Cancer-associated POT1 mutations lead to telomere elongation without induction of a DNA damage response.

Mutations in the shelterin protein POT1 are associated with chronic lymphocytic leukemia (CLL), Hodgkin lymphoma, angiosarcoma, melanoma, and other cancers. These cancer-associated POT1 (caPOT1) mutations are generally heterozygous, missense, or nonsense mutations occurring throughout the POT1 reading frame. Cancers with caPOT1 mutations have elongated telomeres and show increased genomic instability, but which of the two phenotypes promotes tumorigenesis is unclear. We tested the effects of CAS9-engineered caPOT1 mutations in human embryonic and hematopoietic stem cells (hESCs and HSCs, respectively). HSCs with caPOT1 mutations did not show overt telomere damage. In vitro and in vivo competition experiments showed the caPOT1 mutations did not confer a selective disadvantage. Since DNA damage signaling is known to affect the fitness of HSCs, the data argue that caPOT1 mutations do not cause significant telomere damage. Furthermore, hESC lines with caPOT1 mutations showed no detectable telomere damage response while showing consistent telomere elongation. Thus, caPOT1 mutations are likely selected for during cancer progression because of their ability to elongate telomeres and extend the proliferative capacity of the incipient cancer cells.

Deep Reinforcement Learning-Based Adaptive Scheduling for Wireless Time-Sensitive Networking.

Time-sensitive networking (TSN) technologies have garnered attention for supporting time-sensitive communication services, with recent interest extending to the wireless domain. However, adapting TSN to wireless areas faces challenges due to the competitive channel utilization in IEEE 802.11, necessitating exclusive channels for low-latency services. Additionally, traditional TSN scheduling algorithms may cause significant transmission delays due to dynamic wireless characteristics, which must be addressed. This paper proposes a wireless TSN model of IEEE 802.11 networks for the exclusive channel access and a novel time-sensitive traffic scheduler, named the wireless intelligent scheduler (WISE), based on deep reinforcement learning. We designed a deep reinforcement learning (DRL) framework to learn the repetitive transmission patterns of time-sensitive traffic and address potential latency issues from changing wireless conditions. Within this framework, we identified the most suitable DRL model, presenting the WISE algorithm with the best performance. Experimental results indicate that the proposed mechanisms meet up to 99.9% under the various wireless communication scenarios. In addition, they show that the processing delay is successfully limited within the specific time requirements and the scalability of TSN streams is guaranteed by the proposed mechanisms.

Differential Urinary Microbiome and Its Metabolic Footprint in Bladder Cancer Patients Following BCG Treatment.

Recent studies have identified a urinary microbiome, dispelling the myth of urine sterility. Intravesical bacillus Calmette-Guérin (BCG) therapy is the preferred treatment for intermediate to high-risk non-muscle-invasive bladder cancer (BCa), although resistance occurs in 30-50% of cases. Progression to muscle-invasive cancer necessitates radical cystectomy. Our research uses 16S rRNA gene sequencing to investigate how the urinary microbiome influences BCa and its response to BCG therapy. Urine samples were collected via urethral catheterization from patients with benign conditions and non-muscle-invasive BCa, all of whom underwent BCG therapy. We utilized 16S rRNA gene sequencing to analyze the bacterial profiles and metabolic pathways in these samples. These pathways were validated using a real metabolite dataset, and we developed predictive models for malignancy and BCG response. In this study, 87 patients participated, including 29 with benign diseases and 58 with BCa. We noted distinct bacterial compositions between benign and malignant samples, indicating the potential role of the toluene degradation pathway in mitigating BCa development. Responders to BCG had differing microbial compositions and higher quinolone synthesis than non-responders, with two Bifidobacterium species being prevalent among responders, associated with prolonged recurrence-free survival. Additionally, we developed highly accurate predictive models for malignancy and BCG response. Our study delved into the mechanisms behind malignancy and BCG responses by focusing on the urinary microbiome and metabolic pathways. We pinpointed specific beneficial microbes and developed clinical models to predict malignancy and BCG therapy outcomes. These models can track recurrence and facilitate early predictions of treatment responses.

Characterization of 3D Organotypic Culture of Mouse Adipose-Derived Stem Cells.

Although stem cells are a promising avenue for harnessing the potential of adipose tissue, conventional two-dimensional (2D) culture methods have limitations. This study explored the use of three-dimensional (3D) cultures to preserve the regenerative potential of adipose-derived stem cells (ADSCs) and investigated their cellular properties. Flow cytometric analysis revealed significant variations in surface marker expressions between the two culture conditions. While 2D cultures showed robust surface marker expressions, 3D cultures exhibited reduced levels of CD44, CD90.2, and CD105. Adipogenic differentiation in 3D organotypic ADSCs faced challenges, with decreased organoid size and limited activation of adipogenesis-related genes. Key adipocyte markers, such as lipoprotein lipase (LPL) and adipoQ, were undetectable in 3D-cultured ADSCs, unlike positive controls in 2D-cultured mesenchymal stem cells (MSCs). Surprisingly, 3D-cultured ADSCs underwent mesenchymal-epithelial transition (MET), evidenced by increased E-cadherin and EpCAM expression and decreased mesenchymal markers. This study highlights successful ADSC organoid formation, notable MSC phenotype changes in 3D culture, adipogenic differentiation challenges, and a distinctive shift toward an epithelial-like state. These findings offer insights into the potential applications of 3D-cultured ADSCs in regenerative medicine, emphasizing the need for further exploration of underlying molecular mechanisms.

Multitask Learning-Based Deep Signal Identification for Advanced Spectrum Sensing.

The explosive demand for wireless communications has intensified the complexity of spectrum dynamics, particularly within unlicensed bands. To promote efficient spectrum utilization and minimize interference during communication, spectrum sensing needs to evolve to a stage capable of detecting multidimensional spectrum states. Signal identification, which identifies each device's signal source, is a potent method for deriving the spectrum usage characteristics of wireless devices. However, most existing signal identification methods mainly focus on signal classification or modulation classification, thus offering limited spectrum information. In this paper, we propose DSINet, a multitask learning-based deep signal identification network for advanced spectrum sensing systems. DSINet addresses the deep signal identification problem, which involves not only classifying signals but also deriving the spectrum usage characteristics of signals across various spectrum dimensions, including time, frequency, power, and code. Comparative analyses reveal that DSINet outperforms existing shallow signal identification models, with performance improvements of 3.3% for signal classification, 3.3% for hall detection, and 5.7% for modulation classification. In addition, DSINet solves four different tasks with a 65.5% smaller model size and 230% improved computational performance compared to single-task learning model sets, providing meaningful results in terms of practical use.

A Semantic Data-Based Distributed Computing Framework to Accelerate Digital Twin Services for Large-Scale Disasters.

As natural disasters become extensive, due to various environmental problems, such as the global warming, it is difficult for the disaster management systems to rapidly provide disaster prediction services, due to complex natural phenomena. Digital twins can effectively provide the services using high-fidelity disaster models and real-time observational data with distributed computing schemes. However, the previous schemes take little account of the correlations between environmental data of disasters, such as landscapes and weather. This causes inaccurate computing load predictions resulting in unbalanced load partitioning, which increases the prediction service times of the disaster management agencies. In this paper, we propose a novel distributed computing framework to accelerate the prediction services through semantic analyses of correlations between the environmental data. The framework combines the data into disaster semantic data to represent the initial disaster states, such as the sizes of wildfire burn scars and fuel models. With the semantic data, the framework predicts computing loads using the convolutional neural network-based algorithm, partitions the simulation model into balanced sub-models, and allocates the sub-models into distributed computing nodes. As a result, the proposal shows up to 38.5% of the prediction time decreases, compared to the previous schemes.

DRL-OS: A Deep Reinforcement Learning-Based Offloading Scheduler in Mobile Edge Computing.

Hardware bottlenecks can throttle smart device (SD) performance when executing computation-intensive and delay-sensitive applications. Hence, task offloading can be used to transfer computation-intensive tasks to an external server or processor in Mobile Edge Computing. However, in this approach, the offloaded task can be useless when a process is significantly delayed or a deadline has expired. Due to the uncertain task processing via offloading, it is challenging for each SD to determine its offloading decision (whether to local or remote and drop). This study proposes a deep-reinforcement-learning-based offloading scheduler (DRL-OS) that considers the energy balance in selecting the method for performing a task, such as local computing, offloading, or dropping. The proposed DRL-OS is based on the double dueling deep Q-network (D3QN) and selects an appropriate action by learning the task size, deadline, queue, and residual battery charge. The average battery level, drop rate, and average latency of the DRL-OS were measured in simulations to analyze the scheduler performance. The DRL-OS exhibits a lower average battery level (up to 54%) and lower drop rate (up to 42.5%) than existing schemes. The scheduler also achieves a lower average latency of 0.01 to >0.25 s, despite subtle case-wise differences in the average latency.

A Novel Digital Twin Architecture with Similarity-Based Hybrid Modeling for Supporting Dependable Disaster Management Systems.

Disaster management systems require accurate disaster monitoring and prediction services to reduce damages caused by natural disasters. Digital twins of natural environments can provide the services for the systems with physics-based and data-driven disaster models. However, the digital twins might generate erroneous disaster prediction due to the impracticability of defining high-fidelity physics-based models for complex natural disaster behavior and the dependency of data-driven models on the training dataset. This causes disaster management systems to inappropriately use disaster response resources, including medical personnel, rescue equipment and relief supplies, to ensure that it may increase the damages from the natural disasters. This study proposes a digital twin architecture to provide accurate disaster prediction services with a similarity-based hybrid modeling scheme. The hybrid modeling scheme creates a hybrid disaster model that compensates for the errors of physics-based prediction results with a data-driven error correction model to enhance the prediction accuracy. The similarity-based hybrid modeling scheme reduces errors from the data dependency of the hybrid model by constructing a training dataset using similarity assessments between the target disaster and the historical disasters. Evaluations in wildfire scenarios show that the digital twin decreases prediction errors by approximately 50% compared with those of the existing schemes.

Secretory SERPINE1 Expression Is Increased by Antiplatelet Therapy, Inducing MMP1 Expression and Increasing Colon Cancer Metastasis.

Contrary to many reports that antiplatelet agents inhibit cancer growth and metastasis, new solid tumors have been reported in patients receiving long-term antiplatelet therapy. We investigated the effects of these agents directly on cancer cells in the absence of platelets to mimic the effects of long-term therapy. When four antiplatelet agents (aspirin, clopidogrel, prasugrel, and ticagrelor) were administered to colon cancer cells, cancer cell proliferation was inhibited similarly to a previous study. However, surprisingly, when cells were treated with a purinergic P2Y12 inhibitor (purinergic antiplatelet agent), the motility of the cancer cells was significantly increased. Therefore, gene expression profiles were identified to investigate the effect of P2Y12 inhibitors on cell mobility, and Serpin family 1 (SERPINE1) was identified as a common gene associated with cell migration and cell death in three groups. Antiplatelet treatment increased the level of SERPINE1 in cancer cells and also promoted the secretion of SERPINE1 into the medium. Increased SERPINE1 was found to induce MMP1 and, thus, increase cell motility. In addition, an increase in SERPINE1 was confirmed using the serum of patients who received these antiplatelet drugs. With these results, we propose that SERPINE1 could be used as a new target gene to prevent the onset and metastasis of cancer in patients with long-term antiplatelet therapy.

Utility of a Molecular Signature for Predicting Recurrence and Progression in Non-Muscle-Invasive Bladder Cancer Patients: Comparison with the EORTC, CUETO and 2021 EAU Risk Groups.

To evaluate the utility of different risk assessments in non-muscle-invasive bladder cancer (NMIBC) patients, a total of 178 NMIBC patients from Chungbuk National University Hospital (CBNUH) were enrolled, and the predictive value of the molecular signature-based subtype predictor (MSP888) and risk calculators based on clinicopathological factors (EORTC, CUETO and 2021 EAU risk scores) was compared. Of the 178 patients, 49 were newly analyzed by the RNA-sequencing, and their MSP888 subtype was evaluated. The ability of the EORTC, MSP888 and two molecular subtyping systems of bladder cancer (Lund and UROMOL subtypes) to predict progression of 460 NMIBC patients from the UROMOL project was assessed. Cox regression analyses showed that the MSP888 was an independent predictor of NMIBC progression in the CBNUH cohort (p = 0.043). Particularly in patients without an intravesical BCG immunotherapy, MSP888 significantly linked with risk of disease recurrence and progression (both p < 0.05). However, the EORTC, CUETO and 2021 EAU risk scores showed disappointing results with respect to estimating the NMIBC prognosis. In the UROMOL cohort, the MSP888, Lund and UROMOL subtypes demonstrated a similar capacity to predict NMIBC progression (all p < 0.05). Conclusively, the MSP888 is favorable for stratifying patients to facilitate optimal treatment.

Effect of pre-operative internal obturator muscle mass index in MRI on biochemical recurrence of prostate cancer patients after radical prostatectomy: a multi-center study.

BACKGROUND: Recent reports show that the pre-operative or post-operative skeletal mass index (sarcopenia) affects survival rates for various cancers; however, the link between prostate cancer survival and sarcopenia is unclear. Therefore, this study examined the effect of the pre-operative internal obturator muscle (IOM) mass index on biochemical recurrence (BCR) of prostate cancer (PCa) patients who underwent radical prostatectomy. METHODS: In total, 222 patients, who underwent open, laparoscopic, or robot-assisted radical prostatectomy at seven centers in 2011 and were followed up for 5 years, were enrolled. BCR was examined in the context of pre-operative IOM mass index and BMI. RESULTS: The mean age of the patients was 67.82 ± 6.23 years, and the mean pre-operative prostate-specific antigen (PSA) level was 11.61 ± 13.22 ng/ml. There was no significant difference in baseline characteristics between the low and high IOM mass index groups (p > 0.05). Age, pre-op PSA level, ECE, and T-stage were associated with BCR (p = 0.049, p < 0.001, p = 0.001, p = 0.004, respectively). BMI, prostate volume, Gleason score, resection margin, N-stage, M-stage and IOM mass index was not associated with BCR (p > 0.05). CONCLUSIONS: Pre-operative IOM mass index was not associated with BCR; however, long-term follow-up is necessary to evaluate cancer-specific and overall survival of PCa patients.

Prognostic Value of BUB1 for Predicting Non-Muscle-Invasive Bladder Cancer Progression.

Non-muscle-invasive bladder cancer (NMIBC) is a common disease with a high recurrence rate requiring lifetime surveillance. Although NMIBC is not life-threatening, it can progress to muscle-invasive bladder cancer (MIBC), a lethal form of the disease. The management of the two diseases differs, and patients with MIBC require aggressive treatments such as chemotherapy and radical cystectomy. NMIBC patients at a high risk of progression benefit from early immediate cystectomy. Thus, identifying concordant markers for accurate risk stratification is critical to predict the prognosis of NMIBC. Candidate genetic biomarkers associated with NMIBC prognosis were screened by RNA-sequencing of 24 tissue samples, including 16 NMIBC and eight normal controls, and by microarray analysis (GSE13507). Lastly, we selected and investigated a mitotic checkpoint serine/threonine kinase, BUB1, that regulates chromosome segregation during the cell cycle. BUB1 gene expression was tested in 86 NMIBC samples and 15 controls by real-time qPCR. The performance of BUB1 as a prognostic biomarker for NMIBC was validated in the internal Chungbuk cohort (GSE13507) and the external UROMOL cohort (E-MTAB-4321). BUB1 expression was higher in NMIBC patients than in normal controls (p < 0.05), and the overexpression of BUB1 was correlated with NMIBC progression (log-rank test, p = 0.007). In in vitro analyses, BUB1 promoted the proliferation of bladder cancer cells by accelerating the G2/M transition of the cell cycle. Conclusively, BUB1 modulates the G2/M transition to promote the proliferation of bladder cancer cells, suggesting that it could serve as a prognostic marker in NMIBC.

A Molecular Signature Determines the Prognostic and Therapeutic Subtype of Non-Muscle-Invasive Bladder Cancer Responsive to Intravesical Bacillus Calmette-Guérin Therapy.

Non-muscle-invasive bladder cancer (NMIBC) is clinically heterogeneous; thus, many patients fail to respond to treatment and relapse. Here, we identified a molecular signature that is both prognostic and predictive for NMIBC heterogeneity and responses to Bacillus Calmette-Guérin (BCG) therapy. Transcriptomic profiling of 948 NMIBC patients identified a signature-based subtype predictor, MSP888, along with three distinct molecular subtypes: DP.BCG+ (related to progression and response to BCG treatment), REC.BCG+ (related to recurrence and response to BCG treatment), and EP (equivocal prognosis). Patients with the DP.BCG+ subtype showed worse progression-free survival but responded to BCG treatment, whereas those with the REC.BCG+ subtype showed worse recurrence-free survival but responded to BCG treatment. Multivariate analyses revealed that MSP888 showed independent clinical utility for predicting NMIBC prognosis (each p = 0.001 for progression and recurrence, respectively). Comparative analysis of this classifier and previously established molecular subtypes (i.e., Lund taxonomy and UROMOL class) revealed that a great proportion of patients were similar between subtypes; however, the MSP888 predictor better differentiated biological activity or responsiveness to BCG treatment. Our data increase our understanding of the mechanisms underlying the poor prognosis of NMIBC and the effectiveness of BCG therapy, which should improve clinical practice and complement other diagnostic tools.

A Low Geriatric Nutritional Risk Index is Associated with Aggressive Pathologic Characteristics and Poor Survival after Nephrectomy in Clear Renal Cell Carcinoma: A Multicenter Retrospective Study.

Purpose: To investigated the prognostic significance of the geriatric nutritional risk index (GNRI) in patients with surgically treated clear cell renal cell carcinoma (ccRCC).Patients and methods: We retrospectively selected 4,591 consecutive patients with surgically treated ccRCC from a multi-institutional Korean collaboration between 1988 and 2015. The clinical significance of the GNRI as a continuous and categorical variable was determined.Results: Preoperative low GNRI was significantly associated with older age, low body mass index, presence of diabetes, poor performance status, and presence of symptoms at diagnosis, as well as pathologic features such as aggressive tumor characteristics including large tumor size, advanced stage, high nuclear grade, lymphovascular invasion, sarcomatous differentiation, and tumor necrosis. A low GNRI was significantly associated with a short recurrence-free survival (RFS) in localized (pT1-2N0M0) ccRCC and cancer-specific survival (CSS) in the entire cohort, and with short RFS and CSS in the subgroup analysis according to age categories (≤65 and >65 years). Multivariate Cox regression analysis showed that preoperative GNRI, as a continuous or categorical variable, was an independent predictor of RFS and CSS.Conclusion: Malnutrition as assessed by the preoperative GNRI is associated with aggressive tumor characteristics and poor survival in patients with surgically treated ccRCC.

Effects of poloxamer-based thermo-sensitive sol-gel agent on urethral stricture after transurethral resection of the prostate for benign prostatic hyperplasia: a multicentre, single-blinded, randomised controlled trial.

OBJECTIVE: To evaluate the effectiveness of poloxamer-based thermo-sensitive sol-gel instillation, after transurethral resection of the prostate (TURP), for preventing urethral stricture. PATIENTS AND METHODS: In all, 198 patients underwent TURP for benign prostatic hyperplasia. Recruited patients were randomly divided into two groups: groups A and B. Patients in Group A (100 patients, experimental group) received poloxamer-based thermo-sensitive sol-gel instillation and patients in the Group B (98 patients, control group) received lubricant instillation after TURP. Each patient was evaluated at 4 (V1), 12 (V2), and 24 weeks (V3) after TURP. The effectiveness of poloxamer-based thermo-sensitive sol-gel instillation was evaluated based on the International Prostate Symptom Score (IPSS), IPSS-Quality of Life (QoL), Overactive bladder questionnaire (OAB-q), maximum urinary flow rate (Qmax ), post-void residual urine volume (PVR), and cystoscopy. RESULTS: Amongst the initial 198 participants, 80 patients in Group A and 83 in Group B completed the study. There were no significant differences in IPSS-QoL and OAB-q between the groups. However, Qmax was significantly different between groups A and B, at a mean (SD) of 18.92 (9.98) vs 15.58 (9.24) mL/s (P = 0.028) at 24 weeks after TURP. On cystoscopic examination, urethral stricture after TURP was found in two of the 80 patients in Group A and 10 of 83 in Group B (P = 0.023). CONCLUSIONS: Poloxamer-based thermo-sensitive sol-gel instillation after TURP lowered the incidence of urethral stricture.

Intraoperative allogeneic blood transfusion is associated with adverse oncological outcomes in patients with surgically treated non-metastatic clear cell renal cell carcinoma.

BACKGROUND: The objective of this study was to provide more definitive information about the prognostic impact of perioperative blood transfusion (PBT) on patients with surgically treated renal cell carcinoma (RCC). METHODS: A database of 4019 patients with clear cell RCC, all of whom underwent radical or partial nephrectomy as primary therapy as part of a multi-institutional Korean collaboration between 1988 and 2015, was analyzed retrospectively. PBT was defined as transfusion of allogeneic red blood cells during surgery or postsurgical period. Receipt of a PBT, as well as the amount and time of blood transfusion (BT), was compared. RESULTS: Overall, 335 (8.3%) patients received a PBT: 84 received postoperative BT, 202 received intraoperative BT, and 49 received both intraoperative and postoperative BT. Patients receiving a PBT had a poor preoperative immuno-nutritional status, and aggressive tumor characteristics. Multivariate analyses identified PBT as an independent predictor of recurrence-free survival and cancer-specific survival. Prognostic impact of PBT was restricted to those with locally advanced stage (pT3-4), and who underwent radical nephrectomy. Among patients who received a PBT, intraoperative (but not postoperative) BT was a prognostic factor for survival. Among patients who received intraoperative BT, those receiving three or more transfusion units had a significantly worse survival. CONCLUSION: Receipt of a PBT was an independent predictor of RFS and CSS in patients with surgically treated RCC, specifically locally advanced disease. Regarding the prognostic impact of timing or dose of PBT on survival, intraoperative BT and ≥ 3 pRBC units were associated with adverse oncological outcomes.

E2F1 Promotes Progression of Bladder Cancer by Modulating RAD54L Involved in Homologous Recombination Repair.

DNA repair defects are important factors in cancer development. High DNA repair activity can affect cancer progression and chemoresistance. DNA double-strand breaks in cancer cells caused by anticancer agents can be restored by non-homologous end joining (NHEJ) and homologous recombination repair (HRR). Our previous study has identified E2F1 as a key gene in bladder cancer progression. In this study, DNA repair genes related to E2F1 were analyzed, and RAD54L involved in HRR was identified. In gene expression analysis of bladder cancer patients, the survival of patients with high RAD54L expression was shorter with cancer progression than in patients with low RAD54L expression. This study also revealed that E2F1 directly binds to the promoter region of RAD54L and regulates the transcription of RAD54L related to the HRR pathway. This study also confirmed that DNA breaks are repaired by RAD54L induced by E2F1 in bladder cancer cells treated with MMC. In summary, RAD54L was identified as a new target directly regulated by E2F1. Our results suggest that, E2F1 and RAD54L could be used as diagnostic markers for bladder cancer progression and represent potential therapeutic targets.

Azulene-Derived Fluorescent Probe for Bioimaging: Detection of Reactive Oxygen and Nitrogen Species by Two-Photon Microscopy.

Two-photon fluorescence microscopy has become an indispensable technique for cellular imaging. Whereas most two-photon fluorescent probes rely on well-known fluorophores, here we report a new fluorophore for bioimaging, namely azulene. A chemodosimeter, comprising a boronate ester receptor motif conjugated to an appropriately substituted azulene, is shown to be an effective two-photon fluorescent probe for reactive oxygen species, showing good cell penetration, high selectivity for peroxynitrite, no cytotoxicity, and excellent photostability.

Urinary cell-free microRNA biomarker could discriminate bladder cancer from benign hematuria.

The most common symptom of bladder cancer (BC) is hematuria. However, not all patients with hematuria are diagnosed with BC. Here, we explored a novel method to discriminate BC from hematuria under nonmalignant conditions by measuring differences in urinary cell-free microRNA (miRNA) expression between patients with BC and those with hematuria. A multicenter study was performed using 543 urine samples obtained from the National Biobank of Korea, including 326 BC, 174 hematuria and 43 pyuria without cancer. The urinary miR-6124 to miR-4511 ratio was considerably higher in BC than in hematuria or pyuria, and enabled the discrimination of BC from patients with hematuria at a sensitivity of >90% (p < 0.001). Conclusively, the proposed noninvasive diagnostic tool based on the expression ratio of urinary cell-free miR-6124 to miR-4511 can reduce unnecessary cystoscopies in patients with hematuria undergoing evaluation for BC, with a minimal loss in sensitivity for detecting cancer.

Electrical control of terahertz frequency conversion from time-varying surfaces.

We investigate the electrical control of frequency conversion from a time-varying interdigitated photo-conductive antenna (IPCA) and time-varying metasurface in the terahertz (THz) frequency range. Ultrafast near-infrared (NIR) optical pulses rapidly modify the conductivities of the IPCA and metasurface; however, external voltages can retard this conductivity transition. Thus, external voltages can be used to control the frequency conversion process based on the interaction between the THz waves and the time-varying surfaces. In the IPCA, both frequency up- and down-conversion processes are suppressed by external voltages. However, in the metasurface, the down-conversion is dramatically suppressed by external voltages, whereas the suppression on the up-conversion is less effective.