Search Results (181)

Engagement in the arts, particularly developing skills in an art form, represents a cognitively rich activity involving attention, memory, executive function, and sensorimotor coordination. Despite widespread assumptions that artistic abilities such as drawing are innate, they are highly trainable through targeted learning. Different techniques exemplify how structured observational drawing exercises can reshape perceptual and cognitive processing. For example, the negative space drawing technique directs attention to the shapes surrounding an object rather than the object itself. Specific techniques can map onto underlying cognitive processes, and this article examines the translational potential of learning to draw as a cognitive intervention. Due to the Arts’ aesthetic nature, the benefits extend beyond cognitive and can impact modifiable salutogenic factors at large. A toolkit of drawing techniques is provided, with information on the underlying cognitive processes. By connecting the cognitive neuropsychology of observational drawing to cognitive aging, this work contributes to a growing body of evidence supporting the arts as a vehicle for brain health, with particular promise in an aging global population. As technology transforms the landscape of arts and aesthetics, the cognitive value of embodied artmaking is underscored. Full article

The European Union now routinely leverages economic governance to tackle strategic vulnerabilities caused by geopolitical rivalry, foreign dependencies, and supply chain shocks. This article analyses this shift, exploring how the EU adapts its economic toolkit and what restricts its capacity to act as a geoeconomic power. It builds an analytical framework connecting external pressures, strategic vulnerabilities, policy choices, and institutional barriers. Methodologically, the study combines qualitative document analysis of EU policy frameworks with trade metrics and evidence from the Geoeconomic Interconnectivity Index. The findings show a clear expansion in investment screening, anti-coercion tools, targeted industrial policy, and supply-chain diversification—all aimed at safeguarding core sectors and curbing asymmetric exposure. These steps mark a departure from purely regulatory-market logic towards a hybrid model blending market openness, defensive controls, and capacity-building. Persistent institutional splits, conflicting national priorities, technological gaps, and reliance on foreign markets limit the effectiveness of this transition. Ultimately, the EU’s evolving geoeconomic stance aims not for total self-sufficiency, but for the deliberate, strategic management of interdependence. Full article

Drosophila melanogaster shares approximately 75% of human disease-related genes and possesses sophisticated genetic toolkits, including GAL4/UAS, CRISPR-Cas9, and RNA interference (RNAi), making it a rapid, cost-effective, and genetically tractable in vivo platform for natural products (NPs) discovery. This review systematically summarizes the modeling strategies, pathological mechanisms, and therapeutic applications of Drosophila models for six major human diseases, including type 2 diabetes, nephrolithiasis, inflammatory bowel disease, cancer, Alzheimer’s disease, and Parkinson’s disease. Cross-disease analysis identifies five evolutionarily conserved signaling networks—IIS/PI3K/Akt/FOXO, JNK/JAK/STAT, Nrf2/Keap1, mTOR/TORC1, and IMD/Toll—as common molecular targets of bioactive NPs, providing a unified mechanistic framework for understanding their multi-target pharmacological activities and broad therapeutic potential. Critically, we propose a generalizable integrated stepwise pipeline: high-throughput fly screening of crude extracts, bioassay-guided isolation of active monomers, genetic mechanistic dissection via RNAi and mutant rescue, and layered validation in human cells and selective mammalian models. This pipeline addresses key challenges in NPs research, including the identification of bioactive constituents and mechanistic validation, while improving screening efficiency and translational potential. Overall, this review establishes a multi-disease-applicable framework linking disease modeling, conserved signaling mechanisms, and translational pharmacology, providing practical guidance for future mechanism-driven NP discovery and preclinical development using Drosophila. By leveraging Drosophila genetics to bridge evolutionary conservation and human pathology, this framework offers a powerful, paradigm-shifting strategy to accelerate mechanism-driven NP discovery and preclinical development. Full article

Search-and-rescue (SAR) missions following earthquakes and other disasters require aerial video perception systems that do more than detect objects in isolated frames. Operators must maintain the identities of access points, vehicles, responders, hazards, and other mission-relevant targets despite UAV ego-motion, dust, debris, occlusion, scale variation, and abrupt scene transitions. This paper presents E’CHIT (Edge-Oriented Colour Histogram Instance-Guided Tracking), a deployment-oriented, operator-centric UAV tracking framework for real-world disaster-response applications. Its primary scientific contribution is an identity-stabilised, detector-assisted tracking methodology. YOLOv8-seg proposals trained on D’RespNeT initialise and refresh tracks; a Custom-RE3 recurrent module propagates target states through short detector dropouts; and a lightweight EOMC verifier, based on edge orientation, mean colour, and shape consistency, determines whether tracks should be accepted, refreshed, or reacquired. A scene-cut watchdog that combines luminance mean absolute difference (MAD) with HSV histogram divergence prevents stale identities from carrying over after hard edits or sudden feed changes. Custom-RE3 is the continuation module implemented and evaluated in this study. The surrounding E’CHIT wrapper follows an initialise–reseed–verify–reset cycle and is tracker-adaptable at the software-interface level: another compatible SOT or MOT continuation module can be integrated through adapter modifications, state and bounding-box conversion, and method-specific retuning, followed by independent validation. All reported quantitative results therefore apply to the Custom-RE3 implementation. D’RespNeT, the optional reinforcement learning (RL) warm start, the HUD, and the deployment stack support this central tracking contribution. D’RespNeT provides 28 polygon-annotated SAR classes. An author-developed PPO/SAC script is used only during offline detector training. In the reported runs, it produces different early optimisation trajectories for selected difficult or under-represented classes, while the default supervised schedule remains the strongest final global mAP reference. No RL policy runs during deployment; the detector architecture, parameter count, and inference graph remain unchanged. Evaluation on D’RespNeT and authentic disaster-response UAV footage shows that E’CHIT increases Success@IoU ≥ 0.5 from 0.62 to 0.79, reduces identity switches by approximately 71%, and maintains real-time 1080p performance, achieving 164–330 FPS for single-target tracking and 24–100+ FPS for end-to-end multi-target operation on an RTX-class GPU using FP16. The VOT2014, NT-VOT211, and VOTS2024 figures reproduce historical result spaces reported in the literature and include a clearly labelled, non-official E’CHIT operating-point marker solely for context. This marker was not produced using the corresponding official datasets, toolkits, reset rules, or submission routes; it is excluded from the primary quantitative claims and must not be interpreted as a leaderboard rank or a protocol-identical comparison. Overall, the system demonstrates how identity-stable UAV tracks can provide actionable operator cues for target monitoring, entry-point assessment, and UAV–UGV/ground-team coordination in cluttered disaster scenes. Full article

Background: In recent decades, the incidence of colorectal cancer (CRC) has been rising worldwide. CRC ranks second in cancer-related mortality. The identification of reliable biomarkers for early diagnosis and prognosis prediction, along with a deeper understanding of the underlying molecular events, holds substantial promise for improving patient outcomes. The tissue inhibitor of the metalloproteinase 1 (TIMP1) gene is overexpressed in various gastrointestinal malignancies and contributes to tumor progression. However, its role in regulating the CRC tumor immune microenvironment (TIME) and its potential as a clinically actionable prognostic biomarker remain unclear. Methods: To probe how TIMP1 acts as a prognosis-related candidate biomarker in colorectal carcinoma, TCGA-derived datasets were adopted to conduct Kaplan–Meier survival assessment. We also investigated the connection between the expression abundance of TIMP1 and the infiltration of immune populations and intratumoral lymphocytes; furthermore, immune checkpoint-related genes were systematically assessed across multiple tumor types via the TISIDB and TIMER2.0 platforms, with particular emphasis on CRC. We adopted the ESTIMATE scoring system to figure out how TIMP1 gene expression correlates with the phenotypic properties of the colorectal-cancer TIME. We relied on the limma toolkit for the screening of differential transcripts from high-TIMP1 and low-TIMP1 cohorts. Enrichment assessments covering Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes entries were then carried out to predict the potential biological pathways associated with TIMP1. We constructed the protein–protein interaction map for TIMP1-interacting partners via the STRING repository. To further explore TIMP1-correlated genes, we performed Venn diagram intersection analysis combined with Spearman’s correlation test. Finally, quantitative reverse-transcription PCR was then implemented to detect TIMP1 messenger-RNA abundance inside the RKO colorectal carcinoma cell line as well as normal colonic epithelial CCD-18Co cells, which offered in vitro experimental verification for our bioinformatic outcomes. Results: According to outcome data, TIMP1 transcripts were markedly up-regulated in CRC specimens and cell lines relative to normal samples. Elevated TIMP1 expression served as a poor-prognosis indicator for overall survival (hazard ratio [HR] = 0.43, 95% confidence interval [CI] = 0.29–0.64, p < 0.001) and disease-specific survival (HR = 0.39, 95% CI = 0.22–0.68, p = 0.001) among colorectal-carcinoma patients. TIMP1-high and TIMP1-low groups exhibited notable differences in immune cell infiltration (CD8⁺ T, macrophage, mast, neutrophil, B, monocyte, dendritic, and CD4⁺ T cells). TIMP1 expression was also significantly correlated with tumor-infiltrating lymphocytes, key immune checkpoint genes (e.g., CD274 [PD-L1] and CTLA4), and immunomodulatory chemokines (e.g., CCL3 and CCL5). Twelve TIMP1-interacting DEGs were selected: COL5A1, FN1, PRG4, and a cluster of nine MMPs (MMP1/2/3/7/8/9/11/13/14), all of which showed significant positive correlations with TIMP1 (r = 0.31–0.63, all p < 0.001). Conclusions: TIMP1 expression correlates with features of the tumor immune microenvironment and extracellular matrix remodeling in CRC, suggesting that TIMP1 shows potential as a candidate biomarker. However, its potential as a therapeutic target warrants further experimental investigation. Full article

Background/Objectives: Latent fingerprints (LFs) have been a cornerstone of forensic identification through conventional friction ridge pattern analysis; however, the microbial communities they harbor remain a largely untapped source of information. Estimation of the time-since-deposition (TsDp) of LFs is still an unresolved challenge in forensic science, as existing 2D and 3D imaging methodologies provide limited temporal resolution. This study investigated whether temporal shifts in LF-associated microbiota could potentially complement dating approaches via genetic analyses. Methods: LFs were collected from two healthy donors from both hands, pre- and post-hand washing, across three time points spanning 192 h (8 days) under monitored, but uncontrolled, indoor conditions. LF friction ridges were optically examined via 2D and 3D imaging, while microbial communities were characterized by 16S rRNA gene sequencing targeting the V3-V4 region. Microbial profiles were analyzed to distinguish temporally stable core microbiota from transient taxa (alpha and beta diversity) and to statistically identify microbial panels associated with donor, handedness, hand-washing status, and/or temporal succession. Results: A stable core microbiota, dominated by Actinobacteria and Bacilli, persisted across donors, handedness, hand-washing status, and time points. Transient low-abundance taxa, including Nitriliruptoria and Phycisphaerae, exhibited temporal fluctuations influenced by donor characteristics, hand-washing status, and post-deposition interval. Upon excluding time-invariant stable taxa, donor-specific biological profiles comprising 32 and 28 class-rank taxa were selected for each donor, revealing individualized patterns of microbial dynamics. Conclusions: LF-associated microbiomes contain both stable and temporally dynamic taxa, with the potential to provide personalized biological information for TsDp estimation. These preliminary findings contribute to the molecular toolkit of forensic microbiomics by laying the foundation for prospective multimodal models integrating LF microbial and topographical data to improve the temporal interpretation of crime evidence touched by bare hands. Further validation with broader donor cohorts and environmental conditions are essential before operational forensic implementation. Full article

Long-term sickness absence is a growing public health issue, reducing workforce participation and widening health inequalities. Effective interventions must address both health and workplace factors to enable not only return-to-work but sustained employment. This study evaluated the feasibility of a multi-level workplace intervention to support sustainable RTW in large organizations. A two-arm cluster randomised feasibility trial was conducted in nine UK organizations (≥600 employees). Participants included senior leaders and HR professionals (n = 91), workers on long-term sick leave (n = 112), and line managers (n = 83). The IGLOo intervention combined e-learning for leaders/HR with structured toolkits for workers and managers to support RTW before and after return. Feasibility outcomes included recruitment, retention, engagement, acceptability, and usability. Secondary outcomes included RTW timing, sustained participation, mental health, and workplace factors. A mixed methods process evaluation explored implementation and context. Retention, acceptability, and usability met targets, but recruitment and engagement were lower than expected. Potential mechanisms included improved confidence, communication, and self-management. Organizational systems and pressures affected delivery. Exploratory analyses suggested different patterns of return-to-work trajectories across trial arms. Overall, the intervention was acceptable to participants who engaged with it, but recruitment barriers and organizational constraints require substantial modification before any future efficacy trial. Full article

We argue that the core methods of modern machine learning—conformal prediction, large language models and in-context learning, and generative/diffusion models—are not rivals to Bayesian inference but implementations of it, almost always of its predictive (de Finetti) form rather than its parameter-centric (prior-to-posterior) form. (1) Background: A quarter-century after Breiman contrasted the “data-modeling” and “algorithmic” cultures of statistics, we revisit that dichotomy and argue that the predictive view dissolves it—both cultures target the one-step-ahead density $p(y_{n+1}\mid y_{1:n})$, differing only in how they compute it. (2) Methods: We organize the modern toolkit around this predictive object and around amortization—replacing per-dataset inference with a single map learned by simulation—using Generative Bayesian Computation (GBC) as the connective spine. (3) Results: Conformal prediction, autoregressive language models, prior-data fitted networks, and score-based diffusion are each shown to construct, calibrate, or sample from the predictive object, summarized in a single “Rosetta” table; because all are fit by proper scoring rules—equivalently, by Bregman divergences—the information-theoretic frame is the natural unifier. (4) Conclusions: The equivalence is exact in idealized limits, asymptotic under exchangeability and its martingale relaxations, and measurably approximate for trained models—a three-grade taxonomy that we make explicit, row by row, and that bounds the thesis: prediction is not attribution, and the predictive view is deliberately silent about causal structures. Full article

This paper illustrates the theoretical framework, the methodological approach, and the primary findings of a project titled MASSTER (Managing(South)Africa-and-Senegal-Sustainability-Targets-through-Economic-diversification-of-Rural-areas), in which higher educational institutions (HEIs) and organizations from Senegal, South Africa, and Europe collaborate with the aim of addressing the nexus between migration, agriculture and development in Sub-Saharan Africa by co-creating evidence-based training, tools, and actions to foster development and co-development while targeting several Sustainable Development Goals (SDGs), namely Zero-hunger, Good-Health-and-Wellbeing, Gender-Equality, Quality-education, Decent-work-and-economic-growth, Responsible-consumption-and-production, all within the frame of Partnership-for-the-Goals. The MASSTER project employs a transdisciplinary and bottom-up approach based on a cross-sectional study conducted in South Africa and Senegal to identify actual challenges, needs, and resources from farmers (n = 737) and students enrolled in agricultural courses (n = 1.013). Findings underpinned the co-creation of the primary project outcomes: training on agritourism development, farm management, income-generating activities, climate change resilience, and food value chain; toolkits designed to boost the adoption of the Whole of Society Approach and to strengthen cooperation between HEIs and local communities; MASSTER Student-and-alumni-tracking-procedure-with-early-warning-mechanism-for-brain-drain; and a MOOC on critical-thinking-and-empowerment. The MASSTER project can have a relevant impact at local and international levels, providing evidence-based tools to be used by HEIs, stakeholders/policymakers, and the scientific community to actively foster development and co-development. Full article

This article reports the design, implementation, and formative perception-based evaluation of an early-stage virtual reality (VR) prototype that integrates a virtual cane, localized haptic feedback, 3D audio, and a three-layer bioinspired sensing framework. The prototype was implemented in Unity 2022.3 using the XR Interaction Toolkit and URP and was structured according to design science research methodology (DSRM). The bat–whisker–contact framework was used as a functional abstraction to organize distal auditory reference or warning, proximal haptic feedback, and contact confirmation; it was not evaluated against a non-bioinspired baseline. The completed evaluation consisted of an anonymous, voluntary, post-use questionnaire administered to 25 sighted participants who could select which visual-input configurations to experience. The analysis focused on reported clarity, tolerability, initial signal interpretability, and design feedback; it did not include objective navigation metrics or assess clinical efficacy, training transfer, accessibility outcomes, or orientation-and-mobility performance in blind or low-vision users. General responses suggested favorable perceived clarity and multimodal usefulness, while cane length, floor-versus-wall/obstacle differentiation, and reported discomfort identified priorities for technical refinement. In the simulated no-vision condition (n = 21), participants reported high reliance on the cane response, whereas reported initial insecurity or doubt and basic mental map ratings remained mixed. The study contributes an early-stage technological artifact and a formative basis for subsequent controlled evaluations with objective performance measures, reference conditions, and target users or orientation and mobility specialists. Full article

Thyroid cancer (TC) is the most common endocrine malignancy, with incidence increasing worldwide. Although most differentiated TCs have a favorable prognosis, radioiodine (RAI)-refractory differentiated thyroid cancer (DTC), BRAF inhibitor-resistant papillary thyroid cancer, and anaplastic thyroid cancer (ATC) remain major areas of unmet clinical need. The sirtuin (SIRT) family of NAD⁺-dependent enzymes has emerged as a multifaceted regulator of TC biology, with isoform-specific dichotomous roles: SIRT1, SIRT6, and SIRT7 act as tumor promoters through engagement of BRAF/MAPK, PI3K/AKT, epithelial–mesenchymal transition (EMT), and Hippo pathways, while SIRT3 and SIRT4 function as tumor suppressors via mitochondrial metabolic regulation. This review synthesizes recent developments that expand the therapeutic landscape: (i) the recognition that SIRT7 functions as a desuccinylase with preclinically identified oncogenic substrates, modifying KIF23 in ATC and LATS1 in PTC; (ii) the emerging roles of isoform-specific SIRT axes, including the NAMPT–SIRT1–PD-L1 axis, SIRT6-associated regulatory T-cell biology, and SIRT2 as a T-cell metabolic checkpoint, as determinants of immune microenvironment state and potential modulators of immune checkpoint inhibitor response; and (iii) the SIRT6–nuclear receptor coactivator 4 (NCOA4) ferritinophagy axis as a supported ferroptosis vulnerability in ATC, with potential but still hypothesis-generating relevance to dedifferentiated and RAI-refractory DTC. Importantly, the therapeutic logic for SIRT6 is disease-state-specific rather than contradictory: SIRT6 inhibition is rationalized in BRAF-driven aggressive PTC and DTC contexts where SIRT6 supports MAPK signaling, EMT, and ferroptosis resistance, whereas in SIRT6-high ATC, the same enzyme’s NCOA4-dependent ferritinophagy activity may instead be exploited to enhance ferroptosis sensitivity. We review the current SIRT modulator pharmacological toolkit—including EX-527, OSS_128167, and emerging SIRT7-selective inhibitors—and identify the substantial clinical translation gap, with no SIRT-targeted clinical trial yet conducted in TC, despite strong preclinical rationale. We outline biomarker-stratified combination strategies with BRAF/MEK inhibitors, multikinase inhibitors, immune checkpoint inhibitors, and ferroptosis inducers, prioritizing biomarker-driven preclinical validation and, where supported by efficacy and safety data, subsequent early-phase evaluation in BRAF V600E-mutant and SIRT6-high thyroid cancer. Sirtuins thus represent a mechanistically promising and potentially biomarker-stratifiable therapeutic hypothesis for difficult-to-treat thyroid cancer; however, clinical translation remains at an early stage and requires validated biomarkers, isoform-selective compounds, and disease-specific in vivo evidence. Full article

Background/Objectives: Proteolysis Targeting Chimeras (PROTACs) are heterobifunctional small molecules that induce ubiquitin–proteasome–mediated degradation of target proteins and have matured from proof-of-concept chemistry to a clinically validated therapeutic modality, with the first Phase 3 readout reported in 2025. A systematic bibliometric analysis covering this pivotal-trial era, however, has been lacking. This study aimed to map the historical trajectory, current research front, and emerging frontiers of PROTAC research. Methods: We analyzed 2630 PROTAC-related publications indexed in the Web of Science Core Collection (WoSCC) from 2001 to 2025 using a combined toolkit of CiteSpace, HistCite, the Alluvial Generator, and R (ggplot2), covering co-occurrence networks, burst detection, keyword clustering, citation historiography, alluvial flow analysis, and reference co-citation timeline visualization. Results: China and the USA led global output, and the Chinese Academy of Sciences, China Pharmaceutical University, and Harvard University were the most productive institutions; the Journal of Medicinal Chemistry was the leading publishing venue, and Alessio Ciulli, Jian Jin, and Craig M. Crews anchored the author network. Keyword burst analysis showed that early research centred on E3 ubiquitin ligase recruitment and small-molecule PROTAC design, whereas the current hotspots, resolved through keyword clustering and co-citation timelines, included structural basis and ternary complex design, EGFR-directed degradation, oral bioavailability optimization, applications in multiple myeloma and Alzheimer’s disease, tumour-targeted delivery, and computational/AI-driven design. Conclusions: This study extends the bibliometric record of PROTACs across 2001–2025 and identifies oral bioavailability, E3 ligase repertoire expansion, and CNS-penetrant degrader design as the emerging frontiers likely to shape the next phase of the field. Full article

Reverse transcription quantitative real-time PCR (RT-qPCR) is a highly efficient and sensitive technique for quantifying gene transcript levels. The accuracy of gene expression analysis depends critically on the selection of appropriate reference genes for normalization, which is essential to minimize technical variation arising from differences in RNA quality, reverse transcription efficiency, and sample handling. Schisandra chinensis is a medicinally important plant with a long history of use in traditional Chinese medicine and has gained increasing global recognition. In recent years, a growing number of studies have employed molecular biology approaches to investigate the molecular mechanisms underlying secondary metabolite biosynthesis in S. chinensis. However, systematically validated reference genes for RT-qPCR analysis in this species have not yet been established. In the present study, the expression stability of eleven candidate reference genes was evaluated across different tissues and under various abiotic stress conditions in S. chinensis using four statistical algorithms: geNorm, NormFinder, BestKeeper, and RefFinder. Comprehensive analysis revealed that PP2A15 and UBC2 were the optimal reference gene combination for leaves; UBC2 and UBC11 for stems; RPL6 and PP2A15 for roots; RPL21 and RPL6 for fruits; and RPL6 and UBC11 as the best-performing pair across all tissue types. Under abiotic stress conditions, UBC11 and UBC2 exhibited the highest stability in both leaves and roots under salt stress; UBC2 and GPN1 proved most stable under alkaline stress; UBC2 and RPL6 were identified as the most suitable combination under drought stress; and UBC2 and UBQ12 demonstrated consistently stable expression across all three abiotic stress treatments. The reliability of these reference gene combinations was further validated by examining the expression profiles of three target genes. Collectively, these findings establish a validated reference gene toolkit for future gene expression studies in S. chinensis, particularly for the functional characterization of genes involved in lignan biosynthesis and abiotic stress responses. Full article

Objective: This study examined the disparities in the prevalence of obesity among children and adolescents from 1990 to 2022. Methods: Crude prevalence estimates were obtained from the World Health Organization’s (WHO) Global Health Observatory, accessible through the WHO Health Equity Assessment Toolkit (WHO HEAT). The study population comprised children and adolescents aged 5 to 19 years. Obesity was defined as a body mass index (BMI) exceeding two standard deviations above the mean, in accordance with the WHO Growth Reference. Descriptive analysis was employed to examine longitudinal trends and disparities in crude obesity prevalence. The dimensions of age (5–9 and 10–19 years) and sex (female and male) were utilised to assess disparities related to obesity. Absolute and relative inequalities were evaluated using difference (D) and ratio (R) summary measures, respectively. Results: In 1990, the crude prevalence of obesity was higher among female children and adolescents (1.45%; confidence interval [CI] 0.38–3.41) compared to their male counterparts (1.07%; CI 0.14–3.40). However, by 2022, the prevalence was higher among males (8.20%; CI 5.15–12.01) compared to females (5.78%; CI 3.57–8.48). Regarding age, the prevalence of obesity in 1990 was 2.24% among 5–9-year-olds, compared with 0.59% among 10–19-year-olds. Both age groups saw an increase in crude obesity prevalence over time, and by 2022, the prevalence of obesity was 12.10% among 5–9-year-olds, compared with 4.04% among 10–19-year-olds. In 1990, the difference and ratio estimates were 0.38 and 1.36, respectively, indicating a higher prevalence among females than males. Concurrently, the ratio decreased from 1.36 in 1990 to 0.71 in 2022, further confirming the shift towards a higher prevalence of male obesity in later years. The difference in obesity prevalence (5–9 years minus 10–19 years) stayed positive throughout the study period. In 2022, the age difference in crude obesity prevalence was +8.07 percentage points, and the ratio was 3.00, indicating that the younger group had a prevalence three times that of the older group. Conclusions: The prevalence of childhood and adolescent obesity increased significantly from 1990 to 2022, with a shift from females to males and a disproportionate impact on younger children. These trends underscore the necessity for targeted public health interventions that address age- and sex-specific disparities. Full article

The escalating global burden of antimicrobial resistance constitutes a public health crisis. The World Health Organization reports that epidemiological models project 10 million deaths attributable to this issue annually by 2050. Among resistant pathogens, metallo-β-lactamase (MBL)-producing organisms represent a clinical challenge, given their consistent association with high rates of morbidity and mortality. This review summarizes effective treatment options against MBL-producing Enterobacterales. In clinical practice, a pragmatic therapeutic decision rule can be applied: when aztreonam–avibactam (ATM–AVI) is accessible and in vitro susceptibility is confirmed, it should be regarded as the preferred targeted regimen for infections caused by MBL-producing Enterobacterales. In settings where ATM–AVI is unavailable, the combination of ceftazidime–avibactam with aztreonam (CAZ–AVI + ATM) remains the treatment of choice, an approach endorsed by current recommendations from the Infectious Diseases Society of America (IDSA) and the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). Critical evaluation of the published evidence is essential to inform the selection of optimal therapeutic regimens for affected patients. Novel antimicrobial agents are currently under clinical development and may broaden the therapeutic toolkit in the near future. Full article