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This review article represents a collaborative effort across continents, bringing together the latest developments in neuro-ophthalmology with a focus on innovative diagnostic and therapeutic modalities that are shaping the future of the field. Among the most significant advancements is the rise of optical coherence tomography (OCT), now recognized as an indispensable tool in neuro-ophthalmological research, providing unparalleled insights into optic nerve and central nervous system pathologies. Gene therapy, particularly for conditions such as Leber's hereditary optic neuropathy, marks a new frontier in personalized medicine, offering hope for previously untreatable conditions. The article also examines the transformative role of telemedicine and artificial intelligence (AI) in clinical practice, which are revolutionizing patient care and enhancing diagnostic precision. Furthermore, it highlights the impact of novel serological biomarkers on the understanding and management of immune-mediated optic neuritis, and discusses the introduction of new therapeutic agents like Tocilizumab and Teprotumumab, which are redefining treatment paradigms. Collectively, these advancements reflect the profound influence of modern medicine on neuro-ophthalmology, paving the way for improved patient outcomes and fostering new avenues for research and clinical practice.

Background The prevalence and impact of right ventricular dysfunction (RVD) in degenerative mitral regurgitation (DMR) is unknown. We aimed to determine whether RVD assessed by echocardiography in routine clinical practice is independently associated with mortality in patients with DMR. Methods and Results We used data from the MIDA‐Q (Mitral Regurgitation International DAtabase‐Quantitative) registry, which included patients with isolated DMR due to mitral valve prolapse from January 2003 to January 2020 from 5 tertiary centers across North America, Europe, and the Middle East. A cohort of 2917 (mean age: 66 years, 70.8% male patients, follow‐up: 5.2 [3.3–8.3] years) consecutive patients with severe DMR was included and long‐term mortality was analyzed. RVD, identified in 426 (14.6%) patients, was associated with reduced 8‐year survival (55%±3% versus 77%±1%; P <0.001), overall and in all subgroups of patients, even after comprehensive adjustment including left ventricular dilatation and dysfunction, DMR severity, pulmonary pressures, and surgery (adjusted hazard ratio, 1.44 [95% CI, 1.17–1.77]; P <0.001). This excess mortality was observed under medical management (adjusted hazard ratio, 1.57 [95% CI, 1.20–2.05]; P =0.001) and after surgical correction of mitral regurgitation (adjusted hazard ratio, 1.45 [95% CI, 1.02–2.05]; P =0.039). Patients with RVD undergoing surgery within 3 months of diagnosis experienced a better 8‐year survival (73%±4% versus 43%±4%; P <0.001), even after adjustment (adjusted hazard ratio, 0.44 [95% CI, 0.29–0.67]; P <0.001) despite an increase of 1‐month postoperative mortality (7.1% versus 0.5% for patients without RVD; P <0.001). Conclusions RVD is observed in 14.6% of severe DMR and exhibits a powerful and independent association with excess mortality partially attenuated by mitral surgery. Therefore, assessment of right ventricular systolic function should be included in routine DMR evaluation and in the clinical decision‐making process.

Abstract The interactions between transcription factors (TFs) and the target genes could provide a basis for constructing gene regulatory networks (GRNs) for mechanistic understanding of various biological complex processes. From gene expression data, particularly single-cell transcriptomic data containing rich cell-to-cell variations, it is highly desirable to infer TF–gene interactions (TGIs) using deep learning technologies. Numerous models or software including deep learning–based algorithms have been designed to identify transcriptional regulatory relationships between TFs and the downstream genes. However, these methods do not significantly improve predictions of TGIs due to some limitations regarding constructing underlying interactive structures linking regulatory components. In this study, we introduce a deep learning framework, DeepTGI, that encodes gene expression profiles from single-cell and/or bulk transcriptomic data and predicts TGIs with high accuracy. Our approach could fuse the features extracted from Auto-encoder with self-attention mechanism and other networks and could transform multihead attention modules to define representative features. By comparing it with other models or methods, DeepTGI exhibits its superiority to identify more potential TGIs and to reconstruct the GRNs and, therefore, could provide broader perspectives for discovery of more biological meaningful TGIs and for understanding transcriptional gene regulatory mechanisms.

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

Monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), and active multiple myeloma (MM) represent a continuum across the spectrum of plasma cell disorders. While patients with MGUS can be observed, it has a risk of progression to MM, while patients with SMM have a higher risk of progression to MM. Determining the risk of progression is important for proper patient care and elimination of anxiety, especially for patients identified at very low risk of progression. In contrast, identifying patients at high risk may reduce morbidity by more active surveillance or the introduction of therapy. We hypothesized that Fourier Transform InfraRed Spectroscopic analysis of serum combined with machine learning (FTIR/ML) could be used to facilitate this decision-making and correctly stratify patients' risk. Methods: After Institutional Review Board approval, we identified 99 patients with MGUS who did not progress to SMM/MM or AL amyloidosis, 96 patients with SMM who did not progress to active MM over a 2-year interval from diagnosis, and another 96 SMM patients who progressed to MM within two years of diagnosis. The patients had been diagnosed and followed up at Mayo Clinic in Rochester. Serological molecular fingerprint analysis was then performed using surface- and chemical-enhanced infrared absorption FTIR spectroscopy combined with artificial neural network ML. A randomized 10-fold cross-validation analysis was performed using 262 samples for training and the remaining 29 samples for validation to assess the model across ten independent iterations. Receiver operator characteristic (ROC) analysis was used to assess the FTIR/ML algorithm output compared to the clinical outcome data. Results: The patients with both MGUS and SMM had a similar median age (64.4 years), but patients with SMM tended to have lower hemoglobin compared to MGUS (median 12.4 versus 13.8g/dl respectively). As expected, patients with SMM also had a higher serum M-spike (2.0g/dl versus 1.2) and a higher clonal plasma cell burden in the bone marrow (20% versus 9%). FTIR/ML was able to correctly classify sera into MGUS in 95.8% of samples and SMM in 92.9% of samples. This gave an average accuracy of 94.8%. We performed ROC analysis and determined an area under the curve of 98.7%. The F1 score/precision was 94.9%, with a recall of 94.8%. After establishing a suitable threshold, the ML algorithm was able to correctly classify MGUS in 96.8% and SMM in 97.2% of cases. Conclusion: A single serum test at the time of diagnosis can correctly distinguish between MGUS that will not progress to another plasma cell disorder from smoldering multiple myeloma with a high degree of accuracy. Given that the patients with MGUS that were chosen had not progressed to a plasma cell disorder and were correctly identified, this methodology offers an opportunity to provide reassurance and minimize the need for repeat testing and follow-up of such patients.

The prognosis of patients with immunoglobulin light or heavy chain amyloidosis (AL/AH) has improved with the advent of more effective therapies. However, diagnosis is often delayed, with a negative impact on overall survival due to irreversible end-organ damage. Therefore, technologies that could facilitate the diagnosis or raise early suspicion of AL/AH amyloidosis in patients would be beneficial to improve outcomes. We hypothesized that Fourier transform infrared spectroscopic analysis of serum combined with machine learning (FTIR/ML) may be able to correctly diagnose AL/AH amyloidosis compared to patients with monoclonal gammopathy of undetermined significance or smoldering multiple myeloma. Methods: After institutional Review Board approval, we identified 90 patients with AL/AH amyloidosis, 99 patients with MGUS, and 192 patients with smoldering multiple myeloma (96 each who did/did not progress to active myeloma within two years of diagnosis) that had been diagnosed and followed up at Mayo Clinic in Rochester. We then performed surface- and chemical-enhanced infrared absorption FTIR/ML-based molecular fingerprint analysis on serum samples taken from the time of diagnosis to train an AI algorithm to distinguish between the two cohorts. A randomized 10-fold cross-validation analysis was performed using 253 samples (90% from each group) for training and the remaining 29 for testing to assess the model across ten independent iterations. We performed a Receiver Operator Characteristic analysis of the outcomes to measure the model's performance. Results: The patients with immunoglobulin-related amyloidosis had involvement of one or more of the following organs: heart, kidneys, liver, nerve, and gastrointestinal tract. Patients diagnosed with amyloidosis had lower serum albumin (3.0 versus 3.6 g/dl) and higher lambda immunoglobulin-free light chain values compared to those with MGUS (28.4 versus 1.92mg/dl). The predominance of lambda immunoglobulin-free light chains is not unexpected but not diagnostic by itself of AL/AH amyloidosis. Patients with SMM had higher serum M protein, higher immunoglobulin kappa free light chains, and higher bone marrow plasma cell burden (20%) compared to either MGUS (9%) or AL amyloidosis patients (10%). However, none of these are diagnostic features. FTIR/ML was able to correctly classify AL/AH amyloidosis in 80% of samples and MGUS in 83.8%, for an accuracy of 82% with an area under the curve of 89.2%. The precision was 82%, with a recall of 82%. After setting an appropriate threshold, the algorithm was able to correctly identify AL/AH amyloidosis in 86.1% of patients and MGUS in 86.6% of patients. When we compared AL/AH amyloidosis with SMM, FTIR/ML correctly classified AL/AH amyloidosis in 94.4% and SMM in 96.4% for an accuracy of 95.7% and an area under curve of 97.5%. The precision was 95.8%, with a recall of 95.7%. After setting a threshold, the algorithm was able to correctly diagnose SMM in 98.3% and AL/AH amyloidosis in 96.2%. Discussion: FTIR/ML analysis of serum can distinguish between AL/AH amyloidosis and both MGUS and SMM with a high degree of accuracy. Given that the diagnosis of immunoglobulin related amyloidosis is often delayed, our approach, based on a single analysis of a serum sample could potentially accelerate the diagnosis of AL/AH amyloidosis and implementation of life saving therapy.

Introduction: Brexu-cel is an autologous anti-CD19 CAR T-cell therapy approved in the US and EU for treatment of adults with R/R MCL (after ≥2 prior therapies in EU) based on a high objective response rate (ORR; 93%; 67% complete response [CR] rate) in pts who received the pivotal dose (2×106 anti-CD19 CAR T cells/kg; Cohort 1; N=60) in ZUMA-2 (NCT02601313; Wang et al, N Engl J Med 2020). After ~4 years (y) of median follow-up, Brexu-cel demonstrated a median overall survival (OS) of 46.4 months (mo) in 68 pts with R/R MCL in Cohort 1 (Goy et al. ASH 2023). Cohort 2 was established to assess a lower dose (0.5 x 106 anti-CD19 CAR T cells/kg); however, the risk/benefit ratio of the Cohort 1 dose was deemed the optimal dose before Cohort 2 reached full enrollment. Here we report primary outcomes of Cohort 2 and 5-y outcomes of Cohorts 1 and 2. Methods: Pts with R/R MCL and ≤5 prior therapies including a BTKi received optional bridging therapy (protocol-defined), lymphodepleting chemotherapy, and 1 infusion of brexu-cel. The primary endpoint was ORR (CR + partial response [PR]) per Lugano classification (Cheson et al. J Clin Oncol. 2014) by independent radiology review committee (IRRC) assessment. Key secondary endpoints were duration of response (DOR), best objective response (BOR), progression-free survival (PFS), OS, and safety. After ≥24 mo of assessment, pts could transition to long-term follow-up (LTFU), NCT05041309, where they were monitored for late-onset targeted/serious adverse events (AEs) possibly related to brexu-cel, presence of replication-competent retrovirus (RCR), and/or insertional mutagenesis. Descriptive statistics are reported herein. Results: As of the primary analysis data cutoff date, July 24, 2019, 17 pts enrolled in Cohort 2, 14 (82%) of whom were treated with brexu-cel with median follow-up of 16.0 mo (range, 13.9-18.0). Pt characteristics for Cohort 2 (N=14) were similar to Cohort 1; median (range) age and number or prior therapies was 61.5 y (52-73) and 3 (2-5); 100% US-treated, 79% male, 71% extranodal disease, 50% intermediate or high s-MIPI scores, 50% refractory to last therapy, and 43% had prior autologous stem cell transplantation. ORR was 93% (95% CI, 66.1-99.8) per IRRC; 64% had a CR (95% CI, 35.1-87.2), 29% had a PR (95% CI, 8.4-58.1) and 1 pt was not assessed. All 14 pts had ≥1 AE of any grade (Gr), with Gr ≥3 AEs occurring in 93% of pts; the most common being hypotension (50%), white blood cell count decrease (50%), anemia (43%), and neutrophil count decrease (43%). Rates of Gr ≥3 cytokine release syndrome (CRS) and neurological events were 7% and 43%, respectively. As of April 1, 2024, median follow-up (range) for Cohort 1 and 2 was 67.8 mo (58.2-88.6; N=68) and 72.3 mo (70.1-74.3; N=14), respectively. In Cohort 1, 24 pts were still alive (35%; 2 withdrew consent and 1 lost to follow up) and 44 pts died (65%). In Cohort 2, 8 pts were still alive (57%; 2 withdrew consent and 1 lost to follow up) and 6 pts died (43%). A total of 27 pts (Cohort 1, n=23; Cohort 2, n=4) enrolled in the LTFU study by data cutoff with a median follow-up time of 70.2 mo (range, 58.2-88.6). Median (95% CI) investigator-assessed DOR and PFS were 36.5 mo (17.7-48.9; n=60; 17 patients in ongoing response, all CR) and 25.3 mo (12.7-46.6; N=68) in Cohort 1; and 57.5 mo (4.7-not estimable [NE]; n=12; 3 pts in ongoing response, all CR) and 29.5 mo (3.3-NE; N=14) in Cohort 2. Median OS (95% CI) and 60-mo OS rates (95% CI) were 46.5 mo (24.9- 60.2) and 38.5% (26.7-50.1) in Cohort 1; and not reached (9.4-NE) and 53.6% (23.8-76.2) in Cohort 2. One pt had 3 ongoing AEs on LTFU, hypogammaglobulinemia and 2 viral infections that arose prior to LTFU. Two pts died on LTFU, both due to progressive disease; no new secondary malignancies or RCR cases were reported. Conclusions: Consistent with Cohort 1, brexu-cel demonstrated a high ORR, durable responses, and an expected safety profile in pts with R/R MCL in Cohort 2 despite the lower dose. However, small sample size limits interpretation of these results. With &gt;5 y of median follow-up, pts in Cohort 1 and 2 continued to experience durable responses with high 60-mo OS rates. No new safety signals were detected and no secondary malignancies or RCR cases were reported in LTFU. Additionally, ZUMA-2 results are consistent with real-world outcomes of brexu-cel in the post BTKi R/R MCL setting (89% ORR and 81% CR rate; Wang Y, et al. J Clin Oncol. 2023). These results support the continued use of brexu-cel in R/R MCL.

Background: 24-hour urine (24HRU) assessments are a key component of International Myeloma Working Group (IMWG) response criteria for multiple myeloma (MM) and are requested longitudinally in clinical trials even if not routinely used in real-world practice. Several analyses have suggested a limited role for 24HRU if serum immunofixation or free light chain (LC) testing is abnormal (Dejoie Blood 2016, Lahuerta Blood 2023). Adopting urine-free response criteria (with 24HRU removal from every level of IMWG response) may change responses in &lt;5% of patients (Natsuhara et al, Leuk Lymph 2023) but not have been studied in terms of progression-free survival (PFS) in a larger population. Methods: This was a secondary analysis of data from the Phase 3 BMT CTN 0702 (STaMINA) trial (Stadtmauer et al, JCO 2019) studying post-autologous stem cell transplantation (ASCT) strategies. Only patients evaluable for Day +56 response following ASCT were included, and patients with progressive disease (PD, n=8) at this timepoint were excluded. Post-ASCT responses relative to diagnosis were calculated by two sets of criteria. First, traditional responses were calculated per IMWG criteria (Kumar et al, Lancet Onc 2016) as stable disease (SD), partial response (PR), very good PR (VGPR), or complete response (CR, including stringent CR). Second, urine-free response assessments were calculated as follows: negative 24HRU immunofixation no longer required for CR, 24HRU M-protein &lt; 100 milligrams (mg) per day no longer required for VGPR, and no 24HRU M-protein thresholds (e.g., &lt; 200 mg per day or &gt; 90% reduction) required for PR. PFS was estimated (using PD by traditional IMWG criteria or death as events) using proportional hazard models. Results: Of 636 evaluable patients (84% of all BMT CTN 0702 participants), LC-only disease was noted in 18.9% (n=120). Pre-enrollment 24HRU testing at diagnosis was done in 28.9% of patients (n=184). IMWG responses were as follows: CR, 29.4% (n=187) traditional vs 29.7% (n=189) urine-free; VGPR, 37.0% (n=235) traditional vs 36.6% (n=233) urine-free; PR, 30.7% (n=195) for both; SD, 3.0% (n=19) for both. A total of 4 responses (0.6%) changed with urine-free criteria. Three patients were ‘upgraded’ (VGPR to CR, n=2, PR to VGPR, n=1) because 24HRU requirements for CR/VGPR were no longer required. One patient without a measurable serum paraprotein was ‘downgraded’ from a traditional VGPR (with negative 24HRU immunofixation) to a urine-free PR based on LC-only criteria. Among the subset of 184 patients with 24HRU electrophoresis results at diagnosis, there were no differences between traditional and urine-free IMWG responses. Median PFS and 95% confidence intervals (CI) were the same at each depth of both traditional and urine-free criteria: 63.0 months (50.8 - 71.4 months) for CR, 49.6 months (42.6 - 55.1 months) for VGPR, 44.9 months (37.2-54.8 months) for PR, and 34.4 months (14.0-51.5 months) for SD. Urine-free IMWG criteria were highly prognostic for PFS (p = 0.006, 95% CI 1.05-1.36). The achievement of urine-free CR vs urine-free ≤CR was also prognostic (p = 0.005, 95% CI 0.54 - 0.89). Urine-free VGPR vs urine-free ≤VGPR was of borderline significance (p = 0.102, 95% CI 0.66 - 1.04), with median PFS 53.8 months (48.0 - 57.6 months) vs 44.6 months (36.3 - 54.7 months) respectively. Discussion: In this secondary analysis of a Phase 3 trial, omitting 24HRU assessments from IMWG criteria changed &lt;1% of responses and had no impact on PFS prediction at any response depth. 24HRU assessments had been performed for less than a third of patients as standard of care prior to study entry, underscoring its infrequent use outside of trials. Urine-free IMWG assessments would reduce time toxicity and discomfort for patients, particularly for those with limited dexterity. If implemented in trials, they would also simplify study logistics and lower operational costs. Outside of situations such as AL amyloidosis where 24HRU assessments remain critical or for patients with urine as their only measurable MM biomarker, our results support the removal of 24HRU assessments from future iterations of IMWG response criteria. Funding: Grants #U10HL069294 and #U24HL138660 to the BMT CTN from the NHLBI and the NCI; contributions by Celgene Corporation and Millennium Pharmaceuticals, Inc.; funding by The Alliance for Clinical Trials in Oncology, the ECOG-ACRIN Cancer Research Group and SWOG.

Background: Traumatic carotid artery pseudoaneurysms (PSAs) represent a vascular anomaly with potential for serious complications, including stroke. Traditional treatments involve endovascular stenting, which may not be ideally suited to otherwise healthy vessels that have the potential to remodel. Given the limitations of smaller animal models in replicating human vasculature and the need for improved treatment modalities, this study introduces a novel swine model for the creation and evaluation of carotid PSAs. Methods: The PSAs were created from bovine dura and anastomosed in an end-to-side fashion to bilateral carotid arteries. The PSAs were radiologically followed up post-operatively and were harvested at 3 and 10 days for histological analysis. Results: Pseudoaneurysms were successfully created in both animals without intra-operative or immediate post-operative complications. Radiological analysis showed well-perfused PSAs with intra-aneurysmal turbulence, hemodynamically mimicking human carotid artery PSAs. There was no evidence of thrombus or arterial stenosis. Histological examinations revealed thrombus maturation and tight anastomosis of the PSA sac with the native artery. Conclusions: This PSA swine model offers a replicable, cost-effective, and easily implemented tool with the potential to advance carotid PSA management and educational efforts in vascular surgery. Clinical Impact The model presented in this methodology paper allows for a standardized PSA animal model allowing for the standardization of a clinical entity which is frequently heterogenenous in morphology. This can allow for the development of new therapies or provide a ground truth for computer modelling for further in silico study.

Background: The optimal timing of pacemaker reimplantation following transvenous lead removal (TLR) of infected cardiac implantable electronic device (CIED) remains unclear. Objective: Our study aimed to assess the impact of timing to pacemaker reimplantation after TLR of infected CIED on hospital outcomes. Method: Using the Nationwide Readmissions Database, patients aged ≥18 years who underwent new pacemaker implantation with percutaneous approach following TLR of infected CIED from 2017 to 2020 were identified. The study population was stratified based on the timing of pacemaker reimplantation following TLR of infected CIED: early (<5 days) vs delayed (≥5 days). Weighted-propensity-score matched conditional multivariable logistic regressions were performed to determine the impact of the timing on various outcomes. Results: In our study, 469 (66.9%) patients received early device reimplantation, and 232 (33.1%) patients received delayed device reimplantation (≥5 days). Post-procedurally, patients in the delayed group had a higher risk of prolonged hospital stay (95% CI OR: 42.37 (6.36 – 282.11); p<0.01) and non-home discharge (95% CI OR: 2.00 (1.35 – 2.95), p<0.01). There was no significant difference between both groups in the early mortality, 30-day readmission, and procedural complications. Conclusion: Our study suggests that time-to-device reimplantation from TLR of infected CIED did not affect the overall short-term in-hospital outcomes. However, delayed device reimplantation was associated with a higher rate of prolonged hospital stay and non-home discharge.