new opportunities in chiral sensing, emission, and nonlinear photonics within flat optics. However, navigating the vast and complex geometric parameter space to maximize chiroptical responses remains a formidable challenge. To address this problem, we categorize the core design principles from the perspective of symmetry breaking including in‐plane symmetry breaking, out‐of‐plane symmetry breaking, and low‐symmetry lattice engineering. Furthermore, this review highlights the transformative role of machine learning and inverse design in overcoming the computational bottlenecks of traditional heuristic optimizations. We then review the practical applications of these chiral platforms across both linear and nonlinear regimes, focusing on imaging and holography, chiral sensing and polarization detection, circularly polarized light (CPL) emission, and advanced nonlinear chiral functionalities. Finally, major challenges and future research directions are outlined to guide the rational design and scalable implementation of chiral metasurfaces in next‐generation photonic systems.

Mixed feelings: Unintended consequences of HIV outreach care in Zimbabwe

Background Decentralization of antiretroviral therapy (ART) brought treatment to millions of people in Sub-Saharan Africa. However, the implications of such decentralization are still not fully understood. Methods The study included 60 semi-structured interviews with community leaders, healthcare providers, patients, and community members served by a rural mission hospital in Zimbabwe, conducted in January-March 2019. Interviews were transcribed and translated into English and coded using an iterative codebook. Coded extracts were grouped into themes and categories, systematically using QDA Miner qualitative analysis software. Findings The study reveals that treatment-for-all policies and decentralization of ART have indeed improved access to care (as experienced by the study participants). However, the study shows that these policies also had unintended negative consequences. Stigma and complex social relations significantly affect the practices and experiences of ART outreach care, for both patients and healthcare providers, and may hamper attempts to reduce stigma as well as increase physical and social barriers to accessing ART. Conclusions The study’s results highlight the need to understand the consequences of the decentralization of HIV care, as well as the barriers and facilitators associated with ART outreach in order to improve quality of care and provide true accessibility to HIV care for all.

Metabologenomics-guided bioprospecting of blue amazon microbial resources toward drug discovery

A Dopamine Driven Dual‐Amplifier Strategy for High Performance Bioorganic Piezoelectrics via Secondary‐Structure Modulation and Synergistic Molecular Dipoles

ABSTRACT Bio‐proteins with intrinsic piezoelectricity are highly promising for bioelectronics due to their tunable conformations, biocompatibility, and biodegradability. However, their practical applications are severely constrained by difficulties in regulating piezoelectric domains and inherent mechanical brittleness. In this study, we propose a small‐molecule dual‐amplifier strategy to achieve high performance piezoelectric biomaterials. By introducing a dopamine‐mediated modulation approach, a silk fibroin‐based film with an enhanced piezoelectric coefficient of up to 12.7 pC N − 1 is obtained. This performance boost is attributed to a dual mechanism: the dopamine‐induced promotion of β‐sheet formation in silk fibroin, which strengthens its intrinsic piezoelectricity, and the synergistic contribution of piezoelectric dipole moments from dopamine. In addition, the film exhibits superior mechanical robustness and flexibility, tunable stability in aqueous environments, as well as excellent in vitro/vivo biocompatibility. When applied to the sensing of temporomandibular joint motion and oral occlusal contact patterns, the resulting sensors demonstrate high sensitivity and long‐term stability. Furthermore, the generated voltage signals can be effectively encoded and converted into digital information, facilitating data processing and analysis. These results demonstrate small‐molecule modulation represents a reliable approach for enhancing the piezoelectricity of structurally complex proteins, offering a simple and innovative pathway toward the development of high‐performance bio‐piezoelectric materials for digital healthcare.

Association between COMISA and cardiovascular disease: Evidence from the TURKAPNE registry

Background Comorbid insomnia and obstructive sleep apnea (COMISA) is increasingly recognized as a distinct clinical entity, yet its relationship with cardiovascular disease (CVD) remains incompletely understood. We aimed to investigate the association between COMISA and CVD in a large clinical sleep cohort. Methods Using data from the TURKAPNE registry, we analyzed 12,715 adults referred for sleep evaluation and classified participants into four mutually exclusive sleep phenotypes: neither OSA nor insomnia (n = 910), insomnia only (n = 388), OSA only (n = 8,142), and COMISA (n = 3,275). The prevalence of CVD was compared across groups. Multivariable logistic regression models were used to examine associations between COMISA and CVD after adjustment for age, sex, body mass index, education level, smoking status, airway disease, diabetes mellitus, and psychiatric comorbidity. Results The prevalence of COMISA was higher among individuals with CVD compared with those without CVD (31.6% vs. 22.7%; p < 0.001). In contrast, the distribution of insomnia alone and OSA alone showed only minor differences by CVD status. In multivariable analysis, CVD was independently associated with COMISA (odds ratio 1.108, 95% confidence interval 1.006–1.220; p = 0.038), although the magnitude of this association was modest. Female sex, diabetes, airway disease, psychiatric disease, lower educational status, and current smoking were also independently associated with COMISA. Conclusion In this large registry-based cohort, COMISA was more prevalent among individuals with CVD, supporting the concept that it represents a clinically distinct phenotype with an increased cardiometabolic burden. However, the modest effect size suggests that COMISA is influenced by a broader interplay of behavioral and metabolic factors.