Suicide attempt risk stratification is often hampered by the limitations of current binary classification methods, hindering effective management of suicidal behaviour. Despite the increasing cases of suicidal behaviour in high-risk populations, the number of studies on individuals with Systematic Lupus Erythematosus (SLE) with suicidal attempts is limited and remains unclear. SLE is a chronic autoimmune disease where body's defence system gets confused and starts attacking healthy parts of body. Therefore, this study aimed to propose a framework for multi-class prediction of suicide attempt risk in SLE individuals using machine learning. Logistic regression, decision tree, support vector machine, random forest, and gradient boosting were trained and evaluated using five-fold cross-validation on a clinical dataset of 130 patients with SLE. The multi-class models achieved an overall classification performance between 0.75 and 0.85 to classify four risk levels for suicidal behaviour (no risk, low risk, moderate risk, high risk). Specifically, the gradient boosting model trained with eleven features showed the highest precision at 0.82 in predicting suicide attempts in high-risk SLE individual. Feature importance analysis indicated that past suicide attempts and depressive disorders were the strongest predictors of suicide risk in SLE patients. While the multi-class model showed promising precision, the small sample size limits generalizability and requires validation with larger populations. Nonetheless, this preliminary study highlights the potential of risk stratification for supporting early identification and improving clinical decision-making in suicide prevention.

High intracoronary thrombus burden complicates a significant proportion of ST-segment elevation myocardial infarctions (STEMI) managed with primary percutaneous coronary intervention (PCI), and remains a major determinant of procedural complexity, microvascular obstruction, and adverse outcomes. Restoration of epicardial coronary flow alone does not ensure adequate myocardial reperfusion, as distal embolization and no-reflow may occur despite technically successful PCI. Effective management requires an understanding of the dynamic interplay between thrombus burden, culprit plaque morphology, coronary flow, and procedural strategy. Although angiography remains the initial imaging modality, it frequently underestimates thrombus burden and provides limited information regarding the underlying lesion. Intravascular imaging offers complementary insights into thrombus composition, plaque morphology, vessel architecture, and lesion severity, facilitating tailored therapeutic decision-making. Pharmacological treatment integrates potent antiplatelet and anticoagulant therapies, with selective use of intracoronary fibrinolytics and vasodilators in appropriate patients. Mechanical adjuncts, including aspiration thrombectomy, excimer laser coronary angioplasty, and emerging thrombus-modifying technologies, may be beneficial in selected cases, although routine use has not consistently improved clinical outcomes. This review summarizes the contemporary evidence on the pathophysiology, assessment, and management of high thrombus burden in STEMI, highlights the complementary roles of angiography and intravascular imaging, and proposes a practical algorithm for individualized management based on coronary flow, thrombus characteristics, and culprit lesion morphology.

Background/Objectives: Estrogen receptor immunohistochemistry (ER-IHC) exhibits heterogeneous staining and substantial class imbalance, complicating segmentation of ordered expression categories. We evaluated whether class weighting, minority-focused crop sampling, adaptive minority curriculum (AMC), and Focal-Tversky optimization improved a common ResUNet-DS backbone for segmenting background/non-target pixels and C1 ER-negative, C2 weak-positive, C3 moderate-positive, and C4 strong-positive foreground categories. Methods: The dataset comprised 220 paired 512×512 image-mask patches organized into 44 recovered five-patch source groups. A source-group-preserving nested five-fold design used outer folds of 45, 45, 45, 45, and 40 patches. Six controlled training conditions were compared, with four independently selected inner models ensembled for each condition and outer fold. Results: Unweighted random training achieved the best numerical mean for all five primary endpoints: foreground Dice (0.7479±0.0123), C2-C4 Dice (0.7098±0.0128), foreground IoU (0.6074±0.0147), foreground quadratically weighted kappa (0.9761±0.0040), and foreground-ordinal MAE (0.0446±0.0062). Weighted random training was the strongest weighted/minority-sensitive condition but did not exceed the unweighted reference. None of 25 paired outer-fold comparisons reached p<0.05; the minimum raw p-value was 0.0625, and all Holm-adjusted p-values were 0.3125. A 20,000-replicate paired source-group bootstrap preserved the same overall ordering. Conclusions: More complex imbalance-handling strategies did not improve aggregate segmentation over unweighted training. Post hoc analyses showed scope-dependent probability quality and error ranking. IHC4BC provided expression-ordering consistency but not direct external segmentation validation. The findings support preliminary source-group-preserving methodological evidence rather than patient-level, whole-slide, or clinical validity.

A novel furan-functionalized polyisoprene (Furan-PIP) was synthesized via a one-pot, redox-initiated cascade approach using tert-butyl hydroperoxide (TBHP) and tetraethylenepentamine (TEPA) as the initiating system. The polymerization of isoprene proceeded through radical emulsion polymerization, accompanied by in situ epoxidation of the resulting double bonds, followed by ring-opening and furanization reactions. The chemical structure of Furan-PIP was qualitatively characterized by FT-IR and 1H NMR spectroscopy. The appearance of characteristic signals at δ 3.97 and 3.37 ppm (furan ring protons) and δ 8.43 ppm (formyloxy proton) in the 1H NMR spectrum, together with the corresponding FT-IR absorptions at 1725 cm-1 (C=O) and 1015 cm-1 (furan ring), confirmed the successful incorporation of furan and ring-opened moieties. Residual epoxide signals were negligible, indicating near-complete consumption of epoxy groups during the cascade process. Gel permeation chromatography (GPC) revealed a high-molecular-weight polymer (Mn¯ = 45,892 g/mol, PDI = 2.362). The Furan-PIP exhibited a glass transition temperature (Tg) of -49.6 °C and a single-stage thermal degradation at 312 °C. Subsequently, a pre-synthesized antibacterial zinc complex Zn(L-Cl) was physically encapsulated into the Furan-PIP matrix to fabricate a composite material. The composite exhibited time-dependent antibacterial activity against Staphylococcus aureus (S. aureus) over 48 h, leveraging the intrinsic antibacterial property of Zn(L-Cl) previously reported by our group. This work presents a simple and efficient strategy for preparing furan-functionalized elastomers with potential applications in antibacterial materials.

Emetine (EMT), a naturally occurring tetrahydroisoquinoline alkaloid, shows diverse biological actions, including anticancer effects. Despite existing studies, the role of EMT derivatives in cancer, particularly in relation to the PI3K/AKT/mTOR signalling pathway, remains largely underexplored. This review explores the potential of EMT in targeting PI3K/AKT/mTOR molecular pathways across different cancer types. Data were collected from reliable and well-established sources, including PubMed, Scopus, Wiley Online, Web of Science, ScienceDirect, and Google Scholar. Findings showed that EMT derivatives suppress PI3K-AKT-mTOR pathway activity in multiple cancers such as liver, gastric, acute myeloid leukaemia (AML), and brain, with IC50 values ranging from 0.0244 to 1 μM. Beyond its anticancer activity, EMT showed broad pharmacological relevance, including antiviral, antiparasitic, and contraceptive activities. Preclinical assessments suggest preferential cytotoxicity toward cancer cells at low concentrations; however, known dose-dependent adverse effects, including cardiotoxicity and emetic responses at higher doses, necessitate careful dose optimization before clinical translation. Clinical evidence remains insufficient, and EMT should be considered a preclinically active compound warranting further rigorous translational investigation.

The perceptions of the Asia-Pacific interventional community towards intracoronary imaging (ICI) has not been systematically evaluated. This study aimed to evaluate adoption rates, operator perceptions, and attitudes towards ICI amongst the cardiology community in the Asia-Pacific. A web-based survey was conducted from April to September 2025 among cardiologists performing percutaneous coronary intervention from the Asia-Pacific region. Demographic characteristics as well as the availability, frequency of use, and perceptions of ICI were assessed. Among 672 survey responses, 71.4% of respondents were from high-income countries. ICI was available in 93.5% of institutions; however, availability of ICI was lower in low- and middle-income countries (85.3% vs. 96.7%, p < 0.001). Personal experience with intravascular ultrasound was reported by most respondents (93.7%), while 67.7% had experience with optical coherence tomography. Majority of respondents (93.5%) believed that ICI improves clinical outcomes compared with angiography. Cost-effectiveness of ICI was perceived as good by 48.5% of respondents, average by 38.7%, and poor by 10.3%. Major reasons limiting the clinical use of ICI were high cost (56.8%), regulatory/reimbursement issues (42.1%), and prolongation of diagnostic procedure (36.5%). In a cohort consisting predominantly of interventional cardiologists from high-income countries, substantial variability in practice patterns and perceptions were observed according to region. These findings highlight the need for targeted strategies to address the practice gaps within the Asia-Pacific interventional community.

The pursuit of stimuli-responsive smart materials drives innovation in molecular science. Spin-crossover (SCO) compounds, with their reversible switching of magnetic, optical, and electronic properties, stand out as prime candidates. A central challenge for their application is the precise and controllable modulation of SCO characteristics. Utilizing host-guest chemistry in porous frameworks to impart "chemical pressure" is a promising strategy. Here, we report a novel three-dimensional Hofmann-type SCO metal-organic framework, {Fe(pdmh)[Pt(CN)4]} (1) (pdmh = 2-(4-pyridinylmethylene)hydrazide). Single-crystal X-ray diffraction confirms a temperature-driven SCO transition. Magnetic measurements of the pristine framework reveal a cooperative first-order SCO with a thermal hysteresis of ∼20 K. Remarkably, the inclusion of azobenzene guest molecules (1·Azobenzene), whose successful loading is confirmed by infrared spectroscopy, drastically modulates the SCO properties: it shifts the rapid, single-step transition to a higher temperature range (∼250 K on cooling, ∼240 K on heating) and reduces the hysteresis width to ∼10 K. Density functional theory calculations uncover a spin-state-dependent host-guest interaction via π-π stacking, which is significantly stronger in the low-spin state. This enhanced interaction exerts stabilizing chemical pressure on the Fe(II) centers, elucidating a clear mechanism for guest-mediated tuning. Given the photoresponsive nature of azobenzene, this work paves a novel avenue toward the development of optically controlled molecular materials.