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Most patients with triple-negative breast cancer (TNBC) are not candidates for targeted therapy, leaving chemotherapy as the primary treatment option. Recently, immunotherapy has demonstrated promising results in TNBC, due to its immunogenicity. In addition, a novel antibody–drug conjugate, namely, trastuzumab-deruxtecan, has shown effectiveness in TNBC patients with low-HER2 expression (HER2-low). These novel treatment options raise the question about the potential association between the density of stromal tumor-infiltrating lymphocytes (sTILs) and the level of HER2 expression. We aimed to evaluate the association between the level of HER2 expression (HER2-low versus HER2-0) and density of sTILs in TNBC patients, and how they impact the response to neoadjuvant chemotherapy (NAC). This was a retrospective multicenter study including all TNBC patients diagnosed between 2018 and 2022. Central pathology review included sTILs percentages and level of HER2 expression. Tumors were reclassified as either HER2-0 (HER2 IHC 0) or HER2-low (IHC 1 + or 2 + with negative reflex test). Various clinicopathologic characteristics, including sTILs density, and response to NAC were compared between HER2-0 and HER2-low cases. In total, 753 TNBC patients were included in this study, of which 292 patients received NAC. Interobserver agreement between the original pathology report and central review was moderate (77% had the same IHC status after reclassification in either HER2-0 or HER2-low; k = 0.45). HER2-low TNBC represented about one third (36%) of the tumors. No significant difference in sTILs density or complete pathologic response rate was found between HER2-0 and HER2-low cases (p = 0.476 and p = 0.339, respectively). The density of sTILs (≥ 10% sTILs vs. < 10%) was independently associated with achieving a pCR (p = 0.011). In conclusion, no significant association was found between HER2-low status and density of sTILs nor response to NAC. Nonetheless, sTILs could be an in

Purpose: Multifocal disease in PTC is associated with an increased recurrence rate. Multifocal disease (MD) is underdiagnosed with the current gold standard of pre-operative ultrasound staging. Here, we evaluate the use of EMI-137 targeted molecular fluorescence-guided imaging (MFGI) and spectroscopy as a tool for the intra-operative detection of uni- and multifocal papillary thyroid cancer (PTC) aiming to improve disease staging and treatment selection. Methods: A phase-1 study (NCT03470259) with EMI-137 was conducted to evaluate the possibility of detecting PTC using MFGI and quantitative fiber-optic spectroscopy. Results: Fourteen patients underwent hemi- or total thyroidectomy (TTX) after administration of 0.09 mg/kg (n = 1), 0.13 mg/kg (n = 8), or 0.18 mg/kg (n = 5) EMI-137. Both MFGI and spectroscopy could differentiate PTC from healthy thyroid tissue after administration of EMI-137, which binds selectively to MET in PTC. 0.13 mg/kg was the lowest dosage EMI-137 that allowed for differentiation between PTC and healthy thyroid tissue. The smallest PTC focus detected by MFGI was 1.4 mm. MFGI restaged 80% of patients from unifocal to multifocal PTC compared to ultrasound. Conclusion: EMI-137-guided MFGI and spectroscopy can be used to detect multifocal PTC. This may improve disease staging and treatment selection between hemi- and total thyroidectomy by better differentiation between unifocal and multifocal disease. Trial registration: NCT03470259.

Around 40–50% of all triple-negative breast cancer (TNBC) patients achieve a pathological complete response (pCR) after treatment with neoadjuvant chemotherapy (NAC). The identification of biomarkers predicting the response to NAC could be helpful for personalized treatment. This systematic review provides an overview of putative biomarkers at baseline that are predictive for a pCR following NAC. Embase, Medline and Web of Science were searched for articles published between January 2010 and August 2022. The articles had to meet the following criteria: patients with primary invasive TNBC without distant metastases and patients must have received NAC. In total, 2045 articles were screened by two reviewers resulting in the inclusion of 92 articles. Overall, the most frequently reported biomarkers associated with a pCR were a high expression of Ki-67, an expression of PD-L1 and the abundance of tumor-infiltrating lymphocytes, particularly CD8+ T cells, and corresponding immune gene signatures. In addition, our review reveals proteomic, genomic and transcriptomic markers that relate to cancer cells, the tumor microenvironment and the peripheral blood, which also affect chemo-sensitivity. We conclude that a prediction model based on a combination of tumor and immune markers is likely to better stratify TNBC patients with respect to NAC response.

Zebrafish and their mutant lines have been extensively used in cardiovascular studies. In the current study, the novel system, Zebra II, is presented for prolonged electrocardiogram (ECG) acquisition and analysis for multiple zebrafish within controllable working environments. The Zebra II is composed of a perfusion system, apparatuses, sensors, and an in-house electronic system. First, the Zebra II is validated in comparison with a benchmark system, namely iWORX, through various experiments. The validation displayed comparable results in terms of data quality and ECG changes in response to drug treatment. The effects of anesthetic drugs and temperature variation on zebrafish ECG were subsequently investigated in experiments that need real-time data assessment. The Zebra II's capability of continuous anesthetic administration enabled prolonged ECG acquisition up to 1 h compared to that of 5 min in existing systems. The novel, cloud-based, automated analysis with data obtained from four fish further provided a useful solution for combinatorial experiments and helped save significant time and effort. The system showed robust ECG acquisition and analytics for various applications including arrhythmia in sodium induced sinus arrest, temperature-induced heart rate variation, and drug-induced arrhythmia in Tg(SCN5A-D1275N) mutant and wildtype fish. The multiple channel acquisition also enabled the implementation of randomized controlled trials on zebrafish models. The developed ECG system holds promise and solves current drawbacks in order to greatly accelerate drug screening applications and other cardiovascular studies using zebrafish.

Packet loss concealment (PLC) is a tool for enhancing speech degradation caused by poor network conditions or underflow/overflow in audio processing pipelines. We propose a real-time recurrent method that leverages previous outputs to mitigate artefact of lost packets without the prior knowledge of loss mask. The proposed full-band recurrent network (FRN) model operates at 48 kHz, which is suitable for high-quality telecommunication applications. Experiment results highlight the superiority of FRN over an offline non-causal baseline and a top performer in a recent PLC challenge., Comment: In Proceedings ICASSP 2023, 5 pages, 1 figure, 4 tables

Purpose: Patients undergoing prophylactic central compartment dissection (PCLND) for papillary thyroid cancer (PTC) are often overtreated. This study aimed to determine if molecular fluorescence-guided imaging (MFGI) and spectroscopy can be useful for detecting PTC nodal metastases (NM) and to identify negative central compartments intraoperatively. Methods: We used a data-driven prioritization strategy based on transcriptomic profiles of 97 primary PTCs and 80 normal thyroid tissues (NTT) to identify tumor-specific antigens for a clinically available near-infrared fluorescent tracer. Protein expression of the top prioritized antigen was immunohistochemically validated with a tissue microarray containing primary PTC (n = 741) and NTT (n = 108). Staining intensity was correlated with 10-year locoregional recurrence-free survival (LRFS). A phase 1 study (NCT03470259) with EMI-137, targeting MET, was conducted to evaluate safety, optimal dosage for detecting PTC NM with MFGI, feasibility of NM detection with quantitative fiber-optic spectroscopy, and selective binding of EMI-137 for MET. Results: MET was selected as the most promising antigen. A worse LRFS was observed in patients with positive versus negative MET staining (81.9% versus 93.2%; p = 0.02). In 19 patients, no adverse events related to EMI-137 occurred. 0.13 mg/kg EMI-137 was selected as optimal dosage for differentiating NM from normal lymph nodes using MFGI (p < 0.0001) and spectroscopy (p < 0.0001). MFGI identified 5/19 levels (26.3%) without NM. EMI-137 binds selectively to MET. Conclusion: MET is overexpressed in PTC and associated with increased locoregional recurrence rates. Perioperative administration of EMI-137 is safe and facilitates NM detection using MFGI and spectroscopy, potentially reducing the number of negative PCLNDs with more than 25%. Clinical trial registration.: NCT03470259.

The purpose of this review is to assess the state-of-the-art fabrication methods, advances in genome editing, and the use of machine learning to shape the prospective growth in cardiac tissue engineering. Those interdisciplinary emerging innovations would move forward basic research in this field and their clinical applications. The long-entrenched challenges in this field could be addressed by novel 3-dimensional (3D) scaffold substrates for cardiomyocyte (CM) growth and maturation. Stem cell-based therapy through genome editing techniques can repair gene mutation, control better maturation of CMs or even reveal its molecular clock. Finally, machine learning and precision control for improvements of the construct fabrication process and optimization in tissue-specific clonal selections with an outlook of cardiac tissue engineering are also presented.

The purpose of this review is to assess the state-of-the-art fabrication methods, advances in genome editing, and the use of machine learning to shape the prospective growth in cardiac tissue engineering. Those interdisciplinary emerging innovations would move forward basic research in this field and their clinical applications. The long-entrenched challenges in this field could be addressed by novel 3-dimensional (3D) scaffold substrates for cardiomyocyte (CM) growth and maturation. Stem cell-based therapy through genome editing techniques can repair gene mutation, control better maturation of CMs or even reveal its molecular clock. Finally, machine learning and precision control for improvements of the construct fabrication process and optimization in tissue-specific clonal selections with an outlook of cardiac tissue engineering are also presented.

A chip-based electrochemical biosensor is developed herein for the detection of organophosphate (OP) in food materials. The principle of the sensing platform is based on the inhibition of dimethoate (DMT), a typical OP that specifically inhibits acetylcholinesterase (AChE) activity. Carbon nanotube-modified gold electrodes functionalized with polydiallyldimethylammonium chloride (PDDA) and oxidized nanocellulose (NC) were investigated for the sensing of OP, yielding high sensitivity. Compared with noncovalent adsorption and deposition in bovine serum albumin, bioconjugation with lysine side chain activation allowed the enzyme to be stable over three weeks at room temperature. The total amount of AChE was quantified, whose activity inhibition was highly linear with respect to DMT concentration. Increased incubation times and/or DMT concentration decreased current flow. The composite electrode showed a sensitivity 4.8-times higher than that of the bare gold electrode. The biosensor was challenged with organophosphate-spiked food samples and showed a limit of detection (LOD) of DMT at 4.1 nM, with a limit of quantification (LOQ) at 12.6 nM, in the linear range of 10 nM to 1000 nM. Such performance infers significant potential for the use of this system in the detection of organophosphates in real samples.

A chip-based electrochemical biosensor is developed herein for the detection of organophosphate (OP) in food materials. The principle of the sensing platform is based on the inhibition of dimethoate (DMT), a typical OP that specifically inhibits acetylcholinesterase (AChE) activity. Carbon nanotube-modified gold electrodes functionalized with polydiallyldimethylammonium chloride (PDDA) and oxidized nanocellulose (NC) were investigated for the sensing of OP, yielding high sensitivity. Compared with noncovalent adsorption and deposition in bovine serum albumin, bioconjugation with lysine side chain activation allowed the enzyme to be stable over three weeks at room temperature. The total amount of AChE was quantified, whose activity inhibition was highly linear with respect to DMT concentration. Increased incubation times and/or DMT concentration decreased current flow. The composite electrode showed a sensitivity 4.8-times higher than that of the bare gold electrode. The biosensor was challenged with organophosphate-spiked food samples and showed a limit of detection (LOD) of DMT at 4.1 nM, with a limit of quantification (LOQ) at 12.6 nM, in the linear range of 10 nM to 1000 nM. Such performance infers significant potential for the use of this system in the detection of organophosphates in real samples.

We introduce a block-online variant of the temporal feature-wise linear modulation (TFiLM) model to achieve bandwidth extension. The proposed architecture simplifies the UNet backbone of the TFiLM to reduce inference time and employs an efficient transformer at the bottleneck to alleviate performance degradation. We also utilize self-supervised pretraining and data augmentation to enhance the quality of bandwidth extended signals and reduce the sensitivity with respect to downsampling methods. Experiment results on the VCTK dataset show that the proposed method outperforms several recent baselines in both intrusive and non-intrusive metrics. Pretraining and filter augmentation also help stabilize and enhance the overall performance., Comment: Published as a conference paper at ICASSP 2022, 5 pages, 4 figures, 3 tables

In blind source separation of speech signals, the inherent imbalance in the source spectrum poses a challenge for methods that rely on single-source dominance for the estimation of the mixing matrix. We propose an algorithm based on the directional sparse filtering (DSF) framework that utilizes the Lehmer mean with learnable weights to adaptively account for source imbalance. Performance evaluation in multiple real acoustic environments show improvements in source separation compared to the baseline methods., Comment: (c) 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

OBJECTIVES: This study was conducted in order to evaluate the effect of geometric distortion (GD) on MRI lung volume quantification and evaluate available manual, semi-automated, and fully automated methods for lung segmentation.METHODS: A phantom was scanned with MRI and CT. GD was quantified as the difference in phantom's volume between MRI and CT, with CT as gold standard. Dice scores were used to measure overlap in shapes. Furthermore, 11 subjects from a prospective population-based cohort study each underwent four chest MRI acquisitions. The resulting 44 MRI scans with 2D and 3D Gradwarp were used to test five segmentation methods. Intraclass correlation coefficient, Bland-Altman plots, Wilcoxon, Mann-Whitney U, and paired t tests were used for statistics.RESULTS: Using phantoms, volume differences between CT and MRI varied according to MRI positions and 2D and 3D Gradwarp correction. With the phantom located at the isocenter, MRI overestimated the volume relative to CT by 5.56 ± 1.16 to 6.99 ± 0.22% with body and torso coils, respectively. Higher Dice scores and smaller intraobject differences were found for 3D Gradwarp MR images. In subjects, semi-automated and fully automated segmentation tools showed high agreement with manual segmentations (ICC = 0.971-0.993 for end-inspiratory scans; ICC = 0.992-0.995 for end-expiratory scans). Manual segmentation time per scan was approximately 3-4 h and 2-3 min for fully automated methods.CONCLUSIONS: Volume overestimation of MRI due to GD can be quantified. Semi-automated and fully automated segmentation methods allow accurate, reproducible, and fast lung volume quantification. Chest MRI can be a valid radiation-free imaging modality for lung segmentation and volume quantification in large cohort studies.KEY POINTS: • Geometric distortion varies according to MRI setting and patient positioning. • Automated segmentation methods allow fast and accurate lung volume quantification. • MRI is a

OBJECTIVES: This study was conducted in order to evaluate the effect of geometric distortion (GD) on MRI lung volume quantification and evaluate available manual, semi-automated, and fully automated methods for lung segmentation.METHODS: A phantom was scanned with MRI and CT. GD was quantified as the difference in phantom's volume between MRI and CT, with CT as gold standard. Dice scores were used to measure overlap in shapes. Furthermore, 11 subjects from a prospective population-based cohort study each underwent four chest MRI acquisitions. The resulting 44 MRI scans with 2D and 3D Gradwarp were used to test five segmentation methods. Intraclass correlation coefficient, Bland-Altman plots, Wilcoxon, Mann-Whitney U, and paired t tests were used for statistics.RESULTS: Using phantoms, volume differences between CT and MRI varied according to MRI positions and 2D and 3D Gradwarp correction. With the phantom located at the isocenter, MRI overestimated the volume relative to CT by 5.56 ± 1.16 to 6.99 ± 0.22% with body and torso coils, respectively. Higher Dice scores and smaller intraobject differences were found for 3D Gradwarp MR images. In subjects, semi-automated and fully automated segmentation tools showed high agreement with manual segmentations (ICC = 0.971-0.993 for end-inspiratory scans; ICC = 0.992-0.995 for end-expiratory scans). Manual segmentation time per scan was approximately 3-4 h and 2-3 min for fully automated methods.CONCLUSIONS: Volume overestimation of MRI due to GD can be quantified. Semi-automated and fully automated segmentation methods allow accurate, reproducible, and fast lung volume quantification. Chest MRI can be a valid radiation-free imaging modality for lung segmentation and volume quantification in large cohort studies.KEY POINTS: • Geometric distortion varies according to MRI setting and patient positioning. • Automated segmentation methods allow fast and accurate lung volume quantification. • MRI is a

Matrix metalloproteinases (MMPs) remodel the extracellular matrix (ECM) to facilitate epithelial-to-mesenchymal transitions (EMTs) and promote cell specification during embryonic development. In this study, we hypothesized that introducing degradable ECM-based biomaterials to pluripotent stem cell (PSC) aggregates would modulate endogenous proteolytic activity and consequently enhance the differentiation and morphogenesis within 3D PSC aggregates. Gelatin methacrylate (GMA) microparticles (MPs) of low (∼20%) or high (∼90%) cross-linking densities were incorporated into mouse embryonic stem cell (ESC) aggregates, and the effects on MMP activity and cell differentiation were examined with or without MMP inhibition. ESC aggregates containing GMA MPs expressed significantly higher levels of total MMP and MMP-2 than aggregates without MPs. GMA MP incorporation increased expression of EMT markers and enhanced mesenchymal morphogenesis of PSC aggregates. MMP inhibition completely abrogated these effects, and GMA MP-induced MMP activation within ESC aggregates was partially reduced by pSMAD 1/5/8 inhibition. These results suggest that GMA particles activate MMPs by protease-substrate interactions to promote EMT and mesenchymal morphogenesis of ESC aggregates in an MMP-dependent manner. We speculate that controlling protease activity via the introduction of ECM-based materials may offer a novel route to engineer the ECM microenvironment to modulate stem cell differentiation.

Matrix metalloproteinases (MMPs) remodel the extracellular matrix (ECM) to facilitate epithelial-to-mesenchymal transitions (EMTs) and promote cell specification during embryonic development. In this study, we hypothesized that introducing degradable ECM-based biomaterials to pluripotent stem cell (PSC) aggregates would modulate endogenous proteolytic activity and consequently enhance the differentiation and morphogenesis within 3D PSC aggregates. Gelatin methacrylate (GMA) microparticles (MPs) of low (∼20%) or high (∼90%) cross-linking densities were incorporated into mouse embryonic stem cell (ESC) aggregates, and the effects on MMP activity and cell differentiation were examined with or without MMP inhibition. ESC aggregates containing GMA MPs expressed significantly higher levels of total MMP and MMP-2 than aggregates without MPs. GMA MP incorporation increased expression of EMT markers and enhanced mesenchymal morphogenesis of PSC aggregates. MMP inhibition completely abrogated these effects, and GMA MP-induced MMP activation within ESC aggregates was partially reduced by pSMAD 1/5/8 inhibition. These results suggest that GMA particles activate MMPs by protease-substrate interactions to promote EMT and mesenchymal morphogenesis of ESC aggregates in an MMP-dependent manner. We speculate that controlling protease activity via the introduction of ECM-based materials may offer a novel route to engineer the ECM microenvironment to modulate stem cell differentiation.

In wireless communications, it is of utmost importance to exploit multi-user diversity and at the same time provide satisfactory quality of service for all users. However, these two goals often conflict with each other. On one hand, multiuser diversity is maximized by selecting the user with the best channel condition. On the other, ensuring fairness among users demands the allocation of network resources to those who do not necessarily have the best channel conditions. Whenever a user with a poorer channel condition is selected, there is a certain loss in the overall system throughput. The major objective of this thesis is to find scheduling algorithms that guarantee fairness with minimal performance tradeoff. First, we consider multi-user diversity in a multi-user MIMO system. When zero-forcing beam-forming transmission technique is used, the system needs to find a subset of users such that the transmission to these users results in the highest throughput. As the number of users grows, the complexity of the user subset selection increases exponentially. To address this issue, simple user-subset-selection algorithms have been developed that can perform well and are very close to the optimal ones found through an exhaustive search. Maximizing system throughput is a key factor in ensuring high network performance, but guaranteeing service provision to all users is no less important. To support fairness among users, cumulative distribution function (CDF) scheduling is utilized because of the its capability to precisely control allocation for each user. The CDF scheduling algorithm requires knowledge of the channel distribution among all users. However, the channel distribution or even an approximation of it is hard to obtain in real systems. In this dissertation, two classes of practical, CDF-based scheduling algorithms are developed. They are the non-parametric CDF scheduling (NPCS), used when the channel model is unknown, and the parametric CDF scheduling (PCS), use

In wireless communications, it is of utmost importance to exploit multi-user diversity and at the same time provide satisfactory quality of service for all users. However, these two goals often conflict with each other. On one hand, multiuser diversity is maximized by selecting the user with the best channel condition. On the other, ensuring fairness among users demands the allocation of network resources to those who do not necessarily have the best channel conditions. Whenever a user with a poorer channel condition is selected, there is a certain loss in the overall system throughput. The major objective of this thesis is to find scheduling algorithms that guarantee fairness with minimal performance tradeoff. First, we consider multi-user diversity in a multi-user MIMO system. When zero-forcing beam-forming transmission technique is used, the system needs to find a subset of users such that the transmission to these users results in the highest throughput. As the number of users grows, the complexity of the user subset selection increases exponentially. To address this issue, simple user-subset-selection algorithms have been developed that can perform well and are very close to the optimal ones found through an exhaustive search. Maximizing system throughput is a key factor in ensuring high network performance, but guaranteeing service provision to all users is no less important. To support fairness among users, cumulative distribution function (CDF) scheduling is utilized because of the its capability to precisely control allocation for each user. The CDF scheduling algorithm requires knowledge of the channel distribution among all users. However, the channel distribution or even an approximation of it is hard to obtain in real systems. In this dissertation, two classes of practical, CDF-based scheduling algorithms are developed. They are the non-parametric CDF scheduling (NPCS), used when the channel model is unknown, and the parametric CDF scheduling (PCS), use