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Domain Generation Algorithms (DGAs) are used by malware to generate pseudorandom domain names to establish communication between infected bots and command and control servers. While DGAs can be detected by machine learning (ML) models with great accuracy, offering DGA detection as a service raises privacy concerns when requiring network administrators to disclose their DNS traffic to the service provider. The main scientific contribution of this paper is to propose the first end-to-end framework for privacy-preserving classification as a service of domain names into DGA (malicious) or non-DGA (benign) domains. Our framework achieves these goals by carefully designed protocols that combine two privacy-enhancing technologies (PETs), namely secure multi-party computation (MPC) and differential privacy (DP). Through MPC, our framework enables an enterprise network administrator to outsource the problem of classifying a DNS (Domain Name System) domain as DGA or non-DGA to an external organization without revealing any information about the domain name. Moreover, the service provider's ML model used for DGA detection is never revealed to the network administrator. Furthermore, by using DP, we also ensure that the classification result cannot be used to learn information about individual entries of the training data. Finally, we leverage post-training float16 quantization of deep learning models in MPC to achieve efficient, secure DGA detection. We demonstrate that by using quantization achieves a significant speed-up, resulting in a 23% to 42% reduction in inference runtime without reducing accuracy using a three party secure computation protocol tolerating one corruption. Previous solutions are not end-to-end private, do not provide differential privacy guarantees for the model's outputs, and assume that model embeddings are publicly known. Our best protocol in terms of accuracy runs in about 0.22s., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Maia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Although different kidney cancers represent a heterogeneous group of malignancies, multiple subtypes including Von Hippel-Lindau (VHL)-altered clear cell renal cell carcinoma (ccRCC), fumarate hydratase (FH)- and succinate dehydrogenase (SDH)-deficient renal cell carcinoma (RCC), and renal medullary carcinoma (RMC) are affected by genomic instability. Synthetic lethality with poly ADP-ribose polymerase inhibitors (PARPis) has been suggested in preclinical models of these subtypes, and paired PARPis with immune checkpoint blockade (ICB) may achieve additive and/or synergistic effects in patients with previously treated advanced kidney cancers., Objective: To evaluate combined PARPi + ICB in treatment-refractory metastatic kidney cancer., Design, Setting, and Participants: We conducted a single-center, investigator-initiated phase 2 trial in two genomically selected advanced kidney cancer cohorts: (1) VHL-altered RCC with at least one prior ICB agent and one vascular endothelial growth factor (VEGF) inhibitor, and (2) FH- or SDH-deficient RCC with at least one prior ICB agent or VEGF inhibitor and RMC with at least one prior line of chemotherapy., Intervention: Patients received talazoparib 1 mg daily plus avelumab 800 mg intravenously every 14 d in 28-d cycles., Outcome Measurements and Statistical Analysis: The primary endpoint was objective response rate (ORR) by Immune Response Evaluation Criteria in Solid Tumors at 4 mo, and the secondary endpoints included progression-free survival (PFS), overall survival, and safety., Results and Limitations: Cohort 1 consisted of ten patients with VHL-altered ccRCC. All patients had previously received ICB. The ORR was 0/9 patients; one patient was not evaluable due to missed doses. In this cohort, seven patients achieved stable disease (SD) as the best response. The median PFS was 3.5 mo (95% confidence interval [CI] 1.0, 3.9 mo). Cohort 2 consisted of eight patients; four had FH-deficient RCC, one had SDH-deficient RCC, and three had RMC. In this cohort, six patients had previously received ICB. The ORR was 0/8 patients; two patients achieved SD as the best response and the median PFS was 1.2 mo (95% CI 0.4, 2.9 mo). The most common treatment-related adverse events of all grades were fatigue (61%), anemia (28%), nausea (22%), and headache (22%). There were seven grade 3-4 and no grade 5 events., Conclusions: The first clinical study of combination PARPi and ICB therapy in advanced kidney cancer did not show clinical benefit in multiple genomically defined metastatic RCC cohorts or RMC., Patient Summary: We conducted a study to look at the effect of two medications, talazoparib and avelumab, in patients with metastatic kidney cancer who had disease progression on standard treatment. Talazoparib blocks the normal activity of molecules called poly ADP-ribose polymerase, which then prevents tumor cells from repairing themselves and growing, while avelumab helps the immune system recognize and kill cancer cells. We found that the combination of these agents was safe but not effective in specific types of kidney cancer., (Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

ATP-sensitive potassium (KATP) channels couple cell metabolism to cellular electrical activity. Humans affected by severe activating mutations in KATP channels suffer from developmental delay, epilepsy, and neonatal diabetes (DEND syndrome). While the aetiology of diabetes in DEND syndrome is well understood, the pathophysiology of the neurological symptoms remains unclear. We hypothesised that impaired activity of parvalbumin-positive interneurons (PV-INs) may result in seizures and cognitive problems. We found, by performing electrophysiological experiments, that expressing the DEND mutation Kir6.2-V59M selectively in mouse PV-INs reduced intrinsic gamma frequency preference and short-term depression as well as disturbed cognition-associated gamma oscillations and hippocampal sharp waves. Furthermore, the risk of seizures was increased and the day-night shift in gamma activity disrupted. Blocking KATP channels with tolbutamide partially rescued the network oscillations. The non-reversible part may, to some extent, result from observed altered PV-IN dendritic branching and PV-IN arrangement within CA1. In summary, PV-INs play a key role in DEND syndrome, and this provides a framework for establishing treatment options., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Energy transfer between orthogonally arranged chromophores is typically considered impossible according to conventional Förster resonance energy transfer theory. Nevertheless, the disruption of orthogonality by nuclear vibrations can enable energy transfer, what has prompted the necessity for formal expansions of the standard theory. Here, we propose that there is no need to extend conventional Förster theory in such cases. Instead, a more accurate representation of the chromophores is required. Through calculations of the energy transfer rate using structures from a thermal ensemble, rather than relying on equilibrium geometries, we show that the standard Förster resonance energy transfer theory is still capable of describing energy transfer in orthogonally arranged systems. Our calculations explain how thermal vibrations influence the electronic properties of the states involved in energy transfer, affecting the alignment of transition dipole moments and the intensity of transitions.