Registration Phase Research Articles

Security-enabled optimal placement of drone-assisted Intelligent Transportation Systems in mission-critical zones

A massive increase in highly dynamic vehicular nodes has resulted in network instability. Owing to the heterogeneous vehicular environment requires a multi-objective solution using a meta-heuristic optimization algorithm in the event of mission-critical zones with poor signal and secured quick decision-making system. Developed a security-enabled optimal placement of Drones or unmanned aerial vehicles (UAV) in mission-critical zones aims to achieve two primary objectives: 1) Maximizing the effectiveness of the intelligent transportation system (ITS) for traffic management and ubiquitous connectivity in mission-critical zones. 2) Ensuring robust security measures to protect sensitive data and infrastructure. This approach represents a cutting-edge solution for optimizing transportation systems in high-risk environments while safeguarding against potential security threats. The pre-deployment of drones and vehicles (VOBU) parameter occurs during the registration phase, and then the mission-critical zone (MCZ) is identified and stored. The optimal position for drones in MCZs is determined by mathematically modeling a golden eagle optimization (GEO), which is inspired by varying the speed at different stages along their spiral trajectory for cruising and hunting. Furthermore, the robustness of the sensitive data and the real identity is ensured by using a biometric-based AKA algorithm utilizing the prevalent real-or-random (ROR) model and the formal security analysis. Based on a comparison of the simulation results, the proposed SDV-GEOAKA scheme outperforms the existing system- STPTC-A2G, IoDAV, and IMOC with 99.36% of PDR approximately, whereas, SDV-GEOAKA has maintained a load balancing factor with 0.01 to 0.1 when the transmission range between 0-60. When it comes to network coverage, proposed work outperforms with 99.95% during the transmission range of 50mW means it uses a minimum number of drones with maximum connectivity within the coverage range and also has significantly reduced the computation overhead and an increase in anomaly detection rate.

APPS: Authentication-enabled privacy protection scheme for secure data transfer in Internet of Things

The Internet of Things (IoT) is an emerging field that encompasses several heterogeneous devices and smart objects that are integrated with the network. In open platforms, these objects are deployed to present advanced services in numerous applications. Innumerable security-sensitive data is generated by the IoT device and therefore, the security of these devices is an important task. This work formulates a secure data transfer technique in IoT, named Authentication enabled Privacy Protection (APPS) scheme for resource-constrained IoT devices. The proposed scheme demonstrates resilience against various attacks; such as resisting reply attacks, device anonymity, untracebility, session key establishment, quantum attacks and resisting MITM attacks. For the privacy protection scheme, the secured data transfer is initiated between the entities, like IoT devices, servers, and registration centers, by using various phases, namely registration phase, key generation phase, data encryption, authentication, verification, and data retrieval phase. Here, a mathematical model is designed for protecting data privacy using hashing, encryption, secret keys, etc. Finally, performance of proposed APPS model is analyzed; wherein the outcomes reveal that the proposed APPS model attained the maximum detection rate of 0.85, minimal memory usage of 0.497MB, and minimal computational time of 112. 79 sec and minimal turnaround time 131.91 sec.

Application and Optimization of Multi-Factor Authentication and Biometric Technology in Power Grid Energy Network Access Control

With the sudden development in electronic and network technology, the power grid has emerged in several evolved nations and other areas with faster development. Energy storage can enhance the stability, resiliency and efficiency of the electric smart grid. The power grid transfers energy via bidirectional control of energy and information flow. In the power grid, a smart meter is an important component that is deployed on the user side to determine the consumption of energy regularly. However, the data about the usage of electricity leads to the leakage of the private information of the user, which threatens the privacy of the user. The attackers can change the in-transit message induce wrong information and sometimes cause disastrous action. Hence, it is important to assure data security and privacy of users by conducting authentication in power grid communication. An optimization technique named Puzzle Optimization Algorithm (POA) is designed for the efficient privacy-preserving aggregation approach with multi-factor authentication and a biometric scheme. Also, optimal key-based Elliptic Curve Cryptography (ECC) is used to encrypt the sensitive data that are securely stored. Authentication offers high security and texture analysis. In the registration phase, the privacy information of the person with their biometrics is the important feature point of the individual unique identification. Additionally, the designed approach is compared with other existing optimizations to analyse the functionality of the implemented technique. The simulation outcome defined that the suggested technique enhances user privacy and information security than other standard approaches.

Durability of Response With Selpercatinib in Patients With RET-Activated Thyroid Cancer: Long-Term Safety and Efficacy From LIBRETTO-001.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.LIBRETTO-001 is a registrational phase I/II, single-arm, open-label study of selpercatinib in patients with RET (REarranged during Transfection)-activated cancers (ClinicalTrials.gov identifier: NCT03157128). We present long-term safety and efficacy from LIBRETTO-001 in patients with RET-mutant medullary thyroid cancer (MTC; n = 324) and RET fusion-positive thyroid cancer encompassing different histological subtypes (TC; n = 66). At the data cutoff of January 2023, the objective response rate was 82.5% among patients with cabozantinib/vandetanib-naïve MTC and 95.8% among patients with treatment-naïve TC. At a median follow-up time of 42.4 and 44.0 months in patients with cabozantinib/vandetanib-naïve and pretreated MTC, the median progression-free survival (PFS) was not reached and 41.4 months, respectively. At a median follow-up time of 24.9 and 30.4 months in patients with treatment-naïve and pretreated TC, the median PFS was not reached and 27.4 months, respectively. Three-year PFS rates were 75.2% and 87.3% among patients with cabozantinib/vandetanib-naïve MTC and treatment-naïve TC, respectively. Median PFS was similar to median duration of response for each patient group. The safety profile of selpercatinib was consistent with previous reports. With an additional follow-up of 37 months and 228 more patients from the last disclosure, selpercatinib continued to provide durable and robust responses in treatment-naïve and previously treated patients with RET-mutant MTC and RET fusion-positive TC.

New Test to Detect Clustered Graphical Passwords in Passpoints Based on the Perimeter of the Convex Hull

This research paper presents a new test based on a novel approach for identifying clustered graphical passwords within the Passpoints scenario. Clustered graphical passwords are considered a weakness of graphical authentication systems, introduced by users during the registration phase, and thus it is necessary to have methods for the detection and prevention of such weaknesses. Graphical authentication methods serve as a viable alternative to the conventional alphanumeric password-based authentication method, which is susceptible to known weaknesses arising from user-generated passwords of this nature. The test proposed in this study is based on estimating the distributions of the perimeter of the convex hull, based on the hypothesis that the perimeter of the convex hull of a set of five clustered points is smaller than the one formed by random points. This convex hull is computed based on the points that users select as passwords within an image measuring 1920 × 1080 pixels, using the built-in function convhull in Matlab R2018a relying on the Qhull algorithm. The test was formulated by choosing the optimal distribution that fits the data from a total of 54 distributions, evaluated using the Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared tests, thus achieving the highest reliability. Evaluating the effectiveness of the proposed test involves estimating type I and II errors, for five levels of significance α∈{0.01,0.02,0.05,0.1,0.2}, by simulating datasets of random and clustered graphical passwords with different levels of clustering. In this study, we compare the effectiveness and efficiency of the proposed test with existing tests from the literature that can detect this type of pattern in Passpoints graphical passwords. Our findings indicate that the new test demonstrates a significant improvement in effectiveness compared to previously published tests. Furthermore, the joint application of the two tests also shows improvement. Depending on the significance level determined by the user or system, the enhancement results in a higher detection rate of clustered passwords, ranging from 0.1% to 8% compared to the most effective previous methods. This improvement leads to a decrease in the estimated probability of committing a type II error. In terms of efficiency, the proposed test outperforms several previous tests; however, it falls short of being the most efficient, using computation time measured in seconds as a metric. It can be concluded that the newly developed test demonstrates the highest effectiveness and the second-highest efficiency level compared to the other tests available in the existing literature for the same purpose. The test was designed to be implemented in graphical authentication systems to prevent users from selecting weak graphical passwords, enhance password strength, and improve system security.

Hybrid Encryption Model for Secured Three-Phase Authentication Protocol in IoT

The Internet of things (IoT) has recently received a great deal of attention, and there has been a large increase in the number of IoT devices owing to its significance in current communication networks. In addition, the validation of devices is an important concern and a major safety demand in IoT systems, as any faults in the authentication or identification procedure will lead to threatening attacks that cause the system to close. In this study, a new, three-phase authentication protocol in IoT is implemented. The initial phase concerns the user registration phase, in which encryption takes place with a hybrid Elliptic Curve Cryptography (ECC)–Advanced Encryption Standard (AES) model with an optimization strategy, whereby key generation is optimally accomplished via a Self-Improved Aquila Optimizer (SI-AO). The second and third phases include the login process and the authentication phase, in which information flow control-based authentication is conducted. Finally, decryption is achieved based on the hybrid ECC–AES model. The employed scheme’s improvement is established using various metrics.

Natural language processing and stable diffusion model based graphical authentication using passphrase

Graphical passwords or passphrases (GPs) are examined as reliable authentication system over text-based passphrases. Several obtainable applications utilize GPs and image-based authentication schemes. Even though, these authentication methods experience an issue of managing image or pictorial data. Here, Natural Language Processing (NLP)+Stable Diffusion (SD)_graphical authentication is presented for graphical authentication using passphrase. The passphrase, removing stop words, spell check, similarity check, stemming and lemmatization, label encoder, positional embedding and encryption are the steps carried out in registration phase whereas decryption Advanced Encryption Standard (AES), sentence generation, image set generation and grid module are conducted in verification phase. Initially, passphrase is considered and then, stop words are removed from it. Thereafter, spell check as well as similarity check are done and after these processes stemming and lemmatization is performed. In label encoder, label is generated for individual word in passphrase. Afterwards, positional embedding is done and lastly, encryption is conducted in registration phase. In verification phase, encrypted passphrase is decrypted, sentence is generated utilizing Generative Pre-trained Transformer (GPT), image set is generated by SD model and finally, image grid module is accomplished. Moreover, NLP+SD_graphical authentication achieved minimum attack detection, login failure, login time about 0.598, 0.191, 14.175sec and maximum memorability about 0.932.

Efficacy, safety, and determination of RP2D of ABBV-383, a BCMA bispecific antibody, in patients with relapsed/refractory multiple myeloma (RRMM).

7531 Background: MM eventually becomes refractory to current treatments, and new therapeutic options with convenient dosing and improved safety are needed to enhance patient (pt) adherence, access, and outcomes. ABBV-383 is a distinctive next-generation BCMA x CD3 bispecific antibody composed of 2 high-affinity BCMA-binding domains, a low-affinity CD3-binding domain designed to reduce cytokine release syndrome (CRS) risk, and a silenced Fc tail for an extended half-life allowing convenient dosing. ABBV-383 monotherapy has shown promising activity in the ongoing first-in-human phase 1 trial in RRMM (Vij et al. Blood 2023;142[suppl 1]:3378). Here, safety and efficacy results are reported that support the RP2D of 60mg Q4W as the optimal therapeutic ABBV-383 monotherapy dose. Methods: This phase 1 open-label, dose-escalation/expansion trial (NCT03933735) enrolled pts with RRMM who received ≥3 prior lines of therapy with exposure to PI, IMiD, and anti-CD38 mAb. ABBV-383 regimens explored in the expansion phase included 60mg Q4W and 40 or 60mg Q3W. A modified dexamethasone premedication schedule and shortened CRS monitoring period were implemented in the 60mg Q4W cohort for cycle 1. IV ABBV-383 was administered as a flat dose with no step-up schedule. Treatment was continued until disease progression/unacceptable toxicity. Primary objectives were to assess safety, tolerability, PK, PD, and determine the RP2D. Efficacy evaluation was a secondary objective. TEAEs were assessed per CTCAE v5.0 and tumor response per IMWG 2016 criteria. Results: As of May 2023, 220 pts received ABBV-383 (median age: 68 yr [35–92]; median prior therapy lines: 5 [3‒23]). Median FU was 4.1 mo (0.8–5.2) at 60mg Q4W (n=21), 12.2 mo (1.3–34.4) at 40mg Q3W (n=55), and 24.2 mo (0.6–33.4) at 60mg Q3W (n=61). At 60mg Q4W, with the modified premedication regimen, CRS was reported in 43% of pts (38% G1, 5% G2), and ICANS in 5% of pts (G2). In Q3W cohorts, CRS was reported in 71% (40mg; 45% G1, 25% G2) and 70% (60mg; 51% G1, 18% G2, 2% G3) of pts. The incidence of G3/4 neutropenia, anemia, and thrombocytopenia was 14/24/10% at 60mg Q4W, 31/31/16% at 40mg Q3W, and 34/13/13% at 60mg Q3W. G3/4 infections occurred in 10/24/34% of pts at 60mg Q4W, 40mg and 60mg Q3W, respectively. ORR and ≥VGPR were 65/50% at 60mg Q4W, 64/53% at 40mg Q3W, and 60/52% at 60mg Q3W. Corresponding exposure-response (ER) analyses and correlative analyses further supported RP2D determination (separate abstract submissions). Conclusions: The optimal therapeutic dose of 60mg Q4W ABBV-383 monotherapy was selected on the basis of safety, efficacy, and ER analyses. The extended interval of Q4W, with a shortened CRS monitoring period in cycle 1 and no step-up dosing, will improve convenience and reduce the treatment burden for pts. ABBV-383 at 60mg Q4W will be investigated in the registrational phase 3 trial (NCT06158841) in RRMM. Clinical trial information: NCT03933735 .

Exposure-response analyses for optimal therapeutic dose selection of ABBV-383 in patients with relapsed/refractory multiple myeloma (RRMM).

7541 Background: ABBV-383 is a fully human, B-cell maturation antigen (BCMA) × CD3 T-cell–engaging IgG4 bispecific with an effector-silenced Fc region, 2 high-affinity BCMA- and a low-affinity CD3-binding domains. ABBV-383 monotherapy has shown promising activity in patients (pts) with RRMM (Blood 2023;142[suppl 1]:3378). Here, exposure-response (ER) analyses of efficacy and safety endpoints supporting the optimal therapeutic ABBV-383 dose selection are reported in alignment with US FDA’s Project Optimus. Methods: Efficacy (n=218) and safety (n=220) data from the phase 1 study (NCT03933735) escalation cohorts of 0.025 - 120 mg Q3W and expansion cohorts of 20, 40, 60 mg Q3W and 60 mg Q4W including objective response rate (ORR), very good partial response or better (≥VGPR), stringent complete response (sCR)/CR, adverse events (≥G3 and serious), infections (≥G3, overall and serious), cytokine release syndrome (CRS; any-grade, G1, G2, and ≥G2) were modeled. Total(unbound + bound to soluble BCMA) and free (unbound + partially bound to soluble BCMA) Cycle 1 AUCinf, Cmax, and Ctrough and population pharmacokinetic model-derived up to the time of event Cavg and avgCtrough metrics were utilized in the ER analyses (logistic regression; R Version 4.2.2). Relevant pt-specific covariates were tested. Dexamethasone premedication (36 vs 10 mg) was included in CRS models. The ER relationships were utilized to predict the probabilities of efficacy and safety endpoints for relevant doses and thereby, support justification of the optimal therapeutic dose selection. Results: Based on overall assessment, ORR, ≥VGPR, sCR/CR and ≥G3 neutropenia strongly correlated with free Cavg; CRS endpoints (any-grade CRS and G1 only CRS) strongly correlated with Cycle 1 total Cmax (p <0.05). No other endpoints had ER relationships (p >0.05). Only MM type (IgG vs Others) was selected in ≥VGPR and sCR/CR models. ER relationships suggested high response rates of >63% ORR, >53% ≥VGPR, and ≥30% sCR/CR for 40, 60 mg Q3W and 60 mg Q4W. Predictions demonstrated that 20 mg Q3W (<39% ORR and ≥VGPR; <13% sCR/CR) and untested 40 mg Q4W (<60% ORR, <45% ≥VGPR and <23% sCR/CR) provide suboptimal efficacy. The 60 mg Q4W with 36 mg dexamethasone in Cycle1 (limited follow-up and data) was predicted to have ~30% sCR/CR and 31% ≥G3 neutropenia (≈ 40 mg Q3W) and substantially lower any-grade CRS events compared with 40 and 60 mg doses with 10 mg dexamethasone in Cycle 1. Conclusions: While ER analyses indicated promising efficacy and acceptable safety profiles for 40, 60 mg Q3W, and 60 mg Q4W, they support 60 mg Q4W as the optimal ABBV-383 therapeutic dose due to its predicted better therapeutic benefit/risk profile (high response rates, improved/equivalent ≥G3 neutropenia, and lower CRS events) and extended dosing interval. ABBV-383 at 60 mg Q4W will be investigated in the registrational phase 3 trial (NCT06158841) in RRMM.

Blockchain-assisted full-session key agreement for secure data sharing in cloud computing

Data sharing in cloud computing allows multiple data owners to freely share their data resources while security and privacy issues remain inevitable challenges. As a foundation of secure communication, authenticated key agreement (AKA) scheme has been recognized as a promising approach to solve such problems. However, most existing AKA schemes are based on the cloud-based architecture, privacy and security issues will inevitably occur once the centralized authority is attacked. Besides, most previous schemes require an online registration authority for authentication, which may consume significant resources. To address these drawbacks, for secure data sharing in cloud computing, a blockchain-assisted full-session key agreement scheme is proposed. After the registration phase, the registration authority does not engage in authentication and key agreement process. By utilizing blockchain technology, a common session key between the remote user and cloud server can be negotiated, and a shared group key among multiple remote users can be negotiated without private information leakage. Formal and informal security proof demonstrated the proposed scheme is able to meet the security and privacy requirements. The detail performance evaluation shows that the proposed scheme has lower computation costs and acceptable communication overheads while superior security is ensured.

A lightweight group-based SDN-driven encryption protocol for smart home IoT devices

With the increasing adoption rate of Internet of Things (IoT) devices in smart home applications, it is vital to safeguard the privacy and security of information, communications among IoT devices and the underlying infrastructure. In open communication scenarios, an adversary can easily tamper with data transmitted by IoT communication devices. This paper proposes a softwarized lightweight authentication key agreement scheme for smart home applications in Software-Defined IoT (SDIoT) environment. The proposed scheme comprises registration, authentication, and key selection phases. Devices are registered in the registration phase after the successful completion of validation checks, while sessions’ keys are granted to the registered devices in the authentication phase. In the final phase, controllers classify IoT devices based on pre-defined parameters and impose class-specific access control based on classification. The security of the proposed scheme is validated using the widely accepted AVISPAs verification tool against a strong adversary. Simulation results demonstrate that our proposed scheme outperforms existing schemes in terms of running time, computation complexity, and energy consumption. It is found that the proposed scheme has significant cost-effectiveness.

CIU-L: A class-incremental learning and machine unlearning passive sensing system for human identification

With the development of passive sensing technology, WiFi-based identification research has attracted much attention in areas such as human–computer interaction and home security. Although WiFi sensing-based human identification has achieved initial success, it is currently mainly applicable to scenarios where the user’s identity category is fixed and not applicable to scenarios where the user’s identity category changes frequently. In this paper, we propose an identification system (CIU-L) in a scenario where user’s identity categories frequently change, allowing for incremental registration and unregistration of identity categories. To the best of our knowledge, this is the first attempt to register and unregister user identity information under the previous identity category constraints. CIU-L proposes a training and updating strategy in the registration phase of new user to avoid catastrophic forgetting of old user’s identity information, and trains a targeted noise for the user to be unregistered in the unregistration phase of old user, achieving precise removal of the user to be unregistered without affecting the retained users. In addition, this paper presents adequate comparative experiments of CIU-L with other systems in the user identity category fixing scenario. The experimental results show that the average difference between CIU-L and other systems in terms of Accuracy, Precision, Recall and F1-Score is within 5% of each other, while running time and storage space are saved by more than 6 times, which is more capable of meeting the needs of identity recognition in real scenarios.

MmSign: mmWave-based Few-Shot Online Handwritten Signature Verification

Handwritten signature verification has become one of the most important document authentication methods that are widely used in the financial, legal, and administrative sectors. Compared with offline methods based on static signature images, online handwritten signature verification methods are more reliable because of the temporary dynamic information (e.g., signing velocity, writing force, stroke order) that alleviates the risk of being forged. However, most existing online handwritten signature verification solutions are reliant on specific signing devices (e.g., customized pens or writing pads) and require extensive data collection during the registration phase, resulting in poor adaptability and applicability for new users. In this article, we propose mmSign, a millimeter wave (mmWave)–based online handwritten signature verification system, which enables accurate sensing of the user’s hand movements when signing through the superior sensing capability of mmWave. mmSign extracts the time-velocity feature maps from the captured mmWave signals by the carefully designed signal processing algorithms and then exploits a transformer-based verification model for signature verification. In addition, a novel meta-learning strategy with proposed task generation and data augmentation methods is introduced in mmSign to teach the verification model to learn effectively with limited samples, allowing our model to quickly adapt to new users. Extensive experiments show that mmSign is a robust, efficient, and secure handwritten signature verification system, achieving 84.07%, 87.31%, 91.12%, and 96.54% verification accuracy when 1, 3, 5, and 10 labeled signatures are available, respectively, while being resistant to common forgery attacks.

Endothelial function cannot be assessed by the reactive hyperemia following occlusion

Reactive hyperemia (RH) and the post occlusive reactive hyperemia (PORH) are known to assess vascular function in vivo and referred as useful prognostic tools in vascular medicine. However, its translation to clinical practice is poor due to important unsolved inconsistencies. Our group has been studying the adaptive responses following RH. Here we clarify the involved mechanism, its impact on general hemodynamics and the significance of these responses. A convenience sample of fourteen healthy women (48.0 ± 8.0 y.o.) was selected, all being normotensive non-menopausal, with no signs of vascular impairment (normal ankle-brachial index and mean arterial pressure MAP), and with (self-reported) equivalent levels of physical activity. The study followed all principles of good clinical practice established for human research and was previously approved by the institutional Ethics Committee. The protocol included three phases—a baseline register (Phase I) during rest, giving place to the occlusion as part of the PORH maneuver challenge period (Phase II) with one minute, followed by a ten-minute recovery period (Phase III). PORH was performed on one randomly chosen upper limb, using the cuff of the TASK FORCE® platform for the continuous monitoring of blood pressure and hemodynamics. After baseline acquisition, the cuff was rapidly inflated with 200 mmHg to occlude the brachial artery for one minute. Then the cuff was rapidly deflated, and signals registered for recovery recordings. Perfusion was measured in both hands by laser Doppler flowmetry (3rd finger) with a Perimed5000 system. To confirm previous evidence regarding the mechanism(s) involved, we also accessed the RH impact(s) on the contralateral forearm skin circulation by functional imaging using a multi-scan photoptoacoustic tomography (PAT) (MSOT iThera system). The tissue hypoxia related to RH-PORH is referred to evoke a local vasodilation, such that hyperemia occurs following the cessation of occlusion. Thus, any reduction of this response has been associated to endothelial impairment. However, our studies have shown suffcient evidence of a centrally mediated reflex rather than a local response mediated by local vasodilators. In fact, LDF clearly detected significant perfusion reductions in both hands during and following occlusion, more pronounced in the challenged limb, while PAT confirmed similar changes in the superficial plexus on the contralateral forearm. Additionally of interest, no significant hemodynamical changes were found with PORH apart from MAP when comparing recovery with baseline periods. Our results clearly show that the physiological significance of RH or POHR reduction can no longer be regarded to solely represent “endothelial disfunction” but rather an expression of a global adaptive hemodynamical response, centrally mediated, that might originate essential endpoints also measurable in the contralateral limb, with clinical utility. This research was financed by national funds through FCT - Foundation for Science and Technology, I.P. (Portugal), under the [UIDB/04567/2020] and [UIDP/ 04567/2020] projects, and by COFAC/ALIES for the use of the photoacoustic instrument. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

LIBRETTO-431: Confirming the Superiority of Selpercatinib to Chemotherapy and the Lack of Efficacy of Immune Checkpoint Inhibitors in Advanced RET Fusion-Positive (RET+) NSCLC, Another Unique Never-Smoker Predominant Molecular Subtype of NSCLC.

Selpercatinib, a potent and highly selective RET kinase inhibitor with significant CNS activity, has recently gained US approval for the treatment of NSCLC harboring RET fusions (RET+) based on a large-scale single-arm study. The LIBRETTO-431 trial was the global pivotal registration phase 3 trial comparing selpercatinib to platinum-based chemotherapy with or without pembrolizumab as the first-line treatment of patients with advanced RET+ NSCLC. Never-smokers constituted 67.4% of the RET+ NSCLC patients enrolled. KIF5B-RET made up the vast majority (77%) of the RET+ fusion variant with known fusion partner. The results of this study demonstrated significant improvement in progression-free survival (PFS) benefit as well as impressive intracranial disease response in participants treated with selpercatinib as compared to those treated with chemotherapy, with a HR [hazard ratio] of 0.46 (95% CI 0.33-0.70; P < 0.001) for the intention-to-treat (ITT)-pembrolizumab group and HR of 0.46 (95% CI 0.31-0.70, P < 0.001) for the overall ITT-group of patients. The addition of pembrolizumab to platinum/pemetrexed chemotherapy resulted in numerically identical PFS (11.2 months). These results point to selpercatinib's superiority to traditional chemotherapy regimens in the treatment of NSCLC harboring RET fusions and add to literature on the salience of targeted precision oncology and lack of efficacy of immune checkpoint inhibitor in NSCLC patients with never-smoker predominant actionable driver mutations. RET+ NSCLC should be added to the list of molecular subtypes (EGFR+, ALK+, ROS1+) of NSCLC to be excluded in chemoimmunotherapy trial.

Abstract 5086: Functional profiling in lung tumor explants show contributions of the tumor microenvironment to response of Dato-DXdex vivo

Abstract Background: Antibody drug conjugates (ADCs) have demonstrated significant antitumor activity against multiple treatment refractory cancers. While Trastuzumab deruxtecan, a HER2 directed ADC, has shown impressive clinical activity in HER2-expressing cancers, the ability to predict responses of ADCs by IHC has been limited. Dato-DXd is a TROP2 directed ADC that is currently being studied in a number of registrational phase 3 trial incld. TROPION-Lung01. In the phase 1b TROPION-Pan tumor 01 trial (TP01) response to Dato-DXd did not correlate to TROP2 IHC expression. Here we investigate molecular determinants of sensitivity to Dato-DXd using short-term microfluidic culture of patient derived organotypic tumor spheroids (PDOTS). Methods: Surgical NSCLC cases collected from Brigham and Women’s Hospital and St. Elizabeth’s Medical Center under an IRB approved protocol were studied. PDOTS were generated as previously described. Ex vivo response was assessed by live/dead imaging, TROP2 antigen density on EPCAM+ cells by flow cytometry (FCM) and by immunofluorescence (IF). T cell and myeloid cell populations were analyzed by FCM of CD45+ cells isolated during tumor preparation. For a subset of samples single cell RNA sequencing (scRNAseq) was performed. Results:Eleven NSCLC explants were studied. Two specimens were excluded due to excess of fibrotic material. Response to Dato-DXd was measured by change in raw live cell area compared to control samples. Median response to Dato-DXd was -48.5% (ranging from +33.9% to -77.8%). Using a cut-off of -40%, four cases were characterized as non-responders (NR) and 5 as responders (R). Tumor TROP2 expression by IF ranged from 0 to 3+ with no relationship between TROP2 expression and response being observed. TROP2 staining positivity by IF didn’t correlate to Dato-DXd sensitivity ex vivo. TROP2 FCM, on the other hand discriminated between responsive and non-responsive models in 100% of the cases, using a cutoff of MFI &amp;gt;13000. Furthermore, we observed an increase of tumor CD8 abundance in Dato-DXd R compared to NR (median %CD8 in R 10.3% (range 5.1%-62.5%); median %CD8 of live cells in NR 2.3% (range 1.2%-3.7%) p-value 0.029). Conversely, we also observed a trend of higher granulocytic myeloid-derived suppressor cells abundance in NR compared to R (NR median %gMDSC of CD15+ cells 84.1% (range 73.4%-90.2%) ; R median %gMDSC 61.7% (range 54.3%-90.6%); p-value 0.069). In 2 cases with high and low TROP2 MFI available scRNAseq data showed TROP2 expression exclusively in tumor cells, with further analysis ongoing. Conclusion: By functionally profiling NSCLC PDOTS that retain immune cells, we correlated multiple parameters with ex vivo response to Dato-DXd. Our results have important implications for precision deployment of ADCs and suggest that target tumor antigen density in conjunction with addition immune cell features may refine patient selection strategy. Citation Format: Satoru Yasuda, Elena Ivanova, Ha V. Vo, Sophie Kivlehan, Iliana Gjeci, Minh Ha, Patrick Lizotte, Raphael Bueno, David A. Barbie, Cloud P. Paweletz. Functional profiling in lung tumor explants show contributions of the tumor microenvironment to response of Dato-DXdex vivo [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5086.

A Novel Multimodal Fusion Framework Based on Point Cloud Registration for Near-Field 3D SAR Perception

This study introduces a pioneering multimodal fusion framework to enhance near-field 3D Synthetic Aperture Radar (SAR) imaging, crucial for applications like radar cross-section measurement and concealed object detection. Traditional near-field 3D SAR imaging struggles with issues like target–background confusion due to clutter and multipath interference, shape distortion from high sidelobes, and lack of color and texture information, all of which impede effective target recognition and scattering diagnosis. The proposed approach presents the first known application of multimodal fusion in near-field 3D SAR imaging, integrating LiDAR and optical camera data to overcome its inherent limitations. The framework comprises data preprocessing, point cloud registration, and data fusion, where registration between multi-sensor data is the core of effective integration. Recognizing the inadequacy of traditional registration methods in handling varying data formats, noise, and resolution differences, particularly between near-field 3D SAR and other sensors, this work introduces a novel three-stage registration process to effectively address these challenges. First, the approach designs a structure–intensity-constrained centroid distance detector, enabling key point extraction that reduces heterogeneity and accelerates the process. Second, a sample consensus initial alignment algorithm with SHOT features and geometric relationship constraints is proposed for enhanced coarse registration. Finally, the fine registration phase employs adaptive thresholding in the iterative closest point algorithm for precise and efficient data alignment. Both visual and quantitative analyses of measured data demonstrate the effectiveness of our method. The experimental results show significant improvements in registration accuracy and efficiency, laying the groundwork for future multimodal fusion advancements in near-field 3D SAR imaging.

Eco-Patents at the Crossroads Between Technological Neutrality and Environmental Sensitivity

Abstract In a world where global warming and the consequent melting of glaciers seem to have become an irreversible trend, the growing demand for energy and natural resources can be met only if businesses actively foster the green conversion of their strategies and activities. Although primarily devoted to the promotion of technological innovation as such, patent law could play a crucial role in the fight against climate change by favoring those intangibles that are compatible with the environmental imperative. The aim of this paper is to assess the desirability of a patent system that is sensitive and permeable to the need for environmental neutrality as against a system that is neutral to technological innovation. The assessment of this tension is made by focusing on two relevant issues arising in the registration phase: (i) the opportunity to introduce an accelerated procedure for green patents both at the national and at the European level; (ii) the possibility of denying the patentability of highly polluting inventions based on ordre public considerations as well as on other provisions, like Art. 81quinquies of the Italian Intellectual Property Code.

Fortifying Democracy: Deploying Electoral Justice for Robust Personal Data Protection in the Indonesian Election

Elections stand as a cornerstone of democracy, yet the burgeoning integration of technology and personal data underscores the pressing need for safeguarding individual privacy within the electoral process. This study endeavors to scrutinize the efficacy of the Electoral Justice System in fortifying the protection of personal data throughout the registration, verification, and adjudication phases of political party participation in the forthcoming 2024 elections. Through an empirical juridical methodology, this research delves into the practical application of the Electoral Justice System across diverse national contexts, elucidating its role in mitigating the perils of data misuse and upholding electoral integrity. The findings underscore the imperative of imbuing the Electoral Justice System with structural robustness, substantive fidelity, and a conducive legal culture to ensure the seamless functioning of electoral processes. Additionally, stringent regulations, robust data verification protocols, independent oversight mechanisms, and punitive measures emerge as indispensable facets of effective Electoral Justice System implementation, essential for curtailing infringements of the exploitation of personal data and fostering accountable electoral practices.

E-voting system using cloud-based hybrid blockchain technology

With the invention of Internet-enabled devices, cloud and blockchain-based technologies, an online voting system can smoothly carry out election processes. During pandemic situations, citizens tend to develop panic about mass gatherings, which may influence the decrease in the number of votes. This urges a reliable, flexible, transparent, secure, and cost-effective voting system. The proposed online voting system using cloud-based hybrid blockchain technology eradicates the flaws that persist in the existing voting system, and it is carried out in three phases: the registration phase, vote casting phase and vote counting phase. A timestamp-based authentication protocol with digital signature validates voters and candidates during the registration and vote casting phases. Using smart contracts, third-party interventions are eliminated, and the transactions are secured in the blockchain network. Finally, to provide accurate voting results, the practical Byzantine fault tolerance (PBFT) consensus mechanism is adopted to ensure that the vote has not been modified or corrupted. Hence, the overall performance of the proposed system is significantly better than that of the existing system. Further performance was analyzed based on authentication delay, vote alteration, response time, and latency.