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PubMed2026

Chemical and sensory profiling of fermented, washed, and artificially flavored coffee beans: Insights into flavour quality, authenticity, and food safety implications.

This study establishes an integrated framework combining chemical profiling, sensory analysis, and molecular mechanism evaluation to compare flavour quality and authenticity among fermented, washed, and artificially flavored coffees. GC × GC-TOF-MS and UHPLC-HRMS showed that fermented samples had markedly higher ester and aromatic alcohol levels (total esters 74.5 ± 7.8 mg kg-1; phenylethanol 27.5 ± 3.2 mg kg-1, p < 0.01), enhancing fruity-floral notes. Washed coffees contained the highest organic acid concentrations (45.2 ± 3.8 mg kg-1, p < 0.01), supporting brightness and umami. Artificially flavored coffees exhibited elevated exogenous aromatics (vanillin 21.5 ± 3.1 mg kg-1) but significantly fewer Maillard products (p < 0.05) and reduced flavour retention (55% after 14 days). Molecular docking revealed higher theoretical binding affinities for naturally generated compounds, suggesting a potential molecular basis for their greater sensory persistence. The framework supports constructing coffee quality fingerprints and verifying flavour authenticity.

Flavoring Agents↗

PubMed2026

Recent advances in supramolecular macrocycle-based artificial light-harvesting systems.

Artificial light-harvesting systems (ALHSs) inspired by the antenna function of natural photosynthesis provide molecular platforms for collecting excitation energy and directing it to emissive or reactive acceptors. In many supramolecular ALHSs, however, practical performance is limited by poorly defined donor-acceptor orientation, aggregation-caused quenching (ACQ), interfacial defects, and limited stability in aqueous or complex media. Supramolecular macrocycles-particularly pillar[n]arenes (PAs), cucurbit[n]urils (CBs), calixarenes (CAs), cyclodextrins (CDs), and supramolecular coordination complexes (SCCs)-offer a useful design space because their cavities, pre-organized scaffolds, and reversible non-covalent interactions can confine chromophores, tune local donor/acceptor ratios, and modulate Förster resonance energy transfer (FRET). This Review systematically examines the unique structural advantages and assembly mechanisms of the five macrocyclic families, with an emphasis on their use in constructing ALHSs-from single-step to cascaded FRET-and in advancing aqueous photocatalysis, near-infrared bioimaging, panchromatic fluorescence modulation, and singlet oxygen generation. The resulting structure-property-application framework is intended to guide the rational design of macrocycle-assisted photofunctional materials while avoiding overextension of the photosynthesis analogy.

Journal Article↗

PubMed2026

Music therapy in artificial insemination by husband: Effects on psychological distress and clinical pregnancy rate.

BACKGROUND: Infertility treatment can be psychologically burdensome. Evidence on music listening during artificial insemination by husband (AIH) remains limited. We evaluated whether a standardized periprocedural music intervention reduced psychological distress and explored its association with clinical pregnancy. METHODS: In this single-center, open-label randomized trial, 254 women undergoing AIH were allocated 1:1 to routine care or routine care plus two 30-minute music-listening sessions, immediately before and after AIH. The prespecified primary outcome was the continuous 21-item Depression Anxiety Stress Scales (DASS-21) score at follow-up; clinical pregnancy was secondary. DASS-21 was completed at baseline and at day 35 after AIH. Clinical pregnancy was assessed by ultrasonography at days 30 to 35. RESULTS: Continuous DASS-21 anxiety, depression, and stress scores did not differ between groups after adjustment for baseline scores (all P ≥ .868). Absolute postintervention differences were 0.01 point or less for anxiety and depression and 0.08 point for stress, indicating neither statistical nor clinically meaningful improvement. Clinical pregnancy occurred in 34/127 participants (26.77%) in the intervention group and 14/127 (11.02%) in the control group (exploratory secondary outcome; P = .001). CONCLUSION: The intervention did not improve the primary psychological outcome. The higher clinical pregnancy rate is hypothesis-generating because the trial was not powered for pregnancy, the proposed psychological mechanism was not demonstrated, and nonspecific attention and other unmeasured factors cannot be excluded. Replication using an attention-matched control, immediate state-anxiety and physiological measures, participant-preference assessment, and live-birth follow-up is required.

Humans↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the last 50 years and how well-designed cohort studies will provide us with knowledge for research and practice in the future and aid guideline development. We have included data from a large number of cohorts from every continent that have been used to study the development and/or progression of type 2 diabetes, including cohorts that are general population-based, disease-based, intervention-based and registry-based. We have structured the results from the past 50 years based on the following themes: diagnosis and screening, complications, risk factors and pathophysiology. We also discuss the strengths and weaknesses of observational research when compared with other research designs. Finally, we discuss the emerging and future directions for type 2 diabetes research using cohorts, which include novel developments, such as artificial intelligence, precision health and the exposome. We conclude that cohort research has significantly advanced our understanding of type 2 diabetes and aided guideline development, and complements experimental work, such as human randomised controlled trials and animal studies. Both approaches are essential and complementary in our pursuit to provide a more comprehensive understanding of the development and progression of type 2 diabetes, and to change dogma, practice and policies for better outcomes.

Humans↗

PubMed2026

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗

PubMed2026

Fundamentals of pacemakers ECG interpretation - part 2.

BACKGROUND: Modern pacemakers incorporate arrhythmia-response algorithms, ventricular pacing minimization protocols, and safety mechanisms that generate ECG patterns indistinguishable from pathological AV block, sensing malfunction, or device-mediated tachycardia. Failure to recognize these algorithm-driven signatures leads to unnecessary interventions, misdiagnosis, and inappropriate device reprogramming. This manuscript is the second in a two-part series on pacemaker ECG interpretation. METHODS: We conducted a narrative review of peer-reviewed literature and device-specific documentation on algorithm-driven ECG behavior, synthesizing evidence across arrhythmia recognition, upper rate physiology, ventricular pacing minimization, mode switching, safety mechanisms, and hysteresis algorithms. RESULTS: Pacemaker-mediated tachycardia produces regular paced wide-complex tachycardia locked at the upper tracking rate, initiated by any event with retrograde VA conduction. Ventricular tachycardia is identified by QRS morphology diverging from the known paced pattern, absent pacing spikes, and AV dissociation. Upper rate Wenckebach behavior mimics Mobitz type I AV block; 2:1 upper rate response mimics second-degree AV block. Ventricular pacing minimization algorithms produce isolated nonconducted P waves and prolonged AV intervals that simulate pathological conduction disease. Mode switching causes abrupt rate drops misidentified as output failure. Ventricular safety pacing generates a conspicuously short, fixed AV interval. Three discrete pacing artifacts reflect AV-sequential cardiac resynchronization therapy (CRT), ventricular safety pacing in CRT, or His-bundle pacing with backup RV output. Rate and AV hysteresis produce pauses and wandering AV intervals mimicking oversensing or Wenckebach periodicity. CONCLUSIONS: Recognizing algorithm-driven ECG patterns requires knowledge of device timing intervals and refractory periods, which lets clinicians distinguish programmed behavior from true malfunction or cardiac arrhythmia.

Humans↗

PubMed2026

A review into the recent advances in the world of amoebiasis.

PURPOSE OF REVIEW: Amoebiasis is a parasitic infection caused by Entamoeba histolytica , affecting 10% of the global population. It is a well recognized cause of morbidity and mortality in low-middle-income countries where it is endemic. However, with increased migration and global travel, amoebiasis is now more common in high-income countries, although diagnosis is often delayed or even missed due to lack of awareness of the latest epidemiology and optimal diagnostic testing. This review discusses the evolving prevalence, and the current international guidelines for the investigation and treatment of amoebiasis, focusing on recent advances. RECENT FINDINGS: The recent literature shows that the primary investigations for amoebiasis remain the same, though newer modalities such as artificial intelligence-powered microscopy and metagenomics have been developed recently, which aids the accuracy and speed of diagnosis. Treatment remains the same, though current research has found potential new drugs and drug targets which show promise. SUMMARY: This review reinforces the importance of early clinical suspicion, diagnosis and treatment for amoebiasis. What was once a disease only seen in endemic countries or travel-associated imported cases is now more common and must not be missed.

Humans↗

PubMed2026

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida↗

PubMed2026

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗

PubMed2026

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans↗

PubMed2026

The voice clone intelligibility benefit in noise in middle-aged listeners.

Research with younger adults showed that cloned voices are more intelligible than human voices in noise, with a benefit of 13.4%. This study tested whether this benefit extends to 40 middle-aged listeners (45-65 years), as this population may show emerging difficulties with speech-in-noise. Participants recognised sentences by ten human voices and ten voice clones in four noise levels. Cloned voices were 11.8% more intelligible, with benefits enhanced at the two most severe noise levels (15.9% at -6 dB and 17.5% at -3 dB), suggesting cloned speech enhanced perception in middle-aged listeners, potentially by reducing listening effort and compensating for emerging age-related auditory-cognitive decline.

Humans↗

PubMed2026

Effects of permissive hypercapnia on intraoperative cerebral oxygenation and early postoperative cognitive function in older patients with fragile brain function during the non-acute phase undergoing laparoscopic colorectal surgery: A randomized controlled trial.

BACKGROUND AND PURPOSE: Older adults with non-acute fragile brain function (NFBF) may be particularly susceptible to perioperative disturbances in cerebral oxygenation and postoperative neurocognitive decline. Permissive hypercapnia (PHC) may enhance cerebral oxygenation, but its effects in this population remain unclear. We examined whether PHC-based ventilation improves intraoperative regional cerebral oxygen saturation (rSO2) and early postoperative cognitive outcomes in older patients with NFBF undergoing elective laparoscopic colorectal surgery. METHODS: In this single-center, single-blind randomized trial, 76 patients were assigned in a 1:1 ratio to PHC-based or conventional ventilation. The primary outcome was the absolute change in rSO2 from baseline (T0) to the end of surgery (T4). Analyses followed the intention-to-treat principle, with prespecified per-protocol sensitivity analysis. Secondary outcomes included intraoperative rSO2 trajectories, cerebral oxygen extraction-related indices, early postoperative cognitive screening, serum neuron-specific enolase and interleukin-6, and safety outcomes. RESULTS: PHC significantly increased rSO2 relative to conventional ventilation (left: adjusted mean difference [aMD] 10.64, 95% CI 8.96-12.33; right: aMD 10.16, 95% CI 8.22-12.11; both P < 0.001), with consistent sensitivity results. Repeated-measures analyses showed persistently higher intraoperative rSO2 in the PHC group. Cerebral oxygen extraction-related indices were generally lower with PHC. However, early postoperative cognitive outcomes and serum biomarkers did not differ between groups. Emergence time was modestly longer with PHC, whereas adverse events were comparable. CONCLUSIONS: PHC-based ventilation favorably modified intraoperative cerebral oxygenation and oxygen-extraction profiles but did not translate into detectable early postoperative cognitive or biomarker benefits in older adults with NFBF.

Humans↗

PubMed2026

Effect of protective ventilation throughout the intubation period on perioperative oxygenation in patients undergoing MIDCABG: a randomised controlled trial.

INTRODUCTION: Minimally invasive direct coronary artery bypass grafting (MIDCABG) requires prolonged one-lung ventilation (OLV), increasing postoperative pulmonary complications (PPCs) risk. We investigated whether protective lung ventilation (PLV) throughout intubation benefits MIDCABG patients. METHODS: In this single-center randomized study, MIDCABG patients received PLV (low tidal volume of 6-8 mL·kg-1, PEEP of 6 cm H2O, alveolar recruitment maneuvers) or conventional mechanical ventilation (CMV, tidal volume of 8-10 mL·kg-1, without PEEP or maneuvers) from tracheal intubation to extubation. The primary outcome was perioperative oxygenation, assessed by the PaO2/FiO2 ratio. RESULTS: Sixty patients (n = 30 per group) were enrolled. Compared with CMV, PLV improved PaO2/FiO2 ratios (mean difference at OLV60: 34.56 mmHg; 95% CI: 11.78-57.33; p < 0.01), shortened median durations of postoperative mechanical ventilation (median difference: -4.5 h, 95% CI: -8.5 to -0.5; p = 0.013) and hospital stay (median difference: -3.0 days, 95% CI: -5.0 to -1.0; p = 0.019). PLV also reduced driving pressure, airway pressure and intrapulmonary shunt during OLV (all p < 0.05). Desaturation occurred in 23.3% of CMV patients and 13.3% of PLV patients (p = 0.506). Hemodynamic parameters were generally comparable between groups, except for lower MPAP and PVRI in the PLV group during OLV and after ICU admission (p < 0.05). The incidence of PPCs did not differ between groups. CONCLUSIONS: In patients undergoing MIDCABG, PLV applied throughout intubation improved perioperative oxygenation and shortened the duration of postoperative mechanical ventilation and hospital stay, but did not reduce PPCs. CLINICAL TRIAL REGISTRATION: ChiCTR1900022005.

Humans↗

PubMed2026

Current Concepts and Emerging Technologies in Aesthetic Outcome Assessment of Breast Reconstruction.

Aesthetic outcomes are a crucial determinant of the overall success of breast reconstruction. Recently, aesthetic assessment has evolved from relying mainly on subjective impressions to incorporating more quantitative methods. This systematic review summarizes current concepts and emerging technologies in aesthetic outcome assessment after breast reconstruction. A comprehensive search of studies evaluating aesthetic outcomes following implant-based, autologous or hybrid breast reconstruction was performed between 2000 and 2025. Assessments were classified as subjective or objective. Extracted variables included assessment characteristics, aesthetic outcome domains, and patient-centered outcomes. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Levels of evidence were classified according to the Oxford Centre for Evidence-Based Medicine. A total of 51 studies involving 7711 participants from 16 countries were included. Subjective tools were most frequently employed, led by the BREAST-Q (35/51, 69%), followed by expert- or panel-based evaluations (17/51, 33%) and the visual analog scale (2/51, 4%). Objective methods were applied in 19 studies and included 3-dimensional surface imaging (8/51, 16%), BCCT.core (7/51, 14%), eye tracking (3/51, 6%), and artificial intelligence-based analyses (3/51, 6%). Although subjective tools captured satisfaction with breast appearance, objective tools quantified morphological parameters and positional landmarks. BREAST-Q remains the cornerstone of outcome evaluation after breast reconstruction, providing patient-centered perspectives, including, but not limited to, aesthetic perception. A progressive shift toward multimodal evaluation was noticed, as no single modality comprehensively addressed all aesthetic domains. Future research should focus on integrating subjective and objective assessment methods within a unified framework. Level of Evidence: 3 (Therapeutic) For image description, please refer to the figure legend and surrounding text.

Humans↗

PubMed2026

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article↗