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Biofilm-associated infections present a critical therapeutic challenge due to antibiotic resistance and impaired tissue healing. Here, we present a microrobotic system (MZ-8) that integrates real-time human-steered navigation with autonomous, microenvironment-responsive therapy to actively eradicate biofilms and promote tissue regeneration. This microrobotic system features a spine-inspired structure for mechanical biofilm disruption, a pH-responsive ZIF-8 coating for immunomodulatory Zn2+ release, and closed-loop actuation under second near-infrared fluorescence guidance. In a rat model of periprosthetic joint infection, MZ-8 achieved effective biofilm removal, induced a pro-regenerative immune response by polarizing macrophages toward the M2 phenotype, and significantly enhanced tissue regeneration. Transcriptomic analysis further revealed the activation of immunomodulatory pathways and upregulation of M2-associated genes, confirming the system's sequential shift from eradication to repair. Moreover, validation in a rabbit model and human knee joint confirmed its operational feasibility under clinical imaging guidance and excellent biosafety. This work establishes that integrating physical eradication, biochemical immunomodulation, and interactive control within a single system is essential for advancing from infection clearance to functional tissue restoration. Thus, it provides a therapeutic paradigm for biofilm-associated diseases and lays a foundation for future intelligent, clinically adaptive anti-infective systems.

Does direct warming preserve embryonic developmental competence and molecular integrity as well as conventional multi-step warming in vitrified human and mouse cleavage-stage embryos? Direct warming yielded comparable developmental and molecular outcomes to conventional warming in both mouse and human cleavage-stage embryos. Conventional embryo warming uses stepwise cryoprotectant dilution to minimize toxicity and osmotic shock. Direct warming methods have been proposed, but their impact on post-warming development and the molecular comparison remains unclear. This is a controlled experimental study conducted over 18 months. A total of 490 vitrified mouse embryos and 15 donated human embryos were tested either in direct or conventional warming group. A subset underwent embryo transfer and follow-up. Parallel transcriptomic and DNA methylation profiling was performed on mouse and donated human embryos. Mouse cleavage-stage embryos (C57BL/6J) were vitrified and randomly assigned to direct (n = 265) or conventional (n = 225) warming. Post-warming survival and blastocyst formation were assessed in vitro. A subset (n = 211) underwent embryo transfer to evaluate implantation, live birth, and postnatal development to Day 21. For molecular analysis, pooled mouse embryos from fresh, conventional, and direct groups were analyzed by bulk RNA-seq and bisulfite sequencing. Ten vitrified human embryos (n = 5 per group) were analyzed individually by scRNA-seq and scBS-seq. All procedures were conducted under standard IVF lab conditions with ethical approval. Direct warming in mouse achieved comparable survival (95.8% vs 93.8%), blastocyst formation (88.6% vs 88.2%), implantation (82.5% vs 83.0%), and live birth rates (69.6% vs 71.1%) to conventional warming (all P > 0.05). Offspring showed similar growth, developmental milestones, and organ histology. Mouse transcriptome and methylome profiles revealed minimal differences and no significant pathway enrichment. In human embryos, ion channel-related gene variability was observed but without coordinated pathway disruption. Global methylation levels remained within expected developmental ranges. N/A. While the mouse model enables in vivo validation, species-specific differences in embryo size, membrane properties, and development may limit generalizability. As all embryos were cultured under optimized conditions, caution is advised when extrapolating to diverse clinical settings. To our knowledge, this is the first study to provide multi-level evidence supporting the safety and efficacy of direct warming as an alternative to conventional multi-step embryo warming protocols. By incorporating in vivo reproductive outcomes, postnatal development, and molecular profiling, it strengthens current evidence on the feasibility of this approach. The absence of pathway-level disruptions in transcriptome and methylome datasets suggests that direct warming does not impair essential developmental programs. These findings may support the clinical use of simplified warming procedures, especially for cleavage-stage embryo transfer or in resource-limited settings. However, further clinical studies are warranted to confirm long-term safety in humans. This work was supported by Collaborative Research Fund (CRF-C4007-24E), and Early Career Scheme (ECS-26103623) from the University Grants Committee (UGC), and Health and Medical Research Fund (HMRF 12230736) from the Hong Kong Government. The authors report no competing interests. N/A.

Precise regulation of dopamine signaling underlies diverse neuronal processes, yet methods that directly report intracellular dopamine-associated dynamics in living systems remain limited. Here, we present DARibo-Q, a genetically encoded RNA fluorescent biosensor that enables fluorescence imaging of intracellular dopamine-associated modulation through a rationally engineered RNA allosteric transduction architecture. By coupling dopamine recognition to graded shifts in RNA conformational equilibria, DARibo-Q converts ligand-associated changes into a continuous and interpretable optical output under physiological conditions rather than a threshold-based or amplification-dependent response. In neuronal cells, DARibo-Q reports relative dopamine-associated fluorescence changes and resolves mechanistically distinct modes of dopaminergic regulation, enabling mechanism-informed analysis of dopaminergic compounds. The sensor further supports in vivo visualization of drug-modulated dopamine dynamics in zebrafish. Together, this work demonstrates that RNA allostery can be engineered to achieve direct, relatively quantitative signal transduction of small-molecule neurotransmitters in living systems.

Mycotoxins, as toxic secondary metabolites produced by various fungi, represent widespread contaminants in global agricultural products, raw materials, and resulting food and feed supplies. Consequently, the necessity for their sensitive and rapid detection has been steadily escalating to ensure food safety. Among advanced sensing platforms for mycotoxins, electrospun nanofibers (ESNFs) are recognized as a promising option, primarily due to their high surface area, tunable porosity, and functionalization potential. This article reviews recent advancements in ESNF-based sensing techniques for mycotoxin detection. Specifically, the practical utility of ESNF systems has been explored across electrochemical, optical, and quartz crystal microbalance (QCM) platforms. The performance of these covered platforms is assessed and evaluated based on key quality assurance parameters (e.g., LOD, linear detection range, response time, reproducibility, and reusability). Interestingly, Ti3C2Tx MXene/PVDF nanocomposite-based electrochemical aptasensor is found to be the most sensitive system, achieving an ultralow LOD of 2.15 × 10-6 ng mL-1 for the detection of Ochratoxin A. Moreover, studies on ESNFs-based extraction followed by sensing of mycotoxins are also covered.

➢ Osteochondral autograft transfer (OAT) restores hyaline cartilage and subchondral bone in a single stage, offering a durable joint-preserving option for focal full-thickness articular cartilage defects in young, active patients.➢ Optimal candidates have unipolar femoral condyle, patellofemoral, or tibial plateau lesions measuring 1 to 4 cm2; outcomes become less predictable once the defect size exceeds 3 cm2. Outcomes are further influenced by age, activity level, sex, alignment, instability, and meniscal deficiency, with older, lower-demand patients and those with larger lesions demonstrating comparatively inferior results.➢ Technical success requires meticulous recipient-site preparation, perpendicular graft harvest, and flush implantation; both arthroscopic and open approaches achieve reliable results.➢ OAT demonstrates high return-to-sport rates (often >85% within 6 months), significant functional improvements, and superiority over microfracture. Outcomes may be comparable or superior to cellular resurfacing or allograft techniques in appropriately selected patients.➢ Emerging biologic adjuncts, recess-filling strategies, and donor-site substitutes may enhance graft integration and reduce morbidity, although long-term clinical benefits remain unproven.

Short-wave infrared (SWIR) avalanche photodiodes (APDs) are important for LiDAR, free-space optical communication, and low-light imaging. Colloidal quantum dots (CQDs) offer a solution-processable, silicon-compatible SWIR platform, but conventional CQD p-i-n APDs couple photon absorption and avalanche multiplication in the same narrow-bandgap layer, causing severe dark-current growth under high reverse bias. Here, we demonstrate a CQD/i-ZnO APD based on a separate-absorption-charge-multiplication (SACM) architecture. By relocating the high-field multiplication region from the narrow-bandgap CQD absorber to wide-bandgap i-ZnO, this design suppresses tunneling-induced dark current while retaining avalanche multiplication. The optimized device achieves a gain-normalized dark current density of 4.86 × 10-7 A cm-2, the lowest reported among CQD photodetectors with internal gain, and a specific detectivity of 1.15 × 1012 Jones. These results establish SACM field engineering as an effective route toward low-dark-current CQD-based SWIR APDs.

Sellar chondromas are extremely rare benign cartilaginous tumors, representing less than 0.3% of intracranial tumors. Their occurrence in the pediatric population is exceptionally rare and their clinical and radiological presentation frequently mimics that of more common sellar lesions, making preoperative diagnosis particularly challenging. The authors present the case of a 16-year-old female patient with a sellar chondroma treated via a transsphenoidal endoscopic approach and adjuvant radiosurgery. The patient presented with headache, bitemporal hemianopsia, and hormonal alterations. Preoperative imaging suggested craniopharyngioma as the leading diagnosis. Subtotal resection was performed due to firm tumor adherence to the medial wall of the right cavernous sinus, and histopathological examination confirmed the diagnosis of chondroma. Adjuvant radiosurgery was subsequently initiated for the residual tumor. This case highlights the importance of considering sellar chondroma in the differential diagnosis of heterogeneous sellar lesions in the pediatric population even when imaging suggests a more common entity. When gross-total resection is not achievable due to neurovascular involvement, adjuvant radiosurgery represents a safe complementary strategy. Definitive diagnosis relies on histopathological confirmation. https://thejns.org/doi/10.3171/CASE26226.

Anifrolumab, a type I interferon receptor antagonist, has shown effectiveness in treating moderate-to-severe systemic lupus erythematosus (SLE). To fully understand its long-term efficacy, glucocorticoid (GC)-sparing potential, and cumulative safety profile in everyday clinical practice, it is essential to combine up to 4 years of long-term extension (LTE) trial data with emerging real-world evidence (RWE). A systematic literature search was performed across major electronic databases to identify phase 2/3 randomized controlled trials (RCTs), long-term extension (LTE) studies, and RWE cohorts assessing anifrolumab in SLE. Comparative odds ratios (ORs) for RCTs were calculated using the Mantel-Haenszel method, while pooled proportions for single-arm RWE cohorts were estimated using a random-effects model. Primary outcomes included BICLA response, Lupus Low Disease Activity State (LLDAS), GC reduction (to &#x2264; 7.5 mg/day), and Herpes Zoster (HZ) incidence. Ten studies were included, comprising phase 2/3 RCTs, their LTEs (TULIP-LTE, MUSE-LTE), and four European RWE cohorts. In the RCTs (N = 1,093), anifrolumab significantly improved BICLA responses compared to placebo (pooled OR 1.85, 95% CI 1.42-2.41, p < 0.001) and enhanced the likelihood of achieving a target GC dose of &#x2264; 7.5 mg/day (OR 2.24, 95% CI 1.52-3.29, p < 0.001). In the pooled RWE cohorts (N = 294), the estimated attainment rate for LLDAS at 6-12 months was notably high at 75.8% (95% CI 68.4-82.5%). Additionally, 72.5% of real-world patients achieved a >50% reduction in GC dosage. Regarding safety, there was no significant increase in overall serious adverse events (SAEs) (OR 0.82, p = 0.25). Although anifrolumab was linked to a higher risk of HZ (OR 3.45, 95% CI 1.95-6.10, p < 0.001), both LTE and RWE data indicated that these cases were mainly mild to moderate and manageable. Anifrolumab offers rapid, strong, and sustained disease control while providing significant GC-sparing effects in both tightly controlled clinical trials and diverse real-world populations. The long-term safety profile remains stable; however, preventative measures, such as HZ vaccination, should be implemented as part of standard care.

CIS43LS is a long-acting mAb that targets the Plasmodium falciparum circumsporozoite protein. A phase 2 trial showed that a single dose of CIS43LS conferred >85% sterile protection against infection in Malian adults over 6 months. Understanding the pharmacokinetics and pharmacodynamics (PK/PD) of CIS43LS is critical for the further development of CIS43LS and other anti-malaria mAbs. Using 3,777 serum samples collected from 348 trial participants over the 6-month study period, we performed a PK/PD analysis of CIS43LS that included assessments for anti-drug antibodies and target-mediated drug disposition. A two-compartment, non-linear mixed effects population PK model that evaluated demographic, anthropometric, hematologic, baseline parasitemia, and endogenous IgG and IgG1 as potential covariates was used to estimate PK parameters and serum concentrations required to achieve 80% efficacy. The median CIS43LS t1/2 was 63.2 days (95%CI 59.4-67.2 days). Serum concentrations &#x2265;64 &#x3bc;g/mL (95%CI 49-93 &#x3bc;g/mL) corresponded to &#x2265;80% efficacy against infection over 6 months. A simulated dose of 30 mg/kg maintained serum concentrations >64 &#xb5;g/mL in >97.5% of individuals for 4 months, the timeframe for the World Health Organization preferred product characteristics for anti-malaria mAbs. There was no evidence of anti-drug antibodies. Among infected individuals who received CIS43LS, no marked evidence of target-mediated drug disposition was observed. This study indicates that protective CIS43LS levels can be maintained over the course of a single malaria season and provides guidance for PK/PD analyses of anti-malaria mAbs in malaria-endemic populations. NCT04329104. National Institutes of Health and Gates Foundation.

The rapid growth of renewable-based distributed generation (DG) and electric vehicles (EVs) poses significant operational challenges for distribution systems (DSs), particularly under uncertainties in renewable output, load demand, and EV charging behavior. Distribution system operators must therefore evaluate and enhance both DG hosting capacity (DG-HC) and EV hosting capacity (EV-HC) while maintaining voltage security and reducing losses. This study presents a stochastic, multi-objective optimization framework that jointly coordinates smart inverter (SI)-based Volt/VAR control and EV charging scheduling to simultaneously maximize DG-HC and EV-HC and minimize active power losses and voltage deviation. The framework integrates active power management through EV charging coordination and reactive power support via optimally deployed SIs. The resulting multi-objective problem is solved using the Starfish Optimization Algorithm (SFOA) and benchmarked against three established metaheuristics. The methodology is validated on the IEEE 33-bus system and a real 59-bus distribution network in Cairo, Egypt. Results show that coordinated SI-EV control increases DG-HC and EV-HC by up to 74% and 89%, respectively, and achieves voltage deviation reductions of 55% in the IEEE 33-bus system and 11% in the Cairo DS. Comparative analysis confirms that SFOA provides superior convergence and solution quality relative to the competing techniques.

Eukaryotic gene regulation relies on stochastic yet controlled promoter switching, in which genes transition between transcriptionally active and inactive states. Despite the molecular complexity of this process, recent studies have revealed a surprising invariance of the "switching correlation time" (TC)-the characteristic decay time of the autocorrelation function of promoter activity fluctuations-across gene expression levels in multiple genes and organisms. A biophysically plausible explanation for this invariance has so far been lacking. Here, we show that this empirical constraint imposes stringent requirements on minimal yet realistic models of transcriptional regulation. Specifically, reproducing TC-invariance requires regulatory architectures with at least four internal states and nonequilibrium dynamics that break detailed balance. Using Bayesian inference on Drosophila gap gene expression data, we demonstrate that such models i) quantitatively reproduce the observed TC-invariance, ii) remain robust to parameter perturbations, and iii) maximize information transmission from transcription factor concentration to gene expression. Remarkably, the TC-invariant modulation strategy we identify as optimal closely parallels contemporary control-theoretic results on the modulation of stochastic switching systems. Taken together, our results suggest that eukaryotic transcriptional regulation operates in a nonequilibrium regime to balance precision, reaction-rate limitations, and energy dissipation, thereby achieving near-optimal information transmission under fundamental physical constraints.

Motivational interviewing (MI) is an effective approach for supporting health behaviorchange, but face-to-face delivery is resource-intensive and difficult to scale. Rule-based conversational agents (CAs) can improve access; however, their scripted interactions and limited language flexibility constrain MI delivery. While large language models (LLMs) are increasingly being used for MI coaching, their conversational fidelity and quality compared with human coaches and rule-based CAs remain understudied. This study aimed to describe the development of an LLM-based CA, Artificially Intelligent Motivational Interviewing (Aimi), orchestrated with structured workflows, and to evaluate its feasibility, conversational fidelity, and user perceptions during MI coaching interactions. We developed Aimi using structured LLM workflows designed to enhance MI fidelity. We conducted a within-participants study, where 18 adults interacted with (1) Aimi, (2) a novice MI-trained human coach, and (3) a rule-based CA during live text-based role-play coaching sessions. Transcripts were independently evaluated by an MI expert using the Motivational Interviewing Skill Code, Version 2.0 (MISC-2), to assess MI competency and fidelity. Participants completed a user experience questionnaire to provide general feedback and to assess session alliance, dialogue relevance, empathy, engagement, linguistic quality, and perceived motivation to change. Feedback from users was thematically summarized and categorized under strengths and weaknesses for each approach. Aimi achieved fidelity scores comparable to those of the novice human coach and higher than those of the rule-based CA on summary metrics, including higher reflection-to-question ratios (median 0.84, IQR 0.62-0.92 vs 0.62, IQR 0.42-0.74 vs 0.25, IQR 0.17-0.38), more complex reflections (median 66.67%, IQR 46.97%-76.92% vs 50%, IQR 34.38%-61.88% vs 0.00%, IQR 0%-50%), and greater elicitation of client change talk (median 90.83%, IQR 85.89%-100% vs 73.21%, IQR 63.10%-83.19% vs 66.67%, IQR 57.86%-81.94%). User experience ratings showed no significant differences across conditions. User feedback revealed distinct strengths and limitations across the coaching interactions. Participants described Aimi's interactions as personalized, fluid, and adaptive, though sometimes overly reflective and lengthy. The novice human coach was viewed as empathetic and supportive but slow to respond, whereas the rule-based coach was viewed as efficient and structured yet limited in depth and personalization. This study demonstrates the technical feasibility of structured LLM-workflows for MI coaching and their capacity to maintain conversational fidelity comparable to that of a novice MI-trained human coach. Given the role-play paradigm, single-rater coding, and small convenience sample, these comparative findings should be interpreted as exploratory. Our findings serve as a foundational baseline for the development of scalable behavior change interventions in clinical settings.

Vapor-induced structural changes, coupled with modifications in electronic structure, have garnered significant attention owing to their potential application in sensor materials. However, the mechanisms driving the vapor-induced structural changes remain largely unexplored. Herein, we report mechanistic insights into the vapor-induced structural changes of a Pt(II) complex, [Pt(Cl2BAn)(acac)] (=1; Cl2BAn = 3-chlorobenzylidene-3-chloroaniline, acac = acetylacetonato), involving single crystal generation. A microcrystalline powder sample of 1 (1a) exhibited acetone vapor-induced structural changes to 1b (unsolvated polymorphs), accompanied by single crystal generation. Microscopic observations and solubility assessments revealed the process. Compound 1a was partially dissolved in the minimum required quantity of liquid acetone via the condensation of acetone vapor. Second, crystals of 1b were generated from the solution and subsequently grew owing to the lower solubility of 1b than 1a in acetone. The transformation ceased when nearly all 1a was consumed, leaving 1b single crystals with a minimal amount of liquid. 1a and 1b exhibit distinct vapor-condensation behaviors: thus, the reaction ceases when 1a is consumed. Consequently, achieving vapor-induced structural changes requires differences in solubilities and vapor condensation behavior between two polymorphs. These findings highlight one of the mechanisms for vapor-induced crystal structural changes and offer insights into tailoring vapor-response characteristics.

Areca nut (Areca catechu L., Arecaceae) contains bioactive alkaloids, including arecoline, arecaidine, and guvacoline, which are associated with pharmacological and toxicological effects. A rapid and sensitive ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for simultaneous quantification of these alkaloids in rat plasma and was applied to a toxicokinetic study. Chromatographic separation was achieved on a reversed-phase C18 column using gradient elution with aqueous and organic mobile phases containing a volatile acid modifier. Detection was performed by electrospray ionization in the positive ion mode with multiple reaction monitoring, and plasma samples were prepared by protein precipitation. The method was validated according to the current bioanalytical guidelines. The calibration curves showed good linearity (r&#xa0;>&#xa0;0.99) over the tested ranges, the within- and between-run accuracy and precision were within &#xb1;15% (&#xb1;20% at lower limit of quantification (LLOQ)), and the selectivity, carry-over, recovery, matrix effect, dilution integrity, and stability were acceptable. The LLOQs were 10&#xa0;ng/mL for arecoline and guvacoline, and 100&#xa0;ng/mL for arecaidine. The validated method was successfully applied for a toxicokinetic study in rats, and plasma concentration-time profiles of all analytes were characterized. These results show that the developed method is suitable for the quantitative determination of arecoline, arecaidine, and guvacoline in plasma and can be used in toxicokinetic and pharmacokinetic studies.

This study aimed to build and validate a risk prediction model for 1-year major adverse cardiovascular events (MACE) in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI), utilizing novel inflammatory biomarkers. This single-center retrospective cohort study enrolled 1,337 patients with ACS who underwent PCI between January 2021 and December 2023. Six novel inflammatory indexes (NLR, MHR, NHR, SII, SIRI, AISI) were derived from pre-PCI blood tests. After a 7:3 random split into training (n = 936) and validation (n = 401) cohorts, LASSO regression and multivariable Cox proportional hazards models identified independent predictors, and a combined biomarker-based model was constructed. Age, diabetes, Killip Class &#x2265; II, reduced LVEF, multivessel disease, no-reflow phenomenon, NHR, and SIRI were identified as independent predictors. The combined model achieved an AUC of 0.81 (95% CI: 0.78-0.84), which remained stable after optimism correction via bootstrapping. This performance was substantially higher than that of any single biomarker (maximum AUC: 0.71) and demonstrated significant improvements in NRI and IDI (all P < 0.001). Risk stratification demonstrated a clear gradient in MACE incidence: 6.3% (low-risk), 15.1% (intermediate-risk), and 25.3% (high-risk), P. < 0.0001, with consistent predictive performance across all evaluated clinical subgroups. The novel inflammatory biomarker-based model substantially improves risk prediction over clinical variables alone, providing a valuable framework for risk stratification and identifying patients at high residual inflammatory risk who may require closer clinical surveillance.

Temperature variations significantly degrade the measurement accuracy of fiber optic current sensors (FOCS) in critical power systems applications such as high-voltage transmission and renewable energy integration. To address this, we propose an intelligent error compensation method based on an improved Quantum-behaved Particle Swarm Optimization-Neural Network (Levy-Weighted-QPSO-NN) algorithm. The approach leverages easily measurable state parameters-sensing ring temperature, received optical power, half-wave voltage, SLD temperature, and SLD current-as inputs to predict temperature-induced current ratio difference. Experimental validation involved three sensing rings subjected to temperature cycling (-45 &#xb0;C to 70 &#xb0;C), emulating harsh substation environments. The Levy-Weighted-QPSO-NN model achieved 91.11% average prediction accuracy for ratio difference with a correlation coefficient (R&#xb2;) of 0.9223, outperforming QPSO-NN (85.69%) and Weighted-QPSO-NN (88.31%). Key metrics (MAE: 0.0784; RMSE: 0.0819) confirmed superior stability and accuracy. Robustness testing demonstrated consistent performance across varying population sizes (25-70) and iterations (90-150). Using predicted ratio differences for real-time compensation reduced measurement errors from 0.82% to 0.13%, meeting IEC 61869-6/8 and GB/T standards for Class 0.2S accuracy. This method eliminates reliance on complex hardware modifications, offering a generic, algorithm-driven solution for temperature-dependent FOCS errors.

Cryo-electron microscopy (cryo-EM) has become a central tool in structural biology, yet current workflows typically require multiple specialized software packages for data acquisition, three-dimensional (3D) reconstruction, and atomic model building, leading to fragmented pipelines and frequent manual intervention. Here, we present SMART (Shuimu Automated Reconstruction Technology), an integrated software platform that combines three modules-DataSmart for automated data collection, CryoSmart for image processing and 3D reconstruction, and ModelSmart for deep-learning-based atomic model building-within a unified browser-accessible interface. This protocol provides step-by-step instructions for operating all three modules. The workflow encompasses automated specimen navigation and data acquisition, motion correction, contrast transfer function (CTF) estimation, particle picking, two-dimensional (2D) classification, 3D refinement, map enhancement, and atomic model generation. As a representative example, we applied the complete workflow to determine the structure of human TRPML1, a Ca2&#x207a;-permeable lysosomal cation channel, achieving a global resolution of 2.38 &#xc5; by gold-standard Fourier shell correlation (FSC) at the 0.143 criterion. All three modules (DataSmart, CryoSmart, and ModelSmart) were applied sequentially to the same TRPML1 dataset within this study. The protocol is designed to be accessible to users with varying levels of cryo-EM experience.

Retrospective cohort study. To determine whether response to preoperative steroid injection is associated with postoperative outcomes in patients undergoing lumbar fusion for degenerative spondylolisthesis (DS). While injections are common practice in conservative management for DS, it remains unclear whether a positive response to injections is associated with clinical outcomes after surgical intervention. A retrospective review of prospectively collected data was performed on adults undergoing primary lumbar fusion for DS from 2013-2021. Patients were grouped into control (no preoperative injection) and injection cohorts as well as positive versus no response to injections. Demographics, visual analog scale (VAS) back and leg scores, PROMIS Physical Function (PF), PROMIS Pain Interference (PI), and Oswestry Disability Index (ODI) were collected. Injection success was defined as &#x2265;50% pain reduction. Surgical response was assessed using minimal clinically important difference thresholds. Baseline characteristics were compared using Student t tests, and linear regression evaluated associations between injection response and postoperative outcomes. Among 148 patients undergoing posterolateral instrumented fusion, 105 (70.9%) achieved &#x2265;50% symptom relief after injection. Baseline outcome measures did not differ between cohorts (P >0.05). The overall cohort demonstrated significant postoperative improvement in PROMIS PF, PROMIS PI, ODI, and VAS scores at all time points (all P <0.05). Positive injection response was independently associated with greater improvement in ODI at 1 year (&#x3b2;=14.0, P=0.023) and higher PROMIS PF at all time points except 3 months. No significant associations were observed for VAS back, VAS leg, or PROMIS PI. Most patients with DS experience symptomatic relief from injections, and postoperative outcomes improve regardless of injection response. However, a positive injection response is associated with greater improvement in disability and physical function following fusion, which may aid preoperative counseling and shared decision-making. III.

Breast cancer identification via ultrasound images requires high accuracy and transparency to assist clinicians in taking appropriate decisions. This work demonstrates a deep learning system for classification of breast ultrasound images into benign, malignant, and normal images using the EfficientNet-B0 architecture fine-tuned on the Breast Ultrasound Identification (BUSI) dataset. To mitigate class imbalance and stabilize the network, data augmentation including random horizontal flipping, rotation, and color jittering is applied. Gradient-weighted Class Activation Mapping (Grad-CAM) is utilized to generate visual explanations by identifying regions of interest such as tumor margins and texture patterns. The model achieved an average accuracy of 99%, demonstrating high efficacy in lesion detection. The integration of Explainable AI (XAI) not only improves diagnostic confidence but also bridges the gap between clinical practice and AI. The results prove the potential for combining high-performing deep learning models with interpretability methods in developing reliable breast cancer diagnosis tools suitable for actual clinical practice.